基于一种最优核鉴别矢量集的雷达目标识别

基于高分辨距离像的雷达目标识别的关键是如何提取距离像的有效鉴别特征.通过分析核Fisher准则函数下核类内散布矩阵的零空间信息与非零空间信息对识别的贡献,基于同构映射思想,求解出一组最优鉴别矢量集,用于提取距离像的鉴别特征.同时,给出一种快速算法,用较少的训练样本表达投影方向,加快了鉴别特征的提取速度.基于外场实测数据的实验证明了方法的有效性.     

Starch-binding domains in the post-genome era

Starch belongs to the most abundant biopolymers on Earth. As a source of energy, starch is degraded by a large number of various amylolytic enzymes. However, only about 10% of them are capable of binding and degrading raw starch. These enzymes usually possess a distinct sequence-structural module, the so-called starchbinding domain (SBD). In general, all carbohydrate-binding modules (CBMs) have been classified into the CBM families. In this sequence-based classification the individual types of SBDs have been placed into seven CBM families: CBM20, CBM21, CBM25, CBM26, CBM34, CBM41 and CBM45. The family CBM20, known also as a classical C-terminal SBD of microbial amylases, is the most thoroughly studied. The three-dimensional structures have already been determined by X-ray crystallography or nuclear magnetic resonance for SBDs from five CBM families (20, 25, 26, 34 and 41), and the structure of the CBM21 has been modelled. Despite differences among the amino acid sequences, the fold of a distorted β-barrel seems to be conserved together with a similar way of substrate binding (mainly stacking interactions between aromatic residues and glucose rings). SBDs have recently been discovered in many non-amylolytic proteins. These may, for example, have regulatory functions in starch metabolism in plants or glycogen metabolism in mammals. SBDs have also found practical uses. Received 25 May 2006; received after revision 26 June 2006; accepted 3 August 2006     

一种逐步优化灰导数背景值的GM(1,1)建模方法

证明了离散齐次指数函数经一次累加生成后为离散非齐次指数.进而在GM(1,1)以均值生成作为灰导数背影值的基础上,进一步提出了一种逐步优化灰导数背景值的方法,提高了建模精度,特别对于绝对灰度为0(或很小)的具有齐次灰指数律的数据,应用该方法可以得到十分理想的预测模型.     

电子商务安全探讨和网上交易规范设计

首先探讨了电子商务活动中所面临的安全威胁和防范措施,然后在介绍网上交易基本概念的基础上,进一步阐述了网上交易的基本原则和网上交易服务提供者的规范行为。     

本科生毕业论文质量保障体系的构建——本科生撰写毕业论文辅助软件的研究

分析了本科生毕业论文质量滑坡的原因,阐述了研发本科生撰写毕业论文辅助软件的必要性以及毕业论文辅助软件各模块的功能,并分析了毕业论文辅助软件的实用价值。     

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.     

HIV模型的统计诊断

描述HIV的数学模型是一组非线性常微分方程,其中包括CD4+T细胞再感染率和死亡率,HIV病毒死亡率等多个重要未知参数,准确估计这些参数有助于正确了解患者病情发展,以采用个人化治疗方案.针对此模型已提出多个参数估计方法,包括基于数值解的非线性最小二乘,截面似然及两步估计.另一方面,由于客观因素影响,各观测数据对于参数估计的影响大小不同,找出对参数估计影响大的观测值,进一步分析其原因具有重要意义.基于HIV模型的两步估计,构造了用于影响分析的非参数Cook型统计量,并给出其大样本分布.通过模拟数据和临床数据分析发现:(1)所构造统计量可以检测中度以上偏移.(2)相对于内点,边界点对HIV模型的参数估计影响更大.基于以上结论,建议对HIV模型进行参数估计时,对边界点应加以格外关注.提出的方法也可以推广到其他线性常微分方程模型的统计诊断问题中.     

COM组件的设计与使用

本文从现代编程思想出发，介绍了COM组件技术及在现实编程环境中遇到的一些有关COM编程的关键技术．并具体描述了联机手写汉字规整化COM组件的设计及在客户程序中如何使用组件．     

如何在《统计学》课堂中掌握SAS编程技术

结合统计学课堂教学实践,通过分析数据步、程序步以及统计模块,论述了SAS编程技术学习过程中应注重的3个基本环节.     

基于LabVIEW的流水线炉温控制系统设计

控制系统采用模块化的程序设计思想,以生产流水线加热温控系统、WAGO-I/O-SYSTEM、PC机为硬件配置,以LabVIEW为软件开发平台,模拟工件预热、高温、冷却3个阶段,编程实现了温度的实时显示、历史曲线显示、炉温PID控制以及温度超限报警、手动/自动控制的切换等功能。并进一步整定了炉膛PID参数。测试结果表明,该炉温控制系统测量精度较高、安全可靠、界面友好易于操作,而且可扩展性强。本系统针对实验教学改革,适用于开展大学生课外科技活动、拓展实践能力。