• Journal of Korea Water Resources Association
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• v.43 no.8
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• pp.733-745
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• 2010

Seasonality of hydrologic extreme variable is a significant element from a water resources managemental point of view. It is closely related with various fields such as dam operation, flood control, irrigation water management, and so on. Hydrological frequency analysis conjunction with partial duration series rather than block maxima, offers benefits that include data expansion, analysis of seasonality and occurrence. In this study, nonstationary frequency analysis based on the Bayesian model has been suggested which effectively linked with advantage of POT (peaks over threshold) analysis that contains seasonality information. A selected threshold that the value of upper 98% among the 24 hours duration rainfall was applied to extract POT series at Seoul station, and goodness-fit-test of selected GEV distribution has been examined through graphical representation. Seasonal variation of location and scale parameter ($\mu$ and $\sigma$) of GEV distribution were represented by Fourier series, and the posterior distributions were estimated by Bayesian Markov Chain Monte Carlo simulation. The design rainfall estimated by GEV quantile function and derived posterior distribution for the Fourier coefficients, were illustrated with a wide range of return periods. The nonstationary frequency analysis considering seasonality can reasonably reproduce underlying extreme distribution and simultaneously provide a full annual cycle of the design rainfall as well.

• Journal of Korea Water Resources Association
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• v.35 no.6
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• pp.763-777
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• 2002

The objective of this study is to develop computer simulation model that produces precipitation patterns from stochastic model. The hourly precipitation process consists of the precipitation occurrence and precipitation amounts. In this study, an event cluster model developed by Lee and Lee(2002) is used to describe the occurrence process of events, and the hourly precipitation amounts within each event is described by a nonstationary form of a first-order autoregressive process. The complete stochastic model for hourly precipitation is fitted to historical precipitation data by estimating the model parameters. An analysis of historical and simulated hourly precipitation data for Seoul indicates that the stochastic model preserves many of the features of historical precipitation. The autocorrelation coefficients of the historical and simulated data are nearly identical except for lags more than about 3 hours. The precipitation intensity, duration, marginal distributions, and conditional distributions for event characteristics for the historical and simulated data showed in general good agreement with each other.

• Journal of Aerospace System Engineering
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• v.14 no.4
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• pp.10-17
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• 2020

When an aircraft is taxiing, excitation force is applied according to the shape of the road surface. The sprung mass acceleration caused by the excitation of the road surface negatively affects the feeling of boarding. This paper addresses the verification process of the semi-active control method applied to improve the feeling of boarding. The Magneto-Rheological damper landing gear model is employed alongside the control method. It is a Oleo-Pneumatic damper filled with a fluid having the characteristics of increasing yield stress when subjected to a magnetic field. The control method involves verifying Skyhook Control Type2 developed by Skyhook control. The Sinozuka white noise model that considers runway characteristics was employed for the road surface in the simulation. The runway road surface obtained through this model has stochastic characteristics, so the dynamic characteristics were analyzed by applying Monte-Carlo simulation. A dynamic analysis was conducted by co-simulating the landing gear model made by RecurDyn and the control method designed by Simulink. Simulation results show that the Skyhook Control Type2 method has the best control effect in the low speed range compared to the passive type (without control) and skyhook control.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.3
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• pp.563-569
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• 2004

The formulas taking into account the fundamental features of a meteoric radio propagation are obtained. Numerical simulation analysis has shown complex space structure of a field. Time behavior of intensity are researched taking into account nonstationary model. It is shown, this behavior essentially depends on parameters of a meteor trail, and that there is large variety of time dependencies of the signal intensity at the single scattering. In particular, at appropriate parameters of a meteor underdense trail it is possible large duration meteor bursts with which usually refer to an overdense meteor propagation.

• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.377-390
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• 2010

In the case of time-series analysis, it is often more convenient to rely on the frequency domain than the time domain. Spectral density is the core of the frequency-domain analysis that describes autocorrelation structures in a time-series process. Possible ways to estimate spectral density are to compute a periodogram or to average the periodogram over some frequencies with (un)equal weights. This can be an attractive tool to measure the similarity between time-series processes. We employ the metrics based on a smoothed periodogram proposed by Park and Kim (2008) for the classification of different classes of time-series processes. We consider several lag windows with unequal weights instead of a modified Daniel's window used in Park and Kim (2008). We evaluate the performance under various simulation scenarios. Simulation results reveal that the metrics used in this study split the time series into the preassigned clusters better than do the raw-periodogram based ones proposed by Caiado et al. 2006. Our metrics are applied to an economic time-series dataset.

