Youth Expression with Video Surveillance Technology

This qualitative study examines five young Afro-Franco Caribbean males in the Diaspora and their experiences with systems of technology as a tool of oppression and liberation. The study utilized interpretive biography and participatory video research to examine the issues of identity, power/control, surveillance technology, love and freedom. The study made use of a number of data collection methods including interviews, round table discussions, and personal narratives. A hermeneutic theoretical framework is employed to develop an objective view of the problems facing Afro-Franco Caribbean males in the schools and community. The purpose of the study is to provide an environment and new media technology that Afro-Franco Caribbean males can use to engage and discuss their views on issues mentioned above and to ultimately develop a video project to share with the community. Moreover, the study sought to examine an epistemological approach (Creolization) that young black males, particularly Afro-Franco-Caribbean males, might use to communicate, document, and share their everyday experiences in the Diaspora. The findings in the study reveal that the participants are experiencing: (a) a lack of community involvement in the urban space they currently reside, (b) frustration with the perspective of their home country, Haiti, that is commonly shown in mainstream media, and (c) ridicule, shame, and violence in the spaces (school and community) that should be safe. The study provides the community (both local and scholarly) with an opportunity to hear the voices and concerns of youth in the urban space. In addition the study suggests a need for schools to create a critical pedagogical curriculum in which power can be democratically shared.

An examination of factors that influence entrepreneurial intention of high school students in Kenya

Abstract Considerable research has been carried out on entrepreneurship in efforts to understand its incidence in order to influence and maximize its benefits. Essentially, researchers and policy makers have sought to understand the link between individuals and business creation: Why some people start businesses while others do not. The research indicates that personality traits, individual background factors and association of entrepreneurship with career choice and small business enterprises, cannot sufficiently explain entrepreneurship. It is recognized that entrepreneurship is an intentional process and based on Ajzen’s Theory of Planned Behavior, the most defining characteristic of entrepreneurship is the intention to start a business. The purpose of this study was, therefore, to examine factors that influence entrepreneurial intention in high school students in Kenya. Specifically, the study aimed at determining if there were relationships between the perceptions of desirability, and feasibility of entrepreneurship with entrepreneurial intention of the students, identifying any difference in these perceptions with students of different backgrounds, and developing a model to predict entrepreneurship in the students. The study, therefore, tested how well Ajzen’s Theory of Planned Behavior applied in the Kenyan situation. A questionnaire was developed and administered to 969 final year high school students at a critical important point in their career decision making. Participants were selected using a combined convenience and random sampling technique, considering gender, rural/urban location, cost, and accessibility. Survey was the major method of data collection. Data analysis methods included descriptive statistics, correlation, ANOVA, factor analysis, effect size, and regression analysis. iii The findings of this study corroborate results from past studies. Attitudes are found to influence intention, and the attitudes to be moderated by individual background factors. Perceived personal desirability of entrepreneurship was found to have the greatest influence on entrepreneurial intention and perceived feasibility the lowest. The study findings also showed that perceived social desirability and feasibility of entrepreneurship contributed to perception of personal desirability, and that the background factors, including gender and prior experience, influenced entrepreneurial intention both directly and indirectly. In addition, based on the literature reviewed, the study finds that entrepreneurship promotion requires reduction of the high small business mortality rate and creation of both entrepreneurs and entrepreneurial opportunities (Kruger, 2000; Shane & Venkataraman, 2000). These findings have theoretical and practical implications for researchers, policy makers, teachers, and other entrepreneurship practitioners in Kenya.

A study of computational methods to analyze gene expression data

The recent advent of new technologies has led to huge amounts of genomic data. With these data come new opportunities to understand biological cellular processes underlying hidden regulation mechanisms and to identify disease related biomarkers for informative diagnostics. However, extracting biological insights from the immense amounts of genomic data is a challenging task. Therefore, effective and efficient computational techniques are needed to analyze and interpret genomic data. In this thesis, novel computational methods are proposed to address such challenges: a Bayesian mixture model, an extended Bayesian mixture model, and an Eigen-brain approach. The Bayesian mixture framework involves integration of the Bayesian network and the Gaussian mixture model. Based on the proposed framework and its conjunction with K-means clustering and principal component analysis (PCA), biological insights are derived such as context specific/dependent relationships and nested structures within microarray where biological replicates are encapsulated. The Bayesian mixture framework is then extended to explore posterior distributions of network space by incorporating a Markov chain Monte Carlo (MCMC) model. The extended Bayesian mixture model summarizes the sampled network structures by extracting biologically meaningful features. Finally, an Eigen-brain approach is proposed to analyze in situ hybridization data for the identification of the cell-type specific genes, which can be useful for informative blood diagnostics. Computational results with region-based clustering reveals the critical evidence for the consistency with brain anatomical structure.