• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2010.05a
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• pp.397-398
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• 2010

• Proceedings of the Korean Nuclear Society Conference
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• 1999.05a
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• pp.76-76
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• 1999

• Proceedings of the Korean Nuclear Society Conference
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• 2004.05a
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• pp.105-105
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• 2004

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.237-238
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• 2011

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.450-456
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• 2016

STDR (sequence time domain reflectometry) to detect a cable fault using a pseudo noise sequence as a reference signal, and time correlation analysis between the reference signal and reflection signal is robust to noisy environments and can detect intermittent faults including open faults and short circuits. On the other hand, if the distance of the fault location is far away or the fault type is a soft fault, attenuation of the reflected signal becomes larger; hence the correlation coefficient in the STDR becomes smaller, which makes fault detection difficult and the measurement error larger. In addition, automation of the fault location by detection of phase and peak value becomes difficult. Therefore, to improve the cable fault detection of a conventional STDR, this paper proposes the algorithm in that the peak value of the correlation coefficient of the reference signal is detected, and a peak value of the correlation coefficient of the reflected signal is then detected after removing the reference signal. The performance of the proposed method was validated experimentally in low-voltage power cables. The performance evaluation showed that the proposed method can identify whether a fault occurred more accurately and can track the fault locations better than conventional STDR despite the signal attenuation. In addition, there was no error of an automatic fault type and its location by the detection of the phase and peak value through the elimination of the reference signal and normalization of the correlation coefficient.

• Journal of the Institute of Convergence Signal Processing
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• v.18 no.2
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• pp.76-83
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• 2017

In this study, the original medical image, DICOM file, was converted into TIFF, BITMAP, GIF, JPEG image file, and then the conversion loss ratio according to the image compression and conversion process was quantitatively evaluated using Origin pro and ICY image analysis program. As the evaluation method, 50% MTF, structural similarity index, MSE, RMSE, maximum signal - to - noise ratio and so on were evaluated. The TIFF image file showed the same result as DICOM image in all experimental groups, Image file format. In this study, we propose a new method for evaluating the quality of digital images by applying original evaluation program such as Origin pro or ICY medical image analysis program. Is expected to be used as research data in the field of medical image processing, and TIFF image file showing the same result as DICOM image in the basic research field using digital medical image and evaluation program that does not support DICOM file Therefore, it is believed that it will help to secure reliability in digital medical image processing research using image file.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2460-2470
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• 2009

In this study, the parameter extraction for evaluation of the anesthesia depth in each anesthesia stages was conducted. An object of the this experiment study has studied 5 adult patients (mean $\pm$ SD age:$42{\pm}9.13$), ASA classification I and II, undergoing surgery of obstetrics and gynecology. Anaesthesia was maintained with Enflurane. HRV signal was created by R-peak detection algorithm form ECG signal. The HRV data were preprocessing algorithm. It has tried find out the anesthesia parameter which responds the anesthesia events and shows objective anesthesia depth according to anesthesia stage including pre-anesthesia, induction, maintenance, awake and post-anesthesia. In this study, proposed algorithm to analysis the HRV(heart rate variability) signal using wavelet transform in anesthesia stage. Three sorts of wavelet functions applied to PSD. In the result, all of the results were showed similarly. But experiment results of Daubeches 10 is better. Therefore, this parameter is the best parameter in the evaluation of anesthesia stage.

• The Journal of the Acoustical Society of Korea
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• v.42 no.6
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• pp.544-551
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• 2023

Speech enhancement used to improve the perceptual quality and intelligibility of noise speech has been studied as a method using a complex-valued spectrum that can improve both magnitude and phase in a method using a magnitude spectrum. In this paper, a study was conducted on how to apply attention mechanism to complex-valued spectrum-based speech enhancement systems to further improve the intelligibility and quality of noise speech. The attention is performed based on additive attention and allows the attention weight to be calculated in consideration of the complex-valued spectrum. In addition, the global average pooling was used to consider the importance of the feature map. Complex-valued spectrum-based speech enhancement was performed based on the Deep Complex U-Net (DCUNET) model, and additive attention was conducted based on the proposed method in the Attention U-Net model. The results of the experiments on noise speech in a living room environment showed that the proposed method is improved performance over the baseline model according to evaluation metrics such as Source to Distortion Ratio (SDR), Perceptual Evaluation of Speech Quality (PESQ), and Short Time Object Intelligence (STOI), and consistently improved performance across various background noise environments and low Signal-to-Noise Ratio (SNR) conditions. Through this, the proposed speech enhancement system demonstrated its effectiveness in improving the intelligibility and quality of noisy speech.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.2
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• pp.56-62
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• 2015

In this study, we implemented an unconstraint ECG monitoring system on a chair. Nowadays, modern people spend most of their time sitting on the chair. Therefore, it is necessary to have an unconstraint ECG monitoring system that can be used for a long time. The implemented system can perform measurement even with clothes on and it has great advantage on motion artifacts. A pair of unconstraint electrodes are placed on the back of the chair. Amplifier and filters are designed to remove motion artifacts, The baseline noise and power line noise are filtered and very low level of bio-signal is amplified to give a final measurement. Control unit and wireless transmission unit are implemented. Analog signal is converted into digital signal and transmits biological signal to the PC and the smart phone. Therefore continuous ECG monitoring in daily life is made possible. A comparison experiment between Ag / AgCl electrode and unconstraint electrode is conducted to evaluate the performance of the implemented system. As a result, we confirm our unconstraint system can be used for daily life ECG monitoring.

• Journal of Sensor Science and Technology
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• v.27 no.3
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• pp.192-198
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• 2018

Pulse oximetry is a non-invasive method for monitoring how much oxygenated hemoglobin is present in the blood. The principle of pulse oximetry is based on the red infrared light adsorption characteristics of oxygenated and deoxygenated hemoglobin. Even through the convenience of a pulse oximeter, its weak signal-to-noise ratio against motion artifacts and low perfusion makes it difficult to be accepted by execs devices. Several researchers have suggested the use of an adaptive noise cancellation (ANC) algorithm. They have demonstrated that ANC is feasible for reducing the effects of motion artifacts. Masimo Corporation developed a discrete saturation transformation (DST) algorithm that uses a reference signal and ANC. In commercial devices, it is very hard to escape it because Masimo's patents are very powerful and a better method is yet to be developed. This study proposes a new method that can measure noise saturation as well as accurate oxygen saturation from signals with high motion artifacts without using ANC and DST. The proposed algorithm can extract a normal signal without noise from a signal with motion artifacts. The reference signal from a pulse oximeter simulator was used for the evaluation of our proposed algorithm and achieved good results.