344 resultados para Michigan Motor Car Manufacturing Company


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Traffic safety studies demand more than what current micro-simulation models can provide as they presume that all drivers exhibit safe behaviors. All the microscopic traffic simulation models include a car following model. This paper highlights the limitations of the Gipps car following model ability to emulate driver behavior for safety study purposes. A safety adapted car following model based on the Gipps car following model is proposed to simulate unsafe vehicle movements, with safety indicators below critical thresholds. The modifications are based on the observations of driver behavior in real data and also psychophysical notions. NGSIM vehicle trajectory data is used to evaluate the new model and short following headways and Time To Collision are employed to assess critical safety events within traffic flow. Risky events are extracted from available NGSIM data to evaluate the modified model against them. The results from simulation tests illustrate that the proposed model can predict the safety metrics better than the generic Gipps model. The outcome of this paper can potentially facilitate assessing and predicting traffic safety using microscopic simulation.

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Digital information that is place- and time-specific, is increasingly becoming available on all aspects of the urban landscape. People (cf. the Social Web), places (cf. the Geo Web), and physical objects (cf. ubiquitous computing, the Internet of Things) are increasingly infused with sensors, actuators, and tagged with a wealth of digital information. Urban informatics research explores these emerging digital layers of the city at the intersection of people, place and technology. However, little is known about the challenges and new opportunities that these digital layers may offer to road users driving through today’s mega cities. We argue that this aspect is worth exploring in particular with regards to Auto-UI’s overarching goal of making cars both safer and more enjoyable. This paper presents the findings of a pilot study, which included 14 urban informatics research experts participating in a guided ideation (idea creation) workshop within a simulated environment. They were immersed into different driving scenarios to imagine novel urban informatics type of applications specific to the driving context.

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Like other major cities, Brisbane (Australia) has adopted policies to increase residential densities to meet the liveability goal of decreasing car dependence. This objective hinges on urban neighbourhoods being amenity-rich spaces, reducing the need for residents to leave their neighbourhood for everyday living. While older people are attracted to urban settings, there has been little empirical evidence linking liveability satisfaction with older people's use of urban neighbourhoods. Using a case study approach employing qualitative (diaries, in-depth interviews) and quantitative (Global Positioning Systems and Geographical Information Systems mapping) methods,this paper explores the effect of the neighbourhood environment and its influence on liveability for older urban people. Reliance on motor vehicles and issues with availability and access to local amenities inhibit local participation for older people. Highlighting these issues furthers our understanding of the landscape planning and design factors that make urban neighbourhoods more liveable for older residents.

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Objective: To assess the relationship between Bayesian MUNE and histological motor neuron counts in wild-type mice and in an animal model of ALS. Methods: We performed Bayesian MUNE paired with histological counts of motor neurons in the lumbar spinal cord of wild-type mice and transgenic SOD1 G93A mice that show progressive weakness over time. We evaluated the number of acetylcholine endplates that were innervated by a presynaptic nerve. Results: In wild-type mice, the motor unit number in the gastrocnemius muscle estimated by Bayesian MUNE was approximately half the number of motor neurons in the region of the spinal cord that contains the cell bodies of the motor neurons supplying the hindlimb crural flexor muscles. In SOD1 G93A mice, motor neuron numbers declined over time. This was associated with motor endplate denervation at the end-stage of disease. Conclusion: The number of motor neurons in the spinal cord of wild-type mice is proportional to the number of motor units estimated by Bayesian MUNE. In SOD1 G93A mice, there is a lower number of estimated motor units compared to the number of spinal cord motor neurons at the end-stage of disease, and this is associated with disruption of the neuromuscular junction. Significance: Our finding that the Bayesian MUNE method gives estimates of motor unit numbers that are proportional to the numbers of motor neurons in the spinal cord supports the clinical use of Bayesian MUNE in monitoring motor unit loss in ALS patients. © 2012 International Federation of Clinical Neurophysiology.

