School Mathematics, Statistics and Computer Science

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Factors affecting the health status of the people of Lesotho.
(2007) Moeti, Abiel.
Lesotho, like any other country of the world, is faced with the task of improving the
Vector graphics to improve BLAST graphic representations
(2007) Jimenez, Rafael.
BLAST reports can be complicated. Viewing them graphically helps to understand them better, especially when the reports are long. At present "Web BLAST" and the stand-alone "wwwBLAST" versions, distributed by the NCBI, include graph- ical viewers for BLAST results. An alternative approach is "BLAST Graphic Viewer" developed by GMOD as part of the BioPerl library. It provides a more aesthetically pleasing and informative graphical visualization to represent BLAST results. All the strategies mentioned above are based on the use of bitmap graph- ics and dependent on JavaScript code embedded in HTML. We present Vector Graphic BLAST (VEGRA) a Python object orientated library based on BioPy- thon to yield graphical visualization of results from BLAST utilizing vector graph- ics. Graphics produced by VEGRA are better than bitmaps for illustration, more exible because they can be resized and stretched, require less memory, and their interactivity is more e ective as it is independent of tertiary technologies due to its integration into the graphic. In addition, the library facilitates a de nition of any layout for the di erent components of the graphic, as well as adjustment of size and colour properties. This dissertation studies previous alternatives and improves them by making use of vector graphics and thus allowing more e ective presentation of results. VEGRA is not just an improvement for BLAST visualiza- tion but a model that illustrates how other visualization tools could make use of vector graphics. VEGRA currently works with BLAST, nevertheless the library has been written to be extended to other visualization problems.
Estimating risk determinants of HIV and TB in South Africa.
(2009) Mzolo, Thembile.; Mwambi, Henry G.; Zuma, Khangelani.
Where HIV/AIDS has had its greatest adverse impact is on TB. People with TB that are infected with HIV are at increased risk of dying from TB than HIV. TB is the leading cause of death in HIV individuals in South Africa. HIV is the driving factor that increases the risk of progression from latent TB to active TB. In South Africa no coherent analysis of the risk determinants of HIV and TB has been done at the national level this study seeks to mend that gab. This study is about estimating risk determinants of HIV and TB. This will be done using the national household survey conducted by Human Sciences Research Council in 2005. Since individuals from the same household and enumerator area more likely to be more alike in terms of risk of disease or correlated among each other, the GEEs will be used to correct for this potential intraclass correlation. Disease occurrence and distribution is highly heterogeneous at the population, household and the individual level. In recognition of this fact we propose to model this heterogeneity at community level through GLMMs and Bayesian hierarchical modelling approaches with enumerator area indicating the community e ect. The results showed that HIV is driven by sex, age, race, education, health and condom use at sexual debut. Factors associated with TB are HIV status, sex, education, income and health. Factors that are common to both diseases are sex, education and health. The results showed that ignoring the intraclass correlation can results to biased estimates. Inference drawn from GLMMs and Bayesian approach provides some degree of con dence in the results. The positive correlation found at an enumerator area level for both HIV and TB indicates that interventions should be aimed at an area level rather than at the individual level.
Component-based face recognition.
(2008) Dombeu, Jean Vincent Fonou.; Tapamo, Jules-Raymond.
Component-based automatic face recognition has been of interest to a growing number of researchers in the past fifteen years. However, the main challenge remains the automatic extraction of facial components for recognition in different face orientations without any human intervention; or any assumption on the location of these components. In this work, we investigate a solution to this problem. Facial components: eyes, nose, and mouth are firstly detected in different orientations of face. To ensure that the components detected are appropriate for recognition, the Support Vector Machine (SVM) classifer is applied to identify facial components that have been accurately detected. Thereafter, features are extracted from the correctly detected components by Gabor Filters and Zernike Moments combined. Gabor Filters are used to extract the texture characteristics of the eyes and Zernike Moments are applied to compute the shape characteristics of the nose and the mouth. The texture and the shape features are concatenated and normalized to build the final feature vector of the input face image. Experiments show that our feature extraction strategy is robust, it also provides a more compact representation of face images and achieves an average recognition rate of 95% in different face orientations.
Centre manifold theory with an application in population modelling.
