This thesis presents the work conducted during a three year research project in the field of Control Systems and Biomaterials Engineering. The findings are presented over seven chapters, starting with a thorough literature review of the existing methods and key technologies, and following through by highlighting the existing problems with the current methods and how they have been overcome. The data is presented in tables, figures and photographs to enhance understanding and clarification. The research focuses on two relatively new manufacturing methods in the field of Tissue Engineering. Both of the methods are used for creating materials for regeneration of human and animal tissue, with the aim of replacing the current surgical methods. The methods are viewed from a control systems perspective and improvements have been made with the implementation of new technologies and methods. Additionally, further advancements are presented on the theoretical modelling field of control systems, where the shortfalls of existent modelling methods are highlighted and solutions proposed.

Fermentation processes play an integral role in the manufacture of pharmaceutical products. The Quality by Design initiative, combined with Process Analytical Technologies, aims to facilitate the consistent production of high quality products in the most efficient and economical way. The ability to estimate and control product quality from these processes is essential in achieving this aim. Large historical datasets are commonplace in the pharmaceutical industry and multivariate methods based on PCA and PLS have been successfully used in a wide range of applications to extract useful information from such datasets. This thesis has focused on the development and application of novel multivariate methods to the estimation and control of product quality from a number of processes. The document is divided into four main categories. Firstly, the related literature and inherent mathematical techniques are summarised. Following this, the three main technical areas of work are presented. The first of these relates to the development of a novel method for estimating the quality of products from a proprietary process using PCA. The ability to estimate product quality is useful for identifying production steps that are potentially problematic and also increases process efficiency by ensuring that any defective products are detected before they undergo any further processing. The proposed method is simple and robust and has been applied to two separate case studies, the results of which demonstrate the efficacy of the technique. The second area of work concentrates on the development of a novel method of identifying the operational phases of batch fermentation processes and is based on PCA and associated statistics. Knowledge of the operational phases of a process can be beneficial from a monitoring and control perspective and allows a process to be divided into phases that can be approximated by a linear model. The devised methodology is applied to two separate fermentation processes and results show the capability of the proposed method. The third area of work focuses on undertaking a performance evaluation of two multivariate algorithms, PLS and EPLS, in controlling the end-point product yield of fermentation processes. Control of end-point product quality is of crucial importance in many manufacturing industries, such as the pharmaceutical industry. Developing a controller based on historical and identification process data is attractive due to the simplicity of modelling and the increasing availability of process data. The methodology is applied to two case studies and performance evaluated. From both a prediction and control perspective, it is seen that EPLS outperforms PLS, which is important if modelling data is limited.

abstract: Spotlight mode synthetic aperture radar (SAR) imaging involves a tomo- graphic reconstruction from projections, necessitating acquisition of large amounts of data in order to form a moderately sized image. Since typical SAR sensors are hosted on mobile platforms, it is common to have limitations on SAR data acquisi- tion, storage and communication that can lead to data corruption and a resulting degradation of image quality. It is convenient to consider corrupted samples as missing, creating a sparsely sampled aperture. A sparse aperture would also result from compressive sensing, which is a very attractive concept for data intensive sen- sors such as SAR. Recent developments in sparse decomposition algorithms can be applied to the problem of SAR image formation from a sparsely sampled aperture. Two modified sparse decomposition algorithms are developed, based on well known existing algorithms, modified to be practical in application on modest computa- tional resources. The two algorithms are demonstrated on real-world SAR images. Algorithm performance with respect to super-resolution, noise, coherent speckle and target/clutter decomposition is explored. These algorithms yield more accu- rate image reconstruction from sparsely sampled apertures than classical spectral estimators. At the current state of development, sparse image reconstruction using these two algorithms require about two orders of magnitude greater processing time than classical SAR image formation. / Dissertation/Thesis / M.S. Electrical Engineering 2011

