915 resultados para Process planning


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Predicting safety on roadways is standard practice for road safety professionals and has a corresponding extensive literature. The majority of safety prediction models are estimated using roadway segment and intersection (microscale) data, while more recently efforts have been undertaken to predict safety at the planning level (macroscale). Safety prediction models typically include roadway, operations, and exposure variables—factors known to affect safety in fundamental ways. Environmental variables, in particular variables attempting to capture the effect of rain on road safety, are difficult to obtain and have rarely been considered. In the few cases weather variables have been included, historical averages rather than actual weather conditions during which crashes are observed have been used. Without the inclusion of weather related variables researchers have had difficulty explaining regional differences in the safety performance of various entities (e.g. intersections, road segments, highways, etc.) As part of the NCHRP 8-44 research effort, researchers developed PLANSAFE, or planning level safety prediction models. These models make use of socio-economic, demographic, and roadway variables for predicting planning level safety. Accounting for regional differences - similar to the experience for microscale safety models - has been problematic during the development of planning level safety prediction models. More specifically, without weather related variables there is an insufficient set of variables for explaining safety differences across regions and states. Furthermore, omitted variable bias resulting from excluding these important variables may adversely impact the coefficients of included variables, thus contributing to difficulty in model interpretation and accuracy. This paper summarizes the results of an effort to include weather related variables, particularly various measures of rainfall, into accident frequency prediction and the prediction of the frequency of fatal and/or injury degree of severity crash models. The purpose of the study was to determine whether these variables do in fact improve overall goodness of fit of the models, whether these variables may explain some or all of observed regional differences, and identifying the estimated effects of rainfall on safety. The models are based on Traffic Analysis Zone level datasets from Michigan, and Pima and Maricopa Counties in Arizona. Numerous rain-related variables were found to be statistically significant, selected rain related variables improved the overall goodness of fit, and inclusion of these variables reduced the portion of the model explained by the constant in the base models without weather variables. Rain tends to diminish safety, as expected, in fairly complex ways, depending on rain frequency and intensity.

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Expert panels have been used extensively in the development of the "Highway Safety Manual" to extract research information from highway safety experts. While the panels have been used to recommend agendas for new and continuing research, their primary role has been to develop accident modification factors—quantitative relationships between highway safety and various highway safety treatments. Because the expert panels derive quantitative information in a “qualitative” environment and because their findings can have significant impacts on highway safety investment decisions, the expert panel process should be described and critiqued. This paper is the first known written description and critique of the expert panel process and is intended to serve professionals wishing to conduct such panels.

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This paper addresses the problem of constructing consolidated business process models out of collections of process models that share common fragments. The paper considers the construction of unions of multiple models (called merged models) as well as intersections (called digests). Merged models are intended for analysts who wish to create a model that subsumes a collection of process models - typically representing variants of the same underlying process - with the aim of replacing the variants with the merged model. Digests, on the other hand, are intended for analysts who wish to identify the most recurring fragments across a collection of process models, so that they can focus their efforts on optimizing these fragments. The paper presents an algorithm for computing merged models and an algorithm for extracting digests from a merged model. The merging and digest extraction algorithms have been implemented and tested against collections of process models taken from multiple application domains. The tests show that the merging algorithm produces compact models and scales up to process models containing hundreds of nodes. Furthermore, a case study conducted in a large insurance company has demonstrated the usefulness of the merging and digest extraction operators in a practical setting.

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This paper explores models of teaching and learning music composition in higher education. It analyses the pedagogical approaches apparent in the literature on teaching and learning composition in schools and universities, and introduces a teaching model as: learning from the masters; mastery of techniques; exploring ideas; and developing voice. It then presents a learning model developed from a qualitative study into students’ experiences of learning composition at university as: craft, process and art. The relationship between the students’ experiences and the pedagogical model is examined. Finally, the implications for composition curricula in higher education are presented.

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The field of collaborative health planning faces significant challenges due to the lack of effective information, systems and the absence of a framework to make informed decisions. These challenges have been magnified by the rise of the healthy cities movement, consequently, there have been more frequent calls for localised, collaborative and evidence-driven decision-making. Some studies in the past have reported that the use of decision support systems (DSS) for planning healthy cities may lead to: increase collaboration between stakeholders and the general public, improve the accuracy and quality of the decision-making processes and improve the availability of data and information for health decision-makers. These links have not yet been fully tested and only a handful of studies have evaluated the impact of DSS on stakeholders, policy-makers and health planners. This study suggests a framework for developing healthy cities and introduces an online Geographic Information Systems (GIS)-based DSS for improving the collaborative health planning. It also presents preliminary findings of an ongoing case study conducted in the Logan-Beaudesert region of Queensland, Australia. These findings highlight the perceptions of decision-making prior to the implementation of the DSS intervention. Further, the findings help us to understand the potential role of the DSS to improve collaborative health planning practice.

