• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.403-413
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• 2012

The modifications suggested in Uhm et al. (2011) are studied using a partly parametric version of Aalen's additive risk model. A follow-up time period is partitioned into intervals, and hazard functions are estimated as a piecewise constant in each interval. A maximum likelihood estimator by iteratively reweighted least squares and variance estimates are suggested based on the model as well as evaluated by simulations using mean square error and a coverage probability, respectively. In conclusion the modifications are needed when there are a small number of uncensored deaths in an interval to estimate the piecewise constant hazard function.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.4
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• pp.149-154
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• 2008

The concept of robust design was introduced by Dr. G. Taguchi in the late 1940s, and his technique has become commonly known as the Taguchi method or the robust design. In this research, a robust design procedure for microgyroscope is suggested based on the kriging and optimization approaches. The kriging interpolation method is introduced to obtain the surrogate approximation model of true function. Robustness is calculated by the kriging model to reduce real function calculations. For this, objective function is represented by the probability of success, thus facilitating robust optimization. The statistics such as mean and variance are obtained based on the reliable kriging model and the second-order statistical approximation method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4763-4775
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• 2020

This research aims to develop a deep learning-based method that automatically detects and segments the defects on railroad surfaces to reduce the cost of visual inspection of the railroad. We developed our segmentation model by modifying a fully convolutional network model [1], a well-known segmentation model used for machine learning, to detect and segment railroad surface defects. The data used in this research are images of the railroad surface with one or more defect regions. Railroad images were cropped to a suitable size, considering the long height and relatively narrow width of the images. They were also normalized based on the variance and mean of the data images. Using these images, the suggested model was trained to segment the defect regions. The proposed method showed promising results in the segmentation of defects. We consider that the proposed method can facilitate decision-making about railroad maintenance, and potentially be applied for other analyses.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.105-117
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• 2004

In this paper, a new method is developed for estimating the mean of a population which has a linear trend. This method involves drawing a sample by the modified systematic sampling, and then estimating the population mean with an adjusted estimator, not with the sample mean itself. We use the method of least squares in determining the adjusted estimator. The proposed method is shown to be more and more efficient as the linear trend becomes stronger. It turns out to be relatively efficient as compared with the conventional methods if $\sigma$$^2$the variance of the random error term in the infinite superpopulation model, is not very large.

• Smart Structures and Systems
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• v.17 no.6
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• pp.1067-1085
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• 2016

Nonstationary features existing in tropical storms have been frequently captured in recent field measurements, and the applicability of the stationary theory to the analysis of wind characteristics needs to be discussed. In this study, a tropical storm called Nakri measured at Taizhou Bridge site based on structural health monitoring (SHM) system in 2014 is analyzed to give a comparison of the stationary and nonstationary characteristics. The stationarity of the wind records in the view of mean and variance is first evaluated with the run test method. Then the wind data are respectively analyzed with the traditional stationary model and the wavelet-based nonstationary model. The obtained wind characteristics such as the mean wind velocity, turbulence intensity, turbulence integral scale and power spectral density (PSD) are compared accordingly. Also, the stationary and nonstationary PSDs are fitted to present the turbulence energy distribution in frequency domain, among which a modulating function is included in the nonstationary PSD to revise the non-monotonicity. The modulated nonstationary PSD can be utilized to unconditionally simulate the turbulence presented by the nonstationary wind model. The results of this study recommend a transition from stationarity to nonstationarity in the analysis of wind characteristics, and further in the accurate prediction of wind-induced vibrations for engineering structures.

• Journal of Korean Academy of Rural Health Nursing
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• v.9 no.2
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• pp.59-70
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• 2014

Purpose: The present study was to done ascertain variables related to health-related quality of life (HRQOL) and their related factors in elders from urban or rural areas. Methods: Data were collected from raw material of the 2009 community health survey. Participants were 2,140 elders. Health related quality of life (HRQOL) was measured using EQ-5D. Data were analyzed with SPSS 13.0. Results: Mean EQ index score for urban elders was $0.78{\pm}0.23$, Mean EQ index score for rural elders was $0.82{\pm}0.16$. Rural elders had significantly higher EQ-5D index value compared to urban elders. The urban elder HRQOL model accounted for 33.6% of the variance due to depression, age, stress perception. The rural elder HRQOL model accounted for 23.5% of the variance due to exercising walking, skipping breakfast, depression in that order. In comparison, depression, skipping breakfast, livelihood, arthritis, stress perception, hours of sleep and age are strongly associated with HRQOL in both groups. Conclusion: Results indicate that significant differences in HRQOL between elders from the two areas and thus, confirm claims that welfare services for elders should be provided with consideration of the different needs of elders in the two areas, and in particular for addressing depression in elders.

• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.69-84
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• 1997

We consider a linear calibration problem, $y_i = $$\alpha + \beta (x_i - x_0) + \epsilon_i$, $i=1, 2, {\cdot}{\cdot},n$ $y_f = \alpha + \beta (x_f - x_0) + \epsilon, $ where we observe $(x_i, y_i)$'s for the controlled calibration experiments and later we make inference about $x_f$ from a new observation $y_f$. The objective of the calibration design problem is to find the optimal design $x = (x_i, \cdots, x_n$ that gives the best estimates for $x_f$. We compare Kim(1989)'s Bayesian design which minimizes the expected value of the posterior variance of $x_f$ and some optimal designs from literature. Kim suggested the Bayesian optimal design based on the analysis of the characteristics of the expected loss function and numerical must be equal to the prior mean and that the sum of squares be as large as possible. The designs to be compared are (1) Buonaccorsi(1986)'s AV optimal design that minimizes the average asymptotic variance of the classical estimators, (2) D-optimal and A-optimal design for the linear regression model that optimize some functions of $M(x) = \sum x_i x_i'$, and (3) Hunter & Lamboy (1981)'s reference design from their paper. In order to compare the designs which are optimal in some sense, we consider two criteria. First, we compare them by the expected posterior variance criterion and secondly, we perform the Monte Carlo simulation to obtain the HPD intervals and compare the lengths of them. If the prior mean of $x_f$ is at the center of the finite design interval, then the Bayesian, AV optimal, D-optimal and A-optimal designs are indentical and they are equally weighted end-point design. However if the prior mean is not at the center, then they are not expected to be identical.In this case, we demonstrate that the almost Bayesian-optimal design was slightly better than the approximate AV optimal design. We also investigate the effects of the prior variance of the parameters and solution for the case when the number of experiments is odd.

• Journal of Korean Academy of Nursing
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• v.49 no.4
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• pp.437-448
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• 2019

Purpose: This study was conducted to test a path model for the factors related to undergraduate nursing students' clinical practicum stress, based on Lazarus and Folkman's stress-coping model. Methods: This study utilized a path analysis design. A total of 235 undergraduate nursing students participated in this study. The variables in the hypothetical path model consisted of clinical practicum, emotional intelligence, self-efficacy, Nun-chi, and nursing professionalism. We tested the fit of the hypothetical path model using SPSS/WIN 23.0 and AMOS 22.0. Results: The final model fit demonstrated a satisfactory statistical acceptance level: goodness-of-fit-index=.98, adjusted goodness-of-fit-index=.91, comparative fit index=.98, normed fit index=.95, Tucker-Lewis index=.92, and root mean square error of approximation=.06. Self-efficacy (${\beta}=-.22$, p=.003) and Nun-chi behavior (${\beta}=-.17$, p=.024) were reported as significant factors affecting clinical practicum stress, explaining 10.2% of the variance. Nursing professionalism (${\beta}=.20$, p=.006) and self-efficacy (${\beta}=.45$, p<.001) had direct effects on emotional intelligence, explaining 45.9% of the variance. Self-efficacy had indirect effects on Nun-chi understanding (${\beta}=.20$, p<.001) and Nun-chi behavior (${\beta}=.09$, p=.005) through emotional intelligence. Nursing professionalism had indirect effects on Nun-chi understanding (${\beta}=.09$, p=.005) and Nun-chi behavior (${\beta}=.09$, p=.005) through emotional intelligence. The variables for self-efficacy and nursing professionalism explained 29.1% of the Nun-chi understanding and 18.2% of the Nun-chi behavior, respectively. Conclusion: In undergraduate nursing education, it is important to identify and manage factors that affect clinical practicum stress. The findings of this study emphasize the importance of Nun-chi, self-efficacy, emotional intelligence, and nursing professionalism in the development of an educational strategy for undergraduate nursing students.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.9 no.3
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• pp.115-124
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• 1997

We measured the variance of eddy diffusion and associated ‘diffusion coefficients’ in coastal regions of Korea by observing the separation distances among multiple drifters deployed simultaneously at the same initial position. The variance of eddy diffusion was found to be proportional to $t^m$, where t is the time and m is a non-integer scaling exponent between 1.5 and 3.5. The observed scaling exponent of eddy diffusion cannot be reproduced by diffusion models employing constant eddy diffusivity. In this study, we applied fractal theory in simulating exponential increase of variance of eddy diffusion. We employed the fGn(fractional Gaussian noise) as a ‘modified’ random walks corresponding to the oceanic eddy diffusion. The variance of eddy diffusion, which corresponds to the fBm(fractional Brown motion) of our diffusion model, is proportional to $t^{2H}$, where H is Hurst scaling exponent. The temporal increase of the variance. with scaling exponent between 1 and 2, was successfully reproduced by our fractal diffusion model. However, our model cannot reproduce scaling exponent greater than 2. The scaling exponents greater than 2 are associated with the velocity shear of the mean flow.

• The Journal of Korean Academic Society of Nursing Education
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• v.18 no.2
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• pp.229-238
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• 2012

Purpose: The purpose of this study was to evaluate the theory of planned behavior (TPB) in the structural relationship of nursing students' performance related to nosocomial infection control (NIC). Method: Data was collected by using a questionnaire completed by 238 nursing students of three nursing colleges in Suwon, Sokcho. Results: The mean score of performance related to NIC was 3.86. The highest mean score of performance related to NIC was 4.18 (${\pm}0.91$) for 'hand washing' and the lowest mean score was 3.56 (${\pm}1.08$) for 'respiratory system'. In prediction of the intention of nursing students' on NIC, the attitude, the subjective norm, and the perceived behavior control(PBC) of TPB resulted in statistically significant influencing factors (p<0.050). These three variables explained 47.6% of the total variance of the intention of nursing students' on NIC. In predicting the performance related to NIC, the PBC resulted in the direct and main influencing factor of nursing students' performance related to NIC (p<0.010). Intention was not a significant determinant. These two variables explained 13.2% of total variance of the performance related to NIC. Conclusion: This study shows the TPB model's applicability in explaining performance related to NIC of nursing students and highlights the importance of PBC for strategies to enhance performance related to NIC in nursing students.