68,348 research outputs found

    Technology assessment of advanced automation for space missions

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    Six general classes of technology requirements derived during the mission definition phase of the study were identified as having maximum importance and urgency, including autonomous world model based information systems, learning and hypothesis formation, natural language and other man-machine communication, space manufacturing, teleoperators and robot systems, and computer science and technology

    Cursive script recognition using wildcards and multiple experts

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    Variability in handwriting styles suggests that many letter recognition engines cannot correctly identify some hand-written letters of poor quality at reasonable computational cost. Methods that are capable of searching the resulting sparse graph of letter candidates are therefore required. The method presented here employs ‘wildcards’ to represent missing letter candidates. Multiple experts are used to represent different aspects of handwriting. Each expert evaluates closeness of match and indicates its confidence. Explanation experts determine the degree to which the word alternative under consideration explains extraneous letter candidates. Schemata for normalisation and combination of scores are investigated and their performance compared. Hill climbing yields near-optimal combination weights that outperform comparable methods on identical dynamic handwriting data

    Designing Algorithms for Optimization of Parameters of Functioning of Intelligent System for Radionuclide Myocardial Diagnostics

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    The influence of the number of complex components of Fast Fourier transformation in analyzing the polar maps of radionuclide examination of myocardium at rest and stress on the functional efficiency of the system of diagnostics of pathologies of myocardium was explored, and there were defined their optimum values in the information sense, which allows increasing the efficiency of the algorithms of forming the diagnostic decision rules by reducing the capacity of the dictionary of features of recognition.The information-extreme sequential cluster algorithms of the selection of the dictionary of features, which contains both quantitative and category features were developed and the results of their work were compared. The modificatios of the algorithms of the selection of the dictionary were suggested, which allows increasing both the search speed of the optimal in the information sense dictionary and reducing its capacity by 40 %. We managed to get the faultless by the training matrix decision rules, the accuracy of which is in the exam mode asymptotically approaches the limit.It was experimentally confirmed that the implementation of the proposed algorithm of the diagnosing system training has allowed to reduce the minimum representative volume of the training matrix from 300 to 81 vectors-implementations of the classes of recognition of the functional myocardium state

    Temporally-aware algorithms for the classification of anuran sounds

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    Several authors have shown that the sounds of anurans can be used as an indicator of climate change. Hence, the recording, storage and further processing of a huge number of anuran sounds, distributed over time and space, are required in order to obtain this indicator. Furthermore, it is desirable to have algorithms and tools for the automatic classification of the different classes of sounds. In this paper, six classification methods are proposed, all based on the data-mining domain, which strive to take advantage of the temporal character of the sounds. The definition and comparison of these classification methods is undertaken using several approaches. The main conclusions of this paper are that: (i) the sliding window method attained the best results in the experiments presented, and even outperformed the hidden Markov models usually employed in similar applications; (ii) noteworthy overall classification performance has been obtained, which is an especially striking result considering that the sounds analysed were affected by a highly noisy background; (iii) the instance selection for the determination of the sounds in the training dataset offers better results than cross-validation techniques; and (iv) the temporally-aware classifiers have revealed that they can obtain better performance than their nontemporally-aware counterparts.ConsejerĂ­a de InnovaciĂłn, Ciencia y Empresa (Junta de AndalucĂ­a, Spain): excellence eSAPIENS number TIC 570

    An overview of decision table literature 1982-1995.

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    This report gives an overview of the literature on decision tables over the past 15 years. As much as possible, for each reference, an author supplied abstract, a number of keywords and a classification are provided. In some cases own comments are added. The purpose of these comments is to show where, how and why decision tables are used. The literature is classified according to application area, theoretical versus practical character, year of publication, country or origin (not necessarily country of publication) and the language of the document. After a description of the scope of the interview, classification results and the classification by topic are presented. The main body of the paper is the ordered list of publications with abstract, classification and comments.
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