
Computational Science - ICCS 2023
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The five-volume set LNCS 14073-14077 constitutes the proceedings of the 23rd International Conference on Computational Science, ICCS 2023, held in Prague, Czech Republic, during July 3-5, 2023.
The total of 188 full papers and 94 short papers presented in this book set were carefully reviewed and selected from 530 submissions. 54 full and 37 short papers were accepted to the main track; 134 full and 57 short papers were accepted to the workshops/thematic tracks.
The theme for 2023, "Computation at the Cutting Edge of Science ", highlights the role of Computational Science in assisting multidisciplinary research. This conference was a unique event focusing on recent developments in scalable scientific algorithms, advanced software tools; computational grids; advanced numerical methods; and novel application areas. These innovative novel models, algorithms, and tools drive new science through efficient application in physical systems, computational andsystems biology, environmental systems, finance, and others.
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Content
- Intro
- Preface
- Organization
- Contents - Part III
- Computational Collective Intelligence
- Balancing Agents for Mining Imbalanced Multiclass Datasets - Performance Evaluation
- 1 Introduction
- 2 Balancing Agents
- 3 Computational Experiment
- 3.1 Experiment Plan
- 3.2 Performance Measures
- 3.3 Experiment Results
- 4 Conclusions
- References
- Decision Tree-Based Algorithms for Detection of Damage in AIS Data
- 1 Introduction
- 2 Related Works
- 3 Problem Formulation
- 4 Proposed Approach for Damage Detection
- 4.1 Anomaly Detection
- 4.2 Detection of Damage in Standalone Clusters
- 4.3 Detection of Damage Inside Proper Clusters
- 5 Computational Experiment
- 5.1 Overview
- 5.2 Results
- 6 Conclusions
- References
- The Role of Conformity in Opinion Dynamics Modelling with Multiple Social Circles
- 1 Introduction
- 2 Related Work
- 3 Conceptual Framework
- 3.1 Multilayer Networks
- 3.2 Continuous Opinions
- 3.3 Authority
- 3.4 Conformity
- 3.5 Openness to New Views
- 3.6 Sociability
- 4 Simulations
- 4.1 Conformism in Multiple Social Circles
- 4.2 Conformism and Other Factors
- 5 Conclusions
- References
- Impact of Input Data Preparation on Multi-criteria Decision Analysis Results
- 1 Introduction
- 2 Methodology
- 3 Results
- 4 Conclusions
- References
- Computational Diplomacy and Policy
- Automating the Analysis of Institutional Design in International Agreements
- 1 Introduction
- 2 Institutional Grammar and Graphs
- 3 Our Prototype
- 3.1 IG Tagger
- 3.2 Graph of Entities Extraction
- 4 Use Case and Impact
- 5 Conclusions
- References
- Modeling Mechanisms of School Segregation and Policy Interventions: A Complexity Perspective
- 1 Introduction
- 2 Features of Complex Systems
- 2.1 Emergence
- 2.2 Self-organization, Adaptation and Robustness
- 2.3 Feedback, Non-linearity and Tipping Points
- 2.4 Path-dependency
- 3 Complexity in the Mechanisms of School Segregation
- 3.1 Distance
- 3.2 School Profile
- 3.3 School Quality
- 3.4 School Assignment
- 3.5 Gatekeeping
- 3.6 Social Network
- 3.7 School Composition
- 4 Modeling School Segregation Dynamics
- 4.1 Agent-Based Models
- 4.2 An Alternative Explanation for Excess School- Relative to Residential Segregation
- 4.3 An ABM of Amsterdam Primary School Choice
- 5 Challenges
- 6 Conclusion
- References
- An Approach for Probabilistic Modeling and Reasoning of Voting Networks
- 1 Introduction
- 2 Fundamental Concepts
- 3 Literature Review
