使用超声估计肌肉疲劳的初步研究

表面肌电信号把神经肌肉活动和肌肉收缩联系起来，已被视为一种估计肌肉疲劳比较客观的方法，但也存在一些不足。另一方面，超声已广泛应用于医学诊断和研究，在骨骼肌方面也有不少研究报道，但还未见文献报道超声用于肌肉疲劳的估计。本文介绍一套自行开发的新的同步连续采集B超图像、力矩和肌电信号的采集系统，并利用它对肱二头肌的肌肉疲劳进行了估计。试验表明在30秒的肌肉疲劳过程中，肌肉厚度会以非线性的方式增加。     

高固体分羟基丙烯酸树脂的合成

以过氧化二苯甲酰（BPO）／过氧化二异丙苯（DCP）（质量比为2：3）为复合引发剂，二甲苯为溶剂，选用适量含羟基单体和分子量调节剂，以减缓树脂合成聚合反应中的自动加速现象，合成了分子量为3000-4000，多分散性指数d〈2的高固体分羟基丙烯酸树脂．该树脂与缩二脲多异氰酸酯（HDI）的配漆实验证明，所得漆膜鲜映性好、丰满度高、色泽好、雾影值低、综合性能较好．     

Mathematical topographical correction of XPS images using multivariate statistical methods

For rough heterogeneous samples, the contrast observed in XPS images may result from both changes in elemental or chemical composition and sample topography. Background image acquisition and subtraction are frequently utilized to minimize topographical effects so that images represent concentration variations in the sample. This procedure may significantly increase the data acquisition time. Multivariate statistical methods can assist in resolving topographical and chemical information from multispectral XPS images. Principal component analysis (PCA) is one method for identification of the highest correlation/variation between the images. Topography, which is common to all of the images, will be resolved in the first most significant component. The score of this component contains spatial information about the topography of the surface, whereas the loading is a quantitative representation of the topography contribution to each elemental/chemical image. The simple‐to‐use self‐modelling mixture analysis (Simplisma) method is a pure variable method that searches for the source of most differences in the data and therefore has the potential to distinguish between chemical and topographical phases in images. The mathematical background correction scheme is developed and validated by comparing results to the experimental background correction for samples with differing degrees of topography. Copyright © 2004 John Wiley & Sons, Ltd.     

Widrow-cellular neural network and optoelectronic implementation

A new type of optoelectronic cellular neural network has been developed by providing the capability of coefficients adjusment of cellular neural network (CNN) using Widrow based perceptron learning algorithm. The new supervised cellular neural network is called Widrow-CNN. Despite the unsupervised CNN, the proposed learning algorithm allows to use the Widrow-CNN for various image processing applications easily. Also, the capability of CNN for image processing and feature extraction has been improved using basic joint transform correlation architecture. This hardware application presents high speed processing capability compared to digital applications. The optoelectronic Widrow-CNN has been tested for classic CNN feature extraction problems. It yields the best results even in case of hard feature extraction problems such as diagonal line detection and vertical line determination.     

激光水下扫描成像系统的图像修正机理

同步扫描系统可以克服后向散射，但同时也产生了两种非线性，一是扫描线速度的非线性，一是由于距离对光能衰减造成的非线性，两种非线性都需要修正，本文从原理上讨论水下激光成像时能量衰减的修正原理与修正方法，并给出仿真结果。     

试题质量评价研究

教学过程的规范化管理是保证教学质量的重要手段。考试是对教和学的效果的检验，是教学过程管理规范化必须要解决的问题，一直受到教学管理部门的重视，采取了多项措施解决有关问题，其中一个重要的手段是采用试题库。在采用试题库时，必须要有高质量的试题作保证。本探讨基于KDD技术的试题质量评价方法和指标，并通过实例来说明其有效性。     

数字全息中再现像分离问题的研究

详细分析了数字全息的再现像分离条件,指出数字全息和普通全息的再现像分离条件之间的区别,同时也讨论了再现条件对数字全息记录光路的要求,同时给出一种能部分避免再现像重叠的处理方法,并做出相应的实验验证.     

相对论二极管电子枪设计的分析解与实验的比较

本文对轴对称场二极管区电子运动所遵循的近似轨迹方程进行数值求解,以此做为设计相对论二极管电子枪的依据,与实验结果相比较,符合较好。     

神经网络在大型复杂武器装备质量综合评价排序中的应用

从大型复杂武器装备系统的具体特点出发,运用基于神经网络的评价方法,构建了大型复杂武器装备质量综合评价模型。实证分析的结果表明该方法得出的结果与实际情况相符。     

数码相机原理与系统设计研究

介绍了数码相机的工作原理 ,分析了数码相机的系统结构 ,提出了设计数码相机的处理流程。典型的数码相机系统有镜头、闪光灯、光学取景器、LCD显示屏、图像数据存储扩展设备接口、图像数据传输接口、供电系统以及核心处理器等八个主要模块。数码相机的数据流向从图像传感器开始 ,止于图像数据的存储和传输。数据流的处理主要包括模数转换、光学黑电平钳位、针对镜头的边缘畸变的运算修正、坏像素处理、白平衡处理、伽马校正、色彩合成处理、边缘检测 (锐度检测 )和伪彩色检测 (伪彩色抑制 )、JPEG压缩和图像存储器等模块