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350 results on '"Weber, Philippe"'

1. Trends in Maternal Mortality From Obstetric Hemorrhage in France: 15 Years of Confidential Enquiry Into Maternal Deaths

Author

Bonnet, Marie-Pierre, de Vries, Pauline L.M., Levet, Solène, Saucedo, Monica, Morau, Estelle, Dreyfus, Michel, Goffinet, François, Deneux-Tharaux, Catherine, Bruyère, Marie, Cohen, Henri, Ducloy, Jean-Claude, Gomes, Eugênia, Jonard, Marie, Laplace, Jean-Pierre, Le Guern, Véronique, Leroux, Sylvie, Morgand, Claire, Proust, Alain, Rigouzzo, Agnès, Rossignol, Mathias, Tessier, Véronique, Verspyck, Éric, and Weber, Philippe

Published
2024
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4. A Reinforcement Learning Approach to Health Aware Control Strategy

Author

Jha, Mayank Shekhar, Weber, Philippe, Theilliol, Didier, Ponsart, Jean-Christophe, and Maquin, Didier

Subjects
Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Health-aware control (HAC) has emerged as one of the domains where control synthesis is sought based upon the failure prognostics of system/component or the Remaining Useful Life (RUL) predictions of critical components. The fact that mathematical dynamic (transition) models of RUL are rarely available, makes it difficult for RUL information to be incorporated into the control paradigm. A novel framework for health aware control is presented in this paper where reinforcement learning based approach is used to learn an optimal control policy in face of component degradation by integrating global system transition data (generated by an analytical model that mimics the real system) and RUL predictions. The RUL predictions generated at each step, is tracked to a desired value of RUL. The latter is integrated within a cost function which is maximized to learn the optimal control. The proposed method is studied using simulation of a DC motor and shaft wear.

Published
2020

10. Neueste M&A-Entwicklungen - von Fachleuten kommentiert - 25. Zürcher Konferenz Mergers & Acquisitions - Tagungsband 2022

Author

Banelli, Sara, additional, Cochardt, Alexander, additional, Diem, Hans-Jakob, additional, Dubs, Dieter, additional, Gericke, Dieter, additional, Maag, Michael, additional, Nikitine, Alex, additional, Orelli, Mariella, additional, Perlini-Frehner, Fabienne, additional, Siklosi, Katalin, additional, Weber, Philippe A., additional, and Wiesner, Valentin, additional

Published
2023
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22. Reliability Analysis of Fault Tolerant Wind Energy Conversion System with Doubly Fed Induction Generator

Author

Weber, Philippe, Becker, Florent, Mathias, Antoine, Theilliol, Didier, Zhang, Youmin M., Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Su, Chun-Yi, editor, Rakheja, Subhash, editor, and Liu, Honghai, editor

Published
2012
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25. Prognostic considering missing data: An input output hidden Markov model based solution

Author

Shahin, Kamrul Islam, Simon, Christophe, Weber, Philippe, Johansen, Aslak, and Kjærgaard, Mikkel Baun

Abstract

The remaining useful life of a system is unknown and uncertain due to the uncertainty of system failure. However, by monitoring the behaviour of the system, it is possible to predict the current health and also the near future health states. To make a correct prognostic, we need to understand the degradation process of similar systems from the historical data, which is often not easy to collect in huge amount because the degradation process is a slow progression. A complete sequence requires collecting data from the beginning of a system’s operation until its death or failure. However, in reality, most deployments will have to deal with missing data, misreading or sensor saturation. This paper works on handling the missing data for improving the model training by extracting as much information as possible even from the incomplete sequences. In this paper, we propose an IOHMM-based missing data processing method, which is shown to provide better results compared to the list deletion method. A bootstrap method is developed that resamples using replacement sequences picked by the learning algorithms. Two well-known learning algorithms: the Baum Welch and the forward-backward algorithm are adapted to handle the missing data. A numerical application is simulated to demonstrate the role of the proposed algorithm and the corresponding model performance in RUL prediction, which is the basis of the RUL management.

Published
2023
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27. Maternal sudden death: A nationwide retrospective study.

