Computational Collective Intelligence: 15th International Conference, ICCCI 2023, Budapest, Hungary, September 27–29, 2023, Proceedings (Lecture Notes in Computer Science, 14162)

Preface
Organization
Contents
Collective Intelligence and Collective Decision-Making
Hybrid Genetic Algorithms to Determine 2-Optimality Consensus for a Collective of Ordered Partitions
	1 Introduction
	2 Related Works
	3 Ordered Partitions
	4 Proposed Approaches
	5 Simulations and Evaluation
		5.1 Consensus Quality
		5.2 Running Time
	6 Conclusions
	References
From Fragmented Data to Collective Intelligence: A Data Fabric Approach for University Knowledge Management
	1 Introduction
	2 Background and Related Works
	3 Proposed Method: vDFKM Platform
		3.1 Overview
		3.2 Data Fabric-Based Knowledge Management Architecture
		3.3 Knowledge Modelling Based on Metadata and Knowledge Graph
		3.4 Data Sources
		3.5 KM Coordinator
		3.6 Runtime and Data Infrastructure
		3.7 KM-Based Apps
	4 Evaluation and Discussion
		4.1 Context of KM at VNU
		4.2 Deployment Model of vDFKM
		4.3 Results and Discussion
	5 Conclusions
	References
An Architecture for Enabling Collective Intelligence in IoT Networks
	1 Introduction
	2 Literature Review
	3 An Architecture for Collective Intelligence
		3.1 System Architecture
		3.2 AI Information Signaling and AI Layer
		3.3 A Scalable, Private by Design Blockchain Architecture
		3.4 Zero Trust, Blacklisting, Trust Scoring and Anomaly Detection
		3.5 Threat Detection
	4 Security Analysis of the SENTIENCE Architecture
	5 Discussion About SENTIENCE Architecture
	6 Conclusions
	References
Self-Organizing Maps for Data Purchase Support in Data Marketplaces
	1 Introduction
	2 Background and Related Work
		2.1 Data Marketplaces
		2.2 Self-Organizing Maps
	3 Data Selection via SOM
	4 Experiment and Result
	5 Conclusion and Future Work
	References
Agent Based Model of Elementary School Group Learning – A Case Study
	1 Introduction
	2 Related Works
		2.1 Active Learning
		2.2 Three Phases of Learning
		2.3 Peers Tutoring
		2.4 Student’s Characteristic
	3 Proposed Group Model
	4 Simulation
	5 Conclusions
	References
Deep Learning Techniques
Deep Reinforcement Learning for Jointly Resource Allocation and Trajectory Planning in UAV-Assisted Networks
	1 Introduction
	2 Related Work
	3 An RL-Based Approach
	4 Simulation and Analysis
		4.1 Models Used in Simulation
		4.2 Simulation Results
	5 Conclusion
	References
DNGAE: Deep Neighborhood Graph Autoencoder for Robust Blind Hyperspectral Unmixing
	1 Introduction
	2 Related Works
	3 Proposed Method
		3.1 Neighborhood Graph Construction
		3.2 Deep Unmixing Using DNGAE
	4 Experimental Results
		4.1 HSI Data Description
		4.2 Hyperparameters Selection
		4.3 Compared Methods
		4.4 Unmixing Performances
	5 Conclusion
	References
Unlocking the Potential of Deep Learning and Filter Gabor for Facial Emotion Recognition
	1 Introduction
	2 Related Works
	3 Proposed Work
		3.1 Dataset
		3.2 Preprocessing
		3.3 Gabor Filter
		3.4 Hybrid (CNN-LSTM) Model
	4 Experiment Results
		4.1 Evaluation Metrics
		4.2 Results and Discussions
		4.3 Comparison to Other Methods
	5 Conclusion
	References
Graph Convolution Collaborative Filtering with Dense Embeddings
	1 Introduction
	2 Related Work
		2.1 Collaborative Filtering
		2.2 Model-Based CF Method
		2.3 Graph-Based CF Method
	3 Preliminaries
		3.1 Summary of Neural Graph Collaborative Filtering
		3.2 Evaluation of the NGCF ch9refspsngcf Model
	4 Proposed Method
		4.1 NGCF-Based Module
		4.2 Dense Module
