• 천문학회지
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• 제29권spc1호
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• pp.321-322
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• 1996

Using the data on the occurrences of the Ho: and soft X-ray flares for the time interval of January 1, 1986-May :31, 1994, we have studied the middle term(30-300days) pericities of the solar flare production during the activity cycle 22. Power analysis of the time seies of daily H$\alpha$ flare index in the northern hemisphere shows prominent periodicities at 220, 120, 109, and 92 days(see Figures l(a) and l(b)), while in the southern hemisphere, those at 267, 213, 183, 167, and 107 days are apparent, though their peaks are not so distint as those in the northern hemisphere. Periodogram of daily soft X-ray flare index also reveal the periodicities at 279, 205, 164, 117, and 91 days in the northern hemisphere, and at 266, 220, 199, 162, 120, and 100 days in the southern hemisphere. Howeer, the 155-day periodicity reported for the earlier cycles, 19, 20, and 21, could not be confirmed in our analysis. to be submitted to Solar Physics; an extended abstract.

• 천문학회보
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• 제40권1호
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• pp.84.2-84.2
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• 2015

There are probabilistic forecast models for solar flare occurrence, which can be evaluated by various skill scores (e.g. accuracy, critical success index, heidek skill score, true skill score). Since these skill scores assume that two types of forecast errors (i.e. false alarm and miss) are equal or constant, which does not take into account different situations of users, they may be unrealistic. In this study, we make an evaluation of a probabilistic flare forecast model (Lee et al. 2012) which use sunspot groups and its area changes as a proxy of flux emergence. We calculate daily solar flare probabilities from 1996 to 2014 using this model. Overall frequencies are 61.08% (C), 22.83% (M), and 5.44% (X). The maximum probabilities computed by the model are 99.9% (C), 89.39% (M), and 25.45% (X), respectively. The skill scores are computed through contingency tables as a function of forecast probability, which corresponds to the maximum skill score depending on flare class and type of a skill score. For the critical success index widely used, the probability threshold values for contingency tables are 25% (C), 20% (M), and 4% (X). We use a value score with cost/loss ratio, relative importance between the two types of forecast errors. We find that the forecast model has an effective range of cost/loss ratio for each class flare: 0.15-0.83(C), 0.11-0.51(M), and 0.04-0.17(X), also depending on a lifetime of satellite. We expect that this study would provide a guideline to determine the probability threshold for space weather forecast.

• Journal of Astronomy and Space Sciences
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• 제31권2호
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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.

• 천문학회지
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• 제29권spc1호
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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.

• 천문학회보
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• 제41권1호
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• pp.80.1-80.1
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• 2016

There are probabilistic forecast models for solar flare occurrence, which can be evaluated by various skill scores (e.g. accuracy, critical success index, heidek skill score, and true skill score). Since these skill scores assume that two types of forecast errors (i.e. false alarm and miss) are equal or constant, which does not take into account different situations of users, they may be unrealistic. In this study, we make an evaluation of a probabilistic flare forecast model [Lee et al., 2012] which use sunspot groups and its area changes as a proxy of flux emergence. We calculate daily solar flare probabilities from 2011 to 2014 using this model. The skill scores are computed through contingency tables as a function of forecast probability, which corresponds to the maximum skill score depending on flare class and type of a skill score. We use a value score with cost/loss ratio, relative importance between the two types of forecast errors. The forecast probability (y) is linearly changed with the cost/loss ratio (x) in the form of y=ax+b: a=0.88; b=0 (C), a=1.2; b=-0.05(M), a=1.29; b=-0.02(X). We find that the forecast model has an effective range of cost/loss ratio for each class flare: 0.536-0.853(C), 0.147-0.334(M), and 0.023-0.072(X). We expect that this study would provide a guideline to determine the probability threshold and the cost/loss ratio for space weather forecast.

• 천문학회지
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• 제48권5호
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• pp.257-265
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• 2015

We present results of long-term multi-wavelength polarization observations of the powerful blazar 3C 279 after its γ-ray flare on 2013 December 20. We followed up this flare with single-dish polarization observations using two 21-m telescopes of the Korean VLBI Network. Observations carried out weekly from 2013 December 25 to 2015 January 11, at 22 GHz, 43 GHz, 86 GHz simultaneously, as part of the Monitoring Of GAmma-ray Bright AGN (MOGABA) program. We measured 3C 279 total flux densities of 22–34 Jy at 22 GHz, 15–28 Jy (43 GHz), and 10–21 Jy (86 GHz), showing mild variability of ≤ 50 % over the period of our observations. The spectral index between 22 GHz and 86 GHz ranged from −0.13 to −0.36. Linear polarization angles were 27°–38°, 30°–42°, and 33°–50° at 22 GHz, 43 GHz, and 86 GHz, respectively. The degree of linear polarization was in the range of 6–12 %, and slightly decreased with time at all frequencies. We investigated Faraday rotation and depolarization of the polarized emission at 22–86 GHz, and found Faraday rotation measures (RM) of −300 to −1200 rad m⁻² between 22 GHz and 43 GHz, and −800 to −5100 rad m⁻² between 43 GHz and 86 GHz. The RM values follow a power law with a mean power law index a of 2.2, implying that the polarized emission at these frequencies travels through a Faraday screen in or near the jet. We conclude that the regions emitting polarized radio emission may be different from the region responsible for the 2013 December γ-ray flare and are maintained by the dominant magnetic field perpendicular to the direction of the radio jet at milliarcsecond scales.

