Mike Arce is the owner of a 30-hectare farm in an agricultural area on the coast north of Lima, Peru. He must find a solution to the liquidity problem that arose at the end of 2016 and determine if he has adequate accounting information to make his decision. Students are challenged to review information from an accounting and financial perspective. In the resolution of the case, international rules concerning information to be submitted via financial statements must be considered, especially taking into account the rules concerning agriculture, property/plant and equipment and inventories. This case lends itself to analysis and projection of financial statements and to seeking alternative solutions.

Neste trabalho apresentamos uma nova abordagem para a exploração de fibras neurais a partir de imagens de tensores de difusão. A estratégia combina técnicas de visualização de informação e visualização científica para obter uma rápida e precisa interpretação das fibras. Para isto fazemos uma transformação das fibras para vetores, e utilizamos uma nova técnica de projeção multi-dimensional (P-LSP), para trabalhar com conjuntos grandes de dados. A exploração do espaço das fibras é feita através desta projeção. Além disso, é apresentada a extensão das técnicas LSP e P-LSP para criar projeções em 3D, assim como estratégias que permitem interagir com pontos em 3D. Outra contribuição deste trabalho é a modificação de um método apresentado para criar superfícies de densidade fechadas sobre pontos esparsos. Esta modificação torna possível criar superfícies sobre conjuntos de pontos maiores com uma qualidade aceitável, o que é utilizado para representar conjunto de fibras como uma superfície. Esta nova abordagem é comparada com trabalhos similares mostrando nossas vantagens em termos de tempo de processamento, qualidade e funcionalidades para analisar esta categoria de dados / This work presents a novel approach for the exploration of neural fibers extracted from Diffusion Tensor Images. The developed strategy combines techniques from information and scientific visualization in order to attain a fast and precise interpretation of fiber sets. The approach transforms fibers into vectors from which a new multidimensional projection technique (PLSP) capable of handling large data sets. The fiber space is explored through the projection. Additionally this work extends P-LSP and LSP projections to 3D, and defines strategies to interact with 3D sparse points. Another contribution of this work is the extension of a method to create close density surfaces over the sparse space generated by the projections. The visualization approach is compared with other similar work showing advantages in processing time, quality and exploration capability to analyze this type of data sets

Le vieillissement des personnes en situation de handicap est devenu, au cours des quarante dernières années, une problématique prégnante non seulement du secteur médico-social mais aussi de notre société. L’allongement de la durée de la vie est un phénomène positif, résultat des efforts de professionnalisation des accompagnements des personnes en situation de handicap. Le vieillissement est un processus, certes irréversible, mais naturel. Si quelques personnes en sont les rares témoins, dans les années 1980, le phénomène prend de l’ampleur avec le temps et devient un phénomène démographique. Pour le démographe, la notion de vieillissement concerne une population et non des individus. L’observation de ce processus permet de prévoir la tendance de l’évolution des besoins d’une population dans les domaines sanitaires, sociaux et médico-sociaux, mais n’indique rien quant aux besoins de la personne vieillissante. Les populations évoluent, de nouvelles apparaissent et notre système sociétal doit s’adapter à de nouveaux besoins. L’approche socio-démographique du vieillissement des personnes en situation de handicap proposée ici tend à étudier les spécificités de la population avançant en âge au sein des établissements et services médico-sociaux de la région Bourgogne-Franche-Comté. Travailler sur ce sujet implique de comprendre, mais aussi de mesurer l’ampleur de la problématique. / The aging of people with disabilities has become, in the last forty years, a significant issue in the medico-social sector and also in our society. The lengthening of life is a positive phenomenon, a result of the efforts to professionalize the accompaniment of people with disabilities. Aging is a process, certainly irreversible, but natural. If a few people are the rare witnesses, in the 1980s, the phenomenon grows with time and becomes a demographic phenomenon. For the demographer, the notion of aging applies to a population and not to individuals. The observation of this process makes it possible to predict the trend of the changing needs of a population in the health, social and medico-social fields, but does not indicate anything about the needs of the aging person. Populations are changing, new ones are emerging and our societal system needs to adapt to new needs. The socio-demographic approach of the aging of people with disabilities proposed here tends to study the specificities of the aging population within medical and social services and institutions in the Bourgogne-Franche-Comté region. Working on this subject implies understanding but also measuring the extent of the problem.

