Título :	21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part III
Tipo de documento:	documento electrónico
Autores:	Paszynski, Maciej, ; Kranzlmüller, Dieter, ; Krzhizhanovskaya, Valeria V., ; Dongarra, Jack J., ; Sloot, Peter M.A,
Mención de edición:	1 ed.
Editorial:	[s.l.] : Springer
Fecha de publicación:	2021
Número de páginas:	XX, 745 p. 212 ilustraciones, 159 ilustraciones en color.
ISBN/ISSN/DL:	978-3-030-77967-2
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  Ingeniería Informática  Red de computadoras  Informática  Teoría de la Computación  Ingeniería Informática y Redes  Matemáticas de la Computación
Índice Dewey:	40.151
Resumen:	El conjunto de seis volúmenes LNCS 12742, 12743, 12744, 12745, 12746 y 12747 constituye las actas de la 21.ª Conferencia Internacional sobre Ciencias Computacionales, ICCS 2021, celebrada en Cracovia, Polonia, en junio de 2021.* El total de 260 artículos completos y 57 artículos breves presentados en este conjunto de libros fueron cuidadosamente revisados ​​y seleccionados entre 635 presentaciones. Se aceptaron 48 artículos completos y 14 breves en la sección principal de 156 presentaciones; Se aceptaron 212 artículos completos y 43 breves para los talleres/vías temáticas de 479 presentaciones. Los artículos se organizaron en secciones temáticas denominadas: Parte I: Vía principal de ICCS Parte II: Avances en ciencias computacionales de la Tierra de alto rendimiento: aplicaciones y marcos; Aplicaciones de Métodos Computacionales en Inteligencia Artificial y Aprendizaje Automático; Inteligencia Artificial y Computación de Alto Rendimiento para Simulaciones Avanzadas; Desafíos biomédicos y bioinformáticos para la informática Parte III: Aprendizaje del clasificador a partir de datos difíciles; Análisis Computacional de Sistemas Sociales Complejos; Inteligencia Colectiva Computacional; Salud computacional Parte IV: Métodos computacionales para problemas emergentes en el análisis de (des)información; Métodos Computacionales en Agricultura Inteligente; Optimización, Modelado y Simulación Computacional; Ciencias Computacionales en IoT y Sistemas Inteligentes Parte V: Gráficos por Computadora, Procesamiento de Imágenes e Inteligencia Artificial; Ciencias Computacionales Basadas en Datos; Aprendizaje Automático y Asimilación de Datos para Sistemas Dinámicos; Métodos MeshFree y funciones de base radial en ciencias computacionales; Modelado y Simulación Multiescala Parte VI: Taller de Computación Cuántica; 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 Incertidumbre; Enseñanza de Ciencias Computacionales; Cuantificación de la incertidumbre para modelos computacionales *La conferencia se realizó de manera virtual.
