The moose (Alces alces) is very important both economically and ecologically, therefore all knowledge of moose is vital for future management of the moose population. Little is known about moose habitat selection in Sweden. In coastal southwestern Sweden growing human population and new infrastructure projects continuously threaten to fragment and isolate local moose populations. The habitat selection of 22 moose, 8 males and 14 females, in southwestern Sweden was studied from February 2002 until December 2005. The moose were captured and fitted with GPS-collars and positions were collected at 2-hour intervals. The number of moose positions totaled 71103 during the study period of 46 months. Data for individual animals were divided into four seasons: spring, summer, fall and winter based on climate and moose biology. A total of 125 moose seasonal home ranges were generated and habitat use within each of the generated home ranges was studied using Euclidean distance-based analysis. A reclassified digital landcover map was divided into the land use classes agriculture, clear-cut, coniferous forest, deciduous forest, mire and mountain. The results showed that there was a difference in habitat selection between males and females. Males were significantly closer to forest and clear-cuts compared to females. Both males and females selected clear-cuts and avoided agriculture within their home ranges. / Älgen är en viktig art, både ekonomiskt och ekologiskt, och all kunskap är viktig för att även i framtiden kunna sköta en sund älgstam. Trots flertalet studier finns det många frågetecken om älgens habitatval i Sverige. En ökad exploateringstakt och nya infrastrukturprojekt hotar att fragmentera och isolera populationer av älg. Habitatvalet hos 22 älgar, 8 tjurar och 14 kor, i sydvästra Sverige studerades mellan februari 2002 och december 2005. Älgarna sövdes och utrustades med GPS-sändare, deras positioner registrerades varannan timma och det totala antalet positioner under den 46 månader långa studietiden var 71103 stycken. Data från varje älg delades in i 4 säsonger; vår, sommar, höst och vinter, baserat på klimat och älgens biologi. Totalt genererades 125 hemområden baserade på säsong, och valet av habitat inom varje hemområde studerades med hjälp av Euclidean distance-based analysis. En omklassificerad digital marktäckedata användes som var indelad i 6 olika klasser; odlad mark, hygge, barrskog, lövskog, myrmark och berg i dagen. Resultaten visade att det var skillnad mellan könen i hur de väljer habitat. Tjurarna var signifikant närmare barrskog och hyggen än korna, men både tjurar och kor selekterade för hyggen och undvek odlad mark inom deras hemområden.

This work is based on Shafer's Dichromatic Reflection Model as applied to color image formation. The color spaces RGB, XYZ, CIELAB, CIELUV, rgb, l1l2l3, and the new h1h2h3 color space are discussed from this perspective. Two color similarity measures are studied: the Euclidean distance and the vector angle. The work in this thesis is motivated from a practical point of view by several shortcomings of current methods. The first problem is the inability of all known methods to properly segment objects from the background without interference from object shadows and highlights. The second shortcoming is the non-examination of the vector angle as a distance measure that is capable of directly evaluating hue similarity without considering intensity especially in RGB. Finally, there is inadequate research on the combination of hue- and intensity-based similarity measures to improve color similarity calculations given the advantages of each color distance measure. These distance measures were used for two image understanding tasks: edge detection, and one strategy for color image segmentation, namely color clustering. Edge detection algorithms using Euclidean distance and vector angle similarity measures as well as their combinations were examined. The list of algorithms is comprised of the modified Roberts operator, the Sobel operator, the Canny operator, the vector gradient operator, and the 3x3 difference vector operator. Pratt's Figure of Merit is used for a quantitative comparison of edge detection results. Color clustering was examined using the k-means (based on the Euclidean distance) and Mixture of Principal Components (based on the vector angle) algorithms. A new quantitative image segmentation evaluation procedure is introduced to assess the performance of both algorithms. Quantitative and qualitative results on many color images (artificial, staged scenes and natural scene images) indicate good edge detection performance using a vector version of the Sobel operator on the h1h2h3 color space. The results using combined hue- and intensity-based difference measures show a slight improvement qualitatively and over using each measure independently in RGB. Quantitative and qualitative results for image segmentation on the same set of images suggest that the best image segmentation results are obtained using the Mixture of Principal Components algorithm on the RGB, XYZ and rgb color spaces. Finally, poor color clustering results in the h1h2h3 color space suggest that some assumptions in deriving a simplified version of the Dichromatic Reflectance Model might have been violated.

The main result of this thesis is the development of a theory of semidefinite facial reduction for the Euclidean distance matrix completion problem. Our key result shows a close connection between cliques in the graph of the partial Euclidean distance matrix and faces of the semidefinite cone containing the feasible set of the semidefinite relaxation. We show how using semidefinite facial reduction allows us to dramatically reduce the number of variables and constraints required to represent the semidefinite feasible set. We have used this theory to develop a highly efficient algorithm capable of solving many very large Euclidean distance matrix completion problems exactly, without the need for a semidefinite optimization solver. For problems with a low level of noise, our SNLSDPclique algorithm outperforms existing algorithms in terms of both CPU time and accuracy. Using only a laptop, problems of size up to 40,000 nodes can be solved in under a minute and problems with 100,000 nodes require only a few minutes to solve.

