Aggregate‐induced emission in light‐emitting liquid crystal display technology

Nowadays, liquid crystal displays (LCDs) with light‐emission are considered as energy‐efficient devices and are promising alternatives to conventional LCDs. To realize such possibility, strong fluorescent materials with a dichroic properties are required. Aggregate‐induced emission (AIE) is an unusual photophysical phenomenon shown by some luminogenic materials that will be highly emissive in their aggregate state. In this work, we studied the AIE effect of a luminescent liquid crystalline molecule TPE‐PPE in our LC system as a luminophore dopant. The result showed the excellent AIE effect that higher concentration of luminogen in the nematic LC host induced stronger luminescent intensity. Through exposure of a photoisomeriable alignment material sulfonic‐dye‐1, the photopatterning of a light‐emitting LC device was achieved with the use of the TPE‐PPE/nematic LC mixture.     

瓦斯地质动态分析及瓦斯涌出实时预警系统

为了防止煤与瓦斯突出事故,提高矿井的安全保障能力,结合新元公司实际情况,建立了瓦斯地质动态分析及瓦斯涌出实时预警系统。在统计和分析该公司矿井瓦斯地质相关资料的基础上,创建了瓦斯地质空间数据库,采用动态分析技术筛选出了影响瓦斯赋存的主控因素,自动绘制了瓦斯参数等值线并划分出突出危险区。对突出危险区内的工作面进行重点关注,考察其瓦斯涌出特征及预警指标,并与瓦斯监测系统无缝连接,实现了非接触式连续预警。     

声发射技术在地压监测中的应用

对某矿的采空区围岩试样进行了单轴压缩声发射实验,得到了岩石破坏时能率、事件率等声发射参数值,根据这些数值对声发射监测系统参数进行了设置;通过对声发射监测系统长期运行结果的统计,总结出了井下多种活动即岩石声发射、打钻、爆破、人工破碎大块矿石、放矿、敲击的波形及各类波形的参数范围;确定了以能率、事件率为特征的采空区失稳判据,为判断地压灾害提供了可靠依据。     

分数阶区间系统的鲁棒稳定性分析

由于实际的物理系统常会存在各种不确定结构,这些不确定结构给系统的稳定性分析带来了困难和一定的影响,因此对这类带有不确定结构的分数阶系统控制问题的研究,具有广泛的实际应用意义。本文主要针对带有区间不确定性的分数阶控制系统,分析了该系统的鲁棒稳定性问题,首先将区间矩阵用分式线性变换(LFT)表示,然后基于分析得出了此类系统鲁棒稳定的充分必要条件。并给出两个数值算例阐释该方法,仿真结果表明了该方法的有效性。     

基于加载宏的线性规划问题求解

线性规划是运筹学的重要分支,应用十分广泛。本文介绍利用加载宏解决线性规划优化问题求解的详细方法和步骤。该方法可以减少求解线性规划问题的计算量,提高计算速度,并且方便实用。     

Robust fuzzy stabilization of dithered chaotic systems using island-based random optimization algorithm

Applying dither to highly nonlinear systems may suppress chaotic phenomena, but dynamic performance, such as convergence rate and disturbance attenuation, is usually not guaranteed. This paper presents a dithered H_∞ robust fuzzy control scheme to stabilize chaotic systems that ensures disturbance attenuation bounds. In the proposed scheme, Takagi-Sugeno (T-S) fuzzy linear models are used to describe the relaxed models of the dithered chaotic system, and fuzzy controllers are designed based on an extension to the concept of parallel distributed compensation (PDC). Sufficient condition for the existence of the H_∞ robust fuzzy controllers is presented in terms of a novel linear matrix inequalities (LMI) form which takes full consideration of modeling error and disturbances, but cannot be solved by the standard procedures. In order to solve the LMI problem and to identify the chaotic systems as T-S fuzzy modes, we propose a compound optimization strategy called the island-based random-walk algorithm (IRA). The algorithm is composed of a set of communicating random-walk optimization procedures concatenated with the down-hill simplex method. The design procedure and validity of the proposed scheme is demonstrated via numerical simulation of the dithered fuzzy control of a chaotic system.     

