Research on Grid Database Materialized Query Caching Policy

提出了基于XML Database的网格数据库物化查询缓存机制,提高用户查询的速度,均衡网格负载。定义了网格数据库服务质量与数据质量的标准,提出了物化查询选择算法MQS,为用户提供更好的数据服务。In this paper,grid database materialized query caching policy based on XML Database is presented,which will improve the response time of queries and balance the load of the grid.QoS and QoD of grid database are defined to provide parameters.The MQS algorithm acts as cached materialized query selector to provide better data service.福建省自然基金资助项目(A0310008);; 福建省高新技术研究开放计划重点资助项目(2003H043

电子政务基础数据库建设和信息服务研究

电子政务的目标是实现以“Citizen-centered”为宗旨的新的服务型政府。建设的中心问题是数据资源的共享与办公流程的优化重组。基础数据库的建设是电子政务建设的基础,基于基础数据库的信息服务是政府办公透明化的保障,也是电子政务向公众提供服务的重要手段。讨论了电子政务建设中的基础数据库建设问题和信息服务系统的结构和应用

应用ODS 技术解决电子政务系统数据一致性问题

讨论了ODS 技术在电子政务系统中的应用. 将ODS 引入到电子政务系统中形成更为合理的DB2ODS2DW3 层结构,并通过ODS 记录系统和参考表的使用进行全局联机事务处理,使各业务数据库内容可以实时更新,保持数 据的一致性. 从根本上解决密切相关的业务数据库数据不一致的问题

福建省自主创新政策工具的互补性研究

本文以福建省创新政策调查数据为基础,利用互补性的超模函数表述方式,从定量的角度实证检验福建省自主创新政策工具在不同阶段的互补性。结果显示,在提高企业创新力度阶段,人才资源方面的政策与资金投入、外部技术支持、科技创新基地及平台等三方面的政策均存在互补性关系,外部技术支持方面的政策和科技创新基地及平台方面的政策之间存在替代性关系;在创新成果转化阶段,知识产权保护方面的政策和成果转化与产业化方面的政策之间存在替代性关系。福建省软科学项目“国内外自主创新政策比较及海西经济区自主创新政策框架设计”(项目编号:2014R01010061

NDSMMV——A New Dynamic Selection Strategy of Materialized Views for Multi-Dimensional Data

物化视图的选择策略是数据仓库研究的重要问题之一.通过深入研究提出了一种多维数据集中物化视图动态选择的新策略——NDSMMV,包括候选视图生成算法CVGA、物化视图选择算法IGA、物化视图调整算法MAMV和物化视图动态调整算法DMAMV.CVGA基于多维数据格生成候选视图集,对候选视图数量进行压缩以减少后续算法的视图空间搜索代价和时间复杂度;IGA基于视图查询、视图维护和存储空间三元评价标准在候选视图集上进行物化视图的选择;MAMV基于物化视图选择过程已选视图的收益变化情况对物化视图进行进一步调整以提高查询的响应性能;DMAMV定时地判断查询视图类型分布是否变化来决定是否进行物化视图的动态调整,从而避免了物化视图集的"抖动".理论分析和实验结果表明该策略是有效可行的.The selection strategy of materialized view is one of the important issues of data warehouse research.Its goal is to elect a group of materialized views,which could cut down the cost of the query greatly on the basis of the limited storage space.The cost model is proposed at first.Then,a new dynamic selection strategy of materialized views for multi-dimensional data(NDSMMV)is presented,which is composed of four algorithms:CVGA(candidate view generation algorithm),IGA(improved greedy algorithm),MAMV(modulation algorithm of materialized views)and DMAMV(dynamic modulation algorithm of materialized views).CVGA generates the candidate view set based on multi-dimensional data lattice,which reduces the number of candidate views to decrease the space search cost and time consumption of the following algorithm.IGA selects materialized views taking account of view query,view maintenance and space constraint.MAMV modulate the materialized views according to the change of the materialized view profit,which improves the capability of querying materialized views.DMAMV uses the sample space to judge whether it is necessary to change the view set which can avoid sharp dither.The comparative experiment indicates that NDSMMV operates more effectively than BPUS and FPUS in the respect that CVGA reduces the amount of views beforehand.IGA selects the materialized views quickly,MAMV modulates the materialized views accurately,and the query expense decreases further with the modulation of the DMAMV on line,which validates the efficiency of NDSMMV.国家自然科学基金项目(50604012);; 福建省高新技术研究计划重点项目(2003H043)~

Updating Algorithm for Association Rules Based on Fully Mining Incremental Transactions

目前已提出了许多快速的关联规则增量更新挖掘算法,但是它们在处理对新增事务敏感的问题时,往往会丢失一些重要规则。为此,文章提出了一种新的挖掘增量更新后的数据库中频繁项集的算法EUFIA(Entirety Update Frequent Itemsets Algorithm),该算法先对新增事务数据分区,然后快速扫描各分区,能全面有效地挖掘出其中的频繁项集,且不丢失重要规则。同时,最多只扫描1次原数据库也能获得更新后事务数据库的全局频繁项集。研究表明,该算法具有很好的可测量性。Incremental Association rules Mining is an important content of data mining technology.This study proposes a new algorithm,called the Entirety Update Frequent Itemsets Algorithm(EUFIA)for efficiently incrementally mining association rules from large transaction database.Rather than rescanning the original database for some new generated frequent itemsets,EUFIA partitions the incremental database logically according to unit time interval,then accumulates the occurrence counts of new generated frequent itemsets and deletes infrequent itemsets obviously by backward method.Thus,EUFIA can discover newly generated frequent itemsets more efficiently and need rescan the original database only once to get overall frequent itemsets in the final database if necessary.EUFIA has good scalability in our simulation.国家自然科学基金项目(50474033);; 福建省自然科学基金项目(A0310008);; 福建省高新技术研究开放计划重点项目(2003H043

