• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.361-369
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• 2019

With the commercialization of the ADAS functions, the need for the experience of the autonomous driving system is increasing, and the role of the artificial intelligence agent is attracting attention. This study is an autonomous driving experience experiment that verifies the effect of self-efficacy and agent embodiment. Through a simulator experiment, we measured the effect of existence of self-efficacy and agent embodiment on social presence, perceived risk, and perceived ease of use. Results show that self-efficacy had a positive effect on social presence and perceived risk, and agent embodiment negatively affected perceived ease of use. Based on the results of the study, we proposed guidelines for agent design that can increase the acceptance of the semi-autonomous driving system.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.266-270
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• 2018

원자력 방사능 폐기물 또는 원자력 발전소 해체시 발생 가능한 세슘 이온은 인체뿐만 아니라 생태계 환경에도 큰 악영향을 미친다고 알려져 있다. 이러한 세슘 이온은 자연 속으로 손쉽게 스며들어 발생한 지역뿐만 아니라 쉽게 퍼지게 되어 넓은 지역까지 피해를 주게 되며, 반감기가 30년으로써 한번 자연계에 누출되면 장시간 잔존하여 인간 및 생태계에 악영향을 미치게 된다. 세슘이온이 몸속에 들어오게 되면 장에서 몸으로 100% 흡수되며 내장에 축척되어 연조직 전체에 분포하게 되며 갑상선 암과 같은 심각한 위험에 초래하게 된다. 2011년 발생한 후쿠시마 원전 사고 이후 국내에서도 많은 관심을 가지기 시작하였으며, 따라서 수중의 세슘이온을 제거하기 위하여 나노 입자 형태의 기능성을 가진 물질들을 적용한 많은 연구가 이루어지고 있다. 이러한 나노물질들은 수중의 세슘이온 제거에 대하여 우수한 제거효율을 보여주고 있으나 나노 입자 특성상 사용 이후 회수가 어려워 기능성 물질들의 확산 및 축적에 따른 2차 환경오염의 문제점까지 발생하게 된다. 최근 수처리 분야에서 외부 자기장을 주게 되면 자성을 띄게 되는 물질인 자성체에 대한 관심이 급등하고 있다. 이러한 자성체들은 수중에서 별도의 회수 시스템 없이 자성으로 인하여 완벽히 자기분리 된다. 세슘제거에 탁월한 기능성 물질과 완벽한 자기분리가 가능한 자성체를 결합하여 특별한 회수장치 없이 외부 자기장만 주어진다면 수중의 세슘을 효과적으로 제거 또는 처리할 수 있다. 자성체 입자 표면에 흡착제인 프러시안 블루나 제올라이트와 같은 흡착제를 합성하여 수중의 세슘을 제거하는 연구가 활발히 이루어지고 있다. 그러나 기존의 자성체보다 좀 더 높은 자성을 가지고 있으며 외부 자기장에 의해 강하게 반응을 한다고 알려져 있는 강자성체(Ferromagnetic)를 사용하게 된다면 흡착제와 결합 이후 더욱더 강한 자성을 가진 흡착제가 탄생하며 이를 사용하면 높은 처리율뿐만 아니라 높은 슬러지 회수율을 가질 수 있다. 따라서 본 연구는 흡착제나 이온교환수지와 같은 기능성 물질을 사용하여 수중의 세슘을 제거하는 메커니즘과 강자성체가 가지고 있는 강한 자성의 성질을 결합한 복합체 제조에 대한 연구조사를 중점적으로 실시하였다. 본 연구에 의해 연구 조사된 결과를 바탕으로 수중의 세슘 이온에 대하여 높은 제거효율과 회수율을 가지는 새로운 형태의 복합체 제조에 관한 정보를 제공하고자 한다.

