LEADER 00995cam0 2200253 450 001 E600200004088 005 20210528071147.0 010 $a1841133361 100 $a20040901d2002 |||||ita|0103 ba 101 $aeng 102 $aUS 200 1 $aBetweeen competition and free movement$ethe economic constitutional law of the European Community$fJulio Baquero Cruz 210 $aOxford-Portland (Oregon)$cHart$d2002 215 $aXXVIII, 176 p.$c24 cm 700 1$aBaquero Cruz$b, Julio$3A600200027481$4070$0281622 801 0$aIT$bUNISOB$c20210528$gRICA 850 $aUNISOB 852 $aUNISOB$jFondo|Cofin$m121969 912 $aE600200004088 940 $aM 102 Monografia moderna SBN 941 $aM 957 $aFondo|Cofin$b000736$gSI$d121969$hCofin$racquisto$1catenacci$2UNISOB$3UNISOB$420040901083008.0$520210528071147.0$6Spinosa$fPer le modalità di consultazione vedi homepage della Biblioteca link Fondi 996 $aBetweeen competition and free movement$91673973 997 $aUNISOB LEADER 13764nam 22007455 450 001 9910743693003321 005 20250626164219.0 010 $a9783031425363 010 $a3031425367 024 7 $a10.1007/978-3-031-42536-3 035 $a(MiAaPQ)EBC30724508 035 $a(Au-PeEL)EBL30724508 035 $a(DE-He213)978-3-031-42536-3 035 $a(PPN)272266094 035 $a(CKB)28112515600041 035 $a(OCoLC)1396447537 035 $a(EXLCZ)9928112515600041 100 $a20230830d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$a18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) $eSalamanca, Spain, September 5?7, 2023, Proceedings, Volume 2 /$fedited 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 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (376 pages) 225 1 $aLecture Notes in Networks and Systems,$x2367-3389 ;$v750 311 08$aPrint version: 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) Cham : Springer,c2023 9783031425356 320 $aIncludes bibliographical references. 327 $aSpecial 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. 327 $a4.3 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. 327 $a2.1 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. 327 $aA 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. 327 $a3.4 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. 327 $a4.1 Direct Problem and Case of Study. 330 $aThis book of Advances in Intelligent and Soft Computing contains accepted papers presented at SOCO 2023 conference held in the beautiful and historic city of Salamanca (Spain) in September 2023. Soft computing represents a collection or set of computational techniques in machine learning, computer science, and some engineering disciplines, which investigate, simulate, and analyze very complex issues and phenomena. After a through peer-review process, the 18th SOCO 2023 International Program Committee selected 61 papers which are published in these conference proceedings and represents an acceptance rate of 60%. In this relevant edition, a particular emphasis was put on the organization of special sessions. Seven special sessions were organized related to relevant topics such as: Time Series Forecasting in Industrial and Environmental Applications, Technological Foundations and Advanced Applications of Drone Systems, Soft Computing Methods in Manufacturing and ManagementSystems, Efficiency and Explainability in Machine Learning and Soft Computing, Machine Learning and Computer Vision in Industry 4.0, Genetic and Evolutionary Computation in Real World and Industry, and Soft Computing and Hard Computing for a Data Science Process Model. The selection of papers was extremely rigorous to maintain the high quality of the conference. We want to thank the members of the Program Committees for their hard work during the reviewing process. This is a crucial process for creating a high-standard conference; the SOCO conference would not exist without their help. 410 0$aLecture Notes in Networks and Systems,$x2367-3389 ;$v750 606 $aComputational intelligence 606 $aIndustrial engineering 606 $aProduction engineering 606 $aComputational Intelligence 606 $aIndustrial and Production Engineering 615 0$aComputational intelligence. 615 0$aIndustrial engineering. 615 0$aProduction engineering. 615 14$aComputational Intelligence. 615 24$aIndustrial and Production Engineering. 676 $a006.3 702 $aGarci?a Bringas$b Pablo 702 $aPe?rez Garci?a$b Hilde 702 $aMartínez de Pisón$b Francisco Javier 702 $aMarti?nez Alvarez$b Francisco 702 $aTroncoso Lora$b Alicia 702 $aHerrero$b Alvaro 702 $aCalvo Rolle$b Jose? Luis 702 $aQuintia?n$b He?ctor 702 $aCorchado$b Emilio 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910743693003321 996 $a18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023)$94240936 997 $aUNINA