A área de visualização volumétrica engloba um conjunto de técnicas utilizadas na representação, manipulação e exibição de dados associados à região de um volume, possibilitando, assim, a exploração e melhor compreensão do interior de objetos de natureza tridimensional. Contudo, algumas limitações ainda são encontradas nessa área, como, por exemplo, a exploração de mais de um valor simultaneamente em conjuntos de dados volumétricos multivariados. Além desse desafio, outro objeto de grande interesse da comunidade científica é a exploração de volumes variantes no tempo. A complexidade nesse caso está em tratar ou processar uma quantidade muito grande de dados buscando descobrir propriedades, estruturas ou características que variam com o tempo. O presente trabalho propõe técnicas e abordagens, baseadas no conceito de projeções multidimensionais, visando dar apoio à análise de conjuntos volumétricos multivariados que variam no tempo. A primeira técnica proposta, denominada Fastmap*, possibilitou a projeção de espaços de alta dimensionalidade em fluxo contínuo. A segunda técnica apresentada, denominada RLNP, permitiu a projeção de dados por vizinhança mantendo a coerência temporal nos dados projetados, além de possuir a capacidade de projetar espaços de alta dimensão com um nível de stressbaixo. Também, propomos uma abordagem para a análise baseada em atributos, denominada Scatter Projection, que facilita a exploração focada em um atributo específico junto com a similaridade dos dados entre eles. Finalmente, propõe-se uma abordagem baseada na reprojeção de agrupamentos usando técnicas de seleção de atributos para tentar identificar melhor as estruturas internas do volume. Assim, o presente trabalho contribui no sentido de levantar e discutir limitações das técnicas disponíveis, e em seguida, buscar possibilidades de solução para tais questões, propondo técnicas e abordagens que possibilitam a exploração de grandes conjuntos de dados volumétricos multivariados, mantendo a coerência temporal / The area of volume visualization encompasses a set of techniques used for representation, manipulation and display of data associated with a region of a volume, thus enabling the exploration and understanding of the interior of three-dimensional objects. However, some limitations are still encountered in this area. For example, the simultaneous exploration of more than one value in multivariate volumetric datasets. Beyond this challenge, another issue of great interest to the scientific community is the exploration of time-varying volumes. The complexity of this case lies in treatment or processing of a very large amount of data, seeking to discover properties, structures, or characteristics that may vary in time. This work proposes techniques and approaches, based on the concept of multidimensional projections, in order to support multivariate volumetric analysis of time varying data sets. The first technique proposed, called Fastmap*, enables the projection of high dimensional streaming data. The second technique presented, called Recursive Laplacian-based Neiboorhood Projection, allows the projection of data sets based on neighborhoods, maintaining the temporal coherence in the projected data, besides having the ability to project highdimensional spaces with a low level of stress. Also, we propose an approach for the analysis of specific attributes, referred to as Scatter Projection, which facilitates the exploration focused on a specific attribute and on the similarity between them. Finally, we propose an approach based on reprojection of groups using feature selection techniques for better identification of internal structures of the volume. Thus, this study contributes towards surveying and discussing limitations of the area, and then seeks ways of solving these issues, proposing techniques and approaches that enable the exploration of multidimensional volumetric time varying data sets, maintaining the temporal coherence

Neste trabalho apresentamos uma nova abordagem para a exploração de fibras neurais a partir de imagens de tensores de difusão. A estratégia combina técnicas de visualização de informação e visualização científica para obter uma rápida e precisa interpretação das fibras. Para isto fazemos uma transformação das fibras para vetores, e utilizamos uma nova técnica de projeção multi-dimensional (P-LSP), para trabalhar com conjuntos grandes de dados. A exploração do espaço das fibras é feita através desta projeção. Além disso, é apresentada a extensão das técnicas LSP e P-LSP para criar projeções em 3D, assim como estratégias que permitem interagir com pontos em 3D. Outra contribuição deste trabalho é a modificação de um método apresentado para criar superfícies de densidade fechadas sobre pontos esparsos. Esta modificação torna possível criar superfícies sobre conjuntos de pontos maiores com uma qualidade aceitável, o que é utilizado para representar conjunto de fibras como uma superfície. Esta nova abordagem é comparada com trabalhos similares mostrando nossas vantagens em termos de tempo de processamento, qualidade e funcionalidades para analisar esta categoria de dados / This work presents a novel approach for the exploration of neural fibers extracted from Diffusion Tensor Images. The developed strategy combines techniques from information and scientific visualization in order to attain a fast and precise interpretation of fiber sets. The approach transforms fibers into vectors from which a new multidimensional projection technique (PLSP) capable of handling large data sets. The fiber space is explored through the projection. Additionally this work extends P-LSP and LSP projections to 3D, and defines strategies to interact with 3D sparse points. Another contribution of this work is the extension of a method to create close density surfaces over the sparse space generated by the projections. The visualization approach is compared with other similar work showing advantages in processing time, quality and exploration capability to analyze this type of data sets

Dancing a duet with my shadow by integrating dance and digital media in an elaborate and entertaining performance.

