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Sample records for risk analysis model

  1. MATHEMATICAL RISK ANALYSIS: VIA NICHOLAS RISK MODEL AND BAYESIAN ANALYSIS

    Directory of Open Access Journals (Sweden)

    Anass BAYAGA

    2010-07-01

    Full Text Available The objective of this second part of a two-phased study was to explorethe predictive power of quantitative risk analysis (QRA method andprocess within Higher Education Institution (HEI. The method and process investigated the use impact analysis via Nicholas risk model and Bayesian analysis, with a sample of hundred (100 risk analysts in a historically black South African University in the greater Eastern Cape Province.The first findings supported and confirmed previous literature (KingIII report, 2009: Nicholas and Steyn, 2008: Stoney, 2007: COSA, 2004 that there was a direct relationship between risk factor, its likelihood and impact, certiris paribus. The second finding in relation to either controlling the likelihood or the impact of occurrence of risk (Nicholas risk model was that to have a brighter risk reward, it was important to control the likelihood ofoccurrence of risks as compared with its impact so to have a direct effect on entire University. On the Bayesian analysis, thus third finding, the impact of risk should be predicted along three aspects. These aspects included the human impact (decisions made, the property impact (students and infrastructural based and the business impact. Lastly, the study revealed that although in most business cases, where as business cycles considerably vary dependingon the industry and or the institution, this study revealed that, most impacts in HEI (University was within the period of one academic.The recommendation was that application of quantitative risk analysisshould be related to current legislative framework that affects HEI.

  2. Credit Risk Evaluation : Modeling - Analysis - Management

    OpenAIRE

    Wehrspohn, Uwe

    2002-01-01

    An analysis and further development of the building blocks of modern credit risk management: -Definitions of default -Estimation of default probabilities -Exposures -Recovery Rates -Pricing -Concepts of portfolio dependence -Time horizons for risk calculations -Quantification of portfolio risk -Estimation of risk measures -Portfolio analysis and portfolio improvement -Evaluation and comparison of credit risk models -Analytic portfolio loss distributions The thesis contributes to the evaluatio...

  3. Environmental modeling and health risk analysis (ACTS/RISK)

    National Research Council Canada - National Science Library

    Aral, M. M

    2010-01-01

    ... presents a review of the topics of exposure and health risk analysis. The Analytical Contaminant Transport Analysis System (ACTS) and Health RISK Analysis (RISK) software tools are an integral part of the book and provide computational platforms for all the models discussed herein. The most recent versions of these two softwa...

  4. Analysis of uncertainty in modeling perceived risks

    International Nuclear Information System (INIS)

    Melnyk, R.; Sandquist, G.M.

    2005-01-01

    Expanding on a mathematical model developed for quantifying and assessing perceived risks, the distribution functions, variances, and uncertainties associated with estimating the model parameters are quantified. The analytical model permits the identification and assignment of any number of quantifiable risk perception factors that can be incorporated within standard risk methodology. Those risk perception factors associated with major technical issues are modeled using lognormal probability density functions to span the potentially large uncertainty variations associated with these risk perceptions. The model quantifies the logic of public risk perception and provides an effective means for measuring and responding to perceived risks. (authors)

  5. Statistical models for competing risk analysis

    International Nuclear Information System (INIS)

    Sather, H.N.

    1976-08-01

    Research results on three new models for potential applications in competing risks problems. One section covers the basic statistical relationships underlying the subsequent competing risks model development. Another discusses the problem of comparing cause-specific risk structure by competing risks theory in two homogeneous populations, P1 and P2. Weibull models which allow more generality than the Berkson and Elveback models are studied for the effect of time on the hazard function. The use of concomitant information for modeling single-risk survival is extended to the multiple failure mode domain of competing risks. The model used to illustrate the use of this methodology is a life table model which has constant hazards within pre-designated intervals of the time scale. Two parametric models for bivariate dependent competing risks, which provide interesting alternatives, are proposed and examined

  6. Automating risk analysis of software design models.

    Science.gov (United States)

    Frydman, Maxime; Ruiz, Guifré; Heymann, Elisa; César, Eduardo; Miller, Barton P

    2014-01-01

    The growth of the internet and networked systems has exposed software to an increased amount of security threats. One of the responses from software developers to these threats is the introduction of security activities in the software development lifecycle. This paper describes an approach to reduce the need for costly human expertise to perform risk analysis in software, which is common in secure development methodologies, by automating threat modeling. Reducing the dependency on security experts aims at reducing the cost of secure development by allowing non-security-aware developers to apply secure development with little to no additional cost, making secure development more accessible. To automate threat modeling two data structures are introduced, identification trees and mitigation trees, to identify threats in software designs and advise mitigation techniques, while taking into account specification requirements and cost concerns. These are the components of our model for automated threat modeling, AutSEC. We validated AutSEC by implementing it in a tool based on data flow diagrams, from the Microsoft security development methodology, and applying it to VOMS, a grid middleware component, to evaluate our model's performance.

  7. Model risk analysis for risk management and option pricing

    NARCIS (Netherlands)

    Kerkhof, F.L.J.

    2003-01-01

    Due to the growing complexity of products in financial markets, market participants rely more and more on quantitative models for trading and risk management decisions. This introduces a fairly new type of risk, namely, model risk. In the first part of this thesis we investigate the quantitative

  8. Risk analysis: divergent models and convergent interpretations

    Science.gov (United States)

    Carnes, B. A.; Gavrilova, N.

    2001-01-01

    Material presented at a NASA-sponsored workshop on risk models for exposure conditions relevant to prolonged space flight are described in this paper. Analyses used mortality data from experiments conducted at Argonne National Laboratory on the long-term effects of external whole-body irradiation on B6CF1 mice by 60Co gamma rays and fission neutrons delivered as a single exposure or protracted over either 24 or 60 once-weekly exposures. The maximum dose considered was restricted to 1 Gy for neutrons and 10 Gy for gamma rays. Proportional hazard models were used to investigate the shape of the dose response at these lower doses for deaths caused by solid-tissue tumors and tumors of either connective or epithelial tissue origin. For protracted exposures, a significant mortality effect was detected at a neutron dose of 14 cGy and a gamma-ray dose of 3 Gy. For single exposures, radiation-induced mortality for neutrons also occurred within the range of 10-20 cGy, but dropped to 86 cGy for gamma rays. Plots of risk relative to control estimated for each observed dose gave a visual impression of nonlinearity for both neutrons and gamma rays. At least for solid-tissue tumors, male and female mortality was nearly identical for gamma-ray exposures, but mortality risks for females were higher than for males for neutron exposures. As expected, protracting the gamma-ray dose reduced mortality risks. Although curvature consistent with that observed visually could be detected by a model parameterized to detect curvature, a relative risk term containing only a simple term for total dose was usually sufficient to describe the dose response. Although detectable mortality for the three pathology end points considered typically occurred at the same level of dose, the highest risks were almost always associated with deaths caused by tumors of epithelial tissue origin.

  9. Modeling issues in nuclear plant fire risk analysis

    International Nuclear Information System (INIS)

    Siu, N.

    1989-01-01

    This paper discusses various issues associated with current models for analyzing the risk due to fires in nuclear power plants. Particular emphasis is placed on the fire growth and suppression models, these being unique to the fire portion of the overall risk analysis. Potentially significant modeling improvements are identified; also discussed are a variety of modeling issues where improvements will help the credibility of the analysis, without necessarily changing the computed risk significantly. The mechanistic modeling of fire initiation is identified as a particularly promising improvement for reducing the uncertainties in the predicted risk. 17 refs., 5 figs. 2 tabs

  10. Hierarchical Modelling of Flood Risk for Engineering Decision Analysis

    DEFF Research Database (Denmark)

    Custer, Rocco

    protection structures in the hierarchical flood protection system - is identified. To optimise the design of protection structures, fragility and vulnerability models must allow for consideration of decision alternatives. While such vulnerability models are available for large protection structures (e...... systems, as well as the implementation of the flood risk analysis methodology and the vulnerability modelling approach are illustrated with an example application. In summary, the present thesis provides a characterisation of hierarchical flood protection systems as well as several methodologies to model...... and robust. Traditional risk management solutions, e.g. dike construction, are not particularly flexible, as they are difficult to adapt to changing risk. Conversely, the recent concept of integrated flood risk management, entailing a combination of several structural and non-structural risk management...

  11. Tutorial: Parallel Computing of Simulation Models for Risk Analysis.

    Science.gov (United States)

    Reilly, Allison C; Staid, Andrea; Gao, Michael; Guikema, Seth D

    2016-10-01

    Simulation models are widely used in risk analysis to study the effects of uncertainties on outcomes of interest in complex problems. Often, these models are computationally complex and time consuming to run. This latter point may be at odds with time-sensitive evaluations or may limit the number of parameters that are considered. In this article, we give an introductory tutorial focused on parallelizing simulation code to better leverage modern computing hardware, enabling risk analysts to better utilize simulation-based methods for quantifying uncertainty in practice. This article is aimed primarily at risk analysts who use simulation methods but do not yet utilize parallelization to decrease the computational burden of these models. The discussion is focused on conceptual aspects of embarrassingly parallel computer code and software considerations. Two complementary examples are shown using the languages MATLAB and R. A brief discussion of hardware considerations is located in the Appendix. © 2016 Society for Risk Analysis.

  12. Sensitivity Analysis of Launch Vehicle Debris Risk Model

    Science.gov (United States)

    Gee, Ken; Lawrence, Scott L.

    2010-01-01

    As part of an analysis of the loss of crew risk associated with an ascent abort system for a manned launch vehicle, a model was developed to predict the impact risk of the debris resulting from an explosion of the launch vehicle on the crew module. The model consisted of a debris catalog describing the number, size and imparted velocity of each piece of debris, a method to compute the trajectories of the debris and a method to calculate the impact risk given the abort trajectory of the crew module. The model provided a point estimate of the strike probability as a function of the debris catalog, the time of abort and the delay time between the abort and destruction of the launch vehicle. A study was conducted to determine the sensitivity of the strike probability to the various model input parameters and to develop a response surface model for use in the sensitivity analysis of the overall ascent abort risk model. The results of the sensitivity analysis and the response surface model are presented in this paper.

  13. Source modelling in seismic risk analysis for nuclear power plants

    International Nuclear Information System (INIS)

    Yucemen, M.S.

    1978-12-01

    The proposed probabilistic procedure provides a consistent method for the modelling, analysis and updating of uncertainties that are involved in the seismic risk analysis for nuclear power plants. The potential earthquake activity zones are idealized as point, line or area sources. For these seismic source types, expressions to evaluate their contribution to seismic risk are derived, considering all the possible site-source configurations. The seismic risk at a site is found to depend not only on the inherent randomness of the earthquake occurrences with respect to magnitude, time and space, but also on the uncertainties associated with the predicted values of the seismic and geometric parameters, as well as the uncertainty in the attenuation model. The uncertainty due to the attenuation equation is incorporated into the analysis through the use of random correction factors. The influence of the uncertainty resulting from the insufficient information on the seismic parameters and source geometry is introduced into the analysis by computing a mean risk curve averaged over the various alternative assumptions on the parameters and source geometry. Seismic risk analysis is carried for the city of Denizli, which is located in the seismically most active zone of Turkey. The second analysis is for Akkuyu

  14. Integrating Household Risk Mitigation Behavior in Flood Risk Analysis: An Agent-Based Model Approach.

    Science.gov (United States)

    Haer, Toon; Botzen, W J Wouter; de Moel, Hans; Aerts, Jeroen C J H

    2017-10-01

    Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect of human adaptation leads to a misrepresentation of flood risk. This article presents an agent-based model that incorporates human decision making in flood risk analysis. In particular, household investments in loss-reducing measures are examined under three economic decision models: (1) expected utility theory, which is the traditional economic model of rational agents; (2) prospect theory, which takes account of bounded rationality; and (3) a prospect theory model, which accounts for changing risk perceptions and social interactions through a process of Bayesian updating. We show that neglecting human behavior in flood risk assessment studies can result in a considerable misestimation of future flood risk, which is in our case study an overestimation of a factor two. Furthermore, we show how behavior models can support flood risk analysis under different behavioral assumptions, illustrating the need to include the dynamic adaptive human behavior of, for instance, households, insurers, and governments. The method presented here provides a solid basis for exploring human behavior and the resulting flood risk with respect to low-probability/high-impact risks. © 2016 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

  15. Gambler Risk Perception: A Mental Model and Grounded Theory Analysis.

    Science.gov (United States)

    Spurrier, Michael; Blaszczynski, Alexander; Rhodes, Paul

    2015-09-01

    Few studies have investigated how gamblers perceive risk or the role of risk perception in disordered gambling. The purpose of the current study therefore was to obtain data on lay gamblers' beliefs on these variables and their effects on decision-making, behaviour, and disordered gambling aetiology. Fifteen regular lay gamblers (non-problem/low risk, moderate risk and problem gamblers) completed a semi-structured interview following mental models and grounded theory methodologies. Gambler interview data was compared to an expert 'map' of risk-perception, to identify comparative gaps or differences associated with harmful or safe gambling. Systematic overlapping processes of data gathering and analysis were used to iteratively extend, saturate, test for exception, and verify concepts and themes emerging from the data. The preliminary findings suggested that gambler accounts supported the presence of expert conceptual constructs, and to some degree the role of risk perception in protecting against or increasing vulnerability to harm and disordered gambling. Gambler accounts of causality, meaning, motivation, and strategy were highly idiosyncratic, and often contained content inconsistent with measures of disordered gambling. Disordered gambling appears heavily influenced by relative underestimation of risk and overvaluation of gambling, based on explicit and implicit analysis, and deliberate, innate, contextual, and learned processing evaluations and biases.

  16. Advanced uncertainty modelling for container port risk analysis.

    Science.gov (United States)

    Alyami, Hani; Yang, Zaili; Riahi, Ramin; Bonsall, Stephen; Wang, Jin

    2016-08-13

    Globalization has led to a rapid increase of container movements in seaports. Risks in seaports need to be appropriately addressed to ensure economic wealth, operational efficiency, and personnel safety. As a result, the safety performance of a Container Terminal Operational System (CTOS) plays a growing role in improving the efficiency of international trade. This paper proposes a novel method to facilitate the application of Failure Mode and Effects Analysis (FMEA) in assessing the safety performance of CTOS. The new approach is developed through incorporating a Fuzzy Rule-Based Bayesian Network (FRBN) with Evidential Reasoning (ER) in a complementary manner. The former provides a realistic and flexible method to describe input failure information for risk estimates of individual hazardous events (HEs) at the bottom level of a risk analysis hierarchy. The latter is used to aggregate HEs safety estimates collectively, allowing dynamic risk-based decision support in CTOS from a systematic perspective. The novel feature of the proposed method, compared to those in traditional port risk analysis lies in a dynamic model capable of dealing with continually changing operational conditions in ports. More importantly, a new sensitivity analysis method is developed and carried out to rank the HEs by taking into account their specific risk estimations (locally) and their Risk Influence (RI) to a port's safety system (globally). Due to its generality, the new approach can be tailored for a wide range of applications in different safety and reliability engineering and management systems, particularly when real time risk ranking is required to measure, predict, and improve the associated system safety performance. Copyright © 2016 Elsevier Ltd. All rights reserved.

  17. Risk analysis

    International Nuclear Information System (INIS)

    Baron, J.H.; Nunez McLeod, J.; Rivera, S.S.

    1997-01-01

    This book contains a selection of research works performed in the CEDIAC Institute (Cuyo National University) in the area of Risk Analysis, with specific orientations to the subjects of uncertainty and sensitivity studies, software reliability, severe accident modeling, etc. This volume presents important material for all those researches who want to have an insight in the risk analysis field, as a tool to solution several problems frequently found in the engineering and applied sciences field, as well as for the academic teachers who want to keep up to date, including the new developments and improvements continuously arising in this field [es

  18. Empirical Analysis of Farm Credit Risk under the Structure Model

    Science.gov (United States)

    Yan, Yan

    2009-01-01

    The study measures farm credit risk by using farm records collected by Farm Business Farm Management (FBFM) during the period 1995-2004. The study addresses the following questions: (1) whether farm's financial position is fully described by the structure model, (2) what are the determinants of farm capital structure under the structure model, (3)…

  19. A Graphical Adversarial Risk Analysis Model for Oil and Gas Drilling Cybersecurity

    OpenAIRE

    Vieira, Aitor Couce; Houmb, Siv Hilde; Insua, David Rios

    2014-01-01

    Oil and gas drilling is based, increasingly, on operational technology, whose cybersecurity is complicated by several challenges. We propose a graphical model for cybersecurity risk assessment based on Adversarial Risk Analysis to face those challenges. We also provide an example of the model in the context of an offshore drilling rig. The proposed model provides a more formal and comprehensive analysis of risks, still using the standard business language based on decisions, risks, and value.

  20. A Graphical Adversarial Risk Analysis Model for Oil and Gas Drilling Cybersecurity

    Directory of Open Access Journals (Sweden)

    Aitor Couce Vieira

    2014-04-01

    Full Text Available Oil and gas drilling is based, increasingly, on operational technology, whose cybersecurity is complicated by several challenges. We propose a graphical model for cybersecurity risk assessment based on Adversarial Risk Analysis to face those challenges. We also provide an example of the model in the context of an offshore drilling rig. The proposed model provides a more formal and comprehensive analysis of risks, still using the standard business language based on decisions, risks, and value.

  1. Credit Risk Analysis using Machine and Deep Learning models

    OpenAIRE

    Addo , Peter ,; Guegan , Dominique; Hassani , Bertrand

    2018-01-01

    URL des Documents de travail : https://centredeconomiesorbonne.univ-paris1.fr/documents-de-travail-du-ces/; Documents de travail du Centre d'Economie de la Sorbonne 2018.03 - ISSN : 1955-611X; Due to the hyper technology associated to Big Data, data availability and computing power, most banks or lending financial institutions are renewing their business models. Credit risk predictions, monitoring, model reliability and effective loan processing are key to decision making and transparency. In...

  2. Credit Risk Analysis Using Machine and Deep Learning Models

    Directory of Open Access Journals (Sweden)

    Peter Martey Addo

    2018-04-01

    Full Text Available Due to the advanced technology associated with Big Data, data availability and computing power, most banks or lending institutions are renewing their business models. Credit risk predictions, monitoring, model reliability and effective loan processing are key to decision-making and transparency. In this work, we build binary classifiers based on machine and deep learning models on real data in predicting loan default probability. The top 10 important features from these models are selected and then used in the modeling process to test the stability of binary classifiers by comparing their performance on separate data. We observe that the tree-based models are more stable than the models based on multilayer artificial neural networks. This opens several questions relative to the intensive use of deep learning systems in enterprises.

  3. A suite of models to support the quantitative assessment of spread in pest risk analysis

    NARCIS (Netherlands)

    Robinet, C.; Kehlenbeck, H.; Werf, van der W.

    2012-01-01

    In the frame of the EU project PRATIQUE (KBBE-2007-212459 Enhancements of pest risk analysis techniques) a suite of models was developed to support the quantitative assessment of spread in pest risk analysis. This dataset contains the model codes (R language) for the four models in the suite. Three

  4. Regime switching model for financial data: Empirical risk analysis

    Science.gov (United States)

    Salhi, Khaled; Deaconu, Madalina; Lejay, Antoine; Champagnat, Nicolas; Navet, Nicolas

    2016-11-01

    This paper constructs a regime switching model for the univariate Value-at-Risk estimation. Extreme value theory (EVT) and hidden Markov models (HMM) are combined to estimate a hybrid model that takes volatility clustering into account. In the first stage, HMM is used to classify data in crisis and steady periods, while in the second stage, EVT is applied to the previously classified data to rub out the delay between regime switching and their detection. This new model is applied to prices of numerous stocks exchanged on NYSE Euronext Paris over the period 2001-2011. We focus on daily returns for which calibration has to be done on a small dataset. The relative performance of the regime switching model is benchmarked against other well-known modeling techniques, such as stable, power laws and GARCH models. The empirical results show that the regime switching model increases predictive performance of financial forecasting according to the number of violations and tail-loss tests. This suggests that the regime switching model is a robust forecasting variant of power laws model while remaining practical to implement the VaR measurement.

  5. Sensitivity Analysis of the Bone Fracture Risk Model

    Science.gov (United States)

    Lewandowski, Beth; Myers, Jerry; Sibonga, Jean Diane

    2017-01-01

    Introduction: The probability of bone fracture during and after spaceflight is quantified to aid in mission planning, to determine required astronaut fitness standards and training requirements and to inform countermeasure research and design. Probability is quantified with a probabilistic modeling approach where distributions of model parameter values, instead of single deterministic values, capture the parameter variability within the astronaut population and fracture predictions are probability distributions with a mean value and an associated uncertainty. Because of this uncertainty, the model in its current state cannot discern an effect of countermeasures on fracture probability, for example between use and non-use of bisphosphonates or between spaceflight exercise performed with the Advanced Resistive Exercise Device (ARED) or on devices prior to installation of ARED on the International Space Station. This is thought to be due to the inability to measure key contributors to bone strength, for example, geometry and volumetric distributions of bone mass, with areal bone mineral density (BMD) measurement techniques. To further the applicability of model, we performed a parameter sensitivity study aimed at identifying those parameter uncertainties that most effect the model forecasts in order to determine what areas of the model needed enhancements for reducing uncertainty. Methods: The bone fracture risk model (BFxRM), originally published in (Nelson et al) is a probabilistic model that can assess the risk of astronaut bone fracture. This is accomplished by utilizing biomechanical models to assess the applied loads; utilizing models of spaceflight BMD loss in at-risk skeletal locations; quantifying bone strength through a relationship between areal BMD and bone failure load; and relating fracture risk index (FRI), the ratio of applied load to bone strength, to fracture probability. There are many factors associated with these calculations including

  6. The Impact of Consumer Phase Models in Microbial Risk Analysis

    DEFF Research Database (Denmark)

    Nauta, Maarten; Christensen, Bjarke Bak

    2011-01-01

    In quantitative microbiological risk assessment (QMRA), the consumer phase model (CPM) describes the part of the food chain between purchase of the food product at retail and exposure. Construction of a CPM is complicated by the large variation in consumer food handling practices and a limited...... availability of data. Therefore, several subjective (simplifying) assumptions have to be made when a CPM is constructed, but with a single CPM their impact on the QMRA results is unclear. We therefore compared the performance of eight published CPMs for Campylobacter in broiler meat in an example of a QMRA......, where all the CPMs were analyzed using one single input distribution of concentrations at retail, and the same dose-response relationship. It was found that, between CPMs, there may be a considerable difference in the estimated probability of illness per serving. However, the estimated relative risk...

  7. Foundations of Risk Analysis

    CERN Document Server

    Aven, Terje

    2012-01-01

    Foundations of Risk Analysis presents the issues core to risk analysis - understanding what risk means, expressing risk, building risk models, addressing uncertainty, and applying probability models to real problems. The author provides the readers with the knowledge and basic thinking they require to successfully manage risk and uncertainty to support decision making. This updated edition reflects recent developments on risk and uncertainty concepts, representations and treatment. New material in Foundations of Risk Analysis includes:An up to date presentation of how to understand, define and

  8. Application of wildfire simulation models for risk analysis

    Science.gov (United States)

    Ager, A.; Finney, M.

    2009-04-01

    Wildfire simulation models are being widely used by fire and fuels specialists in the U.S. to support tactical and strategic decisions related to the mitigation of wildfire risk. Much of this application has resulted from the development of a minimum travel time (MTT) fire spread algorithm (M. Finney) that makes it computationally feasible to simulate thousands of fires and generate burn probability and intensity maps over large areas (10,000 - 2,000,000 ha). The MTT algorithm is parallelized for multi-threaded processing and is imbedded in a number of research and applied fire modeling applications. High performance computers (e.g., 32-way 64 bit SMP) are typically used for MTT simulations, although the algorithm is also implemented in the 32 bit desktop FlamMap3 program (www.fire.org). Extensive testing has shown that this algorithm can replicate large fire boundaries in the heterogeneous landscapes that typify much of the wildlands in the western U.S. In this paper, we describe the application of the MTT algorithm to understand spatial patterns of burn probability (BP), and to analyze wildfire risk to key human and ecological values. The work is focused on a federally-managed 2,000,000 ha landscape in the central interior region of Oregon State, USA. The fire-prone study area encompasses a wide array of topography and fuel types and a number of highly valued resources that are susceptible to fire. We quantitatively defined risk as the product of the probability of a fire and the resulting consequence. Burn probabilities at specific intensity classes were estimated for each 100 x 100 m pixel by simulating 100,000 wildfires under burn conditions that replicated recent severe wildfire events that occurred under conditions where fire suppression was generally ineffective (97th percentile, August weather). We repeated the simulation under milder weather (70th percentile, August weather) to replicate a "wildland fire use scenario" where suppression is minimized to

  9. Complications from arteriovenous malformation radiosurgery: multivariate analysis and risk modeling

    International Nuclear Information System (INIS)

    Flickinger, John C.; Kondziolka, Douglas; Pollock, Bruce E.; Maitz, Ann H.; Lunsford, L. Dade

    1997-01-01

    Purpose/Objective: To assess the relationships of radiosurgery treatment parameters to the development of complications from radiosurgery for arteriovenous malformations (AVM). Methods and Materials: We evaluated follow-up imaging and clinical data in 307 AVM patients who received gamma knife radiosurgery at the University of Pittsburgh between 1987 and 1993. All patients had regular clinical or imaging follow up for a minimum of 2 years (range: 24-96 months, median = 44 months). Results: Post-radiosurgical imaging (PRI) changes developed in 30.5% of patients with regular follow-up magnetic resonance imaging, and were symptomatic in 10.7% of all patients at 7 years. PRI changes resolved within 3 years developed significantly less often (p = 0.0274) in patients with symptoms (52.8%) compared to asymptomatic patients (94.8%). The 7-year actuarial rate for developing persistent symptomatic PRI changes was 5.05%. Multivariate logistic regression modeling found that the 12 Gy volume was the only independent variable that correlated significantly with PRI changes (p < 0.0001) while symptomatic PRI changes were correlated with both 12 Gy volume (p = 0.0013) and AVM location (p 0.0066). Conclusion: Complications from AVM radiosurgery can be predicted with a statistical model relating the risks of developing symptomatic post-radiosurgical imaging changes to 12 Gy treatment volume and location

  10. Transmission risk assessment of invasive fluke Fascioloides magna using GIS-modelling and multicriteria analysis methods

    Directory of Open Access Journals (Sweden)

    Juhásová L.

    2017-06-01

    Full Text Available The combination of multicriteria analysis (MCA, particularly analytic hierarchy process (AHP and geographic information system (GIS were applied for transmission risk assessment of Fascioloides magna (Trematoda; Fasciolidae in south-western Slovakia. Based on the details on F. magna life cycle, the following risk factors (RF of parasite transmission were determined: intermediate (RFIH and final hosts (RFFH (biological factors, annual precipitation (RFAP, land use (RFLU, flooded area (RFFA, and annual mean air temperature (RFAT (environmental factors. Two types of risk analyses were modelled: (1 potential risk analysis was focused on the determination of the potential risk of parasite transmission into novel territories (data on F. magna occurrence were excluded; (2 actual risk analysis considered also the summary data on F. magna occurrence in the model region (risk factor parasite occurrence RFPO included in the analysis. The results of the potential risk analysis provided novel distribution pattern and revealed new geographical area as the potential risk zone of F. magna occurrence. Although the actual risk analysis revealed all four risk zones of F. magna transmission (acceptable, moderate, undesirable and unacceptable, its outputs were significantly affected by the data on parasite occurrence what reduced the informative value of the actual transmission risk assessment.

  11. Cyber Risk Management for Critical Infrastructure: A Risk Analysis Model and Three Case Studies.

    Science.gov (United States)

    Paté-Cornell, M-Elisabeth; Kuypers, Marshall; Smith, Matthew; Keller, Philip

    2018-02-01

    Managing cyber security in an organization involves allocating the protection budget across a spectrum of possible options. This requires assessing the benefits and the costs of these options. The risk analyses presented here are statistical when relevant data are available, and system-based for high-consequence events that have not happened yet. This article presents, first, a general probabilistic risk analysis framework for cyber security in an organization to be specified. It then describes three examples of forward-looking analyses motivated by recent cyber attacks. The first one is the statistical analysis of an actual database, extended at the upper end of the loss distribution by a Bayesian analysis of possible, high-consequence attack scenarios that may happen in the future. The second is a systems analysis of cyber risks for a smart, connected electric grid, showing that there is an optimal level of connectivity. The third is an analysis of sequential decisions to upgrade the software of an existing cyber security system or to adopt a new one to stay ahead of adversaries trying to find their way in. The results are distributions of losses to cyber attacks, with and without some considered countermeasures in support of risk management decisions based both on past data and anticipated incidents. © 2017 Society for Risk Analysis.

  12. Observations on risk analysis

    International Nuclear Information System (INIS)

    Thompson, W.A. Jr.

    1979-11-01

    This paper briefly describes WASH 1400 and the Lewis report. It attempts to define basic concepts such as risk and risk analysis, common mode failure, and rare event. Several probabilistic models which go beyond the WASH 1400 methodology are introduced; the common characteristic of these models is that they recognize explicitly that risk analysis is time dependent whereas WASH 1400 takes a per demand failure rate approach which obscures the important fact that accidents are time related. Further, the presentation of a realistic risk analysis should recognize that there are various risks which compete with one another for the lives of the individuals at risk. A way of doing this is suggested

  13. A societal risk analysis model for nuclear power plants

    International Nuclear Information System (INIS)

    Klopp, George T.

    2004-01-01

    A review of the last decade and a half reveals that the nuclear power industry, world wide, has devoted increased attention to the concepts of reactor risk, probabilistic risk assessment (PRA), and cost benefit analyses. Millions of dollars have been spent by the industry and by regulatory agencies on studies of specific plants, research into severe accident behavior, and the development of national risk goals. In the United States, there is a major effort underway to evaluate each operating nuclear plant using PRA and the latest information on severe accident behavior. This effort constitutes a search for 'outliers' or vulnerabilities which may be profitably addressed by changes to plant design or operation. The question, then, immediately arises: How much is it reasonable to spend on this particular 'outlier?' The answer to this question, in each case, calls for some systematic vehicle for evaluating the worth of risk reduction. In turn, this calls for some means to look at all aspects of risk using a common yardstick or unit of measure. A review of past practices in such evaluations leads one directly to the classical cost benefit analyses which rarely use any guideline more comprehensive than the old $1000 per person-rem. The real costs of the TMI accident point to a need for a more realistic treatment. The BoPhal accident, the Chernobyl accident, and the Exxon Valdez accident highlight risk aspects previously not explored in detail and further support the postulate that a better method is mandated by history

  14. Enterprise Architecture-Based Risk and Security Modelling and Analysis

    NARCIS (Netherlands)

    Jonkers, Henk; Quartel, Dick; Kordy, Barbara; Ekstedt, Mathias; Seong Kim, Deng

    2016-01-01

    The growing complexity of organizations and the increasing number of sophisticated cyber attacks asks for a systematic and integral approach to Enterprise Risk and Security Management (ERSM). As enterprise architecture offers the necessary integral perspective, including the business and IT aspects

  15. P2P Lending Risk Contagion Analysis Based on a Complex Network Model

    Directory of Open Access Journals (Sweden)

    Qi Wei

    2016-01-01

    Full Text Available This paper analyzes two major channels of P2P lending risk contagion in China—direct risk contagion between platforms and indirect risk contagion with other financial organizations as the contagion medium. Based on this analysis, the current study constructs a complex network model of P2P lending risk contagion in China and performs dynamics analogue simulations in order to analyze general characteristics of direct risk contagion among China’s online P2P lending platforms. The assumed conditions are that other financial organizations act as the contagion medium, with variations in the risk contagion characteristics set under the condition of significant information asymmetry in Internet lending. It is indicated that, compared to direct risk contagion among platforms, both financial organizations acting as the contagion medium and information asymmetry magnify the effect of risk contagion. It is also found that the superposition of media effects and information asymmetry is more likely to magnify the risk contagion effect.

  16. Risk-based systems analysis for emerging technologies: Applications of a technology risk assessment model to public decision making

    International Nuclear Information System (INIS)

    Quadrel, M.J.; Fowler, K.M.; Cameron, R.; Treat, R.J.; McCormack, W.D.; Cruse, J.

    1995-01-01

    The risk-based systems analysis model was designed to establish funding priorities among competing technologies for tank waste remediation. The model addresses a gap in the Department of Energy's (DOE's) ''toolkit'' for establishing funding priorities among emerging technologies by providing disciplined risk and cost assessments of candidate technologies within the context of a complete remediation system. The model is comprised of a risk and cost assessment and a decision interface. The former assesses the potential reductions in risk and cost offered by new technology relative to the baseline risk and cost of an entire system. The latter places this critical information in context of other values articulated by decision makers and stakeholders in the DOE system. The risk assessment portion of the model is demonstrated for two candidate technologies for tank waste retrieval (arm-based mechanical retrieval -- the ''long reach arm'') and subsurface barriers (close-coupled chemical barriers). Relative changes from the base case in cost and risk are presented for these two technologies to illustrate how the model works. The model and associated software build on previous work performed for DOE's Office of Technology Development and the former Underground Storage Tank Integrated Demonstration, and complement a decision making tool presented at Waste Management 1994 for integrating technical judgements and non-technical (stakeholder) values when making technology funding decisions

  17. Modelling and mapping spread in pest risk analysis: a generic approach

    NARCIS (Netherlands)

    Kehlenbeck, H.; Robinet, C.; Werf, van der W.; Kriticos, D.; Reynaud, P.; Baker, R.

    2012-01-01

    Assessing the likelihood and magnitude of spread is one of the cornerstones of pest risk analysis (PRA), and is usually based on qualitative expert judgment. This paper proposes a suite of simple ecological models to support risk assessors who also wish to estimate the rate and extent of spread,

  18. Terrorism Risk Modeling for Intelligence Analysis and Infrastructure Protection

    National Research Council Canada - National Science Library

    Willis, Henry H; LaTourrette, Tom; Kelly, Terrence K; Hickey, Scot; Neill, Samuel

    2007-01-01

    ...? The Office of Intelligence and Analysis (OI&A) at DHS is responsible for using information and intelligence from multiple sources to identify and assess current and future threats to the United States...

  19. A new approach to hazardous materials transportation risk analysis: decision modeling to identify critical variables.

    Science.gov (United States)

    Clark, Renee M; Besterfield-Sacre, Mary E

    2009-03-01

    We take a novel approach to analyzing hazardous materials transportation risk in this research. Previous studies analyzed this risk from an operations research (OR) or quantitative risk assessment (QRA) perspective by minimizing or calculating risk along a transport route. Further, even though the majority of incidents occur when containers are unloaded, the research has not focused on transportation-related activities, including container loading and unloading. In this work, we developed a decision model of a hazardous materials release during unloading using actual data and an exploratory data modeling approach. Previous studies have had a theoretical perspective in terms of identifying and advancing the key variables related to this risk, and there has not been a focus on probability and statistics-based approaches for doing this. Our decision model empirically identifies the critical variables using an exploratory methodology for a large, highly categorical database involving latent class analysis (LCA), loglinear modeling, and Bayesian networking. Our model identified the most influential variables and countermeasures for two consequences of a hazmat incident, dollar loss and release quantity, and is one of the first models to do this. The most influential variables were found to be related to the failure of the container. In addition to analyzing hazmat risk, our methodology can be used to develop data-driven models for strategic decision making in other domains involving risk.

  20. Risk analysis

    International Nuclear Information System (INIS)

    Correa Lizarazu, X.

    2013-01-01

    The power point presentation Colombia risk evaluation experiences, sanitarian regulations evolution, chemical dangers food, biological dangers food, codex alimentarius, trade, industrial effects, dangers identification, data collection and risk profile

  1. RACLOUDS - Model for Clouds Risk Analysis in the Information Assets Context

    Directory of Open Access Journals (Sweden)

    SILVA, P. F.

    2016-06-01

    Full Text Available Cloud computing offers benefits in terms of availability and cost, but transfers the responsibility of information security management for the cloud service provider. Thus the consumer loses control over the security of their information and services. This factor has prevented the migration to cloud computing in many businesses. This paper proposes a model where the cloud consumer can perform risk analysis on providers before and after contracting the service. The proposed model establishes the responsibilities of three actors: Consumer, Provider and Security Labs. The inclusion of actor Security Labs provides more credibility to risk analysis making the results more consistent for the consumer.

  2. Application of adversarial risk analysis model in pricing strategies with remanufacturing

    Directory of Open Access Journals (Sweden)

    Liurui Deng

    2015-01-01

    Full Text Available Purpose: Purpose: This paper mainly focus on the application of adversarial risk analysis (ARA in pricing strategy with remanufacturing. We hope to obtain more realistic results than classical model. Moreover, we also wish that our research improve the development of ARA in pricing strategy of manufacturing or remanufacturing. Approach: In order to gain more actual research, combining adversarial risk analysis, we explore the pricing strategy with remanufacturing based on Stackelberg model. Especially, we build OEM’s 1-order ARA model and further study on manufacturers and remanufacturers’ pricing strategy. Findings: We find the OEM’s 1-order ARA model for the OEM’s product cost C. Besides, we get according manufacturers and remanufacturers’ pricing strategies. Besides, the pricing strategies based on 1-order ARA model have advantage over than the classical model regardless of OEMs and remanufacturers. Research implications: The research on application of ARA imply that we can get more actual results with this kind of modern risk analysis method and ARA can be extensively in pricing strategies of supply chain. Value: Our research improves the application of ARA in remanufacturing industry. Meanwhile, inspired by this analysis, we can also create different ARA models for different parameters. Furthermore, some results and analysis methods can be applied to other pricing strategies of supply chain.

  3. Competing risk models in reliability systems, a Weibull distribution model with Bayesian analysis approach

    International Nuclear Information System (INIS)

    Iskandar, Ismed; Gondokaryono, Yudi Satria

    2016-01-01

    In reliability theory, the most important problem is to determine the reliability of a complex system from the reliability of its components. The weakness of most reliability theories is that the systems are described and explained as simply functioning or failed. In many real situations, the failures may be from many causes depending upon the age and the environment of the system and its components. Another problem in reliability theory is one of estimating the parameters of the assumed failure models. The estimation may be based on data collected over censored or uncensored life tests. In many reliability problems, the failure data are simply quantitatively inadequate, especially in engineering design and maintenance system. The Bayesian analyses are more beneficial than the classical one in such cases. The Bayesian estimation analyses allow us to combine past knowledge or experience in the form of an apriori distribution with life test data to make inferences of the parameter of interest. In this paper, we have investigated the application of the Bayesian estimation analyses to competing risk systems. The cases are limited to the models with independent causes of failure by using the Weibull distribution as our model. A simulation is conducted for this distribution with the objectives of verifying the models and the estimators and investigating the performance of the estimators for varying sample size. The simulation data are analyzed by using Bayesian and the maximum likelihood analyses. The simulation results show that the change of the true of parameter relatively to another will change the value of standard deviation in an opposite direction. For a perfect information on the prior distribution, the estimation methods of the Bayesian analyses are better than those of the maximum likelihood. The sensitivity analyses show some amount of sensitivity over the shifts of the prior locations. They also show the robustness of the Bayesian analysis within the range

  4. Assessing scenario and parametric uncertainties in risk analysis: a model uncertainty audit

    International Nuclear Information System (INIS)

    Tarantola, S.; Saltelli, A.; Draper, D.

    1999-01-01

    In the present study a process of model audit is addressed on a computational model used for predicting maximum radiological doses to humans in the field of nuclear waste disposal. Global uncertainty and sensitivity analyses are employed to assess output uncertainty and to quantify the contribution of parametric and scenario uncertainties to the model output. These tools are of fundamental importance for risk analysis and decision making purposes

  5. ANALYSIS MODELS OF THE BANKRUPTCY RISK IN ROMANIA’S ENERGY SECTOR

    Directory of Open Access Journals (Sweden)

    MIRON VASILE CRISTIAN IOACHIM

    2015-12-01

    Full Text Available The risk, as a concept found in the economic sphere of business represents an analysis area often approached by researchers from the finance and accounting field. Although it is often seen, along with cost-effectiveness and value, as a fundamental element of finance (Stancu, I., 2007, the risk has often facets that make it useful also in analyzing other sides of the economic sphere of business, such as financial position and economic performance of it. From these meanings, we believe that the most suitable for this purpose is the one through which it is analyzed the ability of an entity to avoid bankruptcy. The present study has as main objectives the presentation of bankruptcy risk of an entity from a theoretical point of view and the analysis (from an empirical and comparative point of view through the scoring method of the implementation of various models for analyzing the risk of bankruptcy (Altman, Conan-holder, Taffler, Robertson in Romania’s energy sector, in order to issue an opinion regarding the optimal method for analyzing the bankruptcy risk in the energy sector. The results show that there are significant differences regarding the analysis of the bankruptcy risk through the appliction of different models, proposing the Conan-Holder model as the most appropriate for this sector.

  6. A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis

    NARCIS (Netherlands)

    Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L.; Postmus, Douwe

    2011-01-01

    Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multicriteria model that fully takes into account the evidence on efficacy and adverse drug

  7. A state-of-the-art multi-criteria model for drug benefit-risk analysis

    NARCIS (Netherlands)

    Tervonen, T.; Hillege, H.L.; Buskens, E.; Postmus, D.

    2010-01-01

    Drug benefit-risk analysis is based on firm clinical evidence related to various safety and efficacy outcomes, such as tolerability, treatment response, and adverse events. In this paper, we propose a new approach for constructing a supporting multi-criteria model that fully takes into account this

  8. A threat-vulnerability based risk analysis model for cyber physical system security

    CSIR Research Space (South Africa)

    Ledwaba, Lehlogonolo

    2017-01-01

    Full Text Available model. An analysis of the Natanz system shows that, with an actual case security-risk score at Mitigation level 5, the infested facilities barely avoided a situation worse than the one which occurred. The paper concludes with a discussion on the need...

  9. A model of pathways to artificial superintelligence catastrophe for risk and decision analysis

    Science.gov (United States)

    Barrett, Anthony M.; Baum, Seth D.

    2017-03-01

    An artificial superintelligence (ASI) is an artificial intelligence that is significantly more intelligent than humans in all respects. Whilst ASI does not currently exist, some scholars propose that it could be created sometime in the future, and furthermore that its creation could cause a severe global catastrophe, possibly even resulting in human extinction. Given the high stakes, it is important to analyze ASI risk and factor the risk into decisions related to ASI research and development. This paper presents a graphical model of major pathways to ASI catastrophe, focusing on ASI created via recursive self-improvement. The model uses the established risk and decision analysis modelling paradigms of fault trees and influence diagrams in order to depict combinations of events and conditions that could lead to AI catastrophe, as well as intervention options that could decrease risks. The events and conditions include select aspects of the ASI itself as well as the human process of ASI research, development and management. Model structure is derived from published literature on ASI risk. The model offers a foundation for rigorous quantitative evaluation and decision-making on the long-term risk of ASI catastrophe.

  10. APPLICATION OF IMPRECISE MODELS IN ANALYSIS OF RISK MANAGEMENT OF SOFTWARE SYSTEMS

    Directory of Open Access Journals (Sweden)

    Volodymyr Kharchenko

    2017-11-01

    Full Text Available The analysis of functional completeness for existing detection systems was conducted. It made it possible to define information systems with a similar feature set, to assess the degree of similarity and the matching degree of the means from the "standard" model of risk management system, that considers the recommended ICAO practices and standards on aviation safety, to justify the advisability of decision-making support system creation, using imprecise model and imprecise logic for risk analysis at aviation activities. Imprecise models have a number of features regarding the possibility of taking into account the experts’ intuition and experience, the possibility of more adequate flight safety management processes modelling and obtaining the accurate decisions that correlate with the initial data; support for the rapid development of a safety management system with its further functionality complexity increase; their hardware and software implementation in control systems and decision making is less sophisticated in comparison with classical algorithms.

  11. Is risk analysis scientific?

    Science.gov (United States)

    Hansson, Sven Ove; Aven, Terje

    2014-07-01

    This article discusses to what extent risk analysis is scientific in view of a set of commonly used definitions and criteria. We consider scientific knowledge to be characterized by its subject matter, its success in developing the best available knowledge in its fields of study, and the epistemic norms and values that guide scientific investigations. We proceed to assess the field of risk analysis according to these criteria. For this purpose, we use a model for risk analysis in which science is used as a base for decision making on risks, which covers the five elements evidence, knowledge base, broad risk evaluation, managerial review and judgment, and the decision; and that relates these elements to the domains experts and decisionmakers, and to the domains fact-based or value-based. We conclude that risk analysis is a scientific field of study, when understood as consisting primarily of (i) knowledge about risk-related phenomena, processes, events, etc., and (ii) concepts, theories, frameworks, approaches, principles, methods and models to understand, assess, characterize, communicate, and manage risk, in general and for specific applications (the instrumental part). © 2014 Society for Risk Analysis.

  12. Risk analysis of gravity dam instability using credibility theory Monte Carlo simulation model.

    Science.gov (United States)

    Xin, Cao; Chongshi, Gu

    2016-01-01

    Risk analysis of gravity dam stability involves complicated uncertainty in many design parameters and measured data. Stability failure risk ratio described jointly by probability and possibility has deficiency in characterization of influence of fuzzy factors and representation of the likelihood of risk occurrence in practical engineering. In this article, credibility theory is applied into stability failure risk analysis of gravity dam. Stability of gravity dam is viewed as a hybrid event considering both fuzziness and randomness of failure criterion, design parameters and measured data. Credibility distribution function is conducted as a novel way to represent uncertainty of influence factors of gravity dam stability. And combining with Monte Carlo simulation, corresponding calculation method and procedure are proposed. Based on a dam section, a detailed application of the modeling approach on risk calculation of both dam foundation and double sliding surfaces is provided. The results show that, the present method is feasible to be applied on analysis of stability failure risk for gravity dams. The risk assessment obtained can reflect influence of both sorts of uncertainty, and is suitable as an index value.

  13. Risk assessment model for nuclear accident emergency protection countermeasure based on fuzzy matter-element analysis

    International Nuclear Information System (INIS)

    Xin Jing; Tang Huaqing; Zhang Yinghua; Zhang Limin

    2009-01-01

    A risk assessment model of nuclear accident emergency protection countermeasure based on fuzzy matter-element analysis and Euclid approach degree is proposed in the paper. The weight of assessed index is determined by information entropy and the scoring by experts, which could not only make full use of the inherent information of the indexes adequately, but reduce subjective assumption in the course of assessment effectively. The applied result shows that it is reasonable that the model is adopted to make risk assessment for nuclear accident emergency protective countermeasure,and it could be a kind of effective analytical method and decision making basis to choose the optimum protection countermeasure. (authors)

  14. Modelling tsunami inundation for risk analysis at the Andaman Sea Coast of Thailand

    Science.gov (United States)

    Kaiser, G.; Kortenhaus, A.

    2009-04-01

    The mega-tsunami of Dec. 26, 2004 strongly impacted the Andaman Sea coast of Thailand and devastated coastal ecosystems as well as towns, settlements and tourism resorts. In addition to the tragic loss of many lives, the destruction or damage of life-supporting infrastructure, such as buildings, roads, water & power supply etc. caused high economic losses in the region. To mitigate future tsunami impacts there is a need to assess the tsunami hazard and vulnerability in flood prone areas at the Andaman Sea coast in order to determine the spatial distribution of risk and to develop risk management strategies. In the bilateral German-Thai project TRAIT research is performed on integrated risk assessment for the Provinces Phang Nga and Phuket in southern Thailand, including a hazard analysis, i.e. modelling tsunami propagation to the coast, tsunami wave breaking and inundation characteristics, as well as vulnerability analysis of the socio-economic and the ecological system in order to determine the scenario-based, specific risk for the region. In this presentation results of the hazard analysis and the inundation simulation are presented and discussed. Numerical modelling of tsunami propagation and inundation simulation is an inevitable tool for risk analysis, risk management and evacuation planning. While numerous investigations have been made to model tsunami wave generation and propagation in the Indian Ocean, there is still a lack in determining detailed inundation patterns, i.e. water depth and flow dynamics. However, for risk management and evacuation planning this knowledge is essential. As the accuracy of the inundation simulation is strongly depending on the available bathymetric and the topographic data, a multi-scale approach is chosen in this work. The ETOPO Global Relief Model as a bathymetric basis and the Shuttle Radar Topography Mission (SRTM90) have been widely applied in tsunami modelling approaches as these data are free and almost world

  15. A nutritional risk screening model for patients with liver cirrhosis established using discriminant analysis

    Directory of Open Access Journals (Sweden)

    ZHU Binghua

    2017-06-01

    Full Text Available ObjectiveTo establish a nutritional risk screening model for patients with liver cirrhosis using discriminant analysis. MethodsThe clinical data of 273 patients with liver cirrhosis who were admitted to Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine from August 2015 to March 2016 were collected. Body height, body weight, upper arm circumference, triceps skinfold thickness, subscapular skinfold thickness, and hand grip strength were measured and recorded, and then body mass index (BMI and upper arm muscle circumference were calculated. Laboratory markers including liver function parameters, renal function parameters, and vitamins were measured. The patients were asked to complete Nutritional Risk Screening 2002 and Malnutrition Universal Screening Tool (MUST, and a self-developed nutritional risk screening pathway was used for nutritional risk classification. Observation scales of the four diagnostic methods in traditional Chinese medicine were used to collect patients′ symptoms and signs. Continuous data were expressed as mean±SD (x±s; an analysis of variance was used for comparison between multiple groups, and the least significant difference t-test was used for further comparison between two groups. Discriminant analysis was used for model establishment, and cross validation was used for model verification. ResultsThe nutritional risk screening pathway for patients with liver cirrhosis was used for the screening of respondents, and there were 49 patients (17.95% in non-risk group, 49 (17.95% in possible-risk group, and 175 (64.10% in risk group. The distance criterion function was used to establish the nutritional risk screening model for patients with liver cirrhosis: D1=-11.885+0.310×BMI+0150×MAC+0.005×P-Alb-0.001×Vit B12+0.103×Vit D-0.89×ascites-0.404×weakness-0.560×hypochondriac pain+0035×dysphoria with feverish sensation (note: if a patient has ascites, weakness, hypochondriac pain

  16. Uncertainty and sensitivity analysis of flood risk management decisions based on stationary and nonstationary model choices

    Directory of Open Access Journals (Sweden)

    Rehan Balqis M.

    2016-01-01

    Full Text Available Current practice in flood frequency analysis assumes that the stochastic properties of extreme floods follow that of stationary conditions. As human intervention and anthropogenic climate change influences in hydrometeorological variables are becoming evident in some places, there have been suggestions that nonstationary statistics would be better to represent the stochastic properties of the extreme floods. The probabilistic estimation of non-stationary models, however, is surrounded with uncertainty related to scarcity of observations and modelling complexities hence the difficulty to project the future condition. In the face of uncertain future and the subjectivity of model choices, this study attempts to demonstrate the practical implications of applying a nonstationary model and compares it with a stationary model in flood risk assessment. A fully integrated framework to simulate decision makers’ behaviour in flood frequency analysis is thereby developed. The framework is applied to hypothetical flood risk management decisions and the outcomes are compared with those of known underlying future conditions. Uncertainty of the economic performance of the risk-based decisions is assessed through Monte Carlo simulations. Sensitivity of the results is also tested by varying the possible magnitude of future changes. The application provides quantitative and qualitative comparative results that satisfy a preliminary analysis of whether the nonstationary model complexity should be applied to improve the economic performance of decisions. Results obtained from the case study shows that the relative differences of competing models for all considered possible future changes are small, suggesting that stationary assumptions are preferred to a shift to nonstationary statistics for practical application of flood risk management. Nevertheless, nonstationary assumption should also be considered during a planning stage in addition to stationary assumption

  17. Risk analysis of urban gas pipeline network based on improved bow-tie model

    Science.gov (United States)

    Hao, M. J.; You, Q. J.; Yue, Z.

    2017-11-01

    Gas pipeline network is a major hazard source in urban areas. In the event of an accident, there could be grave consequences. In order to understand more clearly the causes and consequences of gas pipeline network accidents, and to develop prevention and mitigation measures, the author puts forward the application of improved bow-tie model to analyze risks of urban gas pipeline network. The improved bow-tie model analyzes accident causes from four aspects: human, materials, environment and management; it also analyzes the consequences from four aspects: casualty, property loss, environment and society. Then it quantifies the causes and consequences. Risk identification, risk analysis, risk assessment, risk control, and risk management will be clearly shown in the model figures. Then it can suggest prevention and mitigation measures accordingly to help reduce accident rate of gas pipeline network. The results show that the whole process of an accident can be visually investigated using the bow-tie model. It can also provide reasons for and predict consequences of an unfortunate event. It is of great significance in order to analyze leakage failure of gas pipeline network.

  18. The development of stochastic process modeling through risk analysis derived from scheduling of NPP project

    International Nuclear Information System (INIS)

    Lee, Kwang Ho; Roh, Myung Sub

    2013-01-01

    There are so many different factors to consider when constructing a nuclear power plant successfully from planning to decommissioning. According to PMBOK, all projects have nine domains from a holistic project management perspective. They are equally important to all projects, however, this study focuses mostly on the processes required to manage timely completion of the project and conduct risk management. The overall objective of this study is to let you know what the risk analysis derived from scheduling of NPP project is, and understand how to implement the stochastic process modeling through risk management. Building the Nuclear Power Plant is required a great deal of time and fundamental knowledge related to all engineering. That means that integrated project scheduling management with so many activities is necessary and very important. Simulation techniques for scheduling of NPP project using Open Plan program, Crystal Ball program, and Minitab program can be useful tools for designing optimal schedule planning. Thus far, Open Plan and Monte Carlo programs have been used to calculate the critical path for scheduling network analysis. And also, Minitab program has been applied to monitor the scheduling risk. This approach to stochastic modeling through risk analysis of project activities is very useful for optimizing the schedules of activities using Critical Path Method and managing the scheduling control of NPP project. This study has shown new approach to optimal scheduling of NPP project, however, this does not consider the characteristic of activities according to the NPP site conditions. Hence, this study needs more research considering those factors

  19. The development of stochastic process modeling through risk analysis derived from scheduling of NPP project

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Kwang Ho; Roh, Myung Sub [KEPCO International Nuclear Graduate School, Ulsan (Korea, Republic of)

    2013-10-15

    There are so many different factors to consider when constructing a nuclear power plant successfully from planning to decommissioning. According to PMBOK, all projects have nine domains from a holistic project management perspective. They are equally important to all projects, however, this study focuses mostly on the processes required to manage timely completion of the project and conduct risk management. The overall objective of this study is to let you know what the risk analysis derived from scheduling of NPP project is, and understand how to implement the stochastic process modeling through risk management. Building the Nuclear Power Plant is required a great deal of time and fundamental knowledge related to all engineering. That means that integrated project scheduling management with so many activities is necessary and very important. Simulation techniques for scheduling of NPP project using Open Plan program, Crystal Ball program, and Minitab program can be useful tools for designing optimal schedule planning. Thus far, Open Plan and Monte Carlo programs have been used to calculate the critical path for scheduling network analysis. And also, Minitab program has been applied to monitor the scheduling risk. This approach to stochastic modeling through risk analysis of project activities is very useful for optimizing the schedules of activities using Critical Path Method and managing the scheduling control of NPP project. This study has shown new approach to optimal scheduling of NPP project, however, this does not consider the characteristic of activities according to the NPP site conditions. Hence, this study needs more research considering those factors.

  20. Clinical risk analysis with failure mode and effect analysis (FMEA) model in a dialysis unit.

    Science.gov (United States)

    Bonfant, Giovanna; Belfanti, Pietro; Paternoster, Giuseppe; Gabrielli, Danila; Gaiter, Alberto M; Manes, Massimo; Molino, Andrea; Pellu, Valentina; Ponzetti, Clemente; Farina, Massimo; Nebiolo, Pier E

    2010-01-01

    The aim of clinical risk management is to improve the quality of care provided by health care organizations and to assure patients' safety. Failure mode and effect analysis (FMEA) is a tool employed for clinical risk reduction. We applied FMEA to chronic hemodialysis outpatients. FMEA steps: (i) process study: we recorded phases and activities. (ii) Hazard analysis: we listed activity-related failure modes and their effects; described control measures; assigned severity, occurrence and detection scores for each failure mode and calculated the risk priority numbers (RPNs) by multiplying the 3 scores. Total RPN is calculated by adding single failure mode RPN. (iii) Planning: we performed a RPNs prioritization on a priority matrix taking into account the 3 scores, and we analyzed failure modes causes, made recommendations and planned new control measures. (iv) Monitoring: after failure mode elimination or reduction, we compared the resulting RPN with the previous one. Our failure modes with the highest RPN came from communication and organization problems. Two tools have been created to ameliorate information flow: "dialysis agenda" software and nursing datasheets. We scheduled nephrological examinations, and we changed both medical and nursing organization. Total RPN value decreased from 892 to 815 (8.6%) after reorganization. Employing FMEA, we worked on a few critical activities, and we reduced patients' clinical risk. A priority matrix also takes into account the weight of the control measures: we believe this evaluation is quick, because of simple priority selection, and that it decreases action times.

  1. Risk Route Choice Analysis and the Equilibrium Model under Anticipated Regret Theory

    Directory of Open Access Journals (Sweden)

    pengcheng yuan

    2014-02-01

    Full Text Available The assumption about travellers’ route choice behaviour has major influence on the traffic flow equilibrium analysis. Previous studies about the travellers’ route choice were mainly based on the expected utility maximization theory. However, with the gradually increasing knowledge about the uncertainty of the transportation system, the researchers have realized that there is much constraint in expected util­ity maximization theory, because expected utility maximiza­tion requires travellers to be ‘absolutely rational’; but in fact, travellers are not truly ‘absolutely rational’. The anticipated regret theory proposes an alternative framework to the tra­ditional risk-taking in route choice behaviour which might be more scientific and reasonable. We have applied the antici­pated regret theory to the analysis of the risk route choosing process, and constructed an anticipated regret utility func­tion. By a simple case which includes two parallel routes, the route choosing results influenced by the risk aversion degree, regret degree and the environment risk degree have been analyzed. Moreover, the user equilibrium model based on the anticipated regret theory has been established. The equivalence and the uniqueness of the model are proved; an efficacious algorithm is also proposed to solve the model. Both the model and the algorithm are demonstrated in a real network. By an experiment, the model results and the real data have been compared. It was found that the model re­sults can be similar to the real data if a proper regret degree parameter is selected. This illustrates that the model can better explain the risk route choosing behaviour. Moreover, it was also found that the traveller’ regret degree increases when the environment becomes more and more risky.

  2. Decision analysis and risk models for land development affecting infrastructure systems.

    Science.gov (United States)

    Thekdi, Shital A; Lambert, James H

    2012-07-01

    Coordination and layering of models to identify risks in complex systems such as large-scale infrastructure of energy, water, and transportation is of current interest across application domains. Such infrastructures are increasingly vulnerable to adjacent commercial and residential land development. Land development can compromise the performance of essential infrastructure systems and increase the costs of maintaining or increasing performance. A risk-informed approach to this topic would be useful to avoid surprise, regret, and the need for costly remedies. This article develops a layering and coordination of models for risk management of land development affecting infrastructure systems. The layers are: system identification, expert elicitation, predictive modeling, comparison of investment alternatives, and implications of current decisions for future options. The modeling layers share a focus on observable factors that most contribute to volatility of land development and land use. The relevant data and expert evidence include current and forecasted growth in population and employment, conservation and preservation rules, land topography and geometries, real estate assessments, market and economic conditions, and other factors. The approach integrates to a decision framework of strategic considerations based on assessing risk, cost, and opportunity in order to prioritize needs and potential remedies that mitigate impacts of land development to the infrastructure systems. The approach is demonstrated for a 5,700-mile multimodal transportation system adjacent to 60,000 tracts of potential land development. © 2011 Society for Risk Analysis.

  3. Risk analysis of Leksell Gamma Knife Model C with automatic positioning system

    International Nuclear Information System (INIS)

    Goetsch, Steven J.

