• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2003.11a
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• pp.69-76
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• 2003

In this paper, a novel speed control system that implements the fuzzy logic controller(FLC) is proposed. Fuzzy controller is shown more excellent efficency than a conventional controllers in the strength aspect and non-linear controller using IF-THEN rule which can control without process the accurate mathematical modeling about induction motor. But we cannot expect that conventional fuzzy controller divide equally the space of input and output parameter and use the certain shape of triangle membership function. Therefore to develop the efficiency of conventional fuzzy controller, We need to scale the range of membership functions. In this study, proposed fuzzy controller has the ability controlling scale of membership functions using by output scaling factor.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2292-2295
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• 2001

In this paper, The control problem for a series DC motor is considered to adaptive fuzzy sliding-mode control scheme. Based on a nonlinear mathematical model of a series connected DC motor, instead of the combination of a nonlinear transformation and state feedback(feedback linearization) reduces the nonlinear control design. To demonstrate its effectiveness, an experimental study of this controller is presented. Two sets of fuzzy rule bases are utilized to represent the equivalent control input with unknown system functions of the main target. The membership functions of the THEN-part, which is used to construct a suitable equivalent control of SMC, are changed according to the adaptive law. With such a design scheme, we not only maintain the distribution of membership functions over state space but also reduce computing time considerably.

• Tunnel and Underground Space
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• v.6 no.1
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• pp.10-18
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• 1996

Arched openings are generally excavated in underground construction works. Since stress distribution around openings depends on geological structure in rock mass, any shape of arched openings fully conformed with in-situ stress condition should be recommended to maintain mechanical safety of structures. Shape of arched openings is specified by both roof curvature and height-width ratio, and especially this report presents deformation behaviors related with roof curvature. Scale model tests and numerical studies of various shaped openings are conducted, where rectangular opening shows the greatest convergence. Through the anlayses of various arched opengings, as radius of roof curvature is increased, roof lowering and sidewall closure are remarkably increased, whereas floor heaving is increased little by little. By the way, it is useful that displacements of openings are roughly estimated in the stage of preliminary investigation. To find out elastic displacements of arched openings with any roof curvature, regressional formula and charts by least square method are represented. In addition elastoplastic deformation behavoirs of arched openings concerning associated adn non-associated flow rule are discussed.

• Nonlinear Functional Analysis and Applications
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• v.26 no.2
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• pp.347-371
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• 2021

A plethora of applications from mathematical programmings, such as minimax, mathematical programming, penalization and fixed point problems can be framed as variational inequality problems. Most of the methods that used to solve such problems involve iterative methods, that is why, in this paper, we introduce a new extragradient-like method to solve pseudomonotone variational inequalities in a real Hilbert space. The proposed method has the advantage of a variable step size rule that is updated for each iteration based on previous iterations. The main advantage of this method is that it operates without the previous knowledge of the Lipschitz constants of an operator. A strong convergence theorem for the proposed method is proved by letting the mild conditions on an operator 𝒢. Numerical experiments have been studied in order to validate the numerical performance of the proposed method and to compare it with existing methods.

• Nonlinear Functional Analysis and Applications
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• v.27 no.1
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• pp.1-22
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• 2022

The purpose of this research is to formulate a new proximal-type algorithm to solve the equilibrium problem in a real Hilbert space. A new algorithm is analogous to the famous two-step extragradient algorithm that was used to solve variational inequalities in the Hilbert spaces previously. The proposed iterative scheme uses a new step size rule based on local bifunction details instead of Lipschitz constants or any line search scheme. The strong convergence theorem for the proposed algorithm is well-proven by letting mild assumptions about the bifunction. Applications of these results are presented to solve the fixed point problems and the variational inequality problems. Finally, we discuss two test problems and computational performance is explicating to show the efficiency and effectiveness of the proposed algorithm.

