• Journal of Ocean Engineering and Technology
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• v.13 no.3 s.33
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• pp.29-35
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• 1999

At the design of Mark III membrane type LNG tank, an analytical and experimental approach on the fatigue strengths of membrane and its welds are very important in order to assist designers and surveyors. In this study, fatigue tests of lap weld of Mark III membrane type LNG tank were carried out and cumulative damage factor was calculated in order to estimate the fatigue life by probability density function and rule methods. It contained the following tests and reviews : 1) The fatigue tests of lap weld of stainless steel according to statistical testing method recommended by JSME, 2)Preparation of S-N curve for lap welds considering the statistical properties of the results of fatigue tests. 3) Procedure for estimating the initiation life of fatigue crack of lap welds under variable loads by the rule lf classification society and probability density function, 4) Guideline for inspection of lap welds fo membrane type LNG tank.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.4
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• pp.729-739
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• 1997

In this paper, steady-state controllable M/G/1 queueing systems operating under the dyadic policies are considered. A new method to obtain the expected busy period when the D-policy is involved in system operation, is developed. This new method requires derivation of so called 'the pseudo probability density function' of the busy period for the system under consideration, which is completely different from its actual probability density function. However, the proposed pseudo probability density function does generate the correct expected busy period through simple procedures.

• International Journal of Naval Architecture and Ocean Engineering
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• v.2 no.3
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• pp.119-126
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• 2010

The response of ship roll oscillation under random ice impulsive loads modeled by Poisson arrival process is very important in studying the safety of ships navigation in cold regions. Under both external and parametric random excitations the evolution of the probability density function of roll motion is evaluated using the path integral (PI) approach. The PI method relies on the Chapman-Kolmogorov equation, which governs the response transition probability density functions at two close intervals of time. Once the response probability density function at an early close time is specified, its value at later close time can be evaluated. The PI method is first demonstrated via simple dynamical models and then applied for ship roll dynamics under random impulsive white noise excitation.

• Journal of Communications and Networks
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• v.12 no.5
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• pp.399-405
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• 2010

Blind equalization techniques have been used in broadcast and multipoint communications. In this paper, two criteria of minimizing Euclidian distance between two probability density functions (PDFs) for adaptive blind equalizers are presented. For PDF calculation, Parzen window estimator is used. One criterion is to use a set of randomly generated desired symbols at the receiver so that PDF of the generated symbols matches that of the transmitted symbols. The second method is to use a set of Dirac delta functions in place of the PDF of the transmitted symbols. From the simulation results, the proposed methods significantly outperform the constant modulus algorithm in multipath channel environments.

• Journal of the Korean Society of Combustion
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• v.15 no.4
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• pp.15-21
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• 2010

The transported probability density function(PDF) model has been applied to simulate the turbulent nonpremixed piloted jet flame. To realistically account for the mixture fraction PDF informations on the turbulent non-premixed jet flame, the present Lagrangian PDF transport approach is based on the joint velocity-composition-turbulence frequency PDF formulation. The fluctuating velocity of stochastic fields is modeled by simplified Langevin model(SLM), turbulence frequency of stochastic fields is modeled by Jayesh-Pope model and effects of molecular diffusion are represented by the interaction by exchange with the mean (IEM) mixing model. To validate the present approach, the numerical results obtained by the joint velocity-composition-turbulence frequency PDF model are compared with experimental data in terms of the unconditional and conditional means of mixture fraction, temperature and species and PDFs.

• Journal of Korea Multimedia Society
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• v.19 no.3
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• pp.633-641
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• 2016

Automatic defect inspection system is composed of the step in the pre-processing, defect candidate detection, and classification. Polarizing films containing various defects should be minimized over-detection for classifying defect blobs. In this paper, we propose a defect detection algorithm using a skewness of histogram for minimizing over-detection. In order to detect up defects with similar to background pixel, we are used the characteristics of the local region. And the real defect pixels are distinguished from the noise using the probability density function. Experimental results demonstrated the minimized over-detection by utilizing the artificial images and real polarizing film images.

• The Journal of the Acoustical Society of Korea
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• v.17 no.4E
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• pp.3-10
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• 1998

This paper concerns the dynamical behavior, in probabilistic sense, of a feedforward neural network performing auto association for novelty. Networks of retinotopic topology having a one-to-one correspondence between and output units can be readily trained using back-propagation algorithm, to perform autoassociative mappings. A novelty filter is obtained by subtracting the network output from the input vector. Then the presentation of a "familiar" pattern tends to evoke a null response ; but any anomalous component is enhanced. Such a behavior exhibits a promising feature for enhancement of weak signals in additive noise. As an analysis of the novelty filtering, this paper shows that the probability density function of the weigh converges to Gaussian when the input time series is statistically characterized by nonsymmetrical probability density functions. After output units are locally linearized, the recursive relation for updating the weight of the neural network is converted into a first-order random differential equation. Based on this equation it is shown that the probability density function of the weight satisfies the Fokker-Planck equation. By solving the Fokker-Planck equation, it is found that the weight is Gaussian distributed with time dependent mean and variance.

• Journal of the Korean Society of Combustion
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• v.22 no.3
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• pp.29-34
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• 2017

The multi-environment probability density function model has been applied to simulate a turbulent premixed flame in a swirl combustor. To realistically account for the unsteady flow motion inside the combustor, the formulations are derived for the large eddy simulation. The Flamelet generated manifolds is utilized to simplify a multi-dimensional composition space with reasonable accuracy. The sub grid scale mixing is modeled by the interaction by exchange with the mean mixing model. To validate the present approach, the simulation results are compared with experimental data in terms of mean velocity, temperature, and species mass fractions.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.109-118
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• 2008

We present two estimators for discrete non-Gaussian and nonstationary probability density estimation based on a dynamic Bayesian network (DBN). The first estimator is for off line computation and consists of a DBN whose transition distribution is represented in terms of kernel functions. The estimator parameters are the weights and shifts of the kernel functions. The parameters are determined through a recursive learning algorithm using maximum likelihood (ML) estimation. The second estimator is a DBN whose parameters form the transition probabilities. We use an asymptotically convergent, recursive, on-line algorithm to update the parameters using observation data. The DBN calculates the state probabilities using the estimated parameters. We provide examples that demonstrate the usefulness and simplicity of the two proposed estimators.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.4
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• pp.86-92
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• 2008

The expected busy period for the controllable M/G/1 queueing model operating under the triadic Max (N, T, D) policy is derived by using a new concept so called "the pseudo probability density function." In order to justify the proposed approaches for the triadic policy, well-known expected busy periods for the dyadic policies are recovered from the obtained result as special cases.