000937679 000__ 06823cam\a2200577Ii\4500 000937679 001__ 937679 000937679 005__ 20230306151847.0 000937679 006__ m\\\\\o\\d\\\\\\\\ 000937679 007__ cr\nn\nnnunnun 000937679 008__ 200630s2020\\\\sz\a\\\\o\\\\\101\0\eng\d 000937679 019__ $$a1164675180 000937679 020__ $$a9783030504236$$q(electronic book) 000937679 020__ $$a3030504239$$q(electronic book) 000937679 020__ $$z9783030504229 000937679 0248_ $$a10.1007/978-3-030-50 000937679 035__ $$aSP(OCoLC)on1162199067 000937679 035__ $$aSP(OCoLC)1162199067$$z(OCoLC)1164675180 000937679 040__ $$aLQU$$beng$$cLQU$$dLEATE$$dGW5XE 000937679 049__ $$aISEA 000937679 050_4 $$aQA75.5$$b.I23 2020eb 000937679 08204 $$a004.0151 000937679 1112_ $$aInternational Conference on Computational Science$$n(20th :$$d2020 :$$cAmsterdam, Netherlands) 000937679 24510 $$aComputational Science -- ICCS 2020 :$$b20th International Conference, Amsterdam, The Netherlands, June 3-5, 2020, Proceedings.$$nPart IV /$$cValeria V. Krzhizhanovskaya, Gábor Závodszky, Michael H. Lees, Jack J. Dongarra, Peter M. A. Sloot, Sérgio Brissos, João Teixeira (eds.). 000937679 2463_ $$aICCS 2020 000937679 264_1 $$aCham :$$bSpringer,$$c2020. 000937679 300__ $$a1 online resource (xix, 668 pages) :$$billustrations 000937679 336__ $$atext$$btxt$$2rdacontent 000937679 337__ $$acomputer$$bc$$2rdamedia 000937679 338__ $$aonline resource$$bcr$$2rdacarrier 000937679 4901_ $$aLecture notes in computer science ;$$v12140 000937679 4901_ $$aLNCS Sublibrary: SL 1, Theoretical Computer Science and General Issues 000937679 500__ $$aInternational conference proceedings. 000937679 500__ $$aIncludes author index. 000937679 5050_ $$aUtional 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 ion 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 Syndrome Patients 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 Convol. 000937679 506__ $$aAccess limited to authorized users. 000937679 520__ $$aThe 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 Science Part 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 Analysis Part V: Computational Optimization, Modelling and Simulation; Computational Science in IoT and Smart Systems; Computer Graphics, Image Processing and Artificial Intelligence Part 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. 000937679 650_0 $$aComputer science$$vCongresses. 000937679 650_0 $$aComputational complexity$$vCongresses. 000937679 7001_ $$aKrzhizhanovskaya, Valeria V. 000937679 7001_ $$aZávodszky, Gábor. 000937679 7001_ $$aLees, Michael H. 000937679 7001_ $$aDongarra, J. J. 000937679 7001_ $$aSloot, Peter,$$d1956- 000937679 7001_ $$aBrissos, Sérgio. 000937679 7001_ $$aTeixeira, João. 000937679 830_0 $$aLecture notes in computer science ;$$v12140. 000937679 830_0 $$aLNCS sublibrary.$$nSL 1,$$pTheoretical computer science and general issues. 000937679 852__ $$bebk 000937679 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-030-50423-6$$zOnline Access$$91397441.1 000937679 909CO $$ooai:library.usi.edu:937679$$pGLOBAL_SET 000937679 980__ $$aEBOOK 000937679 980__ $$aBIB 000937679 982__ $$aEbook 000937679 983__ $$aOnline 000937679 994__ $$a92$$bISE