通过在U-tree中添加时间戳和速度矢量等时空因素,提出一种基于U-tree的高效率当前及未来不确定位置信息检索的索引结构TPU-tree,可以支持多维空间中不确定移动对象的索引,并提出了一种改进的基于p-bound的MP_BBRQ(modifiedp-bound based...通过在U-tree中添加时间戳和速度矢量等时空因素,提出一种基于U-tree的高效率当前及未来不确定位置信息检索的索引结构TPU-tree,可以支持多维空间中不确定移动对象的索引,并提出了一种改进的基于p-bound的MP_BBRQ(modifiedp-bound based range query)域查询处理算法,能够引入搜索区域进行预裁剪以减少查询精炼阶段所需代价偏高的积分计算.实验仿真表明,采用MP_BBRQ算法的TPU-tree概率查询性能极大地优于传统的TPR-tree索引,且更新性能与传统索引大致相当,具有良好的实用价值.展开更多
ISO 5167:2003(E)总结了20世纪90年代之后国际上标准差压装置的最新研究成果,在ISO 5167:1991(E)的基础上作了多项重大改进,其中标准孔板的不确定度上升到0.5%。在流量二次装置中按照标准所提供的模型对流出系数C和可膨胀性系数ε的非...ISO 5167:2003(E)总结了20世纪90年代之后国际上标准差压装置的最新研究成果,在ISO 5167:1991(E)的基础上作了多项重大改进,其中标准孔板的不确定度上升到0.5%。在流量二次装置中按照标准所提供的模型对流出系数C和可膨胀性系数ε的非线性进行补偿后,保证系统不确定度1.5%(气体、蒸汽)和1.0%(液体)的量程比可达10∶1。为了扩大量程比,可增加1台低量程差压变送器,以提高量程低段的差压测量精确度,进而提高量程低段的流量测量精确度,并在流量二次装置中实现量程切换和各项补偿,量程比可达100∶1,从而将差压法流量测量技术提高到一个新水平。根据特征点不确定度对估算进行了论证,并在流量标准装置上通过了验证。展开更多
介绍了外推法技术,在此基础上提出一种基于几何光学的吸波材料影响评估方法.该方法可以在数字滤波后有效模拟并引入反射信号,通过比较两次外推后的数据,得到对增益测量的影响评估结果.在中国计量科学研究院(National Institute of Metro...介绍了外推法技术,在此基础上提出一种基于几何光学的吸波材料影响评估方法.该方法可以在数字滤波后有效模拟并引入反射信号,通过比较两次外推后的数据,得到对增益测量的影响评估结果.在中国计量科学研究院(National Institute of Metrology,NIM)的外推法装置中进行实验验证,结果表明:该方法可以有效模拟吸波材料的影响,并给出由吸波材料引入的增益测量不确定度分量.该方法目前已应用到NIM和英国国家物理研究院(National Physical Laboratory,NPL)的外推法测量结果评定中,不仅对于外推法,对于在暗室中进行的其他天线测量结果的评估也具有很好的参考价值.展开更多
We prove the existence of an analogy between spatial long-range interactions,which are of the convolution-type introduced in non-relativistic quantum mechanics,and the generalized uncertainty principle predicted from ...We prove the existence of an analogy between spatial long-range interactions,which are of the convolution-type introduced in non-relativistic quantum mechanics,and the generalized uncertainty principle predicted from quantum gravity theories.As an illustration,black hole temperature effects are discussed.It is observed that for specific choices of the moment's kernels,cold black holes may emerge in the theory.展开更多
Distance-based range search is crucial in many real applications.In particular,given a database and a query issuer,a distance-based range search retrieves all the objects in the database whose distances from the query...Distance-based range search is crucial in many real applications.In particular,given a database and a query issuer,a distance-based range search retrieves all the objects in the database whose distances from the query issuer are less than or equal to a given threshold.Often,due to the accuracy of positioning devices,updating protocols or characteristics of applications（for example,location privacy protection）,data obtained from real world are imprecise or uncertain.Therefore, existing approaches over exact databases cannot be directly applied to the uncertain scenario.In this paper,we redefine the distance-based range query in the context of uncertain databases,namely the probabilistic uncertain distance-based range （PUDR） queries,which obtain objects with confidence guarantees.We categorize the topological relationships between uncertain objects and uncertain search ranges into six cases and present the probability evaluation in each case.It is verified by experiments that our approach outperform Monte-Carlo method utilized in most existing work in precision and time cost for uniform uncertainty distribution.This approach approximates the probabilities of objects following other practical uncertainty distribution,such as Gaussian distribution with acceptable errors.Since the retrieval of a PUDR query requires accessing all the objects in the databases,which is quite costly,we propose spatial pruning and probabilistic pruning techniques to reduce the search space.Two metrics,false positive rate and false negative rate are introduced to measure the qualities of query results.An extensive empirical study has been conducted to demonstrate the efficiency and effectiveness of our proposed algorithms under various experimental settings.展开更多
