This book includes research papers presented at the International Conference on Emerging Trends in Expert Applications and Security (NICE-TEAS 2025) jointly organized by WSG University, Bydgoszcz, Poland, Shree KKarni Universe College, Jaipur, and ** IES University, Bhopal, India during 4 6 July 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 AI and machine learning for cyber security and threat detection, big data analytics and real-time data processing, IoT networks, cloud security, edge computing and data protection, deep learning and AI-driven predictive analytics, quantum computing for next-gen expert applications, computer vision and image recognition in smart systems, and multimedia applications in forensics, security and intelligence.

Presents recent research in expert applications and security Discusses the outcomes of NICE-TEAS 2025, held in Bydgoszcz, Poland Serves as a reference resource for researchers and practitioners in academia and industry

Autorentext

Dr. Vijay Singh Rathore is presently working as Professor-CSE & Director of Research and International Relations, IES University, Bhopal, Director, KK Consultancy Services, Jaipur, and also running his own establishment Shree KKarni Universe College, Jaipur (in partnership). He is Membership Chair, ACM Jaipur Chapter, and Past Chairman, CSI Jaipur Chapter. Having Teaching Experience of 22+ Years, Former Professor - CSE and & Director – Out Reach, JECRC, Jaipur, 5 Patents published, 20 PhD Supervised, published 94 Research Papers and 10 Books, Edited 12+ Conference Proceedings with Scopus/SCI indexing and associated as Editor & Reviewer in some reputed Journals, Received 20+ National and International Awards of Repute. His core research areas include Internet Security, Cloud Computing, Big Data, and IoT. He has organized and participated 25+ National & International Conferences of repute.

Dr. Bala Subramanian Raman has been a Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology Roorkee since December 2018 and has been heading the Department since July 2024. Since June 2021, he has been a Joint Faculty in the Mehta Family School of Data Science and Artificial Intelligence at IIT Roorkee. In addition, he has held the iHUB Divyasampark Chair Professor at the Technology Innovation Hub, a joint initiative of the DST, Government of India, and IIT Roorkee, since May 2022. Previously, he served as an Associate Professor in the Department of Computer Science and Engineering from September 2013 to December 2018. Before that, he was with the Department of Mathematics at IIT Roorkee from September 2004 to September 2013, where he served as an Associate Professor and Head of the Computer Vision, Graphics, and Image Processing Laboratory. He was a Guest Professor/Visiting Researcher at the Institute for Document Analysis Knowledge Science (IDAKS) at Osaka Metropolitan University (Formerly Osaka Prefecture University), Osaka, Japan, a position he has held from February 2020 to March 2024.

Swietlana Kashuba is a specialist in engineering and technical sciences, specializing in technical informatics and telecommunications. She is a graduate in Computer Management and Automation Systems, holds a Ph.D. in technical sciences in the field of information technologies, and serves as a professor at WSG University (Poland) and an Honorary Professor at Kharkiv National University of Radio Electronics (Ukraine). Swietlana Kashuba's academic portfolio includes 111 publications, comprising 60 scientific works and 51 methodological papers. Her research interests focus on artificial intelligence, mathematical modeling, and data analysis, particularly in the context of technical and economic applications.

Inhalt

Innovative methods for contact identification of fragments in a patient's body based on machine learning.- Detection of Node Replication Attacks Using Clustering and Ensemble Methods in WSN.- The J-Curve of Productivity: Measuring the True Impact of Digital Business Assets and Financial Technologies on Economic Growth.- The Blockchain Management in Monetary Policy: Measuring Impacts on GDP and Money Supply Structure.- A Machine Learning Approach for Enhancing HPC User's Job Efficiency through Look Before Execution Method.- LiDAR-to-Brain Interface: A Novel Approach Model for Converting LiDAR Data into Neural-Compatible Electrical Signals for Brain Implants.- Android Ransomware Detection Application Using Deep Learning.- Comparative Analysis of Machine Learning Models for Predicting Patient Survival in Echocardiography Procedures.- Deep Learning Based Feature Identification for Ocular Disease Detection Using Vgg16 Model.- Plant Leaf Disease Detection with Deep Learning Techniques: A Review with a Focus on Transformers and Explainable AI.- Evaluating Deep Learning Architectures for Sports Image Classification.- Enhanced Predictive Analysis of Brain Tumor Survival Using Multimodal Data Integration.- Improving the efficiency of sentiment analysis system based on integration with Robotic Process Automation and Knowledge-based System.- Integrating Text and Visual Features for Robust Document Classification: A Machine Learning Approach.- Translating the Art of Poetry: A Comparative Study of Advanced Translation Models.