• Journal of Korean Institute of Industrial Engineers
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• v.13 no.2
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• pp.105-115
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• 1987

Although there are many theoretical methods for the transformation of random variables. it is difficult to find probability density functions for the new random variables because of the complexity in mathematics. The author developed a simulation model solving the above difficulties using FBI (Fortran Based Interpreter) routines. The FBI is a kind of language Interpreter analyzing the arithmetic statement in character data forms. In this paper. the FBI routines will be explained and the structure and applications of simulation model will be also demonstrated. Polynomial curve fitting method is applied to define the probability density function which can not be defined by well-known pdf. This program can also be used for instructing mathematical statistics and identifying distribution of the simulated data.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.494-498
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• 1996

Three fuzzy input space partitoining methods, which are grid, tree, and scatter method, are mainly used until now. These partition methods represent good performance in the modeling of the linear system and nonlinear system with independent modeling variables. But in the case of the nonlinear system with the coupled modeling variables, there should be many fuzzy rules for acquiring the exact fuzzy model. In this paper, it shows that the fuzzy model is acquired using transformed modeling vector by linear transformation of the modeling vector.

• Bulletin of the Korean Chemical Society
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• v.25 no.2
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• pp.285-288
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• 2004

A canonical transformation changes variables such as coordinates and momenta to new variables preserving either the Poisson bracket or the commutation relations depending on whether the problem is classical or quantal respectively. Classically canonical transformations are well established as a powerful tool for solving differential equations. Quantum canonical transformations have been defined and used relatively recently because of the non-commutativeness of the quantum variables. Three elementary canonical transformations and their composite transformations have quantum implementations. Quantum canonical transformations have been mostly used in time-independent Schrodinger equations and a harmonic oscillator with time-dependent angular frequency is probably the only time-dependent problem solved by these transformations. In this work, we apply quantum canonical transformations to a harmonic oscillator in which both angular frequency and equilibrium position are time-dependent.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.69-87
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• 2014

This paper suggests a conditional simulation framework based on multiple data transformations for geostatistical simulation of compositional data. First, log-ratio transformation is applied to original compositional data in order to apply conventional statistical methodologies. As for the next transformations that follow, minimum/maximum autocorrelation factors (MAF) and indicator transformations are sequentially applied. MAF transformation is applied to generate independent new variables and as a result, an independent simulation of individual variables can be applied. Indicator transformation is also applied to non-parametric conditional cumulative distribution function modeling of variables that do not follow multi-Gaussian random function models. Finally, inverse transformations are applied in the reverse order of those transformations that are applied. A case study with surface sediment compositions in tidal flats is carried out to illustrate the applicability of the presented simulation framework. All simulation results satisfied the constraints of compositional data and reproduced well the statistical characteristics of the sample data. Through surface sediment classification based on multiple simulation results of compositions, the probabilistic evaluation of classification results was possible, an evaluation unavailable in a conventional kriging approach. Therefore, it is expected that the presented simulation framework can be effectively applied to geostatistical simulation of various compositional data.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.11
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• pp.1601-1605
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• 2012

Three-phase voltage and current is applied to the three-phase alternating current motors which are commonly used in industry. Three phase variables of a, b, c are converted into d, q, 0 axis and the AC machines are modeled and analyzed. Basically the coordinate transformation or d-q transformation is used for convenience, a few steps are needed to analyze the motor performances - separating d and q components, establishing each equivalent circuit, and solving the differential equations of the circuits. In this study, a modeling technique of induction motor using complex vector is proposed and it can explain the induction motor physically. This method does not need the separating process of d and q components. With this technique, the model becomes simple, is easy to understand in physical, and can get the same results with those from the other models. These simulation results of the proposed model are compared with them for the conformation of the proposed method.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.27-34
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• 2004

The Horvitz-Thompson(H-T) estimator is less efficient than PPS estimators in some cases. We use the two-stage variable transformation in order to remove the drawbacks and increase the efficiency of H-T estimator. We transform the auxiliary variable to use the Midzuno-Sen sampling scheme at the first stage. And the next stage, we also transform the study variable to reduce the variance of H-T estimator using the inclusion probability obtained from the first transformation. We compare the efficiency between a suggested modified H-T estimator and PPS estimators.

• Journal of The Korean Association For Science Education
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• v.12 no.2
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• pp.31-42
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• 1992

The purposes of this study were to find out the degree of formation of the concept of density for the junior high students. The changing pattern of concept in acquiring the concept of density and the degree of development of INRC transformation ability related to the concept of density were also analyzed according to cognitive level and teaching method. The results of this study were as follows. 1) The experimental group were more effective than control group in the formation of the concept of density. 2) Even though students had been taught the concept of density, the various types of preconception were remained and persisted. Especially, the students at concrete level had persisted misconceptions and these misconceptions had been changed to the other misconceptions. 3) In the degree of the formation of the transformation ability of INRC group related to the concept of density in solid phase, the experimental group developed much better on both the abilities of Reciprocal transformation, Correlative transformation and the abilities to manipulate two variables such as volume and mass than control group. 4) The correlation coefficient between GALT score and achivement of the concept of density was 0.67. The correlation coefficient between achivement of the concept of density and the formation the transformation of INRC group related to the concept of density was 0.78.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.10
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• pp.1561-1570
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• 1997

This study explores the treatment of the max-value cost function over a parameter interval in parametric optimization. To avoid the computational burden of the transformation treatment using an artificial variable, a direct treatment of the original max-value cost function is proposed. It is theoretically shown that the transformation treatment results in demanding an additional equality constraint of dual variables as a part of the Kuhn-Tucker necessary conditions. Also, it is demonstrated that the usability and feasibility conditions on the search direction of the transformation treatment retard convergence rate. To investigate numerical performances of both treatments, typical optimization algorithms in ADS are employed to solve a min-max steady-state response optimization. All the algorithm tested reveal that the suggested direct treatment is more efficient and stable than the transformation treatment. Also, the better performing of the direct treatment over the transformation treatment is clearly shown by constrasting the convergence paths in the design space of the sample problem. Six min-max transient response optimization problems are also solved by using both treatments, and the comparisons of the results confirm that the performances of the direct treatment is better than those of the tranformation treatment.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.258-263
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• 2011

In the bilateral tele-operation system, time delay may be a critical problem. Even if system modeling error or time delay occurs, when applied to wave transformation system, the system's stability can be achieved. Using the characteristic b which is an important parameter of wave transformation, the system can display robust performance for time delay. However, since assuming and that the time delay was fixed developing a theory, a stability cannot be guaranteed about the time-varying delay. Therefore, In the paper, Therefore, in this paper, we studied for the method that controls this by applying the fuzzy algorithm which surveyed the timevarying delay characteristics and can adjust the b according to it adaptively.

• Journal of the Korean Data and Information Science Society
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• v.15 no.3
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• pp.617-624
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• 2004

In this article the fuzzy number rank and the fuzzy rank transformation method are introduced in order to analyse the non-parametric fuzzy regression model which cannot be described as a specific functional form such as the crisp data and fuzzy data as a independent and dependent variables respectively. The effectiveness of fuzzy rank transformation methods is compared with other methods through the numerical examples.