• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1547-1555
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• 2015

We study the problem of nonignorable nonresponse in a two-way contingency table and there may be one or two missing categories. We describe a nonignorable nonresponse model for the analysis of two-way categorical table. One approach to analyze these data is to construct several tables (one complete and the others incomplete). There are nonidentifiable parameters in incomplete tables. We describe a hierarchical Bayesian model to analyze two-way categorical data. We use a nonignorable nonresponse model with Bayesian uncertainty analysis by placing priors in nonidentifiable parameters instead of a sensitivity analysis for nonidentifiable parameters. To reduce the effects of nonidentifiable parameters, we project the parameters to a lower dimensional space and we allow the reduced set of parameters to share a common distribution. We use the griddy Gibbs sampler to fit our models and compute DIC and BPP for model diagnostics. We illustrate our method using data from NHANES III data to obtain the finite population proportions.

• Proceedings of the Korea Society for Simulation Conference
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• 1999.04a
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• pp.47-52
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• 1999

In this paper we propose new approximate method for the performance analysis of closed-loop production system with unreliable machines and random processing times. The approximate method decomposes the production system consisting of K machines into a set of K subsystems, each subsystem consisting of two machines separated by a finite buffer. Then, each subsystem is analyzed by analyzing method n isolation. The population constraint of the closed-loop production system is taken into account by prescribing that the sum of average buffer level in the subsystems is equal to the number of customers in the closed-loop production system,. We establish a set of equations that characterizes unknown parameters of the servers in the subsystems. An iterative procedure is then used to determine the unknown parameters. Experimental results show that these methods provide a good estimation of the throughput.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.2
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• pp.240-253
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• 1999

In this paper we propose new approximate methods for the performance analysis of closed-loop production systems with unreliable machines and random processing times. Each approximate method decomposes the production system consisting of K machines into a set of K subsystems, each subsystem consisting of two machines separated by a finite buffer. Then, each subsystem is analyzed by three different analyzing methods in isolation. The population constraint of the closed-loop production system is taken into account by prescribing that the sum of average buffer levels in the subsystems is equal to the number of customers in the closed-loop production system. We establish a set of equations that characterize unknown parameters of the servers in the subsystems. An iterative procedure is then used to determine the unknown parameters. Experimental results show that these methods provide a good estimation of the throughput.

• Communications for Statistical Applications and Methods
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• v.31 no.4
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• pp.365-375
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• 2024

Diverse methods to evaluate the prediction model of a time to event have been proposed in the context of right censored data where all subjects are subject to be susceptible. A time-dependent AUC (area under curve) measures the predictive ability of a marker based on case group and control one which are varying over time. When a substantial portion of subjects are event-free, a population consists of a susceptible group and a cured one. An uncertain curability of censored subjects makes it difficult to define both case group and control one. In this paper, our goal is to propose a time-dependent AUC for a cure rate model when a censoring distribution is related with covariates. A class of inverse probability of censoring weighted (IPCW) AUC estimators is proposed to adjust the possible sampling bias. We evaluate the finite sample performance of the suggested methods with diverse simulation schemes and the application to the melanoma dataset is presented to compare with other methods.

• Clinical and Experimental Pediatrics
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• v.48 no.11
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• pp.1179-1186
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• 2005

Purpose : A universal standard of the birth weight for gestational age cannot be made since girth weight distribution varies with race and other sociodemographic factors. This report aims to establish the birth weight distribution curve by gestational age, specific for Korean live births. Methods : We used the national birth certificate data of all live births in Korea from January 2001 to December 2003; for live births with gestational ages 24 weeks to 44 weeks(n=1,509,763), we obtained mean birth weigh, standard deviation and 10th, 25th, 50th, 75th and 90th percentile values for each gestational age group by one week increment. Then, we investigated the birth weight distribution of each gestational age group by the normal Gaussian model. To establish final standard values of Korean birth weight distribution by gestational age, we used the finite mixture model to eliminate erroneous birth slights for respective gestational ages. Results : For gestational ages 28 weeks 32 weeks, birth weight distribution showed a biologically implausible skewed tail or bimodal distribution. Following correction of the erroneous distribution by using the finite mixture model, the constructed curve of birth weight distribution was compared to those of other studies. The Korean birth weight percentile values were generally lower than those for Norwegians and North Americans, particularly after 37 weeks of gestation. The Korean curve was similar to that of Lubchenco both 50th and 90th percentiles, but generally the Korean curve had higher 10th percentile values. Conclusion : This birth weight distribution curve by gestational age is based on the most recent and the national population data compared to previous studies in Korea. We hope that for Korean infants, this curve will help clinicians in defining and managing the large for gestational age infants and also for infants with intrauterine growth retardation.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.75-87
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• 2009

We propose in this paper a novel approach to image fusion in which the fusion rule is guided by optimizing an image clarity function. A Genetic Algorithm is used to stochastically select, comparative to the clarity function, the optimum block from among the source images. A novel nested Genetic Algorithm with gifted individuals found through bombardment of genes by the mutation operator is designed and implemented. Convergence of the algorithm is analytically and empirically examined and statistically compared (MANOVA) with the canonical GA using 3 test functions commonly used in the GA literature. The resulting GA is invariant to parameters and population size, and a minimal size of 20 individuals is found to be sufficient in the tests. In the fusion application, each individual in the population is a finite sequence of discrete values that represent input blocks. Performance of the proposed technique applied to image fusion experiments, is characterized in terms of Mutual Information (MI) as the output quality measure. The method is tested with C=2 input images. The results of the proposed scheme indicate a practical and attractive alternative to current multi-focus image fusion techniques.

