慢性萎缩性胃炎与正常胃活检组织RNA分布的研究

采用异硫氰酸荧光素（FITC）标记的核糖核酸酶（FITC－RNase）作为探针，结合半薄切片技术，观察了慢性萎缩性胃炎与正常胃活检组织中RNA的分布变化，结果表明：慢性萎缩性胃啖腺体细胞内RNA明显减少，分布部位与正常胃腺体细胞差异较大，这些结果于慢性萎缩性胃炎的病理诊断提供了一些依据，对进一步从分子水平上研究慢性萎缩性胃炎的病理变化及其与胃癌的关系具有一定的意义。     

ANALYSIS OF REGIONAL ECONOMY GROWTH WITH THE THEORY OF DIFFERENTIAL SYSTEM DYNAMICS

In order to describe the interrelation forces among different regions during the economic growth, this paper introduces and analyzes the dynamical system model with the theory of differential systems dynamics. A practical example based on a simplified model is given to analyze the dynamical process of Sichuan economy growth.     

基于强跟踪滤波器估计的最优融合方法

在分布式雷达数据处理模式中 ,数据融合是获得较精确的目标轨迹的主要环节。为克服卡尔曼滤波器对初始值敏感、鲁棒性差和对机动目标跟踪性能差的缺陷 ,通过利用各传感器的观测数据 ,采用强跟踪滤波器对目标进行跟踪 ,以改善目标状态估计的精度。对判定源于同一目标的状态估计值 ,给出了一种估计状态线进行性组合的最优融合准则。得出了实际数据的实验结果。     

Radar Imaging Based on Iterative Algorithms

It has long been realized that the problem of radar imaging is a special case of image reconstruction in which the data are incomplete and noisy. In other fields, iterative reconstruction algorithms have been used successfully to improve the image quality. This paper studies the application of iterative algorithms in radar imaging. A discrete model is first derived, and the iterative algorithms are then adapted to radar imaging. Although such algorithms are usually time consuming, this paper shows that, if the algorithms are appropriately simplified, it is possible to realize them even in real time. The efficiency of iterative algorithms is shown through computer simulations.     

反应条件及添加惰性物质对三聚甲醛合成反应的影响

研究了三聚甲醛合成过程进料浓度、催化剂用量等对副产物（特别是甲酸）生成行为的影响。结果表明，该体系副产物的生成强烈地依赖于反应时间和催化剂硫酸的用量，而与原料浓度的波动无关。在反应－精馏过程的反应器中添加惰性高沸有机物，可有效地缩短反应物的停留时间，提高三聚甲酸的选择性，大大降低快速反应－精馏过程对反应器的设计要求。     

大型喷浆机器人的灵巧度分析

灵巧度是衡量机器人运动失真程度的重要参数。对机器人灵巧度评价指标进行了对比研究 ,结合大型喷浆机器人自由度较多的特点 ,用雅可比矩阵的条件数对喷浆机器人的灵巧度进行了分析。结果表明 ,大型喷浆机器人在不同形位下的条件数都很小 ,具有较好的运动灵巧度。     

服装定价的特殊性与双价值模型

通过对服装价格影响因子及服装价格决策特殊性的分析，建立以认知价值和使用价值为基础，以品牌、质量和季节转换等因子为权重调节系数的服装双价值模型。     

SCHEDULING PROBLEMS - AN OVERVIEW

There seems to be a significant gap between the theoretical and the practical aspects of scheduling problems in the job shop environment. Theoretically, scheduling systems are designed on the basis of an optimum approach to the scheduling model. However in the practice, the optimum that is built into the scheduling applications seems to face some challenges when dealing with the dynamic character of a scheduling system, for instance machine breakdown or change of orders. Scheduling systems have become quite complex in the past few years. Competitive business environments and shorter product life cycles are the imminent challenges being faced by many companies these days. These challenges push companies to anticipate a demand driven supply chain in their business environment. A demand-driven supply chain incorporates the customer view into the supply chain processes. As a consequence of this, scheduling as a core process of the demand-driven supply chain must also reflect the customer view. In addition,     

Face Recognition Based on Support Vector Machine and Nearest Neighbor Classifier

Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with the nearest neighbor classifier (NNC) is proposed. The principal component analysis (PCA) is used to reduce the dimension and extract features. Then one-against-all stratedy is used to train the SVM classifiers. At the testing stage, we propose an al-