970 resultados para distance function


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We analyze how changes in trade openness are related to induced technological innovations that are not only GDP increasing but also pollution saving. Our model includes by-products of carbon dioxide and sulfur dioxide emissions. We estimate a directional distance function for 76 countries over the period 1963-2000 to measure exogenous and trade-induced technological change. On average, we find substantial trade-induced technological progress, and its magnitude is about one third of the overall technological change. The trade-induced technological changes, however, are GDP reducing and pollution increasing. Empirically, we find that increased trade openness correlates to increased pollution.

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Adaptation to climate change has become an important policy question in recent years. Agriculture is an economic activity that is most sensitive to climate change. We evaluate the dynamic effects of productivity change and individual efforts to adapt to climate change. Adaptation actions in agriculture are evaluated to determine how the climate affects production efficiency. In this paper, we use the bi-directional distance function method to measure Japanese rice production loss due to climate. We find that (1) accumulated precipitation has the greatest effect on rice production efficiency and (2) the climate effect on rice production efficiency decreases over time. Our results empirically support the benefit of the adaptation approach.

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The objective of this paper is to provide a more comprehensive e±ciency measure to estimate the performance of OECD and non-OECD countries. A Russell directional distance function that appropriately credits the decision-making unit not only for increase in desirable outputs but also for the decrease of undesirable outputs is derived from the proposed weighted Russell directional distance model. The method was applied to a panel of 116 countries from 1992 to 2010. This framework also decomposes the comprehensive efficiency measure into individual input/ output components' inefficiency scores that are useful for policy making. The results reveal that the OECD countries perform better than the non-OECD countries in overall, goods,labor and capital efficiencies, but worse in bad and energy efficiencies.

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This paper introduces an index of tax optimality that measures the distance of some current tax structure from the optimal tax structure in the presence of public goods. This index is defined on the [0, 1] interval and measures the proportion of the optimal tax rates that will achieve the same welfare outcome as some arbitrarily given initial tax structure. We call this number the Tax Optimality Index. We also show how the basic methodology can be altered to derive a revenue equivalent uniform tax, which measures the tax burden implied by the public sector. A numerical example is used to illustrate the method developed, and extensions of the analysis to handle models with multiple households and nonlinear taxation structures are undertaken.

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This paper presents a statistical aircraft trajectory clustering approach aimed at discriminating between typical manned and expected unmanned traffic patterns. First, a resampled version of each trajectory is modelled using a mixture of Von Mises distributions (circular statistics). Second, the remodelled trajectories are globally aligned using tools from bioinformatics. Third, the alignment scores are used to cluster the trajectories using an iterative k-medoids approach and an appropriate distance function. The approach is then evaluated using synthetically generated unmanned aircraft flights combined with real air traffic position reports taken over a sector of Northern Queensland, Australia. Results suggest that the technique is useful in distinguishing between expected unmanned and manned aircraft traffic behaviour, as well as identifying some common conventional air traffic patterns.

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We present a construction of constant weight codes based on the prime ideals of a Noetherian commutative ring. The coding scheme is based on the uniqueness of the primary decomposition of ideals in Noetherian rings. The source alphabet consists of a set of radical ideals constructed from a chosen subset of the prime spectrum of the ring. The distance function between two radical ideals is taken to be the Hamming metric based on the symmetric distance between sets. As an application we construct codes for random networks employing SAF routing.

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Multi-view head-pose estimation in low-resolution, dynamic scenes is difficult due to blurred facial appearance and perspective changes as targets move around freely in the environment. Under these conditions, acquiring sufficient training examples to learn the dynamic relationship between position, face appearance and head-pose can be very expensive. Instead, a transfer learning approach is proposed in this work. Upon learning a weighted-distance function from many examples where the target position is fixed, we adapt these weights to the scenario where target positions are varying. The adaptation framework incorporates reliability of the different face regions for pose estimation under positional variation, by transforming the target appearance to a canonical appearance corresponding to a reference scene location. Experimental results confirm effectiveness of the proposed approach, which outperforms state-of-the-art by 9.5% under relevant conditions. To aid further research on this topic, we also make DPOSE- a dynamic, multi-view head-pose dataset with ground-truth publicly available with this paper.

