Thesis (M.Sc. (Computer Science))--North-West University, Potchefstroom Campus, 2010.

This study explored the question whether forensic social work meets the requirements set by the South African Council for Social Service Professions (SACSSP) for registration as a specialist field. The requirements are as follows: • It should be an identifiable and definable field in social work. • It should not be a form of intervention. • It should include a distinctive field of social work and not be shared with other professions. • It requires specialized knowledge, skills and experience from the social worker. It has been concluded that forensic social work does indeed meet the requirements for registration and it is recommended that it be registered as such. / Thesis (M.A. (MW Forensic))--North-West University, Potchefstroom Campus, 2009.

Thesis (M.Sc. (Computer Science))--North-West University, Potchefstroom Campus, 2010.

No description available.

Two empirical studies are presented which investigated Sexpert, a rule-based expert system for the treatment of couple sexual dysfunctions. The following hypotheses were evaluated: (1) couples' attitudes towards computerized psychotherapy would improve subsequent to an interaction with Sexpert, (2) couples would find Sexpert more engaging than other sources of information, (3) couples interacting with Sexpert would report learning more about their relationship than those exposed to other sources of information, and (4) Sexpert could influence the sexual behavior of volunteer couples. The research hypotheses were tested in 2 studies (81 & 77 couples respectively) which compared the effects of Sexpert, a sex education book and video, and a therapist, with a no-information control (crossword puzzles). A rigorous statistical analysis of the reliability of couples' self-report of their sexual behavior was made. In study 1, positive attitude shifts towards Sexpert were replicated with semantic differential as well as dissimilarity scales. In study 2, positive attitude shifts were only demonstrated via a ranking methodology. Sexpert was reported to be the most engaging of the experimental manipulations tested in either study. Couples provided with information via Sexpert, video, book, or therapist retrospectively reported significant positive changes in communication, sexuality, feelings, and relationship satisfaction. The highest change ratings were given by participants in the therapist group, followed by the Sexpert, video and book groups. Participants also reported significant learning about many aspects of their relationship and sexuality; however, there were no significant differences between the Sexpert, video, and therapist conditions. The sexual behavior monitoring data did not corroborate retrospectively reported changes in behavior. These inconsistencies in behavioral reporting were attributed to couple reactivity to the monitoring of sexual behavior and to s

Knowledge compilation improves search-intensive problem-solvers that are easily specified but inefficient. One promising approach improves efficiency by constructing a database of problem-instance/best-action pairs that replace problem-solving search with efficient lookup. The database is constructed by reverse enumeration- expanding the complete search space backwards, from the terminal problem instances. This approach has been used successfully in counter-planning to construct perfect problem-solvers for sub domains of chess and checkers. However, the approach is limited to small problems because both the space needed to store the database and the time needed to generate the database grow exponentially with problem size. This thesis addresses these problems through two mechanisms. First, the space needed is reduced through an abstraction mechanism that is especially suited to counter-planning domains. The search space is abstracted by representing problem states as equivalence classes with respect to the goal achieved and the operators as equivalence classes with respect to how they influence the goals. Second, the time needed is reduced through a hueristic best-first control of the reverse enumeration. Since with larger problems it may be impractical to run the compiler to completion, the search is organized to optimize the tradeoff between the time spent compiling a domain and the coverage achieved over that domain. These two mechanisms are implemented in a system that has been applied to problems in chess and checkers. Empirical results demonstrate both the strengths and weaknesses of the approach. In most problems and 80/20 rule was demonstrated, where a small number of patterns were identified early that covered most of the domain, justifying the use of best-first search. In addition, the method was able to automatically generate a set of abstract rules that had previously required two person-months to hand engineer. / Graduation date: 1992

New Zealand�s main export earnings come from the primary production area including agriculture, horticulture, and viticulture. One of the major contributors in this area of horticulture is the production of quality export grade fruit; specifically apples. In order to maintain a competitive advantage, the systems and methods used to grow the fruit are constantly being refined and are increasingly based on data collected and analysed by both the orchardist who grows the produce and also researchers who refine the methods used to determine high levels of fruit quality. To support the task of data analysis and the resulting decision-making process it requires efficient and reliable tools. This thesis attempts to address this issue by applying the techniques of Connectionist-Based Intelligent Information Systems (CBIIS) for Image Analysis and Knowledge Discovery. Using advanced neurocomputing techniques and a novel knowledge engineering methodology, this thesis attempts to seek some solutions to a set of specific problems that exist within the horticultural domain. In particular it describes a methodology based on previous research into neuro-fuzzy systems for knowledge acquisition, manipulation, and extraction and furthers this area by introducing a novel and innovative knowledge-based architecture for knowledge-discovery using an on-line/real-time incremental learning system based on the Evolving Connectionist System (ECOS) paradigm known as the Evolving Fuzzy Neural Network (EFuNN). The emphases of this work highlights knowledge discovery from these data sets using a novel rule insertion and rule extraction method. The advantage of this method is that it can operate on data sets of limited sizes. This method can be used to validate the results produced by the EFuNN and also allow for greater insight into what aspects of the collected data contribute to the development of high quality produce.

Thesis (MEng)--University of South Australia, 1994

Thesis (PhD)--University of South Australia, 1997

Thesis (MSc(Comp & InfoSc))--University of South Australia, 1998