• Journal of Information Processing Systems
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• v.19 no.2
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• pp.232-239
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• 2023

Aiming at the poor compression quality of traditional image compression coding (ICC) algorithm, a multi-description ICC algorithm based on depth learning is put forward in this study. In this study, first an image compression algorithm was designed based on multi-description coding theory. Image compression samples were collected, and the measurement matrix was calculated. Then, it processed the multi-description ICC sample set by using the convolutional self-coding neural system in depth learning. Compressing the wavelet coefficients after coding and synthesizing the multi-description image band sparse matrix obtained the multi-description ICC sequence. Averaging the multi-description image coding data in accordance with the effective single point's position could finally realize the compression coding of multi-description images. According to experimental results, the designed algorithm consumes less time for image compression, and exhibits better image compression quality and better image reconstruction effect.

• Analytical Science and Technology
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• v.12 no.2
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• pp.130-135
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• 1999

A graphite furnace atomic absorption spectrometry (GFAAS) with matrix modification has been used to determine trace amounts of arsenic, lead and selenium in rice flour samples. A mixed solution of palladium and magnesium nitrate was used as a matrix modifier to convert the analyte elements into a phase of higher thermostability and to increase the volatility of concomitants in graphite furnace. Matrix modification effects by the mixed solution were investigated for several elements (As, Cd, Cu, Pb, Se, Zn). It has been found that the matrix modifier substantially increase the pyrolysis and atomization temperature, and absorbance for As, Pb and Se. The concentration of As, Pb and Se in rice flour samples were determined by standard addition method with Zeeman background correction after microwave acid digestion. In this method the characteristic concentrations of As, Pb and Se are 26 ng/g, 18 ng/g, 24 ng/g on the basis of dry sample respectively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.239-247
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• 2018

Adaptive Beamforming (ABF) algorithm, which is a typical jammer suppression algorithm, guarantees the performance on the assumption that the jamming characteristics of the TDS (Training Data Sample) are stationary, which are obtained immediately before and after transmitting the pulse signal. Therefore, effective jammer suppression can not be expected when the jamming characteristics are non-stationary. In this paper, we propose a new jammer suppression algorithm, of which power spectrum fluctuates fast. In this case, we assume that the location of the jammer station is fixed during the processing time. By applying the MPM (Matrix Pencil Method) to the jamming signal in TDS, we can estimate jammer parameters such as power and incident angle, of which the power will vary fast in time or range bins after TDS. Though we assume that the jammer station is fixed, the estimated jammer's incident angle has an error due to the noise, which degrades the performance of the jammer suppression as the jammer power increases fast. Therefore, the jammer's incident angle should be re-estimated at each range bin after TDS. By using the re-estimated jammer's incident angle, we can construct new covariance matrix under the non-stationary jamming environment. Then, the optimum weight for the jammer suppression is obtained by inversing matrix estimation method based on the matrix projection with the estimated jammer parameters as variables. To verify the performance of the proposed algorithm, the SINR (signal-to-interference plus noise ratio) loss of the proposed algorithm is compared with that of the conventional ABF algorithm.

• Analytical Science and Technology
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• v.5 no.4
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• pp.349-358
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• 1992

The direct determination of lead in the whole-blood by graphite furnace atomic absorption spectrometric analysis was carried out by using the sample which was diluted five-fold with 1% Triton X-100. Matrix modification was tried to remove the interferences of blood matrix and also to get the optimum analytical condition. Good agreement with certificated values in reference materials(bovine blood) supplied by comparison program in Japan was obstained when 1% $(NH_4)_2HPO_4$ as matrix modifier and ashing temperature, $700^{\circ}C$ were used or 1% $(NH_4)_2HPO_4$ and 0.1% $PdCl_2$ as matrix modifier and ashed at $700^{\circ}C$. Standard deviations were appeared as 2.2~6.3% for 1% $(NH_4)_2HPO_4$ and 3.1~9.1% for 1% $(NH_4)_2HPO_4$ and 0.1% $PdCl_2$ in the range of $31{\sim}624{\mu}gPb/l$.

• Journal of Korean Society on Water Environment
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• v.22 no.2
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• pp.271-276
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• 2006

The outbreak cases of Cryptosporidium or Giardia from drinking water in abroad have drawn attentions on the public health. It is well known that Cryptosporidium is the most resistant organism against chlorine disinfection. To guesstimate the levels of Cryptosporidium and Giardia in Korean surface water, 1~2 samples from 22 drinking water sources in four Korean major rivers of Han, Keum, Nakdong, and Youngsan were monitored. In addition, two sites in Kyunganchon, a contaminated river were monitored for comparison. In source waters, detection rates of Cryptosporidium and Giardia were 15% (6/39) and 21% (5/24) with the range of 1~3 oocysts/10 L and 1~6 cysts/10 L, respectively. In Kyunganchon, they were 60% (6/10) and 70% (7/10) in the range of 1~9 oocysts/10 L and 10~72 cysts/10 L, respectively. When one of the source waters in Han river was monitored monthly, Cryptosporidium were found mostly in cold season. Matrix of the samples gave influence on the recoveries of the spiked protozoa. The recoveries of both Cryptosporidium and Giardia increased in the samples of Kyunganchon, known as contaminated area. However, protozoan recovery did not show significant relation with turbidity, the index of matrix contamination, which implies that there are additional unveiled features of matrix affecting the recoveries of the protozoa. The protozoan distribution in Kyunganchon showed significant relations with Cl. perfringens, anaerobic and spore forming indicator bacteria of fecal contamination by regression analysis, but not with turbidity, the general indicator of water quality.