- 4 Methodology
- 4.1 Edge Weighting
- 4.2 Probabilistic Centrality
- 4.3 Political Contextualization
- 5 Experimental Evaluation
- 5.1 Synthetic Data
- 5.2 Real Data
- 6 Conclusion
- References
- An Analysis of Political Parties Cohesion Based on Congressional Speeches
- 1 Introduction
- 2 Theoretical Reference
- 2.1 Natural Language Processing
- 2.2 Clustering
- 3 Related Works
- 4 Methodology
- 4.1 Preliminary Approach
- 4.2 Proposed Approach
- 4.3 Validation of Results
- 5 Experimental Evaluation
- 5.1 Hyper-parameter Optimization and Correlation Analysis
- 5.2 Party Cohesion Analysis
- 6 Conclusion
- References
- Computational Health
- Comparative Study of Meta-heuristic Algorithms for Damage Detection Problem
- 1 Introduction
- 2 Structure of Damage Detection Problem
- 2.1 Damage Detection Modelling
- 2.2 The Objective Function Based on Modal Flexibility
- 3 Instruction to the Optimization Method
- 3.1 Differential Evolution DE
- 3.2 Particle Swarm Optimization PSO
- 3.3 Teaching Learning Based Optimization TLBO
- 3.4 Artificial Bee Colony ABC
- 3.5 Harmony Search HS
- 3.6 Sparrow Search Algorithm SSA
- 3.7 Gaining Sharing Knowledge-Based Algorithm GSK-Ali
- 3.8 Manta Ray Foraging Optimization MRFO
- 3.9 Pathfinder Algorithm PFA
- 4 Experimental Results
- 4.1 Test Setup
- 4.2 Numerical Result
- 5 Conclusions
- References
- Estimation of the Impact of COVID-19 Pandemic Lockdowns on Breast Cancer Deaths and Costs in Poland Using Markovian Monte Carlo Simulation
- 1 Introduction
- 2 Related Work
- 2.1 The Impact of COVID-19 Pandemic on Healthcare
- 2.2 Modelling Progression of the Disease
- 2.3 Costs of Breast Cancer Care
- 3 Methodology
- 4 Results and Discussion
- 5 Conclusion
- References
- Machine Learning for Risk Stratification of Diabetic Foot Ulcers Using Biomarkers
- 1 Introduction
- 2 Methods
- 2.1 Recent and Historical Biomarker Datasets
- 2.2 Machine Learning for Risk Stratification
- 2.3 Understanding Important Biomarkers for Risk Stratification
- 3 Results
- 4 Discussion
- 5 Conclusions
- References
- A Robust Machine Learning Protocol for Prediction of Prostate Cancer Survival at Multiple Time-Horizons
- 1 Introduction
- 2 Materials and Methods
- 2.1 Data
- 2.2 Modelling
- 3 Results and Discussion
- 4 Conclusions and Future Works
- References
- Supervised Machine Learning Techniques Applied to Medical Records Toward the Diagnosis of Rare Autoimmune Diseases
- 1 Introduction
- 2 Objective
- 3 Methods
- 3.1 Database Elaboration
- 3.2 Analysis Software
- 3.3 Classification Algorithms
- 3.4 Quality Metrics
- 4 Results
- 4.1 Training Set
- 4.2 Test Set
- 4.3 Applied Classifiers in the Test Set
- 4.4 Comparison Between Models
- 5 Discussion
- 6 Conclusion
- References
- Handwriting Analysis AI-Based System for Assisting People with Dysgraphia
- 1 Introduction
- 2 Literature Review
- 3 Handwriting Analysis AI-Based System for Dysgraphic Person's Aid
- 3.1 Handwritten Text Detection
- 3.2 Handwritten Text Recognition Model
- 3.3 Spelling Correction
- 3.4 Grammar Correction
- 3.5 Text-to-Speech Conversion
- 4 Experimental Evaluation
- 4.1 The Dataset
- 4.2 Results and Discussion
- 5 Conclusion
- References
- Universal Machine-Learning Processing Pattern for Computing in the Video-Oculography
- 1 Introduction
- 2 Methods
- 2.1 Video Signal Quality Check
- 2.2 Face Detection and Facial Components Estimations
- 2.3 Eye Move Estimations
- 2.4 Experimental Application
- 3 Results
- 4 Discussions
- 5 Conclusions
- References
- RuMedSpellchecker: Correcting Spelling Errors for Natural Russian Language in Electronic Health Records Using Machine Learning Techniques
