Publications

Ajaykumar Patel

Voice based pathology detection from respiratory sounds using optimized classifiers

Journal

Journal NameInternational Journal of Computing and Digital Systems

Journal

Journal NameINTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN ENGINEERING AND TECHNOLOGY (IJARET)

Title of PaperDATA EXCHANGE MODEL USING WEB SERVICE FOR HEROGENEOUS DATABASES

PublisherIAEME

Volume Number6

Page Number107-111

Published YearApril 2015

ISSN/ISBN No0976 - 6499

VOICE ENABLE PORTAL

Journal

Journal NameNational Journal - Biannual Publication

Title of PaperVOICE ENABLE PORTAL

PublisherKSV-JSTR

Volume Number1

Page Number41-44

Published YearJune 2010

ISSN/ISBN No0974-9780

M-ticket- An M-commerce Application

Conference

Title of PaperM-ticket- An M-commerce Application

Proceeding NameGREEN-IT & OPEN SOURCE

OrganizationSinhgad Institute of Management (SIOM)

Year , VenueApril 2010 , Sinhgad Institute of Management (SIOM) , Pune

Page Number540-542

ISSN/ISBN No978-93- 80043-89-0

Ankit Thakkar

Fusion of linear and non-linear dimensionality reduction techniques for feature reduction in LSTM-based Intrusion Detection System

Journal

Journal NameApplied Soft Computing

Title of PaperFusion of linear and non-linear dimensionality reduction techniques for feature reduction in LSTM-based Intrusion Detection System

PublisherElsevier

Volume Number154

Page Number1-9

Published YearMarch 2024

ISSN/ISBN No1568-4946

Indexed INScopus, Web of Science

Abstract

Securing networks is becoming increasingly crucial due to the widespread use of information technology. Intrusion Detection System (IDS) plays a crucial role in network security by detecting potential security threats in real-time. In order to create effective IDS, Deep Learning (DL) techniques like Auto Encoder (AE) and Long Short-Term Memory (LSTM) have been widely used. However, the high dimensionality and complexity of network traffic data make it challenging to extract meaningful information. The paper proposes a fusion-based approach that combines AE and Principal Component Analysis (PCA) techniques for dimensionality reduction in IDS. The proposed approach aims to capture both linear and non-linear relationships between features while reducing the dimensionality of the input data. NSL-KDD, UNSW-NB15, CIC-IDS-2017, and MSCAD datasets are used to evaluate this proposed method. The proposed approach has improved accuracy compared to the existing AE+LSTM-based approach by 3% for NSL-KDD and around 1% for UNSW-NB15 and CIC-IDS-2017, while the proposed approach gives comparable results for the MSCAD dataset. The Wilcoxon signed-rank test has been applied to confirm the statistical significance of the result.

A Review on Challenges and Future Research Directions for Machine Learning-Based Intrusion Detection System

Journal

Journal NameArchives of Computational Methods in Engineering

Title of PaperA Review on Challenges and Future Research Directions for Machine Learning-Based Intrusion Detection System

PublisherSpringer

Volume Number30

Page Number4245–4269

Published YearMay 2023

ISSN/ISBN No1886-1784

Indexed INScopus, Web of Science

Abstract

Research in the field of Intrusion Detection is focused on developing an efficient strategy that can identify network attacks. One of the important strategies is to supervise the network events for identifying attacks. Security mechanisms such as Intrusion Detection Systems (IDS) have been used for securing the network infrastructure and network communication against network attacks, wherein Machine Learning (ML) techniques have a notable contribution to design an efficient IDS. However, dependence on modern communication technology and collateral rise in the network attacks affect the performance of ML techniques. In this article, we discuss a detailed overview of intrusion detection using ML techniques. We discuss the steps performed by ML techniques for detecting and classifying intrusions. Moreover, our paper provides a comprehensive overview of state-of-the-art ML techniques used for intrusion detection and classification along with their advantages and limitations. The paper also summarizes research work performed in the field of ML-based IDS. In this paper, we aim to discuss various challenges faced by ML-based IDS. We further discuss future research directions that can be considered for enhancing the efficiency and effectiveness of IDS. Our review will serve as an incentive to novice researchers who aim to work in the field of ML-based IDS.

Attack Classification of Imbalanced Intrusion Data for IoT network Using Ensemble Learning-based Deep Neural Network

Journal

Journal NameIEEE Internet of Things Journal

Title of PaperAttack Classification of Imbalanced Intrusion Data for IoT network Using Ensemble Learning-based Deep Neural Network

PublisherIEEE

Volume Number10

Page Number11888 - 11895

Published YearFebruary 2023

ISSN/ISBN No2327-4662

Indexed INScopus, Web of Science

Abstract

With the increase in popularity of Internet of Things (IoT) and rise in interconnected devices, the need to foster effective security mechanism to handle vulnerabilities and risks in IoT networks has become evident. Security mechanisms such as Intrusion Detection System (IDS) are designed and deployed in IoT network environment to ensure security and prevent unauthorized access to system and resources. Moreover, there have been efforts to design IDS using various Deep Learning (DL) techniques, as these techniques possess intriguing characteristic of representing data with high abstraction. However, intrusion detection datasets used in literature possess imbalance class distribution, which is one of the challenging issue in developing coherent and potent intrusion detection and classification system. In this paper, we aim to address class imbalance problem using ensemble learning approach, namely, Bagging classifier, that uses Deep Neural Network (DNN) as base estimator. Here, in the proposed approach, the training process of DNN is influenced by including class weights that advocates to create balanced training subsets for DNN. The desirability and merit of the proposed approach can be considered as two-fold as it aims to achieve generalization along with addressing the class imbalance problem in intrusion detection datasets. The performance of the proposed approach is evaluated using four intrusion detection datasets, namely, NSL-KDD, UNSW_NB-15, CIC-IDS-2017, and BoT-IoT. Result analysis of the proposed approach is illustrated using various evaluation metrics, namely, accuracy, precision, recall, f-score, and False Positive Rate (FPR). Moreover, results of the proposed approach are also statistically tested using Wilcoxon signed-rank test.

Data fusion with factored quantization for stock trend prediction using neural networks

Journal

Journal NameInformation Processing & Management

Title of PaperData fusion with factored quantization for stock trend prediction using neural networks

PublisherElsevier

Volume Number60

Page Number1-18

Published YearFebruary 2023

ISSN/ISBN No0306-4573

Indexed INScopus, Web of Science

Abstract

As compared to the continuous temporal distributions, discrete data representations may be desired for simplified and faster data analysis and forecasting. Data compression can introduce one of the efficient ways to reduce continuous historical stock market data and present them in discrete forms; while predicting stock trend, a primary concern is towards up and down directions of the price movement and thus, data discretization for a focused approach can be beneficial. In this article, we propose a quantization-based data fusion approach with a primary motivation to reduce data complexity and hence, enhance the prediction ability of a model. Here, the continuous time-series values are transformed into discrete quantum values prior to applying them to a prediction model. We extend the proposed approach and factorize quantization by integrating different quantization step sizes. Such fused data can reduce the data to mainly concentrate on the stock price movement direction. To empirically evaluate the proposed approach for stock trend prediction, we adopt long short-term memory, deep neural network, and backpropagation neural network models and compare our prediction results with five existing approaches on several datasets using ten performance metrics. We analyze the impact of specific quantization factors and determine the individual best as well as overall best factor sizes; the results indicate a consistent performance enhancement in stock trend prediction accuracy as compared to the considered baseline methods with an improvement up to 7%. To evaluate the impact of quantization-based data fusion, we analyze time required to execute the experiments along with percentage reduction in the number of unique numeric terms. Further, these results are statistically evaluated using Wilcoxon signed-rank test. We discuss the superiority and applicability of factored quantization-based data fusion approach and conclude our work with potential future research directions.

Neural network systems with an integrated coefficient of variation-based feature selection for stock price and trend prediction

Journal

Journal NameExpert Systems with Applications

Title of PaperNeural network systems with an integrated coefficient of variation-based feature selection for stock price and trend prediction

PublisherElsevier

Volume Number219

Page Number1-20

Published YearJanuary 2023

ISSN/ISBN No1873-6793

Indexed INScopus, Web of Science

Abstract

Stock market forecasting has been a subject of interest for many researchers; the essential market analyses can be integrated with historical stock market data to derive a set of features. It is crucial to select features with useful in- formation about the specific aspect. In this article, we propose coefficient of variation (CV)-based feature selection for stock prediction. The unitless statis- tical method, CV, is widely used to obtain variability among data distributions. We calculate CV for each feature and integrate an existing method, k-means al- gorithm, as well as proposed methods, median range and top-M , to select a set of features with specific characteristics such as features belonging to the largest cluster, the defined range, and with the highest CV values, respectively. We apply the set of selected features to models such as backpropagation neural net- work (BPNN), long short-term memory (LSTM), gated recurrent unit (GRU), and convolutional neural network (CNN) for stock price and trend prediction. We demonstrate the applicability of our proposed approach using five of the existing feature selection methods, namely, correlation coefficient, Chi2, mutual information, principal component analysis, and variance threshold; comparison indicates remarkable performance enhancement using several accuracy-based, as well as error-based, metrics and the same is statistically supported using Wilcoxon signed-rank test.

Fusion of statistical importance for feature selection in Deep Neural Network-based Intrusion Detection System

Journal

Journal NameInformation Fusion

Title of PaperFusion of statistical importance for feature selection in Deep Neural Network-based Intrusion Detection System

PublisherElsevier

Volume Number90

Page Number353-363

Published YearOctober 2022

ISSN/ISBN No1566-2535

Indexed INScopus, Web of Science

Abstract

Intrusion Detection System (IDS) is an essential part of network as it contributes towards securing the network against various vulnerabilities and threats. Over the past decades, there has been comprehensive study in the field of IDS and various approaches have been developed to design intrusion detection and classification system. With the proliferation in the usage of Deep Learning (DL) techniques and their ability to learn data extensively, we aim to design Deep Neural Network (DNN)-based IDS. In this study, we aim to focus on enhancing the performance of DNN-based IDS by proposing a novel feature selection technique that selects features via fusion of statistical importance using Standard Deviation and Difference of Mean and Median. Here, in the proposed approach, features are pruned based on their rank derived using fusion of statistical importance. Moreover, fusion of statistical importance aims to derive relevant features that possess high discernibility and deviation, that assists in better learning of data. The performance of the proposed approach is evaluated using three intrusion detection datasets, namely, NSL-KDD, UNSW_NB-15, and CIC-IDS-2017. Performance analysis is presented in terms of different evaluation metrics such as accuracy, precision, recall, -score, and False Positive Rate (FPR) and the results are compared with existing feature selection techniques. Apart from evaluation metrics, performance comparison is also presented in terms of execution time. Moreover, results achieved are also statistically tested using Wilcoxon Signed Rank test.

Improving the performance of sentiment analysis using enhanced preprocessing technique and Artificial Neural Network

Journal

Journal NameIEEE Transactions on Affective Computing

Title of PaperImproving the performance of sentiment analysis using enhanced preprocessing technique and Artificial Neural Network

PublisherIEEE

Volume NumberYet to be assigned

Page Number1-12

Published YearSeptember 2022

ISSN/ISBN No1949-3045

Indexed INScopus, Web of Science

Abstract

With the presence of a massive amount of digitally recorded data, an automated computation can be preferable over the manual approach to evaluate sentiments within given textual fragments. Artificial neural network (ANN) is preferred for sentiment analysis (SA) because of its learning ability and adaptive nature towards diverse data. Handling negation in SA is a challenging task, and to address the same, we propose a specific order of preprocessing (PPR) steps to enhance the performance of SA using ANN. Typically, ANN weights are randomly initialized (R-ANN), which may not give the desired performance. As a potential solution, we propose a novel approach named Matching features with output label based Advanced Technique (MAT) to initialize the ANN weights (MAT-ANN). Simulation results conclude the superiority of the proposed approach PPR+MAT-ANN compared to the existing approach EPR+R-ANN i.e., integrating existing preprocessing (EPR) steps with R-ANN. Moreover, PPR+MAT-ANN architecture is significantly simpler than the existing deep learning-based approach named the NeuroSent tool and gives better performance when evaluated upon the Dranziera protocol.

Information fusion-based genetic algorithm with long short-term memory for stock price and trend prediction

Journal

Journal NameApplied Soft Computing

Title of PaperInformation fusion-based genetic algorithm with long short-term memory for stock price and trend prediction

PublisherElsevier

Volume Number128

Page Number1-20

Published YearAugust 2022

ISSN/ISBN No1568-4946

Indexed INScopus, Web of Science

Abstract

Information fusion is one of the critical aspects in diverse fields of applications; while the collected data may provide certain perspectives, a fusion of such data can be a useful way of exploring, expanding, enhancing, and extracting meaningful information for a better organization of the targeted domain. A nature-inspired evolutionary approach, namely, genetic algorithm (GA) is adopted for a variety of applications including stock market prediction. The complex, highly fluctuating financial market-related problems require optimized models for reliable forecasting. Also, it can be observed that stock market etiquettes are generally non-linear in nature and therefore, a broader understanding and analysis of such market behaviors necessitate the collection and fusion of relevant information based on different associated factors. In this article, we propose an information fusion-based GA approach with inter-intra crossover and adaptive mutation (ICAN) for stock price and trend prediction. Inspired by the genetic diversity and survival capability of various organisms, our proposed approach aims to optimize parameters of a long short-term memory prediction model, and selects a set of features; to address these problems of interest, we integrate inter-chromosome as well as conditional intra-chromosome crossover operations along with adaptive mutation to diversify the potential chromosome solutions. We illustrate the step-by-step procedure followed by GA with ICAN and evaluate its performance for one-day-ahead stock price and trend prediction. GA with ICAN-based optimization results in an average reduction of 43%, 27%, and 26% using mean squared error, mean absolute error, and mean absolute percentage error, respectively, as compared to the existing GA-based optimization approaches; further, an average improvement of 61% is encountered using R score. We also compare our work with Ant Lion Optimization approach and demonstrate the significance of GA with ICAN-based optimization. We analyze statistical significance, as well as convergence functions, for GA with ICAN and discuss remarkable performance enhancement; we provide necessary concluding remarks with potential future research directions.

An improved method for classifying depth-based human actions using self-adaptive evolutionary technique

Journal

Journal NameJournal of Ambient Intelligence and Humanized Computing

Title of PaperAn improved method for classifying depth-based human actions using self-adaptive evolutionary technique

PublisherSpringer Berlin Heidelberg

Volume NumberYet to be assigned

Page Number1-17

Published YearMay 2022

ISSN/ISBN No1868-5145

Indexed INScopus, Web of Science

Abstract

Automatic Human Action Recognition (HAR) using RGB-D (Red, Green, Blue, and Depth) videos captivated a lot of attention in the pattern classification field due to low-cost depth cameras. Feature extraction in action recognition is an important aspect. As compared to Depth Motion Maps (DMM), Depth Motion Maps–Local Binary Pattern (DMM–LBP) provides compact representation of features. After extracting features using DMM–LBP, Principal Component Analysis (PCA) is used for dimensionality reduction. For classification task, randomly generated input weights of Extreme Learning Machine (ELM) can lead to non-optimal results. Therefore, in this paper, we have used an improved learning algorithm named Self-adaptive Differential Evolution (SaDE) ELM for action classification. In the proposed approach, DMM–LBP is used for feature extraction and SaDE–ELM is used for action classification. To evaluate strength of the proposed approach, experiments are performed on four public datasets, namely, MSRAction3D, MSRDaily Activity3D, UTD–MHAD, and MSRGesture3D. The proposed approach gives better accuracy compared to existing approaches Kernel ELM (KELM), l2-Collaborative Representation Classifier (l2-CRC), and Probabilistic CRC (ProCRC) methods. We have also presented statistical significance of results in the paper.

Analyzing fusion of regularization techniques in the deep learning‐based intrusion detection system

Journal

Journal Name International Journal of Intelligent Systems

Title of PaperAnalyzing fusion of regularization techniques in the deep learning‐based intrusion detection system

PublisherWiley

Volume Number36

Page Number7340-7388

Published YearAugust 2021

ISSN/ISBN No1098-111X

Indexed INScopus, Web of Science

Abstract

The surge of constantly evolving network attacks can be addressed by designing an effective and efficient Intrusion Detection System (IDS). Various Deep Learning (DL) techniques have been used for designing intelligent IDS. However, DL techniques face an issue of overfitting because of complex network structure and high-dimensional data sets. Dropout and regularization are two competently perceived concepts of DL used for handling overfitting issue to enhance the performance of DL techniques. In this paper, we aim to apply fusion of various regularization techniques, namely, L1, L2, and elastic net regularization, with dropout regularization technique, for analyzing and enhancing the performance of Deep Neural Network (DNN)-based IDS. Experiments are performed using NSL-KDD, UNSW_NB-15, and CIC-IDS-2017 data sets. The value of dropout probability is derived using GridSearchCV-based hyperparameter optimization technique. Moreover, the paper also implements state-of-the-art Machine Learning techniques for the performance comparison. Apart from DNN, we have also presented performance analysis of various DL techniques, namely, Recurrent Neural Network, Long Short-Term Memory, Gated Recurrent Unit, and Convolutional Neural Network using a fusion of regularization techniques for intrusion detection and classification. The empirical study shows that among the techniques implemented, dropout has proved to be more effective compared with L1, L2, and elastic net regularization. Moreover, fusion of dropout with other regularization techniques achieved better results compared with L1 regularization, L2 regularization, and elastic net regularization, individually. The techniques implemented for DNN-based IDS are also statistically tested using the Wilcoxon signed-rank test.

Pearson Correlation Coefficient-based performance enhancement of Vanilla Neural Network for stock trend prediction

Journal

Journal NameNeural Computing and Applications

Title of PaperPearson Correlation Coefficient-based performance enhancement of Vanilla Neural Network for stock trend prediction

PublisherSpringer

Volume Number33

Page Number16985–17000

Published YearJuly 2021

ISSN/ISBN No1433-3058

Indexed INScopus, Web of Science, EBSCO

Abstract

The prediction of a volatile stock market is a challenging task. While various neural networks are integrated to address stock trend prediction problems, the weight initialization of such networks plays a crucial role. In this article, we adopt feed-forward Vanilla Neural Network (VNN) and propose a novel application of Pearson Correlation Coefficient (PCC) for weight initialization of VNN model. VNN consists of an input layer, a single hidden layer, and an output layer; the edges connecting neurons in the input layer and the hidden layer are generally initialized with random weights. While PCC is primarily used to find the correlation between two variables, we propose to apply PCC for weight initialization instead of random initialization (RI) for a VNN model to enhance the prediction performance. We also introduce the application of Absolute PCC (APCC) for weight initialization and analyze the effects of RI, PCC, and APCC values as weights for a VNN model. We conduct an empirical study using these concepts to predict the stock trend and evaluate these three weight initialization techniques on ten years of stock trading archival data of Reliance Industries, Infosys Ltd, HDFC Bank, and Dr. Reddy’s Laboratories for the duration of years 2008 to 2017 for continuous as well as discrete data representations. We further evaluate the applicability of these weight initialization techniques using an ablation study on the considered features and analyze the prediction performance. The results demonstrate that the proposed weight initialization techniques, PCC and APCC, provide higher or comparable results as compared to RI, and the statistical significance of the same is carried out.

iCREST: International Cross-Reference to Exchange-Based Stock Trend Prediction Using Long Short-Term Memory

Book Chapter

Book NameApplied Soft Computing and Communication Networks

PublisherSpringer

Author NameKinjal Chaudhari and Ankit Thakkar

Page Number323-338

Chapter TitleiCREST: International Cross-Reference to Exchange-Based Stock Trend Prediction Using Long Short-Term Memory

Published YearJuly 2021

ISSN/ISBN No978-981-33-6172-0

Indexed INScopus

Abstract

Stock market investments have been primarily aimed at gaining higher profits from the investment; a large number of companies get listed on various stock exchanges to initiate trading through the stock market. For the potential expansion of market tradings, several companies may choose to get listed on multiple exchanges which may be domestic and/or international. In this article, we propose an international cross-reference to exchange-based stock trend (iCREST) prediction approach to study how historical stock market data of a company listed on internationally-located stock exchanges can be integrated. We consider the timezone and currency variations in order to unify the data; we also incorporate data integration-based pre-processing to eliminate loss of useful stock price information. We calculate the difference between exchange prices of a company and adopt long short-term memory (LSTM) models to predict one-day-ahead stock trend on respective exchanges. Our work can be considered as one of the novel approaches that integrate the international stock exchanges to predict the stock trend of corresponding markets. For the experiment, we take datasets of five companies listed on National Stock Exchange (NSE), Bombay Stock Exchange (BSE), as well as New York Stock Exchange (NYSE); the prediction performance is evaluated using directional accuracy (DA), precision, recall, and F-measure metrics. The results using these metrics indicate performance improvement with international exchanges, and hence the potential adaptability of the proposed approach.

Intrusion Detection Using Deep Neural Network with AntiRectifier Layer

Book Chapter

Book NameApplied Soft Computing and Communication Networks

PublisherSpringer

Author NameRitika Lohiya and Ankit Thakkar

Page Number89-105

Chapter TitleIntrusion Detection Using Deep Neural Network with AntiRectifier Layer

Published YearJuly 2021

ISSN/ISBN No978-981-33-6172-0

Indexed INScopus

Abstract

Data security is regarded to be one of the crucial challenges in this fast-growing internet world. Data generated through internet is exposed to various types of vulnerabilities and exploits. Security mechanisms such as Intrusion Detection System (IDS) are designed to detect various types of vulnerabilities and attacks. Various Machine Learning (ML) and Deep Learning (DL) techniques are used for building IDS. In this paper, we aim to build Deep Neural Network (DNN)-based IDS for attack detection and classification. DNN technique has certain challenges such as complex network structure, co-adaptation of feature vectors, over-fitting, to name a few. We aim to address these challenges by using AntiRectifier layer and variants of dropout namely, Standard dropout, Gaussian dropout, and Gaussian Noise. In this paper, we have evaluated DNN-based IDS using NSL-KDD, UNSW_NB-15 and CIC-IDS-2017 dataset. The experimental results show that DNN-based IDS with AntiRectifier layer outperforms compared to ML techniques such as Decision Tree (DT), Random Forest (RF), Naïve Bayes (NB), Support Vector Machine (SVM), k-Nearest Neighbours (k-NN) and variants of dropout namely, Standard dropout, Gaussian dropout, and Gaussian noise in terms of accuracy, precision, recall, f-score, and false positive rate.

A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions

Journal

Journal NameArtificial Intelligence Review

Title of PaperA survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions

PublisherSpringer

Volume NumberYet to be assigned

Page Number1-111

Published YearJuly 2021

ISSN/ISBN No1573-7462

Indexed INScopus, Web of Science, EBSCO

Abstract

With the increase in the usage of the Internet, a large amount of information is exchanged between different communicating devices. The data should be communicated securely between the communicating devices and therefore, network security is one of the dominant research areas for the current network scenario. Intrusion detection systems (IDSs) are therefore widely used along with other security mechanisms such as firewall and access control. Many research ideas have been proposed pertaining to the IDS using machine learning (ML) techniques, deep learning (DL) techniques, and swarm and evolutionary algorithms (SWEVO). These methods have been tested on the datasets such as DARPA, KDD CUP 99, and NSL-KDD using network features to classify attack types. This paper surveys the intrusion detection problem by considering algorithms from areas such as ML, DL, and SWEVO. The survey is a representative research work carried out in the field of IDS from the year 2008 to 2020. The paper focuses on the methods that have incorporated feature selection in their models for performance evaluation. The paper also discusses the different datasets of IDS and a detailed description of recent dataset CIC IDS-2017. The paper presents applications of IDS with challenges and potential future research directions. The study presented, can serve as a pedestal for research communities and novice researchers in the field of network security for understanding and developing efficient IDS models.

RGB-D based human action recognition using evolutionary self-adaptive extreme learning machine with knowledge-based control parameters

Journal

Journal NameJournal of Ambient Intelligence and Humanized Computing

Title of PaperRGB-D based human action recognition using evolutionary self-adaptive extreme learning machine with knowledge-based control parameters

PublisherSpringer

Volume NumberYet to be assigned

Page Number1-19

Published YearJune 2021

ISSN/ISBN No1868-5145

Indexed INScopus, Web of Science, EBSCO

Abstract

Human Action Recognition (HAR) has gained considerable attention due to its various applications such as monitoring activities, robotics, visual surveillance, to name a few. An action recognition task consists of feature extraction, dimensionality reduction, and action classification. The paper proposes an action recognition approach for depth-based input by designing Single Layer Feed forward Network (SLFN) using Self-adaptive Differential Evolution with knowledge-based control parameter-Extreme Learning Machine (SKPDE-ELM). To capture motion cues, we have used Depth Motion Map (DMM) wherein to obtain compact features, Local Binary Pattern (LBP) is applied. Thereafter, for dimensionality reduction, Principal Component Analysis (PCA) is applied to reduce the feature dimensions. For the action classification task, Extreme Learning Machine (ELM) achieves good performance for depth-based input due to its learning speed and good generalization performance. Further, to optimize the performance of ELM classifier, an evolutionary method named SKPDE is used to derive the hidden parameters of ELM classifier. The performance of the proposed approach is compared with the existing approaches Kernel ELM (KELM), L2-Collaborative Representation Classifier (CRC), and Probabilistic CRC (Pro-CRC) using datasets MSRAction3D (with 557 samples), MSRAction3D (with 567 samples), MSRDaily Activity3D, MSRGesture3D, and UTDMHAD. The proposed approach is also statistically tested using Wilcoxon signed rank-test.

A comprehensive survey on deep neural networks for stock market: The need, challenges, and future directions

Journal

Journal NameExpert Systems with Applications

Title of PaperA comprehensive survey on deep neural networks for stock market: The need, challenges, and future directions

PublisherElsevier

Volume Number177

Page Number1-17

Published YearMarch 2021

ISSN/ISBN No0957-4174

Indexed INScopus, Web of Science

Abstract

The stock market has been an attractive field for a large number of organizers and investors to derive useful predictions. Fundamental knowledge of stock market can be utilised with technical indicators to investigate different perspectives of the financial market; also, the influence of various events, financial news, and/or opinions on investors’ decisions and hence, market trends have been observed. Such information can be exploited to make reliable predictions and achieve higher profitability. Computational intelligence has emerged with various deep neural network (DNN) techniques to address complex stock market problems. In this article, we aim to review the significance and need of DNNs in the field of stock price and trend prediction; we discuss the applicability of DNN variations to the temporal stock market data and also extend our survey to include hybrid, as well as metaheuristic, approaches with DNNs. We observe the potential limitations for stock market prediction using various DNNs. To provide an experimental evaluation, we also conduct a series of experiments for stock market prediction using nine deep learning-based models; we analyse the impact of these models on forecasting the stock market data. We also evaluate the performance of individual models with different number of features. We discuss challenges, as well as potential future research directions, and conclude our survey with the experimental study. This survey can be referred for the recent perspectives of DNN-based stock market prediction, primarily covering research spanning over years 2017-2020

Fusion in stock market prediction: A decade survey on the necessity, recent developments, and potential future directions

Journal

Journal NameInformation Fusion

Title of PaperFusion in stock market prediction: A decade survey on the necessity, recent developments, and potential future directions

PublisherElsevier

Volume Number65

Page Number95-107

Published YearJanuary 2021

ISSN/ISBN No1566-2535

Indexed INScopus, Web of Science

Abstract

Investment in a financial market is aimed at getting higher benefits; this complex market is influenced by a large number of events wherein the prediction of future market dynamics is challenging. The investors’ etiquettes towards stock market may demand the need of studying various associated factors and extract the useful information for reliable forecasting. Fusion can be considered as an approach to integrate data or characteristics, in general, and enhance the prediction based on the combinational approach that can aid each other. We conduct a systematic approach to present a survey for the years 2011–2020 by considering articles that have used fusion techniques for various stock market applications and broadly categorize them into information fusion, feature fusion, and model fusion. The major applications of stock market include stock price and trend prediction, risk analysis and return forecasting, index prediction, as well as portfolio management. We also provide an infographic overview of fusion in stock market prediction and extend our survey for other finely addressed financial prediction problems. Based on our surveyed articles, we provide potential future directions and concluding remarks on the significance of applying fusion in stock market.

Application Domains, Evaluation Datasets, and Research Challenges of IoT: A Systematic Review

Journal

Journal NameIEEE Internet of Things Journal

Title of PaperApplication Domains, Evaluation Datasets, and Research Challenges of IoT: A Systematic Review

PublisherIEEE

Volume Number8

Page Number8774 - 8798

Published YearDecember 2020

ISSN/ISBN No2327-4662

Indexed INScopus, Web of Science

Abstract

We are at the brink of Internet of Things (IoT) era where smart devices and other wireless devices are redesigning our environment to make it more correlative, flexible, and communicative. IoT is now evolving to Internet of Everything, as it incorporates and builds a system that includes wireless networks, sensors, cloud servers, analytics, smart devices, and advanced technologies. The IoT systems are equipped with embedded devices having network connectivity and sensors to have a machine to machine interaction. The field of IoT is advancing to provide smart solutions to various applications such as transportation, healthcare, farming, to name a few. Considering the diverse perspective of IoT systems/network, the paper aims at discussing different applications of IoT across various research domains and to highlight the use of IoT in a variety of applications. We have systematically reviewed applications of IoT with the datasets to understand the characteristics of the data collected by the IoT devices. In this paper, a comprehensive survey on the role of IoT in various application domains is presented for the years 2015-2019. The paper lists different commercialized solutions developed in various IoT application domains. The aim to discuss commercialized IoT paradigms is to highlight research efforts performed in the field of IoT that have been transformed into real-life solutions. The paper also discussed research challenges in the field of IoT to strengthen the research for developing future IoT applications.

A Review on Machine Learning and Deep Learning Perspectives of IDS for IoT: Recent Updates, Security Issues, and Challenges

Journal

Journal NameArchives of Computational Methods in Engineering

Title of PaperA Review on Machine Learning and Deep Learning Perspectives of IDS for IoT: Recent Updates, Security Issues, and Challenges

PublisherSpringer Nature

Volume Number28

Page Number3211-3243

Published YearOctober 2020

ISSN/ISBN No1886-1784

Indexed INScopus, Web of Science, EBSCO

Abstract

Internet of Things (IoT) is widely accepted technology in both industrial as well as academic field. The objective of IoT is to combine the physical environment with the cyber world and create one big intelligent network. This technology has been applied to various application domains such as developing smart home, smart cities, healthcare applications, wireless sensor networks, cloud environment, enterprise network, web applications, and smart grid technologies. These wide emerging applications in variety of domains raise many security issues such as protecting devices and network, attacks in IoT networks, and managing resource-constrained IoT networks. To address the scalability and resource-constrained security issues, many security solutions have been proposed for IoT such as web application firewalls and intrusion detection systems. In this paper, a comprehensive survey on Intrusion Detection System (IDS) for IoT is presented for years 2015–2019. We have discussed various IDS placement strategies and IDS analysis strategies in IoT architecture. The paper discusses various intrusions in IoT, along with Machine Learning (ML) and Deep Learning (DL) techniques for detecting attacks in IoT networks. The paper also discusses security issues and challenges in IoT.

A survey on video-based Human Action Recognition: recent updates, datasets, challenges, and applications

Journal

Journal NameArtificial Intelligence Review

Title of PaperA survey on video-based Human Action Recognition: recent updates, datasets, challenges, and applications

PublisherSpringer Netherlands

Volume Number54

Page Number2259–2322

Published YearSeptember 2020

ISSN/ISBN No1573-7462

Indexed INScopus, Web of Science

Abstract

Human Action Recognition (HAR) involves human activity monitoring task in different areas of medical, education, entertainment, visual surveillance, video retrieval, as well as abnormal activity identification, to name a few. Due to an increase in the usage of cameras, automated systems are in demand for the classification of such activities using computationally intelligent techniques such as Machine Learning (ML) and Deep Learning (DL). In this survey, we have discussed various ML and DL techniques for HAR for the years 2011–2019. The paper discusses the characteristics of public datasets used for HAR. It also presents a survey of various action recognition techniques along with the HAR applications namely, content-based video summarization, human–computer interaction, education, healthcare, video surveillance, abnormal activity detection, sports, and entertainment. The advantages and disadvantages of action representation, dimensionality reduction, and action analysis methods are also provided. The paper discusses challenges and future directions for HAR.

Predicting stock trend using an integrated term frequency–inverse document frequency-based feature weight matrix with neural networks

Journal

Journal NameApplied Soft Computing

Title of PaperPredicting stock trend using an integrated term frequency–inverse document frequency-based feature weight matrix with neural networks

PublisherElsevier

Volume Number96

Page Number1-13

Published YearAugust 2020

ISSN/ISBN No1568-4946

Indexed INScopus, Web of Science

Abstract

The financial market consists of various money-making strategies wherein trading through a stock market is an important example. The complex non-linear behaviors of volatile stock markets attract researchers to study inherent patterns. As the primary motivation for investment in such markets is to gain higher profits, potential stocks are given considerable attention using various weighting strategies that can enhance future returns. Term frequency–inverse document frequency (TF–IDF) is a statistical approach with remarkable applications in the financial domain for information retrieval from textual data; it identifies the importance of a term in the given document of a corpus. However, the application of TF–IDF for the numerical data representation is explored to a limited extent. In this article, we propose to extend the applicability of TF–IDF for the numerical time-series stock market data; we process the data and prepare them to be suitable for TF–IDF. We utilize this statistical approach to derive feature weight matrix from the historical stock market data and further, integrate it with the widely explored neural network architectures namely, backpropagation neural network (BPNN), long short-term memory (LSTM), and gated recurrent unit (GRU) for predicting stock market trend. Simulation results show that the proposed integrated approach using TF–IDF-based feature weight matrix and neural networks outperforms the considered recent approaches. The results are statistically supported with p-value less than .01 using a Wilcoxon signed-rank test; our proposed approach is supported with illustrative examples to develop better understanding of the work. Also, remarks on the conclusions and potential future scope are discussed.

A Comprehensive Survey on Portfolio Optimization, Stock Price and Trend Prediction Using Particle Swarm Optimization

Journal

Journal NameArchives of Computational Methods in Engineering

Title of PaperA Comprehensive Survey on Portfolio Optimization, Stock Price and Trend Prediction Using Particle Swarm Optimization

PublisherSpringer Nature

Volume Number28

Page Number2133–2164

Published YearJune 2020

ISSN/ISBN No1886-1784

Indexed INScopus, Web of Science, EBSCO

Abstract

Stock market trading has been a subject of interest to investors, academicians, and researchers. Analysis of the inherent non-linear characteristics of stock market data is a challenging task. A large number of learning algorithms are developed to study market behaviours and enhance the prediction accuracy; they have been optimized using swarm and evolutionary computation such as particle swarm optimization (PSO); its global optimization ability with continuous data has been exploited in financial domains. Limitations in the existing approaches and potential future research directions for enhancing PSO-based stock market prediction are discussed. This article aims at balancing the economics and computational intelligence aspects; it also analyzes the superiority of PSO for stock portfolio optimization, stock price and trend prediction, and other related stock market aspects along with implications of PSO.

Attack classification using feature selection techniques: a comparative study

Journal

Journal NameJournal of Ambient Intelligence and Humanized Computing

Title of PaperAttack classification using feature selection techniques: a comparative study

PublisherSpringer

Volume Number12

Page Number1249–1266

Published YearJune 2020

ISSN/ISBN No1868-5145

Indexed INScopus, Web of Science, EBSCO

Abstract

The goal of securing a network is to protect the information flowing through the network and to ensure the security of intellectual as well as sensitive data for the underlying application. To accomplish this goal, security mechanism such as Intrusion Detection System (IDS) is used, that analyzes the network traffic and extract useful information for inspection. It identifies various patterns and signatures from the data and use them as features for attack detection and classification. Various Machine Learning (ML) techniques are used to design IDS for attack detection and classification. All the features captured from the network packets do not contribute in detecting or classifying attack. Therefore, the objective of our research work is to study the effect of various feature selection techniques on the performance of IDS. Feature selection techniques select relevant features and group them into subsets. This paper implements Chi-Square, Information Gain (IG), and Recursive Feature Elimination (RFE) feature selection techniques with ML classifiers namely Support Vector Machine, Naïve Bayes, Decision Tree Classifier, Random Forest Classifier, k-nearest neighbours, Logistic Regression, and Artificial Neural Networks. The methods are experimented on NSL-KDD dataset and comparative analysis of results is presented.

A Comprehensive Survey on Energy-Efficient Power Management Techniques

Journal

Journal NameProcedia Computer Science

Title of PaperA Comprehensive Survey on Energy-Efficient Power Management Techniques

PublisherScienceDirect

Volume Number167

Page Number1189-1199

Published YearApril 2020

ISSN/ISBN No1877-0509

Indexed INScopus, Others

Abstract

In the current age of machine intelligence, computer literacy has been achieved in terms of its knowledge and ability of utilization at various stages. As compared to the urge of demanding for high computer functionalities as well as performance, the concern towards the cost in attaining such goals has been limited. The developers try to empower a large number of operations which may consume a large amount of energy. The power consumption has been perceived as an important aspect for the stability and growth of an economy of the country; it has also been recognized as one of the factors that impact the environment. This article has considered the prime implication of energy-efficient power management techniques; it discusses the necessity of adopting the energy-aware computer and reviews the existing works on relevant components. This article may be helpful to attain the essentials of green computing.

A Review of the Advancement in Intrusion Detection Datasets

Journal

Journal NameProcedia Computer Science

Title of PaperA Review of the Advancement in Intrusion Detection Datasets

PublisherScienceDirect

Volume Number167

Page Number636-645

Published YearApril 2020

ISSN/ISBN No1877-0509

Indexed INScopus, Others

Abstract

The research in the field of Cyber Security has raised the need to address the issue of cybercrimes that have caused the requisition of the intellectual properties such as break down of computer systems, impairment of important data, compromising the confidentiality, authenticity, and integrity of the user. Considering these scenarios, it is essential to secure the computer systems and the user using an Intrusion Detection System (IDS). The performance of IDS studied by developing an IDS dataset, consisting of network traffic features to learn the attack patterns. Intrusion detection is a classification problem, wherein various Machine Learning (ML) and Data Mining (DM) techniques applied to classify the network data into normal and attack traffic. Moreover, the types of network attacks changed over the years, and therefore, there is a need to update the datasets used for evaluating IDS. This paper list the different IDS datasets used for the evaluation of IDS model. The paper presents an overview of the ML and DM techniques used for IDS along with the discussion on CIC-IDS-2017 and CSE-CIC-IDS-2018. These are recent datasets consisting of network attack features and include new attacks categories. This paper discusses the recent advancement in the IDS datasets that can be used by various research communities as the manifesto for using the new IDS datasets for developing efficient and effective ML and DM based IDS.

CREST: Cross-Reference to Exchange-based Stock Trend Prediction using Long Short-Term Memory

Journal

Journal NameProcedia Computer Science

Title of PaperCREST: Cross-Reference to Exchange-based Stock Trend Prediction using Long Short-Term Memory

PublisherScienceDirect

Volume Number167

Page Number616-625

Published YearApril 2020

ISSN/ISBN No1877-0509

Indexed INScopus, Others

Abstract

Due to a large number of tradings in the stock market, it generally experiences fluctuations throughout the day. Such oscillations influence market capitals of the companies listed on a stock exchange. Hence, in order to take suitable trading steps, prediction of the future stock price as well as trend direction becomes a crucial task. National Stock Exchange (NSE) and Bombay Stock Exchange (BSE) cover the largest market capitalization in India. A company’s shares are traded according to the stock exchange it is listed on; it can also be listed on multiple exchanges. Various approaches have tried to predict stock markets in terms of future indices, price movement, and returns perspectives, however, analyzing stocks of a company, which is listed on multiple exchanges, has been limited to the financial perspectives. In this article, a cross-reference to exchange-based stock trend (CREST) prediction method is proposed using long short-term memory (LSTM). The daily stock prices of Wipro Limited (WIPRO) company, which is listed on NSE as well as BSE, have been collected and the stock price movement of WIPRO in one exchange has been analyzed for predicting the trend in the other exchange. To identify the applicability of our approach, CREST has also experimented with Infosys Limited and Larsen & Toubro Infotech Limited companies. The performance is evaluated using root-mean-square error and directional accuracy along with precision, recall, and F-measure for the results of all three companies.

Role of swarm and evolutionary algorithms for intrusion detection system: A survey

Journal

Journal NameSwarm and Evolutionary Computation

Title of PaperRole of swarm and evolutionary algorithms for intrusion detection system: A survey

PublisherScienceDirect

Volume Number53

Page Number1-34

Published YearMarch 2020

ISSN/ISBN No2210-6502

Indexed INScopus, Web of Science

Abstract

The growth of data and categories of attacks, demand the use of Intrusion Detection System(IDS) effectively using Machine Learning (ML) and Deep Learning (DL) techniques. Apart from the ML and DL techniques, Swarm and Evolutionary (SWEVO) Algorithms have also shown significant performance to improve the efficiency of the IDS models. This survey covers SWEVO-based IDS approaches such as Genetic Algorithm(GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Artificial Bee Colony Optimization(ABC), Firefly Algorithm (FA), Bat Algorithm (BA), and Flower Pollination Algorithm (FPA). The paper also discusses applications of the SWEVO in the field of IDS along with challenges and possible future directions.

Sentiment analysis: an empirical comparison between various training algorithms for artificial neural network

Journal

Journal NameInternational Journal of Innovative Computing and Applications

Title of PaperSentiment analysis: an empirical comparison between various training algorithms for artificial neural network

PublisherInderscience Publishers (IEL)

Volume Number11

Page Number9-29

Published YearFebruary 2020

ISSN/ISBN No1751-6498

Indexed INScopus, Others

VIKAS: a new virtual keyboard-based simple and efficient text CAPTCHA verification scheme

Journal

Journal NameInternational Journal of Information and Computer Security

Title of PaperVIKAS: a new virtual keyboard-based simple and efficient text CAPTCHA verification scheme

PublisherINDERSCIENCE

Volume Number12

Page Number90-105

Published YearDecember 2019

ISSN/ISBN No1744-1773

Indexed INScopus, Others

A Comprehensive Survey on Travel Recommender Systems

Journal

Journal NameArchives of Computational Methods in Engineering

Title of PaperA Comprehensive Survey on Travel Recommender Systems

PublisherSpringer Netherlands

Volume Number27

Page Number1545–1571

Published YearOctober 2019

ISSN/ISBN No1886-1784

Indexed INScopus, EBSCO

Abstract

Travelling is a combination of journey, transportation, travel-time, accommodation, weather, events, and other aspects which are likely to be experienced by most of the people at some point in their life. To enhance such experience, we generally look for assistance in planning a tour. Today, the information available on tourism-related aspects on the Internet is boundless and exploring suitable travel package/product/service may be time-consuming. A recommender system (RS) can assist for various tour-related queries such as top destinations for summer vacation, preferable climate conditions for tracking, the fastest way to transport, or photography assistance for specific destinations. In this survey, we have presented a pervasive review on travel and associated factors such as hotels, restaurants, tourism package and planning, and attractions; we have also tailored recommendations on a tourist’s diverse requirements such as food, transportation, photography, outfits, safety, and seasonal preferences. We have classified travel-based RSs and presented selection criteria, features, and technical aspects with datasets, methods, and results. We have briefly supplemented research articles from diverse facets; various frameworks for a travel-based RS are discussed. We believe our survey would introduce a state-of-the-art travel RS; it may be utilized to solve the existing limitations and extend its applicability.

Travelling Salesman Problem: An Empirical Comparison Between ACO, PSO, ABC, FA and GA

Book Chapter

Book NameAdvances in Intelligent Systems and Computing

PublisherSpringer, Singapore

Author Name Kinjal Chaudhari, Ankit Thakkar

Page Number397-405

Chapter TitleTravelling Salesman Problem: An Empirical Comparison Between ACO, PSO, ABC, FA and GA

Published YearSeptember 2019

ISSN/ISBN No978-981-13-6000-8

Indexed INScopus

A Voting-Based Sentiment Classification Model

Book Chapter

Book Name Advances in Intelligent Systems and Computing

PublisherSpringer, Singapore

Author NameDhara Mungra, Anjali Agrawal, Ankit Thakkar

Page Number 551-558

Chapter TitleA Voting-Based Sentiment Classification Model

Published YearAugust 2019

ISSN/ISBN No978-981-13-8617-6

Indexed INScopus

Survey on handwriting-based personality trait identification

Journal

Journal NameExpert Systems with Applications

Title of PaperSurvey on handwriting-based personality trait identification

PublisherElsevier

Volume Number124

Page Number282-308

Published YearJune 2019

ISSN/ISBN No0957-4174

Indexed INScopus, Web of Science

Abstract

Personality is a combination of various characteristics and qualities of an individual. It may be affected by the growth and evolution of one’s values, attributes, relationships with the community, personal memories of life events, habits, and skills. Behaviours and decisions of an individual are largely directed by his/her personality. Identification of such a personality trait can be performed b

A Survey on Intelligent Transportation System Using Internet of Things

Book Chapter

Book Name Advances in Intelligent Systems and Computing

PublisherSpringer, Singapore

Author NamePalak Patel, Zunnun Narmawala, Ankit Thakkar

Page Number231-240

Chapter TitleA Survey on Intelligent Transportation System Using Internet of Things

Published YearMay 2019

Indexed INScopus

Necessary Precautions in Cognitive Tutoring System

Book Chapter

Book Name Advances in Intelligent Systems and Computing

PublisherSpringer, Singapore

Author NameKevin Vora, Shashvat Shah, Harshad Harsoda, Jeel Sheth, Ankit Thakkar

Page Number 445-452

Chapter TitleNecessary Precautions in Cognitive Tutoring System

Published YearJanuary 2019

ISSN/ISBN No978-981-13-8617-6

Indexed INScopus

The Fog Computing Paradigm: A Rising Need of IoT World

Book Chapter

Book NameAdvances in Intelligent Systems and Computing

PublisherSpringer, Singapore

Author NameShivani Desai, Ankit Thakkar

Page Number387-393

Chapter TitleThe Fog Computing Paradigm: A Rising Need of IoT World

Published YearOctober 2018

ISSN/ISBN No978-981-13-1609-8

Indexed INScopus

Emotion Recognition from Sensory and Bio-Signals: A Survey

Book Chapter

Book Name Advances in Intelligent Systems and Computing

PublisherSpringer, Singapore

Author NameKevin Vora, Shashvat Shah, Harshad Harsoda, Jeel Sheth, Seema Agarwal, Ankit Thakkar, Sapan H Mankad

Page Number345-355

Chapter TitleEmotion Recognition from Sensory and Bio-Signals: A Survey

Published YearOctober 2018

ISSN/ISBN No978-981-13-1609-8

Indexed INScopus

A Simple and Efficient Text-Based CAPTCHA Verification Scheme Using Virtual Keyboard

Book Chapter

Book Name Smart Innovation, Systems and Technologies

PublisherSpringer, Cham

Author NameKajol Patel and Ankit Thakkar

Page Number121-126

Chapter TitleA Simple and Efficient Text-Based CAPTCHA Verification Scheme Using Virtual Keyboard

Published YearAugust 2017

ISSN/ISBN No978-3-319-63644-3

Indexed INScopus, Others

DEAL: Distance and Energy Based Advanced LEACH Protocol

Book Chapter

Book Name Smart Innovation, Systems and Technologies

PublisherSpringer, Cham

Author NameAnkit Thakkar

Page Number370-376

Chapter TitleDEAL: Distance and Energy Based Advanced LEACH Protocol

Published YearAugust 2017

ISSN/ISBN No978-3-319-63644-3

Indexed INScopus, Others

An improved advanced low energy adaptive clustering hierarchy for a dense wireless sensor network

Conference

Title of PaperAn improved advanced low energy adaptive clustering hierarchy for a dense wireless sensor network

Proceeding Name2016 International Conference on Communication and Electronics Systems (ICCES), IEEE

PublisherIEEE

Author NameAnkit Thakkar

Page Number1-6

Published YearOctober 2016

ISSN/ISBN No978-1-5090-1066-0

Indexed INScopus, Others

An improved modified LEACH-C algorithm for energy efficient routing in Wireless Sensor Networks

Journal

Journal NameNirma University Journal of Engineering and Technology (NUJET)

Title of PaperAn improved modified LEACH-C algorithm for energy efficient routing in Wireless Sensor Networks

PublisherNirma University

Volume Number4

Page Number1-5

Published YearDecember 2015

ISSN/ISBN No2231-2870

Indexed INOthers

A new Bollinger Band based energy efficient routing for clustered wireless sensor network

Journal

Journal NameApplied Soft Computing

Title of PaperA new Bollinger Band based energy efficient routing for clustered wireless sensor network

PublisherElsevier

Volume Number32

Page Number144-153

Published YearJuly 2015

ISSN/ISBN No1568-4946

Indexed INScopus

Abstract

Designing of scalable routing protocol with prolonged network lifetime for a wireless sensor network (WSN) is a challenging task. WSN consists of large number of power, communication and computational constrained inexpensive nodes. It is difficult to replace or recharge battery of a WSN node when operated in a hostile environment. Cluster based routing is one of the techniques to provide prolonged network lifetime along with scalability. This paper proposes a technique for cluster formation derived from “Grid based method”. We have also proposed a new decentralized cluster head (CH) election method based on Bollinger Bands. Bollinger Bands are based on Upper Bollinger Band and Lower Bollinger Band, both of these bands are extremely reactive to any change in the inputs provided to them. We have used this property of Bollinger Bands to elect CH. Simulation result shows significant improvement in the network lifetime in comparison with other decentralized and ant based algorithms.

