WorldWideScience

Sample records for risk models based

  1. 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)

  2. 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)

  3. 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.

  4. 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)

  5. Model-based mitigation of availability risks

    NARCIS (Netherlands)

    Zambon, E.; Bolzoni, D.; Etalle, S.; Salvato, M.

    2007-01-01

    The assessment and mitigation of risks related to the availability of the IT infrastructure is becoming increasingly important in modern organizations. Unfortunately, present standards for risk assessment and mitigation show limitations when evaluating and mitigating availability risks. This is due

  6. Model-Based Mitigation of Availability Risks

    NARCIS (Netherlands)

    Zambon, Emmanuele; Bolzoni, D.; Etalle, Sandro; Salvato, Marco

    2007-01-01

    The assessment and mitigation of risks related to the availability of the IT infrastructure is becoming increasingly important in modern organizations. Unfortunately, present standards for Risk Assessment and Mitigation show limitations when evaluating and mitigating availability risks. This is due

  7. 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...

  8. A Knowledge-Based Model of Audit Risk

    OpenAIRE

    Dhar, Vasant; Lewis, Barry; Peters, James

    1988-01-01

    Within the academic and professional auditing communities, there has been growing concern about how to accurately assess the various risks associated with performing an audit. These risks are difficult to conceptualize in terms of numeric estimates. This article discusses the development of a prototype computational model (computer program) that assesses one of the major audit risks -- inherent risk. This program bases most of its inferencing activities on a qualitative model of a typical bus...

  9. 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. 

  10. Risk Assessment of Engineering Project Financing Based on PPP Model

    Directory of Open Access Journals (Sweden)

    Ma Qiuli

    2017-01-01

    Full Text Available At present, the project financing channel is single, and the urban facilities are in short supply, and the risk assessment and prevention mechanism of financing should be further improved to reduce the risk of project financing. In view of this, the fuzzy comprehensive evaluation model of project financing risk which combined the method of fuzzy comprehensive evaluation and analytic hierarchy process is established. The scientificalness and effectiveness of the model are verified by the example of the world port project in Luohe city, and it provides basis and reference for engineering project financing based on PPP mode.

  11. 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

  12. 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.

  13. Task-based dermal exposure models for regulatory risk assessment

    NARCIS (Netherlands)

    Warren, N.D.; Marquart, H.; Christopher, Y.; Laitinen, J.; Hemmen, J.J. van

    2006-01-01

    The regulatory risk assessment of chemicals requires the estimation of occupational dermal exposure. Until recently, the models used were either based on limited data or were specific to a particular class of chemical or application. The EU project RISKOFDERM has gathered a considerable number of

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. Time-based collision risk modeling for air traffic management

    Science.gov (United States)

    Bell, Alan E.

    Since the emergence of commercial aviation in the early part of last century, economic forces have driven a steadily increasing demand for air transportation. Increasing density of aircraft operating in a finite volume of airspace is accompanied by a corresponding increase in the risk of collision, and in response to a growing number of incidents and accidents involving collisions between aircraft, governments worldwide have developed air traffic control systems and procedures to mitigate this risk. The objective of any collision risk management system is to project conflicts and provide operators with sufficient opportunity to recognize potential collisions and take necessary actions to avoid them. It is therefore the assertion of this research that the currency of collision risk management is time. Future Air Traffic Management Systems are being designed around the foundational principle of four dimensional trajectory based operations, a method that replaces legacy first-come, first-served sequencing priorities with time-based reservations throughout the airspace system. This research will demonstrate that if aircraft are to be sequenced in four dimensions, they must also be separated in four dimensions. In order to separate aircraft in four dimensions, time must emerge as the primary tool by which air traffic is managed. A functional relationship exists between the time-based performance of aircraft, the interval between aircraft scheduled to cross some three dimensional point in space, and the risk of collision. This research models that relationship and presents two key findings. First, a method is developed by which the ability of an aircraft to meet a required time of arrival may be expressed as a robust standard for both industry and operations. Second, a method by which airspace system capacity may be increased while maintaining an acceptable level of collision risk is presented and demonstrated for the purpose of formulating recommendations for procedures

  19. Application of Physiologically Based Pharmacokinetic Models in Chemical Risk Assessment

    Directory of Open Access Journals (Sweden)

    Moiz Mumtaz

    2012-01-01

    Full Text Available Post-exposure risk assessment of chemical and environmental stressors is a public health challenge. Linking exposure to health outcomes is a 4-step process: exposure assessment, hazard identification, dose response assessment, and risk characterization. This process is increasingly adopting “in silico” tools such as physiologically based pharmacokinetic (PBPK models to fine-tune exposure assessments and determine internal doses in target organs/tissues. Many excellent PBPK models have been developed. But most, because of their scientific sophistication, have found limited field application—health assessors rarely use them. Over the years, government agencies, stakeholders/partners, and the scientific community have attempted to use these models or their underlying principles in combination with other practical procedures. During the past two decades, through cooperative agreements and contracts at several research and higher education institutions, ATSDR funded translational research has encouraged the use of various types of models. Such collaborative efforts have led to the development and use of transparent and user-friendly models. The “human PBPK model toolkit” is one such project. While not necessarily state of the art, this toolkit is sufficiently accurate for screening purposes. Highlighted in this paper are some selected examples of environmental and occupational exposure assessments of chemicals and their mixtures.

  20. Task-based dermal exposure models for regulatory risk assessment.

    Science.gov (United States)

    Warren, Nicholas D; Marquart, Hans; Christopher, Yvette; Laitinen, Juha; VAN Hemmen, Joop J

    2006-07-01

    The regulatory risk assessment of chemicals requires the estimation of occupational dermal exposure. Until recently, the models used were either based on limited data or were specific to a particular class of chemical or application. The EU project RISKOFDERM has gathered a considerable number of new measurements of dermal exposure together with detailed contextual information. This article describes the development of a set of generic task-based models capable of predicting potential dermal exposure to both solids and liquids in a wide range of situations. To facilitate modelling of the wide variety of dermal exposure situations six separate models were made for groupings of exposure scenarios called Dermal Exposure Operation units (DEO units). These task-based groupings cluster exposure scenarios with regard to the expected routes of dermal exposure and the expected influence of exposure determinants. Within these groupings linear mixed effect models were used to estimate the influence of various exposure determinants and to estimate components of variance. The models predict median potential dermal exposure rates for the hands and the rest of the body from the values of relevant exposure determinants. These rates are expressed as mg or microl product per minute. Using these median potential dermal exposure rates and an accompanying geometric standard deviation allows a range of exposure percentiles to be calculated.

  1. 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.

  2. Risk assessment and model for community-based construction ...

    African Journals Online (AJOL)

    It, therefore, becomes necessary to systematically manage uncertainty in community-based construction in order to increase the likelihood of meeting project objectives using necessary risk management strategies. Risk management, which is an iterative process due to the dynamic nature of many risks, follows three main ...

  3. Radiation risk estimation based on measurement error models

    CERN Document Server

    Masiuk, Sergii; Shklyar, Sergiy; Chepurny, Mykola; Likhtarov, Illya

    2017-01-01

    This monograph discusses statistics and risk estimates applied to radiation damage under the presence of measurement errors. The first part covers nonlinear measurement error models, with a particular emphasis on efficiency of regression parameter estimators. In the second part, risk estimation in models with measurement errors is considered. Efficiency of the methods presented is verified using data from radio-epidemiological studies.

  4. WORKSHOP ON APPLICATION OF STATISTICAL METHODS TO BIOLOGICALLY-BASED PHARMACOKINETIC MODELING FOR RISK ASSESSMENT

    Science.gov (United States)

    Biologically-based pharmacokinetic models are being increasingly used in the risk assessment of environmental chemicals. These models are based on biological, mathematical, statistical and engineering principles. Their potential uses in risk assessment include extrapolation betwe...

  5. 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)

  6. An Integrated Risk Index Model Based on Hierarchical Fuzzy Logic for Underground Risk Assessment

    Directory of Open Access Journals (Sweden)

    Muhammad Fayaz

    2017-10-01

    Full Text Available Available space in congested cities is getting scarce due to growing urbanization in the recent past. The utilization of underground space is considered as a solution to the limited space in smart cities. The numbers of underground facilities are growing day by day in the developing world. Typical underground facilities include the transit subway, parking lots, electric lines, water supply and sewer lines. The likelihood of the occurrence of accidents due to underground facilities is a random phenomenon. To avoid any accidental loss, a risk assessment method is required to conduct the continuous risk assessment and report any abnormality before it happens. In this paper, we have proposed a hierarchical fuzzy inference based model for under-ground risk assessment. The proposed hierarchical fuzzy inference architecture reduces the total number of rules from the rule base. Rule reduction is important because the curse of dimensionality damages the transparency and interpretation as it is very tough to understand and justify hundreds or thousands of fuzzy rules. The computation time also increases as rules increase. The proposed model takes 175 rules having eight input parameters to compute the risk index, and the conventional fuzzy logic requires 390,625 rules, having the same number of input parameters to compute risk index. Hence, the proposed model significantly reduces the curse of dimensionality. Rule design for fuzzy logic is also a tedious task. In this paper, we have also introduced new rule schemes, namely maximum rule-based and average rule-based; both schemes can be used interchangeably according to the logic needed for rule design. The experimental results show that the proposed method is a virtuous choice for risk index calculation where the numbers of variables are greater.

  7. Are Masking-Based Models of Risk Useful?

    Science.gov (United States)

    Gisiner, Robert C

    2016-01-01

    As our understanding of directly observable effects from anthropogenic sound exposure has improved, concern about "unobservable" effects such as stress and masking have received greater attention. Equal energy models of masking such as power spectrum models have the appeal of simplicity, but do they offer biologically realistic assessments of the risk of masking? Data relevant to masking such as critical ratios, critical bandwidths, temporal resolution, and directional resolution along with what is known about general mammalian antimasking mechanisms all argue for a much more complicated view of masking when making decisions about the risk of masking inherent in a given anthropogenic sound exposure scenario.

  8. LIFETIME LUNG CANCER RISKS ASSOCIATED WITH INDOOR RADON EXPOSURE BASED ON VARIOUS RADON RISK MODELS FOR CANADIAN POPULATION.

    Science.gov (United States)

    Chen, Jing

    2017-04-01

    This study calculates and compares the lifetime lung cancer risks associated with indoor radon exposure based on well-known risk models in the literature; two risk models are from joint studies among miners and the other three models were developed from pooling studies on residential radon exposure from China, Europe and North America respectively. The aim of this article is to make clear that the various models are mathematical descriptions of epidemiologically observed real risks in different environmental settings. The risk from exposure to indoor radon is real and it is normal that variations could exist among different risk models even when they were applied to the same dataset. The results show that lifetime risk estimates vary significantly between the various risk models considered here: the model based on the European residential data provides the lowest risk estimates, while models based on the European miners and Chinese residential pooling with complete dosimetry give the highest values. The lifetime risk estimates based on the EPA/BEIR-VI model lie within this range and agree reasonably well with the averages of risk estimates from the five risk models considered in this study. © Crown copyright 2016.

  9. Canadian population risk of radon induced lung cancer variation range assessment based on various radon risk models

    International Nuclear Information System (INIS)

    Chen, Jing

    2017-01-01

    To address public concerns regarding radon risk and variations in risk estimates based on various risk models available in the literature, lifetime lung cancer risks were calculated with five well-known risk models using more recent Canadian vital statistics (5-year averages from 2008 to 2012). Variations in population risk estimation among various models were assessed. The results showed that the Canadian population risk of radon induced lung cancer can vary from 5.0 to 17% for men and 5.1 to 18% for women based on different radon risk models. Averaged over the estimates from various risk models with better radon dosimetry, 13% of lung cancer deaths among Canadian males and 14% of lung cancer deaths among Canadian females were attributable to long-term indoor radon exposure. (authors)

  10. Risk, individual differences, and environment: an Agent-Based Modeling approach to sexual risk-taking.

    Science.gov (United States)

    Nagoski, Emily; Janssen, Erick; Lohrmann, David; Nichols, Eric

    2012-08-01

    Risky sexual behaviors, including the decision to have unprotected sex, result from interactions between individuals and their environment. The current study explored the use of Agent-Based Modeling (ABM)-a methodological approach in which computer-generated artificial societies simulate human sexual networks-to assess the influence of heterogeneity of sexual motivation on the risk of contracting HIV. The models successfully simulated some characteristics of human sexual systems, such as the relationship between individual differences in sexual motivation (sexual excitation and inhibition) and sexual risk, but failed to reproduce the scale-free distribution of number of partners observed in the real world. ABM has the potential to inform intervention strategies that target the interaction between an individual and his or her social environment.

  11. Agent-Based Modelling for Security Risk Assessment

    NARCIS (Netherlands)

    Janssen, S.A.M.; Sharpans'kykh, Alexei; Bajo, J.; Vale, Z.; Hallenborg, K.; Rocha, A.P.; Mathieu, P.; Pawlewski, P.; Del Val, E.; Novais, P.; Lopes, F.; Duque Méndez, N.D.; Julián, V.; Holmgren, J.

    2017-01-01

    Security Risk Assessment is commonly performed by using traditional methods based on linear probabilistic tools and informal expert judgements. These methods lack the capability to take the inherent dynamic and intelligent nature of attackers into account. To partially address the limitations,

  12. Individual-based model for radiation risk assessment

    Science.gov (United States)

    Smirnova, O.

    A mathematical model is developed which enables one to predict the life span probability for mammals exposed to radiation. It relates statistical biometric functions with statistical and dynamic characteristics of an organism's critical system. To calculate the dynamics of the latter, the respective mathematical model is used too. This approach is applied to describe the effects of low level chronic irradiation on mice when the hematopoietic system (namely, thrombocytopoiesis) is the critical one. For identification of the joint model, experimental data on hematopoiesis in nonirradiated and irradiated mice, as well as on mortality dynamics of those in the absence of radiation are utilized. The life span probability and life span shortening predicted by the model agree with corresponding experimental data. Modeling results show the significance of ac- counting the variability of the individual radiosensitivity of critical system cells when estimating the radiation risk. These findings are corroborated by clinical data on persons involved in the elimination of the Chernobyl catastrophe after- effects. All this makes it feasible to use the model for radiation risk assessments for cosmonauts and astronauts on long-term missions such as a voyage to Mars or a lunar colony. In this case the model coefficients have to be determined by making use of the available data for humans. Scenarios for the dynamics of dose accumulation during space flights should also be taken into account.

  13. Modifying EPA radiation risk models based on BEIR VII

    International Nuclear Information System (INIS)

    Pawel, D.; Puskin, J.

    2007-01-01

    This paper summarizes a 'draft White Paper' that provides details on proposed changes in EPA's methodology for estimating radiogenic cancer risks. Many of the changes are based on the contents of a recent National Academy of Sciences (NAS) report (BEIR VII), that addresses cancer and genetic risks from low doses of low-LET radiation. The draft White Paper was prepared for a meeting with the EPA's Science Advisory Board's Radiation Advisory Committee (RAC) in September for seeking advice on the application of BEIR VII and on issues relating to these modifications and expansions. After receiving the Advisory review, we plan to implement the changes by publishing the new methodology in an EPA report, which we expect to submit to the RAC for final review. The revised methodology could then be applied to update the cancer risk coefficients for over 800 radionuclides that are published in EPA's Federal Guidance Report 13. (author)

  14. Some computer simulations based on the linear relative risk model

    International Nuclear Information System (INIS)

    Gilbert, E.S.

    1991-10-01

    This report presents the results of computer simulations designed to evaluate and compare the performance of the likelihood ratio statistic and the score statistic for making inferences about the linear relative risk mode. The work was motivated by data on workers exposed to low doses of radiation, and the report includes illustration of several procedures for obtaining confidence limits for the excess relative risk coefficient based on data from three studies of nuclear workers. The computer simulations indicate that with small sample sizes and highly skewed dose distributions, asymptotic approximations to the score statistic or to the likelihood ratio statistic may not be adequate. For testing the null hypothesis that the excess relative risk is equal to zero, the asymptotic approximation to the likelihood ratio statistic was adequate, but use of the asymptotic approximation to the score statistic rejected the null hypothesis too often. Frequently the likelihood was maximized at the lower constraint, and when this occurred, the asymptotic approximations for the likelihood ratio and score statistics did not perform well in obtaining upper confidence limits. The score statistic and likelihood ratio statistics were found to perform comparably in terms of power and width of the confidence limits. It is recommended that with modest sample sizes, confidence limits be obtained using computer simulations based on the score statistic. Although nuclear worker studies are emphasized in this report, its results are relevant for any study investigating linear dose-response functions with highly skewed exposure distributions. 22 refs., 14 tabs

  15. 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...

  16. Coronary risk assessment by point-based vs. equation-based Framingham models: significant implications for clinical care.

    Science.gov (United States)

    Gordon, William J; Polansky, Jesse M; Boscardin, W John; Fung, Kathy Z; Steinman, Michael A

    2010-11-01

    US cholesterol guidelines use original and simplified versions of the Framingham model to estimate future coronary risk and thereby classify patients into risk groups with different treatment strategies. We sought to compare risk estimates and risk group classification generated by the original, complex Framingham model and the simplified, point-based version. We assessed 2,543 subjects age 20-79 from the 2001-2006 National Health and Nutrition Examination Surveys (NHANES) for whom Adult Treatment Panel III (ATP-III) guidelines recommend formal risk stratification. For each subject, we calculated the 10-year risk of major coronary events using the original and point-based Framingham models, and then compared differences in these risk estimates and whether these differences would place subjects into different ATP-III risk groups (20% risk). Using standard procedures, all analyses were adjusted for survey weights, clustering, and stratification to make our results nationally representative. Among 39 million eligible adults, the original Framingham model categorized 71% of subjects as having "moderate" risk (20%) risk. Estimates of coronary risk by the original and point-based models often differed substantially. The point-based system classified 15% of adults (5.7 million) into different risk groups than the original model, with 10% (3.9 million) misclassified into higher risk groups and 5% (1.8 million) into lower risk groups, for a net impact of classifying 2.1 million adults into higher risk groups. These risk group misclassifications would impact guideline-recommended drug treatment strategies for 25-46% of affected subjects. Patterns of misclassifications varied significantly by gender, age, and underlying CHD risk. Compared to the original Framingham model, the point-based version misclassifies millions of Americans into risk groups for which guidelines recommend different treatment strategies.

  17. An agent-based model of flood risk and insurance

    NARCIS (Netherlands)

    Dubbelboer, J.; Nikolic, I.; Jenkins, K.; Hall, J

    2017-01-01

    Flood risk emerges from the dynamic interaction between natural hazards and human vulnerability. Methods for the quantification of flood risk are well established, but tend to deal with human and economic vulnerability as being static or changing with an exogenously defined trend. In this paper

  18. 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

  19. Risk of portfolio with simulated returns based on copula model

    Science.gov (United States)

    Razak, Ruzanna Ab; Ismail, Noriszura

    2015-02-01

    The commonly used tool for measuring risk of a portfolio with equally weighted stocks is variance-covariance method. Under extreme circumstances, this method leads to significant underestimation of actual risk due to its multivariate normality assumption of the joint distribution of stocks. The purpose of this research is to compare the actual risk of portfolio with the simulated risk of portfolio in which the joint distribution of two return series is predetermined. The data used is daily stock prices from the ASEAN market for the period January 2000 to December 2012. The copula approach is applied to capture the time varying dependence among the return series. The results shows that the chosen copula families are not suitable to present the dependence structures of each bivariate returns. Exception for the Philippines-Thailand pair where by t copula distribution appears to be the appropriate choice to depict its dependence. Assuming that the t copula distribution is the joint distribution of each paired series, simulated returns is generated and value-at-risk (VaR) is then applied to evaluate the risk of each portfolio consisting of two simulated return series. The VaR estimates was found to be symmetrical due to the simulation of returns via elliptical copula-GARCH approach. By comparison, it is found that the actual risks are underestimated for all pairs of portfolios except for Philippines-Thailand. This study was able to show that disregard of the non-normal dependence structure of two series will result underestimation of actual risk of the portfolio.

  20. Recognition of risk situations based on endoscopic instrument tracking and knowledge based situation modeling

    Science.gov (United States)

    Speidel, Stefanie; Sudra, Gunther; Senemaud, Julien; Drentschew, Maximilian; Müller-Stich, Beat Peter; Gutt, Carsten; Dillmann, Rüdiger

    2008-03-01

    Minimally invasive surgery has gained significantly in importance over the last decade due to the numerous advantages on patient-side. The surgeon has to adapt special operation-techniques and deal with difficulties like the complex hand-eye coordination, limited field of view and restricted mobility. To alleviate these constraints we propose to enhance the surgeon's capabilities by providing a context-aware assistance using augmented reality (AR) techniques. In order to generate a context-aware assistance it is necessary to recognize the current state of the intervention using intraoperatively gained sensor data and a model of the surgical intervention. In this paper we present the recognition of risk situations, the system warns the surgeon if an instrument gets too close to a risk structure. The context-aware assistance system starts with an image-based analysis to retrieve information from the endoscopic images. This information is classified and a semantic description is generated. The description is used to recognize the current state and launch an appropriate AR visualization. In detail we present an automatic vision-based instrument tracking to obtain the positions of the instruments. Situation recognition is performed using a knowledge representation based on a description logic system. Two augmented reality visualization programs are realized to warn the surgeon if a risk situation occurs.

  1. Measuring the coupled risks: A copula-based CVaR model

    Science.gov (United States)

    He, Xubiao; Gong, Pu

    2009-01-01

    Integrated risk management for financial institutions requires an approach for aggregating risk types (such as market and credit) whose distributional shapes vary considerably. The financial institutions often ignore risks' coupling influence so as to underestimate the financial risks. We constructed a copula-based Conditional Value-at-Risk (CVaR) model for market and credit risks. This technique allows us to incorporate realistic marginal distributions that capture essential empirical features of these risks, such as skewness and fat-tails while allowing for a rich dependence structure. Finally, the numerical simulation method is used to implement the model. Our results indicate that the coupled risks for the listed company's stock maybe are undervalued if credit risk is ignored, especially for the listed company with bad credit quality.

  2. The use of biologically based cancer risk models in radiation epidemiology

    International Nuclear Information System (INIS)

    Krewski, D.; Zielinski, J.M.; Hazelton, W.D.; Garner, M.J.; Moolgavkar, S.H.

    2003-01-01

    Biologically based risk projection models for radiation carcinogenesis seek to describe the fundamental biological processes involved in neoplastic transformation of somatic cells into malignant cancer cells. A validated biologically based model, whose parameters have a direct biological interpretation, can also be used to extrapolate cancer risks to different exposure conditions with some confidence. In this article, biologically based models for radiation carcinogenesis, including the two-stage clonal expansion (TSCE) model and its extensions, are reviewed. The biological and mathematical bases for such models are described, and the implications of key model parameters for cancer risk assessment examined. Specific applications of versions of the TSCE model to important epidemiologic datasets are discussed, including the Colorado uranium miners' cohort; a cohort of Chinese tin miners; the lifespan cohort of atomic bomb survivors in Hiroshima and Nagasaki; and a cohort of over 200,000 workers included in the National Dose Registry (NDR) of Canada. (author)

  3. Risk-Based Models for Managing Data Privacy in Healthcare

    Science.gov (United States)

    AL Faresi, Ahmed

    2011-01-01

    Current research in health care lacks a systematic investigation to identify and classify various sources of threats to information privacy when sharing health data. Identifying and classifying such threats would enable the development of effective information security risk monitoring and management policies. In this research I put the first step…

  4. 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

  5. A quantitative risk-based model for reasoning over critical system properties

    Science.gov (United States)

    Feather, M. S.

    2002-01-01

    This position paper suggests the use of a quantitative risk-based model to help support reeasoning and decision making that spans many of the critical properties such as security, safety, survivability, fault tolerance, and real-time.

  6. Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

    Science.gov (United States)

    These model-based estimates use two surveys, the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS). The two surveys are combined using novel statistical methodology.

  7. Model-Based Engineering for Supply Chain Risk Management

    Science.gov (United States)

    2015-09-30

    Design Language (AADL), which has tools for modeling and compliance verification, provides an effective capability to model and describe all component...the outsourced units in a supply chain can be an impossible task where the product might be composed of 10,000 individual components at the 4th or...can be used to guide the process of monitoring the award and assurance of the outsourced work. Safety-critical verification of cyber-physical

  8. 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.

  9. Modeling of Ship Collision Risk Index Based on Complex Plane and Its Realization

    OpenAIRE

    Xiaoqin Xu; Xiaoqiao Geng; Yuanqiao Wen

    2016-01-01

    Ship collision risk index is the basic and important concept in the domain of ship collision avoidance. In this paper, the advantages and deficiencies of the various calculation methods of ship collision risk index are pointed out. Then the ship collision risk model based on complex plane, which can well make up for the deficiencies of the widely-used evaluation model proposed by Kearon.J and Liu ruru is proposed. On this basis, the calculation method of collision risk index under the encount...

  10. A Bayesian network model for predicting type 2 diabetes risk based on electronic health records

    Science.gov (United States)

    Xie, Jiang; Liu, Yan; Zeng, Xu; Zhang, Wu; Mei, Zhen

    2017-07-01

    An extensive, in-depth study of diabetes risk factors (DBRF) is of crucial importance to prevent (or reduce) the chance of suffering from type 2 diabetes (T2D). Accumulation of electronic health records (EHRs) makes it possible to build nonlinear relationships between risk factors and diabetes. However, the current DBRF researches mainly focus on qualitative analyses, and the inconformity of physical examination items makes the risk factors likely to be lost, which drives us to study the novel machine learning approach for risk model development. In this paper, we use Bayesian networks (BNs) to analyze the relationship between physical examination information and T2D, and to quantify the link between risk factors and T2D. Furthermore, with the quantitative analyses of DBRF, we adopt EHR and propose a machine learning approach based on BNs to predict the risk of T2D. The experiments demonstrate that our approach can lead to better predictive performance than the classical risk model.

  11. Formal safety assessment based on relative risks model in ship navigation

    Energy Technology Data Exchange (ETDEWEB)

    Hu Shenping [Merchant Marine College, Shanghai Maritime University, 1550, Pudong Dadao, Shanghai 200135 (China)]. E-mail: sphu@mmc.shmtu.edu.cn; Fang Quangen [Merchant Marine College, Shanghai Maritime University, 1550, Pudong Dadao, Shanghai 200135 (China)]. E-mail: qgfang@mmc.shmtu.edu.cn; Xia Haibo [Merchant Marine College, Shanghai Maritime University, 1550, Pudong Dadao, Shanghai 200135 (China)]. E-mail: hbxia@mmc.shmtu.edu.cn; Xi Yongtao [Merchant Marine College, Shanghai Maritime University, 1550, Pudong Dadao, Shanghai 200135 (China)]. E-mail: xiyt@mmc.shmtu.edu.cn

    2007-03-15

    Formal safety assessment (FSA) is a structured and systematic methodology aiming at enhancing maritime safety. It has been gradually and broadly used in the shipping industry nowadays around the world. On the basis of analysis and conclusion of FSA approach, this paper discusses quantitative risk assessment and generic risk model in FSA, especially frequency and severity criteria in ship navigation. Then it puts forward a new model based on relative risk assessment (MRRA). The model presents a risk-assessment approach based on fuzzy functions and takes five factors into account, including detailed information about accident characteristics. It has already been used for the assessment of pilotage safety in Shanghai harbor, China. Consequently, it can be proved that MRRA is a useful method to solve the problems in the risk assessment of ship navigation safety in practice.

  12. Formal safety assessment based on relative risks model in ship navigation

    International Nuclear Information System (INIS)

    Hu Shenping; Fang Quangen; Xia Haibo; Xi Yongtao

    2007-01-01

    Formal safety assessment (FSA) is a structured and systematic methodology aiming at enhancing maritime safety. It has been gradually and broadly used in the shipping industry nowadays around the world. On the basis of analysis and conclusion of FSA approach, this paper discusses quantitative risk assessment and generic risk model in FSA, especially frequency and severity criteria in ship navigation. Then it puts forward a new model based on relative risk assessment (MRRA). The model presents a risk-assessment approach based on fuzzy functions and takes five factors into account, including detailed information about accident characteristics. It has already been used for the assessment of pilotage safety in Shanghai harbor, China. Consequently, it can be proved that MRRA is a useful method to solve the problems in the risk assessment of ship navigation safety in practice

  13. A Risk Assessment Example for Soil Invertebrates Using Spatially Explicit Agent-Based Models

    DEFF Research Database (Denmark)

    Reed, Melissa; Alvarez, Tania; Chelinho, Sonia

    2016-01-01

    Current risk assessment methods for measuring the toxicity of plant protection products (PPPs) on soil invertebrates use standardized laboratory conditions to determine acute effects on mortality and sublethal effects on reproduction. If an unacceptable risk is identified at the lower tier...... population models for ubiquitous soil invertebrates (collembolans and earthworms) as refinement options in current risk assessment. Both are spatially explicit agent-based models (ABMs), incorporating individual and landscape variability. The models were used to provide refined risk assessments for different...... application scenarios of a hypothetical pesticide applied to potato crops (full-field spray onto the soil surface [termed “overall”], in-furrow, and soil-incorporated pesticide applications). In the refined risk assessment, the population models suggest that soil invertebrate populations would likely recover...

  14. 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.

  15. Erosion risk assessment in the southern Amazon - Data Preprocessing, data base application and process based modelling

    Science.gov (United States)

    Schindewolf, Marcus; Herrmann, Marie-Kristin; Herrmann, Anne-Katrin; Schultze, Nico; Amorim, Ricardo S. S.; Schmidt, Jürgen

    2015-04-01

    The study region along the BR 16 highway belongs to the "Deforestation Arc" at the southern border of the Amazon rainforest. At the same time, it incorporates a land use gradient as colonization started in the 1975-1990 in Central Mato Grosso in 1990 in northern Mato Grosso and most recently in 2004-2005 in southern Pará. Based on present knowledge soil erosion is one of the key driver of soil degradation. Hence, there is a strong need to implement soil erosion control measures in eroding landscapes. Planning and dimensioning of such measures require reliable and detailed information on the temporal and spatial distribution of soil loss, sediment transport and deposition. Soil erosion models are increasingly used, in order to simulate the physical processes involved and to predict the effects of soil erosion control measures. The process based EROSION 3D simulation model is used for surveying soil erosion and deposition on regional catchments. Although EROSION 3D is a widespread, extensively validated model, the application of the model on regional scale remains challenging due to the enormous data requirements and complex data processing operations. In this context the study includes the compilation, validation and generalisation of existing land use and soil data in order to generate a consistent EROSION 3D input datasets. As a part of this process a GIS-linked data base application allows to transfer the original soil and land use data into model specific parameter files. This combined methodology provides different risk assessment maps for certain demands on regional scale. Besides soil loss and sediment transport, sediment pass over points into surface water bodies and particle enrichment can be simulated using the EROSION 3D model. Thus the estimation of particle bound nutrient and pollutant inputs into surface water bodies becomes possible. The study ended up in a user-friendly, timesaving and improved software package for the simulation of soil loss and

  16. Development of risk-based computer models for deriving criteria on residual radioactivity and recycling

    International Nuclear Information System (INIS)

    Chen, Shih-Yew

    1995-01-01

    Argonne National Laboratory (ANL) is developing multimedia environmental pathway and health risk computer models to assess radiological risks to human health and to derive cleanup guidelines for environmental restoration, decommissioning, and recycling activities. These models are based on the existing RESRAD code, although each has a separate design and serves different objectives. Two such codes are RESRAD-BUILD and RESRAD-PROBABILISTIC. The RESRAD code was originally developed to implement the U.S. Department of Energy's (DOE's) residual radioactive materials guidelines for contaminated soils. RESRAD has been successfully used by DOE and its contractors to assess health risks and develop cleanup criteria for several sites selected for cleanup or restoration programs. RESRAD-BUILD analyzes human health risks from radioactive releases during decommissioning or rehabilitation of contaminated buildings. Risks to workers are assessed for dismantling activities; risks to the public are assessed for occupancy. RESRAD-BUILD is based on a room compartmental model analyzing the effects on room air quality of contaminant emission and resuspension (as well as radon emanation), the external radiation pathway, and other exposure pathways. RESRAD-PROBABILISTIC, currently under development, is intended to perform uncertainty analysis for RESRAD by using the Monte Carlo approach based on the Latin-Hypercube sampling scheme. The codes being developed at ANL are tailored to meet a specific objective of human health risk assessment and require specific parameter definition and data gathering. The combined capabilities of these codes satisfy various risk assessment requirements in environmental restoration and remediation activities. (author)

  17. Development of risk-based computer models for deriving criteria on residual radioactivity and recycling

    International Nuclear Information System (INIS)

    Chen, S.Y.

    1994-01-01

    Argonne National Laboratory (ANL) is developing multimedia environmental pathway and health risk computer models to assess radiological risks to human health and to derive cleanup guidelines for environmental restoration, decommissioning, and recycling activities. These models are based on the existing RESRAD code, although each has a separate design and serves different objectives. Two such codes are RESRAD-BUILD and RESRAD-PROBABILISTIC. The RESRAD code was originally developed to implement the US Department of Energy's (DOE's) residual radioactive materials guidelines for contaminated soils. RESRAD has been successfully used by DOE and its contractors to assess health risks and develop cleanup criteria for several sites selected for cleanup or restoration programs. RESRAD-BUILD analyzes human health risks from radioactive releases during decommissioning or rehabilitation of contaminated buildings. Risks to workers are assessed for dismantling activities; risks to the public are assessed for occupancy. RESRAD-BUILD is based on a room compartmental model analyzing the effects on room air quality of contaminant emission and resuspension (as well as radon emanation), the external radiation pathway, and other exposure pathways. RESRAD-PROBABILISTIC, currently under development, is intended to perform uncertainty analysis for RESRAD by using the Monte Carlo approach based on the Latin-Hypercube sampling scheme. The codes being developed at ANL are tailored to meet a specific objective of human health risk assessment and require specific parameter definition and data gathering. The combined capabilities of these codes satisfy various risk assessment requirements in environmental restoration and remediation activities

  18. Modeling of Ship Collision Risk Index Based on Complex Plane and Its Realization

    Directory of Open Access Journals (Sweden)

    Xiaoqin Xu

    2016-07-01

    Full Text Available Ship collision risk index is the basic and important concept in the domain of ship collision avoidance. In this paper, the advantages and deficiencies of the various calculation methods of ship collision risk index are pointed out. Then the ship collision risk model based on complex plane, which can well make up for the deficiencies of the widely-used evaluation model proposed by Kearon.J and Liu ruru is proposed. On this basis, the calculation method of collision risk index under the encountering situation of multi-ships is constructed, then the three-dimensional image and spatial curve of the risk index are figured out. Finally, single chip microcomputer is used to realize the model. And attaching this single chip microcomputer to ARPA is helpful to the decision-making of the marine navigators.

  19. Methodological Bases for Describing Risks of the Enterprise Business Model in Integrated Reporting

    Directory of Open Access Journals (Sweden)

    Nesterenko Oksana O.

    2017-12-01

    Full Text Available The aim of the article is to substantiate the methodological bases for describing the business and accounting risks of an enterprise business model in integrated reporting for their timely detection and assessment, and develop methods for their leveling or minimizing and possible prevention. It is proposed to consider risks in the process of forming integrated reporting from two sides: first, risks that arise in the business model of an organization and should be disclosed in its integrated report; second, accounting risks of integrated reporting, which should be taken into account by members of the cross-sectoral working group and management personnel in the process of forming and promulgating integrated reporting. To develop an adequate accounting and analytical tool for disclosure of information about the risks of the business model and integrated reporting, their leveling or minimization, in the article a terminological analysis of the essence of entrepreneurial and accounting risks is carried out. The entrepreneurial risk is defined as an objective-subjective economic category that characterizes the probability of negative or positive consequences of economic-social-ecological activity within the framework of the business model of an enterprise under uncertainty. The accounting risk is suggested to be understood as the probability of unfavorable consequences as a result of organizational, methodological errors in the integrated accounting system, which present threat to the quality, accuracy and reliability of the reporting information on economic, social and environmental activities in integrated reporting as well as threat of inappropriate decision-making by stakeholders based on the integrated report. For the timely identification of business risks and maximum leveling of the influence of accounting risks on the process of formation and publication of integrated reporting, in the study the place of entrepreneurial and accounting risks in

  20. Integrating adaptive behaviour in large-scale flood risk assessments: an Agent-Based Modelling approach

    Science.gov (United States)

    Haer, Toon; Aerts, Jeroen

    2015-04-01

    Between 1998 and 2009, Europe suffered over 213 major damaging floods, causing 1126 deaths, displacing around half a million people. In this period, floods caused at least 52 billion euro in insured economic losses making floods the most costly natural hazard faced in Europe. In many low-lying areas, the main strategy to cope with floods is to reduce the risk of the hazard through flood defence structures, like dikes and levees. However, it is suggested that part of the responsibility for flood protection needs to shift to households and businesses in areas at risk, and that governments and insurers can effectively stimulate the implementation of individual protective measures. However, adaptive behaviour towards flood risk reduction and the interaction between the government, insurers, and individuals has hardly been studied in large-scale flood risk assessments. In this study, an European Agent-Based Model is developed including agent representatives for the administrative stakeholders of European Member states, insurers and reinsurers markets, and individuals following complex behaviour models. The Agent-Based Modelling approach allows for an in-depth analysis of the interaction between heterogeneous autonomous agents and the resulting (non-)adaptive behaviour. Existing flood damage models are part of the European Agent-Based Model to allow for a dynamic response of both the agents and the environment to changing flood risk and protective efforts. By following an Agent-Based Modelling approach this study is a first contribution to overcome the limitations of traditional large-scale flood risk models in which the influence of individual adaptive behaviour towards flood risk reduction is often lacking.

  1. Bayesian risk-based decision method for model validation under uncertainty

    International Nuclear Information System (INIS)

    Jiang Xiaomo; Mahadevan, Sankaran

    2007-01-01

    This paper develops a decision-making methodology for computational model validation, considering the risk of using the current model, data support for the current model, and cost of acquiring new information to improve the model. A Bayesian decision theory-based method is developed for this purpose, using a likelihood ratio as the validation metric for model assessment. An expected risk or cost function is defined as a function of the decision costs, and the likelihood and prior of each hypothesis. The risk is minimized through correctly assigning experimental data to two decision regions based on the comparison of the likelihood ratio with a decision threshold. A Bayesian validation metric is derived based on the risk minimization criterion. Two types of validation tests are considered: pass/fail tests and system response value measurement tests. The methodology is illustrated for the validation of reliability prediction models in a tension bar and an engine blade subjected to high cycle fatigue. The proposed method can effectively integrate optimal experimental design into model validation to simultaneously reduce the cost and improve the accuracy of reliability model assessment

  2. Evaluation model for safety capacity of chemical industrial park based on acceptable regional risk

    Institute of Scientific and Technical Information of China (English)

    Guohua Chen; Shukun Wang; Xiaoqun Tan

    2015-01-01

    The paper defines the Safety Capacity of Chemical Industrial Park (SCCIP) from the perspective of acceptable regional risk. For the purpose of exploring the evaluation model for the SCCIP, a method based on quantitative risk assessment was adopted for evaluating transport risk and to confirm reasonable safety transport capacity of chemical industrial park, and then by combining with the safety storage capacity, a SCCIP evaluation model was put forward. The SCCIP was decided by the smaller one between the largest safety storage capacity and the maximum safety transport capacity, or else, the regional risk of the park will exceed the acceptable level. The developed method was applied to a chemical industrial park in Guangdong province to obtain the maximum safety transport capacity and the SCCIP. The results can be realized in the regional risk control of the park effectively.

  3. Risk assessment of storm surge disaster based on numerical models and remote sensing

    Science.gov (United States)

    Liu, Qingrong; Ruan, Chengqing; Zhong, Shan; Li, Jian; Yin, Zhonghui; Lian, Xihu

    2018-06-01

    Storm surge is one of the most serious ocean disasters in the world. Risk assessment of storm surge disaster for coastal areas has important implications for planning economic development and reducing disaster losses. Based on risk assessment theory, this paper uses coastal hydrological observations, a numerical storm surge model and multi-source remote sensing data, proposes methods for valuing hazard and vulnerability for storm surge and builds a storm surge risk assessment model. Storm surges in different recurrence periods are simulated in numerical models and the flooding areas and depth are calculated, which are used for assessing the hazard of storm surge; remote sensing data and GIS technology are used for extraction of coastal key objects and classification of coastal land use are identified, which is used for vulnerability assessment of storm surge disaster. The storm surge risk assessment model is applied for a typical coastal city, and the result shows the reliability and validity of the risk assessment model. The building and application of storm surge risk assessment model provides some basis reference for the city development plan and strengthens disaster prevention and mitigation.

  4. Addressing dependability by applying an approach for model-based risk assessment

    International Nuclear Information System (INIS)

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

    2007-01-01

    This paper describes how an approach for model-based risk assessment (MBRA) can be applied for addressing different dependability factors in a critical application. Dependability factors, such as availability, reliability, safety and security, are important when assessing the dependability degree of total systems involving digital instrumentation and control (I and C) sub-systems. In order to identify risk sources their roles with regard to intentional system aspects such as system functions, component behaviours and intercommunications must be clarified. Traditional risk assessment is based on fault or risk models of the system. In contrast to this, MBRA utilizes success-oriented models describing all intended system aspects, including functional, operational and organizational aspects of the target. The EU-funded CORAS project developed a tool-supported methodology for the application of MBRA in security-critical systems. The methodology has been tried out within the telemedicine and e-commerce areas, and provided through a series of seven trials a sound basis for risk assessments. In this paper the results from the CORAS project are presented, and it is discussed how the approach for applying MBRA meets the needs of a risk-informed Man-Technology-Organization (MTO) model, and how methodology can be applied as a part of a trust case development

  5. Addressing dependability by applying an approach for model-based risk assessment

    Energy Technology Data Exchange (ETDEWEB)

    Gran, Bjorn Axel [Institutt for energiteknikk, OECD Halden Reactor Project, NO-1751 Halden (Norway)]. E-mail: bjorn.axel.gran@hrp.no; Fredriksen, Rune [Institutt for energiteknikk, OECD Halden Reactor Project, NO-1751 Halden (Norway)]. E-mail: rune.fredriksen@hrp.no; Thunem, Atoosa P.-J. [Institutt for energiteknikk, OECD Halden Reactor Project, NO-1751 Halden (Norway)]. E-mail: atoosa.p-j.thunem@hrp.no

    2007-11-15

    This paper describes how an approach for model-based risk assessment (MBRA) can be applied for addressing different dependability factors in a critical application. Dependability factors, such as availability, reliability, safety and security, are important when assessing the dependability degree of total systems involving digital instrumentation and control (I and C) sub-systems. In order to identify risk sources their roles with regard to intentional system aspects such as system functions, component behaviours and intercommunications must be clarified. Traditional risk assessment is based on fault or risk models of the system. In contrast to this, MBRA utilizes success-oriented models describing all intended system aspects, including functional, operational and organizational aspects of the target. The EU-funded CORAS project developed a tool-supported methodology for the application of MBRA in security-critical systems. The methodology has been tried out within the telemedicine and e-commerce areas, and provided through a series of seven trials a sound basis for risk assessments. In this paper the results from the CORAS project are presented, and it is discussed how the approach for applying MBRA meets the needs of a risk-informed Man-Technology-Organization (MTO) model, and how methodology can be applied as a part of a trust case development.

  6. A risk based model supporting long term maintenance and reinvestment strategy decision making

    Energy Technology Data Exchange (ETDEWEB)

    Sand, Kjell; Montard, Julien; Tremoen, Tord H.

    2010-02-15

    This Technical Report is a product from the project Risk-Based Distribution System Asset Management (short: RISK DSAM) - Work Package 3 Risk exposure on company/strategic level. In the report a concept for portfolio distribution system asset management is presented. The approach comprises four main steps: 1. Decide the asset base. 2. Divide the asset base into relevant archetypes. 3. Develop or select relevant maintenance and reinvestment strategies for the different archetypes. 4. Estimate risks and costs for each archetype for the relevant strategies. For the different steps guidelines are given and a proposal for implementation of the concept is given in terms of a proposed IT system architecture.To evaluate the feasibility of such a concept, a prototype was developed in by using Visual Basic macros in Excel using real technical data from a small DSO. The experience from using the prototype shows that the concept is realistic. All assets are included and depending of the ambition of the risk analysis both simple simulation models and more advanced might be embedded. Presentations of the concept for a utility engineers have receive positive feedback indicating that the concept is regarded as a practical way to develop risk based asset management strategies for the asset fleet. It should be noted that the concept should be applied on a company strategic level and is thus not designed to be applied for a specific project or asset decisions. For this, more detailed models with area specific information, topology etc. are needed. (Author)

  7. Component Degradation Susceptibilities As The Bases For Modeling Reactor Aging Risk

    International Nuclear Information System (INIS)

    Unwin, Stephen D.; Lowry, Peter P.; Toyooka, Michael Y.

    2010-01-01

    The extension of nuclear power plant operating licenses beyond 60 years in the United States will be necessary if we are to meet national energy needs while addressing the issues of carbon and climate. Characterizing the operating risks associated with aging reactors is problematic because the principal tool for risk-informed decision-making, Probabilistic Risk Assessment (PRA), is not ideally-suited to addressing aging systems. The components most likely to drive risk in an aging reactor - the passives - receive limited treatment in PRA, and furthermore, standard PRA methods are based on the assumption of stationary failure rates: a condition unlikely to be met in an aging system. A critical barrier to modeling passives aging on the wide scale required for a PRA is that there is seldom sufficient field data to populate parametric failure models, and nor is there the availability of practical physics models to predict out-year component reliability. The methodology described here circumvents some of these data and modeling needs by using materials degradation metrics, integrated with conventional PRA models, to produce risk importance measures for specific aging mechanisms and component types. We suggest that these measures have multiple applications, from the risk-screening of components to the prioritization of materials research.

  8. 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

  9. Physicologically Based Toxicokinetic Models of Tebuconazole and Application in Human Risk Assessment

    DEFF Research Database (Denmark)

    Jonsdottir, Svava Osk; Reffstrup, Trine Klein; Petersen, Annette

    2016-01-01

    (ADME) of tebuconazole. The developed models were validated on in vivo half-life data for rabbit with good results, and on plasma and tissue concentration-time course data of tebuconazole after i.v. administration in rabbit. In most cases, the predicted concentration levels were seen to be within......A series of physiologically based toxicokinetic (PBTK) models for tebuconazole were developed in four species, rat, rabbit, rhesus monkey, and human. The developed models were analyzed with respect to the application of the models in higher tier human risk assessment, and the prospect of using...... such models in risk assessment of cumulative and aggregate exposure is discussed. Relatively simple and biologically sound models were developed using available experimental data as parameters for describing the physiology of the species, as well as the absorption, distribution, metabolism, and elimination...

