• 한국국방경영분석학회지
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• 제6권2호
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• pp.89-127
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• 1980

The multivariate analysis techniques of cluster analysis are examined in this article. The theory and applications of the techniques and computer software concerning these techniques are discussed and sample jobs are included. A hierarchical cluster analysis algorithm, available in the IMSL software package, is applied to a set of data extracted from a group of subjects for the purpose of partitioning a collection of 26 attributes of a weapon system into six clusters of superattributes. A nonhierarchical clustering procedure were applied to a collection of data of tanks considering of twenty-four observations of ten attributes of tanks. The cluster analysis shows that the tanks cluster somewhat naturally by nationality. The principal componant analysis and the discriminant analysis show that tank weight is the single most important discriminator among nationality although they are not shown in this article because of the space restriction. This is a part of thesis for master's degree in operations research.

• 한국컴퓨터정보학회논문지
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• 제21권5호
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• pp.167-175
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• 2016

The volatile component analysis of 82 commercialized liquors(44 samples of single malt whisky, 20 samples of blended whisky and 18 samples of brandy) was carried out by gas chromatography after liquid-liquid extraction with dichloromethane. Pattern recognition techniques such as principle component analysis(PCA), cluster analysis(CA), linear discriminant analysis(LDA) and partial least square discriminant analysis(PLSDA) were applied for the discrimination of different liquor categories. Classification rules were validated by considering sensitivity and specificity of each class. Both techniques, LDA and PLSDA, gave 100% sensitivity and specificity for all of the categories. These results suggested that the common characteristics and identities as typification of whiskies and brandys was founded by using multivariate data analysis method.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2002년도 봄 학술발표회 논문집
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• pp.197-204
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• 2002

In this study, multivariate analysis based on domestic data(958 EA) of road tunnel, and suggest the easy prediction equation of Q-system. We generate applicable Q-value to numerical analysis method with using the equation and investigate the behavior as variable Q-value of rock mass induced excavation with discontinuum numerical analysis method, UDEC. In the result of the experiment, we research the application range of Q-value to apply the continuum model to discontinuous rock mass is below 0.7 and we testify the applicability of continuum model as researched Q-value with continuum numerical analysis method, FLAC.

• 간호행정학회지
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• 제21권2호
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• pp.184-192
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• 2015

Purpose: This study was done to assess nursing students' practice of patient safety management (PSM), identify factors affecting PSM and provide basic data to develop education programs to strengthen students' competencies for patient safety. Methods: In this descriptive research the practice of PSM by nursing students was examined and predictive factors were identified. Participants were junior and senior nursing students from 7 universities in 7 cities. Self-report questionnaires were used for data collection. Results: Significant positive correlations were found between knowledge of PSM, perception of the importance of PSM and practice of PSM. In multivariate analysis, women students, participation in patient safety education in school, knowledge of PSM, and practice of PSM predicted high perception of the importance of PSM. In multivariate analysis, senior year and participation in patient safety education in school predicted higher knowledge of PSM. In multivariate analysis, perception of the importance of PSM predicted high practice of PSM. Conclusion: In this study, knowledge was not found to directly affect PSM practice, but was found to affect the perception of the importance of PSM, a significant predictive variable. Thus, the importance of PSM should be strongly emphasized during education.

• 생약학회지
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• 제41권4호
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• pp.303-307
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• 2010

To overcome the limit of morphological method for classification of herbal drug, a novel method to discriminate its origin using pyrolysis mass spectrometry-multivariate analysis was developed. This method was applied successfully to Scutellaria baicalensis Georgi, one of the most popular herbal drug in oriental countries. The ethylacetate soluble fractions were prepared by sonication from pulverized roots of S. baicalensis which were collected from various regions including Korea and China, and subjected to direct insertion probe (DIP) mass spectrometry to achieve mass spectra of pyrolizates of extracts. The probe temperature was elevated from $30^{\circ}C$ to $320^{\circ}C$ at increasing rate $64^{\circ}C/min$, and the average mass spectrum calculated from total ion chromatography (TIC) was obtained. The relative peak intensities versus m/z were subjected to SAS program, and the training set (9 from Korea origin and 22 from China origin) was clustered two groups as its origin. In the test set, 11 samples among total 13 test sample were successfully classified according to their origin by developed method with accuracy of 85%.

