• 한국산업정보학회논문지
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• 제20권4호
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• pp.75-87
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• 2015

중복시스템의 일반적인 구조는 기능을 수행하는 주요부품과 주요부품이 고장 나는 경우에 그 기능을 대신 수행하는 대기부품으로 구성되어 있다. 본 연구에서는 하나의 대기부품이 여러 개의 주요부품의 기능을 동시에 대신 수행할 수 있는 다기능 대기부품을 갖는 병렬시스템을 고려한다. 이 시스템을 구성하고 있는 모든 부품들은 작동상태와 고장상태만 갖는 반면 시스템은 구성 부품들의 상태에 따라 다중 상태를 갖는 것을 가정한다. 이러한 중복구조는 항공기와 같이 시스템의 중량이 중요한 요소인 시스템에서 많이 채택되고 있는 구조이다. 본 연구에서는 이와 같은 중복시스템의 신뢰도를 평가하기 위한 새로운 신뢰도모델링 기법을 제안하고 부품들이 상수고장률을 갖는 경우 마코프 분석 방법을 적용하여 시스템의 신뢰도를 구한다. 또한 본 연구에서 고려하고 있는 시스템과 기존에 이미 알려진 병렬시스템과 중복구조를 갖는 병렬시스템의 신뢰도를 비교하여 다기능 대기부품의 효과를 분석한다.

• Communications for Statistical Applications and Methods
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• 제27권1호
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• pp.149-161
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• 2020

In this paper we extend the functional principal component analysis for real-valued random functions to the case of Hilbert-space-valued functional random objects. For this, we introduce an autocovariance operator acting on the space of real-valued functions. We establish an eigendecomposition of the autocovariance operator and a Karuhnen-Loève expansion. We propose the estimators of the eigenfunctions and the functional principal component scores, and investigate the rates of convergence of the estimators to their targets. We detail the implementation of the methodology for the cases of compositional vectors and density functions, and illustrate the method by analyzing time-varying population composition data. We also discuss an extension of the methodology to multivariate cases and develop the corresponding theory.

• 응용통계연구
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• 제19권3호
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• pp.431-445
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• 2006

본 연구는 함수적 데이터 분석의 몇 가지 이론에 대해 소개하고 분석 기법을 실제 자료에 적용하는 내용을 다루었다. 함수적 데이터 분석의 이론적 내용으로 기저를 이용해 자료를 함수적 데이터로 표현하는 방법, 그리고 함수적 데이터의 변동성을 조사하는 주성분분석, 선형모형 등에 대해 살펴보았다. 그리고 우리나라 기온 데이터와 강수량 데이터를 대상으로 각각 함수적 데이터 분석 기법을 적용해 보았다. 또한, 기온과 강수량 데이터에 대해 함수적 회귀모형을 적합시켜 두 변수간의 함수관계를 살펴보았다.

• 산업경영시스템학회지
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• 제40권3호
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• pp.138-147
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• 2017

As the functions and structure of the system are complicated and elaborated, various types of structures are emerging to increase reliability in order to cope with a system requiring higher reliability. Among these, standby systems with standby components for each major component are mainly used in aircraft or power plants requiring high reliability. In this study, we consider a standby system with a multi-functional standby component in which one standby component simultaneously performs the functions of several major components. The structure of a parallel system with multifunctional standby components can also be seen in real aircraft hydraulic pump systems and is very efficient in terms of weight, space, and cost as compared to a basic standby system. All components of the system have complete operation, complete failure, only two states, and the system has multiple states depending on the state of the component. At this time, the multi-functional standby component is assumed to be in a non-operating standby state (Cold Standby) when the main component fails. In addition, the failure rate of each part follows the Weibull distribution which can be expressed as increasing type, constant type, and decreasing type according to the shape parameter. If the Weibull distribution is used, it can be applied to various environments in a realistic manner compared to the exponential distribution that can be reflected only when the failure rate is constant. In this paper, Markov chain analysis method is applied to evaluate the reliability of multi-functional multi-state standby system. In order to verify the validity of the reliability, a graph was generated by applying arbitrary shape parameters and scale parameter values through Excel. In order to analyze the effect of multi-functional multi-state standby system using Weibull distribution, we compared the reliability based on the most basic parallel system and the standby system.

• 응용통계연구
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• 제28권5호
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• pp.885-893
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• 2015

통계청과 한국은행 등 통계작성기관에서 이용되고 있는 계절조정은 연간 경제통계 작성시 시계열을 예측한 후 계절조정방법을 적용하여 1년 후 계절변동을 예측하고 원통계 작성시 원통계에서 이를 제거하여 계절조정계열을 작성하고 있다. 이 경우 계절변동을 효과적으로 예측하는 것이 계절조정계열의 품질 향상을 위해 무엇보다 중요하다. 계절변동은 1년 단위로 비슷한 함수적 형태를 지니면서 변하므로 계절변동은 일종의 함수적 시계열이다. 함수적 시계열은 함수적 주성분분석을 바탕으로 한 함수적 시계열모형으로 예측할 수 있다. 본 연구에서는 함수적 시계열 모형을 이용하여 향후 1년간 계절변동을 예측하는 방안을 마련하고 X-11 방식 등 기존의 예측방법과 비교하여 유용성을 파악하였다.

