• 한국잠사곤충학회지
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• 제32권1호
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• pp.17-30
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• 1990

주성분분석에 의하여 분류된 148개 보존잠품종중에서 제일주성분 score에 따라 10개의 교배모품종을 선발한 후 (정등, 1989), 이들로부터 Top-교잡에 의해 24개 교배조합을 작성하고 조합능력검정을 행함과 동시에 주성분과 교배조합능력과의 상호관계를 분석하였다. 1. 선발된 육종모품종중에서 일본종계 N$_{39}$ 및 중국종계 $C_{46}$ 이 대부분의 형질에서 일반조합능력이 높았다. 2. 특정조합능력은 형질 또는 교배조합에 따라 차이가 심하였다. 3. 육종모품종의 제1주성분 score는 5영경과일수, 전령경과일수, 수견량, 전견중, 견층중, 견층비율, 견사장, 견사량, 해서사장, 생사량비율, 소절등의 일반조합능력과 고도의 정의 상관관계가 있었다. 4. 유사도거리(D$^2$)는 수견양, 해서사장, 해서사량, 해서율, 생사량비율, 소절등의 특정조합능력과 정의 상관이 있었다. 따라서 교배조합의 양친이 원연일수록 이들 5개형질에 대한 특정조합능력은 높게 나타났다. 5. 육종모품종의 특성을 이용한 주성분분석의 제1주성분 score에 의해 일반조합능력의 예측이 가능하였다.

• 한국산학기술학회논문지
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• 제14권9호
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• pp.4342-4348
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• 2013

본 연구는 혈청지질과 비만 및 혈압과의 관련성을 검토하기 위하여 2011년 1월부터 12월까지 1년 동안에 대전광역시의 한 대학병원에서 종합건강검진을 받았던 30세에서 69세의 여성 1,381명을 대상으로 TC, TG, HDL-C, LDL-C, SBP, DBP, 비만도, 체지방률을 측정하여 혈청지질과 비만 및 혈압과의 관련성을 분석하였다. 연구결과, TC, TG, LDL-C, 비만도, 체지방률은 30대에서부터 60대에 걸쳐 단계적으로 상승하는 경향을 보였다. TC, TG 및 LDL-C는 혈압이 높아짐에 따라 상승하였으며, 정상혈압군에 비해 고혈압군에서 유의하게 높은 값을 보였다. TC, TG, SBP 는 비만도가 높아짐에 따라 단계적으로 상승하였고, 정상군에 비해 비만군에서 유의하게 높았으며, HDL-C는 비만도가 높아짐에 따라 감소하는 경향을 보였고, 정상군에 비해 비만군에서 유의하게 낮았다. TC, TG, LDL-C, 체지방률 및 비만도는 상호간에 유의한 정상관을 보인 반면, HDL-C와는 음의 상관을 보였다. 주성분분석 결과 제1주성분은 고혈압 인자, 제2주성분은 비만관련 인자, 제3주성분은 연령과 고지혈증 인자, 제4주성분은 고단백지콜레스테롤 인자가 선정되었다. HDL-C와 관련된 요인을 다중회귀분석을 사용하여 검토한 결과 HDL-C에 영향을 미치는 변수로는 연령, TC, TG 및 체지방률이 선정되었다. 위와 같은 결과는 비만도가 높고 혈압이 높은 군일수록 혈청지질치가 높아짐을 시사하고 있다.

• Progress in Superconductivity
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• 제4권2호
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• pp.114-120
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• 2003

We employed a method eliminating a temporally partial principal component (PC) of multichannel-recorded neuromagnetic fields for excluding spatially correlated noises from event-evoked signals. The noises in magnetoencephalography (MEG) are considered to be mainly spontaneous neuromagnetic fields which are spatially correlated. In conventional MEG experiments, the amplitude of the spontaneous neuromagnetic field is much lager than that of the evoked signal and the synchronized characteristics of the correlated rhythmic noise makes it possible for us to extract the correlation noises from the evoked signal by means of the general PC analysis. However, the whole-time PC of the fields still contains a little projection component of the evoked signal and the elimination of the PC results in the distortion of the evoked signal. Especially, the distortion will not be negligible when the amplitude of the evoked signal is relatively large or when the evoked signals have a spatially-asymmetrical distribution which does not cancel out the corresponding elements of the covariance matrix. In the period of prestimulus, there are only the spontaneous fields and we can find the pure noise PC that is not including the evoked signal. Besides that, we propose a method, called the extended temporal decorrelation method (ETDM), to suppress the distortion of the noise PC from remanent evoked signal components. In this study, we applied the Partial Principal component elimination method (PPCE) and ETDM to simulated signals and the auditory evoked signals that had been obtained with our homemade 37-channel magnetometer-based SQUID system. We demonstrate here that PPCE and ETDM reduce the number of epochs required in averaging to about half of that required in conventional averaging.

