• Journal of Digital Contents Society
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• v.16 no.1
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• pp.113-121
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• 2015

Artifact pattern representation of a method using the digital technology is largely are two digital rubbing technique and digital contrast technique. Digital rubbing technique is clearly with the naked eye to see the original prestigious and difficult to build a digital rubbing data patterns by scanning a prestigious and patterns carved into the artifacts in three dimensions without compromising the circle to represent the three-dimensional effect by contrast it to the objective value refers to a technique that can be represented in digital. Digital contrast technique can not be calculated if the depth information of the object due to the glassy film of artefacts in a three-dimensional surface scanning and the application of this technique refers to a realistic image mapped digital technique for generating digital image contrast. Digital rubbing technique is mainly useful to express the most prestigious and patterns expressed in pottery or tile and stone monument, etc. engraved or embossed, digital contrast techniques can be used effectively to artifacts such as magnetic or glass can not be applied to the digital rubbing technique.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.1
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• pp.106-110
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• 2000

The researches classifying the artificial flaws in welding parts are performed using the pattern recognition technology. For this purpose the signal pattern recognition package including user defined function is developed and the total procedure is made up the digital signal processing, feature extraction, feature selection, classfier design. Specially it is composed with and discussed using the ststistical classfier such as the linear discriminant function classfier, the empirical Bayesian classfier.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.304-309
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• 2003

In this study, natural flaws in welding parts are classified using the signal pattern classification method. The storage digital oscilloscope including FFT function and enveloped waveform generator is used and the signal pattern recognition procedure is made up the digital signal processing, feature extraction, feature selection and classifier design. It is composed with and discussed using the distance classifier that is based on euclidean distance the empirical Bayesian classifier. Feature extraction is performed using the class-mean scatter criteria. The signal pattern classification method is applied to the signal pattern recognition of natural flaws.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.119-124
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• 1999

This paper presents new approach to technology pattern recognition of camera back cover and test of soldering. In real-time implementing of pattern recognition camera back cover and test of soldering, the MVB-03 vision board has been used. Image can be captured from standard CCD monochrome camera in resolutions up to 640$\times$480 pixels. Various options re available for color cameras, a synchronous camera reset, and linescan cameras. Image processing os performed using Texas Instruments TMS320C31 digital signal processors. Image display is via a standard composite video monitor and supports non-destructive color overlay. System processing is possible using c30 machine code. Application software can be written in Borland C++ or Visual C++

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.33-41
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• 2013

In this paper, we implemented the pattern matching with the Arduino and App Inventor platform under the bluetooth mobile environment between Android phone and Arduino Platform. The combination between Arduino and App Inventor makes the feasibility of Android programming easy by wireless communications and provides the opportunity to broaden the functionality for mobile device. We used the softwares which were Arduino IDE, VC++, OpenCV, Processing and App Inventor. And also compared the performance of mobile Arduino platform with LabView GUI programming, we reduced the usage of libraries that compiled and executed the pattern matching programming. We experimented the mobile embedded platform performance under bluetooth communication and verified the functionality of the mobile Arduino platform design for identifying the pattern matching.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.147-156
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• 2012

Most people in our society use credit card instead of cash or check, so credit card is very important economic method. Credit card supposed to be safe, but hackers hack credit card for illegal deal. Also hackers make fake credit card and issue fake credit card to other people. In this thesis it will study and analyze damage case for safe credit card deal. It will use safe credit card system to insert variety of information and data of using pattern in artificial intelligence network, so print out the possibility of risk and monitor the risk of credit card user's deal pattern, so if one of user's pattern is different than normal pattern, it will pop up message in consultant's screen. This thesis will study and suggest way of prevent from illegal deal and user friendly credit card checking system.

• 한국정보디스플레이학회:학술대회논문집
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• 2005.07b
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• pp.1171-1174
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• 2005

This thesis provides a new digital convergence method and apparatus which uses area photo sensor and new analog to digital algorithmic to identify the correct digital pattern position factor of the projection system. This method and apparatus can be applied to the convergence correction in a TV receiver with a display that comprises a display screen with photo sensors positioned adjacent to screen edges. It also can be applied to the manufacture process detection of the projection system to adjust the associative convergence parameter. In this paper, demonstrate how this convergence detecting algorithmic was implemented with four area photo sensors of special designed pattern to the rear projection CRT TV.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.140-143
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• 2001

Digital shearography, a speckle pattern method is based on the superposition of two laterally sheared images. Therefore, object points which are positioned in some distance from each other are superposed in the image plane. This shearography, one of NDT methods without contact, is able to inspect defects in pipelines and pressure vessels that are used in nuclear power plants. This is can inspect whole fields and has a low sensitivity to environmental noise. Because optical setting is very simple, it has a little exhaustion of time, cost and man power. And also it can find a defect position through real time monitoring of a part. This paper, finds out the relationship among shearing quantity image quality and defect size with this method.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.2
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• pp.111-118
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• 2001

In this paper, in order to implement the multi-layered perceptron neural network using pure digital logic circuit model, we propose the new logic neuron structure, the digital canonical multi-layered logic neural network structure, and the multi-stage multi-layered logic neural network structure for pattern recognition applications. And we show that the proposed approach provides an incremental additive learning algorithm, which is very simple and effective.

• Journal of the Korean Society of Safety
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• v.37 no.5
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• pp.14-21
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• 2022

The purpose of this study was to apply the signal pattern recognition technique to the digital wireless fire-alarm system and to reduce unwanted fire alarms. In this study, the fire alarms of the K Institute, which operates the largest digital wireless fire-alarm system in Korea, were classified into normal operations and unwanted fire alarms, and these were analyzed and compared with actual fire signals. In addition, by designing a non-fire signal filter and applying it to the K Institute, we confirmed that the monthly unwanted fire alarm rate of all 5,713 detectors decreased sharply. In particular, the unwanted fire alarm rate for flame decreased from 1.09% to 0.11% and the unwanted fire alarm rate for smoke decreased from 0.65% to 0.035%.