• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.3
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• pp.319-324
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• 2013

In this study, an EP (electro-polishing)-MAP (magnetic abrasive polishing) hybrid process was developed as a precision finishing process. To evaluate the characteristics of this EP-MAP hybrid process, a series of experiments were carried out using various working gaps, current densities, and electrolyte concentrations. As a result, $NaNO_3$ was found to be very suitable as the electrolyte of the hybrid process because there was no electrochemical reaction with the CNT-Co composite. Moreover, an increase in the magnetic flux density affected the liquidity of the electrolyte and prevented it from flowing into the CNT-Co composite powder. For that reason, the lower liquidity of the electrolyte increased the thermal energy on the surface of the workpiece.

• Explosives and Blasting
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• v.34 no.4
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• pp.28-34
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• 2016

Empirical model, phenomenological model, and CFD model have been used to evaluate the blast effects produced by explosion of explosives, flammable gas and liquid or dust. TNT equivalence method which is one of empirical models has been widely used as it is simple. In this study, new peak overpressure-scaled distance and scaled impulse-scaled distance equations are induced through fitting data from the curves given by TNT equivalence method. If the TNT equivalent mass is calculated, it is possible to estimate the peak overpressure and impulse using the regression equations. Differences of peak overpressure with yield factor which is a component of TNT equivalence method are found to be great in near-by distances from explosion source where the increase in overpressure is very steep, but the differences are getting smaller as the distances increase.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.7
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• pp.54-60
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• 2007

We constructed a fiber-optic temperature sensor system using a sensor array with 15 fiber Bragg gratings for distributed temperature monitoring in electrical power systems. A polynomial fitting algorithm was used to compensate the nonlinear action of the MEMS tuneable wavelength filter used for Bragg wavelength demodulation Fixed passband wavelengths from a Fabry-Perot ITU filter were used as reference wavelengths for the fitting algorithm which obtained constant accuracy regardless of the wavelength scanning range and frequency. About 0.18[%] of linearity error compared to reference thermocouple thermometer has been obtained in the preliminary experimental results.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.12
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• pp.1607-1612
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• 2011

In this study, dynamic analysis of a proportional solenoid valve is performed, and an LQG/LTR controller with an integrator is designed to control the proportional solenoid valve. The dynamic characteristic of a valve is identified using experimental data by employing the frequency-domain modeling technique. The purpose of LQG/LTR control with an integrator is to enhance the system response and to improve the tracking accuracy for a complex input signal. Experimental tests are performed to verify the performance of the controller, and the results prove the high performance of the controller.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.1052-1055
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• 2020

본 논문에서는 3D 메시 정보, RGB-D 손 자세 및 2D/3D 손/세그먼트 마스크를 포함하여 인간의 손과 관련된 다양한 컴퓨터 비전 작업에 사용할 수 있는 새로운 다중 모달 합성 벤치마크를 제안 하였다. 생성된 데이터셋은 기존의 대규모 데이터셋인 BigHand2.2M 데이터셋과 변형 가능한 3D 손 메시(mesh) MANO 모델을 활용하여 다양한 손 포즈 변형을 다룬다. 첫째, 중복되는 손자세를 줄이기 위해 전략적으로 샘플링하는 방법을 이용하고 3D 메시 모델을 샘플링된 손에 피팅한다. 3D 메시의 모양 및 시점 파라미터를 탐색하여 인간 손 이미지의 자연스러운 가변성을 처리한다. 마지막으로, 다중 모달리티 데이터를 생성한다. 손 관절, 모양 및 관점의 데이터 공간을 기존 벤치마크의 데이터 공간과 비교한다. 이 과정을 통해 제안된 벤치마크가 이전 작업의 차이를 메우고 있음을 보여주고, 또한 네트워크 훈련 과정에서 제안된 데이터를 사용하여 RGB 기반 손 포즈 추정 실험을 하여 생성된 데이터가 양질의 질과 양을 가짐을 보여준다. 제안된 데이터가 RGB 기반 3D 손 포즈 추정 및 시맨틱 손 세그멘테이션과 같은 품질 좋은 큰 데이터셋이 부족하여 방해되었던 작업에 대한 발전을 가속화할 것으로 기대된다.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.99-108
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• 2022

Among induced polarization (IP) methods, spectral IP (SIP) uses alternating current as a transmission source to measure amplitudes and phase of complex electrical resistivity at each source frequency, which disperse with respect to source frequencies. The frequency dependence, which can be explained by a relaxation model such as Cole-Cole model or equivalent models, is analyzed to estimate SIP parameters from dispersion curves of complex resistivity employing multi-objective optimization (MOO). The estimation uses a generic algorithm to optimize two objective functions minimizing data misfits of amplitude and phase based on Cole-Cole model, which is most widely used to explain IP relaxation effects. The MOO-based estimation properly recovered Cole-Cole model parameters for synthetic examples but hardly fitted for the real laboratory measures ones, which have relatively smaller values of phases (less than about 10 mrad). Discrepancies between scales for data misfits of amplitude and phase, used as parameters of MOO method, and it is in necessity to employ other methods such as machine learning, which can deal with the discrepancies, to estimate SIP parameters from dispersion curves of complex resistivity.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.44-55
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• 2022

