基于混合矩的多输出模型确认指标研究

针对随机不确定性条件下多输出计算模型与物理实验数据之间一致性难以量化度量这一问题,本文提出一组新的基于混合矩的多输出模型确认指标。在不确定情况下,同时考虑到多维输出之间的相关关系和单输出的均值,构建了由多输出数学期望列阵和协方差矩阵组成的多输出模型确认局部混合矩指标和全局混合矩指标。其中局部混合矩指标包括绝对指标(LA-3M)和相对指标(LR-3M),它们适合固定位置的多输出局部模型确认;全局混合矩指标也包括绝对指标(GA-3M)和相对指标(GR-3M),它们适合多点位置的多输出全局模型确认。通过数字算例和工程算例,并与PIT和t-pooling 面积指标进行对比,结果表明本文所提指标可行有效,能够方便地度量计算模型和物理实验之间的差异程度。     

求解特征结构配置问题的一种新方法

基于遗传算法提出了求解线性多变量系统在输出反馈作用下的特征结构配置问题的一种新方法。遗传算法是一种基于自然选择和群体遗传学机理的参数搜索方法。采用遗传算法求解特征结构配置问题,具有适用面广和计算稳定等特性。我们以导弹控制系统为例进行了仿真,结果是令人满意的。     

一种基于离散混沌系统的S-Box候选算法设计

S-Box是现行分组密码中唯一的非线性部件,主要提供了分组密码算法中必需的混淆作用,其密码强度决定了整个分组密码的安全强度。为进一步提高S-Box的强度,结合离散混沌系统的内在随机性、有界性、非周期性及对初始条件和参数极度敏感等特点,提出一种采用多混沌映射和交叉映射生成S-Box的生成算法。实验分析表明,该算法生成的样本密钥敏感性强,随机性好,既能较好地满足S-Box设计所要求的各项准则和特性,安全性高,同时又能降低计算复杂度,提高计算速度,且易于生成和扩展,因而是一种性能良好的S-Box候选算法。     

基于R-树索引的Map-Reduce空间连接聚集操作

空间连接聚集是一种常用并且非常耗时的空间数据库操作,特别是在面对大规模空间数据集时,单机运行环境难以满足其对时空开销的需求,如何设计高效的面向云计算环境中的分布式空间连接聚集算法越来越受到人们关注。Map-Reduce作为云计算的核心模式受限于其扁平化的串行扫描操作模型,常被用来加速非索引的空间连接操作,现有工作尚无将Map-Reduce和R-树索引结合来处理空间连接聚集。因此,提出了基于R-树索引的Map-Reduce空间连接聚集算法(RSJA-MR)来更高效地返回连接聚集结果。提出一种分布式R-树索引结构以支持大规模空间数据的索引,RSJA-MR算法利用分布式R-树生成任务集,任务集的执行满足无依赖并行计算模式,很容易在Map-Reduce框架中进行表达。文中提出一种实时缓存策略以支持索引并发访问。实验结果表明:相比非索引的Map-Reduce连接聚集算法,在空间交叠连接聚集查询上,时间性能最少提升8%,在空间包含连接聚集查询上,时间性能最少提升近35%。     

Defense Spending Promotes Aggregate Output in the United States--Evidence from Cointegration Analysis

This paper provides new evidence on the question of the effects of defense spending on aggregate output in the United States. Earlier studies of this basic issue relied on traditional econometric techniques and the neoclassical production function theory. In this paper, recently developed cointegration methodology and modeling that is inspired by new macroeconomic theory is employed. The results from earlier studies concerning the effects of defense spending are mixed. The findings presented in this paper reveal that there is a quantitatively important and positive relation between defense spending and aggregate output in the United States.     

Collaborative projects and the number of partner nations

Collaborative defence projects have been a distinctive feature of European defence industrial policy. This article focuses on whether the number of partner nations in international collaborative defence and aerospace programmes is a source of inefficiency. It appears that there is not a simple linear relationship. Two nation collaborations can be efficient, but conventional wisdom assumes that inefficiencies emerge with more than two partner nations. Inevitably, data problems made what appears to be a simple hypothesis difficult to test. The major result is that there is no evidence that efficiency as measured by development times is adversely affected by the number of partner nations. A limited sample regression and a comparison of Airbus vs. Boeing shows a similar conclusion.     

The Keynesian IS-MR Model and Military Spending

The issue of guns or butter is one of the most fundamental economic questions, yet there is no consensus on a theoretical framework for examining it. Over the last decade, a version of a simple Keynesian macroeconomic model has been applied a number of times to examining the link between defence spending and economic growth in a range of countries. There are reasons for doubting the soundness of this model as a basis for empirical work.