abstract: Multi-label learning, which deals with data associated with multiple labels simultaneously, is ubiquitous in real-world applications. To overcome the curse of dimensionality in multi-label learning, in this thesis I study multi-label dimensionality reduction, which extracts a small number of features by removing the irrelevant, redundant, and noisy information while considering the correlation among different labels in multi-label learning. Specifically, I propose Hypergraph Spectral Learning (HSL) to perform dimensionality reduction for multi-label data by exploiting correlations among different labels using a hypergraph. The regularization effect on the classical dimensionality reduction algorithm known as Canonical Correlation Analysis (CCA) is elucidated in this thesis. The relationship between CCA and Orthonormalized Partial Least Squares (OPLS) is also investigated. To perform dimensionality reduction efficiently for large-scale problems, two efficient implementations are proposed for a class of dimensionality reduction algorithms, including canonical correlation analysis, orthonormalized partial least squares, linear discriminant analysis, and hypergraph spectral learning. The first approach is a direct least squares approach which allows the use of different regularization penalties, but is applicable under a certain assumption; the second one is a two-stage approach which can be applied in the regularization setting without any assumption. Furthermore, an online implementation for the same class of dimensionality reduction algorithms is proposed when the data comes sequentially. A Matlab toolbox for multi-label dimensionality reduction has been developed and released. The proposed algorithms have been applied successfully in the Drosophila gene expression pattern image annotation. The experimental results on some benchmark data sets in multi-label learning also demonstrate the effectiveness and efficiency of the proposed algorithms. / Dissertation/Thesis / Ph.D. Computer Science 2011

Este trabalho avaliou o potencial da aplicação da técnica recursiva dos mínimos quadrados (MQR) para o ajuste em tempo atual dos parâmetros de modelos autorregressivos com variáveis exógenas (ARX), as quais são constituídas pelos níveis de montante para melhorar o desempenho das previsões de níveis fluviais em tempo atual. Três aspectos foram estudados em conjunto: variação do alcance escolhido para a previsão, variação da proporção da área controlada em bacias a montante e variação da área da bacia da seção de previsão. A pesquisa foi realizada em três dimensões principais: a) metodológica (sem recursividade; com recursividade; com recursividade e fator de esquecimento); b) temporal (6 alcances diferentes: 10, 24, 34, 48, 58 e 72 horas); e c) espacial (variação da área controlada da bacia e da área da bacia definida pela seção de previsão). A área de estudo escolhida para essa pesquisa foi a bacia do rio Uruguai com exutório no posto fluviométrico de Uruguaiana (190.000 km²) e as suas sub-bacias embutidas de Itaqui (131.000 km²), Passo São Borja (125.000km²), Garruchos (116.000 km²), Porto Lucena (95.200 km²), Alto Uruguai (82.300 km²) e Iraí (61.900 km²). Os dados de níveis fluviométricos, com leituras diárias às 07:00 e às 17:00 horas, foram fornecidos pela Companhia de Pesquisa de Recursos Minerais (CPRM), sendo utilizados os dados de 1/1/1991 a 30/6/2015. Para a análise de desempenho dos modelos, foi aplicado como estatística de qualidade o coeficiente de Nash-Sutcliffe (NS) e o quantil 0,95 dos erros absolutos (EA(0,95): erro que não foi ultrapassado com a frequência de 0,95). Observou-se que os erros EA(0,95) dos melhores modelos obtidos para cada bacia sempre aumentam com a redução da área controlada, ou seja, a qualidade das previsões diminui com o deslocamento da seção de controle de jusante para montante. O ganho na qualidade das previsões com a utilização dos recursos adaptativos torna-se mais evidente, especialmente quando observam-se os valores de EA(0,95), pois esta estatística é mais sensível, com diferenças maiores em relação ao coeficiente NS. Além disso, este é mais representativo para os erros maiores, que ocorrem justamente durante os eventos de inundações. De modo geral, foi observado que, à medida que diminui a área da bacia, é possível obter previsões com alcances cada vez menores. Porém a influência do tamanho da área controlada de bacias a montante melhora o desempenho de bacias menores quando se observam principalmente os erros EA(0,95). Por outro lado, se a proporção da bacia controlada de montante já é bastante grande, como é o caso das alternativas 1 e 2 utilizadas para previsão em Itaqui (entre 88,5% e 95,4 %, respectivamente), os recursos adaptativos não fazem muita diferença na obtenção de melhores resultados. Todavia, quando se observam bacias com menores áreas de montante controladas, como é o caso de Porto Lucena para a alternativa 2 (65% de área controlada), o