• 한국경영과학회지
• /
• 제33권2호
• /
• pp.153-174
• /
• 2008

There have been two streams of the studies on development structure : conceptual model approach and statistical analysis approach. But In these days, the latter has been becoming the main approach owing to the development of multivariate statistical methods and statistical packages. In this study, we examine methodologies and results of the leading researches related to development structure based on statistical analysis and propose the future research directions. This analysis would be expected to contribute toward the construction of long-range development policies on each country.

• 응용통계연구
• /
• 제30권5호
• /
• pp.747-757
• /
• 2017

본 논문은 다변량 실현 변동성 계산에서 주기 선택 방안에 대해 연구하고 있다. 고빈도(high frequency) 시계열 자료에 기초한 일간 변동성인 실현변동성을 계산하고 차원 축소 방법인 주성분을 도입하였다. Cholesky 모형을 포함한 다양한 다변량 변동성모형을 주성분을 통해 비교하였으며 KOSPI/삼성전자/현대차 고빈도 수익률 자료를 이용하여 예시하였다.

• 한국식품과학회지
• /
• 제48권5호
• /
• pp.418-423
• /
• 2016

근적외선분광분석기와 에너지 분산형 X선 형광분석기를 이용한 분석방법을 개발하여 각각 97.5, 98.0%의 높은 정확도의 판별식을 확립하였고, 시중 유통 시료를 분석하여 검증한 결과 각각 96.3, 95.0%의 판별 정확도를 확인하였다. 이상의 연구 결과를 통하여 근적외선분광분석기와 에너지 분산형 X선 형광분석기를 이용하여 청국장 원산지 판별이 가능함을 확인하였고 이는 유기성분 함량에 따른 근적외선 흡광도와 무기성분 함량에 따른 X선 형광에너지 강도가 국내산과 수입산 간에 차이가 있기 때문으로 사료된다.

• 대한인간공학회지
• /
• 제26권4호
• /
• pp.103-111
• /
• 2007

The purpose of this study is to categorize and analyze the body shape of obese Korean men that are needed for industrial design. Using the anthropometric data that were surveyed through the 5^th Size Korea project, this study was conducted in four steps mostly through the multivariate statistical analysis. In the first step, Broca, BMI, WHR indices are used to define obesity and select obese men from Korean adults and teens. After 34 human anthropometric variables are supposed to be related to obesity were extracted through an expect survey. In the second step, a factor analysis was executed for those human anthropometric variables. Through this analysis, we obtained the human body factors that are related to the representation of obesity. Then the third step, we used a cluster analysis from the result of the factor analysis. And ANOVA analysis was also conducted to obtain the critical obese human anthropometric variables. In the final step, we found the characteristics of the body types of obese men according to clusters and ages. The body types of obese men classified in the study are expected to be applied to product design for clothing, furniture, automobile packaging, etc.

• Biomolecules & Therapeutics
• /
• 제17권2호
• /
• pp.133-137
• /
• 2009

The root of Astragalus membranaceus is a traditional folk medicine that has been used for many therapeutic purposes in Asia. It reportedly acts as an immunostimulant, tonic, hepatoprotective, diuretic, antidiabetic, analgesic, expectorant, sedative, and anticancer drug. In this study, metabolomic profiling was applied to the roots of A. membranaceus of different ages using NMR coupled with two multivariate statistical analysis methods: such as principal components analysis (PCA) and canonical discriminant analysis (CDA). This allowed various metabolites to be assigned in NMR spectra, including $\gamma$-aminobutyric acid (GABA), aspartic acid, succinic acid, glutamic acid, glutamine, N-acetyl aspartic acid, acetic acid, arginine, alanine, threonine, lactic acid, and valine. The score plot from PCA and also CDA allowed a clear separation between samples according to age.

• 한국약용작물학회지
• /
• 제24권2호
• /
• pp.93-100
• /
• 2016

Background: A set of logical criteria that can accurately identify and verify the cultivation region of raw materials is a critical tool for the scientific management of traditional herbal medicine. Methods and Results: Volatile compounds were obtained from 19 and 32 samples of Angelica gigas Nakai cultivated in Korea and China, respectively, by using steam distillation extraction. The metabolites were identified using GC/MS by querying against the NIST reference library. Data binning was performed to normalize the number of variables used in statistical analysis. Multivariate statistical analyses, such as Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) were performed using the SIMCA-P software. Significant variables with a Variable Importance in the Projection (VIP) score higher than 1.0 as obtained through OPLS-DA and those that resulted in p-values less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Among the 19 variables extracted, styrene, ${\alpha}$-pinene, and ${\beta}$-terpinene were selected as markers to indicate the origin of A. gigas. Conclusions: The statistical model developed was suitable for determination of the geographical origin of A. gigas. The cultivation regions of six Korean and eight Chinese A. gigas. samples were predicted using the established OPLS-DA model and it was confirmed that 13 of the 14 samples were accurately classified.