		4.3 Model Prediction
	5 Experiments
		5.1 Experimental Settings
		5.2 Baselines
		5.3 Performance Comparison
	6 Conclusion
	References
Automatic Quantization of Convolutional Neural Networks Based on Enhanced Bare-Bones Particle Swarm Optimization for Chest X-Ray Image Classification
	1 Introduction
	2 Related Work
	3 Preliminaries
		3.1 Neural Network Quantization
		3.2 Bare-Bones Particle Swarm Optimization
	4 Proposed Method
		4.1 Integer Optimization Model
		4.2 BPSO Algorithm
	5 Experiments
		5.1 Experimental Implementation
		5.2 Results
	6 Discussion
	7 Conclusion
	References
A Convolutional Autoencoder Approach for Weakly Supervised Anomaly Video Detection
	1 Introduction
	2 Video Feature Extraction
	3 Proposed Method
		3.1 Convolutional Autoencoder Based Backbone
		3.2 The RTFM Module
	4 Experiment
		4.1 Dataset Description
		4.2 Evaluation Method
		4.3 Implementation Detail
		4.4 Result Analysis
	5 Conclusion and Perspectives
	References
Sparsity-Invariant Convolution for Forecasting Irregularly Sampled Time Series
	1 Introduction
	2 Related Work
	3 Our Approach
		3.1 Problem Formulation
		3.2 SiConv: Sparsity-Invariant Convolution
	4 Experimental Evaluation
		4.1 Experimental Settings
		4.2 Experiments on Datasets from Various Domains
		4.3 The Effect of Sparsity Level
		4.4 Experiments with Deep Convolutional Networks
	5 Conclusion and Outlook
	References
Efficient Sparse Networks from Watts-Strogatz Network Priors
	1 Introduction
	2 Background
		2.1 Network Pruning
		2.2 Using Network Priors to Generate Sparse ANNs
	3 Methods and Data
		3.1 Sparse Networks from Pruning
		3.2 Matching Full Networks and WS Priors
		3.3 Our Experiment
	4 Results
		4.1 Accuracy Comparison of Networks from Pruning vs Priors
		4.2 Structure of Sparse Networks
		4.3 Dependence of Accuracy on the Structure of Pruned Networks
	5 Conclusions
	References
Natural Language Processing
Exploring the Role of Monolingual Data in Cross-Attention Pre-training for Neural Machine Translation
	1 Introduction
	2 Methodology
		2.1 Cross-Lingual Language Embeddings
		2.2 Cross Connection Interface
		2.3 Pre-training Phase
		2.4 Fine-Tuning Phase
	3 Experiments and Results
		3.1 Setup
		3.2 Results
	4 Further Analysis
	5 Related Work
	6 Conclusion and Future Work
	References
Development of a Dictionary for Preschool Children with Weak Speech Skills Based on the Word2Vec Method
	1 Introduction
	2 Related Work
	3 Methodology
	4 Experiments and Results
	5 Conclusion and Future Work
	References
An Abstractive Automatic Summarization Approach Based on a Text Comprehension Model of Cognitive Psychology
	1 Introduction
		1.1 Automatic Text Summarization
		1.2 Objectives and Major Contributions
	2 Related Cognitive Psychology Research on Reading Comprehension
	3 CogSum: A New Cognitive Abstractive Summarizer
		3.1 The Construction Phase
		3.2 The Integration Phase
	4 Experimental Results
		4.1 Dataset
		4.2 Results and Discussion
	5 Conclusion and Perspective
	References
Detecting Duplicate Multiple Choice Questions in the Large Question Bank
	1 Introduction
	2 Related Works
	3 Methodology
		3.1 Multiple-choice Questions
		3.2 Multiple-choice Questions
		3.3 OCR
		3.4 SBERT
		3.5 Similarity Measurement Method
		3.6 Evaluation Metric
	4 Implementation and Evaluation
		4.1 Implement
		4.2 Dataset
		4.3 Result and Analysis
	5 Conclusion and Future Works
	References
A Context-Aware Approach for Improving Dialog Act Detection in a Multilingual Conversational Platform
	1 Introduction
	2 Methods
		2.1 Recurrent Neural Networks and LSTM
