| Título : |
20th International Conference, Amsterdam, The Netherlands, June 3–5, 2020, Proceedings, Part III |
| Tipo de documento: |
documento electrónico |
| Autores: |
Krzhizhanovskaya, Valeria V., ; Závodszky, Gábor, ; Lees, Michael H., ; Dongarra, Jack J., ; Sloot, Peter M. A., ; Brissos, Sérgio, ; Teixeira, João, |
| Mención de edición: |
1 ed. |
| Editorial: |
[s.l.] : Springer |
| Fecha de publicación: |
2020 |
| Número de páginas: |
XIX, 648 p. 76 ilustraciones |
| ISBN/ISSN/DL: |
978-3-030-50420-5 |
| Nota general: |
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. |
| Palabras clave: |
Ciencias de la Computación Inteligencia artificial Informática Ingeniería Informática Red de computadoras Visión por computador Teoría de la Computación Matemáticas de la Computación Ingeniería Informática y Redes |
| Índice Dewey: |
40.151 |
| Resumen: |
El conjunto de siete volúmenes LNCS 12137, 12138, 12139, 12140, 12141, 12142 y 12143 constituye las actas de la 20.ª Conferencia Internacional sobre Ciencias Computacionales, ICCS 2020, celebrada en Ámsterdam, Países Bajos, en junio de 2020.* El total de 101 artículos y 248 artículos de talleres presentados en este conjunto de libros fueron cuidadosamente revisados y seleccionados entre 719 presentaciones (230 presentaciones para la vía principal y 489 presentaciones para los talleres). Los artículos se organizaron en secciones temáticas denominadas: Parte I: Vía principal de ICCS Parte II: Vía principal de ICCS Parte III: Avances en ciencias computacionales de la Tierra de alto rendimiento: aplicaciones y marcos; Simulaciones basadas en agentes, algoritmos adaptativos y solucionadores; Aplicaciones de Métodos Computacionales en Inteligencia Artificial y Aprendizaje Automático; Desafíos biomédicos y bioinformáticos para la informática Parte IV: Aprendizaje del clasificador a partir de datos difíciles; Sistemas sociales complejos a través de la lente de la ciencia computacional; Salud Computacional; Métodos computacionales para problemas emergentes en el análisis de (des) información Parte V: Optimización, modelado y simulación computacional; Ciencias Computacionales en IoT y Sistemas Inteligentes; Gráficos por computadora, procesamiento de imágenes e inteligencia artificial Parte VI: Ciencias computacionales basadas en datos; Aprendizaje Automático y Asimilación de Datos para Sistemas Dinámicos; Métodos sin malla en ciencias computacionales; Modelado y Simulación Multiescala; Taller de Computación Cuántica Parte VII: Simulaciones de Flujo y Transporte: Modelado, Algoritmos y Computación; Sistemas inteligentes: unión de visión por computadora, redes de sensores y aprendizaje automático; Ingeniería de Software para Ciencias Computacionales; Resolver Problemas con Incertidumbres; Enseñanza de Ciencias Computacionales; CUANTIFICACIÓN DE LA INCERTIDUMBRE PARA MODELOS COMPUTACIONALES *La conferencia fue cancelada debido a la pandemia de COVID-19. |
| Nota de contenido: |
Advances in High-Performance Computational Earth Sciences: Applications and Frameworks -- Data-Driven Approach to Inversion Analysis of Three-dimensional Inner Soil Structure via Wave Propagation Analysis -- Data assimilation in volcano deformation using fast finite element analysis with high fidelity model -- Optimization and Local Time Stepping of an ADER-DG Scheme for Fully Anisotropic Wave Propagation in Complex Geometries -- The challenge of onboard SAR processing: a GPU opportunity -- High-resolution Source Estimation of Volcanic Sulfur Dioxide Emissions Using Large Scale Transport Simulations -- Granulation-based reverse image retrieval for microscopic rock images -- Hybrid SWAN for fast and efficient practical wave modelling - part 2 -- Agent-Based Simulations, Adaptive Algorithms and Solvers -- An agent-based simulation of the spread of Dengue fever -- Hypergraph grammar-based model of adaptive bitmap compression -- Simulation of Neurotransmitter Flow in Three Dimensional Model of Presynaptic Bouton -- Scalable Signal-based Simulation of Autonomous Beings in Complex Environments -- Design of Loss Functions for Solving Inverse Problems using Deep Learning -- Asynchronous Actor-based Approach to Multiobjective Hierarchical Strategy -- MeshingNet: A New Mesh Generation Method based on Deep Learning -- A block preconditioner for scalable large scale finite element incompressible flow simulations -- Integrating Agent-Based Modelling with Copula Theory: Preliminary Insights and Open Problems -- Computational complexity of hierarchically adapted meshes -- A Novel Bio-inspired Hybrid Metaheuristic for Unsolicited Bulk Email Detection -- Applications of Computational Methods in Artificial Intelligence and Machine Learning -- Link Prediction by Analyzing Temporal Behavior of Vertices -- Detecting Most Insightful Parts of Documents using an Attention-Based Model -- Challenge Collapsar(CC) Attack Traffic Detection based on Packet Field Differentiated Preprocessing and Deep