939 resultados para Non-gaussian Random Functions


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The Zagros oak forests in Western Iran are critically important to the sustainability of the region. These forests have undergone dramatic declines in recent decades. We evaluated the utility of the non-parametric Random Forest classification algorithm for land cover classification of Zagros landscapes, and selected the best spatial and spectral predictive variables. The algorithm resulted in high overall classification accuracies (>85%) and also equivalent classification accuracies for the datasets from the three different sensors. We evaluated the associations between trends in forest area and structure with trends in socioeconomic and climatic conditions, to identify the most likely driving forces creating deforestation and landscape structure change. We used available socioeconomic (urban and rural population, and rural income), and climatic (mean annual rainfall and mean annual temperature) data for two provinces in northern Zagros. The most correlated driving force of forest area loss was urban population, and climatic variables to a lesser extent. Landscape structure changes were more closely associated with rural population. We examined the effects of scale changes on the results from spatial pattern analysis. We assessed the impacts of eight years of protection in a protected area in northern Zagros at two different scales (both grain and extent). The effects of protection on the amount and structure of forests was scale dependent. We evaluated the nature and magnitude of changes in forest area and structure over the entire Zagros region from 1972 to 2009. We divided the Zagros region in 167 Landscape Units and developed two measures— Deforestation Sensitivity (DS) and Connectivity Sensitivity (CS) — for each landscape unit as the percent of the time steps that forest area and ECA experienced a decrease of greater than 10% in either measure. A considerable loss in forest area and connectivity was detected, but no sudden (nonlinear) changes were detected at the spatial and temporal scale of the study. Connectivity loss occurred more rapidly than forest loss due to the loss of connecting patches. More connectivity was lost in southern Zagros due to climatic differences and different forms of traditional land use.

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Software metrics offer us the promise of distilling useful information from vast amounts of software in order to track development progress, to gain insights into the nature of the software, and to identify potential problems. Unfortunately, however, many software metrics exhibit highly skewed, non-Gaussian distributions. As a consequence, usual ways of interpreting these metrics --- for example, in terms of "average" values --- can be highly misleading. Many metrics, it turns out, are distributed like wealth --- with high concentrations of values in selected locations. We propose to analyze software metrics using the Gini coefficient, a higher-order statistic widely used in economics to study the distribution of wealth. Our approach allows us not only to observe changes in software systems efficiently, but also to assess project risks and monitor the development process itself. We apply the Gini coefficient to numerous metrics over a range of software projects, and we show that many metrics not only display remarkably high Gini values, but that these values are remarkably consistent as a project evolves over time.

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The present synopsis aims to integrate one study about memory training in very preterm-born children and two studies about cognition in patients with carotid artery stenosis before and after treatments. Preterm-born children are at increased risk of cognitive deficits and behavioural problems compared with peers born at term. This thesis determined whether memory training would improve cognitive functions in school-age very preterm-born children. Memory strategy training produced significant improvements in trained and non-trained cognitive functions; a core working memory training revealed significant effects on short-term memory and working memory tasks. Six months after training, children in both training groups showed better working memory performance than children in the waiting control group. This is evidence that memory training – an external influence on cognition – induces plastic changes in very preterm-born children. Patients with carotid artery stenosis are known to be at increased risk of cognitive impairment. We showed that patients with symptomatic or asymptomatic carotid artery stenosis were at higher risk for cognitive deficits than expected in a normative sample. This thesis seeks to link cognitive plasticity to internal factors like carotid stenosis. An external factor, which influences blood flow to the brain is the nature of the carotid artery stenosis treatment. Research on the effects of carotid artery stenosis treatment on cognition has produced inconsistent results. We found significant improvement in frontal lobe functions, visual memory and motor speed one year after treatment independent of the treatment type (best medical treatment, carotid artery stenting, carotid artery endarterectomy); providing evidence for ‘treatment-induced’ cognitive plasticity. Baseline performance was negatively associated with improvement in various cognitive functions after training in very preterm-born children and after treatment in patients with carotid artery stenosis. The present synopsis aims to integrate these findings into the current and relevant literature, and discuss consequences as well as methodological considerations resulting from the studies constituting the thesis at hand.

