• Journal of Communications and Networks
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• v.8 no.2
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• pp.220-227
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• 2006

In this paper, we present a novel approach to analyze the throughput of direct-sequence spread spectrum multiple access (DS/SSMA) unslotted ALOHA system. In the unslotted system, the departure rate of interfering transmissions is proportional to the number of current interferers that can be regarded as the system state. In order to model this state-dependency, we introduce a two-dimensional state transition model that describes the state transition of the system. This model provides a more rigorous analysis tool for the DS/SSMA unslotted ALOHA systems with both fixed and variable packet lengths. Numerical results reveal that this analysis yields an accurate system performance that coincides with the simulation results. Throughout the analysis we have discovered that the state-dependency of the departure rate causes interference averaging effect in the unslotted system and that this effect yields a higher throughput for the unslotted system than for the slotted system when supported by a strong channel coding.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.1
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• pp.77-84
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• 2007

In this paper, Takagi-Sugeno (TS) fuzzy integral control is investigated to regulate the output voltage of an asymmetric half-bridge (AHB) DC/DC converter; First, we model the dynamic characteristics of the AHB DC/DC converter with state-space averaging method and small perturbation at an operating point. After introducing an additional integral state of the output regulation error, we obtain the $5^{th}$-order TS fuzzy model of the AHB DC/DC converter. Second, the concept of the parallel distributed compensation is applied to design the fuzzy integral controller, in which the state feedback gains are obtained by solving the linear matrix inequalities (LMIs). Finally, simulation results are presented to show the performance of the considered design method as the output voltage regulator and compared to the results for which the conventional loop gain method is used.

• Honam Mathematical Journal
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• v.44 no.3
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• pp.402-418
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• 2022

Noise is a fundamental factor to increased validity and regularity of spike propagation and neuronal firing in the nervous system. In this paper, we examine the stochastic version of the Izhikevich-FitzHugh neuron dynamical model. This approach is based on techniques presented by Luo and Guo, which provide a general framework for the bifurcation and stability analysis of two dimensional stochastic dynamical system as an Itô averaging diffusion system. By using largest lyapunov exponent, local and global stability of the stochastic system at the equilibrium point are investigated. We focus on the two kinds of stochastic bifurcations: the P-bifurcation and the D-bifurcations. By use of polar coordinate, Taylor expansion and stochastic averaging method, it is shown that there exists choices of diffusion and drift parameters such that these bifurcations occurs. Finally, numerical simulations in various viewpoints, including phase portrait, evolution in time and probability density, are presented to show the effects of the diffusion and drift coefficients that illustrate our theoretical results.

• Transactions of the Korean Society of Mechanical Engineers
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• v.19 no.7
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• pp.1691-1701
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• 1995

Two aspects of Large-Eddy Simulation(LES) are investigated in order to improve its performance. The first one is on how to determine the model coefficient in conjunction with a dynamic subgrid-scale model, and the second one is on a wall-layer model(WLM) which allows one to skip near-wall regions to save a large number of grid points otherwise required. Especially, a WLM suitable for a separated flow is considered. Firstly, an averaging technique to calculate the model coefficient of dynamic subgrid-scale modeling(DSGSM) is introduced. The technique is based on the concept of local averaging, and useful to stabilize numerical solution in conjunction with LES of complex turbulent flows using DSGSM. It is relatively simple to implement, and takes very low overhead in CPU time. It is also able to detect the region of negative model coefficient where the "backscattering" of turbulence energy occurs. Secondly, a wall-layer model based on a local turbulence intensity is considered. It locally determines wall-shear stresses depending on the local flow situations including separation, and yields better predictions in separated regions than the conventional WLM. The two techniques are tested for a turbulent obstacle flow, and show the direction of further improvements.rovements.

• Transactions of the Korean hydrogen and new energy society
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• v.29 no.4
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• pp.401-409
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• 2018

A numerical investigation has been conducted to find the effects of pressure losses by struts and rakes, and averaging methods on the performance of a multi-stage axial fan and a multi-stage axial compressor. Struts and rakes which produce pressure losses are installed upstream of the aerodynamic inlet plane in the fan and the compressor rigs. Some of normal stator vanes are substituted with thick vanes with total pressure probes to measure total pressure between stages. Three-dimensional Reynolds-averaged Navier- Stokes equations with $k-{\omega}$ SST turbulence model were applied to analyze the pressure losses by the struts, inlet rakes, and thick instrumented vanes. The hexahedral grids were used to construct computational domain. Inlet pressure losses were evaluated for the compressor as a function of Mach number. The passage pressure losses due to the instrumented vanes were evaluated at the two speed lines in the fan. Total properties, such as pressure and temperature, were evaluated at the exit of the fan and the compressor with two different averaging methods which are area-averaging and mass-averaging, respectively.