  10. A Risk Prediction Model for Sporadic CRC Based on Routine Lab Results.

    Science.gov (United States)

    Boursi, Ben; Mamtani, Ronac; Hwang, Wei-Ting; Haynes, Kevin; Yang, Yu-Xiao

    2016-07-01

    Current risk scores for colorectal cancer (CRC) are based on demographic and behavioral factors and have limited predictive values. To develop a novel risk prediction model for sporadic CRC using clinical and laboratory data in electronic medical records. We conducted a nested case-control study in a UK primary care database. Cases included those with a diagnostic code of CRC, aged 50-85. Each case was matched with four controls using incidence density sampling. CRC predictors were examined using univariate conditional logistic regression. Variables with p value CRC prediction models which included age, sex, height, obesity, ever smoking, alcohol dependence, and previous screening colonoscopy had an AUC of 0.58 (0.57-0.59) with poor goodness of fit. A laboratory-based model including hematocrit, MCV, lymphocytes, and neutrophil-lymphocyte ratio (NLR) had an AUC of 0.76 (0.76-0.77) and a McFadden's R2 of 0.21 with a NRI of 47.6 %. A combined model including sex, hemoglobin, MCV, white blood cells, platelets, NLR, and oral hypoglycemic use had an AUC of 0.80 (0.79-0.81) with a McFadden's R2 of 0.27 and a NRI of 60.7 %. Similar results were shown in an internal validation set. A laboratory-based risk model had good predictive power for sporadic CRC risk.

  11. Projecting Sexual and Injecting HIV Risks into Future Outcomes with Agent-Based Modeling

    Science.gov (United States)

    Bobashev, Georgiy V.; Morris, Robert J.; Zule, William A.

    Longitudinal studies of health outcomes for HIV could be very costly cumbersome and not representative of the risk population. Conversely, cross-sectional approaches could be representative but rely on the retrospective information to estimate prevalence and incidence. We present an Agent-based Modeling (ABM) approach where we use behavioral data from a cross-sectional representative study and project the behavior into the future so that the risks of acquiring HIV could be studied in a dynamical/temporal sense. We show how the blend of behavior and contact network factors (sexual, injecting) play the role in the risk of future HIV acquisition and time till obtaining HIV. We show which subjects are the most likely persons to get HIV in the next year, and whom they are likely to infect. We examine how different behaviors are related to the increase or decrease of HIV risks and how to estimate the quantifiable risk measures such as survival HIV free.

  12. 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)

  13. Holistic flood risk assessment using agent-based modelling: the case of Sint Maarten Island

    Science.gov (United States)

    Abayneh Abebe, Yared; Vojinovic, Zoran; Nikolic, Igor; Hammond, Michael; Sanchez, Arlex; Pelling, Mark

    2015-04-01

    Floods in coastal regions are regarded as one of the most dangerous and harmful disasters. Though commonly referred to as natural disasters, coastal floods are also attributable to various social, economic, historical and political issues. Rapid urbanisation in coastal areas combined with climate change and poor governance can lead to a significant increase in the risk of pluvial flooding coinciding with fluvial and coastal flooding posing a greater risk of devastation in coastal communities. Disasters that can be triggered by hydro-meteorological events are interconnected and interrelated with both human activities and natural processes. They, therefore, require holistic approaches to help understand their complexity in order to design and develop adaptive risk management approaches that minimise social and economic losses and environmental impacts, and increase resilience to such events. Being located in the North Atlantic Ocean, Sint Maarten is frequently subjected to hurricanes. In addition, the stormwater catchments and streams on Sint Maarten have several unique characteristics that contribute to the severity of flood-related impacts. Urban environments are usually situated in low-lying areas, with little consideration for stormwater drainage, and as such are subject to flash flooding. Hence, Sint Maarten authorities drafted policies to minimise the risk of flood-related disasters on the island. In this study, an agent-based model is designed and applied to understand the implications of introduced policies and regulations, and to understand how different actors' behaviours influence the formation, propagation and accumulation of flood risk. The agent-based model built for this study is based on the MAIA meta-model, which helps to decompose, structure and conceptualize socio-technical systems with an agent-oriented perspective, and is developed using the NetLogo simulation environment. The agents described in this model are households and businesses, and

  14. Fuzzy Comprehensive Evaluation of Ecological Risk Based on Cloud Model: Taking Chengchao Iron Mine as Example

    Science.gov (United States)

    Ruan, Jinghua; Chen, Yong; Xiao, Xiao; Yong, Gan; Huang, Ranran; Miao, Zuohua

    2018-01-01

    Aimed at the fuzziness and randomness during the evaluation process, this paper constructed a fuzzy comprehensive evaluation method based on cloud model. The evaluation index system was established based on the inherent risk, present level and control situation, which had been proved to be able to convey the main contradictions of ecological risk in mine on the macro level, and be advantageous for comparison among mines. The comment sets and membership functions improved by cloud model could reflect the uniformity of ambiguity and randomness effectively. In addition, the concept of fuzzy entropy was introduced to further characterize the fuzziness of assessments results and the complexities of ecological problems in target mine. A practical example in Chengchao Iron Mine evidenced that, the assessments results can reflect actual situations appropriately and provide a new theoretic guidance for comprehensive ecological risk evaluation of underground iron mine.

  15. Mean-variance model for portfolio optimization with background risk based on uncertainty theory

    Science.gov (United States)

    Zhai, Jia; Bai, Manying

    2018-04-01

    The aim of this paper is to develop a mean-variance model for portfolio optimization considering the background risk, liquidity and transaction cost based on uncertainty theory. In portfolio selection problem, returns of securities and assets liquidity are assumed as uncertain variables because of incidents or lacking of historical data, which are common in economic and social environment. We provide crisp forms of the model and a hybrid intelligent algorithm to solve it. Under a mean-variance framework, we analyze the portfolio frontier characteristic considering independently additive background risk. In addition, we discuss some effects of background risk and liquidity constraint on the portfolio selection. Finally, we demonstrate the proposed models by numerical simulations.

  16. Risk-based modelling of surface water quality: a case study of the Charles River, Massachusetts

    Science.gov (United States)

    McIntyre, Neil R.; Wagener, Thorsten; Wheater, Howard S.; Chapra, Steven C.

    2003-04-01

    A model of phytoplankton, dissolved oxygen and nutrients is presented and applied to the Charles River, Massachusetts within a framework of Monte Carlo simulation. The model parameters are conditioned using data from eight sampling stations along a 40 km stretch of the Charles River, during a (supposed) steady-state period in the summer of 1996, and the conditioned model is evaluated using data from later in the same year. Regional multi-objective sensitivity analysis is used to identify the parameters and pollution sources most affecting the various model outputs under the conditions observed during that summer. The effects of Monte Carlo sampling error are included in this analysis, and the observations which have least contributed to model conditioning are indicated. It is shown that the sensitivity analysis can be used to speculate about the factors responsible for undesirable levels of eutrophication, and to speculate about the risk of failure of nutrient reduction interventions at a number of strategic control sections. The analysis indicates that phosphorus stripping at the CRPCD wastewater treatment plant on the Charles River would be a high-risk intervention, especially for controlling eutrophication at the control sections further downstream. However, as the risk reflects the perceived scope for model error, it can only be recommended that more resources are invested in data collection and model evaluation. Furthermore, as the risk is based solely on water quality criteria, rather than broader environmental and economic objectives, the results need to be supported by detailed and extensive knowledge of the Charles River problem.

  17. An RES-Based Model for Risk Assessment and Prediction of Backbreak in Bench Blasting

    Science.gov (United States)

    Faramarzi, F.; Ebrahimi Farsangi, M. A.; Mansouri, H.

    2013-07-01

    Most blasting operations are associated with various forms of energy loss, emerging as environmental side effects of rock blasting, such as flyrock, vibration, airblast, and backbreak. Backbreak is an adverse phenomenon in rock blasting operations, which imposes risk and increases operation expenses because of safety reduction due to the instability of walls, poor fragmentation, and uneven burden in subsequent blasts. In this paper, based on the basic concepts of a rock engineering systems (RES) approach, a new model for the prediction of backbreak and the risk associated with a blast is presented. The newly suggested model involves 16 effective parameters on backbreak due to blasting, while retaining simplicity as well. The data for 30 blasts, carried out at Sungun copper mine, western Iran, were used to predict backbreak and the level of risk corresponding to each blast by the RES-based model. The results obtained were compared with the backbreak measured for each blast, which showed that the level of risk achieved is in consistence with the backbreak measured. The maximum level of risk [vulnerability index (VI) = 60] was associated with blast No. 2, for which the corresponding average backbreak was the highest achieved (9.25 m). Also, for blasts with levels of risk under 40, the minimum average backbreaks (<4 m) were observed. Furthermore, to evaluate the model performance for backbreak prediction, the coefficient of correlation ( R 2) and root mean square error (RMSE) of the model were calculated ( R 2 = 0.8; RMSE = 1.07), indicating the good performance of the model.

  18. The determination of risk areas for muddy floods based on a worst-case erosion modelling

    Science.gov (United States)

    Saathoff, Ulfert; Schindewolf, Marcus; Annika Arévalo, Sarah

    2013-04-01

    Soil erosion and muddy floods are a frequently occurring hazard in the German state of Saxony, because of the topography and the high relief energy together with the high proportion of arable land. Still, the events are rather heterogeneously distributed and we do not know where damage is likely to occur. The goal of this study is to locate hot spots for the risk of muddy floods, with the objective to prevent high economic damage in future. We applied a soil erosion and deposition map of Saxony, calculated with the process based soil erosion model EROSION 3D. This map shows the potential soil erosion and transported sediment for worst case soil conditions and a 10 year rain storm event. Furthermore, a map of the current landuse in the state is used. From the landuse map, we extracted those areas that are especially vulnerable to muddy floods, like residential and industrial areas, infrastructural facilities (e.g. power plants, hospitals) and highways. In combination with the output of the soil erosion model, the amount of sediment, that enters each single landuse entity, is calculated. Based on this data, a state-wide map with classified risks is created. The results are furthermore used to identify the risk of muddy floods for each single municipality in Saxony. The results are evaluated with data of real occurred muddy flood events with documented locations during the period between 2000 and 2010. Additionally, plausibility tests are performed for selected areas (examination of landuse, topography and soil). The results prove to be plausible and most of the documented events can be explained by the modelled risk map. The created map can be used by different institutions like city and traffic planners, to estimate the risk of muddy flood occurrence at specific locations. Furthermore, the risk map can serve insurance companies to evaluate the insurance risk of a building. To make them easily accessible, the risk map will be published online via a web GIS

  19. Physics-Based Identification, Modeling and Risk Management for Aeroelastic Flutter and Limit-Cycle Oscillations (LCO), Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed research program will develop a physics-based identification, modeling and risk management infrastructure for aeroelastic transonic flutter and...

  20. Surface water flood risk and management strategies for London: An Agent-Based Model approach

    Directory of Open Access Journals (Sweden)

    Jenkins Katie

    2016-01-01

    Full Text Available Flooding is recognised as one of the most common and costliest natural disasters in England. Flooding in urban areas during heavy rainfall is known as ‘surface water flooding’, considered to be the most likely cause of flood events and one of the greatest short-term climate risks for London. In this paper we present results from a novel Agent-Based Model designed to assess the interplay between different adaptation options, different agents, and the role of flood insurance and the flood insurance pool, Flood Re, in the context of climate change. The model illustrates how investment in adaptation options could reduce London’s surface water flood risk, today and in the future. However, benefits can be outweighed by continued development in high risk areas and the effects of climate change. Flood Re is beneficial in its function to provide affordable insurance, even under climate change. However, it offers no additional benefits in terms of overall risk reduction, and will face increasing pressure due to rising surface water flood risk in the future. The modelling approach and findings are highly relevant for reviewing the proposed Flood Re scheme, as well as for wider discussions on the potential of insurance schemes, and broader multi-sectoral partnerships, to incentivise flood risk management in the UK and internationally.

  1. Intelligent judgements over health risks in a spatial agent-based model.

    Science.gov (United States)

    Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

    2018-03-20

    Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of

  2. Data Sources for the Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

    Science.gov (United States)

    The model-based estimates of important cancer risk factors and screening behaviors are obtained by combining the responses to the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS).

  3. Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling

    Directory of Open Access Journals (Sweden)

    Yvonne Walz

    2015-11-01

    Full Text Available Schistosomiasis is a widespread water-based disease that puts close to 800 million people at risk of infection with more than 250 million infected, mainly in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and the frequency, duration and extent of human bodies exposed to infested water sources during human water contact. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. Since schistosomiasis risk profiling based on remote sensing data inherits a conceptual drawback if school-based disease prevalence data are directly related to the remote sensing measurements extracted at the location of the school, because the disease transmission usually does not exactly occur at the school, we took the local environment around the schools into account by explicitly linking ecologically relevant environmental information of potential disease transmission sites to survey measurements of disease prevalence. Our models were validated at two sites with different landscapes in Côte d’Ivoire using high- and moderateresolution remote sensing data based on random forest and partial least squares regression. We found that the ecologically relevant modelling approach explained up to 70% of the variation in Schistosoma infection prevalence and performed better compared to a purely pixelbased modelling approach. Furthermore, our study showed that model performance increased as a function of enlarging the school catchment area, confirming the hypothesis that suitable environments for schistosomiasis transmission rarely occur at the location of survey measurements.

  4. 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

  5. A Risk-Based Interval Two-Stage Programming Model for Agricultural System Management under Uncertainty

    Directory of Open Access Journals (Sweden)

    Ye Xu

    2016-01-01

    Full Text Available Nonpoint source (NPS pollution caused by agricultural activities is main reason that water quality in watershed becomes worse, even leading to deterioration. Moreover, pollution control is accompanied with revenue’s fall for agricultural system. How to design and generate a cost-effective and environmentally friendly agricultural production pattern is a critical issue for local managers. In this study, a risk-based interval two-stage programming model (RBITSP was developed. Compared to general ITSP model, significant contribution made by RBITSP model was that it emphasized importance of financial risk under various probabilistic levels, rather than only being concentrated on expected economic benefit, where risk is expressed as the probability of not meeting target profit under each individual scenario realization. This way effectively avoided solutions’ inaccuracy caused by traditional expected objective function and generated a variety of solutions through adjusting weight coefficients, which reflected trade-off between system economy and reliability. A case study of agricultural production management with the Tai Lake watershed was used to demonstrate superiority of proposed model. Obtained results could be a base for designing land-structure adjustment patterns and farmland retirement schemes and realizing balance of system benefit, system-failure risk, and water-body protection.

  6. Stimulating household flood risk mitigation investments through insurance and subsidies: an Agent-Based Modelling approach

    Science.gov (United States)

    Haer, Toon; Botzen, Wouter; de Moel, Hans; Aerts, Jeroen

    2015-04-01

    In the period 1998-2009, floods triggered roughly 52 billion euro in insured economic losses making floods the most costly natural hazard in Europe. Climate change and socio/economic trends are expected to further aggrevate floods losses in many regions. Research shows that flood risk can be significantly reduced if households install protective measures, and that the implementation of such measures can be stimulated through flood insurance schemes and subsidies. However, the effectiveness of such incentives to stimulate implementation of loss-reducing measures greatly depends on the decision process of individuals and is hardly studied. In our study, we developed an Agent-Based Model that integrates flood damage models, insurance mechanisms, subsidies, and household behaviour models to assess the effectiveness of different economic tools on stimulating households to invest in loss-reducing measures. Since the effectiveness depends on the decision making process of individuals, the study compares different household decision models ranging from standard economic models, to economic models for decision making under risk, to more complex decision models integrating economic models and risk perceptions, opinion dynamics, and the influence of flood experience. The results show the effectiveness of incentives to stimulate investment in loss-reducing measures for different household behavior types, while assuming climate change scenarios. It shows how complex decision models can better reproduce observed real-world behaviour compared to traditional economic models. Furthermore, since flood events are included in the simulations, the results provide an analysis of the dynamics in insured and uninsured losses for households, the costs of reducing risk by implementing loss-reducing measures, the capacity of the insurance market, and the cost of government subsidies under different scenarios. The model has been applied to the City of Rotterdam in The Netherlands.

  7. Physics-Based Fragment Acceleration Modeling for Pressurized Tank Burst Risk Assessments

    Science.gov (United States)

    Manning, Ted A.; Lawrence, Scott L.

    2014-01-01

    As part of comprehensive efforts to develop physics-based risk assessment techniques for space systems at NASA, coupled computational fluid and rigid body dynamic simulations were carried out to investigate the flow mechanisms that accelerate tank fragments in bursting pressurized vessels. Simulations of several configurations were compared to analyses based on the industry-standard Baker explosion model, and were used to formulate an improved version of the model. The standard model, which neglects an external fluid, was found to agree best with simulation results only in configurations where the internal-to-external pressure ratio is very high and fragment curvature is small. The improved model introduces terms that accommodate an external fluid and better account for variations based on circumferential fragment count. Physics-based analysis was critical in increasing the model's range of applicability. The improved tank burst model can be used to produce more accurate risk assessments of space vehicle failure modes that involve high-speed debris, such as exploding propellant tanks and bursting rocket engines.

  8. Causal Loop-based Modeling on System Dynamics for Risk Communication

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Chang Ju [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of); Kang, Kyung Min [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2009-10-15

    It is true that a national policy should be based on public confidence, analyzing their recognition and attitude on life safety, since they have very special risk perception characteristics. For achieving effective public consensus regarding a national policy such as nuclear power, we have to utilize a risk communication (hereafter, calls RiCom) process. However, domestic research models on RiCom process do not provide a practical guideline, because most of them are still superficial and stick on an administrative aspect. Also, most of current models have no experience in terms of verification and validation for effective applications to diverse stake holders. This study focuses on public's dynamic mechanism through the modeling on system dynamics, basically utilizing casual loop diagram (CLD) and stock flow diagram (SFD), which regards as a critical technique for decision making in many industrial RiCom models.

  9. Causal Loop-based Modeling on System Dynamics for Risk Communication

    International Nuclear Information System (INIS)

    Lee, Chang Ju; Kang, Kyung Min

    2009-01-01

    It is true that a national policy should be based on public confidence, analyzing their recognition and attitude on life safety, since they have very special risk perception characteristics. For achieving effective public consensus regarding a national policy such as nuclear power, we have to utilize a risk communication (hereafter, calls RiCom) process. However, domestic research models on RiCom process do not provide a practical guideline, because most of them are still superficial and stick on an administrative aspect. Also, most of current models have no experience in terms of verification and validation for effective applications to diverse stake holders. This study focuses on public's dynamic mechanism through the modeling on system dynamics, basically utilizing casual loop diagram (CLD) and stock flow diagram (SFD), which regards as a critical technique for decision making in many industrial RiCom models

  10. A Nonparametric Operational Risk Modeling Approach Based on Cornish-Fisher Expansion

    Directory of Open Access Journals (Sweden)

    Xiaoqian Zhu

    2014-01-01

    Full Text Available It is generally accepted that the choice of severity distribution in loss distribution approach has a significant effect on the operational risk capital estimation. However, the usually used parametric approaches with predefined distribution assumption might be not able to fit the severity distribution accurately. The objective of this paper is to propose a nonparametric operational risk modeling approach based on Cornish-Fisher expansion. In this approach, the samples of severity are generated by Cornish-Fisher expansion and then used in the Monte Carlo simulation to sketch the annual operational loss distribution. In the experiment, the proposed approach is employed to calculate the operational risk capital charge for the overall Chinese banking. The experiment dataset is the most comprehensive operational risk dataset in China as far as we know. The results show that the proposed approach is able to use the information of high order moments and might be more effective and stable than the usually used parametric approach.

  11. Environmental risk assessment of selected organic chemicals based on TOC test and QSAR estimation models.

    Science.gov (United States)

    Chi, Yulang; Zhang, Huanteng; Huang, Qiansheng; Lin, Yi; Ye, Guozhu; Zhu, Huimin; Dong, Sijun

    2018-02-01

    Environmental risks of organic chemicals have been greatly determined by their persistence, bioaccumulation, and toxicity (PBT) and physicochemical properties. Major regulations in different countries and regions identify chemicals according to their bioconcentration factor (BCF) and octanol-water partition coefficient (Kow), which frequently displays a substantial correlation with the sediment sorption coefficient (Koc). Half-life or degradability is crucial for the persistence evaluation of chemicals. Quantitative structure activity relationship (QSAR) estimation models are indispensable for predicting environmental fate and health effects in the absence of field- or laboratory-based data. In this study, 39 chemicals of high concern were chosen for half-life testing based on total organic carbon (TOC) degradation, and two widely accepted and highly used QSAR estimation models (i.e., EPI Suite and PBT Profiler) were adopted for environmental risk evaluation. The experimental results and estimated data, as well as the two model-based results were compared, based on the water solubility, Kow, Koc, BCF and half-life. Environmental risk assessment of the selected compounds was achieved by combining experimental data and estimation models. It was concluded that both EPI Suite and PBT Profiler were fairly accurate in measuring the physicochemical properties and degradation half-lives for water, soil, and sediment. However, the half-lives between the experimental and the estimated results were still not absolutely consistent. This suggests deficiencies of the prediction models in some ways, and the necessity to combine the experimental data and predicted results for the evaluation of environmental fate and risks of pollutants. Copyright © 2016. Published by Elsevier B.V.

  12. WRF-based fire risk modelling and evaluation for years 2010 and 2012 in Poland

    Science.gov (United States)

    Stec, Magdalena; Szymanowski, Mariusz; Kryza, Maciej

    2016-04-01

    Wildfires are one of the main ecosystems' disturbances for forested, seminatural and agricultural areas. They generate significant economic loss, especially in forest management and agriculture. Forest fire risk modeling is therefore essential e.g. for forestry administration. In August 2015 a new method of forest fire risk forecasting entered into force in Poland. The method allows to predict a fire risk level in a 4-degree scale (0 - no risk, 3 - highest risk) and consists of a set of linearized regression equations. Meteorological information is used as predictors in regression equations, with air temperature, relative humidity, average wind speed, cloudiness and rainfall. The equations include also pine litter humidity as a measure of potential fuel characteristics. All these parameters are measured routinely in Poland at 42 basic and 94 auxiliary sites. The fire risk level is estimated for a current (basing on morning measurements) or next day (basing on midday measurements). Entire country is divided into 42 prognostic zones, and fire risk level for each zone is taken from the closest measuring site. The first goal of this work is to assess if the measurements needed for fire risk forecasting may be replaced by the data from mesoscale meteorological model. Additionally, the use of a meteorological model would allow to take into account much more realistic spatial differentiation of weather elements determining the fire risk level instead of discrete point-made measurements. Meteorological data have been calculated using the Weather Research and Forecasting model (WRF). For the purpose of this study the WRF model is run in the reanalysis mode allowing to estimate all required meteorological data in a 5-kilometers grid. The only parameter that cannot be directly calculated using WRF is the litter humidity, which has been estimated using empirical formula developed by Sakowska (2007). The experiments are carried out for two selected years: 2010 and 2012. The

  13. Risk Evaluation of Railway Coal Transportation Network Based on Multi Level Grey Evaluation Model

    Science.gov (United States)

    Niu, Wei; Wang, Xifu

    2018-01-01

    The railway transport mode is currently the most important way of coal transportation, and now China’s railway coal transportation network has become increasingly perfect, but there is still insufficient capacity, some lines close to saturation and other issues. In this paper, the theory and method of risk assessment, analytic hierarchy process and multi-level gray evaluation model are applied to the risk evaluation of coal railway transportation network in China. Based on the example analysis of Shanxi railway coal transportation network, to improve the internal structure and the competitiveness of the market.

  14. A risk-return based model to measure the performance of portfolio management

    Directory of Open Access Journals (Sweden)

    Hamid Reza Vakili Fard

    2014-10-01

    Full Text Available The primary concern in all portfolio management systems is to find a good tradeoff between risk and expected return and a good balance between accepted risk and actual return indicates the performance of a particular portfolio. This paper develops “A-Y Model” to measure the performance of a portfolio and analyze it during the bull and the bear market. This paper considers the daily information of one year before and one year after Iran's 2013 precedential election. The proposed model of this paper provides lost profit and unrealized loss to measure the portfolio performance. The proposed study first ranks the resulted data and then uses some non-parametric methods to see whether there is any change because of the changes in markets on the performance of the portfolio. The results indicate that despite increasing profitable opportunities in bull market, the performance of the portfolio did not match the target risk. As a result, using A-Y Model as a risk and return base model to measure portfolio management's performance appears to reduce risks and increases return of portfolio.

  15. 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

  16. Life cycle cost-based risk model for energy performance contracting retrofits

    Science.gov (United States)

    Berghorn, George H.

    Buildings account for 41% of the primary energy consumption in the United States, nearly half of which is accounted for by commercial buildings. Among the greatest energy users are those in the municipalities, universities, schools, and hospitals (MUSH) market. Correctional facilities are in the upper half of all commercial building types for energy intensity. Public agencies have experienced reduced capital budgets to fund retrofits; this has led to the increased use of energy performance contracts (EPC), which are implemented by energy services companies (ESCOs). These companies guarantee a minimum amount of energy savings resulting from the retrofit activities, which in essence transfers performance risk from the owner to the contractor. Building retrofits in the MUSH market, especially correctional facilities, are well-suited to EPC, yet despite this potential and their high energy intensities, efficiency improvements lag behind that of other public building types. Complexities in project execution, lack of support for data requests and sub-metering, and conflicting project objectives have been cited as reasons for this lag effect. As a result, project-level risks must be understood in order to support wider adoption of retrofits in the public market, in particular the correctional facility sub-market. The goal of this research is to understand risks related to the execution of energy efficiency retrofits delivered via EPC in the MUSH market. To achieve this goal, in-depth analysis and improved understanding was sought with regard to ESCO risks that are unique to EPC in this market. The proposed work contributes to this understanding by developing a life cycle cost-based risk model to improve project decision making with regard to risk control and reduction. The specific objectives of the research are: (1) to perform an exploratory analysis of the EPC retrofit process and identify key areas of performance risk requiring in-depth analysis; (2) to construct a

  17. Physiologically Based Toxicokinetic Modelling as a Tool to Support Risk Assessment: Three Case Studies

    Directory of Open Access Journals (Sweden)

    Hans Mielke

    2012-01-01

    Full Text Available In this contribution we present three case studies of physiologically based toxicokinetic (PBTK modelling in regulatory risk assessment. (1 Age-dependent lower enzyme expression in the newborn leads to bisphenol A (BPA blood levels which are near the levels of the tolerated daily intake (TDI at the oral exposure as calculated by EFSA. (2 Dermal exposure of BPA by receipts, car park tickets, and so forth, contribute to the exposure towards BPA. However, at the present levels of dermal exposure there is no risk for the adult. (3 Dermal exposure towards coumarin via cosmetic products leads to external exposures of two-fold the TDI. PBTK modeling helped to identify liver peak concentration as the metric for liver toxicity. After dermal exposure of twice the TDI, the liver peak concentration was lower than that present after oral exposure with the TDI dose. In the presented cases, PBTK modeling was useful to reach scientifically sound regulatory decisions.

  18. A risk-based model for maintenance decision support of civil structures using RAMS

    NARCIS (Netherlands)

    Viana Da Rocha, T. C.; Stipanovic, I.; Hartmann, A.; Bakker, J.

    2017-01-01

    As a cornerstone of transportation asset management, risk-based approaches have been used to support maintenance decisions of civil structures. However, ambiguous and subjective risk criteria and inconsistency on the use of risk-based approaches can lead to a fuzzy understanding of the risks

  19. Evaluating the Risk of Metabolic Syndrome Based on an Artificial Intelligence Model

    Directory of Open Access Journals (Sweden)

    Hui Chen

    2014-01-01

    Full Text Available Metabolic syndrome is worldwide public health problem and is a serious threat to people's health and lives. Understanding the relationship between metabolic syndrome and the physical symptoms is a difficult and challenging task, and few studies have been performed in this field. It is important to classify adults who are at high risk of metabolic syndrome without having to use a biochemical index and, likewise, it is important to develop technology that has a high economic rate of return to simplify the complexity of this detection. In this paper, an artificial intelligence model was developed to identify adults at risk of metabolic syndrome based on physical signs; this artificial intelligence model achieved more powerful capacity for classification compared to the PCLR (principal component logistic regression model. A case study was performed based on the physical signs data, without using a biochemical index, that was collected from the staff of Lanzhou Grid Company in Gansu province of China. The results show that the developed artificial intelligence model is an effective classification system for identifying individuals at high risk of metabolic syndrome.

  20. Developing scenarios to assess future landslide risks: a model-based approach applied to mountainous regions

    Science.gov (United States)

    Vacquie, Laure; Houet, Thomas

    2016-04-01

    In the last century, European mountain landscapes have experienced significant transformations. Natural and anthropogenic changes, climate changes, touristic and industrial development, socio-economic interactions, and their implications in terms of LUCC (land use and land cover changes) have directly influenced the spatial organization and vulnerability of mountain landscapes. This study is conducted as part of the SAMCO project founded by the French National Science Agency (ANR). It aims at developing a methodological approach, combining various tools, modelling platforms and methods, to identify vulnerable regions to landslide hazards accounting for futures LUCC. It presents an integrated approach combining participative scenarios and a LULC changes simulation models to assess the combined effects of LUCC and climate change on landslide risks in the Cauterets valley (French Pyrenees Mountains) up to 2100. Through vulnerability and risk mapping, the objective is to gather information to support landscape planning and implement land use strategies with local stakeholders for risk management. Four contrasting scenarios are developed and exhibit contrasting trajectories of socio-economic development. Prospective scenarios are based on national and international socio-economic contexts relying on existing assessment reports. The methodological approach integrates knowledge from local stakeholders to refine each scenario during their construction and to reinforce their plausibility and relevance by accounting for local specificities, e.g. logging and pastoral activities, touristic development, urban planning, etc. A process-based model, the Forecasting Scenarios for Mountains (ForeSceM) model, developed on the Dinamica Ego modelling platform is used to spatially allocate futures LUCC for each prospective scenario. Concurrently, a spatial decision support tool, i.e. the SYLVACCESS model, is used to identify accessible areas for forestry in scenario projecting logging

  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. A multiparametric magnetic resonance imaging-based risk model to determine the risk of significant prostate cancer prior to biopsy.

    Science.gov (United States)

    van Leeuwen, Pim J; Hayen, Andrew; Thompson, James E; Moses, Daniel; Shnier, Ron; Böhm, Maret; Abuodha, Magdaline; Haynes, Anne-Maree; Ting, Francis; Barentsz, Jelle; Roobol, Monique; Vass, Justin; Rasiah, Krishan; Delprado, Warick; Stricker, Phillip D

    2017-12-01

    To develop and externally validate a predictive model for detection of significant prostate cancer. Development of the model was based on a prospective cohort including 393 men who underwent multiparametric magnetic resonance imaging (mpMRI) before biopsy. External validity of the model was then examined retrospectively in 198 men from a separate institution whom underwent mpMRI followed by biopsy for abnormal prostate-specific antigen (PSA) level or digital rectal examination (DRE). A model was developed with age, PSA level, DRE, prostate volume, previous biopsy, and Prostate Imaging Reporting and Data System (PIRADS) score, as predictors for significant prostate cancer (Gleason 7 with >5% grade 4, ≥20% cores positive or ≥7 mm of cancer in any core). Probability was studied via logistic regression. Discriminatory performance was quantified by concordance statistics and internally validated with bootstrap resampling. In all, 393 men had complete data and 149 (37.9%) had significant prostate cancer. While the variable model had good accuracy in predicting significant prostate cancer, area under the curve (AUC) of 0.80, the advanced model (incorporating mpMRI) had a significantly higher AUC of 0.88 (P prostate cancer. Individualised risk assessment of significant prostate cancer using a predictive model that incorporates mpMRI PIRADS score and clinical data allows a considerable reduction in unnecessary biopsies and reduction of the risk of over-detection of insignificant prostate cancer at the cost of a very small increase in the number of significant cancers missed. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

  3. 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...

  4. Evaluation of three physiologically based pharmacokinetic (PBPK) modeling tools for emergency risk assessment after acute dichloromethane exposure

    NARCIS (Netherlands)

    Boerleider, R. Z.; Olie, J. D N; van Eijkeren, J. C H; Bos, P. M J; Hof, B. G H; de Vries, I.; Bessems, J. G M; Meulenbelt, J.; Hunault, C. C.

    2015-01-01

    Introduction: Physiologically based pharmacokinetic (PBPK) models may be useful in emergency risk assessment, after acute exposure to chemicals, such as dichloromethane (DCM). We evaluated the applicability of three PBPK models for human risk assessment following a single exposure to DCM: one model

  5. Large-scale model-based assessment of deer-vehicle collision risk.

    Directory of Open Access Journals (Sweden)

    Torsten Hothorn

    Full Text Available Ungulates, in particular the Central European roe deer Capreolus capreolus and the North American white-tailed deer Odocoileus virginianus, are economically and ecologically important. The two species are risk factors for deer-vehicle collisions and as browsers of palatable trees have implications for forest regeneration. However, no large-scale management systems for ungulates have been implemented, mainly because of the high efforts and costs associated with attempts to estimate population sizes of free-living ungulates living in a complex landscape. Attempts to directly estimate population sizes of deer are problematic owing to poor data quality and lack of spatial representation on larger scales. We used data on >74,000 deer-vehicle collisions observed in 2006 and 2009 in Bavaria, Germany, to model the local risk of deer-vehicle collisions and to investigate the relationship between deer-vehicle collisions and both environmental conditions and browsing intensities. An innovative modelling approach for the number of deer-vehicle collisions, which allows nonlinear environment-deer relationships and assessment of spatial heterogeneity, was the basis for estimating the local risk of collisions for specific road types on the scale of Bavarian municipalities. Based on this risk model, we propose a new "deer-vehicle collision index" for deer management. We show that the risk of deer-vehicle collisions is positively correlated to browsing intensity and to harvest numbers. Overall, our results demonstrate that the number of deer-vehicle collisions can be predicted with high precision on the scale of municipalities. In the densely populated and intensively used landscapes of Central Europe and North America, a model-based risk assessment for deer-vehicle collisions provides a cost-efficient instrument for deer management on the landscape scale. The measures derived from our model provide valuable information for planning road protection and defining

  6. Home-Based Risk of Falling Assessment Test Using a Closed-Loop Balance Model.

    Science.gov (United States)

    Ayena, Johannes C; Zaibi, Helmi; Otis, Martin J-D; Menelas, Bob-Antoine J

    2016-12-01

    The aim of this study is to improve and facilitate the methods used to assess risk of falling at home among older people through the computation of a risk of falling in real time in daily activities. In order to increase a real time computation of the risk of falling, a closed-loop balance model is proposed and compared with One-Leg Standing Test (OLST). This balance model allows studying the postural response of a person having an unpredictable perturbation. Twenty-nine volunteers participated in this study for evaluating the effectiveness of the proposed system which includes seventeen elder participants: ten healthy elderly ( 68.4 ±5.5 years), seven Parkinson's disease (PD) subjects ( 66.28 ±8.9 years), and twelve healthy young adults ( 28.27 ±3.74 years). Our work suggests that there is a relationship between OLST score and the risk of falling based on center of pressure measurement with four low cost force sensors located inside an instrumented insole, which could be predicted using our suggested closed-loop balance model. For long term monitoring at home, this system could be included in a medical electronic record and could be useful as a diagnostic aid tool.

  7. A Simple Model to Rank Shellfish Farming Areas Based on the Risk of Disease Introduction and Spread.

    Science.gov (United States)

    Thrush, M A; Pearce, F M; Gubbins, M J; Oidtmann, B C; Peeler, E J

    2017-08-01

    The European Union Council Directive 2006/88/EC requires that risk-based surveillance (RBS) for listed aquatic animal diseases is applied to all aquaculture production businesses. The principle behind this is the efficient use of resources directed towards high-risk farm categories, animal types and geographic areas. To achieve this requirement, fish and shellfish farms must be ranked according to their risk of disease introduction and spread. We present a method to risk rank shellfish farming areas based on the risk of disease introduction and spread and demonstrate how the approach was applied in 45 shellfish farming areas in England and Wales. Ten parameters were used to inform the risk model, which were grouped into four risk themes based on related pathways for transmission of pathogens: (i) live animal movement, (ii) transmission via water, (iii) short distance mechanical spread (birds) and (iv) long distance mechanical spread (vessels). Weights (informed by expert knowledge) were applied both to individual parameters and to risk themes for introduction and spread to reflect their relative importance. A spreadsheet model was developed to determine quantitative scores for the risk of pathogen introduction and risk of pathogen spread for each shellfish farming area. These scores were used to independently rank areas for risk of introduction and for risk of spread. Thresholds were set to establish risk categories (low, medium and high) for introduction and spread based on risk scores. Risk categories for introduction and spread for each area were combined to provide overall risk categories to inform a risk-based surveillance programme directed at the area level. Applying the combined risk category designation framework for risk of introduction and spread suggested by European Commission guidance for risk-based surveillance, 4, 10 and 31 areas were classified as high, medium and low risk, respectively. © 2016 Crown copyright.

  8. A Two-Account Life Insurance Model for Scenario-Based Valuation Including Event Risk

    Directory of Open Access Journals (Sweden)

    Ninna Reitzel Jensen

    2015-06-01

    Full Text Available Using a two-account model with event risk, we model life insurance contracts taking into account both guaranteed and non-guaranteed payments in participating life insurance as well as in unit-linked insurance. Here, event risk is used as a generic term for life insurance events, such as death, disability, etc. In our treatment of participating life insurance, we have special focus on the bonus schemes “consolidation” and “additional benefits”, and one goal is to formalize how these work and interact. Another goal is to describe similarities and differences between participating life insurance and unit-linked insurance. By use of a two-account model, we are able to illustrate general concepts without making the model too abstract. To allow for complicated financial markets without dramatically increasing the mathematical complexity, we focus on economic scenarios. We illustrate the use of our model by conducting scenario analysis based on Monte Carlo simulation, but the model applies to scenarios in general and to worst-case and best-estimate scenarios in particular. In addition to easy computations, our model offers a common framework for the valuation of life insurance payments across product types. This enables comparison of participating life insurance products and unit-linked insurance products, thus building a bridge between the two different ways of formalizing life insurance products. Finally, our model distinguishes itself from the existing literature by taking into account the Markov model for the state of the policyholder and, hereby, facilitating event risk.

  9. 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.

  10. Innovative Models of Dental Care Delivery and Coverage: Patient-Centric Dental Benefits Based on Digital Oral Health Risk Assessment.

    Science.gov (United States)

    Martin, John; Mills, Shannon; Foley, Mary E

    2018-04-01

    Innovative models of dental care delivery and coverage are emerging across oral health care systems causing changes to treatment and benefit plans. A novel addition to these models is digital risk assessment, which offers a promising new approach that incorporates the use of a cloud-based technology platform to assess an individual patient's risk for oral disease. Risk assessment changes treatment by including risk as a modifier of treatment and as a determinant of preventive services. Benefit plans are being developed to use risk assessment to predetermine preventive benefits for patients identified at elevated risk for oral disease. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. 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.

  12. 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.

  13. Model-Based Estimation of Collision Risks of Predatory Birds with Wind Turbines

    Directory of Open Access Journals (Sweden)

    Marcus Eichhorn

    2012-06-01

    Full Text Available The expansion of renewable energies, such as wind power, is a promising way of mitigating climate change. Because of the risk of collision with rotor blades, wind turbines have negative effects on local bird populations, particularly on raptors such as the Red Kite (Milvus milvus. Appropriate assessment tools for these effects have been lacking. To close this gap, we have developed an agent-based, spatially explicit model that simulates the foraging behavior of the Red Kite around its aerie in a landscape consisting of different land-use types. We determined the collision risk of the Red Kite with the turbine as a function of the distance between the wind turbine and the aerie and other parameters. The impact function comprises the synergistic effects of species-specific foraging behavior and landscape structure. The collision risk declines exponentially with increasing distance. The strength of this decline depends on the raptor's foraging behavior, its ability to avoid wind turbines, and the mean wind speed in the region. The collision risks, which are estimated by the simulation model, are in the range of values observed in the field. The derived impact function shows that the collision risk can be described as an aggregated function of distance between the wind turbine and the raptor's aerie. This allows an easy and rapid assessment of the ecological impacts of (existing or planned wind turbines in relation to their spatial location. Furthermore, it implies that minimum buffer zones for different landscapes can be determined in a defensible way. This modeling approach can be extended to other bird species with central-place foraging behavior. It provides a helpful tool for landscape planning aimed at minimizing the impacts of wind power on biodiversity.

  14. A Model-based Framework for Risk Assessment in Human-Computer Controlled Systems

    Science.gov (United States)

    Hatanaka, Iwao

    2000-01-01

    The rapid growth of computer technology and innovation has played a significant role in the rise of computer automation of human tasks in modem production systems across all industries. Although the rationale for automation has been to eliminate "human error" or to relieve humans from manual repetitive tasks, various computer-related hazards and accidents have emerged as a direct result of increased system complexity attributed to computer automation. The risk assessment techniques utilized for electromechanical systems are not suitable for today's software-intensive systems or complex human-computer controlled systems. This thesis will propose a new systemic model-based framework for analyzing risk in safety-critical systems where both computers and humans are controlling safety-critical functions. A new systems accident model will be developed based upon modem systems theory and human cognitive processes to better characterize system accidents, the role of human operators, and the influence of software in its direct control of significant system functions. Better risk assessments will then be achievable through the application of this new framework to complex human-computer controlled systems.

  15. 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...

  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. IT Operational Risk Measurement Model Based on Internal Loss Data of Banks

    Science.gov (United States)

    Hao, Xiaoling

    Business operation of banks relies increasingly on information technology (IT) and the most important role of IT is to guarantee the operational continuity of business process. Therefore, IT Risk management efforts need to be seen from the perspective of operational continuity. Traditional IT risk studies focused on IT asset-based risk analysis and risk-matrix based qualitative risk evaluation. In practice, IT risk management practices of banking industry are still limited to the IT department and aren't integrated into business risk management, which causes the two departments to work in isolation. This paper presents an improved methodology for dealing with IT operational risk. It adopts quantitative measurement method, based on the internal business loss data about IT events, and uses Monte Carlo simulation to predict the potential losses. We establish the correlation between the IT resources and business processes to make sure risk management of IT and business can work synergistically.

  18. Development of good modelling practice for phsiologically based pharmacokinetic models for use in risk assessment: The first steps

    Science.gov (United States)

    The increasing use of tissue dosimetry estimated using pharmacokinetic models in chemical risk assessments in multiple countries necessitates the need to develop internationally recognized good modelling practices. These practices would facilitate sharing of models and model eva...

  19. 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.

  20. Modelling domestic stock energy use and heat-related health risk : a GIS-based bottom-up modelling approach

    Energy Technology Data Exchange (ETDEWEB)

    Mavrogianni, A.; Davies, M. [Univ. College London, London (United Kingdom). Bartlett School of Graduate Studies; Chalabi, Z.; Wilkinson, P. [London School of Hygiene and Tropical Medecine, London (United Kingdom); Kolokotroni, M. [Brunel Univ., London (United Kingdom). School of Engineering Design

    2009-07-01

    Approximately 8 per cent of the carbon dioxide (CO{sub 2}) emissions produced in the United Kingdom are produced in London, one of the fastest growing cities worldwide. Based on the projected rates of population and economic growth, a 15 per cent increase of emissions is predicted. In addition to the national target to cut emissions by 80 per cent by 2050, the Mayor of London Climate Change Action Plan set a target to reduce London's CO{sub 2} emissions by 60 per cent by 2025. Significant carbon savings can be achieved in the building sector, particularly since 38 per cent of the total delivered energy in London is associated with domestic energy use. This paper demonstrated a systematic approach towards exploring the impact of urban built form and the combined effect of climate change and the urban heat island (UHI) phenomenon on the levels of domestic energy consumption and heat-related health risk in London. It presented work in progress on the development of a GIS-based energy consumption model and heat vulnerability index of the Greater London Area domestic stock. Comparison of the model output for 10 case study areas with topdown energy statistics revealed that the model successfully ranks areas based on their domestic space heating demand. The health module can be used to determine environments prone to higher risk of heat stress by investigating urban texture factors. A newly developed epidemiological model will be feed into the health module to examine the influence on risk of heat-related mortality of local urban built form characteristics. The epidemiological model is based on multi-variable analysis of deaths during heat wave and non-heat wave days. 29 refs., 1 tab., 7 figs.

  1. Combined prediction model for supply risk in nuclear power equipment manufacturing industry based on support vector machine and decision tree

    International Nuclear Information System (INIS)

    Shi Chunsheng; Meng Dapeng

    2011-01-01

    The prediction index for supply risk is developed based on the factor identifying of nuclear equipment manufacturing industry. The supply risk prediction model is established with the method of support vector machine and decision tree, based on the investigation on 3 important nuclear power equipment manufacturing enterprises and 60 suppliers. Final case study demonstrates that the combination model is better than the single prediction model, and demonstrates the feasibility and reliability of this model, which provides a method to evaluate the suppliers and measure the supply risk. (authors)

  2. The risk management of perishable supply chain based on coloured Petri Net modeling

    Directory of Open Access Journals (Sweden)

    Lu Liu

    2018-03-01

    Full Text Available The supply chain of perishable products is a combination of information organization, sharing and integration. The information modeling of supply chain is constructed to abstract key quality information including environment information, processing procedures and product quality assessments based on principle of quality safety factors and property of decay rate. The coloured Petri Net is applied for integrated description of independent information classification, aiming at risk identification and risk management framework. Well, according to the quality deterioration tendency, risk grades management and decision-making system are established. Practically, the circulation system of aquatic products is studied in this paper for full processing description. The simulation experiments are manipulated on environmental information, processing information and product quality information by the coloured Petri Net. Eventually, the conclusion turns out precisely as such that the coloured Petri Net conclusive for information classification and information transmission while integrated information management is available of efficient risk identification and decision-making system in supply chain of perishable products. Meanwhile, the validity of evaluating management and shelf-life estimation of perishable products are technically feasible.

  3. Comparative performance of diabetes-specific and general population-based cardiovascular risk assessment models in people with diabetes mellitus.

    Science.gov (United States)

    Echouffo-Tcheugui, J-B; Kengne, A P

    2013-10-01

    Multivariable models for estimating cardiovascular disease (CVD) risk in people with diabetes comprise general population-based models and those from diabetic cohorts. Whether one set of models should receive preference is unclear. We evaluated the evidence on direct comparisons of the performance of general population vs diabetes-specific CVD risk models in people with diabetes. MEDLINE and EMBASE databases were searched up to March 2013. Two reviewers independently identified studies that compared the performance of general CVD models vs diabetes-specific ones in the same group of people with diabetes. Independent, dual data extraction on study design, risk models, outcomes; and measures of performance was conducted. Eleven articles reporting on 22 pair wise comparisons of a diabetes-specific model (UKPDS, ADVANCE and DCS risk models) to a general population model (three variants of the Framingham model, Prospective Cardiovascular Münster [PROCAM] score, CardioRisk Manager [CRM], Joint British Societies Coronary Risk Chart [JBSRC], Progetto Cuore algorithm and the CHD-Riskard algorithm) were eligible. Absolute differences in C-statistic of diabetes-specific vs general population-based models varied from -0.13 to 0.09. Comparisons for other performance measures were unusual. Outcomes definitions were congruent with those applied during model development. In 14 comparisons, the UKPDS, ADVANCE or DCS diabetes-specific models were superior to the general population CVD risk models. Authors reported better C-statistic for models they developed. The limited existing evidence suggests a possible discriminatory advantage of diabetes-specific over general population-based models for CVD risk stratification in diabetes. More robust head-to-head comparisons are needed to confirm this trend and strengthen recommendations. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

  4. Risk-based safety indicators

    International Nuclear Information System (INIS)

    Sedlak, J.