(2009) Phongi, Eddy Kimba.; Banasiak, Jacek.
There are basically two types of variables in population modelling, global and local variables. The former describes the behavior of the entire population while the latter describes the behavior of individuals within this population. The description of the population using local variables is more detailed, but it is also computationally costly. In many cases to study the dynamics of this population, it is sufficient to focus only on global variables. In applied sciences, to achieve this, the method of aggregation of variables is used. One of methods used to mathematically justify variables aggregation is the centre manifold theory. In this dissertation we provide detailed proofs of basic results of the centre manifold theory and discuss some examples of applications in population modelling.
Complete symmetry groups : a connection between some ordinary differential equations and partial differential equations.
(2008) Myeni, Senzosenkosi Mandlakayise.; Leach, Peter Gavin Lawrence.; O’Hara, J. G.
The concept of complete symmetry groups has been known for some time in applications to ordinary differential equations. In this Thesis we apply this concept to partial differential equations. For any 1+1 linear evolution equation of Lie’s type (Lie S (1881) Uber die Integration durch bestimmte Integrale von einer Klasse linear partieller Differentialgleichung Archiv fur Mathematik og Naturvidenskab 6 328-368 (translation into English by Ibragimov NH in CRC Handbook of Lie Group Analysis of Differential Equations 2 473-508) containing three and five exceptional point symmetries and a nonlinear equation admitting a finite number of Lie point symmetries, the representation of the complete symmetry group has been found to be a six-dimensional algebra isomorphic to sl(2,R) s A3,1, where the second subalgebra is commonly known as the Heisenberg-Weyl algebra. More generally the number of symmetries required to specify any partial differential equations has been found to equal the number of independent variables of a general function on which symmetries are to be acted. In the absence of a sufficient number of point symmetries which are not solution symmetries one must look to generalized or nonlocal symmetries to remove the deficiency. This is true whether the evolution equation be linear or not. We report Ans¨ atze which provide a route to the determination of the required nonlocal symmetry or symmetries necessary to supplement the point symmetries for the complete specification of the equations. Furthermore we examine the connection of ordinary differential equations to partial differential equations through a common realisation of complete symmetry group. Lastly we revisit the notion of complete symmetry groups and further extend it so that it refers to those groups that uniquely specify classes of equations or systems. This is based on some recent developments pertaining to the properties and the behaviour of such groups in differential equations under the current definition, particularly their representations and realisations for Lie remarkable equations. The results seem to be quite astonishing.
Application of the wavelet transform for sparse matrix systems and PDEs.
(2009) Karambal, Issa.; Paramasur, Nabendra.; Singh, Pravin.
We consider the application of the wavelet transform for solving sparse matrix systems and partial differential equations. The first part is devoted to the theory and algorithms of wavelets. The second part is concerned with the sparse representation of matrices and well-known operators. The third part is directed to the application of wavelets to partial differential equations, and to sparse linear systems resulting from differential equations. We present several numerical examples and simulations for the above cases.
Inference from finite population sampling : a unified approach.
(2007) Hargovan, Kashmira Ansuyah.; Arnab, Raghunath.; North, Delia Elizabeth.
In this thesis, we have considered the inference aspects of sampling from a finite population. There are significant differences between traditional statistical inference and finite population sampling inference. In the case of finite population sampling, the statistician is free to choose his own sampling design and is not confined to independent and identically distributed observations as is often the case with traditional statistical inference. We look at the correspondence between the sampling design and the sampling scheme. We also look at methods used for drawing samples. The non – existence theorems (Godambe (1955), Hanurav and Basu (1971)) are also discussed. Since the minimum variance unbiased estimator does not exist for infinite populations, a number of estimators need to be considered for estimating the same parameter. We discuss the admissible properties of estimators and the use of sufficient statistics and the Rao-Blackwell Theorem for the improvement of inefficient inadmissible estimators. Sampling strategies using auxiliary information, relating to the population, need to be used as no sampling strategy can provide an efficient estimator of the population parameter in all situations. Finally few well known sampling strategies are studied and compared under a super population model.
Investigation of techniques for automatic polyphonic music transcription using wavelets.
(2009) McGuiness, John C.; Murrell, Hugh Crozier.
