2 resultados para ANCA

em Deakin Research Online - Australia


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We present a unified formalism for representing maps and using them for constructing plans of navigation for an autonomous agent. The foundation of this work lies in addressing key questions that an agent is confronted with when navigating. That is, besides the main task of how to reach the intended destination from the current position, the agent faces other questions like: where am I? what landmarks can I see? where is my destination relative to me and the landmarks I am seeing? Fundamental to this representation is the use of visual landmarks, which are used as pivotal points in the landscape being described. Further, in the representation of spatial information and navigation there are three different viewpoints: first, the localized representation from the viewpoint of a sighted, mobile agent; second, the static representation seen by the map-maker; and third, the view of an external agent giving directions on the basis of his own experience/knowledge. The major contribution of this map model and the associated navigation method lies in the framework which unifies these three different points of view. This unification enables the agent to make no distinction in terms of following implicit instructions contained in a map and the directions given by external agents.

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Accurate assessment of physical activity energy expenditure (PAEE) among adolescents is important for surveillance, evaluating interventions, and understanding the relation between energy balance and normal physiological and behavioral growth and development. The purpose of this study was to examine the validity of the Short Questionnaire to Assess Health-Enhancing Physical Activity (SQUASH)13 for measuring PAEE among adolescents. Methods: The participants were seventeen adolescents (9 females; Mean age = 17.53; SD = 0.62). Energy expenditure was measured during a 9-day period with doubly labeled water (DLW). The SQUASH was self-administered on the morning of the 10th day and assessed commuting activities, leisure time activities, household activities, and activities at work and school over the previous 9 days. Results: A Bland-Altman plot indicated that the SQUASH underestimated PAEE compared with DLW by a mean difference of 126 kcal·d-1 (95% limits of agreement:-1,207 to 1,459 kcal·d-1), representative of a 10% underestimation. The Spearman rank order correlation coefficient showed there was a significant association between the SQUASH and DLW (r =.50, P =.04), for estimating PAEE. Conclusion: When using a sample of highly active adolescents, the SQUASH is a valid self-report tool for measuring PAEE at the group and individual rank order level.