Publications

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

Study Of Effect of Parallelism on Time Complexities on Various Operations for Tree Data Structure

Conference

Title of PaperStudy Of Effect of Parallelism on Time Complexities on Various Operations for Tree Data Structure

Year , VenueSeptember 2016 , Aurangabad

Page Number108-112

ISSN/ISBN No9789386171054

Indexed INOthers

Various Approaches to Recognise Human Emotions

Journal

Journal NameInternational Journal of Computer Science and Engineering

Title of PaperVarious Approaches to Recognise Human Emotions

Volume Number7

Page Number173-176

Published YearMarch 2016

ISSN/ISBN No09737391

Indexed INOthers

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 NumberYet to be assigned

Page Number1-49

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 NumberYet to be assigned

Page Number1-16

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

Implementation of Word Sense Disambiguation on Hadoop Using Map-Reduce

Book Chapter

Book NameInformation and Communication Technology for Intelligent Systems

PublisherSpringer, Singapore

Author NameSuresh Chandra Satapathy, Amit Joshi

Page Number573-580

Chapter TitleImplementation of Word Sense Disambiguation on Hadoop Using Map-Reduce

Published YearDecember 2018

ISSN/ISBN No978-981-13-1741-5

Indexed INScopus

Abstract

In Natural Language Processing, it is essential to find a correct sense of sentences or document is written for these type of problem is called word sense disambiguation problem. Currently, any machine learning application based on natural language processing requires to solve this type of problem. To identify the correct sense, pywsd (Python implementations of word sense disambiguation technologi

MobiCloud: Performance Improvement, Application Models and Security Issues

Book Chapter

Book NameSmart Innovation, Systems and Technologies

PublisherSpringer

Author NameSuresh Chandra Satapathy, Amit Joshi

Page Number466-472

Chapter TitleMobiCloud: Performance Improvement, Application Models and Security Issues

Published YearAugust 2017

ISSN/ISBN No2190-3018

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

Title of PaperAdWords : A Study of Usage and Tools

Volume Number7

Page Number95-99

Published YearFebruary 2016

ISSN/ISBN No0973-7391

Indexed INUGC List

Bhavin Shah

Big Data Analytics Model for the Education Sector

Journal

Journal NameInternational Journal of Innovative Technology and Exploring Engineering

Title of PaperBig Data Analytics Model for the Education Sector

PublisherBlue Eyes Intelligence Engineering and Science Publication

Volume Number8

Page Number5

Published YearOctober 2019

ISSN/ISBN No2278-3075

Indexed INScopus

Abstract

With an array of innovative technologies, the 21st century has struck at our door. Many sectors are embracing the implementation of a revolutionary technology called Big Data Analytics. The education sector has lately jumped on the bandwagon. With the new evolving education technology capable of generating Big Data, stakeholders have firmly started adopting the use of Big Data Analytics in the education sector. This paper proposes a model for Big Data Analytics depicting various required components, for the education sector. Various sources of education data provide the necessary input to the model and model produces useful results in the form of the output using various tools and technologies of Big Data ecosystem. The outputs are going to be consumed by various stakeholders of the education sector. The paper also describes the concept of Big Data, new technologies influencing the education sector and explains why Big Data Analytics is going to be core technology in analyzing the data and taking the world of education to new heights. We have also listed beneficiaries and benefits.

Big Data Mining in Education Sector: Critical Issues and Current Status in Indian Context

Journal

Journal NameInternational Journal of Advanced Research in Computer Science and Software Engineering

Title of PaperBig Data Mining in Education Sector: Critical Issues and Current Status in Indian Context

Volume Number5

Page Number1007-1011

Published YearMay 2015

ISSN/ISBN No2277 128X

Abstract

Information and communications technology is revolutionizing education sector. Data about students’ online activities are collected in large volumes and analysed to produce and recommend actions that improve outcomes. Being a largest democracy, India is also trying to join this e-learning era. In terms of the number of Internet users, India stands third in the world. India has immense potential to use big data and mining in education sector. However, there are some critical issues that are blocking fast adoption of this technology. In this paper, we discuss critical issues that are not allowing India to leverage the result of educational data analytics. We also discuss initiatives taken by government and corporate, current status and stakeholders in current digital learning revolution age.

Chandan Trivedi

Irregularity Detection in Clinical Data of Patients Encountering Heart Surgery

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

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

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

Dhaval Jha

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 No23482281

Indexed INUGC List

Strategies for implementing the Knapsack Problem

Journal

Journal NameInternational Journal of Science, Technology and Management

Title of PaperStrategies for implementing the Knapsack Problem

Volume Number6

Page Number419-427

Published YearJune 2017

ISSN/ISBN No23941537

Indexed INOthers

Sequential data mining is the process to find out the frequent sub-sequences from the given sequential dataset. Sequential pattern mining can only reveal the sequence (order) of items, but it does not determine the time interval between two successive events. Time interval sequential mining processes to find out sequential patterns with a time interval between two successive events. In this paper, we will introduce the new cluster technique so we will get a dynamic cluster range rather than fixed. We improve the result of new ITI-PrefixSpan and compare our algorithm with other algorithms in terms of computing time and memory.

