Note: Intro -- Preface -- Organization -- Contents -- Data Mining, Knowledge Discovery and Big Data -- Document Similarity by Word Clustering with Semantic Distance -- 1 Introduction -- 2 Vector Space Model and Dimension Reduction -- 2.1 Vector Space Model -- 2.2 Distance by WordNet -- 2.3 Distance by Word2Vec -- 2.4 Word Clustering -- 2.5 Dimension Reduction by Semantic Distance -- 2.6 Cluster-Word Relation Matrix -- 3 Experimental Results -- 3.1 Conditions of Experiments -- 3.2 Similarity of Documents -- 3.3 Result of Each Method -- 4 BBC Dataset -- 5 Conclusion -- References -- PSO-PARSIMONY: A New Methodology for Searching for Accurate and Parsimonious Models with Particle Swarm Optimization. Application for Predicting the Force-Displacement Curve in T-stub Steel Connections -- 1 Introduction -- 2 Related Works -- 3 PSO-PARSIMONY Methodology -- 4 Case Study -- 5 Experiment and Results Discussion -- 6 Conclusions -- References -- Content-Based Authorship Identification for Short Texts in Social Media Networks -- 1 Introduction -- 2 Proposed Approach -- 3 Experiment -- 3.1 Data Gathering -- 3.2 Data Pre-processing -- 3.3 Word Embeddings -- 3.4 Tweet Mean Vectors and User Mean Vectors -- 3.5 Supervised Learning -- 4 Discussion -- 5 Conclusions -- References -- A Novel Pre-processing Method for Enhancing Classification Over Sensor Data Streams Using Subspace Probability Detection -- 1 Introduction -- 2 Related Work -- 3 Our Proposed Model -- 4 Experiment -- 5 Conclusions -- References -- Bio-inspired Models and Evolutionary Computation -- Remaining Useful Life Estimation Using a Recurrent Variational Autoencoder -- 1 Introduction -- 2 RUL Estimation -- 3 Model Architecture -- 4 Experimental Study -- 4.1 Data Pre-processing -- 4.2 Illustrative Example -- 4.3 Numerical Results -- 5 Concluding Remarks -- References. , Open-Ended Learning of Reactive Knowledge in Cognitive Robotics Based on Neuroevolution -- 1 Introduction -- 2 Knowledge in the Epistemic Multilevel Darwinist Brain (e-MDB) -- 2.1 Knowledge Representation -- 2.2 Knowledge Acquisition and Decision Making -- 3 Policy Learning Process -- 4 Real Robot Example -- 5 Conclusions -- References -- Managing Gene Expression in Evolutionary Algorithms with Gene Regulatory Networks -- 1 Introduction -- 2 Biological Gene Expression -- 3 Gene Regulatory Networks -- 4 Proposed Algorithms -- 4.1 Chromosome Representation -- 4.2 Fitness Evaluation -- 4.3 Mutation -- 4.4 Crossover -- 5 Evaluation -- 6 Results -- 7 Conclusion -- 8 Future Work -- References -- Evolutionary Optimization of Neuro-Symbolic Integration for Phishing URL Detection -- 1 Introduction -- 2 Related Works -- 3 The Proposed Method -- 3.1 Collect and Structuralize Calibration Rules for Deep Learning Classifier -- 3.2 Deep Learning Calibration and Optimization to Improve URL Classification Performance -- 3.3 One-Dimensional Convolutional Recurrent Neural Network to Extract Sequence of Character and Word Features -- 4 Experimental Results -- 4.1 Data Collection -- 4.2 Comparison of Accuracy and Recall Performance -- 4.3 Classification Performance and Chi-Square Test -- 4.4 Analysis of Optimized Combination and Misclassified Cases -- 4.5 Generations for Genetic Algorithm -- 5 Conclusion -- References -- Interurban Electric Vehicle Charging Stations Through Genetic Algorithms -- 1 Introduction -- 2 Problem Description -- 3 Interurban EV Charging Stations Distribution -- 3.1 Utility -- 3.2 Uncovered Area and Distance to Nearest Station -- 3.3 Implementation and Fitness -- 4 Experimental Results -- 5 Conclusions -- References -- An Effective Hybrid Genetic Algorithm for Solving the Generalized Traveling Salesman Problem -- 1 Introduction. , 2 Definition of the Generalized Traveling Salesman Problem -- 3 The Proposed Hybrid Algorithm -- 3.1 Chromosome Structure -- 3.2 Chromosome Optimization -- 3.3 Initial Population -- 3.4 Crossover -- 3.5 Mutation -- 3.6 Genetic Parameters -- 4 Preliminary Computational Results -- 5 Conclusions -- References -- A Simple Genetic Algorithm for the Critical Node Detection Problem -- 1 Introduction -- 2 Related Work -- 3 Maximum Components GA (MaxC-GA) -- 4 Numerical Experiments -- 5 Conclusions -- References -- Learning Algorithms -- Window Size Optimization for Gaussian Processes in Large Time Series Forecasting -- 1 Introduction -- 2 Methodology -- 2.1 Gaussian Processes -- 2.2 Kernel Selection -- 2.3 General Approach to Large Time Series -- 2.4 Data Set -- 3 Results and Analysis -- 3.1 Kernel and Parameter Choice -- 3.2 Hyperparameter Tuning and Interpretability -- 4 Conclusions -- References -- A Binary Classification Model for Toxicity Prediction in Drug Design -- 1 Introduction -- 2 Data and Methods -- 2.1 Dataset Creation -- 2.2 Data Processing -- 2.3 Proposed Model Architecture -- 3 Experiments and Results -- 3.1 Metrics -- 3.2 Scenarios -- 3.3 Results -- 4 Conclusions -- References -- Structure Learning of High-Order Dynamic Bayesian Networks via Particle Swarm Optimization with Order Invariant Encoding -- 1 Introduction -- 2 Background -- 2.1 High-Order Dynamic Bayesian Networks -- 2.2 Particle Swarm Structure Learning -- 3 Encoding and Operators -- 3.1 Natural Vector Encoding -- 3.2 Position and Velocity Operators -- 4 Results -- 4.1 Implementation -- 4.2 Experimental Comparison -- 5 Conclusions -- References -- Prototype Generation for Multi-label Nearest Neighbours Classification -- 1 Introduction -- 2 Related Work -- 3 The Reduction Through Homogeneous Clustering (RHC) Algorithm -- 4 The Proposed Multi-label RHC (MRHC) Algorithm. , 5 Performance Evaluation -- 5.1 Datasets -- 5.2 Experimental Setup -- 5.3 Experimental Results -- 6 Conclusions and Future Work -- References -- Learning Bipedal Walking Through Morphological Development -- 1 Introduction -- 2 Designing a Morphological Development Strategy -- 3 Experimental Setup -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Ethical Challenges from Artificial Intelligence to Legal Practice -- 1 Introduction. From Justice to eJustice -- 2 Objectives -- 3 Methodology -- 4 Developing. The Application of Algorithms in Justice -- 4.1 Artificial Legal Intelligence -- 4.2 Jurimetrics. Legal Decision Support System -- 4.3 Legal Expert Systems -- 5 Results: First Ethical Questions Derived from the Use of AI in Legal Procedures and Processes -- 5.1 Publicity Principle -- 5.2 Principle of Contradiction and Right of Defense -- 5.3 Principle of Procedural Equality or Equality of the Parts -- 5.4 Influence of AI on the Principles of Criminal Process -- 5.5 Preventive and Predictive AI -- 6 Discussion. Future Challenges: Understandability, Intepretability, Explicability, Transparency, and Algorithmic Traceability as Ethical Challenges -- 6.1 A Relationship Between the Jurimetrics with the Global Framework of the eJustice that Guarantees the Nature of the Latter as an Effective Attorney of Justice -- 6.2 Respect for Procedural Data by Means