Database and Expert Systems Applications - DEXA 2025 Workshops: AISys and AI4IP, Bangkok, Thailand, August...

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Lukas Fischer Ulrich Göhner

Database and Expert Systems Applications - DEXA 2025 Workshops

AISys and AI4IP, Bangkok, Thailand, August 25–27, 2025, Proceedings

Lukas Fischer, Ulrich Göhner, Sebnem Gül-Ficici , Dirk Jacob

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English

Springer Nature Switzerland AG
19 August 2025

Information theory; Algorithms & data structures; Databases; Data mining; Expert & knowledge-based systems

Series: Communications in Computer and Information Science

This volume constitutes the refereed proceedings of the 7th International Workshop on AI System Engineering: Math, Modelling and Software, AISys 2025 and the First International Workshop on Optimisation of Industrial Production with AI Algorithms, AI4IP, co-located with the 36th International Conference on Database and Expert Systems Applications, DEXA 2025, which took place in Bangkok, Thailand, during August 25-27, 2025. The 11 full papers were thoroughly reviewed and selected from a total of 23 submissions. They are organized in topical sections as follows: AI System Engineering: Math, Modelling and Software; and Optimization of Industrial Production with AI Algorithms.

Edited by: Lukas Fischer, Ulrich Göhner, Sebnem Gül-Ficici, Dirk Jacob, Gabriele Kotsis
Imprint: Springer Nature Switzerland AG
Country of Publication: Switzerland
Dimensions: Height: 235mm, Width: 155mm,
ISBN: 9783032020024
ISBN 10: 3032020026
Series: Communications in Computer and Information Science
Pages: 116
Publication Date: 19 August 2025
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

.- AI System Engineering: Math, Modelling and Software. .- Exploring the benefits of iterative retrieval-augmented generation for risk mitiga tion in LLM response. .- TrustAI: Designing and Implementing a Trustworthy and User-Centered AI Plat form. .- Collaborative Trustworthy Foundation Model Framework: An Environmental Sustainability Use-Case to Detect Contamination Objects in Organic Waste Streams. .- Optimisation of Industrial Production with AI Algorithms. .- Efficient Federated Learning Integration into Existing MLOps Pipelines via Centralized Model Management. .- Deep Photometric Stereo for Tool Wear Inspection. .- Multi-Objective Reinforcement Learning for Energy-Efficient Industrial Control. .- Deep learning-based defect detection in laser powder bed fusion. .- Prediction of CNC Manufacturing Time Under Real-World Conditions Using Graph Convolutional Networks. .- A Vision-Guided Approach to Pick-and-Place Robotics: From Assembly Drawings to Industrial Assembly Automation. .- Towards Real-time Tool Wear Detection on Edge Devices: A Lightweight Di mensionality Reduction Approach for Spindle Integrated Cutting Force Sensor Data. .- Energy Optimized Piecewise Polynomial Approximation Utilizing Modern Ma chine Learning Optimizers.