SKIP: a novel self-guided adaptive clustering approach to prolong lifetime of wireless sensor networks

Book Chapter

Book NameCommunication and Computing Systems

PublisherTaylor & Francis Group, London

Author NameAnkit Thakkar

Page Number335-340

Chapter TitleSKIP: a novel self-guided adaptive clustering approach to prolong lifetime of wireless sensor networks

Published YearFebruary 2015

ISSN/ISBN No978-1-138-02952-1

Indexed INScopus

Abstract

Wireless Sensor Network (WSN) consists of energy constraint sensor nodes, and it is difficult to replace or recharge batteries of these nodes when they operate in hostile environments. Hence, prolonging the lifetime of WSN nodes is an important issue for any WSN. Cluster based routing techniques improve the lifetime of WSNs, wherein longer stability and shorter instability periods are important aspects to measure network lifetime. Stable period ensures reliability of the data received from the network, as all nodes are alive during this period. This paper discusses a novel distributed adaptive clustering approach, Skip that guides every node to take part in the Cluster Head (CH) election process or not for the current epoch, based on residual energy of a node. Extensive simulations have been carried out to compare the proposed approach with prominent clustering techniques such as Low Energy Adaptive Clustering Hierarchy (LEACH), Stable Election Protocol (SEP) and enhanced Stable Election Protocol (SEP-E). Simulation results show that the proposed approach outperforms to LEACH, SEP and SEP-E protocols. The proposed approach Skip provides longer stability and does not deteriorate instability period. The performance of Skip is also validated using statistical test.

Cluster Head Election for Energy and Delay Constraint Applications of Wireless Sensor Network

Journal

Journal NameIEEE Sensors Journal

Title of PaperCluster Head Election for Energy and Delay Constraint Applications of Wireless Sensor Network

PublisherIEEE

Volume Number14

Page Number 2658 - 2664

Published YearAugust 2014

ISSN/ISBN No1530-437X

Indexed INScopus, Web of Science

Abstract

Designing of a multi-hop Wireless Sensor Network (WSN) depends upon the requirements of the underlying sensing application. The main objective of WSNs is to monitor physical phenomenon of interest in a given region of interest using sensors and provide collected data to sink. The WSN is made of a large number of energy, communication, and computational constraint nodes, to overcome energy constrains, replacing or recharging the batteries of the WSN nodes is an impossible task, once they are deployed in a hostile environment. Therefore, to keep the network alive as long as possible, communication between the WSN nodes must be done with load balancing. Time critical applications like forest fire detection, battle field monitoring demands reception of data by the sink with the bounded delay to avoid disasters. Hence, there is a need to design a protocol which enhances the network lifetime and provides information to the sink with a bounded delay. This paper will address this problem and solution. In this paper, a routing algorithm is proposed by introducing Energy Delay Index for Trade-off (EDIT) to optimize both objectives-energy and delay. The EDIT is used to select cluster heads and “next hop” by considering energy and/or delay requirements of a given application. Proposed approach is derived using two different aspects of distances between a node and the sink named Euclidean distance and Hop-count, and further prove using realistic parameters of radio to get data closest to the test bed implementation. The results aspire to give sufficient insights to others before doing test bed implementation.

Alive nodes based improved low energy adaptive clustering hierarchy for wireless sensor network

Book Chapter

Book Name Smart Innovation, Systems and Technologies

PublisherSpringer, Cham

Author NameAnkit Thakkar, Ketan Kotecha

Page Number51-58

Chapter TitleAlive nodes based improved low energy adaptive clustering hierarchy for wireless sensor network

Published YearApril 2014

ISSN/ISBN No978-3-319-07350-7

Indexed INScopus, Others

A new hybrid method for face recognition

Conference

Title of PaperA new hybrid method for face recognition

Proceeding NameEngineering (NUiCONE), 2013 Nirma University International Conference on

PublisherIEEE

Author NameAnkit Thakkar, N Jivani, J Padasumbiya, CI Patel

Published YearNovember 2013

ISSN/ISBN No2375-1282

Indexed INScopus, Others

Aggregate features approach for texture analysis

Conference

Title of PaperAggregate features approach for texture analysis

Proceeding Name2012 Nirma University International Conference on Engineering (NUiCONE)

PublisherIEEE

Author NameRipal Patel, Chirag I Patel, Ankit Thakkar

Published YearDecember 2012

ISSN/ISBN No2375-1282

Indexed INScopus, Others

Power Aware Scheduling for Adhoc sensor Network Nodes

Conference

Title of PaperPower Aware Scheduling for Adhoc sensor Network Nodes

Proceeding Name 2009 3rd International Conference on Signal Processing and Communication Systems

PublisherIEEE

Author NameAnkit Thakkar, SN Pradhan

Published YearSeptember 2009

ISSN/ISBN No978-1-4244-4473-1

Indexed INScopus, Others

Anuja Nair

Resource allocation in V2X communication: State-of-the-art and research challenges

Journal

Journal NamePhysical Communication, Elsevier [Impact Factor: 2.2]

Title of PaperResource allocation in V2X communication: State-of-the-art and research challenges

PublisherElsevier

Volume Number64

Published YearApril 2024

ISSN/ISBN No1874-4907

Indexed INScopus, Web of Science

Blockchain-Based Decentralized Application for Telesurgery in Metaverse Environment

Conference

Title of PaperBlockchain-Based Decentralized Application for Telesurgery in Metaverse Environment

Proceeding Name2024 14th International Conference on Cloud Computing, Data Science & Engineering (Confluence)

PublisherIEEE

Author NameSatya Chaudhary, Yogi Patel, Sachi Chaudhary, Rajesh Gupta, Riya Kakkar, Sudeep Tanwar, Anuja Nair

Year , VenueJanuary 2024 , Noida, India

Page Number492-497

ISSN/ISBN No2766-421X

Indexed INScopus

Blockchain-Envisioned Onion Routing Framework for Internet of Vehicles Communication toward 6G

Journal

Journal NameIEEE Internet of Things Magazine

Title of PaperBlockchain-Envisioned Onion Routing Framework for Internet of Vehicles Communication toward 6G

PublisherIEEE

Volume Number7

Published YearJanuary 2024

AI-Based Accident Severity Detection Scheme for V2X Communication Beyond 5G Networks

Conference

Title of PaperAI-Based Accident Severity Detection Scheme for V2X Communication Beyond 5G Networks

Proceeding Name2023 IEEE International Conference on Communications Workshops (ICC Workshops)

PublisherIEEE

Author NameAnuja Nair, Dr. Sudeep Tanwar

Organization1002-1007

Year , VenueOctober 2023 , Rome, Italy

ISSN/ISBN No2694-2941

Indexed INScopus

EEG‐based biometric authentication system using convolutional neural network for military applications

Journal

Journal NameSecurity and Privacy, Wiley [ [Impact Factor: 1.9]

Title of PaperEEG‐based biometric authentication system using convolutional neural network for military applications

PublisherWiley

Volume Number7

Published YearOctober 2023

ISSN/ISBN No2475-6725

Indexed INScopus, Web of Science

MetaHate: AI‐based hate speech detection for secured online gaming in metaverse using blockchain

Journal

Journal NameSecurity and Privacy, Wiley [ [Impact Factor: 1.9]

Title of PaperMetaHate: AI‐based hate speech detection for secured online gaming in metaverse using blockchain

PublisherWiley

Volume Number7

Published YearSeptember 2023

ISSN/ISBN No2475-6725

Indexed INScopus, Web of Science

CNN and Bidirectional GRU-Based Heartbeat Sound Classification Architecture for Elderly People

Journal

Journal NameMathematics, MDPI [Impact Factor: 2.592]

Title of PaperCNN and Bidirectional GRU-Based Heartbeat Sound Classification Architecture for Elderly People

PublisherMultidisciplinary Digital Publishing Institute

Volume Number11

Page Number1365

Published YearMarch 2023

Indexed INScopus, Web of Science

EmReSys: AI-based Efficient Employee Ranking and Recommender System for Organizations

Conference

Title of PaperEmReSys: AI-based Efficient Employee Ranking and Recommender System for Organizations

Proceeding Name2022 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)

PublisherIEEE

Author NameDhairya Jadav, Dev Patel, Somya Thacker, Anuja Nair, Rajesh Gupta, Nilesh Kumar Jadav, Sudeep Tanwar

Year , VenueFebruary 2023 , Greater Noida, India

Page Number440-445

Indexed INScopus

Software Effort Estimation using Machine Learning Algorithms

Conference

Title of PaperSoftware Effort Estimation using Machine Learning Algorithms

Proceeding Name2022 6th International Conference on Electronics, Communication and Aerospace Technology

PublisherIEEE

Author NameRuju Shah, Vrunda Shah, Anuja R Nair, Tarjni Vyas, Shivani Desai, Sheshang Degadwala

Year , VenueJanuary 2023 , Coimbatore, India

Page Number1-8

Indexed INScopus

Fusion of blockchain and IoT in scientific publishing: Taxonomy, tools, and future directions

Journal

Journal NameFuture Generation Computer Systems, Elsevier [Impact Factor: 7.307]

Title of PaperFusion of blockchain and IoT in scientific publishing: Taxonomy, tools, and future directions

PublisherNorth-Holland

Volume Number142

Page Number248-275

Published YearJanuary 2023

Indexed INScopus, Web of Science

Blockchain-Assisted Onion Routing Protocol for Internet of Underwater Vehicle Communication

Journal

Journal NameIEEE Internet of Things Magazine

Title of PaperBlockchain-Assisted Onion Routing Protocol for Internet of Underwater Vehicle Communication

PublisherIEEE

Volume Number5

Page Number30-35

Published YearDecember 2022

Blockchain and AI-based Secure Onion Routing Framework for Data Dissemination in IoT Environment Underlying 6G Networks

Conference

Title of PaperBlockchain and AI-based Secure Onion Routing Framework for Data Dissemination in IoT Environment Underlying 6G Networks

Proceeding Name2022 Sixth International Conference on Smart Cities, Internet of Things and Applications (SCIoT)

PublisherIEEE

Author NameRajesh Gupta, Nilesh Kumar Jadav, Anuja Nair, Sudeep Tanwar, Hossein Shahinzadeh

Year , VenueNovember 2022 , Mashhad, Iran

Page Number1-6

Indexed INScopus

AI‐driven network softwarization scheme for efficient message exchange in IoT environment beyond 5G

Journal

Journal NameInternational Journal of Communication Systems, Wiley [Impact Factor: 1.882]

Title of PaperAI‐driven network softwarization scheme for efficient message exchange in IoT environment beyond 5G

PublisherJohn Wiley & Sons Ltd

Published YearSeptember 2022

Indexed INScopus, Web of Science

A taxonomy on smart healthcare technologies: security framework, case study, and future directions

Journal

Journal NameJournal of Sensors, Hindawi [Impact Factor: 2.336]

Title of PaperA taxonomy on smart healthcare technologies: security framework, case study, and future directions

PublisherHindawi

Volume Number2022

Published YearJuly 2022

AI-empowered Secure Data Communication in V2X Environment with 6G Network

Conference

Title of PaperAI-empowered Secure Data Communication in V2X Environment with 6G Network

Proceeding NameIEEE INFOCOM 2022-IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

PublisherIEEE

Author NameAnuja R Nair, Nilesh Kumar Jadav, Rajesh Gupta, Sudeep Tanwar

Year , VenueJune 2022 , New York, NY, USA

Page Number1-6

Indexed INScopus

FAIR: A blockchain-based vaccine distribution scheme for pandemics

Conference

Title of PaperFAIR: A blockchain-based vaccine distribution scheme for pandemics

Proceeding Name2021 IEEE Globecom Workshops (GC Wkshps)

PublisherIEEE

Author NameAnuja R Nair, Rajesh Gupta, Sudeep Tanwar

Year , VenueJanuary 2022 , Madrid, Spain

Page Number1-6

Indexed INScopus

Insights of Deep Learning Applications

Conference

Title of PaperInsights of Deep Learning Applications

Proceeding Name2021 5th International Conference on Electronics, Communication and Aerospace Technology (ICECA)

PublisherIEEE

Author NameHet Shah, Shivani Desai, Tarjni Vyas, Anuja Nair, Sheshang Degadwala

Year , VenueJanuary 2022 , Coimbatore, India

Page Number1355-1360

Indexed INScopus

Intrusion Detection System-Deep Learning Perspective

Conference

Title of PaperIntrusion Detection System-Deep Learning Perspective

Proceeding Name2021 International Conference on Artificial Intelligence and Smart Systems (ICAIS)

PublisherIEEE

Author NameShivani Desai, Bhavyang Dave, Tarjni Vyas, Anuja R Nair

Year , VenueApril 2021 , Coimbatore, India

Page Number1193-1198

Indexed INScopus

Blockchain‐assisted secure UAV communication in 6G environment: Architecture, opportunities, and challenges

Journal

Journal NameIET communications [Impact Factor: 1.345]

Title of PaperBlockchain‐assisted secure UAV communication in 6G environment: Architecture, opportunities, and challenges

PublisherThe Institution of Engineering and Technology

Volume Number15

Page Number1352-1367

Published YearFebruary 2021

Indexed INScopus, Web of Science

Fog Computing Architectures and Frameworks for Healthcare 4.0

Book Chapter

Book NameFog Computing for Healthcare 4.0 Environments

PublisherSpringer, Cham

Author NameAnuja R Nair, Sudeep Tanwar

Page Number55-78

Chapter TitleFog Computing Architectures and Frameworks for Healthcare 4.0

Published YearAugust 2020

Indexed INScopus

Performance Analysis of Video On-demand and Live Video Streaming using Cloud based Services

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperPerformance Analysis of Video On-demand and Live Video Streaming using Cloud based Services

Volume Number21

Page Number479-496

Published YearAugust 2020

Indexed INScopus

Abstract

Recent years have seen an exponential increase in cloud computing for services such as high computational capabilities, vast storage, applications etc. that they provide. Moreover, today’s world is a constant shift from desktop or laptop devices towards handheld smartphones because of the wide range of applications that are supported. This paper discusses the present state of cloud computing for m

Survey on Cluster Based Data Aggregation in Wireless Sensor Network

Journal

Journal NameInternational Journal of Advanced Research in Computer Science

Title of PaperSurvey on Cluster Based Data Aggregation in Wireless Sensor Network

PublisherInternational Journal of Advanced Research in Computer Science

Volume Number8

Page Number311-314

Published YearMay 2017

ISSN/ISBN No0976-5697

Indexed INUGC List

Software Engineering Aided By Multimedia and Hypermedia

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperSoftware Engineering Aided By Multimedia and Hypermedia

Volume Number7

Page Number101-107

Published YearJune 2016

ISSN/ISBN No0973-7391

Indexed INUGC List

AdWords : A Study of Usage and Tools

Journal

Journal NameInternational Journal of Computer Science & Communication

Journal NameSustainability

Title of PaperBlockchain Adoption to Secure the Food Industry: Opportunities and Challenges

PublisherMDPI

Volume Number14

Page Number 7036-7061

Published YearJune 2022

ISSN/ISBN No20711050

Indexed INScopus, PubMed, Web of Science, ABDC, Indian citation Index, EBSCO

GrAb: A Deep Learning-Based Data-Driven Analytics Scheme for Energy Theft Detection

Journal

Journal NameSensor

Title of PaperGrAb: A Deep Learning-Based Data-Driven Analytics Scheme for Energy Theft Detection

PublisherMDPI

Volume Number22

Page Number 4048-4071

Published YearMay 2022

ISSN/ISBN No1424-8220

Indexed INScopus, PubMed, Web of Science, ABDC, Indian citation Index, EBSCO

AI-Empowered Recommender System for Renewable Energy Harvesting in Smart Grid System

Journal

Journal NameIEEE Access

Title of PaperAI-Empowered Recommender System for Renewable Energy Harvesting in Smart Grid System

PublisherIEEE

Volume Number10

Page Number24316- 24326

Published YearFebruary 2022

ISSN/ISBN No2169-3536

Indexed INScopus, PubMed, Web of Science, ABDC, Indian citation Index, EBSCO, Others

A Reinforcement-Learning-Based Secure Demand Response Scheme for Smart Grid System

Journal

Journal NameInternet of Things Journal

Title of PaperA Reinforcement-Learning-Based Secure Demand Response Scheme for Smart Grid System

PublisherIEEE

Volume Number9

Page Number2180 - 2191

Published YearJune 2021

ISSN/ISBN No2327-4662

Indexed INScopus, PubMed, Web of Science, ABDC, Indian citation Index, EBSCO

Ashwin Verma

Blockchain-based Federated Learning in UAVs Beyond 5G Networks: A Solution Taxonomy and Future Directions

Journal

Journal NameIEEE Access

Title of PaperBlockchain-based Federated Learning in UAVs Beyond 5G Networks: A Solution Taxonomy and Future Directions

PublisherIEEE

Volume NumberEarly Access

Page Number1-1

Published YearMarch 2022

ISSN/ISBN No2169-3536

Indexed INScopus, PubMed, Web of Science

Abstract

Recently, unmanned aerial vehicles (UAVs) have gained attention due to increased use-cases in healthcare, monitoring, surveillance, and logistics operations. UAVs mainly communicate with mobile base stations, ground stations (GS), or networked peer UAVs, known as UAV swarms. UAVs communicate with GS, or UAV swarms, over wireless channels to support mission-critical operations. Communication latency, bandwidth, and precision are of prime importance in such operations. With the rise of data-driven applications, fifth-generation (5G) networks would face bottlenecks to communicate at near-real-time, at low latency and improved coverage. Thus, researchers have shifted towards network designs that incorporate beyond 5G (B5G) networks for UAV designs. However, UAVs are resource-constrained, with limited power and battery, and thus centralized cloud-centric models are not suitable. Moreover, as exchanged data is through open channels, privacy and security issues exist. Federated learning (FL) allows data to be trained on local nodes, preserving privacy and improving network communication. However, sharing of local updates is required through a trusted consensus mechanism. Thus, blockchain (BC)-based FL schemes for UAVs allow trusted exchange of FL updates among UAV swarms and GS. To date, limited research has been carried out on the integration of BC and FL in UAV management. The proposed survey addresses the gap and presents a solution taxonomy of BC-based FL in UAVs for B5G networks due to the open problem. This paper presents a reference architecture and compares its potential benefits over traditional BC-based UAV networks. Open issues and challenges are discussed, with possible future directions. Finally, we present a logistics case study of BC-based FL-oriented UAVs in 6G networks. The survey aims to aid researchers in developing potential UAV solutions with the key integrating principles over a diverse set of application verticals.

Statistical analysis on the COVID-19 infection spread in United State of America: a Prophet Forecasting Model

Conference

Title of PaperStatistical analysis on the COVID-19 infection spread in United State of America: a Prophet Forecasting Model

Proceeding Name2021 Sixth International Conference on Image Information Processing (ICIIP)

Indexed INScopus, PubMed, Web of Science

Abstract

This paper proposes a generic scheme VaCoChain, that fuses blockchain (BC) and unmanned aerial vehicles (UAVs) underlying fifth-generation (5G) communication services for timely vaccine distribution during novel coronavirus (COVID-19) and future pandemics. The scheme offers 5G-tactile internet (5G-TI)-based services for UAV communication networks (UAVCN) monitored through ground controller stations (GCs). 5G-TI enabled UAVCN supports real-time dense connectivity at ultra-low round-trip time (RTT) latency of < 1 and high availability of 99.9999%. Thus, it can support resilient vaccine distributions in a phased manner at government-designated nodal centers (NCs) with reduced round trip delays from vaccine production warehouses (VPW). Further, UAVCNs ensure minimizes human intervention and controls vaccine health conditions due to shorter trip times. Once vaccines are supplied at NCs warehouses, then the BC ensures timestamped documentation of vaccinated persons with chronology, auditability, and transparency of supply-chain checkpoints from VPW to NCs. Through smart contracts (SCs), priority groups can be formed for vaccination based on age, healthcare workers, and general commodities. In the simulation, for UAV efficacy, we have compared the scheme against fourth-generation (4G)-assisted long term evolution-advanced (LTE-A), orthogonal frequency division multiplexing (OFDM) channels, and traditional logistics for round-trip time (RTT) latency, logistics, and communication costs. In the BC setup, we have compared the scheme against the existing 5G-TI delivery scheme (Gupta et al.) for processing latency, packet losses, and transaction time. For example, in communication costs, the proposed scheme achieves an average improvement of 9.13 for block meta-information. For 4000 transactions, the proposed scheme has a communication latency of 16s compared to 36s. The packet loss is significantly reduced to 2.5% using 5G-TI compared to 16% in 4G-LTE-A. The proposed scheme has a computation cost of 1.6 ms and a communication cost of 157 bytes, which indicates the proposed scheme efficacy against conventional approaches.

Blockchain Adoption for Trusted Medical Records in Healthcare 4.0 Applications: A Survey

Book Chapter

Book NameProceedings of Second International Conference on Computing, Communications, and Cyber-Security

PublisherSpringer

Author NameUmesh Bodkhe

Page Number759-774

Chapter TitleBlockchain Adoption for Trusted Medical Records in Healthcare 4.0 Applications: A Survey

Published YearMay 2021

ISSN/ISBN No978-981-16-0733-2

Indexed INScopus

Abstract

Healthcare 4.0 allows monitoring of electronic health record (EHR) at distributed locations, through wireless infrastructures like Bluetooth, ZigBee, near-field communication (NFC), and GPRS. Thus, the private EHR data can be tampered by malicious entities that affect updates through different stakeholders like patients, doctors, laboratory technicians, and insurance agencies. Hence, there must be a notion of trust among aforementioned stakeholders. Moreover, the accessed volume of data is humongous; thus, to ensure security and trust, blockchain (BC)-based solutions can handle timestamped volumetric data as chronological ledger. Motivated from the same, the paper presents a systematic survey of BC applications in Healthcare 4.0 ecosystems. The contribution of the paper is to conduct a systematic survey of BC adoption in Healthcare 4.0. The survey identifies tools and technologies to support BC-based healthcare applications and addresses open challenges for future research of integrating BC to secure EHR in Healthcare 4.0 ecosystem.

BaY cP: A novel Bayesian customer Churn prediction scheme for Telecom sector

Conference

Title of PaperBaY cP: A novel Bayesian customer Churn prediction scheme for Telecom sector

Proceeding NameLecture Notes in Networks and Systems

PublisherIEEE

Author NameAshwin Verma

OrganizationNirma University

Year , VenueMay 2021 , UP, India

ISSN/ISBN No978-981-16-0733-2

Indexed INScopus, Web of Science

AnSMart: A SVM-based anomaly detection scheme via system profiling in Smart Grids.

Conference

Title of PaperAnSMart: A SVM-based anomaly detection scheme via system profiling in Smart Grids.

Proceeding Name2021 2nd International Conference on Intelligent Engineering and Management (ICIEM)

PublisherIEEE

Author NameDeepti Saraswat

OrganizationNirma University

Year , VenueApril 2021 , London, UK

Page Number1-1

ISSN/ISBN No978-1-6654-1450-0

Abstract

Anomaly detection techniques analyze consumer spend patterns and grid load profiles to predict possible deviations from normal behavior. However, as the measured data is time-varying, profiling the measured drifts becomes complex owing to the amount of raw generated data. Motivated from the aforementioned discussions, in this paper, we propose a scheme, AnSMart, to predict deviations in smart grid (SG) data through obtained profiling operations. The scheme operates in two phases. In the first phase, valuable grid features are extracted from internal system call lists made by grid kernels after load profiling operations are completed over a day. Then, in the second phase, based on data logs, vector differences are computed for call vectors and malign scenarios are identified. The data is fed to the support vector machine (SVM) model for training, and compromised grid behavior is classified. SVM predicts metrics deviation from normal grids. The deviation is measured depending on parameters like-call vector signal, call-sizes, call-list deviations, and call-return values collected from the open-source libiec61850 library that consists of resource-rich (RR) and resource-limited (RL) libraries for both compromised and uncompromised grids. Based on different cases, a total of 50 experiments were conducted. The obtained F-score is 0.926 and the accuracy of 92.5% is obtained based on system-call stacks and grid operating system (OS) behavior that outperforms the conventional anomaly-based approaches on SG.

DAMS: Dynamic Association for View Materialization based on rule mining scheme

Conference

Title of PaperDAMS: Dynamic Association for View Materialization based on rule mining scheme

Proceeding NameLecture Notes in Electrical Engineering

PublisherSpringer

Author NameAshwin Verma, Pronaya Bhattacharya, Umesh Bodkhe, Akhilesh Ladha, Sudeep Tanwar

OrganizationNirma University

Year , VenueFebruary 2021 , Jammu, India

ISSN/ISBN No978-981-15-8297-4

Indexed INScopus, Web of Science

Bela Shrimali

Neural Network Based Diagnostic Approach for Cervical Cancer Cell Stratification From Pap Smear Images

Conference

Title of PaperNeural Network Based Diagnostic Approach for Cervical Cancer Cell Stratification From Pap Smear Images

PublisherIEEE

Author NameBarkha Bhavsar, Bela Shrimali

Published YearMarch 2024

Indexed INScopus, Web of Science, Others

Fault Detection in Forest Fire Monitoring using Negative Selection Approach

Conference

Title of PaperFault Detection in Forest Fire Monitoring using Negative Selection Approach

PublisherIEEE

Published YearMarch 2024

Indexed INScopus, Others

Meticulous Review: Cutting-Edge Cervix Cancer Stratification Using Image Processing And Machine Learning.

Journal

Journal NameInternational Journal of Computing and Digital Systems

Title of PaperMeticulous Review: Cutting-Edge Cervix Cancer Stratification Using Image Processing And Machine Learning.

PublisherUniversity of Bahrain

Volume Number15.1

Page Number 1343-1358

Published YearMarch 2024

Indexed INScopus, PubMed, Web of Science, Indian citation Index, EBSCO, Others

An Enhanced Diagnosis of Monkeypox Disease Using Deep Learning and a Novel Attention Model Senet on Diversified Dataset

Journal

Journal NameMultimodal Technologies Interaction

Title of PaperAn Enhanced Diagnosis of Monkeypox Disease Using Deep Learning and a Novel Attention Model Senet on Diversified Dataset

PublisherMDPI

Volume Number7

Page Number75

Published YearJuly 2023

ISSN/ISBN No2414-4088

Indexed INScopus, PubMed, Web of Science

Abstract

With the widespread of Monkeypox and increase in the weekly reported number of cases, it is observed that this outbreak continues to put the human beings in risk. The early detection and reporting of this disease will help monitoring and controlling the spread of it and hence, supporting international coordination for the same. For this purpose, the aim of this paper is to classify three diseases viz. Monkeypox, Chikenpox and Measles based on provided image dataset using trained standalone DL models (InceptionV3, EfficientNet, VGG16) and Squeeze and Excitation Network (SENet) Attention model. The first step to implement this approach is to search, collect and aggregate (if require) verified existing dataset(s). To the best of our knowledge, this is the first paper which has proposed the use of SENet based attention models in the classification task of Monkeypox and also targets to aggregate two different datasets from distinct sources in order to improve the performance parameters. The unexplored SENet attention architecture is incorporated with the trunk branch of InceptionV3 (SENet+InceptionV3), EfficientNet (SENet+EfficientNet) and VGG16 (SENet+VGG16) and these architectures improve the accuracy of the Monkeypox classification task significantly. Comprehensive experiments on three datasets depict that the proposed work achieves considerably high results with regard to accuracy, precision, recall and F1-score and hence, improving the overall performance of classification. Thus, the proposed research work is advantageous in enhanced diagnosis and classification of Monkeypox that can be utilized further by healthcare experts and researchers to confront its outspread.

Deep Learning Model based Face Mask Detection for Automated Mandation

Conference

Title of PaperDeep Learning Model based Face Mask Detection for Automated Mandation

PublisherIEEE

Published YearJune 2023

Indexed INScopus

MediBlock: A Blockchain-based Architecture for Secure Healthcare System

Conference

Title of PaperMediBlock: A Blockchain-based Architecture for Secure Healthcare System

PublisherIEEE

Author Name Bela Shrimali , Shivangi Surati, Himani Trivedi

Published YearJune 2023

Blockchain in Supply Chain Management

Book Chapter

PublisherSpringer

Author Name Bela Shrimali , Shivangi Surati, Himani Trivedi, Payal Chaudhari

Chapter TitleBlockchain in Supply Chain Management

Published YearJune 2023

Indexed INScopus, PubMed, Web of Science

Blockchain State-of-the-Art: Architecture, Use Cases, Consensus, Challenges

Journal

Journal NameJournal of King Saud University - Computer and Information Sciences

Title of PaperBlockchain State-of-the-Art: Architecture, Use Cases, Consensus, Challenges

PublisherElsevier

Volume Number34

Page Number6793-6807

Published YearAugust 2021

Indexed INScopus, EBSCO

The Importance of 5G Healthcare Using Blockchain Technologies

Book Chapter

Book Name Blockchain Applications for Healthcare Informatics: Beyond 5G

Author NameBela Shrimali

Chapter TitleThe Importance of 5G Healthcare Using Blockchain Technologies

Published YearJuly 2021

Indexed INScopus, EBSCO

A Fuzzy-based Approach to Evaluate Multi-Objective Optimization for Resource Allocation in Cloud

Journal

Journal NameInternational Journal of Advanced Technology and Engineering Exploration

Title of PaperA Fuzzy-based Approach to Evaluate Multi-Objective Optimization for Resource Allocation in Cloud

Volume Number43

Published YearJanuary 2018

ISSN/ISBN No2394-5443

Indexed INScopus, Others

Multi-Objective Optimization Oriented Policy for Performance and Energy Efficient Resource Allocation In Cloud Environment

Journal

Journal NameJournal of King Saud University - Computer and Information Sciences

Title of PaperMulti-Objective Optimization Oriented Policy for Performance and Energy Efficient Resource Allocation In Cloud Environment

PublisherElsevier

Published YearJanuary 2017

ISSN/ISBN No1319-1578

Indexed INScopus, EBSCO, Others

Comparative Study for Selection of Open Source Hypervisors and Cloud Architectures under Variant Requirements

Journal

Journal NameJournal of Computer Science and Engineering (IJCSE)

Title of PaperComparative Study for Selection of Open Source Hypervisors and Cloud Architectures under Variant Requirements

Published YearMay 2016

ISSN/ISBN NoComparative Study for Selection of Open Source Hypervisors and Cloud Architectures under Variant Requirements

Indexed INOthers

Performance Based Energy Efficient Techniques for VM Allocationin Cloud Environment

Conference

Title of PaperPerformance Based Energy Efficient Techniques for VM Allocationin Cloud Environment

Proceeding NameACM

PublisherACM

Author NameBela Shrimali

Page Number477-486.

Published YearAugust 2015

ISSN/ISBN No 978-1-4503-3361- 0/15/08

Indexed INOthers

Chandan Trivedi

PGASH: Provable group-based authentication scheme for Internet of Healthcare Things

Journal

Journal NamePeer-to-Peer Networking and Applications

Title of PaperPGASH: Provable group-based authentication scheme for Internet of Healthcare Things

PublisherSpringer

Page Number1-20

Published YearJanuary 2024

ISSN/ISBN No1936-6450

Indexed INScopus, Web of Science, Others

Abstract

Electronic healthcare based on medical sensors is now developing to incorporate a significant amount of the Internet of Things (IoT) to communicate between sensors and intended recipients. The key requirements in this domain are to exchange messages safely and to provide confidentiality during communication. Designing and implementing an authentication strategy is essential for resolving security concerns, but it is also challenging to work with constrained computing and processing resources during group communication. Standard one-to-one authentication models do not consider the scalability of resource-limited nodes, which is a vital factor to deal with. However, group authentication presents a unique concept for IoT nodes that verify group members concurrently. The conventional group authentication methods based on the IoT are vulnerable to security risks and cannot defend against attacks like replay attacks, forgery attacks, or unauthorized key distribution by the group manager. In this paper, we propose a dynamic and provable group authentication scheme (GAS) based on a secret sharing scheme that can withstand the dishonest behavior of group managers. We introduced a key updating scenario with a provable group authentication model for dynamic node leaving and joining. Our system complies with the requirements for secrecy and accuracy, and based on security analysis, it is resistant to attacks, as mentioned earlier. Performance analysis and security proof show that our approach performs well in terms of computation cost for group members while maintaining security.

Secrecy aware key management scheme for Internet of Healthcare Things

Journal

Journal NameJournal of Supercomputing

Title of PaperSecrecy aware key management scheme for Internet of Healthcare Things

PublisherSpringer

Volume Number79

Page Number12492–12522

Published YearMarch 2023

Indexed INScopus, Web of Science, Others

A transformative shift toward blockchain-based IoT environments: Consensus, smart contracts, and future directions

Journal

Journal NameSecurity and Privacy

Title of PaperA transformative shift toward blockchain-based IoT environments: Consensus, smart contracts, and future directions

PublisherWiley

Volume Numbere308

Published YearFebruary 2023

Indexed INWeb of Science, Others

Blockchain for Industry 5.0: Vision, Opportunities, Key Enablers, and Future Directions

Journal

Journal NameIEEE Accesss

Title of PaperBlockchain for Industry 5.0: Vision, Opportunities, Key Enablers, and Future Directions

PublisherIEEE

Volume Number10

Page Number69160 - 69199

Published YearJune 2022

ISSN/ISBN No2169-3536

Indexed INScopus, Web of Science

Abstract

Industry 4.0 have witnessed a paradigm shift from cyber-physical systems (CPS) that aims at massive automation, to a more customer-driven approach. The shift has been attributed to the design of hyper-cognitive systems, integration of virtual and extended reality, digital machinery prototyping and twin designs, trusted machine boundaries, collaborative robots, and artificial intelligence (AI)-based supply chains. This new wave, termed Industry 5.0, is expected to leverage massive production with user-centric customization outside the scope of Industry 4.0 ecosystems. Industry 5.0 is expected to assist diverse industrial verticals like healthcare, smart farming, drones, smart grids, and supply chain production ecosystems. However, data is shared among multiple heterogeneous networks, spanning different authoritative domains. Thus, trusted and secured data transfer is crucial to synergize and secure the industrial perimeters. Blockchain (BC) is a preferred choice as a security enabler to Industry 5.0 ecosystems owing to its inherent property of immutability, chronology, and auditability in industrial systems. Limited works are proposed that present the vision and holistic view of BC-assisted Industry 5.0 applications. The article presents a first-of-its-kind survey on BC as a security enabler in Industry 5.0. Based on a descriptive survey methodology and research questions, we presented the key drivers, and potential applications, and propose an architectural vision of BC-based Industry 5.0 in diverse applicative verticals. The survey intends to present solutions that would assist industry practitioners, academicians, and researchers to drive novel BC-assisted solutions in Industry 5.0 verticals.

Blockchain for Information Security and Privacy

Book

PublisherTaylor and Fransis, CRC Press

Published YearDecember 2021

ISSN/ISBN No9781003129486

Indexed INScopus, Others

Blockchain-Based Security and Privacy for Smart Contracts

Book Chapter

Book NameBlockchain for Information Security and Privacy

PublisherTaylor and Fransis, CRC Press

Author NameChandan Trivedi

Chapter TitleBlockchain-Based Security and Privacy for Smart Contracts

Published YearDecember 2021

ISSN/ISBN No9781003129486

Indexed INScopus

Journal

Journal NameInternational Journal of Innovations & Advancement in Computer Science IJIACS

Title of PaperIrregularity Detection in Clinical Data of Patients Encountering Heart Surgery

PublisherAcademic Science

Volume NumberVolume 7, Issue 5

Page Number331-339

Published YearMay 2018

ISSN/ISBN No2347 – 8616

Indexed INUGC List, Others

Abstract

We depict two approaches to manage distinguishing abnormalities in time course of action of multi-parameter clinical data: (1) metric and model-based markers and (2) information astound. (1) Metric and model-based markers are ordinarily used as early advised signs to perceive progresses between substitute states in light of individual time course of action. Here we explore the real nature of existing pointers to perceive fundamental (peculiarities) from non-essential conditions in patients encountering heart surgery, in perspective of a little anonymized clinical trial dataset. We find that a mix of time-fluctuating autoregressive show, kurtosis, and skewness markers successfully perceived fundamental from non-essential patients in 5 out of 36 blood parameters at a window size of 0.3 (ordinary of 37 hours) or higher. (2) Information bewilder measures how the development of one patient's condition fluctuates from that of rest of the people in perspective of the cross-territory of time course of action. With the most outrageous awe and slope features we recognize each and every essential patient at the 0.05 significance level. Moreover we show that a sincere special case acknowledgment does not work, displaying the necessity for the more intricate philosophies examined here. Our preliminary results suggest that future enhancements in early advised systems for persevering condition watching may foresee the start of fundamental advance and allow remedial mediation balancing calm passing. Advance methodology change is relied upon to decline overfitting and deceiving results, and keep an eye on considerable clinical datasets.

Iterative Deconvolution Approach for High Resolution Satellite Imagery

Journal

Journal NameJournal of Geomatics

Title of PaperIterative Deconvolution Approach for High Resolution Satellite Imagery

PublisherIndian Society of Geomatics

Volume Number10

Page Number114-120

Published YearOctober 2016

ISSN/ISBN No2

Indexed INOthers

Daiwat Vyas

DriverSense: A Multi-Modal Framework for Advanced Driver Assistance System

Conference

Title of PaperDriverSense: A Multi-Modal Framework for Advanced Driver Assistance System

Proceeding NameIEEE Explore

PublisherIEEE

Author NameDaiwat Amit Vyas, Manish Chaturvedi

OrganizationIEEE

Year , VenueJanuary 2024 , Bengaluru

Page Number6

ISSN/ISBN No2155-2509

Indexed INScopus

Abstract

Driver distraction, lack of concentration, and increased stress levels are the primary reasons for road accidents. The Advanced Driver Assistance System (ADAS) is used in high-end cars to improve the safety of drivers. These systems use an in-vehicle camera to track the eye movement of a driver and analyze the facial expressions to classify the driver's attention level, mood and/or drowsiness. However, these computer vision-based solutions do not classify the stress and distraction level of a driver which are the major causes of fatality. Further, no ADAS is available to the best of our knowledge for two-wheeler (2W) and three-wheeler (3W) vehicle drivers who represent 80% of the driver population in India. These drivers are exposed to more distractions, stress, and risk due to an open environment. Accordingly, this paper proposes DriverSense, a wearable device based vehicle independent framework for ADAS that uses mobility sensors (e.g., gyroscope, accelerometer, GPS, etc.) and physiological sensors (e.g., EEG, PPG, ECG, SPO2, etc.) to detect aggressiveness and stress level of drivers in real time. The framework employs edge computing to reduce communication delays, and machine learning models for computing inferences related to driver behavior. The results of preliminary experiments conducted using the existing datasets and the data of mobility sensors collected in Ahmedabad city of India are encouraging. The aggressiveness of the drivers could be classified with 86.05% accuracy, whereas the stress level was identified with 88.24% accuracy using existing machine learning algorithms.

Security Analysis of Multi-factor Authentication with Legitimate Key Exchange for Vehicle to Vehicle Communication

Book Chapter

Book NameInternational Conference on ICT for Sustainable Development

PublisherIEEE

Author NameVipul Chudasama, Daiwat Amit Vyas, Devendra Vashi

Page Number10

Chapter TitleSecurity Analysis of Multi-factor Authentication with Legitimate Key Exchange for Vehicle to Vehicle Communication

Published YearNovember 2023

ISSN/ISBN No978-981-99-5651-7

Indexed INScopus, Others

Abstract

Internet of Vehicles (IOV) in which the vehicles share information like traffic, road safety, location sharing, toll payment, road accident, etc. with each other wirelessly. Vehicle Ad-hoc Network (VANET) includes reliable data transmission on a network, frequently changing topology, mobility of vehicles, and security of each component where vehicles can communicate securely and effectively. However, the existing framework has some security issues for which the security properties like nonce and multi-factor authentication needs to consider. At last, we suggest that our framework is more secure and efficient for V2V communication.

Swine Flu Predication Using Machine Learning

PublisherCS Journal

Volume Number7

Page Number186-197

Published YearSeptember 2015

ISSN/ISBN No09737391

Indexed INOthers

Abstract

IoT (Internet of Things) one of the most exiting trends and innovation in the recent history of technological advancement. Also the advances in computer hardware, embedded system devices, networking devices, display devices, control devices, software enhancements etc. has tremendously supported IoT to grow slowly and steadily from leaps to bounds. With computation, connectivity, and data storage becoming more advanced and universal there has been an explosion of IoT based application solutions in diversified domains from health care to public safety, from assembly line scheduling to manufacturing and various other technological domains. IoT can be defined as a network of physical objects, devices that contain embedded technology (like intelligent sensors, controllers etc.) whichcan communicate, sense, or interact with internal or external systems. In other words, when objects can sense and communicate, it changes how and where decisions are made, and who makes them and accordingly operations can be carried out.In this survey a conscious effort has been put forward to investigate the state of the art involved in IoT and its various diversified engineering applications.Latest trends & evolution,challenges, and future scope of this technology have been touched upon for better understanding.Various IoT based applications have been explored and possible approach for enhancing the use of this technology have been discussed in this paper.Future directions and suggestions for effectively and efficiently improving the IoT based application areas have been touched upon. This paper will provide a better insight for anyone who wishes to carry out research in the field of IoT.In this paper we have tried to provide a holistic perspective on IoT and IoT based applications, application areas, research challenges in IoT, trends and future possibilities in IoT

Focused Web Crawler

Conference

Title of PaperFocused Web Crawler

Proceeding NameAdvances in Soft-computing, E-Learning, Information & Communication Technology

PublisherKrishi Sanskriti Publications

Author NameDvijesh Bhatt, Daiwat Amit Vyas, Sharnil Pandya

OrganizationAdvances in Soft-computing, E-Learning, Information & Communication Technology

Year , VenueMarch 2015 , Delhi

Page Number18

ISSN/ISBN No2393-9907

Indexed INOthers

Deepika Shukla

Recognition of Fruits Using Hybrid Features and Machine Learning

Conference

Title of PaperRecognition of Fruits Using Hybrid Features and Machine Learning

Proceeding NameIEEE International Conference on Computing, Analytics and Security Trends

PublisherIEEE

Year , VenueDecember 2016 , College of Engineering , Pune

Page Number572-577

ISSN/ISBN No978-1-5090-1338-8

Empirical Performance Comparison of OODBMS over RDBMS

Journal

Journal NameIJCSC

Title of PaperEmpirical Performance Comparison of OODBMS over RDBMS

Volume Number7

Page Number83-88

Published YearMarch 2016

ISSN/ISBN No0973-7391

Indexed INOthers

Review on Generic Object Recognition Techniques : Challenges and Opportunities

Journal

Journal NameIJARET

Title of PaperReview on Generic Object Recognition Techniques : Challenges and Opportunities

Volume Number6

Page Number104-133

Published YearDecember 2015

ISSN/ISBN No0976-6480

Indexed INUGC List

Analyzing the Comprehensibility of Aspect-Oriented Modelling and Design of Software System

Journal

Journal NameInternational Journal of Computer Application

Title of PaperAnalyzing the Comprehensibility of Aspect-Oriented Modelling and Design of Software System

Volume Number95

Page Number7-11

Published YearJune 2014

ISSN/ISBN No0975 - 8887

Indexed INEBSCO

An Efficient Approach for Job Scheduling in Cloud Computing

Journal

Journal NameInternational Journal of Computer Science Engineering and Information Technology Research (IJCSEITR)

Title of PaperAn Efficient Approach for Job Scheduling in Cloud Computing

PublisherTRANSSTELLAR

Volume Number4-4

Page Number9-14

Published YearAugust 2014

ISSN/ISBN No2249-7943

Indexed INOthers

Analyzing Large-Scaled Applications in Cloud Computing Environment

Journal

Journal NameInternational Journal of Computer Science Engineering and Information Technology Research (IJCSEITR)

Title of PaperAnalyzing Large-Scaled Applications in Cloud Computing Environment

PublisherTRANSSTELLAR

Volume Number4-4

Page Number1-8

Published YearAugust 2014

ISSN/ISBN No2249-7943

Indexed INOthers

Devendrasinh Vashi

An Efficient Hybrid Approach of Attribute Based Encryption for Privacy Preserving Through Horizontally Partitioned Data

Journal

Journal NameProcedia Computer Science

Title of PaperAn Efficient Hybrid Approach of Attribute Based Encryption for Privacy Preserving Through Horizontally Partitioned Data

PublisherElsevier

Volume Number167

Page Number2437–2444

Published YearMarch 2020

ISSN/ISBN No18770509

Indexed INScopus

Performance of Symmetric and Asymmetric Encryption Techniques for Attribute Based Encryption

Journal

Journal NameInternational Journal of Recent Technology and Engineering

Title of PaperPerformance of Symmetric and Asymmetric Encryption Techniques for Attribute Based Encryption

PublisherBlue Eyes Intelligence Engineering & Sciences Publication

Volume Number8

Page Number176-182

Published YearNovember 2019

ISSN/ISBN No2277-3878

Indexed INOthers

Implementation of Attribute based Symmetric Encryption through Vertically Partitioned Data in PPDM

Journal

Journal NameInternational Journal of Engineering and Advanced Technology

Title of PaperImplementation of Attribute based Symmetric Encryption through Vertically Partitioned Data in PPDM

PublisherBlue Eyes Intelligence Engineering & Sciences Publication

Volume Number8

Page Number5384-5390

Published YearAugust 2019

ISSN/ISBN No2249 – 8958

Indexed INScopus

Critical study and analysis for deciding sensitive and non-sensitive attributes of medical healthcare dataset through survey and using association rule mining

Journal

Journal NameInternational Journal of Recent Scientific Research

Title of PaperCritical study and analysis for deciding sensitive and non-sensitive attributes of medical healthcare dataset through survey and using association rule mining

Volume Number8

Page Number17218-17222

Published YearMay 2017

ISSN/ISBN No0976-3031

Indexed INUGC List

Challenges & Opportunities in Privacy Preserving Data Mining for Healthcare Dataset

Conference

Title of PaperChallenges & Opportunities in Privacy Preserving Data Mining for Healthcare Dataset

Proceeding NameICRISET-2017

Author NameDevendra Vashi

OrganizationBirla Vishvakarma Mahavidyalaya Engineering College, VV Nagar

Year , VenueFebruary 2017 , BVM, VV Nagar

Page Number133

ISSN/ISBN No978-93-84339-38-8

Indexed INOthers

Abstract

Now a day’s medical organization, health care Centres, insurance companies are very much interested to do analysis for various diseases. Their objective is to make aware the societies about diseases causes and patterns. Also, insurance companies may introduce medical health care policies as per the analysis of medical data. One of the problems faced during such data mining is that personal or sensitive data is exposed to the public which most of the people may not like. Hence one of the requirements of data extraction during data mining is to preserve the privacy of sensitive/personal data. This is possible using various Privacy Preserving Data Mining (PPDM) techniques. This paper reviews and compares the different PPDM techniques with data mining methods and privacy analysis. Paper also discusses the challenges faced and its solutions during PPDM.

OPTIMAL LECTURE PLANNING FOR TEACHING THE SUBJECT USING AGILE METHODOLOGY

Journal

Journal NameInternational Journal of Advanced Research in Engineering and Technology

Title of PaperOPTIMAL LECTURE PLANNING FOR TEACHING THE SUBJECT USING AGILE METHODOLOGY

Publisher IAEME

Volume Number7

Page Number64–68

Published YearMarch 2016

ISSN/ISBN No0976-6499

Comparative stud of some cryptographic algorithms

Conference

Title of PaperComparative stud of some cryptographic algorithms

Author NameDevendra Vashi

OrganizationSN Patel Institute Of Technology & Research Centre

Year , VenueApril 2015 , SN Patel Institute Of Technology & Research Centre, Bardoli

ISSN/ISBN No978-81-929339-1-7

Indexed INOthers

Abstract

in privacy-preserving data mining technique, the cryptographic process is good to implement properly for making data private while sending data to the third party. This paper is just a study of some of the encryption and decryption technique like DES, RSA and hash function which can be implemented for cryptography. This paper is also emphasized on a comparative study on different encryption technique and how is useful in the cryptographic technique

Gaurang Raval

Detection of traffic rule violation in University campus using deep learning model

Journal

Journal NameInternational Journal of System Assurance Engineering and Management

Title of PaperDetection of traffic rule violation in University campus using deep learning model

PublisherSpringer India

Volume Number14 (6)

Page Number2527-2545

Published YearDecember 2023

ISSN/ISBN No0975-6809

Indexed INScopus, Web of Science

Regenerating vital facial keypoints for impostor identification from disguised images using CNN

Journal

Journal NameExpert Systems with Applications

Title of PaperRegenerating vital facial keypoints for impostor identification from disguised images using CNN

PublisherElsevier B.V.

Volume Number219

Page Number119669

Published YearFebruary 2023

ISSN/ISBN No0957-4174

Indexed INScopus, Web of Science

Journal

Journal NameInternational Journal of Applied Research on Information Technology and Computing

Title of PaperSurvey on Security Provisions in Named Data Networking

PublisherIndianJournals

Volume Number10

Page Number20-26

Published YearMay 2019

ISSN/ISBN No 22493212

Indexed INIndian citation Index

Multi-Objective Optimization Based Clustering in Wireless Sensor Networks Using Harmony Search Algorithm

Journal

Journal NameJournal of Communication Engineering and Systems

Title of PaperMulti-Objective Optimization Based Clustering in Wireless Sensor Networks Using Harmony Search Algorithm

Publisheri-Managers Journal Publications

Volume Number7

Page Number1-12

Published YearAugust 2018

Indexed INIndian citation Index

Natural Language Interface for Multilingual Database

Conference

Title of PaperNatural Language Interface for Multilingual Database

PublisherInternational Conference on Information and Communication Technology for Intelligent Systems (ICTIS)

OrganizationSpringer

Page Number113-120

Published YearAugust 2017

ISSN/ISBN No978-3-319-63644-3

Open Issues in Named Data Networking – A Survey

Book Chapter

Book Name Smart Innovation, Systems and Technologies (SIST, volume 83)

PublisherSpringer, Cham

Page Number 285-292

Chapter TitleOpen Issues in Named Data Networking – A Survey

Published YearAugust 2017

ISSN/ISBN No978-3-319-63673-3

Abstract

Internet is now being used as content distribution network also. Internet users are interested in specific contents rather than host machines where the content is located. Named Data Networking (NDN) is a step towards future Internet architecture that would be based on named data rather than numerically identified hosts. Many projects are in progress to architect the structure of the Internet.

