The focus of this study is the provision of refreshment, retail and supporting facilities at Gautrain stations. This forms part of an overarching strategy called for the deployment of refreshment, retail and supporting facilities at stations. For the purposes of this thesis, the concept of refreshment focuses on the aspects of bodily / physiological and mental refreshment, whether this be through sale of beverages and snacks or distribution and availability of information, news and mental stimulation through design. The strategy is explored in more detail through the design of a multifunctional kiosk for medium term deployment at any of the Gautrain stations. The Hatfield Gautrain station building interior forms the backdrop of an the in depth design and technical development of the intervention. Important factors in this scheme is the identifying of the most popular refreshment and ancillary facilities at other similar train stations as well as the integration of such facilities into the existing Gautrain system identity. The design approach is formulated on the three levels of scale and revolves around the creation of places and the railway station as public meeting place; tectonic expression and various factors relating to cost and sustainability. The aim is to contribute to the understanding of user needs in terms of refreshment, retail and ancillary behaviours (e.g. access to info) at transport interchanges. The thesis contributes to the general field of the environment and cultural landscapes as applicable to the discipline of interior architecture. / Dissertation (MInt(Prof))--University of Pretoria, 2010. / Architecture / unrestricted

<p>The thesis develops nonparametric Bayesian models to handle incomplete categorical variables in data sets with high dimension using the framework of multiple imputation. It presents methods for ignorable missing data in cross-sectional studies, and potentially non-ignorable missing data in panel studies with refreshment samples.</p><p>The first contribution is a fully Bayesian, joint modeling approach of multiple imputation for categorical data based on Dirichlet process mixtures of multinomial distributions. The approach automatically models complex dependencies while being computationally expedient. </p><p>I illustrate repeated sampling properties of the approach</p><p>using simulated data. This approach offers better performance than default chained equations methods, which are often used in such settings. I apply the methodology to impute missing background data in the 2007 Trends in International Mathematics and Science Study.</p><p>For the second contribution, I extend the nonparametric Bayesian imputation engine to consider a mix of potentially non-ignorable attrition and ignorable item nonresponse in multiple wave panel studies. Ignoring the attrition in models for panel data can result in biased inference if the reason for attrition is systematic and related to the missing values. Panel data alone cannot estimate the attrition effect without untestable assumptions about the missing data mechanism. Refreshment samples offer an extra data source that can be utilized to estimate the attrition effect while reducing reliance on strong assumptions of the missing data mechanism. </p><p>I consider two novel Bayesian approaches to handle the attrition and item non-response simultaneously under multiple imputation in a two wave panel with one refreshment sample when the variables involved are categorical and high dimensional. </p><p>First, I present a semi-parametric selection model that includes an additive non-ignorable attrition model with main effects of all variables, including demographic variables and outcome measures in wave 1 and wave 2. The survey variables are modeled jointly using Bayesian mixture of multinomial distributions. I develop the posterior computation algorithms for the semi-parametric selection model under different prior choices for the regression coefficients in the attrition model. </p><p>Second, I propose two Bayesian pattern mixture models for this scenario that use latent classes to model the dependency among the variables and the attrition. I develop a dependent Bayesian latent pattern mixture model for which variables are modeled via latent classes and attrition is treated as a covariate in the class allocation weights. And, I develop a joint Bayesian latent pattern mixture model, for which attrition and variables are modeled jointly via latent classes.</p><p>I show via simulation studies that the pattern mixture models can recover true parameter estimates, even when inferences based on the panel alone are biased from attrition. </p><p>I apply both the selection and pattern mixture models to data from the 2007-2008 Associated Press/Yahoo News election panel study.</p> / Dissertation

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The research study investigates the trauma experienced by Metrorail train drivers. An Employee Assistance Programme (EAP) is a worksite-based programme that assists in dealing with employee’s problems that impact on their job performance and overall production. Trauma awareness and management through therapy are necessary components and contribute to the effective operation of EAP. The study was conducted within the framework of a survey. Face-to-face scheduled interviews were designed and conducted on employees, i.e. Metrorail train drivers, after their respective supervisors had given permission. From the feedback on these interviews, it was apparent that train drivers need the help of EAP services, maybe through psychological counselling and motivation. Witnessing suicides by people on rail tracks apparently is a common occurrence to Metrorail train drivers. These accidents leave them emotionally scarred and haunted for almost their entire lives. EAP services will embrace other elements influencing the performance and occupational well-being of these train drivers. These elements include performance incentives, fringe benefits, security, and conducive train settings. / Dissertation (MSD (Employee Assistance Programme))--University of Pretoria, 2006. / Social Work / unrestricted