• Wind and Structures
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• v.27 no.3
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• pp.199-211
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• 2018

This paper deals with wind fragility and risk analysis of high rise buildings subjected to stochastic wind load. Conventionally, such problems are dealt in full Monte Carlo Simulation framework, which requires extensive computational time. Thus, to make the procedure computationally efficient, application of metamodelling technique in fragility analysis is explored in the present study. Since, accuracy by the conventional Least Squares Method (LSM) based metamodelling is often challenged, an efficient Moving Least Squares Method based adaptive metamodelling technique is proposed for wind fragility analysis. In doing so, artificial time history of wind load is generated by three wind field models: i.e., a simple one based on alongwind component of wind speed; a more detailed one considering coherence and wind directionality effect, and a third one considering nonstationary effect of mean wind. The results show that the proposed approach is more accurate than the conventional LSM based metamodelling approach when compared to full simulation approach as reference. At the same time, the proposed approach drastically reduces computational time in comparison to the full simulation approach. The results by the three wind field models are compared. The importance of non-linear structural analysis in fragility evaluation has been also demonstrated.

• The Journal of the Acoustical Society of Korea
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• v.13 no.6
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• pp.66-74
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• 1994

Simulation of sonar reverberation time series is very useful because most acoustic models are power level models and have a difficulty when performance of hardware system is evaluated under the reverberant condition. Thus, in this paper, the simulation of reverberation time series is attempted, First, normalized spectrum, whose bandwidth is varying in the frequency domain and which has zero-mean Gaussian distribution, is calculated at pre-selected receiving time. Second, reverberation levels given by underwater acoustic model are combined with normalized spectrum in the frequency domain. Finally, nonstationary sonar reverberation time series are simulated by IFT(Inverse Fourier Transform).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.10
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• pp.825-831
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• 2017

Radar clutter in real environment is in general heterogeneous and especially nonstationary if radar geometry is of non-sidelooking monostatic structure or bistatic structure. These clutter properties lead to the insufficient number of secondary data of IID(Independent identically distributed) property, conclusively deteriorate clutter suppression performance. In this paper, we propose a clutter suppression algorithm that estimates the clutter signal belonging to cull under test via calculation using only prior information, rather than using the secondary data. Through analyzing the angle-Doppler spectrum of the clutter signal, we show the estimation of the clutter signal using prior information only is possible and present the derivation of a clutter suppression algorithm through eigen-value analysis. Finally, we show the performance of the proposed algorithm by simulation.

• The Journal of the Acoustical Society of Korea
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• v.13 no.2
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• pp.76-85
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• 1994

A speech enhancement algorithm which attenuates nonstationary colored noise is presented In this paper. The algorithm consists of a stationary Kalman filter and the simple speech/nonspeech detector. While the conventional enhancement systems are focused on a stationary and/or white background noise, this study Is focused on the mort realistic nonstationary and nonwhite noise. An AR model-based vector Kalman filter is used as a noise suppression system and a short-time energy threshold logic is used as a speech/nonspeech classifier. For Kalman filtering. noise coefficients are estimated in the nonspeech frame, and speech coefficients are estimated by applying the EM iteration algorithm. Simulation results using the car noise are presented based on the signal-to-noise ratio and informal listening tests. According to the experimental results, background noises in the nonspeech frames are eliminated almost completely, while some distortions are noticed in the speech frames. The distortion becomes severer as the SNR is reduced to 0dB and -5dB. Intelligibility, however, is not degraded significantly.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1854-1857
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• 1991

A numerically efficient modification of a variable step size LMS (Least Mean Squares) algorithm is proposed. This proposed algorithm is very simple in calculation and has a variable step size adjusted by the filter output error. Its additional computational burden with respect to the conventional LMS algorithm is only two multiplications, two substraction, an addition and some bit operations. In a simulation example, it is shown that the proposed algorithm has not only the faster convergence rate but also less misadjustments in the environment of highly nonstationary and correlated data.