• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.934-936
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• 2005

본 논문에서는 피라미드 계층간에 나타나는 잡음 신호의 특성을 바탕으로 라플라시안 피라미드를 이용한 X-ray 영상의 잡음 제거 방법을 제안한다. 제안하는 방법은 잡음 제거를 위해 X-ray 영상 신호의 지역적 표준 편차와 신호의 영역적 특징을 이용하였다. 지역적 표준 편차는 영상의 경계선 정도와 비례하는 특징을 가지기 때문에 지역적 표준 편차를 이용하여 경계 정보의 손실을 막았다. 또한 라플라시안 피라미드의 각 계층에 잡음 신호가 좁은 면적을 가지며 분포되는 영역적 특징을 이용하여 평평한 지역에서 잡음 신호의 제거 성능을 높였다. X-ray영상 및 잡음이 첨가된 표준 영상에 대한 실험을 통해 제안된 방법이 경계 정보의 유지와 잡음 제거에서 기존의 방법보다 향상된 성능을 보임을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.271-273
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• 2012

중복 제거(De-duplication) 여러 데이터를 저장한 스토리지에서 같은 내용을 담고 있는 파일자체나 블록단위의 chunk 등을 찾아 중복된 내용을 제거하여 중복된 부분은 하나의 데이터 단위를 유지함으로써 스토리지 공간을 절약할 수 있다. 본 논문에서는 실험적인 데이터가 아닌 실제 업무 환경에서 적용될만한 대용량의 데이터 백업을 가정한 상황에 대해 중복 제거 기법을 테스트해봄으로써 중복제거율과 성능을 측정하였으며 이를 시각적으로 표현하는 방법을 제안함으로써 평가자 및 사용자가 알아보기 쉽게 하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.202-205
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• 2012

기존의 고정 길이 분할 (FLC: Fixed Length Chunking) 중복 제거 기법은 파일이 조금이라도 수정이 되면 수정된 블록에 대한 해시 정보가 달라져 중복 데이터 임에도 불구하고 중복 블록으로 검색이 되지 않는 문제점이 있다. 본 연구에서는 FLC 기반의 중복 제거 기법에 데이터 위치(offset) 정보를 활용하여 중복 블록을 효율적으로 찾아냄으로써 기존의 FLC 기반의 중복 제거 기법보다 더 좋은 성능을 발휘하는 유사도 정보를 활용하는 중복 제거 기법(FS_FLC: File Similarity based Fixed Length Chunking)을 설계하고 구현했다. 실험 결과 제안한 알고리즘은 낮은 오버헤드로 가변 분할 기법(VLC: Variable Length Chunking)만큼의 높은 중복 데이터 탐색 성능을 보여주었다.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.138-149
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• 2018

In this paper, we propose a system model which effectively mitigates impulsive noise that degrades the performance of power line communication. Recently, deep learning have shown effective performance improvement in various fields. In order to mitigate effective impulsive noise, we applied a convolution neural network which is one of deep learning algorithm to conventional system. Also, we used a successive interference cancellation scheme to mitigate impulsive noise generated from multi-users. We simulate the proposed model which can be applied to the power line communication in the Section V. The performance of the proposed system model is verified through bit error probability versus SNR graph. In addition, we compare ZF and MMSE successive interference cancellation scheme, successive interference cancellation with optimal ordering, and successive interference cancellation without optimal ordering. Then we confirm which schemes have better performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.16 no.3 s.94
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• pp.319-326
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• 2005

In the multi-carrier OFDM communication system for the high data rate transmission, the ICI caused by phase noise of transceiver local oscillator may degrade the system performance seriously. In this paper, a new ICI self-cancellation scheme using data-conjugate method is proposed to reduce the ICI caused by phase noise effectively. Then, the CPE, ICI and CIR are derived by the phase noise linear approximation method. Besides, to analyze the efficiency of system performance improvement, the proposed method is compared with the original OFDM and the conventional ICI self-cancellation scheme using data-conversion method. As results, the performance degradation caused by ICI can be mitigated effectively in the OFDM system with ICI self-cancellation scheme, and more performance improvement can be achieved by the proposed ICI self-cancellation scheme using data-conjugate method than the conventional ICI self-cancellation scheme using data-conversion method when phase noise exists.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2003.11a
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• pp.207-214
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• 2003