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La propulsión eléctrica constituye hoy una tecnología muy competitiva y de gran proyección de futuro. Dentro de los diversos motores de plasma existentes, el motor de efecto Hall ha adquirido una gran madurez y constituye un medio de propulsión idóneo para un rango amplio de misiones. En la presente Tesis se estudian los motores Hall con geometría convencional y paredes dieléctricas. La compleja interacción entre los múltiples fenómenos físicos presentes hace que sea difícil la simulación del plasma en estos motores. Los modelos híbridos son los que representan un mejor compromiso entre precisión y tiempo de cálculo. Se basan en utilizar un modelo fluido para los electrones y algoritmos de dinámica de partículas PIC (Particle-In- Cell) para los iones y los neutros. Permiten hacer uso de la hipótesis de cuasineutralidad del plasma, a cambio de resolver separadamente las capas límite (o vainas) que se forman en torno a las paredes de la cámara. Partiendo de un código híbrido existente, llamado HPHall-2, el objetivo de la Tesis doctoral ha sido el desarrollo de un código híbrido avanzado que mejorara la simulación de la descarga de plasma en un motor de efecto Hall. Las actualizaciones y mejoras realizadas en las diferentes partes que componen el código comprenden tanto aspectos teóricos como numéricos. Fruto de la extensa revisión de la algoritmia del código HPHall-2 se han conseguido reducir los errores de precisión un orden de magnitud, y se ha incrementado notablemente su consistencia y robustez, permitiendo la simulación del motor en un amplio rango de condiciones. Algunos aspectos relevantes a destacar en el subcódigo de partículas son: la implementación de un nuevo algoritmo de pesado que permite determinar de forma más precisa el flujo de las magnitudes del plasma; la implementación de un nuevo algoritmo de control de población, que permite tener suficiente número de partículas cerca de las paredes de la cámara, donde los gradientes son mayores y las condiciones de cálculo son más críticas; las mejoras en los balances de masa y energía; y un mejor cálculo del campo eléctrico en una malla no uniforme. Merece especial atención el cumplimiento de la condición de Bohm en el borde de vaina, que en los códigos híbridos representa una condición de contorno necesaria para obtener una solución consistente con el modelo de interacción plasma-pared, y que en HPHall-2 aún no se había resuelto satisfactoriamente. En esta Tesis se ha implementado el criterio cinético de Bohm para una población de iones con diferentes cargas eléctricas y una gran dispersión de velocidades. En el código, el cumplimiento de la condición cinética de Bohm se consigue por medio de un algoritmo que introduce una fina capa de aceleración nocolisional adyacente a la vaina y mide adecuadamente el flujo de partículas en el espacio y en el tiempo. Las mejoras realizadas en el subcódigo de electrones incrementan la capacidad de simulación del código, especialmente en la región aguas abajo del motor, donde se simula la neutralización del chorro del plasma por medio de un modelo de cátodo volumétrico. Sin abordar el estudio detallado de la turbulencia del plasma, se implementan modelos sencillos de ajuste de la difusión anómala de Bohm, que permiten reproducir los valores experimentales del potencial y la temperatura del plasma, así como la corriente de descarga del motor. En cuanto a los aspectos teóricos, se hace especial énfasis en la interacción plasma-pared y en la dinámica de los electrones secundarios libres en el interior del plasma, cuestiones que representan hoy en día problemas abiertos en la simulación de los motores Hall. Los nuevos modelos desarrollados buscan una imagen más fiel a la realidad. Así, se implementa el modelo de vaina de termalización parcial, que considera una función de distribución no-Maxwelliana para los electrones primarios y contabiliza unas pérdidas energéticas más cercanas a la realidad. Respecto a los electrones secundarios, se realiza un estudio cinético simplificado para evaluar su grado de confinamiento en el plasma, y mediante un modelo fluido en el límite no-colisional, se determinan las densidades y energías de los electrones secundarios libres, así como su posible efecto en la ionización. El resultado obtenido muestra que los electrones secundarios se pierden en las paredes rápidamente, por lo que su efecto en el plasma es despreciable, no así en las vainas, donde determinan el salto de potencial. Por último, el trabajo teórico y de simulación numérica se complementa con el trabajo experimental realizado en el Pnnceton Plasma Physics Laboratory, en el que se analiza el interesante transitorio inicial que experimenta el motor en el proceso de arranque. Del estudio se extrae que la presencia de gases residuales adheridos a las paredes juegan un papel relevante, y se recomienda, en general, la purga completa del motor antes del modo normal de operación. El resultado final de la investigación muestra que el código híbrido desarrollado representa una buena herramienta de simulación de un motor Hall. Reproduce adecuadamente la física del motor, proporcionando resultados similares a los experimentales, y demuestra ser un buen laboratorio numérico para estudiar el plasma en el interior del motor. Abstract Electric propulsion is today a very competitive technology and has a great projection into the future. Among the various existing plasma thrusters, the Hall effect thruster has acquired a considerable maturity and constitutes an ideal means of propulsion for a wide range of missions. In the present Thesis only Hall thrusters with conventional geometry and dielectric walls are studied. The complex interaction between multiple physical phenomena makes difficult the plasma simulation in these engines. Hybrid models are those representing a better compromise between precision and computational cost. They use a fluid model for electrons and Particle-In-Cell (PIC) algorithms for ions and neutrals. The hypothesis of plasma quasineutrality is invoked, which requires to solve separately the sheaths formed around the chamber walls. On the basis of an existing hybrid code, called HPHall-2, the aim of this doctoral Thesis is to develop an advanced hybrid code that better simulates the plasma discharge in a Hall effect thruster. Updates and improvements of the code include both theoretical and numerical issues. The extensive revision of the algorithms has succeeded in reducing the accuracy errors in one order of magnitude, and the consistency and robustness of the code have been notably increased, allowing the simulation of the thruster in a wide range of conditions. The most relevant achievements related to the particle subcode are: the implementation of a new weighing algorithm that determines more accurately the plasma flux magnitudes; the implementation of a new algorithm to control the particle population, assuring enough number of particles near the chamber walls, where there are strong gradients and the conditions to perform good computations are more critical; improvements in the mass and energy balances; and a new algorithm to compute the electric field in a non-uniform mesh. It deserves special attention the fulfilment of the Bohm condition at the edge of the sheath, which represents a boundary condition necessary to match consistently the hybrid code solution with the plasma-wall interaction, and remained as a question unsatisfactory solved in the HPHall-2 code. In this Thesis, the kinetic Bohm criterion has been implemented for an ion particle population with different electric charges and a large dispersion in their velocities. In the code, the fulfilment of the kinetic Bohm condition is accomplished by an algorithm that introduces a thin non-collisional layer next to the sheaths, producing the ion acceleration, and measures properly the flux of particles in time and space. The improvements made in the electron subcode increase the code simulation capabilities, specially in the region downstream of the thruster, where the neutralization of the plasma jet is simulated using a volumetric cathode model. Without addressing the detailed study of the plasma turbulence, simple models for a parametric adjustment of the anomalous Bohm difussion are implemented in the code. They allow to reproduce the experimental values of the plasma potential and the electron temperature, as well as the discharge current of the thruster. Regarding the theoretical issues, special emphasis has been made in the plasma-wall interaction of the thruster and in the dynamics of free secondary electrons within the plasma, questions that still remain unsolved in the simulation of Hall thrusters. The new developed models look for results closer to reality, such as the partial thermalization sheath model, that assumes a non-Maxwellian distribution functions for primary electrons, and better computes the energy losses at the walls. The evaluation of secondary electrons confinement within the chamber is addressed by a simplified kinetic study; and using a collisionless fluid model, the densities and energies of free secondary electrons are computed, as well as their effect on the plasma ionization. Simulations show that secondary electrons are quickly lost at walls, with a negligible effect in the bulk of the plasma, but they determine the potential fall at sheaths. Finally, numerical simulation and theoretical work is complemented by the experimental work carried out at the Princeton Plasma Physics Laboratory, devoted to analyze the interesting transitional regime experienced by the thruster in the startup process. It is concluded that the gas impurities adhered to the thruster walls play a relevant role in the transitional regime and, as a general recomendation, a complete purge of the thruster before starting its normal mode of operation it is suggested. The final result of the research conducted in this Thesis shows that the developed code represents a good tool for the simulation of Hall thrusters. The code reproduces properly the physics of the thruster, with results similar to the experimental ones, and represents a good numerical laboratory to study the plasma inside the thruster.

