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Computational Science – ICCS 2021 -

Computational Science – ICCS 2021

21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part I
Buch | Softcover
XX, 797 Seiten
2021 | 1st ed. 2021
Springer International Publishing (Verlag)
978-3-030-77960-3 (ISBN)
CHF 179,70 inkl. MwSt
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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 Track

Part 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 Science

Part III: Classifier Learning from Difficult Data; Computational Analysis of Complex Social Systems; Computational Collective Intelligence; Computational Health

Part 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 Systems

Part 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 Simulation

Part 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.


ICCS Main Track.- Smoothing Speed Variability in Age-Friendly Urban Traffic Management.- An innovative employment of NetLogo AIDS model in developing a new chain coding mechanism for compression.- Simulation modeling of epidemic risk in supermarkets: Investigating the impact of social distancing and checkout zone design.- A multi-cell cellular automata model of traffic flow with emergency vehicles: e ect of a corridor of life.- HSLF: HTTP Header Sequence based LSH fingerprints for Application Traffic Classification.- Music genre classification: looking for the Perfect Network.- Big Data for National Security in the Era of COVID-19.- Efficient prediction of spatio-temporal events on the example of the availability of vehicles rented per minute.- Grouped Multi-Layer Echo State Networks with Self-Normalizing Activations.- SGAIN, WSGAIN-CP and WSGAIN-GP: Novel Gan Methods for Missing Data Imputation.- Deep learning driven self-adaptive hp finite element method.- Machine-Learning Based Prediction of Multiple Types of Network Traffic.- Scalable handwritten text recognition system for lexicographic sources of under-resourced languages and alphabets.- Out-plant milk-run-driven mission planning subject to dynamic changes of date and place delivery.- An Efficient Hybrid Planning Framework for In-Station Train Dispatching.- Evaluating energy-aware scheduling algorithms for I/O-intensive scientific workflows.- A Job Shop Scheduling Problem with Due Dates under Conditions of Uncertainty.- New variants of SDLS algorithm for LABS problem dedicated to GPGPU architectures.- Highly E ective GPU Realization of Discrete Wavelet Transform for Big-Data Problems.- A Dynamic Replication Approach for Monte Carlo Photon Transport on Heterogeneous Architectures.- Scientific workflow management on hybrid clouds with cloud bursting and transparent data access.- Scaling Simulation of Continuous Urban Traffic Model for High Performance Computing System.- A Semi-Supervised Approach for Trajectory Segmentation to Identify Di erent Moisture Processes in the Atmosphere.- mRelief: A Reward Penalty based Feature SubsetSelection Considering Data Overlapping Problem.- Reconstruction of Long-Lived Particles in LHCb CERN Project by Data Analysis and Computational Intelligence Methods.- Motion Trajectory Grouping for Human Head Gestures Related to Facial Expressions.- DenLAC: Density Levels Aggregation Clustering - A Flexible Clustering Method.- Acceleration of the Robust Newton Method by the use of the S-iteration.- A New Approach to Eliminate Rank Reversal in the MCDA problems.- Validating Optimal COVID-19 Vaccine Distribution Models.- RNACache: Fast Mapping of RNA-Seq Reads to Transcriptomes using MinHashing.- Digital image reduction for analysis of topological changes in pore space during chemical dissolution.- Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks.- Analytic and Numerical Solutions of Space-Time Fractional Di usion Wave Equationswith di erent Fractional order.- Chebyshev-type rational approximations of the one-way Helmholtz equation for solving a class of wave propagation problems.- Investigating In Situ Reduction via Lagrangian Representations for Cosmology and Seismology Applications.- Revolve-Based Adjoint Checkpointing for Multistage Time Integration.- Comprehensive regularization of PIES for problems modeled by 2D Laplace's equation.- High Resolution TVD Scheme based on Fuzzy Modifiers for Shallow-Water equations.- PIES for viscoelastic analysis.- Fast and Accurate Determination of Graph Node Connectivity Leveraging Approximate Methods.- An Exact Algorithm for Finite Metric Space Embedding into a Euclidean Space when the Dimension of the Space is not Known.- Resolving Policy Conflicts for Cross-Domain Access Control: A Double Auction Approach.- An Adaptive Network Model for Procrastination Behaviour Including Self-Regulation and Emotion Regulation.- Improved Lower Bounds for the Cyclic Bandwidth Problem.-

Erscheinungsdatum
Reihe/Serie Lecture Notes in Computer Science
Theoretical Computer Science and General Issues
Zusatzinfo XX, 797 p. 294 illus., 232 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 1220 g
Themenwelt Mathematik / Informatik Informatik Netzwerke
Mathematik / Informatik Informatik Theorie / Studium
Schlagworte Applications • Artificial Intelligence • Computer Networks • Computer Science • computer vision • conference proceedings • Databases • Image Processing • Informatics • machine learning • Network Protocols • Numerical Methods • parallel processing systems • Processors • Research • Signal Processing • Telecommunication networks • Telecommunication Systems • telecommunication traffic
ISBN-10 3-030-77960-2 / 3030779602
ISBN-13 978-3-030-77960-3 / 9783030779603
Zustand Neuware
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