973 resultados para Commerce Motor Car Company
Resumo:
Higher ambient temperatures will increase heat stress on workers, leading to impacts upon their individual health and productivity. In particular, research has indicated that higher ambient temperatures can increase the prevalence of urolithiasis. This thesis examines the relationship between ambient heat exposure and urolithiasis among outdoor workers in a shipbuilding company in Guangzhou, China, and makes recommendations for minimising the possible impacts of high ambient temperatures on urolithiasis. A retrospective 1:4 matched case-control study was performed to investigate the association between ambient heat exposure and urolithiasis. Ambient heat exposure was characterised by total exposure time, type of work, department and length of service. The data were obtained from the affiliated hospital of the shipbuilding company under study for the period 2003 to 2010. A conditional logistic regression model was used to estimate the association between heat exposure and urolithiasis. This study found that the odds ratio (OR) of urolithiasis for total exposure time was 1.5 (95% confidence interval (CI): 1.2–1.8). Eight types of work in the shipbuilding company were investigated, including welder, assembler, production security and quality inspector, planing machine operator, spray painter, gas-cutting worker and indoor employee. Five out of eight types of work had significantly higher risks for urolithiasis, and four of the five mainly consisted of outdoors work with ORs of 4.4 (95% CI: 1.7–11.4) for spray painter, 3.8 (95% CI: 1.9–7.2) for welder, 2.7 (95% CI: 1.4–5.0) for production security and quality inspector, and 2.2 (95% CI: 1.1–4.3) for assembler, compared to the reference group (indoor employee). Workers with abnormal blood pressure (hypertension) were more likely to have urolithiasis with an OR of 1.6 (95% CI: 1.0–2.5) compared to those without hypertension. This study contributes to the understanding of the association between ambient heat exposure and urolithiasis among outdoor workers in China. In the context of global climate change, this is particularly important because rising temperatures are expected to increase the prevalence of urolithiasis among outdoor workers, putting greater pressure on productivity, occupational health management and health care systems. The results of this study have clear implications for public health policy and planning, as they indicate that more attention is required to protect outdoor workers from heat-related urolithiasis.
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Motor unit number estimation (MUNE) is a method which aims to provide a quantitative indicator of progression of diseases that lead to loss of motor units, such as motor neurone disease. However the development of a reliable, repeatable and fast real-time MUNE method has proved elusive hitherto. Ridall et al. (2007) implement a reversible jump Markov chain Monte Carlo (RJMCMC) algorithm to produce a posterior distribution for the number of motor units using a Bayesian hierarchical model that takes into account biological information about motor unit activation. However we find that the approach can be unreliable for some datasets since it can suffer from poor cross-dimensional mixing. Here we focus on improved inference by marginalising over latent variables to create the likelihood. In particular we explore how this can improve the RJMCMC mixing and investigate alternative approaches that utilise the likelihood (e.g. DIC (Spiegelhalter et al., 2002)). For this model the marginalisation is over latent variables which, for a larger number of motor units, is an intractable summation over all combinations of a set of latent binary variables whose joint sample space increases exponentially with the number of motor units. We provide a tractable and accurate approximation for this quantity and also investigate simulation approaches incorporated into RJMCMC using results of Andrieu and Roberts (2009).
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Many international management programs have capitalised on the value design can have upon potential business solutions and strategies (Martin, 2009 & Brown, 2008) as well as many international design programs introducing designers to business theory and curriculum (Manzini & Rizzo, 2011). This paper presents the findings from structured interviews with undergraduate design students and design industry professionals. Current literature surrounding design led innovation and the role designers’ play within it is also discussed and the challenges facing designers in this emerging design era are presented. The findings from this study indicate that most designers enter an undergraduate program not wanting to become the business leaders of tomorrow. Instead, they enter in the hope they can humbly help people and to make a difference in the world. There are contentions with this perspective, felt by industry, academia and students around why designers need to be taught business theory content. This paper provides the first step to overcoming this challenge by providing insight into the attitudes, perceptions and challenges designers are facing with this new design era.
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Over the last five years we have observed the fallout from the global financial crisis (GFC). International cooperation and jointly adopted policies have dominated many of the solutions to the problems which have arisen. Initially, many nations in response to the GFC, implemented a two pronged short term solution by undertaking fiscal intervention and delivering rescue packages aimed at first, bailing out financial institutions and second, preventing or minimising the impact of a recession. Both programs involved large amounts of domestic spending. It was difficult in early 2007 to foresee the reduction that nations were about the face in domestic revenue collected. Five years on, not only have the first line effects of the GFC reduced the revenue raised by governments around the world, but the consequential costs associated with the rescue packages have also depleted domestic revenue bases. The response by stakeholders has been to attempt to secure domestic revenue bases through fiscally sustainable measures. Domestic sovereignty allows the levying of taxes as a nation chooses. However, rather than raise domestic taxes, revenue may also be increased by stemming the flow of income and capital to low and no-tax jurisdictions. The intervening five-year period since the GFC allows a unique insight into the response by nations and international organisations to tax evasion, tax avoidance and aggressive tax competition through the cross border flows of capital and the resulting affect that the GFC has had on international tax cooperation. By investigating the change in the international tax landscape over the last five years, which reveals the work done by stakeholders in developing fiscally responsible responses to the problems that have arisen, it may be possible to predict the trajectory of the international tax landscape over the next five years.