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This work proposes an optimization of a semi-supervised Change Detection methodology based on a combination of Change Indices (CI) derived from an image multitemporal data set. For this purpose, SPOT 5 Panchromatic images with 2.5 m spatial resolution have been used, from which three Change Indices have been calculated. Two of them are usually known indices; however the third one has been derived considering the Kullbak-Leibler divergence. Then, these three indices have been combined forming a multiband image that has been used in as input for a Support Vector Machine (SVM) classifier where four different discriminant functions have been tested in order to differentiate between change and no_change categories. The performance of the suggested procedure has been assessed applying different quality measures, reaching in each case highly satisfactory values. These results have demonstrated that the simultaneous combination of basic change indices with others more sophisticated like the Kullback-Leibler distance, and the application of non-parametric discriminant functions like those employees in the SVM method, allows solving efficiently a change detection problem.

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Thesis (Ph.D.)--University of Washington, 2016-06

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We investigate an optical scheme to conditionally engineer quantum states using a beam splitter, homodyne detection, and a squeezed vacuum as an ancillar state. This scheme is efficient in producing non-Gaussian quantum states such as squeezed single photons and superpositions of coherent states (SCSs). We show that a SCS with well defined parity and high fidelity can be generated from a Fock state of n

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We describe a generalization of the cluster-state model of quantum computation to continuous-variable systems, along with a proposal for an optical implementation using squeezed-light sources, linear optics, and homodyne detection. For universal quantum computation, a nonlinear element is required. This can be satisfied by adding to the toolbox any single-mode non-Gaussian measurement, while the initial cluster state itself remains Gaussian. Homodyne detection alone suffices to perform an arbitrary multimode Gaussian transformation via the cluster state. We also propose an experiment to demonstrate cluster-based error reduction when implementing Gaussian operations.

