Expansive parking lots, miles of asphalt, and traffic jams: this is what the modern sport stadia has come to represent. Does it have to be this way? What does the future of sports stadia hold? Can we build a stadium that is better integrated to the community around it? The stadium must become a major urban element again and it must engage the urban context. D.C. United, the most storied franchise in MLS history, needs a new home. Baltimore and other locations in Maryland would gladly welcome the Black-and-Red, but it is vital for them to remain within Washington, D.C. in a soccer specific stadium. An area of land on Buzzard Point has already been chosen for the future development of a new soccer specific stadium and is now waiting for city council approval. This thesis aims to explore a new type of urban stadium and a new stadium type as a bicycle destination at Buzzard Point. To explore a new type of urban stadium, it is vital to investigate the site's present features as well as investigate the projected future infrastructure development and real estate growth on the site. These future developments must remain throughout the design process because they will one day make up the stadium's urban context. / Master of Architecture

In today's climate of division, how can urban landscapes reflect unity? How can they remind us of what we have in common? In a city like Washington, D.C. that welcomes millions of visitors from all corners of the globe every year mainly for its many memorials, what would a memorial that invites reflection on issues that concern humanity at large look like? What would it be about? What is the best location for it? This thesis, based on the above questions, explores the memorialization of the resilience of human nature using site, water, different materials, and past and future events. The memorial will be located on Hains point, which is already a designated site for future memorials by the National Capital Planning Commission (NCPC). / This project investigates how to design a memorial with a universal theme that every visitor can relate to. The Memorial aims at providing a space that units, uplifts and invites to reflect on the Resilience of Human Nature in the face of tragedies around the world. It is a reminder that as humans we are more similar than we are different, a reminder that is needed today.

We propose a new construction of point processes, which generalizes the class of infinitely divisible point processes. Examples are the quantum Boson and Fermion gases as well as the classical Gibbs point processes, where the interaction is given by a stable and regular pair potential.

In this thesis, the dynamical system is used as a function on afinite group, to show how states change. We investigate the'numberof cycles' and 'length of cycle' under finite groups. Using grouptheory, fixed point, periodic points and some examples, formulas tofind 'number of cycles' and 'length of cycle' are derived. Theexamples used are on finite cyclic group Z_6 with respectto binary operation '+'. Generalization using finite groups ismade. At the end, I compared the dynamical system over finite cyclic groups with the finite non-cyclic groups and then prove the general formulas to find 'number of cycles' and 'length of cycle' for both cyclic and non-cyclic groups.

No description available.

Graph convolutional networks (GCNs) showed promising results in learning from point cloud data. Applications of GCNs include point cloud classification, point cloud segmentation, point cloud upsampling, and more. Recently, the introduction of Deep Graph Convolutional Networks (DeepGCNs) allowed GCNs to go deeper, and thus resulted in better graph learning while avoiding the vanishing gradient problem in GCNs. By adapting impactful methods from convolutional neural networks (CNNs) such as residual connections, dense connections, and dilated convolutions, DeepGCNs allowed GCNs to learn better from non-Euclidean data. In addition, deep learning methods proved very effective in the task of point cloud upsampling. Unlike traditional optimization-based methods, deep learning-based methods to point cloud upsampling does not rely on priors nor hand-crafted features to learn how to upsample point clouds. In this thesis, I discuss the impact and show the performance results of DeepGCNs in the task of point cloud part segmentation on PartNet dataset. I also illustrate the significance of using GCNs as upsampling modules in the task of point cloud upsampling by introducing two novel upsampling modules: Multi-branch GCN and Clone GCN. I show quantitatively and qualitatively the performance results of our novel and versatile upsampling modules when evaluated on a new proposed standardized dataset: PU600, which is the largest and most diverse point cloud upsampling dataset currently in the literature.

The aim of this thesis is to familiarize with the issue of registration of medical image sequences. The main objective was to focus on the method of feature tracking in the image and various options of its implementation. The theoretical part describes various methods for detection of feature points and future point matching methods. In the practical part these methods were implemented in Matlab programming environment and a simple graphical user interface was created.

