• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.369-374
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• 2002

In this paper, we propose the react-time car license plate recognition algorithm using intensity variation and geometric pattern vector. Generally, difference of car license plate region between character and background is more noticeable than other regions. And also, car license plate region usually shows high density values as well as constant intensity variations. Based on these characteristics, we first extract car license plate region using intensity variations. Secondly, lightness compensation process is performed on the considerably dark and brightness input images to acquire constant extraction efficiency. In the proposed recognition step, we first pre-process noise reduction and thinning steps. And also, we use geometric pattern vector to extract features which independent on the size, translation, and rotation of input values. In the experimental results, the proposed method shows better computation times than conventional circular pattern vector and better extraction results regardless of irregular environment lighting conditions as well as noise, size, and location of plate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.3
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• pp.29-35
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• 2012

In this paper, it is presented the method of image recovering which existing is only pixel processing, but suggesting method is concluding image clustering overlap degree after classfying around unit fixel to crowd pixel. Concluding overlap degree threshold value is after identifying pattern pixel and grasping geometry structure of sample pattern and deduction of deciding function. distinguishing feature space is above four dimension is reason of not visual observation of pattern structure. consideration of distribution structure is distance of center of crowd pixel, the number of each crowd pattern pixel and standard deviation. The over threshold value elimate the overlap image and the downward is recovered and established dynamic image. memory storage deduction of 20% and elevation of 15% performance is estimated in recovery of image.

• Journal of Biomedical Engineering Research
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• v.15 no.4
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• pp.489-497
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• 1994

The most serious problems related to the cardiovascular prothesis are thrombosis and hemolysis. It is known that the flow pattern of cardiovascular prostheses is highly correlated with thrombosis and hemolysis. Laser Doppler Anemometry (LDA) is a usual method to get flow pattern, which is difficult to operate and has narrow measure region. Particle Image Velocimetry (PIV) can solve these problems. Because the flow speed of valve is too high to catch particles by CCD camera, high-speed camera (Hyspeed : Holland-Photonics) was used. The estimated maximum flow speed was 5m/sec and maximum trackable length is 0.5 cm, so the shutter speed was determined as 1000 frames per sec. Several image processing techniques (blurring, segmentation, morphology, etc) were used for the preprocessing. Particle tracking algorithm and 2-D interpolation technique which were necessary in making gridrized velocity pronto, were applied to this PIV program. By using Single-Pulse Multi-Frame particle tracking algorithm, some problems of PIV can be solved. To eliminate particles which penetrate the sheeted plane and to determine the direction of particle paths are these solving methods. 1-D relaxation fomula is modified to interpolate 2-D field. Parachute artificial heart valve which was developed by Seoul National University and Bjork-Shiely valve was testified. For each valve, different flow pattern, velocity profile, wall shear stress and mean velocity were obtained.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.2
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• pp.51-57
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• 2021

The quality of the ceramic sintered coating on a metal surface through laser surface treatment is affected by the laser irradiation pattern. Depending on the laser irradiation pattern, the amount of residual stress and heat applied or accumulated on the surface increases or decreases, affecting the thickness attained in the ceramic sintering area. When the heat energy accumulated in the sintering area is high, the ceramic and the metal alloy melt and sufficiently mix to form a homogeneous and thick bonding interface. In this study, the thermal energy accumulation in the region sintered with zirconia was controlled using four types of laser processing patterns. The thickness of the diffusion region is analyzed by laser-induced breakdown spectroscopy of Mg-ZrO2 generated by laser sintering zirconia powder on the magnesium alloy surface. On the basis of the analysis of the Mg and Zr present in the sintered region through LIBS, the effect of the irradiation pattern on the sintering quality is confirmed by comparing and analyzing the heat and mass transfer tendency of the diffusion layer and the degree of diffusion according to the irradiation pattern. The derived diffusion coefficients differed by up to 9.8 times for each laser scanning pattern.

• The KIPS Transactions:PartD
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• v.8D no.1
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• pp.88-98
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• 2001

in this paper, we imlemented design pattern retrieval system for efficient managemant and reusability of design patterns. Pattern is conssisted of property information and meta information id used for similarity measurement on classification and retrieval of patterns.Meta information od used for UML modeling of patterns. We classified design patterns with the empirical scope in addition to Gamma's basic classification. also we used E-SARM for retrieval represented UML diagram with pattern meta information, and simulated the environment so as to obtain best result on applying to retrieval of design pattern. This system is able ro resister new patterns through pattern viewer and manages these patterns with property informaiton and meta information. Thus this system supports efficient management of patterns, UML modeling, priority pattern retrieval, higher reusability and reduces pattern selection cost.

• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.319-326
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• 2002

In this paper, we have designed and implemented cluttering classification systems- unsupervised classifiers-for the processing of satellite remote sensing images. Implemented systems adopt various design patterns which include a factory pattern and a strategy pattern to support various satellite images'formats and to design compatible systems. The clustering systems consist of sequential clustering, K-Means clustering, ISODATA clustering and Fuzzy C-Means clustering classifiers. The systems are tested by using a Landsat TM satellite image for the classification input. As results, these clustering systems are well designed to extract sample data for the classification of satellite images of which there is no previous knowledge. The systems can be provided with real-time base clustering tools, compatibilities and components' reusabilities as well.

• Proceedings of the Materials Research Society of Korea Conference
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• 2011.05a
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• pp.6.1-6.1
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• 2011

Nanoscale block copolymer (BCP) patterns have been pursued for applications in sub-30 nm nanolithography. BCP self-assembly processing is scalable and low cost, and is well-suited for integration with existing semiconductor fabrication techniques. However, one of the major technical challenges for BCP self-assembly is limited tunability in pattern geometry, dimension, and functionality. We suggest methods for extending the degree of tunability by choosing highly incompatible polymer blocks and utilizing solvent vapor treatment techniques. Siloxane BCPs have been developed as self-assembling resists due to many advantages such as high etch-selectivity, good etch-resistance, long-range ordering, and reduced line-edge roughness. The large incompatibility leads to extensive degree of pattern tunability since the effective volume fraction can be easily manipulated by solvent-based treatment techniques. Thus, control of the microdomain size, periodicity, and morphology is possible by changing the vapor pressure and the mixing ratio of selective solvents. This allows a range of different pattern geometry such as dots, lines and holes and critical dimension simply by changing the processing conditions of a given block copolymer without changing a polymer chain length. We demonstrate highly extensive tunability (critical dimension ~6~30 nm) of self-assembled patterns prepared by a siloxane BCP with extreme incompatibility.

• The Transactions of the Korea Information Processing Society
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• v.2 no.2
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• pp.229-236
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• 1995

The conceptual world of sentence is composed f substantives(nouns) and verbal. The verbal is a semantic center of sentence, the substantives are placed under control of verbal, and they are combined in a various way. In this paper, the structural relation of verbal and substantives are analyzed and the phrase unit sentence which is derived from the result of morphological analysis is interpreted by a variable pattern net. This variable pattern net analyzes the phrases syntactically and semantically and extracts conceptual units of clausal form. This paper expands the traditionally restricted Horn clause theory to the general sentence, separates a simple sentence from a complex sentence automatically, constructs knowledge base by clausal form of logical conceptual units, and applies it to a question-answering system.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.5
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• pp.511-519
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• 1997

This paper presents the automatic recognition algorithm of the license number in on vehicle image. The proposed algorithm uses the correlation coefficient and Hough transform to detect license plate. The m/n ratio reduction is performed to save time and memory. By the correlation coefficient between the standard pattern and the target pattern, licence plate area is roughly extracted. On the extracted local area, preprocessing and binarization is performed. The Hough transform is applied to find the extract outline of the plate. If the detection fails, a smaller or a larger standard pattern is used to compute the correlation coefficient. Through this process, the license plate of different size can be extracted. Two algorithms to each separate number are proposed. One segments each number with projection-histogram, and the other segments each number with the label. After each character is separated, it is recognized by the neural network. This research overlomes the problems in conventional methods, such as the time requirement or failure in extraction of outlines which are due to the processing of the entire image, and by processing in real time, the practical application is possible.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.409-415
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• 2016

Recently several techniques for disaster prevention based on IoT(Internet of Things) are being developed. In this paper, a new smart pattern classification method for electric loads is proposed. CT(Current Transformer) data are extracted from electric loads, and then the sampled CT data are converted using FFT and MFCC. FFT and FMCC data are used for the input data of neural networks. Experiments were conducted using FFT and MFCC data for 7 kinds of electric loads. Experiments results indicate the superiority of MFCC in comparison to FFT.