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This chapter outlines: a brief history of Australian Aboriginal health and health policy and then moves on to demonstrate how the Victorian Aboriginal Community Controlled Health Organisation (VACCHO) undertakes its work and is an example of 'decolonizing policy in action'. Moreover, it highlights how Aboriginal participation in the development of policy and in the planning, delivery, management and evaluation of health programs enables policies and programs to respond effectively to the needs of Aboriginal people and to change future health outcomes for them. It showcases how Aboriginal decision-making has gone some way to decolonizing policymaking and has addressed the power imbalance - both of which have been critical in the improvement in Aboriginal health outcomes.

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The detached housing scheme is a unique and exclusive segment of the residential property market in Malaysia. Generally, the product is expensive and for many Malaysians who can afford them, owning a detached house is a once in a lifetime opportunity. In spite of this, most of the owners fail to fully comprehend the specific need of this type of housing scheme, increasing the risk of it being a problematic project. Unlike other types of pre-designed ‘mass housing’ schemes, the detached housing scheme may be built specifically to cater the needs and demands of its owner. Therefore, maximum owner participation is vital as the development progresses to guarantee the success of the project. In addition, due to it’s unique design the house would have to individually comply with the requirements and regulations of relevant authorities. Failure of owner to recognise this will result in delays, fines and penalties, disputes and ultimately cost overruns. These circumstances highlight the need for a model to guide the owner through the entire development process of a detached house. Therefore, this research aims to develop a model for a successful detached housing development in Malaysia through maximising owner participation during it’s various development stages. To achieve this, questionnaire surveys and case studies methods shall be employed to acquire the detached housing owners’ experiences in developing their detached houses in Malaysia. Relevant statistical tools shall be applied to analyse the responses. The results gained from this study shall be synthesised into a model of successful detached housing development for the reference of future detached housing owners in Malaysia.

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Real-world business processes are resource-intensive. In work environments human resources usually multitask, both human and non-human resources are typically shared between tasks, and multiple resources are sometimes necessary to undertake a single task. However, current Business Process Management Systems focus on task-resource allocation in terms of individual human resources only and lack support for a full spectrum of resource classes (e.g., human or non-human, application or non-application, individual or teamwork, schedulable or unschedulable) that could contribute to tasks within a business process. In this paper we develop a conceptual data model of resources that takes into account the various resource classes and their interactions. The resulting conceptual resource model is validated using a real-life healthcare scenario.

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Sustainable urban development and the liveability of a city are increasingly important issues in the context of land use planning and infrastructure management. In recent years, the promotion of sustainable urban development in Australia and overseas is facing various physical, socio-economic and environmental challenges. These challenges and problems arise from the lack of capability of local governments to accommodate the needs of the population and economy in a relatively short timeframe. The planning of economic growth and development is often dealt with separately and not included in the conventional land use planning process. There is also a sharp rise in the responsibilities and roles of local government for infrastructure planning and management. This increase in responsibilities means that local elected officials and urban planners have less time to prepare background information and make decisions. The Brisbane Urban Growth Model has proven initially successful in providing a dynamic platform to ensure timely and coordinated delivery of urban infrastructure. Most importantly, this model is the first step for local governments in moving toward a systematic approach to pursuing sustainable and effective urban infrastructure management.

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The concept of sustainable urban development has been pushed to the forefront of policy-making and politics as the world wakes up to the impacts of climate change and the effects of modern urban lifestyles. Today, sustainable development has become a very prominent element in the day-to-day debate on urban policy and the expression of that policy in urban planning and development decisions. As a result of this, during the last few years, sustainable development automation applications such as sustainable urban development decision support systems have become popular tools as they offer new opportunities for local governments to realise their sustainable development agendas. This chapter explores a range of issues associated with the application of information and communication technologies and decision support systems in the process of underpinning sustainable urban development. The chapter considers how information and communication technologies can be applied to enhance urban planning, raise environmental awareness, share decisions and improve public participation. It introduces and explores three web-based geographical information systems projects as best practice. These systems are developed as support tools to include public opinion in the urban planning and development processes, and to provide planners with comprehensive tools for the analysis of sustainable urban development variants in order to prepare the best plans for constructing sustainable urban communities and futures.

