• 대한전기학회논문지
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• 제38권10호
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• pp.805-810
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• 1989

This paper presents a method for planning reactive power compensation such as shunt capacitors and reacters so as to maintain bus voltage in acceptable range during steady state operation in power system. The algorithm in this paper decomposes the problem into reactive power planning module for the compensation of bus voltage and load flow module for adjusting the error resulted from the linear approximation. A planning technique is based on linear programming to minimize the amount of added reactive power compensation in each case. Transformer tap settings and generator voltages are adjusted to minimize the compensation. The constraints are the operation limits of the control variables and bus voltages. The result of one sample system is presented to confirm the practical use of the proposed algorithm.

• 대한전기학회논문지
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• 제33권10호
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• pp.396-401
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• 1984

This paper present a method of using simplified models for deriving suboptimal controllers to the original higher-order systems. Routh approximation method is a very useful technique for reducing the order of a linear systems. This method dose not require a knowlege of system eigenvalues and eigenvectors and possesses many desirable features such as preservation of reduced order model stability and minimum computational requirements. These properties are utilized to derive suboptimal controllers in this paper. In order to implement htese ocntrollers on the original system, the relationship between the state vectors of the original system and the reduced order models is required. A procedure fir evaluating an approximate aggregation matrix is also developed. A numerical example is given for the illustration of this method, shich is compared with the existing Model aggregation method in the resultant figures.

• 대한의용생체공학회:의공학회지
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• 제12권2호
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• pp.121-130
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• 1991

This paper presents a QRS recognition algorithm using attribute grammar and its interpreter. This system extracts primitive and their attributes by linear approximation technique and then represented linguistic formation using attribute grammar. These nonterminals and their attributes are evaluated by attribute grammar interpreter. The performance of the QRS recognition algorithm has been evaluated using arrhythmia simulator and CSE ECG library.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2005년도 전기학술대회논문집
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• pp.257-261
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• 2005

The helicopter system is non-linear and complex. Futhermore, because of absence of accurate mathematical model, it is difficult accurately to control its attitude. therefore, we propose a WAVENET control technique to control efficiently its elevation angle and azimuth one. Wavelet neural network(WAVENET) can construct systematically initial neural network as applying wavelet theory to feedforward network. It is proved through computer simulation that WAVENET has more excellent approximation capability than existing neural network. The simulation results using MATLAB are introduced.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.638-640
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• 1998

This paper discusses approximation modelling of discrete-time linear time-varying system(LTVS). The wavelet theory and genetic algorithm are considered as a tool for representing and approximating a LTVS. The joint time-frequency properties of wave analysis are appropriate for describing the LTVS. Simulation results is included to illustrate the potential application of the technique.

• 산업경영시스템학회지
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• 제22권51호
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• pp.99-108
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• 1999

B-ISDN link dimensioning is often known as a difficult problem because of the characteristics of Asynchronous Transfer Mode(ATM) such as various Quality of Services of different service requirements, and the statistical multiplexing resulting from virtual path/virtual circuit connections. In this paper, we propose a nonlinear integer optimization model for dimensioning B-ISDN considering the statistical multiplexing effects of virtual path connections(VPCs) and the modularity of resources allocated to a transmission link. The algorithm based on the simultaneous linear approximation technique as well as some numerical results will be also presented.

• 대한조선학회논문집
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• 제42권5호
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• pp.534-541
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• 2005

Until now, Korean shipyards have accumulated a great amount of data. But they do not have appropriate tools to utilize the data in practical works. Engineering data contains experts' experience and know-how in its own. It is very useful to extract knowledge or information from the accumulated existing data by using data mining technique This paper treats an evolutionary computation based on genetic programming (GP), which can be one of the components to realize data mining. The paper deals with linear models of GP for the regression or approximation problem when given learning samples are not sufficient. The linear model, which is a function of unknown parameters, is built through extracting all possible base functions from the standard GP tree by utilizing the symbolic processing algorithm. In addition to a standard linear model consisting of mathematic functions, one variant form of a linear model, which can be built using low order Taylor series and can be converted into the standard form of a polynomial, is considered in this paper. The suggested model can be utilized as a designing tool to predict design parameters with small accumulated data.

