Institution
Kyonggi University
Education•Suwon, South Korea•
About: Kyonggi University is a education organization based out in Suwon, South Korea. It is known for research contribution in the topics: Catalysis & Dielectric. The organization has 1946 authors who have published 4404 publications receiving 64791 citations.
Topics: Catalysis, Dielectric, Patch antenna, Microstrip antenna, Coating
Papers published on a yearly basis
Papers
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TL;DR: In this article, graphite powders were coated with ZrO2 by the controlled hydrolysis of a zirconium oxychloride aqueous solution, which was carried out with temperature control.
Abstract: Graphite powders were coated with ZrO2 by the controlled hydrolysis of a zirconium oxychloride aqueous solution. Thehydrolysis process was carried out with temperature control because of the low wettability of ZrO2 to the surface of thegraphite. PVA was added to the solution for the enhancement of Zr ion adsorption. The surface of the graphite particles coatedwith ZrO2 was observed by TEM. There are two types of ZrO2 particles; (a) primary particles a few nm in size and (b) secondary particles with ∼0.1 μm size were obtained. The data of oxidation weight loss and surface potentialshow that the graphite surface was successfully modified by the forced hydrolysis of the zirconium chloride aqueous solution.
41 citations
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TL;DR: In this article, a correlated function expansion (CFE) is introduced to identify the role of independent and correlated composition variations upon a desired material property, and to provide an efficient means to compute the property throughout the composition space.
Abstract: A correlated function expansion (CFE) is introduced (a) to identify the role of independent and correlated composition variations upon a desired material property, and (b) to provide an efficient means to compute the property throughout the composition space. As an example the contributions of independent and correlated composition behavior upon the principal energy band gaps for the alloys ${\mathrm{Ga}}_{\mathrm{\ensuremath{\alpha}}}{\mathrm{In}}_{1\mathrm{\ensuremath{-}}\mathrm{\ensuremath{\alpha}}}{\mathrm{P}}_{\mathrm{\ensuremath{\beta}}}{\mathrm{As}}_{1\mathrm{\ensuremath{-}}\mathrm{\ensuremath{\beta}}}$ and ${\mathrm{Ga}}_{\mathrm{\ensuremath{\alpha}}}{\mathrm{In}}_{1\mathrm{\ensuremath{-}}\mathrm{\ensuremath{\alpha}}}{\mathrm{P}}_{\mathrm{\ensuremath{\beta}}}{\mathrm{Sb}}_{\mathrm{\ensuremath{\gamma}}}{\mathrm{As}}_{1\mathrm{\ensuremath{-}}\mathrm{\ensuremath{\beta}}\mathrm{\ensuremath{-}}\mathrm{\ensuremath{\gamma}}}$ are calculated and analyzed by applying the CFE to the universal tight-binding (UTB) Hamiltonian model of the alloys. The convergence properties of the CFE over the entire composition variable space (\ensuremath{\alpha},\ensuremath{\beta},\ensuremath{\gamma}) are examined upon including independent, pair-, and triple-correlated terms. By retaining only independent component contributions in the CFE it was possible to represent the UTB results to better than 90% accuracy for both the alloys ${\mathrm{Ga}}_{\mathrm{\ensuremath{\alpha}}}{\mathrm{In}}_{1\mathrm{\ensuremath{-}}\mathrm{\ensuremath{\alpha}}}{\mathrm{P}}_{\mathrm{\ensuremath{\beta}}}{\mathrm{As}}_{1\mathrm{\ensuremath{-}}\mathrm{\ensuremath{\beta}}}$ and ${\mathrm{Ga}}_{\mathrm{\ensuremath{\alpha}}}{\mathrm{In}}_{1\mathrm{\ensuremath{-}}\mathrm{\ensuremath{\alpha}}}{\mathrm{P}}_{\mathrm{\ensuremath{\beta}}}{\mathrm{Sb}}_{\mathrm{\ensuremath{\gamma}}}{\mathrm{As}}_{1\mathrm{\ensuremath{-}}\mathrm{\ensuremath{\beta}}\mathrm{\ensuremath{-}}\mathrm{\ensuremath{\gamma}}}.$ Pair composition correlations contributed approximately 5--10 % to the band gaps in both alloys and for ${\mathrm{Ga}}_{\mathrm{\ensuremath{\alpha}}}{\mathrm{In}}_{1\mathrm{\ensuremath{-}}\mathrm{\ensuremath{\alpha}}}{\mathrm{P}}_{\mathrm{\ensuremath{\beta}}}{\mathrm{Sb}}_{\mathrm{\ensuremath{\gamma}}}{\mathrm{As}}_{1\mathrm{\ensuremath{-}}\mathrm{\ensuremath{\beta}}\mathrm{\ensuremath{-}}\mathrm{\ensuremath{\gamma}}}$ the triple correlations were at the level of $\ensuremath{\sim}3%.$ The CFE is a generic tool capable of simplifying efforts at finding desired alloy compositions for material properties.
