342 resultados para Management model


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The high levels of end-stage renal disease among Indigenous Australians, particularly in remote areas of the country, are a serious public health concern. The magnitude of the problem is reflected in figures from the Australian and New Zealand Transplant and Dialysis Registry that show that Indigenous Australians experience end-stage renal disease at a rate almost 9–10 times higher than other non-Indigenous Australians. A majority of Indigenous Australians have to relocate to receive appropriate renal dialysis treatment. In some Australian states, renal treatment is based on self-care dialysis which allows those Indigenous Australians to be treated back in their community. Evidence clearly shows that reuniting renal patients with community and family improves overall health and well-being for those Indigenous Australians. With the appropriate resources, training, and support, self-care management of renal dialysis treatment is an effective way for Indigenous people with end-stage renal failure to be treated at home. In this context, the study was used to gain insight and further understanding of the impact that end-stage renal disease and renal dialysis treatment has had on the lives of Indigenous community members. The study findings are from 14 individually interviewed people from South East Queensland. Data from the interviews were analysed using a combination of thematic and content analysis. The study methodology was based on qualitative data principles where the Indigenous community members were able to share their experiences and journeys living with end-stage renal disease. Many of the experiences and understanding closely relate to the renal disease pattern and the treatment with other outside influences, such as social, cultural, and environmental influences, all having an equal impact. Each community member’s experience with end-stage renal disease is unique; some manage with family and medical support, while others try to manage independently. From the study, community members who managed their renal dialysis treatment independently were much more aware of their renal health status. The study provides recommendations towards a model of care to improve the health and well-being is based on self-care and self-determination principles.

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Survival probability prediction using covariate-based hazard approach is a known statistical methodology in engineering asset health management. We have previously reported the semi-parametric Explicit Hazard Model (EHM) which incorporates three types of information: population characteristics; condition indicators; and operating environment indicators for hazard prediction. This model assumes the baseline hazard has the form of the Weibull distribution. To avoid this assumption, this paper presents the non-parametric EHM which is a distribution-free covariate-based hazard model. In this paper, an application of the non-parametric EHM is demonstrated via a case study. In this case study, survival probabilities of a set of resistance elements using the non-parametric EHM are compared with the Weibull proportional hazard model and traditional Weibull model. The results show that the non-parametric EHM can effectively predict asset life using the condition indicator, operating environment indicator, and failure history.

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Many infrastructure and necessity systems such as electricity and telecommunication in Europe and the Northern America were used to be operated as monopolies, if not state-owned. However, they have now been disintegrated into a group of smaller companies managed by different stakeholders. Railways are no exceptions. Since the early 1980s, there have been reforms in the shape of restructuring of the national railways in different parts of the world. Continuous refinements are still conducted to allow better utilisation of railway resources and quality of service. There has been a growing interest for the industry to understand the impacts of these reforms on the operation efficiency and constraints. A number of post-evaluations have been conducted by analysing the performance of the stakeholders on their profits (Crompton and Jupe 2003), quality of train service (Shaw 2001) and engineering operations (Watson 2001). Results from these studies are valuable for future improvement in the system, followed by a new cycle of post-evaluations. However, direct implementation of these changes is often costly and the consequences take a long period of time (e.g. years) to surface. With the advance of fast computing technologies, computer simulation is a cost-effective means to evaluate a hypothetical change in a system prior to actual implementation. For example, simulation suites have been developed to study a variety of traffic control strategies according to sophisticated models of train dynamics, traction and power systems (Goodman, Siu and Ho 1998, Ho and Yeung 2001). Unfortunately, under the restructured railway environment, it is by no means easy to model the complex behaviour of the stakeholders and the interactions between them. Multi-agent system (MAS) is a recently developed modelling technique which may be useful in assisting the railway industry to conduct simulations on the restructured railway system. In MAS, a real-world entity is modelled as a software agent that is autonomous, reactive to changes, able to initiate proactive actions and social communicative acts. It has been applied in the areas of supply-chain management processes (García-Flores, Wang and Goltz 2000, Jennings et al. 2000a, b) and e-commerce activities (Au, Ngai and Parameswaran 2003, Liu and You 2003), in which the objectives and behaviour of the buyers and sellers are captured by software agents. It is therefore beneficial to investigate the suitability or feasibility of applying agent modelling in railways and the extent to which it might help in developing better resource management strategies. This paper sets out to examine the benefits of using MAS to model the resource management process in railways. Section 2 first describes the business environment after the railway 2 Modelling issues on the railway resource management process using MAS reforms. Then the problems emerge from the restructuring process are identified in section 3. Section 4 describes the realisation of a MAS for railway resource management under the restructured scheme and the feasible studies expected from the model.

