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E-raamat: Progress in Artificial Intelligence: 23rd EPIA Conference on Artificial Intelligence, EPIA 2024, Viana do Castelo, Portugal, September 3-6, 2024, Proceedings, Part III

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Progress in Artificial Intelligence: 23rd EPIA Conference on Artificial Intelligence, EPIA 2024, Viana do Castelo, Portugal, September 3-6, 2024, Proceedings, Part IIISuurem pilt
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The 3-volume set LNAI 14967, 14968, and 14969 constitutes the proceedings of the 23rd EPIA Conference on Artificial Intelligence, EPIA 2024, held in Viana do Castelo, Portugal, during September 36, 2024.





The 94 full papers presented in these proceedings were carefully reviewed and selected from 187 submissions. The papers are organized in the following topical sections:





Volume I:





AI and Creativity (AIC); Ambient Intelligence and Affective Environments (AmIA); Artificial Intelligence and IoT in Agriculture (AIoTA); Artificial Intelligence and Law (AIL); and Artificial Intelligence for Industry and Societies (AI4IS). 





Volume II:





Artificial Intelligence in Medicine (AIM); Artificial Intelligence in Power and Energy Systems (AIPES); Artificial Intelligence in Transportation Systems (AITS); Ethics and Responsibility in AI (ERAI); and General AI (GAI).





Volume III:





Generative AI Foundations and Applications (GenAI); Intelligent Robotics (IROBOT); Knowledge Discovery and Business Intelligence (KDBI); Natural Language Processing, Text Mining and Applications (TeMA); and Data-Centric AI Solutions and Emerging Technologies (DCenAI).
Generative AI Foundations and Applications (GenAI).- Large Language
Model for Querying Databases in Portuguese.- A Novel Integration of Federated
Learning and LSTM for Synthetic Time Series Generation.- Assessment on the
Effectiveness of GitHub Copilot as a Code Assistance Tool: An Empirical
Study.- AICIS: A System for Identifying AI Contribution in Textual
Content.- Intelligent Robotics (IROBOT).- AIMSM - A Mechanism to Optimize
Systems with Multiple AI Models: A Case Study in Computer Vision for
Autonomous Mobile Robots.- Defect Detection in the Painting of Combustion
Device Covers using the Deflectometry Method and
YOLOv8.- Information-Oriented and Energy-Aware Path Planning for Small
Unmanned Aerial Vehicles.- Pollinationbots - A Swarm Robotic System for Tree
Pollination.- Knowledge Discovery and Business Intelligence
(KDBI).- Extensible Data Ingestion System for Industry 4.0.- Next Location
Prediction with Time-Evolving Markov Models over Data Streams.- Improving
Fraud Detection with 1D-Convolutional Spiking Neural Networks through
Bayesian Optimization.- A Benchmark of Automated Multivariate Time Series
Forecasting Tools for Smart Cities.- A Data Drift Approach to Update Deployed
Energy Prediction Machine Learning Models.- Optimising Dialogue Flow
Discovery.- BI-Enabled Web Visualization of In-Place Inclinometer Data for
Geotechnical Applications.- An Empirical Evaluation of DeepAR for Univariate
Time Series Forecasting.- Natural Language Processing, Text Mining and
Applications (TeMA).- Meta-prompting Optimized Retrieval-augmented
Generation.- Pseudo-Semantic Graphs for Generating
Paraphrases.- Compositionality and Ambiguity in Multiword Expressions: A
Dataset for the Evaluation of Language Models in Galician.- Bypassing the
Nuances of Portuguese Covert Hate Speech through Contextual
Analysis.- Sequence Labeling for Pun Location and Detection in
Portuguese.- Open Sentence Embeddings for Portuguese with the Serafim PT*
Encoders Family.- WordNet Expansion with Bilingual Word Embeddings and Neural
Machine Translation.- A Galician-Portuguese Generative Model.-Assessing the
Trustworthiness of Large Language Models on Domain-specific
Questions.- Data-Centric AI Solutions and Emerging Technologies
(DCenAI).- Lag Selection for Univariate Time Series Forecasting using Deep
Learning: An Empirical Study.-Chatbot Decision Support with Intent-Rich
Structures in the Hospitality Industry.- Meta TadGAN: Time Series Anomaly
Detection Using TADGAN with Meta-Features.- Context-aware Deep Forecasting:
Principles for the Nation-wide Management of Blood Products.
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