• Communications for Statistical Applications and Methods
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• 제21권1호
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• pp.61-68
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• 2014

We propose binary classification methods by modifying logistic regression classification. We use variable selection procedures instead of original variables to select the principal components. We describe the resulting classifiers and discuss their properties. The performance of our proposals are illustrated numerically and compared with other existing classification methods using synthetic and real datasets.

• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.301-309
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• 2006

In this paper, we show the improved fuzzy c-means clustering method. To improve, we use the double clustering as principal component analysis from objects which is located on common region of more than two clusters. In addition we use the degree of membership (probability) of fuzzy c-means which is the advantage. From simulation result, we find some improvement of accuracy in data of the probability 0.7 exterior and interior of overlapped area.

• 대한수학회보
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• 제49권2호
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• pp.285-293
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• 2012

In this paper, we investigate the hypersurface M in a unit sphere with constant k-th mean curvature and two distinct principal curvatures, and characterize such a hypersurface.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2006년도 추계 학술발표회
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• pp.603-608
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• 2006

In this paper, principal concepts on bi-directional pile load test(BD PLT) specification were explained. These main concepts are kinds of BD PLT, loading capacity, reporting the test results to relevant association etc.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.765-777
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• 2003

In this paper, we investigate some measures as tests of multivariate normality based on principal components. The idea was proposed by Srivastava and Hui(1987). They generalized Shapiro-Wilk statistic for multi variate cases. We show the null distributions of the statistics do not depend on the unknown parameters and mention the asymptotic null distributions. Also power performance of the tests are assessed in a Monte Carlo study.

• Journal of Communications and Networks
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• 제12권2호
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• pp.191-197
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• 2010

In this paper, we propose a novel methodology to identify border gateway protocol (BGP) updates associated with major events - affecting network reachability to multiple ASes - and separate them (statistically) from those attributable to minor events, which individually generate few updates, but collectively form the persistent background noise observed at BGP vantage points. Our methodology is based on principal component analysis, which enables us to transform and reduce the BGP updates into different AS clusters that are likely affected by distinct major events. We demonstrate the accuracy and effectiveness of our methodology through simulations and real BGP data.

• Journal of the Korean Data and Information Science Society
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• 제14권3호
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• pp.545-551
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• 2003

Robust design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper we propose how to simultaneously optimize multiple quality characteristics using the principal component analysis of multivariate statistical analysis. An example is illustrated to compare it with already proposed method.

• 산업기술연구
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• 제2권
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• pp.53-60
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• 1982

A strain gage relief technique was used to determine the magnitude and directions of a virgin principal stresses, but the values measured in the same borehole are always not consistent. This paper has shown the use of the eigen analysis to achieve precise and reliable principal stress from measured values. The best fit stress ellipsoid to the data has been obtained through consideration of direction cosine of each principal stress.

• Journal of the Korean Data and Information Science Society
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• 제15권4호
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• pp.817-823
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• 2004

This paper describes a three dimensional motion recognition algorithm and a system which adopts the algorithm for non-contact human-computer interaction. From sequence of stereos images, five feature regions are extracted with simple color segmentation algorithm and then those are used for three dimensional locus calculation precess. However, the result is not so stable, noisy, that we introduce principal component analysis method to get more robust motion recognition results. This method can overcome the weakness of conventional algorithms since it directly uses three dimensional information motion recognition.

• Journal of the Korean Data and Information Science Society
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• 제15권3호
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• pp.531-542
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• 2004

Principal component analysis and cluster analysis were conducted to comprehensively evaluate the water quality of Busan coastal area with the data collected seasonally by the analysis of surface water at 10 stations from 1997 to 2003. We noted that the first principal component was regarded as a factor related with the input of nutrient-rich fresh water and the second principal component as meteorological characteristics. Also we obtained that water qualities of station 4 and 9 were different from those of other stations in Busan coastal area.