• Journal of IKEEE
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• v.2 no.1 s.2
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• pp.34-41
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• 1998

An integrated circuit for magnetic stripe storage system is implemented. All the analog and digital circuits are integrated in one chip. The analog block contains preamplifier, peak detecter, comparator and reference generater. And digital block includes reference window signal generater, up/down counter for F/2F signal measurement, bit-error detection logic, and control logic. Both the encoding and decoding functions for F/2F signal processing are provided. An AGC(automatic gain control) circuit which was included in conventional circuits is eliminated due to optimized circuit design. Misreading prevention circuits are also proposed by fixing up new reference bit when broken bits are detected. The prototype chip is implemented using $0.8{\mu}m$ N-well CMOS technology and operates from 3.3 V to 7.5 V of supply voltage. It occupies a die area of $3.04mm^2(1.6mm{\times}1.9mm)$ and dissipates 8 mW with a 5 V supply voltage.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.162-170
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• 2013

In recent years, the interests and needs of the Pedestrian Protection System (PPS), which is mounted on the vehicle for the purpose of traffic safety improvement is increasing. In this paper, we propose a pedestrian candidate window extraction and unit cell histogram based HOG descriptor calculation methods. At pedestrian detection candidate windows extraction stage, the bright ratio of pedestrian and its circumference region, vertical edge projection, edge factor, and PCA reconstruction image are used. Dalal's HOG requires pixel based histogram calculation by Gaussian weights and trilinear interpolation on overlapping blocks, But our method performs Gaussian down-weight and computes histogram on a per-cell basis, and then the histogram is combined with the adjacent cell, so our method can be calculated faster than Dalal's method. Our PCA reconstruction error based pedestrian detection candidate window extraction method efficiently classifies background based on the difference between pedestrian's head and shoulder area. The proposed method improves detection speed compared to the conventional HOG just using image without any prior information from camera calibration or depth map obtained from stereo cameras.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.46 no.4
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• pp.70-76
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• 2009

We proposed the device to control a computer mouse with only head movements and eye blinks so that disabilities by car or other accidents can use a computer. The mouse position were estimated from a gyro-sensor which can measure head movements, and the mouse events such as click/double click were from opto sensors which can detect the eyes flicker, respectively. The sensor was mounted on the goggle in order not to disturb the visual field. There was no difference in movement speed between ours and a general mouse, but it required 3$\sim$4 more times in the result of the experiment to evaluate spatial movements and events detection of the proposed mouse because of the low accuracy. We could eliminate cumbersome work to periodically remove the accumulated error and intuitively control the mouse using non-linear relative point method with dead zones. Optical sensors are used in the event detection circuitry designed to remove the influence of the ambient light changes, therefore it was not affected in the change of external light source.

• Journal of Internet Computing and Services
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• v.14 no.4
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• pp.85-90
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• 2013

Currently, the electric fire prediction system uses PIC(Peripheral Interface Controller) for controller microprocessor. PIC has a slower computing speed than DSP does, so its real-time computing ability is inadequate. So with the basic characteristics waveform during arc generation as the standard reference, the comparison to this reference is used to predict and alarm electric fire from arc. While such alarm can be detected and taken care of from a remote central server, that prediction error rate is high and remote control in mobile environment is not available. In this article, the arc detection of time domain and frequency domain and wavelet-based adaptation algorithm executing the adaptation algorithm in conversion domain were applied to develop an electric fire prediction system loaded with new real-time arc detection algorithm using DSP. Also, remote control was made available through iPhone environment-based app development which enabled remote monitoring for arc's electric signal and power quality, and its utility was verified.

• Journal of IKEEE
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• v.18 no.4
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• pp.509-516
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• 2014

CRC feature in a high-speed semiconductor memory devices such as DDR4/GDDR5 increases the data reliability. Conventional CRC method have a massive area overhead and long delay time. It leads to insufficient internal timing margins for CRC calculation. This paper, presents a CRC code method that provides error detection and a real-time matrix type CRC. If there are errors in the data, proposed method can alert to the system in a real-time manner. Compare to the conventional method(XOR 6 stage ATM-8 HEC code), the proposing method can improve the error detection circuits up to 60% and XOR stage delay by 33%. Also the real-time error detection scheme can improve the error detection speed to agerage 50% for the entire data bits(UI0~UI9).