41 citations
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TL;DR: In this article, a reconfigurable rhombus-shaped patch antenna with a Y-shaped feedline for polarization diversity is proposed, which exhibits a simple structure, which consists of two p-i-n diodes, and a Yshaped feed line.
Abstract: In this letter, a reconfigurable rhombus-shaped patch antenna with a Y-shaped feedline for polarization diversity is proposed This antenna exhibits a simple structure, which consists of a rhombus-shaped patch, two p-i-n diodes, and a Y-shaped feedline The two p-i-n diodes are inserted in the gap between the rhombus-shaped patch and the Y-shaped feedline In order to easily supply a dc bias voltage to the p-i-n diodes, a shorting pin is inserted in the center of the rhombus-shaped patch The proposed antenna can be operated in two modes—the left-hand circular polarization (LHCP) and right-hand circular polarization (RHCP) modes—by electrically controlling the two p-i-n diodes The measured 10-dB reflection coefficient and 3-dB axial-ratio bandwidths of the prototype antenna are approximately 562% and 2%, respectively
41 citations
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TL;DR: In this paper, the authors show that the Ca2+ ions of SCSON:Eu2+ preferentially changed the emission wavelength assigned to Eu(I) and affected the emission intensity.
Abstract: Sr2–y–zCazSi(O1–xNx)4:yEu2+ (SCSON:Eu2+) solid solutions were prepared by substituting N3-, Eu2+, and Ca2+ ions into Sr2SiO4 (SSO). These ions contributed differently to the evolution of luminescence of SCSON:Eu2+. SSON:Eu2+ (z = 0) has two activation centers: Eu(I) and Eu(II). The nitridation effects led to a dramatic change in the crystal field surrounding the Eu(II) site but rarely affected the Eu(I) site. Accordingly, SSON:Eu2+ exhibited broad excitation spectra from ultraviolet to visible wavelengths. In comparison with the Eu(II) green emissions of SSO:Eu2+, the dominant peak wavelengths (DPWs) of the Eu(II) emissions were at red emission regions (605–630 nm), depending on the amount of Eu2+ ions. The Ca2+ ions of SCSON:Eu2+ preferentially changed the emission wavelength assigned to Eu(I) and affected the Eu(II) emission intensity. In addition to the spectral properties, the chromaticity coordinates and a low thermal quenching behavior of SCSON:Eu2+ powders demonstrated that they can be a novel red ...
41 citations
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TL;DR: In this paper, a novel generative adversarial network (GAN)-based conjugate gradient SENSE (CG-SENSE) reconstruction framework was proposed for motion correction in multishot MRI.
Abstract: Multishot Magnetic Resonance Imaging (MRI) is a promising data acquisition technique that can produce a high-resolution image with relatively less data acquisition time than the standard spin echo. The downside of multishot MRI is that it is very sensitive to subject motion and even small levels of motion during the scan can produce artifacts in the final magnetic resonance (MR) image, which may result in a misdiagnosis. Numerous efforts have focused on addressing this issue; however, all of these proposals are limited in terms of how much motion they can correct and require excessive computational time. In this paper, we propose a novel generative adversarial network (GAN)-based conjugate gradient SENSE (CG-SENSE) reconstruction framework for motion correction in multishot MRI. First CG-SENSE reconstruction is employed to reconstruct an image from the motion-corrupted k-space data and then the GAN-based proposed framework is applied to correct the motion artifacts. The proposed method has been rigorously evaluated on synthetically corrupted data on varying degrees of motion, numbers of shots, and encoding trajectories. Our analyses (both quantitative as well as qualitative/visual analysis) establish that the proposed method is robust and reduces several-fold the computational time reported by the current state-of-the-art technique.
41 citations
Authors
Showing all 1964 results
Name | H-index | Papers | Citations |
---|---|---|---|
Huu Hao Ngo | 75 | 624 | 24545 |
Jaejung Ko | 48 | 214 | 8615 |
Sang-Ho Lee | 39 | 354 | 4991 |
Hoon Kim | 37 | 605 | 6010 |
Soon-Gil Yoon | 36 | 393 | 4887 |
Dinh Duc Nguyen | 35 | 232 | 4313 |
Soon Woong Chang | 35 | 164 | 4004 |
Dukjoon Kim | 35 | 242 | 5133 |
Kun Chang Lee | 34 | 243 | 5077 |
Ashraf F. Ashour | 33 | 157 | 3745 |
Hyejin Lee | 31 | 154 | 2894 |
Kyung-Yong Chung | 31 | 237 | 3089 |
Eung Soo Kim | 31 | 191 | 3053 |
Choongwan Koo | 31 | 98 | 2650 |
Do-Hee Kim | 30 | 125 | 2559 |