• Communications for Statistical Applications and Methods
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• v.18 no.6
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• pp.761-770
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• 2011

Robust principal components regression is suggested to deal with both the multicollinearity and outlier problem. A main aspect of the robust principal components regression is the selection of an optimal set of principal components. Instead of the eigenvalue of the sample covariance matrix, a selection criterion is developed based on the condition index of the minimum volume ellipsoid estimator which is highly robust against leverage points. In addition, the least trimmed squares estimation is employed to cope with regression outliers. Monte Carlo simulation results indicate that the proposed criterion is superior to existing ones.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.691-699
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• 2017

Data analysts sometimes test the equality of two normal population means by the inspection of the overlapping of two confidence intervals. This method seems simple to use; however, it is a common statistical misconception to suppose that two normal means are not significantly different because of no overlapping. This article will present transforming the confidence interval of the mean difference to individual confidence intervals that are visualized to inspect overlapping. It will also be shown that this technique can be extended when comparing the k normal population means with equal variances.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.151-156
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• 2012

In this paper robust nonlinear image denoising algorithms are introduced for the distribution which is Gaussian in the center and Laplacian in the tails. The distribution is known as the least favorable ${\epsilon}$-contaminated normal distribution that maximizes the asymptotic variance. The proposed filter proves to be the maximum likelihood estimator under the heavy-tailed Gaussian noise environments. It is optimal in the respect of maximizing the efficacy under the above noise environment. Another filter for reducing impulsive noise is proposed by mixing with the myriad filter to propose an amplitude-limited myriad filter. Extensive experiment is conducted with images corrupted with ${\alpha}$-stable noise to analyze the behavior and performance of the proposed filters.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.999-1008
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• 2010

The objective of this paper is to develop variable sampling interval multivariate control charts that can offer significant performance improvements compared to standard fixed sampling rate multivariate control charts. Most research on multivariate control charts has concentrated on the problem of monitoring the process mean, but here we consider the problem of simultaneously monitoring both the mean and variability of the process.

• The Transactions of the Korea Information Processing Society
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• v.2 no.3
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• pp.364-373
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• 1995

We propose a probabilistic design method and performance analysis in the area of dynamic data structures. We assign two stacks to a block which consists of m contiguous memory cells. Frequencies of delete and insert operations are not fixed, but depend on stack heights. We present various probabilistic schema and a rigorous performance analysis for a random memory allocation. Especially, stack coillision problem is studied and exponential increase of the mean of collision time as mlongrightarrow$\infty$is showed. We also present general mathematical schema which can be applied to the performance problems of finite automata and other computer information systems.

• The Journal of Natural Sciences
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• v.10 no.1
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• pp.111-122
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• 1998

This study was performed to investigate the type perceived risk of clothing consumers and the types of information seeking, the relationship between perceived risk and information seeking, and the defferences according to the demographic variables. The surveyed data from 376 college students were analized using Person's correlation, factor analysis, t-test, and ANOVA. The risk perception of clothing consumers was classified into five types: economic and performance risk, loss of time risk, social risk, and loss of fashionability risk. The information seeking was classified into four types: advertisement, observation in shops, information in memory, and opinions of neighbors. The type of risk perception and the types of information seeking were correlated positively and were different according to expenditure on clothing.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.628-631
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• 2010

환경문제에 대한 관심으로 자동차에 대한 경량화가 요구되는 동시에 안전규제가 강화 되고 있어, 높은 인장강도를 가지는 고강도 강의 차체 적용 비율이 점차 증가하고 있다. 또한, 자동차 1대를 조립하기 위한 저항 점용접 횟수를 줄이고, 용접부에 충격안정성을 확보하기 위한 관심이 고조되고 있다. 따라서, 국내 자동차 산업에서 용접부의 신뢰성을 보장하기 다양한 비파괴 검사를 적용하고 있으며, 생산 공정에 적용하고 있다. 그중에서 용접 전극 사이에서 동저항(Dynamic resistance, 용접 공정중모재의 저항값의 변화)을 계측하여 용접성을 평가하는 방법이 제시되고, 차체 조립공정 중에 적용하려는 시도가 이루어지고 있다. 본 연구에서는 자동차 차체용 냉간 압연강판(590MPa dual-phase steel)을 인버터 DC 저항 점 용접하여, 용접전극 사이에서 동저항을 측정 하였다. 용접성은 인장전단 강도로 평가하였고, 용접 공정 변수는 용접 전류, 용접 시간, 가압력을 선정하였다. 동저항 그래프의 ${\alpha}$-peak와 ${\beta}$-peak값을 인장전단 강도에 따라 회귀 분석하여, 동저항에 따른 인장전단 강도를 예측하였다. 추가적으로, 용접부의 외관 형상 중에 압흔 깊이와 압흔자국 지름에 대한 회귀분석을 실시하였으며, 용접부 형상에 대한 신뢰성을 부여하였다.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.05a
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• pp.5-12
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• 2000

본 연구에서, Daubechies'Mother Wavelet를 이용한 이산 웨이블렛 변환(Discrete Wavelet Transform)에 기초한 새롭고 효과적인 특정추출방법을 제안하였다. 특정추출을 이용하여 응용방향을 설명하고 또는 통계적 파라메터의 평가를 행하였다. 본 연구에서는 다음과 같은 몇 가지 사실을 알 수 있었다. 1. 시스템에서 발생된 (인가전압이 0[V]) 노이즈라 볼 수 가있는 렌덤노이즈(Random Noise)를 디지털필터인 FIR(Finite Impulse Response)필터를 통하여 상당한 노이즈를 억제할 수가 있었다. 2. 이산 웨이블렛 변환 시 레벨 1~4까지 변환한 결과 최적의 변환상태 Level-3을 기준으로 하였다. 3. 특정추출 파라메터는 음향방출신호의 최대값, 평균값, 분산, 왜도, 첨쇄도를 특정추출파라메터로 이용하였다. 4. 특정추출 결과를 이용하여 전체 열화시간 중 대표적 음향방출신호 중 초기열화신호, 중기열화신호, 말기열화신호를 얻을 수 있었다. 이런 특정추출을 통하여 변압기열화상태를 진단할 수 있는 가능성을 확인 할 수가 있었다.

• The Journal of Information Technology
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• v.6 no.1
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• pp.65-70
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• 2003

In this papers, we proposed the new method in order to diagnosis partial discharge type of transformers. For wavelet transform, Daubechie's filter is used,, we can obtain wavelet coefficients which is used to extract featrue of statistical parameters(maximum value, average value, dispersion, skewness, kurtosis) about high frequency current signal per 3-electrode type(needle-plane electrode, IEC electrode and Void electrode). Also, these coefficients are used to identify signal of internal partial discharge in transformer. As a result, from compare of high frequency current signal amplitude and average value, we are obtained results of IEC electrode> Void electrode> Needle-Plane electrode. Otherwise, in case of skewness and kurtosis, we are obtained results of Void electrode> IEC electrode> Needle-Plane electrode. As improved method in order to diagnosis partial discharge type of transformers, we use neural network.

• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.241-253
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• 2010

As standard unit root tests are empirically proved to fail to reject the null hypothesis of a unit root for many economic and business time series, it is doubtful that most of those series are informative about the existence of a unit root or that those tests are powerful against relevant alternative hypotheses. This study attempts to perform tests of the null hypothesis of stationarity as well as tests of the null hypothesis of a unit root using the time series data of housing prices in the major metropolitan areas. The results of the additional analyses such as lead-lag, cross-correlation and impulse response for testing the statistical interrelationships between the prices are generally found to be consistent.