of Big Data Techniques that Respect the Rights that Are Set Out in Spanish or European Legislation -- 6.3 Transparency in a Digitized Jurisdictional Framework -- 6.4 Establishment of Responsibilities for the People Who Define the Prediction Algorithms on the Prosperousness of a Claim -- 6.5 Irreplaceability of Lawyers or Other Judicial Agents by AI Legal Systems. , 6.6 Guarantee that the Digitization of the Judicial Process Does not Destroy the Analysis and Legal Argumentation that Any Matter Requires -- 7 Conclusions -- 7.1 Need for Codes of Ethics and Legal Regulations Regarding the Use of AI Technologies -- 7.2 Protection of Privacy -- 7.3 Algorithmic Ethics and Research in Explanatory AI (XAI) -- References -- Visual Analysis and Advanced Data Processing Techniques -- Classification of Burrs Using Contour Features of Image in Milling Workpieces -- 1 Introduction -- 2 Inspection Method -- 2.1 Image Processing -- 2.2 Region of Interest Identification -- 2.3 Feature Vector Calculation -- 2.4 Classification -- 3 Experimental Results -- 4 Conclusions -- References -- Adaptive Graph Laplacian for Convex Multi-Task Learning SVM -- 1 Introduction -- 2 Multi-Task Learning SVMs -- 2.1 Convex Multi-Task Learning SVM -- 2.2 Convex Graph Laplacian MTL SVM -- 3 Convex Adaptative Graph Laplacian MTL SVM -- 4 Synthetic Experimental Results -- 5 Discussion and Conclusions -- References -- Fight Detection in Images Using Postural Analysis -- 1 Introduction -- 2 Related Work -- 3 Existing Datasets for Fighting Detection -- 4 Methodology -- 4.1 Data Gathering -- 4.2 Angles Extraction from Skeleton -- 4.3 Dataset Generation -- 5 Experimentation and Results -- 5.1 Feature Subset Selection -- 5.2 Analysis of Network Learning Curves -- 6 Conclusions -- References -- Applying Vector Symbolic Architecture and Semiotic Approach to Visual Dialog -- 1 Introduction -- 2 Related Works -- 3 Vector Semiotic Architecture for Visual Dialog -- 4 Experiments -- 5 Discussion -- 6 Conclusion -- References -- Transfer Learning Study for Horses Breeds Images Datasets Using Pre-trained ResNet Networks -- 1 Introduction and Motivation -- 2 The Proposal -- 3 Numerical Results -- 3.1 Materials and Methods -- 3.2 Results -- 4 Conclusion and Future Work. , References.

Note: Intro -- Preface -- Organization -- Contents -- Bioinformatics -- A Comparison of Machine Learning Techniques for the Detection of Type-4 PhotoParoxysmal Responses in Electroencephalographic Signals -- 1 Introduction -- 2 Preliminaries and Related Work -- 3 Type-4 PPR Detection Using ML -- 3.1 Dimensional Reduction -- 3.2 Clustering and Classification -- 4 Materials and Methods -- 4.1 Data Set Description -- 4.2 Experimentation Design -- 5 Results and Discussion -- 6 Conclusions and Future Work -- References -- Smartwatch Sleep-Tracking Services Precision Evaluation Using Supervised Domain Adaptation -- 1 Introduction -- 2 The Proposal -- 2.1 Step1: RAW Signals Preprocessing -- 2.2 Step2: Features Computing -- 2.3 Steps 3 and 4: Models Training and Domain Adaptation -- 3 Numerical Results -- 3.1 Materials and Methods -- 3.2 Experimentation Set up -- 3.3 Numerical Results -- 4 Conclusions and Future Work -- References -- Tracking and Classification of Features in the Bio-Inspired Layered Networks -- 1 Introduction -- 2 Bio-Inspired Neural Networks -- 2.1 Background of Asymmetric Neural Networks Based on the Bio-Inspired Network -- 2.2 Model of Asymmetric Networks -- 2.3 Tracking in the Asymmetric Networks -- 2.4 Orthogonality in the Asymmetric Layered Networks -- 3 Sparse Coding for Classification in the Extended Asymmetric Networks -- 3.1 Independence and Sparse Coding on the Orthogonal Subnetworks -- 3.2 Generation of Independent Basis Set via Sparse Coding Realization -- 4 Application to Data Classification via Sparse Coding Realization in the Asymmetric Networks -- 5 Conclusion -- References -- Frailty Related Survival Risks at Short and Middle Term of Older Adults Admitted to Hospital -- 1 Introduction -- 2 Materials and Methods -- 2.1 Study Design and Subjects -- 2.2 Statistical Methods -- 3 Results -- 4 Discussion. , 5 Conclusions and Future Work -- References -- On the Analysis of a Real Dataset of COVID-19 Patients in Alava -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 Study Design -- 3.2 Ethical Approval and Patient Consent -- 3.3 Data Collection and Description -- 3.4 Attribute Analysis -- 3.5 Principal Component Analysis -- 3.6 Logistic Regression Feature Importance -- 4 Discussion -- 5 Conclusion -- References -- Indoor Access Control System Through Symptomatic Examination Using IoT Technology, Fog Computing and Cloud Computing -- 1 Introduction -- 2 Related Works -- 3 Operation of the Control System -- 3.1 Facial Recognition Module -- 3.2 Steps of the Detection System -- 3.3 Medical Sensors -- 3.4 Fog Computing -- 3.5 Statistics Management and User Registration Module -- 3.6 Accessibility Improvements -- 4 Conclusions and Future Work Lines -- References -- Data Mining and Decision Support Systems -- Measuring the Quality Information of Sources of Cybersecurity by Multi-Criteria Decision Making Techniques -- 1 Introduction -- 2 Background -- 2.1 Related Work -- 2.2 DQ Model -- 3 Ranking of Sources by MCDM -- 3.1 Weighted Sum Model (WSM) -- 3.2 Analytic Hierarchy Process (AHP) -- 3.3 Concordance Between Rankings -- 4 Experimental Section -- 5 Results and Discussion -- 6 Conclusions and Future Work -- References -- A Case of Study with the Clustering R Library to Measure the Quality of Cluster Algorithms -- 1 Introduction -- 2 The Clustering Package -- 3 A Case Study Using the Clustering Library on the Dataset of Deaths -- 4 Graphical Distribution of Results -- 5 Conclusions -- References -- Comparing Clustering Techniques on Brazilian Legal Document Datasets -- 1 Introduction -- 2 Related Work -- 3 Theoretical Basis -- 3.1 Clustering Algorithms -- 3.2 Natural Language Processing Techniques -- 4 Methodology -- 4.1 Models Description. , 4.2 Databases, Preprocessing and Embedding -- 4.3 Clustering Evaluation Framework -- 4.4 Clustering Human Evaluation -- 5 Results and Discussion -- 6 Conclusion -- 7 Future Work -- References -- Improving Short Query Representation in LDA Based Information Retrieval Systems -- 1 Introduction -- 2 Material and Methods -- 2.1 Information Retrieval Systems -- 2.2 Latent Dirichlet Allocation -- 2.3 Relevance Estimation -- 3 Proposed Query Representation Method: LDAW -- 3.1 LDAW Calculation Method -- 3.2 Relevance of the Word in Each LDA Topic -- 3.3 Relevance of the Word in the Corpus Vocabulary -- 3.4 Relevance of the Word in the Query -- 3.5 Word Vector Calculation -- 4 Evaluation -- 4.1 Data Sets -- 4.2 Evaluation Measures -- 4.3 Text Pre-processing -- 4.4 Experiments Description -- 5 Results and Discussion -- 6 Conclusions -- References -- A New Game Theoretic Based Random Forest for Binary Classification -- 1 Introduction -- 2 Decision Trees and