442 research outputs found

    Ontology-based specific and exhaustive user profiles for constraint information fusion for multi-agents

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    Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment

    A Case Study for eCampus Spatial: Business Data Exploration

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    Location based querying is the core interaction paradigm between mobile citizens and the Internet of Things, so providing users with intelligent web-services that interact efficiently with web and wireless devices to recommend personalised services is a key goal. With today\u27s popular Web Map Services, users can ask for general information at a specific location, but not detailed information such as related functionality or environments. This shortcoming comes from a lack of connection between non-spatial “business” data and spatial “map” data. This chapter presents a novel approach for location-based querying in web and wireless environments, in which non-spatial business data is dynamically connected to spatial base-map data to provide users with spatially-enabled attribute information at particular locations. The proposed approach is illustrated in a case study at the National University of Ireland in Maynooth (NUIM), where detailed 3D campus building models were constructed. Non-spatial university specific business data such as the functionalities and timetables of class rooms/buildings, campus news, noise levels, and navigation are then explored over the web and presented as both mobile and desktop web-services

    A Study on the Status Quo and Reconstruction Paths for Ecological Imbalance in College English Classroom under the Background of Informationization --Taking Yunnan Minzu University as an Example

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    Based on the theory of educational ecology this paper starts to analyze the status quo of the imbalance in college English classroom of Yunnan Minzu University YMU under the background of informationization attempts to put forward three principles abided in the process of reconstruction then mainly focuses on the reconstruction paths for the college English classroom ecology so as to provide some new ideas for the reform in college English and eventually contributes to the sustainable development of the college English classroom ecolog

    In Homage of Change

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    A Study on the Influencing Factors of Teaching Interaction on Deep Learning from the Perspective of Social Cognitive Theory

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    Based on Social Cognitive Theory SCT a research model is constructed with teaching interaction as the independent variable self-efficacy as the mediating variable and Deep learning as the dependent variable The research uses regression analysis and Bootstrap test to explore the impact of teaching interaction on college students Deep learning and the mediating role of self-efficacy The research results show that teaching interaction positively and significantly affects college students Deep learning and self- efficacy of which material-chemical interaction has the most significant effect on college students Deep learning 0 431 self-efficacy positively affects college students Deep learning 0 255 and play a partial mediating role in teaching interaction and Deep learning Finally the research proposes to build a multi-modal interaction mechanism to promote the realization of Deep learning to create an embodied collaborative learning context to improve the quality of teaching interaction Learn and referenc

    HDHumans: A Hybrid Approach for High-fidelity Digital Humans

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    Photo-real digital human avatars are of enormous importance in graphics, asthey enable immersive communication over the globe, improve gaming andentertainment experiences, and can be particularly beneficial for AR and VRsettings. However, current avatar generation approaches either fall short inhigh-fidelity novel view synthesis, generalization to novel motions,reproduction of loose clothing, or they cannot render characters at the highresolution offered by modern displays. To this end, we propose HDHumans, whichis the first method for HD human character synthesis that jointly produces anaccurate and temporally coherent 3D deforming surface and highlyphoto-realistic images of arbitrary novel views and of motions not seen attraining time. At the technical core, our method tightly integrates a classicaldeforming character template with neural radiance fields (NeRF). Our method iscarefully designed to achieve a synergy between classical surface deformationand NeRF. First, the template guides the NeRF, which allows synthesizing novelviews of a highly dynamic and articulated character and even enables thesynthesis of novel motions. Second, we also leverage the dense pointcloudsresulting from NeRF to further improve the deforming surface via 3D-to-3Dsupervision. We outperform the state of the art quantitatively andqualitatively in terms of synthesis quality and resolution, as well as thequality of 3D surface reconstruction.<br