In order to automatically provide information on fruits in agricultural related broadcasting contents, instance image segmentation of target fruits is required. In addition, the information on the 3D pose of the corresponding fruit may be meaningfully used. This paper represents research that provides information about tomatoes in video content. A large amount of data is required to learn the instance segmentation, but it is difficult to obtain sufficient training data. Therefore, the training data is generated through a data augmentation technique based on a small amount of real images. Compared to the result using only the real images, it is shown that the detection performance is improved as a result of learning through the synthesized image created by separating the foreground and background. As a result of learning augmented images using images created using conventional image pre-processing techniques, it was shown that higher performance was obtained than synthetic images in which foreground and background were separated. To estimate the pose from the result of object detection, a point cloud was obtained using an RGB-D camera. Then, cylinder fitting based on least square minimization is performed, and the tomato pose is estimated through the axial direction of the cylinder. We show that the results of detection, instance image segmentation, and cylinder fitting of a target object effectively through various experiments.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.350-350
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• 2010

에너지 효율이 높은 LED조명을 사용하면 에너지 절감, 이산화탄소, 환경오염물질 배출 감소의 효과를 얻을 수 있다. 그러나 LED조명에서 발생하는 열은 LED조명의 수명과 에너지 효율을 감소시킨다. 따라서 LED조명을 상용화하기 위해서는 LED조명에서 발생되는 열을 효율적으로 제거하는 것이 필수적이며 LED조명 방열판의 생산단가 또한 낮아야 한다. 이러한 조건을 충족하는 LED조명용 방열판은 Al 6063이 주로 사용되고 있다. Al 6063은 열전도 특성이 우수하고 생산단가가 저렴하다. 그러나 100 W급 이상의 고출력 LED조명에 Al 6063을 사용하기 위해서는 Al 6063의 열 방출 특성을 향상시킬 필요가 있다. 금속의 열 방출 특성을 향상시키기 위해서 주로 이용되는 방법은 표면적을 극대화 시키는 것이다. 금속에 국부적인 깊이 부식을 일이키는 Pitting corrosion을 이용하면 저렴한 비용으로 Al 6063의 표면적을 극대화하여 방열판의 열 방출 특성을 향상시킬 수 있다. 실험에 사용한 기본적인 구조의 Al 6063 방열판의 크기는 $50{\times}50{\times}30(mm)$ 이며 1M HCl + 0.05M $H_2SO_4$에서 $I_a$ = +40 mA, $t_a$ = 60 ms, $I_c$ = -40 mA, $t_c$ =20 ms로 50, 100, 200 cycle AC 에칭 하였다. Pitting corrosion된 방열판은 $3W{\times}3$개의 LED모듈에서 1시간 발광 시킨 후, 열화상 카메라를 이용하여 표면온도를 측정하였다. 실험결과 AC에칭 cycle이 증가할수록 발열특성이 우수하였으며, Pitting corrosion을 이용하지 않은 방열판에 비해 최대 $5^{\circ}C$의 표면온도 감소가 이루어졌다. 본 연구를 통해, 저렴하면서도 열 방출 특성이 높은 방열판을 설계하면, 고출력 LED조명의 상용화를 앞당길 수 있을 것이다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.4
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• pp.21-26
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• 2011

Feature ranking is useful to gain knowledge of data and identify relevant features. In this study, we proposed a use of feature ranking for classification of neuro-degeneration and vascular dementia in micro-Raman spectra of platelet. The entire region of the spectrum is divided into local region including several peaks, followed by Gaussian curve fitting method in the region to be modeled. Local minima select from the subregion and then remove the background based on the position by using interpolation method. After preprocessing steps, significant features were selected by feature ranking method to improve the classification accuracy and the computational complexity of classification system. PCA (principal component analysis) transform the selected features and the overall features that is used classification with the number of principal components. These were classified as MAP (maximum a posteriori) and it compared with classification result using overall features. In all experiments, the computational complexity of the classification system was remarkably reduced and the classification accuracy was partially increased. Particularly, the proposed method increased the classification accuracy in the experiment classifying the Parkinson's disease and normal with the average 1.7 %. From the result, it confirmed that proposed method could be efficiently used in the classification system of the neuro-degenerative disease and vascular dementia of platelet.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.5
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• pp.13-20
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• 2008

Although digital hearing aid algorithms have been developed to compensate hearing loss and to help hearing impaired people to communicate with others, digital hearing aid user still complain about difficulty of hearing the speech. The reason could be the quality of speech through digital hearing aid is insufficient to understand the speech caused by feedback, residual noise and etc. And another thing is masking effect among formants that makes sound quality low. In this study, we measured the masking characteristics of normal listeners and hearing impaired listeners having presbyacusis to confirm masking effect in speech itself. The experiment is composed of 5 tests; pure tone test, speech reception threshold (SRT) test, word recognition score (WRS) test, puretone masking test and speech masking test. In speech masking test, there are 25 speeches in each speech set. And log likelihood ratio (LLR) is introduced to evaluate the distortion of each speech objectively. As a result, the speech perception became lower by increasing the quantity of formant enhancement. And each enhanced speech in a speech set has statistically similar LLR, however speech perception is not. It means that acoustic masking effect rather than distortion influences speech perception. In actuality, according to the result of frequency analysis of the speech that people can not answer correctly, level difference between first formant and second formant is about 35dB, and it is similar to result of pure tone masking test(normal hearing subject:36.36dB, hearing impaired subject:32.86dB). Characteristics of masking effect is not similar between normal listeners and hearing impaired listeners. So it is required to check the characteristics of masking effect before wearing a hearing aid and to apply this characteristics to fitting.