Inequalities in levels of health between regions within a country are frequently regarded as a problem. Zimbabwe is characterised by poor and unequal conditions of health (both the state of people‘s health and health services). The health system of the country shows severe spatial inequalities that are manifested at provincial, district and even local levels. The current research therefore examines and analyses the spatial inequalities and temporal variation of health conditions in Zimbabwe. Composite indices were used to determine the people‘s state of health in Zimbabwe. Administrative districts were ranked according to the level of people‘s state of health. Cluster analysis was also performed to demarcate administrative districts according the level of health service provision. Districts with minimum difference were demarcated in a single cluster. Clusters were delineated using data on patterns of diseases and health and such clusters were used to demarcate the country‘s spatial health system according to the Adapted Epidemiological Transition Model. This was meant to evaluate the applicability of the model to Zimbabwe. It emerged from the research that generally the country‘s health conditions are poor and the health system is characterised by severe spatial inequalities. Some districts are experiencing poor health service provision and serious health challenges and are still in the age of pestilence and famine but others have good health service provision as well as highly developed health conditions and are in the age of degenerative and man-made diseases of the epidemiological transition model. It further emerged that the country‘s health has been evolving with signs of improvement since the 1990s. Some proposals are made in research for spatial development of health in the country. Recommendations were made regarding possible adjustment to previous strategies and policies used in Zimbabwe, for the development of the health system of the country. New strategies were also recommended for the improvement of the health system of the country. / Geography / Ph.D. (Geography)

Developing and retaining competitive advantage was a major concern for all companies; it fundamentally relied on being aware of the external environment and customer satisfaction. Modifications of the environment conditions and unexpected economic events could cause of a loss of the level of organisational adjustment and subsequent loss in competitiveness, only those organisations able to rapidly adjust to these dynamics would be able to remain. In some instances, companies decided to geographically co-locate seeking economies of scale and benefiting from complementarities. Literature review revealed the strong support that clusters had from Government and Local Authorities, but it also highlighted the limited practical research in the field. The aim of this research was to measure the dynamism of the cluster formed by the geographical concentration of diverse manufacturers within the Mondragon Cooperativa Group in the Basque region of Spain, and compared it to the individual dynamism of these organisations in order to have a better understanding the actual complementarities and synergies of this industrial colocation. Literature review identified dynamic capabilities as the core enablers of organisation when competing in dynamic environments; based on these capabilities, a model was formulated. This model combined with the primary data collected via questionnaire and interviews helped measure the dynamism of the individual cluster members and the cluster as whole as well as provided an insight on the complementarities and synergies of this type of alliance. The findings of the research concluded that the cluster as a whole was more dynamic than the individual members; nevertheless, the model suggested that there were considerable differences in speed among the cluster members. These differences on speed were determined by the size of the company and their performance in dimensions such as marketing, culture and management. The research also suggested that despite of the clear differences in the level of dynamism among cluster members, all companies benefited in some way from being part of the cluster; these benefits were different in nature depending on each specific members.

published_or_final_version / Education / Master / Master of Education

This study aims to explore policy implications, production and consumption processes between the airline and tourism industries. In particular, policy initiatives, product developments, innovation and consumption patterns are taken into consideration in order to identify the relationship between the two industries within the context of Cyprus. The airline industry, after the implementation of liberalization, has changed considerably in terms of market size, type of airlines and operations. In the case of destination management, innovation and policy planning are key parameters of success. Additionally, new business production methods are imperative, given the emergence of a ‘new-tourist’ who is educated, seeking shorter breaks and more frequent and cheaper trips in unique and unexplored destinations. Both quantitative and qualitative methods of analysis are employed. In particular, 26 interviews of ‘power-elite’ policymakers and stakeholders in Cyprus are used to explore policy implications for the identification of implementation outcomes and their impact on product developments and innovation. Furthermore, 300 self-administered questionnaires were distributed to British travellers to Cyprus, so as to identify the role of the airlines and the extent of the importance attributed to destination. The results of the study suggest a gap in the relation of the tourism and airline industries’ interaction at policy level, outcome, and implementation. More specifically, the airline policy enables the industry to become more adaptive and creative, and innovation is depicted via low-cost carriers (LCCs). The tourism industry has developed a policy that reflects the post/neo-Fordism trends of consumption and production, which refers to niche products. However, there is a dearth of policy theory and implementation, with consistent failures and delays. Thus, tourism is at the stage of renovation without essential innovation in contrast to the airline industry, which is a leader, and a proponent of innovation. In terms of consumption, Factor Analysis suggests that British tourists tend to book their holiday trips based on three categories of airline attributes: ‘Customer service’, ‘Price-sensitive & Internet’ and ‘Selection in travel behaviour’. Cluster analysis suggests three main categories of tourists, namely, ‘Traditional’, ‘Demanding/Opportunists’ and ‘Ambivalent’. The results confirm that consumers have changed and tourism destinations must be able to adapt to their demands and to offer a variety of services and products in order to survive in a competitive global market. In the case of the airline industry and holiday trips, convenience and the airport that the airline is flying from is more important than the cost of the ticket.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

