• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.12-18
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• 2011

In this paper, we proposed Interval Type-2 polynomial Radial Basis Function Neural Networks. In the receptive filed of hidden layer, Interval Type-2 fuzzy set is used. The characteristic of Interval Type-2 fuzzy set has Footprint Of Uncertainly(FOU), which denotes a certain level of robustness in the presence of un-known information when compared with the type-1 fuzzy set. In order to improve the performance of proposed model, we used the linear polynomial function as connection weight of network. The parameters such as center values of receptive field, constant deviation, and connection weight between hidden layer and output layer are optimized by Conjugate Gradient Method(CGM) and Space Search Evolutionary Algorithm(SSEA). The proposed model is applied to gas furnace dataset and its result are compared with those reported in the previous studies.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.247-249
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• 1995

A new localized imaging technique of reduced imaging time using a locally-linear gradient is proposed. Since most fast MR imaging methods need the whole k-space data corresponding to the whole imaging area, there are limitations in reducing the minimum imaging time. The imaging method proposed in this paper uses a specially-made gradient coil generating a local ramp-shape field and uniform field outside of the imaging area. Conventional imaging sequences can be used without any RF/gradient pulse sequence modifications. The proposed localized imaging technique has been implemented on a 2.0 Tesla whole-body system at KAIST and the imaging results show the utility of the proposed technique.

• Communications of the Korean Mathematical Society
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• v.35 no.2
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• pp.639-651
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• 2020

Consider a gradient Einstein-type metric in the setting of K-contact manifolds and (κ, µ)-contact manifolds. First, it is proved that, if a complete K-contact manifold admits a gradient Einstein-type metric, then M is compact, Einstein, Sasakian and isometric to the unit sphere 𝕊²ⁿ⁺¹. Next, it is proved that, if a non-Sasakian (κ, µ)-contact manifolds admits a gradient Einstein-type metric, then it is flat in dimension 3, and for higher dimension, M is locally isometric to the product of a Euclidean space 𝔼ⁿ⁺¹ and a sphere 𝕊ⁿ(4) of constant curvature +4.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.3
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• pp.32-38
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• 2005

FBG sensors have been studied more actively than any other fiber optic sensor because of good multiplexing capabilities among many fiber optic sensors. The demodulation method of FBG sensors is based on the detection of wavelength shift of their sensor peaks and properties such as strain and temperature can be measured by detecting them. However, the signal stability of FBG sensors can be influenced by the strain gradient induced by structural geometry or cracks on the surface when FBG sensors are embedded into or attached on the structure. In this study, the signal characteristics of reflected spectra of FBG sensors under strain gradient were verified and the relations between the grating length of FBG sensors and the amount of strain gradient were investigated. From the experimental results, the recommended working range of FBG sensors under strain gradients was shown quantitatively with respect to grating lengths of them.

• Bulletin of the Korean Space Science Society
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• 2004.04a
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• pp.35-35
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• 2004

Inhomogeneity Is important in wave coupling and mode conversion. We numerically examine the conversion of extraordinary(X) waves into upper hybrid(UH) waves in inhomogeneous plasmas by using a three-dimensional multi-fluid numerical model. A one-dimensional Inhomogeneous density profile is assumed in a cold and collisionless plasma. The density gradient is taken to be perpendicular to the magnetic field. An impulsive input is assumed to excite the X waves in the inhomogeneous box model. (omitted)

• The Bulletin of The Korean Astronomical Society
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• v.45 no.1
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• pp.64.2-64.2
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• 2020

We present the properties of galaxies in filaments around the Virgo cluster with respect to their vertical distance from the filament spine. Using the NASA-Sloan Atlas and group catalogs, we select galaxies that do not belong to groups in filaments. The filament member galaxies are then defined as those located within 3.5 scale length from the filament spine. The filaments are mainly (~86%) composed of low-mass dwarf galaxies of logh2M∗/M⊙ < 9 dominantly located on the blue cloud in color-magnitude diagrams. We observe that the g - r color and stellar mass of galaxies correlate with their vertical distance from the filament spine in which the color becomes red and stellar mass decreases with increasing vertical filament distance. The galaxies were divided into two subsamples in different stellar mass ranges, with lower-mass (logh2M∗/M⊙ ≤ 8) galaxies showing a clear negative g-r color gradient, whereas higher-mass (logh2M∗/M⊙ > 8) galaxies have a flat distribution against the vertical filament distance. We observe a negative EW(Hα) gradient for higher-mass galaxies, whereas lower-mass galaxies show no distinct variation in EW(Hα) against the vertical filament distance. In contrast, the NUV - r color distribution of higher-mass galaxies shows no strong dependence on the vertical filament distance, whereas the lower-mass galaxies show a distinct negative NUV - r color gradient. We do not witness clear gradients of HI fraction in either the higher- or lower-mass subsamples. We propose that the negative color and stellar mass gradients of galaxies can be explained by mass assembly from past galaxy mergers at different vertical filament distances. In addition, galaxy interactions might be responsible for the contrasting features of EW(Hα) and NUV - r color distributions between the higher- and lower-mass subsamples. The HI fraction distributions of the two subsamples suggest that ram-pressure stripping and gas accretion could be ignorable processes in the Virgo filaments.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2393-2398
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• 2003

In this paper, we proposes a new fuzzy inference system for modeling nonlinear systems given input and output data. In the suggested fuzzy inference system, the number of fuzzy rules and parameter values of membership functions are automatically decided by using the kernel-based method. The kernel-based method individually performs linear transformation and kernel mapping. Linear transformation projects input space into linearly transformed input space. Kernel mapping projects linearly transformed input space into high dimensional feature space. The structure of the proposed fuzzy inference system is equal to a Takagi-Sugeno fuzzy model whose input variables are weighted linear combinations of input variables. In addition, the number of fuzzy rules can be reduced under the condition of optimizing a given criterion by adjusting linear transformation matrix and parameter values of kernel functions using the gradient descent method. Once a structure is selected, coefficients in consequent part are determined by the least square method. Simulated result illustrates the effectiveness of the proposed technique.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.10
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• pp.896-901
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• 2015

The skin-frame type structure is designed to investigate the thermal deformation of the wing skin induced by the temperature gradient. In order to effectively simulate the temperature gradient on the wing specimen, a water cooling system is devised on the frame of the specimen. Out of surface skin deformation of the skin-frame type structure made of SUS304 material with respect to the temperature is successfully measured using the digital image correlation (DIC) technique including quantitative evaluation of the measurement uncertainty.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.373-373
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• 2000

In this paper, we propose a fuzzy modeling algorithm which divides the input space more efficiently than convention methods by taking into consideration correlations between components of sample data. The proposed fuzzy modeling algorithm consists of two steps: coarse tuning, which determines consequent parameters approximately using FCRM clustering method, and fine tuning, which adjusts the premise and consequent parameters more precisely by gradient descent algorithm. To evaluate the performance of the proposed fuzzy mode, we use the numerical data of nonlinear function.

• Journal of the Chungcheong Mathematical Society
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• v.20 no.1
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• pp.65-70
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• 2007

We study the existence of nontrivial solutions of the Gradient type Dirichlet boundary value problem for elliptic systems of the form $-{\Delta}U(x)={\nabla}F(x,U(x)),x{\in}{\Omega}$, where ${\Omega}{\subset}R^N(N{\geq}1)$ is a bounded regular domain and U = (u, v) : ${\Omega}{\rightarrow}R^2$. To study the system we use the liking theorem on product space.