1000 resultados para Evolution PDE
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In this thesis, I have investigated the evolution of the high-redshift (z > 3) AGN population by collecting data from some of the major Chandra and XMM-Newton surveys. The final sample (141 sources) is one of the largest selected at z> 3 in the X- rays and it is characterised by a very high redshift completeness (98%). I derived the spectral slopes and obscurations through a spectral anaysis and I assessed the high-z evolution by deriving the luminosity function and the number counts of the sample. The best representation of the AGN evolution is a pure density evolution (PDE) model: the AGN space density is found to decrease by a factor of 10 from z=3 to z=5. I also found that about 50% of AGN are obscured by large column densities (logNH > 23). By comparing these data with those in the Local Universe, I found a positive evolution of the obscured AGN fraction with redshift, especially for luminous (logLx > 44) AGN. I also studied the gas content of z < 1 AGN-hosting galaxies and compared it with that of inactive galaxies. For the first time, I applied to AGN a method to derive the gas mass previously used for inactive galaxies only. AGN are found to live preferentially in gas-rich galaxies. This result on the one hand can help us in understanding the AGN triggering mechanisms, on the other hand explains why AGN are preferentially hosted by star-forming galaxies.
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We present the extension of a methodology to solve moving boundary value problems from the second-order case to the case of the third-order linear evolution PDE qt + qxxx = 0. This extension is the crucial step needed to generalize this methodology to PDEs of arbitrary order. The methodology is based on the derivation of inversion formulae for a class of integral transforms that generalize the Fourier transform and on the analysis of the global relation associated with the PDE. The study of this relation and its inversion using the appropriate generalized transform are the main elements of the proof of our results.
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We analyse the Dirichlet problem for the elliptic sine Gordon equation in the upper half plane. We express the solution $q(x,y)$ in terms of a Riemann-Hilbert problem whose jump matrix is uniquely defined by a certain function $b(\la)$, $\la\in\R$, explicitly expressed in terms of the given Dirichlet data $g_0(x)=q(x,0)$ and the unknown Neumann boundary value $g_1(x)=q_y(x,0)$, where $g_0(x)$ and $g_1(x)$ are related via the global relation $\{b(\la)=0$, $\la\geq 0\}$. Furthermore, we show that the latter relation can be used to characterise the Dirichlet to Neumann map, i.e. to express $g_1(x)$ in terms of $g_0(x)$. It appears that this provides the first case that such a map is explicitly characterised for a nonlinear integrable {\em elliptic} PDE, as opposed to an {\em evolution} PDE.
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La segmentación de imágenes es un campo importante de la visión computacional y una de las áreas de investigación más activas, con aplicaciones en comprensión de imágenes, detección de objetos, reconocimiento facial, vigilancia de vídeo o procesamiento de imagen médica. La segmentación de imágenes es un problema difícil en general, pero especialmente en entornos científicos y biomédicos, donde las técnicas de adquisición imagen proporcionan imágenes ruidosas. Además, en muchos de estos casos se necesita una precisión casi perfecta. En esta tesis, revisamos y comparamos primero algunas de las técnicas ampliamente usadas para la segmentación de imágenes médicas. Estas técnicas usan clasificadores a nivel de pixel e introducen regularización sobre pares de píxeles que es normalmente insuficiente. Estudiamos las dificultades que presentan para capturar la información de alto nivel sobre los objetos a segmentar. Esta deficiencia da lugar a detecciones erróneas, bordes irregulares, configuraciones con topología errónea y formas inválidas. Para solucionar estos problemas, proponemos un nuevo método de regularización de alto nivel que aprende información topológica y de forma a partir de los datos de entrenamiento de una forma no paramétrica usando potenciales de orden superior. Los potenciales de orden superior se están popularizando en visión por computador, pero la representación exacta de un potencial de orden superior definido sobre muchas variables es computacionalmente inviable. Usamos una representación compacta de los potenciales basada en un conjunto finito de patrones aprendidos de los datos de entrenamiento que, a su vez, depende de las observaciones. Gracias a esta representación, los potenciales de orden superior pueden ser convertidos a potenciales de orden 2 con algunas variables auxiliares añadidas. Experimentos con imágenes reales y sintéticas confirman que nuestro modelo soluciona los errores de aproximaciones más débiles. Incluso con una regularización de alto nivel, una precisión exacta es inalcanzable, y se requeire de edición manual de los resultados de la segmentación automática. La edición manual es tediosa y pesada, y cualquier herramienta de ayuda es muy apreciada. Estas herramientas necesitan ser precisas, pero también lo suficientemente rápidas para ser usadas de forma