Neural Network -- Deep Low-Density Separation for Semi-Supervised Classification -- Learning functions using data-dependent regularization: Representer theorem revisited -- Reduction of Numerical Errors in Zernike Invariants Computed via Complex-Valued Integral Images -- Effect of Dataset Size on Efficiency of Collaborative Filtering Recommender Systems with Multi-Clustering as a Neighbourhood Identification Strategy -- GCN-IA: User Profile Based on Graph Convolutional Network with Implicit Association Labels -- Interval AdjointSignificance Analysis for Neural Networks -- Ringer: Systematic Mining of Malicious Domains by Dynamic Graph Convolutional Network -- An Empirical Evaluation Of Attention And Pointer Networks For Paraphrase Generation -- Interval methods for seeking fixed points of recurrent neural networks -- Fusion Learning: A One Shot Federated Learning -- The concept of system for automated scientific literature reviews generation -- A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings -- Retrain or not retrain ? - efficient pruning methods of deep CNN networks -- Hidden Markov Models and their Application for Predicting Failure Events -- Biomedical and Bioinformatics Challenges for Computer Science -- Reference-based Haplotype Phasing with FPGAs -- Tree Based Advanced Relative Expression Analysis -- Testing the significance of interactions in genetic studies using interaction information and resampling technique -- Analysis of ensemble feature selection for correlated high-dimensional RNA-Seq cancer data -- Biological Network Visualization for Targeted Proteomics based on Mean First-Passage Time in Semi-Lazy Random Walks -- Bootstrap Bias Corrected Cross Validation applied to Super Learning -- MMRF-CoMMpass data integration and analysis for identifying prognostic markers -- Using machine learning in accuracy assessment of knowledge-based energy and frequency base likelihood in protein structures -- Quantifying Overfitting Potential in Drug Binding Datasets -- Detection of Tumoral Epithelial Lesions Using Hyperspectral Imaging and Deep Learning -- Statistical iterative reconstruction algorithm based on a continuous-tocontinuous model formulated for spiral cone-beam CT -- Classification of lung diseases using deep learning models -- An Adaptive Space-Filling Curve Trajectory for Mapping 3D Datasets to 1D: Application to Brain Magnetic Resonance Imaging Data for Classification. |
| En línea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
20th International Conference, Amsterdam, The Netherlands, June 3–5, 2020, Proceedings, Part III [documento electrónico] / Krzhizhanovskaya, Valeria V., ; Závodszky, Gábor, ; Lees, Michael H., ; Dongarra, Jack J., ; Sloot, Peter M. A., ; Brissos, Sérgio, ; Teixeira, João, . - 1 ed. . - [s.l.] : Springer, 2020 . - XIX, 648 p. 76 ilustraciones. ISBN : 978-3-030-50420-5 Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
| Palabras clave: |
Ciencias de la Computación Inteligencia artificial Informática Ingeniería Informática Red de computadoras Visión por computador Teoría de la Computación Matemáticas de la Computación Ingeniería Informática y Redes |
| Índice Dewey: |
40.151 |
| Resumen: |
El conjunto de siete volúmenes LNCS 12137, 12138, 12139, 12140, 12141, 12142 y 12143 constituye las actas de la 20.ª Conferencia Internacional sobre Ciencias Computacionales, ICCS 2020, celebrada en Ámsterdam, Países Bajos, en junio de 2020.* El total de 101 artículos y 248 artículos de talleres presentados en este conjunto de libros fueron cuidadosamente revisados y seleccionados entre 719 presentaciones (230 presentaciones para la vía principal y 489 presentaciones para los talleres). Los artículos se organizaron en secciones temáticas denominadas: Parte I: Vía principal de ICCS Parte II: Vía principal de ICCS Parte III: Avances en ciencias computacionales de la Tierra de alto rendimiento: aplicaciones y marcos; Simulaciones basadas en agentes, algoritmos adaptativos y solucionadores; Aplicaciones de Métodos Computacionales en Inteligencia Artificial y Aprendizaje Automático; Desafíos biomédicos y bioinformáticos para la informática Parte IV: Aprendizaje del clasificador a partir de datos difíciles; Sistemas sociales complejos a través de la lente de la ciencia computacional; Salud Computacional; Métodos computacionales para problemas emergentes en el análisis de (des) información Parte V: Optimización, modelado y simulación computacional; Ciencias Computacionales en IoT y Sistemas Inteligentes; Gráficos por computadora, procesamiento de imágenes e inteligencia artificial Parte VI: Ciencias computacionales basadas en datos; Aprendizaje Automático y Asimilación de Datos para Sistemas Dinámicos; Métodos sin malla en ciencias computacionales; Modelado y Simulación Multiescala; Taller de Computación Cuántica Parte VII: Simulaciones de Flujo y Transporte: Modelado, Algoritmos y Computación; Sistemas inteligentes: unión de visión por computadora, redes de sensores y aprendizaje automático; Ingeniería de Software para Ciencias Computacionales; Resolver Problemas con Incertidumbres; Enseñanza de Ciencias Computacionales; CUANTIFICACIÓN DE LA INCERTIDUMBRE PARA MODELOS COMPUTACIONALES *La conferencia fue cancelada debido a la pandemia de COVID-19. |
