968 resultados para Onomasiological Terminological Dictionary


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An on-line algorithm is developed for the location of single cross point faults in a PLA (FPLA). The main feature of the valgorithm is the determination of a fault set corresponding to the response obtained for a failed test. For the apparently small number of faults in this set, all other tests are generated and a fault table is formed. Subsequently, an adaptive procedure is used to diagnose the fault. Functional equivalence test is carried out to determine the actual fault class if the adaptive testing results in a set of faults with identical tests. The large amount of computation time and storage required in the determination, a priori, of all the fault equivalence classes or in the construction of a fault dictionary are not needed here. A brief study of functional equivalence among the cross point faults is also made.

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DEVELOPING A TEXTILE ONTOLOGY FOR THE SEMANTIC WEB AND CONNECTING IT TO MUSEUM CATALOGING DATA The goal of the Semantic Web is to share concept-based information in a versatile way on the Internet. This is achievable using formal data structures called ontologies. The goal of this re-search is to increase the usability of museum cataloging data in information retrieval. The work is interdisciplinary, involving craft science, terminology science, computer science, and museology. In the first part of the dissertation an ontology of concepts of textiles, garments, and accessories is developed for museum cataloging work. The ontology work was done with the help of thesauri, vocabularies, research reports, and standards. The basis of the ontology development was the Museoalan asiasanasto MASA, a thesaurus for museum cataloging work which has been enriched by other vocabularies. Concepts and terms concerning the research object, as well as the material names of textiles, costumes, and accessories, were focused on. The research method was terminological concept analysis complemented by an ontological view of the Semantic Web. The concept structure was based on the hierarchical generic relation. Attention was also paid to other relations between terms and concepts, and between concepts themselves. Altogether 977 concept classes were created. Issues including how to choose and name concepts for the ontology hierarchy and how deep and broad the hierarchy could be are discussed from the viewpoint of the ontology developer and museum cataloger. The second part of the dissertation analyzes why some of the cataloged terms did not match with the developed textile ontology. This problem is significant because it prevents automatic ontological content integration of the cataloged data on the Semantic Web. The research datasets, i.e. the cataloged museum data on textile collections, came from three museums: Espoo City Museum, Lahti City Museum and The National Museum of Finland. The data included 1803 textile, costume, and accessory objects. Unmatched object and textile material names were analyzed. In the case of the object names six categories (475 cases), and of the material names eight categories (423 cases), were found where automatic annotation was not possible. The most common explanation was that the cataloged field was filled with a long sentence comprised of many terms. Sometimes in the compound term, the object name and material, or the name and the way of usage, were combined. As well, numeric values in the material name cataloging field prevented annotation and so did the absence of a corresponding concept in the ontology. Ready-made drop-down lists of materials used in one cataloging system facilitated the annotation. In the case of naming objects and materials, one should use terms in basic form without attributes. The developed textile ontology has been applied in two cultural portals, MuseumFinland and Culturesampo, where one can search for and browse information based on cataloged data using integrated ontologies in an interoperable way. The textile ontology is also part of the national FinnONTO ontology infrastructure. Keywords: annotation, concept, concept analysis, cataloging, museum collection, ontology, Semantic Web, textile collection, textile material

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Contains correspondence as editor of the Detroit Jewish chronicle and of The Jewish news. Of special interest is the correspondence with members of the U.S. Congress relating to aid to Israel, material relating to the boycott of Viceroy cigarettes, the question of the Jewish descent of Franklin Delano Roosevelt, and the dictionary definition of "Jew."

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In this paper we investigate the effectiveness of class specific sparse codes in the context of discriminative action classification. The bag-of-words representation is widely used in activity recognition to encode features, and although it yields state-of-the art performance with several feature descriptors it still suffers from large quantization errors and reduces the overall performance. Recently proposed sparse representation methods have been shown to effectively represent features as a linear combination of an over complete dictionary by minimizing the reconstruction error. In contrast to most of the sparse representation methods which focus on Sparse-Reconstruction based Classification (SRC), this paper focuses on a discriminative classification using a SVM by constructing class-specific sparse codes for motion and appearance separately. Experimental results demonstrates that separate motion and appearance specific sparse coefficients provide the most effective and discriminative representation for each class compared to a single class-specific sparse coefficients.

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In terms of critical discourse, Liberty contributes to the ongoing aesthetic debate on ‘the sublime.’ Philosopher Immanuel Kant (1724–1804) defined the sublime as a failure of rationality in response to sensory overload: a state where the imagination is suspended, without definitive reference points—a state beyond unequivocal ‘knowing.’ I believe the events of September 11, 2001 eluded our understanding in much the same way, leaving us in a moment of suspension between awe and horror. It was an event that couldn’t be understood in terms of scope or scale. It was a moment of overload, which is so difficult to capture in art. With my work I attempt to rekindle that moment of suspension. Like the events of 9/11, Liberty defies definition. Its form is constantly changing; it is always presenting us with new layers of meaning. Nobody quite had a handle on the events that followed 9/11, because the implications were constantly shifting. In the same way, Liberty cannot be contained or defined at any moment in time. Like the events of 9/11, the full story cannot be told in a snapshot. One of the dictionary definitions for the word ‘sublime’ is the conversion of ‘a solid substance directly into a gas, without there being an intermediate liquid phase’. With this in mind, I would like to present Liberty as a work that is literally ‘sublime.’ But what’s really interesting to me about Liberty is that it presents the sublime on all levels: in its medium, in its subject matter (that moment of suspension), and in its formal (formless) presentation. On every level Liberty is sublime—subverting all tangible reference points and eluding capture entirely. Liberty is based on the Statue of Liberty in New York. However, unlike that statue which has stood in New York since 1886 and can be reasonably expected to stand for millennia, this work takes on diminishing proportions, carved as it is in carbon dioxide, a mysterious, previously unexplored medium—one which smokes, snows and dramatically vanishes into a harmless gas. Like the material this work is carved from, the civil liberties of the free world are diminishing fast, since 9/11 and before. This was my thought when I first conceived this work. Now it’s become evident that Liberty expresses a lot more than just this: it demonstrates the erosion of civil liberties, yes. However, it also presents the intangible, indefinable moments in the days and months that followed 9/11. The sculptural work will last for only a short time, and thereafter will exist only in documentation. During this time, the form is continually changing and self-refining, until it disappears entirely, to be inhaled, metabolised and literally taken to heart by viewers.

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This PhD research has proposed new machine learning techniques to improve human action recognition based on local features. Several novel video representation and classification techniques have been proposed to increase the performance with lower computational complexity. The major contributions are the construction of new feature representation techniques, based on advanced machine learning techniques such as multiple instance dictionary learning, Latent Dirichlet Allocation (LDA) and Sparse coding. A Binary-tree based classification technique was also proposed to deal with large amounts of action categories. These techniques are not only improving the classification accuracy with constrained computational resources but are also robust to challenging environmental conditions. These developed techniques can be easily extended to a wide range of video applications to provide near real-time performance.

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