• Asian-Australasian Journal of Animal Sciences
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• v.33 no.4
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• pp.539-546
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• 2020

Objective: The Jeju native pig (JNP) found on the Jeju Island of Korea is a unique black pig known for high-quality meat. To investigate the genetic uniqueness of JNP, we analyzed the selection signature of the JNP in comparison to commercial pigs such as Berkshire and Yorkshire pigs. Methods: We surveyed the genetic diversity to identify the genetic stability of the JNP, using the linkage disequilibrium method. A selective sweep of the JNP was performed to identify the selection signatures. To do so, the population differentiation measure, Weir-Cockerham's F_st was utilized. This statistic directly measures the population differentiation at the variant level. Additionally, we investigated the gene ontologies (GOs) and genetic features. Results: Compared to the Berkshire and Yorkshire pigs, the JNP had lower genetic diversity in terms of linkage disequilibrium decays. We summarized the selection signatures of the JNP as GO. In the JNP and Berkshire pigs, the most enriched GO terms were epithelium development and neuron-related. Considering the JNP and Yorkshire pigs, cellular response to oxygen-containing compound and generation of neurons were the most enriched GO. Conclusion: The selection signatures of the JNP were identified through the population differentiation statistic. The genes with possible selection signatures are expected to play a role in JNP's unique pork quality.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.04a
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• pp.166-171
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• 2004

In this study, shape optimization of micro-static mixer with a cantilever beam was accomplished for mixing the mixing efficiency by using successive response surface approximations. Variables were chosen as the length of cantilever beam and the angle between horizontal and the cantilever beam. Sequential approximate optimization method was used to deal with both highly nonlinear and non-smooth characteristics of flow field in a micro-static mixer. Shape optimization problem of a micro-static mixer can be divided into a series of simple subproblems. Approximation to solve the subproblems was performed by response surface approximation, which does not require the sensitivity analysis. To verify the reliability of approximated objective function and the accuracy of it, ANOVA analysis and variables selection method were implemented, respectively. It was verified that successive response surface approximation worked very well and the mixing efficiency was improved very much comparing with the initial shape of a micro-static mixer.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2273-2286
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• 2000

In order to acquire the precise and fast response for an analytical query, proper selection of the views to materialize in data warehouse is very crucial. In traditional view selection algorithms, the whole relations are considered to be selected as materialized views. However, materializing the whole relations rather than a part of relations results in much worse performance in terms of time and space cost. Therefore, we present an improved algorithm for selection of views to materialize using clustering method to overcome the problem resulted from conventional view selection algorithms. In the presented algorithm, ASVMRT(Algorithm for Selection of Views to daterialize using Iteduced Table). we first generate reduced tables in clata warehouse using automatic clustering based on attrihute-values density, then we consider the combination of reduced tables as materialized views instead of the combination of the original hase relations. For the justification of the proposecl algorithm. we show the experimental results in which both time and space cost are approximately 1.8 times better than the conventional algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.12
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• pp.3133-3151
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• 2012

The optimal price strategy selection of two bounded rational cognitive mobile virtual network operators (MVNOs) in a duopoly spectrum sharing market is investigated. The bounded rational operators dynamically compete to sell the leased spectrum to secondary users in order to maximize their profits. Meanwhile, the secondary users' heterogeneous preferences to rate and price are taken into consideration. The evolutionary game theory (EGT) is employed to model the dynamic price strategy selection of the MVNOs taking into account the response of the secondary users. The behavior dynamics and the evolutionary stable strategy (ESS) of the operators are derived via replicated dynamics. Furthermore, a reward and punishment mechanism is developed to optimize the performance of the operators. Numerical results show that the proposed evolutionary algorithm is convergent to the ESS, and the incentive mechanism increases the profits of the operators. It may provide some insight about the optimal price strategy selection for MVNOs in the next generation cognitive wireless networks.

• IE interfaces
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• v.20 no.1
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• pp.41-48
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• 2007

The main purpose of this paper is cost reduction in absurd pilot positive expense and human accident prevention which is caused by in the pilot selection process. We use classification models such as logistic regression, decision tree, and neural network based on aptitude test results of 505 ROK Air Force applicants in 2001~2004. First, we determine the reliability and propriety against the aptitude test system which has been improved. Based on this conference flight simulator test item was compared to the new aptitude test item in order to make additional yes or no decision from different models in terms of classification accuracy, ROC and Response Threshold side. Decision tree was selected as the most efficient for each sequential flight training result and the last flight training results predict excellent. Therefore, we propose that the standard of pilot selection be adopted by the decision tree and it presents in the aptitude test item which is new a conference flight simulator test.

