Anmerkung: Intro -- Preface -- Organization -- Contents -- Data Mining and Knowledge Discovery -- Screening a Case Base for Stroke Disease Detection -- Abstract -- 1 Introduction -- 2 Knowledge Representation and Reasoning -- 3 A Case Study -- 4 Case Based Reasoning -- 5 Conclusions -- Acknowledgments -- References -- SemSynX: Flexible Similarity Analysis of XML Data via Semantic and Syntactic Heterogeneity/Homogeneity Detection -- 1 Introduction -- 1.1 On the Innovativeness of the SemSynX Proposal -- 2 Running Example -- 3 The SemSynX Approach -- 3.1 XML Data Similarity Analysis in SemSynX -- 4 Experimental Results -- 5 Conclusions and Future Work -- References -- Towards Automatic Composition of Multicomponent Predictive Systems -- 1 Introduction -- 2 Related Work -- 3 MCPS Description -- 4 Contribution to Auto-WEKA -- 5 Methodology -- 6 Results and Discussion -- 7 Conclusion and Future Work -- References -- LiCord: Language Independent Content Word Finder -- 1 Introduction -- 2 Related Work -- 3 LiCord: Proposed Framework -- 3.1 NGram Constructor -- 3.2 Function Word Decider -- 3.3 Feature Value Calculator -- 3.4 Classifier Learner -- 4 Experiment -- 4.1 Experiment 1 -- 4.2 Experiment 2 -- 5 Conclusion -- References -- Mining Correlated High-Utility Itemsets Using the Bond Measure -- 1 Introduction -- 2 Preliminaries and Related Work -- 3 The FCHM Algorithm -- 4 Experimental Study -- 5 Conclusion -- References -- An HMM-Based Multi-view Co-training Framework for Single-View Text Corpora -- 1 Introduction -- 2 View Generation -- 3 Co-training with HMM View -- 4 Experiments -- 5 Results -- 6 Conclusions -- References -- Does Sentiment Analysis Help in Bayesian Spam Filtering? -- 1 Introduction -- 2 Related Work -- 2.1 Spam Filtering Techniques -- 2.2 Sentiment Analysis -- 3 Improving Spam Filtering Using Sentiment Analysis -- 3.1 Bayesian Spam Filtering. , 3.2 Sentiment Analysis -- 4 Experimental Results -- 4.1 Bayesian Spam Filtering Experiment -- 4.2 Sentiment Analysis -- 5 Conclusions -- References -- A Context-Aware Keyboard Generator for Smartphone Using Random Forest and Rule-Based System -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Adaptive Keyboard Generator -- 3.1 Data Collection -- 3.2 Data Analysis -- 3.3 User Behavior Pattern Recognition -- 3.4 GUI Generation -- 4 Experimental Results -- 5 Concluding Remarks -- Acknowledgements -- References -- Privacy Preserving Data Mining for Deliberative Consultations -- 1 Introduction -- 2 Privacy Preserving Data Mining for Deliberative Consultations - Literature Review -- 2.1 Levels of Privacy Preserving -- 2.2 Types of Data Partitioning in Privacy Preserving Data Mining -- 2.3 Methods of Data Modification in Privacy Preserving Data Mining -- 2.4 Privacy Preserving Techniques -- 3 Usability of Privacy Preserving Techniques in Deliberative Consultations -- 4 Conclusions and Future Work -- References -- Feature Selection Using Approximate Multivariate Markov Blankets -- 1 Introduction -- 2 Theoretical Foundations -- 2.1 Bivariate Approach for Feature Redundancy -- 2.2 Multivariate Approach -- 3 Data -- 3.1 Synthetic Datasets -- 3.2 UCI Datasets -- 4 Experiments and Results -- 4.1 Synthetic Datasets -- 4.2 UCI Datasets -- 5 Conclusions and Future Works -- References -- Student Performance Prediction Applying Missing Data Imputation in Electrical Engineering Studies Degree -- Abstract -- 1 Introduction -- 2 Case of Study -- 3 The Used Data Imputation Techniques -- 3.1 The MICE Algorithm -- 3.2 The AAA Algorithm -- 3.3 Models Validation -- 4 Results -- 5 Conclusions -- Acknowledgments -- References -- Accuracy Increase on Evolving Product Unit Neural Networks via Feature Subset Selection -- 1 Introduction -- 2 Methodology. , 2.1 Product Unit Neural Networks and Training Procedure -- 2.2 Experimental Design Distribution -- 2.3 Feature Selection -- 3 Proposal Description -- 4 Experimentation -- 5 Results -- 5.1 Results Applying EDD and EDDFS -- 5.2 Results Obtained with State-of-the-art Classifiers -- 6 Conclusions -- References -- Time Series -- Rainfall Prediction: A Deep Learning Approach -- 1 Introduction -- 2 Related Work -- 3 Data Preparation -- 4 Proposed Architecture -- 5 Experiments -- 5.1 Optimizing the Proposed Network Architecture -- 5.2 Evaluation of the Proposed Network -- 6 Conclusions and Future Work -- References -- Time Series Representation by a Novel Hybrid Segmentation Algorithm -- 1 Introduction -- 2 Hybrid Segmentation Algorithm -- 2.1 Summary of the Algorithm -- 2.2 Genetic Algorithm -- 2.3 Local Search -- 3 Experimental Results and Discussion -- 3.1 Time Series Analysed -- 3.2 Experimental Setting -- 3.3 Discussion -- 4 Conclusions -- References -- A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Time Series Forecasting Based on Nearest Neighbours -- 3.2 Algorithm Implementation for Apache Spark -- 4 Results -- 4.1 Datasets Description -- 4.2 Design of Experiments -- 4.3 Electricity Consumption Big Data Time Series Forecasting -- 5 Conclusions -- References -- Active Learning Classifier for Streaming Data -- 1 Introduction and Related Works -- 2 Active Learning Classifier for Data Stream -- 3 Experiments -- 3.1 Goals -- 3.2 Results -- 3.3 Discussion -- 4 Conclusions -- References -- Bio-inspired Models and Evolutionary Computation -- Application of Genetic Algorithms and Heuristic Techniques for the Identification and Classification of the Information Used by a Recipe Recommender -- 1 Introduction -- 2 Specification of the Proposed Genetic Algorithm. , 2.1 Codification -- 2.2 Starting Generation -- 2.3 GA Operators -- 2.4 Fitness Function -- 2.5 Getting the New Generation -- 2.6 Results -- 3 Heuristics -- 4 Conclusions -- References -- A New Visualization Tool in Many-Objective Optimization Problems -- 1 Introduction -- 2 Related Work -- 3 Proposed Tool -- 3.1 Overview Step -- 3.2 Detail Step -- 4 Experimental Results -- 5 Conclusion -- References -- A Novel Adaptive Genetic Algorithm for Mobility Management in Cellular Networks -- 1 Introduction -- 2 Basic Concepts -- 2.1 The Genetic Algorithm -- 2.2 Adaptation Within Evolutionary Algorithms -- 2.3 Studied Adaptation Strategies -- 2.4 Mobility Management in Cellular Networks -- 3 The Proposed Approach -- 3.1 Initialisation -- 3.2 Selection -- 3.3 Reproduction -- 3.4 Evaluation and Replacement -- 4 Experimental Results and Analysis -- 4.1 Numerical Results -- 4.2 Discussion and Interpretation -- 5 Conclusions -- References -- Bio-Inspired Algorithms and Preferences for Multi-objective Problems -- 1 Introduction -- 2 Foundations -- 3 Interactive Algorithms -- 3.1 CI-NSGA-II -- 3.2 CI-SMS-EMOA -- 3.3 CI-SPEA2 -- 4 Performance Indicators -- 4.1 Referential Cluster Variance Indicator -- 4.2 Hull Volume Indicator -- 5 Experimental Results -- 6 Final Remarks -- References -- Assessment of Multi-Objective Optimization Algorithms for Parametric Identification of a Li-Ion Battery Model -- 1 Introduction -- 2 Semi-physical Model for Li-Ion Battery -- 3 Multi-Objective Approach for Semi-physical Models -- 4 Experimental Results -- 4.1 Experimental Setup and Electronic Instrumentation -- 4.2 Statistical Experimental Design -- 4.3 Numerical Results and Discussion -- 5 Conclusion -- References -- Comparing ACO Approaches in Epilepsy Seizures -- 1 Introduction -- 2 FRBC Learning Metaheuristics for ECI -- 2.1 Pittsburg Learning of Generalized FRBC Models. , 2.2 Ant-Miner+ for Learning FRBCs with Michigan Style -- 3 Experimentation and Results -- 3.1 Materials and Methods -- 3.2 Evaluating the Effect of the Partitioning in the ACO Pittsburg Learning and Ant-Miner+ Michigan Approach -- 4 Conclusions and Future Work -- References -- Estimating the Maximum Power Delivered by Concentrating Photovoltaics Technology Through Atmospheric Conditions Using a Differential Evolution Approach -- 1 Introduction -- 2 CPV Technology -- 2.1 Study of Influential Atmospheric Conditions on the Electric Performance of CPV Modules -- 2.2 The Use of SMR and APE Indexes to Characterise the DNI Spectral Distribution -- 3 Experimental Study -- 4 Conclusions -- References -- A Hybrid Bio-inspired ELECTRE Approach for Decision Making in Purchasing Agricultural Equipment -- Abstract -- 1 Introduction -- 2 Agricultural Decision Making and Related Work -- 3 A Hybrid Bio-Inspired ELECTRE Model -- 3.1 Multiple Criteria Decision Making ELECTRE I Model -- 3.2 Application of Bio-Inspired Ranking Method -- 4 Choosing and Decision Making for Agricultural Equipment -- 4.1 Data Collection - Combine Harvester -- 5 Experimental Results -- 5.1 Experimental Results - Combine Harvester -- 5.2 Complete Ranking PROMETHEE II Method - Experimental Results -- 5.3 Discussion on Experimental Results -- 5.4 Experimental Results - Purchasing Irrigation Equipment -- 6 Conclusion and Future Work -- Acknowledgments -- References -- Learning Algorithms -- Evaluating the Difficulty of Instances of the Travelling Salesman Problem in the Nearby of the Optimal Solution Based on Random Walk Exploration -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Travelling Salesman Problem and Instances -- 3.2 Experimental Setup -- 4 Analysis -- 4.1 How Far from the Optimal Fitness? -- 4.2 Area as Metric -- 4.3 Comparison with the Phase Transition Parameter for TSP. , 5 Conclusions and Future Work.

Anmerkung: 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.

Anmerkung: Intro -- Preface -- Organization -- General Chairs -- International Advisory Committee -- Program Committee Chairs -- Program Committee -- Special Sessions -- Soft Computing Methods in Manufacturing and Management Systems -- Sec7 -- Soft Computing Applications in the Field of Industrial and Environmental Enterprises -- Sec9 -- Optimization, Modeling and Control by Soft Computing Techniques -- Sec11 -- Soft Computing in Aerospace, Mechanical and Civil Engineering: New Methods and Industrial Applications -- Sec13 -- SOCO 2019 Organizing Committee -- Contents -- Machine Learning -- Indexes to Find the Optimal Number of Clusters in a Hierarchical Clustering -- 1 Introduction -- 2 Related Work -- 2.1 Clustering Methods -- 2.2 Validation Indexes -- 3 Our Proposal -- 3.1 Implementation -- 4 Experimentation -- 4.1 Working Environment and Datasets -- 4.2 Experimental Results -- 5 Conclusions -- References -- Analysis and Application of Normalization Methods with Supervised Feature Weighting to Improve K-means Accuracy -- 1 Introduction -- 2 Hypothesis and Foundations -- 3 Proposed Two-Stage Methodology for Normalization and Feature Weighting -- 3.1 First Stage: Normalization