• Journal of the Korea Computer Graphics Society
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• v.27 no.3
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• pp.13-23
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• 2021

In this paper, we proposed a framework that generates the trajectory of a single rigid body based on its COM configuration and contact pose. Because we use a smaller input dimension than when we use a full body state, we can improve the learning time for reinforcement learning. Even with a 68% reduction in learning time (approximately two hours), the character trained by our network is more robust to external perturbations tolerating an external force of 1500 N which is about 7.5 times larger than the maximum magnitude from a previous approach. For this framework, we use centroidal dynamics to calculate the next configuration of the COM, and use reinforcement learning for obtaining a policy that gives us parameters for controlling the contact positions and forces.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.6
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• pp.351-356
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• 2022

In this paper, we present the regression analysis and design optimization for improving the permeability of 3D woven materials based on numerical analysis data. First, the parametric analysis model is generated with variables that define the gap sizes between each directional wire of the woven material. Then, material properties such as bulk modulus, thermal conductivity coefficient, and permeability are calculated using numerical analysis, and these material data are used in the polynomial-based regression analysis. The Pareto optimal solution is obtained between bulk modulus and permeability by using multi-objective optimization and shows their trade-off relation. In addition, gradient-based design optimization is applied to maximize the fluid permeability for 3D woven materials, and the optimal designs are obtained according to the various minimum bulk modulus constraints. Finally, the optimal solutions from regression equations are verified to demonstrate the accuracy of the proposed method.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.4
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• pp.259-264
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• 2023

In this study, we devised a parametric analysis workflow for efficiently analyzing the material properties of 3D woven materials. The parametric model uses wire spacing in the woven materials as a design parameter; we generated 2,500 numerical models with various combinations of these design parameters. Using MATLAB and ANSYS software, we obtained various material properties, such as bulk modulus, thermal conductivity, and fluid permeability of the woven materials, through a parametric batch analysis. We then used this large dataset of material properties to perform a regression analysis to validate the relationship between design variables and material properties, as well as the accuracy of numerical analysis. Furthermore, we constructed an artificial neural network capable of predicting the material properties of 3D woven materials on the basis of the obtained material database. The trained network can accurately estimate the material properties of the woven materials with arbitrary design parameters, without the need for numerical analyses.

• Journal of the Korean earth science society
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• v.37 no.3
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• pp.173-185
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• 2016

The purpose of this study is to investigate the effects of systems thinking on high school students' self-regulatory efficacy and self-confidence that constitute science self-efficacy. We set self-regulatory efficacy as a factor of students' systems thinking affects their self-confidence on science through self-regulatory efficacy. A total of 210 students were sampled from general high schools and 188 valid cases were analyzed. The instrument has 39 items that consist of 20 items measuring systems thinking and 19 items of science self-efficacy. The result of the exploratory factor analysis indicated that 20 items for systems thinking, 8 items for self-regulatory efficacy, 4 items for self-confidence are reasonable. Testing the goodness of fit of a structural equation model, it turn out to be appropriate (${\chi}^2$=344.498, df=242, TLI= .921, RMSEA= .044) using 24 items (mental model, personal mastery, systems analysis, self-regulatory efficacy, and self-confidence were constructed). In addition, the mental model, which is one factor of systems thinking, is mediated by self-regulatory efficacy that affects self-confidence directly and/or indirectly. The results suggest that systems thinking affects science self-efficacy directly and indirectly. Utilizing systems thinking in science education can produce a theoretical basis in improving students' confidence and self-efficacy about science.

• Journal of Korean Society for Geospatial Information Science
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• v.10 no.4 s.22
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• pp.41-50
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• 2002

RPM is the one of the sensor models which is proposed by Open GIS Consortium (OGC) as image transfer standard. And it is the sensor model for end-users using IKONOS, a commercial pushbroom satellite, imagery which provide about 1m ground resolution. Parameters called RPC which is IKONOS RFM coefficients are serviced to end-users. But if some users try to make additional effort to get rigorous geo-spatial information, it is necessary to apply mathematic or abstract sensor models, because vendors don't offer any ancillary data for physical sensor models such as satellite orbit and navigation. Abstract sensor models such as pushbroom Direct Linear Transform (DLT) require many GCPs well distributed in imagery, and mathematic sensor model such as RFM, polynomials need much more GCPs. Therefore RPC modification using additional a few GCPs is the best solution. In this paper, two methods are proposed to modify RPC. One is method to use pseudo GCPs generated in normalized cubic, and another method uses parameters observations and a few GCPs. Through two methods, we get improvement of accuracy 50% and over.

