• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.125-130
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• 2021

Scaffold is used to produce bio sensor. Scaffold is required high dimensional accuracy. 3D printer is used to manufacture scaffold. 3D printer can't detect defect during printing. Defect detection is very important in scaffold printing. Real-time defect detection is very necessary on industry. In this paper, we proposed the method for real-time scaffold defect detection. Real-time defect detection model is produced using CNN(Convolution Neural Network) algorithm. Performance of the proposed model has been verified through evaluation. Real-time defect detection system are manufactured on hardware. Experiments were conducted to detect scaffold defects in real-time. As result of verification, the defect detection system detected scaffold defect well in real-time.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.819-822
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• 1998

The high complexity of digital circuits has changed the digital circuits design mehtods from schemeatic-based to hardware description languages like VHDL, verilog that make hardware faults become more hard to detect. Thus test generation to detect hardware defects is very important part of the design. But most of the test generation methods are gate-level based. In this paper new high-level test generation method to detect stuck-at-faults on gate level is described. This test generation method is independent of synthesis results and reduce the time and efforts for test generation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.10
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• pp.1050-1061
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• 2014

Airborne radar usually use MPRF(medium PRF) waveforms to detect and track look-down or all-directions air-to-air targets. To use MPRF waveforms, airborne radar have to operate optimal PRF schedules and select optimal PRFs able to detect look-down air-to-air targets, overcoming look-down clutter and resolving range/velocity ambiguities. In this paper, we propose a real-time search method for the optimal(and sub-optimal) PRFs able to detect and track targets in real-time change of situation for MPRF pulsed-Doppler airborne radars.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.9
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• pp.1583-1589
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• 2016

This paper proposes an improved spread spectrum time domain reflectometry (ISSTDR) using time-frequency correlation and reference signal elimination method in order to have more accurate fault determination and location detection than conventional (SSTDR) despite increased signal attenuation due to the long distance to cable fault location. The proposed method has a two-step process: the first step is to detect a peak location of the reference signal using time-frequency correlation analysis, and the second step is to detect a peak location of the correlation coefficient of the reflected signal by removing the reference signal. The proposed method was validated through comparison with existing SSTDR methods in open-and short-circuit fault detection experiments of low voltage power cables. The experimental results showed that the proposed method can detect correlation coefficients at fault locations accurately despite reflected signal attenuation so that cable faults can be detected more accurately and clearly in comparison to existing methods.

• The Journal of Korea Robotics Society
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• v.14 no.4
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• pp.301-310
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• 2019

A new algorithm has been propose to detect the reflected light region as disturbances in a real-time vision system. There have been several attempts to detect existing reflected light region. The conventional mathematical approach requires a lot of complex processes so that it is not suitable for a real-time vision system. On the other hand, when a simple detection process has been applied, the reflected light region can not be detected accurately. Therefore, in order to detect reflected light region for a real-time vision system, the detection process requires a new algorithm that is as simple and accurate as possible. In order to extract the reflected light, the proposed algorithm has been adopted several filter equations and clustering processes in the HSI (Hue Saturation Intensity) color space. Also the proposed algorithm used the pre-defined reflected light data generated through the clustering processes to make the algorithm simple. To demonstrate the effectiveness of the proposed algorithm, several images with the reflected region have been used and the reflected regions are detected successfully.

• Wind and Structures
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• v.3 no.3
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• pp.159-175
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• 2000

Many practical time series, including pressure signals measured on roof-corners of low-rise buildings in quartering winds, consist of relatively quiescent periods interrupted by intermittent transients. The dyadic wavelet transform is used to detect these transients in pressure time series and a relatively simple pattern classification scheme is used to detect underlying structure in these transients. Statistical analysis of the resulting pattern classes yields a library of signal "building blocks", which are useful for detailed characterization of transients inherent to the signals being analyzed.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.177-179
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• 2005

This paper suggests a high-speed blurred blob image inspection algorithm. When we inspect some products using high-resolution camera, the detected blob images usually have severe blur. And the blur makes it hard to detect an object. There are many blur-processing algorithms, but most of them have no real-time property for high-speed applications at all. In this paper, an MMX technology based algorithm is suggested. The suggested algorithm was found to be effective to detect the blurred blob images via many simulations and long time real-plant experiments.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.529-532
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• 2003

In this paper, we describe new method to detect face in real-time. We use color information, edge information, and binary information to detect candidate regions of eyes from input image, and then extract face region using the detected eye pall. We verify both eye candidate regions and face region using Support Vector Machines(SVM). It is possible to perform fast and reliable face detection because we can protect false detection through these verification processes. From the experimental results, we confirmed the proposed algorithm shows very excellent face detection performance.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.253-260
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• 2001

Understanding and adapting to changes of customer behavior is an important aspect for a company to survive in continuously changing environment. The aim of this paper is to develop a methodology which detects changes of customer behavior automatically from customer profiles and sales data at different time snapshots. For this purpose, we first define three types of changes as emerging pattern, unexpected change and the added / perished rule. Then we develop similarity and difference measures for rule matching to detect all types of change. Finally, the degree of change is evaluated to detect significantly changed rules. Our proposed methodology can evaluate degree of changes as well as detect all kinds of change automatically from different time snapshot data. A case study for evaluation and practical business implications for this methodology are also provided.

• Journal of Biomedical Engineering Research
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• v.8 no.2
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• pp.215-222
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• 1987

This paper describes the design of a real time arrhythmia detection system using five variables : heart rate, QS width, morphology, alls deviation, and ST segment. To detect individual variables for four patients, we designed multi-processor system. The results of the analysis derived from simulators and 50 patients are compared with the medical diagnoses. The results show that the analysis was able to detect irregularly occuring arrhythmia which does not show up in routine medical examination.