7 resultados para Heteroskedasticity-based identification
em Brock University, Canada
Resumo:
The evolving antimicrobial resistance coupled with a recent increase in incidence highlights the importance of reducing gonococcal transmission. Establishing novel risk factors associated with gonorrhea facilitates the development of appropriate prevention and disease control strategies. Sexual Network Analysis (NA), a novel research technique used to further understand sexually transmitted infections, was used to identify network-based risk factors in a defined region in Ontario, Canada experiencing an increase in the incidence of gonorrhea. Linear network structures were identified as important reservoirs of gonococcal transmission. Additionally, a significant association between a central network position and gonorrhea was observed. The central participants were more likely to be younger, report a greater number of risk factors, engage in anonymous sex, have multiple sex partners in the past six months and have sex with the same sex. The network-based risk factors identified through sexual NA, serving as a method of analyzing local surveillance data, support the development of strategies aimed at reducing gonococcal spread.
Resumo:
A Gram negative aerobic flagellated bacterium with fungal growth inhibitory properties was isolated from a culture of Trichoderma harzianum. According to its cultural characteristics and biochemical properties it was identified as a strain of Alcaligenes (aeca/is Castellani and Chalmers. Antisera prepared in Balbc mice injected with live and heat-killed bacterial cells gave strong reactions with the homologous immunogen and with ATCC 15554, the type strain of A. taeca/is, but not with Escherichia coli or Enterobacter aerogens in immunoprecipitation and dot immunobinding assays. Growth of Botrytis cinerea Pers. and several other fungi was significantly affected when co-cultured with A. taeca/is on solid media. Its detrimental effect on germination and growth of B. cinerea has been found to be associated with antifungal substances produced by the bacterium and released into the growth medium. A biotest for the antibiotic substances, based on their inhibitory effect on germination of B. cinerea conidia, was developed. This biotest was used to study the properties of these substances, the conditions in which they are produced, and to monitor the steps of their separation during extraction procedures. It has been found that at least two substances could be involved in the antagonistic interaction. One of these is a basic volatile substance and has been identified as ammonia. The other substance is a nonvolatile, dialysable, heat stable, polar compound released into the growth medium. After separation of growth medium samples by Sephadex G-10 column chromatography a single peak with a molecular weight below 700 Daltons exhibited inhibitory activity. From its behaviour in electrophoretic separation in agarose gels it seems that this is a neutral or slightly positively charged.
Resumo:
This study had three purposes related to the effective implem,entation and practice of computer-mediated online distance education (C-MODE) at the elementary level: (a) To identify a preliminary framework of criteria 'or guidelines for effective implementation and practice, (b) to identify areas ofC-MODE for which criteria or guidelines of effectiveness have not yet been developed, and (c) to develop an implementation and practice criteria questionnaire based on a review of the distance education literature, and to use the questionnaire in an exploratory survey of elementary C-MODE practitioners. Using the survey instrument, the beliefs and attitudes of 16 elementary C'- MODE practitioners about what constitutes effective implementation and practice principles were investigated. Respondents, who included both administrators and instructors, provided information about themselves and the program in which they worked. They rated 101 individual criteria statenlents on a 5 point Likert scale with a \. point range that included the values: 1 (Strongly Disagree), 2 (Disagree), 3 (Neutral or Undecided), 4 (Agree), 5 (Strongly Agree). Respondents also provided qualitative data by commenting on the individual statements, or suggesting other statements they considered important. Eighty-two different statements or guidelines related to the successful implementation and practice of computer-mediated online education at the elementary level were endorsed. Response to a small number of statements differed significantly by gender and years of experience. A new area for investigation, namely, the role ofparents, which has received little attention in the online distance education literature, emerged from the findings. The study also identified a number of other areas within an elementary context where additional research is necessary. These included: (a) differences in the factors that determine learning in a distance education setting and traditional settings, (b) elementary students' ability to function in an online setting, (c) the role and workload of instructors, (d) the importance of effective, timely communication with students and parents, and (e) the use of a variety of media.
Resumo:
This study probed for an answer to the question, "How do you identify as early as possible those students who are at risk of failing or dropping out of college so that intervention can take place?" by field testing two diagnostic instruments with a group of first semester Seneca College Computer Studies students. In some respects, the research approach was such as might be taken in a pilot study. Because of the complexity of the issue, this study did not attempt to go beyond discovery, understanding and description. Although some inferences may be drawn from the results of the study, no attempt was made to establish any causal relationship between or among the factors or variables represented here. Both quantitative and qualitative data were gathered during. four resea~ch phases: background, early identification, intervention, and evaluation. To gain a better understanding of the problem of student attrition within the School of Computer Studies at Seneca College, several methods were used, including retrospective analysis of enrollment statistics, faculty and student interviews and questionnaires, and tracking of the sample population. The significance of the problem was confirmed by the results of this study. The findings further confirmed the importance of the role of faculty in student retention and support the need to improve the quality of teacher/student interaction. As well, the need __f or ~~ills as~e:ss_~ent foll,,-~ed }JY supportiv e_c_ounsell~_I'l9_ ~~d_ __ placement was supported by the findings from this study. strategies for reducing student attrition were identified by faculty and students. As part of this study, a project referred to as "A Student Alert project" (ASAP) was undertaken at the School of Computer Studies at Seneca College. Two commercial diagnostic instruments, the Noel/Levitz College Student Inventory (CSI) and the Learning and Study Strategies Inventory (LASSI), provided quantitative data which were subsequently analyzed in Phase 4 in order to assess their usefulness as early identification tools. The findings show some support for using these instruments in a two-stage approach to early identification and intervention: the CSI as an early identification instrument and the LASSI as a counselling tool for those students who have been identified as being at risk. The findings from the preliminary attempts at intervention confirmed the need for a structured student advisement program where faculty are selected, trained, and recognized for their advisor role. Based on the finding that very few students acted on the diagnostic results and recommendations, the need for institutional intervention by way of intrusive measures was confirmed.
