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A Spatially-filtered Finite-difference Time-domain Method with Controllable Stability Beyond the Courant LimitChang, Chun 19 July 2012 (has links)
This thesis introduces spatial filtering, which is a technique to extend the time step size beyond the conventional stability limit for the Finite-Difference Time-Domain (FDTD) method, at the expense of transforming field nodes between the spatial domain and the discrete spatial-frequency domain and removing undesired spatial-frequency components at every FDTD update cycle. The spatially-filtered FDTD method is demonstrated to be almost as accurate as and more efficient than the conventional FDTD method via theories and numerical examples. Then, this thesis combines spatial filtering and an existing subgridding scheme to form the spatially-filtered subgridding scheme. The spatially-filtered subgridding scheme is more efficient than existing subgridding schemes because the former allows the time step size used in the dense mesh to be larger than the dense mesh CFL limit. However, trade-offs between accuracy and efficiency are required in complicated structures.
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A Spatially-filtered Finite-difference Time-domain Method with Controllable Stability Beyond the Courant LimitChang, Chun 19 July 2012 (has links)
This thesis introduces spatial filtering, which is a technique to extend the time step size beyond the conventional stability limit for the Finite-Difference Time-Domain (FDTD) method, at the expense of transforming field nodes between the spatial domain and the discrete spatial-frequency domain and removing undesired spatial-frequency components at every FDTD update cycle. The spatially-filtered FDTD method is demonstrated to be almost as accurate as and more efficient than the conventional FDTD method via theories and numerical examples. Then, this thesis combines spatial filtering and an existing subgridding scheme to form the spatially-filtered subgridding scheme. The spatially-filtered subgridding scheme is more efficient than existing subgridding schemes because the former allows the time step size used in the dense mesh to be larger than the dense mesh CFL limit. However, trade-offs between accuracy and efficiency are required in complicated structures.
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Neoclassical theory versus new economic geography. Competing explanations of cross-regional variation in economic developmentFingleton, Bernard, Fischer, Manfred M. 11 1900 (has links) (PDF)
This paper uses data for 255 NUTS-2 European regions over the period 1995-2003
to test the relative explanatory performance of two important rival theories seeking to explain
variations in the level of economic development across regions, namely the neoclassical
model originating from the work of Solow (1956) and the so-called Wage Equation, which is
one of a set of simultaneous equations consistent with the short-run equilibrium of new
economic geography (NEG) theory, as described by Fujita, Krugman and Venables (1999).
The rivals are non-nested, so that testing is accomplished both by fitting the reduced form
models individually and by simply combining the two rivals to create a composite model in an
attempt to identify the dominant theory. We use different estimators for the resulting panel
data model to account variously for interregional heterogeneity, endogeneity, and temporal
and spatial dependence, including maximum likelihood with and without fixed effects, two
stage least squares and feasible generalised spatial two stage least squares plus GMM; also
most of these models embody a spatial autoregressive error process. These show that the
estimated NEG model parameters correspond to theoretical expectation, whereas the
parameter estimates derived from the neoclassical model reduced form are sometimes
insignificant or take on counterintuitive signs. This casts doubt on the appropriateness of
neoclassical theory as a basis for explaining cross-regional variation in economic
development in Europe, whereas NEG theory seems to hold in the face of competition from
its rival. (authors' abstract)
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PUFFER-JACKET-SOFT-SQUAD, PURE SCULPTURE!Ewertson, Sara-Lovise January 2019 (has links)
This degree project starts in the interest for fashion spaces. With this project I want to challenge the way we can experience fashion. I want to push forward the concepts; showroom/ collection. The body is always important and the starting point in my projects. The body is essential both in the sketching and in the final experience. More specifically, In this degree project I am investigating how body, furniture and puffer jacket can relate to each other. How a puffer jacket collection can be perceived spatially and what will it be then.
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Stellar populations in the Green Pea galaxy J1457+2232 : Study of possible age gradients by using highly resolved HST broad band imaging of the Green Peagalaxy SDSS-J145735.13+223201.8 at redshift 0.15.Malmgren, Jan January 2019 (has links)
Abstract In this report I present a study of possible age gradients in the Green Pea galaxy J145735.13+223201.8 to be able to conclude if there is an extended star forming history in such a galaxy. Data are coming from two different sources, highly resolved images in four different wavelengths of stars in the galaxy, and of nebular gas in a narrow band Ha Balmer line filter, from the Hubble Space Telescope (HST), as well as spectral line information from the Sloan Digital Sky Survey (SDSS). I compare the observations with stellar population models from two different libraries, Yggdrasil and Starburst99. Due to the highly resolved images from HST this is one of the first studies of spatially resolved stellar populations in a Green Pea galaxy. With the help from these spatially resolved images it was possible to study star clumps independently from each other. This would not be possible when using only data from SDSS. In this way it was possible to conclude an age difference between the centre of the galaxy and its outskirts. I found that the galaxy has an age gradient at a confidence level greater than 95%.
