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A simplistic view of a dataset is that it is collection of numbers. In fact data are much more than that and all data are collected at a set place and time. Often either the location, or the time, is fixed within the dataset and one or both are disregarded. When the place and time of the collection are incorporated into the analysis, the result is a spatio-temporal model. Spatio-temporal data are the focus of this thesis. The majority of the datasets used are radio tracking studies of animals where the objective is to measure the habitat use. Observations are made over a long period of time and a large area. The largest dataset analysed tracks over a hundred animals, in an area larger than 40 square miles, for multiple years. In this context understanding the spatio-temporal relationships between observations is essential. Even data that do not have an obvious spatial component can benefit from spatio-temporal analysis. For example, the data presented on volatility in the stock market do not have an obvious spatial component. The spatial component is the location in the market, not a physical location. Two different methods for measuring and correcting bias are presented. One method relies on direct modelling of the underlying process being observed. The underlying process is animal movement. A model for animal movement is constructed and used to estimate the missing observations that are thought to be the cause of the bias. The second method does not model the animal movement, but instead relies on a Bayesian Hierarchical Model with some simple assumptions. A long running estimation is used to calculate the most likely result without ever directly estimating the underlying equations. In the second section of the thesis two methods for measuring change from shifts in both spatial and temporal location are presented. The methods, Large Diffeomorphic Deformation Metric Mapping (LDDMM) and Diffeomorphic Demons (DD), were originally developed for anatomical data and are adapted here for nonparametric regression surfaces. These are the first applications of LDDMM and DD outside of computational anatomy.

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Multicasting in Long-Term Evolution (LTE) environments poses several challenges if it is to be reliably implemented. Neither retransmission schemes nor Forward Error Correction (FEC), the traditional error correction approaches, can be readily applied to this system of communication if bandwidth and resources are to be used efficiently. A large number of network parameters and topology variables can influence the cost of telecommunication in such a system. These need to be considered when selecting an appropriate error correction technique for a certain LTE multicast deployment. This dissertation develops a cost model to investigate the costs associated with over-the-air LTE multicasting when different error correction techniques are applied. The benefit of this simplified model is an easily implementable and fast method to evaluate the communications costs of different LTE multicast deployments with the application of error correction techniques. / MIng (Computer and Electronic Engineering), North-West University, Potchefstroom Campus, 2014

In epidemiological studies of an exposure-response association, often only a mismeasured exposure is taken on each individual of the population under study. If ignored, exposure measurement error can bias the estimated exposure-response association in question. A reliability study may be carried out to estimate the relation between the mismeasured and true exposure, which could then be used to adjust for measurement error in the attenuated exposure-response relationship. However, taking repeated exposure measurements may be expensive. Given a fixed total study cost, a two-stage design may be a more efficient approach for regression parameter estimation compared to the traditional single-stage design since, in the second-stage, repeated measurement is restricted to a sample of first-stage subjects. Sampling the extremes of the first-stage exposure distribution has been shown to be more efficient than random sampling.

This thesis explores the impact of peer feedback on two secondary level classrooms studying English as a foreign language in Taiwan. The effectiveness of teacher-led feedback has consistently been the focus of the relevant literature but relatively fewer studies have experimentally investigated the impact of peer-led feedback on learning. This research is based on the belief that the investigation of the process of peer-led feedback, as well as the effectiveness of peer-led correction, will enhance our understanding of learners’ communicative interactions. These data will allow us the opportunity to provide suggestions for successful second/foreign language learning. This study was conducted following a mixed-methods quasi-experimental design involving a variety of data collection and analysis techniques. Observations of peer-peer dialogues taken from a Year 7 and a Year 8 class were analysed using content analysis, in order to classify the types of peer feedback provided by the Year 7 and Year 8 learners. Pre-and post-measures, including English speaking tests, questionnaires, and checklists, were examined with non-parametric statistical tests used to explore any changes in relation to the learners’ speaking development after the quasi-experiment. Key findings included frequency and distribution of seven types of peer feedback, as used by the Year 7 and Year 8 learners, and the statistical results that revealed the differences between the pre-and post-measures. Among the seven types of peer feedback (translation, confirmation, completion, explicit indication, explicit correction, explanation and recasts), explicit correction and translation were the two techniques used most frequently by the learners. Post-test results indicated an improvement in the learners’ speaking performance. The results of pre- and post-questionnaires and pre- and post-checklists showed different levels of change in the learners’ self-evaluation of their own ability to speak English, as well as their attitudes towards corrective feedback. These results allow us to gain insight into the nature of peer interaction in communicative speaking activities as well as learners’ motives behind their feedback behaviours. Additionally, the results shed light on learners’ opinions towards corrective feedback that they received or provided in peer interaction. Further, the results yield a deepened understanding of impacts of peer feedback on L2 development by examining changes in learners’ speaking performance, self-confidence in speaking English and self-evaluation of their own ability to speak English after a peer-led correction treatment. In conclusion, the study suggests that adolescent learners are willing and able to provide each other with feedback in peer interaction. The feedback that they delivered successfully helps their peers to attend to form and has positive impacts on their peers’ English- speaking performance. Moreover, the study provides explanations for learners’ preference for certain types of feedback techniques, which hopefully helps to tackle the mismatch between teachers’ intentions and learners’ expectations of corrective feedback in the L2 classrooms.