• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.767-776
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• 2010

Frontier (1976) suggested a criterion based on the expected length of ordered random intervals under the Broken-stick model (Barton and David, 1956) to determine the optimal number of principal components retained. It is considered to be one of the methods that provide the most consistent simulation results (Jackson, 1993). This study is aimed to propose a method using the distribution of ordered random intervals to evaluate the contribution of principal components. We also examine several types of Gini indices along with the corresponding Lorenz curves to visualize the overall equivalence of those contributions.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.1
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• pp.60-66
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• 2005

Pod shape of twenty soybean (Glycine max L. Merrill) genotypes was evaluated quantitatively by image analysis using elliptic Fourier descriptors and their principal components. The closed contour of each pod projection was extracted, and 80 elliptic Fourier coefficients were calculated for each contour. The Fourier coefficients were standardized so that they were invariant of size, rotation, shift, and chain code starting point. Then, the principal components on the standardized Fourier coefficients were evaluated. The cumulative contribution at the fifth principal component was higher than $95\%$, indicating that the first, second, third, fourth, and fifth principal components represented the aspect ratio of the pod, the location of the pod centroid, the sharpness of the two pod tips and the roundness of the base in the pod contour, respectively. Analysis of variance revealed significant genotypic differences in these principal components and seed number per pod. As the principal components for pod shape varied continuously, pod shape might be controlled by polygenes. It was concluded that principal component scores based on elliptic Fourier descriptors yield seemed to be useful in quantitative parameters not only for evaluating soybean pod shape in a soybean breeding program but also for describing pod shape for evaluating soybean germplasm.

• Journal of the Ergonomics Society of Korea
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• v.10 no.2
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• pp.31-42
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• 1991

To understand the shape of the neck in a view of garment planning, principal component analysis has been appliedto the measurement of the neck. The neck surface development and the cross sections of the neck have been observed. The materials consist of the body mearsurements, the neck surface developments and the cross sec- tions of the necks of a total of 108 korean woman students. The difference between the right side and the left side of the neck has not been reconginiged. But the differenece among the height of the front neck point, that of the side neck point and that of the back neck point has been recognized. 2. The initial 41 items have been found having variety and duplication. So two criteria have been made to solve those problems and the selection of 34 items have been made by each criterion. 3. 43 and 34 items have been compared by means of accumulative ratios of contribution and of clearness within the meaning of principal component. As a result, 34 measurement items have been further anylysis. 4. As a result of principal component analysis on the 34 items, the four principal components have been found obtaines and inter-preted. The four principal components are 1) the thick of the neck, 2) the front neck-line on the waist basic pattern, basic pattern, 3) the shape of the neck surface development, and 4) the back neck-line on the waist basic pattern. 5. According to the graphic informations concerning these principal components, the meaning of these four principal components has been grasped on the visual. As a result, there is a large individual difference in the shape of neck.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.54 no.1
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• pp.24-28
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• 2009

This study was conducted to evaluate the growth characters and yield components of 18 collected sesame cultivars to get basic information on the variation for the sesame breeding using principal component analysis. All characters except days to flowering, days to maturity and 1,000 seed weight showed significantly different. Seed weight per 10 are showed higher coefficient of variance. Capsule bearing stem length and liter weight showed positive correlation with seed yield per 10 are. The principal components analysis grouped the estimated sesame cultivars into four main components which accounted for 83.7% of the total variation at the eigenvalue and its contribution to total variation obtained from principal component analysis. The first principal component ($Z_1$) was applicable to increase plant height, capsule bearing stem length and 1,000-seed weight. The second principal component ($Z_2$) negatively correlated with days to flowering and maturity by which it was applicable to shorten flowering and maturity date of sesame. At the scatter diagram, Yangbaek, Ansan, M1, M2, M4, M7 and M9 were classified as same group, but M10, Yanghuk, Kanghuk, M5, M6, M12 and M13 were classified as different group. This results would be helpful for sesame breeder to understand genetic relationship of some agronomic characters and select promising cross lines for the development of new sesame variety.