Random Forests -- 2.1 FROG -- 2.2 RF-FROG -- 3 Numerical Experiments -- 4 Conclusions -- References -- Concept Drift Detection to Improve Time Series Forecasting of Wind Energy Generation -- 1 Introduction -- 2 Materials and Method -- 2.1 Dataset -- 2.2 Concept Drifts Detection Techniques -- 2.3 Comparison Procedure -- 3 Results -- 4 Conclusions -- References -- A Decision Support Tool for the Static Allocation of Emergency Vehicles to Stations -- 1 Introduction -- 2 Background -- 3 Architecture -- 4 Static Ambulance Allocation Model -- 4.1 Problem Description -- 4.2 Mathematical Model -- 5 Evaluation -- 5.1 Computational Evaluation -- 5.2 Model Evaluation -- 6 Conclusions -- References -- Adapting K-Means Algorithm for Pair-Wise Constrained Clustering of Imbalanced Data Streams -- 1 Introduction -- 2 Algorithm -- 3 Experiments -- 3.1 Research Protocol -- 3.2 Experimental Setup -- 3.3 Results. , 4 Conclusions -- References -- Small Wind Turbine Power Forecasting Using Long Short-Term Memory Networks for Energy Management Systems -- 1 Introduction -- 2 Case Study -- 2.1 Sotavento Galicia Building -- 2.2 Dataset Description -- 3 Energy Management System -- 4 Experiments and Results -- 4.1 Experiments Setup -- 4.2 Results -- 5 Conclusions and Future Work -- References -- CORE-BCD-mAI: A Composite Framework for Representing, Querying, and Analyzing Big Clinical Data by Means of Multidimensional AI Tools -- 1 Introduction -- 2 Motivations: Combining Multidimensional AI Tools and Big Clinical Data -- 3 CORE-BCD-mAI: Methodologies and Anatomy -- 4 CORE-BCD-mAI: Research Challenges -- 5 Conclusions and Future Work -- References -- Generalized Fisher Kernel with Bregman Divergence -- 1 Introduction -- 2 Statement of the Problem -- 2.1 Non-parametric Approach -- 3 Non Parametric General Solutions -- 4 Examples -- 5 Conclusion -- References -- A HAIS Approach to Predict the Energy Produced by a Solar Panel -- 1 Introduction -- 2 Case of Study -- 2.1 Sotavento Bioclimatic House -- 2.2 Bioclimatic House Facilities -- 2.3 Solar Thermal System -- 3 Techniques Applied -- 3.1 Statistical Regression Techniques -- 3.2 Artificial Neural Networks -- 3.3 Clustering Technique -- 4 Results and Discussion -- 5 Conclusions and Future Work -- References -- Deep Learning -- Companion Losses for Ordinal Regression -- 1 Introduction -- 2 OR Overview -- 3 Companion Losses for OR -- 4 Experimental Results -- 4.1 Companion Loss Models -- 4.2 Comparison with Classical or Models -- 5 Discussion and Conclusions -- References -- Convex Multi-Task Learning with Neural Networks -- 1 Introduction -- 2 Multi-Task Learning Approaches -- 2.1 Multi-Task Learning with a Feature-Learning Approach -- 2.2 Multi-Task Learning with a Regularization-Based Approach. , 2.3 Multi-Task Learning with a Combination Approach -- 3 Convex MTL Neural Networks -- 3.1 Definition -- 3.2 Training Procedure -- 3.3 Implementation Details -- 4 Experimental Results -- 4.1 Problems Description -- 4.2 Experimental Procedure -- 4.3 Analysis of the Results -- 5 Conclusions and Further Work -- References -- Smash: A Compression Benchmark with AI Datasets from Remote GPU Virtualization Systems -- 1 Introduction -- 2 Related Work -- 2.1 Remote GPU Virtualization -- 2.2 Compression Libraries -- 2.3 Datasets Used with Compression Libraries -- 3 The Smash Compression Benchmark for AI -- 3.1 A New Dataset for AI Applications -- 3.2 The Smash Compression Benchmark -- 4 Experiments -- 5 Conclusion -- References -- Time Series Forecasting Using Artificial Neural Networks -- 1 Introduction -- 2 Background -- 3 Materials and Methods -- 4 ANN Architectures -- 4.1 Multi-layer Neural Network -- 4.2 Recurrent Neural Networks -- 5 Results and Discussion -- 5.1 Recurrent Neural Network Performance -- 5.2 Results Comparison -- 6 Conclusions -- References -- A Fine-Grained Study of Interpretability of Convolutional Neural Networks for Text Classification -- 1 Introduction -- 2 Related Work -- 2.1 Network Interpretability -- 3 Methodology -- 4 Evaluation -- 4.1 Corpora -- 4.2 Model Studied -- 4.3 Experimental Phase -- 4.4 Study of the Interpretability of the Convolutional Layers -- 5 Conclusions and Future Work -- References -- Olive Phenology Forecasting Using Information Fusion-Based Imbalanced Preprocessing and Automated Deep Learning -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Data Preparation -- 3.2 Imbalanced Techniques -- 3.3 Automated Deep Learning Proposal -- 3.4 Benchmark Algorithms -- 4 Experimentation and Results -- 4.1 Dataset -- 4.2 Evaluation Metrics -- 4.3 Experimental Settings -- 4.4 Results and Discussion. , 5 Conclusions.

Note: Intro -- Preface -- Organization -- General Chair -- Local Chair -- Local Co-Chairs -- International Advisory Committee -- Program Committee Chairs -- Program Committee -- Special Sessions -- Applications of Machine Learning in Computer Vision -- Program Committee -- Soft Computing Applied to Autonomous Robots and Renewable Energy Systems -- Program Committee -- Optimization, Modeling and Control by Soft Computing Techniques -- Program Committee -- Challenges and New Approaches Toward Artificial Intelligence Deployments in Real-World Scenarios -- Program Committee -- Time Series Forecasting in Industrial and Environmental Applications (TSF) -- Program Committee -- Soft Computing Methods in Manufacturing and Management Systems Applied Machine Learning -- Program Committee -- Applied Machine Learning -- Program Committee -- SOCO 2021 Organizing Committee Chairs -- SOCO 2021 Organising Committee -- Contents -- Machine Learning -- A Comparison of Techniques for Virtual Concept Drift Detection -- 1 Introduction -- 2 A Description of the Technologies -- 2.1 Pre-processing Alternatives -- 2.2 Virtual Concept Drift Detection Methods -- 3 Materials and Methods -- 3.1 Virtual Concept Drift Data Sets -- 3.2 Experimental Set Up -- 4 Results and Discussion -- 5 Conclusions and Future Work -- References -- Dimensional Reduction on an Intelligent Model for Efficiency Improvement of Switching Modes Detection -- 1 Introduction -- 2 Case Study -- 3 Model Approach -- 3.1 Dataset -- 3.2 Methods -- 3.3 Classification Model -- 3.4 Experiments Description -- 4 Results -- 5 Conclusions and Future Works -- References -- Performance and Explainability of Reservoir Computing Models for Industrial Prognosis -- 1 Introduction -- 2 Related Work -- 3 Proposed Explainability Technique -- 4 Data and Experimental Design -- 5 Results and Discussion. , 6 Conclusions and Future Research Lines -- References -- A Data-Driven Approach for Components Useful Life Estimation in Wind Turbines -- 1 Introduction -- 2 Data Sources -- 3 Data Science-Based Predictive Process -- 3.1 Requirements -- 3.2 Data Preparation -- 3.3 Predictive Modeling -- 4 Case of Study -- 4.1 Case of Study: Fast Multiplier Shaft Bearing -- 5 Conclusions -- References -- Towards Adaptive Gamification in Small Online Communities -- 1 