L'utilisation de filtre mosaïque hyperspectral semble être la solution idéale pour alléger les imageurs spectraux utilisés lors des missions spatiales. Les contraintes liées à ce type d'utilisation imposent l'emploi de filtres interférentiels multicouches. Ces travaux ont pour but de trouver des solutions pour réaliser un filtre mosaïque hyperspectral avec des filtres interférentiels et non avec les résines colorées traditionnellement utilisées. Pour ce faire une étude théorique sur la simplification des designs des empilements interférentiels a été effectuée. Il en ressort que les empilements restent épais, ce qui complique leur structuration. Plusieurs méthodes de structurations ont été étudiées. En particulier le lift-off qui est la technique actuellement utilisé aujourd'hui et le lift-up. Cette dernière présente l'avantage de ne pas mettre en série le risque technologique associé à chaque réalisation de filtre. Un trade-off entre ces deux techniques a été fait ainsi que des réalisations expérimentales. Celles-ci ont ensuite été caractérisées par un banc de mesure développé dans ce but qui a permis de valider expérimentalement la technique utilisée. / Hyperspectral mosaic filter appears to be the perfect solution to lighten the spectral imagers used in space missions. Such applications require the use of multilayer interference filters. This work aims to find solutions to achieve hyperspectral mosaic filter with interference filters rather than the conventionally used coloured resins. In order to achieve this, a theoretical study on the simplification of multilayer designs was performed. It appears that the stacks are thicker, which makes them difficult to pattern. Several methods of patterning were studied, especially the lift-off technique which is traditionally used and the lift-up. The latter has the advantage to avoid adding the technological risk associated with each filter production. A trade-off between these two techniques was done as well as experimental productions. These were then characterized by a bench developed for this purpose which has experimentally validate the technique used.

O reconhecimento de expressões faciais é uma área de interesse da ciência da computação e tem sido um atrativo para pesquisadores de diferentes áreas, pois tem potencial para promover o desenvolvimento de diferentes tipos de aplicações. Reconhecer automaticamente essas expressões tem se tornado um objetivo, principalmente na área de análise do comportamento humano. Especialmente para estudo das línguas de sinais, a análise das expressões faciais é importante para a interpretação do discurso, pois é o elemento que permite expressar informação prosódica, suporta o desenvolvimento da estrutura gramatical e semântica da língua, e ajuda na formação de sinais com outros elementos básicos da língua. Nesse contexto, as expressões faciais são chamadas de expressões faciais gramaticais e colaboram na composição no sentido semântico das sentenças. Entre as linhas de estudo que exploram essa temática, está aquela que pretende implementar a análise automática da língua de sinais. Para aplicações com objetivo de interpretar línguas de sinais de forma automatizada, é preciso que tais expressões sejam identificadas no curso de uma sinalização, e essa tarefa dá-se é definida como segmentação de expressões faciais gramaticais. Para essa área, faz-se útil o desenvolvimento de uma arquitetura capaz de realizar a identificação de tais expressões em uma sentença, segmentando-a de acordo com cada tipo diferente de expressão usada em sua construção. Dada a necessidade do desenvolvimento dessa arquitetura, esta pesquisa apresenta: uma análise dos estudos na área para levantar o estado da arte; a implementação de algoritmos de reconhecimento de padrões usando Multilayer Perceptron e misturas de especialistas para a resolução do problema de reconhecimento da expressão facial; a comparação desses algoritmos reconhecedores das expressões faciais gramaticais usadas na concepção de sentenças na Língua Brasileira de Sinais (Libras). A implementação e teste dos algoritmos mostraram que a segmentação automática de expressões faciais gramaticais é viável em contextos dependentes do usuários. Para contextos independentes de usuários, o problema de segmentação de expressões faciais representa um desafio que requer, principalmente, a organização de um ambiente de aprendizado estruturado sobre um conjunto de dados com volume e diversidade maior do que os atualmente disponíveis / The recognition of facial expressions is an area of interest in computer science and has been an attraction for researchers in different fields since it has potential for development of different types of applications. Automatically recognizing these expressions has become a goal primarily in the area of human behavior analysis. Especially for the study of sign languages, the analysis of facial expressions represents an important factor for the interpretation of discourse, since it is the element that allows expressing prosodic information, supports the development of the grammatical and semantic structure of the language, and eliminates ambiguities between similar signs. In this context, facial expressions are called grammatical facial expressions. These expressions collaborate in the semantic composition of the sentences. Among the lines of study that explore this theme is the one that intends to implement the