897 resultados para staircase approximation


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Es wird ein Verfahren vorgestellt, mit dem stetige Zufallsgrößen rechnerunterstützt dargestellt und miteinander verknüpft werden können. Die Verteilungsfunktionen der Zufallsgrößen werden mit einem Finite-Elemente-Ansatz in einem endlichen Intervall [tmin; tmax] approximiert. Die Addition zweier Zufallsgrößen wird durch numerische Berechnung des Faltungsintegrals durchgeführt.

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The staircase is presented as the architectural component that most potently embodies thresholds, boundaries and passages due to its diagonal orientation and essence as an intermediary zone. Connections then are made between the kinesthetic requirements of traversing a staircase and viewing a stereoscopic photograph. From this foundation, the haptic essence of stereoscopic photography is proposed as uniquely qualified medium through which to view a staircase and therefore thresholds, boundaries, and passages within architecture. Analyses of stereoviews of staircases in the Palais de Justice in Brussels, the Library of Congress in Washington, and the Palais Garnier (Opéra) in Paris close the essay.

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In this article, we develop the a priori and a posteriori error analysis of hp-version interior penalty discontinuous Galerkin finite element methods for strongly monotone quasi-Newtonian fluid flows in a bounded Lipschitz domain Ω ⊂ ℝd, d = 2, 3. In the latter case, computable upper and lower bounds on the error are derived in terms of a natural energy norm, which are explicit in the local mesh size and local polynomial degree of the approximating finite element method. A series of numerical experiments illustrate the performance of the proposed a posteriori error indicators within an automatic hp-adaptive refinement algorithm.

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We obtain upper bounds for the total variation distance between the distributions of two Gibbs point processes in a very general setting. Applications are provided to various well-known processes and settings from spatial statistics and statistical physics, including the comparison of two Lennard-Jones processes, hard core approximation of an area interaction process and the approximation of lattice processes by a continuous Gibbs process. Our proof of the main results is based on Stein's method. We construct an explicit coupling between two spatial birth-death processes to obtain Stein factors, and employ the Georgii-Nguyen-Zessin equation for the total bound.

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We present a comprehensive analytical study of radiative transfer using the method of moments and include the effects of non-isotropic scattering in the coherent limit. Within this unified formalism, we derive the governing equations and solutions describing two-stream radiative transfer (which approximates the passage of radiation as a pair of outgoing and incoming fluxes), flux-limited diffusion (which describes radiative transfer in the deep interior) and solutions for the temperature-pressure profiles. Generally, the problem is mathematically under-determined unless a set of closures (Eddington coefficients) is specified. We demonstrate that the hemispheric (or hemi-isotropic) closure naturally derives from the radiative transfer equation if energy conservation is obeyed, while the Eddington closure produces spurious enhancements of both reflected light and thermal emission. We concoct recipes for implementing two-stream radiative transfer in stand-alone numerical calculations and general circulation models. We use our two-stream solutions to construct toy models of the runaway greenhouse effect. We present a new solution for temperature-pressure profiles with a non-constant optical opacity and elucidate the effects of non-isotropic scattering in the optical and infrared. We derive generalized expressions for the spherical and Bond albedos and the photon deposition depth. We demonstrate that the value of the optical depth corresponding to the photosphere is not always 2/3 (Milne's solution) and depends on a combination of stellar irradiation, internal heat and the properties of scattering both in optical and infrared. Finally, we derive generalized expressions for the total, net, outgoing and incoming fluxes in the convective regime.

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The abundance of atmospheric oxygen and its evolution through Earth's history is a highly debated topic. The earliest change of the Mo concentration and isotope composition of marine sediments are interpreted to be linked to the onset of the accumulation of free O2 in Earth's atmosphere. The O2 concentration needed to dissolve significant amounts of Mo in water is not yet quantified, however. We present laboratory experiments on pulverized and surface-cleaned molybdenite (MoS2) and a hydrothermal breccia enriched in Mo-bearing sulphides using a glove box setup. Duration of an experiment was 14 days, and first signs of oxidation and subsequent dissolution of Mo compounds start to occur above an atmospheric oxygen concentration of 72 ± 20 ppmv (i.e., 2.6 to 4.6 × 10−4 present atmospheric level (PAL)). This experimentally determined value coincides with published model calculations supporting atmospheric O2 concentrations between 1 × 10−5 to 3 × 10−4 PAL prior to the Great Oxidation Event and sets an upper limit to the molecular oxygen needed to trigger Mo accumulation and Mo isotope variations recorded in sediments. In combination with the published Mo isotope composition of the rock record, this result implies an atmospheric oxygen concentration prior to 2.76 Ga of below 72 ± 20 ppmv.

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This paper presents some ideas about a new neural network architecture that can be compared to a Taylor analysis when dealing with patterns. Such architecture is based on lineal activation functions with an axo-axonic architecture. A biological axo-axonic connection between two neurons is defined as the weight in a connection in given by the output of another third neuron. This idea can be implemented in the so called Enhanced Neural Networks in which two Multilayer Perceptrons are used; the first one will output the weights that the second MLP uses to computed the desired output. This kind of neural network has universal approximation properties even with lineal activation functions. There exists a clear difference between cooperative and competitive strategies. The former ones are based on the swarm colonies, in which all individuals share its knowledge about the goal in order to pass such information to other individuals to get optimum solution. The latter ones are based on genetic models, that is, individuals can die and new individuals are created combining information of alive one; or are based on molecular/celular behaviour passing information from one structure to another. A swarm-based model is applied to obtain the Neural Network, training the net with a Particle Swarm algorithm.