Academic literature on the topic 'Surveillance du modèle'
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Journal articles on the topic "Surveillance du modèle"
Aigrain, Alice. "Jules D., patient, modèle." Photographica, no. 5 (November 21, 2022): 22–41. http://dx.doi.org/10.54390/photographica.982.
Full textWang, Alain. "La Chine s’exporte." Revue Projet N° 395, no. 4 (July 17, 2023): 38–42. http://dx.doi.org/10.3917/pro.395.0038.
Full textBaril12, Alexandre. "Les personnes suicidaires peuvent-elles parler ?" Criminologie 51, no. 2 (September 12, 2018): 189–212. http://dx.doi.org/10.7202/1054240ar.
Full textEmond, V., and D. Saint-Laurent. "Le modèle québécois de surveillance des maladies chroniques à partir des fichiers administratifs." Revue d'Épidémiologie et de Santé Publique 60 (September 2012): S53. http://dx.doi.org/10.1016/j.respe.2012.06.032.
Full textBerger, Emmanuel. "Le modèle judiciaire libéral mis à l'épreuve : la surveillance des juges sous le Directoire." Annales historiques de la Révolution française 337, no. 1 (2004): 41–62. http://dx.doi.org/10.3406/ahrf.2004.2721.
Full textBerger, Emmanuel. "Le modèle judiciaire libéral mis à l’épreuve : la surveillance des juges sous le Directoire." Annales historiques de la Révolution française, no. 337 (September 1, 2004): 41–62. http://dx.doi.org/10.4000/ahrf.1510.
Full textNocetti, Julien. "Internet contre la démocratie ?" Questions internationales 113-114, no. 3 (July 12, 2022): 122–28. http://dx.doi.org/10.3917/quin.113.0122.
Full textNinot, Grégory, and François Carbonnel. "Pour un modèle consensuel de validation clinique et de surveillance des interventions non médicamenteuses (INM)." Hegel N° 3, no. 3 (July 1, 2016): 273–79. http://dx.doi.org/10.3917/heg.063.0273.
Full textNinot, Grégory, and François Carbonnel. "Pour un modèle consensuel de validation clinique et de surveillance des interventions non médicamenteuses (INM)." Hegel N° 3, no. 3 (2016): 273. http://dx.doi.org/10.4267/2042/61405.
Full textLauzeille, D., M. Houot, C. Kamali, F. Moisan, and Y. Iwatsubo. "Surveillance de l’asthme chez des artisans et commerçants : utilisation d’un modèle prédictif de l’asthme – France." Revue d'Épidémiologie et de Santé Publique 62 (September 2014): S199. http://dx.doi.org/10.1016/j.respe.2014.06.091.
Full textDissertations / Theses on the topic "Surveillance du modèle"
Daneshi, Far Zahra. "Contribution à la surveillance et maintenance prédictive des éoliennes." Amiens, 2013. http://www.theses.fr/2013AMIE0102.
Full textThe main existing monitoring systems are using vibrations as indexes to detect fault in the global system. In this way, several vibration sensors should be installed on the generator, the gearbox, and the bearing. The main problem with existing condition monitoring systems is that numerous sensors are installed in the turbine which makes the monitoring system complex and expensive. It is shown that the high rate of missed fault detection (about 40%) of gearbox fault exist in the wind turbines equipped with vibration based condition monitoring systems even with employing so many vibration sensors. This shows that vibration based condition monitoring systems are not reliable enough and a new or complementary condition monitoring system are needed. In this work, a potential approach for detecting drive-train mechanical faults using generator electrical signals has been introduced. Since the generator provides electromechanical coupling, the monitoring of its output power could lead to electrical and mechanical fault detection. In this regard, we studied the effect of the gearbox on the electrical signature of the generator for a variable speed wind turbine generator with a wound rotor and partial power converter (known as type -3). For which, we have developed the wind turbine simulator using MATLAB / Simulink. The dynamic of the planetary gearbox in hardly ever considered in the wind turbine model in the literature. Therefore, generic dynamic model of planetary gearbox for condition monitoring and diagnostic purposes is presented in this work. The model of gearbox is using minimum number of parameters, which includes essential non-linearities such as time varying mesh stiffness, transmission error and damping force. The proposed gearbox model is a generic model and is adapted for all possible power flow configuration of single stage planetary gearbox with any number of planet gears and could also be used in other applications than wind turbine
Bronner, Anne. "Vers un modèle de surveillance intégrée des maladies exotiques abortives chez les bovins en France métropolitaine : évaluation de la surveillance évènementielle et exploration d’outils complémentaires de surveillance syndromique." Thesis, Lyon 1, 2015. http://www.theses.fr/2015LYO10161/document.
