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17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022) : Salamanca, Spain, September 5–7, 2022, Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martinez-de-Pison, José Ramón Villar Flecha, Alicia Troncoso Lora, Enrique A. de la Cal, Álvaro Herrero, Francisco Martínez Álvarez, Giuseppe Psaila, Héctor Quintián, Emilio S. Corchado Rodriguez
| 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022) : Salamanca, Spain, September 5–7, 2022, Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martinez-de-Pison, José Ramón Villar Flecha, Alicia Troncoso Lora, Enrique A. de la Cal, Álvaro Herrero, Francisco Martínez Álvarez, Giuseppe Psaila, Héctor Quintián, Emilio S. Corchado Rodriguez |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (676 pages) |
| Disciplina | 929.605 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Industrial engineering Production engineering Computational Intelligence Industrial and Production Engineering |
| ISBN | 3-031-18050-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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. |
| Record Nr. | UNINA-9910627276703321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) : Salamanca, Spain, September 5–7, 2023, Proceedings, Volume 1 / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado
| 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) : Salamanca, Spain, September 5–7, 2023, Proceedings, Volume 1 / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (305 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Industrial engineering Production engineering Computational Intelligence Industrial and Production Engineering |
| ISBN | 3-031-42529-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Deep Learning, Fuzzy Logic and Evolutionary Computation -- Text Classification for Automatic Distribution of Review Notes in Movie Production -- 1 Introduction -- 2 Dataset -- 3 Methodology -- 3.1 Data Cleaning -- 3.2 Label Estimation -- 3.3 Tokenization -- 3.4 Classification -- 4 Experiments and Results -- 5 Conclusions and Future Work -- References -- Extended Rank-Based Ant Colony Optimization Algorithm for Traveling Salesman Problem -- 1 Introduction -- 2 Ant Colony Optimization -- 3 Proposed ACO Algorithm Plus Local Search -- 4 Results -- 5 Conclusions and Future Work -- References -- Multi-scale Neural Model for Tool-Narayanaswamy-Moynihan Model Parameter Extraction -- 1 Introduction -- 2 Materials and Methods -- 2.1 TNM Model and Its Parameters -- 2.2 Multi-scale Convolutional Neural Model -- 2.3 Dataset -- 3 Experiments and Results -- 3.1 Training Details -- 3.2 Evaluation of Multi-scale Neural Model -- 4 Conclusion -- References -- Application of Fuzzy Logic to the Risk Assessment of Production Machines Failures -- 1 Introduction -- 2 Linguistic Values and Its Analysis in Risk Assessment -- 3 Fuzzy FMEA in the Risk Assessment of Production Downtime -- 4 Conclusion -- References -- First Approach of an Intelligent Automatic System for Aircraft Flap/Slat Positioning -- 1 Introduction -- 2 Brief State of the Art -- 3 Description of the Problem Addressed -- 4 Automation of the Flap/Slat Positioning System -- 4.1 General System Architecture -- 4.2 Fuzzy Decision Block -- 5 Simulation Results and Discussion -- 6 Conclusions and Future Works -- References -- Fuzzy Aggregators in Practice: Meta-Model and Implementation -- 1 Introduction -- 2 Background -- 3 Meta-Modeling Fuzzy Aggregators -- 4 Novel Constructs in J-CO-QL+ and Case Study -- 4.1 Case Study.
