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[null,"1.","Record Nr.",null,"UNINA9910303424403321"]
[null,null,"Titolo",null,"Archiv für Religionspsychologie und Seelenführung"]
[null,null,"Pubbl/distr/stampa",null,"Leipzig : , : Eduard Pfeiffer, , 1929-1936"]
[{"$nulls":4},"Berlin ; , : A. Mitsching"]
[null,null,"Descrizione fisica",null,"1 online resource (3 volumes)"]
[null,null,"Disciplina",null,"200.19"]
[null,null,"Soggetti",null,"Psychology, Religious"]
[{"$nulls":4},"Psychologie religieuse"]
[{"$nulls":4},"psychology of religion"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Periodico"]
[null,"2.","Record Nr.",null,"UNINA9910869171203321"]
[null,null,"Titolo",null,"Computational Science – ICCS 2024 : 24th International Conference, Malaga, Spain, July 2–4, 2024, Proceedings, Part VII / / edited by Leonardo Franco, Clélia de Mulatier, Maciej Paszynski, Valeria V. Krzhizhanovskaya, Jack J. Dongarra, Peter M. A. Sloot"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"9783031637834"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (462 pages)"]
[null,null,"Collana",null,"Lecture Notes in Computer Science, , 1611-3349 ; ; 14838"]
[null,null,"Disciplina",null,"511.3"]
[null,null,"Soggetti",null,"Computer science"]
[{"$nulls":4},"Artificial intelligence"]
[{"$nulls":4},"Computer engineering"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Software engineering"]
[{"$nulls":4},"Computer science - Mathematics"]
[{"$nulls":4},"Theory of Computation"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computer Engineering and Networks"]
[{"$nulls":4},"Software Engineering"]
[{"$nulls":4},"Mathematics of Computing"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Intro -- Preface -- Organization -- Contents - Part VII -- Simulations of Flow and Transport: Modeling, Algorithms and Computation -- Capillary Behaviors of Miscible Fluids in Porous Media: A Pore-Scale Simulation Study -- 1 Introduction -- 2 Methodology -- 2.1 The Network Structure -- 2.2 Numerical Experiments -- 3 Results and Discussion -- 3.1 The Representative Network Size -- 3.2 Capillary Behaviors of Miscible Fluids -- 4 Conclusions -- References -- Numerical Results and Convergence of Some Inf-Sup Stable Elements for the Stokes Problem with Pressure Dirichlet Boundary Condition -- 1 Introduction -- 2 Stokes Problem, Mini Element and Taylor-Hood Element -- 3 Kernel Coercivity, Inf-Sup Stability, Convergence and Open Problem -- 4 Numerical Results -- References -- Unstructured Flux-Limiter Convective Schemes for Simulation of Transport "]
[{"$nulls":4},"Phenomena in Two-Phase Flows -- 1 Introduction -- 2 Mathematical Formulation and Numerical Methods -- 2.1 Transport Equations -- 2.2 Numerical Methods -- 3 Numerical Experiments -- 4 Conclusions -- References -- A Backward-Characteristics Monotonicity Preserving Method for Stiff Transport Problems -- 1 Introduction -- 2 Monotone Backward-Characteristics Scheme for the Convective Term -- 3 Petrov-Galerkin Finite Volume Scheme for the Diffusive Term -- 4 Numerical Results -- 4.1 Slotted Cylinder -- 4.2 Viscous Burgers Equations -- 4.3 Transport in the Loukkos River in Northern Morocco -- 5 Conclusions -- References -- A Three-Dimensional Fluid-Structure Interaction Model for Platelet Aggregates Based on Porosity-Dependent Neo-Hookean Material -- 1 Introduction -- 2 Methodology -- 2.1 Computational Fluid Dynamics -- 2.2 Porosity-Dependent Compressible Neo-Hookean Materials -- 2.3 The Fluid-Structure Coupling -- 3 Results -- 3.1 Compressible Neo-Hookean Parametric Study -- 3.2 FSI Simulation -- 4 Discussion."]