Open Issues in Named Data Networking-A Survey

Conference

Title of PaperOpen Issues in Named Data Networking-A Survey

PublisherSpringer

Year , VenueJanuary 2017 , Ahmedabad , India

Page Number285-292

ISSN/ISBN No978-3-319-63672-6

Securing Application Layer Protocol for IOT

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of Paper Securing Application Layer Protocol for IOT

PublisherIJCSC

Volume Number7

Page Number42-48

Published YearSeptember 2016

Enhancing data delivery with density controlled clustering in wireless sensor networks

Journal

Journal NameMicrosystem Technologies

Title of PaperEnhancing data delivery with density controlled clustering in wireless sensor networks

PublisherSpringer

Volume Number23 (3)

Page Number613-631

Published YearMay 2016

ISSN/ISBN No1432-1858

Optimization of clustering process in WSN with meta-heuristic techniques - a survey

Conference

Title of PaperOptimization of clustering process in WSN with meta-heuristic techniques - a survey

PublisherIEEE

Year , VenueMarch 2016 , 2016 3rd International Conference on Recent Advances in Information Technology (RAIT)

ISSN/ISBN No978-1-4799-8579-1

Analyzing the Performance of Centralized Clustering Techniques for Realistic Wireless Sensor Network Topologies

Conference

Title of PaperAnalyzing the Performance of Centralized Clustering Techniques for Realistic Wireless Sensor Network Topologies

Proceeding NameProcedia Computer Science

PublisherElsevier

Author NameGaurang Raval, Madhuri Bhavsar, Nitin Patel

OrganizationAmity University, Noida

Year , VenueDecember 2015 , Amity University, Noida

Page Number1026-1035

ISSN/ISBN No18770509

Indexed INScopus

Improving Energy Estimation based Clustering with Energy Threshold for Wireless Sensor Networks

Journal

Journal NameInternational Journal of Computer Applications

Title of PaperImproving Energy Estimation based Clustering with Energy Threshold for Wireless Sensor Networks

PublisherIJCA

Volume Number113 (19)

Page Number41-47

Published YearMarch 2015

Improving Data Delivery with Density Control based Clustering in Wireless Sensor Networks

Conference

Title of PaperImproving Data Delivery with Density Control based Clustering in Wireless Sensor Networks

Year , VenueDecember 2014 , At Puri, Odisha, India

ISSN/ISBN No81-85824-46-0

Performance Comparison of Various Clustering Techniques in Wireless Sensor Networks

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of Paper Performance Comparison of Various Clustering Techniques in Wireless Sensor Networks

PublisherIJCSC

Volume Number5

Page Number116-223

Published YearJuly 2014

3-D Localization in Wireless Sensor Networks

Journal

Journal NameInternational Journal of Computer Engineering and Technology (IJCET)

Title of Paper3-D Localization in Wireless Sensor Networks

PublisherIJCET

Volume NumberVolume 5, Issue 3, March 2014, pp. 09-22

Published YearMarch 2014

ISSN/ISBN NoISSN 0976 – 6367(Print) ISSN 0976 – 6375(Online)

Optimization of Clustering Techniques Using Energy Thresholds in Wireless Sensor Networks

Journal

Journal NameInternational Journal of Advanced Research in Engineering and Technology (IJARET)

Title of PaperOptimization of Clustering Techniques Using Energy Thresholds in Wireless Sensor Networks

PublisherIJARET

Volume Number4, Issue 7

Published YearJanuary 2014

ISSN/ISBN NoISSN 0976 - 6480 (Print) ISSN 0976 - 6499 (Online)

Optimization of Collection Tree Protocol

Journal

Journal NameInternational Journal of Advanced Research in Computer Science

Title of PaperOptimization of Collection Tree Protocol

Volume Number4,Issue 8

Published YearJanuary 2013

Optimization of Hierarchical Routing Protocol for Wireless Sensor Networks with Identical Clustering

Conference

Abstract

The primary use of wireless sensor networks (WSNs) is to collect and process data. Most of the energy consumption is due to data transmission. Because of the unique properties of WSNs all raw data samples are not directly sent to the sink node instead data aggregation is preferred. Since sensor nodes are deployed in an open environment such as a battlefield or similar applications

Survey on Energy Efficient Hierarchical Routing Algorithms in Wireless Sensor Networks – A Survey

Conference

Title of PaperSurvey on Energy Efficient Hierarchical Routing Algorithms in Wireless Sensor Networks – A Survey

Proceeding NameProceedings of National Conference, NUCONE

PublisherNUCONE

Published YearJanuary 2009

Analyzing the Performance of Centralized Clustering Techniques for Realistic Wireless Sensor Network Topologies

Conference

Title of PaperAnalyzing the Performance of Centralized Clustering Techniques for Realistic Wireless Sensor Network Topologies

PublisherElsevier

Year , VenueAugust 201 , 3rd International Conference on Recent Trends in Computing 2015 (ICRTC-2015)

ISSN/ISBN No1026 – 1035

Jai Prakash Verma

Analysis of Quantum Computing with Food Processing Use Case

Book Chapter

Book NameCyber Security Using Modern Technologies: Artificial Intelligence, Blockchain and Quantum Cryptography

PublisherCRC Press

Author NameDhaval S Jha, Het Shah, Jai Prakash Verma

Page Number47

Chapter TitleAnalysis of Quantum Computing with Food Processing Use Case

Published YearAugust 2023

ISSN/ISBN No9781000908022

Indexed INScopus

Abstract

Quantum computing has undoubtedly pushed the frontiers of a maximum achievable computational speed. By harnessing the laws of “quantum mechanics,” a quantum computer can easily outperform a conventional computer or a supercomputer [1]. Many problems that are perceived to be unsolvable can be efficiently handled by a quantum computer. A quantum computer can provide solutions to many intractable problems, within reasonable time bounds [2]. Although quantum computing technology is quite fascinating, there are many issues and challenges that need to be addressed. There are many problems that cannot be solved by conventional computers or even by modern-day supercomputers. The computational speed required for solving such problems is quite high, and so all present-day computing machines are overwhelmed by the complexity of such problems. Quantum computing provides the solution for solving such types of problems. Quantum computing is based on the concepts of Quantum Superposition and Quantum Entanglement. A quantum computer is capable of solving highly computationally intensive problems very quickly [3]. Conventional computers process the information stored in the form of bits, whereas a quantum computer uses the concept of quantum bits (qubits). Qubits allow the states to be not only 0 or 1, but also any combination of 0 and 1. This allows a quantum computer to process more information at any given instance of time. Problems, which traditionally take exponential time to solve on a conventional computer or a supercomputer, can be solved by a quantum computer in polynomial.

Conference

Title of PaperAI based Classification for Autism Spectrum Disorder Detection using Video Analysis

Proceeding Name2022 IEEE Bombay Section Signature Conference (IBSSC)

PublisherIEEE

Page Number1-6

Published YearFebruary 2023

Indexed INScopus, Web of Science

Classifying Malignant and Benign Tumors of Breast Cancer: A Comparative Investigation Using Machine Learning Techniques

Journal

Journal NameInternational Journal of Reliable and Quality E-Healthcare (IJRQEH)

Title of PaperClassifying Malignant and Benign Tumors of Breast Cancer: A Comparative Investigation Using Machine Learning Techniques

PublisherIGI GLOBAL

Volume Number12

Page Number1-19

Published YearFebruary 2023

Indexed INScopus

Machine Learning-Based Investigation of Employee Attrition Prediction and Analysis

Book Chapter

Book NameEmerging Technology Trends in Electronics, Communication and Networking

PublisherSpringer, Singapore

Author NameJai Prakash Verma

Page Number221-238

Chapter TitleMachine Learning-Based Investigation of Employee Attrition Prediction and Analysis

Published YearDecember 2022

Indexed INScopus

Abstract Data Models and System Design for Big Data Geospatial Analytics

Book Chapter

Book NameEmerging Technology Trends in Electronics, Communication and Networking

PublisherSpringer, Singapore

Author NameJai Prakash Verma

Page Number177-193

Chapter TitleAbstract Data Models and System Design for Big Data Geospatial Analytics

Published YearDecember 2022

Indexed INScopus

Mobility prediction for uneven distribution of bikes in bike sharing systems

Journal

Journal NameConcurrency and Computation: Practice and Experience

Title of PaperMobility prediction for uneven distribution of bikes in bike sharing systems

PublisherWiley Online Library

Published YearNovember 2022

ISSN/ISBN No1532-0626

Indexed INScopus, Web of Science

A New Approach for Processing Raster Geospatial Big Data in Distributed Environment

Book Chapter

Book NameAdvances in Distributed Computing and Machine Learning

PublisherSpringer, Singapore

Author NameJai Prakash Verma

Page Number83-93

Chapter TitleA New Approach for Processing Raster Geospatial Big Data in Distributed Environment

Published YearJuly 2022

Indexed INScopus

Parameter optimization for surface mounter using a self-alignment prediction model

Journal

Journal NameSoldering & Surface Mount Technology

Title of PaperParameter optimization for surface mounter using a self-alignment prediction model

PublisherEmerald Publishing Limited

Volume Number1

Page Number1

Published YearJuly 2022

ISSN/ISBN No0954-0911

Indexed INScopus, Web of Science

Abstract

Abstract Purpose The purpose of this paper is to develop a machine learning model that predicts the component self-alignment offsets along the length and width of the component and in the angular direction. To find the best performing model, various algorithms like random forest regressor (RFR), support vector regressor (SVR), neural networks (NN), gradient boost (GB) and K-nearest neighbors (KNN) were performed and analyzed. The models were implemented using input features, which can be categorized as solder paste volume, paste-pad offset, component-pad offset, angular offset and orientation. Design/methodology/approach Surface-mount technology (SMT) is the technology behind the production of printed circuit boards, which is used in several types of commercial equipment such as communication devices, home appliances, medical imaging systems and sensors. In SMT, components undergo movement known as self-alignment during the reflow process. Although self-alignment is used to decrease the misalignment, it may not work for smaller size chipsets. If the solder paste depositions are not well-aligned, the self-alignment might deteriorate the final alignment of the component. Findings It were trained on their targets. Results obtained by each method for each target variable were compared to find the algorithm that gives the best performance. It was found that RFR gives the best performance in case of predicting offsets along the length and width of the component, whereas SVR does so in case of predicting offsets in the angular direction. The scope of this study can be extended to developing this model further to predict defects that can occur during the reflow process. It could also be developed to be used for optimizing the placement process in SMT. Originality/value This paper proposes a predictive model that predicts the component self-alignment offsets along the length and width of component and in the angular direction. To find the best performing model, various algorithms like RFR, SVR, NN, GB and KNN were performed and analyzed for predicting the component self-alignment offsets. This helps to achieve the following research objectives: best machine learning model for prediction of component self-alignment offsets. This model can be used to optimize the mounting process in SMT, which reduces occurrences of defects and making the process more efficient.

Collaborative Filtering-Based Music Recommendation in View of Negative Feedback System

Book Chapter

Book Chapter

Book NameEnergy Conservation Solutions for Fog-Edge Computing Paradigms

PublisherSpringer, Singapore

Author NameNaishadh Mehta, Anand Ruparelia, Jai Prakash Verma

Page Number191-213

Chapter TitleFog Computing Based Architecture for Smart City Projects and Applications

Published YearSeptember 2021

ISSN/ISBN No978-981-16-3448-2

Indexed INScopus

Abstract

Shortest Pathfinder for Air Traffic Network: A Graph-Based Analysis

Conference

Title of PaperShortest Pathfinder for Air Traffic Network: A Graph-Based Analysis

Proceeding NameProceedings of the International e-Conference on Intelligent Systems and Signal Processing

PublisherSpringer, Singapore

Author NamePiyushi Jain, Drashti Patel, Jai Prakash Verma

OrganizationGCET, Anand, Gujarat

Year , VenueAugust 2021 , GCET, Anand, Gujarat

Page Number699-712

ISSN/ISBN No978-981-16-2123-9

Indexed INScopus

Abstract

Air Traffic Management is the dynamic, integrated management of air traffic. There has been a dramatic increase in people who are preferring airways over the traditional transportation system as it saves time. The growth will generate countless new routes and require hundreds of new airports and thousands of new planes and pilots. Most of the traffic management is done throughout the flight to help the pilot with ongoing traffic above there. Due to this rapid growth of passengers and the increasing environmental concerns, there is a need to find the shortest and efficient path for any flight considering distance and time. Using graph theory’s Dijkstra algorithm, the shortest point between a source and a distance could be calculated. The shortest path based on parameters including distance and time has been implemented with Neo4j and Apache Spark and hence a comparative study between the two software has also been done. The model was trained using a dataset of air routes of Oceania and was able to predict the best route in terms of distance and time separately. Neo4j provides visual results in the form of a graph while spark provides the shortest distance and route followed in the path. An optimal path that is derived using the shortest distance on the cost of time or vice versa is not only the findings of the system. An equation could be derived that would balance both distance and time. That equation can also be extended to take care of parameters like traffic, weather conditions, and country borders or restricted areas.

Leveraging Deep Learning Techniques on Remotely Sensing Agriculture Data

Book Chapter

Book NameCommunication and Intelligent Systems

PublisherSpringer

Author NameAjaysinh Vikramsinh Kathiya, Jai Prakash Verma, Sanjay Garg

Page Number955-965

Chapter TitleLeveraging Deep Learning Techniques on Remotely Sensing Agriculture Data

Published YearJune 2021

ISSN/ISBN No978-981-15-3325-9

Indexed INScopus

Abstract

Crop yield prediction is very beneficial for the farmers to predict their profit. It can be used by private firms to make business decisions and governments to plan food security as well as planning imports and exports. Several published state-of-the-art techniques rely on handcrafted data. Our model deals with remotely sensed data to predict crop yield using deep learning algorithms such as CNN and LSTM. This model has proved better than existing techniques on evaluation based on its RMSE value. We have leveraged the capabilities of both algorithms to increase the accuracy of crop yield prediction and have successfully closed upon a model that surpassed the accuracy of previously used approaches.

A deep learning based approach for trajectory estimation using geographically clustered data

Journal

Journal NameSN Applied Sciences

Title of PaperA deep learning based approach for trajectory estimation using geographically clustered data

PublisherSpringer Nature

Volume Number3

Page Number1-17

Published YearJune 2021

ISSN/ISBN No2523-3971

Indexed INScopus, Web of Science

Abstract

Computer-Aided-Diagnosis System for Symptom Detection of Breast and Cervical Cancer

Book Chapter

Book Name Lecture Notes in Networks and Systems

PublisherSpringer

Author NamePiyushi Jain, Drashti Patel, Jai Prakash Verma, Sudeep Tanwar

Page Number743-758

Chapter TitleComputer-Aided-Diagnosis System for Symptom Detection of Breast and Cervical Cancer

Published YearMay 2021

ISSN/ISBN No23673370, 23673389

Indexed INScopus

Abstract

As witnessed,’ Cancer metastasis is the leading cause of death worldwide, lots of efforts done for understanding the pathology of cancer for prognosis and diagnosis. Cancer treatment at an early stage can increase the chances of survival of the sufferer considerably. This research aims to contribute to the detection of breast and cervical cancer in the early stages. A comparative study of classification techniques includes Support Vector Classifier (SVC), Multi-layer Perceptron (MLP), and Random Forest (RF) has done to identify the best model for cancer prediction. These models are differentiated for different symptoms collected from electronic health care data. A correlation matrix with a heat map is used for symptoms/feature selection from the results of biopsy examinations applied on a dataset collected from the UCI repository. The predictive model based on Random forest techniques achieves the highest …

Improvised VGG16 CNN Architecture for Predicting Tuberculosis Using the Frontal Chest X-Ray Images

Conference

Title of PaperImprovised VGG16 CNN Architecture for Predicting Tuberculosis Using the Frontal Chest X-Ray Images

Proceeding NameSmart Systems: Innovations in Computing

PublisherSpringer, Singapore

Author NameJai Prakash Verma

OrganizationSSIC 2021, Manipal University, Jaipur, India

Year , VenueJanuary 2021 , SSIC 2021, held in Manipal University, Jaipur, India

Page Number69-80

ISSN/ISBN No978-981-16-2877-1

Indexed INScopus

Predictive Analysis for User Mobility Using Geospatial Data

Book Chapter

Book NameRecent Innovations in Computing

PublisherSpringer Singapore

Author NameJai Prakash Verma, Sudeep Tanwar, Archies Desai, Poojan Khatri, Zdzislaw Polkowski

Page Number845-857

Chapter TitlePredictive Analysis for User Mobility Using Geospatial Data

Published YearJanuary 2021

ISSN/ISBN No1876-1100

Indexed INScopus

Abstract

Extremely usage of smart wearable devices such as smartphones and smartwatches which contain various sensors for location detection such as Wi-Fi, LTE, GPS and motion detection such as accelerometer, it has become easier to obtain user mobility data. Today communication systems are becoming more popular due to the developments in communication technologies. There are various services provided which also help to access the data such as video, audio, images from which we can be used to grab the information or pattern of user mobility. The user mobility where user’s movements and locations can be predicted using various methods and algorithms. It can be predicted through data mining, machine learning, and deep learning algorithms where user’s data are fetched from the communication system. A comparative data mining model base on DBSCAN and RNN-LSTM was proposed for …

Predictive Analysis for User Mobility Using Geospatial Data

Book Chapter

Book NameRecent Innovations in Computing

PublisherSpringer, Singapore

Author NameJai Prakash Verma, Sudeep Tanwar, Archies Desai, Poojan Khatri, Zdzislaw Polkowski

Page Number845-857

Chapter TitlePredictive Analysis for User Mobility Using Geospatial Data

Published YearJanuary 2021

ISSN/ISBN No18761119, 18761100

Indexed INScopus, Web of Science

Abstract

Blockchain Based Framework for Document Authentication and Management of Daily Business Records

Book Chapter

Book NameBlockchain for 5G-Enabled IoT

PublisherSpringer

Author NamePrakrut Chauhan, Jai Prakash Verma, Swati Jain, Rohit Rai

Page Number497-517

Chapter TitleBlockchain Based Framework for Document Authentication and Management of Daily Business Records

Published YearDecember 2020

ISSN/ISBN No978-3-030-67490-8

Indexed INScopus

Event-Triggered Share Price Prediction

Book Chapter

Book NameEvolving Technologies for Computing, Communication and Smart World

PublisherLecture Notes in Electrical Engineering

Author NameJay Pareshkumar Patel, Nikunj Dilipkumar Gondha, Jai Prakash Verma, Zdzislaw Polkowski

Page Number83-96

Chapter TitleEvent-Triggered Share Price Prediction

Published YearNovember 2020

ISSN/ISBN No18761119, 18761100

Indexed INScopus, Web of Science

Abstract

The stock market price analysis or the prediction of the stock prices has always been a classical problem because of the fluctuating prices of the stocks for a particular company based on the economy. This stock market price analysis/prediction problem has attracted researchers from various fields like statistics, machine learning (ML), deep learning (DL), etc. The analysis or prediction of the stock prices will help the individuals/customers to buy/sell shares of a particular company in order to incur profit. The aim of the proposed paper is to accurately predict the future prices of shares of a company. The prediction on prices can be done through various techniques or methods of machine learning and deep learning. In this paper, we are proposing a hybrid approach of deep learning neural network long short-term memory (LSTM) with sentiment analysis to predict the variations in share prices. First, we apply sentiment analysis on the various company news, market sentiments and get the values. Then, the sentiment results are combined with the LSTM features and observed the results. We predicted the variations in the prices of the stocks for one day and for 30 days long-time period. The observation that we got is very helpful to get the idea of a particular company’s future variations in share prices.

Conference

Title of PaperData Consumption-Aware Load Forecasting Scheme for Smart Grid Systems

Proceeding Name2018 IEEE Globecom Workshops (GC Wkshps),

PublisherIEEE Globecom

Author NameJai Prakash Verma

Organization2018 IEEE Globecom Workshops (GC Wkshps), Abu Dhabi, United Arab Emirates, United Arab Emirates

Year , VenueDecember 2018 , Abu Dhabi, United Arab Emirates, United Arab Emirates

Page Number1-6

ISSN/ISBN NoISBN: 978-1-5386-4920-6 , ISBN: 978-1-5386-6977-8

Indexed INScopus

Abstract

With the realisation of the Smart Grids (SG) infrastructure at a large scale, demand predictions can be mapped more accurately. Systems base forecasts on user consumption patterns have mined from old feedback systems to modern extensive sensor based network technologies. Therefore, to derive the usage functions, it is essential to perceive such conditions. These directly impact the power needs and the lifestyle of the consumers, and hence, aid in understanding the user behavior and correspondingly manage power generation. This study propounds mean weather conditions as pivotal to determining power usage. Employing a time based data driven approach, this research functions to predict load expectation in various utilization sectors. Repositioning the adoption of climatic conditions from absolute to relative, the investigation establishes the dependence of collective load prediction on the general weather. The simulation results prove that the time dependent load forecasting model accurately predicts the energy demand of residential and commercial sector.

A Range-Based Approach for Long-Term Forecast of Weather Using Probabilistic Markov Model

Conference

Title of PaperA Range-Based Approach for Long-Term Forecast of Weather Using Probabilistic Markov Model

Proceeding Name 2018 IEEE International Conference on Communications Workshops (ICC Workshops)

Publisher 2018 IEEE International Conference on Communications Workshops (ICC Workshops)

Author NameJai Prakash Verma

Organization 2018 IEEE International Conference on Communications Workshops (ICC Workshops)

Year , VenueMay 2018 , Kansas City, MO, USA

Page Number1-6

ISSN/ISBN No2474-9133

Indexed INScopus

Abstract

Weather forecasts serve to incline individual behaviors and interactions, commercial intentions and organizational efforts. A normal user is usually indifferent to weather statistics and corresponding value predictions but obtains an approximate idea from the average weather conditions. Forecasts justifying overall conditions for a duration which is usually rely on previous observations. Correspondingly, they extend the probability of inducing incorrect predictions as relatively insignificant variations consequently compound to substantial errors. As such, long term predictions are usually limited and unreliable. This paper aims to bridge this gap, by adopting a range specific approach to a probabilistic markov model (PMM). To develop a certainty in availability, we employ a cloud server to house for the analytics. We have achieved a considerable rise in accuracy in the results, along with a simplistic convenience for the user as compared to other available state-of- the-art methods.

Evaluation of Unsupervised Learning based Extractive Text Summarization Technique for Large Scale Review and Feedback Data

Journal

Big Data analytics helps the enterprises and institutions to understand and identify the usability of large amount of data generated by their routine operations. All most third forth part of these types of data is semi-structured text data. Many types of actionable insights can be found from these type of semistructured text data that can help strategic management for making right decision. In this paper we are proposing a recommendation system model for understanding and finding actionable insight from the large amount of text data generated for an educational institution. Here we are discussing different type of data generation sources of this types of data as well as data cleaning processes required. The wordcloud for an educational institution is published that help strategic management for understanding the sentiment of different stack holders mainly students. Herewith we are identifying different types of findings from these sets of words that helps for betterment in the functionaries of an Educational Institution.

Big data analysis: recommendation system with Hadoop framework

Conference

Book Chapter

Book NameFederated Learning for Internet of Medical Things

Publishertaylor and Farncis

Author NameJigna Patel, Jitali Patel, Rupal Kapdi, Shital Patel

Page Number855-864(10)

Chapter TitleEarly Prediction of Prevalent Diseases Using IoMT

Published YearMay 2023

ISSN/ISBN No9781003303374

Indexed INScopus, Web of Science

Abstract

Brain Tumor Segmentation Using Fully Convolution Neural Network

Conference

Title of PaperBrain Tumor Segmentation Using Fully Convolution Neural Network

Proceeding NameInternational Conference on Recent Innovations in Computing: ICRIC 2022, Volume 1

PublisherSpringer Nature Singapore

Author NameRupal A Kapdi, Jigna A Patel, Jitali Patel

Year , VenueMay 2023 , Jammu,India

Page Number3-15

ISSN/ISBN No1876-1119

Indexed INScopus

Abstract

Early stage brain tumor diagnosis can lead to proper treatment planning, which improves patient survival chances. A human expert advises an appropriate medical imaging scan based on the symptoms. Diagnosis done by a human expert is time-consuming, non-reproducible, and highly dependent on the expert’s expertise. The computerized analysis is preferred to help experts in diagnosis. The paper focuses on implementing a fully convolution neural network to segment brain tumor from MRI images. The proposed network achieves comparable dice similarity with reduced network parameters.

COVID Detection from Chest X-Ray Images Using Deep Learning

Conference

Conference

Title of PaperIndexing On Healthcare Big Data

Proceeding NameInternational Conference on Soft Computing for Problem Solving - SocProS 2020

PublisherSpringer

Author NameDr Jigna Patel,Aneri Mehta,Vahishta Vandriwala,Prof Jitali Patel

OrganizationIIT-Indore

Year , VenueDecember 2020 , IIT,Indore

Indexed INScopus

Abstract

Extensive use of tools and technology in the healthcare field, resulting in big data. Indexing helps in faster retrieval of intended data from very big datasets. Indexing of Big Data becomes a major concern when the querying field is present in very few of the input files, but the number of input files is more. In this paper, authors have built an index structure for the datasets having the querying need the full scan of the entire database even though it can be achieved without reading the majority of the input files. Focused literature survey imparts different indexing methodology with a suitable application area. The inverted index is the most suitable indexing for the COVID-19 dataset, including the details of the patients’ of India. The inverted index is created on the column with state names in the dataset. Map-Reduce programming framework is used for implementation with the Apache Hadoop platform. Algorithms for grouping the data, creation of index and querying is exemplified with the explanation. Test cases are designed on COVID-19 dataset with indexing and without indexing. Time taken to create index and to fetch the records are recorded for various volumetric input files. Result and discussion part of this paper indicate the use of index enhanced performance of querying on big data. The performance that is achieved while querying the database after index construction is much better than the normal querying.

Online Analytical Processing for Business Intelligence in Big Data

Journal

Journal NameBig data

Title of PaperOnline Analytical Processing for Business Intelligence in Big Data

PublisherMarry Ann Liebert

Volume Number8

Page Number501-518

Published YearDecember 2020

ISSN/ISBN No2167-6461

Indexed INScopus, PubMed, Web of Science

Abstract

Online analytical processing (OLAP) approach is widely used in business intelligence to cater the multidimensional queries for decades. In this era of cutting-edge technology and the internet, data generation rates have been rising exponentially. Internet of things sensors and social media platforms are some of the major contributors, leading toward the absolute data boom. Storage and speed are the crucial parameters and undoubtedly the burning issues in efficient data handling. The key idea here is to address these two challenges of big data computing in OLAP. In this article, the authors have proposed and implemented OLAP on Hadoop by Indexing (OOHI). OOHI offers a simplified multidimensional model that stores dimensions in the schema server and measures on the Hadoop cluster. Overall setup is divided into various modules, namely: data storage module (DSM), dimension encoding module (DEM), cube segmentation module, segment selection module (SSM), and block selection and process (BSAP) module. Serialization and deserialization concept applied by DSM for storage and retrieval of the data for efficient space utilization. Integer encoding adopted by DEM in dimension hierarchy is selected to escape sparsity problem in multidimensional big data. To reduce search space by chunks of the cube from the queried chunks, SSM plays an important role. Map reduce-based indexing approach and series of seek operations of BSAP module were integrated to achieve parallelism and fault tolerance. Real-time oceanography data and supermarket data sets are applied to demonstrate that OOHI model is data independent. Various test cases are designed to cover the scope of each dimension and volume of data set. Comparative results and performance analytics portray that OOHI outperforms in data storage, dice, slice, and roll-up operations compared with Hadoop based OLAP.

Deep Reinforcement Learning Based Personalized Health Recommendations

Book Chapter

Book NameDeep Learning Techniques for Biomedical and Health Informatics

PublisherSpringer

Author NameJigna Patel

Page Number231-255

Chapter TitleDeep Reinforcement Learning Based Personalized Health Recommendations

Published YearNovember 2019

ISSN/ISBN No978-3-030-33965-4

Indexed INScopus

Abstract

In this age of informatics, it has become paramount to provide personalized recommendations in order to mitigate the effects of information overload. This domain of biomedical and health care informatics is still untapped as far as personalized recommendations are concerned. Most of the existing recommender systems have, to some extent, not been able to address sparsity of data and non-linearity of user-item relationships among other issues. Deep reinforcement learning systems can revolutionize the recommendation architectures because of its ability to use non-linear transformations, representation learning, sequence modelling and flexibility for implementation of these architectures. In this paper, we present a deep reinforcement learning based approach for complete health care recommendations including medicines to take, doctors to consult, nutrition to acquire and activities to perform that consists of exercises and preferable sports. We try to exploit an “Actor-Critic” model for enhancing the ability of the model to continuously update information seeking strategies based on user’s real-time feedback. Health industry usually deals with long-term issues. Traditional recommender systems fail to consider the long-term effects, hence failing to capture dynamic sentiments of people. This approach treats the process of recommendation as a sequential decision process, which addresses the aforementioned issues. It is estimated that over 700 million people will possess wearable devices that will monitor every step they take. Data collected with these smart devices, combined with other sources like, Electronic Health Records, Nutrition Data and data collected from surveys can be processed using Big Data Analysis tools, and fed to recommendation systems to generate desirable recommendations. These data, after encoding (state) into appropriate format, will be fed to the Actor network, which will learn a policy for prioritizing a particular recommendation (action). The action, state pair is fed to the critic network, which generates a reward associated with the action, state pair. This reward is used to update the policy of the Actor network. The critic network learns using a pre-defined Expected Reward. Hence, we find that using tools for Big Data Analytics, and intelligent approaches like Deep Reinforcement Learning can significantly improve recommendation results for health care, aiding in creating seamlessly personalized systems.

Efficient computing of OLAP in Big data warehouse

Journal

Journal NameInternational Journal of Advanced Research in Computer Science

Title of PaperEfficient computing of OLAP in Big data warehouse

PublisherIJARCS

Volume Number9

Page Number201-205

Published YearJanuary 2018

ISSN/ISBN No0976-5697

Indexed INIndian citation Index, UGC List

Big Data Harmonization –Challenges and Applications

Journal

Journal NameInternational Journal on Recent and Innovation Trends in Computing and Communication

Title of PaperBig Data Harmonization –Challenges and Applications

Publisheri

Volume Number5

Page Number206-208

Published YearJune 2017

ISSN/ISBN No2321-8169

Indexed INIndian citation Index, UGC List, Others

Abstract

As data grow, need for big data solution gets increased day by day. Concept of data harmonization exist since two decades. Asdata is to be collected from various heterogeneous sources and techniques of data harmonization allow them to be in a single format at same place it is also called data warehouse. Lot of advancement occurred to analyses historical data by using data warehousing. Innovations uncover the challenges and problems faced by data warehousing every now and then. When the volume and variety of data gets increased exponentially, existing tools might not support the OLAP operations by traditional warehouse approach. In this paper we tried to focus on the research being done in the field of big data warehouse category wise. Research issues and proposed approaches on various kind of dataset is shown. Challenges and advantages of using data warehouse before data mining task are also explained in detail.

Women carrer in IT sector

Conference

Title of PaperWomen carrer in IT sector

Proceeding NameIndian Journal of Technical Education

PublisherGTU

Author NameJigna Patel

OrganizationBVM Engineering College,V.V.Nagar

Year , VenueJanuary 2016 , India

Page Number4

ISSN/ISBN NoISSN:0971-3034

Indexed INOthers

Big data for better health planning

Conference

Title of PaperBig data for better health planning

Proceeding NameIEEE International Conference on Advances in Engineering & Technology Research (ICAETR -2014)

PublisherIEEE Xplore

Author NameJigna Patel

Year , VenueAugust 2014 , Dr. Virendra Swarup Group ofinstitutions, Unnao, India

Page Number4

Indexed INScopus

Abstract

he exponential evolution of data in health care has brought a lot of challenges in tenns of data transfer, storage, computation and analysis. For healthcare usage and applications, ample patient infonnation and historical data, which enclose rich and significant insights that can be exposed using advanced tools and techniques as well as latest machine learning algorithms. Though, the size and rapidity of such great dimensional data requires new big data analytics framework. This paper introduces the thought of data in healthcare and the results of various surveys to show the impact of big data. Few case studies of big data analytics in healthcare is presented. Last section is about the tools and techniques comprising Hadoop, Stonn, Spark and HPCC -big data solution offered to solve big data issues and challenges

Traffic control using fuzzy logic

Journal

Journal NameInternational Journal of Electronics, Communication & InstrumentationEngineering Research and Development

Title of PaperTraffic control using fuzzy logic

PublisherTJPRC

Volume NumberVolume4-4

Page NumberPage no: 27-35

Published YearAugust 2014

ISSN/ISBN No2249-7951

Indexed INOthers

Abstract

Fuzzy Logic is based on distinguish between Binary variable which is present in Classical sets which are restricted. Fuzzy Logic helps us to build linguistic variable which enables us to create minute differences in any application. This paper covers the basics of Fuzzy logic. The entire concept of fuzzy logic is presented in well-defined manner. When to use and how to use fuzzy logic is explained. There are many application in which fuzzy logic is used and I have implemented one of them. I have demonstrated a C++ code with algorithm to detect the traffic flow on roads and I have discussits results. Future scope with the extension of existing code would be helpful

Jitali Patel

ConCollA - A Smart Emotion-based Music Recommendation System for Drivers

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperConCollA - A Smart Emotion-based Music Recommendation System for Drivers

Publisheruniversitatea de vest

Volume Number24

Page Number919–939

Published YearNovember 2023

ISSN/ISBN No18951767

Indexed INScopus, Web of Science

Abstract

The role of sentiment analysis in a recommender system: a systematic survey

Journal

Journal NameInternational Journal of Web Engineering and Technology

Title of PaperThe role of sentiment analysis in a recommender system: a systematic survey

PublisherInderscience

Volume Number17

Page Number29-62

Published YearAugust 2022

ISSN/ISBN No1741-9212

Indexed INScopus

Abstract

Currently, fields like e-commerce, education, social media, tourism, and the entertainment industry rely on recommender systems to provide personalised services to their clients. The most common and widely accepted technique - collaborative filtering, creates recommendations by examining the users' past rating patterns. Collaborative filtering assumes that a users' past rating data accurately reflects their actual preferences. However, different study found that the ratings may not accurately reflect user preferences in the real-world circumstances. Therefore, to deal with this problem, sentiment analysis of user-generated text is started to be used. It helps to improve the performance of recommender systems, as it provides more specific and trustworthy user preferences than ratings. A sentiment-aware recommender system captures sentiment from the user-generated content and provides most suited personalised services to the user. We have classified sentiment enhanced recommender systems according to the level of sentiment analysis and presented technical aspects such as datasets, methodologies and results.

Big Data Analytics for Advanced Viticulture

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperBig Data Analytics for Advanced Viticulture

Publisheruniversitatea de vest

Volume Number22

Page Number302–312

Published YearNovember 2021

ISSN/ISBN No18951767

Indexed INScopus, Web of Science

Abstract

A fusion of aspect and contextual information for rating prediction in recommender system using a latent factor model

Journal

Journal NameInternational Journal of Web Engineering and Technology

Title of PaperA fusion of aspect and contextual information for rating prediction in recommender system using a latent factor model

PublisherInderscience

Volume Number16

Page Number30-52

Published YearJune 2021

ISSN/ISBN No1741-9212

Indexed INScopus

Abstract

Referring to reviews, checking online comments and, visiting different websites before buying any product is a call of the day. Online reviews are an excellent source of information both for users and organisations alike. In this article, a hybrid model, named as aspect and context-based latent factor model (ACMF), is proposed to predict user rating on an item based on star ratings provided by users, feature-opinion information, and context information. ACMF mainly consists of three phases: the first phase extracts spam reviews, the second phase extracts features and opinions from written reviews and calculates the polarity score of opinions. In the last phase, reviews and context information are aggregated to predict the unknown rating of a user for better recommendations. The proposed model is tested on ratings and reviews downloaded from the Amazon website. Experiment results show RMSE of ACMF has been achieved significantly less than other relevant methods.

CNN based Variation and Prediction Analysis of 2m Air Temperature for Different Zones of the Indian Region

Conference

Title of PaperCNN based Variation and Prediction Analysis of 2m Air Temperature for Different Zones of the Indian Region

Proceeding NameInternational Conference on Computing Methodologies and Communication (ICCMC)

PublisherIEEE

Author NameJitali Patel

OrganizationSurya Engineering College, Erode, Tamil Nadu ,India

Year , VenueApril 2021 , Surya Engineering College, Erode, Tamil Nadu ,India

Page Number1798–1804

ISSN/ISBN No978-1-6654-0360-3

Indexed INScopus

Abstract

Time series forecasting is a method that predicts future values by analyzing past values. Temperature alarms are valuable predictions because they are used to safeguard life and property and to increase operational performance. Here 2m air temperature refers to the temperature of air recorded at 2 meters from the ground. Paper consists of time-series prediction of temperature data that has been taken from automatic weather stations(AWS) installed by the Indian Space Research Organisation. Given paper presents the applicability of different machine learning(ML) algorithms like convolutional neural network(CNN), long short term memory(LSTM), and autoregressive integrated moving average(ARIMA) algorithms for the validity of temperature prediction over four different stations which are Ahmedabad, Balasore, Coimbatore, and Udaipur. These stations record the hourly-based temperatures. Based on different datasets, the prediction accuracy of algorithms is compared. The paper discusses the results showing that by applying different algorithms to the different datasets with different characteristics, it is observed that the various algorithms behave distinctly with numerous 1-dimensional datasets based on the variation in recorded values, location, or type of the input data i.e hourly input data or daily input data. This analysis shows that different machine learning algorithms have a different performance ratio while applied to various data sets.

Deep reinforcement learning based personalized health recommendations

Book Chapter

Book NameDeep Learning Techniques for Biomedical and Health Informatics

PublisherSpringer

Author NameJitali Patel

Page Number231-255

Chapter TitleDeep reinforcement learning based personalized health recommendations

Published YearNovember 2019

ISSN/ISBN No2197-6503

Indexed INScopus, Web of Science

Abstract

A Survey on Security Issues in MANETs

Conference

Title of PaperA Survey on Security Issues in MANETs

Proceeding NameInternational Conference on Recent Innovations in Applied Science, Engineering and Technologies

OrganizationInstitution of Engineers, India

Year , VenueJune 2018 , IEI, Mumbai

Page Number146-155

ISSN/ISBN No987-93-87793-30-2

Review on Different types of Spam Filtering Techniques

Journal

Journal NameInternational Journal of Advanced Research in Computer Science

Title of PaperReview on Different types of Spam Filtering Techniques

Volume Number8

Page Number2720-2723

Published YearJune 2017

ISSN/ISBN No0976-5697

Indexed INOthers

Computational Analysis of different Vertex Cover alorithms of various graphs

Conference

Title of PaperComputational Analysis of different Vertex Cover alorithms of various graphs

Proceeding NameInternational Conference on Intelligent Computing and Control Systems

PublisherIEEE

OrganizationVaigai College of Engineering

Year , VenueJune 2017 , Madurai India.

Page Number730-734

A Review on Different types of Spam Filtering Techniques

Journal

Journal NameIJARCS

Title of PaperA Review on Different types of Spam Filtering Techniques

Volume Number8

Published YearJanuary 2017

ISSN/ISBN No0976-5697

Indexed INUGC List

Twitter Followee Recommender System

Conference

Title of PaperTwitter Followee Recommender System

PublisherInternational conference on recent trends in engineering science and management

Year , VenueApril 2016 , Vendant college of Engineering and Technology,Bundi,Rajasthan

Page Number524-534

ISSN/ISBN No978-81-932074-4-4

Deep Learning Algorithms

Journal

Journal Name International Journal of Computer Science & Communication

Title of PaperDeep Learning Algorithms

Volume Number7

Page Number258-263

Published YearMarch 2016

ISSN/ISBN No0973-7391

Indexed INOthers

Assembling a Web Crawler

Conference

Title of PaperAssembling a Web Crawler

Proceeding NameInternational Conference on Recent Innovations in Science, Engineering and Management

Year , VenueMay 2015 , New Delhi

Page Number710-794

ISSN/ISBN No978-81-931039-4-4

Jitendra Bhatia

Unleashing the power of SDN and GNN for network anomaly detection: State‐of‐the‐art, challenges, and future directions

Journal

Journal NameSecurity and Privacy

Title of PaperUnleashing the power of SDN and GNN for network anomaly detection: State‐of‐the‐art, challenges, and future directions

PublisherWiley

Volume Number7

Page Number1-16

Published YearJanuary 2024

ISSN/ISBN No2475-6725

Indexed INWeb of Science

Abstract

Modern computer networks' increasing complexity and scale need serious attention towards network anomaly detection. Software-defined networking (SDN) and graph neural networks (GNN) have emerged as promising approaches for anomaly detection due to their ability to capture dynamic network behavior and learn complex patterns from large-scale network data. The amalgamation of SDN and GNN for network anomaly detection presents promising opportunities for improving the accuracy and efficiency of network anomaly detection. This paper focuses on various trends, issues, and challenges by integrating GNN on the top of SDN for network anomaly detection. The article highlights the advantages of using SDN for providing fine-grained control and programmability in network monitoring. At the same time, GNN can model network behavior as a graph and learn representations from graph-structured data. The authors also discuss the limitations of traditional anomaly detection methods in SDN, such as rule-based approaches, and the potential of GNN to overcome these limitations by leveraging their ability to capture non-linear and dynamic patterns in network data. This paper also presents a case study of DoS attack detection using SDN. The result shows that SDN based approach helps to detect attacks with an accuracy of 97% with future research directions.

A comprehensive review of internet of things and cutting-edge technologies empowering smart farming.

Journal

Journal NameCurrent Science

Title of PaperA comprehensive review of internet of things and cutting-edge technologies empowering smart farming.

PublisherCurrent Science

Volume Number126

Page Number1-15

Published YearJanuary 2024

ISSN/ISBN No0011-3891

Indexed INScopus, Web of Science

Abstract

The agricultural sector plays an important role in contributing significantly to the gross domestic product (GDP) growth in developing countries. On the other hand, agriculture is widely affected by major factors such as environmental changes, natural disasters, pesticide control, and soil and irrigation-related issues, which reduce crop yield. The convergence of Industry 4.0 and agriculture offers an opportunity to move into the next generation of Agriculture 4.0. The internet of things (IoT), remote sensing, machine learning, deep learning, big data, cloud computing, thermal imaging, end-user apps and unmanned aerial vehicles offer a full-stack solution. IoT provides the ubiquitous connectivity of smart devices to the internet to collect, process and analyse a large amount of agriculture field data more quickly and synthesize them to make smart decisions using various machine learning and deep learning algorithms. This study reviews the challenges and major issues in the IoT agriculture domain and explores its emergence with new technologies. It covers the existing literature and illustrates how IoT application based precision agriculture solutions have contributed. A case study on weed detection for smart agriculture using the YOLOv5 model is presented, achieving high accuracy. Finally, various IoT agriculture use cases are discussed, along with current research issues and possible solutions for future IoT-based agriculture advancement.

An Overview of Fog Data Analytics for IoT Applications”

PublisherIEEE

Author NameVrutik Patel, Priya Mehta, Kruti Laving

OrganizationAlliance Technology Conference (ATCON-1)

Year , VenueApril 2023 , Bangalore, India

ISSN/ISBN No978-1-6654-5627-2

Conference

Title of PaperGraph Neural Network based Recommender System

Proceeding NameProceedings of the Seventh International Conference on Communication and Electronics Systems (ICCES 2022)

PublisherIEEE

Author NameRachana Mehta, Kruti Lavingia, Pimal Khanpara, Vijay Dhulera

Page Number1377-1381

Published YearJune 2022

ISSN/ISBN No978-1-6654-9634-6

Indexed INScopus

Information Retrieval and Data Analytics in Internet of Things: Current Perspective, Applications and Challenges

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperInformation Retrieval and Data Analytics in Internet of Things: Current Perspective, Applications and Challenges

Volume Number23(1)

Page Number23-34

Published YearApril 2022

ISSN/ISBN No1895-1767

Indexed INScopus, Web of Science

Augmented Reality and Industry 4.0

Book Chapter

Book NameA Roadmap to Industry 4.0: Smart Production, Smart Business and Sustainable Development

PublisherSpringer, Cham

Author NameKruti Lavingia

Page Numberpp 143-155

Chapter TitleAugmented Reality and Industry 4.0

Published YearNovember 2019

ISSN/ISBN No978-3-030-14544-6

Indexed INScopus

Energy conservation in Multimedia big data computing and the Internet of Things—A challenge

Book Chapter

Book NameMultimedia Big Data Computing for IoT Applications

PublisherSpringer, Singapore

Author NameKruti Lavingia

Page Numberpp 37-57

Chapter TitleEnergy conservation in Multimedia big data computing and the Internet of Things—A challenge

Published YearJuly 2019

ISSN/ISBN No978-981-13-8759-3

Indexed INScopus

GDLC: A Software Engineering Approach in Game Development

Journal

Journal NameInternational Journal of Advance Research in Science and Engineering

Title of PaperGDLC: A Software Engineering Approach in Game Development

Volume Number6(6)

Page Number579-584

Published YearJune 2017

ISSN/ISBN No2319-8354

Indexed INUGC List

Software Engineering in freelancing

Journal

Journal NameInternational Journal of Research and Scientific Innovation

Title of PaperSoftware Engineering in freelancing

Volume Number4(5)

Page Number103-105

Published YearMay 2017

ISSN/ISBN No2321-2705

Indexed INUGC List

Survey Paper on Impact of Cloud Computing on Conventional Software Engineering

Journal

Journal NameInternationa Journal of Computer Science and Engineering

Title of PaperSurvey Paper on Impact of Cloud Computing on Conventional Software Engineering

Volume Number9(5)

Page Number149-152

Published YearMay 2017

ISSN/ISBN No0975-3397

Indexed INUGC List

Security Engineering

Conference

Title of PaperSecurity Engineering

Proceeding NameInternational Conference on Academic Research in Engineering and Management

OrganizationInstitution of Electronics and Telecommunication Engineers, Delhi

Year , VenueApril 2017 , Institution of Electronics and Telecomunication Engineers, Lodhi Road, Delhi

Page Number269 - 274

ISSN/ISBN NoISBN - 978-93-86171-43-6

Indexed INUGC List

Performance Evaluation of Transmission distance and Bit Rates in Inter-Satellite optical wireless communication system

Conference

Title of PaperPerformance Evaluation of Transmission distance and Bit Rates in Inter-Satellite optical wireless communication system

Proceeding Name3rd International Conference on Recent Innovations in Science Engineering and Management

OrganizationSri Venkateswara College of Engineering and Technology, Srikakulam,Andhra Pradesh

Year , VenueFebruary 2017 , Sri Venkateswara College of Engineering and Technology,Srikakulam, Andhrapradesh

Page Number36-40

ISSN/ISBN No978-81-932074-1-3

Indexed INUGC List

Performance evolution of optical link using dispersion compensation fiber and FBG

Conference

Title of PaperPerformance evolution of optical link using dispersion compensation fiber and FBG

Proceeding NameInternational Conference on Recent Trends in Engineering Science, Humanities and Management

OrganizationSri S Ramasamy Naidu Memorial College, Sattur, Tamilnadu

Year , VenueFebruary 2017 , Sri S Ramasamy Naidu Memorial College, Sattur, Tamilnadu

Page Number809-812

ISSN/ISBN NoISBN : 978-93-86171-18-4

Indexed INUGC List

A machine learning approach to improve the efficiency of fake website detection techniques

Journal

Journal NameInternational Journal of Computer Science and Communication

Title of PaperA machine learning approach to improve the efficiency of fake website detection techniques

Volume Number7

Page Number236-243

Published YearMarch 2016

ISSN/ISBN No0973-7391

Indexed INUGC List

A novel approach to improve the efficiency of fake website detection techniques: Survey

Conference

Title of PaperA novel approach to improve the efficiency of fake website detection techniques: Survey

Proceeding Name2nd International Conference on Recent Trends in Engineering Science and Management

OrganizationYMCA, New Delhi

Year , VenueFebruary 2016 , YMCA, New Delhi

Page Number71-78

ISSN/ISBN No978-81-932074-3-7

Indexed INUGC List

Lata Gohil

Blockchain and ML-Based Framework for Diabetes Assessment of Patients in Telesurgery System

Conference

Title of PaperBlockchain and ML-Based Framework for Diabetes Assessment of Patients in Telesurgery System

Proceeding Name2023 3rd International Conference on Smart Generation Computing, Communication and Networking (SMART GENCON)

PublisherIEEE Xplore

Author NameYogi Patel, Denisha Tank, Rajesh Gupt, Riya Kakkar, Nilesh Kumar Jadav, Lata Gohil, Sudeep Tanwar

OrganizationGhousia College of Engineering

Year , VenueDecember 2023 , Ghousia College of Engineering, Ramanagaram Bengaluru

Page Number1-6

ISSN/ISBN No979-8-3503-1912-5

Conference

Title of PaperAutomatic Question Tagging using Machine Learning and Deep learning Algorithms

Proceeding Name2022 6th International Conference on Electronics, Communication and Aerospace Technology

PublisherIEEE Explore

Author NameM. Prajapati, M. Nakrani, T. Vyas, L. Gohil, S. Desai and S. Degadwala

OrganizationRVS Technical Campus, Coimbatore, Tamil Nadu, India

Year , VenueDecember 2022 , Coimbatore, India

Page Number932-938

ISSN/ISBN No978-1-6654-8272-1

Indexed INScopus

Abstract

Stack Overflow is a well-known website which is utilized by nearly everyone who learns to code, share their knowledge and publicly participate in this question-answering forum. The questions posted on the Stack Overflow forum by a user requires a minimum of 1 tag to be manually entered in by them. Tagging most commonly means to associate some single word information about the context of given text or question. Tagging a question is useful in identifying the category that a question or text belongs. It is also beneficial in providing ease of access to a person having a requirement of specific categories of questions. On analysis of tags associated with the questions on the website, it was found that a large number of the questions are labelled by more than one tags, with many of them not being tagged accurately. Due to this situation, it becomes challenging for the users to search for relevant tags. So, the main aim of this research task is to explore methods and compare different techniques in order to create an auto tagging system with the aid of Machine learning and deep learning facilities, accompanied by data preprocessing steps. The dataset for this purpose was taken from Kaggle, known as StackSample dataset, which is a dataset containing 10 percent of the questions present on the website. The output of the research performed for this purpose provided satisfactory results with scope of improvement.

