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Thesis (M.Sc.). / Written for the School of Computer Science. Title from title page of PDF (viewed 2008/05/30). Includes bibliographical references.

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rhe non-copulatory estrous behaviour of semi-free ranging female Japanese monkeys was observed for 3 months, in order to investigate the role of the female in the establishment of mating pairs. It was concluded that the females play a very active role in the formation of mating pairs, showing three times more solicitation behaviour than males. They also reject more than 30% of the advances they do receive. This is interpretated as an indication of selectivity in the choice of sexual partners. The behaviour of the female in this courtship context is described, with emphasis on preceptive or solicitation behaviour. The data were tested for behavioural differences based on the female's age, rank, parity, number of offspring and the presence of an infant, and for differences based on the age, rank and spatial status of the interacting male. Age of the female had the greatest effect on behaviour, with older females behaving in a more calm, sophisticated manner when soliciting a male. Age was also the most significant male variable, with females showing more rejection to younger males. Other than age related findings it must be concluded that these sociological characteristics of the animals are not predictive of the females' courtship behaviour. A number of alternate lines of inquiry for future research are suggested. They include an investigation of the hormonal basis of estrous behaviour, a multivariate analysis, and a sequential analysis of behaviour. / Thesis / Master of Arts (MA)

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A systematic research approach is necessary to investigate complex systems. This approach should provide a tool for examining multifactors in an efficient manner since a large number of factors is usually involved in the design and evaluation of complex systems. This study is used to develop empirical models which describe the functional relationships of many independent variables in the design of a telephone information system. Such a development is based on integrating several data sets using sequential experimentation. Reanalyses of previous experiments were conducted to examine necessary and sufficient conditions for integrating data sets resulting from previous studies. As a result. an experiment was conducted to investigate the effects of independent variables which were not manipulated in the previous experiments. An additional experiment was conducted to provide a bridge among several data sets. The integrated data set was then used to build second-order empirical models using polynomial regression. Determinant values of X'X matrices served as a statistical criterion for achieving minimum variances of coefficients and prediction variances of the models. Based upon the empirical models developed, optimum configurations of the telephone information system were obtained using a nonlinear programming technique. A separate optimization method was used since the empirical models included both continuous variables and discrete variables. Specific procedures and guidelines are suggested in planning and conducting sequential research which deals with a large number of independent variables in an efficient and systematic manner. The procedures and guidelines are summarized based upon the lessons learned from the dissertation research. These include administrative requirements, alternative experimental designs, methodological considerations on conducting sequential experiments, and other necessary rules and decision criteria for bridging data sets and optimizing empirical models. This approach is expected to provide a tool for obtaining generalizable results in human factors research. / Ph. D.

This project brings the bioinformatics community a new development concept in which users can access all data and applications hosted in the main research centers as if they were installed on their local machines, providing seamless integration between disparate services. The project moves to integrate the sequence similarity searching at EBI and NCBI by using web services. It also intends to allow molecular biologists to save their searches and act as a log book for their sequence similarity searches. The project will also allow the biologists to share their sequences and results with others.

In this thesis, we provide computationally efficient algorithms with provable statistical guarantees, for the problem of active learning, by using ideas from sequential analysis. We provide a generic algorithmic framework for active learning in the pool setting, and instantiate this framework by using ideas from learning with experts, stochastic optimization, and multi-armed bandits. For the problem of learning convex combination of a given set of hypothesis, we provide a stochastic mirror descent based active learning algorithm in the stream setting.