- 1 Introduction
- 2 Related Works
- 3 Methods
- 3.1 Types of Spelling Errors
- 3.2 Datasets
- 3.3 Algorithm
- 3.4 Implementation
- 3.5 Language Model
- 3.6 Python Package
- 4 Experiments
- 5 Results and Discussion
- 6 Conclusion
- References
- Named Entity Recognition for De-identifying Real-World Health Records in Spanish
- 1 Introduction
- 2 Related Works
- 3 Materials
- 3.1 Galén Texts Annotation
- 3.2 Named Entities
- 3.3 Data Augmentation
- 4 Methods
- 4.1 Recurrent Neural Models
- 4.2 Transformers
- 5 Experiments and Results
- 5.1 NER systems comparison
- 5.2 Metrics for Each NE
- 6 Conclusions
- References
- Discovering Process Models from Patient Notes
- 1 Introduction
- 2 Related Work
- 3 The Mining Process
- 3.1 Unlabelled Event Log Requirements
- 3.2 Text Processing
- 3.3 Calculating Event Positions
- 3.4 Hierarchical Clustering
- 3.5 Labelling the Ontology
- 3.6 Interactive Process Miner
- 4 Use Case
- 5 Conclusion and Future Works
- References
- Knowledge Hypergraph-Based Multidimensional Analysis for Natural Language Queries: Application to Medical Data
- 1 Introduction
- 2 Related Works
- 3 Proposed Approach
- 3.1 xR2RML mappings generation and KHG building module
- 3.2 Reformulation Module
- 3.3 Verification Module
- 3.4 Multidimensional SPARQL Query Treatment Module
- 4 Evaluation and Discussion
- 4.1 Evaluation of the KHG's Completeness
- 4.2 Evaluation of the KHG-Based MDA
- 5 Conclusions and Future Work
- References
- Coupling Between a Finite Element Model of Coronary Artery Mechanics and a Microscale Agent-Based Model of Smooth Muscle Cells Through Trilinear Interpolation
- 1 Introduction
- 2 Methods
- 2.1 Finite Element Model
- 2.2 Agent-Based Model
- 2.3 Coupling AB and FE Simulations
- 2.4 Pressurization Tests
- 2.5 Assessing the Results
- 3 Results
- 4 Discussion
- 5 Conclusions
- References
- Does Complex Mean Accurate: Comparing COVID-19 Propagation Models with Different Structural Complexity
- 1 Introduction
- 2 Methods
- 2.1 Logistic Models
- 2.2 SEIR Models
- 2.3 Accuracy Indicators
- 3 Results
- 4 Discussion
- References
- Multi-granular Computing Can Predict Prodromal Alzheimer's Disease Indications in Normal Subjects
- 1 Introduction
- 2 Methods
- 2.1 Rough Set Implementation of GC
- 3 Results
- 3.1 Statistics
- 3.2 Rules from the General Model (Group1)
- 3.3 Granular Computing for Reference of Group2 Patients
- 3.4 GC Classification for Longitudinal Reference of Early Stages in AD Patients
- 4 Discussion
- References
- Accounting for Data Uncertainty in Modeling Acute Respiratory Infections: Influenza in Saint Petersburg as a Case Study
- 1 Introduction
- 2 Methods
- 2.1 Incidence Data
- 2.2 Modeling Framework
- 2.3 Calibration Algorithm
- 2.4 Forecasting
- 2.5 Uncertainty Quantification
- 3 Experiments and Results
- 3.1 Interval Estimates of Model Parameters
- 4 Model Forecast
- 5 Conclusion
- References
- A Web Portal for Real-Time Data Quality Analysis on the Brazilian Tuberculosis Research Network: A Case Study
- 1 Introduction
- 2 Objectives
- 3 Methods
- 3.1 Scenario: Research Data on TB in Brazil
- 3.2 Use Case: Line Probe Assay (LPA) Project
- 3.3 Knowledge Discovery in Databases Methods
- 3.4 Tools and Technologies
- 4 Results
- 5 Discussion
- 6 Conclusion
- References
- Use of Decentralized-Learning Methods Applied to Healthcare: A Bibliometric Analysis
- 1 Introduction
- 2 Material and Methods
- 2.1 Bibliographic Database
- 2.2 Study Design
- 2.3 Software and Data Analysis
- 2.4 Ethical Considerations
- 3 Results
- 3.1 General Information
- 3.2 Countries
- 3.3 Affiliation and Institutions
