• 농촌계획
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• 제12권1호
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• pp.37-48
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• 2006

The objectives of this study were to develop an evaluation method of regional vulnerability to agricultural drought and to classify the vulnerability patterns. In order to test the method, 24 city or county areas of Gyeonggi-do were chose. First, statistic data and digital maps referred for agricultural drought were defined, and the input data of 31 items were set up from 5 categories: land use factor, water resource factor, climate factor, topographic and soil factor, and agricultural production foundation factor. Second, for simplification of the factors, principal component analysis was carried out, and eventually 4 principal components which explain about 80.8% of total variance were extracted. Each of the principal components was explained into the vulnerability components of scale factor, geographical factor, weather factor and agricultural production foundation factor. Next, DVIP (Drought Vulnerability Index for Paddy), was calculated using factor scores from principal components. Last, by means of statistical cluster analysis on the DVIP, the study area was classified as 5 patterns from A to E. The cluster A corresponds to the area where the agricultural industry is insignificant and the agricultural foundation is little equipped, and the cluster B includes typical agricultural areas where the cultivation areas are large but irrigation facilities are still insufficient. As for the cluster C, the corresponding areas are vulnerable to the climate change, and the D cluster applies to the area with extensive forests and high elevation farmlands. The last cluster I indicates the areas where the farmlands are small but most of them are irrigated as much.

• 노동경제논집
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• 제28권1호
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• pp.61-82
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• 2005

본 연구는 경제 위기 이후 한국 제조업의 산업간 임금격차가 경제위기 이전 그대로 유지되고 있는가의 여부와, 임금을 결정하는 메커니즘이 외환위기를 지나면서 어떻게 변화하였는가에 관하여 분석하였다. 분석에 사용된 자료는 1995년도와 1999년도 노동부의 "임금구조기본통계조사"이고, 주된 계량 기법으로는 요인분석(factor analysis)과 주성분 회귀분석(principal components regression)을 사용하였다. 분석 결과, 제조업의 산업간 임금격차는 더 벌어졌으며 임금결정의 주된 요인도 외환위기 이전에는 개인의 업무능력이었으나 위기 이후에는 사업체의 특성인 것으로 밝혀졌다.

• 환경위생공학
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• 제9권2호
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• pp.8-23
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• 1994

During the period from Mar., 1991 to Feb., 1992 66 tSP samples were collected by Hi volume air sampler at 1 sampling site in Seoul and the amount of concentration of 21 components(SO$_{4}$$^{2-}$, NO$_{3}$$^{-}$, NH$_{4}$$^{+}$, Cl$^{-}$, Al, Ba, Ca, Cd, Cr, Cu, Fe, It Mg, Mn, Na, Ni, Pt Si, Ti, Zn, Zr ) were measured. And monthly and seasonal variation were surveyed and the principal component analysis( PCA ) were carried out with respect to these amount of pollutants, minimum of visibility and radiation on a horizontal surface. The total amount of soluble ion in water was high in order o(SO$_{4}$$^{2-}$> NO$_{3}$$^{-}$> N%'>Cl$^{-}$ and metal ion was high in order of Na> Ca>Si> Fe> Al> K> Mg> Zn> Pb> Cu>Ti> Mn > Ba> Cr> Zr> Ni> Cd. There was Seasonal variation in concentration for SO$_{4}$$^{2-}$, NH$_{4}$$^{+}$, Cl$^{-}$, Na, Al, Ca, Bt Mg, Fe and Si. It was assumed that the components of the highest concentration on April were depend on yellow sand and the frequency of wind velocity and direction. As the results of PCA, the amount of pollution components was able to characterized with two principal components(Z$_{1}$, Z$_{2}$ ). The first principal components Z$_{1}$ was considered to be a factor indicating the pollutants originated from natural generation and The second principal components Z$_{2}$ was considered to be a factor indicating the pollutants originated from human work. The monthly concentration of pollutants in ISP, minimum of visibility and radiation on a horizontal surface was possible to evaluate by the use of these two principal components Z$_{1}$ and Z$_{2}$ .

• 융합신호처리학회논문지
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• 제11권4호
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• pp.320-325
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• 2010

본 논문은 주성분 분석을 이용하는 얼굴인식 시스템에서 인식후보를 점진적으로 등록하기 위한 방법과 절차에 관한 연구이다. 점진적인 주성분 갱신 방법으로 R-SVD알고리즘을 변형한 SKL 알고리즘을 이용한다. SKL 알고리즘을 이용하면 주성분을 이용하는 얼굴 인식의 문제점으로 지적되어 왔던 인식 후보의 점진적 증가에 따른 재학습 문제를 해결할 수 있다. 또한 이 방법은 밝기 변화에 견고한 객체 트랙킹 분야에도 이용될 수 있다. 본 논문에서는 얼굴인식 시스템에서 SKL 알고리즘을 이용하여 주성분을 점진적으로 갱신하며 적용하는 절차를 제안하고, 표준 KL 변환에 의하여 주성분을 일괄적으로 계산하는 결과와 얼굴 인식성능을 비교한다. 그리고 SKL 알고리즘에 포함된 망각 인자(forgetting factor)가 얼굴인식 성능에 미치는 효과를 실험적으로 확인한다.

