• Korean Journal of Mathematics
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• v.19 no.1
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• pp.101-109
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• 2011

We get a theorem which shows that there exist at least two or three nontrivial weak solutions for the nonlinear parabolic boundary value problem with the variable coefficient jumping nonlinearity. We prove this theorem by restricting ourselves to the real Hilbert space. We obtain this result by approaching the topological method. We use the Leray-Schauder degree theory on the real Hilbert space.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.7
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• pp.138-146
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• 2003

A critical issue in area-based stereo matching lies in selecting a fixed rectangular window size. Previous stereo methods doesn't deal effectively with occluding boundary due to inevitable window-based problems, and so give inaccurate and noisy matching results in areas with steep disparity variations. In this paper, a variable window approach is presented to estimate accurate, detailed and smooth disparities for three-dimensional structure reconstruction. It makes the smoothing of depth discontinuity reduced by evaluating corresponding correlation values and intensity gradient-based similarity in the three-dimensional disparity space. In addition, it investigates maximum connected match candidate points and then devise the novel arbitrarily shaped variable window representative of a same disparity to treat with disparity variations of various structure shapes. We demonstrate the performance of the proposed variable window method with synthetic images, and show how our results improve on those of closely related techniques for accuracy, robustness, matching density and computing speed.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.63-66
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• 1988

In the control of the robotic manipulators, the variable structure control method for the get Point Regualation has a advantage of the insensitivity about parameter variations and disturbances. When the robotic manipulators are controlled by a point-to-point scheme, no path constraint is considered. Thus, the variable structure control method will be effectively applied only if the trajectory of the robot hand is estimated precisely. In this paper, the joint trajectories in the joint space and the hand trajectory in the cartesian space are calculated by the variable structure control method, and an algorithm is suggested to elaborate the deviation error of the robot hand from a straight line path. The result of this study will become a base of the effective path planning about robotic manipulators with the variable structure control concept.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.12
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• pp.1601-1609
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• 1988

In the control of the robotic manipulators, the variable structure control method for the set point Regualation has an advantage of the insensitivity about parameter variations and disturbances. When the robotic manipulatores are controlled by a point-to-point scheme, no path constraint is considered. Thus, the variable structure control method will be effectively applied only if the trajectory of the robot hand is estimated precisely. In this paper, the joint trajectories in the joint space and the hand trajectory in the cartesian space are calculated by the variable structure control method, and an algorithm is suggested to elaborate the deviation error of the robot hand from a straight line path. The result of this study will become a base of the effective path planning about robotic manipulators with the variable structure control concept.

• Kyungpook Mathematical Journal
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• v.64 no.2
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• pp.271-286
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• 2024

In this paper, we prove the existence of distributional solutions in the anisotropic Sobolev space $\mathring{W}^{1,\overrightarrow{p}(\cdot)}(\Omega)$ with variable exponents and zero boundary, for a class of variable exponents anisotropic nonlinear elliptic equations having a compound nonlinearity $G(x, u)=\sum_{i=1}^{N}(\left|f\right|+\left|u\right|)^{p_i(x)-1}$ on the right-hand side, such that f is in the variable exponents anisotropic Lebesgue space $L^{\vec{p}({\cdot})}(\Omega)$, where $\vec{p}({\cdot})=(p_1({\cdot}),{\ldots},p_N({\cdot})){\in}(C(\bar{\Omega},]1,+{\infty}[))^N$.

• Journal of The Korean Astronomical Society
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• v.51 no.5
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• pp.129-142
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• 2018

The DEEP-South (the Deep Ecliptic Patrol of the Southern Sky) photometric census of small Solar System bodies produces massive time-series data of variable, transient or moving objects as a by-product. To fully investigate unexplored variable phenomena, we present an application of multi-aperture photometry and FastBit indexing techniques for faster access to a portion of the DEEP-South year-one data. Our new pipeline is designed to perform automated point source detection, robust high-precision photometry and calibration of non-crowded fields which have overlap with previously surveyed areas. In this paper, we show some examples of catalog-based variability searches to find new variable stars and to recover targeted asteroids. We discover 21 new periodic variables with period ranging between 0.1 and 31 days, including four eclipsing binary systems (detached, over-contact, and ellipsoidal variables), one white dwarf/M dwarf pair candidate, and rotating variable stars. We also recover astrometry (< ${\pm}1-2$ arcsec level accuracy) and photometry of two targeted near-earth asteroids, 2006 DZ169 and 1996 SK, along with the small- (~0.12 mag) and relatively large-amplitude (~0.5 mag) variations of their dominant rotational signals in R-band.

• Steel and Composite Structures
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• v.38 no.4
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• pp.447-462
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• 2021

In this work, we consider a problem in the context of thermoelectric materials with memory-dependent derivative for a half space which is assumed to have variable thermal conductivity depending on the temperature. The Lamé's modulii of the half space material is taken as a function of the vertical distance from the surface of the medium. The surface is traction free and subjected to a time dependent thermal shock. The problem was solved by using the Laplace transform method together with the perturbation technique. The obtained results are discussed and compared with the solution when Lamé's modulii are constants. Numerical results are computed and represented graphically for the temperature, displacement and stress distributions. Affectability investigation is performed to explore the thermal impacts of a kernel function and a time-delay parameter that are characteristic of memory dependent derivative heat transfer in the behavior of tissue temperature. The correlations are made with the results obtained in the case of the absence of memory-dependent derivative parameters.

• The Bulletin of The Korean Astronomical Society
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• v.30 no.2
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• pp.70.2-70.2
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• 2005

• The Bulletin of The Korean Astronomical Society
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• v.31 no.2
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• pp.62.2-62.2
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• 2006

• The Korean Journal of Applied Statistics
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• v.10 no.2
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• pp.293-308
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• 1997

Sliced inverse regression is a method for reducing the dimension of the explanatory variable X without going through any parametric or nonparametric model fitting process. This method explores the simplicity of the inverse view of regression; that is, instead of regressing the univariate output varable y against the multivariate X, we regress X against y. In this article, we propose bivariate sliced inverse regression, whose method regress the multivariate X against the bivariate output variables $y_1, Y_2$. Bivariate sliced inverse regression estimates the e.d.r. directions of satisfying two generalized regression model simultaneously. For the application of bivariate sliced inverse regression, we decompose the output variable y into two variables, one variable y gained by projecting the output variable y onto the column space of X and the other variable r through projecting the output variable y onto the space orthogonal to the column space of X, respectively and then estimate the e.d.r. directions of the generalized regression model by utilize two variables simultaneously. As a result, bivariate sliced inverse regression of considering the variable y and r simultaneously estimates the e.d.r. directions efficiently and steadily when the regression model is linear, quadratic and nonlinear, respectively.