• International Journal of Contents
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• 제9권2호
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• pp.1-7
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• 2013

This paper proposes an efficient matching algorithm based on ASIFT (Affine Scale-Invariant Feature Transform) which is fully invariant to affine transformation. In our approach, we proposed a method of reducing similar measure matching cost and the number of outliers. First, we combined the Manhattan and Chessboard metrics replacing the Euclidean metric by a linear combination for measuring the similarity of keypoints. These two metrics are simple but really efficient. Using our method the computation time for matching step was saved and also the number of correct matches was increased. By applying an Optimized Random Sampling Algorithm (ORSA), we can remove most of the outlier matches to make the result meaningful. This method was experimented on various combinations of affine transform. The experimental result shows that our method is superior to SIFT and ASIFT.

• 대한원격탐사학회지
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• 제26권6호
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• pp.693-703
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• 2010

High spectral resolution of hyperspectral data enables analysis of complex natural phenomena that is reflected on the data nonlinearly. Although many manifold learning methods have been developed for such problems, most methods do not consider the spatial correlation between samples that is inherent and useful in remote sensing data. We propose a manifold learning method which directly combines the spatial proximity and the spectral similarity through kernel PCA framework. A gain factor caused by spatial proximity is first modelled with a heat kernel, and is added to the original similarity computed from the spectral values of a pair of samples. Parameters are tuned with intelligent grid search (IGS) method for the derived manifold coordinates to achieve optimal classification accuracies. Of particular interest is its performance with small training size, because labelled samples are usually scarce due to its high acquisition cost. The proposed spatial kernel PCA (KPCA) is compared with PCA in terms of classification accuracy with the nearest-neighbourhood classification method.

• 한국해양공학회지
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• 제35권5호
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• pp.382-392
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• 2021

In recent years, floating offshore wind turbines have attracted more attention as a new renewable energy resource while bottom-fixed offshore wind turbines reach their limit of water depth. Various projects have been proposed with the rapid increase in installed floating wind power capacity, but the economic aspect remains as a biggest issue. To figure out sensible approaches for saving costs, a comparison analysis of the levelized cost of electricity (LCOE) between floating and bottom-fixed offshore wind turbines was carried out. The LCOE was reviewed from a social perspective and a cost breakdown and a literature review analysis were used to itemize the costs into its various components in each level of power plant and system integration. The results show that the highest proportion in capital expenditure of a floating offshore wind turbine results in the substructure part, which is the main difference from a bottom-fixed wind turbine. A floating offshore wind turbine was found to have several advantages over a bottom-fixed wind turbine. Although a similarity in operation and maintenance cost structure is revealed, a floating wind turbine still has the benefit of being able to be maintained at a seaport. After emphasizing the cost-reduction advantages of a floating wind turbine, its LCOE outlook is provided to give a brief overview in the following years. Finally, some estimated cost drivers, such as economics of scale, wind turbine rating, a floater with mooring system, and grid connection cost, are outlined as proposals for floating wind LCOE reduction.

• 기술혁신연구
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• 제18권2호
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• pp.221-252
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• 2010

본 논문은 기술거래 네트워크와 기술거래 관리의 개념을 제시하고 기술도입자가 도입하고자 하는 기술을 제공하는 최적의 기술제공자를 선택하는 방법론을 제시하는데 목적이 있다. 기술거래 네트워크는 기술제공자, 기술마케터, 기술도입자로 구성되며 기술거래 관리는 기술평가, 기술거래, 기술사업화의 단계로 이루어진다. 기술거래 네트워크에서 기술의 연관도와 기술도입비용의 최적화방법을 통해 기술도입자가 도입하고자 하는 기술을 제공하는 최적의 기술제공자를 선택하는 방법론을 제시하며 이 방법은 기술도입자가 기술을 선택하는데 있어서 유용하게 사용될 것으로 기대된다. 기술제공자 선택 방법론은 기술평가 프로세스와 기술제공자 선택 프로세스로 구성된다. 기술평가 프로세스에서는 기술성에 중점을 둔 새로운 개념의 기술평가방법을 개발하여 기술연관도를 정량적으로 산출하였고 기술제공자 선택 프로세스에서는 기술도입에 따른 제반비용을 정의한 후 기술연관도가 최대가 되고 기술도입비용이 최소가 되는 수리모형을 목표계획법을 이용하여 설계하였다. 기술도입자의 요구조건에 대한 성능을 효과적으로 분석하기 위하여 하위기술 별로 방향성을 부여하여 기술네트워크를 각각 구성하였고 이를 효과적으로 목표계획법에 반영하였다. 사례분석에서는 차기전차 기술제공자 선택 사례를 분석하였다.

• Journal of Information Processing Systems
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• 제3권1호
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• pp.8-15
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• 2007

Grid environments provide the mechanism to share heterogeneous resources among nodes. Because of the similarity between grid environments and P2P networks, the structures of P2P networks can be adapted to enhance scalability and efficiency in deployment and to search for services. In this paper, we present a membership management based on a hierarchical ring which constructs P2P-like Grid environments. The proposed approach uses only a limited number of connections, reducing communication cost. Also, it only keeps local information for membership, which leads to a further reduction in management cost. This paper analyzes the performance of the approach by simulation and compares it with other approaches.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2009년도 학술대회
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• pp.590-595
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• 2009

