Proceedings of International Conference on Data Analytics and Insights

ICDAI 2025, Volume 2
Erscheinungsjahr 2026
ISBN: 978-3-032-14774-5
Verlag: Springer Nature Switzerland AG

Buch, Englisch, 531 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Networks and Systems

This book is a collection of peer-reviewed best selected research papers presented at the International Conference on Data Analytics and Insights (ICDAI 2025), organized by Techno International, Kolkata, India, during August 28–30, 2025. The two volumes of the book cover important topics like sensor and network data analytics and insights; big data analytics and insights; biological and biomedical data analysis and insights; optimization techniques, time series analysis and forecasting; power and energy systems data analytics and insights; civil and environmental data analytics and insights; and industry and applications.

Zielgruppe

Research

Autoren/Hrsg.

Chaki, Nabendu

Debnath, Papiya

Das, Nabanita

Yang, Xin-She

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Informationstheorie, Kodierungstheorie
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik Drahtlostechnologie
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Competitive Travelling Salesman Problem using Simulated Annealing.- A New Algorithm for Solving the Primal Standard two Variables Linear Programming Problem and Numerical Experimental Results.- A Prototype-Based Zero Trust Architecture for Secure Access Control in Enterprise Networks.- EEG Based Dynamic Brain Connectivity to Predict Neurological Outcome of Neonatal Hypoxic-Ischaemic Encephalopathy.- Demand Forecasting in Socio-Economic Groups using Parametric Time-Series Modelling of Smart Meter Data.- Performance Evaluation of 2×1 Array Patch Antenna for Wireless Applications at 27 GHz.- Light Gradient Boosting Classifier for Real-Time Air Quality Monitoring.- NetraGAN: A Novel Approach to Ocular Disease Detection with GAN and Deep Learning.- Unraveling the Influence of Social Network Behaviors and Recommendation Systems on Purchase Intentions: Social-Affective Computing in E-Marketplaces.- Nvidia Stock Trends via YouTube Sentiment Analysis.

Über Autor(innen)

Nabendu Chaki is a senior member of IEEE and an associate professor in the Department of Computer Science & Engineering, University of Calcutta, India. Besides editing several volumes in LNCS, Springer, and other series, Nabendu has authored three textbooks with reputed publishers like Taylor and Francis (CRC Press), Pearson Education, etc. Dr. Chaki has published more than 100 refereed research papers in journals and international conferences. His areas of research interest include image processing, distributed systems, and network security. Dr. Chaki has also served as a research assistant professor in the Ph.D. program (Software Engineering) at US Naval Postgraduate School, Monterey, CA. He is a visiting faculty member for many universities including the University of Ca’Foscari, Venice, Italy. Dr. Chaki has contributed to SWEBOK v3 of the IEEE Computer Society as a knowledge area editor for Mathematical Foundations. 
 
Papiya Debnath is a professor in the Department of Basic Science and Humanities (Mathematics), at Techno International New Town, Kolkata, India. She received her Master of Science in Applied Mathematics from the Indian Institute of Engineering Science and Technology, Shibpur in 2006. She received M.Phil. degree in Applied Mathematics from the University of Calcutta, India, in 2009 and Ph.D. in Applied Mathematics from the University of Calcutta in 2019. She has 18 years of experience in teaching, research, and administration. She has published 49 papers in national, international journals, and conference proceedings, 7 book chapters, and served as the editor of 3 book, and 5 patents. She is guiding 2 Ph.D. students. She is a member of the IEEE EDS and IEEE Geoscience and Remote Sensing Society.

Nabanita Das is an associate professor in the Department of Computer Science & Engineering, Techno International New Town, Kolkata, with over 19 years of experience in the academic field. She received her Ph.D. from the University of Engineering and Management, Kolkata, India. Dr. Das has mentored numerous undergraduate students, helping them publish research papers in recognized international platforms. Her current research focuses on areas such as stock market prediction, sentiment analysis, and the application of machine learning and deep learning in practical scenarios. Dr. Das has published 28 research papers in various journals and conferences. She has published 5 patents. 

Xin-She Yang obtained his DPhil in Applied Mathematics from the University of Oxford. He then worked at Cambridge University and then later at National Physical Laboratory (UK) as a Senior Research Scientist. Now he is Reader in Modelling and Optimization at Middlesex University London, and a co-Editor of the Springer Tracts in Nature-Inspired Computing. He is also an elected Fellow of the Institute of Mathematics and its Applications (FIMA, UK), Fellow of Asian Computational Intelligence Society and Fellow of Soft Computing Research Society. He was the IEEE Computational Intelligence Society (CIS) chair for the Task Force on Business Intelligence and Knowledge Management (2015 to 2020). He has edited more than 50 books and published more than 400 peer-reviewed research papers with more than 100400 citations, and he has been on the prestigious list of most influential researchers or highly-cited researchers (Web of Sciences) for ten consecutive years since 2016.