4.2 Declaring Fuzzy Operator and Fuzzy Aggregators -- 4.3 Soft Querying -- 5 Conclusions -- References -- Machine Learning and Data Mining -- Model-Based Design of the IMO-NMPC Strategy: Real-Time Implementation -- 1 Introduction -- 2 Workflow: From Simulation to Real-Time Execution -- 2.1 Phases -- 3 iMO-NMPC Strategy Implementation -- 4 Experiments -- 4.1 PHASE 3: Simulink Desktop Real-Time Experiments -- 4.2 PHASE 4: Simulink Real-Time Experiments -- 5 Results -- 5.1 SNL1/SNL5 SISO System Simulink Desktop Real-Time -- 5.2 SNL1/SNL5 SISO System Simulink Real-Time (Speedgoat) -- 5.3 SNL1-SNL1 MIMO System Simulink Real-Time (Speedgoat) -- 5.4 SNL1-SNL5 MIMO System Simulink Real-Time (Speedgoat) -- 6 Conclusions -- References -- Hyperspectral Technology for Oil Spills Detection by Using Artificial Neural Network Classifier -- 1 Introduction -- 2 Materials and Methods -- 2.1 Principal Component Analysis (PCA) -- 2.2 Artificial Neural Networks (ANNs) and Bayesian Optimization -- 3 Results and Discussion -- 4 Conclusions -- References -- Neuron Characterization in Complex Cultures Using a Combined YOLO and U-Net Segmentation Approach -- 1 Introduction -- 2 State of the Art -- 3 Materials and Methods -- 3.1 Experimental Setup -- 3.2 Experimental Procedure -- 4 Results and Discussion -- References -- Effectiveness of Quantum Computing in Image Processing for Burr Detection -- 1 Introduction -- 2 Quantum Computing -- 3 Burr Detection -- 4 Proposed Architecture -- 5 Experimental Results -- 6 Conclusions -- References -- Categorization of CoAP DoS Attack Based on One-Class Boundary Methods -- 1 Introduction -- 2 Case Study -- 3 Methods -- 3.1 Approximate Convex Hull -- 3.2 K Nearest Neighborhood -- 3.3 One-Class Support Vector Machine -- 4 Experiments -- 5 Results -- 6 Conclusions and Future Works -- References. TinyNARM: Simplifying Numerical Association Rule Mining for Running on Microcontrollers -- 1 Introduction -- 2 Basic Information -- 2.1 Numerical Association Rule Mining -- 2.2 Classical NARM Using Evolutionary Approaches -- 2.3 TinyML -- 3 TinyNARM -- 4 Experiments and Results -- 4.1 Datasets -- 4.2 Experimental Environment -- 4.3 Results -- 4.4 Discussion -- 5 Conclusion -- References -- Fault Detection in Biological Methanation Process Using Machine Learning: A Comparative Study of Different Algorithms -- 1 Introduction -- 2 Biological Methanation Model and Optimization -- 2.1 Extended Anaerobic Digestion Model (ADM1 ME) -- 2.2 Optimal Operation -- 2.3 ADM1 ME Disturbances and Dataset Generation -- 3 Results and Discussion -- 4 Conclusions and Future Work -- References -- Soft Computing Applications -- Comparative Study of Regression Models Applied to the Prediction of Energy Generated by a Micro Wind Turbine -- 1 Introduction -- 2 Case Study -- 2.1 Sotavento Experimental Bioclimatic House -- 2.2 Dataset -- 3 Applied Methods -- 4 Experiment Setup and Results -- 4.1 Experiments Setup -- 4.2 Metrics -- 4.3 Results -- 5 Conclusions and Future Work -- References -- Comparative Study of Wastewater Treatment Plant Feature Selection for COD Prediction -- 1 Introduction -- 2 Wastewater Treatment Plant Under Study -- 3 Applied Methods -- 3.1 Feature Selection -- 3.2 Regression Techniques -- 4 Experiments and Results -- 4.1 Experiment's Setup -- 4.2 Results -- 4.3 Analysis of Results -- 5 Conclusions and Future Work -- References -- Machine Learning Based System for Detecting Battery State-of-Health -- 1 Introduction -- 2 Case Study -- 3 Materials and Methods -- 3.1 Random Forest -- 3.2 Multilayer Perceptron -- 3.3 K-Nearest Neighbors -- 3.4 Gaussian Process Classifier -- 3.5 Support Vector Classifier -- 4 Experimental Setup -- 5 Results and Analysis. 