• Nuclear Engineering and Technology
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• v.52 no.10
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• pp.2387-2393
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• 2020

In this study, a gradient material for shielding neutrons and gamma rays was developed, which consists of epoxy resin, boron carbide (B₄C), lead (Pb) and a little graphene oxide. It aims light weight and compact, which will be applied on the transportable nuclear reactor. The material is made up of sixteen layers, and the thickness and components of each layer were designed by genetic algorithm (GA) combined with Monte Carlo N Particle Transport (MCNP). In the experiment, the viscosities of the epoxy at different temperatures were tested, and the settlement regularity of Pb particles and B₄C particles in the epoxy was simulated by matlab software. The material was manufactured at 25 ℃, the Pb C and O elements of which were also tested, and the result was compared with the outcome of the simulation. Finally, the material's shielding performance was simulated by MCNP and compared with the uniformity material's. The result shows that the shielding performance of gradient material is more effective than that of the uniformity material, and the difference is most noticeable when the materials are 30 cm thick.

• Smart Media Journal
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• v.2 no.2
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• pp.14-19
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• 2013

Recently, due to the increase of the use of scanned images, the text segmentation techniques, which play critical role to optimize the quality of the scanned images, are required to be updated and advanced. In this study, an algorithm has been developed based on the modification of Gaussian mixture model (GMM) by integrating the calculation of Gaussian detection gradient and the estimation of the number clusters. The experimental results show an efficient method for text segmentation in natural scenes such as storefronts, street signs, scanned journals and newspapers at different size, shape or color of texts in condition of lighting changes and complex background. These indicate that our model algorithm and research approach can address various issues, which are still limitations of other senior algorithms and methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.2
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• pp.70-78
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• 1995

The identification of a fuzzy model using input-output data consists of two parts :Structure identification and parameter identification. In this paper an algorithm to identify those parameters and structures is suggested to solve the problems of the conventional methods. Given a set of input-output data, the consequent parameters are identified by the Hough transform and clustering method, each of which considers the linearity and continuity respectively. The gradient descent algorithm is used to fine-tune parameters of a fuzzy model. Finally, it is shown that this method is useful for the identification of a fuzzy model by simulation, where we only consider a single input and single output system.

• Structural Engineering and Mechanics
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• v.8 no.4
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• pp.401-410
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• 1999

A method of optimum design based on reliability for antenna structures is presented in this paper. By constructing the equivalent event, the formula is derived for calculating the reliability of reflector accuracy of antenna under the action of random wind load. The optimal model is developed, in which the cross sectional areas of member are treated as design variables, the structure weight as objective function, the reliability of reflector accuracy and the strength or stability of structural elements as constraints. The improved accelerated convergence gradient algorithm developed by the author is used. The design results show that the method in this paper is feasible and effective.

• Computers and Concrete
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• v.12 no.2
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• pp.229-241
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• 2013

The objective of this study is to reveal the sufficiency of neural networks (NN) as a securer, quicker, more robust and reliable method to be used in seismic assessment of existing reinforced concrete buildings. The NN based approach is applied as an alternative method to determine the seismic performance of each existing RC buildings, in terms of damage level. In the application of the NN, a multilayer perceptron (MLP) with a back-propagation (BP) algorithm is employed using a scaled conjugate gradient. NN based model wasd eveloped, trained and tested through a based MATLAB program. The database of this model was developed by using a statistical procedure called P25 method. The NN based model was also proved by verification set constituting of real existing RC buildings exposed to 2003 Bingol earthquake. It is demonstrated that the NN based approach is highly successful and can be used as an alternative method to determine the seismic performance of each existing RC buildings.

• Journal of information and communication convergence engineering
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• v.12 no.1
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• pp.60-65
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• 2014

This paper describes an efficient framework for the extraction of a brain tumor from magnetic resonance (MR) images. Before the segmentation process, a median filter is used to filter the image. Then, the morphological gradient is computed and added to the filtered image for intensity enhancement. After the enhancement process, the thresholding value is calculated using the mean and the standard deviation of the image. This thresholding value is used to binarize the image followed by the morphological operations. Moreover, the combination of these morphological operations allows to compute the local thresholding image supported by a flood-fill algorithm and a pixel replacement process to extract the tumor from the brain. Thus, this framework provides a new source of evidence in the field of segmentation that the specialist can aggregate with the segmentation results in order to soften his/her own decision.

• Journal of Communications and Networks
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• v.12 no.6
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• pp.600-604
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• 2010

A method of width adaptation in the radial basis function network (RBFN) using stochastic gradient (SG) algorithm is introduced. Using Taylor's expansion of error signal and differentiating the error with respect to the step-size, the optimal time-varying step-size of the width in RBFN is derived. The proposed approach to adjusting widths in RBFN achieves superior learning speed and the steady-state mean square error (MSE) performance in nonlinear channel environment. The proposed method has shown enhanced steady-state MSE performance by more than 3 dB in both nonlinear channel environments. The results confirm that controlling over step-size of the width in RBFN by the proposed algorithm can be an effective approach to enhancement of convergence speed and the steady-state value of MSE.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.224-241
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• 2015

Multiview plus depth (MVD) videos are widely used in free-viewpoint TV systems. The best-known technique to determine depth information is based on stereo vision. In this paper, we propose a novel local stereo matching algorithm which is radiometric invariant. The key idea is to use a combined matching cost of intensity and gradient based similarity measure. In addition, we realize an adaptive cost aggregation scheme by constructing an adaptive support window for each pixel, which can solve the boundary and low texture problems. In the disparity refinement process, we propose a four-step post-processing technique to handle outliers and occlusions. Moreover, we conduct stereo reconstruction tests to verify the performance of the algorithm more intuitively. Experimental results show that the proposed method is effective and robust against local radiometric distortion. It has an average error of 5.93% on the Middlebury benchmark and is compatible to the state-of-art local methods.

• Journal of the Korean Society of Tobacco Science
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• v.20 no.1
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• pp.87-94
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• 1998

After we made the computer source code with mathematical model of Muramatsu et al. that was expressed by the set of simultaneous first-order ordinary differential equations in evaporation-pyrolysis zone of cigarette, we simulated the distribution profiles of temperature and density of flue-cured tobacco. Those equations were solved numerically with the Runge-Kutta-Gill algorithm assuming step size of 0.025mm by Muramatsu at at,, but in this study the advanced algorithm of Runge-Kutta 4th Order assuming step size of 0.0005mm. The initial conditions and physical parameters of Muramatsu et at. were used for solving them. The calculated values corresponded well with results of Muramatsu et al., especially the gradient of the temperature profile increased with smoldering speed and the thickness of the evaporation-pyrolysis zone decreased with increasing of smoldering speed. On the other hand, the temperature gradient decreased with increasing of the effective thermal-conductivity value and the thickness of the evaporation-pyrolysis zone increased with the effective thermal-conductivity value.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.330-340
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• 2002

In this Paper. a non-linear approach to a design of model reference adaptive control is presented. The approach is demonstrated by a case study of a simple single-pole and no zero, linear, discrete-time plant. The essence of the idea is to generate a full non-linear model of the plant dynamics and the parameter adaptation dynamics as a gradient descent algorithm with respect to a Riemannian metric. It is shown how a Riemannian metric can be chosen so that the modelled plant dynamics do in fact match the true plant dynamics. The performance of the proposed scheme is compared to a traditional model reference adaptive control scheme using the classical sensitivity derivatives (Euclidean gradients) for the descent algorithm.