L'étude de dimensionnement d'un réseau cellulaire est une phase de conception qui doit permettre de déterminer les performances d'un système dans une configuration donnée. Elle inclut l'étude de couverture et l'analyse de trafic. De complexes simulations sont possibles pour connaître les paramètres de performances d'un réseau mais seules les études analytiques fournissent des résultats rapides. Par ailleurs, pour faire face à la demande de hauts débits, à la rareté du spectre fréquentiel et à l'impossibilité d'émettre à de plus fortes puissances, de nouvelles techniques de transmissions sont apparues. Nous sommes ainsi passés d'un système classique à une seule antenne à des systèmes à multiple antennes et même à des scénarios de coopération entre stations de base. Dans cette thèse, nous proposons des modèles analytiques pour l'étude des performances, notamment en termes de probabilités de coupure, de ces évolutions des réseaux cellulaires. Dans une première phase, nous considérons des systèmes multicellulaires à une antenne émettrice et une antenne réceptrice (SISO). Nous proposons deux méthodes d'étude de l'impact conjoint de l'affaiblissement de parcours, de l'effet de masque et des évanouissements rapides. Nous étudions, par la suite, un système à large bande utilisant le retournement temporel comme technique de transmission. Dans une deuxième phase, nous considérons des systèmes multicellulaires à antennes multiple à l'émission ou à la réception (MISO/MIMO) implémentant les schémas de diversité Alamouti et de combinaison par rapport maximal (MRC). Ensuite, nous considérons un système multicellulaire multi-utilisateurs à précodage de forçage à zéro (ZFBF).

MU-MIMO theory predicts manyfold capacity gains by leveraging many antennas (e.g. M >> 10) on wireless base stations to serve many users simultaneously through multi-user beamforming (MUBF). However, realizing such a large-scale design is nontrivial, and has yet to be achieved in the real world. We present the design, realization, and evaluation of Argos, the first reported large-scale base station that is capable of serving many (e.g., 10s of) terminals simultaneously through MUBF. Designed with extreme flexibility and scalability in mind, Argos exploits hierarchical and modular design principles, properly partitions baseband processing, and holistically considers real-time requirements of MUBF. To achieve unprecedented scalability, we devise a novel, completely distributed, beamforming technique, as well as an internal calibration procedure to enable implicit beamforming across large arrays. We implement a prototype with 64 antennas, and demonstrate that it can achieve up to 6.7 fold capacity gains while using a mere 1/64th the transmission power.

This study employs the data from real estate transactions provided by the Department of Land Administration. This study uses the Hedonic Price method and the Difference-in-Difference method to analyze the impact of indoor and outdoor properties on housing prices. In our study, the properties of floor space, stories, age, proximity to MRT stations, and proximity to elementary schools are important factors affecting the housing prices. The results estimated by Difference-in-Difference method show that the coefficient on homes within 500 meters distance of the MRT stations and the coefficient after MRT operating are both significantly positive on housing prices. Although the coefficient on the interaction term is positive, it is not statistically significant.

It has been known for almost two decades that the water proton NMR signal of diffusing water molecules in brain white matter undergoes a non-monoexponential decay with increasing diffusion gradient factor b. With the help of numerical simulations and analytical expressions, much effort has been directed to describing the signal decay and to extracting relevant biophysical features of the system under investigation. However, the physical basis of such nonmonoexponential behavior is still not properly understood. The primary difficulty in characterizing this phenomenon is the variation in behavior in the different directions of diffusion measurement. A combined framework that accounts for the diffusion process in all directions requires several parameters. Addition of many such parameters renders a model to be unwieldy and over-complicated, but over-simplifications can be shown to miss crucially relevant information in the data. In this thesis, I have attempted to handle this problem with simple measurements that span a wide range of parameter space. Compared to often-performed measurements that probe diffusion over a time-scale of 50-100 ms with relatively low diffusion weighting, the measurements here have been done for very short diffusion times of 2 ms and also very long diffusion times up to 2 s. The temperature dependence of the diffusion coefficients has also been extensively probed. To avoid problems related to gross tissue heterogeneity, diffusion-weighted MR imaging in vivo was performed with ultra-high resolution. These simple measurements allowed sequential assessment of many possible arguments that could have led to such non-monoexponential decay curves. Finally, it was concluded that the water in the glial processes was the major contributor to the non-exponential decay, giving rise to a \'slow\' component both along the axonal fibers and transverse to them.