interactiva. Los contornos activos son una buena solución: son buenos para detecciones precisas de fronteras y, en lugar de buscar una solución global, proporcionan un ajuste fino a resultados que ya existían previamente. Sin embargo, requieren una representación implícita que les permita trabajar con cambios topológicos del contorno, y esto da lugar a ecuaciones en derivadas parciales (EDP) que son costosas de resolver computacionalmente y pueden presentar problemas de estabilidad numérica. Presentamos una aproximación morfológica a la evolución de contornos basada en un nuevo operador morfológico de curvatura que es válido para superficies de cualquier dimensión. Aproximamos la solución numérica de la EDP de la evolución de contorno mediante la aplicación sucesiva de un conjunto de operadores morfológicos aplicados sobre una función de conjuntos de nivel. Estos operadores son muy rápidos, no sufren de problemas de estabilidad numérica y no degradan la función de los conjuntos de nivel, de modo que no hay necesidad de reinicializarlo. Además, su implementación es mucho más sencilla que la de las EDP, ya que no requieren usar sofisticados algoritmos numéricos. Desde un punto de vista teórico, profundizamos en las conexiones entre operadores morfológicos y diferenciales, e introducimos nuevos resultados en este área. Validamos nuestra aproximación proporcionando una implementación morfológica de los contornos geodésicos activos, los contornos activos sin bordes, y los turbopíxeles. En los experimentos realizados, las implementaciones morfológicas convergen a soluciones equivalentes a aquéllas logradas mediante soluciones numéricas tradicionales, pero con ganancias significativas en simplicidad, velocidad y estabilidad. ABSTRACT Image segmentation is an important field in computer vision and one of its most active research areas, with applications in image understanding, object detection, face recognition, video surveillance or medical image processing. Image segmentation is a challenging problem in general, but especially in the biological and medical image fields, where the imaging techniques usually produce cluttered and noisy images and near-perfect accuracy is required in many cases. In this thesis we first review and compare some standard techniques widely used for medical image segmentation. These techniques use pixel-wise classifiers and introduce weak pairwise regularization which is insufficient in many cases. We study their difficulties to capture high-level structural information about the objects to segment. This deficiency leads to many erroneous detections, ragged boundaries, incorrect topological configurations and wrong shapes. To deal with these problems, we propose a new regularization method that learns shape and topological information from training data in a nonparametric way using high-order potentials. High-order potentials are becoming increasingly popular in computer vision. However, the exact representation of a general higher order potential defined over many variables is computationally infeasible. We use a compact representation of the potentials based on a finite set of patterns learned fromtraining data that, in turn, depends on the observations. Thanks to this representation, high-order potentials can be converted into pairwise potentials with some added auxiliary variables and minimized with tree-reweighted message passing (TRW) and belief propagation (BP) techniques. Both synthetic and real experiments confirm that our model fixes the errors of weaker approaches. Even with high-level regularization, perfect accuracy is still unattainable, and human editing of the segmentation results is necessary. The manual edition is tedious and cumbersome, and tools that assist the user are greatly appreciated. These tools need to be precise, but also fast enough to be used in real-time. Active contours are a good solution: they are good for precise boundary detection and, instead of finding a global solution, they provide a fine tuning to previously existing results. However, they require an implicit representation to deal with topological changes of the contour, and this leads to PDEs that are computationally costly to solve and may present numerical stability issues. We present a morphological approach to contour evolution based on a new curvature morphological operator valid for surfaces of any dimension. We approximate the numerical solution of the contour evolution PDE by the successive application of a set of morphological operators defined on a binary level-set. These operators are very fast, do not suffer numerical stability issues, and do not degrade the level set function, so there is no need to reinitialize it. Moreover, their implementation is much easier than their PDE counterpart, since they do not require the use of sophisticated numerical algorithms. From a theoretical point of view, we delve into the connections between differential andmorphological operators, and introduce novel results in this area. We validate the approach providing amorphological implementation of the geodesic active contours, the active contours without borders, and turbopixels. In the experiments conducted, the morphological implementations converge to solutions equivalent to those achieved by traditional numerical solutions, but with significant gains in simplicity, speed, and stability.