Gaurang Raval

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

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

Fog computing is an extension to cloud computing, offering benefits such as minimal latency, wide geographical distribution, and location awareness by providing flexible services at the edge of the network. The onset of fog computing has catered solutions to many applications, Smart City projects being one of them. Fog computing has the potential to deliver an impact in smart city projects, as the former application involves economic and social aspects along with the technical aspect. The increase in city urbanization demands smart solutions that tackle critical problems such as healthcare, mobility, infrastructure, parking space availability, waste management, and energy consumption. Industry 4.0 conceptualizes that, Internet of Things (IoT) along with fog computing would be used for the development of a network of devices. These devices function independently in real-time and provide the required infrastructure for a smart city. This research study presents a comprehensive literature survey on the deployment architectures of fog computing in smart city applications such as Smart Waste Management and Smart Parking. An emphasis is laid more on the integration of Industry 4.0’s core concepts and fog computing while also taking into consideration the deployment aspects. With the proposed architectures and mentioned approaches, improvements would be seen in terms of resource utilization, processing overhead, and latency. In the latter part of the research survey, the potential merits of the proposed approaches and future work directions are discussed.

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

Conference

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

Title of PaperBig data analysis: recommendation system with Hadoop framework

Proceeding Name2015 IEEE International Conference on Computational Intelligence & Communication Technology

Publisher2015 IEEE International Conference on Computational Intelligence & Communication Technology

Author NameJai Prakash Verma

Organization2015 IEEE International Conference on Computational Intelligence & Communication Technology

Year , VenueFebruary 2015 , Ghaziabad, India

Page Number92-97

ISSN/ISBN NoISBN: 978-1-4799-6023-1,

Indexed INScopus

Abstract

Recommendation system provides the facility to understand a person's taste and find new, desirable content for them automatically based on the pattern between their likes and rating of different items. In this paper, we have proposed a recommendation system for the large amount of data available on the web in the form of ratings, reviews, opinions, complaints, remarks, feedback, and comments about any item (product, event, individual and services) using Hadoop Framework. We have implemented Mahout Interfaces for analyzing the data provided by review and rating site for movies.

Web Mining: Opinion and Feedback Analysis for Educational Institutions

Journal

Journal NameInternational Journal of Computer Applications

Title of PaperWeb Mining: Opinion and Feedback Analysis for Educational Institutions

PublisherInternational Journal of Computer Applications

Volume Number84

Page Number17-22

Published YearDecember 2013

ISSN/ISBN No0975 – 8887

Indexed INEBSCO

Abstract

Big amount of data available in the forms of reviews, opinions, feedbacks, remarks, comments, observations, clarifications, and explanations that require a robust mechanism to store, retrieve, analyze, and management. In this paper, we are proposing system that provides review or summary of above mention text data available on web for an educational institute. Due to big data size above system can be extended as real time recommendation system for Big Data analysis as future enhancement.

Image to Sound Conversion

Journal

Journal NameInternational Journal of Advance Research in Computer Science and Management Studies

Title of PaperImage to Sound Conversion

PublisherInternational Journal of Advance Research in Computer Science and Management Studies

Volume Number1

Page Number34 - 39

Published YearNovember 2013

ISSN/ISBN NoISSN: 2321-7782 (Online)

Indexed INOthers

Abstract

In this paper we are proposing a system to convert pictures into sound. This proposed system will identify the object from its picture and person will be able to listen to the name of the objects, in the picture. Here we will first get the image from a digital camera then by removing noise by Grey scale and after this Thresholding will be applied. In image processing, thresholding is used to split an image into smaller segments, or junks, using at least one color or grayscale value to define their boundary. After that Object recognizing can be done with Memory-Based Object Recognition Algorithm and object will be identified as Textual name and this name will be stored in the database. Then Optical Character Recognition will be applied to convert text into machine Text. This Text will be converted finally to sound.

Jigna Patel

Indexing On Healthcare Big Data

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

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

Kamal Macwan

Privacy Preserving Approaches for Online Social Network Data Publishing

Book Chapter

Book NameDigital Transformation and Challenges to Data Security and Privacy

PublisherIGI Global

Author NameKamalkumar Macwan, Sankita Patel

Page Number119-132

Chapter TitlePrivacy Preserving Approaches for Online Social Network Data Publishing

Published YearJanuary 2021

Indexed INOthers

Privacy Preserving Approach in Dynamic Social Network Data Publishing

Conference

Title of PaperPrivacy Preserving Approach in Dynamic Social Network Data Publishing

Proceeding Name15th International Conference on Information Security Practice and Experience, ISPEC"19

PublisherSpringer LNCS

Author NameKamalkumar Macwan, Sankita Patel

OrganizationUniversiti Tunku Abdul Rahman, Kuala Lumpur, Malaysia

Year , VenueNovember 2019 , Malaysia

Page Number381-398

Indexed INOthers

“k-NMF Anonymization in Social Network Data Publishing

Journal

Journal NameThe Computer Journal

Title of Paper“k-NMF Anonymization in Social Network Data Publishing

PublisherOxford University Press

Volume Number61 (4)

Page Number601-613

Published YearApril 2018

ISSN/ISBN No1460-2067

Indexed INScopus

Node Differential Privacy in Social Graph Degree Publishing

Journal

Journal NameProcedia computer science

Title of PaperNode Differential Privacy in Social Graph Degree Publishing

PublisherElsevier

Volume Number143

Page Number786-793

Published YearJanuary 2018

Indexed INScopus

Mutual Friend Attack Prevention in SocialNetwork Data Publishing

Conference

Title of PaperMutual Friend Attack Prevention in SocialNetwork Data Publishing

Proceeding Name7th International Conference on Security, Privacy, and Applied Cryptography Engineering

PublisherSpringer LNCS

Author NameKamalkumar Macwan, Sankita Patel

Year , VenueDecember 2017 , Don Bosco College of Engineering, Fatorda, Goa.