This dissertation focuses on methodology specific to microarray data analyses that organize the data in preliminary steps and proposes a cluster analysis method which improves the interpretability of the cluster results. Cluster analysis of microarray data allows samples with similar gene expression values to be discovered and may serve as a useful diagnostic tool. Since microarray data is inherently noisy, data preprocessing steps including smoothing and filtering are discussed. Comparing the results of different clustering methods is complicated by the arbitrariness of the cluster labels. Methods for re-labeling clusters to assess the agreement between the results of different clustering techniques are proposed. Microarray data involve large numbers of observations and generally present as arrays of light intensity values reflecting the degree of activity of the genes. These measurements are often two dimensional in nature since each is associated with an individual sample (cell line) and gene. The usual hierarchical clustering techniques do not easily adapt to this type of problem. These techniques allow only one dimension of the data to be clustered at a time and lose information due to the collapsing of the data in the opposite dimension. A novel clustering technique based on normal mixture distribution models is developed. This method clusters observations that arise from the same normal distribution and allows the data to be simultaneously clustered in two dimensions. The model is fitted using the Expectation/Maximization (EM) algorithm. For every cluster, the posterior probability that an observation belongs to that cluster is calculated. These probabilities allow the analyst to control the cluster assignments, including the use of overlapping clusters. A user friendly program, 2-DCluster, was written to support these methods. This program was written for Microsoft Windows 2000 and XP systems and supports one and two dimensional clustering. The program and sample applications are available at http://etd.vcu.edu. An electronic copy of this dissertation is available at the same address.

This thesis deals with the topic of value and value orientations in the society. The first part of the thesis is the introduction to the issue of values from sociological perspective, and to issue of empirical measurement of values as well. Subsequently the thesis core is own empirical analysis of the data from Aktér surveys, which were carried out in the Czech Republic in 2005, 2007 and 2012. The research intention was to create typology of respondents on the basis of their various value orientations. For this purpose, a battery of questions was used, which was repeatedly asked in the questionnaires in the Aktér surveys. This set of items measured values and life strategies of respondents on the five-point scales. Multidimensional statistical techniques, such as explorative factor analysis and cluster analysis, were employed to the typology-making process. The outcome of this thesis is the presentation of created respondent types (clusters), their identification on the basis of sociodemographic variables and the indication of the typology transformation in the process of time.

Notre recherche vise à établir un cadre pour améliorer la compréhension du marché de capital-risque européen et l’appariement entre entrepreneurs et fonds de capital risque qui a lieu dans ce marché. Nous présentons quatre essais qui permettent de connaître: la littérature théorique et empirique sur le domaine, les différents types des Fonds de Capital Risque qui participent au financement des entreprises en phase de démarrage et les dimensions qui comptent le plus dans les relations entre ces participants. / Our thesis aims to improve the understanding of European Venture Capital market and the matching that takes place between entrepreneurs and Venture Capitalists. We present four essays that allow us to get to know: the theoretical and empirical literature on the subject, the different types of European venture capitalists participating in the financing of early stage ventures and the dimensions that count in this relationship.

La recherche en biométrie a connu une grande évolution durant les dernières annéessurtout avec le développement des méthodes de décomposition de visage. Cependant,ces méthodes ne sont pas robustes particulièrement dans les environnements incontrôlés.Pour faire face à ce problème, l'imagerie multispectrale s'est présentée comme une nouvelletechnologie qui peut être utilisée en biométrie basée sur la reconnaissance de visage.Dans tous ce processus, la qualité des images est un facteur majeur pour concevoirun système de reconnaissance fiable. Il est essentiel de se disposer d'images de hautequalité. Ainsi, il est indispensable de développer des algorithmes et des méthodes pourl'amélioration des données sensorielles. Cette amélioration inclut plusieurs tâches tellesque la déconvolution des images, le defloutage, la segmentation, le débruitage. . . Dansle cadre de cette thèse, nous étudions particulièrement la suppression de bruit ainsi quela segmentation de visage.En général, le bruit est inévitable dans toutes applications et son élimination doit sefaire tout en assurant l'intégrité de l'information confinée dans l'image. Cette exigenceest essentielle dans la conception d'un algorithme de débruitage. Le filtre Gaussienanisotropique est conçu spécifiquement pour répondre à cette caractéristique. Nous proposonsd'étendre ce filtre au cas vectoriel où les données en disposition ne sont plus desvaleurs de pixels mais un ensemble de vecteurs dont les attribues sont la réflectance dansune longueur d'onde spécifique. En outre, nous étendons aussi le filtre de la moyennenon-local (NLM) dans le cas vectoriel. La particularité de ce genre de filtre est la robustesseface au bruit Gaussien.La deuxième tâche dans le but d'amélioration de données sensorielles est la segmentation.Le clustering est l'une des techniques souvent utilisées pour la segmentation etclassification des images. L'analyse du clustering implique le développement de nouveauxalgorithmes particulièrement ceux qui sont basés sur la méthode partitionnelle.Avec cette approche, le nombre de clusters doit être connu d'avance, chose qui n'est pastoujours vraie surtout si nous disposons de données ayant des caractéristiques inconnues.Dans le cadre de cette thèse, nous proposons de nouveaux indices de validationde clusters qui sont capables de prévoir le vrai nombre de clusters même dans le cas dedonnées complexes.A travers ces deux tâches, des expériences sur des images couleurs et multispectrales sontréalisées. Nous avons utilisé des bases de données d'image très connues pour analyserl'approche proposée. / In this thesis, we focus on multispectral image for face recognition. With such application,the quality of the image is an important factor that affects the accuracy of therecognition. However, the sensory data are in general corrupted by noise. Thus, wepropose several denoising algorithms that are able to ensure a good tradeoff betweennoise removal and details preservation. Furthermore, characterizing regions and detailsof the face can improve recognition. We focus also in this thesis on multispectral imagesegmentation particularly clustering techniques and cluster analysis. The effectiveness ofthe proposed algorithms is illustrated by comparing them with state-of-the-art methodsusing both simulated and real multispectral data sets.

