• Smart Structures and Systems
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• 제22권6호
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• pp.711-725
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• 2018

Most of the practical engineering structures exhibit nonlinearity due to nonlinear dynamic characteristics of structural joints, nonlinear boundary conditions and nonlinear material properties. Hence, it is highly desirable to detect and characterize the nonlinearity present in the system in order to assess the true behaviour of the structural system. Further, these identified nonlinear features can be effectively used for damage diagnosis during structural health monitoring. In this paper, we focus on the detection of the nonlinearity present in the system by confining our discussion to only a few selective time-frequency analysis and multivariate analysis based techniques. Both damage induced nonlinearity and inherent structural nonlinearity in healthy systems are considered. The strengths and weakness of various techniques for nonlinear detection are investigated through numerically simulated two different classes of nonlinear problems. These numerical results are complemented with the experimental data to demonstrate its suitability to the practical problems.

• Journal of the Korean Statistical Society
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• 제12권1호
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• pp.24-35
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• 1983

In fitting models to data, selection of the most desirable estimation method and determination of the adequacy of fitted model are the central issues. This paper compares the maximum likelihood estimators and the minimum logit chi-square estimators, both being best asymptotically normal, when logit models are fitted to infant mortality data. Chi-square goodness-of-fit test and likelihood ratio one are also compared. The analysis infant mortality data shows that the outlying observations do not necessarily result in the same impact on goodness-of-fit measures.

• 약학회지
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• 제60권1호
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• pp.29-35
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• 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.

• 산업경영시스템학회지
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• 제20권42호
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• pp.151-159
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• 1997

This Study intends to analyse the degree which Psychological Anxiety affects to Physical Performance using Multivariate Statistical Analysis. For this, we accumulated two type's datum : (1)Data about Psychological anxiety by Spielberger's STAI- Ⅰ·Ⅱ, (2)Data about Physical Performance by AEFH's FITKIT.

• 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.

• 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.

• Journal of the Korean Data and Information Science Society
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• 제14권3호
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• pp.545-551
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• 2003

Robust design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper we propose how to simultaneously optimize multiple quality characteristics using the principal component analysis of multivariate statistical analysis. An example is illustrated to compare it with already proposed method.

• 한국IT서비스학회지
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• 제10권3호
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• pp.265-284
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• 2011

The purpose of this study is to analyze the demand for telemedicine and telehealthmanagement services, which are key elements of home based u-health. The conjoint analysis, which is a conventional method for demand analysis for newly introduced products, is employed, utilizing the survey data on 500 seoul citizens. Further, multivariate probit model is used to estimate the demand. The result shows that the demand for telemedicine services is greater than that of telehealthmanagement services. Further, home-based u-health services will play a role as a complementary for face-to-face medical treatments, rather than a substitute. Meanwhile, the demand for home-based u-health services is found to be very sensitive to price.

• Ocean and Polar Research
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• 제36권1호
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• pp.71-76
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• 2014

This study aims to analyze the market interactions among the main farmed fish species in Korea, using both multivariate and bivariate cointegration analysis. For the analysis of market interactions among farmed fish species, major four farmed fish species, olive flounder (Paralichthys olivaceus), black rockfish (Sebastes schlegeli), red seabream (Pagrus major), and grey mullet (Mugil cephalus) were selected as the analytical target species. And their real price data by month from January 2000 to December 2011 were used in the analysis. The results of the multivariate cointegration test for four farmed fish showed that there would be no long-term equilibrium relationships among farmed fish species, and consequently they do not share the same market. The results of bivariate cointegration test indicated that there was little evidence to suggest that all farmed fish species were cointegrated each other. However, it was only analyzed that olive flounder and grey mullet might have a long run equilibrium relationship.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.681-684
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• 2004

In order for effective damage prevention, it is necessary to have some idea of when, where, why and what kind of natural disasters may strike, and how large they may be. In this study, I made a database which can be use for GIS to facilitate multivariate analysis of presently available data for Shizuoka prefecture. This analysis can map out likely natural disaster locations and causes. Using the result of this analysis for GIS, a regional range of the disaster categorized by factors can be shown and analyzed visually and easily updated when a disaster occurs in the future.