Computational Science - ICCS 2021 21st International Conference, Krakow, Poland, June 16-18, 2021, Proceedings, Part I
The six-volume set LNCS 12742, 12743, 12744, 12745, 12746, and 12747 constitutes the proceedings of the 21st International Conference on Computational Science, ICCS 2021, held in Krakow, Poland, in June 2021.*The total of 260 full papers and 57 short papers presented in this book set were carefully...
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| Main Authors | , , , , |
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| Format | eBook Conference Proceeding |
| Language | English |
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Springer International Publishing AG
2021
Springer International Publishing |
| Edition | 1 |
| Series | Lecture Notes in Computer Science |
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| Abstract | The six-volume set LNCS 12742, 12743, 12744, 12745, 12746, and 12747 constitutes the proceedings of the 21st International Conference on Computational Science, ICCS 2021, held in Krakow, Poland, in June 2021.*The total of 260 full papers and 57 short papers presented in this book set were carefully reviewed and selected from 635 submissions. 48 full and 14 short papers were accepted to the main track from 156 submissions; 212 full and 43 short papers were accepted to the workshops/ thematic tracks from 479 submissions. The papers were organized in topical sections named:Part I: ICCS Main TrackPart II: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Biomedical and Bioinformatics Challenges for Computer SciencePart III: Classifier Learning from Difficult Data; Computational Analysis of Complex Social Systems; Computational Collective Intelligence; Computational HealthPart IV: Computational Methods for Emerging Problems in (dis-)Information Analysis; Computational Methods in Smart Agriculture; Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart SystemsPart V: Computer Graphics, Image Processing and Artificial Intelligence; Data-Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; MeshFree Methods and Radial Basis Functions in Computational Sciences; Multiscale Modelling and SimulationPart VI: Quantum Computing Workshop; Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainty; Teaching Computational Science; Uncertainty Quantification for Computational Models*The conference was held virtually.Chapter "Deep Learning Driven Self-adaptive hp Finite Element Method" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. |
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| AbstractList | The six-volume set LNCS 12742, 12743, 12744, 12745, 12746, and 12747 constitutes the proceedings of the 21st International Conference on Computational Science, ICCS 2021, held in Krakow, Poland, in June 2021.*The total of 260 full papers and 57 short papers presented in this book set were carefully reviewed and selected from 635 submissions. 48 full and 14 short papers were accepted to the main track from 156 submissions; 212 full and 43 short papers were accepted to the workshops/ thematic tracks from 479 submissions. The papers were organized in topical sections named:Part I: ICCS Main TrackPart II: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Artificial Intelligence and High-Performance Computing for Advanced Simulations; Biomedical and Bioinformatics Challenges for Computer SciencePart III: Classifier Learning from Difficult Data; Computational Analysis of Complex Social Systems; Computational Collective Intelligence; Computational HealthPart IV: Computational Methods for Emerging Problems in (dis-)Information Analysis; Computational Methods in Smart Agriculture; Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart SystemsPart V: Computer Graphics, Image Processing and Artificial Intelligence; Data-Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; MeshFree Methods and Radial Basis