• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.36 no.2
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• pp.47-53
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• 2004

In this experiment the effects of the packing structure of pigment on the surface characteristics (smoothness and gloss) of coated paper are studied. Four different kinds of inorganic pigments(clay), ground calcium carbonate(GCC), two of precipitated calcium carbonates(PCC), and two organic pigments(solid bead and hollow type) were used. The method of measuring the relative sediment volume(RSV) was used to analyze the packing structure of coating layer. The relative sediment volume was measured, using the pressure dewatering dry-cake method(PDDM) and centrifuge method. Also, the particle size distribution of coating pigment was determined. The results showed that small amount of organic pigment, added to inorganic pigment, improved smoothness and its effect was greater when GCC was used as inorganic pigment. The efficiency of organic pigment depended upon the inorganic pigment since the organic pigment is packed in the pores formed by the inorganic pigment.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.44 no.3
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• pp.1-8
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• 2012

The effects of several factors including organic pigment blending and calending conditions on the surface and optical properties of coated paper were investigated. When clay and calcium carbonate are blended in the ratio of 7 to 3, highest smoothness and relative sediment volume were obtained. When organic pigments were added to the mixture of clay and calcium carbonate, the relative sediment volume did not changed significantly. However, when organic pigments were added to calcium carbonate, sheet gloss and smoothness were improved, and showed the better results than that obtained from the mixture of organic pigment and clay. When organic pigment is blended with clay, the particles of organic pigment are buried in the packing structure of coating layer. However, the particle shape of calcium carbonate is quite different from that of clay, and the aspect ratio of calcium carbonate is similar to that of organic pigment. Thus organic pigment particles are not buried and improved effectively the physical characteristics of coating layer. When the hollow sphere pigment was blended, opacity and sheet gloss were improved significantly. Even though the coating color applied was reduced, the similar level of opacity was maintained. Also, if particle size and void volume are increased, gloss is improved, because coating layer is easily transformed in calendering. Therefore, even though lower pressure was applied during calendering, the smoothness of surface of coating layer was improved, and the decrease of void volume in coating layer was reduced, and the quality of coated sheet can be improved.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.489-492
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• 2003

In this paper, we propose an iterative mixed norm image restoration algorithm using multi regularization parameters. A functional which combines the regularized l$_2$ norm functional and the regularized l$_4$ functional is proposed. The smoothness of each functional is determined by the regularization parameters. Also, a regularization parameter is used to determine the relative importance between the regularized l$_2$ functional and the regularized l$_4$ functional. An iterative algorithm is utilized for obtaining a solution and its convergence is analyzed.

• The Pure and Applied Mathematics
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• v.1 no.1
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• pp.19-24
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• 1994

Let P be a probability measure on the real line with Lebesque-density f. The usual estimator of the distribution function (≡df) of P for the sample $\chi$$_1$,…, $\chi$$\_$n/ is the empirical df: F$\_$n/(t)=(equation omitted). But this estimator does not take into account the smoothness of F, that is, the existence of a density f. Therefore, one should expect that an estimator which is better adapted to this situation beats the empirical df with respect to a reasonable measure of performance.(omitted)

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.149-157
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• 2010

The purpose of this study is to analyse characteristics of roughness coefficient based on bed-material size of the gravel-bed rivers using field data obtained from nine domestic rivers. Roughness coefficient is calculated using Manning's equation. Roughness coefficient decreases with increasing discharge, but above a certain discharge, it tends to be constant. Similarly, roughness coefficient shows reverse relationship with relative smoothness (R/D). The regression equation adopting theoretically derived value of 2.03 as log coefficient indicates close similarity with the previous equation proposed by Limerinos (1970). Roughness coefficient values converged above certain discharges lie in the range from 0.024 to 0.045. From them, empirical equations based only on bed-material size are derived and compared with those suggested by the previous studies.

• International Journal of Concrete Structures and Materials
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• v.6 no.2
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• pp.101-110
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• 2012

This paper focuses on the finite element (FE) response sensitivity and reliability analyses considering smooth constitutive material models. A reinforced concrete frame is modeled for FE sensitivity analysis followed by direct differentiation method under both static and dynamic load cases. Later, the reliability analysis is performed to predict the seismic behavior of the frame. Displacement sensitivity discontinuities are observed along the pseudo-time axis using non-smooth concrete and reinforcing steel model under quasi-static loading. However, the smooth materials show continuity in response sensitivity at elastic to plastic transition points. The normalized sensitivity results are also used to measure the relative importance of the material parameters on the structural responses. In FE reliability analysis, the influence of smoothness behavior of reinforcing steel is carefully noticed. More efficient and reasonable reliability estimation can be achieved by using smooth material model compare with bilinear material constitutive model.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.399-402
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• 2000

In this paper, we present a regularized mixed norm multichannel image restoration algorithm. The problem of multichannel restoration using both within- and between- channel deterministic information is considered. For each channel a functional which combines the least mean squares (LMS), the least mean fourth(LMF), and a smoothing functional is proposed, We introduce a mixed norm parameter that controls the relative contribution between the LMS and the LMF, and a regularization parameter that defines the degree of smoothness of the solution, both updated at each iteration according to the noise characteristics of each channel. The novelty of the proposed algorithm is that no knowledge of the noise distribution for each channel is required, and the parameters mentioned above are adjusted based on the partially restored image.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.10 no.1
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• pp.46-53
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• 2006

Magnetocardiography provides non-invasive three-dimensional electroanatomical imaging of cardiac electrophysiology. The aim of this study is to find the index for using the indicator of magnetocardiography. An object of this study is 214 papers registered on www.pubmed.com. The index used in magnetocardiography is the interval, morphology, amplitude and integrals of QRS complex, P wave, T wave. The current density and electric field map are used, too. A new try of the index is LAS, W-HEAD, Relative Smoothness index(RS index) etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11C
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• pp.1073-1078
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• 2007

In this paper, we propose an iterative mixed norm image restoration algorithm using multi regularization parameters. A functional which combines the regularized $l_2$ norm functional and the regularized $l_4$ norm functional is proposed to efficiently remove arbitrary noise. The smoothness of each functional is determined by the regularization parameters. Also, a regularization parameter is used to determine the relative importance between the regularized $l_2$ norm functional and the regularized $l_4$ norm functional using kurtosis. An iterative algorithm is utilized for obtaining a solution and its convergence is analyzed. Experimental results demonstrate the capability of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.2C
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• pp.272-282
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• 2004

This paper introduces a regularized mixed norm multi-channel image restoration algorithm using both within-and between- channel deterministic information. For each channel a functional which combines the least mean squares (LMS), the least mean fourth (LMF), and a smoothing functional is proposed. We introduce a mixed norm parameter that controls the relative contribution between the LMS and the LMF, and a regularization parameter defining the degree of smoothness of the solution, where both parameters are updated at each iteration according to the noise characteristics of each channel. The novelty of the proposed algorithm is that no knowledge of the noise distribution for each channel is required and that the parameters mentioned above are adjusted based on the partially restored image.