Advances in Computational Intelligence. MICAI 2024 International Workshops

This book constitutes the revised selected papers of several workshops which were held in conjunction with the MICAI 2024 International Workshops on Advances in Computational Intelligence, MICAI 2024, held in Tonantzintla, Mexico, during October 2125, 2024.

The 38 revised full papers presented in this book were carefully reviewed and selected from 58 submissions.

The papers presented in this volume stem from the following workshops:

17th Workshop of Hybrid Intelligent Systems (HIS 2024)

17th Workshop on Intelligent Learning Environments (WILE 2024)

6th Workshop on New Trends in Computational Intelligence and Applications (CIAPP 2024).

Inhalt

.- WILE 2024 .

.- Expert System for Teaching Classification Systems Workflow.

.- Enhancing Student Theses with Advanced Text Analysis Using NLP and Pre-Trained Models.

.- Competence-Based Student Modelling with Dynamic Bayesian Networks.

.- XploRe: XR tool for learning about the Solar System and its physical phenomena.

.- Emotion Recognition in Virtual Reality Learning Environments: A Multimodal Machine Learning Approach.

.- Enhancing Dropout Prediction Models Through Feature Selection Techniques.

.- Assessing Cognitive Load in Programming Exercises Based on Readability and Lexical Richness.

.- CIAPP 2024 .

.- Air Pollution, Socioeconomic Status, and Avoidable Hospitalizations in Mexico City: A Multifaceted Analysis.

.- Automatic Detection of Abnormal Pedestrian Flows, Using Classification and Tracking with Pre-Trained YOLOv8.

.- Computational time reduction in the induction of Convolutional Decision Trees.

.- Bean landraces color identification through image analysis and Gaussian Mixture Model.

.- Efficient Neural Architecture Search: Computational Cost Reduction Mechanisms in DeepGA.

.- Prediction of epileptic seizure using neuroevolved spiking neural network.

.- Identification of simple geometric figures using Matlab and ROS.

.- Experimental Study for Automatic Feature Construction to Segment Images of Lungs Aected by COVID-19 Using Genetic Programming.

.- Color quantification in common bean landraces using a supervised learning technique.

.- Explainable AI through Decision Trees for black-box models used to support Bacterial Vaginosis Diagnosis.

.- Improving lactation curve estimation in sheep: A comparative analysis of machine learning algorithms across multiple measurement systems.