一个基于对象代理模型的多表现地理信息系统

文中提出了一种基于对象代理模型的实现多表现GIS的新方法。通过地理对象的代理对象来定义多表现,因此代理对象可以用来表示对象的视角多样性和角色多样性。通过对象更新迁移可以支持动态分类和系统一致性维护。另外,对象及其代理对象之间的双向指针使得跨类查询变得非常容易,从而可以扩展查询的范围。文中实现了一个基于对象代理模型的多表现GIS原型,性能测试表明该方法比传统的方法更加有效。     

3D对象动态方位邻接关系及双向关联表示

3D空间对象方位关系的表示和分析在空间数据库、地理信息系统、人工智能和机器人学等领域具有重要的意义。为了分析和处理复杂的3D空间对象的方位关系,讨论了3种3D空间对象方位关系的立体表示模型：3DR7模型、3DR27模型和3DR39模型,给出了方位关系的交集序列;研究了3D空间对象方位关系的动态邻接关系和处理方法;进一步给出了3D空间对象方位关系的双向映射模型。研究成果为3D空间对象方位关系在空间数据库和地理信息系统等领域的应用奠定了基础。     

面向对象的全时域移动对象数据模型

在面向对象模型中加入对动态属性的支持,提出和建立了一种面向对象的支持全时域数据存储和查询的移动对象数据模型。探讨了GPS定位信息中精度、方位等信息对移动对象位置更新的影响,并给出了一种新的基于定位精度、速度和方位的动态阈值位置更新策略,解决了移动对象的全时域存储和查询方法。最后对面向对象的全时域移动对象数据模型进行了验证,实验表明该动态阈值位置更新策略在不影响移动对象运动轨迹精度的情况下,可以有效减少位置更新,节省数据传输流量,减少数据存储量。     

基于固定网格划分和面向类对象的四分树空间索引机制

本文针对地理信息系统中的空间对象形态的不同规则性和空间查询区域的不规则性。提出了一种基于固定网格划分的四分树空间索引机制。     

时空相点移动对象数据索引PM-Tree

随着移动定位技术和无线通讯技术发展,移动对象的应用领域越来越广阔.位置随时间而变化的移动对象产生的时空数据具有规模大、多维性、结构复杂和关系复杂等特点.由于移动对象的运动轨迹大多被限定在特定的交通网络中,因此基于路网的移动对象索引成为时空数据索引研究的一个重要应用分支.目前,针对移动对象历史数据的区域查询优化的研究重点...     

基于R树的方向关系查询处理

方向关系描述了对象间的空间顺序关系.近年来,方向关系查询处理逐渐受到空间数据挖掘和地理信息系统等空间数据库应用领域研究者的关注.方向关系查询处理需要执行方向连接操作,目前有关空间连接的研究主要集中在拓扑关系和距离关系方面,而较少考虑方向关系.研究了基于R树的方向关系查询处理方法,定义了四元组模型表示对象MBR间的方向关系,提出了基于R树的处理方向关系查询过滤(filter)步骤的方法,并将提炼(refinement)步骤细化为3种不同的操作.所提出的方法能够高效处理任意对象间的方向关系查询.考虑到空间数据挖掘中方向关系查询通常是在满足一定距离约束条件的对象之间进行,还提出了一种同时利用方向和距离约束限制R树搜索空间的查询处理算法.实验证明,与不利用R树的方向关系查询处理方法相比,所提出的方法在I/O开销和CPU开销两方面都具有很高的性能.     

Top-k集合空间关键字近似查询方法

近年来,带有位置和文本信息的空间-文本数据的规模迅速增长,以空间-文本数据为背景的空间关键字查询技术得到广泛的研究与应用。现有大多数空间关键字查询方法通常以单个空间对象作为查询结果的基本单元,最近有少数研究工作提出以一组空间对象作为查询结果的基本单元,这组空间对象联合满足用户的查询需求,但却没有考虑组内空间对象之间的关联关系。针对上述问题,提出一种top-[k]集合空间关键字近似查询方法。提出一种基于关联规则的空间对象之间的关联访问度评估方法,设计了一种结合距离和组内空间对象关联访问度的评分函数;提出了一种基于VP-Tree的剪枝策略,用于快速搜索空间对象的局部邻域,进而加快查询匹配速度;利用评分函数计算候选空间对象组合的得分,并以此选取top-[k]组空间对象作为查询结果。实验结果表明,提出的空间对象关联度评估方法具有较高的准确性,提出的剪枝策略具有较高的执行效率,获取的top-[k]组空间对象具有较高的用户满意度。     

