Eigenvectors of the Laplacian of a graph G have received increasing attention in the recent past. Here we investigate their so-called nodal domains, i.e., the connected components of the maximal induced subgraphs of G on which an eigenvector \psi does not change sign. An analogue of Courant's nodal domain theorem provides upper bounds on the number of nodal domains depending on the location of \psi in the spectrum. This bound, however, is not sharp in general. In this contribution we consider the problem of computing minimal and maximal numbers of nodal domains for a particular graph. The class of Boolean Hypercubes is discussed in detail. We find that, despite the simplicity of this graph class, for which complete spectral information is available, the computations are still non-trivial. Nevertheless, we obtained some new results and a number of conjectures. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing

Regression analysis constitutes a large portion of the statistical repertoire in applications. In case where such analysis is used for exploratory purposes with no previous knowledge of the structure one would not wish to impose any constraints on the problem. But in many applications we are interested in a simple parametric model to describe the structure of a system with some prior knowledge of the structure. An important example of this occurs when the experimenter has the strong belief that the regression function changes monotonically in some or all of the predictor variables in a region of interest. The analyses needed for statistical inference under such constraints are nonstandard. The specific aim of this study is to introduce a technique which can be used for statistical inferences of a multivariate simple regression with some non-standard constraints.

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / Neste trabalho, consideramos o conceito de segmento de reta como uma introduÃÃo ao conceito de conjunto convexo e suas aplicaÃÃes no R2 e R3, conceito esse reforÃado com a prova do baricentro do triÃngulo. Calculamos a relaÃÃo de posiÃÃo entre um ponto e um segmento de reta. Definimos o conceito de cone e mostramos os diferentes tipos de cone com alguns exemplos. Definimos a envoltÃria convexa no plano e no espaÃo podendo assim estabelecer a relaÃÃo entre um ponto e um triÃngulo e a relaÃÃo entre um ponto e um tetraedro. Apresentamos o conceito de hiperplano e finalizamos relacionando a convexidade com a simetria. / In this paper, we consider the concept of line segment as an introduction to the concept of convex set and its applications, this concept reinforced by the evidence of centroid of the triangle. We calculate the relative position between a point and a line segment. We define the cone concept and show the different types of cone with some examples. We define the convex envelope in the plane and in space can then estabilish the relationship between a point and a triangle and the relationship between a point and a tetrahedron. Introducing the concept of hyperplane and finished relating the convexity with symmetry.

Cette thèse étudie la fibre de Milnor d'un arrangement d'hyperplans complexe central, et l'opérateur de monodromie sur ses groupes de cohomologie. On s'intéresse à la problématique suivante : peut-on déterminer l'opérateur de monodromie, ou au moins les nombres de Betti de la fibre de Milnor, à partir de l'information contenue dans le treillis d'intersection de l'arrangement? On donne deux théorèmes d'annulation des sous-espaces propres non triviaux de l'opérateur de monodromie. Le premier résultat s'applique à une large classe d'arrangements, le deuxième à des arrangements de droites projectives tels qu'il existe une droite contenant exactement un point de multiplicité supérieure ou égale à trois. Dans le dernier chapitre, on considère la structure de Hodge mixte des groupes de cohomologie de la fibre de Milnor d'un arrangement central et essentiel dans l'espace complexe de dimension quatre. On donne ensuite l'équivalence entre la trivialité de la monodromie, la nullité des coefficients non entiers du spectre de l'arrangement, et la nullité des nombres de Hodge mixtes des groupes de cohomologie de la fibre de Milnor. / This Ph.D.thesis studies the Milnor fiber of a central complex hyperplane arrangement, and the monodromy operator on its cohomology groups. Our aim is to study the following open question: is it possible to determinate the monodromy operator, or at least the Betti numbers of the Milnor fiber, just using the information contained in the intersection lattice of the arrangement? We give two vanishing results on the non trivial eigenspaces of the monodromy. The first one applies to a large class of arrangements, and the second one to projective line arrangements with a line containing exactly one point of multiplicity greater or equal to three.Then we consider the mixed Hodge structure of the cohomology groups of the Milnor fiber, for a central and essential hyperplane arrangement in the complex space of dimension four. In this case, we give the equivalence between triviality of the monodromy, Tate properties, and nullity of the non integer spectrum's coefficients.Keywords: hyperplane arrangement, intersection lattice, Milnor fiber, monodromy.

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Eigenvectors of the Laplacian of a graph G have received increasing attention in the recent past. Here we investigate their so-called nodal domains, i.e. the connected components of the maximal induced subgraphs of G on which an eigenvector ψ does not change sign. An analogue of Courant's nodal domain theorem provides upper bounds on the number of nodal domains depending on the location of ψ in the spectrum. This bound, however, is not sharp in general. In this contribution we consider the problem of computing minimal and maximal numbers of nodal domains for a particular graph. The class of Boolean Hypercubes is discussed in detail. We find that, despite the simplicity of this graph class, for which complete spectral information is available, the computations are still non-trivial. Nevertheless, we obtained some new results and a number of conjectures.

