SAM: Soumissions récentes
Voici les éléments 1436-1442 de 6448
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Communication avec acte(Chinese Society for Composite Materials, 2017)Fused filament Fabrication (FFF) is one of the typical Rapid Prototyping (RP) process that can fabricate prototypes from various model materials. To predict the mechanical behaviour of FFF parts, it is necessary to understand ...
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Article dans une revue avec comité de lecture(Asian Research Publishing Network, 2019)Additive manufacturing of polymer products over the past decade has become widespread in various areas of industry. Using the FFF method, one of the most technologically simple methods of additive manufacturing, it is ...
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Article dans une revue avec comité de lecture(Frontiers, 2021)Augmented Reality (AR) enhances the comprehension of complex situations by making the handling of contextual information easier. Maintenance activities in aeronautics consist of complex tasks carried out on various ...
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A Novel Multi-Criteria Risk Matrix to Assist in the Strategy Formulation Process: The Case of SMEs Article dans une revue avec comité de lecture(World Scientific Pub Co Pte Lt, 2021)Small and medium-sized enterprises (SMEs) are the spine of the European economy and play a key role in adding value in all sectors of the economy. However, due to a lack of methodology and time, SME entrepreneurs struggle ...
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Article dans une revue avec comité de lecture(Informa UK Limited, 2012)In the context of patient-specific 3D bone reconstruction, enhancing the surface with cortical thickness (COT) opens a large field of applications for research and medicine. This functionality calls for database analysis ...
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Article dans une revue avec comité de lecture(Elsevier, 2021)A thermomechanical analysis on a 320 × 256, 30 μm pitch, middle wave infrared detector operating at 100 K is conducted. The stress induced in the HgCdTe single crystal layer needs to be minimized to avoid electro-optical ...
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Article dans une revue avec comité de lecture(Elsevier, 2021)We present an algorithm to learn the relevant latent variables of a large-scale discretized physical system and predict its time evolution using thermodynamically-consistent deep neural networks. Our method relies on sparse ...