6 Conclusions and Future Work -- References -- Leveraging Smart Meter Data for Adaptive Consumer Profiling -- 1 Introduction -- 2 Related Work -- 3 Workflow for Adaptive Clustering Pipeline -- 3.1 General Approach -- 3.2 Dataset for Analysis -- 3.3 Description of the Data Pipeline -- 4 Data Analysis -- 4.1 Ground Truth Cluster Selection and Analysis -- 4.2 Cold-Start Analysis -- 5 Conclusions -- References -- Managing Pandemics Through Agent-Based Simulation: A Case Study Based on COVID-19 -- 1 Managing Pandemics: A Challenging Decision-Making Process -- 2 Review of Simulation Tools to Model Pandemics Evolution -- 3 Modelling Pandemics Evolution Through an Agent-Based Model -- 3.1 Disease Spread Modelling -- 3.2 Disease Evolution and Impact on Healthcare System -- 3.3 Modelling Pharmacological and Non-Pharmacological Measures -- 4 Prototype Implementation Based on COVID-19 -- 5 Validation -- 5.1 Baseline Scenario -- 5.2 Comparison of Non-pharmacological Measures and Baseline Scenario -- 6 Conclusions -- References -- Missing Values Imputation for Visualizing the Air Quality Evolution During the COVID-19 Pandemic in Madrid -- 1 Introduction -- 2 Techniques Applied -- 2.1 Imputation and Regression -- 2.2 Visualization -- 3 A Real-Life Case Study -- 4 Experiments and Results -- 5 Conclusions and Future Work -- References -- Special Session 1: Time Series Forecasting in Industrial and Environmental Applications -- Feature Selection Guided by CVOA Metaheuristic for Deep Neural Networks: Application to Multivariate Time Series Forecasting -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Dataset -- 3.2 Models -- 3.3 Evaluation Metric -- 3.4 Optimization Process -- 4 Results and Discussion -- 4.1 Performance Results -- 4.2 Number of Features Analysis -- 4.3 Best and Worst Predictions Analysis -- 5 Conclusions and Future Work -- References. Neuroevolutionary Transfer Learning for Time Series Forecasting -- 1 Introduction -- 2 Our Proposal -- 3 Results -- 4 Conclusions -- References -- Machine Learning Approaches for Predicting Tree Growth Trends Based on Basal Area Increment -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Acquisition -- 3.2 Data Cleaning -- 3.3 Data Transformation -- 3.4 Machine Learning Algorithms -- 3.5 Model Evaluation -- 4 Results -- 4.1 Input Data -- 4.2 Tree Growth Prediction -- 5 Conclusions and Future Work -- References -- Forecasting Greenhouse Temperature Using Machine Learning Models: Optimizing Crop Production in Andalucia -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Experimental Setup -- 3.2 Machine Learning Models -- 4 Results and Discussion -- 4.1 Data Description -- 4.2 Experimental Results -- 5 Conclusions -- References -- Deep Learning and Metaheuristic for Multivariate Time-Series Forecasting -- 1 Introduction -- 2 Methodology -- 2.1 The Proposed Model -- 2.2 Model Training -- 2.3 Model Evaluation -- 3 Results -- 4 Conclusions -- References -- An Approach to Enhance Time Series Forecasting by Fast Fourier Transform -- 1 Introduction -- 2 Background -- 3 Methodology -- 3.1 Dataset -- 3.2 Feature Engineering -- 3.3 Models to Use -- 4 Results and Discussion -- 5 Conclusions -- References -- Comparative Study of Open Source Database Management Systems to Enable Predictive Maintenance of Autonomous Guided Vehicles -- 1 Introduction -- 2 Use Case -- 3 Methodology -- 3.1 Database Management Systems Under Study -- 3.2 Comparison Procedure -- 3.3 Comparison Perspectives -- 4 Experiments and Results -- 4.1 Functional Comparison -- 4.2 Performance Evaluation -- 5 Conclusions and Future Work -- References -- Integrated Forecast and Optimization for Retailer Allocation in a Two-Echelon Inventory System -- 1 Introduction. 2 Related Literature. |
| Record Nr. | UNINA-9910743701003321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) : Salamanca, Spain, September 5–7, 2023, Proceedings, Volume 2 / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado
| 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) : Salamanca, Spain, September 5–7, 2023, Proceedings, Volume 2 / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (376 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Industrial engineering Production engineering Computational Intelligence Industrial and Production Engineering |
| ISBN |
9783031425363