Removal efficiency of methyl iodide at high temperature process by TEDA-impregnated activated carbon used for radioiodine retention in nuclear facility was experimentally compared with that of silver ion-exchanged synthetic zeolite(AgX), In temperature ranges of$30^{\circ}C$ to $400^{\circ}C$, adsorption capacity of un-impregnated carbon was sharply decreased, but TEDA-impregnated carbon showed similar values of adsorption capacity of AgX even around $100^{\circ}C$. Especially, loading amount of methyl iodide on TEDA carbon up to$250^{\circ}C$ represented higher values compared to un-impregnated carbon. Breakthrough curves of methyl iodide in fixed bed packed with AgX and TEDA-impregnated carbon at high temperature was compared. Removal mechanism of methyl iodide on AgX was proposed, based on analysis of by-product gas generated from adsorption reaction.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.3
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• pp.360-369
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• 2001

This paper proposes the groupwise serial cross interference cancellation(GSCIC) algorithm for coherent detection and analyzes the groupwise serial block interference cancellation(GSBIC) and GSCIC algorithm for an asynchronous wideband DS-CDMA system in a single cell over multipath fading channels. In general, the GSIC algorithm can be grouped into two classes: i.e., GSBIC and GSCIC algorithm. In this paper, the proposed GSCIC algorithm is to improve the performance of the GSBIC algorithm. We compare the performance of the GSCIC and existing GSBIC algorithm in a multipath fading channel to that of the existing SIC algorithm. As a result, the performance of GSCIC algorithm is somewhat better compared with the GSBIC algorithm according to reduction factor $R_{f}$ and is similar to that of the SIC algorithm. And also, the GSBIC and GSCIC algorithms have the advantage that it can be analyzed system performance easily, changing the number of users within a user group according to system capacity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.24-31
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• 2011

This paper proposes spatio-temporal denoising algorithm based on nonlocal means. Though the conventional denoising algorithms based on nonlocal means have good performance in noise removal, it is difficult to implement them into the hardware system due to much computational load and the need for several frame buffers. Therefore we adopted infinite impulse response temporal noise reduction algorithm in the proposed algorithm. Proposed algorithm shows less artificial denoised result in the motionless region. In the motion region, spatial filter based on efficiently improved nonlocal means algorithm conduct noise removal with less motion blur. Experimental results including comparisons with conventional algorithms for various noise levels and test images show the proposed algorithm has a good performance in both visual and quantitative criteria.

• Land and Housing Review
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• v.12 no.2
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• pp.91-97
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• 2021

High levels of fine dust is an increasing health concern in major cities such as Seoul. To improve the indoor air quality of apartments, this study examined the ability of an air shower system installed in an apartment unit to remove fine dust (as defined by ISO 12103-A2) from various clothing items of building occupants entering their apartment. Results of the experiment indicate that an air shower system is effective in removing final dust from clothing after one pass through the system. The fine dust removal efficiency for various clothing items was 74% for a dress suit, 70.6% for hiking clothes, 63.3% for knit-wear, 50.5% for a cotton t-shirt, and 38.8% for a coat. Fine dust removal efficiency increased with a second and third pass through the air shower system by an average of 9.1 and 13.9 percentage points respectively compared to a single pass through the system.

• Journal of the Korea Computer Graphics Society
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• v.27 no.5
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• pp.45-54
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• 2021

Recently, deep learning-based denoising approaches have been actively studied. In particular, with the advances of blind denoising techniques, it become possible to train a deep learning-based denoising model only with noisy images in an image domain where it is impossible to obtain a clean image. We no longer require pairs of a clean image and a noisy image to obtain a restored clean image from the observation. However, it is difficult to recover the target using a deep learning-based denoising model trained by only noisy images if the distribution of the noisy image is far from the distribution of the clean image. To address this limitation, unpaired image denoising approaches have recently been studied that can learn the denoising model from unpaired data of the noisy image and the clean image. ISCL showed comparable performance close to that of supervised learning-based models based on pairs of clean and noisy images. In this study, we propose suitable normalization techniques for each purpose of architectures (e.g., generator, discriminator, and extractor) of ISCL. We demonstrate that the proposed method outperforms state-of-the-art unpaired image denoising approaches including ISCL.