• Journal of Radiation Protection and Research
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• v.26 no.4
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• pp.385-392
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• 2001

Environmental risk factors such as ionizing radiations, heavy metals, and pesticides can cause environmental disasters when they exist in excess. The increases in use of ionizing radiation and agricultural pesticide are somewhat related to the possibility of the disaster. The risk of radiation and pesticide was evaluated by means of the single cell gel electrophoresis (SCGE) assay on the human blood lymphocytes. The lymphocytes were irradiated with $0{\sim}2.0Gy$ of $^{60}Co$ gamma ray. Another groups of lymphocytes were exposed to various concentrations of parathion. Significantly increased tail moment, which was a marker of DNA strand breaks in SCGE assay, showed a clear dose- or concentration-response relationship. Parathion of a recommended concentration for agricultural use ($1mg {\ell}^{-1}$ ) has a strong cytotoxic effect on lymphocytes, which is equivalent to damage induced by 0.1 Gy of ${\gamma}$-ray. Furthermore, $2mg{\ell}^{-1}$ of parathion can give rise to DNA damage equivalent to that induced by 0.25 Gy at which the radiation-induced damage can start to develop into clinical symptoms. The comparative results of this study can provide an experimental basis and biological information for the prevention of environmental disaster.

• Annual Conference on Human and Language Technology
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• 2015.10a
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• pp.151-154
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• 2015

실어증은 뇌손상으로 인해 발생하는 후천적 언어장애로서, 언어를 이해하고 표현하는 능력이 손상된 것이다. 이는 환자 개인의 어려움은 물론이고, 가족과 사회에도 문제를 초래할 수 있으므로 실어증 환자의 진단 및 치료는 중요하다. 그 중에서도 빠른 언어 치료는 발병 후 조기에 시작할수록 회복이 빠르다는 점에서 연구 결과들이 일치하고 있기 때문에 더욱 중요하다. 하지만 환자 대비 언어치료전문가의 수가 적어 치료시기를 놓칠 수 있기 때문에 가장 중요한 것은 빠른 실어증 진단과 전문가와의 접근성이다. 우리나라는 인터넷 보급률과 컴퓨터 보급률이 높기 때문에, 웹기반으로 시스템을 개발 한다면 우수한 접근성을 보장받을 수 있다. 본 연구에서는 개발된 '온라인 언어 재활 훈련 및 진단 시스템'을 제안하고 본 시스템을 통해 얻을 수 있는 데이터와, 이 데이터를 어떻게 가공하여 의미 있는 결과를 도출해 낼 수 있는지 소개한다. 본 시스템은 짧은 시간 안에 실어증 여부 확인과 언어 재활 훈련을 수행할 수 있고, 웹기반으로 개발되어 누구나 쉽게 치료와 관련된 콘텐츠, 정보, 그리고 재활 방법을 공유할 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.451-457
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• 2018

We propose an automatic detection and classification system of sewer damage database based on artificial intelligence and deep learning. In order to optimize the performance, we implemented a robust system against various environmental variations such as illumination and shadow changes. In our proposed system, a crack detection and damage classification method using a deep learning based Convolutional Neural Network (CNN) is implemented. For optimal results, 9,941 CCTV images with $256{\times}256$ pixel resolution were used for machine learning on the damaged area based on the CNN model. As a result, the recognition rate of 98.76% was obtained. Total of 646 images of $720{\times}480$ pixel resolution were extracted from various sewage DB for performance evaluation. Proposed system presents the optimal recognition rate for the automatic detection and classification of damage in the sewer DB constructed in various environments.

• Fire Science and Engineering
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• v.13 no.3
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• pp.19-26
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• 1999

$CO_2$ extinguishing system is the most $\phi$pular among the gas extinguishing system. $CO_2$ is usually stored with liquified state. But, it gasifies at the tip of nozzle when $CO_2$ was released through the pipe and head. A ro$\alpha$n temperature is very low when $CO_2$ was released. So electrical instrument, magnetic storage equipment and memory semiconductor are electrically or physically injured by cooling effect in a few minutes. So, we intend to find out temperature profile and electrical damage in compartment area, and supply basic d data for research and making standards and code through the full scale experiment. As result of experiment on the damage due to cooling effect from $CO_2$ extinguishing system, i instantaneous discharging temperature. was $-82.5^{\circ}C$ in average. An average temp. in the compartment after discharging $CO_2$ was $-40^{\circ}C$.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04b
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• pp.583-585
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• 2000

본 논문에서는 적은 수의 특징점을 이용한 얼굴 복원 방법을 제안한다. 먼저 얼굴을 형태와 질갑 프로토타입들의 선형 중첩으로 모형화한 다음, 특징점에서의 형태와 질감정보만을 가지고 각각의 얼굴이 요구하는 변형의 근사값을 찾는다. 본 논문에서는 이러한 under-determined 조건에서 최소 제곱법(least square minimization method)을 사용하여 최적값을 얻는다. 실험을 통하여 적은 수의 특징점을 이용하여 2차원 얼굴 영상을 효율적으로 복원할 수 있음을 검증하였다. 우리는 제안된 얼굴 영상을 압축하거나 겹침이나 잡영에 의해 손상된 영상으로부터 원래의 전체 정보를 복원하는데 중요한 역할을 할 수 있을 것으로 기대한다.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.459-464
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• 2007

