超材料吸波器的极化特性研究进展

超材料由于具有吸波特性而引起了人们的极大兴趣.简要介绍了超材料产生吸波的原理,并着重阐述了吸波超材料在微波段、光波段以及太赫兹波段的极化特性和相应超材料吸波器结构的模拟及实验研究进展.这种超材料的吸波特性在军事和民用上具有潜在的应用价值.     

基于Timoshenko梁理论的回传射线矩阵法在传感器优化布置中的应用研究

由于结构存在阻尼现象,弹性波在传播过程中信号强度必然会随传播距离而衰减.据此提出弹性波极限传播距离与传感器极限布置间距概念,考虑到在高频率处剪切变形引起的转动惯量对结构动力特性的影响比较大,基于Timoshenko梁理论,结合经典回传射线矩阵法,提出使用局部散射矩阵确定结构损伤检测中的传感器布置极限间距,并将其应用到传感器优化算法中.针对指定检测系统,以桥梁结构Benchmark模型为例,验证算法的有效性.     

叠加Y环单元频率选择表面的设计

对Y环单元进行改造得到了叠加Y环单元图形,以延迟频率选择表面(FSS)的高次谐振,实现无干扰的单通带滤波器.运用谱域法分析得到的叠加Y环单元,并与Y环单元进行对比,分别讨论其角度稳定性、极化稳定性、-3 dB带宽和高次谐振点.分析表明:当中心频点同为17.6 GHz时,叠加Y环单元具有更窄的带宽,而高次谐波向后延迟6....     

浅谈非独立法人的实验室——与组织之间资源共享

越来越多的企业组织内部检测实验室申请CNAS认证,而检测实验室与其所属组织存在很多的软件硬件资源的共用,实验室如何做到既与组织有效共享资源又能确保公正独立.该文对此进行了科学分析,依据<检测和校准实验室能力认可准则>的相关影响要素进行识别,并且提出了客观抖学的处理方法,对非独立法人的实验室管理有着实用的指导意义.     

职业教育视野下的当代建筑理论教学

以当代建筑历史与理论教学的转型为背景,以英国建筑联盟学院1～5年级历史与理论课程的分析为线索,展开对建筑理论学习在职业教育中所承担角色这一问题的思考,并提出与知识学习不同的新的观念—思维方式的训练和独立视野的形成。     

贝叶斯网络结构学习研究

针对贝叶斯网络结构学习方法难以兼顾高准确率和高效率的问题,提出了一种基于Markov Chain Monte Carlo(MCMC)方法的贝叶斯网络结构学习方法的改进.改进包括:使用依赖关系分析,利用统计学的方法对采样空间进行大幅缩减,能够在精确控制准确度的情况下大幅提高时间效率;结合先验知识,从理论角度将先验知识融入评分中得到完全服从后验分布的结果;搜索最优子结构,对于特定的一些结构搜索最优子结构而不是采用贪心的方法,提高了贝叶斯网络结构学习的准确率.通过理论分析可以证明时间复杂度得到了大幅的降低.并且可以在牺牲可预知的准确率的情况下,将指数时间复杂度降为线性时间.大量的数据实验表明,经改进后的方法在时间和准确性上都具有良好的表现.     

Provably good pattern generators for a random pattern test

This paper describes a pseudorandom pattern generator for the random pattern test of combinational circuits. Suppose that a fractionp of the possible patterns detects some fault and the generator generates L patterns to test the circuit. Then the probability that the generator generates a pattern that tests the fault is at leastpL/(pL + 1). The only assumption is that all values of the seed of the generator are equally likely. The seed is twice as long as a single pattern. The generator is less than twice as expensive as a linear feedback shift register. Thus, it can be used in practice. More complicated generators that achieve a better bound are also discussed.This research was supported in part by the National Science Foundation under Grants CCR-8810609 and CDA-8805910.     

Graphoid properties of epistemic irrelevance and independence

This paper investigates Walley's concepts of epistemic irrelevance and epistemic independence for imprecise probability models. We study the mathematical properties of irrelevance and independence, and their relation to the graphoid axioms. Examples are given to show that epistemic irrelevance can violate the symmetry, contraction and intersection axioms, that epistemic independence can violate contraction and intersection, and that this accords with informal notions of irrelevance and independence.     

Epistemic irrelevance on sets of desirable gambles

This paper studies graphoid properties for epistemic irrelevance in sets of desirable gambles. For that aim, the basic operations of conditioning and marginalization are expressed in terms of variables. Then, it is shown that epistemic irrelevance is an asymmetric graphoid. The intersection property is verified in probability theory when the global probability distribution is positive in all the values. Here it is always verified due to the handling of zero probabilities in sets of gambles. An asymmetrical D-separation principle is also presented, by which this type of independence relationships can be represented in directed acyclic graphs.     

Diagnostic Checking in a Flexible Nonlinear Time Series Model

This paper considers a sequence of misspecification tests for a flexible nonlinear time series model. The model is a generalization of both the smooth transition autoregressive (STAR) and the autoregressive artificial neural network (AR-ANN) models. The tests are Lagrange multiplier (LM) type tests of parameter constancy against the alternative of smoothly changing ones, of serial independence, and of constant variance of the error term against the hypothesis that the variance changes smoothly between regimes. The small sample behaviour of the proposed tests is evaluated by a Monte-Carlo study and the results show that the tests have size close to the nominal one and a good power.