112 resultados para MULTIMEDIA CONTENT ADAPTATION


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Poly(vinyl butyral) - MMT clay nanocomposites were synthesized in situ with three different degrees of acetalization and with varying clay content for each vinyl butyral polymer ratio. The clay nano-platelet galleries were expanded, as determined by X-ray diffraction and TEM analysis. The glass transition temperature of the polymer nanocomposites were found to be similar to 56 degrees C and similar to 52 degrees C for the neat polymer and the 4% clay loaded samples, respectively. The 4 wt% clay loaded film showed higher strength and low strain to failure. The dynamic mechanical analysis also confirmed the improved stability of the matrix. The matrix with 0.5 butyral to alcohol ratio for 4 wt% clay exhibited good water vapor transmission compared to all other compositions. The encapsulated devices with 2.5 and 4 wt% clay loaded films increases the device life time and the efficiencies of these films were 50% higher than their encapsulated pristine polymer films. (C) 2015 Elsevier Ltd. All rights reserved.

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A strong influence of Ni content on the diffusion-controlled growth of the (Cu,Ni)(3)Sn and (Cu,Ni)(6)Sn-5 phases by coupling different Cu(Ni) alloys with Sn in the solid state is reported. The continuous increase in the thickness ratio of (Cu,Ni)(6)Sn-5 to (Cu,Ni)(3)Sn with the Ni content is explained by combined kinetic and thermodynamic arguments as follows: (i) The integrated interdiffusion coefficient does not change for the (Cu,Ni)(3)Sn phase up to 2.5 at.% Ni and decreases drastically for 5 at.% Ni. On the other hand, there is a continuous increase in the integrated interdiffusion coefficient for (Cu,Ni)(6)Sn-5 as a function of increasing Ni content. (ii) With the increase in Ni content, driving forces for the diffusion of components increase for both components in both phases but at different rates. However, the magnitude of these changes alone is not large enough to explain the high difference in the observed growth rate of the product phases because of Ni addition. (iv) Kirkendall marker experiments indicate that the Cu6Sn5 phase grows by diffusion of both Cu and Sn in the binary case. However, when Ni is added, the growth is by diffusion of Sn only. (v) Also, the observed grain refinement in the Cu6Sn5 phase with the addition of Ni suggests that the grain boundary diffusion of Sn may have an important role in the observed changes in the growth rate.

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Diffusion controlled growth rate of V3Ga in the Cu(Ga)/V system changes dramatically because of a small change in Ga content in Cu(Ga). One atomic percent increase from 15 to 16 leads to more than double the product phase layer thickness and a decrease in activation energy from 255 to 142 kJ/mol. Kirkendall marker experiment indicates that V3Ga grows because of diffusion of Ga. Role of different factors influencing the diffusion rate of Ga and high growth rate of V3Ga are discussed. (C) 2015 Elsevier Ltd. All rights reserved.

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Image and video analysis requires rich features that can characterize various aspects of visual information. These rich features are typically extracted from the pixel values of the images and videos, which require huge amount of computation and seldom useful for real-time analysis. On the contrary, the compressed domain analysis offers relevant information pertaining to the visual content in the form of transform coefficients, motion vectors, quantization steps, coded block patterns with minimal computational burden. The quantum of work done in compressed domain is relatively much less compared to pixel domain. This paper aims to survey various video analysis efforts published during the last decade across the spectrum of video compression standards. In this survey, we have included only the analysis part, excluding the processing aspect of compressed domain. This analysis spans through various computer vision applications such as moving object segmentation, human action recognition, indexing, retrieval, face detection, video classification and object tracking in compressed videos.

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The serotonin(1A) receptor belongs to the superfamily of G protein-coupled receptors (GPCRs) and is a potential drug target in neuropsychiatric disorders. The receptor has been shown to require membrane cholesterol for its organization, dynamics and function. Although recent work suggests a close interaction of cholesterol with the receptor, the structural integrity of the serotonin(1A) receptor in the presence of cholesterol has not been explored. In this work, we have carried out all atom molecular dynamics simulations, totaling to 3s, to analyze the effect of cholesterol on the structure and dynamics of the serotonin(1A) receptor. Our results show that the presence of physiologically relevant concentration of membrane cholesterol alters conformational dynamics of the serotonin(1A) receptor and, on an average lowers conformational fluctuations. Our results show that, in general, transmembrane helix VII is most affected by the absence of membrane cholesterol. These results are in overall agreement with experimental data showing enhancement of GPCR stability in the presence of membrane cholesterol. Our results constitute a molecular level understanding of GPCR-cholesterol interaction, and represent an important step in our overall understanding of GPCR function in health and disease.

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Vulnerability of communities and natural ecosystems, to potential impacts of climate change in developing countries like India, and the need for adaptation are rapidly emerging as central issues in the debate around policy responses to climate change. The present study presents an approach to identify and prioritize the most vulnerable districts, villages and households in Karnataka State, through a multi-scale assessment of inherent vulnerability to current climate variability. It also identifies the drivers of inherent vulnerability, thereby providing a tool for developing and mainstreaming adaptation strategies, in ongoing developmental or dedicated adaptation programmes. The multi-scale assessment was made for all 30 districts at the state level in Karnataka, about 1220 villages in Chikballapur district, and at the household level for two villages - Gundlapalli and Saddapalli - in Bagepalli taluk of Chikballapur district. At the district, village and household levels, low levels of education and skills are the dominant factors contributing to vulnerability. At the village and household level, the lack of income diversification and livelihood support institutions are key drivers of vulnerability. The approach of multi-scale vulnerability assessment facilitates identification and prioritization of the drivers of vulnerability at different scales, to focus adaptation interventions to address these drivers.

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The utility of canonical correlation analysis (CCA) for domain adaptation (DA) in the context of multi-view head pose estimation is examined in this work. We consider the three problems studied in 1], where different DA approaches are explored to transfer head pose-related knowledge from an extensively labeled source dataset to a sparsely labeled target set, whose attributes are vastly different from the source. CCA is found to benefit DA for all the three problems, and the use of a covariance profile-based diagonality score (DS) also improves classification performance with respect to a nearest neighbor (NN) classifier.