778 resultados para Risk level


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Requirement engineering is a key issue in the development of a software project. Like any other development activity it is not without risks. This work is about the empirical study of risks of requirements by applying machine learning techniques, specifically Bayesian networks classifiers. We have defined several models to predict the risk level for a given requirement using three dataset that collect metrics taken from the requirement specifications of different projects. The classification accuracy of the Bayesian models obtained is evaluated and compared using several classification performance measures. The results of the experiments show that the Bayesians networks allow obtaining valid predictors. Specifically, a tree augmented network structure shows a competitive experimental performance in all datasets. Besides, the relations established between the variables collected to determine the level of risk in a requirement, match with those set by requirement engineers. We show that Bayesian networks are valid tools for the automation of risks assessment in requirement engineering.

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Risk acceptance has been broadly discussed in relation to hazardous risk activities and/or technologies. A better understanding of risk acceptance in occupational settings is also important; however, studies on this topic are scarce. It seems important to understand the level of risk that stakeholders consider sufficiently low, how stakeholders form their opinion about risk, and why they adopt a certain attitude toward risk. Accordingly, the aim of this study is to examine risk acceptance in regard to occupational accidents in furniture industries. The safety climate analysis was conducted through the application of the Safety Climate in Wood Industries questionnaire. Judgments about risk acceptance, trust, risk perception, benefit perception, emotions, and moral values were measured. Several models were tested to explain occupational risk acceptance. The results showed that the level of risk acceptance decreased as the risk level increased. High-risk and death scenarios were assessed as unacceptable. Risk perception, emotions, and trust had an important influence on risk acceptance. Safety climate was correlated with risk acceptance and other variables that influence risk acceptance. These results are important for the risk assessment process in terms of defining risk acceptance criteria and strategies to reduce risks.

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Increased crash risk is associated with sedative medications and researchers and health-professionals have called for improvements to medication warnings about driving. The tiered warning system in France since 2005 indicates risk level, uses a color-coded pictogram, and advises the user to seek the advice of a doctor before driving. In Queensland, Australia, the mandatory warning on medications that may cause drowsiness advises the user not to drive or operate machinery if they self-assess that they are affected, and calls attention to possible increased impairment when combined with alcohol. Objectives The reported aims of the study were to establish and compare risk perceptions associated with the Queensland and French warnings among medication users. It was conducted to complement the work of DRUID in reviewing the effectiveness of existing campaigns and practice guidelines. Methods Medication users in France and Queensland were surveyed using warnings about driving from both contexts to compare risk perceptions associated with each label. Both samples were assessed for perceptions of the warning that carried the strongest message of risk. The Queensland study also included perceptions of the likelihood of crash and level of impairment associated with the warning. Results Findings from the French study (N = 75) indicate that when all labels were compared, the majority of respondents perceived the French Level-3 label as the strongest warning about risk concerning driving. Respondents in Queensland had significantly stronger perceptions of potential impairment to driving ability, z = -13.26, p <.000 (n = 325), and potential chance of having a crash, z = -11.87, p < .000 (n = 322), after taking a medication that displayed the strongest French warning, compared with the strongest Queensland warning. Conclusions Evidence suggests that warnings about driving displayed on medications can influence risk perceptions associated with use of medication. Further analyses will determine whether risk perceptions influence compliance with the warnings.

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Objective: To calculate pooled risk estimates of the association between pigmentary characteristics and basal cell carcinoma (BCC) of the skin. Methods: We searched three electronic databases and reviewed the reference lists of the retrieved articles until July 2012 to identify eligible epidemiologic studies. Eligible studies were those published in between 1965 and July 2012 that permitted quantitative assessment of the association between histologically-confirmed BCC and any of the following characteristics: hair colour, eye colour, skin colour, skin phototype, tanning and burning ability, and presence of freckling or melanocytic nevi. We included 29 studies from 2236 initially identified. We calculated summary odds ratios (ORs) using weighted averages of the log OR, using random effects models. Results: We found strongest associations with red hair (OR 2.02; 95% CI: 1.68, 2.44), fair skin colour (OR 2.11; 95% CI: 1.56, 2.86), and having skin that burns and never tans (OR 2.03; 95% CI: 1.73, 2.38). All other factors had weaker but positive associations with BCC, with the exception of freckling of the face in adulthood which showed no association. Conclusions: Although most studies report risk estimates that are in the same direction, there is significant heterogeneity in the size of the estimates. The associations were quite modest and remarkably similar, with ORs between about 1.5 and 2.5 for the highest risk level for each factor. Given the public health impact of BCC, this meta-analysis will make a valuable contribution to our understanding of BCC.

