• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.19 no.2
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• pp.142-145
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• 2008

Background and Object: The aim of this study is to evaluate the change of patient's subjective voice handicap index (VHI) and acoustic parameters before and after laryngeal microsurgery for benign vocal cord disease. Materials and Method: We analyzed 78 patients who received laryngeal microsurgery for benign vocal cord disease from January 2004 to February 2007 retrospectively. There were 28 vocal polyp, 40 vocal nodule, 5 intracordal cyst and 5 Reinke's edema. Jitter, shimmer, harmony to noise ratio (HNR) were analyzed before surgery and 2-3months after surgery using the Doctor's speech science program. The voice handicap index introduced by the Pittsburgh Voice Center was used to examine patient's subjective change of voice quality. Results: Acoustic parameters of jitter, shimmer and HNR were improved in patients with vocal polyp and vocal nodule after surgery. The acoustic parameters were not improved in patients with Reinke's edema, statistically. Only jitter was improved significantly in patients with intracordal cyst (p<0.05). The VHI was significantly improved after surgery. The change of jitter and shimmer was significantly correlated with the change of VHI after surgery. Conclusion: The acoustic parameters and VHI were significantly improved in patients with benign vocal disease after laryngeal microsurgery.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.447-453
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• 2020

In this paper, we propose a system to extract effective speaker representations from a speech signal using a deep learning method. Based on the fact that speech signal contains identity unrelated information such as text content, emotion, background noise, and so on, we perform a training such that the extracted features only represent speaker-related information but do not represent speaker-unrelated information. Specifically, we propose an auto-encoder based disentanglement method that outputs both speaker-related and speaker-unrelated embeddings using effective loss functions. To further improve the reconstruction performance in the decoding process, we also introduce a discriminator popularly used in Generative Adversarial Network (GAN) structure. Since improving the decoding capability is helpful for preserving speaker information and disentanglement, it results in the improvement of speaker verification performance. Experimental results demonstrate the effectiveness of our proposed method by improving Equal Error Rate (EER) on benchmark dataset, Voxceleb1.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.406-413
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• 2020

In this paper, to improve the classification accuracy of bird and amphibian acoustic sound, we utilize GLU (Gated Linear Unit) and Self-attention that encourages the network to extract important features from data and discriminate relevant important frames from all the input sequences for further performance improvement. To utilize acoustic data, we convert 1-D acoustic data to a log-Mel spectrogram. Subsequently, undesirable component such as background noise in the log-Mel spectrogram is reduced by GLU. Then, we employ the proposed temporal self-attention to improve classification accuracy. The data consist of 6-species of birds, 8-species of amphibians including endangered species in the natural environment. As a result, our proposed method is shown to achieve an accuracy of 91 % with bird data and 93 % with amphibian data. Overall, an improvement of about 6 % ~ 7 % accuracy in performance is achieved compared to the existing algorithms.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.1-9
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• 2008

One of the problems for implementing the spot detection phase in the 2-DE gel image analysis program is the eliminating noises in the image. Remained noises after the preprocessing phase cause the over-segmented regions by the segmentation phase. To identify and exclude the over-segmented background regions, if we use the fixed thresholding method that is choosing an intensity value for the threshold, the spots that is invisible by the eyes but mean a very small amount proteins which have important role in the biological samples could be eliminated. This paper propose an adaptive thresholding method that come from an idea that is got on statistical analysing for the prominences of the peaks. The adaptive thresholding method works as following. Firstly we calculate an average prominence value curve and fit it to exponential function curve, as a result we get parameters for the exponential function. And then we calculate a threshold value by using the parameters and probability distribution of errors. Lastly we apply the threshold value to the region for determining the region is a noise or not. According to the probability distribution of errors, the reliability is 99.85% and we show the correctness of the proposed method by representing experiment results.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.132-145
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• 2009

We present the framework for JND based Illumination and Color Restoration Using Edge-preserving filter for restoring distorted images taken under the arbitrary lighting conditions. The proposed method is effective for appropriate illumination compensation, vivid color restoration, artifacts suppression, automatic parameter estimation, and low computation cost for HW implementation. We show the efficiency of the mean shift filter and sigma filter for illumination compensation with small spread parameter while considering the processing time and removing the artifacts such as HALO and noise amplification. The suggested CRF (color restoration filter) can restore the natural color and correct color distortion artifact more perceptually compared with current solutions. For the automatic processing, the image statistics analysis finds suitable parameter using JND and all constants are pre-defined. We also introduce the ROI-based parameter estimation dealing with small shadow area against spacious well-exposed background in an image for the touch-screen camera. The object evaluation is performed by CMC, CIEde2000, PSNR, SSIM, and 3D CIELAB gamut with state-of-the-art research and existing commercial solutions.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.1
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• pp.98-105
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• 2007

