• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.12
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• pp.1412-1415
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• 2012

Return signals of a ground penetrating radar(GPR) for mine detection at various frequencies and soil moisture contents are analyzed in this paper. We first compute the dielectric constant, conductivity and attenuation loss based on clay loam which is Korea standard soil. The mine-detection images of GPR at various frequencies are also obtained using the finite-difference time-domain(FDTD) technique. Then, the signal-to-clutter ratio(SCR) and received power of the radar are studied. It is shown that the variable frequency channels are suitable for a GPR to detect landmines at various soil conditions.

• Geomechanics and Engineering
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• v.39 no.1
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• pp.105-113
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• 2024

Recently, electrical resistivity surveys have been used to obtain information related to underground structures including burial structure type and depth. However, various field conditions hinder understanding measured electrical resistance, and thus there is a need to understand how various geometries affect electrical resistance. This study explores the effect of geometric parameters of a structure and electrodes on electrical resistance in the framework of the finite element method. First, an electrical resistance module is developed using the generalized mesh modeling technique, and the accuracy of the module is verified by comparing the results with the analytical solution for a cylindrical electrode with conical tip. Then, 387 cases of numerical analysis including geometric parameters of a buried structure and electrodes are conducted to quantitatively estimate the detection depth under a steady-state current condition. The results show that electrical resistance is increased as (1) shallower burial depth of structure, (2) closer distance between ground electrode and structure, (3) longer horizontal electrode distance. In addition, the maximum detection depth corresponding to converged electrical resistance is deeper as (4) closer distance between ground electrode and structure, (5) shorter horizontal electrode distance. The distribution of the electric potential around the electrodes and underground structure is analyzed to provide a better understanding of the measured electrical resistance. As engineering purpose, the empirical equation is proposed to calculate maximum detection depth as first approximation.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.95-102
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• 2003

• ETRI Journal
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• v.38 no.2
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• pp.302-313
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• 2016

Use of a passive bistatic radar (PBR) system in the surveillance or monitoring of an area has its advantages. For example, a PBR system is able to utilize any available signal of opportunity (for example, broadcasting, communication, or radio navigation signals) for the purposes of surveillance. With this in mind, there are potentially many research areas to be explored; in particular, the capability of signals from existing and future communication systems, such as 4G and 5G. Long-Term Evolution (LTE) is the world's most current communication system. Given this fact, this paper presents the latest feasibility studies and experimental results from using LTE signals in PBR applications. Details are provided about aspects such as signal characteristics, experimental configurations, and SNR studies. Six experimental scenarios are carried out to investigate the detection performance of our proposed system on ground-moving targets. The ability to detect is demonstrated through use of the cross-ambiguity function. The detection results suggest that LTE signals are suitable as a source signal for PBR.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.46.2-46.2
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• 2021

We present solar event auto detection using deep-learning-based object detection algorithms and DeepSDO event dataset. DeepSDO event dataset is a new detection dataset with bounding boxed as ground-truth for three solar event (coronal holes, sunspots and prominences) features using Solar Dynamics Observatory data. To access the reliability of DeepSDO event dataset, we compared to HEK data. We train two representative object detection models, the Single Shot MultiBox Detector (SSD) and the Faster Region-based Convolutional Neural Network (R-CNN) with DeepSDO event dataset. We compared the performance of the two models for three solar events and this study demonstrates that deep learning-based object detection can successfully detect multiple types of solar events. In addition, we provide DeepSDO event dataset for further achievements event detection in solar physics.

