9 resultados para need to educate
em Aston University Research Archive
Resumo:
Manufacturing systems that are heavily dependent upon direct workers have an inherent complexity that the system designer is often ill-equipped to understand. This complexity is due to the interactions that cause variations in performance of the workers. Variation in human performance can be explained by many factors, however one important factor that is not currently considered in any detail during the design stage is the physical working environment. This paper presents the findings of ongoing research investigating human performance within manufacturing systems. It sets out to identify the form of the relationships that exist between changes in physical working environmental variables and operator performance. These relationships can provide managers with a decision basis when designing and managing manufacturing systems and their environments.
Resumo:
One of the major challenges in measuring efficiency in terms of resources and outcomes is the assessment of the evolution of units over time. Although Data Envelopment Analysis (DEA) has been applied for time series datasets, DEA models, by construction, form the reference set for inefficient units (lambda values) based on their distance from the efficient frontier, that is, in a spatial manner. However, when dealing with temporal datasets, the proximity in time between units should also be taken into account, since it reflects the structural resemblance among time periods of a unit that evolves. In this paper, we propose a two-stage spatiotemporal DEA approach, which captures both the spatial and temporal dimension through a multi-objective programming model. In the first stage, DEA is solved iteratively extracting for each unit only previous DMUs as peers in its reference set. In the second stage, the lambda values derived from the first stage are fed to a Multiobjective Mixed Integer Linear Programming model, which filters peers in the reference set based on weights assigned to the spatial and temporal dimension. The approach is demonstrated on a real-world example drawn from software development.
Resumo:
Aims: To reassess the utilisation rate of urinary albumin to creatinine ratio (ACR) screening in our centre; and the rate of repeat testing, where appropriate. To look at risk factors for albuminuria in our outpatient population. Methods: All patients attending one of our two weekly diabetes outpatient clinics in 2011–2012 were enrolled in this study. Demographic and relevant clinical data were extracted from electronic care records and analysed using SPSS 21. Results: Our study cohort comprised 998 people (51.4% men;59.6% White, 30.5% Southeast Asian, 9.9% Afro-Caribbean),most of whom had Type 2 diabetes (82.6%). The ACR testing rate in our centre was 62.8% (2012–2013 data; previously 62.4%). The incidence of initial albuminuria was 32.2% in women vs42.8% in men. Just 48.7% of patients (44.4% of women, 51.8% of men) with initial albuminuria were retested: 36.4% of women and 19.7% of men with initial albuminuria had no evidence of this on follow-up. Logistic regression modelling confirmed an association of high systolic blood pressure with albuminuria [odds ratio1.92 (1.01–3.70 in women, 1.08–3.57 in men)]. Treatment with anangiotens in converting enzyme inhibitor (ACEi) or angiotens in 2 receptor blocker (A2RB) was negatively associated with albuminuria in men [odds ratio 0.42 (0.20–0.89)], but not in women. Conclusions: A relatively high, albeit suboptimal, albuminuria screening rate in our outpatient population has been sustained.High systolic blood pressure was confirmed as a risk factor foralbuminuria. The incidence of albuminuria was higher in men, who had a lower rate of negative repeat testing and appeared to benefit more from ACEi/A2RB therapy. More rigorous screening for albuminuria is warranted to identify at-risk individuals.