    2002-01-01

    Purpose: This study was conducted to evaluate the decrease in risk from misadministration of the new Leksell Gamma Knife Model C with Automatic Positioning System compared with previous models. Methods and Materials: Elekta Instruments, A.B. of Stockholm has introduced a new computer-controlled Leksell Gamma Knife Model C which uses motor-driven trunnions to reposition the patient between isocenters (shots) without human intervention. Previous models required the operators to manually set coordinates from a printed list, permitting opportunities for coordinate transposition, incorrect helmet size, incorrect treatment times, missing shots, or repeated shots. Results: A risk analysis was conducted between craniotomy involving hospital admission and outpatient Gamma Knife radiosurgery. A report of the Institute of Medicine of the National Academies dated November 29, 1999 estimated that medical errors kill between 44,000 and 98,000 people each year in the United States. Another report from the National Nosocomial Infections Surveillance System estimates that 2.1 million nosocomial infections occur annually in the United States in acute care hospitals alone, with 31 million total admissions. Conclusions: All medical procedures have attendant risks of morbidity and possibly mortality. Each patient should be counseled as to the risk of adverse effects as well as the likelihood of good results for alternative treatment strategies. This paper seeks to fill a gap in the existing medical literature, which has a paucity of data involving risk estimates for stereotactic radiosurgery

  4. Models for Risk Aggregation and Sensitivity Analysis: An Application to Bank Economic Capital

    Directory of Open Access Journals (Sweden)

    Hulusi Inanoglu

    2009-12-01

    Full Text Available A challenge in enterprise risk measurement for diversified financial institutions is developing a coherent approach to aggregating different risk types. This has been motivated by rapid financial innovation, developments in supervisory standards (Basel 2 and recent financial turmoil. The main risks faced - market, credit and operational – have distinct distributional properties, and historically have been modeled in differing frameworks. We contribute to the modeling effort by providing tools and insights to practitioners and regulators. First, we extend the scope of the analysis to liquidity and interest rate risk, having Basel Pillar II of Basel implications. Second, we utilize data from major banking institutions’ loss experience from supervisory call reports, which allows us to explore the impact of business mix and inter-risk correlations on total risk. Third, we estimate and compare alternative established frameworks for risk aggregation (including copula models on the same data-sets across banks, comparing absolute total risk measures (Value-at-Risk – VaR and proportional diversification benefits-PDB, goodness-of-fit (GOF of the model as data as well as the variability of the VaR estimate with respect to sampling error in parameter. This benchmarking and sensitivity analysis suggests that practitioners consider implementing a simple non-parametric methodology (empirical copula simulation- ECS in order to quantify integrated risk, in that it is found to be more conservatism and stable than the other models. We observe that ECS produces 20% to 30% higher VaR relative to the standard Gaussian copula simulation (GCS, while the variance-covariance approximation (VCA is much lower. ECS yields the highest PDBs than other methodologies (127% to 243%, while Archimadean Gumbel copula simulation (AGCS is the lowest (10-21%. Across the five largest banks we fail to find the effect of business mix to exert a directionally consistent impact on

  5. Information security risk analysis

    CERN Document Server

    Peltier, Thomas R

    2001-01-01

    Effective Risk AnalysisQualitative Risk AnalysisValue AnalysisOther Qualitative MethodsFacilitated Risk Analysis Process (FRAP)Other Uses of Qualitative Risk AnalysisCase StudyAppendix A: QuestionnaireAppendix B: Facilitated Risk Analysis Process FormsAppendix C: Business Impact Analysis FormsAppendix D: Sample of ReportAppendix E: Threat DefinitionsAppendix F: Other Risk Analysis OpinionsIndex

  6. Integrating household risk mitigation behaviour in flood risk analysis : An agent-based model approach

    NARCIS (Netherlands)

    Haer, Toon; Botzen, W.J.W.|info:eu-repo/dai/nl/297620584; Aerts, Jeroen

    2017-01-01

    Recent studies showed that climate change and socioeconomic trends are expected to increase flood risks in many regions. However, in these studies, human behavior is commonly assumed to be constant, which neglects interaction and feedback loops between human and environmental systems. This neglect

  7. The System Cost Model: A tool for life cycle cost and risk analysis

    International Nuclear Information System (INIS)

    Hsu, K.; Lundeen, A.; Shropshire, D.; Sherick, M.

    1996-01-01

    In May of 1994, Lockheed Idaho Technologies Company (LITCO) in Idaho Falls, Idaho and subcontractors began development of the System Cost Model (SCM) application. The SCM estimates life cycle costs of the entire US Department of Energy (DOE) complex for designing; constructing; operating; and decommissioning treatment, storage, and disposal (TSD) facilities for mixed low-level, low-level, and transuranic waste. The SCM uses parametric cost functions to estimate life cycle costs for various treatment, storage, and disposal modules which reflect planned and existing waste management facilities at DOE installations. In addition, SCM can model new TSD facilities based on capacity needs over the program life cycle. The user can provide input data (default data is included in the SCM) including the volume and nature of waste to be managed, the time period over which the waste is to be managed, and the configuration of the waste management complex (i.e., where each installation's generated waste will be treated, stored, and disposed). Then the SCM uses parametric cost equations to estimate the costs of pre-operations (designing), construction, operations and maintenance, and decommissioning these waste management facilities. The SCM also provides transportation costs for DOE wastes. Transportation costs are provided for truck and rail and include transport of contact-handled, remote-handled, and alpha (transuranic) wastes. A complement to the SCM is the System Cost Model-Risk (SCM-R) model, which provides relative Environmental, Safety, and Health (ES and H) risk information. A relative ES and H risk basis has been developed and applied by LITCO at the INEL. The risk basis is now being automated in the SCM-R to facilitate rapid risk analysis of system alternatives. The added risk functionality will allow combined cost and risk evaluation of EM alternatives

  8. Credit Risk Modeling

    DEFF Research Database (Denmark)

    Lando, David

    Credit risk is today one of the most intensely studied topics in quantitative finance. This book provides an introduction and overview for readers who seek an up-to-date reference to the central problems of the field and to the tools currently used to analyze them. The book is aimed at researchers...... and students in finance, at quantitative analysts in banks and other financial institutions, and at regulators interested in the modeling aspects of credit risk. David Lando considers the two broad approaches to credit risk analysis: that based on classical option pricing models on the one hand...

  9. Prediction Model of Collapse Risk Based on Information Entropy and Distance Discriminant Analysis Method

    Directory of Open Access Journals (Sweden)

    Hujun He

    2017-01-01

    Full Text Available The prediction and risk classification of collapse is an important issue in the process of highway construction in mountainous regions. Based on the principles of information entropy and Mahalanobis distance discriminant analysis, we have produced a collapse hazard prediction model. We used the entropy measure method to reduce the influence indexes of the collapse activity and extracted the nine main indexes affecting collapse activity as the discriminant factors of the distance discriminant analysis model (i.e., slope shape, aspect, gradient, and height, along with exposure of the structural face, stratum lithology, relationship between weakness face and free face, vegetation cover rate, and degree of rock weathering. We employ postearthquake collapse data in relation to construction of the Yingxiu-Wolong highway, Hanchuan County, China, as training samples for analysis. The results were analyzed using the back substitution estimation method, showing high accuracy and no errors, and were the same as the prediction result of uncertainty measure. Results show that the classification model based on information entropy and distance discriminant analysis achieves the purpose of index optimization and has excellent performance, high prediction accuracy, and a zero false-positive rate. The model can be used as a tool for future evaluation of collapse risk.

  10. Comparative risk analysis

    International Nuclear Information System (INIS)

    Niehaus, F.

    1988-01-01

    In this paper, the risks of various energy systems are discussed considering severe accidents analysis, particularly the probabilistic safety analysis, and probabilistic safety criteria, and the applications of these criteria and analysis. The comparative risk analysis has demonstrated that the largest source of risk in every society is from daily small accidents. Nevertheless, we have to be more concerned about severe accidents. The comparative risk analysis of five different energy systems (coal, oil, gas, LWR and STEC (Solar)) for the public has shown that the main sources of risks are coal and oil. The latest comparative risk study of various energy has been conducted in the USA and has revealed that the number of victims from coal is 42 as many than victims from nuclear. A study for severe accidents from hydro-dams in United States has estimated the probability of dam failures at 1 in 10,000 years and the number of victims between 11,000 and 260,000. The average occupational risk from coal is one fatal accident in 1,000 workers/year. The probabilistic safety analysis is a method that can be used to assess nuclear energy risks, and to analyze the severe accidents, and to model all possible accident sequences and consequences. The 'Fault tree' analysis is used to know the probability of failure of the different systems at each point of accident sequences and to calculate the probability of risks. After calculating the probability of failure, the criteria for judging the numerical results have to be developed, that is the quantitative and qualitative goals. To achieve these goals, several systems have been devised by various countries members of AIEA. The probabilistic safety ana-lysis method has been developed by establishing a computer program permit-ting to know different categories of safety related information. 19 tabs. (author)

  11. Taxonomic analysis of perceived risk: modeling individual and group perceptions within homogeneous hazard domains

    International Nuclear Information System (INIS)

    Kraus, N.N.; Slovic, P.

    1988-01-01

    Previous studies of risk perception have typically focused on the mean judgments of a group of people regarding the riskiness (or safety) of a diverse set of hazardous activities, substances, and technologies. This paper reports the results of two studies that take a different path. Study 1 investigated whether models within a single technological domain were similar to previous models based on group means and diverse hazards. Study 2 created a group taxonomy of perceived risk for only one technological domain, railroads, and examined whether the structure of that taxonomy corresponded with taxonomies derived from prior studies of diverse hazards. Results from Study 1 indicated that the importance of various risk characteristics in determining perceived risk differed across individuals and across hazards, but not so much as to invalidate the results of earlier studies based on group means and diverse hazards. In Study 2, the detailed analysis of railroad hazards produced a structure that had both important similarities to, and dissimilarities from, the structure obtained in prior research with diverse hazard domains. The data also indicated that railroad hazards are really quite diverse, with some approaching nuclear reactors in their perceived seriousness. These results suggest that information about the diversity of perceptions within a single domain of hazards could provide valuable input to risk-management decisions

  12. Regional probabilistic nuclear risk and vulnerability assessment by integration of mathematical modelling land GIS-analysis

    International Nuclear Information System (INIS)

    Rigina, O.; Baklanov, A.

    2002-01-01

    The Kola Peninsula, Russian Arctic exceeds all other regions in the world in the number of nuclear reactors. The study was aimed at estimating possible radiation risks to the population in the Nordic countries in case of a severe accident in the Kola Peninsula. A new approach based on probabilistic analysis of modelled possible pathways of radionuclide transport and precipitation was developed. For the general population, Finland is at most risk with respect to the Kola NPP, because of: high population density or proximity to the radiation-risk sites and relatively high probability of an airflow trajectory there, and precipitation. After considering the critical group, northern counties in Norway, Finland and Sweden appear to be most vulnerable. (au)

  13. Adversarial risk analysis

    CERN Document Server

    Banks, David L; Rios Insua, David

    2015-01-01

    Flexible Models to Analyze Opponent Behavior A relatively new area of research, adversarial risk analysis (ARA) informs decision making when there are intelligent opponents and uncertain outcomes. Adversarial Risk Analysis develops methods for allocating defensive or offensive resources against intelligent adversaries. Many examples throughout illustrate the application of the ARA approach to a variety of games and strategic situations. The book shows decision makers how to build Bayesian models for the strategic calculation of their opponents, enabling decision makers to maximize their expected utility or minimize their expected loss. This new approach to risk analysis asserts that analysts should use Bayesian thinking to describe their beliefs about an opponent's goals, resources, optimism, and type of strategic calculation, such as minimax and level-k thinking. Within that framework, analysts then solve the problem from the perspective of the opponent while placing subjective probability distributions on a...

  14. A Model of Risk Analysis in Analytical Methodology for Biopharmaceutical Quality Control.

    Science.gov (United States)

    Andrade, Cleyton Lage; Herrera, Miguel Angel De La O; Lemes, Elezer Monte Blanco

    2018-01-01

    control laboratory: It is laborious, time consuming, semi-quantitative, and requires a radioisotope. Along with dot-blot hybridization, two alternatives techniques were evaluated: threshold analysis and quantitative polymerase chain reaction. Quality risk management tools were applied to compare the techniques, taking into account the uncertainties, the possibility of circumstances or future events, and their effects upon method performance. By illustrating the application of these tools with DNA methods, we provide an example of how they can be used to support a scientific and practical approach to decision making and can assess and manage method performance risk using such tools. This paper discusses, considering the principles of quality risk management, an additional approach to the development and selection of analytical quality control methods using the risk analysis tool hazard analysis and critical control points. This tool provides the possibility to find the method procedural steps with higher impact on method reliability (called critical control points). Our model concluded that the radioactive dot-blot assay has the larger number of critical control points, followed by quantitative polymerase chain reaction and threshold analysis. Quantitative polymerase chain reaction is shown to be the better alternative analytical methodology in residual cellular DNA analysis. © PDA, Inc. 2018.

  15. A stochastic multicriteria model for evidence-based decision making in drug benefit-risk analysis.

    Science.gov (United States)

    Tervonen, Tommi; van Valkenhoef, Gert; Buskens, Erik; Hillege, Hans L; Postmus, Douwe

    2011-05-30

    Drug benefit-risk (BR) analysis is based on firm clinical evidence regarding various safety and efficacy outcomes. In this paper, we propose a new and more formal approach for constructing a supporting multi-criteria model that fully takes into account the evidence on efficacy and adverse drug reactions. Our approach is based on the stochastic multi-criteria acceptability analysis methodology, which allows us to compute the typical value judgments that support a decision, to quantify decision uncertainty, and to compute a comprehensive BR profile. We construct a multi-criteria model for the therapeutic group of second-generation antidepressants. We assess fluoxetine and venlafaxine together with placebo according to incidence of treatment response and three common adverse drug reactions by using data from a published study. Our model shows that there are clear trade-offs among the treatment alternatives. Copyright © 2011 John Wiley & Sons, Ltd.

  16. Risk factors of chronic periodontitis on healing response: a multilevel modelling analysis.

    Science.gov (United States)

    Song, J; Zhao, H; Pan, C; Li, C; Liu, J; Pan, Y

    2017-09-15

    Chronic periodontitis is a multifactorial polygenetic disease with an increasing number of associated factors that have been identified over recent decades. Longitudinal epidemiologic studies have demonstrated that the risk factors were related to the progression of the disease. A traditional multivariate regression model was used to find risk factors associated with chronic periodontitis. However, the approach requirement of standard statistical procedures demands individual independence. Multilevel modelling (MLM) data analysis has widely been used in recent years, regarding thorough hierarchical structuring of the data, decomposing the error terms into different levels, and providing a new analytic method and framework for solving this problem. The purpose of our study is to investigate the relationship of clinical periodontal index and the risk factors in chronic periodontitis through MLM analysis and to identify high-risk individuals in the clinical setting. Fifty-four patients with moderate to severe periodontitis were included. They were treated by means of non-surgical periodontal therapy, and then made follow-up visits regularly at 3, 6, and 12 months after therapy. Each patient answered a questionnaire survey and underwent measurement of clinical periodontal parameters. Compared with baseline, probing depth (PD) and clinical attachment loss (CAL) improved significantly after non-surgical periodontal therapy with regular follow-up visits at 3, 6, and 12 months after therapy. The null model and variance component models with no independent variables included were initially obtained to investigate the variance of the PD and CAL reductions across all three levels, and they showed a statistically significant difference (P periodontal therapy with regular follow-up visits had a remarkable curative effect. All three levels had a substantial influence on the reduction of PD and CAL. Site-level had the largest effect on PD and CAL reductions.

  17. Unsharpness-risk analysis

    International Nuclear Information System (INIS)

    Preyssl, C.

    1986-01-01

    Safety analysis provides the only tool for evaluation and quantification of rare or hypothetical events leading to system failure. So far probability theory has been used for the fault- and event-tree methodology. The phenomenon of uncertainties constitutes an important aspect in risk analysis. Uncertainties can be classified as originating from 'randomness' or 'fuzziness'. Probability theory addresses randomness only. The use of 'fuzzy set theory' makes it possible to include both types of uncertainty in the mathematical model of risk analysis. Thus the 'fuzzy fault tree' is expressed in 'possibilistic' terms implying a range of simplifications and improvements. 'Human failure' and 'conditionality' can be treated correctly. Only minimum-maximum relations are used to combine the possibility distributions of events. Various event-classifications facilitate the interpretation of the results. The method is demonstrated by application to a TRIGA-research reactor. Uncertainty as an implicit part of 'fuzzy risk' can be quantified explicitly using an 'uncertainty measure'. Based on this the 'degree of relative compliance' with a quantizative safety goal can be defined for a particular risk. The introduction of 'weighting functionals' guarantees the consideration of the importances attached to different parts of the risk exceeding or complying with the standard. The comparison of two reference systems is demonstrated in a case study. It is concluded that any application of the 'fuzzy risk analysis' has to be free of any hypostatization when reducing subjective to objective information. (Author)

  18. Dealing with project complexity by matrix-based propagation modelling for project risk analysis

    OpenAIRE

    Fang , Chao; Marle , Franck

    2012-01-01

    International audience; Engineering projects are facing a growing complexity and are thus exposed to numerous and interdependent risks. In this paper, we present a quantitative method for modelling propagation behaviour in the project risk network. The construction of the network requires the involvement of the project manager and related experts using the Design Structure Matrix (DSM) method. A matrix-based risk propagation model is introduced to calculate risk propagation and thus to re-eva...

  19. Risk Analysis on Leakage Failure of Natural Gas Pipelines by Fuzzy Bayesian Network with a Bow-Tie Model

    OpenAIRE

    Shan, Xian; Liu, Kang; Sun, Pei-Liang

    2017-01-01

    Pipeline is the major mode of natural gas transportation. Leakage of natural gas pipelines may cause explosions and fires, resulting in casualties, environmental damage, and material loss. Efficient risk analysis is of great significance for preventing and mitigating such potential accidents. The objective of this study is to present a practical risk assessment method based on Bow-tie model and Bayesian network for risk analysis of natural gas pipeline leakage. Firstly, identify the potential...

  20. Predictive value and modeling analysis of MSCT signs in gastrointestinal stromal tumors (GISTs) to pathological risk degree.

    Science.gov (United States)

    Wang, J-K

    2017-03-01

    By analyzing MSCT (multi-slice computed tomography) signs with different risks in gastrointestinal stromal tumors, this paper aimed to discuss the predictive value and modeling analysis of MSCT signs in GISTs (gastrointestinal stromal tumor) to pathological risk degree. 100 cases of primary GISTs with abdominal and pelvic MSCT scan were involved in this study. All MSCT scan findings and enhanced findings were analyzed and compared among cases with different risk degree of pathology. Then GISTs diagnostic model was established by using support vector machine (SVM) algorithm, and its diagnostic value was evaluated as well. All lesions were solitary, among which there were 46 low-risk cases, 24 medium-risk cases and 30 high-risk cases. For all high-risk, medium-risk and low-risk GISTs, there were statistical differences in tumor growth pattern, size, shape, fat space, with or without calcification, ulcer, enhancement method and peritumoral and intratumoral vessels (pvalue at each period (plain scan, arterial phase, venous phase) (p>0.05). The apparent difference lied in plain scan, arterial phase and venous phase for each risk degree. The diagnostic accuracy of SVM diagnostic model established with 10 imaging features as indexes was 70.0%, and it was especially reliable when diagnosing GISTs of high or low risk. Preoperative analysis of MSCT features is clinically significant for its diagnosis of risk degree and prognosis; GISTs diagnostic model established on the basis of SVM possesses high diagnostic value.

  1. Analysis of perceived risk among construction workers: a cross-cultural study and reflection on the Hofstede model.

    Science.gov (United States)

    Martinez-Fiestas, Myriam; Rodríguez-Garzón, Ignacio; Delgado-Padial, Antonio; Lucas-Ruiz, Valeriano

    2017-09-01

    This article presents a cross-cultural study on perceived risk in the construction industry. Worker samples from three different countries were studied: Spain, Peru and Nicaragua. The main goal was to explain how construction workers perceive their occupational hazard and to analyze how this is related to their national culture. The model used to measure perceived risk was the psychometric paradigm. The results show three very similar profiles, indicating that risk perception is independent of nationality. A cultural analysis was conducted using the Hofstede model. The results of this analysis and the relation to perceived risk showed that risk perception in construction is independent of national culture. Finally, a multiple lineal regression analysis was conducted to determine what qualitative attributes could predict the global quantitative size of risk perception. All of the findings have important implications regarding the management of safety in the workplace.

  2. International Conference on Risk Analysis

    CERN Document Server

    Oliveira, Teresa; Rigas, Alexandros; Gulati, Sneh

    2015-01-01

    This book covers the latest results in the field of risk analysis. Presented topics include probabilistic models in cancer research, models and methods in longevity, epidemiology of cancer risk, engineering reliability and economical risk problems. The contributions of this volume originate from the 5th International Conference on Risk Analysis (ICRA 5). The conference brought together researchers and practitioners working in the field of risk analysis in order to present new theoretical and computational methods with applications in biology, environmental sciences, public health, economics and finance.

  3. Psychosocial Modeling of Insider Threat Risk Based on Behavioral and Word Use Analysis

    Energy Technology Data Exchange (ETDEWEB)

    Greitzer, Frank L.; Kangas, Lars J.; Noonan, Christine F.; Brown, Christopher R.; Ferryman, Thomas A.

    2013-10-01

    In many insider crimes, managers and other coworkers observed that the offenders had exhibited signs of stress, disgruntlement, or other issues, but no alarms were raised. Barriers to using such psychosocial indicators include the inability to recognize the signs and the failure to record the behaviors so that they can be assessed. A psychosocial model was developed to assess an employee’s behavior associated with an increased risk of insider abuse. The model is based on case studies and research literature on factors/correlates associated with precursor behavioral manifestations of individuals committing insider crimes. A complementary Personality Factor modeling approach was developed based on analysis to derive relevant personality characteristics from word use. Several implementations of the psychosocial model were evaluated by comparing their agreement with judgments of human resources and management professionals; the personality factor modeling approach was examined using email samples. If implemented in an operational setting, these models should be part of a set of management tools for employee assessment to identify employees who pose a greater insider threat.

  4. The explicit treatment of model uncertainties in the presence of aleatory and epistemic parameter uncertainties in risk and reliability analysis

    International Nuclear Information System (INIS)

    Ahn, Kwang Il; Yang, Joon Eon

    2003-01-01

    In the risk and reliability analysis of complex technological systems, the primary concern of formal uncertainty analysis is to understand why uncertainties arise, and to evaluate how they impact the results of the analysis. In recent times, many of the uncertainty analyses have focused on parameters of the risk and reliability analysis models, whose values are uncertain in an aleatory or an epistemic way. As the field of parametric uncertainty analysis matures, however, more attention is being paid to the explicit treatment of uncertainties that are addressed in the predictive model itself as well as the accuracy of the predictive model. The essential steps for evaluating impacts of these model uncertainties in the presence of parameter uncertainties are to determine rigorously various sources of uncertainties to be addressed in an underlying model itself and in turn model parameters, based on our state-of-knowledge and relevant evidence. Answering clearly the question of how to characterize and treat explicitly the forgoing different sources of uncertainty is particularly important for practical aspects such as risk and reliability optimization of systems as well as more transparent risk information and decision-making under various uncertainties. The main purpose of this paper is to provide practical guidance for quantitatively treating various model uncertainties that would often be encountered in the risk and reliability modeling process of complex technological systems

  5. Analysis of risk factors and the establishment of a risk model for peripherally inserted central catheter thrombosis

    OpenAIRE

    Fang Hu; Ruo-Nan Hao; Jie Zhang; Zhi-Cheng Ma

    2016-01-01

    Objective: To investigate the main risk factors of peripherally inserted central catheter (PICC) related upper extremity deep venous thrombosis and establish the risk predictive model of PICC-related upper extremity deep venous thrombosis. Methods: Patients with PICC who were hospitalized between January 2014 and July 2015 were studied retrospectively; they were divided into a thrombosis group (n = 52), with patients who had a venous thrombosis complication after PICC, and a no-thrombosis ...

  6. Carboy Security Risk Analysis Model of I and C System Using Bayesian Network

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Jinsoo; Heo, Gyunyoung [Kyung Hee Univ., Yongin (Korea, Republic of); Son, Hanseong [Joongbu Univ., Geumsan (Korea, Republic of); Park, Jaekwan [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2013-05-15

    The Korea Institute of Nuclear Safety (KINS) as a regulatory agency declares the R. G 8.22 for applying cyber security in Korea in 2011. In nuclear power industrial, ShinUljin 1, 2 unit and Shingori 3, 4 unit are demonstrating the cyber security for the first time. And in terms of research, the National Security Research Institute and the Korea Atomic Energy Research Institute are developing the nuclear power plant cyber security system in Korean. Currently, these cyber securities like regulation, demonstration and research are focused on nuclear power plant. However, cyber security is also important for the nuclear research reactor like a HANARO which is in Daejeon, primarily due to its characteristic as research reactor since since people access more than power plant. Analysis of the key elements of cyber security is possible to study through the activity-quality and architecture analysis model of cyber security. It is possible to analyze the extent reflected final risk by evaluating input score for each checklist. In this way, you can see an important checklist. Further, if the cyber-attack occurs, it is possible to provide an evidentiary material that is able to determine the key check element corresponding to each situation via a reverse calculation of BN. Finally, Utilization is possible to create a simulated penetratio test scenario according to each situation. Analysis of the key elements of cyber security is possible to study through the activity-quality and architecture analysis model of cyber security. It is possible to analyze the extent reflected in the final risk by evaluating input score for each checklist, in this way, you can see an important checklist. Furthermore, if the cyber-attack occurs, it is possible to provide an evidentiary material that enables to determine the key check element corresponding to each situation via a reverse calculation of BN. Finally, Utilization is possible to create a simulated penetration test scenario according to

  7. Carboy Security Risk Analysis Model of I and C System Using Bayesian Network

    International Nuclear Information System (INIS)

    Shin, Jinsoo; Heo, Gyunyoung; Son, Hanseong; Park, Jaekwan

    2013-01-01

    The Korea Institute of Nuclear Safety (KINS) as a regulatory agency declares the R. G 8.22 for applying cyber security in Korea in 2011. In nuclear power industrial, ShinUljin 1, 2 unit and Shingori 3, 4 unit are demonstrating the cyber security for the first time. And in terms of research, the National Security Research Institute and the Korea Atomic Energy Research Institute are developing the nuclear power plant cyber security system in Korean. Currently, these cyber securities like regulation, demonstration and research are focused on nuclear power plant. However, cyber security is also important for the nuclear research reactor like a HANARO which is in Daejeon, primarily due to its characteristic as research reactor since since people access more than power plant. Analysis of the key elements of cyber security is possible to study through the activity-quality and architecture analysis model of cyber security. It is possible to analyze the extent reflected final risk by evaluating input score for each checklist. In this way, you can see an important checklist. Further, if the cyber-attack occurs, it is possible to provide an evidentiary material that is able to determine the key check element corresponding to each situation via a reverse calculation of BN. Finally, Utilization is possible to create a simulated penetratio test scenario according to each situation. Analysis of the key elements of cyber security is possible to study through the activity-quality and architecture analysis model of cyber security. It is possible to analyze the extent reflected in the final risk by evaluating input score for each checklist, in this way, you can see an important checklist. Furthermore, if the cyber-attack occurs, it is possible to provide an evidentiary material that enables to determine the key check element corresponding to each situation via a reverse calculation of BN. Finally, Utilization is possible to create a simulated penetration test scenario according to

  8. Analysis of a risk prevention document using dependability techniques: a first step towards an effectiveness model

    Science.gov (United States)

    Ferrer, Laetitia; Curt, Corinne; Tacnet, Jean-Marc

    2018-04-01

    Major hazard prevention is a main challenge given that it is specifically based on information communicated to the public. In France, preventive information is notably provided by way of local regulatory documents. Unfortunately, the law requires only few specifications concerning their content; therefore one can question the impact on the general population relative to the way the document is concretely created. Ergo, the purpose of our work is to propose an analytical methodology to evaluate preventive risk communication document effectiveness. The methodology is based on dependability approaches and is applied in this paper to the Document d'Information Communal sur les Risques Majeurs (DICRIM; in English, Municipal Information Document on Major Risks). DICRIM has to be made by mayors and addressed to the public to provide information on major hazards affecting their municipalities. An analysis of law compliance of the document is carried out thanks to the identification of regulatory detection elements. These are applied to a database of 30 DICRIMs. This analysis leads to a discussion on points such as usefulness of the missing elements. External and internal function analysis permits the identification of the form and content requirements and service and technical functions of the document and its components (here its sections). Their results are used to carry out an FMEA (failure modes and effects analysis), which allows us to define the failure and to identify detection elements. This permits the evaluation of the effectiveness of form and content of each components of the document. The outputs are validated by experts from the different fields investigated. Those results are obtained to build, in future works, a decision support model for the municipality (or specialised consulting firms) in charge of drawing up documents.

  9. Analysis of a risk prevention document using dependability techniques: a first step towards an effectiveness model

    Directory of Open Access Journals (Sweden)

    L. Ferrer

    2018-04-01

    Full Text Available Major hazard prevention is a main challenge given that it is specifically based on information communicated to the public. In France, preventive information is notably provided by way of local regulatory documents. Unfortunately, the law requires only few specifications concerning their content; therefore one can question the impact on the general population relative to the way the document is concretely created. Ergo, the purpose of our work is to propose an analytical methodology to evaluate preventive risk communication document effectiveness. The methodology is based on dependability approaches and is applied in this paper to the Document d'Information Communal sur les Risques Majeurs (DICRIM; in English, Municipal Information Document on Major Risks. DICRIM has to be made by mayors and addressed to the public to provide information on major hazards affecting their municipalities. An analysis of law compliance of the document is carried out thanks to the identification of regulatory detection elements. These are applied to a database of 30 DICRIMs. This analysis leads to a discussion on points such as usefulness of the missing elements. External and internal function analysis permits the identification of the form and content requirements and service and technical functions of the document and its components (here its sections. Their results are used to carry out an FMEA (failure modes and effects analysis, which allows us to define the failure and to identify detection elements. This permits the evaluation of the effectiveness of form and content of each components of the document. The outputs are validated by experts from the different fields investigated. Those results are obtained to build, in future works, a decision support model for the municipality (or specialised consulting firms in charge of drawing up documents.

  10. Peak Pc Prediction in Conjunction Analysis: Conjunction Assessment Risk Analysis. Pc Behavior Prediction Models

    Science.gov (United States)

    Vallejo, J.J.; Hejduk, M.D.; Stamey, J. D.

    2015-01-01

    Satellite conjunction risk typically evaluated through the probability of collision (Pc). Considers both conjunction geometry and uncertainties in both state estimates. Conjunction events initially discovered through Joint Space Operations Center (JSpOC) screenings, usually seven days before Time of Closest Approach (TCA). However, JSpOC continues to track objects and issue conjunction updates. Changes in state estimate and reduced propagation time cause Pc to change as event develops. These changes a combination of potentially predictable development and unpredictable changes in state estimate covariance. Operationally useful datum: the peak Pc. If it can reasonably be inferred that the peak Pc value has passed, then risk assessment can be conducted against this peak value. If this value is below remediation level, then event intensity can be relaxed. Can the peak Pc location be reasonably predicted?

  11. Software for occupational health and safety risk analysis based on a fuzzy model.

    Science.gov (United States)

    Stefanovic, Miladin; Tadic, Danijela; Djapan, Marko; Macuzic, Ivan

    2012-01-01

    Risk and safety management are very important issues in healthcare systems. Those are complex systems with many entities, hazards and uncertainties. In such an environment, it is very hard to introduce a system for evaluating and simulating significant hazards. In this paper, we analyzed different types of hazards in healthcare systems and we introduced a new fuzzy model for evaluating and ranking hazards. Finally, we presented a developed software solution, based on the suggested fuzzy model for evaluating and monitoring risk.

  12. Analysis of risk indicators and issues associated with applications of screening model for hazardous and radioactive waste sites

    International Nuclear Information System (INIS)

    Buck, J.W.; Strenge, D.L.; Droppo, J.G. Jr.

    1990-12-01

    Risk indicators, such as population risk, maximum individual risk, time of arrival of contamination, and maximum water concentrations, were analyzed to determine their effect on results from a screening model for hazardous and radioactive waste sites. The analysis of risk indicators is based on calculations resulting from exposure to air and waterborne contamination predicted with Multimedia Environmental Pollutant Assessment System (MEPAS) model. The different risk indicators were analyzed, based on constituent type and transport and exposure pathways. Three of the specific comparisons that were made are (1) population-based versus maximum individual-based risk indicators, (2) time of arrival of contamination, and (3) comparison of different threshold assumptions for noncarcinogenic impacts. Comparison of indicators for population- and maximum individual-based human health risk suggests that these two parameters are highly correlated, but for a given problem, one may be more important than the other. The results indicate that the arrival distribution for different levels of contamination reaching a receptor can also be helpful in decisions regarding the use of resources for remediating short- and long-term environmental problems. The addition of information from a linear model for noncarcinogenic impacts allows interpretation of results below the reference dose (RfD) levels that might help in decisions for certain applications. The analysis of risk indicators suggests that important information may be lost by the use of a single indicator to represent public health risk and that multiple indicators should be considered. 15 refs., 8 figs., 1 tab

  13. Modeling disease risk through analysis of physical interactions between genetic variants within chromatin regulatory circuitry.

    Science.gov (United States)

    Corradin, Olivia; Cohen, Andrea J; Luppino, Jennifer M; Bayles, Ian M; Schumacher, Fredrick R; Scacheri, Peter C

    2016-11-01

    SNPs associated with disease susceptibility often reside in enhancer clusters, or super-enhancers. Constituents of these enhancer clusters cooperate to regulate target genes and often extend beyond the linkage disequilibrium (LD) blocks containing risk SNPs identified in genome-wide association studies (GWAS). We identified 'outside variants', defined as SNPs in weak LD with GWAS risk SNPs that physically interact with risk SNPs as part of a target gene's regulatory circuitry. These outside variants further explain variation in target gene expression beyond that explained by GWAS-associated SNPs. Additionally, the clinical risk associated with GWAS SNPs is considerably modified by the genotype of outside variants. Collectively, these findings suggest a potential model in which outside variants and GWAS SNPs that physically interact in 3D chromatin collude to influence target transcript levels as well as clinical risk. This model offers an additional hypothesis for the source of missing heritability for complex traits.

  14. On Modeling Risk Shocks

    OpenAIRE

    Dorofeenko, Victor; Lee, Gabriel; Salyer, Kevin; Strobel, Johannes

    2016-01-01

    Within the context of a financial accelerator model, we model time-varying uncertainty (i.e. risk shocks) through the use of a mixture Normal model with time variation in the weights applied to the underlying distributions characterizing entrepreneur productivity. Specifically, we model capital producers (i.e. the entrepreneurs) as either low-risk (relatively small second moment for productivity) and high-risk (relatively large second moment for productivity) and the fraction of both types is...

  15. On pseudo-values for regression analysis in competing risks models

    DEFF Research Database (Denmark)

    Graw, F; Gerds, Thomas Alexander; Schumacher, M

    2009-01-01

    For regression on state and transition probabilities in multi-state models Andersen et al. (Biometrika 90:15-27, 2003) propose a technique based on jackknife pseudo-values. In this article we analyze the pseudo-values suggested for competing risks models and prove some conjectures regarding their...

  16. Probabilistic risk analysis and terrorism risk.

    Science.gov (United States)

    Ezell, Barry Charles; Bennett, Steven P; von Winterfeldt, Detlof; Sokolowski, John; Collins, Andrew J

    2010-04-01

    Since the terrorist attacks of September 11, 2001, and the subsequent establishment of the U.S. Department of Homeland Security (DHS), considerable efforts have been made to estimate the risks of terrorism and the cost effectiveness of security policies to reduce these risks. DHS, industry, and the academic risk analysis communities have all invested heavily in the development of tools and approaches that can assist decisionmakers in effectively allocating limited resources across the vast array of potential investments that could mitigate risks from terrorism and other threats to the homeland. Decisionmakers demand models, analyses, and decision support that are useful for this task and based on the state of the art. Since terrorism risk analysis is new, no single method is likely to meet this challenge. In this article we explore a number of existing and potential approaches for terrorism risk analysis, focusing particularly on recent discussions regarding the applicability of probabilistic and decision analytic approaches to bioterrorism risks and the Bioterrorism Risk Assessment methodology used by the DHS and criticized by the National Academies and others.

  17. A suite of models to support the quantitative assessment of spread in pest risk analysis.

    Science.gov (United States)

    Robinet, Christelle; Kehlenbeck, Hella; Kriticos, Darren J; Baker, Richard H A; Battisti, Andrea; Brunel, Sarah; Dupin, Maxime; Eyre, Dominic; Faccoli, Massimo; Ilieva, Zhenya; Kenis, Marc; Knight, Jon; Reynaud, Philippe; Yart, Annie; van der Werf, Wopke

    2012-01-01

    Pest Risk Analyses (PRAs) are conducted worldwide to decide whether and how exotic plant pests should be regulated to prevent invasion. There is an increasing demand for science-based risk mapping in PRA. Spread plays a key role in determining the potential distribution of pests, but there is no suitable spread modelling tool available for pest risk analysts. Existing models are species specific, biologically and technically complex, and data hungry. Here we present a set of four simple and generic spread models that can be parameterised with limited data. Simulations with these models generate maps of the potential expansion of an invasive species at continental scale. The models have one to three biological parameters. They differ in whether they treat spatial processes implicitly or explicitly, and in whether they consider pest density or pest presence/absence only. The four models represent four complementary perspectives on the process of invasion and, because they have different initial conditions, they can be considered as alternative scenarios. All models take into account habitat distribution and climate. We present an application of each of the four models to the western corn rootworm, Diabrotica virgifera virgifera, using historic data on its spread in Europe. Further tests as proof of concept were conducted with a broad range of taxa (insects, nematodes, plants, and plant pathogens). Pest risk analysts, the intended model users, found the model outputs to be generally credible and useful. The estimation of parameters from data requires insights into population dynamics theory, and this requires guidance. If used appropriately, these generic spread models provide a transparent and objective tool for evaluating the potential spread of pests in PRAs. Further work is needed to validate models, build familiarity in the user community and create a database of species parameters to help realize their potential in PRA practice.

  18. Mare Risk Analysis monitor

    International Nuclear Information System (INIS)

    Fuente Prieto, I.; Alonso, P.; Carretero Fernandino, J. A.

    2000-01-01

    The Nuclear Safety Council's requirement that Spanish power plants comply with the requirements of the Maintenance Rule associated with plant risk assessment during power operation, arising from the partial unavailability of systems due to the maintenance activities, has led to need for additional tools to facilitate compliance with said requirements. While the impact on risk produced by individual equipment unavailabilities can easily be evaluated, either qualitatively or quantitatively, the process becomes more complicated when un programmed unavailabilities simultaneously occur in various systems, making it necessary to evaluate their functional impact. It is especially complex in the case of support systems that can affect the functionality of multiple systems. In view of the above, a computer application has been developed that is capable of providing the operator with quick answers based on the specific plant model in order to allow fast risk assessment using the information compiled as part of the Probabilistic Safety Analysis. The paper describes the most important characteristics of this application and the basic design requirements of the MARE Risk Monitor. (Author)

  19. Risk Analysis in Road Tunnels – Most Important Risk Indicators

    DEFF Research Database (Denmark)

    Berchtold, Florian; Knaust, Christian; Thöns, Sebastian

    2016-01-01

    Methodologies on fire risk analysis in road tunnels consider numerous factors affecting risks (risk indicators) and express the results by risk measures. But only few comprehensive studies on effects of risk indicators on risk measures are available. For this reason, this study quantifies...... the effects and highlights the most important risk indicators with the aim to support further developments in risk analysis. Therefore, a system model of a road tunnel was developed to determine the risk measures. The system model can be divided into three parts: the fire part connected to the fire model Fire...... Dynamics Simulator (FDS); the evacuation part connected to the evacuation model FDS+Evac; and the frequency part connected to a model to calculate the frequency of fires. This study shows that the parts of the system model (and their most important risk indicators) affect the risk measures in the following...

  20. A multi-model analysis of risk of ecosystem shifts under climate change

    International Nuclear Information System (INIS)

    Warszawski, Lila; Ostberg, Sebastian; Frieler, Katja; Lucht, Wolfgang; Schaphoff, Sibyll; Buechner, Matthias; Piontek, Franziska; Friend, Andrew; Keribin, Rozenn; Rademacher, Tim Tito; Beerling, David; Lomas, Mark; Cadule, Patricia; Ciais, Philippe; Clark, Douglas B; Kahana, Ron; Ito, Akihiko; Nishina, Kazuya; Kleidon, Axel; Pavlick, Ryan

    2013-01-01

    Climate change may pose a high risk of change to Earth’s ecosystems: shifting climatic boundaries may induce changes in the biogeochemical functioning and structures of ecosystems that render it difficult for endemic plant and animal species to survive in their current habitats. Here we aggregate changes in the biogeochemical ecosystem state as a proxy for the risk of these shifts at different levels of global warming. Estimates are based on simulations from seven global vegetation models (GVMs) driven by future climate scenarios, allowing for a quantification of the related uncertainties. 5–19% of the naturally vegetated land surface is projected to be at risk of severe ecosystem change at 2 ° C of global warming (ΔGMT) above 1980–2010 levels. However, there is limited agreement across the models about which geographical regions face the highest risk of change. The extent of regions at risk of severe ecosystem change is projected to rise with ΔGMT, approximately doubling between ΔGMT = 2 and 3 ° C, and reaching a median value of 35% of the naturally vegetated land surface for ΔGMT = 4 °C. The regions projected to face the highest risk of severe ecosystem changes above ΔGMT = 4 °C or earlier include the tundra and shrublands of the Tibetan Plateau, grasslands of eastern India, the boreal forests of northern Canada and Russia, the savanna region in the Horn of Africa, and the Amazon rainforest. (letter)

  1. Removing the age restrictions for rotavirus vaccination: a benefit-risk modeling analysis.

    Directory of Open Access Journals (Sweden)

    Manish M Patel

    Full Text Available BACKGROUND: To minimize potential risk of intussusception, the World Health Organization (WHO recommended in 2009 that rotavirus immunization should be initiated by age 15 weeks and completed before 32 weeks. These restrictions could adversely impact vaccination coverage and thereby its health impact, particularly in developing countries where delays in vaccination often occur. METHODS AND FINDINGS: We conducted a modeling study to estimate the number of rotavirus deaths prevented and the number of intussusception deaths caused by vaccination when administered on the restricted schedule versus an unrestricted schedule whereby rotavirus vaccine would be administered with DTP vaccine up to age 3 years. Countries were grouped on the basis of child mortality rates, using WHO data. Inputs were estimates of WHO rotavirus mortality by week of age from a recent study, intussusception mortality based on a literature review, predicted vaccination rates by week of age from USAID Demographic and Health Surveys, the United Nations Children's Fund (UNICEF Multiple Indicator Cluster Surveys (MICS, and WHO-UNICEF 2010 country-specific coverage estimates, and published estimates of vaccine efficacy and vaccine-associated intussusception risk. On the basis of the error estimates and distributions for model inputs, we conducted 2,000 simulations to obtain median estimates of deaths averted and caused as well as the uncertainty ranges, defined as the 5th-95th percentile, to provide an indication of the uncertainty in the estimates. We estimated that in low and low-middle income countries a restricted schedule would prevent 155,800 rotavirus deaths (5th-95th centiles, 83,300-217,700 while causing potentially 253 intussusception deaths (76-689. In contrast, vaccination without age restrictions would prevent 203,000 rotavirus deaths (102,000-281,500 while potentially causing 547 intussusception deaths (237-1,160. Thus, removing the age restrictions would avert an

  2. A spatial mean-variance MIP model for energy market risk analysis

    International Nuclear Information System (INIS)

    Yu, Zuwei

    2003-01-01

    The paper presents a short-term market risk model based on the Markowitz mean-variance method for spatial electricity markets. The spatial nature is captured using the correlation of geographically separated markets and the consideration of wheeling administration. The model also includes transaction costs and other practical constraints, resulting in a mixed integer programming (MIP) model. The incorporation of those practical constraints makes the model more attractive than the traditional Markowitz portfolio model with continuity. A case study is used to illustrate the practical application of the model. The results show that the MIP portfolio efficient frontier is neither smooth nor concave. The paper also considers the possible extension of the model to other energy markets, including natural gas and oil markets

  3. A spatial mean-variance MIP model for energy market risk analysis

    International Nuclear Information System (INIS)

    Zuwei Yu

    2003-01-01

    The paper presents a short-term market risk model based on the Markowitz mean-variance method for spatial electricity markets. The spatial nature is captured using the correlation of geographically separated markets and the consideration of wheeling administration. The model also includes transaction costs and other practical constraints, resulting in a mixed integer programming (MIP) model. The incorporation of those practical constraints makes the model more attractive than the traditional Markowitz portfolio model with continuity. A case study is used to illustrate the practical application of the model. The results show that the MIP portfolio efficient frontier is neither smooth nor concave. The paper also considers the possible extension of the model to other energy markets, including natural gas and oil markets. (author)

  4. A spatial mean-variance MIP model for energy market risk analysis

    Energy Technology Data Exchange (ETDEWEB)

    Zuwei Yu [Purdue University, West Lafayette, IN (United States). Indiana State Utility Forecasting Group and School of Industrial Engineering

    2003-05-01

    The paper presents a short-term market risk model based on the Markowitz mean-variance method for spatial electricity markets. The spatial nature is captured using the correlation of geographically separated markets and the consideration of wheeling administration. The model also includes transaction costs and other practical constraints, resulting in a mixed integer programming (MIP) model. The incorporation of those practical constraints makes the model more attractive than the traditional Markowitz portfolio model with continuity. A case study is used to illustrate the practical application of the model. The results show that the MIP portfolio efficient frontier is neither smooth nor concave. The paper also considers the possible extension of the model to other energy markets, including natural gas and oil markets. (author)

  5. A spatial mean-variance MIP model for energy market risk analysis

    Energy Technology Data Exchange (ETDEWEB)

    Yu, Zuwei [Indiana State Utility Forecasting Group and School of Industrial Engineering, Purdue University, Room 334, 1293 A.A. Potter, West Lafayette, IN 47907 (United States)

    2003-05-01

    The paper presents a short-term market risk model based on the Markowitz mean-variance method for spatial electricity markets. The spatial nature is captured using the correlation of geographically separated markets and the consideration of wheeling administration. The model also includes transaction costs and other practical constraints, resulting in a mixed integer programming (MIP) model. The incorporation of those practical constraints makes the model more attractive than the traditional Markowitz portfolio model with continuity. A case study is used to illustrate the practical application of the model. The results show that the MIP portfolio efficient frontier is neither smooth nor concave. The paper also considers the possible extension of the model to other energy markets, including natural gas and oil markets.

  6. Integrating fire behavior models and geospatial analysis for wildland fire risk assessment and fuel management planning

    Science.gov (United States)

    Alan A. Ager; Nicole M. Vaillant; Mark A. Finney

    2011-01-01

    Wildland fire risk assessment and fuel management planning on federal lands in the US are complex problems that require state-of-the-art fire behavior modeling and intensive geospatial analyses. Fuel management is a particularly complicated process where the benefits and potential impacts of fuel treatments must be demonstrated in the context of land management goals...

  7. Business model risk analysis: predicting the probability of business network profitability

    NARCIS (Netherlands)

    Johnson, Pontus; Iacob, Maria Eugenia; Valja, Margus; van Sinderen, Marten J.; Magnusson, Christer; Ladhe, Tobias; van Sinderen, Marten J.; Oude Luttighuis, P.H.W.M.; Folmer, Erwin Johan Albert; Bosems, S.

    In the design phase of business collaboration, it is desirable to be able to predict the profitability of the business-to-be. Therefore, techniques to assess qualities such as costs, revenues, risks, and profitability have been previously proposed. However, they do not allow the modeler to properly

  8. Dam break modelling, risk assessment and uncertainty analysis for flood mitigation

    NARCIS (Netherlands)

    Zagonjolli, M.

    2007-01-01

    In this thesis a range of modelling techniques is explored to deal effectively with flood risk management. In particular, attention is paid to floods caused by failure of hydraulic structures such as dams and dikes. The methods considered here are applied for simulating dam and dike failure events,

  9. Demonstration of a modelling-based multi-criteria decision analysis procedure for prioritisation of occupational risks from manufactured nanomaterials.

    Science.gov (United States)

    Hristozov, Danail; Zabeo, Alex; Alstrup Jensen, Keld; Gottardo, Stefania; Isigonis, Panagiotis; Maccalman, Laura; Critto, Andrea; Marcomini, Antonio

    2016-11-01

    Several tools to facilitate the risk assessment and management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed. This paper proposes such a quantitative risk prioritisation tool, based on a multi-criteria decision analysis algorithm, which combines advanced exposure and dose-response modelling to calculate margins of exposure (MoE) for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios (ES) involving the production and handling of nanoscale titanium dioxide, zinc oxide (ZnO), silver and multi-walled carbon nanotubes. The results of this application demonstrated that bag/bin filling, manual un/loading and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these ES. The ZnO MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritisation results. In order to study how variations in the input data affect our results, we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.

  10. A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance.

    Science.gov (United States)

    Meads, Catherine; Ahmed, Ikhlaaq; Riley, Richard D

    2012-04-01

    A risk prediction model is a statistical tool for estimating the probability that a currently healthy individual with specific risk factors will develop a condition in the future such as breast cancer. Reliably accurate prediction models can inform future disease burdens, health policies and individual decisions. Breast cancer prediction models containing modifiable risk factors, such as alcohol consumption, BMI or weight, condom use, exogenous hormone use and physical activity, are of particular interest to women who might be considering how to reduce their risk of breast cancer and clinicians developing health policies to reduce population incidence rates. We performed a systematic review to identify and evaluate the performance of prediction models for breast cancer that contain modifiable factors. A protocol was developed and a sensitive search in databases including MEDLINE and EMBASE was conducted in June 2010. Extensive use was made of reference lists. Included were any articles proposing or validating a breast cancer prediction model in a general female population, with no language restrictions. Duplicate data extraction and quality assessment were conducted. Results were summarised qualitatively, and where possible meta-analysis of model performance statistics was undertaken. The systematic review found 17 breast cancer models, each containing a different but often overlapping set of modifiable and other risk factors, combined with an estimated baseline risk that was also often different. Quality of reporting was generally poor, with characteristics of included participants and fitted model results often missing. Only four models received independent validation in external data, most notably the 'Gail 2' model with 12 validations. None of the models demonstrated consistently outstanding ability to accurately discriminate between those who did and those who did not develop breast cancer. For example, random-effects meta-analyses of the performance of the

  11. Modeling and Quantification of Team Performance in Human Reliability Analysis for Probabilistic Risk Assessment

    Energy Technology Data Exchange (ETDEWEB)

    Jeffrey C. JOe; Ronald L. Boring

    2014-06-01

    Probabilistic Risk Assessment (PRA) and Human Reliability Assessment (HRA) are important technical contributors to the United States (U.S.) Nuclear Regulatory Commission’s (NRC) risk-informed and performance based approach to regulating U.S. commercial nuclear activities. Furthermore, all currently operating commercial NPPs in the U.S. are required by federal regulation to be staffed with crews of operators. Yet, aspects of team performance are underspecified in most HRA methods that are widely used in the nuclear industry. There are a variety of "emergent" team cognition and teamwork errors (e.g., communication errors) that are 1) distinct from individual human errors, and 2) important to understand from a PRA perspective. The lack of robust models or quantification of team performance is an issue that affects the accuracy and validity of HRA methods and models, leading to significant uncertainty in estimating HEPs. This paper describes research that has the objective to model and quantify team dynamics and teamwork within NPP control room crews for risk informed applications, thereby improving the technical basis of HRA, which improves the risk-informed approach the NRC uses to regulate the U.S. commercial nuclear industry.

  12. Sensitivity analysis of the meteorological model applied in the German risk study (DRS)

    International Nuclear Information System (INIS)

    Vogt, S.

    1982-01-01

    In the first part of this paper it will be shown how the influence of uncertainties in estimation on risk statements is determined using methods of the probability theory. In particular the parameters contained in the dispersion model are studied more thoroughly. In the second part, based on the knowledge gathered in the previous investigations, new and more realistic best estimate values will be proposed for four selected parameters to be used in future work. The modifications in the risk statements by these new parameter values will be commented upon

  13. Flood risk analysis model in the village of St. George/Danube Delta

    Science.gov (United States)

    Armas, I.; Dumitrascu, S.; Nistoran, D.

    2009-04-01

    River deltas may have been cradles for prehistoric civilizations (Day et al. 2007) and still represent favoured areas for human habitats on the basis of their high productivity, biodiversity and favourable economical conditions for river transport (Giosan and Bhattacharya 2005). In the same time, these regions are defined through their high vulnerability to environmental changes, being extremely susceptible to natural disasters, especially to floods. The Danube Delta, with an area of 5640 km2, is the largest ecosystem of the European humid zones. Its state reflects environmental conditions at both local and regional levels via liquid and solid parameters and has to ensure the water supply for the local economy and communities. Flooding of the delta is important for the dynamics of the entire natural system. Floods sustain both alluvial processes and the water supply to deltaic lakes. In addition, flooding frequency is important in flushing the deltaic lake system water, ensuring a normal evolution of both terrestrial and aquatic ecosystems. For human communities, on the other hand, floods are perceived as a risk factor, entailing material damage, human victims and psychological stress. In the perspective of risk assessment research, every populated place faces a certain risk engaged by a disaster, the size of which depends on the specific location, existent hazards, vulnerability and the number of elements at risk. Although natural hazards are currently a main subject of interest on a global scale, a unitary methodological approach has yet to be developed. In the general context of hazard analysis, there is the need to put more emphasis on the problem of the risk analysis. In most cases, it focuses only on an assessment of the probable material damage resulted from a specific risk scenario. Taking these matters into consideration, the aim of this study is to develop an efficient flood risk assessment methodology based on the example of the village of St. George in

  14. Catastrophic loss risks: An economic and legal analysis, and a model state statute

    International Nuclear Information System (INIS)

    Meyer, M.B.

    1984-01-01

    Catastrophic loss risk producing facilities or activities are defined as those human enterprises which are theoretically capable of producing some credible event which entails extremely large losses of human life, health, or property. Two examples of catastrophic loss risk producing facilities are examined, commercial nuclear power plants and LNG terminals. These two types of facilities appear to produce a type of externality in that they impose uncompensated loss risk costs on neighbors. Further, these two types of facilities may be quite dependent upon the subsidies implicit in these externalities for their continued economic operation. A model state statute is proposed which would use insurance premiums as an unbiased source of probability and outcome estimates in order to eliminate this externality and the resulting subsidy, and as a way of improving the present situation within certain economic limits

  15. Contrasting safety assessments of a runway incursion scenario: Event sequence analysis versus multi-agent dynamic risk modelling

    International Nuclear Information System (INIS)

    Stroeve, Sybert H.; Blom, Henk A.P.; Bakker, G.J.

    2013-01-01

    In the safety literature it has been argued, that in a complex socio-technical system safety cannot be well analysed by event sequence based approaches, but requires to capture the complex interactions and performance variability of the socio-technical system. In order to evaluate the quantitative and practical consequences of these arguments, this study compares two approaches to assess accident risk of an example safety critical sociotechnical system. It contrasts an event sequence based assessment with a multi-agent dynamic risk model (MA-DRM) based assessment, both of which are performed for a particular runway incursion scenario. The event sequence analysis uses the well-known event tree modelling formalism and the MA-DRM based approach combines agent based modelling, hybrid Petri nets and rare event Monte Carlo simulation. The comparison addresses qualitative and quantitative differences in the methods, attained risk levels, and in the prime factors influencing the safety of the operation. The assessments show considerable differences in the accident risk implications of the performance of human operators and technical systems in the runway incursion scenario. In contrast with the event sequence based results, the MA-DRM based results show that the accident risk is not manifest from the performance of and relations between individual human operators and technical systems. Instead, the safety risk emerges from the totality of the performance and interactions in the agent based model of the safety critical operation considered, which coincides very well with the argumentation in the safety literature.

  16. Relative risk estimation of Chikungunya disease in Malaysia: An analysis based on Poisson-gamma model

    Science.gov (United States)

    Samat, N. A.; Ma'arof, S. H. Mohd Imam

    2015-05-01

    Disease mapping is a method to display the geographical distribution of disease occurrence, which generally involves the usage and interpretation of a map to show the incidence of certain diseases. Relative risk (RR) estimation is one of the most important issues in disease mapping. This paper begins by providing a brief overview of Chikungunya disease. This is followed by a review of the classical model used in disease mapping, based on the standardized morbidity ratio (SMR), which we then apply to our Chikungunya data. We then fit an extension of the classical model, which we refer to as a Poisson-Gamma model, when prior distributions for the relative risks are assumed known. Both results are displayed and compared using maps and we reveal a smoother map with fewer extremes values of estimated relative risk. The extensions of this paper will consider other methods that are relevant to overcome the drawbacks of the existing methods, in order to inform and direct government strategy for monitoring and controlling Chikungunya disease.

  17. A discriminant analysis prediction model of non-syndromic cleft lip with or without cleft palate based on risk factors.

    Science.gov (United States)

    Li, Huixia; Luo, Miyang; Luo, Jiayou; Zheng, Jianfei; Zeng, Rong; Du, Qiyun; Fang, Junqun; Ouyang, Na

    2016-11-23

    A risk prediction model of non-syndromic cleft lip with or without cleft palate (NSCL/P) was established by a discriminant analysis to predict the individual risk of NSCL/P in pregnant women. A hospital-based case-control study was conducted with 113 cases of NSCL/P and 226 controls without NSCL/P. The cases and the controls were obtained from 52 birth defects' surveillance hospitals in Hunan Province, China. A questionnaire was administered in person to collect the variables relevant to NSCL/P by face to face interviews. Logistic regression models were used to analyze the influencing factors of NSCL/P, and a stepwise Fisher discriminant analysis was subsequently used to construct the prediction model. In the univariate analysis, 13 influencing factors were related to NSCL/P, of which the following 8 influencing factors as predictors determined the discriminant prediction model: family income, maternal occupational hazards exposure, premarital medical examination, housing renovation, milk/soymilk intake in the first trimester of pregnancy, paternal occupational hazards exposure, paternal strong tea drinking, and family history of NSCL/P. The model had statistical significance (lambda = 0.772, chi-square = 86.044, df = 8, P Self-verification showed that 83.8 % of the participants were correctly predicted to be NSCL/P cases or controls with a sensitivity of 74.3 % and a specificity of 88.5 %. The area under the receiver operating characteristic curve (AUC) was 0.846. The prediction model that was established using the risk factors of NSCL/P can be useful for predicting the risk of NSCL/P. Further research is needed to improve the model, and confirm the validity and reliability of the model.

  18. Fuel prices scenario generation based on a multivariate GARCH model for risk analysis in a wholesale electricity market

    International Nuclear Information System (INIS)

    Batlle, C.; Barquin, J.

    2004-01-01

    This paper presents a fuel prices scenario generator in the frame of a simulation tool developed to support risk analysis in a competitive electricity environment. The tool feeds different erogenous risk factors to a wholesale electricity market model to perform a statistical analysis of the results. As the different fuel series that are studied, such as the oil or gas ones, present stochastic volatility and strong correlation among them, a multivariate Generalized Autoregressive Conditional Heteroskedastic (GARCH) model has been designed in order to allow the generation of future fuel prices paths. The model makes use of a decomposition method to simplify the consideration of the multidimensional conditional covariance. An example of its application with real data is also presented. (author)

  19. Products modeling for application in risk analysis, reducing uncertainties; Modelagem de produtos em estudos de risco, reduzindo incertezas

    Energy Technology Data Exchange (ETDEWEB)

    Sodre, Carlos F; Mendes, Renato F; Saker, Leonardo F [PETROBRAS Engenharia, Rio de Janeiro, RJ (Brazil); br, renatomendes@petrobras com; Oliveira, Edimilson J; Aguiar, Paulo Cesar; Pinto, Ulysses Brandao; Badaro, Sonia M [PETROBRAS, Rio de Janeiro, RJ (Brazil). Centro de Pesquisas (CENPES)

    2004-07-01

    Accidental repercussions due to hydrocarbon releases are required on risk analysis studies and contingency plans. The physical effects estimation from releases on vessels or pipelines through out orifices and the estimation of limits for vapor cloud require several modeling, such us: pseudo-mixture estimation, source calculation and dispersion models. These models require physical and chemical properties of the real products in study, so a deep analysis of the original product and the recommended mixtures is demanded. This paper assesses some PETROBRAS refined products and defines pseudo-mixture in order to emulate the physical and chemical properties, for these original products. Finally, it was suggested mixture profiles for some products such as, gasoline, diesel and crude (light), to be applied in next risk studies. (author)

  20. Information Security Risk Analysis

    CERN Document Server

    Peltier, Thomas R

    2010-01-01

    Offers readers with the knowledge and the skill-set needed to achieve a highly effective risk analysis assessment. This title demonstrates how to identify threats and then determine if those threats pose a real risk. It is suitable for industry and academia professionals.

