• Geomechanics and Engineering
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• v.21 no.1
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• pp.85-93
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• 2020

In this article, the generalized thermoelastic theory with fractional derivative is presented to estimate the variation of temperature, the components of stress, the components of displacement and the changes in volume fraction field in two-dimensional porous media. Easily, the exact solutions in the Laplace domain are obtained. By using Laplace and Fourier transformations with the eigenvalues method, the physical quantities are obtained analytically. The numerical results for all the physical quantities considered are implemented and presented graphically. The results display that the present model with the fractional derivative is reduced to the Lord and Shulman (LS) and the classical dynamical coupled (CT) theories when the fractional parameter is equivalent to one and the delay time is equal to zero and respectively.

• Journal of the Korean Mathematical Society
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• v.58 no.1
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• pp.45-67
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• 2021

In this paper, a mathematical dynamical system involving both deterministic (with or without delay) and stochastic "SIR" epidemic model with nonlinear incidence rate in a continuous reactor is considered. A profound qualitative analysis is given. It is proved that, for both deterministic models, if ��d > 1, then the endemic equilibrium is globally asymptotically stable. However, if ��d ≤ 1, then the disease-free equilibrium is globally asymptotically stable. Concerning the stochastic model, the Feller's test combined with the canonical probability method were used in order to conclude on the long-time dynamics of the stochastic model. The results improve and extend the results obtained for the deterministic model in its both forms. It is proved that if ��s > 1, the disease is stochastically permanent with full probability. However, if ��s ≤ 1, then the disease dies out with full probability. Finally, some numerical tests are done in order to validate the obtained results.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.758-762
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• 1994

Complicated dynamical behavior can occur in model reference adaptive control systems when two external sinusoidal signals are introduced although the plant and reference model are stable linear first older systems. The phase portrait plot and the power spectral analysis indicate chaotic behavior. In the system treated, a positive Lyapuniov exponent and non-integer dimension clearly manifest chaotic nature of the system.

• Wind and Structures
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• v.7 no.4
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• pp.265-280
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• 2004

This paper presents some fundamental results on the dynamics of the periodic Karman wake behind a circular cylinder. The wake is treated like a dynamical system. External forcing is then introduced and its effect investigated. The main result obtained is the following. Perturbation of the wake, by controlled cylinder oscillations in the flow direction at a frequency equal to the Karman vortex shedding frequency, leads to instability of the Karman vortex structure. The resulting wake structure oscillates at half the original Karman vortex shedding frequency. For higher frequency excitation the primary pattern involves symmetry breaking of the initially shed symmetric vortex pairs. The Karman shedding phenomenon can be modeled by a nonlinear oscillator. The symmetrical flow perturbations resulting from the periodic cylinder excitation can also be similarly represented by a nonlinear oscillator. The oscillators represent two flow modes. By considering these two nonlinear oscillators, one having inline shedding symmetry and the other having the Karman wake spatio-temporal symmetry, the possible symmetries of subsequent flow perturbations resulting from the modal interaction are determined. A theoretical analysis based on symmetry (group) theory is presented. The analysis confirms the occurrence of a period-doubling instability, which is responsible for the frequency halving phenomenon observed in the experiments. Finally it is remarked that the present findings have important implications for vortex shedding control. Perturbations in the inflow direction introduce 'control' of the Karman wake by inducing a bifurcation which forces the transfer of energy to a lower frequency which is far from the original Karman frequency.

• Journal of Biomedical Engineering Research
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• v.13 no.3
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• pp.181-188
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• 1992

This paper provides an overview of system analysis of immunology. The theoretical research in this area is aimed at an understanding of the precise manner by which the immune system controls Infec pious diseases, cancer, and AIDS. This can provide a systematic plan for immunological experimentation by means of an integrated program of immune system analysis, mathematical modeling and computer simulation. Biochemical reactions and cellular fission are naturally modeled as nonlinear dynamical processes to synthesize the human immune system! as well as the complete organism it is intended to protect. A foundation for the control of tumors is presented, based upon the formulation of a realistic, knowledge based mathematical model of the interaction between tumor cells and the immune system. Ordinary bilinear differential equations which are coupled by such nonlinear term as saturation are derived from the basic physical phenomena of cellular and molecular conservation. The parametric control variables relevant to the latest experimental data are also considered. The model consists of 12 states, each composed of first-order, nonlinear differential equations based on cellular kinetics and each of which can be modeled bilinearly. Finally, tumor control as an application of immunotherapy is analyzed from the basis established.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2004.05a
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• pp.597-600
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• 2004

