• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.91-98
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• 2022

In the next generation wireless communication system, the beamforming technique based on a massive antenna is one of core technologies for transmitting and receiving huge amounts of data, efficiently and accurately. For highly performed and highly reliable beamforming, it is required to accurately estimate the Angle of Arrival (AOA) for the desired signal incident to an antenna. Employing the massive antenna with a large number of elements, although the accuracy of the AOA estimation is enhanced, its computational complexity is dramatically increased so much that real-time communication is difficult. In order to improve this problem, AOA estimation algorithms based on the massive antenna with the low computational complexity have been actively studied. In this paper, we compute and analyze the computational complexity of the cascade AOA estimation algorithm based on the Flexible Massive Concentric Circular Array (FMCCA). In addition, its computational complexity is compared to conventional AOA estimation techniques such as the Multiple Signal Classification (MUSIC) algorithm with the high resolution and the Only Beamspace MUSIC (OBM) algorithm.

• Computational Structural Engineering
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• v.30 no.1
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• pp.24-28
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• 2017

• 한국전산유체공학회:학술대회논문집
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• 2003.10a
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• pp.178-178
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• 2003

• Nuclear Engineering and Technology
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• v.11 no.3
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• pp.219-229
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• 1979

The current status of the computational methods and computer codes for the analysis of reactor kinetics is reviewed. Computational methods which have been developed for space-dependent transient analyses are presented and recent progress in the development of methods is discussed.

• Proceedings of the Korean Society for Language and Information Conference
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• 1996.02a
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• pp.53-62
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• 1996

• Computational Structural Engineering
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• v.22 no.4
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• pp.50-56
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• 2009

• Computational Structural Engineering
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• v.23 no.5
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• pp.34-41
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• 2010

• Computational Structural Engineering
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• v.27 no.4
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• pp.7-19
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• 2014

• Journal of The Korean Association of Information Education
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• v.24 no.2
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• pp.139-146
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• 2020

There is a hot debate about what the core competencies of future generations, who have to live an uncertain future, should cultivate. The future society is expected to become a Software-oriented Society driven by software. Under these circumstances, interest in software education is exploding around the world, and interest in cultivating computational thinking through software education is also increasing. Also, discussions about what computational thinking is and what competence factors are made up are in progress. However, the research on the relationship between the competence factors of computational thinking is relatively insufficient. In order to solve this problem, this study proceeded as follows. First, five competence factors of computational thinking were selected. Second, we defined a path model to analyze the relationships among the competence factors of computational thinking. Third, we chose a test tool to test computational thinking. Fourth, the computational thinking tests were conducted for 801 students in grades 3 through 6 of elementary school. Fifth, implications were derived by analyzing various viewpoints based on the results of the computational thinking test.

• Journal of The Korean Association of Information Education
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• v.19 no.3
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• pp.323-332
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• 2015

The purpose of this study is to verify the effectiveness of teaching and learning strategies of learner-centered learning for the computational thinking that is the educational purpose of SW education. For improving computational thinking, funny and easy educational contents and appropriate teaching and learning strategies are needed. In this study, I applied and verified the learner-centered strategies for non-computer major learners in computational thinking education: collaboration, sharing, self-directed learning. As the result, the teaching and learning of learner-centered learning affects the pleasure and the interest of learners; they affect computational thinking efficacy; it affects intention to use. It is able to apply this learner-centered learning strategies to computational thinking education as an effective educational strategies.