• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.8
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• pp.615-623
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• 2018

The probability density function(PDF) for the amplitude of the reflectivity of low-grazing-angle sea clutter has generally been modeled by a compound-Gaussian distribution, rather than by the Rayleigh distribution, owing to the intensity variation of each clutter patch over time. The texture component forming the reflectivity has been simulated by combining Gamma distribution and memory-less nonlinear transformation(MNLT). On the other hand, there is no typical method available that can be used to simulate the speckle component. We first review Watt's method, wherein the speckle is simulated starting from the Doppler spectrum of the received echoes that is modeled as having a Gaussian shape. Then, we introduce a newly proposed method. The proposed method simulates the speckle by manipulating a clutter covariance matrix through the Cholesky decomposition after minimizing the effect of adjacent clutter patches using an equalizer. The feasibility of the proposed method is validated through simulation, wherein the results from two methods are compared in terms of the Doppler spectrum and the correlation function.

• Journal of the military operations research society of Korea
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• v.35 no.2
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• pp.33-49
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• 2009

The objective of this study is as follows. First, the hazard function on the failure probability density function of the K-1 tracked vehicles can be occurred in the form of the bathtub curve. Second, the failure mode may be different under two different operational situations. The research result shows that the bathtub curve can be fitted in the Weibull distribution, that assumes different shapes according to the specific stage of the system's life cycle. The K-1 tracked vehicle has a relatively high hazard(failure) rate at the time of its first service. The failure rate starts decreasing for a time immediately after it goes into service. After the break-in period, the surviving components have a fairly constant hazard rate. As the K-1 system ages, deterioration of its various parts takes place and the hazard rate starts Increasing. Second, the result shows the failure rate in the harsh operational environment is higher than that in the mild operational environment. In conclusion, the bathtub curve can be logically appropriate in establishing the depot overhaul cycle. Moreover, it is necessary for determining the right time of the depot overhaul to consider not only the age of defense equipment but also the different operational environment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.5
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• pp.1861-1870
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• 2013

A climate change-driven increased hydrological variability has been widely acknowledged over the past decades. In this regards, rainfall simulation techniques are being applied in many countries to consider the increased variability. This study proposed a Homogeneous Hidden Markov Chain(HMM) designed to recognize rather complex patterns of rainfall with discrete hidden states and underlying distribution characteristics via mixture probability density function. The proposed approach was applied to Seoul and Jeonju station to verify model's performance. Statistical moments(e.g. mean, variance, skewness and kurtosis) derived by daily and seasonal rainfall were compared with observation. It was found that the proposed HMM showed better performance in terms of reproducing underlying distribution characteristics. Especially, the HMM was much better than the existing Markov Chain model in reproducing extremes. In this regard, the proposed HMM could be used to evaluate a long-term runoff and design flood as inputs.

• Journal of Korea Water Resources Association
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• v.30 no.3
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• pp.225-233
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• 1997

The nonlinear effects on the statistical properties of wave groups in terms of the average nomber of waves in a group and the mean number of waves in a high run is studied in this paper utilizing the complex envelope and total phase function, random variable transformation technique and perturbation method. It tures out that the phase distribution is modified significantly by nonlinearities and it show systematic excess of values near the mean phase and the corresponding symmetrical deficiency on both sides away from the mean. for the case of threshold crossing rate, it turns out that threshold crossing rate reaches its maxima just below the mean water level rather than zero and considerable amount of probability mass is shifted toward the larger values of water surface elevation as nonlinearity is getting profound. Furthermore, the mean waves in a high run associated with nonlinear wave are shown to have larger values than the linear counterpart. Similar trend can also be found in the average number of waves in a group.

• Journal of The Korean Astronomical Society
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• v.48 no.1
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• pp.75-82
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• 2015

We use a volume-limited sample of quasars in the Sloan Digital Sky Survey (SDSS) DR7 quasar catalog to identify quasar groups and address their statistical significance. This quasar sample has a uniform selection function on the sky and nearly a maximum possible contiguous volume that can be drawn from the DR7 catalog. Quasar groups are identified by using the Friend-of-Friend algorithm with a set of fixed comoving linking lengths. We find that the richness distribution of the richest 100 quasar groups or the size distribution of the largest 100 groups are statistically equivalent with those of randomly-distributed points with the same number density and sky coverage when groups are identified with the linking length of $70h^{-1}Mpc$. It is shown that the large-scale structures like the huge Large Quasar Group (U1.27) reported by Clowes et al. (2013) can be found with high probability even if quasars have no physical clustering, and does not challenge the initially homogeneous cosmological models. Our results are statistically more reliable than those of Nadathur (2013), where the test was made only for the largest quasar group. It is shown that the linking length should be smaller than $50h^{-1}Mpc$ in order for the quasar groups identified in the DR7 catalog not to be dominated by associations of quasars grouped by chance. We present 20 richest quasar groups identified with the linking length of $70h^{-1}Mpc$ for further analyses.