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During the last few decades there have been far going financial market deregulation, technical development, advances in information technology, and standardization of legislation between countries. As a result, one can expect that financial markets have grown more interlinked. The proper understanding of the cross-market linkages has implications for investment and risk management, diversification, asset pricing, and regulation. The purpose of this research is to assess the degree of price, return, and volatility linkages between both geographic markets and asset categories within one country, Finland. Another purpose is to analyze risk asymmetries, i.e., the tendency of equity risk to be higher after negative events than after positive events of equal magnitude. The analysis is conducted both with respect to total risk (volatility), and systematic risk (beta). The thesis consists of an introductory part and four essays. The first essay studies to which extent international stock prices comove. The degree of comovements is low, indicating benefits from international diversification. The second essay examines the degree to which the Finnish market is linked to the “world market”. The total risk is divided into two parts, one relating to world factors, and one relating to domestic factors. The impact of world factors has increased over time. After 1993, when foreign investors were allowed to freely invest in Finnish assets, the risk level has been higher than previously. This was also the case during the economic recession in the beginning of the 1990’s. The third essay focuses on the stock, bond, and money markets in Finland. According to a trading model, the degree of volatility linkages should be strong. However, the results contradict this. The linkages are surprisingly weak, even negative. The stock market is the most independent, while the money market is affected by events on the two other markets. The fourth essay concentrates on volatility and beta asymmetries. Contrary to many international studies there are only few cases of risk asymmetries. When they occur, they tend to be driven by the market-wide component rather than the portfolio specific element.

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Contemporary Irish data on the prevalence of major cardiovascular disease (CVD) risk factors are sparse. The primary aims of this study were (1) to estimate the prevalence of major cardiovascular disease risk factors, including Type 2 Diabetes Mellitus, in the general population of men and women between the ages of 50 and 69 years; and (2) to estimate the proportion of individuals in this age group at high absolute risk of cardiovascular disease events on the basis of pre-existing cardiovascular disease or as defined by the Framingham equation. Participants were drawn from the practice lists of 17 general practices in Cork and Kerry using stratified random sampling. A total of 1018 people attended for screening (490 men, 48%) from 1473 who were invited, a response rate of 69.1%. Cardiovascular disease risk factors and glucose intolerance are common in the population of men and women aged between 50 and 69 years. Almost half the participants were overweight and a further quarter met current international criteria for obesity, one of the highest recorded prevalence rates for obesity in a European population sample. Forty per cent of the population reported minimal levels of physical activity and 19% were current cigarette smokers. Approximately half the sample had blood pressure readings consistent with international criteria for the diagnosis of hypertension, but only 38% of these individuals were known to be hypertensive. Eighty per cent of the population sample had a cholesterol concentration in excess of 5 mmol/l. Almost 4% of the population had Type 2 Diabetes Mellitus, of whom 30% were previously undiagnosed. A total of 137 participants (13.5%) had a history or ECG findings consistent with established cardiovascular disease. Of the remaining 881 individuals in the primary prevention population, a total of 20 high-risk individuals (19 male) had a risk of a coronary heart disease event 30% over ten years according to the Framingham risk equation, giving an overall population prevalence of 2.0% (95% CI 1.3 - 3.0). At a risk level 20% over ten years, an additional 91 individuals (8.9%) were identified. Thus a total of 24.4% of the population were at risk either through pre-existing CVD (13.5%) or an estimated 10-year risk exceeding 20% according to the Framingham risk equation (10.9%). Thus a substantial proportion of middle-aged men are at high risk of CVD. The findings emphasise the scale of the CVD epidemic in Ireland and the need for ongoing monitoring of risk factors at the population level and the need to develop preventive strategies at both the clinical and societal level.

