107 resultados para predictive analytics
em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast
Resumo:
The incorporation of one-dimensional simulation codes within engine modelling applications has proved to be a useful tool in evaluating unsteady gas flow through elements in the exhaust system. This paper reports on an experimental and theoretical investigation into the behaviour of unsteady gas flow through catalyst substrate elements. A one-dimensional (1-D) catalyst model has been incorporated into a 1-D simulation code to predict this behaviour.
Experimental data was acquired using a ‘single pulse’ test rig. Substrate samples were tested under ambient conditions in order to investigate a range of regimes experienced by the catalyst during operation. This allowed reflection and transmission characteristics to be quantified in relation to both geometric and physical properties of substrate elements. Correlation between measured and predicted results is demonstrably good and the model provides an effective analysis tool for evaluating unsteady gas flow through different catalytic converter designs.
Resumo:
Objectives: To determine whether diagnostic triage by general practitioners (GPs) or rheumatology nurses (RNs) can improve the positive predictive value of referrals to early arthritis clinics (EACs).
Methods: Four GPs and two RNs were trained in the assessment of early in?ammatory arthritis (IA) by four visits to an EAC supervised by hospital rheumatologists. Patients referred to one of three EACs were recruited for study and assessed independently by a GP, an RN and one of six rheumatologists. Each assessor was asked to record their clinical ?ndings and whether they considered the patient to have IA. Each was then asked to judge the appropriateness of the referral according to predetermined guidelines. The rheumatologists had been shown previously to have a satisfactory level of agreement in the assessment of IA.
Results: Ninety-six patients were approached and all consented to take part in the study. In 49 cases (51%), the rheumatologist judged that the patient had IA and that the referral was appropriate. The assessments of GPs and RNs were compared with those of the rheumatologists. Levels of agreement were measured using the kappa value, where 1.0 represents total unanimity. The kappa value was
0.77 for the GPs when compared with the rheumatologists and 0.79 for the RNs. Signi?cant stiffness in the morning or after rest and objective joint swelling were the most important clinical features enabling the GPs and RNs to discriminate between IA and non-IA conditions.
Conclusion: Diagnostic triage by GPs or RNs improved the positive predictive value of referrals to an EAC with a degree of accuracy approaching that of a group of experienced rheumatologists.