Master of Landscape Architecture / Department of Landscape Architecture/Regional and Community Planning / Blake M. Belanger / The main streets of the Rocky Mountain West are the social, economic, and cultural centers of their respective communities. Often, these main streets may deteriorate or become abandoned as a result of edge shopping malls and strip style economic development. Thus, a downtown or main street redevelopment effort by the community can help to ensure these economic centers remain. Yet, too often, the redevelopment efforts are oversimplified and fail to integrate the most current street development principles and design initiatives that can benefit not only the community but also the surrounding environment. I n the modern American city, almost half of all daily trips are less than three miles and a third are under one mile. (McCann 2010) “These are distances easily traversed by foot or bicycle, yet 65 percent of trips under one mile are made by automobile.” (McCann 2010) This mobility trend has led to the foundation of programs and organizations that try to promote non-motorized travel. Although these initiatives respond to the human/physical environment, they are far from comprehensive. Today, an integration of smart ecological ideals is essential. How can the revitalization efforts of Rocky Mountain communities be guided to ensure they consider not only the built environment; but also the natural environment? The face of the future main street will be multi-modal and ecologically responsible. Yet, there is presently no clear method of combining the two. A union of the multi-modal principles behind Complete Streets and the ecologically responsible ideals green infrastructure can provide a framework for a new and more inclusive redevelopment approach. The merging of modern ecological and street design principles can lead to a comprehensive Main Street redevelopment program and therefore successfully guide the revitalization efforts of small Rocky Mountain communities in a way that is responsive to future development needs as well as the cultural and ecological aspects of the region. Main Street Evolved will provide a set of tools to guide Colorado Rocky Mountain Main Street redevelopment efforts by providing strategies and implementation guidelines that focus on balancing multi-modal ideals and ecological stormwater management techniques within a small-town mountain context.

This thesis presents novel solutions for two fundamental problems associated with autonomous road driving. The first is accurate and persistent localisation and the second is automatic extrinsic sensor calibration. We start by describing a stereo Visual Odometry (VO) system, which forms the basis of later chapters. This sparse approach to ego-motion estimation leverages the efficacy and speed of the BRIEF descriptor to measure frame-to-frame correspondences and infer subsequent motion. The system is able to output locally metric trajectory estimates as demonstrated on many kilometres of data. We then present a robust vision only localisation system based on a two-stage approach. Firstly we gather a representative survey in ideal weather and lighting conditions. We then leverage locally accurate VO trajectories to synthesise a high resolution orthographic image strip of the road surface. This road image provides a highly descriptive and stable template against which to match subsequent traversals. During the second phase, localisation, we use the VO to provide high frequency pose updates, but correct for the drift inherent in all locally derived pose estimates with low frequency updates from a dense image matching technique. Here a live image stream is registered against synthesised views of the road image generated form the survey. We use an information theoretic measure, Mutual Information, to determine the alignment of live images and synthesised views. Using this measure we are able to successfully localise subsequent traversals of surveyed routes under even the most intense lighting changes expected in outdoor applications. We demonstrate our system localising in multiple environments with accuracy commensurate to that of an Inertial Navigation System. Finally we present a technique for automatically determining the extrinsic calibration between a camera and Light Detection And Ranging (LIDAR) sensor in natural scenes. Rather than requiring a stationary platform as with prior art, we actually exploit platform motion allowing us to aggregate data and adopt a retrospective approach to calibration. Coupled with accurate timing this retrospective approach allows for sensors with non-overlapping fields of view to be calibrated as long as at some point the observed workspaces overlap. We then show how we can improve the accuracy of our calibration estimates by treating each single shot estimate as a noisy measurement and fusing them together using a recursive Bayes filter. We evaluate the calibration algorithm in multiple environments and demonstrate millimetre precision in translation and deci-degrees in rotation.

