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RISS 인기검색어
- 검색키워드
- 저자 : Ben Ayed Mossaad (검색결과 2 건)
- 무료
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- 유료
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Smart Recognition COVID-19 System to Predict Suspicious Persons Based on Face Features
Ben Ayed Mossaad,Massaoudi Ayman,Alshaya Shaya A. 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.3
The coronavirus (COVID-19) is identifi ed at fi rst in Wuhan in December 2019. The apparition of the COVID-19 virus is widely spread to concern all countries worldwide. The World Health Organization (WHO) on March 11 declare COVID-19 a pandemic. This Virus causes a serious infection of the respiratory system. Its high transmission constitutes great problems and challenges. The WHO proposes many actions to limit the spread of the virus such as quarantine and decrease or halt fl ights between states. The actions taken by states in airports are to detect suspicious persons with COVID-19. We aimed to provide a Computer-Aided Diagnosis (CAD) framework to predict suspicious COVID-19 person. This prediction identifi es suspicious persons who suff er from shortness breath which is the main symptom of this disease. Extract shortness breath anomaly through the estimated heart rate from face based-video is the main contribution of the present paper. We developed a Smart Recognition COVID-19 (SRC) system to estimate the breath score. In conclusion, our study achieves an accurate breath score. The error is about 1 breath per minute. The proposed solution is of great importance because it helps managers in the airport to predict suspicious COVID-19 passengers.
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Co‑simulation Improvement for Uncertain Flexible Robot Arm
Lilia Zouari,Mossaad Ben Ayed,Slim Chtourou,Shaya Abdullah Alshaya,Mohamed Abid 대한전기학회 2020 Journal of Electrical Engineering & Technology Vol.15 No.1
Flexible robot arm driven by Brushless DC Motor (BDCM) under uncertainties represents one of the most complex and heterogeneous system. Indeed, the verifcation phase becomes a great challenge for designers. Avoid and predict risks accurately at earlier stage represents the main purpose of the Computer-Aided Design (CAD) feld. This paper treats the case of robotics system for tracking trajectory problem and attempts to improve the verifcation phase by identifying the most suitable co-simulation technique. For the system analyzed in this paper, the fexible robot arm driven by Brushless DC actuator is verifed using the Model In the Loop (MIL) technique, the Software In the Loop (SIL) technique and CODIS+technique. Each one verifes the system according to a particular abstraction level. The performance of each technique is determined by measuring the accuracy and time simulation. Experimental results have revealed that CODIS+is the most adequate technique for fexible robot arm, outperforming MIL and SIL by 4–5 times.
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