It has been said (although sadly I have no source) that music is one of the most useful yet useless phenomena known to mankind. Useless in that it has, apparently, no tangible or immediately practical function in our lives, but extremely useful in that it is a truly universal language between human beings, which transcends boundaries and allows us to express ourselves and experience emotions in rather profound ways. For the majority of us, music exists to be listened to, appreciated, admired (sometimes reviled) but generally as some sort of stimulus for our auditory senses. Some of us feel the need to produce music, perhaps simply for our own creative enjoyment, or maybe because we crave the power it lends us to be able to inspire feelings in others. For those of us who love to know “the reason why” or “how things work” and wish to discover the secrets of music, arguably the greatest of all the arts, there can surely be no doubt that a fascinating world of mathematics, harmony and beauty awaits us. Perhaps the reason why music is able to convey such strong emotions in us is because we are (for whatever strange evolutionary reason or purpose) designed to be innately pattern pursuing, sequence searching and harmony hungry creatures. Music, as we shall discover in this research, is chock-a-block full of the most incredible patterns, which are just waiting to be deciphered.
D-optimal designs for drug synergy.
(2009) Kabera, Muregancuro Gaëtan.; Ndlovu, Principal.; Haines, Linda Margaret.
This thesis is focused on the construction of optimal designs for detecting drug interaction using the two-variable binary logistic model. Two specific models are considered: (1) the binary two-variable logistic model without interaction, and (2) the binary two-variable logistic model with interaction. The two explanatory variables are assumed to be doses of two drugs that may or may not interact when jointly administered to subjects. The main objective of the thesis is to algebraically construct the optimal designs. However, numerical computations are used for constructing optimal designs in cumbersome cases. The problem of constructing optimal designs is to allocate weights to specific points of the design space in such a way that information associated with model parameters is maximized and the variances of the mean responses are minimized. Specifically, the D-optimality criterion discussed in this thesis minimizes the determinant of the asymptotic variance-covariance matrix of the estimates of the model parameters. The number of support points of the D-optimal designs for the two- variable binary logistic model without interaction varies from 3 to 6. Support points are equally weighted only in case of the 3-point designs and in some special cases of the 4-point designs. The number of support points of the D-optimal designs for the two-variable binary logistic model with interaction varies from 4 to 8. Support points are equally weighted only in case of the 4-point designs and in some special cases of 8-point designs. Numerous examples are given to illustrate theoretical results.
Modeling environmental factors affecting the growth of eucalypt clones.
(2009) Chauke, Morries.; Zewotir, Temesgen Tenaw.; Ndlovu, Principal.; Grzeskowiak, Valerie.
Tree growth is influenced by environment and genetic factors. The same tree growing in different areas will have different growth patterns. Trees with different genetic material, e.g. pine and Eucalyptus trees, growing under the same environmental conditions have different growth patterns. Plantation trees in South Africa are mainly used for pulp and paper production. Growth is an important economic factor in the pulp and paper industry. Plantations with fast growth will be available for processing earlier compared to a slow growth plantation. Consequently, it is important to understand the role played by environmental factors, especially climatic factors, on tree growth. This thesis investigated the climatic effects on the radial growth of two Eucalyptus clones using growth data collected daily over five years by Sappi. The general linear model and the time series models were used to assess the effects of climate on radial growth of the two clones. It was found that the two clones have similar overall growth patterns over time, but differ in growth rates. The growth pattern of the two clones appears to be characterized by substantial jumps/changes in growth rates over time. The times at which the jumps/changes in growth rate occur are referred to as the “breakpoints”. The piecewise linear regression model was used to estimate when the breakpoints occur. After estimating the breakpoints, the climatic effects associated with these breakpoints were investigated. The linear and time series modeling results indicated that the contribution of climatic factors on radial growth of Eucalyptus clones was small. Most of the variation in radial growth was explained by the age of the trees. Consequently, this thesis also investigated the appropriate functional relationship between radial growth and age. In particular, this nonlinear growth models were used to model the radial growth process. The investigated growth curve models were those which included the maximum radius and the age at which the radial growth rate is largest as some of the parameters. The maximum growth rate was calculated from the estimated model of each clone. The results indicated that the two clones reach the maximum growth rate at different times. In particular, the two clones reach the maximum growth rates at around 368 and 376 days, respectively. Furthermore, the maximum radius was found to be different for the two clones.