Page Number210-225

Indexed INOthers

k-degree Anonymity Model for Social Network Data Publishing

Journal

Journal NameAdvances in Electrical and Computer Engineering

Title of Paperk-degree Anonymity Model for Social Network Data Publishing

PublisherStefan cel Mare University of Suceava

Volume Number17 (4)

Page Number117-124

Published YearNovember 2017

ISSN/ISBN No1582-7445

Indexed INScopus

Kruti Lavingia

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

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

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.

Journal

Journal NameEnhancing data delivery with density controlled clustering in wireless sensor networks

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

PublisherSpringer Berlin Heidelberg

Volume Number23

Published YearMay 2016

ISSN/ISBN No0946-7076

Abstract

Wireless sensor networks (WSN) are primarily used for sensing and collecting the information from environment. This information is sent to base station (BS), where, it is processed and analyzed by the underlying application. Functioning of WSN highly depend on the deployment strategy and the coordination among the sensor nodes. Preserving the energy is an important goal that must be considered when developing a routing protocol for WSNs. Radio communication in sensor nodes is highly expensive operation in terms of energy usage. Energy can be conserved in an efficient way with specifically customized routing techniques. Data aggregation methods when applied to sensor nodes, clusters are created where data generated from cluster members is aggregated. This kind of data collection strategy results into energy efficient communication. Integration of data aggregation and clustering approach is enabled through customized hierarchical routing strategies. Clustering technique is key to apply and exploit, the advantages in-network data processing offers. This paper compares various clustering protocols like LEACHC, K-means and its variants. The protocols are compared with respect to network lifetime, data delivery and energy consumption. These protocols only consider intra cluster distance of members while doing clustering, due to this non-uniform clusters are created. These kind of clusters do not deliver data periodically and uniformly from every corner of the field. A density control based approach is proposed which does balancing of cluster members assignment in a loose way. A loose density control (LDC) based approach is integrated with K-means clustering method. LDC based approach exhibits improved average data delivery per node, ensuring regular data availability from every corner of the deployment area as long as the nodes are alive. Not only it improves the amount of data delivered, it also improves the network lifetime considerably.

Malaram Kumhar

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 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

Journal

Journal NameJournal of Chemical and Pharmaceutical Sciences

Title of Paper A comprehensive survey on oceanography parameters for developing ocean wave displacement prediction system

PublisherSPB Pharma society

Volume Number8

Page Number273-278

Published YearJune 2015

ISSN/ISBN No0974-2115

Indexed INScopus

Abstract

Optimizing Parallel Scan Smith Waterman Algorithm

Conference

Title of Paper Optimizing Parallel Scan Smith Waterman Algorithm

PublisherIRAJ

Page Number86-89

Published YearSeptember 2014

ISSN/ISBN No320 - 2106

Indexed INOthers

Abstract

Smith - Waterman is a well - known local sequence alignment algorithm that is used for finding regions of maximum similarity between two biological sequences and is known to be a highly compute intensive task. As it is based on dynamic programming it guarantees optimal results. But Dynamic Programming has its own drawbacks such as hea vy memory consumption and significant amount

An Efficient Sparse Matrix Multiplication for skewed matrix on GPU

Conference

Title of PaperAn Efficient Sparse Matrix Multiplication for skewed matrix on GPU

PublisherIEEE

Year , VenueOctober 2012 , Liverpool, UK

Page Number1301-1306

ISSN/ISBN No978-1-4673-2164-8

Indexed INScopus, UGC List

Abstract

This paper presents a new sparse matrix format ALIGNED_COO, an extension to COO format to optimize performance of large sparse matrix having skewed distribution of non-zero elements. Load balancing, alignment and synchronization free distribution of work load are three important factors to improve performance of sparse matrices representing power-law graph. Coordinate (COO) format is selected for

PROS - An Omnipresent Operating System

Journal

Journal NameInternational Journal of Recent Trends in Engineering

Title of PaperPROS - An Omnipresent Operating System

PublisherInternational Journal of Recent Trends in Engineering

Volume Number1

Page Number144-148

Published YearMay 2009

ISSN/ISBN No1797-9617

Indexed INOthers

Abstract

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

Parita Oza

Review of Machine Learning Techniques in Healthcare

Conference

Title of PaperReview of Machine Learning Techniques in Healthcare

PublisherSpringer

OrganizationCentral University of Jammu

Year , VenueMarch 2019 , Delhi

Indexed INScopus

homomorphic Cryptography and it's Applications in Various Domains

Journal

Journal NameLecture notes in Networks and Systems

Title of Paperhomomorphic Cryptography and it's Applications in Various Domains

PublisherSpringer

Volume Number55

Page Number269-278

Published YearNovember 2018

ISSN/ISBN No23673370

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

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 Shah

Page Number1-6

Published YearNovember 2015

Abstract

Biogenic and Mineral oil spill in the ocean can harm the marine ecosystem significantly. Past research suggests image processing on images generated from Synthetic Aperture Radar (SAR) data are the most suitable way of remote oil spill detection. In this paper, the framework for oil spill detection is explained in three step process for oil spill detection viz., dark spot detection, feature extraction, and classification. The paper focuses on Hysteresis algorithm for segmenting the dark spots and decision tree for the classification of dark spots and look alikes. The major steps in oil spill detection have been implemented in imageJ which gives a light weight solution to existing softwares for the said application.

