• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1587-1590
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• 1987

A non-linear filtering for the noise cancelling of signals degraded by random impulsive noise is proposed. The non-linear algorithm is based on a criterion for the overall smoothness of the signal. The smoothness criterion is optimized by a dynamic programming strategy. It performs considerably better than a LDNF(low-distortion nonlinear filter), although being comparable in computing time.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.879-884
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• 1988

For more economical operation of chemical plants, optimal operating conditions are to be set and maintained as far as possible. For this purpose, optimizing control is applied to chemical plants. In this study, a process optimizer composed of a process simulator and an optimization routine using Successive Quadratic Programming as optimization technique is developed and the effect of optimizing control is tested on an example process, and a new process optimization strategy based on modified Jacobian matrix is developed.

• Structural Engineering and Mechanics
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• v.7 no.1
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• pp.19-33
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• 1999

The critical buckling loads of unsymmetrically laminated rectangular plates with a given material system and subjected to combined lateral and inplane loads are maximized with respect to fiber orientations by using a sequential linear programming method together with a simple move-limit strategy. Significant influence of plate aspect ratios, central circular cutouts, lateral loads and end conditions on the optimal fiber orientations and the associated optimal buckling loads of unsymmetrically laminated plates has been shown through this investigation.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.490-495
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• 1992

A neural model predictive control strategy combining a neural network for plant identification and a nonlinear programming algorithm for solving nonlinear control problems is proposed. A constrained nonlinear optimization approach using successive quadratic programming cooperates with neural identification network is used to generate the optimum control law for the complicate continuous/batch chemical reactor systems that have inherent nonlinear dynamics. Based on our approach, we developed a neural model predictive controller(NMPC) which shows excellent performances on nonlinear, model-plant mismatch cases of chemical reactor systems.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.899-902
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• 1993

A neural model predictive control strategy combining a neural network for plant identification and a nonlinear programming algorithm for solving nonlinear control problems is proposed. A constrained nonlinear optimization approach using successive quadratic programming combined with neural identification network is used to generate the optimum control law for complex continuous chemical reactor systems that have inherent nonlinear dynamics. The neural model predictive controller (MNPC) shows good performances and robustness. To whom all correspondence should be addressed.

• Journal of The Korean Association of Information Education
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• v.21 no.5
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• pp.583-593
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• 2017

In order to overcome the difficulties of programming education for beginners, various research strategies such as UMC(Use-Modify-Create), design based learning, discovery learning and play learning are applied. In this study, we developed a HVC(History-VR Coding-Collaboration) learning strategy model for the improvement of learner's computational thinking. The HVC model is composed of a combination module of block type. We developed a 12th session storytelling - based virtual reality programming curriculum. As a result, HVC model and SW education program showed significant difference in improvement of learner's computational thinking.

• Journal of The Korean Association of Information Education
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• v.20 no.1
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• pp.21-28
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• 2016

As the Programming education is organized in Elementary Education Curriculum by the 2015 Revised Curriculum, The study of teaching and learning methods are needed. In this study, we applied the Pair Programming in programming teaching and learning methods that can be applied at Elementary school level. The result of applying creative problem solving ability of the proposed teaching strategy appeared significant difference. Also it showed that a significant difference in the effectiveness of the completed programs and The Gap between Men and Women.

• The Journal of Korean Association of Computer Education
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• v.13 no.2
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• pp.15-23
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• 2010

Computational Literacy education is being required in current digital age, but the educational strategy of it is lacking. In traditional education, instructors have been teaching by considering learners' characteristics for effective learning. It is necessary to investigate their characteristics for applying this method to computational literacy education. Therefore, we taught programming that is main area on computational literacy, and analyzed learners' characteristics focused on Felder's learning style and multiple intelligence. That is, we taught 194 university students computational literacy with scratch that was one of the popular educational programming languages, and analyzed the relation among learning style, multiple intelligence and the students' programming performance. Also, we found considerations through comparing students' characteristics with experts' ones.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.228-230
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• 2018

Recently, many universities have opened lectures on programming in liberal arts subjects. However, learners find it very difficult to learn programming, and efforts to increase interest and interest continue. Especially, in the previous research, it was found that there is a difference in programming learning between boys and girls. In this study, we analyzed the resilience of learners of liberal arts programming lectures. The pre-test was conducted on 399 students. It was found that the male students had a higher average resilience than the female students but a larger deviation. Through this study, we can find a plan for learners' learning strategy for programming learning.

• Journal of The Korean Association of Information Education
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• v.24 no.6
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• pp.597-606
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• 2020

Recently, as students' programming classes are being conducted online, interest in factors that can lead to the success of online programming classes is also increasing. Therefore, in this study, online programming classes were conducted for specialized high school students using a web-based simulation programming tool through TinkerCad. In these online programming classes, students' self-regulation ability and learning flow were set as variables that influence both learning engagement and teaching presence, and the predictive power of each was analyzed. As a result, it was found that both self-regulation ability and learning flow were predictive variables for learning engagement and teaching presence, and that learning flow played a mediating role between self-regulation ability, learning engagement, and teaching presence. This study is meaningful in that it suggested that self-regulation ability and learning flow should be considered more meaningfully in online programming classes, and a practical strategy for this is presented.