Proceedings of International Conference on Data Science and Applications

ICDSA 2022, Volume 2
Herausgegeben:Saraswat, Mukesh; Chowdhury, Chandreyee; Kumar Mandal, Chintan; Gandomi, Amir H.

• Broschiertes Buch

Produktbeschreibung

This book gathers outstanding papers presented at the International Conference on Data Science and Applications (ICDSA 2022), organized by Soft Computing Research Society (SCRS) and Jadavpur University, Kolkata, India, from 26 to 27 March 2022. It covers theoretical and empirical developments in various areas of big data analytics, big data technologies, decision tree learning, wireless communication, wireless sensor networking, bioinformatics and systems, artificial neural networks, deep learning, genetic algorithms, data mining, fuzzy logic, optimization algorithms, image processing, computational intelligence in civil engineering, and creative computing.

Produktdetails

• Lecture Notes in Networks and Systems 552
• Verlag: Springer / Springer Nature Singapore / Springer, Berlin
• Artikelnr. des Verlages: 978-981-19-6633-0
• 1st ed. 2023
• Seitenzahl: 944
• Erscheinungstermin: 7. Februar 2023
• Englisch
• Abmessung: 235mm x 155mm x 47mm
• Gewicht: 1570g
• ISBN-13: 9789811966330
• ISBN-10: 9811966338
• Artikelnr.: 65005377

Autorenporträt

Mukesh Saraswat is an Associate Professor at Jaypee Institute of Information Technology, Noida, India. Dr. Saraswat obtained his Ph.D. in Computer Science & Engineering from ABV-IIITM Gwalior, India. He has more than 19 years of teaching and research experience. He has guided 03 Ph.D. students and presently guiding 04 Ph.D. students. He has published more than 70 journal and conference papers in the area of image processing, pattern recognition, data mining, and soft computing. He was part of successfully completed project funded by SERB, New Delhi on image analysis and currently running one project funded by CRS, RTU, Kota. He has been an active member of many organizing committees for various conferences and workshops. He is also a guest editor of the Array, Journal of Swarm Intelligence, and Journal of Intelligent Engineering Informatics. He is one of the General Chairs of the International Conference on Data Science and Applications. He is also an Editorial Board Member of the Journal MethodsX. Heis also a series editor of the SCRS Book Series on Computing and Intelligent Systems (CIS). He is an active member of IEEE, ACM, CSI, and SCRS Professional Bodies. His research areas include Image Processing, Pattern Recognition, Data Mining, and Soft Computing. Chandreyee Chowdhury is an Associate Professor in the department of Computer Science and Engineering at Jadavpur University, India. She has received M.E in Computer Science and Engineering in 2005 and PhD in 2013 from Jadavpur University. Her research interests include IoT in healthcare, indoor localization, and human activity recognition. She was awarded Post-Doctoral Fellowship by Erusmus Mundus in 2014 to carry out research work at Northumbria University, UK. She has served as technical program committee members of many international conferences. She has published more than 100 papers in reputed journals, book chapters and international peer-reviewed conferences. She is a member of IEEE and IEEE Computer Society. Chintan Kumar Mandal is presently working in the Department of Computer Science and Engineering at Jadavpur University, Kolkata, India. He did his graduation and post-graduation in Computer Science and Engineering from Calcutta University followed by his PhD from Motilal Nehru National Institute of Technology, Allahabad. Prior to these, he did his Physics with Honours from Calcutta University. He has published papers in various journals and conferences. His areas of interest are Computational Geometry, Computer Graphics and Robotics. Amir H. Gandomi is a Professor of Data Science and an ARC DECRA Fellow at the Faculty of Engineering & Information Technology, University of Technology Sydney. Prior to joining UTS, Prof. Gandomi was an Assistant Professor at Stevens Institute of Technology, USA and a distinguished research fellow at BEACON center, Michigan State University, USA. Prof. Gandomi has published over three hundred journal papers and 12 books which collectively have been cited 31,000+ times (H-index = 81). He has been named as one of the most influential scientific minds and received Highly Cited Researcher awards (top 1% publications and 0.1% researchers) for five consecutive years, 2017 to 2021. He also ranked 17th in GP bibliography among more than 15,000 researchers. He has received multiple prestigious awards for his research excellence and impact, such as the 2022 Walter L. Huber Prize which is known as the highest level mid-career research award in all areas of civil engineering. He has served as associate editor, editor, and guest editor in several prestigious journals such as AE of IEEE TBD and IEEE IoTJ. Prof Gandomi is active in delivering keynotes and invited talks. His research interests are (big) data analytics and global optimisation. 

Inhaltsangabe

Improving River Streamflow Forecasting utilizing Multi-layer Perceptron-based Butterfly Optimization Algorithm.- Covid-19 Contact Tracing Using Low Calibrated Transmission Power from BLE - Approach & Algorithm Experimentation.- Monitoring loud commercials in television broadcast.- Potential Customers Prediction in Bank Telemarketing.- Analysis and implementation of normalization techniques on KDD'99 Dataset for Detect and Prevent Intrusion on Network.- Deep Neural Networks Predicting Student Performance.- An Efficient Group Signature Scheme based on ECDLP.- Sentiment Analysis of COVID-19 tweets using TextBlob and Machine Learning classifiers - An evaluation to show how COVID -19 opinions is influencing psychological reactions of people's behaviour in social media.

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Improving River Streamflow Forecasting utilizing Multi-layer Perceptron-based Butterfly Optimization Algorithm.- Covid-19 Contact Tracing Using Low Calibrated Transmission Power from BLE – Approach & Algorithm Experimentation.- Monitoring loud commercials in television broadcast.- Potential Customers Prediction in Bank Telemarketing.- Analysis and implementation of normalization techniques on KDD'99 Dataset for Detect and Prevent Intrusion on Network.- Deep Neural Networks Predicting Student Performance.- An Efficient Group Signature Scheme based on ECDLP.- Sentiment Analysis of COVID-19 tweets using TextBlob and Machine Learning classifiers - An evaluation to show how COVID -19 opinions is influencing psychological reactions of people‘s behaviour in social media.