A comprehensive survey on oceanography parameters for developing ocean wave displacement prediction system

Conference

Title of PaperA comprehensive survey on oceanography parameters for developing ocean wave displacement prediction system

Author NameHiral Trivedi, Monika Shah, Pooja Shah

OrganizationInternational conference JEPPIAAR – ICONSTEM 2015 [THEME:- SEH 2015]

Published YearJanuary 2015

ISSN/ISBN No0974-2115

Abstract

Earth is widely covered by ocean. There are many calamities observed as a result of various unpredicted behaviourof ocean wave movements, and Landscaping under ocean along with response to weather change. These dynamic and drastic behavioursof oceans can be measured by various parameters like. The paper describes in depth learning of various concerned parameters which cover impact of parameters individually, different and co-related with each other. Disaster prediction requires analyzing the history and future of ocean parameters, which is a motivationfor forecasting parameters accurately and efficiently. The paper also discusses various approaches for forecasting future ocean parameters proposed by various researches and predicting one dimensional wave displacement.The various approaches that have been discussed in this paper are: Artificial Neural network, Data Assimilation methods, Genetic Algorithm, Statistical methods, Super ensemble methods and mathematical concepts like partial derivation and Fourier series transformations.

Oil spill detection from SAR image data for remote monitoring of marine pollution using light weight imageJ implementation

Conference

Title of PaperOil spill detection from SAR image data for remote monitoring of marine pollution using light weight imageJ implementation

Publisherieee

Author NameRajkumar Sharma Kruti Vyas,Pooja Shah, Usha Patel, Tanish Zaveri

OrganizationNUiCONE

Published YearJanuary 2015

Enhancing The Capabilities Of Imagej By Incorporating Feature Extraction From SAR Images For Oil Spill Detection

Journal

Journal NameInternational Journal of Advanced Research in Engineering and Technology (IJARET), Volume 6, Issue 4

Title of PaperEnhancing The Capabilities Of Imagej By Incorporating Feature Extraction From SAR Images For Oil Spill Detection

PublisherIAEME

Volume Number6

Page Number41-50

Published YearJanuary 2015

Abstract

Intentional and unintentional Oil spill in the ocean is significantly harmful to marine life, coastal area and whole environment. There are many softwares available which can detect oil spill but they are not application specific and some of them are paid. We have implemented feature extraction for oil spill detection using imageJ tool. This paper gives implementation details and results of features extraction from SAR data. The features selected for the study are most frequently used features assorted from the literature on research of oil spill detection by various scientists.

Face Recognition techniques : A survey for forensics applications

Journal

Journal NameInternational Journal of Advanced Research in Computer Engineering & Technology (IJARCET)

Title of PaperFace Recognition techniques : A survey for forensics applications

Published YearJanuary 2015

Abstract

A wide variety of systems requires reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. Face Recognition is the most natural process for human beings and therefore it is the most natural biometric technique. It is widely used in the areas like information security, access management, law enforcement, criminal investigation etc. The goal of the paper is to have a comprehensive analysis of facial recognition in forensic investigation. It discusses the role of face recognition in investigation and law enforcement applications, with a brief background and origin of face recognition in forensic investigation. The paper also describes the applications of face recognition, a generic automated face recognition system and face recognition algorithms.

Automation of Marine Pollution monitoring using SAR images on Open Source Platform

Conference

Title of PaperAutomation of Marine Pollution monitoring using SAR images on Open Source Platform

Author NameKruti Vyas, Usha Patel, Pooja Shah

Organization5th International Conference on Computer Science and Information Technology (ICCIT 2015)

Published YearJanuary 2015

Survey on Mobile Forensics

Journal

Journal NameInternational Journal of Computer Applications

Title of PaperSurvey on Mobile Forensics

Published YearJanuary 2015

Abstract

With the continued growth of smart phone market, the probability of their use in criminal activities has continued to increase. Mobile phone nowadays comes with a wide variety of software application, new technologies and operating systems. Therefore it becomes complicated for a forensic investigator to examine the evidence from a mobile phone. A proper knowledge of forensic tools and their features is required to collect relevant information. This paper discusses about the mobile device characteristics, the steps for mobile forensic investigation and different tools for mobile forensics. The last section of the paper presents the experimental results of the tools Mobiledit Lite and Autopsy 3.1.2.

Benchmarking Niblack’s Binarization Algorithm Using OpenCV Library Integrated in C++ and FPGA Simulation

Journal

Journal NameInternational Journal of Emerging Technology and Advanced Engineering

Title of PaperBenchmarking Niblack’s Binarization Algorithm Using OpenCV Library Integrated in C++ and FPGA Simulation

PublisherInternational Journal of Emerging Technology and Advanced Engineering

Volume Number4

Page Number201-204

Published YearMarch 2014

ISSN/ISBN No2250-2459

Abstract

Today, real-time processing has become a stipulation in all practical fields especially in image processing. This paper presents an experimental comparison of implementation of Niblack’s Algorithm, a binarization algorithm for image-processing in Visual C++ using OpenCV library with its implementation on FPGA. It aims at addressing the real-time processing scenario and how to overcome the situation using the above implementations. The algorithm is developed using Very High Speed Integrated Circuit (VHSIC) Hardware Description Language (VHDL) and simulated for Field Programmable Gate Array (FPGA).

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

Journal

Journal NameInternational Journal of Computer Science and Communication

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

PublisherCS-Journals

Volume Number5

Page Number51-53

Published YearJanuary 2014

A digital image processing algorithm for automation of human karyotyping

Journal

Journal NameInternational Journal of Computer Science and Communication

Title of PaperA digital image processing algorithm for automation of human karyotyping

PublisherCS-Journals

Volume Number5

Page Number54-56

Published YearJanuary 2014

Abstract

This research work aims to propose and implement a compute efficient application for augmenting the process of paired chromosome alignment called karyotyping. The methodology is a combination of various digital image processing techniques which serves as an effective solution for analyzing and processing raw microscopic images. The different phases for analysis include image acquisition, object segmentation, feature selection and extraction, and finally classification. However, certain open issues need to be tackled such as presence of marker, twisted or overlapped chromosomes. Hence, the consistency of this system relies on image quality and resolution. Manual intervention to some extent accounts for robust identification and classification.

