Computational Science - ICCS 2023

Name: Computational Science - ICCS 2023 | 23rd International Conference, Prague, Czech Republic, July 3-5, 2023, Proceedings, Part I
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23rd International Conference, Prague, Czech Republic, July 3-5, 2023, Proceedings, Part I

Jirí Mikyska Clélia de Mulatier Maciej Paszynski Valeria V. Krzhizhanovskaya Jack J. Dongarra Peter M.A. Sloot(Herausgeber*in)

Springer (Verlag)

Erschienen am 28. Juni 2023

XXI, 699 Seiten

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978-3-031-35995-8 (ISBN)

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Inhalt

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
2 Related Work
3 Preliminaries
3.1 Notations and Assumptions
3.2 Differential Privacy
4 Sharper Utility Bounds for DP-SGD
5 Performance Improving DP-SGD
5.1 Influence Function and Error Analysis
5.2 Performance Improving DP-SGD
5.3 Privacy Guarantees
5.4 Utility Analysis
6 Comparison with Related Work
7 Experimental Results
8 Conclusions
References
Inference of Over-Constrained NFA of Size k+1 to Efficiently and Systematically Derive NFA of Size k for Grammar Learning
1 Introduction
2 The NFA Inference Problem
2.1 Notations
2.2 A ``Meta-model''
2.3 Some Previous Models
3 k_NFA Extensions
3.1 Building a (k+1)_NFA from a k_NFA
3.2 (k+1)_NFA+ Extension
3.3 k_NFA Extension
3.4 Complexity
4 Properties of the Extensions
4.1 (k+1)_NFA+
4.2 (k+1)_NFA
5 Experimentation
5.1 Context for Reproductibility
5.2 Simplified Models
5.3 Results and Discussions
6 Conclusion
References
Differential Dataset Cartography: Explainable Artificial Intelligence in Comparative Personalized Sentiment Analysis
1 Introduction
2 Background
2.1 Personalization in NLP
2.2 Explainable AI
3 Datasets
4 Personalized Architectures
5 HumAnn
6 Differential Data Maps
7 Experimental Setup
8 Results
9 Conclusions and Future Work
References
Alternative Platforms and Privacy Paradox: A System Dynamics Analysis
1 Introduction
2 Theoretical Background
2.1 Privacy as a Social Issue
2.2 Social Theory Based Explanations of the Privacy Paradox
3 A System Dynamics Model of the Privacy Paradox
3.1 Problem Articulation and Dynamic Hypothesis
4 Model Development
4.1 Model Structure
4.2 Model Parameters
4.3 Model Testing and Validation
5 Simulation Results
5.1 Simulation Experiment 1
5.2 Simulation Experiment 2
5.3 Simulation Experiment 3
6 Concluding Discussion
References
The First Scientiffic Evidence for the Hail Cannon
1 Introduction
2 Experimental Verification
3 Numerical Simulations
4 IGA-ADS Simulation of the Hail Cannon
5 Conclusion and Future Work
References
Constituency Parsing with Spines and Attachments
1 Introduction
2 Headed Constituencies
3 The Dataset
4 Proposed Parsing Technique
4.1 Spines
4.2 Spine Based Parsing
5 Parser Architecture
6 Related Work
7 Evaluation
8 Conclusions
References
Performing Aerobatic Maneuver with Imitation Learning
1 Introduction
2 Related Work
3 Data Analysis
3.1 Maneuvers Description
3.2 Evaluation Metrics
3.3 Maneuvers Evaluation
4 Controllers Training
4.1 Results
4.2 Discussion of Results
5 Circuit Controller
6 Conclusion
References
An Application of Evolutionary Algorithms and Machine Learning in Four-Part Harmonization
1 Introduction
1.1 State of the Art
1.2 Contribution
2 Soprano Harmonization Problem
3 Algorithmic Approach
3.1 Genetic Algorithm
3.2 Bayesian Network
3.3 Hybrid Algorithm
4 Test Results
5 Conclusions
References
Predicting ABM Results with Covering Arrays and Random Forests
1 Introduction
2 Related Work
3 Approach
3.1 Heatbugs Model
3.2 Choosing Parameters via Covering Arrays
3.3 Machine Learning
4 Experimental Setup
4.1 Data Gathering and Preparation
4.2 Machine Learning in All Experiments
5 Results
5.1 Experiment A: Low Unhappiness and Low Variation
5.2 Experiment B: Steady Unhappiness
5.3 Experiment C: Average Unhappiness
5.4 Feature Importance