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Groundwater is increasingly recognised as an important yet vulnerable natural resource, and a key consideration in water cycle management. However, communication of sub-surface water system behaviour, as an important part of encouraging better water management, is visually difficult. Modern 3D visualisation techniques can be used to effectively communicate these complex behaviours to engage and inform community stakeholders. Most software developed for this purpose is expensive and requires specialist skills. The Groundwater Visualisation System (GVS) developed by QUT integrates a wide range of surface and sub-surface data, to produce a 3D visualisation of the behaviour, structure and connectivity of groundwater/surface water systems. Surface data (elevation, surface water, land use, vegetation and geology) and data collected from boreholes (bore locations and subsurface geology) are combined to visualise the nature, structure and connectivity of groundwater/surface water systems. Time-series data (water levels, groundwater quality, rainfall, stream flow and groundwater abstraction) is displayed as an animation within the 3D framework, or graphically, to show water system condition changes over time. GVS delivers an interactive, stand-alone 3D Visualisation product that can be used in a standard PC environment. No specialised training or modelling skills are required. The software has been used extensively in the SEQ region to inform and engage both water managers and the community alike. Examples will be given of GVS visualisations developed in areas where there have been community concerns around groundwater over-use and contamination.

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The development of locally-based healthcare initiatives, such as community health coalitions that focus on capacity building programs and multi-faceted responses to long-term health problems, have become an increasingly important part of the public health landscape. As a result of their complexity and the level of investment, it has become necessary to develop innovative ways to help manage these new healthcare approaches. Geographical Information Systems (GIS) have been suggested as one of the innovative approaches that will allow community health coalitions to better manage and plan their activities. The focus of this paper is to provide a commentary on the use of GIS as a tool for community coalitions and discuss some of the potential benefits and issues surrounding the development of these tools.

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Many industrial processes and systems can be modelled mathematically by a set of Partial Differential Equations (PDEs). Finding a solution to such a PDF model is essential for system design, simulation, and process control purpose. However, major difficulties appear when solving PDEs with singularity. Traditional numerical methods, such as finite difference, finite element, and polynomial based orthogonal collocation, not only have limitations to fully capture the process dynamics but also demand enormous computation power due to the large number of elements or mesh points for accommodation of sharp variations. To tackle this challenging problem, wavelet based approaches and high resolution methods have been recently developed with successful applications to a fixedbed adsorption column model. Our investigation has shown that recent advances in wavelet based approaches and high resolution methods have the potential to be adopted for solving more complicated dynamic system models. This chapter will highlight the successful applications of these new methods in solving complex models of simulated-moving-bed (SMB) chromatographic processes. A SMB process is a distributed parameter system and can be mathematically described by a set of partial/ordinary differential equations and algebraic equations. These equations are highly coupled; experience wave propagations with steep front, and require significant numerical effort to solve. To demonstrate the numerical computing power of the wavelet based approaches and high resolution methods, a single column chromatographic process modelled by a Transport-Dispersive-Equilibrium linear model is investigated first. Numerical solutions from the upwind-1 finite difference, wavelet-collocation, and high resolution methods are evaluated by quantitative comparisons with the analytical solution for a range of Peclet numbers. After that, the advantages of the wavelet based approaches and high resolution methods are further demonstrated through applications to a dynamic SMB model for an enantiomers separation process. This research has revealed that for a PDE system with a low Peclet number, all existing numerical methods work well, but the upwind finite difference method consumes the most time for the same degree of accuracy of the numerical solution. The high resolution method provides an accurate numerical solution for a PDE system with a medium Peclet number. The wavelet collocation method is capable of catching up steep changes in the solution, and thus can be used for solving PDE models with high singularity. For the complex SMB system models under consideration, both the wavelet based approaches and high resolution methods are good candidates in terms of computation demand and prediction accuracy on the steep front. The high resolution methods have shown better stability in achieving steady state in the specific case studied in this Chapter.

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The construction industry plays a substantial role in a country’s national economy, irrespective of the country’s levels of economic development. The Malaysian Government has given a much needed boost to the country’s construction projects under the 9th Malaysian Plan where a total of 880 projects worth RM15billion (US$48billion) is to be tendered (The Star, 2006). However, Malaysia has not escaped the problems of project failure. In 2005, 17.3% of 417 Malaysian government contracts projects were considered “sick”. Project procurement is one of the most important stages of project delivery. Even though ethics in project procurement has been identified as one of the contributors to project failure, it has not been systematically studied before from the perspective of client in Malaysia. The aim of this paper is to present an exploration to the ethical issues in project procurement in Malaysian public sector projects. By exploring ethical issues from client perspective, this could provide an ethical standpoint for the project life cycle and could maintain a good affiliation between the clients and the customers. It is expected that findings from this review will be somewhat representative of other developing countries.

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Together with hard and soft networks tangible and intangible regional assets play an important role in the knowledge-based development of competing city-regions. The aim of this paper, therefore, is to investigate the best ways of managing invaluable tangible and intangible assets of city-regions. The paper explores the importance of asset management of city-regions by giving special emphasis on their knowledge asset base. This paper develops and introduces a theoretical framework to conceptualise a new approach to articulate the strategic planning mechanism, so called the 6K1C framework. The 6K1C framework is part of the strategic planning process of continuous improvement of overall public sector performance. The framework provides a proactive check-list approach integrated for managing and harnessing tangible and intangible assets of the post-industrial city-regions.