• Journal of Korean Society for Atmospheric Environment
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• v.5 no.1
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• pp.1-10
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• 1989

The sensitivity analysis is a method to quantify to what extent the output of a model changes with the values of input parameters. This will lead to increase model accuracy through measurement validation. Three line source air quality models, HIWAY 2, PAL, and CALINE 3 were selected for this study. The input parameters analysed included wind speed, wind direction, stability, emission rate, mixing height, receptor distance, initial dispersion coefficient, surface roughness, and averaging time. It turned out that PAL model generally showed higher concentration than other two models, and that between CALINE 3 and HIWAY 2, CALINE 3 showed higher concentration than HIWAY 2 model near the line sources, but beyond a certain downwind distances HIWAY 2 model showed higher concentration. The modesl were very sensitive to wind speed especially in the range of 0 $\sim$ 1 m/s and to wind direction near the parallel wind to streets. In case of emission rate, the output concentration was directly proportional to these input parameters. And the sensitivity of the input parameters such as stability, mixing height, initial dispersion coefficient, surface roughness, and averaging time were not very significant.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.335-343
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• 2021

This paper investigates the effect of institutional quality on FDI inflows by using FDI outflows from Asian countries from 2009 to 2017. We used the FDI data from five major Asian economies, which are South Korea, China, Japan, Singapore, and Hong Kong. The gravity model was used to examine the effect of institutional quality on FDI flows. The regression model considers several independent variables, and we select the most appropriate variables by using the Bayesian Model Averaging (BMA) estimator. We have shown that foreign direct investment from Asian countries depends on the size of home and the partner countries, geographical distance, trade interaction between two countries, economic freedom, labor supply, tariff rate, and capacity of the government. The results of different estimation techniques emphasize that multinational enterprises prefer to invest in those countries which have a higher income, which shows the evidence for Lucas's paradox. The results also show that economic freedom and control of corruption have a positive impact on FDI inwards. The regression results show that better institutional quality in host countries encourages more FDIs from Asian economies. It suggests that the state should control corruption and create a free economic environment to attract FDIs.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.13 no.4
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• pp.317-322
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• 2003

Torsional oscillations of a system incorporating a Hooke's joint are investigated by adopting a nonlinear 2-degree-of-freedom model. Linear and Van der Pol transformations are applied to obtain the equations of motion to which the method of averaging can be readily applied. Various subharmonic and combination resonances are identified with the conditions of their occurrences. Applying the method of averaging leads to the reduced amplitude- and phase-equations of motion, of which constant and periodic solutions are obtained numerically. The periodic solution which emerges from Hopf bifurcation point experiences period doubling bifurcation leading to infinite solution rather than chaotic solution.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06c
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• pp.263-266
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• 2007

This paper discusses the Bayesian statistical inference. This paper discusses the Bayesian inference, MCMC (Markov Chain Monte Carlo) integration, MCMC method, Metropolis-Hastings algorithm, Gibbs sampling, Maximum likelihood estimation, Expectation Maximization algorithm, missing data processing, and BMA (Bayesian Model Averaging). The Bayesian statistical inference is used to process a large amount of data in the areas of biology, medicine, bioengineering, science and engineering, and general data analysis and processing, and provides the important method to draw the optimal inference result. Lastly, this paper discusses the method of principal component analysis. The PCA method is also used for data analysis and inference.

• Journal of Mechanical Science and Technology
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• v.14 no.2
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• pp.168-176
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• 2000

Related to the error dynamics of an adaptive system, averaging theorems are developed for coupled differential equations which consist of ordinary differential equations and a parabolic partial differential equation. The results are then applied to the convergence analysis of the parameter estimate errors in the model reference adaptive control of a nonautonomous parabolic partial differential equation with lowly time-varying parameters.