Data Science and Network Engineering
Description
This book includes research papers presented at the International Conference on Data Science and Network Engineering (ICDSNE 2024) organized by the Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, India, during July 12-13, 2024. It includes research works from researchers, academicians, business executives, and industry professionals for solving real-life problems by using the advancements and applications of data science and network engineering. This book covers many advanced topics, such as artificial intelligence (AI), machine learning (ML), deep learning (DL), computer networks, blockchain, security and privacy, Internet of things (IoT), cloud computing, big data, supply chain management, and many more. Different sections of this book are highly beneficial for the researchers, who are working in the field of data science and network engineering.
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Suyel Namasudra has received Ph.D. degree from the National Institute of Technology Silchar, Assam, India. He was a post-doctorate fellow at the International University of La Rioja (UNIR), Spain. Currently, Dr. Namasudra is working as an assistant professor in the Department of Computer Science and Engineering at the National Institute of Technology Agartala, Tripura, India. Before joining the National Institute of Technology Agartala, Dr. Namasudra was an assistant professor in the Department of Computer Science and Engineering at the National Institute of Technology Patna, Bihar, India. His research interests include blockchain technology, cloud computing, DNA computing, and information security. Dr. Namasudra has edited 7 books, 5 patents, and 86 publications in conference proceedings, book chapters, and refereed journals like IEEE TII, IEEE, TNSM, IEEE TCE, IEEE T-ITS, IEEE TSC, IEEE TCSS, IEEE TCBB, ACM TOMM, ACM TOSN, ACM TALLIP, FGCS, CAEE, and many more.
Nirmalya Kar, a member of IEEE, is currently an assistant professor at the Dept. of Computer Science and Engineering, National Institute of Technical Agartala, and designated Chief Information Security Officer. He has expertise in information security, cyber analytics, data hiding, and DNA computing. He has been actively involved in many major conferences and workshops in program/steering conference chairman positions and as a program committee member. He has organized several conferences related to security and computational intelligence. He is a reviewer of several journals and transcriptions. He has worked as a member of boards of studies of institutions and evaluator of Smart India Hackathons. He is also one of the mentors of Startup Tripura. He has also contributed to industry-academia collaboration, student enablement, and pedagogical learning.
Sarat Kumar Patra received Ph.D. degree from the Edinburgh University, UK, in 1998. He is a professor in the Department of Electronics and Communication Eng at the NIT Rourkela, India. Prof. Patra has a total of 37 years of experience in teaching and industry. His research interests include wireless communication, soft computing, optical communication, and deep learning. Prof. Patra has edited many books and more than 200 publications in conference proceedings, book chapters, and refereed journals. His h-index is 20. Currently, he holds the position of Director at the National Institute of Technology Agartala from May 2023. He also served as the director of IIIT Vadodara from July 2017 to May 2023.
David Taniar received all his degrees (Bachelor, Master, and PhD) in Computer Science. His research expertise includes data warehousing, data management, data engineering, and data analytics. His recent book on Data Warehousing and Analytics (Springer, 2021) has been accessed more than 50 thousand times, and it is being used as a textbook worldwide. He has graduated more than 25 PhD students in his career. He is currently an associate professor at Monash University, Australia.
Content
Hyperparameter Tuning of Fine-Tuned VGG19 Using Sine Cosine Algorithm for Acute Lymphoblastic Leukemia Detection.- Computer Vision and Deep Learning-based Model for Detecting Spoofed Faces in Images.- Explainable AI Insights into a Time Series Weather Prediction Model Using Stacked LSTM.- Patient-specific and Patient-independent Seizure Prediction using Ensemble Learning Technique.- An Intuitive and Modular Framework for Enhanced Human-Machine Synergy.- Wavelet-Transformed k-NN Pipeline for EEG-Based Eye Blink Classification with Time Wrapping.
