The fate of Susan Pevensie has been one of the most controversial and interesting topics of debate about The Chronicles of Narnia since readers realized that she was no longer a friend of Narnia. Many critics have condemned C. S. Lewis for being sexist, thus making the stereotypically feminine Susan with her love of parties, nylons, and lipstick ineligible for salvation. This thesis proposes to look at Susan's choices and fate from the perspective of moral imagination. It argues that Lewis did not bar Susan from heaven to belittle femininity, but rather to comment on the consequences of choice, belief, and the vital exercise of moral imagination. Placing Susan in a fairy-tale world highlights the differences between what is real and what seems impossible and pushes both Susan and the readers to develop their own moral imagination in the pursuit of belief in the truth. Looking at Susan's ambiguous fate and comparing her story to other characters' journeys throughout the series shows readers the power of the imagination and offers hope that Susan, like the rest of her siblings, may make it to Aslan's Country after all.

The purpose of this study was to investigate Korean-American families' beliefs about child development and their child-care practices. Questionnaires were distributed and mailed to wives of Korean-American dual-earner families residing in Utah with young children. Incorporated measures were the Suinn-Lew Asian Self-Identity Acculturation Scale (SL-ASIA), Maternal Expectations of Child Development, questions on the type of child care and its quality, and the Child Care Satisfaction Scale (CCSS). Seventy-three mothers filled out the questionnaire for 104 children's child-care situations. Results showed that Korean-American mothers were moderately acculturated and held both American and Korean values concerning the growth and development of children. There were consistent relationships among the type of child care, mothers' quality rating, and maternal satisfaction, as they relate to family characteristics. That is, the child's age, family income, and the availability of relatives were factors related to the type of child care. Korean-American mothers considered educational activities or learning opportunities as important factors in child care and gave higher ratings to center care than they gave to relative or neighbor care. Also, maternal satisfaction with the care arrangements was positively related to their ratings of quality.

The measurement of religious belief has some social desirability concerns that make the development of an implicit measure of religiosity advantageous. Currently, there are few options for implicitly measuring religious belief. This study attempted to add to this literature by analyzing the automatic judgements of religious belief through the use of an implicit measure known as the MouseTrack task, allowing for the measurement of latency in the expression of these beliefs as well as the certainty of these beliefs by tracking the path taken during the decision process. A sample of 121 undergraduates was recruited from the UK SONA subject pool. Desired religious variance was not achieved in the sample, making interpretation of results difficult. Detailed breakdowns of these path analyses are given. Key trends in findings are discussed.

Human immunodeficiency virus (HIV) and acquired immunodeficiency syndrome (AIDS) are ailments that have a social and political impact in the U.S. Since their discovery more than three decades ago, there has been an intense focus on eradicating these deadly diseases. Although there has been a lot of progress in the fight against HIV and AIDS, there are communities still disproportionately affected by it. Based on data from the Center for Disease Control and Prevention (CDC), one such community is young adults age 20 to 24 (CDC, 2016a). These young adults are at the focal center of the HIV/AIDS epidemic for various reasons; yet, this group is often overlooked in HIV literature and prevention/intervention strategies. Additionally, this community is known for inconsistent condom use, although there have been countless public service announcements (PSAs) and interventions promoting the use of condoms as a means of preventing not only unwanted pregnancy but the contraction of sexual transmitted infections (STIs) including HIV/AIDS. The aim of the current study was to test a comprehensive moderated mediation model and assess factors associated with condom use among early young adults age 18 to 24 above and beyond known variables such as age, gender, and ethnicity/race. These variables included participants’ age of sexual debut, number of lifetime sexual partners, perceived threat of contracting STIs and HIV/AIDS, and exposure to cues to action as predictors of condom use. The decision to expand the study to assess condom use among early young adults (18 -24) as opposed to focusing exclusively on young adults (20 -24) was based on early young adults being less likely to be tested for HIV compared to other age groups (CDC, 2008). For the moderated mediation model, I drew on the health belief model (HBM) and tested whether 1) the relationship between sexual debut and condom use was mediated by number of lifetime sexual partnerships, and 2) the relationships between sexual debut and the mediator were moderated by perceived threat, and whether the relationships between the mediator and condom use was moderated by perceived threat and cues to action. The full model was not supported. The implication of this study is that more current research is needed to understand early young adults and their condom use, as they are a community that is most vulnerable to HIV/AIDS and a key component in the fight against this disease.

