• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1048-1052
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• 2004

In this work, we have investigated a role of linking parameter in Pulse-Coupled Neural Network(PCNN) which is suggested to explain the synchronous activities among neurons in the cat cortex. Then we have found a method to determine the linking parameter for a satisfactory face detection performance in a given color image. Face detection algorithm which uses the color information is independent on pose, size and obstruction of a face. But the use of color information encounters some problems arising from skin-tone color in the background, intensity variation within faces, and presence of random noise and so on. Depending on these conditions, PCNN's linking parameters should be selected an appropriate values. First we obtained the mean and variance of the skin-tone colors by experiments. Then, we introduced a preprocess that the pixel with a mean value of skin-tone colors has the highest level value (255) and the other pixels have values between 0 and 255 according to normal distribution with a variance. This preprocessing leads to an easy decision of the linking parameter of the Pulse-Coupled Neural Network. Through experiments, it is verified that the proposed method can improve the face detection performance compared to the existing methods.

• Journal of the Society of Naval Architects of Korea
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• v.34 no.4
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• pp.91-98
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• 1997

Most dynamic systems have various random properties m excitation and system parameters. In this paper, a procedure for structural response and reliability analysis is proposed for the linear dynamic system with random properties in both excitation and system parameters. The system parameter and response with random properties are modeled by the perturbation technique, and then the response analysis is formulated by probabilistic and vibration theories. Probabilistic FEM is also used for the calculation of mean response which is difficult by the proposed response model. The first passage analysis by the integral equation method is used to analyze the probability of failure. The integral equation method results in the first passage probability in terms of crossing rates and first passage probability densities. In this study it is assumed that excitations, system parameters and responses are Gaussian. As an application example, the probabilities of failure at transient state are calculated for a sdof system with random mass and spring constant subjected to stationary white-noise excitation and the results are compared to those of numerical simulation.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.13 no.2
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• pp.60-66
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• 2017

The standard master curve (MC) approach has the major limitation because it is only applicable to homogeneous datasets. In nature, materials are macroscopically inhomogeneous and involve scatter of fracture toughness data due to various deterministic material inhomogeneity and random inhomogeneity. RPV(reactor pressure vessel) steel has different fracture toughness with varying distance from the inner surface of the wall due to cooling rate in manufacturing process; deterministic inhomogeneity. On the other hand, reference temperature, $T_0$, used in the evaluation of fracture toughness is acting as a random parameter in the evaluation of welding region; random inhomogeneity. In the present paper, four regions, the surface, 1/8T, 1/4T and 1/2T, were considered for fracture toughness specimens of KSNP (Korean Standard Nuclear Plant) SA508 Gr. 3 steel to investigate deterministic material inhomogeneity and random inhomogeneity. Fracture toughness tests were carried out for four regions and three test temperatures in the transition region. Fracture toughness evaluation was performed using the bimodal master curve (BMC) approach which is applicable to the inhomogeneous material. The results of the bimodal master curve analyses were compared with that of conventional master curve analyses. As a result, the bimodal master approach considering inhomogeneous materials provides better description of scatter in fracture toughness data than conventional master curve analysis. However, the difference in the $T_0$ determined by two master curve approaches was insignificant.

• Geotechnical Engineering
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• v.6 no.2
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• pp.5-20
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• 1990

In the seismic analysis of structures, where the dynamic soil-structure interaction (DSSI) is considred, earthquake input motions as well as dynamic soil properties are random in nature. To take into account the random nature of both the input motions and the dynamic soil properties systematically, a probabilistic analysis of the DSSI subjected to seismic loading is proposed in this paper, The complex response method formulized by the elastic half space theory, the random vibration theory, and the Rosenblueth's two-point estimate method are combined for the proposed probabilistic analysis. The conclusions drawn from this study are as follows ' 1) The uncertainty bands of the earthquake input motions proposed by Kanai-Tajimi as well as those of the dynamic properties are large the coefecients of variation of those parameters tinge from 0.4 to 0.6. 2) The uncertainties of the dynamic soil properties are more sensitive to the structural responses than those of the input motion parameters. 3) The effect of correlations between the input motion parameters and the dynamic soil properties is negligible.

• Advances in aircraft and spacecraft science
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• v.3 no.4
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• pp.471-502
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• 2016

This paper presents the dynamic instability analysis of un-damped elastically supported piezoelectric functionally graded (FG) beams subjected to in-plane static and dynamic periodic thermomechanical loadings with uncertain system properties. The elastic foundation model is assumed as one parameter Pasternak foundation with Winkler cubic nonlinearity. The piezoelectric FG beam is subjected to non-uniform temperature distribution with temperature dependent material properties. The Young's modulus and Poison's ratio of ceramic, metal and piezoelectric, density of respective ceramic and metal, volume fraction exponent and foundation parameters are taken as uncertain system properties. The basic nonlinear formulation of the beam is based on higher order shear deformation theory (HSDT) with von-Karman strain kinematics. The governing deterministic static and dynamic random instability equation and regions is solved by Bolotin's approach with Newmark's time integration method combined with first order perturbation technique (FOPT). Typical numerical results in terms of the mean and standard deviation of dynamic instability analysis are presented to examine the effect of slenderness ratios, volume fraction exponents, foundation parameters, amplitude ratios, temperature increments and position of piezoelectric layers by changing the random system properties. The correctness of the present stochastic model is examined by comparing the results with direct Monte Caro simulation (MCS).