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Having a reliable understanding about the behaviours, problems, and performance of existing processes is important in enabling a targeted process improvement initiative. Recently, there has been an increase in the application of innovative process mining techniques to facilitate evidence-based understanding about organizations' business processes. Nevertheless, the application of these techniques in the domain of finance in Australia is, at best, scarce. This paper details a 6-month case study on the application of process mining in one of the largest insurance companies in Australia. In particular, the challenges encountered, the lessons learned, and the results obtained from this case study are detailed. Through this case study, we not only validated existing `lessons learned' from other similar case studies, but also added new insights that can be beneficial to other practitioners in applying process mining in their respective fields.
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Motorcycle trauma is a serious road safety issue in Queensland and throughout Australia. In 2009, Queensland Transport (later Transport and Main Roads or TMR) appointed CARRS-Q to provide a three-year program of Road Safety Research Services for Motorcycle Rider Safety. Funding for this research originated from the Motor Accident Insurance Commission. This program of research was undertaken to produce knowledge to assist TMR to improve motorcycle safety by further strengthening the licensing and training system to make learner riders safer by developing a pre-learner package (Deliverable 1 which is the focus of this report), and by evaluating the Q-Ride CAP program to ensure that it is maximally effective and contributes to the best possible training for new riders (Deliverable 2), which is the focus of this report. Deliverable 3 of the program identified potential new licensing components that will reduce the incidence of risky riding and improve higher-order cognitive skills in new riders. While fatality and injury rates for learner car drivers are typically lower than for those with intermediate licences, this pattern is not found for learner motorcycle riders. Learner riders cannot be supervised as effectively as learner car drivers and errors are more likely to result in injury for learner riders than learner drivers. It is therefore imperative to improve safety for learner riders. Deliverable 1 examines the potential for improving the motorcycle learner and licence scheme by introducing a pre-learner motorcycle licensing and training scheme within Queensland. The tasks undertaken for Deliverable 1 were a literature review, analysis of learner motorcyclist crash and licensing data, and the development of a potential pre-learner motorcycle rider program.
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Readily accepted knowledge regarding crash causation is consistently omitted from efforts to model and subsequently understand motor vehicle crash occurrence and their contributing factors. For instance, distracted and impaired driving accounts for a significant proportion of crash occurrence, yet is rarely modeled explicitly. In addition, spatially allocated influences such as local law enforcement efforts, proximity to bars and schools, and roadside chronic distractions (advertising, pedestrians, etc.) play a role in contributing to crash occurrence and yet are routinely absent from crash models. By and large, these well-established omitted effects are simply assumed to contribute to model error, with predominant focus on modeling the engineering and operational effects of transportation facilities (e.g. AADT, number of lanes, speed limits, width of lanes, etc.) The typical analytical approach—with a variety of statistical enhancements—has been to model crashes that occur at system locations as negative binomial (NB) distributed events that arise from a singular, underlying crash generating process. These models and their statistical kin dominate the literature; however, it is argued in this paper that these models fail to capture the underlying complexity of motor vehicle crash causes, and thus thwart deeper insights regarding crash causation and prevention. This paper first describes hypothetical scenarios that collectively illustrate why current models mislead highway safety researchers and engineers. It is argued that current model shortcomings are significant, and will lead to poor decision-making. Exploiting our current state of knowledge of crash causation, crash counts are postulated to arise from three processes: observed network features, unobserved spatial effects, and ‘apparent’ random influences that reflect largely behavioral influences of drivers. It is argued; furthermore, that these three processes in theory can be modeled separately to gain deeper insight into crash causes, and that the model represents a more realistic depiction of reality than the state of practice NB regression. An admittedly imperfect empirical model that mixes three independent crash occurrence processes is shown to outperform the classical NB model. The questioning of current modeling assumptions and implications of the latent mixture model to current practice are the most important contributions of this paper, with an initial but rather vulnerable attempt to model the latent mixtures as a secondary contribution.
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This study investigated the specificity of the post-concussion syndrome (PCS) expectation-as-etiology hypothesis. Undergraduate students (n = 551) were randomly allocated to one of three vignette conditions. Vignettes depicted either a very mild (VMI), mild (MI), or moderate-to-severe (MSI) motor vehicle-related traumatic brain injury (TBI). Participants reported the PCS and PTSD symptoms that they imagined the depicted injury would produce. Secondary outcomes (knowledge of mild TBI, and the perceived undesirability of TBI) were also assessed. After data screening, the distribution of participants by condition was: VMI (n = 100), MI (n = 96), and MSI (n = 71). There was a significant effect of condition on PCS symptomatology, F(2, 264) = 16.55, p < .001. Significantly greater PCS symptomatology was expected in the MSI condition compared to the other conditions (MSI > VMI; medium effect, r = .33; MSI > MI; small-to-medium effect, r = .22). The same pattern of group differences was found for PTSD symptoms, F(2, 264) = 17.12, p < .001. Knowledge of mild TBI was not related to differences in expected PCS symptoms by condition; and the perceived undesirability of TBI was only associated with reported PCS symptomatology in the MSI condition. Systematic variation in the severity of a depicted TBI produces different PCS and PTSD symptom expectations. Even a very mild TBI vignette can elicit expectations of PCS symptoms.
