• Journal of Microbiology and Biotechnology
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• 제8권1호
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• pp.81-88
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• 1998

The determination of appropriate parameters and parameter conditions is very important for the optimization of production of target materials. Taguchi's method has been used widely as the basis for development trials and optimization during industrial process design. Reaction variables which influence product yield are easily determined and their effects are revealed by just a few reactions, negating the need for extensive experimental investigation. There are usually some factors that are responsible for variations in process characteristics, so called noise factors. Controlling noise factors is very costly and difficult or impossible. Taguchi's experimental design method was examined to determine the control factor's level that is less sensitive to the changes in environmental conditions and other noise factors without control of noise factors. In this study, optimization of lipase-catalyzed production of lysophosphatidic acid (LPA) which has various physiological functions was performed by Taguchi's method. We obtained LPA yields ($66.5\%$) with low variance (5.32) at 400 RPM, molar ratio of 40 : 3 (mol) (fatty acid: G-3-P), 48 h, and $50^{\circ}C$. Thus, bioactive LPA with a desired fatty acid moiety could be produced with high yields and low variance despite various environmental noise factors.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 춘계학술대회
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• pp.877-879
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• 2013

통신 기술을 기반으로한 현대 사회에서 디지털 TV 등 영상장치가 대중화되고 있다. 그러나 전송, 저장, 획득하는 과정에서, 시스템 내 외부적인 원인으로 영상은 잡음에 의해 훼손된다. 따라서 잡음제거 기술의 중요성이 커지고 있으며, 잡음제거를 위한 연구가 활발하게 이루어지고 있다. 본 논문에서는 영상에 첨가되는 AWGN(additive white Gaussian noise)을 제거하기 위하여, 추정한 잡음분산과 마스크 내의 차이를 고려한 가중치 필터 알고리즘을 제안하였다. 그리고 PSNR(peak signal to noise ratio)을 사용하여 제안한 알고리즘의 우수성을 나타내었다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2003년도 추계학술대회논문집
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• pp.324-329
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• 2003

An air-conditioner has various noise sources such as cooling fan noise, pumping noise, flow noise and impact noise. Among these, impact noise is the most unpleasant source. This is because the noise is produced in indoor unit of air-conditioner. To control the noise source effectively, first we must identify the noise sources. When we identify impact noise source, the measurement have to be carried out simultaneously. So we use beamforming method that requires less measurement points than intensity method and acoustic holography. The objective of this paper is to estimate the location of impact source. This objective can be achieved by using minimum variance cepstrum that is able to detect impulse embedded in noise. In this study, modified beamforming method based on cepstrum domain is proposed. Then this method applied to air-conditioner noise sources which produce impact noise.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.535-540
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• 2006

The relationship between the observable noise model and the satellite elevation angle can be modeled quite well by an exponential function.[Jin, 1996] Noise size and dependence on the elevation angle are, however, different for each observation and receiver type. Therefore, the coefficient determination of this model is an issue, and various methods including PR-CP, single difference, and time difference have been suggested. The limitations of them are difficulty to model the carrier phase noise and to eliminate bias. To overcome these disadvantages for using Jin's model, we suggest zero baseline double difference (DD) and noise sorting algorithm. Data DD technique in zero baseline is useful to eliminate all the troublesome GPS biases, and the remaining error is the sum of GPS measurement noises from two satellites. These DD residuals for hours should be sorted by the combination of satellite elevation angles, and then variance value of the residual for each combination can be estimated. Using these values, we construct an over-determined linear equation whose solution is a set of noise variance for each satellite elevation angle. With 24hr Trimble 4000ssi data, we easily worked out the coefficients of the noise model not only for pseudorange but also for carrier phase. We estimated the standard deviation of the measurement DD using our model, and plotted 1 and 3 sigma lines for every epoch to verify the representation of the residual error. 63.3% of pseudorange residual and 65.9% of phase error did not exceed the 1 sigma lines. Additionally, 99.2% and 99.5% of them lied within 3sigma line. These figures prove that the Gaussian property of measurement noise, and that the suggested model by our algorithm corresponds to the observable noise information.

• 대한전자공학회논문지
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• 제25권3호
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• pp.238-242
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• 1988

It is analyzed how performance of phase-locked loop driven by photodetector current in optical receiver will be changed under the condition that Gaussian thermal noise, pattern noise and shot noise are present and the loop has the nonzero detuning frequency. The phase error variance cahnges with the circuit configuration and the produced noise models. The analyzed results are applied to the previously implemented 90.194Mbps optic system whose loop filter is the improved active noninverting 1-st order lag-lead type.

• 대한전자공학회논문지
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• 제23권5호
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• pp.597-604
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• 1986

This paper describes various mismatch phenomena in differential pulse code modulation (DPCM) coding, such as the mismatch effects of probability density functin(pdf), signal variance, and correlation. At a high transmission rate(i.e., above 32 kbits/s), the performance of DPCM can be improved by matching the pdf shape between the input signal and the quantizer. However, the same gain cannot be obtained at a lower transmission rate. Also, it is shown that the gamma quantizer is realtively robust to the variation of pdf shaper and signal variance. Moreover, as the transmission rate increases, the performance of DPCM for the input signal with large variance is worse than that of DPCM for the signal with small variance due to the increase of overload noise. According to our simuladiton results, the mismatch effects of pdf shape and variance appear to yield more degradatin than that of correlation in a DPCM system.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 춘계학술대회 논문집
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• pp.480-481
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• 2014

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2014년도 춘계학술대회 논문집
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• pp.704-705
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• 2014

• Communications for Statistical Applications and Methods
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• 제19권4호
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• pp.619-628
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• 2012

Noise reduction is an important issue in the field of image processing because image noise lowers the quality of the original pure image. The basic difficulty is that the noise and the signal are not easily distinguished. Simple smoothing is the most basic and important procedure to effectively remove the noise; however, the weakness is that the feature area is simultaneously blurred. In this research, we use ways to measure the degree of noise with respect to the degree of image features and propose a Bayesian noise reduction method based on MAP (maximum a posteriori). Simulation results show that the proposed adaptive noise reduction algorithm using Bayesian MAP provides good performance regardless of the level of noise variance.

• Journal of Information Processing Systems
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• 제17권5호
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• pp.1004-1019
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• 2021

To solve the problems of the low image contrast, fuzzy edge details and edge details missing in noisy image fusion, this study proposes a noisy infrared and visible light image fusion algorithm based on non-subsample contourlet transform (NSCT) and an improved bilateral filter, which uses NSCT to decompose an image into a low-frequency component and high-frequency component. High-frequency noise and edge information are mainly distributed in the high-frequency component, and the improved bilateral filtering method is used to process the high-frequency component of two images, filtering the noise of the images and calculating the image detail of the infrared image's high-frequency component. It can extract the edge details of the infrared image and visible image as much as possible by superimposing the high-frequency component of infrared image and visible image. At the same time, edge information is enhanced and the visual effect is clearer. For the fusion rule of low-frequency coefficient, the local area standard variance coefficient method is adopted. At last, we decompose the high- and low-frequency coefficient to obtain the fusion image according to the inverse transformation of NSCT. The fusion results show that the edge, contour, texture and other details are maintained and enhanced while the noise is filtered, and the fusion image with a clear edge is obtained. The algorithm could better filter noise and obtain clear fused images in noisy infrared and visible light image fusion.