Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Taenia solium transmission in a rural community in Honduras : an examination of risk factors and knowledge

Taenia soliurn taeniasis and cysticercosis are recognized as a major public health problem in Latin America. T. soliurn transmission not only affects the health of the individual, but also social and economic development, perpetuating the cycle of poverty. To determine prevalence rates, population knowledge and risk factors associated with transmission, an epidemiological study was undertaken in the rural community of Jalaca. Two standardized questionnaires were used to collect epidemiological and T. soli urn general knowledge data. Kato-Katz technique and an immunoblot assay (EITB) were used to determine taeniasis and seroprevalence, respectively. In total, 139 individuals belonging to 56 households participated in the study. Household characteristics were consistent with conditions of poverty of rural Honduras: 21.4% had no toilet or latrines, 19.6% had earthen floor, and 51.8% lacked indoor tap water. Pigs were raised in 46.4% of households, of which 70% allowed their pigs roaming freely. A human seroprevalence rate of 18.7% and a taeniasis prevalence rate of 2.4% were found. Only four persons answered correctly 2: 6 out of ten T. soliurn knowledge questions, for an average passing score of 2.9%. In general, a serious gap exists in knowledge regarding how humans acquire the infections, especially neurocysticercosis was identified. After regression analysis, the ability to recognize adult tapeworms and awareness of the clinical importance of taeniasis, were found to be significant risk factors for T. soliurn seropositivity. These results demonstrate a high level of transmission and a low level of kn~,wledge about Taenia soliurn in Jalaca. Consequently, intervention measures integrated with health education are necessary to decrease the burden caused by this parasite.

Organizational capacity and knowledge transfer : a qualitative case study of the 2007 Canada Winter Games host society

Understanding and managing the knowledge transfer process in sport organizations is an essential component to enhance organizational capacity. Very little research on either capacity or knowledge transfer within a sport organization exists. Consequently, the purpos e of this qualitative case study was to, examine the transfer of knowledge process within a major games host society. Specifically, two research goals guided the study: 1) To develop a model to explain a knowledge t r ans f e r process in a non-profit ma jor games hos t organization and 2) To examine the relevance of the model to a Canada Games Hos t Society. Data we r e collected from interviews with middle and senior level volunteers as well as senior s t a f f members (n= 27), document s and observations. The findings indicated three barriers to knowledge transfer: structural, systemic, and cultural. As a result of the findings a revised model for knowledge transfer wa s proposed that included modifications related to the direction of knowledge flow, timing of the knowledge transfer process, and group inter-relations. Implications identified the importance of intuition managers, time and organizational levels for successful knowledge transfer. Recommendations for future host societies and the Canada Games Council are presented.

Exploring Teacher Candidates’ Experience, Perception, and Knowledge of Multicultural Education in Two Ontario Universities

In this study, teacher candidates’ experiences, perceptions, and knowledge of multicultural education at 2 Ontario universities were used determine to the effectiveness of their teacher education programs in preparing them to teach in multicultural classrooms. The research also strived to highlight the most effective practices in these programs that contributed to the preparation of teacher candidates for employment in culturally, racially, and ethnically diverse classrooms in Ontario. A questionnaire and interviews were used to determine the effectiveness of the program in preparing them to teach in diverse classrooms. The findings revealed the need for a greater emphasis of multicultural education in teacher education programs at these universities. The data showed that teacher candidates were most critical of the courses and the delivery of the curriculum in relation to multicultural education. Teacher candidates were also concerned with the lack of multicultural education in their practicum placements. In addition, teacher candidates indicated in the questionnaire that they felt competent adapting instruction to the needs of students in multicultural classrooms. However, the results obtained from the interviews were more varied. The interviews highlighted that teacher candidates were hesitant about teaching in culturally diverse classrooms and less likely to state that they were prepared for these teaching environments. As well, many teacher candidates believed their peers were not prepared for multicultural issues. Teacher candidates believed the program could be improved in many ways including specific instruction across all classes, more diverse practicum experiences, guest speakers, case studies, and the creation of new courses that specifically address multicultural education.

