The divisions of the typical army maintenance organization's tasks in wartime are discussed.Two distribution models of armored equipment maintenance objects are presented:one is calculated by maintenance workload ...The divisions of the typical army maintenance organization's tasks in wartime are discussed.Two distribution models of armored equipment maintenance objects are presented:one is calculated by maintenance workload and the other is calculated by maintenance time.Combined with the division of maintenance time limit for the land force's maintenance institutions,the probability distribution of the maintenance object which is produced from the typical armored equipment's technical failure and battle damage in every repair organization is obtained.A new way for the study of the distribution law of battle damage is supplied,which has an active function to improve the accuracy of technical support program.展开更多
目的 :探讨疾病诊断相关分组(Diagnosis Related Groups,DRG)相关指标在护理工作量测算中的应用价值,以期构建更加科学合理的护理工作量评价模型。方法 :以北京市某三级医院31个科室为研究对象,回顾性分析2023年全年各科室11项护理工作...目的 :探讨疾病诊断相关分组(Diagnosis Related Groups,DRG)相关指标在护理工作量测算中的应用价值,以期构建更加科学合理的护理工作量评价模型。方法 :以北京市某三级医院31个科室为研究对象,回顾性分析2023年全年各科室11项护理工作量评价指标的数据,使用熵权法为各指标赋权重,利用秩和比法构建DRG和非DRG工作量评价模型,比较常规测算、DRG模型及非DRG模型3种护理工作量评价方式的优劣。结果:DRG模型和非DRG模型中护士人数、出院人次、床位周转次3个指标权重相同,权重最高的指标均为转入/转出人次,危重人日数次之。相对权重、病例组合指数、护理消耗指数分别处于第8、第5、第10顺位,病例组合指数为模型中不可忽略的重要指标。DRG模型和非DRG模型科室分档结果显示,优档有5个科室(占16%),良档有22个科室(占71%),一般档有4个科室(占13%),分档结果差异具有统计学意义(P<0.05)。结论 :基于DRG相关指标构建的护理工作量评价模型可更好地体现不同科室间的差异,对护理工作量测算具有一定借鉴意义,可为护理管理决策提供科学有效的依据。展开更多
为探究人体呼吸参数与管制工作负荷的关系,本文选取27名被试开展模拟管制实验,对不同类型工作负荷下被试的呼吸参数进行采集分析。首先,根据Spearman秩相关系数计算结果,分别获取与脑力和体力管制工作负荷显著相关的呼吸参数。然后,基...为探究人体呼吸参数与管制工作负荷的关系,本文选取27名被试开展模拟管制实验,对不同类型工作负荷下被试的呼吸参数进行采集分析。首先,根据Spearman秩相关系数计算结果,分别获取与脑力和体力管制工作负荷显著相关的呼吸参数。然后,基于有序Logistic模型方法,以显著相关的呼吸参数为自变量,5类不同严重程度的脑力和体力管制工作负荷为因变量,构建脑力负荷和体力负荷严重程度预测模型并进行似然比和拟合优度检验。进一步,绘制ROC(Receiver Operating Characteristic)曲线,检验预测模型的性能;最后,使用交叉表评价方法预测模型的准确率。结果表明:呼吸参数中,呼吸周期与脑力负荷显著相关,呼吸周期、呼吸幅值和吸呼比与体力负荷显著相关。在0.05的显著性水平下,构建的脑力负荷和体力负荷严重程度预测模型拟合效果良好,整体AUC(Area Under Curve)分别为0.679和0.753,模型均具有一定的检测性能。交叉表评价结果表明,模型对脑力和体力负荷中的高负荷状态预测效果最好,准确率分别高达88.9%和83.3%。本文研究结果能够为基于呼吸参数的管制工作负荷监测提供一定参考价值。展开更多
We present techniques for characterization, modeling and generation of workloads for cloud computing applications. Methods for capturing the workloads of cloud computing applications in two different models - benchmar...We present techniques for characterization, modeling and generation of workloads for cloud computing applications. Methods for capturing the workloads of cloud computing applications in two different models - benchmark application and workload models are described. We give the design and implementation of a synthetic workload generator that accepts the benchmark and workload model specifications generated by the characterization and modeling of workloads of cloud computing applications. We propose the Georgia Tech Cloud Workload Specification Language (GT-CWSL) that provides a structured way for specification of application workloads. The GT-CWSL combines the specifications of benchmark and workload models to create workload specifications that are used by a synthetic workload generator to generate synthetic workloads for performance evaluation of cloud computing applications.展开更多
