894,521 research outputs found

    Distinctive features

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    Creating fair lineups for suspects with distinctive features

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    In their descriptions, eyewitnesses often refer to a culprit's distinctive facial features. However, in a police lineup, selecting the only member with the described distinctive feature is unfair to the suspect and provides the police with little further information. For fair and informative lineups, the distinctive feature should be either replicated across foils or concealed on the target. In the present experiments, replication produced more correct identifications in target-present lineups—without increasing the incorrect identification of foils in target-absent lineups—than did concealment. This pattern, and only this pattern, is predicted by the hybrid-similarity model of recognition

    Distinctive features of economic texts translation

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    В данной статье рассматриваются вопросы, связанные с особенностями перевода экономических текстов. Пристальное внимание уделяется специфическим лексико-грамматическим особенностям, присущим терминологической лексике экономических текстов.This article deals with issues devoted to the peculiarities of economic texts translation. A special attention is paid to the analysis of distinctive lexico-grammatical features which are viewed as core characteristics in translating economic texts

    Distinctive Features of Mobile Messages Processing

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    World’s mobile market pushes past 2 billion lines in 2005. Success in these competitive markets requires operational excellence with product and service innovation to improve the mobile performance. Mobile users very often prefer to send a mobile instant message or text messages rather than talking on a mobile. Well developed “written speech analysis” does not work not only with “verbal speech” but also with “mobile text messages”. The main purpose of our paper is, firstly, to highlight the problems of mobile text messages processing and, secondly, to show the possible ways of solving these problems

    Associative learning in baboons and humans: Species differences in learned attention to visual features

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    We examined attention shifting in baboons and humans during the learning of visual categories. Within a conditional matching-to-sample task, participants of the two species sequentially learned two two-feature categories which shared a common feature. Results showed that humans encoded both features of the initially learned category, but predominantly only the distinctive feature of the subsequently learned category. Although baboons initially encoded both features of the first category, they ultimately retained only the distinctive features of each category. Empirical data from the two species were analyzed with the 1996 ADIT connectionist model of Kruschke. ADIT fits the baboon data when the attentional shift rate is zero, and the human data when the attentional shift rate is not zero. These empirical and modeling results suggest species differences in learned attention to visual features

    The U.S. and Irish Credit Crises: Their Distinctive Differences and Common Features

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    Abstract: Although the US credit crisis precipitated it, the Irish credit crisis is an identifiably separate one, which might have occurred in the absence of the U.S. crash. The distinctive differences between them are notable. Almost all the apparent causal factors of the U.S. crisis are missing in the Irish case; and the same applies vice-versa. At a deeper level, we identify four common features of the two credit crises: capital bonanzas, irrational exuberance, regulatory imprudence, and moral hazard. The particular manifestations of these four “deep” common features are quite different in the two cases.
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