对象

Quantifying similarity/difference between two objects plays an important role in many contexts The quality of the similarity/difference scores can be improved by considering the semantic information related to the features of objects A flexible semantic distance function called X Dist is proposed, which can utilize the semantic information to measure the difference between two objects based on a solution to the transportation problem from linear optimization With a ground distance function for single features being a metric, X Dist is also a metric This property is very useful for making searching efficient, but is not investigated in the previous research Moreover, the experimental results show X Dist can be as good as the previously studied similarity measures in nearest neighbor searching, discriminative power and computing speed

量化对象间相似性/差别的方法具有广泛的用途，利用相关的语义信息能够得到更好的量化结果提出了一个量化对象间语义差别的距离函数XDist，它基于线性优化中的运输问题模型和相关的语义信息量化两个对象之间的差别在量化特征的差别函数是度量的情况下，XDist是一个度量，在提高搜索的效率方面具有优势，弥补了以往研究的不足，而且实验初步表明，此函数在最近邻查询效果、差别分辨力和计算速度方面能与已有函数相媲美1 引言量化对象间相似性/差别的方法具有广泛的用途，例如数据挖掘中的聚类；信息检索中的相似文档查询；协同过滤中的相似用户查询；CBR中的相似案例查询集合是对象特征表示的常用结构，集合的元素是与对象特征相关的项，它们可以

Practically all Python objects have a string presentation either evaluatable from repr( or '', or printable from str. The print statement automatically invokes the str function for an object. This gets even better. When you are defining your own objects, there are hooks for you to create string representations of your object such that repr and str (and '' and print) return an appropriate string as output. And if worse comes to worst and neither repr or str is able to display an object, the Pythonic default is at least to give you something of the format

事实上，所有的Python对象都有一个字符串表示形式（通过repr函数，''或者str函数来展现）。print语句自动为每个对象调用该对象的str方法，这种机制的一个额外的好处就是在你定义你自己的对象时，你可以利用这种机制定义repr(，str或者''或者print来为你的对象创建一种字符串表达形式，它可以在被调用时返回适当的字符串描述信息，这样即使在坏的不能再坏的情况下，repr或者str起码可以给你返回一个对象的信息，Pythonic方式的默认做法是起码给你返回想如下格式的信息

Then the spatial index is constructed which includes not only the external approximate expression but also interior approximate expression of spatial object and is extended from tranditional index only with external approximate expression. The index structures of MR-tree and MRD-tree based on multi-approximate expression are set up with the prototype index of R-tree, and the relevant algorithms about the index of insertion, deletion and search are provided. Then, the efficiencies of constructing index based on the multi-approximate expression and window range query are analysised and compared. In addition, the several algorithms and efficiency of soving the maximum enclosed circle and maximum enclosed rectangle are discussed and analyzed during constructing index based on multi-approximate expression.

首先，论文讨论了空间数据的特点、空间数据库的关键技术以及空间对象间的拓扑、距离以及方向关系，分析了空间对象的外部和内部近似表达，然后将传统索引中只利用空间对象的外部近似扩展为既有空间对象的外部近似又有空间对象的内部近似，即以空间对象的多重近似来构建索引，并以R-tree为索引原型构建基于多重近似的MR-tree和MRD-tree索引结构，然后给出了相关索引的插入、删除及查找算法，并通过实验比较分析了基于多重近似索引与基于外部近似索引的构建效率及窗口范围查询效率。

After analyzing the merit and lack of 9I model, the main idea is proposed: to distill some basic topological relations from 9I model, of which the composite topological relations of complex objects are made up. In detail, the composite topological relationships between region and region, line and line, line and region are particularly discussed;(2)Analyze the characteristics and inner relations of cadastral features. According to the expressional model of complex topological relations, the author discovers the possible topological relations between parcels, parcel lines and parcel points. In addition, sum up the general topological relationship rules of cadastral data.(3) Then the topological relations model is extended to the spatio-temporal data. Time in cadastral database and change semantic are discussed. It's redefined that spatio-temporal topological relations is composed of time, location, status and event relation. Spatio-temporal topological relationships can be represented by extended 4I model. Taking cadastral parcels as example, there are different possible spatio-temporal topological relationships between parcels when they are extended, shrunken, split, merged or others. Thus, some deductions are drawn that, for example, if parcels have be coexisting for some time they are impossible to be overlapped. Furthermore, the parents of parcels alternated and their possible change types can be detected by their spatio-temporal topological relationships.(4) Before carrying out the experiment, the calculation method must be designed.

