靶场仿真中分布式异构网关技术研究

为快速、高效地实现试验与训练领域各靶场、设施和仿真的互操作、重用和可组合,构建实物的、虚拟的、构造的(LVC)分布式网络,研究了目前主要存在的高级分布式仿真架构,包括分布式交互仿真(DIS)、高层体系架构(HLA)及试验与训练使能体系结构(TENA);在对它们的异同进行分析比较的基础上,确定以TENA网关对异构靶场进行无缝连接是实现靶场互联的最佳方案;对网关进行了总体设计并对关键技术进行了分析,网关原型的建立为网关的深入研究和开发奠定了基础。     

动态偏置射频宽带功放设计

射频宽带功率放大器是目前功率放大器的主要发展趋势。为了提高射频宽带功率放大器的增益平坦度与效率,采用推挽结构LDmos晶体管,使用ADS软件对动态偏置电路和匹配电路进行仿真设计。详细介绍了动态偏置功率放大器的工作原理及其实现方法。实现了多倍频程带宽、确保带内增益平坦、提高功率附加效率。仿真结果表明该功率放大器对于100MHz~400MHz的信号,在整个输入功率变化范围内,功率附加效率（PAE）与传统的功放相比提高了5~15%左右。     

嵌入式软件测试的数据获取技术

测试数据获取是嵌入式软件测试的关键技术,其准确性.实时性和可靠性对测试质量有决定性影响.嵌入式软件测试需要根据软件特性和测试要求对数据获取方法进行定制设计.针对侵入式的软件插桩测试技术,着重研究了硬件采集、硬件收发、纯软件方式的插桩实现过程.对非侵入式的边界扫描技术和虚拟仿真技术的数据获取原理进行了分析,并提出了嵌入式开发测试一体化集成应用和全生存周期嵌入式软件开发,测试与管理的思想,指出了嵌入式软件测试的新方向.     

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.     

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。     

Speed up kernel discriminant analysis

Linear discriminant analysis (LDA) has been a popular method for dimensionality reduction, which preserves class separability. The projection vectors are commonly obtained by maximizing the between-class covariance and simultaneously minimizing the within-class covariance. LDA can be performed either in the original input space or in the reproducing kernel Hilbert space (RKHS) into which data points are mapped, which leads to kernel discriminant analysis (KDA). When the data are highly nonlinear distributed, KDA can achieve better performance than LDA. However, computing the projective functions in KDA involves eigen-decomposition of kernel matrix, which is very expensive when a large number of training samples exist. In this paper, we present a new algorithm for kernel discriminant analysis, called Spectral Regression Kernel Discriminant Analysis (SRKDA). By using spectral graph analysis, SRKDA casts discriminant analysis into a regression framework, which facilitates both efficient computation and the use of regularization techniques. Specifically, SRKDA only needs to solve a set of regularized regression problems, and there is no eigenvector computation involved, which is a huge save of computational cost. The new formulation makes it very easy to develop incremental version of the algorithm, which can fully utilize the computational results of the existing training samples. Moreover, it is easy to produce sparse projections (Sparse KDA) with a L ₁-norm regularizer. Extensive experiments on spoken letter, handwritten digit image and face image data demonstrate the effectiveness and efficiency of the proposed algorithm.     

微电子器件温度分布测试技术研究

为改善微电子器件性能,提高可靠性,确定筛选、考核条件等都必须对器件的结温、表面温度分布以及热斑等热特性进行精确测量,红外热像法是当前测量微电子器件热特性最有效的方法之一。文章针对InfrascopeⅡ型显微红外热像仪在实际应用中如何提高其测温准确度和一致性等问题进行了研究,重点分析了样品发射率、背景环境和大气衰减等因素的影响,并给出验证解决方案,取得了满意的结果。     

基于覆盖网络的海上信息栅格无线传输系统研究

文章在通信资源的形式化描述基础上,设计了一种信息栅格的传输体系,为一体化信息系统提供透明的传输服务。针对多重网络传输服务与网络性能的多样性,提出了一种基于作战任务的层次覆盖网络模型,以及实现网络负载均衡的QoS路由算法。     

Using system dynamics for simulation and optimization of one coal industry system under fuzzy environment

In this paper, we have developed a model that integrates system dynamics with fuzzy multiple objective programming (SD-FMOP). This model can be used to study the complex interactions in a industry system. In the process of confirming sensitive parameters and fuzzy variables of the SD model, we made use of fuzzy multi-objective programming to help yield the solution. We adopted the chance-constraint programming model to convert the fuzzy variables into precise values. We use genetic algorithm to solve FMOP model, and obtain the Pareto solution through the programming models. It is evident that FMOP is effective in optimizing the given system to obtain the decision objectives of the SD model. The results recorded from the SD model are in our option, reasonable and credible. These results may help governments to establish more effective policy related to the coal industry development.     

Exploiting effective features for chinese sentiment classification

Features play a fundamental role in sentiment classification. How to effectively select different types of features to improve sentiment classification performance is the primary topic of this paper. Ngram features are commonly employed in text classification tasks; in this paper, sentiment-words, substrings, substring-groups, and key-substring-groups, which have never been considered in sentiment classification area before, are also extracted as features. The extracted features are then compared and analyzed. To demonstrate generality, we use two authoritative Chinese data sets in different domains to conduct our experiments. Our statistical analysis of the experimental results indicate the following: (1) different types of features possess different discriminative capabilities in Chinese sentiment classification; (2) character bigram features perform the best among the Ngram features; (3) substring-group features have greater potential to improve the performance of sentiment classification by combining substrings of different lengths; (4) sentiment words or phrases extracted from existing sentiment lexicons are not effective for sentiment classification; (5) effective features are usually at varying lengths rather than fixed lengths.