• 한국통신학회논문지
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• 제35권4C호
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• pp.364-370
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• 2010

본 논문에서는 무선인지 시스템에서 궤환 오류를 고려한 협력 스펙트럼 센싱 기법에 대해서 제안한다. 협력 센싱에서는 각 부사용자의 자체 센싱 결과를 결합하여 최종 판정을 내리게 되는데, 부사용자가 정확한 자체 센싱결과를 내리더라도 궤환 채널의 상태가 좋지 않은 경우 이를 협력 센싱을하는데 직접적으로 사용할 수 없게 된다. 본 논문에서는 궤환 채널 상태가 좋은 사용자만 선택하여 협력 센싱에 참여하도록 함으로써 목표 오검출 확률을 만족하면서 정검출 확률을 최대화 시키는 협력 센싱 기법에 대해 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제4권6호
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• pp.1042-1062
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• 2010

Cooperative spectrum sensing (CSS) is an effective technology for alleviating the unreliability of local spectrum sensing due to fading/shadowing effects. Unlike most existing solutions, this paper considers the use of CSS technology in decentralized networks where a fusion center is not available. In such a decentralized network, some attackers may sneak into the ranks of cooperative users. On the basis of recent advances in bio-inspired consensus algorithms, an attack-proof, decentralized CSS scheme is proposed in which all secondary users can maintain cooperative sensing by exchanging information locally instead of requiring centralized control or data fusion. Users no longer need any prior knowledge of the network. To counter three potential categories of spectrum sensing data falsification (SSDF) attacks, some anti-attack strategies are applied to the iterative process of information exchange. This enables most authentic users to exclude potentially malicious users from their neighborhood. As represented by simulation results, the proposed scheme can generally ensure that most authentic users reach a consensus within the given number of iterations, and it also demonstrates much better robustness against different SSDF attacks than several existing schemes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1988년도 한국자동제어학술회의논문집(국내학술편); 한국전력공사연수원, 서울; 21-22 Oct. 1988
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• pp.725-728
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• 1988

Image restoration technique using dual sensor is presented in this paper. Digital Radiography image (1024xlO24) is obtained by conventional resolution sensor. We also obtain local DR image data by high resolution sensor. Two dimensional maximum entropy power spectrum estimation (2-D ME PSE) is applied to low resolution image and high resolution image for the purpose of the power spectrum estimation of each image. A class of linear algebraic restoration filter, parametric projection filter (PPF), is derived from the power spectrums of each image. It is shown that the noise energy may be considerably reduced through the PPF.

• Nuclear Engineering and Technology
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• 제44권2호
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• pp.207-224
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• 2012

This article discusses selects of some outstanding problems in nuclear reactor analysis, with proposed approaches thereto and numerical test results, as follows: i) multi-group approximation in the transport equation, ii) homogenization based on isolated single-assembly calculation, and iii) critical spectrum in Monte Carlo depletion.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.612-615
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• 2003

The error diffusion is a good method to reconstruct the continuous tones of an image to the bilevel tones However the reconstruction of edge characteristic by the nor diffusion is represented work when power spectrum is analyzed fer display error. In this paper, we present an edge enhanced error diffusion method to preprocess original image to achieve the enhancement for the edge characteristic. The preprocessing algorithm consist of two processes. First the difference value between the current pixel and the local average of the surrounding pixel in original image is obtained. Second, the weighting function is composed by the magnitude and the sign of the local average. To confirm the effect of the proposed method, it is compared with the conventional edge enhanced error diffusion methods by measuring the radially averaged power spectrum densities (RAPSDs) for their display errors. The comparison result demonstrate the superiority of the proposed method over the conventional ones.

• International Journal of Internet, Broadcasting and Communication
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• 제10권3호
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• pp.59-64
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• 2018

A cooperative spectrum sensing has been proposed to improve the sensing performance in cognitive radio (CR) network. However, cooperative sensing causes additional overhead for reporting the result of local sensing to the fusion center. In this paper, we propose a technique to reduce the overhead of data transmission of cooperative sensing for applying the quantum data fusion technique in cognitive radio networks by omitting the lowest quantized in the local sensed results. If a CR node senses the lowest quantized level, it will not send its local sensing data in the corresponding sensing period. The fusion center can implcitly know that a spectific CR node sensed lowest level if there is no report from that CR node. The goal of proposed sensing policy is to reduce the overhead of quantized data fusion scheme for cooperative sensing. Also, our scheme can be adapted to all quantized data fusion schemes because it only deal with the form of the quantized data report. The experimental results show that the proposed scheme improves performance in terms of reporting overhead.