  1. Optimal timing of vitamin K antagonist resumption after upper gastrointestinal bleeding. A risk modelling analysis.

    Science.gov (United States)

    Majeed, Ammar; Wallvik, Niklas; Eriksson, Joakim; Höijer, Jonas; Bottai, Matteo; Holmström, Margareta; Schulman, Sam

    2017-02-28

    The optimal timing of vitamin K antagonists (VKAs) resumption after an upper gastrointestinal (GI) bleeding, in patients with continued indication for oral anticoagulation, is uncertain. We included consecutive cases of VKA-associated upper GI bleeding from three hospitals retrospectively. Data on the bleeding location, timing of VKA resumption, recurrent GI bleeding and thromboembolic events were collected. A model was constructed to evaluate the 'total risk', based on the sum of the cumulative rates of recurrent GI bleeding and thromboembolic events, depending on the timing of VKA resumption. A total of 121 (58 %) of 207 patients with VKA-associated upper GI bleeding were restarted on anticoagulation after a median (interquartile range) of one (0.2-3.4) week after the index bleeding. Restarting VKAs was associated with a reduced risk of thromboembolism (HR 0.19; 95 % CI, 0.07-0.55) and death (HR 0.61; 95 % CI, 0.39-0.94), but with an increased risk of recurrent GI bleeding (HR 2.5; 95 % CI, 1.4-4.5). The composite risk obtained from the combined statistical model of recurrent GI bleeding, and thromboembolism decreased if VKAs were resumed after three weeks and reached a nadir at six weeks after the index GI bleeding. On this background we will discuss how the disutility of the outcomes may influence the decision regarding timing of resumption. In conclusion, the optimal timing of VKA resumption after VKA-associated upper GI bleeding appears to be between 3-6 weeks after the index bleeding event but has to take into account the degree of thromboembolic risk, patient values and preferences.

  2. Wildfire Risk Main Model

    Data.gov (United States)

    Earth Data Analysis Center, University of New Mexico — The model combines three modeled fire behavior parameters (rate of spread, flame length, crown fire potential) and one modeled ecological health measure (fire regime...

  3. An application of a grey data envelopment analysis model to the risk comparative analysis among power generation technologies

    International Nuclear Information System (INIS)

    Garcia, Pauli A.A.; Melo, P.F. Frutuoso e

    2005-01-01

    The comparative risk analysis is a technique for which one seeks equilibrium among benefits, costs, and risks associated with common-purpose activities performed. In light of the ever-growing world demand for a sustainable power supply, we present in this paper a comparison among different power generation technologies. The data for the comparative analyses has been taken from the literature. A hybrid approach is proposed for performing the comparisons, in which the Grey System Theory and the Data Envelopment Analysis (DEA) are combined. The purpose of this combination is to take into account different features that influence the risk analysis, when one aims to compare different power generation technologies. The generation technologies considered here are: solar, biomass, wind, hydroelectric, oil, natural gas, coal, and nuclear. The criteria considered in the analysis are: contribution to the life expectancy reduction (in years); contribution to the life expectancy growth (in years); used area (in km 2 ); tons of released CO 2 per GWh generated. The results obtained by using the aforementioned approach are promising and demonstrate the advantages of the Grey-DEA approach for the problem at hand. The results show that investments in the nuclear and solar power generation technologies are the options that present the best relative efficiencies, that is, among all considered options, they presented the best cost-benefit-risk relationships. (author)

  4. The supervisor's portfolio: the market price risk of German banks from 2001 to 2003 - Analysis and models for risk aggregation

    OpenAIRE

    Memmel, Christoph; Wehn, Carsten

    2005-01-01

    The Value at Risk of a portfolio differs from the sum of the Values at Risk of the portfolio's components. In this paper, we analyze the problem of how a single economic risk figure for the Value at Risk of a hypothetical portfolio composed of different commercial banks might be obtained for a supervisor. Using the daily profits and losses and the daily Value at Risk figures of twelve German banks for the period from 2001 to 2003, we estimate the Value at Risk of the entire portfolio. We assu...

  5. Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis.

    Science.gov (United States)

    Shearer, Freya M; Longbottom, Joshua; Browne, Annie J; Pigott, David M; Brady, Oliver J; Kraemer, Moritz U G; Marinho, Fatima; Yactayo, Sergio; de Araújo, Valdelaine E M; da Nóbrega, Aglaêr A; Fullman, Nancy; Ray, Sarah E; Mosser, Jonathan F; Stanaway, Jeffrey D; Lim, Stephen S; Reiner, Robert C; Moyes, Catherine L; Hay, Simon I; Golding, Nick

    2018-03-01

    Yellow fever cases are under-reported and the exact distribution of the disease is unknown. An effective vaccine is available but more information is needed about which populations within risk zones should be targeted to implement interventions. Substantial outbreaks of yellow fever in Angola, Democratic Republic of the Congo, and Brazil, coupled with the global expansion of the range of its main urban vector, Aedes aegypti, suggest that yellow fever has the propensity to spread further internationally. The aim of this study was to estimate the disease's contemporary distribution and potential for spread into new areas to help inform optimal control and prevention strategies. We assembled 1155 geographical records of yellow fever virus infection in people from 1970 to 2016. We used a Poisson point process boosted regression tree model that explicitly incorporated environmental and biological explanatory covariates, vaccination coverage, and spatial variability in disease reporting rates to predict the relative risk of apparent yellow fever virus infection at a 5 × 5 km resolution across all risk zones (47 countries across the Americas and Africa). We also used the fitted model to predict the receptivity of areas outside at-risk zones to the introduction or reintroduction of yellow fever transmission. By use of previously published estimates of annual national case numbers, we used the model to map subnational variation in incidence of yellow fever across at-risk countries and to estimate the number of cases averted by vaccination worldwide. Substantial international and subnational spatial variation exists in relative risk and incidence of yellow fever as well as varied success of vaccination in reducing incidence in several high-risk regions, including Brazil, Cameroon, and Togo. Areas with the highest predicted average annual case numbers include large parts of Nigeria, the Democratic Republic of the Congo, and South Sudan, where vaccination coverage in 2016

  6. Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis

    Directory of Open Access Journals (Sweden)

    Freya M Shearer, BSc

    2018-03-01

    Full Text Available Summary: Background: Yellow fever cases are under-reported and the exact distribution of the disease is unknown. An effective vaccine is available but more information is needed about which populations within risk zones should be targeted to implement interventions. Substantial outbreaks of yellow fever in Angola, Democratic Republic of the Congo, and Brazil, coupled with the global expansion of the range of its main urban vector, Aedes aegypti, suggest that yellow fever has the propensity to spread further internationally. The aim of this study was to estimate the disease's contemporary distribution and potential for spread into new areas to help inform optimal control and prevention strategies. Methods: We assembled 1155 geographical records of yellow fever virus infection in people from 1970 to 2016. We used a Poisson point process boosted regression tree model that explicitly incorporated environmental and biological explanatory covariates, vaccination coverage, and spatial variability in disease reporting rates to predict the relative risk of apparent yellow fever virus infection at a 5 × 5 km resolution across all risk zones (47 countries across the Americas and Africa. We also used the fitted model to predict the receptivity of areas outside at-risk zones to the introduction or reintroduction of yellow fever transmission. By use of previously published estimates of annual national case numbers, we used the model to map subnational variation in incidence of yellow fever across at-risk countries and to estimate the number of cases averted by vaccination worldwide. Findings: Substantial international and subnational spatial variation exists in relative risk and incidence of yellow fever as well as varied success of vaccination in reducing incidence in several high-risk regions, including Brazil, Cameroon, and Togo. Areas with the highest predicted average annual case numbers include large parts of Nigeria, the Democratic Republic of the

  7. Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

    Science.gov (United States)

    Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

    2017-12-01

    Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

  8. Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

    Science.gov (United States)

    Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

    2018-06-01

    Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

  9. Melanoma Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing melanoma cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  10. Uncertainty analysis in estimating Japanese ingestion of global fallout Cs-137 using health risk evaluation model

    International Nuclear Information System (INIS)

    Shimada, Yoko; Morisawa, Shinsuke

    1998-01-01

    Most of model estimation of the environmental contamination includes some uncertainty associated with the parameter uncertainty in the model. In this study, the uncertainty was analyzed in a model for evaluating the ingestion of radionuclide caused by the long-term global low-level radioactive contamination by using various uncertainty analysis methods: the percentile estimate, the robustness analysis and the fuzzy estimate. The model is mainly composed of five sub-models, which include their own uncertainty; we also analyzed the uncertainty. The major findings obtained in this study include that the possibility of the discrepancy between predicted value by the model simulation and the observed data is less than 10%; the uncertainty of the predicted value is higher before 1950 and after 1980; the uncertainty of the predicted value can be reduced by decreasing the uncertainty of some environmental parameters in the model; the reliability of the model can definitively depend on the following environmental factors: direct foliar absorption coefficient, transfer factor of radionuclide from stratosphere down to troposphere, residual rate by food processing and cooking, transfer factor of radionuclide in ocean and sedimentation in ocean. (author)

  11. Structural models of public risk perception of radioactive substances in food. An analysis of the data from internet survey

    International Nuclear Information System (INIS)

    Kito, Yayoi; Niiyama, Yoko

    2012-01-01

    In risk communication of food contamination by radioactive substances derived from the accident at Fukushima Daiichi nuclear power plant, it is required that experts, government and the public exchange information and opinions and establish a mutual understanding. To meet these requirements, it is necessary to investigate public risk perception and the structure of perception. We conducted a series of internet surveys in 2011-2012, two times in Kanto- and Kansai-area on men and women aged from 30 to 49 who have children, and once in all parts of Japan on women aged from 20 to 59. From the data analysis, we identified the feature of risk perception of radioactive substances and buying behavior, and moreover, we analyzed the relationship among the perceived risks and other factors using Structural Equation Modeling. (author)

  12. Competing Risks and Multistate Models with R

    CERN Document Server

    Beyersmann, Jan; Schumacher, Martin

    2012-01-01

    This book covers competing risks and multistate models, sometimes summarized as event history analysis. These models generalize the analysis of time to a single event (survival analysis) to analysing the timing of distinct terminal events (competing risks) and possible intermediate events (multistate models). Both R and multistate methods are promoted with a focus on nonparametric methods.

  13. Risk based modelling

    International Nuclear Information System (INIS)

    Chapman, O.J.V.; Baker, A.E.

    1993-01-01

    Risk based analysis is a tool becoming available to both engineers and managers to aid decision making concerning plant matters such as In-Service Inspection (ISI). In order to develop a risk based method, some form of Structural Reliability Risk Assessment (SRRA) needs to be performed to provide a probability of failure ranking for all sites around the plant. A Probabilistic Risk Assessment (PRA) can then be carried out to combine these possible events with the capability of plant safety systems and procedures, to establish the consequences of failure for the sites. In this way the probability of failures are converted into a risk based ranking which can be used to assist the process of deciding which sites should be included in an ISI programme. This paper reviews the technique and typical results of a risk based ranking assessment carried out for nuclear power plant pipework. (author)

  14. Component of the risk analysis

    International Nuclear Information System (INIS)

    Martinez, I.; Campon, G.

    2013-01-01

    The power point presentation reviews issues like analysis of risk (Codex), management risk, preliminary activities manager, relationship between government and industries, microbiological danger and communication of risk

  15. Risk Analysis on Leakage Failure of Natural Gas Pipelines by Fuzzy Bayesian Network with a Bow-Tie Model

    Directory of Open Access Journals (Sweden)

    Xian Shan

    2017-01-01

    Full Text Available Pipeline is the major mode of natural gas transportation. Leakage of natural gas pipelines may cause explosions and fires, resulting in casualties, environmental damage, and material loss. Efficient risk analysis is of great significance for preventing and mitigating such potential accidents. The objective of this study is to present a practical risk assessment method based on Bow-tie model and Bayesian network for risk analysis of natural gas pipeline leakage. Firstly, identify the potential risk factors and consequences of the failure. Then construct the Bow-tie model, use the quantitative analysis of Bayesian network to find the weak links in the system, and make a prediction of the control measures to reduce the rate of the accident. In order to deal with the uncertainty existing in the determination of the probability of basic events, fuzzy logic method is used. Results of a case study show that the most likely causes of natural gas pipeline leakage occurrence are parties ignore signage, implicit signage, overload, and design defect of auxiliaries. Once the leakage occurs, it is most likely to result in fire and explosion. Corresponding measures taken on time will reduce the disaster degree of accidents to the least extent.

  16. Gravity models to classify commuting vs. resident workers. An application to the analysis of residential risk in a contaminated area

    Science.gov (United States)

    2011-01-01

    Background The analysis of risk for the population residing and/or working in contaminated areas raises the topic of commuting. In fact, especially in contaminated areas, commuting groups are likely to be subject to lower exposure than residents. Only very recently environmental epidemiology has started considering the role of commuting as a differential source of exposure in contaminated areas. In order to improve the categorization of groups, this paper applies a gravitational model to the analysis of residential risk for workers in the Gela petrochemical complex, which began life in the early 60s in the municipality of Gela (Sicily, Italy) and is the main source of industrial pollution in the local area. Results A logistic regression model is implemented to measure the capacity of Gela "central location" to attract commuting flows from other sites. Drawing from gravity models, the proposed methodology: a) defines the probability of finding commuters from municipalities outside Gela as a function of the origin's "economic mass" and of its distance from each destination; b) establishes "commuting thresholds" relative to the origin's mass. The analysis includes 367 out of the 390 Sicilian municipalities. Results are applied to define "commuters" and "residents" within the cohort of petrochemical workers. The study population is composed of 5,627 workers. Different categories of residence in Gela are compared calculating Mortality Rate Ratios for lung cancer through a Poisson regression model, controlling for age and calendar period. The mobility model correctly classifies almost 90% of observations. Its application to the mortality analysis confirms a major risk for lung cancer associated with residence in Gela. Conclusions Commuting is a critical aspect of the health-environment relationship in contaminated areas. The proposed methodology can be replicated to different contexts when residential information is lacking or unreliable; however, a careful consideration

  17. Gravity models to classify commuting vs. resident workers. An application to the analysis of residential risk in a contaminated area

    Directory of Open Access Journals (Sweden)

    La Rocca Marina

    2011-01-01

    Full Text Available Abstract Background The analysis of risk for the population residing and/or working in contaminated areas raises the topic of commuting. In fact, especially in contaminated areas, commuting groups are likely to be subject to lower exposure than residents. Only very recently environmental epidemiology has started considering the role of commuting as a differential source of exposure in contaminated areas. In order to improve the categorization of groups, this paper applies a gravitational model to the analysis of residential risk for workers in the Gela petrochemical complex, which began life in the early 60s in the municipality of Gela (Sicily, Italy and is the main source of industrial pollution in the local area. Results A logistic regression model is implemented to measure the capacity of Gela "central location" to attract commuting flows from other sites. Drawing from gravity models, the proposed methodology: a defines the probability of finding commuters from municipalities outside Gela as a function of the origin's "economic mass" and of its distance from each destination; b establishes "commuting thresholds" relative to the origin's mass. The analysis includes 367 out of the 390 Sicilian municipalities. Results are applied to define "commuters" and "residents" within the cohort of petrochemical workers. The study population is composed of 5,627 workers. Different categories of residence in Gela are compared calculating Mortality Rate Ratios for lung cancer through a Poisson regression model, controlling for age and calendar period. The mobility model correctly classifies almost 90% of observations. Its application to the mortality analysis confirms a major risk for lung cancer associated with residence in Gela. Conclusions Commuting is a critical aspect of the health-environment relationship in contaminated areas. The proposed methodology can be replicated to different contexts when residential information is lacking or unreliable

  18. A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation

    International Nuclear Information System (INIS)

    Trucco, P.; Cagno, E.; Ruggeri, F.; Grande, O.

    2008-01-01

    The paper presents an innovative approach to integrate Human and Organisational Factors (HOF) into risk analysis. The approach has been developed and applied to a case study in the maritime industry, but it can also be utilised in other sectors. A Bayesian Belief Network (BBN) has been developed to model the Maritime Transport System (MTS), by taking into account its different actors (i.e., ship-owner, shipyard, port and regulator) and their mutual influences. The latter have been modelled by means of a set of dependent variables whose combinations express the relevant functions performed by each actor. The BBN model of the MTS has been used in a case study for the quantification of HOF in the risk analysis carried out at the preliminary design stage of High Speed Craft (HSC). The study has focused on a collision in open sea hazard carried out by means of an original method of integration of a Fault Tree Analysis (FTA) of technical elements with a BBN model of the influences of organisational functions and regulations, as suggested by the International Maritime Organisation's (IMO) Guidelines for Formal Safety Assessment (FSA). The approach has allowed the identification of probabilistic correlations between the basic events of a collision accident and the BBN model of the operational and organisational conditions. The linkage can be exploited in different ways, especially to support identification and evaluation of risk control options also at the organisational level. Conditional probabilities for the BBN have been estimated by means of experts' judgments, collected from an international panel of different European countries. Finally, a sensitivity analysis has been carried out over the model to identify configurations of the MTS leading to a significant reduction of accident probability during the operation of the HSC

  19. A scenario-based modeling approach for emergency evacuation management and risk analysis under multiple uncertainties

    Energy Technology Data Exchange (ETDEWEB)

    Lv, Y., E-mail: lvyying@hotmail.com [School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044 (China); Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Huang, G.H., E-mail: huang@iseis.org [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Guo, L., E-mail: guoli8658@hotmail.com [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada); Li, Y.P., E-mail: yongping.li@iseis.org [MOE Key Laboratory of Regional Energy and Environmental Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China); Dai, C., E-mail: daichao321@gmail.com [College of Environmental Sciences and Engineering, Peking University, Beijing 100871 (China); Wang, X.W., E-mail: wangxingwei0812@gamil.com [State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875 (China); Sun, W., E-mail: sunwei@iseis.org [Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2 (Canada)

    2013-02-15

    Highlights: ► An interval-parameter joint-probabilistic integer programming method is developed. ► It is useful for nuclear emergency management practices under uncertainties. ► It can schedule optimal routes with maximizing evacuees during a finite time. ► Scenario-based analysis enhances robustness in controlling system risk. ► The method will help to improve the capability of disaster responses. -- Abstract: Nuclear emergency evacuation is important to prevent radioactive harms by hazardous materials and to limit the accidents’ consequences; however, uncertainties are involved in the components and processes of such a management system. In the study, an interval-parameter joint-probabilistic integer programming (IJIP) method is developed for emergency evacuation management under uncertainties. Optimization techniques of interval-parameter programming (IPP) and joint-probabilistic constrained (JPC) programming are incorporated into an integer linear programming framework, so that the approach can deal with uncertainties expressed as joint probability and interval values. The IJIP method can schedule the optimal routes to guarantee the maximum population evacuated away from the effected zone during a finite time. Furthermore, it can also facilitate post optimization analysis to enhance robustness in controlling system violation risk imposed on the joint-probabilistic constraints. The developed method has been applied to a case study of nuclear emergency management; meanwhile, a number of scenarios under different system conditions have been analyzed. It is indicated that the solutions are useful for evacuation management practices. The result of the IJIP method can not only help to raise the capability of disaster responses in a systematic manner, but also provide an insight into complex relationships among evacuation planning, resources utilizations, policy requirements and system risks.

  20. Schistosoma mansoni reinfection: Analysis of risk factors by classification and regression tree (CART modeling.

    Directory of Open Access Journals (Sweden)

    Andréa Gazzinelli

    Full Text Available Praziquantel (PZQ is an effective chemotherapy for schistosomiasis mansoni and a mainstay for its control and potential elimination. However, it does not prevent against reinfection, which can occur rapidly in areas with active transmission. A guide to ranking the risk factors for Schistosoma mansoni reinfection would greatly contribute to prioritizing resources and focusing prevention and control measures to prevent rapid reinfection. The objective of the current study was to explore the relationship among the socioeconomic, demographic, and epidemiological factors that can influence reinfection by S. mansoni one year after successful treatment with PZQ in school-aged children in Northeastern Minas Gerais state Brazil. Parasitological, socioeconomic, demographic, and water contact information were surveyed in 506 S. mansoni-infected individuals, aged 6 to 15 years, resident in these endemic areas. Eligible individuals were treated with PZQ until they were determined to be negative by the absence of S. mansoni eggs in the feces on two consecutive days of Kato-Katz fecal thick smear. These individuals were surveyed again 12 months from the date of successful treatment with PZQ. A classification and regression tree modeling (CART was then used to explore the relationship between socioeconomic, demographic, and epidemiological variables and their reinfection status. The most important risk factor identified for S. mansoni reinfection was their "heavy" infection at baseline. Additional analyses, excluding heavy infection status, showed that lower socioeconomic status and a lower level of education of the household head were also most important risk factors for S. mansoni reinfection. Our results provide an important contribution toward the control and possible elimination of schistosomiasis by identifying three major risk factors that can be used for targeted treatment and monitoring of reinfection. We suggest that control measures that target

  1. STOCHASTIC METHODS IN RISK ANALYSIS

    Directory of Open Access Journals (Sweden)

    Vladimíra OSADSKÁ

    2017-06-01

    Full Text Available In this paper, we review basic stochastic methods which can be used to extend state-of-the-art deterministic analytical methods for risk analysis. We can conclude that the standard deterministic analytical methods highly depend on the practical experience and knowledge of the evaluator and therefore, the stochastic methods should be introduced. The new risk analysis methods should consider the uncertainties in input values. We present how large is the impact on the results of the analysis solving practical example of FMECA with uncertainties modelled using Monte Carlo sampling.

  2. Development and Sensitivity Analysis of a Frost Risk model based primarily on freely distributed Earth Observation data

    Science.gov (United States)

    Louka, Panagiota; Petropoulos, George; Papanikolaou, Ioannis

    2015-04-01

    The ability to map the spatiotemporal distribution of extreme climatic conditions, such as frost, is a significant tool in successful agricultural management and decision making. Nowadays, with the development of Earth Observation (EO) technology, it is possible to obtain accurately, timely and in a cost-effective way information on the spatiotemporal distribution of frost conditions, particularly over large and otherwise inaccessible areas. The present study aimed at developing and evaluating a frost risk prediction model, exploiting primarily EO data from MODIS and ASTER sensors and ancillary ground observation data. For the evaluation of our model, a region in north-western Greece was selected as test site and a detailed sensitivity analysis was implemented. The agreement between the model predictions and the observed (remotely sensed) frost frequency obtained by MODIS sensor was evaluated thoroughly. Also, detailed comparisons of the model predictions were performed against reference frost ground observations acquired from the Greek Agricultural Insurance Organization (ELGA) over a period of 10-years (2000-2010). Overall, results evidenced the ability of the model to produce reasonably well the frost conditions, following largely explainable patterns in respect to the study site and local weather conditions characteristics. Implementation of our proposed frost risk model is based primarily on satellite imagery analysis provided nowadays globally at no cost. It is also straightforward and computationally inexpensive, requiring much less effort in comparison for example to field surveying. Finally, the method is adjustable to be potentially integrated with other high resolution data available from both commercial and non-commercial vendors. Keywords: Sensitivity analysis, frost risk mapping, GIS, remote sensing, MODIS, Greece

  3. Revised Risk Priority Number in Failure Mode and Effects Analysis Model from the Perspective of Healthcare System

    Science.gov (United States)

    Rezaei, Fatemeh; Yarmohammadian, Mohmmad H.; Haghshenas, Abbas; Fallah, Ali; Ferdosi, Masoud

    2018-01-01

    Background: Methodology of Failure Mode and Effects Analysis (FMEA) is known as an important risk assessment tool and accreditation requirement by many organizations. For prioritizing failures, the index of “risk priority number (RPN)” is used, especially for its ease and subjective evaluations of occurrence, the severity and the detectability of each failure. In this study, we have tried to apply FMEA model more compatible with health-care systems by redefining RPN index to be closer to reality. Methods: We used a quantitative and qualitative approach in this research. In the qualitative domain, focused groups discussion was used to collect data. A quantitative approach was used to calculate RPN score. Results: We have studied patient's journey in surgery ward from holding area to the operating room. The highest priority failures determined based on (1) defining inclusion criteria as severity of incident (clinical effect, claim consequence, waste of time and financial loss), occurrence of incident (time - unit occurrence and degree of exposure to risk) and preventability (degree of preventability and defensive barriers) then, (2) risks priority criteria quantified by using RPN index (361 for the highest rate failure). The ability of improved RPN scores reassessed by root cause analysis showed some variations. Conclusions: We concluded that standard criteria should be developed inconsistent with clinical linguistic and special scientific fields. Therefore, cooperation and partnership of technical and clinical groups are necessary to modify these models. PMID:29441184

  4. Revised risk priority number in failure mode and effects analysis model from the perspective of healthcare system

    Directory of Open Access Journals (Sweden)

    Fatemeh Rezaei

    2018-01-01

    Full Text Available Background: Methodology of Failure Mode and Effects Analysis (FMEA is known as an important risk assessment tool and accreditation requirement by many organizations. For prioritizing failures, the index of “risk priority number (RPN” is used, especially for its ease and subjective evaluations of occurrence, the severity and the detectability of each failure. In this study, we have tried to apply FMEA model more compatible with health-care systems by redefining RPN index to be closer to reality. Methods: We used a quantitative and qualitative approach in this research. In the qualitative domain, focused groups discussion was used to collect data. A quantitative approach was used to calculate RPN score. Results: We have studied patient's journey in surgery ward from holding area to the operating room. The highest priority failures determined based on (1 defining inclusion criteria as severity of incident (clinical effect, claim consequence, waste of time and financial loss, occurrence of incident (time - unit occurrence and degree of exposure to risk and preventability (degree of preventability and defensive barriers then, (2 risks priority criteria quantified by using RPN index (361 for the highest rate failure. The ability of improved RPN scores reassessed by root cause analysis showed some variations. Conclusions: We concluded that standard criteria should be developed inconsistent with clinical linguistic and special scientific fields. Therefore, cooperation and partnership of technical and clinical groups are necessary to modify these models.

  5. Cluster Risk of Walking Scenarios Based on Macroscopic Flow Model and Crowding Force Analysis

    Directory of Open Access Journals (Sweden)

    Xiaohong Li

    2018-02-01

    Full Text Available In recent years, accidents always happen in confined space such as metro stations because of congestion. Various researchers investigated the patterns of dense crowd behaviors in different scenarios via simulations or experiments and proposed methods for avoiding accidents. In this study, a classic continuum macroscopic model was applied to simulate the crowded pedestrian flow in typical scenarios such as at bottlenecks or with an obstacle. The Lax–Wendroff finite difference scheme and artificial viscosity filtering method were used to discretize the model to identify high-density risk areas. Furthermore, we introduced a contact crowding force test of the interactions among pedestrians at bottlenecks. Results revealed that in the most dangerous area, the individual on the corner position bears the maximum pressure in such scenarios is 90.2 N, and there is an approximate exponential relationship between crowding force and density indicated by our data. The results and findings presented in this paper can facilitate more reasonable and precise simulation models by utilizing crowding force and crowd density and ensure the safety of pedestrians in high-density scenarios.

  6. Campylobacter Risk Analysis

    DEFF Research Database (Denmark)

    Nauta, Maarten

    In several countries quantitative microbiological risk assessments (QMRAs) have been performed for Campylobacter in chicken meat. The models constructed for this purpose provide a good example of the development of QMRA in general and illustrate the diversity of available methods. Despite...... the differences between the models, the most prominent conclusions of the QMRAs are similar. These conclusions for example relate to the large risk of highly contaminated meat products and the insignificance of contamination from Campylobacter positive flocks to negative flocks during slaughter and processing...

  7. Collision risk-capacity tradeoff analysis of an en-route corridor model

    Directory of Open Access Journals (Sweden)

    Ye Bojia

    2014-02-01

    Full Text Available Flow corridors are a new class of trajectory-based airspace which derives from the next generation air transportation system concept of operations. Reducing the airspace complexity and increasing the capacity are the main purposes of the en-route corridor. This paper analyzes the collision risk-capacity tradeoff using a combined discrete–continuous simulation method. A basic two-dimensional en-route flow corridor with performance rules is designed as the operational environment. A second-order system is established by combining the point mass model and the proportional derivative controller together to simulate the self-separation operations of the aircrafts in the corridor and the operation performance parameters from the User Manual for the Base of Aircraft Data are used in this research in order to improve the reliability. Simulation results indicate that the aircrafts can self-separate from each other efficiently by adjusting their velocities, and rationally setting the values of some variables can improve the rate and stability of the corridor with low risks of loss of separation.

  8. INCLUDING RISK IN ECONOMIC FEASIBILITY ANALYSIS:A STOCHASTIC SIMULATION MODEL FOR BLUEBERRY INVESTMENT DECISIONS IN CHILE

    Directory of Open Access Journals (Sweden)

    GERMÁN LOBOS

    2015-12-01

    Full Text Available ABSTRACT The traditional method of net present value (NPV to analyze the economic profitability of an investment (based on a deterministic approach does not adequately represent the implicit risk associated with different but correlated input variables. Using a stochastic simulation approach for evaluating the profitability of blueberry (Vaccinium corymbosum L. production in Chile, the objective of this study is to illustrate the complexity of including risk in economic feasibility analysis when the project is subject to several but correlated risks. The results of the simulation analysis suggest that the non-inclusion of the intratemporal correlation between input variables underestimate the risk associated with investment decisions. The methodological contribution of this study illustrates the complexity of the interrelationships between uncertain variables and their impact on the convenience of carrying out this type of business in Chile. The steps for the analysis of economic viability were: First, adjusted probability distributions for stochastic input variables (SIV were simulated and validated. Second, the random values of SIV were used to calculate random values of variables such as production, revenues, costs, depreciation, taxes and net cash flows. Third, the complete stochastic model was simulated with 10,000 iterations using random values for SIV. This result gave information to estimate the probability distributions of the stochastic output variables (SOV such as the net present value, internal rate of return, value at risk, average cost of production, contribution margin and return on capital. Fourth, the complete stochastic model simulation results were used to analyze alternative scenarios and provide the results to decision makers in the form of probabilities, probability distributions, and for the SOV probabilistic forecasts. The main conclusion shown that this project is a profitable alternative investment in fruit trees in

  9. Applying data envelopment analysis to preventive medicine: a novel method for constructing a personalized risk model of obesity.

    Directory of Open Access Journals (Sweden)

    Hiroto Narimatsu

    Full Text Available Data envelopment analysis (DEA is a method of operations research that has not yet been applied in the field of obesity research. However, DEA might be used to evaluate individuals' susceptibility to obesity, which could help establish effective risk models for the onset of obesity. Therefore, we conducted this study to evaluate the feasibility of applying DEA to predict obesity, by calculating efficiency scores and evaluating the usefulness of risk models. In this study, we evaluated data from the Takahata study, which was a population-based cohort study (with a follow-up study of Japanese people who are >40 years old. For our analysis, we used the input-oriented Charnes-Cooper-Rhodes model of DEA, and defined the decision-making units (DMUs as individual subjects. The inputs were defined as (1 exercise (measured as calories expended and (2 the inverse of food intake (measured as calories ingested. The output was defined as the inverse of body mass index (BMI. Using the β coefficients for the participants' single nucleotide polymorphisms, we then calculated their genetic predisposition score (GPS. Both efficiency scores and GPS were available for 1,620 participants from the baseline survey, and for 708 participants from the follow-up survey. To compare the strengths of the associations, we used models of multiple linear regressions. To evaluate the effects of genetic factors and efficiency score on body mass index (BMI, we used multiple linear regression analysis, with BMI as the dependent variable, GPS and efficiency scores as the explanatory variables, and several demographic controls, including age and sex. Our results indicated that all factors were statistically significant (p < 0.05, with an adjusted R2 value of 0.66. Therefore, it is possible to use DEA to predict environmentally driven obesity, and thus to establish a well-fitted model for risk of obesity.

  10. Breast cancer risks and risk prediction models.

    Science.gov (United States)

    Engel, Christoph; Fischer, Christine

    2015-02-01

    BRCA1/2 mutation carriers have a considerably increased risk to develop breast and ovarian cancer. The personalized clinical management of carriers and other at-risk individuals depends on precise knowledge of the cancer risks. In this report, we give an overview of the present literature on empirical cancer risks, and we describe risk prediction models that are currently used for individual risk assessment in clinical practice. Cancer risks show large variability between studies. Breast cancer risks are at 40-87% for BRCA1 mutation carriers and 18-88% for BRCA2 mutation carriers. For ovarian cancer, the risk estimates are in the range of 22-65% for BRCA1 and 10-35% for BRCA2. The contralateral breast cancer risk is high (10-year risk after first cancer 27% for BRCA1 and 19% for BRCA2). Risk prediction models have been proposed to provide more individualized risk prediction, using additional knowledge on family history, mode of inheritance of major genes, and other genetic and non-genetic risk factors. User-friendly software tools have been developed that serve as basis for decision-making in family counseling units. In conclusion, further assessment of cancer risks and model validation is needed, ideally based on prospective cohort studies. To obtain such data, clinical management of carriers and other at-risk individuals should always be accompanied by standardized scientific documentation.

  11. Application of fire models for risk analysis in french nuclear power plants

    International Nuclear Information System (INIS)

    Brauns, P.

    1989-04-01

    Numerical simulations of compartment fires have been carried out in the French 900 MW and 1 300 MW nuclear power plants, to obtain quantitative data about this particular kind of risk: characteristic spreading times from one redundant electrical train to the other one, behaviour of important electrical components... The main stages of both studies were the following: selection of rooms, the location or function of which are essential for the plant safety in case of fire, on-site inspections to collect information about these rooms (amount of fuel, openings...), definition of fire scenarios, improvement of the fire model VESTA-PLUS, and, finally calculations using this computer code. The simulations have shown two major trends: i) the spreading times, without taking into account any external intervention, are always greater than half an hour, and ii) the specific design of the 1 300 MW power plants generally prevents one of the redundant train from being damaged due to a fire occurring in a room containing the other one. Examples of typical results obtained are given, showing the capability of application of the improved fire model to complex problems

  12. Risk Analysis Using Modeling and Simulation of Organizational Structure and Behavior, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Most major accidents do not result simply from proximal, physical events, but from the gradual drift of an organization to a state of heightened risk. Risk often...

  13. Spatiotemporal Modeling of Community Risk

    Science.gov (United States)

    2016-03-01

    Ertugay, and Sebnem Duzgun, “Exploratory and Inferential Methods for Spatio-Temporal Analysis of Residential Fire Clustering in Urban Areas,” Fire ...response in communities.”26 In “Exploratory and Inferential Methods for Spatio-temporal Analysis of Residential Fire Clustering in Urban Areas,” Ceyhan...of fire resources spread across the community. Spatiotemporal modeling shows that actualized risk is dynamic and relatively patterned. Though

  14. Quantile uncertainty and value-at-risk model risk.

    Science.gov (United States)

    Alexander, Carol; Sarabia, José María

    2012-08-01

    This article develops a methodology for quantifying model risk in quantile risk estimates. The application of quantile estimates to risk assessment has become common practice in many disciplines, including hydrology, climate change, statistical process control, insurance and actuarial science, and the uncertainty surrounding these estimates has long been recognized. Our work is particularly important in finance, where quantile estimates (called Value-at-Risk) have been the cornerstone of banking risk management since the mid 1980s. A recent amendment to the Basel II Accord recommends additional market risk capital to cover all sources of "model risk" in the estimation of these quantiles. We provide a novel and elegant framework whereby quantile estimates are adjusted for model risk, relative to a benchmark which represents the state of knowledge of the authority that is responsible for model risk. A simulation experiment in which the degree of model risk is controlled illustrates how to quantify Value-at-Risk model risk and compute the required regulatory capital add-on for banks. An empirical example based on real data shows how the methodology can be put into practice, using only two time series (daily Value-at-Risk and daily profit and loss) from a large bank. We conclude with a discussion of potential applications to nonfinancial risks. © 2012 Society for Risk Analysis.

  15. Risk analysis of bioprocesses based on genetically modified bacteria. Pathway and exposure modeling

    Energy Technology Data Exchange (ETDEWEB)

    Rein, A.; Bittens, M. [Tuebingen Univ. (Germany). Zentrum fuer Angewandte Geowissenschaften

    2003-07-01

    For soils contaminated with polychlorinated biphenyls (PCBs), a plant-microorganism system for in situ - bioremediation has been developed. It consists of genetically modified microorganisms (GMOs) in conjunction with plant roots. The GMOs are Pseudomonas fluorescens strains which are genetically engineered to degrade PCB congeners in situ. Their metabolism requires root exudates and is therefore tightly coupled to plant rhizospheres. Compared to wild type organisms, the genetically modified bacteria develop a specificity to PCB as a substrate and therefore foster biodegradation in a more efficient way. To evaluate the efficiency and impact of this bioremediation system for potential field application, lysimeter tests are carried out. The lysimeters are filled with contaminated soil from a PCB release site in Denmark and planted with GMO inoculated plants. On the basis of these experiments, a detailed risk analysis is carried out to obtain conclusions to field-conditions (potential deliberate GMO-release). A qualitative and quantitative assessment of actual or potential effects is performed, addressing transport, fate and exposure of PCBs, GMOs and specific degradation products in different environmental compartments. (orig.)

  16. Environmental risk analysis

    International Nuclear Information System (INIS)

    Lima-e-Silva, Pedro Paulo de

    1996-01-01

    The conventional Risk Analysis (RA) relates usually a certain undesired event frequency with its consequences. Such technique is used nowadays in Brazil to analyze accidents and their consequences strictly under the human approach, valuing loss of human equipment, human structures and human lives, without considering the damage caused to natural resources that keep life possible on Earth. This paradigm was developed primarily because of the Homo sapiens' lack of perception upon the natural web needed to sustain his own life. In reality, the Brazilian professionals responsible today for licensing, auditing and inspecting environmental aspects of human activities face huge difficulties in making technical specifications and procedures leading to acceptable levels of impact, furthermore considering the intrinsic difficulties to define those levels. Therefore, in Brazil the RA technique is a weak tool for licensing for many reasons, and of them are its short scope (only accident considerations) and wrong a paradigm (only human direct damages). A paper from the author about the former was already proposed to the 7th International Conference on Environmetrics, past July'96, USP-SP. This one discusses the extension of the risk analysis concept to take into account environmental consequences, transforming the conventional analysis into a broader methodology named here as Environmental Risk Analysis. (author)

  17. Models of Credit Risk Measurement

    OpenAIRE

    Hagiu Alina

    2011-01-01

    Credit risk is defined as that risk of financial loss caused by failure by the counterparty. According to statistics, for financial institutions, credit risk is much important than market risk, reduced diversification of the credit risk is the main cause of bank failures. Just recently, the banking industry began to measure credit risk in the context of a portfolio along with the development of risk management started with models value at risk (VAR). Once measured, credit risk can be diversif...

  18. Risk analysis and reliability

    International Nuclear Information System (INIS)

    Uppuluri, V.R.R.

    1979-01-01

    Mathematical foundations of risk analysis are addressed. The importance of having the same probability space in order to compare different experiments is pointed out. Then the following topics are discussed: consequences as random variables with infinite expectations; the phenomenon of rare events; series-parallel systems and different kinds of randomness that could be imposed on such systems; and the problem of consensus of estimates of expert opinion

  19. GEP analysis validates high risk MDS and acute myeloid leukemia post MDS mice models and highlights novel dysregulated pathways.

    Science.gov (United States)

    Guerenne, Laura; Beurlet, Stéphanie; Said, Mohamed; Gorombei, Petra; Le Pogam, Carole; Guidez, Fabien; de la Grange, Pierre; Omidvar, Nader; Vanneaux, Valérie; Mills, Ken; Mufti, Ghulam J; Sarda-Mantel, Laure; Noguera, Maria Elena; Pla, Marika; Fenaux, Pierre; Padua, Rose Ann; Chomienne, Christine; Krief, Patricia

    2016-01-27

    In spite of the recent discovery of genetic mutations in most myelodysplasic (MDS) patients, the pathophysiology of these disorders still remains poorly understood, and only few in vivo models are available to help unravel the disease. We performed global specific gene expression profiling and functional pathway analysis in purified Sca1+ cells of two MDS transgenic mouse models that mimic human high-risk MDS (HR-MDS) and acute myeloid leukemia (AML) post MDS, with NRASD12 and BCL2 transgenes under the control of different promoters MRP8NRASD12/tethBCL-2 or MRP8[NRASD12/hBCL-2], respectively. Analysis of dysregulated genes that were unique to the diseased HR-MDS and AML post MDS mice and not their founder mice pointed first to pathways that had previously been reported in MDS patients, including DNA replication/damage/repair, cell cycle, apoptosis, immune responses, and canonical Wnt pathways, further validating these models at the gene expression level. Interestingly, pathways not previously reported in MDS were discovered. These included dysregulated genes of noncanonical Wnt pathways and energy and lipid metabolisms. These dysregulated genes were not only confirmed in a different independent set of BM and spleen Sca1+ cells from the MDS mice but also in MDS CD34+ BM patient samples. These two MDS models may thus provide useful preclinical models to target pathways previously identified in MDS patients and to unravel novel pathways highlighted by this study.

  20. GEP analysis validates high risk MDS and acute myeloid leukemia post MDS mice models and highlights novel dysregulated pathways

    Directory of Open Access Journals (Sweden)

    Laura Guerenne

    2016-01-01

    Full Text Available Abstract Background In spite of the recent discovery of genetic mutations in most myelodysplasic (MDS patients, the pathophysiology of these disorders still remains poorly understood, and only few in vivo models are available to help unravel the disease. Methods We performed global specific gene expression profiling and functional pathway analysis in purified Sca1+ cells of two MDS transgenic mouse models that mimic human high-risk MDS (HR-MDS and acute myeloid leukemia (AML post MDS, with NRASD12 and BCL2 transgenes under the control of different promoters MRP8NRASD12/tethBCL-2 or MRP8[NRASD12/hBCL-2], respectively. Results Analysis of dysregulated genes that were unique to the diseased HR-MDS and AML post MDS mice and not their founder mice pointed first to pathways that had previously been reported in MDS patients, including DNA replication/damage/repair, cell cycle, apoptosis, immune responses, and canonical Wnt pathways, further validating these models at the gene expression level. Interestingly, pathways not previously reported in MDS were discovered. These included dysregulated genes of noncanonical Wnt pathways and energy and lipid metabolisms. These dysregulated genes were not only confirmed in a different independent set of BM and spleen Sca1+ cells from the MDS mice but also in MDS CD34+ BM patient samples. Conclusions These two MDS models may thus provide useful preclinical models to target pathways previously identified in MDS patients and to unravel novel pathways highlighted by this study.

  1. Methods for Risk Analysis

    International Nuclear Information System (INIS)

    Alverbro, Karin

    2010-01-01

    Many decision-making situations today affect humans and the environment. In practice, many such decisions are made without an overall view and prioritise one or other of the two areas. Now and then these two areas of regulation come into conflict, e.g. the best alternative as regards environmental considerations is not always the best from a human safety perspective and vice versa. This report was prepared within a major project with the aim of developing a framework in which both the environmental aspects and the human safety aspects are integrated, and decisions can be made taking both fields into consideration. The safety risks have to be analysed in order to be successfully avoided and one way of doing this is to use different kinds of risk analysis methods. There is an abundance of existing methods to choose from and new methods are constantly being developed. This report describes some of the risk analysis methods currently available for analysing safety and examines the relationships between them. The focus here is mainly on human safety aspects

  2. Risk analysis in cattle fattening in North West Ethiopia: Empirical evidence form two limit Tobit model

    Directory of Open Access Journals (Sweden)

    Habtamu Yesigat Ayenew

    2012-09-01

    Full Text Available Resource allocation is a point of concern in small to large farms and is generally argued that small farmers in developing countries are “poor but efficient”, trying to allocate the limited resources to unlimited desires efficiently in the given production system in the light of their life-long experiences. The issue of market orientation in cattle fattening is basically challenged with the risks and uncertainties in the production and the market. Data were collected from 112 purposively selected fattening operator farmers from 3 districts and 6 peasant associations to see the risks. The data were analyzed through both descriptive and econometric statistical tools using STATA. Only about 13% of the respondents have participated in the farm business with own capital and the vast majority borrowed from Amhara Credit and Saving Association (ACSI through their cooperatives. It is found that production risks are limited while economic and market related risks play vital role in the farm operation. Duration of stay of the cattle, land holding of the household, distance to the development agent’s office and age of the household head increase the risk averse nature of the household and limit their participation in export market. In the other hand, frequency of fattening enhances the risk taking character of the households and their participation in the export of cattle. It is vital to enhance the institutional support from the public to enhance the gain from the fattening activity and market orientation of farming.

  3. Effect of human movement on airborne disease transmission in an airplane cabin: study using numerical modeling and quantitative risk analysis.

    Science.gov (United States)

    Han, Zhuyang; To, Gin Nam Sze; Fu, Sau Chung; Chao, Christopher Yu-Hang; Weng, Wenguo; Huang, Quanyi

    2014-08-06

    Airborne transmission of respiratory infectious disease in indoor environment (e.g. airplane cabin, conference room, hospital, isolated room and inpatient ward) may cause outbreaks of infectious diseases, which may lead to many infection cases and significantly influences on the public health. This issue has received more and more attentions from academics. This work investigates the influence of human movement on the airborne transmission of respiratory infectious diseases in an airplane cabin by using an accurate human model in numerical simulation and comparing the influences of different human movement behaviors on disease transmission. The Eulerian-Lagrangian approach is adopted to simulate the dispersion and deposition of the expiratory aerosols. The dose-response model is used to assess the infection risks of the occupants. The likelihood analysis is performed as a hypothesis test on the input parameters and different human movement pattern assumptions. An in-flight SARS outbreak case is used for investigation. A moving person with different moving speeds is simulated to represent the movement behaviors. A digital human model was used to represent the detailed profile of the occupants, which was obtained by scanning a real thermal manikin using the 3D laser scanning system. The analysis results indicate that human movement can strengthen the downward transport of the aerosols, significantly reduce the overall deposition and removal rate of the suspended aerosols and increase the average infection risk in the cabin. The likelihood estimation result shows that the risk assessment results better fit the outcome of the outbreak case when the movements of the seated passengers are considered. The intake fraction of the moving person is significantly higher than most of the seated passengers. The infection risk distribution in the airplane cabin highly depends on the movement behaviors of the passengers and the index patient. The walking activities of the crew

  4. Sector model analysis of risk on cross-jurisdictional treatment of disaster waste related to the Great East Japan Earthquake

    International Nuclear Information System (INIS)

    Nagashima, Miori; Itokawa, Etsuko; Ozuka, Yohei

    2012-01-01

    This study addressed the controversial issue of disaster waste treatment in the reconstruction efforts following the Great East Japan Earthquake. Using the Sector Model (Matsumoto 2009), we categorized a range of actions taken in relation to the cross-jurisdictional treatment into the four sectors, government, industry, academia, and private. The analysis through this Sector Model made it possible to map the entire layout of waste treatment, inclusive of less-visible industry and academia sectors. Accordingly, we have argued that differences of risk awareness are not necessarily due to sector differences but rather depend on two aspects of the disaster waste treatment; the safety levels and the nationwide treatment of waste in Japan. We further suggest that the discrepancy in the arguments on safety levels emerged as a result of scientific under-determination and cross-jurisdictional treatment from social and/or political under-determination. (author)

  5. Analysis of radon-induced lung cancer risk by a stochastic state-vector model of radiation carcinogenesis

    International Nuclear Information System (INIS)

    Crawford-Brown, Douglas J.; Hofmann, Werner

    2002-01-01

    A biologically based state-vector model (SVM) of radiation carcinogenesis has been extended to incorporate stochasticity of cellular transitions and specific in vivo irradiation conditions in the lungs. Dose-rate-dependent cellular transitions related to the formation of double-stranded DNA breaks, repair of breaks, interactions (translocations) between breaks, fixation of breaks, cellular inactivation, stimulated mitosis and promotion through loss of intercellular communication are simulated by Monte Carlo methods. The stochastic SVM has been applied to the analysis of lung cancer incidence in uranium miners exposed to alpha-emitting radon progeny. When incorporating in vivo features of cell differentiation, stimulated cell division and heterogeneity of cellular doses into the model, excellent agreement between epidemiological data and modelling results could be obtained. At low doses, the model predicts a non-linear dose-response relationship; e.g., computed lung cancer risk at 20 WLM is about half of current lung cancer estimates based on the linear hypothesis. The model also predicts a slight dose rate effect; e.g., at a cumulative exposure of 20 WLM, calculated lung cancer incidence for an exposure rate 0.27 WLM/year (assuming an exposure time of 73 years) is smaller by a factor of 1.2 than that for an exposure rate of 10 WLM/year. (author)

  6. RADTRAN II: a computerized model for risk analysis of transportation of radioactive material

    International Nuclear Information System (INIS)

    Taylor, J.M.; Daniel, S.L.; Biringer, B.E.

    1980-01-01

    The RADTRAN computer code, which formed the basis for the 1977 US generic transportation risk assessment, has been extensively updated. The updated version of the code, denoted RADTRAN II, includes changes based on findings from other transportation risk studies as well as changes based on reevaluation of earlier assumptions, analyses, and computerization techniques. The environmental impact of the transportation of radioactive material can be envisioned as consisting of five components, incident free transport, non-radiological impacts, vehicular accidents, breaches of security/safeguards, and failures of quality assurance. RADTRAN II is designed to evaluate both the incident-free and the accident contribution directly and can be used to evaluate the contributions of breaches of security and quality assurances deviation if some alterations in coding are made. Non-radiological impacts are not addressed

  7. Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis

    OpenAIRE

    Shearer, Freya M; Longbottom, Joshua; Browne, Annie J; Pigott, David M; Brady, Oliver J; Kraemer, Moritz U G; Marinho, Fatima; Yactayo, Sergio; de Araújo, Valdelaine E M; da Nóbrega, Aglaêr A; Fullman, Nancy; Ray, Sarah E; Mosser, Jonathan F; Stanaway, Jeffrey D; Lim, Stephen S

    2018-01-01

    Summary: Background: Yellow fever cases are under-reported and the exact distribution of the disease is unknown. An effective vaccine is available but more information is needed about which populations within risk zones should be targeted to implement interventions. Substantial outbreaks of yellow fever in Angola, Democratic Republic of the Congo, and Brazil, coupled with the global expansion of the range of its main urban vector, Aedes aegypti, suggest that yellow fever has the propensity t...

  8. RISK LOAN PORTFOLIO OPTIMIZATION MODEL BASED ON CVAR RISK MEASURE

    Directory of Open Access Journals (Sweden)

    Ming-Chang LEE

    2015-07-01

    Full Text Available In order to achieve commercial banks liquidity, safety and profitability objective requirements, loan portfolio risk analysis based optimization decisions are rational allocation of assets.  The risk analysis and asset allocation are the key technology of banking and risk management.  The aim of this paper, build a loan portfolio optimization model based on risk analysis.  Loan portfolio rate of return by using Value-at-Risk (VaR and Conditional Value-at-Risk (CVaR constraint optimization decision model reflects the bank's risk tolerance, and the potential loss of direct control of the bank.  In this paper, it analyze a general risk management model applied to portfolio problems with VaR and CVaR risk measures by using Using the Lagrangian Algorithm.  This paper solves the highly difficult problem by matrix operation method.  Therefore, the combination of this paper is easy understanding the portfolio problems with VaR and CVaR risk model is a hyperbola in mean-standard deviation space.  It is easy calculation in proposed method.

  9. Risk Estimation for Lung Cancer in Libya: Analysis Based on Standardized Morbidity Ratio, Poisson-Gamma Model, BYM Model and Mixture Model

    Science.gov (United States)

    Alhdiri, Maryam Ahmed; Samat, Nor Azah; Mohamed, Zulkifley

    2017-03-01

    Cancer is the most rapidly spreading disease in the world, especially in developing countries, including Libya. Cancer represents a significant burden on patients, families, and their societies. This disease can be controlled if detected early. Therefore, disease mapping has recently become an important method in the fields of public health research and disease epidemiology. The correct choice of statistical model is a very important step to producing a good map of a disease. Libya was selected to perform this work and to examine its geographical variation in the incidence of lung cancer. The objective of this paper is to estimate the relative risk for lung cancer. Four statistical models to estimate the relative risk for lung cancer and population censuses of the study area for the time period 2006 to 2011 were used in this work. They are initially known as Standardized Morbidity Ratio, which is the most popular statistic, which used in the field of disease mapping, Poisson-gamma model, which is one of the earliest applications of Bayesian methodology, Besag, York and Mollie (BYM) model and Mixture model. As an initial step, this study begins by providing a review of all proposed models, which we then apply to lung cancer data in Libya. Maps, tables and graph, goodness-of-fit (GOF) were used to compare and present the preliminary results. This GOF is common in statistical modelling to compare fitted models. The main general results presented in this study show that the Poisson-gamma model, BYM model, and Mixture model can overcome the problem of the first model (SMR) when there is no observed lung cancer case in certain districts. Results show that the Mixture model is most robust and provides better relative risk estimates across a range of models. Creative Commons Attribution License

  10. THE USE OF HEC-RAS MODELLING IN FLOOD RISK ANALYSIS

    OpenAIRE

    IOSUB MARINA; MINEA I.; HAPCIUC OANA; ROMANESCU GH.

    2015-01-01

    The fact that, in the Ozana drainage basin, most of the people have built their homes in the river valley, determines that a study focused on identifying the areas exposed to hydrological risk is vital, mostly in the development decisions for villages and in the creation of management plans for emergency situations. This study analyses the mapping methodology of the flood prone areas in the middle and lower sector of the Pluton river, which is a tributary of Ozana river, in its upper sector. ...

  11. RAMS (Risk Analysis - Modular System) methodology

    Energy Technology Data Exchange (ETDEWEB)

    Stenner, R.D.; Strenge, D.L.; Buck, J.W. [and others

    1996-10-01

    The Risk Analysis - Modular System (RAMS) was developed to serve as a broad scope risk analysis tool for the Risk Assessment of the Hanford Mission (RAHM) studies. The RAHM element provides risk analysis support for Hanford Strategic Analysis and Mission Planning activities. The RAHM also provides risk analysis support for the Hanford 10-Year Plan development activities. The RAMS tool draws from a collection of specifically designed databases and modular risk analysis methodologies and models. RAMS is a flexible modular system that can be focused on targeted risk analysis needs. It is specifically designed to address risks associated with overall strategy, technical alternative, and `what if` questions regarding the Hanford cleanup mission. RAMS is set up to address both near-term and long-term risk issues. Consistency is very important for any comparative risk analysis, and RAMS is designed to efficiently and consistently compare risks and produce risk reduction estimates. There is a wide range of output information that can be generated by RAMS. These outputs can be detailed by individual contaminants, waste forms, transport pathways, exposure scenarios, individuals, populations, etc. However, they can also be in rolled-up form to support high-level strategy decisions.

  12. THE USE OF HEC-RAS MODELLING IN FLOOD RISK ANALYSIS

    Directory of Open Access Journals (Sweden)

    IOSUB MARINA

    2015-03-01

    Full Text Available The fact that, in the Ozana drainage basin, most of the people have built their homes in the river valley, determines that a study focused on identifying the areas exposed to hydrological risk is vital, mostly in the development decisions for villages and in the creation of management plans for emergency situations. This study analyses the mapping methodology of the flood prone areas in the middle and lower sector of the Pluton river, which is a tributary of Ozana river, in its upper sector. In order to correctly draw the flood risk maps, the HEC-RAS method has been used, together with the HEC-GeoRAS extension, in ArcGIS. The results that have been obtained, correlate with the field situation in a very high proportion: for a 1% occurance flood, almost 123 households have been damaged, and according to the simulation, a number of 147 buildings have been damaged, therefore other probabilities (that overcome the 1% situation can be used for similar simulations.

  13. Bayesian Analysis for Risk Assessment of Selected Medical Events in Support of the Integrated Medical Model Effort

    Science.gov (United States)

    Gilkey, Kelly M.; Myers, Jerry G.; McRae, Michael P.; Griffin, Elise A.; Kallrui, Aditya S.

    2012-01-01

    The Exploration Medical Capability project is creating a catalog of risk assessments using the Integrated Medical Model (IMM). The IMM is a software-based system intended to assist mission planners in preparing for spaceflight missions by helping them to make informed decisions about medical preparations and supplies needed for combating and treating various medical events using Probabilistic Risk Assessment. The objective is to use statistical analyses to inform the IMM decision tool with estimated probabilities of medical events occurring during an exploration mission. Because data regarding astronaut health are limited, Bayesian statistical analysis is used. Bayesian inference combines prior knowledge, such as data from the general U.S. population, the U.S. Submarine Force, or the analog astronaut population located at the NASA Johnson Space Center, with observed data for the medical condition of interest. The posterior results reflect the best evidence for specific medical events occurring in flight. Bayes theorem provides a formal mechanism for combining available observed data with data from similar studies to support the quantification process. The IMM team performed Bayesian updates on the following medical events: angina, appendicitis, atrial fibrillation, atrial flutter, dental abscess, dental caries, dental periodontal disease, gallstone disease, herpes zoster, renal stones, seizure, and stroke.

  14. Transcriptome and DNA Methylome Analysis in a Mouse Model of Diet-Induced Obesity Predicts Increased Risk of Colorectal Cancer

    Directory of Open Access Journals (Sweden)

    Ruifang Li

    2018-01-01

    Full Text Available Colorectal cancer (CRC tends to occur at older age; however, CRC incidence rates have been rising sharply among young age groups. The increasing prevalence of obesity is recognized as a major risk, yet the mechanistic underpinnings remain poorly understood. Using a diet-induced obesity mouse model, we identified obesity-associated molecular changes in the colonic epithelium of young and aged mice, and we further investigated whether the changes were reversed after weight loss. Transcriptome analysis indicated that obesity-related colonic cellular metabolic switch favoring long-chain fatty acid oxidation happened in young mice, while obesity-associated downregulation of negative feedback regulators of pro-proliferative signaling pathways occurred in older mice. Strikingly, colonic DNA methylome was pre-programmed by obesity at young age, priming for a tumor-prone gene signature after aging. Furthermore, obesity-related changes were substantially preserved after short-term weight loss, but they were largely reversed after long-term weight loss. We provided mechanistic insights into increased CRC risk in obesity.

  15. A comparison of models for risk assessment

    International Nuclear Information System (INIS)

    Kellerer, A.M.; Jing Chen

    1993-01-01

    Various mathematical models have been used to represent the dependence of excess cancer risk on dose, age and time since exposure. For solid cancers, i.e. all cancers except leukaemia, the so-called relative risk model is usually employed. However, there can be quite different relative risk models. The most usual model for the quantification of excess tumour rate among the atomic bomb survivors has been a dependence of the relative risk on age at exposure, but it has been shown recently that an age attained model can be equally applied, to represent the observations among the atomic bomb survivors. The differences between the models and their implications are explained. It is also shown that the age attained model is similar to the approaches that have been used in the analysis of lung cancer incidence among radon exposed miners. A more unified approach to modelling of radiation risks can thus be achieved. (3 figs.)

  16. Kombucha brewing under the Food and Drug Administration model Food Code: risk analysis and processing guidance.

    Science.gov (United States)

    Nummer, Brian A

    2013-11-01

    Kombucha is a fermented beverage made from brewed tea and sugar. The taste is slightly sweet and acidic and it may have residual carbon dioxide. Kombucha is consumed in many countries as a health beverage and it is gaining in popularity in the U.S. Consequently, many retailers and food service operators are seeking to brew this beverage on site. As a fermented beverage, kombucha would be categorized in the Food and Drug Administration model Food Code as a specialized process and would require a variance with submission of a food safety plan. This special report was created to assist both operators and regulators in preparing or reviewing a kombucha food safety plan.

  17. Competition, Innovation, Risk-Taking, and Profitability in the Chinese Banking Sector: An Empirical Analysis Based on Structural Equation Modeling

    Directory of Open Access Journals (Sweden)

    Ti Hu

    2016-01-01

    Full Text Available We introduce a new perspective to systematically investigate the cause-and-effect relationships among competition, innovation, risk-taking, and profitability in the Chinese banking industry. Our hypotheses are tested by the structural equation modeling (SEM, and the empirical results show that (i risk-taking is positively related to profitability; (ii innovation positively affects both risk-taking and profitability, and the effect of innovation on profitability works both directly and indirectly; (iii competition negatively affects risk-taking but positively affects both innovation and profitability, and the effects of competition on risk-taking and profitability work both directly and indirectly; (iv there is a cascading relationship among market competition and bank innovation, risk-taking, and profitability.

  18. Risk analysis for nuclear power plants

    International Nuclear Information System (INIS)

    Koelzer, W.

    1983-01-01

    The German risk analysis program for nuclear power plants aiming at the man and the environment is presented. An accident consequence model to calculate the radiological impact and the potential health effects is described. (E.G.) [pt

  19. Custom v. Standardized Risk Models

    Directory of Open Access Journals (Sweden)

    Zura Kakushadze

    2015-05-01

    Full Text Available We discuss when and why custom multi-factor risk models are warranted and give source code for computing some risk factors. Pension/mutual funds do not require customization but standardization. However, using standardized risk models in quant trading with much shorter holding horizons is suboptimal: (1 longer horizon risk factors (value, growth, etc. increase noise trades and trading costs; (2 arbitrary risk factors can neutralize alpha; (3 “standardized” industries are artificial and insufficiently granular; (4 normalization of style risk factors is lost for the trading universe; (5 diversifying risk models lowers P&L correlations, reduces turnover and market impact, and increases capacity. We discuss various aspects of custom risk model building.

