• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.281-281
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• 2006

• Journal of Information Technology Applications and Management
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• v.24 no.3
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• pp.107-123
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• 2017

This study uses the concept of dominant design to identify the determinants for the emergence of a next-generation dominant electronic display. It employs multiple research methods with the participation of display experts, which combine case studies, an unstructured interview, and the Delphi method. The results show that based on technological innovation and market dominance, a next-generation dominant display is more likely to emerge as a result of technological competition between liquid crystal displays (LCDs) and organic light-emitting diodes (OLEDs). The findings emphasize that the importance of rapid technological innovation, including component and process innovations, and a competitive edge in manufacturing costs are important. The study sheds light on our understanding of dominance in an industry and market, and also provides strategic guidance for practitioners to establish a competitive strategy.

• Journal of the Semiconductor & Display Technology
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• v.16 no.2
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• pp.98-105
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• 2017

In the display industry, the residual vibration of the transfer robot can increase the process time and cause the breakage of the glass substrate, which is critical to productivity of display manufacturing. In this paper, the natural frequencies of transfer robot are analyzed by finite element method. On the basis of the analyzed data, we investigated the response characteristics of input shaping control with or without the glass presence on the hand of the transfer robot using MATLAB program, and compared with the current response characteristics of input shaping control applied to the industry. Based on this, we suggest an optimal residual vibration control method for the practical application in display industry.

• The Research Journal of the Costume Culture
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• v.10 no.6
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• pp.617-632
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• 2002

The purposes of this study are 1) to classify the consumer group according to clothing purchase store(department store, road shop, discount store, Dongdaemoon & Namdaemoon markets) 2) to analyze the differences between VMD attributes which each consumer group value. The attributes on the VMD are categorized as 5 areas 1) interior 2) show window 3) product display & display change cycle 4) color · light · music · small instrument 5) promotion(POP & salesperson). The data were collected from 238 females students and were analyzed by frequency, percent and X²-test. The results of this study are as fellows . 1) On the attribute of Interior, there were significant differences in terms of flow in a store, rest area, the cleanness of floor, show case, and the merchandise itself. 2) On the attribute of show window, there were significant differences in terms of interst of show window. 3) On the attribute of product display & display change cycle, there were significant differences in terms of display method, and display change cycle. 4) On the attribute of color · light · music · small instrument, there were significant differences in terms of interest of color coordination, luminosity and effect of light, and necessity of music & small instrument. 5) On the attribute of promotion(POP & salesperson), there were significant differences in terms of aid of POP.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.11
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• pp.27-33
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• 2011

Recently many display devices support the digital display interface as display market growth. DisplayPort is a next generation display interface at the PC, projector and high definition content applications in more widely used connection solution development. This paper implements multiple streams based on the behavior of the main link that is suitable for the display port v1.1a standard. The limit point of Displayport, interface between the Sink Device and Sink Device is also implemented. And two or more differential image data are enable to output the result through four Lanes stated in display port v1.1a, of two or more display devices without the addition of a separate Lane. The Multiple Video Streaming Controller is implemented with 6,222 ALUTs and 6,686 register, 999,424 of block memory bits synthesized using Quartus II at Altera Audio/Video Development board (Stratix II GX FPGA Chip).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.6
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• pp.669-676
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• 2010

Visualization requires for effective analysis of the spatial data collected by various sensors. The best way to convey 3D digital spatial information which is modeling of the real world to the users, realistic 3D visualization and display technology. Since most of the display is based on 2D or 2.5D projection to the plane, there is limitation in representing real world in 3D space. In this paper, data from airborne LiDAR for topographic mapping, Flashi-LiDAR as emerging sensor with great potential to 3D data acquisition, and multibeam echo-sounder for underwater measurement, were stereoscopically visualized. 3D monitors are getting popular and could be information media and platform in geoinformatics. Therefore, study on creating 3D stereoscopic contents of spatial information is essential for new technology of stereo viewing systems.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.1-9
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• 2010

Recently, 3D stereoscopic display such as 3D stereoscopic cinemas and 3D stereoscopic TV is getting a lot of interest. In general, a stereo image can be used in 3D stereoscopic display. In other hands, for 3D auto stereoscopic display, the elemental images should be generated through visualization from every camera in a lens array. Since a lens array consists of several cameras, it takes a lot of time to generate the elemental images with respect to 3D virtual space, specially, if a large bio-medical volume data is in the 3D virtual space, it will take more time. In order to improve the problem, in this paper, we construct an octree for a given bio-medical volume data and then propose a method to generate the elemental images through efficient rendering of the Octree data using GPU. Experimental results show that the proposed method can obtain more improvement comparable than conventional one, but the development of more efficient method is required.

• The Korean Journal of Applied Statistics
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• v.18 no.1
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• pp.83-98
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• 2005

Exploring distributional patterns of multivariate data is very essential in understanding the characteristics of given data set, as well as in building plausible models for the data. For that purpose, low-dimensional visualization methods have been developed by many researchers along various directions. As one of methods, Kohonen's SOM (Self-Organizing Map) is prominent. SOM compresses the volume of the data, yields abstraction from the data and offers visual display on low-dimensional grids. Although it is proven quite effective, it has one undesirable property: SOM's display is discrete. In this study, we propose two techniques for enhancing quality of SOM's display, so that SOM's display becomes continuous. The proposed methods are demonstrated in two numerical examples.

• Genomics & Informatics
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• v.10 no.4
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• pp.263-265
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• 2012

We developed a user-friendly, interactive program to simultaneously cluster and visualize omics data, such as DNA and protein array profiles. This program provides diverse algorithms for the hierarchical clustering of two-dimensional data. The clustering results can be interactively visualized and optimized on a heatmap. The present tool does not require any prior knowledge of scripting languages to carry out the data clustering and visualization. Furthermore, the heatmaps allow the selective display of data points satisfying user-defined criteria. For example, a clustered heatmap of experimental values can be differentially visualized based on statistical values, such as p-values. Including diverse menu-based display options, QCanvas provides a convenient graphical user interface for pattern analysis and visualization with high-quality graphics.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.121-125
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• 2020

With miniaturization of semiconductor, the manufacturing process become more complex, and undetected small changes in the state of the equipment have unexpectedly changed the process results. Fault detection classification (FDC) system that conducts more active data analysis is feasible to achieve more precise manufacturing process control with advanced machine learning method. However, applying machine learning, especially in supervised learning criteria, requires an arduous data labeling process for the construction of machine learning data. In this paper, we propose a semi-supervised learning to minimize the data labeling work for the data preprocessing. We employed equipment status variable identification (SVID) data and optical emission spectroscopy data (OES) in silicon etch with SF6/O2/Ar gas mixture, and the result shows as high as 95.2% of labeling accuracy with the suggested semi-supervised learning algorithm.