994 resultados para Machine-readable Library Cataloguing
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Mode of access: Internet.
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Mode of access: Internet.
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Recent structural studies of proteins mediating membrane fusion reveal intriguing similarities between diverse viral and mammalian systems. Particularly striking is the close similarity between the transmembrane envelope glycoproteins from the retrovirus HTLV-1 and the filovirus Ebola. These similarities suggest similar mechanisms of membrane fusion. The model that fits most currently available data suggests fusion activation in viral systems is driven by a symmetrical conformational change triggered by an activation event such as receptor binding or a pH change. The mammalian vesicle fusion mediated by the SNARE protein complex most likely occurs by a similar mechanism but without symmetry constraints.
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This paper presents a case study that explores how operator digging style juxtaposes with mechanical capability for a class of hydraulic mining excavators. The relationships between actuator and digging forces are developed and these are used to identify the excavator's capability to apply forces in various directions. Two distinct modes of operation are examined to see how they relate to the mechanical capabilities of the linkage and to establish if one has merit over the other. It is found that one of these styles results in lower loading of the machine.
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The paper introduces an approach to solve the problem of generating a sequence of jobs that minimizes the total weighted tardiness for a set of jobs to be processed in a single machine. An Ant Colony System based algorithm is validated with benchmark problems available in the OR library. The obtained results were compared with the best available results and were found to be nearer to the optimal. The obtained computational results allowed concluding on their efficiency and effectiveness.
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Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. In this paper, we focus on the prediction of drug concentrations using Support Vector Machines (S VM) and the analysis of the influence of each feature to the prediction results. Our study shows that SVM-based approaches achieve similar prediction results compared with pharmacokinetic model. The two proposed example-based SVM methods demonstrate that the individual features help to increase the accuracy in the predictions of drug concentration with a reduced library of training data.
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Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychophysical found frequencies. Our results therefore support the notion that the critical band of spatial frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performance.
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This report was requested by the Innovation and Marketing department of the ETHBibliotek, for the purpose of assessing the social cataloguing tool LibraryThing and its potential uses in an academic library.
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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014
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Pictured here from left to right - Back Row: John Burtniak, Cataloguing. Nick Krenton, Head Cataloguing. Front Row: Sylvia Osterbind, Reference. Arthur Vespry, Chief Librarian. Mara Karnupe, Technical Services. Dianna Kertland, Circulation.
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The Central Library of Cochin University of Science and Technology (CUSAT) has been automated by proprietary software (Adlib Library) since 2000. After 11 years, in 2011, the university authorities decided to shift to an open source software (OSS), for integrated library management system (ILMS), Koha for automating the library housekeeping operations. In this context, this study attempts to share the experiences in cataloging with both type of software. The features of the cataloging modules of both the software are analysed on the badis of certain check points. It is found that the cataloging module of Koha is almost in par with that of proven proprietary software that has been in market for the past 25 years. Some suggestions made by this study may be incorporated for the further development and perfection of Koha.