9/11: WHAT DID WE KNOW AND WHEN DID WE KNOW IT?

In February 1998, Osama Bin Laden published a signed statement calling for a fatwa against the United States for its having ‘declared war against God’. As we now know, the fatwa resulted in the unprecedented attack of 9/11. The issue of whether or not 9/11 was in any way predictable culminated in the public debate between Richard Clarke, former CIA Director George Tenet and the White House. This paper examines whether there was any evidence of a structural change in the terrorism data at or after February 1998 but prior to June 2001, controlling for the possibility of other breaks in earlier periods. In doing so, we use the standard Bai–Perron procedure and our sequential importance sampling (SIS) Markov Chain Monte Carlo (MCMC) method for identifying an unknown number of breaks at unknown dates. We conclude that sophisticated statistical time‐series analysis would not have predicted 9/11.     

TERRORISM AND TOURISM: THE CASE OF TURKEY

Using a time series method called ‘transfer function’, this paper examines the effect of terrorism on tourism in Turkey. The results indicate that there exists a negative but small impact of terrorism, which is observed within approximately one year. However, terrorist attacks in Turkey have accounted for a reduction of six million foreign tourists over the last nine years. Moreover, the economic cost of terrorism in the tourism industry was more than $700 million in 2006. However, terrorist attacks in continental Europe and America, and an active war involving a neighboring country, had no effects on tourism in Turkey.     

Remaking the military industrial relationship: A French‐American comparison

Defense industrial complexes in leading Cold War nations have downsized and reallocated resources to other productive activities in the 1990s. In this paper, we analyze the experience of two key countries ‐ the US and France. Comparing the two countries, we find similar outcomes in budgetary retrenchment and large firm restructuring but marked differences in the pace of downsizing and diversification among small and medium‐sized firms. We hypothesize that three sets of contextual differences may explain these differences: 1) institutional differences in the way that the State bureaucracies ‐ the Pentagon and the French Délégation générale pour l'armement (DGA) ‐ oversee defense industrial matters, 2) differences in military industry ownership and firm size patterns, and 3) differences in the regional distribution of defense industrial capacity and associated regional policies. In closing, we note that the two countries’ defense industrial complexes are becoming more alike and speculate on the significance of invidious competition and interactions between them. We address briefly the future of French/American arms industrial competition and cooperation, given the trend towards transnational security arrangements and defense industry globalization     

基于L曲线的跳频信号重构正则化参数优化

研究了基于L曲线的跳频信号重构正则化参数的选取问题,对跳频信号的稀疏性进行了分析,采用L曲线对系统的最优正则化参数进行了选取．在此基础上,通过推广的正则化FOCUSS算法估计了跳频信号的稀疏表示．仿真结果表明,通过L曲线选取的正则化参数在推广的正则化FOCUSS算法下,能够实现跳频信号在噪声环境下的重构．     

一种高效的通信电台测试点优化故障诊断策略

针对通信电台的测试诊断问题,通过建立“故障一测试”相关性矩阵,提出了一种GADPSO算法与最大诊断信息量准则结合进行通信电台故障诊断的方法．GADPSO算法收敛速度快、计算精度高,既避免了陷入局部最优和早熟收敛,又提高了优化效率;最大诊断信息量准则能全面评判测试点,快速有效地获得测试顺序．该方法为通信电台故障诊断提供了一种高效诊断策略．     

基于禁忌算法的无线传感器网络PEGASIS算法改进

为了减少无线传感器网络节点能耗,延长网络生存时间,在PEGASIS算法的基础上,针对PEGASIS算法中节点之间容易产生长链和簇头选择没有考虑节点剩余能量的问题,提出了一种基于禁忌算法的PEGASIS算法改进。建链阶段采用禁忌算法代替原有的贪婪算法,防止了长链的产生,减小了节点传输距离;同时引入基于剩余能量的簇头选择机制,均衡了节点之间的能耗,延长了节点的生存时间。仿真结果表明,改进算法较PEGASIS算法第1个节点的死亡时间延长了约7倍,半数节点的死亡时间也得到了延长,从而提高了整个网络的生存时间。     

基于贪婪算法的影响网络行动方案优选

针对影响网络中行动方案的优选问题,分析了现有方法存在的不足,提出了一种基于贪婪算法的行动方案优选方法。该方法采用自顶向下的搜索方式,通过分析行动组合对期望效果的整体影响来选择较优的行动方案。并进行实例验证。结果表明,与灵敏度分析法和穷举搜索法相比,该方法能够在较短时间内找到较优的可行行动方案集合,可有效支持行动方案的优选。     

基于呼叫状态的IMS业务触发算法

在IMS会话和和业务控制过程中,随着业务量的增长,S-CSCF面临的负载急剧增加,3GPP原有IMS业务的集中控制方式极易形成性能“瓶颈”,从而影响系统服务质量。为降低会话时延,提高系统性能,本文在研究基于分组的业务触发算法和基于呼叫状态的业务触发算法基础上,提出了一种基于呼叫状态的分组业务触发算法（C-GSTA）,并对其进行性能建模和理论分析。仿真结果表明,在业务种类和业务量增加的情况下,C-GSTA算法能够有效降低S-CSCF与服务器之间的信令流量,提高IMS系统吞吐量,缩短S-CSCF处理时延,改善业务触发性能和网络服务质量。     

需求可拆分的应急物资调度问题的蚁群算法

应急物资调度问题是个典型的需求可拆分的车辆路径问题,区别于传统的车辆路径问题,将每个需求节点只能由一辆车访问的约束去除,允许需求节点由多辆车进行访问。针对应急物资调度问题的特点,建立相应的多目标车辆路径数学规划模型(SDVRP),并根据模型特点设计改进蚁群优化算法。最后,进行相应的算例分析,验证了该模型和算法的有效性。     

双舰编队协同制导防空作战的动态拦截排序问题

针对双舰编队协同制导作战条件下如何对空袭目标进行排序这一问题,依据作战时间给出了排序算法。首先对平台的作战时间进行分析和求解,将射击周期分成了2段,把静态拦截排序问题转化为了2台处理机的同顺序作业排序问题,然后根据输入信息的改变而不断调整空袭目标的顺序以解决动态拦截排序问题,最后在想定条件下仿真计算,结果表明该算法具有较好的适用性。