光学和传感器的防护技术

近年来，光电技术发展异常迅速，在这些技术装备中，当用光学聚焦时，辐射能量对光学元件、探测器都会构成威胁。本文讨论辐射对光学和探测器的影响以及降低其影响的防护技术。     

双能X射线骨密度仪测定技术研究

以Ｌｕｎａｒ公司ＤＰＸ－Ｌ型双能Ｘ射线骨密度仪为例，研究引起测量误差的主要因素并提出质控措施。用自检模块、腰椎体膜评定仪器的体外测量精度好于１％。对１０位志愿者重复２次测量，体内精度对腰椎，ＭＰＤ（平均百分差）为０．４６，ＣＶ（变异系数）为０．７５；对股骨颈，ＭＰＤ为１．２６、ＣＶ为０．４７；Ｗａｒｄ’ｓ三角区ＭＰＤ为２．０１、ＣＶ为１．１４；大转子ＭＰＤ为１．６６、ＣＶ为０．７２。扫描图像由２位     

Emulsifying Properties of the Total Fraction and the Hydrophobic Fraction of Bovine Milk Proteose-peptones

Since proteose-peptone is a mixture of heterogeneous proteins and peptides, its functional properties have not yet been fully understood. The present study was undertaken to elucidate the emulsifying properties of proteose-peptones and a parallel evaluation was performed of the emulsifying activity of the total fraction prepared from bulk skimmed milk by precipitation with ammonium sulphate and of the most hydrophobic fraction purified by hydrophobic interaction fast protein liquid chromatography. A turbidimetric technique was used and the absorbance value at 500 nm was then directly used as the emulsifying activity index. The results obtained confirmed the good emulsifying activity of this protein fraction of the whey and demonstrated the considerable influence of the concentration on the capacity of the proteose-peptones to stabilize a model oil-in-water emulsion. Moreover, at all the concentrations examined, the purified component 3 showed a higher emulsifying activity than the total unpurified fraction.     

高铅硫化铜精矿的二段焙烧

高铅硫化铜精矿进行湿法铜铅分离时，焙烧过程因有低熔点组份产生，使培砂中铜浸出率仅为73％～82％，达不到工艺要求。经二段焙烧后消除了上述影响，铜浸出率达到97．4％，实现了铜铅分离。     

BP网络模型对人脸朝向的识别

研究BP神经网络模型,通过计算机模拟人脑建立神经元网络,使用一部分人脸朝向信息作为训练的实例集,训练稳健后,可以推广应用判断其他人脸的朝向信息,以实现计算机自动识别人脸朝向。先对图片进行归一化等预处理,再应用主成分分析提取特征信息,每幅提取出的特征信息都是8个数据的列向量,构建一个8个输入、17个隐含、3个输出的三层BP网络模型。将训练实例集的特征向量代入训练,调整参数后保证其性能和收敛速度。最后通过大量实验验证,计算机识别的误判率仅为6.7%,模型可靠。     

基于中值滤波和梯度锐化的边缘检测

实现一种基于中值滤波和梯度锐化的边缘检测方法。首先采用既能过滤噪声又能保护边缘信息的中值滤波对图像进行平滑处理。然后采用梯度锐化加强边缘像素强度,通过简单的二值化获得图像的初始边缘,系统采用连通区域标记的方法去除位于图像封闭边界内的残留黑块。最后通过实验结果与人工提取的结果比较,进行误差分析,找出本文算法的不足之处,以便对该算法进行改进。实践证明,本文的边缘检测方法对含有噪声点且灰度分布比较均匀的图像有很好的效果。     

Weighted principal component extraction with genetic algorithms

Pattern recognition techniques have been widely used in a variety of scientific disciplines including computer vision, artificial intelligence, biology, and so forth. Although many methods present satisfactory performances, they still have several weak points, thus leaving a lot of space for further improvements. In this paper, we propose two performance-driven subspace learning methods by extending the principal component analysis (PCA) and the kernel PCA (KPCA). Both methods adopt a common structure where genetic algorithms are employed to pursue optimal subspaces. Because the proposed feature extractors aim at achieving high classification accuracy, enhanced generalization ability can be expected. Extensive experiments are designed to evaluate the effectiveness of the proposed algorithms in real-world problems including object recognition and a number of machine learning tasks. Comparative studies with other state-of-the-art techniques show that the methods in this paper are capable of enhancing generalization ability for pattern recognition systems.     

基于中间件技术的变电站温升在线监测预警系统设计

针对由于各种原因引发变电站发热方面的故障,设计了变电站温升在线监测预警系统,建立了基于中间件技术的变电站温升在线监测预警系统框架模型。采用组件式开发技术设计并实现了变电站温升在线监测预警系统,将系统的构成组件分为界面型组件及数据维护组件。组件式系统能够根据企业需求的变化实现快速重构,提高了信息系统的柔性。     

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.     

Research and Applications of Semi-solid Processing

Since it was pioneered by Flemings and otherresearchers [11, the semi-solid metal processingtechnique has been widely stUdied in the world.Especially in the past decade, SSM as a newproduct forming technique has been rapidly developed and put into commercial applications[2, 31. In recent years, with the development ofthe ado-industry of China, a lot of researchwork on SSM has been done, including the preparation of slumes, reheating and thixoforming[Al6]; moreover, great achievements have …