• 한국지구과학회:학술대회논문집
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• 2004.02a
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• pp.52-57
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• 2004

Korean Peninsula located between Japan and China where earthquakes frequently occur, have little geophysical observation despite its tectonic importance. This study suggests the inland conductive structures inferred from GDS data measured in Korean Peninsula and try to interpret induction arrows quantitatively with the aid of 2- and 3-D geomagnetic induction modeling. Ogcheon Belt (OCB) and Imjin River Belt (IRB) are regarded as main conductive structures in Korea Peninsula, the induction arrows for the period of 60 minutes show very weak anomaly due to sea effect, which is supported by the results of 3-modeling also. However, for the period of 10 minutes, induction arrows at YIN and ICHN show anomalous patterns considered as the effect of IRB in spite of sea effect. The results of 2-D modeling which simplify geological situations provide overall information on IRB

• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.26.1-26.1
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• 2009

Many solar, interplanetary and geomagnetic activity parameters have 11-year cycle on the average in sync with solar sunspot number. The galactic cosmic ray (GCR) intensity measured by ground Neutron Monitor (NM) is one of those parameters showing the unprecedented activity levels in the current solar minimum (2008-2009) of solar cycles 23/24. We defined abnormality as the ratio of deviation from long term mean over mean amplitude of solar cycle change. The abnormality distribution map was drawn using all the data of NM stations available online. The implications of those unprecedented levels of GCR intensities of different cutoff rigidities will be discussed.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.3
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• pp.231-238
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• 2017

In this paper, we propose a method of analyzing exercise behavior to increase health care and exercise effect in personal fitness. In this study, a user wears a band-shaped acceleration sensor, an angular velocity sensor, and a motion sensor equipped with a geomagnetic module. Using the technique presented in this paper, we analyzed the motion of three resistive exercises which is consistent with previous studies. We have acquired a technique for processing personalized exercise information from the data generated in the resistive exercise situation.

• Journal of Astronomy and Space Sciences
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• v.22 no.4
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• pp.431-440
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• 2005

Local K-index is an indicator representing local geomagnetic activity in every 3 hour. For estimation of the local K-index, a reasonable determination of solar quiet curve (undisturbed daily variation of geomagnetic field) is quiet essential. To derive the solar quiet curve, the FMI method, which is one of representative algorithms, uses horizontal components (H and D) of 3 days magnetometer data from the previous day to the next day for a specific day. However, this method is not applicable to real time forecast since it always requires the next day data. In this study, we have devised a new method to estimate local K-index in near real-time by modifying the FMI method. The new method selects a recent quiet day whose $K_p$ indices, reported by NOAA/SEC are all lower than 3, and replace the previous day and the next day data by the recent quiet day data. We estimated 2,672 local K indices from Gyeongzu magnetometer in 2003, and then compared the indices with those from the conventional FMI method. We also compared the K indices with those from Kakioka observatory. As a result, we found that (1) K indices from the new method are nearly consistent with those of the conventional FMI method with a very high correlation (R=0.96); (2) onr local K indices also have a relatively high correlation (R=0.81) with those from Kakioka station. Our results show that the new method can be used for near real-time estimation of local K indices from Gyeongzu magnetometer.

• Journal of Astronomy and Space Sciences
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• v.32 no.4
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• pp.305-310
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• 2015

In this study, we examined a morningside Pi2 pulsation, with a non-substorm signature, that occurred in very quiet geomagnetic conditions (Kp = 0) at 05:38 UT on December 8, 2012, using data obtained by Van Allen Probes A and B (VAP-A and VAP-B, respectively) and at a ground station. Using 1 sec resolution vector magnetic field data, we measured the X-component of the pulsation from the Abu Simbel ground station (L = 1.07, LT = UT +2 hr, where LT represents local time) in Egypt. At the time of the Pi2 event, Abu Simbel and VAP-A (L = 3.3) were in the morning sector (07:38 LT and 07:59 MLT, respectively, where MLT represents magnetic local time), and VAP-B was in the postmidnight sector (04:18 MLT and L = 5.7). VAP-A and VAP-B observed oscillations in the compressional magnetic field component (Bz), which were in close agreement with the X-component measurements of the Pi2 pulsation that were made at Abu Simbel. The oscillations observed by the satellites and on the ground were in phase. Thus, we concluded that the observed morningside Pi2 pulsation was caused by the cavity resonance mode rather than by ionospheric current systems.

