25 research outputs found

    EnquĂȘte auprĂšs des personnels de l’UniversitĂ© de Strasbourg

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    Cette enquĂȘte concerne tous les personnels. Elle est menĂ©e par les Ă©lus Alternative aux trois conseils centraux CA, CR et CFVU, et vise Ă  connaĂźtre votre opinion dans le contexte des 10 ans de l’UniversitĂ© de Strasbourg, Ă  un moment oĂč s’amplifient des discussions, au niveau local comme national, sur les rĂ©formes concernant l’exercice des missions universitaires, le statut des personnels, les modes de recrutement, le financement de la recherche et l’accueil des Ă©tudiants

    Novel optimal recursive filter for state and fault estimation of linear stochastic systems with unknown disturbances

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    This paper studies recursive optimal filtering as well as robust fault and state estimation for linear stochastic systems with unknown disturbances. It proposes a new recursive optimal filter structure with transformation of the original system. This transformation is based on the singular value decomposition of the direct feedthrough matrix distribution of the fault which is assumed to be of arbitrary rank. The resulting filter is optimal in the sense of the unbiased minimum-variance criteria. Two numerical examples are given in order to illustrate the proposed method, in particular to solve the estimation of the simultaneous actuator and sensor fault problem and to make a comparison with the existing literature results

    Exploring West African folk narrative texts using machine learning

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    This paper examines how machine learning (ML) and natural language processing (NLP) can be used to identify, analyze, and generate West African folk tales. Two corpora of West African and Western European folk tales are compiled and used in three experiments on cross-cultural folk tale analysis. In the text generation experiment, two types of deep learning text generators are built and trained on the West African corpus. We show that although the texts range between semantic and syntactic coherence, each of them contains West African features. The second experiment further examines the distinction between the West African and Western European folk tales by comparing the performance of an LSTM (acc. 0.74) with a BoW classifier (acc. 0.93), indicating that the two corpora can be clearly distinguished in terms of vocabulary. An interactive t-SNE visualization of a hybrid classifier (acc. 0.85) highlights the culture-specific words for both. The third experiment describes an ML analysis of narrative structures. Classifiers trained on parts of folk tales according to the three-act structure are quite capable of distinguishing these parts (acc. 0.78). Common n-grams extracted from these parts not only underline cross-cultural distinctions in narrative structures, but also show the overlap between verbal and written West African narratives
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