综合网管中基于模型驱动的元数据管理

提出了一种基于模型驱动的元数据管理方案．方案采用了基于模型的形式化描述方法，统一了专业网管子系统间的元数据模式；通过引入模型驱动技术，从元模型的抽象层次消除了不同专业网管子系统之间存在的“信息孤岛”；方案还对综合网管环境下的元数据理论和交换机制进行了研究，并给出了元数据的管理框架以及元数据交换的Java接口映射．     

Territories,corridors, and networks: A biological model for the premodern state

When depicted on maps as homogenous territorial wholes, ancient states are visually summarized as static entities in a way that conceals the highly fluid dynamics of polity formation, maintenance, and growth. Models derived from studies of animal behavior show that “territory” does not consist of an undifferentiated use of the landscape. Instead, the concept of territory can be parsed into a series of resource‐rich nodes linked by corridors of access, surrounded by unutilized regions and boundaries marked at points of competition. Ancient human groups also can be analyzed as having perceived and occupied landscapes through strategies of flexible networks in which nodes and corridors were surrounded by unutilized spaces around which boundaries were selectively identified and defended. This strategy is identifiable in human social groups at different levels of complexity ranging from hunter‐gatherers through ancient chiefdoms and states. © 2007 Wiley Periodicals, Inc. Complexity 12: 28–35, 2007     

A novel approach based on recurrent neural networks applied to nonlinear systems optimization

This paper presents an efficient approach based on recurrent neural network for solving nonlinear optimization. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The main advantage of the developed network is that it treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network.     

SPR棱镜传感器测量液体折射率的原理

推导了消失波函数的表达式,介绍了衰减全反射现象及SPR传感器测量液体折射率的原理,并利用SPR传感器测量了牛奶样品的反射系数及折射率与脂肪等主要成分含量的关系曲线.     

用于光纤电流传感器的BGO晶体磁光特性研究

在理论分析Bi4Ge3O12（BGO）晶体磁光特性的基础上，利用倍频法测量了不同工作波长下BGO晶体的费尔德常量，获得了与理论相符的实验结果.同时根据BGO晶体费尔德常量随波长的变化关系曲线，通过对该晶体吸收系数的测量，得出了其磁光优值曲线.进而将BGO晶体的磁光特性与光纤电流传感器常用的几种磁光材料作了对比，结果表明BGO晶体适合用于光纤电流传感器.     

电控发动机喷油脉宽的分析

本文介绍了利用喷油脉宽大小的变化来分析电控发动机电控系统、燃油供给等系统故障的一种方法,在汽车故障检测与诊断中有着广泛的应用。     

环形光纤声发射传感器的相位调制特性研究

提出了一种基于光纤Sagnac干涉仪的环形传感器，用于固体表面传播的超声波的检测.这种传感器的特点是能够精确地检测由固体表面传播的超声波产生的微弱振动.当超声波信号通过光纤传感器的两个臂到达探测器时，干涉仪的输出光强度受到了超声信号的调制.通过检测干涉仪的输出光强度并利用Fourier变换，测得了超声信号的振幅和频率.而且对传感系统的位相调制特性进行了仿真，并对实验结果进行了分析，结果表明该系统可用于固体表面传播的超声波频率特征的识别.     

关于环网G（N;S1,S2）的直径

本文首先给出了环网G(N;s_1,s_2)存在有限直径的充要条件;用初等数论方法给出了其直径的简明计算公式;最后讨论了类似文献[3]的环网直径的对偶性问题.     

Characterization of spherical particles using high-order neural networks and scanning flow cytometry

We retrieve the radius R, real n and imaginary k parts of the refractive index of homogeneous spherical particles using angular distribution of the light-scattering intensity. To solve the inverse light-scattering problem we use a high-order neural-network technique. The effect of network parameters on optimization is examined. The technique is evaluated for noise-corrupted input data at 0.6 μm<R<10.6 μm, 1.02<n<1.38, and 0<k<0.03. The errors of retrieval for nonabsorbing particles do not exceed 0.05 μm for radius and 0.015 for refractive index. The experimental verification is fulfilled by experimental data retrieved by means of a scanning flow cytometer. The light-scattering profiles of polystyrene beads and spherized red blood cells are processed with the high-order neural networks and a non-linear regression at Mie theory. The parameters retrieved by the high-order neural networks correlate well with the parameters retrieved by the least-square method.     

D形光纤Bragg光栅弯曲灵敏度的理论和实验研究

用材料力学理论分析了D形光纤Bragg光栅（D-shaped fiber Bragg grating,D-FBG）以及常规光纤Bragg光栅由弯曲引起的轴向应变,得到了光栅Bragg波长漂移的弯曲敏感特性.实验结果和理论计算结果基本相符.与常规FBG相比,该D-FBG的弯曲灵敏度要高近80倍.因此D-FBG可以直接应用于弯曲形变的测量,以及间接应用于压力、加速度等物理量的测量.理论分析和实验结果对采用该类型光纤光栅的器件和传感系统的设计具有参考意义.