• Journal of The Korean Association of Information Education
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• v.25 no.3
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• pp.579-590
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• 2021

This study examined the mediating effect of learning engagement in the relationship between self-regulation, teaching presence and computational thinking in online SW education. To verify the research problem, a blended learning model adopted SW liberal course at A Women's University located in Seoul, which 94 students were enrolled in, was selected. The results of this study and the implications are as follows: First, it was found that learning engagement mediated the relationship between self-regulation and computational thinking. Second, it was found that learning engagement mediated the relationship between teaching presence and computational thinking. This study suggested a plan to improve learners' active engagement and self-regulation strategy in online SW education. In addition, it is significant that this study considered a method for learners to perceive teaching presence in online learning environment.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.27-40
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• 2022

Medical AI, which has lately made significant advances, is playing a vital role, such as assisting clinicians with diagnosis and decision-making. The field of chest X-rays, in particular, is attracting a lot of attention since it is important for accessibility and identification of chest diseases, as well as the current COVID-19 pandemic. However, despite the vast amount of data, there remains a limit to developing an effective AI model due to a lack of labeled data. A research that used federated learning on chest X-ray data to lessen this difficulty has emerged, although it still has the following limitations. 1) It does not consider the problems that may occur in the Non-IID environment. 2) Even in the federated learning environment, there is still a shortage of labeled data of clients. We propose a method to solve the above problems by using the self-supervised learning model as a global model of federated learning. To that aim, we investigate a self-supervised learning methods suited for federated learning using chest X-ray data and demonstrate the benefits of adopting the self-supervised learning model for federated learning.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.2D
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• pp.295-303
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• 2009

The purpose of present study is to examine the effect of guideway characteristics on runnability of low and medium speed maglev vehicle. Dynamic governing equation for 2-dof vehicle and optimal feedback control scheme are developed. And then the effect of vehicle speed, rail roughness, guideway deflection, continuity of spans, each span length on dynamic response of the UTM-01 maglev vehicle are investigated. From the numerical simulation, it is found that the gap between bogie and guideway does not increase greatly within design velocity of the vehicle. The response of vehicle are mostly affected by the guideway deflection rather than rail roughness. As a result of the present study, the runnability of maglev vehicle can be improved by reducing the maximum deflection of guideway and adopting the continuous girder systems.

• Bulletin of the Korean Space Science Society
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• 1994.09a
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• pp.52-52
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• 1994

• Proceedings of KHEA Conference
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• 2004.10a
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• pp.184-184
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• 2004

• The Science & Technology
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• v.25 no.10 s.281
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• pp.51-53
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• 1992

• 베이커리
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• no.11 s.352
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• pp.66-69
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• 1997

• Investigative Magnetic Resonance Imaging
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• v.12 no.2
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• pp.123-130
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• 2008

Purpose : Motion effects in parallel magnetic resonance imaging (MRI) are investigated. Parallel MRI is known to be robust to motion due to its reduced acquisition time. However, if there are some involuntary motions such as heart or respiratory motions involved during the acquisition of the parallel MRI, motion artifacts would be even worse than those in conventional (non-parallel) MRI. In this paper, we defined several types of motions, and their effects in parallel MRI are investigated in comparisons with conventional MRI. Materials and Methods : In order to investigate motion effects in parallel MRI, 5 types of motions are considered. Type-1 and 2 are periodic motions with different amplitudes and periods. Type-3 and 4 are segment-based linear motions, where they are stationary during the segment. Type-5 is a uniform random motion. For the simulation, Cartesian and spiral grid based parallel and non-parallel (conventional) MRI are used. Results : Based on the motions defined, moving artifacts in the parallel and non-parallel MRI are investigated. From the simulation, non-parallel MRI shows smaller root mean square error (RMSE) values than the parallel MRI for the periodic (type-1 and 2) motions. Parallel MRI shows less motion artifacts for linear(type-3 and 4) motions where motions are reduced with shorter acquisition time. Similar motion artifacts are observed for the random motion (type-5). Conclusion : In this paper, we simulate the motion effects in parallel MRI. Parallel MRI is effective in the reduction of motion artifacts when motion is reduced by the shorter acquisition time. However, conventional MRI shows better image quality than the parallel MRI when fast periodic motions are involved.