1,327 research outputs found

    LIPIcs, Volume 251, ITCS 2023, Complete Volume

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    LIPIcs, Volume 251, ITCS 2023, Complete Volum

    Analysis in Web 3D Environments of Thematic Research Networks on Immersive Learning through Variation of Clustering Criteria

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    Este projeto tem como objetivo desenvolver uma ferramenta de visualização 3D baseada na web que proporciona uma compreensão global do campo de Aprendizagem Imersiva. As redes temáti- cas são uma abordagem bem estabelecida para lidar com esses desafios. Portanto, foi realizada uma revisão sistemática da literatura para extrair métodos e critérios de clustering em redes temáticas. A metodologia empregada neste estudo é a pesquisa de Design Science Research, que envolveu o desenvolvimento e a avaliação iterativos da ferramenta de visualização. Entre- vistas com especialistas foram realizadas para identificar os requisitos, e métodos rigorosos, in- cluindo gravação, análise e transcrição das entrevistas, foram aplicados para verificar a relevância da pesquisa. A ferramenta utiliza uma abordagem de visualização de node-link para visualizar estratégias, práticas e artigos associados à aprendizagem imersiva. Além disso, oferece uma var- iedade de funcionalidades de filtragem, permitindo que os usuários filtrem por estratégias, práticas, autores, instituições e outros. Além disso, a ferramenta incorpora várias funcionalidades de clus- tering, como detecção de comunidades usando o algoritmo de Louvain, com variação de critérios de clustering , como associação de temas e de artigos, citação de artigos, co-citação e outros. Os usuários também podem controlar a estrutura da rede modificando o tamanho das clustering, o número e as cores das comunidades. A ferramenta apresenta métodos exploratórios de redes temáticas para navegar no ambiente. Ao combinar redes temáticas com capacidades de clustering e filtragem, essa ferramenta tem como objetivo fornecer uma compreensão global do campo cien- tífico. Sua integração única de tecnologias Web e 3D, juntamente com métodos exploratórios, a diferencia das ferramentas de visualização existentes. Os poderosos algoritmos de clustering da ferramenta, oferecendo critérios diversos para entender as relações conceituais, têm o potencial de ter um impacto significativo na comunidade de aprendizagem imersiva. Ela é projetada para servir como um artefato inovador que aprimora as capacidades analíticas de pesquisadores, educadores e estudantes na área.This project aims to develop a Web-based 3D visualization tool that provides a global understanding of the field of Immersive Learning. Thematic networks are a well-established approach for addressing such challenges. Therefore, a systematic literature review was conducted to extract clustering methods and criteria in thematic networks. The methodology employed in this study is Design Science research, which involved iterative development and evaluation of the visualization tool. Expert interviews were conducted to identify requirements, and rigorous methods, including recording, analyzing, and transcribing interviews, were applied to ascertain the research's relevance. The tool utilizes a node-link visualization approach to represent immersive learning strategies, practices, and associated papers. Additionally, it offers a range of filtering functionali- ties, allowing users to filter by strategies, practices, authors, institutions, and more. Furthermore, the tool incorporates various clustering functionalities, such as community detection using the Louvain Algorithm, with variable clustering criteria such as theme and paper association, paper citation, co-citation, and others. Users can also control the network's structure by modifying clus- ter size, number, and community colors. The tool features thematic networks exploratory methods for navigating the environment. By combining thematic networks with clustering and filtering capabilities, this tool aims to provide a global understanding of the scientific field. Its unique integration of Web and 3D technologies, along with exploratory methods, distinguishes it from existing visualization tools. The tool's powerful clustering algorithms, offering diverse criteria for understanding concept relationships, have the potential to make a significant impact in the immersive learning community. It is designed to serve as an innovative artifact that enhances the analytical capabilities of researchers, educators, and students in the field

    20th SC@RUG 2023 proceedings 2022-2023

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    20th SC@RUG 2023 proceedings 2022-2023

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    Developmental Bootstrapping of AIs

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    Although some current AIs surpass human abilities in closed artificial worlds such as board games, their abilities in the real world are limited. They make strange mistakes and do not notice them. They cannot be instructed easily, fail to use common sense, and lack curiosity. They do not make good collaborators. Mainstream approaches for creating AIs are the traditional manually-constructed symbolic AI approach and generative and deep learning AI approaches including large language models (LLMs). These systems are not well suited for creating robust and trustworthy AIs. Although it is outside of the mainstream, the developmental bootstrapping approach has more potential. In developmental bootstrapping, AIs develop competences like human children do. They start with innate competences. They interact with the environment and learn from their interactions. They incrementally extend their innate competences with self-developed competences. They interact and learn from people and establish perceptual, cognitive, and common grounding. They acquire the competences they need through bootstrapping. However, developmental robotics has not yet produced AIs with robust adult-level competences. Projects have typically stopped at the Toddler Barrier corresponding to human infant development at about two years of age, before their speech is fluent. They also do not bridge the Reading Barrier, to skillfully and skeptically draw on the socially developed information resources that power current LLMs. The next competences in human cognitive development involve intrinsic motivation, imitation learning, imagination, coordination, and communication. This position paper lays out the logic, prospects, gaps, and challenges for extending the practice of developmental bootstrapping to acquire further competences and create robust, resilient, and human-compatible AIs.Comment: 102 pages, 29 figure