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Cloninger’s psychobiological model of temperament and character is a general model of personality that has been widely used in clinical psychology, but has seldom been applied in other domains. In this research we apply Cloninger’s model to the study of leadership. Our study comprised 81 participants who took part in a diverse range of small group tasks. Participants rotated through tasks and groups and rated each other on “emergent leadership.” As hypothesized, leader emergence tended to be consistent regardless of the specific tasks and groups. It was found that personality factors from Cloninger, Svrakic, and Przybeck’s (1993) model could explain trait-based variance in emergent leadership. Results also highlight the role of “cooperativeness” in the prediction of leadership emergence. Implications are discussed in terms of our theoretical understanding of trait-based leadership, and more generally in terms of the utility of Cloninger’s model in leadership research.

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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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A composite line source emission (CLSE) model was developed to specifically quantify exposure levels and describe the spatial variability of vehicle emissions in traffic interrupted microenvironments. This model took into account the complexity of vehicle movements in the queue, as well as different emission rates relevant to various driving conditions (cruise, decelerate, idle and accelerate), and it utilised multi-representative segments to capture the accurate emission distribution for real vehicle flow. Hence, this model was able to quickly quantify the time spent in each segment within the considered zone, as well as the composition and position of the requisite segments based on the vehicle fleet information, which not only helped to quantify the enhanced emissions at critical locations, but it also helped to define the emission source distribution of the disrupted steady flow for further dispersion modelling. The model then was applied to estimate particle number emissions at a bi-directional bus station used by diesel and compressed natural gas fuelled buses. It was found that the acceleration distance was of critical importance when estimating particle number emission, since the highest emissions occurred in sections where most of the buses were accelerating and no significant increases were observed at locations where they idled. It was also shown that emissions at the front end of the platform were 43 times greater than at the rear of the platform. Although the CLSE model is intended to be applied in traffic management and transport analysis systems for the evaluation of exposure, as well as the simulation of vehicle emissions in traffic interrupted microenvironments, the bus station model can also be used for the input of initial source definitions in future dispersion models.

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As organizations reach higher levels of Business Process Management maturity, they tend to collect numerous business process models. Such models may be linked with each other or mutually overlap, supersede one another and evolve over time. Moreover, they may be represented at different abstraction levels depending on the target audience and modeling purpose, and may be available in multiple languages (e.g. due to company mergers). Thus, it is common that organizations struggle with keeping track of their process models. This demonstration introduces AProMoRe (Advanced Process Model Repository) which aims to facilitate the management of (large) process model collections.

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The upper Condamine River in southern Queensland has formed extensive alluvial deposits which have been used for irrigation of cotton crops for over 40 years. Due to excessive use and long term drought conditions these groundwater resources are under substantial threat. This condition is now recognised by all stakeholders, and Qld Department of Environment and Resource Management (DERM) are currently undertaking a water planning process for the Central Condamine Alluvium with water users and other stakeholders. DERM aims to effectively demonstrate the character of the groundwater system and its current status, and notably the continued long-term drawdown of the watertable. It was agreed that 3D visualisation was an ideal tool to achieve this. The Groundwater Visualisation System (GVS) developed at QUT was utilised and the visualisation model developed in conjunction with DERM to achieve a planning-management tool for this particular application

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This research focuses on exploring the links between sport, Indigenous self determination and deeper engagement within mainstream Australia especially with regard to the issue of promoting healthy lifestyles and the role of governance, through sport governance. Against all social, economic and health criteria Indigenous Australians are disadvantaged – despite government attention and financial input. It is well understood that education is a basis to better health, employment and lifestyle (Furneaux and Brown, 2008). However, many of the issues confronting Indigenous people have not responded to conventional government approaches based on program development and policy initiatives from single organisations (Ryan et al 2006). As a consequence, new approaches that both tap into the specific interests of Indigenous people and better engage them in the process of governance are required. The case material of the research focuses on the Australian Football League (AFL) Kickstart program.

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This research assesses the potential impact of weekly weather variability on the incidence of cryptosporidiosis disease using time series zero-inflated Poisson (ZIP) and classification and regression tree (CART) models. Data on weather variables, notified cryptosporidiosis cases and population size in Brisbane were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Both time series ZIP and CART models show a clear association between weather variables (maximum temperature, relative humidity, rainfall and wind speed) and cryptosporidiosis disease. The time series CART models indicated that, when weekly maximum temperature exceeded 31°C and relative humidity was less than 63%, the relative risk of cryptosporidiosis rose by 13.64 (expected morbidity: 39.4; 95% confidence interval: 30.9–47.9). These findings may have applications as a decision support tool in planning disease control and risk management programs for cryptosporidiosis disease.

