机动车辆装载问题的一种混合遗传算法实现*

针对货物装载地和运送目的地均已确定情况下的车辆装载问题,给出了基于遗传算法求解的数学模型,并对基本遗传算法的各个算子针对问题的特点提出了改进方法,同时引入启发式策略,形成了一种混合遗传算法.该算法的特点是各个算子都以提高算法收敛速度和解的最优性为目标,同时种群大小是动态变化的,以求在保证群体多样性的同时加快收敛速度.实验结果表明,该算法对求解此类问题是有效的.     

分布式PACS通信服务中间层构造方法研究

基于目前分布式PACS中存在的问题,提出一个通信服务中间层的构造方法,分别进行了基于设计模式通信框架的构造、DICOM图像互操作和分布式PACS可复用构件的研究.通信服务中间层的构造不仅提高了分布式PACS在网络异构环境中的可移植性、可扩展性以及相关QoS性能,还满足了PACS今后发展中提出的较高的互连互操作性的要求.     

基于智能客户端和SOA的新型ASP模式研究*

在对当前广泛研究的ASP模式进行综述的基础上,提出一种新的基于智能客户端和面向服务体系结构的ASP运行模式.这种模式可以解决ASP服务对数据的全面管理与客户对私有数据的安全性要求之间的矛盾.详细阐述了这一模式的优缺点,并将它与现有模式进行了比较.     

人工神经网络在组织网络化发展评价中的应用*

通过对给定样本模式的学习,构建的三层神经网络模型能够获取评价专家的经验、知识、主观判断以及对目标重要性的权重协调能力,较好地保证评价结果的客观性.实例证明,人工神经网络方法应用于组织网络化发展评价是可行和有效的.     

Windows平台下外围存储设备信息监控*

针对目前使用内部网络的外围存储设备时存在的安全问题,研究了现行外围存储设备使用中的安全保护措施,分析了现有技术方法的欠缺,提出主机外围设备使用统一管理监控的思想,并采用文件系统过滤驱动技术,设计实现了主机外围存储设备信息监控系统.     

高炉物料消耗计量数据自动认证系统的设计与实现*

以某钢铁企业为背景,针对手工认证方式实时性差、精确度低的特点,设计并实现了一套计量数据自动认证系统.该系统通过分析计量数据异常的类型,建立计量数据分析处理智能模型,实现了对计量数据按班进行差错分析和自动认证的功能,认证结果可以自动报送ERP系统.自动认证系统基于Oracle 9i数据库和PowerBuilder 8.0前台开发软件实现,具备自动认证和报表统计功能,是钢铁企业信息管理系统的重要组成部分.     

基于块段模型的三维GIS混合数据结构模型研究*

为了有效地表示三维GIS空间实体,在地质块段模型的基础上,提出了基于八叉树和四面体格网的混合数据结构模型(block octree tetrahedron,BOT模型).采用BOT模型生成算法对块段模型进行重新分割,八叉树作整体描述,四面体格网作局部精确描述,并以不同的灰度值表示不同的单元块属性.同时,为节省存储空间,提出了线性BOT编码技术.实验结果表明,BOT模型充分发挥了八叉树和四面体格网的优点,可以在不增加存储空间的前提下实现对三维目标更高效、更精确的表达.     

CORBA技术在现场设备通信中的应用*

首先简要介绍CORBA体系结构,阐述了利用CORBA的代理机制,通过代理屏蔽不同通信协议差异,以实现设备之间通信的集成策略.该机制能够方便地实现不同协议设备之间的通信集成,而且便于系统扩展,并兼容多种操作系统平台.最后结合具体实例给出现场设备的集成方案.     

Coordinated Recovery of Middleware Services:A Framework and Experiments

Being the most popular runtime infrastructure for distributed systems, middleware can be viewed as a collection of common services. Since the development, deployment and maintenance of distributed systems rely largely on middleware services, the failure of middleware services puts a significant impact on the reliability and availability of the whole system. Though recovery-based fault tolerance is an effective way to improve the reliability of middleware services, it is far away from practice mainly because of the high complexity and cost of the recovery of correlated failures between interdependent services. In this paper,a framework for detecting and recovering the correlated failures of middleware services in an automated way is presented. First, the problem is investigated from two perspectives, i.e.,analyzing the role and impact of middleware services and illustrating a set of correlated failures in J2EE standard services as motivating examples. Then, a general coordinated recovery model is constructed with the elements necessary and su±cient for detecting and recovering correlated failures in middleware services. The supporting framework is demonstrated on three J2EE application servers, i.e., PKUAS, JBoss and JOnAS, one by one without fundamental modifications. Finally, based on the three enhanced application servers, many cases on J2EE common services, including the transaction service, database service, naming and directory service, security service and messaging service, are studied. The experiment results show the effectiveness and applicability of the framework presented in this paper.     

Optimization of post-classification processing of high-resolution satellite image: A case study

The application of remote sensing monitoring techniques plays a crucial role in evaluating and governing the vast amount of ecological construction projects in China. However, extracting information of ecological engineering target through high-resolution satellite image is arduous due to the unique topography and complicated spatial pattern on the Loess Plateau of China. As a result, enhancing classification accuracy is a huge challenge to high-resolution image processing techniques. Image processing techniques have a definitive effect on image properties and the selection of different parameters may change the final classification accuracy during post-classification processing. The common method of eliminating noise and smoothing image is majority filtering. However, the filter function may modify the original classified image and the final accuracy. The aim of this study is to develop an efficient and accurate post-processing technique for acquiring information of soil and water conservation engineering, on the Loess Plateau of China, using SPOT image with 2.5 m resolution. We argue that it is vital to optimize satellite image filtering parameters for special areas and purposes, which focus on monitoring ecological construction projects. We want to know how image filtering influences final classified results and which filtering kernel is optimum. The study design used a series of window sizes to filter the original classified image, and then assess the accuracy of each output map and image quality. We measured the relationship between filtering window size and classification accuracy, and optimized the post-processing techniques of SPOT5 satellite images. We conclude that (1) smoothing with the majority filter is sensitive to the information accuracy of soil and water conservation engineering, and (2) for SPOT5 2.5 m image, the 5×5 pixel majority filter is most suitable kernel for extracting information of ecological construction sites in the Loess Plateau of China.