This dissertation describes the development and implementation of advanced slice-accelerated (SMS) MRI methods for imaging blood perfusion and water diffusion in the human brain. Since its introduction in 1977, Echo-Planar Imaging (EPI) paved the way toward a detailed assessment of the structural and functional properties of the human brain. Currently, EPI is one of the most important MRI techniques for neuroscientific studies and clinical applications. Despite its high prevalence in modern medical imaging, EPI still suffers from sub-optimal time efficiency - especially when high isotropic resolutions are required to adequately resolve sophisticated structures as the human brain. The utilization of novel slice-acceleration methods can help to overcome issues related to low temporal efficiency of EPI acquisitions. The aim of the four studies outlining this thesis is to overcome current limitations of EPI by developing methods for slice-accelerated MRI. The first experimental work of this thesis describes the development of a slice-accelerated MRI sequence for dynamic susceptibility contrast imaging. This method for assessing blood perfusion is commonly employed for brain tumor classifications in clinical practice. Following up, the second project of this thesis aims to extend SMS imaging to diffusion MRI at 7 Tesla. Here, a specialized acquisition method was developed employing various methods to overcome problems related to increased energy deposition and strong image distortion. The increased energy depositions for slice-accelerated diffusion MRI are due to specific radiofrequency (RF) excitation pulses. High energy depositions can limit the acquisition speed of SMS imaging, if high slice-acceleration factors are employed. Therefore, the third project of this thesis aimed at developing a specialized RF pulse to reduce the amount of energy deposition. The increased temporal efficiency of SMS imaging can be employed to acquire higher amounts of imaging data for signal averaging and more stable model fits. This is especially true for diffusion MRI measurements, which suffer from intrinsically low signal-to-noise ratios. However, the typically acquired magnitude MRI data introduce a noise bias in diffusion images with low signal-to-noise ratio. Therefore, the last project of this thesis aimed to resolve the pressing issue of noise bias in diffusion MRI. This was achieved by transforming the diffusion magnitude data into a real-valued data representation without noise bias. In combination, the developed methods enable rapid MRI measurements with high temporal efficiency. The diminished noise bias widens the scope of applications of slice- accelerated MRI with high temporal efficiency by enabling true signal averaging and unbiased model fits. Slice-accelerated imaging for the assessment of water diffusion and blood perfusion represents a major step in the field of neuroimaging. It demonstrates that cur- rent limitations regarding temporal efficiency of EPI can be overcome by utilizing modern data acquisition and reconstruction strategies.

No description available.

Parkinson’s disease (PD) is a progressive neurodegenerative movement disorder characterized by a large number of motor and non-motor deficits, which significantly contribute to reduced quality of life. Despite the definition of the broad spectrum of clinical characteristics, mechanisms triggering illness, the nature of its progression and a character of therapeutic effects still remain unknown. The enormous advances in magnetic resonance imaging (MRI) in the last decades have significantly affected the research attempts to uncover the functional and structural abnormalities in PD and have helped to develop and monitor various treatment strategies, of which dopamine replacement strategies, mainly in form of levodopa, has been the gold standard since the late seventies and eighties. Motor, task-related functional MRI (fMRI) has been extensively used to assess the pathological state of the motor circuitry in PD. Several studies employed motor paradigms and fMRI to review the functional brain responses of participants to levodopa treatment. Interestingly, they provided conflicting results. Wide spectrum of symptoms, variability and asymmetry of the disease presentation, several treatment approaches and their divergent outcomes make PD enormously heterogeneous. In this work we hypothesized that not considering the disease heterogeneity might have been an adequate cause for the discrepant results in aforementioned studies. We show that not accounting for the disease variability might indeed compromise the results and invalidate the consequent interpretations. Accordingly, we propose and formalize a statistical approach to account for the intra and inter subject variability. This might help to minimize this bias in future motor fMRI studies revealing the functional brain dysfunction and contribute to the understanding of still unknown pathophysiological mechanisms underlying PD.