• Communications for Statistical Applications and Methods
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• v.29 no.2
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• pp.193-202
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• 2022

Semi-supervised learning has gained significant attention in recent applications. In this article, we provide a selective overview of popular semi-supervised methods and then propose a simple but effective algorithm for semi-supervised classification using support vector machines (SVM), one of the most popular binary classifiers in a machine learning community. The idea is simple as follows. First, we apply the dimension reduction to the unlabeled observations and cluster them to assign labels on the reduced space. SVM is then employed to the combined set of labeled and unlabeled observations to construct a classification rule. The use of SVM enables us to extend it to the nonlinear counterpart via kernel trick. Our numerical experiments under various scenarios demonstrate that the proposed method is promising in semi-supervised classification.

• The Korean Journal of Air & Space Law and Policy
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• v.22 no.1
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• pp.105-123
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• 2007

The launching of the Taepo-dong 1 on 31 August 1998 by the North Korea was the first case where the diplomatic protests was made against the flight, the purpose of which, the launching State claimed, consisted in space exploration and use. It is the principle regarding the freedom of space exploration and use, as included in the international treaty, that is relevant in applying the various rules and in defining the legal status of the flight. Its legal status, however, was not actually taken into account, as political negotiations leading to the test moratorium has been successful until present day in freezing the political crisis. This implies that the rules of the law lack the validity and logic sufficient in dictating the conduct of the States. This case shows that, in effect, it is not the rule but the politics that is to govern the status of the flight.

• The Korean Journal of Air & Space Law and Policy
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• no.spc
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• pp.87-104
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• 2007

The launching of the Taepo-dong 1 on 31 August 1998 by the North Korea was the first case where the diplomatic protests was made against the flight, the purpose of which, the launching State claimed, consisted in space exploration and use. It is the principle regarding the freedom of space exploration and use, as included in the international treaty, that is relevant in applying the various rules and in defining the legal status of the flight. Its legal status, however, was not actually taken into account, as political negotiations leading to the test moratorium has been successful until present day in freezing the political crisis. This implies that the rules of the law lack the validity and logic sufficient in dictating the conduct of the States. This case shows that, in effect, it is not the rule but the politics that is to govern the status of the flight.

• Journal of Electrical Engineering and Technology
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• v.7 no.4
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• pp.636-645
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• 2012

This study introduces an information granular-based fuzzy radial basis function neural networks (FRBFNN) based on multiobjective optimization and weighted least square (WLS). An improved multiobjective space search algorithm (IMSSA) is proposed to optimize the FRBFNN. In the design of FRBFNN, the premise part of the rules is constructed with the aid of Fuzzy C-Means (FCM) clustering while the consequent part of the fuzzy rules is developed by using four types of polynomials, namely constant, linear, quadratic, and modified quadratic. Information granulation realized with C-Means clustering helps determine the initial values of the apex parameters of the membership function of the fuzzy neural network. To enhance the flexibility of neural network, we use the WLS learning to estimate the coefficients of the polynomials. In comparison with ordinary least square commonly used in the design of fuzzy radial basis function neural networks, WLS could come with a different type of the local model in each rule when dealing with the FRBFNN. Since the performance of the FRBFNN model is directly affected by some parameters such as e.g., the fuzzification coefficient used in the FCM, the number of rules and the orders of the polynomials present in the consequent parts of the rules, we carry out both structural as well as parametric optimization of the network. The proposed IMSSA that aims at the simultaneous minimization of complexity and the maximization of accuracy is exploited here to optimize the parameters of the model. Experimental results illustrate that the proposed neural network leads to better performance in comparison with some existing neurofuzzy models encountered in the literature.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.4 s.304
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• pp.43-50
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• 2005

This paper proposes a new pattern recognition system combining the new adaptive feature weighting based on the genetic algorithm and the modified KNN(K Nearest-Neighbor) rules. The new feature weighting proposed herein avoids the overfitting and finds the Proper feature weighting value by determining the middle value of weights using GA. New GA operators are introduced to obtain the high performance of the system. Moreover, a class dependent feature weighting strategy is employed. Whilst the classical methods use the same feature space for all classes, the Proposed method uses a different feature space for each class. The KNN rule is modified to estimate the class of test pattern using adaptive feature space. Experiments were performed with the unconstrained handwritten numeral database of Concordia University in Canada to show the performance of the proposed method.