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We find a robust relationship between motor vehicle ownership, its interaction with legal heritage and obesity in OECD countries. Our estimates indicate that an increase of 100 motor vehicles per thousand residents is associated with about a 6% point increase in obesity in common law countries, whereas it has a much smaller or insignificant impact in civil law countries. These relations hold whether we examine trend data and simple correlations, or conduct cross-section or panel data regression analysis. Our results suggest that obesity rises with motor vehicle ownership in countries following a common law tradition where individual liberty is encouraged, whereas the link is small or statistically non-existent in countries with a civil law background where the rights of the individual tend to be circumscribed by the power of the state.
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Power system operation and planning are facing increasing uncertainties especially with the deregulation process and increasing demand for power. Probabilistic power system stability assessment and probabilistic power system planning have been identified by EPRI as one of the important trends in power system operations and planning. Probabilistic small signal stability assessment studies the impact of system parameter uncertainties on system small disturbance stability characteristics. Researches in this area have covered many uncertainties factors such as controller parameter uncertainties and generation uncertainties. One of the most important factors in power system stability assessment is load dynamics. In this paper, composite load model is used to consider the uncertainties from load parameter uncertainties impact on system small signal stability characteristics. The results provide useful insight into the significant stability impact brought to the system by load dynamics. They can be used to help system operators in system operation and planning analysis.
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Over the last two decades, the internet and e-commerce have reshaped the way we communicate, interact and transact. In the converged environment enabled by high speed broadband, web 2.0, social media, virtual worlds, user-generated content, cloud computing, VoIP, open source software and open content have rapidly become established features of our online experience. Business and government alike are increasingly using the internet as the preferred platform for delivery of their goods and services and for effective engagement with their clients. New ways of doing things online and challenges to existing business, government and social activities have tested current laws and often demand new policies and laws, adapted to the new realities. The focus of this book is the regulation of social, cultural and commercial activity on the World Wide Web. It considers developments in the law that have been, and continue to be, brought about by the emergence of the internet and e-commerce. It analyses how the law is applied to define rights and obligations in relation to online infrastructure, content and practices.
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As e-commerce is becoming more and more popular, the number of customer reviews that a product receives grows rapidly. In order to enhance customer satisfaction and their shopping experiences, it has become important to analysis customers reviews to extract opinions on the products that they buy. Thus, Opinion Mining is getting more important than before especially in doing analysis and forecasting about customers’ behavior for businesses purpose. The right decision in producing new products or services based on data about customers’ characteristics means profit for organization/company. This paper proposes a new architecture for Opinion Mining, which uses a multidimensional model to integrate customers’ characteristics and their comments about products (or services). The key step to achieve this objective is to transfer comments (opinions) to a fact table that includes several dimensions, such as, customers, products, time and locations. This research presents a comprehensive way to calculate customers’ orientation for all possible products’ attributes.
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• Car-bicycle and car-motorcycle crashes often serious • Car driver mostly at fault, often because of failure to see (Schramm et al, 2010) • Car drivers with motorcycling experience less likely to be involved in motorcycle crashes or be at fault (Brooks & Guppy, 1990; Magazzu et al., 2006) and hold more positive beliefs about motorcyclists (Crundall et al., 2008) • Does bicycle riding experience have the same benefits?
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Failure to give way by motor vehicles is a factor in many collisions with both powered and unpowered two wheelers (TWs). Motor vehicle drivers often report that they did not see the TW, but research has shown that motor vehicle drivers who have experience riding a motorcycle are less likely to fail to detect motorcycles. The research reported here examines whether this phenomenon extends to detection of bicycles and whether car drivers who have experience with one mode of TW show improved detection of the other mode. A driving simulator study was conducted in an Australian urban setting which incorporated some of the most common car-TW crash scenarios. Participants with car-only, car plus motorcycle, car plus bicycle, and car plus bicycle plus motorcycle experience operated a car simulator. Their interactions with both types of TWs were measured in terms of visual detection, lateral distance and speed when approaching and passing. The effects of different levels of colour and lighting of the TWs on driver responses were also examined. The attitudes of participants towards TWs were measured in a questionnaire.
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This paper investigates the social and environmental disclosure practices of two large multinational companies, specifically Nike and Hennes&Mauritz. Utilising a joint consideration of legitimacy theory and media agenda setting theory, we investigate the linkage between negative media attention, and positive corporate social and environmental disclosures. Our results generally support a view that for those industry‐related social and environmental issues attracting the greatest amount of negative media attention, these corporations react by providing positive social and environmental disclosures. The results were particularly significant in relation to labour practices in developing countries – the issue attracting the greatest amount of negative media attention for the companies in question.