• KOREAN JOURNAL OF CROP SCIENCE
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• v.43 no.1
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• pp.6-10
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• 1998

This study was conducted to obtain basic information on the development of new triticale cultivars with good quality and high productivity for soiling feed. Twelve cultivars introduced from Poland, Canada and two cultivars developed in Korea were planted in the experimental field at Ansong National University in 1995. Major growth traits and nutrient components for feed were measured and analyzed using principal component analysis and average linkage cluster analysis. 'Prego', 'Prag 46/3', and 'Clercal' were relatively high in forage yield. Most of forage nutrient contents except cellulose were higher in Prego, Clercal, and 'Cumulus' than other cultivars. Results of principal component analysis on 11 traits including forage yield and nutrient contents showed that 72.59% of total variation were explained by the first and second principal components. The Z$_1$ had high correlation with the contents of forage nutrient components and Z$_2$ with plant height, fresh, and dry weight. Fourteen cultivars were classified into 7 groups by multivariate analysis. Clercal and Prego in Group I could be useful source for the improvement of triticale as an important forage crop because they exhibited high productivity as well as high contents of nutrient components for feed.

• Journal of the Korean Society of Food Culture
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• v.31 no.1
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• pp.105-110
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• 2016

The objective of this study was to determine sensory profiles of rice confections. The samples used in this study obtained from Korea (traditional Korea rice snack and local specialty rice snack) and three countries (USA, Japan, and China) were evaluated and compared. The sensory characteristics of five kinds of rice confections were evaluated using a sensory test and were analyzed via quantitative description analysis (QDA), principal component analysis (PCA), and hierarchical cluster analysis (HCA). In the descriptive analysis, 10 trained panelists evaluated sensory characteristics consisting of 19 attributes, and there were significant differences (p<0.05) among the 16 characteristics. For the descriptive data, multivariate analysis of variance was carried out and identified differences among the samples. The PCA of rice confections for the first two principal components could explain 85.66% of the variations. The Korean, Japanese, and Chinese rice confections were savory, gritty, and particle-sized, the other Korean local specialty rice confections were fruity, sweet, honey-flavored, compact, and crispy, and those from the USA were glossy, grainy, bright, adhesive, cohesive, crispy, and sweet.

• Korean Journal of Human Ecology
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• v.8 no.2
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• pp.313-325
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• 1999

This study aimed to classify the data of children's bodies into several clusters by principal component scores that were extracted through the factor analysis in the former study, and to describe the distribution and body characteristics of the clusters. The sample was 308 elementary school children aged from 6 to 8 and the anthropometric measurements were performed indirectly from the photographs of the subjects, which was the same as the first analysis. The data were analysed statistically using SPSSWIN Ver. 8.0. Through the statistical analysis, 3 clusters were obtained from the data. The first cluster distributed more in the children aged 7 and 8 than in the children aged 6. The somatotype of this group was the tallest among the three groups, and they were the most developed group compared to the two other groups in lateral component as well as in linear component. The second cluster group wasn't well developed in lateral components, and had lowest level in Rohrer Index, so this group had thin figures compared to the other groups. The third cluster revealed dominant distribution in the group aged 6, and the group had the least developed linear components but higher level in Rohrer Index. Each cluster group revealed peculiar somatotype that was dominant in one group but rarely in other cluster groups. Lateral views of these characteristics were showed using the average of the measurements of clusters.

• Journal of Wetlands Research
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• v.21 no.3
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• pp.215-223
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• 2019

In this study, we analyzed the water quality characteristics of major tributaries of Nakdong River through statistical analysis such as correlation analysis, principal component and factor analysis, and cluster analysis. Organic matter and nutrients are highly correlated, and are high in spring and autumn, and seasonal water quality management is required. Principal component and factor analysis showed that 82% of total variance could be explained by 4 principal components such as organic matter, nutrients, nature, and weather. BOD, COD, TOC, and TP items were analyzed as major influencing factors. As a result of the cluster analysis, the four clusters were classified according to seasonal organic matter and nutrient pollution. Kumho River watershed showed high pollution characteristics in all seasons. Therefore, effective management of water quality in tributary streams requires measures in consideration of spatio-temporal characteristics and multivariate statistical techniques may be useful in water quality management and policy formulation.

• Korean Journal of Medicinal Crop Science
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• v.16 no.4
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• pp.218-224
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• 2008

This study was conducted to obtain the basic data for using the Artemisia genetic resources as a medicinal crop. 24 taxa including Artemisia capillaris Thunb. were analyzed by principal component analysis of 25 characters and cluster analysis for classification. In Principal components analysis of individuals of taxa using 25 morphological characters of reproductive organ, the first, the second, the third and the fourth components contributed 44.73%, 16.86%, 8.88%, and 7.07% of the variations, respectively. The cumulative contribution from the first to the fourth principal components was 77.56%. In cluster analysis, taxa of Artemisia L. was seperated 3 group by 25 morphological characters of reproductive organ, but it didn't completely coincident with Kitamura classification.

