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The inferred mode protocol uses contextual reasoning and local mediators to eliminate the need to access specic modes to perform draw, select, move and delete operations in a sketch interface. This thesis describe an observational experiment to understand the learn- ability, user preference and frequency of use of mode inferencing in a sketch appli- cation. Novel methodology is presented to study both quantitative and long term qualitative facets of mode inferencing. The experiment demonstrated that participants instructed in the in- terface features enjoyed fluid transitions between modes. As well, interaction techniques were not self-revealing: Participants who were not instructed in interaction techniques took longer to learn about inferred mode features and were more negative about the interaction techniques. Over multiple sketching sessions, as users develop expertise with the system, they combine inferred mode techniques to speed interaction, and frequently make use of scratch space on the display to retrain themselves and to tune their behaviors. Lastly, post- task interviews outline impediments to discoverability and how performance is affected by negative perceptions around computational intelligence. The results of this work inform the design of sketch interface techniques that incorporate noncommand features.

My PhD research focuses on the recommendation of optimal designs for two-colour microarray experiments. Two-colour microarrays are a technology used to investigate the behaviour of many thousands of genes in a single experiment. This technology has created the potential for making significant advances in the field of bioinformatics. Careful statistical design is crucial to realize the full potential of microarray technology. My research has focused on the recommendation of designs that are optimal in terms of precision for effects that are of scientific interest, making the most effective use of available resources. Based on statistical efficiency, the optimality criterion used is Pareto optimality. A design is defined to be Pareto optimal if there is no other design that leads to equal or greater precision for each effect of scientific interest and strictly greater precision for at least one. My PhD thesis was submitted in June and key aspects of my research are summarised below. Pareto optimality enables the recommendation of designs that are particularly efficient for the effects that are of scientific interest. I have developed methodology to cater for effects of interest that correspond to contrasts rather than solely considering parameters of the statistical linear model. My approach also caters for additional experimental considerations such as contrasts that are of equal scientific interest. During my PhD, I have provided advice regarding the design of two-colour microarray experiments aimed at discovering the genetic basis of medical conditions. For large experiments, it is not feasible to examine all possible designs in an exhaustive search for Pareto optimal designs. I have adapted the multiple objective metaheuristic method of Pareto simulated annealing to the microarray context. The aim of Pareto simulated annealing is to generate an approximation to the set of Pareto optimal designs in a relatively short time. At each iteration, a sample of generating designs is used to explore the design space in an efficient way. This involves the setting of a number of Pareto simulated annealing parameters and the development of appropriate quality measures. I have developed algorithms to search systematically for the optimal values of the tuning parameters based on Pareto simulated annealing and response surface methodology. / Thesis (Ph.D.) -- University of Adelaide, School of Mathematical Sciences, 2010

Thesis (M.S. in Operations Research)--Naval Postgraduate School, June 2008. / Thesis Advisor(s): Lucas, Thomas W. "June 2008." Description based on title screen as viewed on August 25, 2008 Includes bibliographical references (p. 45). Also available in print.

Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 2008. / Thesis Advisor(s): Lucas, Thomas W. "September 2008." Description based on title screen as viewed on November 6, 2008. Includes bibliographical references (p. 89-90). Also available in print.