automatic analysis of sign language. For applications aiming to interpret signal languages in an automated way, it is necessary that such expressions be identified in the course of a signaling, and that task is called \"segmentation of grammatical facial expressions\'\'. For this area, it is useful to develop an architecture capable of performing the identification of such expressions in a sentence, segmenting it according to each different type of expression used in its construction. Given the need to develop this architecture, this research presents: a review of studies already carried out in the area; the implementation of pattern recognition algorithms using Multilayer Perceptron and mixtures of experts to solve the facial expression recognition problem; the comparison of these algorithms as recognizers of grammatical facial expressions used in the conception of sentences in the Brazilian Language of Signs (Libras). The implementation and tests carried out with such algorithms showed that the automatic segmentation of grammatical facial expressions is practicable in user-dependent contexts. Regarding user-independent contexts, this is a challenge which demands the organization of a learning environment structured on datasets bigger and more diversified than those current available

Este trabalho é um estudo das dispersões metrológicas em aproximações de funções tidas como não conhecidas ou não totalmente conhecidas. A metodologia alternativa para esse fim são as redes neurais artificiais do tipo Multilayer Perceptrons (MLP), aqui utilizadas como aproximadoras de funções. As funções aproximadas são curvas de calibração decorrentes de indicações de instrumentos ou sistemas de medição numa calibração. Essas curvas levam consigo propriedades metrológicas e possuem, neste trabalho, papel de ponte entre os elementos considerados da teoria metrológica e os elementos considerados da teoria da Inteligência Computacional: as Multilayer Perceptrons (MLPs). Uma balança externa de medição de esforços aerodinâmicos e uma Língua Eletrônica (LE), aplicada na medição da concentração de cátions, foram os meios de aplicação dos conceitos dessa metodologia alternativa. As proposições desta tese visam implementar melhorias na exatidão do ajuste das curvas de calibração por meio da consideração dos seguintes fatores: grandezas de influências, incertezas nos Valores Objetivos (VOs), tendência de medição de erros sistemáticos ocultos ou não solvidos e indicadores de desempenho metrológicos. A indicação da qualidade na medição ou a indicação da competência metrológica de um laboratório de calibração é estabelecida pelos valores das incertezas, e a curva de calibração é o ponto de partida para os cálculos desses valores. Visto que o estabelecimento dessa curva é uma das dificuldades para o cálculo das incertezas e a própria curva é uma fonte de incerteza, sua aproximação requer uma a cuidadosa e meticulosa metodologia, daí a importância estratégica deste trabalho. As dispersões metrológicas possuem conotação de incertezas nas medições e elas são a base para a determinação de seu valor numérico; assim, os indicadores de desempenho podem representar essas dispersões e a recíproca também é verdadeira: a incerteza padrão pode ser um dos indicadores de desempenho. Sintetizando, nesta tese é mostrado de que forma a teoria da inteligência computacional adentra na teoria da metrologia e vice versa, nas esferas dos elementos aqui considerados. / The present study investigates metrological dispersions in fitting partially or totally unknown functions. An alternative method is the application of a multilayer perceptron neural network used here to fit functions. The fitting functions are calibration curves from calibration indications of measurement systems or instruments. These curves hold metrological properties and establish a link between elements of Metrological theory and elements of Computing Intelligence theory: the Multilayer Perceptrons. An external balance of aerodynamic forces and moments and an electronic tongue applied in the measurement of cation concentrations were the measurement systems used to apply the concepts of this alternative methodology. This thesis proposes improvements in the accuracy of fitting calibration curves considering the following factors: influence quantities, uncertainties about target values, tendency of hidden or not solved systematic errors and metrological performance functions. The measurement quality indicator or the laboratory metrological competence indicator is established by uncertainty values and the calibration curve is the starting point for the calculation of these values. The establishment of this curve is one of the difficulties in assessing uncertainties and the curve itself is an uncertainty source. Therefore, a careful and meticulous methodology is necessary in curve approximation, which explains the strategic importance of this work. Metrological dispersions have connotation of uncertainty in measurements and are the basis for calculating their numerical values, the performance functions can represent metrological dispersions and the opposite is also true: the standard uncertainty can be a performance function. Making a synthesis, this thesis demonstrates how computing intelligence theory takes into account the metrological theory and vice versa, in the elements of these theories that were discussed in the present study.

