913 resultados para Probabilistic fire risk analysis


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A review of extinction risk analysis and viability methods is presented. The importance of environmental, demographic and genetic uncertainties, as well as the role of catastrophes are successively considered, and different approaches aiming at the integration of these risk factors in predictive population dynamic models are discussed.

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La gestion des risques est souvent appréhendée par l'utilisation de méthodes linéaires mettant l'accent sur des raisonnements de positionnement et de type causal : à tel événement correspond tel risque et telle conséquence. Une prise en compte des interrelations entre risques est souvent occultée et les risques sont rarement analysés dans leurs dynamiques et composantes non linéaires. Ce travail présente ce que les méthodes systémiques et notamment l'étude des systèmes complexes sont susceptibles d'apporter en matière de compréhension, de management et d'anticipation et de gestion des risques d'entreprise, tant sur le plan conceptuel que de matière appliquée. En partant des définitions relatives aux notions de systèmes et de risques dans différents domaines, ainsi que des méthodes qui sont utilisées pour maîtriser les risques, ce travail confronte cet ensemble à ce qu'apportent les approches d'analyse systémique et de modélisation des systèmes complexes. En mettant en évidence les effets parfois réducteurs des méthodes de prise en compte des risques en entreprise ainsi que les limitations des univers de risques dues, notamment, à des définitions mal adaptées, ce travail propose également, pour la Direction d'entreprise, une palette des outils et approches différentes, qui tiennent mieux compte de la complexité, pour gérer les risques, pour aligner stratégie et management des risques, ainsi que des méthodes d'analyse du niveau de maturité de l'entreprise en matière de gestion des risques. - Risk management is often assessed through linear methods which stress positioning and causal logical frameworks: to such events correspond such consequences and such risks accordingly. Consideration of the interrelationships between risks is often overlooked and risks are rarely analyzed in their dynamic and nonlinear components. This work shows what systemic methods, including the study of complex systems, are likely to bring to knowledge, management, anticipation of business risks, both on the conceptual and the practical sides. Based on the definitions of systems and risks in various areas, as well as methods used to manage risk, this work confronts these concepts with approaches of complex systems analysis and modeling. This work highlights the reducing effects of some business risk analysis methods as well as limitations of risk universes caused in particular by unsuitable definitions. As a result this work also provides chief officers with a range of different tools and approaches which allows them a better understanding of complexity and as such a gain in efficiency in their risk management practices. It results in a better fit between strategy and risk management. Ultimately the firm gains in its maturity of risk management.

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Northern Ireland Health Technical Memorandum 86 Part 2 Fire Risk Assessment in Healthcare Premises

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Northern Ireland Health Technical Memorandum 86 Fire Risk Assessment Part 1 Community Healthcare Premises

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Health Technical Memorandum 84 Fire risk assessment in residential care premises

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This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

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We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos

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BACKGROUND The possible differences in the disease spectrum and prognosis of HIV infection in women and men is a major point of concern. Women are under-represented in randomized clinical trials and in some cohorts. Discordant results have often been obtained depending on the setting. METHODS We assessed gender differences in clinical and epidemiological features, antiretroviral treatment (ART) exposure and survival in two multicentre cohorts of HIV-positive subjects in Spain: CoRIS-MD and CoRIS. Competing risk regression models were used to assess gender effect on time to start ART and time to first ART change, and a Cox regression model to estimate gender effect on time to death. RESULTS Between January 1996 and December 2008, 1,953 women and 6,072 men naive to ART at study entry were included. The trend analysis over time showed the percentage of women in the younger (<20 years) and older (>50 years) strata increased significantly (P<0.001) from 0.5% and 1.8% in 1996 to 4.9% and 4.2% in 2008, respectively. By competing risk analysis women started ART earlier than men (adjusted subhazard ratio [ASHR] 1.21, 95% CI 1.11, 1.31) in CoRIS cohort, while in CoRIS-MD none of these differences were observed. In both cohorts women showed a shorter time to the first ART change (ASHR 1.10, 95% CI 1.01, 1.19). Pregnancy and patient's/physician's decisions as reasons for changing were more frequent in women than in men in CoRIS. In the Cox regression model, gender was not associated with differences in survival. CONCLUSIONS In two large cohorts in Spain, we observed relevant gender differences in epidemiological characteristics and antiretroviral exposure outcomes, while survival differences were not attributable to gender.