This thesis shows the result from investigations of methods that use distance vectors when matching pictures. The distance vectors are available in a distance map made by the Euclidean Distance Transform. The investigated methods use the two characteristic features of the distance vector when matching pictures, length and direction. The length of the vector is used to calculate a value of how good a match is and the direction of the vector is used to predict a transformation to get a better match. The results shows that the number of calculation steps that are used during a search can be reduced compared to matching methods that only uses the distance during the matching.

This work is based on Shafer's Dichromatic Reflection Model as applied to color image formation. The color spaces RGB, XYZ, CIELAB, CIELUV, rgb, l1l2l3, and the new h1h2h3 color space are discussed from this perspective. Two color similarity measures are studied: the Euclidean distance and the vector angle. The work in this thesis is motivated from a practical point of view by several shortcomings of current methods. The first problem is the inability of all known methods to properly segment objects from the background without interference from object shadows and highlights. The second shortcoming is the non-examination of the vector angle as a distance measure that is capable of directly evaluating hue similarity without considering intensity especially in RGB. Finally, there is inadequate research on the combination of hue- and intensity-based similarity measures to improve color similarity calculations given the advantages of each color distance measure. These distance measures were used for two image understanding tasks: edge detection, and one strategy for color image segmentation, namely color clustering. Edge detection algorithms using Euclidean distance and vector angle similarity measures as well as their combinations were examined. The list of algorithms is comprised of the modified Roberts operator, the Sobel operator, the Canny operator, the vector gradient operator, and the 3x3 difference vector operator. Pratt's Figure of Merit is used for a quantitative comparison of edge detection results. Color clustering was examined using the k-means (based on the Euclidean distance) and Mixture of Principal Components (based on the vector angle) algorithms. A new quantitative image segmentation evaluation procedure is introduced to assess the performance of both algorithms. Quantitative and qualitative results on many color images (artificial, staged scenes and natural scene images) indicate good edge detection performance using a vector version of the Sobel operator on the h1h2h3 color space. The results using combined hue- and intensity-based difference measures show a slight improvement qualitatively and over using each measure independently in RGB. Quantitative and qualitative results for image segmentation on the same set of images suggest that the best image segmentation results are obtained using the Mixture of Principal Components algorithm on the RGB, XYZ and rgb color spaces. Finally, poor color clustering results in the h1h2h3 color space suggest that some assumptions in deriving a simplified version of the Dichromatic Reflectance Model might have been violated.

The main result of this thesis is the development of a theory of semidefinite facial reduction for the Euclidean distance matrix completion problem. Our key result shows a close connection between cliques in the graph of the partial Euclidean distance matrix and faces of the semidefinite cone containing the feasible set of the semidefinite relaxation. We show how using semidefinite facial reduction allows us to dramatically reduce the number of variables and constraints required to represent the semidefinite feasible set. We have used this theory to develop a highly efficient algorithm capable of solving many very large Euclidean distance matrix completion problems exactly, without the need for a semidefinite optimization solver. For problems with a low level of noise, our SNLSDPclique algorithm outperforms existing algorithms in terms of both CPU time and accuracy. Using only a laptop, problems of size up to 40,000 nodes can be solved in under a minute and problems with 100,000 nodes require only a few minutes to solve.

Faces provide cues for judgments regarding the emotional state of individuals. Using signal-detection methodology and a standardized stimulus set, the overall aim of the present dissertation was to investigate the detection of emotional facial expressions (i.e., angry and happy faces) with neutral expressions as the nontarget stimuli. Study I showed a happy-superiority effect and a bias towards reporting happiness in female faces. As work progressed, questions arose regarding whether the emotional stimuli were equal with regard to perceived strength of emotion, and whether the neutral faces were perceived as neutral. To further investigate the effect of stimulus quality on the obtained findings, Study II was designed such that the facial stimuli were rated on scales of happy-sad, angry-friendly, and emotionality. Results showed that ‘neutral’ facial expressions were not rated as neutral, and that there was a greater perceived distance between happy and neutral faces than between angry and neutral faces. These results were used to adjust the detectability measures to compensate for the varying distances of the angry and happy stimuli from the neutral stimuli in the emotional space. The happy-superiority effect was weakened, while an angry-female disadvantage remained. However, as these results were based upon different participant groups for detection and emotional rating, Study III was designed to investigate whether the results from Studies I and II could be replicated in a design where the same participants performed both tasks. Again, the results showed the non-neutrality of ‘neutral’ expressions and that happiness was more easily detected than anger, as shown in general emotion as well as specific emotion detection. Taken together, the overall results of the present dissertation demonstrate a happy-superiority effect that was greater for female than male faces, that angry-female faces were the most difficult to detect, and a bias to report female faces as happy. / At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: In press. Paper 2: Manuscript. Paper 3: Manuscript.