  20. A model-based analysis of decision making under risk in obsessive-compulsive and hoarding disorders.

    Science.gov (United States)

    Aranovich, Gabriel J; Cavagnaro, Daniel R; Pitt, Mark A; Myung, Jay I; Mathews, Carol A

    2017-07-01

    Attitudes towards risk are highly consequential in clinical disorders thought to be prone to "risky behavior", such as substance dependence, as well as those commonly associated with excessive risk aversion, such as obsessive-compulsive disorder (OCD) and hoarding disorder (HD). Moreover, it has recently been suggested that attitudes towards risk may serve as a behavioral biomarker for OCD. We investigated the risk preferences of participants with OCD and HD using a novel adaptive task and a quantitative model from behavioral economics that decomposes risk preferences into outcome sensitivity and probability sensitivity. Contrary to expectation, compared to healthy controls, participants with OCD and HD exhibited less outcome sensitivity, implying less risk aversion in the standard economic framework. In addition, risk attitudes were strongly correlated with depression, hoarding, and compulsion scores, while compulsion (hoarding) scores were associated with more (less) "rational" risk preferences. These results demonstrate how fundamental attitudes towards risk relate to specific psychopathology and thereby contribute to our understanding of the cognitive manifestations of mental disorders. In addition, our findings indicate that the conclusion made in recent work that decision making under risk is unaltered in OCD is premature. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. Using Structured Additive Regression Models to Estimate Risk Factors of Malaria: Analysis of 2010 Malawi Malaria Indicator Survey Data

    Science.gov (United States)

    Chirombo, James; Lowe, Rachel; Kazembe, Lawrence

    2014-01-01

    Background After years of implementing Roll Back Malaria (RBM) interventions, the changing landscape of malaria in terms of risk factors and spatial pattern has not been fully investigated. This paper uses the 2010 malaria indicator survey data to investigate if known malaria risk factors remain relevant after many years of interventions. Methods We adopted a structured additive logistic regression model that allowed for spatial correlation, to more realistically estimate malaria risk factors. Our model included child and household level covariates, as well as climatic and environmental factors. Continuous variables were modelled by assuming second order random walk priors, while spatial correlation was specified as a Markov random field prior, with fixed effects assigned diffuse priors. Inference was fully Bayesian resulting in an under five malaria risk map for Malawi. Results Malaria risk increased with increasing age of the child. With respect to socio-economic factors, the greater the household wealth, the lower the malaria prevalence. A general decline in malaria risk was observed as altitude increased. Minimum temperatures and average total rainfall in the three months preceding the survey did not show a strong association with disease risk. Conclusions The structured additive regression model offered a flexible extension to standard regression models by enabling simultaneous modelling of possible nonlinear effects of continuous covariates, spatial correlation and heterogeneity, while estimating usual fixed effects of categorical and continuous observed variables. Our results confirmed that malaria epidemiology is a complex interaction of biotic and abiotic factors, both at the individual, household and community level and that risk factors are still relevant many years after extensive implementation of RBM activities. PMID:24991915

  2. Intentional risk management through complex networks analysis

    CERN Document Server

    Chapela, Victor; Moral, Santiago; Romance, Miguel

    2015-01-01

    This book combines game theory and complex networks to examine intentional technological risk through modeling. As information security risks are in constant evolution,  the methodologies and tools to manage them must evolve to an ever-changing environment. A formal global methodology is explained  in this book, which is able to analyze risks in cyber security based on complex network models and ideas extracted from the Nash equilibrium. A risk management methodology for IT critical infrastructures is introduced which provides guidance and analysis on decision making models and real situations. This model manages the risk of succumbing to a digital attack and assesses an attack from the following three variables: income obtained, expense needed to carry out an attack, and the potential consequences for an attack. Graduate students and researchers interested in cyber security, complex network applications and intentional risk will find this book useful as it is filled with a number of models, methodologies a...

  3. Identifying Some Risk Factors for the Time to Death of the Elderly Using the Semi-Parametric Blended Model of Survival Analysis With Competing Risks

    Directory of Open Access Journals (Sweden)

    Samane Hajiabbasi

    2018-01-01

    Conclusion In single-variable fitting, age, history of myocardial infarction, history of stroke, and kidney problems were identified to have significant effects on the time to death of the elderly. Based on one-variable semi-parametric competing risk mixture fitted models, more significant risk factors for the time to death of elderly was identified when compared with a fitted multivariate mode to the data. This implies that the role of some independent variables can be explained by other independent variables.

  4. Illicit trafficking of radiological and nuclear materials: modeling and analysis of trafficking trends and risks

    International Nuclear Information System (INIS)

    York, David L.; Love, Tracia L.; Rochau, Gary Eugene

    2005-01-01

    understood as to prepare for the sustained global development of the nuclear fuel cycle. Conversely, modeling and analyses of this activity must not be limited in their scope to loosely organized criminal smuggling, but address the problem as a commercial, industrial project for the covert development of nuclear technologies and unconventional weapon development.

  5. Model Risk in Portfolio Optimization

    Directory of Open Access Journals (Sweden)

    David Stefanovits

    2014-08-01

    Full Text Available We consider a one-period portfolio optimization problem under model uncertainty. For this purpose, we introduce a measure of model risk. We derive analytical results for this measure of model risk in the mean-variance problem assuming we have observations drawn from a normal variance mixture model. This model allows for heavy tails, tail dependence and leptokurtosis of marginals. The results show that mean-variance optimization is seriously compromised by model uncertainty, in particular, for non-Gaussian data and small sample sizes. To mitigate these shortcomings, we propose a method to adjust the sample covariance matrix in order to reduce model risk.

  6. Probabilistic risk assessment model for allergens in food: sensitivity analysis of the minimum eliciting dose and food consumption

    NARCIS (Netherlands)

    Kruizinga, A.G.; Briggs, D.; Crevel, R.W.R.; Knulst, A.C.; Bosch, L.M.C.v.d.; Houben, G.F.

    2008-01-01

    Previously, TNO developed a probabilistic model to predict the likelihood of an allergic reaction, resulting in a quantitative assessment of the risk associated with unintended exposure to food allergens. The likelihood is estimated by including in the model the proportion of the population who is

  7. Quality Risk Evaluation of the Food Supply Chain Using a Fuzzy Comprehensive Evaluation Model and Failure Mode, Effects, and Criticality Analysis

    Directory of Open Access Journals (Sweden)

    Libiao Bai

    2018-01-01

    Full Text Available Evaluating the quality risk level in the food supply chain can reduce quality information asymmetry and food quality incidents and promote nationally integrated regulations for food quality. In order to evaluate it, a quality risk evaluation indicator system for the food supply chain is constructed based on an extensive literature review in this paper. Furthermore, a mathematical model based on the fuzzy comprehensive evaluation model (FCEM and failure mode, effects, and criticality analysis (FMECA for evaluating the quality risk level in the food supply chain is developed. A computational experiment aimed at verifying the effectiveness and feasibility of this proposed model is conducted on the basis of a questionnaire survey. The results suggest that this model can be used as a general guideline to assess the quality risk level in the food supply chain and achieve the most important objective of providing a reference for the public and private sectors when making decisions on food quality management.

  8. "Know What to Do If You Encounter a Flash Flood": Mental Models Analysis for Improving Flash Flood Risk Communication and Public Decision Making.

    Science.gov (United States)

    Lazrus, Heather; Morss, Rebecca E; Demuth, Julie L; Lazo, Jeffrey K; Bostrom, Ann

    2016-02-01

    Understanding how people view flash flood risks can help improve risk communication, ultimately improving outcomes. This article analyzes data from 26 mental models interviews about flash floods with members of the public in Boulder, Colorado, to understand their perspectives on flash flood risks and mitigation. The analysis includes a comparison between public and professional perspectives by referencing a companion mental models study of Boulder-area professionals. A mental models approach can help to diagnose what people already know about flash flood risks and responses, as well as any critical gaps in their knowledge that might be addressed through improved risk communication. A few public interviewees mentioned most of the key concepts discussed by professionals as important for flash flood warning decision making. However, most interviewees exhibited some incomplete understandings and misconceptions about aspects of flash flood development and exposure, effects, or mitigation that may lead to ineffective warning decisions when a flash flood threatens. These include important misunderstandings about the rapid evolution of flash floods, the speed of water in flash floods, the locations and times that pose the greatest flash flood risk in Boulder, the value of situational awareness and environmental cues, and the most appropriate responses when a flash flood threatens. The findings point to recommendations for ways to improve risk communication, over the long term and when an event threatens, to help people quickly recognize and understand threats, obtain needed information, and make informed decisions in complex, rapidly evolving extreme weather events such as flash floods. © 2015 Society for Risk Analysis.

  9. An analysis of a three-factor model proposed by the Danish Society of Actuaries for forecasting and risk analysis

    DEFF Research Database (Denmark)

    Jørgensen, Peter Løchte; Slipsager, Søren Kærgaard

    2016-01-01

    This paper provides the explicit solution to the three-factor diffusion model recently proposed by the Danish Society of Actuaries to the Danish industry of life insurance and pensions. The solution is obtained by use of the known general solution to multidimensional linear stochastic differential...

  10. Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs.

    Science.gov (United States)

    Ganga, G M D; Esposto, K F; Braatz, D

    2012-01-01

    The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

  11. Country risk analysis

    International Nuclear Information System (INIS)

    David, A.

    1992-01-01

    This paper reports that the oil industry has been an internationally based industry that has been heavily dependent on outside financing sources. Historically, financing came from investment houses that, in most cases, participated in the projects as equity investors. However, investment companies can no longer satisfy the capital requirements of the current high level of exploration and development activities. The current trend is to involve commercial banks on a purely lending basis. Commercial banks, by their nature, are risk averse. In the case of oil and gas exploration and production they are asked to take not only technical risk and price risk but geopolitical risk as well. Methods have been developed by commercial banks to reduce technical and price risks to point which enables them to be comfortable with a loan. However, geopolitical risks are more difficult to assess. The risk associated with many countries are the nationalization of the investment, new tax restrictions, restriction of currency movements, and/or revisions to the production sharing agreements

  12. Mortality Risk After Transcatheter Aortic Valve Implantation: Analysis of the Predictive Accuracy of the Transcatheter Valve Therapy Registry Risk Assessment Model.

    Science.gov (United States)

    Codner, Pablo; Malick, Waqas; Kouz, Remi; Patel, Amisha; Chen, Cheng-Han; Terre, Juan; Landes, Uri; Vahl, Torsten Peter; George, Isaac; Nazif, Tamim; Kirtane, Ajay J; Khalique, Omar K; Hahn, Rebecca T; Leon, Martin B; Kodali, Susheel

    2018-05-08

    Risk assessment tools currently used to predict mortality in transcatheter aortic valve implantation (TAVI) were designed for patients undergoing cardiac surgery. We aim to assess the accuracy of the TAVI dedicated American College of Cardiology / Transcatheter Valve Therapies (ACC/TVT) risk score in predicting mortality outcomes. Consecutive patients (n=1038) undergoing TAVI at a single institution from 2014 to 2016 were included. The ACC/TVT registry mortality risk score, the Society of Thoracic Surgeons - Patient Reported Outcomes (STS-PROM) score and the EuroSCORE II were calculated for all patients. In hospital and 30-day all-cause mortality rates were 1.3% and 2.9%, respectively. The ACC/TVT risk stratification tool scored higher for patients who died in-hospital than in those who survived the index hospitalization (6.4 ± 4.6 vs. 3.5 ± 1.6, p = 0.03; respectively). The ACC/TVT score showed a high level of discrimination, C-index for in-hospital mortality 0.74, 95% CI [0.59 - 0.88]. There were no significant differences between the performance of the ACC/TVT registry risk score, the EuroSCORE II and the STS-PROM for in hospital and 30-day mortality rates. The ACC/TVT registry risk model is a dedicated tool to aid in the prediction of in-hospital mortality risk after TAVI.

  13. An analysis of a three-factor model proposed by the Danish Society of Actuaries for forecasting and risk analysis

    OpenAIRE

    Jørgensen, Peter Løchte; Slipsager, Søren Kærgaard

    2016-01-01

    This paper provides the explicit solution to the three-factor diffusion model recently proposed by the Danish Society of Actuaries to the Danish industry of life insurance and pensions. The solution is obtained by use of the known general solution to multidimensional linear stochastic differential equation systems. With offset in the explicit solution, we establish the conditional distribution of the future state variables which allows for exact simulation. Using exact simulation, we illustra...

  14. Risk analysis of Odelouca cofferdam

    OpenAIRE

    Pimenta, L.; Caldeira, L.; Maranha das Neves, E.

    2009-01-01

    In this paper we present the risk analysis of Odelouca Cofferdam, using an event tree analysis. The initializing events, failure modes and analysed limit states are discussed based on an influence diagram. The constructed event trees and their interpretation are presented. The obtained risk values are represented in an FN plot superimposed to the acceptability and tolerability risk limits proposed for Portuguese dams. Initially, particular emphasis is placed on the main characteristic...

  15. An innovative expression model of human health risk based on the quantitative analysis of soil metals sources contribution in different spatial scales.

    Science.gov (United States)

    Zhang, Yimei; Li, Shuai; Wang, Fei; Chen, Zhuang; Chen, Jie; Wang, Liqun

    2018-09-01

    Toxicity of heavy metals from industrialization poses critical concern, and analysis of sources associated with potential human health risks is of unique significance. Assessing human health risk of pollution sources (factored health risk) concurrently in the whole and the sub region can provide more instructive information to protect specific potential victims. In this research, we establish a new expression model of human health risk based on quantitative analysis of sources contribution in different spatial scales. The larger scale grids and their spatial codes are used to initially identify the level of pollution risk, the type of pollution source and the sensitive population at high risk. The smaller scale grids and their spatial codes are used to identify the contribution of various sources of pollution to each sub region (larger grid) and to assess the health risks posed by each source for each sub region. The results of case study show that, for children (sensitive populations, taking school and residential area as major region of activity), the major pollution source is from the abandoned lead-acid battery plant (ALP), traffic emission and agricultural activity. The new models and results of this research present effective spatial information and useful model for quantifying the hazards of source categories and human health a t complex industrial system in the future. Copyright © 2018 Elsevier Ltd. All rights reserved.

  16. ISM Approach to Model Offshore Outsourcing Risks

    Directory of Open Access Journals (Sweden)

    Sunand Kumar

    2014-07-01

    Full Text Available In an effort to achieve a competitive advantage via cost reductions and improved market responsiveness, organizations are increasingly employing offshore outsourcing as a major component of their supply chain strategies. But as evident from literature number of risks such as Political risk, Risk due to cultural differences, Compliance and regulatory risk, Opportunistic risk and Organization structural risk, which adversely affect the performance of offshore outsourcing in a supply chain network. This also leads to dissatisfaction among different stake holders. The main objective of this paper is to identify and understand the mutual interaction among various risks which affect the performance of offshore outsourcing.  To this effect, authors have identified various risks through extant review of literature.  From this information, an integrated model using interpretive structural modelling (ISM for risks affecting offshore outsourcing is developed and the structural relationships between these risks are modeled.  Further, MICMAC analysis is done to analyze the driving power and dependency of risks which shall be helpful to managers to identify and classify important criterions and to reveal the direct and indirect effects of each criterion on offshore outsourcing. Results show that political risk and risk due to cultural differences are act as strong drivers.

  17. RISK ANALYSIS IN MILK PROCESSING

    Directory of Open Access Journals (Sweden)

    I. PIRVUTOIU

    2008-05-01

    Full Text Available This paper aimed to evaluate Risk bankruptcy using “Score Method” based on Canon and Holder’s Model. The data were collected from the Balance Sheet and Profit and Loss Account for the period 2005-2007, recorded by a Meat processing Plant (Rador Commercial Company .The study has put in evidence the financial situation of the company,the level of the main financial ratios fundamenting the calculation of Z score function value in the three years The low values of Z score function recorded every year reflects that the company is still facing backruptcy. However , the worst situation was recorded in the years 2005 and 2006, when baknruptcy risk was ranging between 70 – 80 % . In the year 2007, the risk bankruptcy was lower, ranging between 50-70 % , as Z function recorded a value lower than 4 .For Meat processing companies such an analysis is compulsory at present as long as business environment is very risky in our country.

  18. Probabilistic risk analysis for nuclear power plants

    International Nuclear Information System (INIS)

    Hauptmanns, U.

    1988-01-01

    Risk analysis is applied if the calculation of risk from observed failures is not possible, because events contributing substantially to risk are too seldom, as in the case of nuclear reactors. The process of analysis provides a number of benefits. Some of them are listed. After this by no means complete enumeration of possible benefits to be derived from a risk analysis. An outline of risk studiesd for PWR's with some comments on the models used are given. The presentation is indebted to the detailed treatment of the subject given in the PRA Procedures Guide. Thereafter some results of the German Risk Study, Phase B, which is under way are communicated. The paper concludes with some remarks on probabilistic considerations in licensing procedures. (orig./DG)

  19. A real-time, dynamic early-warning model based on uncertainty analysis and risk assessment for sudden water pollution accidents.

    Science.gov (United States)

    Hou, Dibo; Ge, Xiaofan; Huang, Pingjie; Zhang, Guangxin; Loáiciga, Hugo

    2014-01-01

    A real-time, dynamic, early-warning model (EP-risk model) is proposed to cope with sudden water quality pollution accidents affecting downstream areas with raw-water intakes (denoted as EPs). The EP-risk model outputs the risk level of water pollution at the EP by calculating the likelihood of pollution and evaluating the impact of pollution. A generalized form of the EP-risk model for river pollution accidents based on Monte Carlo simulation, the analytic hierarchy process (AHP) method, and the risk matrix method is proposed. The likelihood of water pollution at the EP is calculated by the Monte Carlo method, which is used for uncertainty analysis of pollutants' transport in rivers. The impact of water pollution at the EP is evaluated by expert knowledge and the results of Monte Carlo simulation based on the analytic hierarchy process. The final risk level of water pollution at the EP is determined by the risk matrix method. A case study of the proposed method is illustrated with a phenol spill accident in China.

  20. Risk analysis: opening the process

    International Nuclear Information System (INIS)

    Hubert, Ph.; Mays, C.

    1998-01-01

    This conference on risk analysis took place in Paris, 11-14 october 1999. Over 200 paper where presented in the seven following sessions: perception; environment and health; persuasive risks; objects and products; personal and collective involvement; assessment and valuation; management. A rational approach to risk analysis has been developed in the three last decades. Techniques for risk assessment have been thoroughly enhanced, risk management approaches have been developed, decision making processes have been clarified, the social dimensions of risk perception and management have been investigated. Nevertheless this construction is being challenged by recent events which reveal how deficits in stakeholder involvement, openness and democratic procedures can undermine risk management actions. Indeed, the global process most components of risk analysis may be radically called into question. Food safety has lately been a prominent issue, but now debates appear, or old debates are revisited in the domains of public health, consumer products safety, waste management, environmental risks, nuclear installations, automobile safety and pollution. To meet the growing pressures for efficiency, openness, accountability, and multi-partner communication in risk analysis, institutional changes are underway in many European countries. However, the need for stakeholders to develop better insight into the process may lead to an evolution of all the components of risks analysis, even in its most (technical' steps. For stakeholders of different professional background, political projects, and responsibilities, risk identification procedures must be rendered understandable, quantitative risk assessment must be intelligible and accommodated in action proposals, ranging from countermeasures to educational programs to insurance mechanisms. Management formats must be open to local and political input and other types of operational feedback. (authors)

  1. Risk Monitoring through Traceability Information Model

    OpenAIRE

    Juan P. Zamora; Wilson Adarme; Laura Palacios

    2012-01-01

    This paper shows a traceability framework for supply risk monitoring, beginning with the identification, analysis, and evaluation of the supply chain risk and focusing on the supply operations of the Health Care Institutions with oncology services in Bogota, Colombia. It includes a brief presentation of the state of the art of the Supply Chain Risk Management and traceability systems in logistics operations, and it concludes with the methodology to integrate the SCRM model with the traceabili...

  2. Modelling allergenic risk

    DEFF Research Database (Denmark)

    Birot, Sophie

    combines second order Monte-Carlo simulations with Bayesian inferences [13]. An alternative method using second order Monte-Carlo simulations was proposed to take into account the uncertainty from the inputs. The uncertainty propagation from the inputs to the risk of allergic reaction was also evaluated...... countries is proposed. Thus, the allergen risk assessment can be performed cross-nationally and for the correct food group. Then the two probabilistic risk assessment methods usually used were reviewed and compared. First order Monte-Carlo simulations are used in one method [14], whereas the other one......Up to 20 million Europeans suffer from food allergies. Due to the lack of knowledge about why food allergies developed or how to protect allergic consumers from the offending food, food allergy management is mainly based on food allergens avoidance. The iFAAM project (Integrated approaches to Food...

  3. Risk analysis; Analisis de riesgos

    Energy Technology Data Exchange (ETDEWEB)

    Baron, J H; Nunez McLeod, J; Rivera, S S [Universidad Nacional de Cuyo, Mendoza (Argentina). Instituto de Capacitacion Especial y Desarrollo de Ingenieria Asistida por Computadora (CEDIAC)

    1997-07-01

    This book contains a selection of research works performed in the CEDIAC Institute (Cuyo National University) in the area of Risk Analysis, with specific orientations to the subjects of uncertainty and sensitivity studies, software reliability, severe accident modeling, etc. This volume presents important material for all those researches who want to have an insight in the risk analysis field, as a tool to solution several problems frequently found in the engineering and applied sciences field, as well as for the academic teachers who want to keep up to date, including the new developments and improvements continuously arising in this field. [Spanish] Este libro contiene una seleccion de trabajos de investigacion realizados dentro del Instituto de Capacitacion Especial y Desarrollo de la Ingenieria Asistida por Computadora en el area del analisis de riesgos, con una orientacion hacia el estudio de incertidumbres y sensibilidad, confiabilidad de software, modelacion de accidentes severos, etc. Este volumen recoge un material de indudable importancia e interes para todos aquellos investigadores y profesionales que desean incursionar en este campo del analisis de riesgos como herramienta para la solucion de problemas frecuentemente encontrados en la ingenieria y las ciencias aplicadas, asi como para los academicos que desean mantenerse al dia, conociendo los nuevos desarrollos y tecnicas que constantemente aparecen en su area.

  4. Resolution of an uncertain closed-loop logistics model: an application to fuzzy linear programs with risk analysis.

    Science.gov (United States)

    Wang, Hsiao-Fan; Hsu, Hsin-Wei

    2010-11-01

    With the urgency of global warming, green supply chain management, logistics in particular, has drawn the attention of researchers. Although there are closed-loop green logistics models in the literature, most of them do not consider the uncertain environment in general terms. In this study, a generalized model is proposed where the uncertainty is expressed by fuzzy numbers. An interval programming model is proposed by the defined means and mean square imprecision index obtained from the integrated information of all the level cuts of fuzzy numbers. The resolution for interval programming is based on the decision maker (DM)'s preference. The resulting solution provides useful information on the expected solutions under a confidence level containing a degree of risk. The results suggest that the more optimistic the DM is, the better is the resulting solution. However, a higher risk of violation of the resource constraints is also present. By defining this probable risk, a solution procedure was developed with numerical illustrations. This provides a DM trade-off mechanism between logistic cost and the risk. Copyright 2010 Elsevier Ltd. All rights reserved.

  5. A model-based risk management framework

    Energy Technology Data Exchange (ETDEWEB)

    Gran, Bjoern Axel; Fredriksen, Rune

    2002-08-15

    The ongoing research activity addresses these issues through two co-operative activities. The first is the IST funded research project CORAS, where Institutt for energiteknikk takes part as responsible for the work package for Risk Analysis. The main objective of the CORAS project is to develop a framework to support risk assessment of security critical systems. The second, called the Halden Open Dependability Demonstrator (HODD), is established in cooperation between Oestfold University College, local companies and HRP. The objective of HODD is to provide an open-source test bed for testing, teaching and learning about risk analysis methods, risk analysis tools, and fault tolerance techniques. The Inverted Pendulum Control System (IPCON), which main task is to keep a pendulum balanced and controlled, is the first system that has been established. In order to make risk assessment one need to know what a system does, or is intended to do. Furthermore, the risk assessment requires correct descriptions of the system, its context and all relevant features. A basic assumption is that a precise model of this knowledge, based on formal or semi-formal descriptions, such as UML, will facilitate a systematic risk assessment. It is also necessary to have a framework to integrate the different risk assessment methods. The experiences so far support this hypothesis. This report presents CORAS and the CORAS model-based risk management framework, including a preliminary guideline for model-based risk assessment. The CORAS framework for model-based risk analysis offers a structured and systematic approach to identify and assess security issues of ICT systems. From the initial assessment of IPCON, we also believe that the framework is applicable in a safety context. Further work on IPCON, as well as the experiences from the CORAS trials, will provide insight and feedback for further improvements. (Author)

  6. Advances in probabilistic risk analysis

    International Nuclear Information System (INIS)

    Hardung von Hardung, H.

    1982-01-01

    Probabilistic risk analysis can now look back upon almost a quarter century of intensive development. The early studies, whose methods and results are still referred to occasionally, however, only permitted rough estimates to be made of the probabilities of recognizable accident scenarios, failing to provide a method which could have served as a reference base in calculating the overall risk associated with nuclear power plants. The first truly solid attempt was the Rasmussen Study and, partly based on it, the German Risk Study. In those studies, probabilistic risk analysis has been given a much more precise basis. However, new methodologies have been developed in the meantime, which allow much more informative risk studies to be carried out. They have been found to be valuable tools for management decisions with respect to backfitting, reinforcement and risk limitation. Today they are mainly applied by specialized private consultants and have already found widespread application especially in the USA. (orig.) [de

  7. The effectiveness and cost effectiveness of dark chocolate consumption as prevention therapy in people at high risk of cardiovascular disease: best case scenario analysis using a Markov model

    OpenAIRE

    Zomer, Ella; Owen, Alice; Magliano, Dianna J; Liew, Danny; Reid, Christopher M

    2012-01-01

    Objective To model the long term effectiveness and cost effectiveness of daily dark chocolate consumption in a population with metabolic syndrome at high risk of cardiovascular disease. Design Best case scenario analysis using a Markov model. Setting Australian Diabetes, Obesity and Lifestyle study. Participants 2013 people with hypertension who met the criteria for metabolic syndrome, with no history of cardiovascular disease and not receiving antihypertensive therapy. Main outcome measures ...

  8. A benefit–risk assessment model for statins using multicriteria decision analysis based on a discrete choice experiment in Korean patients

    Directory of Open Access Journals (Sweden)

    Byun JH

    2016-06-01

    Full Text Available Ji-Hye Byun,1 Sun-Hong Kwon,1 Ji-Hye Ha,2 Eui-Kyung Lee1 1School of Pharmacy, Sungkyunkwan University, Suwon-si, Gyeonggi-do, 2Ministry of Food and Drug Safety, Cheongju-si, Chungcheongbuk-do, South Korea Purpose: The benefit–risk balance for drugs can alter post approval owing to additional data on efficacy or adverse events. This study developed a quantitative benefit–risk assessment (BRA model for statins using multicriteria decision analysis with discrete choice experiments and compared a recent BRA with that at the time of approval. Patients and methods: Following a systematic review of the literature, the benefit criteria within the statin BRA model were defined as a reduction in the plasma low-density lipoprotein cholesterol level and a reduction in myocardial infarction incidence; the risk criteria were hepatotoxicity (Liv and fatal rhabdomyolysis (Rha. The scores for these criteria were estimated using mixed treatment comparison methods. Weighting was calculated from a discrete choice experiment involving 203 Korean patients. The scores and weights were integrated to produce an overall value representing the benefit–risk balance, and sensitivity analyses were conducted. Results: In this BRA model, low-density lipoprotein (relative importance [RI]: 37.50% was found to be a more important benefit criterion than myocardial infarction (RI: 35.43%, and Liv (RI: 16.28% was a more important risk criterion than Rha (RI: 10.79%. Patients preferred atorvastatin, and the preference ranking of cerivastatin and simvastatin was switched post approval because of the emergence of additional risk information related to cerivastatin. Conclusion: A quantitative statin BRA model confirmed that the preference ranking of statins changed post approval because of the identification of additional benefits or risks. Keywords: multicriteria decision analysis, statin, quantitative benefit–risk assessment, discrete choice experiment

  9. Introduction of the risk analysis

    International Nuclear Information System (INIS)

    Campon, G.; Martinez, I.

    2013-01-01

    An introduction of risks analysis was given in the exposition which main issues were: food innocuousness, world, regional and national food context,change of paradigms, health definition, risk, codex, standardization, food chain role, trade agreement, codex alimentarius, food transmission diseases cost impact

  10. Hydroproject risk analysis

    International Nuclear Information System (INIS)

    Murdock, R.V.; Gulliver, J.S.

    1991-01-01

    Traditionally, economic feasibility studies performed for potential hydropower plant sites have included either no uncertainty or at best an ad hoc value associated with estimated benefits. However, formal methods for analyzing uncertainty do exist and have been outlined in the past. An application of these methods is demonstrated through conversion of a hydropower survey program, HYFEAS, to run on LOTUS 1-2-3, using the add-in software package RISK. In this paper the program principals are outlined and a case study of it's application to a hydropower site is presented

  11. A methodology for modeling regional terrorism risk.

    Science.gov (United States)

    Chatterjee, Samrat; Abkowitz, Mark D

    2011-07-01

    Over the past decade, terrorism risk has become a prominent consideration in protecting the well-being of individuals and organizations. More recently, there has been interest in not only quantifying terrorism risk, but also placing it in the context of an all-hazards environment in which consideration is given to accidents and natural hazards, as well as intentional acts. This article discusses the development of a regional terrorism risk assessment model designed for this purpose. The approach taken is to model terrorism risk as a dependent variable, expressed in expected annual monetary terms, as a function of attributes of population concentration and critical infrastructure. This allows for an assessment of regional terrorism risk in and of itself, as well as in relation to man-made accident and natural hazard risks, so that mitigation resources can be allocated in an effective manner. The adopted methodology incorporates elements of two terrorism risk modeling approaches (event-based models and risk indicators), producing results that can be utilized at various jurisdictional levels. The validity, strengths, and limitations of the model are discussed in the context of a case study application within the United States. © 2011 Society for Risk Analysis.

  12. Multilevel joint competing risk models

    Science.gov (United States)

    Karunarathna, G. H. S.; Sooriyarachchi, M. R.

    2017-09-01

    Joint modeling approaches are often encountered for different outcomes of competing risk time to event and count in many biomedical and epidemiology studies in the presence of cluster effect. Hospital length of stay (LOS) has been the widely used outcome measure in hospital utilization due to the benchmark measurement for measuring multiple terminations such as discharge, transferred, dead and patients who have not completed the event of interest at the follow up period (censored) during hospitalizations. Competing risk models provide a method of addressing such multiple destinations since classical time to event models yield biased results when there are multiple events. In this study, the concept of joint modeling has been applied to the dengue epidemiology in Sri Lanka, 2006-2008 to assess the relationship between different outcomes of LOS and platelet count of dengue patients with the district cluster effect. Two key approaches have been applied to build up the joint scenario. In the first approach, modeling each competing risk separately using the binary logistic model, treating all other events as censored under the multilevel discrete time to event model, while the platelet counts are assumed to follow a lognormal regression model. The second approach is based on the endogeneity effect in the multilevel competing risks and count model. Model parameters were estimated using maximum likelihood based on the Laplace approximation. Moreover, the study reveals that joint modeling approach yield more precise results compared to fitting two separate univariate models, in terms of AIC (Akaike Information Criterion).

  13. Globally-Applicable Predictive Wildfire Model   a Temporal-Spatial GIS Based Risk Analysis Using Data Driven Fuzzy Logic Functions

    Science.gov (United States)

    van den Dool, G.

    2017-11-01

    This study (van den Dool, 2017) is a proof of concept for a global predictive wildfire model, in which the temporal-spatial characteristics of wildfires are placed in a Geographical Information System (GIS), and the risk analysis is based on data-driven fuzzy logic functions. The data sources used in this model are available as global datasets, but subdivided into three pilot areas: North America (California/Nevada), Europe (Spain), and Asia (Mongolia), and are downscaled to the highest resolution (3-arc second). The GIS is constructed around three themes: topography, fuel availability and climate. From the topographical data, six derived sub-themes are created and converted to a fuzzy membership based on the catchment area statistics. The fuel availability score is a composite of four data layers: land cover, wood loads, biomass, biovolumes. As input for the climatological sub-model reanalysed daily averaged, weather-related data is used, which is accumulated to a global weekly time-window (to account for the uncertainty within the climatological model) and forms the temporal component of the model. The final product is a wildfire risk score (from 0 to 1) by week, representing the average wildfire risk in an area. To compute the potential wildfire risk the sub-models are combined usinga Multi-Criteria Approach, and the model results are validated against the area under the Receiver Operating Characteristic curve.

  14. Prostate Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing prostate cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  15. Colorectal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing colorectal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  16. Esophageal Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing esophageal cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  17. Bladder Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing bladder cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  18. Lung Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing lung cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  19. Breast Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing breast cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  20. Pancreatic Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing pancreatic cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  1. Ovarian Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing ovarian cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  2. Liver Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing liver cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  3. Testicular Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of testicular cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  4. Cervical Cancer Risk Prediction Models

    Science.gov (United States)

    Developing statistical models that estimate the probability of developing cervical cancer over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

  5. Risk analysis for rumor propagation in metropolises based on improved 8-state ICSAR model and dynamic personal activity trajectories

    Science.gov (United States)

    Zhang, N.; Huang, H.; Duarte, M.; Zhang, J.

    2016-06-01

    Social media has developed extremely fast in metropolises in recent years resulting in more and more rumors disturbing our daily lives. Knowing the characteristics of rumor propagation in metropolises can help the government make efficient rumor refutation plans. In this paper, we established a dynamic spatio-temporal comprehensive risk assessment model for rumor propagation based on an improved 8-state ICSAR model (Ignorant, Information Carrier, Information Spreader, Advocate, Removal), large personal activity trajectory data, and governmental rumor refutation (anti-rumor) scenarios. Combining these relevant data with the 'big' traffic data on the use of subways, buses, and taxis, we simulated daily oral communications among inhabitants in Beijing. In order to analyze rumor and anti-rumor competition in the actual social network, personal resistance, personal preference, conformity, rumor intensity, government rumor refutation and other influencing factors were considered. Based on the developed risk assessment model, a long-term dynamic rumor propagation simulation for a seven day period was conducted and a comprehensive rumor propagation risk distribution map was obtained. A set of the sensitivity analyses were conducted for different social media and propagation routes. We assessed different anti-rumor coverage ratios and the rumor-spreading thresholds at which the government started to launch anti-rumor actions. The results we obtained provide worthwhile references useful for governmental decision making towards control of social-disrupting rumors.

  6. Risk modelling in portfolio optimization

    Science.gov (United States)

    Lam, W. H.; Jaaman, Saiful Hafizah Hj.; Isa, Zaidi

    2013-09-01

    Risk management is very important in portfolio optimization. The mean-variance model has been used in portfolio optimization to minimize the investment risk. The objective of the mean-variance model is to minimize the portfolio risk and achieve the target rate of return. Variance is used as risk measure in the mean-variance model. The purpose of this study is to compare the portfolio composition as well as performance between the optimal portfolio of mean-variance model and equally weighted portfolio. Equally weighted portfolio means the proportions that are invested in each asset are equal. The results show that the portfolio composition of the mean-variance optimal portfolio and equally weighted portfolio are different. Besides that, the mean-variance optimal portfolio gives better performance because it gives higher performance ratio than the equally weighted portfolio.

  7. Models for Pesticide Risk Assessment

    Science.gov (United States)

    EPA considers the toxicity of the pesticide as well as the amount of pesticide to which a person or the environments may be exposed in risk assessment. Scientists use mathematical models to predict pesticide concentrations in exposure assessment.

  8. Differentiated risk models in portfolio optimization: a comparative analysis of the degree of diversification and performance in the São Paulo Stock Exchange (BOVESPA

    Directory of Open Access Journals (Sweden)

    Ivan Ricardo Gartner

    2012-08-01

    Full Text Available Faced with so many risk modeling alternatives in portfolio optimization, several questions arise regarding their legitimacy, utility and applicability. In particular, a question arises involving the adherence of the alternative models with regard to the basic presupposition of Markowitz's classical model, with regard to the concept of diversification as a means of controlling the relationship between risk and return within a process of optimization. In this context, the aim of this article is to explore the risk-differentiated configurations that entropy can provide, from the point of view of the repercussions that these have on the degree of diversification and on portfolios performance. The reach of this objective requires that a comparative analysis is made between models that include entropy in their formulation and the classic Markowitz model. In order to contribute to this debate, this article proposes that adaptations are made to the models of relative minimum entropy and of maximum entropy, so that these can be applied to investment portfolio optimizations. The comparative analysis was based on performance indicators and on a ratio of the degree of portfolio diversification. The portfolios were formed by considering a sample of fourteen assets that compose the IBOVESPA, which were projected during the period from January 2007 to December 2009, and took into account the matrices of covariance that were formed as from January 1999. When comparing the Markowitz model with two models that were constructed to represent new risk configurations based on entropy optimization, the present study concluded that the first model was far superior to the others. Not only did the Markowitz model present better accumulated nominal yields, it also presented a far greater predictive efficiency and better effective performance, when considering the trade-off between risk and return. However, with regards to diversification, the Markowitz model concentrated

  9. Risk modelling study for carotid endarterectomy.

    Science.gov (United States)

    Kuhan, G; Gardiner, E D; Abidia, A F; Chetter, I C; Renwick, P M; Johnson, B F; Wilkinson, A R; McCollum, P T

    2001-12-01

    The aims of this study were to identify factors that influence the risk of stroke or death following carotid endarterectomy (CEA) and to develop a model to aid in comparative audit of vascular surgeons and units. A series of 839 CEAs performed by four vascular surgeons between 1992 and 1999 was analysed. Multiple logistic regression analysis was used to model the effect of 15 possible risk factors on the 30-day risk of stroke or death. Outcome was compared for four surgeons and two units after adjustment for the significant risk factors. The overall 30-day stroke or death rate was 3.9 per cent (29 of 741). Heart disease, diabetes and stroke were significant risk factors. The 30-day predicted stroke or death rates increased with increasing risk scores. The observed 30-day stroke or death rate was 3.9 per cent for both vascular units and varied from 3.0 to 4.2 per cent for the four vascular surgeons. Differences in the outcomes between the surgeons and vascular units did not reach statistical significance after risk adjustment. Diabetes, heart disease and stroke are significant risk factors for stroke or death following CEA. The risk score model identified patients at higher risk and aided in comparative audit.

  10. Spatial analysis and risk mapping of soil-transmitted helminth infections in Brazil, using Bayesian geostatistical models.

    Science.gov (United States)

    Scholte, Ronaldo G C; Schur, Nadine; Bavia, Maria E; Carvalho, Edgar M; Chammartin, Frédérique; Utzinger, Jürg; Vounatsou, Penelope

    2013-11-01

    Soil-transmitted helminths (Ascaris lumbricoides, Trichuris trichiura and hookworm) negatively impact the health and wellbeing of hundreds of millions of people, particularly in tropical and subtropical countries, including Brazil. Reliable maps of the spatial distribution and estimates of the number of infected people are required for the control and eventual elimination of soil-transmitted helminthiasis. We used advanced Bayesian geostatistical modelling, coupled with geographical information systems and remote sensing to visualize the distribution of the three soil-transmitted helminth species in Brazil. Remotely sensed climatic and environmental data, along with socioeconomic variables from readily available databases were employed as predictors. Our models provided mean prevalence estimates for A. lumbricoides, T. trichiura and hookworm of 15.6%, 10.1% and 2.5%, respectively. By considering infection risk and population numbers at the unit of the municipality, we estimate that 29.7 million Brazilians are infected with A. lumbricoides, 19.2 million with T. trichiura and 4.7 million with hookworm. Our model-based maps identified important risk factors related to the transmission of soiltransmitted helminths and confirm that environmental variables are closely associated with indices of poverty. Our smoothed risk maps, including uncertainty, highlight areas where soil-transmitted helminthiasis control interventions are most urgently required, namely in the North and along most of the coastal areas of Brazil. We believe that our predictive risk maps are useful for disease control managers for prioritising control interventions and for providing a tool for more efficient surveillance-response mechanisms.

  11. Modeling renewable energy company risk

    International Nuclear Information System (INIS)

    Sadorsky, Perry

    2012-01-01

    The renewable energy sector is one of the fastest growing components of the energy industry and along with this increased demand for renewable energy there has been an increase in investing and financing activities. The tradeoff between risk and return in the renewable energy sector is, however, precarious. Renewable energy companies are often among the riskiest types of companies to invest in and for this reason it is necessary to have a good understanding of the risk factors. This paper uses a variable beta model to investigate the determinants of renewable energy company risk. The empirical results show that company sales growth has a negative impact on company risk while oil price increases have a positive impact on company risk. When oil price returns are positive and moderate, increases in sales growth can offset the impact of oil price returns and this leads to lower systematic risk.

  12. Genetic and Environmental Risk for Chronic Pain and the Contribution of Risk Variants for Major Depressive Disorder: A Family-Based Mixed-Model Analysis.

    Science.gov (United States)

    McIntosh, Andrew M; Hall, Lynsey S; Zeng, Yanni; Adams, Mark J; Gibson, Jude; Wigmore, Eleanor; Hagenaars, Saskia P; Davies, Gail; Fernandez-Pujals, Ana Maria; Campbell, Archie I; Clarke, Toni-Kim; Hayward, Caroline; Haley, Chris S; Porteous, David J; Deary, Ian J; Smith, Daniel J; Nicholl, Barbara I; Hinds, David A; Jones, Amy V; Scollen, Serena; Meng, Weihua; Smith, Blair H; Hocking, Lynne J

    2016-08-01

    Chronic pain is highly prevalent and a significant source of disability, yet its genetic and environmental risk factors are poorly understood. Its relationship with major depressive disorder (MDD) is of particular importance. We sought to test the contribution of genetic factors and shared and unique environment to risk of chronic pain and its correlation with MDD in Generation Scotland: Scottish Family Health Study (GS:SFHS). We then sought to replicate any significant findings in the United Kingdom Biobank study. Using family-based mixed-model analyses, we examined the contribution of genetics and shared family environment to chronic pain by spouse, sibling, and household relationships. These analyses were conducted in GS:SFHS (n = 23,960), a family- and population-based study of individuals recruited from the Scottish population through their general practitioners. We then examined and partitioned the correlation between chronic pain and MDD and estimated the contribution of genetic factors and shared environment in GS:SFHS. Finally, we used data from two independent genome-wide association studies to test whether chronic pain has a polygenic architecture and examine whether genomic risk of psychiatric disorder predicted chronic pain and whether genomic risk of chronic pain predicted MDD. These analyses were conducted in GS:SFHS and repeated in UK Biobank, a study of 500,000 from the UK population, of whom 112,151 had genotyping and phenotypic data. Chronic pain is a moderately heritable trait (heritability = 38.4%, 95% CI 33.6% to 43.9%) that is significantly concordant in spouses (variance explained 18.7%, 95% CI 9.5% to 25.1%). Chronic pain is positively correlated with depression (ρ = 0.13, 95% CI 0.11 to 0.15, p = 2.72x10-68) and shows a tendency to cluster within families for genetic reasons (genetic correlation = 0.51, 95%CI 0.40 to 0.62, p = 8.24x10-19). Polygenic risk profiles for pain, generated using independent GWAS data, were associated with

  13. Genetic and Environmental Risk for Chronic Pain and the Contribution of Risk Variants for Major Depressive Disorder: A Family-Based Mixed-Model Analysis.

    Directory of Open Access Journals (Sweden)

    Andrew M McIntosh

    2016-08-01

    Full Text Available Chronic pain is highly prevalent and a significant source of disability, yet its genetic and environmental risk factors are poorly understood. Its relationship with major depressive disorder (MDD is of particular importance. We sought to test the contribution of genetic factors and shared and unique environment to risk of chronic pain and its correlation with MDD in Generation Scotland: Scottish Family Health Study (GS:SFHS. We then sought to replicate any significant findings in the United Kingdom Biobank study.Using family-based mixed-model analyses, we examined the contribution of genetics and shared family environment to chronic pain by spouse, sibling, and household relationships. These analyses were conducted in GS:SFHS (n = 23,960, a family- and population-based study of individuals recruited from the Scottish population through their general practitioners. We then examined and partitioned the correlation between chronic pain and MDD and estimated the contribution of genetic factors and shared environment in GS:SFHS. Finally, we used data from two independent genome-wide association studies to test whether chronic pain has a polygenic architecture and examine whether genomic risk of psychiatric disorder predicted chronic pain and whether genomic risk of chronic pain predicted MDD. These analyses were conducted in GS:SFHS and repeated in UK Biobank, a study of 500,000 from the UK population, of whom 112,151 had genotyping and phenotypic data. Chronic pain is a moderately heritable trait (heritability = 38.4%, 95% CI 33.6% to 43.9% that is significantly concordant in spouses (variance explained 18.7%, 95% CI 9.5% to 25.1%. Chronic pain is positively correlated with depression (ρ = 0.13, 95% CI 0.11 to 0.15, p = 2.72x10-68 and shows a tendency to cluster within families for genetic reasons (genetic correlation = 0.51, 95%CI 0.40 to 0.62, p = 8.24x10-19. Polygenic risk profiles for pain, generated using independent GWAS data, were associated

  14. Spatial Analysis GIS Model for Identifying the Risk Induced by Landslides. A Case Study: A.T.U. of Șieu

    Directory of Open Access Journals (Sweden)

    Dorel Colniţă

    2016-11-01

    Full Text Available The risk induced by landslides on residential infrastructure, transport infrastructure and agricultural land causes problems of local management that need to be solved by reducing negative effects and decrease the frequency of their occurrence. This study followed the development and implementation of a model for identifying the risk induced by landslides through the analysis of spatial occurrence probability for landslides at the administrative territorial unit of Șieu, following the semi-quantitative method governed in Romania by G.D. no 447/2003 and then through the exposure of housing infrastructure at landslides was possible to frame landslides on risk classes. The entire approach was based on GIS spatial analysis, creating a specific detailed database of causing and triggering factors of landslides and not at least, a database for risk receptors, in this study, represented by the constructions of villages associated with the studied administrative territorial units. The final result of the model highlights the framing of constructions on qualitative risk classes at landslides, revealing the elements of infrastructure that need post and pre event measures of protection.

  15. Gender Analysis of Risk in Innovation System

    DEFF Research Database (Denmark)

    Ayinde, Ope; Muchie, Mammo; Abaniyan, E. O.

    2011-01-01

    the new maize variety. The analytical tools used include descriptive statistics, regression model; risk utility functions and risk parameter analysis. The result showed that invasion by animals, disease and pest, lack of access to credit wind and price fluctuation were the major risk facing the maize......This study analyzed risk by gender in innovation in Kwara state, Nigeria, using downy mildew resistant maize production as case study. The study employed primary and secondary data. The primary data were collected from well-structured questionnaires administered to both male and female producing...... producers in the area in the usage of the new innovation. The study also revealed that male producers were willing to take risk in the new maize variety production than the female, while the females were more indifferent to the risk involved in the new maize production variety than males. None...

  16. Risk-oriented analysis of the German prototype fast breeder reactor SNR-300: off-site accident consequence model and results of the study

    International Nuclear Information System (INIS)

    Bayer, A.; Ehrhardt, J.

    1984-01-01

    Accident off-site consequence calculations and risk assessments performed for the ''risk oriented analysis'' of the German prototype fast breeder reactor SNR-300 were performed with a modified version of the off-site accident consequence model UFOMOD. The modifications mainly relate to the deposition and resuspension processes, the ingestion model, and the dose factors. Consequence calculations at the site of Kalkar on the Rhine River were performed for 115 weather sequences in 36 wind directions. They were based on seven release categories evaluated for the SNR-300 with two different fueling strategies: plutonium from Magnox reactors only and plutonium from light water reactors and Magnox reactors. In parallel, the corresponding frequencies of occurrence are determined. The following results are generated: 1. complementary cumulative frequency distribution functions for collective fatalities and collective doses 2. expected values of the collective fatalities and collective doses as well as distance-dependent expected values of individual fatality 3. contributions of the different exposure pathways to fatalities with respect to the various organs. For comparison with the risk of a PWR-1300, calculations for the PWR-1300 of the ''German Risk Study'' were repeated with the same modified consequence model. Comparison shows that smaller risks result for the SNR-300. However, the confidence interval bandwidths obtained for the frequencies of the release categories for the SNR-300 are larger than those of the PWR-1300

  17. Information risk and security modeling

    Science.gov (United States)

    Zivic, Predrag

    2005-03-01

    This research paper presentation will feature current frameworks to addressing risk and security modeling and metrics. The paper will analyze technical level risk and security metrics of Common Criteria/ISO15408, Centre for Internet Security guidelines, NSA configuration guidelines and metrics used at this level. Information IT operational standards view on security metrics such as GMITS/ISO13335, ITIL/ITMS and architectural guidelines such as ISO7498-2 will be explained. Business process level standards such as ISO17799, COSO and CobiT will be presented with their control approach to security metrics. Top level, the maturity standards such as SSE-CMM/ISO21827, NSA Infosec Assessment and CobiT will be explored and reviewed. For each defined level of security metrics the research presentation will explore the appropriate usage of these standards. The paper will discuss standards approaches to conducting the risk and security metrics. The research findings will demonstrate the need for common baseline for both risk and security metrics. This paper will show the relation between the attribute based common baseline and corporate assets and controls for risk and security metrics. IT will be shown that such approach spans over all mentioned standards. The proposed approach 3D visual presentation and development of the Information Security Model will be analyzed and postulated. Presentation will clearly demonstrate the benefits of proposed attributes based approach and defined risk and security space for modeling and measuring.

  18. Cabin Environment Physics Risk Model

    Science.gov (United States)

    Mattenberger, Christopher J.; Mathias, Donovan Leigh

    2014-01-01

    This paper presents a Cabin Environment Physics Risk (CEPR) model that predicts the time for an initial failure of Environmental Control and Life Support System (ECLSS) functionality to propagate into a hazardous environment and trigger a loss-of-crew (LOC) event. This physics-of failure model allows a probabilistic risk assessment of a crewed spacecraft to account for the cabin environment, which can serve as a buffer to protect the crew during an abort from orbit and ultimately enable a safe return. The results of the CEPR model replace the assumption that failure of the crew critical ECLSS functionality causes LOC instantly, and provide a more accurate representation of the spacecraft's risk posture. The instant-LOC assumption is shown to be excessively conservative and, moreover, can impact the relative risk drivers identified for the spacecraft. This, in turn, could lead the design team to allocate mass for equipment to reduce overly conservative risk estimates in a suboptimal configuration, which inherently increases the overall risk to the crew. For example, available mass could be poorly used to add redundant ECLSS components that have a negligible benefit but appear to make the vehicle safer due to poor assumptions about the propagation time of ECLSS failures.

  19. ProRisk : risk analysis instrument : developed for William properties

    NARCIS (Netherlands)

    van Doorn, W.H.W.; Egeberg, Ingrid; Hendrickx, Kristoff; Kahramaner, Y.; Masseur, B.; Waijers, Koen; Weglicka, K.A.

    2005-01-01

    This report presents a Risk Analysis Instrument developed for William Properties. Based on the analysis, it appears that the practice of Risk Analysis exists within the organization, yet rather implicit. The Risk Analysis Instrument comes with a package of four components: an activity diagram, a

  20. The air emissions risk assessment model (AERAM)

    International Nuclear Information System (INIS)

    Gratt, L.B.

    1991-01-01

    AERAM is an environmental analysis and power generation station investment decision support tool. AERAM calculates the public health risk (in terms of the lifetime cancers) in the nearby population from pollutants released into the air. AERAM consists of four main subroutines: Emissions, Air, Exposure and Risk. The Emission subroutine uses power plant parameters to calculate the expected release of the pollutants. A coal-fired and oil-fired power plant are currently available. A gas-fired plant model is under preparation. The release of the pollutants into the air is followed by their dispersal in the environment. The dispersion in the Air Subroutine uses the Environmental Protection Agency's model, Industrial Source Complex-Long Term. Additional dispersion models (Industrial Source Complex - Short Term and Cooling Tower Drift) are being implemented for future AERAM versions. The Expose Subroutine uses the ambient concentrations to compute population exposures for the pollutants of concern. The exposures are used with corresponding dose-response model in the Risk Subroutine to estimate both the total population risk and individual risk. The risk for the dispersion receptor-population centroid for the maximum concentration is also calculated for regulatory-population purposes. In addition, automated interfaces with AirTox (an air risk decision model) have been implemented to extend AERAM's steady-state single solution to the decision-under-uncertainty domain. AERAM was used for public health risks, the investment decision for additional pollution control systems based on health risk reductions, and the economics of fuel vs. health risk tradeoffs. AERAM provides that state-of-the-art capability for evaluating the public health impact airborne toxic substances in response to regulations and public concern

  1. Index analysis and human health risk model application for evaluating ambient air-heavy metal contamination in Chemical Valley Sarnia.

    Science.gov (United States)

    Olawoyin, Richard; Schweitzer, Linda; Zhang, Kuangyuan; Okareh, Oladapo; Slates, Kevin

    2018-02-01

    The impacts of air emissions as a consequence of industrial activities around communities of human habitation have been extensively reported. This study is the first to assess potential adverse human health effects in the Chemical Valley Sarnia (CVS) area, around the St. Clair River, using health risk models, ecological and pollution indices. Large quantities of particulate matters (PM) are generated from anthropogenic activities, which contain several heavy metals in trace quantities with potentially adverse effects to humans and environmental health. The distribution, and human health impact assessment of trace element concentrations in PM fractions were examined. Elemental concentrations of As, Cd, Cr (VI), Cu, Fe, Mn, Pb, Ni, Zn were determined in the PM size-segregated samples collected from the CVS area between 2014 and 2017. The results showed relatively high concentration of PM air quality guidelines. Pb concentration (143.03 ± 46.87ηg/m 3 ) was 3.6 times higher than the air quality standards of NAAQS. Cr (VI) showed moderate to considerable contamination ( C f =4) in the CVS while Cr (VI), Pb, and Ni had enrichment factor E f < 3 (minimal), signifying contributions from anthropogenic activities. Pollution load index (P Li ) value observed was 1.4 indicating human health risk from the PM, especially for the children in the area. The deposition fluxes (DΦ) showed that PM-bound metals could potentially bypass the head airways and cause damages to the tracheobronchial tree, increasing the human health risks of nephroblastomasis development. The main route of entry for the heavy metal bound PM in humans were observed as through ingestion and inhalation. The highest total excess cancer risks observed for children (6.7×10 -4 ) and adult (1.0×10 -4 ) indicating potential cancer effects. The Incremental Lifetime Cancer Risk (ILCR) increased from Pb < Ni < Cd < Cr (VI) < As. Overall, children are more likely to develop carcinogenic and non-carcinogenic health

  2. Common approach of risks analysis

    International Nuclear Information System (INIS)

    Noviello, L.; Naviglio, A.

    1996-01-01

    Although, following the resolutions of the High German Court, the protection level of the human beings is an objective which can change in time, it is obvious that it is an important point when there is a risk for the population. This is true more particularly for the industrial plants whose possible accidents could affect the population. The accidents risk analysis indicates that there is no conceptual difference between the risks of a nuclear power plant and those of the other industrial plants as chemical plants, the gas distribution system and the hydraulic dams. A legislation analysis induced by the Seveso Directive for the industrial risks give some important indications which should always be followed. This work analyses more particularly the legislative situation in different European countries and identifies some of the most important characteristics. Indeed, for most of the countries, the situation is different and it is a later difficulties source for nuclear power plants. In order to strengthen this reasoning, this paper presents some preliminary results of an analysis of a nuclear power plant following the approach of other industrial plants. In conclusion, it will be necessary to analyse again the risks assessment approach for nuclear power plants because the real protection level of human beings in a country is determined by the less regulated of the dangerous industrial plants existing at the surroundings. (O.M.)

  3. Risk Characterization uncertainties associated description, sensitivity analysis

    International Nuclear Information System (INIS)

    Carrillo, M.; Tovar, M.; Alvarez, J.; Arraez, M.; Hordziejewicz, I.; Loreto, I.

    2013-01-01

    The power point presentation is about risks to the estimated levels of exposure, uncertainty and variability in the analysis, sensitivity analysis, risks from exposure to multiple substances, formulation of guidelines for carcinogenic and genotoxic compounds and risk subpopulations

  4. Fuzzy audit risk modeling algorithm

    Directory of Open Access Journals (Sweden)

    Zohreh Hajihaa

    2011-07-01

    Full Text Available Fuzzy logic has created suitable mathematics for making decisions in uncertain environments including professional judgments. One of the situations is to assess auditee risks. During recent years, risk based audit (RBA has been regarded as one of the main tools to fight against fraud. The main issue in RBA is to determine the overall audit risk an auditor accepts, which impact the efficiency of an audit. The primary objective of this research is to redesign the audit risk model (ARM proposed by auditing standards. The proposed model of this paper uses fuzzy inference systems (FIS based on the judgments of audit experts. The implementation of proposed fuzzy technique uses triangular fuzzy numbers to express the inputs and Mamdani method along with center of gravity are incorporated for defuzzification. The proposed model uses three FISs for audit, inherent and control risks, and there are five levels of linguistic variables for outputs. FISs include 25, 25 and 81 rules of if-then respectively and officials of Iranian audit experts confirm all the rules.

  5. Risk factors and visual fatigue of baggage X-ray security screeners: a structural equation modelling analysis.

    Science.gov (United States)

    Yu, Rui-Feng; Yang, Lin-Dong; Wu, Xin

    2017-05-01

    This study identified the risk factors influencing visual fatigue in baggage X-ray security screeners and estimated the strength of correlations between those factors and visual fatigue using structural equation modelling approach. Two hundred and five X-ray security screeners participated in a questionnaire survey. The result showed that satisfaction with the VDT's physical features and the work environment conditions were negatively correlated with the intensity of visual fatigue, whereas job stress and job burnout had direct positive influences. The path coefficient between the image quality of VDT and visual fatigue was not significant. The total effects of job burnout, job stress, the VDT's physical features and the work environment conditions on visual fatigue were 0.471, 0.469, -0.268 and -0.251 respectively. These findings indicated that both extrinsic factors relating to VDT and workplace environment and psychological factors including job burnout and job stress should be considered in the workplace design and work organisation of security screening tasks to reduce screeners' visual fatigue. Practitioner Summary: This study identified the risk factors influencing visual fatigue in baggage X-ray security screeners and estimated the strength of correlations between those factors and visual fatigue. The findings were of great importance to the workplace design and the work organisation of security screening tasks to reduce screeners' visual fatigue.

  6. Standardised risk analysis as a communication tool

    International Nuclear Information System (INIS)

    Pluess, Ch.; Montanarini, M.; Bernauer, M.

    1998-01-01

    Full text of publication follows: several European countries require a risk analysis for the production, storage or transport a dangerous goods. This requirement imposes considerable administrative effort for some sectors of the industry. In order to minimize the effort of such studies, a generic risk analysis for an industrial sector proved to help. Standardised procedures can consequently be derived for efficient performance of the risk investigations. This procedure was successfully established in Switzerland for natural gas transmission lines and fossil fuel storage plants. The development process of the generic risk analysis involved an intense discussion between industry and authorities about methodology of assessment and the criteria of acceptance. This process finally led to scientific consistent modelling tools for risk analysis and to an improved communication from the industry to the authorities and the public. As a recent example, the Holland-Italy natural gas transmission pipeline is demonstrated, where this method was successfully employed. Although this pipeline traverses densely populated areas in Switzerland, using this established communication method, the risk problems could be solved without delaying the planning process. (authors)

  7. Models of Economic Analysis

    OpenAIRE

    Adrian Ioana; Tiberiu Socaciu

    2013-01-01

    The article presents specific aspects of management and models for economic analysis. Thus, we present the main types of economic analysis: statistical analysis, dynamic analysis, static analysis, mathematical analysis, psychological analysis. Also we present the main object of the analysis: the technological activity analysis of a company, the analysis of the production costs, the economic activity analysis of a company, the analysis of equipment, the analysis of labor productivity, the anal...

  8. H15-42: CFD analysis for risk analysis in urban environments - Tilburg city case study

    NARCIS (Netherlands)

    Hulsbosch-Dam, C.; Mack, A.; Ratingen, S. van; Rosmuller, N.; Trijssenaar, I.

