Computational Science - ICCS 2024

Name: Computational Science - ICCS 2024 | 24th International Conference, Malaga, Spain, July 2-4, 2024, Proceedings, Part VII
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24th International Conference, Malaga, Spain, July 2-4, 2024, Proceedings, Part VII

Leonardo Franco Clélia de Mulatier Maciej Paszynski Valeria V. Krzhizhanovskaya Jack J. Dongarra Peter M. A. Sloot(Editor)

Springer (Publisher)

Published on 28. June 2024

XXIV, 444 pages

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978-3-031-63783-4 (ISBN)

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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

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Content

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 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
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
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 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
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
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 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
1 Introduction
2 Model and Methods
3 Data Sets and Results
3.1 Data and Measures
3.2 Results Analysis
4 Conclusion
References
A Cross-Domain Perspective to Clustering with Uncertainty
1 Introduction
2 Methodology and Approach
3 A Cross-Domain Analysis
4 Discussion
4.1 Overview
4.2 Major Gaps and Challenges
5 Conclusions
References
Direct Solver Aiming at Elimination of Systematic Errors in 3D Stellar Positions
1 Introduction
2 The Astrometric Problem
3 Methods
3.1 The Astrometric Least-Squares Solution
3.2 The Hipparcos, Gaia and JASMINE Astrometric Solutions
3.3 The ARI JASMINE Astrometric Solution
3.4 Approaches to Build a Direct Astrometric Solver
4 Proposed Architecture of the Direct Astrometric Solver
4.1 Matrix Building Module
4.2 Matrix Inversion Module
4.3 Residuals Calculation Module
5 Discussion
6 Conclusion
References
On Estimation of Numerical Solution in Prager&Synge Sense
1 Introduction
2 Prager&Synge Method
3 The Numerical Solution in Prager&Synge Sense
4 The Methods for Approximation of Prager&Synge Solution
4.1 Truncation Error Based Estimation of Prager&Synge Solution
4.2 Approximation Error Based Estimation of the Solution in Prager&Synge Sense
4.3 Nonintrusive Option for Estimation of Prager&Synge Solution
5 Test Problem and Numerical Algorithms
6 The Results of Numerical Tests
7 Conclusion
References
Enhancing Out-of-Distribution Detection Through Stochastic Embeddings in Self-supervised Learning
1 Introduction
2 Related Works
3 Methodology
3.1 Deterministic Self-supervised Learning
3.2 Stochastic Embeddings
3.3 Stochastic Regularization
3.4 Stochastic OOD Detectors
4 Experiments
4.1 Downstream Tasks Evaluation
4.2 OOD Detection
4.3 Ablation Study
5 Conclusions
References
Enhancing the Parallel UC2B Framework: Approach Validation and Scalability Study
1 Introduction
2 State of the Art
3 Software Architectures of Enhanced Parallel UC2B
3.1 Unite and Conquer Approach
3.2 Parallel UC2B Insights
3.3 Algorithm of Enhanced Parallel UC2B
4 Experiments and Analysis
4.1 Validation of the Approach
4.2 Performance Demonstration of the Approach
5 Conclusion
References
Towards Modelling and Simulation of Organisational Routines
1 Introduction
2 Background and Motivation
3 Proposed Data Model for Routine Dynamics
4 Demonstration of Routines Data Model In-Use
4.1 Scikit-learn Development as a Data Source
4.2 Research Replication Using Our Data Model
4.3 Modelling Routines in the scikit-learn OSS project
5 Discussion
5.1 Opportunities for Modelling Routines
5.2 Challenges of Modelling Routines
6 Conclusion
References
Teaching Computational Science
Enhancing Computational Science Education Through Practical Applications: Leveraging Predictive Analytics in Box Meal Services
1 Introduction
2 Related Work
2.1 Meal Box Catering and Online Food Delivery
2.2 Customer Profiling
2.3 Machine Learning and Artificial Neural Networks
3 Materials and Methods
3.1 Dataset
3.2 Machine Learning Algorithms
4 Results
4.1 Environment Setup
4.2 Data Collection and Structure
4.3 Model Performance Evaluation
5 Discussion
5.1 Experiential Learning Opportunities
5.2 Interdisciplinary Collaboration
5.3 Industry Relevance
6 Conclusion
References
Teaching High-performance Computing Systems - A Case Study with Parallel Programming APIs: MPI, OpenMP and CUDA
1 Introduction
2 Related Work
3 Motivations
4 High Performance Computing Systems Course
4.1 Aims, Structure and Scope
4.2 Lecture
4.3 Laboratory Tasks
5 Evaluation
5.1 Methodology
5.2 Computational Task
5.3 Students' Subjective Evaluation of Parallel Programming APIs
5.4 Practical Evaluation of Students' Codes Using Objective Metrics
5.5 Discussion
6 Conclusion and Future Work
References
Evaluating Teacher's Classroom Performance
1 Introduction
2 Students' Perception of Their Own Learning
3 Professor Evaluation and Actual Learning
4 The Illusion of Learning: A Definition of Teaching Fluency
5 Factors Biasing Professor Evaluation. Honesty in Evaluation.
6 Persistence of Professor Evaluation: Correlations Over Time and Across Groups
7 The Relationship Between Professor Evaluation and Their Level of Rigor
8 The Relationship Between Learning, Professor Evaluation, and Grades
9 Does Teacher Evaluation Encourage Poor Teaching Practices? Grade Inflation and Student Work Deflation
10 The Role of Social Media
11 Alternatives for Assessing Teacher Performance in the Classroom: A Tec Model
12 Conclusions
References
Analyzing Grade Inflation in Engineering Education
1 Introduction
2 First Part: A Conversation with ChatGPT
3 Second Part. Traditional Bibliographical Search
3.1 Causes of Grade Inflation
4 Third Part: Recommendations for Controlling Grade Inflation
5 Conclusions
References
Author Index

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Computational Science - ICCS 2024

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