Anxiety-Related Disorders in Primary-Junior Grades (K-3): Teacher Perceptions and Knowledge

This study used a descriptive case study design to analyze teachers’ experiences of anxiety-related conditions and emotions in the primary-junior grades (K-3). The study sought to examine (a) educators’ perceptions of anxiety conditions and how such interpretations influence their teaching practice; (b) teachers’ knowledge of the diagnostic processes, symptomology, and emotions related to anxiety disorders; (c) primary teachers’ knowledge of and experience with emotional regulation strategies and therapeutic approaches for anxiety; and (d) additional strategies and knowledge that should be available to help students. The study adopted Bronfenbrenner’s (1986) Ecological Model to frame participants’ experiences and perspectives, as well as the impact of several factors (e.g., school, home) and individuals (e.g. teachers, parents, students) on students’ anxiety and the participants’ perspectives. Through in-person interviews, participants shared their experiences with and knowledge about students in their teaching practice who had experienced anxiety-related conditions and emotions. Four major themes emerged from the data: symptoms and situational contexts; knowledge of strategies and interventions; understanding and perspectives of students; anxious emotional responses; and challenges. The study contributes to the literature by providing the real-life perspectives and experiences of primary-junior teachers (K-3) related to students experiencing anxiety. The study provides further information for educators, administrators, and research regarding any additional support and knowledge that should be implemented to further assist educators and students in regards to anxiety.

Interaction and knowledge exchange among academic business librarians in Ontario

A research project submitted to the Faculty of Extension, University of Alberta in partial fulfillment of the requirements for the degree of Master of Arts in Communications and Technology in 2005.

Search engine advertising in web retailing : an efficiency analysis

This study examines the efficiency of search engine advertising strategies employed by firms. The research setting is the online retailing industry, which is characterized by extensive use of Web technologies and high competition for market share and profitability. For Internet retailers, search engines are increasingly serving as an information gateway for many decision-making tasks. In particular, Search engine advertising (SEA) has opened a new marketing channel for retailers to attract new customers and improve their performance. In addition to natural (organic) search marketing strategies, search engine advertisers compete for top advertisement slots provided by search brokers such as Google and Yahoo! through keyword auctions. The rationale being that greater visibility on a search engine during a keyword search will capture customers' interest in a business and its product or service offerings. Search engines account for most online activities today. Compared with the slow growth of traditional marketing channels, online search volumes continue to grow at a steady rate. According to the Search Engine Marketing Professional Organization, spending on search engine marketing by North American firms in 2008 was estimated at $13.5 billion. Despite the significant role SEA plays in Web retailing, scholarly research on the topic is limited. Prior studies in SEA have focused on search engine auction mechanism design. In contrast, research on the business value of SEA has been limited by the lack of empirical data on search advertising practices. Recent advances in search and retail technologies have created datarich environments that enable new research opportunities at the interface of marketing and information technology. This research uses extensive data from Web retailing and Google-based search advertising and evaluates Web retailers' use of resources, search advertising techniques, and other relevant factors that contribute to business performance across different metrics. The methods used include Data Envelopment Analysis (DEA), data mining, and multivariate statistics. This research contributes to empirical research by analyzing several Web retail firms in different industry sectors and product categories. One of the key findings is that the dynamics of sponsored search advertising vary between multi-channel and Web-only retailers. While the key performance metrics for multi-channel retailers include measures such as online sales, conversion rate (CR), c1ick-through-rate (CTR), and impressions, the key performance metrics for Web-only retailers focus on organic and sponsored ad ranks. These results provide a useful contribution to our organizational level understanding of search engine advertising strategies, both for multi-channel and Web-only retailers. These results also contribute to current knowledge in technology-driven marketing strategies and provide managers with a better understanding of sponsored search advertising and its impact on various performance metrics in Web retailing.

Towards Evaluating and Modelling the Impacts of Mobile-Based Augmented Reality Applications on Learning and Engagement

Mobile augmented reality applications are increasingly utilized as a medium for enhancing learning and engagement in history education. Although these digital devices facilitate learning through immersive and appealing experiences, their design should be driven by theories of learning and instruction. We provide an overview of an evidence-based approach to optimize the development of mobile augmented reality applications that teaches students about history. Our research aims to evaluate and model the impacts of design parameters towards learning and engagement. The research program is interdisciplinary in that we apply techniques derived from design-based experiments and educational data mining. We outline the methodological and analytical techniques as well as discuss the implications of the anticipated findings.