Indexing large moving objects from past to future with PCFI

In moving object database, the moving objects' current position must be kept in memory, also to the trajectory, in some case, as same as the future. But the current existing indexes such as SEB tree, SETI tree, 2+3R tree, 2 3RT tree and etc. can only provide the capability for past and current query, and the TPR Tree, TPR * Tree and etc. can only provide the capability for current and future query. None of them can provide a strategy for indexing the past, current and also the future information of moving objects. In this paper, we propose the past current future Index (PCFI Index) to index the past, current & future information of the moving objects. It is the combination of SETI tree and TPR * tree, the SETI liking index is used for indexing the historical trajectory segments except the front line structure, and the moving objects' current positions, velocities are indexed via the in memory frontline structure which mainly implemented with TPR * tree. Considering the large update operations on TPR tree of large population, a hash table considering cache sensitivity is also introduced. It works with the frontline part, leading a bottom up update of the tree. The performance analysis proves that the PCFI index can handle most of the query efficiently and provides a uniform solution for the trajectory query, time slice query, internal query and moving query.     

Indexing large moving objects from past to future with PCFI

In moving object database,the moving objects’current position must be kept in memory,also to the trajectory,in some case,as same as the future. But the current existing indexes such as SEB-tree,SETI-tree,2+3R-tree,2-3RT-tree and etc. can only provide the capability for past and current query,and the TPR-Tree,TPR* -Tree and et. can only provide the capability for current and future query. None of them can provide a strategy for indexing the past,current and also the future information of moving objects. In this paper,we propose the past-current-future Index (PCFI-Index) to index the past,current & future information of the moving objects. It is the combination of SETI-tree and TPR*-tree,the SETI liking index is used for indexing the historical trajectory segments except the front line structure,and the moving objects’ current positions,velocities are indexed via the in-memory frontline strucltre which mainly implemented with TPR*-tree. Considering the large update operations on TPR-tree of large population,a hash table considering cache sensitivity is also introduced. It works with the frontline part,leading a bottom-up update of the tree. The performance analysis proves that the PCFI-iidex can handle most of the query efficiently and provides a uniform solution for the trajectory query,time-slice query,internal query and moving query.     

An index method for continuous moving objects

There are current, historical and future information about continuously moving spatio-temporal objects. And there are correspondingly spatio-temporal indexes for current, past and future querying. Among the various types of spatio-temporal access methods, no one can support historical and future information querying. The Time Parameterized R-tree(TPR-tree) employs the idea of parametric bounding rectangles in the R-tree. It can effectively support predictive querying to continuously moving objects.Unfortunately, TPR-tree can not used to historical querying. This paper presents a partial-persistence method in order to extend TPR-tree for querying past information of moving objects. In this method, several TPR-trees will be created for more effectively predictive querying, because TPR-tree has a time horizon limit for predictive querying.Further more, a B-tree will be used to index time dimension. Since the partial-persistence method brings about huge storage space using, this paper also discusses some methods on how to reduce storage space. Finally, this paper presents an extensive experimental study for the proposed method and gives some interesting directions for future work.     

An index method for continuous moving objects

There are current, historical and future information about continuously moving spatio-temporal objects. And there are correspondingly spatio-temporal indexes for current, past and future querying. Among the various types of spatio-temporal access methods, no one can support historical and future information querying. The Time Parameterized R-tree(TPR-tree) employs the idea of parametric bounding rectangles in the R-tree. It can effectively support predictive querying to continuously moving objects. Unfortunately, TPR-tree can not used to historical querying. This paper presents a partial-persistence method in order to extend TPR-tree for querying past information of moving objects. In this method, several TPR-trees will be created for more effectively predictive querying, because TPR-tree has a time horizon limit for predictive querying. Further more, a B-tree will be used to index time dimension. Since the partial-persistence method brings about huge storage space using, this paper also discusses some methods on how to reduce storage space. Finally, this paper presents an extensive experimental study for the proposed method and gives some interesting directions for future work.     

An index method for continuous moving objects

There are current,historical and future information about continuously moving spatio-temporal objects. And there are correspondingly spatio-temporal indexes for current, past and future querying. Among te various types of spatio-temporal access methods, no one can support historical and future information querying. The Time Parameterized R-tree (TPR-tree) employs the idea of parametric bounding rectangles in the R-tree. It can effectively support predictive querying to continuously moving objects. Unfortunately, TPR-tree can not used to historical querying. This paper presents a partial-persistence method in order to extend TPR-tree for querying past information of moving objects. In this method, several TPR-trees will be created for more effectively predictive queryiig,because TPR-tree has a time horizon limit for predictive queryiig. Further more,a B-tre e will be use d to index time dimension. Since the partial-persistence method brings about huge storage space using,this paper also discusses some methods on how to reduce storage space. Finally,this paper presents an extensive experimental study for the proposed method and gives some interesting directions for future work:.     