    2001-12-01

    The report is structured as follows: 1. Risk-based safety indicators: Typology of risk-based indicators (RBIs); Tools for defining RBIs; Requirements for the PSA model; Data sources for RBIs; Types of risks monitored; RBIs and operational safety indicators; Feedback from operating experience; PSO model modification for RBIs; RBI categorization; RBI assessment; RBI applications; Suitable RBI applications. 2. Proposal for risk-based indicators: Acquiring information from operational experience; Method of acquiring safety relevance coefficients for the systems from a PSA model; Indicator definitions; On-line indicators. 3. Annex: Application of RBIs worldwide. (P.A.)

  5. A risk assessment model based on fuzzy logic for electricity distribution system asset management

    Directory of Open Access Journals (Sweden)

    Alireza Yazdani

    2014-06-01

    Full Text Available Electricity distribution systems are considered as the most critical sectors in countries because of the essentiality of power supplement security, socioeconomic security, and way of life. According to the central role of electricity distribution systems, risk analysis helps decision maker determine the most serious risk items to allocate the optimal amount of resources and time. Probability-impact (PI matrix is one of the most popular methods for assessment of the risks involved in the system. However, the traditional PI matrix is criticized for its inability to take into account the inherent uncertainty imposed by real-world systems. On the other hand, fuzzy sets are capable of handling the uncertainty. Thus, in this paper, fuzzy risk assessment model is developed in order to assess risk and management for electricity distribution system asset protection. Finally, a comparison analysis is conducted to show the effectiveness and the capability of the new risk assessment model.

  6. Methodology for the Model-based Small Area Estimates of Cancer Risk Factors and Screening Behaviors - Small Area Estimates

    Science.gov (United States)

    This model-based approach uses data from both the Behavioral Risk Factor Surveillance System (BRFSS) and the National Health Interview Survey (NHIS) to produce estimates of the prevalence rates of cancer risk factors and screening behaviors at the state, health service area, and county levels.

  7. Assessing Breast Cancer Risk Estimates Based on the Gail Model and Its Predictors in Qatari Women.

    Science.gov (United States)

    Bener, Abdulbari; Çatan, Funda; El Ayoubi, Hanadi R; Acar, Ahmet; Ibrahim, Wanis H

    2017-07-01

    The Gail model is the most widely used breast cancer risk assessment tool. An accurate assessment of individual's breast cancer risk is very important for prevention of the disease and for the health care providers to make decision on taking chemoprevention for high-risk women in clinical practice in Qatar. To assess the breast cancer risk among Arab women population in Qatar using the Gail model and provide a global comparison of risk assessment. In this cross-sectional study of 1488 women (aged 35 years and older), we used the Gail Risk Assessment Tool to assess the risk of developing breast cancer. Sociodemographic features such as age, lifestyle habits, body mass index, breast-feeding duration, consanguinity among parents, and family history of breast cancer were considered as possible risks. The mean age of the study population was 47.8 ± 10.8 years. Qatari women and Arab women constituted 64.7% and 35.3% of the study population, respectively. The mean 5-year and lifetime breast cancer risks were 1.12 ± 0.52 and 10.57 ± 3.1, respectively. Consanguineous marriage among parents was seen in 30.6% of participants. We found a relationship between the 5-year and lifetime risks of breast cancer and variables such as age, age at menarche, gravidity, parity, body mass index, family history of cancer, menopause age, occupation, and level of education. The linear regression analysis identified the predictors for breast cancer in women such as age, age at menarche, age of first birth, family history and age of menopausal were considered the strong predictors and significant contributing risk factors for breast cancer after adjusting for ethnicity, parity and other variables. The current study is the first to evaluate the performance of the Gail model for Arab women population in the Gulf Cooperation Council. Gail model is an appropriate breast cancer risk assessment tool for female population in Qatar.

  8. Construction of risk prediction model of type 2 diabetes mellitus based on logistic regression

    Directory of Open Access Journals (Sweden)

    Li Jian

    2017-01-01

    Full Text Available Objective: to construct multi factor prediction model for the individual risk of T2DM, and to explore new ideas for early warning, prevention and personalized health services for T2DM. Methods: using logistic regression techniques to screen the risk factors for T2DM and construct the risk prediction model of T2DM. Results: Male’s risk prediction model logistic regression equation: logit(P=BMI × 0.735+ vegetables × (−0.671 + age × 0.838+ diastolic pressure × 0.296+ physical activity× (−2.287 + sleep ×(−0.009 +smoking ×0.214; Female’s risk prediction model logistic regression equation: logit(P=BMI ×1.979+ vegetables× (−0.292 + age × 1.355+ diastolic pressure× 0.522+ physical activity × (−2.287 + sleep × (−0.010.The area under the ROC curve of male was 0.83, the sensitivity was 0.72, the specificity was 0.86, the area under the ROC curve of female was 0.84, the sensitivity was 0.75, the specificity was 0.90. Conclusion: This study model data is from a compared study of nested case, the risk prediction model has been established by using the more mature logistic regression techniques, and the model is higher predictive sensitivity, specificity and stability.

  9. Using integrated environmental modeling to automate a process-based Quantitative Microbial Risk Assessment

    Science.gov (United States)

    Integrated Environmental Modeling (IEM) organizes multidisciplinary knowledge that explains and predicts environmental-system response to stressors. A Quantitative Microbial Risk Assessment (QMRA) is an approach integrating a range of disparate data (fate/transport, exposure, an...

  10. Using Integrated Environmental Modeling to Automate a Process-Based Quantitative Microbial Risk Assessment (presentation)

    Science.gov (United States)

    Integrated Environmental Modeling (IEM) organizes multidisciplinary knowledge that explains and predicts environmental-system response to stressors. A Quantitative Microbial Risk Assessment (QMRA) is an approach integrating a range of disparate data (fate/transport, exposure, and...

  11. Designing an integrated model based on the indicators Quality and Earned Value for risk management in Information Technology Projects

    OpenAIRE

    TATLARI, Mohammad Reza; KAZEMİPOOR, Hamed

    2015-01-01

    There are two effective factors on Information Technology (IT) projects risk including quality and earned value so that by controlling these two factors and their increased level in IT projects, the corresponding risk can be decreased. Therefore in present study, an integrated model was designed based on quality and earned value indicators for risk management in IT projects on a new and efficient approach. The proposed algorithm included the steps such as preparing a list of several indicator...

  12. Evaluating Computer-Based Assessment in a Risk-Based Model

    Science.gov (United States)

    Zakrzewski, Stan; Steven, Christine; Ricketts, Chris

    2009-01-01

    There are three purposes for evaluation: evaluation for action to aid the decision making process, evaluation for understanding to further enhance enlightenment and evaluation for control to ensure compliance to standards. This article argues that the primary function of evaluation in the "Catherine Wheel" computer-based assessment (CBA)…

  13. A global airport-based risk model for the spread of dengue infection via the air transport network.

    Directory of Open Access Journals (Sweden)

    Lauren Gardner

    Full Text Available The number of travel-acquired dengue infections has seen a consistent global rise over the past decade. An increased volume of international passenger air traffic originating from regions with endemic dengue has contributed to a rise in the number of dengue cases in both areas of endemicity and elsewhere. This paper reports results from a network-based risk assessment model which uses international passenger travel volumes, travel routes, travel distances, regional populations, and predictive species distribution models (for the two vector species, Aedes aegypti and Aedes albopictus to quantify the relative risk posed by each airport in importing passengers with travel-acquired dengue infections. Two risk attributes are evaluated: (i the risk posed by through traffic at each stopover airport and (ii the risk posed by incoming travelers to each destination airport. The model results prioritize optimal locations (i.e., airports for targeted dengue surveillance. The model is easily extendible to other vector-borne diseases.

  14. Data analyses and modelling for risk based monitoring of mycotoxins in animal feed

    NARCIS (Netherlands)

    Ine van der Fels-Klerx, H.J.; Adamse, Paulien; Punt, Ans; Asselt, van Esther D.

    2018-01-01

    Following legislation, European Member States should have multi-annual control programs for contaminants, such as for mycotoxins, in feed and food. These programs need to be risk based implying the checks are regular and proportional to the estimated risk for animal and human health. This study

  15. A process-based model for the definition of hydrological alert systems in landslide risk mitigation

    Directory of Open Access Journals (Sweden)

    M. Floris

    2012-11-01

    Full Text Available The definition of hydrological alert systems for rainfall-induced landslides is strongly related to a deep knowledge of the geological and geomorphological features of the territory. Climatic conditions, spatial and temporal evolution of the phenomena and characterization of landslide triggering, together with propagation mechanisms, are the key elements to be considered. Critical steps for the development of the systems consist of the identification of the hydrological variable related to landslide triggering and of the minimum rainfall threshold for landslide occurrence.

    In this paper we report the results from a process-based model to define a hydrological alert system for the Val di Maso Landslide, located in the northeastern Italian Alps and included in the Vicenza Province (Veneto region, NE Italy. The instability occurred in November 2010, due to an exceptional rainfall event that hit the Vicenza Province and the entire NE Italy. Up to 500 mm in 3-day cumulated rainfall generated large flood conditions and triggered hundreds of landslides. During the flood, the Soil Protection Division of the Vicenza Province received more than 500 warnings of instability phenomena. The complexity of the event and the high level of risk to infrastructure and private buildings are the main reasons for deepening the specific phenomenon occurred at Val di Maso.

    Empirical and physically-based models have been used to identify the minimum rainfall threshold for the occurrence of instability phenomena in the crown area of Val di Maso landslide, where a retrogressive evolution by multiple rotational slides is expected. Empirical models helped in the identification and in the evaluation of recurrence of critical rainfall events, while physically-based modelling was essential to verify the effects on the slope stability of determined rainfall depths. Empirical relationships between rainfall and landslide consist of the calculation of rainfall

  16. A risk-based model for predicting the impact of using condoms on the spread of sexually transmitted infections

    Directory of Open Access Journals (Sweden)

    Asma Azizi

    2017-02-01

    Full Text Available We create and analyze a mathematical model to understand the impact of condom-use and sexual behavior on the prevalence and spread of Sexually Transmitted Infections (STIs. STIs remain significant public health challenges globally with a high burden of some Sexually Transmitted Diseases (STDs in both developed and undeveloped countries. Although condom-use is known to reduce the transmission of STIs, there are a few quantitative population-based studies on the protective role of condom-use in reducing the incidence of STIs. The number of concurrent partners is correlated with their risk of being infectious by an STI such as chlamydia, gonorrhea, or syphilis. We develop a Susceptible-Infectious-Susceptible (SIS model that stratifies the population based on the number of concurrent partners. The model captures the multi-level heterogeneous mixing through a combination of biased (preferential and random (proportional mixing processes between individuals with distinct risk levels, and accounts for differences in condom-use in the low- and high-risk populations. We use sensitivity analysis to assess the relative impact of high-risk people using condom as a prophylactic intervention to reduce their chance of being infectious, or infecting others. The model predicts the STI prevalence as a function of the number of partners of an individual, and quantifies how this distribution of effective partners changes as a function of condom-use. Our results show that when the mixing is random, then increasing the condom-use in the high-risk population is more effective in reducing the prevalence than when many of the partners of high-risk people have high risk. The model quantifies how the risk of being infected increases for people who have more partners, and the need for high-risk people to consistently use condoms to reduce their risk of infection. Keywords: Mathematical modeling, Sexually transmitted infection (STI, Biased (preferential mixing, Random

  17. Predicting the Risk of Attrition for Undergraduate Students with Time Based Modelling

    Science.gov (United States)

    Chai, Kevin E. K.; Gibson, David

    2015-01-01

    Improving student retention is an important and challenging problem for universities. This paper reports on the development of a student attrition model for predicting which first year students are most at-risk of leaving at various points in time during their first semester of study. The objective of developing such a model is to assist…

  18. Regulatory activity based risk model identifies survival of stage II and III colorectal carcinoma.

    Science.gov (United States)

    Liu, Gang; Dong, Chuanpeng; Wang, Xing; Hou, Guojun; Zheng, Yu; Xu, Huilin; Zhan, Xiaohui; Liu, Lei

    2017-11-17

    Clinical and pathological indicators are inadequate for prognosis of stage II and III colorectal carcinoma (CRC). In this study, we utilized the activity of regulatory factors, univariate Cox regression and random forest for variable selection and developed a multivariate Cox model to predict the overall survival of Stage II/III colorectal carcinoma in GSE39582 datasets (469 samples). Patients in low-risk group showed a significant longer overall survival and recurrence-free survival time than those in high-risk group. This finding was further validated in five other independent datasets (GSE14333, GSE17536, GSE17537, GSE33113, and GSE37892). Besides, associations between clinicopathological information and risk score were analyzed. A nomogram including risk score was plotted to facilitate the utilization of risk score. The risk score model is also demonstrated to be effective on predicting both overall and recurrence-free survival of chemotherapy received patients. After performing Gene Set Enrichment Analysis (GSEA) between high and low risk groups, we found that several cell-cell interaction KEGG pathways were identified. Funnel plot results showed that there was no publication bias in these datasets. In summary, by utilizing the regulatory activity in stage II and III colorectal carcinoma, the risk score successfully predicts the survival of 1021 stage II/III CRC patients in six independent datasets.

  19. Towards a resource-based habitat approach for spatial modelling of vector-borne disease risks.

    Science.gov (United States)

    Hartemink, Nienke; Vanwambeke, Sophie O; Purse, Bethan V; Gilbert, Marius; Van Dyck, Hans

    2015-11-01

    Given the veterinary and public health impact of vector-borne diseases, there is a clear need to assess the suitability of landscapes for the emergence and spread of these diseases. Current approaches for predicting disease risks neglect key features of the landscape as components of the functional habitat of vectors or hosts, and hence of the pathogen. Empirical-statistical methods do not explicitly incorporate biological mechanisms, whereas current mechanistic models are rarely spatially explicit; both methods ignore the way animals use the landscape (i.e. movement ecology). We argue that applying a functional concept for habitat, i.e. the resource-based habitat concept (RBHC), can solve these issues. The RBHC offers a framework to identify systematically the different ecological resources that are necessary for the completion of the transmission cycle and to relate these resources to (combinations of) landscape features and other environmental factors. The potential of the RBHC as a framework for identifying suitable habitats for vector-borne pathogens is explored and illustrated with the case of bluetongue virus, a midge-transmitted virus affecting ruminants. The concept facilitates the study of functional habitats of the interacting species (vectors as well as hosts) and provides new insight into spatial and temporal variation in transmission opportunities and exposure that ultimately determine disease risks. It may help to identify knowledge gaps and control options arising from changes in the spatial configuration of key resources across the landscape. The RBHC framework may act as a bridge between existing mechanistic and statistical modelling approaches. © 2014 The Authors. Biological Reviews published by John Wiley & Sons Ltd on behalf of Cambridge Philosophical Society.

  20. 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.

  1. 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...

  2. Probabilistic Modeling of Seismic Risk Based Design for a Dual System Structure

    OpenAIRE

    Sidi, Indra Djati

    2017-01-01

    The dual system structure concept has gained popularity in the construction of high-rise buildings over the last decades. Meanwhile, earthquake engineering design provisions for buildings have moved from the uniform hazard concept to the uniform risk concept upon recognizing the uncertainties involved in the earthquake resistance of concrete structures. In this study, a probabilistic model for the evaluation of such risk is proposed for a dual system structure consisting of shear walls or cor...

  3. Estimated cancer risk of dioxins to humans using a bioassay and physiologically based pharmacokinetic model

    International Nuclear Information System (INIS)

    Maruyama, Wakae; Aoki, Yasunobu

    2006-01-01

    The health risk of dioxins and dioxin-like compounds to humans was analyzed quantitatively using experimental data and mathematical models. To quantify the toxicity of a mixture of three dioxin congeners, we calculated the new relative potencies (REPs) for 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), 1,2,3,7,8-pentachlorodibenzo-p-dioxin (PeCDD), and 2,3,4,7,8- pentachlorodibenzofuran (PeCDF), focusing on their tumor promotion activity. We applied a liver foci formation assay to female SD rats after repeated oral administration of dioxins. The REP of dioxin for a rat was determined using dioxin concentration and the number of the foci in rat liver. A physiologically based pharmacokinetic model (PBPK model) was used for interspecies extrapolation targeting on dioxin concentration in liver. Toxic dose for human was determined by back-estimation with a human PBPK model, assuming that the same concentration in the target tissue may cause the same level of effect in rats and humans, and the REP for human was determined by the toxic dose obtained. The calculated REPs for TCDD, PeCDD, and PeCDF were 1.0, 0.34, and 0.05 for rats, respectively, and the REPs for humans were almost the same as those for rats. These values were different from the toxic equivalency factors (TEFs) presented previously (Van den Berg, M., Birnbaum, L., Bosveld, A.T.C., Brunstrom, B., Cook, P., Feeley, M., Giesy, J.P., Hanberg, A., Hasegawa, R., Kennedy, S.W., Kubiak, T., Larsen, J.C., Rolaf van Leeuwen, F.X., Liem, A.K.D., Nolt, C., Peterson, R.E., Poellinger. L., Safe, S., Schrenk, D., Tillitt, D, Tysklind, M., Younes, M., Waern, F., Zacharewski, T., 1998. Toxic equivalency factors (TEFs) for PCBs, PCDDs, PCDFs for humans and wildlife. Environ. Health Perspect. 106, 775-792). The relative risk of excess liver cancer for Japanese people in general was 1.7-6.5 x 10 -7 by TCDD only, and 2.9-11 x 10 -7 by the three dioxins at the present level of contamination

  4. A School-Based Violence Prevention Model for At-Risk Eighth Grade Youth.

    Science.gov (United States)

    Rollin, Stephen A.; Kaiser-Ulrey, Cheryl; Potts, Isabelle; Creason, Alia Haque

    2003-01-01

    Examines the effectiveness of a school and community-based violence prevention program for at-risk eighth-grade students. School officials matched intervention students with community-based mentors in an employment setting. Findings suggest that mentored students had significant reductions in total number and days of suspensions, days of sanction,…

  5. Risk Evaluation of a UHV Power Transmission Construction Project Based on a Cloud Model and FCE Method for Sustainability

    Directory of Open Access Journals (Sweden)

    Huiru Zhao

    2015-03-01

    Full Text Available In order to achieve the sustainable development of energy, Ultra High Voltage (UHV power transmission construction projects are being established in China currently. Their high-tech nature, the massive amount of money involved, and the need for multi-agent collaboration as well as complex construction environments bring many challenges and risks. Risk management, therefore, is critical to reduce the risks and realize sustainable development of projects. Unfortunately, many traditional risk assessment methods may not perform well due to the great uncertainty and randomness inherent in UHV power construction projects. This paper, therefore, proposes a risk evaluation index system and a hybrid risk evaluation model to evaluate the risk of UHV projects and find out the key risk factors. This model based on a cloud model and fuzzy comprehensive evaluation (FCE method combines the superiority of the cloud model for reflecting randomness and discreteness with the advantages of the fuzzy comprehensive evaluation method in handling uncertain and vague issues. For the sake of proving our framework, an empirical study of “Zhejiang-Fuzhou” UHV power transmission construction project is presented. As key contributions, we find the risk of this project lies at a “middle” to “high” level and closer to a “middle” level; the “management risk” and “social risk” are identified as the most important risk factors requiring more attention; and some risk control recommendations are proposed. This article demonstrates the value of our approach in risk identification, which seeks to improve the risk control level and the sustainable development of UHV power transmission construction projects.

  6. Predictive Accuracy of a Cardiovascular Disease Risk Prediction Model in Rural South India – A Community Based Retrospective Cohort Study

    Directory of Open Access Journals (Sweden)

    Farah N Fathima

    2015-03-01

    Full Text Available Background: Identification of individuals at risk of developing cardiovascular diseases by risk stratification is the first step in primary prevention. Aims & Objectives: To assess the five year risk of developing a cardiovascular event from retrospective data and to assess the predictive accuracy of the non laboratory based National Health and Nutrition Examination Survey (NHANES risk prediction model among individuals in a rural South Indian population. Materials & Methods: A community based retrospective cohort study was conducted in three villages where risk stratification was done for all eligible adults aged between 35-74 years at the time of initial assessment using the NHANES risk prediction charts. Household visits were made after a period of five years by trained doctors to determine cardiovascular outcomes. Results: 521 people fulfilled the eligibility criteria of whom 486 (93.3% could be traced after five years. 56.8% were in low risk, 36.6% were in moderate risk and 6.6% were in high risk categories. 29 persons (5.97% had had cardiovascular events over the last five years of which 24 events (82.7% were nonfatal and five (17.25% were fatal. The mean age of the people who developed cardiovascular events was 57.24 ± 9.09 years. The odds ratios for the three levels of risk showed a linear trend with the odds ratios for the moderate risk and high risk category being 1.35 and 1.94 respectively with the low risk category as baseline. Conclusion: The non laboratory based NHANES charts did not accurately predict the occurrence of cardiovascular events in any of the risk categories.

  7. A point-based prediction model for cardiovascular risk in orthotopic liver transplantation: The CAR-OLT score.

    Science.gov (United States)

    VanWagner, Lisa B; Ning, Hongyan; Whitsett, Maureen; Levitsky, Josh; Uttal, Sarah; Wilkins, John T; Abecassis, Michael M; Ladner, Daniela P; Skaro, Anton I; Lloyd-Jones, Donald M

    2017-12-01

    Cardiovascular disease (CVD) complications are important causes of morbidity and mortality after orthotopic liver transplantation (OLT). There is currently no preoperative risk-assessment tool that allows physicians to estimate the risk for CVD events following OLT. We sought to develop a point-based prediction model (risk score) for CVD complications after OLT, the Cardiovascular Risk in Orthotopic Liver Transplantation risk score, among a cohort of 1,024 consecutive patients aged 18-75 years who underwent first OLT in a tertiary-care teaching hospital (2002-2011). The main outcome measures were major 1-year CVD complications, defined as death from a CVD cause or hospitalization for a major CVD event (myocardial infarction, revascularization, heart failure, atrial fibrillation, cardiac arrest, pulmonary embolism, and/or stroke). The bootstrap method yielded bias-corrected 95% confidence intervals for the regression coefficients of the final model. Among 1,024 first OLT recipients, major CVD complications occurred in 329 (32.1%). Variables selected for inclusion in the model (using model optimization strategies) included preoperative recipient age, sex, race, employment status, education status, history of hepatocellular carcinoma, diabetes, heart failure, atrial fibrillation, pulmonary or systemic hypertension, and respiratory failure. The discriminative performance of the point-based score (C statistic = 0.78, bias-corrected C statistic = 0.77) was superior to other published risk models for postoperative CVD morbidity and mortality, and it had appropriate calibration (Hosmer-Lemeshow P = 0.33). The point-based risk score can identify patients at risk for CVD complications after OLT surgery (available at www.carolt.us); this score may be useful for identification of candidates for further risk stratification or other management strategies to improve CVD outcomes after OLT. (Hepatology 2017;66:1968-1979). © 2017 by the American Association for the Study of Liver

  8. Using Cutting-Edge Tree-Based Stochastic Models to Predict Credit Risk

    Directory of Open Access Journals (Sweden)

    Khaled Halteh

    2018-05-01

    Full Text Available Credit risk is a critical issue that affects banks and companies on a global scale. Possessing the ability to accurately predict the level of credit risk has the potential to help the lender and borrower. This is achieved by alleviating the number of loans provided to borrowers with poor financial health, thereby reducing the number of failed businesses, and, in effect, preventing economies from collapsing. This paper uses state-of-the-art stochastic models, namely: Decision trees, random forests, and stochastic gradient boosting to add to the current literature on credit-risk modelling. The Australian mining industry has been selected to test our methodology. Mining in Australia generates around $138 billion annually, making up more than half of the total goods and services. This paper uses publicly-available financial data from 750 risky and not risky Australian mining companies as variables in our models. Our results indicate that stochastic gradient boosting was the superior model at correctly classifying the good and bad credit-rated companies within the mining sector. Our model showed that ‘Property, Plant, & Equipment (PPE turnover’, ‘Invested Capital Turnover’, and ‘Price over Earnings Ratio (PER’ were the variables with the best explanatory power pertaining to predicting credit risk in the Australian mining sector.

  9. Mode of action based risk assessment of the botanical food-borne alkenylbenzene apiol from parsley using physiologically based kinetic (PBK) modelling and read-across from safrole

    NARCIS (Netherlands)

    Alajlouni, A.M.; Al-Malahmeh, A.J.; Kiwamoto, Reiko; Wesseling, Sebastiaan; Soffers, A.E.M.F.; Al-Subeihi, A.A.A.; Vervoort, Jacques; Rietjens, I.M.C.M.

    2016-01-01

    The present study developed physiologically-based kinetic (PBK) models for the alkenylbenzene apiol in order to facilitate risk assessment based on read-across from the related alkenylbenzene safrole. Model predictions indicate that in rat liver the formation of the 1'-sulfoxy metabolite is about

  10. Integration of an Evidence Base into a Probabilistic Risk Assessment Model. The Integrated Medical Model Database: An Organized Evidence Base for Assessing In-Flight Crew Health Risk and System Design

    Science.gov (United States)

    Saile, Lynn; Lopez, Vilma; Bickham, Grandin; FreiredeCarvalho, Mary; Kerstman, Eric; Byrne, Vicky; Butler, Douglas; Myers, Jerry; Walton, Marlei

    2011-01-01

    This slide presentation reviews the Integrated Medical Model (IMM) database, which is an organized evidence base for assessing in-flight crew health risk. The database is a relational database accessible to many people. The database quantifies the model inputs by a ranking based on the highest value of the data as Level of Evidence (LOE) and the quality of evidence (QOE) score that provides an assessment of the evidence base for each medical condition. The IMM evidence base has already been able to provide invaluable information for designers, and for other uses.

  11. Overview of the Graphical User Interface for the GERM Code (GCR Event-Based Risk Model

    Science.gov (United States)

    Kim, Myung-Hee; Cucinotta, Francis A.

    2010-01-01

    The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERM code calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERM code also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERM code accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERM code for application to thick target experiments. The GERM code provides scientists participating in NSRL experiments with the data needed for the interpretation of their

  12. Overview of the Graphical User Interface for the GERMcode (GCR Event-Based Risk Model)

    Science.gov (United States)

    Kim, Myung-Hee Y.; Cucinotta, Francis A.

    2010-01-01

    The descriptions of biophysical events from heavy ions are of interest in radiobiology, cancer therapy, and space exploration. The biophysical description of the passage of heavy ions in tissue and shielding materials is best described by a stochastic approach that includes both ion track structure and nuclear interactions. A new computer model called the GCR Event-based Risk Model (GERM) code was developed for the description of biophysical events from heavy ion beams at the NASA Space Radiation Laboratory (NSRL). The GERMcode calculates basic physical and biophysical quantities of high-energy protons and heavy ions that have been studied at NSRL for the purpose of simulating space radiobiological effects. For mono-energetic beams, the code evaluates the linear-energy transfer (LET), range (R), and absorption in tissue equivalent material for a given Charge (Z), Mass Number (A) and kinetic energy (E) of an ion. In addition, a set of biophysical properties are evaluated such as the Poisson distribution of ion or delta-ray hits for a specified cellular area, cell survival curves, and mutation and tumor probabilities. The GERMcode also calculates the radiation transport of the beam line for either a fixed number of user-specified depths or at multiple positions along the Bragg curve of the particle. The contributions from primary ion and nuclear secondaries are evaluated. The GERMcode accounts for the major nuclear interaction processes of importance for describing heavy ion beams, including nuclear fragmentation, elastic scattering, and knockout-cascade processes by using the quantum multiple scattering fragmentation (QMSFRG) model. The QMSFRG model has been shown to be in excellent agreement with available experimental data for nuclear fragmentation cross sections, and has been used by the GERMcode for application to thick target experiments. The GERMcode provides scientists participating in NSRL experiments with the data needed for the interpretation of their

  13. Model of personalised risk assessment of phytoestrogen intake based on 11 SNP in ESR1 and ESR2 genes

    Directory of Open Access Journals (Sweden)

    Radoslav Zidek

    2016-12-01

    Full Text Available Phytoestrogens can induce biological responses in vertebrates by mimicking or modulating the action or production of endogenous hormones, and because of their structural similarity with estradiol they have the ability to cause estrogenic or anti-estrogenic effects. Risk assessment of phytoestrogens intake may therefore provide important information useful in the adjustment of nutrients composition, as one of nutrigenomics approaches. Proper risk assessment is an essential part of good nutrient composition. The current risk assessment procedures does use an additive effect of genes, but the accumulation of relevant factors do not count with the distribution of risk in the European population. A combination of approaches based on genetic score, along with the use of the data bases like 1000 genomes and dbSNP is a powerful tool for population risk modelling that would provide reasonable results without needs of as testing a representative number of individual genetic profiles.

  14. A model-based approach to preplanting risk assessment for gray leaf spot of maize.

    Science.gov (United States)

    Paul, P A; Munkvold, G P

    2004-12-01

    ABSTRACT Risk assessment models for gray leaf spot of maize, caused by Cercospora zeae-maydis, were developed using preplanting site and maize genotype data as predictors. Disease severity at the dough/dent plant growth stage was categorized into classes and used as the response variable. Logistic regression and classification and regression tree (CART) modeling approaches were used to predict severity classes as a function of planting date (PD), amount of maize soil surface residue (SR), cropping sequence, genotype maturity and gray leaf spot resistance (GLSR) ratings, and longitude (LON). Models were development using 332 cases collected between 1998 and 2001. Thirty cases collected in 2002 were used to validate the models. Preplanting data showed a strong relationship with late-season gray leaf spot severity classes. The most important predictors were SR, PD, GLSR, and LON. Logistic regression models correctly classified 60 to 70% of the validation cases, whereas the CART models correctly classified 57 to 77% of these cases. Cases misclassified by the CART models were mostly due to overestimation, whereas the logistic regression models tended to misclassify cases by underestimation. Both the CART and logistic regression models have potential as management decision-making tools. Early quantitative assessment of gray leaf spot risk would allow for more sound management decisions being made when warranted.

  15. Risk-based technical specifications: Development and application of an approach to the generation of a plant specific real-time risk model

    International Nuclear Information System (INIS)

    Puglia, B.; Gallagher, D.; Amico, P.; Atefi, B.

    1992-10-01

    This report describes a process developed to convert an existing PRA into a model amenable to real time, risk-based technical specification calculations. In earlier studies (culminating in NUREG/CR-5742), several risk-based approaches to technical specification were evaluated. A real-time approach using a plant specific PRA capable of modeling plant configurations as they change was identified as the most comprehensive approach to control plant risk. A master fault tree logic model representative of-all of the core damage sequences was developed. Portions of the system fault trees were modularized and supercomponents comprised of component failures with similar effects were developed to reduce the size of the model and, quantification times. Modifications to the master fault tree logic were made to properly model the effect of maintenance and recovery actions. Fault trees representing several actuation systems not modeled in detail in the existing PRA were added to the master fault tree logic. This process was applied to the Surry NUREG-1150 Level 1 PRA. The master logic mode was confirmed. The model was then used to evaluate frequency associated with several plant configurations using the IRRAS code. For all cases analyzed computational time was less than three minutes. This document Volume 2, contains appendices A, B, and C. These provide, respectively: Surry Technical Specifications Model Database, Surry Technical Specifications Model, and a list of supercomponents used in the Surry Technical Specifications Model

  16. Modeling tumor control probability for spatially inhomogeneous risk of failure based on clinical outcome data

    DEFF Research Database (Denmark)

    Lühr, Armin; Löck, Steffen; Jakobi, Annika

    2017-01-01

    PURPOSE: Objectives of this work are (1) to derive a general clinically relevant approach to model tumor control probability (TCP) for spatially variable risk of failure and (2) to demonstrate its applicability by estimating TCP for patients planned for photon and proton irradiation. METHODS AND ...

  17. 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...

  18. Remediation Strategies for Learners at Risk of Failure: A Course Based Retention Model

    Science.gov (United States)

    Gajewski, Agnes; Mather, Meera

    2015-01-01

    This paper presents an overview and discussion of a course based remediation model developed to enhance student learning and increased retention based on literature. This model focuses on course structure and course delivery in a compressed semester format. A comparative analysis was applied to a pilot study of students enrolled in a course…

  19. Integrated Monitoring and Modeling of Carbon Dioxide Leakage Risk Using Remote Sensing, Ground-Based Monitoring, Atmospheric Models and Risk-Indexing Tools

    Science.gov (United States)

    Burton, E. A.; Pickles, W. L.; Gouveia, F. J.; Bogen, K. T.; Rau, G. H.; Friedmann, J.

    2006-12-01

    estimating its associated risk, spatially and temporally. This requires integration of subsurface, surface and atmospheric data and models. To date, we have developed techniques to map risk based on predicted atmospheric plumes and GIS/MT (meteorologic- topographic) risk-indexing tools. This methodology was derived from study of large CO2 releases from an abandoned well penetrating a natural CO2 reservoir at Crystal Geyser, Utah. This integrated approach will provide a powerful tool to screen for high-risk zones at proposed sequestration sites, to design and optimize surface networks for site monitoring and/or to guide setting science-based regulatory compliance requirements for monitoring sequestration sites, as well as to target critical areas for first responders should a catastrophic-release event occur. This work was performed under the auspices of the U.S. Dept. of Energy by University of California, Lawrence Livermore National Laboratory under Contract W-7405-Eng-48.

  20. Modeling infection transmission in primate networks to predict centrality-based risk.

    Science.gov (United States)

    Romano, Valéria; Duboscq, Julie; Sarabian, Cécile; Thomas, Elodie; Sueur, Cédric; MacIntosh, Andrew J J

    2016-07-01

    Social structure can theoretically regulate disease risk by mediating exposure to pathogens via social proximity and contact. Investigating the role of central individuals within a network may help predict infectious agent transmission as well as implement disease control strategies, but little is known about such dynamics in real primate networks. We combined social network analysis and a modeling approach to better understand transmission of a theoretical infectious agent in wild Japanese macaques, highly social animals which form extended but highly differentiated social networks. We collected focal data from adult females living on the islands of Koshima and Yakushima, Japan. Individual identities as well as grooming networks were included in a Markov graph-based simulation. In this model, the probability that an individual will transmit an infectious agent depends on the strength of its relationships with other group members. Similarly, its probability of being infected depends on its relationships with already infected group members. We correlated: (i) the percentage of subjects infected during a latency-constrained epidemic; (ii) the mean latency to complete transmission; (iii) the probability that an individual is infected first among all group members; and (iv) each individual's mean rank in the chain of transmission with different individual network centralities (eigenvector, strength, betweenness). Our results support the hypothesis that more central individuals transmit infections in a shorter amount of time and to more subjects but also become infected more quickly than less central individuals. However, we also observed that the spread of infectious agents on the Yakushima network did not always differ from expectations of spread on random networks. Generalizations about the importance of observed social networks in pathogen flow should thus be made with caution, since individual characteristics in some real world networks appear less relevant than

  1. Consumer Product Data for Exposure Screening, Modeling and Prioritization, and Risk-based Decision Making

    Science.gov (United States)

    This presentation will provide an overview of the research efforts underway in EPA ORD's Chemicals for Safety and Sustainability research program which relate to providing information to prioritize chemicals in consumer products based on risk. It also describes effort to make dat...

  2. A Two-Account Life Insurance Model for Scenario-Based Valuation Including Event Risk

    DEFF Research Database (Denmark)

    Jensen, Ninna Reitzel; Schomacker, Kristian Juul

    2015-01-01

    Using a two-account model with event risk, we model life insurance contracts taking into account both guaranteed and non-guaranteed payments in participating life insurance as well as in unit-linked insurance. Here, event risk is used as a generic term for life insurance events, such as death......, disability, etc. In our treatment of participating life insurance, we have special focus on the bonus schemes “consolidation” and “additional benefits”, and one goal is to formalize how these work and interact. Another goal is to describe similarities and differences between participating life insurance...... product types. This enables comparison of participating life insurance products and unit-linked insurance products, thus building a bridge between the two different ways of formalizing life insurance products. Finally, our model distinguishes itself from the existing literature by taking into account...

  3. Screening for gestational diabetes mellitus by a model based on risk indicators

    DEFF Research Database (Denmark)

    Jensen, Dorte Møller; Mølsted-Pedersen, Lars; Beck-Nielsen, Henning

    2003-01-01

    OBJECTIVE: This study was performed to prospectively evaluate a screening model for gestational diabetes mellitus on the basis of clinical risk indicators. STUDY DESIGN: In a prospective multicenter study with 5235 consecutive pregnant women, diagnostic testing with a 2-hour 75-g oral glucose...... of the results from tested women to the whole group in question, a 2.4% prevalence of gestational diabetes mellitus was calculated. Sensitivity and specificity of the model was 80.6 (73.7-87.6) and 64.8 (63.5-66.1), respectively (95% CIs). CONCLUSION: Under ideal conditions, sensitivity of the model...

  4. Modelling and Simulating of Risk Behaviours in Virtual Environments Based on Multi-Agent and Fuzzy Logic

    Directory of Open Access Journals (Sweden)

    Linqin Cai

    2013-11-01

    Full Text Available Due to safety and ethical issues, traditional experimental approaches to modelling underground risk behaviours can be costly, dangerous and even impossible to realize. Based on multi-agent technology, a virtual coalmine platform for risk behaviour simulation is presented to model and simulate the human-machine-environment related risk factors in underground coalmines. To reveal mine workers' risk behaviours, a fuzzy emotional behaviour model is proposed to simulate underground miners' responding behaviours to potential hazardous events based on cognitive appraisal theories and fuzzy logic techniques. The proposed emotion model can generate more believable behaviours for virtual miners according to personalized emotion states, internal motivation needs and behaviour selection thresholds. Finally, typical accident cases of underground hazard spotting and locomotive transport were implemented. The behaviour believability of virtual miners was evaluated with a user assessment method. Experimental results show that the proposed models can create more realistic and reasonable behaviours in virtual coalmine environments, which can improve miners' risk awareness and further train miners' emergent decision-making ability when facing unexpected underground situations.

  5. Risk Level Based Management System: a control banding model for occupational health and safety risk management in a highly regulated environment

    Energy Technology Data Exchange (ETDEWEB)

    Zalk, D; Kamerzell, R; Paik, S; Kapp, J; Harrington, D; Swuste, P

    2009-05-27

    The Risk Level Based Management System (RLBMS) is an occupational risk management (ORM) model that focuses occupational safety, hygeiene, and health (OSHH) resources on the highest risk procedures at work. This article demonstrates the model's simplicity through an implementation within a heavily regulated research institution. The model utilizes control banding strategies with a stratification of four risk levels (RLs) for many commonly performed maintenance and support activities, characterizing risk consistently for comparable tasks. RLBMS creates an auditable tracking of activities, maximizes OSHH professional field time, and standardizes documentation and control commensurate to a given task's RL. Validation of RLs and their exposure control effectiveness is collected in a traditional quantitative collection regime for regulatory auditing. However, qualitative risk assessment methods are also used within this validation process. Participatory approaches are used throughout the RLBMS process. Workers are involved in all phases of building, maintaining, and improving this model. This work participation also improves the implementation of established controls.

  6. Quantitative microbial risk assessment for spray irrigation of dairy manure based on an empirical fate and transport model

    Science.gov (United States)

    Burch, Tucker R; Spencer, Susan K.; Stokdyk, Joel; Kieke, Burney A; Larson, Rebecca A; Firnstahl, Aaron; Rule, Ana M; Borchardt, Mark A.

    2017-01-01

    BACKGROUND: Spray irrigation for land-applying livestock manure is increasing in the United States as farms become larger and economies of scale make manure irrigation affordable. Human health risks from exposure to zoonotic pathogens aerosolized during manure irrigation are not well understood. OBJECTIVES: We aimed to a) estimate human health risks due to aerosolized zoonotic pathogens downwind of spray-irrigated dairy manure; and b) determine which factors (e.g., distance, weather conditions) have the greatest influence on risk estimates. METHODS: We sampled downwind air concentrations of manure-borne fecal indicators and zoonotic pathogens during 21 full-scale dairy manure irri- gation events at three farms. We fit these data to hierarchical empirical models and used model outputs in a quantitative microbial risk assessment (QMRA) to estimate risk [probability of acute gastrointestinal illness (AGI)] for individuals exposed to spray-irrigated dairy manure containing Campylobacter jejuni, enterohemorrhagic Escherichia coli (EHEC), or Salmonella spp. RESULTS: Median risk estimates from Monte Carlo simulations ranged from 10−5 to 10−2 and decreased with distance from the source. Risk estimates for Salmonella or EHEC-related AGI were most sensitive to the assumed level of pathogen prevalence in dairy manure, while risk estimates for C. jejuni were not sensitive to any single variable. Airborne microbe concentrations were negatively associated with distance and positively associated with wind speed, both of which were retained in models as a significant predictor more often than relative humidity, solar irradiation, or temperature. CONCLUSIONS: Our model-based estimates suggest that reducing pathogen prevalence and concentration in source manure would reduce the risk of AGI from exposure to manure irrigation, and that increasing the distance from irrigated manure (i.e., setbacks) and limiting irrigation to times of low wind speed may also reduce risk.

  7. Risk based surveillance for vector borne diseases

    DEFF Research Database (Denmark)

    Bødker, Rene

    of samples and hence early detection of outbreaks. Models for vector borne diseases in Denmark have demonstrated dramatic variation in outbreak risk during the season and between years. The Danish VetMap project aims to make these risk based surveillance estimates available on the veterinarians smart phones...... in Northern Europe. This model approach may be used as a basis for risk based surveillance. In risk based surveillance limited resources for surveillance are targeted at geographical areas most at risk and only when the risk is high. This makes risk based surveillance a cost effective alternative...... sample to a diagnostic laboratory. Risk based surveillance models may reduce this delay. An important feature of risk based surveillance models is their ability to continuously communicate the level of risk to veterinarians and hence increase awareness when risk is high. This is essential for submission...

  8. Validation of a model for ranking aquaculture facilities for risk-based disease surveillance.

    Science.gov (United States)

    Diserens, Nicolas; Falzon, Laura Cristina; von Siebenthal, Beat; Schüpbach-Regula, Gertraud; Wahli, Thomas

    2017-09-15

    A semi-quantitative model for risk ranking of aquaculture facilities in Switzerland with regard to the introduction and spread of Viral Haemorrhagic Septicaemia (VHS) and Infectious Haematopoietic Necrosis (IHN) was developed in a previous study (Diserens et al., 2013). The objective of the present study was to validate this model using data collected during field visits on aquaculture sites in four Swiss cantons compared to data collected through a questionnaire in the previous study. A discrepancy between the values obtained with the two different methods was found in 32.8% of the parameters, resulting in a significant difference (pranking of Swiss aquaculture facilities according to their risk of getting infected with or spreading of VHS and IHN, as the five facilities that tested positive for these diseases in the last ten years were ranked as medium or high risk. Moreover, because the seven fish farms that were infected with Infectious Pancreatic Necrosis (IPN) during the same period also belonged to the risk categories medium and high, the classification appeared to correlate with the occurrence of this third viral fish disease. Copyright © 2017 Elsevier B.V. All rights reserved.

  9. Assessing surface water flood risk and management strategies under future climate change: Insights from an Agent-Based Model.

    Science.gov (United States)

    Jenkins, K; Surminski, S; Hall, J; Crick, F

    2017-10-01

    Climate change and increasing urbanization are projected to result in an increase in surface water flooding and consequential damages in the future. In this paper, we present insights from a novel Agent Based Model (ABM), applied to a London case study of surface water flood risk, designed to assess the interplay between different adaptation options; how risk reduction could be achieved by homeowners and government; and the role of flood insurance and the new flood insurance pool, Flood Re, in the context of climate change. The analysis highlights that while combined investment in property-level flood protection and sustainable urban drainage systems reduce surface water flood risk, the benefits can be outweighed by continued development in high risk areas and the effects of climate change. In our simulations, Flood Re is beneficial in its function to provide affordable insurance, even under climate change. However, the scheme does face increasing financial pressure due to rising surface water flood damages. If the intended transition to risk-based pricing is to take place then a determined and coordinated strategy will be needed to manage flood risk, which utilises insurance incentives, limits new development, and supports resilience measures. Our modelling approach and findings are highly relevant for the ongoing regulatory and political approval process for Flood Re as well as for wider discussions on the potential of insurance schemes to incentivise flood risk management and climate adaptation in the UK and internationally. Copyright © 2017 Elsevier B.V. All rights reserved.

  10. Prioritization of chemicals in the aquatic environment based on risk assessment: analytical, modeling and regulatory perspective.

    Science.gov (United States)

    Guillén, D; Ginebreda, A; Farré, M; Darbra, R M; Petrovic, M; Gros, M; Barceló, D

    2012-12-01

    The extensive and intensive use of chemicals in our developed, highly technological society includes more than 100,000 chemical substances. Significant scientific evidence has lead to the recognition that their improper use and release may result in undesirable and harmful side-effects on both the human and ecosystem health. To cope with them, appropriate risk assessment processes and related prioritization schemes have been developed in order to provide the necessary scientific support for regulatory procedures. In the present paper, two of the elements that constitute the core of risk assessment, namely occurrence and hazard effects, have been discussed. Recent advances in analytical chemistry (sample pre-treatment and instrumental equipment, etc.) have allowed for more comprehensive monitoring of environmental pollution reaching limits of detection up to sub ng L(-1). Alternative to analytical measurements, occurrence models can provide risk managers with a very interesting approach for estimating environmental concentrations from real or hypothetical scenarios. The most representative prioritization schemes used for issuing lists of concerning chemicals have also been examined and put in the context of existing environmental policies for protection strategies and regulations. Finally, new challenges in the field of risk-assessment have been outlined, including those posed by new materials (i.e., nanomaterials), transformation products, multi-chemical exposure, or extension of the risk assessment process to the whole ecosystem. Copyright © 2012 Elsevier B.V. All rights reserved.

  11. Developing a suitable model for supplier selection based on supply chain risks: an empirical study from Iranian pharmaceutical companies.

    Science.gov (United States)

    Mehralian, Gholamhossein; Rajabzadeh Gatari, Ali; Morakabati, Mohadese; Vatanpour, Hossein

    2012-01-01

    The supply chain represents the critical link between the development of new product and the market in pharmaceutical industry. Over the years, improvements made in supply chain operations have focused largely on ways to reduce cost and gain efficiencies in scale. In addition, powerful regulatory and market forces have provided new incentives for pharmaceutical firms to basically rethink the way they produce and distribute products, and also to re-imagine the role of the supply chain in driving strategic growth, brand differentiation and economic value in the health continuum. The purpose of this paper is to formulate basic factors involved in risk analysis of pharmaceutical industry, and also determine the effective factors involved in suppliers selection and their priorities. This paper is based on the results of literature review, experts' opinion acquisition, statistical analysis and also using MADM models on data gathered from distributed questionnaires. The model consists of the following steps and components: first factors involved in to supply chain risks are determined. Based on them a framework is considered. According the result of statistical analysis and MADM models the risk factors are formulated. The paper determines the main components and influenceial factors involving in the supply chain risks. Results showed that delivery risk can make an important contribution to mitigate the risk of pharmaceutical industry.