Nota de contenido:	Classifier Learning from Difficult Data -- Soft Confusion Matrix Classifier for Stream Classification -- Some proposal of the high dimensional PU learning classification procedure -- Classifying Functional Data from Orthogonal Projections – model, properties and fast implementation -- Clustering and Weighted Scoring Algorithm Based on Estimating the Number of Clusters -- Exact Searching for the Smallest Deterministic Automaton -- Learning Invariance in Deep Neural Networks -- Mimicking learning for 1-NN classifiers -- Application of Multi-Objective Optimization to Feature Selection for a Difficult Data Classification Task -- Deep Embedding Features for Action Recognition on Raw Depth Maps -- Analysis of variance application in the construction of classifier ensemble based on optimal feature subset for the task of supporting glaucoma diagnosis -- Multi-objective evolutionary undersampling algorithm for imbalanced data classification -- Missing value imputation method using separate features nearest neighbors algorithm -- On Validity of Extreme Value Theory-Based Parametric Models for Out-of-Distribution Detection -- Clustering-based Ensemble Pruning in the Imbalanced Data Classification -- Improvement of random undersampling to avoid excessive removal of points from a given area of the majority class -- Predictability Classes for Forecasting Bank Clients Behavior by Transactional Data -- A Non-Intrusive Machine Learning Solution for Malware Detection and Data Theft Classification in Smartphones -- Analysis of Semestral Progress in Higher Technical Education with HMM Models -- Vicinity-based Abstraction: VA-DGCNN Architecture for Noisy 3D Indoor Object Classification -- Grid-Based Concise Hash for Solar Images -- Machine learning algorithms for conversion of CVSS base score from 2.0 to 3.x -- Applicability of Machine Learning to Short-Term Prediction of Changes in the Low Voltage Electricity Distribution Network -- Computational Analysis of Complex Social Systems.-A Model for Urban Social Networks -- Three-state opinion q-voter model with bounded confidence -- The evolution of political views within the model with two binary opinions -- How to reach consensus? Better disagree with your neighbor -- Efficient calibration of a financial agent-based model using the method of simulated moments -- Computational Collective Intelligence -- A Method for Improving Word Representation Using Synonym Information -- Fast Approximate String Search for Wikification -- ASH: A New Tool for Automated and Full-Text Search in Systematic Literature Reviews -- A Voice-based Travel Recommendation System Using Linked Open Data -- Learning from Imbalanced Data Streams based on Over-Sampling and Instance Selection -- Computational Intelligence Techniques for Assessing Data Quality: Towards Knowledge-Driven Processing -- The Power of a Collective: Team of Agents Solving Instances of the Flow Shop and Job Shop Problems -- Bagging and single decision tree approaches todispersed data -- An Intelligent Social Collective with Facebook-based Communication -- Multi-Agent Spatial SIR-Based Modeling and Simulation of Infection Spread Management -- Multi-Criteria Seed Selection for Targeted In uence Maximization within Social Networks -- How Attachment to your Primary Caregiver Influences your First Adult Relationship: An Adaptive Network Model of Attachment Theory -- Computational Health -- Hybrid Predictive Modelling for Finding Optimal Multipurpose Multicomponent Therapy -- Towards cost-effective treatment of periprosthetic joint infection: from statistical analysis to Markov models -- Optimization of Selection of Tests in Diagnosing the Patient by General Practitioner -- Simulation of Burnout Processes by a Multi-Order Adaptive Network Model -- Reversed Correlation-Based Pairwised EEG Channel Selection in Emotional State Recognition -- Theory of Mind Helps to Predict Neurodegenerative Processes in Parkinson's Disease -- Regaining Cognitive Control: AnAdaptive Computational Model Involving Neural Correlates of Stress, Control and Intervention -- MAM: A Metaphor-based Approach for Mental Illness Detection -- Feature Engineering with Process Mining Technique for Patient State Predictions -- Comparative Evaluation of Lung Cancer CT Image Synthesis with Generative Adversarial Networks -- Deep convolutional neural networks in application to kidney segmentation in the DCE-MR images -- Comparison of Efficiency, Stability and Interpretability of Feature Selection Methods for Multiclassification Task on Medical Tabular Data -- Side effect alerts generation from EHR in Polish -- des-ist: a simulation framework to streamline event-based in silico trials -- Identifying Synergistic Interventions to Address COVID-19 Using a Large Scale Agent-Based Model -- Modeling co-circulation of influenza strains in heterogeneous urban populations: the role of herd immunity and uncertainty factors -- Two-Way Coupling Between 1D Blood Flow and 3D Tissue Perfusion Models -- Applying DCT combined cepstrum for the assessment of the arteriovenous fistula condition -- Electrocardiogram Quality Assessment with Autoencoder -- Stenosis assessment via volumetric flow rate calculation -- Fuzzy ontology for patient emergency department triage -- Ontology-based decision support system for dietary recommendations for type 2 diabetes mellitus.