• Earthquakes and Structures
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• 제7권4호
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• pp.587-607
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• 2014

Progressive collapse, which is referred to as the collapse of the entire building under local damages, is a common failure mode happened by earthquakes. The collapse process highly depends on the whole structural system. Since, asymmetry of the building plan leads to the local damage concentration; it may intensify the progressive collapse mechanism of asymmetric buildings. In this research the progressive collapse of regular and irregular 6-story RC ordinary moment resisting frame buildings are studied in the presence of the earthquake loads. Collapse process and collapse propagation are investigated using nonlinear time history analyses (NLTHA) in buildings with 5%, 15% and 25% mass asymmetry with respect to the number of collapsed hinges and story drifts criteria. Results show that increasing the value of mass eccentricity makes the asymmetric buildings become unstable earlier and in the early stages with lower number of the collapsed hinges. So, with increasing the mass eccentricity in building, instability and collapse of the entire building occurs earlier, with lower potential of the progressive collapse. It is also demonstrated that with increasing the mass asymmetry the decreasing trend of the number of collapsed beam and column hinges is approximately similar to the decreasing trend in the average story drifts of the mass centers and stiff edges. So, as an alternative to a much difficult-to-calculate local response parameter of the number of collapsed hinges, the story drift, as a global response parameter, measures the potential of progressive collapse more easily.

• 대한기계학회논문집B
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• 제39권10호
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• pp.795-803
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• 2015

본 연구에서는 발전용 터빈 제 1 단 동익 흡입면에서 발달하는 경계층유동에 대하여 체계적으로 연구하였다. 이를 위해 흡입면에서 열부하가 급격하게 변화하는 대표적인 영역에 대하여, 경계층의 평균 유속, 난류강도, 에너지스펙트럼 등을 측정하였다. 그 결과 흡입면 경계층유동이 층류에서 난류 경계층으로 천이됨을 확인할 수 있었고, 이 천이경로는 박리버블의 전단층에서 주로 발생하는 박리유동 천이로 확인되었다. 흡입면에서 열부하의 최소값이 존재하는 곳은 흡입면 경계층유동의 천이가 시작되는 위치에 해당하며, 열부하가 최대인 곳은 박리유동 천이가 모두 마무리되어 벽근처에 강력한 난류유동이 존재하는 곳과 일치하였다. 에너지스펙트럼의 측정을 통하여, 흡입면 경계층의 박리유동 천이 전후에 나타나는 난류운동에너지의 주파수 특성을 자세히 파악할 수 있었다.

• 인터넷정보학회논문지
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• 제12권1호
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• pp.1-10
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• 2011

스펙트럼 검출은 인지 무선 시스템(Cognitive Radios) 구현을 위한 핵심 기술들 중의 하나이다. 스펙트럼 검출에서 문제시되는 점들 중에 하나는 페이딩(Fading) 및 쉐도윙(Shadowing) 등으로 인해서 스펙트럼 검출 성능이 저하된다는 것이다. 이 문제점을 해결하기 위해 제안된 방법 중 하나가 협력 스펙트럼 검출 방법이다. 이 방법을 통해 비협력 스펙트럼 검출 방식의 성능을 개선할 수 있지만, 여전히 큰 장애물과 같은 간섭 요인에 의해 스펙트럼 성능이 영향을 받는다는 단점이 있다. 특히, 기존의 대부분의 연구에서는 고정된 1차 사용자(Primary User, PU)를 고려하고 있지만 향후 유비쿼터스(Ubiquitous) 환경에서는 이동성을 가지는 1차 사용자가 존재하는 시스템을 고려해야 한다. 이러한 환경에서 기존의 협력 스펙트럼 검출 방식은 정확성이 낮은 검출 성능을 보이고 고려하지 않아도 될 2차 사용자(Cognitive User, CR user)의 국부 센싱값을 전송함으로써 많은 에너지를 소비하는 문제점이 있다. 본 논문에서는 이러한 문제를 해결하기 위해서, 무선 인지 시스템에서의 이동성을 가지는 1차 사용자의 위치를 추정하고 이를 기반으로 간섭 영향을 받는 2차 사용자를 검출한다. 또한 검출된 간섭영향을 받는 2차 사용자의 센싱 정보를 융합 결정할 때 배제함으로써 스펙트럼 검출의 정확성을 높이는 방법을 제안하다. 시뮬레이션을 통하여 제안된 알고리즘이 기존 알고리즘 보다 정확한 스펙트럼 검출을 보인다.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.402-410
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• 2017

For many years, researchers in face description area have been representing and recognizing faces based on different methods that include subspace discriminant analysis, statistical learning and non-statistics based approach etc. But still automatic face recognition remains an interesting but challenging problem. This paper presents a novel and efficient face image representation method based on Optimized Local Ternary Pattern (OLTP) texture features. The face image is divided into several regions from which the OLTP texture feature distributions are extracted and concatenated into a feature vector that can act as face descriptor. The recognition is performed using nearest neighbor classification method with Chi-square distance as a similarity measure. Extensive experimental results on Yale B, ORL and AR face databases show that OLTP consistently performs much better than other well recognized texture models for face recognition.