Switchgrass (Panicum virgatum), a perennial C4 grass species, has the capacity to not only improve the quality of the soil in which it grows but also promote soil carbon storage to offset rising atmospheric CO2. This research investigated soil organic carbon (SOC) dynamics beneath switchgrass using natural abundance 13C and soil carbon fractionation following the establishment of this crop in a native and predominantly C3 plant region in southeastern Ontario. I investigated SOC dynamics by sampling adjacent commercial switchgrass fields and appropriate paired control fields at sites where the time since switchgrass establishment varied from 4-11 years. SOC and natural 13C abundance were measured in paired fields to assess management-induced changes in the quantity, source, and turnover time of soil carbon. To better elucidate carbon cycling dynamics over a relatively short time since switchgrass establishment, multiple soil fractionation techniques were applied to better understand carbon dynamics of soil organic matter with various mean residence times. Establishment of switchgrass results in marginal increases in SOC, primarily at sites where intensive soil management (i.e. tillage) practices preceded switchgrass establishment. Changes were observed in some of the more labile SOC pools, as well as in the δ13C values of the bulk soil and soil carbon fractions, indicating that growing switchgrass was causing the incorporation of switchgrass-derived carbon into the soil. Even resistant SOC pools, with turnover times of over 100 years, incorporated significant quantities of switchgrass carbon in 11 years. Annual increases in SOC, however, were less than values reported elsewhere. The potential for soil carbon storage exists, likely due to longer mean residence times of the carbon in soils beneath switchgrass compared with other cultivation systems. Changes in SOC following switchgrass establishment related strongly to the amount of root biomass, time since establishment and prior soil management practices. The decomposition rates derived in this research should be integrated into soil carbon modeling applications intended to support the emergence of switchgrass in southeastern Ontario. The results of my research can advance soil carbon models and be used to make regional assessment of the potential impact of growing switchgrass for bioenergy in southeastern Ontario. / Thesis (Master, Geography) -- Queen's University, 2012-01-30 13:56:06.269

Research in the last decades has shown that individuals with high degrees in the personality trait of alexithymia not only have difficulties in identifying and recognizing own feelings, but also show deficits in reading emotions from facial expressions of other people. Therefore, the current dissertation investigates the neural correlates of recognizing emotional facial expressions as a function of alexithymia. Initially, a theoretical introduction is given and existing findings from behavioral as well as structural and functional neuroimaging research are presented. Open questions are identified and addressed in one structural and two functional magnetic resonance imaging studies that were compiled into three original research articles. Study 1 examined the gray matter profile of high and low alexithymic individuals in selected brain regions relevant for processing emotional faces. In Study 2, functional neuroimaging was used to investigate the neural correlates of high alexithymic individuals\' difficulties in labeling briefly presented (≤ 100 ms) facial expressions of emotion. Study 3 investigated neural activations as a function of alexithymia during the labeling of emotional facial expressions when these are presented with little temporal constraints (≥ 1 s). The results of these studies are summarized and integrated with the existing literature. Finally, open issues are discussed and ideas for further research are outlined.

