Big-Data-Analytics in Astronomy, Science, and Engineering [[electronic resource] ] : 9th International Conference on Big Data Analytics, BDA 2021, Virtual Event, December 7–9, 2021, Proceedings / / edited by Shelly Sachdeva, Yutaka Watanobe, Subhash Bhalla

• Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022
• Edizione: 1st ed. 2022.
• Descrizione fisica: 1 online resource (283 pages)
• Disciplina: 006.312
• Soggetto topico: Data mining; Computer engineering; Computer networks; Application software; Machine learning; Data Mining and Knowledge Discovery; Computer Engineering and Networks; Computer and Information Systems Applications; Machine Learning
• Persona (resp. second.): WatanobeYutaka; SachdevaShelly; BhallaSubhash <1956->
• Note generali: Includes index.
• Nota di contenuto: Data Science: Systems -- Big Data Management for Policy Support in Sustainable Development -- Development of the Research Data Archive at OIST -- Symbolic Regression and Graph Neural Networks for Interpretable Scientic Discovery -- A front-end framework selection assistance system with customizable quantification indicators based on analysis of repository and community data -- DATA SCIENCE: Architectures -- Autonomous real-time science-driven follow-up of survey transients -- Deep Learning Application for Reconstruction of Large-Scale Structure of the Universe -- Identification of Distinctive Behavior Patterns of Bots and Human Teams in Soccer -- Cosmic density field reconstruction with a sparsity prior using images of distant galaxies -- Big Data Analytics in Domain-Specific Systems -- Blockchain Enabled System for Interoperable Healthcare -- Skin cancer recognition for low resolution images -- Forecasting AQI data with IoT Enabled Indoor Air Quality Monitoring System -- Journey of Database Migration From RDBMS to NoSQL Data Stores -- Information Interchange of Web Data Resources -- Cascaded Anomaly Detection with Coarse Sampling in Distributed Systems -- Video Indexing System based on Multimodal Information Extraction using combination of ASR and OCR -- GA-ProM: A Genetic Algorithm for Discovery of Complete Process Models from Unbalanced logs -- Experimenting with Assamese Handwritten Character Recognition -- Business Analytics -- Approximate Fault-tolerant Data Stream Aggregation for Edge Computing -- Internet of Things Integrated with Multi-level Authentication for Secured IoT Data Stream through TLS/SSL Layer -- Enhanced Bond Energy Algorithm for Vertical Fragmentation of IoT Data in a Fog Environment -- Approximate Query Processing with Error Guarantees. .
• Sommario/riassunto: This book constitutes the proceedings of the 9th International Conference on Big Data Analytics, BDA 2021, which took place virtually during December 7–9, 2021. The 15 full papers and 1 short paper included in this volume were carefully reviewed and selected from 60 submissions. They were organized in topical sections as follows: Data science: systems; data science: architectures; big data analytics in healthcare support systems, information interchange of web data resources; and business analytics.
• Titolo autorizzato: Big-data-analytics in astronomy, science, and engineering
• ISBN: 3-030-96600-3
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996464534303316
• Lo trovi qui: Univ. di Salerno
• Serie: Information Systems and Applications, incl. Internet/Web, and HCI ; ; 13167