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As organizations reach higher levels of Business Process Management maturity, they tend to accumulate large collections of process models. These repositories may contain thousands of activities and be managed by different stakeholders with varying skills and responsibilities. However, while being of great value, these repositories induce high management costs. Thus, it becomes essential to keep track of the various model versions as they may mutually overlap, supersede one another and evolve over time. We propose an innovative versioning model and associated storage structure, specifically designed to maximize sharing across process model versions, and to automatically handle change propagation. The focal point of this technique is to version single process model fragments, rather than entire process models. Indeed empirical evidence shows that real-life process model repositories have numerous duplicate fragments. Experiments on two industrial datasets confirm the usefulness of our technique.

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Recent years have seen an increased uptake of business process management technology in industries. This has resulted in organizations trying to manage large collections of business process models. One of the challenges facing these organizations concerns the retrieval of models from large business process model repositories. For example, in some cases new process models may be derived from existing models, thus finding these models and adapting them may be more effective and less error-prone than developing them from scratch. Since process model repositories may be large, query evaluation may be time consuming. Hence, we investigate the use of indexes to speed up this evaluation process. To make our approach more applicable, we consider the semantic similarity between labels. Experiments are conducted to demonstrate that our approach is efficient.

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Business process models are becoming available in large numbers due to their popular use in many industrial applications such as enterprise and quality engineering projects. On the one hand, this raises a challenge as to their proper management: How can it be ensured that the proper process model is always available to the interested stakeholder? On the other hand, the richness of a large set of process models also offers opportunities, for example with respect to the re-use of existing model parts for new models. This paper describes the functionalities and architecture of an advanced process model repository, named APROMORE. This tool brings together a rich set of features for the analysis, management and usage of large sets of process models, drawing from state-of-the art research in the field of process modeling. A prototype of the platform is presented in this paper, demonstrating its feasibility, as well as an outlook on the further development of APROMORE.

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It is noted from observations of Compton (2009), Richards (2008), Taylor and Bennett (2002), and others that succession leadership planning and development fails to receive adequate attention in the corporate sector (see Byham 2002; Richards 2008; Wellins and Byham 2001). This paper acknowledges a marked paucity of systematic succession leadership development in education organisations. The need would seem to be compounded at a time when substantial attrition in the leadership ranks is expected over the next five years, reflecting widespread workforce demographics (Busine and Watt 2005; Jacobzone, Cambois, Chaplain, and Robine 1998; Taylor and Bennett 2002). The Lantern model has been developed in response to a perceived need to offer an integrated, systematic approach to organisational and succession leadership development. The model offers an organising framework for considering succession leadership development in a strategic, integrated way. The concept is based on organisational development and leadership literature which sees leadership development not as a series of 'tacked on' activities but as an organic 'whole of organisation' approach fostering the relevant knowledge, skills and understandings which support and 'grow' leaders as the organisation goes about its business. This paper explores how such an ideal might happen, and it suggests that pursuing such an ideal is timely. The leadership baton is set to shift at an accelerated rate in universities, as for organisations broadly, owing to age-related attrition. Moreover, given the increased complexity and demands of the leadership remit in the education leadership environment, it would seem particularly opportune to explore a framework concentrating on engendering a positive, connected organisational climate capable of growing strategic leadership strength from within. Eight core elements of the model, derived from the literature and practice research, are explored. The Lantern model purports to 'cover the bases' of succession leadership development, with particular reference to the education environment. The model is next described

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Purpose - This paper seeks to examine the complex relationships between urban planning, infrastructure management, sustainable urban development, and to illustrate why there is an urgent need for local governments to develop a robust planning support system which integrates with advance urban computer modelling tools to facilitate better infrastructure management and improve knowledge sharing between the community, urban planners, engineers and decision makers. Design/methodology/approach - The methods used in this paper includes literature review and practical project case observations. Originality/value - This paper provides an insight of how the Brisbane's planning support system established by Brisbane City Council has significantly improved the effectiveness of urban planning, infrastructure management and community engagement through better knowledge management processes. Practical implications - This paper presents a practical framework for setting up a functional planning support system within local government. The integration of the Brisbane Urban Growth model, Virtual Brisbane and the Brisbane Economic Activity Monitoring (BEAM) database have proven initially successful to provide a dynamic platform to assist elected officials, planners and engineers to understand the limitations of the local environment, its urban systems and the planning implications on a city. With the Brisbane's planning support system, planners and decision makers are able to provide better planning outcomes, policy and infrastructure that adequately address the local needs and achieve sustainable spatial forms.