  12. Developing a Suitable Model for Supplier Selection Based on Supply Chain Risks: An Empirical Study from Iranian Pharmaceutical Companies

    Science.gov (United States)

    Mehralian, Gholamhossein; Rajabzadeh Gatari, Ali; Morakabati, Mohadese; Vatanpour, Hossein

    2012-01-01

    The supply chain represents the critical link between the development of new product and the market in pharmaceutical industry. Over the years, improvements made in supply chain operations have focused largely on ways to reduce cost and gain efficiencies in scale. In addition, powerful regulatory and market forces have provided new incentives for pharmaceutical firms to basically rethink the way they produce and distribute products, and also to re-imagine the role of the supply chain in driving strategic growth, brand differentiation and economic value in the health continuum. The purpose of this paper is to formulate basic factors involved in risk analysis of pharmaceutical industry, and also determine the effective factors involved in suppliers selection and their priorities. This paper is based on the results of literature review, experts’ opinion acquisition, statistical analysis and also using MADM models on data gathered from distributed questionnaires. The model consists of the following steps and components: first factors involved in to supply chain risks are determined. Based on them a framework is considered. According the result of statistical analysis and MADM models the risk factors are formulated. The paper determines the main components and influenceial factors involving in the supply chain risks. Results showed that delivery risk can make an important contribution to mitigate the risk of pharmaceutical industry. PMID:24250442

  13. Development of a diagnosis- and procedure-based risk model for 30-day outcome after pediatric cardiac surgery.

    Science.gov (United States)

    Crowe, Sonya; Brown, Kate L; Pagel, Christina; Muthialu, Nagarajan; Cunningham, David; Gibbs, John; Bull, Catherine; Franklin, Rodney; Utley, Martin; Tsang, Victor T

    2013-05-01

    The study objective was to develop a risk model incorporating diagnostic information to adjust for case-mix severity during routine monitoring of outcomes for pediatric cardiac surgery. Data from the Central Cardiac Audit Database for all pediatric cardiac surgery procedures performed in the United Kingdom between 2000 and 2010 were included: 70% for model development and 30% for validation. Units of analysis were 30-day episodes after the first surgical procedure. We used logistic regression for 30-day mortality. Risk factors considered included procedural information based on Central Cardiac Audit Database "specific procedures," diagnostic information defined by 24 "primary" cardiac diagnoses and "univentricular" status, and other patient characteristics. Of the 27,140 30-day episodes in the development set, 25,613 were survivals, 834 were deaths, and 693 were of unknown status (mortality, 3.2%). The risk model includes procedure, cardiac diagnosis, univentricular status, age band (neonate, infant, child), continuous age, continuous weight, presence of non-Down syndrome comorbidity, bypass, and year of operation 2007 or later (because of decreasing mortality). A risk score was calculated for 95% of cases in the validation set (weight missing in 5%). The model discriminated well; the C-index for validation set was 0.77 (0.81 for post-2007 data). Removal of all but procedural information gave a reduced C-index of 0.72. The model performed well across the spectrum of predicted risk, but there was evidence of underestimation of mortality risk in neonates undergoing operation from 2007. The risk model performs well. Diagnostic information added useful discriminatory power. A future application is risk adjustment during routine monitoring of outcomes in the United Kingdom to assist quality assurance. Copyright © 2013 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.

  14. 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.

  15. A geographical information system-based web model of arbovirus transmission risk in the continental United States of America

    Directory of Open Access Journals (Sweden)

    Sarah K. Konrad

    2012-11-01

    Full Text Available A degree-day (DD model of West Nile virus capable of forecasting real-time transmission risk in the continental United States of America up to one week in advance using a 50-km grid is available online at https://sites. google.com/site/arbovirusmap/. Daily averages of historical risk based on temperatures for 1994-2003 are available at 10- km resolution. Transmission risk maps can be downloaded from 2010 to the present. The model can be adapted to work with any arbovirus for which the temperature-related parameters are known, e.g. Rift Valley fever virus. To more effectively assess virus establishment and transmission, the model incorporates “compound risk” maps and forecasts, which includes livestock density as a parameter.

  16. Data Analyses and Modelling for Risk Based Monitoring of Mycotoxins in Animal Feed

    Directory of Open Access Journals (Sweden)

    H.J. (Ine van der Fels-Klerx

    2018-01-01

    Full Text Available Following legislation, European Member States should have multi-annual control programs for contaminants, such as for mycotoxins, in feed and food. These programs need to be risk based implying the checks are regular and proportional to the estimated risk for animal and human health. This study aimed to prioritize feed products in the Netherlands for deoxynivalenol and aflatoxin B1 monitoring. Historical mycotoxin monitoring results from the period 2007–2016 were combined with data from other sources. Based on occurrence, groundnuts had high priority for aflatoxin B1 monitoring; some feed materials (maize and maize products and several oil seed products and complete/complementary feed excluding dairy cattle and young animals had medium priority; and all other animal feeds and feed materials had low priority. For deoxynivalenol, maize by-products had a high priority, complete and complementary feed for pigs had a medium priority and all other feed and feed materials a low priority. Also including health consequence estimations showed that feed materials that ranked highest for aflatoxin B1 included sunflower seed and palmkernel expeller/extracts and maize. For deoxynivalenol, maize products were ranked highest, followed by various small grain cereals (products; all other feed materials were of lower concern. Results of this study have proven to be useful in setting up the annual risk based control program for mycotoxins in animal feed and feed materials.

  17. Data Analyses and Modelling for Risk Based Monitoring of Mycotoxins in Animal Feed

    Science.gov (United States)

    van der Fels-Klerx, H.J. (Ine); Adamse, Paulien; Punt, Ans; van Asselt, Esther D.

    2018-01-01

    Following legislation, European Member States should have multi-annual control programs for contaminants, such as for mycotoxins, in feed and food. These programs need to be risk based implying the checks are regular and proportional to the estimated risk for animal and human health. This study aimed to prioritize feed products in the Netherlands for deoxynivalenol and aflatoxin B1 monitoring. Historical mycotoxin monitoring results from the period 2007–2016 were combined with data from other sources. Based on occurrence, groundnuts had high priority for aflatoxin B1 monitoring; some feed materials (maize and maize products and several oil seed products) and complete/complementary feed excluding dairy cattle and young animals had medium priority; and all other animal feeds and feed materials had low priority. For deoxynivalenol, maize by-products had a high priority, complete and complementary feed for pigs had a medium priority and all other feed and feed materials a low priority. Also including health consequence estimations showed that feed materials that ranked highest for aflatoxin B1 included sunflower seed and palmkernel expeller/extracts and maize. For deoxynivalenol, maize products were ranked highest, followed by various small grain cereals (products); all other feed materials were of lower concern. Results of this study have proven to be useful in setting up the annual risk based control program for mycotoxins in animal feed and feed materials. PMID:29373559

  18. [Non-linear System Dynamics Simulation Modeling of Adolescent Obesity: Using Korea Youth Risk Behavior Web-based Survey].

    Science.gov (United States)

    Lee, Hanna; Park, Eun Suk; Yu, Jae Kook; Yun, Eun Kyoung

    2015-10-01

    The purpose of this study was to develop a system dynamics model for adolescent obesity in Korea that could be used for obesity policy analysis. On the basis of the casual loop diagram, a model was developed by converting to stock and flow diagram. The Vensim DSS 5.0 program was used in the model development. We simulated method of moments to the calibration of this model with data from The Korea Youth Risk Behavior Web-based Survey 2005 to 2013. We ran the scenario simulation. This model can be used to understand the current adolescent obesity rate, predict the future obesity rate, and be utilized as a tool for controlling the risk factors. The results of the model simulation match well with the data. It was identified that a proper model, able to predict obesity probability, was established. These results of stock and flow diagram modeling in adolescent obesity can be helpful in development of obesity by policy planners and other stakeholders to better anticipate the multiple effects of interventions in both the short and the long term. In the future we suggest the development of an expanded model based on this adolescent obesity model.

  19. Effect of risk-based payment model on caries inequalities in preschool children assessed by geo-mapping.

    Science.gov (United States)

    Holmén, Anders; Strömberg, Ulf; Håkansson, Gunnel; Twetman, Svante

    2018-01-05

    To describe, with aid of geo-mapping, the effects of a risk-based capitation model linked to caries-preventive guidelines on the polarization of caries in preschool children living in the Halland region of Sweden. The new capitation model was implemented in 2013 in which more money was allocated to Public Dental Clinics surrounded by administrative parishes inhabited by children with increased caries risk, while a reduced capitation was allocated to those clinics with a low burden of high risk children. Regional geo-maps of caries risk based on caries prevalence, level of education and the families purchasing power were produced for 3-6-year-old children in 2010 (n = 10,583) and 2016 (n = 7574). Newly migrated children to the region (n = 344 in 2010 and n = 522 in 2016) were analyzed separately. A regional caries polarization index was calculated as the ratio between the maximum and minimum estimates of caries frequency on parish-level, based on a Bayesian hierarchical mapping model. Overall, the total caries prevalence (dmfs > 0) remained unchanged from 2010 (10.6%) to 2016 (10.5%). However, the polarization index decreased from 7.0 in 2010 to 5.6 in 2016. Newly arrived children born outside Sweden had around four times higher caries prevalence than their Swedish-born peers. A risk-based capitation model could reduce the socio-economic inequalities in dental caries among preschool children living in Sweden. Although updated evidence-based caries-preventive guidelines were released, the total prevalence of caries on dentin surface level was unaffected 4 years after the implementation.

  20. A risk explicit interval linear programming model for uncertainty-based environmental economic optimization in the Lake Fuxian watershed, China.

    Science.gov (United States)

    Zhang, Xiaoling; Huang, Kai; Zou, Rui; Liu, Yong; Yu, Yajuan

    2013-01-01

    The conflict of water environment protection and economic development has brought severe water pollution and restricted the sustainable development in the watershed. A risk explicit interval linear programming (REILP) method was used to solve integrated watershed environmental-economic optimization problem. Interval linear programming (ILP) and REILP models for uncertainty-based environmental economic optimization at the watershed scale were developed for the management of Lake Fuxian watershed, China. Scenario analysis was introduced into model solution process to ensure the practicality and operability of optimization schemes. Decision makers' preferences for risk levels can be expressed through inputting different discrete aspiration level values into the REILP model in three periods under two scenarios. Through balancing the optimal system returns and corresponding system risks, decision makers can develop an efficient industrial restructuring scheme based directly on the window of "low risk and high return efficiency" in the trade-off curve. The representative schemes at the turning points of two scenarios were interpreted and compared to identify a preferable planning alternative, which has the relatively low risks and nearly maximum benefits. This study provides new insights and proposes a tool, which was REILP, for decision makers to develop an effectively environmental economic optimization scheme in integrated watershed management.

  1. A Risk Explicit Interval Linear Programming Model for Uncertainty-Based Environmental Economic Optimization in the Lake Fuxian Watershed, China

    Directory of Open Access Journals (Sweden)

    Xiaoling Zhang

    2013-01-01

    Full Text Available The conflict of water environment protection and economic development has brought severe water pollution and restricted the sustainable development in the watershed. A risk explicit interval linear programming (REILP method was used to solve integrated watershed environmental-economic optimization problem. Interval linear programming (ILP and REILP models for uncertainty-based environmental economic optimization at the watershed scale were developed for the management of Lake Fuxian watershed, China. Scenario analysis was introduced into model solution process to ensure the practicality and operability of optimization schemes. Decision makers’ preferences for risk levels can be expressed through inputting different discrete aspiration level values into the REILP model in three periods under two scenarios. Through balancing the optimal system returns and corresponding system risks, decision makers can develop an efficient industrial restructuring scheme based directly on the window of “low risk and high return efficiency” in the trade-off curve. The representative schemes at the turning points of two scenarios were interpreted and compared to identify a preferable planning alternative, which has the relatively low risks and nearly maximum benefits. This study provides new insights and proposes a tool, which was REILP, for decision makers to develop an effectively environmental economic optimization scheme in integrated watershed management.

  2. An example of population-level risk assessments for small mammals using individual-based population models.

    Science.gov (United States)

    Schmitt, Walter; Auteri, Domenica; Bastiansen, Finn; Ebeling, Markus; Liu, Chun; Luttik, Robert; Mastitsky, Sergey; Nacci, Diane; Topping, Chris; Wang, Magnus

    2016-01-01

    This article presents a case study demonstrating the application of 3 individual-based, spatially explicit population models (IBMs, also known as agent-based models) in ecological risk assessments to predict long-term effects of a pesticide to populations of small mammals. The 3 IBMs each used a hypothetical fungicide (FungicideX) in different scenarios: spraying in cereals (common vole, Microtus arvalis), spraying in orchards (field vole, Microtus agrestis), and cereal seed treatment (wood mouse, Apodemus sylvaticus). Each scenario used existing model landscapes, which differed greatly in size and structural complexity. The toxicological profile of FungicideX was defined so that the deterministic long-term first tier risk assessment would result in high risk to small mammals, thus providing the opportunity to use the IBMs for risk assessment refinement (i.e., higher tier risk assessment). Despite differing internal model design and scenarios, results indicated in all 3 cases low population sensitivity unless FungicideX was applied at very high (×10) rates. Recovery from local population impacts was generally fast. Only when patch extinctions occured in simulations of intentionally high acute toxic effects, recovery periods, then determined by recolonization, were of any concern. Conclusions include recommendations for the most important input considerations, including the selection of exposure levels, duration of simulations, statistically robust number of replicates, and endpoints to report. However, further investigation and agreement are needed to develop recommendations for landscape attributes such as size, structure, and crop rotation to define appropriate regulatory risk assessment scenarios. Overall, the application of IBMs provides multiple advantages to higher tier ecological risk assessments for small mammals, including consistent and transparent direct links to specific protection goals, and the consideration of more realistic scenarios. © 2015 SETAC.

  3. Synthetic biology between challenges and risks: suggestions for a model of governance and a regulatory framework, based on fundamental rights.

    Science.gov (United States)

    Colussi, Ilaria Anna

    2013-01-01

    This paper deals with the emerging synthetic biology, its challenges and risks, and tries to design a model for the governance and regulation of the field. The model is called of "prudent vigilance" (inspired by the report about synthetic biology, drafted by the U.S. Presidential Commission on Bioethics, 2010), and it entails (a) an ongoing and periodically revised process of assessment and management of all the risks and concerns, and (b) the adoption of policies - taken through "hard law" and "soft law" sources - that are based on the principle of proportionality (among benefits and risks), on a reasonable balancing between different interests and rights at stake, and are oriented by a constitutional frame, which is represented by the protection of fundamental human rights emerging in the field of synthetic biology (right to life, right to health, dignity, freedom of scientific research, right to environment). After the theoretical explanation of the model, its operability is "checked", by considering its application with reference to only one specific risk brought up by synthetic biology - biosecurity risk, i.e. the risk of bioterrorism.

  4. GIS-based flood risk model evaluated by Fuzzy Analytic Hierarchy Process (FAHP)

    Science.gov (United States)

    Sukcharoen, Tharapong; Weng, Jingnong; Teetat, Charoenkalunyuta

    2016-10-01

    Over the last 2-3 decades, the economy of many countries around the world has been developed rapidly but it was unbalanced development because of expecting on economic growth only. Meanwhile it lacked of effective planning in the use of natural resources. This can significantly induce climate change which is major cause of natural disaster. Hereby, Thailand has also suffered from natural disaster for ages. Especially, the flood which is most hazardous disaster in Thailand can annually result in the great loss of life and property, environment and economy. Since the flood management of country is inadequate efficiency. It is unable to support the flood analysis comprehensively. This paper applied Geographic Information System and Multi-Criteria Decision Making to create flood risk model at regional scale. Angthong province in Thailand was used as the study area. In practical process, Fuzzy logic technique has been used to improve specialist's assessment by implementing with Fuzzy membership because human decision is flawed under uncertainty then AHP technique was processed orderly. The hierarchy structure in this paper was categorized the spatial flood factors into two levels as following: 6 criteria (Meteorology, Geology, Topography, Hydrology, Human and Flood history) and 8 factors (Average Rainfall, Distance from Stream, Soil drainage capability, Slope, Elevation, Land use, Distance from road and Flooded area in the past). The validity of the pair-wise comparison in AHP was shown as C.R. value which indicated that the specialist judgment was reasonably consistent. FAHP computation result has shown that the first priority of criteria was Meteorology. In addition, the Rainfall was the most influencing factor for flooding. Finally, the output was displayed in thematic map of Angthong province with flood risk level processed by GIS tools. The map was classified into: High Risk, Moderate Risk and Low Risk (13.20%, 75.58%, and 11.22% of total area).

  5. 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.

  6. Study on quantitative risk assessment model of the third party damage for natural gas pipelines based on fuzzy comprehensive assessment

    International Nuclear Information System (INIS)

    Qiu, Zeyang; Liang, Wei; Lin, Yang; Zhang, Meng; Wang, Xue

    2017-01-01

    As an important part of national energy supply system, transmission pipelines for natural gas are possible to cause serious environmental pollution, life and property loss in case of accident. The third party damage is one of the most significant causes for natural gas pipeline system accidents, and it is very important to establish an effective quantitative risk assessment model of the third party damage for reducing the number of gas pipelines operation accidents. Against the third party damage accident has the characteristics such as diversity, complexity and uncertainty, this paper establishes a quantitative risk assessment model of the third party damage based on Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE). Firstly, risk sources of third party damage should be identified exactly, and the weight of factors could be determined via improved AHP, finally the importance of each factor is calculated by fuzzy comprehensive evaluation model. The results show that the quantitative risk assessment model is suitable for the third party damage of natural gas pipelines and improvement measures could be put forward to avoid accidents based on the importance of each factor. (paper)

  7. Diagnosis Of The Risk For Carotid Artery Stenos Based On Thermal Model In Infrared Images

    Directory of Open Access Journals (Sweden)

    Fatemeh Valipoori Goodarzi

    2017-02-01

    Full Text Available Background and purpose: Ischemic stroke is the third leading cause of death and a common cause of hospitalization in the United States of America and is also an important factor for Inability of patients and carotid stenos is one of the most important factors in creating it. Now, Imaging studies include: Angiography, MRI, CT scan and Doppler ultrasonography , are used to detect carotid artery stenos that is one of the most important causes of ischemic stroke. However, each method has unique advantages and disadvantages, that many of them will have a compromise between performance and accuracy versus easy usage and cost considerations. In contrast, in this paper, thermography is used as a non-invasive and cost effective to detect carotid artery Stenos and thus the risk of stroke. Materials and methods: This study is done on a series of thermal images obtained from the Clinical Center in California. In this imaging, the automatic detection of carotid artery stenos and thus Risk for stroke was done, based on: (1 the difference of average temperature between the right and left carotid arteries in the neck (2 The presence or absence of internal and external carotid arteries. Results: In this study, with the survey conducted by a specialist brain of patients had been previously, the accuracy of this work is confirmed. the techniques and points that are Experimental and  scientifically based  and obtained in this study, can help to doctors for Early detection of Artery disease, based on analysis of thermal images . Conclusion: The method presented in this paper is considered as a non-invasive and cost-effective method that automatically operates to detect the carotid arteries and prevent the Risk for stroke.

  8. 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).

  9. Model-based measurement of latent risk in time series with applications.

    NARCIS (Netherlands)

    Bijleveld, F.D. Commandeur, J.J.F. Gould, P. & Koopman, S.J.

    2008-01-01

    Risk is at the centre of many policy decisions in companies, governments and other institutions.The risk of road fatalities concerns local governments in planning countermeasures, the risk and severity of counterparty default concerns bank risk managers daily and the risk of infection has actuarial

  10. Model-based measurement of latent risk in time series with applications.

    NARCIS (Netherlands)

    Bijleveld, F.D. Commandeur, J.J.F. Gould, P. & Koopman, S.J.

    2006-01-01

    Risk is at the center of many policy decisions in companies, governments and other institutions. The risk of road fatalities concerns local governments in planning counter- measures, the risk and severity of counterparty default concerns bank risk managers on a daily basis and the risk of infection

  11. Knowledge-Based Energy Damage Model for Evaluating Industrialised Building Systems (IBS Occupational Health and Safety (OHS Risk

    Directory of Open Access Journals (Sweden)

    Abas Nor Haslinda

    2016-01-01

    Full Text Available Malaysia’s construction industry has been long considered hazardous, owing to its poor health and safety record. It is proposed that one of the ways to improve safety and health in the construction industry is through the implementation of ‘off-site’ systems, commonly termed ‘industrialised building systems (IBS’ in Malaysia. This is deemed safer based on the risk concept of reduced exposure, brought about by the reduction in onsite workers; however, no method yet exists for determining the relative safety of various construction methods, including IBS. This study presents a comparative evaluation of the occupational health and safety (OHS risk presented by different construction approaches, namely IBS and traditional methods. The evaluation involved developing a model based on the concept of ‘argumentation theory’, which helps construction designers integrate the management of OHS risk into the design process. In addition, an ‘energy damage model’ was used as an underpinning framework. Development of the model was achieved through three phases, namely Phase I – knowledge acquisitaion, Phase II – argument trees mapping, and Phase III – validation of the model. The research revealed that different approaches/methods of construction projects carried a different level of energy damage, depending on how the activities were carried out. A study of the way in which the risks change from one construction process to another shows that there is a difference in the profile of OHS risk between IBS construction and traditional methods.Therefore, whether the option is an IBS or traditional approach, the fundamental idea of the model is to motivate construction designers or decision-makers to address safety in the design process and encourage them to examine carefully the probable OHS risk variables surrounding an action, thus preventing accidents in construction.

  12. 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.

  13. Evaluation of caries risk in a young adult population using a computer-based risk assessment model (Cariogram

    Directory of Open Access Journals (Sweden)

    Ilkay Peker

    2012-06-01

    Conclusions: According to the results of this study, the most important factors for caries risk were the past caries experience, fluoride programs, and S. mutans and Lactobacillus counts in saliva. Cariogram is a helpful method for dentists in clinical practice to assess caries risk, and it can be used as a didactic tool for patient education and motivation.

  14. Collision risk in white-tailed eagles. Modelling kernel-based collision risk using satellite telemetry data in Smoela wind-power plant

    Energy Technology Data Exchange (ETDEWEB)

    May, Roel; Nygaard, Torgeir; Dahl, Espen Lie; Reitan, Ole; Bevanger, Kjetil

    2011-05-15

    Large soaring birds of prey, such as the white-tailed eagle, are recognized to be perhaps the most vulnerable bird group regarding risk of collisions with turbines in wind-power plants. Their mortalities have called for methods capable of modelling collision risks in connection with the planning of new wind-power developments. The so-called 'Band model' estimates collision risk based on the number of birds flying through the rotor swept zone and the probability of being hit by the passing rotor blades. In the calculations for the expected collision mortality a correction factor for avoidance behaviour is included. The overarching objective of this study was to use satellite telemetry data and recorded mortality to back-calculate the correction factor for white-tailed eagles. The Smoela wind-power plant consists of 68 turbines, over an area of approximately 18 km2. Since autumn 2006 the number of collisions has been recorded on a weekly basis. The analyses were based on satellite telemetry data from 28 white-tailed eagles equipped with backpack transmitters since 2005. The correction factor (i.e. 'avoidance rate') including uncertainty levels used within the Band collision risk model for white-tailed eagles was 99% (94-100%) for spring and 100% for the other seasons. The year-round estimate, irrespective of season, was 98% (95-99%). Although the year-round estimate was similar, the correction factor for spring was higher than the correction factor of 95% derived earlier from vantage point data. The satellite telemetry data may provide an alternative way to provide insight into relative risk among seasons, and help identify periods or areas with increased risk either in a pre- or post construction situation. (Author)

  15. An Empirical Agent-Based Model to Simulate the Adoption of Water Reuse Using the Social Amplification of Risk Framework.

    Science.gov (United States)

    Kandiah, Venu; Binder, Andrew R; Berglund, Emily Z

    2017-10-01

    Water reuse can serve as a sustainable alternative water source for urban areas. However, the successful implementation of large-scale water reuse projects depends on community acceptance. Because of the negative perceptions that are traditionally associated with reclaimed water, water reuse is often not considered in the development of urban water management plans. This study develops a simulation model for understanding community opinion dynamics surrounding the issue of water reuse, and how individual perceptions evolve within that context, which can help in the planning and decision-making process. Based on the social amplification of risk framework, our agent-based model simulates consumer perceptions, discussion patterns, and their adoption or rejection of water reuse. The model is based on the "risk publics" model, an empirical approach that uses the concept of belief clusters to explain the adoption of new technology. Each household is represented as an agent, and parameters that define their behavior and attributes are defined from survey data. Community-level parameters-including social groups, relationships, and communication variables, also from survey data-are encoded to simulate the social processes that influence community opinion. The model demonstrates its capabilities to simulate opinion dynamics and consumer adoption of water reuse. In addition, based on empirical data, the model is applied to investigate water reuse behavior in different regions of the United States. Importantly, our results reveal that public opinion dynamics emerge differently based on membership in opinion clusters, frequency of discussion, and the structure of social networks. © 2017 Society for Risk Analysis.

  16. Agent based models for testing city evacuation strategies under a flood event as strategy to reduce flood risk

    Science.gov (United States)

    Medina, Neiler; Sanchez, Arlex; Nokolic, Igor; Vojinovic, Zoran

    2016-04-01

    This research explores the uses of Agent Based Models (ABM) and its potential to test large scale evacuation strategies in coastal cities at risk from flood events due to extreme hydro-meteorological events with the final purpose of disaster risk reduction by decreasing human's exposure to the hazard. The first part of the paper corresponds to the theory used to build the models such as: Complex adaptive systems (CAS) and the principles and uses of ABM in this field. The first section outlines the pros and cons of using AMB to test city evacuation strategies at medium and large scale. The second part of the paper focuses on the central theory used to build the ABM, specifically the psychological and behavioral model as well as the framework used in this research, specifically the PECS reference model is cover in this section. The last part of this section covers the main attributes or characteristics of human beings used to described the agents. The third part of the paper shows the methodology used to build and implement the ABM model using Repast-Symphony as an open source agent-based modelling and simulation platform. The preliminary results for the first implementation in a region of the island of Sint-Maarten a Dutch Caribbean island are presented and discussed in the fourth section of paper. The results obtained so far, are promising for a further development of the model and its implementation and testing in a full scale city

  17. Expert judgment based multi-criteria decision model to address uncertainties in risk assessment of nanotechnology-enabled food products

    International Nuclear Information System (INIS)

    Flari, Villie; Chaudhry, Qasim; Neslo, Rabin; Cooke, Roger

    2011-01-01

    Currently, risk assessment of nanotechnology-enabled food products is considered difficult due to the large number of uncertainties involved. We developed an approach which could address some of the main uncertainties through the use of expert judgment. Our approach employs a multi-criteria decision model, based on probabilistic inversion that enables capturing experts’ preferences in regard to safety of nanotechnology-enabled food products, and identifying their opinions in regard to the significance of key criteria that are important in determining the safety of such products. An advantage of these sample-based techniques is that they provide out-of-sample validation and therefore a robust scientific basis. This validation in turn adds predictive power to the model developed. We achieved out-of-sample validation in two ways: (1) a portion of the expert preference data was excluded from the model’s fitting and was then predicted by the model fitted on the remaining rankings and (2) a (partially) different set of experts generated new scenarios, using the same criteria employed in the model, and ranked them; their ranks were compared with ranks predicted by the model. The degree of validation in each method was less than perfect but reasonably substantial. The validated model we applied captured and modelled experts’ preferences regarding safety of hypothetical nanotechnology-enabled food products. It appears therefore that such an approach can provide a promising route to explore further for assessing the risk of nanotechnology-enabled food products.

  18. A Vulnerability-Based, Bottom-up Assessment of Future Riverine Flood Risk Using a Modified Peaks-Over-Threshold Approach and a Physically Based Hydrologic Model

    Science.gov (United States)

    Knighton, James; Steinschneider, Scott; Walter, M. Todd

    2017-12-01

    There is a chronic disconnection among purely probabilistic flood frequency analysis of flood hazards, flood risks, and hydrological flood mechanisms, which hamper our ability to assess future flood impacts. We present a vulnerability-based approach to estimating riverine flood risk that accommodates a more direct linkage between decision-relevant metrics of risk and the dominant mechanisms that cause riverine flooding. We adapt the conventional peaks-over-threshold (POT) framework to be used with extreme precipitation from different climate processes and rainfall-runoff-based model output. We quantify the probability that at least one adverse hydrologic threshold, potentially defined by stakeholders, will be exceeded within the next N years. This approach allows us to consider flood risk as the summation of risk from separate atmospheric mechanisms, and supports a more direct mapping between hazards and societal outcomes. We perform this analysis within a bottom-up framework to consider the relevance and consequences of information, with varying levels of credibility, on changes to atmospheric patterns driving extreme precipitation events. We demonstrate our proposed approach using a case study for Fall Creek in Ithaca, NY, USA, where we estimate the risk of stakeholder-defined flood metrics from three dominant mechanisms: summer convection, tropical cyclones, and spring rain and snowmelt. Using downscaled climate projections, we determine how flood risk associated with a subset of mechanisms may change in the future, and the resultant shift to annual flood risk. The flood risk approach we propose can provide powerful new insights into future flood threats.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. Development and Evaluation of a Simple, Multifactorial Model Based on Landing Performance to Indicate Injury Risk in Surfing Athletes.

    Science.gov (United States)

    Lundgren, Lina E; Tran, Tai T; Nimphius, Sophia; Raymond, Ellen; Secomb, Josh L; Farley, Oliver R L; Newton, Robert U; Steele, Julie R; Sheppard, Jeremy M

    2015-11-01

    To develop and evaluate a multifactorial model based on landing performance to estimate injury risk for surfing athletes. Five measures were collected from 78 competitive surfing athletes and used to create a model to serve as a screening tool for landing tasks and potential injury risk. In the second part of the study, the model was evaluated using junior surfing athletes (n = 32) with a longitudinal follow-up of their injuries over 26 wk. Two models were compared based on the collected data, and magnitude-based inferences were applied to determine the likelihood of differences between injured and noninjured groups. The study resulted in a model based on 5 measures--ankle-dorsiflexion range of motion, isometric midthigh-pull lower-body strength, time to stabilization during a drop-and-stick (DS) landing, relative peak force during a DS landing, and frontal-plane DS-landing video analysis--for male and female professional surfers and male and female junior surfers. Evaluation of the model showed that a scaled probability score was more likely to detect injuries in junior surfing athletes and reported a correlation of r = .66, P = .001, with a model of equal variable importance. The injured (n = 7) surfers had a lower probability score (0.18 ± 0.16) than the noninjured group (n = 25, 0.36 ± 0.15), with 98% likelihood, Cohen d = 1.04. The proposed model seems sensitive and easy to implement and interpret. Further research is recommended to show full validity for potential adaptations for other sports.

  5. A carbon risk prediction model for Chinese heavy-polluting industrial enterprises based on support vector machine

    International Nuclear Information System (INIS)

    Zhou, Zhifang; Xiao, Tian; Chen, Xiaohong; Wang, Chang

    2016-01-01

    Chinese heavy-polluting industrial enterprises, especially petrochemical or chemical industry, labeled low carbon efficiency and high emission load, are facing the tremendous pressure of emission reduction under the background of global shortage of energy supply and constrain of carbon emission. However, due to the limited amount of theoretic and practical research in this field, problems like lacking prediction indicators or models, and the quantified standard of carbon risk remain unsolved. In this paper, the connotation of carbon risk and an assessment index system for Chinese heavy-polluting industrial enterprises (eg. coal enterprise, petrochemical enterprises, chemical enterprises et al.) based on support vector machine are presented. By using several heavy-polluting industrial enterprises’ related data, SVM model is trained to predict the carbon risk level of a specific enterprise, which allows the enterprise to identify and manage its carbon risks. The result shows that this method can predict enterprise’s carbon risk level in an efficient, accurate way with high practical application and generalization value.

  6. New approaches to infection prevention and control: implementing a risk-based model regionally.

    Science.gov (United States)

    Wale, Martin; Kibsey, Pamela; Young, Lisa; Dobbyn, Beverly; Archer, Jana

    2016-06-01

    Infectious disease outbreaks result in substantial inconvenience to patients and disruption of clinical activity. Between 1 April 2008 and 31 March 2009, the Vancouver Island Health Authority (Island Health) declared 16 outbreaks of Vancomycin Resistant Enterococci and Clostridium difficile in acute care facilities. As a result, infection prevention and control became one of Island Health's highest priorities. Quality improvement methodology, which promotes a culture of co-production between front-line staff, physicians and Infection Control Practitioners, was used to develop and test a bundle of changes in practices. A series of rapid Plan-Do-Study-Act cycles, specific to decreasing hospital-acquired infections, were undertaken by a community hospital, selected for its size, clinical specialty representation, and enthusiasm amongst staff and physicians for innovation and change. Positive results were incorporated into practice at the test site, and then introduced throughout the rest of the Health Authority. The changes implemented as a result of this study have enabled better control of antibiotic resistant organisms and have minimized disruption to routine activity, as well as saving an estimated $6.5 million per annum. When outbreaks do occur, they are now controlled much more promptly, even in existing older facilities. Through this process, we have changed our approach in Infection Prevention and Control (IPAC) from a rules-based approach to one that is risk-based, focusing attention on identifying and managing high-risk situations. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

  7. Fuzzy rule-based modelling for human health risk from naturally occurring radioactive materials in produced water

    International Nuclear Information System (INIS)

    Shakhawat, Chowdhury; Tahir, Husain; Neil, Bose

    2006-01-01

    Produced water, discharged from offshore oil and gas operations, contains chemicals from formation water, condensed water, and any chemical added down hole or during the oil/water separation process. Although, most of the contaminants fall below the detection limits within a short distance from the discharge port, a few of the remaining contaminants including naturally occurring radioactive materials (NORM) are of concern due to their bioavailability in the media and bioaccumulation characteristics in finfish and shellfish species used for human consumption. In the past, several initiatives have been taken to model human health risk from NORM in produced water. The parameters of the available risk assessment models are imprecise and sparse in nature. In this study, a fuzzy possibilistic evaluation using fuzzy rule based modeling has been presented. Being conservative in nature, the possibilistic approach considers possible input parameter values; thus provides better environmental prediction than the Monte Carlo (MC) calculation. The uncertainties of the input parameters were captured with fuzzy triangular membership functions (TFNs). Fuzzy if-then rules were applied for input concentrations of two isotopes of radium, namely 226 Ra, and 228 Ra, available in produced water and bulk dilution to evaluate the radium concentration in fish tissue used for human consumption. The bulk dilution was predicted using four input parameters: produced water discharge rate, ambient seawater velocity, depth of discharge port and density gradient. The evaluated cancer risk shows compliance with the regulatory guidelines; thus minimum risk to human health is expected from NORM components in produced water

  8. 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.

  9. Choosing where to work at work - towards a theoretical model of benefits and risks of activity-based flexible offices.

    Science.gov (United States)

    Wohlers, Christina; Hertel, Guido

    2017-04-01

    Although there is a trend in today's organisations to implement activity-based flexible offices (A-FOs), only a few studies examine consequences of this new office type. Moreover, the underlying mechanisms why A-FOs might lead to different consequences as compared to cellular and open-plan offices are still unclear. This paper introduces a theoretical framework explaining benefits and risks of A-FOs based on theories from work and organisational psychology. After deriving working conditions specific for A-FOs (territoriality, autonomy, privacy, proximity and visibility), differences in working conditions between A-FOs and alternative office types are proposed. Further, we suggest how these differences in working conditions might affect work-related consequences such as well-being, satisfaction, motivation and performance on the individual, the team and the organisational level. Finally, we consider task-related (e.g. task variety), person-related (e.g. personality) and organisational (e.g. leadership) moderators. Based on this model, future research directions as well as practical implications are discussed. Practitioner Summary: Activity-based flexible offices (A-FOs) are popular in today's organisations. This article presents a theoretical model explaining why and when working in an A-FO evokes benefits and risks for individuals, teams and organisations. According to the model, A-FOs are beneficial when management encourages employees to use the environment appropriately and supports teams.

  10. Development of a risk prediction model for lung cancer: The Japan Public Health Center-based Prospective Study.

    Science.gov (United States)

    Charvat, Hadrien; Sasazuki, Shizuka; Shimazu, Taichi; Budhathoki, Sanjeev; Inoue, Manami; Iwasaki, Motoki; Sawada, Norie; Yamaji, Taiki; Tsugane, Shoichiro

    2018-03-01

    Although the impact of tobacco consumption on the occurrence of lung cancer is well-established, risk estimation could be improved by risk prediction models that consider various smoking habits, such as quantity, duration, and time since quitting. We constructed a risk prediction model using a population of 59 161 individuals from the Japan Public Health Center (JPHC) Study Cohort II. A parametric survival model was used to assess the impact of age, gender, and smoking-related factors (cumulative smoking intensity measured in pack-years, age at initiation, and time since cessation). Ten-year cumulative probability of lung cancer occurrence estimates were calculated with consideration of the competing risk of death from other causes. Finally, the model was externally validated using 47 501 individuals from JPHC Study Cohort I. A total of 1210 cases of lung cancer occurred during 986 408 person-years of follow-up. We found a dose-dependent effect of tobacco consumption with hazard ratios for current smokers ranging from 3.78 (2.00-7.16) for cumulative consumption ≤15 pack-years to 15.80 (9.67-25.79) for >75 pack-years. Risk decreased with time since cessation. Ten-year cumulative probability of lung cancer occurrence estimates ranged from 0.04% to 11.14% in men and 0.07% to 6.55% in women. The model showed good predictive performance regarding discrimination (cross-validated c-index = 0.793) and calibration (cross-validated χ 2 = 6.60; P-value = .58). The model still showed good discrimination in the external validation population (c-index = 0.772). In conclusion, we developed a prediction model to estimate the probability of developing lung cancer based on age, gender, and tobacco consumption. This model appears useful in encouraging high-risk individuals to quit smoking and undergo increased surveillance. © 2018 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

  11. Using Geographic Information System-based Ecologic Niche Models to Forecast the Risk of Hantavirus Infection in Shandong Province, China

    Science.gov (United States)

    Wei, Lan; Qian, Quan; Wang, Zhi-Qiang; Glass, Gregory E.; Song, Shao-Xia; Zhang, Wen-Yi; Li, Xiu-Jun; Yang, Hong; Wang, Xian-Jun; Fang, Li-Qun; Cao, Wu-Chun

    2011-01-01

    Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in Shandong Province, China. In this study, we combined ecologic niche modeling with geographic information systems (GIS) and remote sensing techniques to identify the risk factors and affected areas of hantavirus infections in rodent hosts. Land cover and elevation were found to be closely associated with the presence of hantavirus-infected rodent hosts. The averaged area under the receiver operating characteristic curve was 0.864, implying good performance. The predicted risk maps based on the model were validated both by the hantavirus-infected rodents' distribution and HFRS human case localities with a good fit. These findings have the applications for targeting control and prevention efforts. PMID:21363991

  12. Use of a risk-based hydrogeologic model to set remedial goals in a Puget Sound basin watershed

    International Nuclear Information System (INIS)

    Pascoe, G.; Gould, L.; Martin, J.; Riley, M.; Floyd, T.

    1995-01-01

    The Port of Seattle is redeveloping industrial land for a container terminal along the southwest Seattle waterfront. Concrete, asphalt, ballast, and a landfill geomembrane will cover the site and prevent direct contact with surface soils, so remedial goals focused on groundwater contamination from subsurface soils. Groundwater at the site flows along an old stormwater drain, in a filled estuary of a small creek, to Elliott Bay. Remedial goals for a variety of organic chemicals, metals, and TPH in subsurface soils were identified to protect marine receptors in the bay and their consumers. Washington State and federal marine water quality criteria were the starting points in the risk-based model, and corresponding concentrations of chemicals in groundwater were back-calculated through a hydrogeologic model. The hydrogeologic model included a mixing zone component in the bay and dilution/attenuation factors along the groundwater transport pathway that were determined from onsite groundwater and surface water chemical concentrations. A rearranged Summers equation was then applied in a second back-calculation to determine subsurface soil concentrations corresponding to the back calculated groundwater concentrations. The equation was based on calculated aquifer flow rates for the small creek watershed and rates of infiltration through surface materials calculated for each redevelopment soil cover type by the HELP model. Results of the risk-based hydrogeologic back-calculation model indicate that, depending on soil cover type at the site, concentrations in subsurface soils of PCBs from 2 to 1,000 mg/kg and of TPH up to free phase concentration would not result in risks to marine organisms or their consumers in Elliott Bay

  13. Research on Investment Risk Management of Chinese Prefabricated Construction Projects Based on a System Dynamics Model

    Directory of Open Access Journals (Sweden)

    Ming Li

    2017-09-01

    Full Text Available Prefabricated construction, a new direction for the future development of the Chinese construction industry, can maximize the requirements of “green”. As a new form of green building, prefabricated construction is of particular interest. On account of the immature development of the green building market in China, the investment risk for prefabricated construction is higher than for traditional architecture. Hence, it is especially important to improve its investment risk identification and management. This study adopts system dynamics and builds a risk identification feedback chart and risk flow chart, to comprehensively identify investment risks that projects in China may face and to process quantitative estimation of investment risk factors. Key factors influencing project investment risks are found, and corresponding measures are pointedly proposed. This paper may provide guidance and a reference for promoting the sound development of prefabricated construction in China.

  14. Toward risk assessment 2.0: Safety supervisory control and model-based hazard monitoring for risk-informed safety interventions

    International Nuclear Information System (INIS)

    Favarò, Francesca M.; Saleh, Joseph H.

    2016-01-01

    Probabilistic Risk Assessment (PRA) is a staple in the engineering risk community, and it has become to some extent synonymous with the entire quantitative risk assessment undertaking. Limitations of PRA continue to occupy researchers, and workarounds are often proposed. After a brief review of this literature, we propose to address some of PRA's limitations by developing a novel framework and analytical tools for model-based system safety, or safety supervisory control, to guide safety interventions and support a dynamic approach to risk assessment and accident prevention. Our work shifts the emphasis from the pervading probabilistic mindset in risk assessment toward the notions of danger indices and hazard temporal contingency. The framework and tools here developed are grounded in Control Theory and make use of the state-space formalism in modeling dynamical systems. We show that the use of state variables enables the definition of metrics for accident escalation, termed hazard levels or danger indices, which measure the “proximity” of the system state to adverse events, and we illustrate the development of such indices. Monitoring of the hazard levels provides diagnostic information to support both on-line and off-line safety interventions. For example, we show how the application of the proposed tools to a rejected takeoff scenario provides new insight to support pilots’ go/no-go decisions. Furthermore, we augment the traditional state-space equations with a hazard equation and use the latter to estimate the times at which critical thresholds for the hazard level are (b)reached. This estimation process provides important prognostic information and produces a proxy for a time-to-accident metric or advance notice for an impending adverse event. The ability to estimate these two hazard coordinates, danger index and time-to-accident, offers many possibilities for informing system control strategies and improving accident prevention and risk mitigation

  15. Risk-based safety indicators

    International Nuclear Information System (INIS)

    Szikszai, T.

    1997-01-01

    The presentation discusses the following issues: The objectives of the risk-based indicator programme. The characteristics of the risk-based indicators. The objectives of risk-based safety indicators - in monitoring safety; in PSA applications. What indicators? How to produce the risk based indicators? PSA requirements

  16. The application of cure models in the presence of competing risks: a tool for improved risk communication in population-based cancer patient survival.

    Science.gov (United States)

    Eloranta, Sandra; Lambert, Paul C; Andersson, Therese M-L; Björkholm, Magnus; Dickman, Paul W

    2014-09-01

    Quantifying cancer patient survival from the perspective of cure is clinically relevant. However, most cure models estimate cure assuming no competing causes of death. We use a relative survival framework to demonstrate how flexible parametric cure models can be used in combination with competing-risks theory to incorporate noncancer deaths. Under a model that incorporates statistical cure, we present the probabilities that cancer patients (1) have died from their cancer, (2) have died from other causes, (3) will eventually die from their cancer, or (4) will eventually die from other causes, all as a function of time since diagnosis. We further demonstrate how conditional probabilities can be used to update the prognosis among survivors (eg, at 1 or 5 years after diagnosis) by summarizing the proportion of patients who will not die from their cancer. The proposed method is applied to Swedish population-based data for persons diagnosed with melanoma, colon cancer, or acute myeloid leukemia between 1973 and 2007.

  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. A Risk Prediction Model Based on Lymph-Node Metastasis in Poorly Differentiated-Type Intramucosal Gastric Cancer.

    Directory of Open Access Journals (Sweden)

    Jeung Hui Pyo

    Full Text Available Endoscopic submucosal dissection (ESD for undifferentiated type early gastric cancer is regarded as an investigational treatment. Few studies have tried to identify the risk factors that predict lymph-node metastasis (LNM in intramucosal poorly differentiated adenocarcinomas (PDC. This study was designed to develop a risk scoring system (RSS for predicting LNM in intramucosal PDC.From January 2002 to July 2015, patients diagnosed with mucosa-confined PDC, among those who underwent curative gastrectomy with lymph node dissection were reviewed. A risk model based on independent predicting factors of LNM was developed, and its performance was internally validated using a split sample approach.Overall, LNM was observed in 5.2% (61 of 1169 patients. Four risk factors [Female sex, tumor size ≥ 3.2 cm, muscularis mucosa (M3 invasion, and lymphatic-vascular involvement] were significantly associated with LNM, which were incorporated into the RSS. The area under the receiver operating characteristic curve for predicting LNM after internal validation was 0.69 [95% confidence interval (CI, 0.59-0.79]. A total score of 2 points corresponded to the optimal RSS threshold with a discrimination of 0.75 (95% CI 0.69-0.81. The LNM rates were 1.6% for low risk (<2 points and 8.9% for high-risk (≥2 points patients, with a negative predictive value of 98.6% (95% CI 0.98-1.00.A RSS could be useful in clinical practice to determine which patients with intramucosal PDC have low risk of LNM.

  19. A bayesian nework based risk model for volume loss in soft soils in mechanized bored tunnels

    NARCIS (Netherlands)

    Chivatá Cárdenas, Ibsen; Al-Jibouri, Saad H.S.; Halman, Johannes I.M.

    2012-01-01

    Volume loss is one of the most important risks when boring a tunnel. This is particularly true when a tunnel is being constructed in soft soils. The risk of excessive volume loss, if materialised can lead to large consequences such as damage in buildings on the surface. This paper describes the

  20. 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...

  1. Stochastic Model Predictive Fault Tolerant Control Based on Conditional Value at Risk for Wind Energy Conversion System

    Directory of Open Access Journals (Sweden)

    Yun-Tao Shi

    2018-01-01

    Full Text Available Wind energy has been drawing considerable attention in recent years. However, due to the random nature of wind and high failure rate of wind energy conversion systems (WECSs, how to implement fault-tolerant WECS control is becoming a significant issue. This paper addresses the fault-tolerant control problem of a WECS with a probable actuator fault. A new stochastic model predictive control (SMPC fault-tolerant controller with the Conditional Value at Risk (CVaR objective function is proposed in this paper. First, the Markov jump linear model is used to describe the WECS dynamics, which are affected by many stochastic factors, like the wind. The Markov jump linear model can precisely model the random WECS properties. Second, the scenario-based SMPC is used as the controller to address the control problem of the WECS. With this controller, all the possible realizations of the disturbance in prediction horizon are enumerated by scenario trees so that an uncertain SMPC problem can be transformed into a deterministic model predictive control (MPC problem. Finally, the CVaR object function is adopted to improve the fault-tolerant control performance of the SMPC controller. CVaR can provide a balance between the performance and random failure risks of the system. The Min-Max performance index is introduced to compare the fault-tolerant control performance with the proposed controller. The comparison results show that the proposed method has better fault-tolerant control performance.