• Journal of Life Science
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• v.13 no.3
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• pp.343-348
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• 2003

This study was conducted to get basic information on the Korean local corn line collected from Busan City and Kyungnam Province, a total of 49 lines were selected and assessed by the principal component analysis method. In the result of principal component analysis for 7 characteristics, 67.4% and 86.3% of total variation could be appreciated by the first two and first four principal components, respectively. Contribution of characteristics to principal component was high at upper principal components and low at lower principal components. Biological meaning of principal component and plant types corresponding to the each principal component were explained clearly by the correlation coefficient between principal component and characteristics. The first principal component appeared to correspond to the size of plant and ear, and the duration of vegetative growing period. The second principal component appeared to correspond to the number of ear and tiller. But the meaning of the third and fourth principal components were not clear.

• Korean Journal of Agricultural Science
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• v.8 no.2
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• pp.139-151
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• 1981

To obtain breeding materials 57 Korean local corn lines collected were assessed and classified by the application of principal component analysis. The results obtained were as follows. 1. In the result of principal component analysis for 27 characters, 67.1% and 88.6% of total variation could be appreciated by the first four and fir st ten principal component respectively. 2. According to the value of characters and principal components, contribution of characters to principal components were very variable. 3. Biological meaning of the principal component and plant type corresponded to the each principal component were explained clear by the correlation coefficients between principal components and characters. 4. 57 lines were classified into 4 lineal groups by the taxonomic distances.

• Bulletin of the Korean Chemical Society
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• v.26 no.12
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• pp.2027-2032
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• 2005

This paper demonstrates details of thermal behavior of Langmuir-Blodgett (LB) film of poly(tert-butyl methacrylate) (PtBMA) by using the principal component analysis based two-dimensional correlation spectroscopy (PCA2D) through eigenvalue manipulating transformation (EMT). By uniformly lowering the power of a set of eigenvalues associated with the original data, the smaller eigenvalues becomes more prominent and the subtle contribution from minor components is now highlighted much more strongly than the original data. Thus, the subtle difference of thermal behavior of LB film of PtBMA from minor components, which is not readily detectable in the conventional 2D correlation analysis, is much more noticeable than the original data. PCA2D correlation spectra with EMT operation for the temperature-dependent IR spectra of LB film of PtBMA reveal the hidden property of phase transition processes during heating.

• 한국석유지질학회:학술대회논문집
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• spring
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• pp.10-14
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• 1998

A systematic methodology is developed for the electrofacies determination from wireline log data using multivariate statistical analysis. To consider corresponding contribution of each log and reduce the computational dimension, multivariate logs are transformed into a single variable through principal components analysis. Resultant principal components logs are segmented using the statistical zonation method to enhance the efficiency and quality of the interpreted results. Hierarchical cluster analysis is then used to group the segments into electrofacies. Optimal number of groups is determined on the basis of the ratio of within-group variance to total variance and core data. This technique is applied to the wells in the Korea Continental Shelf. The results of field application demonstrate that the prediction of lithology based on the electrofacies classification matches well to the core and the cutting data with high reliability This methodology for electrofacies classification can be used to define the reservoir characteristics which are helpful to the reservoir management.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.485-492
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• 2014

In baseball, the traditional measure of pitchers are wins and ERA. But these statistics are influenced by luck or team power. So sabermetrician proposes a number of indicators that predict future performance. We determine a new measure, which we call pitching grade index (PGI) that efficiently summarizes a pitcher's performance on a numerical scale using principal components analysis. The PGI statistic can often be useful to assessing a pitcher's individual contribution. Also K-means clustering algorithm are used for segmentation of players into groups.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.6
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• pp.735-749
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• 2018

In this study, one studied the principal factors and water-quality components that determine the concentration of chemical oxygen demand (COD) in seawater in estuaries, such as the Han, Geum, Youngsan, Seomjin, and Nakdong rivers in Korea. The principal factors determining the concentration of COD in seawater indicated by the principal component analysis were salinity, exogenous origin and autochthonous resources based on chlorophyll-a. Moreover, organic matter in the submarine sediment layer also had a secondary effect. Regression slope assessed the contribution of water-quality components to determine the concentration of COD in the estuary. One found that the effect of salinity on the overall survey was significant. Moreover, the effect of chlorophyll-a was also appeared in April and August. In each estuary, the most significant contribution factor was chlorophyll-a in the Nakdong River and salinity in the Han and Yongsan rivers. The contribution of salinity and chlorophyll-a were found to be the largest in the Geum River. The salinity and chlorophyll-a in the Seomjin River showed a low contribution.