Music Genre Classification using Deep Learning

Conference

Title of PaperMusic Genre Classification using Deep Learning

Proceeding Name2022 6th International Conference on Computing Methodologies and Communication (ICCMC)

PublisherIEEE Explore

Author NameMitt Shah, Nandit Pujara, Kaushil Mangaroliya, Lata Gohil, Tarjni Vyas, Sheshang Degadwala

OrganizationSurya Engineering College(SEC), Erode

Year , VenueMarch 2022 , Erode, India

Page Number974-978

ISSN/ISBN No978-1-6654-1029-8

Massive amount of digital data is available in form of unstructured text. It is highly required to extract useful information from this textual data. The process to discover non-trivial information and knowledge which are previously unknown is knows as Text Mining. This paper discusses process and techniques with respect to Text Mining.

Madhuri Bhavsar

SLAMMP Framework for Cloud Resource Management and Its Impact on Healthcare Computational Techniques

Journal

Journal NameInternational Journal of E-Health and Medical Communications (IJEHMC)

Title of PaperSLAMMP Framework for Cloud Resource Management and Its Impact on Healthcare Computational Techniques

PublisherIGI Global

Published YearJuly 2021

Indexed INScopus, Web of Science, Others

SDN-Enabled Adaptive Broadcast Timer for Data Dissemination in Vehicular Ad Hoc Networks

Journal

Journal NameIEEE Transactions on Vehicular Technology

Title of PaperSDN-Enabled Adaptive Broadcast Timer for Data Dissemination in Vehicular Ad Hoc Networks

PublisherIEEE

Volume Number70

Page Number8134-8147

Published YearJune 2021

ISSN/ISBN No1939-9359

Indexed INScopus

Feature Combination of Pauli and H/A/Alpha Decomposition for Improved Oil Spill Detection Using SAR

Conference

Title of PaperFeature Combination of Pauli and H/A/Alpha Decomposition for Improved Oil Spill Detection Using SAR

Proceeding NameRecent Trends in Image Processing and Pattern Recognition: Third International Conference, RTIP2R

PublisherSpringer

Year , VenueFebruary 2021 , Singapore

Page Number134-147

ISSN/ISBN No978-981-16-0507-9

On Performance Enhancement of Molecular Dynamics Simulation Using HPC Systems

Conference

Title of PaperOn Performance Enhancement of Molecular Dynamics Simulation Using HPC Systems

Proceeding NameProceedings of Second International Conference on Computing, Communications, and Cyber-Security

PublisherSpringer

Year , VenueJanuary 2021 , Singapiore

Page Number1031-1044

ISSN/ISBN No978-981-16-0733-2

CS2M: Cloud Security and SLA Management

Journal

Journal NameAnnals of the Romanian Society for Cell Biology (2021)

Title of PaperCS2M: Cloud Security and SLA Management

PublisherAssociation of Cell Biology Romania

Volume Number25

Page Number4459 - 4465

Published YearJanuary 2021

ISSN/ISBN No1583-6258

Indexed INScopus

C2B-SCHMS: Cloud Computing and Bots Security for COVID-19 Data and Healthcare Management Systems

Conference

Title of PaperC2B-SCHMS: Cloud Computing and Bots Security for COVID-19 Data and Healthcare Management Systems

Proceeding NameProceedings of Second International Conference on Computing, Communications, and Cyber-Security.

PublisherSpringer

Year , VenueDecember 2020 , Singapore

ISSN/ISBN No978-3-030-67490-8

Advance Cloud Data Analytics for 5G Enabled IoT

Book Chapter

Book NameBlockchain for 5G-Enabled IoT: The New Wave for Industrial Automation

PublisherSpringer, Cham

Page Number159-180

Chapter TitleAdvance Cloud Data Analytics for 5G Enabled IoT

Published YearDecember 2020

Monitoring and Prediction of SLA for IoT based Cloud

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperMonitoring and Prediction of SLA for IoT based Cloud

PublisherSCPE

Volume Number21

Page Number349-358

Published YearAugust 2020

Indexed INScopus, Others

Monitoring IaaS Cloud for Healthcare Systems: Healthcare Information Management and Cloud Resources Utilization

Journal

Journal NameInternational Journal of E-Health and Medical Communications (IJEHMC)

Title of PaperMonitoring IaaS Cloud for Healthcare Systems: Healthcare Information Management and Cloud Resources Utilization

PublisherIGI Global

Volume Number11

Page Number54-70

Published YearJuly 2020

Indexed INScopus, Others

SDN-Enabled Network Coding-Based Secure Data Dissemination in VANET Environment

Journal

Journal NameIEEE Internet of Things Journal

Title of PaperSDN-Enabled Network Coding-Based Secure Data Dissemination in VANET Environment

PublisherIEEE

Page Number6078-6087

Published YearJuly 2020

ISSN/ISBN No2327-4662

Establishing Trust in the Cloud Using Machine Learning Methods

Conference

Title of PaperEstablishing Trust in the Cloud Using Machine Learning Methods

Proceeding NameIn Proceedings of First International Conference on Computing, Communications, and Cyber-Security

PublisherSpringer

Year , VenueApril 2020 , Singapore

Page Number791-805

ISSN/ISBN No978-981-15-3369-3

Performance consequence of user space file systems due to extensive CPU sharing in virtual environment

Journal

Journal NameCluster Computing

Title of PaperPerformance consequence of user space file systems due to extensive CPU sharing in virtual environment

PublisherSpringer

Page Number3119-3137

Published YearFebruary 2020

Indexed INScopus, PubMed

Preserving SLA Parameters for Trusted IaaS Cloud: An Intelligent Monitoring Approach

Journal

Journal NameRecent Patents on Engineering

Title of PaperPreserving SLA Parameters for Trusted IaaS Cloud: An Intelligent Monitoring Approach

PublisherBentham Science

Volume Number14

Page Number530-540

Published YearJanuary 2020

ISSN/ISBN No2212-4047

Indexed INScopus

Achieving Trust using RoT in IaaS Cloud

Journal

Journal NameProcedia Computer Science

Title of PaperAchieving Trust using RoT in IaaS Cloud

PublisherElsevier

Volume Number167

Page Number487-495

Published YearJanuary 2020

Indexed INScopus

Efficient Resource Provisioning Through Workload Prediction in the Cloud System

Conference

Title of PaperEfficient Resource Provisioning Through Workload Prediction in the Cloud System

Proceeding Name Smart Trends in Computing and Communications

PublisherSpringer

Year , VenueDecember 2019 , Singapore

Page Number317-325

ISSN/ISBN No978-981-15-0077-0

Adaptive cloud resource management through workload prediction

Journal

Journal NameEnergy Systems

Title of PaperAdaptive cloud resource management through workload prediction

PublisherSpringer

Published YearNovember 2019

Software Defined Vehicular Networks: A Comprehensive Review

Journal

Journal NameInternational Journal of Communications:Software Defined Vehicular Networks: A Comprehensive Review

Title of PaperSoftware Defined Vehicular Networks: A Comprehensive Review

PublisherWiley

Volume Numberearly access

Page Numberearly access

Published YearJanuary

ISSN/ISBN No1099-1131

Indexed INScopus, Web of Science, EBSCO, UGC List, Others

Abstract

The recent breakthroughs in the automobile industries and telecommunication technologies along with the exceptional multimodal mobility services brought focus on Intelligent Transportation System (ITS), of which Vehicular Adhoc Networks (VANETs) gain much more attention. The distinctive features of Software Defined Networking (SDN) leverages the vehicular networks by its state of the centralized art having a comprehensive view of the network. Its potential to bring the flexibility, programmability and other extensive advancements to vehicular networks has set the stage for a novel networking paradigm termed as Software-Defined Vehicular Networks (SDVNs). Many researchers have demonstrated the SDN based VANETs with the various configuration of the SDN components in VANET architecture. However, a compilation of the work on the SDN based VANET system as a whole incorporating its architecture, use-cases, and opportunities is still inadequate. We start with the summary of the recent studies exist on the SDVNs, followed by the comprehensive explanation of its components. Next, we present the taxonomy of SDVN based on the architecture modes, protocols, access technologies and opportunities with trending technologies. Finally, we highlights the challenges, open research issues, and future research directions.

Trust Management and Monitoring at an IaaS Level of Cloud Computing

Conference

Title of PaperTrust Management and Monitoring at an IaaS Level of Cloud Computing

Proceeding NameSRRN Elsevier

PublisherSRRN Elsevier

Year , VenueJanuary , MNIT, Jaipur

Page Number-

ISSN/ISBN No1556-5068

Indexed INUGC List

Abstract

Now a days Cloud Computing is as a major utility, same as electricity and water bills where we pay as we go with the consumption of the said resources, as organization usages cloud computing services and pays as per their usage of the resources. In this research paper, the authors aspect are towards at what trust is and how trust value can be maintained to create its trust level among the end users and the cloud service provider with the help of on demand monitoring mechanism and invoking the monitoring techniques only when the trust fluctuates to maintain its dignity towards the trust shown by the end use .In monitoring the present status of the resources are analyzed and based upon the same the new instances will be created to satisfy the need of the end users to maintain the trust level.

Influence of Monitoring : Fog and Edge Computing

Journal

Journal NameScalable Computing: Practice and Experience Publishing

Title of PaperInfluence of Monitoring : Fog and Edge Computing

PublisherSCPE

Volume Number20

Published YearMay 2019

Indexed INScopus, Others

Influence of Montoring: Fog and Edge Computing

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperInfluence of Montoring: Fog and Edge Computing

PublisherSCPE

Volume Number20

Page Number365–376

Published YearMay 2019

ISSN/ISBN No1895-1767

Indexed INScopus, Web of Science, UGC List

Abstract

The evolution of the Internet of Things (IoT) has augmented the necessity for Cloud, edge and fog platforms. The chief benefit of cloud-based schemes is they allow data to be collected from numerous services and sites, which is reachable from any place of the world. The organizations will be benefited by merging the cloud platform with the on-site fog networks and edge devices and as result, this will increase the utilization of the IoT devices and end users too. The network traffic will reduce as data will be distributed and this will also improve the operational efficiency. The impact of monitoring in edge and fog computing can play an important role to efficiently utilize the resources available at these layers. This paper discusses various techniques involved for monitoring for edge and fog computing and its advantages. The paper ends with a case study to demonstarte the need of monitoring in fog and edge in the healthcare system.

Classification of crop types using C band SAR Data

Conference

Title of PaperClassification of crop types using C band SAR Data

Proceeding NameInternational Conference on Knowledge Discovery in Science and Technology-2019(ICKDST-19)

PublisherJAC

Year , VenueFebruary 2019 , Pune, India

Exploratory Learning of Resource Management in Private Cloud Environment

Journal

Journal NameInternational Journal of Recent Technology and Engineering

Title of PaperExploratory Learning of Resource Management in Private Cloud Environment

Volume Number8

Published YearJanuary 2019

ISSN/ISBN No2277-3878

Indexed INScopus

Prediction Based Efficient Resource Provisioning and Its Impact on QoS Parameters in the Cloud Environment

Journal

Journal NameInternational Journal of Electrical and Computer Engineering (IJECE)

Title of PaperPrediction Based Efficient Resource Provisioning and Its Impact on QoS Parameters in the Cloud Environment

PublisherInstitute of Advanced Engineering and Science (IAES)

Volume Number8

Page Number5359-5370

Published YearDecember 2018

ISSN/ISBN No2088-8708

Indexed INScopus, Others

Infrastructure as a Code in Cloud Environment for Dynamic Auto Scaling

Journal

Journal NameInternational Journal of Computing and Applications

Title of PaperInfrastructure as a Code in Cloud Environment for Dynamic Auto Scaling

PublisherSerial Publications, New Delhi (India)

Volume Number16

Page Number159-164

Published YearJune 2018

ISSN/ISBN No0973-5704

Reducing the Operative Resource Monitoring Mechanism Overhead in Cloud: An IaaS Perspective

Conference

Title of PaperReducing the Operative Resource Monitoring Mechanism Overhead in Cloud: An IaaS Perspective

Proceeding NameProceedings of 3rd International Conference on Internet of Things and Connected Technologies (ICIoTCT)

PublisherElsevier

Year , VenueMay 2018 , Jaipur, India

Chronicles of Assaults at Cloud Computing and its Influence at an IaaS

Conference

Title of PaperChronicles of Assaults at Cloud Computing and its Influence at an IaaS

Proceeding NameProceedings of 3rd International Conference on Internet of Things and Connected Technologies (ICIoTCT)

PublisherElsevier

Year , VenueMay 2018 , Jaipur, India

Performance Analysis of Local, Network and Distributed File Systems Running Inside User’s Virtual Machines in Cloud Environment

Journal

Journal NameAdvanced in Modelling and Analysis

Title of PaperPerformance Analysis of Local, Network and Distributed File Systems Running Inside User’s Virtual Machines in Cloud Environment

PublisherInternational Information and Engineering Technology Association (IIETA)

Page Number48-55

Published YearMarch 2018

Inspection of Trust Based Cloud Using Security and Capacity Management at an IaaS Level

Journal

Journal NameProcedia computer science Elsevier:Inspection of Trust Based Cloud Using Security and Capacity Management at an IaaS Level

Title of PaperInspection of Trust Based Cloud Using Security and Capacity Management at an IaaS Level

PublisherElsevier

Internet based computing has provided lots of flexibility with respect to the usages of resources, as per the current demand of the users, and granting them the said resources has its own benefits, if given in proper manner i.e. exactly what the user has asked. In this paper the autonomic computing concepts has been discussed which will be very useful for the better utilisation of the resources at an IaaS (Infrastructure as a Service) level of the cloud computing. As Cloud Computing is highly scalable and virtualisation has become an important means for the efficient utilisation of the resources. Seeking the right amount of the resources at right time should be the goal of any CSP (Cloud service provider), On the other hand the CSPs has to deal with the situation of over provisioning and under provisioning, there should be some self-managing scheme through which the resources should be made available to the requesting user in an efficient manner to satisfy the need of their requirement with an improved resource utilisation. We have discussed the usage of autonomic computing to enhance the resource utilisation in the IaaS of cloud computing through various ways.

SLA Based an Efficient and Reliable Resource Provisioning in Private Cloud

Journal

Journal NameInternational Journal of Computer Science and Communication

Title of PaperSLA Based an Efficient and Reliable Resource Provisioning in Private Cloud

PublisherComputer Science and Electronic Journals

Volume Number8

Page Number141-145

Published YearSeptember 2017

ISSN/ISBN No0973-7391

SLA Management in Cloud Federation

Conference

Title of PaperSLA Management in Cloud Federation

Proceeding NameInternational Conference on Information and Communication Technology for Intelligent Systems(ICTIS)

PublisherSpringer, Cham

Published YearAugust 2017

ISSN/ISBN No978-3-319-63645-0

Capacity Planning Through Monitoring of Context Aware Tasks at IaaS Level of Cloud Computing

Journal

Journal NameLNICST springer: Capacity Planning Through Monitoring of Context Aware Tasks at IaaS Level of Cloud Computing

Title of PaperCapacity Planning Through Monitoring of Context Aware Tasks at IaaS Level of Cloud Computing

PublisherSpringer, Cham

Volume Number220

Page Number66-74

Published YearAugust 2017

ISSN/ISBN No1867-8211

Indexed INScopus, UGC List

Abstract

Cloud Computing is the exercise of using a network of remote servers held on the Internet to store, manage, and process data which have the characteristics as an elasticity, scalability or scalable resource sharing managed by the resource management. Even the growing demand of cloud computing has radically increased the energy consumption of the data centres, which is a critical scenario in the era of cloud computing, hence the resources has to be used efficiently, which ultimately will minimise the energy. Resource management itself will get the data from resource monitoring and resource prediction for the smooth conduction of the tasks and its allocated resources. In this paper the monitoring mechanism in the cloud has been discussed and its results are used to trigger the prediction rule engine which provides the cloud service provider (CSP) to start allocating the resources in the efficient manner, even the concept of failure handling has been mentioned based upon the certain parameter which will also inform the CSP to handle the failure task and try to mitigate this and again re schedule the failed task.

Efficient Resource Monitoring and Prediction Techniques in an IaaS Level of Cloud Computing: Survey

Journal

Journal NameLNICST springer:Efficient Resource Monitoring and Prediction Techniques in an IaaS Level of Cloud Computing: Survey

Title of PaperEfficient Resource Monitoring and Prediction Techniques in an IaaS Level of Cloud Computing: Survey

PublisherSpringer, Cham

Volume Number220

Page Number47-55

Published YearAugust 2017

ISSN/ISBN No1867-8211

Indexed INScopus, UGC List

Abstract

In this paper, we have discussed about the various techniques through which the cloud computing monitoring and prediction can be achieved, This paper provides the survey of the techniques related to monitoring and prediction for the efficient usages of the resources available at the IaaS level of cloud. As cloud provides the services, which are elastic, scalable or highly dynamic in nature, which binds us to make the correct usages of the resources, but in real situations the (Cloud Service Provider)CSP’s has to face the situation of under provisioning and over provisioning, where the resources are not fully utilized and being wasted, though this is the survey paper, it ends up with the proposed model where both the concepts of the Monitoring and Prediction will be combined together to give a better vision of the future resource demand in IaaS layer of Cloud Computing.

Performance Analysis of Microsoft Windows 2008 R2 Active Directory Server in Consolidated Virtualized Environment on IBM’s HS22 High Performance Blade

Conference

Title of PaperPerformance Analysis of Microsoft Windows 2008 R2 Active Directory Server in Consolidated Virtualized Environment on IBM’s HS22 High Performance Blade

Proceeding NameCommunication and Electronics Systems (ICCES 2016)

PublisherIEEE

Year , VenueOctober 2016 , Coimbatore

ISSN/ISBN No978-1-5090-1066-0

Design of efficient algorithm for secured key exchange over Cloud Computing

Conference

Title of PaperDesign of efficient algorithm for secured key exchange over Cloud Computing

Proceeding Name2016 6th International Conference-Cloud System and Big Data Engineering (Confluence)

PublisherIEEE

Year , VenueJuly 2016 , Noida, India

Page Number180-187

ISSN/ISBN No978-1-4673-8203-8

Enhancing Data Delivery with Density Controlled Clustering in Wireless Sensor Networks

Journal

Journal NameJournal of Micro System Technologies (Springer)

Title of PaperEnhancing Data Delivery with Density Controlled Clustering in Wireless Sensor Networks

PublisherSpringer

Page Number613-631

Published YearMay 2016

Resource provisioning strategies in cloud: a survey

Journal

Journal NameInternational Journal of Computer Science and Communication

Title of PaperResource provisioning strategies in cloud: a survey

PublisherComputer Science and Electronic Journals

Volume Number7

Page Number12-15

Published YearMarch 2016

ISSN/ISBN No0973-7391

Proposed Ontology Framework for Dynamic Resource Provisioning on Public Cloud

Journal

Journal NameInternational Journal of Advanced Research in Engineering and Technology (IJARET)

Title of PaperProposed Ontology Framework for Dynamic Resource Provisioning on Public Cloud

PublisherThe International Association of Engineering and Management Education (IAEME)

Page Number118-131

Published YearJanuary 2016

Indexed INEBSCO

Classification of Weather Indices on Secured Computational Grid

Journal

Journal NameInternational Journal of u- and e- Service, Science and Technology

Title of PaperClassification of Weather Indices on Secured Computational Grid

Volume Number4

Published YearJune 2011

ISSN/ISBN No2005-4270

NGSched - An Efficient Scheduling Algorithm handling interactive jobs in Grid Environment

Journal

Journal NameInternational Journal of Grid and Distributed Computing IJGDC

Journal

Journal NameNirma university Journal of Engineering and Technology

Title of PaperUser Centric Job Management in Grid Using Multiple Agents an Unified Approach

PublisherDirectory of Open Access Journals

Volume Number1

Published YearOctober 2010

Effective Resource Management in Clouds Using Advance Reservation

Conference

Title of PaperEffective Resource Management in Clouds Using Advance Reservation

Proceeding Name2010 International Conference on Intelligent Network and Computing (ICINC 2010)

Year , VenueJanuary 2010 , Malasiya

Page Number380-383

Scavenging Idle CPU Cycles for Creation of Inexpensive Supercomputing Power

Journal

Journal NameInternational Journal of Computer Theory and Engineering

Title of PaperScavenging Idle CPU Cycles for Creation of Inexpensive Supercomputing Power

Volume Number1

Published YearJanuary 2009

Indexed INEBSCO, Others

Performance Assessment of Computational Grid on Weather Indices from HOAPS data

Conference

Title of PaperPerformance Assessment of Computational Grid on Weather Indices from HOAPS data

Proceeding NameProceedings of International Conference on Cluster and Grid Computing systems

PublisherWASET (World Academy of Science, Engineering and Technology)

Published YearJanuary 2008

Performance Assessment of Computational Grid on Weather Indices from HOAPS Data

Journal

Journal NameInternational Journal of World Academy of Science, Engineering and Technology

Title of PaperPerformance Assessment of Computational Grid on Weather Indices from HOAPS Data

Published YearJanuary 2008

Malaram Kumhar

HEAL-SDN: Artificial Neural Network-based Secure Data Exchange Framework for SDN Controllers in Healthcare 4.0

Conference

Title of PaperHEAL-SDN: Artificial Neural Network-based Secure Data Exchange Framework for SDN Controllers in Healthcare 4.0

PublisherIEEE

Author NameMalaram Kumhar, Jitendra Bhatia, Nilesh Kumar Jadav, Ali Asgar Padaria, Rajesh Gupta, Sudeep Tanwar, Joel JPC Rodrigues

Year , VenueMarch 2024 , Kuala Lumpur, Malaysia

Page Number1832-1837

ISSN/ISBN No979-8-3503-7021-8

Indexed INScopus

IoMT-Enabled Smart Healthcare: State-of-the-Art, Security and Future Directions

Conference

Title of PaperIoMT-Enabled Smart Healthcare: State-of-the-Art, Security and Future Directions

PublisherIEEE

Author NameShivam Tripathi, Vatsalkumar Makwana, Malaram Kumhar, Harshal Trivedi, Jitendra Bhatia, Sudeep Tanwar, Hossein Shahinzadeh

Year , VenueFebruary 2024 , Online

Page Number36-43

ISSN/ISBN No979-8-3503-4942-9

Indexed INScopus

AI-based Intelligent SDN Controller to Optimize Onion Routing Framework for IoMT Environment

Conference

Title of PaperAI-based Intelligent SDN Controller to Optimize Onion Routing Framework for IoMT Environment

PublisherIEEE

Author NameMalaram Kumhar, Jitendra Bhatia, Nilesh Kumar Jadav, Rajesh Gupta, Sudeep Tanwar

Year , VenueOctober 2023 , Online

Page Number885-890

ISSN/ISBN No979-8-3503-3308-4

Indexed INScopus

Secure and Explainable Artificial Intelligence (XAI) in Cloud Ecosystems: Challenges and Opportunities

Book Chapter

Book Name Lecture Notes in Networks and Systems

PublisherSpringer Nature Singapore

Author NameDarshi Khalasi, Devang Bathwar, Jitendra Bhatia, Malaram Kumhar, Vinodray Thumar

Page Number553-567

Chapter TitleSecure and Explainable Artificial Intelligence (XAI) in Cloud Ecosystems: Challenges and Opportunities

Published YearSeptember 2023

ISSN/ISBN No2367-3389

Indexed INScopus

Deep Learning-Based Single-Image Super-Resolution: A Comprehensive Review

Journal

Journal NameIEEE Access

Title of PaperDeep Learning-Based Single-Image Super-Resolution: A Comprehensive Review

PublisherIEEE

Volume Number11

Page Number21811-21830

Published YearFebruary 2023

Indexed INScopus, Web of Science

An Overview of Fog Data Analytics for IoT Applications

Journal

Journal NameSensors

Title of PaperAn Overview of Fog Data Analytics for IoT Applications

PublisherMDPI

Volume Number23

Page Number1-32

Published YearDecember 2022

Indexed INScopus, Web of Science

Software-defined networks-enabled fog computing for IoT-based healthcare: Security, challenges and opportunities

Journal

Journal NameSecurity and Privacy

Title of PaperSoftware-defined networks-enabled fog computing for IoT-based healthcare: Security, challenges and opportunities

PublisherWiley

Volume Numbere291

Page Number1-15

Published YearNovember 2022

Indexed INScopus

Edge Computing in SDN-Enabled IoTBased Healthcare Frameworks: Challenges and Future Research Directions

Journal

Journal NameInternational Journal of Reliable and Quality E-Healthcare

Title of PaperEdge Computing in SDN-Enabled IoTBased Healthcare Frameworks: Challenges and Future Research Directions

PublisherIGI Global

Volume Number11

Page Number1-15

Published YearSeptember 2022

Indexed INScopus

Emerging Communication Technologies for 5G-Enabled Internet of Things Applications

Book Chapter

Book NameBlockchain for 5G-Enabled IoT

PublisherSpringer

Author NameMalaram Kumhar, Jitendra Bhatia

Page Number133-158

Chapter TitleEmerging Communication Technologies for 5G-Enabled Internet of Things Applications

Published YearMay 2021

ISSN/ISBN No978-3-030-67489-2

Indexed INScopus

Advances in Single Image Super-Resolution: A Deep Learning Perspective

Book Chapter

Book NameLecture Notes in Networks and Systems

PublisherSpringer

Author NameKaransingh Chauhan, Hrishikesh Patel, Ridham Dave, Jitendra Bhatia and Malaram Kumhar

Page Number443-455

Chapter TitleAdvances in Single Image Super-Resolution: A Deep Learning Perspective

Published YearMay 2020

ISSN/ISBN No978-981-15-3368-6

Indexed INScopus

Quality Evaluation Model for Multimedia Internet of Things (MIoT) Applications: Challenges and Research Directions

Book Chapter

Book NameAdvances in Intelligent Systems and Computing

PublisherSpringer

Author NameMalaram Kumhar, Gaurang Raval and Vishal Parikh

Page Number330-336

Chapter TitleQuality Evaluation Model for Multimedia Internet of Things (MIoT) Applications: Challenges and Research Directions

Published YearMarch 2020

ISSN/ISBN No978-3-030-39874-3

Indexed INScopus

Swine Flu Predication Using Machine Learning

Book Chapter

Book NameSmart Innovation, Systems and Technologies

PublisherSpringer

Author NameDvijesh Bhatt, Daiwat Vyas, Malaram Kumhar and Ajay Patel

Page Number611-617

Chapter TitleSwine Flu Predication Using Machine Learning

Published YearDecember 2018

ISSN/ISBN No978-981-13-1746-0

Indexed INScopus

Medical Diagnosis System Using Machine Learning

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperMedical Diagnosis System Using Machine Learning

PublisherIJCSC

Volume Number7

Page Number177-182

Published YearApril 2016

ISSN/ISBN No0973-7391

Indexed INOthers

Improving Security in P2P File Sharing Based on Network Coding for DTN

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperImproving Security in P2P File Sharing Based on Network Coding for DTN

PublisherIJCSC

Volume Number7

Page Number167-172

Published YearMarch 2016

ISSN/ISBN No0973-7391

Indexed INOthers

Ransomware: A Threat to Cyber security

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperRansomware: A Threat to Cyber security

PublisherIJCSC

Volume Number7

Page Number224-227

Published YearSeptember 2015

ISSN/ISBN No0973-7391

Indexed INOthers

Perspective Study on Load Balancing Paradigms in Cloud Computing

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperPerspective Study on Load Balancing Paradigms in Cloud Computing

PublisherIJCSC

Volume Number6

Page Number112-120

Published YearMarch 2015

ISSN/ISBN No0973-7391

Indexed INOthers

Survey on QoS Aware Routing Protocols for Wireless Multimedia Sensor Networks

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperSurvey on QoS Aware Routing Protocols for Wireless Multimedia Sensor Networks

PublisherIJCSC

Volume Number6

Page Number121-128

Published YearMarch 2015

ISSN/ISBN No0973-7391

Indexed INOthers

The object recognition concept is being widely used a result of increasing CCTV surveillance and the need for automatic object or activity detection from images or video. Increases in the use of various sensor networks have also raised the need of lightweight process frameworks. Much research has been carried out in this area, but the research scope is colossal as it deals with open-ended problems such as being able to achieve high accuracy in little time using lightweight process frameworks. Convolution Neural Networks and their variants are widely used in various computer vision activities, but most of the architectures of CNN are application-specific. There is always a need for generic architectures with better performance. This paper introduces the Dimension-Based Generic Convolution Block (DBGC), which can be used with any CNN to make the architecture generic and provide a dimension-wise selection of various height, width, and depth kernels. This single unit which uses the separable convolution concept provides multiple combinations using various dimension-based kernels. This single unit can be used for height-based, width-based, or depth-based dimensions; the same unit can even be used for height and width, width and depth, and depth and height dimensions. It can also be used for combinations involving all three dimensions of height, width, and depth. The main novelty of DBGC lies in the dimension selector block included in the proposed architecture. Proposed unoptimized kernel dimensions reduce FLOPs by around one third and also reduce the accuracy by around one half; semi-optimized kernel dimensions yield almost the same or higher accuracy with half the FLOPs of the original architecture, while optimized kernel dimensions provide 5 to 6% higher accuracy with around a 10 M reduction in FLOPs.

Amalgamation of blockchain and sixth‐generation‐envisioned responsive edge orchestration in future cellular vehicle‐to‐anything ecosystems: Opportunities and challenges

Journal

Journal NameTransactions on Emerging Telecommunications Technologies

Title of PaperAmalgamation of blockchain and sixth‐generation‐envisioned responsive edge orchestration in future cellular vehicle‐to‐anything ecosystems: Opportunities and challenges

PublisherWiley

Volume Numbere4410

Page Number123

Published YearDecember 2021

ISSN/ISBN Noe4410

Abstract

CP-BDHCA: Blockchain-Based Confidentiality-Privacy Preserving Big Data Scheme for Healthcare Clouds and Applications

Journal

Journal NameIEEE Journal of Biomedical and Health Informatics

Title of PaperCP-BDHCA: Blockchain-Based Confidentiality-Privacy Preserving Big Data Scheme for Healthcare Clouds and Applications

Volume Number26

Page Number1937-1948

Published YearJanuary 2021

Indexed INScopus, Web of Science

Monika shah

Data Modeling Practices for E-Commerce.

Journal

Journal NameGrenze International Journal of Engineering & Technology (GIJET)

Title of PaperData Modeling Practices for E-Commerce.

Publisher Trivandrum GRENZE Scientific Society

Volume Number10(1)

Page Number613-622

Published YearJanuary 2024

ISSN/ISBN No2395-5295

Indexed INScopus, EBSCO

Document Store Schema Design Alternatives and Their Impact

Conference

Title of PaperDocument Store Schema Design Alternatives and Their Impact

Proceeding NameInternational Conference on Data Analytics & Management

PublisherSpringer Nature Singapore

Author NameMonika Shah, Amit Kothari

Page Number471-482

Published YearNovember 2023

ISSN/ISBN No978-981-99-6549-6

Indexed INScopus

Comparative analysis of detecting over-claim permissions from android apps

Conference

Title of PaperComparative analysis of detecting over-claim permissions from android apps

Proceeding Name2023 International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC)

PublisherIEEE

Author NameRaj J Majethiya, Monika Shah

Page Number1-8

Published YearFebruary 2023

Schema-free (flexible schema) is an attractive feature in the NoSQL document store, where users can access the database without referring to its schema. It reduces the stress of developers to design database schema and applications. Data modeling is defined as arranging application data using acceptable data structuring patterns and is the primary component of the schema design in the document store. In addition, studies have continued examining NoSQL’s energy consumption pattern. But, our recent survey does not observe any energy-efficienct analysis for NoSQL schema. This work therefore designs alternative schemes using a particular combination of document store structuring patterns and analyzes storage criteria for everything. In NoSQL, the use of indexing and application-level joints is widely adopted. This article also compares performance and energy requirements for query processing with/without indexing, and application-level join operations and also helps to design query optimization.

Identification of artificially ripen mango using aroma and texture features

Conference

Title of PaperIdentification of artificially ripen mango using aroma and texture features

Proceeding Name2021 International Conference on Intelligent Technologies, CONIT 2021

PublisherIEEE

Page Number1-6

Published YearJune 2021

ISSN/ISBN No978-172818583-5

Indexed INScopus

Abstract

Mango is known as a king of fruit. It has a unique sweet taste, flavor, and nutritionally rich attributes. Therefore, it is beloved by all age groups of people. Looking at the high popularity of ripening mangoes, vendors are attracted to artificial ripening using hazardous chemicals like calcium carbide. Most governments have banned the use of calcium carbide. Unfortunately, the use of calcium carbide still exists as per several reports. Today, the public is being aware and cautious to avoid buying such artificially ripened mango. But, it is difficult for humans to differentiate an artificially ripe and naturally ripe mango and that too specifically for some species like Kesar by the human eye. This paper proposes a non-destructive approach to identify an artificially ripened Kesar mango. The first phase uses image features and a decision tree to classify mango into ripe, unripe, and partially ripe categories with 93% accuracy. The second phase discards unripe mango images and processes to identify artificially ripened or ripening mango using GLSM based image processing and an MQ3 aroma sensor.

Efficient Classification of True Positive and False Positive XSS and CSRF Vulnerabilities Reported by the Testing Tool

Conference

Title of PaperEfficient Classification of True Positive and False Positive XSS and CSRF Vulnerabilities Reported by the Testing Tool

Proceeding NameProceedings of Second International Conference on Computing, Communications, and Cyber-Security

PublisherSpringer

Author NameMonika Shah, Himani Lad

Page Number871-884

Published YearOctober 2020

ISSN/ISBN No978-981160732-5

Indexed INScopus

Abstract

Security testing is essential for website and web applications in current days. It is easy for an attacker to invade the security and do malicious activities through web applications if they are not properly protected against known attacks. General practice in web application before release is using testing tools to recognize the possible set of vulnerabilities, which can be true-positive or false-positive. Then the developer team will be asked to revise code to protect against true-positive vulnerabilities. For that, the testing team needs to classify each reported vulnerability into true-positive and false-positive individually, which is very time-consuming. This article suggests innovation in this practice to reduce the time of recognizing true-positive vulnerabilities. It presents a novel approach to classify reported multiple vulnerabilities of different attacks using a single script and in single go. These attacks should share common triggering events or testing process. Cross-Site Scripting (XSS) and Cross-Site Request Forgery (CSRF) attacks are chosen to illustrate the approach

On Performance Enhancement of Molecular Dynamics Simulation Using HPC Systems

Conference

Title of PaperOn Performance Enhancement of Molecular Dynamics Simulation Using HPC Systems

Proceeding NameProceedings of Second International Conference on Computing, Communications, and Cyber-Security

Author NameTejal Rathod, Monika Shah, Madhuri Bhavsar, Niraj Shah, Gaurang Raval

Page Number1031-1044

Published YearOctober 2020

ISSN/ISBN No978-981160732-5

Indexed INScopus

A Comprehensive Survey on Energy-Efficient Power Management Techniques

Journal

Journal NameProcedia Computer Science

Title of PaperA Comprehensive Survey on Energy-Efficient Power Management Techniques

PublisherElsevier

Volume Number167

Page Number1189-1199

Published YearJanuary 2020

ISSN/ISBN No18770509

Indexed INScopus

Design and simulation of single electron transistor based SRAM and its memory controller at room temperature

Journal

Journal NameInternational Journal of Integrated Engineering

Title of PaperDesign and simulation of single electron transistor based SRAM and its memory controller at room temperature

Volume Number11

Page Number186-195

Abstract

The terabytes of information available on the internet creates a severe demand of scalable information retrieval systems. Sparse Matrix Vector Multiplication (SpMV) is a well-known kernel for such computing applications in science and engineering world. This raises need of designing an efficient SpMV. Researchers are putting their continuous effort to optimize SpMV that deal with wide class of spa

A comprehensive survey on oceanography parameters for developing ocean wave displacement prediction system - *Best Paper

Journal

Journal NameJournal of Chemical and Pharmaceutical Sciences

The central idea presented in this paper is to show the architecture and working of an Operating System running over the network, thus leading to global computing. "PROS", as it is named, provides transparency meaning it would work same as a real operating system on the PC without need of static installation. PROS would load up on the user's PC irrespective of the location along with user’s

Niranjan Devashrayee

Design and Analysis of Low-Power High-Speed Shared Charge Reset Technique based Dynamic Latch Comparator

Journal

Journal NameMicroelectronics Journal, Elsevier Journals

Title of PaperDesign and Analysis of Low-Power High-Speed Shared Charge Reset Technique based Dynamic Latch Comparator

PublisherElsevier

Volume Number74

Page Number116-126

Published YearApril 2018

ISSN/ISBN No2226-2692

Indexed INScopus

Abstract

Circuit intricacy, high-speed, low-power, small area requirement, and high resolution are crucial factors for high-speed and low-power applications like analog-to-digital converters (ADCs). The delay analysis of classical dynamic latch comparators is presented to add more insight of their design parameters, which effects the performance parameter. In this research, a new architecture of dynamic latch comparator is presented, which is able to provide high-speed, consumes low-power and requires smaller die area. The proposed comparator benefits from a new shared charge logic based reset technique to achieve high-speed with low-power consumption. It is shown by simulation and analysis that the delay time is significantly reduced compared to a conventional dynamic latched comparator. The proposed circuit is designed and simulated in 90 nm CMOS technology. The results show that, for the proposed comparator, the delay is 51.7 ps and consumes only 33.62  μW power, at 1 V supply voltage and 1 GHz clock frequency. In addition, the proposed dynamic latch comparator has a layout size of 7.2μm × 8.1μm.

Purpose of Internet of Thing (IoT) is to carry each entity on the web, consequently creating tremendous measure of information that can crush network data transfer capacity. To provide cloud services in boundary of end user edge computing turned into promising fashion, to conquer such problem, from centralized computation to decentralized computation. Over the last one decade the advancement of Internet services has constrained outlook changes in the course of the monolithic architectures to Service Oriented Architecture (SOA) and thusly from SOA to microservices. So in this paper we will try to investigate the suitability of microservices architecture style in edge computing environment and determine some similarities in the goals of microservices architecture style and edge computing environment.

Detection and prevention mechanism for TTL field tampering form of DDoS attack in MANET’s

Journal

Journal NameInternational Journal of Computer Applications

Title of PaperDetection and prevention mechanism for TTL field tampering form of DDoS attack in MANET’s

PublisherFoundation of Computer Science

Volume Number975

Published YearJanuary 2015

ISSN/ISBN No2348-2281

Indexed INOthers

Review on Basic Clustering Techniques for Heterogeneous Wireless Sensor Networks

Journal

Journal NameInternational Journal of Scientific and Research Publications

Title of PaperReview on Basic Clustering Techniques for Heterogeneous Wireless Sensor Networks

Volume Number4

Page Number1-4

Published YearAugust 2014

ISSN/ISBN No2250-3153

Indexed INOthers

Smart Farming Based on IoT Edge Computing: Applying Machine Learning Models for Disease and Irrigation Water Requirement Prediction in Potato Crop Using Containerized Microservices

Book Chapter

Book NamePrecision Agriculture for Sustainability Use of Smart Sensors, Actuators, and Decision Support Systems

PublisherApple Academic and CRC Press

Author NameNitin Rathore, Anand Rajavat

Chapter TitleSmart Farming Based on IoT Edge Computing: Applying Machine Learning Models for Disease and Irrigation Water Requirement Prediction in Potato Crop Using Containerized Microservices

Published YearJuly 2023 (forthcoming)

ISSN/ISBN No971774913734

Indexed INScopus, Web of Science

Parita Oza

Do digital images tell the truth?

Book Chapter

Book NameDigital Image Security

PublisherCRC Press

Author NameA Bruno, P Oza, F Adedoyin, M Tliba, MA Kerkouri, A Sekhri, A Chetouani, M Gao

Page Number247-265

Chapter TitleDo digital images tell the truth?

Published YearMarch 2024

Indexed INScopus, Web of Science

Digital mammography dataset for breast cancer diagnosis research (DMID) with breast mass segmentation analysis

Journal

Journal NameBiomedical Engineering Letters

Title of PaperDigital mammography dataset for breast cancer diagnosis research (DMID) with breast mass segmentation analysis

PublisherSpringer

Volume Number14

Page Number317-330

Published YearMarch 2024

ISSN/ISBN No2093-9868

Indexed INScopus, Web of Science

Exploring the Benefits of Data Augmentation for Breast Cancer Classification using Transfer Learning

Book Chapter

Book NameWorld Conference on Information Systems for Business Management

PublisherSpringer Nature Singapore

Author NameAaditya Darakh, Aditya Shah, Parita Oza

Page Number509-520

Chapter TitleExploring the Benefits of Data Augmentation for Breast Cancer Classification using Transfer Learning

Published YearFebruary 2024

Indexed INScopus, Web of Science

Breast lesion classification from mammograms using deep neural network and test-time augmentation

Journal

Journal Name2024/2 Journal Neural Computing and Applications

Title of PaperBreast lesion classification from mammograms using deep neural network and test-time augmentation

PublisherSpringer

Volume Number36

Page Number2101-2117

Published YearFebruary 2024

Indexed INScopus, Web of Science

AI in breast imaging: Applications, challenges, and future research

Book Chapter

Book NameComputational intelligence and modelling techniques for disease detection in mammogram images

PublisherAcademic Press

Author NameParita Oza

Page Number39-54

Chapter TitleAI in breast imaging: Applications, challenges, and future research

Published YearJanuary 2024

Indexed INScopus, Web of Science

Social Distance Detection using Customized YOLOv4 (SDDYv4) Model

Journal

Journal NameInternational Journal of Computing and Digital Systems

Title of PaperSocial Distance Detection using Customized YOLOv4 (SDDYv4) Model

PublisherUniversity of Bahrain

Volume Number14

Page Number10481-10489

Published YearDecember 2023

Indexed INScopus

Evaluating the Igraph Community Detection Algorithms on Different Real Networks

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperEvaluating the Igraph Community Detection Algorithms on Different Real Networks

Volume Number24

Published YearJuly 2023

Indexed INScopus, Web of Science

Selection of best machine learning model to predict delay in passenger airlines

Journal

Journal NameIEEE Access

Title of PaperSelection of best machine learning model to predict delay in passenger airlines

Published YearJuly 2023

Indexed INScopus, Web of Science

Patch Extraction and Classifier for Abnormality Classification in Mammography Imaging

Book Chapter

Book NameLecture Notes in Networks and Systems , Third Congress on Intelligent Systems: Proceedings of CIS 2022

PublisherSpringer

Author NameParita Oza, Paawan Sharma, Samir Patel

Page Number1-9

Chapter TitlePatch Extraction and Classifier for Abnormality Classification in Mammography Imaging

Published YearMay 2023

ISSN/ISBN No978-981-19-9379-4

Indexed INScopus

Artificial Intelligence and Graph Theory Application for Diagnosis of Neurological Disorder Using fMRI

Book Chapter

Book NameLecture Notes in Electrical Engineering, Proceedings of International Conference on Recent Innovations in Computing: ICRIC 2022

PublisherSpringer

Author NameBansari Prajapati, Parita Oza, Smita Agrawal

Page Number41-56

Chapter TitleArtificial Intelligence and Graph Theory Application for Diagnosis of Neurological Disorder Using fMRI

Published YearMay 2023

ISSN/ISBN No978-981-19-9876-8

Indexed INScopus

CoviDistBand: IoT-Based Wearable Smart Band to Ensure Social Distancing

Book Chapter

Book NameRenewable Energy Optimization, Planning and Control: Proceedings of ICRTE 2022

PublisherSpringer

Author NameVraj Bhatt, Jaimin Topiwala, Smita Agrawal, Parita Oza

Page Number71-79

Chapter TitleCoviDistBand: IoT-Based Wearable Smart Band to Ensure Social Distancing

Published YearMarch 2023

ISSN/ISBN No978-981-19-8963-6

Data Encryption Approach Using Hybrid Cryptography and Steganography with Combination of Block Ciphers

Book Chapter

Book NameAdvancements in Smart Computing and Information Security

PublisherSpringer Nature

Author NameHet Shah, Parita Oza, Smita Agrawal

Page Number59-69

Chapter TitleData Encryption Approach Using Hybrid Cryptography and Steganography with Combination of Block Ciphers

Published YearJanuary 2023

Indexed INScopus

Sentiment Analysis of Customer Feedback and Reviews for Airline Services using Language Representation Model

Journal

Journal NameProcedia Computer Science

Title of PaperSentiment Analysis of Customer Feedback and Reviews for Airline Services using Language Representation Model

PublisherElsevier

Volume Number218

Page Number2459-2467

Published YearJanuary 2023

Indexed INScopus

Deep ensemble transfer learning-based framework for mammographic image classification

Journal

Journal NameThe Journal of Supercomputing

Title of PaperDeep ensemble transfer learning-based framework for mammographic image classification

PublisherSpringer

Published YearDecember 2022

Indexed INScopus, Web of Science

Transfer Learning Assisted Classification of Artefacts Removed and Contrast Improved Digital Mammograms

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperTransfer Learning Assisted Classification of Artefacts Removed and Contrast Improved Digital Mammograms

Volume Number23

Page Number115-127

Published YearOctober 2022

Indexed INScopus

Computer-Aided Breast Cancer Diagnosis: A Comparative Analysis of Breast Imaging Modalities and Mammogram Repositories.

Journal

Journal NameCurrent Medical Imaging

Title of PaperComputer-Aided Breast Cancer Diagnosis: A Comparative Analysis of Breast Imaging Modalities and Mammogram Repositories.

PublisherBentham Science Publishers

Volume Number19

Page Number456 - 468

Published YearAugust 2022

Indexed INScopus, Web of Science

A Transfer Representation Learning Approach for Breast Cancer Diagnosis from Mammograms using EfficientNet Models

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperA Transfer Representation Learning Approach for Breast Cancer Diagnosis from Mammograms using EfficientNet Models

Volume Number23

Page Number51-58

Published YearAugust 2022

Indexed INScopus

A Secure DBA Management System: A Comprehensive Study

Book Chapter

Book NameLecture Notes in Networks and Systems (Proceedings of Third International Conference on Computing, Communications, and Cyber-Security.)