Modelling acute HIV infection using longitudinally measured biomarker data including informative drop-out.
(2009) Werner, Lise.; Mwambi, Henry G.
Background. Numerous methods have been developed to model longitudinal data. In HIV/AIDS studies, HIV markers, CD4+ count and viral load are measured over time. Informative drop-out and the lower detection limit of viral load assays can bias the results and influence assumptions of the models. Objective The objective of this thesis is to describe the evolution of HIV markers in an HIV-1 subtype C acutely infected cohort of women from the CAPRISA 002: Acute Infection Study in Durban, South Africa. They were HIV treatment naive. Methods. Various linear mixed models were fitted to both CD4+ count and viral load, adjusting for repeated measurements, as well as including intercept and slope as random effects. The rate of change in each of the HIV markers was assessed using weeks post infection as both a linear effect and piecewise linear effects. Left-censoring of viral load was explored to account for missing data resulting from undetectable measurements falling below the lower detection limit of the assay. Informative drop- out was addressed by using a method of joint modelling in which a longitudinal and survival model were jointly linked using a latent Gaussian process. The progression of HIV markers were described and the effectiveness and usefulness of each modelling procedure was evaluated. Results. 62 women were followed for a median of 29 months post infection (IQR 20-39). Viral load increased sharply by 2.6 log copies/ml per week in the first 2 weeks of infection and decreased by 0.4 log copies/ml per week the next fortnight. It decreased at a slower rate thereafter. Similarly CD4+ count fell in the first 2 weeks by 4.4 square root cells/ul per week then recovered slightly only to decrease again. Left-censoring was unnecessary in this acute infection cohort as few viral load measures were below the detection limit and provided no improvement on model fit. Conclusion. Piecewise linear effects proved to be useful in quantifying the degree at which the HIV markers progress during the first few weeks of HIV infection, whereas modelling time as a linear effect was not very meaningful. Modelling HIV markers jointly with informative drop-out is shown to be necessary to account for the missing data incurred from participants leaving the study to initiate ARV treatment. In ignoring this drop-out, CD4+ count is estimated to be higher than what it actually is.
Time series modelling with application to South African inflation data
(2009) Chinomona, Amos
The research is based on financial time series modelling with special application
Linear model diagnostics and measurement error
(2010-09-07) Siverpersad, Ishara.
The general linear model, the weighted linear model, and the generalized linear model are presented in detail. Diagnostic tools for the linear models are considered. In general the standard analysis for linear models does not account for measurement error.
Computer assisted education : design, development and evaluation.
(2001) Murrell, Katherine Ann.; Meyerowitz, Jane Julia.
Educational institutions throughout the world are increasingly facing classes of educationally, culturally and linguistically diverse student groups. At the same time economic constraints require these institutions to expand their student base and they are therefore looking to distance education and continuing education modules to meet these challenges. Simultaneously rapid advances in desktop computing capabilities and Internet delivered information have revived interest in Computer Assisted Education (CAE). The University of Natal is no exception to these trends; schools, departments and individual members of staff are increasingly exploring the possibility of using the University's computer infrastructure to assist in delivering quality education, maintaining current standards, and addressing the multiple needs of the students. To investigate these issues a CAE program was developed for use in the Nelson R. Mandela School of Medicine to investigate how students would make use 'of the technology, and to report on the development and evaluation processes of such a development. In doing so various lessons could be learnt which could inform the further development of such software at the University. In order to support the development of the CAE program an extensive literature survey into current educational theory was conducted. Its objectives were to explore and understand all the factors affecting the development and use of computer based systems as an educational tool. Particular aspects considered were • the debate between constructivist and instructivist theory in their applicability to both the medium and the subject material. • instructional styles, and with them the learning styles, that could be used to support the educational goals of the diverse student population. • instructional design methodologies that are currently used as well as media production methodologies. The goal of this aspect of the research was to advise both the development of the case study and to gain a broader understanding of the methodology that could be used for other developments. Included in this phase of the research are methods and criteria for selection of authoring systems and interface design issues in a multi-cultural multi-lingual environment. • the review of different evaluation strategies in order to incorporate appropriate evaluation in the CAE case study. • the investigation of broader sociological and historical factors that may influence the way in which CAE can be used effectively in a South African context. The presumption was that students from historically disadvantaged backgrounds and those with English as a second language would be less willing to use technological interventions than those who were more likely to have had access to computers earlier in their education. The case study set out to investigate if this presumption was valid, and if so what elements of design and delivery could facilitate these students' usage of such systems. However, these presumptions were not validated by the case study, showing the exact opposite of expectations, with more historically disadvantaged students showing a willingness to use the module.