Identifying object isomerism in multidatabase systems

In a multidatabase system that consists of object databases, the same real-world entity can be stored as objects in different databases with incompatible object identifiers. How to identify and integrate these objects representing the same entities such that (a) object duplication in the query result can be avoided, (b) information for the entity can be gathered, and (c) the specialization of multiple classes can be built is an important issue to provide a well structured global object schema and a more informative query result. In this paper, we extend our results on probabilistic query processing and joining relations on incompatible keys to solve the problem. Various data and schema conflicts such as missing data, inconsistent data and domain mismatch which may exist in classes from different databases are considered in the process of identification.Recommended by: Amit Sheth     

Pictorial Query Specification for Browsing Through Spatially Referenced Image Databases

A pictorial query specification technique that enables the formulation of complex pictorial queries for browsing through a collection of spatially referenced images is presented. It is distinguished from most other methods by the fact that in these methods the query image specifies a target database image in its entirety whereas in our approach the query image specifies the combination of objects that the target database image should contain rather than being treated as a whole image. The query objects are represented by shape features although other features such as color, texture or wavelets could also be used. Using our technique, it is possible to specify which particular objects should appear in the target images as well as how many occurrences of each object are required. Moreover, it is possible to specify the minimum required certainty of matching between query-image objects and database-image objects, as well as to impose spatial constraints that specify bounds on the distance between objects and the relative direction between them. These spatial constraints can also be used to specify other topological relations such as enclosure, intersection, overlap, etc. Each pictorial query is composed of one or more query images. Each query image is constructed by selecting the required query objects and positioning them according to the desired spatial configuration. Boolean combinations of two or more query images are also possible by use of AND and OR operators. A query image may be negated in order to specify conditions that should not be satisfied by the database images that are retrieved successfully. In addition, a capability is provided to specify whether the same instance of an object is to be used when it appears in more than one of the query images that make up the pictorial query, or whether two different instances are allowed. Several example queries are given that demonstrate the expressive power of this query specification method. An algorithm for retrieving all database images that conform to a given pictorial query specification is presented. The user interface for using this pictorial query specification method to browse the results in a map image database application is described and illustrated via screen shots.     

空间方向关系描述模型及其GIS应用分析

空间方向关系建模是一个属于空间认知范畴的研究问题。近20年来,该研究问题受到来自计算机、人工智能、机器人以及地理信息科学等领域的众多学者们关注,提出了许多形式化描述模型。首先阐述了方向关系描述框架、表达形式、基本性质以及影响方向关系描述的主要因素。然后,重点回顾及评价了一些较有代表性的方向关系建模方法及其在GIS空间查询、分析、推理中的应用,指出了其中存在的一些主要问题。最后,展望了方向关系模型及其应用中有待进一步研究的若干相关工作。     

Spatial targeting using queries in a 3-D GIS environment with application to mineral exploration

A query framework for spatial targeting within a 3-D geographic information system (GIS) software environment is introduced. Input to a query consists of parameters relevant to the query type together with a set of Common Earth Modelling objects represented as point sets, polygonal lines, surfaces, and grids or a region set (subset) thereof. The result of a 3-D GIS query is a region within each of the input objects that consists of nodes or grid cells where the query criteria was satisfied. We provide example scenarios, drawn from mineral exploration, where 3-D queries are used to guide spatial targeting within a near-mine or regional map scale setting. Query types supported are: proximity query (to a “probe” object), property query (numeric attribute), shell query (containment within a closed surface), meta-data query, feature query (dome, depression, curvature), trend query (dip plane, vector) and intersection query (with a “probe” object). Queries can be specific for a given object type but in general transcend object types. Standard set theoretical operations for a query results in newly defined regions and are supported within the Gocad^© development environment. This development focuses on queries relevant in the 3-D data integration and interpretation stages of mature geological model development as well as early analysis, typically undertaken before a fully partitioned and attributed 3-D topological model is available.     