    Integrative Levels of Knowing

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    Diese Dissertation beschĂ€ftigt sich mit einer systematischen Organisation der epistemologischen Dimension des menschlichen Wissens in Bezug auf Perspektiven und Methoden. Insbesondere wird untersucht inwieweit das bekannte Organisationsprinzip der integrativen Ebenen, das eine Hierarchie zunehmender KomplexitĂ€t und Integration beschreibt, geeignet ist fĂŒr eine grundlegende Klassifikation von Perspektiven bzw. epistemischen Bezugsrahmen. Die zentrale These dieser Dissertation geht davon aus, dass eine angemessene Analyse solcher epistemischen Kontexte in der Lage sein sollte, unterschiedliche oder gar konfligierende Bezugsrahmen anhand von kontextĂŒbergreifenden Standards und Kriterien vergleichen und bewerten zu können. Diese Aufgabe erfordert theoretische und methodologische Grundlagen, welche die BeschrĂ€nkungen eines radikalen Kontextualismus vermeiden, insbesondere die ihm innewohnende Gefahr einer Fragmentierung des Wissens aufgrund der angeblichen InkommensurabilitĂ€t epistemischer Kontexte. Basierend auf JĂŒrgen Habermas‘ Theorie des kommunikativen Handelns und seiner Methodologie des hermeneutischen Rekonstruktionismus, wird argumentiert, dass epistemischer Pluralismus nicht zwangslĂ€ufig zu epistemischem Relativismus fĂŒhren muss und dass eine systematische Organisation der Perspektivenvielfalt von bereits existierenden Modellen zur kognitiven Entwicklung profitieren kann, wie sie etwa in der Psychologie oder den Sozial- und Kulturwissenschaften rekonstruiert werden. Der vorgestellte Ansatz versteht sich als ein Beitrag zur multi-perspektivischen Wissensorganisation, der sowohl neue analytische Werkzeuge fĂŒr kulturvergleichende Betrachtungen von Wissensorganisationssystemen bereitstellt als auch neue Organisationsprinzipien vorstellt fĂŒr eine Kontexterschließung, die dazu beitragen kann die AusdrucksstĂ€rke bereits vorhandener Dokumentationssprachen zu erhöhen. Zudem enthĂ€lt der Anhang eine umfangreiche Zusammenstellung von Modellen integrativer Wissensebenen.This dissertation is concerned with a systematic organization of the epistemological dimension of human knowledge in terms of viewpoints and methods. In particular, it will be explored to what extent the well-known organizing principle of integrative levels that presents a developmental hierarchy of complexity and integration can be applied for a basic classification of viewpoints or epistemic outlooks. The central thesis pursued in this investigation is that an adequate analysis of such epistemic contexts requires tools that allow to compare and evaluate divergent or even conflicting frames of reference according to context-transcending standards and criteria. This task demands a theoretical and methodological foundation that avoids the limitation of radical contextualism and its inherent threat of a fragmentation of knowledge due to the alleged incommensurability of the underlying frames of reference. Based on JĂŒrgen Habermas’s Theory of Communicative Action and his methodology of hermeneutic reconstructionism, it will be argued that epistemic pluralism does not necessarily imply epistemic relativism and that a systematic organization of the multiplicity of perspectives can benefit from already existing models of cognitive development as reconstructed in research fields like psychology, social sciences, and humanities. The proposed cognitive-developmental approach to knowledge organization aims to contribute to a multi-perspective knowledge organization by offering both analytical tools for cross-cultural comparisons of knowledge organization systems (e.g., Seven Epitomes and Dewey Decimal Classification) and organizing principles for context representation that help to improve the expressiveness of existing documentary languages (e.g., Integrative Levels Classification). Additionally, the appendix includes an extensive compilation of conceptions and models of Integrative Levels of Knowing from a broad multidisciplinary field

    Unsupervised Hyperbolic Representation Learning via Message Passing Auto-Encoders

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    Most of the existing literature regarding hyperbolic embedding concentrate upon supervised learning, whereas the use of unsupervised hyperbolic embedding is less well explored. In this paper, we analyze how unsupervised tasks can benefit from learned representations in hyperbolic space. To explore how well the hierarchical structure of unlabeled data can be represented in hyperbolic spaces, we design a novel hyperbolic message passing auto-encoder whose overall auto-encoding is performed in hyperbolic space. The proposed model conducts auto-encoding the networks via fully utilizing hyperbolic geometry in message passing. Through extensive quantitative and qualitative analyses, we validate the properties and benefits of the unsupervised hyperbolic representations. Codes are available at https://github.com/junhocho/HGCAE
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