Software testing processes as a linear dynamic system

Software testing is essential for software reliability improvement and assurance, and the processes of software testing are intrinsically dynamic. However they are seldom investigated in a mathematically rigorous manner. In this paper a theoretical study is presented to examine the dynamic behavior of software testing. More specifically, a set of simplifying assumptions is adopted to formulate and quantify the software testing processes. The mathematical formulae for the expected number of observed software failures are rigorously derived, the bounds and trends of the expected number of observed software failures are analyzed, and the variance of the number of observed software failures is examined. On the other hand, it is demonstrated that under the simplifying assumptions, the software testing processes can be treated as a linear dynamic system. This suggests that the software testing processes could be classified as linear or non-linear, and there be intrinsic link between software testing and system dynamics.     

1D correlation filter based class-dependence feature analysis for face recognition

In this paper, a novel one-dimensional correlation filter based class-dependence feature analysis (1D-CFA) method is presented for robust face recognition. Compared with original CFA that works in the two dimensional (2D) image space, 1D-CFA encodes the image data as vectors. In 1D-CFA, a new correlation filter called optimal extra-class origin output tradeoff filter (OEOTF), which is designed in the low-dimensional principal component analysis (PCA) subspace, is proposed for effective feature extraction. Experimental results on benchmark face databases, such as FERET, AR, and FRGC, show that OEOTF based 1D-CFA consistently outperforms other state-of-the-art face recognition methods. This demonstrates the effectiveness and robustness of the novel method.     

CPU demand for web serving: Measurement analysis and dynamic estimation

Managing the resources in a large Web serving system requires knowledge of the resource needs for service requests of various types. In order to investigate the properties of Web traffic and its demand, we collected measurements of throughput and CPU utilization and performed some data analyses. First, we present our findings in relation to the time-varying nature of the traffic, the skewness of traffic intensity among the various types of requests, the correlation among traffic streams, and other system-related phenomena. Then, given such nature of web traffic, we devise and implement an on-line method for the dynamic estimation of CPU demand.

Assessing resource needs is commonly performed using techniques such as off-line profiling, application instrumentation, and kernel-based instrumentation. Little attention has been given to the dynamic estimation of dynamic resource needs, relying only on external and high-level measurements such as overall resource utilization and request rates. We consider the problem of dynamically estimating dynamic CPU demands of multiple kinds of requests using CPU utilization and throughput measurements. We formulate the problem as a multivariate linear regression problem and obtain its basic solution. However, as our measurement data analysis indicates, one is faced with issues such as insignificant flows, collinear flows, space and temporal variations, and background noise. In order to deal with such issues, we present several mechanisms such as data aging, flow rejection, flow combining, noise reduction, and smoothing. We implemented these techniques in a Work Profiler component that we delivered as part of a broader system management product. We present experimental results from using this component in scenarios inspired by real-world usage of that product.     

A new vertex result for robustness problems with interval matrix uncertainty

This paper¹ addresses a family of robustness problems in which the system under consideration is affected by interval matrix uncertainty. The main contribution of the paper is a new vertex result that drastically reduces the number of extreme realizations required to check robust feasibility. This vertex result allows one to solve, in a deterministic way and without introducing conservatism, the corresponding robustness problem for small and medium size problems. For example, consider quadratic stability of an autonomous n_x dimensional system. In this case, instead of checking vertices, we show that it suffices to check 2^2n_x specially constructed systems. This solution is still exponential, but this is not surprising because the problem is NP-hard. Finally, vertex extensions to multiaffine interval families and some sufficient conditions (in LMI form) for robust feasibility are presented. Some illustrative examples are also given.