• Journal of the Korean Data and Information Science Society
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• 제25권3호
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• pp.485-492
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• 2014

투수를 평가할 때 중요한 요소는 일반적으로 다승과 방어율을 사용하지만 이 지표들은 팀의 도움 또는 운과 같은 요소의 영향을 받는다. 그래서 야구통계학자들은 투수 개인의 능력만을 측정하는 많은 지표들을 제안하였는데 이와 같은 평가지표들은 가짓수가 너무 많고 복잡하기 때문에 팬들을 때때로 당황하게 만든다. 본 연구에서는 대표적인 투수평가지표들을 이용하여 지표들의 특성을 반영하는 주성분을 찾아보고 한국프로야구에 적합한 투수들의 능력을 객관적으로 평가할 수 있는 투수지표를 제안하였다.

• Communications for Statistical Applications and Methods
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• 제29권2호
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• pp.225-238
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• 2022

In this paper, we propose a clustering method for advanced metering infrastructure (AMI) data in Korea. As AMI data presents non-stationarity, we consider time-dependent frequency domain principal components analysis, which is a proper method for locally stationary time series data. We develop a new clustering method based on time-varying eigenvectors, and our method provides a meaningful result that is different from the clustering results obtained by employing conventional methods, such as K-means and K-centres functional clustering. Simulation study demonstrates the superiority of the proposed approach. We further apply the clustering results to the evaluation of the electricity price system in South Korea, and validate the reform of the progressive electricity tariff system.

• 한국환경생태학회지
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• 제29권2호
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• pp.145-161
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• 2015

This research was conducted in order to understand the hybridization between Quercus aliena Blume and Q. serrata Murray in Korea which show wide range of morphological variations within species and interspecific variations of diverse overlapping characteristics caused by hybridization. Morphological analysis (principal components analysis; PCA) of 116 individuals representing two species and their intermediates were performed. As a result, two species were clearly distinguished in terms of morphology, and intermediate morpho-types assumed to be hybrids between the two species were mostly located in the middle of each parent species in the plot of the principal components analysis. There was a clear distinction between two species in trichome distribution pattern which is an important diagnostic character in taxonomy of genus Quercus, whereas intermediate morpho-types showed intermediate state between two species' trichome distributions. Forty-two individuals representing two species and their intermediates were examined for leaf flavonoid constituents. Twenty-three flavonoid compounds were isolated and identified: They were glycosylated derivatives of flavonols, kaempferol, quercetin, isorhamnetin and myricetin. The flavonoid constituents of Q. aliena were five glycosylated derivatives: kaempferol 3-O-galactoside, kaempferol 3-O-glucoside, quercetin 3-O-galactoside, quercetin 3-O-glucoside, and Isorhamnetin 3-O-glucoside. The flavonoid constituents of Q. serrata had 20 diverse flavonol compounds including five flavonoid compounds found in Q. aliena. It was found that there is a clear difference in flavonoid constituents of Q. aliena and Q. serrata. Flavonoid chemistry is very useful in recognizing each species and putative hybrids. The flavonoid constituents of intermediates were a mixture of the two species' constituents and they generally showed similar characteristics to morpho-types. The hybrids between Q. aliena and Q. serrata showed morphologically and chemically diverse characteristics and it is assumed that there are frequent interspecific hybridization and introgression.

• 대한화학회지
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• 제41권2호
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• pp.105-112
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• 1997

건어물 중의 냄새나는 질소화합물을 증류동시 추출법으로 추출하여 GC-MS로 분석하였다. Amine의 equivalent chain length를 구하여 머무름시간으로부터 탄소수와 차수를 예측할 수 있었다. 새우, 멸치, 북어, 대구, 오징어, 문어, 쥐포, 병어포, 홍합, 조갯살 등 우리 나라에서 많이 식용되는 시료를 분석대상으로 하였다. Dimethylamine, trimethylamine, diethylamine 등은 건어물에서 검출되지 않았으나 methylamine, acetamide, thiazole, 2-hydroxy isopropylamine, N-methyl pyrroline, cyclohexylamine 같은 냄새나는 질소화합물들이 GC-MS로 확인되었다. 건어물의 냄새패턴을 식별하기 위하여 GC-MS 피크면적을 자료로 주성분분석을 적용하였다. 주성분분석에 의한 다변량해석은 건어물의 냄새패턴의 유사성과 이질성의 식별에 유익하다는 결론을 얻었다.

