820 resultados para Risk assessment Mathematical models


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Some polycyclic aromatic hydrocarbons (PAHs) are ubiquitous in air and have been implicated as carcinogenic materials. Therefore, literature is replete with studies that are focused on their occurrence and profiles in indoor and outdoor air samples. However, because the relative potency of individual PAHs vary widely, health risks associated with the presence of PAHs in a particular environment cannot be extrapolated directly from the concentrations of individual PAHs in that environment. In addition, database on the potency of PAH mixtures is currently limited. In this paper, we have utilized multi-criteria decision making methods (MCDMs) to simultaneously correlate PAH-related health risk in some microenvironments to the concentration levels, ethoxyresorufin-O-deethylase (EROD) activity induction equivalency factors and toxic equivalency factors (TEFs) of PAHs found in those microenvironments. The results showed that the relative risk associated with PAHs in different air samples depends on the index used. Nevertheless, this approach offers a promising tool that could help identify microenvironments of concern and assist the prioritisation of control strategies.

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The historical challenge of environmental impact assessment (EIA) has been to predict project-based impacts accurately. Both EIA legislation and the practice of EIA have evolved over the last three decades in Canada, and the development of the discipline and science of environmental assessment has improved how we apply environmental assessment to complex projects. The practice of environmental assessment integrates the social and natural sciences and relies on an eclectic knowledge base from a wide range of sources. EIA methods and tools provide a means to structure and integrate knowledge in order to evaluate and predict environmental impacts.----- This Chapter will provide a brief overview of how impacts are identified and predicted. How do we determine what aspect of the natural and social environment will be affected when a mine is excavated? How does the practitioner determine the range of potential impacts, assess whether they are significant, and predict the consequences? There are no standard answers to these questions, but there are established methods to provide a foundation for scoping and predicting the potential impacts of a project.----- Of course, the community and publics play an important role in this process, and this will be discussed in subsequent chapters. In the first part of this chapter, we will deal with impact identification, which involves appplying scoping to critical issues and determining impact significance, baseline ecosystem evaluation techniques, and how to communicate environmental impacts. In the second part of the chapter, we discuss the prediction of impacts in relation to the complexity of the environment, ecological risk assessment, and modelling.

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Previous work by Professor John Frazer on Evolutionary Architecture provides a basis for the development of a system evolving architectural envelopes in a generic and abstract manner. Recent research by the authors has focused on the implementation of a virtual environment for the automatic generation and exploration of complex forms and architectural envelopes based on solid modelling techniques and the integration of evolutionary algorithms, enhanced computational and mathematical models. Abstract data types are introduced for genotypes in a genetic algorithm order to develop complex models using generative and evolutionary computing techniques. Multi-objective optimisation techniques are employed for defining the fitness function in the evaluation process.

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Risks and uncertainties are inevitable in engineering projects and infrastructure investments. Decisions about investment in infrastructure such as for maintenance, rehabilitation and construction works can pose risks, and may generate significant impacts on social, cultural, environmental and other related issues. This report presents the results of a literature review of current practice in identifying, quantifying and managing risks and predicting impacts as part of the planning and assessment process for infrastructure investment proposals. In assessing proposals for investment in infrastructure, it is necessary to consider social, cultural and environmental risks and impacts to the overall community, as well as financial risks to the investor. The report defines and explains the concept of risk and uncertainty, and describes the three main methodology approaches to the analysis of risk and uncertainty in investment planning for infrastructure, viz examining a range of scenarios or options, sensitivity analysis, and a statistical probability approach, listed here in order of increasing merit and complexity. Forecasts of costs, benefits and community impacts of infrastructure are recognised as central aspects of developing and assessing investment proposals. Increasingly complex modelling techniques are being used for investment evaluation. The literature review identified forecasting errors as the major cause of risk. The report contains a summary of the broad nature of decision-making tools used by governments and other organisations in Australia, New Zealand, Europe and North America, and shows their overall approach to risk assessment in assessing public infrastructure proposals. While there are established techniques to quantify financial and economic risks, quantification is far less developed for political, social and environmental risks and impacts. The report contains a summary of the broad nature of decision-making tools used by governments and other organisations in Australia, New Zealand, Europe and North America, and shows their overall approach to risk assessment in assessing public infrastructure proposals. While there are established techniques to quantify financial and economic risks, quantification is far less developed for political, social and environmental risks and impacts. For risks that cannot be readily quantified, assessment techniques commonly include classification or rating systems for likelihood and consequence. The report outlines the system used by the Australian Defence Organisation and in the Australian Standard on risk management. After each risk is identified and quantified or rated, consideration can be given to reducing the risk, and managing any remaining risk as part of the scope of the project. The literature review identified use of risk mapping techniques by a North American chemical company and by the Australian Defence Organisation. This literature review has enabled a risk assessment strategy to be developed, and will underpin an examination of the feasibility of developing a risk assessment capability using a probability approach.