3031425367 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Special Session 2: Technological Foundations and Advanced Applications of Drone Systems -- Level 3 Data Fusion -- 1 Ontological Foundations -- 2 Level 3 Data Fusion -- 3 DNN Implementation -- 3.1 CoA Recognition -- 3.2 Event Prediction -- 3.3 Forensic Assessment -- 4 Modeling Courses of Action -- 4.1 Probability of Action -- 4.2 CoA Utility Modeling -- 4.3 Evaluating Response Effectiveness -- References -- Image Classification Using Contrastive Language-Image Pre-training: Application to Aerial Views of Power Line Infrastructures -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Selection and Processing -- 3.2 Data Labeling and Caption Generation -- 3.3 CLIP Classifier Selection Methodology -- 4 Results and Discussion -- 4.1 Zero-Shot vs. Few-Shot Classifier -- 4.2 CLIP Fine-Tuning -- 4.3 Final model -- 5 Conclusions -- References -- A Realistic UAS Traffic Generation Tool to Evaluate and Optimize U-Space Airspace Capacity -- 1 Introduction -- 2 Realistic UAS Traffic Generation and Specification -- 2.1 Identification of Common UAS Patterns -- 2.2 Traffic Generation Module -- 2.3 Traffic Specification Module -- 3 Validation of the Traffic Generation and Specification Modules -- 4 Next Steps: Towards a Separation Optimization and Evaluation Framework -- 5 Conclusions -- References -- UAV Airframe Classification Using Acceleration Spectrograms -- 1 Introduction -- 2 State of the Art -- 3 Proposed System -- 3.1 UAV Dataset and Spectrogram Generation -- 3.2 Classification Algorithm -- 4 Experiments and Results -- 5 Conclusions -- References -- Tuning Process Noise in INS/GNSS Fusion for Drone Navigation Based on Evolutionary Algorithms -- 1 Introduction -- 2 INS/GNSS -- 3 Tuning Process -- 4 Case Study -- 4.1 Mission Problem and Simulation Configuration -- 4.2 Filter Parameters.
4.3 Optimization Algorithms -- 5 Results -- 5.1 Results Comparison -- 6 Conclusions -- References -- Special Session 3: Soft Computing Methods in Manufacturing and Management Systems -- Digital Twins of Production Systems Based on Discrete Simulation and Machine Learning Algorithms -- 1 Introduction -- 2 Reinforcement Learning -- 3 A Digital Twin Based on Discrete-Event Simulation as a Reinforcement Learning Agent Environment -- 4 Summary -- References -- Edge Architecture for the Integration of Soft Models Based Industrial AI Control into Industry 4.0 Cyber-Physical Systems -- 1 Introduction -- 2 Related Work -- 3 Architecture -- 4 Validation -- 5 Conclusions -- References -- The Use of Line Simplification and Vibration Suppression Algorithms to Improve the Quality of Determining the Indoor Location in RTLSs -- 1 Introduction -- 1.1 Methods and Technologies for Determining Indoor Location -- 2 Decawave as an Example of RTLS Based on UWB Technology -- 3 Algorithms for Improving RTLS Data -- 3.1 Polyline Simplification Algorithms -- 3.2 Location Instability Suppression Algorithm (LISA) -- 4 Research on the Effectiveness of Algorithms -- 4.1 Discussion of Results -- 5 Summary -- References -- Possibilities of Decision Support in Organizing Production Processes -- 1 Introduction -- 2 Industry 4.0 -- 2.1 Technologies of the Industry 4.0 -- 3 Methodology -- 4 Conclusion -- References -- Special Session 4: Efficiency and Explainability in Machine Learning and Soft Computing -- Efficient Short-Term Time Series Forecasting with Regression Trees -- 1 Introduction -- 2 Materials and Method -- 2.1 Dataset -- 2.2 Experimental Setup -- 2.3 Evaluation Procedure -- 3 Results -- 4 Conclusions -- References -- Generating Synthetic Fetal Cardiotocography Data with Conditional Generative Adversarial Networks -- 1 Introduction -- 2 Methodology. 2.1 Conditional Generative Adversarial Networks -- 2.2 Classifiers -- 3 Experiments -- 3.1 Dataset -- 3.2 CGAN Parameter Tuning -- 3.3 Classifiers Hyperparameter and Parameter Tuning -- 4 Results and Discussion -- 5 Conclusions -- References -- Olive Oil Fly Population Pest Forecasting Using Explainable Deep Learning -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 ADL -- 3.2 Benchmark Algorithms -- 3.3 Explainability -- 4 Experimentation and Results -- 4.1 Input Data -- 4.2 Results and Discussion -- 4.3 Explainability -- 5 Conclusions and Future Work -- References -- Explaining Learned Patterns in Deep Learning by Association Rules Mining -- 1 Introduction -- 2 Related Works -- 3 Methodology -- 3.1 Preprocessing -- 3.2 Rules Mining -- 3.3 Calculate Metrics -- 3.4 Classify -- 4 Results and Discussion -- 4.1 Experimental Setting -- 4.2 Metrics -- 4.3 Results -- 5 Conclusions -- References -- Special Session 5: Machine Learning and Computer Vision in Industry 4.0 -- A Deep Learning Ensemble for Ultrasonic Weld Quality Control -- 1 Introduction -- 2 Technology -- 2.1 Manufacturing Process -- 2.2 Deep Learning Models -- 3 Deep Learning Ensemble -- 4 Experimental Results -- 5 Conclusion -- References -- Indoor Scenes Video Captioning -- 1 Introduction -- 2 Related Works -- 2.1 Video Captioning -- 2.2 Indoor Scene Captioning -- 3 Methodology -- 4 Experiments -- 4.1 Charades Dataset -- 4.2 Postprocessing -- 4.3 Setup -- 4.4 Results -- 5 Conclusion -- References -- A Multimodal Dataset to Create Manufacturing Digital Twins -- 1 Introduction -- 2 Related Work -- 2.1 Pose Estimation for Action Recognition -- 3 Experimental Setup and Data Acquisition -- 4 Dataset Discussion -- 4.1 Dataset Top View -- 4.2 Dataset Side View -- 4.3 Dataset Front View -- 5 Datarecords -- 6 Conclusions and Future Work -- References. A Modified Loss Function Approach for Instance Segmentation Improvement and Application in Fish Markets -- 1 Introduction -- 2 Dataset -- 3 Proposed Method -- 4 Experiments and Results -- 4.1 Experimental Setup -- 4.2 Results -- 5 Conclusions -- References -- Parallel Processing Applied to Object Detection with a Jetson TX2 Embedded System -- 1 Introduction -- 2 Methodology -- 3 System Architecture -- 3.1 Software Architecture -- 3.2 Hardware Architecture -- 4 Experimental Results -- 5 Conclusion -- References -- Deep Learning-Based Emotion Detection in Aphasia Patients -- 1 Introduction -- 2 Related Work -- 3 Dataset -- 4 Approach -- 5 Evaluation -- 6 Conclusion -- References -- Defect Detection in Batavia Woven Fabrics by Means of Convolutional Neural Networks -- 1 Introduction and Previous Work -- 2 Related Work -- 3 Case Study -- 4 Methods and Experimentation -- 4.1 Methods -- 4.2 Experimentation -- 5 Results -- 6 Conclusions -- References -- An Image Mosaicing-Based Method for Bird Identification on Edge Computing Devices -- 1 Introduction -- 2 Image Mosaicing-Based Method -- 3 Experiments and Results -- 3.1 Results -- 3.2 Analysis of the Results -- 4 Conclusion -- References -- HoloDemtect: A Mixed Reality Framework for Cognitive Stimulation Through Interaction with Objects -- 1 Introduction -- 2 Related Works -- 3 HoloLens 2 Application -- 3.1 HoloLens 2 API -- 3.2 Implementation Details -- 3.3 Data Collection -- 4 Evaluation of the Proposal -- 4.1 Qualitative Analysis -- 4.2 Quantitative Analysis -- 5 Conclusions -- References -- Accurate Estimation of Parametric Models of the Human Body from 3D Point Clouds -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Obtaining and Preprocessing of the 3D Model. -- 3.2 Estimation of an Intermediate Template Using BPS Neural Network -- 3.3 First Minimization: BPS to SMPL. 3.4 Second Minimization: 3D Scan to SMPL -- 4 Experiments -- 4.1 Datasets and Evaluation Metrics -- 4.2 Results -- 5 Conclusions -- References -- Lightweight Cosmetic Contact Lens Detection System for Iris Recognition at a Distance -- 1 Introduction -- 2 Related Work -- 3 Overview of the IAAD Framework -- 4 The Approach for Cosmetic Contact Lens Detection -- 4.1 BSIF Encoding of an Iris Pattern -- 4.2 Building the Ensemble of Classifiers -- 5 Results -- 5.1 Cross-Dataset Testing -- 6 Conclusions and Future Work -- References -- Vehicle Warning System Based on Road Curvature Effect Using CNN and LSTM Neural Networks -- 1 Introduction -- 2 Road Curvature-Based Dynamics of the Vehicle -- 3 Risky Maneuvers Identification by CNN and LSTM Models -- 3.1 Model's Selection of Variables -- 3.2 Deep Convolutional Neural Network Model -- 4 Results and Discussion -- 5 Conclusions and Future Works -- References -- Special Session 6: Genetic and Evolutionary Computation in Real World and Industry -- Enhancing Time Series Anomaly Detection Using Discretization and Word Embeddings -- 1 Introduction -- 2 Experimental Study -- 2.1 Problem Formulation -- 2.2 Data Preprocessing -- 2.3 Model Architecture -- 2.4 Datasets -- 3 Results -- 4 Conclusions and Future Work -- References -- Multi-objective Optimization for Multi-Robot Path Planning on Warehouse Environments -- 1 Introduction -- 2 Non-Dominated Genetic Algorithm Approach -- 2.1 Route Generation -- 2.2 Initial Population -- 2.3 Crossover -- 2.4 Mutation -- 3 Experimentation Setup -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- On the Prediction of Anomalous Contaminant Diffusion -- 1 Introduction -- 2 Bevilacqua-Galeão (BG) Model and Numerical Solution -- 2.1 BG Model -- 2.2 Numerical Solution -- 2.3 Differential Evolution (DE) Method -- 3 Inverse Problem Formulation -- 4 Results. 4.1 Direct Problem and Case of Study. |