<p>Advancements in retinal imaging technologies have drastically improved the quality of eye care in the past couple decades. Scanning laser ophthalmoscopy (SLO) and optical coherence tomography (OCT) are two examples of critical imaging modalities for the diagnosis of retinal pathologies. However current-generation SLO and OCT systems have limitations in diagnostic capability due to the following factors: the use of bulky tabletop systems, monochromatic imaging, and resolution degradation due to ocular aberrations and diffraction. </p><p>Bulky tabletop SLO and OCT systems are incapable of imaging patients that are supine, under anesthesia, or otherwise unable to maintain the required posture and fixation. Monochromatic SLO and OCT imaging prevents the identification of various color-specific diagnostic markers visible with color fundus photography like those of neovascular age-related macular degeneration. Resolution degradation due to ocular aberrations and diffraction has prevented the imaging of photoreceptors close to the fovea without the use of adaptive optics (AO), which require bulky and expensive components that limit the potential for widespread clinical use. </p><p>In this dissertation, techniques for extending the diagnostic capability of SLO and OCT systems are developed. These techniques include design strategies for miniaturizing and combining SLO and OCT to permit multi-modal, lightweight handheld probes to extend high quality retinal imaging to pediatric eye care. In addition, a method for extending true color retinal imaging to SLO to enable high-contrast, depth-resolved, high-fidelity color fundus imaging is demonstrated using a supercontinuum light source. Finally, the development and combination of SLO with a super-resolution confocal microscopy technique known as optical photon reassignment (OPRA) is demonstrated to enable high-resolution imaging of retinal photoreceptors without the use of adaptive optics.</p> / Dissertation

Le recalage des images du cerveau vise à réduire la variabilité anatomique entre les differentes sujets, et à créer un espace commun pour l'analyse de groupe. Les approches multi-modales essaient de minimiser les variations de forme du cortex et des structures internes telles que des faisceaux de fibres nerveuses. Ces approches nécessitent une identification préalable de ces structures, ce qui s'avère une tâche difficile en l'absence d'un atlas complet de référence. Nous proposons une extension de l'algorithme de recalage difféomorphe des Démons pour recaler conjointement des images et des faisceaux de fibres. Dans cette thèse, nous analysons différentes représentations des faisceaux de fibres comme une séquence de points, un nuage de points, les courants et les mesures. Différentes distances sont analysées et étudiées dans l'algorithme de recalage. Pour simplifier la représentation de la matière blanche nous utilisons et étendons les algorithmes de classification existants. En étendant le recalage d'images afin d'ajouter des descripteurs de la géométrie des fibres nerveuses, nous espérons améliorer les futures analyses concernant les matières grise et blanche. Nous avons démontré l'efficacité de notre algorithme en recalant conjointement des images anatomiques pondérées en T1 et des faisceaux de fibres. Nous avons comparé nos résultats à des approches concurrentes, l'une multimodale s'appuyant sur l'anisotropie fractionnaire et la pondération T1, l'autre sur les tenseurs de diffusion, et obtenu de meilleures performances à l'aide de notre algorithme. Enfin, nous mettons en évidence sur des études de groupe en IRMf que notre méthodologie et notre implémentation apportent un gain en sensibilité de détection des activations cérébrales. / Brain image registration aims at reducing anatomical variability across subjects to create a common space for group analysis. Multi-modal approaches intend to minimize cortex shape variations along with internal structures, such as fiber bundles. These approaches require prior identification of the structures, which remains a challenging task in the absence of a complete reference atlas. We propose an extension of the Diffeomorphic Demons image registration to jointly register images and fiber bundles. In this thesis we analyze differents representations of the fiber bundles such as ordered points, clouds of points, Currents and Measures. Different distances are analyzed and implemented into the registration algorithm. To simplify white matter representation we also analyze, use and extend existing clustering algorithms. By extending the image registration to include geometric fiber bundles descriptors we hope to improve future analyses regarding both, grey and white matter. We demonstrate the efficacy of our algorithm by registering simultaneously T1 images and fiber bundles and compare results with a multi-modal T1+Fractional Anisotropy (FA) and a tensor-based registration algorithms and obtain superior performance with our approach. We provide preliminary evidence that our implementation improves the sensitivity of activation detection in fMRI group studies.

