>Magister Scientiae - MSc / Purpose:This research investigates the existence of long-term equilibrium relationships among the stock market indices of Brazil, Russia, India, China and South Africa (BRICS). It further investigates cointegrated stock pairs for possible implementation of statistical arbitrage trading techniques.Design:We utilize standard multivariate time series analysis procedures to inspect unit roots to assess stationarity of the series. Thereafter, cointegration is tested by the Johansen and Juselius (1990) procedure and the variables are interpreted by a Vector Error Correction Model (VECM). Statistical arbitrage is investigated through the pairs trading technique.Findings:The five stock indices are found to be cointegrated. Analysis shows that the cointegration rank among the variables is significantly influenced by structural breaks. Two pairs of stock variables are also found to be cointegrated. This guaranteed the mean reversion property necessary for the successful execution of the pairs trading technique. Determining the optimal spread threshold also proved to be highly significant with respect to the success of this trading technique.Value:This research seeks to expand on the literature covering long-run co-movements of the volatile emerging market indices. Based on the cointegration relation shared by the BRICS, the research also seeks to encourage risk taking when investing. We achieve this by showing the potential rewards that can be realized through employing appropriate statistical arbitrage trading techniques in these markets.

>Magister Scientiae - MSc / There are five fundamental parameters that characterize any sign language gesture. They are hand shape, orientation, motion and location, and facial expressions. The SASL group at the University of the Western Cape has created systems to recognize each of these parameters in an input video stream. Most of these systems make use of the Support Vector Machine technique for the classification of data due to its high accuracy. It is, however, unknown how other machine learning techniques compare to Support Vector Machines in the recognition of each of these parameters. This research lays the foundation for the process of determining optimum machine learning techniques for each parameter by comparing Support Vector Machines to Artificial Neural Networks and Random Forests in the context of South African Sign Language hand shape recognition. Li, a previous researcher at the SASL group, created a state-of-the-art hand shape recognition system that uses Support Vector Machines to classify hand shapes. This research re-implements Li’s feature extraction procedure but investigates the use of Artificial Neural Networks and Random Forests in the place of Support Vector Machines as a comparison. The machine learning techniques are optimized and trained to recognize ten SASL hand shapes and compared in terms of classification accuracy, training time, optimization time and classification time.

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Please read the abstract in the front section of this document / Thesis (PhD (Mathematics))--University of Pretoria, 2006. / Mathematics and Applied Mathematics / unrestricted

Variable speed drive technology has advanced dramatically in the last 10 years with the advent of new power devices. In this study, a three phase induction motor drive using Insulated Gate Bipolar Transistors (IGBT) at the inverter power stage is introduced to implement speed and position control for the revolving stage in the Frederic Wood Theatre This thesis presents a solution to control a 3-phase induction motor using the Texas Instruments (TI) Digital Signal Processor (DSP) TMS320F2407A. The use of this DSP yields enhanced operations, fewer system components, lower system cost and increased efficiency. The control algorithm is based on the constant volts-per-hertz principle because the exact speed control is not needed. Reflective object sensors which are mounted on concrete frame are used to detect accurate edge position of revolving stage. The sinusoidal voltage waveforms are generated by the DSP using the space vector modulation technique. In order to satisfy some operating conditions for safe and agreeable operation, a look-up table, which is used to give command voltage and speed signals in software, is applied to limit the maximum speed and acceleration of the revolving stage. Meanwhile, a boost voltage signal is added at the low frequency areas to make the motor produce maximum output torque when starting. A test prototype is then built to validate the performance. Several tests are implemented into the IGBT drive to explore the reason for unacceptable oscillations in IGBT’s gate control signals. Improvement methods in hardware layout are suggested for the final design. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

The global movement of aquatic non-indigenous species can have severe ecological, environmental and economic impacts emphasizing the need to identify potential invaders and transport pathways. Initial transport is arguably the most important stage of the invasion process owing to its role in selectively determining potential invasion candidates. This study characterizes a well defined human-mediated dispersal mechanism, ballast water transport, as a vector for the introduction of non-indigenous zooplankton. Ballast water exchange in the open ocean is the most widely adopted practice for reducing the threat of aquatic invasions and is mandatory for most foreign vessels intending to release ballast in Canadian waters. Ships entering Canadian ports are categorized into the following three shipping classes based on current regulations: overseas vessels carrying exchanged ballast water, intra-coastal vessels carrying exchanged ballast water or intra-coastal vessels carrying un-exchanged ballast water. This study characterizes zooplankton communities associated with each of these shipping classes sampled from ports on Canada’s Pacific coast, Atlantic coast and the Great Lakes Basin. Ballast water samples were collected and analyzed from 77 vessels between 2006 - 2007. The ballast water environment was found to be diverse, with over 193 zooplankton taxa, 71 of which were non-indigenous to their receiving environments. Intracoastal vessels containing un-exchanged coastal water transported the greatest density of non-indigenous zooplankton into Canadian ports. Total zooplankton density was found to be negatively correlated with ballast water age The absence of mandatory ballast water exchange and the younger ballast water age of coastal un-exchanged vessels is likely responsible for the higher density of non-indigenous zooplankton in intracoastal un-exchanged vessels. Propagule pressure, invasion history and environmental suitability are all useful in evaluating invasion potential and all suggest that intracoastal un-exchanged vessels pose the greatest invasion threat to Canadian aquatic ecosystems. In conclusion, although the risk of primary introductions from overseas ports may have been reduced through open-ocean exchange of ballast water, secondary introductions from previously invaded ports in North America may be the primary threat to Canadian aquatic ecosystems via this transport vector. / Science, Faculty of / Earth, Ocean and Atmospheric Sciences, Department of / Graduate