ganho no desempenho dos modelos com a utilização dos recursos adaptativos completos (MQR+f.e: mínimos quadrados recursivos com fator de esquecimento) torna-se relevante. / This study evaluated the potential of the application of the recursive least squares technique (RLS) to adjust in real time the model parameters of the autoregressive models with exogenous variables (ARX), which consists of the upstream levels, to improve the performance of the forecasts of river levels in real time. Three aspects were studied jointly: the variation of the lead time chosen for the forecast, the variation in the proportion of controlled area in upstream basins and variation in the area of forecasting section of the basin. The research was conducted in three main dimensions: a) methodological (without recursion; with recursion; with recursion and forgetting factor); b) temporal (6 different lead times: 10, 24, 34, 48, 58 and 72 hours); and c) spatial (variation in the controlled area of the basin and the area of the basin defined by the forecast section). The study area chosen for this research was the Uruguay River basin with its outflow at the river gage station of Uruguaiana (190,000 km²) and its entrenched sub-basins in Itaqui (131,000 km²), Passo São Borja (125,000 km²), Garruchos (116,000 km²), Porto Lucena (95,200 km²), Alto Uruguai (82,300 km²), and Iraí (61,900 km²). The river levels data, with daily readings at 7am and 5pm, were provided by the Company of Mineral Resources Research (CPRM), with the data used from January 1, 1991 to June 30, 2015. We applied the Nash-Sutcliffe coefficient (NS) and the quantile 0.95 of absolute errors (EA(0,95): error has not been exceeded at the rate of 0.95) for the analysis of models performances. We observed that the errors EA(0.95) of the best models obtained for each basin always increase with the reduction of the controlled area then the quality of the forecasts decreases with displacement of the downstream control section upstream. The gain in quality of the forecasts with the use of adaptive resources becomes more evident especially when the observed values of EA(0.95) as this statistic is more sensitive with greater differences in relation to the Nash-Sutcliffe Coefficient (NS). Moreover, this is most representative for larger errors which occur precisely during flooding events. In general, we observed that, as much as the area of the basin decreases, it is possible to obtain forecasts with smaller lead times, but the influence of the size of the area controlled upstream basins improves the performance of smaller basins when observing, especially the errors EA (0.95). However, if the proportion of the upstream of controlled basin is already quite large - as in the case of the alternatives 1 and 2 used for forecast in Itaqui (between 88.5% and 95.4%, respectively) - the adaptive resources do not differ too much in getting better results. However, when observing basins with smaller areas controlled upstream - as is the case of Porto Lucena to alternative 2 (65% controlled area) - the performance gain of the models with the use of the complete adaptive resources (MQR+f.e.) becomes relevant.

Neste trabalho são propostos métodos para a estimação de parâmetros de motores de indução através do método dos Mínimos Quadrados com medição apenas de tensões, correntes e resistência do estator em um ensaio de partida em vazio. São detalhados os procedimentos para o tratamento dos sinais medidos, além das estimações do fluxo magnético e da velocidade mecânica do motor. Para a estimação dos parâmetros elétricos, são propostos métodos que diferem nos requisitos e no tratamento dos parâmetros como invariantes ou variantes no tempo. Em relação a esse último caso, é empregado um método de estimação de parâmetros por janelas de dados, aplicando um modelo com parâmetros invariantes no tempo localmente em diversas partes do ensaio. São feitas simulações para validar os métodos propostos, e dados de ensaio de três motores de diferentes potências são utilizados para analisar a escala de variação paramétrica durante a partida. É feita uma comparação entre os resultados obtidos com e sem consideração de variação nos parâmetros. / In this work, methods are proposed to estimate the parameters of induction motors through the Least Squares method with the measurement of only voltages, currents and resistance of the stator in a no-load startup test. Procedures are detailed to process the measured signals, as well as to estimate magnetic flux and rotor mechanical speed. In order to estimate the electrical parameters, methods are proposed which differ in their requisites and in the treatment of parameters as time invariant or time-varying. For the latter, a methodology for parameter estimation through data windows is used, applying a model with time invariant parameters locally to different parts of the test. Simulations are made to validate the proposed methodology, and data from tests of three motors with different powers are used to analyze the scale of parameter variation during startup. A comparison is made between the results obtained with and without the consideration of variation in the parameters.

