Transnational terrorism as a spillover of domestic disputes in other countries

This paper models transnational terrorism as a three‐way strategic interaction involving a government that faces armed opposition at home, which may spill over in the form of acts of terrorism by the state's opponents against the government's external sponsor. The external sponsor also utilises deterrence against potential terrorists, which only lowers terrorism if terrorists are not intrinsically motivated by a deep‐seated sense of humiliation. The model highlights the importance of intrinsic motivation. A rise in the external power's preference for deterrence against terrorism may backfire in these circumstances. Increases in the government's military efficiency against the rebels, who are also terrorists against the government's sponsor, raises overall levels of violence.     

Interval scheduling: A survey

In interval scheduling, not only the processing times of the jobs but also their starting times are given. This article surveys the area of interval scheduling and presents proofs of results that have been known within the community for some time. We first review the complexity and approximability of different variants of interval scheduling problems. Next, we motivate the relevance of interval scheduling problems by providing an overview of applications that have appeared in literature. Finally, we focus on algorithmic results for two important variants of interval scheduling problems. In one variant we deal with nonidentical machines: instead of each machine being continuously available, there is a given interval for each machine in which it is available. In another variant, the machines are continuously available but they are ordered, and each job has a given “maximal” machine on which it can be processed. We investigate the complexity of these problems and describe algorithms for their solution. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

基于时变量测方差的多传感器多目标优化分配算法

在目标跟踪过程中,目标的动态模型通常在笛卡尔坐标系中,而量测是在极/球坐标系中得到的。在基于卡尔曼滤波及其一些改进算法中,设定量测方差固定不变,可能导致滤波发散。为此提出了一种基于时变量测方差的多传感器资源管理算法。该算法通过统计方法求出转换测量值误差的均值和方差,利用转化卡尔曼滤波算法估计误差协方差,基于协方差的效能函数进行多传感器多目标分配。仿真结果显示该算法在目标跟踪过程中满足跟踪精度要求,并实现传感器资源的充分的利用。     

保证率点值区间估计的Monte-Carlo方法

提出了一种根据实测样本系列对保证率点值进行区间估计的Ｍｏｎｔｅ─Ｃａｒｌｏ方法。对于具有正态分布或对数正态分布的样本,首先推出总体参数的分布,然后用Ｍｏｎｔｅ─Ｃａｒｌｏ法生成总体参数系列,据此求得相应的保证率点值系列,最后通过经验分布推得在给定置信度下保证率点值的区间估计,本文还给出了一个算例。     

改进的精密三点法——在线测量直线度方法的再探讨

在原精密三点法的基础上,对插值方法进行了改进,对随机误差采用了相应的数据处理方法,使得分离结果更加接近真实值,并有效地去除了随机误差的影响,得到了采样值加密的曲线,文中给出了改进的精密三点法的算法和流程图。从仿真和实验结果来看,该方法是具有可行性和可靠性的。     

C76、C78、C82、C84和C90的π电子磁化率

采用规范不变分子轨道方法,计算了Ｄ_２—Ｃ_（７６）、Ｃ_（２ｖ）￣－和Ｄ_３—Ｃ_（７８）、Ｃ_２—Ｃ_（８２）、Ｄ_２—和Ｄ_（２ｄ）—Ｃ_（８４）以及Ｃ_２—Ｃ_（９０）的л电子磁化率。其结果表明这些纯碳原子团簇分子具有较大的抗磁磁化率。反映出这些分子具有一定的芳香性及其л电子有较大的共有化运动程度。     

比例最小偏度单形UKF的RBF神经网络算法

为提高RBF神经网络的建模性能,提出一种基于改进无迹Kalman滤波(UKF)的RBF神经网络训练算法。在该算法中,首先将比例最小偏度单形Sigma点采样策略引入UT,以有效改进UKF,提升其计算效率,然后利用改进的UKF优化估计RBF神经网络的最优参数。仿真结果表明,改进的UKF比EKF具有更高的RBF神经网络模型训练精度,与传统UKF的模型精度大体相当,但速度更快,计算效率更高。     

隔离型DC/DC变换器的嵌入式滤波设计

传统的隔离型DC/DC变换器输入端电流断续,会对电源或负载产生严重的电磁干扰,利用嵌入式滤波(Built-in Input Filter,BIF)的方法可以实现输入电流的连续。以嵌入式滤波全桥为例对嵌入式滤波的原理进行了分析,提出了隔离型DC/DC变换器嵌入式滤波拓扑、变压器以及交叉耦合电容参数的设计方法,并用该方法推导和设计了带有嵌入式滤波功能的半桥拓扑,利用PSIM软件进行了仿真分析。搭建了新型半桥拓扑的试验样机,验证了设计方法的有效性。     

装甲车辆驾驶动作模糊模式识别研究

针对装甲车辆驾驶技能等级评判系统中,如何将驾驶训练过程中采集的驾驶动作数据还原成实际驾驶操作动作的瓶颈问题,采用模糊模式识别的方法,实现了对无限长待识序列数据的识别,并通过对实车采集数据的分析,验证了识别的有效性和准确性。     

柴油机运行参数对颗粒过滤器压降特性影响的试验研究

基于排气背压的柴油机颗粒过滤器(Diesel Particulate Filter,DPF)再生时机判断是DPF后处理系统的关键。针对壁流式过滤器,采取理论与试验相结合的方法,研究了柴油机不同的排气流量、温度以及DPF加载水平对过滤器压降特性的影响规律。结果表明:压降随温度升高基本成线性增长;随流量增加基本成二次方增长;随碳烟加载量的增加而增长的趋势是曲线斜率先大、后小、再增大。随后分析了排气背压和流量、温度以及碳烟加载量之间的数学关系。研究对于准确判断车载DPF的再生时机,进一步提升DPF后处理系统性能具有一定的指导意义。