  2. 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.

  3. 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

  4. 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…

  5. Risk-based high-throughput chemical screening and prioritization using exposure models and in vitro bioactivity assays

    DEFF Research Database (Denmark)

    Shin, Hyeong-Moo; Ernstoff, Alexi; Arnot, Jon

    2015-01-01

    We present a risk-based high-throughput screening (HTS) method to identify chemicals for potential health concerns or for which additional information is needed. The method is applied to 180 organic chemicals as a case study. We first obtain information on how the chemical is used and identify....../oral contact, or dermal exposure. The method provides high-throughput estimates of exposure and important input for decision makers to identify chemicals of concern for further evaluation with additional information or more refined models....

  6. Estimating the value of a Country's built assets: investment-based exposure modelling for global risk assessment

    Science.gov (United States)

    Daniell, James; Pomonis, Antonios; Gunasekera, Rashmin; Ishizawa, Oscar; Gaspari, Maria; Lu, Xijie; Aubrecht, Christoph; Ungar, Joachim

    2017-04-01

    In order to quantify disaster risk, there is a demand and need for determining consistent and reliable economic value of built assets at national or sub national level exposed to natural hazards. The value of the built stock in the context of a city or a country is critical for risk modelling applications as it allows for the upper bound in potential losses to be established. Under the World Bank probabilistic disaster risk assessment - Country Disaster Risk Profiles (CDRP) Program and rapid post-disaster loss analyses in CATDAT, key methodologies have been developed that quantify the asset exposure of a country. In this study, we assess the complementary methods determining value of building stock through capital investment data vs aggregated ground up values based on built area and unit cost of construction analyses. Different approaches to modelling exposure around the world, have resulted in estimated values of built assets of some countries differing by order(s) of magnitude. Using the aforementioned methodology of comparing investment data based capital stock and bottom-up unit cost of construction values per square meter of assets; a suitable range of capital stock estimates for built assets have been created. A blind test format was undertaken to compare the two types of approaches from top-down (investment) and bottom-up (construction cost per unit), In many cases, census data, demographic, engineering and construction cost data are key for bottom-up calculations from previous years. Similarly for the top-down investment approach, distributed GFCF (Gross Fixed Capital Formation) data is also required. Over the past few years, numerous studies have been undertaken through the World Bank Caribbean and Central America disaster risk assessment program adopting this methodology initially developed by Gunasekera et al. (2015). The range of values of the building stock is tested for around 15 countries. In addition, three types of costs - Reconstruction cost

  7. 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...

  8. The use of long range identification and tracking (LRIT) for modelling the risk of ship-based oil spills

    Energy Technology Data Exchange (ETDEWEB)

    Szeto, Andrew [Canadian Coast Guard (Canada)], email: andrew.szeto@dfo-mpo.gc.ca; Pelot, Ronald [Dalhousie University (Canada)], email: ronald.pelot@dal.ca

    2011-07-01

    Accidents involving oil tankers have caused many and sometimes very large oil spills. Such spills to marine areas have a significant impact on environmental quality affecting all aspects of marine ecosystems. Based on valid shipping traffic data as a very important factor that must be considered in modeling the risk of ship-based oil spills, this paper shows the importance of use of the long-range identification and tracking (LRIT) system and looks at how it can be implemented to better assess ship-based oil pollution. The system is a new, accurate and reliable world-wide vessel tracking system with a range of data extended out to 1000 nm from Canadian shores and currently tracks up to about 900 vessels a day in real-time. It is believed that traffic data and effective monitoring can assist with search planning for detection of mystery spills, better resource deployment for spill mitigation, and improving information for research and management.

  9. Escherichia coli pollution in a Baltic Sea lagoon: a model-based source and spatial risk assessment.

    Science.gov (United States)

    Schippmann, Bianca; Schernewski, Gerald; Gräwe, Ulf

    2013-07-01

    Tourism around the Oder (Szczecin) Lagoon, at the southern Baltic coast, has a long tradition, is an important source of income and shall be further developed. Insufficient bathing water quality and frequent beach closings, especially in the Oder river mouth, hamper tourism development. Monitoring data gives only an incomplete picture of Escherichia coli (E. coli) bacteria sources, spatial transport patterns, risks and does neither support an efficient bathing water quality management nor decision making. We apply a 3D ocean model and a Lagrangian particle tracking model to analyse pollution events and to obtain spatial E. coli pollution maps based on scenario simulations. Model results suggests that insufficient sewage treatment in the city of Szczecin is the major source of faecal pollution, even for beaches 20km downstream. E. coli mortality rate and emission intensity are key parameters for concentration levels downstream. Wind and river discharge play a modifying role. Prevailing southwestern wind conditions cause E. coli transport along the eastern coast and favour high concentration levels at the beaches. Our simulations indicate that beach closings in 2006 would not have been necessary according to the new EU-Bathing Water Quality Directive (2006/7/EC). The implementation of the new directive will, very likely, reduce the number of beach closings, but not the risk for summer tourists. Model results suggest, that a full sewage treatment in Szczecin would allow the establishment of new beaches closer to the city (north of Dabie lake). Copyright © 2013 Elsevier GmbH. All rights reserved.

  10. 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.

  11. A risk-based multi-objective model for optimal placement of sensors in water distribution system

    Science.gov (United States)

    Naserizade, Sareh S.; Nikoo, Mohammad Reza; Montaseri, Hossein

    2018-02-01

    In this study, a new stochastic model based on Conditional Value at Risk (CVaR) and multi-objective optimization methods is developed for optimal placement of sensors in water distribution system (WDS). This model determines minimization of risk which is caused by simultaneous multi-point contamination injection in WDS using CVaR approach. The CVaR considers uncertainties of contamination injection in the form of probability distribution function and calculates low-probability extreme events. In this approach, extreme losses occur at tail of the losses distribution function. Four-objective optimization model based on NSGA-II algorithm is developed to minimize losses of contamination injection (through CVaR of affected population and detection time) and also minimize the two other main criteria of optimal placement of sensors including probability of undetected events and cost. Finally, to determine the best solution, Preference Ranking Organization METHod for Enrichment Evaluation (PROMETHEE), as a subgroup of Multi Criteria Decision Making (MCDM) approach, is utilized to rank the alternatives on the trade-off curve among objective functions. Also, sensitivity analysis is done to investigate the importance of each criterion on PROMETHEE results considering three relative weighting scenarios. The effectiveness of the proposed methodology is examined through applying it to Lamerd WDS in the southwestern part of Iran. The PROMETHEE suggests 6 sensors with suitable distribution that approximately cover all regions of WDS. Optimal values related to CVaR of affected population and detection time as well as probability of undetected events for the best optimal solution are equal to 17,055 persons, 31 mins and 0.045%, respectively. The obtained results of the proposed methodology in Lamerd WDS show applicability of CVaR-based multi-objective simulation-optimization model for incorporating the main uncertainties of contamination injection in order to evaluate extreme value

  12. Predictive Accuracy of the PanCan Lung Cancer Risk Prediction Model -External Validation based on CT from the Danish Lung Cancer Screening Trial

    DEFF Research Database (Denmark)

    Winkler Wille, Mathilde M.; van Riel, Sarah J.; Saghir, Zaigham

    2015-01-01

    Objectives: Lung cancer risk models should be externally validated to test generalizability and clinical usefulness. The Danish Lung Cancer Screening Trial (DLCST) is a population-based prospective cohort study, used to assess the discriminative performances of the PanCan models. Methods: From...... the DLCST database, 1,152 nodules from 718 participants were included. Parsimonious and full PanCan risk prediction models were applied to DLCST data, and also coefficients of the model were recalculated using DLCST data. Receiver operating characteristics (ROC) curves and area under the curve (AUC) were...... used to evaluate risk discrimination. Results: AUCs of 0.826–0.870 were found for DLCST data based on PanCan risk prediction models. In the DLCST, age and family history were significant predictors (p = 0.001 and p = 0.013). Female sex was not confirmed to be associated with higher risk of lung cancer...

  13. Mode of action based risk assessment of the botanical food-borne alkenylbenzene apiol from parsley using physiologically based kinetic (PBK) modelling and read-across from safrole.

    Science.gov (United States)

    Alajlouni, Abdalmajeed M; Al Malahmeh, Amer J; Kiwamoto, Reiko; Wesseling, Sebastiaan; Soffers, Ans E M F; Al-Subeihi, Ala A A; Vervoort, Jacques; Rietjens, Ivonne M C M

    2016-03-01

    The present study developed physiologically-based kinetic (PBK) models for the alkenylbenzene apiol in order to facilitate risk assessment based on read-across from the related alkenylbenzene safrole. Model predictions indicate that in rat liver the formation of the 1'-sulfoxy metabolite is about 3 times lower for apiol than for safrole. These data support that the lower confidence limit of the benchmark dose resulting in a 10% extra cancer incidence (BMDL10) that would be obtained in a rodent carcinogenicity study with apiol may be 3-fold higher for apiol than for safrole. These results enable a preliminary risk assessment for apiol, for which tumor data are not available, using a BMDL10 value of 3 times the BMDL10 for safrole. Based on an estimated BMDL10 for apiol of 5.7-15.3 mg/kg body wt per day and an estimated daily intake of 4 × 10(-5) mg/kg body wt per day, the margin of exposure (MOE) would amount to 140,000-385,000. This indicates a low priority for risk management. The present study shows how PBK modelling can contribute to the development of alternatives for animal testing, facilitating read-across from compounds for which in vivo toxicity studies on tumor formation are available to compounds for which these data are unavailable. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  14. Towards a resource-based habitat approach for spatial modelling of vector-borne disease risks

    NARCIS (Netherlands)

    Hartemink, N.; Vanwambeke, S.O.; Purse, B.V.; Gilbert, M.; Van Dyck, H.

    2015-01-01

    Given the veterinary and public health impact of vector-borne diseases, there is a clear need to assess the suitability of landscapes for the emergence and spread of these diseases. Current approaches for predicting disease risks neglect key features of the landscape as components of the functional

  15. Intelligent judgements over health risks in a spatial agent-based model

    NARCIS (Netherlands)

    Abdulkareem, Shaheen A.; Augustijn, Ellen Wien; Mustafa, Yaseen T.; Filatova, Tatiana

    2018-01-01

    Background: Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more

  16. Genetic background and 227Thorium as risk factors in biologically based models for induction of bone cancer in mice

    International Nuclear Information System (INIS)

    Heidenreich, W.F.; Rosemann, M.

    2012-01-01

    We explore the potential for the biologically based two-stage clonal expansion model to make statements about the influence of genetic factors on the steps in the model. We find evidence that the different susceptibility of BALB/C and CBA/Ca mice to bone cancer after 227 Thorium injection may be mostly due to different promotional responses to radiation. In BALB/C x CBA/Ca back-crossed mice, we analyzed the specific contribution of two individual loci in the carcinogenic process. This analysis suggests that the two high- or low-risk alleles are acting on promotion or on the background parameters, but not on radiation-induced initiation. Taken together with the comparison of CBA/Ca and BALB/C mice, this hints at the possibility that the two loci are candidates for modifying radiation-induced promotion. (orig.)

  17. Evaluating the Risk of Metabolic Syndrome Based on an Artificial Intelligence Model

    OpenAIRE

    Chen, Hui; Xiong, Shenghua; Ren, Xuan

    2014-01-01

    Metabolic syndrome is worldwide public health problem and is a serious threat to people's health and lives. Understanding the relationship between metabolic syndrome and the physical symptoms is a difficult and challenging task, and few studies have been performed in this field. It is important to classify adults who are at high risk of metabolic syndrome without having to use a biochemical index and, likewise, it is important to develop technology that has a high economic rate of return to s...

  18. Robust Coordination of Autonomous Systems through Risk-sensitive, Model-based Programming and Execution

    Science.gov (United States)

    2015-10-09

    execution to halt immediately, leading to conservatism . 5.2 Searching for optimal, risk-bounded cRMPL pro- grams Because cRMPL supports programs that...the timing re- quirements with probabilistic guarantees without undue conservatism . 6.1 Problem Statement In field deployment on critical missions, the...the space of potential solution policies in domains with non-destructive constraint violations, leading to conservatism . A CC-POMDP formu- lation, on

  19. Applying a machine learning model using a locally preserving projection based feature regeneration algorithm to predict breast cancer risk

    Science.gov (United States)

    Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Mirniaharikandehei, Seyedehnafiseh; Qian, Wei; Zheng, Bin

    2018-03-01

    Both conventional and deep machine learning has been used to develop decision-support tools applied in medical imaging informatics. In order to take advantages of both conventional and deep learning approach, this study aims to investigate feasibility of applying a locally preserving projection (LPP) based feature regeneration algorithm to build a new machine learning classifier model to predict short-term breast cancer risk. First, a computer-aided image processing scheme was used to segment and quantify breast fibro-glandular tissue volume. Next, initially computed 44 image features related to the bilateral mammographic tissue density asymmetry were extracted. Then, an LLP-based feature combination method was applied to regenerate a new operational feature vector using a maximal variance approach. Last, a k-nearest neighborhood (KNN) algorithm based machine learning classifier using the LPP-generated new feature vectors was developed to predict breast cancer risk. A testing dataset involving negative mammograms acquired from 500 women was used. Among them, 250 were positive and 250 remained negative in the next subsequent mammography screening. Applying to this dataset, LLP-generated feature vector reduced the number of features from 44 to 4. Using a leave-onecase-out validation method, area under ROC curve produced by the KNN classifier significantly increased from 0.62 to 0.68 (p breast cancer detected in the next subsequent mammography screening.

  20. Using physiologically based pharmacokinetic (PBPK) modeling for dietary risk assessment of titanium dioxide (TiO2) nanoparticles.

    Science.gov (United States)

    Bachler, Gerald; von Goetz, Natalie; Hungerbuhler, Konrad

    2015-05-01

    Nano-sized titanium dioxide particles (nano-TiO2) can be found in a large number of foods and consumer products, such as cosmetics and toothpaste, thus, consumer exposure occurs via multiple sources, possibly involving different exposure routes. In order to determine the disposition of nano-TiO2 particles that are taken up, a physiologically based pharmacokinetic (PBPK) model was developed. High priority was placed on limiting the number of parameters to match the number of underlying data points (hence to avoid overparameterization), but still reflecting available mechanistic information on the toxicokinetics of nano-TiO2. To this end, the biodistribution of nano-TiO2 was modeled based on their ability to cross the capillary wall of the organs and to be phagocytosed in the mononuclear phagocyte system (MPS). The model's predictive power was evaluated by comparing simulated organ levels to experimentally assessed organ levels of independent in vivo studies. The results of our PBPK model indicate that: (1) within the application domain of the PBPK model from 15 to 150 nm, the size and crystalline structure of the particles had a minor influence on the biodistribution; and (2) at high internal exposure the particles agglomerate in vivo and are subsequently taken up by macrophages in the MPS. Furthermore, we also give an example on how the PBPK model may be used for risk assessment. For this purpose, the daily dietary intake of nano-TiO2 was calculated for the German population. The PBPK model was then used to convert this chronic external exposure into internal titanium levels for each organ.

  1. 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

  2. Developing a Risk Model for Fire in Passenger Ships - Based on Bayesian Belief Network

    OpenAIRE

    Dokmo, Hanne Bjørkås

    2016-01-01

    Passenger ships, especially cruise ships, are rapidly increasing in size. With larger vessels, comes a greater risk to the passengers if something where to happen. A fire on a passenger vessel can spread quickly, and with as much as thousands of people needing to be evacuated many things could go wrong. The issue of the safety on board is therefore crucial to consider, seeing as the consequences could be tremendous. There are three types of passenger ships; Passenger vessel, RoPax vessel and ...

  3. Risk-based configuration control

    International Nuclear Information System (INIS)

    Szikszai, T.

    1997-01-01

    The presentation discusses the following issues: The Configuration Control; The Risk-based Configuration Control (during power operation mode, and during shutdown mode). PSA requirements. Use of Risk-based Configuration Control System. Configuration Management (basic elements, benefits, information requirements)

  4. 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

  5. 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

  6. Modelling soil erosion risk based on RUSLE-3D using GIS in a ...

    Indian Academy of Sciences (India)

    2016-08-26

    watershed ... Click here to view fulltext PDF ... The RUSLE-3D (Revised Universal Soil Loss Equation-3D) model was implemented in geographic information system (GIS) for predicting the soil loss and the spatial patterns of soil ...

  7. Risk of Cyberterrorism to Naval Ships Inport Naval Station Everett: A Model Based Project Utilizing SIAM

    National Research Council Canada - National Science Library

    Tester, Rodrick A

    2007-01-01

    .... In doing so, an influence net model was designed to discover the likelihood of a successful cyber attack However, first it was necessary to establish what the best mitigation tools are in defense...

  8. Risk of Cyberterrorism to Naval Ships Inport Naval Station Everett: A Model Based Project Utilizing SIAM

    National Research Council Canada - National Science Library

    Tester, Rodrick A

    2007-01-01

    Based on numerous high level concerns that the cyber threat is expected to increase, as well as the already documented uses of cyber warfare, it is necessary to ensure our naval ships are hardened against such attacks...

  9. The Risk Assessment Study for Electric Power Marketing Competitiveness Based on Cloud Model and TOPSIS

    Science.gov (United States)

    Li, Cunbin; Wang, Yi; Lin, Shuaishuai

    2017-09-01

    With the rapid development of the energy internet and the deepening of the electric power reform, the traditional marketing mode of electric power does not apply to most of electric power enterprises, so must seek a breakthrough, however, in the face of increasingly complex marketing information, how to make a quick, reasonable transformation, makes the electric power marketing competitiveness assessment more accurate and objective becomes a big problem. In this paper, cloud model and TOPSIS method is proposed. Firstly, build the electric power marketing competitiveness evaluation index system. Then utilize the cloud model to transform the qualitative evaluation of the marketing data into quantitative values and use the entropy weight method to weaken the subjective factors of evaluation index weight. Finally, by TOPSIS method the closeness degrees of alternatives are obtained. This method provides a novel solution for the electric power marketing competitiveness evaluation. Through the case analysis the effectiveness and feasibility of this model are verified.

  10. Probabilistic risk model for staphylococcal intoxication from pork-based food dishes prepared in food service establishments in Korea.

    Science.gov (United States)

    Kim, Hyun Jung; Griffiths, Mansel W; Fazil, Aamir M; Lammerding, Anna M

    2009-09-01

    Foodborne illness contracted at food service operations is an important public health issue in Korea. In this study, the probabilities for growth of, and enterotoxin production by, Staphylococcus aureus in pork meat-based foods prepared in food service operations were estimated by the Monte Carlo simulation. Data on the prevalence and concentration of S. aureus as well as compliance to guidelines for time and temperature controls during food service operations were collected. The growth of S. aureus was initially estimated by using the U.S. Department of Agriculture's Pathogen Modeling Program. A second model based on raw pork meat was derived to compare cell number predictions. The correlation between toxin level and cell number as well as minimum toxin dose obtained from published data was adopted to quantify the probability of staphylococcal intoxication. When data gaps were found, assumptions were made based on guidelines for food service practices. Baseline risk model and scenario analyses were performed to indicate possible outcomes of staphylococcal intoxication under the scenarios generated based on these data gaps. Staphylococcal growth was predicted during holding before and after cooking, and the highest estimated concentration (4.59 log CFU/g for the 99.9th percentile value) of S. aureus was observed in raw pork initially contaminated with S. aureus and held before cooking. The estimated probability for staphylococcal intoxication was very low, using currently available data. However, scenario analyses revealed an increased possibility of staphylococcal intoxication when increased levels of initial contamination in the raw meat, andlonger holding time both before and after cooking the meat occurred.

  11. A Practical Probabilistic Graphical Modeling Tool for Weighing Ecological Risk-Based Evidence

    Science.gov (United States)

    Past weight-of-evidence frameworks for adverse ecological effects have provided soft-scoring procedures for judgments based on the quality and measured attributes of evidence. Here, we provide a flexible probabilistic structure for weighing and integrating lines of evidence for e...

  12. Overview of Dioxin Kinetics and Application of Dioxin Physiologically Based Phannacokinetic (PBPK) Models to Risk Assessment

    Science.gov (United States)

    The available data on the pharmacokinetics of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in animals and humans have been thoroughly reviewed in literature. It is evident based on these reviews and other analyses that three distinctive features of TCDD play important roles in dete...

  13. 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.)

  14. 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.

  15. 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.

  16. Predictive accuracy of the PanCan lung cancer risk prediction model - external validation based on CT from the Danish Lung Cancer Screening Trial

    International Nuclear Information System (INIS)

    Winkler Wille, Mathilde M.; Dirksen, Asger; Riel, Sarah J. van; Jacobs, Colin; Scholten, Ernst T.; Ginneken, Bram van; Saghir, Zaigham; Pedersen, Jesper Holst; Hohwue Thomsen, Laura; Skovgaard, Lene T.

    2015-01-01

    Lung cancer risk models should be externally validated to test generalizability and clinical usefulness. The Danish Lung Cancer Screening Trial (DLCST) is a population-based prospective cohort study, used to assess the discriminative performances of the PanCan models. From the DLCST database, 1,152 nodules from 718 participants were included. Parsimonious and full PanCan risk prediction models were applied to DLCST data, and also coefficients of the model were recalculated using DLCST data. Receiver operating characteristics (ROC) curves and area under the curve (AUC) were used to evaluate risk discrimination. AUCs of 0.826-0.870 were found for DLCST data based on PanCan risk prediction models. In the DLCST, age and family history were significant predictors (p = 0.001 and p = 0.013). Female sex was not confirmed to be associated with higher risk of lung cancer; in fact opposing effects of sex were observed in the two cohorts. Thus, female sex appeared to lower the risk (p = 0.047 and p = 0.040) in the DLCST. High risk discrimination was validated in the DLCST cohort, mainly determined by nodule size. Age and family history of lung cancer were significant predictors and could be included in the parsimonious model. Sex appears to be a less useful predictor. (orig.)

  17. Predictive accuracy of the PanCan lung cancer risk prediction model - external validation based on CT from the Danish Lung Cancer Screening Trial

    Energy Technology Data Exchange (ETDEWEB)

    Winkler Wille, Mathilde M.; Dirksen, Asger [Gentofte Hospital, Department of Respiratory Medicine, Hellerup (Denmark); Riel, Sarah J. van; Jacobs, Colin; Scholten, Ernst T.; Ginneken, Bram van [Radboud University Medical Center, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands); Saghir, Zaigham [Herlev Hospital, Department of Respiratory Medicine, Herlev (Denmark); Pedersen, Jesper Holst [Copenhagen University Hospital, Department of Thoracic Surgery, Rigshospitalet, Koebenhavn Oe (Denmark); Hohwue Thomsen, Laura [Hvidovre Hospital, Department of Respiratory Medicine, Hvidovre (Denmark); Skovgaard, Lene T. [University of Copenhagen, Department of Biostatistics, Koebenhavn Oe (Denmark)

    2015-10-15

    Lung cancer risk models should be externally validated to test generalizability and clinical usefulness. The Danish Lung Cancer Screening Trial (DLCST) is a population-based prospective cohort study, used to assess the discriminative performances of the PanCan models. From the DLCST database, 1,152 nodules from 718 participants were included. Parsimonious and full PanCan risk prediction models were applied to DLCST data, and also coefficients of the model were recalculated using DLCST data. Receiver operating characteristics (ROC) curves and area under the curve (AUC) were used to evaluate risk discrimination. AUCs of 0.826-0.870 were found for DLCST data based on PanCan risk prediction models. In the DLCST, age and family history were significant predictors (p = 0.001 and p = 0.013). Female sex was not confirmed to be associated with higher risk of lung cancer; in fact opposing effects of sex were observed in the two cohorts. Thus, female sex appeared to lower the risk (p = 0.047 and p = 0.040) in the DLCST. High risk discrimination was validated in the DLCST cohort, mainly determined by nodule size. Age and family history of lung cancer were significant predictors and could be included in the parsimonious model. Sex appears to be a less useful predictor. (orig.)

  18. [A risk-based monitoring model for health care service institutions as a tool to protect health rights in Peru].

    Science.gov (United States)

    Benites-Zapata, Vicente A; Saravia-Chong, Héctor A; Mezones-Holguin, Edward; Aquije-Díaz, Allen J; Villegas-Ortega, José; Rossel-de-Almeida, Gustavo; Acosta-Saal, Carlos; Philipps-Cuba, Flor

    2016-01-01

    To describe the monitoring model of the Health Care Service Institutions (HCSI) of the National Health Authority (NHA) and assess the factors associated with risk-adjusted normative compliance (%RANC) within the Peruvian Health System (PHS). We carried out a case study of the experience of the NHA in the development and implementation of a monitoring program based on the ISO 31000-2009. With HCSI as the units of analysis, we calculated the %RANC (a scorein continuous scale ranging from 0 to 100) for comprehensive monitoring (CM) and for specific evaluations made from 2013 to 2015. A higher score in the %RANC means lower operational risk. Also, slope coefficients (β) and their 95% confidence intervals (95% CI) were estimated using generalized linear models to estimate the association between %RANC as outcome, and health subsector, region, level of care and year, as explanatory variables. The NHA made 1444 evaluations. For CM, only the Social Security Administration had higher %RANC than private centers (β=7.7%; 95% CI 3.5 to 11.9). The HCSI of the coastal region (β=-5.2, 95% CI -9.4 to -1.0), andean region (β=-12.5; 95% CI -16.7 to -8.3) and jungle region (β=-12.6, 95% CI% -17.7 to -7.6) had lower %RANC than those located in Lima Metropolitan area. %RANC was higher in 2015 than 2013 (β=10.8; 95% CI 6.4 to 15.3). The %RANC differs by health subsector, region and year of supervision. For CM, the HCSI in the Social Security Administration and in the Lima Metropolitan area had better scores, and scores improved over time. The implementation of actions aimed at improving %RANC in order to foster the full exercise of health rights in the PHS is suggested.

  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. 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.

  1. Predictive Accuracy of the PanCan Lung Cancer Risk Prediction Model -External Validation based on CT from the Danish Lung Cancer Screening Trial

    NARCIS (Netherlands)

    Wille, M.M.W.; Riel, S.J. van; Saghir, Z.; Dirksen, A.; Pedersen, J.H.; Jacobs, C.; Thomsen, L.H.u.; Scholten, E.T.; Skovgaard, L.T.; Ginneken, B. van

    2015-01-01

    Lung cancer risk models should be externally validated to test generalizability and clinical usefulness. The Danish Lung Cancer Screening Trial (DLCST) is a population-based prospective cohort study, used to assess the discriminative performances of the PanCan models.From the DLCST database, 1,152

  2. Screening Models for Cardiac Risk Evaluation in Emergency Abdominal Surgery. I. Evaluation of the Intraoperative Period Risk based on Data from the Preoperative Period

    Directory of Open Access Journals (Sweden)

    Mikhail Matveev

    2008-04-01

    Full Text Available A classification of intraoperative cardio-vascular complications (CVC was performed, based on data from 466 patients subjected to emergency surgery, due to severe abdominal surgical diseases or traumas, in accordance with the severe criteria of ACC/AHA for CVC in noncardiac surgery. There were 370 intraoperative CVC registered, distributed as follows: groups with low risk (148, moderate risk (200, and high risk (22. Patient groups were formed, according to the CVC risk level, during the intraoperative period, for which the determinant factor for the group distribution of patients was the complication with the highest risk. Individual data was collected for each patient, based on 65 indices: age, physical status, diseases, surgical interventions, anaesthesiological information, intra and postoperative cardio-vascular complications, disease outcome, causes of death, cardiovascular disease anamnesis, anamnesis of all other nonsurgical diseases present, laboratory results, results from all imaging and instrumental examinations, etc. On the basis of these indices, a new distribution of the risk factors was implemented, into groups with different levels of risk of CVC during intraoperative period. This result is a solid argument, substantiating the proposal to introduce these adjustments for determining the severity of CVC in the specific conditions of emergency abdominal surgery.

  3. 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.

  4. Risk-based high-throughput chemical screening and prioritization using exposure models and in vitro bioactivity assays

    International Nuclear Information System (INIS)

    Shin, Hyeong-Moo; Ernstoff, Alexi; Csiszar, Susan A.

    2015-01-01

    We present a risk-based high-throughput screening (HTS) method to identify chemicals for potential health concerns or for which additional information is needed. The method is applied to 180 organic chemicals as a case study. We first obtain information on how the chemical is used and identify relevant use scenarios (e.g., dermal application, indoor emissions). For each chemical and use scenario, exposure models are then used to calculate a chemical intake fraction, or a product intake fraction, accounting for chemical properties and the exposed population. We then combine these intake fractions with use scenario-specific estimates of chemical quantity to calculate daily intake rates (iR; mg/kg/day). These intake rates are compared to oral equivalent doses (OED; mg/kg/day), calculated from a suite of ToxCast in vitro bioactivity assays using in vitro-to-in vivo extrapolation and reverse dosimetry. Bioactivity quotients (BQs) are calculated as iR/OED to obtain estimates of potential impact associated with each relevant use scenario. Of the 180 chemicals considered, 38 had maximum iRs exceeding minimum OEDs (i.e., BQs > 1). For most of these compounds, exposures are associated with direct intake, food/oral contact, or dermal exposure. The method provides high-throughput estimates of exposure and important input for decision makers to identify chemicals of concern for further evaluation with additional information or more refined models

  5. Risk assessment of agricultural water requirement based on a multi-model ensemble framework, southwest of Iran

    Science.gov (United States)

    Zamani, Reza; Akhond-Ali, Ali-Mohammad; Roozbahani, Abbas; Fattahi, Rouhollah

    2017-08-01

    Water shortage and climate change are the most important issues of sustainable agricultural and water resources development. Given the importance of water availability in crop production, the present study focused on risk assessment of climate change impact on agricultural water requirement in southwest of Iran, under two emission scenarios (A2 and B1) for the future period (2025-2054). A multi-model ensemble framework based on mean observed temperature-precipitation (MOTP) method and a combined probabilistic approach Long Ashton Research Station-Weather Generator (LARS-WG) and change factor (CF) have been used for downscaling to manage the uncertainty of outputs of 14 general circulation models (GCMs). The results showed an increasing temperature in all months and irregular changes of precipitation (either increasing or decreasing) in the future period. In addition, the results of the calculated annual net water requirement for all crops affected by climate change indicated an increase between 4 and 10 %. Furthermore, an increasing process is also expected regarding to the required water demand volume. The most and the least expected increase in the water demand volume is about 13 and 5 % for A2 and B1 scenarios, respectively. Considering the results and the limited water resources in the study area, it is crucial to provide water resources planning in order to reduce the negative effects of climate change. Therefore, the adaptation scenarios with the climate change related to crop pattern and water consumption should be taken into account.

  6. A spatially-based modeling framework for assessing the risks of soil-associated metals to bats

    International Nuclear Information System (INIS)

    Hernout, Béatrice V.; Somerwill, Kate E.; Arnold, Kathryn E.; McClean, Colin J.; Boxall, Alistair B.A.

    2013-01-01

    Populations of some species of bats are declining in some regions of Europe. These declines are probably due to a range of pressures, including climate change, urbanization and exposure to toxins such as metals. This paper describes the development, paramaterisation and application of a spatially explicit modeling framework to predict the risks of soil-associated metals (lead, copper, zinc and cadmium) to bat health. Around 5.9% of areas where bats reside were predicted to have lead levels that pose a risk to bat health. For copper, this value was 2.8%, for cadmium it was 0.6% and for zinc 0.5%. Further work is therefore warranted to explore the impacts of soil-associated metals on bat populations in the UK. - Highlights: ► A modeling framework is presented to estimate risks of contaminants to wildlife. ► The model has been applied to soil metal contamination and bat species. ► Results indicate that lead and copper pose the greatest risk to bat health. ► A risk is predicted for up to 6% of areas where bats reside in England and Wales. - Application of a novel, spatially explicit risk assessment framework indicates that the health of insectivorous bat species in some regions of the UK may be at threat from exposure to soil associated metals.

  7. Risk-based performance indicators

    International Nuclear Information System (INIS)

    Azarm, M.A.; Boccio, J.L.; Vesely, W.E.; Lofgren, E.

    1987-01-01

    The purpose of risk-based indicators is to monitor plant safety. Safety is measured by monitoring the potential for core melt (core-melt frequency) and the public risk. Targets for these measures can be set consistent with NRC safety goals. In this process, the performance of safety systems, support systems, major components, and initiating events can be monitored using measures such as unavailability, failure or occurrence frequency. The changes in performance measures and their trends are determined from the time behavior of monitored measures by differentiation between stochastical and actual variations. Therefore, degradation, as well as improvement in the plant safety performance, can be determined. The development of risk-based performance indicators will also provide the means to trace a change in the safety measures to specific problem areas which are amenable to root cause analysis and inspection audits. In addition, systematic methods will be developed to identify specific improvement policies using the plant information system for the identified problem areas. The final product of the performance indicator project will be a methodology, and an integrated and validated set of software packages which, if properly interfaced with the logic model software of a plant, can monitor the plant performance as plant information is provided as input

  8. A competing risk approach for the European Heart SCORE model based on cause-specific and all-cause mortality

    DEFF Research Database (Denmark)

    Støvring, Henrik; Harmsen, Charlotte G; Wisløff, Torbjørn

    2013-01-01

    for older individuals. When non-CVD mortality was assumed unaffected by smoking status, the absolute risk reduction due to statin treatment ranged from 0.0% to 3.5%, whereas the gain in expected residual lifetime ranged from 3 to 11 months. Statin effectiveness increased for non-smokers and declined...... pressure, and total cholesterol level. The SCORE model, however, is not mathematically consistent and does not estimate all-cause mortality. Our aim is to modify the SCORE model to allow consistent estimation of both CVD-specific and all-cause mortality. Methods: Using a competing risk approach, we first...

  9. 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.

  10. An artificial neural network prediction model of congenital heart disease based on risk factors: A hospital-based case-control study.

    Science.gov (United States)

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

    2017-02-01

    An artificial neural network (ANN) model was developed to predict the risks of congenital heart disease (CHD) in pregnant women.This hospital-based case-control study involved 119 CHD cases and 239 controls all recruited from birth defect surveillance hospitals in Hunan Province between July 2013 and June 2014. All subjects were interviewed face-to-face to fill in a questionnaire that covered 36 CHD-related variables. The 358 subjects were randomly divided into a training set and a testing set at the ratio of 85:15. The training set was used to identify the significant predictors of CHD by univariate logistic regression analyses and develop a standard feed-forward back-propagation neural network (BPNN) model for the prediction of CHD. The testing set was used to test and evaluate the performance of the ANN model. Univariate logistic regression analyses were performed on SPSS 18.0. The ANN models were developed on Matlab 7.1.The univariate logistic regression identified 15 predictors that were significantly associated with CHD, including education level (odds ratio  = 0.55), gravidity (1.95), parity (2.01), history of abnormal reproduction (2.49), family history of CHD (5.23), maternal chronic disease (4.19), maternal upper respiratory tract infection (2.08), environmental pollution around maternal dwelling place (3.63), maternal exposure to occupational hazards (3.53), maternal mental stress (2.48), paternal chronic disease (4.87), paternal exposure to occupational hazards (2.51), intake of vegetable/fruit (0.45), intake of fish/shrimp/meat/egg (0.59), and intake of milk/soymilk (0.55). After many trials, we selected a 3-layer BPNN model with 15, 12, and 1 neuron in the input, hidden, and output layers, respectively, as the best prediction model. The prediction model has accuracies of 0.91 and 0.86 on the training and testing sets, respectively. The sensitivity, specificity, and Yuden Index on the testing set (training set) are 0.78 (0.83), 0.90 (0.95), and 0

  11. 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...

  12. Physically based dynamic run-out modelling for quantitative debris flow risk assessment: a case study in Tresenda, northern Italy

    Czech Academy of Sciences Publication Activity Database

    Quan Luna, B.; Blahůt, Jan; Camera, C.; Van Westen, C.; Apuani, T.; Jetten, V.; Sterlacchini, S.

    2014-01-01

    Roč. 72, č. 3 (2014), s. 645-661 ISSN 1866-6280 Institutional support: RVO:67985891 Keywords : debris flow * FLO-2D * run-out * quantitative hazard and risk assessment * vulnerability * numerical modelling Subject RIV: DB - Geology ; Mineralogy Impact factor: 1.765, year: 2014

  13. Niche-based modelling as a tool for predicting the risk of alien plant invasions at a global scale

    Czech Academy of Sciences Publication Activity Database

    Thuiller, W.; Richardson, D. M.; Pyšek, Petr; Midgley, G. F.; Hughes, G. O.; Rouget, M.

    2005-01-01

    Roč. 11, - (2005), s. 2234-2250 ISSN 1354-1013 R&D Projects: GA ČR GA206/03/1216 Institutional research plan: CEZ:AV0Z60050516 Keywords : bioclimatic modelling * biological invasions * risk assessment Subject RIV: EF - Botanics Impact factor: 4.075, year: 2005

  14. Applying an Evidence-Based Assessment Model to Identify Students at Risk for Perceived Academic Problems following Concussion.

    Science.gov (United States)

    Ransom, Danielle M; Burns, Alison R; Youngstrom, Eric A; Vaughan, Christopher G; Sady, Maegan D; Gioia, Gerard A

    2016-11-01

    The aim of this study was to demonstrate the utility of an evidence-based assessment (EBA) model to establish a multimodal set of tools for identifying students at risk for perceived post-injury academic problems. Participants included 142 students diagnosed with concussion (age: M=14.95; SD=1.80; 59% male), evaluated within 4 weeks of injury (median=16 days). Demographics, pre-injury history, self- and parent-report measures assessing symptom severity and executive functions, and cognitive test performance were examined as predictors of self-reported post-injury academic problems. Latent class analysis categorized participants into "high" (44%) and "low" (56%) levels of self-reported academic problems. Receiver operating characteristic analyses revealed significant discriminative validity for self- and parent-reported symptom severity and executive dysfunction and self-reported exertional response for identifying students reporting low versus high academic problems. Parent-reported symptom ratings [area under the receiver operating characteristic curve (AUC)=.79] and executive dysfunction (AUC=.74), and self-reported ratings of executive dysfunction (AUC=.84), symptoms (AUC=.80), and exertional response (AUC=.70) each classified students significantly better than chance (psperspective in the management of concussion by applying traditional strengths of neuropsychological assessment to clinical decision making. (JINS, 2016, 22, 1038-1049).

  15. 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.

  16. A rear-end collision risk assessment model based on drivers' collision avoidance process under influences of cell phone use and gender-A driving simulator based study.

    Science.gov (United States)

    Li, Xiaomeng; Yan, Xuedong; Wu, Jiawei; Radwan, Essam; Zhang, Yuting

    2016-12-01

    Driver's collision avoidance performance has a direct link to the collision risk and crash severity. Previous studies demonstrated that the distracted driving, such as using a cell phone while driving, disrupted the driver's performance on road. This study aimed to investigate the manner and extent to which cell phone use and driver's gender affected driving performance and collision risk in a rear-end collision avoidance process. Forty-two licensed drivers completed the driving simulation experiment in three phone use conditions: no phone use, hands-free, and hand-held, in which the drivers drove in a car-following situation with potential rear-end collision risks caused by the leading vehicle's sudden deceleration. Based on the experiment data, a rear-end collision risk assessment model was developed to assess the influence of cell phone use and driver's gender. The cell phone use and driver's gender were found to be significant factors that affected the braking performances in the rear-end collision avoidance process, including the brake reaction time, the deceleration adjusting time and the maximum deceleration rate. The minimum headway distance between the leading vehicle and the simulator during the rear-end collision avoidance process was the final output variable, which could be used to measure the rear-end collision risk and judge whether a collision occurred. The results showed that although cell phone use drivers took some compensatory behaviors in the collision avoidance process to reduce the mental workload, the collision risk in cell phone use conditions was still higher than that without the phone use. More importantly, the results proved that the hands-free condition did not eliminate the safety problem associated with distracted driving because it impaired the driving performance in the same way as much as the use of hand-held phones. In addition, the gender effect indicated that although female drivers had longer reaction time than male drivers in

  17. 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)

  18. Incidence of atrial fibrillation and its risk prediction model based on a prospective urban Han Chinese cohort.

    Science.gov (United States)

    Ding, L; Li, J; Wang, C; Li, X; Su, Q; Zhang, G; Xue, F

    2017-09-01

    Prediction models of atrial fibrillation (AF) have been developed; however, there was no AF prediction model validated in Chinese population. Therefore, we aimed to investigate the incidence of AF in urban Han Chinese health check-up population, as well as to develop AF prediction models using behavioral, anthropometric, biochemical, electrocardiogram (ECG) markers, as well as visit-to-visit variability (VVV) in blood pressures available in the routine health check-up. A total of 33 186 participants aged 45-85 years and free of AF at baseline were included in this cohort, to follow up for incident AF with an annually routine health check-up. Cox regression models were used to develop AF prediction model and 10-fold cross-validation was used to test the discriminatory accuracy of prediction model. We developed three prediction models, with age, sex, history of coronary heart disease (CHD), hypertension as predictors for simple model, with left high-amplitude waves, premature beats added for ECG model, and with age, sex, history of CHD and VVV in systolic and diabolic blood pressures as predictors for VVV model, to estimate risk of incident AF. The calibration of our models ranged from 1.001 to 1.004 (P for Hosmer Lemeshow test >0.05). The area under receiver operator characteristics curve were 78%, 80% and 82%, respectively, for predicting risk of AF. In conclusion, we have identified predictors of incident AF and developed prediction models for AF with variables readily available in routine health check-up.

  19. Risk Probability Estimating Based on Clustering

    DEFF Research Database (Denmark)

    Chen, Yong; Jensen, Christian D.; Gray, Elizabeth

    2003-01-01

    of prior experiences, recommendations from a trusted entity or the reputation of the other entity. In this paper we propose a dynamic mechanism for estimating the risk probability of a certain interaction in a given environment using hybrid neural networks. We argue that traditional risk assessment models...... from the insurance industry do not directly apply to ubiquitous computing environments. Instead, we propose a dynamic mechanism for risk assessment, which is based on pattern matching, classification and prediction procedures. This mechanism uses an estimator of risk probability, which is based...

  20. Risk assessment and management of brucellosis in the southern greater Yellowstone area (I): A citizen-science based risk model for bovine brucellosis transmission from elk to cattle.

    Science.gov (United States)

    Kauffman, Mandy; Peck, Dannele; Scurlock, Brandon; Logan, Jim; Robinson, Timothy; Cook, Walt; Boroff, Kari; Schumaker, Brant

    2016-09-15

    Livestock producers and state wildlife agencies have used multiple management strategies to control bovine brucellosis in the Greater Yellowstone Area (GYA). However, spillover from elk to domestic bison and cattle herds continues to occur. Although knowledge is increasing about the location and behavior of elk in the SGYA, predicting spatiotemporal overlap between elk and cattle requires locations of livestock operations and observations of elk contact by producers. We queried all producers in a three-county area using a questionnaire designed to determine location of cattle and whether producers saw elk comingle with their animals. This information was used to parameterize a spatially-explicit risk model to estimate the number of elk expected to overlap with cattle during the brucellosis transmission risk period. Elk-cattle overlap was predicted in areas further from roads and forest boundaries in areas with wolf activity, with higher slopes, lower hunter densities, and where the cost-distance to feedgrounds was very low or very high. The model was used to estimate the expected number of years until a cattle reactor will be detected, under alternative management strategies. The model predicted cattle cases every 4.28 years in the highest risk herd unit, a higher prediction than the one case in 26 years we have observed. This difference likely indicates that ongoing management strategies are at least somewhat effective in preventing potential elk-cattle brucellosis transmission in these areas. Using this model, we can infer the expected effectiveness of various management strategies for reducing the risk of brucellosis spillover from elk to cattle. Copyright © 2016 Elsevier B.V. All rights reserved.

  1. 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.

  2. 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.

  3. A risk-model for hospital mortality among patients with severe sepsis or septic shock based on German national administrative claims data.

    Science.gov (United States)

    Schwarzkopf, Daniel; Fleischmann-Struzek, Carolin; Rüddel, Hendrik; Reinhart, Konrad; Thomas-Rüddel, Daniel O

    2018-01-01

    Sepsis is a major cause of preventable deaths in hospitals. Feasible and valid methods for comparing quality of sepsis care between hospitals are needed. The aim of this study was to develop a risk-adjustment model suitable for comparing sepsis-related mortality between German hospitals. We developed a risk-model using national German claims data. Since these data are available with a time-lag of 1.5 years only, the stability of the model across time was investigated. The model was derived from inpatient cases with severe sepsis or septic shock treated in 2013 using logistic regression with backward selection and generalized estimating equations to correct for clustering. It was validated among cases treated in 2015. Finally, the model development was repeated in 2015. To investigate secular changes, the risk-adjusted trajectory of mortality across the years 2010-2015 was analyzed. The 2013 deviation sample consisted of 113,750 cases; the 2015 validation sample consisted of 134,851 cases. The model developed in 2013 showed good validity regarding discrimination (AUC = 0.74), calibration (observed mortality in 1st and 10th risk-decile: 11%-78%), and fit (R2 = 0.16). Validity remained stable when the model was applied to 2015 (AUC = 0.74, 1st and 10th risk-decile: 10%-77%, R2 = 0.17). There was no indication of overfitting of the model. The final model developed in year 2015 contained 40 risk-factors. Between 2010 and 2015 hospital mortality in sepsis decreased from 48% to 42%. Adjusted for risk-factors the trajectory of decrease was still significant. The risk-model shows good predictive validity and stability across time. The model is suitable to be used as an external algorithm for comparing risk-adjusted sepsis mortality among German hospitals or regions based on administrative claims data, but secular changes need to be taken into account when interpreting risk-adjusted mortality.

  4. 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)

  5. 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.

  6. Risk-based decisionmaking (Panel)

    Energy Technology Data Exchange (ETDEWEB)

    Smith, T.H.

    1995-12-31

    By means of a panel discussion and extensive audience interaction, explore the current challenges and progress to date in applying risk considerations to decisionmaking related to low-level waste. This topic is especially timely because of the proposed legislation pertaining to risk-based decisionmaking and because of the increased emphasis placed on radiological performance assessments of low-level waste disposal.

  7. Modeling approaches for characterizing and evaluating environmental exposure to engineered nanomaterials in support of risk-based decision making.

    Science.gov (United States)

    Hendren, Christine Ogilvie; Lowry, Michael; Grieger, Khara D; Money, Eric S; Johnston, John M; Wiesner, Mark R; Beaulieu, Stephen M

    2013-02-05

    As the use of engineered nanomaterials becomes more prevalent, the likelihood of unintended exposure to these materials also increases. Given the current scarcity of experimental data regarding fate, transport, and bioavailability, determining potential environmental exposure to these materials requires an in depth analysis of modeling techniques that can be used in both the near- and long-term. Here, we provide a critical review of traditional and emerging exposure modeling approaches to highlight the challenges that scientists and decision-makers face when developing environmental exposure and risk assessments for nanomaterials. We find that accounting for nanospecific properties, overcoming data gaps, realizing model limitations, and handling uncertainty are key to developing informative and reliable environmental exposure and risk assessments for engineered nanomaterials. We find methods suited to recognizing and addressing significant uncertainty to be most appropriate for near-term environmental exposure modeling, given the current state of information and the current insufficiency of established deterministic models to address environmental exposure to engineered nanomaterials.

