• Journal of Astronomy and Space Sciences
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• v.34 no.2
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• pp.105-110
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• 2017

Solar wind density depletions are phenomena that solar wind density is rapidly decreased and keep the state. They are generally believed to be caused by the interplanetary (IP) shocks. However, there are other cases that are hardly associated with IP shocks. We set up a hypothesis for this phenomenon and analyze this study. We have collected the solar wind parameters such as density, speed and interplanetary magnetic field (IMF) data related to the solar wind density depletion events during the period from 1996 to 2013 that are obtained with the advanced composition explorer (ACE) and the Wind satellite. We also calculate two pressures (magnetic, dynamic) and analyze the relation with density depletion. As a result, we found total 53 events and the most these phenomena's sources caused by IP shock are interplanetary coronal mass ejection (ICME). We also found that solar wind density depletions are scarcely related with IP shock's parameters. The solar wind density is correlated with solar wind dynamic pressure within density depletion. However, the solar wind density has an little anti-correlation with IMF strength during all events of solar wind density depletion, regardless of the presence of IP shocks. Additionally, In 47 events of IP shocks, we find 6 events that show a feature of blast wave. The quantities of IP shocks are weaker than blast wave from the Sun, they are declined in a short time after increasing rapidly. We thus argue that IMF strength or dynamic pressure are an important factor in understanding the nature of solar wind density depletion. Since IMF strength and solar wind speed varies with solar cycle, we will also investigate the characteristics of solar wind density depletion events in different phases of solar cycle as an additional clue to their physical nature.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.2
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• pp.51.2-51.2
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• 2010

We have investigated 63 intense geomagnetic storms (Dst $\leq$ -100 nT) that occurred from 1998 to 2006. Using these events, we compared Dst forecast models: Burton et al. (1975), Fenrich and Luhmann (1998), O'Brien and McPherron (2000a), Wang et al. (2003), and Temerin and Li (2002, 2006) models. For comparison, we examined a linear correlation coefficient, RMS error, the difference of Dst minimum value (${\Delta}$peak), and the difference of Dst minimum time (${\Delta}$peak_time) between the observed and the predicted during geomagnetic storm period. As a result, we found that Temerin and Li model is mostly much better than other models. The model produces a linear correlation coefficient of 0.94, a RMS (Root Mean Square) error of 14.89 nT, a MAD (Mean Absolute Deviation) of ${\Delta}$peak of 12.54 nT, and a MAD of ${\Delta}$peak_time of 1.44 hour. Also, we classified storm events as five groups according to their interplanetary origin structures: 17 sMC events (IP shock and MC), 18 SH events (sheath field), 10 SH+MC events (Sheath field and MC), 8 CIR events, and 10 nonMC events (non-MC type ICME). We found that Temerin and Li model is also best for all structures. The RMS error and MAD of ${\Delta}$peak of their model depend on their associated interplanetary structures like; 19.1 nT and 16.7 nT for sMC, 12.5 nT and 7.8 nT for SH, 17.6 nT and 15.8 nT for SH+MC, 11.8 nT and 8.6 nT for CIR, and 11.9 nT and 10.5 nT for nonMC. One interesting thing is that MC-associated storms produce larger errors than the other-associated ones. Especially, the values of RMS error and MAD of ${\Delta}$peak of SH structure of Temerin and Li model are very lower than those of other models.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.70.2-70.2
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• 2014

We developed a three-dimensional (3D) magnetohydrodynamic (MHD) simulation code to reproduce the structure of a solar wind and the propagation of a coronal mass ejection (CME) through it. This code is constructed by a finite volume method based on a total variation diminishing (TVD) scheme using an unstructured grid system (Tanaka 1994). The grid system can avoid the singularity arising in the spherical coordinate system. In this study, we made an improvement of the code focused on the propagation of a CME through a solar wind, which extends a previous work done by Nakamizo et al. (2009). We first reconstructed a solar wind in a steady state from physical values obtained at 50 solar radii away from the Sun via an MHD tomography applied to interplanetary scintillation (IPS) data (Hayashi et al. 2003). We selected CR2057 and inserted a spheromak-type CME (Kataoka et al. 2009) into a reconstructed solar wind. As a result, we found that our simulation well captures the velocity, temperature and density profiles of an observed solar wind. Furthermore, we successfully reproduce the general characteristics of an interplanetary coronal mass ejection (ICME) obtained by the Helios 1/2 spacecraft (R. J. FORSYTH et al. 2006).