6 Conclusions
References
Vecpar - A Framework for Portability and Parallelization
1 Introduction
2 State of the Art and Related Work
3 Proposed Approach
4 Evaluation
4.1 BabelStream Benchmark
4.2 Vecpar Internal Benchmark
4.3 Track Reconstruction Use Cases
5 Conclusions and Future Work
References
Self-supervised Deep Heterogeneous Graph Neural Networks with Contrastive Learning
1 Introduction
2 Related Work
2.1 Heterogeneous Graph Neural Networks
2.2 Contrastive Learning
3 Preliminary
4 The Proposed DHG-CL Model
4.1 Node Transformation
4.2 Cross-Layer Semantic Encoder
4.3 Graph-Based Contrastive Learning
5 Experiments
5.1 Experimental Setup
5.2 Node Classification
5.3 Node Clustering
5.4 Visualization
5.5 Variant Analysis
5.6 Parameter Analysis
6 Conclusion and Future Work
References
First-Principles Calculation to N-type Beryllium Related Co-doping and Beryllium Doping in Diamond
1 Introduction
2 Calculation Methods
3 Results and Discussion
3.1 Impurity Formation Energy (Ef)
3.2 Ionization Energies
3.3 Electronic Structure
3.4 Band Structure
4 Conclusions
References
Machine Learning Detects Anomalies in OPS-SAT Telemetry
1 Introduction
2 Materials and Methods
2.1 Dataset
2.2 Detecting OPS-SAT Anomalies Using Machine Learning
3 Experimental Validation
3.1 Experiment 1: Exploiting Original Training Dataset
3.2 Experiment 2: Augmenting Training Datasets
4 Conclusions and Future Work
References
Wildfire Perimeter Detection via Iterative Trimming Method
1 Introduction
2 Thermal Infrared Image of a Wildfire
3 Delaunay Triangulation and Iterative Trimming
3.1 Delaunay Triangulation
3.2 Iterative Trimming Method
4 Results and Discussion
4.1 Iterative Trimming Method
4.2 Canny Edge Detector
4.3 Graph-Cut Method
4.4 Level Set Method
5 Conclusions
References
Variable Discovery with Large Language Models for Metamorphic Testing of Scientific Software
1 Introduction
2 State of the Art
3 Discovering I/O Variables with an LLM
3.1 LLM-Based Workflow
3.2 Prompt Construction and LLM Particulars
4 Evaluation
4.1 Ground Truth and Experiment Setup
4.2 Results
4.3 Discussion and Threats to Validity
5 Conclusion and Future Work
References
On Irregularity Localization for Scientific Data Analysis Workflows
1 Introduction
2 Motivation and Background
2.1 General Framework for Outcome-Preserving Input Reduction
3 Instantiation of the General Framework
4 Investigated Reduction Strategies
4.1 Baseline (Leave-One-Out)
4.2 Delta Debugging (dd-min)
4.3 Probabilistic Delta Debugging (prob-dd)
4.4 Similarity-Based Isolation (similarity-iso)
5 Evaluation
5.1 Experimental Setup
5.2 Results
5.3 Summary and Threats to Validity
6 Related Work
7 Conclusion and Future Work
References
RAFEN - Regularized Alignment Framework for Embeddings of Nodes
1 Introduction
2 Related Work
3 The Proposed RAFEN Framework
4 Experimental Setup
4.1 Datasets
4.2 Node Embeddings
4.3 Aligned Models
4.4 Link Prediction
5 Results
5.1 Embeddings Aggregation Method Comparison
5.2 Comparison of RAFEN's -Based Variants
5.3 RAFEN Comparison to Baselines
6 Conclusion and Future Work
References
CLARIN-Emo: Training Emotion Recognition Models Using Human Annotation and ChatGPT
1 Introduction
2 Related Work
3 Datasets
3.1 CLARIN-Emo: Human Texts and Annotations
3.2 Stockbrief-GPT: Human Texts Annotated by ChatGPT
3.3 ChatGPT-Emo: ChatGPT Texts and Annotations
4 Models
4.1 Sequential Sentence Classification
4.2 Text Classification
5 Experiments
5.1 Sequential Sentence Classification
5.2 Text Classification
6 Results
7 Conclusions and Future Work
References
B2-FedGAN: Balanced Bi-directional Federated GAN
1 Introduction
2 Related Work
3 Bi-directional FedAvg Based Balanced GAN for Learning Process
4 Experimental Setup
4.1 Data Collection
4.2 Results
5 Conclusion
References
Graph-Level Representations Using Ensemble-Based Readout Functions
1 Introduction
2 Related Work
2.1 Graph Neural Networks