• Journal of Astronomy and Space Sciences
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• v.19 no.2
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• pp.133-140
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• 2002

Space Physics Sensor onboard the KOMPSAT-1, which was launched at 1999, had transmitted ionospheric data during the solar maximum from June 2000 to August 2001. When the KOMPSAT-1 has passed the equatorial region, equatorial bubbles, in which the electron density abruptly decreases, had frequently been detected. Statistical analysis of the data obtained during the entire operational period shows equatorial bubbles frequently occur across the Atlantic region where the geomagnetic field strength is weak. Also, equatorial bubbles occur more frequently for lower Kp index. The results are in good agreement with the previous observations by DMSP satellites and radio experiments at the Peruvian sector The correlation between electron density and the electron temperature shows various behaviors from event to event.

• Journal of Astronomy and Space Sciences
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• v.30 no.4
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• pp.247-253
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• 2013

It has long been known that the magnetospheric particles can precipitate into the atmosphere of the Earth. In this paper we examine such precipitation of energetic electrons using the data obtained from low-altitude polar orbiting satellite observations. We analyze the precipitating electron flux data for many periods selected from a total of 84 storm events identified for 2001-2012. The analysis includes the dependence of precipitation on the Kp index and the electron energy, for which we use three energies E1 > 30 keV, E2 > 100 keV, E3 > 300 keV. We find that the precipitation is best correlated with Kp after a time delay of < 3 hours. Most importantly, the correlation with Kp is notably tighter for lower energy than for higher energy in the sense that the lower energy precipitation flux increases more rapidly with Kp than does the higher energy precipitation flux. Based on this we suggest that the Kp index reflects excitation of a wave that is responsible for scattering of preferably lower energy electrons. The role of waves of other types should become increasingly important for higher energy, for which we suggest to rely on other indicators than Kp if one can identify such an indicator.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.973-975
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• 2016

In this paper, we propose a selective extended Kalman filter based accurate pose estimation of the rigid body using a sensor fusion method. The pose of a rigid body can be estimated roughly by the Gauss-Newton method using the acceleration data and geomagnetic data, which can be refined with vision information and the gyro sensor information. However strong external interference noise makes the rough pose estimation difficult. In this paper, according to the measurement level of the external interference noise, the extended Kalman filter selectively uses mostly vision and gyro sensor information to increase the estimation credibility under strong interference noise environment.

• Journal of Platform Technology
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• v.11 no.5
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• pp.97-103
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• 2023

Unlike GPS, which is an outdoor positioning technology that is universally and uniformly used all over the world, various technologies are still being developed in the field of indoor positioning technology. In order to acquire accurate indoor location information, a standard of representative indoor positioning technology is required. Recently, indoor positioning technology is expanding into the Real Time Location Service (RTLS) area based on high-precision location data. Accordingly, a new type of indoor positioning technology is being proposed. Thanks to the development of artificial intelligence, artificial intelligence-based indoor positioning technology using wireless signal data of a smartphone is rapidly developing. At this time, in the process of collecting data necessary for artificial intelligence learning, data that is distorted or inappropriate for learning may be included, resulting in lower indoor positioning accuracy. In this study, we propose a data preprocessing technology for artificial intelligence learning to obtain improved indoor positioning results through the refinement process of the collected data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3858-3874
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• 2021

As an essential part of the urban transportation system, precise perception of the traffic flow parameters at the traffic signal intersection ensures traffic safety and fully improves the intersection's capacity. Traditional detection methods of road traffic flow parameter can be divided into the micro and the macro. The microscopic detection methods include geomagnetic induction coil technology, aerial detection technology based on the unmanned aerial vehicles (UAV) and camera video detection technology based on the fixed scene. The macroscopic detection methods include floating car data analysis technology. All the above methods have their advantages and disadvantages. Recently, indoor location methods based on wireless signals have attracted wide attention due to their applicability and low cost. This paper extends the wireless signal indoor location method to the outdoor intersection scene for traffic flow parameter estimation. In this paper, the detection scene is constructed at the intersection based on the received signal strength indication (RSSI) ranging technology extracted from the wireless signal. We extracted the RSSI data from the wireless signals sent to the road side unit (RSU) by the vehicle nodes, calibrated the RSSI ranging model, and finally obtained the traffic flow parameters of the intersection entrance road. We measured the average speed of traffic flow through multiple simulation experiments, the trajectory of traffic flow, and the spatiotemporal map at a single intersection inlet. Finally, we obtained the queue length of the inlet lane at the intersection. The simulation results of the experiment show that the RSSI ranging positioning method based on wireless signals can accurately estimate the traffic flow parameters at the intersection, which also provides a foundation for accurately estimating the traffic flow state in the future era of the Internet of Vehicles.