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Titlebook: Dependable Computing – EDCC 2024 Workshops; SafeAutonomy, TRUST Behrooz Sangchoolie,Rasmus Adler,Adriano Mancini Conference proceedings 20

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发表于 2025-3-21 18:56:42 | 显示全部楼层 |阅读模式
书目名称Dependable Computing – EDCC 2024 Workshops
副标题SafeAutonomy, TRUST
编辑Behrooz Sangchoolie,Rasmus Adler,Adriano Mancini
视频video
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Dependable Computing – EDCC 2024 Workshops; SafeAutonomy, TRUST  Behrooz Sangchoolie,Rasmus Adler,Adriano Mancini Conference proceedings 20
描述This book constitutes the refereed proceedings of Workshops held at the 19th European Dependable Computing Conference, EDCC 2024: ​First Workshop on Safe Autonomous Systems, SafeAutonomy 2024, and the First Workshop on the Role of TRUST in the implementation of Digital Technologies: Blockchain Technology and Artificial Intelligence in Smart Cities, TRUST IN BLOCKCHAIN 2024. .The 13 workshop papers presented in this book were thoroughly reviewed and selected from 14 submissions. The TRUST IN BLOCKCHAIN workshop accepted extended abstract submissions, whereas the SafeAutonomy workshop accepted regular technical papers, case studies, PhD forum papers, as well as position papers. They deal with latest research results on theory, techniques, systems, and tools for the design, validation, operationand evaluation of dependable and secure computing systems. .
出版日期Conference proceedings 2024
关键词artificial intelligence; blockchain; energy trading; demand response; cyber security; forecasting; deep le
版次1
doihttps://doi.org/10.1007/978-3-031-56776-6
isbn_softcover978-3-031-56775-9
isbn_ebook978-3-031-56776-6Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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STARS: A Tool for Measuring Scenario Coverage When Testing Autonomous Robotic Systemsthe automotive domain. To enable statements on the absolute number or fractions of tested scenarios, methods and tools for computing their coverage are needed. In this paper, we present STARS, a tool for specifying semantic environment features and measuring scenario coverage when testing autonomous systems.
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https://doi.org/10.1007/978-3-0348-9236-0testing methods, become infeasible. Virtual testing seems like a promising alternative to traditional methods, especially as part of a scenario-based verification and validation methodology. But in order to transfer the test results of a system from a simulation to the real world, we need to argue t
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Linear Discrete Dynamical Systems,an be not avoided, system-specific instantiations of assurance case patterns are both costly and time-consuming. It becomes especially complex to maintain an assurance case for a system when the requirements of the System-Under-Assurance change, or an assurance claim becomes invalid due to, e.g., de
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Computational Dynamical Systems Using XPPAUTthe automotive domain. To enable statements on the absolute number or fractions of tested scenarios, methods and tools for computing their coverage are needed. In this paper, we present STARS, a tool for specifying semantic environment features and measuring scenario coverage when testing autonomous
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