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井下煤工鼻病的探讨
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作者 宋殿兴 张朝宗 张光现 《工业卫生与职业病》 CAS CSCD 1994年第3期185-186,共2页
为阐明职业性长期接触粉尘的井下煤工鼻病的发生特点,本文对1423名井下煤工进行了调查。结果发现,煤工在井下工作时,由于鼻腔受粉尘、有害气体的刺激,久而久之形成了多种鼻病,尤其以干燥性鼻炎为多。由此认为,干燥性鼻炎是井... 为阐明职业性长期接触粉尘的井下煤工鼻病的发生特点,本文对1423名井下煤工进行了调查。结果发现,煤工在井下工作时,由于鼻腔受粉尘、有害气体的刺激,久而久之形成了多种鼻病,尤其以干燥性鼻炎为多。由此认为,干燥性鼻炎是井下煤工的一种多发病,必须引起有关领导和医务人员的重视,积极做好防治工作。 展开更多
关键词 井下煤工 鼻病 粉尘
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Concurrent collision probability of RFID tags in underground mine personnel position systems 被引量:1
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作者 JI Yuchu,XU Zhao,FENG Qinzhu,SANG Yuan School of Information & Electrical Engineering,China University of Mining & Technology,Xuzhou 221008,China 《Mining Science and Technology》 EI CAS 2010年第5期734-737,共4页
According to the basic requirements of underground mine personnel position systems and the working characteristics of active RFID tags,we studied the cause of concurrent collision of RFID tags and leak reading probabi... According to the basic requirements of underground mine personnel position systems and the working characteristics of active RFID tags,we studied the cause of concurrent collision of RFID tags and leak reading probability,by means of theoretical analysis and computation.The result shows that the probability of wireless collision increases linearly with an increase in the number of tags.The probability of collision and leak reading can be reduced by extending the working period of the duty cycle and using a backoff algorithm.In a practical application,a working schedule for available labels has been designed according to the requirement of the project. 展开更多
关键词 personnel position system RFID collision probability of RFID tag
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A method for detecting miners based on helmets detection in underground coal mine videos
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作者 Cai Limei Qian Jiansheng 《Mining Science and Technology》 EI CAS 2011年第4期553-556,共4页
In order to monitor dangerous areas in coal mines automatically,we propose to detect helmets from underground coal mine videos for detecting miners.This method can overcome the impact of similarity between the targets... In order to monitor dangerous areas in coal mines automatically,we propose to detect helmets from underground coal mine videos for detecting miners.This method can overcome the impact of similarity between the targets and their background.We constructed standard images of helmets,extracted four directional features,modeled the distribution of these features using a Gaussian function and separated local images of frames into helmet and non-helmet classes.Out experimental results show that this method can detect helmets effectively.The detection rate was 83.7%. 展开更多
关键词 Human detection Helmet detection Coal mine Gaussian model Image pattern recognition
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