• The Journal of the Korea Contents Association
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• v.13 no.6
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• pp.55-66
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• 2013

In these days, small devices like smartphones, TV, and projectors are popular, and they are being developed rapidly. The projector is being used in cinema and exhibition because it makes a big screen. This feature makes new expression named projection-mapping in art world. Projection-mapping is being utilized extensively in stages of performances, and it use variety of shape's screens. But projection-mapping has limitation in space. So in this paper, we propose new performance system for projection-mapping and it make possible to overcome many difficulties. Also, we discuss the result of using the system in actual performance. We hope to develop the utilization of projection-mapping in performance.

• Investigative Magnetic Resonance Imaging
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• v.25 no.4
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• pp.300-312
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• 2021

Compressed sensing (CS) has been investigated in magnetic resonance (MR) parametric mapping to reduce scan time. However, the relatively long reconstruction time restricts its widespread applications in the clinic. Recently, deep learning-based methods have shown great potential in accelerating reconstruction time and improving imaging quality in fast MR imaging, although their adaptation to parametric mapping is still in an early stage. In this paper, we proposed a novel deep learning-based framework DEMO for fast and robust MR parametric mapping. Different from current deep learning-based methods, DEMO trains the network in an unsupervised way, which is more practical given that it is difficult to acquire large fully sampled training data of parametric-weighted images. Specifically, a CS-based loss function is used in DEMO to avoid the necessity of using fully sampled k-space data as the label, thus making it an unsupervised learning approach. DEMO reconstructs parametric weighted images and generates a parametric map simultaneously by unrolling an interaction approach in conventional fast MR parametric mapping, which enables multi-tasking learning. Experimental results showed promising performance of the proposed DEMO framework in quantitative MR T1ρ mapping.

• Journal of Power Electronics
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• v.18 no.4
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• pp.1027-1036
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• 2018

In this paper a new generalized space vector pulse width modulation scheme is proposed based on the principle of reverse mapping to drive the switches of multilevel inverters. This projected scheme is developed based on the middle vector of the subhexagon which holds the tip of the reference vector, which plays a major role in mapping the reference vector. A new approach is offered to produce middle vector of the subhexagon which holds tip of the reference vector in the multilevel space vector plane. By using middle vector of the subhexagon, reference vector is linked towards the inner two level sub-hexagon. Then switching vectors, switching sequence and dwell times corresponding to a particular sector of a two-level inverter are determined. After that, by using the two level stage findings, the switching vectors related to exact position of the reference vector are directly generated based on principle of the reverse mapping approach and do not need to be found at n level stage. In the reverse mapping principle, the middle vector of subhexagon is added to the formerly found two level switching vectors. The proposed generalized algorithm is efficient and it can be applied to an inverter of any level. In this paper, the proposed scheme is explained for a five-level inverter and the performance is analyzed for five level and three level inverters through MATLAB. The simulation results are validated by implementing the propose scheme on a V/f controlled three-level inverter fed induction motor using dSPACE control desk.

• Honam Mathematical Journal
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• v.36 no.4
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• pp.777-786
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• 2014

We construct an orthonormal basis for the Bergman space associated to a simply connected domain. We use the or-thonormal basis for the Hardy space consisting of the Szegő kernel and the Riemann mapping function and rewrite their area integrals in terms of arc length integrals using the complex Green's identity. And we make a note about the matrix of a Toeplitz operator with respect to the orthonormal basis constructed in the paper.

• Communications of the Korean Mathematical Society
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• v.16 no.2
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• pp.277-285
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• 2001

The purpose of this paper is to give a proof of a generalized convex-valued selection theorem which is given by weakening a Banach space to a completely metrizable locally convex topological vector space, i.e., a Frechet space. We also develop the properties of upper semi-continuous singlevalued mapping to those of upper semi-continuous multivalued mappings. These properties wil be applied in our further consideraations of selection theorems.

• The Mathematical Education
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• v.22 no.1
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• pp.31-33
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• 1983

In this paper, we investigate the properties of the semi-continuous functions on the first axiom space, n-th product space, pseudo-metric space, and proximity space. Counterexample is used when the converse of the theorem is not hold.

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.21-28
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• 2016

Circle detection has long been studied as one of fundamental image processing applications. It is used in divers areas including industrial inspection, medial image analysis, radio astronomy data analysis, and other object recognition applications. The most widely used class of circle detection techniques is the circle Hough transform and its variants. Management of 3 dimensional parameter histogram used in these methods brings about spatial and temporal overheads, and a lot of studies have dealt the problem. This paper proposes a robust circle detection method using maximal symmetry property of circle. The basic idea is that if perpendicular bisectors of pairs of edges are accumulated in image space, center of circle is determined to be the location of highest accumulation. However, directly implementing the idea in image space requires a lot of calculations. The method of this paper reduces the number of calculations by mapping the perpendicular bisectors into parameter space, selecting small number of parameters, and mapping them inversely into image space. Test on 22 images shows the calculations of the proposed method is 0.056% calculations of the basic idea. The test images include simple circles, multiple circles with various sizes, concentric circles, and partially occluded circles. The proposed method detected circles in various situations successfully.

• The Mathematical Education
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• v.24 no.1
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• pp.17-19
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• 1985

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2005.11a
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• pp.23-57
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• 2005

• Proceedings of the Korean Vacuum Society Conference
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• 2008.02a
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• pp.57-57
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• 2008