- 3.4 Sources and Publications
- 3.5 Authors
- 3.6 Keywords and Concepts
- 4 Discussion
- 5 Conclusion
- References
- Computational Modelling of Cellular Mechanics
- Simulating Initial Steps of Platelet Aggregate Formation in a Cellular Blood Flow Environment
- 1 Introduction
- 2 Initial Platelet Aggregate Formation Model
- 2.1 Conceptual Model Considerations
- 2.2 Model Design and Implementation
- 3 Case Study
- 4 Discussion
- 5 Conclusion
- References
- Estimating Parameters of 3D Cell Model Using a Bayesian Recursive Global Optimizer (BaRGO)
- 1 Introduction
- 2 Bayesian Inference on Population Parameters in Evolutionary Optimization
- 3 Bayesian Recursive Global Optimizer (BaRGO)
- 4 Applications of BaRGO
- 4.1 Estimating Function Parameters in 2D Minimization Problems
- 4.2 Estimating the RBC Model Parameters Using Data from Optical Tweezers Experiment
- 5 Conclusions
- References
- A Novel High-Throughput Framework to Quantify Spatio-Temporal Tumor Clonal Dynamics
- 1 Introduction
- 2 Materials and Methods
- 2.1 Cell Culture
- 2.2 Multicolor Marking
- 2.3 Treatment Assay
- 2.4 The Effect of Fibroblasts on Cell Growth
- 2.5 Imaging
- 2.6 Image Analysis
- 2.7 Model Development
- 3 Results and Discussions
- 4 Conclusions
- References
- Computational Optimization, Modelling and Simulation
- Expedited Metaheuristic-Based Antenna Optimization Using EM Model Resolution Management
- 1 Introduction
- 2 Antenna Optimization. Variable-Resolution Models
- 2.1 EM-driven Design. Problem Formulation
- 2.2 Variable-Resolution EM Models
- 3 Population-Based Optimization with Variable-Fidelity EM Models
- 3.1 Nature-Inspired Algorithms. Generic Structure
- 3.2 Variable-Resolution Model Management
- 4 Demonstration Experiments
- 4.1 Test Cases
- 4.2 Setup and Numerical Results
- 4.3 Discussion
- 5 Conclusion
- References
- Dynamic Core Binding for Load Balancing of Applications Parallelized with MPI/OpenMP
- 1 Introduction
- 2 Dynamic Core Binding (DCB)
- 2.1 Concept of DCB
- 2.2 Binding Policy
- 2.3 Load Balancing Among Nodes
- 3 DCB Library
- 3.1 Interface
- 3.2 Creation of Load-Balanced Communicator
- 4 Numerical Evaluations
- 4.1 Target Application
- 4.2 Environments and Conditions
- 4.3 Effectiveness of the Load-Balancing Among Nodes Using SA
- 4.4 Performance Improvement
- 4.5 Reducing Energy Consumption
- 5 Conclusion
- References
- Surrogate-Assisted Ship Route Optimisation
- 1 Introduction
- 2 Related Research
- 3 Problem Formulation
- 4 Proposed Solution
- 4.1 The Solution Space Representation
- 4.2 Pruning in Simulation and Estimation
- 4.3 Surrogate-Based Performance Measure Estimator
- 4.4 The Algorithm
- 5 Results and Discussion
- 6 Conclusions
- A The Ship Simulation Model
- References
- Optimization of Asynchronous Logging Kernels for a GPU Accelerated CFD Solver
- 1 Introduction
- 2 Description of the FaSTAR Solver
- 2.1 Solver Introduction
- 2.2 Acceleration of the Solver
- 2.3 Asynchronous Execution of Logging Kernels
- 3 Implementation of Mixed Precision Kernels
- 3.1 Single Precision
- 3.2 Half Precision
- 4 Validation and Performance
- 4.1 Description of the Cases
- 4.2 Accuracy Analysis
- 4.3 Performance Analysis
- 5 Conclusion
- References
- Constrained Aerodynamic Shape Optimization Using Neural Networks and Sequential Sampling
- 1 Introduction
- 2 Aerodynamic Shape Optimization
- 2.1 Problem Formulation
- 2.2 Constrained GBO Algorithm with Adjoints
- 2.3 Constrained EGONN Algorithm
- 3 Results
- 4 Conclusion
- References
- Optimal Knots Selection in Fitting Degenerate Reduced Data
- 1 Introduction
- 2 Degenerate Case: First and Last Accelerations Given
