Advances and Trends in Artificial Intelligence. Theory and Applications - 38th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2025, Kitakyushu, Japan, July 1-4, 2025, Proceedings, Part I

This book constitutes the refereed proceedings of the 38th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems on Advances and Trends in Artificial Intelligence, IEA/AIE 2025, held in Kitakyushu, Japan, in July 1 4, 2025.
The 80 full papers and 9 short papers included in this book were carefully reviewed and selected from 130 submissions. They focus on the following topical sections:
Part I: Reinforcement Learning; Optimization; Natural Language Processing; Multi-Agent; Machine Learning and Decision Making; Knowledge Representation; Data Engineering; Large Language Model; Computer Vision.

Part II: Robotics; Education; Cyber Security; Healthcare and Medical Applications; Advanced Applied Intelligence Methodologies and Applications; Intelligent Systems and e-Applications; Industrial and Engineering Applications.

List of contents

.- Reinforcement Learning.
.- An Enhanced Preference-Based Reinforcement Learning Framework for Autonomous System.
.- Reinforcement Learning based Iterated Greedy for Parallel Machine Scheduling with Weighted Earliness Tardiness.
.- VMD-IMF Enhanced Hyper Graph Attention Module Based Reinforcement Learning For Portfolio Optimization.
.- A reinforcement learning based framework to the facility layout problem.
.- Optimization.
.- Bayesian Optimization for Fine-Tuning an AI Solver: Application to Preventive Maintenance Scheduling Problems.
.- Domain Generalization through Domain-Expert Risk Assessment.
.- Enhanced Optimization Space Learning: Towards Real-Time Compiler Optimization.
.- Optimizing Feature Selection Binary Peacock Algorithm with improved movement strategy.
.- Natural Language Processing.
.- Apply TF-IDF and LDA to Explore Topics and Related Trends in Electric Vehicle Reviews.
.- Identifying Fake Reviews and Their Implications Using BERT and LDA: A Case Study of Online Shopping Website Reviews.
.- A Lightweight and Efficient Punctuation and Word Casing Prediction Model for On Device Streaming ASR.
.- SYNCAD: Synchronised Yields from Narrative Cross Modal Audio and Data.
.- MultiGAU: Real Time Sign Language Generation using Multimodal Gated Attention.
.- Classification of Approval Desires and Analysis of Emotional and Linguistic Features in SNS Posts Using Generative AI.
.- Multi-Agent.
.- Hierarchical Multi-Agent Reinforcement Learning with Epistemic Priors for Scalable Communicationless Coordination of Teamable Agents.
.- DynaMIX: Sample-Efficient Multi Agent Reinforcement Learning with Multi-Step Temporal Forward Dynamics Modeling.
.- Automated Issue Hierarchy Generation for Improved Automated Negotiation Outcomes.
.- Machine Learning and Decision Making.
.- Distribution Variance for Surrogate Weights in Multi-Criteria Decision Analysis.
.- Bridging the Trust Gap: Leveraging Explainable AI for Personalized E-Commerce Recommendations.
.- A clustering method based on hesitant difference granularity.
.- Evaluation of Efficient AI for the Edge: Insights from Deep Neural Networks Model Compression Techniques Applied to Occupancy Detection.
.- LSTM-based Proactive Scheduling of Stream Applications in Edge/Cloud Environments.
.- Uncertainty Quantification Of Multimodal Models.
.- Knowledge Representation.
.- Automating OntoClean Ontology Verification.
.- Automating OntoClean - Subsumption Hierarchy Construction.
.- Possibilistic Reasoning with Fuzzy Formal Contexts: An Extended Abstract.
.- A Strategy for Implementing Garbage Detection in Ontology Completion using Description Logics.
.- Data Engineering.
.- Uncertainty-based Instance-Dependent Noisy Label Datasets Generation.
.- Guided by Uncertainty: Semi-supervised Domain Adaptation with Curriculum and Contrastive Learning.
.- Linking Data Meaningfully: Identifying Meaningful Keys and Foreign Keys from Data.
.- CAMI: A missing value imputation method based on causal discovery and self-attention.
.- MDR: An Ontology Vocabulary and Registry Service for Dataset Catalogs.
.- A-REACT: Adaptive Resampling and Active Classification for Thresholded Anomalies.
.- DistResampleR-Lite: Light Distributed Resampler for Imbalanced Regression Problems.
.- Fast HSIC-based tests for random processes.
.- Large Language Model.
.- Exploring the Efficacy of Large Language Models in Predicting Chemical Toxicity.
.- Towards Predicting Complex Carpooling Trajectories with Context-Augmented BERT LLM in Chaotic Environments.
.- LLM-base MaSE, A Software Development Framework for Developing Multi-Agent Systems.
.- Computer Vision.
.- WeldViT: A Lightweight Network for Online Identification of Multi-Label Welding Defects.
.- Impact of Replay Ratios on Performance and Efficiency in Continual Learning for Skeleton-based Action Recognition.
.- Extending YOLO for Feature-Based Classification Through Numerical-to-Image Transformation.
.- Lost in the Noise: Evading and Detecting Backdoors in Conditional Diffusion Models.
. SkinPalNet: An Advanced Ensemble Model for Skin Cancer Diagnosis with Computer Vision Approach.
.- Enhancing Minimarket Customer Experience through YOLOv8-Powered Checkout Systems.
.- Brain Tumor MRI Interpretation: Towards a Benchmark for Medical Visual Question Answering.

Product details

• Assisted by: Moonis Ali (Editor), Moonis Ali et al (Editor), Hamido Fujita (Editor), Yinglin Wang (Editor), Yutaka Watanobe (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Release: 11.09.2025
• EAN: 9789819688883
• ISBN: 978-981-9688-88-3
• No. of pages: 507
• Dimensions: 155 mm x 30 mm x 235 mm
• Weight: 844 g
• Illustrations: XX, 507 p. 167 illus.
• Series: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > IT