O reconhecimento de expressões faciais é uma área de interesse da ciência da computação e tem sido um atrativo para pesquisadores de diferentes áreas, pois tem potencial para promover o desenvolvimento de diferentes tipos de aplicações. Reconhecer automaticamente essas expressões tem se tornado um objetivo, principalmente na área de análise do comportamento humano. Especialmente para estudo das línguas de sinais, a análise das expressões faciais é importante para a interpretação do discurso, pois é o elemento que permite expressar informação prosódica, suporta o desenvolvimento da estrutura gramatical e semântica da língua, e ajuda na formação de sinais com outros elementos básicos da língua. Nesse contexto, as expressões faciais são chamadas de expressões faciais gramaticais e colaboram na composição no sentido semântico das sentenças. Entre as linhas de estudo que exploram essa temática, está aquela que pretende implementar a análise automática da língua de sinais. Para aplicações com objetivo de interpretar línguas de sinais de forma automatizada, é preciso que tais expressões sejam identificadas no curso de uma sinalização, e essa tarefa dá-se é definida como segmentação de expressões faciais gramaticais. Para essa área, faz-se útil o desenvolvimento de uma arquitetura capaz de realizar a identificação de tais expressões em uma sentença, segmentando-a de acordo com cada tipo diferente de expressão usada em sua construção. Dada a necessidade do desenvolvimento dessa arquitetura, esta pesquisa apresenta: uma análise dos estudos na área para levantar o estado da arte; a implementação de algoritmos de reconhecimento de padrões usando Multilayer Perceptron e misturas de especialistas para a resolução do problema de reconhecimento da expressão facial; a comparação desses algoritmos reconhecedores das expressões faciais gramaticais usadas na concepção de sentenças na Língua Brasileira de Sinais (Libras). A implementação e teste dos algoritmos mostraram que a segmentação automática de expressões faciais gramaticais é viável em contextos dependentes do usuários. Para contextos independentes de usuários, o problema de segmentação de expressões faciais representa um desafio que requer, principalmente, a organização de um ambiente de aprendizado estruturado sobre um conjunto de dados com volume e diversidade maior do que os atualmente disponíveis / The recognition of facial expressions is an area of interest in computer science and has been an attraction for researchers in different fields since it has potential for development of different types of applications. Automatically recognizing these expressions has become a goal primarily in the area of human behavior analysis. Especially for the study of sign languages, the analysis of facial expressions represents an important factor for the interpretation of discourse, since it is the element that allows expressing prosodic information, supports the development of the grammatical and semantic structure of the language, and eliminates ambiguities between similar signs. In this context, facial expressions are called grammatical facial expressions. These expressions collaborate in the semantic composition of the sentences. Among the lines of study that explore this theme is the one that intends to implement the automatic analysis of sign language. For applications aiming to interpret signal languages in an automated way, it is necessary that such expressions be identified in the course of a signaling, and that task is called \"segmentation of grammatical facial expressions\'\'. For this area, it is useful to develop an architecture capable of performing the identification of such expressions in a sentence, segmenting it according to each different type of expression used in its construction. Given the need to develop this architecture, this research presents: a review of studies already carried out in the area; the implementation of pattern recognition algorithms using Multilayer Perceptron and mixtures of experts to solve the facial expression recognition problem; the comparison of these algorithms as recognizers of grammatical facial expressions used in the conception of sentences in the Brazilian Language of Signs (Libras). The implementation and tests carried out with such algorithms showed that the automatic segmentation of grammatical facial expressions is practicable in user-dependent contexts. Regarding user-independent contexts, this is a challenge which demands the organization of a learning environment structured on datasets bigger and more diversified than those current available

