• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.6
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• pp.959-967
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• 2008

The body measurement ratios and indices used in this study are all 3D female measurement data of the two countries were obtained from Size Korea Project and SizeUSA Project. The purpose of the study is to compare and analyze body measurement data between two countries. The results of this research are helpful for the clothing manufacturer and company to trade with America. The samples were 1,988 Korean and 6,306 American females. Thirty-five body measurement ratios and indices were chosen as the principal measurements in making garments. The conclusion of this research was as follow; First, U.S. females have measurements that exceed Korean women, except for crotch length total and shoulder slope. Second, the correlation coefficients of height and weight are relatively higher than other measurements in the two countries' body measurements. Finally, American women's height ratios are significantly bigger than Korean women's in most height ratios. On the other hand, Korean are significantly bigger than American in weight ratios. The drop values of Korean females are also smaller than those of American. It was recognized that American women are much bigger, wider and more obese than Korean according to the results by utilizing the girth ratios. BMI, Rohrer and Vervaeck index.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.519-527
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• 2003

Speech is much influenced by the existence of outliers which are introduced by such an unexpected happenings as additive background noise, change of speaker's utterance pattern and voice detection errors. These kinds of outliers may result in severe degradation of speaker recognition performance. In this paper, we proposed the GMM based on robust principal component analysis (RPCA-GMM) using M-estimation to solve the problems of both ouliers and high dimensionality of training feature vectors in speaker identification. Firstly, a new feature vector with reduced dimension is obtained by robust PCA obtained from M-estimation. The robust PCA transforms the original dimensional feature vector onto the reduced dimensional linear subspace that is spanned by the leading eigenvectors of the covariance matrix of feature vector. Secondly, the GMM with diagonal covariance matrix is obtained from these transformed feature vectors. We peformed speaker identification experiments to show the effectiveness of the proposed method. We compared the proposed method (RPCA-GMM) with transformed feature vectors to the PCA and the conventional GMM with diagonal matrix. Whenever the portion of outliers increases by every 2%, the proposed method maintains almost same speaker identification rate with 0.03% of little degradation, while the conventional GMM and the PCA shows much degradation of that by 0.65% and 0.55%, respectively This means that our method is more robust to the existence of outlier.

• Microbiology and Biotechnology Letters
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• v.20 no.3
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• pp.355-361
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• 1992

In order to evaluate an enzyme-linked immunosorbent assay(ELISA) for practical use in detecting aflatoxin $B_1(AFB_1)$ from cereals, we compared $AFB_1$ concentrations of samples contaminated artificially or naturally that were quantitated by the ELISA with those spiked or quantitated by HPLC. Cotton seed meals(19 items), rape seed meals(ll), soybean meals(9), and corns(3) imported from foreign countries were used as sample cereals. The standard curves of each cereal class showed that 1-100 ng/g of $AFB_1$ from cereals could be assayed by the ELISA. When artificially contaminated cereals were assayed by ELISA, the average recovery of AFB! from samples spiked to 3 ng/g and more was 138%(68-193%), although that spiked to 1 ng/g was somewhat high(268%). The average C.V. of recovery was 7.0%(0-22.2%). When naturally contaminated cereals were assayed, the concentrations of $AFB_1$ below 10 ng/g especially from rape seed meals quantitated by ELISA were much lower than those determined by HPLC. However, the concentrations of 10 ng/g and more from samples, except a few extraordinary samples. quantitated by ELISA were similar to those determined by HPLC, especially in case of cotton seed meals whose average recovery (ELISA/HPLC) was 153%. In conclusion, the ELISA was elucidated such as a practical tool to detect $AFB_1$ of 10 ng/g and more from cereals.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.45-52
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• 2021

Although many studies have been conducted to identify unknown attacks in cyber security intrusion detection systems, studies based on outliers are attracting attention. Accordingly, we identify outliers by defining categories for unknown attacks. The unknown attacks were investigated in two categories: first, there are factors that generate variant attacks, and second, studies that classify them into new types. We have conducted outlier studies that can identify similar data, such as variants, in the category of studies that generate variant attacks. The big problem of identifying anomalies in the intrusion detection system is that normal and aggressive behavior share the same space. For this, we applied a technique that can be divided into clear types for normal and attack by discrete wavelet transformation and detected anomalies. As a result, we confirmed that the outliers can be identified through One-Class SVM in the data reconstructed by discrete wavelet transform.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.342-344
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• 2023

