913 resultados para risk-based modeling


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IEEE 802.16 standard specifies a contention based bandwidth request scheme for best-effort and non-real time polling services in Point-to-MultiPoint (PMP) architecture. In this letter we propose an analytical model for the scheme and study how the performances of bandwidth efficiency and channel access delay change with the contention window size, the number of contending subscriber stations, the number of slots allocated for bandwidth request and data transmission. Simulations validate its high accuracy. © 2007 IEEE.

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This paper is dedicated to modelling of network maintaining based on live example – maintaining ATM banking network, where any problems are mean money loss. A full analysis is made in order to estimate valuable and not-valuable parameters based on complex analysis of available data. Correlation analysis helps to estimate provided data and to produce a complex solution of increasing network maintaining effectiveness.

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Objectives: To develop a decision support system (DSS), myGRaCE, that integrates service user (SU) and practitioner expertise about mental health and associated risks of suicide, self-harm, harm to others, self-neglect, and vulnerability. The intention is to help SUs assess and manage their own mental health collaboratively with practitioners. Methods: An iterative process involving interviews, focus groups, and agile software development with 115 SUs, to elicit and implement myGRaCE requirements. Results: Findings highlight shared understanding of mental health risk between SUs and practitioners that can be integrated within a single model. However, important differences were revealed in SUs' preferred process of assessing risks and safety, which are reflected in the distinctive interface, navigation, tool functionality and language developed for myGRaCE. A challenge was how to provide flexible access without overwhelming and confusing users. Conclusion: The methods show that practitioner expertise can be reformulated in a format that simultaneously captures SU expertise, to provide a tool highly valued by SUs. A stepped process adds necessary structure to the assessment, each step with its own feedback and guidance. Practice Implications: The GRiST web-based DSS (www.egrist.org) links and integrates myGRaCE self-assessments with GRiST practitioner assessments for supporting collaborative and self-managed healthcare.

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Analysis of risk measures associated with price series data movements and its predictions are of strategic importance in the financial markets as well as to policy makers in particular for short- and longterm planning for setting up economic growth targets. For example, oilprice risk-management focuses primarily on when and how an organization can best prevent the costly exposure to price risk. Value-at-Risk (VaR) is the commonly practised instrument to measure risk and is evaluated by analysing the negative/positive tail of the probability distributions of the returns (profit or loss). In modelling applications, least-squares estimation (LSE)-based linear regression models are often employed for modeling and analyzing correlated data. These linear models are optimal and perform relatively well under conditions such as errors following normal or approximately normal distributions, being free of large size outliers and satisfying the Gauss-Markov assumptions. However, often in practical situations, the LSE-based linear regression models fail to provide optimal results, for instance, in non-Gaussian situations especially when the errors follow distributions with fat tails and error terms possess a finite variance. This is the situation in case of risk analysis which involves analyzing tail distributions. Thus, applications of the LSE-based regression models may be questioned for appropriateness and may have limited applicability. We have carried out the risk analysis of Iranian crude oil price data based on the Lp-norm regression models and have noted that the LSE-based models do not always perform the best. We discuss results from the L1, L2 and L∞-norm based linear regression models. ACM Computing Classification System (1998): B.1.2, F.1.3, F.2.3, G.3, J.2.

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In the years 2004 and 2005, we collected samples of phytoplankton, zooplankton, and macroinvertebrates in an artificial small pond in Budapest (Hungary). We set up a simulation model predicting the abundances of the cyclopoids, Eudiaptomus zachariasi, and Ischnura pumilio by considering only temperature and the abundance of population of the previous day. Phytoplankton abundance was simulated by considering not only temperature but the abundances of the three mentioned groups. When we ran the model with the data series of internationally accepted climate change scenarios, the different outcomes were discussed. Comparative assessment of the alternative climate change scenarios was also carried out with statistical methods.