• Wind and Structures
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• v.27 no.1
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• pp.41-57
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• 2018

Concentrated Solar Photovoltaic (CPV) is a promising alternative to conventional solar structures. These solar tracking structures need to be optimized to be competitive against other types of energy production. In particular, the selection of the structural parameters needs to be optimized with regards to the dynamic wind response. This study aims to evaluate the effect of the main structural parameters, as selected in the preliminary design phase, on the wind response and then on the weight of the steel support structure. A parametric study has been performed where parameters influencing dynamic wind response are varied. The study is performed using a semi-deterministic time-domain wind analysis method. Unsteady aerodynamic model is applied for the shape of the CPV structure collector at different configurations in conjunction with a consistent mass-spring-damper model with the corresponding degrees of freedom to describe the dynamic response of the system. It is shown that, unlike the static response analysis, the variation of the peak wind response with many structural parameters is highly nonlinear because of the dynamic wind action. A steel structural optimization process reveals that close attention to structural and site wind parameters could lead to optimal design of CPV steel support structure.

• The Korean Journal of Malacology
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• v.28 no.4
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• pp.335-342
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• 2012

This study was conducted to estimation the selection response for growth-related traits in 31-month old of Pacific abalone, Haliotis discus hannai were born in 2008. In overall mean of surveyed traits and standard deviation showed $76.31{\pm}7.247$ mm of shell length, $49.48{\pm}5.307$ mm of shell width and $40.96{\pm}6.80$ g of total weight. The effect of sex and maturity were statistically significant in all traits include out a condition factor (p < 0.01). And In effect of sex, female were higher than male in all traits excepting condition factor, significantly. In correlation between breeding value and phenotypic value by each traits, showed rank correlation coefficient and simple correlation coefficient, which represented low positive correlation. A hopeful genetic improvement to the next generation showed 6.96 mm of shell length, 4.47 mm of shel width and 12.93 g of total weight. Therefor, It is considered that if considering properly selection intensity and selection ratio, efficient improvement could be made.

• Journal of Korean Academy of Nursing
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• v.34 no.2
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• pp.213-224
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• 2004

Purpose: This study was aimed to evaluate the effect of progressive muscle relaxation training using biofeedback on perceived stress, stress response, immune response and climacteric symptoms, Method: This was a crossover, pre-post test design, The study subjects are 36 middle-aged women who were selected at 2 public health centers, The independent variable was Biofeedback training for 4 weeks, twice a week and home training for 4 weeks, Dependent variables were perceived stress, stress response, immune response, and climacteric symptoms measured with Hildtch's scale (1996), Result: Progressive muscle relaxation training using biofeedback was not effective in reducing perceived stress, but it was shown to be effective in reducing physiological stress responses such as pulse rate and EMG, Though blood pressure and skin conductance were repeatedly down, and skin temperature slowly increased, there were no statistically significant differences. Progressive muscle relaxation training using biofeedback was not effective in reducing serum cortisol, enhancing immune responses, or decreasing climacteric symptoms. Conclusion: The findings point to a pressing need for further, well-controlled and designed research with consideration in selection of subjects and instruments, frequency of measurements, the sampling method, and intervention modalities.

• Earthquakes and Structures
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• v.27 no.1
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• pp.41-55
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• 2024

There are obvious differences between the characteristics of offshore ground motion and onshore ground motion in current studies, and factors such as water layer and site conditions have great influence on the characteristics of offshore ground motion. In addition, unlike seismic response analysis of offshore superstructures such as sea-crossing bridges, tunnels are affected by offshore soil constraints, so it is necessary to consider the dynamic interaction between structure and offshore soil layer. Therefore, a seismic response analysis model considering the seawater, soil layer and tunnel structure coupling is established. Firstly, the measured offshore and different soil layers onshore ground records are input respectively, and the difference of seismic response under different types of ground motions is analyzed. Then, the models of different site conditions were input into the measured onshore bedrock strong ground motion records to study the influence of seawater layer and silt soft soil layer on the seabed and tunnel structure. The results show that the overall seismic response between the seabed and the tunnel structure is more significant when the offshore ground motion is input. The seawater layer can suppression the vertical seismic response of seabed and tunnel structure, while the slit soft soil layer can amplify the horizontal seismic response. The results will help to promote seismic wave selection of marine structures and provide reference for improving the accuracy of seismic design of immersed tunnels.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.733-749
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• 2018

Sample selection arises as a result of the partial observability of the outcome of interest in a study. Heckman introduced a sample selection model to analyze such data and proposed a full maximum likelihood estimation method under the assumption of normality. Recently sample selection models for binomial and Poisson response variables have been proposed. Based on the theory of symmetry-modulated distribution, we extend these to a model for overdispersed count data. This type of data with no sample selection is often modeled using negative binomial distribution. Hence we propose a sample selection model for overdispersed count data using the negative binomial distribution. A real data application is employed. Simulation studies reveal that our estimation method based on profile log-likelihood is stable.