Resumo:
This study probed for an answer to the question, "How do you identify as early as possible those students who are at risk of failing or dropping out of college so that intervention can take place?" by field testing two diagnostic instruments with a group of first semester Seneca College Computer ,Studies students. In some respects, the research approach was such as might be taken in a pilot study_ Because of the complexity of the issue, this study did not attempt to go beyond discovery, understanding and description. Although some inferences may be drawn from the results of the study, no attempt was made to establish any causal relationship between or among the factors or variables represented here. Both quantitative and qualitative data were gathered during four resea~ch phases: background, early identification, intervention, and evaluation. To gain a better understanding of the problem of student attrition within the School of Computer Studies at Seneca College, several methods were used, including retrospective analysis of enrollment statistics, faculty and student interviews and questionnaires, and tracking of the sample population. The significance of the problem was confirmed by the results of this study. The findings further confirmed the importance of the role of faculty in student retention and support the need to improve the quality of teacher/student interaction. As well, the need for skills assessmen~-followed by supportive counselling, and placement was supported by the findings from this study. strategies for reducing student attrition were identified by faculty and students. As part of this study, a project referred to as "A Student Alert Project" (ASAP) was undertaken at the School of Computer Studies at Seneca college. Two commercial diagnostic instruments, the Noel/Levitz College Student Inventory (CSI) and the Learning and Study Strategies Inventory (LASSI), provided quantitative data which were subsequently analyzed in Phase 4 in order to assess their usefulness as early identification tools. The findings show some support for using these instruments in a two-stage approach to early identification and intervention: the CSI as an early identification instrument and the LASSI as a counselling tool for those students who have been identified as being at risk. The findings from the preliminary attempts at intervention confirmed the need for a structured student advisement program where faculty are selected, trained, and recognized for their advisor role. Based on the finding that very few students acted on the diagnostic results and recommendations, the need for institutional intervention by way of intrusive measures was confirmed.
Resumo:
The purpose of the present study was first to determine what influences international students' perceptions of prejudice, and secondly to examine how perceptions of prejudice would affect international students' group identification. Variables such as stigma vulnerability and contact which have been previously linked with perceptions of prejudice and intergroup relations were re-examined (Berryman-Fink, 2006; Gilbert, 1998; Nesdale & Todd, 2000), while variables classically linked to prejudicial attitudes such as right-wing authoritarianism and openness to experience were explored in relation to perceptions of prejudice. Furthermore, the study examined how perceptions of prejudice might affect the students' identification choices, by testing two opposing models. The first model was based on the motivational nature of social identity theory (Tajfel & Turner, 1986) while the second model was based on the cognitive nature of self-categorization theory/ rejection-identification model (Turner, Hogg, Oakes, Reicher, & Wetherell, 1987; Schmitt, Spears, & Branscombe,2003). It was hypothesized that stigma vulnerability, right-wing authoritarianism, openness to experience and contact would predict both personal and group perceptions of prejudice. It was also hypothesized that perceptions of prejudice would predict group identification. If the self-categorizationlrejection-identification model was supported, international students would identify with the international students. If the social mobility strategy was supported, international students would identify with the university students group. Participants were 98 international students who filled out questionnaires on the Brock University Psychology Department Website. The first hypothesis was supported. The combination of stigma vulnerability, right-wing authoritarianism, openness to experience and contact predicted both personal and group prejudice perceptions of international students. Furthermore, the analyses supported the self-categorizationlrejectionidentification model. International identification was predicted by the combination of personal and group prejudice perceptions of international students.
Resumo:
Remote sensing techniques involving hyperspectral imagery have applications in a number of sciences that study some aspects of the surface of the planet. The analysis of hyperspectral images is complex because of the large amount of information involved and the noise within that data. Investigating images with regard to identify minerals, rocks, vegetation and other materials is an application of hyperspectral remote sensing in the earth sciences. This thesis evaluates the performance of two classification and clustering techniques on hyperspectral images for mineral identification. Support Vector Machines (SVM) and Self-Organizing Maps (SOM) are applied as classification and clustering techniques, respectively. Principal Component Analysis (PCA) is used to prepare the data to be analyzed. The purpose of using PCA is to reduce the amount of data that needs to be processed by identifying the most important components within the data. A well-studied dataset from Cuprite, Nevada and a dataset of more complex data from Baffin Island were used to assess the performance of these techniques. The main goal of this research study is to evaluate the advantage of training a classifier based on a small amount of data compared to an unsupervised method. Determining the effect of feature extraction on the accuracy of the clustering and classification method is another goal of this research. This thesis concludes that using PCA increases the learning accuracy, and especially so in classification. SVM classifies Cuprite data with a high precision and the SOM challenges SVM on datasets with high level of noise (like Baffin Island).