981 resultados para antenna coupled resonator matching sections


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The current study reports the synthesis and properties of a novel isoindoline nitroxide contg. a benzophenone chromophore fused into the carbon framework. When exposed to UV light, rather than undergoing traditional benzophenone photochem. pathways, the presence of the nitroxide enables an energy transfer process whereby the nitroxide enters an excited state which induces an efficient hydrogen atom transfer from unactivated alkanes.

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Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

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Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

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GPR is widely used for ballast fouling identification, however, there are no robust guidelines to find the degree and type of fouling quantitatively. In this study, GPR studies were carried out on model and actual railway tracks using three ground coupled antennas and considering three fouling materials. Three ground coupled antennas viz., 100 MHz, 500 MHz and 800 MHz antennas were used for the initial survey and it was found that the 800 MHz ground coupled antenna is an optimum one to get quality results. Three major fouling materials viz., screened/broken ballast, coal and iron ore were used to construct prototype model sections, which were 1/2 of the actual Indian broad-gauge railway track. A separate model section has been created for each degree and type of fouling and GPR surveys were carried out. GPR study shows that increasing the fouling content results in a decrease in the Electromagnetic Wave (EMW) velocity and an increase in the dielectric constant. EMW velocity of ballast fouled with screened ballast was found to be more than coal fouled ballast and iron ore fouled ballast at any degree of fouling and EMW velocity of iron ore fouled ballast was found to be less than coal and screen ballast fouled ballast. Dielectric constant of iron ore fouled ballast was found to be higher than coal and screen ballast fouled ballast for all degrees of fouling. Average slope of the trend line of screen ballast fouled section is low (25.6 degrees), coal fouled ballast is medium (27.8 degrees) and iron ore fouled ballast is high (47.6 degrees). (C) 2016 Elsevier B.V. All rights reserved.

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Coupled Monte Carlo depletion systems provide a versatile and an accurate tool for analyzing advanced thermal and fast reactor designs for a variety of fuel compositions and geometries. The main drawback of Monte Carlo-based systems is a long calculation time imposing significant restrictions on the complexity and amount of design-oriented calculations. This paper presents an alternative approach to interfacing the Monte Carlo and depletion modules aimed at addressing this problem. The main idea is to calculate the one-group cross sections for all relevant isotopes required by the depletion module in a separate module external to Monte Carlo calculations. Thus, the Monte Carlo module will produce the criticality and neutron spectrum only, without tallying of the individual isotope reaction rates. The onegroup cross section for all isotopes will be generated in a separate module by collapsing a universal multigroup (MG) cross-section library using the Monte Carlo calculated flux. Here, the term "universal" means that a single MG cross-section set will be applicable for all reactor systems and is independent of reactor characteristics such as a neutron spectrum; fuel composition; and fuel cell, assembly, and core geometries. This approach was originally proposed by Haeck et al. and implemented in the ALEPH code. Implementation of the proposed approach to Monte Carlo burnup interfacing was carried out through the BGCORE system. One-group cross sections generated by the BGCORE system were compared with those tallied directly by the MCNP code. Analysis of this comparison was carried out and led to the conclusion that in order to achieve the accuracy required for a reliable core and fuel cycle analysis, accounting for the background cross section (σ0) in the unresolved resonance energy region is essential. An extension of the one-group cross-section generation model was implemented and tested by tabulating and interpolating by a simplified σ0 model. A significant improvement of the one-group cross-section accuracy was demonstrated.