• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.429-432
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• 2015

We present a kinematic study of the parsec-scale radio jet in OJ 287, one of the most studied BL Lac objects, during ${\gamma}$-ray flares, to explore the relation between parsec-scale radio jet activity and ${\gamma}$-ray emission. The 22-GHz light curve of OJ 287 show three obvious flare events around 2011 May, 2011 October, and 2012 March. The second radio flare occurred during the ${\gamma}$-ray flaring period, and the third radio flare seemed to precede the ${\gamma}$-ray flare by one month. One jet component moved outward with respect to the core component with an apparent superluminal speed (~ 11c) from 2010 November to 2011 November. Then it changed direction, moving apparently inward in 2011 November, when the ${\gamma}$-ray flare occurred. The observed apparent inward motion of the jet at 22 GHz could be caused by a new jet component, unresolved at 22 GHz, in the innermost region.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.2
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• pp.46.2-46.2
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• 2018

The active region NOAA AR 12673 is the most flare productive active region in the solar cycle 24. On 2017 September 07, it produced an X1.3 flare, three M-class, and several C-class flares. We successfully observed several C-class flares from 16:50 UT to 22:00 UT using the 1.6m Goode Solar Telescope (GST; formerly NST) at Big Bear Solar Observatory (BBSO). The GST provides us with unprecedented high-resolution data of the Sun since 2009. Interestingly, we observed the active region in He I D3 and 10830 lines simultaneously. The data shows several interesting features: (1) D3 emission seems to be much weaker than 10830 emission around 21:29 UT; (2) a small loop seen in 10830 is moving upward and is brightened around 21:16 UT, but it is not clear in D3; (3) there are waves in the penumbra seen in 10830 line center; (4) there is a jet with twisting motion. In this presentation, we will give the results of our analysis and interpretations.

• Bulletin of the Korean Space Science Society
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• 1999.09a
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• pp.85-85
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• 1999

No Abstract, See Full Text

• Bulletin of the Korean Space Science Society
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• 2008.04a
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• pp.24.3-24.3
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• 2008

• Journal of The Korean Astronomical Society
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• v.29 no.spc1
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• pp.315-316
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• 1996

Based on X-ray (1-8 ${\AA}$) flux data for 1972-1995 the integral spectra of solar flare energy were computed. It has been shown that the spectral index $\beta$ of the integral energy spectrum (IES) vanes systematically with the 11-year cycle phase. The interval of $\beta$-variations (0.47 <$\beta$<1) is characteristic of UV-Cet stars. The maximum energy of the X-ray flares does not exceed $10^{32}$ erg.

• Journal of The Korean Astronomical Society
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• v.29 no.spc1
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• pp.331-332
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• 1996

We present 3 rare subtypes of the FFSs observed with high temporal resolution at 4-frequency (1.42, 2.13, 2.84 and 4.2G GHz). The various FFSs occurred during the main and post-flare phase can demonstrate that coronal nonthermal electron acceleration/injection may go through the whole development process of flares, and deduce that there may exist the re-forming of loop-like structures in the post-flare phase, and the complex multi-type magnetic structures in corona.

• The Bulletin of The Korean Astronomical Society
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• v.33 no.2
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• pp.36.1-36.1
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• 2008

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.51.2-51.2
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• 2019

As one of the Korean VLBI Network (KVN) Key Science Programs, the Interferometric Monitoring of Gamma-ray Bright AGNs (iMOGABA) aims to reveal the origins and nature of the gamma ray flares in active galactic nuclei (AGNi). Here we report a summary of activities and recent scientific results of the iMOGABA program, including statistical properties of the whole sample, as well as scientific highlights for the iMOGABA on specific sources. We also introduce future prospects and directions for the development and expansion of iMOGABA.

• Journal of Astronomy and Space Sciences
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• v.31 no.2
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• pp.145-148
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• 2014

There was a research on the prolongation of solar cycle 23 by the solar cyclic variation of solar, interplanetary geomagnetic parameters by Oh & Kim (2013). They also suggested that the sunspot number cannot typically explain the variation of total solar irradiance any more. Instead of the sunspot number, a new index is introduced to explain the degree of solar activity. We have analyzed the frequency of sunspot appearance, the length of solar cycle, and the rise time to a solar maximum as the characteristics of solar cycle. Then, we have examined the predictability of solar activity by the characteristics of preceding solar cycle. We have also investigated the hemispheric variation of flare index for the periods that the leading sunspot has the same magnetic polarity. As a result, it was found that there was a good correlation between the length of preceding solar cycle and spotless days. When the length of preceding solar cycle gets longer, the spotless days increase. It is also shown that the shorter rise time to a solar maximum is highly correlated with the increase of sunspots at a solar maximum. Therefore, the appearance frequency of spotless days and the length of solar cycle are more significant than the general sunspot number as an index of declining solar activity. Additionally, the activity of flares leads in the northern hemisphere and is stronger in the hemisphere with leading sunspots in positive polarity than in the hemisphere with leading sunspots in negative polarity. This result suggests that it is necessary to analyze the magnetic polarity's effect on the flares and to interpret the period from the solar maximum to solar maximum as the definition of solar cycle.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.2
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• pp.61.1-61.1
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• 2017

As the application of deep-learning methods has been succeeded in various fields, they have a high potential to be applied to space weather forecasting. Convolutional neural network, one of deep learning methods, is specialized in image recognition. In this study, we apply the AlexNet architecture, which is a winner of Imagenet Large Scale Virtual Recognition Challenge (ILSVRC) 2012, to the forecast of daily solar flare occurrence using the MatConvNet software of MATLAB. Our input images are SOHO/MDI, EIT $195{\AA}$, and $304{\AA}$ from January 1996 to December 2010, and output ones are yes or no of flare occurrence. We consider other input images which consist of last two images and their difference image. We select training dataset from Jan 1996 to Dec 2000 and from Jan 2003 to Dec 2008. Testing dataset is chosen from Jan 2001 to Dec 2002 and from Jan 2009 to Dec 2010 in order to consider the solar cycle effect. In training dataset, we randomly select one fifth of training data for validation dataset to avoid the over-fitting problem. Our model successfully forecasts the flare occurrence with about 0.90 probability of detection (POD) for common flares (C-, M-, and X-class). While POD of major flares (M- and X-class) forecasting is 0.96, false alarm rate (FAR) also scores relatively high(0.60). We also present several statistical parameters such as critical success index (CSI) and true skill statistics (TSS). All statistical parameters do not strongly depend on the number of input data sets. Our model can immediately be applied to automatic forecasting service when image data are available.