Kernel-based meshless methods for approximating functions and solutions of partial differential equations have many applications in engineering fields. As only scattered data are used, meshless methods using radial basis functions can be extended to complicated geometry and high-dimensional problems. In this thesis, kernel-based least-squares methods will be used to solve several direct and inverse problems. In chapter 2, we consider discrete least-squares methods using radial basis functions. A general l^2-Tikhonov regularization with W_2^m-penalty is considered. We provide error estimates that are comparable to kernel-based interpolation in cases in which the function being approximated is within and is outside of the native space of the kernel. These results are extended to the case of noisy data. Numerical demonstrations are provided to verify the theoretical results. In chapter 3, we apply kernel-based collocation methods to elliptic problems with mixed boundary conditions. We propose some weighted least-squares formulations with different weights for the Dirichlet and Neumann boundary collocation terms. Besides fill distance of discrete sets, our weights also depend on three other factors: proportion of the measures of the Dirichlet and Neumann boundaries, dimensionless volume ratios of the boundary and domain, and kernel smoothness. We determine the dependencies of these terms in weights by different numerical tests. Our least-squares formulations can be proved to be convergent at the H^2 (Ω) norm. Numerical experiments in two and three dimensions show that we can obtain desired convergent results under different boundary conditions and different domain shapes. In chapter 4, we use a kernel-based least-squares method to solve ill-posed Cauchy problems for elliptic partial differential equations. We construct stable methods for these inverse problems. Numerical approximations to solutions of elliptic Cauchy problems are formulated as solutions of nonlinear least-squares problems with quadratic inequality constraints. A convergence analysis with respect to noise levels and fill distances of data points is provided, from which a Tikhonov regularization strategy is obtained. A nonlinear algorithm is proposed to obtain stable solutions of the resulting nonlinear problems. Numerical experiments are provided to verify our convergence results. In the final chapter, we apply meshless methods to the Gierer-Meinhardt activator-inhibitor model. Pattern transitions in irregular domains of the Gierer-Meinhardt model are shown. We propose various parameter settings for different patterns appearing in nature and test these settings on some irregular domains. To further simulate patterns in reality, we construct different kinds of domains and apply proposed parameter settings on different patches of domains found in nature.

Peixoto, A. A. T. Detecção multiusuário baseada em tensores para sistemas de comunicação sem fio cooperativos. 2017. 115 f. Dissertação (Mestrado em Engenharia Elétrica e da Computação) - Campus de Sobral, Universidade Federal do Ceará, Sobral, 2017. / Submitted by Programa de Pós-Graduação Engenharia Elétrica e de Computação (secretaria_ppgeec@sobral.ufc.br) on 2017-08-14T13:53:24Z No. of bitstreams: 1 2017_dis_aatpeixoto.pdf: 1646922 bytes, checksum: a562da60d08daac64247b2013ca22436 (MD5) / Approved for entry into archive by Djeanne Costa (djeannecosta@gmail.com) on 2017-08-17T11:50:56Z (GMT) No. of bitstreams: 1 2017_dis_aatpeixoto.pdf: 1646922 bytes, checksum: a562da60d08daac64247b2013ca22436 (MD5) / Made available in DSpace on 2017-08-17T11:50:56Z (GMT). No. of bitstreams: 1 2017_dis_aatpeixoto.pdf: 1646922 bytes, checksum: a562da60d08daac64247b2013ca22436 (MD5) Previous issue date: 2017-07 / Signal processing applications in wireless communications may sometimes take advantage of multilinear algebra concepts. This can be done by modeling the signals as high order tensors. From this context, tensor decompositions such as the Parallel Factor analysis (PARAFAC), may be found useful. On the other hand, cooperative communications and Multiple-Input Multiple-Output (MIMO) systems are ways for granting better data rates, capacity, fading mitigation and coverage. Joining the signal processing capabilities of tensor algebra, MIMO and cooperative communications can bring great benefits in wireless communications systems. In this dissertation, two receivers are proposed for two system models that are a multiuser DS-CDMA (Direct-Sequence Code-Division Multiple-Access) uplink based on multirelay cooperative communications. The two system models are almost the same, except that in one of them, multiuser interference is considered at the relays. The Amplify-and-Forward (AF) protocol is used on all the relays, thus exploiting cooperative diversity. For the received signal of the first system model, a quadrilinear PARAFAC decomposition will be adopted and by doing so, the proposed tensor-based semi-blind receiver can jointly estimate the transmitted symbols, channel gains and spatial signatures of all users by assuming previous knowledge of the users spreading codes and a few transmitted symbols. For the second system model, multiuser interference is considered at the relays, then, a receiver based on a trilinear