Este trabalho é um estudo das dispersões metrológicas em aproximações de funções tidas como não conhecidas ou não totalmente conhecidas. A metodologia alternativa para esse fim são as redes neurais artificiais do tipo Multilayer Perceptrons (MLP), aqui utilizadas como aproximadoras de funções. As funções aproximadas são curvas de calibração decorrentes de indicações de instrumentos ou sistemas de medição numa calibração. Essas curvas levam consigo propriedades metrológicas e possuem, neste trabalho, papel de ponte entre os elementos considerados da teoria metrológica e os elementos considerados da teoria da Inteligência Computacional: as Multilayer Perceptrons (MLPs). Uma balança externa de medição de esforços aerodinâmicos e uma Língua Eletrônica (LE), aplicada na medição da concentração de cátions, foram os meios de aplicação dos conceitos dessa metodologia alternativa. As proposições desta tese visam implementar melhorias na exatidão do ajuste das curvas de calibração por meio da consideração dos seguintes fatores: grandezas de influências, incertezas nos Valores Objetivos (VOs), tendência de medição de erros sistemáticos ocultos ou não solvidos e indicadores de desempenho metrológicos. A indicação da qualidade na medição ou a indicação da competência metrológica de um laboratório de calibração é estabelecida pelos valores das incertezas, e a curva de calibração é o ponto de partida para os cálculos desses valores. Visto que o estabelecimento dessa curva é uma das dificuldades para o cálculo das incertezas e a própria curva é uma fonte de incerteza, sua aproximação requer uma a cuidadosa e meticulosa metodologia, daí a importância estratégica deste trabalho. As dispersões metrológicas possuem conotação de incertezas nas medições e elas são a base para a determinação de seu valor numérico; assim, os indicadores de desempenho podem representar essas dispersões e a recíproca também é verdadeira: a incerteza padrão pode ser um dos indicadores de desempenho. Sintetizando, nesta tese é mostrado de que forma a teoria da inteligência computacional adentra na teoria da metrologia e vice versa, nas esferas dos elementos aqui considerados. / The present study investigates metrological dispersions in fitting partially or totally unknown functions. An alternative method is the application of a multilayer perceptron neural network used here to fit functions. The fitting functions are calibration curves from calibration indications of measurement systems or instruments. These curves hold metrological properties and establish a link between elements of Metrological theory and elements of Computing Intelligence theory: the Multilayer Perceptrons. An external balance of aerodynamic forces and moments and an electronic tongue applied in the measurement of cation concentrations were the measurement systems used to apply the concepts of this alternative methodology. This thesis proposes improvements in the accuracy of fitting calibration curves considering the following factors: influence quantities, uncertainties about target values, tendency of hidden or not solved systematic errors and metrological performance functions. The measurement quality indicator or the laboratory metrological competence indicator is established by uncertainty values and the calibration curve is the starting point for the calculation of these values. The establishment of this curve is one of the difficulties in assessing uncertainties and the curve itself is an uncertainty source. Therefore, a careful and meticulous methodology is necessary in curve approximation, which explains the strategic importance of this work. Metrological dispersions have connotation of uncertainty in measurements and are the basis for calculating their numerical values, the performance functions can represent metrological dispersions and the opposite is also true: the standard uncertainty can be a performance function. Making a synthesis, this thesis demonstrates how computing intelligence theory takes into account the metrological theory and vice versa, in the elements of these theories that were discussed in the present study.

Die Beeinflussung optischer Eigenschaften durch Bestrahlung stellt eine Grundlage für die Herstellung anisotroper optischer Komponenten dar. In dünnen Schichten von Azobenzen-Polymeren kann optische Anisotropie durch linear polarisierte Bestrahlung induziert oder modifiziert werden. Ziel der Arbeit war es, wesentliche Struktur-Eigenschafts-Beziehungen zum Prozess der Photoorientierung zu erarbeiten, um so eine Optimierung der Materialien für verschiedene Anwendungen ermöglichen. <br><br> In isotropen Schichten flüssigkristalliner und amorpher Azobenzen-Polymeren wird das Ausmaß der induzierten optischen Anisotropie günstig durch eine Donor/Akzeptor-Substitution in 4,4'-Position beeinflusst. Die Induktionsgeschwindigkeit ist in Schichten flüssigkristalliner Polymeren deutlich geringer, jedoch lassen sich höhere Werte der Doppelbrechung und des Dichroismus erreichen. In Copolymeren bewirkt die Photoorientierung der Azobenzen-Seitengruppen eine kooperative Orientierung von formanisotropen Seitengruppen. Die Mesogenität der nicht-photochromen Seitengruppen erhöht das Ausmaß der induzierten optischen Anisotropie. Die Stabilität der induzierten Doppelbrechung und des Dichroismus wird durch diese Gruppen gesteigert. <br><br> In Schichten flüssigkristalliner Polymeren wird die induzierte optische Anisotropie beim Tempern im Bereich der Mesophasen erheblich verstärkt. Dabei reicht ein geringes Maß an induzierter