PublisherSpringer

Author NameParita Oza

Chapter TitleA Secure DBA Management System: A Comprehensive Study

Published YearJuly 2022

Indexed INScopus

Concurrency Control in Distributed Database Systems: An In-Depth Analysis

Book Chapter

Book NameLecture Notes in Networks and Systems

PublisherSpringer

Author NameParita Oza

Chapter TitleConcurrency Control in Distributed Database Systems: An In-Depth Analysis

Published YearJuly 2022

Indexed INScopus

Towards automating irrigation: a fuzzy logic-based water irrigation system using IoT and deep learning

Journal

Journal NameModeling Earth Systems and Environment

Title of PaperTowards automating irrigation: a fuzzy logic-based water irrigation system using IoT and deep learning

Published YearJuly 2022

ISSN/ISBN No2363-6203

Indexed INScopus

Image Augmentation Techniques for Mammogram Analysis

Journal

Journal NameJournal of Imaging

Title of PaperImage Augmentation Techniques for Mammogram Analysis

PublisherMDPI

Volume Number8

Published YearMay 2022

ISSN/ISBN No2313-433X

Indexed INScopus, PubMed, Web of Science

Deep convolutional neural networks for computer-aided breast cancer diagnostic: a survey

Journal

Journal NameNeural Computing and Applications

Title of PaperDeep convolutional neural networks for computer-aided breast cancer diagnostic: a survey

PublisherSpringer London

Published YearNovember 2021

Indexed INScopus, Web of Science

Enhanced Secure ATM authentication using NFC Technology and Iris Verification

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperEnhanced Secure ATM authentication using NFC Technology and Iris Verification

Volume Number22

Page Number273-282

Published YearSeptember 2021

Indexed INScopus

A bottom-up review of image analysis methods for suspicious region detection in mammograms

Journal

Journal NameJournal of Imaging

Title of PaperA bottom-up review of image analysis methods for suspicious region detection in mammograms

Volume Number7

Published YearSeptember 2021

ISSN/ISBN No2313-433X

Indexed INScopus, Web of Science

A Comprehensive Study of Mammogram Classification Techniques

Book Chapter

Book NameTracking and Preventing Diseases with Artificial Intelligence

PublisherSpringer, Cham

Page Number217-238

Chapter TitleA Comprehensive Study of Mammogram Classification Techniques

Published YearJuly 2021

Indexed INScopus

Machine learning applications for computer-aided medical diagnostics

Book Chapter

Book NameLecture Notes in Networks and Systems (Proceedings of Second International Conference on Computing, Communications, and Cyber-Security)

PublisherSpringer, Singapore

Author NameParita Oza, Paawan Sharma, Samir Patel

Page Number377-392

Chapter TitleMachine learning applications for computer-aided medical diagnostics

Published YearMay 2021

ISSN/ISBN No978-981-16-0733-2

Indexed INScopus

Diabetes prediction using machine learning

Book Chapter

Book NameLecture Notes in Networks and Systems (Proceedings of Second International Conference on Computing, Communications, and Cyber-Security)

PublisherSpringer, Singapore

Author NameHarsh Patel, Parita Oza, Smita Agrawal

Page Number703-715

Chapter TitleDiabetes prediction using machine learning

Published YearMay 2021

Indexed INScopus

A drive through computer-aided diagnosis of breast cancer: a comprehensive study of clinical and technical aspects

Book Chapter

Book NameRecent Innovations in Computing

PublisherSpringer

Author NameParita Oza, Paawan Sharma, Samir Patel

Page Number233-249

Chapter TitleA drive through computer-aided diagnosis of breast cancer: a comprehensive study of clinical and technical aspects

Published YearMarch 2021

Indexed INScopus

AI Approaches for Breast Cancer Diagnosis: A Comprehensive Study

Conference

Title of PaperAI Approaches for Breast Cancer Diagnosis: A Comprehensive Study

Proceeding NameProceedings of International Conference on Innovative Computing and Communications

PublisherSpringer, Singapore

Author NameHarsh Patel, Parita Oza, Smita Agrawal

Year , VenueFebruary 2021 , Delhi

Page Number393-419

Indexed INScopus

Review of machine learning techniques in health care

Book Chapter

Book NameLecture Notes in Electrical Engineering (Proceedings of ICRIC 2019)

PublisherSpringer, Cham

Page Number103-111

Chapter TitleReview of machine learning techniques in health care

Published YearNovember 2019

ISSN/ISBN No978-3-030-29407-6

Indexed INScopus

Homomorphic Cryptography and Its Applications in Various Domains

Book Chapter

Book NameLecture Notes in Networks and Systems

PublisherSpringer

Page Number269-278

Chapter TitleHomomorphic Cryptography and Its Applications in Various Domains

Published YearNovember 2018

ISSN/ISBN No978-981-13-2324-9

Indexed INScopus

Encryption Algorithm using Rubik’s Cube Principle for Secure Transmission of Multimedia Files

Conference

Title of PaperEncryption Algorithm using Rubik’s Cube Principle for Secure Transmission of Multimedia Files

Proceeding Name3ICMRP2016Conferenceproceeding

PublisherResearch and Scientific Innovation Society

Year , VenueDecember 2016 , AMA, IIM-A Road, Ahmedabad

Page Number239-243

Indexed INOthers

Wearable live streaming gadget using Raspberry pi

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperWearable live streaming gadget using Raspberry pi

Volume Number7

Page Number69-75

Published YearMarch 2016

ISSN/ISBN No0973-7391

Indexed INUGC List

Performance Evaluation of Unicast and Multicast Routing in Wireless Ad-hoc Networks

Conference

Title of PaperPerformance Evaluation of Unicast and Multicast Routing in Wireless Ad-hoc Networks

Proceeding NameICCCCIT 2015 conference proceeding

OrganizationTECHNICAL RESEARCH ORGANISATION INDIA

Year , VenueJuly 2015 , Bhopal

Page Number1-3

ISSN/ISBN No978-93-85225-37-6

Indexed INOthers

Tracking Cancer Patients Medical History Using Wireless Emerging Technology: Near Field Communication

Journal

Journal NameInternational Journal of VLSI design & Communication Systems (VLSICS)

Title of PaperTracking Cancer Patients Medical History Using Wireless Emerging Technology: Near Field Communication

Volume Number6

Published YearFebruary 2015

ISSN/ISBN No0976 - 1527

Indexed INEBSCO

Performance Evaluation of Ad-Hoc on-Demand Distance Vector Routing Protocol and its Multi-Path Variant AOMDV

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperPerformance Evaluation of Ad-Hoc on-Demand Distance Vector Routing Protocol and its Multi-Path Variant AOMDV

Volume Number5

Page Number51-53

Published YearMarch 2014

ISSN/ISBN No0973-7391

Indexed INUGC List

Optimized Data Aggregation Protocol in WSN for Automation of water Sprinklers

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperOptimized Data Aggregation Protocol in WSN for Automation of water Sprinklers

Volume Number5

Page Number46-50

Published YearMarch 2014

ISSN/ISBN No0973-7391

Indexed INUGC List

A Comparative Study on MANET Routing Protocols

Journal

Journal NameInternational Journal of Computer Science and Technology

Title of PaperA Comparative Study on MANET Routing Protocols

Volume Number3

Page Number821-832

Published YearJuly 2012

ISSN/ISBN No0976-8491

Indexed INOthers

Pimal Khanpara

Toward the internet of things forensics: A data analytics perspective

Journal

Journal NameSecurity and Privacy

Title of PaperToward the internet of things forensics: A data analytics perspective

PublisherWiley Periodicals, Inc.

Volume Numbere306

Published YearMarch 2023

ISSN/ISBN No2475-6725

Indexed INWeb of Science, Others

The Evolution of Ad Hoc Networks for Tactical Military Communications: Trends, Technologies, and Case Studies

Conference

Title of PaperThe Evolution of Ad Hoc Networks for Tactical Military Communications: Trends, Technologies, and Case Studies

Proceeding NameProceedings of Third International Conference on Sustainable Expert Systems

PublisherSpringer, Singapore

Author NameZalak Patel, Pimal Khanpara, Sharada Valiveti & Gaurang Raval

Page Number331-346

Published YearFebruary 2023

ISSN/ISBN No2367-3389

Indexed INScopus, Others

Image-based Seat Belt Fastness Detection using Deep Learning

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperImage-based Seat Belt Fastness Detection using Deep Learning

Volume Number23

Page Number441-455

Published YearDecember 2022

ISSN/ISBN No1895-1767

Indexed INScopus, Web of Science, EBSCO

A context‐aware internet of things‐driven security scheme for smart homes

Journal

Journal NameSecurity and Privacy

Title of PaperA context‐aware internet of things‐driven security scheme for smart homes

PublisherWiley Periodicals, Inc.

Volume Numbere269

Published YearSeptember 2022

ISSN/ISBN No2475-6725

Indexed INWeb of Science

Graph Neural Network based Recommender System

Conference

Title of PaperGraph Neural Network based Recommender System

Proceeding NameProceedings of the Seventh International Conference on Communication and Electronics Systems (ICCES 2022)

PublisherIEEE

Author NameRachana Mehta, Kruti Lavingia, Pimal Khanpara, Vijay Dhulera

Page Number1377-1381

Published YearJune 2022

ISSN/ISBN No 978-1-6654-9634-6

Indexed INScopus

Blockchain-based E-Voting Technology: Opportunities and Challenges

Conference

Title of PaperBlockchain-based E-Voting Technology: Opportunities and Challenges

Proceeding NameProceedings of the Seventh International Conference on Communication and Electronics Systems (ICCES 2022)

PublisherIEEE

Author NamePimal Khanpara, Shivam Patel, Sharada Valiveti

Page Number855-861

Published YearJune 2022

ISSN/ISBN No 978-1-6654-9634-6

Indexed INScopus

Predicting Stock Market Trends using Random Forest: A Comparative Analysis

Conference

Title of PaperPredicting Stock Market Trends using Random Forest: A Comparative Analysis

Proceeding NameProceedings of the Seventh International Conference on Communication and Electronics Systems (ICCES 2022)

PublisherIEEE

Author NameKruti Lavingia, Pimal Khanpara, Rachana Mehta, Niket Kothari, Karan Parekh

Page Number1544-1550

Published YearJune 2022

ISSN/ISBN No978-1-6654-9634-6

Indexed INScopus

Robust and secure routing protocols for MANET-based internet of things systems—A survey

Book Chapter

Book NameEmergence of Cyber Physical System and IoT in Smart Automation and Robotics

PublisherSpringer

Author NameRajvi Trivedi, Pimal Khanpara

Page Number175-188

Chapter TitleRobust and secure routing protocols for MANET-based internet of things systems—A survey

Published YearMay 2021

ISSN/ISBN No978-3-030-66222-6

Indexed INScopus

Blockchain for industry 4.0: A comprehensive review

Journal

Journal NameIEEE Access

Title of PaperBlockchain for industry 4.0: A comprehensive review

PublisherIEEE

Volume Number8

Page Number79764-79800

Published YearApril 2020

ISSN/ISBN No2169-3536

Indexed INScopus, Web of Science, EBSCO

Abstract

Due to the proliferation of ICT during the last few decades, there is an exponential increase in the usage of various smart applications such as smart farming, smart healthcare, supply-chain & logistics, business, tourism and hospitality, energy management etc. However, for all the aforementioned applications, security and privacy are major concerns keeping in view of the usage of the open channel, i.e., Internet for data transfer. Although many security solutions and standards have been proposed over the years to enhance the security levels of aforementioned smart applications, but the existing solutions are either based upon the centralized architecture (having single point of failure) or having high computation and communication costs. Moreover, most of the existing security solutions have focussed only on few aspects and fail to address scalability, robustness, data storage, network latency, auditability, immutability, and traceability. To handle the aforementioned issues, blockchain technology can be one of the solutions. Motivated from these facts, in this paper, we present a systematic review of various blockchain-based solutions and their applicability in various Industry 4.0-based applications. Our contributions in this paper are in four fold. Firstly, we explored the current state-of-the-art solutions in the blockchain technology for the smart applications. Then, we illustrated the reference architecture used for the blockchain applicability in various Industry 4.0 applications. Then, merits and demerits of the traditional security solutions are also discussed in comparison to their countermeasures. Finally, we provided a comparison of existing blockchain-based security solutions using various parameters to provide deep insights to the readers about its applicability in various applications.

Additive manufacturing: concepts and technologies

Book Chapter

Book NameA Roadmap to Industry 4.0: Smart Production, Sharp Business and Sustainable Development

PublisherSpringer

Author NamePimal Khanpara, Sudeep Tanwar

Page Number171-185

Chapter TitleAdditive manufacturing: concepts and technologies

Published YearNovember 2019

ISSN/ISBN No978-3-030-14544-6

Indexed INScopus

Energy conservation in multimedia big data computing and the Internet of Things—A challenge

Book Chapter

Book NameMultimedia Big Data Computing for IoT Applications

PublisherSpringer

Author NamePimal Khanpara, Kruti Lavingia

Page Number37-57

Chapter TitleEnergy conservation in multimedia big data computing and the Internet of Things—A challenge

Published YearJuly 2019

ISSN/ISBN No978-981-13-8759-3

Indexed INScopus

A Survey on Security Issues in MANETs

Conference

Title of PaperA Survey on Security Issues in MANETs

OrganizationAET

Year , VenueJune 2018 , Mumbai

Survivability in MANETs

Journal

Journal NameInternational Journal of Advanced Research in Computer Engineering & Technology

Title of PaperSurvivability in MANETs

PublisherIJARCET

Volume Number7

Page Number7-10

Published YearJanuary 2018

Indexed INUGC List

Survey of Techniques Used for Tolerance of Flooding Attacks in DTN

Book Chapter

Book NameInformation and Communication Technology for Intelligent Systems

PublisherSpringer, Singapore

Page Number599-607

Chapter TitleSurvey of Techniques Used for Tolerance of Flooding Attacks in DTN

Published YearJanuary 2018

ISSN/ISBN No978-981-13-1742-2

Indexed INScopus, UGC List

Security in Mobile Ad Hoc Networks

Book Chapter

Book NameProceedings of International Conference on Communication and Networks

PublisherSpringer, Singapore

Author NamePimal Khanpara, Bhushan Trivedi

Page Number501-511

Chapter TitleSecurity in Mobile Ad Hoc Networks

Published YearApril 2017

ISSN/ISBN No978-981-10-2750-5

Indexed INScopus, UGC List

Abstract

Due to the proliferation of mobile devices, Mobile Ad hoc Networks (MANETs) are increasing in popularity. However, security of such networks is an important issue as MANETs are vulnerable to various attacks occurring at different layers of TCP/IP protocol suite. This paper focuses on the Network layer vulnerabilities as this layer is responsible for one of the basic MANET functions, routing.

A REVIEW ON FUZZY LOGIC BASED ROUTING IN AD HOC NETWORKS

Journal

Journal NameInternational Journal of Advanced Research in Engineering and Technology

Title of PaperA REVIEW ON FUZZY LOGIC BASED ROUTING IN AD HOC NETWORKS

PublisherIAEME

Volume Number5

Page Number75-81

Published YearMay 2014

Indexed INOthers

Routing in Ad Hoc Network Using Ant Colony Optimization

Book Chapter

Book NameCommunication and Networking

PublisherSpringer, Berlin, Heidelberg

Page Number393-404

Chapter TitleRouting in Ad Hoc Network Using Ant Colony Optimization

Published YearMarch 2011

ISSN/ISBN No978-3-642-17604-3

Indexed INScopus, UGC List

Abstract

The ad hoc networks have a dynamic topology and are infrastructure less. So it is required to implement a new network protocol for providing an efficient end to end communication based on TCP/IP structure. There is a need to re-define or modify the functions of each layer of TCP/IP model to provide end to end communication between nodes.

Pooja Chaturvedi

Machine Learning Based Approach for Traffic Rule Violation Detection

Conference

Title of PaperMachine Learning Based Approach for Traffic Rule Violation Detection

Proceeding NameIEEE 7th International Conference on Recent Advances and Innovations in Engineering (ICRAIE)

PublisherIEEE Xplore

Author NameK. Lavingia, M. Vaja, P. Chaturvedi and A. Lavingia

OrganizationNational Institute of Technology Surathkal

Year , VenueDecember 2022 , Surathkal

Page Number244-249

ISSN/ISBN No978-1-6654-8910-2

Indexed INScopus

Abstract

A Deep Learning Based Target Coverage Protocol for Edge Computing Enabled Wireless Sensor Networks

Book Chapter

Crop classification with Hyperspectral images : A transfer learning approach

Journal

Journal NameModeling Earth Systems and Environment

Title of PaperCrop classification with Hyperspectral images : A transfer learning approach

Page Number1 to 11

Published YearNovember 2022

ISSN/ISBN NoP - 02363-6203, E- 2363-6211

Indexed INScopus, Web of Science, Others

IoT based Ambient Assisted Living Technologies for Healthcare: Concepts and Design Challenges

Conference

Title of PaperIoT based Ambient Assisted Living Technologies for Healthcare: Concepts and Design Challenges

Author NameP Purohit, P Khanpara, U Patel, P Kathiria

Page Number111-116

Published YearNovember 2022

Indexed INScopus

Document Classification using Deep Neural Network with word embedding techniques

Journal

Journal NameInt. J. of Web Engineering and Technology

Title of PaperDocument Classification using Deep Neural Network with word embedding techniques

Volume Number17

Page Number203-22

Published YearSeptember 2022

ISSN/ISBN No1476-1289

Indexed INScopus, Others

Hyperspectral Image Classification using Transfer Learning

Book Chapter

Book NameLecture Notes in Networks and Systems

Author NameUsha Patel,Preeti Kathiria, Smit Patel

Page Number545-556

Chapter TitleHyperspectral Image Classification using Transfer Learning

Published YearAugust 2022

ISSN/ISBN Noe-ISSN 2367-3389, P-ISSN 2367-3370

Indexed INScopus

Fuzzy Logic Inference-Based Automated Water Irrigation System

Journal

Journal NameInternational Journal of Ambient Computing and Intelligence (IJACI)

Title of PaperFuzzy Logic Inference-Based Automated Water Irrigation System

Volume Number13

Page Number1 to 15

Published YearJuly 2022

ISSN/ISBN No1941-6245

Indexed INScopus, Web of Science, Others

Trend analysis and forecasting of publication activities by Indian computer science researchers during the period of 2010–23

Journal

Journal NameExpert Systems -Wiley

Title of PaperTrend analysis and forecasting of publication activities by Indian computer science researchers during the period of 2010–23

ISSN/ISBN NoISSN: 2278-3075

Indexed INScopus, Others

IoT Based Home Automation with Smart Fan and AC using NodeMCU

Book Chapter

Book NameLecture Notes in Electrical Engineering(LNEE)

Author NameRaj Desai, Abhishek Gandhi, Preeti Kathiria, Smita Agrawal and Parita Oza

Page Number197-207

Chapter TitleIoT Based Home Automation with Smart Fan and AC using NodeMCU

Published YearNovember 2019

ISSN/ISBN NoISBN- 978 3 030 29406 -9

Indexed INScopus

Smart Auditorium Automation System Based on Object Recognition

Journal

Journal NameInternational Journal of Recent Technology and Engineering (IJRTE)

Title of PaperSmart Auditorium Automation System Based on Object Recognition

Volume NumberVolume-8 issue -4

Page Number11305-11310

Published YearNovember 2019

ISSN/ISBN No2277-3878(Online)

Indexed INScopus, Others

Study of Different Document Representation Models for Finding Phrase Based Similarity.

Journal

Journal Namesmart innovation, systems and technologies - Springer

Title of PaperStudy of Different Document Representation Models for Finding Phrase Based Similarity.

Volume Number106

Page Number455-464

Published YearDecember 2018

ISSN/ISBN No21903018

Indexed INScopus

Study of Different Document Representation Models for Finding Phrase Based Similarity.

Journal

Journal Namesmart innovation, systems and technologies - Springer

Title of PaperStudy of Different Document Representation Models for Finding Phrase Based Similarity.

PublisherSpringer

Volume Number1

Page Number455-464

Published YearDecember 2018

ISSN/ISBN No21903018

Indexed INScopus, Others

Study of Various Methods Used in Reverse Engineering

Journal

Journal NameInternational Journal of Research in Electronics AND Computer Engineering

Title of PaperStudy of Various Methods Used in Reverse Engineering

Volume Number6

Page Number1457-1459

Published YearJune 2018

ISSN/ISBN No2393-9028

Indexed INOthers

IoT Based approach for Controlling Electrical Peripheral Devices of Auditorium

Journal

Journal NameInternational Journal of Advanced Research in Computer Science

Title of PaperIoT Based approach for Controlling Electrical Peripheral Devices of Auditorium

Volume NumberVolume 8, No. 5,

Page Number2777-2781

Published YearJune 2017

ISSN/ISBN No0976-5697

Indexed INEBSCO, Others

Web Crawler : Review of Different Types of Web Crawler, Its Issues, Applications and Research Opportunities

Journal

Journal NameInternational Journal of Advanced Research in Computer Science

Title of PaperWeb Crawler : Review of Different Types of Web Crawler, Its Issues, Applications and Research Opportunities

Volume NumberVolume 8, No. 3

Page Number1199-1202

Published YearApril 2017

ISSN/ISBN No0976-5697

Indexed INEBSCO, Others

Performance evaluation of counting words from files using OpenMP

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperPerformance evaluation of counting words from files using OpenMP

Volume NumberVolume 7 No. 1

Page Number59-63

Published YearMarch 2016

ISSN/ISBN No0973-7391

Indexed INIndian citation Index, Others

A NAIVE METHOD FOR ONTOLOGY CONSTRUCTION

Journal

Journal NameInternational Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI)

Title of PaperA NAIVE METHOD FOR ONTOLOGY CONSTRUCTION

Volume NumberVol.5, No.1

Page Number53-62

Published YearFebruary 2016

ISSN/ISBN No2321–404X

Indexed INIndian citation Index, Others

A Geo-Location based Mobile Service that Dynamically Locates and Notifies the nearest Blood Donors for Blood Donation during Medical Emergencies

Journal

Journal NameInternational Journal of Computer Applications

Title of PaperA Geo-Location based Mobile Service that Dynamically Locates and Notifies the nearest Blood Donors for Blood Donation during Medical Emergencies

Volume NumberVolume 88 – No.3

Page Number34-39

Published YearFebruary 2014

ISSN/ISBN No0975 – 8887

Indexed INEBSCO

Priyank Thakkar

Scalable clustering for EO data using efficient raster representation

Journal

Journal NameMultimedia Tools and Applications

Title of PaperScalable clustering for EO data using efficient raster representation

PublisherSpringer US

Volume Number82

Page Number12303–12319

Published YearMarch 2023

ISSN/ISBN No1573-7721

Indexed INScopus

Identification of handwritten Gujarati alphanumeric script by integrating transfer learning and convolutional neural networks

Journal

Journal NameSadhana

Title of PaperIdentification of handwritten Gujarati alphanumeric script by integrating transfer learning and convolutional neural networks

PublisherSpringer India

Volume Number47

Page Number653-674

Published YearJune 2022

ISSN/ISBN No0973-7677

Indexed INScopus

Addressing Item Cold Start Problem in Collaborative Filtering-Based Recommender Systems Using Auxiliary Information

Conference

Title of PaperAddressing Item Cold Start Problem in Collaborative Filtering-Based Recommender Systems Using Auxiliary Information

Proceeding NameIOT with Smart Systems: Proceedings of ICTIS 2022, Volume 2

PublisherSpringer Nature Singapore

Author NameRonakkumar Patel, Priyank Thakkar

Year , VenueApril 2022 , Ahmedabad

Page Number133-142

ISSN/ISBN No978-981-19-3575-6

Indexed INScopus

A dynamic scenario‐driven technique for stock price prediction and trading

Journal

Journal NameJournal of Forecasting

Title of PaperA dynamic scenario‐driven technique for stock price prediction and trading

PublisherWiley

Volume Number41

Page Number653-674

Published YearApril 2022

ISSN/ISBN No1099-131X

Indexed INScopus, Web of Science

Text Summarization Approaches Under Transfer Learning and Domain Adaptation Settings—A Survey

Conference

Title of PaperText Summarization Approaches Under Transfer Learning and Domain Adaptation Settings—A Survey

Proceeding NameComputational Intelligence and Data Analytics: Proceedings of ICCIDA 2022

PublisherSpringer Nature Singapore

Author NameMeenaxi Tank, Priyank Thakkar

OrganizationVasavi College of Enginnering

Year , VenueJanuary 2022 , Hyderabad

Page Number73-88

ISSN/ISBN No978-981-19-3391-2

Indexed INScopus

Predicting stock price movement using a stack of multi-sized filter maps and convolutional neural networks

Journal

Journal NameInternational Journal of Computational Science and Engineering

Title of PaperPredicting stock price movement using a stack of multi-sized filter maps and convolutional neural networks

PublisherInderscience Publishers (IEL)

Volume Number25

Page Number22-33

Published YearJanuary 2022

ISSN/ISBN No1742-7193

Indexed INScopus, Web of Science, Others

Image Denoising with Self-adaptive Multi-UNET Valve

Conference

Title of PaperImage Denoising with Self-adaptive Multi-UNET Valve

Proceeding NameSoft Computing for Problem Solving, Advances in Intelligent Systems and Computing

PublisherSpringer

Author NameYash Thesia, Meera Suthar, Tirth Pandya, Priyank Thakkar

OrganizationIIT Indore

Year , VenueDecember 2020 , IIT Indore (Online)

Page Number647-659

ISSN/ISBN No2194-5365

Indexed INOthers

Next-generation artificial intelligence techniques for satellite data processing

Book Chapter

Book NameArtificial Intelligence Techniques for Satellite Image Analysis

PublisherSpringer, Cham

Author NameNeha Sisodiya, Nitant Dube, Priyank Thakkar

Page Number235-254

Chapter TitleNext-generation artificial intelligence techniques for satellite data processing

Published YearJanuary 2020

ISSN/ISBN No978-3-030-24178-0

Indexed INScopus

Extreme Weather Prediction Using 2-Phase Deep Learning Pipeline

Conference

Title of PaperExtreme Weather Prediction Using 2-Phase Deep Learning Pipeline

Proceeding NameComputer Vision and Image Processing, Communications in Computer and Information Science

PublisherSpringer, Singapore

Author NameVidhey Oza, Yash Thesia, Dhananjay Rasalia, Priyank Thakkar, Nitant Dube & Sanjay Garg

Year , VenueSeptember 2019 , Jaipur

Page Number266-282

ISSN/ISBN No978-981-15-4015-8

Indexed INScopus

Combining user-based and item-based collaborative filtering using machine learning

Conference

Title of PaperCombining user-based and item-based collaborative filtering using machine learning

Proceeding NameInformation and Communication Technology for Intelligent Systems, Smart Innovation, Systems and Technologies

PublisherSpringer, Singapore

Author NamePriyank Thakkar, Krunal Varma, Vijay Ukani, Sapan Mankad & Sudeep Tanwar

Year , VenueApril 2018 , Ahmedabad

Page Number173-180

ISSN/ISBN No978-981-13-1747-7

Indexed INScopus

Software Defined Network-Based Vehicular Adhoc Networks for Intelligent Transportation System: Recent Advances and Future Challenges

Conference

Title of PaperSoftware Defined Network-Based Vehicular Adhoc Networks for Intelligent Transportation System: Recent Advances and Future Challenges

Proceeding NameInternational Conference on Futuristic Trends in Network and Communication Technologies

PublisherSpringer, Singapore

Page Number325-337

Published YearFebruary 2018

Indexed INScopus

Outcome fusion-based approaches for user-based and item-based collaborative filtering

Conference

Title of PaperOutcome fusion-based approaches for user-based and item-based collaborative filtering

Proceeding NameInformation and Communication Technology for Intelligent Systems, Smart Innovation, Systems and Technologies

PublisherSpringer, Singapore

Author NamePriyank Thakkar, Krunal Varma, Vijay Ukani

Year , VenueMarch 2017 , Ahmedabad

Page Number127-135

ISSN/ISBN No978-3-319-63645-0

Indexed INScopus

Personalized Resource Recommendations using Learning from Positive and Unlabeled Examples

Journal

Journal NameNirma University Journal of Engineering and Technology

Title of PaperPersonalized Resource Recommendations using Learning from Positive and Unlabeled Examples

PublisherNirma University

Volume Number5

Page Number12-20

Published YearAugust 2016

ISSN/ISBN No2231-2870

Indexed INOthers

Predicting stock market index using fusion of machine learning techniques

Journal

Journal NameExpert Systems with Applications

Title of PaperPredicting stock market index using fusion of machine learning techniques

PublisherElsevier

Volume Number42

Page Number2162-2172

Published YearMarch 2015

ISSN/ISBN No0957-4174

Indexed INScopus, UGC List

Predicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques

Journal

Journal NameExpert Systems with Applications

Title of PaperPredicting stock and stock price index movement using trend deterministic data preparation and machine learning techniques

PublisherElsevier

Volume Number42

Page Number259-268

Published YearJanuary 2015

ISSN/ISBN No0957-4174

Indexed INScopus, UGC List

Conference

Title of PaperBig data analytics architecture for agro advisory system

Proceeding NameHigh Performance Computing Workshops (HiPCW)

PublisherIEEE

Published YearDecember 2016

Indexed INScopus

ICT Interventions to Improve the Performance of Canal Irrigation Sector in India

Conference

Journal

Journal NameInternational Journal of Computer Applications,Special issues on IP Multimedia Communications

Title of PaperLoad Balancing in Distributed System using Genetic Algorithm

Published YearJanuary 2011

Indexed INOthers

Rachana Mehta

A Secure Mechanism for Safeguarding Cloud Infrastructure

Conference

Title of PaperA Secure Mechanism for Safeguarding Cloud Infrastructure

Proceeding NameAdvancements in Smart Computing and Information Security: First International Conference, ASCIS 2022, Part II

PublisherSpringer Nature

Author NameKhare Pratyush, Vivek Kumar Prasad, Rachana Mehta, Madhuri Bhavsar

Page Number144-158

Published YearJanuary 2023

Indexed INScopus

Review of Crop Yield Estimation using Machine Learning and Deep Learning Techniques

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperReview of Crop Yield Estimation using Machine Learning and Deep Learning Techniques

Volume Number23

Page Number59-80

Published YearAugust 2022

Predicting Stock Market Trends using Random Forest: A Comparative Analysis

Conference

Title of PaperPredicting Stock Market Trends using Random Forest: A Comparative Analysis

Proceeding Name2022 7th International Conference on Communication and Electronics Systems (ICCES)

PublisherIEEE

Author NameKruti Lavingia, Pimal Khanpara, Rachana Mehta, Karan Patel, Niket Kothari

Page Number1544-1550

Published YearJune 2022

Indexed INScopus

Risk Assessment and Management using Machine Learning Approaches

Conference

Title of PaperRisk Assessment and Management using Machine Learning Approaches

Proceeding Name2022 International Conference on Applied Artificial Intelligence and Computing (ICAAIC)

PublisherIEEE

Author NameSmita Darandale, Rachana Mehta

Published YearJune 2022

Indexed INScopus

Graph Neural Network based Recommender System

Conference

Title of PaperGraph Neural Network based Recommender System

Proceeding Name2022 7th International Conference on Communication and Electronics Systems (ICCES)

PublisherIEEE

Author NameRachana Mehta, Kruti Lavingia, Pimal Khanpara, Vijay Dulera

Page Number1377-1381

Published YearJune 2022

Journal

Journal NameInternational Journal of Business Intelligence and Data Mining

Title of PaperEvolution of singular value decomposition in recommendation systems: a review

PublisherInderscience Publishers

Volume NumberVol.14 No.4

Page Number20

Published YearApril 2019

Indexed INScopus

A review on matrix factorization techniques in recommender systems

Conference

Title of PaperA review on matrix factorization techniques in recommender systems

Proceeding Name2nd International Conference on Communication Systems, Computing and IT Applications (CSCITA)

PublisherIEEE

Author NameRachana Mehta, Keyur Rana

Year , VenueApril 2017 , Mumbai, India

Page Number4

ISSN/ISBN No978-1-5090-4381-1

Indexed INScopus

An empirical analysis on SVD based recommendation techniques

Conference

Title of PaperAn empirical analysis on SVD based recommendation techniques

Proceeding NameInnovations in Power and Advanced Computing Technologies (i-PACT)

PublisherIEEE

Author NameRachana Mehta, Keyur Rana

Year , VenueApril 2017 , Vellore, India

Page Number7

ISSN/ISBN No978-1-5090-5682-8

Indexed INScopus

Rajan Datt

Student Attendance Management SystemUsing Fingerprint Scanner

Journal

Journal NameInternational Journal of Pure and Applied Mathematics

Title of PaperStudent Attendance Management SystemUsing Fingerprint Scanner

Volume Number119

Page Number2273-2277

Published YearJune 2018

Abstract

in order to identify person uniquely various things are used such as iris, lip print, fingerprint. In this paper we have developed Student Attendance Management System which is used to identify the students uniquely using their Fingerprints. For the development of this system we have used Raspberry Pi 3, Serial 16x2 Serial LCD and Fingerprint Scanner tools. By using this we have developed system which isstoring information of the student, verifying detail and generate report for the future use. During the attendance verification student keep his finger against the scanner and system will find whether the record is existing in the database or not, display proper message. We have also test system with various test case and found good results. By using this system teacher can save their time and increase accuracy in the results.

DATA EXCHANGE MODEL USING WEB SERVICE FOR HEROGENEOUS DATABASES

Journal

Journal NameINTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN ENGINEERING AND TECHNOLOGY (IJARET)

Title of PaperDATA EXCHANGE MODEL USING WEB SERVICE FOR HEROGENEOUS DATABASES

PublisherIAEME

Volume Number6

Page Number107-111

Published YearApril 2015

ISSN/ISBN No0976 - 6499

Indexed INUGC List

Abstract

In this paper, we have purpose method to exchange the data between the various databases that are not having a same formats, due to the heterogeneous structure of the databases. Now in the information technology field there is fast development is there, due to that people are using different network, operating system and applications of heterogeneous platforms. So in order to sharing of information between the various databases we have purposed model using web service to exchange the data between the heterogeneous databases. This model is used to exchange data of various databases using some functions of databases, SOAP, XML, WSDL and UDDI.

Efficient Technique for FingerPrint Recognition

Journal

Journal NameInt. J. of Data Modeling and Knowledge Management

Title of PaperEfficient Technique for FingerPrint Recognition

PublisherMind Reader Publications

Volume Number1

Page Number45-50

Published YearDecember 2011

METHODOLOGY FOR DATA TRANSFER WITH ATTACHMENT USING WEB SERVICE

Journal

Journal NameINTERNATIONAL JOURNAL OF EMERGING TECHNOLOGIES AND APPLICATIONS IN ENGINEERING, TECHNOLOGY AND SCIENCES

Title of PaperMETHODOLOGY FOR DATA TRANSFER WITH ATTACHMENT USING WEB SERVICE

Volume Number4

Page Number409-411

Published YearJuly 2011

ISSN/ISBN No0974-3588

Abstract

Web service is supporting very simple requests with simple parameters to fully supporting modern, object-oriented languages. XML-RPC, arguably one of the earliest forms of Web services, only supported simple types -- strings, integers, Boolean etc. SOAP took this one step further with its encoding rules for object. In this paper we are going describe how binary data is transfer using web service. Binary data can be useful in many security applications to encrypt a data, multimedia application to work with image, movies, music and for some engineering application to represent data efficiently.

Rajesh Gupta

Classification of Potentially Hazardous Asteroids Using Supervised Quantum Machine Learning

Journal

Journal NameIEEE Access

Internet of Things (IoT) has evolved many day-to-day objects into smart objects, which humans can control when they are connected via Internet. Its practical implementation came into existence a few years back. Since the advent of IoT, it has tackled many challenges such as management, tracking, observation, etc. It has contributed to various fields such as Healthcare 4.0, smart grid, smart agriculture, Intelligent Transportation Systems (ITS), smart cities, smart homes, smart cars, and many more. It has applications through almost all domains, but the question arises: the performance evaluating parameters about specific IoT applications to consider to detect flaws in it. As per literature, there exist no such article helps beginners in selecting performance evaluation parameters for IoT-enabled applications. Motivated from the aforementioned facts, this paper presents a survey on performance evaluation metrics’ systematic study for various IoT applications. We then graphically present the comparison of multiple parameters of domains security, energy efficiency, data storage, and network performance. From the analysis, we can infer that, in the smart city, latency is the most usable parameter, i.e., 77%. In contrast, in Healthcare 4.0, equal importance is given to latency and network bandwidth, which is 50%. Also, in Industry 4.0, scalability is the most opted performance parameter by the researchers, which is 100%. The smart grid application uses latency and delay are the most valuable parameters, i.e., 60%.

LEAF: A Federated Learning-Aware Privacy Preserving Framework for Healthcare Ecosystem

Journal

Journal NameIEEE Transactions on Network and Service Management

Title of PaperLEAF: A Federated Learning-Aware Privacy Preserving Framework for Healthcare Ecosystem

PublisherIEEE

Page Number1-13

Published YearJune 2023

ISSN/ISBN No1932-4537

Indexed INScopus, Web of Science

Abstract

Over the last decades, the healthcare industry has been revolutionized like anything, especially after the Covid-19 surge. Various artificial intelligence approaches have also been explored during this era for their applicability in healthcare. However, traditional AI techniques and algorithms are prone to overfitting with minimum robustness to unseen or untrained data. So, there is a requirement for new techniques which can counterfeit the issues mentioned earlier. Federated learning (FL) can help to make specific AI services for the network of hospitals with less overfitting and more robust modules. However, with the inclusion of FL, the problem related to user privacy is the biggest challenge, making using FL in the real world a grand challenge. Most solutions presented in the literature used blockchain technology to mitigate the issues mentioned earlier. However, it prevents third-party systems from penetrating the decision process, but the network devices can access shared data. Moreover, blockchain implementation requires new paradigms and infrastructure with an additional overhead cost. Motivated by these facts, the paper presents a limited access encryption algorithm incorporating FL (LEAF) framework, i.e., an encryption technique that solves privacy issues with the help of edge-enabled AI models. The proposed LEAF framework preserves user privacy and minimizes overhead costs. The authors have evaluated the performance of the LEAF framework using extensive simulations and achieved superior results. The achieved accuracy of the proposed LEAF framework is 3% more than that of the traditional centralized and FL-based systems advantages without compromising user privacy. In the best scenario, the proposed framework’s encryption process also compresses the data size by 4-5 times.

An Improved Dense CNN Architecture for Deepfake Image Detection

Journal

Journal NameIEEE Access

Title of PaperAn Improved Dense CNN Architecture for Deepfake Image Detection

PublisherIEEE

Volume Number11

Page Number22081 - 22095

Published YearMarch 2023

ISSN/ISBN No2169-3536

Indexed INScopus, Web of Science

Abstract

Recent advancements in computer vision processing need potent tools to create realistic deepfakes. A generative adversarial network (GAN) can fake the captured media streams, such as images, audio, and video, and make them visually fit other environments. So, the dissemination of fake media streams creates havoc in social communities and can destroy the reputation of a person or a community. Moreover, it manipulates public sentiments and opinions toward the person or community. Recent studies have suggested using the convolutional neural network (CNN) as an effective tool to detect deepfakes in the network. But, most techniques cannot capture the inter-frame dissimilarities of the collected media streams. Motivated by this, this paper presents a novel and improved deep-CNN (D-CNN) architecture for deepfake detection with reasonable accuracy and high generalizability. Images from multiple sources are captured to train the model, improving overall generalizability capabilities. The images are re-scaled and fed to the D-CNN model. A binary-cross entropy and Adam optimizer are utilized to improve the learning rate of the D-CNN model. We have considered seven different datasets from the reconstruction challenge with 5000 deepfake images and 10000 real images. The proposed model yields an accuracy of 98.33% in AttGAN, [Facial Attribute Editing by Only Changing What You Want (AttGAN)] 99.33% in GDWCT,[Group-wise deep whitening-and-coloring transformation (GDWCT)] 95.33% in StyleGAN, 94.67% in StyleGAN2, and 99.17% in StarGAN [A GAN capable of learning mappings among multiple domains (StarGAN)] real and deepfake images, that indicates its viability in experimental setups.

EmReSys: AI-based Efficient Employee Ranking and Recommender System for Organizations

Conference

Journal

Abstract

Plagiarism is stealing information or idea from someone without giving proper acknowledgement. Currently plagiarism is increasing in different fields like education, industry. There is need to prevent plagiarism. There are four types of stylometric features available namely: lexical, syntactic, semantic, content specific. In this paper we have added three new features for detecting plagiarism namely noun, adjective and rhyming words. For calculating these features, we have used our own Marathi text corpus. These features will be useful for detecting plagiarism and linguistic researchers.

Measuring Author Impression Using Cosine Similarity Algorithm

Journal

Journal

Journal NameInternational Journal of Computer Applications

Title of PaperA Review on Plagiarism Detection Tools

PublisherIJCA

Volume NumberVolume 125 No11

Published YearSeptember 2015

ISSN/ISBN No0975 8887

Indexed INOthers

Abstract

Plagiarism has become an increasingly serious problem in the academic world. It is aggravated by the easy access to and the ease of cutting and pasting from a wide range of materials available on the internet. It constitutes academic theft - the offender has 'stolen' the work of others and presented the stolen work as if it were his or her own. It goes to the integrity and honesty of a person. It stifles creativity and originality, and defeats the purpose of education The plagiarism is a widespread and growing problem in the academic process. The traditional manual detection of plagiarism by human is difficult, not accurate, and time consuming process as it is difficult for any person to verify with the existing data. The main purpose of this paper is to present existing tools about in regards with plagiarism detection. Plagiarism detection tools are useful to the academic community to detect plagiarism of others and avoid such unlawful activity. This paper describes some of the plagiarism detection tools available for plagiarism checking and types of plagiarism.

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperConcolla – A Smart Emotion-Based Music Recommendation System For Drivers

Proceeding NameLecture Notes in Electrical Engineering

Author NameJigna Patel, Jitali Patel, Rupal A. Kapdi

OrganizationCyber Security Research Lab

Year , VenueJuly 2023 , Ghaziabad

Indexed INScopus

Interpretability of Segmentation and Overall Survival for Brain Tumors

Book Chapter

Book NameExplainable AI in Healthcare Unboxing Machine Learning for Biomedicine

PublisherCRC Press, Taylor and Francis Group

Author NameRupal A. Kapdi, Snehal Rajput, Monehdra Roy, Mehul S. Raval

Page Number111-130

Chapter TitleInterpretability of Segmentation and Overall Survival for Brain Tumors

Published YearJuly 2023

ISSN/ISBN No9781003333425

Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine

Book

PublisherCRC Press, Taylor and Francis Group

Published YearJuly 2023

ISSN/ISBN No9781003333425

Abstract

This book combines technology and the medical domain. It covers advances in computer vision (CV) and machine learning (ML) that facilitate automation in diagnostics and therapeutic and preventive health care. The special focus on eXplainable Artifi cial Intelligence (XAI) uncovers the black box of ML and bridges the semantic gap between the technologists and the medical fraternity. Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine intends to be a premier reference for practitioners, researchers, and students at basic, intermediary levels and expert levels in computer science, electronics and communications, information technology, instrumentation and control, and electrical engineering. This book will benefi t readers in the following ways: • Explores state of art in computer vision and deep learning in tandem to develop autonomous or semi-autonomous algorithms for diagnosis in health care • Investigates bridges between computer scientists and physicians being built with XAI • Focuses on how data analysis provides the rationale to deal with the challenges of healthcare and making decision-making more transparent • Initiates discussions on human-AI relationships in health care • Unites learning for privacy preservation in health care

Interpretable machine learning model to predict survival days of malignant brain tumor patients

Journal

Journal NameMachine Learning: Science and Technology

Title of PaperInterpretable machine learning model to predict survival days of malignant brain tumor patients

PublisherIOP

Volume Number4

Page Number2

Published YearMay 2023

ISSN/ISBN No2632-2153

Indexed INScopus, Web of Science

Abstract

An artificial intelligence (AI) model’s performance is strongly influenced by the input features. Therefore, it is vital to find the optimal feature set. It is more crucial for the survival prediction of the glioblastoma multiforme (GBM) type of brain tumor. In this study, we identify the best feature set for predicting the survival days (SD) of GBM patients that outrank the current state-of-the-art methodologies. The proposed approach is an end-to-end AI model. This model first segments tumors from healthy brain parts in patients’ MRI images, extracts features from the segmented results, performs feature selection, and makes predictions about patients’ survival days (SD) based on selected features. The extracted features are primarily shape-based, location-based, and radiomics-based features. Additionally, patient metadata is also included as a feature. The selection methods include recursive feature elimination, permutation importance (PI), and finding the correlation between the features. Finally, we examined features’ behavior at local (single sample) and global (all the samples) levels. In this study, we find that out of 1265 extracted features, only 29 dominant features play a crucial role in predicting patients’ SD. Among these 29 features, one is metadata (age of patient), three are location-based, and the rest are radiomics features. Furthermore, we find explanations of these features using post-hoc interpretability methods to validate the model’s robust prediction and understand its decision. Finally, we analyzed the behavioral impact of the top six features on survival prediction, and the findings drawn from the explanations were coherent with the medical domain. We find that after the age of 50 years, the likelihood of survival of a patient deteriorates, and survival after 80 years is scarce. Again, for location-based features, the SD is less if the tumor location is in the central or back part of the brain. All these trends derived from the developed AI model are in sync with medically proven facts. The results show an overall 33% improvement in the accuracy of SD prediction compared to the top-performing methods of the BraTS-2020 challenge.

THREE CLASS CLASSIFICATION OF ALZHEIMER’S DISEASE USING DEEP NEURAL NETWORKS

Journal

Journal NameCurrent Medical Imaging

Title of PaperTHREE CLASS CLASSIFICATION OF ALZHEIMER’S DISEASE USING DEEP NEURAL NETWORKS

PublisherBentham Science

Volume Number19

Page Number855-864

Published YearMarch 2023

ISSN/ISBN No1875-6603

Indexed INScopus, PubMed, Web of Science

Abstract

IMAGE-BASED SEAT BELT FASTNESS DETECTION USING DEEP LEARNING

Journal

Journal NameSCALABLE COMPUTING: PRACTICE AND EXPERIENCE

Title of PaperIMAGE-BASED SEAT BELT FASTNESS DETECTION USING DEEP LEARNING

PublisherUniversitatea de vest

Volume Number23

Page Number441-455

Published YearDecember 2022

ISSN/ISBN No1895-1767

Indexed INScopus

YOGA POSE ESTIMATION USING MACHINE LEARNING

Conference

Title of PaperYOGA POSE ESTIMATION USING MACHINE LEARNING

PublisherFOURTH INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATIONS AND CYBER SECURITY (IC4S-2022)

Author NameIshika Shah, Greeva Khant, Jitali Patel, Jigna Patel, Rupal A. Kapdi

OrganizationKRISHNA ENGINEERING COLLEGE, GHAZIABAD

Year , VenueDecember 2022 , KRISHNA ENGINEERING COLLEGE, GHAZIABAD

Page Number1-6

Indexed INScopus

SURVIVAL PREDICTION OF MALIGNANT BRAIN TUMOR PATIENTS

Conference

Title of PaperSURVIVAL PREDICTION OF MALIGNANT BRAIN TUMOR PATIENTS

Proceeding NameRECENT AND FUTURE TRENDS IN SMART ELECTRONICS SYSTEM AND MANUFACTURING

OrganizationSYMBIOSIS INSTITUTE OF TECHNOLOGY, PUNE

Year , VenueDecember 2022 , SYMBIOSIS INSTITUTE OF TECHNOLOGY, PUNE

Page Number1-11

Indexed INScopus

An Optimized Search-Enabled Hotel Recommender System

Conference

Title of PaperAn Optimized Search-Enabled Hotel Recommender System

OrganizationCentral University of Jammu, J & K

Published YearMay 2022

Indexed INScopus

Brain Tumor Segmentation using Fully Convolution Neural Network

Conference

Title of PaperBrain Tumor Segmentation using Fully Convolution Neural Network

OrganizationCentral University of Jammu, J & K

Published YearMay 2022

Indexed INScopus

VeDrishti: Big Data doctor with visionary emotion detection system

Conference

Title of PaperVeDrishti: Big Data doctor with visionary emotion detection system

OrganizationDepartment of Computer Applications and Department of Computer Science, Kattankulathur

Published YearFebruary 2022

Indexed INScopus

Big data Warehouse in Healthcare-Opportunities and Challenges

Conference

Title of PaperBig data Warehouse in Healthcare-Opportunities and Challenges

Author NameJigna S. Patel, Jitali Patel, Rupal A. Kapdi

OrganizationDepartment of Computer Applications and Department of Computer Science, Kattankulathur

Published YearFebruary 2022

Indexed INScopus

Early Onset Alzheimer Disease Classification using Convolution Neural Network

Conference

Title of PaperEarly Onset Alzheimer Disease Classification using Convolution Neural Network

Proceeding NameSmart Innovation, Systems and Technologies (SIST) Series

PublisherSpringer

Author NameHappy Ramani, Rupal Kapdi

OrganizationAditya Institute of Technology and Management

Year , VenueDecember 2021 , AITAM, Aandhra Pradesh, India

Indexed INScopus

3D Semantic Segmentation of Brain Tumor for Overall Survival Prediction

Journal

Journal NameLecture Notes in Computer Science

Title of Paper3D Semantic Segmentation of Brain Tumor for Overall Survival Prediction

PublisherSpringer

Volume Number12659

Page Number215-227

Published YearMarch 2021

ISSN/ISBN No1611-3349 / 978-3-030-72087-2

Indexed INScopus

Abstract

Journal NameAdvances in Intelligent Systems and Computing

Title of PaperBrain Tumor Segmentation Using K-means–FCM Hybrid Technique

PublisherSpringer

Volume Number696

Published YearMay 2018

ISSN/ISBN No2194-5357

Indexed INScopus, UGC List

Abstract

Automatic brain tumor segmentation and detection is always very challenging and difficult task with respect to accuracy which is more important as brain surgery is a critical and complicated process. The medical professional can interpret magnetic resonance images (MRI), but this task is time-consuming, error-prone and tedious. So automatic segmentation technique is needed which is the unsolved ch

Deep Learning for Automated Brain Tumor Segmentation in MRI Images

Book Chapter

Book NameSoft Computing based Medical Image Analysis

PublisherElsevier

Page Number183-201

Chapter TitleDeep Learning for Automated Brain Tumor Segmentation in MRI Images

Published YearJanuary 2018

ISSN/ISBN No978-0-12-813087-2

Indexed INScopus

Object Detection Using Deep Neural Network

Conference

Title of PaperObject Detection Using Deep Neural Network

Proceeding NameInternational Conference on Intelligent Computing and Control Systems

PublisherIEEE Explore

Author NameMalay Shah, Rupal Kapdi

OrganizationVaigai College of Engineering, Madurai, India

Year , VenueMay 2017 , Vaigai College of Engineering, Madurai, India

Page Number787-790

Indexed INScopus

Abstract

The problem discussed in this article is object detection using deep neural network especially convolution neural networks. Object detection was previously done using only conventional deep convolution neural network whereas using regional based convolution network [3] increases the accuracy and also decreases the time required to complete the program. The dataset used is PASCAL VOC 2012 which contains 20 labels. The dataset is very popular in image recognition, object detection, and other image processing problems. Supervised learning is also possible in implementing the problem using Decision trees or more likely SVM. But neural network works best in image processing because they can handle images well.

Case Study

Case Study TitleBrain Tumor Segmentation – Towards a better life

PublisherCSI Communication of India

Published YearDecember 2016

ISSN/ISBN No0970 647X

Indexed INScopus

Copy Move Forgery Detection Using SIFT and GMM

Conference

Title of PaperCopy Move Forgery Detection Using SIFT and GMM

Proceeding NameIEEE Explore

PublisherIEEE Explore

Author NameNeetu Yadav, Rupal Kapdi

OrganizationNirma University

Year , VenueNovember 2015 , Nirma University

Page Number1-4

ISSN/ISBN No978-1-4799-9990-3

Indexed INScopus

Abstract

Modifying or enhancing an image is ubiquitous but, when enhancement tends to change the interpretation of the image they are termed as an attempt of forgery on digital images. Copy move forgery (CMF) is a simple technique and has a number of well built tools in a number of image enhancement software. CMF detection techniques often tend to establish similarity between copied and pasted region on the same image as both are from same original image. Keypoint and block based techniques are used to determine the CMF. SIFT keypoints are combined with different techniques to accurately localize forgery. High imensionality of feature vector acts as a bottleneck in SIFT based analysis. We propose a method to detect CMF using SIFT descriptors which are clustered using GMM and segment the obtained suspect region speeding up the analysis.

Copy Move Forgery Detection Using SIFT Features – An Analysis

Journal

Journal NameNirma University Journal of Engineering and Technology

Title of PaperCopy Move Forgery Detection Using SIFT Features – An Analysis

PublisherNirma University

Volume Number4

Page Number11-14

Published YearJanuary 2015

ISSN/ISBN No2231-2870

Indexed INUGC List

Abstract

Emphasis on the need for authentication of image content has increased since images have been inferred to have some cognitive effects on human brain coupled along with the pervasiveness of images. General form of malicious image manipulations is Copy Move Forgery (CMF) in which a region is cloned from source location and pasted onto the same image at a target location. Techniques often used to hide or increase presence of an object in the image. This need to establish detection of image originality and authentication without using any prior details of the image has increased by many folds. In this paper, we present a list of comparisons on the detection of image forgeries mostly pertaining to CMF using SIFT method. An effort has been made to produce suffused paper by quoting most of the recent practices by providing an in-depth analysis of range of different techniques for forgery localization.