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In sport and exercise biomechanics, forward dynamics analyses or simulations have frequently been used in attempts to establish optimal techniques for performance of a wide range of motor activities. However, the accuracy and validity of these simulations is largely dependent on the complexity of the mathematical model used to represent the neuromusculoskeletal system. It could be argued that complex mathematical models are superior to simple mathematical models as they enable basic mechanical insights to be made and individual-specific optimal movement solutions to be identified. Contrary to some claims in the literature, however, we suggest that it is currently not possible to identify the complete optimal solution for a given motor activity. For a complete optimization of human motion, dynamical systems theory implies that mathematical models must incorporate a much wider range of organismic, environmental and task constraints. These ideas encapsulate why sports medicine specialists need to adopt more individualized clinical assessment procedures in interpreting why performers' movement patterns may differ.

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A shortage of affordable housing is a major problem in Australia today. This is mainly due to the limited supply of affordable housing that is provided by the non-government housing sector. Some private housing developers see the provision of affordable housing for lower income people as a high risk investment which offers a lower return than broader market-based housing. The scarcity of suitable land, a limited government ‘subsidy’, and increasing housing costs have not provided sufficient development incentives to encourage their investment despite the existing high demand for affordable housing. This study analyses the risk management process conducted by some private and not-for-profit housing providers in South East Queensland, and draws conclusions about the relationship between risk assessments/responses and past experiences. In-depth interviews of selected non-government housing providers have been conducted to facilitate an understanding of their approach to risk assessment/response in developing and in managing affordable housing projects. These developers use an informal risk management process as part of their normal business process in accordance with industry standards. A simple qualitative matrix has been used to analyse probability and impacts using a qualitative scale - low, medium and high. For housing providers who have considered investing in affordable housing but have not yet implemented any such projects, affordable housing development is seen as an opportunity that needs to be approached with caution. The risks associated with such projects and the levels of acceptance of these are not consistently identified by current housing providers. Many interviewees agree that the recognition of financial risk and the fear of community rejection of such housing projects have restrained them from committing to such investment projects. This study suggests that implementing improvements to the risk mitigation and management framework may assist in promoting the supply of affordable housing by non-government providers.

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Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Appropriate mathematical models that are capable of estimating times to failures and the probability of failures in the future are essential in EAM. In most real-life situations, the lifetime of an engineering asset is influenced and/or indicated by different factors that are termed as covariates. Hazard prediction with covariates is an elemental notion in the reliability theory to estimate the tendency of an engineering asset failing instantaneously beyond the current time assumed that it has already survived up to the current time. A number of statistical covariate-based hazard models have been developed. However, none of them has explicitly incorporated both external and internal covariates into one model. This paper introduces a novel covariate-based hazard model to address this concern. This model is named as Explicit Hazard Model (EHM). Both the semi-parametric and non-parametric forms of this model are presented in the paper. The major purpose of this paper is to illustrate the theoretical development of EHM. Due to page limitation, a case study with the reliability field data is presented in the applications part of this study.

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Purpose: The purpose of this paper is to analyse the risk management process conducted by some private and not-for-profit affordable housing providers in South East Queensland, and draw conclusions about the relationship between risk assessments/responses and past experiences.----- Design/methodology/approach: In-depth interviews of selected non-government housing providers have been conducted to facilitate an understanding of their approach to risk assessment in developing and in managing affordable housing projects. Qualitative data are analysed using thematic analysis to find emerging themes suggested by interview participants.----- Findings: The paper finds that informal risk management process is used as part of normal business process in accordance with industry standards. Many interviewees agree that the recognition of financial risk and the fear of community rejection of such housing projects have restrained them from committing to such investment projects. The levels of acceptance of risk are not always consistent across housing providers which create opportunities to conduct multi-stakeholder partnership to reduce overall risk.----- Research limitations/implications: The paper has implications for developers or investors who seek to include affordable housing as part of their portfolio. However, data collected in the study are a cross-section of interviews that will not include the impact on recent tax incentives offers by the Australian Commonwealth Government.----- Practical implications: The study suggests that implementing improvements to the risk mitigation and management framework may assist in promoting the supply of affordable housing by non-government providers.----- Originality/value: The focus of the study is the interaction between partnerships and risk management in development and management of affordable rental housing.

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Quantitative Microbial Risk Assessment (QMRA) analysis was used to quantify the risk of infection associated with the exposure to pathogens from potable and non-potable uses of roof-harvested rainwater in South East Queensland (SEQ). A total of 84 rainwater samples were analysed for the presence of faecal indicators (using culture based methods) and zoonotic bacterial and protozoan pathogens using binary and quantitative PCR (qPCR). The concentrations of Salmonella invA, and Giardia lamblia β-giradin genes ranged from 65-380 genomic units/1000 mL and 9-57 genomic units/1000 mL of water, respectively. After converting gene copies to cell/cyst number, the risk of infection from G. lamblia and Salmonella spp. associated with the use of rainwater for bi-weekly garden hosing was calculated to be below the threshold value of 1 extra infection per 10,000 persons per year. However, the estimated risk of infection from drinking the rainwater daily was 44-250 (for G. lamblia) and 85-520 (for Salmonella spp.) infections per 10,000 persons per year. Since this health risk seems higher than that expected from the reported incidences of gastroenteritis, the assumptions used to estimate these infection risks are critically discussed. Nevertheless, it would seem prudent to disinfect rainwater for potable use.