클라우드 시장의 성장과 마이크로 서비스 접근식이 제기됨에 따라 IT인프라를 관리하기 위한 연구가 최근 활발히 이루어지고 있다. 하지만 고도화 및 분산된 환경에서 관찰 가능성 응용을 확보하기 어렵다는 문제점을 가지고 있다. 따라서 본 연구에서는 모니터링 시스템을 통한 데이터 분석 중 수집한 데이터의 분석이 난해하다는 문제를 해결하기 위한 방법을 제안한다. 제안된 방법은 NAB 데이터셋을 대상으로 STUMPY를 이용하여 데이터를 시각화하고, CNN을 이용하여 분류 작업을 수행한다. 분류를 수행한 데이터셋은 이상치 데이터와 이상 전조 데이터, 정상 데이터셋으로 분류하여 데이터셋을 구성한다. 구성한 학습 데이터셋에 대해 훈련을 마친 딥러닝 모델은 부하 테스트 환경에서 수집한 데이터에 대한 그래프 패턴을 분석하여 이상치 데이터와 이상 전조 데이터를 탐지한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.5
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• pp.1535-1545
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• 2014

This study aims at improving the Reliability of DSRC Traffic information considering Traffic and Road Characteristics. First of all, this study analyzed the characteristics of DSRC data on urban expressway and problems of outlier data occurrence. After then, this study produced reliable traffic information by using an optimal method of the Outlier-Filtering. After Outlier-Filtering, this study performed accuracy evaluation and appropriateness check for the number of samples per confidence level. As a result, it showed that the MAPE was between 2.2% and 9.7% and RSME was between 2.2 and 7.5 which are very similar figures to the actual average traffic speed. Also, The samples of both Am peak and Pm peak periods were analyzed to be appropriate at the confidence level of 95%, and 90% within the allowable error range of 5kph.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.9 no.6
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• pp.33-42
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• 2010

Travel speed is an important parameter in measurement of road traffic. UTIS(Urban Traffic Information System) was developed as a type of section detector. However, UTIS incur errors caused by irregular vehicle trajectories, wireless communication range and so on. This paper suggests a new model that use an error-filtering algorithm to improve the accuracy of travel speed measurements. In the field test, the variance of the percent errors measured by the new model was reduced. Therefore, it can be concluded that the proposed model significantly improves travel speed measuring accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.9A
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• pp.1592-1600
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• 2001

본 논문에서는 IMT-2000을 위한 이중 모드 패킷 전송 방식에 대한 성능을 분석하고, 동적 임계치 설정을 이용한 이중 모드 패킷 전송 방식을 제안한다. 먼저, 다양한 채널 환경과 트래픽 유형을 고려하여, 공용 채널과 전용채널 간의 모드 전환을 위한 임계치의 변화에 따른 성능의 변화를 고찰하였다. 성능 분석 결과, 채널 환경과 트래픽 형태에 따라서 스위칭 임계치 설정이 매우 중요하며, 성능에 큰 영향을 미치게 된다는 것을 알 수 있었다. 그리고, 이중 모드 방식에서 스위칭 임계치를 동적으로 설정하는 방식을 제안하고 시뮬레이션을 통해 성능을 분석하였다. 제안된 동적 임계치를 사용할 경우에 채널 상황이나 트래픽 특성 변화에 적응적으로 대처할 수 있어, 전반적으로 고정 임계치 방식보다 성능이 크게 개선됨을 알 수 있었다.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05a
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• pp.125-130
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• 1996

최근 고리원자력 4호기 압력용기에 대한 제 3차 감시시험$^{(1)}$ 이 수행되었고 그 과정 중 측정된 시편에서의 반응률을 근거로 선량분석을 수행하였다. ENDF/B-VI를 근거로 만들어진BUGLE93$^{(2)}$ 라이브러리를 사용하여 각분할코드인 DORT version 2.7.3$^{(3)}$ 를 이용한 forward 및 adjoint 수송 계산 결과와 측정된 반응률을 결합하여 고리 4호기 원자로의 감시시편 X를 대상으로 1 MeV이상의 중성자속, 0.1 MeV 이상의 중성자속 및 dpa(displacement per atom)를 계산하여 측정치와 계산치를 비교하였다.

• The Korean Journal of Applied Statistics
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• v.32 no.6
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• pp.889-898
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• 2019

The problem of missing value imputation for variables in surveys that include item missing becomes complicated if outliers and logical boundary conditions between other survey items cannot be ignored. If there are outliers and boundaries in a variable including missing values, imputed values based on previous regression-based imputation methods are likely to be biased and not meet boundary conditions. In this paper, we approach these difficulties in imputation by combining various robust regression models and multiple imputation methods. Through a simulation study on various scenarios of outliers and boundaries, we find and discuss the optimal combination of robust regression and multiple imputation method.