Sanjay Patel

Santoshinee Mohapatra

Fault Detection in Forest Fire Monitoring using Negative Selection Approach

Conference

Title of PaperFault Detection in Forest Fire Monitoring using Negative Selection Approach

Proceeding NameIEEE HTC

PublisherIEEE

Author NameSantoshinee Mohapatra

OrganizationIEEE

Year , VenueMarch 2024 , Rajkot

Page Number732-736

ISSN/ISBN No979-8-3503-2614-7

Indexed INScopus, Web of Science

Abstract

Forests are the lifelines of any economy. Forest fires are uncontrolled and unpredictable once occur, identified after their wider spread in the forest. Forest fire detection using Wireless Sensor Network (WSN) is a significant application to monitor it. However, in some situations, unreliable/incorrect data may be sent by sensor nodes due to some fault, resulting in significant problems. Such faulty sensor nodes are unknown to the network and that causes major problems. Hence, the Detection of faulty nodes, if any, is essential and a prerequisite. To fulfill this necessity, faulty node, and forest fire detection is carried out in this research. A Negative Selection Approach (NSA) is introduced in the first phase for faulty node detection and a threshold-based approach is introduced for forest fire detection in the second phase of the proposed work. The experimental findings manifest that the proposed methodology performs efficiently in different scenarios. An NSA-based fault detection approach provides better accuracy with an average of 98.18%, an average of 3.56% False Alarm Rate (FAR), and an average of 1.81% False Positive Rate (FPR).

Fault detection for VANET using vehicular cloud

Conference

Title of Paper Fault detection for VANET using vehicular cloud

Proceeding NameIntelligent and Cloud Computing: Proceedings of ICICC 2019, Volume 2

PublisherSpringer Singapore

Author NameSantoshinee Mohapatra

OrganizationSpringer

Year , VenueJanuary 2021 , Bhubaneswar

Page Number87-95

Indexed INScopus

Fault Diagnosis in Wireless Sensor Network Using Self/Non-self Discrimination Principle

Conference

Title of Paper Fault Diagnosis in Wireless Sensor Network Using Self/Non-self Discrimination Principle

Proceeding NameProgress in Computing, Analytics and Networking: Proceedings of ICCAN 2019

PublisherSpringer Singapore

Author NameSantoshinee Mohapatra

OrganizationSpringer

Year , VenueDecember 2020 , Bhubaneswar

Page Number161 - 168

Indexed INScopus

Fault diagnosis in wireless sensor network using negative selection algorithm and support vector machine

Journal

Journal NameComputational Intelligence

Title of Paper Fault diagnosis in wireless sensor network using negative selection algorithm and support vector machine

PublisherWiley

Volume Number36

Page Number1374-1393

Published YearAugust 2020

Immune inspired fault diagnosis in wireless sensor network

Book Chapter

Book NameNature Inspired Computing for Wireless Sensor Networks

PublisherSpringer Singapore

Author NameSantoshinee Mohapatra

Page Number103-116

Chapter Title Immune inspired fault diagnosis in wireless sensor network

Published YearJanuary 2020

Detecting emotions from human speech: role of gender information

Conference

Title of PaperDetecting emotions from human speech: role of gender information

Proceeding NameIEEE Xplore

PublisherIEEE

OrganizationIEEE Tensymp 2022

Year , VenueJuly 2022 , IIT Bombay

Page Number1-6

ISSN/ISBN No2642-6102

Indexed INScopus

On the performance of empirical mode decomposition-based replay spoofing detection in speaker verification systems

Journal

Journal NameProgress in Artificial Intelligence

Title of PaperOn the performance of empirical mode decomposition-based replay spoofing detection in speaker verification systems

PublisherSpringer

Volume Number9

Page Number325-339

Published YearDecember 2020

ISSN/ISBN No2192-6360

Indexed INScopus, Web of Science

Voice liveness detection under feature fusion and cross-environment scenario

Journal

Journal NameMultimedia Tools and Applications

Title of PaperVoice liveness detection under feature fusion and cross-environment scenario

PublisherSpringer

Published YearJuly 2020

ISSN/ISBN No1573-7721

Indexed INScopus

Development of a Novel Database in Gujarati Language for Spoken Digits Classification

Book Chapter

Book NameCommunications in Computer and Information Science

PublisherSpringer, Singapore

Page Number208-219

Chapter TitleDevelopment of a Novel Database in Gujarati Language for Spoken Digits Classification

Published YearMay 2020

ISSN/ISBN No978-981-15-4828-4

Indexed INScopus

Investigating Feature Reduction Strategies for Replay Antispoofing in Voice Biometrics

Book Chapter

Book NameLecture Notes in Computer Science

PublisherSpringer, Cham

Page Number400-408

Chapter TitleInvestigating Feature Reduction Strategies for Replay Antispoofing in Voice Biometrics

Published YearDecember 2019

ISSN/ISBN No978-3-030-34872-4

Indexed INScopus

On the Performance of Cepstral Features for Voice-Based Gender Recognition

Book Chapter

Book NameInformation and Communication Technology for Intelligent Systems

PublisherSpringer, Singapore

Page Number327-333

Chapter TitleOn the Performance of Cepstral Features for Voice-Based Gender Recognition

Published YearJanuary 2019

ISSN/ISBN No978-981-13-1747-7

Indexed INScopus, UGC List

Detection of Mimicry Attacks on Speaker Verification System for Cartoon Characters’ Dataset

Book Chapter

Book NameInformation and Communication Technology for Intelligent Systems

PublisherSpringer, Singapore

Page Number319-326

Chapter TitleDetection of Mimicry Attacks on Speaker Verification System for Cartoon Characters’ Dataset

Published YearJanuary 2019

ISSN/ISBN No978-981-13-1747-7

Indexed INScopus, UGC List

Towards Development of Smart and Reliable Voice Based Personal Assistants

Conference

Title of PaperTowards Development of Smart and Reliable Voice Based Personal Assistants

Proceeding NameTENCON 2018-2018 IEEE Region 10 Conference

PublisherIEEE

Author NameSapan H Mankad, Viramya Shah, Sanjay Garg

Year , VenueOctober 2018 , Jeju, South Korea

Page Number2473-2478

Emotion Recognition from Sensory and Bio-Signals: A Survey

Book Chapter

Book NameAdvances in Intelligent Systems and Computing

PublisherSpringer, Singapore

Page Number345-355

Chapter TitleEmotion Recognition from Sensory and Bio-Signals: A Survey

Published YearOctober 2018

ISSN/ISBN No978-981-13-1610-4

Indexed INScopus, UGC List

Investigating the Effect of Varying Window Sizes in Speaker Diarization for Meetings Domain

Book Chapter

Book NameSmart Innovation, Systems and Technologies

PublisherSpringer, Cham

Page Number361-369

Chapter TitleInvestigating the Effect of Varying Window Sizes in Speaker Diarization for Meetings Domain

Published YearAugust 2017

ISSN/ISBN No978-3-319-63645-0

Indexed INScopus, UGC List

Emerging Role of Crowdsourcing in MOOCs: A Review

Journal

Journal NameInternational Journal of Control Theory and Applications

Title of PaperEmerging Role of Crowdsourcing in MOOCs: A Review

PublisherInternational Science Press

Volume Number9

Page Number273-280

Published YearNovember 2016

ISSN/ISBN No09745572

Indexed INScopus

Automatic Weight Calculation Based Associative Classifier

Journal

Journal NameInternational Journal of Artificial Intelligence and Knowledge Discovery

Title of PaperAutomatic Weight Calculation Based Associative Classifier

PublisherRG Education Society

Volume Number6

Page Number1-5

Published YearOctober 2016

ISSN/ISBN No2231-0312

Indexed INOthers

Predicting learning behaviour of students: Strategies for making the course journey interesting

Conference

Title of PaperPredicting learning behaviour of students: Strategies for making the course journey interesting

Proceeding NameIntelligent Systems and Control (ISCO), 2016 10th International Conference on

PublisherIEEE

Year , VenueJuly 2016 , Karpagam Engineering College, Coimbatore

Page Number1-6

A new approach to address Subset Sum problem

Conference

Title of PaperA new approach to address Subset Sum problem

Proceeding NameConfluence The Next Generation Information Technology Summit (Confluence), 2014 5th International Conference -

PublisherIEEE

Year , VenueSeptember 2014 , Amity University, Noida

Page Number953-956

Indexed INOthers

Application of Software Defined Radio for Noise Reduction Using Empirical Mode Decomposition

Book Chapter

Book NameAdvances in Intelligent and Soft Computing

PublisherSpringer, Berlin, Heidelberg

Author NameDavid C. Wyld, Jan Zizka, Dhinaharan Nagamalai

Page Number113-121

Chapter TitleApplication of Software Defined Radio for Noise Reduction Using Empirical Mode Decomposition

Published YearMay 2012

ISSN/ISBN No978-3-642-30157-5

Indexed INScopus

Smart Inbox: A comparison based approach to classify the incoming mails

Journal

Journal NameInternational Journal of Artificial Intelligence and Knowledge Discovery

Title of PaperSmart Inbox: A comparison based approach to classify the incoming mails

PublisherRG Education Society

Volume Number1

Page Number29-32

Published YearJanuary 2011

ISSN/ISBN No2231-0312

Indexed INOthers

Saurin Parikh

A Review of Non Invasive Blood Pressure Monitoring using Artificial Intelligence based Approaches

Conference

Title of PaperA Review of Non Invasive Blood Pressure Monitoring using Artificial Intelligence based Approaches

Proceeding Name2022 International Conference on Applied Artificial Intelligence and Computing (ICAAIC)

PublisherIEEE

Author NameVimal Sheoran, Gaurang Raval, Sharada Valiveti, Saurin Parikh

Organization(ICAAIC)

Year , VenueMay 2022 , Online

Page Number6

ISSN/ISBN No978-1-6654-9711-4

Indexed INScopus

Abstract

The problem of non-invasive blood pressure monitoring has been tackled by researchers for quite some time now and it still remains an open problem with ever developing solutions trying to satisfy measurement standards and experimentally successful solutions trying to find their way into the commercial market. The problem continues to be solved in 2022 and as more and more viable solutions are being proposed via different techniques, different experimental setups and different instrumentation, it is important to have a brief retrospect of the work that has already been done in this dynamic field. The study here compiles some of the most recent and the most effective work that has been done in the field of non-invasive blood pressure monitoring and categorises it into two broad fields, Pulse Transit Time based approaches and Artificial Intelligence based approaches. The study aims to be a starting point for people who are picking up this problem for the first time or wish to look at alternative approaches.

A Survey on Reading Habit of Library Users during COVID-19 Lockdown

Journal

Journal NameLibrary Philosophy and Practice

Title of PaperA Survey on Reading Habit of Library Users during COVID-19 Lockdown

PublisherLibrary Philosophy and Practice

Volume Number1A

Page Number6

Published YearSeptember 2020

ISSN/ISBN No15220222

Indexed INScopus

Abstract

E-Libraries has become more relevant in present situation of COVID-19 pandemic as it has caused an international lockdown in the world and India. Causing majority of the citizens to stay at home. The survey was conducted to study the reading habits of various library users (volunteers) during this situation. Besides the reading habit, the survey also collected the data for the various activities carried out by users at home. Main finding of the survey is that the users had taken keen interest to switch over to reading eBooks and 70% of student users and 53% of faculty users are reading more e-content especially books/magazines/research papers. Besides the extensive reading habit, the survey also discloses the greater involvement of users for learning/leisure/hobby activities at home. Student users have also reported spending more quality life with family members at home. Above all, the survey disclosed the reading of books as the main activity of the users during lockdown. This finding will inspire the organizations for establishing scalable and secure elibrary Infrastructure and for focusing on acquiring more eBooks for the eLibrary and provide better services to their users during situations like that of COVID-19.

Feature Weighted Linguistics Classifier for Predicting Learning Difficulty Using Eye Tracking

Journal

Journal NameACM Transactions on Applied Perception

Title of PaperFeature Weighted Linguistics Classifier for Predicting Learning Difficulty Using Eye Tracking

PublisherACM

Volume Number17-2

Page Number25

Published YearMay 2020

ISSN/ISBN No1544-3558

Indexed INScopus, Web of Science, EBSCO

Abstract

This article presents a new approach to predict learning difficulty in applications such as e-learning using eye movement and pupil response. We have developed 12 eye response features based on psycholinguistics, contextual information processing, anticipatory behavior analysis, recurrence fixation analysis, and pupillary response. A key aspect of the proposed approach is the temporal analysis of the feature response to the same concept. Results show that variations in eye response to the same concept over time are indicative of learning difficulty. A Feature Weighted Linguistics Classifier (FWLC) was developed to predict learning difficulty in real time. The proposed approach predicts learning difficulty with an accuracy of 90%.

Predicting Learning Difficulty based on Gaze and Pupil Response

Conference

Title of PaperPredicting Learning Difficulty based on Gaze and Pupil Response

Proceeding NameUMAP 2018 - Adjunct Publication of the 26th Conference on User Modeling, Adaptation and Personalization

PublisherACM 26th Conference on User Modeling, Adaptation and Personalization

OrganizationACM-UMAP

Year , VenueJuly 2018 , Singapore

Page Number5

ISSN/ISBN No978-145035784-5

Indexed INScopus

Eye Gaze Feature Classification for Predicting Levels of Learning

Conference

Title of PaperEye Gaze Feature Classification for Predicting Levels of Learning

Proceeding NameCEUR Workshop Proceedings, 8th International Workshop on Personalization Approaches in Learning Environments, PALE 2018

PublisherInternational Conference on Artificial intelligence in Education - PALE 2018, London, UK

OrganizationAIED- PALE

Year , VenueJune 2018 , London, USA

Page Number6

ISSN/ISBN No16130073

Indexed INScopus

High Bit-Depth Medical Image Compression with HEVC

Journal

Journal NameIEEE Journal of Biomedical and Health Informatics

Title of PaperHigh Bit-Depth Medical Image Compression with HEVC

PublisherIEEE Journal of Biomedical and Health Informatics

Volume Number22

Page Number9

Published YearMarch 2018

ISSN/ISBN No2168-2208

Indexed INScopus, PubMed, Web of Science

Predicting Information Context Processing from Eye Movements

Conference

Title of PaperPredicting Information Context Processing from Eye Movements

Proceeding Nameproceeding of the 19th European Conference on Eye Movements 2017

PublisherJournal of Eye Movement Research

OrganizationECEM

Year , VenueAugust 2017 , Germany, Europe

ISSN/ISBN No1995-8692

Indexed INOthers

Real-Time Learning Level Assessment using Eye Tracking

Conference

Title of PaperReal-Time Learning Level Assessment using Eye Tracking

Proceeding NameWorkshop proceeding on Computational and Mathematical models in Vision (MODVIS, a Satellite event of VSS 2017)

PublisherWorkshop proceeding on Computational and Mathematical models in Vision (MODVIS, a Satellite event of VSS 2017)

OrganizationMODVIS, a satellite event of VSS

Year , VenueMay 2017 , Tampa, Florida, USA

Indexed INOthers

Content Dependent Intra Mode Selection for Medical Image Compression using HEVC

Conference

Title of PaperContent Dependent Intra Mode Selection for Medical Image Compression using HEVC

Proceeding NameICCE

PublisherIEEE

OrganizationCES

Year , VenueJanuary 2016 , Las Vegas, USA

Page Number4

ISSN/ISBN No978-1-4673-8364-6

Indexed INScopus

Evaluation of HEVC compression for high bit depth medical images

Conference

Title of PaperEvaluation of HEVC compression for high bit depth medical images

Proceeding Name2016 IEEE International Conference on Consumer Electronics (ICCE)

PublisherIEEE

OrganizationICCE

Year , VenueJanuary 2016 , Las Vegas, USA

Page Number4

ISSN/ISBN No978-1-4673-8364-6

Indexed INScopus

Efficient algorithm for Auto Correction using n-gram indexing

Journal

Journal NameInternational Journal of Computer & Communication Technology

Title of PaperEfficient algorithm for Auto Correction using n-gram indexing

PublisherInternational Journal of Computer & Communication Technology

Volume Number3

Page Number5

Published YearJanuary 2014

ISSN/ISBN No 0975 - 7449

Indexed INOthers

A Geo-Location based Mobile Service that Dynamically Locates and Notifies the Nearest Blood Donors for Blood Donation during Medical Emergencies

Journal

Journal NameInternational Journal of Computer Applications (IJCA)

Title of PaperA Geo-Location based Mobile Service that Dynamically Locates and Notifies the Nearest Blood Donors for Blood Donation during Medical Emergencies

PublisherInternational Journal of Computer Applications (IJCA)

Volume Number88

Page Number6

Published YearJanuary 2014

ISSN/ISBN No0975-8887

Indexed INOthers

Analysis of Network Performance by Configuring Static ARP Based Network

Conference

Title of PaperAnalysis of Network Performance by Configuring Static ARP Based Network

Proceeding NameNational Seminar on Recent Advances on Information Technology (RAIT-2009)

PublisherNational Seminar on Recent Advances on Information Technology (RAIT-2009)

OrganizationNational Seminar on Recent Advances on Information Technology (RAIT-2009)

Year , VenueJanuary 2009 , Indian School of Mines,

Indexed INOthers

Sharada Valiveti

Regenerating vital facial keypoints for impostor identification from disguised images using CNN

Journal

Journal NameExpert Systems with Applications

Title of PaperRegenerating vital facial keypoints for impostor identification from disguised images using CNN

PublisherElsevier

Volume Number219

Page Number11

Published YearJune 2023

ISSN/ISBN No0957-4174

Indexed INScopus, Web of Science

Abstract

Technical advancements in the digital era have eased up the time required to complete complex tasks by a decisive rate. These advancements introduce several threats. Hence, there is a compelling need to provide security for systems against these threats. Identity and data thefts are the major threats which require immediate, effective and responsive solutions. Face recognition systems have evolved over the last few years, providing a suitable solution for authenticating an individual. However, the system running on facial recognition can be interfered by disguise. This paper discusses the approaches used in detecting a disguise and analysing the captured face among the other non-disguised faces in the dataset. The parameters used for detection and analysis are the keypoints of the face. These keypoints may be blocked, hidden or disoriented due to the presence of props on the face. The proposed approach aims to avoid this interference by creating an estimate of the face based on fewer available keypoints. The estimated face so created, is then matched with the available set of faces to determine the probabilistic chance of the matched person’s presence even though a disguise had been detected. Thus the solution provides a clear distinction if the image obtained proves to be of an impostor or an intruder with obfuscation with a said probability. The Disguised Faces in the Wild (DFW) dataset has been used.

An efficient bio-inspired routing scheme for tactical ad hoc networks

Journal

Journal NameScalable Computing: Practice and Experience

Title of PaperAn efficient bio-inspired routing scheme for tactical ad hoc networks

PublisherSCPE

Volume Number24

Page Number45-55

Published YearApril 2023

ISSN/ISBN No1895-1767

Indexed INScopus, Web of Science, EBSCO

Abstract

Ad hoc networks are temporary networks, created mainly for applications that are infrastructure-less. Such networks and network nodes demand special characteristics like mobile nodes having dynamic topology, wireless medium, heterogeneous deployment environment, and reactive or proactive routing depending on the nature of the network which includes network parameters such as node placement, mobility model, number of participants in the network, patterns of mobility, etc. Due to these characteristics and the mobility of network nodes, the process of routing is quite challenging in the ad hoc environment, especially when the node mobility is high. Bio-inspired routing can be an effective solution to meet all the design requirements and deal with the issues of tactical ad hoc networks. Different types of nature-inspired routing mechanisms are possible to use for tactical networks. This paper proposes the design of a novel Ant Colony Optimization-based routing strategy for ad hoc networks. Ant-based algorithms are dynamic and have adaptive behavior. Hence, they are competent for routing in ad hoc networks. Our proposed routing scheme is evaluated based on the network’s performance by varying different parameters. The performance of our proposed ACO-based routing approach is also compared to some existing ad hoc routing mechanisms. Different metrics in different deployment scenarios that can affect the efficiency of our proposed protocol are taken into consideration to evaluate the performance.

Profiling Cyber Crimes from News Portals Using Web Scraping

Conference

Title of PaperProfiling Cyber Crimes from News Portals Using Web Scraping

Proceeding Name Futuristic Trends in Networks and Computing Technologies

PublisherLecture Notes in Electrical Engineering, Springer

Author NameJoel Christian, Sharada Valiveti, Swati Jain

OrganizationNirma University

Year , VenueNovember 2022 , Nirma University

Page Number1007-1016

ISSN/ISBN No978-981-19-5037-7

Indexed INScopus, Web of Science

Abstract

In the past few years and especially during the pandemic period everything is going online. Everyone is connected through the Internet. With this rapid surge, cyber crimes are also skyrocketing. The government has made efforts to cope with situation but that is not enough. India faced a loss of more than Rs. 1.25 trillion ($16 billion USD) due to cyber crimes. Online news are a reliable source of information which are always up to date and freely available. In this paper, we conduct a survey of web scraping related previous works. Web scraping is a method to gather information from websites. With this knowledge we have proposed a system of web scraping where we gather cyber crime related news articles. From this data we can classify the crimes into their respective categories according to their regions and time period. This can help law enforcement and also create awareness amongst common people.

Blockchain based E-Voting: Opportunities and Challenges

Conference

Title of PaperBlockchain based E-Voting: Opportunities and Challenges

Proceeding Name7th International Conference on Communication and Electronic Systems ICCES-2022

PublisherIEEE

Author NamePimal Khanpara, Shivam Patel, Sharada Valiveti

Year , VenueJune 2022 , Coimbatore, India

Page Number855-861

Indexed INScopus

A Review of Non Invasive Blood Pressure Monitoring using Artificial Intelligence based Approaches

Conference

Title of PaperA Review of Non Invasive Blood Pressure Monitoring using Artificial Intelligence based Approaches

Proceeding NameProceedings - International Conference on Applied Artificial Intelligence and Computing, ICAAIC 2022

PublisherInstitute of Electrical and Electronics Engineers Inc.

Author NameVimal Sheoran, Gaurang Raval, Sharada Valiveti, Saurin Parikh

Year , VenueMay 2022 , Salem,

Page Number101-106

ISSN/ISBN No978-166549710-7

Journal

Journal NameInternational Journal of Advanced Research in Engineering & Technology (IJARET)

Title of PaperAnalyzing The Performance of Bandwidth Starvation Attack in Lan

Page Number145-153

Published YearFebruary 2014

Performance Evaluation Of Byzantine Flood Rushing Attack In Ad Hoc Network

Journal

Journal NameInternational Journal of Electronics and Communication Engineering & Technology (IJECET)

Title of PaperPerformance Evaluation Of Byzantine Flood Rushing Attack In Ad Hoc Network

Published YearFebruary 2014

ISSN/ISBN No0976-6464

Routing in Ad Hoc Network Using Ant Colony Optimization

Book Chapter

Book NameInternational Conference on Future Generation Communication and Networking FGCN 2010

PublisherCommunications in Computer and Information Science, vol 120. Springer, Berlin, Heidelberg

Page Number393-404

Chapter TitleRouting in Ad Hoc Network Using Ant Colony Optimization

Published YearDecember 2010

ISSN/ISBN No978-3-642-17604-3

Indexed INScopus

Trust Based Routing in Ad Hoc Network

Book Chapter

Book NameInternational Conference on Future Generation Communication and Networking FGCN 2010

PublisherCommunications in Computer and Information Science, vol 120. Springer, Berlin, Heidelberg

Page Number381-392

Chapter TitleTrust Based Routing in Ad Hoc Network

Published YearDecember 2010

ISSN/ISBN No978-3-642-17604-3

Indexed INScopus

Non-Repudiation in Ad Hoc Networks

Book Chapter

Book NameInternational Conference on Future Generation Communication and Networking

Publisher Communications in Computer and Information Science, Springer

Page Number405-415

Chapter TitleNon-Repudiation in Ad Hoc Networks

Published YearDecember 2010

ISSN/ISBN No978-3-642-17604-3

Indexed INScopus

Comparative Study of Distributed Intrusion Detection in ad hoc networks

Journal

Journal NameInternational Journal of Computer Applications

Title of PaperComparative Study of Distributed Intrusion Detection in ad hoc networks

PublisherInternational Journal of Computer Applications

Volume Number8

Page Number11-16

Published YearOctober 2010

ISSN/ISBN No0975 - 8887

Indexed INEBSCO

Abstract

In recent years ad hoc networks are widely used because of mobility and open architecture nature. But new technology always comes with its own set of problems. Security of ad hoc network is an area of widespread research in recent years. Some unique characteristics of ad hoc network itself are an immense dilemma in the way of security.

Shivani Desai

Parkinson’s Disease Detection Using Machine Learning

Conference

Title of PaperParkinson’s Disease Detection Using Machine Learning

PublisherSpringer

Author Name Shivani Desai

OrganizationICISS 2022

Published YearFebruary 2022

Indexed INScopus

Insights of Deep Learning Applications

Conference

Title of PaperInsights of Deep Learning Applications

PublisherIEEE Explore

Author Name Shivani Desai

OrganizationICECA-2021

Published YearDecember 2021

Indexed INScopus

Email autocomplete function using RNN encoder-decoder sequence to sequence model

Conference

Title of PaperEmail autocomplete function using RNN encoder-decoder sequence to sequence model

PublisherIEEE Explore

Author NameShivani desai

OrganizationICECA-2021

Published YearDecember 2021

Indexed INScopus

Deep learning-based scheme to diagnose Parkinson's disease

Journal

Journal NameExpert Systems

Title of Paper Deep learning-based scheme to diagnose Parkinson's disease

Publisherwiley

Published YearMay 2021

Indexed INScopus

Intrusion Detection System - Deep Learning Perspective

Conference

Title of PaperIntrusion Detection System - Deep Learning Perspective

Proceeding NameIEEE Explore

PublisherIEEE Explore

Author NameShivani Desai ; Bhavyang Dave ; Tarjni Vyas ; Anuja R. Nair

OrganizationJCT College of Engineering and Tchnology

Blockchain-Driven Real-Time Incentive Approach for Energy Management System

Journal

Journal NameMathematics

Title of PaperBlockchain-Driven Real-Time Incentive Approach for Energy Management System

PublisherMDPI

Volume Number11

Page Number928

Published YearFebruary 2023

ISSN/ISBN No22277390

Indexed INScopus, Web of Science

Data Encryption Approach Using Hybrid Cryptography and Steganography with Combination of Block Ciphers

Conference

Title of Paper Data Encryption Approach Using Hybrid Cryptography and Steganography with Combination of Block Ciphers

Proceeding NameCommunications in Computer and Information Science

PublisherSpringer Nature Switzerland

Author NameSmita Agrawal

Organization1st International Conference on Advancements in Smart Computing and Information Security, ASCIS 2022

Year , VenueJanuary 2023 , Institute of Technology, Nirma University, Department of Computer Science and Engineering, Ahmedabad, India

Page Number59-69

ISSN/ISBN No18650929

Indexed INScopus

Blockchain and Reverse Auction-based EVs Energy Trading Approach for Optimal Pricing

Conference

Title of PaperBlockchain and Reverse Auction-based EVs Energy Trading Approach for Optimal Pricing

Proceeding NameProceedings of the 13th International Conference on Cloud Computing, Data Science and Engineering, Confluence 2023

PublisherIEEE

Author NameSmita Agrawal

Organization Institute of Technology, Nirma University, Department of Computer Science and Engineering, Ahmedabad, India

Year , VenueJanuary 2023 , Institute of Technology, Nirma University, Department of Computer Science and Engineering, Ahmedabad, India

Page Number412 - 417

ISSN/ISBN No978-166546263-1

Indexed INScopus

A Review on Standardizing Electric Vehicles Community Charging Service Operator Infrastructure

Journal

Journal NameApplied Sciences (Switzerland)

Title of PaperA Review on Standardizing Electric Vehicles Community Charging Service Operator Infrastructure

PublisherMDPI

Volume Number12

Page Number12096

Published YearNovember 2022

ISSN/ISBN No20763417

Indexed INScopus

Blockchain and Deep Learning-Based Fault Detection Framework for Electric Vehicles

Journal

Journal NameMathematics

Title of PaperBlockchain and Deep Learning-Based Fault Detection Framework for Electric Vehicles

PublisherMDPI

Volume Number10

Page Number3626

Published YearOctober 2022

ISSN/ISBN No22277390

Indexed INScopus

Blockchain and IoT-Driven Optimized Consensus Mechanism for Electric Vehicle Scheduling at Charging Stations

Journal

Journal NameSustainability (Switzerland)

Title of PaperBlockchain and IoT-Driven Optimized Consensus Mechanism for Electric Vehicle Scheduling at Charging Stations

PublisherMDPI

Volume Number14

Page Number12800

Published YearOctober 2022

ISSN/ISBN No20711050

Indexed INScopus

Blockchain and Double Auction-Based Trustful EVs Energy Trading Scheme for Optimum Pricing

Journal

Journal NameMathematics

Title of PaperBlockchain and Double Auction-Based Trustful EVs Energy Trading Scheme for Optimum Pricing

PublisherMDPI

Volume Number10

Page Number2748

Published YearAugust 2022

ISSN/ISBN No22277390

Indexed INScopus

A Taxonomy on Smart Healthcare Technologies: Security Framework, Case Study, and Future Directions

Journal

Journal NameJournal of Sensors

Title of PaperA Taxonomy on Smart Healthcare Technologies: Security Framework, Case Study, and Future Directions

PublisherHindawi

Volume Number2022

Page Number-

Published YearJuly 2022

ISSN/ISBN No1687725X

Indexed INScopus

A Secure DBA Management System: A Comprehensive Study

Conference

Title of PaperA Secure DBA Management System: A Comprehensive Study

Proceeding NameLecture Notes in Networks and Systems

PublisherSpringer Nature Singapore

Author NameSmita Agrawal

Organization3rd International Conference on Computing, Communications, and Cyber-Security, IC4S 2021

Year , VenueJuly 2022 , Institute of Technology, Nirma University, Department of Computer Science and Engineering, Ahmedabad, India

Page Number883 - 893

ISSN/ISBN No23673370

Indexed INOthers

Concurrency Control in Distributed Database Systems: An In-Depth Analysis

Conference

Title of PaperConcurrency Control in Distributed Database Systems: An In-Depth Analysis

Proceeding NameLecture Notes in Networks and Systems

PublisherSpringer Nature Singapore

Author NameSmita Agrawal

OrganizationComputer Science and Engineering Department, Nirma University, Ahmedabad, India

Year , VenueJuly 2022 , Institute of Technology, Nirma University, Department of Computer Science and Engineering, Ahmedabad, India

Page Number223 - 234

ISSN/ISBN No23673370

Indexed INScopus

Blockchain-based secure and trusted data sharing scheme for autonomous vehicle underlying 5G

Journal

Journal NameJournal of Information Security and Applications

Title of PaperBlockchain-based secure and trusted data sharing scheme for autonomous vehicle underlying 5G

PublisherElsevier

Volume Number67

Page Number103179

Published YearJune 2022

ISSN/ISBN No22142134

Indexed INScopus

Journal

Journal NameTurkish Journal of Electrical Engineering and Computer Sciences

Title of PaperBlockchain and federated learning-based security solutions for telesurgery system: a comprehensive review

PublisherTurkish Journal of Electrical Engineering and Computer Sciences

Volume Number30

Page Number2446-2488

Published YearJanuary 2022

ISSN/ISBN No13000632

Indexed INScopus

Enhanced Secure ATM authentication using NFC Technology and Iris Verification

Journal

Journal NameScalable Computing

Title of PaperEnhanced Secure ATM authentication using NFC Technology and Iris Verification

PublisherSCPE- Institute e-Austria Timisoara

Volume Number22(2)

Page Number273–282

Published YearOctober 2021

ISSN/ISBN No1895-1767

Indexed INScopus, Web of Science

Abstract

In today’s world technology has advanced to such an extent that it is interchangeable with connection and convenience. ATM was one of the major breakthroughs, and over the time it has provided better convenience in fulfilling one’s banking needs. Although, there are certain predicaments that such ATM transactions are susceptible too. The conventional PIN based authentication that is presently accustomed in all ATM apparatus is liable to shoulder surfing, hassle in remembering the multiple PIN and the rest. The physical card brings along setbacks in particular, wearing out of the magnetic strip attributable to frequent usage, losing or getting it stolen. Aside from these there are other unlawful activities that are carried upon. The objective of this paper is to present a solution to the above stated problems. In contrast to standard architecture, the proposed solution incorporates NFC enabled smartphones as a substitute for physical card and iris based authentication for PIN.

AI Approaches for Breast Cancer Diagnosis: A Comprehensive Study

Conference

Title of Paper AI Approaches for Breast Cancer Diagnosis: A Comprehensive Study

Proceeding NameAdvances in Intelligent Systems and Computing,

PublisherSpringer, Singapore

Author NamePatel H.J., Oza P., Agrawal S.

Page Number-

Published YearAugust 2021

ISSN/ISBN No978-981-16-3071-2

Indexed INScopus, EBSCO, Others

Abstract

According to the report of the World Health Organization (WHO), the most common and dangerous disease among women is known to be breast cancer. Breast cancer is a life-threatening disease and may cause death of women. Early detection of breast cancer can decrease mortality rate and improve survival rate in women. Various artificial intelligence (AI) approaches have been used by the research community to build computer-aided diagnosis (CAD) systems for early detection of breast cancer. This study presents various breast imaging modalities used for the cancer diagnosis, related work in this domain, various pre-processing techniques to improve the quality of breast images and applications of machine learning (ML) for breast imaging. The study also presents various deep learning (DL) approaches to build a system for automated breast cancer diagnosis. Various pre-trained deep learning models are also presented in the study. Due to an imbalanced and inconsistent dataset, AI models may not perform well. We have also discussed various techniques to improve the performance of the model. Prediction, segmentation, and classification deep neural network models along with the various imaging modalities are presented which are beneficial for the diagnosis process of breast cancer.

SAG Cluster: An unsupervised graph clustering based on collaborative similarity for community detection in complex networks

Journal

Journal NamePhysica A: Statistical Mechanics and its Applications

Title of PaperSAG Cluster: An unsupervised graph clustering based on collaborative similarity for community detection in complex networks

PublisherElsevier

Volume Number563

Page Number1-16

Published YearFebruary 2021

ISSN/ISBN No0378-4371

Indexed INScopus, PubMed, Web of Science

Abstract

Many real-world social networks such as brain graph, protein structure, food web, transportation system, World Wide Web, online social networks exist in the form of a complex network. In such complex networks, pattern identification or community detection requires extra effort in which identifying community is a significant problem in various research areas. Most of the clustering methods on graphs predominantly emphasize on the topological structure without considering connectivity between vertices and not bearing in mind the vertex properties/attributes or similarity-based on indirectly connected vertices. A novel clustering algorithm SAG-Cluster with K-medoids framework presented for detecting communities using a collaborative similarity measure which considers attribute importance in case the pair of disconnected nodes. A novel path strategy using classic Basel problem for the indirectly connected node as well as balanced attribute similarity and distance function is proposed. On two real data sets, experimental results show the effectiveness of SAG-Cluster with the comparison of other relevant methods.

Diabetes Prediction Using Machine Learning

Conference

Title of PaperDiabetes Prediction Using Machine Learning

Proceeding NameLecture Notes in Networks and Systems

PublisherSpringer Singapore

Author NameSmita Agrawal

Organization2nd International Conference on Computing, Communications, and Cyber-Security, IC4S 2020

Year , VenueJanuary 2021 , Institute of Technology, Nirma University, Department of Computer Science and Engineering, Ahmedabad, India

Page Number703 - 715

ISSN/ISBN No23673370

Indexed INScopus

Data Ingestion and Analysis Framework for Geoscience Data

Book Chapter

Book NameLecture Notes in Electrical Engineering

PublisherSpringer, Singapore

Page Number809-820

Chapter TitleData Ingestion and Analysis Framework for Geoscience Data

Published YearJanuary 2021

ISSN/ISBN No978-981-15-8296-7

Indexed INScopus

Abstract

Big earth data analytics is an emerging field since environmental sciences are probably going to profit by its different systems supporting the handling of the enormous measure of earth observation data, gained and produced through perceptions. It additionally benefits by giving enormous stockpiling and registering capacities. Be that as it may, big earth data analytics requires explicitly planned instruments to show specificities as far as significance of the geospatial data, intricacy of handling, and wide heterogeneity of information models and arrangements [1]. Data ingestion and analysis framework for geoscience data is the study and implementation of extracting data on the system and processing it for change detection and to increase the interoperability with the help of analytical frameworks which aims at facilitating the understanding of the data in a systematic manner. In this paper, we address the challenges and opportunities in the climate data through the climate data toolbox for MATLAB [2] and how it can be beneficial to resolve various climate-change-related analytical difficulties.

Predictive maintenance and monitoring of industrial machine using machine learning

Journal

Journal NameScalable Computing

Title of PaperPredictive maintenance and monitoring of industrial machine using machine learning

PublisherWest University of Timisoara

Volume Number20(4)

Page Number663-668

Published YearDecember 2019

ISSN/ISBN No18951767

Indexed INScopus, Web of Science, EBSCO

Abstract

Machine learning is one of the break-through technologies of the modern digital world. It's applications are found in various research domain such as medicine, image processing, production and manufacturing, aviation and autonomics and many more. To efficiently run a machine, it's maintenance and its monitoring automation system play key role. The major problem we are targetting is to overcome the lack of an automation system which can give accuracy rate of the production machine at a given instance of time. Also the important energy meter parameters required to make power report in automation system for addressing the production issues, at given interval of time, were also not recorded. Thus in this paper, we describe how machine learning techniques is used for prediction of accuracy of running production machine. To address this issues, we have used supervised machine learning technique of Binary decision tree using CART method and for power report, while the data is fetched using RS232 to RS485 convertor via Modbus communication protocol. Using CART we have predicted the machine accuracy at a given time with specific energy meter readings as its input features. This paper discusses the problem definition identified, data analysis of energy meter data and it's fetching and at the end ML techniques applied to predict accuracy of running production machine. In the end we prepare various power reports of the different machines from the fetched parameters as well as produce a graphical warning of deteriorate performance of the machine at a given instance of the time. © 2019 SCPE.

IoT-based home automation with smart fan and AC using NodeMCU

Book Chapter

Book NameLecture Notes in Electrical Engineering

PublisherSpringer

Page Number197-207

Chapter Title IoT-based home automation with smart fan and AC using NodeMCU

Published YearNovember 2019

ISSN/ISBN NoISSN: 18761100 ISBN: 978-303029406-9

Indexed INScopus, PubMed, EBSCO

Clustering Algorithm for Community Detection in Complex Network: a Comprehensive Review

Journal

Journal NameRecent Patents on Computer Science

Title of PaperClustering Algorithm for Community Detection in Complex Network: a Comprehensive Review

PublisherBentham Science

Volume Number19

Published YearJune 2019

ISSN/ISBN NoISSN (Print): 2666-2558 ISSN (Online): 2666-2566

ISSN/ISBN No1793-820

Indexed INEBSCO, Others

The proliferation of digitization in the automotive industry has witnessed the drastic transition from fossil-fuel vehicles to autonomous Electric Vehicles (EVs) to enable colossal data communication in an Industrial Internet of Things (IIoT) environment. However, the malicious attacker can deter message exchange between autonomous EVs with various security attacks such as ransomware, cyber-trojan, and injection. Thus, to mitigate the aforementioned security issues, we proposed a deep learning-based secure message exchange framework, i.e., SEAM to safeguard the data communication between autonomous EVs in an IIoT environment. The proposed framework leverages the Long Short-Term Memory (LSTM) model to classify message requests as malicious or benign, enabling seamless and secure communication between EVs. The message classification performed by the LSTM helps autonomous EVs decide the message's authenticity, reducing road fatalities. The model training includes various state-of-the-art deep learning models such as Gated Recurrent Unit (GRU), Recurrent Neural Network (RNN) and LSTM. Finally, the performance of the SEAM is evaluated considering various metrics such as F-score, precision, recall, loss curve, accuracy curve, and confusion matrix for the best performing LSTM model in which Adam yields the best performance over other optimizers.

Cyber Security and Digital Forensics (Proceedings of the International Conference, ReDCySec 2023)

Book

PublisherSpringer

Published YearMarch 2024

ISSN/ISBN No978-981-99-9810-4

Indexed INScopus, Web of Science

Abstract

The book contains peer-reviewed papers from the International Conference on Recent Developments in Cyber Security organized by the Center for Cyber Security and Cryptology at Sharda University in June 2023. This volume focuses on privacy and secrecy of information, cryptography, applications and analysis, cyber threat intelligence and mitigation, cyber-physical systems, cyber threat intelligence, quantum cryptography and blockchain technologies and their application, etc. This book is a unique collection of chapters from different areas with a common theme and will be immensely useful to academic researchers and practitioners in the industry.

Multi-agent-based decentralized residential energy management using Deep Reinforcement Learning

Journal

Journal NameJournal of Building Engineering

Title of PaperMulti-agent-based decentralized residential energy management using Deep Reinforcement Learning

PublisherElsevier

Volume Number87

Page Number109031

Published YearMarch 2024

ISSN/ISBN No2352-7102

Indexed INScopus, Web of Science

Abstract

In smart grid, energy consumption has grown exponentially in residential houses, which necessitates the adoption of demand response management. To alleviate and handle the energy management in residential houses, an efficient residential energy management (REM) system can be employed to regulate the energy consumption of appliances for several energy loads such as non-shiftable, shiftable, and controllable loads. Many researchers have focused on the REM using machine learning and deep learning techniques which is not able to provide secure and optimal energy management procedure. Thus, in this paper, a multi-agent-based decentralized REM, i.e., MD-REM approach is proposed using Deep Reinforcement Learning (DRL) with the utilization of blockchain. Furthermore, The combinatorial model DQN, i.e., Q-learning and deep neural network (DNN) is employed, to gain the optimal price based on the reduced energy consumption by appliances associated with different energy loads utilizing the Markov Decision Process (MDP). Here, multiple agents are designed to handle different energy loads and consumption is controlled by the DQN agent, then reduced consumption data is securely shared among all stakeholders using blockchain-based smart contract. The performance evaluation of the proposed MD-REM approach seems to be efficient in terms of reduced energy consumption, optimal energy price, reward, and total profit analysis. Moreover, blockchain-based result is evaluated for the proposed MD-REM approach considering the performance metrics such as transaction efficiency, Interplanetary File System (IPFS) bandwidth utilization, and data storage cost comparison.

FedOnion: FL and Onion Routing-Driven Secure Data Exchange Framework for 5G-IIoT Applications

Conference

The advent of telemedicine with its remote surgical procedures has effectively transformed the working of healthcare professionals. The evolution of telemedicine facilitates the remote monitoring of patients that lead to the advent of telesurgery systems, i.e. one of the most critical applications in telemedicine systems. Apart from gaining popularity, the telesurgery system may encounter security and trust issues of patients’ data while communicating with the surgeon for their remote treatment. Motivated by this, we have presented a comprehensive survey on secure telesurgery systems comprising healthcare, surgical robots, traditional telesurgery systems, and the role of artificial intelligence to deal with the numerous security attacks associated with the patients’ health data. Furthermore, we propose a blockchain and federated learning-based secure telesurgery system to secure the communication between patient and surgeon. The results of the proposed system are better than those of the traditional system in terms of improved latency, low data storage cost, and enhanced data offloading. Finally, we explore the research challenges and issues associated with the telesurgery system.

