• The Korean Journal of Zoology
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• v.24 no.2
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• pp.91-98
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• 1981

It has been confirmed that two dendrograms resulted from two similarity matrices, average taxonomic distance and correlation coefficient matrices, are different with each other when cluster analyses were performed with 571 adults of deer mice, Peromyscus maniculatus using 30 morphometric characters. To choose one of two similarity matrices mentioned above in order to construct a dendrogram representing phenetic relationships among taxa, an objective method using the result from principal component analysis as a standard result to compare with two matrices has been suggested.

• Journal of Soil and Groundwater Environment
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• v.27 no.6
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• pp.22-36
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• 2022

Water resources in Jeju Island are dependent virtually entirely on groundwater. For groundwater resources, drought damage can cause environmental and economic losses because it progresses slowly and occurs for a long time in a large area. Therefore, this study quantitatively evaluated groundwater level fluctuations using principal component and cluster analyses for 42 monitoring wells in Jeju Island, and further identified the types of groundwater fluctuations caused by drought. As a result of principal component analysis for the monthly average groundwater level during 2005-2019 and the daily average groundwater level during the dry season, it was found that the first three principal components account for most of the variance 74.5-93.5% of the total data. In the cluster analysis using these three principal components, most of wells belong to Cluster 1, and seasonal characteristics have a significant impact on groundwater fluctuations. However, wells belonging to Cluster 2 with high factor loadings of components 2 and 3 affected by groundwater pumping, tide levels, and nearby surface water are mainly distributed on the west coast. Based on these results, it is expected that groundwater in the western area will be more vulnerable to saltwater intrusion and groundwater depletion caused by drought.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.49 no.4
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• pp.295-299
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• 2004

The prices of domestic green tea products are relatively expensive and price differences within products of the same levels of quality are various. Also, there is no basic criteria on evaluation of green tea quality. To group 43 commercial green tea products into several parts by the principal component and cluster analyses, this work was done by use of 8 chemical constituents which were analyzed by NIR system. The principal component and cluster analyses revealed 8 groups. The first group included 16 products that had lower free amino acid and theanine contents. The second group included 5 products having higher free amino acid and theanine contents, but lower ash contents. The third group included 13 products showing medium values of 8 constituents. The IV group included 4 products having higher contents of moisture, free amino acids, and theanine. The V group included 1 product showing higher moisture but lower catechins contents. The VI group included 2 products that had higher moisture and catechins contents, but lower free amino acid and theanine contents. The VII group had higher moisture and catechins contents. The VIII group had higher ash and vitamin C contents. The free amino acid contents which were the most important in flavor evaluation of green tea quality did highly positively correlate with the contents of total nitrogen $(0.956^{**}),\;theanine\;(0.981^{**}),\;and\;caffeine\;(0.793^{**})$, but negatively with the contents of ash $(-0.884^{**})$. The catechins used as for functional ingredients did correlate with contents of caffeine(+) and vitamin C(-), respectively.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.645-648
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• 2003

Induction motors are a critical component of industrial processes. Sudden failures of such machines can cause the heavy economical losses and the deterioration of system reliability. Based on the reliability and cost competitiveness of driving system (motors), the faults detection and the diagnosis of system are considered very important factors. In order to perform the faults detection and diagnosis of motors, the vibration monitoring method and motor current signature analysis (MCSA) method are emphasized. In this paper, MCSA method is used for induction motor fault diagnosis. This method analyses the motor's supply current. since this diagnoses faults of the motor. The diagnostic algorithm is based on the principal component analysis(PCA), and the diagnosis system is programmed by using LabVIEW and MATLAB.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.6
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• pp.2561-2567
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• 2015

Pancreatic ductal adenocarcinoma (PDAC) is a leading cause of cancer death worldwide. Our study aimed to reveal molecular mechanisms. Microarray data of GSE15471 (including 39 matching pairs of pancreatic tumor tissues and patient-matched normal tissues) was downloaded from Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) in PDAC tissues compared with normal tissues by limma package in R language. Then GO and KEGG pathway enrichment analyses were conducted with online DAVID. In addition, principal component analysis was performed and a protein-protein interaction network was constructed to study relationships between the DEGs through database STRING. A total of 532 DEGs were identified in the 38 PDAC tissues compared with 33 normal tissues. The results of principal component analysis of the top 20 DEGs could differentiate the PDAC tissues from normal tissues directly. In the PPI network, 8 of the 20 DEGs were all key genes of the collagen family. Additionally, FN1 (fibronectin 1) was also a hub node in the network. The genes of the collagen family as well as FN1 were significantly enriched in complement and coagulation cascades, ECM-receptor interaction and focal adhesion pathways. Our results suggest that genes of collagen family and FN1 may play an important role in PDAC progression. Meanwhile, these DEGs and enriched pathways, such as complement and coagulation cascades, ECM-receptor interaction and focal adhesion may be important molecular mechanisms involved in the development and progression of PDAC.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.3
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• pp.351-361
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• 2013