Consequences of architecture and resource allocation for growth dynamics of bunchgrass clones.
(2005) Tomlinson, Kyle Warwick.; O'Connor, Timothy Gordon.; Hearne, John W.; Swart, Johan.
In order to understand how bunchgrasses achieve dominance over other plant growth forms and how they achieve dominance over one another in different environments, it is first necessary to develop a detailed understanding of how their growth strategy interacts with the resource limits of their environment. Two properties which have been studied separately in limited detail are architecture and disproportionate resource allocation. Architecture is the structural layout of organs and objects at different hierarchical levels. Disproportionate resource allocation is the manner in which resources are allocated across objects at each level of hierarchy. Clonal architecture and disproportionate resource allocation may interact significantly to determine the growth ability of clonal plants. These interactions have not been researched in bunchgrasses. This thesis employs a novel simulation technique, functional-structural plant modelling, to investigate how bunchgrasses interact with the resource constraints imposed in humid grasslands. An appropriate functional-structural plant model, the TILLERTREE model, is developed that integrates the architectural growth of bunchgrasses with environmental resource capture and disproportionate resource allocation. Simulations are conducted using a chosen model species Themeda triandra, and the environment is parameterised using characteristics of the Southern Tall Grassveld, a humid grassland type found in South Africa. Behaviour is considered at two levels, namely growth of single ramets and growth of multiple ramets on single bunchgrass clones. In environments with distinct growing and non-growing seasons, bunchgrasses are subjected to severe light depletion during regrowth at the start of each growing season because of the accumulation of dead material in canopy caused by the upright, densely packed manner in which they grow. Simulations conducted here indicate that bunchgrass tillers overcome this resource bottleneck through structural adaptations (etiolation, nonlinear blade mass accretion, residual live photosynthetic surface) and disproportionate resource allocation between roots and shoots of individual ramets that together increase the temporal resource efficiency of ramets by directing more resources to shoot growth and promoting extension of new leaves through the overlying dead canopy. The architectural arrangement of bunchgrasses as collections of tillers and ramets directly leads to consideration of a critical property of clonal bunchgrasses: tiller recruitment. Tiller recruitment is a fundamental discrete process limiting the vegetative growth of bunchgrass clones. Tiller recruitment occurs when lateral buds on parent tillers are activated to grow. The mechanism that controls bud outgrowth has not been elucidated. Based on a literature review, it is here proposed that lateral bud outgrowth requires suitable signals for both carbohydrate and nitrogen sufficiency. Subsequent simulations with the model provide corroborative evidence, in that greatest clonal productivity is achieved when both signals are present. Resource allocation between live structures on clones may be distributed proportionately in response to sink demand or disproportionately in response to relative photosynthetic productivity. Model simulations indicate that there is a trade-off between total clonal growth and individual tiller growth as the level of disproportionate allocation between ramets on ramet groups and between tillers on ramets increases, because disproportionate allocation reduces tiller population size and clonal biomass, but increases individual tiller performance. Consequently it is proposed that different life strategies employed by bunchgrasses, especially annual versus perennial life strategies, may follow more proportionate and less proportionate allocation strategies respectively, because the former favours maximal resource capture and seed production while the latter favours individual competitive ability. Structural disintegration of clones into smaller physiologically integrated units (here termed ramet groups) that compete with one another for resources is a documented property of bunchgrasses. Model simulations in which complete clonal integration is enforced are unable to survive for long periods because resource bottlenecks compromise all structures equally, preventing them from effectively overcoming resource deficits during periods when light is restrictive to growth. Productivity during the period of survival is also reduced on bunchgrass clones with full integration relative to clones that disintegrate because of the inefficient allocation of resources that arises from clonal integration. This evidence indicates that clonal disintegration allows bunchgrass clones both to increase growth efficiency and pre-empt potential death, by promoting the survival of larger ramet groups and removing smaller ramet groups from the system. The discrete nature of growth in bunchgrasses and the