• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.04a
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• pp.70-80
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• 2000

In order to reduce seismic hazard the characteristics of strong earthquakes are required. In the region where strong earthquakes do not happen frequently the stochastic simulation of strong motion is an alternative way to predict strong motions. this simulation required input parameters such as the quality factor the corner frequency the moment magnitude the stress drop and so on which can be obtained from analyses of records of small and intermediate earthquakes. Using those parameters obtained in the previous work the strong ground motions are predicted employing the stochastic method, . The results are compared to the two observed earthquakes-the Ulsan Offshore Earthquake and the Kyungju Earthquake. Although some deviations are found the predictions are similar to the observed data. Finally we computed attenuation equations for PGA PGV and ground accelerations for some frequencies using the results of predictions. These results can be used for earthquake engineering and more reliable results will come out as earthquake observations continue.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.03a
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• pp.20-27
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• 2002

Conventional Levenberg-Marquardt's nonlinear inversion method is simply modified by taking into account the second derivatives of the Hessian matrix so as to give robust inversion results. The weight of the second derivative terms is determined by the value of so-called λ in Levenberg-Marquardt's method. The new inversion method is applied to observed data from small-to-moderate earthquakes to simultaneously evaluate the modes parameters of the stochastic point-source model in and around the Korean Peninsula. Best estimates of the stochastic model parameters are obtained along with their statistics and compared with the previous results. Overall characteristics of the model parameters are found to be more of those of interplate than intraplate tectonic region.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.211-218
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• 1994

Stochastic computation employs random pulse streams to represent numbers. In this paper, we study a new method to implement the number system which uses the ratio of the numbers of ones and zeros in the pulse streams. In this number system. if P is the probability that a pulse is one in a pulse stream then the number X represented by the pulse stream is defined as P/(1-P). We propose circuits to implement the basic operations such as addition multiplication and sigmoid function with this number system and examine the error characteristics of such operations in stochastic computation. We also propose a neuron model and derive a learning algorithm based on backpropagation for the 3-layered feedforward neural networks. We apply this learning algorithm to a digit recognition problem. To analyze the results, we discuss the errors due to the variance of the random pulse streams and the quantization noise of finite length register.

• Transactions of the Korean Society of Mechanical Engineers
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• v.6 no.4
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• pp.308-314
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• 1982

An experimental study has been made for the dispersion phenomena by a stochastic model in a turbulent pipe flow. Local instantaneous passage of suspended solid particles were recorded in two dimensions, employing a periscopic system coupled vidicon camera. Probability density of passage was calculated. Second moment shows qualitatively that dispersive action is dependent on particle's geometric characteristics in vertical pipe flow. In case that density of the solid particles is larger than that of liquid, particles have a tendency to approach from the center of pipe to the wall, and in the contrary case the approach the center of pipe. It seems that there exists a field of radial accelerations, centrifugal or centripetal according to the sign of density difference between two phases.

• Journal of Korean Institute of Industrial Engineers
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• v.15 no.2
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• pp.33-44
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• 1989

This paper presents stochastic-statistical dominance rules which eliminate dominated alternatives thereby reduce the number of satisficing alternatives to a manageable size so that the decision maker can choose the best alternative among them when neither the utility function nor the probability distribution of outcomes is exactly known. Specifically, it is assumed that only the characteristics of the utility function and the value function are known. Also, it is assumed that prior probabilities of the mutually exclusive states of nature are not known, but their relative bounds are known. First, the notion of relative risk aversion is used to describe the decision maker's attitude toward risk, which is defined with the acknowledgement that the utility function of the decision maker is a composite function of a cardinal value function and a utility function with-respect to the value function. Then, stochastic-statistical dominance rules are developed to screen out dominated alternatives according to the decision maker's attitude toward risk represented in the form of the measure of relative risk aversion.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.17 no.1
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• pp.101-106
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• 2004

The phenomenon of PD(Partial Discharge) is accompanied by electromagnetic wave which can be detected by UHF(Ultra High Frequency) antenna. The signals obtaining from UHF antenna are very high rapid pulse and have wide band frequency responses. The distribution of PRPD(Phase Resolved Partial Discharge) which consisted of those pulse train can show distinct characteristics of PD sources. But it is not sufficient to discriminate among PD sources. This paper suggests that the stochastic parameters formed by preprocessing of STFT(Short Time Fourier Transform) are good tools for differentiate from PD sources. The stochastic parameters are CC(Cross Correlation) mean value, CC standard deviation, CC skewness, CC kurtosis.

• Journal of the Korean Society for Railway
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• v.11 no.1
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• pp.75-80
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• 2008

Human factors still play a significant part in many railway accidents. It is well blown that SPAD (Signal Passed at Danger) remains as the single most cause of railway accidents. In this study a stochastic model is developed to quantify SPAD human reliability. This model provides closed-form mathematical expressions into which multiple factors affecting the reliability of man-machine systems can be incorporated. Two basic elements are combined to form the framework for modeling: random signal occurrence and transient human performance characteristics.

• Journal of Korean Society on Water Environment
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• v.25 no.1
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• pp.112-119
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• 2009

Based on the study of soil water dynamics, this study is to suggest an advanced stochastic soil water model for future study for drought application. One distinguishable remark of this study is the derivation of soil water dynamic controling equation for 3-stage loss functions in order to understand the temporal behaviour of soil water with reaction to the precipitation. In terms of modeling, a model with rather simpler structure can be applied to regenerate the key characteristics of soil water behavior, and especially the probabilistic solution of the derived soil water dynamic equation can be helpful to provide better and clearer understanding of soil water behavior. Moreover, this study will be the future cornerstone of applying to more realistic phenomenon such as drought management.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.515-525
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• 2007

In this paper, we develop a co-design methodology of stochastic optimal controllers and network parameters that optimizes the overall quality of control (QoC) in networked control systems (NCSs). A new dynamic model for NCSs is provided. The relationship between the system stability and performance and the sampling frequency is investigated, and the analysis of co-design of control and network parameters is presented to determine the working range of the sampling frequency in an NCS. This optimal sampling frequency range is derived based on the system dynamics and the network characteristics such as data rate, time-delay upper bound, data-packet size, and device processing time. With the optimal sampling frequency, stochastic optimal controllers are designed to improve the overall QoC in an NCS. This co-design methodology is a useful rule of thumb to choose the network and control parameters for NCS implementation. The feasibility and effectiveness of this co-design methodology is verified experimentally by our NCS test bed, a ball magnetic-levitation (maglev) system.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.7
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• pp.919-926
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• 2012

In order to control a LTI(Linear Time Invariant) system subjected to system noise and measurement noise, first of all, it is necessary to estimate the state of system with reliability. Kalman filtering technique has been widely used to estimate the state of the stochastic LTI system with stationary noise characteristics because of its estimation ability versus algorithm simplicity. However, it often fails to estimate the state of the LTI system of which system parameter uncertainty exists partly and/or input uncertainty exists. In this paper, a new estimation technique based on Kalman filter is suggested for stochastic LTI system under parameter uncertainty and/or input uncertainty. A fuzzy estimation algorithm against uncertainties is introduced so as to compensate the state estimate filtered by Kalman filter. In order to verify the state estimation performance of the suggested technique, several simulations are accomplished.