• Nuclear Engineering and Technology
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• v.46 no.2
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• pp.147-158
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• 2014

In order to investigate how the microstructure of fuel/matrix-interaction (FMI) layers change during irradiation, different U-7Mo dispersion fuel plates have been irradiated to high fission density and then characterized using scanning electron microscopy (SEM). Specifially, samples from irradiated U-7Mo dispersion fuel elements with pure Al, Al-2Si and AA4043 (~4.5 wt.%Si) matrices were SEM characterized using polished samples and samples that were prepared with a focused ion beam (FIB). Features not observable for the polished samples could be captured in SEM images taken of the FIB samples. For the Al matrix sample, a relatively large FMI layer develops, with enrichment of Xe at the FMI layer/Al matrix interface and evidence of debonding. Overall, a significant penetration of Si from the FMI layer into the U-7Mo fuel was observed for samples with Si in the Al matrix, which resulted in a change of the size (larger) and shape (round) of the fission gas bubbles. Additionally, solid fission product phases were observed to nucleate and grow within these bubbles. These changes in the localized regions of the microstructure of the U-7Mo may contribute to changes observed in the macroscopic swelling of fuel plates with Al-Si matrices.

• Safety and Health at Work
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• v.10 no.2
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• pp.196-204
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• 2019

Background: Liquid chromatography-tandem mass spectrometry (LC-MSMS) for simultaneous analysis of multiple microbial secondary metabolites (MSMs) is potentially subject to interference by matrix components. Methods: We examined potential matrix effects (MEs) in analyses of 31 MSMs using ultraperformance LC-MSMS. Twenty-one dust aliquots from three buildings (seven aliquots/building) were spiked with seven concentrations of each of the MSMs ($6.2pg/{\mu}l-900pg/{\mu}l$) and then extracted. Another set of 21 aliquots were first extracted and then, the extract was spiked with the same concentrations. We added deepoxy-deoxynivalenol (DOM) to all aliquots as a universal internal standard. Ten microliters of the extract was injected into the ultraperformance LC-MSMS. ME was calculated by subtracting the percentage of the response of analyte in spiked extract to that in neat standard from 100. Spiked extract results were used to create a matrix-matched calibration (MMC) curve for estimating MSM concentration in dust spiked before extraction. Results: Analysis of variance was used to examine effects of compound (MSM), building and concentration on response. MEs (range: 63.4%-99.97%) significantly differed by MSM (p < 0.01) and building (p < 0.05). Mean percent recoveries adjusted with DOM and the MMC method were 246.3% (SD = 226.0) and 86.3% (SD = 70.7), respectively. Conclusion: We found that dust MEs resulted in substantial underestimation in quantifying MSMs and that DOM was not an optimal universal internal standard for the adjustment but that the MMC method resulted in more accurate and precise recovery compared with DOM. More research on adjustment methods for dust MEs in the simultaneous analyses of multiple MSMs using LC-MSMS is warranted.

• Communications of the Korean Mathematical Society
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• v.26 no.4
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• pp.603-610
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• 2011

In this paper, we propose an algorithm for identifying ${\omega}_j{\in}(0,\;{\infty}),\;a_j,b_j{\in}\mathbb{C}$ and N of the following trigonometric series $f(t)=a_0+ \sum\limits_{j=1}^N[a_jcos{\omega}_jt+b_j\;sin{\omega}_jt]$ by means of the finite number of sample values. We prove that the frequency components are shown to be the solutions of some characteristic equation related to the inverse of a Hankel matrix derived from the sample values.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.549-557
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• 2016

In this paper we propose multiclassification method for large data sets by ensembling least squares support vector machines (LS-SVM) with principal components instead of raw input vector. We use the revised one-vs-all method for multiclassification, which is one of voting scheme based on combining several binary classifications. The revised one-vs-all method is performed by using the hat matrix of LS-SVM ensemble, which is obtained by ensembling LS-SVMs trained using each random sample from the whole large training data. The leave-one-out cross validation (CV) function is used for the optimal values of hyper-parameters which affect the performance of multiclass LS-SVM ensemble. We present the generalized cross validation function to reduce computational burden of leave-one-out CV functions. Experimental results from real data sets are then obtained to illustrate the performance of the proposed multiclass LS-SVM ensemble.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.609-620
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• 2005

In the secondary data analysis for categorical data, situations often arise in which the estimated cell variances are available, but not the full matrix of variances. In this case researchers are often inclined to use Pearson-type test statistics for homogeneity. However, for a complex sample observed cell proportions are not distributed as multinomial and Pearson-type test statistic generally is not distributed asymptotically as chi-square distribution. This paper evaluates powers for Wald test and Pearson-type test and the first order corrected test of Pearson-type test for homogeneity. The resulting power curves indicate that as the misspecification effect increases, the amount of inflation of significance level and the loss of power Pearson-type test are getting more severe.