The optimal sample allocation problem for mapped outputs

Abstract not available

A novel neural/symbolic hybrid approach to heuristically optimized fuel allocation and automated revision of heuristics in nuclear engineering

FUELCON is an expert system for optimized refueling design in nuclear engineering. This task is crucial for keeping down operating costs at a plant without compromising safety. FUELCON proposes sets of alternative configurations of allocation of fuel assemblies that are each positioned in the planar grid of a horizontal section of a reactor core. Results are simulated, and an expert user can also use FUELCON to revise rulesets and improve on his or her heuristics. The successful completion of FUELCON led this research team into undertaking a panoply of sequel projects, of which we provide a meta-architectural comparative formal discussion. In this paper, we demonstrate a novel adaptive technique that learns the optimal allocation heuristic for the various cores. The algorithm is a hybrid of a fine-grained neural network and symbolic computation components. This hybrid architecture is sensitive enough to learn the particular characteristics of the ‘in-core fuel management problem’ at hand, and is powerful enough to use this information fully to automatically revise heuristics, thus improving upon those provided by a human expert.

Nursing resources and patient outcomes in intensive care: a systematic review of the literature

Objectives: To evaluate the empirical evidence linking nursing resources to patient outcomes in intensive care settings as a framework for future research in this area. Background: Concerns about patient safely and the quality of care are driving research on the clinical and cost-effectiveness of health care interventions, including the deployment of human resources. This is particularly important in intensive care where a large proportion of the health care budget is consumed and where nursing staff is the main item of expenditure. Recommendations about staffing levels have been trade but may not be evidence based and may not always be achieved in practice. Methods: We searched systematically for studies of the impact of nursing resources (e.g. nurse-patient ratios, nurses' level of education, training and experience) on patient Outcomes, including mortality and adverse events, in adult intensive care. Abstracts of articles were reviewed and retrieved if they investigated the relationship between nursing resources and patient Outcomes. Characteristics of the studies were tabulated and the quality of the Studies assessed. Results: Of the 15 studies included in this review, two reported it statistical relationship between nursing resources and both mortality and adverse events, one reported ail association to mortality only, seven studies reported that they Could not reject the null hypothesis of no relationship to mortality and 10 studies (out of 10 that tested the hypothesis) reported a relationship to adverse events. The main explanatory mechanisms were the lack of time for nurses to perform preventative measures, or for patient surveillance. The nurses' role in pain control was noted by One author. Studies were mainly observational and retrospective and varied in scope from 1 to 52 units. Recommendations for future research include developing the mechanisms linking nursing resources to patient Outcomes, and designing large multi-centre prospective Studies that link patient's exposure to nursing care oil a shift-by-shift basis over time. (C) 2007 Elsevier Ltd. All rights reserved.