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In this paper, I analyze the role of longevity risk in Hungary in the public pension system and the life annuity segment of the life insurance market, which are two primary financial sectors of relevance to this special type of actuarial risk, using state-of-the- art econometric methodology. To this end, I present an overview and the mathematical background of several important current mortality forecasting techniques from the Lee–Carter model up to unifying paradigm of the Age–Period–Cohort family of models. After presenting the findings of a case study on the public pension system based on the paper of Bajk ́o, Maknics, T ́oth and V ́ekas, I conclude that longevity risk jeopardizes the sustainability of the Hungarian public pension system in the long run. In another case study, I present an analysis of the role of longevity risk in the pre- mium of private pension annuities, a relevant topic due to recent changes in a law on Hungarian voluntary pension funds, following an earlier analysis of M ́ajer and Kov ́acs. Based on the criterion on out-of-sample forecasting accuracy, I find that the Cairns–Blake– Dowd mortality forecasting model aimed specifically at modeling old-age mortality outperforms the Lee–Carter model applied by M ́ajer and Kov ́acs . Based on numerical results, I finally conclude that the role of longevity risk in the Hungarian life annuity mar- ket has increased significantly in the past decade and is likely to further increase in the future.

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Pesticide monitoring in St. Lucie County by various local, state and federal agencies has indicated consistent residues of several pesticides, including ethion and bromacil. Although pesticides have long been known to pose a threat to non-target species and much background monitoring has been done, no pesticide aquatic risk assessment has been done in this geographical area. Several recognized United States Environmental Protection Agency (USEPA) methods of quantifying risk are employed here to include hazard quotients (HQ) and probabilistic modeling with sensitivity analysis. These methods are employed to characterize potential impacts to aquatic biota of the C-25 Canal and the Indian River Lagoon (in St. Lucie County, Florida) based on current agricultural pesticide use and drainage patterns. The model used in the analysis incorporates available physical-chemical property data, local hydrology, ecosystem information, and pesticide use practices. HQ's, probabilistic distributions, and field sample analyses resulted in high levels of concern (LOCs), which usually indicates a need for regulatory action, including restrictions on use, or cancellation. ^

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Choosing between Light Rail Transit (LRT) and Bus Rapid Transit (BRT) systems is often controversial and not an easy task for transportation planners who are contemplating the upgrade of their public transportation services. These two transit systems provide comparable services for medium-sized cities from the suburban neighborhood to the Central Business District (CBD) and utilize similar right-of-way (ROW) categories. The research is aimed at developing a method to assist transportation planners and decision makers in determining the most feasible system between LRT and BRT. ^ Cost estimation is a major factor when evaluating a transit system. Typically, LRT is more expensive to build and implement than BRT, but has significantly lower Operating and Maintenance (OM) costs than BRT. This dissertation examines the factors impacting capacity and costs, and develops cost models, which are a capacity-based cost estimate for the LRT and BRT systems. Various ROW categories and alignment configurations of the systems are also considered in the developed cost models. Kikuchi's fleet size model (1985) and cost allocation method are used to develop the cost models to estimate the capacity and costs. ^ The comparison between LRT and BRT are complicated due to many possible transportation planning and operation scenarios. In the end, a user-friendly computer interface integrated with the established capacity-based cost models, the LRT and BRT Cost Estimator (LBCostor), was developed by using Microsoft Visual Basic language to facilitate the process and will guide the users throughout the comparison operations. The cost models and the LBCostor can be used to analyze transit volumes, alignments, ROW configurations, number of stops and stations, headway, size of vehicle, and traffic signal timing at the intersections. The planners can make the necessary changes and adjustments depending on their operating practices. ^