Methods -- 3.2 Second Stage: Feature Weighting Strategy -- 4 Results -- 5 Conclusions -- References -- Classifying Excavator Operations with Fusion Network of Multi-modal Deep Learning Models -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Video-Based Model -- 3.2 Sensor-Based Model -- 3.3 Fusion Network -- 4 Experiments -- 4.1 Dataset and Experimental Settings -- 4.2 Result Analysis -- 5 Conclusion -- Acknowledgement -- References -- A Study on Trust in Black Box Models and Post-hoc Explanations -- 1 Introduction -- 2 Intelligibility and Trust -- 2.1 Human Subject Studies and Trust Measures -- 2.2 Post-hoc Explanation Approaches -- 3 Method. , 3.1 Participants -- 3.2 Materials -- 3.3 Design -- 3.4 Procedure -- 4 Results -- 4.1 Trust Variables -- 5 Conclusion -- References -- A Study on Hyperparameter Configuration for Human Activity Recognition -- 1 Introduction -- 2 Related Work -- 3 Activity Recognition Overview -- 4 Experimental Results -- 4.1 The PAMAP2 Dataset -- 4.2 Experimental Setup -- 4.3 HAR Accuracy Results -- 4.4 Execution Time and Energy Consumption -- 5 Conclusion -- References -- A Fuzzy Approach for Sentences Relevance Assessment in Multi-document Summarization -- Abstract -- 1 Introduction -- 2 Proposed Method -- 2.1 Preprocessing -- 2.2 Semantic Graph Generation -- 2.3 Graph Merging Process -- 2.4 Concepts Clustering -- 2.5 Fuzzy Relevance Assessment of the Sentences -- 2.6 Summary Construction -- 3 Experimental Results -- 4 Conclusions and Future Works -- Acknowledgments -- References -- Online Estimation of the State of Health of a Rechargeable Battery Through Distal Learning of a Fuzzy Model -- 1 Introduction -- 2 Description of the Proposed Model -- 2.1 IC Curves and Analysis -- 2.2 Proposed Model and Learning Methodology -- 2.3 Fuzzy Rule-Based Model -- 3 Empirical Study -- 3.1 Experimental Setup -- 3.2 Numerical Results -- 4 Concluding Remarks -- References -- A Proposal for the Development of Lifelong Dialog Systems -- 1 Introduction and Related Work -- 2 Statistical Dialog Management Methodologies -- 3 User Intention Modeling -- 4 Emotional State Recognition -- 5 The Enhanced UAH Dialog System -- 6 Experiments -- 7 Conclusions and Future Work -- References -- Smart Cities and IOT -- Real-Time Big Data Analytics in Smart Cities from LoRa-Based IoT Networks -- 1 Introduction -- 2 Related Works -- 3 System Architecture -- 3.1 LoRa Based Infrastructure -- 3.2 JSON Payload Buffering and Preprocessing -- 3.3 Real-Time Environment -- 3.4 Big Data Streaming Engine. , 4 Results -- 4.1 Dataset Construction and Linear Regression Parametrization -- 4.2 Experimental Setup -- 4.3 Analysis -- 5 Conclusions -- References -- Deep Learning in Modeling Energy Cost of Buildings in the Public Sector -- Abstract -- 1 Introduction -- 2 Literature Review -- 3 Data and Sampling -- 4 Methodology -- 5 Results and Discussion -- 6 Conclusion -- Acknowledgments -- References -- Framework for the Detection of Physiological Parameters with Musical Stimuli Based on IoT -- Abstract -- 1 Introduction -- 2 Physiological Parameters, Emotions and External Stimuli -- 2.1 From the Theories of Emotion to Affective Computing -- 2.2 Physiological Parameters and Emotional States -- 2.3 IoT and Biosensors -- 3 Smoodsically. An Overview of the Framework Proposed -- 4 Case Study -- 4.1 EDA and Temperature Results -- 5 Conclusion and Future Work -- Acknowledgments -- References -- Edge Computing Architectures in Industry 4.0: A General Survey and Comparison -- 1 Introduction -- 