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科研院所实验室安全管理探讨 被引量:17
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作者 张春宇 陈浩宇 +1 位作者 袁征 毛军文 《实验室研究与探索》 CAS 北大核心 2017年第1期293-296,共4页
通过系统分析影响科研院所实验室安全管理的软件和硬件等因素,提出将实验室安全管理与实验室正规化建设有机地结合起来,实现安全与发展"双赢"的工作思路。把实验室安全管理工作的模式从安全管控转到人员素质管理上来,通过科... 通过系统分析影响科研院所实验室安全管理的软件和硬件等因素,提出将实验室安全管理与实验室正规化建设有机地结合起来,实现安全与发展"双赢"的工作思路。把实验室安全管理工作的模式从安全管控转到人员素质管理上来,通过科学、系统、完善的安全教育,提高科研人员的素质,努力实现自我管理、自我控制。明确职责,建立责任机制,把安全管理进行细化和量化;不断完善规章制度,规范各类实验操作,加大对各类危险品的管控力度;组织实验室对应急处置预案进行制定和完善,积极组织演练,提高事故的快速处置能力,并充分借助科技手段增强安全管控效益;完善实验室安全防控机制,建立实验室安全巡查、安全考核、安全群防机制。逐步摸索出一套行之有效的管理方法,建立实验室安全长效机制。 展开更多
关键词 科研院所 实验室安全管理 创新管理模式
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基于无迹卡尔曼滤波软测量技术的汽车行驶状态估计 被引量:2
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作者 郝亮 郭立新 《科学技术与工程》 北大核心 2018年第27期79-84,共6页
为了有效解决电动汽车在行驶过程中的车速、质心侧偏角和横摆角速度等参数低成本测量的问题,采用无迹卡尔曼搭建了软测量算法;该算法充分考虑电动汽车动态行驶状况下非线性的影响因素,同时采用非线性的高速公路研究所动态轮胎模型对轮... 为了有效解决电动汽车在行驶过程中的车速、质心侧偏角和横摆角速度等参数低成本测量的问题,采用无迹卡尔曼搭建了软测量算法;该算法充分考虑电动汽车动态行驶状况下非线性的影响因素,同时采用非线性的高速公路研究所动态轮胎模型对轮胎侧向力进行精确估计。通过与Car Sim动力学仿真软件进行联合仿真,对比分析验证所建立的软测量算法能够准确、实时地估计出电动汽车的运动参数。 展开更多
关键词 电动汽车 低成本测量 无迹卡尔曼滤波 软测量算法 高速公路研究所动态轮胎模型 联合仿真
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自适应软测量算法的汽车行驶状态估计 被引量:3
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作者 郝亮 郭立新 《东北大学学报(自然科学版)》 EI CAS CSCD 北大核心 2019年第1期70-76,共7页
为了实现车辆行驶状态低成本测量,设计了估计汽车行驶状态参数的传统无迹卡尔曼滤波器和能够有效解决噪声时变特性的次优Sage-Husa噪声估计器相结合算法,通过建立电动汽车3自由度的动力学模型和HSRI轮胎模型,且融合低成本测量的纵、横... 为了实现车辆行驶状态低成本测量,设计了估计汽车行驶状态参数的传统无迹卡尔曼滤波器和能够有效解决噪声时变特性的次优Sage-Husa噪声估计器相结合算法,通过建立电动汽车3自由度的动力学模型和HSRI轮胎模型,且融合低成本测量的纵、横向加速度和方向盘转向角传感器测量信息,从而可精确估计电动汽车行驶状态.在选定的典型工况下,通过与无迹卡尔曼软测量算法进行对比,硬件在环实验结果有效地验证了自适应无迹卡尔曼软测量算法具有很好的鲁棒性,且比无迹卡尔曼软测量算法更加能够有效地估计电动汽车的行驶状态. 展开更多
关键词 自适应无迹卡尔曼软测量算法 次优Sage-Husa噪声估计器 3自由度动力学模型 HSRI轮胎模型 硬件在环
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科研院所实验室安全管理方法 被引量:20
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作者 李倩 《中国安全科学学报》 CAS CSCD 北大核心 2021年第S01期62-67,共6页
为预防科研试验安全事故,利用行为安全管理(BBS)模型,研究提高科研化工实验室安全管理方法。分析近5年化工实验室事故案例原因,结合当前实验室管理存在问题,归纳出科研院所安全管理的重点及要点;基于行为安全管理模型,从组织行为和个人... 为预防科研试验安全事故,利用行为安全管理(BBS)模型,研究提高科研化工实验室安全管理方法。分析近5年化工实验室事故案例原因,结合当前实验室管理存在问题,归纳出科研院所安全管理的重点及要点;基于行为安全管理模型,从组织行为和个人行为2个层面,即安全文化、安全管理体系、安全教育培训、安全检查与隐患排查、人员个体防护、设备安全管控等方面,有针对性地提出提升实验室安全管理方法及有效措施。结果表明:在组织行为和个人行为双重管理下,提高实验室安全管理水平和科研人员安全意识,从而避免或减少实验室安全事故。 展开更多
关键词 科研院所 实验室 安全管理 行为安全管理(BBS) 组织行为
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Big Data Interprets US Opioid Crisis
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作者 Zidong Wang Poning Fan 《Proceedings of Business and Economic Studies》 2018年第3期23-29,共7页
Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need t... Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need to explore solutions to the drug crisis in the United States.In this paper,the model of in-depth analysis is established under the condition of obtaining the opioid data and the influence factor data of the large sample of five state[1].In the first part,we use the Highway Safety Research Institute model based on the differential equation model to predict the initial value,find the initial position of the drug transfer,and obtain the curve of the number of different groups over time by fitting the data,so that the curves can be predicted the changing trends of the groups in the future.It was found that in Kentucky State,the county’s most likely to start using opioids were Pike and Bale.In Ohio,the county’s most likely to start using opioids are Jackson and Scioto.In Pennsylvania State,Mercer and Lackawanna are the counties most likely to start using opioids.Martinsville and Galax are the counties where Virginia State is most likely to start using opioids.Logan and Mingo are the counties where West Virginia State is most likely to start using opioids.In the second part,the gray prediction model is used to further