Terminal airspace(TMA)is the airspace centering several military and civil aviation airports with complex route structure,limited airspace resources,traffic flow,difficult management and considerable airspace complexi...Terminal airspace(TMA)is the airspace centering several military and civil aviation airports with complex route structure,limited airspace resources,traffic flow,difficult management and considerable airspace complexity.A scientific and rational sectorization of TMA can optimize airspace resources,and sufficiently utilize the control of human resources to ensure the safety of TMA.The functional sectorization model was established based on the route structure of arriving and departing aircraft as well as controlling requirements.Based on principles of sectorization and topological relations within a network,the arrival and departure sectorization model was established,using tree based ant colony algorithm(ACO)searching.Shanghai TMA was taken as an example to be sectorizaed,and the result showed that this model was superior to traditional ones when arrival and departure routes were separated at dense airport terminal airspace.展开更多
With the aim of improving parameter identification and, eventually, evaluating driver distraction with changes in gaze direction, we applied a genetic algorithm (GA) method to identify parameters for an existing vesti...With the aim of improving parameter identification and, eventually, evaluating driver distraction with changes in gaze direction, we applied a genetic algorithm (GA) method to identify parameters for an existing vestibulo-ocular reflex (VOR) model. By changing the initial inputs to the GA and fixing two parameters pertaining to the horizontal direction, we achieved improved parameter identification with a lower mean-square error. The influence of driver distraction on eye movement with changes in gaze direction was evaluated from the difference between the predicted and observed VOR in the vertical axis. When a driver was given an additional mental workload, the mean-square error between the measured and simulated values was bigger than that in the absence of the mental workload. This confirmed the relationship between driver distraction and eye movement in the vertical direction. We hope that this method can be applied in evaluating driver distraction.展开更多
TTCN-3(Testing and Test Control Notation version 3)是一种面向黑盒测试的测试描述与实现语言.随着TTCN-3语言的广泛应用,用户对使用TTCN-3进行性能测试的需求日益强烈.然而,TTCN-3语言没有提供有效的负载描述和产生机制.目前,在使用...TTCN-3(Testing and Test Control Notation version 3)是一种面向黑盒测试的测试描述与实现语言.随着TTCN-3语言的广泛应用,用户对使用TTCN-3进行性能测试的需求日益强烈.然而,TTCN-3语言没有提供有效的负载描述和产生机制.目前,在使用TTCN-3产生性能测试的负载时,通常需要依靠大量的人工编码.该文提出了一种模型驱动方法以更加有效地支持面向TTCN-3的负载生成.在该方法中,负载指标模型用于刻画负载指标及约束关系;负载剖面模型则能够定义指标的取值及指标值随时间变化的情况.基于这些模型,该文提出的算法能够完成从模型到TTCN-3测试系统的自动转换.TTCN-3测试系统可在负载控制点的支持下得以执行,从而模拟出满足模型描述的负载场景.该文通过案例分析验证了上述方法的有效性和所模拟负载场景的准确性.展开更多
文摘The divisions of the typical army maintenance organization's tasks in wartime are discussed.Two distribution models of armored equipment maintenance objects are presented:one is calculated by maintenance workload and the other is calculated by maintenance time.Combined with the division of maintenance time limit for the land force's maintenance institutions,the probability distribution of the maintenance object which is produced from the typical armored equipment's technical failure and battle damage in every repair organization is obtained.A new way for the study of the distribution law of battle damage is supplied,which has an active function to improve the accuracy of technical support program.
