• Investigative Magnetic Resonance Imaging
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• v.2 no.1
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• pp.58-66
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• 1998

Purpose : This paper introduces a new three dimensional magnetic Resonance Image classification which is based on Mar kov Random Field-Gibbs Random Field with a line model. Material and Methods : The performance of the Gibbs Classifier over a statistically heterogeneous image can be improved if the local stationary regions in the image are disassociated from each other through the mechanism of the interaction parameters defined at the local neighborhood level. This usually involves the construction of a line model for the image. In this paper we construct a line model for multisignature images based on the differential of the image which can provide an a priori estimate of the unobservable line field, which may lie in regions with significantly different statistics. the line model estimated from the original image data can in turn be used to alter the values of the interaction parameters of the Gibbs Classifier. Results : MRF-Gibbs classifier for volumetric MR images is developed under the condition that the domain of the image classification is $E^{3}$ space rather thatn the conventional $E^{2}$ space. Compared to context free classification, MRF-Gibbs classifier performed better in homogeneous and along boundaries since contextual information is used during the classification. Conclusion : We construct a line model for multisignature, multidimensional image and derive the interaction parameter for determining the energy function of MRF-Gibbs classifier.

• Journal of the Korean Geotechnical Society
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• v.25 no.12
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• pp.13-25
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• 2009

In this paper, a numerical procedure of probabilistic slope stability analysis that considers the spatial variability of soil properties is presented. The procedure extends the deterministic analysis based on the limit equilibrium method of slices to a probabilistic approach that accounts for the uncertainties and spatial variation of the soil parameters. Making no a priori assumptions about the critical failure surface like the Random Finite Element Method (RFEM), the approach saves the amount of solution time required to perform the analysis. Two-dimensional random fields are generated based on a Karhunen-Lo$\grave{e}$ve expansion in a fashion consistent with a specified marginal distribution function and an autocorrelation function. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses were performed to verify the application potential of the proposed method and to study the effects of uncertainty caused by the spatial heterogeneity on the stability of slope. The results show that the proposed method can efficiently consider the various failure mechanisms caused by the spatial variability of soil property in the probabilistic slope stability assessment.

• Journal of Astronomy and Space Sciences
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• v.16 no.1
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• pp.41-52
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• 1999

Near-earth space is composed of plasmas which embed a number of plasma waves. Space plasmas consist of electrons and multi-ion that determine local wave propagation characteristics. In multi-ion plasmas, it is difficult to find out analytic solutions from the dispersion relation in general. In this work, we have developed a model with an arbitrary magnetic field and density as well as multi-ion plasmas. This model allows us to investigate how plasma waves behave when they propagate along realistic magnetic field lines, which are assumed by IGRF(International Geomagnetic Reference Field). The results are found to be useful for the analysis of the in situ observational data in space. For instance, if waves are assumed to propagate into the polar region, from the equatorial region, our model quantitatively show how polarization is altered along earth travel path.

• Journal of the Korean Geotechnical Society
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• v.28 no.12
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• pp.65-76
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• 2012

In this study, probabilistic analysis of seepage through a two-layered soil foundation was performed. The hydraulic conductivity of soil shows significant spatial variations in different layers because of stratification; further, it varies on a smaller scale within each individual layer. Therefore, the deterministic seepage analysis method was extended to develop a probabilistic approach that accounts for the uncertainties and spatial variation of the hydraulic conductivity in a layered soil profile. Two-dimensional random fields were generated on the basis of the Karhunen-Lo$\grave{e}$ve expansion in a manner consistent with a specified marginal distribution function and an autocorrelation function for each layer. A Monte Carlo simulation was then used to determine the statistical response based on the random fields. A series of analyses were performed to verify the application potential of the proposed method and to study the effects of uncertainty due to the spatial heterogeneity on the seepage behavior of two-layered soil foundation beneath water retaining structure. The results showed that the probabilistic framework can be used to efficiently consider the various flow patterns caused by the spatial variability of the hydraulic conductivity in seepage assessment for a layered soil foundation.

• Water for future
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• v.22 no.2
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• pp.201-211
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• 1989

Using the storm data which was augmented by the stochastic correlation with it's neighbors, the multiquadric equation of random surface of total storm depth is constructed. And to separate the local components from it's regionals and find the regional characteristics, a double Fourier analysis was applied to the total depths of storm data. The local components, storm residuals of each storm was assumed to be homogeneous random field and investigated with it's autocorrelation function. For the practical application, isotropic was assumed and that was identified with emprical data. Coefficients of normalized autocorrelation for all storms showed similar apperance. Using this emprical result, an example of the radial spectral distribution function which represints the spatial characteristics of rainfall over Han River Basin during 1975-1983 is presented.

