987 resultados para soft-commutation techniques


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The structure and chemical environment of Cu in Cu/CeO2 catalysts synthesized by the solution combustion method have been investigated by X-ray diffraction (XRD), transmission electron microscopy (TEM), electron paramagnetic resonance (EPR) spectroscopy, X-ray photoelectron spectroscopy (XPS), cyclic voltammetry (CV), and extended X-ray fine structure (EXAFS) spectroscopy. High-resolution XRD studies of 3 and 5 atom % Cu/CeO2 do not show CuO lines in their respective patterns. The structure could be refined for the composition Ce1-xCuxO2-delta (x = 0.03 and 0.05; delta similar to 0.13 and 0.16) in the fluorite structure with 5-8% oxide ion vacancy. High-resolution TEM did not show CuO particles in 5 atom % Cu/CeO2. EPR as well as XPS studies confirm the presence of Cu2+ species in the CeO2 matrix. Redox potentials of Cu species in the CeO2 matrix are lower than those in CuO. EXAFS investigations of these catalysts show an average coordination number of 3 around the Cu2+ ion in the first shell at a distance of 1.96 Angstrom, indicating the O2- ion vacancy around the Cu2+ ion. The Cu-O bond length also decreases compared to that in CuO. The second and third shell around the Cu2+ ion in the catalysts are attributed to -Cu2+-O2--Cu2+ - at 2.92 Angstrom and -Cu2+-O2--Ce4+- at the distance of 3.15 Angstrom, respectively. The present results provide direct evidence for the formation of a Ce1-xCuxO2-delta type of solid solution phase having -square-Cu2+-O-Ce4+- kind of linkages.

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Visualization of fluids has wide applications in science, engineering and entertainment. Various methodologies Of visualizing fluids have evolved which emphasize on capturing different aspects of the fluids accurately. In this survey the existing methods for realistic visualization of fluids are reviewed. The approaches are classified based on the key concept they rely on for fluid modeling. This classification allows for easy selection of the method to be adopted for visualization given an application. It also enables identification of alternative techniques for fluid modeling.

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This paper introduces a scheme for classification of online handwritten characters based on polynomial regression of the sampled points of the sub-strokes in a character. The segmentation is done based on the velocity profile of the written character and this requires a smoothening of the velocity profile. We propose a novel scheme for smoothening the velocity profile curve and identification of the critical points to segment the character. We also porpose another method for segmentation based on the human eye perception. We then extract two sets of features for recognition of handwritten characters. Each sub-stroke is a simple curve, a part of the character, and is represented by the distance measure of each point from the first point. This forms the first set of feature vector for each character. The second feature vector are the coeficients obtained from the B-splines fitted to the control knots obtained from the segmentation algorithm. The feature vector is fed to the SVM classifier and it indicates an efficiency of 68% using the polynomial regression technique and 74% using the spline fitting method.

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The methods of design available for geocell-supported embankments are very few. Two of the earlier methods are considered in this paper and a third method is proposed and compared with them. The first method is the slip line method proposed by earlier researchers. The second method is based on slope stability analysis proposed by this author earlier and the new method proposed is based on the finite element analyses. In the first method, plastic bearing failure of the soil was assumed and the additional resistance due to geocell layer is calculated using a non-symmetric slip line field in the soft foundation soil. In the second method, generalpurpose slope stability program was used to design the geocell mattress of required strength for embankment using a composite model to represent the shear strength of geocell layer. In the third method proposed in this paper, geocell reinforcement is designed based on the plane strain finite element analysis of embankments. The geocell layer is modelled as an equivalent composite layer with modified strength and stiffness values. The strength and dimensions of geocell layer is estimated for the required bearing capacity or permissible deformations. These three design methods are compared through a design example.

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We compare the high energy behaviour of hadronic photon-photon cross-sections in different models. We find that the photon-photon cross-section appears to rise faster than the purely hadronic ones (proton-proton and proton-antiproton).

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Growing concern over the status of global and regional bioenergy resources has necessitated the analysis and monitoring of land cover and land use parameters on spatial and temporal scales. The knowledge of land cover and land use is very important in understanding natural resources utilization, conversion and management. Land cover, land use intensity and land use diversity are land quality indicators for sustainable land management. Optimal management of resources aids in maintaining the ecosystem balance and thereby ensures the sustainable development of a region. Thus sustainable development of a region requires a synoptic ecosystem approach in the management of natural resources that relates to the dynamics of natural variability and the effects of human intervention on key indicators of biodiversity and productivity. Spatial and temporal tools such as remote sensing (RS), geographic information system (GIS) and global positioning system (GPS) provide spatial and attribute data at regular intervals with functionalities of a decision support system aid in visualisation, querying, analysis, etc., which would aid in sustainable management of natural resources. Remote sensing data and GIS technologies play an important role in spatially evaluating bioresource availability and demand. This paper explores various land cover and land use techniques that could be used for bioresources monitoring considering the spatial data of Kolar district, Karnataka state, India. Slope and distance based vegetation indices are computed for qualitative and quantitative assessment of land cover using remote spectral measurements. Differentscale mapping of land use pattern in Kolar district is done using supervised classification approaches. Slope based vegetation indices show area under vegetation range from 47.65 % to 49.05% while distance based vegetation indices shoes its range from 40.40% to 47.41%. Land use analyses using maximum likelihood classifier indicate that 46.69% is agricultural land, 42.33% is wasteland (barren land), 4.62% is built up, 3.07% of plantation, 2.77% natural forest and 0.53% water bodies. The comparative analysis of various classifiers, indicate that the Gaussian maximum likelihood classifier has least errors. The computation of talukwise bioresource status shows that Chikballapur Taluk has better availability of resources compared to other taluks in the district.