• 대한전자공학회논문지
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• 제22권2호
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• pp.82-89
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• 1985

MCO 문제의 해석을 하기 위한 weight P-norm방법을 연구하여 새로운 non-inferior해를 구하였다. Weight 최소화방법을 MOSFET NAND 게이트에 적용하여 최적 non-inferior해를 구하였다. 또한 본 논문에서 응용한 최소화방법은 목적함수가 non-convex일때도 적용된다. 본 논문의 최소화 방법의 결과를 Lightner의 결과와 비교하여 효율성을 입증하였다.

• 한국CDE학회논문집
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• 제17권4호
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• pp.282-293
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• 2012

This paper presents an error-bounded B-spline fitting technique to approximate unorganized data within a prescribed error tolerance. The proposed approach includes two main steps: leastsquares minimization and error-bounded approximation. A B-spline hypervolume is first described as a data representation model, which includes its mathematical definition and the data structure for implementation. Then we present the least-squares minimization technique for the generation of an approximate B-spline model from the given data set, which provides a unique solution to the problem: overdetermined, underdetermined, or ill-conditioned problem. We also explain an algorithm for the error-bounded approximation which recursively refines the initial base model obtained from the least-squares minimization until the Euclidean distance between the model and the given data is within the given error tolerance. The proposed approach is demonstrated with some examples to show its usefulness and a good possibility for various applications.

• 한국CDE학회논문집
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• 제17권4호
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• pp.246-252
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• 2012

The piping route of hydraulic hose is designed with avoiding interferences to surrounding components. However, in a real practice, the piping route is mostly decided with an expert's experiences on site due to the complexity of design. Thus, this paper proposes a design methodology of the optimized route of a hose. We use NURBS representation to describe the piping route, which is possible to be locally modified, and an energy minimization method is applied to avoid interferences to the surroundings. In other words, the NURBS curve describing a piping route is modified to meet the desired positions from minimizing the perturbation of the control points, and the strain energy of the curve is then optimized to make the curve natural. The proposed method is implemented and its feasibility is validated using the commercial CAD software, CATIA V5.

• 대한전기학회논문지:전력기술부문A
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• 제48권7호
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• pp.863-871
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• 1999

While Logic Based Expert System (LBES) has a merit of rapid and complete inference, it also has a defect of huge knowledge base. Hierarchical LBES (HLBES) replaces the assertion time inference of LBES with the multi-level logic minimization procedure, and it guarantees smaller knowledge base comparing with LBES. This paper has two contributions. The one is proposing so-called fact-minimization procedure which reduces not only the number of facts or measured events but also the size of knowledge base dramatically. The other contribution is application of HLBES and the proposed fact-minimization to the fault diagnosis of power system. The application is successfully performed in the example with the transmission system which takes 72 goals and 352 facts.

• 대한전자공학회논문지
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• 제27권7호
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• pp.997-1004
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• 1990

In this paper, a design method of a robust adaptive regulator with feedfoward path based on the explicit criterion minimization is proposed. The convergence speed of parameter estimation is improved by using the stochastic Newton minimization method in the criterion minimization algorithm, and sensitivity derivatives are used in the regulator calculation for improving the robustness of the control system. Trh proposed adaptive regulator is applied to the stable minimum-phase and nonminimum-phase system, the results are shown that control performance and disturbance compensation ability of the regulator are improved. And the choosing method of input penalty is proposed.

• KIEE International Transactions on Power Engineering
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• 제12A권1호
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• pp.31-35
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• 2002

This paper presents a new operation scheme of UPFC to minimize both generation costs and active power losses in a normal operation state of power system. In a normal operation, cost minimization is a matter of primary concern among operating objectives. This paper considers two kinds of costs, generation costs and transmission losses. The total generation cost of active powers can be minimized by optimal power flow, and active power losses in the transmission system can be also minimized by power flow control of UPFC incorporated with minimization of generation costs. In order to determine amounts of active power reference of each UPFC required for the cost minimization, an iterative optimization algorithm based on the power flow calculation using the decoupled UPFC model is proposed. For verification of the proposed method, intensive studies have been performed on a 3-unit 6-bus system equipped with a UPFC.

• 한국정보전자통신기술학회논문지
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• 제12권5호
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• pp.521-528
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• 2019

Epilepsy is one of the most prevalent neurological diseases. Electroencephalogram (EEG) signals are widely used for monitoring and diagnosis tool for epileptic seizure. Typically, a huge amount of EEG signals is needed, where they are visually examined by experienced clinicians. In this study, we propose a simple automatic seizure detection framework using intracranial EEG signals. We suggest a sparse approximation based classification (SAC) scheme by solving overdetermined system. L1-norm minimization algorithms are utilized for efficient sparse signal recovery. For evaluation of the proposed scheme, the public EEG dataset obtained by five healthy subjects and five epileptic patients is utilized. The results show that the proposed fast L1-norm minimization based SAC methods achieve the 99.5% classification accuracy which is 1% improved result than the conventional L2 norm based method with negligibly increased execution time (42msec).

• International journal of advanced smart convergence
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• 제13권2호
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• pp.88-93
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• 2024

The main problem with existing edge detection techniques is that they have many limitations in detecting edges for complex and diverse images that exist in the real world. This is because only edges of a defined shape are discovered based on an accurate definition of the edge. One of the methods to solve this problem is the cost minimization method. In the cost minimization method, cost elements and cost functions are defined and used. The cost function calculates the cost for the candidate edge model generated according to the candidate edge generation strategy, and if the cost is found to be satisfactory, the candidate edge model becomes the edge for the image. In this study, we proposed an enhanced candidate edge generation strategy to discover edges for more diverse types of images in order to improve the shortcoming of the cost minimization method, which is that it only discovers edges of a defined type. As a result, improved edge detection results were confirmed.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 춘계학술대회 논문집
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• pp.1251-1252
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• 2010

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 춘계학술대회 논문집
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• pp.843-844
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• 2010