Introduction -- 2 Adaptive Gamification -- 3 A Framework for Adaptive Gamification -- 3.1 Algorithms for Adaptive Gamification in Small Communities -- 4 Experiments -- 4.1 Simulation Setting -- 4.2 Experimental Results -- 5 Conclusions -- References -- LSTM vs CNN in Real Ship Trajectory Classification -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Real World Binary Dataset -- 3.2 Classical Approach -- 3.3 Deep Learning Approach -- 4 Experiments and Results -- 5 Conclusions -- Reference -- A Comparison of Learning Approaches to Dialogue Management in Conversational Systems -- 1 Introduction -- 2 Proposed Techniques -- 3 Datasets -- 4 Proposed Methodologies -- 4.1 Retrieval-Based Model -- 4.2 Generative Model -- 5 Conclusions and Future Work -- References -- Aspect-Based Sentiment Analysis in Drug Reviews Based on Hybrid Feature Learning -- 1 Introduction -- 2 The Proposed Classification System -- 2.1 Pre-processing -- 2.2 Feature Extraction -- 2.3 Sentiment Classification -- 3 Experimental Results and Discussion -- 3.1 Experimental Analysis -- 3.2 Comparative Analysis Against State-of-the-art Approaches -- 4 Conclusions and Future Work -- References -- Smart Cities and IOT -- Low-Cost Deep Learning-Based Prototype for Automatic Identification of Traffic Signs in Vehicles -- 1 Introduction -- 2 Materials and Methods -- 2.1 Deployed Infrastructure -- 2.2 Deep Learning Models. , 2.3 Data Set Description -- 2.4 Experimental Setup -- 3 Results and Discussion -- 3.1 Model Training Results -- 3.2 Validation with the Physical Deployment -- 4 Conclusions -- References -- Visual Mining of Industrial Gas Turbines Sensor Data as an Industry 4.0 Application -- 1 Introduction -- 2 Materials and Methods -- 2.1 Gas Turbines and Sensor Data -- 2.2 UMAP for Multivariate Data Visualization -- 2.3 Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) -- 2.4 Agnostic Feature Selection (AFS) -- 2.5 Experimental Settings -- 3 Results and Discussion -- 4 Conclusions -- References -- Visually Monitoring the Performance of a Component-Based Robot -- 1 Introduction -- 2 Hybrid Unsupervised Exploratory Plots -- 2.1 DBSCAN -- 3 Monitoring Performance in Robots -- 4 Experiments and Results -- 5 Conclusions and Future Work -- References -- Optimizing Communication Data Streams in Edge Computing Systems Using Bayesian Algorithms -- 1 Introduction -- 2 Background -- 2.1 Naive Bayesian Classifier -- 3 Experiments -- 3.1 Algorithm Performance -- 3.2 Experimentation Steps -- 4 Conclusion -- References -- Temporal Data Analysis -- Time Series Forecasting of Gold Prices with the Help of Its Decomposition and Multivariate Adaptive Regression Splines -- 1 Introduction -- 2 State of the Art of Gold Prices Forecasting -- 3 Materials and Methods -- 3.1 The Database -- 3.2 Time Series Decomposition -- 3.3 Multivariate Adaptive Regression Splines -- 3.4 Performance Indicators -- 4 Results -- 4.1 Training of a Gold Price MARS Forecasting Model with the Original Time Series -- 4.2 Training of a Gold Price MARS Forecasting Model with the Trend Component of the Time Series -- 4.3 Comparison of the Results Obtained by the Models Applied -- 5 Discussion -- 6 Conclusions -- References. , Time Series Analysis for the COMEX Gold Spot Price Forecasting by Using NARX DE/SVR and DE/GPR Techniques -- 1 Introduction -- 2 Materials and Methods -- 2.1 Experimental Dataset -- 2.2 Support Vector Regression (SVR) for Time Series Analysis -- 2.3 Gaussian Process Regression (GPR) for Time Series Analysis -- 2.4 Differential Evolution (DE) Optimizer -- 2.5 Computational Procedure and Numerical Schemes -- 3 Results and Discussion -- 4 Conclusions -- References -- Data Mines in Real Estate Web Pages: Investigation of Changes in the Czech Real Estate Market Based on Elasticity and on Modified Price Volume Indicator -- 1 Introduction -- 1.1 Data Mining Investigation of Real Estate Market Based on Cluster Analysis -- 1.2 The Main Objectives of the Study -- 2 Material and Methods -- 2.1 Data and Architecture of Software Solution -- 2.2 Elasticity -- 2.3 Modified Price-Volume Indicator -- 2.4 Cluster Analysis -- 3 Numerical Study -- 3.1 Source Data -- 3.2 Results -- 4 Conclusion -- References -- Soft Computing Applications -- The Weak Supervision Approach for Question Answering over Text Using Triplets Recovering with QA-Based Rankers -- 1 Introduction -- 2 Related Work -- 3 The QA-Based Weak Supervision Approach for QAT-Model Training Using Recovered Triplets -- 3.1 Weak Supervision for QAT-Triplets Recovering -- 3.2 Document Searching: Ranking and Re-ranking -- 3.3 Question Answering over Text -- 4 Experimental Study -- 4.1 Datasets -- 4.2 Experimental Settings -- 4.3 Document Searching. Ranking and Re-ranking -- 4.4 Question Answering over Recovered Text -- 5 Conclusion -- References -- VR-Photosense: A Virtual Reality Photic Stimulation Interface for the Study of Photosensitivity -- 1 Introduction -- 2 Related Work: Photosensitive Epilepsy and Virtual Reality -- 2.1 The Science of Photo-Sensitivity -- 2.2 Virtual Reality. , 2.3 Detecting EEG Abnormalities Using Intermittent Photic Stimulation -- 3 An Introduction to VR-Photosense -- 3.1 Measuring Photo-Sensitivity with VR-Photosense -- 4 Conclusions and Future Directions -- References -- Guidance of Unmanned Surface Vehicle Fleet Using Genetic Algorithm-Based Approach -- 1 Introduction -- 2 Proposed Algorithms -- 2.1 Low-Level Control -- 2.2 Local Planning -- 2.3 Global Planning -- 2.4 Genetic Algorithm -- 3 Experiments -- 3.1 Problem Formulation -- 3.2 Implementation of Global Planning Using Genetic Algorithm -- 3.3 Results of Global Planning -- 4 Conclusion -- References -- Toward Reusing the Numerical Association Rule Mining Models -- 1 Introduction -- 2 Numerical Association Rule Mining -- 3 The Reusable NARM Model -- 4 Practical Simulations and Evaluations -- 4.1 Discussion and Issues to Consider -- 5 Conclusion -- References -- Powering Soft Querying in J-CO-QL with JavaScript Functions -- 1 Introduction -- 2 Background -- 2.1 Brief Introduction to Fuzzy Sets -- 2.2 Related Work -- 2.3 The J-CO Framework -- 3 Case Study and J-CO-QL Script -- 3.1 JavaScript Function and Fuzzy Operator -- 3.2 Retrieving and Preprocessing Data -- 3.3 Soft Querying -- 4 Conclusions -- References -- Image Reconstruction of Colored Bitmap Fractal Images Through Bat Algorithm and Color-Based Image Clustering -- 1 Introduction -- 2 Iterated Function Systems -- 3 The Bat Algorithm -- 4 The Proposed Method -- 4.1 Color-Based Image Clustering of the Input Image -- 4.2 Obtaining Dominant Color for Each Cluster -- 4.3 Population Encoding Scheme -- 4.4 The Fitness Function -- 5 Experimental Results -- 6 Conclusions and Future Work -- References -- Intraday Energy Resource Scheduling for Load Aggregators Considering Local Market -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Intraday Model -- 2.2 Problem Formulaion -- 3 Case Study. , 4 Results and Discussion.