移动对象数据库将来查询方法研究

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移动对象的建模和查询

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基于道路网络的移动对象全时态索引与查询

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期货期权的多维Black-Scholes模型

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二维电大尺寸目标电磁散射特性的特征基函数法分析

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ICBCG算法在涡流有限元解法中的应用与探讨

用类比法给出了ICBCG算法迭代格式,并把它应用于涡流的有限元计算。对它的收敛性进行了较详细的分析与探讨,提出了在某些场合可以使收敛加速的返回迭代法。     

试探中国古代文论对社会古今观念的回应一以汉魏六朝时期文论为例

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2000—2015年黑河流域中上游NDVI时空变化及其与气候的关系

选择西北第二大内陆河黑河流域中上游为研究区, 以2000—2015年逐月NDVI数据、月均温和月降水数据、DEM数据和基础地理信息数据为数据源, 采用RS, GIS 和数理统计分析等方法, 从区域尺度和像元尺度揭示区域NDVI时空变化格局及其与气候的关系。结果显示: 1) 2000—2015年, 黑河流域中上游NDVI总体上呈现增长趋势, 其中夏季的增长速率最大, 明显高于春季和秋季; NDVI快速增长区主要位于中游地区黑河干流两侧的绿洲地带; NDVI显著下降区位于张掖市市辖区、酒泉市市辖区以及其他县城所在地; 2) 夏季NDVI与降水相关性较高, 而春、秋季NDVI与气温相关性较高; 夏季NDVI与夏季降水的显著相关性主要体现在远离黑河干流的大片低覆被草地、戈壁以及荒漠, 而邻近黑河的人工绿洲地带NDVI与降水没有显著相关性; 3) NDVI响应降水的时滞效应较明显, 夏季NDVI对降水的响应普遍存在1个月的时间滞后, 最长能滞后2个月。研究结果可以为区域植被恢复和生态系统管理提供参考。     

基于离散元法的杆系结构几何非线性大变形分析

提出应用离散元法(DEM)来求解二维、三维杆系结构的几何非线性大变形问题.基于简单梁理论,推导了适用于杆系结构分析的弹簧接触刚度系数计算公式,给出了时间步长临界值估算方法,并用实例对其进行了正确性检验.DEM方法本质上是求解结构的动力行为,对于需要计算静力解的问题,综合考虑数值精度和计算效率,建议阻尼系数取为0.7.列出了3个典型数值算例,即2个平面框架和1个空间网格结构,分别对其静力和动力大变形行为进行了模拟,并将结果与其他计算方法的结果进行比较,两者吻合良好.利用DEM方法处理几何非线性问题时无需组集刚度矩阵,也无需迭代求解非线性方程,故该方法适宜于处理杆系结构的大变形问题.     

厦门港浮游动物体内色氨酸的荧光法测定

建立了海洋浮游动物体内色氨酸的荧光分析方法.将1 mg左右样品置于安瓿瓶中,加1 mL 5.5 mol/L NaOH为水解液,在110℃水解20 h.水解产物用HCl中和,然后用KH2PO4-NaOH缓冲液调节pH为10.5,在激发波长225 nm,发射波长350 nm处测定荧光强度.方法线性范围0~0.07 mg/L,检测限为2.5×10-3mg/L,回收率99.5%~109.3%.应用该方法测量了7种从厦门港采集的浮游动物的色氨酸含量.     

基于激光测高卫星的东南极表面高变化分析

利用美国国家冰雪数据中心(NSIDC)最新发布的ICESat(云和地面高度卫星)R633版本的GLA12激光测高数据,使用重复轨最小二乘平面拟合的方法,计算得到东南极兰伯特冰川流域(Lambert)2003年~2009年的高程变化率.使用高度计重复观测数据确定表面高变化的时候,要考虑地形坡度的影响.假定在沿ICESat重复轨道小段范围内,可以用平面来拟合坡度和高程变化,并依此来计算高程变化.结果表明,Lambert冰川流域2003年~2009年平均高程变化率为(1±0.5)cm·yr-1.与已有研究成果以及交叉点获取的高程变化比较,提出的重复轨平面拟合方法有效可行.     

磷酸铵镁结晶法高效回收提钒废水中的高浓度氨氮

为实现提钒废水中氨氮的高效回收,探究了磷酸铵镁(MAP)结晶法回收提钒废水中高浓度氨氮过程中磷源、镁源、pH值、沉淀时间和n(Mg):n(N):n(P)对氨氮回收率的影响,采用Box-Behnken响应面法进行优化建模并用XRD分析产物.结果表明:MgCl2·6H2 O和Na2 HPO4·12H2 O是最适合的镁源和磷...     

楔形基无网格法解的存在惟一性

将楔形基函数与配点法结合构造了一种新的无网格法。该方法无需背景积分网格,是一种真正的无网格法。将该方法应用于求解椭圆型方程问题,给出了解的存在惟一性,并通过数值算例验证了该算法的可行性。     

从冲淤规律论马尾港的扩建

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