This dissertation describes a new methodology for multi-modal (2-D + 3-D) face modeling and recognition. There are advantages in using each modality for face recognition. For example, the problems of pose variation and illumination condition, which cannot be resolved easily by using the 2-D data, can be handled by using the 3-D data. However, texture, which is provided by 2-D data, is an important cue that cannot be ignored. Therefore, we use both the 2-D and 3-D modalities for face recognition and fuse the results of face recognition by each modality to boost the overall performance of the system. In this dissertation, we consider two different cases for multi-modal face modeling and recognition. In the first case, the 2-D and 3-D data are registered. In this case we develop a unified graph model called Attributed Relational Graph (ARG) for face modeling and recognition. Based on the ARG model, the 2-D and 3-D data are included in a single model. The developed ARG model consists of nodes, edges, and mutual relations. The nodes of the graph correspond to the landmark points that are extracted by an improved Active Shape Model (ASM) technique. In order to extract the facial landmarks robustly, we improve the Active Shape Model technique by using the color information. Then, at each node of the graph, we calculate the response of a set of log-Gabor filters applied to the facial image texture and shape information (depth values); these features are used to model the local structure of the face at each node of the graph. The edges of the graph are defined based on Delaunay triangulation and a set of mutual relations between the sides of the triangles are defined. The mutual relations boost the final performance of the system. The results of face matching using the 2-D and 3-D attributes and the mutual relations are fused at the score level. In the second case, the 2-D and 3-D data are not registered. This lack of registration could be due to different reasons such as time lapse between the data acquisitions. Therefore, the 2-D and 3-D modalities are modeled independently. For the 3-D modality, we developed a fully automated system for 3-D face modeling and recognition based on ridge images. The problem with shape matching approaches such as Iterative Closest Points (ICP) or Hausdorff distance is the computational complexity. We model the face by 3-D binary ridge images and use them for matching. In order to match the ridge points (either using the ICP or the Hausdorff distance), we extract three facial landmark points: namely, the two inner corners of the eyes and the tip of the nose, on the face surface using the Gaussian curvature. These three points are used for initial alignment of the constructed ridge images. As a result of using ridge points, which are just a fraction of the total points on the surface of the face, the computational complexity of the matching is reduced by two orders of magnitude. For the 2-D modality, we model the face using an Attributed Relational Graph. The results of the 2-D and 3-D matching are fused at the score level. There are various techniques to fuse the 2-D and 3-D modalities. In this dissertation, we fuse the matching results at the score level to enhance the overall performance of our face recognition system. We compare the Dempster-Shafer theory of evidence and the weighted sum rule for fusion. We evaluate the performance of the above techniques for multi-modal face recognition on various databases such as Gavab range database, FRGC (Face Recognition Grand Challenge) V2.0, and the University of Miami face database.

Research in the areas of target detection, tracking, and geo-location is most important for enabling an unmanned aerial vehicle (UAV) platform to autonomously execute a mission or task without the need for a pilot or operator. Small-class UAVs and video camera sensors complemented with "soft sensors" realized only in software as a combination of a priori knowledge and sensor measurements are called upon to replace the cumbersome precision sensors on-board a large class UAV. The objective of this research is to develop a geo-location solution for use on-board multiple UAVs with mounted video camera sensors only to accurately geo-locate and track a target. This research introduces an estimation solution that combines the power of the particle filter with the utility of the video sensor as a general solution for passive target geo-location on-board multiple UAVs. The particle filter is taken advantage of, with its ability to use all of the available information about the system model, system uncertainty, and the sensor uncertainty to approximate the statistical likelihood of the target state. The geo-location particle filter is tested online and in real-time in a simulation environment involving multiple UAVs with video cameras and a maneuvering ground vehicle as a target. Simulation results show the geo-location particle filter estimates the target location with a high accuracy, the addition of UAVs or particles to the system improves the location estimation accuracy with minimal addition of processing time, and UAV control and trajectory generation algorithms restrict each UAV to a desired range to minimize error.

Wind waves are highly complex, random phenomena. One way to describe the irregular nature of the sea surface is the use of wave energy spectrum. Spectral information for wind waves in the Black Sea is extremely limited. Knowledge on spectral characteristics of wind waves would contribute to scientific, engineering and operational coastal and marine activities in the Black Sea. The aim of the present thesis is to investigate characteristics of wind wave spectra for the Eastern Black Sea. This would allow detailed understanding of the nature of the waves occurring in this enclosed basin. Long-term wave measurements obtained by directional buoys deployed offshore at Sinop, Hopa and Gelendzhik were utilized as the three sets of wave data. Records were analyzed to identify them as uni-modal or multi-modal spectra, and occurrences of spectral peaks were computed. Single peaked spectra were studied as belonging to fully arisen or developing sea states. Model parameters of JONSWAP and PM spectra were estimated for the observed spectra by using a least square error method. The records of developing seas were further analyzed to select the ones belonging to stable wind conditions. Fetch dependencies of non-dimensional spectral variables, mean parameters of JONSWAP model spectrum and the envelop of dimensionless spectra were investigated for this data sub-set.

