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- Tiuganji, Natalia M., et al.
(författare)
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Eating Behavior (Duration, Content, and Timing) Among Workers Living under Different Levels of Urbanization
- 2020
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Ingår i: Nutrients. - : MDPI AG. - 2072-6643. ; 12:2
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Tidskriftsartikel (refereegranskat)abstract
- Urbanization has contributed to extended wakefulness, which may in turn be associated with eating over a longer period. Here, we present a field study conducted in four groups with different work hours and places of living in order to investigate eating behavior (duration, content, and timing). Anthropometric measures were taken from the participants (rural (n = 22); town (n = 19); city-day workers (n = 11); city-night workers (n = 14)). In addition, a sociodemographic questionnaire was self-answered and 24-h food recalls were applied for three days. The 24-h food recalls revealed that fat intake varied according to the groups, with the highest consumption by the city-day workers. By contrast, city-day workers had the lowest intake of carbohydrate, whereas the rural group had the highest. In general, all groups had some degree of inadequacy in food consumption. Eating duration was negatively correlated with total energy intake, fat, and protein consumption in the rural and town groups. There was a positive correlation between body mass index and eating duration in both city groups. The rural group had the earliest start time of eating, and this was associated with a lower body mass index. This study suggested that food content and timing, as well as eating duration, differed according to place of living, which in turn may be linked to lifestyle.
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- Pham, M.-T., et al.
(författare)
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Distances and Means of Direct Similarities
- 2014
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Ingår i: International Journal of Computer Vision. - : Springer-Verlag New York. - 0920-5691 .- 1573-1405. ; 112:3, s. 285-306
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Tidskriftsartikel (refereegranskat)abstract
- The non-Euclidean nature of direct isometries in a Euclidean space, i.e. transformations consisting of a rotation and a translation, creates difficulties when computing distances, means and distributions over them, which have been well studied in the literature. Direct similarities, transformations consisting of a direct isometry and a positive uniform scaling, present even more of a challenge—one which we demonstrate and address here. In this article, we investigate divergences (a superset of distances without constraints on symmetry and sub-additivity) for comparing direct similarities, and means induced by them via minimizing a sum of squared divergences. We analyze several standard divergences: the Euclidean distance using the matrix representation of direct similarities, a divergence from Lie group theory, and the family of all left-invariant distances derived from Riemannian geometry. We derive their properties and those of their induced means, highlighting several shortcomings. In addition, we introduce a novel family of left-invariant divergences, called SRT divergences, which resolve several issues associated with the standard divergences. In our evaluation we empirically demonstrate the derived properties of the divergences and means, both qualitatively and quantitatively, on synthetic data. Finally, we compare the divergences in a real-world application: vote-based, scale-invariant object recognition. Our results show that the new divergences presented here, and their means, are both more effective and faster to compute for this task.
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