支持信息集成的校园信息门户的研究与设计

信息集成是信息化发展到一定阶段的新需求,探讨了数字校园中信息集成的含义,并提出了一种支持信息集成的门户的体系结构.提出的校园信息门户对经典型门户体系结构进行了扩展,重点分析了校园信息门户各组成模块的功能和设计,也对校园信息门户实现的关键技术进行了探讨.校园信息门户对经典型门户的扩展部分的设计能够很好地符合数字校园信息集成的需求,是一套新颖且可行的校园信息集成解决方案.     

企业信息门户的体系结构

企业信息门户已经成为未来企业信息化与电子商务发展的重要方面。本文从企业信息门户的发展和兴起开始．阐述了企业信息门户的一些基本功能和扩展：企业电子商务战略的基础设施、扩展的门户访问方式、内容管理、B2B扩展、企业信息集成。最后本文提出了一个基于J2EE架构的开放式企业信息门户的体系结构。     

高校数字化校园信息门户的设计与实现

数字化校园建设是推动教育信息化的重要的系统工程,本文对数字化校园信息门户建设过程中所需要的关键技术进行了详细的阐述,论述了校园信息门户的具体工作方式以及Portlet技术的具体实现。并设计出了信息门户的总体框架、软件实现架构以及内容连接。最后通过信息集成与整合给出了一种高校信息门户实现的解决方案。     

高校数字化校园信息门户的设计与实现

数字化校园建设是推动教育信息化的重要的系统工程,本文对数字化校园信息门户建设过程中所需要的关键技术进行了详细的阐述,论述了校园信息门户的具体工作方式以及Portlet技术的具体实现。并设计出了信息门户的总体框架、软件实现架构以及内容连接。最后通过信息集成与整合给出了一种高校信息门户实现的解决方案。     

企业信息门户及其在水利领域中的应用

采用企业信息门户技术来实现企业不同应用系统的集成,是企业信息化建设的一个最佳方案。该文介绍,企业信息门户的主要技术,针对“数字黄河”建设工程中面临的问题,提出了水利信息门户的概念,并用来设计和实现一个原型系统。     

知识管理在信息门户中的应用

信息门户在企业知识管理中的直接作用是知识获取和知识传递的入口和通道。一方面,通过信息门户将知识信息进行收集和汇总,另一方面,通过信息门户将知识、信息进行分发和传递。应用知识管理的门户解决方案根据系统实现方式的不同分为两种．第一种实现方式是通过Portal产品与成熟知识管理产品集成的解决方案,第二种实现方式是基于门户产品内置的知识管理组件结合用户的实际业务情况组装成完善的解决方案。     

基于Portal构建企业信息系统集成平台

针对目前企业信息化建设中存在的"信息竖井"问题,应用Portal技术,提出解决方案,构建企业信息系统门户平台,集成现有应用系统.该方案介绍了企业门户的多层次体系结构及其构建,阐述了基于门户技术的应用系统集成及统一用户管理与授权的实现.     

浅谈发电企业一体化信息门户平台的建设

通过开发电厂企业信息门户及应用系统整合项目,叙述该项目启动的原因并提出方案。通过门户的建设,从信息资源分析和规划、应用集成和BI集成三个方面来将分散的应用、开发、安全、数据进行统一,建立企业一体化信息门户平台,使信息门户平台能够更好地解决信息化建设中各类资源的整合问题。     

浅谈发电企业一体化信息门户平台的建设

通过开发电厂企业信息门户及应用系统整合项目,叙述该项目启动的原因并提出方案。通过门户的建设．从信息资源分析和规划、应用集成和BI集成三个方面来将分散的应用、开发、安全、数据进行统一,建立企业一体化信息门户平台,使信息门户平台能够更好地解决信息化建设中各类资源的整合问题。     