The purpose of my project is to determine how a multimodal/intermedial text can be used when teaching in upper secondary school. Can using a text that to some point is current in the pupils’ lives lift the interest for the specific subject? I opted to pick up Gunther Kress’ research, Diana Laurillard’s book and Christina Olin-Scheller’s work on the subject. I have used several hours of lesson planning and the lesson itself with subsequent work consisting, among other things, of three qualitative interviews to achieve my purpose. Based on a qualitative approach, I discuss the results, which show that it is in fact very uplifting. It is possible to work with multimodal/intermedial/intertextual texts, in many ways. / Syftet med denna uppsats är att undersöka hur en multimodal/intermedial text kan användas i undervisningen på gymnasienivå. Detta skall ske genom att utgå från elevernas perspektiv och referensramar, söka rätt på en aktuell text som finns i elevernas vardag och se om det blir intressant för eleverna att arbeta med en sådan text. Jag har valt att arbeta med Gunther Kress forskning, Diana Laurillards bok om ämnet och även Christina Olin-Schellers avhandling om ämnet, samt därutöver relevant och nödvändigt material för att vetenskapligt förankra begrepp och synpunkter.                       Jag har använt mig av en lektionsplanering, en utförd lektion samt tre kvalitativa intervjuer i efterarbetet av lektionen för att uppnå mitt syfte. Lektionen utspelade sig våren 2012 på en svensk gymnasieskola. Utifrån ett kvalitativt förhållningssätt diskuterar jag resultatet, vilket visar en mycket positiv respons på att hämta upp en multimodal/intermedial aktuell text från elevernas vardagsmiljö, och arbeta med denna i undervisningen.

Today the modern power system is more dynamic and its operation is a subject to a number of constraints that are reflected in various management and planning tools used by system operators. In the case of hourly generation planning, Economic Dispatch (ED) allocates the outputs of all committed generating units, which are previously identified by the solution of the Unit Commitment (UC) problem. Thus, the accurate solutions of the ED and UC problems are essential in order to operate the power system in an economic and efficient manner. A number of computation techniques have progressively been proposed to solve these critical issues. One of them is a Particle Swarm Optimisation (PSO), which belongs to the evolutionary computation techniques, and it has attracted a great attention of the research community since it has been found to be extremely effective in solving a wide range of engineering problems. The attractive characteristics of PSO include: ease of implementation, fast convergence compared with the traditional evolutionary computation techniques and stable convergence characteristic. Although the PSO algorithms can converge very quickly towards the optimal solutions for many optimisation problems, it has been observed that in problems with a large number of suboptimal areas (i.e. multi-modal problems), PSO could get trapped in those local minima, including ED and UC problems. Aiming at enhancing the diversity of the traditional PSO algorithms, this thesis proposes a method of combining the PSO algorithms with a real-valued natural mutation (RVM) operator to enhance the global search capability and investigate the performance of the proposed algorithm compared with the standard PSO algorithms and other algorithms. Prior to applying to ED and UC problems, the proposed method is tested with some selected mathematical functions where the results show that it can avoid being trapped in local minima. The proposed methodology is then applied to ED and UC problems, and the obtained results show that it can provide solutions with good accuracy and stable convergence characteristic with simple implementation and satisfactory calculation time. Furthermore, the sensitivity analysis of PSO parameters has been studied so as to investigate the response of the proposed method to the parameter variations, especially in both ED and UC problems. The outcome of this research shows that the proposed method succeeds in dealing with the PSO' s drawbacks and also shows the superiority over the traditional PSO algorithms and other methods in terms of high quality solutions, stable convergence characteristic, and robustness.

