• Composites Research
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• v.16 no.3
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• pp.58-67
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• 2003

To perform the realtime strain and fracture monitoring of the smart composite structures, two optical fiber sensor systems are proposed. The two types of the coherent sources were used for fracture signal detection - EDFA with FBG and EDFA with Fabry-Perot filter. These sources were coupled to EFPI sensors imbedded in composite specimens. To understand the characteristics of matrix crack signals, at first, we performed tensile tests using surface attached PZT sensors by changing the thickness and width of the specimens. This paper describes the implementation of time-frequency analysis such as short time Fourier transform (STFT) and wavelet transform (WT) for the quantitative evaluation of fracture signals. The experimental result shows the distinctive signal features in frequency domain due to the different specimen shapes. And, from the test of tensile load monitoring using optical fiber sensor systems, measured strain agreed with the value of electric strain gage and the fracture detection system could detect the moment of damage with high sensitivity to recognize the onset of micro-crack fracture signal.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.174-179
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• 2018

Currently, various security technologies such as fingerprint recognition and face recognition are being developed. However, although many technologies have been developed, the field of incorporating technologies is quite limited. In particular, it is easy to adapt modern security technologies into existing digital systems, but it is difficult to introduce new digital technologies in systems using analog systems. However, if the system can be widely used, it is worth replacing the analog system with the digital system. Therefore, the selected topic is the electronic attendance system. In this paper, a camera is installed to a door to perform a Haar-like feature training for face detecting and real-time face recognition with a Eigenface in principal component analysis(PCA) based face recognition using raspberry pi. The collected data was transmitted to the smartphone using wireless communication, and the application for the viewer who can receive and manage the information on the smartphone was completed.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1183-1186
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• 2004

In the steel production line, the molten metal of a furnace is transformed into billet and then moves to the heating furnace of the hot rolling mill. This paper describes about the realtime billet characters recognition system in the steel production line. Normally, the billets are mixed at yard so that their identifications are very difficult and very important processing. The character recognition algorithm used in this paper is base on the subspace method by K-L transformation. With this method, we need no special feature extraction steps, which are usually error prone. So the gray character images are directly used as input vectors of the classifier. To train the classifier, we have extracted eigen vectors of each character used in the billet numbers, which consists of 10 arabia numbers and 26 alphabet aharacters, which are gathered from billet images of the production line. We have developed billet characters recognition system using this algorithm and tested this system in the steel production line during the 8-days. The recognition rate of our system in the field test has turned out to be 94.1% (98.6% if the corrupted characters are excluded). In the results, we confirmed that our recognition system has a good performance in the poor environments and ill-conditioned marking system like as steel production plant.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1458-1463
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• 2004

Tracking is one of the most important pre-required task for many application such as human-computer interaction through gesture and face recognition, motion analysis, visual servoing, augment reality, industrial assembly and robot obstacle avoidance. Recently, 3D information of object is required in realtime for many aforementioned applications. 3D tracking is difficult problem to solve because during the image formation process of the camera, explicit 3D information about objects in the scene is lost. Recently, many vision system use stereo camera especially for 3D tracking. The 3D feature based tracking(3DFBT) which is on of the 3D tracking system using stereo vision have many advantage compare to other tracking methods. If we assumed the correspondence problem which is one of the subproblem of 3DFBT is solved, the accuracy of tracking depends on the accuracy of camera calibration. However, The existing calibration method based on accurate camera model so that modelling error and weakness to lens distortion are embedded. Therefore, this thesis proposes 3D feature based tracking method using SVM which is used to solve reconstruction problem.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.176-180
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• 2004

The ST-segment that the beginning part of T wave is the important diagnostic parameter to finding myocardial ischemia. Abnormal ST appears in two types. One is the level change, and the other is the pattern change. In this paper, we describe the monitoring of abnormal ST using PC based system. Hardware of this system consists of transmitter, receiver and PC. The function of transmitter is measuring ECG in three channels which are selected manually and transmitting the data to receiver by digital radio way. Connection with receiver and PC is by RS232C, and the data received on the PC is analyzed automatically by ECG analysis algorithm and saved to file. In the algorithm part for detecting abnormal ST, ST-segments are approximated by a polynomial. This method can detect all of the deviation and pattern change of ST-segment regardless the change in the heart rate or sampling rate. To gain algorithm reliability, the method rejects distorted polynomial approximation by calculation the difference between the approximated ST-segment and original ST-segment. In pre-signal processing, the wavelet transformation separates high frequency bands including QRS complex from the original ECG. Consequently, the process improves the performance of detecting each feature points.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.399-402
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• 2005

