• Investigative Magnetic Resonance Imaging
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• v.26 no.2
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• pp.104-116
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• 2022

The purpose of this study is to systematically determine an optimal percentile cut-off in histogram analysis for calculating the mean parameters obtained from a non-Gaussian continuous-time random-walk (CTRW) diffusion model for differentiating individual glioma grades. This retrospective study included 90 patients with histopathologically proven gliomas (42 grade II, 19 grade III, and 29 grade IV). We performed diffusion-weighted imaging using 17 b-values (0-4000 s/mm²) at 3T, and analyzed the images with the CTRW model to produce an anomalous diffusion coefficient (D_m) along with temporal (𝛼) and spatial (𝛽) diffusion heterogeneity parameters. Given the tumor ROIs, we created a histogram of each parameter; computed the P-values (using a Student's t-test) for the statistical differences in the mean D_m, 𝛼, or 𝛽 for differentiating grade II vs. grade III gliomas and grade III vs. grade IV gliomas at different percentiles (1% to 100%); and selected the highest percentile with P < 0.05 as the optimal percentile. We used the mean parameter values calculated from the optimal percentile cut-offs to do a receiver operating characteristic (ROC) analysis based on individual parameters or their combinations. We compared the results with those obtained by averaging data over the entire region of interest (i.e., 100th percentile). We found the optimal percentiles for D_m, 𝛼, and 𝛽 to be 68%, 75%, and 100% for differentiating grade II vs. III and 58%, 19%, and 100% for differentiating grade III vs. IV gliomas, respectively. The optimal percentile cut-offs outperformed the entire-ROI-based analysis in sensitivity (0.761 vs. 0.690), specificity (0.578 vs. 0.526), accuracy (0.704 vs. 0.639), and AUC (0.671 vs. 0.599) for grade II vs. III differentiations and in sensitivity (0.789 vs. 0.578) and AUC (0.637 vs. 0.620) for grade III vs. IV differentiations, respectively. Percentile-based histogram analysis, coupled with the multi-parametric approach enabled by the CTRW diffusion model using high b-values, can improve glioma grading.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.11
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• pp.85-92
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• 1992

In this paper we propose a diffusion neural network model. In this model, each excitatory and inhibitory neuron has the capability of diffusing external excitations. We show that this model can be used for the detection of intensity changes of an input image. The relations between the diffusion coefficient, the iteration number of diffusion, and the detected spatial frequency are analyzed. The calculation time is reduced than that of a LOG(a Laplacian of a Gaussian) method.

• Structural Engineering and Mechanics
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• v.75 no.2
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• pp.133-144
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• 2020

This investigation is to study the effect of gravitational field and diffusion on a microstretch thermoelastic medium heating by a non-Gaussian laser beam. The problem was studied in the context of the dual-phase-lag model. The normal mode analysis is used to solve the problem to obtain the exact expressions for the non-dimensional displacement components, the micro-rotation, the stresses, and the temperature distribution. The effect of time parameter, heat flux parameter and gravity response of three theories of thermoelasticity i.e. dual-phase-lag model (DPL), Lord and Shulman theory (L-S) and coupled theory (CT) on these quantities have been depicted graphically for a particular model.

• Journal of Radiation Protection and Research
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• v.12 no.2
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• pp.28-36
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• 1987

Gaussian plume model is used to assess environmental dose for abnormal radioactive release in nuclear facility, but there has a problem to use it for complex terrain. In this report, MATTEW and WIND04 Codes which had been verified were used to calculate wind field in the complex terrain. Under the base of these codes principle, wind fields were obtained from the calculation of the finite difference approximation for advection-diffusion equations which satisfy the mass-conservative law. Particle concentrations and external doses were calculated by using PIC model which approximate the particle to radioactive cloud, and atmospheric diffusion of the particles from the random walk method. The results show that the adjusted wind fields and the distributions of the exposure dose vary with the topography of the complex terrain.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.9 no.3
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• pp.115-124
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• 1997

We measured the variance of eddy diffusion and associated ‘diffusion coefficients’ in coastal regions of Korea by observing the separation distances among multiple drifters deployed simultaneously at the same initial position. The variance of eddy diffusion was found to be proportional to $t^m$, where t is the time and m is a non-integer scaling exponent between 1.5 and 3.5. The observed scaling exponent of eddy diffusion cannot be reproduced by diffusion models employing constant eddy diffusivity. In this study, we applied fractal theory in simulating exponential increase of variance of eddy diffusion. We employed the fGn(fractional Gaussian noise) as a ‘modified’ random walks corresponding to the oceanic eddy diffusion. The variance of eddy diffusion, which corresponds to the fBm(fractional Brown motion) of our diffusion model, is proportional to $t^{2H}$, where H is Hurst scaling exponent. The temporal increase of the variance. with scaling exponent between 1 and 2, was successfully reproduced by our fractal diffusion model. However, our model cannot reproduce scaling exponent greater than 2. The scaling exponents greater than 2 are associated with the velocity shear of the mean flow.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.6
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• pp.757-765
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• 1999

