• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1055-1067
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• 2017

Most previous works to study for the depression of the disabilities in Korea have analyzed the repeated measured data of each individual under the mutually independent assumption. In this study, Korea Welfare Panel data of the disabilities surveyed additionally every three years are analyzed to detect the significant exploratory variables by the linear mixed models. A suitable correlation matrix is considered for the dependency of repeated measurement of each individual. The random effect to reflect the characteristics of the individuals as well as the fixed effect is included in the fitted linear mixed model. By the residual plot of the fixed effect model, the problem that the averages of residuals of each individual do not seem to be around zero is described. Further, the residual plot and the Q-Q plot coming from the selected final model are shown that the problem is modified well.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.246-248
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• 2021

Recently data has been transformed into a data economy and society that acts as a catalyst for the development of all industries and the creation of new value, and COVID-19 is accelerating digital transformation. In the upcoming intelligent Internet of Things era, the availability of decentralized systems such as blockchain and mixnet is emerging to solve the security problems of centralized systems that makes it difficult to utilize data safely and efficiently. Blockchain manages data in a transparent and decentralized manner and guarantees the reliability and integrity of the data through agreements between participants, but the transparency of the data threatens the privacy of users. On the other hand, mixed net technology for protecting privacy protects privacy in distributed networks, but due to inefficient power consumption efficiency and processing speed issues, low cost, light weight, low power consumption Internet Hard to use. In this paper, we analyze the limitations of conventional mixed-net technology and propose a mixed-net technology method for low power consumption, high speed, and the Internet of things.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1534-1541
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• 1996

Routing security is the confidentiality of route taken by the data transmitted over communication networks. If the route is detected by an adversary, the probability is high that the data lost or the data can be intercepted by the adversary. Therefore, the route must be protected. To accomplish this, we select an intermediate node secretly and transmit the data using this intermediate node, instead of sending the data to a destination node using the shortest direct path. Furthermore, if we use a number of secret routes from a node to a destination node, data security is much stronger since we can transmit partial data rather than entire data along a secret route. Finally, the idea above is implemented on MRNS Network.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.123-137
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• 2018

A nonlinear mixed effects model is mainly used to analyze repeated measurement data in various fields. A nonlinear mixed effects model consists of two stages: the first-stage individual-level model considers intra-individual variation and the second-stage population model considers inter-individual variation. The individual-level model, which is the first stage of the nonlinear mixed effects model, estimates the parameters of the nonlinear regression model. It is the same as the general nonlinear regression model, and usually estimates parameters using the least squares estimation method. However, the least squares estimation method may have a problem that the estimated value of the parameters and standard errors become extremely large if the assumed nonlinear function is not explicitly revealed by the data. In this paper, a new estimation method is proposed to solve this problem by introducing the ridge regression method recently proposed in the nonlinear regression model into the first-stage individual-level model of the nonlinear mixed effects model. The performance of the proposed estimator is compared with the performance with the standard estimator through a simulation study. The proposed methodology is also illustrated using quantitative high throughput screening data obtained from the US National Toxicology Program.

• Journal of Korean Society of Forest Science
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• v.104 no.1
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• pp.111-116
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• 2015

The purpose of this study was to evaluate mixed model of dbh-height relation containing random effect. Data were obtained from a survey site for Quercus variabilis in Gangwon region and remeasured the same site after three years. The mixed model were used to fixed effect in the dbh-height relation for Quercus variabilis, with random effect representing correlation of survey period were obtained. To verify the evaluation of the model for random effect, the akaike information criterion (abbreviated as, AIC) was used to calculate the variance-covariance matrix, and residual of repeated data. The estimated variance-covariance matrix, and residual were -0.0291, 0.1007, respectively. The model with random effect (AIC = -215.5) has low AIC value, comparison with model with fixed effect (AIC = -154.4). It is for this reason that random effect associated with categorical data is used in the data fitting process, the model can be calibrated to fit repeated site by obtaining measurements. Therefore, the results of this study could be useful method for developing model using repeated measurement.

• Journal of the Korean Data and Information Science Society
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• v.25 no.5
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• pp.1025-1038
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• 2014

Linear mixed model has often been utilized for genetic association analysis with family-based samples. The correlation matrix for family-based samples is constructed with kinship coefficient and assumes that parental phenotypes are independent and the amount of correlations between parent and offspring is same as that of correlations between siblings. However, for instance, there are positive correlations between parental heights, which indicates that the assumption for correlation matrix is often violated. The statistical validity and power are affected by the appropriateness of assumed variance covariance matrix, and in this thesis, we provide the linear mixed model with flexible variance covariance matrix. Our results show that the proposed method is usually more efficient than existing approaches, and its application to genome-wide association study of body mass index illustrates the practical value in real data analysis.