		2.2 Transformers and BERT
		2.3 Context-Aware Dialogue Act Detection
	3 Experimental Results
		3.1 Datasets
		3.2 Experimental Settings
		3.3 Evaluation Metrics
		3.4 Results
	4 Conclusion
	References
Data Mining and Machine Learning
Efficient Association Rules Minimization Using a Double-Stage Quine-McCluskey-Based Approach
	1 Introduction
	2 Related Work
		2.1 Association Rules
		2.2 The QM Approach
	3 Methodology
		3.1 System Architecture
		3.2 Our Method for Applying the QM on Association Rules
		3.3 Redundancy Elimination After System Reduction
	4 Experimental Results
	5 Conclusion
	References
Complexity-Based Code Embeddings
	1 Introduction
	2 Related Work
	3 Converting an Algorithm to an Embedding
	4 System Architecture
	5 Dataset
	6 Results
		6.1 Binary Classification
		6.2 Multi-label Classification
	7 Conclusions and Further Research
	References
Differentially Private Copulas, DAG and Hybrid Methods: A Comprehensive Data Utility Study
	1 Introduction
	2 Related Work
	3 Generative Algorithms Selection
		3.1 PrivBayes
		3.2 DPCopula and Gaussian
		3.3 Copula-Schirley (Vine)
	4 Evaluation Framework
		4.1 Macro Statistics
		4.2 Data Utility
	5 Experimental Setup and Results
		5.1 G Score
		5.2 Accuracy Metrics
		5.3 Macro-Statistics
	6 Conclusions and Future Work
	References
Analysing Android Apps Classification and Categories Validation by Using Latent Dirichlet Allocation
	1 Introduction
	2 Literature Survey
		2.1 Natural Language Processing
		2.2 Latent Dirichlet Allocation
	3 Methodology
		3.1 Data Set Gathering
		3.2 Data Set Processing Techniques
		3.3 Topic Modeling with Latent Dirichlet Allocation
		3.4 Experimental Setup
		3.5 Evaluation Approach
	4 Experiments and Results
		4.1 Comparative Analysis of the Scenarios Results
		4.2 Analysis of the Best Model
	5 Conclusion and Future Work
	References
Staircase Recognition Based on Possibilistic Feature Quality Assessment Method
	1 Introduction
	2 Basic Concept of Staircase Recognition Process
		2.1 Data Collection
		2.2 Pre-processing: Multi-scale Signal Representation and Filtering
		2.3 Feature Extraction and Fusion
		2.4 Possibilistic Modeling of Uncertain Feature Measurements
		2.5 Classification
	3 Feature Quality Assessment Method
		3.1 Feature Classification Based on Feature Quality
		3.2 Feature Complementarity for Optimal Feature Subset
	4 Experimental Results
		4.1 Experimental Setup
		4.2 Performance Results of Stair Recognition System Using Depth Data
	5 Conclusion
	References
Social Networks and Intelligent Systems
Toward Effective Link Prediction Based on Local Information in Organizational Social Networks
	1 Introduction
	2 Link Prediction in Social Networks
		2.1 Problem Formulation
		2.2 Methods
	3 Similarity-Based Approaches to the LP Problem
	4 Predicting Links in the Organizational Social Network - Computational Experiment
		4.1 Goal of the Experiment
		4.2 Dataset
		4.3 Experimental Settings
		4.4 Evaluation Metrics
		4.5 Dedicated Algorithms for Solving the LP Problem in OSN
		4.6 Experimental Results and Analysis
	5 Conclusions
	References
A New Topic Modeling Method for Tweets Comparison
	1 Introduction
	2 Related Work
	3 Basic Notions
	4 Proposed Modeling Method
		4.1 Algorithm
	5 Experimental Results
	6 Conclusions
	References
Measuring Gender: A Machine Learning Approach to Social Media Demographics and Author Profiling
	1 Introduction
	2 Related Work
	3 Data and Methods
		3.1 Domain and Training Data
		3.2 Preprocessing and Tokenization
		3.3 Ensemble Classifier
