• 산업공학
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• 제22권4호
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• pp.336-346
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• 2009

One of primary assumptions on DEA is that all DMUs for evaluation should be homogeneous. In comparative analysis among DMUs with relative efficiency measurement, it should be evaluated under identical conditions by ruling out external environmental influences. In this study, a measurement of innovation efficiency using the three-stage approach is performed. The approach employs DEA to measure relative efficiency and Tobit regressions to control external variables affecting innovation activity. The approach applied to firms in Korean Innovation Survey: Service Sector 2003 and 2006. Final efficiency scores of the approach represent net efficiency of the innovation. This study found that there is a increasing on technical efficiency of third stage, and it has difference with first stage significantly. Besides, a decrease on standard deviation of third stage is found. It means DMUs biased lower due to unfavorable condition and ones biased higher due to favorable condition are fallen into an identical operating environment through the approach. A measurement of net efficiency, excluding external effects, ensures the homogeneity of DMUs so that improves the reliability in terms of its analysis results. This study is expected to provide a direction and to be a valuable reference to further evaluation of innovation performance in Korean service sector.

• 한국생산제조학회지
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• 제19권4호
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• pp.469-475
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• 2010

The objective of this study is to integrate reliability analysis into shape optimization problem using the evolutionary structural optimization (ESO) in the application example. Reliability-based shape optimization is formulated as volume minimization problem with probabilistic stress constraint under minimization max. von Mises stress and allow stress. Young's modulus, external load and thickness are considered as uncertain variables. In order to compute reliability index, four methods, i.e., reliability index approach (RIA), performance measure approach (PMA), single-loop singlevector (SLSV) and adaptive-loop (ADL), are used. Reliability-based shape optimization design process is conducted to obtain optimal shape satisfying max. von Mises stress and reliability index constraints with the above four methods, and then each result is compared with respect to numerical stability and computing time.

• 기술혁신학회지
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• 제1권2호
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• pp.220-230
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• 1998

Recent concerns over national and corporate competitiveness have stimulated a renewed interest in organization's performance. The organization's performance primarily depends on resources including human resources, budget, physical based resources, and so on. Especially because the relationship between organization's performance ;md individual capabilities is more evident in R & D organizations where the knowledge base is embodied in people, there has taken an increasing interest in the methodologies for measuring the capabilities of R & D personnel. This paper presents new methodological approach to measure the capabilities of R & D personnel. And the model is empirically applied to ETRI, a public R & D organization in Korea. On the basis of the results, the implications for R & D management are discussed, with regard to R & D business and human resources management.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2017년도 추계학술대회
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• pp.199-200
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• 2017

eLoran 테스트베드의 국제적 요구성능을 충족하기 위해서는 선박 입출항 항로의 ASF 측정뿐만 아니라 보정정보의 제공을 통해 사용자의 위치정확도를 개선시켜야 한다. 항만을 입출항하는 선박의 항법요구 성능인 국제해사기구(IMO)의 HEA (Harbor Entrance and Approach) 요구성능은 10미터 이내의 측위정확도를 요구하고 있다. 그러므로 본 논문에서는 eLoran 테스트베드 내에서 신규 송신국 및 보정기준국(Differential Loran Station)의 위치에 따른 IMO HEA 측위정확도 성능 도달 가능성에 대해 시뮬레이션을 통해 예측해 본다.

• International Journal of Control, Automation, and Systems
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• 제4권4호
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• pp.438-447
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• 2006

Fuzzy controller's design depends mainly on the rule base and membership functions over the controller's input and output ranges. This paper presents two different approaches to deal with these design issues. A simple and efficient approach; namely, Fuzzy Subtractive Clustering is used to identify the rule base needed to realize Fuzzy PI and PD type controllers. This technique provides a mechanism to obtain the reduced rule set covering the whole input/output space as well as membership functions for each input variable. But it is found that some membership functions projected from different clusters have high degree of similarity. The number of membership functions of each input variable is then reduced using a similarity measure. In this paper, the fuzzy subtractive clustering approach is shown to reduce 49 rules to 8 rules and number of membership functions to 4 and 6 for input variables (error and change in error) maintaining almost the same level of performance. Simulation on a wide range of linear and nonlinear processes is carried out and results are compared with fuzzy PI and PD type controllers without clustering in terms of several performance measures such as peak overshoot, settling time, rise time, integral absolute error (IAE) and integral-of-time multiplied absolute error (ITAE) and in each case the proposed schemes shows an identical performance.

• 한국측량학회지
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• 제30권6_2호
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• pp.665-672
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• 2012

Amid rapidly increasing imagery inputs and their volume in a remote sensing imagery database, Content-Based Image Retrieval (CBIR) is an effective tool to search for an image feature or image content of interest a user wants to retrieve. It seeks to capture salient features from a 'query' image, and then to locate other instances of image region having similar features elsewhere in the image database. For a CBIR approach that uses texture as a primary feature primitive, designing a texture descriptor to better represent image contents is a key to improve CBIR results. For this purpose, an extended feature vector combining the Gabor filter and co-occurrence histogram method is suggested and evaluated for quantitywise and qualitywise retrieval performance criterion. For the better CBIR performance, assessing similarity between high dimensional feature vectors is also a challenging issue. Therefore a number of distance metrics (i.e. L1 and L2 norm) is tried to measure closeness between two feature vectors, and its impact on retrieval result is analyzed. In this paper, experimental results are presented with several CBIR samples. The current results show that 1) the overall retrieval quantity and quality is improved by combining two types of feature vectors, 2) some feature is better retrieved by a specific feature vector, and 3) retrieval result quality (i.e. ranking of retrieved image tiles) is sensitive to an adopted similarity metric when the extended feature vector is employed.

• 한국산업경영시스템학회:학술대회논문집
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• 한국산업경영시스템학회 2002년도 춘계학술대회
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• pp.125-132
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• 2002

We study clustering algorithm for sequences of categorical values. Clustering is a data mining problem that has received significant attention by the database community. Traditional clustering algorlthms deal with numerical or categorical data points. However, there exist many important databases that store categorical data sequences. In this paper we introduce new similarity measure and develope a hierarchical clustering algorithm. An experimental section shows performance of the proposed approach.

• Journal of the Korean Data and Information Science Society
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• 제5권2호
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• pp.59-74
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• 1994

The hazard ratio may be useful as a descriptive measure to compare the hazard experience of a treatment group with that of a control group. In this paper, we propose a kernel estimator of hazard ratio with censored survival data. The uniform consistency and asymptotic normality of the proposed estimator are proved by using counting process approach. In order to assess the performance of the proposed estimator, we compare the kernel estimator with Cox estimator and the generalized rank estimators of hazard ratio in terms of MSE by Monte Carlo simulation.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 하계종합학술대회논문집
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• pp.689-692
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• 1998

Matching two images is an essential step for many computer vision applications. A new approach to the scale and rotation invariant scene matching is presented. A set of andidate parameters are hypthesized by mapping the angular difference and a new distance measure to the hough space and by detecting maximally consistent points. The proposed method is shown to be much faster than the conventinal one where the relaxation process is repeated until convergence, while providing robust matching performance, without a priori information on the geometrical transformation parameters.

• 산업경영시스템학회지
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• 제26권1호
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• pp.17-21
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• 2003

We study clustering algorithm for sequences of categorical values. Clustering is a data mining problem that has received significant attention by the database community. Traditional clustering algorithms deal with numerical or categorical data points. However, there exist many important databases that store categorical data sequences. In this paper, we introduce new similarity measure and develop a hierarchical clustering algorithm. An experimental section shows performance of the proposed approach.