Author

Braund, Sophia, Leviel, Juliette, Morau, Estelle, Deneux‐Tharaux, Catherine, Verspyck, Eric, Cohen, Henri, Dreyfus, Michel, Ducloy, Jean‐Claude, Jonard, Marie, Laplace, Jean‐Pierre, Le Guern, Véronique, Leroux, Sylvie, Proust, Alain, Rigouzzo, Agnès, Rossignol, Mathias, Tessier, Véronique, Verspyck, Éric, and Weber, Philippe

Subjects
SUDDEN death, CARDIAC arrest, CAUSES of death, COMPUTED tomography, RETROSPECTIVE studies
Abstract

Objective: To determine the prevalence of maternal sudden death (MSD) and to compare the characteristics of death between women with explained and unexplained sudden death. Design: A national retrospective study in France. Population Maternal deaths related to an unexpected sudden cardiac arrest were extracted from the French National Confidential Enquiry into Maternal Deaths database for 2007–2012. Methods: Maternal, pregnancy, sudden death characteristics and maternal investigations were compared between women with explained and unexplained cause of death. Results: A total of 83 maternal sudden deaths and 4 949 890 live births occurred over the period studied, thus accounting for 16% of all maternal deaths (n = 510). Death was explained in 51 (61%) women and unexplained in 32 women (39%). Compared with women with unexplained death, women with explained death were more often found to have in‐hospital cardiac arrest (47% versus 12%, P < 0.01), witnessed cardiac arrest (86% versus 62%, P = 0.03) and in‐hospital death (82% versus 47%, P < 0.01). Postmortem investigations such as autopsy and/or CT scan (65% versus 31%, P < 0.01) were also more often carried out in women with explained death. The proportion of deaths for which the preventability factors could not be assessed was 58% among unexplained MSD and 7% among explained MSD. Conclusion: Maternal sudden death is a rare event but accounts for a high proportion of all maternal deaths. This highlights the importance of providing training in diagnostic and management strategy for care providers. Systematic postmortem investigations are required to help understand causes and improve practices. [ABSTRACT FROM AUTHOR]

Published
2023
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30. Le fabuleux destin de l’enquête sur la mortalité maternelle

Author

Morau, Estelle, primary, Dreyfus, Michel, additional, Deneux-Tharaux, Catherine, additional, Beaumont, Étienne, additional, Bruyère, Marie, additional, Cohen, Henri, additional, Ducloy, Jean-Claude, additional, Gomes, Eugênia, additional, Jonard, Marie, additional, Laplace, Jean-Pierre, additional, Le Guern, Véronique, additional, Leroux, Sylvie, additional, Morau, Estelle, additional, Morgand, Claire, additional, Proust, Alain, additional, Rigouzzo, Agnès, additional, Rossignol, Mathias, additional, Saucedo, Monica, additional, Tessier, Véronique, additional, Vacheron, Marie-Noëlle, additional, Verspyck, Éric, additional, and Weber, Philippe, additional

Published
2021
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31. Evidential networks for reliability analysis and performance evaluation of systems with imprecise knowledge

Author

Simon, Christophe and Weber, Philippe

Subjects
Event history analysis -- Usage, Graph theory -- Analysis, Combinatorial probabilities -- Usage, Geometric probabilities -- Usage, Probabilities -- Usage, Business, Electronics, Electronics and electrical industries
Abstract

Evidential networks are described for managing imprecise probabilities, where these networks are directed acyclic graphs that handle random and epistemic uncertainties due to Dempster-Shafer structures. Evidential networks are extended with imprecise utility functions to deal with system performance evaluation problems and also for system reliability evaluation problems.

Published
2009

32. Modèle IOHMM pour le diagnostic et le pronostic de systèmes

Author

Shahin, Kamrul Islam, Simon, Christophe, Weber, Philippe, Centre de Recherche en Automatique de Nancy (CRAN), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), and Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SPI]Engineering Sciences [physics], dégradation, état de santé, condition opérationnelle, [SPI.AUTO]Engineering Sciences [physics]/Automatic
Abstract

National audience; Dans cet article, nous proposons d’exploiter une forme évoluée de modèle de Markov caché (HMM) pour représenter le processus d’évolution de l’état de santé d’un système. Ce type de modèle présente plusieurs intérêts. Il correspond bien au principe d’évolution d’un élément (état de santé) complexe et non observable directement, mais au travers de variables d’observation. Sa nature stochastique permet la prise en compte de l’incertitude : bruit d’observation (incertitude de données), processus d’évolution plus complexe qu’imaginé (incertitude de modèle). Dans ce contexte, les réseaux bayésiens dynamiques et notamment les 2 Time slices Bayésien Networks sont particulièrement bien appropriés pour représenter une HMM conditionnée par des états de conditions opérationnelles et ainsi formé une classe évoluée de HMM, les Input-Output HMM (IOHMM).