2.2 Graph-Level Prediction
3 Graph Neural Network Readouts
3.1 Problem Statement
3.2 Non-parametrized Readout Functions
3.3 Parametrized Readout Functions
3.4 Ensemble Readouts
4 Experiments
4.1 Datasets
4.2 Evaluation Protocol
4.3 Results
5 Conclusion
References
Parallel Adjoint Taping Using MPI
1 Introduction
2 Notation and Foundations
3 Serial Adjoint Reversal of Evolution
3.1 Reversal of Serial Evolution
4 Parallel Adjoints of Evolution
4.1 Parallel Reversal Procedure
4.2 Run Time Analysis
5 Case Study: Lorenz Attractor
6 Case Study: Parallel Taping in OpenFOAM
7 Summary and Outlook
References
A Moral Foundations Dictionary for the European Portuguese Language: The Case of Portuguese Parliamentary Debates
1 Introduction
2 Related Work
3 European Portuguese Moral Foundations Dictionary
3.1 Semi-supervised Translation of the English MFD
3.2 Experimental Validation
4 Morality in the Portuguese Assembly of the Republic, a Case Study
4.1 Parliamentary Transcripts
4.2 Measuring Moral Load
4.3 Political Analysis
5 Conclusions
References
Towards Automatic Generation of Digital Twins: Graph-Based Integration of Smart City Datasets
1 Introduction
2 Motivation
3 Formal Background
3.1 Spatially-Triggered Graph Transformations
3.2 Notations
4 Solution Outline
4.1 OpenStreetMap Graph Generation
4.2 Sensor Modelling
4.3 Sensor Assignment
4.4 Traffic Flow Modelling
5 Conclusions and Future Work
References
Forecasting Cryptocurrency Prices Using Contextual ES-adRNN with Exogenous Variables
1 Introduction
2 Data and Forecasting Problem
3 Model
3.1 Main Track
3.2 Context Track
4 Experimental Study
5 Conclusions
References
Enhanced Emotion and Sentiment Recognition for Empathetic Dialogue System Using Big Data and Deep Learning Methods
1 Introduction
2 Terabot - A Therapeutic Dialogue System
2.1 Sentiment and Emotion Classification
3 Datasets
3.1 CORTEX Dataset
3.2 Common Crawl Dataset
4 Experiments
4.1 Improving the Classification Model
4.2 Dataset Expansion Process
5 Results and Discussion
5.1 Impact of Improved Language Model
5.2 Impact of Extended Training Dataset
6 Conclusions
References
Automatic Delta-Adjustment Method Applied to Missing Not At Random Imputation
1 Introduction
2 Related Work
3 Automatic Delta-Adjustment Method
4 Experimental Setup
5 Results
6 Conclusions
References
Data Integration Landscapes: The Case for Non-optimal Solutions in Network Diffusion Models
1 Introduction
2 Background and Related Work
3 Data Integration Landscapes
3.1 Entity Resolution
3.2 Graph Resolution
3.3 Multiple Resolution Functions
4 Probability Assignment
5 Experiment
5.1 Instantiation
5.2 Dataset
5.3 Model
5.4 Results
6 Conclusions
References
Excessive Internet Use in the Organizational Context: A Proposition of the New Instrument to Measure Cyberloafing at Work
1 Introduction
1.1 Dimensionality of Cyberloafing
1.2 Antecedents and Consequences of Cyberloafing
2 Method
2.1 Participants and Procedure
2.2 Measures
3 Results
3.1 Factor Structure and Reliability of the CBLS-15 Measure
3.2 Cyberloafing and Work-Related Characteristics
4 Discussion
4.1 Practical Implications
4.2 Limitations and Future Directions
5 Conclusions
References
FAIR-FATE: Fair Federated Learning with Momentum
1 Introduction
2 Related Work
3 Problem Statement
3.1 Federated Learning and Momentum
3.2 Fairness Metrics
3.3 Objective
4 FAIR-FATE: Fair Federated Learning with Momentum
5 Experiments
5.1 Datasets
5.2 Non-identical Client Data
5.3 Implementation and Setup Details
5.4 Experimental Results
6 Conclusion and Future Work
References
Multi-agent Cellular Automaton Model for Traffic Flow Considering the Heterogeneity of Human Delay and Accelerations
1 Introduction
2 Model
2.1 Parameters
2.2 Limiting Distances
2.3 Dynamics
2.4 Agents Behaviour
3 Numerical Results
4 Conclusion
References
A Contrastive Self-distillation BERT with Kernel Alignment-Based Inference
1 Introduction
2 Related Work
