• 비파괴검사학회지
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• 제22권5호
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• pp.532-538
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• 2002

3가지 종류의 알루미늄 합금강의 피로균열 진전 시 균열 열림 및 닫힘에 따른 음향방출 신호를 분류하기 위하여 주성분 분석 방법과 인공신경망 기법을 적용하였다. 재료의 균열 열림과 닫힘, 마찰 등과 같은 여러 가지 AE 신호를 얻기 위하여 피로시험을 수행하였다. 주성분 분석결과 AE 파라미터의 제 1 및 제 2 주성분만으로도 균열 열렴 및 닫힘에 대한 AE 신호의 변이를 94% 이상 설명할 수 있는 것으로 분석되어 주성분 분석 기법을 이용한 균열 열림 및 닫힘에 대한 신호해석이 가능한 것으로 나타났다. AE 신호의 주성분들을 입력변수로 사용한 인공신경망을 이용하여 균열 열림 및 닫힘을 분류할 수 있는 분류기를 개발하고 평가한 결과 분류기의 입력 변수로서 2개의 주성분을 이용 할 경우 전체 AE 파라미터를 입력변수로 사용한 경우 보다 분류 성능이 향상되었다.

• Plant Resources
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• 제5권3호
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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.

• 대한공간정보학회지
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• 제23권3호
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• pp.85-93
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• 2015

This paper mainly introduces the methods of extracting landslide information using ALOS(Advanced Land Observing Satellite) images and GIS(Geographical Information System) technology. In this study, we classified images using three different methods which are the unsupervised the supervised and the PCA(Principal Components Analysis) for extracting landslide information based on characteristics of ALOS image. From the image classification results, we found out that the quality of classified image extracted with PCA supervised method was superior than the other images extracted with the other methods. But the accuracy of landslide information extracted from this image classification was still very low as the pixels were very similar between the landslide and safety regions. It means that it is really difficult to distinguish those areas with an image classification method alone because the values of pixels between the landslide and other areas were similar, particularly in a region where the landslide and other areas coexist. To solve this problem, we used the LSM(Landslide Susceptibility Map) created with ArcView software through weighted overlay GIS method in the areas. Finally, the developed LSM was applied to the image classification process using the ALOS images. The accuracy of the extracted landslide information was improved after adopting the PCA and LSM methods. Finally, we found that the landslide region in the study area can be calculated and the accuracy can also be improved with the LSM and PCA image classification methods using GIS tools.

• Journal of Pharmaceutical Investigation
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• 제39권1호
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• pp.43-49
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• 2009

Aspirin or acetylsalicylic acid, a member of the salicylate family, is frequently used as an analgesic, antipyretic, anti-inflammatory and antiplatelet drug. Because aspirin is chemically unstable in water and heat for tablet formulation, additives including lubricants are used in preparing aspirin tablets, using a dry-granulation process. Aspirin tablets are produced by a number of manufacturers which usually use their own unique combination of additives during the manufacturing process. In this study, we employed an NMR based metabolomics technique to identify the manufacturers of various aspirin tablets. Aspirin tablets from six different companies were analyzed by 1H 400 MHz NMR. The acquired data was then integrated and processed by principal component analysis (PCA). Based on the NMR data, we were able to identify peaks corresponding to acetylsalicylic acid in all of the six samples, whereas different NMR patterns were found in the aromatic and aliphatic regions depending on the unique additive used. These observations led to the conclusion that the differences in the NMR patterns among the different aspirin tablets were due to the presence of additives.

• 한국약용작물학회지
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• 제20권6호
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• pp.466-471
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• 2012

'Usul' is a traditional medicinal herb, which has anti-inflammatory activities is distributed in India, Nepal, China, Korea, Japan. Korea pharmacopeia listed 'Usul' as either a species of Achyranthes japonica (Miq.) Nakai or A. bidentata Blume. Recent taxonomic studies in China and Japan delimited these taxa as two varieties, A. bidentata Blume var. bidentata and var. japonica Miq. A multivariate morphometric study of Achyranthes bidentata complex was undertaken to assess the entities of taxa that usefully could be recognized. Five quantitative characters were reviewed and analyzed with 293 specimens from Korea. The univariate analysis of inflorescence length, interval between florets, angle between floret and floral axis indicated that ranges among all taxa were continuous. However, quantitative characters of membrane size and the number of hairs within 4 were useful to identify two varieties. In PCA, the first three principal components accounted for 89.4% of the total variance. PCA revealed that var. bidentata showed distinctions in morphological attributes from var. japonica entity. Therefore, continued recognition at the infraspecifc level for these taxa is supported.

