• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.210-220
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• 2017

This study investigated the effect of social support (MOS-SSS), and physical (ADL, IADL) and mental (CES-D, MMSE-K) function on the quality of life (WHOQOL- BREF) among the elderly at care facilities. The survey respondents were 524 elderly aged 65 and older living in 15 care facilities located in D city. Data were collected through a personal interview conducted by interviewers who visited each care facility from November 2015 to January 2016. As a result, the quality of life was significantly lower in the elderly group with lower social support, with dysfunction in ADL and IADL than in the normal range group, with depression and cognitive impairment group than in the normal range group. The quality of life had a significant positive correlation with social support, ADL, IADL and cognitive impairment, but a significant negative correlation with depression. According to the results of covariance structure analysis, physical function had a greater impact on the quality of life than mental function or social support. Lower quality of life was associated with lower physical and mental function and lower social support. Therefore, concrete measures need to be devised to enhance physical function in order to improve the quality of life among the elderly in care facilities.

• Atmosphere
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• v.26 no.3
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• pp.483-492
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• 2016

We have examined the random error of eddy covariance (EC) measurements on the basis of two-tower approach during daytime. Two EC towers were placed on the grassland with different vegetation density near Gumi-weir. We calculated the random error using three different methods. The first method (M1) is two-tower method suggested by Hollinger and Richardson (2005) where random error is based on differences between simultaneous flux measurements from two towers in very similar environmental conditions. The second one (M2) is suggested by Kessomkiat et al. (2013), which is extended procedure to estimate random error of EC data for two towers in more heterogeneous environmental conditions. They removed systematic flux difference due to the energy balance deficit and evaporative fraction difference between two sites before determining the random error of fluxes using M1 method. Here, we introduce the third method (M3) where we additionally removed systematic flux difference due to available energy difference between two sites. Compared to M1 and M2 methods, application of M3 method results in more symmetric random error distribution. The magnitude of estimated random error is smallest when using M3 method because application of M3 method results in the least systematic flux difference between two sites among three methods. An empirical formula of random error is developed as a function of flux magnitude, wind speed and measurement height for use in single tower sites near Nakdong River. This study suggests that correcting available energy difference between two sites is also required for calculating the random error of EC data from two towers at heterogeneous site where vegetation density is low.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.3
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• pp.463-472
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• 1994

A method of stochastic response analysis of base-isolated fluid-filled pool structures subject to random ground excitations is studied. Fluid-structure interaction effects between the flexible walls and contained fluid are taken into account in the form of added mass matrix derived by FEM modeling of the contained fluid motion. The stationary ground excitation is represented by Modified Clough-Penzien spectral model and the nonstationary one is obtained by imposing an envelope function on the stationary one. The stationary and nonstationary response statistics of the two different isolation systems are obtained by solving the governing Lyapunov covariance matrix differential equations.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.427-439
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• 2017

Quade (1967) proposed RANK ANCOVA, which is a nonparametric method to test differences between treatments when there are covariates. Hwang and Kim (2012) also proposed a joint placement test on covariate-adjusted residuals. In this paper, we proposed a new nonparametric method to control the effect of covariate on a response variable that uses linear statistics on covariate adjusted-residuals. The score function used in the linear statistics was proposed by Jeon and Kim (2016). Monte Carlo simulation is also conducted to compare the empirical powers of the proposed method with previous methods.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.352-361
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• 2003

We have evaluated the extent of saltwater intrusion from electrical resistivity distribution in a coastal aquifer system in the southeastern part of Busan, Korea. This aquifer system is divided into four layers according to the hydrogeologic characteristics and the horizontal extent of intruded saltwater is determined at each layer through the geostatistical interpretation of electrical resistivity data. In order to define the statistical structure of electrical resistivity data, variogram analysis is carried out to obtain best generalized covariance models. IRF-k (intrinsic random function of order k) kriging is performed with covariance models to produce the plane of spatial mean resistivities. The kriged estimates are evaluated by cross validation to show a good agreement with the true values and the statistics of cross validation represented low errors for the estimates. In the resistivity contour maps more than 5 m below the surface, we can see a dominant direction of saltwater intrusion beginning from the east side. The area of saltwater intrusion increases with depth. The northeast side has low resistivities less than 5 ohm-m due to the presence of saline water in the depth range of 20 m through 70 m. These results show that the application of geostatistical technique to electrical resistivity data is useful for assessing saltwater intrusion in a coastal aquifer system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.475-480
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• 2005

