• 중소기업융합학회논문지
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• 제3권1호
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• pp.31-41
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• 2013

치명적인 사고를 막기 위해 드라이버 졸음 (DD)를 검출하는 다양한 최근 방법이 제안되고있다. 본 논문은 운전자의 눈에 폐쇄 속도를 모니터링 할 수 있는 기능을 AdaBoost 기반 물체 검출 알고리즘에 적용한 DD 탐지 시스템 구현에서 하드웨어/소프트웨어 공동 설계 방법을 제안한다. 소프트웨어 구성 요소는 DD 검출 알고리즘 중에서 필요한 기능성을 완전하게 달성하기 위해 전체적인 제어 및 논리 연산을 구현한다. 반면, 본 연구에서는 DD 검출 알고리즘의 중요한 기능은 처리를 가속화하기 위해 맞춤형 하드웨어 구성 요소를 통해 가속된다. 하드웨어/소프트웨어 아키텍처는 비디오 도터 보드와 알테라 DE2 보드에 구현되었습니다. 제안 된 구현의 성능을 평가하고 몇 가지 최근의 작품을 벤치마킹했다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권7호
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• pp.2736-2754
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• 2015

Android dominates the mobile operating system market, which stimulates the rapid spread of mobile malware. It is quite challenging to detect mobile malware. System call sequence analysis is widely used to identify malware. However, the malware detection accuracy of existing approaches is not satisfactory since they do not consider correlation of system calls in the sequence. In this paper, we propose a new scheme called Artificial Neural Networks (ANNs) on Co-occurrence Matrices Droid (ANNCMDroid), using co-occurrence matrices to mine correlation of system calls. Our key observation is that correlation of system calls is significantly different between malware and benign software, which can be accurately expressed by co-occurrence matrices, and ANNs can effectively identify anomaly in the co-occurrence matrices. Thus at first we calculate co-occurrence matrices from the system call sequences and then convert them into vectors. Finally, these vectors are fed into ANN to detect malware. We demonstrate the effectiveness of ANNCMDroid by real experiments. Experimental results show that only 4 applications among 594 evaluated benign applications are falsely detected as malware, and only 18 applications among 614 evaluated malicious applications are not detected. As a result, ANNCMDroid achieved an F-Score of 0.981878, which is much higher than other methods.

• 전자공학회논문지B
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• 제29B권11호
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• pp.111-119
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• 1992

In this paper, we propose an edge detection scheme for noisy images based on the co-occurrence matrix. In the proposed scheme based on the step edge model, the gray level information is simply converted into a bit-map, i.e., the uniform and boundary regions of an image are transformed into a binary pattern by using the local mean. In this binary bit-map pattern, 0 and 1 densely distributed near the boundary region while they are randomly distributed in the uniform region. To detect the boundary region, the co-occurrence matrix on the bit-map is introduced. The effectiveness of the proposed scheme is shown via a quantitative performance comparison to the conventional edge detection methods and the simulation results for noisy images are also presented.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2001년도 Proceedings ICPE 01 2001 International Conference on Power Electronics
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• pp.365-368
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• 2001

The advantage of the squirrel cage induction motor is the brush less rotor. This advantage for operation and maintenance turns out to be a disadvantage for the detection of the cage rotor bar and endring defects, which means that the detection of cage faults is due to the measurement and analysis of only the stator input signals. The monitoring task in an inverter drive is complicated mainly because the voltage and current waveforms are nonsinusoidal and the high dv/dt values from fast switching inverterd distort the measurements. In this paper, we are going to discuss the detection method of broken rotor bar of the inverter fed squirrel cage induction motor by the motor current signature analysis(MCSA) and the opening terminal voltage signal analysis.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2006년도 하계종합학술대회
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• pp.847-848
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• 2006

R-type thermocouple(TC) interface circuits with cold-junction compensator(CJC) and its broken wires detection was developed. The circuit consists of a CJC device, a instrumentation amplifier(IA), and two resistor and a diode for broken wire detection. The experiment results show that the interface circuit has a good CJC function on the temperature range for $20^{\circ}C$ to $1400^{\circ}C$. At the range the output voltage of the IA was -14V when the TC was broken. At normal operation condition the output voltage of IA was 0V to 10V for the temperature range.

• Journal of Multimedia Information System
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• 제6권1호
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• pp.15-22
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• 2019

There are many ways to perform face recognition. The first step of face recognition is the face detection step. If the face is not found in the first step, the face recognition fails. Face detection research has many difficulties because it can be varied according to face size change, left and right rotation and up and down rotation, side face and front face, facial expression, and light condition. In this study, facial features are extracted and the extracted features are geometrically reconstructed in order to improve face recognition rate in extracted face region. Also, it is aimed to adjust face angle using reconstructed facial feature vector, and to improve recognition rate for each face angle. In the recognition attempt using the result after the geometric reconstruction, both the up and down and the left and right facial angles have improved recognition performance.

• 센서학회지
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• 제18권6호
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• pp.449-455
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• 2009

In this paper, we developed a digital gait analyzer using the triaxial accelerometer(TA). An approach for normal gait detection employing decay slope peak detection(DSPD) algorithm was presented. The TA was attached to the center of the waist of a subject. The subject walked a bare floor at 60, 92 and 120 steps/minute. We analyzed vertical axis acceleration signal for gait detection. At 60, 92, 120 steps/minute walking, detection accuracy of gait events were over 99 % accuracy.

• 한국방사성폐기물학회:학술대회논문집
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• 한국방사성폐기물학회 2017년도 추계학술논문요약집
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• pp.309-310
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• 2017

• 한국방사성폐기물학회:학술대회논문집
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• 한국방사성폐기물학회 2019년도 춘계학술논문요약집
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• pp.341-342
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• 2019

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.2059-2064
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• 2004

Texture analysis is an important role for automatic visual insfection. This paper presents an application of wavelet extension and Gray level co-occurrence matrix (GLCM) for detection of defect encountered in textured images. Texture characteristic in low quality images is not to easy task to perform caused by noise, low frequency and small dimension. In order to solve this problem, we have developed a procedure called wavelet image extension. Wavelet extension procedure is used to determine the frequency bands carrying the most information about the texture by decomposing images into multiple frequency bands and to form an image approximation with higher resolution. Thus, wavelet extension procedure offers the ability to robust feature extraction in images. Then the features are extracted from the co-occurrence matrices computed from the sub-bands which performed by partitioning the texture image into sub-window. In the detection part, Mahalanobis distance classifier is used to decide whether the test image is defective or non defective.