11 resultados para process model, sensor, risk, YAWL

em University of Queensland eSpace - Australia


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Minimal representations are known to have no redundant elements, and are therefore of great importance. Based on the notions of performance and size indices and measures for process systems, the paper proposes conditions for a process model being minimal in a set of functionally equivalent models with respect to a size norm. Generalized versions of known procedures to obtain minimal process models for a given modelling goal, model reduction based on sensitivity analysis and incremental model building are proposed and discussed. The notions and procedures are illustrated and compared on a simple example, that of a simple nonlinear fermentation process with different modelling goals and on a case study of a heat exchanger modelling. (C) 2004 Elsevier Ltd. All rights reserved.

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The aim of the study presented was to implement a process model to simulate the dynamic behaviour of a pilot-scale process for anaerobic two-stage digestion of sewage sludge. The model implemented was initiated to support experimental investigations of the anaerobic two-stage digestion process. The model concept implemented in the simulation software package MATLAB(TM)/Simulink(R) is a derivative of the IWA Anaerobic Digestion Model No.1 (ADM1) that has been developed by the IWA task group for mathematical modelling of anaerobic processes. In the present study the original model concept has been adapted and applied to replicate a two-stage digestion process. Testing procedures, including balance checks and 'benchmarking' tests were carried out to verify the accuracy of the implementation. These combined measures ensured a faultless model implementation without numerical inconsistencies. Parameters for both, the thermophilic and the mesophilic process stage, have been estimated successfully using data from lab-scale experiments described in literature. Due to the high number of parameters in the structured model, it was necessary to develop a customised procedure that limited the range of parameters to be estimated. The accuracy of the optimised parameter sets has been assessed against experimental data from pilot-scale experiments. Under these conditions, the model predicted reasonably well the dynamic behaviour of a two-stage digestion process in pilot scale. (C) 2004 Elsevier Ltd. All rights reserved.

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Predictive genetic testing for serious, mature-onset genetic illness represents a unique context in health decision making. This article presents findings from an exploratory qualitative Australian-based study into the decision making of individuals at risk for Huntington's disease (HD) with regard to predictive genetic testing. Sixteen in-depth interviews were conducted with a range of at-risk individuals. Data analysis revealed four discrete decision-making positions rather than a 'to test' or not to test' dichotomy. A conceptual dimension of (non-)openness and (non-)engagement characterized the various decisions. Processes of decision making and a concept of 'test readiness' were identified. Findings from this research, while not generalizable, are discussed in relation to theoretical frameworks and stage models of health decision making, as well as possible clinical implications.

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As process management projects have increased in size due to globalised and company-wide initiatives, a corresponding growth in the size of process modeling projects can be observed. Despite advances in languages, tools and methodologies, several aspects of these projects have been largely ignored by the academic community. This paper makes a first contribution to a potential research agenda in this field by defining the characteristics of large-scale process modeling projects and proposing a framework of related issues. These issues are derived from a semi -structured interview and six focus groups conducted in Australia, Germany and the USA with enterprise and modeling software vendors and customers. The focus groups confirm the existence of unresolved problems in business process modeling projects. The outcomes provide a research agenda which directs researchers into further studies in global process management, process model decomposition and the overall governance of process modeling projects. It is expected that this research agenda will provide guidance to researchers and practitioners by focusing on areas of high theoretical and practical relevance.

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In this paper, we present a top down approach for integrated process modelling and distributed process execution. The integrated process model can be utilized for global monitoring and visualization and distributed process models for local execution. Our main focus in this paper is the presentation of the approach to support automatic generation and linking of distributed process models from an integrated process definition.

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Following study, participants received 2 tests. The 1st was a recognition test; the 2nd was designed to tap recollection. The objective was to examine performance on Test I conditional on Test 2 performance. In Experiment 1, contrary to process dissociation assumptions, exclusion errors better predicted subsequent recollection than did inclusion errors. In Experiments 2 and 3, with alternate questions posed on Test 2, words having high estimates of recollection with one question had high estimates of familiarity with the other question. Results supported the following: (a) the 2-test procedure has considerable potential for elucidating the relationship between recollection and familiarity; (b) there is substantial evidence for dependency between such processes when estimates are obtained using the process dissociation and remember-know procedures; and (c) order of information access appears to depend on the question posed to the memory system.

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The development of a new process model of cement grinding in two-stage mills is discussed. The new model has been used to simulate cement grinding and predicting mill performance in open and closed circuit configuration. The new model considered the two-compartment mill as perfectly mixed slices in series. The breakage rate function uses the back calculation technique to determine offline using drop weight and abrasion tests.

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Perinatal mortality is very high in Bangladesh. In this setting, few community-level studies have assessed the influence of underlying maternal health factors on perinatal outcomes. We used the data from a community-based clinical controlled trial conducted between 1994 and 1997 in the catchment areas of a large MCH/FP hospital located in Mirpur, a suburban area of Dhaka in Bangladesh, to investigate the levels of perinatal mortality and its associated maternal health factors during pregnancy. A total of 2007 women were followed after recruitment up to delivery, maternal death, or until they dropped out of the study. Of these, 1584 who gave birth formed our study subjects. The stillbirth rate was 39.1 per 1000 births [95% confidence interval (CI) 39.0, 39.3] and the perinatal mortality rate (up to 3 days) was 54.3 per 1000 births [95% CI 54.0, 54.6] among the study population. In the fully adjusted logistic regression model, the risk of perinatal mortality was as high as 2.7 times [95% CI 1.5, 4.9] more likely for women with hypertensive disorders, 5.0 times [95% CI 2.3, 10.8] as high for women who had antepartum haemorrhage and 2.6 times [95% CI 1.2, 5.8] as high for women who had higher haemoglobin levels in pregnancy when compared with their counterparts. The inclusion of potential confounding variables such as poor obstetric history, sociodemographic characteristics and preterm delivery influenced only marginally the net effect of important maternal health factors associated with perinatal mortality. Perinatal mortality in the study setting was significantly associated with poor maternal health conditions during pregnancy. The results of this study point towards the urgent need for monitoring complications in high-risk pregnancies, calling for the specific components of the safe motherhood programme interventions that are designed to manage these complications of pregnancy.

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Semantic priming occurs when a subject is faster in recognising a target word when it is preceded by a related word compared to an unrelated word. The effect is attributed to automatic or controlled processing mechanisms elicited by short or long interstimulus intervals (ISIs) between primes and targets. We employed event-related functional magnetic resonance imaging (fMRI) to investigate blood oxygen level dependent (BOLD) responses associated with automatic semantic priming using an experimental design identical to that used in standard behavioural priming tasks. Prime-target semantic strength was manipulated by using lexical ambiguity primes (e.g., bank) and target words related to dominant or subordinate meaning of the ambiguity. Subjects made speeded lexical decisions (word/nonword) on dominant related, subordinate related, and unrelated word pairs presented randomly with a short ISI. The major finding was a pattern of reduced activity in middle temporal and inferior prefrontal regions for dominant versus unrelated and subordinate versus unrelated comparisons, respectively. These findings are consistent with both a dual process model of semantic priming and recent repetition priming data that suggest that reductions in BOLD responses represent neural priming associated with automatic semantic activation and implicate the left middle temporal cortex and inferior prefrontal cortex in more automatic aspects of semantic processing.