		3.4 Benchmarking
	4 Results
		4.1 Classifier Evaluation
		4.2 Discussion
	5 Conclusion
	References
Crisis Detection by Social and Remote Sensing Fusion: A Selective Attention Approach
	1 Introduction
	2 Related Works
	3 Methodology
		3.1 Feature Map and Embedding Extraction
		3.2 Selective Attention Module
	4 Experiment Results
		4.1 Dataset
		4.2 Baselines
		4.3 Evaluation Metrics
		4.4 Results and Discussion
	5 Conclusions and Future Work
	References
Educational Videos Recommendation System Based on Topic Modeling
	1 Introduction
	2 Related Work
	3 Proposed Approach
		3.1 Preprocessing
		3.2 Language Model
		3.3 Latent Factor Model (LFM)
	4 Dataset
	5 Experiments and Results
		5.1 Originality Source Data Evaluation
		5.2 Leaner Historical Data Preparing
		5.3 Rating Prediction
	6 Rating Hybridization
		6.1 Discussion
	References
Cybersecurity, Blockchain Technology and Internet of Things
A Two-Hop Neighborhood Based Berserk Detection Algorithm for Probabilistic Model of Consensus in Distributed Ledger Systems
	1 Introduction
	2 Related Work
	3 A New Berserk Detection Algorithm
		3.1 Abbreviations and Annotations of Terms
		3.2 Method
	4 Evaluation
		4.1 Experimental Setting
		4.2 Results
		4.3 Discussion
	5 Conclusions
	References
Trust Assessment on Data Stream Imputation in IoT Environments
	1 Introduction
	2 Related Works
	3 CSIV Method
		3.1 Method Description
		3.2 Algorithm
	4 Experiments
		4.1 Description of the Datasets
		4.2 Evaluation Metrics
		4.3 Configurations
		4.4 Results
	5 Conclusion and Future Work
	References
Optimizing Merkle Tree Structure for Blockchain Transactions by a DC Programming Approach
	1 Introduction
	2 Merkle Tree in Ethereum System
	3 Optimization Model for the Problem of Constructing Merkle Tree in Blockchain Based System
		3.1 Problem Definition
		3.2 The Optimization Model
	4 Solving the Merkle Tree Designing Problem by DCA
	5 Numerical Experiments
		5.1 Experiment Setting
		5.2 Comparative Algorithms
		5.3 Comparative Results
	6 Conclusion
	References
Wearable Tag for Indoor Localization in the Context of Ambient Assisted Living
	1 Introduction
	2 System Description
	3 Methods
		3.1 Experimental Procedure and Participants
		3.2 Data Analysis
	4 Results and Discussion
	5 Conclusions
	References
Hyperledger Blockchain-Enabled Cold Chain Application for Flower Logistics
	1 Introduction
	2 Flower Cold Chain Problem and BlockChain Applicability
	3 Hyperledger Framework
	4 Hyperledger Application for Orchid Logistics
	5 Discussions and Conclusions
	References
A Fully Decentralized Privacy-Enabled Federated Learning System
	1 Introduction
	2 Literature Review
		2.1 Federated Learning
		2.2 Security and Privacy
		2.3 Prior Art
	3 Methodology
	4 Results
	5 Discussion
	6 Conclusion
	References
Cooperative Strategies for Decision Making and Optimization
Two-Dimensional Pheromone in Ant Colony Optimization
	1 Introduction
	2 Ant Colony Optimization
	3 Two-Dimensional Pheromone for Ant Colony Optimization
		3.1 Depositing the Pheromone
		3.2 Interpreting the Pheromone Information
	4 Experimental Evaluation
		4.1 Testing Framework
		4.2 Experimental Results
	5 Conclusion
	References
Analysis of Different Reinsertion Strategies in Steady State Genetic Algorithm
	1 Introduction
	2 Problem Statement
	3 Methodology
		3.1 Unchanged Parameters of SSGA During the Experiment
		3.2 Reinsertion Strategies Used
		3.3 Used Continuous Benchmark Functions
		3.4 Used Discrete Benchmark Problems
	4 Results
	5 Conclusions
	References
Traffic Optimization by Local Bacterial Memetic Algorithm