• 한국의학물리학회지:의학물리
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• 제14권4호
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• pp.211-217
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• 2003

주성분분석은 잘 알려진 데이터 분석 방법으로써 높은 차원의 데이터를 낮은 차원의 데이터로 표현하는데 효과적이어서 얼굴인식, 데이터 압축 등에 이용되고 있다. 주성분분석을 하게 되면 원 데이터의 공분산 행렬로부터 정규직교한 고유벡터와 해당하는 고유치를 얻게 되고 그 중 큰 값을 가지는 고유벡터 들을 선택하여 선형 변환함으로써 데이터의 차원을 줄일 수 있게 된다. 망막에 빛 자극이 인가되면 시세포 층에서 전기신호로 변환된 후 복잡한 신경회로를 거쳐 최종적으로 신경절세포 층에서 활동전위의 형태로 출력되게 된다. 본 연구에서는 다채널전극을 사용하여 여러 개 망막 신경절세포로부터 유래되는 활동전위를 기록한 후 개개의 신호를 구분하는 과정을 거치고, 이어서 그 신호를 만들어 내는 각 뉴론들끼리의 시간적, 공간적 흥분발사 패턴을 이해함으로써 궁극적으로 시각정보 인코딩 기전을 밝히려는 연구 목표하에 그 첫 단계로서 망막 신경절세포의 활동전위를 기록한 후 분류하는 과정을 성공적으로 수행하였기에 그 내용을 서술하고자 한다. 망막에서 기록되는 신경절세포 활동전위는 불규칙하고 확률적이기 때문에 주성분분석을 통하여 그 유형을 분류할 수 있었다. 토끼 눈으로부터 망막을 박리하여 망막조각을 얻은 후 신경절세포 층이 전극표면을 향하도록 전극에 부착하였다. 8${\times}$8의 microelectrode array (MEA)를 전극으로 사용하였고, 증폭기는 MEA 60 system을 사용하여 신경절세포 활동전위를 기록하였다. 활동전위 기록 후 파형 분류를 하였다. 잡음이 섞여있는 기록으로부터 신호를 검출하기 위하여, 잡음역치($\pm$3$\sigma$)를 설정하였다. 역치를 넘는 파형 만을 획득한 후 주성분분석을 통해 각 파형의 첫 번째 주성분, 두 번째 주성분을 계산하여 2차원 평면에 투사함으로써 몇 개의 의미있는 클러스터를 얻었다. 이 클러스터는 곧 각 신경절세포에서 유래되는 파형을 반영하므로 주성분분석을 통하여 망막 신경절세포의 활동전위를 각 세포별로 분류할 수 있음을 확인하였다.

• 한국기후변화학회지
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• 제7권3호
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• pp.269-282
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• 2016

Watershed area can be submerged due to constructions and management of dams, and these change can impact not only on ecosystem and environment of river basin area but also on local climate. This study is conducted to construct and classify climate zones of Andong Dam watershed where the area is submerged due to the construction of the dam. By applying Principal Components Analysis (PCA) and Getis-Ord $Gi^*$ statistics, three climate zones were classified for the result. Each zone was then analyzed and validated with climatic and geological features including topography, land cover, and forest type map. As a result of the analysis, there was a difference in temperature, elevation, precipitation and tree species distribution among the zones. Also, an analysis of land cover map showed that there were more agricultural land near Andong Reservoir. This study on the climatic classification is considered to be useful as the basis for decision-making or policy enforcement regarding ecosystem, environmental management or climate change response.

• Journal of Information Processing Systems
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• 제10권4호
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• pp.555-567
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• 2014

Biometric performance improvement is a challenging task. In this paper, a hierarchical strategy fusion based on multimodal biometric system is presented. This strategy relies on a combination of several biometric traits using a multi-level biometric fusion hierarchy. The multi-level biometric fusion includes a pre-classification fusion with optimal feature selection and a post-classification fusion that is based on the similarity of the maximum of matching scores. The proposed solution enhances biometric recognition performances based on suitable feature selection and reduction, such as principal component analysis (PCA) and linear discriminant analysis (LDA), as much as not all of the feature vectors components support the performance improvement degree.

• 한국가스학회지
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• 제18권3호
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• pp.53-59
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• 2014

본 연구에서는 비정상상태 운전을 기본으로 하는 CNG 충전소를 대상으로 다변량 통계분석방법 중의 하나인 다차원의 대용량 데이터 처리에 적합한 주성분분석(PCA) 기법을 사용하여 실시간 이상감지 및 진단이 가능한 모니터링 시스템을 제안하였다. CNG 충전소로부터 매초 간격으로 수집되는 7개의 압력센서 데이터와 5개의 온도센서 데이터의 주요 경향을 나타내는 변수들의 조합으로 주성분이라 불리는 새로운 특성변수들을 산출하고, 분산의 분포를 통해 특성변수의 계산으로부터 모델을 구축하였다. 모니터링은 구축된 모델을 통해 운전 중의 실시간 데이터를 반영하여 진행된다. 시스템 검증 및 정확성을 개선하기 위해 모니터링 테스트를 수행한 결과, 정상상태의 모든 데이터를 정상으로 판단하였고, 이상 데이터의 성공적인 검출 시 관련 변수를 추적하여 비정상 원인을 찾아낼 수 있었다.

• 센서학회지
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• 제22권3호
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• pp.219-222
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• 2013

The exhaled breath contains gases generated from human body. When disease occurs in the body, exhaled breath may include gas components released from disease metabolism. If we can find specific elements through analysis of the exhaled gases, this approach is an effective way to diagnose the disease. The lung function has a close relationship with exhalation. Exhaled gases from COPD (Chronic Obstructive Pulmonary Disease) patients can be analyzed by gas chromatography-mass spectroscopy (GC-MS) and a gas sensor system. The exhaled breath for healthy person and COPD patients had different components. Significantly more benzendicarboxylic acid was detected from COPD patients than in healthy persons. In addition, patients had a variety of decane. Phosphorous compounds with different isomers were detected from patients. The results obtained by gas sensor system were processed by PCA (Principal Component Analysis). The PCA results revealed distinct difference between the patients and healthy people.