Investigation of performance variations due to the amplitude of group-delay ripple in chirped fiber Bragg gratings

We measure the system impacts due to the amplitude of group-delay (GD) ripple in single and cascaded chirped fiber Bragg gratings (CFBGs). Signals with smaller pulse width result in smaller performance variation at the same data rate. A 65-ps peak-to-peak GD ripple induces 0.9, 1.7, and 2.7 dB maximum penalties for 10, 20, and 40-Gb/s, respectively. We also find that cascading gratings with random ripple causes much less degradation than cascading gratings with the same ripple profile.     

3D polymeric microfluidic device fabrication via contact liquid photolithographic polymerization (CLiPP)

In this contribution, a new method for the fabrication of complex polymeric microfluidic devices is presented. The technology, contact liquid photolithographic polymerization (CLiPP), overcomes many of the drawbacks associated with other rapid prototyping schemes, such as limited materials choices and time-consuming microassembly protocols. CLiPP shares many traits with other photolithographic methods, but three distinct features: (i) liquid photoresists in contact with the photomask, (ii) readily removed sacrificial materials, and (iii) living radical processes, enable multiple polymeric chemistries and mechanical properties while simultaneously enabling facile fabrication of 3D geometries and surface chemistry control. This contribution details fabrication techniques and methods for the fabrication of high aspect ratio posts covalently bonded to a polymeric substrate, an array of independently stacked bars on top of perpendicular bars, multiple undercut structures fabricated simultaneously, and a complex 3D geometry with intertwined channels.     

Bayesian and Dempster-Shafer fusion

The Kalman Filter is traditionally viewed as a prediction-correction filtering algorithm. In this work we show that it can be viewed as a Bayesian fusion algorithm and derive it using Bayesian arguments. We begin with an outline of Bayes theory, using it to discuss well-known quantities such as priors, likelihood and posteriors, and we provide the basic Bayesian fusion equation. We derive the Kalman Filter from this equation using a novel method to evaluate the Chapman-Kolmogorov prediction integral. We then use the theory to fuse data from multiple sensors. Vying with this approach is the Dempster-Shafer theory, which deals with measures of “belief”, and is based on the nonclassical idea of “mass” as opposed to probability. Although these two measures look very similar, there are some differences. We point them out through outlining the ideas of the Dempster-Shafer theory and presenting the basic Dempster-Shafer fusion equation. Finally we compare the two methods, and discuss the relative merits and demerits using an illustrative example.     

A new approach for constructing the concept map

In recent years, e-learning system has become more and more popular and many adaptive learning environments have been proposed to offer learners customized courses in accordance with their aptitudes and learning results. For achieving the adaptive learning, a predefined concept map of a course is often used to provide adaptive learning guidance for learners. However, it is difficult and time consuming to create the concept map of a course. Thus, how to automatically create a concept map of a course becomes an interesting issue. In this paper, we propose a Two-Phase Concept Map Construction (TP-CMC) approach to automatically construct the concept map by learners’ historical testing records. Phase 1 is used to preprocess the testing records; i.e., transform the numeric grade data, refine the testing records, and mine the association rules from input data. Phase 2 is used to transform the mined association rules into prerequisite relationships among learning concepts for creating the concept map. Therefore, in Phase 1, we apply Fuzzy Set Theory to transform the numeric testing records of learners into symbolic data, apply Education Theory to further refine it, and apply Data Mining approach to find its grade fuzzy association rules. Then, in Phase 2, based upon our observation in real learning situation, we use multiple rule types to further analyze the mined rules and then propose a heuristic algorithm to automatically construct the concept map. Finally, the Redundancy and Circularity of the concept map constructed are also discussed. Moreover, we also develop a prototype system of TP-CMC and then use the real testing records of students in junior high school to evaluate the results. The experimental results show that our proposed approach is workable.     

High mobility,low voltage polymer transistor

We introduce a polymer transistor that operates with low supply voltage and yet has a field-effect mobility higher than the mobilities reported for low voltage polymer transistors. A simple plasma oxidation of the gate metal to form a thin (3.74 nm) top metal oxide layer in the gate metal is involved in the fabrication that acts as the gate dielectric. With ultrathin gate dielectrics, the variation in the dielectric thickness and the surface roughness scattering can severely limit the mobility attainable. The plasma oxidation under certain conditions produces a very smooth oxide surface, leading to the high mobility.     

Radio resource management for a mobile network with TD-CDMA

In the paper, we proposed a resource allocation method employing maximal compatible cliques to make use of channel bandwidth as efficiently as possible in a TD-CDMA system. Furthermore, the strength of beacon signals was also measured to decide whether or not to reserve resources for hand-off users, in order to reduce their dropping probabilities. Finally, we conducted several experiments to validate that our method could make use of the finite resources efficiently, thereby revealing better blocking probabilities and dropping probabilities than other methods.     

双MCU架构航标监控终端的研制

针对航标监控终端对低功耗、高可靠性的要求,采用双MCU架构设计.在软件系统中建立多任务消息机制,引入时限服务策略对任务的运行时间进行约束,只需定时器和少量资源,提高了软件的可靠性.实际应用表明,该终端的性能指标完全满足设计要求.     

Monitoring unit root and multiple structural changes: An information criterion approach

An information criterion-based model selection method is proposed for monitoring unit root and multiple structural changes. In this method, a battery of possible models is considered by changing the integration order (I(0) or I(1)) and the combinations of change points. Next, the best model is selected from among alternative models via a modified Bayesian information criterion (BIC). Accordingly, on the basis of the selected model, the process that generates the observed time series is determined. The BIC is modified in order to adjust the frequency count of incorrectly selecting stationary models via the conventional BIC. The simulation results of monitoring unit root and structural change suggest that the proposed method outperforms the conventional hypothesis testing method in terms of detection accuracy and detection speed. Furthermore, the empirical results suggest that the proposed method exhibits better performances with regard to detection stability and forecastability.     

脉冲噪声环境下宽带循环平稳信号DOA估计算法

针对传统二阶循环相关算法在脉冲噪声环境中的显著退化问题,本文以α稳定分布为噪声模型,提出基于分数低阶循环相关的波达方向(Direction of arrival,DOA)估计算法。利用分数低阶循环相关的相移特性,将宽带循环平稳信号的DOA估计问题转化为"中心频率"为ε的窄带问题,解决了宽带情况下DOA估计困难的问题。计算机仿真结果进一步验证了此算法的有效性,且性能优于传统SC-SSF(Spectral correlation signal subspacefitting)算法。     

基于动态特性描述的变量加权型分散式故障检测方法

现代工业生产过程往往具有复杂的动态特性: 不同测量变量间会存在不同的时序相关性, 且变量间的相互影响会反映在不同的采样时刻上. 现有的动态过程监测模型往往不能充分挖掘变量间的动态特性, 其故障检测效果也有待进一步提高. 在此背景下, 本文提出一种基于动态特性描述的变量加权型分散式故障检测方法. 利用最大相关最小冗余(Minimal redundancy maximal relevance, mRMR) 算法更准确地描述动态过程变量间的相关性关系, 并利用该相关性的值对原始增广矩阵进行加权处理, 且不同延迟变量对当前测量值的影响大小就通过权值来体现, 因此能更加全面地刻画该测量值的动态特性. 最后建立一种融合mRMR算法, 贝叶斯推理以及动态主成分分析(Dynamic principal componemt amalysis, DPCA)模型的新的分布式建模策略, 提高了模型的容错能力和泛化能力, 取得了更好的故障检测结果.