1,721,089 research outputs found

    Distributed artificial intelligence for edge computing

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    In an increasingly wide range of work and personal life settings, sensors and micro-devices embedded into objects generate continuous data streams with high volume, velocity and heterogeneity. Such data can be analyzed to detect and infer knowledge about phenomenons and events of interest. By learning from data, Artificial Intelligence (AI) methods enable automating an ever larger amount of activities and decision-making tasks with comparable or better proficiency than human experts. Big Data applications based on pervasive Internet of Things (IoT) deployments are now a well-established reality: they feed large Machine Learning (ML) models, which are trained exploiting the huge computational resources of cloud computing infrastructures to offer increasingly accurate prediction capabilities on fresh data. However, the increasing miniaturization of IoT devices equipped with highly accurate sensors enables novel Cyber-Physical Systems (CPSs) with tight feedback loops coupling computation, communication and control tasks. CPS applications are expanding in sensitive fields like high-precision manufacturing, telemedicine, and self-driving vehicles. Those scenarios require real-time response, high computational and bandwidth efficiency, cost-effectiveness to support business scalability and strict data privacy constraints. For this reason, classical cloud-based approaches are progressively integrated with the Edge Computing (EC) architectural model, which distributes significant processing and storage resources at the edge of the local network, in closer proximity to field devices and sensors. This paradigm allows AI-based IoT applications to scale even more, as models are trained with massive amounts of data generated by large deployments of micro- and nano-devices, and ML inference achieves ever greater accuracy. In this context, the Edge Intelligence paradigm --which promotes the integration of EC and AI-- is increasingly adopted to execute inference on data at the border of local networks, employing models trained in the cloud. The next logical step in Cloud-Edge AI cooperation is to enable training tasks on edge nodes as well. However, as of now flexible approaches to combine Edge Intelligence with cloud infrastructures, allowing dynamic migration of training and inference tasks, are not available yet. This thesis proposes a Cloud-Edge AI microservice architecture, based on Osmotic Computing principles. A full pipeline consisting in data collection from local devices, preprocessing, AI model training and inferencing is supported either on the edge, on the cloud or both, exploiting computational resources opportunistically based on device status, available bandwidth, and application requirements on latency, prediction accuracy, and privacy. To demonstrate the feasibility of the proposed framework, a prototype has been realized with commodity hardware leveraging open-source software technologies. It has been used in a small-scale intelligent manufacturing case study, carrying out experiments on elapsed time and network activity in (i) data gathering, (ii) AI model training and validation, and (iii) prediction tasks. Obtained results validate the key benefits of the approach. In addition to architectural aspects, open issues still limiting the full applicability of EC include the heterogeneity of devices, services, and information that arise in pervasive contexts, the integrity of the gathered data, and the trustworthiness and dependability of autonomous decisions. The Semantic Web of Things (SWoT), coalescing the Semantic Web and IoT paradigms, has been proposed to overcome these problems. In SWoT environments, the dynamic exchange of knowledge fragments expressed in logic-based formalisms in volatile wireless networks of independent agents enables decentralized collaborative service discovery, autonomous decision and user decision support. A relevant problem in such scenarios consists in evaluating agreements and disagreements about knowledge produced by different interacting agents, in order to possibly reconcile conflicts and determine the best overall outcome to accomplish distributed coordination. In AI, Argumentation is recognized as a powerful formalism to negotiate and solve disagreements within a group of agents, which convey knowledge represented as a constellation of arguments and counterarguments. The argumentation literature provides a wealth of frameworks for agent decision-making and coordination. Nevertheless, few proposals leverage Semantic Web languages and technologies, which can provide a well-known formal model for arguments, well-studied inference algorithms for the assessment of argument relations and approaches to evaluate argument acceptability. This thesis presents a novel Bipolar Weighted Argumentation Framework, where arguments are modeled as Description Logics concept expressions in Web Ontology Language (OWL) 2, and their relations are assessed via semantic matchmaking, leveraging non-standard inference services with logic-based outcome explanation. Argument acceptability is computed via a novel propagation-based ranking semantics, which supports argument cycles and information fading. In order to make the proposal suitable for pervasive semantic agents in resource-constrained devices, optimizations in argument assessment and ranking evaluation are adopted, while a graph simplification approach via pruning is proposed and experimentally tested as a tunable trade-off between computational resource usage and accuracy of results. Validation of the approach has been carried out by means of a prototypical implementation of a player agent for the StarCraft II real-time strategy game, whose environment allows simulating the complexities of real CPS scenarios

    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

    Author Index

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    koamabayili/VECTRON-author-checklist: VECTRON author checklist

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    We have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used

    Author Under Sail The Imagination of Jack London, 1893-1902

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    In Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Intro -- Title Page -- Copyright Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- 1. Spirit Truth -- 2. From Absorption to Theatricality and Back Again -- 3. "I Will Build a New Present" -- 4. Sons as Authors -- 5. Fathers as Publishers -- 6. The Daughter as Author -- 7. Lovers as Authors -- 8. At Sea with the Family -- 9. Yellow News, Yellow Stories -- 10. The Return Home -- Notes -- Bibliography -- Index -- About Jay WilliamsIn Author Under Sail, Jay Williams offers the first complete literary biography of Jack London as a professional writer engaged in the labor of writing. It examines the authorial imagination in London's work, the use of imagination in both his fiction and nonfiction, and the ways he defined imagination in the creative process in his business dealings with his publishers, editors, and agents. In this first volume of a two-volume biography, Williams traverses the years 1893 to 1902, from London's "Story of a Typhoon" to The People of the Abyss. The Jack London who emerges in the pages of Author Under Sail is a writer whose partnership with publishers, most notably his productive alliance with George Brett of Macmillan, was one of the most formative in American literary history. London pioneered many author models during the heyday of realism and naturalism, blurring the boundaries of these popular genres by focusing on absorption and theatricality and the representation of the seen and unseen. London created an impassioned, sincere, and extremely personal realism unlike that of other American writers of the time. Author Under Sail is a literary tour de force that reveals the full range of London as writer, creative citizen, and entrepreneur at the same time it sheds light on the maverick side of machine-age literature.Description based on publisher supplied metadata and other sources.Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, YYYY. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries
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