complex population dynamics that arise from the architectural growth and the temporal resource dynamics of the environment, may explain why different bunchgrass species dominate under different environments. In the final section this idea is explored by manipulating two species tiller traits that have been shown to be associated with species distributions across non-selective in defoliation regimes, namely leaf organ growth rate and tiller size (mass or height). Simulations with these properties indicate that organ growth rate affects daily nutrient demands and therefore the rate at which tillers are terminated, but had only a small effect on seasonal resource capture. Tiller mass size affects the size of the live tiller population where smaller tiller clones maintain greater numbers of live tillers, which allows them to them to sustain greater biomass over winter and therefore to store more reserves for spring regrowth, suggesting that size may affect seasonal nitrogen capture. The greatest differences in clonal behaviour are caused by tiller height, where clones with shorter tillers accumulate substantially more resources than clones with taller tillers. This provides strong evidence there is trade-off for bunchgrasses between the ability to compete for light and the ability to compete for nitrogen, which arises from their growth architecture. Using this evidence it is proposed that bunchgrass species will be distributed across environments in response to the nitrogen productivity. Shorter species will dominate at low nitrogen productivity, while taller species dominate at high nitrogen productivity. Empirical evidence is provided in support of this proposal.
An investigation into the use of genetic programming for the induction of novice procedural programming solution algorithms in intelligent programming tutors.
(2004) Pillay, Nelishia.; Sartori-Angus, Alan G.
Intelligent programming tutors have proven to be an economically viable and effective means of assisting novice programmers overcome learning difficulties. However, the large-scale use of intelligent programming tutors has been impeded by the high developmental costs associated with building intelligent programming tutors. The research presented in this thesis forms part of a larger initiative aimed at reducing these costs by building a generic architecture for the development of intelligent programming tutors. One of the facilities that must be provided by the generic architecture is the automatic generation of solutions to programming problems. The study presented in the thesis examines the use of genetic programming as means of inducing solution algorithms to novice programming problems. The scope of the thesis is limited to novice procedural programming paradigm problems requiring the use of arithmetic, string manipulation, conditional, iterative and recursive programming structures. The methodology employed in the study is proof-by-demonstration. A genetic programming system for the induction of novice procedural solution algorithms was implemented and tested on randomly chosen novice procedural programming problems. The study has identified the standard and advanced genetic programming features needed for the successful generation of novice procedural solution algorithms. The outcomes of this study include the derivation of an internal representation language for representing procedural solution algorithms and a high-level programming problem specification format for describing procedural problems, in the generic architecture. One of the limitations of genetic programming is its susceptibility to converge prematurely to local optima and not find a solution in some cases. The study has identified fitness function biases against certain structural components that are needed to find a solution, as an additional cause of premature convergence in this domain. It presents an iterative structure-based algorithm as a solution to this problem. This thesis has contributed to both the fields of genetic programming and intelligent programming tutors. While genetic programming has been successfully implemented in various domains, it is usually applied to a single problem within that domain. In this study the genetic programming system must be capable of solving a number of different programming problems in different application domains. In addition to this, the study has also identified a means of overcoming premature convergence caused by fitness function biases in a genetic programming system for the induction of novice procedural programming algorithms. Furthermore, although a number of studies have addressed the student modelling and pedagogical aspects of intelligent programming tutors, none have examined the automatic generation of problem solutions as a means of reducing developmental costs. Finally, this study has contributed to the ongoing research being conducted by the artificial intelligence in education community, to test the effectiveness of using machine learning techniques in the development of different aspects of intelligent tutoring systems.
Longitudinal survey data analysis.
(2006) Nasirumbi, Pamela Opio.; Zewotir, Temesgen Tenaw.