• 한국가스학회지
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• 제10권4호
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• pp.29-33
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• 2006

화학공정 설계에서 공정의 위험성 판단은 중요한 부분이다. 실제 화학공정에 사용되는 가연성 물질의 화재 및 폭발 위험성을 판단하는 인화점에 대한 예측은 그 방법 중의 하나이다. 본 연구에서는 2성분계 가연성 물질의 인화점에 대한 실험 자료를 이용하여 다변량 통계 분석법(partial least squares(PLS), quadratic partial least squares(QPLS))을 이용하여 2성분계 혼합물의 인화점을 예측하였고, 기존의 Raoult의 법칙과 Van Laar 식에 의한 예측값과 비교해 보았다.

• 한국터널지하공간학회 논문집
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• 제2권2호
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• pp.41-49
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• 2000

지하 터널 굴착 등의 암반 공학적 문제에 있어서 암반분류가 널리 적용되고 있다. 하지만, 조사 방법이 체계화되어 있지 않아서 터널 지질 전문가라 할지라도 암반분류에 어려움이 많은 문제점을 가지고 있다. 본 연구에서는 다변량분석을 이용하여 객관적이고 사용하기 간편한 암반분류법을 제시하였다. RMR 요소는 RQD, 절리상태, 지하수, 강도, 보정, 절리간격 순으로 중요도가 결정되었으며, 각각의 단계에서 RMR에 관한 최적의 다중회귀모형식을 제시하였다.

• 경영과학
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• 제32권2호
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• pp.69-78
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• 2015

This paper considers a Bayesian Poisson model for multivariate count data using multiplicative rates. More specifically we compose the parameter for overall arrival rates by the product of two parameters, a common effect and an individual effect. The common effect is composed of autoregressive evolution of the parameter, which allows for analysis on seasonal effects on all multivariate time series. In addition, analysis on individual effects allows the researcher to differentiate the time series by whatevercharacterization of their choice. This type of model allows the researcher to specifically analyze two different forms of effects separately and produce a more robust result. We illustrate a simple MCMC generation combined with a Gibbs sampler step in estimating the posterior joint distribution of all parameters in the model. On the whole, the model presented in this study is an intuitive model which may handle complicated problems, and we highlight the properties and possible applications of the model with an example, analyzing real time series data involving customer arrivals to a large retail store.

• 한국건설관리학회논문집
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• 제8권5호
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• pp.191-200
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• 2007

This paper introduces a tool for predicting potential cost overrun during project execution and for quantifying the uncertainty on the expected project cost, which is occasionally changed by the unknown effects resulted from project's complications and unforeseen environments. The model proposed in this stuff is useful in diagnosing cost performance as a project progresses and in monitoring the changes of the uncertainty as indicators for a warning signal. This model is intended for the use by project managers who forecast the change of the uncertainty and its magnitude. The paper presents a mathematical approach for modifying the costs of incomplete work packages and project cost, and quantifying reduced uncertainties at a consistent confidence level as actual cost information of an ongoing project is obtained. Furthermore, this approach addresses the effects of actual informed data of completed work packages on the re-estimates of incomplete work packages and describes the impacts on the variation of the uncertainty for the expected project cost incorporating Multivariate Probabilistic Analysis (MPA) and Bayes' Theorem. For the illustration purpose, the Introduced model has employed an example construction project. The results are analyzed to demonstrate the use of the model and illustrate its capabilities.

• 정보처리학회논문지C
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• 제10C권4호
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• pp.397-404
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• 2003

프로그램 행위기반 침입탐지 기법은 데몬 프로그램이나 루트 권한으로 실행되는 프로그램이 발생시키는 시스템 호출들을 분석하고 프로그램 행위 프로파일을 구축하여 잠재적인 공격을 효과적으로 탐지한다. 그러나 각 프로그램마다 매우 큰 프로파일이 구축되어야 하는 문제점이 있다. 본 논문은 프로파일의 크기를 줄이기 위해, 프로그램 행위 프로파일링 및 이상행위 탐지에 X$^2$ 거리기반 다변량 분석 기법을 응용하였다. 실험 결과, 프로파일을 비교적 작게 유지하면서 탐지율에서는 의미있는 결과를 보였다.