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

21st International Conference, Krakow, Poland, June 16–18, 2021, Proceedings, Part III [documento electrónico] / Paszynski, Maciej, ; Kranzlmüller, Dieter, ; Krzhizhanovskaya, Valeria V., ; Dongarra, Jack J., ; Sloot, Peter M.A,  . -  1 ed.  . - [s.l.] : Springer, 2021 . - XX, 745 p. 212 ilustraciones, 159 ilustraciones en color.
ISBN : 978-3-030-77967-2
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  Ingeniería Informática  Red de computadoras  Informática  Teoría de la Computación  Ingeniería Informática y Redes  Matemáticas de la Computación
Índice Dewey:	40.151
Resumen:	El conjunto de seis volúmenes LNCS 12742, 12743, 12744, 12745, 12746 y 12747 constituye las actas de la 21.ª Conferencia Internacional sobre Ciencias Computacionales, ICCS 2021, celebrada en Cracovia, Polonia, en junio de 2021.* El total de 260 artículos completos y 57 artículos breves presentados en este conjunto de libros fueron cuidadosamente revisados ​​y seleccionados entre 635 presentaciones. Se aceptaron 48 artículos completos y 14 breves en la sección principal de 156 presentaciones; Se aceptaron 212 artículos completos y 43 breves para los talleres/vías temáticas de 479 presentaciones. Los artículos se organizaron en secciones temáticas denominadas: Parte I: Vía principal de ICCS Parte II: Avances en ciencias computacionales de la Tierra de alto rendimiento: aplicaciones y marcos; Aplicaciones de Métodos Computacionales en Inteligencia Artificial y Aprendizaje Automático; Inteligencia Artificial y Computación de Alto Rendimiento para Simulaciones Avanzadas; Desafíos biomédicos y bioinformáticos para la informática Parte III: Aprendizaje del clasificador a partir de datos difíciles; Análisis Computacional de Sistemas Sociales Complejos; Inteligencia Colectiva Computacional; Salud computacional Parte IV: Métodos computacionales para problemas emergentes en el análisis de (des)información; Métodos Computacionales en Agricultura Inteligente; Optimización, Modelado y Simulación Computacional; Ciencias Computacionales en IoT y Sistemas Inteligentes Parte V: Gráficos por Computadora, Procesamiento de Imágenes e Inteligencia Artificial; Ciencias Computacionales Basadas en Datos; Aprendizaje Automático y Asimilación de Datos para Sistemas Dinámicos; Métodos MeshFree y funciones de base radial en ciencias computacionales; Modelado y Simulación Multiescala Parte VI: Taller de Computación Cuántica; 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 Incertidumbre; Enseñanza de Ciencias Computacionales; Cuantificación de la incertidumbre para modelos computacionales *La conferencia se realizó de manera virtual.