In this paper, we propose a timing detector using suboptimal maximum likelihood method. The proposed method has an simple reference signal generator. Additionally, timing detector's gain of the proposed method is the same to Early-Late gate and ML method. We reveal that tracking range of time tracker is narrow because of using data-decision, that is, tracking range is ${\pm}0.06ns$ for the 4-order Gaussian monocycle with 0.7ns pulse width. Therefore we can find that searcher must have very accurate acquisition procedure. When estimating a performance of time tracker, we consider a jitter in transmitter and receiver's pulse generation process as well as background noise. By using computer simulation, we propose mean/variance of timing detector and tracking process. Also we consider a mobility in tracking process, i.e., timing error modeled ramp function. In order to propose a performance of time tracker, we consider only one correlation demodulator.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.50.1-50.1
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• 2014

The Multi-purpose InfraRed Imaging System (MIRIS) is the main payload of Science and Technology Satellite 3 (STSAT-3), which was launched onboard Dnepr rocket from Russian Yasny Launch Base in November 2013. The MIRIS is an infrared (IR) camera, and the telescope has to be cooled down to below 200K in order to reduce thermal background noise. For the effective cooling and low-power consumption, we applied passive cooling method to the thermal design of the MIRIS. We also conducted thermal analysis and tested for the passive cooling before the launch of STSAT-3. After the launch, we have received State-of-Health (SOH) data from the satellite on orbit, including temperature monitoring results. It is important that the temperature of the telescope was shown to be cooled down to below 200K. In this paper, we present both the temperature data of the MIRIS on orbit and the thermal analysis results in the laboratory. We also compare these results and discuss the verification of the passive cooling.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9C
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• pp.863-870
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• 2009

Bilateral filter (BF) is a nonlinear filter for sharpness enhancement and noise removal. The BF performs the function by the two Gaussian filters, the domain filter and the range filter. To apply the BF to infrared (IR) small target detection, the standard deviation of the two Gaussian filters need to be changed adaptively between the background region and the target region. This paper presents a new BF with the adaptive standard deviation based on the analysis of the edge component of the local window, also having the variable filter size. This enables the BF to perform better and become more suitable in the field of small target detection Experimental results demonstrate that the proposed method is robust and efficient than the conventional methods.

• Journal of the Ergonomics Society of Korea
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• v.30 no.6
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• pp.689-694
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• 2011

Objective: The aim of this study is to evaluate the fluctuation of signal amplitude during repetitive dynamic contraction based on surface electromyography(EMG). Background: The most previous studies were considered isometric muscle contraction and they were difference to smoothing window length by moving average filter. In practical, the human movement is dynamic state. Dynamic EMG signal which indicated as the nonstationary pattern should be analyzed differently compared with the static EMG signal. Method: Ten male subjects participated in this experiment, and EMG signal was recorded by biceps brachii, anterior/posterior deltoid, and upper/lower trapezius muscles. The subject was performed to repetitive right horizontal lifting task during ten cycles. This study was considered three independent variables(muscle, amplitude processing technique, and smoothing window length) as the within-subject experimental design. This study was estimated muscular activation by means of the linear envelope technique(LE). The dependent variable was set coefficient of variation(CV) of LE for each cycle. Results: The ANOVA results showed that the main and interaction effects between the amplitude processing technique and smoothing window length were significant difference. The CV value of peak LE was higher than mean LE. According to increase the smoothing window length, this study shows that the CV trend of peak LE was decreased. However, the CV of mean LE was analyzed constant fluctuation trend regardless of the smoothing window length. Conclusion: Based on these results, we expected that using the mean LE and 300ms window length increased reproducibility and signal noise ratio during repetitive dynamic muscle contraction. Application: These results can be used to provide fundamental information for repetitive dynamic EMG signal processing.

• Korean Journal of Optics and Photonics
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• v.26 no.1
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• pp.44-53
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• 2015

Since the technology of current image sensors is limited to the megapixel class, it is necessary to use an image-stitching technique to create a gigapixel image from hundreds or thousands of photos taken by a megapixel image sensor. In this paper, we investigate the entire process of gigapixel camera technology employing a robotic panoramic head plus a stitching technique, and analyze the gigapixel camera technologies of Duke University and BAE Systems from the viewpoint of optical design structure. Hopefully this knowledge will lead to a new optical structure for a gigapixel camera. Meanwhile, we also perceive the need for additional image processing to reduce the noise of photos with a background of fog and mist, taken far from the camera lens.