Published
2020

33. Input-output hidden markov model for system health diagnostic considering missing data

Author

Shahin, Kamrul Islam, Simon, Christophe, Weber, Philippe, Theilliol, Didier, Maquin, Didier, Centre de Recherche en Automatique de Nancy (CRAN), and Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)

Subjects
[SPI.AUTO] Engineering Sciences [physics]/Automatic, Modelling and simulation, Fault diagnosis, [SPI.AUTO]Engineering Sciences [physics]/Automatic
Abstract

International audience; Sensor data can be used to diagnose the system's health. A challenge comes when the data contain missing or invalid data. It is common that sensors misread for various reasons. So, data contain missing measurements and sensor saturation. The main contribution in this paper is to implement a method based on the Input-Output Hidden Markov Model that trains the model using the missing measurements and sensor saturation, then diagnoses the system health at given operating conditions. Usually, if a data set contains some sequences with missing elements then they can be excluded from the analysis. It cleans the data set but reduces its size. This strategy knows as list-wise or case-wise deletion is less suitable for real application cases. The proposed method includes the sequences with missing data into the analysis by generating the missing elements to complete the sequence. The maximum likelihood is applied to estimate IOHMM parameters that offer substantial improvements over list-wise deletion. A numerical application with simulated data sets illustrates the method.

Published
2020

34. Probabilité de défaillance à la demande moyenne et tests longs par réseaux bayésiens dynamiques

Author

Simon, Christophe, Mechri, Walid, WEBER, Philippe, GBONSOU, Moriaque Gaël, Centre de Recherche en Automatique de Nancy (CRAN), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Université de Tunis El Manar (UTM), and Institut pour la Maîtrise des Risques

Subjects
SIS, test d'inspection, [SPI]Engineering Sciences [physics], durée de test, stratégie de test, [SPI] Engineering Sciences [physics], indisponibilité moyenne
Abstract

National audience; Cet article étudie la modélisation de l'indisponibilité des systèmes instrumentés de sécurité (SIS) par les réseaux bayésiens dynamiques (RBD) dans le cas particulier de tests de durée importante. La durée augmente la complexité du modèle lorsque l'on considère l'indisponibilité des composants étant donné le test, mais elle est plus réaliste.

Published
2020

35. PFD moyenne et tests longs par réseaux bayésiens dynamiques

Author

Simon, Christophe, Mechri, Walid, Weber, Philippe, Maquin, Didier, Centre de Recherche en Automatique de Nancy (CRAN), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), LARA Tunis, Ecole Nationale d'Ingénieurs de Tunis (ENIT), and Université de Tunis El Manar (UTM)-Université de Tunis El Manar (UTM)

Subjects
[SPI.AUTO] Engineering Sciences [physics]/Automatic, ComputingMilieux_MISCELLANEOUS, [SPI.AUTO]Engineering Sciences [physics]/Automatic
Abstract

National audience

Published
2020

37. Reduction of antibiotic use in the community reduces the rate of colonization with penicillin G-nonsusceptible Streptococcus pneumoniae

Author

Guillemot, Didier, Varon, Emmanuelle, Bernede, Claire, Weber, Philippe, Henriet, Laurence, Simon, Sylvie, Laurent, Cecile, Lecoeur, Herve, and Carbon, Claude

Subjects
Bacterial pneumonia -- Diagnosis, Bacterial pneumonia -- Care and treatment, Pneumonia -- Diagnosis, Pneumonia -- Care and treatment, Streptococcal infections -- Diagnosis, Streptococcal infections -- Care and treatment, Penicillin G -- Research, Health, Health care industry
Published
2005

44. Improvement of a disk diffusion method for antibiotic susceptibility testing of anaerobic bacteria. French recommendations revisited for 2020

Author

Dubreuil, L., primary, Jehl, F., additional, Cattoen, C., additional, Bonnet, R., additional, Bru, J.P., additional, Caron, F., additional, Cattoir, Vincent, additional, Courvalin, Patrice, additional, Jarlier, Vincent, additional, Lina, Gérard, additional, Merens, Audrey, additional, Plesiat, Patrick, additional, Marie-Cécile, P.L.O.Y., additional, Soussy, Claude-James, additional, Varon, Emmanuelle, additional, and Weber, Philippe, additional

Published
2020
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