    2013-01-01

    For risk analysis studies, relatively simple dispersion models are generally applied, such as Gaussian dispersion and dense gas dispersion models. For rail transport risk analyses in the Netherlands, fixed consequence distances are applied for various standard scenarios of hazardous materials

  9. Carcinogenesis model analysis for breast cancer incidence among atomic bomb survivors and the implications for cancer risk estimate for radiological protection

    International Nuclear Information System (INIS)

    Kai, Michiaki; Kusama, Tomoko

    2000-01-01

    Breast cancer incidence is the highest risk due to radiation among atomic bomb survivors. The excess relative risk of the early-onset breast cancer seems to be remarkably high for the youngest age-at-exposure groups. The cancer risk estimate of breast cancer is a current issue in radiological protection. We used a two-stage stochastic model for carcinogenesis to analyze the breast cancer incidence among atomic bomb survivors (Kai, et al. Radiat. Res. 1997). Our purpose is to examine the dependence of radiation risk on age at exposure using the two-stage model and how to transfer it to other populations for radiological protection. We fitted the model assuming that radiation acts as an initiator and that the rate of radiation-induced mutation and background initiation mutation leading to baseline cancer are additive. We took two age-dependence, not attained age but age at exposure, of the spontaneous process into account. First, age-dependence of spontaneous initiation was expressed by a linear model. We also modeled the age-dependence of spontaneous net growth rate of initiated cells by a linear function. As far as radiation-induced initiation is concerned, we took a stepwise function other than a liner function into account. The analysis did not show that the radiation mutation for the youngest age-at-exposure groups below age 10 was higher than for the older groups. Furthermore, the incidence of female breast cancer in Japan is increasing and the birth cohort effect can be observed in atomic bomb survivors. Our model assumed that an acute exposure to atomic radiation can only initiate cancers and do not influence other stages of carcinogenesis, whereas spontaneous initiation and promotion are age-dependent to consider birth cohort effects. When these cohort effects are properly accounted for, the shape of the age-specific incidence curve in Japan is remarkably similar to the age-specific incidence in western populations (shown in figure). Recently Little and

  10. Model of MSD Risk Assessment at Workplace

    OpenAIRE

    K. Sekulová; M. Šimon

    2015-01-01

    This article focuses on upper-extremity musculoskeletal disorders risk assessment model at workplace. In this model are used risk factors that are responsible for musculoskeletal system damage. Based on statistic calculations the model is able to define what risk of MSD threatens workers who are under risk factors. The model is also able to say how MSD risk would decrease if these risk factors are eliminated.

  11. Overcoming barriers to integrating economic analysis into risk assessment.

    Science.gov (United States)

    Hoffmann, Sandra

    2011-09-01

    Regulatory risk analysis is designed to provide decisionmakers with a clearer understanding of how policies are likely to affect risk. The systems that produce risk are biological, physical, and social and economic. As a result, risk analysis is an inherently interdisciplinary task. Yet in practice, risk analysis has been interdisciplinary in only limited ways. Risk analysis could provide more accurate assessments of risk if there were better integration of economics and other social sciences into risk assessment itself. This essay examines how discussions about risk analysis policy have influenced the roles of various disciplines in risk analysis. It explores ways in which integrated bio/physical-economic modeling could contribute to more accurate assessments of risk. It reviews examples of the kind of integrated economics-bio/physical modeling that could be used to enhance risk assessment. The essay ends with a discussion of institutional barriers to greater integration of economic modeling into risk assessment and provides suggestions on how these might be overcome. © 2011 Society for Risk Analysis.

  12. Assessing the impact of uncertainty on flood risk estimates with reliability analysis using 1-D and 2-D hydraulic models

    Directory of Open Access Journals (Sweden)

    L. Altarejos-García

    2012-07-01

    Full Text Available This paper addresses the use of reliability techniques such as Rosenblueth's Point-Estimate Method (PEM as a practical alternative to more precise Monte Carlo approaches to get estimates of the mean and variance of uncertain flood parameters water depth and velocity. These parameters define the flood severity, which is a concept used for decision-making in the context of flood risk assessment. The method proposed is particularly useful when the degree of complexity of the hydraulic models makes Monte Carlo inapplicable in terms of computing time, but when a measure of the variability of these parameters is still needed. The capacity of PEM, which is a special case of numerical quadrature based on orthogonal polynomials, to evaluate the first two moments of performance functions such as the water depth and velocity is demonstrated in the case of a single river reach using a 1-D HEC-RAS model. It is shown that in some cases, using a simple variable transformation, statistical distributions of both water depth and velocity approximate the lognormal. As this distribution is fully defined by its mean and variance, PEM can be used to define the full probability distribution function of these flood parameters and so allowing for probability estimations of flood severity. Then, an application of the method to the same river reach using a 2-D Shallow Water Equations (SWE model is performed. Flood maps of mean and standard deviation of water depth and velocity are obtained, and uncertainty in the extension of flooded areas with different severity levels is assessed. It is recognized, though, that whenever application of Monte Carlo method is practically feasible, it is a preferred approach.

  13. Integration of Human Reliability Analysis Models into the Simulation-Based Framework for the Risk-Informed Safety Margin Characterization Toolkit

    International Nuclear Information System (INIS)

    Boring, Ronald; Mandelli, Diego; Rasmussen, Martin; Ulrich, Thomas; Groth, Katrina; Smith, Curtis

    2016-01-01

    This report presents an application of a computation-based human reliability analysis (HRA) framework called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER). HUNTER has been developed not as a standalone HRA method but rather as framework that ties together different HRA methods to model dynamic risk of human activities as part of an overall probabilistic risk assessment (PRA). While we have adopted particular methods to build an initial model, the HUNTER framework is meant to be intrinsically flexible to new pieces that achieve particular modeling goals. In the present report, the HUNTER implementation has the following goals: • Integration with a high fidelity thermal-hydraulic model capable of modeling nuclear power plant behaviors and transients • Consideration of a PRA context • Incorporation of a solid psychological basis for operator performance • Demonstration of a functional dynamic model of a plant upset condition and appropriate operator response This report outlines these efforts and presents the case study of a station blackout scenario to demonstrate the various modules developed to date under the HUNTER research umbrella.

  14. Integration of Human Reliability Analysis Models into the Simulation-Based Framework for the Risk-Informed Safety Margin Characterization Toolkit

    Energy Technology Data Exchange (ETDEWEB)

    Boring, Ronald [Idaho National Lab. (INL), Idaho Falls, ID (United States); Mandelli, Diego [Idaho National Lab. (INL), Idaho Falls, ID (United States); Rasmussen, Martin [Norwegian Univ. of Science and Technology, Trondheim (Norway). Social Research; Herberger, Sarah [Idaho National Lab. (INL), Idaho Falls, ID (United States); Ulrich, Thomas [Idaho National Lab. (INL), Idaho Falls, ID (United States); Groth, Katrina [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Smith, Curtis [Idaho National Lab. (INL), Idaho Falls, ID (United States)

    2016-06-01

    This report presents an application of a computation-based human reliability analysis (HRA) framework called the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER). HUNTER has been developed not as a standalone HRA method but rather as framework that ties together different HRA methods to model dynamic risk of human activities as part of an overall probabilistic risk assessment (PRA). While we have adopted particular methods to build an initial model, the HUNTER framework is meant to be intrinsically flexible to new pieces that achieve particular modeling goals. In the present report, the HUNTER implementation has the following goals: • Integration with a high fidelity thermal-hydraulic model capable of modeling nuclear power plant behaviors and transients • Consideration of a PRA context • Incorporation of a solid psychological basis for operator performance • Demonstration of a functional dynamic model of a plant upset condition and appropriate operator response This report outlines these efforts and presents the case study of a station blackout scenario to demonstrate the various modules developed to date under the HUNTER research umbrella.

  15. Trip report: workshop on risk analysis and geologic modeling in relation to the disposal of radioactive wastes into geological formations

    International Nuclear Information System (INIS)

    Claiborne, H.C.

    1977-01-01

    The Workshop was co-sponsored by the Commission of European Communities (CEC) and the Office of Economic Cooperation and Development/Nuclear Energy Agency (OECD/NEA), with primary object being to promote international cooperation in developing and using risk assessment techniques for the long-term safety assessment of waste disposal. The attendance was restricted to specialists in the field and a few observers; 43 people were in attendance representing 14 different countries. Nothing particularly new or novel was presented nor any formal cooperation agreed upon. However, there was a feeling that continued informal cooperation was helpful and should be continued. Greater or lesser degrees of formality could be decided later. The U.S. program was definitely more advanced and larger in scope than the others that were discussed. Countries that seemed to have significant programs include the Federal Republic of Germany, France, Canada, Sweden, and the CEC. Abstracts of papers are presented together with consensus reports on containment failure modes and geosphere transport modeling

  16. Model based risk assessment - the CORAS framework

    Energy Technology Data Exchange (ETDEWEB)

    Gran, Bjoern Axel; Fredriksen, Rune; Thunem, Atoosa P-J.

    2004-04-15

    Traditional risk analysis and assessment is based on failure-oriented models of the system. In contrast to this, model-based risk assessment (MBRA) utilizes success-oriented models describing all intended system aspects, including functional, operational and organizational aspects of the target. The target models are then used as input sources for complementary risk analysis and assessment techniques, as well as a basis for the documentation of the assessment results. The EU-funded CORAS project developed a tool-supported methodology for the application of MBRA in security-critical systems. The methodology has been tested with successful outcome through a series of seven trial within the telemedicine and ecommerce areas. The CORAS project in general and the CORAS application of MBRA in particular have contributed positively to the visibility of model-based risk assessment and thus to the disclosure of several potentials for further exploitation of various aspects within this important research field. In that connection, the CORAS methodology's possibilities for further improvement towards utilization in more complex architectures and also in other application domains such as the nuclear field can be addressed. The latter calls for adapting the framework to address nuclear standards such as IEC 60880 and IEC 61513. For this development we recommend applying a trial driven approach within the nuclear field. The tool supported approach for combining risk analysis and system development also fits well with the HRP proposal for developing an Integrated Design Environment (IDE) providing efficient methods and tools to support control room systems design. (Author)

  17. Implementing the Bayesian paradigm in risk analysis

    International Nuclear Information System (INIS)

    Aven, T.; Kvaloey, J.T.

    2002-01-01

    The Bayesian paradigm comprises a unified and consistent framework for analyzing and expressing risk. Yet, we see rather few examples of applications where the full Bayesian setting has been adopted with specifications of priors of unknown parameters. In this paper, we discuss some of the practical challenges of implementing Bayesian thinking and methods in risk analysis, emphasizing the introduction of probability models and parameters and associated uncertainty assessments. We conclude that there is a need for a pragmatic view in order to 'successfully' apply the Bayesian approach, such that we can do the assignments of some of the probabilities without adopting the somewhat sophisticated procedure of specifying prior distributions of parameters. A simple risk analysis example is presented to illustrate ideas

  18. What is a risk. [Quantitative risk analysis

    Energy Technology Data Exchange (ETDEWEB)

    Schoen, G [Physikalisch-Technische Bundesanstalt, Braunschweig (Germany, F.R.)

    1979-02-01

    The following article is a revised version of a lecture given by the author during the VDE meeting 'Technical Expert Activities' in Brunswick. First of all, the concept of 'risk' is discussed which leads to a probability scale which then permits a definition of the 'justifiable risk' as the boundary between 'hazard' and 'safety'. The boundary is quantified indirectly from laws, regulations, instructions, etc. to the 'Technological rules' for special fields of application by minimum requirement data. These viewpoints described in detail are not only of substantial significance for the creation of safety regulations but also for their application and consequently for jurisdiction.

  19. Computational modeling for irrigated agriculture planning. Part II: risk analysis Modelagem computacional para planejamento em agricultura irrigada: Parte II - Análise de risco

    Directory of Open Access Journals (Sweden)

    João C. F. Borges Júnior

    2008-09-01

    Full Text Available Techniques of evaluation of risks coming from inherent uncertainties to the agricultural activity should accompany planning studies. The risk analysis should be carried out by risk simulation using techniques as the Monte Carlo method. This study was carried out to develop a computer program so-called P-RISCO for the application of risky simulations on linear programming models, to apply to a case study, as well to test the results comparatively to the @RISK program. In the risk analysis it was observed that the average of the output variable total net present value, U, was considerably lower than the maximum U value obtained from the linear programming model. It was also verified that the enterprise will be front to expressive risk of shortage of water in the month of April, what doesn't happen for the cropping pattern obtained by the minimization of the irrigation requirement in the months of April in the four years. The scenario analysis indicated that the sale price of the passion fruit crop exercises expressive influence on the financial performance of the enterprise. In the comparative analysis it was verified the equivalence of P-RISCO and @RISK programs in the execution of the risk simulation for the considered scenario.Técnicas de avaliação de riscos procedentes de incertezas inerentes à atividade agrícola devem acompanhar os estudos de planejamento. A análise de risco pode ser desempenhada por meio de simulação, utilizando técnicas como o método de Monte Carlo. Neste trabalho, teve-se o objetivo de desenvolver um programa computacional, denominado P-RISCO, para utilização de simulações de risco em modelos de programação linear, aplicar a um estudo de caso e testar os resultados comparativamente ao programa @RISK. Na análise de risco, observou-se que a média da variável de saída, valor presente líquido total (U, foi consideravelmente inferior ao valor máximo de U obtido no modelo de programação linear. Constatou

  20. Project Portfolio Risk Identification and Analysis, Considering Project Risk Interactions and Using Bayesian Networks

    Directory of Open Access Journals (Sweden)

    Foroogh Ghasemi

    2018-05-01

    Full Text Available An organization’s strategic objectives are accomplished through portfolios. However, the materialization of portfolio risks may affect a portfolio’s sustainable success and the achievement of those objectives. Moreover, project interdependencies and cause–effect relationships between risks create complexity for portfolio risk analysis. This paper presents a model using Bayesian network (BN methodology for modeling and analyzing portfolio risks. To develop this model, first, portfolio-level risks and risks caused by project interdependencies are identified. Then, based on their cause–effect relationships all portfolio risks are organized in a BN. Conditional probability distributions for this network are specified and the Bayesian networks method is used to estimate the probability of portfolio risk. This model was applied to a portfolio of a construction company located in Iran and proved effective in analyzing portfolio risk probability. Furthermore, the model provided valuable information for selecting a portfolio’s projects and making strategic decisions.

  1. Terminological Ontologies for Risk and Vulnerability Analysis

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2014-01-01

    Risk and vulnerability analyses are an important preliminary stage in civil contingency planning. The Danish Emergency Management Agency has developed a generic model and a set of tools that may be used in the preparedness planning, i.e. for identifying and describing society’s critical functions......, for formulating threat scenarios and for assessing consequences. Terminological ontologies, which are systems of domain specific concepts comprising concept relations and characteristics, are useful, both when describing the central concepts of risk and vulnerability analysis (meta concepts), and for further...

  2. Approach to uncertainty in risk analysis

    Energy Technology Data Exchange (ETDEWEB)

    Rish, W.R.

    1988-08-01

    In the Fall of 1985 EPA's Office of Radiation Programs (ORP) initiated a project to develop a formal approach to dealing with uncertainties encountered when estimating and evaluating risks to human health and the environment. Based on a literature review of modeling uncertainty, interviews with ORP technical and management staff, and input from experts on uncertainty analysis, a comprehensive approach was developed. This approach recognizes by design the constraints on budget, time, manpower, expertise, and availability of information often encountered in ''real world'' modeling. It is based on the observation that in practice risk modeling is usually done to support a decision process. As such, the approach focuses on how to frame a given risk modeling problem, how to use that framing to select an appropriate mixture of uncertainty analyses techniques, and how to integrate the techniques into an uncertainty assessment that effectively communicates important information and insight to decision-makers. The approach is presented in this report. Practical guidance on characterizing and analyzing uncertainties about model form and quantities and on effectively communicating uncertainty analysis results is included. Examples from actual applications are presented.

  3. Approach to uncertainty in risk analysis

    International Nuclear Information System (INIS)

    Rish, W.R.

    1988-08-01

    In the Fall of 1985 EPA's Office of Radiation Programs (ORP) initiated a project to develop a formal approach to dealing with uncertainties encountered when estimating and evaluating risks to human health and the environment. Based on a literature review of modeling uncertainty, interviews with ORP technical and management staff, and input from experts on uncertainty analysis, a comprehensive approach was developed. This approach recognizes by design the constraints on budget, time, manpower, expertise, and availability of information often encountered in ''real world'' modeling. It is based on the observation that in practice risk modeling is usually done to support a decision process. As such, the approach focuses on how to frame a given risk modeling problem, how to use that framing to select an appropriate mixture of uncertainty analyses techniques, and how to integrate the techniques into an uncertainty assessment that effectively communicates important information and insight to decision-makers. The approach is presented in this report. Practical guidance on characterizing and analyzing uncertainties about model form and quantities and on effectively communicating uncertainty analysis results is included. Examples from actual applications are presented

  4. Risk analysis in radiosurgery treatments using risk matrices

    International Nuclear Information System (INIS)

    Delgado, J. M.; Sanchez Cayela, C.; Ramirez, M. L.; Perez, A.

    2011-01-01

    The aim of this study is the risk analysis process stereotactic single-dose radiotherapy and evaluation of those initiating events that lead to increased risk and a possible solution in the design of barriers.

  5. Risk Factors Analysis and Death Prediction in Some Life-Threatening Ailments Using Chi-Square Case-Based Reasoning (χ2 CBR) Model.

    Science.gov (United States)

    Adeniyi, D A; Wei, Z; Yang, Y

    2018-01-30

    A wealth of data are available within the health care system, however, effective analysis tools for exploring the hidden patterns in these datasets are lacking. To alleviate this limitation, this paper proposes a simple but promising hybrid predictive model by suitably combining the Chi-square distance measurement with case-based reasoning technique. The study presents the realization of an automated risk calculator and death prediction in some life-threatening ailments using Chi-square case-based reasoning (χ 2 CBR) model. The proposed predictive engine is capable of reducing runtime and speeds up execution process through the use of critical χ 2 distribution value. This work also showcases the development of a novel feature selection method referred to as frequent item based rule (FIBR) method. This FIBR method is used for selecting the best feature for the proposed χ 2 CBR model at the preprocessing stage of the predictive procedures. The implementation of the proposed risk calculator is achieved through the use of an in-house developed PHP program experimented with XAMP/Apache HTTP server as hosting server. The process of data acquisition and case-based development is implemented using the MySQL application. Performance comparison between our system, the NBY, the ED-KNN, the ANN, the SVM, the Random Forest and the traditional CBR techniques shows that the quality of predictions produced by our system outperformed the baseline methods studied. The result of our experiment shows that the precision rate and predictive quality of our system in most cases are equal to or greater than 70%. Our result also shows that the proposed system executes faster than the baseline methods studied. Therefore, the proposed risk calculator is capable of providing useful, consistent, faster, accurate and efficient risk level prediction to both the patients and the physicians at any time, online and on a real-time basis.

  6. Multivariate survival analysis and competing risks

    CERN Document Server

    Crowder, Martin J

    2012-01-01

    Multivariate Survival Analysis and Competing Risks introduces univariate survival analysis and extends it to the multivariate case. It covers competing risks and counting processes and provides many real-world examples, exercises, and R code. The text discusses survival data, survival distributions, frailty models, parametric methods, multivariate data and distributions, copulas, continuous failure, parametric likelihood inference, and non- and semi-parametric methods. There are many books covering survival analysis, but very few that cover the multivariate case in any depth. Written for a graduate-level audience in statistics/biostatistics, this book includes practical exercises and R code for the examples. The author is renowned for his clear writing style, and this book continues that trend. It is an excellent reference for graduate students and researchers looking for grounding in this burgeoning field of research.

  7. Human Plague Risk: Spatial-Temporal Models

    Science.gov (United States)

    Pinzon, Jorge E.

    2010-01-01

    This chpater reviews the use of spatial-temporal models in identifying potential risks of plague outbreaks into the human population. Using earth observations by satellites remote sensing there has been a systematic analysis and mapping of the close coupling between the vectors of the disease and climate variability. The overall result is that incidence of plague is correlated to positive El Nino/Southem Oscillation (ENSO).

  8. Risk Analysis Group annual progress report 1984

    International Nuclear Information System (INIS)

    1985-06-01

    The activities of the Risk Analysis Group at Risoe during 1984 are presented. These include descriptions in some detail of work on general development topics and risk analysis performed as contractor. (author)

  9. Geomatic 3d Modeling of a Statue (also) for Structural Analysis and Risk Evaluation: the Example of San Giovannino Martelli in Florence

    Science.gov (United States)

    Spangher, A.; Visintini, D.; Tucci, G.; Bonora, V.

    2017-05-01

    This work has been developed among the researches of a PhD thesis in Civil and Environmental Engineering and Architecture of the University of Udine in cooperation with the GECO Laboratory of the University of Florence. It focuses on the interaction between Geomatics and Structural Analysis, both applied to cultural heritage, and expressly to artefacts and structures in stone materials, like the case study of this paper, the marble statue called "San Giovannino Martelli" (Saint John the Baptist) conserved in Florence. At the beginning, some interesting examples of surveying and structural analyses on statues are reported, in order to remind the complementary tasks and requirements of geomatics and structural analysis. Current laser scanning systems can accurately survey the geometry of a statue or any cultural heritage artefact, essential to understand their structural behaviour and resilience capability. Afterwards, following the few Italian regulations in this field, the possible risks of museum goods are described: topics of this part are more familiar for structural engineers as object classification, seismic reactions, damage mechanisms, possible movements (adherent, slipping and oscillation), dynamic domains, anyway necessary steps to evaluate the risk and so to define eventual interventions. The artistic description of the statue, its debated attribution to Donatello or/and to Desiderio da Settignano and its history is later recalled, remembering that the surveying has been done for the idea to 3D print a replica and to place it in the original place. Having used a close range laser scanner, the obtained 3D model has an impressive geometrical Level of Detail (LoD), whose geometric features are explained in the paper, underlying that such extremely detailed mesh is directly given as output from the laser scanner software. The model simplifications by four decimation are therefore explained and also changes to geometry, like shifts on centre of the mass or

  10. GEOMATIC 3D MODELING OF A STATUE (ALSO FOR STRUCTURAL ANALYSIS AND RISK EVALUATION: THE EXAMPLE OF SAN GIOVANNINO MARTELLI IN FLORENCE

    Directory of Open Access Journals (Sweden)

    A. Spangher

    2017-05-01

    Full Text Available This work has been developed among the researches of a PhD thesis in Civil and Environmental Engineering and Architecture of the University of Udine in cooperation with the GECO Laboratory of the University of Florence. It focuses on the interaction between Geomatics and Structural Analysis, both applied to cultural heritage, and expressly to artefacts and structures in stone materials, like the case study of this paper, the marble statue called “San Giovannino Martelli” (Saint John the Baptist conserved in Florence. At the beginning, some interesting examples of surveying and structural analyses on statues are reported, in order to remind the complementary tasks and requirements of geomatics and structural analysis. Current laser scanning systems can accurately survey the geometry of a statue or any cultural heritage artefact, essential to understand their structural behaviour and resilience capability. Afterwards, following the few Italian regulations in this field, the possible risks of museum goods are described: topics of this part are more familiar for structural engineers as object classification, seismic reactions, damage mechanisms, possible movements (adherent, slipping and oscillation, dynamic domains, anyway necessary steps to evaluate the risk and so to define eventual interventions. The artistic description of the statue, its debated attribution to Donatello or/and to Desiderio da Settignano and its history is later recalled, remembering that the surveying has been done for the idea to 3D print a replica and to place it in the original place. Having used a close range laser scanner, the obtained 3D model has an impressive geometrical Level of Detail (LoD, whose geometric features are explained in the paper, underlying that such extremely detailed mesh is directly given as output from the laser scanner software. The model simplifications by four decimation are therefore explained and also changes to geometry, like shifts on

  11. The ATLAS Analysis Model

    CERN Multimedia

    Amir Farbin

    The ATLAS Analysis Model is a continually developing vision of how to reconcile physics analysis requirements with the ATLAS offline software and computing model constraints. In the past year this vision has influenced the evolution of the ATLAS Event Data Model, the Athena software framework, and physics analysis tools. These developments, along with the October Analysis Model Workshop and the planning for CSC analyses have led to a rapid refinement of the ATLAS Analysis Model in the past few months. This article introduces some of the relevant issues and presents the current vision of the future ATLAS Analysis Model. Event Data Model The ATLAS Event Data Model (EDM) consists of several levels of details, each targeted for a specific set of tasks. For example the Event Summary Data (ESD) stores calorimeter cells and tracking system hits thereby permitting many calibration and alignment tasks, but will be only accessible at particular computing sites with potentially large latency. In contrast, the Analysis...

  12. Risk terrain modeling predicts child maltreatment.

    Science.gov (United States)

    Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

    2016-12-01

    As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  13. A background to risk analysis. Vol. 3

    International Nuclear Information System (INIS)

    Taylor, J.R.

    1979-01-01

    This 4-volumes report gives a background of ideas, principles, and examples which might be of use in developing practical methods for risk analysis. Some of the risk analysis techniques described are somewhat experimental. The report is written in an introductory style, but where some point needs further justifi- cation or evaluation, this is given in the form of a chapter appenix. In this way, it is hoped that the report can serve two purposes, - as a basis for starting risk analysis work and as a basis for discussing effectiveness of risk analysis procedures. The report should be seen as a preliminary stage, prior to a program of industrial trials of risk analysis methods. Vol. 3 contains chapters on quantification of risk, failure and accident probability, risk analysis and design, and examles of risk analysis for process plant. (BP)

  14. A background risk analysis. Vol. 1

    International Nuclear Information System (INIS)

    Taylor, J.R.

    1979-01-01

    This 4-volumes report gives a background of ideas, principles, and examples which might be of use in developing practical methods for risk analysis. Some of the risk analysis techniques, described are somewhat experimental. The report is written in an introductory style, but where some point needs further justification or evaluation, this is given in the form of a chapter appendix. In this way, it is hoped that the report can serve two purposes, - as a basis for starting risk analysis work and as a basis for discussing effectiveness of risk analysis procedures. The report should be seen as a preliminary stage, prior to a program of industrial trials of risk analysis methods. Vol. 1 contains a short history of risk analysis, and chapters on risk, failures, errors and accidents, and general procedures for risk analysis. (BP)

  15. Modeling Terrorism Risk to the Air Transportation System: An Independent Assessment of TSA’s Risk Management Analysis Tool and Associated Methods

    Science.gov (United States)

    2012-01-01

    considered under RMAT, expanding the range of attack pathways available to attackers, and inclusion of off-airport freight pro- cessing, catering ...perspectives on risk from Boeing and from consultations with Randy Harris of Delta Airlines , Eric Thacker of the Air Transport Association, and Chris...multiple first-class airline tickets) and, as a result, less attractive than publicly available information, which is relatively inexpensive. It

  16. Generalised linear mixed models analysis of risk factors for contamination of Danish broiler flocks with Salmonella typhimurium

    DEFF Research Database (Denmark)

    Chriél, Mariann; Stryhn, H.; Dauphin, G.

    1999-01-01

    are the broiler flocks (about 4000 flocks) which are clustered within producers. Broiler flocks with ST-infected parent stocks show increased risk of salmonella infection, and also the hatchery affects the salmonella status significantly. Among the rearing factors, only the use of medicine as well as the time......We present a retrospective observational study of risk factors associated with the occurrence of Salmonella typhimurium (ST) in Danish broiler flocks. The study is based on recordings from 1994 in the ante-mortem database maintained by the Danish Poultry Council. The epidemiological units...

  17. Risk analysis as a decision tool

    International Nuclear Information System (INIS)

    Yadigaroglu, G.; Chakraborty, S.

    1985-01-01

    From 1983 - 1985 a lecture series entitled ''Risk-benefit analysis'' was held at the Swiss Federal Institute of Technology (ETH), Zurich, in cooperation with the Central Department for the Safety of Nuclear Installations of the Swiss Federal Agency of Energy Economy. In that setting the value of risk-oriented evaluation models as a decision tool in safety questions was discussed on a broad basis. Experts of international reputation from the Federal Republic of Germany, France, Canada, the United States and Switzerland have contributed to report in this joint volume on the uses of such models. Following an introductory synopsis on risk analysis and risk assessment the book deals with practical examples in the fields of medicine, nuclear power, chemistry, transport and civil engineering. Particular attention is paid to the dialogue between analysts and decision makers taking into account the economic-technical aspects and social values. The recent chemical disaster in the Indian city of Bhopal again signals the necessity of such analyses. All the lectures were recorded individually. (orig./HP) [de

  18. Risk Measurement and Risk Modelling Using Applications of Vine Copulas

    Directory of Open Access Journals (Sweden)

    David E. Allen

    2017-09-01

    Full Text Available This paper features an application of Regular Vine copulas which are a novel and recently developed statistical and mathematical tool which can be applied in the assessment of composite financial risk. Copula-based dependence modelling is a popular tool in financial applications, but is usually applied to pairs of securities. By contrast, Vine copulas provide greater flexibility and permit the modelling of complex dependency patterns using the rich variety of bivariate copulas which may be arranged and analysed in a tree structure to explore multiple dependencies. The paper features the use of Regular Vine copulas in an analysis of the co-dependencies of 10 major European Stock Markets, as represented by individual market indices and the composite STOXX 50 index. The sample runs from 2005 to the end of 2013 to permit an exploration of how correlations change indifferent economic circumstances using three different sample periods: pre-GFC (January 2005–July 2007, GFC (July 2007– September 2009, and post-GFC periods (September 2009–December 2013. The empirical results suggest that the dependencies change in a complex manner, and are subject to change in different economic circumstances. One of the attractions of this approach to risk modelling is the flexibility in the choice of distributions used to model co-dependencies. The practical application of Regular Vine metrics is demonstrated via an example of the calculation of the VaR of a portfolio made up of the indices.

  19. Migration Stress, Poor Mental Health, and Engagement in Sex with High-Risk Partners: A Mediation Modeling Analysis of Data from Rural-to-Urban Migrants in China.

    Science.gov (United States)

    Yu, Bin; Chen, Xinguang; Yan, Yaqiong; Gong, Jie; Li, Fang; Robserson, Emily

    2017-12-01

    There is a growing need for better understanding of mechanisms underpinning the relationship between migration stress and HIV risk behaviors for the development of HIV prevention and control policy. Survey data from a random sample of 1,293 Chinese rural-to-urban migrants were analyzed. Stress was assessed using the Domestic Migration Stress Questionnaire (DMSQ), mental health status was assessed using the Brief Symptoms Inventory (BSI), and having sex with high risk partners was assessed as if ever have had sex with high risk partners (e.g., sex workers, intravenous injection drug users, blood donors, persons infected with HIV, persons with sexually transmitted infection, and same gender partners) in the past year. The proposed relationship was tested using mediation modeling method. Among the sample, 5.5% reported having had sex with high-risk partners in the past year. Mediation analysis indicated that the relationship between DMSQ scores and having sex with high-risk partners was mediated by BSI (coefficient =0.41, 95% CI [0.21, 0.65]), including its components of somatization (0.32 [0.15, 0.53]), obsessive-compulsive disorder (0.31 [0.07, 0.55]), depression (0.45 [0.23, 0.72]), anxiety (0.41 [0.23, 0.63]), and hostility (0.35 [0.17, 0.56]). Furthermore, the effect was more pronounced in males than in females. The study findings provide new data advancing our understanding of the mechanism of engagement in risky sex, underscoring the need for the HIV prevention policies in China to pay more attention to mental health of the rural-to-urban migrant population.

  20. Risk analysis for earth dam overtopping

    Directory of Open Access Journals (Sweden)

    Mo Chongxun

    2008-06-01

    Full Text Available In this paper, a model of overtopping risk under the joint effects of floods and wind waves, which is based on risk analysis theory and takes into account the uncertainties of floods, wind waves, reservoir capacity and discharge capacity of the spillway, is proposed and applied to the Chengbihe Reservoir in Baise City in Guangxi Zhuang Autonomous Region. The simulated results indicate that the flood control limiting level can be raised by 0.40 m under the condition that the reservoir overtopping risk is controlled within a mean variance of 5×10−6. As a result, the reservoir storage will increase to 16 million m3 and electrical energy generation and other functions of the reservoir will also increase greatly.

  1. Quantitative Risk Analysis: Method And Process

    Directory of Open Access Journals (Sweden)

    Anass BAYAGA

    2010-03-01

    Full Text Available Recent and past studies (King III report, 2009: 73-75; Stoney 2007;Committee of Sponsoring Organisation-COSO, 2004, Bartell, 2003; Liebenberg and Hoyt, 2003; Reason, 2000; Markowitz 1957 lament that although, the introduction of quantifying risk to enhance degree of objectivity in finance for instance was quite parallel to its development in the manufacturing industry, it is not the same in Higher Education Institution (HEI. In this regard, the objective of the paper was to demonstrate the methods and process of Quantitative Risk Analysis (QRA through likelihood of occurrence of risk (phase I. This paper serves as first of a two-phased study, which sampled hundred (100 risk analysts in a University in the greater Eastern Cape Province of South Africa.The analysis of likelihood of occurrence of risk by logistic regression and percentages were conducted to investigate whether there were a significant difference or not between groups (analyst in respect of QRA.The Hosmer and Lemeshow test was non-significant with a chi-square(X2 =8.181; p = 0.300, which indicated that there was a good model fit, since the data did not significantly deviate from the model. The study concluded that to derive an overall likelihood rating that indicated the probability that a potential risk may be exercised within the construct of an associated threat environment, the following governing factors must be considered: (1 threat source motivation and capability (2 nature of the vulnerability (3 existence and effectiveness of current controls (methods and process.

  2. Risk analysis in oil spill response planning

    International Nuclear Information System (INIS)

    Chernoplekov, A.N.; Alexandrov, A.A.

    2005-01-01

    Tiered response is a basic approach to emergency plans, including oil spill response (OSR). This paper delineates a huge set of accidental scenarios within a certain tier of response generated by a computer during risk assessment. Parameters such as the amount of oil spilled, duration of discharge and types of losses should be provided in OSR scenarios. Examples of applications include offshore installations, sub sea or onshore pipelines, and localized onshore facilities. The paper demonstrates how to use risk analysis results for delineating all likely spills into groups that need a specific tier response. The best world practices and Russian regulatory approaches were outlined and compared. Corresponding algorithms were developed and their application in pipelines was presented. The algorithm combines expert's skills and spill trajectory modeling with the net environmental benefit analysis principle into the incident specific emergency response planning. 9 refs., 13 tabs., 2 figs

  3. Integrated Reliability and Risk Analysis System (IRRAS)

    International Nuclear Information System (INIS)

    Russell, K.D.; McKay, M.K.; Sattison, M.B.; Skinner, N.L.; Wood, S.T.; Rasmuson, D.M.

    1992-01-01

    The Integrated Reliability and Risk Analysis System (IRRAS) is a state-of-the-art, microcomputer-based probabilistic risk assessment (PRA) model development and analysis tool to address key nuclear plant safety issues. IRRAS is an integrated software tool that gives the user the ability to create and analyze fault trees and accident sequences using a microcomputer. This program provides functions that range from graphical fault tree construction to cut set generation and quantification. Version 1.0 of the IRRAS program was released in February of 1987. Since that time, many user comments and enhancements have been incorporated into the program providing a much more powerful and user-friendly system. This version has been designated IRRAS 4.0 and is the subject of this Reference Manual. Version 4.0 of IRRAS provides the same capabilities as Version 1.0 and adds a relational data base facility for managing the data, improved functionality, and improved algorithm performance

  4. Risk matrix model for rotating equipment

    Directory of Open Access Journals (Sweden)

    Wassan Rano Khan

    2014-07-01

    Full Text Available Different industries have various residual risk levels for their rotating equipment. Accordingly the occurrence rate of the failures and associated failure consequences categories are different. Thus, a generalized risk matrix model is developed in this study which can fit various available risk matrix standards. This generalized risk matrix will be helpful to develop new risk matrix, to fit the required risk assessment scenario for rotating equipment. Power generation system was taken as case study. It was observed that eight subsystems were under risk. Only vibration monitor system was under high risk category, while remaining seven subsystems were under serious and medium risk categories.

  5. Traditional Dietary Pattern Increases Risk of Prostate Cancer in Argentina: Results of a Multilevel Modeling and Bias Analysis from a Case-Control Study

    International Nuclear Information System (INIS)

    Niclis, C.; Roman, M. D.; Eynard, A. R.; Diaz, M. D. P.

    2015-01-01

    There is increasing evidence that dietary habits play a role in prostate cancer (PC) occurrence. Argentinean cancer risk studies require additional attention because of the singular dietary pattern of this population. A case-control study (147 PC cases, 300 controls) was conducted in Cordoba (Argentina) throughout 2008-2013. A principal component factor analysis was performed to identify dietary patterns. A mixed logistic regression model was applied, taking into account family history of cancer. Possible bias was evaluated by probabilistic bias analysis. Four dietary patterns were identified: Traditional (fatty red meats, offal, processed meat, starchy vegetables, added sugars and sweets, candies, fats, and vegetable oils), Prudent (non starchy vegetables, whole grains), Carbohydrate (sodas/juices and bakery products), and Cheese (cheeses). High adherence to the Traditional (OR 2.82, 95 % CI: 1.569-5.099) and Carbohydrate Patterns (OR 2.14, 95 % CI: 1.470-3.128) showed a promoting effect for PC, whereas the Prudent and Cheese Patterns were independent factors. PC occurrence was also associated with family history of PC. Bias adjusted ORs indicate that the validity of the present study is acceptable. High adherence to characteristic Argentinean dietary patterns was associated with increased PC risk. Our results incorporate original contributions to knowledge about scenarios in South American dietary patterns and PC occurrence.

  6. Traditional Dietary Pattern Increases Risk of Prostate Cancer in Argentina: Results of a Multilevel Modeling and Bias Analysis from a Case-Control Study

    Directory of Open Access Journals (Sweden)

    Camila Niclis

    2015-01-01

    Full Text Available There is increasing evidence that dietary habits play a role in prostate cancer (PC occurrence. Argentinean cancer risk studies require additional attention because of the singular dietary pattern of this population. A case-control study (147 PC cases, 300 controls was conducted in Córdoba (Argentina throughout 2008–2013. A principal component factor analysis was performed to identify dietary patterns. A mixed logistic regression model was applied, taking into account family history of cancer. Possible bias was evaluated by probabilistic bias analysis. Four dietary patterns were identified: Traditional (fatty red meats, offal, processed meat, starchy vegetables, added sugars and sweets, candies, fats, and vegetable oils, Prudent (nonstarchy vegetables, whole grains, Carbohydrate (sodas/juices and bakery products, and Cheese (cheeses. High adherence to the Traditional (OR 2.82, 95%CI: 1.569–5.099 and Carbohydrate Patterns (OR 2.14, 95%CI: 1.470–3.128 showed a promoting effect for PC, whereas the Prudent and Cheese Patterns were independent factors. PC occurrence was also associated with family history of PC. Bias adjusted ORs indicate that the validity of the present study is acceptable. High adherence to characteristic Argentinean dietary patterns was associated with increased PC risk. Our results incorporate original contributions to knowledge about scenarios in South American dietary patterns and PC occurrence.

  7. Analysis of intervention strategies for inhalation exposure to polycyclic aromatic hydrocarbons and associated lung cancer risk based on a Monte Carlo population exposure assessment model.

    Science.gov (United States)

    Zhou, Bin; Zhao, Bin

    2014-01-01

    It is difficult to evaluate and compare interventions for reducing exposure to air pollutants, including polycyclic aromatic hydrocarbons (PAHs), a widely found air pollutant in both indoor and outdoor air. This study presents the first application of the Monte Carlo population exposure assessment model to quantify the effects of different intervention strategies on inhalation exposure to PAHs and the associated lung cancer risk. The method was applied to the population in Beijing, China, in the year 2006. Several intervention strategies were designed and studied, including atmospheric cleaning, smoking prohibition indoors, use of clean fuel for cooking, enhancing ventilation while cooking and use of indoor cleaners. Their performances were quantified by population attributable fraction (PAF) and potential impact fraction (PIF) of lung cancer risk, and the changes in indoor PAH concentrations and annual inhalation doses were also calculated and compared. The results showed that atmospheric cleaning and use of indoor cleaners were the two most effective interventions. The sensitivity analysis showed that several input parameters had major influence on the modeled PAH inhalation exposure and the rankings of different interventions. The ranking was reasonably robust for the remaining majority of parameters. The method itself can be extended to other pollutants and in different places. It enables the quantitative comparison of different intervention strategies and would benefit intervention design and relevant policy making.

  8. Analysis of intervention strategies for inhalation exposure to polycyclic aromatic hydrocarbons and associated lung cancer risk based on a Monte Carlo population exposure assessment model.

    Directory of Open Access Journals (Sweden)

    Bin Zhou

    Full Text Available It is difficult to evaluate and compare interventions for reducing exposure to air pollutants, including polycyclic aromatic hydrocarbons (PAHs, a widely found air pollutant in both indoor and outdoor air. This study presents the first application of the Monte Carlo population exposure assessment model to quantify the effects of different intervention strategies on inhalation exposure to PAHs and the associated lung cancer risk. The method was applied to the population in Beijing, China, in the year 2006. Several intervention strategies were designed and studied, including atmospheric cleaning, smoking prohibition indoors, use of clean fuel for cooking, enhancing ventilation while cooking and use of indoor cleaners. Their performances were quantified by population attributable fraction (PAF and potential impact fraction (PIF of lung cancer risk, and the changes in indoor PAH concentrations and annual inhalation doses were also calculated and compared. The results showed that atmospheric cleaning and use of indoor cleaners were the two most effective interventions. The sensitivity analysis showed that several input parameters had major influence on the modeled PAH inhalation exposure and the rankings of different interventions. The ranking was reasonably robust for the remaining majority of parameters. The method itself can be extended to other pollutants and in different places. It enables the quantitative comparison of different intervention strategies and would benefit intervention design and relevant policy making.

  9. Modeling intelligent adversaries for terrorism risk assessment: some necessary conditions for adversary models.

    Science.gov (United States)

    Guikema, Seth

    2012-07-01

    Intelligent adversary modeling has become increasingly important for risk analysis, and a number of different approaches have been proposed for incorporating intelligent adversaries in risk analysis models. However, these approaches are based on a range of often-implicit assumptions about the desirable properties of intelligent adversary models. This "Perspective" paper aims to further risk analysis for situations involving intelligent adversaries by fostering a discussion of the desirable properties for these models. A set of four basic necessary conditions for intelligent adversary models is proposed and discussed. These are: (1) behavioral accuracy to the degree possible, (2) computational tractability to support decision making, (3) explicit consideration of uncertainty, and (4) ability to gain confidence in the model. It is hoped that these suggested necessary conditions foster discussion about the goals and assumptions underlying intelligent adversary modeling in risk analysis. © 2011 Society for Risk Analysis.

  10. Methods and models used in comparative risk studies

    International Nuclear Information System (INIS)

    Devooght, J.

    1983-01-01

    Comparative risk studies make use of a large number of methods and models based upon a set of assumptions incompletely formulated or of value judgements. Owing to the multidimensionality of risks and benefits, the economic and social context may notably influence the final result. Five classes of models are briefly reviewed: accounting of fluxes of effluents, radiation and energy; transport models and health effects; systems reliability and bayesian analysis; economic analysis of reliability and cost-risk-benefit analysis; decision theory in presence of uncertainty and multiple objectives. Purpose and prospect of comparative studies are assessed in view of probable diminishing returns for large generic comparisons [fr

  11. Computational Aspects of Dam Risk Analysis: Findings and Challenges

    Directory of Open Access Journals (Sweden)

    Ignacio Escuder-Bueno

    2016-09-01

    Full Text Available In recent years, risk analysis techniques have proved to be a useful tool to inform dam safety management. This paper summarizes the outcomes of three themes related to dam risk analysis discussed in the Benchmark Workshops organized by the International Commission on Large Dams Technical Committee on “Computational Aspects of Analysis and Design of Dams.” In the 2011 Benchmark Workshop, estimation of the probability of failure of a gravity dam for the sliding failure mode was discussed. Next, in 2013, the discussion focused on the computational challenges of the estimation of consequences in dam risk analysis. Finally, in 2015, the probability of sliding and overtopping in an embankment was analyzed. These Benchmark Workshops have allowed a complete review of numerical aspects for dam risk analysis, showing that risk analysis methods are a very useful tool to analyze the risk of dam systems, including downstream consequence assessments and the uncertainty of structural models.

  12. Outcome prediction in plasmacytoma of bone: a risk model utilizing bone marrow flow cytometry and light-chain analysis.

    Science.gov (United States)

    Hill, Quentin A; Rawstron, Andy C; de Tute, Ruth M; Owen, Roger G

    2014-08-21

    The purpose of this study was to use multiparameter flow cytometry to detect occult marrow disease (OMD) in patients with solitary plasmacytoma of bone and assess its value in predicting outcome. Aberrant phenotype plasma cells were demonstrable in 34 of 50 (68%) patients and comprised a median of 0.52% of bone marrow leukocytes. With a median follow-up of 3.7 years, 28 of 50 patients have progressed with a median time to progression (TTP) of 18 months. Progression was documented in 72% of patients with OMD vs 12.5% without (median TTP, 26 months vs not reached; P = .003). Monoclonal urinary light chains (ULC) were similarly predictive of outcome because progression was documented in 91% vs 44% without (median TTP, 16 vs 82 months; P < .001). By using both parameters, it was possible to define patients with an excellent outcome (lacking both OMD and ULC, 7.7% progression) and high-risk patients (OMD and/or ULC, 75% progression; P = .001). Trials of systemic therapy are warranted in high-risk patients. © 2014 by The American Society of Hematology.

  13. A methodological framework for detecting ulcers' risk in diabetic foot subjects by combining gait analysis, a new musculoskeletal foot model and a foot finite element model.

    Science.gov (United States)

    Scarton, Alessandra; Guiotto, Annamaria; Malaquias, Tiago; Spolaor, Fabiola; Sinigaglia, Giacomo; Cobelli, Claudio; Jonkers, Ilse; Sawacha, Zimi

    2018-02-01

    Diabetic foot is one of the most debilitating complications of diabetes and may lead to plantar ulcers. In the last decade, gait analysis, musculoskeletal modelling (MSM) and finite element modelling (FEM) have shown their ability to contribute to diabetic foot prevention and suggested that the origin of the plantar ulcers is in deeper tissue layers rather than on the plantar surface. Hence the aim of the current work is to develop a methodology that improves FEM-derived foot internal stresses prediction, for diabetic foot prevention applications. A 3D foot FEM was combined with MSM derived force to predict the sites of excessive internal stresses on the foot. In vivo gait analysis data, and an MRI scan of a foot from a healthy subject were acquired and used to develop a six degrees of freedom (6 DOF) foot MSM and a 3D subject-specific foot FEM. Ankle kinematics were applied as boundary conditions to the FEM together with: 1. only Ground Reaction Forces (GRFs); 2. OpenSim derived extrinsic muscles forces estimated with a standard OpenSim MSM; 3. extrinsic muscle forces derived through the (6 DOF) foot MSM; 4. intrinsic and extrinsic muscles forces derived through the 6 DOF foot MSM. For model validation purposes, simulated peak pressures were extracted and compared with those measured experimentally. The importance of foot muscles in controlling plantar pressure distribution and internal stresses is confirmed by the improved accuracy in the estimation of the peak pressures obtained with the inclusion of intrinsic and extrinsic muscle forces. Copyright © 2017 Elsevier B.V. All rights reserved.

  14. Soil pH Errors Propagation from Measurements to Spatial Predictions - Cost Benefit Analysis and Risk Assessment Implications for Practitioners and Modelers

    Science.gov (United States)

    Owens, P. R.; Libohova, Z.; Seybold, C. A.; Wills, S. A.; Peaslee, S.; Beaudette, D.; Lindbo, D. L.

    2017-12-01

    The measurement errors and spatial prediction uncertainties of soil properties in the modeling community are usually assessed against measured values when available. However, of equal importance is the assessment of errors and uncertainty impacts on cost benefit analysis and risk assessments. Soil pH was selected as one of the most commonly measured soil properties used for liming recommendations. The objective of this study was to assess the error size from different sources and their implications with respect to management decisions. Error sources include measurement methods, laboratory sources, pedotransfer functions, database transections, spatial aggregations, etc. Several databases of measured and predicted soil pH were used for this study including the United States National Cooperative Soil Survey Characterization Database (NCSS-SCDB), the US Soil Survey Geographic (SSURGO) Database. The distribution of errors among different sources from measurement methods to spatial aggregation showed a wide range of values. The greatest RMSE of 0.79 pH units was from spatial aggregation (SSURGO vs Kriging), while the measurement methods had the lowest RMSE of 0.06 pH units. Assuming the order of data acquisition based on the transaction distance i.e. from measurement method to spatial aggregation the RMSE increased from 0.06 to 0.8 pH units suggesting an "error propagation". This has major implications for practitioners and modeling community. Most soil liming rate recommendations are based on 0.1 pH unit increments, while the desired soil pH level increments are based on 0.4 to 0.5 pH units. Thus, even when the measured and desired target soil pH are the same most guidelines recommend 1 ton ha-1 lime, which translates in 111 ha-1 that the farmer has to factor in the cost-benefit analysis. However, this analysis need to be based on uncertainty predictions (0.5-1.0 pH units) rather than measurement errors (0.1 pH units) which would translate in 555-1,111 investment that

  15. Models for assessing and managing credit risk

    Directory of Open Access Journals (Sweden)

    Neogradi Slađana

    2014-01-01

    Full Text Available This essay deals with the definition of a model for assessing and managing credit risk. Risk is an inseparable component of any average and normal credit transaction. Looking at the different aspects of the identification and classification of risk in the banking industry as well as representation of the key components of modern risk management. In the first part of the essay will analyze how the impact of credit risk on bank and empirical models for determining the financial difficulties in which the company can be found. Bank on the basis of these models can reduce number of approved risk assets. In the second part, we consider models for improving credit risk with emphasis on Basel I, II and III, and the third part, we conclude that the most appropriate model and gives the best effect for measuring credit risk in domestic banks.

  16. LANDSAFE: LANDING SITE RISK ANALYSIS SOFTWARE FRAMEWORK

    Directory of Open Access Journals (Sweden)

    R. Schmidt

    2012-08-01

    Full Text Available The European Space Agency (ESA is planning a Lunar Lander mission in the 2018 timeframe that will demonstrate precise soft landing at the polar regions of the Moon. To ensure a safe and successful landing a careful risk analysis has to be carried out. This is comprised of identifying favorable target areas and evaluating the surface conditions in these areas. Features like craters, boulders, steep slopes, rough surfaces and shadow areas have to be identified in order to assess the risk associated to a landing site in terms of a successful touchdown and subsequent surface operation of the lander. In addition, global illumination conditions at the landing site have to be simulated and analyzed. The Landing Site Risk Analysis software framework (LandSAfe is a system for the analysis, selection and certification of safe landing sites on the lunar surface. LandSAfe generates several data products including high resolution digital terrain models (DTMs, hazard maps, illumination maps, temperature maps and surface reflectance maps which assist the user in evaluating potential landing site candidates. This paper presents the LandSAfe system and describes the methods and products of the different modules. For one candidate landing site on the rim of Shackleton crater at the south pole of the Moon a high resolution DTM is showcased.

  17. Streamlining project delivery through risk analysis.

    Science.gov (United States)

    2015-08-01

    Project delivery is a significant area of concern and is subject to several risks throughout Plan Development : Process (PDP). These risks are attributed to major areas of project development, such as environmental : analysis, right-of-way (ROW) acqu...

  18. The influence of sensation-seeking and parental and peer influences in early adolescence on risk involvement through middle adolescence: A structural equation modeling analysis.

    Science.gov (United States)

    Wang, Bo; Deveaux, Lynette; Lunn, Sonja; Dinaj-Koci, Veronica; Li, Xiaoming; Stanton, Bonita

    2016-03-01

    This study examined the relationships between youth and parental sensation-seeking, peer influence, parental monitoring and youth risk involvement in adolescence using structural equation modeling. Beginning in grade-six, longitudinal data were collected from 543 students over three years. Youth sensation-seeking in grade six contributed to risk involvement in early adolescence (grades six and seven) indirectly through increased peer risk influence and decreased parental monitoring but did not have a direct contribution. It contributed directly and indirectly to risk involvement in middle adolescence (grades eight and nine). Parent sensation-seeking at baseline was positively associated with peer risk influence and negatively associated with parental monitoring; it had no direct effect on adolescent risk involvement. Parental monitoring buffers negative peer influence on adolescent risk involvement. Results highlight the need for intervention efforts to provide normative feedback about adolescent risky behaviors and to vary among families in which parents and/or youth have high sensation-seeking propensities.

  19. Formal Modeling and Verification of Opportunity-enabled Risk Management

    OpenAIRE

    Aldini, Alessandro; Seigneur, Jean-Marc; Ballester Lafuente, Carlos; Titi, Xavier; Guislain, Jonathan

    2015-01-01

    With the advent of the Bring-Your-Own-Device (BYOD) trend, mobile work is achieving a widespread diffusion that challenges the traditional view of security standard and risk management. A recently proposed model, called opportunity-enabled risk management (OPPRIM), aims at balancing the analysis of the major threats that arise in the BYOD setting with the analysis of the potential increased opportunities emerging in such an environment, by combining mechanisms of risk estimation with trust an...

  20. Development of QSAR models using artificial neural network analysis for risk assessment of repeated-dose, reproductive, and developmental toxicities of cosmetic ingredients.

    Science.gov (United States)

    Hisaki, Tomoka; Aiba Née Kaneko, Maki; Yamaguchi, Masahiko; Sasa, Hitoshi; Kouzuki, Hirokazu

    2015-04-01

    Use of laboratory animals for systemic toxicity testing is subject to strong ethical and regulatory constraints, but few alternatives are yet available. One possible approach to predict systemic toxicity of chemicals in the absence of experimental data is quantitative structure-activity relationship (QSAR) analysis. Here, we present QSAR models for prediction of maximum "no observed effect level" (NOEL) for repeated-dose, developmental and reproductive toxicities. NOEL values of 421 chemicals for repeated-dose toxicity, 315 for reproductive toxicity, and 156 for developmental toxicity were collected from Japan Existing Chemical Data Base (JECDB). Descriptors to predict toxicity were selected based on molecular orbital (MO) calculations, and QSAR models employing multiple independent descriptors as the input layer of an artificial neural network (ANN) were constructed to predict NOEL values. Robustness of the models was indicated by the root-mean-square (RMS) errors after 10-fold cross-validation (0.529 for repeated-dose, 0.508 for reproductive, and 0.558 for developmental toxicity). Evaluation of the models in terms of the percentages of predicted NOELs falling within factors of 2, 5 and 10 of the in-vivo-determined NOELs suggested that the model is applicable to both general chemicals and the subset of chemicals listed in International Nomenclature of Cosmetic Ingredients (INCI). Our results indicate that ANN models using in silico parameters have useful predictive performance, and should contribute to integrated risk assessment of systemic toxicity using a weight-of-evidence approach. Availability of predicted NOELs will allow calculation of the margin of safety, as recommended by the Scientific Committee on Consumer Safety (SCCS).

  1. Development of probabilistic risk analysis library

    International Nuclear Information System (INIS)

    Soga, Shota; Kirimoto, Yukihiro; Kanda, Kenichi

    2015-01-01

    We developed a library that is designed to perform level 1 Probabilistic Risk Analysis using Binary Decision Diagram (BDD). In particular, our goal is to develop a library that will allow Japanese electric utilities to take the advantages of BDD that can solve Event Tree (ET) and Fault Tree (FT) models analytically. Using BDD, the library supports negation in FT which allows more flexible modeling of ET/FT. The library is written by C++ within an object-oriented framework using open source software. The library itself is a header-only library so that Japanese electric utilities can take advantages of its transparency to speed up development and to build their own software for their specific needs. In this report, the basic capabilities of the library is briefly described. In addition, several applications of the library are demonstrated including validation of MCS evaluation of PRA model and evaluation of corrective and preventive maintenance considering common cause failure. (author)

  2. MODELING CREDIT RISK THROUGH CREDIT SCORING

    OpenAIRE

    Adrian Cantemir CALIN; Oana Cristina POPOVICI

    2014-01-01

    Credit risk governs all financial transactions and it is defined as the risk of suffering a loss due to certain shifts in the credit quality of a counterpart. Credit risk literature gravitates around two main modeling approaches: the structural approach and the reduced form approach. In addition to these perspectives, credit risk assessment has been conducted through a series of techniques such as credit scoring models, which form the traditional approach. This paper examines the evolution of...

  3. The study of the risk management model of construction project

    International Nuclear Information System (INIS)

    Jiang Bo; Feng Yanping; Liu Changbin

    2010-01-01

    The paper first analyzed the development of the risk management of construction project and the risk management processes, and then briefly introduced the risk management experience of foreign project management. From the project management by objectives point of view, the greatest risk came from the lack of clarity of the objectives in the project management, which led to the project's risk emergence. In the analysis of the principles of the project objectives identification and risk allocation, the paper set up a project management model which insurance companies involved in the whole process of the project management, and simply analyzed the roles of insurance company at last. (authors)

  4. On the validation of risk analysis-A commentary

    International Nuclear Information System (INIS)

    Rosqvist, Tony

    2010-01-01

    Aven and Heide (2009) [1] provided interesting views on the reliability and validation of risk analysis. The four validation criteria presented are contrasted with modelling features related to the relative frequency-based and Bayesian approaches to risk analysis. In this commentary I would like to bring forth some issues on validation that partly confirm and partly suggest changes in the interpretation of the introduced validation criteria-especially, in the context of low probability-high consequence systems. The mental model of an expert in assessing probabilities is argued to be a key notion in understanding the validation of a risk analysis.

  5. Modeling Research Project Risks with Fuzzy Maps

    Science.gov (United States)

    Bodea, Constanta Nicoleta; Dascalu, Mariana Iuliana

    2009-01-01

    The authors propose a risks evaluation model for research projects. The model is based on fuzzy inference. The knowledge base for fuzzy process is built with a causal and cognitive map of risks. The map was especially developed for research projects, taken into account their typical lifecycle. The model was applied to an e-testing research…

  6. Risk analysis of nuclear safeguards regulations

    International Nuclear Information System (INIS)

    Al-Ayat, R.A.; Altman, W.D.; Judd, B.R.

    1982-06-01

    The Aggregated Systems Model (ASM), a probabilisitic risk analysis tool for nuclear safeguards, was applied to determine benefits and costs of proposed amendments to NRC regulations governing nuclear material control and accounting systems. The objective of the amendments was to improve the ability to detect insiders attempting to steal large quantities of special nuclear material (SNM). Insider threats range from likely events with minor consequences to unlikely events with catastrophic consequences. Moreover, establishing safeguards regulations is complicated by uncertainties in threats, safeguards performance, and consequences, and by the subjective judgments and difficult trade-offs between risks and safeguards costs. The ASM systematically incorporates these factors in a comprehensive, analytical framework. The ASM was used to evaluate the effectiveness of current safeguards and to quantify the risk of SNM theft. Various modifications designed to meet the objectives of the proposed amendments to reduce that risk were analyzed. Safeguards effectiveness was judged in terms of the probability of detecting and preventing theft, the expected time to detection, and the expected quantity of SNM diverted in a year. Data were gathered in tours and interviews at NRC-licensed facilities. The assessment at each facility was begun by carefully selecting scenarios representing the range of potential insider threats. A team of analysts and facility managers assigned probabilities for detection and prevention events in each scenario. Using the ASM we computed the measures of system effectiveness and identified cost-effective safeguards modifications that met the objectives of the proposed amendments

  7. Risk Modelling for Passages in Approach Channel

    Directory of Open Access Journals (Sweden)

    Leszek Smolarek

    2013-01-01

    Full Text Available Methods of multivariate statistics, stochastic processes, and simulation methods are used to identify and assess the risk measures. This paper presents the use of generalized linear models and Markov models to study risks to ships along the approach channel. These models combined with simulation testing are used to determine the time required for continuous monitoring of endangered objects or period at which the level of risk should be verified.

  8. Modeling for operational event risk assessment

    International Nuclear Information System (INIS)

    Sattison, M.B.

    1997-01-01

    The U.S. Nuclear Regulatory Commission has been using risk models to evaluate the risk significance of operational events in U.S. commercial nuclear power plants for more seventeen years. During that time, the models have evolved in response to the advances in risk assessment technology and insights gained with experience. Evaluation techniques fall into two categories, initiating event assessments and condition assessments. The models used for these analyses have become uniquely specialized for just this purpose

  9. Operational risk quantification and modelling within Romanian insurance industry

    Directory of Open Access Journals (Sweden)

    Tudor Răzvan

    2017-07-01

    Full Text Available This paper aims at covering and describing the shortcomings of various models used to quantify and model the operational risk within insurance industry with a particular focus on Romanian specific regulation: Norm 6/2015 concerning the operational risk issued by IT systems. While most of the local insurers are focusing on implementing the standard model to compute the Operational Risk solvency capital required, the local regulator has issued a local norm that requires to identify and assess the IT based operational risks from an ISO 27001 perspective. The challenges raised by the correlations assumed in the Standard model are substantially increased by this new regulation that requires only the identification and quantification of the IT operational risks. The solvency capital requirement stipulated by the implementation of Solvency II doesn’t recommend a model or formula on how to integrate the newly identified risks in the Operational Risk capital requirements. In this context we are going to assess the academic and practitioner’s understanding in what concerns: The Frequency-Severity approach, Bayesian estimation techniques, Scenario Analysis and Risk Accounting based on risk units, and how they could support the modelling of operational risk that are IT based. Developing an internal model only for the operational risk capital requirement proved to be, so far, costly and not necessarily beneficial for the local insurers. As the IT component will play a key role in the future of the insurance industry, the result of this analysis will provide a specific approach in operational risk modelling that can be implemented in the context of Solvency II, in a particular situation when (internal or external operational risk databases are scarce or not available.

  10. Risk analysis and safety rationale

    International Nuclear Information System (INIS)

    Bengtsson, G.

