Uncertainty visualization in 3D scalar data

One problem in most three-dimensional (3D) scalar data visualization techniques is that they often overlook to depict uncertainty that comes with the 3D scalar data and thus fail to faithfully present the 3D scalar data and have risks which may mislead users’ interpretations, conclusions or even decisions. Therefore this thesis focuses on the study of uncertainty visualization in 3D scalar data and we seek to create better uncertainty visualization techniques, as well as to find out the advantages/disadvantages of those state-of-the-art uncertainty visualization techniques. To do this, we address three specific hypotheses: (1) the proposed Texture uncertainty visualization technique enables users to better identify scalar/error data, and provides reduced visual overload and more appropriate brightness than four state-of-the-art uncertainty visualization techniques, as demonstrated using a perceptual effectiveness user study. (2) The proposed Linked Views and Interactive Specification (LVIS) uncertainty visualization technique enables users to better search max/min scalar and error data than four state-of-the-art uncertainty visualization techniques, as demonstrated using a perceptual effectiveness user study. (3) The proposed Probabilistic Query uncertainty visualization technique, in comparison to traditional Direct Volume Rendering (DVR) methods, enables radiologists/physicians to better identify possible alternative renderings relevant to a diagnosis and the classification probabilities associated to the materials appeared on these renderings; this leads to improved decision support for diagnosis, as demonstrated in the domain of medical imaging. For each hypothesis, we test it by following/implementing a unified framework that consists of three main steps: the first main step is uncertainty data modeling, which clearly defines and generates certainty types of uncertainty associated to given 3D scalar data. The second main step is uncertainty visualization, which transforms the 3D scalar data and their associated uncertainty generated from the first main step into two-dimensional (2D) images for insight, interpretation or communication. The third main step is evaluation, which transforms the 2D images generated from the second main step into quantitative scores according to specific user tasks, and statistically analyzes the scores. As a result, the quality of each uncertainty visualization technique is determined.

Dutch influence in the urban landscape of Cork City pre-1800: Fact or myth?

The early years of the eighteenth century Irish port town, Cork saw an expansion of its city limits, an era of reconstruction both within and beyond the walls of its Medieval townscape and a reclamation of its marshlands to the east and west. New people, new ideas and the beginnings of new wealth infused the post Elizabethan character of the recently siege battered city. It also brought a desire for something different, something new, an opportunity to redefine the ambience and visual perception of the urban landscape and thereby make a statement about its intended cultural and social orientations. It brought an opportunity to re-imagine and model a new, continental style of place and surrounding environment.

Job retention and turnover: a study of child protection and welfare social workers in Ireland

Retaining social workers in child protection and welfare organisations has been identified as a problem in Ireland (McGrath, 2001; Ombudsman for Children, 2006; Houses of the Oireachtas, 2008) and internationally (Ellet et al., 2006; Mor Barak et al., 2006; Tham, 2006). While low levels of retention have been identified, there is no research that examines the factors in Ireland that influence the retention of social workers. In this thesis, data is analysed from qualitative interviews with 45 social workers in the Health Service Executive South about what influences their decisions to stay in or leave child protection and welfare social work. These social workers’ views are examined in relation to quantitative research on the levels of turnover and employment mobility of child protection and welfare social workers employed in the same organisation. Contrary to expectations, the study found that the retention rate of social workers during the period of data collection (March 2005 to December 2006) was high and that the majority of social workers remained positive about this work and their retention. The quality of social workers’ supervision, social supports from colleagues, high levels of autonomy, a commitment to child protection and welfare work, good variety in the work, and a perception that they were making a difference, emerged as important factors in social workers’ decisions to stay. Perceptions of being unsupported by the organisation, which was usually described in terms of high caseloads and demanding workloads, a lack of resources, work with involuntary clients and not being able to make a difference, were the most significant factors in social workers’ decisions to leave and/or to want to leave. Social workers felt particularly professionally unsupported when they received low quality and/or infrequent professional supervision. This thesis critiques the theories of perceived organisational support theory, social exchange theory and job characteristics theory, and uses the concept of ‘professional career’, to help analyse the retention of social workers in child protection and welfare.

Combining and choosing case base maintenance algorithms

Case-Based Reasoning (CBR) uses past experiences to solve new problems. The quality of the past experiences, which are stored as cases in a case base, is a big factor in the performance of a CBR system. The system's competence may be improved by adding problems to the case base after they have been solved and their solutions verified to be correct. However, from time to time, the case base may have to be refined to reduce redundancy and to get rid of any noisy cases that may have been introduced. Many case base maintenance algorithms have been developed to delete noisy and redundant cases. However, different algorithms work well in different situations and it may be difficult for a knowledge engineer to know which one is the best to use for a particular case base. In this thesis, we investigate ways to combine algorithms to produce better deletion decisions than the decisions made by individual algorithms, and ways to choose which algorithm is best for a given case base at a given time. We analyse five of the most commonly-used maintenance algorithms in detail and show how the different algorithms perform better on different datasets. This motivates us to develop a new approach: maintenance by a committee of experts (MACE). MACE allows us to combine maintenance algorithms to produce a composite algorithm which exploits the merits of each of the algorithms that it contains. By combining different algorithms in different ways we can also define algorithms that have different trade-offs between accuracy and deletion. While MACE allows us to define an infinite number of new composite algorithms, we still face the problem of choosing which algorithm to use. To make this choice, we need to be able to identify properties of a case base that are predictive of which maintenance algorithm is best. We examine a number of measures of dataset complexity for this purpose. These provide a numerical way to describe a case base at a given time. We use the numerical description to develop a meta-case-based classification system. This system uses previous experience about which maintenance algorithm was best to use for other case bases to predict which algorithm to use for a new case base. Finally, we give the knowledge engineer more control over the deletion process by creating incremental versions of the maintenance algorithms. These incremental algorithms suggest one case at a time for deletion rather than a group of cases, which allows the knowledge engineer to decide whether or not each case in turn should be deleted or kept. We also develop incremental versions of the complexity measures, allowing us to create an incremental version of our meta-case-based classification system. Since the case base changes after each deletion, the best algorithm to use may also change. The incremental system allows us to choose which algorithm is the best to use at each point in the deletion process.

The double bind for non-traditional families in post-primary settings; to tell or not to tell their family identity

This thesis involved researching normative family discourses which are mediated through educational settings. The traditional family, consisting of father, mother and children all living together in one house is no longer reflective of the home situation of many Irish students (Lunn and Fahey, 2011). My study problematizes the dominant discourses which reflect how family differences are managed and recognised in schools. A framework using Foucauldian post structural critical analysis traces family stratification through the organisation of institutional and interpersonal relations at micro level in four post-primary schools. Standardising procedures such as the suppression of intimate relations between and among teacher and student, as well as the linear ordering of intergenerational relations, such as teacher/student and adult/child are critiqued. Normalising discourses operate in practices such as notes home which presume two parents together. Teacher assumptions about heterosexual two-parent families make it difficult for students to be open about a family setup that is constructed as different to the rest of the schools'. The management of family difference and deficit through pastoral care structures suggests a school-based politics of family adjustment. These practices beg the question whether families are better off not telling the school about their family identity. My thesis will be of interest to educational research and educational policy because it highlights how changing demographics such as family compositions are mis-conceptualised in schools, as well as revealing the changing forms of family governance through regimes such as pastoral care. This analysis allows for the existence of, and a valuing for, alternative modes of family existence, so that future curricular and legal discourses can be challenged in the interest of equity and social justice.