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PURPOSE: Risk-stratified guidelines can improve quality of care and cost-effectiveness, but their uptake in primary care has been limited. MeTree, a Web-based, patient-facing risk-assessment and clinical decision support tool, is designed to facilitate uptake of risk-stratified guidelines. METHODS: A hybrid implementation-effectiveness trial of three clinics (two intervention, one control). PARTICIPANTS: consentable nonadopted adults with upcoming appointments. PRIMARY OUTCOME: agreement between patient risk level and risk management for those meeting evidence-based criteria for increased-risk risk-management strategies (increased risk) and those who do not (average risk) before MeTree and after. MEASURES: chart abstraction was used to identify risk management related to colon, breast, and ovarian cancer, hereditary cancer, and thrombosis. RESULTS: Participants = 488, female = 284 (58.2%), white = 411 (85.7%), mean age = 58.7 (SD = 12.3). Agreement between risk management and risk level for all conditions for each participant, except for colon cancer, which was limited to those <50 years of age, was (i) 1.1% (N = 2/174) for the increased-risk group before MeTree and 16.1% (N = 28/174) after and (ii) 99.2% (N = 2,125/2,142) for the average-risk group before MeTree and 99.5% (N = 2,131/2,142) after. Of those receiving increased-risk risk-management strategies at baseline, 10.5% (N = 2/19) met criteria for increased risk. After MeTree, 80.7% (N = 46/57) met criteria. CONCLUSION: MeTree integration into primary care can improve uptake of risk-stratified guidelines and potentially reduce "overuse" and "underuse" of increased-risk services.Genet Med 18 10, 1020-1028.

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The use of appropriate acceptance criteria in the risk assessment process for occupational accidents is an important issue but often overlooked in the literature, particularly when new risk assessment methods are proposed and discussed. In most cases, there is no information on how or by whom they were defined, or even how companies can adapt them to their own circumstances. Bearing this in mind, this study analysed the problem of the definition of risk acceptance criteria for occupational settings, defining the quantitative acceptance criteria for the specific case study of the Portuguese furniture industrial sector. The key steps to be considered in formulating acceptance criteria were analysed in the literature review. By applying the identified steps, the acceptance criteria for the furniture industrial sector were then defined. The Cumulative Distribution Function (CDF) for the injury statistics of the industrial sector was identified as the maximum tolerable risk level. The acceptable threshold was defined by adjusting the CDF to the Occupational, Safety & Health (OSH) practitioners’ risk acceptance judgement. Adjustments of acceptance criteria to the companies’ safety cultures were exemplified by adjusting the Burr distribution parameters. An example of a risk matrix was also used to demonstrate the integration of the defined acceptance criteria into a risk metric. This work has provided substantial contributions to the issue of acceptance criteria for occupational accidents, which may be useful in overcoming the practical difficulties faced by authorities, companies and experts.

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Farming systems research is a multi-disciplinary holistic approach to solve the problems of small farms. Small and marginal farmers are the core of the Indian rural economy Constituting 0.80 of the total farming community but possessing only 0.36 of the total operational land. The declining trend of per capita land availability poses a serious challenge to the sustainability and profitability of farming. Under such conditions, it is appropriate to integrate land-based enterprises such as dairy, fishery, poultry, duckery, apiary, field and horticultural cropping within the farm, with the objective of generating adequate income and employment for these small and marginal farmers Under a set of farm constraints and varying levels of resource availability and Opportunity. The integration of different farm enterprises can be achieved with the help of a linear programming model. For the current review, integrated farming systems models were developed, by Way Of illustration, for the marginal, small, medium and large farms of eastern India using linear programming. Risk analyses were carried out for different levels of income and enterprise combinations. The fishery enterprise was shown to be less risk-prone whereas the crop enterprise involved greater risk. In general, the degree of risk increased with the increasing level of income. With increase in farm income and risk level, the resource use efficiency increased. Medium and large farms proved to be more profitable than small and marginal farms with higher level of resource use efficiency and return per Indian rupee (Rs) invested. Among the different enterprises of integrated farming systems, a chain of interaction and resource flow was observed. In order to make fanning profitable and improve resource use efficiency at the farm level, the synergy among interacting components of farming systems should be exploited. In the process of technology generation, transfer and other developmental efforts at the farm level (contrary to the discipline and commodity-based approaches which have a tendency to be piecemeal and in isolation), it is desirable to place a whole-farm scenario before the farmers to enhance their farm income, thereby motivating them towards more efficient and sustainable fanning.