The direction-constrained <Emphasis Type="Italic">k</Emphasis> nearest neighbor query

Finding k nearest neighbor objects in spatial databases is a fundamental problem in many geospatial systems and the direction is one of the key features of a spatial object. Moreover, the recent tremendous growth of sensor technologies in mobile devices produces an enormous amount of spatio-directional (i.e., spatially and directionally encoded) objects such as photos. Therefore, an efficient and proper utilization of the direction feature is a new challenge. Inspired by this issue and the traditional k nearest neighbor search problem, we devise a new type of query, called the direction-constrained k nearest neighbor (DCkNN) query. The DCkNN query finds k nearest neighbors from the location of the query such that the direction of each neighbor is in a certain range from the direction of the query. We develop a new index structure called MULTI, to efficiently answer the DCkNN query with two novel index access algorithms based on the cost analysis. Furthermore, our problem and solution can be generalized to deal with spatio-circulant dimensional (such as a direction and circulant periods of time such as an hour, a day, and a week) objects. Experimental results show that our proposed index structure and access algorithms outperform two adapted algorithms from existing kNN algorithms.     

DART+: Direction-aware bichromatic reverse k nearest neighbor query processing in spatial databases

This article presents a novel type of queries in spatial databases, called the direction-aware bichromatic reverse k nearest neighbor(DBRkNN) queries, which extend the bichromatic reverse nearest neighbor queries. Given two disjoint sets, P and S, of spatial objects, and a query object q in S, the DBRkNN query returns a subset P′ of P such that k nearest neighbors of each object in P′ include q and each object in P′ has a direction toward q within a pre-defined distance. We formally define the DBRkNN query, and then propose an efficient algorithm, called DART, for processing the DBRkNN query. Our method utilizes a grid-based index to cluster the spatial objects, and the B⁺-tree to index the direction angle. We adopt a filter-refinement framework that is widely used in many algorithms for reverse nearest neighbor queries. In the filtering step, DART eliminates all the objects that are away from the query object more than a pre-defined distance, or have an invalid direction angle. In the refinement step, remaining objects are verified whether the query object is actually one of the k nearest neighbors of them. As a major extension of DART, we also present an improved algorithm, called DART+, for DBRkNN queries. From extensive experiments with several datasets, we show that DART outperforms an R-tree-based naive algorithm in both indexing time and query processing time. In addition, our extension algorithm, DART+, also shows significantly better performance than DART.     

Explicit graphs in a functional model for spatial databases

Observing that networks are ubiquitous in applications for spatial databases, we define a new data model and query language that especially supports graph structures. This model integrates concepts of functional data modeling with order-sorted algebra. Besides object and data type hierarchies, graphs are available as an explicit modeling tool, and graph operations are part of the query language. Graphs have three classes of components, namely, nodes, edges, and explicit paths. These are at the same time object types within the object type hierarchy and can be used like any other type. Explicit paths are useful because real-world objects often correspond to paths in a network. Furthermore, a dynamic generalization concept is introduced to handle heterogeneous collections of objects in a query. In connection with spatial data types, this leads to powerful modeling and querying capabilities for spatial databases, in particular for spatially embedded networks such as highways, rivers, public transport, and so forth. We use multilevel order-sorted algebra as a formal framework for the specification of our model. Roughly spoken, the first-level algebra defines types and operations of the query language, whereas the second-level algebra defines kinds (collections of types) and type constructors as functions between kinds, and so provides the types that can be used at the first level     

An object deputy model for realization of flexible and powerful objectbases

In object-oriented databases, data and methods are combined by objects and their classes. Information redundancies are removed by the notions of class hierarchy and inheritance. This contributes the realization of high-performance systems. However, the flexibility of object structures still remains a problem due to its encapsulation feature. In this paper, we introduce an object deputy model which extends conventional object-oriented models with the concepts of deputy objects and deputy classes. A deputy object has its own identifier and may possess its own attributes and methods. It can also have attributes that are computed from values stored within its source object, and can be associated with methods generated from these of the source object. The inheritances are realized by switching operations, which make it possible to realize controllable, selective and dynamic inheritance structures. Schemata of deputy objects are defined by deputy classes which can be derived by an object deputy algebra. An object can have many deputy objects, and several objects can share a single deputy object. Thus, objects can be indirectly divided and combined through their deputy objects. We show that several difficult database problems, such as flexible views, objects with more than one role, object migration, and multiple inheritance become much easier in this model. The data-knowledge coordination model developed for the integration of distributed databases and knowledge-bases can also be realized easily by the object deputy model. Finally, we discuss several advanced database applications of this model, such as geographic databases, virtual office systems, and distant education systems.     