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We present in this paper ideas to tackle the problem of analysing and forecasting nonstationary time series within the financial domain. Accepting the stochastic nature of the underlying data generator we assume that the evolution of the generator's parameters is restricted on a deterministic manifold. Therefore we propose methods for determining the characteristics of the time-localised distribution. Starting with the assumption of a static normal distribution we refine this hypothesis according to the empirical results obtained with the methods anc conclude with the indication of a dynamic non-Gaussian behaviour with varying dependency for the time series under consideration.

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This paper presents a general methodology for estimating and incorporating uncertainty in the controller and forward models for noisy nonlinear control problems. Conditional distribution modeling in a neural network context is used to estimate uncertainty around the prediction of neural network outputs. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localize the possible control solutions to consider. A nonlinear multivariable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non Gaussian distributions of control signal as well as processes with hysteresis.

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We consider the direct adaptive inverse control of nonlinear multivariable systems with different delays between every input-output pair. In direct adaptive inverse control, the inverse mapping is learned from examples of input-output pairs. This makes the obtained controller sub optimal, since the network may have to learn the response of the plant over a larger operational range than necessary. Moreover, in certain applications, the control problem can be redundant, implying that the inverse problem is ill posed. In this paper we propose a new algorithm which allows estimating and exploiting uncertainty in nonlinear multivariable control systems. This approach allows us to model strongly non-Gaussian distribution of control signals as well as processes with hysteresis. The proposed algorithm circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider.

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We describe a template model for perception of edge blur and identify a crucial early nonlinearity in this process. The main principle is to spatially filter the edge image to produce a 'signature', and then find which of a set of templates best fits that signature. Psychophysical blur-matching data strongly support the use of a second-derivative signature, coupled to Gaussian first-derivative templates. The spatial scale of the best-fitting template signals the edge blur. This model predicts blur-matching data accurately for a wide variety of Gaussian and non-Gaussian edges, but it suffers a bias when edges of opposite sign come close together in sine-wave gratings and other periodic images. This anomaly suggests a second general principle: the region of an image that 'belongs' to a given edge should have a consistent sign or direction of luminance gradient. Segmentation of the gradient profile into regions of common sign is achieved by implementing the second-derivative 'signature' operator as two first-derivative operators separated by a half-wave rectifier. This multiscale system of nonlinear filters predicts perceived blur accurately for periodic and aperiodic waveforms. We also outline its extension to 2-D images and infer the 2-D shape of the receptive fields.

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Edge blur is an important perceptual cue, but how does the visual system encode the degree of blur at edges? Blur could be measured by the width of the luminance gradient profile, peak ^ trough separation in the 2nd derivative profile, or the ratio of 1st-to-3rd derivative magnitudes. In template models, the system would store a set of templates of different sizes and find which one best fits the `signature' of the edge. The signature could be the luminance profile itself, or one of its spatial derivatives. I tested these possibilities in blur-matching experiments. In a 2AFC staircase procedure, observers adjusted the blur of Gaussian edges (30% contrast) to match the perceived blur of various non-Gaussian test edges. In experiment 1, test stimuli were mixtures of 2 Gaussian edges (eg 10 and 30 min of arc blur) at the same location, while in experiment 2, test stimuli were formed from a blurred edge sharpened to different extents by a compressive transformation. Predictions of the various models were tested against the blur-matching data, but only one model was strongly supported. This was the template model, in which the input signature is the 2nd derivative of the luminance profile, and the templates are applied to this signature at the zero-crossings. The templates are Gaussian derivative receptive fields that covary in width and length to form a self-similar set (ie same shape, different sizes). This naturally predicts that shorter edges should look sharper. As edge length gets shorter, responses of longer templates drop more than shorter ones, and so the response distribution shifts towards shorter (smaller) templates, signalling a sharper edge. The data confirmed this, including the scale-invariance implied by self-similarity, and a good fit was obtained from templates with a length-to-width ratio of about 1. The simultaneous analysis of edge blur and edge location may offer a new solution to the multiscale problem in edge detection.

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We apply well known nonlinear diffraction theory governing focusing of a powerful light beam of arbitrary shape in medium with Kerr nonlinearity to the analysis of femtosecond (fs) laser processing of dielectric in sub-critical (input power less than the critical power of selffocusing) regime. Simple analytical expressions are derived for the input beam power and spatial focusing parameter (numerical aperture) that are required for achieving an inscription threshold. Application of non-Gaussian laser beams for better controlled fs inscription at higher powers is also discussed. © 2007 Optical Society of America.