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Spatially varying defocus blur estimation and applications / Estimação de borramento por desfoco especialmente variante e aplicaçõesKaraali, Ali January 2017 (has links)
Esta tese apresenta dois métodos diferentes de estimativa de desfocagem usando uma única imagem. Ambos os métodos assumem uma função de espalhamento de ponto (Point Spread Function - PSF) Gaussiana e exploram a razão de magnitudes de gradientes de versões re-borradas da imagem original com escalas diferentes nas bordas da imagem, o que fornece uma expressão matemática fechada para borramento local. A primeira abordagem calcula perfis 1D ao longo de pontos de borda ortogonais ao contorno local, e avalia a localização da borda (máximo da derivada primeira) para selecionar adaptativamente o número de escalas no re-borramento. Considerando o consumo de tempo de explorar perfis de aresta orientados 1D, um segundo método foi proposto com base em gradientes de imagem diretamente no domínio 2D, e os parâmetros de re-borramento locais foram selecionados com base na concordância de um detector de bordas calculado em várias escalas. Dada uma estimativa inicial da escala de desfocagem nas posições de borda proporcionada por qualquer um destes dois métodos, é também proposto um passo de correção que atenua os erros introduzidos pela discretização da formulação contínua. Um novo método de filtragem local que suaviza as estimativas refinadas ao longo dos contornos de imagem também é proposto, e um filtro de domínio conjunto (jointdomain filter) rápido é explorado para propagar informações de desfocagem para toda a imagem, gerando o mapa de desfocagem completo. Os resultados experimentais em imagens sintéticas e reais mostram que os métodos propostos apresentam resultados promissores para a estimativa de borramento por desfoco, com um bom compromisso entre qualidade e tempo de execução quando comparados a técnicas estado-da-arte. Para lidar com sequências de vídeo desfocadas, a consistência temporal também foi incluída no modelo proposto. Mais precisamente, Filtros de Kalman foram aplicados para gerar estimativas temporais suaves para cada pixel quando a aparência local da sequência de vídeo não varia muito, permitindo transições durante mudanças drásticas da aparência local, que podem se relacionar com oclusões/desoclusões. Finalmente, esta tese também mostra aplicações dos métodos propostos para a estimativa de desfocagem de imagem e vídeo. Um novo método de redimensionamento (retargeting) de imagens é proposto para fotos tiradas por câmera com baixa profundidade de campo. O método inclui informação de desfocamento local no contexto do método seam carving, visando preservar objetos em foco com melhor qualidade visual. Assumindo que os pixels em foco estejam relacionados às regiões de interesse de uma imagem com desfocamento, o método de redimensionamento proposto começa com um método de corte (cropping), o qual remove as partes sem importância (borradas) da imagem, e então o método seam carving é aplicado com uma nova função de energia que prioriza as regiões em foco. Os resultados experimentais mostram que o método proposto funciona melhor na preservação de objetos em foco do que outras técnicas de redimensionamento de imagens. A tese também explora o método de estimação de desfocagem proposto no contexto de des-borramento de imagens e sequências de vídeo, e os resultados foram comparados com vários outros métodos de estimação de desfocagem. Os resultados obtidos mostram que as métricas tipicamente usadas para avaliar métodos de estimação de desfocagem (por exemplo, erro absoluto médio) podem não estar correlacionadas com a qualidade das métricas de imagem desfocada, como a Relação Sinal-Ruído de Pico. / This dissertation presents two different defocus blur estimation methods for still images. Both methods assume a Gaussian Point Spread Function (PSF) and explore the ratio of gradient magnitudes of reblurred images computed at edge location with different scales, which provides a closed form mathematical formulation for the local blur assuming continuous-time signals. The first approach computes 1D profiles along edge points orthogonal to the local contour, and evaluate the location of the edge (maximum of the derivative) to adaptively select the number of reblurring scales. Considering the time consumption of exploring 1D oriented edge profiles, a second method was proposed based on 2D multiscale image gradients, and local reblurring parameters were selected based on the agreement of an edge detector computed at several scales. Given an initial estimate of the blur scale at edge locations provided by either of these two methods, a correction step that accounts for the discretization of the continuous formulation is also proposed. A novel local filtering method that smooths the refined estimates along the image contours is also proposed, and a fast joint domain filter is explored to propagate blur information to the whole image to generate the full blur map. Experimental results on synthetic and real images show that the proposed methods have