Titlebook: Hormonal Carcinogenesis V; Jonathan J. Li,Sara A. Li,Thierry Maudelonde Book 2008 The Editor(s) (if applicable) and The Author(s), under e

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Vanessa Duong,Patrick Augereau,Eric Badia,Stéphan Jalaguier,Vincent Cavailles us to use ever more complex algorithms in server-based large vocabulary ASR systems (e.g. in telephony applications), the capability of embedded platforms will always lag behind. Nevertheless as the popularity of ASR application grows, we can expect an increasing demand for functionality on embedde

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Rapha?l Métivier,Guillaume Huet,Rozenn Gallais,Laurence Finot,Fabien Petit,Christophe Tiffoche,Yohan speech recognition performance. One of these issues is the performance degradation of ASR over mobile networks that results from distortions produced by speech coding algorithms employed in mobile communication systems, transmission errors occurring over mobile telephone channels, and ambient backg

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Ross L. Prenticeces in signal processing, algorithms,architectures, and hardware. These advances include: the adoption of astatistical pattern recognition paradigm; the use of the hidden Markovmodeling framework to characterize both the spectral and the temporalvariations in the speech signal; the use of a large se

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What Can We Learn about Breast Cancer from Stem Cells? essential functions such as absorption of nutrients, protection from infection, and replacement of cells damaged by insults including toxins, radiation and trauma. This need to constantly replenish the mature cells of a tissue presents a particularly vexing problem for complex multicellular animals

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Ovarian Cancer: Linking Genomics to New Target Discovery and Molecular Markers — The Way Ahead(1,2). It arises from ovarian surface epithelial (OSE) cells, and is currently classified by surgical and histological appearance (see Table 1), although the predictive value of this morphologic classification is limited (3).

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