• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2003년도 하계학술대회 논문집
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• pp.62-65
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• 2003

We propose an algorithm for almost unsupervised detection of linear structures, in particular, axes in road network and river, as seen in synthetics aperture radar (SAR) images. The first is local step and used to extract linear features from the speckle radar image, which are treated as road segment candidates. We present two local line detectors as well as a method for fusing information from these detectors. The second is global step, we identify the real roads among the segment candidates by defining a Markov random field (MRF) on a set of segments, which introduces contextual knowledge about the shape of road objects.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2000년도 추계종합학술대회논문집
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• pp.121-124
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• 2000

We propose an algorithm for almost unsupervised detection of linear structures, in particular, axes in road network and river, as seen in synthetics aperture radar (SAR) images. The first is local step and used to extract linear features from the speckle radar image, which are treated as road segment candidates. We present two local line detectors as well as a method for fusing Information from these detectors. The second is hybrid step, we Identify the real roads among the segment candidates by defining a Markov random field (MRF) on a set of segments, which introduces contextual knowledge about the shape of road objects.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2000년도 하계종합학술대회논문집
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• pp.221-224
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• 2000

We propose an algorithm for almost unsupervised detection of linear structures, in particular, axes in road network and river, as seen in synthetics aperture radar (SAR) images. The first is local step and used to extract linear features from the speckle radar image, which are treated as road segment candidates. We present two local line detectors as well as a method for fusing information from these detectors. The second is global step, we identify the real roads among the segment candidates by defining a Markov random field (MRF) on a set of segments, which introduces contextual knowledge about the shape of road objects.

• 융합보안논문지
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• 제18권4호
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• pp.27-33
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• 2018

스트림 암호는 1회용 패드(one time pad)형 암호 알고리즘으로 랜덤한 비트(또는 문자)들의 열을 열쇠로 사용하여 평문과 XOR과 같은 간단한 연산을 통해 암호화하므로 알고리즘의 안전성은 사용되는 열쇠의 난수성에 의존한다. 그러므로 사용되는 열쇠에 대해 주기, 선형복잡도, 비선형도, 상관면역도 등의 수학적 분석을 통해 보다 안전한 암호시스템을 설계할 수 있는 장점이 있다. 스트림 암호에서의 암호화 열쇠는 고유다항식을 가지고 LFSR(linear feedback shift register)에서 열쇠이진 수열을 생성하여 사용한다. 이 고유다항식 중 비도가 가장 우수한 다항식이 바로 원시다항식이다. 원시다항식은 스트림 암호뿐만 아니라 8차 원시 다항식을 사용한 블록암호인 SEED암호, 그리고 24차 원시 다항식을 사용하여 설계한 공개열쇠암호인 CR(Chor-Rivest) 암호 등에서도 널리 이용되고 있다. 본 논문의 주요내용은 이러한 암호알고리즘을 연구하는데 사용되는 갈루아(Galois)체에서의 원시다항식에 대한 개념과 다양한 성질들을 고찰해 보고 소수 p의 값이 2이상인 경우 $F_p$에서의 기약다항식과 원시다항식의 개수를 구하는 정리를 증명해 보았다. 이러한 연구는 보다 비도가 높은 원시다항식을 찾아 새로운 암호알고리즘을 개발하는 기반 연구가 될 수 있다.

• 천문학회보
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• 제45권1호
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• pp.66.3-66.3
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• 2020

We present the optical design of Linear Astigmatism Free - Three Mirror System (LAF-TMS) D200 for UVO-Multiband Polarizing Imager System (UVOMPIS). LAF-TMS D200 is the off-axis wide-field telescope with EPD = 200 mm, F/2, and Field of View (FoV) = 2° × 4°. Its optical mirrors are optimized to freeform surfaces for high-quality optical performance over a wide FoV. The proposed mirror holder consists of four aluminum optomechanical modules that have applied for LAF-TMS D150 which is a prototype of the LAF-TMS system. It can accurately mount mirrors and also can sustain from vibration environments. As a feasibility study, quasi-static, modal, harmonic, and random vibration analyses have been performed to LAF-TMS D150 optomechanical structure under the qualification level of the Soyuz-2/Fregat launch system. We evaluate the vibration analysis results in terms of von Mises stress and Margin of Safety.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 추계학술대회
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• pp.616-621
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• 2003

Fluid-elastic instability is believed to be a cause of the large-amplitude vibration and resulting rapid wear of heat exchanger tubes when the flow velocity exceeds a critical value. For sub-critical flow velocities, the random turbulence excitation is the main mechanism to be considered in predicting the long-term wear of steam generator tubes. Since flow-induced interactions of the tubes with tube supports in the sub-critical flow velocity can cause a localized tube wear, tube movement in the clearance between the tube and tube support as well as the normal contact force on the tubes by fluid should be maintained as low as possible. A simplified method is used for predicting fretting-wear damage of the double $90^{\circ}$U-bend tubes. The approach employed is based on the straight single-span tube analytical model proposed by Connors, the linear structural dynamic theory of Appendix N-1300 to ASME Section III and the Archard's equation for adhesive wear. Results from the presented method show a similar trend compared with the field data. This method can be utilized to predict the fretting-wear of the double $90^{\circ}$U-bend tubes in steam generators.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1996년도 춘계학술대회 논문집
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• pp.24-29
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• 1996

The seniconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip effect on the functions of the semiconductors. The defects of the chip surface is crack or void. Because general inspection method requires many inspection processes, the inspection system which searches immediately and preciselythe defects of the semiconductor chip surface. We propose the inspection method by using the computer vision system. This study presents an image processing algorithm for inspecting the surface defects(crack, void)of the semiconductor test samples. The proposed image processing algorithm aims to reduce inspection time, and to analyze those experienced operator. This paper regards the chip surface as random texture, and deals with the image modeling of randon texture image for searching the surface defects. For texture modeling, we consider the relation of a pixel and neighborhood pixels as noncasul model and extract the statistical characteristics from the radom texture field by using the 2D AR model(Aut oregressive). This paper regards on image as the output of linear system, and considers the fidelity or intelligibility criteria for measuring the quality of an image or the performance of the processing techinque. This study utilizes the variance of prediction error which is computed by substituting the gary level of pixel of another texture field into the two dimensional AR(autoregressive model)model fitted to the texture field, estimate the parameter us-ing the PAA(parameter adaptation algorithm) and design the defect detection filter. Later, we next try to study the defect detection search algorithm.

• 대한전자공학회논문지TC
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• 제48권9호
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• pp.10-16
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• 2011

채널 부호화된 심볼은 연집 오류(Burst error)에 취약한 특성으로 인해 송신단에서 인터리빙 과정을 거쳐 송신된다. 수신단에서는 채널을 통하여 발생된 연집 오류를 디인터리빙 과정을 통해 랜덤 오류(Random error)로 변화시키고 채널 복호화를 통하여 오류 정정 효과를 높인다. 그러나 수신단에서 송신단의 인터리버 파라미터를 알지 못하는 경우에는 인터리빙은 특정 패턴에 의한 일종의 암호화로 볼 수 있으며 디인터리빙이 어렵게 된다. 최근 선형 블록 부호가 블록 인터리빙 되었을 때 선형 블록 부호의 선형성을 이용하여 인터리버 파라미터를 추정하는 기법들의 연구가 진행되었다. 그러나 길쌈 부호가 인터리빙 되었을 때, 선형 블록 부호와 달리 부호어 길이에 따라 구분되는 선형성을 이용할 수 없기 때문에 기존 선형 블록 부호의 선형성을 이용한 방법으로는 인터리버의 파라미터를 추정할 수 없다. 본 논문에서는 길쌈부호가 블록 인터리빙이 되었을 때 길쌈 부호 복원(Convolutional code reconstruction) 기법을 이용하여 블록 인터리버의 행과 열을 추정하는 블라인드 블록 디인터리빙 기법을 제안한다.

• 융합신호처리학회논문지
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• 제2권2호
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• pp.7-12
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• 2001

본 논문에서는 스페클 노이즈를 포함하는 SAR 영상에서 도로망과 같은 선형 구조를 검출하기 위하여 하이브리드 특징 검출 방법을 사용하였다. 먼저 국소적으로 이웃한 영역에 대하여 평균 밝기 비율 또는 통계적 특성을 고려하여 국소적 에지를 검출하였고, 도로에 대한 많은 정보를 위하여 양 검출기로부터 검출된 응답을 결합하였으며, 결합된 에지 세그먼트 중 도로에 일치하는 세그먼트를 결정하고, 연결하여 완전한 도로망을 검출하였다. 본 논문에서 도로망의 검출 방법으로 도로에 대한 일반적인 사전 지식을 MRF 모델로 정의하고, 제안한 세그먼트의 상호 작용 포인터 프로세서에 의한 에너지 함수를 최적화하여 도로망을 검출하였다.

• 한국물환경학회지
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• 제33권3호
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• pp.326-333
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• 2017

The lakes and reservoirs have been reported as important sources of carbon emissions to the atmosphere in many countries. Although field experiments and theoretical investigations based on the fundamental gas exchange theory have proposed the quantitative amounts of Net Atmospheric Flux (NAF) in various climate regions, there are still large uncertainties at the global scale estimation. Mechanistic models can be used for understanding and estimating the temporal and spatial variations of the NAFs considering complicated hydrodynamic and biogeochemical processes in a reservoir, but these models require extensive and expensive datasets and model parameters. On the other hand, data driven machine learning (ML) algorithms are likely to be alternative tools to estimate the NAFs in responding to independent environmental variables. The objective of this study was to develop random forest (RF) and multi-layer artificial neural network (ANN) models for the estimation of the daily $CO_2$ NAFs in Daecheong Reservoir located in Geum River of Korea, and compare the models performance against the multiple linear regression (MLR) model that proposed in the previous study (Chung et al., 2016). As a result, the RF and ANN models showed much enhanced performance in the estimation of the high NAF values, while MLR model significantly under estimated them. Across validation with 10-fold random samplings was applied to evaluate the performance of three models, and indicated that the ANN model is best, and followed by RF and MLR models.