信息整合在高校信息门户建设中的应用

为了更好解决高校信息门户过程中存在的问题,本文针对高校个性化信息门户建设进行了研究,介绍了信息整合的背景、概念及其方式,同时提出了个性化信息门户建设的总体框架,通过在数据整合与身份认证整合的基础上进行信息整合实现高校资源与服务的综合利用。     

Grey relational analysis method for 2-tuple linguistic multiple attribute group decision making with incomplete weight information

With respect to 2-tuple linguistic multiple attribute group decision making problems with incomplete weight information, some basic concepts and operational laws of 2-tuple linguistic variables are introduced. An optimization model based on the maximizing deviation method, by which the attribute weights can be determined, is established. According to the traditional ideas of grey relational analysis (GRA), the optimal alternative(s) is determined by calculating the linguistic degree of grey relation of every alternative and 2-tuple linguistic positive ideal solution and 2-tuple linguistic negative ideal solution. It is based on the concept that the optimal alternative should have the largest degree of grey relation from positive ideal solution and the smallest degree of grey relation from the negative ideal solution. The method has exact characteristic in linguistic information processing. It avoided information distortion and losing which occur formerly in the linguistic information processing. Finally, a numerical example is used to illustrate the use of the proposed method. The result shows the approach is simple, effective and easy to calculate.     

Integration of multi-time-scale models in time series forecasting

A solution to the problem of producing long-range forecasts on a short sampling interval is proposed. It involves the incorporation of information from a long sampling interval series, which could come from an independent source, into forecasts produced by a state-space model based on a short sampling interval. The solution is motivated by the desire to incorporate yearly electricity consumption information into weekly electricity consumption forecasts. The weekly electricity consumption forecasts are produced by a state-space structural time series model. It is shown that the forecasts produced by the forecasting model based on weekly data can be improved by the incorporation of longer-time-scale information, particularly when the forecast horizon is increased from 1 year to 3 years. A further example is used to demonstrate the approach, where yearly UK primary fuel consumption information is incorporated into quarterly fuel consumption forecasts.     

遗传算法与蚂蚁算法的融合

遗传算法具有快速随机的全局搜索能力，但对于系统中的反馈信息利用却无能为力，当求解到一定范围时往往做大量无为的冗余迭代，求精确解效率低．蚂蚁算法是通过信息素的累积和更新收敛于最优路径上，具有分布式并行全局搜索能力，但初期信息素匮乏，求解速度慢，算法是将遗传算法与蚂蚁算法融合，采用遗传算法生成信息素分布，利用蚂蚁算法求精确解，优势互补，仿真表明取得了非常好的效果。     

On principles for the selection of shape functions for the Generalized Finite Element Method

Effective shape functions for the Generalized Finite Element Method should reflect the available information on the solution. This information is partially fuzzy, because the solution is, of course, unknown, and typically the only available information is the solution’s inclusion in a variety of function spaces. It is desirable to choose shape functions that perform robustly over a family of relevant situations. Quantitative notions of robustness are introduced and discussed. We show, in particular, that in one dimension polynomials are robust when the available information consists in inclusions in Sobolev-type spaces that are x-independent.     

利用数据仓库技术解决异构数据库的集成问题

企业信息系统存在大量的异构数据库，如何集成异构数据库、解决信息孤岛现象是我们面临的问题。利用数据仓库技术来集成异构数据库是一个理想的解决方案。本文给出了异构数据库的集成方案，提出了从异构数据库抽取和转换数据的新方法，提出了ODBC用于数据抽取过程的思路，提出了数据转换规则集的概念并用于数据抽取过程中。数据仓库的建立不仅实现了企业信息系统中信息的集成，更重要的是为企业决策提供了信息源。     

On constructing a shortest linear recurrence relation

It has been shown in the literature that a formulation of the minimal partial realization problem in terms of exact modeling of a behavior lends itself to an iterative polynomial solution. For the scalar case, we explicitly present such a solution in full detail. Unlike classical solution methods based on Hankel matrices, the algorithm is constructive. It iteratively constructs a partial realization of minimal McMillian degree. The algorithm is known in information theory as the Berlekamp-Massey algorithm and is used for constructing a shortest linear recurrence relation for a finite sequence of numbers     

