• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1185-1199
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• 2016

Two phase sampling (double sampling) is often used when there is inadequate population information for proper stratification. Many recent papers have been devoted to the estimation method to improve the precision of the estimator using first phase information. In this study we suggested outlier weight adjustment methods to improve estimation precision based on the weight of the generalized ratio-cum-product estimator. Small simulation studies are conducted to compare the suggested methods and the usual method. Real data analysis is also performed.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.27-38
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• 1995

In the surveys of sensitive issues of the population that is composed of several unknown-size stratum, we propose the unrelated question model with quantitative attribute by using stratified double sampling. And, we consider two types of sample allocations under the fixed cost, which are the proportional allocation, the optimum allocation. In efficiency, the proosed model is inferior to the unrelated question model with quantitative attribute by stratified sampling in case of the size of each stratum is known. But we find that efficiency of the proposed model is increased, when the selecting probability of sensitive question p is small and first stage sample size n' is large.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.675-694
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• 2008

We propose a new sampling design for the Korean Livestock Production Cost Survey. In this sampling design, the survey population is derived from the 2005’s agricultural census of Korea. And coefficient of variation(CV) is estimated from the current livestock production cost survey data, and the estimated CV’s are used to find the optimal sample size which satisfies the predetermined precision of estimation. In order to save the enumeration cost, the agriculture enumeration districts are used as a primary sampling unit(psu). Final sample is selected by double sampling. Also, we propose the estimator which is able to reflect the change of the population of livestock production households.

• Journal of radiological science and technology
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• v.40 no.3
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• pp.443-451
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• 2017

Mammography is commonly used for screening early breast cancer. However, mammographic images, which depend on the physical properties of breast components, are limited to provide information about whether a lesion is malignant or benign. Although a dual-energy subtraction technique decomposes a certain material from a mixture, it increases radiation dose and degrades the accuracy of material decomposition. In this study, we simulated a breast phantom using attenuation characteristics, and we proposed a technique to enable the accurate material decomposition by applying weighting factors for the dual-energy mammography based on a photon-counting detector using a Monte Carlo simulation tool. We also evaluated the contrast and noise of simulated breast images for validating the proposed technique. As a result, the contrast for a malignant tumor in the dual-energy weighted subtraction technique was 0.98 and 1.06 times similar than those in the general mammography and dual-energy subtraction techniques, respectively. However the contrast between malignant and benign tumors dramatically increased 13.54 times due to the low contrast of a benign tumor. Therefore, the proposed technique can increase the material decomposition accuracy for malignant tumor and improve the diagnostic accuracy of mammography.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.6
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• pp.479-487
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• 2020

A new double-pulse laser system that combines Raman and laser induced plasma spectroscopy (LIPS) in a single unit is proposed. The study attempts to enhance the laser induced plasma signals while simultaneously extracting the desired molecular signals from Raman spectroscopy. In low pressure conditions such as the lunar atmosphere, the measuring of plasma emission is hard because of the low electron density and short persistence time causing a rapid plasma expansion. Furthermore, in the integration of the detecting system aimed at space exploration, the minimization of laser system is important in terms of the payload mass. Simultaneous molecular and atomic detection that gave highly resolved spectral data at pressure below 0.07 torr is demonstrated amongst eight rock samples test. The plasma stacking produced from the double-pulse laser enhanced the signal intensity of calcium and oxygen lines in calcite matrix by twofold, compared to a conventional LIPS.

• Applied Chemistry for Engineering
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• v.4 no.2
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• pp.254-263
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• 1993

The industry of amino acids has developed for the synthetic methods, zymotechnics from the methods of extraction. In the present, part of amino acids (L-cystine, L-tyrosine, etc.) is manufactured by the methods of extraction, but most of amino acids is produced by synthetic methods, zymotechnics. Among the methods, the synthetic methods use of cyanic acid, which generate a large of waste water by acid or alkali in hydrolysis. In this point of view, improved new synthetic methods are demanded for being the influence of environment. This article Introduces new synthetic methods of phenyl alnine, further more, the recent of research results are introduced to prepare the derivative ${\alpha}-keto$ acids of precursor for preparing more than particular amino acids.

