• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.6
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• pp.538-544
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• 2012

Analysis of thermal performance is required for the economic operation of turbine cycle of power plant. We developed corrective model of main feed water flow which is the most important parameter for the precise analysis of turbine cycle performance. Classification model for the identification of feed water flow measurement status was applied to increase the suitability of the corrective model. We used neural network and support vector machine to develop estimation model of main feed water flow with more generalization capability. The estimation model can be used practically to evaluate corrective performance of turbine cycle plant.

• Journal of the military operations research society of Korea
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• v.16 no.1
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• pp.113-129
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• 1990

This paper presents the simulation model to decide the mean size of cannibalization aircraft (MSCA) under steady state when an airbase makes use of cannibalization to support the spare parts of an airfleet. In this model, the essential factors such as mission requirements, mission time, failure time, repair time, repair capability, inventory policy, cannivalization rule are considered. The model is constructed with above factors and actual airbase operating rules for a basis. Because of the tangled interdependencies among the each factors, it is inevitable to construct the model by the simulation technique. The mission and support system of the airbase is considered as a closed queueing network with a finite number of unit The troubled aircrafts are repaired in accordance with the priorities that are determined by their repair times. The illustrative example of the model, using the actual data of xx-airbase, is presented. The model would be a useful tool not only to determine the MSCA and the size of scheduled maintenance aircraft but to evaluate the NORS (not operationally ready supply) rate and the availability of an airfleet.

• Structural Engineering and Mechanics
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• v.71 no.3
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• pp.245-255
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• 2019

In this paper, an inverted-pendulum model consisting of a point supported by spring limbs with roller feet is adopted to simulate human walking load. To establish the kinematic motion of first and second single and double support phases, the Lagrangian variation method was used. Given a set of model parameters, desired walking speed and initial states, the Newmark-${\beta}$ method was used to solve the above kinematic motion for studying the effects of roller radius, stiffness, impact angle, walking speed, and step length on the ground reaction force, energy transfer, and height of center of mass transfer. The numerical simulation results show that the inverted-pendulum model for walking is conservative as there is no change in total energy and the duration time of double support phase is 50-70% of total time. Based on the numerical analysis, a dynamic load factor ${\alpha}_{wi}$ is proposed for the traditional walking load model.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.223-229
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• 2022

Early detection can help prevent heart disease, which is one of the most common reasons for death. This paper provides a clinical support model for predicting cardiac disease. The model is built using two publicly available data sets. The admissibility and application of the the model are justified by a sequence of tests. Implementation of the model and testing are also discussed

• Korean Journal of Child Studies
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• v.37 no.3
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• pp.53-68
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• 2016

Objective: This study examined the relationships between negative affect, social support, and career maturity among adolescents. Methods: The participants in this study comprised 260 $1^{th}$ junior high school students in a Seoul metropolitan area. They completed questionnaires on level of negative affect, social support, and career maturity. Data were analyzed by means of basic descriptive statistics, Pearson's correlations, and multiple and hierarchical regression analyses. Aiken and West's method was used to determine the interactive model's modality. Results: The major findings were as follows: First, negative affect was negatively correlated with social support and career maturity. Social support was positively correlated with career maturity. Second, significant interaction effects were found between negative affect and social support on career maturity; that is, for male students, significant interaction effects were found between negative affect and social support (parent support) on career maturity (career determinacy/career independence). For female students, significant interaction effects were found between negative affect and social support (peer support) on career maturity (career confidence/career readiness/career determinacy/career independence). Conclusion: These results suggest the need to intervene in relation to social support (parent support/peer support) and to improve career maturity among adolescents.

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.267-280
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• 2013

College tuition is a significant economic, social, and political issue in Korea. We conduct a Bayesian analysis of a hierarchical model to address the factors related to college tuition based on a survey data collected by Statistics Korea. A binary response variable is selected depending on if more than 70% of tuition costs are supported by parents, and a hierarchical Probit model is constructed with areas as groups. A set of explanatory variables is selected from a factor analysis of available variables in the survey. A Markov chain Monte Carlo algorithm is used to estimate parameters. From the analysis results, income and stress are significantly related to college tuition support from parents. Parents with high income tend to support children's college tuition and students with parents' financial support tend to be mentally less stressed; subsequently, this shows that the economic status of parents significantly affects the mental health of college students. Gender, a healthy life style, and college satisfaction are not significant factors. Comparing areas in terms of the degrees of correlation between stress/income and tuition support from parents, students in Kangwon-do are the most mentally stressed when parents' support is limited; in addition, the positive correlation between parents support and income is stronger in big cities compared to provincial areas.

• Proceedings of the Korea Concrete Institute Conference
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• 1999.10a
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• pp.429-432
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• 1999

The concrete slab on the foundation may have curling and warping deformations due to moisture and temperature gradient of its section. These deformations may change the support conditions of concrete slabs, and cause higher level of stresses than expected. This study was performed to verify the effect of partial support condition of concrete slab on the foundation due to its deformations and to develop the useful analytic method for describing these phenomenons. The partial support condition verified by FWD test results, and it was concluded that the gap model could be useful in analysing the concrete slab with partial support conditions.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.467-474
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• 2006

In this paper we present a weighted support vector machine(SVM) and a weighted least squares support vector machine(LS-SVM) for the prediction in the heteroscedastic regression model. By adding weights to standard SVM and LS-SVM the better fitting ability can be achieved when errors are heteroscedastic. In the numerical studies, we illustrate the prediction performance of the proposed procedure by comparing with the procedure which combines standard SVM and LS-SVM and wild bootstrap for the prediction.

• Journal of Korea Technology Innovation Society
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• v.2 no.3
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• pp.1-18
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• 1999

The purpose of this research is to analyze the influence of the factors on the performance of na-tional R&D support program. A LISREL model was employed to analyze the relationship between the factors and the performance which was measured in the technological and commercial aspect. The result of the study reveals the R&D management business administration the age and the size of the company industry domain are the factors whose relationship with the performance are sta-tistically significant.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1569-1574
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• 2005

In this paper, I propose an intelligent credit rating system using a bankruptcy prediction model based on support vector machines (SVMs). SVMs are promising methods because they use a risk function consisting of the empirical error and a regularized term which is derived from the structural risk minimization principle. This study examines the feasibility of applying SVM in Predicting corporate bankruptcies by comparing it with other data mining techniques. In addition. this study presents architecture and prototype of intelligeht credit rating systems based on SVM models.