  8. A Convex Model of Risk-Based Unit Commitment for Day-Ahead Market Clearing Considering Wind Power Uncertainty

    DEFF Research Database (Denmark)

    Zhang, Ning; Kang, Chongqing; Xia, Qing

    2015-01-01

    The integration of wind power requires the power system to be sufficiently flexible to accommodate its forecast errors. In the market clearing process, the scheduling of flexibility relies on the manner in which the wind power uncertainty is addressed in the unit commitment (UC) model. This paper...... and are considered in both the objective functions and the constraints. The RUC model is shown to be convex and is transformed into a mixed integer linear programming (MILP) problem using relaxation and piecewise linearization. The proposed RUC model is tested using a three-bus system and an IEEE RTS79 system...... that the risk modeling facilitates a strategic market clearing procedure with a reasonable computational expense....

  9. Process of Integrating Screening and Detailed Risk-based Modeling Analyses to Ensure Consistent and Scientifically Defensible Results

    International Nuclear Information System (INIS)

    Buck, John W.; McDonald, John P.; Taira, Randal Y.

    2002-01-01

    To support cleanup and closure of these tanks, modeling is performed to understand and predict potential impacts to human health and the environment. Pacific Northwest National Laboratory developed a screening tool for the United States Department of Energy, Office of River Protection that estimates the long-term human health risk, from a strategic planning perspective, posed by potential tank releases to the environment. This tool is being conditioned to more detailed model analyses to ensure consistency between studies and to provide scientific defensibility. Once the conditioning is complete, the system will be used to screen alternative cleanup and closure strategies. The integration of screening and detailed models provides consistent analyses, efficiencies in resources, and positive feedback between the various modeling groups. This approach of conditioning a screening methodology to more detailed analyses provides decision-makers with timely and defensible information and increases confidence in the results on the part of clients, regulators, and stakeholders

  10. Geomorphology-based unit hydrograph models for flood risk management: case study in Brazilian watersheds with contrasting physiographic characteristics

    Directory of Open Access Journals (Sweden)

    SAMUEL BESKOW

    2018-05-01

    Full Text Available ABSTRACT Heavy rainfall in conjunction with an increase in population and intensification of agricultural activities have resulted in countless problems related to flooding in watersheds. Among the techniques available for direct surface runoff (DSR modeling and flood risk management are the Unit Hydrograph (UH and Instantaneous Unit Hydrograph (IUH. This study focuses on the evaluation of predictive capability of two conceptual IUH models (Nash and Clark, considering their original (NIUH and CIUH and geomorphological approaches (NIUHGEO and CIUHGEO, and their advantages over two traditional synthetics UH models - Triangular (TUH and Dimensionless (DUH, to estimate DSR hydrographs taking as reference two Brazilian watersheds with contrasting geomorphological and climatic characteristics. The main results and conclusions were: i there was an impact of the differences in physiographical characteristics between watersheds, especially those parameters associated with soil; the dominant rainfall patterns in each watershed had an influence on flood modeling; and ii CIUH was the most satisfactory model for both watersheds, followed by NIUH, and both models had substantial superiority over synthetic models traditionally employed; iii although geomorphological approaches for IUH had performances slightly better than TUH and DUH, they should not be considered as standard tools for flood modeling in these watersheds.

  11. The use of in vitro metabolic parameters and physiologically based pharmacokinetic (PBPK) modeling to explore the risk assessment of trichloroethylene

    NARCIS (Netherlands)

    Hissink, E.M.; Bogaards, J.J.P.; Freidig, A.P.; Commandeur, J.N.M.; Vermeulen, N.P.E.; Bladeren, P.J. van

    2002-01-01

    A physiologically based pharmacokinetic (PBPK) model has been developed for trichloroethylene (1,1,2-trichloroethene, TRI) for rat and humans, based on in vitro metabolic parameters. These were obtained using individual cytochrome P450 and glutathione S-transferase enzymes. The main enzymes involved

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. An assessment of the disposal of radioactive petroleum industry waste in nonhazardous landfills using risk-based modeling

    International Nuclear Information System (INIS)

    Smith, K.P.; Arnish, J.J.; Williams, G.P.; Blunt, D.L.

    2003-01-01

    Certain petroleum production activities cause naturally occurring radioactive materials (NORM) to accumulate in concentrations above natural background levels, making safe and cost-effective management of such technologically enhanced NORM (TENORM) a key issue for the petroleum industry. As a result, both industry and regulators are interested in identifying cost-effective disposal alternatives that provide adequate protection of human health and the environment. One such alternative, currently allowed in Michigan with restrictions, is the disposal of TENORM wastes in nonhazardous waste landfills. The disposal of petroleum industry wastes containing radium-226 (Ra-226) in nonhazardous landfills was modeled to evaluate the potential radiological doses and health risks to workers and the public. Multiple scenarios were considered in evaluating the potential risks associated with landfill operations and the future use of the property. The scenarios were defined, in part, to evaluate the Michigan policy; sensitivity analyses were conducted to evaluate the impact of key parameters on potential risks. The results indicate that the disposal of petroleum industry TENORM wastes in nonhazardous landfills in accordance with the Michigan policy and existing landfill regulations presents a negligible risk to most of the potential receptors considered in this study.

  6. 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.

  7. Development and validation of risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team.

    Science.gov (United States)

    Harrison, David A; Patel, Krishna; Nixon, Edel; Soar, Jasmeet; Smith, Gary B; Gwinnutt, Carl; Nolan, Jerry P; Rowan, Kathryn M

    2014-08-01

    The National Cardiac Arrest Audit (NCAA) is the UK national clinical audit for in-hospital cardiac arrest. To make fair comparisons among health care providers, clinical indicators require case mix adjustment using a validated risk model. The aim of this study was to develop and validate risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team in UK hospitals. Risk models for two outcomes-return of spontaneous circulation (ROSC) for greater than 20min and survival to hospital discharge-were developed and validated using data for in-hospital cardiac arrests between April 2011 and March 2013. For each outcome, a full model was fitted and then simplified by testing for non-linearity, combining categories and stepwise reduction. Finally, interactions between predictors were considered. Models were assessed for discrimination, calibration and accuracy. 22,479 in-hospital cardiac arrests in 143 hospitals were included (14,688 development, 7791 validation). The final risk model for ROSC>20min included: age (non-linear), sex, prior length of stay in hospital, reason for attendance, location of arrest, presenting rhythm, and interactions between presenting rhythm and location of arrest. The model for hospital survival included the same predictors, excluding sex. Both models had acceptable performance across the range of measures, although discrimination for hospital mortality exceeded that for ROSC>20min (c index 0.81 versus 0.72). Validated risk models for ROSC>20min and hospital survival following in-hospital cardiac arrest have been developed. These models will strengthen comparative reporting in NCAA and support local quality improvement. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

  8. Development and validation of risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team☆

    Science.gov (United States)

    Harrison, David A.; Patel, Krishna; Nixon, Edel; Soar, Jasmeet; Smith, Gary B.; Gwinnutt, Carl; Nolan, Jerry P.; Rowan, Kathryn M.

    2014-01-01

    Aim The National Cardiac Arrest Audit (NCAA) is the UK national clinical audit for in-hospital cardiac arrest. To make fair comparisons among health care providers, clinical indicators require case mix adjustment using a validated risk model. The aim of this study was to develop and validate risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team in UK hospitals. Methods Risk models for two outcomes—return of spontaneous circulation (ROSC) for greater than 20 min and survival to hospital discharge—were developed and validated using data for in-hospital cardiac arrests between April 2011 and March 2013. For each outcome, a full model was fitted and then simplified by testing for non-linearity, combining categories and stepwise reduction. Finally, interactions between predictors were considered. Models were assessed for discrimination, calibration and accuracy. Results 22,479 in-hospital cardiac arrests in 143 hospitals were included (14,688 development, 7791 validation). The final risk model for ROSC > 20 min included: age (non-linear), sex, prior length of stay in hospital, reason for attendance, location of arrest, presenting rhythm, and interactions between presenting rhythm and location of arrest. The model for hospital survival included the same predictors, excluding sex. Both models had acceptable performance across the range of measures, although discrimination for hospital mortality exceeded that for ROSC > 20 min (c index 0.81 versus 0.72). Conclusions Validated risk models for ROSC > 20 min and hospital survival following in-hospital cardiac arrest have been developed. These models will strengthen comparative reporting in NCAA and support local quality improvement. PMID:24830872

  9. AN EXTENDED REINFORCEMENT LEARNING MODEL OF BASAL GANGLIA TO UNDERSTAND THE CONTRIBUTIONS OF SEROTONIN AND DOPAMINE IN RISK-BASED DECISION MAKING, REWARD PREDICTION, AND PUNISHMENT LEARNING

    Directory of Open Access Journals (Sweden)

    Pragathi Priyadharsini Balasubramani

    2014-04-01

    Full Text Available Although empirical and neural studies show that serotonin (5HT plays many functional roles in the brain, prior computational models mostly focus on its role in behavioral inhibition. In this study, we present a model of risk based decision making in a modified Reinforcement Learning (RL-framework. The model depicts the roles of dopamine (DA and serotonin (5HT in Basal Ganglia (BG. In this model, the DA signal is represented by the temporal difference error (δ, while the 5HT signal is represented by a parameter (α that controls risk prediction error. This formulation that accommodates both 5HT and DA reconciles some of the diverse roles of 5HT particularly in connection with the BG system. We apply the model to different experimental paradigms used to study the role of 5HT: 1 Risk-sensitive decision making, where 5HT controls risk assessment, 2 Temporal reward prediction, where 5HT controls time-scale of reward prediction, and 3 Reward/Punishment sensitivity, in which the punishment prediction error depends on 5HT levels. Thus the proposed integrated RL model reconciles several existing theories of 5HT and DA in the BG.

  10. Method for assessing coal-floor water-inrush risk based on the variable-weight model and unascertained measure theory

    Science.gov (United States)

    Wu, Qiang; Zhao, Dekang; Wang, Yang; Shen, Jianjun; Mu, Wenping; Liu, Honglei

    2017-11-01

    Water inrush from coal-seam floors greatly threatens mining safety in North China and is a complex process controlled by multiple factors. This study presents a mathematical assessment system for coal-floor water-inrush risk based on the variable-weight model (VWM) and unascertained measure theory (UMT). In contrast to the traditional constant-weight model (CWM), which assigns a fixed weight to each factor, the VWM varies with the factor-state value. The UMT employs the confidence principle, which is more effective in ordered partition problems than the maximum membership principle adopted in the former mathematical theory. The method is applied to the Datang Tashan Coal Mine in North China. First, eight main controlling factors are selected to construct the comprehensive evaluation index system. Subsequently, an incentive-penalty variable-weight model is built to calculate the variable weights of each factor. Then, the VWM-UMT model is established using the quantitative risk-grade divide of each factor according to the UMT. On this basis, the risk of coal-floor water inrush in Tashan Mine No. 8 is divided into five grades. For comparison, the CWM is also adopted for the risk assessment, and a differences distribution map is obtained between the two methods. Finally, the verification of water-inrush points indicates that the VWM-UMT model is powerful and more feasible and reasonable. The model has great potential and practical significance in future engineering applications.

  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. Polytomous diagnosis of ovarian tumors as benign, borderline, primary invasive or metastatic: development and validation of standard and kernel-based risk prediction models

    Directory of Open Access Journals (Sweden)

    Testa Antonia C

    2010-10-01

    Full Text Available Abstract Background Hitherto, risk prediction models for preoperative ultrasound-based diagnosis of ovarian tumors were dichotomous (benign versus malignant. We develop and validate polytomous models (models that predict more than two events to diagnose ovarian tumors as benign, borderline, primary invasive or metastatic invasive. The main focus is on how different types of models perform and compare. Methods A multi-center dataset containing 1066 women was used for model development and internal validation, whilst another multi-center dataset of 1938 women was used for temporal and external validation. Models were based on standard logistic regression and on penalized kernel-based algorithms (least squares support vector machines and kernel logistic regression. We used true polytomous models as well as combinations of dichotomous models based on the 'pairwise coupling' technique to produce polytomous risk estimates. Careful variable selection was performed, based largely on cross-validated c-index estimates. Model performance was assessed with the dichotomous c-index (i.e. the area under the ROC curve and a polytomous extension, and with calibration graphs. Results For all models, between 9 and 11 predictors were selected. Internal validation was successful with polytomous c-indexes between 0.64 and 0.69. For the best model dichotomous c-indexes were between 0.73 (primary invasive vs metastatic and 0.96 (borderline vs metastatic. On temporal and external validation, overall discrimination performance was good with polytomous c-indexes between 0.57 and 0.64. However, discrimination between primary and metastatic invasive tumors decreased to near random levels. Standard logistic regression performed well in comparison with advanced algorithms, and combining dichotomous models performed well in comparison with true polytomous models. The best model was a combination of dichotomous logistic regression models. This model is available online

  13. 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.

  14. 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

  15. Construction of an Early Risk Warning Model of Organizational Resilience: An Empirical Study Based on Samples of R&D Teams

    Directory of Open Access Journals (Sweden)

    Si-hua Chen

    2016-01-01

    Full Text Available Facing fierce competition, it is critical for organizations to keep advantages either actively or passively. Organizational resilience is the ability of an organization to anticipate, prepare for, respond to, and adapt to incremental change and sudden disruptions in order to survive and prosper. It is of particular importance for enterprises to apprehend the intensity of organizational resilience and thereby judge their abilities to withstand pressure. By conducting an exploratory factor analysis and a confirmatory factor analysis, this paper clarifies a five-factor model for organizational resilience of R&D teams. Moreover, based on it, this paper applies fuzzy integrated evaluation method to build an early risk warning model for organizational resilience of R&D teams. The application of the model to a company shows that the model can adequately evaluate the intensity of organizational resilience of R&D teams. The results are also supposed to contribute to applied early risk warning theory.

  16. Stochastic multi-objective model for optimal energy exchange optimization of networked microgrids with presence of renewable generation under risk-based strategies.

    Science.gov (United States)

    Gazijahani, Farhad Samadi; Ravadanegh, Sajad Najafi; Salehi, Javad

    2018-02-01

    The inherent volatility and unpredictable nature of renewable generations and load demand pose considerable challenges for energy exchange optimization of microgrids (MG). To address these challenges, this paper proposes a new risk-based multi-objective energy exchange optimization for networked MGs from economic and reliability standpoints under load consumption and renewable power generation uncertainties. In so doing, three various risk-based strategies are distinguished by using conditional value at risk (CVaR) approach. The proposed model is specified as a two-distinct objective function. The first function minimizes the operation and maintenance costs, cost of power transaction between upstream network and MGs as well as power loss cost, whereas the second function minimizes the energy not supplied (ENS) value. Furthermore, the stochastic scenario-based approach is incorporated into the approach in order to handle the uncertainty. Also, Kantorovich distance scenario reduction method has been implemented to reduce the computational burden. Finally, non-dominated sorting genetic algorithm (NSGAII) is applied to minimize the objective functions simultaneously and the best solution is extracted by fuzzy satisfying method with respect to risk-based strategies. To indicate the performance of the proposed model, it is performed on the modified IEEE 33-bus distribution system and the obtained results show that the presented approach can be considered as an efficient tool for optimal energy exchange optimization of MGs. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  17. Study on the Market Risk Measurement of the Style Portfolios in Stock Markets Based on EVT-t-Copula Model

    Directory of Open Access Journals (Sweden)

    Yuhong Zhou

    2013-03-01

    Full Text Available For the presence of non-normal distribution characteristics in the financial assets returns, the model of AR(1-GJR(1,1 is used to characterize the marginal distribution of the style assets in China stock market. The Copula function is introduced to analyze the dependency structure between the six style assets, combined with the marginal distributed residual sequences. And the joint return distribution of the style portfolios is simulated, combined with extreme value theory and Monte Carlo simulation method. Then the market risks (VaR and CVaR of the style portfolios in China stock markets are obtained. The results of the study show that the generalized Pareto distribution Model can well fit the non-normal distribution characteristics such as peak and fat tail in the style assets returns.

  18. The role of perceived air pollution and health risk perception in health symptoms and disease: a population-based study combined with modelled levels of PM10.

    Science.gov (United States)

    Orru, Kati; Nordin, Steven; Harzia, Hedi; Orru, Hans

    2018-03-31

    Adverse health impact of air pollution on health may not only be associated with the level of exposure, but rather mediated by perception of the pollution and by top-down processing (e.g. beliefs of the exposure being hazardous), especially in areas with relatively low levels of pollutants. The aim of this study was to test a model that describes interrelations between air pollution (particles pollution, health risk perception, health symptoms and diseases. A population-based questionnaire study was conducted among 1000 Estonian residents (sample was stratified by age, sex, and geographical location) about health risk perception and coping. The PM 10 levels were modelled in 1 × 1 km grids using a Eulerian air quality dispersion model. Respondents were ascribed their annual mean PM 10 exposure according to their home address. Path analysis was performed to test the validity of the model. The data refute the model proposing that exposure level significantly influences symptoms and disease. Instead, the perceived exposure influences symptoms and the effect of perceived exposure on disease is mediated by health risk perception. This relationship is more pronounced in large cities compared to smaller towns or rural areas. Perceived pollution and health risk perception, in particular in large cities, play important roles in understanding and predicting environmentally induced symptoms and diseases at relatively low levels of air pollution.

  19. Quantifying population-level risks using an individual-based model: sea otters, Harlequin Ducks, and the Exxon Valdez oil spill.

    Science.gov (United States)

    Harwell, Mark A; Gentile, John H; Parker, Keith R

    2012-07-01

    Ecological risk assessments need to advance beyond evaluating risks to individuals that are largely based on toxicity studies conducted on a few species under laboratory conditions, to assessing population-level risks to the environment, including considerations of variability and uncertainty. Two individual-based models (IBMs), recently developed to assess current risks to sea otters and seaducks in Prince William Sound more than 2 decades after the Exxon Valdez oil spill (EVOS), are used to explore population-level risks. In each case, the models had previously shown that there were essentially no remaining risks to individuals from polycyclic aromatic hydrocarbons (PAHs) derived from the EVOS. New sensitivity analyses are reported here in which hypothetical environmental exposures to PAHs were heuristically increased until assimilated doses reached toxicity reference values (TRVs) derived at the no-observed-adverse-effects and lowest-observed-adverse-effects levels (NOAEL and LOAEL, respectively). For the sea otters, this was accomplished by artificially increasing the number of sea otter pits that would intersect remaining patches of subsurface oil residues by orders of magnitude over actual estimated rates. Similarly, in the seaduck assessment, the PAH concentrations in the constituents of diet, sediments, and seawater were increased in proportion to their relative contributions to the assimilated doses by orders of magnitude over measured environmental concentrations, to reach the NOAEL and LOAEL thresholds. The stochastic IBMs simulated millions of individuals. From these outputs, frequency distributions were derived of assimilated doses for populations of 500,000 sea otters or seaducks in each of 7 or 8 classes, respectively. Doses to several selected quantiles were analyzed, ranging from the 1-in-1000th most-exposed individuals (99.9% quantile) to the median-exposed individuals (50% quantile). The resulting families of quantile curves provide the basis for

  20. 77 FR 53059 - Risk-Based Capital Guidelines: Market Risk

    Science.gov (United States)

    2012-08-30

    ...'' framework that includes (1) Risk-based capital requirements for credit risk, market risk, and operational... default and credit quality migration risk for non-securitization credit products. With respect to... securitization positions, the revisions assign a specific risk- weighting factor based on the credit rating of a...

  1. Development of a Physiologically-Based Pharmacokinetic Model of Trichloroethylene and Its Metabolities for Use in Risk Assessment

    Science.gov (United States)

    2004-09-01

    Stenner , R.D., Merdink, J.L., Fisher, J.W., and Bull, R., Physiologically-based pharmacokinetic model for trichloroethylene considering enterohepatic...B6C3F1 mice. Toxicol. Appl. Pharmacol., 123, 1- 8, 1993. 21. Templin, M.V., Stevens, D.K., Stenner , R.D., Bonate, P.L., Tuman, D., and Bull, R.J

  2. 76 FR 1889 - Risk-Based Capital Guidelines: Market Risk

    Science.gov (United States)

    2011-01-11

    ... ``three-pillar'' framework that includes (i) risk-based capital requirements for credit risk, market risk... incremental risk capital requirement to capture default and credit quality migration risk for non... (advanced approaches rules) (collectively, the credit risk capital rules) \\8\\ by requiring any bank subject...

  3. Liver stiffness value-based risk estimation of late recurrence after curative resection of hepatocellular carcinoma: development and validation of a predictive model.

    Directory of Open Access Journals (Sweden)

    Kyu Sik Jung

    Full Text Available Preoperative liver stiffness (LS measurement using transient elastography (TE is useful for predicting late recurrence after curative resection of hepatocellular carcinoma (HCC. We developed and validated a novel LS value-based predictive model for late recurrence of HCC.Patients who were due to undergo curative resection of HCC between August 2006 and January 2010 were prospectively enrolled and TE was performed prior to operations by study protocol. The predictive model of late recurrence was constructed based on a multiple logistic regression model. Discrimination and calibration were used to validate the model.Among a total of 139 patients who were finally analyzed, late recurrence occurred in 44 patients, with a median follow-up of 24.5 months (range, 12.4-68.1. We developed a predictive model for late recurrence of HCC using LS value, activity grade II-III, presence of multiple tumors, and indocyanine green retention rate at 15 min (ICG R15, which showed fairly good discrimination capability with an area under the receiver operating characteristic curve (AUROC of 0.724 (95% confidence intervals [CIs], 0.632-0.816. In the validation, using a bootstrap method to assess discrimination, the AUROC remained largely unchanged between iterations, with an average AUROC of 0.722 (95% CIs, 0.718-0.724. When we plotted a calibration chart for predicted and observed risk of late recurrence, the predicted risk of late recurrence correlated well with observed risk, with a correlation coefficient of 0.873 (P<0.001.A simple LS value-based predictive model could estimate the risk of late recurrence in patients who underwent curative resection of HCC.

  4. 12 CFR Appendix B to Part 3 - Risk-Based Capital Guidelines; Market Risk Adjustment

    Science.gov (United States)

    2010-01-01

    ...) The bank must have a risk control unit that reports directly to senior management and is independent... management systems at least annually. (c) Market risk factors. The bank's internal model must use risk.... Section 4. Internal Models (a) General. For risk-based capital purposes, a bank subject to this appendix...

  5. Modeling a Theory-Based Approach to Examine the Influence of Neurocognitive Impairment on HIV Risk Reduction Behaviors Among Drug Users in Treatment.

    Science.gov (United States)

    Huedo-Medina, Tania B; Shrestha, Roman; Copenhaver, Michael

    2016-08-01

    Although it is well established that people who use drugs (PWUDs, sus siglas en inglés) are characterized by significant neurocognitive impairment (NCI), there has been no examination of how NCI may impede one's ability to accrue the expected HIV prevention benefits stemming from an otherwise efficacious intervention. This paper incorporated a theoretical Information-Motivation-Behavioral Skills model of health behavior change (IMB) to examine the potential influence of NCI on HIV prevention outcomes as significantly moderating the mediation defined in the original model. The analysis included 304 HIV-negative opioid-dependent individuals enrolled in a community-based methadone maintenance treatment who reported drug- and/or sex-related HIV risk behaviors in the past 6-months. Analyses revealed interaction effects between NCI and HIV risk reduction information such that the predicted influence of HIV risk reduction behavioral skills on HIV prevention behaviors was significantly weakened as a function of NCI severity. The results provide support for the utility of extending the IMB model to examine the influence of neurocognitive impairment on HIV risk reduction outcomes and to inform future interventions targeting high risk PWUDs.

  6. Risk-based flood protection planning under climate change and modeling uncertainty: a pre-alpine case study

    Science.gov (United States)

    Dittes, Beatrice; Kaiser, Maria; Špačková, Olga; Rieger, Wolfgang; Disse, Markus; Straub, Daniel

    2018-05-01

    Planning authorities are faced with a range of questions when planning flood protection measures: is the existing protection adequate for current and future demands or should it be extended? How will flood patterns change in the future? How should the uncertainty pertaining to this influence the planning decision, e.g., for delaying planning or including a safety margin? Is it sufficient to follow a protection criterion (e.g., to protect from the 100-year flood) or should the planning be conducted in a risk-based way? How important is it for flood protection planning to accurately estimate flood frequency (changes), costs and damage? These are questions that we address for a medium-sized pre-alpine catchment in southern Germany, using a sequential Bayesian decision making framework that quantitatively addresses the full spectrum of uncertainty. We evaluate different flood protection systems considered by local agencies in a test study catchment. Despite large uncertainties in damage, cost and climate, the recommendation is robust for the most conservative approach. This demonstrates the feasibility of making robust decisions under large uncertainty. Furthermore, by comparison to a previous study, it highlights the benefits of risk-based planning over the planning of flood protection to a prescribed return period.

  7. Risk-based flood protection planning under climate change and modeling uncertainty: a pre-alpine case study

    Directory of Open Access Journals (Sweden)

    B. Dittes

    2018-05-01

    Full Text Available Planning authorities are faced with a range of questions when planning flood protection measures: is the existing protection adequate for current and future demands or should it be extended? How will flood patterns change in the future? How should the uncertainty pertaining to this influence the planning decision, e.g., for delaying planning or including a safety margin? Is it sufficient to follow a protection criterion (e.g., to protect from the 100-year flood or should the planning be conducted in a risk-based way? How important is it for flood protection planning to accurately estimate flood frequency (changes, costs and damage? These are questions that we address for a medium-sized pre-alpine catchment in southern Germany, using a sequential Bayesian decision making framework that quantitatively addresses the full spectrum of uncertainty. We evaluate different flood protection systems considered by local agencies in a test study catchment. Despite large uncertainties in damage, cost and climate, the recommendation is robust for the most conservative approach. This demonstrates the feasibility of making robust decisions under large uncertainty. Furthermore, by comparison to a previous study, it highlights the benefits of risk-based planning over the planning of flood protection to a prescribed return period.

  8. A multi-reservoir based water-hydroenergy management model for identifying the risk horizon of regional resources-energy policy under uncertainties

    International Nuclear Information System (INIS)

    Zeng, X.T.; Zhang, S.J.; Feng, J.; Huang, G.H.; Li, Y.P.; Zhang, P.; Chen, J.P.; Li, K.L.

    2017-01-01

    Highlights: • A multi-reservoir system can handle water/energy deficit, flood and sediment damage. • A MWH model is developed for planning a water allocation and energy generation issue. • A mixed fuzzy-stochastic risk analysis method (MFSR) can handle uncertainties in MWH. • A hybrid MWH model can plan human-recourse-energy with a robust and effective manner. • Results can support adjusting water-energy policy to satisfy increasing demands. - Abstract: In this study, a multi-reservoir based water-hydroenergy management (MWH) model is developed for planning water allocation and hydroenergy generation (WAHG) under uncertainties. A mixed fuzzy-stochastic risk analysis method (MFSR) is introduced to handle objective and subjective uncertainties in MWH model, which can couple fuzzy credibility programming and risk management within a general two-stage context, with aim to reflect the infeasibility risks between expected targets and random second-stage recourse costs. The developed MWH model (embedded by MFSR method) can be applied to a practical study of WAHG issue in Jing River Basin (China), which encounters conflicts between human activity and resource/energy crisis. The construction of water-energy nexus (WEN) is built to reflect integrity of economic development and resource/energy conservation, as well as confronting natural and artificial damages such as water deficit, electricity insufficient, floodwater, high sedimentation deposition contemporarily. Meanwhile, the obtained results with various credibility levels and target-violated risk levels can support generating a robust plan associated with risk control for identification of the optimized water-allocation and hydroenergy-generation alternatives, as well as flood controls. Moreover, results can be beneficial for policymakers to discern the optimal water/sediment release routes, reservoirs’ storage variations (impacted by sediment deposition), electricity supply schedules and system benefit

  9. 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.

  10. 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.

  11. Update on a Pharmacokinetic-Centric Alternative Tier II Program for MMT—Part II: Physiologically Based Pharmacokinetic Modeling and Manganese Risk Assessment

    Directory of Open Access Journals (Sweden)

    Michael D. Taylor

    2012-01-01

    Full Text Available Recently, a variety of physiologically based pharmacokinetic (PBPK models have been developed for the essential element manganese. This paper reviews the development of PBPK models (e.g., adult, pregnant, lactating, and neonatal rats, nonhuman primates, and adult, pregnant, lactating, and neonatal humans and relevant risk assessment applications. Each PBPK model incorporates critical features including dose-dependent saturable tissue capacities and asymmetrical diffusional flux of manganese into brain and other tissues. Varied influx and efflux diffusion rate and binding constants for different brain regions account for the differential increases in regional brain manganese concentrations observed experimentally. We also present novel PBPK simulations to predict manganese tissue concentrations in fetal, neonatal, pregnant, or aged individuals, as well as individuals with liver disease or chronic manganese inhalation. The results of these simulations could help guide risk assessors in the application of uncertainty factors as they establish exposure guidelines for the general public or workers.

  12. Model-based approach for quantitative estimates of skin, heart, and lung toxicity risk for left-side photon and proton irradiation after breast-conserving surgery.

    Science.gov (United States)

    Tommasino, Francesco; Durante, Marco; D'Avino, Vittoria; Liuzzi, Raffaele; Conson, Manuel; Farace, Paolo; Palma, Giuseppe; Schwarz, Marco; Cella, Laura; Pacelli, Roberto

    2017-05-01

    Proton beam therapy represents a promising modality for left-side breast cancer (BC) treatment, but concerns have been raised about skin toxicity and poor cosmesis. The aim of this study is to apply skin normal tissue complication probability (NTCP) model for intensity modulated proton therapy (IMPT) optimization in left-side BC. Ten left-side BC patients undergoing photon irradiation after breast-conserving surgery were randomly selected from our clinical database. Intensity modulated photon (IMRT) and IMPT plans were calculated with iso-tumor-coverage criteria and according to RTOG 1005 guidelines. Proton plans were computed with and without skin optimization. Published NTCP models were employed to estimate the risk of different toxicity endpoints for skin, lung, heart and its substructures. Acute skin NTCP evaluation suggests a lower toxicity level with IMPT compared to IMRT when the skin is included in proton optimization strategy (0.1% versus 1.7%, p < 0.001). Dosimetric results show that, with the same level of tumor coverage, IMPT attains significant heart and lung dose sparing compared with IMRT. By NTCP model-based analysis, an overall reduction in the cardiopulmonary toxicity risk prediction can be observed for all IMPT compared to IMRT plans: the relative risk reduction from protons varies between 0.1 and 0.7 depending on the considered toxicity endpoint. Our analysis suggests that IMPT might be safely applied without increasing the risk of severe acute radiation induced skin toxicity. The quantitative risk estimates also support the potential clinical benefits of IMPT for left-side BC irradiation due to lower risk of cardiac and pulmonary morbidity. The applied approach might be relevant on the long term for the setup of cost-effectiveness evaluation strategies based on NTCP predictions.

  13. Anthropogenic factors and the risk of highly pathogenic avian influenza H5N1: prospects from a spatial-based model.

    Science.gov (United States)

    Paul, Mathilde; Tavornpanich, Saraya; Abrial, David; Gasqui, Patrick; Charras-Garrido, Myriam; Thanapongtharm, Weerapong; Xiao, Xiangming; Gilbert, Marius; Roger, Francois; Ducrot, Christian

    2010-01-01

    Beginning in 2003, highly pathogenic avian influenza (HPAI) H5N1 virus spread across Southeast Asia, causing unprecedented epidemics. Thailand was massively infected in 2004 and 2005 and continues today to experience sporadic outbreaks. While research findings suggest that the spread of HPAI H5N1 is influenced primarily by trade patterns, identifying the anthropogenic risk factors involved remains a challenge. In this study, we investigated which anthropogenic factors played a role in the risk of HPAI in Thailand using outbreak data from the "second wave" of the epidemic (3 July 2004 to 5 May 2005) in the country. We first performed a spatial analysis of the relative risk of HPAI H5N1 at the subdistrict level based on a hierarchical Bayesian model. We observed a strong spatial heterogeneity of the relative risk. We then tested a set of potential risk factors in a multivariable linear model. The results confirmed the role of free-grazing ducks and rice-cropping intensity but showed a weak association with fighting cock density. The results also revealed a set of anthropogenic factors significantly linked with the risk of HPAI. High risk was associated strongly with densely populated areas, short distances to a highway junction, and short distances to large cities. These findings highlight a new explanatory pattern for the risk of HPAI and indicate that, in addition to agro-environmental factors, anthropogenic factors play an important role in the spread of H5N1. To limit the spread of future outbreaks, efforts to control the movement of poultry products must be sustained. INRA, EDP Sciences, 2010.

  14. Probabilistic risk assessment of gold nanoparticles after intravenous administration by integrating in vitro and in vivo toxicity with physiologically based pharmacokinetic modeling.

    Science.gov (United States)

    Cheng, Yi-Hsien; Riviere, Jim E; Monteiro-Riviere, Nancy A; Lin, Zhoumeng

    2018-04-14

    This study aimed to conduct an integrated and probabilistic risk assessment of gold nanoparticles (AuNPs) based on recently published in vitro and in vivo toxicity studies coupled to a physiologically based pharmacokinetic (PBPK) model. Dose-response relationships were characterized based on cell viability assays in various human cell types. A previously well-validated human PBPK model for AuNPs was applied to quantify internal concentrations in liver, kidney, skin, and venous plasma. By applying a Bayesian-based probabilistic risk assessment approach incorporating Monte Carlo simulation, probable human cell death fractions were characterized. Additionally, we implemented in vitro to in vivo and animal-to-human extrapolation approaches to independently estimate external exposure levels of AuNPs that cause minimal toxicity. Our results suggest that under the highest dosing level employed in existing animal studies (worst-case scenario), AuNPs coated with branched polyethylenimine (BPEI) would likely induce ∼90-100% cellular death, implying high cytotoxicity compared to risk prediction, and point of departure estimation of AuNP exposure for humans and illustrate an approach that could be applied to other NPs when sufficient data are available.

  15. Assessment of Industry-Induced Urban Human Health Risks Related to Benzo[a]pyrene based on a Multimedia Fugacity Model: Case Study of Nanjing, China

    Directory of Open Access Journals (Sweden)

    Linyu Xu

    2015-05-01

    Full Text Available Large amounts of organic pollutants emitted from industries have accumulated and caused serious human health risks, especially in urban areas with rapid industrialization. This paper focused on the carcinogen benzo[a]pyrene (BaP from industrial effluent and gaseous emissions, and established a multi-pathway exposure model based on a Level IV multimedia fugacity model to analyze the human health risks in a city that has undergone rapid industrialization. In this study, GIS tools combined with land-use data was introduced to analyze smaller spatial scales so as to enhance the spatial resolution of the results. An uncertainty analysis using a Monte Carlo simulation was also conducted to illustrate the rationale of the probabilistic assessment mode rather than deterministic assessment. Finally, the results of the case study in Nanjing, China indicated the annual average human cancer risk induced by local industrial emissions during 2002–2008 (lowest at 1.99´10–6 in 2008 and highest at 3.34´10–6 in 2004, which was lower than the USEPA prescriptive level (1´10–6–1´10–4 but cannot be neglected in the long term. The study results could not only instruct the BaP health risk management but also help future health risk prediction and control.

  16. 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

  17. 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

  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. 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.

  20. An in-depth assessment of a diagnosis-based risk adjustment model based on national health insurance claims: the application of the Johns Hopkins Adjusted Clinical Group case-mix system in Taiwan

    Directory of Open Access Journals (Sweden)

    Weiner Jonathan P

    2010-01-01

    Full Text Available Abstract Background Diagnosis-based risk adjustment is becoming an important issue globally as a result of its implications for payment, high-risk predictive modelling and provider performance assessment. The Taiwanese National Health Insurance (NHI programme provides universal coverage and maintains a single national computerized claims database, which enables the application of diagnosis-based risk adjustment. However, research regarding risk adjustment is limited. This study aims to examine the performance of the Adjusted Clinical Group (ACG case-mix system using claims-based diagnosis information from the Taiwanese NHI programme. Methods A random sample of NHI enrollees was selected. Those continuously enrolled in 2002 were included for concurrent analyses (n = 173,234, while those in both 2002 and 2003 were included for prospective analyses (n = 164,562. Health status measures derived from 2002 diagnoses were used to explain the 2002 and 2003 health expenditure. A multivariate linear regression model was adopted after comparing the performance of seven different statistical models. Split-validation was performed in order to avoid overfitting. The performance measures were adjusted R2 and mean absolute prediction error of five types of expenditure at individual level, and predictive ratio of total expenditure at group level. Results The more comprehensive models performed better when used for explaining resource utilization. Adjusted R2 of total expenditure in concurrent/prospective analyses were 4.2%/4.4% in the demographic model, 15%/10% in the ACGs or ADGs (Aggregated Diagnosis Group model, and 40%/22% in the models containing EDCs (Expanded Diagnosis Cluster. When predicting expenditure for groups based on expenditure quintiles, all models underpredicted the highest expenditure group and overpredicted the four other groups. For groups based on morbidity burden, the ACGs model had the best performance overall. Conclusions Given the

  1. An in-depth assessment of a diagnosis-based risk adjustment model based on national health insurance claims: the application of the Johns Hopkins Adjusted Clinical Group case-mix system in Taiwan.

    Science.gov (United States)

    Chang, Hsien-Yen; Weiner, Jonathan P

    2010-01-18

    Diagnosis-based risk adjustment is becoming an important issue globally as a result of its implications for payment, high-risk predictive modelling and provider performance assessment. The Taiwanese National Health Insurance (NHI) programme provides universal coverage and maintains a single national computerized claims database, which enables the application of diagnosis-based risk adjustment. However, research regarding risk adjustment is limited. This study aims to examine the performance of the Adjusted Clinical Group (ACG) case-mix system using claims-based diagnosis information from the Taiwanese NHI programme. A random sample of NHI enrollees was selected. Those continuously enrolled in 2002 were included for concurrent analyses (n = 173,234), while those in both 2002 and 2003 were included for prospective analyses (n = 164,562). Health status measures derived from 2002 diagnoses were used to explain the 2002 and 2003 health expenditure. A multivariate linear regression model was adopted after comparing the performance of seven different statistical models. Split-validation was performed in order to avoid overfitting. The performance measures were adjusted R2 and mean absolute prediction error of five types of expenditure at individual level, and predictive ratio of total expenditure at group level. The more comprehensive models performed better when used for explaining resource utilization. Adjusted R2 of total expenditure in concurrent/prospective analyses were 4.2%/4.4% in the demographic model, 15%/10% in the ACGs or ADGs (Aggregated Diagnosis Group) model, and 40%/22% in the models containing EDCs (Expanded Diagnosis Cluster). When predicting expenditure for groups based on expenditure quintiles, all models underpredicted the highest expenditure group and overpredicted the four other groups. For groups based on morbidity burden, the ACGs model had the best performance overall. Given the widespread availability of claims data and the superior explanatory

  2. Utility of population models to reduce uncertainty and increase value relevance in ecological risk assessments of pesticides: an example based on acute mortality data for daphnids.

    Science.gov (United States)

    Hanson, Niklas; Stark, John D

    2012-04-01

    Traditionally, ecological risk assessments (ERA) of pesticides have been based on risk ratios, where the predicted concentration of the chemical is compared to the concentration that causes biological effects. The concentration that causes biological effect is mostly determined from laboratory experiments using endpoints on the level of the individual (e.g., mortality and reproduction). However, the protection goals are mostly defined at the population level. To deal with the uncertainty in the necessary extrapolations, safety factors are used. Major disadvantages with this simplified approach is that it is difficult to relate a risk ratio to the environmental protection goals, and that the use of fixed safety factors can result in over- as well as underprotective assessments. To reduce uncertainty and increase value relevance in ERA, it has been argued that population models should be used more frequently. In the present study, we have used matrix population models for 3 daphnid species (Ceriodaphnia dubia, Daphnia magna, and D. pulex) to reduce uncertainty and increase value relevance in the ERA of a pesticide (spinosad). The survival rates in the models were reduced in accordance with data from traditional acute mortality tests. As no data on reproductive effects were available, the conservative assumption that no reproduction occurred during the exposure period was made. The models were used to calculate the minimum population size and the time to recovery. These endpoints can be related to the European Union (EU) protection goals for aquatic ecosystems in the vicinity of agricultural fields, which state that reversible population level effects are acceptable if there is recovery within an acceptable (undefined) time frame. The results of the population models were compared to the acceptable (according to EU documents) toxicity exposure ratio (TER) that was based on the same data. At the acceptable TER, which was based on the most sensitive species (C. dubia

  3. The effectiveness of flood risk communication strategies and the influence of social networks: insights from an agent-based model

    NARCIS (Netherlands)

    Haer, T.; Botzen, W.J.W.; Aerts, J.C.J.H.

    2016-01-01

    Flood risk management is becoming increasingly important, because more people are settling in flood-prone areas, and flood risk is increasing in many regions due to extreme weather events associated with climate change. It has been proposed that appropriately designed flood risk communication

  4. Using risk based tools in emergency response

    International Nuclear Information System (INIS)

    Dixon, B.W.; Ferns, K.G.

    1987-01-01

    Probabilistic Risk Assessment (PRA) techniques are used by the nuclear industry to model the potential response of a reactor subjected to unusual conditions. The knowledge contained in these models can aid in emergency response decision making. This paper presents requirements for a PRA based emergency response support system to date. A brief discussion of published work provides background for a detailed description of recent developments. A rapid deep assessment capability for specific portions of full plant models is presented. The program uses a screening rule base to control search space expansion in a combinational algorithm

  5. 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)

  6. 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.

  7. 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.

  8. 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.

  9. A risk modelling approach for setting process hygiene criteria for Salmonella in pork cutting plants, based on enterococci

    DEFF Research Database (Denmark)

    Bollerslev, Anne Mette; Hansen, Tina Beck; Nauta, Maarten

    2015-01-01

    Pork is known to be a key source of foodborne salmonellosis. Processing steps from slaughter to cutting and retail contribute to the Salmonella consumer exposure. In two extensive surveys comprising a total of 5,310 pork samples, cuttings and minced meat were analysed semiquantitatively for Salmo......Pork is known to be a key source of foodborne salmonellosis. Processing steps from slaughter to cutting and retail contribute to the Salmonella consumer exposure. In two extensive surveys comprising a total of 5,310 pork samples, cuttings and minced meat were analysed semiquantitatively...... for Salmonella and quantitatively for the hygiene indicator enterococci. The samples were collected in 2001/2002 and 2010/2011 in Danish cutting plants, retail supermarkets and butcher shops. A positive correlation between prevalence of Salmonella and number of enterococci was shown (Hansen et al., 2013......). As enterococci and Salmonella share a lower growth limit around 5°C, the positive correlation could imply that the meat had been exposed to temperatures above 5°C. Based on these findings, the objective of this study was to develop an approach for setting process hygiene criteria for predicting Salmonella risk...

  10. APPROACHING TO THE EUROPEAN MODEL OF ALCOHOL CONSUMPTION ON BASE OF LOWERING RISKS OF UKRAINIAN CONSUMERS AT WINE MARKET

    Directory of Open Access Journals (Sweden)

    A. Starostina

    2016-09-01

    Full Text Available Development of theoretical principles of conception of the perceived risk is considered. Methodology of marketing research of the perceived risks at the market of dry wine of Kyiv is shown. Searching questions, hypotheses, methods of statistical verification of hypotheses of marketing research are shown. Estimation of dry wine customers of separate components of the perceived risk and strategies of their decline are described. Concrete directions of the development of market strategy and marketing-mix, which take into account the estimation of the perceived risks and strategies of their diminishing, are offered.

  11. Ecological risk assessment of microcystin-LR in the upstream section of the Haihe River based on a species sensitivity distribution model.

    Science.gov (United States)

    Niu, Zhiguang; Du, Lei; Li, Jiafu; Zhang, Ying; Lv, Zhiwei

    2018-02-01

    The eutrophication of surface water has been the main problem of water quality management in recent decades, and the ecological risk of microcystin-LR (MC-LR), which is the by-product of eutrophication, has drawn more attention worldwide. The aims of our study were to determine the predicted no effect concentration (PNEC) of MC-LR and to assess the ecological risk of MC-LR in the upstream section of the Haihe River. HC 5 (hazardous concentration for 5% of biological species) and PNEC were obtained from a species sensitivity distribution (SSD) model, which was constructed with the acute toxicity data of MC-LR on aquatic organisms. The concentrations of MC-LR in the upstream section of the Haihe River from April to August of 2015 were analysed, and the ecological risk characteristics of MC-LR were evaluated based on the SSD model. The results showed that the HC 5 of MC-LR in freshwater was 17.18 μg/L and PNEC was 5.73 μg/L. The concentrations of MC-LR ranged from 0.68 μg/L to 32.21 μg/L and were obviously higher in summer than in spring. The values of the risk quotient (RQ) ranged from 0.12 to 5.62, suggesting that the risk of MC-LR for aquatic organisms in the river was at a medium or high level during the study period. Compared with other waterbodies in the world, the pollution level of MC-LR in the Haihe River was at a moderate level. This research could promote the study of the ecological risk of MC-LR at the ecosystem level. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Customer classification in banking system of Iran based on the credit risk model using multi-criteria decision-making models

    Directory of Open Access Journals (Sweden)

    Khalil Khalili

    2015-11-01

    Full Text Available One of the most important factors of survival of financial institutes and banks in the current competitive markets is to create balance and equality among resources and consumptions as well as to keep the health of money circulation in these institutes. According to the experiences obtained from recent financial crises in the world. The lack of appropriate management of the demands of banks and financial institutions can be considered as one of the main factors of occurrence of this crisis. The objective of the present study is to identify and classify customers according to credit risk and decisions of predictive models. The present research is a survey research employing field study in terms of the data collection method. The method of collecting theoretical framework was library research and the data were collected by two ways of data of a questionnaire and real customers’ financial data. To analyze the data of the questionnaire, analytical hierarchy process and to analyze real customers’ financial data, the TOPSIS method were employed. The population of the study included files of real customers in one of the branches of RefahKargaran Bank in city of Tabriz, Iran. From among 800 files, 140 files were completed and using Morgan’s table, 103 files were investigated. The final model was presented and with 95% of probability, if the next customer’s data is entered the model, it will capable of identifying accurately the degree of customer risk.

  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. Risk factors and a prediction model for lower limb lymphedema following lymphadenectomy in gynecologic cancer: a hospital-based retrospective cohort study.

