• Publications of The Korean Astronomical Society
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• v.15 no.spc2
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• pp.65-71
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• 2000

We have investigated the numerical methods to calculate model atmosphere for the analysis of spectral lines emitted from the sun and stars. Basic equations used in our calculations are radiative transfer, statistical equilibrium and charge-particle conservations. Transfer equation has been solved to get emitting spectral line profile as an initial value problem using Adams-Bashforth-Moulton method with accuracy as high as 12th order. And we have calculated above non linear differential equations simultaneously as a boundary value problem by finite difference method of 3 points approximation through Feautrier elimination scheme. It is found that all computing programs coded by above numerical methods work successfully for our model atmosphere.

• Communications for Statistical Applications and Methods
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• v.24 no.1
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• pp.1-13
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• 2017

This manuscript summarized advances in bootstrap methods for long-range dependent time series data. The stationary linear long-memory process is briefly described, which is a target process for bootstrap methodologies on time-domain and frequency-domain in this review. We illustrate time-domain bootstrap under long-range dependence, moving or non-overlapping block bootstraps, and the autoregressive-sieve bootstrap. In particular, block bootstrap methodologies need an adjustment factor for the distribution estimation of the sample mean in contrast to applications to weak dependent time processes. However, the autoregressive-sieve bootstrap does not need any other modification for application to long-memory. The frequency domain bootstrap for Whittle estimation is provided using parametric spectral density estimates because there is no current nonparametric spectral density estimation method using a kernel function for the linear long-range dependent time process.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1203-1206
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• 1998

Considerable research in the last three decades has examined the problem of enhancement of speech degraded by additive background noise. We compare traditional methods such as spectral subtraction and Wiener filter, recently proposed psychoacoustic model based methods such as perceptual filter and noise suppression in EVRC in terms of performance and complexity.

• Journal of KIISE
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• v.43 no.6
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• pp.686-691
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• 2016

In this paper, we introduced the adaptive spectral co-clustering, a spectral clustering for multiview data, especially data with more than three views. In the adaptive spectral co-clustering, the performance is improved by sharing information from diverse views. For the efficiency in information sharing, a co-training approach is adopted. In the co-training step, a set of parameters are estimated to make all views in data maximally independent, and then, information is shared with respect to estimated parameters. This co-training step increases the efficiency of information sharing comparing with ordinary feature concatenation and co-training methods that assume the independence among views. The adaptive spectral co-clustering was evaluated with synthetic dataset and multi lingual document dataset. The experimental results indicated the efficiency of the adaptive spectral co-clustering with the performances in every iterations and similarity matrix generated with information sharing.

• Journal of the Optical Society of Korea
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• v.20 no.4
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• pp.515-523
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• 2016

Spectral reflectance is sparse in space, and while the traditional spectral-reconstruction algorithm does not make full use of this characteristic sparseness, the compressive sensing algorithm can make full use of it. In this paper, on the basis of analyzing compressive sensing based on the orthogonal matching pursuit algorithm, a new algorithm based on the Dice matching criterion is proposed. The Dice similarity coefficient is introduced, to calculate the correlation coefficient of the atoms and the residual error, and is used to select the atoms from a library. The accuracy of Spectral reconstruction based on the pseudo-inverse method, Wiener estimation method, OMP algorithm, and DOMP algorithm is compared by simulation on the MATLAB platform and experimental testing. The result is that spectral-reconstruction accuracy based on the DOMP algorithm is higher than for the other three methods. The root-mean-square error and color difference decreases with an increasing number of principal components. The reconstruction error decreases as the number of iterations increases. Spectral reconstruction based on the DOMP algorithm can improve the accuracy of color-information replication effectively, and high-accuracy color-information reproduction can be realized.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.19 no.1
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• pp.1-7
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• 2009

To establish the Fourier-Transform Infra-Red spectrophotometry(FTIR) Direct-On-Filter(DOF) technique as a useful analytical method for quartz in respirable dust samples, an influence of the kaolinite should be corrected. Respirable dust, created in a dust chamber containing the standard material of quartz and kaolinite were collected using a cyclone equipped with a 25 mm, $0.8\;{\mu}m$ pore size DM filter as a collection medium. This study was designed to compare three methods of correction for kaolinite when quantifying the content of quartz, including the least square, the optimum choice and the spectral subtraction methods. The content of quartz in the respirable dust samples was overestimated by 6.2% when mixed with kaolinite(35.5% by weight). The content of quartz containing kaolinite(72.8% by weight) were overestimated by 32%. The spectral subtraction method underestimated the quartz content by 1.5%, while the other two correction methods, the optimum choice and the least square method, overestimated the quartz content by 1.9% to 6.4% and 0.04 to 1.1%, respectively. The results of this study are suggested that, when correcting for effects of kaolinite on quantitative analysis of quartz in respirable dust by FTIR direct-on-filter method, the least square method produce the most unbiased results be compared with those of other correction methods.

• Speech Sciences
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• v.10 no.2
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• pp.77-84
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• 2003

In this research, we seek the beginning of the speech and detect the stationary speech region using lip information. Performing running average of the estimated speech signal in the stationary region, we reduce the effect of musical noise which is inherent to the conventional MlMSE (Minimum Mean Square Error) speech enhancement algorithm. In addition to it, SFM (Spectral Flatness Measure) is incorporated to reduce the speech signal estimation error due to speaking habit and some lacking lip information. The proposed algorithm with Wiener filtering shows the superior performance to the conventional methods according to MOS (Mean Opinion Score) test.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.10A
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• pp.1764-1771
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• 2001

It has developed a PCM signal acquisition(PCMA) system which can analyze status of signals in order to establish rapid diagnosing in TDX-families signaling service equipment. We develop the quick Fourier transform(QFT) for length 2$\^$M/ data to analyze the power spectral of the PCMA system. This algorithm can reduces the number of floating-point operations necessary to compute the DFT by a factor of two or four over direct methods or Goertzels method for prime lengths. In the experimental results, the system classifies the type of signals and finally discriminates the digit.

• Journal of the Korean Chemical Society
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• v.57 no.6
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• pp.721-725
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• 2013

Reaction between 2-pyridinecarboxylic acid (Hpic) and $K_3[Cr(O_2)_4]$ give complex $[Cr(pic)_3].H_2O$ (1) which is characterized by elemental analysis and spectroscopic methods (FT-IR, Raman) and X-ray crystallography. In the crystal structure of 1, chromium atom with coordinated by three nitrogen and three oxygen atoms has a distorted octahedral geometry. Also a water molecule is incorporated in crystal network. Each water molecule acts as hydrogen bond bridging and connects two adjacent complexes by two $O-H{\cdots}O$ hydrogen bonds.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.04a
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• pp.24-30
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• 1990

An improved algorithm for simulation of multi-variate random processes has been presented. It is based on the spectral representation method. The conventional methods give sample time histories which satisfy the target spectral density matrix only in the sense of ensemble average. However, the present method can generate sample functions which satisfy the target spectra in the ergodic sense. Example analysis is given for the simulation of earthquake accelerations with three components.