A two-degree-of-freedom out-of-plane model with contact stiffness is presented to describe dynamical interaction between the pad and disc of a disc brake system. It is assumed that the out-of-plane motion of the system depends on the friction force acting along the in-plane direction. Dynamic friction coefficient is modelled as a function of both in-plane relative velocity and out-of-plane normal force. When the friction coefficient depends only on the relative velocity, the contact stiffness has the role of negative stiffness. The results of stability analysis show that the stiffness of both pad and disc are equally important. Complex eigenvalue analysis is conducted for the case that the friction coefficient is also dependent on the normal force. The results further verify the importance of the stiffness. It has also been found that increasing the gradient of friction coefficient with respect to the normal force makes the system more unstable. Nonlinear analysis is also performed to demonstrate various responses. Comparing the responses with experimental data has shown that the proposed model may qualitatively well represent a certain type of brake noise.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.4
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• pp.336-339
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• 2001

The ozone forecasting systems have many problems because the mechanism of the ozone concentration is highly complex, nonlinear, and nonstationary. Especially, the performance of the prediction results in the high-level ozone concentration are not good. This paper describes the modeling method of the ozone prediction system using neuro-fuzzy approaches and fuzzy clustering methods. The dynamic polynomial neural network (DPNN) based upon a typical algorithm of GMDH (group method of data handling) is a useful method for data analysis, the identification of nonlinear complex systems, and prediction of dynamical systems.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.519-526
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• 2011

An investigation of the mechanism of period-doubling bifurcation in a voltage mode controlled buck-boost converter operating in discontinuous conduction mode is conducted from the viewpoint of nonlinear dynamical systems. The discrete iterative model describing the dynamics of the close-loop is derived. Period-doubling bifurcation occurs at certain values of the feedback factor. Results from numerical simulations and experiments are provided to verify the evolution of perioddoubling bifurcation, and the results are consistent with the theoretical analysis. These results show that the buck-boost converters exhibit a wide range of nonlinear behavior, and the system exhibits a typical period-doubling bifurcation route to chaos under particular operating conditions.

• Bulletin of the Korean Mathematical Society
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• v.49 no.4
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• pp.705-714
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• 2012

In this paper, we study nonlinear equation arising in MEMS modeling electrostatic actuation. We will prove the local and global existence of solutions of the generalized parabolic MEMS equation. We present that there exists a constant ${\lambda}^*$ such that the associated stationary problem has a solution for any ${\lambda}$ < ${\lambda}^*$ and no solution for any ${\lambda}$ > ${\lambda}^*$. We show that when ${\lambda}$ < ${\lambda}^*$ the global solution converges to its unique maximal steady-state as $t{\rightarrow}{\infty}$. We also obtain the condition for the existence of a touchdown time $T{\leq}{\infty}$ for the dynamical solution. Furthermore, there exists $p_0$ > 1, as a function of $p$, the pull-in voltage ${\lambda}^*(p)$ is strictly decreasing with respect to 1 < $p$ < $p_0$, and increasing with respect to $p$ > $p_0$.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.6
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• pp.616-628
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• 2000

In this paper, we present the modeling of the ozone prediction system using Neuro-Fuzzy approaches. The mechanism of ozone concentration is highly complex, nonlinear, and nonstationary, the modeling of ozone prediction system has many problems and the results of prediction is not a good performance so far. The Dynamic Polynomial Neural Network(DPNN) which employs a typical algorithm of GMDH(Group Method of Data Handling) is a useful method for data analysis, identification of nonlinear complex system, and prediction of a dynamical system. The structure of the final model is compact and the computation speed to produce an output is faster than other modeling methods. In addition to DPNN, this paper also includes a Fuzzy Logic Method for modeling of ozone prediction system. The results of each modeling method and the performance of ozone prediction are presented. The proposed method shows that the prediction to the ozone concentration based upon Neuro-Fuzzy approaches gives us a good performance for ozone prediction in high and low ozone concentration with the ability of superior data approximation and self organization.