11 resultados para Ranking

em Brock University, Canada


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This research illuminates the relationship between female adolescents' self-concept and their experience of physical education. This was accomplished through three stages of interviews and a Qsort. The topics through which the research was categorized included peer support, teachers as significant others, meaningful connections to the body, and curriculum content. During stage one female physical education specialists, curriculum coordinators, and adolescents were interviewed to develop Q-items for the Q-sort. The second stage Involved two groups of females between the ages of 12 and 14 years who participated in the Q-sort. The final stage involved an insight group that consisted of four Q-sort participants who interpreted the highest ranking Q-items. Critical to this research was giving these adolescents the opportunity to voice what was important to them. The results of the research included descriptions of the elements in physical education that were deemed most important by female adolescent students. The topics of "peer support" and "meaningful connections to the body" were ranked the highest. By interpreting the rich insights of the discussion group, it was found that peers were most influential to these young girls. Perceiving and bestowing respect were imperative in this stage of their lives.

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Adults and children can discriminate various emotional expressions, although there is limited research on sensitivity to the differences between posed and genuine expressions. Adults have shown implicit sensitivity to the difference between posed and genuine happy smiles in that they evaluate T-shirts paired with genuine smiles more favorably than T-shirts paired with posed smiles or neutral expressions (Peace, Miles, & Johnston, 2006). Adults also have shown some explicit sensitivity to posed versus genuine expressions; they are more likely to say that a model i?,feeling happy if the expression is genuine than posed. Nonetheless they are duped by posed expressions about 50% of the time (Miles, & Johnston, in press). There has been no published study to date in which researchers report whether children's evaluation of items varies with expression and there is little research investigating children's sensitivity to the veracity of facial expressions. In the present study the same face stimuli were used as in two previous studies (Miles & Johnston, in press; Peace et al., 2006). The first question to be addressed was whether adults and 7-year-olds have a cognitive understanding of the differences between posed and genuine happiness {scenario task). They evaluated the feelings of children who expressed gratitude for a present that they did or did not want. Results indicated that all participants had a fundamental understanding of the difference between real and posed happiness. The second question involved adults' and children's implicit sensitivity to the veracity of posed and genuine smiles. Participants rated and ranked beach balls paired with faces showing posed smiles, genuine smiles, and neutral expressions. Adults ranked.but did not rate beach balls paired with genuine smiles more favorably than beach balls paired with posed smiles. Children did not demonstrate implicit sensitivity as their ratings and rankings of beach balls did not vary with expressions; they did not even rank beach balls paired with genuine expressions higher than beach balls paired with neutral expressions. In the explicit (show/feel) task, faces were presented without the beach balls and participants were first asked whether each face was showing happy and then whether each face wasfeeling happy. There were also two matching trials that presented two faces at once; participants had to indicate which person was actuallyfeeling happy. In the show condition both adults and 7-year-olds were very accurate on genuine and neutral expressions but made some errors on posed smiles. Adults were fooled about 50% of the time by posed smiles in thefeel condition (i.e., they were likely to say that a model posing happy was really feeling happy) and children were even less accurate, although they showed weak sensitivity to posed versus genuine expressions. Future research should test an older age group of children to determine when explicit sensitivity to posed versus genuine facial expressions becomes adult-like and modify the ranking task to explore the influence of facial expressions on object evaluations.

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One hundred and thirty-three parents of students new ~o ~ive independent schools in Ontario wer. surveyed to inve~tigate school choice behaviour. Paren~s were asKed to indicate their reasons for changing schooling, ~he criteria for selection o~ a school and the nature of the search process. Parents were also asKed to ranK speci~ic precipitants for change and criteria for choice. Spearman RanK Correla.tion tests were run comparing precipitants for change and criteria for choice for the entire sample and sub-groups based on socioeconomic status, gender of the child and family size. No signl~icant differences were found between the various $ub-groups, however, there was a strong positive correlation between precipitants for change and criteria for choice.Chi sq,uare tests were run compa.ring the number of information sources utilized in the search process, and a comparison was made between the importance of the va.rious sources of information. The majority of parents were classified as ac~ive searchers, researching one alternative more carefully than others. Socioeconomic status was the only factor to have a sign ific:ant- effect on the ranKing of information sources.

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Most of this volume consists of correspondence between high ranking U.S. and British statesmen. E.g., James Madison, James Monroe, The Marquess Wellesley (brother of Arthur Wellesley, Duke of Wellington). The discussion centers around the War of 1812. Also includes facsimilies of treaties signed between Great Britain and Sweden, Russia and Sicily.

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Complex networks have recently attracted a significant amount of research attention due to their ability to model real world phenomena. One important problem often encountered is to limit diffusive processes spread over the network, for example mitigating pandemic disease or computer virus spread. A number of problem formulations have been proposed that aim to solve such problems based on desired network characteristics, such as maintaining the largest network component after node removal. The recently formulated critical node detection problem aims to remove a small subset of vertices from the network such that the residual network has minimum pairwise connectivity. Unfortunately, the problem is NP-hard and also the number of constraints is cubic in number of vertices, making very large scale problems impossible to solve with traditional mathematical programming techniques. Even many approximation algorithm strategies such as dynamic programming, evolutionary algorithms, etc. all are unusable for networks that contain thousands to millions of vertices. A computationally efficient and simple approach is required in such circumstances, but none currently exist. In this thesis, such an algorithm is proposed. The methodology is based on a depth-first search traversal of the network, and a specially designed ranking function that considers information local to each vertex. Due to the variety of network structures, a number of characteristics must be taken into consideration and combined into a single rank that measures the utility of removing each vertex. Since removing a vertex in sequential fashion impacts the network structure, an efficient post-processing algorithm is also proposed to quickly re-rank vertices. Experiments on a range of common complex network models with varying number of vertices are considered, in addition to real world networks. The proposed algorithm, DFSH, is shown to be highly competitive and often outperforms existing strategies such as Google PageRank for minimizing pairwise connectivity.

