Applied Computer Sciences in Engineering: 11th Workshop on Engineering Applications, WEA 2024, Barranquilla, Colombia, October 23–25, 2024, Proceedings, Part I

The two-volume set CCIS 2222 + 2223 constitutes the proceedings of the 11th Workshop on Engineering Applications, WEA 2024, which took place in Barranquilla, Colombia, during October 23–25, 2024. The 42 full papers presented here were carefully reviewed and selected from 97 submissions. The papers are organized in the following topical sections: Part I - Artificial Intelligence. Part II - Optimization; Simulation; Applications.

Table of Contents:
.- Artificial Intelligence. .- Zero-Shot Spam Email Classification Using Pre-trained Large Language Models. .- Automatic Recognition System for Public Transport Robberies Based on Deep Learning. .- Reinforcement Learning Model applied In A Pair Trading Strategy. .- Neural networks informed by physics applied to solving an optimal investment-consumption problem. .- Deep Learning-based object detection of relevant morphological traits for enhancing automatic classification of freshwater macroinvertebrates. .- Deep Tracking Portfolios using Autoencoders and Variational Autoencoders. .- On the use of a foundation acoustic model to identify highly relevant phonetic information of Parkinson’s speech. .- Improvement in the Management of Potable Water Distribution Using Data Science for the Detection and Correction of Errors in Operational Measurement Systems. .- Wrist Motion Pattern Recognition from EMG Signal Processing Using Machine Learning and Neural Networks. .- Skin Disease Pre-diagnosis with Novel Visual Transformers. .- Enhancing the Diagnostic Accuracy of Diabetes and Prediabetes with Neural Network-Based Area Under the Curve Analysis of OGTT Data. .- Improving Energy Management in Artificial Pancreas using an Event-trigger MPC Strategy. .- Advancements in AI-Driven Emotion Recognition: A Study on CNN and DMD Methodologies. .- Control of a buck converter using arti cial neural network NARMA-L2 controller. .- Design of a crime prediction model for Barranquilla using Machine Learning algorithms. .- A smart mobile mapping application for the evaluation of road infrastructure in urban and rural corridors. .- Analysis of variables related to criminal violence and public insecurity in the city of Barranquilla, Colombia, using crispy methodology and python programming language. .- Comparison of Motor Imagery and Motor Execution Networks Using the Phase Lag Index. .- Compare computer visions algorithms for estimate 6Dof cameras pose. .- Digital Twin framework proposal based uncertainty management models optimisation and interactive design. .- Data-driven Demand Localization for Effective Disaster Response.