基于蚁群聚类算法的离群挖掘方法

离群挖掘是数据挖掘研究的重要内容,在实际生活中获得广泛应用。该文首先给出了离群数据的量化定义,并用基于蚁群的聚类学习方法,产生了状态空间的整体特征。然后结合具体的设备对象,提出了离群数据的挖掘方法。最后进行了实验验证,结果表明该文提出的方法是有效的。     

压力容器壳体曲面造型与展开误差分析

采用基于特征的多面体造型方法，解决了压力容器壳体曲面造型的问题，同时，提出了一种筒体展开的算法，并进行了误差分析与修正。     

加密算法与单片机编程

结合单片机编程信息的特点，对各种加密算法在单片机编程中的应用进行了研究     

嵌岩灌注桩的竖向承载力研究

结合实测和试验资料，从理论上分析嵌岩灌注桩竖向承载力问题，及其各种影响因素。归纳总结了确定嵌岩灌注桩的承载力方法。     

平改坡工程的研究和分析

青岛的建筑素有"万国博览会"之称,"红瓦绿树,碧海蓝天",在过去的百年历史中一直是青岛美丽的象征,随着时间的推移,特别是上世纪50年代至80年代,在沿海风貌保护区和市区重要区域出现了一些平顶建筑,与周边的环境很不协调,影响了这些区域的景观效果,破坏了青岛独特的建筑风貌.     

无线环境下一种新的证书状态查询方案

分析有线环境现有证书状态查询方案的基础上,提出了一种对传统的 O C S P进行了改进的方案-用户端部分缓存的ocsp方案,并将其与其他证书状态查询方案进行了比较。该方案借鉴了哈希链的思想,具有很高的安全性,可以有效减少用户端及服务器端的运算量,降低带宽负荷,适合用作无线环境下的证书状态查询方案。     

Maintaining mobile transactional consistency in hybrid broadcast environments

Recently there have been attempts in several research areas at efficiently utilizing the resources of mobile computers. Considering the properties in mobile computing environments, push-based data dissemination systems have lately attracted considerable attention. However, skewed access patterns among mobile clients makes response time worse, and they prefer to send data requests to the server explicitly through an uplink channel. A broadcast supporting an uplink channel is called a hybrid broadcast. In this paper, we devise new transaction processing algorithms for hybrid broadcasts. It is assumed that data objects that the server maintains are divided into Push_Data for periodic broadcasting and Pull_Data for on-demand service. That is, clients have to explicitly request data objects in Pull_Data. Maintaining transactional consistency in this environment without much additional cost is our main concern. Finally, we evaluate performance behavior through simulation study.Received: 15 November 2002, Published online: 5 August 2004This work was done as part of the Information & Communication Fundamental Technology Research Program, supported by the Ministry of Information & Communication in the Republic of Korea.     

Perturbation Analysis of Multiclass Stochastic Fluid Models

We use a stochastic fluid model (SFM) to capture the operation of finite-capacity queueing systems with multiple customer classes. We derive gradient estimators for class-dependent loss and workload related performance metrics with respect to any one of several threshold parameters used for buffer control. These estimators are shown to be unbiased and directly observable from a sample path without any knowledge of underlying stochastic characteristics of the traffic processes. This renders them computable in on-line environments and easily implementable in settings such as communication networks.