Automatic Karyotyping of Human Chromosomes Using Band Patterns

Journal

Journal NameInternational Journal of Scientific Research

Title of PaperAutomatic Karyotyping of Human Chromosomes Using Band Patterns

Publisherthe global journals

Volume Number2

Page Number154-156

Published YearDecember 2013

Image Creation Using Coordinate Information

Journal

Journal NameInternational Journal of Computer Science and Technology

Title of PaperImage Creation Using Coordinate Information

Publishercosmic journals

Volume Number3

Published YearDecember 2012

Optimizing architecture of Vehicle to Infrastructure Communication

Journal

Journal Nameinternational journal of computer applications

Title of PaperOptimizing architecture of Vehicle to Infrastructure Communication

Volume Number53

Page Number29-35

Published YearSeptember 2012

Abstract

The road side infrastructure plays a vital role for any Vehicular Ad-hoc Network for implementing a rich set of applications like traffic monitoring and management, road disaster mitigation etc. This is the reason that efficient communication between the vehicles and the road side infrastructure is required. The application under consideration is providing a zero traffic lane (Z-Lane) for an ambulance. The scenarios are implemented with the help of Simulation of Urban Mobility (SUMO) which is a road traffic simulator based on Krauss Mobility Model. For the normal working of the said application, road side infrastructure broadcasts alert messages informing the vehicle drivers to vacant the lane. The problem addressed in this research work is the scenario where no infrastructure is present in the range of ambulance. In this case, the trigger from the ambulance must reach the nearest infrastructure as early as possible. For this purpose vehicle to vehicle communication is used. After analyzing various routing algorithms Ad-hoc On Demand Distance Vector (AODV) routing algorithm is chosen for the said communication. The AODV protocol has significant amount of end to end delay. The research work aims to modify AODV to reduce the Route REQuest (RREQ) packet generation. This is done using the geographic position of the neighboring node. The simulation results of the implementation of modified AODV shows that the number of RREQ packets reduces drastically and in turn end-to-end delay also reduces. The network traffic simulation is done with the help of Network Simulator-2.

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 Number831-832

Published YearSeptember 2012

Handling Fuzzy SQL on Crisp databases using Lex-YACC

Journal

Journal Nameinternational journal of computer applications

Title of PaperHandling Fuzzy SQL on Crisp databases using Lex-YACC

Volume Number4

Page Number5-8

Published YearJanuary 2010

Abstract

Conventional querying language presumes precision and certainty in user queries. But in factual situations the queries may be imprecise and may be desired to result in uncertain outcome. Introducing fuzziness in querying permits the realistic querying on the crisp data. In this paper, we propose the architecture for fuzzy querying along with an experimental implementation of the same. The implementation is using LEX and YACC that facilitate the lexical analysis of fuzzy terms and parsing the fuzzy query respectively. Fuzzy query is interpreted by the parser and the consequent semantic actions are carried out on MySQL database.

Preeti Kathiria

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, UGC List

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

PublisherI2OR Publication Services LLP

Volume Number6 APR.-JUNE 2018

Page Number1457-1459

Published YearApril 2018

ISSN/ISBN No2393-9028

Indexed INUGC List, Others

A NAIVE METHOD FOR ONTOLOGY CONSTRUCTION

Conference

Title of PaperA NAIVE METHOD FOR ONTOLOGY CONSTRUCTION

Proceeding NameNational Conference on Soft Computing and its application

OrganizationCharotar University of Science & Technology (CHARUSAT),

Page Number269-278

Published YearFebruary 2016

ISSN/ISBN No2319-1015

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, Others

Priyank Thakkar

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

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 INUGC List

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

Opinion spam detection using feature selection

Conference

Title of PaperOpinion spam detection using feature selection

Proceeding Name2014 International Conference on Computational Intelligence and Communication Networks (CICN)

PublisherIEEE

Page Number560-564

Published YearNovember 2014

Pronaya Bhattacharya

MudraChain: Blockchain-Based Framework for Automated Cheque Clearance in Financial Institutions

Journal

Journal NameFuture Generation Computer Systems

Title of PaperMudraChain: Blockchain-Based Framework for Automated Cheque Clearance in Financial Institutions

PublisherElsevier BV

Published YearOctober 2019

ISSN/ISBN No0167-739X

Indexed INScopus, Web of Science

Modern optical data centers: Design challenges and Issues

Book Chapter

Book NameAlgorithms for Intelligent Systems

PublisherSpringer Berlin Heidelberg

Author NameArunendra Singh, Richa Singh, Pronaya Bhattacharya, Amod Kumar Tiwari

Chapter TitleModern optical data centers: Design challenges and Issues

Published YearAugust 2019

ISSN/ISBN No2524-7565

Indexed INScopus

BloHosT: Blockchain Enabled Smart Tourism and Hospitality Management

Conference

Title of PaperBloHosT: Blockchain Enabled Smart Tourism and Hospitality Management

Proceeding NameInternational Conference on Computer, Information and Telecommunication Systems

PublisherIEEE

Author NameUmesh Bodkhe, Pronaya Bhattacharya, Sudeep Tanwar, Sudhanshu Tyagi, Neeraj Kumar, M.S. Obaidat

Year , VenueAugust 2019 , China

Indexed INScopus

GIS based DSS Model for Business Site Selection

Journal

Journal NameInternational Journal of Information Technology and Electrical Engineering

Title of PaperGIS based DSS Model for Business Site Selection

PublisherITEE International Journal of Information Technology and Electrical Engineering