• 한국측량학회지
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• 제28권3호
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• pp.361-367
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• 2010

이 연구에서는 국토지리정보원 14개 GPS 상시관측소에서 수집된 약 5년간의 GPS 자료를 고정밀 처리하여 연속적인 수직좌표 시계열을 생성하였다. 그리고 1차 선형회귀식을 사용하여 GPS 상시관측소 속도를 계산하였으며, GPS 수직좌표 변동 경향을 분석하기 위해 주성분분석을 실시하였다. 가장 우세한 성분의 신호를 나타내는 모드 1을 대상으로 분석한 결과 약 4.2mm/yr의 수직 속도가 산출되었다. 그리고 모드 1의 고유 벡터 값에서 일관성을 보였다. 따라서 분석대상 기간 동안에는 모든 관측소가 일제히 상승하는 신호를 보이고 있음을 알 수 있었다. 또한 14개 GPS 상시관측소 시계열에서 주성분분석을 통해 산출된 모드 1 신호를 제거하고 모드 1의 신호 제거 전 후에 따른 관측소 수직좌표 시계열의 정밀도 변화를 분석하였다. 그 결과, 수직좌표 시계열의 정밀도는 평균 34.8% 향상되었다.

• 한국물환경학회지
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• 제23권1호
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• pp.161-168
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• 2007

The main aim of this work is focus on the Geum river water quality evaluation of pollution data obtained by monitoring measurement during the period 2001-2005. The complex data matrix 19 (entire monitoring stations)*13 (parameters), 60 (month)*13 (parameters) and 20 (season)*13 (parameters) were treated with different multivariate techniques such as factor analysis/principal component analysis (FA/PCA). FA/PCA identified two factor (19*13) classified pollutant Loading factor (BOD, COD, pH, Cond, T-N, T-P, $NH_3$-N, $NO_3$-N, $PO_4$-P, Chl-a), seasonal factor (water temp, SS) and three Factor (60*13, 20*13) classified pollutant Loading factor (BOD, COD, Cond, T-N, T-P, $NH_3$-N, $NO_3$-N, $PO_4$-P), seasonal factor (water temp, SS) and metabolic factor (Chl-a, pH). Loadings of pollutant factor is potent influence main factor in the Geum river which is explained by loadings of pollutant factor at whole sampling stations (71.16%), month (52.75%) and season (56.57%) of main water quality stations. Result of this study is that pollutant loading factor is affected at Gongju 1, 2, Buyeo 1, 2, Gangkyeong, Yeongi stations by entire stations and entire month (Gongju 1, Cheongwon stations), April, May, July and August (buyeo 1) by month. Also the pollutant Loading factor is season gives an influence in winter (Gongju 1, buyeo 1) from main sampling stations, but Cheongwon characteristic is non-seasonal influenced. This study presents necessity and usefulness of multivariate statistic techniques for evaluation and interpretation of large complex data set with a view to get better information data effective management of water sources.

