996 resultados para region representation


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In this paper, taking the northern region of Changxing County for example, with ammonia nitrogen as a pollution assessment index, we used an improved export coefficient method for estimate polluting load of non-point source pollution (NSP) and the social pollution survey data in the study area to estimate point source pollution. By comparing the total pollution output and the national surface water environmental quality standards find that the whole study area achieves the second water quality standard. However, Jiapu Township exceeds the water quality standards seriously because of the superfluous point source pollution. The water quality of other Townships is good. Further analysis showed that different types of land use and proportions in the northern region of Changxing County have a significant impact on the non-point source pollution, the general law is farmland contributes the largest share of the non-point source pollution output, followed by residential area and bare land, besides, with the increase in the proportion of forest and the decrease of farmland and residential area, the non-point source pollution reduces gradually. © 2010 IEEE.

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We obtained four phases of land cover spatial data sets by interpreting MSS images of middle and late 1970s and three phases of TM images of late 1980s, 2004 and 2008 based on field investigation in Three Rivers' Source Region. We analyzed the temporal and spatial characteristics of land cover and macro ecological changes in Three Rivers' Source Region in Qinghai-Tibet plateau since middle and late 1970s. Indicated by land cover condition index change rate and land cover change index, land cover and macroscopical ecological condition degenerated (7090 period Zc -0.63, LCCI -0.58)-obviously degenerated (9004 period, Zc -0.94, LCCI -1.76)-slightly meliorated (0408 period, Zc 0.06, LCCI 0.33). This course was jointly driven by climate change, grassland stocking pressure and implement of ecological construction project.

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Subspace learning is the process of finding a proper feature subspace and then projecting high-dimensional data onto the learned low-dimensional subspace. The projection operation requires many floating-point multiplications and additions, which makes the projection process computationally expensive. To tackle this problem, this paper proposes two simple-but-effective fast subspace learning and image projection methods, fast Haar transform (FHT) based principal component analysis and FHT based spectral regression discriminant analysis. The advantages of these two methods result from employing both the FHT for subspace learning and the integral vector for feature extraction. Experimental results on three face databases demonstrated their effectiveness and efficiency.

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This paper presents a new region-based unified tensor level set model for image segmentation. This model introduces a three-order tensor to comprehensively depict features of pixels, e.g., gray value and the local geometrical features, such as orientation and gradient, and then, by defining a weighted distance, we generalized the representative region-based level set method from scalar to tensor. The proposed model has four main advantages compared with the traditional representative method as follows. First, involving the Gaussian filter bank, the model is robust against noise, particularly the salt-and pepper-type noise. Second, considering the local geometrical features, e. g., orientation and gradient, the model pays more attention to boundaries and makes the evolving curve stop more easily at the boundary location. Third, due to the unified tensor pixel representation representing the pixels, the model segments images more accurately and naturally. Fourth, based on a weighted distance definition, the model possesses the capacity to cope with data varying from scalar to vector, then to high-order tensor. We apply the proposed method to synthetic, medical, and natural images, and the result suggests that the proposed method is superior to the available representative region-based level set method.

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A model experiment was done to clear the formation mechanism of protective layers during combustion of polypropylene (PP)/organically modified montmorillonite (OMMT) nanocomposites. The investigation was focused on the effects of annealing temperature on the structural changes and protective layer formation. The decomposition of OMMT and degradation of PP/OMMT nanocomposites were characterized by means of thermogravimetric analysis (TGA). The structural evolution and composition change in the surface region of PP/OMMT nanocomposites during heating were monitored by means of X-ray photoelectron spectroscopy (XPS), ATR-FTIR and field emission scanning electron microscopy (FESEM).

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RE3+-activated alpha- and beta-CaAl2B2O7 (RE = Tb, Ce) were synthesized with the method of high-temperature solid-state reaction. Their VUV excitation and VUV-excited emission spectra are measured and discussed in the present article. The charge transfer band of Tb3+ and Ce3+ is respectively calculated to be at 151 +/- 2 and 159 +/- 3 nm. All the samples show an activator-independent excitation peak at about 175 nm and an emission peak at 350-360 nm ascribed to the host absorption and emission band, respectively.