Computational Science -- ICCS 2023 : 23rd International Conference, Prague, Czech Republic, July 3-5, 2023, Proceedings. Part I / Ji? ̕Miky?ka, Clľia de Mulatier, Maciej Paszynski, Valeria V. Krzhizhanovskaya, Jack J. Dongarra, Peter M.A. Sloot, editors.

Intro
Preface
Organization
Contents - Part I
ICCS 2023 Main Track Full Papers
Improving the Resiliency of Decentralized Crowdsourced Blockchain Oracles
1 Introduction
2 Related Work
3 Proposed Model
3.1 System Overview
3.2 Agents
3.3 Reputation
3.4 Threat Models
3.5 Rewards
3.6 Evaluation
4 Experiments and Simulation
4.1 Simulation Settings
4.2 Participation Control
4.3 Weighted Voting
4.4 Stratified Voting
5 Discussion
6 Conclusion
References
Characterization of Pedestrian Contact Interaction Trajectories
1 Introduction

2 Datasets
3 Data Analysis
4 Conclusion
References
Siamese Autoencoder-Based Approach for Missing Data Imputation
1 Introduction
2 Related Work
3 Siamese Autoencoder-Based Approach for Imputation
3.1 Deep Autoencoder Architecture
3.2 Custom Loss Function
3.3 Custom Triplet Mining
4 Experimental Setup
5 Results
6 Conclusions
References
An Intelligent Transportation System for Tsunamis Combining CEP, CPN and Fuzzy Logic
1 Introduction
2 Related Work
3 Application Scenario
4 The CEP Event Patterns
5 The Fuzzy Inference System
6 CPN Model

7 Conclusions and Future Work
References
Downscaling WRF-Chem: Analyzing Urban Air Quality in Barcelona City
1 Introduction
2 Data, Materials and Methods
2.1 Case Study
2.2 Model Description, Chemistry and Physics Schemes
3 Experimental Results
3.1 Meteorology Results
3.2 Air Quality Results
4 Conclusions
References
Influence of Activation Functions on the Convergence of Physics-Informed Neural Networks for 1D Wave Equation
1 Introduction
2 Wave Equation
3 Training
4 Numerical Results
5 Experiments
5.1 Parameters Tuning

5.2 Activation Functions
6 Results
7 Conclusions and Future Work
References
Accelerating Multivariate Functional Approximation Computation with Domain Decomposition Techniques
1 Introduction
1.1 Related Work
2 Approach
2.1 Numerical Background
2.2 Shared Knot Spans at Subdomain Interfaces
2.3 Solver Workflow
2.4 Implementation
3 Results
3.1 Error Convergence Analysis
3.2 Real Simulation Datasets
3.3 Parallel Scalability
4 Summary
References
User Popularity Preference Aware Sequential Recommendation
1 Introduction
2 Related Works

2.1 Sequential Recommendation
2.2 Popularity Aware Recommendation
2.3 Contrastive Learning
3 Proposed Method
3.1 Problem Statement
3.2 Basic Model
3.3 Sequential Popularity Perception Module
3.4 Popularity Contrastive Learning Module
3.5 Network Training
4 Experiment
4.1 Datasets
4.2 Baselines
4.3 Implementation Details and Evaluation Metrics
4.4 Performance Comparison
4.5 Performance on Particular Users
4.6 Ablation Study
5 Conclusion
References
Data Heterogeneity Differential Privacy: From Theory to Algorithm
1 Introduction