• 반도체디스플레이기술학회지
• /
• 제20권3호
• /
• pp.125-130
• /
• 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.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 1998년도 하계종합학술대회논문집
• /
• pp.819-822
• /
• 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.

• 한국전자파학회논문지
• /
• 제25권10호
• /
• pp.1050-1061
• /
• 2014

항공기 레이더는 하방 또는 사방의 공대공 표적을 탐지/추적하기 위하여 보통 MPRF 파형을 사용한다. 항공기용 레이더가 MPRF 파형을 운용하기 위하여, 거리/속도에서 존재하는 모호성을 해결하면서 클러터를 회피하여 하방 공대공 표적을 탐지할 수 있는 최적의 PRF들을 선택하여 운용할 수 있어야 한다. 이 논문은 실시간 환경변화 상황에서 표적을 탐지/추적하기 위한 최적의 PRF들을 실시간으로 찾는 방법을 제시한다.

• 전기학회논문지
• /
• 제65권9호
• /
• pp.1583-1589
• /
• 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.

• 로봇학회논문지
• /
• 제14권4호
• /
• pp.301-310
• /
• 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
• /
• 제3권3호
• /
• pp.159-175
• /
• 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.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
• /
• pp.177-179
• /
• 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.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2003년도 신호처리소사이어티 추계학술대회 논문집
• /
• pp.529-532
• /
• 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.

• 한국지능정보시스템학회:학술대회논문집
• /
• 한국지능정보시스템학회 2001년도 춘계정기학술대회
• /
• pp.253-260
• /
• 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.

• 대한의용생체공학회:의공학회지
• /
• 제8권2호
• /
• pp.215-222
• /
• 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.