• Korean Journal of Social Welfare
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• v.67 no.1
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• pp.263-288
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• 2015

This study is to research the mediating effects of optimism and quality of relationship which interpersonal traumatic experience influences posttraumatic growth. It focuss on verifying the impact of interpersonal traumatic experience to optimism and quality of relationship and the influence of optimism and quality of relationship to posttraumatic growth. And also it is to verify dual mediating effect between optimism and quality of relationship. Data for this study were collected through the use of a survey instrument completed by 405 interpersonal traumatic experience, 30-60 age group. Collected data were analysed by AMOS program, Structure Equation Model(SEM) was implemented to verify the mediating effect between optimism and quality of relationship. Finally, Phantom Variable was utilized for verification of indirect influence of a multi mediating effects. The findings of this study were as follows, First, the result shows that the higher level interpersonal traumatic experience, the higher posttraumatic growth they have. Second, it shows that optimism and quality of relationship have partial mediating effect between interpersonal traumatic experience and posttraumatic growth. Third, it was analyzed that optimism and quality of relationship had double mediating effect. Based on these findings, the research discussion reinforced the importance of intervene with its optimism and quality of relationship in the site of those who experience interpersonal trauma. Theological, political and practical implications of this study are as follows. First, it has a series of significance in terms of that this study confirmed its influence considering the quality of relationship from interpersonal experience among relevant factors of traumatic accident, optimism among individual factors, quality of relationship among environmental factors based on 'the crisis of life and the theory of individual growth'. econd, even though optimism and quality of relationship were proved as major predictors for posttraumatic growth of those who experience interpersonal traumatic, psychological support center for traumatic experience is not operated systematically in Korea. Third, this study implies that it should intervene mainly with its optimism and quality of relationship in the site of those who experience interpersonal trauma such as any abuses including sexual abuse, bullying, and divorce.

• Korean Journal of Culture and Social Issue
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• v.27 no.4
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• pp.457-474
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• 2021

The study aimed to investigate the relation between patriarchal family environment and zero-sum beliefs, and the mediating effect of sexism on the relation based on the Instrumental Model of Group Conflict (Esses et al., 1998). This study also examined the moderating effect of gender on the relation between patriarchal family environment and sexism, and the moderated mediating effect of gender through sexism. Participants were 310 first-year college students (234 males and 76 females) in the college of science and engineering, and they completed a survey consisting of patriarchal family environment, sexism, and zero-sum belief. Data were analyzed using SPSS Macro Process, and the results indicated that the relation between patriarchal family environment and zero-sum beliefs was fully mediated by sexism. In addition, the relation between patriarchal family environment and sexism was moderated by gender. Specifically, patriarchal family environment significantly predicted sexism for men, but not for women. Moreover, only for men, sexism mediated the relation between patriarchal family environment and zero-sum beliefs. Therefore, patriarchal family environment could cause sexism which could promote zero-sum beliefs for men.

• Journal of Advanced Technology Convergence
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• v.3 no.1
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• pp.21-31
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• 2024

The study confirmed the relationship between attractiveness and suitability in the relationship between the formativeness of creating the artistic form of a virtual influencer who acts as an advertising model, advertising attention, and advertising attitude. To confirm this, the subjects of the study were the MZ generation and X generation, which have a high rate of SNS use. The analysis method used SPSS statistics 27.0 and SPSS process macro version. The research results are as follows. First, it was confirmed that attractiveness and suitability fully mediate the relationship between formativeness and advertising attention. In the path of formativeness and advertising attention, the total effect was found to be higher than the direct effect, and it was confirmed that there was a double parallel mediation effect through attractiveness and suitability in the relationship between the formativeness of virtual influencers and advertising attention. Second, it was confirmed that formativeness affects the mediating variable, attractiveness, but attractiveness does not affect attitude toward advertising. Since formativeness affects suitability and suitability in turn influences attitude toward advertising, it was confirmed that there is a full mediating effect between these variables. According to these results, the parallel mediating effect of attractiveness and formativeness was not confirmed in the relationship between formativeness and attitude towards advertising. The above study is significant in that it presents academic implications and practical implications by examining the dual and parallel mediating effects of attractiveness and suitability in the relationship between formativeness, advertising attention, and advertising attitude variables, which are considered in the production of virtual influencers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.10 no.4
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• pp.43-52
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• 1990

Theoretical foundation and algorithms are presented of a new surface modeling and pre-processing system for the three-dimensional structures. The modeling method is based on the boundary representation scheme and composed of two hierarchical model structures: curve-network and surface models. The concept of modeling curve as a union of links is introduced to facilitate surface modeling via various transfinite mapping techniques or Coons Patches. Efficiency and novel aspects of the present method are discussed. Finite element mesh genceration and application procedures will be reported in a later paper.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.2
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• pp.20-30
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• 2001

In the paper, we propose a predictive control scheme using multiple neural network-based prediction models. To construct the multiple models, we select several specific values of a parameter whose variation affects serious control performance in the plant. Among the multiple prediction models, we choose one that shows the best predictions for future outputs of the plant by a switching technique. Based on a nonlinear programming method, we calculate the current process input in the nonlinear predictive control system with multiple prediction models. The proposed control method is shown to be very effective when a parameter of the plant changes or the time delay, if it exists, varies. It is also shown that the proposed method is successfully applied for the control of suspension in a electro-magnetic levitation system.