Functions in Computational Sciences; Multiscale Modelling and SimulationPart VI: Quantum Computing Workshop; Simulations of Flow and Transport: Modeling, Algorithms and Computation; Smart Systems: Bringing Together Computer Vision, Sensor Networks and Machine Learning; Software Engineering for Computational Science; Solving Problems with Uncertainty; Teaching Computational Science; Uncertainty Quantification for Computational Models*The conference was held virtually.Chapter "Deep Learning Driven Self-adaptive hp Finite Element Method" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com. |
| Author | Kranzlmüller, Dieter Paszynski, Maciej Sloot, Peter M. A Krzhizhanovskaya, Valeria V Dongarra, Jack J |
| Author_xml | – sequence: 1 fullname: Paszynski, Maciej – sequence: 2 fullname: Kranzlmüller, Dieter – sequence: 3 fullname: Krzhizhanovskaya, Valeria V – sequence: 4 fullname: Dongarra, Jack J – sequence: 5 fullname: Sloot, Peter M. A |
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| Copyright | Springer Nature Switzerland AG 2021. Chapter "Deep Learning Driven Self-adaptive Hp Finite Element Method" is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). For further details see license information in the chapter. |
| Copyright_xml | – notice: Springer Nature Switzerland AG 2021. Chapter "Deep Learning Driven Self-adaptive Hp Finite Element Method" is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/). For further details see license information in the chapter. |
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| DOI | 10.1007/978-3-030-77961-0 |
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| Editor | Kranzlmüller, Dieter Paszynski, Maciej Dongarra, Jack J. Krzhizhanovskaya, Valeria V. Sloot, Peter M. A. |
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| RelatedPersons | Hartmanis, Juris Gao, Wen Bertino, Elisa Woeginger, Gerhard Goos, Gerhard Steffen, Bernhard Yung, Moti |
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| SubjectTerms | Artificial Intelligence Computer Science Computer science-Congresses Computer Systems Organization and Communication Networks Image Processing and Computer Vision Mathematics of Computing Theory of Computation |
| Subtitle | 21st International Conference, Krakow, Poland, June 16-18, 2021, Proceedings, Part I |
| TableOfContents | 6.3 Surge Capability -- 7 Conclusion -- References -- Scientific Workflow Management on Hybrid Clouds with Cloud Bursting and Transparent Data Access -- 1 Introduction -- 2 Related Work -- 3 Cloud Bursting Solution for Scientific Workflows -- 3.1 Architecture -- 3.2 Workflow Partitioning -- 4 Evaluation -- 4.1 Workflow Partitioning Analysis -- 4.2 Experimental Runs -- 4.3 Discussion -- 5 Conclusions and Future Work -- References -- Scaling Simulation of Continuous Urban Traffic Model for High Performance Computing System -- 1 Introduction -- 2 Scalable Traffic Simulations -- 3 Towards HPC-Grade Traffic Simulation -- 3.1 Initialization of the Simulation -- 3.2 Data Scalability -- 3.3 Massive Parallelism Issues -- 3.4 Simulation Results Processing -- 4 Evaluation of Traffic Simulation Scalability -- 4.1 Strong Scalability -- 4.2 Weak Scalability -- 5 Conclusions and Further Work -- References -- A Semi-supervised Approach for Trajectory Segmentation to Identify Different Moisture Processes in the Atmosphere -- 1 Introduction -- 2 Background -- 2.1 Trajectory Clustering -- 2.2 Research Data -- 3 Experimental Evaluation -- 4 Discussion -- 5 Conclusion -- References -- mRelief: A Reward Penalty Based Feature Subset Selection Considering Data Overlapping Problem -- 1 Introduction -- 2 Preliminaries -- 2.1 Relief -- 2.2 ReliefF -- 2.3 SURF and SURF* -- 2.4 MultiSURF* and MultiSURF -- 3 Modified Relief (mRelief) -- 3.1 Candidate Feature Selection -- 3.2 Final Feature Subset Selection -- 3.3 An Illustrative Example -- 4 Result Analysis and Discussions -- 4.1 Dataset