Intelligent Systems : 34th Brazilian Conference, BRACIS 2024, Belém do Pará, Brazil, November 17-21, 2024, Proceedings, Part III (Lecture Notes in Computer Science)

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Intelligent Systems : 34th Brazilian Conference, BRACIS 2024, Belém do Pará, Brazil, November 17-21, 2024, Proceedings, Part III (Lecture Notes in Computer Science)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 470 p.
  • 言語 ENG
  • 商品コード 9783031790348

Full Description

The four-volume set LNAI 15412-15415 constitutes the refereed proceedings of the 34th Brazilian Conference on Intelligent Systems, BRACIS 2024, held in Belém do Pará, Brazil, during November 17-21, 2024.

The 116 full papers presented here were carefully reviewed and selected from 285 submissions. They were organized in three key tracks: 70 articles in the main track, showcasing cutting-edge AI methods and solid results; 10 articles in the AI for Social Good track, featuring innovative applications of AI for societal benefit using established methodologies; and 36 articles in other AI applications, presenting novel applications using established AI methods, naturally considering the ethical aspects of the application.

Contents

.- Other AI Applications.

.- A Case Study on Water Demand Forecasting in a Coastal Tourist City.

.- A Knowledge Engineering-Based Approach to Detect Gaming the System in Novice Programmers.

.- Acoustic Features and Autoencoders for Fault Detection in Rotating Machines: A Case Study.

.- Affective states in novice programmers: automatically detecting and analyzing the impact on learning.

.- An Analysis of Time-Frequency Consistency in Human Activity Recognition.

.- An Evaluation of Temporal Neighborhood Coding Variants in Smartphone-Based Human Activity Recognition.

.- AnisotropicBreast-ViT: Breast Cancer Classification in Ultrasound Images using Anisotropic Filtering and Vision Transformer.

.- Anomalies diagnostic in endoscopic images using Deep Learning Ensemble models.

.- Automated Segmentation of Computed Tomography Images for COVID-19 Patient Evaluation.

.- Combining clustering and genetic algorithms for portfolio optimization: a case study with B3 companies.

.- Comparative Analysis of Machine Learning Algorithms for Identifying Genetic Markers Linked to Alzheimer's Disease.

.- Comparing LIME and SHAP global explanations for Human Activity Recognition.

.- Damage Identification of Wind Turbine Blades.

.- Emotion Recognition in Instrumental Music Using AI.

.- Enhancing Multiobjective Genetic Algorithms for Pharmaceutical Batch Scheduling: A Study on Partitioned Selection with constraints and Mutation Greedy Local Search Strategy.

.- Evaluating Sentiment Quantification Methods in Brazilian Portuguese Corpora.

.- Evaluating Short Text Stream Clustering on Large E-commerce Datasets.

.- Evolutionary Adjustment of a Cellular Automata-based Model for Wildfire Spreading.

.- Exploring Score-based Ranking Fairness in Marketplace Environments through Simulation.

.- HAVANA: Hybrid Attentional Graph Convolutional Network Semantic Venue Annotation Model.

.- Impact of Pre-training Datasets on Human Activity Recognition with Contrastive Predictive Coding.

.- Improving Colorectal Cancer Diagnosis using MIRNet and InceptionV3 on Histopathological.

.- Integrating tensor-based data analytics and adaptive prediction for informed decision-making support.

.- Investigating Methods to Detect Off-Topic Essays.

.- Machine Learning and Time Series Analysis to Forecast Hotel Room Prices.

.- Modeling and Predicting Crimes in the City of S˜ao Paulo Using Graph Neural Networks.

.- Predicting Engagement of Brazilian Politicians on TikTok: A Machine Learning Approach.

.- Preserving Privacy and Enhancing Robustness: Federated Learning for Lung Disease Identification in Chest X-Ray Images.

.- RLPortfolio: Reinforcement Learning for Financial Portfolio Optimization.

.- Scaling and Adapting Large Language Models for Portuguese Open Information Extraction: A Comparative Study of Fine-Tuning and LoRA.

.- Special-Crowd-Distance boosted MESH applied to the operation of cascade hydro-power plants.

.- The Impact of Double Transfer Learning in VGG Architectures for Metastasis Breast Cancer Detection.

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