• 환경정책연구
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• 제6권4호
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• pp.103-127
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• 2007

본 연구는 정부의 국제환경규범 결정과정에 영향을 줄 수 있는 이익집단들의 정치적 행동을 조감하는데 필요한 정치경제학 모형을 제시한다. 복잡하고 다양한 이익집단의 집단행동을 분석하기 위해서 본 연구는 최근 유행하는 메뉴 옥션 유형의 선거비용 기부 모형으로부터 시작하여 다수 조정자-다수 대리인 이론에 근거하는 국제 이익집단 정치와 더불어 공동 대리인 모형과 다수 조정자-다수 대리인 모델이 혼재되어 있는 경우까지 조감하였다. 국제무역이론의 특정생산요소 모형을 바탕으로 다양한 이익집단 정치경제모형에서 결정될 수 있는 균형 환경규범의 수준을 분석하여 근래 점증하는 환경주의자 이익집단의 정치적 역할 등을 가늠하도록 한다. 2국 소국가 개방경제를 가정하여 각국의 일방적인 환경규범입안은 매우 완화된 수준에서 이루어질 것이고 이 때문에 초래되는 외부효과는 정부 간 협력을 통하여 내재화될 수 있다는 종래의 이론적 주장에서 탈피하여 국가 간 협력을 통하여 달성될 수 있는 최적의 국제환경규범 수준이 동일한 이익을 추구하는 각국의 이익집단 간의 협력을 통해서도 가능함을 지적한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권10호
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• pp.4903-4929
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• 2018

In this study, a fully automatic pose and expression invariant 3D face alignment algorithm is proposed to handle frontal and profile face images which is based on a two pass course to fine alignment strategy. The first pass of the algorithm coarsely aligns the face images to an intrinsic coordinate system (ICS) through a single 3D rotation and the second pass aligns them at fine level using a minimum nose tip-scanner distance (MNSD) approach. For facial recognition, multi-view faces are synthesized to exploit real 3D information and test the efficacy of the proposed system. Due to optimal separating hyper plane (OSH), Support Vector Machine (SVM) is employed in multi-view face verification (FV) task. In addition, a multi stage unified classifier based face identification (FI) algorithm is employed which combines results from seven base classifiers, two parallel face recognition algorithms and an exponential rank combiner, all in a hierarchical manner. The performance figures of the proposed methodology are corroborated by extensive experiments performed on four benchmark datasets: GavabDB, Bosphorus, UMB-DB and FRGC v2.0. Results show mark improvement in alignment accuracy and recognition rates. Moreover, a computational complexity analysis has been carried out for the proposed algorithm which reveals its superiority in terms of computational efficiency as well.

• 한국컴퓨터정보학회논문지
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• 제16권3호
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• pp.149-156
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• 2011

멀티캐스트 라우팅은 무선 다중 홉 네트워크에서 일대다 통신을 위하여 많은 영역에서 이용되며 멀티캐스트 그룹 멤버에게 효율적이고 공평한 통신 환경을 마련한다. 하지만 그룹 멤버의 통신 관리, 각 전송 경로간의 신호간섭 등 요인은 멀티캐스트 소스 노드에게 비교적 큰 부하를 발생시키고 전체 멀티캐스팅의 효율을 저하시킨다. 본 논문에서는 "지역 기반의 계층적 멀티캐스트 라우팅 기법"이라고 하는 새로운 라우팅 기법을 제안하였다. 이 라우팅 기법은 지역 기반 라우팅 프로토콜의 속성을 기반으로 프로액티브 라우팅 기법을 지역 내부 노드 레벌의 멀티캐스팅에서, 리액티브 라우팅 기법을 지역 레벌의 경로 설정에 적용하여 설계하였다. 계층적이고 독립적인 멀티캐스팅이 서로 분리된 지역에서 작동함으로서 멀티캐스트 소스 노드의 부하를 분산시켰고 다중 경로사이의 신호 간섭을 최대한 회피하여 이상적인 멀티캐스트 전송률을 실현할 수 있었다.

• 한국통신학회논문지
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• 제38B권3호
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• pp.207-215
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• 2013

본 논문은 효율적인 무선 AMI 네트워크를 위한 채널 할당 및 스케줄링 기법에 관한 것이다. AMI 시스템에서, 제안하는 다중채널 클러스터 네트워크는 NC(Network Coordinator)와 CDA(Clustered Data Aggregator) 간의 통신 채널을 네트워크 채널로 정의 하고, CDA와 OMD(Out Meter Display), SMD(Smart Meter Device) 간의 통신채널을 그룹 채널로 정의한다. 네트워크 채널과 그룹채널이 혼합된 다중채널 클러스터 기반의 AMI 네트워크는 물리적/논리적 수용가 채널 클러스터링을 통해서 관리의 효율성을 증대하고, 인접 클러스터간 구별되는 채널 사용을 통한 검침 데이터의 신뢰성을 증대한다. 또한 다중채널 클러스터 기반의 채널할당을 통하여 데이터의 빠른 수집이 가능하며 검침망의 크기를 증가시킨다.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.411-419
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• 2017

