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

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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

  • 言語:ENG
  • ISBN:9789819688883
  • eISBN:9789819688890

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Description

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.

Table 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.

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