• Journal of applied mathematics & informatics
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• v.14 no.1_2
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• pp.225-235
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• 2004

The sign central matrices were characterized by Ando and Brualdi. And, the nearly sign central matrices were characterized by Lee and Cheon. In this paper, we give another characterization of nearly sign central matrices. Also, we introduce the nearly minimal sign central matrices and study the properties of nearly minimal sign central matrices.

• Bulletin of the Korean Mathematical Society
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• v.37 no.4
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• pp.771-778
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• 2000

The sign-central matrices were characterized by Ando and Brualdi. In this paper, we define a nearly sign-central matrices and give a characterization of nearly sign-central matrices.

• The Korean Journal of Zoology
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• v.33 no.4
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• pp.454-460
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• 1990

The effed of acrylamide on the nervous system has heen morphologically studied using light and electron microscopes. The light micrographs on central and pedpheral nervous tissues of mouse treated with acrylamide monomer showed total vacuolation of spinal cord, cell degradation containing neuron and neuroglia, and distal nerve fiber degeneration. The electron micrographs showed ultrastrudural changes. Abnormal mitochondria in neuron, splitting of myelin sheath in lumbar ventral root nerve, partial disintergration of myelin sheath and axoplasmic degeneration in sciatic nerve, and overafl polyneuropathies in nervous system were observed. These results suggest that acrylarnide intoxicated mouse shows distal behavioral neuropathy as an earlist clinical sign, but the initial effect of acrylamide on the nervous system seems to appear at nearly the same time in both central and peripheral nervous systems.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.3
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• pp.19-25
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• 2013

Recently, more accurate database information of facilities is being required, with the increase in importance of urban road facility management. Therefore, this study proposed how to automatically detect particular traffic signs necessary for efficient construction of road facility DB. For this study, central locations of facilities were searched, after recognition and automatic detection of particular traffic signs through an image. Then, coordinate values of traffic signs calculated in the study were compared with real coordinate values, in order to evaluate the accuracy of traffic sign locations which were finally detected. Computer vision technology was used in recognizing and detecting traffic signs through OPEN CV-based coding, and photogrammetry was used in calculating accurate locations of detected traffic signs. For the experiment, circular road signal(No Parking) and triangular road signal(Crosswalk) were chosen out of various kinds of road signals. The research result showed that the circular road signal had a nearly 50cm error value, and the triangular road signal had a nearly 60cm error value, when comparing the calculated coordinates with the real coordinates. Though this result is not satisfactory, it is considered that there would be no problem to find locations of traffic signs.