IETM技术在便携式工卡系统中的应用研究

从飞机制造的角度出发,以IETM技术为基础,以带Windows 7操作系统的便携式终端为硬件平台,研究开发应用于某机机载机电设备装配指导的交互式电子工卡系统。文中主要介绍了系统设计的背景知识、开发架构和软硬件实现方法,结合XML和SQL数据库技术创作符合GJB6600标准的应用系统。该系统的成功研制和投入使用可将电子信息技术的最新研究成果用于生产实践,既可有效地减轻生产一线工作人员的劳动强度,又能极大地提高飞机数字化制造效率。     

Preparation and properties of close-packed composite materials

Monodisperse silica particles of about 0.3m diameter are suspended in methacrylate monomer using a carefully selected dispersant. Many steric dispersants are hydrocarbon chains with a reactive end-group. These are not effective as dispersants for silica in moderately polar solvents, such as esters and the methacrylate monomers. Good dispersion was obtained with a methacrylate polymer terminated by a chlorosilane end group. Settling or centrifugation of these unagglomerated dispersions gives well-packed particle beds. Polymerization of the surrounding monomer produces composite materials with high packing fractions and a high degree of regularity. Moduli and strengths of these composites are reported.     

物联网智能家居系统的研究与设计

智能家居有广阔的应用前景.针对传统家居控制上的缺陷,采用B/S架构设计了智能家居管理系统,采用ZigBee无线网络实现对各类家居设备的信息采集和指令控制.用SQL Server 2005数据库管理系统与家庭网关,进行数据的传递与接收.通过Web浏览器,用户可以实现对智能家居系统的管理.     

选择性集成算法分类与比较

选择性集成是当前机器学习领域的研究热点之一。由于选择性集成属于NP"难"问题,人们多利用启发式方法将选择性集成转化为其他问题来求得近似最优解,因为各种算法的出发点和描述角度各不相同,现有的大量选择性集成算法显得繁杂而没有规律。为便于研究人员迅速了解和应用本领域的最新进展,本文根据选择过程中核心策略的特征将选择性集成算法分为四类,即迭代优化法、排名法、分簇法、模式挖掘法;然后利用UCI数据库的20个常用数据集,从预测性能、选择时间、结果集成分类器大小三个方面对这些典型算法进行了实验比较;最后总结了各类方法的优缺点,并展望了选择性集成的未来研究重点。     

基于JSP的移动开发技术论坛的设计与实现

本文讨论基于B/S模式的一种JSP论坛的设计与实现。完成的功能模块包括用户注册,浏览板块,发帖,回帖等,管理员编辑,删除等管理帖子功能,管理管理员用户功能等。     

电动车制动能量再生反馈控制研究

研究了电动汽车制动过程中的能量回馈，设计了混合励磁无刷电动机在汽车制动过程的能量再生反馈控制系统。以脉宽调制调压调速系统为例，研究各种制动态下的能量回馈过程。并将其安装在EV6600电动汽车上进行试验，结果表明：该控制系统可达到10%左右的能量回收效率。     

图像中的文本定位技术研究综述

介绍了图像中文本定位技术的研究现状,依据定位所利用的特征进行分类,分析了其中几种典型算法,并对文本定位算法的性能评价标准进行了深入讨论。     

碱土金属在萃取剂与树脂间反应平衡常数的测定

研究了碱土金属离子在Ｄ００１树脂与８－羟基喹啉三氯甲烷溶液间的平衡常数Ｏ－ｔＫ的测定。其值依Ｍｇ、Ｃａ、Ｓｒ、Ｂａ次序减小。并得出萃取剂浓度［ＨＡ］。与金属离子在两相分配的关系。     

Generalized Transfer Subspace Learning Through Low-Rank Constraint

It is expensive to obtain labeled real-world visual data for use in training of supervised algorithms. Therefore, it is valuable to leverage existing databases of labeled data. However, the data in the source databases is often obtained under conditions that differ from those in the new task. Transfer learning provides techniques for transferring learned knowledge from a source domain to a target domain by finding a mapping between them. In this paper, we discuss a method for projecting both source and target data to a generalized subspace where each target sample can be represented by some combination of source samples. By employing a low-rank constraint during this transfer, the structure of source and target domains are preserved. This approach has three benefits. First, good alignment between the domains is ensured through the use of only relevant data in some subspace of the source domain in reconstructing the data in the target domain. Second, the discriminative power of the source domain is naturally passed on to the target domain. Third, noisy information will be filtered out during knowledge transfer. Extensive experiments on synthetic data, and important computer vision problems such as face recognition application and visual domain adaptation for object recognition demonstrate the superiority of the proposed approach over the existing, well-established methods.     

充油S-SBR加工行为的研究

在中试装置上合成相对分子质量分布较宽的充油S-SBR，考察不同环烷油和芳烃油填充量的充油S-SBR的流变性能和混炼行为。结果表明，增大油的填充量能提高充油S-SBR的流动性能，充芳烃油S-SBR相对于充环烷油的S-SBR对温度更敏感，宽相对分子质量分布的充环烷油S-SBR的混炼性能优于S-SBR1204及E-SBRl778，竟相对分子质量分布的充芳烃油S-SBR的混炼性能优于S-SBR1204，Solprene380和E-SBR1712。