文摘为探究人体呼吸参数与管制工作负荷的关系,本文选取27名被试开展模拟管制实验,对不同类型工作负荷下被试的呼吸参数进行采集分析。首先,根据Spearman秩相关系数计算结果,分别获取与脑力和体力管制工作负荷显著相关的呼吸参数。然后,基于有序Logistic模型方法,以显著相关的呼吸参数为自变量,5类不同严重程度的脑力和体力管制工作负荷为因变量,构建脑力负荷和体力负荷严重程度预测模型并进行似然比和拟合优度检验。进一步,绘制ROC(Receiver Operating Characteristic)曲线,检验预测模型的性能;最后,使用交叉表评价方法预测模型的准确率。结果表明:呼吸参数中,呼吸周期与脑力负荷显著相关,呼吸周期、呼吸幅值和吸呼比与体力负荷显著相关。在0.05的显著性水平下,构建的脑力负荷和体力负荷严重程度预测模型拟合效果良好,整体AUC(Area Under Curve)分别为0.679和0.753,模型均具有一定的检测性能。交叉表评价结果表明,模型对脑力和体力负荷中的高负荷状态预测效果最好,准确率分别高达88.9%和83.3%。本文研究结果能够为基于呼吸参数的管制工作负荷监测提供一定参考价值。
文摘We present techniques for characterization, modeling and generation of workloads for cloud computing applications. Methods for capturing the workloads of cloud computing applications in two different models - benchmark application and workload models are described. We give the design and implementation of a synthetic workload generator that accepts the benchmark and workload model specifications generated by the characterization and modeling of workloads of cloud computing applications. We propose the Georgia Tech Cloud Workload Specification Language (GT-CWSL) that provides a structured way for specification of application workloads. The GT-CWSL combines the specifications of benchmark and workload models to create workload specifications that are used by a synthetic workload generator to generate synthetic workloads for performance evaluation of cloud computing applications.
基金supported by the National Natural Science Foundation of China(Nos.U1233101,71271113)the Fundamental Research Funds for the Central Universities(No.NS2016062)
文摘Terminal airspace(TMA)is the airspace centering several military and civil aviation airports with complex route structure,limited airspace resources,traffic flow,difficult management and considerable airspace complexity.A scientific and rational sectorization of TMA can optimize airspace resources,and sufficiently utilize the control of human resources to ensure the safety of TMA.The functional sectorization model was established based on the route structure of arriving and departing aircraft as well as controlling requirements.Based on principles of sectorization and topological relations within a network,the arrival and departure sectorization model was established,using tree based ant colony algorithm(ACO)searching.Shanghai TMA was taken as an example to be sectorizaed,and the result showed that this model was superior to traditional ones when arrival and departure routes were separated at dense airport terminal airspace.
文摘With the aim of improving parameter identification and, eventually, evaluating driver distraction with changes in gaze direction, we applied a genetic algorithm (GA) method to identify parameters for an existing vestibulo-ocular reflex (VOR) model. By changing the initial inputs to the GA and fixing two parameters pertaining to the horizontal direction, we achieved improved parameter identification with a lower mean-square error. The influence of driver distraction on eye movement with changes in gaze direction was evaluated from the difference between the predicted and observed VOR in the vertical axis. When a driver was given an additional mental workload, the mean-square error between the measured and simulated values was bigger than that in the absence of the mental workload. This confirmed the relationship between driver distraction and eye movement in the vertical direction. We hope that this method can be applied in evaluating driver distraction.
文摘TTCN-3(Testing and Test Control Notation version 3)是一种面向黑盒测试的测试描述与实现语言.随着TTCN-3语言的广泛应用,用户对使用TTCN-3进行性能测试的需求日益强烈.然而,TTCN-3语言没有提供有效的负载描述和产生机制.目前,在使用TTCN-3产生性能测试的负载时,通常需要依靠大量的人工编码.该文提出了一种模型驱动方法以更加有效地支持面向TTCN-3的负载生成.在该方法中,负载指标模型用于刻画负载指标及约束关系;负载剖面模型则能够定义指标的取值及指标值随时间变化的情况.基于这些模型,该文提出的算法能够完成从模型到TTCN-3测试系统的自动转换.TTCN-3测试系统可在负载控制点的支持下得以执行,从而模拟出满足模型描述的负载场景.该文通过案例分析验证了上述方法的有效性和所模拟负载场景的准确性.