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.132.2-132.2
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• 2012

We have investigated the characteristics of magnetic cloud (MC) and ejecta (EJ) associated coronal mass ejections (CMEs) based on the assumption that all CMEs have a flux rope structure. For this, we used 54 CMEs and their interplanetary counter parts (interplanetary CMEs: ICMEs) that constitute the list of events used by the NASA/LWS Coordinated Data Analysis Workshop (CDAW) on CME flux ropes. We considered the location, angular width, and speed as well as the direction parameter, D. The direction parameter quantifies the degree of asymmetry of the CME shape, and shows how closely the CME propagation is directed to Earth. For the 54 CDAW events, we found several properties of the CMEs as follows: (1) the average value of D for the 23 MCs (0.62) is larger than that for the 31 EJs (0.49), which indicates that the MC-associated CMEs propagate more directly to the Earth than the EJ-associated CMEs; (2) comparison between the direction parameter and the source location shows that the majority of the MC-associated CMEs are ejected along the radial direction, while many of the EJ-associated CMEs are ejected non-radially; (3) the mean speed of MC-associated CMEs (946 km/s) is faster than that of EJ-associated CMEs (771 km/s). For seven very fast CMEs (>1500 km/s), all CMEs with large D (>0.4) are associated with MCs and the CMEs with small D are associated with EJs. From the statistical analysis of CME parameters, we found the superiority of the direction parameter. Based on these results, we suggest that the CME trajectory essentially decides the observed ICME structure.

• Bulletin of the Korean Space Science Society
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• 2010.04a
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• pp.39.1-39.1
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• 2010

We have investigated interplanetary (IP) structures of 82 intense geomagnetic storms (Dst $\leq$ -100 nT) that occurred from 1998 to 2006. According to their interplanetary origins, we classified them as four groups: 20 sMC events (IP shock and MC), 19 SH events (sheath field), 12 SH+MC events (Sheath field and MC), and 8 nonMC events (non-MC type ICME). For each group, we examined the relationships between Dst index and solar/IP parameters, namely, direction parameter (DP), CME speed ($V_{CME}$), solar wind speed ($V_{SW}$), minimum of IMF $B_z$ component($Bz_{min}$), and maximum of $E_y$ component ($Ey_{max}$).We found that the relationships strongly depend on their IP source. Our main results can be summarized as follows: 1) The correlation between Dst and DP is the best for the SH+MC events (r = -0.61). 2) The relationship between Dst and $V_{CME}$ gives the best correlation for the sMC events (r = -0.56). 3) There is the best correlation between Dst and $V_{SW}$ for the sMC events (r = -0.61), while there is a very weak correlation (r=-0.17) for the SH events. 4) The relationship between Dst and $Bz_{min}$ gives the best correlation (r = -0.87) for the SH+MC events. 5) The correlation between Dst and $Ey_{max}$ is the best for the SH+MC events (r = -0.87). Summing up, the sMC and SH+MC events give us good correlations, but the SH events, weak correlations. From this study, we suggest that this tendency should be caused by the characteristics of IMF southward components, e.g., smooth field rotations for the MC events and highly IMF fluctuations for the SH events.

• Communications of Mathematical Education
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• v.23 no.4
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• pp.1023-1041
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• 2009

The importance of the mathematical education on the ICT environment has been increased as the educational environment has been changed in 21st century. In Korea, many researches on ICT tools have appeared over the last 10 years. But most of researches are depending on the foreign tools, that was one major obstacle on adapting them in our mathematics curriculum. But we found the new open source tool which is called Sage-Math can be in effective solution to resolve those problems. Now we produce what we have done in linear algebra with this Sage-Math and mobile modules.

• Journal of the Korean School Mathematics Society
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• v.14 no.4
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• pp.423-442
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• 2011

The purpose of this study was to examine the effects of tasks setting for mathematical modelling in the complex real situations. The tasks setting(MMa, MeA) in mathematical modelling was so important that we can't ignore its effects to develop meaning and integrate mathematical ideas. The experimental setting were two groups ($N_1=103$, $N_2=103$) at public high school and non-experimental setting was one group($N_3=103$). In mathematical achievement, we found meaningful improvement for MeA group on modelling tasks, but no meaningful effect on information processing tasks. The statistical method used was ACONOVA analysis. Beside their achievement, we were much concerned about their modelling approach that TSG21 had suggested in Category "Educational & cognitive Midelling". Subjects who involved in experimental works showed very interesting approach as Exploration, analysis in some situation ${\Rightarrow}$ Math. questions ${\Rightarrow}$ Setting models ${\Rightarrow}$ Problem solution ${\Rightarrow}$ Extension, generalization, but MeA group spent a lot of time on step: Exploration, analysis and MMa group on step, Setting models. Both groups integrated actively many heuristics that schoenfeld defined. Specially, Drawing and Modified Simple Strategy were the most powerful on approach step 1,2,3. It was very encouraging that those experimental setting was improved positively more than the non-experimental setting on mathematical belief and interest. In our school system, teaching math. modelling could be a answer about what kind of educational action or environment we should provide for them. That is, mathematical learning.