利用Web服务实现功能强大的在线编辑

利用Web服务的面向服务的分布式计算模型的特性，解决Web模式中的实时问题。并结合ActiveX控件技术和Word^TM VBA技术提出一个在线编辑的方案，利用word^TM的强大编辑功能与普遍性实现了功能强大的在线编辑器。     

基于MathML的数学公式在线编辑与传输的研究

大量公式和符号的编辑与传输处理是在线数学学术交流与教育活动中很重要的一个内容,MathML(Mathematical Markup Language)的出现为数学公式的在线编辑提供了强有力的支持.在对比分析相关技术的基础上,基于MathML设计一个在线公式编辑器并应用于数学论坛中,实现了公式的在线编辑、发布与显示等功能,具有很好的平台无关性、灵活性和可扩展性.     

具有主动适应机制的通用权限控制组件的设计与实现

现阶段的通用权限控制组件存在通用性不够,应用范围有限的问题。文章提出了一个具有主动适应机制的,适用基于角色的权限控制模型的系统的通用权限组件。主动适应机制能有效地屏蔽不同系统权限信息的差异性,大大提高了组件的通用性。     

空间数据转换与考古探测WebGIS

在传统考古领域中,利用现代探测和信息技术辅助考古发掘,该文阐述了多源空间数据转换为符合W3C标准GML通用格式的过程,并将其转换为SVG文件,实现了客户端的交互操作,介绍了GML技术和SVG技术,分析了考古探测WebGIS的系统结构,研究了数据转换方法,最后建立系统,验证了模拟结果。     

Ajax在油藏模型显示分析系统的应用

为了解决油藏模型显示分析系统中存在的服务器响应延迟、用户等待时间长等问题,提出一种将Ajax技术应用到原系统的改进方案.在原有系统架构的基础上增加Ajax引擎,分担服务器的部分业务逻辑,将页面表现与应用逻辑进行分离.通过页面的局部更新,实现了地图加载与信息查询过程的页面无刷新.实验结果表明,Ajax技术在系统中的应用,有效减少了网络中的数据传输与处理,降低了服务器负载,避免了服务器响应延迟,使用户体验得到了优化.     

ShowDocument：在线文档编辑与分享

ShowDocument提供了非常便捷的网络服务,用户可以在线上传文件,并邀请其他入来查看、编辑和讨论,而且操作简单易用。     

基于Web服务的WebGIS研究与实现

自Web服务的概念出现以来，在IT界引起了极大的关切．人们积极探讨其长短并考虑其在自己的研究领域中是否具有可用性。本文首先分析了Web服务应用于WebGIS的必然性；接着，探讨了Web服务应用于WebGIS的三大主要作用；其一．扩展了WebGIS的功能，使其能满足复杂的GIS应用；其二，实现真正的互操作；其三．实现了软件的实时更。最后．给出一个基于Web服务的WebGIS体系结构并进行了简单的实现。     

在线编辑Office文档

你是否遇到过这样的尴尬:将Office套件创建的文档拷贝到其他电脑,却由于软件原因无法打开,比如版本问题、兼容性问题等。又或者在某台电脑上临时编辑文档,却不想下载安装Office套件。其实遇到这样的情况我们可以利用SkyDrive的在线编辑功能来帮忙,以     

基于WebGIS空间数据库的研究

自然资源和地理信息空间数据库的研究是当前研究的热点之一。由于资源环境的不断恶化，各级政府部门都很重视、投全也很大．积累了大量的自然资源数据，如何科学地利用这些数据去保护环境是当前面临的重大课题。先说明了WebGIS一般特点，然后与江苏省自然资源空间数据库的建设相结合，具体介绍了基于WebGIS的空间数据库的系统设计方法和设计过程。     

在线多媒体试题编辑系统的设计与实现

针对在传统的在线试题编辑系统中不支持多媒体试题编辑的弊端,本文提出了基于J2EE技术平台,利用eEditor组件实现的在线多媒体试题编辑系统的方法,并给出了具体的设计方案及关键代码.     

科学考察空间数据WebGIS信息发布及可视化研究

为有效共享科学考察第一手数据资料,结合考察采样及调查数据的时空特性,采用WebGIS及RIA Flex等最新网络及可视化技术,提出一种在线发布科考空间信息的系统框架,实现多元科学考察数据基于WebGIS的空间信息发布与可视化表达.基于J2EE架构设计与实现多元科考空间数据的统一访问Web服务接口,完成空间数据内容的统一...     