인터넷 상의 웹 문서의 수가 기하급수적으로 늘어남에 따라서, 정보검색에서의 웹 문서 클러스터링은 성능과 속도가 매우 중요하게 되었다. 웹 문서 클러스터링은 의미적으로 관계가 있는 웹 문서들을 같은 클러스터로 군집함으로써 정보 검색을 보다 빠르고, 정보를 정확하게 제공할 수 있다. 그물망 그래프 형태의 클러스터링은 모든 문서간의 유사도를 측정함으로써 재현율을 높일 수 있지만, 높은 계산 비용을 갖는다. 본 논문에서는 그물망 형태의 클러스터링의 재현율과 정확율을 유지하며 계산 비용을 줄이기 위하여, 웹 문서의 구조적 특징인 하이퍼링크(Hyperlinks)를 이용한 클러스터링 방법을 제안한다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.376-376
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• 2000

Several algorithmic models have been proposed to estimate software cost and other management parameters. In particular, early prediction of completion time is absolutely essential for proper advance planning and a version of the possible ruin of a project. However, estimation is difficult because of its similarity to export judgment approaches and for its potential as an expert assistant in support of human judgment. Especially, the nature of the Norden/Rayleigh curve used by Putnam, renders it unreliable during the initial phases of the project, in projects involving a fast manpower buildup, as is the case with most software projects. Estimating software development effort is more complexity, because of infrastructure software related to target-machines hardware and process characteristics should be considered in software development for DCS (Distributed Control System). In this paper, we propose software development effort estimation technique using adaptive neural fuzzy inference system. The methods is applied to case-based projects and discussed.

• 한국산학기술학회:학술대회논문집
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• 한국산학기술학회 2003년도 Proceeding
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• pp.223-230
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• 2003

Feature-based similarity retrieval has become an important research issue in multimedia database systems. The features of multimedia data are useful for discriminating between multimedia objects (e 'g', documents, images, video, music score, etc.). For example, images are represented by their color histograms, texture vectors, and shape descriptors, and are usually high-dimensional data. The performance of conventional multidimensional data structures(e'g', R- Tree family, K-D-B tree, grid file, TV-tree) tends to deteriorate as the number of dimensions of feature vectors increases. The R＊-tree is the most successful variant of the R-tree. In this paper, we propose a SOM-based R＊-tree as a new indexing method for high-dimensional feature vectors.The SOM-based R＊-tree combines SOM and R＊-tree to achieve search performance more scalable to high dimensionalities. Self-Organizing Maps (SOMs) provide mapping from high-dimensional feature vectors onto a two dimensional space. The mapping preserves the topology of the feature vectors. The map is called a topological of the feature map, and preserves the mutual relationship (similarity) in the feature spaces of input data, clustering mutually similar feature vectors in neighboring nodes. Each node of the topological feature map holds a codebook vector. A best-matching-image-list. (BMIL) holds similar images that are closest to each codebook vector. In a topological feature map, there are empty nodes in which no image is classified. When we build an R＊-tree, we use codebook vectors of topological feature map which eliminates the empty nodes that cause unnecessary disk access and degrade retrieval performance. We experimentally compare the retrieval time cost of a SOM-based R＊-tree with that of an SOM and an R＊-tree using color feature vectors extracted from 40, 000 images. The result show that the SOM-based R＊-tree outperforms both the SOM and R＊-tree due to the reduction of the number of nodes required to build R＊-tree and retrieval time cost.

• 한국ITS학회 논문지
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• 제7권5호
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• pp.53-63
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• 2008

교본 연구는, 구간속도 검지를 위한 기존의 방법인 프로브차량 방식과 차량 번호판 인식 방식의 문제점을 보완할 수 있는 대안으로써, 도로 구간 시.종점에서의 차량 시퀀스 패턴을 이용하여 구간속도 검지가 가능토록 하는 알고리즘을 개발, 제시하였다. 본 알고리즘은 구간 시.종점에서의 차량들을 '차종 순차(Precedence)패턴을 순서대로 나열한 일정한 길이의 시퀀스 그룹'으로 인식하고, 종점에서의 특정 시퀀스에 대응하는, 시점에서의 시퀀스를 탐색하여 가장 유사도가 높은 시퀀스를 동일 그룹으로 간주하여 해당 구간의 통행 시간을 산출하였다. 유사도 비용의 정의에 따라 세 가지의 모델을 제시하였으며, 차량 유출입에 의한 이상치를 제거하고 가공함으로써 정보제공 주기에 가장 적합한 구간 대표 통행시간을 산출할 수 있도록 하였다. 컴퓨터 모의 실험을 통해 구간길이와 통과차량 수를 증가시키면서 차종별, 시.종점의 시퀀스 길이별로 반복 시뮬레이션 한 결과, 평균 최대 오차율 3.46%로서 현장 적용성에서 뛰어난 가능성을 보였다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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• pp.5-8
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• 2003

This paper presents a methodology to be able to select an appropriate RP system that suits the end use of a part. Evaluation factors used in process selection include major attributes such as accuracy, roughness, strength, elongation, part cost and build time that greatly affect the performance of RP systems. Crisp values such as accuracy and surface roughness are obtained with a new test part developed. The test part is designed with conjoint analysis to reflect users' preference. The part cost and build time that have approximate ranges due to cost and many variable parameters are presented by linguistic values that can be described with triangular fuzzy numbers. Based on the evaluation values obtained, an appropriate RP process for a specific part application is selected by using the modified TOPSIS(Technique of Order Preference by Similarity to Ideal Solution) method. It uses crisp data as well as linguistic variables, and each weight on the alternatives is assigned by using pair-wise comparison matrix. The ranking order helps the decision making of the selection of RP systems.