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Single fluid schemes that rely on an interface function for phase identification in multicomponent compressible flows are widely used to study hydrodynamic flow phenomena in several diverse applications. Simulations based on standard numerical implementation of these schemes suffer from an artificial increase in the width of the interface function owing to the numerical dissipation introduced by an upwind discretization of the governing equations. In addition, monotonicity requirements which ensure that the sharp interface function remains bounded at all times necessitate use of low-order accurate discretization strategies. This results in a significant reduction in accuracy along with a loss of intricate flow features. In this paper we develop a nonlinear transformation based interface capturing method which achieves superior accuracy without compromising the simplicity, computational efficiency and robustness of the original flow solver. A nonlinear map from the signed distance function to the sigmoid type interface function is used to effectively couple a standard single fluid shock and interface capturing scheme with a high-order accurate constrained level set reinitialization method in a way that allows for oscillation-free transport of the sharp material interface. Imposition of a maximum principle, which ensures that the multidimensional preconditioned interface capturing method does not produce new maxima or minima even in the extreme events of interface merger or breakup, allows for an explicit determination of the interface thickness in terms of the grid spacing. A narrow band method is formulated in order to localize computations pertinent to the preconditioned interface capturing method. Numerical tests in one dimension reveal a significant improvement in accuracy and convergence; in stark contrast to the conventional scheme, the proposed method retains its accuracy and convergence characteristics in a shifted reference frame. Results from the test cases in two dimensions show that the nonlinear transformation based interface capturing method outperforms both the conventional method and an interface capturing method without nonlinear transformation in resolving intricate flow features such as sheet jetting in the shock-induced cavity collapse. The ability of the proposed method in accounting for the gravitational and surface tension forces besides compressibility is demonstrated through a model fully three-dimensional problem concerning droplet splash and formation of a crownlike feature. (C) 2014 Elsevier Inc. All rights reserved.

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Reynolds averaged Navier-Stokes model performances in the stagnation and wake regions for turbulent flows with relatively large Lagrangian length scales (generally larger than the scale of geometrical features) approaching small cylinders (both square and circular) is explored. The effective cylinder (or wire) diameter based Reynolds number, ReW ≤ 2.5 × 103. The following turbulence models are considered: a mixing-length; standard Spalart and Allmaras (SA) and streamline curvature (and rotation) corrected SA (SARC); Secundov's νt-92; Secundov et al.'s two equation νt-L; Wolfshtein's k-l model; the Explicit Algebraic Stress Model (EASM) of Abid et al.; the cubic model of Craft et al.; various linear k-ε models including those with wall distance based damping functions; Menter SST, k-ω and Spalding's LVEL model. The use of differential equation distance functions (Poisson and Hamilton-Jacobi equation based) for palliative turbulence modeling purposes is explored. The performance of SA with these distance functions is also considered in the sharp convex geometry region of an airfoil trailing edge. For the cylinder, with ReW ≈ 2.5 × 103 the mixing length and k-l models give strong turbulence production in the wake region. However, in agreement with eddy viscosity estimates, the LVEL and Secundov νt-92 models show relatively little cylinder influence on turbulence. On the other hand, two equation models (as does the one equation SA) suggest the cylinder gives a strong turbulence deficit in the wake region. Also, for SA, an order or magnitude cylinder diameter decrease from ReW = 2500 to 250 surprisingly strengthens the cylinder's disruptive influence. Importantly, results for ReW ≪ 250 are virtually identical to those for ReW = 250 i.e. no matter how small the cylinder/wire its influence does not, as it should, vanish. Similar tests for the Launder-Sharma k-ε, Menter SST and k-ω show, in accordance with physical reality, the cylinder's influence diminishing albeit slowly with size. Results suggest distance functions palliate the SA model's erroneous trait and improve its predictive performance in wire wake regions. Also, results suggest that, along the stagnation line, such functions improve the SA, mixing length, k-l and LVEL results. For the airfoil, with SA, the larger Poisson distance function increases the wake region turbulence levels by just under 5%. © 2007 Elsevier Inc. All rights reserved.