Note: Intro -- Preface -- CISIS 2021 -- Organization -- General Chair -- Local Chair -- Local Co-chairs -- Program Committee Chairs -- Program Committee -- CISIS 2021: Special Sessions -- Building Trust in Ecosystems and Ecosystem Components -- Program Committee -- CISIS 2021 Organizing Committee Chairs -- CISIS 2021 Organizing Committee -- ICEUTE 2021 -- Organization -- General Chair -- Local Chair -- Local Co-chairs -- Program Committee Chairs -- Program Committee -- ICEUTE 2021: Special Sessions -- Sustainable Personal Goals: Engaging Students in their Learning Process -- Program Committee -- ICEUTE 2021 Organizing Committee Chairs -- ICEUTE 2021 Organizing Committee -- Contents -- A Fast Heterogeneous Approach to Enhanced Blockchain Attack Resilience and Mitigation -- 1 Introduction -- 2 Related Work -- 2.1 The CUDA Framework -- 2.2 Challenges in Heterogeneous Implementations -- 3 Implementation -- 4 Experimental Results -- 5 Conclusion -- References -- Estimating Re-identification Risk by Means of Formal Conceptualization -- 1 Introduction -- 2 Background -- 2.1 Risk-Based Methodologies for Preserving Privacy -- 2.2 Formal Concept Analysis -- 3 Estimating Risk Using Formal Concepts -- 3.1 Semantic Interpretation of Risk Metrics -- 3.2 Semantic Risk -- 3.3 Semantic Risk Management -- 4 Conclusions and Future Work -- References -- Beta Hebbian Learning for Intrusion Detection in Networks of IoT Devices -- 1 Introduction -- 2 Case Study -- 3 Dataset -- 4 Beta Hebbian Learning Algorithm as Projection Model for CyberActtacks Visualization -- 5 Experiments and Results -- 6 Conclusions and Future Works -- References -- Attacks Detection on Sampled Netflow Traffic Through Image Analysis with Convolutional Neural Networks (CNN) -- 1 Introduction -- 2 Materials and Methods -- 2.1 Data Gathering -- 2.2 Image Generation -- 2.3 Training the CNN -- 3 Results. , 4 Conclusions and Further Work -- References -- Analysis of the Performance of Different Accountability Strategies for Autonomous Robots -- 1 Introduction -- 2 System Architecture -- 3 System Application Using Sysdig, Librdkafka, Apache Kafka and MongoDB -- 3.1 Sysdig -- 3.2 Librdkafka Message Producer -- 3.3 Apache Kafka -- 3.4 MongoDB -- 4 Experimentation -- 4.1 Software Artifacts -- 5 Evaluation -- 5.1 Assessment Scenarios -- 5.2 Metrics -- 6 Results and Discussion -- 6.1 Log Benchmarking -- 6.2 System Benchmarking -- 7 Conclusions -- References -- Analysis of NetFlow Features' Importance in Malicious Network Traffic Detection -- 1 Introduction -- 2 Materials and Methods -- 2.1 NetFlow -- 2.2 RedCAYLE -- 2.3 MoEv -- 2.4 DOROTHEA -- 2.5 Data Gathering -- 2.6 Evaluation -- 3 Results and Discussion -- 4 Conclusions -- References -- Localizing Worst-Parent Rank Attack Using Intelligent Edges of Smart Buildings -- 1 Introduction -- 1.1 Background -- 1.2 Related Work -- 2 System Description -- 3 Worst-Parent Attack -- 4 Simulation of Worst-Parent Attack -- 5 Results and Discussion -- 5.1 Preprocessing and Machine Learning -- 5.2 Results -- 5.3 Discussion -- 6 Conclusions -- References -- Towards a Fog Based Computing Conceptual Framework for Biometric Digital Identification Systems -- 1 Introduction -- 1.1 Motivation -- 1.2 Background of the Problem -- 1.3 Statement of Background of the Problem -- 2 Related Works -- 3 Current State of Research -- 4 A Conceptual Framework for IOT and Data Cloud Biometric Digital Identities -- 5 Evaluation of the Conceptual Framework -- 5.1 Results -- 6 Conclusion and Future Work -- References -- Detection of Denial of Service Attacks in an MQTT Environment Using a One-Class Approach -- 1 Introduction -- 2 Case Study -- 2.1 Dataset Description -- 3 Classifier Approach to Detect DoS Attacks -- 3.1 Classifier Approach. , 3.2 Methods -- 3.3 Experiments Setup -- 3.4 Preprocessing -- 3.5 Results -- 4 Conclusions and Futures Works -- References -- Fuzzy Logic System for Risk and Energy Efficiency Estimation of Driving Maneuvers -- 1 Introduction -- 2 Road and Vehicle Dynamics -- 3 Risky Maneuvers Identification by a Fuzzy Mamdani System -- 3.1 Variables of the Fuzzy Inference System -- 3.2 Mamdani-Type Fuzzy Identification System -- 4 Results and Discussion -- 5 Conclusions and Future Work -- References -- Machine Learning Ensemble Methods for Optical Network Traffic Prediction -- 1 Introduction -- 2 Datasets -- 3 Network Model and Machine Learning Approach -- 4 Numerical Results -- 5 Conclusions -- References -- Assessing the Impact of Batch-Based Data Aggregation Techniques for Feature Engineering on Machine Learning-Based Network IDSs -- 1 Introduction -- 2 Dataset and Methods -- 2.1 UGR'16 Dataset -- 2.2 Methods -- 3 Experimental Design -- 4 Results and Discussion -- 5 Conclusions and Future Work -- References -- Gait-Based Authentication Using a RGB Camera -- 1 Introduction -- 2 Materials and Methods -- 2.1 OpenPose -- 2.2 Dataset -- 2.3 Data Labeling -- 2.4 Model Fitting -- 2.5 Methods of Evaluation -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- The Neverending Story: Memory Corruption 30 Years Later -- 1 Introduction -- 2 Background -- 3 Memory Error Detection -- 3.1 Static Analysis -- 3.2 Instrumentation and Runtime Monitoring -- 3.3 Fuzzing -- 3.4 Symbolic Execution -- 4 Memory Corruption Exploitation -- 4.1 Code-Reuse Attacks -- 4.2 Data-Only Attacks -- 5 Defense Strategies -- 5.1 Enhanced Software Diversity -- 5.2 Control-Flow Integrity -- 5.3 Data-Flow Integrity -- 5.4 Software Fault Isolation -- 6 Related Work -- 7 Conclusion -- References. , StegoPass - Utilization of Steganography to Produce a Novel Unbreakable Biometric Based Password Authentication Scheme -- 1 Introduction -- 2 Methodology -- 3 Experimental Results -- 4 Conclusion and Future Work -- References -- A Repeated Mistake is a Choice: Considering Security Issues and Risks in Quantum Computing from Scratch -- 1 Introduction -- 2 Quantum Programming Languages (QPL) -- 2.1 Imperative Languages -- 3 Limitations of the Hardware -- 4 Analysis for Security in Quantum Languages -- 4.1 Analysis of the Base Language -- 4.2 Analysis of Errors in the Definition of Circuits -- 4.3 Dynamic Analysis of the Program -- 4.4 Work of Mention -- 5 Conclusions -- References -- Advanced 3D Visualization of Android Malware Families -- 1 Introduction -- 2 HUEPs -- 3 Experimental Study -- 3.1 Android Malware Genome Dataset -- 3.2 Obtained HUEP Visualizations -- 4 Conclusions and Future Work -- References -- SPECIAL SESSION: Building Trust in Ecosystems and Ecosystem Components -- BIECO Runtime Auditing Framework -- 1 Introduction -- 2 Related Work -- 3 Conceptual Idea -- 4 BIECO Auditing Process -- 5 Runtime Auditing Framework -- 5.1 Predictive Simulation -- 5.2 Runtime Monitoring -- 6 Conclusions and Future Work -- References -- Basic Aspects in Redundancy-Based Intrusion Tolerance -- 1 Introduction and Related Work -- 2 Overview of Redundancy-Based Intrusion Tolerance -- 3 Cyber Attack Model -- 4 Categories of System Components Targeted