• Survey Research
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• v.10 no.3
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• pp.1-19
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• 2009

This study investigates the utilities of spatial analysis in the context of survey research using Geographical Information System(GIS) and Geographically Weighted Regression (GWR) which take account of spatial heterogeneity. Many social phenomena involve spatial dimension, and with the development of GIS, GPS receiver, and online location-based services, spatial information can be collected and utilized more easily, and thus application of spatial analysis in the survey research is getting easier. The traditional OLS regression models which assume independence of observations and homoscedasticity of errors cannot handle spatial dependence problem. GWR is a spatial analysis technique which utilizes spatial information as well as attribute information, and estimated using geographically weighted function under the assumption that spatially close cases are more related than distant cases. Residential survey data from a Primary Autonomous District are used to estimate a model of public service satisfaction. The findings show that GWR handles the problem of spatial auto-correlation and increases goodness-of-fit of model. Visualization of spatial variance of effects of the independent variables using GIS allows us to investigate effects and relationships of those variables more closely and extensively. Furthermore, GIS and GWR analyses provide us a more effective way of identifying locations where the effect of variable is exceptionally low or high, and thus finding policy implications for social development.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.9
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• pp.999-1004
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• 2014

In the present paper, the effects of initial crack location on spatial randomness of fatigue crack growth resistance (FCGR) in friction stir welded (FSWed) AA7075-T651 plates were studied. The objective of this study is to characterize the statistical properties of FCGR for three different types of initial crack location (ICL) specimens. In this work, the FCGR coefficients were treated as a spatial random process. It was found that the FCGR coefficients for all initial crack location specimens closely followed a two parameter Weibull distribution. The shape parameter of the Weibull distribution for BM-ICL specimens showed the largest value of 7.50, and that for the WM-ICL specimens showed the smallest value of 2.61. In addition, the autocorrelation functions for all the ICL specimens followed the exponential function.

• Journal of the Korean Geotechnical Society
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• v.24 no.8
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• pp.111-123
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• 2008

Geotechnical engineering problems are characterized by many sources of uncertainty. Some of these sources are connected to the uncertainties of soil properties involved in the analysis. In this paper, a numerical procedure for a probabilistic analysis that considers the spatial variability of soil properties is presented to study the response of spatially random soil. The approach integrates a commercial finite difference method and random field theory into the framework of a probabilistic analysis. Two-dimensional non-Gaussian random fields are generated based on a Karhunen-$Lo{\grave{e}}ve$ expansion in a fashion consistent with a specified marginal distribution function and an autocorrelation function. A Monte Carlo simulation is then used to determine the statistical response based on the random fields. A series of analyses were performed to study the effects of uncertainty due to the spatial heterogeneity on the settlement and bearing capacity of a rough strip footing. The simulations provide insight into the application of uncertainty treatment to the geotechnical problem and show the importance of the spatial variability of soil properties with regard to the outcome of a probabilistic assessment.

• Geophysics and Geophysical Exploration
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• v.12 no.1
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• pp.121-131
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• 2009

In recent years, microtremor array observations have been used for estimation of shear-wave velocity structures. One of the methods is the conventional spatial autocorrelation (SPAC) method, which requires simultaneous recording at least with three or four sensors. Modified SPAC methods such as 2sSPAC, and linear array methods, allow estimating shear-wave structures by using only two sensors, but suffer from instability of the spatial autocorrelation coefficient for frequency ranges higher than 1.0 Hz. Based on microtremor measurements from four different size triangular arrays and four same-size triangular and linear arrays, we have demonstrated the stability of SPAC coefficient for the frequency range from 2 to 4 or 5 Hz. The phase velocities, obtained by fitting the SPAC coefficients to the Bessel function, are also consistent up to the frequency 5 Hz. All data were processed by the SPAC method, with the exception of the spatial averaging for the linear array cases. The arrays were deployed sequentially at different times, near a site having existing Parallel Seismic (PS) borehole logging data. We also used the imaginary part of the SPAC coefficients as a data-quality indicator. Based on perturbations of the autocorrelation spectrum (and in some cases on visual examination of the record waveforms) we divided data into so-called 'reliable' and 'unreliable' categories. We then calculated the imaginary part of the SPAC spectrum for 'reliable', 'unreliable', and complete (i.e. 'reliable' and 'unreliable' datasets combined) datasets for each array, and compared the results. In the case of insufficient azimuthal distribution of the stations (the linear array) the imaginary curve shows some instability and can therefore be regarded as an indicator of insufficient spatial averaging. However, in the case of low coherency of the wavefield the imaginary curve does not show any significant instability.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.226.1-226.1
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• 2014

이온빔 소스는 반도체 및 디스플레이 공정에 있어, 표면 에칭 및 증착 등 여러 응용 분야에 활발히 이용되고 있다. 본 연구에 사용된 원형 이온빔 소스는 선형 이온빔 소스의 가장자리에서의 특성 분석을 위해 제작되었으며, 높은 직류전압과 자기장 공간에서 플라즈마를 방전시키고 발생된 이온들을 가속시켜 높은 에너지의 이온빔을 발생시킨다. 이온빔 특성 분석을 위해 전위지연 탐침과 패러데이 탐침을 개발하였다. 전위지연 탐침은 격자판에 전압을 인가하여 선택적으로 이온을 수집하고, 이온의 에너지분포함수를 측정한다. 패러데이 탐침은 이온 수집기와 가드링으로 구성되어 수집기 표면에 일정한 플라즈마 쉬스를 형성하여 정확한 이온전류밀도를 측정한다. 본 연구에서는, 아르곤 기체를 이용하여 기체유량(8~12 sccm) 및 방전전압(1~2 kV)에 따라 방전전류 16~54 mA, 소모전력 16~108 mW의 특성을 보였다. 운전압력은 0.4~0.54 mTorr이며, 이온소스로부터 18 cm 거리에서 이온전류밀도와 이온에너지분포를 측정하였다. 또한, 중공음극선을 이용하여 인위적으로 전자를 이온 소스에서 발생된 플라즈마에 공급하고 이온빔 및 플라즈마의 특성 변화를 위 시스템에서 분석하였다.