• KSTLE International Journal
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• 제2권1호
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• pp.35-39
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• 2001

In this paper, statistical approach is undertaken to investigate the classification of wear debris which is the key function of objective assessment of wear debris morphology. Wear tests are run to produce various kinds of wear debris. The images of wear debris from wear tests are captured with image acquisition equipment. By thresholding, two-dimensional binary images of wear debris are made and, then, morphological parameters are used to quantify the images of debris. Parametric and nonparametric discriminant method are employed to classify wear debris into predefined wear conditions. It is demonstrated that classification accuracy of parametric and nonparametric discriminant method is similar. The selected use of morphological parameters by stepwise discriminant analysis can generally improve the classification accuracy of parametric and nonparametric discriminant method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2129-2147
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• 2019

This paper introduces an adaptive face recognition method based on a Novel Incremental Kernel Nonparametric Discriminant Analysis (IKNDA) that is able to learn through time. More precisely, the IKNDA has the advantage of incrementally reducing data dimension, in a discriminative manner, as new samples are added asynchronously. Thus, it handles dynamic and large data in a better way. In order to perform face recognition effectively, we combine the Gabor features and the ordinal measures to extract the facial features that are coded across local parts, as visual primitives. The variegated ordinal measures are extraught from Gabor filtering responses. Then, the histogram of these primitives, across a variety of facial zones, is intermingled to procure a feature vector. This latter's dimension is slimmed down using PCA. Finally, the latter is treated as a facial vector input for the advanced IKNDA. A comparative evaluation of the IKNDA is performed for face recognition, besides, for other classification endeavors, in a decontextualized evaluation schemes. In such a scheme, we compare the IKNDA model to some relevant state-of-the-art incremental and batch discriminant models. Experimental results show that the IKNDA outperforms these discriminant models and is better tool to improve face recognition performance.

• Journal of the Korean Data and Information Science Society
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• 제16권1호
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• pp.19-31
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• 2005

Brain injured patients who had the driver's license before the injury of the brain were tested with the newly developed tool CPAD by Hangyang Medical School and the National Rehabilitation Center. The CPAD contains many variables to measure the ability of driving. Also for each patient the American standard CBDI score was measured and the result was compared with the CPAD results. Of interest is to classify the patients as pass, border, fail group after the CPAD test. To derive the discriminant functions with the group information based on CBDI, parametric/nonparametric and multivariate/univariate discriminant analysis was performed and discussed.

• Journal of the Korean Statistical Society
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• 제30권2호
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• pp.193-217
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• 2001

Despite of the rich literature in discriminant analysis, this complicated subject remains much to be explored. In this article, we study the theoretical foundation that supports Fisher's linear discriminant analysis (LDA) by setting up the classification problem under the dimension reduction framework as in Li(1991) for introducing sliced inverse regression(SIR). Through the connection between SIR and LDA, our theory helps identify sources of strength and weakness in using CRIMCOORDS(Gnanadesikan 1977) as a graphical tool for displaying group separation patterns. This connection also leads to several ways of generalizing LDA for better exploration and exploitation of nonlinear data patterns.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2006년도 춘계공동학술대회 논문집
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• pp.1214-1220
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• 2006

In this article, it will be shown that a nonparametric and data-adaptive approach to the variance change point (VCP) detection problem is possible by formulating it as a pattern classification problem. Technical aspects of the VCP detector are discussed, which include its training strategy and selection of proper classification tool.

• 대한치과교정학회지
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• 제34권5호
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• pp.371-379
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• 2004

본 연구는 1999-2003년 사이에 출판된 대한치과교정학회지(KJO)의 논문 247편과 American Journal of Orthodontics and Dentofacial Orthopedics (AJODO)의 논문 250편들이 사용하고 있는 통계기법들을 연도별로 조사 비교하였다. 각각의 저널에서 어떠한 통계기법들이 자주 사용되었는지, 최근 들어 통계기법의 변화가 있었는지 자주 쓰이는 통계기법들에 대한 주의할 점을 고려했는지 어떠한 고급통계기법을 사용하였는지를 살펴보았다. KJO는 이 기간 동안의 모든 논문을 연구대상으로 하였고 AJODO는 각 해마다 50편의 논문을 original article이면서 통계기법을 사용한 논문들 중에서 무작위로 추출하였다. 빈번히 사용된 통계기법은 KJO의 논문에서는 t-검정, 분산분석, 상관분석. 비모수분석, 회귀분석, $x^2-$검정. 요인 분석의 순이었고 AJODO의 논문에서는 t-검정. 분산분석. 비모수분석, 상관분석, 회귀분석, $x^2$-검정, 요인분석의 순이었다. 5년 동안의 통계기법의 변화를 살펴본 결과 KJO에서는 유의한 변화를 관찰할 수 없었으나$(x^2=17.38,\;p = 0.6881)$ AJODO에서는 유의한 변화를 관찰할 수 있었다.$(x^2=42.41,\;p =0.0397)$ 각 통계분석에 해당하는 가정의 점검을 간과한 경우가 있었으며 통계분석 전에 이상치 등의 자료의 탐색이 필요하며 소표본일 경우 좀 더 다른 통계적 접근 방법이 필요하다 고급통계기법으로는 KJO에서는 인자분석과 판별분석을 통해 부정교합자에게 적용이 가능한 골격유형의 감별기준을 도출하였고 AJODO에서는 다기관센터를 통한 임상시험에서 ITT분석을 실시하였으며 생존분석 죈 GEE분석을 실시하였다. 단순한 통계기법만으로는 정확한 자료의 분석이 행해졌다고 보기는 어렵고 자료와 가설에 맞는 단변수 분석후의 다변량 통계 분석 방법을 통하여 정확한 결론을 유추해 내는 노력이 필요하다 치과학 분야의 자료의 특성 중 하나는 서로 상관관계가 높으며 반복 측정치를 가지는 것인데, 올바른 통계기법을 도입하여 그 결과에 대한 바른 해석을 할 수 있도록 해야 하겠다.