Data Science, AI and Applications: First International Conference, ICDSAIA 2025, Dhaka, Bangladesh, July 18–19, 2025, Proceedings, Part III(2683 Communications in Computer and Information Science)

The three-volume set CCIS 2681-2683 constitutes the post-conference proceedings of the First International Conference on Data Science, Artificial Intelligence and Applications, ICDSAIA 2025, held in Dhaka, Bangladesh, during July 18-19, 2025. The 99 full papers included in this book were carefully reviewed and selected from 190 submissions. They focus on latest advancements in data science, artificial intelligence (AI), and their applications across diverse sectors--including healthcare, education, finance, governance, agriculture, and sustainable development--highlighting its potential to solve pressing societal challenges and accelerate progress toward the Sustainable Development Goals (SDGs).

Table of Contents:
Part-vol-I. Part-vol-II. Part-vol-III. .- Network-Based Approaches and Gene Expression  Profiling to Identify the Molecular Mechanism of Stomach Cancer. .- Smart Urban Farming: Integrating AI and IoT with Renewable Energy in Vertical Farming. .- Comparative Analysis of Classification and Regression Models for Schizophrenia Risk Prediction. .- A Review for Bridging Clinical and Technical Gaps with Hybrid-ML in Schizophrenia Diagnosis. .- Adaptive Aggregated Federated Learning for Real-Time Intrusion Detection in Edge Computing. .- An Intelligent Bin with Sensor Integration and Ensemble Machine Learning-Based Fill Prediction. .- Optical Character Recognition for Dari Language in Afghanistan. .- Detecting AI-Generated Text Using Machine Learning: A Comparative Study of MLP and RoBERTa-Based Models. .- Vision Guard: Computer Vision-Based Door Detection and Navigation Assistance for the Visually Impaired. .- IoT Enabled Pest Detection and Disease Management System for Agriculture 4.0. .- Design and Implementation of an AI-Powered Outcome-Based Education (OBE) Management System. .- Fake Review Detection in Low-Resource Settings with Multilingual Transformer Models: The Case of Bangla. .- SimBlock-PoS: Enhancing SimBlock to Evaluate Stake-Based and Work-Based Blockchain Consensus Mechanisms. .- Improving Missing Data Imputation with GF-WAI: An Explainable AI-Based Ensemble Method for Dengue Disease Prediction. .- Logistic Regression-based Machine Learning Model for Early Alzheimer’s Detection Using the OASIS Dataset. .- A Deep Learning-Based Framework for Bangla Vehicle License Plate Detection and Recognition. .- Harnessing AI for Early Detection of Tomato Leaf Diseases: A Machine Learning Perspective. .- RoadNet: A Deep Learning Framework for Road Extraction from Remote Sensing Data. .- Explainable Machine Learning for Fall Detection and Alert System: A Cloud-Integrated Approach Using Smartphone Sensors. .- Malicious Domain Detection with  Deep Learning and Bayesian Optimization Approaches. .- Ecological Overshoot: The Blindspot of Sustainable Computing. .- Plant Disease Classification by Ensemble Metaheuristic-Deep Learning Approach. .- Analysing and Predicting Housing Affordability Trends in the UK Using Machine Learning. .- An End-to-End Aspect-Based Sentiment Analysis Framework for a Real-Time Personalized Product Recommendation System.  .- A Lightweight Transformer-Based Encoder-Decoder Model for Video Summarization. .- A Multi-Agent RAG system for Legal Information Retrieval in Bangladesh. .- Data-Efficient Image Transmission and Enhancement for UAVs: A Color Quantization and Super-Resolution Approach. .- An Evaluation of Advanced Neural Network and Machine Learning Models for Sentiment Analysis on Product Reviews. .- Harnessing Machine Learning to Analyze Passenger Sentiments in the Bangladesh Railway System. .- Investigating the VR rollercoaster experience by applying AI models to biometric data. .- Assessing Electronic Customer Relationship Management Readiness in Banks. .- A Comparative Analysis of State-of-the-Art Speech-to-Text models for court applications. .- The Key Determinants of Road Accidents: A  Machine Learning Analysis.