149 research outputs found

    Can you help me America?

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    There is no place on earth in our time that can offer more hope and support than the United States of America. Despite the struggle, America is my home and will continue to grow and help shape this great country positively

    Le corps igné de Nefza (Tunisie septentrionale) : caractéristiques géophysiques et discussion du mécanisme de sa mise en place

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    La présence de roches ignées a été mise en évidence dans le Nord-Ouest de la Tunisie dans les régions de Nefza et des Mogod. La répartition géographique de ces indices montre qu'ils sont alignés suivant la direction Est-Ouest (N80°). L'interprétation des données aéromagnétiques et gravimétriques, conjuguée avec une modélisation géophysique du type 2D 1/2 ont permis de caractériser le corps igné de la région de Nefza. Les résultats montrent qu'il s'agit d'une roche intra-sédimentaire de densité supérieure à 2.8, peu profonde (700 à 800 m), allongée dans la direction N80° et de susceptibilité magnétique de l'ordre de 500 E-6 (cgs). Les corps d'origine magmatique de la région, en particulier celui de Nefza, sont associés à un gradient géothermique anormalement élevé. Compte tenu de la géométrie de ce corps et du contexte géologique, il semble que sa mise en place est liée à une zone de faiblesse de la lithosphère qui correspond à une fracturation profonde de direction proche de l'Est-Ouest. (Résumé d'auteur

    A review of drought monitoring using remote sensing and data mining methods

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    Comportement à l'impact des composites fibres de verre/Epoxy modifié copolymère à bloc.

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    Epoxy resins are widely used in the design of fibre composite materials. This increasing use finds its reason in the fact that these materials have excellent mechanical and thermal properties. Playing on its chemical composition and curing speed, it’s possible to vary the mechanical properties from the extreme flexibility to high rigidity. However, the inherent toughness of a highly crosslinked epoxy is relatively low. It therefore seems desirable for high impact resistance applications, to improve the toughness, without affecting the other usual properties of this polymer. Recent studies have shown a significant improvement in impact resistance of epoxy in the presence of block copolymers. Our work aims to investigate the effect of triblock copolymer-based acrylate (Nanostrength) on the impact resistance of glass / epoxy composite. An experimental device, called "drop tower" is used to perform impact tests on composites with or without Nanostrength. Dynamic mechanical analyses (DMA) were conducted, first to characterize the effect of addition of Nanostrength on the thermomechanical properties, but also to establish a correlation between thermomechanical properties and impact resistance. Different observation tools, such as optical observation, scanning electron microscopy (SEM) and atomic force microscopy (AFM) were used to visualize the material damages. Adding Nanostrength in epoxy leads to the improvement of impact resistance of the composite material. A slight decrease in the storage modulus and glass transition temperature have been observed. Microscopic observations shown that the different failure modes of the composite are mainly delamination, fibres breakage and matrix cracking. It was also observed that the presence of Nanostrength role as cracks deflect

    Expect: EXplainable Prediction Model for Energy ConsumpTion

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    With the steady growth of energy demands and resource depletion in today’s world, energy prediction models have gained more and more attention recently. Reducing energy consumption and carbon footprint are critical factors for achieving efficiency in sustainable cities. Unfortunately, traditional energy prediction models focus only on prediction performance. However, explainable models are essential to building trust and engaging users to accept AI-based systems. In this paper, we propose an explainable deep learning model, called EXPECT, to forecast energy consumption from time series effectively. Our results demonstrate our proposal’s robustness and accuracy when compared to the baseline methods
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