• Korean Journal Plant Pathology
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• v.12 no.4
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• pp.432-436
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• 1996

역전사 중합효소 연쇄반응(RT-PCR)을 이용하여 담배(Nicotiana glutinosa)에 증식시킨 7종의 오이 모자이크 바이러스(CMV)를 검정하였다. RT-PCR을 위한 간단하고 신속한 바이러스 핵산의 조즙액 추출법이 개발되었으며, CMV 외피단백질 유전자 부위를 기초로 하여 제작한 20개의 염기로 구성된 primer를 사용하여 RT-PCR을 실시한 결과, 약 490 염기쌍의 DNA 단편들이 이병식물의 조즙액으로부터 증폭되었다. EcoRI 및 MspI을 이용한 RT-PCR 산물의 분석에 의하여, 공시한 7종의 바이러스는 모두 CMV subgroup I으로 동정되었다. Ouchterlony 한천젤 이중 확산법을 이용한 항혈청 검정에서도 7종의 바이러스 모두 CMV-Y의 항혈청과 단일의 침강선을 형성하였다.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.39-57
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• 2001

Categorical data has sometimes misclassification errors. If this data will be analyzed, then estimated cell probabilities could be biased and the standard Pearson X2 tests may have inflated true type I error rates. On the other hand, if we regard wellclassified data with misclassified one, then we might spend lots of cost and time on adjustment of misclassification. It is a necessary and important step to ask whether categorical data is misclassified before analyzing data. In this paper, when data is misclassified at one of two variables for two-dimensional contingency table and marginal sums of a well-classified variable are fixed. We explore to partition marginal sums into each cells via the concepts of Bound and Collapse of Sebastiani and Ramoni (1997). The double sampling scheme (Tenenbein 1970) is used to obtain informations of misclassification. We propose test statistics in order to solve misclassification problems and examine behaviors of the statistics by simulation studies.

• Journal of Korean Society of Forest Science
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• v.101 no.2
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• pp.213-219
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• 2012

The $5^{th}$ national forest inventory (NFI5) has been reorganized to annual inventory system for providing multi-resources forest statistics at a point in time. The objective of this study is to evaluate statistical estimators for estimating forest growing stock in Chungcheongbuk-Do from annual inventory data. When comparing two estimators; simple random sampling (SRS) and double sampling for post-stratification (DSS), for estimating mean forest growing stock ($m^3/ha$) at each surveyed year, the estimate for DSS in which a population of interest is stratified into three sub-population (forest cover types) was more precise than that for SRS. To combine annual inventory field data, three estimators (Temporally Indifferent Method; TIM, Moving Average; MA, and Weighted Moving Average; WMA) were compared. Even though the estimated mean for TIM and WMA is identical, WMA-DSS is preferred to provide more smaller variance of estimated mean and to adjust for catastrophic events at a surveyed year (so-called "lag bias") by annual inventory data.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.189-198
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• 2024

Lipreading is one of the important parts of speech recognition, and several studies have been conducted to improve the performance of lipreading in lipreading systems for speech recognition. Recent studies have used method to modify the model architecture of lipreading system to improve recognition performance. Unlike previous research that improve recognition performance by modifying model architecture, we aim to improve recognition performance without any change in model architecture. In order to improve the recognition performance without modifying the model architecture, we refer to the cues used in human lipreading and set other regions such as chin and cheeks as regions of interest along with the lip region, which is the existing region of interest of lipreading systems, and compare the recognition rate of each region of interest to propose the highest performing region of interest In addition, assuming that the difference in normalization results caused by the difference in interpolation method during the process of normalizing the size of the region of interest affects the recognition performance, we interpolate the same region of interest using nearest neighbor interpolation, bilinear interpolation, and bicubic interpolation, and compare the recognition rate of each interpolation method to propose the best performing interpolation method. Each region of interest was detected by training an object detection neural network, and dynamic time warping templates were generated by normalizing each region of interest, extracting and combining features, and mapping the dimensionality reduction of the combined features into a low-dimensional space. The recognition rate was evaluated by comparing the distance between the generated dynamic time warping templates and the data mapped to the low-dimensional space. In the comparison of regions of interest, the result of the region of interest containing only the lip region showed an average recognition rate of 97.36%, which is 3.44% higher than the average recognition rate of 93.92% in the previous study, and in the comparison of interpolation methods, the bilinear interpolation method performed 97.36%, which is 14.65% higher than the nearest neighbor interpolation method and 5.55% higher than the bicubic interpolation method. The code used in this study can be found a https://github.com/haraisi2/Lipreading-Systems.