	1 Introduction
	2 Related Literature
	3 Memetic Traffic Optimization
	4 Experiment
		4.1 Experiment Description
		4.2 Experimental Results
		4.3 Discussion
	5 Conclusion and Further Work
	References
Optimizing Fire Control Monitoring System in Smart Cities
	1 Introduction
	2 Literature Review
	3 Process and Problem Presentation
	4 Mathematical Modeling
	5 Proposed Algorithms
		5.1 Longest-Smallest Time Algorithm (LST)
		5.2 Longest-Smallest Time Excluding the Longest-Area Time Algorithm (LELT)
		5.3 Longest-Smallest Time Excluding the Smallest-Area Time Algorithm (LEST)
		5.4 Probabilistic Longest-Area Time Algorithm (PLT)
	6 Results and Discussion
	7 Conclusion and Future Works
	References
Computational Intelligence for Digital Content Understanding
Desertification Detection in Satellite Images Using Siamese Variational Autoencoder with Transfer Learning
	1 Introduction
	2 Related Work
	3 Method
		3.1 Variational Autoencoder Background
		3.2 Siamese Variational Autoencoder Background
		3.3 Transfer Learning
	4 Experimental Evaluation
		4.1 Study Area and Dataset
		4.2 Implementation Details
		4.3 Evaluation Metrics
	5 Results and Discussion
		5.1 Comparative Method Evaluation
		5.2 Desertification Detection Outcomes
		5.3 The Advantages and Limitations
	6 Conclusion and Outlook
	References
Speaker Identification Enhancement Using Emotional Features
	1 Introduction
	2 Related Works
		2.1 Voice Activity Detection (VAD)
		2.2 Change Point Detection/Speaker Segmentation
		2.3 Speakers Embedding
		2.4 Speaker Identification (Classification)
	3 Proposed Method
		3.1 Voice Activity Detection (WEBRTC VAD)
		3.2 Change Point Detection or Speaker Segmentation (BiLSTM)
		3.3 Speaker Embedding (Triplet Loss)
		3.4 Speaker Classification (Sequential/Functional Keras API)
	4 Experiments and Results
		4.1 Speaker Segmentation
		4.2 Effect of Emotions on Speaker Identification
		4.3 Speaker Classification
		4.4 Discussion
	5 Conclusion
	References
Classification of Punches in Olympic Boxing Using Static RGB Cameras
	1 Introduction
	2 Related Works
	3 Methodology
		3.1 Data Collection
		3.2 Data Labeling
		3.3 Classification
	4 Experiments
	5 Conclusions
	References
Learning Human Postures Using Lab-Depth HOG Descriptors
	1 Introduction
	2 Previous Work
	3 Proposed Method
		3.1 People Detection
		3.2 The Multispectral Lab-D Edge Detection
		3.3 The Multispectral Lab-D HOG Descriptor
		3.4 Human Posture Classification
	4 Experimental Evaluation and Results
		4.1 Dataset
		4.2 Experimental Protocol
		4.3 Implementation Details
		4.4 Results
		4.5 Discussion
	5 Conclusion
	References
SemiMemes: A Semi-supervised Learning Approach for Multimodal Memes Analysis
	1 Introduction
	2 Related Works
	3 Methodology
		3.1 Overview
		3.2 Cross Modality Auto Encoder (CROM-AE) - Stage 1
		3.3 Raw and Cooked Features Classification Model (RAW-N-COOK) - Stage 2
	4 Experimental Results
		4.1 Datasets
		4.2 Setup
		4.3 Results
	5 Conclusion
	References
Extrinsic Calibration Framework for Camera-Lidar Fusion Using Recurrent Residual Network
	1 Introduction
	2 Related Work
	3 Methodology
		3.1 Architecture
		3.2 Output Processing
		3.3 Dataset Pre-processing
		3.4 Loss Functions
		3.5 Training Procedure
	4 Results and Discussion
	5 Conclusion
	References
GAN-Based Data Augmentation and Pseudo-label Refinement for Unsupervised Domain Adaptation Person Re-identification
	1 Introduction
	2 Related Works
		2.1 GAN-based Data Augmentation
		2.2 Label Noise Refinement Method for Unsupervised Person Re-ID
