• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.3
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• pp.29-38
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• 2022

In this study, the shaking table tests were carried out on six types of non-structural elements installed on a full-scale two-story steel structure. The shaking table tests were performed for non-structural elements with and without seismic isolators. In this study, the seismic performance of Uninterruptible Power Supply (UPS) specimens was tested and investigated. Non-seismic details were composed of conventional channel section steel beams, and the seismic isolators were composed of high damping rubber bearing (HDRB) and wire isolator. The input acceleration time histories were artificially generated to satisfy the requirements proposed by the ICC-ES AC156 code. Based on the test results, the damage and dynamic characteristics of the UPS with the seismic isolator were investigated in terms of the natural frequency, damping ratio, acceleration time history responses, dynamic amplification factors, and relative displacements. The results from the shaking table showed that the dynamic characteristics of the UPS including the acceleration response were significantly improved when using the seismic isolator.

• Journal of The Korean Association For Science Education
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• v.44 no.2
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• pp.141-153
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• 2024

The 2022 revised science curriculum aims to develop the ability to solve scientific problems arising in daily life and society based on convergent thinking stimulated through participation in research activities using artificial intelligence (AI). Therefore, we developed a science-AI convergence education program that combines the science curriculum with artificial intelligence and employed it in convergence classes for high school students. The aim of the science-AI convergence class was for students to qualitatively understand the movement of a damped pendulum and build an AI model to predict the position of the pendulum using the block coding platform KNIME. Individual in-depth interviews were conducted to understand and interpret the learners' experiences. Based on Giorgi's phenomenological research methodology, we described the learners' learning processes and changes, challenges and limitations of the class. The students collected data and built the AI model. They expected to be able to predict the surrounding phenomena based on their experimental results and perceived the convergence class positively. On the other hand, they still perceived an with the unfamiliarity of platform, difficulty in understanding the principle of AI, and limitations of the teaching method that they had to follow, as well as limitations of the course content. Based on this, we discussed the strengths and limitations of the science-AI convergence class and made suggestions for science-AI convergence education. This study is expected to provide implications for developing science-AI convergence curricula and implementing them in the field.