Finding optimal alternatives based on efficient comparative preference inference

Choosing the right or the best option is often a demanding and challenging task for the user (e.g., a customer in an online retailer) when there are many available alternatives. In fact, the user rarely knows which offering will provide the highest value. To reduce the complexity of the choice process, automated recommender systems generate personalized recommendations. These recommendations take into account the preferences collected from the user in an explicit (e.g., letting users express their opinion about items) or implicit (e.g., studying some behavioral features) way. Such systems are widespread; research indicates that they increase the customers' satisfaction and lead to higher sales. Preference handling is one of the core issues in the design of every recommender system. This kind of system often aims at guiding users in a personalized way to interesting or useful options in a large space of possible options. Therefore, it is important for them to catch and model the user's preferences as accurately as possible. In this thesis, we develop a comparative preference-based user model to represent the user's preferences in conversational recommender systems. This type of user model allows the recommender system to capture several preference nuances from the user's feedback. We show that, when applied to conversational recommender systems, the comparative preference-based model is able to guide the user towards the best option while the system is interacting with her. We empirically test and validate the suitability and the practical computational aspects of the comparative preference-based user model and the related preference relations by comparing them to a sum of weights-based user model and the related preference relations. Product configuration, scheduling a meeting and the construction of autonomous agents are among several artificial intelligence tasks that involve a process of constrained optimization, that is, optimization of behavior or options subject to given constraints with regards to a set of preferences. When solving a constrained optimization problem, pruning techniques, such as the branch and bound technique, point at directing the search towards the best assignments, thus allowing the bounding functions to prune more branches in the search tree. Several constrained optimization problems may exhibit dominance relations. These dominance relations can be particularly useful in constrained optimization problems as they can instigate new ways (rules) of pruning non optimal solutions. Such pruning methods can achieve dramatic reductions in the search space while looking for optimal solutions. A number of constrained optimization problems can model the user's preferences using the comparative preferences. In this thesis, we develop a set of pruning rules used in the branch and bound technique to efficiently solve this kind of optimization problem. More specifically, we show how to generate newly defined pruning rules from a dominance algorithm that refers to a set of comparative preferences. These rules include pruning approaches (and combinations of them) which can drastically prune the search space. They mainly reduce the number of (expensive) pairwise comparisons performed during the search while guiding constrained optimization algorithms to find optimal solutions. Our experimental results show that the pruning rules that we have developed and their different combinations have varying impact on the performance of the branch and bound technique.

Block copolymer self-assembly based device structures

This thesis investigated the block copolymer (BCP) thin film characteristics and pattern formation using a set of predetermined molecular weights of PS-b-PMMA and PS-b-PDMS. Post BCP pattern fabrication on the required base substrate a dry plasma etch process was utilised for successful pattern transfer of the BCP resist onto underlying substrate. The resultant sub-10 nm device features were used in front end of line (FEoL) fabrication of active device components in integrated circuits (IC). The potential use of BCP templates were further extended to metal and metal-oxide nanowire fabrication. These nanowires were further investigated in real-time applications as novel sensors and supercapacitors.

Factors relating to motivation to change behaviour in individuals who are overweight: application of the health belief model

Background: Obesity is the most important health challenge faced at a global level and represents a rapidly growing problem to the health of populations. Given the escalating global health problem of obesity and its co-morbidities, the need to re-appraise its management is more compelling than ever. The normalisation of obesity within our society and the acceptance of higher body weights have led to individuals being unaware of the reality of their weight status and gravity of this situation. Recognition of the problem is a key component of obesity management and it remains especially crucial to address this issue. A large amount of research has been undertaken on obesity however, limited research has been undertaken using the Health Belief Model. Aim: The aim of the research was to determine factors relating to motivation to change behaviour in individuals who perceive themselves to be overweight and investigate whether the constructs of the Health Belief Model help to explain motivation to change behaviour. Method: The research design was quantitative, correlational and cross-sectional. The design was guided by the Health Belief Model. Data Collection: Data were collected online using a multi-section and multi-item questionnaire, developed from a review of the theoretical and empirical research. Descriptive and inferential statistical analyses were employed to describe relationships between variables. Sample: A sample of 202 men and women who perceived themselves to be overweight participated in the research. Results: Following multivariate regression analysis, perceived barriers to weight loss and perceived benefits of weight loss were significant predictors of motivation to change behaviour. The perceived barriers to weight loss which were significant were psychological barriers to weight loss (p =<0.019) and environmental barriers to physical activity (p=<0.032).The greatest predictor of motivation to change behaviour was the perceived benefits of weight loss (p<0.001). Perceived susceptibility to obesity and perceived severity of obesity did not emerge as significant predictors in this model. Total variance explained by the model was 33.5%. Conclusion: Perceived barriers to weight loss and perceived benefits of weight loss are important determinants of motivation to change behaviour. The current study demonstrated the limited applicability of the Health Belief Model constructs to motivation to change behaviour, as not all core dimensions proved significant predictors of the dependant variable.

Development of block copolymer lithography for device structure fabrication

This thesis investigated well-ordered block copolymer (BCP) thin film characteristics and their use for nanoscale pattern formation using a series of polystyrene-block-polymethylmethacrylate (PS-b-PMMA), polystyrene-blockpolydimethylsiloxane (PS-b-PDMS) and polystyrene-block-poly(ethylene oxide) (PS-b-PEO) systems of various molecular weights. BCP thin films, which act as an ‘on-chip’ etch mask and material templates, are highly promising self-assembling process for future scalable nanolithography. Unlike conventional BCP processing methods, the work in this thesis demonstrates that well-ordered patterns can be achieved in a few seconds compared to several hours by use of a non-conventional microwave assisted technique. As a result, well-ordered BCP nanoscale structures can be developed in industry appropriate periods facilitating their incorporation into current technologies. An optimised and controlled plasma dry etch process was used for successful pattern transfer to the underlying silicon substrate. Long range ordered BCP templates were further modified by selective metal inclusion technique to form a hard mask template towards fabrication of high aspect ratio nanopillars and nanowires. The work described here is centred on how these templates might be used to generate function at substrate surfaces. Herein we describe a number of innovations which might allow their successful uptake in a number of applications.