• 지질공학
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• 제32권3호
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• pp.377-388
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• 2022

최근, 다수의 연구가 지수적으로 증가하는 지진 자료를 효율적이고 정확하게 처리하기 위해 기계학습을 활용하고 있다. 본 연구는 지진의 발생 시간, 위치, 규모의 정보를 확장하여 기계학습에 적용 가능한 자료를 제작한 후, 주성분 분석을 통해 추출한 자료의 주요 성분으로 자료의 차원을 축소하였다. 차원이 확장된 자료는 36,699개의 지진 사건을 포함하는 Global Centroid Moment Tensor 카탈로그로부터 얻은 지진 정보의 통계량으로 구성되었다. 표준화와 최대-최소화 스케일링을 활용하여 자료 전처리를 수행하였으며, 스케일링이 완료된 자료에 주성분 분석을 적용하여 자료의 주요 특징을 추출하였다. 스케일링은 상이한 단위로 인한 특징 값의 차이를 현저히 감소시켰으며, 그 중 표준화는 다른 전처리에 비해서 각 특징의 중앙값을 더 균등하게 변환하였다. 주성분 분석이 스케일링이 적용되지 않은 자료로부터 추출한 여섯 개의 주성분은 원본 자료의 정보를 99% 설명하였다. 표준화와 최대-최소 스케일링이 적용된 자료로부터 추출한 열여섯 개의 주성분은 원본 자료의 정보의 98%를 재구성하였다. 이는 특징 값의 분포가 균등한 자료의 정보를 보존하기 위해서는 더 많은 주성분이 필요함을 지시한다. 본 연구는 지진 데이터와 지진 거동과의 관계를 분석하는 효율적이고 정확한 기계 학습 모형을 훈련시키기 위한 데이터 처리 방법을 제안하였다.

• 분석과학
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• 제10권5호
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• pp.362-369
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• 1997

HPLC를 이용하여 생산지와 밀원꽃이 알려진 5종의 꿀 중 당성분을 분석한 다음 화학계량학적 고찰을 수행하였다. 꿀의 주된 당성분은 fructose, glucose였으며, 1종의 꿀에서는 sucrose가 소량 검출되었다. 산지별, 밀원꽃별로 당 함량을 비교하였다. Fructose/glucose 함량비는 0.99~1.55 범위로서 문헌값과 잘 일치하였다. Principal components analysis(PCA) plot은 산지별, 밀원꽃별로 확연히 구분되었다. 주성분점수가 커질수록 당 함량이 증가되었고 fructose/glucose 함량비는 감소되었다. 화학계량학적 접근방법은 꿀시료의 당조성 패턴을 비교하고 품질평가 및 부정화 적발에 유용하였다.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1998년도 추계학술대회
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• pp.257-258
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• 1998

To reveal the interconnected brain regions involved in human working memory, their functional connectivity was analyzed using principal component analysis (PCA). rCBF PET scans were peformed on 5 normal volunteers during the verbal and visual working memory tasks and PCA was applied. PCA produced the first principal components related with the increase of the difficulty and the second one which demonstrate the dissociation of verbal and visual memory system.

• Plant Resources
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• 제2권2호
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• pp.75-80
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• 1999

Twenty two varieties of pecan including wild types were classified based on 6 characters measured by principal component analysis score distance. The results are summarized as fellow. Twenty two varieties were classified into 5 groups based in PCA score distance. Five groups were distinctly characterized by many morphological characters. Total variation could be explained by 51%, 95%, 99% with first, third and fifth principal components respectively. Varimax rotation of the factor loading of the first factors indicated that the first component was highly loaded with leaf characters, the second component with fruit characters, but fruit length was negative loaded. The second, the third and the fourths groups of cultivars had very close genetic parentage similarity.

• Nuclear Engineering and Technology
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• 제32권5호
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• pp.485-494
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• 2000

In this work, a fuzzy neural network is used to estimate the relevant sensor signal using other sensor signals. Noise components in input signals into the fuzzy neural network are removed through the wavelet denoising technique . Principal component analysis (PCA) is used to reduce the dimension of an input space without losing a significant amount of information. A lower dimensional input space will also usually reduce the time necessary to train a fuzzy-neural network. Also, the principal component analysis makes easy the selection of the input signals into the fuzzy neural network. The fuzzy neural network parameters are optimized by two learning methods. A genetic algorithm is used to optimize the antecedent parameters of the fuzzy neural network and a least-squares algorithm is used to solve the consequent parameters. The proposed algorithm was verified through the application to the pressurizer water level and the hot-leg flowrate measurements in pressurized water reactors.

• 산업경영시스템학회지
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• 제38권1호
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• pp.143-151
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• 2015

In this paper, we investigate how the power consumption of a heat pump dryer depends on various factors in the drying process by analyzing variables that affect the power consumption. Since there are in general many variables that affect the power consumption, for a feasible analysis, we utilize the principal component analysis to reduce the number of variables (or dimensionality) to two or three. We find that the first component is correlated positively to the entrance temperature of various devices such as compressor, expander, evaporator, and the second, negatively to condenser. We then model the power consumption as a multiple regression with two and/or three transformed variables of the selected principal components. We find that fitted value from the multiple regression explains 80~90% of the observed value of the power consumption. This results can be applied to a more elaborate control of the power consumption in the heat pump dryer.