	3 Proposed Method: DAUET
		3.1 Overview
		3.2 GAN-Based Training Data Augmentation
		3.3 Pseudo-Label Refinement
		3.4 Mean Teacher Architecture
	4 Experiments and Evaluation
		4.1 Implementation Details
		4.2 Ablation Study and Analysis
		4.3 Comparison with SOTA Methods
	5 Conclusions
	References
Intelligent Automated Pancreas Segmentation Using U-Net Model Variants
	1 Introduction
	2 Related Work
	3 Variants of U-Net Model
		3.1 U-Net Model for Image Segmentation:
		3.2 Attention U-Net Model for Image Segmentation
		3.3 Residual Attention U-Net Model for Image Segmentation
	4 Methods and Techniques
		4.1 Model Selection Factors
		4.2 Proposed Model
	5 Results and Discussion
	6 Conclusion
	References
Knowledge Engineering and Application for Industry 4.0
Energy and Congestion Awareness Traffic Scheduling in Hybrid Software-Defined Network with Flow Splitting
	1 Introduction
	2 Related Works
	3 Energy and Congestion Awareness Traffic Scheduling in Hybrid Software-Defined Network with Flow Splitting
		3.1 Model Formulation
		3.2 Heuristic Algorithm
	4 Result and Discussion
	5 Conclusion
	References
``Is Proton Good Enough?\'\' - A Performance Comparison Between Gaming on Windows and Linux
	1 Introduction
	2 Related Works
	3 Experiment Setup
		3.1 Research Environment
		3.2 Benchmark Data Collection Software
		3.3 Measured Metrics
		3.4 Video Game Selection
		3.5 The Testing Procedure
	4 Results
		4.1 DirectX 12\'s Impact on Performance
		4.2 Technical Difficulties Present When Running Games on Linux
	5 Discussion
	6 Conclusions
	References
Complete Coverage and Path Planning for Emergency Response by UAVs in Disaster Areas
	1 Introduction
	2 The Problem Model—A Disaster Area Map
	3 The Problem Solution—UAVs\' Paths
	4 Evaluation of UAVs\' Paths
	5 The Optimization Method
	6 Experimental Research
		6.1 Test Cases and Plan of Experiments
		6.2 Results of Experiments
	7 Conclusions
	References
Complex Layers of Ranked Prognostic Models
	1 Introduction
	2 Datasets with Ranked Relations
	3 Linear Separability and Ranked Models
	4 Ranked Criterion Functions k (w)
	5 Designing Complex Layers of Ranked Prognostic Models
	6 Margins Based on the L1 Norm
	7 Example: Causal Sequence of Liver Diseases
	8 Concluding Remarks
	References
Configuration of Project Team Members’ Competences: A Proactive and Reactive Approach
	1 Introduction
	2 Background
	3 Problem Statement and Mathematical Model
	4 Implementation and Computational Examples
	5 Conclusions
	References
Computational Intelligence in Medical Applications
Teeth Disease Recognition Based on X-ray Images
	1 Introduction
	2 Literature Review
	3 Data Preparation
	4 Diseases Recognition
	5 The Experiments Results
	6 Conclusion
	References
Predicting Alzheimer’s Disease Diagnosis Risk Over Time with Survival Machine Learning on the ADNI Cohort
	1 Introduction
	2 Related Work
	3 Problem Definition
	4 Methodology
		4.1 Data Description
		4.2 Predictors
		4.3 Data Preprocessing
		4.4 Model Development
		4.5 Nested Cross-Validation and Monte Carlo Simulation
		4.6 Performance Metrics
		4.7 Software and Hardware
	5 Results
	6 Discussion
	7 Conclusion
	References
MEP: A Comprehensive Medicines Extraction System on Prescriptions
	1 Introduction
	2 Related Work
		2.1 Text Detection and Recognition
		2.2 Post-OCR
	3 Background
		3.1 CRAFT
		3.2 TCN
	4 The Prescription Medicine Extraction System
		4.1 Craft-Text-Detector
		4.2 VietOCR
		4.3 Medicine Extractor
		4.4 MergeOCR
		4.5 Medicine Classifier
		4.6 Context-Aware Spell Correction
