• Journal of applied mathematics & informatics
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• v.42 no.3
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• pp.635-646
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• 2024

In this research work, we introduce and investigate four innovative types of soft spaces, pushing the boundaries of traditional spatial concepts. These new types of soft spaces are named as soft T_b space, soft T^#_b space, soft T^##_b space and soft_αT^#_b space. Through rigorous analysis and experimentation, we uncover and propose distinct characteristics that define and differentiate these spaces. In this research work, we have established that every soft $T_{\frac{1}{2}}$ space is a soft _αT^#_b space, every soft T_b space is a soft _αT^#_b space, every soft T^#_b space is a soft _αT^#_b space, every soft T_b space is a soft T^#_b space, every soft T^#_b space is a soft T^##_b space, every soft $T_{\frac{1}{2}}$ space is a soft ^#T_b space and every soft T_b space is a soft #T_b space.

• Korean Journal of Digital Imaging in Medicine
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• v.9 no.1
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• pp.21-30
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• 2007

Our objective was to evaluate the CT attenuation coefficient and noise of spatial domain filtering as an alternative to additional image reconstruction using different kernels in abdominal CT. Derived from thin collimated source images was generated using abdomen B10 (very smooth), B20 (smooth), B30 (medium smooth), B40 (medium), B50 (medium sharp), B60 (sharp), B70 (very sharp) and B80 (ultra sharp) kernels. Quantitative CT coefficient and noise measurements provided comparable HU (hounsfield) units in this respect. CT attenuation coefficient (mean HU) values in the abdominal were 60.4$\sim$62.2 HU and noise (7.6$\sim$63.8 HU) in the liver parenchyma. In the stomach a mean (CT attenuation coefficient) of -2.2$\sim$0.8 HU and noise (10.1$\sim$82.4 HU) was measured. Image reconstructed with a convolution kernel led to an increase in noise, whereas the results for CT attenuation coefficient were comparable. Image medications of image sharpness and noise eliminate the need for reconstruction using different kernels in the future. CT images increase the diagnostic accuracy may be controlled by adjusting CT various kernels, which should be adjusted to take into account the kernels of the CT undergoing the examination.

• Journal of the Chungcheong Mathematical Society
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• v.19 no.4
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• pp.393-402
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• 2006

We investigate relations between multiplicity of solutions and source terms in a elliptic equation. We have a concerne with a sharp result for multiplicity of a nonlinear Laplacian differential equation.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.762-765
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• 2004

Patterned alignment of reactive mesogens on a grating was investigated for use in phase retarders. The relative importance of the topology and the surface energy of the grating for RM alignment is discussed. Possible mechanisms of RM alignment for different grating pitches are discussed.

• Bulletin of the Korean Mathematical Society
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• v.45 no.1
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• pp.1-10
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• 2008

We prove a sharp inequality for some multilinear operator related to Marcinkiewicz integral operator. As application, we obtain the weighted norm inequality and L log L type estimate for the multilinear operator.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.595-596
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• 2011

• Journal of the Chungcheong Mathematical Society
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• v.23 no.4
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• pp.629-633
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• 2010

In this paper we provide a sharp lower bound of the first Neumann eigenvalue of a compact hypersurface $\Sigma$ inside a convex set C in a Riemannian manifold under the assumption that ${\partial}{\Sigma}$ meets ${\partial}C$ orthogonally.

• Communications of the Korean Mathematical Society
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• v.38 no.2
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• pp.461-468
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• 2023

This paper attempts to investigate a new subfamily 𝓢𝓣_𝜗,𝜎 (𝛼, 𝛽, 𝛾, 𝜇) of spirallike functions endowed with Mittag-Leffler and Wright functions. The paper further investigates sharp coefficient bounds for functions that belong to this class.

• Journal of the Korean Mathematical Society
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• v.45 no.4
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• pp.1089-1100
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• 2008

For a pointed space X, the subgroups of self-homotopy equivalences $Aut_{\sharp}_N(X)$, $Aut_{\Omega}(X)$, $Aut_*(X)$ and $Aut_{\Sigma}(X)$ are considered, where $Aut_{\sharp}_N(X)$ is the group of all self-homotopy classes f of X such that $f_{\sharp}=id\;:\;{\pi_i}(X){\rightarrow}{\pi_i}(X)$ for all $i{\leq}N{\leq}{\infty}$, $Aut_{\Omega}(X)$ is the group of all the above f such that ${\Omega}f=id;\;Aut_*(X)$ is the group of all self-homotopy classes g of X such that $g_*=id\;:\;H_i(X){\rightarrow}H_i(X)$ for all $i{\leq}{\infty}$, $Aut_{\Sigma}(X)$ is the group of all the above g such that ${\Sigma}g=id$. We will prove that $Aut_{\Omega}(X_1{\times}\cdots{\times}X_n)$ has two factorizations similar to those of $Aut_{\sharp}_N(X_1{\times}\cdots{\times}\;X_n)$ in reference [10], and that $Aut_{\Sigma}(X_1{\vee}\cdots{\vee}X_n)$, $Aut_*(X_1{\vee}\cdots{\vee}X_n)$ also have factorizations being dual to the former two cases respectively.

• Journal of Broadcast Engineering
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• v.12 no.4
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• pp.350-359
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• 2007

In this paper we present a simple, efficient method for detection of sharp digital images. Recently many digital cameras are equipped with various autofocusing functions to help users take well-focused pictures as easily as possible. However, acquired digital pictures can be further degraded by motion, limited contrast, and inappropriate amount of exposure, to name a few. In order to decide whether to process the image or not, or whether to delete it or not, reliable measure of image quality to detect sharp images from blurry ones is needed. This paper presents a blurriness/sharpness measure, and demonstrates its feasibility using extensive experiments. This method is fast and easy to implement, and accurate. Regardless of the detection accuracy, existing measures are computation-intensive. However, the proposed measure in this paper is not demanding in computation time. Needless to say, this measure can be used for various imaging applications including autofocusing and astigmatism correction.