analyze the time series of each factor,the maximum likelihood estimation method is used to obtain the weight of each factor,and the weight coefficient matrix is used to simulate the multivariate regression equation,and the factors that have the greatest influence on opioid abuse are educational background and family composition.In the third part,the hypothesis test model of two groups(the data type is proportional)is used to verify the difference between the influence factors(including the predicted values)in the first two parts of the states,thus verifying the feasibility between them.At the same time,we put forward a few suggestions to combine the current situation in the United States with the CDC data.We believe that in order to address the opium crisis,the U.S.government needs to strengthen not only oversight of doctors'prescriptions,but also make joint efforts of all sectors of society to fundamentally reduce the barriers to the use of opioids. 展开更多
关键词 highway safety research institute model synthetic drug data fitting GRAY prediction HYPOTHESIS test antidrug ADVICE
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Big Data Interprets US Opioid Crisis
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作者 Zidong Wang Poning Fan 《Proceedings of Business and Economic Studies》 2020年第6期68-74,共7页
Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need t... Since 2010,there has been a new round of drug crises in the United States.The abuse of opioids has led to a sharp increase in the number of people involved in drug crimes in the United States.There is an urgent need to explore solutions to the drug crisis in the United States.In this paper,the model of in-depth analysis is established under the condition of obtaining the opioid data and the influence factor data of the large sample of five state[1].In the first part,we use the Highway Safety Research Institute model based on the differential equation model to predict the initial value,find the initial position of the drug transfer,and obtain the curve of the number of different groups over time by fitting the data,so that the curves can be predicted the changing trends of the groups in the future.It was found that in Kentucky State,the county's most likely to start using opioids were Pike and Bale.In Ohio,the county's most likely to start using opioids are Jackson and Scioto.In Pennsylvania State,Mercer and Lackawanna are the counties most likely to start using opioids.Martinsville and Galax are the counties where Virginia State is most likely to start using opioids.Logan and Mingo are the counties where West Virginia State is most likely to start using opioids.In the second part,the gray prediction model is used to further analyze the time series of each factor,the maximum likelihood estimation method is used to obtain the weight of each factor,and the weight coefficient matrix is used to simulate the multivariate regression equation,and the factors that have the greatest influence on opioid abuse are educational background and family composition.In the third part,the hypothesis test model of two groups(the data type is proportional)is used to verify the difference between the influence factors(including the predicted values)in the first two parts of the states,thus verifying the feasibility between them.At the same time,we put forward a few suggestions to combine the current situation in the United States with the CDC data.We believe that in order to address the opium crisis,the U.S.government needs to strengthen not only oversight of doctors'prescriptions,but also make joint efforts of all sectors of society to fundamentally reduce the barriers to the use of opioids. 展开更多
关键词 highway safety research institute model synthetic drug data itting gray prediction hypothesis test antidrug advice
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