LEADER 12994nam 22007575 450 001 996538664503316 005 20230628080202.0 010 $a3-031-35995-X 024 7 $a10.1007/978-3-031-35995-8 035 $a(MiAaPQ)EBC30611296 035 $a(Au-PeEL)EBL30611296 035 $a(DE-He213)978-3-031-35995-8 035 $a(PPN)272259659 035 $a(EXLCZ)9927279100700041 100 $a20230628d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputational Science ? ICCS 2023$b[electronic resource] $e23rd International Conference, Prague, Czech Republic, July 3?5, 2023, Proceedings, Part I /$fedited by Ji?í Miky?ka, Clélia de Mulatier, Maciej Paszynski, Valeria V. Krzhizhanovskaya, Jack J. Dongarra, Peter M.A. Sloot 205 $a1st ed. 2023. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2023. 215 $a1 online resource (718 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v14073 311 08$aPrint version: Mikyska, Ji?í Computational Science - ICCS 2023 Cham : Springer International Publishing AG,c2023 9783031359941 320 $aIncludes bibliographical references and index. 327 $aIntro -- 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. 327 $aAccelerating 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. 327 $a4 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. 327 $a4 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. 327 $aFirst-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). 327 $a4.4 Similarity-Based Isolation (similarity-iso). 330 $aThe five-volume set LNCS 14073-14077 constitutes the proceedings of the 23rd International Conference on Computational Science, ICCS 2023, held in Prague, Czech Republic, during July 3-5, 2023. The total of 188 full papers and 94 short papers presented in this book set were carefully reviewed and selected from 530 submissions. 54 full and 37 short papers were accepted to the main track; 134 full and 57 short papers were accepted to the workshops/thematic tracks. The theme for 2023, "Computation at the Cutting Edge of Science", highlights the role of Computational Science in assisting multidisciplinary research. This conference was a unique event focusing on recent developments in scalable scientific algorithms, advanced software tools; computational grids; advanced numerical methods; and novel application areas. These innovative novel models, algorithms, and tools drive new science through efficient application in physical systems, computational and systems biology, environmental systems, finance, and others. 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v14073 606 $aComputer science 606 $aArtificial intelligence 606 $aComputer engineering 606 $aComputer networks 606 $aSoftware engineering 606 $aComputer science?Mathematics 606 $aTheory of Computation 606 $aArtificial Intelligence 606 $aComputer Engineering and Networks 606 $aSoftware Engineering 606 $aMathematics of Computing 615 0$aComputer science. 615 0$aArtificial intelligence. 615 0$aComputer engineering. 615 0$aComputer networks. 615 0$aSoftware engineering. 615 0$aComputer science?Mathematics. 615 14$aTheory of Computation. 615 24$aArtificial Intelligence. 615 24$aComputer Engineering and Networks. 615 24$aSoftware Engineering. 615 24$aMathematics of Computing. 676 $a929.605 702 $aMikys?ka$b Jir?i? 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996538664503316 996 $aComputational science - ICCS 2023$93551814 997 $aUNISA LEADER 03366oam 2200697I 450 001 9910960587003321 005 20251117093040.0 010 $a1-04-005718-7 010 $a0-429-10802-8 010 $a1-62870-687-2 010 $a1-4398-6247-8 024 7 $a10.1201/b13686 035 $a(CKB)2670000000316822 035 $a(EBL)1107587 035 $a(OCoLC)823719651 035 $a(SSID)ssj0000803475 035 $a(PQKBManifestationID)11487144 035 $a(PQKBTitleCode)TC0000803475 035 $a(PQKBWorkID)10810260 035 $a(PQKB)10148621 035 $a(CaSebORM)9781439862469 035 $a(Au-PeEL)EBL1107587 035 $a(CaPaEBR)ebr10641387 035 $a(CaONFJC)MIL584744 035 $a(OCoLC)827884273 035 $a(MiAaPQ)EBC1107587 035 $a(OCoLC)1280138066 035 $a(FINmELB)ELB140910 035 $a(EXLCZ)992670000000316822 100 $a20180331d2013 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 14$aThe basics of oil spill cleanup /$fMerv Fingas 205 $a3rd ed. 210 $aBoca Raton, FL $cTaylor & Francis$dc2013 210 1$aBoca Raton, Fla. :$cCRC Press,$d2013. 215 $a1 online resource (273 p.) 300 $aDescription based upon print version of record. 311 08$a1-4398-6246-X 320 $aIncludes bibliographical references and index. 327 $aFront Cover; Contents; Preface; Acknowledgments; Author; List of Illustrations; List of Tables; Introduction; Chapter 1 - Oil Spills: Why Do They Happen and How Often?; Chapter 2 - Response to Oil Spills; Chapter 3 - Types of Oil and Their Properties; Chapter 4 - Behavior of Oil in the Environment; Chapter 5 - Analysis, Detection, and Remote Sensing of Oil Spills; Chapter 6 - Containment on Water; Chapter 7 - Oil Recovery on Water; Chapter 8 - Separation, Pumping, Decontamination, and Disposal; Chapter 9 - Spill-Treating Agents; Chapter 10 - In-Situ Burning 327 $aChapter 11 - Shoreline Cleanup and RestorationChapter 12 - Oil Spills on Land; Chapter 13 - Effects of Oil Spills on the Environment; Glossary; Reading for Further Information; Back Cover 330 $aAn examination of pollution caused by crude oils and petroleum products derived from them, this book covers how oil spills are measured and detected and discusses the properties of the oil as well as its long-term fate in the environment. This third edition contains a new chapter devoted to pollution effects on wildlife. It focuses on the cleanup of oil spills that occur in water, since these spills spread most rapidly and cause the most visible environmental damage. It also includes coverage of the latest technologies as well as recent spills, including the Gulf of Mexico--$cProvided by publisher. 606 $aOil pollution of the sea$xEnvironmental aspects$zNorth America 606 $aOil spills$xCleanup 615 0$aOil pollution of the sea$xEnvironmental aspects 615 0$aOil spills$xCleanup. 676 $a628.1/6833 676 $a628.16833 686 $aSCI026000$2bisacsh 700 $aFingas$b Mervin F.$0935992 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910960587003321 996 $aThe basics of oil spill cleanup$94489500 997 $aUNINA