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A graph consists of a set and a binary relation on that set. Each element of the set is a node of the graph, while each element of the binary relation is an edge of the graph that encodes a relationship between two nodes. Graph are pervasive in many areas of science, engineering, and the social sciences: servers on the Internet are connected, proteins interact in large biological systems, social networks encode the relationships between people, and functions call each other in a program. In these domains, the graphs can become very large, consisting of hundreds of thousands of nodes and millions of edges. Graph drawing approaches endeavour to place these nodes in two or three-dimensional space with the intention of fostering an understanding of the binary relation by a human being examining the image. However, many of these approaches to drawing do not exploit higher-level structures in the graph beyond the nodes and edges. Frequently, these structures can be exploited for drawing. As an example, consider a large computer network where nodes are servers and edges are connections between those servers. If a user would like understand how servers at UBC connect to the rest of the network, a drawing that accentuates the set of nodes representing those servers may be more helpful than an approach where all nodes are drawn in the same way. In a feature-based approach, features are subgraphs exploited for the purposes of drawing. We endeavour to depict not only the binary relation, but the high-level relationships between features. This thesis extensively explores a feature-based approach to graph vi sualization and demonstrates the viability of tools that aid in the visual ization of large graphs. Our contributions lie in presenting and evaluating novel techniques and algorithms for graph visualization. We implement five systems in order to empirically evaluate these techniques and algorithms, comparing them to previous approaches.

A graph consists of a set and a binary relation on that set. Each element of the set is a node of the graph, while each element of the binary relation is an edge of the graph that encodes a relationship between two nodes. Graph are pervasive in many areas of science, engineering, and the social sciences: servers on the Internet are connected, proteins interact in large biological systems, social networks encode the relationships between people, and functions call each other in a program. In these domains, the graphs can become very large, consisting of hundreds of thousands of nodes and millions of edges. Graph drawing approaches endeavour to place these nodes in two or three-dimensional space with the intention of fostering an understanding of the binary relation by a human being examining the image. However, many of these approaches to drawing do not exploit higher-level structures in the graph beyond the nodes and edges. Frequently, these structures can be exploited for drawing. As an example, consider a large computer network where nodes are servers and edges are connections between those servers. If a user would like understand how servers at UBC connect to the rest of the network, a drawing that accentuates the set of nodes representing those servers may be more helpful than an approach where all nodes are drawn in the same way. In a feature-based approach, features are subgraphs exploited for the purposes of drawing. We endeavour to depict not only the binary relation, but the high-level relationships between features. This thesis extensively explores a feature-based approach to graph vi sualization and demonstrates the viability of tools that aid in the visual ization of large graphs. Our contributions lie in presenting and evaluating novel techniques and algorithms for graph visualization. We implement five systems in order to empirically evaluate these techniques and algorithms, comparing them to previous approaches.

A graph consists of a set and a binary relation on that set. Each element of the set is a node of the graph, while each element of the binary relation is an edge of the graph that encodes a relationship between two nodes. Graph are pervasive in many areas of science, engineering, and the social sciences: servers on the Internet are connected, proteins interact in large biological systems, social networks encode the relationships between people, and functions call each other in a program. In these domains, the graphs can become very large, consisting of hundreds of thousands of nodes and millions of edges. Graph drawing approaches endeavour to place these nodes in two or three-dimensional space with the intention of fostering an understanding of the binary relation by a human being examining the image. However, many of these approaches to drawing do not exploit higher-level structures in the graph beyond the nodes and edges. Frequently, these structures can be exploited for drawing. As an example, consider a large computer network where nodes are servers and edges are connections between those servers. If a user would like understand how servers at UBC connect to the rest of the network, a drawing that accentuates the set of nodes representing those servers may be more helpful than an approach where all nodes are drawn in the same way. In a feature-based approach, features are subgraphs exploited for the purposes of drawing. We endeavour to depict not only the binary relation, but the high-level relationships between features. This thesis extensively explores a feature-based approach to graph vi sualization and demonstrates the viability of tools that aid in the visual ization of large graphs. Our contributions lie in presenting and evaluating novel techniques and algorithms for graph visualization. We implement five systems in order to empirically evaluate these techniques and algorithms, comparing them to previous approaches. / Science, Faculty of / Computer Science, Department of / Graduate

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The rail dynamics modeling package NUCARS has been used extensively to model freight cars. We have found that it can also be used effectively to model freight locomotives. This thesis discusses the development of a NUCARS model to represent a six-axle freight locomotive equipped with steerable trucks. This includes separating it into a set of individual bodies, representing the suspension components as inter-body connections, and validation of the computer model. This model is then used to conduct a study of the impact on tangent track stability and curving performance of varying suspension parameters. It is found that the presence of damping in the system improves hunting stability, while increasing wheel conicity is harmful to stability and varying the flexicoiling stiffness has little effect. In curving, the clearances between the axles and truck frame are very important. Limiting these clearances in the steerable truck causes it to curve similar to a conventional straight locomotive truck and increases both the track force ratios and angles of attack. Increasing the wheel conicity increases an axle's tendency to align with the track and improves the locomotive's curving performance. The lateral stiffness of the inter-axle links and inter-motor links has little effect on the curving of the locomotive. / Master of Science

