1,720,966 research outputs found

    Towards an AI-Based Framework for Autonomous Design and Construction: Learning from Reinforcement Learning Success in RTS Games

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    The present study summarizes the state-of-the-art research in deep reinforcement learning (DRL) techniques in the architecture, engineering and construction industry and it formulates a general framework for autonomous design and construction. The framework is inspired by the noticeable success of DRL and imitation learning algorithms in real time strategy (RTS) games, which normally require efficient resource planning and long-term strategic coordination. The objective of the proposed framework is to reduce data segregation and loss of project information. The prevention of data leakage is achieved by replacing the linear process with an iterative one where the consequences of design decisions on the construction process (and vice versa) are understood in a virtual environment simultaneously. The proposed framework also exploits recent advances in simulated physics-based environments, like game engines. Designers and builders can therefore simulate on-site scenarios and exchange views on the required design and construction goals early in the project. The multi-objective optimization problem is then passed to artificial agents. These agents train on achieving the project goals under the supervision of a team of humans. The tacit knowledge transferred to the brain of the agents can later be deployed on-site through execution robots. The proposed approach is demonstrated by a proof-of-concept software application, showcasing a brick pavilion project. Design and construction constraints are first imposed by the user. Agents are then trained using a DRL algorithm

    Implementing Immersive Worlds for Metaverse-Based Participatory Design through Photogrammetry and Blockchain

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    This paper explores participatory design methods for the interconnection of digital recording techniques, like digital photogrammetry and Gaussian splatting, with emerging domains such as the metaverse and blockchain technology. The focus lies in community engagement and the economic growth of urban and rural areas through blockchain integration, utilizing low-cost digitalization methods to create Web3 environments mirroring real settlements. Through a case study of an Italian village, the potential of participatory design and community-led development strategies in revitalizing neglected areas are explored, and the use of low-cost drone-based photogrammetry and Gaussian splatting in digitization are compared, highlighting their advantages and drawbacks considering the aim of this work, i.e., the creation of an interactive metaverse space. Ultimately, the study underscores the transformative role of digital technologies in reshaping design processes and fostering community development through a workflow, stressing collaborative decision-making and blockchain-driven economy, manufacturing, and maintenance through self-ownership models and performance-based smart contracts

    Going Beyond Counting First Authors in Author Co-citation Analysis

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    The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed

    Variations on the Author

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    “Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship

    Appropriate Similarity Measures for Author Cocitation Analysis

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    We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis

    Dispelling the Myths Behind First-author Citation Counts

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    We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more sophisticated methods

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