    1989-01-01

    Decision making with respect to safety is becoming more and more complex. The risk involved must be taken into account together with numerous other factors such as the benefits, the uncertainties and the public perception. Can the decision maker be aided by some kind of system, general rules of thumb, or broader perspective on similar decisions? This question has been addressed in a joint Nordic project relating to nuclear power. Modern techniques for risk assessment and management have been studied, and parallels drawn to such areas as offshore safety and management of toxic chemicals in the environment. The report summarises the finding of 5 major technical reports which have been published in the NORD-series. The topics includes developments, uncertainties and limitations in probabilistic safety assessments, negligible risks, risk-cost trade-offs, optimisation of nuclear safety and radiation protection, and the role of risks in the decision making process. (author) 84 refs

  11. Korean risk assessment model for breast cancer risk prediction.

    Science.gov (United States)

    Park, Boyoung; Ma, Seung Hyun; Shin, Aesun; Chang, Myung-Chul; Choi, Ji-Yeob; Kim, Sungwan; Han, Wonshik; Noh, Dong-Young; Ahn, Sei-Hyun; Kang, Daehee; Yoo, Keun-Young; Park, Sue K

    2013-01-01

    We evaluated the performance of the Gail model for a Korean population and developed a Korean breast cancer risk assessment tool (KoBCRAT) based upon equations developed for the Gail model for predicting breast cancer risk. Using 3,789 sets of cases and controls, risk factors for breast cancer among Koreans were identified. Individual probabilities were projected using Gail's equations and Korean hazard data. We compared the 5-year and lifetime risk produced using the modified Gail model which applied Korean incidence and mortality data and the parameter estimators from the original Gail model with those produced using the KoBCRAT. We validated the KoBCRAT based on the expected/observed breast cancer incidence and area under the curve (AUC) using two Korean cohorts: the Korean Multicenter Cancer Cohort (KMCC) and National Cancer Center (NCC) cohort. The major risk factors under the age of 50 were family history, age at menarche, age at first full-term pregnancy, menopausal status, breastfeeding duration, oral contraceptive usage, and exercise, while those at and over the age of 50 were family history, age at menarche, age at menopause, pregnancy experience, body mass index, oral contraceptive usage, and exercise. The modified Gail model produced lower 5-year risk for the cases than for the controls (p = 0.017), while the KoBCRAT produced higher 5-year and lifetime risk for the cases than for the controls (pKorean women, especially urban women.

  12. The effectiveness and cost effectiveness of dark chocolate consumption as prevention therapy in people at high risk of cardiovascular disease: best case scenario analysis using a Markov model.

    Science.gov (United States)

    Zomer, Ella; Owen, Alice; Magliano, Dianna J; Liew, Danny; Reid, Christopher M

    2012-05-30

    To model the long term effectiveness and cost effectiveness of daily dark chocolate consumption in a population with metabolic syndrome at high risk of cardiovascular disease. Best case scenario analysis using a Markov model. Australian Diabetes, Obesity and Lifestyle study. 2013 people with hypertension who met the criteria for metabolic syndrome, with no history of cardiovascular disease and not receiving antihypertensive therapy. Treatment effects associated with dark chocolate consumption derived from published meta-analyses were used to determine the absolute number of cardiovascular events with and without treatment. Costs associated with cardiovascular events and treatments were applied to determine the potential amount of funding required for dark chocolate therapy to be considered cost effective. Daily consumption of dark chocolate (polyphenol content equivalent to 100 g of dark chocolate) can reduce cardiovascular events by 85 (95% confidence interval 60 to 105) per 10,000 population treated over 10 years. $A40 (£25; €31; $42) could be cost effectively spent per person per year on prevention strategies using dark chocolate. These results assume 100% compliance and represent a best case scenario. The blood pressure and cholesterol lowering effects of dark chocolate consumption are beneficial in the prevention of cardiovascular events in a population with metabolic syndrome. Daily dark chocolate consumption could be an effective cardiovascular preventive strategy in this population.

  13. A background to risk analysis. Vol. 2

    International Nuclear Information System (INIS)

    Taylor, J.R.

    1979-01-01

    This 4-volumes report gives a background of ideas, principles and examples which might be of use in developing practical methods for risk analysis. Some of the risk analysis techniques described are somewhat experimental. The report is written in an introductory style, but where some point needs further justification or evaluation, this is given in the form of a chapter appendix. In this way, it is hoped that the report can serve two purposes, - as a basis for starting risk analysis work and as a basis for discussing effectiveness of risk analysis procedures. The report should be seen as a preliminary stage, prior to a program of industrial trials of risk analysis methods. Vol. 2 treats generic methods of qualitative failure analysis. (BP)

  14. Risk Analysis of Telecom Enterprise Financing

    Institute of Scientific and Technical Information of China (English)

    YU Hua; SHU Hua-ying

    2005-01-01

    The main research objects in this paper are the causes searching and risk estimating method for telecom enterprises' financial risks. The multi-mode financing for telecom enterprises makes it flexible to induce the capital and obtain the profit by corresponding projects. But there are also potential risks going with these financing modes. After making analysis of categories and causes of telecom enterprises' financing risk, a method by Analytic Hierarchy Process (AHP) is put forward to estimating the financing risk. And the author makes her suggestion and opinion by example analysis, in order to provide some ideas and basis for telecom enterprise's financing decision-making.

  15. An investment plan for preventing child injuries using risk priority number of failure mode and effects analysis methodology and a multi-objective, multi-dimensional mixed 0-1 knapsack model

    International Nuclear Information System (INIS)

    Bas, Esra

    2011-01-01

    In this paper, a general framework for child injury prevention and a multi-objective, multi-dimensional mixed 0-1 knapsack model were developed to determine the optimal time to introduce preventive measures against child injuries. Furthermore, the model maximises the prevention of injuries with the highest risks for each age period by combining preventive measures and supervision as well as satisfying budget limits and supervision time constraints. The risk factors for each injury, variable, and time period were based on risk priority numbers (RPNs) obtained from failure mode and effects analysis (FMEA) methodology, and these risk factors were incorporated into the model as objective function parameters. A numerical experiment based on several different situations was conducted, revealing that the model provided optimal timing of preventive measures for child injuries based on variables considered.

  16. PRA and Risk Informed Analysis

    International Nuclear Information System (INIS)

    Bernsen, Sidney A.; Simonen, Fredric A.; Balkey, Kenneth R.

    2006-01-01

    The Boiler and Pressure Vessel Code (BPVC) of the American Society of Mechanical Engineers (ASME) has introduced a risk based approach into Section XI that covers Rules for Inservice Inspection of Nuclear Power Plant Components. The risk based approach requires application of the probabilistic risk assessments (PRA). Because no industry consensus standard existed for PRAs, ASME has developed a standard to evaluate the quality level of an available PRA needed to support a given risk based application. The paper describes the PRA standard, Section XI application of PRAs, and plans for broader applications of PRAs to other ASME nuclear codes and standards. The paper addresses several specific topics of interest to Section XI. Important consideration are special methods (surrogate components) used to overcome the lack of PRA treatments of passive components in PRAs. The approach allows calculations of conditional core damage probabilities both for component failures that cause initiating events and failures in standby systems that decrease the availability of these systems. The paper relates the explicit risk based methods of the new Section XI code cases to the implicit consideration of risk used in the development of Section XI. Other topics include the needed interactions of ISI engineers, plant operating staff, PRA specialists, and members of expert panels that review the risk based programs

  17. Advances in Risk Analysis with Big Data.

    Science.gov (United States)

    Choi, Tsan-Ming; Lambert, James H

    2017-08-01

    With cloud computing, Internet-of-things, wireless sensors, social media, fast storage and retrieval, etc., organizations and enterprises have access to unprecedented amounts and varieties of data. Current risk analysis methodology and applications are experiencing related advances and breakthroughs. For example, highway operations data are readily available, and making use of them reduces risks of traffic crashes and travel delays. Massive data of financial and enterprise systems support decision making under risk by individuals, industries, regulators, etc. In this introductory article, we first discuss the meaning of big data for risk analysis. We then examine recent advances in risk analysis with big data in several topic areas. For each area, we identify and introduce the relevant articles that are featured in the special issue. We conclude with a discussion on future research opportunities. © 2017 Society for Risk Analysis.

  18. Probabilistic methods in fire-risk analysis

    International Nuclear Information System (INIS)

    Brandyberry, M.D.

    1989-01-01

    The first part of this work outlines a method for assessing the frequency of ignition of a consumer product in a building and shows how the method would be used in an example scenario utilizing upholstered furniture as the product and radiant auxiliary heating devices (electric heaters, wood stoves) as the ignition source. Deterministic thermal models of the heat-transport processes are coupled with parameter uncertainty analysis of the models and with a probabilistic analysis of the events involved in a typical scenario. This leads to a distribution for the frequency of ignition for the product. In second part, fire-risk analysis as currently used in nuclear plants is outlines along with a discussion of the relevant uncertainties. The use of the computer code COMPBRN is discussed for use in the fire-growth analysis along with the use of response-surface methodology to quantify uncertainties in the code's use. Generalized response surfaces are developed for temperature versus time for a cable tray, as well as a surface for the hot gas layer temperature and depth for a room of arbitrary geometry within a typical nuclear power plant compartment. These surfaces are then used to simulate the cable tray damage time in a compartment fire experiment

  19. 38 CFR 75.115 - Risk analysis.

    Science.gov (United States)

    2010-07-01

    ... 38 Pensions, Bonuses, and Veterans' Relief 2 2010-07-01 2010-07-01 false Risk analysis. 75.115 Section 75.115 Pensions, Bonuses, and Veterans' Relief DEPARTMENT OF VETERANS AFFAIRS (CONTINUED) INFORMATION SECURITY MATTERS Data Breaches § 75.115 Risk analysis. If a data breach involving sensitive personal information that is processed or...

  20. The development of a 3D risk analysis method.

    Science.gov (United States)

    I, Yet-Pole; Cheng, Te-Lung

    2008-05-01

    Much attention has been paid to the quantitative risk analysis (QRA) research in recent years due to more and more severe disasters that have happened in the process industries. Owing to its calculation complexity, very few software, such as SAFETI, can really make the risk presentation meet the practice requirements. However, the traditional risk presentation method, like the individual risk contour in SAFETI, is mainly based on the consequence analysis results of dispersion modeling, which usually assumes that the vapor cloud disperses over a constant ground roughness on a flat terrain with no obstructions and concentration fluctuations, which is quite different from the real situations of a chemical process plant. All these models usually over-predict the hazardous regions in order to maintain their conservativeness, which also increases the uncertainty of the simulation results. On the other hand, a more rigorous model such as the computational fluid dynamics (CFD) model can resolve the previous limitations; however, it cannot resolve the complexity of risk calculations. In this research, a conceptual three-dimensional (3D) risk calculation method was proposed via the combination of results of a series of CFD simulations with some post-processing procedures to obtain the 3D individual risk iso-surfaces. It is believed that such technique will not only be limited to risk analysis at ground level, but also be extended into aerial, submarine, or space risk analyses in the near future.

  1. A background to risk analysis. Vol. 4

    International Nuclear Information System (INIS)

    Taylor, J.R.

    1979-01-01

    This 4-volumes report gives a background of ideas, principles, and examples which might be of use in developing practical methods for risk analysis. Some of the risk analysis techniques described are somewhat experimental. The report is written in an introductory style, but where some point needs further justification or evaluation, this is given in the form of a chapter appendix. In this way, it is hoped that the report can serve two purposes, - as a basis for starting risk analysis work and as a basis for discussing effectiveness of risk analysis procedures. The report should be seen as a preliminary stage, prior to a program of industrial trials of risk analysis methods. Vol. 4 treats human error in plant operation. (BP)

  2. Estimation of value at risk and conditional value at risk using normal mixture distributions model

    Science.gov (United States)

    Kamaruzzaman, Zetty Ain; Isa, Zaidi

    2013-04-01

    Normal mixture distributions model has been successfully applied in financial time series analysis. In this paper, we estimate the return distribution, value at risk (VaR) and conditional value at risk (CVaR) for monthly and weekly rates of returns for FTSE Bursa Malaysia Kuala Lumpur Composite Index (FBMKLCI) from July 1990 until July 2010 using the two component univariate normal mixture distributions model. First, we present the application of normal mixture distributions model in empirical finance where we fit our real data. Second, we present the application of normal mixture distributions model in risk analysis where we apply the normal mixture distributions model to evaluate the value at risk (VaR) and conditional value at risk (CVaR) with model validation for both risk measures. The empirical results provide evidence that using the two components normal mixture distributions model can fit the data well and can perform better in estimating value at risk (VaR) and conditional value at risk (CVaR) where it can capture the stylized facts of non-normality and leptokurtosis in returns distribution.

  3. Reliability and validity of risk analysis

    International Nuclear Information System (INIS)

    Aven, Terje; Heide, Bjornar

    2009-01-01

    In this paper we investigate to what extent risk analysis meets the scientific quality requirements of reliability and validity. We distinguish between two types of approaches within risk analysis, relative frequency-based approaches and Bayesian approaches. The former category includes both traditional statistical inference methods and the so-called probability of frequency approach. Depending on the risk analysis approach, the aim of the analysis is different, the results are presented in different ways and consequently the meaning of the concepts reliability and validity are not the same.

  4. Concordance for prognostic models with competing risks

    DEFF Research Database (Denmark)

    Wolbers, Marcel; Blanche, Paul; Koller, Michael T

    2014-01-01

    The concordance probability is a widely used measure to assess discrimination of prognostic models with binary and survival endpoints. We formally define the concordance probability for a prognostic model of the absolute risk of an event of interest in the presence of competing risks and relate i...

  5. Why operational risk modelling creates inverse incentives

    NARCIS (Netherlands)

    Doff, R.

    2015-01-01

    Operational risk modelling has become commonplace in large international banks and is gaining popularity in the insurance industry as well. This is partly due to financial regulation (Basel II, Solvency II). This article argues that operational risk modelling is fundamentally flawed, despite efforts

  6. Urban flooding and health risk analysis by use of quantitative microbial risk assessment

    DEFF Research Database (Denmark)

    Andersen, Signe Tanja

    D thesis is to identify the limitations and possibilities for optimising microbial risk assessments of urban flooding through more evidence-based solutions, including quantitative microbial data and hydrodynamic water quality models. The focus falls especially on the problem of data needs and the causes......, but also when wading through a flooded area. The results in this thesis have brought microbial risk assessments one step closer to more uniform and repeatable risk analysis by using actual and relevant measured data and hydrodynamic water quality models to estimate the risk from flooding caused...... are expected to increase in the future. To ensure public health during extreme rainfall, solutions are needed, but limited knowledge on microbial water quality, and related health risks, makes it difficult to implement microbial risk analysis as a part of the basis for decision making. The main aim of this Ph...

  7. Structural reliability analysis applied to pipeline risk analysis

    Energy Technology Data Exchange (ETDEWEB)

    Gardiner, M. [GL Industrial Services, Loughborough (United Kingdom); Mendes, Renato F.; Donato, Guilherme V.P. [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil)

    2009-07-01

    Quantitative Risk Assessment (QRA) of pipelines requires two main components to be provided. These are models of the consequences that follow from some loss of containment incident, and models for the likelihood of such incidents occurring. This paper describes how PETROBRAS have used Structural Reliability Analysis for the second of these, to provide pipeline- and location-specific predictions of failure frequency for a number of pipeline assets. This paper presents an approach to estimating failure rates for liquid and gas pipelines, using Structural Reliability Analysis (SRA) to analyze the credible basic mechanisms of failure such as corrosion and mechanical damage. SRA is a probabilistic limit state method: for a given failure mechanism it quantifies the uncertainty in parameters to mathematical models of the load-resistance state of a structure and then evaluates the probability of load exceeding resistance. SRA can be used to benefit the pipeline risk management process by optimizing in-line inspection schedules, and as part of the design process for new construction in pipeline rights of way that already contain multiple lines. A case study is presented to show how the SRA approach has recently been used on PETROBRAS pipelines and the benefits obtained from it. (author)

  8. Analysis and risk management after Fukushima

    International Nuclear Information System (INIS)

    Nelson, P. F.

    2011-11-01

    This article describes the impact in the nuclear industry after the only accidents with affectation to the public: the Three Mile Island and Chernobyl. and discusses what comes after Fukushima with regard to the Safety Probabilistic Analysis (Spa) and their use in the decisions taking. A reference to the standard ASME/ANS of Spa is made and the possible changes due to the learned lessons after the Fukushima accident. The main changes are described in the art state and the priorities of the Spa studies. These include the change in the mission time of the emergency systems, the necessity to model the alternating systems, the risk consideration of a site with multi-units, the importance of making a Spa level 3 and the Spa of external events. The Spa is the key tool of the discipline of risk management, but given the learned lessons, is more necessary in all the aspects of the operation and surveillance of a nuclear power plant. A strategy is presented to improve the response to a severe accident, that includes consider the risks of the specific nuclear power plant. (Author)

  9. The complex model of risk and progression of AMD estimation

    Directory of Open Access Journals (Sweden)

    V. S. Akopyan

    2012-01-01

    Full Text Available Purpose: to develop a method and a statistical model to estimate individual risk of AMD and the risk for progression to advanced AMD using clinical and genetic risk factors.Methods: A statistical risk assessment model was developed using stepwise binary logistic regression analysis. to estimate the population differences in the prevalence of allelic variants of genes and for the development of models adapted to the population of Moscow region genotyping and assessment of the influence of other risk factors was performed in two groups: patients with differ- ent stages of AMD (n = 74, and control group (n = 116. Genetic risk factors included in the study: polymorphisms in the complement system genes (C3 and CFH, genes at 10q26 locus (ARMS2 and HtRA1, polymorphism in the mitochondrial gene Mt-ND2. Clinical risk factors included in the study: age, gender, high body mass index, smoking history.Results: A comprehensive analysis of genetic and clinical risk factors for AMD in the study group was performed. Compiled statis- tical model assessment of individual risk of AMD, the sensitivity of the model — 66.7%, specificity — 78.5%, AUC = 0.76. Risk factors of late AMD, compiled a statistical model describing the probability of late AMD, the sensitivity of the model — 66.7%, specificity — 78.3%, AUC = 0.73. the developed system allows determining the most likely version of the current late AMD: dry or wet.Conclusion: the developed test system and the mathematical algorhythm for determining the risk of AMD, risk of progression to advanced AMD have fair diagnostic informative and promising for use in clinical practice.

  10. Calculating excess lifetime risk in relative risk models

    International Nuclear Information System (INIS)

    Vaeth, M.; Pierce, D.A.

    1990-01-01

    When assessing the impact of radiation exposure it is common practice to present the final conclusions in terms of excess lifetime cancer risk in a population exposed to a given dose. The present investigation is mainly a methodological study focusing on some of the major issues and uncertainties involved in calculating such excess lifetime risks and related risk projection methods. The age-constant relative risk model used in the recent analyses of the cancer mortality that was observed in the follow-up of the cohort of A-bomb survivors in Hiroshima and Nagasaki is used to describe the effect of the exposure on the cancer mortality. In this type of model the excess relative risk is constant in age-at-risk, but depends on the age-at-exposure. Calculation of excess lifetime risks usually requires rather complicated life-table computations. In this paper we propose a simple approximation to the excess lifetime risk; the validity of the approximation for low levels of exposure is justified empirically as well as theoretically. This approximation provides important guidance in understanding the influence of the various factors involved in risk projections. Among the further topics considered are the influence of a latent period, the additional problems involved in calculations of site-specific excess lifetime cancer risks, the consequences of a leveling off or a plateau in the excess relative risk, and the uncertainties involved in transferring results from one population to another. The main part of this study relates to the situation with a single, instantaneous exposure, but a brief discussion is also given of the problem with a continuous exposure at a low-dose rate

  11. Bias in risk-benefit analysis

    International Nuclear Information System (INIS)

    Mazur, A.

    1985-01-01

    Risk-benefit analysis has become popular in the past decade as a means of improving decision making, especially in the area of technology policy. Here risk-benefit analysis is compared to other (equally defensible) approaches to decision making, showing how it favors some political interests more than others, and suggesting why it has recently come to the fore as a tool of political analysis. A considerable portion of the discussion concerns nuclear power. 6 references

  12. Risk matrix model applied to the outsourcing of logistics' activities

    Directory of Open Access Journals (Sweden)

    Fouad Jawab

    2015-09-01

    Full Text Available Purpose: This paper proposes the application of the risk matrix model in the field of logistics outsourcing. Such an application can serve as the basis for decision making regarding the conduct of a risk management in the logistics outsourcing process and allow its prevention. Design/methodology/approach: This study is based on the risk management of logistics outsourcing in the field of the retail sector in Morocco. The authors identify all possible risks and then classify and prioritize them using the Risk Matrix Model. Finally, we have come to four possible decisions for the identified risks. The analysis was made possible through interviews and discussions with the heads of departments and agents who are directly involved in each outsourced activity. Findings and Originality/value: It is possible to improve the risk matrix model by proposing more personalized prevention measures according to each company that operates in the mass-market retailing. Originality/value: This study is the only one made in the process of logistics outsourcing in the retail sector in Morocco through Label’vie as a case study. First, we had identified as thorough as we could all possible risks, then we applied the Risk Matrix Model to sort them out in an ascending order of importance and criticality. As a result, we could hand out to the decision-makers the mapping for an effective control of risks and a better guiding of the process of risk management.

  13. Collision Risk Analysis for HSC

    DEFF Research Database (Denmark)

    Urban, Jesper; Pedersen, Preben Terndrup; Simonsen, Bo Cerup

    1999-01-01

    High Speed Craft (HSC) have a risk profile, which is distinctly different from conventional ferries. Due to different hull building material, structural layout, compartmentation and operation, both frequency and consequences of collision and grounding accidents must be expected to be different fr...

  14. [Simplified models for analysis of sources of risk and biomechanical overload in craft industries: practical application in confectioners, pasta and pizza makers].

    Science.gov (United States)

    Placci, M; Cerbai, M

    2011-01-01

    The food industry is of great importance in Italy; it is second only to the engineering sector, involving about 440,000 workers. However, 90% of the food businesses have less than 10 employees and are exempt from legal obligation to provide a detailed Risk Assessment Document. The aim of the study was to identify the inconveniences and risks present in the workplaces analyzed with particular reference to biomechanical risk of the upper limbs and the lumbar spine. This preliminary study, carried out by using pre-mapping of the inconveniences and risks (5) and the "mini-checklist OCRA" (4), involved 15 small food businesses: ovens for baking bread, pastry shops, pizzerias and the production of "Piadina" (flat bread). Although undoubtedly with differences, confectioners, pasta makers, pizza makers and "piadinari" were exposed to similar risks. By analyzing the final graphs, action areas can be identified on which further risk analysis can be made. Exposure is mainly related to repetitive movements, manual handling of loads and a common occurrence is the risk of allergy to flour dust. There are real peaks in demand from customers, that inevitably increase work demands and consequently biomechanical overload. In future studies it will be interesting to investigate this aspect by studying the variations in work demand and the final exposure index of the working day.

  15. Generalized indices for radiation risk analysis

    International Nuclear Information System (INIS)

    Bykov, A.A.; Demin, V.F.

    1989-01-01

    A new approach to ensuring nuclear safety has begun forming since the early eighties. The approach based on the probabilistic safety analysis, the principles of acceptable risk, the optimization of safety measures, etc. has forced a complex of adequate quantitative methods of assessment, safety analysis and risk management to be developed. The method of radiation risk assessment and analysis hold a prominent place in the complex. National and international research and regulatory organizations ICRP, IAEA, WHO, UNSCEAR, OECD/NEA have given much attention to the development of the conceptual and methodological basis of those methods. Some resolutions of the National Commission of Radiological Protection (NCRP) and the Problem Commission on Radiation Hygiene of the USSR Ministry of Health should be also noted. Both CBA (cost benefit analysis) and other methods of radiation risk analysis and safety management use a system of natural and socio-economic indices characterizing the radiation risk or damage. There exist a number of problems associated with the introduction, justification and use of these indices. For example, the price, a, of radiation damage, or collective dose unit, is a noteworthy index. The difficulties in its qualitative and quantitative determination are still an obstacle for a wide application of CBA to the radiation risk analysis and management. During recent 10-15 years these problems have been a subject of consideration for many authors. The present paper also considers the issues of the qualitative and quantitative justification of the indices of radiation risk analysis

  16. Understanding HIV Transmission Risk Behavior Among HIV-Infected South Africans Receiving Antiretroviral Therapy: An Information—Motivation—Behavioral Skills Model Analysis

    Science.gov (United States)

    Kiene, Susan M.; Fisher, William A.; Shuper, Paul A.; Cornman, Deborah H.; Christie, Sarah; MacDonald, Susan; Pillay, Sandy; Mahlase, Gethwana; Fisher, Jeffrey D.

    2014-01-01

    The current study applied the Information—Motivation—Behavioral Skills (IMB) model (J. D. Fisher & Fisher, 1992; W. A. Fisher & Fisher, 1993) to identify factors associated with HIV transmission risk behavior among HIV-infected South Africans receiving antiretroviral therapy (ART), a population of considerable significance for curtailing, or maintaining, South Africa’s generalized HIV epidemic. HIV prevention information, HIV prevention motivation, HIV prevention behavioral skills, and HIV transmission risk behavior were assessed in a sample of 1,388 South Africans infected with HIV and receiving ART in 16 clinics in KwaZulu-Natal, South Africa. Results confirmed the assumptions of the IMB model and demonstrated that HIV prevention information and HIV prevention motivation work through HIV prevention behavioral skills to affect HIV transmission risk behavior in this population. Subanalyses confirmed these relationships for HIV transmission risk behavior overall and for HIV transmission risk behavior with partners perceived to be HIV-negative or HIV-status unknown. A consistent pattern of gender differences showed that for men, HIV prevention information and HIV prevention motivation may have direct links with HIV preventive behavior, while for women, the effects of HIV prevention information and HIV prevention motivation work through HIV prevention behavioral skills to affect HIV preventive behavior. These IMB model-based findings suggest directions for HIV prevention interventions with South African men and women living with HIV and on ART as an important component of overall strategies to contain South Africa’s generalized HIV epidemic. PMID:23477576

  17. Understanding HIV transmission risk behavior among HIV-infected South Africans receiving antiretroviral therapy: an information--motivation--behavioral skills model analysis.

    Science.gov (United States)

    Kiene, Susan M; Fisher, William A; Shuper, Paul A; Cornman, Deborah H; Christie, Sarah; Macdonald, Susan; Pillay, Sandy; Mahlase, Gethwana; Fisher, Jeffrey D

    2013-08-01

    The current study applied the Information-Motivation-Behavioral Skills (IMB) model (Fisher & Fisher, 1992; Fisher & Fisher, 1993) to identify factors associated with human immunodeficiency virus (HIV) transmission risk behavior among HIV-infected South Africans receiving antiretroviral therapy (ART), a population of considerable significance for curtailing, or maintaining, South Africa's generalized HIV epidemic. HIV prevention information, HIV prevention motivation, HIV prevention behavioral skills, and HIV transmission risk behavior were assessed in a sample of 1,388 South Africans infected with HIV and receiving ART in 16 clinics in KwaZulu-Natal, South Africa. Findings confirmed the assumptions of the IMB model and demonstrated that HIV prevention information and HIV prevention motivation work through HIV prevention behavioral skills to affect HIV transmission risk behavior in this population. Subanalyses confirmed these relationships for HIV transmission risk behavior overall and for HIV transmission risk behavior with partners perceived to be HIV-negative or HIV-status unknown. A consistent pattern of gender differences showed that for men, HIV prevention information and HIV prevention motivation may have direct links with HIV preventive behavior, whereas for women, the effect of HIV prevention motivation works through HIV prevention behavioral skills to affect HIV preventive behavior. These IMB model-based findings suggest directions for HIV prevention interventions with South African men and women living with HIV and on ART as an important component of overall strategies to contain South Africa's generalized HIV epidemic. PsycINFO Database Record (c) 2013 APA, all rights reserved.

  18. Risk Analysis and Decision Making FY 2013 Milestone Report

    Energy Technology Data Exchange (ETDEWEB)

    Engel, David W.; Dalton, Angela C.; Dale, Crystal; Jones, Edward; Thompson, J.

    2013-06-01

    Risk analysis and decision making is one of the critical objectives of CCSI, which seeks to use information from science-based models with quantified uncertainty to inform decision makers who are making large capital investments. The goal of this task is to develop tools and capabilities to facilitate the development of risk models tailored for carbon capture technologies, quantify the uncertainty of model predictions, and estimate the technical and financial risks associated with the system. This effort aims to reduce costs by identifying smarter demonstrations, which could accelerate development and deployment of the technology by several years.

  19. Modeling Banking, Sovereign, and Macro Risk in a CCA Global VAR

    OpenAIRE

    Dale F. Gray

    2013-01-01

    The purpose of this paper is to develop a model framework for the analysis of interactions between banking sector risk, sovereign risk, corporate sector risk, real economic activity, and credit growth for 15 European countries and the United States. It is an integrated macroeconomic systemic risk model framework that draws on the advantages of forward-looking contingent claims analysis (CCA) risk indicators for the banking systems in each country, forward-looking CCA risk indicators for sover...

  20. The influence of sensation-seeking and parental and peer influences in early adolescence on risk involvement through middle adolescence: A structural equation modeling analysis

    Science.gov (United States)

    Wang, Bo; Deveaux, Lynette; Lunn, Sonja; Dinaj-Koci, Veronica; Li, Xiaoming; Stanton, Bonita

    2014-01-01

    This study examined the relationships between youth and parental sensation-seeking, peer influence, parental monitoring and youth risk involvement in adolescence using structural equation modeling. Beginning in grade-six, longitudinal data were collected from 543 students over three years. Youth sensation-seeking in grade six contributed to risk involvement in early adolescence (grades six and seven) indirectly through increased peer risk influence and decreased parental monitoring but did not have a direct contribution. It contributed directly and indirectly to risk involvement in middle adolescence (grades eight and nine). Parent sensation-seeking at baseline was positively associated with peer risk influence and negatively associated with parental monitoring; it had no direct effect on adolescent risk involvement. Parental monitoring buffers negative peer influence on adolescent risk involvement. Results highlight the need for intervention efforts to provide normative feedback about adolescent risky behaviors and to vary among families in which parents and/or youth have high sensation-seeking propensities. PMID:27030784

  1. Literature Review on Modeling Cyber Networks and Evaluating Cyber Risks.

    Energy Technology Data Exchange (ETDEWEB)

    Kelic, Andjelka; Campbell, Philip L

    2018-04-01

    The National Infrastructure Simulations and Analysis Center (NISAC) conducted a literature review on modeling cyber networks and evaluating cyber risks. The literature review explores where modeling is used in the cyber regime and ways that consequence and risk are evaluated. The relevant literature clusters in three different spaces: network security, cyber-physical, and mission assurance. In all approaches, some form of modeling is utilized at varying levels of detail, while the ability to understand consequence varies, as do interpretations of risk. This document summarizes the different literature viewpoints and explores their applicability to securing enterprise networks.

  2. Driving Strategic Risk Planning With Predictive Modelling For Managerial Accounting

    DEFF Research Database (Denmark)

    Nielsen, Steen; Pontoppidan, Iens Christian

    for managerial accounting and shows how it can be used to determine the impact of different types of risk assessment input parameters on the variability of important outcome measures. The purpose is to: (i) point out the theoretical necessity of a stochastic risk framework; (ii) present a stochastic framework......Currently, risk management in management/managerial accounting is treated as deterministic. Although it is well-known that risk estimates are necessarily uncertain or stochastic, until recently the methodology required to handle stochastic risk-based elements appear to be impractical and too...... mathematical. The ultimate purpose of this paper is to “make the risk concept procedural and analytical” and to argue that accountants should now include stochastic risk management as a standard tool. Drawing on mathematical modelling and statistics, this paper methodically develops risk analysis approach...

  3. A Network Model of Credit Risk Contagion

    Directory of Open Access Journals (Sweden)

    Ting-Qiang Chen

    2012-01-01

    Full Text Available A network model of credit risk contagion is presented, in which the effect of behaviors of credit risk holders and the financial market regulators and the network structure are considered. By introducing the stochastic dominance theory, we discussed, respectively, the effect mechanisms of the degree of individual relationship, individual attitude to credit risk contagion, the individual ability to resist credit risk contagion, the monitoring strength of the financial market regulators, and the network structure on credit risk contagion. Then some derived and proofed propositions were verified through numerical simulations.

  4. Safety analysis, risk assessment, and risk acceptance criteria

    International Nuclear Information System (INIS)

    Jamali, K.

    1997-01-01

    This paper discusses a number of topics that relate safety analysis as documented in the Department of Energy (DOE) safety analysis reports (SARs), probabilistic risk assessments (PRA) as characterized primarily in the context of the techniques that have assumed some level of formality in commercial nuclear power plant applications, and risk acceptance criteria as an outgrowth of PRA applications. DOE SARs of interest are those that are prepared for DOE facilities under DOE Order 5480.23 and the implementing guidance in DOE STD-3009-94. It must be noted that the primary area of application for DOE STD-3009 is existing DOE facilities and that certain modifications of the STD-3009 approach are necessary in SARs for new facilities. Moreover, it is the hazard analysis (HA) and accident analysis (AA) portions of these SARs that are relevant to the present discussions. Although PRAs can be qualitative in nature, PRA as used in this paper refers more generally to all quantitative risk assessments and their underlying methods. HA as used in this paper refers more generally to all qualitative risk assessments and their underlying methods that have been in use in hazardous facilities other than nuclear power plants. This discussion includes both quantitative and qualitative risk assessment methods. PRA has been used, improved, developed, and refined since the Reactor Safety Study (WASH-1400) was published in 1975 by the Nuclear Regulatory Commission (NRC). Much debate has ensued since WASH-1400 on exactly what the role of PRA should be in plant design, reactor licensing, 'ensuring' plant and process safety, and a large number of other decisions that must be made for potentially hazardous activities. Of particular interest in this area is whether the risks quantified using PRA should be compared with numerical risk acceptance criteria (RACs) to determine whether a facility is 'safe.' Use of RACs requires quantitative estimates of consequence frequency and magnitude

  5. Expert judgement models in quantitative risk assessment

    Energy Technology Data Exchange (ETDEWEB)

    Rosqvist, T. [VTT Automation, Helsinki (Finland); Tuominen, R. [VTT Automation, Tampere (Finland)

    1999-12-01

    Expert judgement is a valuable source of information in risk management. Especially, risk-based decision making relies significantly on quantitative risk assessment, which requires numerical data describing the initiator event frequencies and conditional probabilities in the risk model. This data is seldom found in databases and has to be elicited from qualified experts. In this report, we discuss some modelling approaches to expert judgement in risk modelling. A classical and a Bayesian expert model is presented and applied to real case expert judgement data. The cornerstone in the models is the log-normal distribution, which is argued to be a satisfactory choice for modelling degree-of-belief type probability distributions with respect to the unknown parameters in a risk model. Expert judgements are qualified according to bias, dispersion, and dependency, which are treated differently in the classical and Bayesian approaches. The differences are pointed out and related to the application task. Differences in the results obtained from the different approaches, as applied to real case expert judgement data, are discussed. Also, the role of a degree-of-belief type probability in risk decision making is discussed.

  6. Expert judgement models in quantitative risk assessment

    International Nuclear Information System (INIS)

    Rosqvist, T.; Tuominen, R.

    1999-01-01

    Expert judgement is a valuable source of information in risk management. Especially, risk-based decision making relies significantly on quantitative risk assessment, which requires numerical data describing the initiator event frequencies and conditional probabilities in the risk model. This data is seldom found in databases and has to be elicited from qualified experts. In this report, we discuss some modelling approaches to expert judgement in risk modelling. A classical and a Bayesian expert model is presented and applied to real case expert judgement data. The cornerstone in the models is the log-normal distribution, which is argued to be a satisfactory choice for modelling degree-of-belief type probability distributions with respect to the unknown parameters in a risk model. Expert judgements are qualified according to bias, dispersion, and dependency, which are treated differently in the classical and Bayesian approaches. The differences are pointed out and related to the application task. Differences in the results obtained from the different approaches, as applied to real case expert judgement data, are discussed. Also, the role of a degree-of-belief type probability in risk decision making is discussed

  7. Risk Decision Making Model for Reservoir Floodwater resources Utilization

    Science.gov (United States)

    Huang, X.

    2017-12-01

    Floodwater resources utilization(FRU) can alleviate the shortage of water resources, but there are risks. In order to safely and efficiently utilize the floodwater resources, it is necessary to study the risk of reservoir FRU. In this paper, the risk rate of exceeding the design flood water level and the risk rate of exceeding safety discharge are estimated. Based on the principle of the minimum risk and the maximum benefit of FRU, a multi-objective risk decision making model for FRU is constructed. Probability theory and mathematical statistics method is selected to calculate the risk rate; C-D production function method and emergy analysis method is selected to calculate the risk benefit; the risk loss is related to flood inundation area and unit area loss; the multi-objective decision making problem of the model is solved by the constraint method. Taking the Shilianghe reservoir in Jiangsu Province as an example, the optimal equilibrium solution of FRU of the Shilianghe reservoir is found by using the risk decision making model, and the validity and applicability of the model are verified.

  8. An Analysis of the Relationship between Casualty Risk Per Crash and Vehicle Mass and Footprint for Model Year 2003-2010 Light-Duty Vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Wenzel, Tom P. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2018-01-05

    The Department of Energy’s (DOE) Vehicle Technologies Office funds research on development of technologies to improve the fuel economy of both light- and heavy-duty vehicles, including advanced combustion systems, improved batteries and electric drive systems, and new lightweight materials. Of these approaches to increase fuel economy and reduce fuel consumption, reducing vehicle mass through more extensive use of strong lightweight materials is perhaps the easiest and least expensive method; however, there is a concern that reducing vehicle mass may lead to more fatalities. Lawrence Berkeley National Laboratory (LBNL) has conducted several analyses to better understand the relationship between vehicle mass, size and safety, in order to ameliorate concerns that down-weighting vehicles will inherently lead to more fatalities. These analyses include recreating the regression analyses conducted by the National Highway Traffic Safety Administration (NHTSA) that estimate the relationship between mass reduction and U.S. societal fatality risk per vehicle mile of travel (VMT), while holding vehicle size (i.e. footprint, wheelbase times track width) constant; these analyses are referred to as LBNL Phase 1 analysis. In addition, LBNL has conducted additional analysis of the relationship between mass and the two components of risk per VMT, crash frequency (crashes per VMT) and risk once a crash has occurred (risk per crash); these analyses are referred to as LBNL Phase 2 analysis.

  9. [Survival analysis with competing risks: estimating failure probability].

    Science.gov (United States)

    Llorca, Javier; Delgado-Rodríguez, Miguel

    2004-01-01

    To show the impact of competing risks of death on survival analysis. We provide an example of survival time without chronic rejection after heart transplantation, where death before rejection acts as a competing risk. Using a computer simulation, we compare the Kaplan-Meier estimator and the multiple decrement model. The Kaplan-Meier method overestimated the probability of rejection. Next, we illustrate the use of the multiple decrement model to analyze secondary end points (in our example: death after rejection). Finally, we discuss Kaplan-Meier assumptions and why they fail in the presence of competing risks. Survival analysis should be adjusted for competing risks of death to avoid overestimation of the risk of rejection produced with the Kaplan-Meier method.

  10. Risk Based Milk Pricing Model at Dairy Farmers Level

    Directory of Open Access Journals (Sweden)

    W. Septiani

    2017-12-01

    Full Text Available The milk price from a cooperative institution to farmer does not fully cover the production cost. Though, dairy farmers encounter various risks and uncertainties in conducting their business. The highest risk in milk supply lies in the activities at the farm. This study was designed to formulate a model for calculating milk price at farmer’s level based on risk. Risks that occur on farms include the risk of cow breeding, sanitation, health care, cattle feed management, milking and milk sales. This research used the location of the farm in West Java region. There were five main stages in the preparation of this model, (1 identification and analysis of influential factors, (2 development of a conceptual model, (3 structural analysis and the amount of production costs, (4 model calculation of production cost with risk factors, and (5 risk based milk pricing model. This research built a relationship between risks on smallholder dairy farms with the production costs to be incurred by the farmers. It was also obtained the formulation of risk adjustment factor calculation for the variable costs of production in dairy cattle farm. The difference in production costs with risk and the total production cost without risk was about 8% to 10%. It could be concluded that the basic price of milk proposed based on the research was around IDR 4,250-IDR 4,350/L for 3 to 4 cows ownership. Increasing farmer income was expected to be obtained by entering the value of this risk in the calculation of production costs. 

  11. Challenges in the vulnerability and risk analysis of critical infrastructures

    International Nuclear Information System (INIS)

    Zio, Enrico

    2016-01-01

    The objective of this paper is to provide a systematic view on the problem of vulnerability and risk analysis of critical infrastructures. Reflections are made on the inherent complexities of these systems, related challenges are identified and possible ways forward for their analysis and management are indicated. Specifically: the framework of vulnerability and risk analysis is examined in relation to its application for the protection and resilience of critical infrastructures; it is argued that the complexity of these systems is a challenging characteristic, which calls for the integration of different modeling perspectives and new approaches of analysis; examples of are given in relation to the Internet and, particularly, the electric power grid, as representative of critical infrastructures and the associated complexity; the integration of different types of analyses and methods of system modeling is put forward for capturing the inherent structural and dynamic complexities of critical infrastructures and eventually evaluating their vulnerability and risk characteristics, so that decisions on protections and resilience actions can be taken with the required confidence. - Highlights: • The problem of the protection and resilience of CIs is the focus of the work. • The vulnerability and risk analysis framework for this is critically examined. • The complexity of CIs is presented as a challenge for system modeling and analysis. • The integration of different modeling perspectives of analysis is put forward as a solution. • The extension of the analysis framework to new methods for dealing with surprises and black swans is advocated.

  12. Computer code for general analysis of radon risks (GARR)

    International Nuclear Information System (INIS)

    Ginevan, M.

    1984-09-01

    This document presents a computer model for general analysis of radon risks that allow the user to specify a large number of possible models with a small number of simple commands. The model is written in a version of BASIC which conforms closely to the American National Standards Institute (ANSI) definition for minimal BASIC and thus is readily modified for use on a wide variety of computers and, in particular, microcomputers. Model capabilities include generation of single-year life tables from 5-year abridged data, calculation of multiple-decrement life tables for lung cancer for the general population, smokers, and nonsmokers, and a cohort lung cancer risk calculation that allows specification of level and duration of radon exposure, the form of the risk model, and the specific population assumed at risk. 36 references, 8 figures, 7 tables

  13. GIS risk analysis of hazardous materials transport

    International Nuclear Information System (INIS)

    Anders, C.; Olsten, J.

    1991-01-01

    The Geographic Information System (GIS) was used to assess the risks and vulnerability of transporting hazardous materials and wastes (such as gasoline, explosives, poisons, etc) on the Arizona highway system. This paper discusses the methodology that was utilized, and the application of GIS systems to risk analysis problems

  14. Analysis of regional scale risk to whirling disease in populations of Colorado and Rio Grande cutthroat trout using Bayesian belief network model

    Science.gov (United States)

    Kolb Ayre, Kimberley; Caldwell, Colleen A.; Stinson, Jonah; Landis, Wayne G.

    2014-01-01

    Introduction and spread of the parasite Myxobolus cerebralis, the causative agent of whirling disease, has contributed to the collapse of wild trout populations throughout the intermountain west. Of concern is the risk the disease may have on conservation and recovery of native cutthroat trout. We employed a Bayesian belief network to assess probability of whirling disease in Colorado River and Rio Grande cutthroat trout (Oncorhynchus clarkii pleuriticus and Oncorhynchus clarkii virginalis, respectively) within their current ranges in the southwest United States. Available habitat (as defined by gradient and elevation) for intermediate oligochaete worm host, Tubifex tubifex, exerted the greatest influence on the likelihood of infection, yet prevalence of stream barriers also affected the risk outcome. Management areas that had the highest likelihood of infected Colorado River cutthroat trout were in the eastern portion of their range, although the probability of infection was highest for populations in the southern, San Juan subbasin. Rio Grande cutthroat trout had a relatively low likelihood of infection, with populations in the southernmost Pecos management area predicted to be at greatest risk. The Bayesian risk assessment model predicted the likelihood of whirling disease infection from its principal transmission vector, fish movement, and suggested that barriers may be effective in reducing risk of exposure to native trout populations. Data gaps, especially with regard to location of spawning, highlighted the importance in developing monitoring plans that support future risk assessments and adaptive management for subspecies of cutthroat trout.

  15. A comprehensive Network Security Risk Model for process control networks.

    Science.gov (United States)

    Henry, Matthew H; Haimes, Yacov Y

    2009-02-01

    The risk of cyber attacks on process control networks (PCN) is receiving significant attention due to the potentially catastrophic extent to which PCN failures can damage the infrastructures and commodity flows that they support. Risk management addresses the coupled problems of (1) reducing the likelihood that cyber attacks would succeed in disrupting PCN operation and (2) reducing the severity of consequences in the event of PCN failure or manipulation. The Network Security Risk Model (NSRM) developed in this article provides a means of evaluating the efficacy of candidate risk management policies by modeling the baseline risk and assessing expectations of risk after the implementation of candidate measures. Where existing risk models fall short of providing adequate insight into the efficacy of candidate risk management policies due to shortcomings in their structure or formulation, the NSRM provides model structure and an associated modeling methodology that captures the relevant dynamics of cyber attacks on PCN for risk analysis. This article develops the NSRM in detail in the context of an illustrative example.

  16. Adoption of Building Information Modelling in project planning risk management

    Science.gov (United States)

    Mering, M. M.; Aminudin, E.; Chai, C. S.; Zakaria, R.; Tan, C. S.; Lee, Y. Y.; Redzuan, A. A.

    2017-11-01

    An efficient and effective risk management required a systematic and proper methodology besides knowledge and experience. However, if the risk management is not discussed from the starting of the project, this duty is notably complicated and no longer efficient. This paper presents the adoption of Building Information Modelling (BIM) in project planning risk management. The objectives is to identify the traditional risk management practices and its function, besides, determine the best function of BIM in risk management and investigating the efficiency of adopting BIM-based risk management during the project planning phase. In order to obtain data, a quantitative approach is adopted in this research. Based on data analysis, the lack of compliance with project requirements and failure to recognise risk and develop responses to opportunity are the risks occurred when traditional risk management is implemented. When using BIM in project planning, it works as the tracking of cost control and cash flow give impact on the project cycle to be completed on time. 5D cost estimation or cash flow modeling benefit risk management in planning, controlling and managing budget and cost reasonably. There were two factors that mostly benefit a BIM-based technology which were formwork plan with integrated fall plan and design for safety model check. By adopting risk management, potential risks linked with a project and acknowledging to those risks can be identified to reduce them to an acceptable extent. This means recognizing potential risks and avoiding threat by reducing their negative effects. The BIM-based risk management can enhance the planning process of construction projects. It benefits the construction players in various aspects. It is important to know the application of BIM-based risk management as it can be a lesson learnt to others to implement BIM and increase the quality of the project.

  17. Competing Risks Copula Models for Unemployment Duration

    DEFF Research Database (Denmark)

    Lo, Simon M. S.; Stephan, Gesine; Wilke, Ralf

    2017-01-01

    The copula graphic estimator (CGE) for competing risks models has received little attention in empirical research, despite having been developed into a comprehensive research method. In this paper, we bridge the gap between theoretical developments and applied research by considering a general...... class of competing risks copula models, which nests popular models such as the Cox proportional hazards model, the semiparametric multivariate mixed proportional hazards model (MMPHM), and the CGE as special cases. Analyzing the effects of a German Hartz reform on unemployment duration, we illustrate...

  18. A quality risk management model approach for cell therapy manufacturing.

    Science.gov (United States)

    Lopez, Fabio; Di Bartolo, Chiara; Piazza, Tommaso; Passannanti, Antonino; Gerlach, Jörg C; Gridelli, Bruno; Triolo, Fabio

    2010-12-01

    International regulatory authorities view risk management as an essential production need for the development of innovative, somatic cell-based therapies in regenerative medicine. The available risk management guidelines, however, provide little guidance on specific risk analysis approaches and procedures applicable in clinical cell therapy manufacturing. This raises a number of problems. Cell manufacturing is a poorly automated process, prone to operator-introduced variations, and affected by heterogeneity of the processed organs/tissues and lot-dependent variability of reagent (e.g., collagenase) efficiency. In this study, the principal challenges faced in a cell-based product manufacturing context (i.e., high dependence on human intervention and absence of reference standards for acceptable risk levels) are identified and addressed, and a risk management model approach applicable to manufacturing of cells for clinical use is described for the first time. The use of the heuristic and pseudo-quantitative failure mode and effect analysis/failure mode and critical effect analysis risk analysis technique associated with direct estimation of severity, occurrence, and detection is, in this specific context, as effective as, but more efficient than, the analytic hierarchy process. Moreover, a severity/occurrence matrix and Pareto analysis can be successfully adopted to identify priority failure modes on which to act to mitigate risks. The application of this approach to clinical cell therapy manufacturing in regenerative medicine is also discussed. © 2010 Society for Risk Analysis.

  19. Dealing with phenomenological uncertainty in risk analysis

    International Nuclear Information System (INIS)

    Theofanous, T.G.

    1994-01-01

    The Risk-Oriented Accident Analysis Methodology (ROAAM) is summarized and developed further towards a formal definition. The key ideas behind the methodology and these more formal aspects are also presented and discussed

  20. Risk and safety analysis of nuclear systems

    National Research Council Canada - National Science Library

    Lee, John C; McCormick, Norman J

    2011-01-01

    .... The first half of the book covers the principles of risk analysis, the techniques used to develop and update a reliability data base, the reliability of multi-component systems, Markov methods used...

  1. Revealing the underlying drivers of disaster risk: a global analysis

    Science.gov (United States)

    Peduzzi, Pascal

    2017-04-01

    Disasters events are perfect examples of compound events. Disaster risk lies at the intersection of several independent components such as hazard, exposure and vulnerability. Understanding the weight of each component requires extensive standardisation. Here, I show how footprints of past disastrous events were generated using GIS modelling techniques and used for extracting population and economic exposures based on distribution models. Using past event losses, it was possible to identify and quantify a wide range of socio-politico-economic drivers associated with human vulnerability. The analysis was applied to about nine thousand individual past disastrous events covering earthquakes, floods and tropical cyclones. Using a multiple regression analysis on these individual events it was possible to quantify each risk component and assess how vulnerability is influenced by various hazard intensities. The results show that hazard intensity, exposure, poverty, governance as well as other underlying factors (e.g. remoteness) can explain the magnitude of past disasters. Analysis was also performed to highlight the role of future trends in population and climate change and how this may impacts exposure to tropical cyclones in the future. GIS models combined with statistical multiple regression analysis provided a powerful methodology to identify, quantify and model disaster risk taking into account its various components. The same methodology can be applied to various types of risk at local to global scale. This method was applied and developed for the Global Risk Analysis of the Global Assessment Report on Disaster Risk Reduction (GAR). It was first applied on mortality risk in GAR 2009 and GAR 2011. New models ranging from global assets exposure and global flood hazard models were also recently developed to improve the resolution of the risk analysis and applied through CAPRA software to provide probabilistic economic risk assessments such as Average Annual Losses (AAL

  2. Analysis of Alternatives for Risk Assessment Methodologies and Tools

    Energy Technology Data Exchange (ETDEWEB)

    Nachtigal, Noel M. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). System Analytics; Fruetel, Julia A. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Systems Research and Analysis; Gleason, Nathaniel J. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Systems Research and Analysis; Helms, Jovana [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Systems Research and Analysis; Imbro, Dennis Raymond [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Systems Research and Analysis; Sumner, Matthew C. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Systems Research and Analysis

    2013-10-01

    The purpose of this document is to provide a basic overview and understanding of risk assessment methodologies and tools from the literature and to assess the suitability of these methodologies and tools for cyber risk assessment. Sandia National Laboratories (SNL) performed this review in support of risk modeling activities performed for the Stakeholder Engagement and Cyber Infrastructure Resilience (SECIR) division of the Department of Homeland Security (DHS) Office of Cybersecurity and Communications (CS&C). The set of methodologies and tools covered in this document is not intended to be exhaustive; instead, it focuses on those that are commonly used in the risk assessment community. The classification of methodologies and tools was performed by a group of analysts with experience in risk analysis and cybersecurity, and the resulting analysis of alternatives has been tailored to address the needs of a cyber risk assessment.

  3. Risk communication: a mental models approach

    National Research Council Canada - National Science Library

    Morgan, M. Granger (Millett Granger)

    2002-01-01

    ... information about risks. The procedure uses approaches from risk and decision analysis to identify the most relevant information; it also uses approaches from psychology and communication theory to ensure that its message is understood. This book is written in nontechnical terms, designed to make the approach feasible for anyone willing to try it. It is illustrat...

  4. Criterion of Semi-Markov Dependent Risk Model

    Institute of Scientific and Technical Information of China (English)

    Xiao Yun MO; Xiang Qun YANG

    2014-01-01

    A rigorous definition of semi-Markov dependent risk model is given. This model is a generalization of the Markov dependent risk model. A criterion and necessary conditions of semi-Markov dependent risk model are obtained. The results clarify relations between elements among semi-Markov dependent risk model more clear and are applicable for Markov dependent risk model.

  5. ANALYSIS METHODS OF BANKRUPTCY RISK IN ROMANIAN ENERGY MINING INDUSTRY

    Directory of Open Access Journals (Sweden)

    CORICI MARIAN CATALIN

    2016-12-01

    Full Text Available The study is an analysis of bankruptcy risk and assessing the economic performance of the entity in charge of energy mining industry from southwest region. The scientific activity assesses the risk of bankruptcy using score’s method and some indicators witch reflecting the results obtained and elements from organization balance sheet involved in mining and energy which contributes to the stability of the national energy system. Analysis undertaken is focused on the application of the business organization models that allow a comprehensive assessment of the risk of bankruptcy and be an instrument of its forecast. In this study will be highlighted developments bankruptcy risk within the organization through the Altman model and Conan-Holder model in order to show a versatile image on the organization's ability to ensure business continuity

  6. Dynamic occupational risk model for offshore operations in harsh environments

    International Nuclear Information System (INIS)

    Song, Guozheng; Khan, Faisal; Wang, Hangzhou; Leighton, Shelly; Yuan, Zhi; Liu, Hanwen

    2016-01-01

    The expansion of offshore oil exploitation into remote areas (e.g., Arctic) with harsh environments has significantly increased occupational risks. Among occupational accidents, slips, trips and falls from height (STFs) account for a significant portion. Thus, a dynamic risk assessment of the three main occupational accidents is meaningful to decrease offshore occupational risks. Bow-tie Models (BTs) were established in this study for the risk analysis of STFs considering extreme environmental factors. To relax the limitations of BTs, Bayesian networks (BNs) were developed based on BTs to dynamically assess risks of STFs. The occurrence and consequence probabilities of STFs were respectively calculated using BTs and BNs, and the obtained probabilities verified BNs' rationality and advantage. Furthermore, the probability adaptation for STFs was accomplished in a specific scenario with BNs. Finally, posterior probabilities of basic events were achieved through diagnostic analysis, and critical basic events were analyzed based on their posterior likelihood to cause occupational accidents. The highlight is systematically analyzing STF accidents for offshore operations and dynamically assessing their risks considering the harsh environmental factors. This study can guide the allocation of prevention resources and benefit the safety management of offshore operations. - Highlights: • A novel dynamic risk model for occupational accidents. • First time consideration of harsh environment in occupational accident modeling. • A Bayesian network based model for risk management strategies.

  7. Risk management model of winter navigation operations

    International Nuclear Information System (INIS)

    Valdez Banda, Osiris A.; Goerlandt, Floris; Kuzmin, Vladimir; Kujala, Pentti; Montewka, Jakub

    2016-01-01

    The wintertime maritime traffic operations in the Gulf of Finland are managed through the Finnish–Swedish Winter Navigation System. This establishes the requirements and limitations for the vessels navigating when ice covers this area. During winter navigation in the Gulf of Finland, the largest risk stems from accidental ship collisions which may also trigger oil spills. In this article, a model for managing the risk of winter navigation operations is presented. The model analyses the probability of oil spills derived from collisions involving oil tanker vessels and other vessel types. The model structure is based on the steps provided in the Formal Safety Assessment (FSA) by the International Maritime Organization (IMO) and adapted into a Bayesian Network model. The results indicate that ship independent navigation and convoys are the operations with higher probability of oil spills. Minor spills are most probable, while major oil spills found very unlikely but possible. - Highlights: •A model to assess and manage the risk of winter navigation operations is proposed. •The risks of oil spills in winter navigation in the Gulf of Finland are analysed. •The model assesses and prioritizes actions to control the risk of the operations. •The model suggests navigational training as the most efficient risk control option.

  8. Hierarchic Analysis Method to Evaluate Rock Burst Risk

    Directory of Open Access Journals (Sweden)

    Ming Ji

    2015-01-01

    Full Text Available In order to reasonably evaluate the risk of rock bursts in mines, the factors impacting rock bursts and the existing grading criterion on the risk of rock bursts were studied. By building a model of hierarchic analysis method, the natural factors, technology factors, and management factors that influence rock bursts were analyzed and researched, which determined the degree of each factor’s influence (i.e., weight and comprehensive index. Then the grade of rock burst risk was assessed. The results showed that the assessment level generated by the model accurately reflected the actual risk degree of rock bursts in mines. The model improved the maneuverability and practicability of existing evaluation criteria and also enhanced the accuracy and science of rock burst risk assessment.

  9. Economic analysis and management of climatic risks

    Energy Technology Data Exchange (ETDEWEB)

    Hourcade, J.C. (Centre International de Recherche sur l' Environnement et le Developpement, 92 - Montrouge (France))

    1994-01-01

    This paper aims at framing the collective decision problem in the face of climate change. It shows why it would be irrelevant to handle it in the form of a classical decision under uncertainty framework where a cost-benefit analysis is carried out including probability distribution on damages and risk aversion coefficients. A sequential approach to policy making is then proposed as an alternative in order to account for the inertia of socio-economic dynamics and the value of information. A simple model illustrates the gap between these two approaches; it shows the importance of combining the investments on climatic research, innovation policies and so-called 'no regret' short term decisions. It shows the fact that, even if they can be considered as quantitatively moderate, these potentials have a critical impact on long term viability of development; they embed a very high information value, lengthening the learning time vis-a-vis potentially major but controversial risks. (author). 21 refs., 3 figs.

  10. Probabilistic risk analysis in chemical engineering

    International Nuclear Information System (INIS)

    Schmalz, F.

    1991-01-01

    In risk analysis in the chemical industry, recognising potential risks is considered more important than assessing their quantitative extent. Even in assessing risks, emphasis is not on the probability involved but on the possible extent. Qualitative assessment has proved valuable here. Probabilistic methods are used in individual cases where the wide implications make it essential to be able to assess the reliability of safety precautions. In this case, assessment therefore centres on the reliability of technical systems and not on the extent of a chemical risk. 7 figs

  11. Applying Multi-Criteria Analysis Methods for Fire Risk Assessment

    Directory of Open Access Journals (Sweden)

    Pushkina Julia

    2015-11-01

    Full Text Available The aim of this paper is to prove the application of multi-criteria analysis methods for optimisation of fire risk identification and assessment process. The object of this research is fire risk and risk assessment. The subject of the research is studying the application of analytic hierarchy process for modelling and influence assessment of various fire risk factors. Results of research conducted by the authors can be used by insurance companies to perform the detailed assessment of fire risks on the object and to calculate a risk extra charge to an insurance premium; by the state supervisory institutions to determine the compliance of a condition of object with requirements of regulations; by real state owners and investors to carry out actions for decrease in degree of fire risks and minimisation of possible losses.

  12. DYNAMIC HYBRIDS UNDER SOLVENCY II: RISK ANALYSIS AND MODIFICATION POSSIBILITIES

    Directory of Open Access Journals (Sweden)

    Christian Maier

    2017-06-01

    Full Text Available In this study, we investigate the new and standardized European system of supervisory called Solvency II. In essence, asymmetric distribution of information between policyholder and insurer triggered this new regulation which aims at better protecting policyholders. Its three-pillar model is about to challenge both, insurers as well as policyholders. The first pillar includes quantitative aspects, the second pillar contains qualitative aspects and the third pillar comprises market transparency and reporting obligations. Underwriting risks, the default risk of a bank and market risks can be identified for the dynamic hybrid. Solvency II covers all these risks in the first pillar and insurers shall deposit sufficient risk-bearing capital. In our analysis, we first identify the dynamic hybrid specific risks under the Solvency II regime und then develop product modifications to reduce this risk.

  13. Pre-sealing risk analysis

    International Nuclear Information System (INIS)

    Ensminger, D.A.; Hough, M.E.; Oston, S.G.