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Objective: To use our Bayesian method of motor unit number estimation (MUNE) to evaluate lower motor neuron degeneration in ALS. Methods: In subjects with ALS we performed serial MUNE studies. We examined the repeatability of the test and then determined whether the loss of MUs was fitted by an exponential or Weibull distribution. Results: The decline in motor unit (MU) numbers was well-fitted by an exponential decay curve. We calculated the half life of MUs in the abductor digiti minimi (ADM), abductor pollicis brevis (APB) and/or extensor digitorum brevis (EDB) muscles. The mean half life of the MUs of ADM muscle was greater than those of the APB or EDB muscles. The half-life of MUs was less in the ADM muscle of subjects with upper limb than in those with lower limb onset. Conclusions: The rate of loss of lower motor neurons in ALS is exponential, the motor units of the APB decay more quickly than those of the ADM muscle and the rate of loss of motor units is greater at the site of onset of disease. Significance: This shows that the Bayesian MUNE method is useful in following the course and exploring the clinical features of ALS. 2012 International Federation of Clinical Neurophysiology.

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The following paper presents insights found during an ongoing industry engagement with a family-owned manufacturing SME in Australia. The initial findings presented as a case study look at the opportunities available to the firm engaging in a design led approach to innovation. Over the period of one year, the first author’s immersion within the firm seeks to unpack the cultural, strategic, product opportunities and challenges when adopting design led innovation. This can provide a better understanding of how a firm can more effectively assess their value proposition in the market and what factors of the business are imperative in stimulating competitive difference. The core insight identified from this paper is that design led innovation cannot be seen and treated as a discrete event, nor a series of steps or stages; rather the whole business model needs to be in focus to achieve holistic, sustainable innovation. Initial insights were found through qualitative interviews with internal employees including: overcoming silos; moving from reactive to proactive design; empowerment; vision for growth and the framing of innovation.

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Traffic safety studies mandate more than what existing micro-simulation models can offer as they postulate that every driver exhibits a safe behaviour. All the microscopic traffic simulation models are consisting of a car-following model and the Gazis–Herman–Rothery (GHR) car-following model is a widely used model. This paper highlights the limitations of the GHR car-following model capability to model longitudinal driving behaviour for safety study purposes. This study reviews and compares different version of the GHR model. To empower the GHR model on precise metrics reproduction a new set of car-following model parameters is offered to simulate unsafe vehicle conflicts. NGSIM vehicle trajectory data is used to evaluate the new model and short following headways and Time to Collision are employed to assess critical safety events within traffic flow. Risky events are extracted from available NGSIM data to evaluate the modified model against the generic versions of the GHR model. The results from simulation tests illustrate that the proposed model does predict the safety metrics better than the generic GHR model. Additionally it can potentially facilitate assessing and predicting traffic facilities’ safety using microscopic simulation. The new model can predict Near-miss rear-end crashes.

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The automotive industry has been the focus of digital human modeling (DHM) research and application for many years. In the highly competitive marketplace for personal transportation, the desire to improve the customer’s experience has driven extensive research in both the physical and cognitive interaction between the vehicle and its occupants. Human models provide vehicle designers with tools to view and analyze product interactions before the first prototypes are built, potentially improving the design while reducing cost and development time. The focus of DHM research and applications began with prediction and representation of static postures for purposes of driver workstation layout, including assessments of seat adjustment ranges and exterior vision. Now DHMs are used for seat design and assessment of driver reach and ingress/egress. DHMs and related simulation tools are expanding into the cognitive domain, with computational models of perception and motion, and into the dynamic domain with models of physical responses to ride and vibration. Moreover, DHMs are now widely used to analyze the ergonomics of vehicle assembly tasks. In this case, the analysis aims to determine whether workers can be expected to complete the tasks safely and with good quality. This preface provides a review of the literature to provide context for the nine new papers presented in this special issue.

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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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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.