promising results for defocus blur estimation, with a good trade off between running time and accuracy when compared to state-of-the art defocus blur estimation methods. To deal with blurry video sequences, temporal consistency was also included in the proposed model. More precisely, Kalman Filters were applied to generate smooth temporal estimates for each pixel when the local appearance of the video sequence does not vary much, and allowing sharp transitions during drastic local appearance changes, which might relate to occlusions/disocclusions. Finally, this dissertation also shows applications of the proposed methods for image and video blur estimation. A new image retargeting method is proposed for photos taken by a shallow Depth of Field (DoF) camera. The method includes defocus blur information with the seam carving framework aiming to preserve in-focus objects with better visual quality. Assuming the in-focus pixels related to regions of interest of a blurry image, the proposed retargeting method starts with a cropping method, which removes the unimportant parts (blurry) of the image, then the seam carving method is applied with a novel energy function that prioritizes in-focus regions. Experimental results show that the proposed blur aware retargeting method works better at preserving in-focus objects than other well known competitive retargeting methods. The dissertation also explores the proposed blur estimation method in the context of image and video deblurring, and results were compared with several other blur estimation methods. The obtained results show that metrics typically used to evaluate blur estimation methods (e.g. Mean Absolute Error) might not be correlated with the quality of deblurred image metrics, such as Peak Signal to Noise Ratio.
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Spatial Frequency-Based Objective Function for Optimization of Dose Heterogeneity in Grid TherapyEmil, Fredén January 2019 (has links)
In this project we introduced a spatial frequency-based objective function for optimization of dose distributions used in spatially fractionated radiotherapy (also known as grid therapy). Several studies indicate that tissues can tolerate larger mean doses of radiation if the dose is delivered heterogeneously or to a partial volume of the organ. The objective function rewards heterogeneous dose distributions in the collaterally irradiated healthy tissues and is based on the concept of a maximum stem-cell migration distance. The stem-cell depletion hypothesis stipulates that damaged tissues can be repopulated by nearby surviving stem-cells within a critical volume outlined by the maximum migration distance. Proton grid therapy dose distributions were calculated to study the viability of our spatial frequency-based objective function. These were computed analytically with a proton pencil beam dose kernel. A multi-slit collimator placed flush against the surface of a water phantom defined the entrance fluence. The collimator geometry was described by two free parameters: the slit width and the number of slits within a specified field width. Organs at risk (OARs) and a planning target volume (PTV) were defined. Two dose constraints were set on the PTV and objective function values were computed for the OARs. The objective function measures the high-frequency content of a masked dose distribution, where the distinction between low- and high frequencies was made based on a characteristic distance. Out of the feasible solutions, the irradiation geometry that produced the maximum objective function value was selected as the optimal solution. With the spatial frequency-based objective function we were able to find, by brute-force search, unique optimal solutions to the constrained optimization problem. The optimal solutions were found on the boundary of the solution space. The objective function can be applied directly to arbitrarily shaped regions of interest and to dose distributions produced by multiple field angles. The next step is to implement the objective function in an optimization environment of a commercial treatment planning system (TPS).
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Dryland vulnerability : typical patterns and dynamics in support of vulnerability reduction effortsSietz, Diana January 2011 (has links)
The pronounced constraints on ecosystem functioning and human livelihoods in drylands are frequently exacerbated by natural and socio-economic stresses, including weather extremes and inequitable trade conditions. Therefore, a better understanding of the relation between these stresses and the socio-ecological systems is important for advancing dryland development. The concept of vulnerability as applied in this dissertation describes this relation as encompassing the exposure to climate, market and other stresses as well as the sensitivity of the systems to these stresses and their capacity to adapt. With regard to the interest in improving environmental and living conditions in drylands, this dissertation aims at a meaningful generalisation of heterogeneous vulnerability situations.
