948 resultados para Clustering analysis


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We present a technique for team design based on cognitive work analysis (CWA). We first develop a rationale for this technique by discussing the limitations of conventional approaches for team design in light of the special characteristics of first-of-a-kind, complex systems. We then introduce the CWA-based technique for team design and provide a case study of how we used this technique to design a team for a first-of-a-kind, complex military system during the early stages of its development. In addition to illustrating the CWA-based technique by example, the case study allows us to evaluate the technique. This case study demonstrates that the CWA-based technique for team design is both feasible and useful, although empirical validation of the technique is still necessary. Applications of this work include the design of teams for first-of-a-kind, complex systems in military, medical, and industrial domains.

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Almost all leprosy cases reported in industrialized countries occur amongst immigrants or refugees from developing countries where leprosy continues to be an important health issue. Screening for leprosy is an important question for governments in countries with immigration and refugee programmes. A decision analysis framework is used to evaluate leprosy screening. The analysis uses a set of criteria and parameters regarding leprosy screening, and available data to estimate the number of cases which would be detected by a leprosy screening programme of immigrants from countries with different leprosy prevalences, compared with a policy of waiting for immigrants who develop symptomatic clinical diseases to present for health care. In a cohort of 100,000 immigrants from high leprosy prevalence regions (3.6/10,000), screening would detect 32 of the 42 cases which would arise in the destination country over the 14 years after migration; from medium prevalence areas (0.7/10,000) 6.3 of the total 8.1 cases would be detected, and from low prevalence regions (0.2/10,600) 1.8 of 2.3 cases. Using Australian data, the migrant mix would produce 74 leprosy cases from 10 years intake; screening would detect 54, and 19 would be diagnosed subsequently after migration. Screening would only produce significant case-yield amongst immigrants from regions or social groups with high leprosy prevalence. Since the number of immigrants to Australia from countries of higher endemnicity is not large routine leprosy screening would have a small impact on case incidence.

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The aim of this work was to exemplify the specific contribution of both two- and three-dimensional (31)) X-ray computed tomography to characterise earthworm burrow systems. To achieve this purpose we used 3D mathematical morphology operators to characterise burrow systems resulting from the activity of an anecic (Aporrectodea noctunia), and an endogeic species (Allolobophora chlorotica), when both species were introduced either separately or together into artificial soil cores. Images of these soil cores were obtained using a medical X-ray tomography scanner. Three-dimensional reconstructions of burrow systems were obtained using a specifically developed segmentation algorithm. To study the differences between burrow systems, a set of classical tools of mathematical morphology (granulometries) were used. So-called granulometries based on different structuring elements clearly separated the different burrow systems. They enabled us to show that burrows made by the anecic species were fatter, longer, more vertical, more continuous but less sinuous than burrows of the endogeic species. The granulometry transform of the soil matrix showed that burrows made by A. nocturna were more evenly distributed than those of A. chlorotica. Although a good discrimination was possible when only one species was introduced into the soil cores, it was not possible to separate burrows of the two species from each other in cases where species were introduced into the same soil core. This limitation, partly due to the insufficient spatial resolution of the medical scanner, precluded the use of the morphological operators to study putative interactions between the two species.

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The increased use of trickle or drip irrigation is seen as one way of helping to improve the sustainability of irrigation systems around the world. However, soil water and solute transport properties and soil profile characteristics are often not adequately incorporated in the design and management of trickle systems. In this paper, we describe results of a simulation study designed to highlight the impacts of soil properties on water and solute transport from buried trickle emitters. The analysis addresses the influence of soil hydraulic properties, soil layering, trickle discharge rate, irrigation frequency, and timing of nutrient application on wetting patterns and solute distribution. We show that (1) trickle irrigation can improve plant water availability in medium and low permeability fine-textured soils, providing that design and management are adapted to account for their soil hydraulic properties, (2) in highly permeable coarse-textured soils, water and nutrients move quickly downwards from the emitter, making it difficult to wet the near surface zone if emitters are buried too deep, and (3) changing the fertigation strategy for highly permeable coarse-textured soils to apply nutrients at the beginning of an irrigation cycle can maintain larger amounts of nutrient near to and above the emitter, thereby making them less susceptible to leaching losses. The results demonstrate the need to account for differences in soil hydraulic properties and solute transport when designing irrigation and fertigation management strategies. Failure to do this will result in inefficient systems and lost opportunities for reducing the negative environmental impacts of irrigation.

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Functional magnetic resonance imaging (FMRI) analysis methods can be quite generally divided into hypothesis-driven and data-driven approaches. The former are utilised in the majority of FMRI studies, where a specific haemodynamic response is modelled utilising knowledge of event timing during the scan, and is tested against the data using a t test or a correlation analysis. These approaches often lack the flexibility to account for variability in haemodynamic response across subjects and brain regions which is of specific interest in high-temporal resolution event-related studies. Current data-driven approaches attempt to identify components of interest in the data, but currently do not utilise any physiological information for the discrimination of these components. Here we present a hypothesis-driven approach that is an extension of Friman's maximum correlation modelling method (Neurolmage 16, 454-464, 2002) specifically focused on discriminating the temporal characteristics of event-related haemodynamic activity. Test analyses, on both simulated and real event-related FMRI data, will be presented.

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This paper measured the variations in performance of small municipalities in the State of Sao Paulo, Brazil, regarding the technical efficiency in the use of public funds in public primary health care actions concerning the funding profile, in a scenario of fiscal federalism. Technical efficiency is one of the parameters of evaluation of public sector performance and was measured by means of Data Envelopment Analysis (DEA). The correlation analysis of DEA score was used to verify possible associations between technical efficiency and the funding profile of expenses with health care. The results showed that 6.41% of the municipalities were considered efficient. They also showed that the level of municipality dependence to inter-governmental general purpose grants and the national health funding specific purpose grants have negative correlation with efficiency scores.

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The stock market suffers uncertain relations throughout the entire negotiation process, with different variables exerting direct and indirect influence on stock prices. This study focuses on the analysis of certain aspects that may influence these values offered by the capital market, based on the Brazil Index of the Sao Paulo Stock Exchange (Bovespa), which selects 100 stocks among the most traded on Bovespa in terms of number of trades and financial volume. The selected variables are characterized by the companies` activity area and the business volume in the month of data collection, i.e. April/2007. This article proposes an analysis that joins the accounting view of the stock price variables that can be influenced with the use of multivariate qualitative data analysis. Data were explored through Correspondence Analysis (Anacor) and Homogeneity Analysis (Homals). According to the research, the selected variables are associated with the values presented by the stocks, which become an internal control instrument and a decision-making tool when it comes to choosing investments.