Anisotropie aus, um Doppelbrechungs- und Dichroismuswerte zu erzielen, wie sie für LC-Domänen typisch sind. <br><br> In orientierten Schichten von Azobenzen-Polymeren wird das Resultat der linear polarisierten Bestrahlung durch die Stärke der anisotropen Wechselwirkungen in den flüssigkristallinen Domänen oder den LB-Multilayern bestimmt. Eine lichtinduzierte Reorientierung kann nur erreicht werden, wenn diese Wechselwirkungen überwunden werden können. Erfolgt eine Photoreorientierung in den orientierten Polymerschichten, werden in Copolymeren formanisotrope Seitengruppen ebenfalls kooperativ reorientiert. Eine vorgelagerte UV-Bestrahlung kann durch Erzeugung eines hohen Anteils an nicht-mesogenen Z-Isomeren die anisotropen Wechselwirkungen stark schwächen und so die Seitengruppen entkoppeln. Aus diesem Zustand erfolgt die Photoreorientierung mit einer der Photoorientierung in isotropen Schichten vergleichbaren Effizienz. <br><br> Die erarbeiteten Struktur-Eigenschafts-Beziehungen liefern einen Beitrag zur Optimierung derartiger Materialien für Anwendungen in den Bereichen optischer Funktionsschichten, holographischer Datenspeicherung oder der Generierung von Oberflächenreliefgittern. / The modification of optical characteristics by irradiation represents a basis for the creation of anisotropic optical components. In thin films of azobenzene polymers optical anisotropy can be induced or modified by linearly polarized irradiation. The goal of the work was it to compile substantial structure property relations of the photoorientation process in order to support an optimization of the materials for different applications. <br><br> In isotropic films of liquid crystalline and amorphous azobenzene polymers the extent of the induced optical anisotropy is increased by a donor/acceptor substitution in 4,4'-position. The induction speed is clearly smaller in films of liquid crystalline polymers, however higher values of birefringence and dichroism can be reached. In copolymers the photoorientation of the azobenzene side groups causes a cooperative orientation of form-anisotropic side groups. The mesogenity of the non-photochromic side groups increases the extent of the induced optical anisotropy. <br><br> The stability of the induced birefringence and dichroism is increased by these groups considerably. In films of liquid crystalline polymers the induced optical anisotropy is substantially amplified on annealing within the range of the mesophases. In this way, a small ratio of induced anisotropy is sufficient, in order to obtain birefringence and dichroism values as typical for LC domains. <br><br> In oriented films of azobenzene polymers the result of the linear polarized irradiation is determined by the strength of the anisotropic interactions in the liquid crystalline domains or the LB multilayers. A light-induced reorientation can be only achieved, if these interactions can be overcome. If a photoreorientation takes place in the oriented layers of copolymers, form-anisotropic side groups are cooperatively reoriented. An initial UV irradiation can strongly weaken the anisotropic interactions by generating of a high fraction of non-mesogenic z-isomers and decouples in this way the side groups. From this state the photoreorientation proceeds with an efficiency one comparable to the photoorientation in isotropic films. <br><br> The compiled structure property relations supplies a contribution for the optimization of such materials for applications in the fields of optical function films, holographic data storage or the generation of surface relief gratings.

Layer-by-layer assembly of polyelectrolytes is a simple technique based on the self-assembly of polycations and polyanions mainly by electrostatic interactions, which has gained considerable scientific interest for its versatility of applications. Ease of fabrication process, inexpensive approach and use to coat surfaces with various geometries prompts the researchers to select this technique not only for the surface modification applications but also to study the processes which exploit the 3D matrix properties of polyelectrolyte multilayer films (PEMs). Recent advances have been made where PEMs coatings have been utilized for their bio-applications like drug delivery and in tissue engineering for modifying the biomaterial's surfaces. In the field of drug delivery and tissue engineering the location and availability of the constituent molecules is very important, which is defined by their ability to diffuse through the encapsulating material or reservoir. So the main objective of this thesis is to understand the transport of molecules in ultrathin Polyelectrolyte Multilayer Films in lateral as well as transverse direction to the substrate. To study this transport behaviour in PEMs, we have employed various strategies which can enhance or suppress the diffusivity across PEMs. Thus, understanding the diffusion at nanoscale resolution will lead us to design better host materials for loading of drugs and growth factors for various biomedical applications.

