片上网络中一种单周期2GHz无缓冲路由器

近年来,无缓冲路由器由于不需要缓冲器而成为片上网络低开销的解决方案。为了提高无缓冲路由器的性能,提出一种单周期高性能无缓冲片上网络路由器。该路由器使用一个简单的置换网络替换串行化的交换分配器与交叉开关以实现高性能。虚通道路由器与基准无缓冲路由器相比,该路由器在TSMC65nm工艺下可以以较小的面积开销达到2GHz的时钟频率。在合成通信负载与真实应用负载下的模拟结果表明,该路由器的包平均延迟远小于虚通道路由器和其他无缓冲路由器。     

基于复杂网络的联合作战指挥体系研究

以作战指挥理论需求为牵引,从复杂网络的角度对联合作战指挥体系问题进行网络抽象,将指挥体系中的指挥机构作为网络的节点,将指挥关系作为网络的边,按照指挥体系历史发展的规律,从简单到复杂,分别构建了传统层级纵长树状型的指挥体系网络模型,在树状模型基础上,增加了横向联系但依然具有层级结构的信息共享改进型的指挥体系网络模型,以及...     

直升机装备子母弹对坦克群作战的效能分析

分析了几个影响坦克威胁程度的主要因素,采用新的归一化效用函数法,对各目标的威胁程度进行评估,确定智能子母弹的攻击瞄准点.然后建立智能子母弹对目标攻击过程的数学模型及毁伤概率的计算模型,通过蒙特卡洛方法计算各目标命中的子弹数目.综合目标的特性进行多次仿真,得出了子母弹对整个坦克群目标的作战效能.最后模拟实现了整个攻击过程...     

扩展信念网络模型的军事情报检索系统设计

着眼信息化战争条件下军事情报分类、处理困难的现实,在深入分析军事情报检索系统特点基础上,提出一个基于分类的自动存储和利用查询术语同义词关系扩展信念模型的检索军事情报检索原型系统,详细描述了其存储和检索设计思路.     

无线Mesh网络技术研究

无线Mesh网络是新近出现的一种无线多跳网状拓扑网络,在多领域被广泛的应用。简要介绍了无线Mesh网络的结构、特点及应用,并重点分析了影响无线Mesh网性能的主要技术因素。     

IED casualties mask the real problem: it's us

Casualty figures suggest that the US/Allied Counter Improvised Explosive Device (C-IED) policy and the present allocation of national assets, resources, and intellectual capital have not been very successful. A number of explanations for why this has been the case are discussed and critiqued here.     

Crime facilitation purposes of social networking sites: A review and analysis of the ‘cyberbanging’ phenomenon

There have been growing claims in media circles and law-enforcement settings that street gangs and criminal groups are turning to Internet-based social networking sites for various reasons ranging from the showcasing of their images and exploits to the suspected recruitment of members. The present study investigates whether such a trend is, in fact, in place. The presence of street gangs on these Internet sites is referred to as cyberbanging. While there is some anecdotal evidence suggesting that gangs are turning to social networking sites, there is little available research on exactly how street gangs and criminal groups use the Internet. Our main argument is that gang culture is in many ways an individualized phenomenon and this feature ties in directly with recent assessments of the Internet as a setting that is governed by a process of networked individualism. This theoretical link between the individualized gang setting and the presence of gang members on social networking sites helps us understand why recruitment is improbable even in a context where people are openly diffusing their image and exploits to a growing number of Internet users. The empirical segment of this research adds to this general outlook. Based on a keyword search of over 50 street gang names, the three main social networking sites (Twitter, Facebook, and MySpace) were monitored for street gang presence. Results illustrate that gang presence on social networking sites is linked primarily to promoting a general gang or street culture through individual displays. In regard to the visitors to such sites, there is no evidence that they are being tricked or manipulated in any way. They are, however, showing their curiosity in regard to such groups and, for those who share their comments and opinions, signs of support are evident. Thus, whereas criminal gangs are not proactively using the Internet to convert anyone into being gang members, social networking sites are creating a new venue for people who share or are sensitive to the values underlying street gang lifestyle to come together. These sites essentially create a new convergence setting for gang members to interact with a wider number of people who would probably never have been exposed to their lifestyles and exploits through physical interactions. The study's conclusion extends these findings toward further research in this area, as well as outlining the more relevant implications for law-enforcement monitoring of this growing phenomenon.     

信息推荐系统中的朋友关系预测算法设计

伴随着互联网规模的不断扩展,信息过载问题越来越突出。信息推荐系统被视为解决信息过载问题的最有效方法。然而目前的方法大多数仅考虑用户独立的反馈,而忽略用户的社会属性对推荐的重要作用,这对信息推荐系统的性能会造成巨大的影响。为此,本文提出了基于朋友关系预测的信息推荐算法,将用户的社会关系预测引入信息推荐过程中,分别基于用户的拓扑信息及历史交互信息建立用户社会关系的存在性判定及关系类型判定,并利用线性回归分析方法和逻辑回归分析方法实现了基本特征的融合。最后,通过在Epinions和Slashdot真实数据集上的实验证明,本方法能够有效提高用户社会关系预测的准确性。     

PHEV电池电荷状态估计设计及仿真

电池管理系统(battery management system,BMS)是混合动力汽车(parallel hybrid electric vehicle,PHEV)能量管理系统中的核心组成部分,而其中电池电荷状态(state of charge,soc)则是PHEV控制策略中的重要参数.针对PHEV动力电池组SOC系统高度非线性和复杂性的特点,提出了一种基于改进的BP神经网络的HEV动力电池组的实时SOC估计,并对网络的收敛性进行了证明.利用大量PHEV动力电池组在行驶过程中充放电的数据样本,对神经网络进行网络训练并且进行仿真.结果表明,与传统离线SOC估计方法相比,能够有效地减小误差,提高电池SOC的精度.     

人工神经网络的装甲兵体系作战协同效果评估

针对基于信息系统的装甲兵体系作战中的协同问题,在综合分析装甲机械化部队体系作战协同过程及信息流程的基础上,构建了基于精确性、有序性、灵活性、时效性等原则的协同效果评估指标体系,采用基于人工神经网络的多指标综合评价方法,建立基于BP神经网络的综合评价模型,并结合实证分析,利用MATLAB软件进行仿真计算,为装甲兵体系作战协同效果评估提供了较好的途径,为装甲兵指挥员更加合理地组织信息化条件下体系作战协同提供决策依据.