Within this thesis, I performed a systematic review of approaches to broad-scale modelling of disease vector distributions and determined the most widely used methods predict current species niches and project the models forward under future climate scenarios without temporal validation. I then provided a forward-looking summary of emerging techniques to improve the reliability and transferability of those models, including historical calibration. I then predicted Anopheles mosquito distributions across Tanzania in 2001 (before large-scale ITN distributions) and compared this model with countrywide ITN use by 2012 to assess where the most suitable mosquito habitats were located and whether ITN rollouts in Tanzania ensured coverage of such areas. I concluded that ITNs in Tanzania did not optimally target areas most at risk of malaria. In doing so, I provided a new approach to monitoring and evaluating vector control interventions across large spatial scales.

Weekly collections were conducted from May to December, 2007 (153 trap nights, total) in Denton, Texas, in and around large storm drains and overpass drainage facilities in residential and non-residential areas, using Centers for Disease Control (CDC) light traps and gravid traps. A total of 1964 mosquitoes were collected, representing 24 species within 6 genera: Aedes, Anopheles, Culiseta, Culex, Psorophora, and Uranotaenia. Culex was the most abundant genus, representing 75% of all mosquitoes collected; Aedes was the second most abundant, representing 12 % of all mosquitoes collected. Cx. quinquefasciatus was the dominant species collected via gravid traps; Cx. (Melanoconion) species were the dominant species collected via CDC light traps. Data of gravid traps and light traps were analyzed separately using nonparametric correlation analysis, comparing environmental data and physical characteristics to total abundance of mosquitoes. There was no significant correlation found when comparing the three dominant species collected in light traps (unidentified Cx. (Melanoconion) sp, Cx. quinquefasciatus, and Ae. vexans) to environmental characteristics and physical characteristics. Analysis of Cx. quinquefasciatus collected in gravid traps indicated no significant correlation between abundance, environmental data, and physical characteristics. Linear regression models were analyzed to determine if either environmental variables or physical characteristics of the drainage system explained the species abundance collected; no individual variable showed an association of significance. Analysis of Cx. quinquefasciatus collected in storm drains via gravid traps determined temperature to be the most important variable in determining population abundance and explained 99% of the population variability.

The purpose of this paper is to present the results of a study of linear spaces with special emphasis of linear transformations, norms, and inner products.

Ingeniero Civil Matemático / El suicidio en Chile se ha convertido en uno de los problemas más necesarios de hacer frente en salud pública, más aún, si consideramos que la enorme mayoría de las personas que mueren por suicidio presentan algún diagnóstico psiquiátrico y han consultado a un especialista los meses antes de cometer suicidio. Esto, motiva la creación de indicadores y alertas para detectar de forma eficaz y oportuna cuando una persona ingresa a una zona de riesgo suicida. En el presente trabajo se aborda este problema, definiendo una zona o espectro de riesgo suicida, y generando modelos matemáticos y estadísticos para la detección de pacientes en esta zona de riesgo. Para esto, se utiliza una base de datos de 707 pacientes, consultantes de salud mental, de tres centros de salud distintos de la región metropolitana. La base de datos a su vez contempla 343 variables, incluyendo tanto información sociodemográfica de cada paciente, como también sus respuestas en siete instrumentos clínicos utilizados habitualmente en salud mental (DEQ, STAXI, OQ, RFL, APGAR, PBI Madre y PBI Padre). Inicialmente la base de datos es depurada eliminando aquellos campos y/o registros con gran porcentaje de valores nulos, mientras que la imputación de valores perdidos se realiza mediante técnicas tradicionales y en algunos casos según el criterio experto, donde se utiliza un método de imputación según valor de subescala para los distintos instrumentos clínicos. Posteriormente, se realiza una reducción de atributos mediante el uso de herramientas estadísticas y provenientes del machine learning. Con esta información, se generan cinco modelos utilizando distintas técnicas y herramientas del ámbito de la minería de datos y machine learning mediante aprendizaje supervisado. Los modelos son generados y calibrados usando el lenguaje estadístico R, y se comparan sus resultados mediante cuatro métricas distintas: precisión (o accuracy), sensibilidad, especificidad, y mediante su representación en el espacio ROC. El modelo o clasificador finalmente propuesto corresponde a un modelo de support vector machine, que permite discriminar cuando un paciente se encuentra en una zona de riesgo suicida. El modelo fue entrenado utilizando un kernel de tipo RBF, y utiliza tan sólo 22 variables predictoras, entregando una precisión aproximada del $78%, calculada mediante k-validación cruzada de n-folds con k=100 y n=10.