• 한국환경과학회지
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• 제9권1호
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• pp.1-11
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• 2000

A study on the variational characteristics of water quality and phytoplankton biomass by principal component analysis(PCA) was carried out in Kogum-sudo from February to October in 1993. We analyzed PCA on biological factors such as chlorophyll a and phytoplankton cell numbers for centric and pennate diatoms, phytoflagellates, and total phytoplankton as well as physico-chemical factors as water temperature, salinity, transparency, dissolved oxygen(DO), saturation of DO, apparent oxygen utilization (AOU), chemical oxygen demand(COD), nutrient (ammonia, nitrite, nitrate, phosphate and silicate), N/P ratio and suspended solid(SS). The source of nutrients supply depended on the mineralization of organic matters and inputs of seawater from outside rather than runoff of freshwater. The phytoplankton biomass was changed within short interval period by nutrients change. And it was controlled by the combination of several environmental factors, especially of light intensity, ammonia and phosphate. The marine environmental characteristics were determined by the mineralization of organic matters in winter, by runoff of freshwater including high nutrients concentration in spring, by ammonia uptake and high phytoplankton productivity in summer, and phosphate supplied input seawater from outside of Kogeum-sudo in autumn. And Kogum-sudo was separated with 2 regions by score distributions of PCA. That is to say, one region was middle parts of straits which was characterized by the mixing seawater and the accumulated organic matters, other one region was Pungnam Bay and the water around Kogum Island which was done by high phytoplankyon biomass and productivity year-round.

• 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$_{2}$ .

• 한국대기환경학회지
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• 제20권5호
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• pp.583-591
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• 2004

In this study, methodologies for the rational organization of air pollution monitoring network were examined by understanding the characteristics of temporal and spatial distribution of secondary air pollution, whose significance would increase hereafter. The data on $O_3$ and $NO_2$ concentrations during high ozone period in 1998~1999 recorded at the nine air pollution monitoring station in Busan were analysed using principal component analysis (PCA) and cumulative semivariogram. It was found that the ozone concentration was deeply associated with the daily emission characteristics or the $O_3$ precusors, and nitrogen dioxide concentration largely depends on the emission strength of regional sources. According to the spatial distribution analysis of ozone and nitrogen dioxide in Busan using cumulative semivariograms, the number of monitoring stations for the secondary air pollution can be reduced in east-west direction, but reinforced in north-south direction to explain the spacial variability. More scientific and rational relocation of air pollution monitoring network in Busan would be needed to investigate pollution status accurately and to plan and implement the pollution reduction policies effectively.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.244-247
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• 2003

Multi-temporal data is used to determine the rate of deforestation between the years 1976, 1987 and 2000. Three Landsat TM images, for each period, are pre-processed, mosaicked and normalized difference vegetation index (NDVI) values computed. Based on the values, totally non-forested areas are masked out. The forested areas, both partially and wholly, show a very high degree of correlation between all the bands (reflective), thus necessitating application of principal component analysis. The first two principal components and NDVI values (scaled to 0 ? 255) are used in K-means unsupervised classification to distinguish forest from non-forest areas (that appeared as forest at first). Comparison of the resulting thematic maps gives an annual deforestation rate of roughly 15 0000ha. or 2% between any two epochs.

• Toxicological Research
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• 제28권2호
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• pp.81-91
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• 2012

Many risk factors exist for chemotherapy-induced nausea and vomiting (CINV). This study utilized a multivariate projection technique to identify which risk factors were predictive of CINV in clinical practice. A single-centre, prospective, observational study was conducted from January 2007~July 2010 in Singapore. Patients were on highly (HECs) and moderately emetogenic chemotherapies with/without radiotherapy. Patient demographics and CINV risk factors were documented. Daily recording of CINV events was done using a standardized diary. Principal component (PC) analysis was performed to identify which risk factors could differentiate patients with and without CINV. A total of 710 patients were recruited. Majority were females (67%) and Chinese (84%). Five risk factors were potential CINV predictors: histories of alcohol drinking, chemotherapy-induced nausea, chemotherapy-induced vomiting, fatigue and gender. Period (ex-/current drinkers) and frequency of drinking (social/chronic drinkers) differentiated the CINV endpoints in patients on HECs and anthracycline-based, and XELOX regimens, respectively. Fatigue interference and severity were predictive of CINV in anthracycline-based populations, while the former was predictive in HEC and XELOX populations. PC analysis is a potential technique in analyzing clinical population data, and can provide clinicians with an insight as to what predictors to look out for in the clinical assessment of CINV. We hope that our results will increase the awareness among clinician-scientists regarding the usefulness of this technique in the analysis of clinical data, so that appropriate preventive measures can be taken to improve patients' quality of life.