文摘通过在U-tree中添加时间戳和速度矢量等时空因素,提出一种基于U-tree的高效率当前及未来不确定位置信息检索的索引结构TPU-tree,可以支持多维空间中不确定移动对象的索引,并提出了一种改进的基于p-bound的MP_BBRQ(modifiedp-bound based range query)域查询处理算法,能够引入搜索区域进行预裁剪以减少查询精炼阶段所需代价偏高的积分计算.实验仿真表明,采用MP_BBRQ算法的TPU-tree概率查询性能极大地优于传统的TPR-tree索引,且更新性能与传统索引大致相当,具有良好的实用价值.
文摘介绍了外推法技术,在此基础上提出一种基于几何光学的吸波材料影响评估方法.该方法可以在数字滤波后有效模拟并引入反射信号,通过比较两次外推后的数据,得到对增益测量的影响评估结果.在中国计量科学研究院(National Institute of Metrology,NIM)的外推法装置中进行实验验证,结果表明:该方法可以有效模拟吸波材料的影响,并给出由吸波材料引入的增益测量不确定度分量.该方法目前已应用到NIM和英国国家物理研究院(National Physical Laboratory,NPL)的外推法测量结果评定中,不仅对于外推法,对于在暗室中进行的其他天线测量结果的评估也具有很好的参考价值.
文摘We prove the existence of an analogy between spatial long-range interactions,which are of the convolution-type introduced in non-relativistic quantum mechanics,and the generalized uncertainty principle predicted from quantum gravity theories.As an illustration,black hole temperature effects are discussed.It is observed that for specific choices of the moment's kernels,cold black holes may emerge in the theory.
基金supported by the National High Technology Research and Development 863 Program of China under Grant No. 2007AA01Z404the Program of Jiangsu Province under Grant No.BE2008135.
文摘Distance-based range search is crucial in many real applications.In particular,given a database and a query issuer,a distance-based range search retrieves all the objects in the database whose distances from the query issuer are less than or equal to a given threshold.Often,due to the accuracy of positioning devices,updating protocols or characteristics of applications（for example,location privacy protection）,data obtained from real world are imprecise or uncertain.Therefore, existing approaches over exact databases cannot be directly applied to the uncertain scenario.In this paper,we redefine the distance-based range query in the context of uncertain databases,namely the probabilistic uncertain distance-based range （PUDR） queries,which obtain objects with confidence guarantees.We categorize the topological relationships between uncertain objects and uncertain search ranges into six cases and present the probability evaluation in each case.It is verified by experiments that our approach outperform Monte-Carlo method utilized in most existing work in precision and time cost for uniform uncertainty distribution.This approach approximates the probabilities of objects following other practical uncertainty distribution,such as Gaussian distribution with acceptable errors.Since the retrieval of a PUDR query requires accessing all the objects in the databases,which is quite costly,we propose spatial pruning and probabilistic pruning techniques to reduce the search space.Two metrics,false positive rate and false negative rate are introduced to measure the qualities of query results.An extensive empirical study has been conducted to demonstrate the efficiency and effectiveness of our proposed algorithms under various experimental settings.
