• 대한의용생체공학회:의공학회지
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• 제30권4호
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• pp.279-287
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• 2009

Magnetic resonance electrical impedance tomography (MREIT) is a new medical imaging modality providing cross-sectional images of a conductivity distribution inside an electrically conducting object. MREIT has rapidly progressed in its theory, algorithm and experimental technique and now reached the stage of in vivo animal and human experiments. Conductivity image reconstructions in MREIT require various steps of carefully implemented numerical computations. To facilitate MREIT research, there is a pressing need for an MREIT software package with an efficient user interface. In this paper, we present an example of such a software, called CoReHA which stands for conductivity reconstructor using harmonic algorithms. It offers various computational tools including preprocessing of MREIT data, identification of boundary geometry, electrode modeling, meshing and implementation of the finite element method. Conductivity image reconstruction methods based on the harmonic $B_z$ algorithm are used to produce cross-sectional conductivity images. After summarizing basics of MREIT theory and experimental method, we describe technical details of each data processing task for conductivity image reconstructions. We pay attention to pitfalls and cautions in their numerical implementations. The presented software will be useful to researchers in the field of MREIT for simulation as well as experimental studies.

• 산업기술연구
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• 제19권
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• pp.127-133
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• 1999

This paper is a research about system identification which optimizes uncertain geothechnical properties from the data measured during geotechnical design and construction. Various numerical optimization algorithms of Simplex method, Powell method, Rosenbrock method and Levenberg-Marquardt method were applied to the excavation problem to determine which method showed the best results with respect to robustness of success in finding an optimal solution to within a certain accuracy and number of function evaluations. From the results of numerical analysis, all of four algorithms are converged to exact solution after satisfying the allowed criteria, and Levenberg-Marquardt's algorithms was identified to be the most efficient method in number of function evaluations. System identification was applied to geotechnical engineering problems, possibly being occurred in field, to verify its applicability : estimation of settlement due to self-weight consolidation in dredged and filled soil. For self-weight consolidational settlement of a dredged soil, a program of evaluating the constitutive relationship of effective stress-void ratio-permeability was developed by using the technique of system identification. Thus, consolidational characteristics of a dredged soil, having a very high initial void ratio, can be evaluated.

• 대한안전경영과학회지
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• 제10권3호
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• pp.245-251
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• 2008

The research proposes three ANOVA(Analysis of Variance) tests using expected mean square(EMS) algorithms in various split-plot designs. The variance tests consist of Never-Pool test, Sometimes-Pool test and Always-Pool test. This paper also presents two EMS algorithms such as standard method and easy method. These algorithms are useful to make a decision rule for pooling. Numerical examples are illustrated for various split-plot designs such as split-plot designs, split-split-plot designs, repetition split-plot designs, and nested designs. Pragmatically, the results are summarized and compared with popular ANOVA spreadsheets and data model equations.

• 한국지능시스템학회논문지
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• 제14권2호
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• pp.247-252
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• 2004

In this paper are proposed 2nd-order PD-type iterative learning control algorithms for linear continuous-time system and linear discrete-time system. In contrast to conventional methods, the proposed learning algorithms are constructed based on both time-domain performance and iteration-domain performance. The convergence of the proposed learning algorithms is proved. Also, it is shown that the proposed method has robustness in the presence of external disturbances and the convergence accuracy can be improved. A numerical example is provided to show the effectiveness of the proposed algorithms.

• Management Science and Financial Engineering
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• 제18권1호
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• pp.13-20
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• 2012

This paper considers a revenue maximization problem on a single processor. Each job is identified as its processing time, initial reward, reward decreasing rate, and preferred start time. If the processor starts a job at time zero, revenue of the job is its initial reward. However, the revenue decreases linearly with the reward decreasing rate according to its processing start time till its preferred start time and finally its revenue is zero if it is started the processing after the preferred time. Our objective is to find the optimal sequence which maximizes the total revenue. For the problem, we characterize the optimal solution properties and prove the NP-hardness. Based upon the characterization, we develop a branch-and-bound algorithm for the optimal sequence and suggest five heuristic algorithms for efficient solutions. The numerical tests show that the characterized properties are useful for effective and efficient algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.525-525
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• 2000

In this paper, we present recursive algorithms for state space model identification using subspace extraction via Schur complement. It is shown that an estimate of the extended observability matrix can be obtained by subspace extraction via Schur complement. A relationship between the least squares residual and the Schur complement matrix obtained from input-output data is shown, and the recursive algorithms for the subspace-based state-space model identification (4SID) methods are developed. We also proposed the above algorithm for an instrumental variable (IV) based 4SID method. Finally, a numerical example of the application of the algorithms is illustrated.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.370-370
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• 2000

In this paper, we design a Multi-Fuzzy model by means of HCM clustering and genetic algorithms for a nonlinear system. In order to determine structure of the proposed Multi-Fuzzy model, HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy ate identified by genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy mode] and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

• 한국정밀공학회지
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• 제13권11호
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• pp.73-81
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• 1996

This paper presents a general procedure for the selection of the machining parameters for a given machine which provides the maximum material removal rate using a Genetic Algorithms(GAs). Some constraints were given in order to achieve desired surface integrity and cutting tool life conditions as wel as to protect machine tool. Such a constrained problem can be transformaed to unconstrained problem by associating a penalty with all constraint violations and the penalties are included in the function evaluation. Genetic Algorithms can be used for finding global optimum cutting conditions with respect to the above cost function transformed by pennalty function method. From the demonstration of the numerical results, it was found that the near optimal conditions could be obtained regardless of complex solution space such as cutting environment.

• Nonlinear Functional Analysis and Applications
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• 제29권2호
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• pp.307-332
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• 2024

Two inertial extragradient-type algorithms are introduced for solving convex pseudomonotone variational inequalities with fixed point problems, where the associated mapping for the fixed point is a 𝜌-demicontractive mapping. The algorithm employs variable step sizes that are updated at each iteration, based on certain previous iterates. One notable advantage of these algorithms is their ability to operate without prior knowledge of Lipschitz-type constants and without necessitating any line search procedures. The iterative sequence constructed demonstrates strong convergence to the common solution of the variational inequality and fixed point problem under standard assumptions. In-depth numerical applications are conducted to illustrate theoretical findings and to compare the proposed algorithms with existing approaches.

• 대한조선학회논문집
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• 제49권2호
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• pp.196-202
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• 2012

In this study, numerical analysis of viscous flows is carried out based on the unstructured grid. There exist some difficulties in expressing and computing numerical derivatives on the unstructured grid due to lack of the structured characteristics. The general computer algorithms are developed to perform numerical derivatives easily and extended to be applicable to various geometries composed of hybrid meshes. And the optimal method of strongly implicit procedure is newly contrived to accelerate the rate of convergence in solving the pressure Poisson equation. To verify numerical schemes, the driven cavity problems of 2 and 3 dimension are simulated. The numerical results are compared with others and our numerical schemes are shown to be valid.