by Attacks -- 5 System Model and Failure Assumptions -- 6 Type of Redundancy -- 7 Final Considerations and Next Steps -- References -- A Survey on the State of the Art of Vulnerability Assessment Techniques -- 1 Introduction -- 2 Vulnerability Detection Techniques -- 2.1 Anomaly Detection-Based Techniques -- 2.2 Vulnerable Code Pattern Recognition -- 2.3 Vulnerability Prediction Models. , 3 Vulnerability Exploitability Forecasting Techniques -- 4 Vulnerability Propagation Models -- 5 Conclusions -- References -- Data Based Message Validation as a Security Cornerstone in Loose Coupling Software Architecture -- 1 Introduction -- 1.1 Related Work -- 2 Context of the Work -- 2.1 Functional Requirements for the Communication Channel -- 2.2 Non-functional Requirements for the Communication Channel -- 3 Architecture of the Communication Channel -- 4 Architecture Validation -- 5 Conclusions -- References -- A Comparative Study of the Most Important Methods for Forecasting the ICT Systems Vulnerabilities -- 1 Introduction -- 2 Methods of Forecasting the ICT Systems Vulnerabilities -- 2.1 Time Series Forecasting Based Models -- 2.2 Artificial Intelligence-Based Models -- 2.3 ICT Vulnerabilities Forecasting -- 3 Conclusions -- References -- Comparison of Safety and Security Analysis Techniques -- 1 Introduction -- 2 Background -- 3 State-of-the-Art -- 3.1 CHASSIS -- 3.2 FMEVA -- 3.3 SAHARA -- 3.4 STPA-Sec -- 4 Applying Safety and Security Analysis Methods on Collaborating Systems -- 4.1 Use Case Definition -- 5 Conclusions and Future Work -- References -- General Track -- A Simple User Guide for Erasmus+ Teaching and Training. The Case of the University of Catania -- 1 Introduction, Approaches, Methodologies and Dataset of the REALISE Project -- 2 Results: The Case Study of the University of Catania -- 3 Conclusions -- References -- Virtual Implementation of Practical Control Subjects as an Alternative to Face-to-Face Laboratory Lessons -- 1 Introduction -- 2 Background -- 3 Case Study -- 3.1 Tank-Level Plant -- 3.2 Control System -- 4 Integration Approach -- 4.1 Virtual Plant with Factory I/O -- 4.2 Interface and Control with Node-RED -- 5 Implemented Solution -- 5.1 Communicating Applications over Modbus TCP -- 5.2 PID Control with Node-RED. , 5.3 Visualization, Analysis and Results.

Note: Intro -- Preface -- Organization -- General Chair -- International Advisory Committee -- Program Committee Chairs -- Program Committee -- Special Sessions -- Machine Learning and Computer Vision in Industry 4.0 -- Program Committee -- Time Series Forecasting in Industrial and Environmental Applications -- Program Committee -- Optimization, Modeling, and Control by Soft Computing Techniques -- Program Committee -- Soft Computing Applied to Renewable Energy Systems -- Program Committee -- Preprocessing Big Data in Machine Learning -- Program Committee -- Tackling Real-World Problems with Artificial Intelligence -- Program Committee -- SOCO 2022 Organizing Committee Chairs -- SOCO 2022 Organizing Committee -- Contents -- Decision Support and Deep Learning -- Anomaly Detection of Security Threats to Cyber-Physical Systems: A Study -- 1 Introduction -- 2 Statistical Analysis -- 3 Literature Analysis -- 3.1 CPS Security Design -- 3.2 Anomaly Detection/Threat Detection in CPS -- 4 Outstanding Challenges -- 5 Conclusions -- References -- Predictive Maintenance for Maintenance-Effective Manufacturing Using Machine Learning Approaches -- 1 Introduction -- 2 State-of-the-Art -- 3 Training/Testing Dataset -- 4 Proposed Methodology -- 4.1 Gradient Boosting Training -- 4.2 Support Vector Machine Training -- 5 Results and Discussion -- 6 Conclusions -- References -- Estimation of Lamb Weight Using Transfer Learning and Regression -- 1 Introduction -- 2 Image Acquisition and Data Preparation -- 3 Proposed Architecture -- 4 Experimental Results -- 5 Conclusions -- References -- UAV Simulation for Object Detection and 3D Reconstruction Fusing 2D LiDAR and Camera -- 1 Introduction -- 2 Related Works -- 3 Simulation Framework -- 4 Proposed Process -- 5 Demonstration and Evaluation -- 6 Conclusions and Perspectives -- References. , A SO2 Pollution Concentrations Prediction Approach Using Autoencoders -- 1 Introduction -- 2 Database -- 3 Methodology -- 4 Results -- 5 Conclusions -- References -- CPU Computation Influence on Energy Consumption Forecasting Activities of a Building -- 1 Introduction -- 2 Methodology -- 3 Case Study and Results -- 3.1 Case Study -- 3.2 Results -- 4 Conclusions -- References -- Python-Based Ecosystem for Agent Communities Simulation -- 1 Introduction -- 2 Related Works -- 3 Proposed Solution -- 3.1 PEAK Multi-agent System Platform -- 3.2 Management -- 4 Case Study -- 5 Conclusion -- References -- Deep Learning Approach for the Prediction of the Concentration of Chlorophyll ɑ in Seawater. A Case Study in El Mar Menor (Spain) -- 1 Introduction -- 2 Area Description and Datasets -- 3 Methods -- 3.1 Artificial Neural Networks -- 3.2 Bayesian Regularized Neural Networks -- 3.3 Long Short-Term Memory Neural Networks -- 3.4 Mutual Information -- 3.5 Minimum-Redundancy-Maximum-Relevance (mRMR) -- 4 Experimental Procedure -- 4.1 Creation of the Lagged Datasets -- 4.2 Forecasting Models -- 5 Results and Discussion -- 6 Conclusions -- References -- Evolutionary Computing -- A Hybrid Discrete Symbiotic Organisms Search Algorithm and List-Based Simulated Annealing Algorithm for Traveling Salesman Problem -- 1 Introduction -- 2 A Discrete Symbiotic Organisms Search Algorithm for TSP -- 2.1 Mutualism Phase -- 2.2 Commensalism Phase -- 2.3 Parasitism Phase -- 3 A List-Based Simulated Annealing Algorithm for TSP -- 4 A Hybrid DSOS-LBSA Algorithm for TSP -- 5 Computational Results and Discussion -- 5.1 Parameter Settings -- 5.2 Computational Results and Analysis -- 6 Conclusion and Future Work -- References -- Estimation of Distribution Algorithms Applied to the Next Release Problem -- 1 Introduction -- 2 Next Release Problem -- 2.1 Related Work. , 2.2 Multi-objective Next Release Problem -- 3 Proposal: Univariate EDAs for the MONRP -- 3.1 MONRP-UMDA -- 3.2 MONRP-PBIL -- 4 Experimental Evaluation -- 4.1 Algorithms -- 4.2 Datasets -- 4.3 Methodology -- 5 Results and Analysis -- 5.1 Best Configurations -- 5.2 Pareto Front Results -- 5.3 Metrics Results -- 6 Conclusions and Future Works -- References -- An Extremal Optimization Approach to the Pairwise Connectivity Critical Node Detection Problem -- 1 Introduction -- 2 Related Work and Problem Formulation -- 3 Extremal Optimization -- 4 Numerical Experiments -- 5 Conclusions -- References -- Neural Networks and Data Mining -- Dimensional Reduction Applied to an Intelligent Model for Boost Converter Switching Operation -- 1 Introduction -- 2 Case Study -- 3 Model Approach -- 3.1 Dataset -- 3.2 Methods -- 3.3 Classification Model -- 3.4 Experiments Description -- 4 Results -- 5 Conclusions and Future Works -- References -- Intuitionistic Fuzzy Sets in