영상기반의 3자원 복원(reconstruction)에 대한 연구가 컴퓨터 성능의 발전과 다양한 영상기반의 복원 알고리즘의 연구로 인해 최근 좋은 결과를 보이고 있으나, 이는 얼굴영역과 같은 목적이 되는 영역이 각 입력영상으로부터 미리 정확하게 추출되어 있다고 가정하기 때문이다. 일반적으로 목적이 되는 영역을 추출하기 위해 차영상이 많이 이용되고 있지만 차영상은 잡음과 구멍(hole)과 같은 오 추출된 영역이 발생하기 때문에 목적이 되는 영역을 3차원으로 복원을 할 때 심각한 오류를 초래할 수 있다. 전경물체(목적이 되는 영역)을 정확하게 추출하기 위해 최근 그래프 컷(graph cut)을 이용한 방법이 다양하게 시도되고 있다. 그래프 컷은 데이터 항(data term)과 스무드 항(smooth term)으로 구성된 에너지 함수를 전역적으로 최소화하는 방법으로 여러 공학적 문제에서 좋은 결과를 보이고 있지만, 에너지 함수의 데이터 항을 설정할 때 필요한 사전정보를 자동으로 얻기가 어렵다. 스테레오 비전의 깊이 정보가 최근 전경 물체 추출을 위한 사전정보로 많이 이용되고 있고 그들의 실험환경에서는 좋은 결과를 보이지만, 3차원 얼굴 복원에서 얼굴의 대부분이 동질의 영역을 가지고 있기 때문에 깊이 정보를 구하기 어려워 정확한 사전정보를 구하기가 어렵다. 본 논문에서는 3차원 얼굴 복원을 효과적으로 하기 위한 그래프 컷 기반의 전경 물체 추출 방법을 제안한다. 에너지 함수의 데이터 항을 설정하기 위해 전경 물체에 대한 사전정보를 추출해야 하며, 이를 위해 차영상을 이용하여 대략적인 전경 물체 추출하고, 사전정보에 대한 오류를 줄이기 위해 잡음과 그림자 영역을 제거한다. 잡음과 그림자 영역을 제거하면 구멍이 발생하거나 실루엣이 손상되는 문제가 발생한다. 손상된 정보는 근접한 픽셀이 유사하지 않을 때 낮은 비용을 할당하는 에너지 함수의 스무드(smooth) 항에 의해 에지 정보를 기반으로 채워진다. 결론적으로 제안된 방법은 스무드 항과 대략적으로 설정된 데이터 항으로 구성된 에너지 함수를 그래프 컷으로 전역적으로 최소화함으로써 더욱 정확하게 목적이 되는 영역을 추출할 수 있다.

• Journal of Korean Society of Steel Construction
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• v.22 no.1
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• pp.13-20
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• 2010

Seismic risk assessment of railway bridges is an important issue for a transportation network, because loss of functionality of railway bridges could result in severe disruption of the railway line, as no redundant routing systems generally exist. Although many studies have been conducted by numerous researchers regarding fragility analyses of bridge structure, little or no studies have been done for fragility analyses of a class of bridge structures considering their geometric variability. This study performs a fragility analysis for Track-on Steel-Plate-Girder (TOSPG) railway bridges in Korea considering their span variability. Seismic fragility curves are developed for a series of bridges with different spans varying from 2 to 15. At last, the fragility curves for the whole TOSPG bridges in Korea are also developed using the total probability theorem. This study is expected to effectively contribute to the seismic risk assessment of railway lines, where a number of bridges are present.

• Journal of the Korean Geotechnical Society
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• v.18 no.3
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• pp.51-59
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• 2002

This paper deals with development of a damage risk assessment system for adjacent buildings to under-passing tunnel face considering 3D-ground movement. The system consists of building and ground information module, monitoring data module, settlement evaluation module, and building damage risk assessment module. The major modules, settlement evaluation module and building damage assessment module, are based on settlement estimation model suggested by Attewell et al (1982) and the building damage assessment method by Mair et al. (1996). After estimating 3D-ground movements due to tunneling with settlement evaluation module, damage assessment far buildings is performed using building damage risk assessment module. The developed system has two major functions; 1) calculation of 3D-settlement with ground loss ($V_{s}$)or maximum settlement ($w_{max}$) and inflection point (i) using various empirical formulae, monitoring data, numerical results, and so on; 2) assessment of damage risk for adjacent buildings of arbitrary section with position change of tunnel face. The field data given by Boscadin and Cording (1989) leer the case of two-storied masonry building near the Metro tunnel in Washington D.C. was simulated to verify the applicability of the developed system.

• Journal of Broadcast Engineering
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• v.23 no.4
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• pp.503-510
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• 2018

Restoring of damaged images is a fundamental problem that was attempted before digital image processing technology appeared. Various algorithms for reconstructing damaged images have been introduced. However, the results show inferior restoration results compared with manual restoration. Recent developments of DNN (Deep Neural Network) have introduced various studies that apply it to image restoration. However, if the wide area is damaged, it can not be solved by a general interpolation method. In this case, it is necessary to reconstruct the damaged area through contextual information of surrounding images. In this paper, we propose an image restoration network using a generative adversarial network (GAN). The proposed system consists of image generation network and discriminator network. The proposed network is verified through experiments that it is possible to recover not only the natural image but also the texture of the original image through the inference of the damaged area in restoring various types of images.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.6
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• pp.630-640
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• 2002

The compressed video bitstream is very sensitive to transmission errors. If we lost packet or received with errors during the transmission, not only the current frame will be corrupted, but also errors will propagate to succeeding frames. Error concealment is a data recovery technique that enables the decoder to conceal effects of transmission errors by predicting the lost or corrupted video data from the previously reconstructed error free information. Motion vection recovery and motion compensation with the estimated motion vector is a good approach to conceal the corrupted macroblock data. In this paper, we prove that it is reasonable to use the estimated motion vector to conceal the lost macroblock by providing macroblock distortion models. After we propose a new motion vector recovery algorithm based on optical flow fields, we compare its performance to those of conventional error concealment methods. The proposed algorithm has smaller computational complexity than those of conventional algorithms.