Cette thèse aborde l'optimisation multicritère et l'optimisation à deux niveaux. L'investigation porte principalement sur les méthodes, les applications et les liens possibles entre les deux classes d'optimisation. Premièrement, nous développons une méthode de résolution des problèmes d'optimisation linéaire multicritère. Pour ce faire, nous introduisons une nouvelle caractérisation des faces efficaces et exploitons le résultat selon lequel l'ensemble des tableaux idéaux associés aux sommets extrêmes dégénérés est connexe. Ceci a permis de développer une approche de parcours de sommet extrême pour générer l'ensemble des solutions efficaces. Dans le même ordre d'idée, nous développons une méthode de résolution des problèmes linéaires à deux niveaux. L'approche est basée sur un résultat, que nous avons formalisé et démontré, qui stipule que la solution optimale du problème linéaire à deux niveaux est l'un des sommets extrêmes du domaine admissible. L'implémentation de l'approche a permis de démontrer qu'il existait dans la littérature des problèmes dont les solutions connues étaient fausses. Deuxièmement, en termes d'applications, nous construisons un modèle d'optimisation multicritère pouvant être exploité dans l'optique d'une planification optimale de la distribution de l'énergie électrique au Cameroun. Nous proposons aussi, à partir d'un modèle d'optimisation à deux niveaux, une technique dont la mise en œuvre par l'État pourrait permettre de protéger les industries locales de la concurrence des firmes internationales. Enfin, nous étudions l'interrelation entre l'optimisation multicritère et l'optimisation à deux niveaux. Tout d'abord, nous tirons des conditions de Pareto-optimalité des solutions du problème à deux niveaux. Ensuite, nous montrons qu'il est possible d'obtenir une solution optimale de certaines classes de problèmes d'optimisation à deux niveaux en résolvant deux problèmes particuliers d'optimisation multicritère. Puis, nous étudions le cas de problème à deux niveaux dans lequel chaque décideur possède plusieurs fonctions objectifs conflictuelles, en nous focalisant sur le cas linéaire. Après, nous construisons un problème artificiel d'optimisation linéaire multicritère dont l'ensemble des solutions efficaces est égal au domaine des solutions admissibles du problème du leader. Pour terminer, nous utilisons ce résultat pour proposer deux approches de résolution dépendant chacune des aspirations du leader / This thesis addresses two important classes of optimization : multiobjective optimization and bilevel optimization. The investigation concerns their solution methods, applications, and possible links between them. First of all, we develop a procedure for solving Multiple Objective Linear Programming Problems (MOLPP). The method is based on a new characterization of efficient faces. It exploits the connectedness property of the set of ideal tableaux associated to degenerated points in the case of degeneracy. We also develop an approach for solving Bilevel Linear Programming Problems (BLPP). It is based on the result that an optimal solution of the BLPP is reachable at an extreme point of the underlying region. Consequently, we develop a pivoting technique to find the global optimal solution on an expanded tableau that represents the data of the BLPP. The solutions obtained by our algorithm on some problems available in the literature show that these problems were until now wrongly solved. Some applications of these two areas of optimization problems are explored. An application of multicriteria optimization techniques for finding an optimal planning for the distribution of electrical energy in Cameroon is provided. Similary, a bilevel optimization model that could permit to protect any economic sector where local initiatives are threatened is proposed. Finally, the relationship between the two classes of optimization is investigated. We first look at the conditions that guarantee that the optimal solution of a given BPP is Pareto optimal for both upper and lower level objective functions. We then introduce a new relation that establishes a link between MOLPP and BLPP. Moreover, we show that, to solve a BPP, it is possible to solve two artificial M0PPs. In addition, we explore Bilevel Multiobjective Programming Problem (BMPP), a case of BPP where each decision maker (DM) has more than one objective function. Given a MPP, we show how to construct two artificial M0PPs such that any point that is efficient for both problems is also efficient for the BMPP. For the linear case specially, we introduce an artificial MOLPP such that its resolution can permit to generate the whole feasible set of the leader DM. Based on this result and depending on whether the leader can evaluate or not his preferences for his different objective functions, two approaches for obtaining efficient solutions are presented

The 3-D fluorescence microscope has become the method of choice in biological sciences for living cells study. However, the data acquired with conventional3-D fluorescence microscopy are not quantitatively significant because of distortions induced by the optical acquisition process. Reliable measurements need the correction of theses distortions. Knowing the instrument impulse response, also known as the PSF, one can consider the backward process of convolution induced by the microscope, known as "deconvolution". However, when the system response is not invariant in the observation field, the classical algorithms can introduce large errors in the results. In this thesis we propose a new approach, which can be easily adapted to any classical deconvolution algorithm, direct or iterative, for bypassing the non-invariance PSF problem, without any modification to the later. Based on the hypothesis that the minimal error in a restored image using non-invariance assumption is located near the used PSF position, the EMMA (Evolutive Merging Masks Algorithm) blends multiple deconvolutions in the invariance assumption using a specific merging mask set. In order to obtain sufficient number of measured PSF at various depths for a better restoration using EMMA (or any other depth-variant deconvolution algorithm) we propose a 3D PSF interpolation algorithm based on the image moments theory using Zernike polynomials as decomposition base. The known PSF are decomposed into Zernike moments set and each moment's variation is fitted into a polynomial function, the resulting functions are then used to interpolate the needed PSF's Zernike moments set to reconstruct the interpolated PSF.

The main purpose of this thesis, called The local changes in discriminatory sensation above a myofascial Trigger Point, was to assess the relationship of a local nociception in the form of the myofascial Trigger Point to the local discriminatory sensation. Based on the theoretical information, hypothesis concerning the relationship of MTrP and two point discrimination were experimentally checked. The subject of the research was the trigger point trapezius pars ascendens. Localized MTrP was clinically evaluated in terms of both static and dynamic factors. Using a palpometer, its sensitivity by level of pressure generated pain (pressure generated pain threshold) was rated. The quality of two-point discrimination was rated as well. Furthermore it was also rated how a made isometric relaxation changed the sensitivity as nociceptive so discriminatory. Discriminatory sensation (attention threshold (AT-TPD), stable threshold (SSV-TPD)) in the region above the trigger point was measured by a mechanical caliper with modified tips radius of 1mm. Generally 23 probands were examined, 11 of them had simultaneously diagnosed a presence of the constitutional hypermobility. The results of the work confirmed that the made isometric relaxation had a significant influence on the change of thresholds discrimination of two...