J-CO-QL+? -- 1 Introduction -- 2 Background -- 2.1 Classical Fuzzy Sets -- 2.2 Intuitionistic Fuzzy Sets and Relations -- 2.3 Example: Representing Medical Knowledge -- 3 Intuitionistic Fuzzy Sets and J-CO-QL+ -- 3.1 J-CO-QL+ Data Model and Execution Model -- 3.2 J-CO-QL+ Script -- 4 Learned Lessons and Conclusions -- References -- Assessing the Efficient Market Hypothesis for Cryptocurrencies with High-Frequency Data Using Time Series Classification -- 1 Introduction -- 2 Literature Review -- 3 Methods -- 4 Experiments and Results -- 4.1 Datasets Used -- 4.2 Experimental Settings and Performance Measures -- 4.3 Results -- 5 Conclusions -- References -- Blockchain for Supply Chain Traceability with Data Validation -- 1 Introduction -- 2 Related Work -- 3 Blockchain-Based GSC Traceability -- 4 Smart Contract for GSC Traceability -- 5 Smart Contract Implementation and Performance Evaluation. , 6 Conclusions and Future Work -- References -- Compression of Clustered Ship Trajectories for Context Learning and Anomaly Detection -- 1 Introduction -- 2 Background Information -- 2.1 Data Pre-processing and Data Imbalance -- 2.2 Trajectory Clustering -- 2.3 Trajectory Compression -- 3 Proposed Architecture -- 3.1 Data Preparation and Cluster Generation -- 3.2 Compression of Trajectories -- 3.3 Representative Points Extraction -- 4 Results Analysis -- 5 Conclusions and Perspectives -- References -- DR Participants' Actual Response Prediction Using Artificial Neural Networks -- 1 Introduction -- 2 Proposed Methodology -- 3 Case Study -- 4 Results and Discussion -- 5 Conclusion -- References -- Non-linear Neural Models to Predict HRC Steel Price in Spain -- 1 Introduction and Previous Work -- 2 Materials and Methods -- 2.1 Dataset -- 2.2 Non-lineal Neural Models -- 3 Experiments and Results -- 4 Conclusions and Future Work -- References -- Soft Computing Applications -- First Steps Predicting Execution of Civil Works from Georeferenced Infrastructure Data -- 1 Introduction -- 1.1 State of the Art -- 1.2 Research Proposal -- 2 Methodology -- 2.1 Preprocess -- 2.2 Data Analysis -- 2.3 Dataset Generation -- 2.4 Supervised Classification -- 2.5 Evaluation -- 2.6 Results -- 3 Conclusion -- References -- Virtual Sensor to Estimate Air Pollution Heavy Metals Using Bioindicators -- 1 Introduction -- 2 Database -- 3 Methodology -- 4 Results -- 5 Conclusions -- References -- Regression Techniques to Predict the Growth of Potato Tubers -- 1 Introduction -- 2 Previous Work -- 3 Regression Techniques -- 3.1 Multiple Linear Regression -- 3.2 Multilayer Perceptron -- 3.3 Radial-Basis Function Network -- 3.4 Support Vector Machine -- 4 Materials and Methods -- 5 Results and Discussion -- 6 Conclusions and Future Work -- References. , Reliability-Sensitive Optimization for Provision of Ancillary Services by Tempo-Spatial Correlated Distributed Energy Resources -- 1 Introduction -- 2 Multivariate Correlation Modeling -- 2.1 Pair-Copula Construction -- 2.2 D-Vine Copula Structure -- 3 Reliability-Sensitive Optimization -- 3.1 Multivariate Correlation Modeling -- 3.2 Joint Reliability Evaluation Methodology -- 4 Simulation Study -- 5 Conclusion -- References -- Special Session on Machine Learning and Computer Vision in Industry 4.0 -- Predictive Maintenance of ATM Machines by Modelling Remaining Useful Life with Machine Learning Techniques -- 1 Introduction -- 2 Materials -- 3 Methods -- 3.1 Task Definition -- 3.2 Feature Extraction and Selection -- 3.3 Pre-processing -- 3.4 Machine Learning Model -- 3.5 Experimental Procedure -- 4 Results -- 5 PdM Decision Support System for SIMPLE Project -- 6 Conclusions -- References -- The Impact of Content Deletion on Tabular Data Similarity Using Contextual Word Embeddings -- 1 Introduction -- 2 Related Work -- 3 Research Method -- 4 Experiments -- 4.1 Models -- 4.2 Datasets -- 4.3 Results -- 5 Conclusions and Future Work -- References -- Deep Learning-Based Dementia Prediction Using Multimodal Data -- 1 Introduction -- 2 DementiaBank Dataset -- 3 Approach -- 3.1 Audio -- 3.2 Text -- 3.3 Multimodal -- 3.4 Other Approaches -- 4 Evaluation -- 5 Conclusion -- References -- Lightweight Models in Face Attribute Recognition: Performance Under Oclussions -- 1 Introduction -- 2 Related Work -- 3 Description of the System -- 3.1 Models -- 3.2 Datasets -- 4 Experimental Setup -- 4.1 Training -- 4.2 Evaluation -- 5 Evaluation with Masked Faces -- 6 Conclusions and Future Work -- References -- Small Vessel Detection in Changing Seaborne Environments Using Anchor-Free Detectors on Aerial Images -- 1 Introduction -- 2 Related Work -- 2.1 Vessel Detection. , 2.2 Datasets.

Note: Intro -- Preface -- Organization -- CISIS 2021 -- General Chair -- Program Committee Chair -- Program Committee -- CISIS 2022: Special Sessions -- Cybersecurity in Future Connected Societies -- Program Committee -- Cybersecurity and Trusted Supply Chains of ICT -- Program Committee -- Intelligent Solutions for Cybersecurity -- Program Committee -- CISIS 2022 Organizing Committee Chairs -- CISIS 2022 Organizing Committee -- ICEUTE 2022 -- Organization -- General Chair -- Program Committee Chair -- Program Committee -- ICEUTE 2022 Organizing Committee Chairs -- ICEUTE 2022 Organizing Committee -- Contents -- CISIS Applications -- Analysis of Long-Range Forecast Strategies for IoT on Urban Water Consumption Prediction Task -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Dataset -- 3.2 Experiment Design -- 3.3 Machine Learning Algorithms -- 4 Experimental Results -- 5 Conclusion -- References -- Genetic Algorithm Based Aggregation for Federated Learning in Industrial Cyber Physical Systems -- 1 Introduction -- 2 Related Work -- 3 FedGA-ICPS Framework -- 3.1 Industrial CPS -- 3.2 Learning -- 3.3 Election -- 3.4 Aggregation -- 3.5 Broadcasting -- 4 Experimental Results -- 5 Conclusion -- References -- Hand SOS Gesture Detection by Computer Vision -- 1 Introduction -- 2 Problem Description -- 3 Model Architecture -- 4 Model Evaluation -- 5 Conclusions -- References -- Prediction of Smart Energy Meter Network Traffic Features for Anomaly Detection -- 1 Introduction -- 2 Security Risks in Smart Metering Networks -- 3 The Methodology for the SMCN Anomaly/Attack Detection -- 3.1 Detection and Elimination of Outliers, Based on the Isolation Forest Algorithm -- 3.2 Calculation of Multi-step Prediction for Anomaly Detection with 1D CNN -- 4 Experimental Results -- 5 Conclusions -- References. , An Anomaly Detection Approach for Realtime Identification Systems Based on Centroids -- 1 Introduction -- 2 Case of Study -- 2.1 Level Control Plant -- 2.2 System Integration and Its Control Implementation -- 2.3 Dataset -- 3 Methodological Approach -- 3.1 On-Line Identification Stage. Recursive Least Square -- 3.2 Fault Detection Stage -- 4 Experiments and Results -- 5 Conclusions and Future Work -- References -- Powerful Biogeography-Based Optimization Algorithm with Local Search Mechanism for Job Shop Scheduling