Full textThe surveillance system for exotic abortive diseases in French cattle (i.e. abortive diseases that are not currently found in France), such as brucellosis, is a typical example of a surveillance system that is in need of improvement. This type of surveillance only actually exists for brucellosis. Clinical surveillance is the cornerstone of brucellosis surveillance and consists in the mandatory notification of each bovine abortion. However, while no quantitatively assessments have been made, it is common knowledge that this type of surveillance suffers from high levels of under-reporting. By providing an in-depth assessment of the bovine abortion notification surveillance system, we quantified its low sensitivity and identified the influence of structural, human and health factors on how decisions to report abortions are taken. In addition, demographic and reproductive data, collected for purposes of traceability and for genetic performance improvement, were used to devise indirect indicators of abortion occurrence. By modeling the temporal and spatio-temporal variations of these indicators, we highlighted the ability for syndromic surveillance systems to identify the occurrence of abortive events at individual and herd scale. Based on these studies, improving exotic abortive disease surveillance requires revising the mandatory notification surveillance system and developing syndromic surveillance systems. More generally, considering the difficulties in predicting the occurrence of exotic or emerging diseases and their clinical and epidemiological forms, it is necessary to reorganize the surveillance of exotic diseases by setting up integrated surveillance systems that would include different surveillance modalities. Such surveillance systems, implemented by production sector, would focus on known or unknown diseases, showing clinical or subclinical forms, and sporadic, epizootic or diffuse patterns, and would thus maximize the ability to detect exotic or emerging diseases
Roux, Gilles. "Surveillance dans les ateliers automatisés : une approche par observation d'un modèle de commande." Grenoble INPG, 1990. http://www.theses.fr/1990INPG0107.
Full textGehin, Anne-Lise. "Analyse fonctionnelle et modèle générique des capteurs intelligents : application à la surveillance de l'anesthésie." Lille 1, 1994. http://www.theses.fr/1994LIL10001.
Full textTruong, Xuan Viet. "Optimization by Simulation of an Environmental Surveillance Network : application to the Fight against Rice Pests in the Mekong Delta (Vietnam)." Electronic Thesis or Diss., Paris 6, 2014. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2014PA066278.pdf.
Full textAn efficient surveillance network is an invaluable tool to monitor and assess the different states of a given ecosystem. With the information collected by such a network, predictions can be generated using thorough spatio-temporal analyses, which can then support decision makers and stakeholders. Human dominated ecosystems are highly dynamic and complex , where most of the observed variables have mutual non-linear interactions. In addition, the human activities have a considerable impact on almost all ecosystems they inhabit, where they tend to disrupt the ecological balance in short period of times. The surveillance of such ecosystems by different technical solutions is complex and dynamic where designing an “optimal” surveillance network, i.e., a network that would reflect an almost realtime situation of an ecosystem. Often traditional optimization techniques fail to reflect the evolutions of the reality associated with these ecosystems.An example of such a situation, is the Mekong Delta region of Vietnam, where the provincial agricultural managers are concerned with the regular invasions of Brown Plant Hoppers (BPH), a particularly active rice pest, because of the diseases they carry and transmit to the rice yields. Their biggest concern is having a constantly accurate account of the current distribution of BPH waves, since it is the basis of establishing different prevention strategies. The time frame is short for applying these strategies: at least one week is needed between the moment where a prediction of the density of BPH can be estimated by the experts and warnings are sent to farmers and other end users and the moment where a strategy can be efficiently applied. To improve the efficiency of the system, the Vietnamese government has established a light-trap network [1] [2] that can capture multiple kinds of insects, especially BPH, and which data (the density of insects per trap) is collected and analyzed daily. Maintaining this network in a good state of operation has become an important national program of the Ministry of Agriculture and Rural Development of Vietnam since 2006. Although the current light-trap network is considered as a necessity for supporting the fight against various plant pests, it has three restrictions: (1) it misses detailed accounts on the life cycle of the BPH, (2) the network has remained stable since its initial design and has not, therefore, completely adapted to the huge changes that the ecosystem of the Mekong Delta has undergone in the recent years especially due to limitations in management, and (3) the network itself is very sparsely distributed
Bernichi, Mâamoun. "Surveillance logicielle à base d'une communauté d'agents mobiles." Phd thesis, Université Paris-Est, 2009. http://tel.archives-ouvertes.fr/tel-00480718.
