Proceedings of International Conference on Computational Technologies for Research in Data Analytics
Description
This book discusses the outcomes of International Conference on Computational Technologies for Research in Data Analytics (ICCTRDA-2025) was held on November 21-22, 2025, at DuyTan University, Da Nang, Vietnam. The conference has attracted many high-quality submissions and stimulated the cutting-edge research discussions among many academic pioneering researchers, scientists, industrial engineers, students with the reception of more than 1200 papers from different parts of the world. Only 180 papers have been accepted and registered with an acceptance ratio of 15% to be published in four volumes of prestigious springer Lecture Notes on Networks and Systems (LNNS) series.
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Persons
Dr. Nhu Gia Nguyen received a Ph.D. degree in computer science from Ha Noi University of Science at Vietnam National University, Vietnam. Currently, he is Dean of the Graduate School at Duy Tan University, Vietnam. He has a total academic teaching experience of 18 years with more than 50 publications in reputed international conferences, journals, and online book chapter contributions (indexed by: SCI, SCIE, SSCI, Scopus, DBLP). His areas of research include: network communication, security and vulnerability, network performance analysis and simulation, cloud computing, image processing in biomedical. Presently he is Associate Editor of the International Journal of Synthetic Emotions (IJSE).
Prof. Ajay Jaiswal has an academic background from prestigious institutions like IIT Roorkee and JNU. With over 25 years of experience in academics, research, and administration, he currently serves as Principal of the School of Open Learning, University of Delhi. Additionally, he holds the position of OSD at the Institute of Cyber Security Law, University of Delhi. A prolific author and researcher, Prof. Jaiswal has contributed to numerous research articles and books and has been actively involved in editorial and organizing committees for journals and international conferences. His research interests include pattern recognition, image processing, and machine learning. He was honored as the "Best Teacher" by the Government of NCT Delhi for 2013-14.
Dr. Ta Minh Thanh received the Bachelor of Engineering degree and the Master degree of Computer Science from National Defence Academy, Japan, in 2005 and 2008, respectively. He was Lecturer of Le Quy Don University, Ha Noi, Viet Nam, from 2005. In 2015, he received the Ph.D. degree in computer science from Tokyo Institute of Technology, Tokyo, Japan. He received the standards of associate professor title in 2019. His research interests lie in the area of watermarking, network security, and computer.
Content
An Adaptive Decision Support for Hyper-local Crop Recommendation with Integration of Remote Sensing Sensory Technology.- The Role of GAN-Based Techniques in Fake Audio Detection: A Machine Learning Comparison.- Automated Generation and Quality Assessment Analysis of Achang Ethnic Group Brocade Patterns Based on Intelligent Recognition.- Depression Detection in Speech using Wav2Vec 2.0 Feature Extraction.- Evaluating Speech Synthesis Techniques for Medical Image Captions using LLMs and GANS.- Assessment of Professional Success and Job Satisfaction through Cloud-based Method.- Gesture Recognition for Remote Control Systems Using Kernel Principal Component Analysis (KPCA) and Trajectory Normalization.- Denial-of-Service in Quantum based Key Exchange over Classical Network Protocols.- Design and Application of a Cable Overheating Fault Early Warning System Based on a Gas Sensor Array.- Anticipatory Autonomic Management of Poly-Cloud Environments: A Machine Intelligence Paradigm.- Causal Explainable AI Using Quantum Inspired Embeddings for Financial Risk Modeling.- Flooding Cyberattacks in Cloud Computing-based SDN: Emerging Trends, Detection, and Mitigation.- Prediction Algorithm for Consumer Immersive Behavior in AI Virtual Shopping Scenarios.- Evaluating the Performance of Electron Magnetic Lenses by Using FEMM Simulation.- Understanding Driver Behavior Through Machine Learning Analysis of In-Vehicle Coupon Recommendation Data.