Volume Number8

Page Number54-59

Published YearAugust 2019

ISSN/ISBN No2306-708X

Indexed INOthers

A proposed Buffer based Load balanced Optical Switch with AO- NACK scheme in modern Optical DataCentres

Book Chapter

Book NameSpringer Lecture notes in Electrical Engineering

PublisherSpringer Berlin Heidelberg

Author NamePronaya Bhattacharya, Amod Kumar Tiwari, Akhilesh Ladha, and Sudeep Tanwar

Chapter TitleA proposed Buffer based Load balanced Optical Switch with AO- NACK scheme in modern Optical DataCentres

Published YearJune 2019

ISSN/ISBN No1876-1100

Indexed INScopus

Dual-Buffer-Based Optical Datacenter Switch Design

Journal

Journal NameJournal of Optical Communications

Title of PaperDual-Buffer-Based Optical Datacenter Switch Design

PublisherDe Gryuters Gmbh

Volume NumberAhead of Print DOI: https://doi.org/10.1515/joc-2019-0023

Published YearMay 2019

ISSN/ISBN No0173-4911

Indexed INScopus, Web of Science

Abstract

The unbounded growth of Cloud-based services and Internet-of-Things (IoT) using Software Defined Networking (SDN) has resulted in bandwidth requirements that have grown enormously over the years. To meet this exponential growth that is currently outpacing Moore’s Law, we need Optical Interconnection Networks (OIN) that can satisfy the user’s requirements. In a similar direction Arrayed Waveguide Gratings (AWG)-based optical interconnects have been heavily investigated in past and many switch designs have emerged over the period of time. This paper proposes a dual-buffer-based optical switch design where the primary buffer stores the contending packets, while the secondary input buffer stores the contending packets which are blocked by AWG for one slot duration only. Moreover, if a blocked packet is generated on the same node then All-Optical Negative Acknowledgement (AO-NACK) will be used for blocked packets. This paper investigates the various issues related to storage of blocked packets, the analysis is done both at physical and network layers in terms of bit error rate (BER) and packet loss probability, respectively. It is found that with proposed switch design BER is 10 times lower than the earlier design, and the number of re-transmitted packets at the load of 0.8, reduces to 26 from 32 as in earlier switch design.

Mobile Edge Computing enabled Blockchain Framework-A survey

Book Chapter

Book NameSpringer Lecture notes in Electrical Engineering

PublisherSpringer Berlin Heidelberg

Author NamePronaya Bhattacharya, Sudeep Tanwar, Akhilesh Ladha, Rushabh Shah

Chapter TitleMobile Edge Computing enabled Blockchain Framework-A survey

Published YearMarch 2019

ISSN/ISBN No1876-1100

Indexed INScopus

Dual Buffers Optical Based Packet Switch incorporating Arrayed Waveguide Gratings

Journal

Journal NameJournal of Engineering Research

Title of PaperDual Buffers Optical Based Packet Switch incorporating Arrayed Waveguide Gratings

PublisherAcademic Publication Council

Volume Number7

Page Number1

Published YearMarch 2019

ISSN/ISBN No2307-1885

Indexed INScopus, Web of Science

Abstract

Optical packet switching is an upcoming and promising technology that can be used in optical data Centres and in next generation data transfer due to the enormous bandwidth of optical fiber. In recently proposed OPS design to resolve contention among packets fiber delay lines (FDLs) based buffering is preferred choice. In this paper, a dual buffer based optical packet switch design is proposed, where buffer sizes are chosen intelligently thus allowing storage of large number of contending packets within limited buffer storage. Hence, using a limited number of FDLs very low packet loss rate is possible.Through simulations, it has been shown that at the load of “0.9” a very low packet loss rate of the order of 10^-8 is possible.To the best of our knowledge, this is the lowest packet loss rate using FDLs till date in any switch design.The proposed switch design is also compared with recently published designs to prove its superiority over other designs. The analysis of the switch is done in terms of power budget analysis, cost analysis, and packet loss performance under different buffering conditions.

Bit Error Rate Analysis of Hybrid Buffer-Based Switch for Optical Data Centres

Journal

Journal NameJournal of Optical Communications

Title of PaperBit Error Rate Analysis of Hybrid Buffer-Based Switch for Optical Data Centres

PublisherDe Gryuters Gmbh

Volume NumberAhead of Print DOI: https://doi.org/10.1515/joc-2019-0008

Published YearFebruary 2019

ISSN/ISBN No2191-6322

Indexed INScopus, Web of Science

E-mail Spam Filtering using Genetic Algorithm based on Probabilistic Weights and Words Count

Journal

Journal NameInternational Journal of Integrated Engineering

Title of PaperE-mail Spam Filtering using Genetic Algorithm based on Probabilistic Weights and Words Count

PublisherPenerbit UTHM

Published YearJanuary 2019

ISSN/ISBN No2229-838X

Conference

Title of PaperA Distributed Credit Transfer Educational Framework based on Blockchain

Proceeding NameProceedings of the Second IEEE International Conference on Advances in Computing, Control and Communication Technology.