Description -- 4.2 Implementation Detail -- 4.3 Comparison of mRelief with the State-of-the-Art Methods -- 5 Conclusion -- References -- Reconstruction of Long-Lived Particles in LHCb CERN Project by Data Analysis and Computational Intelligence Methods -- 1 Introduction Music Genre Classification: Looking for the Perfect Network -- 1 Introduction -- 1.1 Related Work -- 1.2 Contribution and Paper Structure -- 2 Deep Learning Models -- 2.1 Convolutional Neural Network -- 2.2 1-Dimensional Convolutional Recurrent Neural Network -- 2.3 2-Dimensional Convolutional Recurrent Neural Network -- 2.4 Recurrent Neural Network with Long Short-Term Memory Cells (LSTM) -- 2.5 Ensembles -- 3 Experiments -- 3.1 Dataset and Hardware Setup -- 3.2 Additional Settings -- 3.3 Quantitative Results -- 3.4 Qualitative Results -- 3.5 Comparison of the Outcomes -- 4 Conclusions -- References -- Big Data for National Security in the Era of COVID-19 -- 1 Introduction -- 2 COVID-19 and National Security -- 3 An Overview of the Framework -- 3.1 Event Polarisation and Early Warning Alert (Q1) -- 3.2 Radical Behaviour (Q2, Q3 and Q4) -- 3.3 Ideology (Q5) -- 3.4 Web Insights (Q6) -- 4 Analysing Two COVID-19 Disruptive Events -- 4.1 Data Collection and Cleansing -- 4.2 Early Warning Alert (Q1) -- 4.3 Radical Behaviour (Q2, Q3 and Q4) -- 4.4 Ideology (Q5) -- 4.5 Web Insights (Q6) -- 5 Conclusions -- References -- Efficient Prediction of Spatio-Temporal Events on the Example of the Availability of Vehicles Rented per Minute -- 1 Introduction -- 1.1 Contribution -- 2 Related Work -- 3 Model and Problem Definition -- 4 Dataset -- 4.1 Performance Measures -- 5 Results -- 6 Conclusion -- References -- Grouped Multi-Layer Echo State Networks with Self-Normalizing Activations -- 1 Introduction -- 2 ESN Architectures -- 2.1 Shallow Echo State Network -- 2.2 Self-Normalizing Activation Function on Hyper-Sphere -- 2.3 Grouped Deep Echo State Network -- 3 AutoESN Library -- 4 Results -- 5 Conclusion -- References -- SGAIN, WSGAIN-CP and WSGAIN-GP: Novel GAN Methods for Missing Data Imputation -- 1 Introduction -- 2 Imputation Methods Based on GAN Evaluating Energy-Aware Scheduling Algorithms for I/O-Intensive Scientific Workflows -- 1 Introduction -- 2 Background -- 2.1 Scientific Workflows -- 2.2 Power and Energy Consumption -- 3 Analysis of Energy-Aware Workflow Scheduling Algorithms -- 3.1 SPSS-EB -- 3.2 EnReal -- 3.3 Workflow Energy Consumption Analysis -- 4 Energy-Aware Scheduling of I/O-Intensive Workflows -- 4.1 I/O- and Energy-Aware Scheduling -- 4.2 Experimental Evaluation -- 5 Related Work -- 6 Conclusion and Future Work -- References -- A Job Shop Scheduling Problem with Due Dates Under Conditions of Uncertainty -- 1 Introduction -- 2 Problem Formulation -- 3 Uncertainty -- 4 Computational Experiments -- 5 Summary -- References -- New Variants of SDLS Algorithm for LABS Problem Dedicated to GPGPU Architectures -- 1 Introduction -- 2 New Variants of SDLS Search Algorithms for LABS -- 2.1 The SDLS-2 Algorithm with Extended Neighbourhood -- 2.2 Sequential Version of the SDLS-DT Algorithm -- 2.3 Parallel Version of SDLS-DT for GPGPU -- 3 Effectiveness of the Proposed Algorithms -- 4 Conclusions and Further Work -- References -- Highly Effective GPU Realization of Discrete Wavelet Transform for Big-Data Problems -- 1 Introduction -- 2 Calculation of One-Dimensional DWT -- 2.1 Calculations Based on the Convolution -- 2.2 Calculations Based on the Lattice Structure -- 3 The Proposed Lattice Structure -- 4 Experimental Analysis -- 5 Conclusions -- References -- A Dynamic Replication Approach for Monte Carlo Photon Transport on Heterogeneous Architectures -- 1 Introduction -- 2 Background -- 3 Related Works -- 4 Our Method -- 4.1 Step 1: Assignment -- 4.2 Step 2: Distribution -- 4.3 Step 3: Mapping -- 5 Experiment Overview -- 5.1 Hardware and Software -- 5.2 Experimental Factors -- 5.3 Measurements -- 