BaRCODe: A Blockchain-based Framework for Remote COVID Detection for Healthcare 5.0

Conference

Title of PaperBaRCODe: A Blockchain-based Framework for Remote COVID Detection for Healthcare 5.0

Proceeding NameIEEE INFOCOM 2022 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

PublisherIEEE

Author NameDhairya Jadav; Dev Patel; Rajesh Gupta; Nilesh Kumar Jadav; Sudeep Tanwar

OrganizationIEEE ComSac

Year , VenueJuly 2022 , Seoul, Korea

Page Number782-787

ISSN/ISBN No2694-2941

Indexed INScopus

Abstract

PublisherIEEE

Year , VenueMarch 2022 , Noida, India

ISSN/ISBN No978-1-6654-3701-1

Indexed INScopus

A Taxonomy of Fake News Classification Techniques: Survey and Implementation Aspects

Journal

Journal NameIEEE Access

Title of PaperA Taxonomy of Fake News Classification Techniques: Survey and Implementation Aspects

Page Number30367 - 30394

Published YearMarch 2022

ISSN/ISBN No2169-3536

Indexed INScopus, Web of Science

AI-Empowered Recommender System for Renewable Energy Harvesting in Smart Grid System

Journal

Journal NameIEEE Access

Title of PaperAI-Empowered Recommender System for Renewable Energy Harvesting in Smart Grid System

PublisherIEEE

Page Number24316 - 24326

Published YearFebruary 2022

ISSN/ISBN No2169-3536

Indexed INScopus, Web of Science

A Comprehensive Review of the Technological Solutions to Analyse the Effects of Pandemic Outbreak on Human Lives

Journal

Journal NameMedicina, MDPI

Title of PaperA Comprehensive Review of the Technological Solutions to Analyse the Effects of Pandemic Outbreak on Human Lives

Published YearFebruary 2022

Indexed INScopus, Web of Science

A survey on energy-efficient resource allocation schemes in device-to-device communication

Journal

Journal NameInternational Journal of Communication Systems

Title of PaperA survey on energy-efficient resource allocation schemes in device-to-device communication

Published YearFebruary 2022

Indexed INScopus, Web of Science

BFLEdge: Blockchain based federated edge learning scheme in V2X underlying 6G communications

Conference

Title of PaperBFLEdge: Blockchain based federated edge learning scheme in V2X underlying 6G communications

Proceeding Name 2022 12th International Conference on Cloud Computing, Data Science & Engineering (Confluence)

PublisherIEEE

Author NameVishwa AmitKumar Patel; Pronaya Bhattacharya; Sudeep Tanwar; Nilesh Kumar Jadav; Rajesh Gupta

Title of PaperAdversarial learning techniques for security and privacy preservation: A comprehensive review

PublisherWiley Online Library

Published YearJanuary 2022

Federated Learning for Air Quality Index Prediction using UAV Swarm Networks

Conference

Title of PaperFederated Learning for Air Quality Index Prediction using UAV Swarm Networks

Proceeding Name2021 IEEE Global Communications Conference (GLOBECOM)

PublisherIEEE

Author NamePrateek Chhikara; Rajkumar Tekchandani; Neeraj Kumar; Sudeep Tanwar; Joel J. P. C. Rodrigues

OrganizationIEEE

Year , VenueDecember 2021 , Madrid, Spain

Page Number1-6

ISSN/ISBN No978-1-7281-8104-2

Indexed INScopus, Others

Abstract

People need to breathe, and so do other living beings, including plants and animals. It is impossible to overlook the impact of air pollution on nature, human well-being, and concerned countries' economies. Monitoring of air pollution and future predictions of air quality have lately displayed a vital concern. There is a need to predict the air quality index with high accuracy; on a real-time basis to prevent people from health issues caused by air pollution. With the help of Unmanned Aerial Vehicle's onboard sensors, we can collect air quality data easily. The paper proposes a distributed and decentralized Federated Learning approach within a UAV swarm. The accumulated data by the sensors are used as an input to the Long Short Term Memory (LSTM) model. Each UAV used its locally gathered data to train a model before transmitting the local model to the central base station. The central base station creates a master model by combining all the UAV's local model weights of the participating UAVs in the FL process and transmits it to all UAV s in the subsequent cycles. The effectiveness of the proposed model is evaluated with other machine learning models using various evaluation metrics using test data from the capital city of India, i.e., Delhi

Coalition of 6G and Blockchain in AR/VR Space: Challenges and Future Directions

Journal

Journal NameIEEE Access

Title of PaperCoalition of 6G and Blockchain in AR/VR Space: Challenges and Future Directions

Volume Number9

Published YearDecember 2021

ISSN/ISBN No2169-3536

Indexed INScopus, Web of Science

SaTYa: Trusted Bi-LSTM-Based Fake News Classification Scheme for Smart Community

Journal

Journal NameIEEE Transactions on Computational Social Systems

Title of PaperSaTYa: Trusted Bi-LSTM-Based Fake News Classification Scheme for Smart Community

PublisherIEEE

Published YearDecember 2021

ISSN/ISBN No2329-924X

Indexed INScopus, Web of Science

Machine Learning in Signal Processing: Applications, Challenges, and the Road Ahead

Book

PublisherTaylor & Francis

Published YearDecember 2021

ISSN/ISBN No9780367618902

Indexed INScopus

GaRuDa: A Blockchain-Based Delivery Scheme Using Drones for Healthcare 5.0 Applications

Journal

Journal NameIEEE Internet of Things Magazine

Title of PaperGaRuDa: A Blockchain-Based Delivery Scheme Using Drones for Healthcare 5.0 Applications

PublisherIEEE

Page Number60 - 66

Published YearDecember 2021

ISSN/ISBN No2576-3199

Indexed INScopus, Web of Science

Amalgamation of Blockchain and AI to Classify Malicious Behavior of Autonomous Vehicles

Conference

Title of PaperAmalgamation of Blockchain and AI to Classify Malicious Behavior of Autonomous Vehicles

Proceeding Name2021 International Conference on Computer, Information and Telecommunication Systems (CITS)

PublisherIEEE

Year , VenueNovember 2021 , Istanbul, Turkey

ISSN/ISBN No978-1-6654-4913-7

Indexed INScopus

Blockchain and Multiple Linear Regression-based Energy Trading Scheme for Electric Vehicles

Conference

Title of PaperBlockchain and Multiple Linear Regression-based Energy Trading Scheme for Electric Vehicles

Proceeding Name 2021 International Conference on Computer, Information and Telecommunication Systems (CITS)

PublisherIEEE

Year , VenueNovember 2021 , Istanbul, Turkey

ISSN/ISBN No978-1-6654-4913-7

Indexed INScopus

Deep learning-based malicious smart contract detection scheme for internet of things environment

Journal

Journal NameComputers & Electrical Engineering

Title of PaperDeep learning-based malicious smart contract detection scheme for internet of things environment

PublisherElseiver

Volume Number97

Published YearNovember 2021

ISSN/ISBN No0045-7906

Indexed INScopus, Web of Science

XAI-AV: Explainable Artificial Intelligence for Trust Management in Autonomous Vehicles

Conference

Title of PaperXAI-AV: Explainable Artificial Intelligence for Trust Management in Autonomous Vehicles

Proceeding Name 2021 International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI)

PublisherIEEE

Year , VenueOctober 2021 , Beijing, China

ISSN/ISBN No978-1-6654-3208-5

Indexed INScopus

Blockchain-based Data Dissemination Scheme for 5G-enabled Softwarized UAV Networks

Journal

Journal Name IEEE Transactions on Green Communications and Networking

Title of PaperBlockchain-based Data Dissemination Scheme for 5G-enabled Softwarized UAV Networks

PublisherIEEE

Volume Number5

Page Number1712 - 1721

Published YearSeptember 2021

ISSN/ISBN No2473-2400

Indexed INScopus, Web of Science

Multiagent-based secure energy management for multimedia grid communication using Q-learning

Journal

Journal NameMultimedia Tools and Applications

Title of PaperMultiagent-based secure energy management for multimedia grid communication using Q-learning

PublisherSpringerLink

Published YearSeptember 2021

ISSN/ISBN No1573-7721

Indexed INScopus, Web of Science

BCovX: Blockchain-based COVID Diagnosis Scheme using Chest X-Ray for Isolated Location

Conference

Title of PaperBCovX: Blockchain-based COVID Diagnosis Scheme using Chest X-Ray for Isolated Location

Proceeding Name ICC 2021 - IEEE International Conference on Communications

PublisherIEEE

Year , VenueAugust 2021 , Montreal, QC, Canada

ISSN/ISBN No1938-1883

Indexed INScopus

A Machine Learning Approach to Classify Network Traffic

Conference

Title of PaperA Machine Learning Approach to Classify Network Traffic

Proceeding Name2021 13th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)

PublisherIEEE

Year , VenueAugust 2021 , Pitesti, Romania

ISSN/ISBN No978-1-6654-2534-6

Indexed INScopus

Interference Mitigation and Secrecy Ensured for NOMA-Based D2D Communications Under Imperfect CSI

Conference

Title of PaperInterference Mitigation and Secrecy Ensured for NOMA-Based D2D Communications Under Imperfect CSI

Proceeding Name ICC 2021 - IEEE International Conference on Communications

PublisherIEEE

Year , VenueAugust 2021 , Montreal, QC, Canada

ISSN/ISBN No1938-1883

Indexed INScopus

FaitH: Trusted Chain Network for Non-Cooperative D2D Communication Underlying HetNet

Conference

Title of PaperFaitH: Trusted Chain Network for Non-Cooperative D2D Communication Underlying HetNet

Proceeding Name2021 13th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)

PublisherIEEE

Year , VenueAugust 2021 , Pitesti, Romania

ISSN/ISBN No978-1-6654-2534-6

Indexed INScopus

MedBlock: An AI-enabled and Blockchain-driven Medical Healthcare System for COVID-19

Conference

Title of PaperMedBlock: An AI-enabled and Blockchain-driven Medical Healthcare System for COVID-19

Proceeding NameICC 2021 - IEEE International Conference on Communications

PublisherIEEE

Year , VenueAugust 2021 , Montreal, QC, Canada

ISSN/ISBN No1938-1883

Indexed INScopus

PoRF: Proof-of-Reputation-based Consensus Scheme for Fair Transaction Ordering

Conference

Title of PaperPoRF: Proof-of-Reputation-based Consensus Scheme for Fair Transaction Ordering

Proceeding Name2021 13th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)

PublisherIEEE

Year , VenueAugust 2021 , Pitesti, Romania

ISSN/ISBN No978-1-6654-2534-6

Indexed INScopus

Res6Edge: An Edge-AI Enabled Resource Sharing Scheme for C-V2X Communications towards 6G

Conference

Title of PaperRes6Edge: An Edge-AI Enabled Resource Sharing Scheme for C-V2X Communications towards 6G

Proceeding Name2021 International Wireless Communications and Mobile Computing (IWCMC)

PublisherIEEE

Year , VenueAugust 2021 , Harbin City, China

ISSN/ISBN No2376-6506

Indexed INScopus

B-IoMV: Blockchain-based onion routing protocol for D2D communication in an IoMV environment beyond 5G

Journal

Journal NameElsevier Vehicular Communications

Title of PaperB-IoMV: Blockchain-based onion routing protocol for D2D communication in an IoMV environment beyond 5G

PublisherElseiver

Volume Number33

Published YearAugust 2021

ISSN/ISBN No2214-2096

Indexed INScopus, Web of Science

VaCoChain: Blockchain-based 5G-assisted UAV Vaccine distribution scheme for future pandemics

Journal

Journal Name IEEE Journal of Biomedical and Health Informatics

Title of PaperVaCoChain: Blockchain-based 5G-assisted UAV Vaccine distribution scheme for future pandemics

PublisherIEEE

Published YearAugust 2021

ISSN/ISBN No2168-2208

Indexed INScopus, Web of Science

Blockchain for 5G Healthcare Applications: Security and privacy solutions

Book

PublisherIET

Published YearAugust 2021

ISSN/ISBN No978-1-83953-325-9

Indexed INScopus

PRS-P2P: A Prosumer Recommender System for Secure P2P Energy Trading using Q-Learning Towards 6G

Conference

Title of PaperPRS-P2P: A Prosumer Recommender System for Secure P2P Energy Trading using Q-Learning Towards 6G

Proceeding Name 2021 IEEE International Conference on Communications Workshops (ICC Workshops)

PublisherIEEE

Year , VenueJuly 2021 , Montreal, QC, Canada

ISSN/ISBN No2694-2941

Indexed INScopus

EVBlocks: A Blockchain-Based Secure Energy Trading Scheme for Electric Vehicles underlying 5G-V2X Ecosystems

Journal

Journal NameWireless Personal Communications

Title of PaperEVBlocks: A Blockchain-Based Secure Energy Trading Scheme for Electric Vehicles underlying 5G-V2X Ecosystems

Published YearJuly 2021

ISSN/ISBN No1572-834X

Indexed INScopus, Web of Science

Fusion of AI techniques to tackle COVID-19 pandemic: models, incidence rates, and future trends

Journal

Journal NameMultimedia Systems

Title of PaperFusion of AI techniques to tackle COVID-19 pandemic: models, incidence rates, and future trends

PublisherSpringerLink

Published YearJuly 2021

ISSN/ISBN No1432-1882

Indexed INScopus, Web of Science

Secrecy-ensured NOMA-based cooperative D2D-aided fog computing under imperfect CSI

Journal

Journal NameJournal of Information Security and Applications

Title of PaperSecrecy-ensured NOMA-based cooperative D2D-aided fog computing under imperfect CSI

PublisherElseiver

Volume Number59

Published YearJune 2021

ISSN/ISBN No2214-2126

Indexed INScopus, Web of Science

Energy Consumption Minimization Scheme for NOMA-Based Mobile Edge Computation Networks Underlaying UAV

Journal

Journal NameIEEE Systems Journal

Title of PaperEnergy Consumption Minimization Scheme for NOMA-Based Mobile Edge Computation Networks Underlaying UAV

PublisherIEEE

Volume Number15

Page Number5724 - 5733

Published YearMay 2021

ISSN/ISBN No1937-9234

Indexed INScopus, Web of Science

Emergence of Cyber Physical System and IoT in Smart Automation and Robotics: Computer Engineering in Automation

Book

PublisherSpringerLink

Published YearMay 2021

ISSN/ISBN No978-3-030-66224-0

Indexed INScopus

A taxonomy of energy optimization techniques for smart cities: Architecture and future directions

Journal

Journal NameExpert Systems

Title of PaperA taxonomy of energy optimization techniques for smart cities: Architecture and future directions

PublisherWiley Online Library

Published YearApril 2021

ISSN/ISBN No1468-0394

Indexed INScopus, Web of Science

Machine learning-based traffic scheduling techniques for intelligent transportation system: Opportunities and challenges

Journal

Journal NameInternational Journal of Communication Systems

Title of PaperMachine learning-based traffic scheduling techniques for intelligent transportation system: Opportunities and challenges

PublisherWiley Online Library

Published YearApril 2021

ISSN/ISBN No1099-1131

Indexed INScopus, Web of Science

6G-enabled Edge Intelligence for Ultra -Reliable Low Latency Applications: Vision and Mission

Journal

Journal NameComputer Standards & Interfaces

Title of Paper6G-enabled Edge Intelligence for Ultra -Reliable Low Latency Applications: Vision and Mission

PublisherElseiver

Volume Number77

Published YearFebruary 2021

ISSN/ISBN No0920-5489

Indexed INScopus, Web of Science

Blockchain for 5G-Enabled IoT: The new wave for Industrial Automation

Book

PublisherSpringerLink

Published YearJanuary 2021

ISSN/ISBN No978-3-030-67490-8

Title of PaperProbabilistic Markov Model-based Health Routine Recommender System for Sleep Apnea Patients

Proceeding NameIEEE Conference on Communications (IEEE ICC-2019), Shanghai, China

OrganizationIEEE Conference on Communications (IEEE ICC-2019), Shanghai, China

Year , VenueMay 2019 , Shanghai, China

Page Number1-6

Indexed INScopus

Chapter 9 Specific Cloud Service Models

Book Chapter

Book NameInstant Guide to Cloud Computing, A. Nayyar (ed.), BPB Publications

Publisher BPB Publications

Page Number299-342

Chapter TitleChapter 9 Specific Cloud Service Models

Published YearApril 2019

ISSN/ISBN No978-93-88176-66-8

Indexed INScopus

Chapter 3: Software Errors

Book Chapter

Book NameA. Nayyar (ed.) Software Testing, BPB Publications,

PublisherA. Nayyar (ed.) Software Testing, BPB Publications,

Chapter TitleChapter 3: Software Errors

Published YearApril 2019

Indexed INScopus

Tactile Internet for Autonomous Vehicles: Latency and Reliability Analysis

Journal

Journal NameIEEE Wireless Communication Magazine

Title of PaperTactile Internet for Autonomous Vehicles: Latency and Reliability Analysis

Published YearApril 2019

Indexed INScopus, Web of Science

Securing Electronics Healthcare Records in Healthcare 4.0: A Biometric-based Approach

Journal

Journal NameComputers & Electrical Engineering,

Title of PaperSecuring Electronics Healthcare Records in Healthcare 4.0: A Biometric-based Approach

Published YearApril 2019

Indexed INScopus, Web of Science

DIYA: Tactile Internet Driven Delay Assessment NOMA-based Scheme for D2D Communication

Journal

Journal NameIEEE Transaction on Industrial Informatics

Title of PaperDIYA: Tactile Internet Driven Delay Assessment NOMA-based Scheme for D2D Communication

Page Number1-12

Published YearApril 2019

Indexed INScopus, Web of Science

Chapter 9: Specific Cloud Service Models

Book Chapter

Book NameInstant Guide to Cloud Computing, BPB Publications, 2018

Publisher BPB Publications, 2018

Chapter TitleChapter 9: Specific Cloud Service Models

Published YearApril 2019

ISSN/ISBN No978-93-88176-66-8

Journal

Journal NameInternational Journal of Communication System

Title of PaperTactile Internet for Industry 4.0 in 5G Era: A Comprehensive Review

Published YearMarch 2019

Indexed INScopus, Web of Science

“Software Defined Vehicular Networks: A Comprehensive Review

Journal

Journal NameInternational Journal of Communication System

Title of Paper“Software Defined Vehicular Networks: A Comprehensive Review

Page Number1-26

Published YearMarch 2019

Indexed INScopus, Web of Science

Cross Layer NOMA Interference Mitigation for Femtocell users in 5G

Journal

Journal NameIEEE Transaction Vehicular Technology,

Title of PaperCross Layer NOMA Interference Mitigation for Femtocell users in 5G

Page Number1-12

Published YearFebruary 2019

Indexed INScopus, Web of Science

BHEEM: A Blockchain-based Framework for Securing Electronic Health Records

Conference

Title of PaperBHEEM: A Blockchain-based Framework for Securing Electronic Health Records

Proceeding NameIEEE GLOBECOM Conference, Abu Dhabi, UAE

PublisherIEEE GLOBECOM Conference, Abu Dhabi, UAE

Year , VenueFebruary 2019 , Abu Dhabi, UAE

Indexed INScopus

Abstract

BHEEM: A Blockchain-based Framework for Securing Electronic Health Records

Human Arthritis Analysis in Fog Computing Environment using Bayesian Network Classifier and Thread Protocol

Journal

Journal NameIEEE Consumer Electronics Magazine (In press; Impact Factor: 1.434 (SCI))

Title of PaperHuman Arthritis Analysis in Fog Computing Environment using Bayesian Network Classifier and Thread Protocol

Published YearJanuary

ISSN/ISBN No2162-2248

Indexed INScopus, Web of Science

Abstract

he scope covers the following areas that are related to “consumer electronics” and other topics considered of interest to consumer electronics: video technology, audio technology, white goods, home care products, mobile communications, gaming, air care products, home medical devices, fitness devices, home automation and networking devices, consumer solar technology, home theater, digital imaging,

Fog Data Analytics: A Taxonomy and Process Model

Journal

Journal NameJournal of Network and Computer Applications

Title of PaperFog Data Analytics: A Taxonomy and Process Model

Volume Number128

Page Number90-104, 2019

Published YearJanuary 2019

Indexed INScopus, Web of Science

Fog Computing for Smart Grid Systems in 5G Environment: Challenges and Solutions

Journal

Journal NameIEEE Wireless Communication Magazine

Title of PaperFog Computing for Smart Grid Systems in 5G Environment: Challenges and Solutions

PublisherIEEE

Page Number1-7

Published YearJanuary 2019

Indexed INScopus, Web of Science

TILAA: Tactile Internet-based Ambient Assistant Living In Fog Environment

Journal

Journal NameFuture Generation Computer Systems

Title of PaperTILAA: Tactile Internet-based Ambient Assistant Living In Fog Environment

Volume Number98

Page Number635-649

Published YearJanuary 2019

Indexed INScopus, Web of Science

Evaluation of Pattern based Customized Approach for Stock Market Trend Prediction with Big Data and Machine Learning Techniques

Journal

Journal NameInternational Journal of Business Analytics, IGI Global

Title of PaperEvaluation of Pattern based Customized Approach for Stock Market Trend Prediction with Big Data and Machine Learning Techniques

Page Number1-13

Published YearJanuary 2019

Indexed INScopus

Resolving Conflicts in Requirement Engineering Through Agile Software Development: A Comparative Case Study”

Book Chapter

Book NameInternational Conference on Innovative Computing and Communications. Lecture Notes in Networks and Systems

PublisherSpringer, Singapore

Page Number349-357

Chapter TitleResolving Conflicts in Requirement Engineering Through Agile Software Development: A Comparative Case Study”

Published YearJanuary 2019

Indexed INScopus

Chapter 10: Resource Allocation in Cloud Computing

Book Chapter

Book NameInstant Guide to Cloud Computing, A. Nayyar (ed.), BPB Publications

PublisherBPB Publications

Page Number343-376

Chapter TitleChapter 10: Resource Allocation in Cloud Computing

Published YearJanuary 2019

ISSN/ISBN No978-93-88176-66-8

Indexed INScopus

Online Signature-based Biometrics Recognition

Book Chapter

Book NameBiometric-Based Physical and Cybersecurity Systems,, Springer Nature Switzerland AG 2019

PublisherBiometric-Based Physical and Cybersecurity Systems,, Springer Nature Switzerland AG 2019

Page Number255-285

Chapter Title Online Signature-based Biometrics Recognition

Published YearJanuary 2019

Indexed INScopus

Tensor Decomposition of Biometric Data using Singular Value Decomposition.

Comparison and Evaluation of Real Time Reservation Technologies in the Intelligent Public Transport System

Conference

Title of PaperComparison and Evaluation of Real Time Reservation Technologies in the Intelligent Public Transport System

Proceeding NameFifth International Conference on Parallel, Distributed and Grid Computing (PDGC) (PDGC-2018), Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh, India

Page Number1-6

Published YearDecember 2018

Indexed INScopus

CR-NOMA based Interference Mitigation Scheme for 5G Femtocells users

Conference

Title of PaperCR-NOMA based Interference Mitigation Scheme for 5G Femtocells users

Proceeding NameIEEE Global Communications Conference (IEEE GLOBECOM- 2018), Abu Dhabi, UAE,

Year , VenueDecember 2018 , (IEEE GLOBECOM- 2018), Abu Dhabi, UAE,

Page Number1-6

Indexed INScopus

MRD: Sink-based Multi Route Diversity for Wireless Sensor Networks

Conference

Title of PaperMRD: Sink-based Multi Route Diversity for Wireless Sensor Networks

Proceeding NameIEEE Global Communications Conference (IEEE GLOBECOM-2018) Abu Dhabi, UAE

Page Number1-6

Published YearDecember 2018

Indexed INScopus

Hybrid Energy System for Upgrading the Rural Environment

Conference

Title of PaperHybrid Energy System for Upgrading the Rural Environment

Proceeding NameIEEE Global Communications Conference (IEEE GLOBECOM-2018), Abu Dhabi, UAE

PublisherIEEE Global Communications Conference (IEEE GLOBECOM-2018), Abu Dhabi, UAE

Page Number1-6

Published YearDecember 2018

Indexed INScopus

“Comparison and Evaluation of Real Time Reservation Technologies in the Intelligent Public Transport System

Book Chapter

Book NameFifth International Conference on Parallel, Distributed and Grid Computing (PDGC) (PDGC-2018),

Page Number1-6

Chapter Title“Comparison and Evaluation of Real Time Reservation Technologies in the Intelligent Public Transport System

Published YearDecember 2018

Indexed INScopus

Journal

Journal NameJournal of Network and Computer Applications

Title of PaperMultimedia Big Data Computing and Internet of Things Applications: A Taxonomy and Process Model

Volume Number124

Page Number 169-195

Published YearDecember 2018

ISSN/ISBN No1084-8045

Indexed INScopus, Web of Science

Abstract

With an exponential increase in the provisioning of multimedia devices over the Internet of Things (IoT), a significant amount of multimedia data (also referred to as multimedia big data – MMBD) is being generated. Current research and development activities focus on scalar sensor data based IoT or general MMBD and overlook the complexity of facilitating MMBD over IoT.

ADYTIA: Adaptive and Dynamic TCP Interface Architecture for Mobile Data Offloading in Heterogeneous Networks

Journal

Journal NameInternational Journal of Communication System

Title of PaperADYTIA: Adaptive and Dynamic TCP Interface Architecture for Mobile Data Offloading in Heterogeneous Networks

Volume Number32:2

Page Number1-20

Published YearNovember 2018

Indexed INScopus, Web of Science

Verification and Validation Techniques for Streaming Big Data Analytics in Internet of Things Environment

Journal

Journal NameIET Networks, 2019,

Title of PaperVerification and Validation Techniques for Streaming Big Data Analytics in Internet of Things Environment

Page Number1-8, DOI: 10.1049/ietnet.2018.518, 2019

Published YearNovember 2018

Indexed INScopus

Fog Computing for Healthcare 4.0 Environment: Opportunities and Challenges

Journal

Journal NameComputers & Electrical Engineering, Elsevier (SCI, IF: 1.747)

Title of PaperFog Computing for Healthcare 4.0 Environment: Opportunities and Challenges

PublisherElsevier

Volume Number72

Page Number1-13

Published YearNovember 2018

ISSN/ISBN No0045-7906

Indexed INScopus, Web of Science

Abstract

Internet of things provides interaction with billions of objects across the world using the Internet. In Internet of thing era, Healthcare Industry has grown-up from 1.0 to 4.0 generation. Healthcare 3.0 was hospital centric, where patients of long-lasting sickness suffered a lot due to multiple hospital visits for their routine checkups. This in turn, prolonged the treatment of such patients.

Resolving Conflicts in Requirement Engineering through Agile Software Development: A Comparative Case Study

Book Chapter

Book NameIn: Bhattacharyya S., Hassanien A., Gupta D., Khanna A., Pan I. (eds) International Conference on Innovative Computing and Communications. Lecture Notes in Networks and Systems, vol 55. Springer, Singapore

PublisherLecture Notes in Networks and Systems, Springer

Author Name Bhattacharyya, S., Hassanien

Page Number349-357

Chapter TitleResolving Conflicts in Requirement Engineering through Agile Software Development: A Comparative Case Study

Published YearNovember 2018

ISSN/ISBN No978-981-13-2324-9

Indexed INScopus

“A Systematic Review on Security Issues in VANET”, Security and P

Journal

Journal NameSecurity and Privacy Journal, Wiley

Title of Paper“A Systematic Review on Security Issues in VANET”, Security and P

PublisherWiley

Volume Number1:5

Page Number1-27

Published YearAugust 2018

Indexed INScopus, Web of Science

A Systematic Review on Scheduling Public Transport using IoT as Tool

Conference

Title of PaperA Systematic Review on Scheduling Public Transport using IoT as Tool

Proceeding NameSmart Innovations in Communication and Computational Sciences. Advances in Intelligent Systems and C

PublisherSpringer, Singapore,

Year , VenueJuly 2018 , Singapore,

Page Number39-48

ISSN/ISBN No978-981-10-8970-1

Indexed INScopus

Design of an Anonymity-Preserving Group Formation Based Authentication Protocol in Global Mobility Networks

Journal

Journal NameIEEE Access (SCI, Impact Factor: 3.557)

Title of PaperDesign of an Anonymity-Preserving Group Formation Based Authentication Protocol in Global Mobility Networks

PublisherIEEE Access

Volume Number6(1)

Page Number20673-20693

Published YearMay 2018

ISSN/ISBN No2169-3536

Indexed INScopus, Web of Science

Abstract

Global mobility networks (GLOMONETs) provide the ubiquitous services for mobile users while enabling global roaming. Each user belongs to a specific home network (HA) where he/she is registered. When a user is in the domain of a foreign agent (FA), the FA needs to provide service only after authenticating the user (with HA’s help). A remote user authentication scheme for GLOMONETs needs to validat

M-Tesla-Based Security Assessment in Wireless Sensor Network

Journal

Journal NameProcedia Computer Science, Elsevier. (Indexed in SCOPUS)

Title of PaperM-Tesla-Based Security Assessment in Wireless Sensor Network

PublisherElsevier

Volume Number132

Page Number1154-1162.

Published YearApril 2018

ISSN/ISBN No1877-0509

Indexed INScopus, Web of Science

LA-MHR: Learning Automata Based Multilevel Heterogeneous Routing for Opportunistic Shared Spectrum Access to Enhance Lifetime of WSN

Journal

Journal NameIEEE Access (SCI, Impact Factor: 3.557)

Title of PaperLA-MHR: Learning Automata Based Multilevel Heterogeneous Routing for Opportunistic Shared Spectrum Access to Enhance Lifetime of WSN

Publisher IEEE Systems Journal

Volume Number6

Page Number1-11

Published YearApril 2018

ISSN/ISBN No2169-3536

Indexed INScopus, Web of Science

Abstract

n wireless sensor networks (WSNs), optimal energy utilization is one of the most crucial issues which needs special attention. It has been observed from the existing literature that communication among sensor nodes (SNs) consumes more energy than computation. Therefore, an efficient mechanism needs to be designed for energy conservation during communication among different SNs. To address these ga

Chapter 10: Resource Allocation in Cloud Computing

Book Chapter

Book NameInstant Guide to Cloud Computing, BPB Publications, 2018

PublisherBPB Publications, 2018

Chapter TitleChapter 10: Resource Allocation in Cloud Computing

Published YearApril 2018

ISSN/ISBN No978-93-88176-66-8

Indexed INScopus

Software Defined Network-Based Vehicular Adhoc Networks for Intelligent Transportation System: Recent Advances and Future Challenges

Book Chapter

Book NameCommunications in Computer and Information Science

PublisherSpringer singapure

Page Number325-337

Chapter TitleSoftware Defined Network-Based Vehicular Adhoc Networks for Intelligent Transportation System: Recent Advances and Future Challenges

Published YearFebruary 2018

Conference

Title of PaperEnsuring Privacy and Security in E-Health Records

PublisherIEEE CITS-2018, Colmar, France

Year , VenueJanuary 2018 , IEEE CITS-2018, Colmar, France

ISSN/ISBN No978-1-5386-4599-4

Indexed INScopus

Blind Signatures Based Secured E-Healthcare System

Conference

Title of PaperBlind Signatures Based Secured E-Healthcare System

PublisherIEEE CITS-2018, Colmar, France

Year , VenueJanuary 2018 , IEEE CITS-2018, Colmar, France

ISSN/ISBN No978-1-5386-4599-4

Indexed INScopus

TCP-EXPO: Empirical Approach to Transport Layer Protocol for High-Speed Networks

Conference

Title of PaperTCP-EXPO: Empirical Approach to Transport Layer Protocol for High-Speed Networks

Proceeding NameIEEE ICC-2018, Kansas City, USA (Indexed in IEEE-Xplore, SCOPUS)

PublisherIEEE ICC-2018, Kansas City, USA (Indexed in IEEE-Xplore, SCOPUS)

Year , VenueJanuary 2018 , IEEE ICC-2018, Kansas City, USA

ISSN/ISBN No2474-9133

Indexed INScopus

A Range-based approach for Long-Term Forecast of Weather Using Probabilistic Markov Model

Conference

Title of PaperA Range-based approach for Long-Term Forecast of Weather Using Probabilistic Markov Model

PublisherIEEE ICC-2018, Kansas City, USA (Indexed in IEEE-Xplore, SCOPUS)

Year , VenueJanuary 2018 , IEEE ICC-2018, Kansas City, USA

ISSN/ISBN No2474-9133

Indexed INScopus

his book presents the latest developments in biometrics technologies and reports on new approaches, methods, findings, and technologies developed or being developed by the research community and the industry. The book focuses on introducing fundamental principles and concepts of key enabling technologies for biometric systems applied for both physical and cyber security.

Mobile Computing

Book

PublisherBhavya Publication, Delhi

Published YearMarch 2017

ISSN/ISBN No978-93-83992-25-6

Energy Optimization in Smart Grid using Tensor Decomposition

Journal

Journal NameInternational Journal of Computer Sciences and Engineering (Indexed in ICI, Google Scholar,UGC listed

Title of PaperEnergy Optimization in Smart Grid using Tensor Decomposition

Volume Number5:11

Page Number192-196

Published YearJanuary 2017

ISSN/ISBN No0974-5572

Indexed INScopus, Web of Science

Public Transport Tracking and its Issues

Journal

Journal NameInternational Journal of Computer Sciences and Engineering (Indexed in ICI, Google Scholar as well a

Title of PaperPublic Transport Tracking and its Issues

Volume Number5:11

Published YearJanuary 2017

ISSN/ISBN No2347-2693

Indexed INScopus, Web of Science

HDNcfm: Handwritten Digit Recognition System Using No Combination of Feature Maps

Journal

Journal NameInternational Journal of Advanced Research in Computer Science

Title of Paper HDNcfm: Handwritten Digit Recognition System Using No Combination of Feature Maps

Volume Number8

Published YearJanuary 2017

ISSN/ISBN No0976-5697

Indexed INScopus, Web of Science

PI-Cloud: A Sensor-Cloud oriented Measurement to Management System for Precise Irrigation based Agriculture

Conference

Title of PaperPI-Cloud: A Sensor-Cloud oriented Measurement to Management System for Precise Irrigation based Agriculture

Proceeding NameIEEE International Conference on Global Communication, GLOBECOM- 2017, Singapore

Year , VenueJanuary 2017 , GLOBECOM- 2017, Singapore

ISSN/ISBN No978-1-5090-5019-2

Indexed INScopus

Suitability of Big Data Analytics in Indian Banking Sector to Increase Revenue and Profitability

Conference

Title of PaperSuitability of Big Data Analytics in Indian Banking Sector to Increase Revenue and Profitability

Proceeding NameIEEE, ICACCA-2017, Tula Institute, Dehradhun, UA

Year , VenueJanuary 2017 , IEEE, ICACCA-2017, Tula Institute, Dehradhun, UA

ISSN/ISBN No978-1-5090-6403-8

Indexed INScopus

Fog based Enhanced Safety Management System for Miners

Conference

Title of PaperFog based Enhanced Safety Management System for Miners

Proceeding NameIEEE, ICACCA-2017, Tula Institute, Dehradhun, UA

Year , VenueJanuary 2017 , IEEE, ICACCA-2017, Tula Institute, Dehradhun, UA

ISSN/ISBN No978-1-5090-6403-8

Indexed INScopus

FAAL: Fog Computing based Patient Monitoring System for Ambient Assisted Living

Conference

Title of PaperFAAL: Fog Computing based Patient Monitoring System for Ambient Assisted Living

Proceeding NameIEEE 19th International Conference on e-Health Networking, Applications and Services, Healthcom-2017

PublisherIEEE 19th International Conference on e-Health Networking, Applications and Services, Healthcom-2017

Published YearJanuary 2017

ISSN/ISBN No978-1-5090-6704-6

Indexed INScopus

Home-based Exercise System for Patients Using IoT Enabled Smart Speaker

Conference

Title of PaperHome-based Exercise System for Patients Using IoT Enabled Smart Speaker

Proceeding NameIEEE 19th International Conference on e-Health Networking, Applications and Services, Healthcom-2017

Published YearJanuary 2017

ISSN/ISBN No978-1-5090-6704-6

Indexed INScopus

An Advanced Internet of Thing based Security Alert System for Smart Home

Conference

Title of PaperAn Advanced Internet of Thing based Security Alert System for Smart Home

PublisherInternational Conference on Computer, Information and Telecommunication Systems IEEE-CITS-2017, Dali

Year , VenueJanuary 2017 , IEEE-CITS-2017, Dali

ISSN/ISBN No978-1-5090-5957-7

Indexed INScopus

GATA: GPS-Arduino Based Tracking and Alarm System for Protection of Wildlife Animals

Conference

Title of PaperGATA: GPS-Arduino Based Tracking and Alarm System for Protection of Wildlife Animals

Proceeding Namenternational Conference on Computer, Information and Telecommunication Systems IEEE-CITS-2017, Dali

Publishernternational Conference on Computer, Information and Telecommunication Systems IEEE-CITS-2017, Dali

Year , VenueJanuary 2017 , IEEE-CITS-2017, Dali

ISSN/ISBN No978-1-5090-5957-7

Indexed INScopus

Big Data Analytics

Book

PublisherBhavya Publication, Delhi

Published YearJanuary 2017

ISSN/ISBN No978-93-83992-25-8

Routing in Heterogeneous Wireless Sensor Networks

Book

PublisherLap Lambert Academic Publishing, Germany

Published YearDecember 2016

ISSN/ISBN No978-3-330-02892-0

Abstract

Although many proposals exist in market addressing the Routing in HWSN issue, but node heterogeneity of SNs has not been exploited to its full potential. So there is a requirement of categorization of SNs based upon different performance evaluation metrics. Motivated by the above facts, in this book, we provide a complete categorization of various heterogeneous routing protocols for WSNs.

Analysis of Software Testing Techniques: Theory to Practical Approach

Journal

Journal NameIndian Journal of Science and Technology

Title of PaperAnalysis of Software Testing Techniques: Theory to Practical Approach

Volume Number9(32)

Page Number1-6

Published YearAugust 2016

ISSN/ISBN No0974-6846

Indexed INScopus, Web of Science, EBSCO

Abstract

n today’s scenario software testing is crucial aspect for any software company because the cost of maintenance is much more than development in software companies. We all make mistakes, some of them are not important, but some of them are harmful for software life cycle. So we should start testing the code/software that we are going to generate from initial stage because at later stage recovery

Min-Parent: An Effective Approach to Enhance Resource Utilization in Cloud Environment,

Conference

Title of PaperMin-Parent: An Effective Approach to Enhance Resource Utilization in Cloud Environment,

PublisherIEEE-ICACCA- 2016, Dehradhun, UA

Published YearJanuary 2016

ISSN/ISBN No978-1-5090-0673-1

IoT, Smart Grid and M2M are paradigms that are expected to dominate in 5G networks and, hence, the role of WSNs is of great importance. In WSNs, horizontal and vertical levels of node heterogeneity has been studied in the past for various operation such as data capturing, processing and communication at different levels of nodes in wireless sensor networks (WSNs). For saving energy consumption of

Learning Automata-Based Coverage Oriented Clustering in HWSNs

Conference

Title of PaperLearning Automata-Based Coverage Oriented Clustering in HWSNs

Proceeding NameIEEE-ICACCE-2015, Dehradhun, UA

Year , VenueJanuary 2015 , Dehradhun, UA

ISSN/ISBN No978-1-4799-1734-1

Indexed INScopus

Bayesian Coalition Game-Based Optimized Clustering in Wireless Sensor Networks

Conference

Title of PaperBayesian Coalition Game-Based Optimized Clustering in Wireless Sensor Networks

Proceeding NameIEEE International Conference on Communications (IEEE-ICC-2015), London, UK

Published YearJanuary 2015

ISSN/ISBN No978-1-4673-6432-4

Indexed INScopus

EEMHR: Energy-efficient multilevel heterogeneous routing protocol for wireless sensor networks

Journal

Journal NameInternational Journal of Communication System, Wiley (SCI, Impact Factor: 1.717)

Title of PaperEEMHR: Energy-efficient multilevel heterogeneous routing protocol for wireless sensor networks

PublisherWiley

Volume Number27(9)

Published YearMarch 2014

ISSN/ISBN No1099-1131

Indexed INScopus, Web of Science

Abstract

Wireless Sensor Networks (WSNs) are being used in wide areas of applications for data collection and processing. Energy management is one of the crucial issues that need special attention in WSNs. But most of the existing solutions for energy management are restricted in defining the number of levels for node heterogeneity for efficient energy management. Due to this restriction, a performance deg

Selective Cluster Based Energy Efficient routing protocol for homogeneous wireless sensor network

Journal

Journal NameWireless BANs for Pervasive Healthcare & Smart Environments, ZTE Communication

Title of PaperSelective Cluster Based Energy Efficient routing protocol for homogeneous wireless sensor network

Volume Number12(3)

Published YearJanuary 2014

Indexed INScopus, Web of Science

EHE-LEACH: Enhanced Heterogeneous LEACH Protocol for Lifetime Enhancement of WSNs,

Conference

Title of PaperEHE-LEACH: Enhanced Heterogeneous LEACH Protocol for Lifetime Enhancement of WSNs,

Proceeding NameIEEE-ICACCI-3013 Cited by 14 (IEEE Digital Library), 24 (Google Scholar)

Published YearJanuary 2013

ISSN/ISBN No978-1-4673-6217-7

Indexed INScopus

Software Testability Analysis using Cyclomatic Complexity

Conference

Title of PaperSoftware Testability Analysis using Cyclomatic Complexity

Proceeding NameNational conference on RTACM, Tiagrajar School of Management, Madurai (Tamilnadu)

Year , VenueJanuary 2009 , National conference on RTACM, Tiagrajar School of Management, Madurai (Tamilnadu)

Indexed INScopus

MPI Messaging Structure for Mobile Adhoc Network

Journal

Journal NameInternational Journal of Hybrid Computational Intelligence

Title of PaperMPI Messaging Structure for Mobile Adhoc Network

Volume Number1(2)

Page Number215-224

Published YearJanuary 2008

ISSN/ISBN No0975-3680

Indexed INScopus, Web of Science

Sunil Gautam

Wireless Sensor Networks With the Context of Knowledge-Based Management

Book Chapter

Book NameConstraint Decision-Making Systems in Engineering

PublisherIGI Global

Author NameSunil Gautam

Page Number18-40

Chapter TitleWireless Sensor Networks With the Context of Knowledge-Based Management

Published YearJanuary 2023

Indexed INScopus

Abstract

Wireless sensor networks (WSN) play in vital role in different research area technology, electronics, and telecommunication, but these wireless sensor networks have limited computational capability and memory. The basic functions of WSN are analysis, processing, storage, and mining of data. Due to the flexibility of WSN in solving problems of various fields, it has gained more popularity. WSNs have been successfully applied in a variety of applications. In these days, knowledge management systems are attracting research that emerge with wireless sensor networks to reduce drawback of sensors. This chapter presents the review literature of knowledge management and demonstrates creating, managing, sharing, and utilizing in organizations.

Intelligent Intrusion Detection System Using Deep Learning Technique

Conference

Title of PaperIntelligent Intrusion Detection System Using Deep Learning Technique

Proceeding NameComputing, Communication and Learning: First International Conference, CoCoLe 2022

PublisherSpringer Nature Switzerland

Author NameSunil Gautam

OrganizationNIT Warangal,

Year , VenueJanuary 2023 , NIT Warangal,

Page Number220-230

Indexed INScopus

Abstract

There is constant growth in the digitization of information across the world. However, this rapid growth has raised concerns over the security of the information. Today’s internet is made up of nearly half a million different networks. Network intrusions are very common these days which put user information at high risk. An intrusion detection system (IDS) is a software/system to analyze and monitor the data for the detection of intrusions in the host/network. An intrusion Detection System competent in detecting zero-day attacks and network anomalies is highly demanded. Researchers have used different methods to develop robust IDS. However, none of the methods is exceptionally well and meets every requirement of IDS. Machine learning/Deep learning (ML/DL) are among the widely used methods to develop IDS. This proposed technique uses a DL model, Recurrent Neural Network (RNN) with Gated Recurrent

Composition of Hybrid Deep Learning Model and Feature Optimization for Intrusion Detection System

Journal

Journal NameMDPI Sensors

Title of PaperComposition of Hybrid Deep Learning Model and Feature Optimization for Intrusion Detection System

PublisherMDPI

Volume Number23(2)

Page Number890

Published YearJanuary 2023

Indexed INScopus, Web of Science

Abstract

Recently, with the massive growth of IoT devices, the attack surfaces have also intensified. Thus, cybersecurity has become a critical component to protect organizational boundaries. In networks, Intrusion Detection Systems (IDSs) are employed to raise critical flags during network management. One aspect is malicious traffic identification, where zero-day attack detection is a critical problem of study. Current approaches are aligned towards deep learning (DL) methods for IDSs, but the success of the DL mechanism depends on the feature learning process, which is an open challenge. Thus, in this paper, the authors propose a technique which combines both CNN, and GRU, where different CNN–GRU combination sequences are presented to optimize the network parameters. In the simulation, the authors used the CICIDS-2017 benchmark dataset and used metrics such as precision, recall, False Positive Rate (FPR), True Positive Rate (TRP), and other aligned metrics. The results suggest a significant improvement, where many network attacks are detected with an accuracy of 98.73%, and an FPR rate of 0.075. We also performed a comparative analysis with other existing techniques, and the obtained results indicate the efficacy of the proposed IDS scheme in real cybersecurity setups.

Data-Driven Android Malware Analysis Intelligence

Book Chapter

Book NameMethods, Implementation, and Application of Cyber Security Intelligence and Analytics

PublisherIGI Global

Author NameSunil Gautam

Page Number181-200

Chapter TitleData-Driven Android Malware Analysis Intelligence

Published YearOctober 2022

Indexed INScopus

Abstract

Android OS powers the majority of the market share. Malware acts as stimuli to the vulnerabilities in Android devices as it affects a huge amount of user data. Users' data is at high risk when it comes to attacks through varied types of malware. Also, mutations in malware have brought up newer variants in them. Malware families have been expanding, thereby making analysis and classification diverse. Mainly classified into static, dynamic, and alternative or hybrid analysis, the field of malware analysis is facing many repercussions. The development of malware is endless and hence calls for intelligent and self-learning approaches in this regard. However, more distinct techniques are in need and can be served by integrating intelligent and analytical capabilities. This chapter involves a fourfold approach with major contributions to review existing Android malware analysis techniques, intelligent techniques for Android.

A Composite Approach of Intrusion Detection Systems: Hybrid RNN and Correlation-Based Feature Optimization

Journal

Journal NameA Composite Approach of Intrusion Detection Systems: Hybrid RNN and Correlation-Based Feature Optimization

Title of PaperA Composite Approach of Intrusion Detection Systems: Hybrid RNN and Correlation-Based Feature Optimization

PublisherElectronics MDPI

Volume Number11

Page Number1-25

Published YearOctober 2022

An intrusion detection system (IDS) detects the malicious activities, running in the system that may be a single system or a networked system. Furthermore, the intrusion-based systems monitor the data in a system against the suspicious activities and also secure the entire network. Detection of malicious attacks with keeping acceptability of low false alarm rate is a challenging task in intrusion detection. In this paper, we analyze the three statistical approaches namely principal component analysis (PCA), linear discriminant analysis (LDA), and naive Bayes classifier (NBC), employed in host-based intrusion detection systems (HIDS) and we detect the accuracy rate using these approaches.

Anomaly detection system using entropy based technique

Conference

Title of PaperAnomaly detection system using entropy based technique

Proceeding Name1st International Conference on Next Generation Computing Technologies (NGCT)

Author NameIEEE

Page Number738-743

Published YearApril 2015

Indexed INScopus

Abstract

An Intrusion detection system (IDS) is a module of software and/or hardware that monitors the activities occurring in a computer system or network system. The IDSs use various algorithms for detecting malicious activities. One of them is feature selection algorithm that depends on dimensionality reduction of the datasets. In this paper, we propose a novel feature selection algorithm based on information gain (entropy). We use the Knowledge Discovery and Data Mining cup dataset'99 for detecting the attacks and to classify them in four categories as well. Our algorithm provides better detection rate than the existing Fast Feature Reduction in Intrusion Detection Datasets (FFRIDD) and Multi-Level Dimensionality Reduction Methods (MLDRM).

Multivariate linear regression model for host based intrusion detection

Conference

Title of PaperMultivariate linear regression model for host based intrusion detection

Proceeding NameComputational Intelligence in Data Mining

PublisherSpringer, New Delhi

Author NameSunil Gautam

Page Number361-371

Published YearJanuary 2015

Indexed INScopus

Abstract

Computer security is an important issue for an organization due to increasing cyber-attacks. There exist some intelligent techniques for designing intrusion detection systems which can protect the computer and network systems. In this paper, we discuss multivariate linear regression model (MLRM) to develop an anomaly detection system for outlier detection in hardware profiles. We perform experiments on performance logfiles taken from a personal computer. Simulation results show that our model discovers intrusion effectively and efficiently.

Swati Jain

Parameter optimization for surface mounter using a self-alignment prediction model

Journal

Journal NameSoldering & Surface Mount Technology

Title of Paper Parameter optimization for surface mounter using a self-alignment prediction model

PublisherEmerald Publishing Limited

Volume Number35

Page Number78-85

Published YearFebruary 2023

Indexed INScopus, Web of Science

Machine Learning-Based Model for Effective Resource Provisioning in Cloud

Conference

Title of PaperMachine Learning-Based Model for Effective Resource Provisioning in Cloud

Proceeding NameFuturistic Trends in Networks and Computing Technologies: Select Proceedings of Fourth International Conference on FTNCT 2021

PublisherSpringer Nature-Nirma University

Author NamePayal Saluja, Swati Jain, Madhuri Bhavsar

OrganizationNirma University

Page Number935-950

Published YearNovember 2022

Abstract

With the rise of digitization, documents are being created, modified, and shared digitally. Unlike hard copies, it is difficult to ascertain the authenticity of these digital documents. Thus, there is a need to authenticate and verify digital documents in an efficient manner. In this chapter, a decentralized application has been proposed, which uses a smart contract to facilitate the authentication and verification of documents by leveraging the blockchain technology. In contrast to the traditional way of storing the entire input digital document, this approach creates a unique fingerprint of every input document by using a cryptographic hash function. This fingerprint is stored on the blockchain network to verify the document in future. This blockchain based solution can be used by organizations to authenticate the documents that they generate and allow other entities to verify them.