A pattern recognition approach based on clustering revealed typical vulnerability-creating mechanisms at global and local scales. One study presents the first analysis of dryland vulnerability with global coverage at a sub-national resolution. The cluster analysis resulted in seven typical patterns of vulnerability according to quantitative indication of poverty, water stress, soil degradation, natural agro-constraints and isolation. Independent case studies served to validate the identified patterns and to prove the transferability of vulnerability-reducing approaches. Due to their worldwide coverage, the global results allow the evaluation of a specific system’s vulnerability in its wider context, even in poorly-documented areas. Moreover, climate vulnerability of smallholders was investigated with regard to their food security in the Peruvian Altiplano. Four typical groups of households were identified in this local dryland context using indicators for harvest failure risk, agricultural resources, education and non-agricultural income. An elaborate validation relying on independently acquired information demonstrated the clear correlation between weather-related damages and the identified clusters. It also showed that household-specific causes of vulnerability were consistent with the mechanisms implied by the corresponding patterns. The synthesis of the local study provides valuable insights into the tailoring of interventions that reflect the heterogeneity within the social group of smallholders.
The conditions necessary to identify typical vulnerability patterns were summarised in five methodological steps. They aim to motivate and to facilitate the application of the selected pattern recognition approach in future vulnerability analyses. The five steps outline the elicitation of relevant cause-effect hypotheses and the quantitative indication of mechanisms as well as an evaluation of robustness, a validation and a ranking of the identified patterns. The precise definition of the hypotheses is essential to appropriately quantify the basic processes as well as to consistently interpret, validate and rank the clusters. In particular, the five steps reflect scale-dependent opportunities, such as the outcome-oriented aspect of validation in the local study.
Furthermore, the clusters identified in Northeast Brazil were assessed in the light of important endogenous processes in the smallholder systems which dominate this region. In order to capture these processes, a qualitative dynamic model was developed using generalised rules of labour allocation, yield extraction, budget constitution and the dynamics of natural and technological resources. The model resulted in a cyclic trajectory encompassing four states with differing degree of criticality. The joint assessment revealed aggravating conditions in major parts of the study region due to the overuse of natural resources and the potential for impoverishment. The changes in vulnerability-creating mechanisms identified in Northeast Brazil are well-suited to informing local adjustments to large-scale intervention programmes, such as “Avança Brasil”.
Overall, the categorisation of a limited number of typical patterns and dynamics presents an efficient approach to improving our understanding of dryland vulnerability. Appropriate decision-making for sustainable dryland development through vulnerability reduction can be significantly enhanced by pattern-specific entry points combined with insights into changing hotspots of vulnerability and the transferability of successful adaptation strategies. / Die Grenzen ökologischer Funktionen und menschlicher Lebensweisen in Trockengebieten werden häufig durch natürlichen und sozio-ökonomischen Stress, wie extreme Wetterereignisse und ungerechte Handelsbedingungen, weiter verengt. Zur Förderung der Entwicklung in Trockengebieten ist es daher wichtig, die Beziehung zwischen den Stressfaktoren und den sozio-ökologischen Systemen besser zu verstehen. Das Konzept der Vulnerabilität, welches in der vorliegenden Dissertation angewandt wird, beschreibt dieses Verhältnis durch die Exposition, Sensitivität und Anpassungsfähigkeit von Systemen im Hinblick auf Klima-, Markt- und anderen Stress. Bezüglich des Interesses, die Umwelt- und Lebensbedingungen in Trockengebieten zu verbessern, zielt diese Dissertation darauf ab, die vielschichtigen Ursachen und Veränderungen von Vulnerabilität sinnvoll zu verallgemeinern.
Eine clusterbasierte Mustererkennung zeigte typische Mechanismen auf, welche Vulnerabilität auf globaler und lokaler Ebene verursachen. Dabei stellt die globale Studie die erste flächendeckende Untersuchung von Vulnerabilität in Trockengebieten mit sub-nationaler Auflösung dar. Die Clusteranalyse identifizierte sieben typische Muster basierend auf der quantitativen Beschreibung von Armut, Wasserknappheit, Bodendegradation, natürlichen Produktionshemmnissen und Isolation. Die Gültigkeit der ermittelten Cluster und die Übertragbarkeit von Anpassungsmaßnahmen innerhalb ähnlicher Gebiete wurden anhand unabhängiger Fallstudien belegt. Die flächendeckende Erfassung erlaubt es, die Vulnerabilität eines Systems in seinem größeren Kontext zu bewerten, auch in weniger gut durch Fallstudien dokumentierten Gebieten. Weiterhin wurde die Klimavulnerabilität von Kleinbauern bezüglich ihrer Nahrungsmittelsicherung im peruanischen Altiplano untersucht. In diesem lokalen Kontext wurden vier Cluster von Haushalten gemäß ihrer Produktionsrisiken, landwirtschaftlichen Ressourcen, der Bildung und ihres nicht-landwirtschaftlichen Einkommens unterschieden. Eine erweiterte Gültigkeitsprüfung unter Nutzung unabhängig erhobener Informationen stellte heraus, dass wetterbedingte Schäden mit den ermittelten Clustern korrelieren und dass haushaltsspezifische Schadensursachen mit den durch die Muster angezeigten Mechanismen übereinstimmen. Die lokale Studie liefert wertvolle Hinweise auf bedarfsgerechte Eingriffe unter Beachtung der Heterogenität innerhalb der sozialen Gruppe der Kleinbauern.