    1980-01-01

    This report describes studies of accidents involving high-level radioactive waste before sealing the waste into a repository. The report summarizes work done in this area during Fiscal Year 1978 and supplements previous work. Models of accident probability, severity, and consequences are refined and extended

  14. Development of a cyber security risk model using Bayesian networks

    International Nuclear Information System (INIS)

    Shin, Jinsoo; Son, Hanseong; Khalil ur, Rahman; Heo, Gyunyoung

    2015-01-01

    Cyber security is an emerging safety issue in the nuclear industry, especially in the instrumentation and control (I and C) field. To address the cyber security issue systematically, a model that can be used for cyber security evaluation is required. In this work, a cyber security risk model based on a Bayesian network is suggested for evaluating cyber security for nuclear facilities in an integrated manner. The suggested model enables the evaluation of both the procedural and technical aspects of cyber security, which are related to compliance with regulatory guides and system architectures, respectively. The activity-quality analysis model was developed to evaluate how well people and/or organizations comply with the regulatory guidance associated with cyber security. The architecture analysis model was created to evaluate vulnerabilities and mitigation measures with respect to their effect on cyber security. The two models are integrated into a single model, which is called the cyber security risk model, so that cyber security can be evaluated from procedural and technical viewpoints at the same time. The model was applied to evaluate the cyber security risk of the reactor protection system (RPS) of a research reactor and to demonstrate its usefulness and feasibility. - Highlights: • We developed the cyber security risk model can be find the weak point of cyber security integrated two cyber analysis models by using Bayesian Network. • One is the activity-quality model signifies how people and/or organization comply with the cyber security regulatory guide. • Other is the architecture model represents the probability of cyber-attack on RPS architecture. • The cyber security risk model can provide evidence that is able to determine the key element for cyber security for RPS of a research reactor

  15. The role of multiple regression and exploratory data analysis in the development of leukemia incidence risk models for comparison of radionuclide air stack emissions from nuclear and coal power industries

    International Nuclear Information System (INIS)

    Prybutok, V.R.

    1995-01-01

    Risk associated with power generation must be identified to make intelligent choices between alternate power technologies. Radionuclide air stack emissions for a single coal plant and a single nuclear plant are used to compute the single plant leukemia incidence risk and total industry leukemia incidence risk. Leukemia incidence is the response variable as a function of radionuclide bone dose for the six proposed dose response curves considered. During normal operation a coal plant has higher radionuclide emissions than a nuclear plant and the coal industry has a higher leukaemia incidence risk than the nuclear industry, unless a nuclear accident occurs. Variation of nuclear accident size allows quantification of the impact of accidents on the total industry leukemia incidence risk comparison. The leukemia incidence risk is quantified as the number of accidents of a given size for the nuclear industry leukemia incidence risk to equal the coal industry leukemia incidence risk. The general linear model is used to develop equations that relate the accident frequency required for equal industry risks to the magnitude of the nuclear emission. Exploratory data analysis revealed that the relationship between the natural log of accident number versus the natural log of accident size is linear. (Author)

  16. Reliability and risk analysis methods research plan

    International Nuclear Information System (INIS)

    1984-10-01

    This document presents a plan for reliability and risk analysis methods research to be performed mainly by the Reactor Risk Branch (RRB), Division of Risk Analysis and Operations (DRAO), Office of Nuclear Regulatory Research. It includes those activities of other DRAO branches which are very closely related to those of the RRB. Related or interfacing programs of other divisions, offices and organizations are merely indicated. The primary use of this document is envisioned as an NRC working document, covering about a 3-year period, to foster better coordination in reliability and risk analysis methods development between the offices of Nuclear Regulatory Research and Nuclear Reactor Regulation. It will also serve as an information source for contractors and others to more clearly understand the objectives, needs, programmatic activities and interfaces together with the overall logical structure of the program

  17. [The analysis of climatic and biological parameters for the pest spread risk modelling of the wood nematode species Bursaphelenchus spp. and Devibursaphelenchus teratospicularis (Rhabditida: Aphelenchoidea)].

    Science.gov (United States)

    Ryss, A Y; Mokrousov, M V

    2014-01-01

    Based on the forest woody species wilt areassurvey in Nizhniy Novgorod region in August 2014, the possible factors of the pest spread risk modelling were analysed on six species of the genus Bursaphelenchus and Devibursaphelenchus teratospicularis using six parameters: plant host species, beetle vector species, average temperatures in July and January, annual precipitation. It was concluded that these parameters in the evaluated wilt spots correspond to climatic and biological data of the already published woody plants wilt records in Europe and Asia caused by the same nematode pest species. It was speculated that the annual precipitation of 600 mm and average July temperature of 25 degrees C or higher, are the critical combination that may be used to develop the predicative risk modelling in the forests' and parks' wilt monitoring.

  18. [A model list of high risk drugs].

    Science.gov (United States)

    Cotrina Luque, J; Guerrero Aznar, M D; Alvarez del Vayo Benito, C; Jimenez Mesa, E; Guzman Laura, K P; Fernández Fernández, L

    2013-12-01

    «High-risk drugs» are those that have a very high «risk» of causing death or serious injury if an error occurs during its use. The Institute for Safe Medication Practices (ISMP) has prepared a high-risk drugs list applicable to the general population (with no differences between the pediatric and adult population). Thus, there is a lack of information for the pediatric population. The main objective of this work is to develop a high-risk drug list adapted to the neonatal or pediatric population as a reference model for the pediatric hospital health workforce. We made a literature search in May 2012 to identify any published lists or references in relation to pediatric and/or neonatal high-risk drugs. A total of 15 studies were found, from which 9 were selected. A model list was developed mainly based on the ISMP one, adding strongly perceived pediatric risk drugs and removing those where the pediatric use was anecdotal. There is no published list that suits pediatric risk management. The list of pediatric and neonatal high-risk drugs presented here could be a «reference list of high-risk drugs » for pediatric hospitals. Using this list and training will help to prevent medication errors in each drug supply chain (prescribing, transcribing, dispensing and administration). Copyright © 2013 Asociación Española de Pediatría. Published by Elsevier Espana. All rights reserved.

  19. Uncertainty analysis in the applications of nuclear probabilistic risk assessment

    International Nuclear Information System (INIS)

    Le Duy, T.D.

    2011-01-01

    The aim of this thesis is to propose an approach to model parameter and model uncertainties affecting the results of risk indicators used in the applications of nuclear Probabilistic Risk assessment (PRA). After studying the limitations of the traditional probabilistic approach to represent uncertainty in PRA model, a new approach based on the Dempster-Shafer theory has been proposed. The uncertainty analysis process of the proposed approach consists in five main steps. The first step aims to model input parameter uncertainties by belief and plausibility functions according to the data PRA model. The second step involves the propagation of parameter uncertainties through the risk model to lay out the uncertainties associated with output risk indicators. The model uncertainty is then taken into account in the third step by considering possible alternative risk models. The fourth step is intended firstly to provide decision makers with information needed for decision making under uncertainty (parametric and model) and secondly to identify the input parameters that have significant uncertainty contributions on the result. The final step allows the process to be continued in loop by studying the updating of beliefs functions given new data. The proposed methodology was implemented on a real but simplified application of PRA model. (author)

  20. Environmental risk analysis of hazardous material rail transportation

    International Nuclear Information System (INIS)

    Saat, Mohd Rapik; Werth, Charles J.; Schaeffer, David; Yoon, Hongkyu; Barkan, Christopher P.L.

    2014-01-01

    Highlights: • Comprehensive, nationwide risk assessment of hazardous material rail transportation. • Application of a novel environmental (i.e. soil and groundwater) consequence model. • Cleanup cost and total shipment distance are the most significant risk factors. • Annual risk varies from $20,000 to $560,000 for different products. • Provides information on the risk cost associated with specific product shipments. -- Abstract: An important aspect of railroad environmental risk management involves tank car transportation of hazardous materials. This paper describes a quantitative, environmental risk analysis of rail transportation of a group of light, non-aqueous-phase liquid (LNAPL) chemicals commonly transported by rail in North America. The Hazardous Materials Transportation Environmental Consequence Model (HMTECM) was used in conjunction with a geographic information system (GIS) analysis of environmental characteristics to develop probabilistic estimates of exposure to different spill scenarios along the North American rail network. The risk analysis incorporated the estimated clean-up cost developed using the HMTECM, route-specific probability distributions of soil type and depth to groundwater, annual traffic volume, railcar accident rate, and tank car safety features, to estimate the nationwide annual risk of transporting each product. The annual risk per car-mile (car-km) and per ton-mile (ton-km) was also calculated to enable comparison between chemicals and to provide information on the risk cost associated with shipments of these products. The analysis and the methodology provide a quantitative approach that will enable more effective management of the environmental risk of transporting hazardous materials

  1. Environmental risk analysis of hazardous material rail transportation

    Energy Technology Data Exchange (ETDEWEB)

    Saat, Mohd Rapik, E-mail: mohdsaat@illinois.edu [Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 1243 Newmark Civil Engineering Laboratory, 205 North Mathews Avenue, Urbana, IL 61801 (United States); Werth, Charles J.; Schaeffer, David [Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 1243 Newmark Civil Engineering Laboratory, 205 North Mathews Avenue, Urbana, IL 61801 (United States); Yoon, Hongkyu [Sandia National Laboratories, Albuquerque, NM 87123 (United States); Barkan, Christopher P.L. [Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 1243 Newmark Civil Engineering Laboratory, 205 North Mathews Avenue, Urbana, IL 61801 (United States)

    2014-01-15

    Highlights: • Comprehensive, nationwide risk assessment of hazardous material rail transportation. • Application of a novel environmental (i.e. soil and groundwater) consequence model. • Cleanup cost and total shipment distance are the most significant risk factors. • Annual risk varies from $20,000 to $560,000 for different products. • Provides information on the risk cost associated with specific product shipments. -- Abstract: An important aspect of railroad environmental risk management involves tank car transportation of hazardous materials. This paper describes a quantitative, environmental risk analysis of rail transportation of a group of light, non-aqueous-phase liquid (LNAPL) chemicals commonly transported by rail in North America. The Hazardous Materials Transportation Environmental Consequence Model (HMTECM) was used in conjunction with a geographic information system (GIS) analysis of environmental characteristics to develop probabilistic estimates of exposure to different spill scenarios along the North American rail network. The risk analysis incorporated the estimated clean-up cost developed using the HMTECM, route-specific probability distributions of soil type and depth to groundwater, annual traffic volume, railcar accident rate, and tank car safety features, to estimate the nationwide annual risk of transporting each product. The annual risk per car-mile (car-km) and per ton-mile (ton-km) was also calculated to enable comparison between chemicals and to provide information on the risk cost associated with shipments of these products. The analysis and the methodology provide a quantitative approach that will enable more effective management of the environmental risk of transporting hazardous materials.

  2. WIPP fire hazards and risk analysis

    International Nuclear Information System (INIS)

    1991-05-01

    The purpose of this analysis was to conduct a fire hazards risk analysis of the Transuranic (TRU) contact-handled waste receipt, emplacement, and disposal activities at the Waste Isolation Pilot Plant (WIPP). The technical bases and safety envelope for these operations are defined in the approved WIPP Final Safety Analysis Report (FSAR). Although the safety documentation for the initial phase of the Test Program, the dry bin scale tests, has not yet been approved by the Department of Energy (DOE), reviews of the draft to date, including those by the Advisory Committee on Nuclear Facility Safety (ACNFS), have concluded that the dry bin scale tests present no significant risks in excess of those estimated in the approved WIPP FSAR. It is the opinion of the authors and reviewers of this analysis, based on sound engineering judgment and knowledge of the WIPP operations, that a Fire Hazards and Risk Analysis specific to the dry bin scale test program is not warranted prior to first waste receipt. This conclusion is further supported by the risk analysis presented in this document which demonstrates the level of risk to WIPP operations posed by fire to be extremely low. 15 refs., 41 figs., 48 tabs

  3. Maritime transportation risk analysis: Review and analysis in light of some foundational issues

    International Nuclear Information System (INIS)

    Goerlandt, Floris; Montewka, Jakub

    2015-01-01

    Many methods and applications for maritime transportation risk analysis have been presented in the literature. In parallel, there is a recent focus on foundational issues in risk analysis, with calls for intensified research on fundamental concepts and principles underlying the scientific field. This paper presents a review and analysis of risk definitions, perspectives and scientific approaches to risk analysis found in the maritime transportation application area, focusing on applications addressing accidental risk of shipping in a sea area. For this purpose, a classification of risk definitions, an overview of elements in risk perspectives and a classification of approaches to risk analysis science are applied. Results reveal that in the application area, risk is strongly tied to probability, both in definitions and perspectives, while alternative views exist. A diffuse situation is also found concerning the scientific approach to risk analysis, with realist, proceduralist and constructivist foundations co-existing. Realist approaches dominate the application area. Very few applications systematically account for uncertainty, neither concerning the evidence base nor in relation to the limitations of the risk model in relation to the space of possible outcomes. Some suggestions are made to improve the current situation, aiming to strengthen the scientific basis for risk analysis. - Highlights: • Risk analyses in maritime transportation analysed in light of foundational issues. • Focus on definitions, perspectives and scientific approaches to risk analysis. • Probability-based definitions and realist approaches dominate the field. • Findings support calls for increased focus on foundational issues in risk research. • Some suggestions are made to improve the current situation

  4. A Macroeconomic Model of Credit Risk in Uruguay

    Directory of Open Access Journals (Sweden)

    Gabriel Illanes

    Full Text Available In this paper we evaluate credit risk of the economy as a whole, aiming at the study of the financial stability. This analysis uses as proxy the credit granted by the banking system. We use a non-linear parametric model based on Merton's structural framework for the analysis of the risk associated to a loan portfolio. In this model, default occurs when the return of an economic agent falls under certain threshold which depends on different macroeconomic variables. We use this model to assess the credit risk module in stress tests for the local banking system. We also estimate the "elasticities" of credit categories correspondig to corporate credit and consumer credit, both in national currency and american dollars. We obtain the parameters for the model using maximum likelihood, where the likelihood function contains a random latent factor which is assumed to follow a normal distribution.

  5. A mathematical prediction model incorporating molecular subtype for risk of non-sentinel lymph node metastasis in sentinel lymph node-positive breast cancer patients: a retrospective analysis and nomogram development.

    Science.gov (United States)

    Wang, Na-Na; Yang, Zheng-Jun; Wang, Xue; Chen, Li-Xuan; Zhao, Hong-Meng; Cao, Wen-Feng; Zhang, Bin

    2018-04-25

    Molecular subtype of breast cancer is associated with sentinel lymph node status. We sought to establish a mathematical prediction model that included breast cancer molecular subtype for risk of positive non-sentinel lymph nodes in breast cancer patients with sentinel lymph node metastasis and further validate the model in a separate validation cohort. We reviewed the clinicopathologic data of breast cancer patients with sentinel lymph node metastasis who underwent axillary lymph node dissection between June 16, 2014 and November 16, 2017 at our hospital. Sentinel lymph node biopsy was performed and patients with pathologically proven sentinel lymph node metastasis underwent axillary lymph node dissection. Independent risks for non-sentinel lymph node metastasis were assessed in a training cohort by multivariate analysis and incorporated into a mathematical prediction model. The model was further validated in a separate validation cohort, and a nomogram was developed and evaluated for diagnostic performance in predicting the risk of non-sentinel lymph node metastasis. Moreover, we assessed the performance of five different models in predicting non-sentinel lymph node metastasis in training cohort. Totally, 495 cases were eligible for the study, including 291 patients in the training cohort and 204 in the validation cohort. Non-sentinel lymph node metastasis was observed in 33.3% (97/291) patients in the training cohort. The AUC of MSKCC, Tenon, MDA, Ljubljana, and Louisville models in training cohort were 0.7613, 0.7142, 0.7076, 0.7483, and 0.671, respectively. Multivariate regression analysis indicated that tumor size (OR = 1.439; 95% CI 1.025-2.021; P = 0.036), sentinel lymph node macro-metastasis versus micro-metastasis (OR = 5.063; 95% CI 1.111-23.074; P = 0.036), the number of positive sentinel lymph nodes (OR = 2.583, 95% CI 1.714-3.892; P model based on the results of multivariate analysis was established to predict the risk of non

  6. Flood Risk Assessment Based On Security Deficit Analysis

    Science.gov (United States)

    Beck, J.; Metzger, R.; Hingray, B.; Musy, A.

    Risk is a human perception: a given risk may be considered as acceptable or unac- ceptable depending on the group that has to face that risk. Flood risk analysis of- ten estimates economic losses from damages, but neglects the question of accept- able/unacceptable risk. With input from land use managers, politicians and other stakeholders, risk assessment based on security deficit analysis determines objects with unacceptable risk and their degree of security deficit. Such a risk assessment methodology, initially developed by the Swiss federal authorities, is illustrated by its application on a reach of the Alzette River (Luxembourg) in the framework of the IRMA-SPONGE FRHYMAP project. Flood risk assessment always involves a flood hazard analysis, an exposed object vulnerability analysis, and an analysis combing the results of these two previous analyses. The flood hazard analysis was done with the quasi-2D hydraulic model FldPln to produce flood intensity maps. Flood intensity was determined by the water height and velocity. Object data for the vulnerability analysis, provided by the Luxembourg government, were classified according to their potential damage. Potential damage is expressed in terms of direct, human life and secondary losses. A thematic map was produced to show the object classification. Protection goals were then attributed to the object classes. Protection goals are assigned in terms of an acceptable flood intensity for a certain flood frequency. This is where input from land use managers and politicians comes into play. The perception of risk in the re- gion or country influences the protection goal assignment. Protection goals as used in Switzerland were used in this project. Thematic maps showing the protection goals of each object in the case study area for a given flood frequency were produced. Com- parison between an object's protection goal and the intensity of the flood that touched the object determine the acceptability of the risk and the

  7. Impact of Age on the Risk of Advanced Colorectal Neoplasia in a Young Population: An Analysis Using the Predicted Probability Model.

    Science.gov (United States)

    Jung, Yoon Suk; Park, Chan Hyuk; Kim, Nam Hee; Lee, Mi Yeon; Park, Dong Il

    2017-09-01

    The incidence of colorectal cancer is decreasing in adults aged ≥50 years and increasing in those aged probability models for ACRN in a population aged 30-49 years. Of 96,235 participants, 57,635 and 38,600 were included in the derivation and validation cohorts, respectively. The predicted probability model considered age, sex, body mass index, family history of colorectal cancer, and smoking habits, as follows: Y ACRN  = -8.755 + 0.080·X age  - 0.055·X male  + 0.041·X BMI  + 0.200·X family_history_of_CRC  + 0.218·X former_smoker  + 0.644·X current_smoker . The optimal cutoff value for the predicted probability of ACRN by Youden index was 1.14%. The area under the receiver-operating characteristic curve (AUROC) values of our model for ACRN were higher than those of the previously established Asia-Pacific Colorectal Screening (APCS), Korean Colorectal Screening (KCS), and Kaminski's scoring models [AUROC (95% confidence interval): model in the current study, 0.673 (0.648-0.697); vs. APCS, 0.588 (0.564-0.611), P probability model can assess the risk of ACRN more accurately than existing models, including the APCS, KCS, and Kaminski's scoring models.

  8. Ecological models and pesticide risk assessment: current modeling practice.

    Science.gov (United States)

    Schmolke, Amelie; Thorbek, Pernille; Chapman, Peter; Grimm, Volker

    2010-04-01

    Ecological risk assessments of pesticides usually focus on risk at the level of individuals, and are carried out by comparing exposure and toxicological endpoints. However, in most cases the protection goal is populations rather than individuals. On the population level, effects of pesticides depend not only on exposure and toxicity, but also on factors such as life history characteristics, population structure, timing of application, presence of refuges in time and space, and landscape structure. Ecological models can integrate such factors and have the potential to become important tools for the prediction of population-level effects of exposure to pesticides, thus allowing extrapolations, for example, from laboratory to field. Indeed, a broad range of ecological models have been applied to chemical risk assessment in the scientific literature, but so far such models have only rarely been used to support regulatory risk assessments of pesticides. To better understand the reasons for this situation, the current modeling practice in this field was assessed in the present study. The scientific literature was searched for relevant models and assessed according to nine characteristics: model type, model complexity, toxicity measure, exposure pattern, other factors, taxonomic group, risk assessment endpoint, parameterization, and model evaluation. The present study found that, although most models were of a high scientific standard, many of them would need modification before they are suitable for regulatory risk assessments. The main shortcomings of currently available models in the context of regulatory pesticide risk assessments were identified. When ecological models are applied to regulatory risk assessments, we recommend reviewing these models according to the nine characteristics evaluated here. (c) 2010 SETAC.

  9. Quantified Risk Ranking Model for Condition-Based Risk and Reliability Centered Maintenance

    Science.gov (United States)

    Chattopadhyaya, Pradip Kumar; Basu, Sushil Kumar; Majumdar, Manik Chandra

    2017-06-01

    In the recent past, risk and reliability centered maintenance (RRCM) framework is introduced with a shift in the methodological focus from reliability and probabilities (expected values) to reliability, uncertainty and risk. In this paper authors explain a novel methodology for risk quantification and ranking the critical items for prioritizing the maintenance actions on the basis of condition-based risk and reliability centered maintenance (CBRRCM). The critical items are identified through criticality analysis of RPN values of items of a system and the maintenance significant precipitating factors (MSPF) of items are evaluated. The criticality of risk is assessed using three risk coefficients. The likelihood risk coefficient treats the probability as a fuzzy number. The abstract risk coefficient deduces risk influenced by uncertainty, sensitivity besides other factors. The third risk coefficient is called hazardous risk coefficient, which is due to anticipated hazards which may occur in the future and the risk is deduced from criteria of consequences on safety, environment, maintenance and economic risks with corresponding cost for consequences. The characteristic values of all the three risk coefficients are obtained with a particular test. With few more tests on the system, the values may change significantly within controlling range of each coefficient, hence `random number simulation' is resorted to obtain one distinctive value for each coefficient. The risk coefficients are statistically added to obtain final risk coefficient of each critical item and then the final rankings of critical items are estimated. The prioritization in ranking of critical items using the developed mathematical model for risk assessment shall be useful in optimization of financial losses and timing of maintenance actions.

  10. Lung cancer risk models from experimental animals

    International Nuclear Information System (INIS)

    Gilbert, E.S.

    1988-03-01

    The objective of this paper is to present analyses of data based on methods that adequately account for time-related factors and competiting risks, and that yield results that are expressed in a form comparable to results obtained from recent analyses of epidemiological studies of humans exposed to radon and radon daughters. These epidemiological analyses have modeled the hazard, or age-specific death rates, as a function of factors such as dose and dose rate, time from exposure, and time from cessation of exposure. The starting point for many of the analyses of human data has been the constant relative risk modeling which the age-specific death rates are assumed to be a function of cumulative dose, and the risks due to exposure are assumed to be proportional to the age-specific baseline death rates. However, departures from this initial model, such as dependence of risks on age at risk and/or time from exposure, have been investigated. These analyses have frequently been based on a non-parametric model that requires minimal assumptions regarding the baseline risks and their dependence on age

  11. Quantitative occupational risk model: Single hazard

    International Nuclear Information System (INIS)

    Papazoglou, I.A.; Aneziris, O.N.; Bellamy, L.J.; Ale, B.J.M.; Oh, J.

    2017-01-01

    A model for the quantification of occupational risk of a worker exposed to a single hazard is presented. The model connects the working conditions and worker behaviour to the probability of an accident resulting into one of three types of consequence: recoverable injury, permanent injury and death. Working conditions and safety barriers in place to reduce the likelihood of an accident are included. Logical connections are modelled through an influence diagram. Quantification of the model is based on two sources of information: a) number of accidents observed over a period of time and b) assessment of exposure data of activities and working conditions over the same period of time and the same working population. Effectiveness of risk reducing measures affecting the working conditions, worker behaviour and/or safety barriers can be quantified through the effect of these measures on occupational risk. - Highlights: • Quantification of occupational risk from a single hazard. • Influence diagram connects working conditions, worker behaviour and safety barriers. • Necessary data include the number of accidents and the total exposure of worker • Effectiveness of risk reducing measures is quantified through the impact on the risk • An example illustrates the methodology.

  12. Risk analysis of industrial plants operation

    International Nuclear Information System (INIS)

    Hubert, Philippe

    1989-12-01

    This study examines the possibilities of systematic technology risk analysis in view of territorial management (city, urban community, region), including chronic and accidental risks. The objective was to relate this evaluation with those done for permanent water and air pollution. Risk management for pollution are done for a long time. A number of studies were done in urban communities and regions both for air and water pollution. The second objective is related to management of industrial risks: nuclear, petrochemical, transport of hazardous material, pipelines, etc. At the beginning, three possibilities of effects are taken into account: human health, economic aspect and water, and possibilities of evaluation are identified. Elements of risk identification are presented for quantification of results [fr

  13. Risk analysis of alternative energy sources

    International Nuclear Information System (INIS)

    Kazmer, D.R.

    1982-01-01

    The author explores two points raised by Miller Spangler in a January 1981 issue: public perception of risks involving nuclear power plants relative to those of conventional plants and criteria for evaluating the way risk analyses are made. On the first point, he concludes that translating public attitudes into the experts' language of probability and risk could provide better information and understanding of both the attitudes and the risks. Viewing risk analysis methodologies as filters which help to test historical change, he suggests that the lack of information favors a lay jury approach for energy decisions. Spangler responds that Congress is an example of lay decision making, but that a lay jury, given public disinterest and polarization, would probably not improve social justice on the nuclear issue. 5 references, 4 figures

  14. RISK LEVEL ANALYSIS ON THE PREVENTIVE EROSION CAPACITY OF BRIDGES

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Deficiency of the Preventive Erosion Capacity (PEC) of a bridge pier is the main factor leading to bridge failures. In this paper, the PEC of bridge piers was analyzed using the stochastic analysis method. The definitions of the reliability and risk level of a bridge pier subjected to water erosion were proposed and a computational model for erosion depth and risk level in was suggested.

  15. LANDSAFE: LANDING SITE RISK ANALYSIS SOFTWARE FRAMEWORK

    OpenAIRE

    Schmidt, Ralph; Bostelmann, Jonas; Cornet, Yves; Heipke, Christian; Philippe, Christian; Poncelet, Nadia; de Rosa, Diego; Vandeloise, Yannick

    2012-01-01

    The European Space Agency (ESA) is planning a Lunar Lander mission in the 2018 timeframe that will demonstrate precise soft landing at the polar regions of the Moon. To ensure a safe and successful landing a careful risk analysis has to be carried out. This is comprised of identifying favorable target areas and evaluating the surface conditions in these areas. Features like craters, boulders, steep slopes, rough surfaces and shadow areas have to be identified in order to assess the risk assoc...

  16. Impact Analysis for Risks in Informatics Systems

    OpenAIRE

    Baicu, Floarea; Baches, Maria Alexandra

    2013-01-01

    In this paper are presented methods of impact analysis on informatics system security accidents, qualitative and quantitative methods, starting with risk and informational system security definitions. It is presented the relationship between the risks of exploiting vulnerabilities of security system, security level of these informatics systems, probability of exploiting the weak points subject to financial losses of a company, respectively impact of a security accident on the company. Herewit...

  17. Methodology for risk-based analysis of technical specifications

    International Nuclear Information System (INIS)

    Vesely, W.E.; Gaertner, J.P.; Wagner, D.P.

    1985-01-01

    Part of the effort by EPRI to apply probabilistic risk assessment methods and results to the solution of utility problems involves the investigation of methods for risk-based analysis of technical specifications. The culmination of this investigation is the SOCRATES computer code developed by Battelle's Columbus Laboratories to assist in the evaluation of technical specifications of nuclear power plants. The program is designed to use information found in PRAs to re-evaluate risk for changes in component allowed outage times (AOTs) and surveillance test intervals (STIs). The SOCRATES program is a unique and important tool for technical specification evaluations. The detailed component unavailability model allows a detailed analysis of AOT and STI contributions to risk. Explicit equations allow fast and inexpensive calculations. Because the code is designed to accept ranges of parameters and to save results of calculations that do not change during the analysis, sensitivity studies are efficiently performed and results are clearly displayed

  18. A "Toy" Model for Operational Risk Quantification using Credibility Theory

    OpenAIRE

    Hans B\\"uhlmann; Pavel V. Shevchenko; Mario V. W\\"uthrich

    2009-01-01

    To meet the Basel II regulatory requirements for the Advanced Measurement Approaches in operational risk, the bank's internal model should make use of the internal data, relevant external data, scenario analysis and factors reflecting the business environment and internal control systems. One of the unresolved challenges in operational risk is combining of these data sources appropriately. In this paper we focus on quantification of the low frequency high impact losses exceeding some high thr...

  19. Conceptual models for cumulative risk assessment.

    Science.gov (United States)

    Linder, Stephen H; Sexton, Ken

    2011-12-01

    In the absence of scientific consensus on an appropriate theoretical framework, cumulative risk assessment and related research have relied on speculative conceptual models. We argue for the importance of theoretical backing for such models and discuss 3 relevant theoretical frameworks, each supporting a distinctive "family" of models. Social determinant models postulate that unequal health outcomes are caused by structural inequalities; health disparity models envision social and contextual factors acting through individual behaviors and biological mechanisms; and multiple stressor models incorporate environmental agents, emphasizing the intermediary role of these and other stressors. The conclusion is that more careful reliance on established frameworks will lead directly to improvements in characterizing cumulative risk burdens and accounting for disproportionate adverse health effects.

  20. Fuzzy logic model to quantify risk perception

    International Nuclear Information System (INIS)

    Bukh, Julia; Dickstein, Phineas

    2008-01-01

    The aim of this study is a quantification of public risk perception towards the nuclear field so as to be considered in decision making whenever the public involvement is sought. The proposed model includes both qualitative factors such as familiarity and voluntariness and numerical factors influencing risk perception, such as probability of occurrence and severity of consequence. Since part of these factors can be characterized only by qualitative expressions and the determination of them are linked with vagueness, imprecision and uncertainty, the most suitable method for the risk level assessment is Fuzzy Logic, which models qualitative aspects of knowledge and reasoning processes without employing precise quantitative analyses. This work, then, offers a Fuzzy-Logic based mean of representing the risk perception by a single numerical feature, which can be weighted and accounted for in decision making procedures. (author)

  1. Risk of the Maritime Supply Chain System Based on Interpretative Structural Model

    Directory of Open Access Journals (Sweden)

    Jiang He

    2017-11-01

    Full Text Available Marine transportation is the most important transport mode of in the international trade, but the maritime supply chain is facing with many risks. At present, most of the researches on the risk of the maritime supply chain focus on the risk identification and risk management, and barely carry on the quantitative analysis of the logical structure of each influencing factor. This paper uses the interpretative structure model to analysis the maritime supply chain risk system. On the basis of comprehensive literature analysis and expert opinion, this paper puts forward 16 factors of maritime supply chain risk system. Using the interpretative structure model to construct maritime supply chain risk system, and then optimize the model. The model analyzes the structure of the maritime supply chain risk system and its forming process, and provides a scientific basis for the controlling the maritime supply chain risk, and puts forward some corresponding suggestions for the prevention and control the maritime supply chain risk.

  2. Lifestyle-based risk model for fall risk assessment

    OpenAIRE

    Sannino, Giovanna; De Falco, Ivanoe; De Pietro, Guiseppe

    2016-01-01

    Purpose: The aim of this study was to identify the explicit relationship between life-style and the risk of falling under the form of a mathematical model. Starting from some personal and behavioral information of a subject as, e.g., weight, height, age, data about physical activity habits, and concern about falling, the model would estimate the score of her/his Mini-Balance Evaluation Systems (Mini-BES) test. This score ranges within 0 and 28, and the lower its value the more likely the subj...

  3. Analytical Modeling for Underground Risk Assessment in Smart Cities

    Directory of Open Access Journals (Sweden)

    Israr Ullah

    2018-06-01

    Full Text Available In the developed world, underground facilities are increasing day-by-day, as it is considered as an improved utilization of available space in smart cities. Typical facilities include underground railway lines, electricity lines, parking lots, water supply systems, sewerage network, etc. Besides its utility, these facilities also pose serious threats to citizens and property. To preempt accidental loss of precious human lives and properties, a real time monitoring system is highly desirable for conducting risk assessment on continuous basis and timely report any abnormality before its too late. In this paper, we present an analytical formulation to model system behavior for risk analysis and assessment based on various risk contributing factors. Based on proposed analytical model, we have evaluated three approximation techniques for computing final risk index: (a simple linear approximation based on multiple linear regression analysis; (b hierarchical fuzzy logic based technique in which related risk factors are combined in a tree like structure; and (c hybrid approximation approach which is a combination of (a and (b. Experimental results shows that simple linear approximation fails to accurately estimate final risk index as compared to hierarchical fuzzy logic based system which shows that the latter provides an efficient method for monitoring and forecasting critical issues in the underground facilities and may assist in maintenance efficiency as well. Estimation results based on hybrid approach fails to accurately estimate final risk index. However, hybrid scheme reveals some interesting and detailed information by performing automatic clustering based on location risk index.

  4. Risk Assessment and Integration Team (RAIT) Portfolio Risk Analysis Strategy

    Science.gov (United States)

    Edwards, Michelle

    2010-01-01

    Impact at management level: Qualitative assessment of risk criticality in conjunction with risk consequence, likelihood, and severity enable development of an "investment policy" towards managing a portfolio of risks. Impact at research level: Quantitative risk assessments enable researchers to develop risk mitigation strategies with meaningful risk reduction results. Quantitative assessment approach provides useful risk mitigation information.

  5. Bayesian Inference for NASA Probabilistic Risk and Reliability Analysis

    Science.gov (United States)

    Dezfuli, Homayoon; Kelly, Dana; Smith, Curtis; Vedros, Kurt; Galyean, William

    2009-01-01

    This document, Bayesian Inference for NASA Probabilistic Risk and Reliability Analysis, is intended to provide guidelines for the collection and evaluation of risk and reliability-related data. It is aimed at scientists and engineers familiar with risk and reliability methods and provides a hands-on approach to the investigation and application of a variety of risk and reliability data assessment methods, tools, and techniques. This document provides both: A broad perspective on data analysis collection and evaluation issues. A narrow focus on the methods to implement a comprehensive information repository. The topics addressed herein cover the fundamentals of how data and information are to be used in risk and reliability analysis models and their potential role in decision making. Understanding these topics is essential to attaining a risk informed decision making environment that is being sought by NASA requirements and procedures such as 8000.4 (Agency Risk Management Procedural Requirements), NPR 8705.05 (Probabilistic Risk Assessment Procedures for NASA Programs and Projects), and the System Safety requirements of NPR 8715.3 (NASA General Safety Program Requirements).

  6. [Risk factor analysis of the patients with solitary pulmonary nodules and establishment of a prediction model for the probability of malignancy].

    Science.gov (United States)

    Wang, X; Xu, Y H; Du, Z Y; Qian, Y J; Xu, Z H; Chen, R; Shi, M H

    2018-02-23

    Objective: This study aims to analyze the relationship among the clinical features, radiologic characteristics and pathological diagnosis in patients with solitary pulmonary nodules, and establish a prediction model for the probability of malignancy. Methods: Clinical data of 372 patients with solitary pulmonary nodules who underwent surgical resection with definite postoperative pathological diagnosis were retrospectively analyzed. In these cases, we collected clinical and radiologic features including gender, age, smoking history, history of tumor, family history of cancer, the location of lesion, ground-glass opacity, maximum diameter, calcification, vessel convergence sign, vacuole sign, pleural indentation, speculation and lobulation. The cases were divided to modeling group (268 cases) and validation group (104 cases). A new prediction model was established by logistic regression analying the data from modeling group. Then the data of validation group was planned to validate the efficiency of the new model, and was compared with three classical models(Mayo model, VA model and LiYun model). With the calculated probability values for each model from validation group, SPSS 22.0 was used to draw the receiver operating characteristic curve, to assess the predictive value of this new model. Results: 112 benign SPNs and 156 malignant SPNs were included in modeling group. Multivariable logistic regression analysis showed that gender, age, history of tumor, ground -glass opacity, maximum diameter, and speculation were independent predictors of malignancy in patients with SPN( P prediction model for the probability of malignancy as follow: p =e(x)/(1+ e(x)), x=-4.8029-0.743×gender+ 0.057×age+ 1.306×history of tumor+ 1.305×ground-glass opacity+ 0.051×maximum diameter+ 1.043×speculation. When the data of validation group was added to the four-mathematical prediction model, The area under the curve of our mathematical prediction model was 0.742, which is greater

  7. Bankruptcy risk model and empirical tests

    Science.gov (United States)

    Podobnik, Boris; Horvatic, Davor; Petersen, Alexander M.; Urošević, Branko; Stanley, H. Eugene

    2010-01-01

    We analyze the size dependence and temporal stability of firm bankruptcy risk in the US economy by applying Zipf scaling techniques. We focus on a single risk factor—the debt-to-asset ratio R—in order to study the stability of the Zipf distribution of R over time. We find that the Zipf exponent increases during market crashes, implying that firms go bankrupt with larger values of R. Based on the Zipf analysis, we employ Bayes’s theorem and relate the conditional probability that a bankrupt firm has a ratio R with the conditional probability of bankruptcy for a firm with a given R value. For 2,737 bankrupt firms, we demonstrate size dependence in assets change during the bankruptcy proceedings. Prepetition firm assets and petition firm assets follow Zipf distributions but with different exponents, meaning that firms with smaller assets adjust their assets more than firms with larger assets during the bankruptcy process. We compare bankrupt firms with nonbankrupt firms by analyzing the assets and liabilities of two large subsets of the US economy: 2,545 Nasdaq members and 1,680 New York Stock Exchange (NYSE) members. We find that both assets and liabilities follow a Pareto distribution. The finding is not a trivial consequence of the Zipf scaling relationship of firm size quantified by employees—although the market capitalization of Nasdaq stocks follows a Pareto distribution, the same distribution does not describe NYSE stocks. We propose a coupled Simon model that simultaneously evolves both assets and debt with the possibility of bankruptcy, and we also consider the possibility of firm mergers. PMID:20937903

  8. Implications of lower risk thresholds for statin treatment in primary prevention: analysis of CPRD and simulation modelling of annual cholesterol monitoring.

    Science.gov (United States)

    McFadden, Emily; Stevens, Richard; Glasziou, Paul; Perera, Rafael

    2015-01-01

    To estimate numbers affected by a recent change in UK guidelines for statin use in primary prevention of cardiovascular disease. We modelled cholesterol ratio over time using a sample of 45,151 men (≥40years) and 36,168 women (≥55years) in 2006, without statin treatment or previous cardiovascular disease, from the Clinical Practice Research Datalink. Using simulation methods, we estimated numbers indicated for new statin treatment, if cholesterol was measured annually and used in the QRISK2 CVD risk calculator, using the previous 20% and newly recommended 10% thresholds. We estimate that 58% of men and 55% of women would be indicated for treatment by five years and 71% of men and 73% of women by ten years using the 20% threshold. Using the proposed threshold of 10%, 84% of men and 90% of women would be indicated for treatment by 5years and 92% of men and 98% of women by ten years. The proposed change of risk threshold from 20% to 10% would result in the substantial majority of those recommended for cholesterol testing being indicated for statin treatment. Implications depend on the value of statins in those at low to medium risk, and whether there are harms. Copyright © 2014. Published by Elsevier Inc.

  9. Seismic risk analysis in the German risk study phase B

    International Nuclear Information System (INIS)

    Hasser, D.; Liemersdorf, J.

    1989-01-01

    The paper discusses some aspects of the seismic risk part of the German risk study for nuclear power plants, phase B. First simplified analyses in phase A of the study allowed a rough classification of structures and systems of the PWR reference plant according to their seismic risk contribution. These studies were extended in phase B using improved models for the dynamic analyses of buildings, structures and components as well as for the probabilistic analyses of seismic loading, failure probabilities and event trees. The methodology of deriving probabilistic seismic load descriptions is explained and compared with the methods in phase A of the study and in other studies. Some details of the linear and nonlinear dynamic analyses of structures are reported, in order to demonstrate the influence of different assumptions for material behavior and failure criteria. The probabilistic structural and event tree analyses are discussed with respect to the distribution assumptions, acceptable simplifications, special results for the PWR reference plant and, finally, the influence of model uncertainties

  10. New algorithm for risk analysis in radiotherapy

    International Nuclear Information System (INIS)

    Torres, Antonio; Montes de Oca, Joe

    2015-01-01

    Risk analyses applied to radiotherapy treatments have become an undeniable necessity, considering the dangers generated by the combination of using powerful radiation fields on patients and the occurrence of human errors and equipment failures during these treatments. The technique par excellence to execute these analyses has been the risk matrix. This paper presents the development of a new algorithm to execute the task with wide graphic and analytic potentialities, thus transforming it into a very useful option for risk monitoring and the optimization of quality assurance. The system SECURE- MR, which is the basic software of this algorithm, has been successfully used in risk analysis regarding different kinds of radiotherapies. Compared to previous methods, It offers new possibilities of analysis considering risk controlling factors as the robustness of reducers of initiators frequency and its consequences. Their analytic capacities and graphs allow novel developments to classify risk contributing factors, to represent information processes as well as accidental sequences. The paper shows the application of the proposed system to a generic process of radiotherapy treatment using a lineal accelerator. (author)

  11. Living PRAs [probabilistic risk analysis] made easier with IRRAS [Integrated Reliability and Risk Analysis System

    International Nuclear Information System (INIS)

    Russell, K.D.; Sattison, M.B.; Rasmuson, D.M.

    1989-01-01

    The Integrated Reliability and Risk Analysis System (IRRAS) is an integrated PRA software tool that gives the user the ability to create and analyze fault trees and accident sequences using an IBM-compatible microcomputer. This program provides functions that range from graphical fault tree and event tree construction to cut set generation and quantification. IRRAS contains all the capabilities and functions required to create, modify, reduce, and analyze event tree and fault tree models used in the analysis of complex systems and processes. IRRAS uses advanced graphic and analytical techniques to achieve the greatest possible realization of the potential of the microcomputer. When the needs of the user exceed this potential, IRRAS can call upon the power of the mainframe computer. The role of the Idaho National Engineering Laboratory if the IRRAS program is that of software developer and interface to the user community. Version 1.0 of the IRRAS program was released in February 1987 to prove the concept of performing this kind of analysis on microcomputers. This version contained many of the basic features needed for fault tree analysis and was received very well by the PRA community. Since the release of Version 1.0, many user comments and enhancements have been incorporated into the program providing a much more powerful and user-friendly system. This version is designated ''IRRAS 2.0''. Version 3.0 will contain all of the features required for efficient event tree and fault tree construction and analysis. 5 refs., 26 figs

  12. Improving default risk prediction using Bayesian model uncertainty techniques.

    Science.gov (United States)

    Kazemi, Reza; Mosleh, Ali

    2012-11-01

    Credit risk is the potential exposure of a creditor to an obligor's failure or refusal to repay the debt in principal or interest. The potential of exposure is measured in terms of probability of default. Many models have been developed to estimate credit risk, with rating agencies dating back to the 19th century. They provide their assessment of probability of default and transition probabilities of various firms in their annual reports. Regulatory capital requirements for credit risk outlined by the Basel Committee on Banking Supervision have made it essential for banks and financial institutions to develop sophisticated models in an attempt to measure credit risk with higher accuracy. The Bayesian framework proposed in this article uses the techniques developed in physical sciences and engineering for dealing with model uncertainty and expert accuracy to obtain improved estimates of credit risk and associated uncertainties. The approach uses estimates from one or more rating agencies and incorporates their historical accuracy (past performance data) in estimating future default risk and transition probabilities. Several examples demonstrate that the proposed methodology can assess default probability with accuracy exceeding the estimations of all the individual models. Moreover, the methodology accounts for potentially significant departures from "nominal predictions" due to "upsetting events" such as the 2008 global banking crisis. © 2012 Society for Risk Analysis.

  13. Automated procedure for performing computer security risk analysis

    International Nuclear Information System (INIS)

    Smith, S.T.; Lim, J.J.

    1984-05-01

    Computers, the invisible backbone of nuclear safeguards, monitor and control plant operations and support many materials accounting systems. Our automated procedure to assess computer security effectiveness differs from traditional risk analysis methods. The system is modeled as an interactive questionnaire, fully automated on a portable microcomputer. A set of modular event trees links the questionnaire to the risk assessment. Qualitative scores are obtained for target vulnerability, and qualitative impact measures are evaluated for a spectrum of threat-target pairs. These are then combined by a linguistic algebra to provide an accurate and meaningful risk measure. 12 references, 7 figures

  14. An Agent-Based Model of Evolving Community Flood Risk.

    Science.gov (United States)

    Tonn, Gina L; Guikema, Seth D

    2017-11-17

    Although individual behavior plays a major role in community flood risk, traditional flood risk models generally do not capture information on how community policies and individual decisions impact the evolution of flood risk over time. The purpose of this study is to improve the understanding of the temporal aspects of flood risk through a combined analysis of the behavioral, engineering, and physical hazard aspects of flood risk. Additionally, the study aims to develop a new modeling approach for integrating behavior, policy, flood hazards, and engineering interventions. An agent-based model (ABM) is used to analyze the influence of flood protection measures, individual behavior, and the occurrence of floods and near-miss flood events on community flood risk. The ABM focuses on the following decisions and behaviors: dissemination of flood management information, installation of community flood protection, elevation of household mechanical equipment, and elevation of homes. The approach is place based, with a case study area in Fargo, North Dakota, but is focused on generalizable insights. Generally, community mitigation results in reduced future damage, and individual action, including mitigation and movement into and out of high-risk areas, can have a significant influence on community flood risk. The results of this study provide useful insights into the interplay between individual and community actions and how it affects the evolution of flood risk. This study lends insight into priorities for future work, including the development of more in-depth behavioral and decision rules at the individual and community level. © 2017 Society for Risk Analysis.

  15. SDI CFD MODELING ANALYSIS

    Energy Technology Data Exchange (ETDEWEB)

    Lee, S.

    2011-05-05

    The Savannah River Remediation (SRR) Organization requested that Savannah River National Laboratory (SRNL) develop a Computational Fluid Dynamics (CFD) method to mix and blend the miscible contents of the blend tanks to ensure the contents are properly blended before they are transferred from the blend tank; such as, Tank 50H, to the Salt Waste Processing Facility (SWPF) feed tank. The work described here consists of two modeling areas. They are the mixing modeling analysis during miscible liquid blending operation, and the flow pattern analysis during transfer operation of the blended liquid. The transient CFD governing equations consisting of three momentum equations, one mass balance, two turbulence transport equations for kinetic energy and dissipation rate, and one species transport were solved by an iterative technique until the species concentrations of tank fluid were in equilibrium. The steady-state flow solutions for the entire tank fluid were used for flow pattern analysis, for velocity scaling analysis, and the initial conditions for transient blending calculations. A series of the modeling calculations were performed to estimate the blending times for various jet flow conditions, and to investigate the impact of the cooling coils on the blending time of the tank contents. The modeling results were benchmarked against the pilot scale test results. All of the flow and mixing models were performed with the nozzles installed at the mid-elevation, and parallel to the tank wall. From the CFD modeling calculations, the main results are summarized as follows: (1) The benchmark analyses for the CFD flow velocity and blending models demonstrate their consistency with Engineering Development Laboratory (EDL) and literature test results in terms of local velocity measurements and experimental observations. Thus, an application of the established criterion to SRS full scale tank will provide a better, physically-based estimate of the required mixing time, and

  16. The watchdog role of risk analysis

    International Nuclear Information System (INIS)

    Reijen, G. van; Vinck, W.

    1983-01-01

    The reason why the risks of large-scale technology attract more attention lies in the fact that accidents would have more disastrous results and in the fact that it is probably more attractive to study the risks of some large projects than to do the same for a greater number of smaller projects. Within this presentation there will be some opening remarks on the Role of the Commission of the European Community with regard to accident prevention. The development of the concept of quantitative risks is dealt with. This development leads to a combinded of deterministic and probabilistic methods. The presentation concludes with some critical remarks on quantitative risk analysis and its use. (orig./HP) [de

  17. Development and validation of a prognostic model to predict death in patients with traumatic bleeding, and evaluation of the effect of tranexamic acid on mortality according to baseline risk: a secondary analysis of a randomised controlled trial.

    Science.gov (United States)

    Perel, P; Prieto-Merino, D; Shakur, H; Roberts, I

    2013-06-01

    Severe bleeding accounts for about one-third of in-hospital trauma deaths. Patients with a high baseline risk of death have the most to gain from the use of life-saving treatments. An accurate and user-friendly prognostic model to predict mortality in bleeding trauma patients could assist doctors and paramedics in pre-hospital triage and could shorten the time to diagnostic and life-saving procedures such as surgery and tranexamic acid (TXA). The aim of the study was to develop and validate a prognostic model for early mortality in patients with traumatic bleeding and to examine whether or not the effect of TXA on the risk of death and thrombotic events in bleeding adult trauma patients varies according to baseline risk. Multivariable logistic regression and risk-stratified analysis of a large international cohort of trauma patients. Two hundred and seventy-four hospitals in 40 high-, medium- and low-income countries. We derived prognostic models in a large placebo-controlled trial of the effects of early administration of a short course of TXA [Clinical Randomisation of an Antifibrinolytic in Significant Haemorrhage (CRASH-2) trial]. The trial included 20,127 trauma patients with, or at risk of, significant bleeding, within 8 hours of injury. We externally validated the model on 14,220 selected trauma patients from the Trauma Audit and Research Network (TARN), which included mainly patients from the UK. We examined the effect of TXA on all-cause mortality, death due to bleeding and thrombotic events (fatal and non-fatal myocardial infarction, stroke, deep-vein thrombosis and pulmonary embolism) within risk strata in the CRASH-2 trial data set and we estimated the proportion of premature deaths averted by applying the odds ratio (OR) from the CRASH-2 trial to each of the risk strata in TARN. For the stratified analysis according baseline risk we considered the intervention TXA (1 g over 10 minutes followed by 1 g over 8 hours) or matching placebo. For the

  18. Risk management in organic coffee supply chains : testing the usefulness of critical risk models

    NARCIS (Netherlands)

    Brusselaers, J.F.; Benninga, J.; Hennen, W.H.G.J.

    2011-01-01

    This report documents the findings of the analysis of the supply chain of organic coffee from Uganda to the Netherlands using a Chain Risk Model (CRM). The CRM considers contamination of organic coffee with chemicals as a threat for the supply chain, and analyses the consequences of contamination in

  19. Game Theoretic Risk Analysis of Security Threats

    CERN Document Server

    Bier, Vicki M

    2008-01-01

    Introduces reliability and risk analysis in the face of threats by intelligent agents. This book covers applications to networks, including problems in both telecommunications and transportation. It provides a set of tools for applying game theory TO reliability problems in the presence of intentional, intelligent threats

  20. Economic impact assessment in pest risk analysis

    NARCIS (Netherlands)

    Soliman, T.A.A.; Mourits, M.C.M.; Oude Lansink, A.G.J.M.; Werf, van der W.

    2010-01-01

    According to international treaties, phytosanitary measures against introduction and spread of invasive plant pests must be justified by a science-based pest risk analysis (PRA). Part of the PRA consists of an assessment of potential economic consequences. This paper evaluates the main available

  1. Analysis of Advantages and Disadvantages of Current Operational Risk Management Models (AS/NZS 4360, AS/NZS ISO 9000, AS/NZS ISO 14000, AS/NZS 4801, AS/NZS 3806, AS/NZS 4444

    Directory of Open Access Journals (Sweden)

    Ferry Jie

    2002-09-01

    Full Text Available This paper will describe about the analysis of advantages and disadvantages of current operational risk management models (AS/NZS 4360: Risk Management, AS/NZS 4801: Occupational Health and Safety Management Systems, AS/NZS ISO 9001: Quality Management System, AS/NZS ISO 14001: Environment Management System, AS/NZS 3806: Compliance Management System, AS/NZS 4444: Information Security Management  based on expert experiences and extracting the literature review. The advantages of most current models are widely adopted by industries of various of sizes as the basis for their operational risk management. In addition, they may help the organizations to improve the operations and competitiveness. However, there are some disadvantages of most current models such as the models are very general (guidance only, not specific to cover particular risks of industries.  And they don’t have the specific tools and processes.  In addition, they may not be able to integrate all elements of the management systems such as safety, health, environment, quality, security, and compliance. 

  2. Analysis of interactions among barriers in project risk management

    Science.gov (United States)

    Dandage, Rahul V.; Mantha, Shankar S.; Rane, Santosh B.; Bhoola, Vanita

    2018-03-01

    In the context of the scope, time, cost, and quality constraints, failure is not uncommon in project management. While small projects have 70% chances of success, large projects virtually have no chance of meeting the quadruple constraints. While there is no dearth of research on project risk management, the manifestation of barriers to project risk management is a less dwelt topic. The success of project management is oftentimes based on the understanding of barriers to effective risk management, application of appropriate risk management methodology, proactive leadership to avoid barriers, workers' attitude, adequate resources, organizational culture, and involvement of top management. This paper represents various risk categories and barriers to risk management in domestic and international projects through literature survey and feedback from project professionals. After analysing the various modelling methods used in project risk management literature, interpretive structural modelling (ISM) and MICMAC analysis have been used to analyse interactions among the barriers and prioritize them. The analysis indicates that lack of top management support, lack of formal training, and lack of addressing cultural differences are the high priority barriers, among many others.

  3. Analysis of Blade Fragment Risk at a Wind Energy Facility

    Energy Technology Data Exchange (ETDEWEB)

    Simms, David A [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Larwood, Scott [University of the Pacific

    2018-04-06

    An analysis was performed to determine the risk posed by wind turbine fragments on roads and buildings at the National Wind Technology Center at the National Renewable Energy Laboratory. The authors used a previously developed model of fragment trajectory and took into account the wind speed/direction distribution at the site and the probability of rotor failure. The risk was assessed by determining the likelihood of impact and related consequences. For both the roads and buildings, the risk varied from low to routine, which was considered acceptable. The analysis was compared with previous recommendations on wind turbine setback distances. The results showed that a setback to property lines of 2 times the overall turbine height would be acceptable. However, the setback to dwellings should probably be increased from 3 to 3.5 times the overall turbine height for an acceptable risk.

  4. A Probabilistic Typhoon Risk Model for Vietnam

    Science.gov (United States)

    Haseemkunju, A.; Smith, D. F.; Brolley, J. M.

    2017-12-01

    Annually, the coastal Provinces of low-lying Mekong River delta region in the southwest to the Red River Delta region in Northern Vietnam is exposed to severe wind and flood risk from landfalling typhoons. On average, about two to three tropical cyclones with a maximum sustained wind speed of >=34 knots make landfall along the Vietnam coast. Recently, Typhoon Wutip (2013) crossed Central Vietnam as a category 2 typhoon causing significant damage to properties. As tropical cyclone risk is expected to increase with increase in exposure and population growth along the coastal Provinces of Vietnam, insurance/reinsurance, and capital markets need a comprehensive probabilistic model to assess typhoon risk in Vietnam. In 2017, CoreLogic has expanded the geographical coverage of its basin-wide Western North Pacific probabilistic typhoon risk model to estimate the economic and insured losses from landfalling and by-passing tropical cyclones in Vietnam. The updated model is based on 71 years (1945-2015) of typhoon best-track data and 10,000 years of a basin-wide simulated stochastic tracks covering eight countries including Vietnam. The model is capable of estimating damage from wind, storm surge and rainfall flooding using vulnerability models, which relate typhoon hazard to building damageability. The hazard and loss models are validated against past historical typhoons affecting Vietnam. Notable typhoons causing significant damage in Vietnam are Lola (1993), Frankie (1996), Xangsane (2006), and Ketsana (2009). The central and northern coastal provinces of Vietnam are more vulnerable to wind and flood hazard, while typhoon risk in the southern provinces are relatively low.

  5. Model based climate information on drought risk in Africa

    Science.gov (United States)

    Calmanti, S.; Syroka, J.; Jones, C.; Carfagna, F.; Dell'Aquila, A.; Hoefsloot, P.; Kaffaf, S.; Nikulin, G.

    2012-04-01

    The United Nations World Food Programme (WFP) has embarked upon the endeavor of creating a sustainable Africa-wide natural disaster risk management system. A fundamental building block of this initiative is the setup of a drought impact modeling platform called Africa Risk-View that aims to quantify and monitor weather-related food security risk in Africa. The modeling approach is based the Water Requirement Satisfaction Index (WRSI), as the fundamental indicator of the performances of agriculture and uses historical records of food assistance operation to project future potential needs for livelihood protection. By using climate change scenarios as an input to Africa Risk-View it is possible, in principles, to evaluate the future impact of climate variability on critical issues such as food security and the overall performance of the envisaged risk management system. A necessary preliminary step to this challenging task is the exploration of the sources of uncertainties affecting the assessment based on modeled climate change scenarios. For this purpose, a limited set of climate models have been selected in order verify the relevance of using climate model output data with Africa Risk-View and to explore a minimal range of possible sources of uncertainty. This first evaluation exercise started before the setup of the CORDEX framework and has relied on model output available at the time. In particular only one regional downscaling was available for the entire African continent from the ENSEMBLES project. The analysis shows that current coarse resolution global climate models can not directly feed into the Africa RiskView risk-analysis tool. However, regional downscaling may help correcting the inherent biases observed in the datasets. Further analysis is performed by using the first data available under the CORDEX framework. In particular, we consider a set of simulation driven with boundary conditions from the reanalysis ERA-Interim to evaluate the skill drought

  6. Application of the Beck model to stock markets: Value-at-Risk and portfolio risk assessment

    Science.gov (United States)

    Kozaki, M.; Sato, A.-H.

    2008-02-01

    We apply the Beck model, developed for turbulent systems that exhibit scaling properties, to stock markets. Our study reveals that the Beck model elucidates the properties of stock market returns and is applicable to practical use such as the Value-at-Risk estimation and the portfolio analysis. We perform empirical analysis with daily/intraday data of the S&P500 index return and find that the volatility fluctuation of real markets is well-consistent with the assumptions of the Beck model: The volatility fluctuates at a much larger time scale than the return itself and the inverse of variance, or “inverse temperature”, β obeys Γ-distribution. As predicted by the Beck model, the distribution of returns is well-fitted by q-Gaussian distribution of Tsallis statistics. The evaluation method of Value-at-Risk (VaR), one of the most significant indicators in risk management, is studied for q-Gaussian distribution. Our proposed method enables the VaR evaluation in consideration of tail risk, which is underestimated by the variance-covariance method. A framework of portfolio risk assessment under the existence of tail risk is considered. We propose a multi-asset model with a single volatility fluctuation shared by all assets, named the single β model, and empirically examine the agreement between the model and an imaginary portfolio with Dow Jones indices. It turns out that the single β model gives good approximation to portfolios composed of the assets with non-Gaussian and correlated returns.

  7. Stochastic Watershed Models for Risk Based Decision Making

    Science.gov (United States)

    Vogel, R. M.

    2017-12-01

    Over half a century ago, the Harvard Water Program introduced the field of operational or synthetic hydrology providing stochastic streamflow models (SSMs), which could generate ensembles of synthetic streamflow traces useful for hydrologic risk management. The application of SSMs, based on streamflow observations alone, revolutionized water resources planning activities, yet has fallen out of favor due, in part, to their inability to account for the now nearly ubiquitous anthropogenic influences on streamflow. This commentary advances the modern equivalent of SSMs, termed `stochastic watershed models' (SWMs) useful as input to nearly all modern risk based water resource decision making approaches. SWMs are deterministic watershed models implemented using stochastic meteorological series, model parameters and model errors, to generate ensembles of streamflow traces that represent the variability in possible future streamflows. SWMs combine deterministic watershed models, which are ideally suited to accounting for anthropogenic influences, with recent developments in uncertainty analysis and principles of stochastic simulation

  8. Risk considerations related to lung modeling

    International Nuclear Information System (INIS)

    Masse, R.; Cross, F.T.

    1989-01-01

    Improved lung models provide a more accurate assessment of dose from inhalation exposures and, therefore, more accurate dose-response relationships for risk evaluation and exposure limitation. Epidemiological data for externally irradiated persons indicate that the numbers of excess respiratory tract carcinomas differ in the upper airways, bronchi, and distal lung. Neither their histogenesis and anatomical location nor their progenitor cells are known with sufficient accuracy for accurate assessment of the microdosimetry. The nuclei of sensitive cells generally can be assumed to be distributed at random in the epithelium, beneath the mucus and tips of the beating cilia and cells. In stratified epithelia, basal cells may be considered the only cells at risk. Upper-airway tumors have been observed in both therapeutically irradiated patients and in Hiroshima-Nagasaki survivors. The current International Commission on Radiological Protection Lung-Model Task Group proposes that the upper airways and lung have a similar relative risk coefficient for cancer induction. The partition of the risk weighting factor, therefore, will be proportional to the spontaneous death rate from tumors, and 80% of the weighting factor for the respiratory tract should be attributed to the lung. For Weibel lung-model branching generations 0 to 16 and 17 to 23, the Task Group proposes an 80/20 partition of the risk, i.e., 64% and 16%, respectively, of the total risk. Regarding risk in animals, recent data in rats indicate a significantly lower effectiveness for lung-cancer induction at low doses from insoluble long-lived alpha-emitters than from Rn daughters. These findings are due, in part, to the fact that different regions of the lung are irradiated. Tumors in the lymph nodes are rare in people and animals exposed to radiation.44 references

  9. A general psychopathology factor (P factor) in children: Structural model analysis and external validation through familial risk and child global executive function.