Prediction of Mental Illness in Heart Disease Patients: Association of Comorbidities, Dietary Supplements, and Antibiotics as Risk Factors

Journal

Journal NameJournal of personalized medicine

Title of PaperPrediction of Mental Illness in Heart Disease Patients: Association of Comorbidities, Dietary Supplements, and Antibiotics as Risk Factors

PublisherMDPI

Volume Number10

Page Number214

Published YearNovember 2020

Indexed INScopus

Abstract

Comorbidities, dietary supplement use, and prescription drug use may negatively (or positively) affect mental health in cardiovascular patients. Although the significance of mental illnesses, such as depression, anxiety, and schizophrenia, on cardiovascular disease is well documented, mental illnesses resulting from heart disease are not well studied. In this paper, we introduce the risk factors of mental illnesses as an exploratory study and develop a prediction framework for mental illness that uses comorbidities, dietary supplements, and drug usage in heart disease patients. Particularly, the data used in this study consist of the records of 68,647 patients with heart disease, including the patient’s mental illness information and the patient’s intake of dietary supplements, antibiotics, and comorbidities. Patients in age groups <61, gender differences, and drug intakes, such as Azithromycin, Clarithromycin, Vitamin B6, and Coenzyme Q10, were associated with mental illness. For predictive modeling, we consider applying various state-of-the-art machine learning techniques with tuned parameters and finally obtain the following: Depression: 78.01% accuracy, 79.13% sensitivity, 72.65% specificity, and 86.26% Area Under the Curve (AUC). Anxiety: 82.93% accuracy, 82.86% sensitivity, 83.35% specificity, and 88.45% AUC. Schizophrenia: 87.59% accuracy, 87.70% sensitivity, 85.14% specificity, and 92.73% AUC. Disease: 86.63% accuracy, 95.50% sensitivity, 77.76% specificity, and 91.59% AUC. From the results, we conclude that using heart disease information, comorbidities, dietary supplement use, and antibiotics enables us to accurately predict …

Deep Neural Network based classification of tumorous and non-tumorous Medical Images

Book Chapter

Book NameSpringer Smart Innovation, Systems and Technologies

Chapter TitleDeep Neural Network based classification of tumorous and non-tumorous Medical Images

Published YearJanuary

Indexed INScopus

Deep Q-Learning for Navigation of Robotic Arm for Tokamak Inspection

Journal

Journal NameAlgorithms and Architectures for Parallel Processing

Title of PaperDeep Q-Learning for Navigation of Robotic Arm for Tokamak Inspection

PublisherSpringer

Volume Number11337

Page Number10

Published YearDecember 2018

ISSN/ISBN No978-3-030-05063-4

Indexed INOthers

Abstract

Computerized human-machine interfaces are used to control the manipulators and robots for inspection and maintenance activities in Tokamak. The activities embrace routine and critical activities such as tile inspection, dust cleaning, equipment handling and replacement tasks. Camera(s) is deployed on the robotic arm which moves inside the chamber to accomplish the inspection task. For navigating t

A Proposed Method for Disruption Classification in Tokamak Using Convolutional Neural Network

Book Chapter

Book NameTowards Extensible and Adaptable Methods in Computing

Chapter TitleA Proposed Method for Disruption Classification in Tokamak Using Convolutional Neural Network

Published YearJanuary 2018

Abstract

Thermonuclear fusion is one of the alternative sources of energy. Fusion reactors use a device called tokamak. Classification of favorable and non-favorable discharges in a tokamak is very important for plasma operation point of view. Non-favorable discharges are mainly disruptive in nature which causes certain losses of confinement that take place abruptly and affect the integrity of tokamak. Dur

Weighted Fusion of LBP and CCH Features for Effective Content Based Image Retrieval

Conference

Title of PaperWeighted Fusion of LBP and CCH Features for Effective Content Based Image Retrieval

Proceeding NameInternational Conference on Signal Processing and Communications (SPCOM'16), IISC, Bangalore

OrganizationIISC, Bangalore

Published YearJanuary 2018

Deep learning feature map for content based image retrieval system for remote sensing application

Journal

Journal NameInternational Journal of Image Mining

Title of PaperDeep learning feature map for content based image retrieval system for remote sensing application

PublisherInderscience

Volume Number2

Page Number11

Published YearSeptember 2016

Abstract

This paper proposes a model for content based image retrieval system (CBIR), in which handcrafted feature set is replaced with feature set learnt from deep learning, convolutional neural network (CNN) for image retrieval. Feature map obtained from CNN is of high dimension, which makes the matching process expensive in terms of time and computation. Hence to recapitulate information in smaller dime

Parallel Approach To Expedite Morphological Feature Extraction Of Remote Sensing Images for CBIR System

Conference

Title of PaperParallel Approach To Expedite Morphological Feature Extraction Of Remote Sensing Images for CBIR System

Proceeding Name35th IEEE International Geoscience and Remote Sensing Symposium, Quebec Canada

PublisherIEEE

OrganizationQuebec City, QC, Canada

Year , VenueNovember 2014 , Quebec City, QC, Canada

Page Number4

ISSN/ISBN No14716409

Abstract

In this paper, we have proposed a parallel approach to the morphological feature extraction process and demonstrated a good computational speedup. Remote sensing images have a typical property of incrementing constantly and each image being very large. Since the images are acquired constantly and hence added into the database regularly in good numbers, hence there is a need to make the feature ext

Computation Performance Gain in Key Feature Extraction for CBIR system for Remote Sensing Images

Conference

Title of PaperComputation Performance Gain in Key Feature Extraction for CBIR system for Remote Sensing Images

Proceeding NameEighth International Conference on Image and Signal Processing (ICISP 2014), Elsevier

Published YearJanuary 2014

ISSN/ISBN No9789351072522

Exploring a new direction in colour and texture based satellite image search and retrieval system

Conference

Title of PaperExploring a new direction in colour and texture based satellite image search and retrieval system

Proceeding Name2011 Nirma University International Conference on Engineering

PublisherIEEE

OrganizationNirma University

Year , VenueDecember 2012 , Nirma University, Ahmedabad, Gujarat, India

Page Number5

ISSN/ISBN No2375-1282

Abstract

Content based Image Retrieval systems (CBIR) have become a reliable tool for many image database applications. Today, the need for reliable, automated satellite image classification and browsing systems is more than ever before. Everyday there is a massive amount of remotely sensed data being collected and sent by terrestrial satellites for analysis. The use of automated tools for this analysis ha

Detection of Moving Object using Continuous Background Estimation Based on Probability of Pixel Intensity Occurrences

Journal

Journal NameInternational Journal of Computer Science and Telecommunications

Title of PaperDetection of Moving Object using Continuous Background Estimation Based on Probability of Pixel Intensity Occurrences

PublisherIJCST

Volume Number3

Page Number5

Published YearMay 2012

Abstract

Video object segmentation is an important part of real time surveillance system. For any video segmentation algorithm to be suitable in real time, must require less computational load. This paper addresses the problem of maintaining the background with the changes in the scene. The algorithm proposed in this paper enables to update the background image timely without compromising the time taken fo

Performance Measure of Image Processing Algorithms on DSP Processor & FPGA Based Coprocessor

Conference

Title of PaperPerformance Measure of Image Processing Algorithms on DSP Processor & FPGA Based Coprocessor

Proceeding Name2010 International Conference on Advances in Communication, Network, and Computing

Published YearOctober 2010

Abstract

Published YearJuly 2019

Indexed INScopus

A survey and evaluation of supervised machine learning techniques for spam e-mail filtering

Conference

Title of PaperA survey and evaluation of supervised machine learning techniques for spam e-mail filtering

Proceeding Name IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT)

PublisherIEEE

Author NameCoimbatore, India

Published YearJanuary

ISSN/ISBN No978-1-4799-6084-2

Indexed INScopus

Music Information Retrieval: A Window into the Needs and Challenges

Conference

Title of PaperMusic Information Retrieval: A Window into the Needs and Challenges

Proceeding NameInternational Conference on Emerging Research in Computing, Information, Communication and Applications

PublisherSpringer, Singapore

Published YearNovember 2017

Indexed INScopus

Word Sense Disambiguation for Indian Languages

Conference

Title of PaperWord Sense Disambiguation for Indian Languages

Proceeding NameInternational Conference on Emerging Research in Computing, Information, Communication and Applications

PublisherSpringer, Singapore

Published YearNovember 2017

Indexed INOthers

Google AdWords: A Window into the Google Display Network

Book Chapter

Book Name Lecture Notes in Networks and Systems

PublisherSpringer

Chapter TitleGoogle AdWords: A Window into the Google Display Network

Published YearNovember 2017

ISSN/ISBN No978-981-10-3931-7

Indexed INScopus

MobiCloud: Performance Improvement, Application Models and Security Issues

Book Chapter

Book Name Smart Innovation, Systems and Technologies

PublisherSpringer

Chapter TitleMobiCloud: Performance Improvement, Application Models and Security Issues

Published YearAugust 2017

ISSN/ISBN No978-3-319-63672-6

Indexed INScopus

Towards the Next Generation of Web of Things: A Survey on Semantic Web of Things’ Framework

Book Chapter

Book Name Smart Innovation, Systems and Technologies

PublisherSpringer

Page Number31-39

Chapter TitleTowards the Next Generation of Web of Things: A Survey on Semantic Web of Things’ Framework

Published YearJuly 2016

ISSN/ISBN No978-3-319-30932-3

Indexed INScopus

Text Categorization and State-of-Art Support Vector Machine

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperText Categorization and State-of-Art Support Vector Machine

PublisherCSI journals

Published YearMarch 2016

Indexed INOthers

A Study of Working of Ad Auctioning by Google AdWords

Book Chapter

Book Name Advances in Intelligent Systems and Computing

PublisherSpringer

Page Number471-480

Chapter TitleA Study of Working of Ad Auctioning by Google AdWords

Published YearFebruary 2016

ISSN/ISBN No978-981-10-0133-8

Indexed INScopus

Movie Related Information Retrieval Using Ontology Based Semantic Search

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperMovie Related Information Retrieval Using Ontology Based Semantic Search

PublisherCSI journals

Published YearSeptember 2014

Indexed INOthers

Video Search Engine Tool

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperVideo Search Engine Tool

PublisherCSI journals

Published YearSeptember 2014

Indexed INOthers

Tejal Upadhyay

Study and Analysis of Gene Expression Clustering with Gaussian Mixed Effects Models and Smoothing

Journal

Journal NameInternational Journal of Computer Science and Network Security

Title of PaperStudy and Analysis of Gene Expression Clustering with Gaussian Mixed Effects Models and Smoothing

Volume Number20

Published YearMay 2020

ISSN/ISBN No1738-7906

Indexed INWeb of Science

Abstract

A large number of longitudinal studies measuring gene expression aim to stratify the genes according to their differential temporal behaviors. Genes with similar expression patterns may reflect functional responses of biological relevance. However, these measurements come with intrinsic noise which makes their time series clustering a difficult task. Here, we have shown how to cluster such data with mixed effects models with nonparametric smoothing spline fitting and is able to robustly stratify genes by their complex time series patterns. The article has, besides the main clustering methods, a set of functionalities assisting the user to visualize and assess the clustering results, and to choose the optimal clustering solution. The first part is about the introduction to gene expression, how time series can be applied and how the clustering is important to gene expression. The Gaussian mixed effect model is also explain. The second part is about the related work already done with some references. The third part is about our own process and workflow with diagram. How the clustering is applied and diagrams of different cluster sets. The fourth part is about results and discussion, how the silhouette analysis is important and using 3 clusters and 4 clusters how the data sets look like. The fifth part is shown with applications of clustering effects, how the yeast data sets can be divided into clusters etc. The sixth part shows the methodology of mixed Gaussian effects and smoothing splines. The last part is about conclusion and references.

With the tremendous growth in mobile phones, mobile application development is an important emerging arena. Moreover, various applications fail to serve the purpose of getting the attention of the intended users, which is determined by their User Interface (UI) and User Experience (UX). As a result, developers often find it challenging to meet the users’ expectations. To date, several reviews have been carried out which explored various aspects of design and the experience of mobile applications using UX/UI. However, many of these existing surveys primarily focused on only some of the issues in isolation but did not consider all the major parameters such as visualisation/graphics, context, user behaviour/emotions/control, usability, adaptability/flexibility, language, and feedback. In our pilot survey, we gathered the preferences and perceptions of a heterogeneous group of concerned people and considered all the aforementioned parameters. These preferences would serve as a reference to mobile application developers, giving them useful insights. Our proposed approach would help mobile application developers and designers focus on the particular UI/UX problems of mobile applications as per their relevant context. A comparative analysis of the various UI and UX factors that determine a mobile application interface is presented in this paper

Blockchain-assisted industrial automation beyond 5G networks

Journal

Journal NameComputers & Industrial Engineering

Title of PaperBlockchain-assisted industrial automation beyond 5G networks

PublisherPergamon

Volume Number169

Page Number1-16

Published YearJuly 2022

ISSN/ISBN No0360-8352

Indexed INScopus, ABDC, Others

Abstract

Automation of industrial tasks becomes the necessity of organizations due to high risks and low operational efficiency associated with traditional procedures. The industrial Internet-of-thing (IIoT) has proved it a reality with ubiquitous computing, which interconnects tens of billions of objects, such as devices and machines, for real-time data transfer. However, the rapid increase in the number of connected devices and machines leads to various security issues, such as data modification, sniffing, and many more. Achieving secure and reliable communication between devices becomes challenging as the entire communication takes place over an open channel, i.e., the Internet. Most of the security solutions presented in the literature are centralized and susceptible to security, latency, reliability, and single-point-of-failure issues. Blockchain is a plausible solution to mitigate the aforementioned issues with reduced capital and operating expenditures, whereas the sixth-generation (6G) network makes communication faster and more reliable. Motivated by these facts, this paper presents an exhaustive survey on blockchain-based industrial automation in the 6G environment. Also, a blockchain and 6G-enabled industrial automation architecture for secure and efficient communication among IIoT devices is proposed. This paper also presents a case study on blockchain-based additive manufacturing for designing three-dimensional products to validate the proposed architecture. The performance of the proposed case study is evaluated based on network parameters such as delay, packet loss, scalability, network bandwidth, computation time, and data storage cost. Finally, various research challenges and future directions are suggested in this emerging area.

P2COMM: A Secure and Low-Cost Message Dissemination Scheme for Connected Vehicles

Conference

Journal

Journal NameTransactions on Emerging Telecommunications Technologies

Title of PaperAmalgamation of blockchain and sixth‐generation‐envisioned responsive edge orchestration in future cellular vehicle‐to‐anything ecosystems: Opportunities and challenges

PublisherWiley

Volume Number1

Page Number1-20

Published YearDecember 2021

ISSN/ISBN No2161-3915

Indexed INScopus, Web of Science, Indian citation Index, Others

Abstract

EVBlocks: A blockchain-based secure energy trading scheme for electric vehicles underlying 5G-V2X ecosystems

Journal

Journal NameWireless Personal Communications,

Title of PaperEVBlocks: A blockchain-based secure energy trading scheme for electric vehicles underlying 5G-V2X ecosystems

PublisherSpringer

Volume Number1

Page Number1-41

Published YearDecember 2021

ISSN/ISBN No0929-6212

Indexed INScopus, Web of Science, Indian citation Index, Others

Abstract

In this paper, the authors propose a secure and trusted energy trading (ET) scheme for electric vehicles (EVs) for vehicle-to-anything (V2X) ecosystems. The scheme, named as EVBlocks, facilitates ET among entities (i.e., EVs, charging stations (CS), and smart grids (SG)) in a secured and trusted manner through a consortium blockchain (CBC) network. The scheme operates in three phases. In the first phase, to allow real-time and resilient network orchestration of V2X nodes, we consider the ET service designed over a fifth-generation (5G) enabled software-defined networking (SDN) environment. Integration of SDN in 5G-V2X ecosystems allows V2X nodes to eliminate intermediaries and handle many requests with a minimum response time. Then, in the second phase, a non-cooperative game is presented that optimizes a cost function and converges to reach at least one Nash equilibrium point. Finally, a consensus algorithm Proof-of-Greed (PoG) is proposed that handles fluctuations in charging/discharging EVs through an event-driven scheduling mechanism. The obtained results are compared against parameters, such as ET time, State-of-Charge (SoC) levels, EV utility, block-convergence time, profits, computation, and communication costs. For example, EVBlocks achieve an average SOC charge of 22.8MW, with a peak at 377.5MW, the average power dissipation of 4.1125 kWH that is lower than 25% against existing conventional and fixed tariff schemes. The scheme converges at stable profit values for 5 EVs through a non-cooperative game. For proposed PoG consensus, the block convergence time for 1000 nodes is 138.96 seconds, at a computation cost of 46.92 milliseconds (ms) and communication cost of 149 bytes. The comparative analysis suggests the proposed scheme is efficient as compared to existing state-of-the-art approaches against compared parameters.

Blockchain-based royalty contract transactions scheme for Industry 4.0 supply-chain management

Journal

Journal NameInformation processing & management

Title of PaperBlockchain-based royalty contract transactions scheme for Industry 4.0 supply-chain management

Volume Number58

Page Number1-14

Published YearJuly 2021

ISSN/ISBN No0306-4573

Indexed INScopus, Web of Science, Indian citation Index, Others

Abstract

Industry 4.0-based oil and gas supply-chain (OaG-SC) industry automates and efficiently executes most of the processes by using cloud computing (CC), artificial intelligence (AI), Internet of things (IoT), and industrial Internet of things (IIoT). However, managing various operations in OaG-SC industries is a challenging task due to the involvement of various stakeholders. It includes landowners, Oil and Gas (OaG) company operators, surveyors, local and national level government bodies, financial institutions, and insurance institutions. During mining, OaG company needs to pay incentives as a royalty to the landowners. In the traditional existing schemes, the process of royalty transaction is performed between the OaG company and landowners as per the contract between them before the start of the actual mining process. These contracts can be manipulated by attackers (insiders or outsiders) for their advantages, creating an unreliable and un-trusted royalty transaction. It may increase disputes between both parties. Hence, a reliable, cost-effective, trusted, secure, and tamper-resistant scheme is required to execute royalty contract transactions in the OaG industry. Motivated from these research gaps, in this paper, we propose a blockchain-based scheme, which securely executes the royalty transactions among various stakeholders in OaG industries. We evaluated the performance of the proposed scheme and the smart contracts’ functionalities and compared it with the existing state-of-the-art schemes using various parameters. The results obtained illustrate the superiority of the proposed scheme compared to the existing schemes in the literature.

Blockchain adoption for trusted medical records in healthcare 4.0 applications: a survey

Book Chapter

Book Name Lecture Notes in Networks and Systems book series (LNNS,volume 203): Proceedings of Second International Conference on Computing, Communications, and Cyber-Security

PublisherSpringer, Singapore

Author NameUmesh Bodkhe, Sudeep Tanwar, Pronaya Bhattacharya, Ashwin Verma

Page Number759-774

Chapter TitleBlockchain adoption for trusted medical records in healthcare 4.0 applications: a survey

Published YearMay 2021

ISSN/ISBN No978-981-16-0733-2

Indexed INScopus, Others

Abstract

Secure Data Dissemination Techniques for IoT Applications: Research Challenges and Opportunities

Journal

Journal NameSoftware Practice and Experience

Title of PaperSecure Data Dissemination Techniques for IoT Applications: Research Challenges and Opportunities

PublisherWiley

Volume Number1

Page Number1-23

Published YearFebruary 2021

ISSN/ISBN No1097-024X

Indexed INScopus, Web of Science, Indian citation Index, Others

Abstract

Internet of Things (IoT) connects different objects in the physical world to the Internet, and various Internet protocols are used to provide communication services to a large number of these embedded devices termed as smart devices. But, these devices are resource-constrained, low configured, and have very low power storage capacity, which depends on the services offered by the protocols. For the exchange of information to the end-users, smart devices communicate through an open channel, such as the Internet, which is not secure enough. Moreover, efficient delivery ratio, secure data forwarding are not achieved because of the enormous amount of data produced by these smart devices and the possibility of security threats. So there is a need to devise a secure and reliable data dissemination scheme for the IoT environment. Motivated from the these facts, this paper presents a systematic review and propose a solution taxonomy for secure data dissemination techniques for various smart IoT-based applications. This paper also includes a comparison of the state-of-the-art data dissemination techniques used for the Internet of Vehicles (IoVs), Internet of Drones (IoDs), and Internet of Battlefield Things (IoBTs) applications along with their merits and demerits. Finally, the research challenges and possible countermeasures are also discussed in detail, which gives insights to the beginners who want to start work in this emerging area.

P2IoV:Privacy Preserving Lightweight Secure Data Dissemination Scheme for Internet of Vehicles

Conference

Journal

Journal NameIEEE Access

Title of PaperBlockchain for industry 4.0: a comprehensive review

PublisherIEEE

Volume Number8

Page Number79764-79800

Published YearApril 2020

ISSN/ISBN NoIEEE Access 2169-3536

Indexed INScopus, Web of Science, Others

Abstract

IIGPTS: IoT-based framework for Intelligent Green Public Transportation System

Book Chapter

Book Name Lecture Notes in Networks and Systems book series (LNNS,volume 121) : Proceedings of First International Conference on Computing, Communications, and Cyber-Security (IC4S 2019)

PublisherSpringer Nature Singapore Pte Ltd.

Author NameAkhilesh Ladha, Nirbhay Chaubey, Pronoya Bhattacharya, Umesh Bodkhe

Page Number1-14

Chapter TitleIIGPTS: IoT-based framework for Intelligent Green Public Transportation System

Published YearMarch 2020

ISSN/ISBN No 978-981-15-3368-6

Indexed INScopus, Others

Abstract

Today, growing urbanization coupled with the high demands of daily commute for working professionals has increased the popularity of public transport systems (PTS). The traditional PTS is in high demand in urban cities and heavily contributes to air pollution, traffic accidents, road congestion, increase of green house gases like oxides of carbon (OC), methane (CH4), and oxides of nitrogen (NOx) emissions. PTS also suffers from the limitations of preset routes, privacy, crowd, and less space for passengers. Some PTS are densely crowded in few routes, whereas in other routes they are not crowded at all. Thus, the aforementioned limitations of toxic emissions coupled with load management and balancing in PTS are a critical issue. The paper proposes IIGPTS: IoT-based framework for Intelligent Green Public Transportation System that addresses the mentioned issues by measuring emission sensor readings with respect to varying parameters like passenger density (total carrying load), fuel consumption, and routing paths. The performance of IIGPTS is analyzed at an indicated time slot to measure emissions and load on the system. Then, the simulation is performed based on dynamic routes by increasing passenger load and measuring the service time for user traffic as requests, also considering the request drops. The results obtained by IIGPTS framework indicate a delay of 104 s for 10,000 requests spread across an entire day, which is negligible considering the load. Thus, IIGPTS can intelligently handle varying capacity loads at varying routes, with fewer emissions, making the realization of green eco-friendly PTS systems a reality.

A Survey on Decentralized Consensus Mechanisms for Cyber Physical Systems

Journal

In the era of Industry 4.0, e-tourism uses bulk of digital payments through applications supported by heterogeneous payment gateways. These heterogeneous payment gateways open the doors for the attackers to perform malicious activities such as-hacking of wallet accounts, identity theft, attacks on payment clearance cycles. In e-tourism, financial data is maintained in a centralized cloud server, which can lead to payment failures during peak traffic. The aforementioned issues can be addressed by the usage of a decentralized mechanism such as-blockchain, which enables trust and reputation management among various stakeholders such as-banks, travel agencies, airports, railways, cruises, hotels, restaurants, and local taxis. Motivated by the above discussion, we propose a framework named as BloHosT (Blockchain Enabled Smart Tourism and Hospitality Management), which allows tourists to interact with various stakeholders through a single wallet identifier linked with a cryptocurrency server to initiate payments. BloHosT uses an immutable ledger, where no proofs are required during travel that provides a hassle-free experience to tourists. Also, a Tourism enabled Deep-Learning (TeDL) framework is presented as a part of BloHosT framework, which is trained on experience of previous visited travelers. It provides rating scores to prospective travelers about the recently visited locations by previous travelers. Finally, through case studies, we demonstrate that BloHosT achieves a high Return of Investment (ROI) in tourism sector as compared to traditional frameworks

“Managing Cooperative Behaviour in Social Communication” ICASCCT 2014, Hyderabad

Journal

Journal NameIEEE Access

Title of PaperBlockchain and AI-Empowered Healthcare Insurance Fraud Detection: An Analysis, Architecture, and Future Prospects

PublisherIEEE

Volume Number10

Page Number79606-79627

Published YearJanuary 2022

Indexed INScopus, Web of Science

Hardware Implementation of Public Key Cryptography for Small-Scale Devices

Book Chapter

Book NameLecture Notes in Networks and Systems book series

PublisherSpringer

Page Number9-15

Chapter TitleHardware Implementation of Public Key Cryptography for Small-Scale Devices

Published YearNovember 2018

ISSN/ISBN No978-981-13-2323-2

Indexed INScopus

Abstract

Vijay Ukani

Ocean Surface Pollution Detection: Applicability Analysis of V-Net with Data Augmentation for Oil Spill and Other Related Ocean Surface Feature Monitoring

Book Chapter

Book NameCommunication and Intelligent Systems

PublisherSpringer

Author NameNaishadh Mehta, Pooja Shah, Pranshav Gajjar, Vijay Ukani

Page Number11-25

Chapter Title Ocean Surface Pollution Detection: Applicability Analysis of V-Net with Data Augmentation for Oil Spill and Other Related Ocean Surface Feature Monitoring

Published YearAugust 2022

ISSN/ISBN No978-981-19-2130-8

Indexed INScopus

Optimized Reverse TCP Shell Using One-Time Persistent Connection

Book Chapter

Book NameInnovations in Information and Communication Technologies

PublisherSpringer

Author NameAnush Manglani, Tadrush Desai, Pooja Shah, Vijay Ukani

Page Number351-358

Chapter TitleOptimized Reverse TCP Shell Using One-Time Persistent Connection

Published YearJuly 2021

ISSN/ISBN No978-3-030-66218-9

Book Chapter

Book NameSmart Innovation, Systems and Technologies

PublisherSpringer

Page Number293-302

Chapter TitleA Range-Based Adaptive and Collaborative Localization for Wireless Sensor Networks

Published YearDecember 2018

ISSN/ISBN No978-981-13-1747-7

Indexed INScopus, UGC List

Outcome fusion-based approaches for user-based and item-based collaborative filtering

Book Chapter

Book NameSmart Innovation, Systems and Technologies

PublisherSpringer

Author NamePriyank Thakkar, Krunal Varma, Vijay Ukani

Page Number127-135

Chapter TitleOutcome fusion-based approaches for user-based and item-based collaborative filtering

Published YearAugust 2017

ISSN/ISBN No978-3-319-63645-0

Indexed INScopus

Routing Protocols for Wireless Multimedia Sensor Networks: Challenges and Research Issues

Book Chapter

Book Name Smart Innovation, Systems and Technologies

PublisherSpringer

Page Number157-164

Chapter TitleRouting Protocols for Wireless Multimedia Sensor Networks: Challenges and Research Issues

Published YearAugust 2017

ISSN/ISBN No978-3-319-63645-0

Indexed INScopus, UGC List

Efficient Vehicle Detection and Classification for Traffic Surveillance System

Book Chapter

Book NameCommunications in Computer and Information Science

PublisherSpringer, Singapore

Page Number495-503

Chapter TitleEfficient Vehicle Detection and Classification for Traffic Surveillance System

Published YearJuly 2017

ISSN/ISBN No978-981-10-5426-6

Indexed INScopus, UGC List, Others

Open Issues in Named Data Networking - A Survey

Book Chapter

Book NameSmart Innovation, Systems and Technologies

PublisherSpringer, Cham

Page Number285-292

Chapter TitleOpen Issues in Named Data Networking - A Survey

Published YearMarch 2017

ISSN/ISBN No978-3-319-63672-6

Indexed INScopus, UGC List

Abstract

QoS Aware Geographic Routing Protocol for Multimedia Transmission in Wireless Sensor Network

Conference

Title of PaperQoS Aware Geographic Routing Protocol for Multimedia Transmission in Wireless Sensor Network

Proceeding Name2015 5th Nirma University International Conference on Engineering (NUiCONE)

PublisherIEEEXplore

OrganizationNirma University

Year , VenueDecember 2015 , Nirma University

Indexed INOthers

A Realistic Coverage Model with Backup Set Computation for Wireless Video Sensor Network

Journal

Journal NameNirma University Journal of Technology

Title of PaperA Realistic Coverage Model with Backup Set Computation for Wireless Video Sensor Network

PublisherNirma University

Volume Number4

Page Number20-24

Published YearAugust 2015

Computation of Coverage Backup Set for Wireless Video Sensor Networks

Conference

Title of PaperComputation of Coverage Backup Set for Wireless Video Sensor Networks

Proceeding NameTENSYMP 2015 - An International Conference of IEEE region 10

PublisherIEEEXplore

OrganizationIEEE Region 10

Year , VenueMay 2015 , GIFT City, Gandhinagar

Page Number37-40

Indexed INOthers

An Energy Efficient Routing Protocol for Wireless Multimedia Sensor Networks

Conference

Title of PaperAn Energy Efficient Routing Protocol for Wireless Multimedia Sensor Networks

Proceeding NameDevices, Circuits and Communications (ICDCCom), 2014 International Conference on

PublisherIEEEXplore

OrganizationKrishna Engineering College

Year , VenueSeptember 2014 , Gaziabad

Page Number1-6

Indexed INOthers

VAQMAC: Video Aware QoS MAC Protocol for Wireless Video Sensor Networks

Journal

Journal NameInternational Journal of Electronics and Communication Engineering And Technology

Title of PaperVAQMAC: Video Aware QoS MAC Protocol for Wireless Video Sensor Networks

Volume Number4

Page Number103-115

Published YearApril 2014

Aggregation in Wireless Multimedia Sensor Networks

Conference

Title of PaperAggregation in Wireless Multimedia Sensor Networks

Proceeding NameEngineering (NUiCONE), 2013 Nirma University International Conference on

PublisherIEEEXplore

OrganizationNirma University

Year , VenueNovember 2013 , Nirma University

Page Number1-6

Indexed INOthers

An Empirical Analysis of Multiclass Classification Techniques in Data Mining

Conference

Title of PaperAn Empirical Analysis of Multiclass Classification Techniques in Data Mining

Proceeding NameEngineering (NUiCONE), 2011 Nirma University International Conference on

PublisherIEEEXplore

OrganizationNirma University

Year , VenueDecember 2011 , Nirma University

Page Number1-5

Indexed INOthers

Vipul Chudasama

Security Analysis of Multi-factor Authentication with Legitimate Key Exchange for Vehicle to Vehicle Communication

Book Chapter

Book NameLecture Notes in Networks and Systems

PublisherSpringer, Singapore

Author NameVipul Chudasama

Page Number437-446

Chapter TitleSecurity Analysis of Multi-factor Authentication with Legitimate Key Exchange for Vehicle to Vehicle Communication

Published YearNovember 2023

ISSN/ISBN No978-981-99-5652-4

Indexed INScopus

Abstract

Next-Generation Firewall with Intelligent IPS

Book Chapter

Book NameLecture Notes in Electrical Engineering

PublisherSpringer, Singapore

Author NameParth Barot, Sharada Valiveti , Vipul Chudasama

Page Number 387–395

Chapter TitleNext-Generation Firewall with Intelligent IPS

Published YearMay 2023

ISSN/ISBN No978-981-19-8865-3

Indexed INScopus

Abstract

These days, Internet is used for almost everything. There are several mediums (channels) available for people to search for information that is relevant either in terms of business or entertainment perspective. These mediums can be used by a hacker to steal information and perform an attack on any network infrastructure using various techniques. Hence, securing the network is essential for cybersecurity. Accordingly, various types of attacks like denial of service (DoS) attacks, backdoors, buffer overflow, guess the password, Smurf DoS, etc., are quite prevalent and are commonly used by an attacker. This paper presents the complete process to detect and re-mediate/mitigate these attacks using automatic detection techniques. The paper includes ways to improve network security using the feature of intrusion prevention system in firewall by detecting and analyzing the packet flows. The main objective of the paper is to detect the attack, analyze it, and if it is risky then drop the attacking packet before it harms the network. Also, the paper presents the error and accuracy rate of detecting attacks using the different machine learning algorithms which can be used in the IPS.

Voice Based Pathology Detection from Respiratory Sounds using Optimized Classifiers

Journal

Journal NameInternational Journal of Computing and Digital Systems

Title of Paper Voice Based Pathology Detection from Respiratory Sounds using Optimized Classifiers

PublisherUniversity of Bahrain

Volume Number13

Page Number327-339

Published YearJanuary 2023

ISSN/ISBN No2210-142X

Indexed INScopus

Cloud computing provides services from the available pool of resources. Even with the available condition, cloud computing can reach the peak of success amongst cloud user. The issue they face is the barrier of trust between the end users for using the given services. Conventional security and protection controls keeps on being executed on cloud; however, because of its liquid and dynamic nature, a testable trust estimate of the cloud is required. This research paper exhibits an analysis of the present trust administration strategies for cloud operations. In this research paper, we proposed a model for trust administration using Fuzzy Logic, which can be beneficial for cloud service providers to select trusted datacenter for consumers.

SLA Management in Cloud Federation

Journal

Journal NameInternational Conference on Information and Communication Technology for Intelligent Systems

Title of PaperSLA Management in Cloud Federation

PublisherSpringer, Singapore

Volume Number84

Page Number397-404

Published YearNovember 2017

ISSN/ISBN No978319636443

Indexed INScopus

Abstract

Now a days cloud computing is the major area of research Because cloud computing has own many benefits. Cloud computing also provides cost effective Resources so that it can become more and more helpful to IT trends. Distributed computing is an extensive arrangement that conveys IT as an administration. It is an Internet-based registering arrangement where shared assets are given like power disseminated on the electrical grid. Cloud suggest to a particular IT environment that is expected with the end goal of remotely provisioning versatile and measured IT resources. Whereas the Internet gives open access to many Web-based IT assets, a cloud is commonly exclusive and offers access to IT assets that is metered following SLAs implementation depends on guidelines that are redesigned in runtime so as to proactively recognize conceivable SLA Violations and handle them in a proper manner. Our proposed framework allows the creation and implementation of effective SLA for provisioning of service. SLA management are one kind of common comprehension between CSP (Cloud Service Provider) and customer.

Weight Based Workflow Scheduling in Cloud Federation

Journal

Journal NameInternational Conference on Information and Communication Technology for Intelligent Systems

Title of PaperWeight Based Workflow Scheduling in Cloud Federation

PublisherSpringer, Singapore

Volume Number84

Page Number405-411

Published YearAugust 2017

ISSN/ISBN No978319636443

Indexed INScopus

Abstract

To cater the need of a user as the requirement of infrastructure, application building environment or contemporary software private and public clouds are exiting for provisioning of such services. But cloud providers are facing the problem of how to deploy their applications over different clouds keeping in mind their different requirements in terms of QoS (Cost, resource utilization, execution time). Different clouds have different advantages such as one cloud will be more reliable and efficient whereas, private cloud will be more secure or less expensive. In order to get the benefits of both clouds, we can use the concept of cloud federation. When using cloud federation it becomes important how to schedule large workflows over federated clouds. Proposed work addresses the issue of scheduling large workflow over federated clouds. SMARTFED is used for the cloud federation and our algorithm is used to schedule different workflows according to the QoS parameters over the federation.

Vishal Parikh

Intelligent Video Analytic Based Framework for Multi-view Video Summarization

Journal

Journal NameInternational Journal of Computing and Digital Systems

Title of PaperIntelligent Video Analytic Based Framework for Multi-view Video Summarization

PublisherUniversity of Bahrain Scientific Journals

Volume Number12

Page Number619-628

Published YearAugust 2022

ISSN/ISBN No2210-142X

Indexed INScopus

Abstract

A multi-view surveillance system captures the scenic details from a different perspective, defined by camera placements. The recorded data is used for feature extraction, which can be further utilized for various pattern-based analytic processes like object detection, event identification, and object tracking. In this proposed work, we present a method for creating a network of the optimal number of video cameras, to cover the maximum overlapping area under surveillance. In the proposed work, the focus is on developing algorithms for deciding efficient camera placement of multiple cameras at various junctions and intersections to generate a video summary based on the multiple views. Deep learning models like YOLO have been used for object detection based on the generation of a large number of bounding boxes and the associated search technique for generating rankings based on the views of the multiple cameras. Based on the view quality, the dominant views will be located. Further, keyframes are selected based on maximum frame coverage from these views. A video summary will be generated based on these keyframes. Thus, the video summary is generated through solving a multi-objective optimization problem based on keyframe importance evaluated using a maximum frame coverage.

Comparative Analysis of Key-frame Extraction Techniques for Video Summarization

Journal

Journal NameRecent Advances in Computer Science and Communications

Title of PaperComparative Analysis of Key-frame Extraction Techniques for Video Summarization

PublisherBentham Science

Volume Number14

Page Number2753-2763

Published YearJuly 2020

ISSN/ISBN No2666-2558

Indexed INScopus

Abstract

Background: With technological advancement, the quality of life of people has improved. Also, with technological advancement, large amounts of data are produced by people. The data is in the forms of text, images and videos. Hence, there is a need for significant efforts and means of devising methodologies for analyzing and summarizing them to manage with the space constraints. Video summaries can be generated either by keyframes or by skim/shot. The keyframe extraction is done based on deep learning-based object detection techniques. Various object detection algorithms have been reviewed for generating and selecting the best possible frames as keyframes. A set of frames is extracted out of the original video sequence and based on the technique used, one or more frames of the set are decided as a keyframe, which then becomes the part of the summarized video. The following paper discusses the selection of various keyframe extraction techniques in detail. Methods: The research paper is focused on the summary generation for office surveillance videos. The major focus of the summary generation is based on various keyframe extraction techniques. For the same, various training models like Mobilenet, SSD, and YOLO are used. A comparative analysis of the efficiency for the same showed that YOLO gives better performance as compared to the other models. Keyframe selection techniques like sufficient content change, maximum frame coverage, minimum correlation, curve simplification, and clustering based on human presence in the frame have been implemented. Results: Variable and fixed-length video summaries were generated and analyzed for each keyframe selection technique for office surveillance videos. The analysis shows that the output video obtained after using the Clustering and the Curve Simplification approaches is compressed to half the size of the actual video but requires considerably less storage space. The technique depending on the change of frame content between consecutive frames for keyframe selection produces the best output for office surveillance videos. Conclusion: In this paper, we discussed the process of generating a synopsis of a video to highlight the important portions and discard the trivial and redundant parts. Firstly, we have described various object detection algorithms like YOLO and SSD, used in conjunction with neural networks like MobileNet, to obtain the probabilistic score of an object that is present in the video. These algorithms generate the probability of a person being a part of the image for every frame in the input video. The results of object detection are passed to keyframe extraction algorithms to obtain the summarized video. Our comparative analysis for keyframe selection techniques for office videos will help in determining which keyframe selection technique is preferable.

Optimal Camera Placement for Multimodal Video Summarization

Book Chapter

Book NameCommunications in Computer and Information Science

PublisherSpringer

Author NameVishal Parikh, Priyanka Sharma, Vijay Ukani

Page Number123-134

Chapter TitleOptimal Camera Placement for Multimodal Video Summarization

Published YearDecember 2018

ISSN/ISBN No978-981-13-3804-5

Indexed INScopus, UGC List

Routing Protocols for Wireless Multimedia Sensor Networks: Challenges and Research Issues

Book Chapter

Book NameSmart Innovation, Systems and Technologies

PublisherSpringer

Author NameVijay Ukani

Page Number157-164

Chapter TitleRouting Protocols for Wireless Multimedia Sensor Networks: Challenges and Research Issues

Published YearAugust 2017

ISSN/ISBN No2190-3026

Indexed INScopus, EBSCO, Others

Abstract

Due to miniaturization of hardware and availability of low-cost, low-power sensors, Wireless Sensor Network and Multimedia Sensor Network applications are increasing day by day. Each application has a specific quality of service and experience requirements. The design of routing and MAC protocol which can fulfill the requirements of the application is challenging given the constrained nature of these devices. Considerable efforts are directed towards the design of energy efficient QoS-aware routing protocols. In this article, we present state of the art review of routing protocols for Wireless Multimedia Sensor Networks while addressing the challenges and providing insight into research issues.

Improving Security in P2P File Sharing Based on Network Coding for DTN

Journal

Journal NameInternational Journal of Computer Science & Communication

Title of PaperImproving Security in P2P File Sharing Based on Network Coding for DTN

PublisherIJCSC

Volume Number7

Page Number167-172

Published YearMarch 2016

ISSN/ISBN No0973-7391

Indexed INOthers

E-commerce Recommendation System usingAssociation Rule Mining and Clustering

Journal

Journal NameInternational Journal of Innovations & Advancement in Computer Science

Title of PaperE-commerce Recommendation System usingAssociation Rule Mining and Clustering

PublisherAcademic Science

Volume Number4

Page Number148-155

Published YearMay 2015

ISSN/ISBN No2347-8616

Conference

Title of PaperReducing the Operative Resource Monitoring Mechanism Overhead in Cloud: An IaaS Perspective

PublisherElsevier

Page Number-

Published YearApril 2018

ISSN/ISBN No1556-5068

Indexed INUGC List

Abstract

Today we are in the era of distributed system and cloud computing is the best example for the same. Resource management is an important issue in cloud computing, we need to keep track of the available resources in cloud, so that we can give services to user to fulfil their requirement. Which leads in helping to generate maximum revenue, lower power consumption, carbon emission and ultimately leads to green computing. So with the help of resource monitoring we can get the data about how, when, in what amount of resources for a particular cloud and the user. With effective resource monitoring, by minimizing some monitoring units we can reduce the cost of monitoring in terms of computation and power consumption. Our main objective is to reduce the monitoring technique, so that the amount of computation and power consumption can be saved which will lead to smart and green computing. In this research paper we are discussing about the algorithm that will reduce the activation period of the monitoring and also we had discussed the Hidden Markov Model (HMM) for the decision making in monitoring aspect.

Chronicles of Assaults at Cloud Computing and Its Influence at an IaaS

Conference

Title of PaperChronicles of Assaults at Cloud Computing and Its Influence at an IaaS

Proceeding NameProceedings of 3rd International Conference on Internet of Things and Connected Technologies (ICIoTCT), 2018 held at Malaviya National Institute of Technology, Jaipur (India) on March 26-27, 2018

PublisherElsevier SSRN

Author NameElsevier SSRN

OrganizationMalaviya National Institute of Technology, Jaipur (India)

Published YearMarch 2018

ISSN/ISBN No1556-5068

Indexed INUGC List

Inspection of Trust Based Cloud Using Security and Capacity Management at an IaaS Level

Journal

Journal NameElsevier Procedia:Inspection of Trust Based Cloud Using Security and Capacity Management at an IaaS Level

Title of PaperInspection of Trust Based Cloud Using Security and Capacity Management at an IaaS Level

PublisherElsevier

Volume Number132

Page Number1280-1289

Published YearFebruary 2018

ISSN/ISBN No1877-0509

Indexed INScopus, UGC List

Abstract

Cloud Computing is an example of the distributed system where the end user has to connect to the services given by the cloud which is maintained by the cloud service provider (CSP). The user has to have certain trust upon the cloud as finally, the end user has to migrate the jobs into the cloud of some third party, as the on-premises data or sources are to be kept across the globe, the CSP have to maintain the trust level so that the end user can opt for the services given by the certain trusted Cloud. Ultimately there will be various elements of levels happening at the CSP side to maintain the trust level, like the safety features for security has to be identified, federation related or Virtual Machine migration techniques status has to be always monitored to maintain and avoid certain uncertainty which will affect the trust level of the cloud, which can lead to the compromised situation in between the end user and CSP, as a result the trust value will decrease, In this paper we are proposing a techniques where the security features and conditions for load balancing monitoring technique with proactive actions will be analyzed to maintain the specified trust level.

Internet-based computing has provided lots of flexibility with respect to the usages of resources, as per the current demand of the users, and granting them the said resources has its own benefits if given in proper manner i.e. exactly what the user has asked. In this paper, the autonomic computing concepts have been discussed which will be very useful for the better utilization of the resources a

The prediction of future ten years shows exponential growth in wireless connections, high-speed Internet and data demands. Mobile network operators (MNOs) need to provide essential capacity for more than 100 billion connections in the global mobile communications network. The contribution of this paper is the analysis of the coverage, capacity and cost requirement of 4G-LTE and 5G networks across the Ahmedabad and Gandhinagar cities for the period of 2019–2029. We forecast the number of 4G-LTE and 5G subscribers and their data demands over the years. To accomplish such capacity requirement and to ensure the coverage across the cities, various radio propagation models are used to calculate the base station site requirement. The published data on networks deployment cost for various scenario (rural, urban, suburban, dense urban) are used to evaluate capital expenditure (CAPEX) and operational expenditure (OPEX) cost. The key findings of the study are as follows: (a) 4G-LTE is insufficient to provide high-speed data without acquiring additional spectrum bandwidth (b) 5G technologies can provide significant coverage and capacity even in the dense urban area (c) The cost of deploying 5G infrastructure is almost three times higher than the 4G-LTE.

Log Transformed Coherency Matrix for Differentiating Scattering Behaviour of Oil Spill Emulsions Using SAR Images

Journal

Journal NameMathematics

Title of PaperLog Transformed Coherency Matrix for Differentiating Scattering Behaviour of Oil Spill Emulsions Using SAR Images

PublisherMDPI

Volume Number10

Page Number1697

Published YearMay 2022

Indexed INScopus, Web of Science

Abstract

Oil spills on the ocean surface are a serious threat to the marine ecosystem. Automation of oil spill detection through full/dual polarimetric Synthetic Aperture Radar (SAR) images is considered a good aid for oil spill disaster management. This paper uses the power of log transformation to discern the scattering behavior more effectively from the coherency matrix (T3). The proposed coherency matrix is tested on patches of the clean sea surface and four different classes of oil spills, viz. heavy sedimented oil, thick oil, oil-water emulsion, fresh oil; by analyzing the entropy (H), anisotropy (A), and mean scattering angle alpha (𝛼 ), following the H/A/𝛼 decomposition. Experimental results show that not only does the proposed T3 matrix differentiate between Bragg scattering of the clean sea surface from a random scattering of thick oil spills but is also able to distinguish between different emulsions of oil spills with water and sediments. Moreover, unlike classical T3, the proposed method distinguishes concrete-like structures and heavy sedimented oil even though both exhibit similar scattering behavior. The proposed algorithm is developed and validated on the data acquired by the UAVSAR full polarimetric L band SAR sensor over the Gulf of Mexico (GOM) region during the Deepwater Horizon (DWH) oil spill accident in June 2010.

A Survey on Green Internet of Things

Conference

Title of PaperA Survey on Green Internet of Things

Proceeding Name2018 Fourteenth International Conference on Information Processing (ICINPRO)

Author NameKrishna Shah, Zunnun Narmawala

Published YearMay 2020

Indexed INScopus

A systematic review on scheduling public transport using IoT as tool

Journal

Journal NameAdvances in Intelligent Systems and Computing

Title of PaperA systematic review on scheduling public transport using IoT as tool

PublisherSpringer

Volume Number670

Page Number39-48

Published YearJuly 2018

ISSN/ISBN No21945357

Indexed INScopus, UGC List

Abstract

Public transport can play an important role in reducing usage of private vehicles by individuals which can, in turn, reduce traffic congestion, pollution, and usage of fossil fuel. But, for that public transport needs to be reliable. People should not have to wait for the bus for a long time without having any idea when the bus will come. Further, people should get a seat in the bus. To ensure this, efficiently and accurately scheduling and provisioning of buses is of paramount importance. In fact, nowadays buses are scheduled as per the need. But these scheduling is being done manually in India. Our survey shows that there are many algorithms proposed in the literature for scheduling and provisioning of buses. There is a need to tailor these algorithms for Indian scenario. We present a brief overview of these algorithms in this paper. We also identify open issues which need to be addressed.

Proximity and community aware heterogeneous human mobility (P-CAHM) model for mobile social networks (MSN)

Journal

Journal NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

Title of PaperProximity and community aware heterogeneous human mobility (P-CAHM) model for mobile social networks (MSN)

PublisherSpringer

Volume Number220

Page Number137-146

Published YearJanuary 2018

ISSN/ISBN No18678211

Indexed INScopus, UGC List

Abstract

Peer-to-peer opportunistic communication between mobile devices carried by humans without using any infrastructure is largely unexploited. The encounter pattern of the devices depends on human mobility pattern which is governed by human social behaviour. Individuals belong to multiple communities. These social ties significantly affect humans’ movement pattern. Traditional mobility models, such as

A comparative study of various community detection algorithms in the mobile social network

Conference

Title of PaperA comparative study of various community detection algorithms in the mobile social network

Proceeding NameNUiCONE 2015 - 5th Nirma University International Conference on Engineering

PublisherIEEE

Author NameAnkit Didwania

OrganizationNirma University

Year , VenueNovember 2015 , Nirma University

Page Number1-6

ISSN/ISBN No978-1-4799-9991-0

Indexed INScopus

Delay tolerant ad hoc network between mobile devices is a promising paradigm which can avoid significant cost of cellular data transfer. Many interesting applications such as peer-to-peer file transfer, micro-blogging etc. are possible on this network. We propose viral spread (Many-to-all broadcast) for such networks. Viral spread can be useful to variety of such applications as well as...

Improved heterogeneous human walk mobility model with hub and gateway identification

Journal

Journal NameLecture Notes in Computer Science

Title of PaperImproved heterogeneous human walk mobility model with hub and gateway identification

PublisherSpringer

Volume Number8314

Page Number469-483

Published YearJanuary 2014

ISSN/ISBN No03029743

Indexed INScopus, UGC List

Abstract

Heterogeneous Human Walk (HHW) model [1] mimics human mobility and is based on two important properties of social network: overlapping community structure and heterogeneous popularity. But, it does not produce heterogeneous local popularities of nodes in a community as observed in real mobility traces. Further, it does not consider Levy walk nature of human mobility which has significant impact on performance of protocols. We propose Improved Heterogeneous Human Walk (IHHW) model that correctly produces heterogeneous local popularities and also incorporates Levy walk nature of human mobility within overlapping community structure. As popular nodes are very useful for data dissemination, we also propose theoretical methods to identify popular nodes within community (hubs) and in entire network (gateways) from overlapping community structure itself. These nodes can act as hubs/gateways till overlapping community structure does not change. Our methods eliminate the need to identify and change these nodes dynamically when network is operational.

Performance enhancement of multimedia traffic over wireless ad hoc networks using network coding

Conference

Conference

Title of PaperSurvey on multimedia transmission using network coding over wireless networks

Proceeding NameSurvey on multimedia transmission using network coding over wireless networks

PublisherIEEE

Author NameTwisa Mehta

OrganizationNirma University

Year , VenueDecember 2011 , Nirma University

Page Number1-6

ISSN/ISBN No2375-1282

Indexed INScopus

Abstract

These days the growth of multimedia applications (e.g. VOIP, teleconferencing etc) over Wireless Networks is on its peak and will further increase with the time. The available bandwidth for Wireless Networks fails to meet the requirements which result in high packet loss of multimedia data, delay in transmission and decreases the quality of multimedia applications. So many approaches are proposed for multimedia streams over Wireless Networks to deal with packet loss and delay over time varying bandwidth. Network Coding is one of the many proposed approaches. This approach works well for transmission of multimedia traffic in a distributed lossy environment where only partial or uncertain information is available for decision making. Network Coding technique allows an intermediate node to combine the data (packets) from different input links and sends encoded data on its output links. So, by employing appropriate variant of Network Coding scheme at each intermediate node (linear combination of input data with the concept of generation) can achieve the network capacity. This paper presents the survey of various papers in which a Network Coding technique is applied on multimedia transmission over Wireless Networks.

MIDTONE: Multicast in delay tolerant networks

Conference

Title of PaperMIDTONE: Multicast in delay tolerant networks

Proceeding Name4th International Conference on Communications and Networking in China, CHINACOM 2009

PublisherIEEE

Author NameZunnun Narmawala

OrganizationXidian University and Xi'an Jiaotong University.

Year , VenueAugust 2009 , Xian, China

Page Number1-8

ISSN/ISBN No978-1-4244-4337-6

Indexed INScopus

Abstract

Delay Tolerant Networks (DTN) are sparse ad hoc networks in which no contemporaneous path exists between any two nodes in the network most of the time. Due to non-availability of end-to-end paths, multicast protocols of traditional networks fail in DTN because they try to find connected multicast graph between source and destination nodes before forwarding data packets. Routing protocols proposed for DTN follow `store-carry-forward' paradigm in which two nodes exchange messages with each other only when they come into contact. In the process, `single-copy' schemes maintain only one copy of the message in the network at any time and the forwarding node waits for the pre-determined next node to transfer the message. `Multi-copy' schemes spread more than one copy of the message opportunistically when nodes come into contact rather than waiting for pre-determined next node. While multi-copy schemes improve chances of delivery and work well even without any knowledge of the network, communication overhead and buffer occupancy are quite high for these schemes. We propose multi-copy routing protocol for multicasting in DTN called ldquoMulticast in Delay Tolerant Networks (MIDTONE)rdquo which uses `network coding' to reduce this overhead without compromising performance. Network coding is a mechanism in which nodes encode two or more incoming packets and forward encoded packets instead of forwarding them as it is. We also propose three novel packet purging schemes to drain packets out of the network which takes advantage of features of network coding to increase buffer efficiency. As simulation results suggest, our protocol achieves significantly less delay to deliver all the packets in infinite buffer case and higher delivery ratio in finite buffer case compared to non-network coding based multi-copy scheme. We also provide empirical relation to estimate optimal generation size for given network and performance parameters.

Effect of network coding on buffer management in wireless sensor network

Conference

Title of PaperEffect of network coding on buffer management in wireless sensor network

Proceeding NameISSNIP 2008 - Proceedings of the 2008 International Conference on Intelligent Sensors, Sensor Networks and Information Processing

PublisherIEEE

Author NameSunil Jardosh

OrganizationThe University of Melbourne

Year , VenueDecember 2008 , Sydney, Australia

ISSN/ISBN No978-1-4244-3822-8

Indexed INScopus

Abstract

In resource constrained wireless sensor networks (WSN), it is highly desirable to make efficient use of available buffer. Hence for the WSN designed for the monitoring applications, buffer management is a key requirement at sensor nodes. We have proposed an efficient buffer management scheme based on random linear network coding as the in-network processing on data packets. With buffer allocation from source to sink path, our scheme distributes the buffer requirement among the nodes on the path. Further in the case of a packet loss, the proposed scheme recovers packet from available information distributed on the path from source to sink. We have compared our scheme with conventional buffer management scheme. Results show that network coding based buffer management scheme has better buffer availability with less redundancy and reduced loss recovery cost.

Survey of applications of network coding in wired and wireless networks

Conference

Title of PaperSurvey of applications of network coding in wired and wireless networks

Proceeding NameProceedings of the 14th National Conference on Communications

Author NameZunnun Narmawala

OrganizationIIT Bombay

Year , VenueFebruary 2008 , IIT Bombay

Abstract

We review the basic works in the area of network coding and present a detailed survey of applications of network coding in network problems. It is shown that both in wired and wireless networks, multicast and broadcast protocols perform better with network coding. Even in unicast applications, network coding based protocols perform as well as the protocols without network coding. We also survey the applications of network coding in the domains of Peer-to-Peer Networks, Delay Tolerant Networks and Wireless Sensor Networks. It is apparent from the results that innovative use of network coding can improve the performance of a variety of applications in these domains. Finally, we also suggest a number of interesting open problems in these domains where network coding can be used.