• Journal of the Korean Magnetics Society
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• v.19 no.3
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• pp.113-119
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• 2009

$^{57}Fe_xCu_{1-x}O$(x = 0.0, 0.02) powders were prepared by sol-gel method and their crystallographic and magnetic hyperfine properties have been studied using X-ray diffraction and $M{\ddot{o}}ssbauer$ spectroscopy (MS). The crystal structure of the samples is found to be monoclinic without any secondary phases and their lattice parameters increase with increasing annealing temperature ($T_A$), which is attributed to an increase in oxygen-vacancy content. MS measurements at room temperature indicate that $Fe^{3+}$ ions substitute $Cu^{2+}$ sites and ferromagnetic phase grow with increasing $T_A$. Magnetic hyperfine and quadrupole interactions of $^{57}Fe_{0.02}Cu_{0.98}O$ ($T_A=500^{\circ}C$) in the antiferromagnetic state at 17 K have been studied, yielding the following results: $H_{hf}=426.94\;kOe$, ${\Delta}E_Q=-3.67\;mm/s$, I.S.=0.32 mm/s, ${\theta}=65^{\circ}$, ${\phi}=0^{\circ}$, and ${\eta}=0.6$.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.2
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• pp.44-50
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• 2010

Recently, the crude oil price per one barrel in 2005 cost 49.4 dollars. But the value of crude oil in 2007 had ascended 68.4 dollars which was skyrocketed 38.5[%] owing to the sudden rise of energy price. As it has been growing the necessity of energy efficiency, energy intentive companies actively try to implement energy management system It has been studied to improve the energy saving for household sector using the smart metering system which can give the information of energy prices, pattern on real time to energy consumers and voluntarily lead the activities of energy saving. In this paper, we estimated potential benefits and value of smart metering system through california test.

• Journal of IKEEE
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• v.23 no.4
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• pp.1302-1308
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• 2019

This paper presents an approach for classifying image made by acquired position data from a 2D Lidar sensor with a convolutional neural network (CNN). Lidar sensor has been widely used for unmanned devices owing to advantages in term of data accuracy, robustness against geometry distortion and light variations. A CNN algorithm consists of one or more convolutional and pooling layers and has shown a satisfactory performance for image classification. In this paper, different types of CNN architectures based on training methods, Gradient Descent(GD) and Levenberg-arquardt(LM), are implemented. The LM method has two types based on the frequency of approximating Hessian matrix, one of the factors to update training parameters. Simulation results of the LM algorithms show better classification performance of the image data than that of the GD algorithm. In addition, the LM algorithm with more frequent Hessian matrix approximation shows a smaller error than the other type of LM algorithm.

• The Transactions of the Korean Institute of Power Electronics
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• v.2 no.1
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• pp.33-38
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• 1997

Generally, various semiconductor switching devices for power systems are used in battery chargers for electric vehicle. When these used, it takes the problems of transient-current or distortion of waveforms in power systems near by battery chargers because of harmonics and large peak-current, low power factor, etc., caused by the non-linearity of these devices. Recently, power factor control, line current peak-cut, harmonics reduction which was ignored in past is more and more important. In this paper, to solve those problems we will improve the characteristics of voltage rising and propose the high power factor converter circuit for battery chargers. Our proposed system convert commutated voltage to AC resonant wave in high frequency inverter and rectify the link voltages passed high-frequency transformer and transfer the DC voltages. Especially, the effect using these converter system can be improved very large by power factor control and we have to verify the possibilities of improvement through the experiment of Pb-Acid battery application.

• Geophysics and Geophysical Exploration
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• v.16 no.3
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• pp.154-162
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• 2013

Vertical electrical sounding and 2D electrical resistivity survey were applied for evaluating the characteristics of alluvial layers at a groundwater artificial recharge site. The fine particles in alluvial layer, main target layer of groundwater artificial recharge, may cause clogging phenomena. In this case, electrical resistivity method is an effective technique to verify the spatial distribution of low-resistivity layers, such as saturated silts and clays. On the other hand, much attention should be paid to interpret the resistivity data in unconsolidated layers, because thick clayey overburden sometimes produces a masking effect on underlying interbedded resistive sands and gravels. Considering these points, we designed 35 points arranged in a grid form for vertical electrical sounding and 10 lines for 2D electrical resistivity survey, and concentrated our effort on enhancing the vertical and horizontal resolution of resistivity images. According to the results, 15 meters thick layers consisting of sands and gravels are located in 30 meters below ground. And the spatial distribution of silts and clays are mapped, which may cause clogging. Consequently, this approach can contribute to design and determine the location and depth of injection and observation wells for groundwater artificial recharge.

• Geophysics and Geophysical Exploration
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• v.22 no.3
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• pp.99-106
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• 2019

Resistivity method has been used for the dam safety inspection and, for the convenience of fieldwork, two-dimensional (2D) resistivity data has been usually measured along the dam crest. However, since the dam has three-dimensional (3D) structure, 2D resistivity survey along the dam crest violates 2D assumption and 3D effects caused by 3D topography and material properties in the dam distort the inversion result of 2D resistivity data acquired along the dam crest. Furthermore, it is really hard to evaluate the 3D structure of the dam and 3D leakage pathway using 2D resistivity survey because 2D resistivity survey can provide only 2D resistivity section beneath the survey line. In this study, 3D resistivity survey was conducted at a dam in Korea. By comparing the results from 3D and 2D resistivity surveys, merit and demerits of 3D survey were investigated. Finally, it was confirmed that 3D survey can provide more accurate information about the dam status and 3D leakage pathway compared to the 2D survey. Therefore the 3D resistivity survey should be actively expanded for more accurate dam safety inspection even though more time and expense are required.

