Spring框架对数据持久化的支持与实现

O/R Mapping技术有效地解决了数据持久化问题.Spring框架支持ORM技术,它的SpringDAO和Spring ORM功能提供了对Hibernate框架的深入支持.通过XML配置文件描述Bean对象及其依赖关系,Spring利用IoC容器实现了Bean的装配与控制;同时通过建立POJO映射形成了ORM的体系结构.掌握基于Bean容器的开发模式,使控制层、逻辑层及数据层实现充分解耦,是Spring开发工作的核心.     

自乳化水性环氧防腐涂料乳液的探索研究

通过相转化法,用磷酸和丙烯酸及其酯类单体对环氧树脂进行改性,得到了一种性能优良的自乳化水性环氧防腐涂料乳液,主要用于容器内壁的防护装饰。     

新滩油包水型稠油加剂降粘效果及微观分析

胜利新滩油田的油包水(W/O)型稠油的常温粘度高、流动性差、集输能耗大,必须对其进行降粘处理,否则难以集输.基于新滩W/O型稠油加剂后的降粘效果与稳定性,采用复配技术研制其反相降粘剂VRKD18.该剂为两种非离子表面活性剂的复合体系,其使用与储存方便,对新滩W/O型稠油的降粘效果显著,可使其50℃51 s-1下的表观粘度由7 000～11 000 mpa·s降到100mpa·s以下.采用影像分析技术,观测与分析新滩W/O型稠油的加剂反相过程、微观结构及液滴粒径分布,进而探讨其降粘机理.结果表明,新滩W/O型稠油在VRKD18剂作用下可自发反相,其粘度降低主要是由于VRKD18剂改变了其内外相结构、分散液滴相互作用的大小及方式,这为其集输工艺的更新奠定了基础.     

SG32525芯片在开关(逆变)电源中的应用

在研制开关电源和后备式UPS(不间断电源)的工程实践中,为提高其转换效率,减少外围元器件,减小体积,并提高长时间工作的可靠性与PWM(脉宽调制)的控制精度,对新型PWM集成芯片SG3525的功能特点、控制特性及外围电路进行了研究。讨论了该芯片在UPS逆变电源和开关稳压电源中的应用,利用该芯片设计并制作了高效率的开关电源与UPS逆变电源。     

一类特殊循环矩阵的求逆

求逆矩阵通常的方法是初等变换法或伴随矩阵法，计算量大且容易出错，本文利用循环矩阵的特殊性质给出了一类特殊循环矩阵求逆的计算公式，简化了一类特殊循环矩阵求逆的计算。     

基于抛物线拉东变换的地震道重构

研究了一种基于抛物线拉东变换(PRT)的地震道外推和内插方法，该方法根据部分NMO校正后的CMP(Common Middle Point，共中心点)道集中地震同相轴的抛物线假设，在待重建道的位置用零值道代替，然后采用迭代方式，通过带限抛物线拉东正变换和最小平方抛物线拉东反变换进行数据重构．结果表明，该方法可用于叠前道集中缺失道的重建、外推、内插以及数据重采样和数据规则化等方面．模型数据和实际数据应用还表明本方法是有效的和稳健的，它不需要精确的NMO速度，具有很强的抗噪能力，且能进行中间偏移距道和远偏移距道的处理，对于多次波的消除、AVO分析、DMO处理和某些三维叠前偏移成像方法都将是有益的．     

Query based model learning and stable tracking of a robot arm using radial basis function network

In the context of a robot manipulator, a generalized neural emulator over the complete workspace is very difficult to obtain because of dimensionally insufficient training data. A query based learning algorithm is proposed in this paper that can generate new examples where control inputs are independent of states of the system. This algorithm is centered around the concept of network inversion using an extended Kalman filtering based algorithm. This is a novel idea since robot manipulator is an open loop unstable system and generation of control input independent of state is a research issue for neural model identification. Two trajectory independent stable control schemes have been designed using the neural emulator. One of the control schemes uses forward-inverse-modeling approach to update the controller parameters adaptively following Lyapunov function synthesis technique. The proposed scheme is trajectory independent unlike the back-propagation scheme. The second type of controller predicts the minimum variance estimate of control action using recall process (network inversion) and the control law is derived following a Lyapunov function synthesis approach so that the closed loop system consisting of controller and neural emulator remains stable. The simulation experiments show that the model validation approach is efficient and the proposed control schemes guarantee stable accurate tracking.     

20KHZ IGBT PWM 型高效大功率超声波发生器

本文论述２０ＫＨＺＰＷＭ（脉冲宽度调制）型大功率超声波发生器的原理和电路组成。ＰＷＭ信号是由性能优越的ＴＬ４９４集成电路产生，高频逆变器采用国际先进的磁性材料和ＩＧＢＴ功率器件构成。逆变器将输出的高频电压送入超声波换能器，从而辐射出超声波。该系统具有电路简单，工作可靠，体积小，成本低，输出功率调节方便，效率高，实用性强等特点。     

n阶方阵求逆的两个公式

针对ｎ阶方阵的逆阵问题，分别利用矩阵乘积及正交化方法给出了求Ａ＾－１的两个表达式，从而达到运算量小且实用之目的。     

Numerical inversion of multidimensional Laplace transforms by the Laguerre method

Numerical transform inversion can be useful to solve stochastic models arising in the performance evaluation of telecommunications and computer systems. We contribute to this technique in this paper by extending our recently developed variant of the Laguerre method for numerically inverting Laplace transforms to multidimensional Laplace transforms. An important application of multidimensional inversion is to calculate time-dependent performance measures of stochastic systems. Key features of our new algorithm are: (1) an efficient FFT-based extension of our previously developed variant of the Fourierseries method to calculate the coefficients of the multidimensional Laguerre generating function, and (2) systematic methods for scaling to accelerate convergence of infinite series, using Wynn's ε-algorithm and exploiting geometric decay rates of Laguerre coefficients. These features greatly speed up the algorithm while controlling errors. We illustrate the effectiveness of our algorithm through numerical examples. For many problems, hundreds of function evaluations can be computed in just a few seconds.