2 Internet of Things and Edge Computing -- 3 Edge Computing Reference Architectures -- 3.1 FAR-Edge RA -- 3.2 Edge Computing RA 2.0 -- 3.3 Industrial Internet Consortium RA -- 4 Evaluation of the Edge Reference Architectures -- 5 Conclusions and Future Work -- References -- Predictive Maintenance from Event Logs Using Wavelet-Based Features: An Industrial Application -- 1 Introduction -- 2 From Event to Time Functions -- 3 Methods -- 3.1 Wavelets Transform -- 3.2 Random Forest -- 4 Experiments -- 4.1 Predictive Performance -- 4.2 Variable Importance -- 4.3 Observations Proximity -- 5 Discussion and Conclusion -- References -- Building Robust Prediction Models for Defective Sensor Data Using Artificial Neural Networks -- 1 Introduction -- 2 Proposed Approach -- 2.1 NoiseDrop -- 2.2 Input Drop -- 3 Experimental Setup -- 3.1 Data -- 3.2 Results -- 4 Conclusions -- References. , Temporal Data Analysis -- Ensemble Deep Learning for Forecasting 222Rn Radiation Level at Canfranc Underground Laboratory -- 1 Introduction -- 2 Methods and Materials -- 2.1 Convolutional Neural Networks -- 2.2 Seasonal and Trend Decomposition Using Loess -- 2.3 Recurrent Neural Networks -- 2.4 Statistics -- 3 Experimental Results and Models Comparison -- 4 Conclusions -- References -- Search of Extreme Episodes in Urban Ozone Maps -- 1 Introduction -- 2 Methods and Materials -- 2.1 DBSCAN -- 2.2 Distance Metrics -- 3 Experimental Results -- 3.1 Outliers Detection with DBSCAN and L2 Norm -- 3.2 Outliers Detection with DBSCAN and L1-Norm -- 4 Conclusions -- References -- A Novel Heuristic Approach for the Simultaneous Selection of the Optimal Clustering Method and Its Internal Parameters for Time Series Data -- 1 Introduction -- 2 Proposed Harmony Search Algorithm for Optimal Clustering Configuration (HSOCC) -- 2.1 Encoding Solution -- 2.2 Steps of the HSOCC Algorithm -- 3 Simulation Results -- 4 Conclusions and Future Work -- References -- A Hybrid Approach for Short-Term NO2 Forecasting: Case Study of Bay of Algeciras (Spain) -- Abstract -- 1 Introduction -- 2 Area and Data Description -- 3 Methods -- 3.1 LASSO -- 3.2 ANNs -- 4 Experimental Procedure -- 5 Results and Discussion -- 6 Conclusions -- Acknowledgements -- References -- Context-Aware Data Mining vs Classical Data Mining: Case Study on Predicting Soil Moisture -- 1 Introduction -- 1.1 Related Work -- 1.2 Context-Aware DM vs Classical DM Concepts -- 2 Experimental Setup -- 2.1 Description (Reading) of the Existing Data -- 2.2 Preprocessing the Data -- 2.3 Preliminary Decisions Before Implementing the Data Mining Processes -- 3 Experiment Implementation and Results -- 3.1 Classical DM vs CADM Process Implementation -- 3.2 DM vs CADM Results -- 4 Conclusions -- References. , DTW as Alignment Function in the Context of Time Series Balancing -- 1 Introduction -- 2 The Proposal -- 2.1 The TS_SMOTE Algorithm -- 2.2 The Distance Functions and Alignment Issues in Balancing TS Problems -- 2.3 Building an Unaligned Dataset -- 3 Experiments and Results -- 3.1 Materials and Methods -- 3.2 Numerical Results -- 4 Conclusions -- References -- Feature Clustering to Improve Fall Detection: A Preliminary Study -- 1 Introduction -- 2 Peak Detection and Feature Extraction -- 3 Data Modeling and Classification -- 4 Experimental Design -- 4.1 Dataset Description -- 4.2 Cross Validation -- 5 Obtained Results and Discussion -- 6 Conclusions -- References -- Data Generation and Preparation -- Creation of Synthetic Data with Conditional Generative Adversarial