Les robots mobiles à roues orientables gagnent de la mobilité en employant des roues conventionnelles entièrement orientables, comportant deux joints actifs, un pour la direction et un autre pour la conduite. En dépit d'avoir seulement un degré de mobilité (DOM) (défini ici comme degrés de liberté instantanément autorisés DOF), correspondant à la rotation autour du centre de rotation instantané (ICR), ces robots peuvent effectuer des trajectoires planaires complexes de $ 2D $. Ils sont moins chers et ont une capacité de charge plus élevée que les roues non conventionnelles (par exemple, Sweedish ou Omni-directional) et, en tant que telles, préférées aux applications industrielles. Cependant, ce type de structure de robot mobile présente des problèmes de contrôle textit {basic} difficiles de la coordination de la direction pour éviter les combats d'actionneur, en évitant les singularités cinématiques (ICR à l'axe de la direction) et les singularités de représentation (du modèle mathématique). En plus de résoudre les problèmes de contrôle textit {basic}, cette thèse attire également l'attention et présente des solutions aux problèmes de textit {niveau d'application}. Plus précisément, nous traitons deux problèmes: la première est la nécessité de reconfigurer "de manière discontinue" les articulations de direction, une fois que la discontinuité dans la trajectoire du robot se produit. Une telle situation - la discontinuité dans le mouvement du robot - est plus susceptible de se produire de nos jours, dans le domaine émergent de la collaboration homme-robot. Les robots mobiles qui fonctionnent à proximité des travailleurs humains en mouvement rapide rencontrent généralement une discontinuité dans la trajectoire calculée en ligne. Le second apparaît dans les applications nécessitant que l'angle de l'angle soit maintenu, certains objets ou fonctionnalités restent dans le champ de vision (p. Ex., Pour les tâches basées sur la vision) ou les changements de traduction. Ensuite, le point ICR est nécessaire pour déplacer de longues distances d'un extrême de l'espace de travail à l'autre, généralement en passant par le centre géométrique du robot, où la vitesse du robot est limitée. Dans ces scénarios d'application, les contrôleurs basés sur l'ICR à l'état de l'art conduiront à des comportements / résultats insatisfaisants. Dans cette thèse, nous résolvons les problèmes de niveau d'application susmentionnés; à savoir la discontinuité dans les commandes de vitesse du robot et une planification meilleure / efficace pour le contrôle du mouvement du point ICR tout en respectant les limites maximales de performance des articulations de direction et en évitant les singularités cinématiques et représentatives. Nos résultats ont été validés expérimentalement sur une base mobile industrielle. / Steerable wheeled mobile robots gain mobility by employing fully steerable conventional wheels, having two active joints, one for steering, and another for driving. Despite having only one degree of mobility (DOM) (defined here as the instantaneously accessible degrees of freedom DOF), corresponding to the rotation about the instantaneous center of rotation (ICR), such robots can perform complex $2D$ planar trajectories. They are cheaper and have higher load carrying capacity than non-conventional wheels (e.g., Sweedish or Omni-directional), and as such preferred for industrial applications. However, this type of mobile robot structure presents challenging textit{basic} control issues of steering coordination to avoid actuator fighting, avoiding kinematic (ICR at the steering joint axis) and representation (from the mathematical model) singularities. In addition to solving the textit{basic} control problems, this thesis also focuses attention and presents solutions to textit{application level} problems. Specifically we deal with two problems: the first is the necessity to "discontinuously" reconfigure the steer joints, once discontinuity in the robot trajectory occurs. Such situation - discontinuity in robot motion - is more likely to happen nowadays, in the emerging field of human-robot collaboration. Mobile robots working in the vicinity of fast moving human workers, will usually encounter discontinuity in the online computed trajectory. The second appears in applications requiring that some heading angle is to be maintained, some object or feature stays in the field of view (e.g., for vision-based tasks), or the translation verse changes. Then, the ICR point is required to move long distances from one extreme of the workspace to the other, usually passing by the robot geometric center, where the feasible robot velocity is limited. In these application scenarios, the state-of-art ICR based controllers will lead to unsatisfactory behavior/results. In this thesis, we solve the aforementioned application level problems; namely discontinuity in robot velocity commands, and better/efficient planning for ICR point motion control while respecting the maximum steer joint performance limits, and avoiding kinematic and representational singularities. Our findings has been validated experimentally on an industrial mobile base.

Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. We propose a performance criterion for a local descriptor based on the tradeoff between selectivity and invariance. In this paper, we evaluate several local descriptors with respect to selectivity and invariance. The descriptors that we evaluated are Gaussian derivatives up to the third order, gray image patches, and Laplacian-based descriptors with either three scales or one scale filters. We compare selectivity and invariance to several affine changes such as rotation, scale, brightness, and viewpoint. Comparisons have been made keeping the dimensionality of the descriptors roughly constant. The overall results indicate a good performance by the descriptor based on a set of oriented Gaussian filters. It is interesting that oriented receptive fields similar to the Gaussian derivatives as well as receptive fields similar to the Laplacian are found in primate visual cortex.

Thesis(M.S.)--Auburn University, 2006. / Abstract. Vita. Includes bibliographic references (p.47-50).

Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. We propose a performance criterion for a local descriptor based on the tradeoff between selectivity and invariance. In this paper, we evaluate several local descriptors with respect to selectivity and invariance. The descriptors that we evaluated are Gaussian derivatives up to the third order, gray image patches, and Laplacian-based descriptors with either three scales or one scale filters. We compare selectivity and invariance to several affine changes such as rotation, scale, brightness, and viewpoint. Comparisons have been made keeping the dimensionality of the descriptors roughly constant. The overall results indicate a good performance by the descriptor based on a set of oriented Gaussian filters. It is interesting that oriented receptive fields similar to the Gaussian derivatives as well as receptive fields similar to the Laplacian are found in primate visual cortex.