Problem with Additional Constraints -- 1 Introduction -- 2 Job Shop Scheduling Problem with Time Lags and Single Transport Robot: JSPTL-STR -- 3 Powerful Biogeography-Based Optimization with Local Search Mechanism for Job Shop Scheduling Problem with Time Lags and Single Transport Robot -- 3.1 Habitat Representation -- 3.2 Initialization of Population -- 3.3 Migration Operator -- 3.4 Mutation Operator -- 4 Experimental Results -- 5 Conclusion -- References -- Dimensionality-Reduction Methods for the Analysis of Web Traffic -- 1 Introduction and Previous Work -- 2 Applied Methods -- 2.1 Laplacian Eigenmaps -- 2.2 Isomap -- 2.3 t-Distributed Stochastic Neighbor Embedding -- 2.4 Beta Hebbian Learning -- 3 Dataset -- 4 Results -- 4.1 Dataset 1 -- 4.2 Dataset 2 -- 5 Conclusions and Future Work -- References -- Special Session on Cybersecurity in Future Connected Societies -- About the Fujisaki-Okamoto Transformation in the Code-Based Algorithms of the NIST Post-quantum Call -- 1 Introduction -- 2 Theoretical Background -- 2.1 Security Definitions -- 2.2 Code-Based Encryption -- 3 Modern FO-Like Transformations -- 3.1 Encrypt-with-Hash -- 3.2 Implicit/Explicit Rejection -- 3.3 Definition of the Shared Secret -- 3.4 Additional Hash -- 4 FO Transformation Application in Code-Based Algorithms -- 4.1 Classic McEliece -- 4.2 BIKE -- 4.3 HQC. , 5 Conclusions -- References -- Analysis of Secret Key Agreement Protocol for Massive MIMO Systems -- 1 Introduction -- 2 System Model -- 3 Proposed SKA -- 3.1 Precoding Design -- 3.2 Protocol Design -- 4 Simulation Results -- 4.1 Secrecy Capacity -- 4.2 SKA Complexity -- 5 Conclusion -- References -- Efficient Implementation of Stream Cipher SNOW 3G for Resource-Constrained Devices -- 1 Introduction -- 2 SNOW 3G Description -- 3 Equivalent Binary Model of LFSR in GF(2n) -- 4 Efficient Implementation -- 5 Performance Evaluation -- 6 Conclusions -- References -- State of the Art of Cybersecurity in Cooperative, Connected and Automated Mobility -- 1 Introduction -- 2 CCAM Ecosystem -- 3 Challenges in CCAM Solutions -- 4 CCAM Cybersecurity -- 4.1 Threats and Attack Analysis -- 4.2 Cyberattack Target Examples -- 4.3 Cybersecurity Methodologies in the CCAM Development Process -- 5 Cryptography -- 5.1 Post-quantum Cryptography -- 5.2 Lightweight Cryptography -- 6 Conclusions -- References -- Cryptographic Protocols in Advanced Metering Infrastructures in Smart Grids -- 1 Introduction -- 2 Smart Grids and Advanced Metering Infrastructures -- 3 Security in Advanced Metering Infrastructures -- 4 Cryptographic Protocols to Secure Advanced Metering Infrastructures -- 5 Conclusions -- References -- Special Session on Cybersecurity and Trusted Supply Chains of ICT -- Orchestrator Architecture and Communication Methodology for Flexible Event Driven Message Based Communication -- 1 Introduction -- 2 Related Work -- 3 Communication Principles in Microservices-Based Architectures -- 3.1 Communication Between Microservices -- 3.2 Security -- 3.3 Communication Stages -- 4 Asynchronous Service State Handling -- 5 Orchestrator Architecture -- 5.1 Microservices Lifecycle in BIECO -- 6 Advantages and Disadvantages of This Approach -- 7 Conclusions -- References. , A Comparative Study of Machine Learning Algorithms for the Detection of Vulnerable Python Libraries -- 1 Introduction -- 2 Approach -- 2.1 Data Collection -- 2.2 Feature Extraction -- 2.3 Modelling -- 3 Implementation and Evaluation -- 3.1 Evaluation -- 4 Conclusions -- References -- Evaluation of the Reliability Index of IP Addresses in Reputation Lists -- 1 Introduction -- 2 Materials and Methods -- 2.1 Reputation Lists -- 2.2 IDS - Intrusion Detection System -- 2.3 Implementation -- 2.4 Metrics -- 3 Results -- 4 Conclusions and Further Work -- References -- Forecasting the Number of Bugs and Vulnerabilities in Software Components Using Neural Network Models -- 1 Introduction -- 2 Literature Review -- 3 Neural Network Models -- 4 Data Collection -- 5 Experimental Results -- 6 Conclusions -- References -- Special Session on Intelligent Solutions for Cybersecurity Systems -- Reinforcement Learning Model Free with GLIE Monte-Carlo on Policy Update for Network Topology Discovery -- 1 Introduction -- 2 Markov Decision Process -- 2.1 Preliminaries -- 2.2 MDP for Finding Information in Complex Networks -- 3 Performance Evaluation -- 3.1 Case Study Description -- 3.2 Results -- 4 Conclusion -- References -- Obfuscating LLVM Intermediate Representation Source Code with NSGA-II -- 1 Introduction -- 2 Background -- 3 Problem Definition -- 4 Evolutionary Multi-objective Optimization -- 5 Experimental Setup -- 6 Validation and Experimental Results -- 7 Conclusions and Future Work -- References -- A Deep Learning-Based Approach for Mimicking Network Topologies: The Neris Botnet as a Case of Study -- 1 Introduction -- 2 Background -- 3 Network Topology Generation with Deep Learning -- 3.1 UGR'16 Dataset: The Neris Botnet -- 3.2 Proposed Methodology -- 4 Experimental Design -- 5 Results and Discussion -- 6 Conclusions and Future Work -- References -- ICEUTE. , Evaluating Classifiers' Performance to Detect Attacks in Website Traffic -- 1 Introduction and Previous Work -- 2 Applied Methods -- 2.1 Information Gain -- 2.2 The LASSO -- 2.3 Support Vector Machines -- 2.4 k-Nearest Neighbour -- 3 Dataset on Web Attacks -- 4 Results -- 5 Conclusions and Future Work -- References -- Evaluation of an Interactive Guide for Robotics Self-learning -- 1 Introduction -- 2 Interactive Guide for Robotics Self-learning -- 2.1 Didactic Objectives -- 2.2 Sections -- 3 Results -- 4 Conclusions and Future Works -- References -- Gamifying the Classroom for the Acquisition of Skills Associated with Machine Learning: A Two-Year Case Study -- 1 Introduction -- 2 Gamification in Data Science and Machine Learning -- 3 Development of the Innovation Experience -- 3.1 Objectives -- 3.2 Materials and Methods -- 4 Results -- 4.1 Assessment Questionnaires -- 4.2 Results of the Teaching Innovation Experience -- 5 Conclusions -- References -- Hackathon in Teaching: Applying Machine Learning to Life Sciences Tasks -- 1 Introduction -- 2 Development of the Innovation Experience -- 2.1 Objectives -- 2.2 Materials and Methods -- 3 Results -- 3.1 Knowledge Assessment Questionnaires -- 3.2 Self-assessment -- 3.3 Qualitative Analysis -- 3.4 Results of the Teaching Innovation Experience -- 3.5 Strengths and Weaknesses of the Project -- 4 Conclusions -- References -- Digital Platforms for Education. The Case of e4you -- 1 Introduction -- 2 Materials and Methods -- 2.1 The e4you Platform -- 3 Teacher-Student Interaction. The Environment -- 3.1 Teacher-Platform Interaction -- 3.2 Learner-Platform Interaction -- 4 Main Results of Educacional Interacion -- 5 Conclusions -- References -- 3D Virtual Laboratory for Control Engineering Using Blended Learning Methodology -- 1 Introduction -- 2 Materials and Methods -- 2.1 Background. , 2.2 Virtual Plant with Factory I/O.