In this study the Principal Component Analysis (PCA) was applied to flow data in a water distribution pipe system to analyze the relevance between the flow observation dates, which have the outliers of observed night flows, and the maintenance records. The data was obtained from four small size water distribution blocks to which 13 maintenance records such as pipe leak and water meter leak belong. The flow data during four months were used for the analysis. The analysis was carried out to identify an appropriate analysis period for a PCA model for a water distribution block. To facilitate the analyses a computational algorithm was developed. MATLAB was utilized to realize the algorithm as a computer program. As a result, an appropriate PCA period for each of the case study small size water distribution blocks was identified.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.592-599
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• 2015

In big data environment, we need new approach for big data analysis, because the characteristics of big data, such as volume, variety, and velocity, can analyze entire data for inferring population. But traditional methods of statistics were focused on small data called random sample extracted from population. So, the classical analyses based on statistics are not suitable to big data analysis. To solve this problem, we propose an approach to efficient big data analysis. In this paper, we consider a big data analysis using principal component analysis, which is popular method in multivariate statistics. To verify the performance of our research, we carry out diverse simulation studies.

• Journal of Ecology and Environment
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• v.31 no.4
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• pp.309-316
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• 2008

To develop a monitoring method for soil microbial communities in rice paddy fields, we used terminal restriction fragment length polymorphism (T-RFLP) to compare soil bacterial community structure in rice paddy fields experiencing different management practices: organic practices, conventional practices without a winter barley rotation, and conventional practices with a winter barley rotation. Restriction fragment length profiles from soils farmed using organic practices showed very different patterns from those from conventional practices with and without barley rotation. In principal component analyses, restriction fragment profiles in organic practice samples were clearly separated from those in conventional practice samples, while principal component analysis did not show a clear separation for soils farmed using conventional practices with and without barley rotation. The cluster analysis showed that the bacterial species compositions of soils under organic practices were significantly different from those under conventional practices at the 95% level, but soils under conventional practice with and without barley rotation did not significantly differ. Although the loadings from principal component analyses and the Ribosomal DNA Project II databases suggested candidate species important for soils under organic farming practices, it was very difficult to get detailed bacterial species information from terminal restriction fragment length polymorphism. Rank-abundance diagrams and diversity indices showed that restriction fragment peaks under organic farming showed high Pielou's Evenness Index and the reciprocal of Simpson Index suggesting high bacterial diversity in organically farmed soils.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.2
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• pp.71-78
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• 2016

The study of water environment system in Changnyeong-Haman weir section using a statistical analysis has been conducted. Statistical analyses used in this study were the correlation analysis, the principal components, and the factor analysis. The purpose of the study is to establish better understanding of relationships between water quality factors in the Changnyeong-Haman weir section which can provide useful information to manage Nakdong river. According to correlation analyses on COD and TOC, it revealed that the value of correlation coefficient was 0.844. Furthermore, the results from the principal component analysis categorized the water quality factors into three factor groups, the first principal factor group included COD, TOC, BOD, pH, water temperature (WT). And, it was observed that the concentration of cyanobacteria in the water body decreased, while the concentrations of the diatoms and the green algae increased after the events of rainfall.

• Korean Journal of Plant Taxonomy
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• v.38 no.2
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• pp.93-109
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• 2008

The morphological variation was analysed to examine previous hypotheses on the taxonomy of B. amurensis complex which includes B. amurensis Rupr. var. amurensis, B. amurensis var. quelpaertensis (Nakai) Nakai and B. amurensis var. latifolia Nakai. The results from the univariational and principal components analyses employing 22 putatively diagnostic characters indicate that B. amurensis var. quelpaertensis is distinct from var. amurensis in the length and width of leaves, angle of leaf apex, distance between spinose teeth, length of internode, number of flowers per inflorescence, whereas B. amurensis var. latifolia is different from other varieties in the angle of leaf apex and leaf length/width ratio. In principal component analysis, the characters of the leaf including leaf width and length were the main characteristics to distinguish those three taxa. The evidence both from the principal components analyses and current geographical distribution pattern suggest that retaining the varietal status for the two taxa, B. amurensis var. latifolia and B. amurensis var. quelpaertensis is reasonable.