• International Journal of Aeronautical and Space Sciences
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• v.9 no.2
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• pp.79-86
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• 2008

High performance direct-iterative hybrid linear solver for large scale finite element problem is developed. Direct solution method is robust but difficult to parallelize, whereas iterative solution method is opposite for direct method. Therefore, combining two solution methods is desired to get both high performance parallel efficiency and numerical robustness for large scale structural analysis problems. Hybrid method mentioned in this paper is based on FETI-DP (Finite Element Tearing and Interconnecting-Dual Primal method) which has good parallel scalability and efficiency. It is suitable for fourth and second order finite element elliptic problems including structural analysis problems. We are using the hybrid concept of theses two solution method categories, combining the multifrontal solver into FETI-DP based iterative solver. Hybrid solver is implemented for our general structural analysis code, IPSAP.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.949-952
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• 2002

A regression model is used in predicting the response variable given predictor variables However, in case of large number of predictor variables, a regression model has some problems such as multicollinearity, interpretation of the functional relationship between the response and predictors and prediction accuracy. A clustering method and stepwise regression could be used to reduce the amount of data by grouping predictors having similar properties and by selecting the subset of predictors. respectively. This paper proposes a prediction method combining clustering method and stepwise regression. The proposed method fits a global model and local models and predicts responses given new observations by using both models. The paper also compares the performance of proposed method with stepwise regression via a real data of ample obtained in a steel process.

• International journal of steel structures
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• v.18 no.4
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• pp.1410-1419
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• 2018

Recently, a repair method by bonding patch plates is being applied to corroded steel structures. However, one of the issues of patch plate bonding repair is the brittle debonding of the patch plates. Generally, when the delamination of the patch plates occurs, the composite effect acting between the steel members and patch plates abruptly decreases. Therefore, to prevent the brittle debonding of the patch plates, a repair method combining an adhesive and stud bolts is proposed. Till date, tensile and compressive tests have been performed for the proposed method. In this study, plate bending tests were conducted to verify the effectiveness of this method under bending conditions. Furthermore, two types of epoxy resin-based adhesives were prepared to evaluate the effectiveness of the proposed method with different adhesive properties. The test results show that the proposed method is able to prevent the brittle debonding of the patch plates in the case of both epoxy resins.

• Proceedings of the KOR-KST Conference
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• 1999.10a
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• pp.405-410
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• 1999

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.35-51
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• 2008

Comparative studies in Phase III clinical trials quite often involve two or more equally important endpoints, and one cannot select primary endpoint from them. O'Brien(1984) proposed for continuous endpoints the OLS and GLS statistics as milti-variate test statistics. Pocock et al. (1987) mentioned the possibility of analyzing a mixture of data types, such as quantitative, binary and survival data types, with the OLS and GLS statistics, but the authors did not explore problems in combining several endpoints of different types. Furthermore, they did not perform a simulation study to assess the efficiencies of the OLS and GLS statistics for endpoints of a mixture of data types. In this paper, we propose the combining methods of correlated P-values for the analysis of multiple endpoints, and compare the efficiencies of this method with those of OLS and GLS statistics for a mixture of data types with a simulation study. Among the several methods of combining P-values that are more advantageous than combining of OLS and GLS statistics, method B maintains nominal significance levels and is more efficient, while method F and G have type I error rates that are larger than the specified significance levels, which might occasionally lead to a wrong conclusion.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.413-427
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• 2022

The purpose of this study was to improve and verify task value and academic self-efficacy of university students with metaverse gamification teaching method combining flipped learning and project-based learning. The subjects in this study were 16 university students majoring in counseling psychology who engaged in K university in cheong-ju. The subjects were assigned to the experimental group or the comparison group. The experimental group received the proposed metaverse gamification teaching method combining flipped learning and project-based learning while comparison group received teacher-centered learning. The dependent variables in this study were task value and academic self-efficacy. Each variable was assessed before class, after the end of the class. At the end of the class, the experimental group engaged statistically significantly higher levels of task value and academic self-efficacy than the comparison group. The findings of this study suggest that this metaverse gamification teaching method combining flipped learning and project-based learning is effective at improving task value and academic self-efficacy.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.593-596
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• 1999

In this paper, we propose an image retrieval system using the MBCM(Modified Borda Count method) in CME(Combining Multiple Experts). It combines color-, shape- and texture-based retrieval sub-systems. CME method can complementarily combine results of each retrieval system, which uses different features. There are some problems when the Borda count method in pattern recognition is applied to image retrieval. Thus, we propose a modified Borda count method to solve these problems. In the experiment, our method reduces false positive errors and produces better results than that of each retrieval module that uses only one feature.

• The Journal of Korea Robotics Society
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• v.8 no.2
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• pp.104-115
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• 2013

For natural human-robot interaction, we need to know location and shape of facial feature in real environment. In order to track facial feature robustly, we can use the method combining particle filter and active appearance model. However, processing speed of this method is too slow. In this paper, we propose two ideas to improve efficiency of this method. The first idea is changing the number of particles situationally. And the second idea is switching the prediction model situationally. Experimental results is presented to show that the proposed method is about three times faster than the method combining particle filter and active appearance model, whereas the performance of the proposed method is maintained.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.6
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• pp.321-327
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• 2019

Spectral Beam Combining (SBC) is used for a high-power fiber laser in order to overcome the power limitation of single fiber laser. In SBC, several laser bwams with different wavelengths are combined to obtain a single-aperture beam by diffraction grating. The combining efficiency is dependent on a linewidth, beam quality and specific wavelength of each beam among others. In this paper, we consider the method of a wavelength monitoring and a feedback control of laser diodes used as seeds of laser beams to obtain optimum combining conditions. In order to measure the wavelengths of multi-beam, we use the high resolution camera and diffraction grating with 1,800l/mm. The experiment results show the possibility of feedback control of a current and temperature of multi-seed laser diodes to obtain optimum wavelengths for SBC.

• International Journal of Industrial Entomology and Biomaterials
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• v.13 no.2
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• pp.63-72
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• 2006

Parthenogenesis, the development of unfertilized ovum opens new perspectives in silkworm breeding in the development of homozygous breeds. In order to improve induction of artificial parthenogenesis in the excised unfertilized eggs of different breeds of the silkworm, Bombyx mori L., a new method was devised and the results were compared with the routine method. General and specific combining abilities and hybrid vigour of newly developed bivoltine breeds were analyzed utilizing bivoltine breeds viz., $CSR_2,\;CSR_4,\;CSR_{17}\;and\;NB_4D_2$ Estimation of GCA revealed superiority of the breeds, $DNB_1$ for eight characters followed by $DNB_4$ for five characters. Among the testers, $CSR_2$ was found good general combiner for seven characters followed by $CSR_{17}$ for four characters. A great deal of variations was observed among the hybrids studied. Five hybrids namely, $DNB_1{\times}CSR_2,\;DNB_4{\times}CSR_4,\;DNB_4{\times}NB_4D_2,\;DNB_6{\times}CSR_2\;and\;DNB_7{\times}CSR_2$ showed significant SCA effects for 5-6 characters. The hybrid, $DNB_4{\times}CSR_4$ showed its superiority by expressing significant hybrid vigour over BPV for 7 characters. Majority of the hybrids exhibited significant hybrid vigour for survival rate, yield/10,000 larvae by weight, cocoon weight, cocoon shell weight, filament length and denier.