3 Method
3.1 Early Exit
3.2 Classification Loss
3.3 Contrastive Loss
3.4 Distillation Loss
3.5 Total Loss
3.6 Centered Kernel Alignment
4 Experiments
4.1 Experimental Results on GLUE and ELUE
4.2 Ablation Study
4.3 Parameter Analysis
5 Conclusion
References
Turning Flight Simulation with Fluid-Rigid Body Interaction for Flying Car with Contra-Rotating Propellers
1 Introduction
2 Numerical Approach
2.1 Governing Equations
2.2 Moving Computational Domain Approach
2.3 Coupled Simulation with Rigid Body
3 Flight Simulation of eVTOL Flying Car
3.1 Computational Model
3.2 Control Model
3.3 Flight Condition
4 Result and Discussion
5 Conclusions
References
Combining Outlierness Scores and Feature Extraction Techniques for Improvement of OoD and Adversarial Attacks Detection in DNNs
1 Introduction
2 Related Work
3 Method
3.1 Different Categories of OoD Detection Methods
3.2 Feature Extraction
3.3 Proposed Ensemble OoD Detector
4 Experiments and Results
4.1 OoD Detection Problem
4.2 Attacks
4.3 Sensitivity Analysis
4.4 Limitations
5 Conclusion
References
From Online Behaviours to Images: A Novel Approach to Social Bot Detection
1 Introduction
2 Related Work
3 Useful Notions
3.1 Digital DNA
3.2 Convolutional Neural Networks
4 From Digital DNA to Images
5 Datasets
5.1 Cresci-2017
5.2 Cresci-Stock 2018
5.3 TwiBot20
6 Experiments and Results
7 Conclusions
References
Linking Scholarly Datasets-The EOSC Perspective
1 Introduction
2 The EOSC and Open Scholarly Datasets
2.1 The EOSC and the EOSC Future Project
2.2 Scholarly Datasets
3 Related Work
4 The OARGLink Framework-Problem Statement and General Idea
5 Data Processing Flow in the OARGLink
6 The OARGLink Customization
6.1 Linking Samples of the OARG and AminerNetwork
6.2 Linking Samples of the OpenAIRE and MAG
7 The Overall Results and Their Verification
8 Discussion
9 Summary and Future Work
References
Memory-Efficient All-Pair Suffix-Prefix Overlaps on GPU
1 Introduction
2 Background and Related Work
3 Methodology
4 GPU Implementation
4.1 Overview
4.2 Sorting and Searching in Hybrid-Memory
5 Results
5.1 Datasets and Testbed
5.2 Execution Times
5.3 Scalability
5.4 Comparison of Execution Times with Other Tools
6 Conclusions
References
Ensemble Based Learning for Automated Safety Labeling of Prescribed Fires
1 Introduction
2 QUIC-Fire Output Data
3 Feature Definitions
4 Automatic Labeling Algorithm
4.1 Postprocessing of QUIC-Fire Output
4.2 Process of Automatic Labeling
5 Optimization
6 Numerical Results
6.1 Ensemble Based Learning
6.2 Automated Safety Labeling
6.3 Re-evaluation of Manual Labeling
6.4 Further Improvements
7 Conclusions
References
SLAM Methods for Augmented Reality Systems for Flight Simulators
1 Introduction
2 Materials and Methods
3 Results and Discussion
4 Conclusion
References
Improving the Performance of Task-Based Linear Algebra Software with Autotuning Techniques on Heterogeneous Architectures
1 Introduction
2 The Chameleon Library
3 Self-optimization Methodology
3.1 Selecting the Search Strategy
3.2 Training the Routines
3.3 Validating the Methodology
4 Experimental Study
4.1 Selecting the Routine Parameters
4.2 Selecting the System and Scheduling Parameters
4.3 Validating the Methodology
5 Conclusions
References
Tempo and Time Signature Detection of a Musical Piece
1 Introduction
1.1 Related Work
1.2 Contribution
2 Tempo and Time Signature Detection Method
3 Quantitative Experiments
3.1 Dataset
3.2 Effectiveness Evaluation Criteria
3.3 Tempo Detection
3.4 Time Signature Detection
4 Conclusions and Future Work
References
Correction to: Alternative Platforms and Privacy Paradox: A System Dynamics Analysis
Correction to: Chapter "Alternative Platforms and Privacy Paradox: A System Dynamics Analysis" in J. Mikyska et al. (Eds.): Computational Science - ICCS 2023, LNCS 14073, https://doi.org/10.1007/978-3-031-35995-8_12
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