L’utilisation des réseaux de transport est conditionnée par l’efficacité et la simplicité de leur utilisation. En réponse à une mobilité exacerbée, volontaire ou subie, l’offre de transport se développe et motive tout à la fois, en un cycle continu, des déplacements encore plus exigeants. De manière complémentaire, la mobilité est bousculée par l’arrivée de nouvelles modalités de transport pouvant faire émerger, comme dans le cadre du covoiturage, des acteurs ou des pratiques jusqu’alors inexistants. Si la technologie permet de suivre cette évolution dans les services d’information aux voyageurs, il reste toujours à satisfaire des attentes déterminées par des usages en constante évolution. C’est de ce point de vue que l’obtention de chemins multiples pour relier une origine à une destination est un facteur qui n’est plus à négliger, surtout dans des réseaux de transport denses et comportant de nombreux modes et lignes de transport. Une liberté dans le choix laissé à l’utilisateur du réseau réduit les sentiments d’exclusion, d’incompréhension ou d’anxiété qui peuvent survenir face à une application logicielle ou sur internet et qui effectuent des choix arbitraires de façon autoritaire. De plus, cela permet de vérifier la qualité de l’offre de transport, car plus il existe de moyens différents pour effectuer un trajet dans un intervalle de temps donné, meilleur est le service. Cette thèse s’intéresse au calcul de telles alternatives par le biais de l’énumération par coût croissant des chemins entre deux points, puis par le filtrage de ceux-ci suivant des critères, supposés quelconques et laissés à l’appréciation des professionnels de transport qui peuvent ainsi faire varier les angles d’analyses de leurs offres.Par ailleurs, la synchronisation de trajets de plusieurs utilisateurs, en vue d’usages sociaux ou de déplacements mutualisés, est étudiée dans ce manuscrit sous l’angle du covoiturage. En ne considérant que deux usagers, l’objectif est de minimiser le temps de trajet global des participants sous la contrainte qu’ils partagent une partie de leur chemin entre un point de rencontre et un point de séparation qu’il faut alors déterminer. Sont également étudiées les variantes associées au changement des conditions de transport de chacun des participants comme l’établissement d’une origine ou d’une destination commune parallèlement à des contraintes sur les heures de départ ou d’arrivée des usagers. Enfin, puisque la voiture est très souvent pénalisée par la prise en charge d’un piéton, il convient d’étudier comment ce détour peut être contraint et les impacts sur les gains que cette limitation engendre.Cette thèse a été réalisée dans un contexte CIFRE pour la société MobiGIS. Lestravaux qui s’y rapportent ont fait l’objet de réalisations pratiques tant pour fournirdes solutions de mobilité dans le cadre des activités de l’entreprise que pour évaluerexpérimentalement les performances des algorithmes proposés pour les résoudre. / Efficiency and simplicity are two conditions upon which the use of a transportation system is relevant. May it be intentional or imposed, an increasing mobility triggers the need to enhance the transportation offer. In turn, such a response encourages an even more demanding mobility in a constantly adapting cycle. In parallel, new and forthcoming means of transportation emerge from time to time with unknown practices and renewed actors : exactly like what carpooling is stirring at the moment. Passenger information systems can technically deal with such evolutions thanks to improved technologies but they still struggle to keep up with constantly changing usage expectations.From this perspective the computation of several paths from an origin to a destination becomes increasingly relevant. This issue is even more crucial in dense transportation networks in which many modes and lines of transportation are combined. Indeed, giving some traveling choices to the end user reduces the feeling of exclusion, anxiety and the lack of understanding which may arise when facing arbitrary decisions dictated by a software or an Internet application. It is also helpful to estimate the quality of the transportation offer since the more paths exist to go from point A to point B within a fixed time window, the better the service is. This thesis focuses on the computation of such alternatives by the gradually increasing enumeration of paths between two points. Given this input, the pruning necessary to obtain such a diverse selection is assumed not to be known in advance. It is left up to transportation professionals who may choose a fitted solution based on their specific knowledge and objectives.Another subject studied in this thesis concerns the itinerary synchronization of several users for various social uses such as shared travels. It is here seen from the perspective of carpooling. Considering only two users, the problem is to minimize the traveling cost of the users under the constraint that they must share some part of their respective trips with one another. Solving this problem is equivalent to finding a pick up point and a drop off location between which both paths overlap. Multiple corner cases concerning the transportation conditions of each user as well as the special cases of shared origins or destinations are studied. The constraints on the arrival and/or departure times may also vary. Last but not least and since the driver is often penalized when giving up a lift, the restriction to a maximal detour the driver accepts, compared to his shortest path, is analyzed with respect to the benefits such a limitation generates.This thesis was funded by the MobiGIS company under the CIFRE (Industrial Agreement of Training through Research) researching context. The related work consisted in the practical implementation of mobility solutions within the framework of the company as well as the experimental performances evaluation of the algorithms proposed to solve them.