PARAFAC decomposition is proposed. The estimation of the second receiver is done in two phases with the first phase being a supervised stage where non-orthogonal training sequences are sent by all users. During the second phase, the users' data symbols are then estimated. Both receivers use the Alternating Least Squares (ALS) algorithm to fit the tensor models, assuming no channel state information (CSI) at the base station neither at the relays. With computational simulations, we will also provide performance evaluation of the proposed receivers for various cases and system variations. / As aplicações de processamento de sinal em sistemas de comunicações sem fio às vezes podem tirar proveito de conceitos de álgebra multilinear. Isso pode ser feito modelando os sinais como tensores de ordem elevada. Neste contexto, as decomposições tensoriais, tais como a análise de fatores paralelos (Parallel Facor - PARAFAC), podem ser úteis. Por outro lado, as comunicações cooperativas e a área de sistemas de múltiplas-entradas e múltiplas-saídas (Multiple-Input Multiple-Ouput - MIMO) são uma maneira de se alcançar melhores taxas de dados, capacidade, qualidade de transmissão e cobertura. Juntando-se as capacidades de processamento de sinal da álgebra tensorial, dos sistemas MIMO e das comunicações cooperativas, podemos obter grandes benefícios nos sistemas de comunicações sem fio. Nesta dissertação, dois receptores são propostos para dois modelos de sistema, que são o enlace reverso de um sistema DS-CDMA multiusuário baseado em comunicações cooperativas auxiliadas por múltiplos retransmissores. Os dois modelos de sistema são quase iguais, exceto que em um deles, a interferência de múltiplos usuários é considerada nos retransmissores. O protocolo Amplify-and-Forward (AF) é aplicado em cada retransmissor, explorando a diversidade cooperativa. Para o sinal recebido no primeiro modelo de sistema, uma decomposição tensorial PARAFAC quadrilinear será adotada e, ao fazê-lo, o receptor semi-cego proposto pode estimar conjuntamente os símbolos transmitidos, ganhos de canais e assinaturas espaciais de todos os usuários, assumindo o conhecimento prévio dos códigos de espalhamento dos usuários e alguns símbolos transmitidos. Para o segundo modelo de sistema, interferência multiusuário é considerada nos retransmissores dos usuários, então, um receptor baseado em uma decomposição PARAFAC trilinear é proposto. O segundo receptor realiza as estimações em duas fases, sendo a primeira fase um estágio supervisionado em que todos os usuários enviam sequências de treinamento não ortogonais. Durante a segunda fase, os símbolos de dados dos usuários são então estimados. Ambos os receptores usam o algoritmo ALS (Alternating Least Squares) para ajustar os modelos tensoriais, assumindo nenhuma informação de estado do canal (CSI - Channel State Information) na estação base nem nos retransmissores. Com simulações computacionais, também forneceremos avaliação de desempenho dos receptores propostos para vários casos e variações do sistema.

O estudo do comportamento reológico de fluidos não Newtonianos tem grande importância em diversas áreas da engenharia. O aumento na demanda destes fluidos por exemplo, no uso doméstico, pessoal e em processos químicos acarreta em dificuldades que vão desde o processo de sua mistura ao seu manuseio. Dentre os fluidos não Newtonianos estão os viscoelásticos, os quais exibem deformação aparente quando os níveis de tensões são inferiores ao limite de escoamento do material e, dentro desta classe, alguns ainda podem apresentam comportamento elástico quando submetidos à baixa taxa de cisalhamento. Juntamente com os efeitos elasto-viscoplásticos, os materiais podem apresentar comportamento tixotrópico, onde devido as tensões sua reestruturação não é instantânea. Na presente Tese, fez-se um estudo numérico a fim de analisar o problema especifico de escoamentos de fluidos elasto-viscoplásticos com comportamento tixotrópico em uma expansão planar abrupta na razão de aspecto 4 : 1. O modelo mecânico aplicado consiste de uma equação viscoelástica para o campo de tensões, uma evolutiva para o parâmetro de estrutura do material, bem como as equações de conservação de massa e momento. O modelo mecânico aplicado mostrou-se capaz de prever o comportamento tixotrópico. A aproximação numérica do modelo aplicado foi feita através do método estabilizado de elementos finitos, especificamente o método Galerkin Mínimos-Quadrados (GLS), o qual foi implementado no código de elementos finitos para fluidos não Newtonianos em desenvolvimento no Laboratório de Mecânica dos Fluidos Aplicada e Computacional (LAMAC) da Universidade Federal do Rio Grande do Sul. Os fenômenos reológicos presentes no problema foram analisados a partir da influência da cinemática do escoamento, da elasticidade e da tixotropia, no nível de estruturação do material, na posição e tamanho das regiões não escoadas e na deformação elástica do material. Os resultados mostraram-se satisfatórios, pois condizem com os apresentados na literatura, apontando a boa predição do modelo mecânico aplicado bem como a robustez de sua implementação computacional. / The rheological behavior of non-Newtonian uids study is of great then importance in many areas of engineering. The increase in demand of