[{"$nulls":4},"5 Conclusion -- References -- Modeling of Turbulent Flow over 2D Backward-Facing Step Using Generalized Hydrodynamic Equations -- 1 Introduction -- 1.1 Generalized Boltzmann Transport Equation (GBE) -- 2 Generalized Hydrodynamic Equations as Governing Equations -- 3 Backward-Facing Step Flow Problem -- 3.1  Numerical Simulations Results -- 4 Conclusions -- References -- Simulation of Droplet Dispersion from Coughing with Consideration of Face Mask Motion -- 1 Introduction -- 2 Numerical Approach -- 2.1 Governing Equations for Fluid Flow -- 2.2 Equation of Motion for Droplets -- 3 Measurement of Face Mask Deformation -- 3.1 Measuring Instrument -- 3.2 Measurement Results -- 4 Simulation of Human Model Wearing Mask -- 4.1 Computational Mesh and Conditions -- 4.2 Result of Fluid Flow Simulation -- 4.3 Result of Droplet Motion Simulation -- 5 Applicational Computation -- 5.1 Transplant Calculation for Dynamic Mask -- 5.2 Setting up the Pushing Wheelchair Scenario -- 5.3 Results of the Pushing Wheelchair Scenario -- 6 Conclusion -- References -- Implementation of the QGD Algorithm Using AMR Technology and GPU Parallel Computing -- 1 Introduction -- 2 Mathematical Model -- 3 QGD Implementation in AMReX -- 3.1 Numerical Algorithm Based on QGD in AMReX -- 3.2 Solver Structure -- 4 Problem Statement -- 5 Results and Discussion -- 5.1 OpenFOAM (rhoCentralFoam and QGDFoam) -- 5.2 AmrQGD Features -- 5.3 Solving Performance -- 6 Conclusion -- References -- Smart Systems: Bringing Together Computer Vision, Sensor Networks, and Artificial Intelligence -- Deep Learning Residential Building Segmentation for Evaluation of Suburban Areas Development -- 1 Introduction -- 2 Related Works -- 3 Methods -- 3.1 Deep Learning Model -- 4 Results -- 4.1 SegFormer Tests on Various Data Sets -- 4.2 SegFormer vs. Other Methods -- 5 Conclusions -- References."]
[{"$nulls":4},"Analysing Urban Transport Using Synthetic Journeys -- 1 Introduction -- 2 Related Works -- 3 System Overview -- 3.1 JourneyGenerator -- 3.2 JourneyDescriber -- 3.3 JourneyAnalyser -- 3.4 Implementation -- 4 Results -- 4.1 Aggregation of Journey Features into Frequent Routes and Distribution Functions -- 4.2 Analysing Spatial Distribution of the Level of Service Features -- 4.3 Adding Spatial Aspects to Travel Mode Choice Modelling -- 4.4 Data Needs of the System -- 5 Conclusions -- References -- LoRaWAN Infrastructure Design and Implementation for Soil Moisture Monitoring: A Real-World Practical Case -- 1 Introduction -- 2 State of the Art -- 3 Methodology -- 4 Proposed Solution -- 4.1 Analysis and Design of the LoRaWAN Network -- 4.2 Implementation of the LoRaWAN Network -- 4.3 Development of the Web Application -- 5 Tests -- 5.1 Functionality Tests -- 5.2 "]
[{"$nulls":4},"Usability Tests -- 5.3 Sensor and LoRaWAN Network Test -- 6 Conclusions -- References -- A Framework for Intelligent Generation of Intrusion Detection Rules Based on Grad-CAM -- 1 Introduction -- 2 Related Work -- 2.1 Intrusion Detection System -- 2.2 Intelligent Intrusion Detection Rule Generation -- 3 Methodology -- 3.1 Data Processing -- 3.2 TextCNN Model Training -- 3.3 Grad-Cam Based Analysis -- 3.4 Sensitive Words Aggregation -- 3.5 Regular Expression Design and Rule Formulation -- 4 Experiments Evaluation -- 4.1 Datasets -- 4.2 Experimental Environment and Other Configurations -- 4.3 Evaluation Metrics -- 4.4 Evaluation Results and Discussion -- 5 Conclusion and Future Work -- References -- BotRGA: Neighborhood-Aware Twitter Bot Detection with Relational Graph Aggregation -- 1 Introduction -- 2 Related Work -- 2.1 Graph Neural Network -- 2.2 Twitter Bot Detection -- 3 Methodology -- 3.1 Overview -- 3.2 Feature Encoding -- 3.3 Graph Construction -- 3.4 Relational Graph Aggregation."]