The purpose of this study was to investigate the shift of Thai teachers' views of learning and their pedagogical practices from the traditional approach to be more centered on an argument-based inquiry approach (ABI) in Thai classrooms, where teachers and learners have long been familiar with the lecture-based tradition. Other than examining the changes, the study further explored the relationship throughout the ABI implementation phase with a specific focus on driving questions, problem solving and reasoning, and establishing a supportive learning environment. The study was conducted in Thailand with five physics teachers. Data collection involved classroom observations and teacher interviews. The constant comparative method was employed throughout the data analysis process. The research questions that guided this study were: (1) What changes occurred in teachers' pedagogical practices and views of learning throughout the implementation phase of the argument-based inquiry approach? (2) If change did occur, what was the relationship of the change among the observed criteria (questioning, problem solving, and the establishing of a supportive learning environment)? The results revealed that after fourteen weeks, the three teachers who expressed a positive attitude toward the ABI approach and expressed their willingness to practice started to shift their practices and views of learning toward a student-centered model. Although each teacher exhibited a different starting point within the three observed criteria, they all began to shift their practices first, before reflecting on their beliefs. In contrast to these teachers, the other two teachers were impeded by several barriers and therefore failed to implement the approach. These positive attitude, willingness, and shift of practice appear to be connected and necessary for change. The study highlights that in order to support the implementation of the ABI approach, especially in a large class size cultural setting, opportunities for teachers to be challenged in both classroom and cognitive spaces, where they are immersed in authentic practices and be able to reflect on their own actions as well as their existing beliefs, are crucial. However, to advance the dimensions of this issue, long-term professional development and a longitudinal study observing a large class size cultural settings are suggested.

A descriptive, phenomenological research design was used to gain a deeper understanding of the nature and meaning of couples’ experiences as they made the transition to parenthood. Specifically, this study examined what is the lived experience of couples making the transition to parenthood and what meaning do they ascribed to the experience of brief, couple-focused, preventative interventions? Five couples who were expecting their first baby participated in this study. From the data provided, two major categories emerged. The first was the couples’ experiences with becoming new parents and the second was the couples’ experiences with therapy. Under the first category, five major themes emerged: (1) physical and emotional challenges, (2) bonding with baby, (3) satisfaction in roles and new identity, (4) impact of social support, and (5) stability of relationship satisfaction. Three themes were discovered under the category related to the couples’ experience with therapy: (1) facilitated communication, (2) stress management, and (3) preparation for the transition. This study concluded by discussing the essence of the phenomenon of couples’ experiences with the transition to parenthood and the meaning they ascribed to therapeutic interventions along with clinical implications of these findings.

This thesis presents a new approach for selecting a manipulator arm configuration (a pose) in an environment where the positions of the work items are not able to be fully controlled. The approach utilizes a belief formed from a priori knowledge, observations and predictive models to select manipulator poses and motions. Standard methods for manipulator control provide a fully specified Cartesian pose as the input to a robot controller which is assumed to act as an ideal Cartesian motion device. While this approach simplifies the controller and makes it more portable, it is not well suited for less-controlled environments where the work item position or orientation may not be completely observable and where a measure of the accuracy of the available observations is required. The proposed approach suggests selecting a manipulator configuration using two types of rating function. When uncertainty is high, configurations are rated by combining a belief, represented by a probability density function, and a value function in a decision theoretic manner enabling selection of the sensor??s motion based on its probabilistic contribution to information gain. When uncertainty is low the mean or mode of the environment state probability density function is utilized in task specific linear or angular distances constraints to map a configuration to a cost. The contribution of this thesis is in providing two formulations that allow joint configurations to be found using non-linear optimization algorithms. The first formulation shows how task specific linear and angular distance constraints are combined in a cost function to enable a satisfying pose to be selected. The second formulation is based on the probabilistic belief of the predicted environment state. This belief is formed by utilizing a Bayesian estimation framework to combine the a priori knowledge with the output of sensor data processing, a likelihood function over the state space, thereby handling the uncertainty associated with sensing in a less controlled environment. Forward models are used to transform the belief to a predicted state which is utilized in motion selection to provide the benefits of a feedforward control strategy. Extensive numerical analysis of the proposed approach shows that using the fed-forward belief improves tracking performance by up to 19%. It is also shown that motion selection based on the dynamically maintained belief reduces time to target detection by up to 50% compared to two other control approaches. These and other results show how the proposed approach is effectively able to utilize an uncertain environment state belief to select manipulator arm configurations.