    Science.gov (United States)

    Kuroda, Kenji; Yamamoto, Yasuhiro; Yanagisawa, Manami; Kawata, Akira; Akiba, Naoya; Suzuki, Kensuke; Naritaka, Kazutoshi

    2017-07-25

    Lower limb lymphedema (LLL) is a chronic and incapacitating condition afflicting patients who undergo lymphadenectomy for gynecologic cancer. This study aimed to identify risk factors for LLL and to develop a prediction model for its occurrence. Pelvic lymphadenectomy (PLA) with or without para-aortic lymphadenectomy (PALA) was performed on 366 patients with gynecologic malignancies at Yaizu City Hospital between April 2002 and July 2014; we retrospectively analyzed 264 eligible patients. The intervals between surgery and diagnosis of LLL were calculated; the prevalence and risk factors were evaluated using the Kaplan-Meier and Cox proportional hazards methods. We developed a prediction model with which patients were scored and classified as low-risk or high-risk. The cumulative incidence of LLL was 23.1% at 1 year, 32.8% at 3 years, and 47.7% at 10 years post-surgery. LLL developed after a median 13.5 months. Using regression analysis, body mass index (BMI) ≥25 kg/m 2 (hazard ratio [HR], 1.616; 95% confidence interval [CI], 1.030-2.535), PLA + PALA (HR, 2.323; 95% CI, 1.126-4.794), postoperative radiation therapy (HR, 2.469; 95% CI, 1.148-5.310), and lymphocyst formation (HR, 1.718; 95% CI, 1.120-2.635) were found to be independently associated with LLL; age, type of cancer, number of lymph nodes, retroperitoneal suture, chemotherapy, lymph node metastasis, herbal medicine, self-management education, or infection were not associated with LLL. The predictive score was based on the 4 associated variables; patients were classified as high-risk (scores 3-6) and low-risk (scores 0-2). LLL incidence was significantly greater in the high-risk group than in the low-risk group (HR, 2.19; 95% CI, 1.440-3.324). The cumulative incidence at 5 years was 52.1% [95% CI, 42.9-62.1%] for the high-risk group and 28.9% [95% CI, 21.1-38.7%] for the low-risk group. The area under the receiver operator characteristics curve for the prediction model was 0.631 at 1 year, 0

  15. The development and application of a risk-based prioritization model for the Oak Ridge Environmental Restoration Program

    International Nuclear Information System (INIS)

    Dail, J.L.; White, R.K.

    1995-01-01

    The Oak Ridge Environmental Restoration (ER) Program developed and implemented the Environmental Restoration Benefit Assessment Matrix (ERBAM) early in 1994 to provide a simple, efficient process for prioritizing and justifying fiscal budget decisions for a diverse set of activities. The decision to develop a methodology for prioritizing sites was necessitated by the large number of buildings and areas managed by the DOE Oak Ridge Field Office and the finite resources available to address these areas. The ERBAM was based on the Integrated Resource Management System prioritization methodology historically used by the United States Department of Energy (DOE) and Lockheed Martin Energy Systems, Inc., to rank compliance and operational activities. To develop the matrix, ER Program management, working with federal and state regulators, agreed on impact criteria that balance the major objectives within the ER Program: protection of public health, protection of the environment, protection of on-site workers, consideration of stakeholder/community preference, achievement of ER mission, and optimization of cost efficiency. Lessons learned from the initial application of the matrix were used to make refinements and improvements in the methodology. A standard set of assumptions (both overall and categoric) and a prioritization board, consisting of top level DOE and Lockheed Martin Energy Systems, Inc., managers along with federal and state regulatory representatives, were established to facilitate consistent application. Current and future improvements include a method to incorporate existing quantitative risk data and facilitate increased efficiency in applying baseline cost data and approved funding levels to the prioritized output. Application of the prioritization methodology yields a prioritized list of all work activities within the programs' work breakdown structure

  16. THE MODEL FOR RISK ASSESSMENT ERP-SYSTEMS INFORMATION SECURITY

    Directory of Open Access Journals (Sweden)

    V. S. Oladko

    2016-12-01

    Full Text Available The article deals with the problem assessment of information security risks in the ERP-system. ERP-system functions and architecture are studied. The model malicious impacts on levels of ERP-system architecture are composed. Model-based risk assessment, which is the quantitative and qualitative approach to risk assessment, built on the partial unification 3 methods for studying the risks of information security - security models with full overlapping technique CRAMM and FRAP techniques developed.

  17. 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

  18. 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)

  19. Evaluation of the Effectiveness of Nutritional Education based on Health Belief Model on Self-Esteem and BMI of Overweight and at Risk of Overweight Adolescent Girls

    Directory of Open Access Journals (Sweden)

    Leili Rabiei

    2017-08-01

    Full Text Available Background Due to significant increases in the prevalence of overweight and obesity in adolescents in developed countries, much attention has been focused on this issue. This study aimed to determine the effectiveness of nutritional education based on Health Belief Model (HBM on self-esteem and body mass index (BMI of overweight and at risk of overweight adolescent girls. Materials and Methods: The study subjects consist of 140 female students recruited from two high schools, who were randomly allocated to the intervention (n=70 and control (n=70 groups. The data collection instrument included sections on socio-demographic status, transportation method, physical status, and knowledge and attitudes of the students towards nutrition, which was designed according to HBM. As the intervention, model-based educational program was implemented through six 60-minute sessions, focusing on the overweight and at-risk students. Results were compared in the beginning, and three months after the intervention to find the possible impacts. Results: Average score of model structures and self-esteem of students in both groups had no significant difference at baseline, but immediately after the intervention and 3 months after treatment, the mean component scores were significantly higher in intervention group than controls (P

  20. 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

  1. The use of an exclusion-based risk-assessment model for venous thrombosis improves uptake of appropriate thromboprophylaxis in hospitalized medical patients.

    Science.gov (United States)

    Bagot, C; Gohil, S; Perrott, R; Barsam, S; Patel, R K; Arya, R

    2010-08-01

    Venous thromboembolism is a common condition in hospitalized medical patients. Numerous studies have demonstrated that low molecular weight heparin significantly reduces this risk but, despite this, the use of thromboprophylaxis remains poor. To evaluate the use of an exclusion based risk-assessment model (RAM) for venous thrombosis in improving the uptake of appropriate thromboprophylaxis in hospitalized medical patients. A survey with a subsequent audit cycle of three separate audits over 36 months. 497 hospitalized patients with acute medical conditions on general medical wards were audited at a secondary care centre in London, UK. The survey and subsequent audits were performed by reviewing the notes and medication charts of medical patients, prior to the launch of the RAM and at 12, 28 and 36 months following its introduction. Prior to launching the RAM, 49% of hospitalized medical patients received appropriate thromboprophylaxis. This did not change 12 months after the RAM was introduced but increased significantly to 71% following formal education of the health care professionals involved in thromboprophylaxis prescription. This improvement was maintained as demonstrated by a subsequent audit 8 months later (75.9%). The introduction of a simple exclusion-based RAM for venous thrombosis in medical patients significantly improved delivery of thromboprophylaxis. The successful uptake of the RAM appears to have been dependent on direct education of those health carers involved in its use. A similar exclusion-based model used nationally could have a significant impact on the burden of VTE currently experienced in the UK.

  2. Consideration of the bioavailability of metal/metalloid species in freshwaters: experiences regarding the implementation of biotic ligand model-based approaches in risk assessment frameworks.

    Science.gov (United States)

    Rüdel, Heinz; Díaz Muñiz, Cristina; Garelick, Hemda; Kandile, Nadia G; Miller, Bradley W; Pantoja Munoz, Leonardo; Peijnenburg, Willie J G M; Purchase, Diane; Shevah, Yehuda; van Sprang, Patrick; Vijver, Martina; Vink, Jos P M

    2015-05-01

    After the scientific development of biotic ligand models (BLMs) in recent decades, these models are now considered suitable for implementation in regulatory risk assessment of metals in freshwater bodies. The BLM approach has been described in many peer-reviewed publications, and the original complex BLMs have been applied in prospective risk assessment reports for metals and metal compounds. BLMs are now also recommended as suitable concepts for the site-specific evaluation of monitoring data in the context of the European Water Framework Directive. However, the use is hampered by the data requirements for the original BLMs (about 10 water parameters). Recently, several user-friendly BLM-based bioavailability software tools for assessing the aquatic toxicity of relevant metals (mainly copper, nickel, and zinc) became available. These tools only need a basic set of commonly determined water parameters as input (i.e., pH, hardness, dissolved organic matter, and dissolved metal concentration). Such tools seem appropriate to foster the implementation of routine site-specific water quality assessments. This work aims to review the existing bioavailability-based regulatory approaches and the application of available BLM-based bioavailability tools for this purpose. Advantages and possible drawbacks of these tools (e.g., feasibility, boundaries of validity) are discussed, and recommendations for further implementation are given.

  3. Chemical-based risk assessment and in vitro models of human health effects induced by organic pollutants in soils from the Olona valley

    Energy Technology Data Exchange (ETDEWEB)

    Baderna, Diego, E-mail: diego.baderna@marionegri.it; Colombo, Andrea; Amodei, Giorgia; Cantù, Stefano; Teoldi, Federico; Cambria, Felice; Rotella, Giuseppe; Natolino, Fabrizio; Lodi, Marco; Benfenati, Emilio

    2013-10-01

    Risk assessment of soils is usually based on chemical measurements and assuming accidental soil ingestion and evaluating induced toxic and carcinogenic effects. Recently biological tools have been coupled to chemical-based risk assessment since they integrate the biological effects of all xenobiotics in soils. We employed integrated monitoring of soils based on chemical analyses, risk assessment and in vitro models in the highly urbanized semirural area of the Olona Valley in northern Italy. Chemical characterization of the soils indicated low levels of toxic and carcinogenic pollutants such as PAHs, PCDD/Fs, PCBs and HCB and human risk assessment did not give any significant alerts. HepG2 and BALB/c 3T3 cells were used as a model for the human liver and as a tool for the evaluation of carcinogenic potential. Cells were treated with soil extractable organic matters (EOMs) and the MTS assay, LDH release and morphological transformation were selected as endpoints for toxicity and carcinogenicity. Soil EOMs induced dose-dependent inhibition of cell growth at low doses and cytotoxicity after exposure to higher doses. This might be the result of block of cell cycle progression to repair DNA damage caused by oxidative stress; if this DNA damage cannot be repaired, cells die. No significant inductions of foci were recorded after exposure to EOMs. These results indicate that, although the extracts contain compounds with proven carcinogenic potential, the levels of these pollutants in the analyzed soils were too low to induce carcinogenesis in our experimental conditions. In this proposed case study, HepG2 cells were found an appropriate tool to assess the potential harm caused by the ingestion of contaminated soil as they were able to detect differences in the toxicity of soil EOMs. Moreover, the cell transformation assay strengthened the combined approach giving useful information on carcinogenic potential of mixtures. Highlights: • A combined approach for risk

  4. Area-based assessment of extinction risk.

    Science.gov (United States)

    Hei, Fangliang

    2012-05-01

    Underpinning the International Union for Conservation of Nature (IUCN) Red List is the assessment of extinction risk as determined by the size and degree of loss of populations. The IUCN system lists a species as Critically Endangered, Endangered, or Vulnerable if its population size declines 80%, 50%, or 30% within a given time frame. However, effective implementation of the system faces substantial challenges and uncertainty because geographic scale data on population size and long-term dynamics are scarce. I develop a model to quantify extinction risk using a measure based on a species' distribution, a much more readily obtained quantity. The model calculates the loss of the area of occupancy that is equivalent to the loss of a given proportion of a population. It is a very simple yet general model that has no free parameters and is independent of scale. The model predicted well the distributions of 302 tree species at a local scale and the distributions of 348 species of North American land birds. This area-based model provides a solution to the long-standing problem for IUCN assessments of lack of data on population sizes, and thus it will contribute to facilitating the quantification of extinction risk worldwide.

  5. A risk-based sensor placement methodology

    International Nuclear Information System (INIS)

    Lee, Ronald W.; Kulesz, James J.

    2008-01-01

    A risk-based sensor placement methodology is proposed to solve the problem of optimal location of sensors to protect population against the exposure to, and effects of, known and/or postulated chemical, biological, and/or radiological threats. Risk is calculated as a quantitative value representing population at risk from exposure at standard exposure levels. Historical meteorological data are used to characterize weather conditions as the frequency of wind speed and direction pairs. The meteorological data drive atmospheric transport and dispersion modeling of the threats, the results of which are used to calculate risk values. Sensor locations are determined via an iterative dynamic programming algorithm whereby threats detected by sensors placed in prior iterations are removed from consideration in subsequent iterations. In addition to the risk-based placement algorithm, the proposed methodology provides a quantification of the marginal utility of each additional sensor. This is the fraction of the total risk accounted for by placement of the sensor. Thus, the criteria for halting the iterative process can be the number of sensors available, a threshold marginal utility value, and/or a minimum cumulative utility achieved with all sensors

  6. 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)

  7. Determination of risk factors for child fall based on the Calgary Family Assessment Model - doi:10.5020/18061230.2010.p101

    Directory of Open Access Journals (Sweden)

    Aline de Souza Pereira

    2012-01-01

    Full Text Available Objective: To determine risk factors for falls in children based on the Calgary Family Assessment Model (CFAM. Method: A qualitative approach, in which we interviewed six relatives of children who were admitted to an emergency hospital in Fortaleza, Ceara due to fall in the period from August to September, 2005. According to the CFAM we did the genogram and eco-map of two families (1 and (2. Results: By the genogram and eco-map of the families, we observed that (1 is a single parent family with six children, Roman Catholic, earns one minimum wage and attends both school and Family Health Basic Unit (UBSF. (2 is a nuclear family, with two children, Roman Catholic, earns three or more minimum wages and attends school, work and UBSF. Conclusion: The Calgary Family Assessment Model enabled to know the family structures of the children who had suffered falls and helped in defining the risk factors that exist within families and social environments in which these children attend. Family income, number of children, the presence or absence of fathers, schooling and lack of spaces for education support represent risk factors for these accidents.

  8. Estimating the risk of gestational diabetes mellitus : a clinical prediction model based on patient characteristics and medical history

    NARCIS (Netherlands)

    van Leeuwen, M.; Opmeer, B. C.; Zweers, E. J. K.; van Ballegooie, E.; ter Brugge, H. G.; de Valk, H. W.; Visser, G. H. A.; Mol, B. W. J.

    Objective To develop a clinical prediction rule that can help the clinician to identify women at high and low risk for gestational diabetes mellitus (GDM) early in pregnancy in order to improve the efficiency of GDM screening. Design We used data from a prospective cohort study to develop the

  9. 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...

  10. Risk Decision Making Based on Decision-theoretic Rough Set: A Three-way View Decision Model

    OpenAIRE

    Huaxiong Li; Xianzhong Zhou

    2011-01-01

    Rough set theory has witnessed great success in data mining and knowledge discovery, which provides a good support for decision making on a certain data. However, a practical decision problem always shows diversity under the same circumstance according to different personality of the decision makers. A simplex decision model can not provide a full description on such diverse decisions. In this article, a review of Pawlak rough set models and probabilistic rough set models is presented, and a ...

  11. Risk-based classification system of nanomaterials

    International Nuclear Information System (INIS)

    Tervonen, Tommi; Linkov, Igor; Figueira, Jose Rui; Steevens, Jeffery; Chappell, Mark; Merad, Myriam

    2009-01-01

    Various stakeholders are increasingly interested in the potential toxicity and other risks associated with nanomaterials throughout the different stages of a product's life cycle (e.g., development, production, use, disposal). Risk assessment methods and tools developed and applied to chemical and biological materials may not be readily adaptable for nanomaterials because of the current uncertainty in identifying the relevant physico-chemical and biological properties that adequately describe the materials. Such uncertainty is further driven by the substantial variations in the properties of the original material due to variable manufacturing processes employed in nanomaterial production. To guide scientists and engineers in nanomaterial research and application as well as to promote the safe handling and use of these materials, we propose a decision support system for classifying nanomaterials into different risk categories. The classification system is based on a set of performance metrics that measure both the toxicity and physico-chemical characteristics of the original materials, as well as the expected environmental impacts through the product life cycle. Stochastic multicriteria acceptability analysis (SMAA-TRI), a formal decision analysis method, was used as the foundation for this task. This method allowed us to cluster various nanomaterials in different ecological risk categories based on our current knowledge of nanomaterial physico-chemical characteristics, variation in produced material, and best professional judgments. SMAA-TRI uses Monte Carlo simulations to explore all feasible values for weights, criteria measurements, and other model parameters to assess the robustness of nanomaterial grouping for risk management purposes.

  12. Risk-based classification system of nanomaterials

    Energy Technology Data Exchange (ETDEWEB)

    Tervonen, Tommi, E-mail: t.p.tervonen@rug.n [University of Groningen, Faculty of Economics and Business (Netherlands); Linkov, Igor, E-mail: igor.linkov@usace.army.mi [US Army Research and Development Center (United States); Figueira, Jose Rui, E-mail: figueira@ist.utl.p [Technical University of Lisbon, CEG-IST, Centre for Management Studies, Instituto Superior Tecnico (Portugal); Steevens, Jeffery, E-mail: jeffery.a.steevens@usace.army.mil; Chappell, Mark, E-mail: mark.a.chappell@usace.army.mi [US Army Research and Development Center (United States); Merad, Myriam, E-mail: myriam.merad@ineris.f [INERIS BP 2, Societal Management of Risks Unit/Accidental Risks Division (France)

    2009-05-15

    Various stakeholders are increasingly interested in the potential toxicity and other risks associated with nanomaterials throughout the different stages of a product's life cycle (e.g., development, production, use, disposal). Risk assessment methods and tools developed and applied to chemical and biological materials may not be readily adaptable for nanomaterials because of the current uncertainty in identifying the relevant physico-chemical and biological properties that adequately describe the materials. Such uncertainty is further driven by the substantial variations in the properties of the original material due to variable manufacturing processes employed in nanomaterial production. To guide scientists and engineers in nanomaterial research and application as well as to promote the safe handling and use of these materials, we propose a decision support system for classifying nanomaterials into different risk categories. The classification system is based on a set of performance metrics that measure both the toxicity and physico-chemical characteristics of the original materials, as well as the expected environmental impacts through the product life cycle. Stochastic multicriteria acceptability analysis (SMAA-TRI), a formal decision analysis method, was used as the foundation for this task. This method allowed us to cluster various nanomaterials in different ecological risk categories based on our current knowledge of nanomaterial physico-chemical characteristics, variation in produced material, and best professional judgments. SMAA-TRI uses Monte Carlo simulations to explore all feasible values for weights, criteria measurements, and other model parameters to assess the robustness of nanomaterial grouping for risk management purposes.

  13. 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.

  14. A risk-based microbiological criterion that uses the relative risk as the critical limit

    DEFF Research Database (Denmark)

    Andersen, Jens Kirk; Nørrung, Birgit; da Costa Alves Machado, Simone

    2015-01-01

    A risk-based microbiological criterion is described, that is based on the relative risk associated to the analytical result of a number of samples taken from a food lot. The acceptable limit is a specific level of risk and not a specific number of microorganisms, as in other microbiological...... criteria. The approach requires the availability of a quantitative microbiological risk assessment model to get risk estimates for food products from sampled food lots. By relating these food lot risk estimates to the mean risk estimate associated to a representative baseline data set, a relative risk...... estimate can be obtained. This relative risk estimate then can be compared with a critical value, defined by the criterion. This microbiological criterion based on a relative risk limit is particularly useful when quantitative enumeration data are available and when the prevalence of the microorganism...

  15. Winner's Curse Correction and Variable Thresholding Improve Performance of Polygenic Risk Modeling Based on Genome-Wide Association Study Summary-Level Data.

    Directory of Open Access Journals (Sweden)

    Jianxin Shi

    2016-12-01

    Full Text Available Recent heritability analyses have indicated that genome-wide association studies (GWAS have the potential to improve genetic risk prediction for complex diseases based on polygenic risk score (PRS, a simple modelling technique that can be implemented using summary-level data from the discovery samples. We herein propose modifications to improve the performance of PRS. We introduce threshold-dependent winner's-curse adjustments for marginal association coefficients that are used to weight the single-nucleotide polymorphisms (SNPs in PRS. Further, as a way to incorporate external functional/annotation knowledge that could identify subsets of SNPs highly enriched for associations, we propose variable thresholds for SNPs selection. We applied our methods to GWAS summary-level data of 14 complex diseases. Across all diseases, a simple winner's curse correction uniformly led to enhancement of performance of the models, whereas incorporation of functional SNPs was beneficial only for selected diseases. Compared to the standard PRS algorithm, the proposed methods in combination led to notable gain in efficiency (25-50% increase in the prediction R2 for 5 of 14 diseases. As an example, for GWAS of type 2 diabetes, winner's curse correction improved prediction R2 from 2.29% based on the standard PRS to 3.10% (P = 0.0017 and incorporating functional annotation data further improved R2 to 3.53% (P = 2×10-5. Our simulation studies illustrate why differential treatment of certain categories of functional SNPs, even when shown to be highly enriched for GWAS-heritability, does not lead to proportionate improvement in genetic risk-prediction because of non-uniform linkage disequilibrium structure.

  16. 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.

  17. Adequacy of relative and absolute risk models for lifetime risk estimate of radiation-induced cancer

    International Nuclear Information System (INIS)

    McBride, M.; Coldman, A.J.

    1988-03-01

    This report examines the applicability of the relative (multiplicative) and absolute (additive) models in predicting lifetime risk of radiation-induced cancer. A review of the epidemiologic literature, and a discussion of the mathematical models of carcinogenesis and their relationship to these models of lifetime risk, are included. Based on the available data, the relative risk model for the estimation of lifetime risk is preferred for non-sex-specific epithelial tumours. However, because of lack of knowledge concerning other determinants of radiation risk and of background incidence rates, considerable uncertainty in modelling lifetime risk still exists. Therefore, it is essential that follow-up of exposed cohorts be continued so that population-based estimates of lifetime risk are available

  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. Incentivising flood risk adaptation through risk based insurance premiums : Trade-offs between affordability and risk reduction

    NARCIS (Netherlands)

    Hudson, Paul F.; Botzen, W.J.W.; Feyen, L.; Aerts, Jeroen C.J.H.

    2016-01-01

    The financial incentives offered by the risk-based pricing of insurance can stimulate policyholder adaptation to flood risk while potentially conflicting with affordability. We examine the trade-off between risk reduction and affordability in a model of public-private flood insurance in France and

  20. 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...

  1. 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

  2. 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.

  3. Statistical and RBF NN models : providing forecasts and risk assessment

    OpenAIRE

    Marček, Milan

    2009-01-01

    Forecast accuracy of economic and financial processes is a popular measure for quantifying the risk in decision making. In this paper, we develop forecasting models based on statistical (stochastic) methods, sometimes called hard computing, and on a soft method using granular computing. We consider the accuracy of forecasting models as a measure for risk evaluation. It is found that the risk estimation process based on soft methods is simplified and less critical to the question w...

  4. Risk-based regulation: Challenges and opportunities

    International Nuclear Information System (INIS)

    Bari, R.A.

    1995-01-01

    Over the last twenty years, man has witnessed a gradual but steady movement toward increased usage of risk-based methods and results in the regulatory process. The ''risk perspective'' as a supportive view to existing (non-risk-based or deterministic) information used in decision making has a firm foothold now in most countries that regulate nuclear power. Furthermore, in the areas outside the nuclear power field, such as health risk assessment, risk-based information is used increasingly to make decisions on potential impacts of chemical, biological, and radiological exposures. Some of the principal concepts and issues that are pertinent to risk-based regulation are reviewed. There is a growing interest in most countries in the use of risk-based methods and results to facilitate decision-making associated with regulatory processes. A summary is presented of the challenges and opportunities related to expanded use of risk-based regulation

  5. Risk-adjusted capitation based on the Diagnostic Cost Group Model: an empirical evaluation with health survey information

    NARCIS (Netherlands)

    L.M. Lamers (Leida)

    1999-01-01

    textabstractOBJECTIVE: To evaluate the predictive accuracy of the Diagnostic Cost Group (DCG) model using health survey information. DATA SOURCES/STUDY SETTING: Longitudinal data collected for a sample of members of a Dutch sickness fund. In the Netherlands the sickness

  6. [Risk-oriented model of the control of the level of electric magnetic fields of base stations of cellular communications].

    Science.gov (United States)

    Lutsenko, L A; Tulakin, A V; Egorova, A M; Mikhailova, O M; Gvozdeva, L L; Chigryay, E K

    The purpose of this study was to give the description of harmful effects of the impact of electromagnetic radiations from base stations of cellular communication as the most common sources of radio frequencies of electromagnetic fields in the environment. The highest values of the energy flux density were measured on the roofs of houses where antennas are installed - more than 10 pW/cm. The lowest values were recorded in inside premises with expositions of 0.1-1 pW/cm. In the close location of the railway station to the base stations of the cellular communication there was seen a cumulative effect. There are proposed both new safe hygienic approaches to the control for the safety of the work of base station and protective measures.

  7. 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.

  8. Breast cancer screening in an era of personalized regimens: a conceptual model and National Cancer Institute initiative for risk-based and preference-based approaches at a population level.

    Science.gov (United States)

    Onega, Tracy; Beaber, Elisabeth F; Sprague, Brian L; Barlow, William E; Haas, Jennifer S; Tosteson, Anna N A; D Schnall, Mitchell; Armstrong, Katrina; Schapira, Marilyn M; Geller, Berta; Weaver, Donald L; Conant, Emily F

    2014-10-01

    Breast cancer screening holds a prominent place in public health, health care delivery, policy, and women's health care decisions. Several factors are driving shifts in how population-based breast cancer screening is approached, including advanced imaging technologies, health system performance measures, health care reform, concern for "overdiagnosis," and improved understanding of risk. Maximizing benefits while minimizing the harms of screening requires moving from a "1-size-fits-all" guideline paradigm to more personalized strategies. A refined conceptual model for breast cancer screening is needed to align women's risks and preferences with screening regimens. A conceptual model of personalized breast cancer screening is presented herein that emphasizes key domains and transitions throughout the screening process, as well as multilevel perspectives. The key domains of screening awareness, detection, diagnosis, and treatment and survivorship are conceptualized to function at the level of the patient, provider, facility, health care system, and population/policy arena. Personalized breast cancer screening can be assessed across these domains with both process and outcome measures. Identifying, evaluating, and monitoring process measures in screening is a focus of a National Cancer Institute initiative entitled PROSPR (Population-based Research Optimizing Screening through Personalized Regimens), which will provide generalizable evidence for a risk-based model of breast cancer screening, The model presented builds on prior breast cancer screening models and may serve to identify new measures to optimize benefits-to-harms tradeoffs in population-based screening, which is a timely goal in the era of health care reform. © 2014 American Cancer Society.

  9. Risk-based optimization of land reclamation

    International Nuclear Information System (INIS)

    Lendering, K.T.; Jonkman, S.N.; Gelder, P.H.A.J.M. van; Peters, D.J.

    2015-01-01

    Large-scale land reclamations are generally constructed by means of a landfill well above mean sea level. This can be costly in areas where good quality fill material is scarce. An alternative to save materials and costs is a ‘polder terminal’. The quay wall acts as a flood defense and the terminal level is well below the level of the quay wall. Compared with a conventional terminal, the costs are lower, but an additional flood risk is introduced. In this paper, a risk-based optimization is developed for a conventional and a polder terminal. It considers the investment and residual flood risk. The method takes into account both the quay wall and terminal level, which determine the probability and damage of flooding. The optimal quay wall level is found by solving a Lambert function numerically. The terminal level is bounded by engineering boundary conditions, i.e. piping and uplift of the cover layer of the terminal yard. It is found that, for a representative case study, the saving of reclamation costs for a polder terminal is larger than the increase of flood risk. The model is applicable to other cases of land reclamation and to similar optimization problems in flood risk management. - Highlights: • A polder terminal can be an attractive alternative for a conventional terminal. • A polder terminal is feasible at locations with high reclamation cost. • A risk-based approach is required to determine the optimal protection levels. • The depth of the polder terminal yard is bounded by uplifting of the cover layer. • This paper can support decisions regarding alternatives for port expansions.

  10. A Risk Metric Assessment of Scenario-Based Market Risk Measures for Volatility and Risk Estimation: Evidence from Emerging Markets

    Directory of Open Access Journals (Sweden)

    Sitima Innocent

    2015-03-01

    Full Text Available The study evaluated the sensitivity of the Value- at- Risk (VaR and Expected Shortfalls (ES with respect to portfolio allocation in emerging markets with an index portfolio of a developed market. This study utilised different models for VaR and ES techniques using various scenario-based models such as Covariance Methods, Historical Simulation and the GARCH (1, 1 for the predictive ability of these models in both relatively stable market conditions and extreme market conditions. The results showed that Expected Shortfall has less risk tolerance than VaR based on the same scenario-based market risk measures

  11. The Influence of Base Rate and Case Information on Health-Risk Perceptions: A Unified Model of Self-Positivity and Self-Negativity

    OpenAIRE

    Dengfeng Yan; Jaideep Sengupta

    2013-01-01

    This research examines how consumers use base rate (e.g., disease prevalence in a population) and case information (e.g., an individual's disease symptoms) to estimate health risks. Drawing on construal level theory, we propose that consumers' reliance on base rate (case information) will be enhanced (weakened) by psychological distance. A corollary of this premise is that self-positivity (i.e., underestimating self-risk vs. other-risk) is likely when the disease base rate is high but the cas...

  12. Risk based seismic design criteria

    International Nuclear Information System (INIS)

    Kennedy, R.P.

    1999-01-01

    In order to develop a risk based seismic design criteria the following four issues must be addressed: (1) What target annual probability of seismic induced unacceptable performance is acceptable? (2) What minimum seismic margin is acceptable? (3) Given the decisions made under Issues 1 and 2, at what annual frequency of exceedance should the safe-shutdown-earthquake (SSE) ground motion be defined? (4) What seismic design criteria should be established to reasonably achieve the seismic margin defined under Issue 2? The first issue is purely a policy decision and is not addressed in this paper. Each of the other three issues are addressed. Issues 2 and 3 are integrally tied together so that a very large number of possible combinations of responses to these two issues can be used to achieve the target goal defined under Issue 1. Section 2 lays out a combined approach to these two issues and presents three potentially attractive combined resolutions of these two issues which reasonably achieves the target goal. The remainder of the paper discusses an approach which can be used to develop seismic design criteria aimed at achieving the desired seismic margin defined in resolution of Issue 2. Suggestions for revising existing seismic design criteria to more consistently achieve the desired seismic margin are presented. (orig.)

  13. Big data based fraud risk management at Alibaba

    OpenAIRE

    Chen, Jidong; Tao, Ye; Wang, Haoran; Chen, Tao

    2015-01-01

    With development of mobile internet and finance, fraud risk comes in all shapes and sizes. This paper is to introduce the Fraud Risk Management at Alibaba under big data. Alibaba has built a fraud risk monitoring and management system based on real-time big data processing and intelligent risk models. It captures fraud signals directly from huge amount data of user behaviors and network, analyzes them in real-time using machine learning, and accurately predicts the bad users and transactions....

  14. The Effectiveness of an Educational Intervention Based on the Health Belief Model in the Empowerment of Stockbreeders Against High-Risk Behaviors Associated with Brucellosis

    Directory of Open Access Journals (Sweden)

    Vahid Babaei

    2014-12-01

    Full Text Available Background and Objectives: Brucellosis is among the most common zoonotic diseases. Educational programs can be effective in the prevention of this disease in humans. The present study was conducted to assess the effectiveness of an educational intervention based on the Health Belief Model (HBM in the empowerment of stockbreeders against high risk behaviors associated with brucellosis in Charuymaq county, East Azerbaijan. Materials and Methods: The present quasi-experimental study was conducted in 2014 in Charuymaq county. A total of 200 people selected through stratified random sampling participated in the study. Data were collected using a researcher-designed questionnaire including items on participants' demographic information, knowledge and the HBM constructs. Training sessions were then designed and held for the intervention group. Three months after the intervention was held, data were collected from both groups and then analyzed using descriptive statistics including the Mann-Whitney U test and the Wilcoxon test. Results: The mean scores obtained for knowledge, HBM constructs (perceived susceptibility, severity, barriers and benefits and self-efficacy and brucellosis preventive behaviors showed no significant differences between the two groups before the intervention however, after the educational intervention, significant differences were observed between the mean scores obtained by the intervention group and the control group (P<0.05. Conclusion: The cooperation of charismatic individuals with intervention programs and the use of education theories can be more effective in modifying high-risk behaviors these programs should therefore be widely implemented across the country.

  15. 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...

  16. Risk-based emergency decision support

    International Nuclear Information System (INIS)

    Koerte, Jens

    2003-01-01

    In the present paper we discuss how to assist critical decisions taken under complex, contingent circumstances, with a high degree of uncertainty and short time frames. In such sharp-end decision regimes, standard rule-based decision support systems do not capture the complexity of the situation. At the same time, traditional risk analysis is of little use due to variability in the specific circumstances. How then, can an organisation provide assistance to, e.g. pilots in dealing with such emergencies? A method called 'contingent risk and decision analysis' is presented, to provide decision support for decisions under variable circumstances and short available time scales. The method consists of nine steps of definition, modelling, analysis and criteria definition to be performed 'off-line' by analysts, and procedure generation to transform the analysis result into an operational decision aid. Examples of pilots' decisions in response to sudden vibration in offshore helicopter transport method are used to illustrate the approach

  17. Study of a risk-based piping inspection guideline system.

    Science.gov (United States)

    Tien, Shiaw-Wen; Hwang, Wen-Tsung; Tsai, Chih-Hung

    2007-02-01

    A risk-based inspection system and a piping inspection guideline model were developed in this study. The research procedure consists of two parts--the building of a risk-based inspection model for piping and the construction of a risk-based piping inspection guideline model. Field visits at the plant were conducted to develop the risk-based inspection and strategic analysis system. A knowledge-based model had been built in accordance with international standards and local government regulations, and the rational unified process was applied for reducing the discrepancy in the development of the models. The models had been designed to analyze damage factors, damage models, and potential damage positions of piping in the petrochemical plants. The purpose of this study was to provide inspection-related personnel with the optimal planning tools for piping inspections, hence, to enable effective predictions of potential piping risks and to enhance the better degree of safety in plant operations that the petrochemical industries can be expected to achieve. A risk analysis was conducted on the piping system of a petrochemical plant. The outcome indicated that most of the risks resulted from a small number of pipelines.

  18. Risk-based methodology for USNRC inspections

    International Nuclear Information System (INIS)

    Wong, S.M.; Holahan, G.M.; Chung, J.W.; Johnson, M.R.

    1995-01-01

    This paper describes the development and trial applications of a risk-based methodology to enhance the inspection processes for US nuclear power plants. Objectives of risk-based methods to complement prescriptive engineering approaches in US Nuclear Regulatory Commission (USNRC) inspection programs are presented. Insights from time-dependent risk profiles of plant configurational from Individual Plant Evaluation (IPE) studies were integrated to develop a framework for optimizing inspection efforts in NRC regulatory initiatives. Lessons learned from NRC pilot applications of the risk-based methodology for evaluation of the effectiveness of operational risk management programs at US nuclear power plant sites are also discussed

  19. 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.)

  20. 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.

  1. Climate-Agriculture-Modeling and Decision Tool for Disease (CAMDT-Disease) for seasonal climate forecast-based crop disease risk management in agriculture

    Science.gov (United States)

    Kim, K. H.; Lee, S.; Han, E.; Ines, A. V. M.

    2017-12-01

    Climate-Agriculture-Modeling and Decision Tool (CAMDT) is a decision support system (DSS) tool that aims to facilitate translations of probabilistic seasonal climate forecasts (SCF) to crop responses such as yield and water stress. Since CAMDT is a software framework connecting different models and algorithms with SCF information, it can be easily customized for different types of agriculture models. In this study, we replaced the DSSAT-CSM-Rice model originally incorporated in CAMDT with a generic epidemiological model, EPIRICE, to generate a seasonal pest outlook. The resulting CAMDT-Disease generates potential risks for selected fungal, viral, and bacterial diseases of rice over the next months by translating SCFs into agriculturally-relevant risk information. The integrated modeling procedure of CAMDT-Disease first disaggregates a given SCF using temporal downscaling methods (predictWTD or FResampler1), runs EPIRICE with the downscaled weather inputs, and finally visualizes the EPIRICE outputs as disease risk compared to that of the previous year and the 30-year-climatological average. In addition, the easy-to-use graphical user interface adopted from CAMDT allows users to simulate "what-if" scenarios of disease risks over different planting dates with given SCFs. Our future work includes the simulation of the effect of crop disease on yields through the disease simulation models with the DSSAT-CSM-Rice model, as disease remains one of the most critical yield-reducing factors in the field.

  2. 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.

  3. 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.

  4. 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

  5. Estimating the Value-at-Risk for some stocks at the capital market in Indonesia based on ARMA-FIGARCH models

    Science.gov (United States)

    Sukono; Lesmana, E.; Susanti, D.; Napitupulu, H.; Hidayat, Y.

    2017-11-01

    Value-at-Risk has already become a standard measurement that must be carried out by the financial institution for both internal interest and regulatory. In this paper, the estimation of Value-at-Risk of some stocks with econometric models approach is analyzed. In this research, we assume that the stock return follows the time series model. To do the estimation of mean value we are using ARMA models, while to estimate the variance value we are using FIGARCH models. Furthermore, the mean value estimator and the variance are used to estimate the Value-at-Risk. The result of the analysis shows that from five stock PRUF, BBRI, MPPA, BMRI, and INDF, the Value-at-Risk obtained are 0.01791, 0.06037, 0.02550, 0.06030, and 0.02585 respectively. Since Value-at-Risk represents the maximum risk size of each stock at a 95% level of significance, then it can be taken into consideration in determining the investment policy on stocks.

  6. 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.

  7. Effects of education based on the health belief model on screening behavior in high risk women for breast cancer, Tehran, Iran.

    Science.gov (United States)

    Hajian, Sepideh; Vakilian, Katayon; Najabadi, Khadijeh Mirzaii; Hosseini, Jalil; Mirzaei, Hamid Reza

    2011-01-01

    Breast cancer is the most common malignancy in women. Early diagnosis allows efficient treatment and increases survival, but the efficacy of breast self examination (BSE) is not sufficiently well established. The American Cancer Society aims to give women the opportunity to recognize the utility, limitations and adverse effects of breast cancer screening through education models based on psychological theories. With the Health Belief Model, people's health perceptions and attitudes influence their practices, for example with screening. The purpose of this randomized controlled clinical trial was to determine the effect of education based on this model on breast cancer screening in high risk Iranian women. Participants were women with a family history of breast cancer (mother, sister, and daughter). After explanation of the study objectives to participants, they were recruited on obtaining oral consent and each filled out the study questionnaire based on the Health Belief Model. Allocation was into two groups by computerized randomization, control and intervention, receiving education on breast cancer screening. Perceived susceptibility to and seriousness of breast cancer, perceived usefulness of and barriers to BSE, clinical breast examination, and mammography, and self-efficacy in the ability to perform these, were assessed, with comparison of scores for BSE practice before and after education and doing mammography and clinical examination by a physician in intervention and control group. The mean age was 37.8 ± 11.7 (range 19-60). The mean rank in the intervention group significantly differed before and after the education, but except for " perceived threat" and "perceived usefulness of breast self examination", we did not find any significant differences from the control group. After educational sessions, breast self examination and clinical examination practice rates were elevated. Health education based on well known psychological theories for breast cancer

  8. Including investment risk in large-scale power market models

    DEFF Research Database (Denmark)

    Lemming, Jørgen Kjærgaard; Meibom, P.

    2003-01-01

    Long-term energy market models can be used to examine investments in production technologies, however, with market liberalisation it is crucial that such models include investment risks and investor behaviour. This paper analyses how the effect of investment risk on production technology selection...... can be included in large-scale partial equilibrium models of the power market. The analyses are divided into a part about risk measures appropriate for power market investors and a more technical part about the combination of a risk-adjustment model and a partial-equilibrium model. To illustrate...... the analyses quantitatively, a framework based on an iterative interaction between the equilibrium model and a separate risk-adjustment module was constructed. To illustrate the features of the proposed modelling approach we examined how uncertainty in demand and variable costs affects the optimal choice...

  9. Prediction of Drug Attitude in Adolescents Based on Family Training Risk Factors for Mental Health in Society: Designing a Model for Prevention of Addiction

    Directory of Open Access Journals (Sweden)

    M Parsian

    2015-06-01

    Full Text Available Background & objectives: Substance abuse is one of the worst humanitarian issues in recent years which undermines the base and foundations of human society. Its prevention requires the application of multiple theories in various disciplines together with diverse methods and techniques. Several studies have been emphasized on the role of personal and familial variables as risk factors for substance use . However, this study was done in order to predict drug addiction attitude in adolescents according to the family training risk factors to prevent substance abuse and to design a model for the prevention of addiction .   Methods: This study is a descriptive and survey research performed on a sample of 373 male and female students selected randomly among the five high school students in Ghaemshahr city. Then a questionnaire including parenting styles, attitude to addiction and social problem solving skill as well as a socioeconomic questionnaire distributed among the students. For data analysis, the statistical method of descriptive statistics and path analysis has been used.   Results: Results of this study have shown that the component of parenting styles has a direct and positive impact on attitudes to drug addiction. In addition, there was a direct and positive non-significant relationship between the adaptive social problem solving skills and attitude to drug addiction and also direct and negative significant relationship between the non-adaptive social problem solving skills on this attitudes. A direct and negative significant relationship was also seen between parenting styles and attitude to drug addiction.   Conclusions: Based on the results of present study, the components of parenting styles have a direct and negative impact on attitudes to drug addiction. Also there is a direct and significant relationship between the components of non-adaptive social problem solving skills and the variable of social attitude in adolescents . But the

  10. Base Station Performance Model

    OpenAIRE

    Walsh, Barbara; Farrell, Ronan

    2005-01-01

    At present the testing of power amplifiers within base station transmitters is limited to testing at component level as opposed to testing at the system level. While the detection of catastrophic failure is possible, that of performance degradation is not. This paper proposes a base station model with respect to transmitter output power with the aim of introducing system level monitoring of the power amplifier behaviour within the base station. Our model reflects the expe...

  11. Conservation of documental collections: implementation of a risk management model in archives based on the case study of Portuguese National Archive Torre do Tombo

    Directory of Open Access Journals (Sweden)

    Luís Filipe Raposo Pereira

    2014-01-01

    Full Text Available The year of 2006 marked the beginning of an innovative project in the field of archives, related with the assessment and evaluation of environmental and biological risks in the Portuguese National Archive, Torre do Tombo. With a first phase in 2006-2007 related with the assessment of environmental and biological risks, in 2009 began the second phase seeking to establish an overall perspective of all risk involved in the deterioration of documentation. The management model defined for Portuguese National Archive, Torre do Tombo sets benchmarks for institutions with the responsibility in safeguarding archival heritage with historical and cultural value, reflecting the progresses since then, in the preventive conservation area – particularly the integration of risk assessment models in its analysis and decision processes. The articulation of management and conservation concepts, allowed the functional optimization of institutions and a sustained comprehension of the different levels involved in preservation, within an organization.

  12. A comparative review of radiation-induced cancer risk models

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Seung Hee; Kim, Ju Youl [FNC Technology Co., Ltd., Yongin (Korea, Republic of); Han, Seok Jung [Risk and Environmental Safety Research Division, Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2017-06-15

    With the need for a domestic level 3 probabilistic safety assessment (PSA), it is essential to develop a Korea-specific code. Health effect assessments study radiation-induced impacts; in particular, long-term health effects are evaluated in terms of cancer risk. The objective of this study was to analyze the latest cancer risk models developed by foreign organizations and to compare the methodology of how they were developed. This paper also provides suggestions regarding the development of Korean cancer risk models. A review of cancer risk models was carried out targeting the latest models: the NUREG model (1993), the BEIR VII model (2006), the UNSCEAR model (2006), the ICRP 103 model (2007), and the U.S. EPA model (2011). The methodology of how each model was developed is explained, and the cancer sites, dose and dose rate effectiveness factor (DDREF) and mathematical models are also described in the sections presenting differences among the models. The NUREG model was developed by assuming that the risk was proportional to the risk coefficient and dose, while the BEIR VII, UNSCEAR, ICRP, and U.S. EPA models were derived from epidemiological data, principally from Japanese atomic bomb survivors. The risk coefficient does not consider individual characteristics, as the values were calculated in terms of population-averaged cancer risk per unit dose. However, the models derived by epidemiological data are a function of sex, exposure age, and attained age of the exposed individual. Moreover, the methodologies can be used to apply the latest epidemiological data. Therefore, methodologies using epidemiological data should be considered first for developing a Korean cancer risk model, and the cancer sites and DDREF should also be determined based on Korea-specific studies. This review can be used as a basis for developing a Korean cancer risk model in the future.

  13. Backtesting for Risk-Based Regulatory Capital

    NARCIS (Netherlands)

    Kerkhof, F.L.J.; Melenberg, B.

    2002-01-01

    In this paper we present a framework for backtesting all currently popular risk measurement methods (including value-at-risk and expected shortfall) using the functional delta method.Estimation risk can be taken explicitly into account.Based on a simulation study we provide evidence that tests for

  14. Annual effective dose due to residential radon progeny in Sweden: Evaluations based on current risk projections models and on risk estimates from a nation-wide Swedish epidemiological study

    Energy Technology Data Exchange (ETDEWEB)

    Doi, M [National Inst. of Radiological Sciences, Chiba (Japan); Lagarde, F [Karolinska Inst., Stockholm (Sweden). Inst. of Environmental Medicine; Falk, R; Swedjemark, G A [Swedish Radiation Protection Inst., Stockholm (Sweden)

    1996-12-01

    Effective dose per unit radon progeny exposure to Swedish population in 1992 is estimated by the risk projection model based on the Swedish epidemiological study of radon and lung cancer. The resulting values range from 1.29 - 3.00 mSv/WLM and 2.58 - 5.99 mSv/WLM, respectively. Assuming a radon concentration of 100 Bq/m{sup 3}, an equilibrium factor of 0.4 and an occupancy factor of 0.6 in Swedish houses, the annual effective dose for the Swedish population is estimated to be 0.43 - 1.98 mSv/year, which should be compared to the value of 1.9 mSv/year, according to the UNSCEAR 1993 report. 27 refs, tabs, figs.

  15. Annual effective dose due to residential radon progeny in Sweden: Evaluations based on current risk projections models and on risk estimates from a nation-wide Swedish epidemiological study

    International Nuclear Information System (INIS)

    Doi, M.; Lagarde, F.