• Journal of Korea Water Resources Association
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• v.52 no.12
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• pp.1001-1009
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• 2019

Due to recent increasing heavy snow in Korea, the damage caused by heavy snow is also increasing. In Korea, there are many efforts including establishing disaster prevention measures to reduce the damage throughout the country, but it is difficult to establish the design criteria due to the characteristics of heavy snow. In this study, snowfall frequency analysis was performed to estimate design snow depths using observed snow depth data at Jinju, Changwon and Hapcheon stations. The conventional frequency analysis is sometime limted to apply to the snow depth data containing zero values which produce unrealistc estimates of distributon parameters. To overcome this problem, this study employed mixed distributions based on Lognormal, Generalized Pareto (GP), Generalized Extreme Value (GEV), Gamma, Gumbel and Weibull distribution. The results show that the mixed distributions produced smaller design snow depths than single distributions, which indicated that the mixed distributions are applicable and practical to estimate design snow depths.

• Ocean and Polar Research
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• v.26 no.1
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• pp.65-75
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• 2004

In order to understand the water masses and their distribution in the eastern Yellow Sea from winter to spring, a cluster analysis was applied to the temperature and salinity data of Korea Oceanographic Data Center from 1970 to 1990. From December to April, Yellow Sea Cold Water (YSCW) dominates the eastern Yellow Sea, whereas Eastern Yellow Sea Mixed Water (MW) and Yellow Sea Warm Water (YSWW) are found in the southern part of the eastern Yellow Sea. MW appears at the frontal region around $34^{\circ}N$ between YSCW in the north and YSWW in the south. On the other hand, Tshushima Warm Water (TWW) is found around Jeju Island and the South Sea of Korea. These water masses are relatively well-mixed throughout the water column due to the winter monsoon. However, the water column begins to be stratified in spring due to increased solar heating, the diminishing winds and fresh water discharge, and the water masses in June may be separated into surface, intermediate and bottom layers of the water column. YSWW advances northwestward from December to February and retreats southeastward from February to April. This suggests a periodic movement of water masses in the southern part of the eastern Yellow Sea from winter to spring. YSWW may continue to move eastward with the prevailing eastward current to the South Sea from April to June. Also, the front relaxes in June, but the mixed water advances to the north, increasing salinity. The salinity is also higher in the nearshore region than offshore. This indicates an influx of oceanic water to the north in the nearshore region of the eastern Yellow Sea in spring in the form of mixed water.

• Journal of Korean Society for Quality Management
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• v.44 no.4
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• pp.799-811
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• 2016

Purpose: The conjoint analyst in marketing are interested in detecting whether there exist synergy or antagonistic effects between two attributes. In the cases where attributes have two or three levels, we research on the design of survey questionnaire to estimate all the main effect and as many two factor interaction effects as possible. Methods: We consider the balanced incomplete block (BIB) mixed level factorial design $2^f{\times}3^g$ or fractional factorial design. To reduce the number of questions in a questionnaire, we propose the balanced incomplete block mixed level design with minimum aberration which is generated by implementing proc factex in SAS. Also, we propose using two or three level BIB factorial design instead of mixed level designs by transforming three level attributes into two attributes of two levels and two level attribute into three level attribute by using dummy level technique. Results: We propose three methods for designing survey questionnaire where the block and design generators are found with practical number of questions in a questionnaire. By analyzing all the respondents survey data generated by the simulation study, we find the proper model and do the concepts optimization. Conclusion: The proposed methods of designing survey questionnaires seem to perform well in the sense that the proper model, and then the optimal concept is found in a case study where all the respondents survey data are generated by the simulation study.

• Journal of Korean Society of Forest Science
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• v.96 no.2
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• pp.160-169
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• 2007

The data used to develop distance-independent individual models for natural mixed forests were collected from 712 remeasured permanent sample plots (25,526 trees) of 10-year periodic from 1990 to 2000 in Baihe Forest Bureau of Changbai Mountains, northeast China. Based on analyzing relationship between diameter increment of individual trees with tree size, competitive status, and site condition, the diameter growth models for individual trees of 15 species growing in mixed-species uneven-aged forest stands, that have simple form, good predicting precision, and easily applicable, were developed using stepwise regression method. The main variables influencing on diameter increment of individual trees were tree size and competition, however, the site conditions were not significantly related with diameter increment. The tree size variables (lnDBH and $DBH^2$) were the most significant and important predictors of diameter growth existing in all 15 growth models. The diameter increment was directly proportional to tree diameter for each species. For the competitive factors in growth model, the relative diameter (RD), canopy closure (P), and the ratio of diameter of subject tree with maximum diameter (DDM) were contributed to the diameter increment at a certain extent. Other measures of stand density, such as basal area of stand (G) and stand density index (SDI), were not significantly influenced on diameter increment. Site factors, such as site index, slope and aspect were not important to diameter increment and excluded in the final models. The total variance explained by the final models of squared diameter increment ($R^2$) for all 15 species ranged from 35% to 72% and these results compared quit closely with those of Wykoff (1990) for mixed conifer stands. Using independent data set, validation measures were evaluated for predicting models of diameter increment developed in this study. The result indicated that the estimated precision was all greater than 94% and the models were suitable to describe diameter increment.