Nota de contenido:	Classifier Learning from Difficult Data -- Soft Confusion Matrix Classifier for Stream Classification -- Some proposal of the high dimensional PU learning classification procedure -- Classifying Functional Data from Orthogonal Projections – model, properties and fast implementation -- Clustering and Weighted Scoring Algorithm Based on Estimating the Number of Clusters -- Exact Searching for the Smallest Deterministic Automaton -- Learning Invariance in Deep Neural Networks -- Mimicking learning for 1-NN classifiers -- Application of Multi-Objective Optimization to Feature Selection for a Difficult Data Classification Task -- Deep Embedding Features for Action Recognition on Raw Depth Maps -- Analysis of variance application in the construction of classifier ensemble based on optimal feature subset for the task of supporting glaucoma diagnosis -- Multi-objective evolutionary undersampling algorithm for imbalanced data classification -- Missing value imputation method using separate features nearest neighbors algorithm -- On Validity of Extreme Value Theory-Based Parametric Models for Out-of-Distribution Detection -- Clustering-based Ensemble Pruning in the Imbalanced Data Classification -- Improvement of random undersampling to avoid excessive removal of points from a given area of the majority class -- Predictability Classes for Forecasting Bank Clients Behavior by Transactional Data -- A Non-Intrusive Machine Learning Solution for Malware Detection and Data Theft Classification in Smartphones -- Analysis of Semestral Progress in Higher Technical Education with HMM Models -- Vicinity-based Abstraction: VA-DGCNN Architecture for Noisy 3D Indoor Object Classification -- Grid-Based Concise Hash for Solar Images -- Machine learning algorithms for conversion of CVSS base score from 2.0 to 3.x -- Applicability of Machine Learning to Short-Term Prediction of Changes in the Low Voltage Electricity Distribution Network -- Computational Analysis of Complex Social Systems.-A Model for Urban Social Networks -- Three-state opinion q-voter model with bounded confidence -- The evolution of political views within the model with two binary opinions -- How to reach consensus? Better disagree with your neighbor -- Efficient calibration of a financial agent-based model using the method of simulated moments -- Computational Collective Intelligence -- A Method for Improving Word Representation Using Synonym Information -- Fast Approximate String Search for Wikification -- ASH: A New Tool for Automated and Full-Text Search in Systematic Literature Reviews -- A Voice-based Travel Recommendation System Using Linked Open Data -- Learning from Imbalanced Data Streams based on Over-Sampling and Instance Selection -- Computational Intelligence Techniques for Assessing Data Quality: Towards Knowledge-Driven Processing -- The Power of a Collective: Team of Agents Solving Instances of the Flow Shop and Job Shop Problems -- Bagging and single decision tree approaches todispersed data -- An Intelligent Social Collective with Facebook-based Communication -- Multi-Agent Spatial SIR-Based Modeling and Simulation of Infection Spread Management -- Multi-Criteria Seed Selection for Targeted In uence Maximization within Social Networks -- How Attachment to your Primary Caregiver Influences your First Adult Relationship: An Adaptive Network Model of Attachment Theory -- Computational Health -- Hybrid Predictive Modelling for Finding Optimal Multipurpose Multicomponent Therapy -- Towards cost-effective treatment of periprosthetic joint infection: from statistical analysis to Markov models -- Optimization of Selection of Tests in Diagnosing the Patient by General Practitioner -- Simulation of Burnout Processes by a Multi-Order Adaptive Network Model -- Reversed Correlation-Based Pairwised EEG Channel Selection in Emotional State Recognition -- Theory of Mind Helps to Predict Neurodegenerative Processes in Parkinson's Disease -- Regaining Cognitive Control: AnAdaptive Computational Model Involving Neural Correlates of Stress, Control and Intervention -- MAM: A Metaphor-based Approach for Mental Illness Detection -- Feature Engineering with Process Mining Technique for Patient State Predictions -- Comparative Evaluation of Lung Cancer CT Image Synthesis with Generative Adversarial Networks -- Deep convolutional neural networks in application to kidney segmentation in the DCE-MR images -- Comparison of Efficiency, Stability and Interpretability of Feature Selection Methods for Multiclassification Task on Medical Tabular Data -- Side effect alerts generation from EHR in Polish -- des-ist: a simulation framework to streamline event-based in silico trials -- Identifying Synergistic Interventions to Address COVID-19 Using a Large Scale Agent-Based Model -- Modeling co-circulation of influenza strains in heterogeneous urban populations: the role of herd immunity and uncertainty factors -- Two-Way Coupling Between 1D Blood Flow and 3D Tissue Perfusion Models -- Applying DCT combined cepstrum for the assessment of the arteriovenous fistula condition -- Electrocardiogram Quality Assessment with Autoencoder -- Stenosis assessment via volumetric flow rate calculation -- Fuzzy ontology for patient emergency department triage -- Ontology-based decision support system for dietary recommendations for type 2 diabetes mellitus.
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