342 resultados para Management model


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This cross disciplinary study was conducted as two research and development projects. The outcome is a multimodal and dynamic chronicle, which incorporates the tracking of spatial, temporal and visual elements of performative practice-led and design-led research journeys. The distilled model provides a strong new approach to demonstrate rigour in non-traditional research outputs including provenance and an 'augmented web of facticity'.

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Objective: The aim of this study was to develop a model capable of predicting variability in the mental workload experienced by frontline operators under routine and nonroutine conditions. Background: Excess workload is a risk that needs to be managed in safety-critical industries. Predictive models are needed to manage this risk effectively yet are difficult to develop. Much of the difficulty stems from the fact that workload prediction is a multilevel problem. Method: A multilevel workload model was developed in Study 1 with data collected from an en route air traffic management center. Dynamic density metrics were used to predict variability in workload within and between work units while controlling for variability among raters. The model was cross-validated in Studies 2 and 3 with the use of a high-fidelity simulator. Results: Reported workload generally remained within the bounds of the 90% prediction interval in Studies 2 and 3. Workload crossed the upper bound of the prediction interval only under nonroutine conditions. Qualitative analyses suggest that nonroutine events caused workload to cross the upper bound of the prediction interval because the controllers could not manage their workload strategically. Conclusion: The model performed well under both routine and nonroutine conditions and over different patterns of workload variation. Application: Workload prediction models can be used to support both strategic and tactical workload management. Strategic uses include the analysis of historical and projected workflows and the assessment of staffing needs. Tactical uses include the dynamic reallocation of resources to meet changes in demand.

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This thesis provides two main contributions. The first one is BP-TRBAC, a unified authorisation model that can support legacy systems as well as business process systems. BP-TRBAC supports specific features that are required by business process environments. BP-TRBAC is designed to be used as an independent enterprise-wide authorisation model, rather than having it as part of the workflow system. It is designed to be the main authorisation model for an organisation. The second contribution is BP-XACML, an authorisation policy language that is designed to represent BPM authorisation policies for business processes. The contribution also includes a policy model for BP-XACML. Using BP-TRBAC as an authorisation model together with BP-XACML as an authorisation policy language will allow an organisation to manage and control authorisation requests from workflow systems and other legacy systems.

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BACKGROUND: Monitoring studies revealed high concentrations of pesticides in the drainage canal of paddy fields. It is important to have a way to predict these concentrations in different management scenarios as an assessment tool. A simulation model for predicting the pesticide concentration in a paddy block (PCPF-B) was evaluated and then used to assess the effect of water management practices for controlling pesticide runoff from paddy fields. RESULTS: The PCPF-B model achieved an acceptable performance. The model was applied to a constrained probabilistic approach using the Monte Carlo technique to evaluate the best management practices for reducing runoff of pretilachlor into the canal. The probabilistic model predictions using actual data of pesticide use and hydrological data in the canal showed that the water holding period (WHP) and the excess water storage depth (EWSD) effectively reduced the loss and concentration of pretilachlor from paddy fields to the drainage canal. The WHP also reduced the timespan of pesticide exposure in the drainage canal. CONCLUSIONS: It is recommended that: (1) the WHP be applied for as long as possible, but for at least 7 days, depending on the pesticide and field conditions; (2) an EWSD greater than 2 cm be maintained to store substantial rainfall in order to prevent paddy runoff, especially during the WHP.

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The prevailing model of psychiatric facility design does not fulfil its potential in supporting the healing process. A salutogenic approach can improve coherence and foster meaning, will actually improve mental health outcomes, not only manage patient behaviour.

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Enterprise System (ES) implementation and management are knowledge intensive tasks that inevitably draw upon the experience of a wide range of people with diverse knowledge capabilities. Knowledge Management (KM) has been identified as a critical success factor in ES projects. Despite the recognized importance of managing knowledge for ES benefits realization, systematic attempts to conceptualize KM-structures have been few. Where the adequacy of KM-structures is assessed, the process and measures are typically idiosyncratic and lack credibility. Using the ‘KM-process’, itself based in sociology of knowledge, this paper conceptualizes four main constructs to measure the adequacy of KM-structures. The SEM model is tested using 310 responses gathered from 27 ES installations that had implemented SAP R/3. The findings reveal six constructs for KM-structure. Furthermore, the paper demonstrates the application of KM-structures in the context of ES using the Adaptive Structuration Theory. The results demonstrate that having adequate KM-structures in place, while necessary, is not sufficient. These rules and resources must be appropriated to have greater positive influence on the Enterprise System. Furthermore, the study provides empirical support for knowledge-based theory by illustrating the importance of knowledge use/re-use (vs. knowledge creation) as the most important driver in the process of KM.

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The high degree of variability and inconsistency in cash flow study usage by property professionals demands improvement in knowledge and processes. Until recently limited research was being undertaken on the use of cash flow studies in property valuations but the growing acceptance of this approach for major investment valuations has resulted in renewed interest in this topic. Studies on valuation variations identify data accuracy, model consistency and bias as major concerns. In cash flow studies there are practical problems with the input data and the consistency of the models. This study will refer to the recent literature and identify the major factors in model inconsistency and data selection. A detailed case study will be used to examine the effects of changes in structure and inputs. The key variable inputs will be identified and proposals developed to improve the selection process for these key variables. The variables will be selected with the aid of sensitivity studies and alternative ways of quantifying the key variables explained. The paper recommends, with reservations, the use of probability profiles of the variables and the incorporation of this data in simulation exercises. The use of Monte Carlo simulation is demonstrated and the factors influencing the structure of the probability distributions of the key variables are outline. This study relates to ongoing research into functional performance of commercial property within an Australian Cooperative Research Centre.