	5 Experiment
		5.1 Datasets
		5.2 Parameter Settings
		5.3 Evaluation Metrics
		5.4 Results and Analysis
	6 Conclusion
	References
New Approaches to Monitoring Respiratory Activity as Part of an Intelligent Model for Stress Assessment
	1 Introduction
	2 Related Work
		2.1 Respiratory Activity and Healthcare
		2.2 Solutions for Respiratory Assessment
		2.3 Stress and Respiration
		2.4 Stress Assessment
	3 Materials and Methods
		3.1 Respiratory Rate Estimation
		3.2 Intelligent Approach to Stress Assessment
		3.3 Experimental Procedure
	4 Results and Discussion
		4.1 Assessment of the Proposed Methods for Estimating Respiratory Rate
		4.2 Thermal Stress Induction and Validation of Stress Level Classification
	5 Conclusion
	References
An Adaptive Network Model for Anorexia Nervosa: Addressing the Effects of Therapy
	1 Introduction
	2 Background
	3 The Modeling Approach
	4 The Designed Computational Adaptive Network Model
	5 Simulation Results
	6 Conclusion and Discussion
	References
ReVQ-VAE: A Vector Quantization-Variational Autoencoder for COVID-19 Chest X-Ray Image Recovery
	1 Introduction
	2 Related Works on Image Recovery Based on Deep Learning
	3 Background of AE, VAE
		3.1 Autoencoders (AE)
		3.2 Variational Autoencoders (VAE)
	4 Proposed Method of Image Recovery Based on VQ-VAE (ReVQ-VAE)
		4.1 Vector Quantized Variational Autoencoder (VQ-VAE)
		4.2 ReVQ-VAE Architecture
	5 Experimental Results
		5.1 Dataset Description
		5.2 Experimental Setup
		5.3 Recovery Results of ReVQ-VAE
		5.4 Comparison of ReVQ-VAE Model with Existing Architectures
	6 Conclusion
	References
Ensemble Models and Data Fusion
Credit Risk Scoring Using a Data Fusion Approach
	1 Introduction
	2 Related Work
		2.1 Credit Scoring
		2.2 Natural Language Processing
	3 Methodology
		3.1 Data Overview
		3.2 Text Feature Treatment
		3.3 Data Preprocessing
		3.4 Models
		3.5 Model Performance
	4 Results
		4.1 Exploratory Data Analysis
		4.2 Model Performance
	5 Conclusions
	References
Goal-Oriented Classification of Football Results
	1 Introduction
	2 Background
		2.1 Related Works
		2.2 Problem Definition and Methods
	3 Proposed Solution
		3.1 Data Preparation and Preprocessing
		3.2 ACDT and ACDF Algorithms
		3.3 Goal-Oriented Function
	4 Numerical Experiments
	5 Conclusions and Future Works
	References
Learning from Imbalanced Data Streams Using Rotation-Based Ensemble Classifiers
	1 Introduction
	2 Related Work and Motivation
	3 The WECOI Approach to Learning from Imbalanced Data
	4 Rotation-Based Technique for WECOI
	5 Results of Computational Experiments
	6 Conclusions
	References
DE-Forest – Optimized Decision Tree Ensemble
	1 Introduction and Related Works
	2 Proposition of DE-Forest Algorithm
	3 Experimental Evaluation
		3.1 Setup
		3.2 Results
		3.3 Lesson Learned
	4 Conclusion
	References
Mining Multiple Class Imbalanced Datasets Using a Specialized Balancing Algorithm and the Adaboost Technique
	1 Introduction
	2 Balancing Classifiers
	3 Implementation of OVO and Adaboost Strategies
	4 Computational Experiment
		4.1 Experiment Plan
		4.2 Experiment Results
	5 Conclusion
	References
Investigation and Prediction of Cognitive Load During Memory and Arithmetic Tasks
	1 Introduction
	2 Related Works
	3 Experimental Design, Selected Metrics, and Results
		3.1 Experimental Setup
		3.2 Metrics Extraction
		3.3 Analysis of the Results
	4 Cognitive Load Prediction Model
		4.1 Basic Notions
		4.2 Ensemble Learning Model for Cognitive Load Prediction
	5 Future Works and Summary
	References
Author Index