- 3 Critical Points for Degenerate Case
- 4 Experiments
- 5 Conclusions
- References
- A Case Study of the Profit-Maximizing Multi-Vehicle Pickup and Delivery Selection Problem for the Road Networks with the Integratable Nodes
- 1 Introduction
- 2 Preliminaries
- 3 Problem Formulation
- 3.1 Correctness
- 3.2 Space Complexity
- 4 Experiment
- 4.1 Simulation Instances Generation
- 4.2 Experimental Setup
- 4.3 Results
- 4.4 Discussion
- 5 Conclusion
- References
- Symbolic-Numeric Computation in Modeling the Dynamics of the Many-Body System TRAPPIST
- 1 Introduction
- 2 Statement of the Problem and Differential Equations of Motion
- 3 Equation of Motion in the Osculating Elements
- 3.1 Extraction of the Perturbing Function
- 3.2 Differential Equations of Motion in Analogues of the Second System of Poincaré variables
- 4 The Secular Part of the Main Part of the Perturbing Function
- 5 Evolutionary Equations
- 5.1 Derivation of Evolution Equations
- 5.2 Transition to Dimensionless Variables
- 6 The Algorithm of Calculations
- 7 Conclusion
- References
- Transparent Checkpointing for Automatic Differentiation of Program Loops Through Expression Transformations
- 1 Introduction
- 1.1 Adjoint Timestepping Checkpointing
- 1.2 Contribution
- 1.3 Use Case: Burgers' Equation
- 2 Design of Checkpointing.jl
- 3 Implementation
- 4 Results
- 5 Conclusion
- References
- Performance of Selected Nature-Inspired Metaheuristic Algorithms Used for Extreme Learning Machine
- 1 Introduction
- 2 Extreme Learning Machine
- 2.1 Classification
- 3 Genetic Extreme Learning Machine
- 4 Nature-Inspired Metaheuristic Algorithms
- 5 Experiments and Results
- 6 Conclusions
- References
- Simulation-Based Optimisation Model as an Element of a Digital Twin Concept for Supply Chain Inventory Control
- 1 Introduction
- 2 Decision Support in Supply Chain Management
- 3 Case Study
- 3.1 Problem Definition
- 3.2 Methods
- 3.3 Data and Input Parameters
- 3.4 Assumptions
- 3.5 Simulation Phase
- 3.6 Verification and Validation
- 4 Results
- 4.1 Simulation-Based Optimisation Scenarios
- 4.2 Discussion
- 4.3 The Concept of Digital Twin in SC Inventory Control
- 5 Conclusions
- References
- Semi-supervised Learning Approach to Efficient Cut Selection in the Branch-and-Cut Framework
- 1 Introduction
- 2 Methods
- 2.1 Cut Evaluation and Data Labelling
- 2.2 Unsupervised Pre-training
- 2.3 Model Architecture
- 2.4 Data Sets
- 2.5 Hyperparameters
- 2.6 Implementation
- 3 Results
- 4 Conclusion
- References
- Efficient Uncertainty Quantification Using Sequential Sampling-Based Neural Networks
- 1 Introduction
- 2 Methods
- 3 Numerical Experiments
- 4 Conclusion
- References
- Hierarchical Learning to Solve PDEs Using Physics-Informed Neural Networks
- 1 Introduction
- 2 Physics-Informed Neural Networks
- 3 Hierarchical PINN
- 3.1 Hierarchical Design of Networks
- 3.2 HiPINN Algorithm
- 4 Numerical Experiments
- 4.1 Poisson Equation
- 4.2 Steady-State Advection-Diffusion Equation
- 5 Discussions and Conclusions
- References
- SPMD-Based Neural Network Simulation with Golang
- 1 Introduction
- 2 Related Work and Baseline Research
- 3 Parallel Neuronal Networks
- 4 Performance Evaluation
- 4.1 Network Configurations
- 4.2 Comparing the Performances
- 5 Findings and Conclusion
- References
- Low-Cost Behavioral Modeling of Antennas by Dimensionality Reduction and Domain Confinement
- 1 Introduction
- 2 Domain-Confined Modeling Using Pre-screening and Dimensionality Reduction
- 2.1 Performance-Driven Modeling
- 2.2 Domain Definition
- 3 Results
- 4 Conclusion
- References