基于位置-文本关系的空间对象top-k查询与排序方法

针对普通的空间关键字查询通常会导致多查询结果的问题。本文提出了一种基于空间对象位置-文本相关度的top- k 查询与排序方法,用于获取与给定空间关键字查询在文本上相关且位置上相近的典型空间对象。该方法分为离线处理和在线查询处理2个阶段。在离线阶段,根据空间对象之间的位置相近性和文本相似性,度量任意一对空间对象之间的位置-文本关系紧密度。在此基础上,提出了基于概率密度的代表性空间对象选取算法,根据空间对象之间的位置-文本关系为每个代表性空间对象构建相应的空间对象序列。在线查询处理阶段,对于一个给定的空间关键字查询,利用Cosine相似度评估方法计算查询条件与代表性空间对象之间的相关度,然后使用阈值算法（threshold algorithm,TA）在预先创建的空间对象序列上快速选出top- k 个满足查询需求的典型空间对象。实验结果表明:提出的空间对象top- k 查询与排序方法能够有效地满足用户查询需求,并且具有较高的准确性、典型性和执行效率。     

空间对象及其拓扑关系

论文首先讨论了传统的地理信息系统中空间对象的空间数据模型,提出了面向对象的层次矢量数据模型。然后定性地分析了空间对象点与点、点与线和点与区域之间的拓扑关系,并给出了一种形式化表达空间对象成分拓扑关系的模型。最后,将这种模型与空间对象之间的拓扑关系结合起来,使其可以方便地处理地理信息系统中的对象间的拓扑关系。     

一种对象代理数据库的跨类查询优化方法

对象代理数据库中跨类查询可以充分发挥对象代理模型的灵活性,为用户提供个性化数据服务,其执行效率十分重要。然而在处理多个跨类属性查询时,现有基于路径表达式的跨类查询实现存在对公共路径节点对象进行重复获取的情形,执行效率较低。针对跨类查询中加快获取终点对象的问题,优化核心思想是减少对路径上节点对象的重复与不必要的遍历,包括两个关键策略:首先是将路径节点整体作为虚拟路径视图统一获取节点对象,避免了多跨类属性查询下公共路径节点的冗余遍历;其次是针对路径复杂过长的跨类查询,依据代价估计策略选择物化查询涉及起点与终点对象,利用缓存减少执行时路径上中间节点的遍历。分别在属性数目与结果集规模两方面进行了对比实验,实验结果表明了优化方法的有效性。     

小目标检测研究综述

随着计算机视觉和人工智能技术的快速发展,目标检测受到了更加广泛的关注。由于小目标像素占比小、语义信息少、易受复杂场景干扰以及易聚集遮挡等问题,导致小目标检测一直是目标检测领域中的一大难点。目前,视觉的小目标检测在生活的各个领域中日益重要。为了进一步促进小目标检测的发展,提高小目标检测的精度与速度,优化其算法模型,本文针对小目标检测中存在的问题,梳理了国内外研究现状及成果。首先,分别从小目标可视化特征、目标分布情况和检测环境等角度对小目标检测的难点进行了分析,同时从数据增强、超分辨率、多尺度特征融合、上下文语义信息、锚框机制、注意力机制以及特定的检测场景等方面系统总结了小目标检测方法,并整理了在框架结构、损失函数、预测和匹配机制等方面发展的较为成熟的单阶段小目标检测方法。其次,本文对小目标检测的评价指标以及可用于小目标检测的各类数据集进行了详细介绍,并针对部分经典的小目标检测方法在MSCOCO(Microsoft common objects in context)、VisDrone2021(vision meets drones2021)和Tsinghua-Tencent100K等数据...