PublisherIEEE Digital Xplore

Author NameAbhishek Srivastava, Pronaya Bhattacharya, Arunendra Singh, Atul Mathur, Om Prakash, and Rajeshkumar Pradhan

OrganizationAllahabad University

Year , VenueSeptember 2018 , Allahabad University

Page Number54-59

ISSN/ISBN No978-1-5386-4146-0

Indexed INScopus

A Critical Review of Next Generation Data Centres

Journal

Journal NameInternational Journal of Information Technology and Electrical Engineering

Title of PaperA Critical Review of Next Generation Data Centres

PublisherUniversity

Volume Number7

Page Number12-17

Published YearApril 2018

ISSN/ISBN No2306-708X

Indexed INUGC List

Abstract

Demand for higher bandwidth is increasing as the day progresses. Current electronic switching used in data Centres are now facing bottleneck to match data rates. To alleviate such problem, fiber optic technology is used in backbone network, and switching is still performed using electronic circuitry after performing O/E conversion. However, till recent past, data transfer technology heavily relies on electronics. Therefore, researchers propose the used of both electrical and optical technology for high speed data transfer. Data center technology is emerging over the period of time. However, due to the commercial un-availability of tunable wavelength converters all-optical data Centres is not feasible till date. In the recent past many data Centres core switch designs are proposed, which uses both electronic packet switching (EPS) and optical circuit switching (OCS) depending on network requirements, and rate at which data arrives. This paper presents the overview of the recently proposed data Centres design along with their pros and cons. This paper reviews both well established and up-coming data Centres design which can be considered as near future designs.

Comparative Study for Proposed Algorithm for All-Optical Network with Negative Acknowledgement (AO-NACK)

Conference

Title of PaperComparative Study for Proposed Algorithm for All-Optical Network with Negative Acknowledgement (AO-NACK)

Proceeding NameProceedings of the 7th International Conference on Computer and Communication

PublisherACM Digital Library

Author NamePronaya Bhattacharya, Arunendra Singh, Akhilesh Kumar, Amod Kumar Tiwari, and Rajiv Srivastava

OrganizationACM

Year , VenueNovember 2017 , MNNIT Allahabad

Page Number47-51

ISSN/ISBN No978-1-4503-5324-3

Indexed INScopus

Abstract

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

Evolution of singular value decomposition in recommendation systems: a review

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.

Rupal Kapdi

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.

Rushabh Shah

Comparative Performance Study of Various Content Based Image Retrieval Methods

Book Chapter

Book NameSmart Innovation, Systems and Technologies, VOLUME 50

PublisherSPRINGER

Author NameSuresh Chandra Satapathy , Swagatam Das

Page Number397-407

Chapter TitleComparative Performance Study of Various Content Based Image Retrieval Methods

Published YearJuly 2016

ISSN/ISBN No Print ISBN 978-3-319-30932-3 Online ISBN 978-3-319-30933-0

Indexed INScopus

Abstract

With the increase in the data storage and data acquisition technologies there is an increase in huge image database. Therefore we need to develop proper and accurate systems to manage this database. Here in this paper we focus on the transformation technique to search, browse and retrieve images from large database. Here we have discussed briefly about the CBIR technique for image retrieval using

Comparative Performance Study of Various Content Based Image Retrieval Methods

Conference

Title of PaperComparative Performance Study of Various Content Based Image Retrieval Methods

Proceeding NameProceedings of First International Conference on Information and Communication Technology for Intelligent Systems: Volume 1

PublisherSPRINGER, CHAM

Author NameSuresh Chandra Satapathy , Swagatam Das

OrganizationVENUS COLLEGE OF ENGINEERING

Year , VenueNovember 2015 , AHMEDABAD

Page Number397-407

ISSN/ISBN NoPrint ISBN 978-3-319-30932-3 Online ISBN 978-3-319-30933-0

Indexed INScopus

Abstract

Performance Analysis of Region of Interest Based Compression Method for Medical Images

Conference

Title of PaperPerformance Analysis of Region of Interest Based Compression Method for Medical Images

Proceeding Name2014 Fourth International Conference on Advanced Computing & Communication Technologies

PublisherConference Publishing Services (CPS) and IEEE Explore

Author NameIEEE

OrganizationROHTAK, HARYANA

Year , VenueFebruary 2014 , ROHTAK

Page Number53-58

ISSN/ISBN No978-1-4799-4910-6/14

Indexed INScopus

Abstract

In medical domain the high quality image data is maintained with the help of highly efficient servers across the network. There are some areas of medicine where it is sufficient to maintain high image quality only for diagnostically important regions, for example, tumor region of the brain MRI. Thus, the regions of interest

Sapan H Mankad

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

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

Survey on Security Provisions in Named Data Networking

Journal

Journal NameInternational Journal of Applied Research on Information Technology and Computing

Title of PaperSurvey on Security Provisions in Named Data Networking

PublisherIndian Journals

Volume Number10

Page Number1-7

Published YearApril 2019

ISSN/ISBN No0975-8089

Indexed INIndian citation Index

Abstract

Named Data Networking (NDN) is considered to be a new proposed Internet architecture which is fundamentally different from host-centric communications in Internet. Here, instead of sending data packet to specific locations, NDN retrieves data by name. This methodology addresses the IP’s (Internet Protocol) communication issues as well as the digital distribution and management issues. This content has to be authenticated and signed by the originator of the content. This security model is core to NDN from functioning perspective. Internet raises multiple-challenge issues related to end to end communication. On the other hand, a NDN differs fundamentally in the host-to-host communication design of today’s internet. Hence, NDN gives rise to several research challenges. In NDN, focus is on digital signature and authentication. So, the public key using which the data is signed is to be made available to the intended stake holders. Hence, public key management issue is critical to NDN. The certificate format and related systems and protocols for supporting certificate distribution and revocation are intrinsic to the NDN architecture. In this paper, exhaustive survey of various security aspects that deal with provisioning of digital signature mechanisms for NDN are presented.