• Journal of IKEEE
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• v.27 no.4
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• pp.464-471
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• 2023

In this paper, we propose a method to reduce age distortion in facial expression image generation using StyleGAN Encoder. The facial expression image generation process first creates a face image using StyleGAN Encoder, and changes the expression by applying the learned boundary to the latent vector using SVM. However, when learning the boundary of a smiling expression, age distortion occurs due to changes in facial expression. The smile boundary created in SVM learning for smiling expressions includes wrinkles caused by changes in facial expressions as learning elements, and it is determined that age characteristics were also learned. To solve this problem, the proposed method calculates the correlation coefficient between the smile boundary and the age boundary and uses this to introduce a method of adjusting the age boundary at the smile boundary in proportion to the correlation coefficient. To confirm the effectiveness of the proposed method, the results of an experiment using the FFHQ dataset, a publicly available standard face dataset, and measuring the FID score are as follows. In the smile image, compared to the existing method, the FID score of the smile image generated by the ground truth and the proposed method was improved by about 0.46. In addition, compared to the existing method in the smile image, the FID score of the image generated by StyleGAN Encoder and the smile image generated by the proposed method improved by about 1.031. In non-smile images, compared to the existing method, the FID score of the non-smile image generated by the ground truth and the method proposed in this paper was improved by about 2.25. In addition, compared to the existing method in non-smile images, it was confirmed that the FID score of the image generated by StyleGAN Encoder and the non-smile image generated by the proposed method improved by about 1.908. Meanwhile, as a result of estimating the age of each generated facial expression image and measuring the estimated age and MSE of the image generated with StyleGAN Encoder, compared to the existing method, the proposed method has an average age of about 1.5 in smile images and about 1.63 in non-smile images. Performance was improved, proving the effectiveness of the proposed method.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.117-122
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• 2006

In the geophysical monitoring to understand the change of subsurface material properties with time, the time-invariant static subsurface model is commonly adopted to reconstruct a time-lapse image. This assumption of static model, however, can be invalid particularly when fluid migrates very quickly in highly permeable medium in the brine injection experiment. In such case, the resultant subsurface images may be severely distorted. In order to alleviate this problem, we develop a new least-squares inversion algorithm under the assumption that the subsurface model will change continuously in time. Instead of sampling a time-space model into numerous space models with a regular time interval, a few reference models in space domain at different times pre-selected are used to describe the subsurface structure continuously changing in time; the material property at a certain space coordinate are assumed to change linearly in time. Consequently, finding a space-time model can be simplified into obtaining several reference space models. In order to stabilize iterative inversion and to calculate meaningful subsurface images varying with time, the regularization along time axis is introduced assuming that the subsurface model will not change significantly during the data acquisition. The performance of the proposed algorithm is demonstrated by the numerical experiments using the synthetic data of crosshole dc resistivity tomography.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.231-234
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• 2007

The magnetic sensor using electromagnetic principle. which transfers magnatic into electric. is the electric component.It has been widely applied to the industry, university and the reseach. However there are some problems. Not only the korean domestic sensor manufacture skills are still lower then the advanced manufacture's but also production of sensor is not well organized yet. Due to cahnging excitation cvurrent, excitation freq and the rate magnetic permeability core, there sometimes would be distorted phenomena or loaded phenomena which result in limited measurment range. Therefore, the signal conversion device should support to receive undistorted and nice output. This paper focuses on both the design of signal transform circuit using inductive proximity sensor and the signal transfer equipment (Z device) which detects thickness of painted material.

• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.268-274
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• 2007

Traditional two-dimensional (2D) interpretation of magnetotelluric (MT) data utilizes only transverse magnetic (TM)-mode data, because 2D inversion of transverse electric (TE)-mode data results in spurious features when 3D structures exist in the subsurface. The application of a 3D inversion algorithm to a single MT profile can reduce contamination due to off-profile anomalies and help us to incorporate TE-mode data in the interpretation. In this study, we conduct 2D and 3D inversions of MT data observed along two lines in Jeju Island. First, we invert apparent resistivities and phases in the TM and TE modes separately. Then, we perform 2D joint inversion of both TM- and TE-mode data and 3D inversion of both Zxy- and Zyx-mode data corresponding to TE- and TM-mode data in 2D. The resistivity images derived from all four data show that the geoelectrical structure in Jeju Island is a three-layered earth with the resistive-conductive-resistive stratigraphy within a depth of 5 km. The 3D inversion does not produce clear anomalies in the reconstructed profile image, while all of 2D do. This attributed to the possibility that 2D inversion results are distorted by exiting off-profile 3D anomalies in Jeju. With 3D inversion of 2D profile MT data, we can deduce more reliable results that are not seriously distorted by off-profile 3D anomalies.