Information of the maximum Doppler frequency enable to optimize many channel-adaptive techniques and radio resource management methods for mobile radio communication systems. In this paper, we propose two maximum Doppler frequency estimators which are based on the level crossing rate(LCR) and the covariance function (COV). To eliminate the effect of additive noise, we analyze the conditions for the estimators independent of the signal-to-noise ratio(SNR) and implement the conditions with a simple downsampling process. The proposed methods achieve good SNR-independent performance.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.65-83
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• 2022

Although various statistical methods have been developed to map time-dependent genetic factors, most identified genetic variants can explain only a small portion of the estimated genetic variation in longitudinal traits. Gene-gene and gene-time/environment interactions are known to be important putative sources of the missing heritability. However, mapping epistatic gene-gene interactions is extremely difficult due to the very large parameter spaces for models containing such interactions. In this paper, we develop a Gaussian process (GP) based nonparametric Bayesian variable selection method for longitudinal data. It maps multiple genetic markers without restricting to pairwise interactions. Rather than modeling each main and interaction term explicitly, the GP model measures the importance of each marker, regardless of whether it is mostly due to a main effect or some interaction effect(s), via an unspecified function. To improve the flexibility of the GP model, we propose a novel grid-based method for the within-subject dependence structure. The proposed method can accurately approximate complex covariance structures. The dimension of the covariance matrix depends only on the number of fixed grid points although each subject may have different numbers of measurements at different time points. The deviance information criterion (DIC) and the Bayesian predictive information criterion (BPIC) are proposed for selecting an optimal number of grid points. To efficiently draw posterior samples, we combine a hybrid Monte Carlo method with a partially collapsed Gibbs (PCG) sampler. We apply the proposed GP model to a mouse dataset on age-related body weight.

• Women's Health Nursing
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• v.22 no.1
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• pp.30-38
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• 2016

Purpose: This study was conducted to examine effects of a sexual function improvement program on sexual distress, sexual satisfaction and marital intimacy among breast cancer survivors. Methods: With quasi-experimental design, a total of 54 women after breast surgery were assigned into experimental group (n=28) and control group (n=26) after recruited via convenience sampling. They were endocrine surgery outpatients in university hospital at Chonnam province. Experimental group received a sexual function improvement program 5 sessions over 5 weeks. Sexual distress, sexual satisfaction, and marital intimacy were examined with self-report structured questionaries. Data were analyzed using $x^2$ test, Fisher's exact, independent t-test, and analysis of covariance with SPSS 17.0/window program. Results: Women who participated in the sexual function improvement program had lower sexual distress (F=27.29, p<.001), higher sexual satisfaction (t=3.09, p=.003) higher marital intimacy (F=17.51, p<.001) than the women who did not participate. Conclusion: Results suggest that a sexual function improvement program can be effective strategy to improve sexual distress, sexual satisfaction and marital intimacy. Therefore, this program can be regarded as useful nursing intervention program for breast cancer survivors.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.10
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• pp.1382-1387
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• 2017

Objective: During the last decade, genetic evaluation of dairy cows using longitudinal data (test day milk yield or 305-day milk yield) using random regression method has been officially adopted in several countries. The objectives of this study were to estimate covariance functions for genetic and permanent environmental effects and to obtain genetic parameters of 305-day milk yield over seven parities. Methods: Data including 60,279 total 305-day milk yield of 17,309 Iranian Holstein dairy cows in 7 parities calved between 20 to 140 months between 2004 and 2011. Residual variances were modeled by homogeneous and step functions with 7 and 10 classes. Results: The results showed that a third order polynomial for additive genetic and permanent environmental effects plus a step function with 10 classes for the residual variance was the most adequate and parsimonious model to describe the covariance structure of the data. Heritability estimates obtained by this model varied from 0.17 to 0.28. The performance of this model was better than repeatability model. Moreover, 10 classes of residual variance produce the more accurate result than 7 classes or homogeneous residual effect. Conclusion: A quadratic Legendre polynomial for additive genetic and permanent environmental effects with 10 step function residual classes are sufficient to produce a parsimonious model that explained the change in 305-day milk yield over consecutive parities of Iranian Holstein cows.

• Journal of the Korean Data and Information Science Society
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• v.25 no.1
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• pp.237-244
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• 2014

It is known that the dierence in the length between two location parameters of two random variables is equivalent to the difference in the area between two cumulative distribution functions. In this paper, we suggest two applications by using the difference of distribution functions. The first is that the difference of expectations of a certain function of two continuous random variables such as the differences of two kth moments and two moment generating functions could be defined by using the difference between two univariate distribution functions. The other is that the difference in the volume between two empirical bivariate distribution functions is derived. If their covariance is estimated to be zero, the difference in the volume between two empirical bivariate distribution functions could be defined as the difference in two certain areas.