Full textTruong, Xuan Viet. "Optimization by Simulation of an Environmental Surveillance Network : application to the Fight against Rice Pests in the Mekong Delta (Vietnam)." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066278/document.
Full textAn efficient surveillance network is an invaluable tool to monitor and assess the different states of a given ecosystem. With the information collected by such a network, predictions can be generated using thorough spatio-temporal analyses, which can then support decision makers and stakeholders. Human dominated ecosystems are highly dynamic and complex , where most of the observed variables have mutual non-linear interactions. In addition, the human activities have a considerable impact on almost all ecosystems they inhabit, where they tend to disrupt the ecological balance in short period of times. The surveillance of such ecosystems by different technical solutions is complex and dynamic where designing an “optimal” surveillance network, i.e., a network that would reflect an almost realtime situation of an ecosystem. Often traditional optimization techniques fail to reflect the evolutions of the reality associated with these ecosystems.An example of such a situation, is the Mekong Delta region of Vietnam, where the provincial agricultural managers are concerned with the regular invasions of Brown Plant Hoppers (BPH), a particularly active rice pest, because of the diseases they carry and transmit to the rice yields. Their biggest concern is having a constantly accurate account of the current distribution of BPH waves, since it is the basis of establishing different prevention strategies. The time frame is short for applying these strategies: at least one week is needed between the moment where a prediction of the density of BPH can be estimated by the experts and warnings are sent to farmers and other end users and the moment where a strategy can be efficiently applied. To improve the efficiency of the system, the Vietnamese government has established a light-trap network [1] [2] that can capture multiple kinds of insects, especially BPH, and which data (the density of insects per trap) is collected and analyzed daily. Maintaining this network in a good state of operation has become an important national program of the Ministry of Agriculture and Rural Development of Vietnam since 2006. Although the current light-trap network is considered as a necessity for supporting the fight against various plant pests, it has three restrictions: (1) it misses detailed accounts on the life cycle of the BPH, (2) the network has remained stable since its initial design and has not, therefore, completely adapted to the huge changes that the ecosystem of the Mekong Delta has undergone in the recent years especially due to limitations in management, and (3) the network itself is very sparsely distributed
ZAMAI, Eric. "Architecture de surveillance-commande pour les systèmes à événements discrets complexes." Phd thesis, Université Paul Sabatier - Toulouse III, 1997. http://tel.archives-ouvertes.fr/tel-00010078.
Full textLi, Zhongyang. "Suivi de multi-modulations non linéaires pour la surveillance." Phd thesis, Université de Grenoble, 2013. http://tel.archives-ouvertes.fr/tel-00935243.
Full textAbou, Ghaida Hussein. "Modélisation de l’équilibre et système de surveillance posturale." Thesis, Rennes 1, 2014. http://www.theses.fr/2014REN1S167.
Full textProblems of balance are often diagnosed thanks to plantar pressure cartography systems or forces platform that measure the center of pressure displacement. These professional systems are restricted in use to medical environments, and until now, the balance monitoring systems do not offer complete satisfaction in terms of mobility and acceptability. In order to overcome these limitation and in the context of telemedicine and e-health, we aimed to develop tools for ambulatory monitoring of postural equilibrium and to understand the balance control. We have first undertaken a theoretical study on the feasibility of measuring plantar pressure and dynamic displacement of the center of pressure, from a very small number of sensors. For these applications, we have proposed a simplified mechanical foot model, as well as related assumptions. The model describes the physical relationship between foot posture and distribution of plantar pressures following its biomechanical characteristics. Based on a prototype of an instrumented insole with only 3 sensors, we have verified experimentally the ability of the system and the methods to generate both the stabilogram and the plantar pressure maps. Comparison is made with a matrix reference system, and characterization in terms of uncertainty in the case of normal foot in standing position and during walking is detailed. The measured stabilogram can be analyzed to characterize the signature of balance. We have also proposed a specific three-dimensional model describing the dynamics of balance. Based on simulation, it leads to identify the main physiological parameters related to balance control
Books on the topic "Surveillance du modèle"
W, Moore James. Le contrôle des armements conventionnels et le désarmement en Europe: Un modèle pour l'appréciation de l'efficacité du système de vérification. Ottawa, Ont: Ministère des affaires extérieures, 1990.
Find full textDeterministic aspects in mathematical demography. Berlin: Springer-Verlag, 1985.
Find full textCenters for Disease Control (U.S.), ed. Preparing summary disease surveillance reports: Module 13. [Atlanta, Ga.?]: U.S. Dept. of Health and Human Services, Public Health Service, Centers for Disease Control, 1988.