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2002 Mathematics Subject Classification: 35G20, 47H30
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Motivated by the celebrated example of Y. Kannai of a linear partial differential operator which is hypoelliptic but not locally solvable, we consider it class of evolution operators with real-analytic coefficients and study their local solvability both in L(2) and in the weak sense. In order to do so we are led to propose a generalization of the Nirenberg-Treves condition (psi) which is suitable to our study. (C) 2009 Published by Elsevier Inc.
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[EN] In this paper we present a new model for optical flow calculation using a variational formulation which preserves discontinuities of the flow much better than classical methods. We study the Euler-Lagrange equations asociated to the variational problem. In the case of quadratic energy, we show the existence and uniqueness of the corresponding evolution problem. Since our method avoid linearization in the optical flow constraint, it can recover large displacement in the scene. We avoid convergence to irrelevant local minima by embedding our method into a linear scale-space framework and using a focusing strategy from coarse to fine scales.
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In this contribution we simulate numerically the evolution of a viscous fluid drop rotating about a fixed axis at constant angular velocity ? or constant angular momentum L, surrounded by another viscous fluid. The problem is considered in the limit of large Ekman number and small Reynolds number. In the lecture we will describe the numerical method we have used to solve the PDE system that describes the evolution of the drop (3D boundary element method). We will also present the results we have obtained, paying special attention to the stability/instability of the equilibrium shapes.
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The thermal evolution process of RuO2–Ta2O5/Ti coatings with varying noble metal content has been investigated under in situ conditions by thermogravimetry combined with mass spectrometry. The gel-like films prepared from alcoholic solutions of the precursor salts (RuCl3·3H2O, TaCl5) onto titanium metal support were heated in an atmosphere containing 20% O2 and 80% Ar up to 600 °C. The evolution of the mixed oxide coatings was followed by the mass spectrometric ion intensity curves. The cracking of retained solvent and the combustion of organic surface species formed were also followed by the mass spectrometric curves. The formation of carbonyl- and carboxylate-type surface species connected to the noble metal was identified by Fourier transform infrared emission spectroscopy. These secondary processes–catalyzed by the noble metal–may play an important role in the development of surface morphology and electrochemical properties. The evolution of the two oxide phases does not take place independently, and the effect of the noble metal as a combustion catalyst was proved.
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The Australasian Science Education Research Association Ltd. (ASERA) is the oldest educational research association in Australasia. Starting as an informal meeting of science educators at Monash University in May 1970, it has evolved progressively without major controversy into a formally constituted limited company that promotes science education at all levels and contexts. There are no revelations of fractures within the association, and no accounts of major controversy, other than reference to a few grumbles here and there when changes were proposed. So, has the ASERA experience been positive and uplifting for all? Are there unspoken controversies? Can the uncontroversial be made controversial?
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Cultural policy studies have previously highlighted the importance of multiple logics, friction and contradiction in cultural policy. Recent developments in institutional theory provide a framework for analysing change in cultural policy which explores movement between these multiple and sometimes contradictory logics. This paper analyses the role of friction in the evolution of Australian film industry policy and in particular the tension between competing logics regarding nationalism, commercialism and the state. The paper is suggestive of the relevance of institutional theory as a framework for understanding cultural policy evolution.
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Research in science education is now an international activity. This book asks for the first time, Does this research activity have an identity?-It uses the significant studies of more than 75 researchers in 15 countries to see to what extent they provide evidence for an identity as a distinctive field of research.-It considers trends in the research over time, and looks particularly at what progression in the research entails.-It provides insight into how researchers influence each other and how involvement in research affects the being of the researcher as a person.-It addresses the relation between research and practice in a manner that sees teaching and learning in the science classroom as interdependent with national policies and curriculum traditions about science. It gives graduate students and other early researchers an unusual overview of their research area as a whole. Established researchers will be interested in, and challenged by, the identity the author ascribes to the research and by the plea he makes for the science content itself to be seen as problematic.