Asymptotic solutions to weakly coupled stochastic teams withnonclassical information

The authors develop a new iterative approach toward the solution of a class of two-agent dynamic stochastic teams with nonclassical information when the coupling between the agents is weak, either through the state dynamics or through the information channel. In each case, the weak coupling is characterized in terms of a small (perturbation) parameter. When this parameter value (say, ∈) is set equal to zero, the original fairly complex dynamic team, with a nonclassical information pattern, is decomposed into or converted to relatively simple stochastic control or team problems, the solution of which makes up the zeroth-order approximation (in a function space) to the team-optical solution of the original problem. The fact that the zeroth-order solution approximates the optimal cost up to at least O(∈) is shown. It is also shown that approximations of all orders can be obtained by solving a sequence of stochastic control and/or simpler team problems     

Extension of TOPSIS method for 2-tuple linguistic multiple attribute group decision making with incomplete weight information

With respect to linguistic multiple attribute group decision making problems with incomplete weight information, a new method is proposed. In the method, the 2-tuple linguistic representation developed in recent years is used to aggregate the linguistic assessment information. In order to get the weight vector of the attribute, we establish an optimization model based on the basic ideal of traditional technique for order performance by similarity to ideal solution, by which the attribute weights can be determined. Then, the optimal alternative(s) is determined by calculating the shortest distance from the 2-tuple linguistic positive ideal solution, and on the other side, the farthest distance of the 2-tuple linguistic negative ideal solution. The method has exact characteristic in linguistic information processing. It avoided information distortion and losing, which occur formerly in the linguistic information processing. Finally, a numerical example is used to illustrate the use of the proposed method. The result shows the approach is simple, effective, and easy to calculate.     

基于人脸检测和人眼跟踪的个人计算机安全保护系统

传统的信息保密方法虽然能够起到很好的保密效果,但其对信息的保密存在很强的刻意性,很难做到对个人信息不经意泄漏的防护,在信息安全方面存在一定的漏洞。文章在关注此类问题的基础上提出了一种有效的解决方法,通过对人脸的识别及人眼跟踪技术研究,实现了人脸对计算机屏幕保护的实时控制,达到与传统计算机桌面保护系统的完美结合,是对个人计算机信息安全保密手段的一种有效补充。     

User-centered indexing for adaptive information access

We are focusing on information access tasks characterized by large volume of hypermedia connected technical documents, a need for rapid and effective access to familiar information, and long-term interaction with evolving information. The problem for technical users is to build and maintain a personalized task-oriented model of the information to quickly access relevant information. We propose a solution which provides user-centered adaptive information retrieval and navigation. This solution supports users in customizing information access over time. It is complementary to information discovery methods which provide access to new information, since it lets users customize future access to previously found information. It relies on a technique, called Adaptive Relevance Network, which creates and maintains a complex indexing structure to represent personal user's information access maps organized by concepts. This technique is integrated within the Adaptive HyperMan system, which helps NASA Space Shuttle flight controllers organize and access large amount of information. It allows users to select and mark any part of a document as interesting, and to index that part with user-defined concepts. Users can then do subsequent retrieval of marked portions of documents. This functionality allows users to define and access personal collections of information, which are dynamically computed. The system also supports collaborative review by letting users share group access maps. The adaptive relevance network provides long-term adaptation based both on usage and on explicit user input. The indexing structure is dynamic and evolves over time. Learning and generalization support flexible retrieval of information under similar concepts. The network is geared towards more recent information access, and automatically manages its size in order to maintain rapid access when scaling up to large hypermedia space. We present results of simulated learning experiments.Dr. Mathé and Dr. Chen are contractors with Recom Technologies, Inc.