Lagrangian particle dispersion model(LPDM) is an effective tool to calculate the dispersion from a point source since it dose not induce numerical diffusion errors in solving the pollutant dispersion equation. Fictitious particles are released to the atmosphere from the emission source and they are then transported by the mean velocity and diffused by the turbulent eddy motion in the LPDM. The concentration distribution from the dispersed particles in the calculation domain are finally estimated by applying a particle count method or a Gaussian kernel method. The two methods for calculating concentration profiles were compared each other and tested against the analytic solution and the tracer experiment to find the strength and weakness of each method and to choose computationally time saving method for the LPDM. The calculated concentrations from the particle count method was heavily dependent on the number of the particles released at the emission source. It requires lots fo particle emission to reach the converged concentration field. And resulting concentrations were also dependent on the size of numerical grid. The concentration field by the Gaussian kernel method, however, converged with a low particle emission rate at the source and was in good agreement with the analytic solution and the tracer experiment. The results showed that Gaussian kernel method was more effective method to calculate the concentrations in the LPDM.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1994.11a
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• pp.40-45
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• 1994

The TCAD(Technology Computer Aided Design) software tool is a popular name to be able to simulate the semiconductor process and device circuit. We have developed a two-dimensional TCAD software tool included an editor, parser, each process unit, and 2D, 3D graphic routine that is Integrated Environment. The initial grid for numerical analysis is automatically generated with the geometric series that use the user default(given) line and position separated with grid interval and the nodes corresponding to each mesh point stoic the all the possible attribute. Also, we made a data structure called PIF for input or output. Methods of ion implantation in this paper arc Monte Carlo, Gaussian Pearson and Dual-Pearson. Analytical model such as Gaussian, Pearson and Dual-Pearson were considered the multilayer structure and two-dimensional tilted implantation. We simuttaneously calculated the continuity equation of impurity and point defect in diffusion simulation. Oxidation process was simulated by analytical ERFC(Complementary Error Function) model for local oxidation.

• Journal of Radiation Protection and Research
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• v.23 no.4
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• pp.251-257
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• 1998

A diffusion model of radioactive gaseous effluents is improved to apply for domestic nuclear power plants. Up to now, XOQDOQ computer code package developed by U. S NRC has been used for the assessment of radioactive plume dispersion by normal operation of domestic nuclear power plants. XOQDOQ adopts the straight-line Gaussian plume model which was basically derived for the plane terrain. However, since there are so many mountains in Korea, the several shortcomings of XOQDOQ are improved to consider the complex terrain effects. In this work, wind direction change is considered by modifying the wind rose frequency using meteorological data of the local weather stations. In addition, an effective height correction model, a plume reduction model due to plume penetration into mountain, and a wet deposition model are adopted for more realistic assessments. The proposed methodology is implemented in Yongkwang nuclear power plants, and can be used for other domestic nuclear power plants.

• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.891-896
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• 2009

The puff models have been developed to simulate the advection-diffusion processes of dredging suspended solids, either alone or in combination with Eulerian models. Computational efficiency and accuracy are of prime importance in designing these hybrid approaches to simulate a pollutant discharge, and we characterize two relatively simple Lagrangian techniques in this regard: forward Gaussian puff tracking (FGPT), and backward Gaussian puff tracking (BGPT). FGPT and BGPT offer dramatic savings in computational expense, but their applicability is limited by accuracy concerns in the presence of spatially variable flow or diffusivity fields or complex no-flux or open boundary conditions. For long simulations, particle and/or puff methods can transition to an Eulerian model if appropriate, since the relative computational expense of Lagrangian methods increases with time for continuous sources. Although we focus on simple Lagrangian models that are not suitable to all environmental applications, many of the implementation and computational efficiency concerns outlined herein would also be relevant to using higher order particle and puff methods to extend the near field.

• Journal of IKEEE
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• v.24 no.4
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• pp.1136-1140
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• 2020

As air pollution caused by fine dust becomes serious, interest in the spread of fine dust and prediction of air quality is increasing. The causes of fine dust are very diverse, and some fine dust naturally occurs through forest fires and yellow dust, but most of them are known to be caused by air pollutants from burning fossil fuels such as petroleum and coal or from automobile exhaust gas. In this paper, the CALPUFF model recommended by the US EPA is used, and CALPUFF diffusion modeling is performed by generating a wind field through the CALMET model as a meteorological preprocessing program that generates a three-dimensional wind field, which is a meteorological element required by CALPUFF. Through this, we propose a fine dust diffusion modeling and air quality prediction system that reflects complex topography.