• 천문학회보
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• 제42권2호
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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.

• 한국의상디자인학회지
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• 제15권2호
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• pp.77-89
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• 2013

This study investigated the formation of silhouette and hemline shape of knit flare skirts according to the properties of knit material through virtual clothing with a 3D virtual clothing system called i-Designer of Technoa, thus building a database of the property data of knit material to reduce the number of sample making steps repeated and implemented several times in the process of clothes making. The results would help to estimate a silhouette in advance, offer assistance to the development of original knit wear, and explore ways to provide basic data for the development of the knit industry of the nation. The investigator made 12 kinds of experimental clothes to the angles(width of skirt: $90^{\circ}$ and $180^{\circ}$), gauge(7G, 12G, and 15G), and grain directions(wale and bias direction) of experimental clothes for virtual clothing. The dynamic characteristics of knit skirt samples according to each gauge were measured with the KES-FB system. Draper shapes were analyzed with the sectional shape data of hemline based on i-Designer. As for the measurements of the sectional shape of hemline and the formation of silhouette, the number of nodes, the average height of node mountains and valleys, and the hemline width right and left and before and after increased at the angle of $180^{\circ}$ than $90^{\circ}$. As gauges multiplied, the number of nodes, and silhouette angle dropping. When considering grain directions, the number of nodes and silhouette index increased in the wale direction at the angle of $90^{\circ}$ with the number of nodes and silhouette angle increasing in the wale direction at the angle of $180^{\circ}$.

• 천문학회지
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• 제45권2호
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• pp.31-38
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• 2012

In this study we apply Support Vector Machine (SVM) to the prediction of geo-effective halo coronal mass ejections (CMEs). The SVM, which is one of machine learning algorithms, is used for the purpose of classification and regression analysis. We use halo and partial halo CMEs from January 1996 to April 2010 in the SOHO/LASCO CME Catalog for training and prediction. And we also use their associated X-ray flare classes to identify front-side halo CMEs (stronger than B1 class), and the Dst index to determine geo-effective halo CMEs (stronger than -50 nT). The combinations of the speed and the angular width of CMEs, and their associated X-ray classes are used for input features of the SVM. We make an attempt to find the best model by using cross-validation which is processed by changing kernel functions of the SVM and their parameters. As a result we obtain statistical parameters for the best model by using the speed of CME and its associated X-ray flare class as input features of the SVM: Accuracy=0.66, PODy=0.76, PODn=0.49, FAR=0.72, Bias=1.06, CSI=0.59, TSS=0.25. The performance of the statistical parameters by applying the SVM is much better than those from the simple classifications based on constant classifiers.

• 천문학회보
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• 제41권1호
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• pp.65.1-65.1
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• 2016

We present results of long-term multi-wavelength polarization observations of the powerful blazar 3C 279 after its ${\gamma}$-ray flare on 2013 December 20. We followed up this flare by means of single-dish polarization observations with two 21-m telescopes of the Korean VLBI Network, carried out weekly from 2013 December 25 to January 11, and at 22, 43, and 86 GHz, simultaneously. These observations were part of the Monitoring Of GAmma-ray Bright AGNs (MOGABA) program. We Measured 3C 279 total flux densities at 22, 43, and 86 GHz, showing a mild variability of a factor of ${\leq}50%$ over the period of our observations. The spectral index ranged from -0.13 to -0.36 at between 22 and 86 GHz. The degree of linear polarization was in the range of 6 ~ 12 %, and slightly decreased with time at all frequencies. We found Faraday rotation measures (RM) of -300 to $-1200rad\;m^{-2}$ between 22 and 43 GHz, and -800 to $-5100rad\;m^{-2}$ between 43 and 86 GHz. The RM values follow a power law ${\mid}RM{\mid}{\propto}{\nu}^{\alpha}$, with a mean ${\alpha}$ of 2.2, implying that the polarized emission at these frequencies travels through a Faraday screen in or near the jet. We conclude that the regions emitting polarized radio emission may be different from the region responsible for the 2013 December ${\gamma}$-ray flare, and that these regions are maintained by the dominant magnetic field perpendicular to the direction of the radio jet at milliarcsecond scales.