Small world,big guns: globalization,interstate security networks and conventional weapons imports

With the burgeoning influence of emerging markets in Asia, a tectonic shift is taking place in the global security landscape. Asian states are concomitantly arming as their economic clout grows. In light of these developments, security analysts would benefit from a formal means of placing these arms acquisitions in a structural context. Are arms acquisitions on par with the expectations of Asian states, given their structural dispositions, or are recent acquisitions beyond anticipated levels? By using a dynamic panel regression of 187 states from 1950 to 2011, this research predicts arms import volume using the degree of interstate arms linkages, the size of a state's military, and its level of economic development. The technique offers analysts a formal means of distinguishing orthodox behavior in importing conventional weapons from extraneous security motivations. The article concludes by generating near-term forecasts of Asian arms imports and discussing the implications of the technique.     

Partial input to output impacts in DEA: Production considerations and resource sharing among business subunits

Data envelopment analysis (DEA) is a methodology for evaluating the relative efficiencies of peer decision‐making units (DMUs), in a multiple input/output setting. Although it is generally assumed that all outputs are impacted by all inputs, there are many situations where this may not be the case. This article extends the conventional DEA methodology to allow for the measurement of technical efficiency in situations where only partial input‐to‐output impacts exist. The new methodology involves viewing the DMU as a business unit, consisting of a set of mutually exclusive subunits, each of which can be treated in the conventional DEA sense. A further consideration involves the imposition of constraints in the form of assurance regions (AR) on pairs of multipliers. These AR constraints often arise at the level of the subunit, and as a result, there can be multiple and often inconsistent AR constraints on any given variable pair. We present a methodology for resolving such inconsistencies. To demonstrate the overall methodology, we apply it to the problem of evaluating the efficiencies of a set of steel fabrication plants. © 2013 Wiley Periodicals, Inc. Naval Research Logistics, 2013     

抗差最小二乘估计在惯组外场标定中的应用

惯组在外场进行标定时常常会受到环境的振动干扰,从而会对惯组的标定精度造成极大的影响.为解决这一问题,在分析了粗差对惯组标定精度影响的前提下,建立了一种改进的辨识惯组误差系数的数学模型,使其能够分辨出那些受到振动干扰影响的惯组误差系数.最后利用抗差最小二乘估计对惯组误差系数进行处理,通过等价权函数的连续降权和连续减弱影响处理,抵制了异常数据对惯组标定精度的影响.仿真结果表明,抗差最小二乘估计具有很强的抗差能力,能有效减弱异常干扰对参数估计的影响,提高惯组外场标定的精度和数据的可靠性.     

基于波导干涉条纹的目标距离特征量提取方法

浅海波导中目标辐射噪声LOFAR谱图存在明暗相间的干涉条纹,从中可以提取出目标距离特征量信息,它反映了目标运动过程中的距离变化率。低信噪比情况下,条纹特征不够清晰,提取的距离特征量值精度会降低。提出了一种边缘定向增强型偏微分方程去噪方法,对LOFAR谱图进行处理,使条纹特征更加明显。海试数据处理结果表明,去噪处理后提取出的距离特征量精度明显提高。为满足实时性需要,提出了基于CUDA的距离特征量实时处理方法,实验结果表明能大幅提高算法运行速度。     

ANALYSING THE DETERMINANTS OF TERRORISM IN TURKEY USING GEOGRAPHICALLY WEIGHTED REGRESSION

This paper investigates the determinants of provincial terrorism in Turkey taking spatial dimension into account for the time period 1990–2006. Following a traditional global regression analysis, spatial variations in the relationships are examined with geographically weighted regression (GWR) to obtain locally different parameter estimates. Empirical results indicate that increases in income and schooling ratio tend to reduce the provincial average level of terrorism, whereas an increase in unemployment enhances it. Moreover, GWR results indicate that the provincial effects of per capita income and education are more pronounced for the Eastern and South Eastern provinces compared to the Western provinces.     

Economic Performance And Terrorist Activity In Latin America

We investigate the link between economic performance and terrorism for 18 Latin American countries from 1970 to 2007, taking into account the potentially complex nature of this link. Panel causality analysis findings indicate that during this period, terrorism had no causal effect on economic growth. By contrast, we find that growth reduced terrorism in the less developed but not in the higher developed Latin American economies. We argue that group-specific differences (linked to patterns of economic development) govern this causal heterogeneity. From a series of negative binomial regressions we gain additional support for our findings, while also identifying further determinants of terrorism.     

基于统计回归模型的突发事件网络舆情研究

突发事件网络舆情传播速度快,在较短的时间内能够引起社会大众的广泛关注,产生较大的影响.通过利用突发事件网络舆情传播规律和酶促反应相似的机理,构建统计回归模型来研究分析突发事件网络舆情的规律,并通过实例进行论证,以期为政府应对突发事件网络舆情提供参考.     

Sequential learning versus no learning in Bayesian regression models

We consider two regression models: linear and logistic. The dependent variable is observed periodically and in each period a Bayesian formulation is used to generate updated forecasts of the dependent variable as new data is observed. One would expect that including new data in the Bayesian updates results in improved forecasts over not including the new data. Our findings indicate that this is not always true. We show there exists a subset of the independent variable space that we call the “region of no learning.” If the independent variable values for a given period in the future are in this region, then the forecast does not change with any new data. Moreover, if the independent variable values are in a neighborhood of the region of no learning, then there may be little benefit to wait for the new data and update the forecast. We propose a statistical approach to characterize this neighborhood which we call the “region of little learning.” Our results provide insights into the trade‐offs that exist in situations when the decision maker has an incentive to make an early decision based on an early forecast versus waiting to make a later decision based on an updated forecast. © 2014 Wiley Periodicals, Inc. Naval Research Logistics 61: 532–548, 2014     

局部状态检测的GPS/INS组合导航转发式干扰检验方法

针对GPS/INS(Global Positioning System/Inertial Navigation System)组合导航中GPS转发式干扰问题,在分析故障变化特性与故障诊断函数特性之间关系的基础上,提出了一种基于局部状态χ2检验的方法。通过观测值的变化、观测模型的变化和χ2检验中x赞1k的变化论证了方法的可行性,并得出组合导航受到转发式干扰是判断系统发生故障的充分而非必要条件的结论。最后通过在仿真轨迹中加入诱偏来模拟转发式干扰,仿真实验证明该方法能够以较高的灵敏度和较高的准确性判断转发式干扰的发生。     

军用飞机燃油消耗多元线性回归模型

为了解决军用飞机非标准动作燃油消耗建模问题,利用实际飞参数据,采用多元线性回归方法进行建模分析。建立了燃油消耗量与飞行时间、油箱平均油量、平均高度、平均速度、T1温度、T4温度、N2转速、高度变化量、飞机外挂的多元线性回归模型,并对回归模型进行统计性检验和验证。结论显示:模型拟合度较好,符合军用飞机飞行耗油规律,对军用飞机非标准动作燃油消耗规律研究具有重要意义。