The quality of mathematics knowledge attained by students entering university in Science, Technology, Engineering and Mathematics (STEM) fields has been decreasing. There is a need to enhance students’ mathematical knowledge in order to maintain the standards of STEM curriculum at university. The rationale of this study was to investigate the influence of Pre-Calculus Mathematics Refreshment module taught using Meta-cognitive skills and Co-operative Learning (MCL), or Co-operative Learning (CL) only, or Traditional lecture (T) intervention method to First Year pre-engineering Students on their Applied Calculus 1 in an Ethiopian university. The study further investigated the influence of Pre-Calculus Mathematics Refreshment module for MCL, or CL, or T intervention method on male and female students’ achievement. The refreshment module and Applied Calculus 1 scores were measured through posttest and normal class room score of Applied Calculus 1 result. The dependent variables were student achievement in pre-calculus refreshment Module and Applied Calculus 1. Out of 29 universities in Ethiopia only four were selected to participate in this study. Population of this study was all pre-engineering first year students in those universities in 2016/2017. The sample consisted of 200 pre-engineering university students who studied in four of Ethiopian universities and one class was randomly selected by lottery method from existing pre-engineering classes in each university. Two experimental groups which were taught MCL and the other CL intervention method and two of them were control groups upon whom the control novice with traditional lecture method and control without intervention was applied. In each group 50 students of 25 males and 25 females were purposely selected from sampled class. A pre-calculus mathematics Pre-test was administered first, where the average scores of all students Pre-test result was below 33%. Then, first MCL and CL intervention methods were discussed and exercised for one week before implementing the study. For the study, selected pre-calculus mathematics topics was taught in all classrooms for 32 periods i.e. 50min x32= 26.7hrs at the beginning of the first semester parallel with Applied Calculus 1 for the academic year 2016 / 2017. The statistical tools used under this procedure include descriptive statistics percentage, mean and standard deviation and inferential statistics, T-test, and one-way analysis of variance (one-way ANOVA). The results show statistically significant differences (Sig 0.00) at the significance level (0.05) between students that learnt pre-calculus refreshment module and control group which did not. Among the students those learned pre-calculus refreshment module through MCL, CL and T method students in the MCL and CL groups’ posttest scores significantly different from T group in pre-calculus results both with Sig of 0.00. But there was no significant difference between MCL & CL groups were Sig is 0.97. Additionally, the female students in the MCL group was not significant different from CL and T group, on an impact of refreshment module, in Applied Calculus 1 mathematics where Sig is 0.994 and 0.237 respectively, and CL female group scores significantly different from T group in Applied Calculus 1 results with Sig 0.042. The male students in the MCL and CL groups were significantly different from T group in Applied Calculus 1with Sig of 0.07 and 0.012 respectively. Also, there was a positive correlation between Pre-Calculus refreshment module and Applied Calculus 1 with correlation coefficient of 0.835. Lastly, the result of pre-calculus mathematics posttest scores with the female students in MCL relatively increased than male students, than in CL and T groups, which indicated that MCL benefit more female students than male students. The differences were more in favor of pre-calculus mathematics refreshment with MCL intervention method. To improve success in engineering participation of all students, recommended that a pre-calculus module should be offered by all universities for first year engineering students, structured co-operative learning with purpose has significant gains for effective instruction, and to increase the success rate of female students this study has proven that they are trainable and therefore, meta-cognition skills have to be nurtured for female students. / Mathematics Education / D. Phil (Mathematics Education in Science and Technology)

The subject of this diploma thesis is the preparation of project documentation for the implementation of new sports and cultural centre Otradov. The dominant feature of the complex objects stands and multipurpose hall. The building is architecturally designed with an effort to fit in too much of rural architecture. Multipurpose hall has two floors, one third roofed flat roof, two-thirds of the roof ridge. The core system is aerated concrete blocks. The building is two-storey grandstand with the carrier deck. Roofing is solved by means of broken wooden beams. Sanitary facilities is dealt wall system and roofed shed roof. Athletics track, the surface of the polyurethane mixture designed for sports.