• Journal of Information Processing Systems
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• v.13 no.2
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• pp.215-235
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• 2017

Foraging is a biological process, where a bacterium moves to search for nutriments, and avoids harmful substances. This paper proposes a hybrid approach integrating the bacterial foraging optimization algorithm (BFOA) in a radial basis function neural network, applied to image classification, in order to improve the classification rate and the objective function value. At the beginning, the proposed approach is presented and described. Then its performance is studied with an accent on the variation of the number of bacteria in the population, the number of reproduction steps, the number of elimination-dispersal steps and the number of chemotactic steps of bacteria. By using various values of BFOA parameters, and after different tests, it is found that the proposed hybrid approach is very robust and efficient for several-image classification.

• Journal of Astronomy and Space Sciences
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• v.21 no.4
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• pp.263-274
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• 2004

High resolution spectroscopic observations of BX And using the BOBS (Bohyunsan Optical Echelle Spectrograph) of Bohyunsan Optical Astronomical Observatory (BOAO) were performod during 26-27, Feb. 2003. From the observations, we obtained 38 line spectra of BX And which cover all phases except the phase interval between $0.^p1$ and $0.^p3$. Both methods of the CCF (Cross-Correlation Function) and BF (Broadening Function) were used to get the radial velocities of primary and secondary components. Both velocities of the primary and secondary stars were calculated with the BF method while only primary velocities were determined with the CCF. Using new radial velocity curves, the maximum radial velocities of the primary and secondary stars were obtained as $K_1=90.1km/s\;and\;K_2=196.6km/s$, respectively. New absolute dimension of BX And was deduced with the combination of our spectroscopic solution with the photometric one of Bell et al. (1990).

• Nonlinear Functional Analysis and Applications
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• v.26 no.2
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• pp.237-272
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• 2021

The main purpose of the present paper is to study the asymptotic behavior near the origin of radial solutions of the equation 𝚫_p u(x) + u^q(x) + f(x) = 0 in ℝ^N\{0}, where p > 2, q > 1, N ≥ 1 and f is a continuous radial function on ℝ^N\{0}. The study depends strongly of the sign of the function f and the asymptotic behavior near the origin of the function |x|^λf(|x|) with suitable conditions on λ > 0.

• Korean Journal of Materials Research
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• v.4 no.6
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• pp.644-650
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• 1994

The submicron powders of high-purity silicon have been produced by Electrohydrodynamic Atomization. Field-emission scanning transmission electron microscopy(STEM) is used to determine the microstructure and solidification phase. .Then it is found that the droplets less than 60nm diameter are solidified as the amorphous phase. A useful and accessible characterization of atomic arrangements in amorphous solids can be given in terms of a radial distribution function. According to experimental determinations of the radial distribution function for amorphous silicon, its similarity to the crystalline structure at small radial distances indicates that the basic tetrahedral arrangement found in the diamond cubic structure of silicon must be maintained in the amorphous structure.

• 한국정보통신설비학회:학술대회논문집
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• 2009.08a
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• pp.382-386
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• 2009

Online or sequential learning is one of the most basic and powerful method to train neuron network, and it has been widely used in disease detection, weather prediction and other realistic classification problem. At present, there are many algorithms in this area, such as MRAN, GAP-RBFN, OS-ELM, SVM and SMC-RBF. Among them, SMC-RBF has the best performance; it has less number of hidden neurons, and best efficiency. However, all the existing algorithms use signal normal distribution as kernel function, which means the output of the kernel function is same at the different direction. In this paper, we use multi-variable normal distribution as kernel function, and derive EKF learning formulas for multi-variable normal distribution kernel function. From the result of the experience, we can deduct that the proposed method has better efficiency performance, and not sensitive to the data sequence.

• Archives of Pharmacal Research
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• v.3 no.1
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• pp.13-16
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• 1980

The model of an isolated organ system has been constructed to simulated the behavior of drug in the circulatory system of an acting organ or site. The model is developed on the following assumptions : The drug in the microcirculatory system cannot permeate the capilary walls. The capilary bed is modeled as a simple ideal plug flow system with and without radial concentration gradient. The mathematical model is developed from basic considerations of drug distribution with hemodynamical and pharmacokinetical meanings. It is considered that a nonmetabolic drug substance is injected into the arterial inflow site of an isolated organ at a constant rate. The concentration of the drug in the outflow site is mathematically expressed as a function of time.

• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.63-71
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• 2011

Cardiac disorder data are generally tested using the classifier and QRS-Complex and R-R interval which is used in this experiment are often extracted by ECG(Electrocardiogram) signals. The experimentation of ECG data with classifier is generally performed with SVM(Support Vector Machine) and MLP(Multilayer Perceptron) classifier, but this study experimented with Best-First Decision Tree(B-F Tree) derived from the Dicision Tree among Random Forest classifier algorithms to improve accuracy. To compare and analyze accuracy, experimentation of SVM, MLP, RBF(Radial Basic Function) Network and Decision Tree classifiers are performed and also compared the result of announced papers carried out under same interval and data. Comparing the accuracy of Random Forest classifier with above four ones, Random Forest is the best in accuracy. As though R-R interval was extracted using Band-pass filter in pre-processing of this experiment, in future, more filter study is needed to extract accurate interval.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.634-639
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• 2003

It has been studied the flow near a rotating disk with surface topography. The system Ekman number is assumed very small, i.e., $E[{\equiv}\frac{\nu}{{\Omega}^{\ast}L^{\ast2}}]<<1$ in which $L^{\ast}$ denotes a disk radius, ${\nu}$ kinematic viscosity of the fluid and ${\Omega}^{\ast}$ angular velocity of the basic state. Disk surface has a sinusoidal topographic variation along radial coordinate, i.e., $z={\delta}cos(2{\pi}{\omega}r)$, where ${\delta}$ and ${\omega}$ are, respectively, nondimensional amplitude and wave number of the disk surface. Analytic solutions, being useful over the parametric ranges of ${\delta}{\sim}O$( $E^{1/2}$ ) and ${\omega}{\leq}O$ ( $E^{1/2}$ ), are secured in a series-function form of Fourier-Bessel type. An asymptotic behavior, when $E{\rightarrow}0$, is clarified as : for a disk with surface roughness, in contrast to the case of a flat disk, the azimuthal velocity increases in magnitude, together with the thickening boundary layer. The radial velocity, however, decreases in magnitude as the amplitude of surface waviness increases. Consequently, the overall Ekman pumping at the edge of the boundary layer remains unchanged, maintaining the constant value equal to that of the flat disk.

• Applied Microscopy
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• v.33 no.3
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• pp.195-204
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• 2003

The Experimental calibration method has been investigated to correct d-spacing estimation and to identify phases in the electron diffraction data acquired by imaging plates. When the diffraction data from the imaging plate was corrected by the d-spacing calibration method with the radial intensity distribution plotting in this experiment, The accuracy of d-spacing estimation was significantly increased in errors of about 0.5%. The experimental calibration equation followed up the first order exponential decay function was derived from the trace of d-spacing deviation between the measured and the calculated values. It was applied to the analysis of d-spacing and the phase identification of the transitional phases formed from [001] gibbsite specimen by electron beam irradiation effect. In this case more accurate phase identification and d-spacing evaluation is possible for the transitional phases whose diffraction patterns are complicatedly superimposed. It is concluded that ${\chi}$-alumina, ${\gamma}$-alumina and ${\sigma}$-alumina are clearly identified as the major transitional phases formed from gibbsite by electron beam irradiation for 120 min.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11C
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• pp.1085-1091
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• 2006

The major goal of this paper is to develop a practically implemental radial basis function (RBF) neural network based multi-user detector (MUD) for direct sequence (DS)-CDMA system. This work is expected to provide an efficient solution for RBF based MUD by quickly setting up the proper number of RBF centers and their locations required in training. The basic idea in this research is to estimate all the possible RBF centers by using supervised ${\kappa-means$ clustering technique, and select the only centers which locate near seemingly decision boundary between centers, and reduce further by grouping the some of centers adjacent each other. Therefore, it reduces the computational burden for finding the proper number of RBF centers and their locations in the existing RBF based MUD, and ultimately, make its implementation practical.