• 대한의용생체공학회:의공학회지
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• 제27권2호
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• pp.59-63
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• 2006

Magnetocardiogram (MCG) topography is a useful diagnostic technique that employs multi-channel magnetocardiograms. Measurement of artifact-free MCG signals is essenctial to obtain MCG topography or map for a diagnosis of human heart. Principal component analysis (PCA) combined with an artificial neural network (ANN) is proposed to remove a pulse-type artifact in the MCG signals. The algorithm is composed of a PCA module which decomposes the obtained signal into its principal components, followed by an ANN module for the classification of the components automatically. In the experiments with volunteer subjects, 97% of the decisions that were made by the ANN were identical to those by the human experts. Using the proposed technique, the MCG topography was successfully obtained without the artifact.

• 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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• 제43권1호
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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.

• 정보보호학회논문지
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• 제24권5호
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• pp.1013-1022
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• 2014

상관관계 전력 분석(Correlation Power Analysis, CPA)은 암호장비에서 알고리즘이 수행될 때 누설되는 전력 소비 신호와 알고리즘의 중간 계산 값의 상관도를 이용하여 비밀키를 추출하는 부채널 공격 방법이다. CPA는 누설된 전력 소비의 시간적인 동기 또는 잡음에 의해 공격 성능이 영향을 받는다. 최근 전력 분석의 성능 향상을 위해 다양한 신호 처리 기술이 연구되어지고 있으며, 그 중 주성분 분석 기반의 신호 압축 기술이 제안되었다. 주성분 분석 기반의 신호 압축은 주성분 선택 방법에 따라 분석 성능에 영향을 주기 때문에 주성분 선택은 중요한 문제이다. 본 논문에서는 CPA의 성능 향상을 위해 전력 소비와의 상관도가 높은 주성분을 선택하는 주성분 선택 기법을 제안한다. 또한 각 주성분이 갖는 특징이 다르다는 점을 이용한 주성분 기반 CPA 분석 기법을 제안하고, 기존 방법과 제안하는 방법의 실험적인 분석을 통해 공격 성능이 향상됨을 보인다.

• KDI Journal of Economic Policy
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• 제42권2호
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• pp.57-84
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• 2020

This study analyzes global inflation synchronization and derives policy implications for the Korean economy. Unlike previous studies that assume a single global inflation factor, this study investigates if inflation in Korea can be explained further by other global inflation factors. Our principal component analysis provides three principal components for global inflation that are linked to the Korea inflation rate - the first component is closely related to OECD inflation, and the second and third components reflect China's inflation. This study empirically demonstrates via in-sample fitting and out-of-sample forecasting that the three principal components of global inflation play a significant role in explaining and predicting Korean inflation in the short-term, while their role is limited in the mid-term. Domestic macroeconomic variables are found to be more important for the mid-term movements of the Korean inflation rate. The empirical results here suggest that the Bank of Korea should focus more on domestic economic conditions than on global inflation when implementing monetary policy because global factors are likely to be already reflected in domestic macro-variables in the mid-term.

• 비파괴검사학회지
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• 제23권3호
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• pp.254-262
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• 2003

본 연구는 목재(참나무 판목 판재) 건조 중 발생하는 음향방출 신호에 대하여 목재 내 수분이동에 의한 신호와 표면할열에 의한 신호를 해석하고 분류하기 위하여 수행되었다. AE 신호의 특징값들에 대한 상관분석을 실시하여 상호의존성이 높은 변수를 제거한 후 주성분 분석을 실시하였다. AE 변수들을 독립변수로 한 분류기와 주성분들을 독립변수로 한 분류기에 대하여 분류성능을 비교하였다. 목재 건조 시 발생하는 표면할열과 수분이동에 따른 AE 신호 파형을 분석한 결과 대체적으로 표면할열에 의한 신호가 최대진폭이 크며 상승시간이 팎고 상대적으로 고주파의 신호인 것으로 분석되었다. 다중 회귀분석모델을 이용하여 수분이동에 의한 신호와 표면할열에 의한 신호를 분류할 수 있는 분류기를 개발하고 평가한 결과 개별 AE 변수들을 독립변수로 하는 분류기 보다 주성분들을 독립변수로 하는 분류기의 분류성능이 양호한 것으로 나타났다.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2003년도 춘계 학술발표회 논문집
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• pp.151-156
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• 2003

Variable selection algorithm for principal component analysis using penalized likelihood method is proposed. We will adopt a probabilistic principal component idea to utilize likelihood function for the problem and use HARD penalty function to force coefficients of any irrelevant variables for each component to zero. Consistency and sparsity of coefficient estimates will be provided with results of small simulated and illustrative real examples.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2001년도 춘계학술대회논문집:21세기 신지식정보의 창출
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• pp.280-287
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• 2001

The studies to estimate the surface spectral reflectance of an object have received widespread attention using the multi-spectral camera system. However, the multi-spectral camera system requires the additional color filter according to increment of the channel and system complexity is increased by multiple capture. Thus, this paper proposes an algorithm to reduce the estimation error of surface spectral reflectance with the conventional 3-band RGB camera. In the proposed method, adaptive principal components for each pixel are calculated by renewing the population of surface reflectances and the adaptive principal components can reduce estimation error of surface spectral reflectance of current pixel. To evacuate performance of the proposed estimation method, 3-band principal component analysis, 5-band wiener estimation method, and the proposed method are compared in the estimation experiment with the Macbeth ColorChecker. As a result, the proposed method showed a lower mean square ems between the estimated and the measured spectra compared to the conventional 3-band principal component analysis method and represented a similar or advanced estimation performance compared to the 5-band wiener method.

• 수산경영론집
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• 제14권2호
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• pp.1-14
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• 1983

This paper considers a classification of the 88 islands located at Kyong-nam area in Korea, using by examples of 12 components of the islands. By means of principal component analysis 2 principle components were extracted, which explained a total of 73.7% of the variance. Using an eigen variable criterion (λ>1), no further principle components were discussed. Principal component 1 and 2 explained 63.4% and 10.3% of the total variance respectively, The representation of the unrelated factor scores along the first and second principal axes produced a new information with respect to the classification of the islands. Based upon the representation, 88 islands were classified into 6 groups i. e. A, B, C, D, E, and F according to similarity of the components among them in this paper. The "Group F" belongs to a miscellaneous assortment that does not fit into the logical category. category.

• 한국의류학회지
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• 제14권3호
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• pp.208-215
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• 1990

The purpose of this study is to provide the fundamental data of a dummy design for more suitable ready made clothing by making a pattern of somatic types and analyzing their morphological characteristics in accordance with different pattern of somatic types. The side view silhouettes of 90 junior high school girls of age $13\~16$ in seoul urban area were measured by means of the plan photographing and the low data were examined by principal component analysis, while the principal component analysis was applied and three components were extracted and then interpreted to explain to variation of the form of the body. Using three components respectively the cluster analysis was carried out and the subject classified into 4 cluster The following outcomes are obtained. . The results of principal component analysis of this study would be turned out the three; 1) The first principal component shows the degree of erectness or stoop of the figure. 2) The second principal component was a stature length or a growth rate. 3) The third principal component was the obesity component. 2. The results of cluster analysis by using three principal component analysis would be turned out the four cluser; 1) Cluster 1 ($29\%$ of the total) is characterized with lower stature. 2) Cluster 2 ($21\%$ of the total) is characterized with backward somatotype, and the highest leg. 3) Cluster 3 ($23\%$ of the total) is thicked back of neck. 4) Cluster 4 ($27\%$ of the total) is characterized with forward somatotype, and highest stature, height.