    Science.gov (United States)

    Martel, Michelle M; Pan, Pedro M; Hoffmann, Maurício S; Gadelha, Ary; do Rosário, Maria C; Mari, Jair J; Manfro, Gisele G; Miguel, Eurípedes C; Paus, Tomás; Bressan, Rodrigo A; Rohde, Luis A; Salum, Giovanni A

    2017-01-01

    High rates of comorbidities and poor validity of disorder diagnostic criteria for mental disorders hamper advances in mental health research. Recent work has suggested the utility of continuous cross-cutting dimensions, including general psychopathology and specific factors of externalizing and internalizing (e.g., distress and fear) syndromes. The current study evaluated the reliability of competing structural models of psychopathology and examined external validity of the best fitting model on the basis of family risk and child global executive function (EF). A community sample of 8,012 families from Brazil with children ages 6-12 years completed structured interviews about the child and parental psychiatric syndromes, and a subsample of 2,395 children completed tasks assessing EF (i.e., working memory, inhibitory control, and time processing). Confirmatory factor analyses tested a series of structural models of psychopathology in both parents and children. The model with a general psychopathology factor ("P factor") with 3 specific factors (fear, distress, and externalizing) exhibited the best fit. The general P factor accounted for most of the variance in all models, with little residual variance explained by each of the 3 specific factors. In addition, associations between child and parental factors were mainly significant for the P factors and nonsignificant for the specific factors from the respective models. Likewise, the child P factor-but not the specific factors-was significantly associated with global child EF. Overall, our results provide support for a latent overarching P factor characterizing child psychopathology, supported by familial associations and child EF. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  10. Surplus analysis of Sparre Andersen insurance risk processes

    CERN Document Server

    Willmot, Gordon E

    2017-01-01

    This carefully written monograph covers the Sparre Andersen process in an actuarial context using the renewal process as the model for claim counts. A unified reference on Sparre Andersen (renewal risk) processes is included, often missing from existing literature. The authors explore recent results and analyse various risk theoretic quantities associated with the event of ruin, including the time of ruin and the deficit of ruin. Particular attention is given to the explicit identification of defective renewal equation components, which are needed to analyse various risk theoretic quantities and are also relevant in other subject areas of applied probability such as dams and storage processes, as well as queuing theory. Aimed at researchers interested in risk/ruin theory and related areas, this work will also appeal to graduate students in classical and modern risk theory and Gerber-Shiu analysis.

  11. Case studies: Risk-based analysis of technical specifications

    International Nuclear Information System (INIS)

    Wagner, D.P.; Minton, L.A.; Gaertner, J.P.

    1987-01-01

    The SOCRATES computer program uses the results of a Probabilistic Risk Assessment (PRA) or a system level risk analysis to calculate changes in risk due to changes in the surveillance test interval and/or the allowed outage time stated in the technical specification. The computer program can accommodate various testing strategies (such as staggered or simultaneous testing) to allow modeling of component testing as it is carried out at a plant. The methods and computer program are an integral part of a larger decision process aimed at determining benefits from technical specification changes. These benefits can include cost savings to the utilities by reducing forced shutdowns with no adverse impacts on risk. Three summaries of case study applications are included to demonstrate the types of results that can be achieved through risk-based evaluation of technical specifications. (orig.)

  12. Modeling foreign exchange risk premium in Armenia

    Czech Academy of Sciences Publication Activity Database

    Poghosyan, T.; Kočenda, E.; Zemčík, Petr

    2008-01-01

    Roč. 44, č. 1 (2008), s. 41-61 ISSN 1540-496X R&D Projects: GA MŠk LC542 Institutional research plan: CEZ:AV0Z70850503 Keywords : foreign exchange risk premium * Armenia * affine term structure models Subject RIV: AH - Economics Impact factor: 0.611, year: 2008

  13. Modeling foreign exchange risk premium in Armenia

    Czech Academy of Sciences Publication Activity Database

    Poghosyan, Tigran; Kočenda, Evžen; Zemčík, P.

    2008-01-01

    Roč. 44, č. 1 (2008), s. 41-61 ISSN 1540-496X R&D Projects: GA MŠk LC542 Institutional research plan: CEZ:MSM0021620846 Keywords : foreign exchange risk premium * Armenia * affine term structure models Subject RIV: AH - Economics Impact factor: 0.611, year: 2008

  14. A Probabilistic Asteroid Impact Risk Model

    Science.gov (United States)

    Mathias, Donovan L.; Wheeler, Lorien F.; Dotson, Jessie L.

    2016-01-01

    Asteroid threat assessment requires the quantification of both the impact likelihood and resulting consequence across the range of possible events. This paper presents a probabilistic asteroid impact risk (PAIR) assessment model developed for this purpose. The model incorporates published impact frequency rates with state-of-the-art consequence assessment tools, applied within a Monte Carlo framework that generates sets of impact scenarios from uncertain parameter distributions. Explicit treatment of atmospheric entry is included to produce energy deposition rates that account for the effects of thermal ablation and object fragmentation. These energy deposition rates are used to model the resulting ground damage, and affected populations are computed for the sampled impact locations. The results for each scenario are aggregated into a distribution of potential outcomes that reflect the range of uncertain impact parameters, population densities, and strike probabilities. As an illustration of the utility of the PAIR model, the results are used to address the question of what minimum size asteroid constitutes a threat to the population. To answer this question, complete distributions of results are combined with a hypothetical risk tolerance posture to provide the minimum size, given sets of initial assumptions. Model outputs demonstrate how such questions can be answered and provide a means for interpreting the effect that input assumptions and uncertainty can have on final risk-based decisions. Model results can be used to prioritize investments to gain knowledge in critical areas or, conversely, to identify areas where additional data has little effect on the metrics of interest.

  15. Issues in Value-at-Risk Modeling and Evaluation

    NARCIS (Netherlands)

    J. Daníelsson (Jón); C.G. de Vries (Casper); B.N. Jorgensen (Bjørn); P.F. Christoffersen (Peter); F.X. Diebold (Francis); T. Schuermann (Til); J.A. Lopez (Jose); B. Hirtle (Beverly)

    1998-01-01

    textabstractDiscusses the issues in value-at-risk modeling and evaluation. Value of value at risk; Horizon problems and extreme events in financial risk management; Methods of evaluating value-at-risk estimates.

  16. Multi-hazard risk analysis for management strategies

    Science.gov (United States)

    Kappes, M.; Keiler, M.; Bell, R.; Glade, T.

    2009-04-01

    Risk management is very often operating in a reactive way, responding to an event, instead of proactive starting with risk analysis and building up the whole process of risk evaluation, prevention, event management and regeneration. Since damage and losses from natural hazards raise continuously more and more studies, concepts (e.g. Switzerland or South Tyrol-Bolozano) and software packages (e.g. ARMAGEDOM, HAZUS or RiskScape) are developed to guide, standardize and facilitate the risk analysis. But these approaches focus on different aspects and are mostly closely adapted to the situation (legislation, organization of the administration, specific processes etc.) of the specific country or region. We propose in this study the development of a flexible methodology for multi-hazard risk analysis, identifying the stakeholders and their needs, processes and their characteristics, modeling approaches as well as incoherencies occurring by combining all these different aspects. Based on this concept a flexible software package will be established consisting of ArcGIS as central base and being complemented by various modules for hazard modeling, vulnerability assessment and risk calculation. Not all modules will be developed newly but taken from the current state-of-the-art and connected or integrated into ArcGIS. For this purpose two study sites, Valtellina in Italy and Bacelonnette in France, were chosen and the hazards types debris flows, rockfalls, landslides, avalanches and floods are planned to be included in the tool for a regional multi-hazard risk analysis. Since the central idea of this tool is its flexibility this will only be a first step, in the future further processes and scales can be included and the instrument thus adapted to any study site.

  17. Supplemental Hazard Analysis and Risk Assessment - Hydrotreater

    Energy Technology Data Exchange (ETDEWEB)

    Lowry, Peter P. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Wagner, Katie A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2015-04-01

    A supplemental hazard analysis was conducted and quantitative risk assessment performed in response to an independent review comment received by the Pacific Northwest National Laboratory (PNNL) from the U.S. Department of Energy Pacific Northwest Field Office (PNSO) against the Hydrotreater/Distillation Column Hazard Analysis Report issued in April 2013. The supplemental analysis used the hazardous conditions documented by the previous April 2013 report as a basis. The conditions were screened and grouped for the purpose of identifying whether additional prudent, practical hazard controls could be identified, using a quantitative risk evaluation to assess the adequacy of the controls and establish a lower level of concern for the likelihood of potential serious accidents. Calculations were performed to support conclusions where necessary.

  18. Modeling inputs to computer models used in risk assessment

    International Nuclear Information System (INIS)

    Iman, R.L.

    1987-01-01

    Computer models for various risk assessment applications are closely scrutinized both from the standpoint of questioning the correctness of the underlying mathematical model with respect to the process it is attempting to model and from the standpoint of verifying that the computer model correctly implements the underlying mathematical model. A process that receives less scrutiny, but is nonetheless of equal importance, concerns the individual and joint modeling of the inputs. This modeling effort clearly has a great impact on the credibility of results. Model characteristics are reviewed in this paper that have a direct bearing on the model input process and reasons are given for using probabilities-based modeling with the inputs. The authors also present ways to model distributions for individual inputs and multivariate input structures when dependence and other constraints may be present

  19. Blended Risk Approach in Applying PSA Models to Risk-Based Regulations

    International Nuclear Information System (INIS)

    Dimitrijevic, V. B.; Chapman, J. R.

    1996-01-01

    In this paper, the authors will discuss a modern approach in applying PSA models in risk-based regulation. The Blended Risk Approach is a combination of traditional and probabilistic processes. It is receiving increased attention in different industries in the U. S. and abroad. The use of the deterministic regulations and standards provides a proven and well understood basis on which to assess and communicate the impact of change to plant design and operation. Incorporation of traditional values into risk evaluation is working very well in the blended approach. This approach is very application specific. It includes multiple risk attributes, qualitative risk analysis, and basic deterministic principles. In blending deterministic and probabilistic principles, this approach ensures that the objectives of the traditional defense-in-depth concept are not compromised and the design basis of the plant is explicitly considered. (author)

  20. Revenue Risk Modelling and Assessment on BOT Highway Project

    Science.gov (United States)

    Novianti, T.; Setyawan, H. Y.

    2018-01-01

    The infrastructure project which is considered as a public-private partnership approach under BOT (Build-Operate-Transfer) arrangement, such as a highway, is risky. Therefore, assessment on risk factors is essential as the project have a concession period and is influenced by macroeconomic factors and consensus period. In this study, pre-construction risks of a highway were examined by using a Delphi method to create a space for offline expert discussions; a fault tree analysis to map intuition of experts and to create a model from the underlying risk events; a fuzzy logic to interpret the linguistic data of risk models. The loss of revenue for risk tariff, traffic volume, force majeure, and income were then measured. The results showed that the loss of revenue caused by the risk tariff was 10.5% of the normal total revenue. The loss of revenue caused by the risk of traffic volume was 21.0% of total revenue. The loss of revenue caused by the force majeure was 12.2% of the normal income. The loss of income caused by the non-revenue events was 6.9% of the normal revenue. It was also found that the volume of traffic was the major risk of a highway project because it related to customer preferences.

  1. Mechanistic modeling for mammography screening risks

    International Nuclear Information System (INIS)

    Bijwaard, Harmen

    2008-01-01

    Full text: Western populations show a very high incidence of breast cancer and in many countries mammography screening programs have been set up for the early detection of these cancers. Through these programs large numbers of women (in the Netherlands, 700.000 per year) are exposed to low but not insignificant X-ray doses. ICRP based risk estimates indicate that the number of breast cancer casualties due to mammography screening can be as high as 50 in the Netherlands per year. The number of lives saved is estimated to be much higher, but for an accurate calculation of the benefits of screening a better estimate of these risks is indispensable. Here it is attempted to better quantify the radiological risks of mammography screening through the application of a biologically based model for breast tumor induction by X-rays. The model is applied to data obtained from the National Institutes of Health in the U.S. These concern epidemiological data of female TB patients who received high X-ray breast doses in the period 1930-1950 through frequent fluoroscopy of their lungs. The mechanistic model that is used to describe the increased breast cancer incidence is based on an earlier study by Moolgavkar et al. (1980), in which the natural background incidence of breast cancer was modeled. The model allows for a more sophisticated extrapolation of risks to the low dose X-ray exposures that are common in mammography screening and to the higher ages that are usually involved. Furthermore, it allows for risk transfer to other (non-western) populations. The results have implications for decisions on the frequency of screening, the number of mammograms taken at each screening, minimum and maximum ages for screening and the transfer to digital equipment. (author)

  2. Risk of the Maritime Supply Chain System Based on Interpretative Structural Model

    OpenAIRE

    Jiang He; Xiong Wei; Cao Yonghui

    2017-01-01

    Marine transportation is the most important transport mode of in the international trade, but the maritime supply chain is facing with many risks. At present, most of the researches on the risk of the maritime supply chain focus on the risk identification and risk management, and barely carry on the quantitative analysis of the logical structure of each influencing factor. This paper uses the interpretative structure model to analysis the maritime supply chain risk system. On the basis of com...

  3. Risk and safety analysis of nuclear systems

    CERN Document Server

    Lee, John C

    2011-01-01

    The book has been developed in conjunction with NERS 462, a course offered every year to seniors and graduate students in the University of Michigan NERS program. The first half of the book covers the principles of risk analysis, the techniques used to develop and update a reliability data base, the reliability of multi-component systems, Markov methods used to analyze the unavailability of systems with repairs, fault trees and event trees used in probabilistic risk assessments (PRAs), and failure modes of systems. All of this material is general enough that it could be used in non-nuclear a

  4. An Analysis of the Relationship between Casualty Risk Per Crash and Vehicle Mass and Footprint for Model Year 2000-2007 Light-Duty Vehicles

    Energy Technology Data Exchange (ETDEWEB)

    Wenzel, Tom [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Environmental Energy Technologies Division. Building Technology and Urban Systems Dept.

    2012-08-01

    NHTSA recently completed a logistic regression analysis (Kahane 2012) updating its 2003 and 2010 studies of the relationship between vehicle mass and US fatality risk per vehicle mile traveled (VMT). The new study updates the previous analyses in several ways: updated FARS data for 2002 to 2008 involving MY00 to MY07 vehicles are used; induced exposure data from police reported crashes in several additional states are added; a new vehicle category for car-based crossover utility vehicles (CUVs) and minivans is created; crashes with other light-duty vehicles are divided into two groups based on the crash partner vehicle’s weight, and a category for all other fatal crashes is added; and new control variables for new safety technologies and designs, such as electronic stability controls (ESC), side airbags, and methods to meet voluntary agreement to improve light truck compatibility with cars, are included.

  5. Risk management model in road transport systems

    Science.gov (United States)

    Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.

    2016-08-01

    The article presents the results of a study of road safety indicators that influence the development and operation of the transport system. Road safety is considered as a continuous process of risk management. Authors constructed a model that relates the social risks of a major road safety indicator - the level of motorization. The model gives a fairly accurate assessment of the level of social risk for any given level of motorization. Authors calculated the dependence of the level of socio-economic costs of accidents and injured people in them. The applicability of the concept of socio-economic damage is caused by the presence of a linear relationship between the natural and economic indicators damage from accidents. The optimization of social risk is reduced to finding the extremum of the objective function that characterizes the economic effect of the implementation of measures to improve safety. The calculations make it possible to maximize the net present value, depending on the costs of improving road safety, taking into account socio-economic damage caused by accidents. The proposed econometric models make it possible to quantify the efficiency of the transportation system, allow to simulate the change in road safety indicators.

  6. A mathematical model for environmental risk assessment in manufacturing industry

    Institute of Scientific and Technical Information of China (English)

    何莉萍; 徐盛明; 陈大川; 党创寅

    2002-01-01

    Environmental conscious manufacturing has become an important issue in industry because of market pressure and environmental regulations. An environmental risk assessment model was developed based on the network analytic method and fuzzy set theory. The "interval analysis method" was applied to deal with the on-site monitoring data as basic information for assessment. In addition, the fuzzy set theory was employed to allow uncertain, interactive and dynamic information to be effectively incorporated into the environmental risk assessment. This model is a simple, practical and effective tool for evaluating the environmental risk of manufacturing industry and for analyzing the relative impacts of emission wastes, which are hazardous to both human and ecosystem health. Furthermore, the model is considered useful for design engineers and decision-maker to design and select processes when the costs, environmental impacts and performances of a product are taken into consideration.

  7. Risk and sensitivity analysis in relation to external events

    International Nuclear Information System (INIS)

    Alzbutas, R.; Urbonas, R.; Augutis, J.

    2001-01-01

    This paper presents risk and sensitivity analysis of external events impacts on the safe operation in general and in particular the Ignalina Nuclear Power Plant safety systems. Analysis is based on the deterministic and probabilistic assumptions and assessment of the external hazards. The real statistic data are used as well as initial external event simulation. The preliminary screening criteria are applied. The analysis of external event impact on the NPP safe operation, assessment of the event occurrence, sensitivity analysis, and recommendations for safety improvements are performed for investigated external hazards. Such events as aircraft crash, extreme rains and winds, forest fire and flying parts of the turbine are analysed. The models are developed and probabilities are calculated. As an example for sensitivity analysis the model of aircraft impact is presented. The sensitivity analysis takes into account the uncertainty features raised by external event and its model. Even in case when the external events analysis show rather limited danger, the sensitivity analysis can determine the highest influence causes. These possible variations in future can be significant for safety level and risk based decisions. Calculations show that external events cannot significantly influence the safety level of the Ignalina NPP operation, however the events occurrence and propagation can be sufficiently uncertain.(author)

  8. Investment appraisal using quantitative risk analysis.

    Science.gov (United States)

    Johansson, Henrik

    2002-07-01

    Investment appraisal concerned with investments in fire safety systems is discussed. Particular attention is directed at evaluating, in terms of the Bayesian decision theory, the risk reduction that investment in a fire safety system involves. It is shown how the monetary value of the change from a building design without any specific fire protection system to one including such a system can be estimated by use of quantitative risk analysis, the results of which are expressed in terms of a Risk-adjusted net present value. This represents the intrinsic monetary value of investing in the fire safety system. The method suggested is exemplified by a case study performed in an Avesta Sheffield factory.

  9. Operations and Modeling Analysis

    Science.gov (United States)

    Ebeling, Charles

    2005-01-01

    The Reliability and Maintainability Analysis Tool (RMAT) provides NASA the capability to estimate reliability and maintainability (R&M) parameters and operational support requirements for proposed space vehicles based upon relationships established from both aircraft and Shuttle R&M data. RMAT has matured both in its underlying database and in its level of sophistication in extrapolating this historical data to satisfy proposed mission requirements, maintenance concepts and policies, and type of vehicle (i.e. ranging from aircraft like to shuttle like). However, a companion analyses tool, the Logistics Cost Model (LCM) has not reached the same level of maturity as RMAT due, in large part, to nonexistent or outdated cost estimating relationships and underlying cost databases, and it's almost exclusive dependence on Shuttle operations and logistics cost input parameters. As a result, the full capability of the RMAT/LCM suite of analysis tools to take a conceptual vehicle and derive its operations and support requirements along with the resulting operating and support costs has not been realized.

  10. Construction of Site Risk Model using Individual Unit Risk Model in a NPP Site

    Energy Technology Data Exchange (ETDEWEB)

    Lim, Ho Gon; Han, Sang Hoon [KAERI, Daejeon (Korea, Republic of)

    2016-05-15

    Since Fukushima accident, strong needs to estimate site risk has been increased to identify the possibility of re-occurrence of such a tremendous disaster and prevent such a disaster. Especially, in a site which has large fleet of nuclear power plants, reliable site risk assessment is very emergent to confirm the safety. In Korea, there are several nuclear power plant site which have more than 6 NPPs. In general, risk model of a NPP in terms of PSA is very complicated and furthermore, it is expected that the site risk model is more complex than that. In this paper, the method for constructing site risk model is proposed by using individual unit risk model. Procedure for the development of site damage (risk) model was proposed in the present paper. Since the site damage model is complicated in the sense of the scale of the system and dependency of the components of the system, conventional method may not be applicable in many side of the problem.

  11. Value at Risk models for Energy Risk Management

    OpenAIRE

    Novák, Martin

    2010-01-01

    The main focus of this thesis lies on description of Risk Management in context of Energy Trading. The paper will predominantly discuss Value at Risk and its modifications as a main overall indicator of Energy Risk.

  12. Identification and control of factors influencing flow-accelerated corrosion in HRSG units using computational fluid dynamics modeling, full-scale air flow testing, and risk analysis

    Energy Technology Data Exchange (ETDEWEB)

    Pietrowski, Ronald L. [The Consolidated Edison Company of New York, Inc., New York, NY (United States)

    2010-11-15

    In 2009, Consolidated Edison's East River heat recovery steam generator units 10 and 20 both experienced economizer tube failures which forced each unit offline. Extensive inspections indicated that the primary failure mechanism was flow-accelerated corrosion (FAC). The inspections revealed evidence of active FAC in all 7 of the economizer modules, with the most advanced stages of degradation being noted in center modules. Analysis determined that various factors were influencing and enabling this corrosion mechanism. Computational fluid dynamics and full-scale air flow testing showed very turbulent feedwater flow prevalent in areas of the modules corresponding with the pattern of FAC damage observed through inspection. It also identified preferential flow paths, with higher flow velocities, in certain tubes directly under the inlet nozzles. A FAC risk analysis identified more general susceptibility to FAC in the areas experiencing damage due to feedwater pH, operating temperatures, local shear fluid forces, and the chemical composition of the original materials of construction. These, in combination, were the primary root causes of the failures. Corrective actions were identified, analyzed, and implemented, resulting in equipment replacements and repairs. (orig.)

  13. Dynamic risk analysis using bow-tie approach

    International Nuclear Information System (INIS)

    Khakzad, Nima; Khan, Faisal; Amyotte, Paul

    2012-01-01

    Accident probability estimation is a common and central step to all quantitative risk assessment methods. Among many techniques available, bow-tie model (BT) is very popular because it represent the accident scenario altogether including causes and consequences. However, it suffers a static structure limiting its application in real-time monitoring and probability updating which are key factors in dynamic risk analysis. The present work is focused on using BT approach in a dynamic environment in which the occurrence probability of accident consequences changes. In this method, on one hand, failure probability of primary events of BT, leading to the top event, are developed using physical reliability models, and constantly revised as physical parameters (e.g., pressure, velocity, dimension, etc) change. And, on the other hand, the failure probability of safety barriers of the BT are periodically updated using Bayes’ theorem as new information becomes available over time. Finally, the resulting, updated BT is used to estimate the posterior probability of the consequences which in turn results in an updated risk profile. - Highlights: ► A methodology is proposed to make bow-tie method adapted for dynamic risk analysis. ► Physical reliability models are used to revise the top event. ► Bayes’ theorem is used to update the probability of safety barriers. ► The number of accidents in sequential time intervals is used to form likelihood function. ► The risk profile is updated for varying physical parameters and for different times.

  14. Quantitative risk analysis preoperational of gas pipeline

    Energy Technology Data Exchange (ETDEWEB)

    Manfredi, Carlos; Bispo, Gustavo G.; Esteves, Alvaro [Gie S.A., Buenos Aires (Argentina)

    2009-07-01

    The purpose of this analysis is to predict how it can be affected the individual risk and the public's general security due to the operation of a gas pipeline. In case that the single or social risks are considered intolerable, compared with the international standards, to be recommended measures of mitigation of the risk associated to the operation until levels that can be considered compatible with the best practices in the industry. The quantitative risk analysis calculates the probability of occurrence of an event based on the frequency of occurrence of the same one and it requires a complex mathematical treatment. The present work has as objective to develop a calculation methodology based on the previously mentioned publication. This calculation methodology is centered in defining the frequencies of occurrence of events, according to representative database of each case in study. Besides, it settles down the consequences particularly according to the considerations of each area and the different possibilities of interferences with the gas pipeline in study. For each one of the interferences a typical curve of ignition probabilities is developed in function from the distance to the pipe. (author)

  15. Decision Model on Financing a Project Using Knowledge about Risk Areas

    OpenAIRE

    Ioana POPOVICI; Emil SCARLAT; Francesco RIZZO

    2011-01-01

    The research presents an alternative to the classical method of measuring financial risk in funding a project. The goal of the model described in the paper implies identifying "risky areas" within the financial balance of the project. The model analysis the financial risk behavior studied along four scenarios by varying only the cost of financing source used according to the specific type of funding. The model introduces the time factor into the analysis of financial risk due to the specific ...

  16. Zero risk fuel fabrication: a systems analysis

    International Nuclear Information System (INIS)

    1979-01-01

    Zero risk is a concept used to ensure that system requirements are developed through a systems approach such that the choice(s) among alternatives represents the balanced viewpoints of performance, achievability and risk. Requirements to ensure characteristics such as stringent accountability, low personnel exposure and etc. are needed to guide the development of component and subsystems for future LMFBR fuel supply systems. To establish a consistent and objective set of requirements, RF and M-TMC has initiated a systems requirements analysis activity. This activity pivots on judgement and experience provided by a Task Force representing industrial companies engaged in fuel fabrication in licensed facilities. The Task Force members are listed in Appendix A. Input developed by this group is presented as a starting point for the systems requirements analysis

  17. Crop insurance: Risks and models of insurance

    Directory of Open Access Journals (Sweden)

    Čolović Vladimir

    2014-01-01

    Full Text Available The issue of crop protection is very important because of a variety of risks that could cause difficult consequences. One type of risk protection is insurance. The author in the paper states various models of insurance in some EU countries and the systems of subsidizing of insurance premiums by state. The author also gives a picture of crop insurance in the U.S., noting that in this country pays great attention to this matter. As for crop insurance in Serbia, it is not at a high level. The main problem with crop insurance is not only the risks but also the way of protection through insurance. The basic question that arises not only in the EU is the question is who will insure and protect crops. There are three possibilities: insurance companies under state control, insurance companies that are public-private partnerships or private insurance companies on a purely commercial basis.

  18. Multi-hazard risk analysis related to hurricanes

    Science.gov (United States)

    Lin, Ning

    Hurricanes present major hazards to the United States. Associated with extreme winds, heavy rainfall, and storm surge, landfalling hurricanes often cause enormous structural damage to coastal regions. Hurricane damage risk assessment provides the basis for loss mitigation and related policy-making. Current hurricane risk models, however, often oversimplify the complex processes of hurricane damage. This dissertation aims to improve existing hurricane risk assessment methodology by coherently modeling the spatial-temporal processes of storm landfall, hazards, and damage. Numerical modeling technologies are used to investigate the multiplicity of hazards associated with landfalling hurricanes. The application and effectiveness of current weather forecasting technologies to predict hurricane hazards is investigated. In particular, the Weather Research and Forecasting model (WRF), with Geophysical Fluid Dynamics Laboratory (GFDL)'s hurricane initialization scheme, is applied to the simulation of the wind and rainfall environment during hurricane landfall. The WRF model is further coupled with the Advanced Circulation (AD-CIRC) model to simulate storm surge in coastal regions. A case study examines the multiple hazards associated with Hurricane Isabel (2003). Also, a risk assessment methodology is developed to estimate the probability distribution of hurricane storm surge heights along the coast, particularly for data-scarce regions, such as New York City. This methodology makes use of relatively simple models, specifically a statistical/deterministic hurricane model and the Sea, Lake and Overland Surges from Hurricanes (SLOSH) model, to simulate large numbers of synthetic surge events, and conducts statistical analysis. The estimation of hurricane landfall probability and hazards are combined with structural vulnerability models to estimate hurricane damage risk. Wind-induced damage mechanisms are extensively studied. An innovative windborne debris risk model is

  19. Risk Analysis of Accounting Information System Infrastructure

    OpenAIRE

    MIHALACHE, Arsenie-Samoil

    2011-01-01

    National economy and security are fully dependent on information technology and infrastructure. At the core of the information infrastructure society relies on, we have the Internet, a system designed initially as a scientists’ forum for unclassified research. The use of communication networks and systems may lead to hazardous situations that generate undesirable effects such as communication systems breakdown, loss of data or taking the wrong decisions. The paper studies the risk analysis of...

  20. Risk analysis of external radiation therapy

    International Nuclear Information System (INIS)

    Arvidsson, Marcus

    2011-09-01

    External radiation therapy is carried out via a complex treatment process in which many different groups of staff work together. Much of the work is dependent on and in collaboration with advanced technical equipment. The purpose of the research task has been to identify a process for external radiation therapy and to identify, test and analyze a suitable method for performing risk analysis of external radiation therapy

  1. Risk and value analysis of SETI

    Science.gov (United States)

    Billingham, J.

    1990-01-01

    This paper attempts to apply a traditional risk and value analysis to the Search for Extraterrestrial Intelligence--SETI. In view of the difficulties of assessing the probability of success, a comparison is made between SETI and a previous search for extraterrestrial life, the biological component of Project Viking. Our application of simple Utility Theory, given some reasonable assumptions, suggests that SETI is at least as worthwhile as the biological experiment on Viking.

  2. The prostate cancer risk stratification (ProCaRS) project: Recursive partitioning risk stratification analysis

    International Nuclear Information System (INIS)

    Rodrigues, George; Lukka, Himu; Warde, Padraig; Brundage, Michael; Souhami, Luis; Crook, Juanita; Cury, Fabio; Catton, Charles; Mok, Gary; Martin, Andre-Guy; Vigneault, Eric; Morris, Jim; Warner, Andrew; Gonzalez Maldonado, Sandra; Pickles, Tom

    2013-01-01

    Background: The Genitourinary Radiation Oncologists of Canada (GUROC) published a three-group risk stratification (RS) system to assist prostate cancer decision-making in 2001. The objective of this project is to use the ProCaRS database to statistically model the predictive accuracy and clinical utility of a proposed new multi-group RS schema. Methods: The RS analyses utilized the ProCaRS database that consists of 7974 patients from four Canadian institutions. Recursive partitioning analysis (RPA) was utilized to explore the sub-stratification of groups defined by the existing three-group GUROC scheme. 10-fold cross-validated C-indices and the Net Reclassification Index were both used to assess multivariable models and compare the predictive accuracy of existing and proposed RS systems, respectively. Results: The recursive partitioning analysis has suggested that the existing GUROC classification system could be altered to accommodate as many as six separate and statistical unique groups based on differences in BFFS (C-index 0.67 and AUC 0.70). GUROC low-risk patients would be divided into new favorable-low and low-risk groups based on PSA ⩽6 and PSA >6. GUROC intermediate-risk patients can be subclassified into low-intermediate and high-intermediate groups. GUROC high-intermediate-risk is defined as existing GUROC intermediate-risk with PSA >=10 AND either T2b/c disease or T1T2a disease with Gleason 7. GUROC high-risk patients would be subclassified into an additional extreme-risk group (GUROC high-risk AND (positive cores ⩾87.5% OR PSA >30). Conclusions: Proposed RS subcategories have been identified by a RPA of the ProCaRS database

  3. Applied decision analysis and risk evaluation

    International Nuclear Information System (INIS)

    Ferse, W.; Kruber, S.

    1995-01-01

    During 1994 the workgroup 'Applied Decision Analysis and Risk Evaluation; continued the work on the knowledge based decision support system XUMA-GEFA for the evaluation of the hazard potential of contaminated sites. Additionally a new research direction was started which aims at the support of a later stage of the treatment of contaminated sites: The clean-up decision. For the support of decisions arising at this stage, the methods of decision analysis will be used. Computational aids for evaluation and decision support were implemented and a case study at a waste disposal site in Saxony which turns out to be a danger for the surrounding groundwater ressource was initiated. (orig.)

  4. Risk factor analysis of equine strongyle resistance to anthelmintics

    Directory of Open Access Journals (Sweden)

    G. Sallé

    2017-12-01

    Full Text Available Intestinal strongyles are the most problematic endoparasites of equids as a result of their wide distribution and the spread of resistant isolates throughout the world. While abundant literature can be found on the extent of anthelmintic resistance across continents, empirical knowledge about associated risk factors is missing. This study brought together results from anthelmintic efficacy testing and risk factor analysis to provide evidence-based guidelines in the field. It involved 688 horses from 39 French horse farms and riding schools to both estimate Faecal Egg Count Reduction (FECR after anthelmintic treatment and to interview farm and riding school managers about their practices. Risk factors associated with reduced anthelmintic efficacy in equine strongyles were estimated across drugs using a marginal modelling approach. Results demonstrated ivermectin efficacy (96.3% ± 14.5% FECR, the inefficacy of fenbendazole (42.8% ± 33.4% FECR and an intermediate profile for pyrantel (90.3% ± 19.6% FECR. Risk factor analysis provided support to advocate for FEC-based treatment regimens combined with individual anthelmintic dosage and the enforcement of tighter biosecurity around horse introduction. The combination of these measures resulted in a decreased risk of drug resistance (relative risk of 0.57, p = 0.02. Premises falling under this typology also relied more on their veterinarians suggesting practitionners play an important role in the sustainability of anthelmintic usage. Similarly, drug resistance risk was halved in premises with frequent pasture rotation and with stocking rate below five horses/ha (relative risk of 0.53, p < 0.01. This is the first empirical risk factor analysis for anthelmintic resistance in equids. Our findings should guide the implementation of more sustained strongyle management in the field. Keywords: Horse, Nematode, Anthelmintic resistance, Strongyle, Cyathostomin

  5. Improvement of the projection models for radiogenic cancer risk

    International Nuclear Information System (INIS)

    Tong Jian

    2005-01-01

    Calculations of radiogenic cancer risk are based on the risk projection models for specific cancer sites. Improvement has been made for the parameters used in the previous models including introductions of mortality and morbidity risk coefficients, and age-/ gender-specific risk coefficients. These coefficients have been applied to calculate the radiogenic cancer risks for specific organs and radionuclides under different exposure scenarios. (authors)

  6. Risco privado em infra-estrutura pública: uma análise quantitativa de risco como ferramenta de modelagem de contratos Private risk in public infrastructure: a quantitative risk analysis as a contract modeling tool

    Directory of Open Access Journals (Sweden)

    Luiz E. T. Brandão

    2007-12-01

    Full Text Available Parcerias público-privadas (PPP são arranjos contratuais onde o governo assume compromissos futuros por meio de garantias e opções. São alternativas para aumentar a eficiência do Estado por uma alocação mais eficiente de incentivos e riscos. No entanto, a determinação do nível ótimo de garantias e a própria alocação de riscos são geralmente realizadas de forma subjetiva, podendo levar o governo a ter que assumir passivos significativos. Este artigo propõe um modelo de valoração quantitativa de garantias governamentais em projetos de PPP por meio da metodologia das opções reais, e este modelo é aplicado a um projeto de concessão rodoviária. Os autores analisam o impacto de diversos níveis de garantia de receita sobre o valor e risco do projeto, bem como o valor esperado do desembolso futuro do governo em cada uma das situações, concluindo que é possível ao poder público determinar o nível ótimo de garantia em função do grau de redução de risco desejado, e que o desenho e a modelagem contratual de projetos de PPP podem se beneficiar de ferramentas quantitativas aqui apresentadas.Public private partnerships (PPP are contractual arrangements in which the government assumes future obligations by providing project guarantees. They are considered a way of increasing government efficiency through a more efficient allocation of risks and incentives. On the other hand, the assessment and determination the optimal level of these guarantees is usually subjective, exposing the government to potentially high future liabilities. This article proposes a quantitative model for the evaluation of government guarantees in PPP projects under the real options approach, and applies this model to a toll highway concession with a minimum revenue guarantee. It studies the impact of different guarantee levels on the value and the risk of the project, as well as the expected level of future cash payments to be made by the government in

  7. Risk assessment and remedial policy evaluation using predictive modeling

    International Nuclear Information System (INIS)

    Linkov, L.; Schell, W.R.

    1996-01-01

    As a result of nuclear industry operation and accidents, large areas of natural ecosystems have been contaminated by radionuclides and toxic metals. Extensive societal pressure has been exerted to decrease the radiation dose to the population and to the environment. Thus, in making abatement and remediation policy decisions, not only economic costs but also human and environmental risk assessments are desired. This paper introduces a general framework for risk assessment and remedial policy evaluation using predictive modeling. Ecological risk assessment requires evaluation of the radionuclide distribution in ecosystems. The FORESTPATH model is used for predicting the radionuclide fate in forest compartments after deposition as well as for evaluating the efficiency of remedial policies. Time of intervention and radionuclide deposition profile was predicted as being crucial for the remediation efficiency. Risk assessment conducted for a critical group of forest users in Belarus shows that consumption of forest products (berries and mushrooms) leads to about 0.004% risk of a fatal cancer annually. Cost-benefit analysis for forest cleanup suggests that complete removal of organic layer is too expensive for application in Belarus and a better methodology is required. In conclusion, FORESTPATH modeling framework could have wide applications in environmental remediation of radionuclides and toxic metals as well as in dose reconstruction and, risk-assessment

  8. Physics-based Entry, Descent and Landing Risk Model

    Science.gov (United States)

    Gee, Ken; Huynh, Loc C.; Manning, Ted

    2014-01-01

    A physics-based risk model was developed to assess the risk associated with thermal protection system failures during the entry, descent and landing phase of a manned spacecraft mission. In the model, entry trajectories were computed using a three-degree-of-freedom trajectory tool, the aerothermodynamic heating environment was computed using an engineering-level computational tool and the thermal response of the TPS material was modeled using a one-dimensional thermal response tool. The model was capable of modeling the effect of micrometeoroid and orbital debris impact damage on the TPS thermal response. A Monte Carlo analysis was used to determine the effects of uncertainties in the vehicle state at Entry Interface, aerothermodynamic heating and material properties on the performance of the TPS design. The failure criterion was set as a temperature limit at the bondline between the TPS and the underlying structure. Both direct computation and response surface approaches were used to compute the risk. The model was applied to a generic manned space capsule design. The effect of material property uncertainty and MMOD damage on risk of failure were analyzed. A comparison of the direct computation and response surface approach was undertaken.

  9. Plant and control system reliability and risk model

    International Nuclear Information System (INIS)

    Niemelae, I.M.

    1986-01-01

    A new reliability modelling technique for control systems and plants is demonstrated. It is based on modified boolean algebra and it has been automated into an efficient computer code called RELVEC. The code is useful for getting an overall view of the reliability parameters or for an in-depth reliability analysis, which is essential in risk analysis, where the model must be capable of answering to specific questions like: 'What is the probability of this temperature limiter to provide a false alarm', or 'what is the probability of air pressure in this subsystem to drop below lower limit'. (orig./DG)

  10. Including model uncertainty in risk-informed decision making

    International Nuclear Information System (INIS)

    Reinert, Joshua M.; Apostolakis, George E.

    2006-01-01

    Model uncertainties can have a significant impact on decisions regarding licensing basis changes. We present a methodology to identify basic events in the risk assessment that have the potential to change the decision and are known to have significant model uncertainties. Because we work with basic event probabilities, this methodology is not appropriate for analyzing uncertainties that cause a structural change to the model, such as success criteria. We use the risk achievement worth (RAW) importance measure with respect to both the core damage frequency (CDF) and the change in core damage frequency (ΔCDF) to identify potentially important basic events. We cross-check these with generically important model uncertainties. Then, sensitivity analysis is performed on the basic event probabilities, which are used as a proxy for the model parameters, to determine how much error in these probabilities would need to be present in order to impact the decision. A previously submitted licensing basis change is used as a case study. Analysis using the SAPHIRE program identifies 20 basic events as important, four of which have model uncertainties that have been identified in the literature as generally important. The decision is fairly insensitive to uncertainties in these basic events. In three of these cases, one would need to show that model uncertainties would lead to basic event probabilities that would be between two and four orders of magnitude larger than modeled in the risk assessment before they would become important to the decision. More detailed analysis would be required to determine whether these higher probabilities are reasonable. Methods to perform this analysis from the literature are reviewed and an example is demonstrated using the case study

  11. Safety analysis and risk assessment handbook

    International Nuclear Information System (INIS)

    Peterson, V.L.; Colwell, R.G.; Dickey, R.L.

    1997-01-01

    This Safety Analysis and Risk Assessment Handbook (SARAH) provides guidance to the safety analyst at the Rocky Flats Environmental Technology Site (RFETS) in the preparation of safety analyses and risk assessments. Although the older guidance (the Rocky Flats Risk Assessment Guide) continues to be used for updating the Final Safety Analysis Reports developed in the mid-1980s, this new guidance is used with all new authorization basis documents. With the mission change at RFETS came the need to establish new authorization basis documents for its facilities, whose functions had changed. The methodology and databases for performing the evaluations that support the new authorization basis documents had to be standardized, to avoid the use of different approaches and/or databases for similar accidents in different facilities. This handbook presents this new standardized approach. The handbook begins with a discussion of the requirements of the different types of authorization basis documents and how to choose the one appropriate for the facility to be evaluated. It then walks the analyst through the process of identifying all the potential hazards in the facility, classifying them, and choosing the ones that need to be analyzed further. It then discusses the methods for evaluating accident initiation and progression and covers the basic steps in a safety analysis, including consequence and frequency binning and risk ranking. The handbook lays out standardized approaches for determining the source terms of the various accidents (including airborne release fractions, leakpath factors, etc.), the atmospheric dispersion factors appropriate for Rocky Flats, and the methods for radiological and chemical consequence assessments. The radiological assessments use a radiological open-quotes templateclose quotes, a spreadsheet that incorporates the standard values of parameters, whereas the chemical assessments use the standard codes ARCHIE and ALOHA

  12. Analysis of coastal protection under rising flood risk

    Directory of Open Access Journals (Sweden)

    Megan J. Lickley

    2014-01-01

    Full Text Available Infrastructure located along the U.S. Atlantic and Gulf coasts is exposed to rising risk of flooding from sea level rise, increasing storm surge, and subsidence. In these circumstances coastal management commonly based on 100-year flood maps assuming current climatology is no longer adequate. A dynamic programming cost–benefit analysis is applied to the adaptation decision, illustrated by application to an energy facility in Galveston Bay. Projections of several global climate models provide inputs to estimates of the change in hurricane and storm surge activity as well as the increase in sea level. The projected rise in physical flood risk is combined with estimates of flood damage and protection costs in an analysis of the multi-period nature of adaptation choice. The result is a planning method, using dynamic programming, which is appropriate for investment and abandonment decisions under rising coastal risk.

  13. New challenges on uncertainty propagation assessment of flood risk analysis

    Science.gov (United States)

    Martins, Luciano; Aroca-Jiménez, Estefanía; Bodoque, José M.; Díez-Herrero, Andrés

    2016-04-01

    Natural hazards, such as floods, cause considerable damage to the human life, material and functional assets every year and around the World. Risk assessment procedures has associated a set of uncertainties, mainly of two types: natural, derived from stochastic character inherent in the flood process dynamics; and epistemic, that are associated with lack of knowledge or the bad procedures employed in the study of these processes. There are abundant scientific and technical literature on uncertainties estimation in each step of flood risk analysis (e.g. rainfall estimates, hydraulic modelling variables); but very few experience on the propagation of the uncertainties along the flood risk assessment. Therefore, epistemic uncertainties are the main goal of this work, in particular,understand the extension of the propagation of uncertainties throughout the process, starting with inundability studies until risk analysis, and how far does vary a proper analysis of the risk of flooding. These methodologies, such as Polynomial Chaos Theory (PCT), Method of Moments or Monte Carlo, are used to evaluate different sources of error, such as data records (precipitation gauges, flow gauges...), hydrologic and hydraulic modelling (inundation estimation), socio-demographic data (damage estimation) to evaluate the uncertainties propagation (UP) considered in design flood risk estimation both, in numerical and cartographic expression. In order to consider the total uncertainty and understand what factors are contributed most to the final uncertainty, we used the method of Polynomial Chaos Theory (PCT). It represents an interesting way to handle to inclusion of uncertainty in the modelling and simulation process. PCT allows for the development of a probabilistic model of the system in a deterministic setting. This is done by using random variables and polynomials to handle the effects of uncertainty. Method application results have a better robustness than traditional analysis

  14. Train integrity detection risk analysis based on PRISM

    Science.gov (United States)

    Wen, Yuan

    2018-04-01

    GNSS based Train Integrity Monitoring System (TIMS) is an effective and low-cost detection scheme for train integrity detection. However, as an external auxiliary system of CTCS, GNSS may be influenced by external environments, such as uncertainty of wireless communication channels, which may lead to the failure of communication and positioning. In order to guarantee the reliability and safety of train operation, a risk analysis method of train integrity detection based on PRISM is proposed in this article. First, we analyze the risk factors (in GNSS communication process and the on-board communication process) and model them. Then, we evaluate the performance of the model in PRISM based on the field data. Finally, we discuss how these risk factors influence the train integrity detection process.

  15. Path analysis of risk factors leading to premature birth.

    Science.gov (United States)

    Fields, S J; Livshits, G; Sirotta, L; Merlob, P

    1996-01-01

    The present study tested whether various sociodemographic, anthropometric, behavioral, and medical/physiological factors act in a direct or indirect manner on the risk of prematurity using path analysis on a sample of Israeli births. The path model shows that medical complications, primarily toxemia, chorioammionitis, and a previous low birth weight delivery directly and significantly act on the risk of prematurity as do low maternal pregnancy weight gain and ethnicity. Other medical complications, including chronic hypertension, preclampsia, and placental abruption, although significantly correlated with prematurity, act indirectly on prematurity through toxemia. The model further shows that the commonly accepted sociodemographic, anthropometric, and behavioral risk factors act by modifying the development of medical complications that lead to prematurity as opposed to having a direct effect on premature delivery. © 1996 Wiley-Liss, Inc. Copyright © 1996 Wiley-Liss, Inc.

  16. AGROFOREST SYSTEM INVESTMENT ANALYSIS UNDER RISK

    Directory of Open Access Journals (Sweden)

    Luiz Moreira Coelho Junior

    2008-12-01

    Full Text Available Agroforestry System is the ecological and economical interaction of the use of the land, with the combination ofagriculture, livestock and forest production, in temporary sequence and in a simultaneous way. The studies of investments in projectsassume the existence of risks and uncertainties. An alternative to reduce the risk in the forest investment is the association with theagricultural. This work analyzed the situations of risk of a system agroflorestal. Monte Carlo s method comes from the theory ofsimulations and stands out as a powerful and useful tool to provide a distribution of probabilities for the analysis of decision. A totalof 10,000 interactions of the Net Present Value (VPL, of Internal Rate of Return (TIR and of the Equivalent Periodic Benefit (BPEwere made in order to establish the probability distribution. The results presented 78.65% of chance of VPL being US$ 1,410.00;77.56% of chance of TIR being 36.36%, and; 75.39% of chance of BPE being US$ 309.70; the agroforestry system presented lowinvestment risk; and the livestock is the main product of the agrossilvopastoril system, followed by charcoal.

  17. Risk factors for deep vein thrombosis and pulmonary embolism after traumatic injury: A competing risks analysis.

    Science.gov (United States)

    Van Gent, Jan-Michael; Calvo, Richard Yee; Zander, Ashley L; Olson, Erik J; Sise, C Beth; Sise, Michael J; Shackford, Steven R

    2017-12-01

    Venous thromboembolism, including deep vein thrombosis (DVT) and pulmonary embolism (PE), is typically reported as a composite measure of the quality of trauma center care. Given that recent data suggesting postinjury DVT and PE are distinct clinical processes, a better understanding may result from analyzing them as independent, competing events. Using competing risks analysis, we evaluated our hypothesis that the risk factors and timing of postinjury DVT and PE are different. We examined all adult trauma patients admitted to our Level I trauma center from July 2006 to December 2011 who received at least one surveillance duplex ultrasound of the lower extremities and who were at high risk or greater for DVT. Outcomes included DVT and PE events, and time-to-event from admission. We used competing risks analysis to evaluate risk factors for DVT while accounting for PE as a competing event, and vice versa. Of 2,370 patients, 265 (11.2%) had at least one venous thromboembolism event, 235 DVT only, 19 PE only, 11 DVT and PE. Within 2 days of admission, 38% of DVT cases had occurred compared with 26% of PE. Competing risks modeling of DVT as primary event identified older age, severe injury (Injury Severity Score, ≥ 15), mechanical ventilation longer than 4 days, active cancer, history of DVT or PE, major venous repair, male sex, and prophylactic enoxaparin and prophylactic heparin as associated risk factors. Modeling of PE as the primary event showed younger age, nonsevere injury (Injury Severity Score, risk factors for PE and DVT after injury were different, suggesting that they are clinically distinct events that merit independent consideration. Many DVT events occurred early despite prophylaxis, bringing into question the preventability of postinjury DVT. We recommend trauma center quality reporting program measures be revised to account for DVT and PE as unique events. Epidemiologic, level III.

  18. New risk metrics and mathematical tools for risk analysis: Current and future challenges

    International Nuclear Information System (INIS)

    Skandamis, Panagiotis N.; Andritsos, Nikolaos; Psomas, Antonios; Paramythiotis, Spyridon

    2015-01-01

    The current status of the food safety supply world wide, has led Food and Agriculture Organization (FAO) and World Health Organization (WHO) to establishing Risk Analysis as the single framework for building food safety control programs. A series of guidelines and reports that detail out the various steps in Risk Analysis, namely Risk Management, Risk Assessment and Risk Communication is available. The Risk Analysis approach enables integration between operational food management systems, such as Hazard Analysis Critical Control Points, public health and governmental decisions. To do that, a series of new Risk Metrics has been established as follows: i) the Appropriate Level of Protection (ALOP), which indicates the maximum numbers of illnesses in a population per annum, defined by quantitative risk assessments, and used to establish; ii) Food Safety Objective (FSO), which sets the maximum frequency and/or concentration of a hazard in a food at the time of consumption that provides or contributes to the ALOP. Given that ALOP is rather a metric of the public health tolerable burden (it addresses the total ‘failure’ that may be handled at a national level), it is difficult to be interpreted into control measures applied at the manufacturing level. Thus, a series of specific objectives and criteria for performance of individual processes and products have been established, all of them assisting in the achievement of FSO and hence, ALOP. In order to achieve FSO, tools quantifying the effect of processes and intrinsic properties of foods on survival and growth of pathogens are essential. In this context, predictive microbiology and risk assessment have offered an important assistance to Food Safety Management. Predictive modelling is the basis of exposure assessment and the development of stochastic and kinetic models, which are also available in the form of Web-based applications, e.g., COMBASE and Microbial Responses Viewer), or introduced into user

  19. New risk metrics and mathematical tools for risk analysis: Current and future challenges

    Energy Technology Data Exchange (ETDEWEB)

    Skandamis, Panagiotis N., E-mail: pskan@aua.gr; Andritsos, Nikolaos, E-mail: pskan@aua.gr; Psomas, Antonios, E-mail: pskan@aua.gr; Paramythiotis, Spyridon, E-mail: pskan@aua.gr [Laboratory of Food Quality Control and Hygiene, Department of Food Science and Technology, Agricultural University of Athens, Iera Odos 75, 118 55, Athens (Greece)

    2015-01-22

    The current status of the food safety supply world wide, has led Food and Agriculture Organization (FAO) and World Health Organization (WHO) to establishing Risk Analysis as the single framework for building food safety control programs. A series of guidelines and reports that detail out the various steps in Risk Analysis, namely Risk Management, Risk Assessment and Risk Communication is available. The Risk Analysis approach enables integration between operational food management systems, such as Hazard Analysis Critical Control Points, public health and governmental decisions. To do that, a series of new Risk Metrics has been established as follows: i) the Appropriate Level of Protection (ALOP), which indicates the maximum numbers of illnesses in a population per annum, defined by quantitative risk assessments, and used to establish; ii) Food Safety Objective (FSO), which sets the maximum frequency and/or concentration of a hazard in a food at the time of consumption that provides or contributes to the ALOP. Given that ALOP is rather a metric of the public health tolerable burden (it addresses the total ‘failure’ that may be handled at a national level), it is difficult to be interpreted into control measures applied at the manufacturing level. Thus, a series of specific objectives and criteria for performance of individual processes and products have been established, all of them assisting in the achievement of FSO and hence, ALOP. In order to achieve FSO, tools quantifying the effect of processes and intrinsic properties of foods on survival and growth of pathogens are essential. In this context, predictive microbiology and risk assessment have offered an important assistance to Food Safety Management. Predictive modelling is the basis of exposure assessment and the development of stochastic and kinetic models, which are also available in the form of Web-based applications, e.g., COMBASE and Microbial Responses Viewer), or introduced into user

  20. New risk metrics and mathematical tools for risk analysis: Current and future challenges

    Science.gov (United States)

    Skandamis, Panagiotis N.; Andritsos, Nikolaos; Psomas, Antonios; Paramythiotis, Spyridon

    2015-01-01

    The current status of the food safety supply world wide, has led Food and Agriculture Organization (FAO) and World Health Organization (WHO) to establishing Risk Analysis as the single framework for building food safety control programs. A series of guidelines and reports that detail out the various steps in Risk Analysis, namely Risk Management, Risk Assessment and Risk Communication is available. The Risk Analysis approach enables integration between operational food management systems, such as Hazard Analysis Critical Control Points, public health and governmental decisions. To do that, a series of new Risk Metrics has been established as follows: i) the Appropriate Level of Protection (ALOP), which indicates the maximum numbers of illnesses in a population per annum, defined by quantitative risk assessments, and used to establish; ii) Food Safety Objective (FSO), which sets the maximum frequency and/or concentration of a hazard in a food at the time of consumption that provides or contributes to the ALOP. Given that ALOP is rather a metric of the public health tolerable burden (it addresses the total `failure' that may be handled at a national level), it is difficult to be interpreted into control measures applied at the manufacturing level. Thus, a series of specific objectives and criteria for performance of individual processes and products have been established, all of them assisting in the achievement of FSO and hence, ALOP. In order to achieve FSO, tools quantifying the effect of processes and intrinsic properties of foods on survival and growth of pathogens are essential. In this context, predictive microbiology and risk assessment have offered an important assistance to Food Safety Management. Predictive modelling is the basis of exposure assessment and the development of stochastic and kinetic models, which are also available in the form of Web-based applications, e.g., COMBASE and Microbial Responses Viewer), or introduced into user-friendly softwares

  1. A Big Data Analysis Approach for Rail Failure Risk Assessment.

    Science.gov (United States)

    Jamshidi, Ali; Faghih-Roohi, Shahrzad; Hajizadeh, Siamak; Núñez, Alfredo; Babuska, Robert; Dollevoet, Rolf; Li, Zili; De Schutter, Bart

    2017-08-01

    Railway infrastructure monitoring is a vital task to ensure rail transportation safety. A rail failure could result in not only a considerable impact on train delays and maintenance costs, but also on safety of passengers. In this article, the aim is to assess the risk of a rail failure by analyzing a type of rail surface defect called squats that are detected automatically among the huge number of records from video cameras. We propose an image processing approach for automatic detection of squats, especially severe types that are prone to rail breaks. We measure the visual length of the squats and use them to model the failure risk. For the assessment of the rail failure risk, we estimate the probability of rail failure based on the growth of squats. Moreover, we perform severity and crack growth analyses to consider the impact of rail traffic loads on defects in three different growth scenarios. The failure risk estimations are provided for several samples of squats with different crack growth lengths on a busy rail track of the Dutch railway network. The results illustrate the practicality and efficiency of the proposed approach. © 2017 The Authors Risk Analysis published by Wiley Periodicals, Inc. on behalf of Society for Risk Analysis.

  2. Forewarning model for water pollution risk based on Bayes theory.

    Science.gov (United States)

    Zhao, Jun; Jin, Juliang; Guo, Qizhong; Chen, Yaqian; Lu, Mengxiong; Tinoco, Luis

    2014-02-01

    In order to reduce the losses by water pollution, forewarning model for water pollution risk based on Bayes theory was studied. This model is built upon risk indexes in complex systems, proceeding from the whole structure and its components. In this study, the principal components analysis is used to screen out index systems. Hydrological model is employed to simulate index value according to the prediction principle. Bayes theory is adopted to obtain posterior distribution by prior distribution with sample information which can make samples' features preferably reflect and represent the totals to some extent. Forewarning level is judged on the maximum probability rule, and then local conditions for proposing management strategies that will have the effect of transforming heavy warnings to a lesser degree. This study takes Taihu Basin as an example. After forewarning model application and vertification for water pollution risk from 2000 to 2009 between the actual and simulated data, forewarning level in 2010 is given as a severe warning, which is well coincide with logistic curve. It is shown that the model is rigorous in theory with flexible method, reasonable in result with simple structure, and it has strong logic superiority and regional adaptability, providing a new way for warning water pollution risk.

  3. A scenario-based procedure for seismic risk analysis

    International Nuclear Information System (INIS)

    Kluegel, J.-U.; Mualchin, L.; Panza, G.F.

    2006-12-01

    A new methodology for seismic risk analysis based on probabilistic interpretation of deterministic or scenario-based hazard analysis, in full compliance with the likelihood principle and therefore meeting the requirements of modern risk analysis, has been developed. The proposed methodology can easily be adjusted to deliver its output in a format required for safety analysts and civil engineers. The scenario-based approach allows the incorporation of all available information collected in a geological, seismotectonic and geotechnical database of the site of interest as well as advanced physical modelling techniques to provide a reliable and robust deterministic design basis for civil infrastructures. The robustness of this approach is of special importance for critical infrastructures. At the same time a scenario-based seismic hazard analysis allows the development of the required input for probabilistic risk assessment (PRA) as required by safety analysts and insurance companies. The scenario-based approach removes the ambiguity in the results of probabilistic seismic hazard analysis (PSHA) which relies on the projections of Gutenberg-Richter (G-R) equation. The problems in the validity of G-R projections, because of incomplete to total absence of data for making the projections, are still unresolved. Consequently, the information from G-R must not be used in decisions for design of critical structures or critical elements in a structure. The scenario-based methodology is strictly based on observable facts and data and complemented by physical modelling techniques, which can be submitted to a formalised validation process. By means of sensitivity analysis, knowledge gaps related to lack of data can be dealt with easily, due to the limited amount of scenarios to be investigated. The proposed seismic risk analysis can be used with confidence for planning, insurance and engineering applications. (author)

  4. Model of Axiological Dimension Risk Management

    Directory of Open Access Journals (Sweden)

    Kulińska Ewa

    2016-01-01

    Full Text Available It was on the basis of the obtained results that identify the key prerequisites for the integration of the management of logistics processes, management of the value creation process, and risk management that the methodological basis for the construction of the axiological dimension of the risk management (ADRM model of logistics processes was determined. By taking into account the contribution of individual concepts to the new research area, its essence was defined as an integrated, structured instrumentation aimed at the identification and implementation of logistics processes supporting creation of the value added as well as the identification and elimination of risk factors disturbing the process of the value creation for internal and external customers. The base for the ADRM concept of logistics processes is the use of the potential being inherent in synergistic effects which are obtained by using prerequisites for the integration of the management of logistics processes, of value creation and risk management as the key determinants of the value creation.

  5. Risk analysis for renewable energy projects due to constraints arising

    Science.gov (United States)

    Prostean, G.; Vasar, C.; Prostean, O.; Vartosu, A.

    2016-02-01

    Starting from the target of the European Union (EU) to use renewable energy in the area that aims a binding target of 20% renewable energy in final energy consumption by 2020, this article illustrates the identification of risks for implementation of wind energy projects in Romania, which could lead to complex technical implications, social and administrative. In specific projects analyzed in this paper were identified critical bottlenecks in the future wind power supply chain and reasonable time periods that may arise. Renewable energy technologies have to face a number of constraints that delayed scaling-up their production process, their transport process, the equipment reliability, etc. so implementing these types of projects requiring complex specialized team, the coordination of which also involve specific risks. The research team applied an analytical risk approach to identify major risks encountered within a wind farm project developed in Romania in isolated regions with different particularities, configured for different geographical areas (hill and mountain locations in Romania). Identification of major risks was based on the conceptual model set up for the entire project implementation process. Throughout this conceptual model there were identified specific constraints of such process. Integration risks were examined by an empirical study based on the method HAZOP (Hazard and Operability). The discussion describes the analysis of our results implementation context of renewable energy projects in Romania and creates a framework for assessing energy supply to any entity from renewable sources.

  6. System Analysis and Risk Assessment (SARA) system

    International Nuclear Information System (INIS)

    Krantz, E.A.; Russell, K.D.; Stewart, H.D.; Van Siclen, V.S.

    1986-01-01

    Utilization of Probabilistic Risk Assessment (PRA) related information in the day-to-day operation of plant systems has, in the past, been impracticable due to the size of the computers needed to run PRA codes. This paper discusses a microcomputer-based database system which can greatly enhance the capability of operators or regulators to incorporate PRA methodologies into their routine decision making. This system is called the System Analysis and Risk Assessment (SARA) system. SARA was developed by EG and G Idaho, Inc. at the Idaho National Engineering Laboratory to facilitate the study of frequency and consequence analyses of accident sequences from a large number of light water reactors (LWRs) in this country. This information is being amassed by several studies sponsored by the United States Nuclear Regulatory Commission (USNRC). To meet the nee