The Wireless Mesh Network (WMN) is a multi-hop wireless network consisting of mesh routers and clients, where the mesh routers have minimal mobility and form the backbone. The WMN is primarily designed to access outer network to mesh clients through backhaul gateways. As traffic converges on the gateways, traffic hotspots are likely to form in the neighborhood of the gateways. In this paper, we propose Congestion Aware Multi-path Routing (CAMR) protocol to tackle this problem. Upon congestion, CAMR divides the clients under a mesh STA into two groups and returns a different path for each group. The CAMR protocol triggers multi-path routing in such a manner that the packet reordering problem is avoided. Through simulations, we show that CAMR improves the performance of the WMN in terms of throughput, delay and packet drop ratio.

• Journal of Information Display
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• 제11권4호
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• pp.169-172
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• 2010

This paper proposes a multi-touch detection technology that can be applied to large LCDs. To achieve this goal, a set of IR LEDs and sensors was used to construct an IR matrix, and a new algorithm based on Hough transform was applied. This approach reduced the "Ghost" response of the multi-touch detection technology to make it better than other IR touch recognition technologies, and showed robust performance in terms of multi-touch recognition.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.262-265
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• 2007

Preliminary results are reported on ship detection using coherence images computed from cross-correlating images of multi-look-processed dual-polarization data (HH and HV) of ENVISAT ASAR. The traditional techniques of ship detection by radars such as CFAR (Constant False Alarm Rate) rely on the amplitude data, and therefore the detection tends to become difficult when the amplitudes of ships images are at similar level as the mean amplitude of surrounding sea clutter. The proposed method utilizes the property that the multi-look images of ships are correlated with each other. Because the inter-look images of sea surface are covered by uncorrelated speckle, cross-correlation of multi-look images yields the different degrees of coherence between the images and water. The polarimetric information of ships, land and intertidal zone are first compared based on the cross-correlation between HH and HV. In the next step, we examine the technique when the dual-polarization data are split into two multi-look Images.

• 경영과학
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• 제24권2호
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• pp.57-72
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• 2007

Many Applications of scientific research have coupled with functional data signal clustering techniques to discover novel characteristics that can be used for the diagnoses of several issues. In this article we present an interpretable multi-scale cluster hierarchy framework for clustering functional data using its multi-aspect frequency information. The suggested method focuses on how to effectively select transformed features/variables in unsupervised manner so that finally reduce the data dimension and achieve the multi-purposed clustering. Specially, we apply our suggested method to mutual fund returns and make superior-performing funds group based on different aspects such as global patterns, seasonal variations, levels of noise, and their combinations. To promise our method producing a quality cluster hierarchy, we give some empirical results under the simulation study and a set of real life data. This research will contribute to financial market analysis and flexibly fit to other research fields with clustering purposes.

• ETRI Journal
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• 제36권6호
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• pp.960-967
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• 2014

In this paper, an analytical framework is proposed for the optimization of network performance through joint congestion control, channel allocation, rate allocation, power control, scheduling, and routing with the consideration of fairness in multi-channel wireless multihop networks. More specifically, the framework models the network by a generalized network utility maximization (NUM) problem under an elastic link data rate and power constraints. Using the dual decomposition technique, the NUM problem is decomposed into four subproblems - flow control; next-hop routing; rate allocation and scheduling; power control; and channel allocation - and finally solved by a low-complexity distributed method. Simulation results show that the proposed distributed algorithm significantly improves the network throughput and energy efficiency compared with previous algorithms.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.80-83
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• 2003

A Genetic algorithm is a searching algorithm that based on the law of the survival of the fittest. Multi-population Genetic Algorithms are a modified form of genetic algorithm. Therefore, experience with fuzzy logic and genetic algorithm has proven to be that a combination of them can efficiently make up for their own deficiency. The Multi-population Genetic Algorithms independently evolve subpopulations. In this paper, we suggest a new coding method that independently evolves subpopulations using the fuzzy logic controller. The fuzzy logic controller has applied two fuzzy logic controllers that are implemented to adaptively adjust the crossover rate and mutation rate during the optimization process. The migration scheme in the multi-population genetic algorithms using fuzzy logic controllers is tested for a function optimization problem, and compared with other group migration schemes, therefore the groups migration scheme is then performed. The results demonstrate that the migration scheme in the multi-population genetic algorithms using fuzzy logic controller has a much better performance.