Overweight and obesity in Canada has significantly increased during the last three decades, paralleled by increased intake of fat and sugar particularly sugary beverages leading to higher level of energy intake, as well as reduction in physical activity. Canadian Community Health Survey, Cycle 2.2, 2004 (CCHS 2.2), provides the opportunity to evaluate beverage intakes of Canadians in relation to overweight and obesity using Body Mass Index (BMI).<p> To examine the association between sugar-sweetened beverages and BMI in Canadian adults, we used data from CCHS 2.2 (n=14,304, aged >18 year and <65 year) in which dietary intake was assessed using 24-h recall. In various steps, data on beverage consumption were identified, coded and classified. Using descriptive statistics, we determined total gram intake and the contribution of each beverage to total energy intake among age/sex groups. To determine the most suitable patterns of beverage consumptions among Canadian adults, a cluster analysis K-means method was applied. Males and females were classified into distinct clusters based on the dominant pattern of beverage intakes. Finally, step-wise logistic regression models were used to determine associations between sugar-sweetened beverages and BMI, controlling for age, marital status, income, education, physical activity, total energy intake, immigration status, smoking habits and ethnicity. To account for complex survey design, all data were weighted and bootstrapped.<p> BMI in women with predominant fruit drink pattern (791.1±32.9 g) was significantly higher than those with no dominant pattern in beverage consumption (28.3±1 vs. 26.8±0.3 respectively, P<0.001). In women, high intake of fruit drinks was a significant predictor of overweight (OR=1.84, 95% C.I:1.06-3.20), obesity (OR=2.55, 95% C.I:1.46-4.47) and overweight/obesity (OR=2.05, 95% C.I:1.29-3.25). In men, mean BMI was not different among beverage consumption clusters and none of the beverages was a predictor for overweight and obesity. For the first time, in a nationally representative data, we report association of sugar-sweetened beverages and overweight and obesity in Canadian women.

Under the mechanism of natural selection, creatures are forced to evolve naturally in order to survive. Keen-sighted jumping spiders have long been considered as the main predation pressure of terrestrial arthropod. Many species benefit from mimicking the appearance of jumping spider. In this study according to the experimental data from Wang (2009b), a data analysis is undertaken concerning male Ptocasius strupifer¡¦s behavior to different subject groups, namely, male Ptocasius strupifer, female Ptocasius strupifer, male Plexippus paykulli, female Plexippus paykulli, Cataclysta angulata and Eugauria albidentata, so as to investigate the jumping spider mimicry of Eugauria albidentata. In this work, our interest is to compare the behavior of male Ptocasius strupifer on Eugauria albidentata with there of the other five groups mentioned above, and identify which one is the most similar to there of Eugauria albidentata . We use different statistical methods, i.e. likelihood ratio test, factor analysis and cluster analysis to evaluate the closeness of the behavior between different groups. According to the analysis result, it shows that the behavior of Ptocasius strupifer towards Eugauria albidentata is more similar to those of both female Ptocasius strupifer and female Plexippus paykulli. Moreover there is a wide discrepancy between Eugauria albidentata and Cataclysta angulata, although both of them belong to Musotiminae.

Thesis (M.S.) -- New Jersey Institute of Technology, Dept. of Computer and Information Science, 2000. / Includes bibliographical references. Also available via the World Wide Web.

Thesis (M.A.)--Western Kentucky University, 2009 / Includes bibliographical references (leaves 28-31).

Thesis (Ph. D.)--Rutgers University, 2009. / "Graduate Program in Computer Science." Includes bibliographical references (p. 78-82).

Thesis (Ph. D.)--University of Texas at Austin, 2002. / Vita. Includes bibliographical references (leaves 191-214). Available also in a digital version from Dissertation Abstracts.

The task of multi-body motion segmentation refers to segmenting feature trajectories in a sequence of images according to their 3D motion affinity without knowing the number of motions in advance. It is critical for understanding and reconstructing a dynamic scene. This problem essentially consists of two subproblems, segmenting features and detecting the number of motions. While the state-of-the-art LBF algorithm achieves segmentation accuracy as high as 96.5%, it is still disturbed by a phenomenon called over-locality. A novel mode seeking algorithm with an adaptive distance measure is proposed to avoid this problem, and improves the accuracy to 98.1%. The LBF algorithm is incapable of detecting the number of motions itself. A randomized version of the mode seeking algorithm is presented, which could detect the number as well as preserve satisfactory segmentation accuracy. To detect the number of motions, a kernel optimization method locates it via kernel alignment. However, it suffers from over-locality and over-detects the number of motions. An intersection measure and two mutual information measures are presented to solve this problem. Using these measures, the proposed clustering consensus framework recasts the motion number detection problem to a clustering consensus problem. It extends the kernel optimization method from two-clustering consensus to multiple-clustering consensus. A large number of experiments and comparisons have been done, and convincing results are obtained. / published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

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Thesis (M.S.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains vi, 59 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 57-59).

Thesis (M.S.)--Rochester Institute of Technology, 2004. / Typescript. Includes bibliographical references (leaves 60-65).