• Communications for Statistical Applications and Methods
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• 제28권2호
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• pp.135-150
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• 2021

We propose principal differential analysis based classification methods. Computations of squared multiple correlation function (RSQ) and principal differential analysis (PDA) scores are reviewed; in addition, we combine principal differential analysis results with the logistic regression for binary classification. In the numerical study, we compare the principal differential analysis based classification methods with functional principal component analysis based classification. Various scenarios are considered in a simulation study, and principal differential analysis based classification methods classify the functional data well. Gene expression data is considered for real data analysis. We observe that the PDA score based method also performs well.

• 한국작물학회지
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• 제54권1호
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• pp.24-28
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• 2009

This study was conducted to evaluate the growth characters and yield components of 18 collected sesame cultivars to get basic information on the variation for the sesame breeding using principal component analysis. All characters except days to flowering, days to maturity and 1,000 seed weight showed significantly different. Seed weight per 10 are showed higher coefficient of variance. Capsule bearing stem length and liter weight showed positive correlation with seed yield per 10 are. The principal components analysis grouped the estimated sesame cultivars into four main components which accounted for 83.7% of the total variation at the eigenvalue and its contribution to total variation obtained from principal component analysis. The first principal component ($Z_1$) was applicable to increase plant height, capsule bearing stem length and 1,000-seed weight. The second principal component ($Z_2$) negatively correlated with days to flowering and maturity by which it was applicable to shorten flowering and maturity date of sesame. At the scatter diagram, Yangbaek, Ansan, M1, M2, M4, M7 and M9 were classified as same group, but M10, Yanghuk, Kanghuk, M5, M6, M12 and M13 were classified as different group. This results would be helpful for sesame breeder to understand genetic relationship of some agronomic characters and select promising cross lines for the development of new sesame variety.

• Elastomers and Composites
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• 제57권3호
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• pp.100-106
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• 2022

Waterborne polyurethane-acrylate(WPUA) dispersions were prepared by surfactant-free emulsion polymerization in a two-step process. In the first step, polytetrahydrofuran, isophorone diisocyanate, dimethylol proponic acid, and 2-hydroxyethyl methacrylate were used to synthesize a vinyl-terminated polyurethane prepolymer. In the second step, styrene, methyl methacrylate, butyl acrylate, and different multi-functional crosslinkers were copolymerized. 1,6-hexanediol diacrylate, trimethylolpropane triacrylate, and pentaerythritol tetraacrylate were used as the crosslinkers, and their effect on the mechanical and thermal properties of WPUA was investigated. Overall, as the number of functional groups of the cross-linker increased, the gel fraction improved to 79.26%, the particle size increased from 75.9 nm to 148.7 nm, and the tensile strength was improved from 5.86 MPa to 12.40 MPa. In thermal properties, the glass transition temperature and decomposition temperature increased by 9.9℃ and 18℃, respectively. The chemical structures of the WPUA dispersions were characterized by Fourier-transform infrared spectroscopy. The synthesized WPUA has high potential for applications such as coatings, leather coatings, adhesives, and wood finishing.

• Communications for Statistical Applications and Methods
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• 제29권1호
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• pp.103-125
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• 2022

In this paper, we analyze the time series data of the case and death counts of COVID-19 that broke out in China in December, 2019. The study period is during the lockdown of Wuhan. We exploit functional data analysis methods to analyze the collected time series data. The analysis is divided into three parts. First, the functional principal component analysis is conducted to investigate the modes of variation. Second, we carry out the functional canonical correlation analysis to explore the relationship between confirmed and death cases. Finally, we utilize a clustering method based on the Expectation-Maximization (EM) algorithm to run the cluster analysis on the counts of confirmed cases, where the number of clusters is determined via a cross-validation approach. Besides, we compare the clustering results with some migration data available to the public.

• 한국신뢰성학회지:신뢰성응용연구
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• 제15권4호
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• pp.233-240
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• 2015

We analyse reliability of multi-state UH-60 helicopter hydraulic pump system with a multi-functional standby component using Markov analysis method. The system consists of seven components: 2 main pumps, 1 standby pump, 2 primary servos, and 2 tail rotor servos. The standby pump can take over when one more than components fail. Therefore the standby pump is multi-functional standby component. The system has four states: good, deteriorated, dangerous, and failed. The components have 2 states: working and failed. We assume the system is unrepairable when the components fail. We estimate failure distributions and rates using collected failure time data in field. And we classify multi-state of the system according to emergency procedure of UH-60A student handout. We obtain the reliabilities of multi-state system using Visual Basic program because the differential equations is extremely complicated and tedious to solve.