Understanding silica-supported metal catalysts: Pd/silica as a case study

Supported metal catalysts, particularly noble metals supported on SiO₂, have attracted considerable attention due to the importance of the silica–metal interface in heterogeneous catalysis and in electronic device fabrication. Several important issues, e.g., the stability of the metal–oxide interface at working temperatures and pressures, are not well-understood. In this review, the present status of our understanding of the metal–silica interface is reviewed. Recent results of model studies in our laboratories on Pd/SiO₂/Mo(1 1 2) using LEED, AES and STM are reported. In this work, epitaxial, ultrathin, well-ordered SiO₂ films were grown on a Mo(1 1 2) substrate to circumvent complications that frequently arise from the silica–silicon interface present in silica thin films grown on silicon.     

改进型UDP组播的性能分析及其在实时电源控制系统中的应用

文章通过采用带连接的UDP、I/O复用技术、关闭UDP校验和功能、负载均衡等技术对普通的UDP组播技术进行改进,使之在每个控制周期(1ms)内满足了分布式实时控制系统的实时性和可靠性要求。在将改进型的UDP组播技术应用于实际控制系统之前,文中构建了一个模拟局域网进行测试,对比结果表明改进后的组播技术无论在数据包延迟、丢包率等方面较改进前的UDP组播性能有较大幅度的提高。     

基于虚拟仪器的现代温度检测系统的研究

对一个基于虚拟仪器的现代温度检测系统进行了系统的论述，并给出了具体实现方案及结果。     

A new detection algorithm (NDA) based on fuzzy cellular neural networks for white blood cell detection.

White blood cell detection is one of the most basic and key steps in the automatic recognition system of white blood cells in microscopic blood images. Its accuracy and stability greatly affect the operating speed and recognition accuracy of the whole system. But there are only a few methods available for cell detection or segmentation due to the complexity of the microscopic images. This paper focuses on this issue. Based on the detailed analysis of the existing two methods--threshold segmentation followed by mathematical morphology (TSMM), and the fuzzy logic method--a new detection algorithm (NDA) based on fuzzy cellular neural networks is proposed. NDA combines the advantages of TSMM and the fuzzy logic method, and overcomes their drawbacks. With NDA, we can detect almost all white blood cells, and the contour of each detected cell is nearly complete. Its adaptability is strong and the running speed is expected to be comparatively high due to the easy hardware implementation of FCN. Experimental results show good performance.     

自动监视和告警系统中红外弱小目标的识别

红外弱小目标识别一直是自动监视和告警系统中的一项关键技术。成像跟踪识别系统的算法研究需要分析特定应用环境中的背景和目标特点，本文第一部分对此进行了分析。接下来，在对应用环境进行分析的基础上，对远距离红外小目标的探测、识别和跟踪算法进行了介绍。最后，针对视频环境下的红外跟踪，介绍了为提高跟踪稳定性而进行的一系列实验及其原理装置。     

Anti-collusion fingerprinting for multimedia

Digital fingerprinting is a technique for identifying users who use multimedia content for unintended purposes, such as redistribution. These fingerprints are typically embedded into the content using watermarking techniques that are designed to be robust to a variety of attacks. A cost-effective attack against such digital fingerprints is collusion, where several differently marked copies of the same content are combined to disrupt the underlying fingerprints. We investigate the problem of designing fingerprints that can withstand collusion and allow for the identification of colluders. We begin by introducing the collusion problem for additive embedding. We then study the effect that averaging collusion has on orthogonal modulation. We introduce a tree-structured detection algorithm for identifying the fingerprints associated with K colluders that requires O(Klog(n/K)) correlations for a group of n users. We next develop a fingerprinting scheme based on code modulation that does not require as many basis signals as orthogonal modulation. We propose a new class of codes, called anti-collusion codes (ACCs), which have the property that the composition of any subset of K or fewer codevectors is unique. Using this property, we can therefore identify groups of K or fewer colluders. We present a construction of binary-valued ACC under the logical AND operation that uses the theory of combinatorial designs and is suitable for both the on-off keying and antipodal form of binary code modulation. In order to accommodate n users, our code construction requires only O(/spl radic/n) orthogonal signals for a given number of colluders. We introduce three different detection strategies that can be used with our ACC for identifying a suspect set of colluders. We demonstrate the performance of our ACC for fingerprinting multimedia and identifying colluders through experiments using Gaussian signals and real images.     

弯曲性分叉河道中污染物扩散性的初步研究

弯曲性分叉河道中水流特征复杂,对污染物扩散有很大影响。为了定量分析其水流特征对污染物扩散的影响,采用有限元方法求解弯曲性分叉河道中的污染物扩散数学模型,研究其中污染物扩散的状况。主要针对河道回流、绕流对污染物扩散的影响进行了详细数值模拟计算,并分别给出了可视化结果及平均的扩散距离。计算结果表明:边界层稍微减弱污染物的扩散,弯道分离使污染物扩散呈现多向扩散,而回流和绕流尾迹区使污染物很难扩散,从而有利于泄漏污染物的收集和集中治理。     

炼油厂碱性污水生物催化氧化预处理工艺研究

在对炼油厂碱性污水水质分析的基础上,提出采用生物催化氧化工艺对碱性污水进行预处理。试验结果表明,在水力停留时间为4 h,曝气量(标准状态)为8 m3／h的条件下,碱性污水的硫化物去除率可达90％以上,出水中的硫化物平均值为15．2 mg/L,CODCR、酚和油的去除率分别为47．5％,44．1％,50．8％,其中CODCR体积负荷为3．85 kg／(m3·d),是传统生化处理的10倍, 达到了污水预处理的目的。