Advances in Soft Computing

Name: Advances in Soft Computing | 22nd Mexican International Conference on Artificial Intelligence, MICAI 2023, Yucatán, Mexico, November 13-18, 2023, Proceedings, Part II
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22nd Mexican International Conference on Artificial Intelligence, MICAI 2023, Yucatán, Mexico, November 13-18, 2023, Proceedings, Part II

Hiram Calvo Lourdes Martínez-Villaseñor Hiram Ponce(Editor)

Springer (Publisher)

Published on 8. November 2023

XIX, 333 pages

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978-3-031-47640-2 (ISBN)

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Content

Intro
Preface
Organization
Contents - Part II
Contents - Part I
Natural Language Processing
Visualizing the Cosmos: A Novel Method for Text Recombination with Space News
1 Introduction
2 Dataset
3 Data Recombination Method
4 Experiments
5 Evaluation and Results
6 Conclusion
References
Propitter: A Twitter Corpus for Computational Propaganda Detection
1 Introduction
2 Related Work
3 The Construction of Propitter
3.1 Construction Methodology
3.2 Propitter Statistics
4 Experiments and Results
4.1 Baseline Results
4.2 On the Challenges of Propitter
5 Conclusions
References
Data Mining and Analysis of NLP Methods in Students Evaluation of Teaching
1 Introduction
2 Related Work
3 Methodology
3.1 Data Sampling and Participants
4 Results
4.1 Data Exploration
4.2 Results with TF-IDF Vectors
5 Discussion and Conclusion
References
Data Imputation with Adversarial Neural Networks for Causal Discovery from Subsampled Time Series
1 Introduction
2 Background
2.1 Causal Graphical Models for Time Series
2.2 Subsampling in Time Series
3 Related Work
3.1 PCMCI Algorithm
3.2 Deep Learning in Causal Discovery
3.3 Causal Discovery in Subsampled Time Series
4 Data Imputation for Causal Discovery of Time Series
4.1 Representation and Assumptions
4.2 Data Imputation
4.3 Generative Adversarial Model Architecture
4.4 Causal Structure Learning
5 Experimental Results
5.1 Experimental Setup
5.2 Experiment 1: Subsampled Time Series with the Same Noise Distributions
5.3 Experiments 2-5: Subsampled Time Series with Different Noise Distributions and Time Steps
5.4 Discussion
6 Conclusions and Future Work
References
Exploring the Challenges and Limitations of Unsupervised Machine Learning Approaches in Legal Concepts Discovery
1 Introduction
2 Theoretical Framework
3 Methodology
3.1 Data Source
3.2 Data Preprocessing
3.3 Topic Modelling Approach
3.4 Word Embedding Approach
3.5 Clusters Appraisal
4 Results and Discussion
5 Conclusion and Future Work
References
Large Sentiment Dictionary of Russian Words
1 Introduction
2 Related Works
3 Data and Method
4 Results
5 Discussion
6 Conclusion
References
An Interpretable Authorship Attribution Algorithm Based on Distance-Related Characterizations of Tokens
1 Introduction
2 State-of-the-Art
3 A Novel Embedding
4 Results
5 Conclusions and Discussion
References
Comparing Transformer-Based Machine Translation Models for Low-Resource Languages of Colombia and Mexico
1 Introduction
2 Indigenous Languages in this Research
3 Methodology
3.1 The Datasets Creation
3.2 Experimentation Setting
4 Results
4.1 Analysis of Results
5 Related Works
6 Conclusion
6.1 Future Work
References
Disaster Tweets: Analysis from the Metaphor Perspective and Classification Using LLM's
1 Introduction
2 Context and Motivation
2.1 Conceptual Metaphor
2.2 Large Language Models
3 State of the Art
4 Data Analysis
4.1 Dataset
4.2 Preprocessing
5 Models
5.1 BERT
5.2 RoBERTa
5.3 DistilBert
6 Results
7 Conclusion and Future Work
References
LLM's for Spanish Song Text Analysis and Classification Using Language Variants
1 Introduction
2 Motivation and Theoretical Concepts
2.1 Large Language Models
3 State of the Art
4 Datasets
5 Solution Proposal
5.1 Preprocessing
5.2 Classification
5.3 BERT-Base-Cased
5.4 RoBERTa-Base
5.5 DistilBERT-Base-Multilingual-Cased
6 Results
7 Conclusions and Future Work
References
Bioinformatics and Medical Applications
Boosting Kidney Stone Identification in Endoscopic Images Using Two-Step Transfer Learning*-1pc
1 Introduction
2 Materials and Methods
2.1 Datasets
2.2 Two-Step Transfer Learning
3 Results and Discussion
3.1 Two Step TL-Approach Results
3.2 Comparison with the State-of-the-art
4 Conclusion and Perspective
References
Automatic Assessment of Canine Trainability Using Heart Rate Responses to Positive and Negative Emotional Stimuli
1 Introduction
2 Methodology
2.1 Development of the Protocol for Dataset Generation
2.2 Experimental Procedure
2.3 Ethical Considerations
2.4 Obtained Dataset
3 Results
4 Discussion
5 Conclusions
References
LSTM-Based Infected Mosquitos Detection Using Wingbeat Sound