| Record Nr. | UNINA-9910743693003321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
The 19th International Conference on Soft Computing Models in Industrial and Environmental Applications SOCO 2024 : Salamanca, Spain, October 9-11, 2024 Proceedings, Volume 2 / / edited by Héctor Quintián, Emilio Corchado, Alicia Troncoso Lora, Hilde Pérez García, Esteban Jove, José Luis Calvo Rolle, Francisco Javier Martínez de Pisón, Pablo García Bringas, Francisco Martínez Álvarez, Álvaro Herrero Cosío, Paolo Fosci
| The 19th International Conference on Soft Computing Models in Industrial and Environmental Applications SOCO 2024 : Salamanca, Spain, October 9-11, 2024 Proceedings, Volume 2 / / edited by Héctor Quintián, Emilio Corchado, Alicia Troncoso Lora, Hilde Pérez García, Esteban Jove, José Luis Calvo Rolle, Francisco Javier Martínez de Pisón, Pablo García Bringas, Francisco Martínez Álvarez, Álvaro Herrero Cosío, Paolo Fosci |
| Autore | Quintián Héctor |
| Edizione | [1st ed. 2025.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 |
| Descrizione fisica | 1 online resource (336 pages) |
| Disciplina | 006.3 |
| Altri autori (Persone) |
CorchadoEmilio
Troncoso LoraAlicia Pérez GarcíaHilde JoveEsteban Calvo RolleJosé Luis Martínez de PisónFrancisco Javier García BringasPablo Martínez AlvarezFrancisco Herrero CosíoÁlvaro |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Industrial engineering Production engineering Computational Intelligence Industrial and Production Engineering |
| ISBN | 9783031750106 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | -- Part I Special Session: Machine Learning and Computer Vision in Industry 4.0. -- Chapter 1 Computer Vision Based Quality Control for Molding Injection Machines. -- Chapter 2 Towards a comprehensive taxonomy of cobots: A tool for multi-criteria classification. -- Chapter 3 Novel positional encoding methods for neural rendering. -- Chapter 4 Enhancing Object Segmentation via Few-Shot Learning with Limited Annotated Data. -- Chapter 5 Early breast cancer detection by automated analysis of mammograms with deep convolutional networks. -- Chapter 6 Feature Selection for Multi-Label Classification in Predictive Maintenance. -- Chapter 7 Transforming Manufacturing through Human Digital Twins: A New Architectural Approach, etc. |
| Record Nr. | UNINA-9910983046303321 |
Quintián Héctor
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2025 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Hybrid Artificial Intelligent Systems : 18th International Conference, HAIS 2023, Salamanca, Spain, September 5–7, 2023, Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado
| Hybrid Artificial Intelligent Systems : 18th International Conference, HAIS 2023, Salamanca, Spain, September 5–7, 2023, Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, Francisco Martínez Álvarez, Alicia Troncoso Lora, Álvaro Herrero, José Luis Calvo Rolle, Héctor Quintián, Emilio Corchado |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (789 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Artificial Intelligence |
| ISBN | 3-031-40725-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Anomaly and Fault Detection -- One-Class Reconstruction Methods for Categorizing DoS Attacks on CoAP -- Application of anomaly detection models to malware detection in the presence of concept drift -- Identification of anomalies in urban sound data with Autoencoders -- Revisiting Histogram Based Outlier Scores: Strengths and Weaknesses -- Data Mining and Decision Support Systems -- Model performance prediction: a Meta-Learning approach for concept drift detection -- Reinforcing Assessment Processes Using Proactive Case-Based Reasoning Mechanisms -- Meta-Learning for hyperparameters tuning in CNNs for Chest Images -- A Fuzzy Logic Ensemble Approach to Concept Drift Detection -- Multi-Task Gradient Boosting -- Exploratory Study of Data Sampling Methods for Imbalanced Legal Text Classification -- Exploring delay reduction on Edge Computing architectures from a Heuristic approach -- Probability Density Function for Clustering Validation -- Comprehensive analysis of different techniques for data augmentation and proposal of new variants of BOSME & GAN -- Multidimensional Models