• Journal of The Korean Astronomical Society
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• v.53 no.2
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• pp.49-57
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• 2020

We present numerical simulations of decaying hydrodynamic turbulence initially driven by solenoidal (divergence-free) and compressive (curl-free) drivings. Most previous numerical studies for decaying turbulence assume an isothermal equation of state (EOS). Here we use a polytropic EOS, P ∝ ρ^γ, with polytropic exponent γ ranging from 0.7 to 5/3. We mainly aim at determining the effects of γ and driving schemes on the decay law of turbulence energy, E ∝ t^-α. We additionally study probability density function (PDF) of gas density and skewness of the distribution in polytropic turbulence driven by compressive driving. Our findings are as follows. First of all, we find that even if γ does not strongly change the decay law, the driving schemes weakly change the relation; in our all simulations, turbulence decays with α ≈ 1, but compressive driving yields smaller α than solenoidal driving at the same sonic Mach number. Second, we calculate compressive and solenoidal velocity components separately and compare their decay rates in turbulence initially driven by compressive driving. We find that the former decays much faster so that it ends up having a smaller fraction than the latter. Third, the density PDF of compressively driven turbulence with γ > 1 deviates from log-normal distribution: it has a power-law tail at low density as in the case of solenoidally driven turbulence. However, as it decays, the density PDF becomes approximately log-normal. We discuss why decay rates of compressive and solenoidal velocity components are different in compressively driven turbulence and astrophysical implication of our findings.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.36 no.8
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• pp.829-837
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• 2012

Direct numerical simulations were carried out for turbulent channel flows with $Re_{\tau}$ = 180, 395 and 590 to investigate the turbulent flow structure related to the Reynolds shear stress. By examining the probability density function, the second quadrant (Q2) events with the largest contribution to the mean Reynolds shear stress were identified. The change in the inclination angle of Q2 events varies with wall units in $y^+<50$ and with the channel half height in y/h > 0.5. Conditionally averaged flow fields for the Q2 event show that the flow structures associated with Reynolds shear stress are a quasi-streamwise vortex in the buffer layer and a hairpin-shaped vortex in the outer layer. Three-dimensional visualization of the distribution of high Reynolds shear stress reveals that the organization of hairpin vortices in the outer layer having a size of 1.5~3 h is associated with large-scale motions with high Reynolds shear stress in the outer layer.

• Journal of KIISE:Information Networking
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• v.33 no.2
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• pp.131-138
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• 2006

To achieve security in wireless sensor networks(WSN), it is important to be able to encrypt and authenticate messages sent among sensor nodes. Due to resource constraints, many key agreement schemes used in general networks such as Diffie-Hellman and public-key based schemes are not suitable for wireless sensor networks. The current pre-distribution of secret keys uses q-composite random key and it randomly allocates keys. But there exists high probability not to be public-key among sensor nodes and it is not efficient to find public-key because of the problem for time and energy consumption. To remove problems in pre-distribution of secret keys, we propose a new cryptographic key management protocol, which is based on the clustering scheme but does not depend on probabilistic key. The protocol can increase efficiency to manage keys because, before distributing keys in bootstrap, using public-key shared among nodes can remove processes to send or to receive key among sensors. Also, to find outcompromised nodes safely on network, it selves safety problem by applying a function of lightweight attack-detection mechanism.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.5
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• pp.29-39
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• 2012

The main objective is to predict the future degradation and maintenance budget for a suspension bridge system. Bayesian inference is applied to find the posterior probability density function of the source parameters (damage indices and serviceability), given ten years of maintenance data. The posterior distribution of the parameters is sampled using a Markov chain Monte Carlo method. The simulated risk prediction for decreased serviceability conditions are posterior distributions based on prior distribution and likelihood of data updated from annual maintenance tasks. Compared with conventional linear prediction model, the proposed quadratic model provides highly improved convergence and closeness to measured data in terms of serviceability, risky factors, and maintenance budget for bridge components, which allows forecasting a future performance and financial management of complex infrastructures based on the proposed quadratic stochastic regression model.

• Journal of the Korean Geotechnical Society
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• v.33 no.7
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• pp.29-41
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• 2017

There are uncertainties about the seismic load caused by seismic waves, which cannot be predicted due to the characteristics of the earthquake occurrence. Therefore, it is necessary to consider these uncertainties by probabilistic analysis. In this paper, procedures to develop a fragility curve that is a representative method to evaluate the safety of a structure by stochastic analysis were proposed for cut slopes. Fragility curve that considers uncertainties of soil shear strength parameters was prepared by Monte Carlo Simulation using pseudo static analysis. The fragility curve considering the uncertainty of the input ground motion was developed by performing time-history seismic analysis using selected 30 real ground input motions and the Newmark type displacement evaluation analysis. Fragility curves are represented as the cumulative probability distribution function with lognormal distribution by using the maximum likelihood estimation method.