• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.67.6-67
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• 2001

In this paper, we present an attitude control of self-standing for a two-wheeled inverted-pendulum-like mobile robot based on the nonlinear control theory. Nonlinear dynamic equations are linearized by using the Lie derivative, and a pole placement controller is designed. Characteristics of the controller are examined by numerical simulations to show the self-standing attitude of the mobile robot in standing and in moving.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.5
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• pp.850-856
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• 2001

Even though the hydraulic servo system has been widely used in industrial and military equipments since it has a lot of advantages, it is not easy to design controller due to the high nonlinearities and the parametric uncertainties. The dynamic behavior of the real process in the hydraulic servo system differs from that described by its model because the model is linearized. Another reason of the difference is caused by the variety of parameters, since the system parameters of the dynamic equation are affected by the operating conditions such as temperature and pressure. In this study, the designing process of the MRNC with a PID compensator is introduced and applied to the load sensing hydraulic servo system. The results show that the designed controller guarantees the robust control performance despite of both the nonlinearities and the parametric uncertainties.

• Journal of the Korean Mathematical Society
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• v.43 no.5
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• pp.1019-1045
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• 2006

As a natural generalization of a Sasakian space form, we define a contact strongly pseudo-convex CR-space form (of constant pseudo-holomorphic sectional curvature) by using the Tanaka-Webster connection, which is a canonical affine connection on a contact strongly pseudo-convex CR-manifold. In particular, we classify a contact strongly pseudo-convex CR-space form $(M,\;\eta,\;\varphi)$ with the pseudo-parallel structure operator $h(=1/2L\xi\varphi)$, and then we obtain the nice form of their curvature tensors in proving Schurtype theorem, where $L\xi$ denote the Lie derivative in the characteristic direction $\xi$.

• Bulletin of the Korean Mathematical Society
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• v.47 no.1
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• pp.1-15
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• 2010

Let M be a real hypersurface with almost contact metric structure $(\phi,g,\xi,\eta)$ in a complex space form $M_n(c)$, $c\neq0$. In this paper we prove that if $R_{\xi}L_{\xi}g=0$ holds on M, then M is a Hopf hypersurface in $M_n(c)$, where $R_{\xi}$ and $L_{\xi}$ denote the structure Jacobi operator and the operator of the Lie derivative with respect to the structure vector field $\xi$ respectively. We characterize such Hopf hypersurfaces of $M_n(c)$.

• Proceedings of the KSME Conference
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• 2004.04a
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• pp.497-502
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• 2004

This paper presents applications of the objective stress rates to stress update algorithms for transient shell dynamic analysis within the context of explicit time integration. The hypo elasto-plastic materials are assumed in establishing constitutive equations. The derivation of the objective stress rates are investigated by use of the Lie derivative. Comparison results are given between the Kirchhoff and Cauchy stress formulation. The Jacobian determination algorithm proposed in this paper is presented in association with the Belytschko-Lin-Tsay shell theory. Several numerical examples are demonstrated including contact and non-contact examples, by which proposed algorithms are compared with respect to the accuracy and effectiveness.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.24 no.4
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• pp.383-389
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• 2011

In this paper, a statistical calibration method is proposed in order to identify the variability of complex modulus for a rubber material due to operational temperature and experimental/model errors. To describe temperature- and frequency-dependent material properties, a fractional derivative model and a shift factor relationship are used. A likelihood function is defined as a product of the probability density functions where experimental values lie on the model. The variation of the fractional derivative model parameters is obtained by maximizing the likelihood function. Using the proposed method, the variability of a synthetic rubber material is estimated and applied to a rubber mount problem. The dynamic characteristics of the rubber mount are calculated using a finite element model of which material properties are sampled from Monte Carlo simulation. The calculated dynamic stiffnesses show very large variation.

• Bulletin of the Korean Mathematical Society
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• v.52 no.5
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• pp.1535-1547
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• 2015

A vector field on a Riemannian manifold (M, g) is called concircular if it satisfies ${\nabla}X^v={\mu}X$ for any vector X tangent to M, where ${\nabla}$ is the Levi-Civita connection and ${\mu}$ is a non-trivial function on M. A smooth vector field ${\xi}$ on a Riemannian manifold (M, g) is said to define a Ricci soliton if it satisfies the following Ricci soliton equation: $$\frac{1}{2}L_{\xi}g+Ric={\lambda}g$$, where $L_{\xi}g$ is the Lie-derivative of the metric tensor g with respect to ${\xi}$, Ric is the Ricci tensor of (M, g) and ${\lambda}$ is a constant. A Ricci soliton (M, g, ${\xi}$, ${\lambda}$) on a Riemannian manifold (M, g) is said to have concircular potential field if its potential field is a concircular vector field. In the first part of this paper we determine Riemannian manifolds which admit a concircular vector field. In the second part we classify Ricci solitons with concircular potential field. In the last part we prove some important properties of Ricci solitons on submanifolds of a Riemannian manifold equipped with a concircular vector field.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.