Find full textCenters for Disease Control (U.S.), ed. Preparing summary disease surveillance reports: Module 13. [Atlanta, Ga.?]: U.S. Dept. of Health and Human Services, Public Health Service, Centers for Disease Control, 1988.
Find full textFrisen, Marianne. Financial Surveillance. New York: John Wiley & Sons, Ltd., 2008.
Find full textStochastic processes in demography and their computer implementation. Berlin: Springer-Verlag, 1985.
Find full textTomasz, Okruszko, ed. Wetlands: Monitoring, modelling and management. London: Taylor & Francis, 2007.
Find full textChan-Lau, Jorge A. Market-based estimation of default probabilities and its application to financial market surveillance. [Washington, D.C.]: International Monetary Fund, Monetary and Financial Systems Dept., 2006.
Find full textChan-Lau, Jorge A. Currency mismatches and corporate default risk: Modeling, measurement, and surveillance applications. [Washington, D.C.]: International Monetary Fund, 2006.
Find full textM, Wager Michael, Moore, Andrew W., Ph.D., and Aryel Ron M, eds. Handbook of biosurveillance. Boston: Academic Press, 2006.
Find full textBook chapters on the topic "Surveillance du modèle"
Gibson, G., and C. A. Gilligan. "Inference and prediction with individual-based stochastic models of epidemics." In Biosecurity surveillance: quantitative approaches, 253–64. Wallingford: CABI, 2015. http://dx.doi.org/10.1079/9781780643595.0253.
Full textLow-Choy, S. "Hierarchical models for evaluating surveillance strategies: diversity within a common modular structure." In Biosecurity surveillance: quantitative approaches, 75–108. Wallingford: CABI, 2015. http://dx.doi.org/10.1079/9781780643595.0075.
Full textRenton, M., and D. Savage. "Statistical emulators of simulation models to inform surveillance and response to new biological invasions." In Biosecurity surveillance: quantitative approaches, 296–312. Wallingford: CABI, 2015. http://dx.doi.org/10.1079/9781780643595.0296.
Full textKleinman, Ken. "Generalized Linear Models and Generalized Linear Mixed Models for Small-Area Surveillance." In Spatial and Syndromic Surveillance for Public Health, 77–94. Chichester, UK: John Wiley & Sons, Ltd, 2005. http://dx.doi.org/10.1002/0470092505.ch5.
Full textChasanis, Vasileios, and Aristidis Likas. "Event Detection and Classification in Video Surveillance Sequences." In Artificial Intelligence: Theories, Models and Applications, 309–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12842-4_35.
Full textBoursalie, Omar, Reza Samavi, and Thomas E. Doyle. "Evaluation Metrics for Deep Learning Imputation Models." In AI for Disease Surveillance and Pandemic Intelligence, 309–22. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93080-6_22.
Full textPoppe, Chris, Gaëtan Martens, Peter Lambert, and Rik Van de Walle. "Improved Background Mixture Models for Video Surveillance Applications." In Computer Vision – ACCV 2007, 251–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-76386-4_23.
Full textHuang, Tianci, Xiangzhong Fang, Jingbang Qiu, and Takeshi Ikenaga. "Adaptively Adjusted Gaussian Mixture Models for Surveillance Applications." In Lecture Notes in Computer Science, 689–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11301-7_70.
Full textRao, V. Sree Hari, and M. Naresh Kumar. "Predictive Dynamics: Modeling for Virological Surveillance and Clinical Management of Dengue." In Dynamic Models of Infectious Diseases, 1–41. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-3961-5_1.
Full textMezzina, G., M. Barbareschi, Salavatore De Simone, Alessandro Di Benedetto, G. Narracci, C. L. Saragaglia, D. Serra, and Daniela De Venuto. "Smart On-Board Surveillance Module for Safe Autonomous Train Operations." In Lecture Notes in Electrical Engineering, 317–25. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95498-7_44.
Full textConference papers on the topic "Surveillance du modèle"
Salih, Maryam A., May A. Salih, Hala Jamal, and Aliyaa Hussain. "Hybrid module for low-cost surveillance system." In 2017 6th International Conference on Information and Communication Technology and Accessibility (ICTA). IEEE, 2017. http://dx.doi.org/10.1109/icta.2017.8336012.
Full textBaptist Andrews, Leo John, Sarathkumar D, and Raymon Antony Raj. "IOT Based Surveillance Camera with GPS Module." In 2023 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS). IEEE, 2023. http://dx.doi.org/10.1109/sceecs57921.2023.10062961.