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Purpose: To investigate the impact of glaucomatous visual impairment on postural sway and falls among older adults.Methods: The sample comprised 72 community-dwelling older adults with open-angle glaucoma, aged 74.0 5.8 years (range 62 to 90 years). Measures of visual function included binocular visual acuity (high-contrast), binocular contrast sensitivity (Pelli- Robson) and binocular visual fields (merged monocular HFA 24-2 SITA-Std). Postural stability was assessed under four conditions: eyes open and closed, on a firm and on a foam surface. Falls were monitored for six months with prospective falls diaries. Regression models, adjusting for age and gender, examined the association between vision measures and postural stability (linear regression) and the number of falls (negative binomial regression). Results: Greater visual field loss was significantly associated with poorer postural stability with eyes open, both on firm (r = 0.34, p < 0.01) and foam (r = 0.45, p < 0.001) surfaces. Eighteen (25 per cent) participants experienced at least one fall: 12 (17 per cent) participants fell only once and six (eight per cent) participants fell two or more times (up to five falls). Visual field loss was significantly associated with falling; the rate of falls doubled for every 10 dB reduction in field sensitivity (rate ratio = 1.08, 95% CI = 1.02–1.13). Importantly, in a model comprising upper and lower field sensitivity, only lower field loss was significantly associated with the number of falls (rate ratio = 1.17, 95% CI = 1.04–1.33). Conclusions: Binocular visual field loss was significantly associated with postural instability and falls among older adults with glaucoma. These findings provide valuable directions for developing falls risk assessment and falls prevention strategies for this population.

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Road curves are an important feature of road infrastructure and many serious crashes occur on road curves. In Queensland, the number of fatalities is twice as many on curves as that on straight roads. Therefore, there is a need to reduce drivers’ exposure to crash risk on road curves. Road crashes in Australia and in the Organisation for Economic Co-operation and Development(OECD) have plateaued in the last five years (2004 to 2008) and the road safety community is desperately seeking innovative interventions to reduce the number of crashes. However, designing an innovative and effective intervention may prove to be difficult as it relies on providing theoretical foundation, coherence, understanding, and structure to both the design and validation of the efficiency of the new intervention. Researchers from multiple disciplines have developed various models to determine the contributing factors for crashes on road curves with a view towards reducing the crash rate. However, most of the existing methods are based on statistical analysis of contributing factors described in government crash reports. In order to further explore the contributing factors related to crashes on road curves, this thesis designs a novel method to analyse and validate these contributing factors. The use of crash claim reports from an insurance company is proposed for analysis using data mining techniques. To the best of our knowledge, this is the first attempt to use data mining techniques to analyse crashes on road curves. Text mining technique is employed as the reports consist of thousands of textual descriptions and hence, text mining is able to identify the contributing factors. Besides identifying the contributing factors, limited studies to date have investigated the relationships between these factors, especially for crashes on road curves. Thus, this study proposed the use of the rough set analysis technique to determine these relationships. The results from this analysis are used to assess the effect of these contributing factors on crash severity. The findings obtained through the use of data mining techniques presented in this thesis, have been found to be consistent with existing identified contributing factors. Furthermore, this thesis has identified new contributing factors towards crashes and the relationships between them. A significant pattern related with crash severity is the time of the day where severe road crashes occur more frequently in the evening or night time. Tree collision is another common pattern where crashes that occur in the morning and involves hitting a tree are likely to have a higher crash severity. Another factor that influences crash severity is the age of the driver. Most age groups face a high crash severity except for drivers between 60 and 100 years old, who have the lowest crash severity. The significant relationship identified between contributing factors consists of the time of the crash, the manufactured year of the vehicle, the age of the driver and hitting a tree. Having identified new contributing factors and relationships, a validation process is carried out using a traffic simulator in order to determine their accuracy. The validation process indicates that the results are accurate. This demonstrates that data mining techniques are a powerful tool in road safety research, and can be usefully applied within the Intelligent Transport System (ITS) domain. The research presented in this thesis provides an insight into the complexity of crashes on road curves. The findings of this research have important implications for both practitioners and academics. For road safety practitioners, the results from this research illustrate practical benefits for the design of interventions for road curves that will potentially help in decreasing related injuries and fatalities. For academics, this research opens up a new research methodology to assess crash severity, related to road crashes on curves.

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Three particular geometrical shapes of parallelepiped, cylindrical and spheres were selected from potatoes (aspect ratio = 1:1, 2:1, 3:1), cut beans (length:diameter = 1:1, 2:1, 3:1) and peas respectively. The density variation of food particulates was studied in a batch fluidised bed dryer connected to a heat pump dehumidifier system. Apparent density and bulk density were evaluated with non-dimensional moisture at three different drying temperatures of 30, 40 and 50 o C. Relative humidity of hot air was kept at 15% in all drying temperatures. Several empirical relationships were developed for the determination of changes in densities with the moisture content. Simple mathematical models were obtained to relate apparent density and bulk density with moisture content.