Computational Science – ICCS 2020

TRAMA

The seven-volume set LNCS 12137, 12138, 12139, 12140, 12141, 12142, and 12143 constitutes the proceedings of the 20th International Conference on Computational Science, ICCS 2020, held in Amsterdam, The Netherlands, in June 2020.* The total of 101 papers and 248 workshop papers presented in this book set were carefully reviewed and selected from 719 submissions (230 submissions to the main track and 489 submissions to the workshops). The papers were organized in topical sections named:Part I: ICCS Main Track Part II: ICCS Main Track Part III: Advances in High-Performance Computational Earth Sciences: Applications and Frameworks; Agent-Based Simulations, Adaptive Algorithms and Solvers; Applications of Computational Methods in Artificial Intelligence and Machine Learning; Biomedical and Bioinformatics Challenges for Computer SciencePart IV: Classifier Learning from Difficult Data; Complex Social Systems through the Lens of Computational Science; Computational Health; Computational Methods for Emerging Problems in (Dis-)Information AnalysisPart V: Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems; Computer Graphics, Image Processing and Artificial IntelligencePart VI: Data Driven Computational Sciences; Machine Learning and Data Assimilation for Dynamical Systems; Meshfree Methods in Computational Sciences; Multiscale Modelling and Simulation; Quantum Computing Workshop Part VII: 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 Uncertainties; Teaching Computational Science; UNcErtainty QUantIficatiOn for ComputationAl modeLs*The conference was canceled due to the COVID-19 pandemic.

SOMMARIO

Classifier Learning from Difficult Data.- Di?erent 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 Di?usion and Emerging Complexity in Innovation Systems.- Mapping the port influence di?usion 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.

ALTRE INFORMAZIONI

• Condizione: Nuovo
• ISBN: 9783030504229
• Collana: Lecture Notes in Computer Science
• Dimensioni: 235 x 155 mm
• Formato: Brossura
• Illustration Notes: XIX, 668 p. 247 illus., 192 illus. in color.
• Pagine Arabe: 668
• Pagine Romane: xix