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This study presents a new methodology based on risk/investment to solve transmission network expansion planning (TNEP) problem with multiple future scenarios. Three mathematical models related to TNEP problems considering multiple future generation and load scenarios are also presented. These models will provide planners with a meaningful risk assessment that enable them to determine the necessary funding for transmission lines at a permissible risk level. The results using test and real systems show that the proposed method presents better solutions compared with scenario analysis method. ©The Institution of Engineering and Technology 2013.

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This paper reviews the literature of construction risk modelling and assessment. It also reviews the real practice of risk assessment. The review resulted in significant results, summarised as follows. There has been a major shift in risk perception from an estimation variance into a project attribute. Although the Probability–Impact risk model is prevailing, substantial efforts are being put to improving it reflecting the increasing complexity of construction projects. The literature lacks a comprehensive assessment approach capable of capturing risk impact on different project objectives. Obtaining a realistic project risk level demands an effective mechanism for aggregating individual risk assessments. The various assessment tools suffer from low take-up; professionals typically rely on their experience. It is concluded that a simple analytical tool that uses risk cost as a common scale and utilises professional experience could be a viable option to facilitate closing the gap between theory and practice of risk assessment.

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People, animals and the environment can be exposed to multiple chemicals at once from a variety of sources, but current risk assessment is usually carried out based on one chemical substance at a time. In human health risk assessment, ingestion of food is considered a major route of exposure to many contaminants, namely mycotoxins, a wide group of fungal secondary metabolites that are known to potentially cause toxicity and carcinogenic outcomes. Mycotoxins are commonly found in a variety of foods including those intended for consumption by infants and young children and have been found in processed cereal-based foods available in the Portuguese market. The use of mathematical models, including probabilistic approaches using Monte Carlo simulations, constitutes a prominent issue in human health risk assessment in general and in mycotoxins exposure assessment in particular. The present study aims to characterize, for the first time, the risk associated with the exposure of Portuguese children to single and multiple mycotoxins present in processed cereal-based foods (CBF). Portuguese children (0-3 years old) food consumption data (n=103) were collected using a 3 days food diary. Contamination data concerned the quantification of 12 mycotoxins (aflatoxins, ochratoxin A, fumonisins and trichothecenes) were evaluated in 20 CBF samples marketed in 2014 and 2015 in Lisbon; samples were analyzed by HPLC-FLD, LC-MS/MS and GC-MS. Daily exposure of children to mycotoxins was performed using deterministic and probabilistic approaches. Different strategies were used to treat the left censored data. For aflatoxins, as carcinogenic compounds, the margin of exposure (MoE) was calculated as a ratio of BMDL (benchmark dose lower confidence limit) to the aflatoxin exposure. The magnitude of the MoE gives an indication of the risk level. For the remaining mycotoxins, the output of exposure was compared to the dose reference values (TDI) in order to calculate the hazard quotients (ratio between exposure and a reference dose, HQ). For the cumulative risk assessment of multiple mycotoxins, the concentration addition (CA) concept was used. The combined margin of exposure (MoET) and the hazard index (HI) were calculated for aflatoxins and the remaining mycotoxins, respectively. 71% of CBF analyzed samples were contaminated with mycotoxins (with values below the legal limits) and approximately 56% of the studied children consumed CBF at least once in these 3 days. Preliminary results showed that children exposure to single mycotoxins present in CBF were below the TDI. Aflatoxins MoE and MoET revealed a reduced potential risk by exposure through consumption of CBF (with values around 10000 or more). HQ and HI values for the remaining mycotoxins were below 1. Children are a particularly vulnerable population group to food contaminants and the present results point out an urgent need to establish legal limits and control strategies regarding the presence of multiple mycotoxins in children foods in order to protect their health. The development of packaging materials with antifungal properties is a possible solution to control the growth of moulds and consequently to reduce mycotoxin production, contributing to guarantee the quality and safety of foods intended for children consumption.

