大学生优柔寡断、适应性、自我调节学习与学业拖延的关系研究

研究旨在探索优柔寡断人格、适应性、自我调节学习与大学生学业拖延的关系,揭示学业拖延的影响机制,对大学生学业拖延的干预提供启示。选取1654名大学生开展了问卷调查,结果显示:(1)大学生学业拖延行为在中等偏下水平,学业拖延改变倾向在中等偏上水平,功能性拖延水平在中等水平;(2)优柔寡断与拖延行为呈正相关,情感适应性、自我效能与拖延行为呈负相关;优柔寡断、自我调节策略与拖延行为改变倾向呈负相关,适应性、认知策略与拖延行为改变倾向呈正相关;优柔寡断与功能性学业拖延呈负相关;自我调节学习与功能性学业拖延呈正相关;(3)大学生适应性在优柔寡断影响一般学业拖延行为中起到中介作用;自我调节学习、适应性在优柔寡断影响拖延行为改变倾向中起到中介作用;自我调节学习在优柔寡断影响功能性学业拖延中起到中介作用。     

高级在轨系统的自相似业务量预测链路优化模型

在AOS高级在轨系统链路协议的基础上,分析了具有自相似特性的业务流量,提出了一种基于FARIMA模型的自相似预测的链路优化模型。该预测模型基于分数阶统计理论,在估计赫斯特参数的基础上,根据不同的时间粒度,提前预测突发业务量的到来,从而降低了网络丢包率。仿真表明模型在20点预测内具有较好拟合性,在一定置信区间下具有较好的预测成功概率和较低的虚警概率,同时使网络丢包率大幅下降。     

异步非平稳干扰抑制方法

为解决单通道条件下异步非平稳干扰抑制问题,提出基于数据驱动的稀疏分量分析干扰抑制方法,旨在从接收到的混叠信号中恢复期望信号。该方法利用深度卷积神经网络对输入/输出端数据间的复杂映射关系的强大建模能力,实现了目标信号稀疏域的自适应选择、稀疏域中目标信号稀疏表示的自适应学习以及目标信号的自动恢复。与以往干扰抑制算法不同,所提方法在时域上完成了“端到端”的信号波形恢复,且对混叠观测无先验要求,相比现有方法更具普适性。仿真实验验证了所提干扰抑制方法在不同环境噪声和干扰信号强度及泛化测试条件下的有效性,对干扰的抑制性能显著优于现有算法。     

基于网络结构的武器装备体系能力分析

现代战争以及从"平台为中心"转向以"网络为中心",强调的是通过各类武器平台通过相互之间的协作配合而形成作战网络来实现体系能力。从宏观和微观两个角度分析了武器装备体系能力的实现机理,构建了武器装备体系的作战网络结构模型,给出了作战网络结构模型中的节点类型和关系类型,提出了能力环的概念,从作战网络结构的角度对武器装备体系的整体能力进行了分析,并给出了具体算例。     

一类非线性系统的自适应模糊反推近似滑模控制

针对一类含有未知非线性函数项和外界干扰的不确定纯反馈非线性系统,提出了一种自适应模糊反推近似滑模变结构控制方法。采用中值定理和隐函数定理使未知非仿射输入函数拥有显式的控制输入,利用模糊系统逼近未知非线性函数,动态面控制技术解决了反推设计中出现的"微分爆炸"问题。所提出的自适应近似滑模控制方案削弱了传统滑模控制中的抖振现象。从理论上证明了所设计的控制器能够保证闭环系统所有信号半全局一致终结有界。仿真算例验证了算法的有效性。     

Nuclear deterrence and cyber warfare: coexistence or competition?

Nuclear deterrence and cyber war seem almost antithetical in their respective intellectual pedigrees. Nuclear weapons are unique in their ability to create mass destruction in a short time. Information or “cyber” weapons, at least for the most part, aim at sowing confusion or mass disruption instead of widespread physical destruction. Nevertheless, there are some intersections between cyber and nuclear matters, and these have the potential to become troublesome for the future of nuclear deterrence. For example, cyber attacks might complicate the management of a nuclear crisis. As well, information attacks on command-control and communications systems might lead to a mistaken nuclear launch based on false warnings, to erroneous interpretations of data or to panic on account of feared information blackout. It is not inconceivable that future nuclear strike planning will include a preliminary wave of cyber strikes or at least a more protracted “preparation of the battlefield” by roaming through enemy networks to plant malware or map vulnerabilities.     

Sharp bounds for the reliability of systems and mixtures with ordered components

In this article, we study how to derive bounds for the reliability and the expected lifetime of a coherent system with heterogeneous ordered components. These bounds can be used to compare the performance of the systems obtained by permuting the components at a given system structure, that is, to study where we should place the different components at a system structure to get the most reliable system. Moreover, a similar procedure is applied to get bounds for mixtures and for the generalized proportional hazard rate model when the baseline populations are ordered. © 2017 Wiley Periodicals, Inc. Naval Research Logistics 64: 108–116, 2017     

基于稀疏贝叶斯学习的扩展目标雷达关联成像*

雷达关联成像不依赖于雷达与目标的相对运动,是一种高分辨凝视成像方式。传统的关联成像方法未考虑复杂扩展目标的结构信息,在高分辨成像时的应用受到限制,为此提出一种自适应结构配对稀疏贝叶斯学习方法。该算法在稀疏贝叶斯学习的框架内针对扩展目标建立一种结构配对层次化高斯先验模型,然后采用变分贝叶斯期望-最大化算法交替进行目标重构和参数优化。该算法将某一信号分量的重构与周围信号分量联系起来,并能在迭代过程中自适应地调整表征各信号分量相关性的参数。实验结果表明,该方法针对扩展目标可以有效地进行高分辨成像。     

The role and capabilities of major weapon systems transferred between 1950 and 2010: Empirical examinations of an arms transfer data set

Arms transfers provide exporters an avenue to provide security to other states while gaining economic benefits. Arms transfers provide importers an avenue to gain security without having to rely on alliances. Past research uses aggregate measures of the monetary or security value of major weapon system transfers without accounting for strategic differences in possible use in interstate and civil conflict. This article presents a data set on interstate transfers of major weapon systems between 1950 and 2010 building upon Stockholm Peach Research Institute’s Arms Trade Register with several improvements. First, it disaggregates land weapons and air weapons into categories reflecting their strategic capabilities. Second, model level characteristics (e.g. age, speed, and range) are drawn from Jane’s Defence sources. Additionally, the data set covers a larger range of time and states than previous data sets categorizing arms. To demonstrate the usefulness, this article first presents summary statistics of the data set and then replicates an earlier test to show that the effect of human rights and regime types on United States transfers differs across the categories of arms compared to alternative measures of arms transfers.     

基于不稳定性采样的主动学习方法

传统的主动学习方法往往仅基于当前的目标模型来挑选样本,而忽略了历史模型所蕴含的对未标注样本预测稳定性的信息。因此,提出基于不稳定性采样的主动学习方法,依据历史模型的预测差异来估计每个未标注样本对提高模型性能的潜在效用。该方法基于历史模型对样本的预测后验概率之间的差异来衡量无标注样本的不稳定性,并挑选最不稳定的样本进行查询。在多个数据集上的大量实验结果验证了方法的有效性。