    Resilient and Scalable Forwarding for Software-Defined Networks with P4-Programmable Switches

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    Traditional networking devices support only fixed features and limited configurability. Network softwarization leverages programmable software and hardware platforms to remove those limitations. In this context the concept of programmable data planes allows directly to program the packet processing pipeline of networking devices and create custom control plane algorithms. This flexibility enables the design of novel networking mechanisms where the status quo struggles to meet high demands of next-generation networks like 5G, Internet of Things, cloud computing, and industry 4.0. P4 is the most popular technology to implement programmable data planes. However, programmable data planes, and in particular, the P4 technology, emerged only recently. Thus, P4 support for some well-established networking concepts is still lacking and several issues remain unsolved due to the different characteristics of programmable data planes in comparison to traditional networking. The research of this thesis focuses on two open issues of programmable data planes. First, it develops resilient and efficient forwarding mechanisms for the P4 data plane as there are no satisfying state of the art best practices yet. Second, it enables BIER in high-performance P4 data planes. BIER is a novel, scalable, and efficient transport mechanism for IP multicast traffic which has only very limited support of high-performance forwarding platforms yet. The main results of this thesis are published as 8 peer-reviewed and one post-publication peer-reviewed publication. The results cover the development of suitable resilience mechanisms for P4 data planes, the development and implementation of resilient BIER forwarding in P4, and the extensive evaluations of all developed and implemented mechanisms. Furthermore, the results contain a comprehensive P4 literature study. Two more peer-reviewed papers contain additional content that is not directly related to the main results. They implement congestion avoidance mechanisms in P4 and develop a scheduling concept to find cost-optimized load schedules based on day-ahead forecasts

    A Comprehensive Survey on the Cooperation of Fog Computing Paradigm-Based IoT Applications: Layered Architecture, Real-Time Security Issues, and Solutions

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    The Internet of Things (IoT) can enable seamless communication between millions of billions of objects. As IoT applications continue to grow, they face several challenges, including high latency, limited processing and storage capacity, and network failures. To address these stated challenges, the fog computing paradigm has been introduced, purpose is to integrate the cloud computing paradigm with IoT to bring the cloud resources closer to the IoT devices. Thus, it extends the computing, storage, and networking facilities toward the edge of the network. However, data processing and storage occur at the IoT devices themselves in the fog-based IoT network, eliminating the need to transmit the data to the cloud. Further, it also provides a faster response as compared to the cloud. Unfortunately, the characteristics of fog-based IoT networks arise traditional real-time security challenges, which may increase severe concern to the end-users. However, this paper aims to focus on fog-based IoT communication, targeting real-time security challenges. In this paper, we examine the layered architecture of fog-based IoT networks along working of IoT applications operating within the context of the fog computing paradigm. Moreover, we highlight real-time security challenges and explore several existing solutions proposed to tackle these challenges. In the end, we investigate the research challenges that need to be addressed and explore potential future research directions that should be followed by the research community.©2023 The Authors. Published by IEEE. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/fi=vertaisarvioitu|en=peerReviewed

    Energy-Sustainable IoT Connectivity: Vision, Technological Enablers, Challenges, and Future Directions

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    Technology solutions must effectively balance economic growth, social equity, and environmental integrity to achieve a sustainable society. Notably, although the Internet of Things (IoT) paradigm constitutes a key sustainability enabler, critical issues such as the increasing maintenance operations, energy consumption, and manufacturing/disposal of IoT devices have long-term negative economic, societal, and environmental impacts and must be efficiently addressed. This calls for self-sustainable IoT ecosystems requiring minimal external resources and intervention, effectively utilizing renewable energy sources, and recycling materials whenever possible, thus encompassing energy sustainability. In this work, we focus on energy-sustainable IoT during the operation phase, although our discussions sometimes extend to other sustainability aspects and IoT lifecycle phases. Specifically, we provide a fresh look at energy-sustainable IoT and identify energy provision, transfer, and energy efficiency as the three main energy-related processes whose harmonious coexistence pushes toward realizing self-sustainable IoT systems. Their main related technologies, recent advances, challenges, and research directions are also discussed. Moreover, we overview relevant performance metrics to assess the energy-sustainability potential of a certain technique, technology, device, or network and list some target values for the next generation of wireless systems. Overall, this paper offers insights that are valuable for advancing sustainability goals for present and future generations.Comment: 25 figures, 12 tables, submitted to IEEE Open Journal of the Communications Societ

    LIPIcs, Volume 261, ICALP 2023, Complete Volume

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    LIPIcs, Volume 261, ICALP 2023, Complete Volum
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