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Nanoparticles <100 nanometres are being introduced into industrial processes, but they are suspected to cause similar negative health effects to ambient particles. Poor knowledge about the scale of introduction has not allowed global risk analysis until now. In 2006 a targeted telephone survey among Swiss companies (1) showed the usage of nanoparticles in a few selected companies but did not provide data to extrapolate to the full Swiss workforce. The purpose of the study presented here was to provide a quantitative estimate of the potential occupational exposure to nanoparticles in Swiss industry. Method: A layered representative questionnaire survey among 1626 Swiss companies of the production sector was conducted in 2007. The survey was a written questionnaire, collecting data about the used nanoparticles, the number of potentially exposed persons in the companies and their protection strategy. Results: The response rate of the study was 58.3%. The number of companies estimated to be using nanoparticles in Switzerland was 586 (95% Confidence Interval 145 to 1027). It is estimated that 1309 workers (95% CI 1073 to 1545) do their job in the same room as a nanoparticle application. Personal protection was shown to be the predominant protection means. Such information is valuable for risk evaluation. The low number of companies dealing with nanoparticles in Switzerland suggests that policy makers as well as health, safety and environmental officers within companies can focus their efforts on a relatively small number of companies or workers. The collected data about types of particles and applications may be used for research on prevention strategies and adapted protection means. However, to reflect the most recent trends, the information presented here has to be continuously updated, and a large-scale inventory of the usage should be considered.

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Achieving a high degree of dependability in complex macro-systems is challenging. Because of the large number of components and numerous independent teams involved, an overview of the global system performance is usually lacking to support both design and operation adequately. A functional failure mode, effects and criticality analysis (FMECA) approach is proposed to address the dependability optimisation of large and complex systems. The basic inductive model FMECA has been enriched to include considerations such as operational procedures, alarm systems. environmental and human factors, as well as operation in degraded mode. Its implementation on a commercial software tool allows an active linking between the functional layers of the system and facilitates data processing and retrieval, which enables to contribute actively to the system optimisation. The proposed methodology has been applied to optimise dependability in a railway signalling system. Signalling systems are typical example of large complex systems made of multiple hierarchical layers. The proposed approach appears appropriate to assess the global risk- and availability-level of the system as well as to identify its vulnerabilities. This enriched-FMECA approach enables to overcome some of the limitations and pitfalls previously reported with classical FMECA approaches.

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Because of the increase in workplace automation and the diversification of industrial processes, workplaces have become more and more complex. The classical approaches used to address workplace hazard concerns, such as checklists or sequence models, are, therefore, of limited use in such complex systems. Moreover, because of the multifaceted nature of workplaces, the use of single-oriented methods, such as AEA (man oriented), FMEA (system oriented), or HAZOP (process oriented), is not satisfactory. The use of a dynamic modeling approach in order to allow multiple-oriented analyses may constitute an alternative to overcome this limitation. The qualitative modeling aspects of the MORM (man-machine occupational risk modeling) model are discussed in this article. The model, realized on an object-oriented Petri net tool (CO-OPN), has been developed to simulate and analyze industrial processes in an OH&S perspective. The industrial process is modeled as a set of interconnected subnets (state spaces), which describe its constitutive machines. Process-related factors are introduced, in an explicit way, through machine interconnections and flow properties. While man-machine interactions are modeled as triggering events for the state spaces of the machines, the CREAM cognitive behavior model is used in order to establish the relevant triggering events. In the CO-OPN formalism, the model is expressed as a set of interconnected CO-OPN objects defined over data types expressing the measure attached to the flow of entities transiting through the machines. Constraints on the measures assigned to these entities are used to determine the state changes in each machine. Interconnecting machines implies the composition of such flow and consequently the interconnection of the measure constraints. This is reflected by the construction of constraint enrichment hierarchies, which can be used for simulation and analysis optimization in a clear mathematical framework. The use of Petri nets to perform multiple-oriented analysis opens perspectives in the field of industrial risk management. It may significantly reduce the duration of the assessment process. But, most of all, it opens perspectives in the field of risk comparisons and integrated risk management. Moreover, because of the generic nature of the model and tool used, the same concepts and patterns may be used to model a wide range of systems and application fields.

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Summary: Use of microbiological risk analysis in the development of HACCP-systems in the food industry

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Manufactured nanoparticles are introduced into industrial processes, but they are suspected to cause similar negative health effects as ambient particles. The poor knowledge about the scale of this introduction did not allow global risk analysis so far. In 2006 a targeted telephone survey among Swiss companies (1) showed the usage of nanoparticles in a few selected companies but did not provide data to extrapolate on the totality of the Swiss workforce. To gain this kind of information a layered representative questionnaire survey among 1'626 Swiss companies was conducted in 2007. Data was collected about the number of potentially exposed persons in the companies and their protection strategy. The response rate was 58.3%. An expected number of 586 companies (95%−confidence interval 145 to 1'027) was shown by this study to use nanoparticles in Switzerland. Estimated 1'309 (1'073 to 1'545) workers do their job in the same room as a nanoparticle application. Personal protection was shown to be the predominant type of protection means. Companies starting productions with nanomaterials need to consider incorporating protection measures into the plans. This will not only benefit the workers' health, but will also likely increase the competitiveness of the companies. Technical and organisational protection means are not only more cost−effective on the long term, but are also easier to control. Guidelines may have to be designed specifically for different industrial applications, including fields outside nanotechnology, and adapted to all sizes of companies.