• Membrane and Water Treatment
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• v.13 no.5
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• pp.245-257
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• 2022

Water quality characteristics and their spatial variations in the Nakdong River were statistically analyzed by multivariate techniques including correlation analysis, CA, and FA/PCA based on water quality parameters for 17 sites over 2017-2019, yielding PI values for primary factors. Site 10 indicated the highest parameter concentrations, and results of pearson's correlation analysis suggest that non-biodegradable organic matter had been distributed on the site. Five clusters were identified in order of descending pollution levels: I (Ib > Ia) > II (IIa > IIb) > III. Spatial variations started from sub-cluster Ib in which Daegu city and Geumho-river are joined. T-P, PO4-P, SS, COD, and TOC corresponded to VF 1 and 2, which were found to be principal components with strong influence on water quality. Sub-cluster Ib was strongly influenced by NO3-N and T-N compared to other clusters. According to the PIs, water quality pollution deteriorated due to non-biodegradable organic matter, nitrogen- and phosphorus-based nutrient salts in the middle and lower reaches, illustrating worsening water pollution due to inflows of anthropogenic sources on the Geumho-river, i.e., sewage and wastewater, discharged from Site 10, at which there is a concentration of urban, agricultural, and industrial areas.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2B
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• pp.237-248
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• 2008

Precipitation variability in Korea is mainly influenced by climate circulation such as sea surface temperature, not a local convection. Therefore, this study investigates relationship between monthly precipitation of 61 station observed by Korea Meteorological Administration and global sea surface temperatures (SSTs). The main components of monthly precipitation in Korea are extracted by a method which consists of the principal analysis combined with the cluster analysis, to examine the correlation between monthly rainfalls and SSTs. The relationships between main components of monthly precipitation and SSTs exists in Pacific Ocean. At the result of Wavelet Transform analysis, The 2-4 year band have a strong wavelet power spectrum and the low frequency. the correlation coefficient between low frequency components of monthly rainfalls and SSTs calculated bigger then correlation coefficient between main components and SSTs. Hence, these results propose a prediction possibility of monthly precipitations using the varition of SSTs.

• Plant Resources
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• v.5 no.3
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• pp.214-223
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• 2002

The objective of this study was to understand the conservation of gene resources and provide information for mass selection' of winter bud characters among the selected populations of Kalopanax septemlobus Koidz using analysis of variance(ANOVA) tests. The obtained results are shown below; 1. Ten populations of K. septemlobus were selected for the study of the variation of winter bud characters in Korea. The results of the analysis of variance(ANOVA) tests shows that there were statistically significant differences in all of the winter bud characters among those populations. 2. Correlation analysis shows that width between Height and DBH(Diameter at breast height) characters have negative relationship with all of the characters, as ABL(Apical branch length), ABW(Apical branch width), AWBL(Apical branch winter bud length), AWBW(Apical branch winter bud width), ABT(Apical branch No. of thorns), ABLB(Apical branch No. of lateral bud) and LBL(Lateral branch length), LBW(Lateral branch width), LBT(Lateral branch No. of thorns), LBLB(Lateral branch No. of lateral bud). 3. The result of principal component analysis(PCA) for winter buds showed that the first principal components(PC' s) to the fourth principal component explains about 78% of the total variation. The first principal component(PC) was correlated with AWBW, LWBW, and LBL and the ratio of ABL/ABW and LBL/LBW out of 16 winter bud characters. The second principal component correlated with ABL, ABW, ABLB, LWBL(Lateral branch winter bud length), and LBW and the ratio of AWBL/AWBW. The third principal component correlated with ABL, ABW, LWBL, LBL, and the ratio of LBL/LBW. The fourth principal component correlated with LBL and the ratio of LWBL/LWBW(Lateral branch winter bud width), LBL/LBW. Therefore, these characters were important to analysis of the variation for winter bud characters among selected populations of K. septemlobus in Korea. 4. Cluster analysis using the average linkage method based on 10 selected populations for the 16 winter bud characters of K. septemlobus in Korea showed a clustering into two groups by level of distance 1.1(Fig. 3). As can be seen in Fig. 3, Group I consisted of three areas(Mt. Sori, Mt. Balwang and Mt. Worak) and Group Ⅱ contisted of seven areas(Suwon, Mt. Chuwang, Mt. Kyeryong, Mt. Kaji, Mt. Jiri, Muan, and Mt. Halla). The result of cluster analysis for winter bud characters corresponded well with principal component analysis, as is shown in Fig. 2.

• International Journal of Industrial Entomology and Biomaterials
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• v.14 no.1
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• pp.23-32
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• 2007

The nature of genetic variation and diversity among the 65 multivoltine silkworm genotypes was evaluated for 16 post cocoon characters. The components of genetic variation revealed higher PCV (60.487%) and GCV (44.56%) for evenness (variation 1) followed by cohesion (PCV=55.38%, GCV=40.36%) and non-broken filament length (PCV=32.05%, GCV=31.28%). The higher heritability ($h^2$ in broad sense) was observed for boil-off loss (95.6%) followed by non-broken filament length (95.22%). The both genotypic and phenotypic correlation indicated significant positive correlation of filament length with non-broken filament length, silk recovery, raw silk, neatness, and low neatness; and negative correlation with denier, renditta and silk waste. The principal component analysis (PCA) revealed 75.381 % of total variance from the five principal components extracted. On the basis of Mahalonobis' $D^2$ values (Ward's minimum variance), the sixty-five multivoltine silkworm genotypes were classified in to 9 clusters with substantial inter and intra cluster distances. Number of genotypes included in different clusters varied from 3 to 17. The results indicated that the optimum distance obtained in cluster VII (15.059) along with higher cluster mean values especially for filament length, non broken filament length, renditta, silk recovery, silk waste, and raw silk emphasized the utilization of these genotypes in the conventional silkworm breeding programme for improvement of multivoltine silk fibre quality. The possibility of exploiting genetic variation in post cocoon traits for efficient breeding programme is discussed.

• 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.