JUCS - Journal of Universal Computer Science 29(11): 1250-1253, doi: 10.3897/jucs.112577
Traceable Use of Emerging Technologies in Smart Systems
expand article infoWolfram Luther‡, Gregor Schiele‡
‡ University of Duisburg‐Essen, Duisburg, Germany

Corresponding author: Wolfram Luther ( wolfram.luther@gmail.com )

© Wolfram Luther, Gregor Schiele.
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Citation: Luther W, Schiele G (2023) Traceable Use of Emerging Technologies in Smart Systems. JUCS - Journal of Universal Computer Science 29(11): 1250-1253. https://doi.org/10.3897/jucs.112577
Open Access
Abstract
This volume presents a selection of invited papers from the 3rd 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. 
Keywords
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