• Journal of the Korean Institute of Telematics and Electronics
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• v.20 no.3
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• pp.13-20
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• 1983

A method for the detecting defined vertices is described in this paper. An alogrithm detecting vertex position by means of calculating an error and distinguishing the defined inner and outer corners by the chain code of line segments is described. To calculate the error, virtual links are detected by means of a jointing relations of line segments for a contour. And so an error is calculated by measuring a minimum distance from a jointing point between the line segments to virtual link. As a result, this method is more flexible and effective than conventional Freeman's method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.3
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• pp.268-273
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• 2005

We propose the specialized product-line development methodology for developing the embedded system of an MSDFS (Multi Sensor Data Fusion System : called MSDFS). The product-line methodology provides a simultaneous design between software and hardware, high level reusability. However this is insufficient in requirement analysis stage due to be focused on software architecture, detailed design and code. Thus we apply the business model based on IDEF0 technique to traditional methodology. In this paper, we describe the processes of developing Core-Asset, which are requirement analysis, feature modeling, validation. The proposed model gives the efficient result for eliciting features, and ensures the high level reusability of modules performing on embedded system.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.723-730
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• 2006

In the electrical railway, the tension ascension of contact wire is essential to speed up of train and current collection performance of catenary largely depends on the tension. The tension variation rate of the tensioning device used in existing line limits within 5%, and the tension variation rate of the spring-type tensioning device installed at the section where tensioning length is short bounds within 15%. So it is urgent for us to localize it for high speed line, which the tension variation rate is limited within 3%. Therefore in this study, a pulley-type tensioning device for high speed line is developed. To verify the performance of developed device, a performance test, overload test and failure test is carried out under the code of the Kyung-Bu High Speed line. And it is secured durability performance through a fatigue test.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.1025-1032
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• 2006

The PVRC(Pressure Vessel Research Council) damping is for the response spectrum analysis of the piping system. In this study, the possibility to apply it to the time history analysis is evaluated to reduce the higher conservatism for the structural integrity. The evaluation was performed for the surge line connecting the pressurizer to the hot-leg, and the whole mode includes the RCS and the building structures with the surge line. The analyses were performed using ANSYS code. The first modal analysis shows the modes of the surge line are isolated from those of the other structures. The composite modal damping was calculated with PVRC damping for the surge line and RG 1.60 damping for the other structures by using ANSYS routines. Of the calculated composite modal damping values, the composite modal damping values related to the modes of the surge line were replaced with the PVRC damping values with respect to its frequencies. With this replacement, the composite modal damping values of the other structures were not changed. Based on this decouple characteristics, the time history analyses for the seismic events with PVRC damping for the surge line were performed. And the results show the resultant loads can be reduced by up to 50%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1766-1784
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• 2014

Finger vein images contain rich oriented features. Local line binary pattern (LLBP) is a good oriented feature representation method extended from local binary pattern (LBP), but it is limited in that it can only extract horizontal and vertical line patterns, so effective information in an image may not be exploited and fully utilized. In this paper, an orientation-selectable LLBP method, called generalized local line binary pattern (GLLBP), is proposed for finger vein recognition. GLLBP extends LLBP for line pattern extraction into any orientation. To effectually improve the matching accuracy, the soft power metric is employed to calculate the matching score. Furthermore, to fully utilize the oriented features in an image, the matching scores from the line patterns with the best discriminative ability are fused using the Hamacher rule to achieve the final matching score for the last recognition. Experimental results on our database, MMCBNU_6000, show that the proposed method performs much better than state-of-the-art algorithms that use the oriented features and local features, such as LBP, LLBP, Gabor filter, steerable filter and local direction code (LDC).

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.1
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• pp.35-41
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• 2010

In order to improve the productivity and the yield at assembling line of finished goods' manufacturers, it is necessary that the fabricated parts are supplied to the assembly line not only just in time (JIT) but also just in sequence (JIS). Parts that are not delivered just in time can cause assembly line to be delayed, and parts that are not delivered just in sequence can cause assembly line to be halted or defected products. For JIT and JIS implementation, in the paper we propose the smart pallet based just-in-sequence parts delivery system in which RFID and USN technologies are converged. Compared with the bar-code based just-in-sequence parts delivery system, the proposed system can reduce unnecessary time for confirming parts' type and sequence and unnecessary cost by bar-code labeling and sequence data' documenting. The proposed system also can overcome the drawbacks of the RFID based just-in-sequence parts delivery system such as transmission range limit and difficulties of confirming parts' type and sequence in real time. Finally, we show the implementation of the proposed system, and its practicality.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.996-1003
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• 2022

In this paper, we present a new method for determining the scan line and range for vision-based 1-D barcode recognition. This is a study on how to detect valid barcode representative points and directions by applying the DBSCAN clustering method based on block HOG (histogram of gradient) and determine scan lines and barcode crosslines based on this. In this paper, the minimum and maximum search techniques were applied to determine the cross-line range of barcodes based on the obtained scan lines. This can be applied regardless of the barcode size. This technique enables barcode recognition even by detecting only a partial area of the barcode, and does not require rotation to read the code after detecting the barcode area. In addition, it is possible to detect barcodes of various sizes. Various experimental results are presented to evaluate the performance of the proposed technique in this paper.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.46.3-47
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• 2021

Recently a multilayer spectral inversion (MLSI) model has been proposed to infer the physical parameters of plasmas in the solar chromosphere. The inversion solves a three-layer radiative transfer model using the strong absorption line profiles, H alpha and Ca II 8542 Å, taken by the Fast Imaging Solar Spectrograph (FISS). The model successfully provides the physical plasma parameters, such as source functions, Doppler velocities, and Doppler widths in the layers of the photosphere to the chromosphere. However, it is quite expensive to apply the MLSI to a huge number of line profiles. For example, the calculating time is an hour to several hours depending on the size of the scan raster. We apply deep neural network (DNN) to the inversion code to reduce the cost of calculating the physical parameters. We train the models using pairs of absorption line profiles from FISS and their 13 physical parameters (source functions, Doppler velocities, Doppler widths in the chromosphere, and the pre-determined parameters for the photosphere) calculated from the spectral inversion code for 49 scan rasters (~2,000,000 dataset) including quiet and active regions. We use fully connected dense layers for training the model. In addition, we utilize a skip connection to avoid a problem of vanishing gradients. We evaluate the model by comparing the pairs of absorption line profiles and their inverted physical parameters from other quiet and active regions. Our result shows that the deep learning model successfully reproduces physical parameter maps of a scan raster observation per second within 15% of mean absolute percentage error and the mean squared error of 0.3 to 0.003 depending on the parameters. Taking this advantage of high performance of the deep learning model, we plan to provide the physical parameter maps from the FISS observations to understand the chromospheric plasma conditions in various solar features.

• Proceedings of the Korean Nuclear Society Conference
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• 2004.10a
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• pp.427-428
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• 2004

• Proceedings of the Korean Nuclear Society Conference
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• 2001.05a
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• pp.248.2-248
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• 2001