Networks -- 1 Introduction -- 2 Methodology -- 2.1 Generative Adversarial Networks -- 2.2 Conditional Adversarial Networks -- 2.3 Dataset -- 2.4 Software and Experimental Setting -- 3 Results -- 3.1 Generating New Credit Card Data with CGANs -- 3.2 Similarity of the Data -- 3.3 Classification Results -- 4 Discussion -- References -- Data Selection to Improve Anomaly Detection in a Component-Based Robot -- 1 Introduction and Previous Work -- 2 Anomaly Detection -- 2.1 Support Vector Machines -- 2.2 Metrics -- 3 Experiments and Results -- 3.1 Dataset -- 3.2 Results on the Whole Dataset -- 3.3 Results on Trial 21 -- 4 Conclusions and Future Work -- References -- Addressing Low Dimensionality Feature Subset Selection: ReliefF(-k) or Extended Correlation-Based Feature Selection(eCFS)? -- 1 Introduction -- 2 Background -- 3 The Proposed Approach -- 4 Experimentation -- 5 Results -- 6 Conclusions -- References -- A Predictive Maintenance Model Using Recurrent Neural Networks -- 1 Introduction -- 2 Background -- 3 Case Study -- 4 LSTM Architecture -- 5 Results -- 5.1 Network Classifier. , 5.2 Regressive Network.

Anmerkung: 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.

Anmerkung: Intro -- Preface -- CISIS 2019 -- Organization -- General Chairs -- International Advisory Committee -- Program Committee Chairs -- Program Committee -- Special Sessions -- From the Least to the Least: Cryptographic and Data Analytics Solutions to Fulfil Least Minimum Privilege and Endorse Least Minimum Effort in Information Systems -- Sec8 -- CISIS 2019 Organizing Committee -- ICEUTE 2019 -- Organization -- General Chairs -- Program Committee Chairs -- Program Committee -- Special Sessions -- Looking for Camelot: New Approaches to Asses Competencies -- Sec17 -- Innovation in Computer Science Education -- Sec19 -- ICEUTE 2019 Organizing Committee -- Contents -- General Track -- Perturbing Convolutional Feature Maps with Histogram of Oriented Gradients for Face Liveness Detection -- Abstract -- 1 Introduction -- 2 Literature Review -- 3 Methodology -- 3.1 Generating Perturbed Feature Maps -- 3.2 CNN Architecture -- 3.3 Training -- 4 Experimental Results and Discussions -- 4.1 Effect of Activation Functions on Perturbed Feature Maps -- 4.2 Intra-database Face Liveness Detection -- 4.3 Cross-Database Face Liveness Detection -- 4.4 Comparison with State-of-the-Art Approaches -- 5 Conclusion and Future Work -- Acknowledgements -- References -- Comparison of System Call Representations for Intrusion Detection -- 1 Introduction -- 2 Related Work -- 3 Comparison of System Call Representations -- 4 Data -- 5 Experiments -- 5.1 Experiment Setup -- 5.2 Evaluation of Results -- 6 Conclusion -- References -- Efficient Verification of Security Protocols Time Properties Using SMT Solvers -- 1 Introduction -- 2 Preliminaries -- 3 SMT-Based Verification -- 4 Experimental Results -- 5 Conclusions -- References -- A Framework of New Hybrid Features for Intelligent Detection of Zero Hour Phishing Websites -- Abstract -- 1 Introduction -- 2 Related Works. , 3 Framework Design -- 3.1 Architecture -- 3.2 Phishing Webpage Predictive Features -- 4 Experiments and Results -- 5 Discussions -- 6 Conclusion -- Acknowledgement -- References -- Mirkwood: An Online Parallel Crawler -- 1 Introduction -- 2 Architecture -- 2.1 Seed Extraction -- 2.2 Environment -- 2.3 Forest -- 2.4 Spider Nest -- 2.5 Spider and Spider Legs -- 2.6 Technologies -- 3 Seed Extraction Autonomous Module -- 3.1 Seed Extraction Process -- 4 