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Background: The role of common, low to intermediate risk alleles in breast cancer need to be examined due to their relatively high prevalence. Among many cellular pathways, replication has a pivotal role in cell division and frequently targeted during carcinogenesis. Replication is governed by a host of genes involved in a number of different pathways. This study investigates the effects of replication-gene variants in relation to breast cancer and how this relationship is affected by ethnicity, menopausal status and breast tumour subtype. Methods: Data from a case-control study with 997 incident breast cancer cases and 1,050 age frequency matched controls in Vancouver, British Columbia and Kingston, Ontario were used. Unconditional logistic regression was used to calculate odds ratios between 45 replication gene variants and breast cancer risk, assuming an additive genetic model adjusted for age and centre, presented for Europeans and East Asians separately. Polytomous logistic regression was used to assess odds ratios between each SNP and four breast cancer subtypes defined by hormone receptor status among Europeans. All analyses were stratified by menopausal status. The Benjamini–Hochberg false discovery rate (FDR) was used to address multiple comparisons. Results: Among Europeans, the SNPs in FGFR2, TOX3 and 11q13 loci were associated with breast cancer after controlling for multiple comparisons. Test of heterogeneity showed the SNPs rs1045185, rs4973768, rs672888, rs1219648, rs2420946 among Europeans and rs889312 among East Asians conferred differential risk across the tumour subtypes. Conclusions: Specific SNPs in replication genes were associated with breast cancer, and the risk level differed by tumour subtype defined by ER/PR/Her2 status and ethnicity.

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Calibration process in micro-simulation is an extremely complicated phenomenon. The difficulties are more prevalent if the process encompasses fitting aggregate and disaggregate parameters e.g. travel time and headway. The current practice in calibration is more at aggregate level, for example travel time comparison. Such practices are popular to assess network performance. Though these applications are significant there is another stream of micro-simulated calibration, at disaggregate level. This study will focus on such microcalibration exercise-key to better comprehend motorway traffic risk level, management of variable speed limit (VSL) and ramp metering (RM) techniques. Selected section of Pacific Motorway in Brisbane will be used as a case study. The discussion will primarily incorporate the critical issues encountered during parameter adjustment exercise (e.g. vehicular, driving behaviour) with reference to key traffic performance indicators like speed, lane distribution and headway; at specific motorway points. The endeavour is to highlight the utility and implications of such disaggregate level simulation for improved traffic prediction studies. The aspects of calibrating for points in comparison to that for whole of the network will also be briefly addressed to examine the critical issues such as the suitability of local calibration at global scale. The paper will be of interest to transport professionals in Australia/New Zealand where micro-simulation in particular at point level, is still comparatively a less explored territory in motorway management.

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Calibration process in micro-simulation is an extremely complicated phenomenon. The difficulties are more prevalent if the process encompasses fitting aggregate and disaggregate parameters e.g. travel time and headway. The current practice in calibration is more at aggregate level, for example travel time comparison. Such practices are popular to assess network performance. Though these applications are significant there is another stream of micro-simulated calibration, at disaggregate level. This study will focus on such micro-calibration exercise-key to better comprehend motorway traffic risk level, management of variable speed limit (VSL) and ramp metering (RM) techniques. Selected section of Pacific Motorway in Brisbane will be used as a case study. The discussion will primarily incorporate the critical issues encountered during parameter adjustment exercise (e.g. vehicular, driving behaviour) with reference to key traffic performance indicators like speed, land distribution and headway; at specific motorway points. The endeavour is to highlight the utility and implications of such disaggregate level simulation for improved traffic prediction studies. The aspects of calibrating for points in comparison to that for whole of the network will also be briefly addressed to examine the critical issues such as the suitability of local calibration at global scale. The paper will be of interest to transport professionals in Australia/New Zealand where micro-simulation in particular at point level, is still comparatively a less explored territory in motorway management.