Large systems often have a long life-span and their system and software architecture design comprise many intricately related elements. The verification and maintenance of these architecture designs require an understanding of how and why the system are constructed. Design rationale is the reasoning behind a design and it provides an explanation of the design. However, the reasoning is often undocumented or unstructured in practice. This causes difficulties in the understanding of the original design, and makes it hard to detect inconsistencies, omissions and conflicts without any explanations to the intricacies of the design. Research into design rationale in the past has focused on argumentation-based design deliberations. Argumentation-based design rationale models provide an explicit representation of design rationale. However, these methods are ineffective in communicating design reasoning in practice because they do not support tracing to design elements and requirements in an effective manner. In this thesis, we firstly report a survey of practising architects to understand their perception of the value of design rationale and how they use and document this knowledge. From the survey, we have discovered that practitioners recognize the importance of documenting design rationale and frequently use them to reason about their design choices. However, they have indicated certain barriers to the use and documentation of design rationale. The results have indicated that there is no systematic approach to using and capturing design rationale in current architecture design practice. Using these findings, we address the issues of representing and applying architecture design rationale. We have constructed a rationale-based architecture model to represent design rationale, design objects and their relationships, which we call Architecture Rationale and Element Linkage (AREL). AREL captures both qualitative and quantitative rationale for architecture design. Quantitative rationale uses costs, benefits and risks to justify architecture decisions. Qualitative rationale documents the issues, arguments, alternatives and tradeoffs of a design decision. With the quantitative and qualitative rationale, the AREL model provides reasoning support to explain why architecture elements exist and what assumptions and constraints they depend on. Using a causal relationship in the AREL model, architecture decisions and architecture elements are linked together to explain the reasoning of the architecture design. Architecture Rationalisation Method (ARM) is a methodology that makes use of AREL to facilitate architecture design. ARM uses cost, benefit and risk as fundamental elements to rank and compare alternative solutions in the decision making process. Using the AREL model, we have proposed traceability and probabilistic techniques based on Bayesian Belief Networks (BBN) to support architecture understanding and maintenance. These techniques can help to carry out change impact analysis and rootcause analysis. The traceability techniques comprise of forward, backward and evolution tracings. Architects can trace the architecture design to discover the change impacts by analysing the qualitative reasons and the relationships in the architecture design. We have integrated BBN to AREL to provide an additional method where probability is used to evaluate and reason about the change impacts in the architecture design. This integration provides quantifiable support to AREL to perform predictive, diagnostic and combined reasoning. In order to align closely with industry practices, we have chosen to represent the rationale-based architecture model in UML. In a case study, the AREL model is applied retrospectively to a real-life bank payment systems to demonstrate its features and applications. Practising architects who are experts in the electronic payment system domain have been invited to evaluate the case study. They have found that AREL is useful in helping them understand the system architecture when they compared AREL with traditional design specifications. They have commented that AREL can be useful to support the verification and maintenance of the architecture because architects do not need to reconstruct or second-guess the design reasoning. We have implemented an AREL tool-set that is comprised of commercially available and custom-developed programs. It enables the capture of architecture design and its design rationale using a commercially available UML tool. It checks the well-formedness of an AREL model. It integrates a commercially available BBN tool to reason about the architecture design and to estimate its change impacts.

<p>Stark tro på en rättvis värld (BJW) har setts ha samband med en benägenhet att nedvärdera olycksdrabbade men även med positiva aspekter såsom stresshantering. Politiskt har BJW setts relaterad till högerorientering. Denna studie kombinerar relationen mellan BJW och politik med fokusering på attribuering av orsaker till arbetslöshet vilket tidigare förbisetts. Elever (n = 63) från gymnasium och högskola tog ställning till föreslagna orsaker till arbetslöshet och besvarade bakgrundsfrågor inklusive politisk hemvist och två olika BJW-skalor: dels en cynisk inställning till andras misslyckanden (deserved misfortune, DM), dels en förmåga att glädjas över andras framgång (deserved good fortune, DGF). DM och DM för deltagare med lågt DGF uppvisade samband med högerpolitisk orientering, vilket även korrelerade positivt med intern attribution. En tendens till korrelation mellan DM och intern attribution återfanns, men inga signifikanta samband mellan BJW och attribution. Uppdelningen av BJW samt möjligheter till och behovet av framtida forskning diskuteras utifrån resultaten.</p>

In many applications of graphical models arising in computer vision, the hidden variables of interest are most naturally specified by continuous, non-Gaussian distributions. There exist inference algorithms for discrete approximations to these continuous distributions, but for the high-dimensional variables typically of interest, discrete inference becomes infeasible. Stochastic methods such as particle filters provide an appealing alternative. However, existing techniques fail to exploit the rich structure of the graphical models describing many vision problems. Drawing on ideas from regularized particle filters and belief propagation (BP), this paper develops a nonparametric belief propagation (NBP) algorithm applicable to general graphs. Each NBP iteration uses an efficient sampling procedure to update kernel-based approximations to the true, continuous likelihoods. The algorithm can accomodate an extremely broad class of potential functions, including nonparametric representations. Thus, NBP extends particle filtering methods to the more general vision problems that graphical models can describe. We apply the NBP algorithm to infer component interrelationships in a parts-based face model, allowing location and reconstruction of occluded features.