• 응용통계연구
• /
• 제11권2호
• /
• pp.389-401
• /
• 1998

본 논문에서는 멀티미디어를 활용한 회귀분석 학습시스템 CybeRClass(Cyber Regression Class)를 소개하고자 한다. CybeRClass는 음성정보와 애니메이션 등을 활용하여 회귀분석에 대한 학습을 시켜주는 시스템이다. 이 시스템은 군집분석이나 판별분석 등의 다변량분석 학습이 가능하도록 설계되었다. 멀티미디어 기술을 위한 도구로는 Multimedia ToolBook을 사용하였으며, 통계계산과 통계그라픽을 위해서는 객체지향 통계 언어인 Xlisp-Stat을 사용하였다.

• Environmental Engineering Research
• /
• 제11권2호
• /
• pp.63-76
• /
• 2006

Multivariate analysis and batch monitoring on a pilot-scale sequencing batch reactor (SBR) are described for integrated wastewater treatment management system, where a batchwise multiway independent component analysis method (MICA) are used to extract meaningful hidden information from non-Gaussian wastewater treatment data. Three-way batch data of SBR are unfolded batch-wisely, and then a non-Gaussian multivariate monitoring method is used to capture the non-Gaussian characteristics of normal batches in biological wastewater treatment plant. It is successfully applied to an 80L SBR for biological wastewater treatment, which is characterized by a variety of error sources with non-Gaussian characteristics. The batchwise multivariate monitoring results of a pilot-scale SBR for integrated wastewater treatment management system showed more powerful monitoring performance on a WWTP application than the conventional method since it can extract non-Gaussian source signals which are independent and cross-correlation of variables.

• 약학회지
• /
• 제60권1호
• /
• pp.29-35
• /
• 2016

Traditional Korean medicines may be managed more scientifically, through the development of logical criterion to verify their cultivation region. It contributes to advance the industry of traditional herbal medicines. Volatile compounds were obtained from 14 samples of domestic Taeksa and 30 samples of Chinese Taeksa by steam distillation. The metabolites were identified by NIST mass spectral library in the obtained gas chromatography/mass spectrometer (GC/MS) data of 35 training samples. The multivariate statistical analysis, such as Principal Component Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), were performed based on the qualitative and quantitative data. Finally trans-(2,3-diphenylcyclopropyl)methyl phenyl sulfoxide (47.265 min), 1,2,3,4-tetrahydro-1-phenyl-naphthalene (47.781 min), spiro[4-oxatricyclo[5.3.0.0.(2,6)]decan-3-one-5,2'-cyclohexane] (54.62 min), 6-[7-nitrobenzofurazan-4-yl]amino-morphinan-4,5-epoxy (54.86 min), p-hydroxynorephedrine (55.14 min) were determined as marker metabolites to verify candidates for the origin of Taeksa. The statistical model was well established to determine the origin of Taeksa. The cultivation areas of test samples, each 3 domestic and 6 Chinese Taeksa were predicted by the established OPLS-DA model and it was confirmed that all 9 samples were precisely classified.

• Korean Chemical Engineering Research
• /
• 제45권1호
• /
• pp.87-92
• /
• 2007

최근 공정의 이상을 감지하고 진단하기 위한 공정 모니터링 시스템의 개발이 공정 시스템 분야에서 많은 주목을 받고 있다. 공정으로부터 얻어지는 데이터는 공정의 특성에 대한 유용한 정보를 제공하고 이는 공정의 모델링과 모니터링 그리고 제어에 사용된다. 현대의 화학 및 환경 공정은 고차원적인 특성과 변수간의 강한 상관관계와 동특성 그리고 비선형적 특성을 가지고 있어 모델 기반 접근을 통해 공정을 분석하는 것을 쉽지 않다. 이러한 모델 기반 접근의 한계를 극복하기 위해 많은 시스템 엔지니어와 연구자들이 주성분 분석법(principal component analysis, PCA) 또는 부분 최소 자승법(partial least squares, PLS)과 같은 다변량 분석을 접목한 통계 기반 접근법에 초점을 맞추고 있다. 또한 동특성, 비선형성 등과 같은 특성을 가진 공정에 적용하기 위해 많은 다변량 분석법들이 보완되었다. 여기에서는 동적 주성분 분석법(dynamic PCA)과 케노니컬 변수 분석법(canonical variate analysis)을 이용한 결측 데이터의 예측법과 공정 변수의 복원을 통한 센서 오작동의 판별법에 대해 언급해 보고자 한다.