超立方体结构并行处理系统的可靠性的计算机仿真

本文介绍立方体结构并行处理系统的原理及可靠性的计算机仿真并给出结果     

对混合Abel群中一定理证明的改进

本文指出了A.T.库洛什“群论”(上)书中一定理证明的错误,并给出了正确的证明。     

天津市各区县经济发展水平的多元统计分析

本文选取了10项适当的主要经济指标对天津市18个区（县）的经济发展水平进行系统聚类分析和主成分分析，综合评价了各区县的经济发展水平．     

云南民族大学科技处经费管理系统设计

依据软件工程的思想,分析介绍了云南民族大学科技处经费管理系统开发的整个过程,包括设计思想和整体实施过程:(1)系统开发环境的选择;(2)系统设计;(3)系统测试和发布.     

基于灰聚类和小波网络的企业投资决策绩效集成评价

基于公司的战略和利益相关者的考虑，本文设计了财务层面绩效指标、技术创新层面指标、顾客层面绩效指标、业务流程层面绩效指标、发展潜力层面绩效指标和社会和环保层面绩效指标六个层面的企业投资决策绩效评价指标体系。建立了标杆瞄准和主成分分析相结合的指标筛选的方法，设计了基于灰色聚类和小波网络模型的企业投资决策集成评价模型，并对焦化行业进行了实证分析。     

基于FPGA的IP仿真验证平台

IP（集成电路知识产权芯核）的仿真和硬件验证是IP开发中不可缺少的环节．文中基于FPGA（现场可编程门阵列）开发了一个IP仿真验证平台,并使用PCI（外部设备互连）总线来测试IP．用户只要将自已设计的IP插入所开发的仿真验证平台,就可以方便地对IP进行测试．文中还对所设计的平台进行了软件仿真,以验证其功能,并在载有Xilinx Spartan-3 600E FPGA的PCI插卡上进行上板调试．结果表明,所建立的基于FPGA的IP仿真验证平台可以对IP进行有效的仿真和验证,并具有良好的稳定性和实用价值．     

Cooperative Sensor Anomaly Detection Using Global Information

Sensor networks are deployed in many application areas nowadays ranging from environment monitoring, industrial monitoring, and agriculture monitoring to military battlefield sensing. The accuracy of sensor readings is without a doubt one of the most important measures to evaluate the quality of a sensor and its network. Therefore, this work is motivated to propose approaches that can detect and repair erroneous (i.e., dirty) data caused by inevitable system problems involving various hardware and software components of sensor networks. As information about a single event of interest in a sensor network is usually reflected in multiple measurement points, the inconsistency among multiple sensor measurements serves as an indicator for data quality problem. The focus of this paper is thus to study methods that can effectively detect and identify erroneous data among inconsistent observations based on the inherent structure of various sensor measurement series from a group of sensors. Particularly, we present three models to characterize the inherent data structures among sensor measurement traces and then apply these models individually to guide the error detection of a sensor network. First, we propose a multivariate Gaussian model which explores the correlated data changes of a group of sensors. Second, we present a Principal Component Analysis (PCA) model which captures the sparse geometric relationship among sensors in a network. The PCA model is motivated by the fact that not all sensor networks have clustered sensor deployment and clear data correlation structure. Further, if the sensor data show non-linear characteristic, a traditional PCA model can not capture the data attributes properly. Therefore, we propose a third model which utilizes kernel functions to map the original data into a high dimensional feature space and then apply PCA model on the mapped linearized data. All these three models serve the purpose of capturing the underlying phenomenon of a sensor network from its global view, and then guide the error detection to discover any anomaly observations. We conducted simulations for each of the proposed models, and evaluated the performance by deriving the Receiver Operating Characteristic (ROC) curves.     

裴务齐正字本《刊谬补缺切韵》异构字声符的音韵类型及其成因

收集裴务齐正字本《刊谬补缺切韵》中的异构字,其中声符代换的有149组。这些代换声符的声音在隋唐时期可分为两类:音同声符,音近声符。探究声符变化的原因有四点:反映语音演变,方言不同,简省笔画,误用。     

TChart和TDBChart组件在地质绘图中的应用

通过比较组件的常用属性、方法和特点，对Delphi中提供的TChart和TDBChart组件在地质绘图中的应用进行了探讨。同时对计算机图形学中常用的最小二乘法逼近算法，进行了介绍。灵活使用这两个组件，不仅可以提高地质绘图的效率，在相应算法的支持下，减小作图误差还能大大提高绘图精度，具有很强的实用性。     

基于PCA的RBF神经网络预测方法研究

主成分分析(PCA)法可以提取样本集的主成分,实现样本的最优压缩,从而降低样本的维数。针对用RBF神经网络进行多因素时间序列预测时样本特征指标过多的问题,提出用统计理论的PCA方法对数据进行预处理,再选出几个主成分作为神经网络的输入节点.仿真实验表明,基于PCA的RBF神经网络模型在拟合预测中与一般的RBF神经网络模型相比有较好效果,简化了网络结构,改善了预测精度.