these uids - for example, domestic use, personal and processes chemical - causes di culties ranging from the process of mixing it to handling. Among the non-Newtonian uids are viscoelastic, which exhibit apparent deformation when stress levels are lower than the yield limit of the material and, within this class, some still have elastic behavior when subjected to low shear rates. Together with the elastic-viscoplastic e ects, materials may exhibit thixotropic behavior, ie, due the restructuring strain is not instantaneous. In this thesis was made a numerical study to simulate the speci c problem of ow of elastic-viscoplastic uids with thixotropic behavior in abrupt planar expansion { common geometry in industrial systems associated with elastic-viscoplastic uids, whose ratio the aspect is 4:1. The mechanical behavior of most of these structured materials, are highly non-Newtonian, with this, there is need to make them more pseudoplastic, causing undesirable behaviors such as thixotropic which is a phenomenon somewhat characterized and modeled in the literature. The mechanical model applied is able to predict thixotropic behavior and is composed of a viscoelastic equation for the stress eld and an evolutionary to the material structure parameter in addition to the mass and momentum conservation equations. This mechanical model is approximated by a stabilized nite element model, called the Galerkin method of least squares (GLS). In order to study the rheological phenomena present in the problem is analyzed the in uence of the ow kinematics, elasticity and thixotropy in the level of structure of the material, in position and size of unyielded regions and the elastic deformation of the material. The results were satisfactory, since the the study of intensity the U the results agree with those reported in the literature pointing to good prediction of the mechanical model applied well as the hardiness of their computational implementation.The results of the elasticity showed quite spectacular behavior of unyielded regions of the material since for high values of relaxation time, the unyielded region of channel larger has the form of " ngers"because of the high exibility of the material along the line of symmetry of the channel. The results of the analysis of the elastic deformation show, that model correctly dosing the elasticity in the unyielded regions. The thixotropic e ects reported a slower structuring of the material with increasing characteristic time, in response to strain change caused by the expansion, results indicate that for high values of relaxation time, higher the distance between the unyielded regions of smaller channel and larger.

Food inflation in South Africa has been viewed as an important source of underlying inflationary pressures in the economy due to its persistence beyond that of other commodities. Although several studies found food to be one of the factors that influence purchase decisions, there still appears to be an absence of research that directly links food inflation to consumers’ decisions, especially when financing the purchase of new passenger vehicles in South Africa. In this regard, this study investigated whether the increase in the prices of food products has a significant effect on passenger vehicle purchases in South Africa. Leaning on the literature that argues that economic factors do not play much of a role in passenger vehicle purchase decisions in South Africa, it was hypothesised that there is no supported relationship between food inflation and passenger vehicle purchases in South Africa. Using secondary time series data, the Pearson correlation test revealed a negative but insignificant relationship between food inflation and vehicle purchases in South Africa. The ordinary least squares estimate of the purchase function, taking into account several economic factors that influence passenger vehicle purchase decisions in the literature, showed that disposable income of households along with vehicle purchases of the previous period are to be considered as main determinants of vehicle purchases in South Africa. In addition, it was also revealed that new vehicle prices are also a significant determinant of vehicle purchases. The Johansen cointegration test revealed that the variables in the vehicle purchase function were cointegrated in the long run. The vector error correction model showed a long-run relationship, albeit insignificant, between food inflation and vehicle purchases and no relationship between the two variables in the short run. The Granger causality test revealed that food inflation and vehicle purchases are independent from each other, meaning that no causal effect was found between the variables, regardless of the direction of the test. This study concluded that economic factors such as interest rate and fuel price have an insignificant influence on passenger vehicle purchases in South Africa. In the same line, the impact of food inflation on passenger vehicle purchases in South Africa was found to be insignificant, therefore, the conclusion was drawn that the increase in the prices of food products will not play a considerable role in consumers’ decisions regarding passenger vehicle purchase in South Africa. / Business Management / M. Com. (Business Management)