Background: Immunological and virological responses to ART are important outcome indicators that are mostly used to evaluate the success of an ART program. A comparative performance between ART providers based on the two outcomes can be useful in optimising resources to underperforming providers and advising quality improvement plans. Aim: To compare immunological and virological responses of ART for adult HIV positive patients between providers in Tshwane District, Gauteng Province, South Africa. Methodology: This study was an analytical observational study that retrospectively compared patient treatment outcomes on immunological and virological responses between 16 Antiretroviral Therapy (ART) providers. The analysis compared baseline patients’ status on these two outcomes with their statuses after 6 and12 months on ART. Ordinary logistic regression was used to calculate Standardised Incidence Ratios (SIR), while multilevel model analysis was used to calculate specific provider random effects of poor immunological and virological responses. Results: After 6 months of treatment, the SIR of poor immunological outcome for all clinics under study, as predicted by the unadjusted logistic regression models was 0.29 (95% CI: 0.27-0.31), but varied from a low of 0.14 (95% CI: 0.00-0.40) to a high of 0.66 (95% CI: 0.13-1.20) between the clinics. Two clinics had a Standardised Incidence Ratio (SIR) of poor immunological response that was significantly below 1 (poor immunological rate below average), while three clinics had an SIR above 1 (poor immunological rate above average) under the unadjusted logistic models. After adjusting for the effects of gender, age, drug combination, religion and present virological status, no clinic had a SIR that was significantly below 1, but two clinics had a SIR that was significantly above 1. xi Under the logistic multilevel (MLLR) analysis, the unadjusted model flagged two clinics whose clinic specific effects were below zero (lower rate of poor immunological outcome below that of the total sample) and one clinic whose clinic specific effect was above zero (higher rate of poor immunological outcome below the total sample rate). The adjusted model showed that no clinic had residual effects that were significantly below or above zero. The confidence intervals for MLLR model were found not to be wider than those of the logistic regression (LR) models particularly for clinics with small sample sizes. A number of clinics changed the relative order of their SIR/random effects after case-mix adjustments under both the LR and MLLR modelling. For poor virological response, both the LRD and MLLR models indicated no clinic specific effects. The predicted poor virological response rate by the case-mix unadjusted LR model was 0.12 (95% CI 0.11 - 0.13). All clinics except one had SIRs that were not significantly different from 1. After adjusting for CD4 count and age, no clinic had an SIR that was significantly different from 1. Conclusions: Case-mix or patients baseline characteristics explained much of the variation in the Standardised Incidence Ratios (SIR) of poor immunological outcome after 6 months of patient treatment, while provider (clinic) specific effects explained much of the variation after 12 months of treatment. After 6 months of treatment, the results also showed that there were significant differences in the SIR between the clinics before case-mix adjustments, but the differences disappeared after case-mix adjustments. This shows that comparison of treatment outcomes between providers (clinics) can be misleading if no proper adjustment are made for confounding factors. Differences in the SIRs for poor virological outcome, after 6 months of patient treatment were no longer significant between clinics after taking account of CD4 count and age. / Dissertation (MSc)--University of Pretoria, 2014. / gm2014 / School of Health Systems and Public Health / unrestricted

In this thesis, we present the local rank differences (LRD). These novel image features are invariant to lighting changes and are suitable for object detection in programmable hardware, such as FPGA. The performance of AdaBoost classifiers with the LRD was tested on a face detection dataset with results which are similar to the Haar-like features which are the state of the art in real-time object detection. These results together with the fact that the LRD are evaluated much faster in FPGA then the Haar-like features are very encouraging and suggest that the LRD may be a solution for future hardware object detectors. We also present a framework for experiments with boosting methods in computer vision. This framework is very flexible and, at the same time, offers high learning performance and a possibility for future parallelization. The framework is available as open source software and we hope that it will simplify work for other researchers.

This thesis deals with a face detection on mobile phones. It especially focuses on Windows Mobile platform. The introduction is therefore devoted to this operating system and alternatives of working with the camera. The next part of the text refers to general problems of the face detection in the image considering the weak performance of the target device. Another part of this thesis is a description of the acquisition of images from the camera using DirectShow multimedia framework and creation of a custom transformation filter for the face detection. Achieved results are summarized in the conclusion. It takes a form of tests examining different mobile devices. All difficulties arising during Windows Mobile developing are also mentioned.