• Korean Journal of Remote Sensing
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• v.33 no.4
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• pp.359-375
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• 2017

We developed fog detection algorithm (KNU_FDA) based on the optical and textural properties of fog using satellite (COMS) and ground observation data. The optical properties are dual channel difference (DCD: BT3.7 - BT11) and albedo, and the textural properties are normalized local standard deviation of IR1 and visible channels. Temperature difference between air temperature and BT11 is applied to discriminate the fog from other clouds. Fog detection is performed according to the solar zenith angle of pixel because of the different availability of satellite data: day, night and dawn/dusk. Post-processing is also performed to increase the probability of detection (POD), in particular, at the edge of main fog area. The fog probability is calculated by the weighted sum of threshold tests. The initial threshold and weighting values are optimized using sensitivity tests for the varying threshold values using receiver operating characteristic analysis. The validation results with ground visibility data for the validation cases showed that the performance of KNU_FDA show relatively consistent detection skills but it clearly depends on the fog types and time of day. The average POD and FAR (False Alarm Ratio) for the training and validation cases are ranged from 0.76 to 0.90 and from 0.41 to 0.63, respectively. In general, the performance is relatively good for the fog without high cloud and strong fog but that is significantly decreased for the weak fog. In order to improve the detection skills and stability, optimization of threshold and weighting values are needed through the various training cases.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.1
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• pp.19-25
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• 2010

Most faults are single-phase-to-ground fault in ungrounded system. The fault currents of single-phase-to-ground are much smaller than detection thresholds of measurement devices, so detecting single-phase-to-ground faults is difficult and important in ungrounded system. The protection coordination method using SGR(Selective Ground Relay) and OVGR(Overvoltage Ground Relay) is generally used in ungrounded system. But this method only detects fault line and it has the possibility of malfunction. This paper proposed to advanced protection coordination method in ungrounded system. The method just using zero-sequence current can detect fault line, fault phase, fault section at terminal device. The general protection method is used to back up protection. In the case study, the proposed method has been testified in demo system by Matlab/Simulink simulations.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.1274-1279
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• 2004

This paper proposes technique to detect ground fault in railway high voltage distribution lines. Overcurrent relay technique is widely used for detecting one line ground fault that occurs most frequently in railway high voltage distribution lines. However, ground fault in distribution line is usually high impedance fault with arc. Because the fault current magnitude measured in substation is very small, the conventional overcurrent relay can't detect the high impedance ground fault. Therefore this paper proposes the advanced technique using wavelet transform. It extracts D1 component from fault signals and detects fault comparing magnitude of D1 component in each phase. To evaluate this proposed technique, we model distribution system using PSCAD/EMTDC and extract various fault data. In conclusion this technique can detect ground fault including high impedance fault regardless of fault distance, fault impedance etc.

• Preventive Nutrition and Food Science
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• v.4 no.3
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• pp.171-174
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• 1999

For monitoring lipid oxidation development in cooked ground pork during refrigerationm, malonaldehydethiobarbituric acid(MA-TBA) contents were measured using high performance liquid chromatography(HPLC). As the oxidation proceeded during refergeration, TBA-reaction substances(TBARS) absorbances increased and the corresponding HPLC peak areas also increased proportationately. The correlation coefficient between the HPLC peak areas and MA-TBA absorbance were 0.9979. The treatemtn of cetrimide, an ion pairing agent, gave a complete resolution of the MA-TBA complex and the butanol extraction of the complex increased its recovery by 37.8%. Both cetrimide treatment and butanol extraction are essential steps for analyzing MA-TBA complex in ground pork wiht HPLC. A reliable and specific measurement of NA-TBA in ground pork was successfully performed using HPLC.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.69-74
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• 2011

In the curving detection method by using an accelerometer, the ride comfort in the first car is worse than one in the others due to spend the time to calculate the tilting command and drive the tilting mechanism after entering in the curve. In order to enhance the ride comfort in the first car, the preditive curve detection method which predicts the distance from a train to the starting point of curve by using the GPS, Tachometer, Ground balise and position DB for track. In this study, we predicted and evaluated the ride comfort for predictive curve detection method in transient curves according to the shape and dimension of transient curve and the various driving speed. Also, we predicted the improvement of the ride comfort for predictive curve detection method by comparing with the result of the ride comfort for predictive curve detection method and for curve detection method using an accelerometer in the short transient curve.