• Current Optics and Photonics
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• 제5권6호
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• pp.686-698
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• 2021

A camouflaged encryption scheme based on Hadamard matrix and ghost imaging is proposed. In the process of the encryption, an orthogonal matrix is used as the projection pattern of ghost imaging to improve the definition of the reconstructed images. The ciphertext of the secret image is constrained to the camouflaged image. The key of the camouflaged image is obtained by the method of sparse decomposition by principal component orthogonal basis and the constrained ciphertext. The information of the secret image is hidden into the information of the camouflaged image which can improve the security of the system. In the decryption process, the authorized user needs to extract the key of the secret image according to the obtained random sequences. The real encrypted information can be obtained. Otherwise, the obtained image is the camouflaged image. In order to verify the feasibility, security and robustness of the encryption system, binary images and gray-scale images are selected for simulation and experiment. The results show that the proposed encryption system simplifies the calculation process, and also improves the definition of the reconstructed images and the security of the encryption system.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.488-491
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• 1997

The PMGS(Plant Model Generating System) was developed based on modular modeling method and fluid network calculation concept. Fluid network calculation is used as a method of real-time computation of fluid network, and the module which has a topology with node and branch is defined to take advantages of modular modeling. Also, the database which have a shared memory as an instance is designed to manage simulation data in real-time. The applicability of the PMGS was examined implementing the HRSG(Heat Recovery Steam Generator) control logic on DCS.

• 전기의세계
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• 제23권3호
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• pp.70-76
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• 1974

Computer is used to analyze nonlinear networks. Integrated circuits and new nonlinear elements have generated much interest in nonlinear circuit theory. A key to the understanding and analysis of nonlinear circuits is the study of characteristics for nonlinear elements and nonlinear resistive networks both in theory and in computation. In this apper, an iteration method using cut set analysis for nonlinear dc analysis based on Branin's method is described. Application of this algorithm to solve two nonlinear problems, is presented and a possible method of improving the basic algorithm by means of a sparse matrix technique is described.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2008년도 추계학술대회논문집
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• pp.545-560
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• 2008

O Source import ㅁDirect import form Nastran, ANSYS ㅁDirect import of all the RPM from the files containing the structural results O Solver ㅁDirect computation of all RPM (multiple load case): one matrix resolution with multiple RHS ㅁEfficient solvers (MUMPS, SPARSE, Iterative) ㅁFrequency parallelisms available for very large problems O In practice ㅁSmall problems run on a desktop ㅁLarge problems can exceed 3kHz on a car engine O Easy to mesh ㅁ3D model created in a few minutes thanks to the unequal meshes. O And all Actran standard features

• 대한전기학회:학술대회논문집
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• 대한전기학회 1989년도 추계학술대회 논문집 학회본부
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• pp.176-179
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• 1989

Newton's OPF algorithm, for each iteration, solves with second order approximation of Lagraqngian function and sparse matrix technique. When load model is applied to this technique, load voltages have tendency to be fixed at lower limit. It makes the solution inadequte. In this paper, reference bus voltage specification technique suggested to make adequate load voltage. This method is verified useful 6-bus Ward-Hale sample system.

• 대한수학회논문집
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• 제9권2호
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• pp.449-465
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• 1994

The two common numerical methods to approximate the solution of partial differential equations are the finite element method and the finite difference method. They both lead to solving large sparse linear systems. For many applications, it is not unusal that the order of matrix is greater than 10, 000. For this kind of problem, a direct method such as Gaussian elimination can not be used because of the prohibitive cost. To this end, many iterative methods with modest cost have been studied and proposed by numerical analysts.(omitted)

• KIEE International Transactions on Power Engineering
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• 제2A권4호
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• pp.145-152
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• 2002

This paper illustrates applications of the Component Object Model (COM) for power system software developments. As an integral part of Microsoft's component services, COM has gained increased popularity for developing enterprise applications. This paper illustrates the concepts of COM and the latest developments as well as the available tools for developing COM components. Possible COM applications for developing power system software, such as sparse matrix manipulation, fault location, genetic algorithm applications, and so on. are presented. Advantages and promises brought about by COM are manifested through these examples.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2013년도 전력전자학술대회 논문집
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• pp.84-85
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• 2013

본 논문은 스파스 매트릭스 컨버터로 구동되는 유도전동기에 과도응답특성 개선을 위한 모델예측제어 기법을 제안한다. 제안하는 기법은 유도전동기의 파라미터를 이용하여 구한 예측 토크와 자속을 통하여 비용함수를 최소화하는 최적의 스위칭 상태를 결정한다. 시뮬레이션을 통해 제안한 제어 기법의 타당성을 검증한다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2003년도 가을 학술발표논문집 Vol.30 No.2 (1)
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• pp.4-6
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• 2003

A holistic representation, such as sparse ceding or independent component analysis (ICA), was successfully applied to explain early auditory processing and sound classification. In contrast, Part-based representation is an alternative way of understanding object recognition in brain. In this paper. we employ the non-negative matrix factorization (NMF)［1］which learns parts-based representation for sound classification. Feature extraction methods from spectrogram using NMF are explained. Experimental results show that NMF-based features improve the performance of sound classification over ICA-based features.

• Journal of Electrical Engineering and information Science
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• 제1권2호
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• pp.125-133
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• 1996

In this paper, we dicuss on the properties related to the circular filtering in orthogonal transform domain. The efficient filtering schemes in six orthogonal transform domains are presented by generalizing the convolution-multiplication property of the DFT. In brief, the circular filtering can be accomplished by multiplying the transform domain filtering matrix W, which is shown to be very sparse, yielding the computational gains compared with the time domain processing. As an application, decimation and interpolation techniques in orthogonal transform domains are also investigated.