[PDF] 2020 Ieee Real Time Systems Symposium Rtss eBook
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The IEEE Real Time Systems Symposium (RTSS) is the premier conference in the field of real time systems, and is a venue for researchers and practitioners to showcase innovations covering all aspects of real time systems, including theory, design, analysis, implementation, evaluation, and experience RTSS 2020 continues the trend of making RTSS an expansive and inclusive event, striving to embrace new and emerging areas of real time systems research RTSS 2020 welcomes submissions of high quality, original research papers related to both real time system theory and practice Submissions can go to either the real time system track (Track 1) or the design and application track (Track 2) which covers Cyber Physical Systems, HW SW integration and system level design, and Internet of Things (IoT)
This book constitutes revised selected papers from the 26th Argentine Congress on Computer Science, CACIC 2020, held in San Justo, Buenos Aires, Argentina in October 2020. Due to the COVID-19 pandemic the conference was held in a virtual mode. The 21 full papers and 3 short papers presented in this volume were carefully reviewed and selected from a total of 118 submissions. They were organized in topical sections named: intelligent agents and systems; distributed and parallel processing; computer technology applied to education; graphic computation, images and visualization; software engineering; databases and data mining; hardware architectures, networks, and operating systems; innovation in software systems; signal processing and real-time systems; innovation in computer science education; computer security; and digital governance and smart cities.
This book constitutes the thoroughly refereed proceedings of the 39th National Conference of Theoretical Computer Science, NCTCS 2021, held in Yinchuan, China, in July 2021. The 67 full papers were carefully reviewed and selected from 145 submissions, and 14 of them were selected for the volume. The papers present recent research in the areas of information hiding, data detection and recognition, system scheduling, time series prediction, and formal analysis.
This book constitutes the thoroughly refereed post-conference proceedings of the 26th International Workshop on Job Scheduling Strategies for Parallel Processing, JSSPP 2023, held in St. Petersburg, FL, USA, during May 19, 2023. The 8 full papers and one keynote paper included in this book were carefully reviewed and selected from 14 submissions. The volume contains two sections: keynote and technical papers.
Providing a high level of autonomy for a human-machine team requires assumptions that address behavior and mutual trust. The performance of a human-machine team is maximized when the partnership provides mutual benefits that satisfy design rationales, balance of control, and the nature of autonomy. The distinctively different characteristics and features of humans and machines are likely why they have the potential to work well together, overcoming each other's weaknesses through cooperation, synergy, and interdependence which forms a “collective intelligence. Trust is bidirectional and two-sided; humans need to trust AI technology, but future AI technology may also need to trust humans.Putting AI in the Critical Loop: Assured Trust and Autonomy in Human-Machine Teams focuses on human-machine trust and “assured performance and operation in order to realize the potential of autonomy. This book aims to take on the primary challenges of bidirectional trust and performance of autonomous systems, providing readers with a review of the latest literature, the science of autonomy, and a clear path towards the autonomy of human-machine teams and systems. Throughout this book, the intersecting themes of collective intelligence, bidirectional trust, and continual assurance form the challenging and extraordinarily interesting themes which will help lay the groundwork for the audience to not only bridge the knowledge gaps, but also to advance this science to develop better solutions. Assesses the latest research advances, engineering challenges, and the theoretical gaps surrounding the question of autonomy Reviews the challenges of autonomy (e.g., trust, ethics, legalities, etc.), including gaps in the knowledge of the science Offers a path forward to solutions Investigates the value of trust by humans of HMTs, as well as the bidirectionality of trust, understanding how machines learn to trust their human teammates