    1996-12-01

    Effective dose per unit radon progeny exposure to Swedish population in 1992 is estimated by the risk projection model based on the Swedish epidemiological study of radon and lung cancer. The resulting values range from 1.29 - 3.00 mSv/WLM and 2.58 - 5.99 mSv/WLM, respectively. Assuming a radon concentration of 100 Bq/m 3 , an equilibrium factor of 0.4 and an occupancy factor of 0.6 in Swedish houses, the annual effective dose for the Swedish population is estimated to be 0.43 - 1.98 mSv/year, which should be compared to the value of 1.9 mSv/year, according to the UNSCEAR 1993 report. 27 refs, tabs, figs

  16. Electricity market pricing, risk hedging and modeling

    Science.gov (United States)

    Cheng, Xu

    In this dissertation, we investigate the pricing, price risk hedging/arbitrage, and simplified system modeling for a centralized LMP-based electricity market. In an LMP-based market model, the full AC power flow model and the DC power flow model are most widely used to represent the transmission system. We investigate the differences of dispatching results, congestion pattern, and LMPs for the two power flow models. An appropriate LMP decomposition scheme to quantify the marginal costs of the congestion and real power losses is critical for the implementation of financial risk hedging markets. However, the traditional LMP decomposition heavily depends on the slack bus selection. In this dissertation we propose a slack-independent scheme to break LMP down into energy, congestion, and marginal loss components by analyzing the actual marginal cost of each bus at the optimal solution point. The physical and economic meanings of the marginal effect at each bus provide accurate price information for both congestion and losses, and thus the slack-dependency of the traditional scheme is eliminated. With electricity priced at the margin instead of the average value, the market operator typically collects more revenue from power sellers than that paid to power buyers. According to the LMP decomposition results, the revenue surplus is then divided into two parts: congestion charge surplus and marginal loss revenue surplus. We apply the LMP decomposition results to the financial tools, such as financial transmission right (FTR) and loss hedging right (LHR), which have been introduced to hedge against price risks associated to congestion and losses, to construct a full price risk hedging portfolio. The two-settlement market structure and the introduction of financial tools inevitably create market manipulation opportunities. We investigate several possible market manipulation behaviors by virtual bidding and propose a market monitor approach to identify and quantify such

  17. 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

  18. Development of Science-Based Permitting Guidance for Geological Sequestration of CO2 in Deep Saline Aquifers Based on Modeling and Risk Assessment

    Energy Technology Data Exchange (ETDEWEB)

    Jean-Philippe Nicot; Renaud Bouroullec; Hugo Castellanos; Susan Hovorka; Srivatsan Lakshminarasimhan; Jeffrey Paine

    2006-06-30

    Underground carbon storage may become one of the solutions to address global warming. However, to have an impact, carbon storage must be done at a much larger scale than current CO{sub 2} injection operations for enhanced oil recovery. It must also include injection into saline aquifers. An important characteristic of CO{sub 2} is its strong buoyancy--storage must be guaranteed to be sufficiently permanent to satisfy the very reason that CO{sub 2} is injected. This long-term aspect (hundreds to thousands of years) is not currently captured in legislation, even if the U.S. has a relatively well-developed regulatory framework to handle carbon storage, especially in the operational short term. This report proposes a hierarchical approach to permitting in which the State/Federal Government is responsible for developing regional assessments, ranking potential sites (''General Permit'') and lessening the applicant's burden if the general area of the chosen site has been ranked more favorably. The general permit would involve determining in the regional sense structural (closed structures), stratigraphic (heterogeneity), and petrophysical (flow parameters such as residual saturation) controls on the long-term fate of geologically sequestered CO{sub 2}. The state-sponsored regional studies and the subsequent local study performed by the applicant will address the long-term risk of the particular site. It is felt that a performance-based approach rather than a prescriptive approach is the most appropriate framework in which to address public concerns. However, operational issues for each well (equivalent to the current underground injection control-UIC-program) could follow regulations currently in place. Area ranking will include an understanding of trapping modes. Capillary (due to residual saturation) and structural (due to local geological configuration) trappings are two of the four mechanisms (the other two are solubility and mineral trappings

  19. 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.

  20. Risk Prediction Model for Severe Postoperative Complication in Bariatric Surgery.

    Science.gov (United States)

    Stenberg, Erik; Cao, Yang; Szabo, Eva; Näslund, Erik; Näslund, Ingmar; Ottosson, Johan

    2018-01-12

    Factors associated with risk for adverse outcome are important considerations in the preoperative assessment of patients for bariatric surgery. As yet, prediction models based on preoperative risk factors have not been able to predict adverse outcome sufficiently. This study aimed to identify preoperative risk factors and to construct a risk prediction model based on these. Patients who underwent a bariatric surgical procedure in Sweden between 2010 and 2014 were identified from the Scandinavian Obesity Surgery Registry (SOReg). Associations between preoperative potential risk factors and severe postoperative complications were analysed using a logistic regression model. A multivariate model for risk prediction was created and validated in the SOReg for patients who underwent bariatric surgery in Sweden, 2015. Revision surgery (standardized OR 1.19, 95% confidence interval (CI) 1.14-0.24, p prediction model. Despite high specificity, the sensitivity of the model was low. Revision surgery, high age, low BMI, large waist circumference, and dyspepsia/GERD were associated with an increased risk for severe postoperative complication. The prediction model based on these factors, however, had a sensitivity that was too low to predict risk in the individual patient case.

  1. 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.

  2. A random forest based risk model for reliable and accurate prediction of receipt of transfusion in patients undergoing percutaneous coronary intervention.

    Directory of Open Access Journals (Sweden)

    Hitinder S Gurm

    Full Text Available BACKGROUND: Transfusion is a common complication of Percutaneous Coronary Intervention (PCI and is associated with adverse short and long term outcomes. There is no risk model for identifying patients most likely to receive transfusion after PCI. The objective of our study was to develop and validate a tool for predicting receipt of blood transfusion in patients undergoing contemporary PCI. METHODS: Random forest models were developed utilizing 45 pre-procedural clinical and laboratory variables to estimate the receipt of transfusion in patients undergoing PCI. The most influential variables were selected for inclusion in an abbreviated model. Model performance estimating transfusion was evaluated in an independent validation dataset using area under the ROC curve (AUC, with net reclassification improvement (NRI used to compare full and reduced model prediction after grouping in low, intermediate, and high risk categories. The impact of procedural anticoagulation on observed versus predicted transfusion rates were assessed for the different risk categories. RESULTS: Our study cohort was comprised of 103,294 PCI procedures performed at 46 hospitals between July 2009 through December 2012 in Michigan of which 72,328 (70% were randomly selected for training the models, and 30,966 (30% for validation. The models demonstrated excellent calibration and discrimination (AUC: full model  = 0.888 (95% CI 0.877-0.899, reduced model AUC = 0.880 (95% CI, 0.868-0.892, p for difference 0.003, NRI = 2.77%, p = 0.007. Procedural anticoagulation and radial access significantly influenced transfusion rates in the intermediate and high risk patients but no clinically relevant impact was noted in low risk patients, who made up 70% of the total cohort. CONCLUSIONS: The risk of transfusion among patients undergoing PCI can be reliably calculated using a novel easy to use computational tool (https://bmc2.org/calculators/transfusion. This risk prediction

  3. Models of evaluating efficiency and risks on integration of cloud-base IT-services of the machine-building enterprise: a system approach

    Science.gov (United States)

    Razumnikov, S.; Kurmanbay, A.

    2016-04-01

    The present paper suggests a system approach to evaluation of the effectiveness and risks resulted from the integration of cloud-based services in a machine-building enterprise. This approach makes it possible to estimate a set of enterprise IT applications and choose the applications to be migrated to the cloud with regard to specific business requirements, a technological strategy and willingness to risk.

  4. The high-density lipoprotein-adjusted SCORE model worsens SCORE-based risk classification in a contemporary population of 30 824 Europeans

    DEFF Research Database (Denmark)

    Mortensen, Martin B; Afzal, Shoaib; Nordestgaard, Børge G

    2015-01-01

    .8 years of follow-up, 339 individuals died of CVD. In the SCORE target population (age 40-65; n = 30,824), fewer individuals were at baseline categorized as high risk (≥5% 10-year risk of fatal CVD) using SCORE-HDL compared with SCORE (10 vs. 17% in men, 1 vs. 3% in women). SCORE-HDL did not improve...... with SCORE, but deteriorated risk classification based on NRI. Future guidelines should consider lower decision thresholds and prioritize CVD morbidity and people above age 65....

  5. Challenges of using HIV as a primary risk indicator: Need for integrated blood donor risk management model

    NARCIS (Netherlands)

    Mapako, T.; Parirewa, J.J.; Emmanuel, J.C.; Mvere, D.A.; Massundah, E.; Mavunganidze, G.; Marowa, L.M.; Postma, M.J.; Van Hulst, M.

    2015-01-01

    Background: The use of risk modelling in blood safety is increasing getting momentum. NBSZ initiated blood donor risk profiling based on donation frequency (r-coding) since 1994 and in 2006 a generic risk classification model was developed (include age and donation venue) which was mainly based on

  6. Risk-based SMA for Cubesats

    Science.gov (United States)

    Leitner, Jesse

    2016-01-01

    This presentation conveys an approach for risk-based safety and mission assurance applied to cubesats. This presentation accompanies a NASA Goddard standard in development that provides guidance for building a mission success plan for cubesats based on the risk tolerance and resources available.

  7. 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...

  8. 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

  9. A software quality model and metrics for risk assessment

    Science.gov (United States)

    Hyatt, L.; Rosenberg, L.

    1996-01-01

    A software quality model and its associated attributes are defined and used as the model for the basis for a discussion on risk. Specific quality goals and attributes are selected based on their importance to a software development project and their ability to be quantified. Risks that can be determined by the model's metrics are identified. A core set of metrics relating to the software development process and its products is defined. Measurements for each metric and their usability and applicability are discussed.

  10. Web Based VRML Modelling

    NARCIS (Netherlands)

    Kiss, S.; Sarfraz, M.

    2004-01-01

    Presents a method to connect VRML (Virtual Reality Modeling Language) and Java components in a Web page using EAI (External Authoring Interface), which makes it possible to interactively generate and edit VRML meshes. The meshes used are based on regular grids, to provide an interaction and modeling

  11. Prediction of Banking Systemic Risk Based on Support Vector Machine

    Directory of Open Access Journals (Sweden)

    Shouwei Li

    2013-01-01

    Full Text Available Banking systemic risk is a complex nonlinear phenomenon and has shed light on the importance of safeguarding financial stability by recent financial crisis. According to the complex nonlinear characteristics of banking systemic risk, in this paper we apply support vector machine (SVM to the prediction of banking systemic risk in an attempt to suggest a new model with better explanatory power and stability. We conduct a case study of an SVM-based prediction model for Chinese banking systemic risk and find the experiment results showing that support vector machine is an efficient method in such case.

  12. 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

  13. Nuclear insurance risk assessment using risk-based methodology

    International Nuclear Information System (INIS)

    Wendland, W.G.

    1992-01-01

    This paper presents American Nuclear Insurers' (ANI's) and Mutual Atomic Energy Liability Underwriters' (MAELU's) process and experience for conducting nuclear insurance risk assessments using a risk-based methodology. The process is primarily qualitative and uses traditional insurance risk assessment methods and an approach developed under the auspices of the American Society of Mechanical Engineers (ASME) in which ANI/MAELU is an active sponsor. This process assists ANI's technical resources in identifying where to look for insurance risk in an industry in which insurance exposure tends to be dynamic and nonactuarial. The process is an evolving one that also seeks to minimize the impact on insureds while maintaining a mutually agreeable risk tolerance

  14. [Factors affecting in-hospital mortality in patients with sepsis: Development of a risk-adjusted model based on administrative data from German hospitals].

    Science.gov (United States)

    König, Volker; Kolzter, Olaf; Albuszies, Gerd; Thölen, Frank

    2018-05-01

    Inpatient administrative data from hospitals is already used nationally and internationally in many areas of internal and public quality assurance in healthcare. For sepsis as the principal condition, only a few published approaches are available for Germany. The aim of this investigation is to identify factors influencing hospital mortality by employing appropriate analytical methods in order to improve the internal quality management of sepsis. The analysis was based on data from 754,727 DRG cases of the CLINOTEL hospital network charged in 2015. The association then included 45 hospitals of all supply levels with the exception of university hospitals (range of beds: 100 to 1,172 per hospital). Cases of sepsis were identified via the ICD codes of their principal diagnosis. Multiple logistic regression analysis was used to determine the factors influencing in-hospital lethality for this population. The model was developed using sociodemographic and other potential variables that could be derived from the DRG data set, and taking into account current literature data. The model obtained was validated with inpatient administrative data of 2016 (51 hospitals, 850,776 DRG cases). Following the definition of the inclusion criteria, 5,608 cases of sepsis (2016: 6,384 cases) were identified in 2015. A total of 12 significant and, over both years, stable factors were identified, including age, severity of sepsis, reason for hospital admission and various comorbidities. The AUC value of the model, as a measure of predictability, is above 0.8 (H-L test p>0.05, R 2 value=0.27), which is an excellent result. The CLINOTEL model of risk adjustment for in-hospital lethality can be used to determine the mortality probability of patients with sepsis as principal diagnosis with a very high degree of accuracy, taking into account the case mix. Further studies are needed to confirm whether the model presented here will prove its value in the internal quality assurance of hospitals

  15. The Comparison of Inductive Reasoning under Risk Conditions between Chinese and Japanese Based on Computational Models: Toward the Application to CAE for Foreign Language

    Science.gov (United States)

    Zhang, Yujie; Terai, Asuka; Nakagawa, Masanori

    2013-01-01

    Inductive reasoning under risk conditions is an important thinking process not only for sciences but also in our daily life. From this viewpoint, it is very useful for language learning to construct computational models of inductive reasoning which realize the CAE for foreign languages. This study proposes the comparison of inductive reasoning…

  16. Using a High-Resolution Ensemble Modeling Method to Inform Risk-Based Decision-Making at Taylor Park Dam, Colorado

    Science.gov (United States)

    Mueller, M.; Mahoney, K. M.; Holman, K. D.

    2015-12-01

    The Bureau of Reclamation (Reclamation) is responsible for the safety of Taylor Park Dam, located in central Colorado at an elevation of 9300 feet. A key aspect of dam safety is anticipating extreme precipitation, runoff and the associated inflow of water to the reservoir within a probabilistic framework for risk analyses. The Cooperative Institute for Research in Environmental Sciences (CIRES) has partnered with Reclamation to improve understanding and estimation of precipitation in the western United States, including the Taylor Park watershed. A significant challenge is that Taylor Park Dam is located in a relatively data-sparse region, surrounded by mountains exceeding 12,000 feet. To better estimate heavy precipitation events in this basin, a high-resolution modeling approach is used. The Weather Research and Forecasting (WRF) model is employed to simulate events that have produced observed peaks in streamflow at the location of interest. Importantly, an ensemble of model simulations are run on each event so that uncertainty bounds (i.e., forecast error) may be provided such that the model outputs may be more effectively used in Reclamation's risk assessment framework. Model estimates of precipitation (and the uncertainty thereof) are then used in rainfall runoff models to determine the probability of inflows to the reservoir for use in Reclamation's dam safety risk analyses.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. A Hierarchal Risk Assessment Model Using the Evidential Reasoning Rule

    Directory of Open Access Journals (Sweden)

    Xiaoxiao Ji

    2017-02-01

    Full Text Available This paper aims to develop a hierarchical risk assessment model using the newly-developed evidential reasoning (ER rule, which constitutes a generic conjunctive probabilistic reasoning process. In this paper, we first provide a brief introduction to the basics of the ER rule and emphasize the strengths for representing and aggregating uncertain information from multiple experts and sources. Further, we discuss the key steps of developing the hierarchical risk assessment framework systematically, including (1 formulation of risk assessment hierarchy; (2 representation of both qualitative and quantitative information; (3 elicitation of attribute weights and information reliabilities; (4 aggregation of assessment information using the ER rule and (5 quantification and ranking of risks using utility-based transformation. The proposed hierarchical risk assessment framework can potentially be implemented to various complex and uncertain systems. A case study on the fire/explosion risk assessment of marine vessels demonstrates the applicability of the proposed risk assessment model.

  2. The Application of Asymmetric Liquidity Risk Measure in Modelling the Risk of Investment

    Directory of Open Access Journals (Sweden)

    Garsztka Przemysław

    2015-06-01

    Full Text Available The article analyses the relationship between investment risk (as measured by the variance of returns or standard deviation of returns and liquidity risk. The paper presents a method for calculating a new measure of liquidity risk, based on the characteristic line. In addition, it is checked what is the impact of liquidity risk to the volatility of daily returns. To describe this relationship dynamic econometric models were used. It was found that there was an econometric relationship between the proposed measure liquidity risk and the variance of returns.

  3. Development of new risk based regulations

    International Nuclear Information System (INIS)

    Nielsen, L.

    1999-01-01

    A short presentation of the oil and gas industry in Norway, and a brief overview of the regulatory regime in the petroleum sector in Norway is given. Risk analysis has been performed in Norway since 1981 and the various applications will be described. These risk analyses are quite different from a nuclear PSA and some of these differences will be commented. Risk based optimisation techniques such as RCM (Reliability Centred Maintenance) and Risk Based Inspection is used in the industry, with very limited support from the risk analysis. Some of the limitation that exist when such techniques are imported from other industries will be commented on. NPD (Norwegian Petroleum Directorate) is revising our regulations and some of the future plants when it comes to risk informed regulatory requirements will be presented. (au)

  4. 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.

  5. Maintenance evaluation using risk based criteria

    International Nuclear Information System (INIS)

    Torres Valle, A.

    1996-01-01

    The maintenance evaluation is currently performed by using economic and, in some case, technical equipment failure criteria, however this is done to a specific equipment level. In general, when statistics are used the analysis for maintenance optimization are made isolated and whit a post mortem character; The integration provided by mean of Probabilistic Safety assessment (PSA) together with the possibilities of its applications, allow for evaluation of maintenance on the basis of broader scope criteria in regard to those traditionally used. The evaluate maintenance using risk based criteria, is necessary to follow a dynamic and systematic approach, in studying the maintenance strategy, to allow for updating the initial probabilistic models, for including operational changes that often take place during operation of complex facilities. This paper proposes a dynamic evaluation system of maintenance task. The system is illustrated by means of a practical example

  6. Risk based limits for Operational Safety Requirements

    International Nuclear Information System (INIS)

    Cappucci, A.J. Jr.

    1993-01-01

    OSR limits are designed to protect the assumptions made in the facility safety analysis in order to preserve the safety envelope during facility operation. Normally, limits are set based on ''worst case conditions'' without regard to the likelihood (frequency) of a credible event occurring. In special cases where the accident analyses are based on ''time at risk'' arguments, it may be desirable to control the time at which the facility is at risk. A methodology has been developed to use OSR limits to control the source terms and the times these source terms would be available, thus controlling the acceptable risk to a nuclear process facility. The methodology defines a new term ''gram-days''. This term represents the area under a source term (inventory) vs time curve which represents the risk to the facility. Using the concept of gram-days (normalized to one year) allows the use of an accounting scheme to control the risk under the inventory vs time curve. The methodology results in at least three OSR limits: (1) control of the maximum inventory or source term, (2) control of the maximum gram-days for the period based on a source term weighted average, and (3) control of the maximum gram-days at the individual source term levels. Basing OSR limits on risk based safety analysis is feasible, and a basis for development of risk based limits is defensible. However, monitoring inventories and the frequencies required to maintain facility operation within the safety envelope may be complex and time consuming

  7. Risk based inspection for atmospheric storage tank

    Science.gov (United States)

    Nugroho, Agus; Haryadi, Gunawan Dwi; Ismail, Rifky; Kim, Seon Jin

    2016-04-01

    Corrosion is an attack that occurs on a metallic material as a result of environment's reaction.Thus, it causes atmospheric storage tank's leakage, material loss, environmental pollution, equipment failure and affects the age of process equipment then finally financial damage. Corrosion risk measurement becomesa vital part of Asset Management at the plant for operating any aging asset.This paper provides six case studies dealing with high speed diesel atmospheric storage tank parts at a power plant. A summary of the basic principles and procedures of corrosion risk analysis and RBI applicable to the Process Industries were discussed prior to the study. Semi quantitative method based onAPI 58I Base-Resource Document was employed. The risk associated with corrosion on the equipment in terms of its likelihood and its consequences were discussed. The corrosion risk analysis outcome used to formulate Risk Based Inspection (RBI) method that should be a part of the atmospheric storage tank operation at the plant. RBI gives more concern to inspection resources which are mostly on `High Risk' and `Medium Risk' criteria and less on `Low Risk' shell. Risk categories of the evaluated equipment were illustrated through case study analysis outcome.

  8. Population-based absolute risk estimation with survey data

    Science.gov (United States)

    Kovalchik, Stephanie A.; Pfeiffer, Ruth M.

    2013-01-01

    Absolute risk is the probability that a cause-specific event occurs in a given time interval in the presence of competing events. We present methods to estimate population-based absolute risk from a complex survey cohort that can accommodate multiple exposure-specific competing risks. The hazard function for each event type consists of an individualized relative risk multiplied by a baseline hazard function, which is modeled nonparametrically or parametrically with a piecewise exponential model. An influence method is used to derive a Taylor-linearized variance estimate for the absolute risk estimates. We introduce novel measures of the cause-specific influences that can guide modeling choices for the competing event components of the model. To illustrate our methodology, we build and validate cause-specific absolute risk models for cardiovascular and cancer deaths using data from the National Health and Nutrition Examination Survey. Our applications demonstrate the usefulness of survey-based risk prediction models for predicting health outcomes and quantifying the potential impact of disease prevention programs at the population level. PMID:23686614

  9. Craniopharyngioma adherence: a comprehensive topographical categorization and outcome-related risk stratification model based on the methodical examination of 500 tumors.

    Science.gov (United States)

    Prieto, Ruth; Pascual, José María; Rosdolsky, Maria; Castro-Dufourny, Inés; Carrasco, Rodrigo; Strauss, Sewan; Barrios, Laura

    2016-12-01

    , 20%). The types of CP attachment associated with the worst surgical outcomes are the ring-like, bowl-like, and circumferential ones with fusion to the TVF or replacement of this structure (p < 0.001). The CP topography is the variable that best predicts the type of CP attachment (p < 0.001). Ring-like and circumferential attachments were observed for CPs invading the TVF (secondary intraventricular CPs) and CPs developing within the TVF itself (infundibulo-tuberal CPs). Brain invasion and peritumoral gliosis occurred predominantly in the ring-like and circumferential adherence patterns (p < 0.001). A multivariate model including the variables CP topography, tumor consistency, and the presence of hydrocephalus, infundibulo-tuberal syndrome, and/or hypothalamic dysfunction accurately predicts the severity of CP attachment in 87% of cases. CONCLUSIONS A comprehensive descriptive model of CP adherence in 5 hierarchical levels of increased severity-mild, moderate, serious, severe, and critical-was generated. This model, based on the location, morphology, and strength of the attachment can be used to anticipate the surgical risk of hypothalamic injury and to plan the degree of removal accordingly.

  10. 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...

  11. 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...

  12. Estimating the decline in excess risk of chronic obstructive pulmonary disease following quitting smoking - a systematic review based on the negative exponential model.

    Science.gov (United States)

    Lee, Peter N; Fry, John S; Forey, Barbara A

    2014-03-01

    We quantified the decline in COPD risk following quitting using the negative exponential model, as previously carried out for other smoking-related diseases. We identified 14 blocks of RRs (from 11 studies) comparing current smokers, former smokers (by time quit) and never smokers, some studies providing sex-specific blocks. Corresponding pseudo-numbers of cases and controls/at risk formed the data for model-fitting. We estimated the half-life (H, time since quit when the excess risk becomes half that for a continuing smoker) for each block, except for one where no decline with quitting was evident, and H was not estimable. For the remaining 13 blocks, goodness-of-fit to the model was generally adequate, the combined estimate of H being 13.32 (95% CI 11.86-14.96) years. There was no heterogeneity in H, overall or by various studied sources. Sensitivity analyses allowing for reverse causation or different assumed times for the final quitting period little affected the results. The model summarizes quitting data well. The estimate of 13.32years is substantially larger than recent estimates of 4.40years for ischaemic heart disease and 4.78years for stroke, and also larger than the 9.93years for lung cancer. Heterogeneity was unimportant for COPD, unlike for the other three diseases. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

  13. Estimating the decline in excess risk of cerebrovascular disease following quitting smoking--a systematic review based on the negative exponential model.

    Science.gov (United States)

    Lee, Peter N; Fry, John S; Thornton, Alison J

    2014-02-01

    We attempted to quantify the decline in stroke risk following quitting using the negative exponential model, with methodology previously employed for IHD. We identified 22 blocks of RRs (from 13 studies) comparing current smokers, former smokers (by time quit) and never smokers. Corresponding pseudo-numbers of cases and controls/at risk formed the data for model-fitting. We tried to estimate the half-life (H, time since quit when the excess risk becomes half that for a continuing smoker) for each block. The method failed to converge or produced very variable estimates of H in nine blocks with a current smoker RR <1.40. Rejecting these, and combining blocks by amount smoked in one study where problems arose in model-fitting, the final analyses used 11 blocks. Goodness-of-fit was adequate for each block, the combined estimate of H being 4.78(95%CI 2.17-10.50) years. However, considerable heterogeneity existed, unexplained by any factor studied, with the random-effects estimate 3.08(1.32-7.16). Sensitivity analyses allowing for reverse causation or differing assumed times for the final quitting period gave similar results. The estimates of H are similar for stroke and IHD, and the individual estimates similarly heterogeneous. Fitting the model is harder for stroke, due to its weaker association with smoking. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

  14. Model Based Temporal Reasoning

    Science.gov (United States)

    Rabin, Marla J.; Spinrad, Paul R.; Fall, Thomas C.

    1988-03-01

    Systems that assess the real world must cope with evidence that is uncertain, ambiguous, and spread over time. Typically, the most important function of an assessment system is to identify when activities are occurring that are unusual or unanticipated. Model based temporal reasoning addresses both of these requirements. The differences among temporal reasoning schemes lies in the methods used to avoid computational intractability. If we had n pieces of data and we wanted to examine how they were related, the worst case would be where we had to examine every subset of these points to see if that subset satisfied the relations. This would be 2n, which is intractable. Models compress this; if several data points are all compatible with a model, then that model represents all those data points. Data points are then considered related if they lie within the same model or if they lie in models that are related. Models thus address the intractability problem. They also address the problem of determining unusual activities if the data do not agree with models that are indicated by earlier data then something out of the norm is taking place. The models can summarize what we know up to that time, so when they are not predicting correctly, either something unusual is happening or we need to revise our models. The model based reasoner developed at Advanced Decision Systems is thus both intuitive and powerful. It is currently being used on one operational system and several prototype systems. It has enough power to be used in domains spanning the spectrum from manufacturing engineering and project management to low-intensity conflict and strategic assessment.

  15. 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.

  16. 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

  17. Prototype Biology-Based Radiation Risk Module Project

    Science.gov (United States)

    Terrier, Douglas; Clayton, Ronald G.; Patel, Zarana; Hu, Shaowen; Huff, Janice

    2015-01-01

    Biological effects of space radiation and risk mitigation are strategic knowledge gaps for the Evolvable Mars Campaign. The current epidemiology-based NASA Space Cancer Risk (NSCR) model contains large uncertainties (HAT #6.5a) due to lack of information on the radiobiology of galactic cosmic rays (GCR) and lack of human data. The use of experimental models that most accurately replicate the response of human tissues is critical for precision in risk projections. Our proposed study will compare DNA damage, histological, and cell kinetic parameters after irradiation in normal 2D human cells versus 3D tissue models, and it will use a multi-scale computational model (CHASTE) to investigate various biological processes that may contribute to carcinogenesis, including radiation-induced cellular signaling pathways. This cross-disciplinary work, with biological validation of an evolvable mathematical computational model, will help reduce uncertainties within NSCR and aid risk mitigation for radiation-induced carcinogenesis.

  18. 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...

  19. Risk Based Optimal Fatigue Testing

    DEFF Research Database (Denmark)

    Sørensen, John Dalsgaard; Faber, M.H.; Kroon, I.B.

    1992-01-01

    Optimal fatigue life testing of materials is considered. Based on minimization of the total expected costs of a mechanical component a strategy is suggested to determine the optimal stress range levels for which additional experiments are to be performed together with an optimal value...

  20. 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.

  1. A climate-based prediction model in the high-risk clusters of the Mekong Delta region, Vietnam: towards improving dengue prevention and control.

    Science.gov (United States)

    Phung, Dung; Talukder, Mohammad Radwanur Rahman; Rutherford, Shannon; Chu, Cordia

    2016-10-01

    To develop a prediction score scheme useful for prevention practitioners and authorities to implement dengue preparedness and controls in the Mekong Delta region (MDR). We applied a spatial scan statistic to identify high-risk dengue clusters in the MDR and used generalised linear-distributed lag models to examine climate-dengue associations using dengue case records and meteorological data from 2003 to 2013. The significant predictors were collapsed into categorical scales, and the β-coefficients of predictors were converted to prediction scores. The score scheme was validated for predicting dengue outbreaks using ROC analysis. The north-eastern MDR was identified as the high-risk cluster. A 1 °C increase in temperature at lag 1-4 and 5-8 weeks increased the dengue risk 11% (95% CI, 9-13) and 7% (95% CI, 6-8), respectively. A 1% rise in humidity increased dengue risk 0.9% (95% CI, 0.2-1.4) at lag 1-4 and 0.8% (95% CI, 0.2-1.4) at lag 5-8 weeks. Similarly, a 1-mm increase in rainfall increased dengue risk 0.1% (95% CI, 0.05-0.16) at lag 1-4 and 0.11% (95% CI, 0.07-0.16) at lag 5-8 weeks. The predicted scores performed with high accuracy in diagnosing the dengue outbreaks (96.3%). This study demonstrates the potential usefulness of a dengue prediction score scheme derived from complex statistical models for high-risk dengue clusters. We recommend a further study to examine the possibility of incorporating such a score scheme into the dengue early warning system in similar climate settings. © 2016 John Wiley & Sons Ltd.

  2. WTS - Risk Based Resource Targeting (RBRT) -

    Data.gov (United States)

    Department of Transportation — The Risk Based Resource Targeting (RBRT) application supports a new SMS-structured process designed to focus on safety oversight of systems and processes rather than...

  3. Risk-based decision making for terrorism applications.

    Science.gov (United States)

    Dillon, Robin L; Liebe, Robert M; Bestafka, Thomas

    2009-03-01

    This article describes the anti-terrorism risk-based decision aid (ARDA), a risk-based decision-making approach for prioritizing anti-terrorism measures. The ARDA model was developed as part of a larger effort to assess investments for protecting U.S. Navy assets at risk and determine whether the most effective anti-terrorism alternatives are being used to reduce the risk to the facilities and war-fighting assets. With ARDA and some support from subject matter experts, we examine thousands of scenarios composed of 15 attack modes against 160 facility types on two installations and hundreds of portfolios of 22 mitigation alternatives. ARDA uses multiattribute utility theory to solve some of the commonly identified challenges in security risk analysis. This article describes the process and documents lessons learned from applying the ARDA model for this application.

  4. [Ecological risk assessment of hydropower dam construction on aquatic species in middle reaches of Lancang River, Southwest China based on ESHIPPO model].

    Science.gov (United States)

    Li, Xiao-Yan; Peng, Ming-Chun; Dong, Shi-Kui; Liu, Shi-Liang; Li, Jin-Peng; Yang, Zhi-Feng

    2013-02-01

    An investigation was conducted on the phytoplankton, zooplankton, and fish at 8 sampling sections in the Manwan Reservoir before and after the construction of Xiaowan Hydropower Dam. The modified ESHIPPO model was applied to study the changes of the featured aquatic species, including endangered species, endemic specie, peis resource species, and native fish, aimed to make an ecological risk assessment of the dam construction on the aquatic species. The dam construction had definite ecological risk on the aquatic species, especially the endemic fish, in Langcang River, due to the changes of hydrological conditions. The endemic species including Bangia atropurpurea, Lemanea sinica, Prasiola sp., Attheyella yunnanensis, and Neutrodiaptomus mariadvigae were at high ecological risk, and thus, besides monitoring, protection measures were needed to be taken to lower the possibility of the species extinction. The widely distributed species of phytoplankton and zooplankton were at medium ecological risk, and protection measures besides monitoring should be prepared. Twelve kinds of native fish, including Barbodes huangchuchieni, Sinilabeo laticeps, Racoma lantsangensis, Racoma lissolabiatus, Paracobitis anguillioides, Schistura latifasciata, Botia nigrolineata, Vanmanenia striata, Homaloptera yunnanensis, Platytropius longianlis, Glyptothorax zanaensis, and Pseudecheneis immaculate, were at high ecological risk, and protection measures needed to be developed to prevent the possibility of the species loss and extinction.

  5. 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.

  6. Risk-Based Operation and Maintenance of Offshore Wind Turbines

    DEFF Research Database (Denmark)

    Nielsen, Jannie Sønderkær

    to oil and gas structures. In addition, condition monitoring systems are often available, and the information should be taken into account when making decisions. In this thesis, methods for risk-based maintenance planning using Bayesian methods are investigated, with the aim of making optimal decisions......, but presently maintenance is not planned using advanced methods taking all available information into account in a consistent manner. Maintenance decisions can be made based on risk-based methods, where the total expected life cycle costs are minimized. Methods have been developed for assessing the corrective...... considering all available information. First, a theoretical damage model is formulated, the model is then updated using condition monitoring data, and the updated model is used as basis for risk-based decision making. Several approaches for solving the decision problems have been considered: various types...

  7. Enhanced leak detection risk model development

    Energy Technology Data Exchange (ETDEWEB)

    Harron, Lorna; Barlow, Rick; Farquhar, Ted [Enbridge Pipelines Inc., Edmonton, Alberta (Canada)

    2010-07-01

    Increasing concerns and attention to pipeline safety have engaged pipeline companies and regulatory agencies to extend their approaches to pipeline integrity. The implementation of High Consequence Areas (HCAs) has especially had an impact on the development of integrity management protocols (IMPs) for pipelines. These IMPs can require that a risk based assessment of integrity issues be applied to specific HCA risk factors. This paper addresses the development of an operational risk assessment approach for pipeline leak detection requirements for HCAs. A detailed risk assessment algorithm that includes 25 risk variables and 28 consequence variables was developed for application to all HCA areas. This paper describes the consultative process that was used to workshop the development of this algorithm. Included in this description is how the process addressed various methods of leak detection across a wide variety of pipelines. The paper also looks at development challenges and future steps in applying operation risk assessment techniques to mainline leak detection risk management.

  8. Comparison of models used for ecological risk assessment and human health risk assessment

    International Nuclear Information System (INIS)

    Ryti, R.T.; Gallegos, A.F.

    1994-01-01

    Models are used to derive action levels for site screening, or to estimate potential ecological or human health risks posed by potentially hazardous sites. At the Los Alamos National Laboratory (LANL), which is RCRA-regulated, the human-health screening action levels are based on hazardous constituents described in RCRA Subpart S and RESRAD-derived soil guidelines (based on 10 mRem/year) for radiological constituents. Also, an ecological risk screening model was developed for a former firing site, where the primary constituents include depleted uranium, beryllium and lead. Sites that fail the screening models are evaluated with site-specific human risk assessment (using RESRAD and other approaches) and a detailed ecological effect model (ECOTRAN). ECOTRAN is based on pharmacokinetics transport modeling within a multitrophic-level biological-growth dynamics model. ECOTRAN provides detailed temporal records of contaminant concentrations in biota, and annual averages of these body burdens are compared to equivalent site-specific runs of the RESRAD model. The results show that thoughtful interpretation of the results of these models must be applied before they can be used for evaluation of current risk posed by sites and the benefits of various remedial options. This presentation compares the concentrations of biological media in the RESRAD screening runs to the concentrations in ecological endpoints predicted by the ecological screening model. The assumptions and limitations of these screening models and the decision process where these are screening models are applied are discussed

  9. Developing points-based risk-scoring systems in the presence of competing risks.

    Science.gov (United States)

    Austin, Peter C; Lee, Douglas S; D'Agostino, Ralph B; Fine, Jason P

    2016-09-30

    Predicting the occurrence of an adverse event over time is an important issue in clinical medicine. Clinical prediction models and associated points-based risk-scoring systems are popular statistical methods for summarizing the relationship between a multivariable set of patient risk factors and the risk of the occurrence of an adverse event. Points-based risk-scoring systems are popular amongst physicians as they permit a rapid assessment of patient risk without the use of computers or other electronic devices. The use of such points-based risk-scoring systems facilitates evidence-based clinical decision making. There is a growing interest in cause-specific mortality and in non-fatal outcomes. However, when considering these types of outcomes, one must account for competing risks whose occurrence precludes the occurrence of the event of interest. We describe how points-based risk-scoring systems can be developed in the presence of competing events. We illustrate the application of these methods by developing risk-scoring systems for predicting cardiovascular mortality in patients hospitalized with acute myocardial infarction. Code in the R statistical programming language is provided for the implementation of the described methods. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

  10. Decision tree-based modelling for identification of potential interactions between type 2 diabetes risk factors: a decade follow-up in a Middle East prospective cohort study.

    Science.gov (United States)

    Ramezankhani, Azra; Hadavandi, Esmaeil; Pournik, Omid; Shahrabi, Jamal; Azizi, Fereidoun; Hadaegh, Farzad

    2016-12-01

    The current study was undertaken for use of the decision tree (DT) method for development of different prediction models for incidence of type 2 diabetes (T2D) and for exploring interactions between predictor variables in those models. Prospective cohort study. Tehran Lipid and Glucose Study (TLGS). A total of 6647 participants (43.4% men) aged >20 years, without T2D at baselines ((1999-2001) and (2002-2005)), were followed until 2012. 2 series of models (with and without 2-hour postchallenge plasma glucose (2h-PCPG)) were developed using 3 types of DT algorithms. The performances of the models were assessed using sensitivity, specificity, area under the ROC curve (AUC), geometric mean (G-Mean) and F-Measure. T2D was primary outcome which defined if fasting plasma glucose (FPG) was ≥7 mmol/L or if the 2h-PCPG was ≥11.1 mmol/L or if the participant was taking antidiabetic medication. During a median follow-up of 9.5 years, 729 new cases of T2D were identified. The Quick Unbiased Efficient Statistical Tree (QUEST) algorithm had the highest sensitivity and G-Mean among all the models for men and women. The models that included 2h-PCPG had sensitivity and G-Mean of (78% and 0.75%) and (78% and 0.78%) for men and women, respectively. Both models achieved good discrimination power with AUC above 0.78. FPG, 2h-PCPG, waist-to-height ratio (WHtR) and mean arterial blood pressure (MAP) were the most important factors to incidence of T2D in both genders. Among men, those with an FPG≤4.9 mmol/L and 2h-PCPG≤7.7 mmol/L had the lowest risk, and those with an FPG>5.3 mmol/L and 2h-PCPG>4.4 mmol/L had the highest risk for T2D incidence. In women, those with an FPG≤5.2 mmol/L and WHtR≤0.55 had the lowest risk, and those with an FPG>5.2 mmol/L and WHtR>0.56 had the highest risk for T2D incidence. Our study emphasises the utility of DT for exploring interactions between predictor variables. Published by the BMJ Publishing Group Limited. For permission

  11. An investigation on the effect of Health Belief Model-based education on refusal skills in high risk situations among female students.

    Science.gov (United States)

    Boroumandfar, Khadijeh; Shabani, Fatemeh; Ghaffari, Mohtasham

    2012-03-01

    Various studies show an association between lack of social skills in adolescents and the future incidence of behavioral disorders. If girls, as future mothers, lack adequate health, awareness, self confidence and social skills, they may act as a source of many social problems. Therefore, the present study has tried to educate this group on one of the most essential social skills, refusal skill in high risk situation. This is a field quasi experimental study conducted on 145 female students in middle schools in Arak, Iran in 2010-2011. The schools were randomly selected. The subjects were selected through systematic random sampling from the schools' log book. The data were collected by questionnaires containing personal and familial characteristics, three health belief model structures, and behavioral intention in high risk situations. The data were analyzed by descriptive statistical tests (frequency distribution, mean, SD) and inferential tests of repetitive variance analysis and T-test through SPSS. In the present study, repetitive variance analysis showed that education by use of a health belief model had a positive effect on refusal skills in high risk situations as well as perceived barriers (p = 0.007), self-efficacy (p = 0.015), behavioral intention (p = 0.048) after educational intervention in the study group, but not on perceived benefits (p = 0.180). The results showed that education significantly increased refusal skills in high risk situations in the study group through the health belief model. With regard to the results, it is essential to equip the students with preventive behaviors to guarantee their physical, emotional and social health.

  12. A model for the optimal risk management of (farm) firms

    DEFF Research Database (Denmark)

    Rasmussen, Svend

    Current methods of risk management focus on efficiency and do not provide operational answers to the basic question of how to optimise and balance the two objectives, maximisation of expected income and minimisation of risk. This paper uses the Capital Asset Pricing Model (CAPM) to derive...... an operational criterion for the optimal risk management of firms. The criterion assumes that the objective of the firm manager is to maximise the market value of the firm and is based on the condition that the application of risk management tools has a symmetric effect on the variability of income around...... the mean. The criterion is based on the expected consequences of risk management on relative changes in the variance of return on equity and expected income. The paper demonstrates how the criterion may be used to evaluate and compare the effect of different risk management tools, and it illustrates how...

  13. Ingestion risks of metals in groundwater based on TIN model and dose-response assessment - A case study in the Xiangjiang watershed, central-south China

    International Nuclear Information System (INIS)

    Chai, Liyuan; Wang, Zhenxing; Wang, Yunyan; Yang, Zhihui; Wang, Haiying; Wu, Xie

    2010-01-01

    Groundwater samples were collected in the Xiangjiang watershed in China from 2002 to 2008 to analyze concentrations of arsenic, cadmium, chromium, copper, iron, lead, mercury, manganese, and zinc. Spatial and seasonal trends of metal concentrations were then discussed. Combined with geostatistics, an ingestion risk assessment of metals in groundwater was performed using the dose-response assessment method and the triangulated irregular network (TIN) model. Arsenic concentration in groundwater had a larger variation from year to year, while the variations of other metal concentrations were minor. Meanwhile, As concentrations in groundwater over the period of 2002-2004 were significantly higher than that over the period of 2005-2007, indicating the improvement of groundwater quality within the later year. The hazard index (HI) in 2002 was also significantly higher than that in 2005, 2006, 2007 and 2008. Moreover, more than 80% of the study area recorded an HI of more than 1.0 for children, suggesting that some people will experience deleterious health effects from drinking groundwater in the Xiangjiang watershed. Arsenic and manganese were the largest contributors to human health risks (HHRs). This study highlights the value of long-term health risk evaluation and the importance of geographic information system (GIS) technologies in the assessment of watershed-scale human health risk.

  14. Managing business model innovation risks - lessons for theory and practice

    DEFF Research Database (Denmark)

    Taran, Yariv; Chester Goduscheit, René; Boer, Harry

    2015-01-01

    approach, arguing from a “no risk no reward” aphorism, a sloppy implementation approach towards business model innovation may result in catastrophic, sometimes even fatal, consequences to a firm’s core business. Based on four unsuccessful business model innovation experiences, which took place in three...

  15. Skull base tumor model.

    Science.gov (United States)

    Gragnaniello, Cristian; Nader, Remi; van Doormaal, Tristan; Kamel, Mahmoud; Voormolen, Eduard H J; Lasio, Giovanni; Aboud, Emad; Regli, Luca; Tulleken, Cornelius A F; Al-Mefty, Ossama

    2010-11-01

    Resident duty-hours restrictions have now been instituted in many countries worldwide. Shortened training times and increased public scrutiny of surgical competency have led to a move away from the traditional apprenticeship model of training. The development of educational models for brain anatomy is a fascinating innovation allowing neurosurgeons to train without the need to practice on real patients and it may be a solution to achieve competency within a shortened training period. The authors describe the use of Stratathane resin ST-504 polymer (SRSP), which is inserted at different intracranial locations to closely mimic meningiomas and other pathological entities of the skull base, in a cadaveric model, for use in neurosurgical training. Silicone-injected and pressurized cadaveric heads were used for studying the SRSP model. The SRSP presents unique intrinsic metamorphic characteristics: liquid at first, it expands and foams when injected into the desired area of the brain, forming a solid tumorlike structure. The authors injected SRSP via different passages that did not influence routes used for the surgical approach for resection of the simulated lesion. For example, SRSP injection routes included endonasal transsphenoidal or transoral approaches if lesions were to be removed through standard skull base approach, or, alternatively, SRSP was injected via a cranial approach if the removal was planned to be via the transsphenoidal or transoral route. The model was set in place in 3 countries (US, Italy, and The Netherlands), and a pool of 13 physicians from 4 different institutions (all surgeons and surgeons in training) participated in evaluating it and provided feedback. All 13 evaluating physicians had overall positive impressions of the model. The overall score on 9 components evaluated--including comparison between the tumor model and real tumor cases, perioperative requirements, general impression, and applicability--was 88% (100% being the best possible

  16. Proliferation Risk Characterization Model Prototype Model - User and Programmer Guidelines

    Energy Technology Data Exchange (ETDEWEB)

    Dukelow, J.S.; Whitford, D.

    1998-12-01

    A model for the estimation of the risk of diversion of weapons-capable materials was developed. It represents both the threat of diversion and site vulnerability as a product of a small number of variables (two to eight), each of which can take on a small number (two to four) of qualitatively defined (but quantitatively implemented) values. The values of the overall threat and vulnerability variables are then converted to threat and vulnerability categories. The threat and vulnerability categories are used to define the likelihood of diversion, also defined categorically. The evaluator supplies an estimate of the consequences of a diversion, defined categorically, but with the categories based on the IAEA Attractiveness levels. Likelihood and Consequences categories are used to define the Risk, also defined categorically. The threat, vulnerability, and consequences input provided by the evaluator contains a representation of his/her uncertainty in each variable assignment which is propagated all the way through to the calculation of the Risk categories. [Appendix G available on diskette only.

  17. Predicting the cumulative risk of death during hospitalization by modeling weekend, weekday and diurnal mortality risks.

    Science.gov (United States)

    Coiera, Enrico; Wang, Ying; Magrabi, Farah; Concha, Oscar Perez; Gallego, Blanca; Runciman, William

    2014-05-21

    Current prognostic models factor in patient and disease specific variables but do not consider cumulative risks of hospitalization over time. We developed risk models of the likelihood of death associated with cumulative exposure to hospitalization, based on time-varying risks of hospitalization over any given day, as well as day of the week. Model performance was evaluated alone, and in combination with simple disease-specific models. Patients admitted between 2000 and 2006 from 501 public and private hospitals in NSW, Australia were used for training and 2007 data for evaluation. The impact of hospital care delivered over different days of the week and or times of the day was modeled by separating hospitalization risk into 21 separate time periods (morning, day, night across the days of the week). Three models were developed to predict death up to 7-days post-discharge: 1/a simple background risk model using age, gender; 2/a time-varying risk model for exposure to hospitalization (admission time, days in hospital); 3/disease specific models (Charlson co-morbidity index, DRG). Combining these three generated a full model. Models were evaluated by accuracy, AUC, Akaike and Bayesian information criteria. There was a clear diurnal rhythm to hospital mortality in the data set, peaking in the evening, as well as the well-known 'weekend-effect' where mortality peaks with weekend admissions. Individual models had modest performance on the test data set (AUC 0.71, 0.79 and 0.79 respectively). The combined model which included time-varying risk however yielded an average AUC of 0.92. This model performed best for stays up to 7-days (93% of admissions), peaking at days 3 to 5 (AUC 0.94). Risks of hospitalization vary not just with the day of the week but also time of the day, and can be used to make predictions about the cumulative risk of death associated with an individual's hospitalization. Combining disease specific models with such time varying- estimates appears to

  18. A semi-quantitative model for risk appreciation and risk weighing

    DEFF Research Database (Denmark)

    Bos, Peter M.J.; Boon, Polly E.; van der Voet, Hilko

    2009-01-01

    Risk managers need detailed information on (1) the type of effect, (2) the size (severity) of the expected effect(s) and (3) the fraction of the population at risk to decide on well-balanced risk reduction measures. A previously developed integrated probabilistic risk assessment (IPRA) model...... provides quantitative information on these three parameters. A semi-quantitative tool is presented that combines information on these parameters into easy-readable charts that will facilitate risk evaluations of exposure situations and decisions on risk reduction measures. This tool is based on a concept...... detailed information on the estimated health impact in a given exposure situation. These graphs will facilitate the discussions on appropriate