82 resultados para Practical corporal


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Perfect information is seldom available to man or machines due to uncertainties inherent in real world problems. Uncertainties in geographic information systems (GIS) stem from either vague/ambiguous or imprecise/inaccurate/incomplete information and it is necessary for GIS to develop tools and techniques to manage these uncertainties. There is a widespread agreement in the GIS community that although GIS has the potential to support a wide range of spatial data analysis problems, this potential is often hindered by the lack of consistency and uniformity. Uncertainties come in many shapes and forms, and processing uncertain spatial data requires a practical taxonomy to aid decision makers in choosing the most suitable data modeling and analysis method. In this paper, we: (1) review important developments in handling uncertainties when working with spatial data and GIS applications; (2) propose a taxonomy of models for dealing with uncertainties in GIS; and (3) identify current challenges and future research directions in spatial data analysis and GIS for managing uncertainties.

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Realising memory intensive applications such as image and video processing on FPGA requires creation of complex, multi-level memory hierarchies to achieve real-time performance; however commerical High Level Synthesis tools are unable to automatically derive such structures and hence are unable to meet the demanding bandwidth and capacity constraints of these applications. Current approaches to solving this problem can only derive either single-level memory structures or very deep, highly inefficient hierarchies, leading in either case to one or more of high implementation cost and low performance. This paper presents an enhancement to an existing MC-HLS synthesis approach which solves this problem; it exploits and eliminates data duplication at multiple levels levels of the generated hierarchy, leading to a reduction in the number of levels and ultimately higher performance, lower cost implementations. When applied to synthesis of C-based Motion Estimation, Matrix Multiplication and Sobel Edge Detection applications, this enables reductions in Block RAM and Look Up Table (LUT) cost of up to 25%, whilst simultaneously increasing throughput.

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In many European shelters, dogs may spend many years confined. A poor environment and inappropriate management may lead to a low quality of life. The absence of harmonised European regulatory frameworks defining the minimum requirements for shelter facilities makes the definition of welfare standards for kennelled dogs challenging. Here, a new protocol was developed and tested to help identify the main welfare issues for shelter dogs. Twenty-six indicators were identified including management, resource and animal based measures. Accuracy and interobserver reliability were checked between four assessors. The protocol was applied in 29 shelters (n=1308 dogs) in six European countries. Overall prevalence of poor health conditions was below 10%. Test-retest reliability and validity of the protocol were investigated with encouraging results. A logistic regression was carried out to assess the potential of the protocol as a tool to identify welfare hazards in shelter environments. Inappropriate space allowance, for example, was found to be a risk factor potentially affecting the animal's cleanliness, skin condition and body condition. The protocol was designed to be concise and easy to implement. Systematic data collection could help identify welfare problems that are likely to arise in certain shelter designs and thus determine improvement in animal care standards.

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Diagnosis of glaucoma and delivery of effective treatment is difficult everywhere, but additional challenges are evident in less affluent parts of the world, where the largest numbers of patients with this disease are living. The problems of providing good glaucoma care are examined with especial reference to south-east Asia including China and India and countries in sub-Saharan Africa. The relatively low priority given to glaucoma by vision-related and other nongovernmental organizations (NGOs) due to difficulties faced in delivering effective glaucoma screening and therapeutic interventions are discussed, together with possible future directions for increasing resources and priority for glaucoma care in poor areas.

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Researchers have proposed 1-factor, 2-factor, and bifactor solutions to the 12-item Consideration of Future Consequences Scale (CFCS-12). In order to overcome some measurement problems and to create a robust and conceptually useful two-factor scale the CFCS-12 was recently modified to include two new items and to become the CFCS-14. Using a University sample, we tested four competing models for the CFCS-14: (a) a 12-item unidimensional model, (b) a model fitted for two uncorrelated factors (CFC-Immediate and CFC-Future), (c) a model fitted for two correlated factors (CFC-I and CFC-F), and (d) a bifactor model. Results suggested that the addition of the two new items has strengthened the viability of a two factor solution of the CFCS-14. Results of linear regression models suggest that the CFC-F factor is redundant. Further studies using alcohol and mental health indicators are required to test this redundancy.