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Purpose. The goal of this study is to improve the favorable molecular interactions between starch and PPC by addition of grafting monomers MA and ROM as compatibilizers, which would advance the mechanical properties of starch/PPC composites. ^ Methodology. DFT and semi-empirical methods based calculations were performed on three systems: (a) starch/PPC, (b) starch/PPC-MA, and (c) starch-ROM/PPC. Theoretical computations involved the determination of optimal geometries, binding-energies and vibrational frequencies of the blended polymers. ^ Findings. Calculations performed on five starch/PPC composites revealed hydrogen bond formation as the driving force behind stable composite formation, also confirmed by the negative relative energies of the composites indicating the existence of binding forces between the constituent co-polymers. The interaction between starch and PPC is also confirmed by the computed decrease in stretching CO and OH group frequencies participating in hydrogen bond formation, which agree qualitatively with the experimental values. ^ A three-step mechanism of grafting MA on PPC was proposed to improve the compatibility of PPC with starch. Nine types of 'blends' produced by covalent bond formation between starch and MA-grafted PPC were found to be energetically stable, with blends involving MA grafted at the 'B' and 'C' positions of PPC indicating a binding-energy increase of 6.8 and 6.2 kcal/mol, respectively, as compared to the non-grafted starch/PPC composites. A similar increase in binding-energies was also observed for three types of 'composites' formed by hydrogen bond formation between starch and MA-grafted PPC. ^ Next, grafting of ROM on starch and subsequent blend formation with PPC was studied. All four types of blends formed by the reaction of ROM-grafted starch with PPC were found to be more energetically stable as compared to the starch/PPC composite and starch/PPC-MA composites and blends. A blend of PPC and ROM grafted at the ' a&d12; ' position on amylose exhibited a maximal increase of 17.1 kcal/mol as compared with the starch/PPC-MA blend. ^ Conclusions. ROM was found to be a more effective compatibilizer in improving the favorable interactions between starch and PPC as compared to MA. The ' a&d12; ' position was found to be the most favorable attachment point of ROM to amylose for stable blend formation with PPC.^

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Performance-based maintenance contracts differ significantly from material and method-based contracts that have been traditionally used to maintain roads. Road agencies around the world have moved towards a performance-based contract approach because it offers several advantages like cost saving, better budgeting certainty, better customer satisfaction with better road services and conditions. Payments for the maintenance of road are explicitly linked to the contractor successfully meeting certain clearly defined minimum performance indicators in these contracts. Quantitative evaluation of the cost of performance-based contracts has several difficulties due to the complexity of the pavement deterioration process. Based on a probabilistic analysis of failures of achieving multiple performance criteria over the length of the contract period, an effort has been made to develop a model that is capable of estimating the cost of these performance-based contracts. One of the essential functions of such model is to predict performance of the pavement as accurately as possible. Prediction of future degradation of pavement is done using Markov Chain Process, which requires estimating transition probabilities from previous deterioration rate for similar pavements. Transition probabilities were derived using historical pavement condition rating data, both for predicting pavement deterioration when there is no maintenance, and for predicting pavement improvement when maintenance activities are performed. A methodological framework has been developed to estimate the cost of maintaining road based on multiple performance criteria such as crack, rut and, roughness. The application of the developed model has been demonstrated via a real case study of Miami Dade Expressways (MDX) using pavement condition rating data from Florida Department of Transportation (FDOT) for a typical performance-based asphalt pavement maintenance contract. Results indicated that the pavement performance model developed could predict the pavement deterioration quite accurately. Sensitivity analysis performed shows that the model is very responsive to even slight changes in pavement deterioration rate and performance constraints. It is expected that the use of this model will assist the highway agencies and contractors in arriving at a fair contract value for executing long term performance-based pavement maintenance works.

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Breast cancer is the second leading cause of cancer death in United States women, estimated to be diagnosed in 1 out of 8 women in their lifetime. Screening mammography detects breast cancer in its pre-clinical stages when treatment strategies have the greatest chance of success, and is currently the only population-wide prevention method proven to reduce the morbidity and mortality associated with breast cancer. Research has shown that the majority of women are not screened annually, with estimates ranging front 6% - 30% of eligible women receiving all available annual mammograms over a 5-year or greater time frame. Health behavior theorists believe that perception of risk/susceptibility to a disease influences preventive health behavior, in this case, screening mammography The purpose of this dissertation is to examine the association between breast cancer risk perception and repeat screening mammography using a structural equation modeling (SEM) framework. A series of SEM multivariate regressions were conducted using self-reported, nationally representative data from the 2005 National Health Interview Survey. Interaction contrasts were tested to measure the potential moderating effects of variables which have been shown to be predictive of mammography use (physician recommendation, economic barriers, structural barriers, race/ethnicity) on the association between breast cancer risk perception and repeat mammography, while controlling for the covariates of age, income, region, nativity, and educational level. Of the variables tested for moderation, results of the SEM analyses identify physician recommendation as the only moderator of the relationship between risk perception and repeat mammography, thus the potentially most effective point of intervention to increase mammography screening, and decrease the morbidity and mortality associated with breast cancer. These findings expand the role of the physician from recommendation to one of attenuating the effect of risk perception and increasing repeat screening. The long range application of the research is the use of the SEM methodology to identify specific points of intervention most likely to increase preventive behavior in population-wide research, allowing for the most effective use of intervention funds.^