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Multi-finger caging offers a rigorous and robust approach to robot grasping. This thesis provides several novel algorithms for caging polygons and polyhedra in two and three dimensions. Caging refers to a robotic grasp that does not necessarily immobilize an object, but prevents it from escaping to infinity. The first algorithm considers caging a polygon in two dimensions using two point fingers. The second algorithm extends the first to three dimensions. The third algorithm considers caging a convex polygon in two dimensions using three point fingers, and considers robustness of this cage to variations in the relative positions of the fingers.

This thesis describes an algorithm for finding all two-finger cage formations of planar polygonal objects based on a contact-space formulation. It shows that two-finger cages have several useful properties in contact space. First, the critical points of the cage representation in the hand’s configuration space appear as critical points of the inter-finger distance function in contact space. Second, these critical points can be graphically characterized directly on the object’s boundary. Third, contact space admits a natural rectangular decomposition such that all critical points lie on the rectangle boundaries, and the sublevel sets of contact space and free space are topologically equivalent. These properties lead to a caging graph that can be readily constructed in contact space. Starting from a desired immobilizing grasp of a polygonal object, the caging graph is searched for the minimal, intermediate, and maximal caging regions surrounding the immobilizing grasp. An example constructed from real-world data illustrates and validates the method.

A second algorithm is developed for finding caging formations of a 3D polyhedron for two point fingers using a lower dimensional contact-space formulation. Results from the two-dimensional algorithm are extended to three dimension. Critical points of the inter-finger distance function are shown to be identical to the critical points of the cage. A decomposition of contact space into 4D regions having useful properties is demonstrated. A geometric analysis of the critical points of the inter-finger distance function results in a catalog of grasps in which the cages change topology, leading to a simple test to classify critical points. With these properties established, the search algorithm from the two-dimensional case may be applied to the three-dimensional problem. An implemented example demonstrates the method.

This thesis also presents a study of cages of convex polygonal objects using three point fingers. It considers a three-parameter model of the relative position of the fingers, which gives complete generality for three point fingers in the plane. It analyzes robustness of caging grasps to variations in the relative position of the fingers without breaking the cage. Using a simple decomposition of free space around the polygon, we present an algorithm which gives all caging placements of the fingers and a characterization of the robustness of these cages.

