Artificial Intelligence Applications and Innovations 20th IFIP WG 12.5 International Conference, AIAI 2024, Corfu, Greece, June 27–30, 2024, Proceedings, Part III

This book constitutes the refereed proceedings of the 20th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2024, held in Corfu, Greece, during June 27–30, 2024.

The 100 full papers and 8 short papers included in this book were carefully reviewed and selected from 213 submissions. The diverse nature of papers presented demonstrates the vitality of AI algorithms and approaches. It certainly proves the very wide range of AI applications as well.

.- A comparison of AI methods for Groundwater Level Prediction in Burkina Faso.
.- A Deep Learning-Based Framework for Racket Sports Court Registration.
.- Beyond Sentiment in Stock Price Prediction: Integrating News Sentiment and Investor Attention with Temporal Fusion     Transformer.
.- Cross-Relational Reasoning for Neural Tensor Networks.
.- C-XGBoost: A tree boosting model for causal effect estimation.
.- FCGAN: Spectral Convolutions via FFT for Channel-Wide Receptive Field in Generative Adversarial Networks.
.- Forecasting Longitudinal Acceleration in Urban Vehicles.
.- Lip Recognition Based on Bi-GRU with Multi-Head Self-Attention.
.- Multivariate Time-Series Methods with Uncertainty Estimation for Correcting Physics-Based Model: Comparisons and   Generalization for Industrial Drilling Process.
.- Towards robust Road Quality Detection using different Detection Models.
.- Towards Semantically Conscious, Conversation-based Chatbot Services for Migrants.
.- Using Boosting and Neural Networks Methods to Detect Healthcare Fraud.
.- Artificial Intelligence Modeling of the Efficiency of a Biological Treatment Installation.
.- Carbon-Aware Machine Learning: A case study on cellular traffic forecasting with Spiking Neural Networks.
.- Emerging research topics identification using Temporal Graph Neural Networks.
.- Explanations for Core Decomposition.
.- Graph Neural Networks In PyTorch For Link Prediction In Industry 4.0 Process Graphs.
.- Knowledge Graph Completion using Structural and Textual Embeddings.
.- Lightweight Inference by Neural Network Pruning: Accuracy, Time and Comparison.
.- Multi-Adaptive Neural Modelling of the Interplay of Changing Organisational Contexts, Epigenetics, and Personality Traits in the Development of Burnout.
.- Parameterization of the Victor-Purpura distance for matching temporal neural activity patterns in real-time.
.- A Constraint-Based Greedy-Local-Global Search for the Warehouse Location Problem.
.- A Second-Order Adaptive Network Model for Political Opinion Dynamics.
.- An evaluation framework for synthetic data generation models.
.- Risk Assessment of COVID-19 Transmission on Cruise Ships Using Fuzzy Rules.
.- Statistical Modeling of Univariate Unimodal Data using ?-sigmoid Mixture Models.
.- Test Case Features as Hyper-heuristics for Inductive Programming.