New insights on survivability in multi-domain optical networks

With the development of intelligent optical networks and the general multi-protocol label switching (GMPLS) technique, the seamless convergence between IP network and optical network is no longer be a dream but a practical reality. Similar to the Internet, current optical networks have been divided into multiple domains each of which has its own network provider and management policy. Therefore, the development of multi-domain optical networks will be the trend of new-generation intelligent optical networks, and GMPLS-based survivability for multi-domain optical networks will become a hot topic of research in the future. This paper provides a comprehensive review of the existing survivable schemes in multi-domain optical networks and analyzes the shortcomings of current research. Based on previous studies, we present possible challenges and propose new ideas to design efficient survivable schemes to guide the future work of researchers in multi-domain optical networks.     

An integrated multi-objective immune algorithm for optimizing the wire bonding process of integrated circuits

Optimization of the wire bonding process of an integrated circuit (IC) is a multi-objective optimization problem (MOOP). In this research, an integrated multi-objective immune algorithm (MOIA) that combines an artificial immune algorithm (IA) with an artificial neural network (ANN) and a generalized Pareto-based scale-independent fitness function (GPSIFF) is developed to find the optimal process parameters for the first bond of an IC wire bonding. The back-propagation ANN is used to establish the nonlinear multivariate relationships between the wire boning parameters and the multi-responses, and is applied to generate the multiple response values for each antibody generated by the IA. The GPSIFF is then used to evaluate the affinity for each antibody and to find the non-dominated solutions. The “Error Ratio” is then applied to measure the convergence of the integrated approach. The “Spread Metric” is used to measure the diversity of the proposed approach. Implementation results show that the integrated MOIA approach does generate the Pareto-optimal solutions for the decision maker, and the Pareto-optimal solutions have good convergence and diversity performance.     

基于3G终端的双处理器间通信模块设计

在现在的手机终端中,由于视频、音频的编解码需要占用大量的CPU时间,因此在3G终端中再增加一个CPU来进行多媒体信息的处理成为必然,通过主CPU上运行多媒体块所要解决的核心问题.通过主从CPU之间约定特定的消息来实现主CPU对从CUP的控制,而从CPU对主CPU的定时和携带数据满住固定大小这两种反馈机制有效解决了双CPU间的通讯问题.     

基于椭圆曲线的一种高效率数字签名

为给出一种基于椭圆曲线密码的高效率的数字签名方案.不仅在算法设计时完全避免了费时的求逆运算,而且利用消息HASH值的汉明重量作为消息摘要进行签名与验证.结果在同等安全性下,该方案比通用的ECDSA等方案运行时间更短.新方案可适用于网络等对签名实时性要求较高的场合.     

基于RIA的网络科技资源呈现系统的研究与实现

面对分布式环境下的异构网络科技资源,对其进行集成和共享,并为用户提供统一、快速的展现方式尤为重要.RIA (Rich Internet Application) 技术是Web 应用程序发展过程中产生的一种具有高度互动性和丰富用户体验的网络应用技术,是下一代Web 应用程序发展的方向.基于RIA技术,针对网络科技资源的异构性、丰富性等特征,研究并实现了一套高效的网络科技资源呈现系统.相对传统的B/S架构,具有不可比拟的优势.     

一种基于启发式搜索的论文元数据提取算法

随着大量的科研论文以电子文档的形式出现, 为了高效地检索这些科研文献资料,从中精确地抽取这些论文头部的元数据信息显得十分有必要.在条件随机场模型的基础上,提出了一种启发式搜索算法来对论文头部的元数据信息进行提取.该算法首先利用文本分块技术和特征提取规则来对文本进行预处理,然后结合条件随机场概率模型利用启发式搜索来进行元数据的提取.实验结果表明,在相同概率模型的基础上,该算法有着较好的性能,在精确度和召回率方面都有了明显的提高.     

基于伪并行遗传算法的聚类分析方法

针对传统的基于聚类准则的聚类算法初始化敏感和容易陷入局部极值的问题,设计了一种新的基于伪并行遗传算法的聚类方法.采用实数编码方式对每个样本所属的类别进行编码,通过空类的识别和修复来修正不舍法的染色体.在引入离散随机变异算子和优化方向变异算子的基础上,结合迁移策略和插入策略,达到兼顾局部收敛速度和全局收敛性能的目的.与K-均值算法对比仿真实验,表明了这种基于伪并行遗传算法的聚类新方法的可行性和有效性.     

小型钨丝电热原子吸收光谱仪的电源

随着对分析仪器的小型化、便携式需求的提高,钨丝电热原子吸收光谱仪在便携式分析仪器方面显示了很大的潜力.为进一步满足现场分析的需要,以单片机为芯片,为小型钨丝电热原子吸收光谱仪的空心阴极灯和钨丝电热原子化器设计稳定的一体化恒流电源;并编写PC机的控制软件,以USB或RS232方式与电源通信,方便控制空心阴极灯和钨丝电热原子化器电流,以及原子吸收过程.以此电路设计的小型钨丝电热原子吸收光谱仪对镉、铅、金和银的标准溶液测试结果为:检出限分别为(0.1,6.0,5.0,0.6)μg/L,相对标准偏差分别为8.2%,5.3%,6.0%和7.2%.测试结果表明:电源很稳定,达到了文献报道的钨丝电热原子吸收光谱的分析性能.     

烯烃催化裂解反应动力学的研究

根据脉冲微反条件下C5～C8烯烃裂解产物分布,建立烯烃裂解反应网络,通过参数估计方法确定反应网络动力学常数、反应活化能和指前因子.结果表明,随着碳数的增加,C5～C8烯烃单分子裂解反应速率加快.反应温度600℃时C5～C8正构烯烃裂解生成丙烯,其反应速率常数的比值为1:8.18:38.48:27.98,最快生成丙烯的是1-庚烯.反应温度相同,1-烯烃的主要裂解反应速率是碳数相同的2-甲基-2-烯烃的1.1～1.6倍.C5烯烃裂解为单、双分子裂化并存的反应体系,但双分子裂解反应速率远大于单分子裂解,双分子反应占优势.     

Integration of a stereo vision system and a laser range finder for 3-D construction

In this article, we investigate the problem of integrating a binocular stereo vision system and a laser range finder to construct a 3-D map of the environment. The proposed scheme is realized by using the alignment parameters obtained in the 2-D map construction of the laser range finder for the 3-D data generated by the stereo vision system. The 2-D map alignment task is formulated as an optimization problem of minimizing the alignment errors between local maps and selected parts of the developing global map. The problem is then solved using the Simplex method. To increase the robustness of the searching process, multiple initial guesses are provided in the Simplex method. The performance of the proposed architecture is verified by experimental results from a mobile vehicle for obstacle avoidance.