| Título : |
20th International Conference, Amsterdam, The Netherlands, June 3–5, 2020, Proceedings, Part IV |
| 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, 668 p. 247 ilustraciones, 192 ilustraciones en color. |
| ISBN/ISSN/DL: |
978-3-030-50423-6 |
| 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 Gestión de base de datos Inteligencia artificial Informática Ingeniería Informática Red de computadoras Teoría de la Computación Sistema de administración de base de datos 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: |
Classifier Learning from Difficult Data -- Different strategies of fitting logistic regression for positive and unlabelled data -- Branch-and-Bound Search for Training Cascades of Classifiers -- Application of the stochastic gradient method in the construction of the maincomponents of PCA in the task diagnosis of multiple sclerosis in children -- Grammatical Inference by Answer Set Programming -- Dynamic Classifier Selection for data with skewed class distribution using Imbalance Ratio and Euclidean distance -- On Model Evaluation under Non-constant Class Imbalance -- A Correction Method of a Base Classifier Applied to Imbalanced Data Classification -- Standard Decision Boundary in a support-domain of fuzzy classifier prediction for the task of imbalanced data classification -- Employing One-class SVM Classifier Ensemble for Imbalanced Data Stream Classification -- Clustering and Weighted Scoring in Geometric Space Support Vector Machine Ensemble for Highly Imbalanced Data Classification -- Performance Analysis of Binarization Strategies for Multi-Class Imbalanced Data Classification -- Towards Network Anomaly Detection Using Graph Embedding -- Maintenance and Security System for PLC Railway LED Sign Communication Infrastructure -- Behavioral Biometric User Authentication from URL Logs -- On the impact of network data balancing in cybersecurity applications -- Pattern recognition model to aid the optimization of Dynamic Spectrally-Spatially Flexible Optical Networks -- Missing Features Reconstruction Using a Wasserstein Generative Adversarial Imputation Network -- Complex Social Systems through the Lens of Computational Science -- Cooperation for public goods under uncertainty -- An Information-Theoretic and Dissipative Systems Approach to the Study of Knowledge Diffusion and Emerging Complexity in Innovation Systems -- Mapping the port influence diffusion patterns: a case study of Rotterdam, Antwerp and Singapore -- Entropy-based Measure for Influence Maximization in Temporal Networks -- Evaluation of the Costs of Delayed Campaigns for Limiting the Spread of Negative Content, Panic and Rumours in Complex Networks -- From generality to specificity: on matter of scale in social media topic Communities.-Computational Health -- Hybrid Text Feature Modeling for Disease Group Prediction using Unstructured Physician Notes -- Early signs of critical slowing down in heart surface electrograms of ventricular fibrillation victims -- A Comparison of Generalized Stochastic Milevsky-Promislov Mortality Models with continuous non-Gaussian Filters -- Ontology-Based Inference for Supporting Clinical Decisions in Mental Health -- Towards Prediction of Heart Arrhythmia Onset Using Machine Learning -- Stroke ICU Patient Mortality Day Prediction -- Universal measure for medical image quality evaluation based on gradient approach -- Constructing Holistic Patient Flow Simulation Using System Approach -- Investigating Coordination of Hospital Departments in Delivering Healthcare for Acute Coronary SyndromePatients using Data-Driven Network Analysis -- A Machine Learning Approach To Short-term Body Weight Prediction In A Dietary Intervention Program -- An analysis of demographic data in Irish healthcare domain to support semantic uplift -- From Population to Subject-Specific Reference Intervals -- Analyzing the spatial distribution of acute coronary syndrome cases using synthesized data on arterial hypertension prevalence -- The Atrial Fibrillation Risk Score for Hyperthyroidism Patients -- Applicability of Machine Learning Methods to Multi-Label Medical Text Classification -- Machine Learning Approach for the Early Prediction of the Risk of Overweight and Obesity in Young People -- Gait Abnormality Detection in People with Cerebral Palsy using an Uncertainty-based State-space Model -- Analyses of public health databases via clinical pathway modelling: TBWEB -- Preliminary results on Pulmonary Tuberculosis detection in Chest X-Ray using Convolutional Neural Networks -- Risk-based AED Placement – Singapore Case -- Time Expressions Identification without Human-labeled Corpus for Clinical Text Mining in Russian -- Experiencer detection and automated extraction of a family disease tree from medical texts in Russian language -- Computational Methods for Emerging Problems in (Dis-)Information Analysis -- Machine Learning – the results are not the only thing that matters! What about security, explainability and fairness? -- Syntactic and Semantic Bias Detection and Countermeasures -- Detecting Rumours in Disasters: An Imbalanced Learning Approach -- Sentiment Analysis for Fake News Detection by Means of Neural Networks. |