To investigate the effect of environmental pollution on the health of children in the Durban South Industrial Basin (DSIB) due to its proximity to industrial activities, 233 children from five primary schools were considered. Three of these schools were located in the south of Durban while the other two were in the northern residential areas that were closer to industrial activities. Data collected included the participants' demographic, health, occupational, social and economic characteristics. In addition, environmental information was monitored throughout the study specifically, measurements on the levels of some ambient air pollutants. The objective of this thesis is to investigate which of these factors had an effect on the lung function of the children. In order to achieve this objective, different sample survey data analysis techniques are investigated. This includes the design-based and model-based approaches. The nature of the survey data finally leads to the longitudinal mixed model approach. The multicolinearity between the pollutant variables leads to the fitting of two separate models: one with the peak counts as the independent pollutant measures and the other with the 8-hour maximum moving average as the independent pollutant variables. In the selection of the fixed-effects structure, a scatter-plot smoother known as the loess fit is applied to the response variable individual profile plots. The random effects and the residual effect are assumed to have different covariance structures. The unstructured (UN) covariance structure is used for the random effects, while using the Akaike information criterion (AIC), the compound symmetric (CS) covariance structure is selected to be appropriate for the residual effects. To check the model fit, the profiles of the fitted and observed values of the dependent variables are compared graphically. The data is also characterized by the problem of intermittent missingness. The type of missingness is investigated by applying a modified logistic regression model missing at random (MAR) test. The results indicate that school location, sex and weight are the significant factors for the children's respiratory conditions. More specifically, the children in schools located in the northern residential areas are found to have poor respiratory conditions as compared to those in the Durban-South schools. In addition, poor respiratory conditions are also identified for overweight children.
The application of the unified modelling language and soft systems metholdology for modelling the production process in an aluminium plant.
(2003) Sewchurran, Kosheek.; Warren, Peter R.
This research explores the combined use of soft systems methodology (SSM) and UML based business process modelling (BPM) techniques. These two techniques are integrated to provide a framework for the analysis and definition of suitable business process models. Such integration better supports developers following objectoriented (00) approaches than traditional business process modelling. The thesis describes the importance and difficulties in getting development proj ects aimed at the correct needs. We provide an overview of current business process modelling practices. From this it is argued that current practices show two major weaknesses. Firstly, the modelling language that is used is not a current standard amongst developers who now expect 00 and UML based approaches. Secondly, the techniques used do not emphasise analysis, often resulting in a lack of appreciation of the problem. In order to deal with these inadequacies, the thesis critically examines suitable techniques that can be used to analyse and model business processes to support the developer's requirements. The examination of SSM reveals that the technique does deal with the analysis limitations of current business process modelling techniques. SSM has been linked to information systems provision by previous researchers. Unfortunately the examination ofthese research attempts shows that the linking is conducted in an ad-hoc manner with no underlying theoretical basis or emphasis on business process modelling. We show how soft systems methodology techniques can be married with Eriksson and Penker (2000) UML business process modelling techniques following Mingers (2001) multi-methodology framework in a way that can over come these difficulties. This combined business analysis and modelling technique is applied to the production process in an aluminium rolling plant. Based on the experiences at one site, the integrated approach is able to deal with the complexities caused by multiple stakeholders, and is able to provide a UML representation of the required business process to guide developers.
Executive information systems usage : the impact of web-based technologies.
(2002) Averweg, Udo Richard Franz.; Petkov, Don.
Executive Information Systems (EIS) grew out ofthe information needs of top executives. The recent literature reports that EIS usage has spread throughout organisations. Web-based technologies are causing a revisit of existing IT implementation models, including those for EIS. These technologies include: Intranet, Internet, Extranet, e-Commerce: Business-to-Business (B2B), e-Comrnerce: Business-to-Consumer (B2C), Wireless Application Protocol (WAP) and other mobile technologies. The author conducts a field study of 31 well-established organisations in KwaZulu/Natal, South Africa, which have EIS experience. A validated survey instrument is administered to an EIS stakeholder in each organisation surveyed. This dissertation reports on (1) an investigation into previous research on IT adoption; (2) that there is little evidence to support that the theoretical usage aspects of the Technology Acceptance Model (TAM) are echoed in EIS implementations in KwaZulu/Natal; and (3) identifies and ranks Web-based technologies in order of their perceived impact on EIS currently and in the future. There is a positive impact level trend for all Web-based technologies on future EIS implementations. The results from this field study could be useful in formulating a set of management perspectives for organisations in South Africa wishing to embark on EIS implementation programs.

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