- Real-Time Reconstruction of Complex Flow in Nanoporous Media: Linear vs Non-linear Decoding
- 1 Introduction
- 2 Fluid Flow in 2D Porous Medium
- 2.1 Mathematical Framework for the Velocity Field Reconstruction
- 3 Shallow Neural Decoder
- 4 Least Squares Linear Algorithm
- 5 Monte Carlo Optimization of Gauge Placement
- 6 Conclusion
- References
- Model of Perspective Distortions for a Vision Measuring System of Large-Diameter Bent Pipes
- 1 Introduction
- 2 Description of the Proposed Measuring System
- 3 Mathematical Models of Bent Pipes
- 3.1 Single-Bent Pipe Model
- 3.2 Twice-Bent Pipe Model in One Plane
- 4 Determining the Angle of Bending and Straight Sections of Pipes
- 5 Experimental Research
- 6 Conclusions
- References
- Outlier Detection Under False Omission Rate Control
- 1 Introduction
- 2 FOR Control Procedure
- 2.1 Preliminaries
- 2.2 Control of FOR: Theoretical Results
- 2.3 FOR Control: Empirical Rule
- 2.4 Construction of p-values
- 3 Experimental Setting
- 4 Results
- 5 Conclusions
- References
- Minimal Path Delay Leading Zero Counters on Xilinx FPGAs
- 1 Introduction
- 1.1 Efficient Logic Block Usage on Xilinx FPGAs
- 2 High-Level-Synthesis (HLS) Tools Background
- 3 Description of the LZC Design and Implementation
- 3.1 Demonstration of the Design on a Small-Sized Example
- 4 Results and Discussion
- 5 Conclusion
- References
- Reduction of the Computational Cost of Tuning Methodology of a Simulator of a Physical System
- 1 Introduction
- 2 The Simulation Model and the Simulation Domain Characterization
- 3 Proposed Methodology
- 3.1 Check Simulation - Reality
- 3.2 Simulations Shoot
- 3.3 Set/Get Past Events
- 4 Experience Environment and Experimental Results
- 5 Conclusions and Future Works
- References
- A Hypergraph Model and Associated Optimization Strategies for Path Length-Driven Netlist Partitioning
- 1 Introduction
- 2 Preliminaries
- 2.1 Notations and Definitions
- 2.2 Related Work
- 3 Contributions
- 3.1 Initial Partitioning Based on Breadth-First Search Driven by Vertex Criticality (DBFS)
- 3.2 Initial Partitioning Based on Depth-First Search and Vertex Criticality (DDFS)
- 3.3 FM-Based Local Optimization Heuristic (DKFM)
- 4 Experimental Results
- 4.1 Methdology
- 4.2 Initial Partitioning Algorithms
- 4.3 Refinement Algorithm
- 5 Conclusion and Future Work
- References
- Graph TopoFilter: A Method for Noisy Labels Detection for Graph-Structured Classes
- 1 Introduction
- 2 Related Work
- 3 Problem Definition
- 4 The Algorithm
- 5 Case Study
- 5.1 Data Set
- 5.2 Knowledge Graph
- 5.3 Experiments
- 6 Summary
- References
- Dynamic Data Replication for Short Time-to-Completion in a Data Grid
- 1 Introduction
- 2 State of the Art
- 3 Optimization Method
- 4 Justification and Evaluation
- 5 Results and Conclusions
- 6 Conclusion and Future Work
- References
- Detection of Anomalous Days in Energy Demand Using Leading Point Multi-regression Model
- 1 Introduction
- 2 Leading Points Multi-regression Model
- 2.1 Data
- 2.2 Model, Errors and Variable Selection
- 2.3 Application of the Model
- 3 Analysis of Anomalyous Profiles
- 3.1 Daily Errors of the Model
- 3.2 Identification of Unusual Daily Energy Consumption Profiles
- 4 Summary
- References
- Correction to: Coupling Between a Finite Element Model of Coronary Artery Mechanics and a Microscale Agent-Based Model of Smooth Muscle Cells Through Trilinear Interpolation
- Correction to: Chapter 20 in: J. Mikyska et al. (Eds.): Computational Science - ICCS 2023, LNCS 14075, https://doi.org/10.1007/978-3-031-36024-4_20
- Author Index
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