Experimental Results -- 4.1 Qualitative Results -- 4.2 Performance Results -- 5 Related Work -- 5.1 Focused Crawlers -- 5.2 General-Purpose Crawlers -- 6 Conclusions and Future Work -- References -- Improving SVM Classification on Imbalanced Datasets for EEG-Based Person Authentication -- 1 Introduction -- 2 New Bias Proposal for Imbalanced Datasets in SVM -- 3 Experiments and Results -- 4 Conclusion and Future Work -- References -- Solving the Test Case Prioritization Problem with Secure Features Using Ant Colony System -- 1 Introduction -- 2 Regression Testing and the Test Case Prioritization Problem: Definitions and Algorithms -- 3 Test Case Prioritization ANT (TCP-ANT) Algorithm -- 3.1 Definitions -- 3.2 Description of the TCP-ANT Algorithm -- 4 Security Perspective of TCP. Numerical Results and Discussions -- 5 Conclusions and Further Work -- References -- Toward an Privacy Protection Based on Access Control Model in Hybrid Cloud for Healthcare Systems -- 1 Introduction -- 2 Related Works -- 3 Our Approach -- 3.1 Policy Structure -- 3.2 Privacy Protection Based on Access Control Model in Hybrid Cloud for Healthcare Systems -- 3.3 The Resolution for Conflict Policy -- 3.4 Algorithm -- 4 Evaluation -- 5 Conclusion -- References -- Video Anomaly Detection and Localization in Crowded Scenes -- 1 Introduction -- 2 Feature Extraction -- 2.1 Optical Flow Estimation -- 2.2 Binary Quantization Map. , 2.3 Partition of the Region -- 2.4 Anomaly Detection -- 3 Experimental Results -- 3.1 Datasets -- 3.2 Comparative Analysis -- 4 Conclusion and Future Works -- References -- Beta Chaotic Map Based Image Steganography -- 1 Introduction -- 2 Related Works -- 3 Proposed Approach -- 3.1 Beta Chaotic Map -- 3.2 Least Significant Bit Technique -- 3.3 Image Hiding Process -- 4 Analysis Results -- 4.1 Histogram Analysis -- 4.2 MSE Test -- 4.3 PSNR Test -- 5 Conclusion -- References -- Deep Wavelet Extreme Learning Machine for Data Classification -- 1 Introduction -- 2 Related Works -- 2.1 Extreme Learning Machine -- 2.2 Wavelet Theory -- 3 Proposed Approach -- 4 Results -- 4.1 Database Description -- 4.2 Results and Discussion -- 5 Conclusion -- References -- Palm Vein Age and Gender Estimation Using Center Symmetric-Local Binary Pattern -- 1 Introduction -- 2 Related Works -- 3 Proposed Palm Vein Based Age and Gender Estimation System -- 3.1 Feature Extraction -- 3.2 Classification -- 4 Experimental Results -- 4.1 Database -- 4.2 Performance Metrics -- 4.3 Evaluation of Feature Extraction Settings -- 4.4 Performances Evaluation -- 5 Conclusion -- References -- Neuro-Evolutionary Feature Selection to Detect Android Malware -- Abstract -- 1 Introduction -- 2 Feature Selection -- 3 Experimental Study -- 3.1 Drebin Dataset -- 3.2 Results -- 4 Conclusions and Future Work -- References -- Improving Blockchain Security Validation and Transaction Processing Through Heterogeneous Computing -- 1 Introduction -- 2 Related Work -- 2.1 The CUDA Framework -- 2.2 Tree Challenges in GPGPU Implementations -- 3 Implementation -- 4 Experimental Results -- 5 Conclusion -- References -- Anomaly Detection on Patients Undergoing General Anesthesia -- 1 Introduction -- 2 Case of Study -- 2.1 Dataset Description -- 3 Applied Techniques to Validate the Proposed Model. , 3.1 Model Approach -- 3.2 One-Class Techniques -- 3.3 Artificial Outlier Generation. The Boundary Value Method -- 4 Experiments and Results -- 4.1 Approximate Convex Hull Classifiers -- 4.2 SVM Classifiers -- 4.3 Artificial Neural Network