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Turvallisuuteen liittyvän ohjausjärjestelmän tehtävänä on siirtää ja käsitellä turvallisuuskriittistä tietoa. Esimerkiksi anturin (turvalaitteen) havaitessa vaaravyöhykkeelle pyrkivän ihmisen tulee ensimmäisenä tiedon välittyä ohjausjärjestelmään. Ohjausjärjestelmän on muodostettava saapuneen tiedon perusteella käsky tehonohjauselimille. Tehonohjauselimillä säädellään koneen käyttöenergian syöttöä ja sitä kautta on mahdollista pysäyttää koneen liike ennen mahdollisen vahingon sattumista. Perinteiset turvaratkaisut ovat perustuneet pakkotoimintaisiin releisiin ja kahdennuksiin. Tällämenetelmällä on toteutettu varmatoimintaisia turvaratkaisuja, joissa yksittäiset viat ovat paljastuneet. Nykyisin on kuitenkin yhä enemmän tarvetta integroida turvatoiminnot automaatiojärjestelmään ja toteuttaa turvaratkaisut hajautetuillajärjestelmillä. Hajautetut järjestelmät sisältävät osittain ohjelmoitavien järjestelmien etuja ja haittoja, mutta tuovat mukanaan myös uudenlaisia vikoja. Työn tarkoitus oli selvittää, millaisia rajoituksia koneturvallisuus asettaa paperiteollisuuden pituusleikkurien turvallisuuteen liittyville ohjausjärjestelmille, sekä selvittää turvallisuuteen liittyvien järjestelmien rakennetta ja ominaisuuksia. Tässä työssä tutkittiin AS-i, EsaLan ja ProfiSafe turvajärjestelmiä teknisten tietojen perusteella. Tutkitut järjestelmät ovat erilaisia ja soveltuvat tämän vuoksi hieman erilaisiin kohteisiin. Kaikilla näillä järjestelmillä on kuitenkin mahdollista toteuttaa pituusleikkurin turvaväyläjärjestelmässä riittävä turvallisuuden taso koneturvallisuuden näkökulmasta. Tämä edellyttää oikein tehtyä riskianalyysiä ja oikeita suunnittelumenetelmiä. Teknisten tietojen perusteella otettiin testattavaksi AS-i safety at workja EsaLan:in Compact järjestelmät, joille suoritettiin sähkömagneettiseen yhteensopivuuteen (EMC) ja toiminnallisuuteen liittyviä testejä.

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Diplomityön tavoitteena on luoda kokonaisvaltainen kuva sähkökaupassa esiintyvistä riskeistä ja niiden analysointi- sekä hallintamenetelmistä. Toinen päätavoitteista on lisätä ymmärrystä markkinoiden erikoispiirteistä, kuten siirtokapasiteettirajoituksista, kysynnän hintajouston puutteesta ja markkinoiden keskittyneisyydestä, sekä arvioida niiden merkitystä sähkökaupan riskienhallinnan näkökulmasta. Markkinoiden erikoispiirteet ja sähkön tuotantoon ja kulutukseen vaikuttavat fundamentaaliset tekijät aiheuttavat suuria muutoksia pörssisähkön hintatasossa. Sähkön volatiliteetti yhdessä useiden muiden riskitekijöiden kanssa aiheuttaa sähkökaupantoimijoille todellisen tarpeen riskienhallinnalle. Sähkökauppa tarjoaa haasteellisen toimintaympäristön riskienhallinnan näkökulmasta. Sähkökaupassa esiintyvien riskien täydellinen hallitseminen on miltei mahdoton tehtävä, mutta sähkökaupan toimintaympäristön tunteminen ja järjestelmällisesti toteutettu riskienhallinta luovat hyvät edellytykset menestyksekkäälle toiminnalle sähkökaupassa. Diplomityössä käsitellään sähkökaupassa esiintyviä riskejä ja niidensyntyyn vaikuttavia tekijöitä. Näiden asioiden ymmärtäminen luo pohjan sähkökaupan onnistuneelle riskienhallinnalle. Työssä käydään myös läpi yleisimmät sähkökaupassa käytetyt riskianalyysin menetelmät. Diplomityössä esitellään sähköpörssin tarjoamat johdannaistuotteet ja havainnollistetaan niiden käyttöä osana sähkökaupan riskienhallintaa. Työn lopussa käsitellään profiiliriskin muodostumista jasen vaikutuksia sähkön hankintakustannuksiin.