Traceable use of emerging technologies in smart systems

doi:10.17185/duepublico/81675

Sammelwerk Di., 28. Nov.. 2023 CC BY-ND 4.0

Veröffentlicht

Traceable use of emerging technologies in smart systems

Schiele, Gregor (Hrsg.); Luther, Wolfram (Hrsg.)

This volume presents a selection of invited papers from the 3^rd Workshop on Collaborative Technologies and Data Science in Smart City Applications (CODASSCA 2022): From Data to Information and Knowledge, held in Yerevan, Armenia, August, 23-25, and further articles from a free call for papers JUCS-CODASSCA-2023 published by Easychair. The workshop continues the cooperation between the University of Duisburg‐Essen (UDE) and the American University of Armenia (AUA) funded by the German Academic Exchange Service (DAAD) and the German Research Foundation (DFG). The workshop took place together with a one-week summer school on the topic Enhancements of Deep Learning for Intelligent Applications and the Connected Society.

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Datum der Veröffentlichung:: 28.11.2023
URN:: urn:nbn:de:hbz:465-20240228-090549-3
DOI:: 10.17185/duepublico/81675
Sprache:: Englisch
Ressourcentyp:: Text
Schlagwörter:: AI-based data mining; application troubleshooting; authentication; automated root cause analysis (RCA); BRCA1/2 mutation probability; cloud infrastructures; cloud-native applications; cyclical patterns; data fusion & integration; Dempster-Shafer evidence theory (DST); distance learning; distributed tracing; explainable AI (XAI); hypothesis testing; interval analysis; key performance indicators (KPI); machine learning (ML); project-based learning; RED metrics; rule-induction systems; sales goals and operation planning; security; social networks; spatio-temporal data; video activity report; work engagement
Kollektion:: E-Publikationen
Sachgruppen der Deutschen Nationalbibliographie:: 004 Informatik
Link URL:: https://lib.jucs.org/issue/4670
Einrichtung:: Fakultät für Ingenieurwissenschaften, Informatik und Angewandte Kognitionswissenschaft, Informatik, Intelligente Systeme
Förderung:: Die Veröffentlichung dieses Werkes wurde aus Mitteln des Publikationsfonds der Universität Duisburg-Essen unterstützt.
Informationen zur Erstveröffentlichung:: JUCS - Journal of Universal Computer Science, 2023, 29(11): Special Issue.
https://lib.jucs.org/issue/4670
Versionskennzeichen:: Version of Record / Verlagsversion