Supported by Document-Oriented Databases -- Financial Distress Prediction in an Imbalanced Data Stream Environment -- Improving the Quality of Quantum Services Generation Process: Controlling Errors and Noise -- Comparison of deep reinforcement learning path-following system based on road geometry and an adaptive cruise control for autonomous vehicles -- Deep Learning -- A New Hybrid CNN-LSTM for Wind Power Forecasting in Ethiopia -- Companion Classification Losses for Regression Problems -- Analysis of transformer model applications -- Real-time Workflow Scheduling in Cloud with Recursive Neural Network and List Scheduling -- Robust Losses in Deep Regression -- Structure Learning in Deep Multi-Task Models -- Validating by Deep Learning an Efficient Method for Genomic Sequence Analysis: Genomic Spectrograms -- Sentiment Analysis for Vietnamese – Based Hybrid Deep Learning Models -- Optimizing LIME explanations using REVEL Metrics -- Assessing the Impact of Noise on Quantum Neural Networks: An Experimental Analysis -- Varroa mite detection using deep learning techniques -- Evolutionary Computation and Optimization -- Enhancing Evolutionary Optimization Performance under Byzantine Fault Conditions -- A hybrid based genetic algorithm for solving the clustered generalized traveling salesman problem -- Feature Ranking for Feature Sorting and Feature Selection with Optimisation -- Efficient Simulation of Pollutant Dispersion using Machine Learning -- Hybrid Intelligent Parsimony Search in Small High-dimensional Datasets -- An integer linear programming model for team formation in the classroom with constraints -- Improved Evolutionary Approach for Tuning Topic Models with Additive Regularization -- Time ofArrival error characterization for precise indoor localization of Autonomous Ground Vehicles -- Feature Selection based on a Decision Tree Genetic Algorithm -- Exact and Heuristic Lexicographic Methods for the Fuzzy Traveling Salesman Problem -- A Novel Genetic Algorithm with Specialized Genetic Operators for Clustering -- The Analysis of Hybrid Brain Storm Optimisation Approaches in Feature Selection -- HAIS Applications -- Supporting Emotion Recognition in Human-Robot Interactions: An Experimental Italian Textual Dataset -- Hybrid Intelligent Control for Maximum Power Point Tracking of a Floating Wind Turbine -- Statistical Dialog Tracking and Management for Task-oriented Conversational Systems -- A Causally Explainable Deep Learning Model with Modular Bayesian Network for Predicting Electric Energy Demand -- Using Large Language Models for Interpreting Autonomous Robots Behaviors -- Comparative analysis of intelligent techniques for categorization of the operational status of LiFePo4 batteries -- To Enhance Full-Text Biomedical Document Classification through Semantic Enrichment -- Predicting innovative cities using spatio-temporal activity patterns -- Daily accumulative photovoltaic energy prediction using hybrid intelligent model -- Comparison of geospatial trajectory clustering and feature trajectory clustering for public transportation trip data -- Image and Speech Signal Processing -- Adapting YOLOv8 as a vision-based animal detection system to facilitate herding -- Image classification understanding with Model Inspector tool -- Study on Synthetic Video Generation of Embryo Development -- Image reconstruction using Cellular Automata and Neural Networks -- Agents and Multiagents -- Monte-Carlo Tree Search for Multi-Agent Pathfinding: Preliminary Results -- The Problem of Concept Learning and Goals of Reasoning in Large Language Models -- Multi-AgentSystem for Multimodal Machine Learning Object Detection -- Biomedical Applicatons -- Convolutional Neural Networks for Diabetic Retinopathy Grading from iPhone Fundus Images -- Risk factors and survival after premature hospital readmission in frail subjects with delirium -- Generalizing an Improved GrowCut Algorithm for Mammography Lesion Detection -- Coherence of COVID-19 mortality of Spain versus western European countries -- A Feature Selection and Association Rule Approach to Identify Genes Associated with Metastasis and Low Survival in Sarcoma -- Analysis of Frequency Bands in Electroencephalograms for Automatic Detection of Photoparoxysmal Responses -- Textural and shape features for lesion classification in mammogram analysis -- Intent Recognition using Recurrent Neural Networks on Vital Sign Data: A Machine Learning Approach. |
