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.     

User Preference for a Control-Based Reduced Processing Decision Support Interface

This study examined trainee crime-scene investigators' preference for, and accuracy in using, four different computer-based decision support interface designs, each of which incorporated a different reduced processing information acquisition strategy. The interfaces differed on the basis of the number of options that could be considered simultaneously and the level of control that could be exercised over the number and sequence in which feature values were accessed. Forty trainee investigators completed six decision scenarios in which they were asked to acquire information and formulate a decision by selecting one of three options. The study comprised two phases, the first of which involved familiarizing participants with each of the four interface designs and collecting performance and subjective data. The second phase involved trainees selecting one of the four interfaces to engage in a fifth and sixth decision scenario involving high or low levels of time-pressure. The results indicated that the “all options, full control” interface was the preferred option in the low time-pressure condition. Although the strategy remained the most frequently selected in the high time-pressure condition, this preference was not significant. It was concluded that the perceptions of difficulty and the degree of user control over information acquisition were more important than perceived efficiency in the selection of computer-based interface designs. The outcomes have implications for the design of decision support systems.     

Fairness-related challenges in mobile opportunistic networking

The fundamental challenge in opportunistic networking, regardless of the application, is when and how to forward a message. Rank-based forwarding techniques currently represent one of the most promising methods for addressing this message forwarding challenge. While these techniques have demonstrated great efficiency in performance, they do not address the rising concern of fairness amongst various nodes in the network. Higher ranked nodes typically carry the largest burden in delivering messages, which creates a high potential of dissatisfaction amongst them. In this paper, we adopt a real-trace driven approach to study and analyze the trade-offs between efficiency, cost, and fairness of rank-based forwarding techniques in mobile opportunistic networks.Our work comprises three major contributions. First, we quantitatively analyze the trade-off between fair and efficient environments. Second, we demonstrate how fairness coupled with efficiency can be achieved based on real mobility traces. Third, we propose FOG, a real-time distributed framework to ensure efficiency–fairness trade-off using local information. Our framework, FOG, enables state-of-the-art rank-based opportunistic forwarding algorithms to ensure a better fairness–efficiency trade-off while maintaining a low overhead. Within FOG, we implement two real-time distributed fairness algorithms; Proximity Fairness Algorithm (PFA), and Message Context Fairness Algorithm (MCFA). Our data-driven experiments and analysis show that mobile opportunistic communication between users may fail with the absence of fairness in participating high-ranked nodes, and an absolute fair treatment of all users yields inefficient communication performance. Finally our analysis shows that FOG-based algorithms ensure relative equality in the distribution of resource usage among neighbor nodes while keeping the success rate and cost performance near optimal.     

Local nonlinear unknown input observer

This paper proposes a new nonlinear unknown input observer. The observer design approach utilizes the first order Taylor expansion. The observer gains are then obtained by a systematic method. In this paper, we added some improvements to this method. The developed approach also can enable observer design for a large class of differentiable nonlinear systems. The necessary and sufficient conditions for the existence of the observer are given. A numerical example is given to illustrate the attractiveness and the simplicity of the new design procedure.     

A Replicated Survey of IT Software Project Failures

Despite various industry reports about the failure rates of software projects, there's still uncertainty about the actual figures. Researchers performed a global Web survey of IT departments in 2005 and 2007. The results suggest that the software crisis is perhaps exaggerated and that most software projects deliver. However, the overall project failure rate, including cancelled and completed but poorly performing projects, remains arguably high for an applied discipline.     

基于BP神经网络的盲数字水印算法

该文将二值水印嵌入到宿主图像的小波变换域的低频分量中,利用BP神经网络很好的非线性映射和自学习、自适应学习特点实现水印信息的盲提取,仿真实验结果表明该算法既能抵抗常规的图像处理攻击,也能抵抗一定程度的几何攻击,如JPEG压缩、剪切、加噪和滤波等,具有较好的鲁棒性和不可见性。     

Hierarchically Distributed Peer-to-Peer Document Clustering and Cluster Summarization

In distributed data mining, adopting a flat node distribution model can affect scalability. To address the problem of modularity, flexibility and scalability, we propose a Hierarchically-distributed Peer-to-Peer (HP2PC) architecture and clustering algorithm. The architecture is based on a multi-layer overlay network of peer neighborhoods. Supernodes, which act as representatives of neighborhoods, are recursively grouped to form higher level neighborhoods. Within a certain level of the hierarchy, peers cooperate within their respective neighborhoods to perform P2P clustering. Using this model, we can partition the clustering problem in a modular way across neighborhoods, solve each part individually using a distributed K-means variant, then successively combine clusterings up the hierarchy where increasingly more global solutions are computed. In addition, for document clustering applications, we summarize the distributed document clusters using a distributed keyphrase extraction algorithm, thus providing interpretation of the clusters. Results show decent speedup, reaching 165 times faster than centralized clustering for a 250-node simulated network, with comparable clustering quality to the centralized approach. We also provide comparison to the P2P K-means algorithm and show that HP2PC accuracy is better for typical hierarchy heights. Results for distributed cluster summarization match those of their centralized counterparts with up to 88% accuracy.     

炼油企业蒸汽动力系统改造优化研究

针对当前形势下炼油企业蒸汽动力系统存在的巨大改造潜力,提出了蒸汽动力系统改造的优化方法;该方法首先通过运行优化方案分析和系统设备诊断找出系统存在问题,然后通过专家知识系统提出一系列解决的方案,建立系统改造方案的超结构和考虑柔性调节的优化改造混合整数线性规划(MILP)模型,求解模型并确定最优的改造方案;文章最后部分给出了详细的案例分析,结果表明应用本文提出的改造优化策略方法确定的最佳改造方案可以为案例背景炼油企业蒸汽动力系统节约大约6%的运行费用,投资回收期约0.38年;本文提出的优化改造方法为推动炼油企业蒸汽动力系统的节能降耗提供了定的理论指导和技术支持.