• Proceedings of the Korean Magnestics Society Conference
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• 2007.05a
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• pp.118.2-118.2
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• 2007

• 한국초전도학회:학술대회논문집
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• v.13
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• pp.53-53
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• 2003

• 한국초전도학회:학술대회논문집
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• 2009.07a
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• pp.45-45
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• 2009

• Proceedings of the Korean Vacuum Society Conference
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• 1998.02a
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• pp.165-165
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• 1998

• Proceedings of the Korean Vacuum Society Conference
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• 1998.02a
• /
• pp.183-183
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• 1998

• 한국초전도학회:학술대회논문집
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• v.12
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• pp.40-40
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• 2002

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.448-449
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• 2007

The PMMA plates with periodic ~200 nm nanosized patterned array were fabricated through the nanoimprint technique with their proper Ni stamper. The computer coding was also made with the Mathematica language software via RCWA (Rigorous Continuous Wave Analysis) and it is confirmed that simulation results are in good agreement with the experimental ones.

• Journal of IKEEE
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• v.20 no.1
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• pp.94-102
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• 2016

This paper proposes a new prediction method to reduce times and labor of repetitive multi-physics simulation. To achieve exact results from the whole simulation processes, complex modeling and huge amounts of time are required. Current multi-physics analysis focuses on the simulation method itself and the simulation environment to reduce times and labor. However this paper proposes an alternative way to reduce simulation times and labor by exploiting machine learning algorithm trained with data set from simulation results. Through comparing each machine learning algorithm, Gaussian Process Regression showed the best performance with under 100 training data and how similar results can be achieved through machine-learning without a complex simulation process. Given trained machine learning algorithm, it's possible to predict the result after changing some features of the simulation model just in a few second. This new method will be helpful to effectively reduce simulation times and labor because it can predict the results before more simulation.

• Proceedings of the Korean Magnestics Society Conference
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• 2017.05a
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• pp.92-92
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• 2017

• Progress in Superconductivity and Cryogenics
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• v.5 no.1
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• pp.44-47
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• 2003

There are several simulation programs in studying superconductor RSFQ (Rapid Single flux Quantum) electronic devices, which include WRspice, WinS, PSCAN, and JSIM. Even though different research groups use different simulation programs, it is not well known about which program gives the simulation results closer to the measurement values. In this work, we used both WRspice and WinS to simulate RSFQ OR gate and to compare the results from the different simulations. This comparison would help in deciding which program is better in the RSFQ circuit design. In the confluence buffer, which is the one of the main components of the DR gate, the measured bias margins were ${\times}23.2%$, while the margins from the simulations were ${\pm}35.56%$ from WRspice and it 53.1% from WinS. However, with the actual fabricated circuit parameters WRspice gave ${\pm}27%$. In WinS the circuit did not operate. We concluded that WRspice is more reliable.