| Record Nr. | UNINA-9910742491303321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Hybrid artificial intelligent systems : 17th International Conference, HAIS 2022, Salamanca, Spain, September 5-7, 2022, proceedings / / Pablo García Bringas (editor)
| Hybrid artificial intelligent systems : 17th International Conference, HAIS 2022, Salamanca, Spain, September 5-7, 2022, proceedings / / Pablo García Bringas (editor) |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (523 pages) |
| Disciplina | 006.3 |
| Collana | Lecture notes in computer science. Lecture notes in artificial intelligence |
| Soggetto topico |
Artificial intelligence
Data mining |
| ISBN | 3-031-15471-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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. |
| Record Nr. | UNISA-996490364203316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Hybrid Artificial Intelligent Systems : 17th International Conference, HAIS 2022, Salamanca, Spain, September 5–7, 2022, Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, José Ramón Villar Flecha, Alicia Troncoso Lora, Enrique A. de la Cal, Álvaro Herrero, Francisco Martínez Álvarez, Giuseppe Psaila, Héctor Quintián, Emilio Corchado
| Hybrid Artificial Intelligent Systems : 17th International Conference, HAIS 2022, Salamanca, Spain, September 5–7, 2022, Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, José Ramón Villar Flecha, Alicia Troncoso Lora, Enrique A. de la Cal, Álvaro Herrero, Francisco Martínez Álvarez, Giuseppe Psaila, Héctor Quintián, Emilio Corchado |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (523 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Social sciences - Data processing Data mining Artificial Intelligence Computer Application in Social and Behavioral Sciences Data Mining and Knowledge Discovery |
| ISBN |
9783031154713
3031154711 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Comparison of Machine Learning Techniques for the Detection of Type-4 PhotoParoxysmal Responses in EEG Signals -- Smartwatch sleep-tracking services precision evaluation using supervised domain adaptation -- Tracking and Classification of Features in the Bio-inspired Layered Networks -- Frailty related survival risks at short and middle term of older adults admitted to hospital -- On the analysis of a real dataset of COVID-19 patients in Alava -- Indoor access control system through symptomatic examination using IoT technology, fog computing and cloud computing -- Measuring the quality information of sources of cybersecurity by multi-criteria decision making techniques -- A case of study with the Clustering R library to measure the quality of cluster algorithms. |
| Record Nr. | UNINA-9910734825603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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International Joint Conference 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022) 13th International Conference on EUropean Transnational Education (ICEUTE 2022) : Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, José Ramón Villar Flecha, Alicia Troncoso Lora, Enrique A. de la Cal, Álvaro Herrero, Francisco Martínez Álvarez, Giuseppe Psaila, Héctor Quintián, Emilio Corchado
| International Joint Conference 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022) 13th International Conference on EUropean Transnational Education (ICEUTE 2022) : Proceedings / / edited by Pablo García Bringas, Hilde Pérez García, Francisco Javier Martínez de Pisón, José Ramón Villar Flecha, Alicia Troncoso Lora, Enrique A. de la Cal, Álvaro Herrero, Francisco Martínez Álvarez, Giuseppe Psaila, Héctor Quintián, Emilio Corchado |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (279 pages) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Computational intelligence
Engineering - Data processing Education Computational Intelligence Data Engineering |
| ISBN | 3-031-18409-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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. |
| Record Nr. | UNINA-9910629283603321 |
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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