6 Results -- 6.1 Algorithm Performance -- 6.2 Load Balance Efficiency 2 Long-Lived Particles in LHCb 3 Novel Generative Imputation Methods -- 3.1 Notation and Problem Formulation -- 3.2 Slim GAIN -- 3.3 Wasserstein Slim GAIN with Clipping Penalty -- 3.4 Wasserstein Slim GAIN with Gradient Penalty -- 4 Experimental Results -- 4.1 Response Times -- 4.2 RMSE Performance -- 4.3 AUROC Performance -- 5 Conclusions -- References -- Deep Learning Driven Self-adaptive Hp Finite Element Method -- 1 Introduction -- 2 Self-adaptive hp-FEM with Neural Network -- 3 Conclusions -- References -- Machine-Learning Based Prediction of Multiple Types of Network Traffic -- 1 Introduction -- 2 Related Work -- 3 Data Analysis -- 4 Proposed Models and Algorithms -- 5 Numerical Experiments -- 6 Conclusions and Future Work -- References -- Scalable Handwritten Text Recognition System for Lexicographic Sources of Under-Resourced Languages and Alphabets -- 1 Introduction -- 2 Related Work -- 3 Data -- 3.1 Original Data -- 3.2 Synthetic Data for Training -- 3.3 Manually Labelled Subsets -- 4 Methodological Workflow -- 4.1 Detection of the Index Word -- 4.2 Recognition -- 4.3 Transfer Learning -- 4.4 Postprocessing -- 5 Application -- 6 Results -- 7 Discussion -- 8 Conclusion -- References -- Out-Plant Milk-Run-Driven Mission Planning Subject to Dynamic Changes of Date and Place Delivery -- 1 Introduction -- 2 Literature Review -- 3 An Ordered Fuzzy Numbers Framework -- 4 Problem Formulation -- 5 OFN-Based Constraint Satisfaction Problem -- 6 Dynamic Mission Planning -- 7 Computational Experiments -- 8 Conclusions -- References -- An Efficient Hybrid Planning Framework for In-Station Train Dispatching -- 1 Introduction -- 2 The In-Station Train Dispatching Problem -- 3 Description of the Framework -- 3.1 Preprocessor -- 3.2 Optimised Planning Engine -- 3.3 Visualisation Tool -- 4 Experimental Analysis -- 5 Related Work and Conclusions -- References Intro -- Preface -- Organization -- Contents - Part I -- ICCS 2021 Main Track -- Smoothing Speed Variability in Age-Friendly Urban Traffic Management -- 1 Introduction -- 2 Related Work -- 3 System Model -- 4 CoMAAPRAS -- 4.1 Update Road Pheromone -- 4.2 Collaborative Decision Making -- 5 Experiment Design -- 6 Results -- 6.1 Speed Variability -- 6.2 Waiting Time -- 6.3 Fuel Consumption -- 6.4 Travel Time -- 7 Conclusions -- References -- An Innovative Employment of the NetLogo AIDS Model in Developing a New Chain Code for Compression -- 1 Introduction -- 2 Method -- 3 Results -- 4 Discussion and Conclusion -- References -- Simulation Modeling of Epidemic Risk in Supermarkets: Investigating the Impact of Social Distancing and Checkout Zone Design -- 1 Introduction -- 2 Modeling Infection Transmission -- 3 Simulation Setup -- 4 Results -- 5 Conclusions -- References -- A Multi-cell Cellular Automata Model of Traffic Flow with Emergency Vehicles: Effect of a Corridor of Life -- 1 Introduction -- 2 Proposed Model -- 2.1 Road Structure, Types of Vehicles and Real Data -- 2.2 The Corridor of Life -- 2.3 Safe Distance Between Cars and the Friction Conflict -- 2.4 The Rules of Traffic Movement -- 3 Results -- 4 Conclusions -- References -- HSLF: HTTP Header Sequence Based LSH Fingerprints for Application Traffic Classification -- 1 Introduction -- 2 Background and Related Work -- 2.1 Traffic Classification Solutions -- 2.2 Research on HTTP Headers -- 3 Preprocessing -- 3.1 Weight Assignment -- 3.2 HTTP Header Sequence -- 4 HTTP Header Sequence Based LSH Fingerprints -- 4.1 LSH Fingerprint -- 4.2 Fingerprint Database -- 4.3 Application Identification -- 5 Experiments -- 5.1 Dataset -- 5.2 Multi-class Classification Performance -- 5.3 Compared with Classic Machine Learning Models -- 5.4 Comparison with Other Approaches -- 6 Conclusion -- References |
| Title | Computational Science - ICCS 2021 |
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