• Journal of the Korean Operations Research and Management Science Society
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• v.12 no.1
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• pp.19-26
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• 1987

In analyzing time series, estimating the level or the current mean of the process plays an important role in understanding its structure and in being able to make forecasts. The studies the class of time series models where the level of the process is assumed to follow a random walk and the deviation from the level follow an ARMA process. The estimation and forecasting problem in a Bayesian framework and uses the Kalman filter to obtain forecasts based on estimates of level. In the analysis of time series, we usually make the assumption that the time series is generated by one model. However, in many situations the time series undergoes a structural change at one point in time. For example there may be a change in the distribution of random variables or in parameter values. Another example occurs when the level of the process changes abruptly at one period. In order to study such problems, the assumption that level follows a random walk process is relaxed to include a major level change at a particular point in time. The major level change is detected by examining the likelihood raio under a null hypothesis of no change and an alternative hypothesis of a major level change. The author proposes a method for estimation the size of the level change by adding one state variable to the state space model of the original Kalman filter. Detailed theoretical and numerical results are obtained for th first order autoregressive process wirth level changes.

• Journal of Astronomy and Space Sciences
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• v.22 no.2
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• pp.89-112
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• 2005

We determine the rotation velocities of 108 spiral and irregular galaxies (XV-Sample) from first-order rotation curves from position-velocity maps, based on short 21-cm observations with the Westerbork Synthesis Radio Telescope (WSRT). To test the usual random motion corrections, we compare the global HI linewidths and the rotation velocities, obtained from kinematical fits to two-dimensional velocity fields for a sample of 28 galaxies (RC-Sample), and find that the most frequently used correction formulae (Tully & Fouque 1985) are not very satisfactory. The rotation velocity parameter (the random-motion corrected HI linewidth: W?), derived with these corrections, may be statistically equal to two times the true rotation velocity, but in individual cases the differences can be large. We analyse, for both RC- and XV-Samples, the dependence of the slope of, and scatter in the Tully-Fisher relation on the definition of the rotation velocity parameters- For the RC-Sample, we find that the scatter in the Tully-Fisher relation can be reduced considerably when the rotation velocities derived from rotation curves are used instead of the random-motion corrected global H I linewidths. No such reduction in the scatter is seen for XV-Sample. We conclude that the reduction of the scatter in the Tully-Fisher relation seems to be related to the use of two-dimensional velocity information: accurate rotation velocity and kinematical inclination.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.337-352
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• 2005

In this paper, a fuzzy logic implementation of the random early detection (RED) mechanism [1] is presented. The main objective of the proposed fuzzy controller is to reduce the loss probability of the RED mechanism without any change in channel utilization. Based on previous studies, it is clear that the performance of RED algorithm is extremely related to the traffic load as well as to its parameters setting. Using fuzzy logic capabilities, we try to dynamically tune the loss probability of the RED gateway. To achieve this goal, a two-input-single-output fuzzy controller is used. To achieve a low packet loss probability, the proposed fuzzy controller is responsible to control the $max_{p}$ parameter of the RED gateway. The inputs of the proposed fuzzy controller are 1) the difference between average queue size and a target point, and 2) the difference between the estimated value of incoming data rate and the target link capacity. To evaluate the performance of the proposed fuzzy mechanism, several trials with file transfer protocol (FTP) and burst traffic were performed. In this study, the ns-2 simulator [2] has been used to generate the experimental data. All simulation results indicate that the proposed fuzzy mechanism out performs remarkably both the traditional RED and Adaptive RED (ARED) mechanisms [3]-[5].

• Transactions of the Korean Society of Mechanical Engineers B
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• v.20 no.9
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• pp.3015-3029
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• 1996

The notion of effective transport property of a heterogeneous medium implies that the medium is large enough that the ergodic theorem holds and local fluctuation of the property can be neglected. In case that the medium is not large enough compared to its characteristic microstructure length scale, the effective property fluctuates and differs from the value of the medium being large enough. As a representative transport phenomenon, diffusion was considered and the fluctuation of varying effective diffusion property, diffusion coarseness $C_k$, was defined as a quantifying parameter. Scaled effective diffusion property, $^*$>/k$_1$ and $C_k$ were computed for the two phase random media consisting of matrix of diffusion coefficient k$_1$ and spheres of diffusion coefficient k$_2$. Numerical simulations were performed by use of the so-called first passage time technique and data were collected for existing microstructure models of hard spheres(HS), overlapping spheres(OS) and penetrable concentric shells(PCS).

• Asian-Australasian Journal of Animal Sciences
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• v.17 no.7
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• pp.914-918
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• 2004

The random regression model methodology was applied into the estimation of genetic parameters for body weights in Chinese Simmental cattle to replace the traditional multiple trait models. The variance components were estimated using Gibbs sampling procedure on Bayesion theory. The data were extracted for Chinese Simmental cattle born during 1980 to 2000 from 6 national breeding farms, where records from 3 months to 36 months were only used in this study. A 3 orders Legendre polynomial was defined as the submodel to describe the general law of that body weight changing with months of age in population. The heritabilities of body weights from 3 months to 36 months varied between 0.31 and 0.48, where the heritabilities from 3 months to 12 months slightly decreased with months of age but ones from 13 months to 36 months increased with months of age. Specially, the heritabilities at eighteenth and twenty-fourth month of age were 0.33 and 0.36, respectively, which were slightly greater than 0.30 and 0.31 from multiple trait models. In addition, the genetic and phenotypic correlations between body weights at different month ages were also obtained using regression model.