[{"$nulls":4},"3.5 Semantic Fusion Networks -- 3.6 Learning and Optimization -- 4 Experiments -- 4.1 Dataset -- 4.2 Baselines and Experiment Setting -- 4.3 Main Results -- 4.4 Ablation Study -- 4.5 Generalization Study -- 4.6 Representation Learning Study -- 5 Conclusion and Future Work -- References -- SOCXAI: Leveraging CNN and SHAP Analysis for Battery SOC Estimation and Anomaly Detection -- 1 Introduction -- 2 Related Work -- 3 A Glimpse at Times Series -- 4 Convolutional Neural Network-Based Model for Battery SOC Estimation -- 4.1 Dataset -- 4.2 Data Preprocessing -- 4.3 Model Architecture -- 4.4 Explaining Predictions -- 5 Experimental Evaluation -- 5.1 Experimental Protocol -- 5.2 Results -- 6 Conclusion and Perspectives -- References -- Towards Detection of Anomalies in Automated Guided Vehicles Based on Telemetry Data -- 1 Introduction -- 2 Related Works -- 3 Anomaly Detection Based on AGV Telemetry Data -- 3.1 Data in Intralogistics Systems -- 3.2 Overview of the Methodology -- 3.3 Anomalies Caused by Mechanical Problems -- 3.4 Anomalies Caused by Tire and Wheel Damage -- 4 Datasets -- 4.1 Test Drives with Changing Payload Weight -- 4.2 Distorted Natural Navigation Data -- 5 Experimental Validation -- 5.1 Detecting Potential Mechanical Wear or Excessive Friction -- 5.2 Detecting Problems with Wheels -- 6 Discussion and Conclusions -- References -- Analysis of Marker and SLAM-Based Tracking for Advanced Augmented Reality (AR)-Based Flight Simulation -- 1 Introduction -- 2 Related Works -- 3 Materials and Methods -- 3.1 Camera Calibration -- 3.2 Experimental Setup -- 4 Result and Discussion -- 4.1 Quantitative Assessment of Tracking Systems -- 5 Conclusion -- References -- Automated Prediction of Air Pollution Conditions in Environment Monitoring Systems -- 1 Introduction -- 1.1 Motivation and Goal -- 1.2 Literature Review -- 2 The Proposed Solution."]
[{"$nulls":4},"2.1 Proposed Architecture of the Models -- 2.2 A Sample Implementation -- 3 Results -- 3.1 First Scenario: Base Scenario -- 3.2 Second Scenario: Meteorological Data Scenario -- 3.3 Third Scenario: Weather Forecast Improvement Scenario -- 3.4 Fourth Scenario: Spatial Dependencies Improvement Scenario -- 3.5 Comparison -- 3.6 Forecasting Visualization -- 4 Summary and Future Work -- 4.1 Designed Models and Methods -- 4.2 Improvements -- References -- Chaos: Moving Chaos Engineering to IoT Devices -- 1 Introduction -- 1.1 Challenges -- 1.2 Contribution -- 2 Related Work -- 2.1 IoT Faults Taxonomy -- 2.2 Operating Systems for IoT -- 3 Chaos Tool Concept -- 3.1 IoT Faults Modeling -- 3.2 Chaos Tool Design -- 3.3 Data Faults Injection -- 3.4 Hardware Faults Injection -- 3.5 Software Faults Injection -- 4 Use Case and Evaluation -- 4.1 Temperature -- 4.2 "]
[{"$nulls":4},"Acceleration -- 4.3 Battery Measurement -- 4.4 CPU Usage -- 4.5 Memory Consumption -- 5 Summary -- References -- Enhancing Lifetime Coverage in Wireless Sensor Networks: A Learning Automata Approach -- 1 Introduction -- 2 Theoretical Background -- 2.1 Learning Automata -- 2.2 Related Work -- 3 Automata-Based Approach to the WSN Lifetime Optimization -- 4 Experimental Study -- 5 Conclusion -- References -- Solving Problems with Uncertainties -- A Rational Logit Dynamic for Decision-Making Under Uncertainty: Well-Posedness, Vanishing-Noise Limit, and Numerical Approximation -- 1 Introduction -- 1.1 Research Background -- 1.2 Objectives and Contributions -- 2 Formulation and Analysis -- 2.1 Rational Logit Dynamic -- 2.2 Well-Posedness and Stability -- 2.3 Numerical Discretization -- 3 Application -- 4 Conclusion -- Appendix -- References -- Fragmented Image Classification Using Local and Global Neural Networks: Investigating the Impact of the Quantity of Artificial Objects on Model Performance."]
[{"$nulls":4},"1 Introduction."]
[null,null,null,"Sommario/riassunto","The 7-volume set LNCS 14832 – 14838 constitutes the proceedings of the 24th International Conference on Computational Science, ICCS 2024, which took place in Malaga, Spain, during July 2–4, 2024. The 155 full papers and 70 short papers included in these proceedings were carefully reviewed and selected from 430 submissions. They were organized in topical sections as follows: Part I: ICCS 2024 Main Track Full Papers; Part II: ICCS 2024 Main Track Full Papers; Part III: ICCS 2024 Main Track Short Papers; Advances in High-Performance Computational Earth Sciences: Numerical Methods, Frameworks and Applications; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Part IV: Biomedical and Bioinformatics Challenges for Computer Science; Computational Health; Part V: Computational Optimization, Modelling, and Simulation; Generative AI and Large Language Models (LLMs) in Advancing Computational Medicine; Machine Learning and Data Assimilation for Dynamical Systems; Multiscale Modelling and Simulation; Part VI: Network Models and Analysis: From Foundations to Artificial Intelligence; Numerical Algorithms and Computer Arithmetic for Computational Science; Quantum Computing; Part VII: Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks, and Artificial Intelligence; Solving Problems with Uncertainties; Teaching Computational Science."]