| 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 IV [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, 668 p. 247 ilustraciones, 192 ilustraciones en color. ISBN : 978-3-030-50423-6 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 Gestión de base de datos Inteligencia artificial Informática Ingeniería Informática Red de computadoras Teoría de la Computación Sistema de administración de base de datos 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: |
Classifier Learning from Difficult Data -- Different strategies of fitting logistic regression for positive and unlabelled data -- Branch-and-Bound Search for Training Cascades of Classifiers -- Application of the stochastic gradient method in the construction of the maincomponents of PCA in the task diagnosis of multiple sclerosis in children -- Grammatical Inference by Answer Set Programming -- Dynamic Classifier Selection for data with skewed class distribution using Imbalance Ratio and Euclidean distance -- On Model Evaluation under Non-constant Class Imbalance -- A Correction Method of a Base Classifier Applied to Imbalanced Data Classification -- Standard Decision Boundary in a support-domain of fuzzy classifier prediction for the task of imbalanced data classification -- Employing One-class SVM Classifier Ensemble for Imbalanced Data Stream Classification -- Clustering and Weighted Scoring in Geometric Space Support Vector Machine Ensemble for Highly Imbalanced Data Classification -- Performance Analysis of Binarization Strategies for Multi-Class Imbalanced Data Classification -- Towards Network Anomaly Detection Using Graph Embedding -- Maintenance and Security System for PLC Railway LED Sign Communication Infrastructure -- Behavioral Biometric User Authentication from URL Logs -- On the impact of network data balancing in cybersecurity applications -- Pattern recognition model to aid the optimization of Dynamic Spectrally-Spatially Flexible Optical Networks -- Missing Features Reconstruction Using a Wasserstein Generative Adversarial Imputation Network -- Complex Social Systems through the Lens of Computational Science -- Cooperation for public goods under uncertainty -- An Information-Theoretic and Dissipative Systems Approach to the Study of Knowledge Diffusion and Emerging Complexity in Innovation Systems -- Mapping the port influence diffusion patterns: a case study of Rotterdam, Antwerp and Singapore -- Entropy-based Measure for Influence Maximization in Temporal Networks -- Evaluation of the Costs of Delayed Campaigns for Limiting the Spread of Negative Content, Panic and Rumours in Complex Networks -- From generality to specificity: on matter of scale in social media topic Communities.-Computational Health -- Hybrid Text Feature Modeling for Disease Group Prediction using Unstructured Physician Notes -- Early signs of critical slowing down in heart surface electrograms of ventricular fibrillation victims -- A Comparison of Generalized Stochastic Milevsky-Promislov Mortality Models with continuous non-Gaussian Filters -- Ontology-Based Inference for Supporting Clinical Decisions in Mental Health -- Towards Prediction of Heart Arrhythmia Onset Using Machine Learning -- Stroke ICU Patient Mortality Day Prediction -- Universal measure for medical image quality evaluation based on gradient approach -- Constructing Holistic Patient Flow Simulation Using System Approach -- Investigating Coordination of Hospital Departments in Delivering Healthcare for Acute Coronary SyndromePatients using Data-Driven Network Analysis -- A Machine Learning Approach To Short-term Body Weight Prediction In A Dietary Intervention Program -- An analysis of demographic data in Irish healthcare domain to support semantic uplift -- From Population to Subject-Specific Reference Intervals -- Analyzing the spatial distribution of acute coronary syndrome cases using synthesized data on arterial hypertension prevalence -- The Atrial Fibrillation Risk Score for Hyperthyroidism Patients -- Applicability of Machine Learning Methods to Multi-Label Medical Text Classification -- Machine Learning Approach for the Early Prediction of the Risk of Overweight and Obesity in Young People -- Gait Abnormality Detection in People with Cerebral Palsy using an Uncertainty-based State-space Model -- Analyses of public health databases via clinical pathway modelling: TBWEB -- Preliminary results on Pulmonary Tuberculosis detection in Chest X-Ray using Convolutional Neural Networks -- Risk-based AED Placement – Singapore Case -- Time Expressions Identification without Human-labeled Corpus for Clinical Text Mining in Russian -- Experiencer detection and automated extraction of a family disease tree from medical texts in Russian language -- Computational Methods for Emerging Problems in (Dis-)Information Analysis -- Machine Learning – the results are not the only thing that matters! What about security, explainability and fairness? -- Syntactic and Semantic Bias Detection and Countermeasures -- Detecting Rumours in Disasters: An Imbalanced Learning Approach -- Sentiment Analysis for Fake News Detection by Means of Neural Networks. |
| 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 IV
