• Korean Journal of Computational Design and Engineering
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• v.4 no.1
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• pp.32-42
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• 1999

Approximate lofting or skinning is one of practical surface modeling techniques well used in CAD and reverse engineering applications. Presented in this paper is a method for approximately lofting a given set of curves wihin a specified tolereance. It is based on refitting input curves simultaneously on a common knot vector and interpolating them to get a resultant NURBS surface. A concept of reducing the number of interior knots of the common knot vector is well adopted to acquire more compact representation for the resultant surface. Energy minimization is newly introduced in curve refitting process to stabilize the solution of the fitting problem and get more fair curve. The proposed approximate lofting provides more smooth surface models and realizes more efficient data reduction expecially when the parameterization and compatibility of input curves are not good enough. The method has been successfully implemented in a new CAD/CAM product VX Vision? of Varimetrix Corporation.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.9-17
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• 2017

This paper describes a process of developing commercial real time image recognition system with company. In this paper we will make a system that is combining an empirical kernel map method and conjugate least squares support vector machine in order to represent images in a low-dimensional subspace for real time image recognition. In the traditional approach calculating these eigenspace models, known as traditional PCA method, model must capture all the images needed to build the internal representation. Updating of the existing eigenspace is only possible when all the images must be kept in order to update the eigenspace, requiring a lot of storage capability. Proposed method allows discarding the acquired images immediately after the update. By experimental results we can show that empirical kernel map has similar accuracy compare to traditional batch way eigenspace method and more efficient in memory requirement than traditional one. This experimental result shows that proposed model is suitable for commercial real time image recognition system.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.754-759
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• 1992

In this paper, we proposed a mixed H$_{2}$/H$_{\infty}$ optimal controller design method using the parameterization of H$_{2}$ suboptimal controller. The method is based on the minimization of H$_{2}$ performance measure with an H$_{\infty}$-norm constraint. We also derived the necessary and sufficient conditions for existence of solution from the decoupled Riccati equations. And the designed controller has state-space representation.n.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.5
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• pp.624-629
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• 1998

Evolutionary computation techniques can solve search problems using simulated evolution based on the ‘survival of the fittest’. Recently, the genetic programming (GP) which evolves computer programs using the genetic algorithm was introduced. In this paper, the genetic programming technique is used in order to design a rule based controller consisting of condition-action rules for an unknown system. No a priori knowledge about the structure of the controller is needed. Representation of a solution, functions and terminals in GP are analyzed, and a method of constructing a fuzzy logic controller using the obtained rule based controller is described. A simulation example using a nonlinear system shows the validity and efficiency of the proposed method.

• Proceedings of the KSR Conference
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• 2001.10a
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• pp.329-334
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• 2001

This paper presents exact autotransformer-fed AC electric railroad system modeling using constant current mode. The theory is based on the solution of algebraic. The proposed modeling is considered the line self-impedances and mutual-impedances. Besides, the load modeling improved results are obtained as application to the proposed constant current mode. In the analysis on AT-fed AC electric railroad system circuit, a generalized analysis method using the loop equation on a case by case. the simulation objectives are to calculate the catenary and rail voltages with respect to ground, as the train moves along a section of line between two adjacent ATs. The model contains assumptions regarding the representation of the autotransformer, the impedance of the track/catenary system, and the grounding arrangements, which all effect the accuracy of the result. The modeling results seem very reasonable. It is established that techniques for the AC electric railroad system modeling and analysis.

• Journal of applied mathematics & informatics
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• v.19 no.1_2
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• pp.179-190
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• 2005

We deal with the Cauchy problem for the space-time fractional diffusion equation, which is obtained from standard diffusion equation by replacing the second-order space derivative with a Caputo (or Riemann-Liouville) derivative of order ${\beta}{\in}$ (0, 2] and the first-order time derivative with Caputo derivative of order ${\beta}{\in}$ (0, 1]. The fundamental solution (Green function) for the Cauchy problem is investigated with respect to its scaling and similarity properties, starting from its Fourier-Laplace representation. We derive explicit expression of the Green function. The Green function also can be interpreted as a spatial probability density function evolving in time. We further explain the similarity property by discussing the scale-invariance of the space-time fractional diffusion equation.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.47-47
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• 1989

This paper considers the parallel machines scheduling problem characterized as a multi-objective combinatorial problem. As this problem belongs to the NP-complete problem, genetic algorithms are applied instead of the traditional analytical approach. The purpose of this study is to show how the problem can be effectively solved by using genetic algorithms with a permutation approach. First, a permutation representation which can effectively represent the chromosome is introduced for this problem . Next, a schedule builder which employs the combination of scheduling theories and a simple heuristic approach is suggested. Finally, through the computer experiments of genetic algorithm to test problems, we show that the niche formation method does not contribute to getting better solutions and that the PMX crossover operator is the best among the selected four recombination operators at least for our problem in terms of both the performance of the solution and the operational convenience.

• Interdisciplinary Bio Central
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• v.3 no.3
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• pp.9.1-9.5
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• 2011

Entity Attribute Value (EAV) is the widely used solution to represent high dimensional and sparse data, but EAV is not search efficient for knowledge extraction. In this paper, we have proposed a search efficient data model: Optimized Entity Attribute Value (OEAV) for physical representation of high dimensional and sparse data as an alternative of widely used EAV. We have implemented both EAV and OEAV models in a data warehousing en-vironment and performed different relational and warehouse queries on both the models. The experimental results show that OEAV is dramatically search efficient and occupy less storage space compared to EAV.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.85-89
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• 2007

Many authors considered the computational aspect of sup-min convolution when applied to weighted average operations. They used a computational algorithm based on a-cut representation of fuzzy sets, nonlinear programming implementation of the extension principle, and interval analysis. It is well known that $T_W$(the weakest t-norm)-based addition and multiplication preserve the shape of L-R type fuzzy numbers. In this paper, we consider the computational aspect of the extension principle by the use of $T_W$ when the principle is applied to fuzzy weighted average operations. We give the exact solution for the case where variables and coefficients are L-L fuzzy numbers without programming or the aid of computer resources.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.280-280
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• 2000

In this paper, we propose a method of constructing equation using bio-inspired emergent and evolutionary concepts. This method is algorithm that is based on the characteristics of the biological DNA and growth of plants. Here is. we propose a constructing method to make a DNA coding method for production rule of L-system. L-system is based on so-called the parallel rewriting mechanism. The DNA coding method has no limitation in expressing the production rule of L-system. Evolutionary algorithms motivated by Darwinian natural selection are population based searching methods and the high performance of which is highly dependent on the representation of solution space. In order to verify the effectiveness of our scheme, we apply it to one step ahead prediction of Mackey-Glass time series.