• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.5
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• pp.25-34
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• 2010

By introducing additional nodes called Steiner points, the problem of Steiner Minimum Tree whose length can be shorter than Minimum Spanning Tree and which connects all input terminal nodes belongs to Non-Polynomial Complete domain. Though diverse heuristic methods can be applied to the problem, most of them may meet serious pains in computing and waiting for a solution of the problem with numerous input nodes. For numerous input nodes, an efficient PTAS approximation method producing candidate unit steiner trees with portals in most bottom layer, merging them hierarchically to construct their parent steiner trees in upper layer and building swiftly final approximation Steiner tree in most top layer is suggested in this paper. The experiment with 16,000 input nodes and designed 16 unit areas in most bottom layer shows 85.4% execution time improvement in serial processing and 98.9% in parallel processing comparing with pure Steiner heuristic method, though 0.24% overhead of tree length. Therefore, the suggested PTAS Steiner tree method can have a wide range applications to build a large scale approximation Steiner tree quickly.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.1
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• pp.39-48
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• 2013

This paper develops a 2-D moving least squares(MLS) difference method for Stefan problem by extending the 1-D version of the conventional method. Unlike to 1-D interfacial modeling, the complex topology change in 2-D domain due to arbitrarily moving boundary is successfully modelled. The MLS derivative approximation that drives the kinetics of moving boundary is derived while the strong merit of MLS Difference Method that utilizes only nodal computation is effectively conserved. The governing equations are differentiated by an implicit scheme for achieving numerical stability and the moving boundary is updated by an explicit scheme for maximizing numerical efficiency. Numerical experiments prove that the MLS Difference Method shows very good accuracy and efficiency in solving complex 2-D Stefan problems.

• The KIPS Transactions:PartD
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• v.9D no.3
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• pp.389-398
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• 2002

Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. This paper presents a stochastic model for the software failure phenomenon based on a nonhomogeneous Poisson process(NHPP) and performs Bayesian inference using prior information. The failure process is analyzed to develop a suitable mean value function for the NHPP ; expressions are given for several performance measure. Actual software failure data are compared with several model on the constant reflecting the quality of testing. The performance measures and parametric inferences of the suggested models using Rayleigh distribution and Laplace distribution are discussed. The results of the suggested models are applied to real software failure data and compared with Goel model. Tools of parameter point inference and 95% credible intereval was used method of Gibbs sampling. In this paper, model selection using the sum of the squared errors was employed. The numerical example by NTDS data was illustrated.

• Journal of Korea Water Resources Association
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• v.39 no.3 s.164
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• pp.253-259
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• 2006

In almost all previous hydrological studies, the standard approach adopted for nonlinear time series analysis is to perform system characterization first followed by forecasting. However, a practical inverse approach for forecasting nonlinear hydrological time series was proposed recently To investigate the applicability standard approach method and inverse approach, this study used a theoretical time series (Mackey-Glass time series) and daily streamflows of the Bear River in Idaho. To predict a theoretical time series and daily streamflow, this study used local approximation method. From chaos analysis, chaotic characteristics are found in daily streamflow of the Bear River in Idaho. Resulting from 1, 3 and 5-day prediction, inverse approach method is shown to be better than the standard approach for a theoretical chaotic time series and daily streamflow.

• Korean Journal of Remote Sensing
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• v.19 no.6
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• pp.465-478
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• 2003

This paper presents two methods for automatic estimation of threshold values in unsupervised change detection of multi-temporal remote sensing images. The proposed methods consist of two analytical steps. The first step is to compute the parameters of a 3-component Gaussian mixture model from difference or ratio images. The second step is to determine a threshold value using Bayesian rule for minimum error. The first method which is an extended version of Bruzzone and Prieto' method (2000) is to apply an Expectation-Maximization algorithm for estimation of the parameters of the Gaussian mixture model. The second method is based on an iterative thresholding algorithm that successively employs thresholding and estimation of the model parameters. The effectiveness and applicability of the methods proposed here were illustrated by two experiments and one case study including the synthetic data sets and KOMPSAT-1 EOC images. The experiments demonstrate that the proposed methods can effectively estimate the model parameters and the threshold value determined shows the minimum overall error.