<p>This thesis concerns dimensions and projections of sets that could be described as fractals. The background is applied problems regarding analysis of human tissue. One way to characterize such complicated structures is to estimate the dimension. The existence of different types of dimensions makes it important to know about their properties and relations to each other. Furthermore, since medical images often are constructed by x-ray, it is natural to study projections.</p><p>This thesis consists of an introduction and a summary, followed by three papers.</p><p>Paper I, Anders Nilsson, Dimensions and Projections: An Overview and Relevant Examples, 2006. Manuscript.</p><p>Paper II, Anders Nilsson and Peter Wingren, Homogeneity and Non-coincidence of Hausdorff- and Box Dimensions for Subsets of ℝ<i>n</i>, 2006. Submitted.</p><p>Paper III, Anders Nilsson and Fredrik Georgsson, Projective Properties of Fractal Sets, 2006. To be published in Chaos, Solitons and Fractals.</p><p>The first paper is an overview of dimensions and projections, together with illustrative examples constructed by the author. Some of the most frequently used types of dimensions are defined, i.e. Hausdorff dimension, lower and upper box dimension, and packing dimension. Some of their properties are shown, and how they are related to each other. Furthermore, theoretical results concerning projections are presented, as well as a computer experiment involving projections and estimations of box dimension.</p><p>The second paper concerns sets for which different types of dimensions give different values. Given three arbitrary and different numbers in (0,<i>n</i>), a compact set in ℝ<i>n</i> is constructed with these numbers as its Hausdorff dimension, lower box dimension and upper box dimension. Most important in this construction, is that the resulted set is homogeneous in the sense that these dimension properties also hold for every non-empty and relatively open subset.</p><p>The third paper is about sets in space and their projections onto planes. Connections between the dimensions of the orthogonal projections and the dimension of the original set are discussed, as well as the connection between orthogonal projection and the type of projection corresponding to realistic x-ray. It is shown that the estimated box dimension of the orthogonal projected set and the realistic projected set can, for all practical purposes, be considered equal.</p>

The South Nation watershed is located in Eastern Ontario, Canada and managed under the authority of the South Nation Conservation (SNC). The watershed covers an area of 400,000 hectares with four dominant categories of land-use classes (60% agriculture, 34% forest, 5% mixed urban, and 1% other). Water quality is a great concern for the SNC as many anthropogenic activities generate harmful pollutants (such as heavy metals, nitrogen, phosphorus, and pesticides) that are discharged to the river through surface and groundwater flow. The discharge patterns of these pollutants are mainly driven by land-use distribution within the watershed which has been constantly evolving with urbanization and intensification of agriculture. Major changes in land-uses can potentially offset current SNC efforts to mitigate water pollution. The objective of the current study is to predict land-use series of maps for the South Nation watershed starting from 1991 to 2020. The prediction is carried out using the land-use allocation algorithm of the Dyna-CLUE (Dynamic Conversion of Land-Use and its Effects) model which is implemented for local regions. Dyna-CLUE is a spatially explicit hybrid land-use allocation model that combines estimation and simulation models, and its allocation procedures predict future trends of land-use surface (estimated from historical trends). The binary logistic regression is used to link preferences of land-use classes and potential demographic and geographic driving factors. Expert judgment was used to select a set of spatial driving factors believed to be responsible for changes in land-use distribution in the South Nation watershed. Three different scenarios for future development of the region were considered, with different initial conditions and conversion restrictions. The simulation results were evaluated using visual and statistical validation techniques to assess the performance of the model in generating maps similar to reality. The Dyna-CLUE model was successfully applied to the South Nation watershed. It was observed that the simulated maps generated from the model were in good agreement with the reality maps. This was confirmed through statistical validation via map pair analysis (error matrix) used to assess the overall accuracy of the model predictions. Results showed that the model was sensitive to land-use restrictions. Such type of modeling can be valuable for assessing the land-use changes at the local level, and setting up a decision support system for the South Nation Conservation towards sustainable land-use management in the watershed. Better results are expected to be achieved with more reliable datasets (i.e., accurate classification of land-use types in reality maps). Data availability and quality were the main obstacles that faced this research work. Our work has the merit to be the first application of CLUE model in Eastern Ontario.

In our project we discuss a finite element time-relaxation method for high Reynolds number flows. The key idea consists of using local projections on polynomials defined on macro element of each pair of two elements sharing a face. We give the formulation for the scalar convection–diffusion equation and a numerical illustration.

The explosive growth of digital data collection and processing demands a new approach to the historical engineering methods of data correlation and model creation. A new prediction methodology based on high dimensional data has been developed. Since most high dimensional data resides on a low dimensional manifold, the new prediction methodology is one of dimensional reduction with embedding into a diffusion space that allows optimal distribution along the manifold. The resulting data manifold space is then used to produce a probability density function which uses spatial weighting to influence predictions i.e. data nearer the query have greater importance than data further away. The methodology also allows data of differing phenomenology e.g. color, shape, temperature, etc to be handled by regression or clustering classification. The new methodology is first developed, validated, then applied to common engineering situations, such as critical heat flux prediction and shuttle pitch angle determination. A number of illustrative examples are given with a significant focus placed on the objective identification of two-phase flow regimes. It is shown that the new methodology is robust through accurate predictions with even a small number of data points in the diffusion space as well as flexible in the ability to handle a wide range of engineering problems.