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Facial expressions are visible signs of person's affective state, cognitive activity and personality. Automatic recognition of facial expressions is an important component for a wide spectrum of applications including human-computer interfaces, video conferencing, augmented reality and human activity monitoring to mention a few. Facial expression representation is an essential part in the automatic recognition of facial expressions. It is concerned with finding distinguishable features that can be utilised for representing different facial expressions without constraints of age, ethnicity or gender. This thesis reports on research and development in the facial expression representation. The author has proposed two novel methods for representing facial expressions. One is based on the shape space vector (SSV) of the statistical shape model (SSM); the other is based on the SSV of the B-spline statistical shape model (BSSM). The first proposed method uses the SSV of the SSM as a significant feature for representing facial expressions embedded in 3-D facial surfaces. In order to obtain the SSV, a novel model-based surface registration method is proposed that iteratively deforms and matches the model to an unseen new facial surface. Two major stages are included in this method, namely, model building and model fitting. In the model building stage, a SSM is built by using a training data set with estimated correspondences. In the model fitting stage, the built model is adapted to represent the shape of the new facial surface, which has not been included in the training data set. To build the model, the thin plate spline warping has been used so that all of the facial surfaces in the training data set are aligned into a common reference facial surface and the dense correspondences of points between these facial surfaces can be calculated. To fit the model to the new facial surface a modified iterative closest point (ICP) algorithm and least-squares projection on to the estimated shape space, constructed using the training data set, are applied. The second proposed method uses the SSV of the BSSM for facial expression representation. The mddel is built using B-spline control points instead of the surface points as in the SSM based method. In order to obtain the control points of B-spline, a novel method for the B-spline surface fitting has been proposed. The robustness and efficiency of both model-based facial expression representation methods are improved by introducing a multi-resolution scheme in the model fitting stage. The experimental results on simulated and real 3-D facial surfaces show that the proposed methods can effectively provide distinguishable features for facial expression analysis and recognition.

Participation in contributing content to online communities remains heavily skewed. Yet little research has focused on lowering the contribution effort. I describe a general approach to facilitating user-generated content within the context of Wikipedia. I also present the IntelWiki prototype, a design and implementation of this approach, which aims to make it easier for users to create or enhance the free-form text in Wikipedia articles. The IntelWiki system i) recommends article-relevant reference materials, ii) draws the users' attention to key aspects of the recommendations, and iii) allows users to consult the recommended materials in context. A laboratory evaluation with 16 novice Wikipedia editors revealed that, in comparison to the default Wikipedia design, IntelWiki's approach has positive impacts on editing quantity and quality. Participants also reported experiencing significantly lower mental workload while editing with IntelWiki and preferred the new design.

Trust is a judgement of unquestionable utility - as humans we use it every day of our lives. However, trust has suffered from an imperfect understanding, a plethora of definitions, and informal use in the literature and in everyday life. It is common to say "I trust you, " but what does that mean? This thesis provides a clarification of trust. We present a formalism for trust which provides us with a tool for precise discussion. The formalism is implementable: it can be embedded in an artificial agent, enabling the agent to make trust-based decisions. Its applicability in the domain of Distributed Artificial Intelligence (DAI) is raised. The thesis presents a testbed populated by simple trusting agents which substantiates the utility of the formalism. The formalism provides a step in the direction of a proper understanding and definition of human trust. A contribution of the thesis is its detailed exploration of the possibilities of future work in the area.

Thesis (Ph. D.)--University of Texas at Austin, 2009. / Title from PDF title page (University of Texas Digital Repository, viewed on July 30, 2009). Vita. Includes bibliographical references.

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In recent years an increasing focus has been placed on the development of students’ skills of critical thinking, problem solving and independent learning, throughout their time at university. There is an increasing shift towards incorporating activities which promote students’ active engagement with course materials – with the intention of promoting a deeper understanding of their chosen subject. Many tools and techniques are available that facilitate students’ transition from the passive recipient of knowledge, to a central, active actor in the learning process. One such tool, PeerWise, is an online, free to use application where students are encouraged to write multiple choice questions for their peers to answer, resulting in a bank of questions for students to test their knowledge and understanding. Students are given opportunities to give feedback to question authors on the quality of the question, in the form of a numerical rating or a qualitative comment, which provides further scope for students to engage in discussion about the question. It is hypothesised that actively engaging with course material will promote a deeper understanding of its content and will develop students’ skills of problem solving and critical thinking. The research in this thesis explores the relationship between engagement with PeerWise and performance in end of course examinations in six courses (physics, chemistry and biology), across three academic years within three research intensive UK universities. This work aims to unpick the nature of student interactions on PeerWise, and the extent to which engagement with each activity on the system is associated with attainment, when controlling for a student’s prior ability and other relevant factors such as their gender. Student views on engaging with the system have also been gathered to understand the degree to which students find PeerWise useful to their learning, and the ways in which they interact with the platform. Although the results paint a complex picture of the relationship between PeerWise use and attainment, in most courses, and for most ability levels, students who engage to a higher level with PeerWise achieve a higher exam score than their lower engaging peers. There is also often a significant, positive correlation between engaging with PeerWise and end of course exam score which persists, even when controlling for a student’s prior ability. Although it would seem to be that answering questions and writing high quality feedback is more often associated with attainment than writing questions and receiving feedback, the results suggest that engagement across all activities is most beneficial to students – indicating that overall engagement with the task is key to student learning.

The purpose of this study was to investigate the effect of elaborations on memory . Two types of elaborations (self-generated elaboration and experimenterprovided elaboration) were examined. The experiment consisted of three phases (incidental learning phase, immediate test phase, and delayed test phase). In the incidental learning phase, subjects were asked to make plausibility judgments about 28 fictitious episodes. Half of these were about well-known individuals and the other half were about unknown individuals. Each name (either well-known or unknown) was presented with either two supportive facts or without the supportive facts. During the immediate test phase, subjects were given unexpected memory tests. One week later, unexpected delayed memory tests were administered. Results from both immediate and delayed tests indicated that self-generated elaborations based on prior knowledge subjects had about well-known individuals enhanced the retention of target information, whereas experimenter-provided elaborations involving the presence of supportive facts only benefited memory performance when the subjects had prior knowledge about the individuals. Experimenter-provided elaborations were also effective to the extent that the encoding context was reinstated at testing.