Das zentrale Thema dieser Dissertation ist die Anwendung illustrativer Methoden auf zwei bisher ungelöste Probleme der Strömungsvisualisierung. Das Ziel der Strömungsvisualisierung ist die Bereitstellung von Software, die Experten beim Auswerten ihrer Strömungsdaten und damit beim Erkenntnisgewinn unterstützt. Bei der illustrativen Visualisierung handelt es sich um einen Zweig der Visualisierung, der sich an der künstlerischen Arbeit von Illustratoren orientiert. Letztere sind darauf spezialisiert komplizierte Zusammenhänge verständlich und ansprechend zu vermitteln. Die angewendeten Techniken werden in der illustrativen Visualisierung auf reale Daten übertragen, um die Effektivität der Darstellung zu erhöhen. Das erste Problem, das im Rahmen dieser Dissertation bearbeitet wurde, ist die eingeschränkte Verständlichkeit von komplexen Stromflächen. Selbstverdeckungen oder Aufrollungen behindern die Form- und Strömungswahrnehmung und machen diese Flächen gerade in interessanten Strömungssituationen wenig nützlich. Auf Basis von handgezeichneten Strömungsdarstellungen haben wir ein Flächenrendering entwickelt, das Silhouetten, nicht-photorealistische Beleuchtung und illustrative Stromlinien verwendet. Interaktive Flächenschnitte erlauben die Exploration der Flächen und der Strömungen, die sie repräsentieren. Angewendet auf verschiedene Stromflächen ließ sich zeigen, dass die Methoden die Verständlichkeit erhöhen, v.a. in Bereichen komplexer Strömung mit Aufwicklungen oder Singularitäten. Das zweite Problem ist die Strömungsanalyse des Blutes aus 4D PC-MRI-Daten. An diese relativ neue Datenmodalität werden hohe Erwartungen für die Erforschung und Behandlung kardiovaskulärer Krankheiten geknüpft, da sie erstmals ein dreidimensionales, zeitlich aufgelöstes Abbild der Hämodynamik liefert. Bisher werden 4D PC-MRI-Daten meist mit Werkzeugen der klassischen Strömungsvisualisierung verarbeitet. Diese werden den besonderen Ansprüchen der medizinischen Anwender jedoch nicht gerecht, die in kurzer Zeit eine übersichtliche Darstellung der relevanten Strömungsaspekte erhalten möchten. Wir haben ein Werkzeug zur visuellen Analyse der Blutströmung entwickelt, welches eine einfache Detektion von markanten Strömungsmustern erlaubt, wie z.B. Jets, Wirbel oder Bereiche mit hoher Blutverweildauer. Die Grundidee ist hierbei aus vorberechneten Integrallinien mit Hilfe speziell definierter Linienprädikate die relevanten, d.h. am gefragten Strömungsmuster, beteiligten Linien ausgewählt werden. Um eine intuitive Darstellung der Resultate zu erreichen, haben wir uns von Blutflußillustrationen inspirieren lassen und präsentieren eine abstrakte Linienbündel- und Wirbeldarstellung. Die Linienprädikatmethode sowie die abstrakte Darstellung der Strömungsmuster wurden an 4D PC-MRI-Daten von gesunden und pathologischen Aorten- und Herzdaten erfolgreich getestet. Auch die Evaluierung durch Experten zeigt die Nützlichkeit der Methode und ihr Potential für den Einsatz in der Forschung und der Klinik. / This thesis’ central theme is the use of illustrative methods to solve flow visualization problems. The goal of flow visualization is to provide users with software tools supporting them analyzing and extracting knowledge from their fluid dynamics data. This fluid dynamics data is produced in large amounts by simulations or measurements to answer diverse questions in application fields like engineering or medicine. This thesis deals with two unsolved problems in flow visualization and tackles them with methods of illustrative visualization. The latter is a subbranch of visualization whose methods are inspired by the art work of professional illustrators. They are specialized in the comprehensible and esthetic representation of complex knowledge. With illustrative visualization, their techniques are applied to real data to enhance their representation. The first problem dealt with in this thesis is the limited shape and flow perception of complex stream surfaces. Self-occlusion and wrap-ups hinder their effective use in the most interesting flow situations. On the basis of hand-drawn flow illustrations, a surface rendering method was designed that uses silhouettes, non-photorealistic shading, and illustrative surface stream lines. Additionally, geometrical and flow-based surface cuts allow the user an interactive exploration of the surface and the flow it represents. By applying this illustrative technique to various stream surfaces and collecting expert feedback, we could show that the comprehensibility of the stream surfaces was enhanced – especially in complex areas with surface wrap-ups and singularities. The second problem tackled in this thesis is the analysis of blood flow from 4D PC-MRI data. From this rather young data modality, medical experts expect many advances in the research of cardiovascular diseases because it delivers a three-dimensional and time-resolved image of the hemodynamics. However, 4D PC-MRI data are mainly processed with standard flow visualizaton tools, which do not fulfill the requirements of medical users. They need a quick and easy-to-understand display of the relevant blood flow aspects. We developed a tool for the visual analysis of blood flow that allows a fast detection of distinctive flow patterns, such as high-velocity jets, vortices, or areas with high residence times. The basic idea is to precalculate integral lines and use specifically designed line predicates to select and display only lines involved in the pattern of interest. Traditional blood flow illustrations inspired us to an abstract and comprehensible depiction of the resulting line bundles and vortices. The line predicate method and the illustrative flow pattern representation were successfully tested with 4D PC-MRI data of healthy and pathological aortae and hearts. Also, the feedback of several medical experts confirmed the usefulness of our methods and their capabilities for a future application in the clinical research and routine.