• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.387-391
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• 1997

냉각재중의 방사능을 띤 성분 중에는 이온교환기에서 제거가 가능한 이온성분과 함께 필터에 의해서 주로 제거되는 입자성 물질로 존재한다. 운전중의 냉각재내 방사성 부식생성물의 물리적 조성 분포 측정 결과에 따르면 90%이상이 0.45$mu extrm{m}$필터에 의해 제거되는 입자성 물질로 구성되어 있다. 이로 인해 새수지 충전후 얼마 사용하지 않은 탈염기의 제염계수가 탈염기에서 완벽한 제거가 어려운 입자성 부식생성물로 인해 10이하를 나타낼 수 있다. 1차계통에 쓰이는 수지의 성능검사를 위해 사용하고 있는 현재의 제염계수 측정법은 다음과 같은 두가지 이유로 완벽하지 않음을 알 수 있다. 첫째, 냉각재중의 방사능을 띤 성분중에는 이온교환기에서 제거가 가능한 이온성분과 함께 필터에 의해 제거되는 입자성 물질도 함께 존재하므로 탈염기의 제염계수 측정 절차는 입자성 물질을 배제한 후 측정해야 하며, 특히 수치 교체를 결정하기 위한 제염계수 측정시에는 여과된 여액으로 방사능 농도를 측정하는 것이 바람직하다. 둘째 운전중인 냉각재의 시료중에는 핵분열 수율이 높고 핵연료봉 손상부위로 유출이 용이한 불활성 기체핵종들이 많이 존재하며, 탈염기 후단에서 채취한 시료중에도 많이 존재하고, 시료 이송과 방사능 측정동안의 짧은 시간동안에도 계속 붕괴반응함으로서 새로 생긴 핵종으로 인해 마치 탈염기의 제거능이 낮은 것으로 오판될 수 있다. 이러한 측정 오차인자를 고려하여야 1차계통 탈염기의 교환능력을 정확히 판정할 수 있다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.1
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• pp.29-36
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• 2004

Generally, wavelet coefficients can be classified into two categories: large coefficients with much signal information and small coefficients with little signal component. This statistical characteristic of wavelet coefficient is approximated to Gaussian mixture model and efficiently applied to noise reduction. In this paper, we propose an image denoising method using mixture modeling of wavelet coefficients. Binary mask value is generated by proper threshold which classifies wavelet coefficients into two categories. Information of binary mask value is used to remove image noise. We also develope an enhancement method of mask value using morphological filter, and apply it to image denoising for improvement of the proposed method. Simulation results shows the proposed method have better PSNRs than those of the state of art denoising methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.47-54
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• 2005

In general, wavelet coefficients are composed of a few large coefficients and a lot of small coefficients. In this paper, we propose image denoising algorithm using Bernoulli-Gaussian mixture model based on sparse characteristic of wavelet coefficient. The Bernoulli-Gaussian mixture is composed of the multiplication of Bernoulli random variable and Gaussian mixture random variable. The image denoising is performed by using Bayesian estimation. We present an effective denoising method through simplified parameter estimation for Bernoulli random variable using local expected squared error. Simulation results show our method outperforms the states-of-art denoising methods when using orthogonal wavelets.

• International Journal of Highway Engineering
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• v.12 no.3
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• pp.131-137
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• 2010

In this paper, overseas criteria and research results were reviewed to develop a rational criterion proper to domestic airport runways on measurement of friction coefficient and removal of rubber deposit. The friction coefficients of the runways of the Incheon International Airport were measured by the ASFT(Airport Surface Friction Tester) from August 2007 to July 2009 and the data at intensively landed points were analyzed. Variation of the friction coefficient due to accumulation and removal of tire rubber was analyzed and seasonal influence on the variation were investigated by pavement types. The friction coefficient steadily decreased over a long term despite periodical removal of the rubber deposits. The variation of the friction coefficient in summer was larger than other seasons and asphalt pavement was more sensitive to the seasonal influence than concrete pavement. The friction coefficient of the asphalt pavement with macro texture was even larger than that of early age concrete pavement with micro texture. The variation of the friction coefficient of the asphalt pavement due to the deposit and removal of the tire rubber was also larger than that of the concrete pavement.