Autoencoder Classifier -- 5 Conclusions and Future Works -- References -- Special Session: From the Least to the Least: Cryptographic and Data Analytics Solutions to Fulfill Least Minimum Privilege and Endorse Least Minimum Effort in Information Systems -- An Internet Voting Proposal Towards Improving Usability and Coercion Resistance -- 1 Introduction -- 1.1 Related Work -- 1.2 Our Contribution -- 2 Parties and Building Blocks -- 3 Description of Our Protocol -- 3.1 Pre-election Phase -- 3.2 Election Phase -- 3.3 Tallying Phase -- 4 Conclusion and Future Work -- References -- Linearization of Cryptographic Sequences -- 1 Introduction -- 2 Binomial Sequences -- 3 The Generalized Self-shrinking Generator -- 4 Binomial Representation of Generalized Sequences -- 5 Conclusions -- References -- On-the-Fly Testing an Implementation of Arrow Lightweight PRNG Using a LabVIEW Framework -- 1 Introduction -- 2 Related Work -- 3 A Description of the Generator Under Study: Arrow PRNG -- 4 LabVIEW Framework -- 4.1 Real-Time Simulation -- 4.2 On-the-Fly Testing -- 5 Conclusion -- References -- A Novel Construction for Streaming Networks with Delays -- 1 Introduction -- 2 Preliminaries -- 2.1 Burst Erasure Channel -- 3 Convolutional Codes over the Erasure Channel with Low Delay -- 3.1 Burst of Erasures -- 3.2 Our Construction -- 4 Isolated Erasures -- 5 Conclusion -- References -- Hyot: Leveraging Hyperledger for Constructing an Event-Based Traceability System in IoT -- 1 Introduction -- 2 The Hyperledger Initiative -- 3 Hyot -- 4 Conclusions -- References. , Special Session: Looking for Camelot: New Approaches to Asses Competencies -- Data Mining for Statistical Evaluation of Summative and Competency-Based Assessments in Mathematics -- Abstract -- 1 Introduction -- 2 Empirical Data and Methodology -- 2.1 Data Description -- 2.2 Data Mining Methods -- 3 Results from Statistical Analyses -- 3.1 Initial Data Processing -- 3.2 Results from Cluster Analysis -- 3.3 Results from CART Modeling -- 4 Conclusion -- Acknowledgments -- References -- Looking for the Antidote for Contaminated Water: Learning Through an Escape Game -- 1 Looking for the Antidote for Contaminated Water -- 2 Solving the Riddles and Problems -- 2.1 Parabolic Motion -- 2.2 Types of Plastics -- 2.3 Refraction Index -- 2.4 Musical Ladder with Glasses -- 2.5 Metacognition Staircase -- 2.6 Secondary Education Law -- 2.7 Opening the Sixth Padlock -- 3 Innovation Through Breakout -- 4 Discussion -- 5 Evaluation -- 6 Conclusion -- References -- Enhancing Collaborative Learning Through Pedagogical Alignment -- Abstract -- 1 Introduction -- 2 Research Methodology -- 3 Context of Application -- 4 Pedagogical Strategy and Dynamics -- 5 Implementation of the Collaborative Working Group -- 6 Outcomes of the Implementation -- 7 Outcomes of the Academic Performance -- 7.1 Group Performance -- 7.2 Individualized Performance -- 8 Conclusions -- References -- Rules_Math: Establishing Assessment Standards -- 1 What Happens the First Day of a Math Course? -- 2 The New Engineering Paradigm: Competencies-Based Assessment -- 3 Proposal: Definition of Assessment Standards -- 4 Case Study: Written Exam for a Calculus Course -- 4.1 Objectives -- 4.2 Contents -- 4.3 Problem -- 4.4 Multiple Choice Tests -- 4.5 Project -- 5 Conclusions and Future Work -- References -- Evaluate Mathematical Competencies in Engineering Using Video-Lessons -- 1 Introduction. , 2 Description of the Study.

Anmerkung: 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.