Crowdfunding är i den moderna digitala världen ett populärt sätt att samla in pengar till sitt projekt. Kickstarter är en av de ledande sidorna för crowdfunding. Predicering av ett Kickstarter-projekts framgång eller misslyckande kan därav vara av stort intresse för entreprenörer.Studiens syfte är att jämföra fyra olika algoritmers prediceringsförmåga på två olika Kickstarter-dataset. Det ena datasetet sträcker sig mellan åren 2020-2021, och det andra mellan åren 2016-2021. Algoritmerna som jämförs är KNN, Naive Bayes, MLP, och Random Forest.Av dessa fyra modeller så skapades i denna studie de bästa produktionsmodellerna av KNN och Random Forest. KNN var bäst för 2020-2021-datasetet, med 77,0% träffsäkerhet. Random Forest var bäst för 2016-2021-datasetet, med 76,8% träffsäkerhet. / Crowdfunding has in the modern, digitalized world become a popular method for gathering money for a project. Kickstarter is one of the most popular websites for crowdfunding. This means that predicting the success or failure of a Kickstarter-project by way of machine learning could be of great interest to entrepreneurs.The purpose of this study is to compare the predictive abilities of four different algorithms on two different Kickstarter-datasets. One dataset contains data in the span of the years 2020-2021, and the other contains data from 2016-2021. The algorithms used in this study are KNN, Naive Bayes, MLP and Random Forest.Out of these four algorithms, the top-performing prediction abilities for the two datasets were found in KNN and Random Forest. KNN was the best-performing algorithm for 2020-2021, with 77,0% accuracy. Random Forest had the top score for 2016-2021, with 76,8% accuracy. The language used in this study is Swedish.

This research addresses the novel application of design of experiment, artificial neural net-works and logistic regression to study the effect of demographic characteristics on the risk of acquiring HIV infection among the antenatal clinic attendees in South Africa. The annual antenatal HIV survey is the only major national indicator for HIV prevalence in South Africa. This is a vital technique to understand the changes in the HIV epidemic over time. The annual antenatal clinic data contains the following demographic characteristics for each pregnant woman; age (herein called mother's age), partner's age (herein father's age), population group (race), level of education, gravidity (number of pregnancies), parity (number of children born), HIV and syphilis status. This project applied a screening design of experiment technique to rank the effects of individual demographic characteristics on the risk of acquiring an HIV infection. There are a various screening design techniques such as fractional or full factorial and Plackett-Burman designs. In this work, a two-level fractional factorial design was selected for the purposes of screening. In addition to screening designs, this project employed response surface methodologies (RSM) to estimate interaction and quadratic effects of demographic characteristics using a central composite face-centered and a Box-Behnken design. Furthermore, this research presents the novel application of multi-layer perceptron’s (MLP) neural networks to model the demographic characteristics of antenatal clinic attendees. A review report was produced to study the application of neural networks to modelling HIV/AIDS around the world. The latter report is important to enhance our understanding of the extent to which neural networks have been applied to study the HIV/AIDS pandemic. Finally, a binary logistic regression technique was employed to benchmark the results obtained by the design of experiments and neural networks methodologies. The two-level fractional factorial design demonstrated that HIV prevalence was highly sensitive to changes in the mother's age (15-55 years) and level of her education (Grades 0-13). The central composite face centered and Box-Behnken designs employed to study the individual and interaction effects of demographic characteristics on the spread of HIV in South Africa, demonstrated that HIV status of an antenatal clinic attendee was highly sensitive to changes in pregnant mother's age and her educational level. In addition, the interaction of the mother's age with other demographic characteristics was also found to be an important determinant of the risk of acquiring an HIV infection. Furthermore, the central composite face centered and Box-Behnken designs illustrated that, individual-ally the pregnant mother's parity and her partner's age had no marked effect on her HIV status. However, the pregnant woman’s parity and her male partner’s age did show marked effects on her HIV status in “two way interactions with other demographic characteristics”. The multilayer perceptron (MLP) sensitivity test also showed that the age of the pregnant woman had the greatest effect on the risk of acquiring an HIV infection, while her gravidity and syphilis status had the lowest effects. The outcome of the MLP modelling produced the same results obtained by the screening and response surface methodologies. The binary logistic regression technique was compared with a Box-Behnken design to further elucidate the differential effects of demographic characteristics on the risk of acquiring HIV amongst pregnant women. The two methodologies indicated that the age of the pregnant woman and her level of education had the most profound effects on her risk of acquiring an HIV infection. To facilitate the comparison of the performance of the classifiers used in this study, a receiver operating characteristics (ROC) curve was applied. Theoretically, an ROC analysis provides tools to select optimal models and to discard suboptimal ones independent from the cost context or the classification distribution. SAS Enterprise MinerTM was employed to develop the required receiver-of-characteristics (ROC) curves. To validate the results obtained by the above classification methodologies, a credit scoring add-on in SAS Enterprise MinerTM was used to build binary target scorecards comprised of HIV positive and negative datasets for probability determination. The process involved grouping variables using weights-of-evidence (WOE), prior to performing a logistic regression to produce predicted probabilities. The process of creating bins for the scorecard enables the study of the inherent relationship between demographic characteristics and an in-dividual’s HIV status. This technique increases the understanding of the risk ranking ability of the scorecard method, while offering an added advantage of being predictive.

