高分辨率合成孔径雷达图像舰船检测方法

寻找针对高分辨率SAR图像的舰船目标检测算法。利用KSW双阈值分割技术，其效果比传统检测方法好，有利于进一步的目标分类和识别。且必须根据SAR图像分辨率来选择舰船检测算法。     

Protein Extraction from Heat-stabilized Defatted Rice Bran: II. The Role of Amylase, Celluclast, and Viscozyme

ABSTRACT: The effectiveness of 3 carbohydrases for protein extraction from heat-stabilized defatted rice bran (HDRB) was evaluated. Amylase, viscozyme and celluclast extracted a maximum of 45.4, 12.1, and 28.5% protein, respectively. Further study showed that extracted protein ranged from 9.5 to 58.4% under conditions of water to bran ratio (5:1 to 20:1), α-amylase (0 to 110000 units/10 g rice bran), temperature (35 to 55 °C), and time (1 to 8 h). The maximum protein extracted was 58.4% with a water to bran ratio of 17:1, 87637 units amylase, and 50.9 °C. These results suggest that impure food-grade amylase containing protease is more effective than celluclast and viscozyme in protein extraction from HDRB.     

Kernel Spectral Matched Filter for Hyperspectral Imagery

In this paper a kernel-based nonlinear spectral matched filter is introduced for target detection in hyperspectral imagery, which is implemented by using the ideas in kernel-based learning theory. A spectral matched filter is defined in a feature space of high dimensionality, which is implicitly generated by a nonlinear mapping associated with a kernel function. A kernel version of the matched filter is derived by expressing the spectral matched filter in terms of the vector dot products form and replacing each dot product with a kernel function using the so called kernel trick property of the Mercer kernels. The proposed kernel spectral matched filter is equivalent to a nonlinear matched filter in the original input space, which is capable of generating nonlinear decision boundaries. The kernel version of the linear spectral matched filter is implemented and simulation results on hyperspectral imagery show that the kernel spectral matched filter outperforms the conventional linear matched filter.     

基于ANN的声目标识别系统及其DSP实时实现

介绍了一种基于人工神经网络(ANN)的声目标识别系统,概述了用MATLAB专用工具箱对神经网络权值进行训练及仿真的过程,叙述了ANN目标识别系统的数字信号处理器(DSP)实时实现过程,并着重分析定点实现过程中程序变量的定标、非线性运算的实现、溢出的处理等关键步骤.对不同字长的识别结果进行比较表明,基于定点实时实现的系统数据保持很高的精度,可以得到与浮点处理相同的识别率.     

芳烃抽提装置技术改造

由于中国石化锦西石化分公司600kt／a连续重整装置的建设，芳烃抽提装置的原料由原来的脱戊烷油变为Ce组分。为此，对抽余油水洗塔和芳烃分离部分的苯塔塔盘，以及苯塔塔顶和塔底抽出部分进行了改造，更换部分机泵和增加变频泵，并将常规仪表改为DCS控制。改造后装置实现一次开车成功，生产出合格产品。抽余油中总芳烃含量小于0．1％，苯回收率达到99%以上。     

石油渣油制备针状焦研究--中间馏分热反应研究

石油渣油的组成复杂,分子量分布宽,直接焦化不能生产针状焦。采用一定的预处理技术将渣油中适宜制备针状焦的组分保留,可获得理想的焦化原料。通过以辽河减压渣油为原料,经溶剂萃取对渣油进行"掐头去尾"处理,获得了分子量分布窄、杂质含量少的中间馏分A及馏分B。对馏分A、B分别进行热反应研究,结果表明:渣油的预处理效果明显,中间馏分热反应产物具有光学各向异性物含量高、取向性好等特点,是制备针状焦的理想原料。     

金的分离富集

综述了金的分离和富集方法，主要包括各种吸附和萃取方法。采用活性炭和泡沫塑料(简称泡塑)吸附分离金是传统的分离富集法，有负载活性炭和有负载泡塑可以提高富集金的能力。近些年，离子交换树脂和离子交换纤维素在分离富集金的应用中，占有相当大的比例。萃取法除了使用传统的MIBK作为萃取剂，又见报道硫醚、亚砜、醇类等作为萃取剂的各种萃取体系。中引用参考献107篇。     

矿石中金的快速测定

研究了活性炭纤维滤布富集分离的条件和解脱方法,并利用微波溶样、液珠萃取比色法测定矿石中的金。该方法的测定范围为(0.5~xx)×10-6,相对标准偏差RSD为3.2%,可用于矿石中金的野外快速测定。     

用Promax处理LD22-l“模糊带”地震资料

通过LD22-l构造地震资料目标处理,搞清了“模糊带”,引进交互处理系统是成功的.     

眼球的自动定位

提出了一种由粗到细自动定位人脸的一个重要特征即眼球圆心的方法，该方法综合运用局部二值化，霍夫变换，像纱聚类，边缘提取等技术，对均匀或非均匀光照下拍摄或戴眼镜的照片都能获得很高的定位精度，适用于处理证件照。