• 한국동물학회지
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• 제24권2호
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• pp.91-98
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• 1981

Deer mice, Peromyscus maniculatus, 의 성체 571마리의 30개 morphometric 형질들을 이용한 cluster analyses에서 두가지의 similarity 행렬식 (Average taxonomic distance와 Correlation coefficient 행렬식)을 이용한 dendrogram이 서로 다르다는 것이 확인되었다. 이들 두가지의 행렬식 중에서 taxarks의 형태적인 유연관계를 나타내는 하나의 dendrogram만을 선택하기 위한 한 객관적방법이 제안되었다. 즉 principal component analysis에 의한 결과를 비교할 표준결과로 이용하는 방법이다.

• 한국지하수토양환경학회지:지하수토양환경
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• 제27권6호
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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.

• 한국작물학회지
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• 제49권4호
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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.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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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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• 제16권6호
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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.

• 상하수도학회지
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• 제27권3호
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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.

• 한국지능시스템학회논문지
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• 제25권6호
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• pp.592-599
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• 2015

빅 데이터 환경에서 빅데이터를 분석하기 위한 새로운 방법의 필요성이 대두되고 있다. 데이터의 크기, 다양성, 그리고 적재 속도 등의 빅데이터 특성으로 인해 모집단의 추론에서 전체 데이터의 분석이 가능해졌기 때문이다. 그러나 전통적인 통계분석 방법은 모집단으로부터 추출된 확률표본에 초점이 맞추어져 있다. 따라서 기존의 통계적 접근방법은 빅데이터 분석에 적합하지 않은 경우가 발생한다. 이와 같은 문제점을 해결하기 위하여 본 논문에서는 빅데이터분석을 위한 새로운 접근방법에 대하여 제안하였다. 특히 대표적인 다변량 통계분석 기법인 주성분 분석을 이용하여 효율적인 빅데이터분석을 위한 방법론을 연구하였다. 제안방법의 성능평가를 위하여 통계적 모의실험을 실시하였다.

• Journal of Ecology and Environment
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• 제31권4호
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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.

• 대한환경공학회지
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• 제38권2호
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• pp.71-78
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• 2016

본 연구에서는 낙동강 창녕함안보 구간의 수질을 통계분석을 이용하여 수질 특성을 파악하였다. 다양한 통계분석기법 중에서 상관분석과 주성분분석 및 요인분석을 실시하였으며, 강우에 따른 조류의 천이양상을 연구하였다. 이는 향후 창녕함안보 구간의 수질관리정책 수립을 위한 기초 자료를 구축하는데 매우 중요한 자료이다. 측정 자료의 상관성 분석 결과, 클로로필-a와 조류는 상관성이 유의하지 않게 나타났으며, 요인분석 결과로 3개의 주성분이 추출되었으며, 제 1요인으로는 COD, TOC, BOD, pH, 수온이 분류되었다. 또한, 강우에 따른 조류의 천이양상을 분석한 결과, 강우 후에는 남조류의 수중개체 농도가 감소하는 추세를 보인 반면, 규조류와 녹조류의 개체 농도는 다소 증가하였다.

• 식물분류학회지
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• 제38권2호
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• pp.93-109
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• 2008

본 연구에서는 B. amurensis complex를 구성하는 세 분류군, 매발톱나무(B. amurensis Rupr. var. amurensis), 섬매발톱나무[B. amurensis var. quelpaertensis (Nakai) Nakai] 및 왕매발톱나무(B. amurensis var. latifolia Nakai)를 대상으로 형태 변이 분석을 수행하여 이들에 대한 기존의 분류학적 견해를 논의하였다. 분류군 간에 차이를 나타낼 것으로 조사된 22개 형질에 대한 변이 양상 조사 및 주성분분석을 수행한 결과 섬매발톱나무는 엽신의 길이와 폭, 엽정의 각도, 거치 간격, 절간 길이, 화서당 꽃의 수 등 여러 형질에서 나머지 두 분류군과 차이를 보였고, 왕매발톱나무는 엽정의 각도, 엽신의 폭과 길이 비에서 다른 두 분류군과 달랐다. 주성분분석 결과 엽신의 길이와 폭 및 엽정의 각도 등 잎의 형질이 분류군의 차이를 잘 반영하는 유용한 형질로 재확인되었으며, 절간의 길이와 화서를 구성하는 꽃의 수는 이들 종내 분류군들을 구분하는 새로운 식별형질로 밝혀졌다. 이들 세 분류군의 지리적 분포와 변이 양상 및 주성분분석 결과를 종합해 고려할 때 섬매발톱나무와 왕매발톱나무를 각각 변종으로 인정하는 것이 가장 타당할 것으로 판단하였다.