• 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.

• 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.

• 약학회지
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• 제48권1호
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• pp.6-12
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• 2004

Near-infrared spectra of methanol-water mixtures and acetonitrile-water mixtures were acquired to find interactions between solvents widely used for reverse-phase liquid chromatography. Mixtures were prepared to give a series of increasing mole fractions of methanol or acetonitrile in water. Data matrices of acquired spectra were analyzed to determine the proper number of principal components of each mixture system using Malinowski's factor indicator function. Initial guess of score matrix and loading matrix were calculated by nonlinear iterative partial least squares (NIPALS) algorithm for faster computation. Iterative target transform factor analysis (ITTFA) was applied to convert the initial estimation of score matrix to true concentration profile and loading matrix to pure spectra of pure components of the mixtures. In case of methanol-water the number of principal components was found to be 4 and those initial guess of factors were converted to the pure spectra of water methanol and two kinds of complexes. In case of acetonitrile-water the number of pure components of the mixtures was found to be 3 and the pure spectrum of acetonitrile-water complex was found. The nonlinear characteristics of concentration profiles of complexes in the solvent mixtures may give a good criteria in understanding their elution characteristics in reverse-phase liquid chromatogrsphy.

• Journal of Biosystems Engineering
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• 제34권2호
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• pp.114-119
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• 2009

Field test was conducted to investigate primary factors reducing rapeseed harvesting using a reciprocating cutter-bar of combine. The results showed that the correlation between crop moisture content and yield loss had a U-type, which indicated that the yield reduction increased at too high and too low crop moisture contents. The proper ranges of crop moisture contents were 27${\sim}$35%, 21${\sim}$56%, and 62${\sim}$73% in case of grain, pod and stem, respectively. Crop moisture content was negatively correlated with header loss, but positively correlated with threshing loss. In contrary, stem moisture content showed positive correlations with total loss, threshing loss and separation loss. Working speed was positively correlated with header loss. Total flow rate, pod flow rate and stem flow rate were highly correlated with threshing loss and separation loss. However, grain flow rate did not show any correlation with total loss. According to the principal component analysis, two principal components were derived as components with eigenvalues greater than 1.0. The contribution rates of the first and the second components were 52.7% and 38.9%, which accounted for 91.6% of total variance. As a contributive factor influencing total loss of rapeseed mechanical harvesting, a crop moisture content factor was greater than a crop flow rate factor. The stepwise multiple regression analysis for total loss was conducted using crop moisture content factor, crop flow rate factor and coefficient. However, the model did not show any correlation among independent and dependent factors ($R^2$=0.060).

• 정보처리학회논문지B
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• 제15B권4호
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• pp.285-292
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• 2008

색상 히스토그램은 영상의 색상 특징을 표현하기 위한 특징 벡터로 빈번히 사용되지만, 고차원의 특징 벡터를 생성하므로 효율성의 면에서 한계점을 갖고 있다. 본 논문에서는 주어진 차량 영상의 색상 히스토그램에 PCA (principal components analysis) 기법을 적용하여 특징 벡터의 차원을 축소시키는 방법을 제안한다. 차원이 축소된 특징 벡터들에 대해서는 SVM (support vector machine) 기법을 적용하여 차량 색상을 인식하기 위해 사용한다. 특징 벡터의 차원을 1/32로 축소한 결과, 차원이 축소되기 이전의 특징 벡터와 비교하여 약 1.42%의 미소한 차이로 색상 인식 성공률이 감소하였다. 또한, 색상 인식의 수행 시간은 1/31로 단축됨으로써 효율적으로 색상 인식을 수행할 수 있었다.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2006년도 정기 학술대회 논문집
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• pp.1001-1008
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• 2006

The main objective of this paper is to compare economical effectiveness of typical methods for checking stability in principal components of steel cable-stayed bridges. Elastic and inelastic buckling analyses are carried out for frame-like numerical models of cable-stayed bridges. The axial-flexural interaction equations prescribed in AASHTO Allowable Stress Design (ASD) and AASHTO Load and Resistance Factor Design (LRFD) are used in order to check the stability of principal components. Parametric studies are performed for numerical models which have the center span length of 300m, 600m, 900m and l200m with different girder depths. Peak values of the interaction equations are calculated at the intersection point between girders and towers. These peak values are considered as a major factor to design of principal components of cable-stayed bridges. As a result, more economical design for girders and towers can be feasible using the inelastic buckling analysis. In addition, LRFD codes are more economical about 20% on the average than ASD codes for all numerical models of cable-stayed bridges.