| Nota de contenido: |
Advances in High-Performance Computational Earth Sciences: Applications and Frameworks -- Data-Driven Approach to Inversion Analysis of Three-dimensional Inner Soil Structure via Wave Propagation Analysis -- Data assimilation in volcano deformation using fast finite element analysis with high fidelity model -- Optimization and Local Time Stepping of an ADER-DG Scheme for Fully Anisotropic Wave Propagation in Complex Geometries -- The challenge of onboard SAR processing: a GPU opportunity -- High-resolution Source Estimation of Volcanic Sulfur Dioxide Emissions Using Large Scale Transport Simulations -- Granulation-based reverse image retrieval for microscopic rock images -- Hybrid SWAN for fast and efficient practical wave modelling - part 2 -- Agent-Based Simulations, Adaptive Algorithms and Solvers -- An agent-based simulation of the spread of Dengue fever -- Hypergraph grammar-based model of adaptive bitmap compression -- Simulation of Neurotransmitter Flow in Three Dimensional Model of Presynaptic Bouton -- Scalable Signal-based Simulation of Autonomous Beings in Complex Environments -- Design of Loss Functions for Solving Inverse Problems using Deep Learning -- Asynchronous Actor-based Approach to Multiobjective Hierarchical Strategy -- MeshingNet: A New Mesh Generation Method based on Deep Learning -- A block preconditioner for scalable large scale finite element incompressible flow simulations -- Integrating Agent-Based Modelling with Copula Theory: Preliminary Insights and Open Problems -- Computational complexity of hierarchically adapted meshes -- A Novel Bio-inspired Hybrid Metaheuristic for Unsolicited Bulk Email Detection -- Applications of Computational Methods in Artificial Intelligence and Machine Learning -- Link Prediction by Analyzing Temporal Behavior of Vertices -- Detecting Most Insightful Parts of Documents using an Attention-Based Model -- Challenge Collapsar(CC) Attack Traffic Detection based on Packet Field Differentiated Preprocessing and Deep Neural Network -- Deep Low-Density Separation for Semi-Supervised Classification -- Learning functions using data-dependent regularization: Representer theorem revisited -- Reduction of Numerical Errors in Zernike Invariants Computed via Complex-Valued Integral Images -- Effect of Dataset Size on Efficiency of Collaborative Filtering Recommender Systems with Multi-Clustering as a Neighbourhood Identification Strategy -- GCN-IA: User Profile Based on Graph Convolutional Network with Implicit Association Labels -- Interval AdjointSignificance Analysis for Neural Networks -- Ringer: Systematic Mining of Malicious Domains by Dynamic Graph Convolutional Network -- An Empirical Evaluation Of Attention And Pointer Networks For Paraphrase Generation -- Interval methods for seeking fixed points of recurrent neural networks -- Fusion Learning: A One Shot Federated Learning -- The concept of system for automated scientific literature reviews generation -- A Proposed Machine Learning Model for Forecasting Impact of Traffic-Induced Vibrations on Buildings -- Retrain or not retrain ? - efficient pruning methods of deep CNN networks -- Hidden Markov Models and their Application for Predicting Failure Events -- Biomedical and Bioinformatics Challenges for Computer Science -- Reference-based Haplotype Phasing with FPGAs -- Tree Based Advanced Relative Expression Analysis -- Testing the significance of interactions in genetic studies using interaction information and resampling technique -- Analysis of ensemble feature selection for correlated high-dimensional RNA-Seq cancer data -- Biological Network Visualization for Targeted Proteomics based on Mean First-Passage Time in Semi-Lazy Random Walks -- Bootstrap Bias Corrected Cross Validation applied to Super Learning -- MMRF-CoMMpass data integration and analysis for identifying prognostic markers -- Using machine learning in accuracy assessment of knowledge-based energy and frequency base likelihood in protein structures -- Quantifying Overfitting Potential in Drug Binding Datasets -- Detection of Tumoral Epithelial Lesions Using Hyperspectral Imaging and Deep Learning -- Statistical iterative reconstruction algorithm based on a continuous-tocontinuous model formulated for spiral cone-beam CT -- Classification of lung diseases using deep learning models -- An Adaptive Space-Filling Curve Trajectory for Mapping 3D Datasets to 1D: Application to Brain Magnetic Resonance Imaging Data for Classification. |
| En línea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
|  |
20th International Conference, Amsterdam, The Netherlands, June 3–5, 2020, Proceedings, Part III