For efficient and accurate diagnosis of ultrasound images, the time gain compensation (TGC) and dynamic range (DR) control of the ultrasound echo signal are important. TGC is for compensating the attenuation of the ultrasound echo signal along the depth, and DR is used to control the image contrast. In this paper, we propose an algorithm for finding the optimized values of TGC and DR automatically. For TGC, the degree of compensation is determined along the depth based on the effective attenuation estimation of ultrasound signal. For DR optimization, we introduce a novel cost function on the basis of the characteristics of ultrasound image, which provides the minimum value at the optimal DR. Experiments have been performed by applying the proposed algorithm to a real US imaging system. The results show that the algorithm automatically can determine the values of TGC and DR in realtime so that the subjective quality of the corresponding US image may be good enough for diagnosis.

• Journal of Information Management
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• v.36 no.4
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• pp.51-69
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• 2005

High-speed classification method becomes an important research issue in text categorization systems. A fast text categorization technique, named feature value voting, is introduced recently on the text categorization problems. But the classification accuracy of this technique is not good as its classification speed. We present a novel approach for feature selection, named document-side feature selection, and apply it to feature value voting method. In this approach, there is no feature selection process in learning phase; but realtime feature selection is executed in classification phase. Our results show that feature value voting with document-side feature selection can allow fast and accurate text classification system, which seems to be competitive in classification performance with Support Vector Machines, the state-of-the-art text categorization algorithms.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.1
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• pp.117-124
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• 2016

Virtual environment is widely used for analyzing malware which is increasing very rapidly. However, knowing this trend, hackers are adopting virtual environment detection techniques for malware to kill itself or stop malicious behaviors when detecting virtual environments. Various research is going on in order to thwart any efforts to utilize anti-virtualization techniques, but until now several techniques can evade most of well known virtual environments, making malware analysis very difficult. Emulab developed by Utah University assigns real systems and networks as researchers want in realtime. This research seeks how to use Emulab for malware analysis.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.74-76
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• 2010

Digital images or videos are used in modern digital devices. The resolution of HDTV in digital broadcasting system is higher than that of previous analog systems. Also, mobile phone with 3G can provide images as well as video streaming services in realtime. In these circumstances, the visual quality of images has become an important factor. We can make image clear by transient improvement process that reduces transient in edges. In this paper, we present an transient improvement algorithm. The proposed algorithm improves edges by making smooth edge to steep edge. Before performing transient improvement algorithm, edge detection algorithm should be operated. Laplacian operator is used in edge detection, and the absolute value of it is used to calculate gain value. Then, local maximum and minimum values are computed to discriminate current pixel value to raise up or pull down. Compensating value that gain value multiplies with the difference between maximum (or minimum) value and current pixel value adds (or subtracts) to current pixel value. That is, improved signal is generated by making the narrow transient of edge. The advantage of proposed algorithm is that it doesn't produce shooting problem like overshoot or undershoot.

• Environmental Analysis Health and Toxicology
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• v.19 no.2
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• pp.161-167
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• 2004

Air quality monitoring is a primary activity for industrial and social environment. The government identifies the pollutants that each industry must monitor. Especially, the VOCs (Volatile Organic Compounds), which are very harmful to human body and environment atmosphere, should be controlled under the government policy. However, the VOCs, which have not been confirmed in emission sources are very difficult to monitor. It is needed to develop the monitoring system that allow the continuous and in situ measurement of VOCs mixture in different environmental matrices. Gas chromatography and mass spectrometry are the most prevalent current techniques among those available for the analysis of VOCs. But, they need a large size analytical instrument, which costs a great deal for purchase and operation. In addition, it has some limitations for realtime environmental monitoring such as location problems and slow processing time. Recently, several companies have commercialized a portable VOCs measurement systems, which cannot classify various kinds of VOCs but total quantities. We have developed a VOCs measurement system, which recognizes various kinds and quantities of VOCs, such as benzene, toluene, and xylene (BTX). Also, it can be used as a stand- alone type and/or fixed type in the vehicle with rack for real -time environmental monitoring.