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Adolescence is a pivotal period offering both opportunities and constraints on individual development. It is during this important time that one decides upon and commits to the values, goals, and beliefs which will form one's identity and guide one throughout the lifespan. Positive youth development programs, such as the Miami Youth Development Project's Changing Lives Program, target the formation of a positive sense of identity as a critical intervention point. Through developing a coherent and positive sense of self, adolescents take control of and responsibility for their lives and their decisions. Furthermore, a positive identity has been found to be a developmental asset and is linked to lower risk behaviors and positive outcomes including increased self-esteem, sense of purpose, and a positive view of the future. Positive youth development programs, which promote positive identity development, have been found to be more strongly tied to positive outcomes including skills, values, and competencies than have contextual opportunities. As such, it is critical to determine what leads to positive identity development. ^ The current study used structural equation modeling to evaluate three potential mediators of identity development. Findings indicated good model fit where change in identity commitment and change in identity exploration were mediated by informational identity style, personal expressiveness, and identity distress. There were also significant differences found between the control and intervention groups indicative of intervention effects. The findings of the current study suggest potential areas of intervention as well as the need for further research including longitudinal study and the use of qualitative methodology. ^

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Conceptual database design is an unusually difficult and error-prone task for novice designers. This study examined how two training approaches---rule-based and pattern-based---might improve performance on database design tasks. A rule-based approach prescribes a sequence of rules for modeling conceptual constructs, and the action to be taken at various stages while developing a conceptual model. A pattern-based approach presents data modeling structures that occur frequently in practice, and prescribes guidelines on how to recognize and use these structures. This study describes the conceptual framework, experimental design, and results of a laboratory experiment that employed novice designers to compare the effectiveness of the two training approaches (between-subjects) at three levels of task complexity (within subjects). Results indicate an interaction effect between treatment and task complexity. The rule-based approach was significantly better in the low-complexity and the high-complexity cases; there was no statistical difference in the medium-complexity case. Designer performance fell significantly as complexity increased. Overall, though the rule-based approach was not significantly superior to the pattern-based approach in all instances, it out-performed the pattern-based approach at two out of three complexity levels. The primary contributions of the study are (1) the operationalization of the complexity construct to a degree not addressed in previous studies; (2) the development of a pattern-based instructional approach to database design; and (3) the finding that the effectiveness of a particular training approach may depend on the complexity of the task.

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Context The internet is gaining popularity as a means of delivering employee-based cardiovascular (CV) wellness interventions though little is known about the cardiovascular health outcomes of these programs. In this review, we examined the effectiveness of internet-based employee cardiovascular wellness and prevention programs. Evidence Acquisition We conducted a systematic review by searching PubMed, Web of Science and Cochrane library for all published studies on internet-based programs aimed at improving CV health among employees up to November 2012. We grouped the outcomes according to the American Heart Association (AHA) indicators of cardiovascular wellbeing – weight, BP, lipids, smoking, physical activity, diet, and blood glucose. Evidence Synthesis A total of 18 randomized trials and 11 follow-up studies met our inclusion/exclusion criteria. Follow-up duration ranged from 6 – 24 months. There were significant differences in intervention types and number of components in each intervention. Modest improvements were observed in more than half of the studies with weight related outcomes while no improvement was seen in virtually all the studies with physical activity outcome. In general, internet-based programs were more successful if the interventions also included some physical contact and environmental modification, and if they were targeted at specific disease entities such as hypertension. Only a few of the studies were conducted in persons at-risk for CVD, none in blue-collar workers or low-income earners. Conclusion Internet based programs hold promise for improving the cardiovascular wellness among employees however much work is required to fully understand its utility and long term impact especially in special/at-risk populations.