Towards certain fixes with editing rules and master data

A variety of integrity constraints have been studied for data cleaning. While these constraints can detect the presence of errors, they fall short of guiding us to correct the errors. Indeed, data repairing based on these constraints may not find certain fixes that are guaranteed correct, and worse still, may even introduce new errors when attempting to repair the data. We propose a method for finding certain fixes, based on master data, a notion of certain regions, and a class of editing rules. A certain region is a set of attributes that are assured correct by the users. Given a certain region and master data, editing rules tell us what attributes to fix and how to update them. We show how the method can be used in data monitoring and enrichment. We also develop techniques for reasoning about editing rules, to decide whether they lead to a unique fix and whether they are able to fix all the attributes in a tuple, relative to master data and a certain region. Furthermore, we present a framework and an algorithm to find certain fixes, by interacting with the users to ensure that one of the certain regions is correct. We experimentally verify the effectiveness and scalability of the algorithm.     

Searching and editing MPEG-compressed video in a distributed online environment

WebClip (on-line demo at http://www.ctr.columbia.edu/webclip) is a compressed video searching and editing system operating over the World Wide Web. WebClip uses a distributed client-server model including a server engine for content analysis/editing, and clients for interactive controls of video browsing/editing. It specializes several unique features, including compressed-domain video feature extraction and manipulation, multi-resolution video access, content based video browsing/retrieval, and a distributed network architecture.     

Nearest neighbor editing aided by unlabeled data

This paper proposes a novel method for nearest neighbor editing. Nearest neighbor editing aims to increase the classifier’s generalization ability by removing noisy instances from the training set. Traditionally nearest neighbor editing edits (removes/retains) each instance by the voting of the instances in the training set (labeled instances). However, motivated by semi-supervised learning, we propose a novel editing methodology which edits each training instance by the voting of all the available instances (both labeled and unlabeled instances). We expect that the editing performance could be boosted by appropriately using unlabeled data. Our idea relies on the fact that in many applications, in addition to the training instances, many unlabeled instances are also available since they do not need human annotation effort. Three popular data editing methods, including edited nearest neighbor, repeated edited nearest neighbor and All k-NN are adopted to verify our idea. They are tested on a set of UCI data sets. Experimental results indicate that all the three editing methods can achieve improved performance with the aid of unlabeled data. Moreover, the improvement is more remarkable when the ratio of training data to unlabeled data is small.     

Integrating spatial data display with virtual reconstruction

Archaeological excavations record a vast amount of 3D data. Layering artifact data on a virtual reconstruction of a site helps correlate the distribution of artifacts with their proximity to structural features. In the case presented in this article, we describe how computer graphics techniques make it possible to incorporate the display of artifact data distributions into the structural and environmental context of site architecture (specifically, a prehistoric pithouse). We have found that visualizing excavation data in this manner can help identify the implications of architectural constraints on usage areas as well as spatial distribution of artifacts with respect to significant site features     

Approximation polynomial algorithm for the data editing and data cleaning problem

The work considers the mathematical aspects of one of the most fundamental problems of data analysis: search (choice) among a collection of objects for a subset of similar ones. In particular, the problem appears in connection with data editing and cleaning (removal of irrelevant (not similar) elements). We consider the model of this problem, i.e., the problem of searching for a subset of maximal cardinality in a finite set of points of the Euclidean space for which quadratic variation of points with respect to its unknown centroid does not exceed a given fraction of the quadratic variation of points of the input set with respect to its centroid. It is proved that the problem is strongly NP-hard. A polynomial 1/2-approximation algorithm is proposed. The results of the numerical simulation demonstrating the effectiveness of the algorithm are presented.     

基于Java/Oracle Spatial构架的WebGIS研究与应用

Java开发WebGIS应用是一门新兴的技术。Oracle Spatial采用面向对象技术来管理空间数据,而面向对象数据模型正是目前GIS发展的方向。探讨了Java技术在WebGIS中的应用,分析了拓扑关系和面向对象的数据模型和Oracle Spatial空间数据库,最后讨论了结合Java和OracleSpatial的WebGIS应用实例。     

Clustering spatial data with a hybrid EM approach

In spatial clustering, in addition to the object similarity in the normal attribute space, similarity in the spatial space needs to be considered and objects assigned to the same cluster should usually be close to one another in the spatial space. The conventional expectation maximization (EM) algorithm is not suited for spatial clustering because it does not consider spatial information. Although neighborhood EM (NEM) algorithm incorporates a spatial penalty term to the criterion function, it involves much more iterations in every E-step. In this paper, we propose a Hybrid EM (HEM) approach that combines EM and NEM. Its computational complexity for every pass is between EM and NEM. Experiments also show that its clustering quality is better than EM and comparable to NEM.     

Visualizing spatial multivalue data

We introduce multivalue data as a new data type in the context of scientific visualization. While this data type has existed in other fields, the visualization community has largely ignored it. Formally, a multivalue datum is a collection of values about a single variable. Multivalue data sets can be defined for multiple dimensions. A spatial multivalue data set consists of a multivalue datum at each physical location in the domain. The time dimension is equally valid. This leads to spatio-temporal multivalue data sets where there is time varying, multidimensional data with a multivalue datum at each location and time. The spatial multivalue data type captures multiple instances of the same variable at each location in space. Visualizing spatial multivalue data sets is a new challenge.