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

Journal

Journal NameJournal on Communication Engineering and Systems

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

Publisheri-Manager Publication

Volume Number7

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

The Fog Computing Paradigm: A Rising Need of IoT World

Conference

Title of PaperThe Fog Computing Paradigm: A Rising Need of IoT World

Proceeding NameProceedings of the 2nd International Conference on Data Engineering and Communication Technology

PublisherSpringer

OrganizationICDECT 2017

Page Number387-393

Published YearOctober 2018

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

Indexed INScopus

Traffic Signal Synchronization Using Computer Vision and Wireless Sensor Networks

Conference

Title of PaperTraffic Signal Synchronization Using Computer Vision and Wireless Sensor Networks

Proceeding NameArtificial Intelligence and Evolutionary Computations in Engineering Systems

PublisherSpringer

OrganizationICAIECES 2015

Page Number 743-751

Published YearFebruary 2016

ISSN/ISBN No978-81-322-2654-3

Indexed INScopus

Smita Agrawal

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.

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

Sudeep Tanwar

Security and Privacy of Electronics Healthcare Records, In Preparation,

Book

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

Swati Jain

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

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

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

Tejal Upadhyay

Heart Disease Prediction Using Machine Learning and Data Mining Techniques

Journal

Journal NameComputer Science and Electronics Journals

Title of PaperHeart Disease Prediction Using Machine Learning and Data Mining Techniques

PublisherCS - Journals

Volume Number7

Page Number129-137

Published YearSeptember 2015

ISSN/ISBN No0973-7391

Indexed INUGC List

Abstract

—Heart disease is the main reason for death in the world over the last decade. Almost one person dies of Heart disease about every minute in the United States alone. Researchers have been using several data mining techniques to help health care professionals in the diagnosis of heart disease. However using data mining technique can reduce the number of test that are required. In order to reduce number of deaths from heart diseases there have to be a quick and efficient detection technique. Decision Tree is one of the effective data mining methods used. This research compares different algorithms of Decision Tree classification seeking better performance in heart disease diagnosis using WEKA. The algorithms which are tested is J48 algorithm, Logistic model tree algorithm and Random Forest algorithm. The existing datasets of heart disease patients from Cleveland database of UCI repository is used to test and justify the performance of decision tree algorithms. This datasets consists of 303 instances and 76 attributes. Subsequently, the classification algorithm that has optimal potential will be suggested for use in sizeable data. The goal of this study is to extract hidden patterns by applying data mining techniques, which are noteworthy to heart diseases and to predict the presence of heart disease in patients where this presence is valued from no presence to likely presence

Umesh Bodkhe

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 NoIEEE Access 2169-3536

Indexed INScopus, Web of Science, Others

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

A Survey on Decentralized Consensus Mechanisms for Cyber Physical Systems

Journal

Journal NameIEEE ACCESS

Title of PaperA Survey on Decentralized Consensus Mechanisms for Cyber Physical Systems

PublisherIEEE

Volume Number8

Page Number54371 - 54401

Published YearMarch 2020

ISSN/ISBN No2169-3536

Indexed INScopus, Web of Science, Others

Abstract

Modern industry 4.0 applications are shifting towards decentralized automation of computing and cyber-physical systems (CPS), which necessitates building a robust, secure, and efficient system that performs complex interactions with other physical processes. To handle complex interactions in CPS, trust and consensus among various stakeholders is a prime concern. In a similar direction, consensus algorithms in blockchain have evolved over the years that focus on building smart, robust, and secure CPS. Thus, it is imperative to understand the key components, functional characteristics, and architecture of different consensus algorithms used in CPS. Many consensus algorithms exist in the literature with a specified set of functionalities, performance, and computing services. Motivated from these facts, in this survey, we present a comprehensive analysis of existing state-of-the-art consensus mechanisms and highlight their strength and weaknesses in decentralized CPS applications. In the first part, we present the scope of the proposed survey and identify gaps in the existing surveys. Secondly, we present the review method and objectives of the proposed survey based on research questions that address the gaps in existing studies. Then, we present a solution taxonomy of decentralized consensus mechanisms for various CPS applications. Then, open issues and challenges are also discussed in deploying various consensus mechanisms in the CPS with their merits and demerits. The proposed survey will act as a road-map for blockchain developers and researchers to evaluate and design future consensus mechanisms, which helps to build an efficient CPS for industry 4.0 stakeholders

“Managing Cooperative Behaviour in Social Communication” ICASCCT 2014, Hyderabad

Conference

Title of Paper“Managing Cooperative Behaviour in Social Communication” ICASCCT 2014, Hyderabad

Proceeding NameAdvances in Soft Computing and Communication Technologies (ICASCCT) 2014, Hyderabad

Year , VenueAugust 2014 , Hyderabad

ISSN/ISBN No 2229-3515

Indexed INUGC List

Usha Patel

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

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

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

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

Energy Aware Computing Resource Allocation Using PSO in Cloud

Book Chapter

Book NameInformation and Communication Technology for Intelligent Systems

PublisherSpringer, Singapore

Page Number511-519

Chapter TitleEnergy Aware Computing Resource Allocation Using PSO in Cloud

Published YearDecember 2018

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

Indexed INScopus, UGC List

Abstract

In cloud computing, a large number of resources are used like data Centres, servers, computing resources (VMs), and IoT devices. One of the key challenges in cloud computing is to provide energy-efficient resource management. In this resource management, energy is one of the key parameters which is to be resolved.

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

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

Zunnun Narmawala

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

Conference

Title of PaperViral spread in mobile social network using network coding

Proceeding Name11th IEEE India Conference: Emerging Trends and Innovation in Technology, INDICON 2014

PublisherIEEE

OrganizationIEEE Pune Section

Year , VenueDecember 2014 , Pune

ISSN/ISBN No2325-9418

Indexed INScopus

Abstract

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.