971 resultados para Homogeneous Kernels
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Stellar kinematic groups are kinematical coherent groups of stars that might have a common origin. These groups are dispersed throughout the Galaxy over time by the tidal effects of both Galactic rotation and disc heating, although their chemical content remains unchanged. The aim of chemical tagging is to establish that the abundances of every element in the analysis are homogeneus among the members. We study the case of the Hyades Supercluster to compile a reliable list of members (FGK stars) based on our chemical tagging analysis. For a total of 61 stars from the Hyades Supercluster, stellar atmospheric parameters (T_eff, log g, ξ, and [Fe/H]) are determined using our code called StePar, which is based on the sensitivity to the stellar atmospheric parameters of the iron EWs measured in the spectra. We derive the chemical abundances of 20 elements and find that their [X/Fe] ratios are consistent with Galactic abundance trends reported in previous studies. The chemical tagging method is applied with a carefully developed differential abundance analysis of each candidate member of the Hyades Supercluster, using a well-known member of the Hyades cluster as a reference (vB 153). We find that only 28 stars (26 dwarfs and 2 giants) are members, i.e. that 46% of our candidates are members based on the differential abundance analysis. This result confirms that the Hyades Supercluster cannot originate solely from the Hyades cluster.
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A Rh phosphine complex, derived from the Wilkinson’s catalyst, has been immobilized by ion-exchange on the ammonium form of a Al-MCM-41 sample. Ammonium ions have been exchanged by cholamine ions, which act as an amine ligand, and then the Wilkinson’s catalyst has been immobilized by substitution of a phosphine ligand by the anchored amine. This is a novel immobilization procedure, as a ligand, instead of the whole complex, is tethered to the support by ion exchange. The obtained hybrid catalyst has been characterized by Elemental Analysis, DRIFTS and XPS. The quantitative exchange of ammonium by cholamine and coordination of Rh to amines has been observed. Most of the anchored Rh is considered to be coordinated to the ligand tethered to the support and a small proportion seems to be interacting with the protonated ligand or with the support surface. The catalyst has been tested in the hydrogenation of cyclohexene and in the hydroformylation of 1-octene. In the first case the catalyst is active and reusable, while a strong Rh leaching takes place in the second one.
Growing Neural Gas approach for obtaining homogeneous maps by restricting the insertion of new nodes
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The Growing Neural Gas model is used widely in artificial neural networks. However, its application is limited in some contexts by the proliferation of nodes in dense areas of the input space. In this study, we introduce some modifications to address this problem by imposing three restrictions on the insertion of new nodes. Each restriction aims to maintain the homogeneous values of selected criteria. One criterion is related to the square error of classification and an alternative approach is proposed for avoiding additional computational costs. Three parameters are added that allow the regulation of the restriction criteria. The resulting algorithm allows models to be obtained that suit specific needs by specifying meaningful parameters.
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Preparation of homogeneous CNT coatings in insulating silica capillary tubes is carried out by an innovative electrochemically-assisted method in which the driving force for the deposition is the change in pH inside the confined space between the inner electrode and the capillary walls. This method represents a great advancement in the development of CNT coatings following a simple, cost-effective methodology.
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This note provides an approximate version of the Hahn–Banach theorem for non-necessarily convex extended-real valued positively homogeneous functions of degree one. Given p : X → R∪{+∞} such a function defined on the real vector space X, and a linear function defined on a subspace V of X and dominated by p (i.e. (x) ≤ p(x) for all x ∈ V), we say that can approximately be p-extended to X, if is the pointwise limit of a net of linear functions on V, every one of which can be extended to a linear function defined on X and dominated by p. The main result of this note proves that can approximately be p-extended to X if and only if is dominated by p∗∗, the pointwise supremum over the family of all the linear functions on X which are dominated by p.
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Since the beginning of 3D computer vision problems, the use of techniques to reduce the data to make it treatable preserving the important aspects of the scene has been necessary. Currently, with the new low-cost RGB-D sensors, which provide a stream of color and 3D data of approximately 30 frames per second, this is getting more relevance. Many applications make use of these sensors and need a preprocessing to downsample the data in order to either reduce the processing time or improve the data (e.g., reducing noise or enhancing the important features). In this paper, we present a comparison of different downsampling techniques which are based on different principles. Concretely, five different downsampling methods are included: a bilinear-based method, a normal-based, a color-based, a combination of the normal and color-based samplings, and a growing neural gas (GNG)-based approach. For the comparison, two different models have been used acquired with the Blensor software. Moreover, to evaluate the effect of the downsampling in a real application, a 3D non-rigid registration is performed with the data sampled. From the experimentation we can conclude that depending on the purpose of the application some kernels of the sampling methods can improve drastically the results. Bilinear- and GNG-based methods provide homogeneous point clouds, but color-based and normal-based provide datasets with higher density of points in areas with specific features. In the non-rigid application, if a color-based sampled point cloud is used, it is possible to properly register two datasets for cases where intensity data are relevant in the model and outperform the results if only a homogeneous sampling is used.
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The FANOVA (or “Sobol’-Hoeffding”) decomposition of multivariate functions has been used for high-dimensional model representation and global sensitivity analysis. When the objective function f has no simple analytic form and is costly to evaluate, computing FANOVA terms may be unaffordable due to numerical integration costs. Several approximate approaches relying on Gaussian random field (GRF) models have been proposed to alleviate these costs, where f is substituted by a (kriging) predictor or by conditional simulations. Here we focus on FANOVA decompositions of GRF sample paths, and we notably introduce an associated kernel decomposition into 4 d 4d terms called KANOVA. An interpretation in terms of tensor product projections is obtained, and it is shown that projected kernels control both the sparsity of GRF sample paths and the dependence structure between FANOVA effects. Applications on simulated data show the relevance of the approach for designing new classes of covariance kernels dedicated to high-dimensional kriging.
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The spatial data set delineates areas with similar environmental properties regarding soil, terrain morphology, climate and affiliation to the same administrative unit (NUTS3 or comparable units in size) at a minimum pixel size of 1km2. The scope of developing this data set is to provide a link between spatial environmental information (e.g. soil properties) and statistical data (e.g. crop distribution) available at administrative level. Impact assessment of agricultural management on emissions of pollutants or radiative active gases, or analysis regarding the influence of agricultural management on the supply of ecosystem services, require the proper spatial coincidence of the driving factors. The HSU data set provides e.g. the link between the agro-economic model CAPRI and biophysical assessment of environmental impacts (updating previously spatial units, Leip et al. 2008), for the analysis of policy scenarios. Recently, a statistical model to disaggregate crop information available from regional statistics to the HSU has been developed (Lamboni et al. 2016). The HSU data set consists of the spatial layers provided in vector and raster format as well as attribute tables with information on the properties of the HSU. All input data for the delineation the HSU is publicly available. For some parameters the attribute tables provide the link between the HSU data set and e.g. the soil map(s) rather than the data itself. The HSU data set is closely linked the USCIE data set.
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Includes bibliographical references (20).
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Supported by: Contract AT (11-1)-1018 with the U.S. Atomic Energy Commission and the Advanced Research Projects Agency.
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"Other issues of this report may bear the number BAW-7."
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Photocopy of microfilm. Springfield, Va. : National Technical Information Service, [1979]
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"ONR Contract No. Nonr-1055(00)."
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Mode of access: Internet.
Regular singular points of a system of homogeneous linear differential equations of the first order.
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"From Proceedings of the American Academy of Arts and Sciences, v.38, no. 9, Oct. 1902."