• 한국전자현미경학회:학술대회논문집
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• 2005.11a
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• pp.99-100
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• 2005

• Proceedings of the Korean Vacuum Society Conference
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• 1997.07a
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• pp.154-154
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• 1997

• Proceedings of the Korean Magnestics Society Conference
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• 2008.12a
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• pp.67.2-67.2
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• 2008

• Journal of the Korean Ceramic Society
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• v.48 no.2
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• pp.147-151
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• 2011

In this study, we prepared graphene by using the modified Hummers-Offeman method and then introduced the metals (Pt, Pd and Fe) for dispersion on the surface of the graphene for synthesis of metal-graphene composites. The characterization of the prepared graphene and metal-graphene composites was performed by X-ray diffraction (XRD), scanning electron microscopy (SEM) with energy dispersive X-ray (EDX) analysis and transmission electron microscopy (TEM). According to the results, it can be observed that the prepared graphene consists of thin stacked flakes of shapes having a well-defined multilayered structure at the edge. And the metal particles are dispersed uniformly on the surface of the graphene with an average particle size of 20 nm.

• Proceedings of the Microbiological Society of Korea Conference
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• 2005.05a
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• pp.187.1-187
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• 2005

• Kyungpook Mathematical Journal
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• v.18 no.1
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• pp.85-89
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• 1978

In this paper locally uniform spaces have been characterized through covers. It has been shown that both the approaches are equivalent.

• Proceedings of the Korean Vacuum Society Conference
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• 1996.02a
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• pp.168-168
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• 1996

• Bulletin of the Korean Chemical Society
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• v.14 no.2
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• pp.295-297
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• 1993

• Proceedings of the Korean Vacuum Society Conference
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• 2004.08a
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• pp.227-227
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• 2004

• International Journal of Aeronautical and Space Sciences
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• v.13 no.4
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• pp.491-498
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• 2012

A Ground Based Augmentation System (GBAS) is an enabling technology for an aircraft's precision approach based on a Global Navigation Satellite System (GNSS). However, GBAS is vulnerable to interference, so effective GNSS interference detection and mitigation methods need to be employed. In this paper, an intentional GNSS interference detection and characterization algorithm is proposed. The algorithm uses Automatic Gain Control (AGC) gain and adaptive notch filter parameters to classify types of incoming interference and to characterize them. The AGC gain and adaptive lattice IIR notch filter parameter values in GNSS receivers are examined according to interference types and power levels. Based on those data, the interference detection and characterization algorithm is developed and Monte Carlo simulations are carried out for performance analysis of the proposed method. Here, the proposed algorithm is used to detect and characterize single-tone continuous wave interference, swept continuous wave interference, and band-limited white Gaussian noise. The algorithm can be used for GNSS interference monitoring in an excessive Radio Frequency Interference environment which causes loss of receiver tracking. This interference detection and characterization algorithm will be used to enhance the interference mitigation algorithm.