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Добірка наукової літератури з теми "Immeubles intelligents – Évaluation du risque"
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Дисертації з теми "Immeubles intelligents – Évaluation du risque"
Rumeau, Pierre. "Etude par l'évaluation et l'analyse de risques des possibilités de mise en production de services basés sur les HIS." Grenoble, 2010. http://www.theses.fr/2010GRENS031.
Повний текст джерелаAn activity monitoring health smart home (HIS type) based upon an infrared sensor network and the related data fusion was deployed in intermediate and long-term geriatric wards. Frail elderly people in those facilities are the closest substitute to home-dwellers, yet the staff provides the standard for activity monitoring. We could show that: 1. HIS is little intrusive and readily accepted. 2. We may model the capabilities of HIS to trigger an alarm and compare it to other devices measuring activity in specific frail populations. 3. We proved our model on the clinical case of a falling Lewy's bodies disease patient. 4. ISOFDIS 14971 norm on risk management may apply to HIS. 5. Returns may be expected from the first implementation year if an HI Sis deployed at the home a frail elderly lady with cardiovascular condition. Therefore, proposing a commercial service using HIS is medically, socially and economically relevant
Baroni, Michel. "Analyse du risque de l'immobilier physique : évaluation et application aux financements structurés." Paris 10, 2002. http://www.theses.fr/2002PA100009.
Повний текст джерелаThe aim of the thesis is to analyze the risk factors associated with real estate physical investment. A rich database of over 100000 transactions mainly for residential properties in the Paris area over the 1973-1998 period is explored. The main risk factors are identified using the Principal Component Analysis as well as a Stepwise WLS Regression Method. .
Laarabi, Mohamed Haitam. "Optimisation multicritère des itinéraires pour transport des marchandises dangereuses en employant une évaluation en logique floue du risque et la simulation du trafic à base d'agents." Thesis, Paris, ENMP, 2014. http://www.theses.fr/2014ENMP0074/document.
Повний текст джерелаEveryday thousands of trucks transporting hundreds of thousands of tons of dangerous goods by various modalities and both within and across nations. However, the term “dangerous” indicates an intrinsic adversity that characterize these products, which can manifest in an accident leading to release of a hazardous substance (e.g. radioactive, flammable, explosive etc.). In this situation, the consequences can be lethal to human beings, other living organisms and damage the environment and public/private properties.The importance of dangerous goods boils down to the significant economic benefits that generates. In fact, one cannot deny the contribution of the transport of all fossil fuel derived product, which represents more than 60% of dangerous goods transported in Europe. Eni, the Italian leading petrochemical company, every day operates a fleet of about 1,500 trucks, which performs numerous trips from loading terminals to filling stations. Distribution of petroleum products is a risky activity, and an accident during the transportation may lead to serious consequences.Aware of what is at stake, the division Eni R&M - Logistics Secondary, historically active in Genoa headquarters, is collaborating since 2002 with the DIBRIS department at University of Genoa, and the CRC at Mines ParisTech, with the purpose of studying possible improvements regarding safety in transport of dangerous goods, particularly petroleum products. Over years, this collaboration has led to the development of different technologies and mainly to an information and decision support system. The major component of this system is a platform for monitoring Eni fleet, at the national level, to deliver the products to the distribution points, called the Transport Integrated Platform (TIP). These vehicles are equipped with a device capable of transmitting data stream in real-time using a GPRS modem. The data transmitted can be of different nature and contain information about the state of the vehicle and occurred events during the trip. These data are intended to be received by centralized servers then get processed and stored, in order to support various applications within the TIP.With this in mind, the studies undertaken throughout the thesis are directed towards the development of a proposal to further minimize the risk related to the transportation of dangerous goods. In other words, a trade-off based model for route selection taking into consideration economic and safety factors. The objective is prompted by the need to support existent regulations and safety standards, which does not assure a full warranty against accidents involving dangerous goods.The goal is carried out by considering the existent system as basis for developing an Intelligent Transportation System (ITS) aggregating multiple software platforms. These platforms should allow planners and decision makers to monitor in real-time their fleet, to assess risk and evaluate all possible routes, to simulate and create different scenarios, and to assist at finding solutions to particular problems.Throughout this dissertation, I highlight the motivation for such research work, the related problem statements, and the challenges in dangerous goods transport. I introduce the TIP as the core for the proposed ITS architecture. For simulation purposes, virtual vehicles are injected into the system. The management of the data collection was the subject of technical improvement for more reliability, efficiency and scalability in real-time monitoring of dangerous goods shipment. Finally, I present a systematic explanation of the methodology for route optimization considering both economic and risk criteria. The risk is assessed based on various factors mainly the frequency of accident leading to hazardous substance release and its consequences. Uncertainty quantification in risk assessment is modelled using fuzzy sets theory
Amokrane, Kahina. "Suivi de l'apprenant en environnement virtuel pour la formation à la prévention des risques sur des sites SEVESO." Compiègne, 2010. http://www.theses.fr/2010COMP1874.
Повний текст джерелаA site classified "Seveso" is an industrial installation where the activity presents a significant risk to surrounding populations, in case of serious accident. Hence, the limitations encountered to reach this kind of site, particulary in the context of training. Virtual reality is one of the technologies that appear interesting to remedy these limitations. It allows to make the learner in situations close to reality and allows him to learn without any risk. My PhD thesis work falls within the framework of using virtual reality for risk prevention training. Our objectives are 1) to script virtual environment according to learner actions and profile, and pedagogical goals, 2) to trace learner activity and all the events sequences, from causes to effects, with argued explanations. For this, we base on knowledge representation models : task description language, ontology, erros model, Bayesian Networks. To achieve our objectives, we need to interpret the observable actions performed by a learner and their effects in virtual environments to determine performed task, commited errors and produced risks. To do this, we proposed an intelligent tutor called HERA (Helpful staff for safety learning in virtual environments)
Alves, de Lima Danilo. "Sensor-based navigation applied to intelligent electric vehicles." Thesis, Compiègne, 2015. http://www.theses.fr/2015COMP2191/document.
Повний текст джерелаAutonomous navigation of car-like robots is a large domain with several techniques and applications working in cooperation. It ranges from low-level control to global navigation, passing by environment perception, robot localization, and many others in asensor-based approach. Although there are very advanced works, they still presenting problems and limitations related to the environment where the car is inserted and the sensors used. This work addresses the navigation problem of car-like robots based on low cost sensors in urban environments. For this purpose, an intelligent electric vehicle was equipped with vision cameras and other sensors to be applied in three big areas of robot navigation : the Environment Perception, Local Navigation Control, and Global Navigation Management. In the environment perception, a 2D and 3D image processing approach was proposed to segment the road area and detect the obstacles. This segmentation approach also provides some image features to local navigation control.Based on the previous detected information, a hybrid control approach for vision based navigation with obstacle avoidance was applied to road lane following. It is composed by the validation of a Visual Servoing methodology (deliberative controller) in a new Image-based Dynamic Window Approach (reactive controller). To assure the car’s global navigation, we proposed the association of the data from digital maps in order tomanage the local navigation at critical points, like road intersections. Experiments in a challenging scenario with both simulated and real experimental car show the viabilityof the proposed methodology