Digital human modeling and applications in health, safety, ergonomics and risk management. Anthropometry, human behavior, and communication : 13th International Conference, DHM 2022, held as part of the 24th HCI International Conference, HCII 2022, Virtual event, June 26-July 1, 2022, Proceedings. Part I / / Vincent G. Duffy (editor)

• Record Nr.: UNISA996478869603316
• Pubbl/distr/stampa: Cham, Switzerland : , : Springer, , [2022]; ©2022
• ISBN: 9783031058905; 9783031058899
• Descrizione fisica: 1 online resource (377 pages)
• Collana: Lecture notes in computer science ; ; 13319
• Disciplina: 001.434
• Soggetti: Digital computer simulation; Medical care - Data processing
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Note generali: Description based upon print version of record.
• Nota di bibliografia: Includes bibliographical references and index.

Data Science : 4th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2018, Zhengzhou, China, September 21-23, 2018, Proceedings, Part II / / edited by Qinglei Zhou, Qiguang Miao, Hongzhi Wang, Wei Xie, Yan Wang, Zeguang Lu

• Record Nr.: UNINA9910299301903321
• Pubbl/distr/stampa: Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2018
• ISBN: 978-981-13-2206-8; 981-13-2206-6
• Edizione: [1st ed. 2018.]
• Descrizione fisica: 1 online resource (XXIX, 649 p. 269 illus.)
• Collana: Communications in Computer and Information Science, , 1865-0937 ; ; 902
• Disciplina: 006.3
• Soggetti: Data mining; Application software; Artificial intelligence; Computer networks; Image processing - Digital techniques; Computer vision; Data Mining and Knowledge Discovery; Computer and Information Systems Applications; Artificial Intelligence; Computer Communication Networks; Computer Imaging, Vision, Pattern Recognition and Graphics
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di contenuto: Computational theory for data science -- Big data management and applications -- Data quality and data preparation -- Evaluation and measurement in data science -- Data visualization -- Big data mining and knowledge management -- Infrastructure for data science -- Machine learning for data science -- Data security and privacy -- Applications of data science -- Case study of data science -- Multimedia data management and analysis -- Data-driven scientific research -- Data-driven bioinformatics -- Data-driven healthcare -- ; Data-driven management -- Data-driven e-government -- Data-driven smart city/planet -- Data marketing and economics -- Social media and recommendation systems -- Data-driven security -- Data-driven business model innovation -- Social and/or organizational impacts of data science.
• Sommario/riassunto: This two volume set (CCIS 901 and 902) constitutes the refereed proceedings of the 4th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2018 (originally ICYCSEE) held in Zhengzhou, China, in September 2018. The 125 revised full papers presented in these two volumes were carefully reviewed and selected from 1057 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including mathematical issues in data science, computational theory for data science, big data management and applications, data quality and data preparation, evaluation and measurement in data science, data visualization, big data mining and knowledge management, infrastructure for data science, machine learning for data science, data security and privacy, applications of data science, case study of data science, multimedia data management and analysis, data-driven scientific research, data-driven bioinformatics, data-driven healthcare, data-driven management, data-driven eGovernment, data-driven smart city/planet, data marketing and economics, social media and recommendation systems, data-driven security, data-driven business model innovation, social and/or organizational impacts of data science.