• Journal of Internet Computing and Services
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• v.8 no.6
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• pp.155-167
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• 2007

There are four types of human beings according to the Sasang Typology, Oriental medical doctors frequently prescribe healthcare information and treatment depending on one's type, The feature ratios (Table 1) on the human face are the most important criterions to decide which type a patient is. In this paper, we proposed a system to extract these feature ratios from the people's side face, There are two challenges in acquiring the feature ratio: one that selecting representative features; the other, that detecting region of interest from human profile facial image effectively and calculating the feature ratio accurately. In our system, an adaptive color model is used to separate human side face from background, and the method based on geometrical model is designed for region of interest detection. Then we present the error analysis caused by image variation in terms of image size and head pose, To verify the efficiency of the system proposed in this paper, several experiments are conducted using about 173 korean's left side facial photographs. Experiment results shows that the accuracy of our system is increased 17,99% after we combine the front face features with the side face features, instead of using the front face features only.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.557-568
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• 2008

An ontology as the core element of Semantic Web is a formal specification of a conceptualization of shared domain knowledge. The use of well-defined ontologies can increase the quality of interoperable information systems in the area of Semantic Web. However, in practice, it is not easy to develop high-quality ontologies which have no errors. Therefore, with methodologies for ontology design, various methods or tools for ontology analysis supporting for error-detection might be very helpful for ontology developers. In this paper, we propose a novel approach for analyzing the core constructs of ontology based on the Formal Concept Analysis and develop a tool that supports error-checking ontologies. Our approach can serve not only as a guidance to modify the existing ontologies, but also as a valuable tool in developing high-quality ontologies.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.8
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• pp.1814-1822
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• 1997

In this paper, we present a new digital signature for copyright protection of digital images. The proposed algorithm is designed to be more robust to both the compression (quantization) errors and the illegal signature attack by a third party. More specifically, to maximize the watermaking effect, we embed the watermark by randomly adding or subtracking a fixed number instead of executing the XORs. Also, to improve the reliability of the watermark detection, we extact the watermark only on some image blocks, which are less sensitive to the compression error. Futhermore, the unrecovered compression errors are further detected by the Hypothesis testing. The illegal signalture attack of a third party is also protected by using some probabilistic decisions of the MSE between the orignal image and the signed image. Experimental results show that the peroposed algorithm is more robust to the quantization errors and illegal signature attack by a third party.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.435-442
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• 2015

In this paper, we propose a tracking and recognition of pedestrian/vehicle for intelligent multi-visual surveillance system. The intelligent multi-visual surveillance system consists of several fixed cameras and one calibrated PTZ camera, which automatically tracks and recognizes the detected moving objects. The fixed wide-angle cameras are used to monitor large open areas, but the moving objects on the images are too small to view in detail. But, the PTZ camera is capable of increasing the monitoring area and enhancing the image quality by tracking and zooming in on a target. The proposed system is able to determine whether the detected moving objects are pedestrian/vehicle or not using the SVM. In order to reduce the tracking error, an improved camera calibration algorithm between the fixed cameras and the PTZ camera is proposed. Various experimental results show the effectiveness of the proposed system.

• The Journal of the Acoustical Society of Korea
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• v.29 no.1
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• pp.69-75
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• 2010

In this paper, the pitch is detected after the elimination of formant ingredients by flattening the spectrum in frequency domain. In order to remove impact of formant and transition frequency in the signal spectrum, formant envelop is made by linear interpolation with any points each sub-band and the spectrum of speech signal is compensated by the reverse of the envelop interpolated linearly after we divide frequency band into several segment based on LSP and detect the points. The experimental result showed the proposed method appeared an outstanding performance in compared with LPC, Cepstrum, Lifter methods. The method reduced the gross error rate 1.30% than the LPC method which appeared a good performance except the proposed method. Also, the proposed method showed low error rate in noise environment.