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O cálculo do equilíbrio de fases é um problema de grande importância em processos da engenharia, como, por exemplo, na separação por destilação, em processos de extração e simulação da recuperação terciária de petróleo, entre outros. Mas para resolvê-lo é aconselhável que se estude a priori a estabilidade termodinâmica do sistema, a qual consiste em determinar se uma dada mistura se apresenta em uma ou mais fases. Tal problema pode ser abordado como um problema de otimização, conhecido como a minimização da função distância do plano tangente à energia livre de Gibbs molar, onde modelos termodinâmicos, de natureza não convexa e não linear, são utilizados para descrevê-lo. Esse fato tem motivado um grande interesse em técnicas de otimização robustas e eficientes para a resolução de problemas relacionados com a termodinâmica do equilíbrio de fases. Como tem sido ressaltado na literatura, para proporcionar uma completa predição do equilíbrio de fases, faz-se necessário não apenas a determinação do minimizador global da função objetivo do teste de estabilidade, mas também a obtenção de todos os seus pontos estacionários. Assim, o desenvolvimento de metodologias para essa tarefa desafiadora tem se tornado uma nova área de pesquisa da otimização global aplicada à termodinâmica do equilíbrio, com interesses comuns na engenharia química e na engenharia do petróleo. O foco do presente trabalho é uma nova metodologia para resolver o problema do teste de estabilidade. Para isso, usa-se o chamado método do conjunto gerador para realizar buscas do tipo local em uma rede de pontos previamente gerada por buscas globais efetuadas com uma metaheurística populacional, no caso o método do enxame de partículas.Para se obter mais de um ponto estacionário, minimizam-se funções de mérito polarizadas, cujos pólos são os pontos previamente encontrados. A metodologia proposta foi testada na análise de quatorze misturas polares previamente consideradas na literatura. Os resultados mostraram que o método proposto é robusto e eficiente a ponto de encontrar, além do minimizador global, todos os pontos estacionários apontados previamente na literatura, sendo também capaz de detectar, em duas misturas ternárias estudadas, pontos estacionários não obtidos pelo chamado método de análise intervalar, uma técnica confiável e muito difundida na literatura. A análise do teste de estabilidade pela simples utilização do método do enxame de partículas associado à técnica de polarização mencionada acima, para a obtenção de mais de um ponto estacionário (sem a busca local feita pelo método do conjunto gerador em uma dada rede de pontos), constitui outra metodologia para a resolução do problema de interesse. Essa utilização é uma novidade secundária deste trabalho. Tal metodologia simplificada exibiu também uma grande robustez, sendo capaz de encontrar todos os pontos estacionários pesquisados. No entanto, quando comparada com a abordagem mais geral proposta aqui, observou-se que tal simplificação pode, em alguns casos onde a função de mérito apresenta uma geometria mais complexa, consumir um tempo de máquina relativamente grande, dessa forma é menos eficiente.

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Accurate and efficient computation of the distance function d for a given domain is important for many areas of numerical modeling. Partial differential (e.g. HamiltonJacobi type) equation based distance function algorithms have desirable computational efficiency and accuracy. In this study, as an alternative, a Poisson equation based level set (distance function) is considered and solved using the meshless boundary element method (BEM). The application of this for shape topology analysis, including the medial axis for domain decomposition, geometric de-featuring and other aspects of numerical modeling is assessed. © 2011 Elsevier Ltd. All rights reserved.

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The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space and on scalability to high-dimensional problems. The mathematical developments rely on the theory of gradient descent algorithms adapted to the Riemannian geometry that underlies the set of fixedrank positive semidefinite matrices. In contrast with previous contributions in the literature, no restrictions are imposed on the range space of the learned matrix. The resulting algorithms maintain a linear complexity in the problem size and enjoy important invariance properties. We apply the proposed algorithms to the problem of learning a distance function parameterized by a positive semidefinite matrix. Good performance is observed on classical benchmarks. © 2011 Gilles Meyer, Silvere Bonnabel and Rodolphe Sepulchre.

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Wydział Fizyki:Instytut Obserwatorium Astronomiczne

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Quantifying the similarity between two trajectories is a fundamental operation in analysis of spatio-temporal databases. While a number of distance functions exist, the recent shift in the dynamics of the trajectory generation procedure violates one of their core assumptions; a consistent and uniform sampling rate. In this paper, we formulate a robust distance function called Edit Distance with Projections (EDwP) to match trajectories under inconsistent and variable sampling rates through dynamic interpolation. This is achieved by deploying the idea of projections that goes beyond matching only the sampled points while aligning trajectories. To enable efficient trajectory retrievals using EDwP, we design an index structure called TrajTree. TrajTree derives its pruning power by employing the unique combination of bounding boxes with Lipschitz embedding. Extensive experiments on real trajectory databases demonstrate EDwP to be up to 5 times more accurate than the state-of-the-art distance functions. Additionally, TrajTree increases the efficiency of trajectory retrievals by up to an order of magnitude over existing techniques.