This research addresses the novel application of design of experiment, artificial neural net-works and logistic regression to study the effect of demographic characteristics on the risk of acquiring HIV infection among the antenatal clinic attendees in South Africa. The annual antenatal HIV survey is the only major national indicator for HIV prevalence in South Africa. This is a vital technique to understand the changes in the HIV epidemic over time. The annual antenatal clinic data contains the following demographic characteristics for each pregnant woman; age (herein called mother's age), partner's age (herein father's age), population group (race), level of education, gravidity (number of pregnancies), parity (number of children born), HIV and syphilis status. This project applied a screening design of experiment technique to rank the effects of individual demographic characteristics on the risk of acquiring an HIV infection. There are a various screening design techniques such as fractional or full factorial and Plackett-Burman designs. In this work, a two-level fractional factorial design was selected for the purposes of screening. In addition to screening designs, this project employed response surface methodologies (RSM) to estimate interaction and quadratic effects of demographic characteristics using a central composite face-centered and a Box-Behnken design. Furthermore, this research presents the novel application of multi-layer perceptron’s (MLP) neural networks to model the demographic characteristics of antenatal clinic attendees. A review report was produced to study the application of neural networks to modelling HIV/AIDS around the world. The latter report is important to enhance our understanding of the extent to which neural networks have been applied to study the HIV/AIDS pandemic. Finally, a binary logistic regression technique was employed to benchmark the results obtained by the design of experiments and neural networks methodologies. The two-level fractional factorial design demonstrated that HIV prevalence was highly sensitive to changes in the mother's age (15-55 years) and level of her education (Grades 0-13). The central composite face centered and Box-Behnken designs employed to study the individual and interaction effects of demographic characteristics on the spread of HIV in South Africa, demonstrated that HIV status of an antenatal clinic attendee was highly sensitive to changes in pregnant mother's age and her educational level. In addition, the interaction of the mother's age with other demographic characteristics was also found to be an important determinant of the risk of acquiring an HIV infection. Furthermore, the central composite face centered and Box-Behnken designs illustrated that, individual-ally the pregnant mother's parity and her partner's age had no marked effect on her HIV status. However, the pregnant woman’s parity and her male partner’s age did show marked effects on her HIV status in “two way interactions with other demographic characteristics”. The multilayer perceptron (MLP) sensitivity test also showed that the age of the pregnant woman had the greatest effect on the risk of acquiring an HIV infection, while her gravidity and syphilis status had the lowest effects. The outcome of the MLP modelling produced the same results obtained by the screening and response surface methodologies. The binary logistic regression technique was compared with a Box-Behnken design to further elucidate the differential effects of demographic characteristics on the risk of acquiring HIV amongst pregnant women. The two methodologies indicated that the age of the pregnant woman and her level of education had the most profound effects on her risk of acquiring an HIV infection. To facilitate the comparison of the performance of the classifiers used in this study, a receiver operating characteristics (ROC) curve was applied. Theoretically, an ROC analysis provides tools to select optimal models and to discard suboptimal ones independent from the cost context or the classification distribution. SAS Enterprise MinerTM was employed to develop the required receiver-of-characteristics (ROC) curves. To validate the results obtained by the above classification methodologies, a credit scoring add-on in SAS Enterprise MinerTM was used to build binary target scorecards comprised of HIV positive and negative datasets for probability determination. The process involved grouping variables using weights-of-evidence (WOE), prior to performing a logistic regression to produce predicted probabilities. The process of creating bins for the scorecard enables the study of the inherent relationship between demographic characteristics and an in-dividual’s HIV status. This technique increases the understanding of the risk ranking ability of the scorecard method, while offering an added advantage of being predictive.