Die notwendigen Bedingungen zur Erkennung typischer Muster ergaben fünf methodische Schritte. Ihre Darlegung soll die Anwendung der gewählten Methode in zukünftigen Vulnerabilitätsstudien anregen und erleichtern. Die fünf Schritte umfassen die Ableitung relevanter Ursache-Wirkungs-Hypothesen, die Quantifizierung der Mechanismen, die Bewertung von Robustheit und Gültigkeit sowie die Ordnung der ermittelten Muster nach dem Grad der Vulnerabilität. Dabei ist die genaue Beschreibung der Hypothesen eine wesentliche Voraussetzung für die Quantifizierung der grundlegenden Prozesse sowie eine einheitliche Interpretation, Gültigkeitsprüfung und Ordnung der ermittelten Muster. Besondere Beachtung finden skalenbedingte Aspekte, wie beispielsweise die ergebnisorientierte Gültigkeitsprüfung in der lokalen Studie.
Weiterhin wurden die in Nordostbrasilien ermittelten Cluster im Hinblick auf wichtige endogene Prozesse in den dort vorherrschenden kleinbäuerlichen Nutzungssystemen untersucht. Diese Prozesse umfassen die Aufteilung der Arbeitskraft, die landwirtschaftliche Produktion sowie Einkommens- und Ressourcendynamiken. Sie wurden in einem qualitativen dynamischen Modell erfasst, welches eine zyklische Trajektorie mit vier unterschiedlich problematischen Entwicklungszuständen ergab. Als besonders problematischer Aspekt verschärfte sich die Vulnerabilität in weiten Teilen des Untersuchungsgebietes durch die Übernutzung natürlicher Ressourcen und die Möglichkeit weiterer Verarmung. Die in Nordostbrasilien gezeigten Veränderungen sind dazu geeignet, groß angelegte Entwicklungsprogramme, wie zum Beispiel “Avança Brasil”, angemessen an lokale Gegebenheiten anzupassen.
Insgesamt ermöglicht es die Kategorisierung einer begrenzten Anzahl typischer Muster und Veränderungen, die Vulnerabilität in Trockengebieten besser zu verstehen. Eine nachhaltige Entwicklung von Trockengebieten basierend auf der Minderung von Vulnerabilität kann durch musterspezifische Ansätze zusammen mit Hinweisen zu Veränderungen im Schweregrad und zur Übertragbarkeit erfolgreicher Anpassungsstrategien wirkungsvoll unterstützt werden.
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Spatially Resolved Equalization: A New Concept in Intermodal Dispersion Compensation for Multimode FiberPatel, Ketan M. January 2004 (has links)
The use of optical fiber is of great interest in developing extensive, high-speed networking infrastructures. Optical fiber provide many advantages over traditional copper cables and wireless links. Among them are high security, low electromagnetic interference, extremely low loss and high bandwidths, light weight and manageability. However, the very small wavelengths associated with optical radiation requires very small waveguide dimensions. Waveguide dimension of single mode fiber (SMF) are < 10µm, resulting in relatively poor yield in device manufacturing. For residential and other last-mile networks topologies, cost constraints limit the appeal of SMF. Multimode fiber (MMF) allow for less restrictive manufacturing tolerances; however, the distortion that results from the dispersion in propagation among the many modes can be prohibitively large for data rates approaching and exceeding 1 Gb/s.
To improve the deployability of MMF, a method of dispersion compensation that maintains the ease-of-use characteristic of MMF is required This dissertation demonstrates an opto-electronic method of dispersion compensation by the use of a multisegment photodetector. It is shown the modes of the fiber can be seperated such that when the individual photodetector signals are combined, the resulting temporal response of the fiber link is improved from that of a conventional fiber link. This method is extremely robust to system variation and is independent of data rate and transmission format, allowing it to be employed in a wide variety of optical links. More importantly, the implementation demonstrated is comparable, in simplicity and alignment tolerance, to a conventional photodetector. System performance is shown using both temporal and frequency response as well as real bit error rate and eye diagram measurements.
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Cyclic Dynamics of Spatially Heterogeneous Populations - From Biodiversity to Disease PrevalenceLamouroux, David 14 December 2012 (has links)
No description available.
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