• The Journal of the Acoustical Society of Korea
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• v.19 no.4
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• pp.3-15
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• 2000

In this paper we present a new image denoising filter that can suppress additive noise components while preserving signal components in the wavelet domain. The proposed filter, which we call an adaptive wavelet shrinkage(AWS) filter, is composed of two operators: the wavelet killing operator and the adaptive shrinkage operator. Each operator is selected based on the threshold value which is estimated adaptively by using the local statistics of the wavelet coefficients. In the wavelet killing operation, the small wavelet coefficients below the threshold value are replaced by zero to suppress noise components in the wavelet domain. The adaptive shrinkage operator attenuates noise components from the wavelet components above the threshold value adaptively. The experimental results show that the proposed filter is more effective than the other methods in preserving signal components while suppressing noise.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.565-568
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• 2000

본 논문에서는 data-driven 반향제거기 구조에서 타이밍 지터의 보상 방법을 제안한다. V.90PCM 모뎀환경에서 네트윅 클록에 동기가 되어 동작하는 사용자 터미널 모뎀이 디지털 PLL (DPLL)을 이용하여 타이밍 복원을 하면 타이밍 지터 성분이 반향제거기의 성능을 순간적으로 악화 시키게 된다. 제안된 방법은 두개의 계수세트 들로부터 타이밍 지터 발생시 필요한 계수를 디콘볼루션 알고리듬을 이용하여 FIR 필터링을 통해 구하며 발생하는 지터 성분 의 대부분을 보상 해 준다. 또한 제안 방법은 waveform driven 반향제거기에 비해 약간의 성능열화가 있지만 적은 연산량으로 타이밍 지터보상을 할 수 있는 장점이 있다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.34-42
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• 2006

In general, almost information is stored in only a few wavelet coefficients. This sparse characteristic of wavelet coefficient can be modeled by the mixture of Gaussian probability density function and point mass at zero, and denoising for this prior model is peformed by using Bayesian estimation. In this paper, we propose a method of parameter estimation for denoising using hypothesis-testing problem. Hypothesis-testing problem is applied to variance of wavelet coefficient, and $X^2$-test is used. Simulation results show our method outperforms about 0.3dB higher PSNR(peak signal-to-noise ratio) gains compared to the states-of-art denoising methods when using orthogonal wavelets.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.111-116
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• 2004

It is essential to know the information about the prior model for wavelet coefficients, the probability distribution of noise, and the variance of wavelet coefficients for noise reduction using Bayesian estimation in wavelet domain. In general denoising methods, the signal variance is estimated from the proper prior model for wavelet coefficients. In this paper, we propose a variable window size decision algorithm to estimate signal variance according to image region. Simulation results shows the proposed method have better PSNRs than those of the state of art denoising methods.

• The Journal of the Acoustical Society of Korea
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• v.22 no.4
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• pp.261-268
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• 2003

Conventional acoustic echo cancellers using ES algorithm have simple structure and fast convergence speed compared with those using NLMS algorithm, but they are very weak to external noise because ES algorithm updates the adaptive filter taps based on average energy reduction rate of room impulse response in specific acoustical condition. To solve this problem, in this paper, a new update algorithm for acoustic echo canceller with stepsize matrix generator is proposed. A set of stepsizes is determined based on residual error energy which is estimated by two moving average operators, and applied to the echo canceller in matrix from, resulting in improved convergence speed. Simulations in various noise condition show that the proposed algorithm improves the robustness of acoustic echo canceller to external noise.

• Journal of Broadcast Engineering
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• v.12 no.6
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• pp.555-564
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• 2007

Discrete cosine transform (DCT) coefficient dropping is well recognized as an efficient rate adaptation transcoding in motion-compensated (MC)-DCT based MPEG-compressed videos. However, in this scheme, the errors incurred by the DCT coefficient-dropping are propagated and often result in significant visual quality degradation. This paper presents two propositions describing well the statistical properties of propagated errors. That is, we propose that the DCT error of the current frame is not correlated to the propagated errors of the previous frames. We also propose that the overall distortions in a given frame can be approximated as the sum of the DCT error of the current frame and the propagated errors from the previous frames. Then, it is shown that several computer simulations with different video sequences verify the effectiveness of the proposed statistical analyses.