1 Introduction
2 Acoustic Chamber Design and Database Construction
2.1 Recording Condition and Dataset Construction
2.2 Proposed LSTM-Based Scheme
3 Experimental Results
4 Conclusions
References
FAU-Net: An Attention U-Net Extension with Feature Pyramid Attention for Prostate Cancer Segmentation
1 Introduction
2 State-of-the-Art
3 Materials and Methods
3.1 Dataset
3.2 Feature Pyramid Attention
3.3 Proposed Work
4 Results and Discussion
4.1 Quantitative Results
4.2 Qualitative Results
5 Conclusion
References
Implementation of a Digital Electromyographic Signal Processor Synthesized on an FPGA Development Board for Biocontrol Systems
1 Introduction
2 Related Work
3 Methods and Materials
3.1 Analog Signal Conditioning
3.2 Analog to Digital Conversion
3.3 Digital Filter
3.4 Signal Segmentation and Characteristic Extraction
3.5 Characteristic Classification
3.6 Module Integration and Implementation
4 Results and Analysis
5 Conclusions and Future Work
References
BEC-1D: Biosignal-Based Emotions Classification with 1D ConvNet
1 Introduction
2 Related Works
2.1 Facial Gestures
2.2 EEG Signals
2.3 ECG Signals
2.4 GSR Signals and Multi-modal Emotion Recognition
3 Materials and Methods
3.1 Young Adult's Affective Data Dataset
3.2 1-D Convolutional Neural Networks
3.3 Performance Metrics
4 Proposal
4.1 Signal Preprocessing
5 Results
5.1 Validation Methods and Evaluation
5.2 Classification Results
6 Conclusions
References
Feature Selection and Classification for Searching Light at Night Exposure and Students' Weight Relationship
1 Introduction
2 Related Work
3 Data Description
4 Experiments
4.1 Experiments Design
4.2 Configuration Details of Experiments
5 Experiments Results
5.1 Results of Experiment 1
5.2 Results of Experiment 2
6 Conclusions and Future Work
References
PumaMedNet-CXR: An Explainable Generative Artificial Intelligence for the Analysis and Classification of Chest X-Ray Images
1 Introduction
2 Methodology
2.1 Model Architecture
3 Results
3.1 Latent Space Interpolation
3.2 Transfer Learning
3.3 Explainability
4 Summary and Conclusions
References
Robotics and Applications
Visual Navigation Algorithms for Mobile Manipulators in Service Shops
1 Introduction
2 Industrial Challenge
3 The Problem Formulation
4 Development
4.1 Navigation
4.2 Vision
4.3 Object Manipulation
5 Results
6 Conclusion
References
NATLOC: Natural Language Object Localization
1 Introduction
2 Theory and Research
2.1 Image Generation
2.2 Image Matching Model
2.3 Reinforcement Learning
2.4 Differential Robot
3 Methodology
4 Results
4.1 Agent Training Results
5 Discussion
6 Conclusion
References
Backup Solutions for the Refueling Problem in Foreign Transportation: A Case Study in Mexico
1 Introduction
1.1 Importance of Fuel
2 Transportation Model
2.1 Problem Statement
2.2 Mathematical Model
2.3 Example
3 Genetic Algorithm
3.1 Proposal
3.2 Additional Mutation
4 Numerical Results
5 Conclusion and Future Work
References
Self-location Algorithm for the Strategic Movement of Humanoid Robots
1 Introduction
2 Antecedents
3 Methods and Materials
3.1 Instruments
3.2 Process
4 Results
4.1 Execution Times
4.2 Confusion Matrix and ROC Curves
4.3 Performance Evaluation
5 Conclusions
6 Discussion
A Additional Tables
References
Learning Neural Radiance Fields of Forest Structure for Scalable and Fine Monitoring
1 Introduction
2 Background
2.1 Neural Radiance Fields
3 Are Neural Fields Capable of Extracting 3D Structure in Forestry?
3.1 Terrestrial Imagery
4 Neural Radiance Fields: A Framework for Remote Sensing Fusion in Forestry
4.1 Filing in the Missing Below-Canopy Structure in ALS Data with TLS
4.2 Aerial Imagery
5 Prediction of Forest Factor Metrics
6 Conclusion
References
Edge AI-Based Vein Detector for Efficient Venipuncture in the Antecubital Fossa
1 Introduction
2 Literature Review
2.1 Image Acquisition Approaches
2.2 Computer-Based Vein Distribution Localization
2.3 Edge AI Methods
3 Material and Methods
3.1 Forearm Vein Segmentation
3.2 Cubital Fossa Localization
3.3 Hardware Development
4 Experimental Results
4.1 Forearm Vein Segmentation
4.2 Antecubital Fossa Localization
5 Conclusions and Future Work
References
Varroa Mite Detection in Honey Bees with Artificial Vision
1 Introduction
2 Related Works
3 Research Context
3.1 Bee Hive
3.2 The Electrical Power Supply System
3.3 Communication System
3.4 Data Processing Center
3.5 Software System
4 Experiments
4.1 Recognition of the Bees in the Image
4.2 Recognition of the Bees in the Image with the Varroa Mite
5 Conclusions
6 Future Works
References
Author Index

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Advances in Soft Computing

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