Cânceres de pele não melanoma (CPNM) representam 95% das neoplasias cutâneas, dentre as quais o carcinoma espinocelular (CEC) é a forma mais agressiva devido a seu padrão de crescimento invasivo e possivelmente metastático. O padrão ouro para o diagnóstico é o exame clínico e avaliação histopatológica, que são subjetivos e dependem da experiência do médico e patologista envolvidos no procedimento. Considerando que o diagnóstico precoce é fundamental para alcançar um tratamento com resultados favoráveis, o presente trabalho utilizou a espectroscopia FTIR (Fourier transform infrared spectroscopy) para avaliar as alterações bioquímicas em pele normal causadas por lesões neoplásicas precursoras de carcinoma espinocelular. Para isto, as lesões foram induzidas quimicamente no dorso de camundongos Swiss via aplicação tópica de 9,10-dimetil-1,2-benzantraceno (DMBA) e 12-tetradecanoforbol-13-acetato (TPA) por um período de 28 semanas. Os espectros de absorção no infravermelho por transformada de Fourier foram coletados na região do infravermelho médio (4000-400 cm-1) no modo de reflexão total atenuada (ATR) e pré-processados para análise posterior. Considerou-se a amplitude da segunda derivada dos espectros de absorção como critério de comparação entre os grupos, nos quais foi observado redução de fibras colágenas e glicogênio no tecido neoplásico, assim como o aumento na intensidade de absorção de modos vibracionais associados a ácidos nucleicos e conteúdo proteico. A técnica de análise por agrupamento (HCA) foi utilizada para classificação dos espectros de tecidos normal e neoplásico, na qual obteve-se 92,6% de acurácia na discriminação dos dados. Diante disso, conclui-se que a espectroscopia FTIR associada a análise por agrupamento apresenta-se como uma potencial ferramenta para complementar a análise histopatológica na rotina clínica durante o diagnóstico de carcinoma espinocelular. / Nonmelanoma skin cancers represent 95% of cutaneous neoplasms, which squamous cell carcinoma (SCC) is the more aggressive form due to its invasive growth pattern and potentially metastatic. Histopathologycal analysis and clinical exam are the gold standard for diagnosis, which are subjective and depend on the experience of the physician and pathologist involved in the procedure. Considering that early diagnosis has fundamental importance to achieving a treatment with favorable results, this study used FTIR spectroscopy (Fourier transform Infrared spectroscopy) to assess the biochemical changes in normal skin caused by neoplastic lesions precursors of squamous cell carcinoma. For this, the lesions were chemically induced in the back of Swiss mice by topical application of 9,10- dimethyl-1,2-benzanthracene (DMBA) and 12 tetradecanoforbol-13-acetate (TPA) for a 28- week period. Fourier transform infrared spectra from normal and neoplastic tissue were collected in the mid-infrared region (4000-400 cm-1) using attenuated total reflection (ATR) sampling mode and pre-processed for group comparison. The amplitude of second derivative was considered as criteria for group comparison, which showed a reduction of collagen fibers and glycogen content in the neoplastic tissue, as well as increasing in the vibrational modes associated with nucleic acids and protein content. Hierarchical Cluster Analysis (HCA) was used for classification of spectra from neoplastic and normal tissue and obtained an accuracy of 92,6% sorting the data. In this sense, we conclude that FTIR spectroscopy associated with HCA presents as a potential tool for complementary histopathological analysis in the clinical diagnosis of squamous cell carcinoma.