Background. Hyperplane folding was introduced by Lars Lundberg et al. in Hyperplane folding increased the margin while suffering from a flaw, referred to asover-rotation in this thesis. The aim of this thesis is to introduce a new different technique thatwould not over-rotate data points. This novel technique is referred to as RubberBand folding in the thesis. The following research questions are addressed: 1) DoesRubber Band folding increases classification accuracy? 2) Does Rubber Band fold-ing increase the Margin? 3) How does Rubber Band folding effect execution time? Rubber Band folding was implemented and its result was compared toHyperplane folding and the Support-vector machine. This comparison was done byapplying Stratified ten-fold cross-validation on four data sets for research question1 & 2. Four folds were applied for both Hyperplane folding and Rubber Band fold-ing, as more folds can lead to over-fitting. While research question 3 used 15 folds,in order to see trends and is not affected by over-fitting. One BMI data set, wasartificially made for the initial Hyperplane folding paper. Another data set labeled patients with, or without a liver disorder. Another data set predicted if patients havebenign- or malign cancer cells. Finally, a data set predicted if a hepatitis patient isalive within five years.Results.Rubber Band folding achieved a higher classification accuracy when com-pared to Hyperplane folding in all data sets. Rubber Band folding increased theclassification in the BMI data set and cancer data set while the accuracy for Rub-ber Band folding decreased in liver and hepatitis data sets. Hyperplane folding’saccuracy decreased in all data sets.Both Rubber Band folding and Hyperplane folding increases the margin for alldata sets tested. Rubber Band folding achieved a margin higher than Hyperplanefolding’s in the BMI and Liver data sets. Execution time for both the classification ofdata points and the training time for the classifier increases linearly per fold. RubberBand folding has slower growth in classification time when compared to Hyperplanefolding. Rubber Band folding can increase the classification accuracy, in whichexact cases are unknown. It is howevered believed to be when the data is none-linearly seperable.Rubber Band folding increases the margin. When compared to Hyperplane fold-ing, Rubber Band folding can in some cases, achieve a higher increase in marginwhile in some cases Hyperplane folding achieves a higher margin.Both Hyperplane folding and Rubber Band folding increases training time andclassification time linearly. The difference between Hyperplane folding and RubberBand folding in training time was negligible while Rubber bands increase in classifi-cation time was lower. This was attributed to Rubber Band folding rotating fewerpoints after 15 folds.

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Darbe nagrinėjami judesiai n-matėje hiperplokštuminių elementų erdvėje . Gauti rezultatai: 1. Įrodyta, kad n-matėje hiperplokštuminių elementų erdvėje maksimalus judesių grupių parametrų skaičius yra parametrai. 2. Įrodyta, kad n-matėje hiperplokštuminių elementų erdvėje su nesimetrine tiesine sietimi maksimalus judesių grupių parametrų skaičius yra parametrai. / The present work analyses movements in n-dimensional space of hyperplaine elements . The received results: 1. It was proved that in the n-dimensional space the maximum number of movement groups parameters, number is parameters 2. It was proved that in the n-dimensional space the maximum number of movement groups parameters with asymmetric linear connection is parameters.

CoordenaÃÃo de AperfeiÃoamento de Pessoal de NÃvel Superior / Neste trabalho, consideramos combinaÃÃes afins de vetores de um espaÃo vetorial com especiais aplicaÃÃes no ensino mÃdio atravÃs da mÃdia aritmÃtica ponderada e da desigualdade de Jensen. Verificamos caracterÃsticas de transformaÃÃes lineares de conjuntos especÃficos nos espaÃos vetoriais como conjuntos convexos e variedades afins, atravÃs do nÃcleo e da imagem das transformaÃÃes. Estabelecemos relaÃÃes entre transformaÃÃes afins, combinaÃÃes afins e transformaÃÃes lineares. Discutimos a dimensÃo do hiperplano relacionando-o como variedade afim. Vemos que todo subespaÃo vetorial de Rn com dimensÃo n - 1 Ã um hiperplano, assim como o nÃcleo de um funcional linear. / In this paper, we consider combinations of related vectors of a vector space with special applications in high school through the weighted arithmetic mean and the Jensen inequality. We observed characteristics of specific sets of linear transformations in the vector spaces as convex sets and related varieties through the core and image transformations. Established relations between affine transformations, combinations thereof and linear transformations. We discuss the size of the hyperplane relating it as affine variety. We see that all of Rn vector subspace with dimension n - 1 is a hyperplane, as the core of a linear functional.