This book includes research papers presented at the International Conference on Data Science and Network Engineering (ICDSNE 2025) organized by the Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, India, during July 18 19, 2025. It includes research work 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),…mehr
This book includes research papers presented at the International Conference on Data Science and Network Engineering (ICDSNE 2025) organized by the Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, India, during July 18 19, 2025. It includes research work 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.
Artikelnr. des Verlages: 89569336, 978-3-032-07734-9
Seitenzahl: 339
Erscheinungstermin: 22. November 2025
Englisch
Abmessung: 235mm x 155mm
ISBN-13: 9783032077349
ISBN-10: 3032077346
Artikelnr.: 75323012
Herstellerkennzeichnung
Springer-Verlag GmbH
Tiergartenstr. 17
69121 Heidelberg
ProductSafety@springernature.com
Autorenporträt
Suyel Namasudra has received Ph.D. degree from the National Institute of Technology Silchar, 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 CSE at the NIT Agartala, India. Before joining the NIT Agartala, Dr. Namasudra was an assistant professor in the Department of CSE at the NIT Patna, India. His research interests include blockchain technology, cloud computing, IoT, and machine learning. Dr. Namasudra has edited 9 books, 5 patents, and 89 publications in conference proceedings, book chapters, and refereed journals. He is the Editor-in-Chief of the Cloud Computing and Data Science (ISSN: 2737-4092 (online)) journal. Dr. Namasudra is a senior member of IEEE and ACM, and he has been featured in the list of the top 2% scientists in the world from 2021 to 2024. His h-index is 41. 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. He is working as a professor in the Department of ECE 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. Byung-Gyu Kim received the B.S. degree from Pusan National University, Republic of Korea (South Korea), in 1996, the M.S. degree from the Korea Advanced Institute of Science and Technology (KAIST), in 1998, and the Ph.D. degree from the Department of Electrical Engineering and Computer Science, KAIST, in 2004. In March 2016, he joined the Department of Information Technology (IT) Engineering, Sookmyung Women’s University, South Korea, where he is currently a Full Professor. He has published over 240 international journal articles and conference papers, and patents in his field. Dr. Kim is a Professional Member of ACM and IEICE. He also served or serves on Organizing Committee of CSIP 2011, a Co-Organizer of CICCAT2016/2017, The Seventh International Conference on Advanced Computing, Networking, and Informatics (ICACNI 2019), the EAI 13th International Conference on Wireless Internet Communications Conference (WiCON 2020), and the Program Committee Members of many international conferences
Inhaltsangabe
Ensemble Classifier for Real-Time Breast Cancer Classification on Histopathology Images.- A Smart Surveillance Framework for Real-Time Suspicious Activity Detection and Automated Alert Generation Using YOLOv8.- Enhancing E-Commerce Trust: An Integrated Product Recommendation and Fake Review Detection System.- Hardware-Efficient Neural Network for Voice Disorder Classification from Multi-Source Datasets.- Predictive Maintenance on C-MAPSS Using LSTM Variants and Attention.- Unveiling Ebola-Human Protein Links through Network Embedding and Unsupervised Machine Learning.- Discount Optimisation in Food Delivery Using Machine Learning.
Ensemble Classifier for Real-Time Breast Cancer Classification on Histopathology Images.- A Smart Surveillance Framework for Real-Time Suspicious Activity Detection and Automated Alert Generation Using YOLOv8.- Enhancing E-Commerce Trust: An Integrated Product Recommendation and Fake Review Detection System.- Hardware-Efficient Neural Network for Voice Disorder Classification from Multi-Source Datasets.- Predictive Maintenance on C-MAPSS Using LSTM Variants and Attention.- Unveiling Ebola-Human Protein Links through Network Embedding and Unsupervised Machine Learning.- Discount Optimisation in Food Delivery Using Machine Learning.
Es gelten unsere Allgemeinen Geschäftsbedingungen: www.buecher.de/agb
Impressum
www.buecher.de ist ein Internetauftritt der buecher.de internetstores GmbH
Geschäftsführung: Monica Sawhney | Roland Kölbl | Günter Hilger
Sitz der Gesellschaft: Batheyer Straße 115 - 117, 58099 Hagen
Postanschrift: Bürgermeister-Wegele-Str. 12, 86167 Augsburg
Amtsgericht Hagen HRB 13257
Steuernummer: 321/5800/1497
USt-IdNr: DE450055826