This master's thesis deals with face detection on mobile phones with Android OS. The introduction describes some algorithms used for pattern detection from image, as well as various techniques of features extracting. After that Android platform development specifics, including basic description of development tools, are described. Architecture of SIMD is introduced in next part of this work. After acquiring basic knowleage analysis and implementation of final app are descrited. Performance tests are conducted whose results are summarized in the conclusion.

This thesis concerns measuring, understanding and modelling Internet traffic. We first study the origins of the statistical properties of Internet traffic, in particular its scaling behaviour, and propose a constructive model of packet traffic with physically motivated parameters. We base our analysis on a large amount of empirical data measured on different networks, and use a so called semi-experimental approach to isolate certain features of traffic we seek to model. These results lead to the choice of a particular Poisson cluster process, known as Bartlett-Lewis point process, for a new packet traffic model. This model has a small number of parameters with simple networking meaning, and is mathematically tractable. It allows us to gain valuable insight on the underlying mechanisms creating the observed statistics. / In practice, Internet traffic measurements are limited by the very large amount of data generated by high bandwidth links. This leads us to also investigate traffic sampling strategies and their respective inversion methods. We argue that the packet sampling mechanism currently implemented in Internet routers is not practical when one wants to infer the statistics of the full traffic from partial measurements. We advocate the use of flow sampling for many purposes. We show that such sampling strategy is much easier to invert and can give reasonable estimates of higher order traffic statistics such as distribution of number of packets per flow and spectral density of the packet arrival process. This inversion technique can also be used to fit the Bartlett-Lewis point process model from sampled traffic. / We complete our understanding of Internet traffic by focusing on the small scale behaviour of packet traffic. To do so, we use data from a fully instrumented Tier-1 router and measure the delays experienced by all the packets crossing it. We present a simple router model capable of simply reproducing the measured packet delays, and propose a scheme to export router performance information based on busy periods statistics. We conclude this thesis by showing how the Bartlett-Lewis point process can model the splitting and merging of packet streams in a router.

The thesis deals with image classifiers and their implementation using FPGA technology. There are discussed weak and strong classifiers in the work. As an example of strong classifiers, the AdaBoost algorithm is described. In the case of weak classifiers, basic types of feature classifiers are shown, including Haar and Gabor wavelets. The rest of work is primarily focused on LBP, LRP and LR classifiers, which are well suitable for efficient implementation in FPGAs. With these classifiers is designed pseudo-parallel architecture. Process of classifications is divided on software and hardware parts. The thesis deals with hardware part of classifications. The designed classifier is very fast and produces results of classification every clock cycle.

Táto práca popisuje niekoľko vybraných algoritmov, ktoré boli primárne vyvinuté pre CPU procesory, avšak vzhľadom k vysokému dopytu po ich vylepšeniach sme sa rozhodli ich využiť v prospech GPGPU (procesorov grafického adaptéra). Modifikácia týchto algoritmov bola zároveň cieľom nášho výskumu, ktorý  bol prevedený pomocou CUDA rozhrania. Práca je členená podľa troch skupín algoritmov, ktorým sme sa venovali: detekcia objektov v reálnom čase, spektrálna analýza obrazu a detekcia čiar v reálnom čase. Pre výskum detekcie objektov v reálnom čase sme zvolili použitie LRD a LRP funkcií.  Výskum spektrálnej analýzy obrazu bol prevedný pomocou PCA a NTF algoritmov. Pre potreby skúmania detekcie čiar v reálnom čase sme používali dva rôzne spôsoby modifikovanej akumulačnej schémy Houghovej transformácie. Pred samotnou časťou práce venujúcej sa konkrétnym algoritmom a predmetu skúmania, je v úvodných kapitolách, hneď po kapitole ozrejmujúcej dôvody skúmania vybranej problematiky, stručný prehľad architektúry GPU a GPGPU. Záverečné kapitoly sú zamerané na konkretizovanie vlastného prínosu autora, jeho zameranie, dosiahnuté výsledky a zvolený prístup k ich dosiahnutiu. Súčasťou výsledkov je niekoľko vyvinutých produktov.