• KSBB Journal
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• v.11 no.2
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• pp.254-261
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• 1996

Attenuated varicella-zoster virus (VZV) was propagated in human lung fibroblast (HLF) cells Among media tested in this work, DMEM was the best medium for the growth of HLF cells. Because HLF was a normal finite cell line, cell growth late was dependent on the age of HLF cells. When the population doubling level (PDL) was higher than 46, apoptosis of HLF cells started and cell growth rate decreased. The optimum temperature for the cell growth and virus propagation in the T-flask culture was $37^{\circ}C$. In a microcarrier culture system in which Cytodex-3 was used for the VZV propagation in spinner vessels, the yield of plaque forming cells was lower than that in the T-flask culture. The relatively high shear environment near microcarriers was thought to cause the low yield of VZV in the microcarrier culture system.

• Smart Structures and Systems
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• v.26 no.4
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• pp.451-468
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• 2020

Although model updating has been widely applied using a specific optimization algorithm with a single objective function using frequencies, mode shapes or frequency response functions, there are few studies that investigate hybrid optimization algorithms for real structures. Many of them did not take into account the sensitivity of the updating parameters to the model outputs. Therefore, in this paper, optimization algorithms and sensitivity analysis are applied for model updating of a real cable-stayed bridge, i.e., the Kien bridge in Vietnam, based on experimental data. First, a global sensitivity analysis using Morris method is employed to find out the most sensitive parameters among twenty surveyed parameters based on the outputs of a Finite Element (FE) model. Then, an objective function related to the differences between frequencies, and mode shapes by means of MAC, COMAC and eCOMAC indices, is introduced. Three metaheuristic algorithms, namely Gravitational Search Algorithm (GSA), Particle Swarm Optimization algorithm (PSO) and hybrid PSOGSA algorithm, are applied to minimize the difference between simulation and experimental results. A laboratory pipe and Kien bridge are used to validate the proposed approach. Efficiency and reliability of the proposed algorithms are investigated by comparing their convergence rate, computational time, errors in frequencies and mode shapes with experimental data. From the results, PSO and PSOGSA show good performance and are suitable for complex and time-consuming analysis such as model updating of a real cable-stayed bridge. Meanwhile, GSA shows a slow convergence for the same number of population and iterations as PSO and PSOGSA.

• Journal of the Korean Physical Society
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• v.73 no.10
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• pp.1406-1409
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• 2018

We have frequently encountered the rapid changes that prevalent opinion of the social community is toppled by a new and opposite opinion against the pre-exiting one. To understand this interesting process, mean-field model with infinite-interaction range has been mostly considered in previous studies S. A. Marvel et al., Phys. Rev. Lett. 110, 118702 (2012). However, the mean-field interaction range is lack of reality in the sense that any individual cannot interact with all of the others in the community. Based on it, in the present work, we consider a simple model of opinion consensus so-called basic model on the low-dimensional lattices (d = 1, 2) with finite interaction range. The model consists of four types of subpopulations with different opinions: A, B, AB, and the zealot of A denoted by $A_c$, following the basic model shown in the work by S. A. Marvel et al.. Comparing with their work, we consider the finite range of the interaction, and particularly reconstruct the lattice structure by adding new links when the two individuals have the distance < ${\sigma}$. We explore how the interaction range ${\sigma}$ affects the opinion consensus process on the reconstructed lattice structure. We find that the critical fraction of population for $A_c$ required for the opinion consensus on A shows different behaviors in the small and large interaction ranges. Especially, the critical fraction for $A_c$ increases with the size of ${\sigma}$ in the region of small interaction range, which is counter-intuitive: When the interaction range is increased, not only the number of nodes affected by $A_c$ but also that affected by B grows, which is believed to cause the increasing behavior of the critical fraction for $A_c$. We also present the difference of dynamic process to the opinion consensus between the regions of small and large interaction ranges.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2001.10a
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• pp.153-168
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• 2001

In the country where the population concentrates in the metropolis with the narrow land, development of th ocean space is necessary. Recently, mega-float offshore structure is studied as one of the effective utilization of the ocean space. And very large floating structure are now being considered for various applications such as floating airports, offshore cities and so on. This very large structure is relatively flexible compared with real floating structures like large ships. when we estimate dynamic responses of these structures in waves, the elastic deformation is important, because vertical dimension is small compared with horizontal. And it is necessary to examine the effect of ocean wave eternal force received from the natural environment. In this study, the mat-type large floating structure is made to be analytical model. And the analysis of the dynamic response as it receives regular wave is studied. The finite element method is used in the analysis of structure part of this model. And the analysis is carried out using the boundary element method in the fluid part. In order to know the characteristics of the dynamic response of the large floating structures, effects of wavelength, bending rigidity of the structure, water depth, and wave direction on dynamic response of the floating structure are studied by use of numerical calculation.