Resumo: O objetivo do presente trabalho foi estudar a divergência genética por meio de caracteres morfológicos de frutos, diásporos, ráquilas e plântulas, entre palmeiras matrizes de Oenocarpus bacaba Mart., em três populações naturais do Amapá, Comunidade Lontra da Pedreira, Parque Zoobotânico em Macapá e Município de Porto Grande. A divergência genética foi avaliada pela análise de agrupamento, através do algaritmo de Tocher e do método do Ward, obtido a partir da matriz de dissimilaridade pela Distância Euclidiana. A técnica dos componentes principais foi utilizada para identificar a importância relativa de cada variável para a divergência genética. Houve certa concordância nos dois métodos de agrupamento. Dos 17 caracteres avaliados 10 deles (60%) são passíveis de descarte nas três áreas de estudo / Abstract: The objective of this work was to study the genetic divergence for morphological characters of fruits, disseminules, rachilles and seedlings, among matrices of Oenocarpus bacaba Mart. palm, in three natural populations of Amapa city, Lontra da Pedreira community, Park Zoobotany in Macapa and Porto Grande municipality. The genetic divergence was assessed by clusters analysis by the Tocher algaritmo and Ward's method, obtained from the matrix of dissimilarity of the Euclidian distance. The technique of principal components was used to identify the relative importance of each variable for genetic divergence. There was some agreement among the two groups The twenty characters evaluated, 10 of them (60%) are likely to discard of the three areas of study / Orientadora: Fabíola Vitti Môro / Coorientador: Antônio Sérgio Ferraudo / Coorientador: Fabiano Cesarino / Banca: Raquel Silva Costa / Banca: Ricardo Machado da Silva / Mestre

Orientador: Carlile Campos Lavor / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Matemática Estatística e Computação Científica / Made available in DSpace on 2018-08-25T18:42:28Z (GMT). No. of bitstreams: 1 Rezende_GermanoAbudde_D.pdf: 1418033 bytes, checksum: 61d29b02274278ede5ffca797e26371a (MD5) Previous issue date: 2014 / Resumo: A geometria de distâncias é o estudo da geometria baseado no conceito de distância. Ela é útil em várias aplicações, onde os dados de entrada consistem de um conjunto incompleto de distâncias, e a saída é um conjunto de pontos no espaço euclidiano, que realiza as distâncias dadas. No Problema de Geometria de Distâncias (DGP), é dado um inteiro K > 0 e um grafo simples, não direcionado, G = (V,E,d), cujas arestas são ponderadas por uma função não negativa d. Queremos determinar se existe uma função (realização) que leva os vértices de V em coordenadas no espaço euclidiano K-dimensional, satisfazendo todas as restrições de distâncias dadas por d. Um DGPk (com K fixado) está fortemente relacionado a um outro tipo de problema, que trata dos possíveis completamentos de uma certa matriz de distâncias euclidianas. Este último pode ser visto, em um certo sentido, como o "dual do primeiro problema". Neste trabalho, exploramos essa dualidade com a finalidade de propor melhorias no método Branch-and-Prune aplicado a uma versão discreta do DGPk / Abstract: Distance Geometry is the study of geometry based on the concept of distance. It is useful in many applications where the input data consists of an incomplete set of distances, and the output is a set of points in some Euclidean space which realizes the given distances. In the Distance Geometry Problem (DGP), it is given an integer K > 0 and a simple undirected weighted graph G = (V,E,d), whose edges are weighted by a non-negative function d. We want to determine if there is a (realization) function that associates the vertices of V with coordinates of the K-dimensional Euclidean space satisfying all distance constraints given by d. A DGPk (with K fixed) is closely related to another type of problem, which treats the possible completions of a certain Euclidean distance matrix. In some sense, this is the "dual" of the first problem. We explore this duality in order to improve the Branch-and-Prune method applied to a discrete version of the DGPk / Doutorado / Matematica Aplicada / Doutor em Matemática Aplicada

According to IRIG 106-15, the ARTM CPM waveform, a kind of multi-h partial response continuous phase modulation (CPM), has almost three times the spectral efficiency of PCM/FM and approximately the same detection efficiency of PCM/FM. But the improved spectral efficiency of ARTM CPM comes at the price of computational complexity in the receiver. This paper focuses on multi-h full response CPM, which generally has less detection complexity than ARTM CPM, but also has good spectral efficiency and detection efficiency. Taking the minimum Euclidean distance, spectral efficiency and detection complexity as judgment criterions, optimum parameter combinations for multi-h full response CPM are presented.