具体研究工作及成果如下：（1）根据点集拓扑理论中与拓扑空间相关的概念，本文对空间的点、线、面进行了重新定义，以区分对象的复杂性；分析了9I模型在表示简单对象方面的优点，以及在表达复杂对象上的不足，阐述了本文的研究思路和解决方案，并以复杂的面面、线线和线面为例详细探讨了复合拓扑关系的表达方法；（2）分析了地籍权属数据和地类数据的内涵、特点和要素之间的联系，根据复杂对象的拓扑关系表达模型，本文讨论了宗地、界址线、界址点之间，图斑、线状地物、零星地类之间可能存在的拓扑关系和形式化表达方法，归纳总结了地籍对象的拓扑关系满足的约束性规则；（3）将拓扑关系的研究延伸到时空领域，从地籍对象的时态性出发，本文阐述了地籍数据中时间的含义和变化语义描述的需要；从时间、位置、状态、事件等之间的拓扑关系方面，重新系统性地进行了时空拓扑关系的定义；研究了一维时间和二维空间的集成表达方式，以宗地、界址线为例，分析了变更前后不同时间区间里可能的拓扑关系，探讨了时空拓扑关系对时空变化操作类型和变化语义的推理方法和意义；（4）为实现空间拓扑关系的查询分析等应用，本文研究了空间拓扑关系的计算方法。

Mild realism defines fictional objects as a kind of abstract objects. And antirealism considers that fictional objects are nothing or none. This paper holds and proves that fictional objects are one kind of abstract objects produced by the"third world".

极端实在论者把虚构对象看作与抽象对象和实体对象具有同等地位的另一种具有客观存在的对象；温和实在论把虚构对象定义为抽象对象的一种；非实在论者完全否定虚构对象的存在，把虚构对象等同于空无和虚无。

The frondose implement step is that: first, establishes the Use Case fig of environment system in accordance with the proposed target function, of which on the basis identifies and makes sure the basic object and classes.

具体实施步骤是：首先根据提出的环境系统的目标功能，建立系统的Use Case图，在此基础上识别并确定系统的基本对象和类；随后设计这些对象和类的属性、方法和操作，绘制对象类图；接着通过分析对象和类之间的关系，确定对象间的行为和活动，并通过绘制活动图、顺序图、状态图来反映对象间的行为及对类的状态的影响。

The model is composed of six primitive and six objects. The primitive elements are vertex, segment, triangle, secund quadrilateral, QTPV and DEM, respectively. And the objects are point, line, surface, volume, complex and spatial object, respectively.

模型包含顶点、线段、三角形、侧面四边形、似三棱柱体元和DEM 6个基本元素，同时包含点对象、线对象、面对象、体对象、复杂对象、空间对象等6个对象。

This method stratifies the object subnets using the object-oriented concept and technology,and simplifies the object subnet in each layer in turn using the reduction rules on the premise of keeping the subnet natures,and simultaneously carries on the deadlock detection to the object subnet as well as the corresponding object subnet's,until all objects have been disposed of.

该方法运用面向对象的概念和技术，为对象子网进行分层，且在保持子网性质的前提下，利用约简规则依次简化每层对象子网，并同时检测对象子网以及相应对象子网间的死锁关系，直到所有对象处理完毕。

Five class objects of geodetic data are determined. They are spatial datum object, point object, network object, intersection object and collection object. The object-oriented geodetic data model is established in the paper.

确定了5种大地测量数据的对象类，即空间基准对象、点对象、网对象、关联对象和集合对象，并以此建立了大地测量数据的对象模型。

In this paper a novel ontology-based data semantic fusing frame named ODSF is introduced, the basic element of ODSF is dataset its semantic is obtained by the mapping between the domain ontology and dataset. ODSF adopts nested relation model to represent the schema information of dataset, and realizes the data fusing from coarse-grained level to the small-grained level by wrapping the datasets registered in virtual database as a new dataset. We also present the semantic model of ODSF, query executing process and algorithm of virtual database, so ODSF can provide the semantic supported and QoS supported data access for user. The experiments demonstrate our work and show the feasibility and effectiveness of ODSF and its key techniques.

本文提出了基于本体的语义数据容融合方法ODSF；该方法中的基本元素是数据对象，通过数据对象和领域本体之间的映射关系来表达数据对象的语义，使用嵌套关系模型来表达数据对象的模式信息，通过一个网格节点中集成的所有数据对象作为下一个节点的数据对象来实现数据资源由粗到细的融合；定义了ODSF的语义模型，给出了虚拟数据库的查询执行过程和算法，可以为使用者提供具有语义支持、服务质量保障的数据访问服务；通过原型系统验证了ODSF中理论和关键技术的正确性和可行性。

The absorption and distribution of chromium were studied in ryeusing nutrient culture technique and pot experiment.

采用不同浓度K2CrO4(0，0.4，0.8和1.2 mmol/L)的Hoagland营养液处理黑麦幼苗，测定铬在黑麦体内的亚细胞分布、铬化学形态及不同部位的积累。

By analyzing theory foundation of mathematical morphology in the digital image processing, researching morphology arithmetic of the binary Image, discussing two basic forms for the least structure element: dilation and erosion.

通过分析数学形态学在图像中的理论基础，研究二值图像的形态分析算法，探讨最小结构元素的两种基本形态：膨胀和腐蚀；分析了数学形态学复杂算法的基本原理，把数学形态学的部分并行处理理念引入到家实际应用中。