Full textFerro, Duco, and Alfons Salden. "Self-organizing mobile surveillance security networks." In 2007 2nd Bio-Inspired Models of Network, Information and Computing Systems (BIONETICS). IEEE, 2007. http://dx.doi.org/10.1109/bimnics.2007.4610114.
Full text"Building a Privacy Accountable Surveillance System." In Special Session on Security and Privacy in Model Based Engineering. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005401606460654.
Full textMoors, Mark, and Dirk Schulz. "Improved Markov Models for Indoor Surveillance." In 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE, 2006. http://dx.doi.org/10.1109/iros.2006.281871.
Full textFerro, Duco, and Alfons Salden. "Self-organizing mobile surveillance security networks." In 2nd International ICST Conference on Bio-Inspired Models of Network, Information, and Computing Systems. IEEE, 2007. http://dx.doi.org/10.4108/icst.bionetics2007.2478.
Full textHeikkilä, Marko, and Matti Pietikäinen. "An image mosaicing module for wide-area surveillance." In the third ACM international workshop. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1099396.1099400.
Full textComitz, Paul. "Are aviation data models too Complex?" In 2013 Integrated Communications, Navigation and Surveillance Conference (ICNS). IEEE, 2013. http://dx.doi.org/10.1109/icnsurv.2013.6548598.
Full textBaron, Anna, Radu F. Babiceanu, and Remzi Seker. "Trustworthiness requirements and models for aviation and aerospace systems." In 2018 Integrated Communications, Navigation, Surveillance Conference (ICNS). IEEE, 2018. http://dx.doi.org/10.1109/icnsurv.2018.8384831.
Full textGarcia, Anna Baron, Radu F. Babiceanu, and Remzi Seker. "Trustworthiness requirements and models for aviation and aerospace systems." In 2018 Integrated Communications, Navigation, Surveillance Conference (ICNS). IEEE, 2018. http://dx.doi.org/10.1109/icnsurv.2018.8384911.
Full textReports on the topic "Surveillance du modèle"
Grappel, Robert D., Garrett S. Harris, Mark J. Kozar, and Randall T. Wiken. Elementary Surveillance (ELS) and Enhanced Surveillance (EHS) Validation via Mode S Secondary Radar Surveillance. Fort Belvoir, VA: Defense Technical Information Center, April 2008. http://dx.doi.org/10.21236/ada489387.
Full textEdmunds, T. Agent-based Disease Surveillance and Transmission Model. Office of Scientific and Technical Information (OSTI), December 2021. http://dx.doi.org/10.2172/1835684.
Full textPhipps, Jr, Neta Warren E., Danielson Beny, and D. A. Parallelization of the Naval Space Surveillance Satellite Motion Model. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada531142.
Full textShinn, Antoinette M. PET-CT Animal Model for Surveillance of Embedded Metal Fragments. Fort Belvoir, VA: Defense Technical Information Center, December 2012. http://dx.doi.org/10.21236/ada618102.
Full textEdmunds, T. A. A Markov Chain Model for evaluating the effectiveness of randomized surveillance procedures. Office of Scientific and Technical Information (OSTI), January 1994. http://dx.doi.org/10.2172/10142261.
Full textBarnes, R., B. Schneier, C. Jennings, T. Hardie, B. Trammell, C. Huitema, and D. Borkmann. Confidentiality in the Face of Pervasive Surveillance: A Threat Model and Problem Statement. RFC Editor, August 2015. http://dx.doi.org/10.17487/rfc7624.
Full textSmith, Amy M., and Richard E. Heyman. Family Maltreatment, Substance Problems, and Suicidality: Prevalence Surveillance and Ecological Risk/Protective Factors Models. Fort Belvoir, VA: Defense Technical Information Center, April 2008. http://dx.doi.org/10.21236/ada494430.
Full textPaul, Tiffany M., Mary Fendley, and Soloman Gibbs. Application of the Augmented Operator Function Model for Developing Cognitive Metrics in Persistent Surveillance. Fort Belvoir, VA: Defense Technical Information Center, September 2013. http://dx.doi.org/10.21236/ada595397.
Full textVANKEUREN, J. C. Dose calculations for the B plant FSAR in the surveillance and maintenance mode. Office of Scientific and Technical Information (OSTI), February 1999. http://dx.doi.org/10.2172/781552.
Full textShukla, Indu, Rajeev Agrawal, Kelly Ervin, and Jonathan Boone. AI on digital twin of facility captured by reality scans. Engineer Research and Development Center (U.S.), November 2023. http://dx.doi.org/10.21079/11681/47850.
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