Data Science and Applications
Description
This book gathers outstanding papers presented at the 5th International Conference on Data Science and Applications (ICDSA 2024), organized by Soft Computing Research Society (SCRS) and Malaviya National Institute of Technology Jaipur, India, from 17 to 19 July 2024. The book is divided into four volumes, and 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.
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Dr. Satyasai Jagannath Nanda is an associate professor in the Dept. of Electronics and Communication Engg., Malaviya National Institute of Technology Jaipur, India. He received PhD degree from School of Electrical Sciences, IIT Bhubaneswar; M. Tech. degree from Dept. of Electronics and Communication Engg., NIT Rourkela and B.E. degree from Institute of Technical Education and Research, Bhubaneswar. He received the prestigious IEI Young Engineers Award by Institution of Engineers. He has published 55 journal articles and 65 international conference proceedings, which, to date, have received 2000+ citations. He is a lead Guest Editor of the journal SN Computer Science, Springer. He is the principal investigator of 5G laboratory established by Department of Telecom, Govt. of India at MNIT Jaipur. Under his supervision, 08 researchers have been awarded PhD, and 05 researchers are continuing their research work. His research interests are Adaptive Signal Processing, Multi-objective optimization, Data Clustering, Neural Networks, and Evolutionary Computation.
Prof. Rajendra Prasad Yadav is currently working as a Professor-HAG in the Department of Electronics and Communication Engineering, Malaviya National Institute of Technology, Jaipur, Rajasthan, India. He has more than four decades of teaching and research experience. He was instrumental in starting new B.Tech, M.Tech courses and formulating Ph.D Ordinances for starting research work in Rajasthan Technical University (RTU) Kota and other affiliated Engg colleges as Vice Chancellor of the University. He has served as HOD of Electronics and Comm. Engg., President Sports and Library, Hostel warden, Dean Student Affairs at MNIT Jaipur. He was also the Chief Vigilance Officer of MNIT Jaipur. Prof. Yadav received the Ph.D degree from MREC Jaipur and M.Tech degree from IIT Delhi. Under his supervision 15 Ph.D students have received Ph.D degree, 7 students are working for their Ph.D degree. Fourty M.Tech students have carried out their dissertation work under his guidance. He has published more than 240 peer review research papers which has received fifteen hundred citations. His research interest are Error Control Codes and MIMO-OFDM, RF and Antenna Systems, Mobile and Wireless Communication Systems, Optical Switching and Materials, Mobile Adhoc and Sensor Network, Device Characterization and MEMS, Cognitive Radio Networks.
Amir H. Gandomi is a Professor of Data Science at the Faculty of Engineering & Information Technology, University of Technology Sydney. He is also affiliated with Obuda University, Budapest, as a Distinguished Professor. Prior to joining UTS, Prof. Gandomi was an Assistant Professor at the Stevens Institute of Technology and a distinguished research fellow at BEACON Center, Michigan State University. Prof. Gandomi has published over three hundred journal papers and 12 books, which have collectively been cited 60,000 times. He has been named as one of the most influential scientific minds and received the Highly Cited Researcher award (top 1% publications and 0.1% researchers) from Web of Science for six years. In a recent study at Stanford University, released by Elsevier, Prof Amir H Gandomi is ranked 24th most impactful researcher in the AI and Image Processing subfield in 2023! He also ranked 18th in GP bibliography among more than 17,000 researchers. He has received multiple prestigious awards for his research excellence and impact, such as the 2024 IEEE TCSC Award for Excellence in Scalable Computing (MCR), 2023 Achenbach Medal, and the 2022 Walter L. Huber Prize, 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. Prof Gandomi is active in delivering keynotes and invited talks. His research interests are global optimisation and (big) data analytics.
Prof. Mukesh Saraswat is a Professor and Associate Dean (Innovation) at Jaypee Institute of Information Technology (JIIT), Noida, India. Prof. Saraswat obtained his Ph.D. in Computer Science & Engineering from ABV-IIITM Gwalior, India. He has more than 20 years of teaching and research experience. He has guided 04 Ph.D. students and presently guiding 04 Ph.D. students. He has published more than 80 journal and conference papers in the areas of image processing, pattern recognition, and soft computing. He was part of a completed project funded by SERB, New Delhi on image analysis and 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 Faculty in charge of Jaypee Youth Club at JIIT, Noida. He is also a guest editor of the Array, Journal of Swarm Intelligence, SN Computer Science, 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 Advisory Board Member of the Journal MethodsX. He is an active member of ACM, CSI, and SCRS Professional Bodies.
Content
Impact on Sustainable Factors in Plywood Industry: A soft computing approach.- Exploring Deep Learning Approaches in Medical Image Processing for Lung Cancer Cell Detection: A Comprehensive Review.- Enhancing Fake News Detection: A Hybrid Approach with LSTM and Convolutional Neural Networks.- Detecting Imbalanced Network Traffic Intrusions using the Long Short-Term Memory (LSTM) Algorithm.- Classification and Recommendation Methods for Sleep Apnea Syndrome.