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Institution

Mines ParisTech

EducationParis, France
About: Mines ParisTech is a education organization based out in Paris, France. It is known for research contribution in the topics: Finite element method & Microstructure. The organization has 6564 authors who have published 11676 publications receiving 359898 citations. The organization is also known as: École nationale supérieure des mines de Paris & École des mines de Paris.


Papers
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Journal ArticleDOI
TL;DR: A CDSS is currently being developed to optimize AR control and an algorithm developed by consensus is presented, which should be confirmed by appropriate trials.
Abstract: The selection of pharmacotherapy for patients with allergic rhinitis (AR) depends on several factors, including age, prominent symptoms, symptom severity, control of AR, patient preferences, and cost. Allergen exposure and the resulting symptoms vary, and treatment adjustment is required. Clinical decision support systems (CDSSs) might be beneficial for the assessment of disease control. CDSSs should be based on the best evidence and algorithms to aid patients and health care professionals to jointly determine treatment and its step-up or step-down strategy depending on AR control. Contre les MAladies Chroniques pour un VIeillissement Actif en Languedoc-Roussillon (MACVIA-LR [fighting chronic diseases for active and healthy ageing]), one of the reference sites of the European Innovation Partnership on Active and Healthy Ageing, has initiated an allergy sentinel network (the MACVIA-ARIA Sentinel Network). A CDSS is currently being developed to optimize AR control. An algorithm developed by consensus is presented in this article. This algorithm should be confirmed by appropriate trials.

126 citations

Journal ArticleDOI
TL;DR: In this paper, a combination of microscopic and pyrolytic methods applied on a Cenomanian kerogen was used to demonstrate the crucial role of the mineral matrix both in organic matter preservation during kerogen formation and in kerogen stability once formed.

126 citations

Journal ArticleDOI
TL;DR: In this article, the authors focus on two main domains where these properties play a major role: cleaving techniques used to obtain a thin silicon layer for photovoltaic applications and MEMS.
Abstract: Single-crystal silicon is extensively used in the semiconductor industry. Even though most of the steps during processing involve somehow thermo-mechanical treatment of silicon, we will focus on two main domains where these properties play a major role: cleaving techniques used to obtain a thin silicon layer for photovoltaic applications and MEMS. The evolution and validation of these new processes often rely on numerical simulations. The accuracy of these simulations, however, requires accurate input data for a wide temperature range. Numerous studies have been performed, and most of the needed parameters are generally available in the literature, but unfortunately, some discrepancies are observed in terms of measured data regarding fracture mechanics parameters. The aim of this article is to gather all these data and discuss the validity of these properties between room temperature and 1273 K. Particular attention is given to silicon fracture properties depending on crystallographic orientations, and to the brittle–ductile temperature transition which can strongly affect the quality of silicon layers.

126 citations

Journal ArticleDOI
TL;DR: A strict Lyapunov function for boundary control with integral actions of hyperbolic systems of conservation laws that can be diagonalised with Riemann invariants, is presented and can be implemented as a feedback of the state measured only at the boundaries.

125 citations

Proceedings ArticleDOI
14 Jun 2020
TL;DR: This work presents a novel technique, coined implicit affordances, to effectively leverage RL for urban driving thus including lane keeping, pedestrians and vehicles avoidance, and traffic light detection, and is the first to present a successful RL agent handling such a complex task especially regarding the traffic light Detection.
Abstract: Reinforcement Learning (RL) aims at learning an optimal behavior policy from its own experiments and not rule-based control methods. However, there is no RL algorithm yet capable of handling a task as difficult as urban driving. We present a novel technique, coined implicit affordances, to effectively leverage RL for urban driving thus including lane keeping, pedestrians and vehicles avoidance, and traffic light detection. To our knowledge we are the first to present a successful RL agent handling such a complex task especially regarding the traffic light detection. Furthermore, we have demonstrated the effectiveness of our method by winning the Camera Only track of the CARLA challenge.

125 citations


Authors

Showing all 6591 results

NameH-indexPapersCitations
Francis Bach11048454944
Olivier Delattre10349039258
Richard M. Murray9771169016
Bruno Latour9636494864
George G. Malliaras9438228533
George S. Wilson8871633034
Zhong-Ping Jiang8159724279
F. Liu8042823869
Kazu Suenaga7532926287
Carlo Adamo7544436092
Edith Heard7519623899
Enrico Zio73112723809
John J. Jonas7037921544
Bernard Asselain6940923648
Eric Guibal6929416397
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202315
202264
2021274
2020260
2019250
2018249