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Hub Location Problems play vital economic roles in transportation and telecommunication networks where goods or people must be efficiently transferred from an origin to a destination point whilst direct origin-destination links are impractical. This work investigates the single allocation hub location problem, and proposes a genetic algorithm (GA) approach for it. The effectiveness of using a single-objective criterion measure for the problem is first explored. Next, a multi-objective GA employing various fitness evaluation strategies such as Pareto ranking, sum of ranks, and weighted sum strategies is presented. The effectiveness of the multi-objective GA is shown by comparison with an Integer Programming strategy, the only other multi-objective approach found in the literature for this problem. Lastly, two new crossover operators are proposed and an empirical study is done using small to large problem instances of the Civil Aeronautics Board (CAB) and Australian Post (AP) data sets.

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The Portuguese community is one of the largest diasporic groups in the Greater Toronto Area and the choice of retention and transmission of language and culture to Luso-Canadians is crucial to the development and sustainability of the community. The overall objective of this study is to learn about the factors that influence Luso-Canadian mothers’ inclination to teach Portuguese language and cultural retention to their children. To explore this topic I employed a qualitative research design that included in-depth interviews conducted in 2012 with six Luso-Canadian mothers. Three central arguments emerged from the findings. First, Luso-Canadian mothers interviewed posses a pronounced desire for their children to succeed academically, and to provide opportunities that their children that they did not have. Second, five of the mothers attempt to achieve this mothering objective partly by disconnecting from their Portuguese roots, and by disassociating their children from the Portuguese language and culture. Third, the disconnection they experience and enact is influenced by the divisions evident in the Portuguese community in the GTA that divides regions and hierarchically ranks dialects, and groups. I conclude that the children in these households inevitably bear the prospects of maintaining a vibrant Portuguese community in the GTA and I propose that actions by the community in ranking dialects influence mothers’ decisions about transmitting language and culture to their children.

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Understanding the relationship between genetic diseases and the genes associated with them is an important problem regarding human health. The vast amount of data created from a large number of high-throughput experiments performed in the last few years has resulted in an unprecedented growth in computational methods to tackle the disease gene association problem. Nowadays, it is clear that a genetic disease is not a consequence of a defect in a single gene. Instead, the disease phenotype is a reflection of various genetic components interacting in a complex network. In fact, genetic diseases, like any other phenotype, occur as a result of various genes working in sync with each other in a single or several biological module(s). Using a genetic algorithm, our method tries to evolve communities containing the set of potential disease genes likely to be involved in a given genetic disease. Having a set of known disease genes, we first obtain a protein-protein interaction (PPI) network containing all the known disease genes. All the other genes inside the procured PPI network are then considered as candidate disease genes as they lie in the vicinity of the known disease genes in the network. Our method attempts to find communities of potential disease genes strongly working with one another and with the set of known disease genes. As a proof of concept, we tested our approach on 16 breast cancer genes and 15 Parkinson's Disease genes. We obtained comparable or better results than CIPHER, ENDEAVOUR and GPEC, three of the most reliable and frequently used disease-gene ranking frameworks.

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In this thesis we are going to analyze the dictionary graphs and some other kinds of graphs using the PagerRank algorithm. We calculated the correlation between the degree and PageRank of all nodes for a graph obtained from Merriam-Webster dictionary, a French dictionary and WordNet hypernym and synonym dictionaries. Our conclusion was that PageRank can be a good tool to compare the quality of dictionaries. We studied some artificial social and random graphs. We found that when we omitted some random nodes from each of the graphs, we have not noticed any significant changes in the ranking of the nodes according to their PageRank. We also discovered that some social graphs selected for our study were less resistant to the changes of PageRank.

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As a result of mutation in genes, which is a simple change in our DNA, we will have undesirable phenotypes which are known as genetic diseases or disorders. These small changes, which happen frequently, can have extreme results. Understanding and identifying these changes and associating these mutated genes with genetic diseases can play an important role in our health, by making us able to find better diagnosis and therapeutic strategies for these genetic diseases. As a result of years of experiments, there is a vast amount of data regarding human genome and different genetic diseases that they still need to be processed properly to extract useful information. This work is an effort to analyze some useful datasets and to apply different techniques to associate genes with genetic diseases. Two genetic diseases were studied here: Parkinson’s disease and breast cancer. Using genetic programming, we analyzed the complex network around known disease genes of the aforementioned diseases, and based on that we generated a ranking for genes, based on their relevance to these diseases. In order to generate these rankings, centrality measures of all nodes in the complex network surrounding the known disease genes of the given genetic disease were calculated. Using genetic programming, all the nodes were assigned scores based on the similarity of their centrality measures to those of the known disease genes. Obtained results showed that this method is successful at finding these patterns in centrality measures and the highly ranked genes are worthy as good candidate disease genes for being studied. Using standard benchmark tests, we tested our approach against ENDEAVOUR and CIPHER - two well known disease gene ranking frameworks - and we obtained comparable results.

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The wrestler's name is Bronko Nagurski and the number stamped on the reverse of the card is 764. He was born in Rainy River, Ontario and wrestled from 1939 to 1960. He also played football for the Chicago Bears as a fullback under George Halas in the 1930s. His honours include Pro Football Hall of Fame, College Football Hall of Fame, Canadian Wrestling Hall of Fame. He was voted 35th of the top 100 football players of all time (the highest ranking non-American on the list).