• Structural Engineering and Mechanics
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• 제45권1호
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• pp.95-110
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• 2013

In the recent decade, practical of wavelet technique is being utilized in various domain of science. Particularly, engineers are interested to the wavelet solution method in the time series analysis. Fundamentally, seismic responses of structures against time history loading such as an earthquake, illustrates optimum capability of systems. In this paper, a procedure using particularly discrete Haar wavelet basis functions is introduced, to solve dynamic equation of motion. In the proposed approach, a straightforward formulation in a fluent manner is derived from the approximation of the displacements. For this purpose, Haar operational matrix is derived and applied in the dynamic analysis. It's free-scaled matrix converts differential equation of motion to the algebraic equations. It is shown that accuracy of dynamic responses relies on, access of load in the first step, before piecewise analysis added to the technique of equation solver in the last step for large scale of wavelet. To demonstrate the effectiveness of this scheme, improved formulations are extended to the linear and nonlinear structural dynamic analysis. The validity and effectiveness of the developed method is verified with three examples. The results were compared with those from the numerical methods such as Duhamel integration, Runge-Kutta and Wilson-${\theta}$ method.

• Investigative Magnetic Resonance Imaging
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• 제20권4호
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• pp.215-223
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• 2016

Purpose: The management of metal-induced field inhomogeneities is one of the major concerns of distortion-free magnetic resonance images near metallic implants. The recently proposed method called "Slice Encoding for Metal Artifact Correction (SEMAC)" is an effective spin echo pulse sequence of magnetic resonance imaging (MRI) near metallic implants. However, as SEMAC uses the noisy resolved data elements, SEMAC images can have a major problem for improving the signal-to-noise ratio (SNR) without compromising the correction of metal artifacts. To address that issue, this paper presents a novel reconstruction technique for providing an improvement of the SNR in SEMAC images without sacrificing the correction of metal artifacts. Materials and Methods: Low-rank approximation in each coil image is first performed to suppress the noise in the slice direction, because the signal is highly correlated between SEMAC-encoded slices. Secondly, SEMAC images are reconstructed by the best linear unbiased estimator (BLUE), also known as Gauss-Markov or weighted least squares. Noise levels and correlation in the receiver channels are considered for the sake of SNR optimization. To this end, since distorted excitation profiles are sparse, $l_1$ minimization performs well in recovering the sparse distorted excitation profiles and the sparse modeling of our approach offers excellent correction of metal-induced distortions. Results: Three images reconstructed using SEMAC, SEMAC with the conventional two-step noise reduction, and the proposed image denoising for metal MRI exploiting sparsity and low rank approximation algorithm were compared. The proposed algorithm outperformed two methods and produced 119% SNR better than SEMAC and 89% SNR better than SEMAC with the conventional two-step noise reduction. Conclusion: We successfully demonstrated that the proposed, novel algorithm for SEMAC, if compared with conventional de-noising methods, substantially improves SNR and reduces artifacts.

• 대한기계학회논문집A
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• 제35권8호
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• pp.921-931
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• 2011

본 연구는 B-스플라인 하이퍼볼륨을 사용하여 주어진 비정렬 데이터를 근사화하는 데이터 근사기법에 관한 것이다. 개발 구현을 위한 B-스플라인 하이퍼볼륨의 자료 구조가 기술되며 해당 메모리 크기의 측정을 통해 간결한 표현 모델임을 보인다. 제안하는 근사 기법은 두 가지 알고리즘으로 구성된다. 하나는 B-스플라인 하이퍼볼륨의 절점 벡터 결정에 관한 것이고, 다른 하나는 조정점 결정에 관한 것으로 최소자승 최소화 문제의 해를 구함으로써 얻게 된다. 여기서 구한 해는 데이터 복잡성에 의존하지 않는다. 본 연구 방식은 다양한 형태의 데이터 분포를 가지고 근사 정밀도, 메모리 사용량, 계산 시간 등의 근사화 성능(수준)을 평가한다. 더불어 기존 방법과의 비교를 통해 유용성을 보이며, 비구속 최적화 예제를 통하여 다양한 응용 분야로의 가능성을 보여준다.