Crashworthiness design of vehicle by using multiobjective robust optimization

Although deterministic optimization has to a considerable extent been successfully applied in various crashworthiness designs to improve passenger safety and reduce vehicle cost, the design could become less meaningful or even unacceptable when considering the perturbations of design variables and noises of system parameters. To overcome this drawback, we present a multiobjective robust optimization methodology to address the effects of parametric uncertainties on multiple crashworthiness criteria, where several different sigma criteria are adopted to measure the variations. As an example, a full front impact of vehicle is considered with increase in energy absorption and reduction of structural weight as the design objectives, and peak deceleration as the constraint. A multiobjective particle swarm optimization is applied to generate robust Pareto solution, which no longer requires formulating a single cost function by using weighting factors or other means. From the example, a clear compromise between the Pareto deterministic and robust designs can be observed. The results demonstrate the advantages of using multiobjective robust optimization, with not only the increase in the energy absorption and decrease in structural weight from a baseline design, but also a significant improvement in the robustness of optimum.     

GNSS卫星信号模拟器码和载波NCO研究与实现

NCO是卫星信号模拟器中频信号处理的关键部分;介绍了GNSS卫星信号模拟器码NCO和载波NCO的原理及作用,建立DDS模型,确定基本参数并根据参数设计了码NCO和载波NCO基本结构;给出了码NCO和载波NCO的实现过程,利用verilog在Xilinx'ISE 11.2和modelsim6.5中完成载波NCO和码NCO的设计和仿真,在FPGA中进行了实现,并给出仿真波形和信号频谱图;本码NCO和载波NCO模块已应用于某型GNSS模拟器样机,通过程序仿真与样机测试,证明本码NCO和载波NCO模块性能满足GNSS卫星信号模拟器系统需求.     

基于二阶梯度的图像增强算法研究

针对PCB图像的特点对图像进行增强处理,使得图像的边缘更加突出,灰度的对比度增加,同时滤除靠近边缘的噪声,为后续图像分割时更有效的选取阈值打下良好基础。使用二阶梯度算子获得图像的增强效果,实验表明,不仅解决了边缘附近噪声去除问题,而且有效地突出了边缘信息,图像的黑白对比分明,尤其是目标图像靠近边缘部分灰度值明显高于其他的非边缘区域。     

平均保障延误时间（MLDT）建模方法研究

针对现代装备系统的精确化保障要求,对装备保障的主要参数指标MLDT进行了建模分析,主要分析了三种计算方法：图估法、解析法和基于排队论的MLDT建模理论,解决了评估MLDT指标时的定量计算问题。     

Sorcery: Overcoming deceptive votes in P2P content sharing systems

Deceptive voting behaviors of malicious users are known as the main reason of causing content pollution in Peer-to-Peer (P2P) content sharing systems. Due to the nature of P2P overlay network such as self-organization and anonymity, the existing methods on identifying deceptive votes are not effective, especially for collusive attackers. This paper presents Sorcery, a novel active challenge-response mechanism based on the notion that one side of interaction with the dominant information can detect whether the other side is telling a lie. To make each client obtain the dominant information, our approach introduces the social network to the P2P content sharing system; therefore, clients can establish the friend-relationships with the users who are either acquaintances in reality or those reliable online friends. Using the confidential voting histories of friends as own dominant information, the client challenges target content providers with the overlapping votes of both his friends and the target content provider, thus detecting whether the content provider is a deceptive user. Moreover, Sorcery provides the punishment mechanism which can reduce the impact brought by deceptive voting behaviors, and our work also discusses some key practical issues. The experimental results illustrate that Sorcery can effectively overcome the problem of deceptive voting behaviors in P2P content sharing systems, and work better than the existing reputation models.     

基于ADSP-BF561的英文字符库设计

针对以ADSP-BF561芯片为核心的目标跟踪系统中显示目标运动及提示信息的需要,提出了基于ADSP-BF561的英文字符库的设计方案.该字符库中包括26个小写英文字符(a～z)、10个数字(0～9),以及“:”和空格共计38个符号.该字符库通过使用存储在ADSP-BF561的L2存储器上的数据类型为布尔型、大小为16...     

西藏高校数字图书馆数据安全现状分析及防护策略

数据安全是图书馆开展各项数字化服务前提和保证,本文通过分析目前西藏高校图书馆数据安全的现状及存在的问题,结合西藏各高校图书馆实际,提出了数据安全的防护策略,希望为西藏高校图书馆数据安全建设抛砖引玉。     

Feature Extraction Using Laplacian Maximum Margin Criterion

Feature extraction by Maximum Margin Criterion (MMC) can more efficiently calculate the discriminant vectors than LDA, by avoiding calculation of the inverse within-class scatter matrix. But MMC ignores the local structures of samples. In this paper, we develop a novel criterion to address this issue, namely Laplacian Maximum Margin Criterion (Laplacian MMC). We define the total Laplacian matrix, within-class Laplacian matrix and between-class Laplacian matrix by using the similar weight of samples to capture the scatter information. Laplacian MMC based feature extraction gets the discriminant vectors by maximizing the difference between between-class laplacian matrix and within-class laplacian matrix. Experiments on FERET and AR face databases show that Laplacian MMC works well.     

Computational investigation of interactions between human H2 receptor and its agonists

Type 2 histamine receptor (H(2)R) is widely distributed in the body. Its main function is modulating the secretion of gastric acid. Most gastric acid-related diseases are closely associated with it. In this study, a combination of pharmacophore modeling, homology modeling, molecular docking and molecular dynamics methods were performed on human H(2)R and its agonists to investigate interaction details between them. At first, a pharmacophore model of H(2)R agonists was developed, which was then validated by QSAR and database searching. Afterwards, a model of the H(2)R was built utilizing homology modeling method. Then, a reference agonist was docked into the receptor model by induced fit docking. The 'induced' model can dramatically improve the recovery ratio from 46.8% to 69.5% among top 10% of the ranked database in the simulated virtual screening. The pharmocophore model and the receptor model matched very well each other, which provided valuable information for future studies. Asp98, Asp186 and Tyr190 played key roles in the binding of H(2)R agonists, and direct interactions were observed between the three residues and agonists. Residue Tyr250 could also form a hydrogen bond with H(2)R agonists. These findings would be very useful for the discovery of novel and potent H(2)R agonists.     

Energy-aware weighted graph based dynamic topology control algorithm

In this paper a new energy-aware weighted dynamic topology control (WDTC) algorithm is proposed to extend the lifetime of wireless network and balance the nodes’ energy consumption. The idea is that each node builds its local minimum spanning tree (MST) based on the energy-aware weighted graph and the network topology is adjusted accordingly. It was proved theoretically that the topology under WDTC algorithm could preserve the network connectivity and a sufficient condition for the degree of no more than 6 was also given. Simulation shows that WDTC algorithm can effectively prolong the network lifetime and has good topological features.