Study on extraction technology of volatile oil from cortex phellodendri by supercritical carbon dioxide

使用超临界二氧化碳技术对经过超声-微波处理过的黄柏中的挥发油进行萃取,并对萃取工艺进行响应面优化。在单因素预实验的基础上,以萃取压力、萃取温度、萃取时间为响应因素,黄柏挥发油的萃取量为响应值,根据中心组合(bOX-bEHnkEn)实验设计原理,采用三因素三水平的响应面分析法,确定各工艺条件对萃取量的影响,并用扫描电子显微镜(SEM)对萃取前、未超声-微波处理超临界萃取后及超声-微波处理超临界萃取后的黄柏进行比较观察,对萃取效果进行了微观解释。结果表明,经过超声-微波处理过的黄柏中的挥发油超临界二氧化碳萃取最佳工艺条件为:萃取压力为34MPA,萃取温度为41℃,萃取时间为66MIn,萃取率达6.03%。The supercritical carbon dioxide extraction of volatile oil from processed cortex phellodendri was optimized by response surface methodology(RSM).According to the principle of Box-Behnken central composite design,extraction pressure,extraction temperature,extraction time were chosen as response factors,extraction mass was chosen as response value,and a three-factor and three level central composite design was adopted to determine the influence of various technological conditions.Using SEM observed the cortex phellodendri before and after extraction,and explained the extraction effects from microcosmic aspect.The results showed that the optimum extraction conditions were as follows:extraction pressure 34MPa,extraction temperature 41℃,extraction time 66min,extraction yield was 6.03%.湖南省科技厅重大专项(2008FJ1007);2010年吉首大学大学生研究性学习与创新性实验计划项目(JSU-CX-2010-49

三七总苷对二甲基亚硝胺致肝纤维化大鼠胶原代谢的影响

目的:考察三七总苷对二甲基亚硝胺(DMN)致肝纤维化模型大鼠胶原代谢的影响。方法:用DMN复制中度肝纤维化模型,随机分为三七总苷组、干扰素组、三七总苷配合干扰素组、阴性对照组,分别以相应的药物连续治疗8周,检测各组大鼠血清肝功能、透明质酸及肝组织羟脯氨酸(Hyp)含量,结合常规病理HE、苦味酸-天狼星红染色,评价肝组织炎症及纤维化程度。结果:中度肝纤维化大鼠模型经过连续8周的三七总苷治疗,Hyp含量明显少于模型对照组,差异显著(P<0.05),其血清学指标、肝纤维化分级等方面均出现了不同程度的改善。结论:三七总苷能够降低大鼠胶原沉积,减少DMN所致肝纤维化大鼠胶原含量

LSNCCP:A Clustering Algorithm Based on the Largest Set of Not-Covered Core Points

聚类在数据挖掘、模式识别等许多领域有着重要的应用 提出了一种新颖的聚类算法 :一种基于最大不相含核心点集的聚类算法LSNCCP(aclusteringalgorithmbasedonthelargestsetofnot coveredcorepoints) 在密度定义的基础上 ,考察核心点之间的距离关系 ,定义相含、相交、相离这 3种核心点之间的关系 ,最后找出一个最大不相含核心点集 ,在此基础上进行聚类 ,并且找到解决丢失点问题的快速方法 该最大不相含核心点集只是全部核心点集合的一个很小的子集 ,因此有效地缩减了同类算法中搜寻核心点的时间 理论和实验上证明了这种算法的可行性和优越性Clustering is an important application area for many fields including data mining, pattern recognition, etc. In this paper, a novel clustering algorithm LSNCCP(a clustering algorithm based on the largest set of not-covered core points) is proposed. On the basis of the definition of density, the distance between the core points is discussed. And then, the three essential distance relation: covered core points, intersectant core points, and separate core points. Finally, the largest set of not-covered core points is found and based on the set the data can cluster very well. Because the largest set of not-covered core points is a lesser subset of the all core points, the new algorithm cuts short the time of searching all core points in the similar algorithms. The feasibility and the advantage or the new algorithm are proved in theory and experiment.福建省自然科学基金项目 (A0 3 10 0 0 8) ;; 福建省高新技术研究开放计划重点项目 (2 0 0 3H0 43

大豆异黄酮对肝纤维化大鼠肝损伤保护作用的实验研究

目的观察大豆异黄酮(SI)对实验性肝纤维化大鼠肝损伤的保护作用,为进一步研究SI抗肝纤维化作用提供实验依据。方法采用CCl4诱导的肝纤维化大鼠模型,造模同时用SI水溶液10ml/kg·d(90mg/kg·d)灌胃进行早期干预,检测血清肝功能(ALT、AST、ALB、TP),光镜下观察肝组织病理变化及炎症活动度。结果SI可明显降低大鼠血清ALT、AST水平,升高血清ALB、TP水平,减轻肝实质的炎症病理损伤。结论SI具有一定的保肝护肝作用,有助于预防和阻断肝纤维化的发生