• Korean Journal of Remote Sensing
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• v.15 no.3
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• pp.195-208
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• 1999

In the classification of satellite images, the representative of training of classes is very important factor that affects the classification accuracy. Hence, in order to improve the classification accuracy, it is required to optimize pre-classification stage which determines classification parameters rather than to develop classifiers alone. In this study, the normality of training are calculated at the preclassification stage using SPOT XS and LANDSAT TM. A correlation coefficient of multivariate Q-Q plot with 5% significance level and a variance of initial training are considered as an object function of genetic algorithm in the training normalization process. As a result of normalization of training using the genetic algorithm, it was proved that, for the study area, the mean and variance of each class shifted to the population, and the result showed the possibility of prediction of the distribution of each class.

• Journal of the Korea Computer Graphics Society
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• v.26 no.5
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• pp.1-13
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• 2020

In this paper, we propose a new method to stable simulation the directional ice shape by coupling of freezing solver and viscous water flow. The proposed ice modeling framework considers viscous fluid flow in the direction of ice growth, which is important in freezing simulation. The water simulation solution uses the method of applying a new viscous technique to the IISPH(Implicit incompressible SPH) simulation, and the ice direction and the glaze effect use the proposed anisotropic freezing solution. The condition in which water particles change state to ice particles is calculated as a function of humidity and new energy with water flow. Humidity approximates a virtual water film on the surface of the object, and fluid flow is incorporated into our anisotropic freezing solution to guide the growth direction of ice. As a result, the results of the glaze and directional freezing simulations are shown stably according to the flow direction of viscous water.

• Journal of the Korean Geotechnical Society
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• v.23 no.8
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• pp.117-127
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• 2007

Slope stability analysis is a geotechnical engineering problem characterized by many sources of uncertainty. Some of them are connected to the uncertainties of soil properties involved in the analysis. In this paper, a numerical procedure for integrating commercial finite difference method into probabilistic analysis of slope stability is presented. Since the limit-state function cannot be expressed in an explicit form, the ANN-based response surface method is adopted to approximate the limit-state function and the first-, second-order reliability method and the Monte Carlo simulation technique are used to calculate the probability of failure. Probabilistic stability assessments for a hypothetical two-layer slope and the Sugar Creek embankment were performed to verify the application potential to the slope stability problems. The examples show the successful implementation and the possibility of the extension of the proposed procedure to the variety of geotechnical engineering problems.

• Journal of the Korean Geotechnical Society
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• v.26 no.4
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• pp.47-58
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• 2010

Seepage rate through the core zone of rockfill dam, estimated from graphical technique and the equation by Sakamoto (1998), is different from the real condition because of neglecting unsaturated flow. With existing method to estimate total seepage rate, it is difficult to understand the tendency of total seepage rate changes by reservoir water level change. Steady state seepage rate and the factors affecting the time needed to attain to changes of reservoir water level and saturated hydraulic conductivity and unsaturated hydraulic properties of core material are analysed thorough the 2-D steady and unsteady state seepage analyses of Soyanggang dam. Numerical results revealed that the seepage rate can be expressed by the linear equation form and the value of unsaturated soil parameter n is the most important factor affecting the seepage rate and the time needed to attain steady state. The estimation method presented in this study can be used by the designer and the personnel of dam safety for convenient estimation of seepage rate and quantitative analysis of measured seepage rate without 2-D and 3-D numerical analyses.

• The Journal of the Acoustical Society of Korea
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• v.29 no.2
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• pp.148-153
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• 2010

In speech signal processing, speech signal corrupted by noise should be enhanced to improve quality. Usually noise estimation methods need flexibility for variable environment. Noise profile is renewed on silence region to avoid effects of speech properties. So we have to preprocess finding voice region before noise estimation. However, if received signal does not have silence region, we cannot apply that method. In this paper, we proposed SNR estimation method for continuous speech signal. A Speech signal consists of Voice and Unvoiced Band in The MBE excitation model. And the energy of speech signal is mostly distributed on voiced region, so we can estimate SNR by the ratio of voiced region energy to unvoiced. We use the IMBE vocoder for the Voice or Unvoice band of segmented speech signal. Continuously we calculate the segmented SNR using that information and the energy of each band. And we estimate the SNR of continuous speech signal.