日常交互中朋友关系强度度量方法

针对如何度量日常生活中人们之间的关系强度问题展开研究,提出一个从日常轨迹、语义位置以及语义标签三个层次度量朋友之间关系强度的层级模型FRSHV。采用动态时间规整模型通过计算朋友之间的空间距离来度量其日常轨迹之间的相似度,进而使用轨迹序列熵值对用户每天轨迹的相似度进行加权处理,将其作为朋友之间的关系强度;采用主题模型隐含狄利克雷分布分别计算朋友之间的基于语义位置和语义标签的行为模式的相似性,将其作为朋友之间的关系强度;采用集成学习的思想对三个层次的度量结果进行投票,以投票结果作为最终的朋友之间的关系强度。在公开数据集上对FRSHV模型的有效性进行实验验证,结果表明该模型能够有效地度量朋友之间的关系强度。     

文本情报信息筛选与聚类的一种处理方法

目前大数据时代情况下的信息有文本、图像、语音和视频等多种形式,而且信息的容量非常大,怎样高效、正确地筛选、分类和处理、利用这些信息,为决策者提供指挥与控制的科学依据显得尤为重要。据此对文本情报信息提出了一种文本聚类的特征选择以及特征变换的方法,利用单词在文本中的出现次数的概率来选择参与聚类的单词,并且对单词出现概率模型定义了特征变换函数,提高了文本信息的筛选、分类和处理的精度,能快速、准确地提取所需要的情报信息提供给指挥与控制的决策者参考、使用。     

Does defence expenditure have a spillover effect on income inequality? A cross-regional analysis in China

China’s defence expenditure has been growing rapidly along with GDP growth during the past two decades. Meanwhile, the income gap has continued to increase. There are conflicting views regarding whether the defence expenditure is capable of reducing income inequality. Therefore, this paper investigates the existence of any spillover effect of defence expenditure on income inequality, with a special focus on the regional differences among 31 provinces and 7 military regions in China. We extend panel cointegration and the impulse response function by using panel data during the period of 1997–2012. The empirical results show that the defence expenditure has an impact on income inequality, and the effect varies over different regions in China. The defence expenditure has a spillover effect on income inequality in the full sample panel and the southeastern panel. An increase in the defence expenditure does not crowd out social welfare spending due to the high level of economic development and government expenditure. On the contrary, in the northern panel, the effect is opposite because of the unbalanced economic development levels within the panel. Beijing as the capital of China, benefits more from the expansion of defence expenditure thus widening the income gap. In addition, the impulse response analyses further confirm a stronger effect of the defence expenditure on income inequality in the northern and the southeastern panels over a short period.     

图像融合的客观质量评估

随着图像融合技术在武器自动化系统中的广泛应用,图像融合的质量评估问题,即图像融合的性能评估问题,在融合方案的选择中具有重要地位。由于人工主观的图像融合评估具有很大的工程化和自动化难度,国际上研究人员都将研究目标投向了客观图像融合质量评估的研究中。从历史发展的角度系统地回顾了客观图像融合质量评估的发展历程和研究现状,对近十年来的客观图像融合质量评估方法进行了分类和分析。同时,对于国际上几种流行的图像融合质量评估方法的性能测定思路进行了介绍。对于图像融合质量评估现状的分析和讨论有助于我们对图像融合的质量评估方法进行更深入的研究。     

LEACH—DRT算法中基于神经网络的数据预测算法

为了保证无线传感器网络中数据的完整性,针对基于LEACH路由协议的动态轮时间算法存在的问题,提出一种基于人工神经网络的数据预测算法。该动态轮时间算法中,部分簇因调整后的轮时间不足以完成数据的采集而丢失数据。数据预测算法结合传感器节点数据具有时空相关性的特点,将时空延迟算子引入神经网络模型,并通过建立的神经网络模型对数据进行预测。仿真时采用伯克利英特尔实验室的传感器数据,通过Mafl软件对模型进行测试并分析仿真结果。实验结果表明：该算法对连续多个数据的预测效果理想,预测误差始终保持在较低水平。     

军用电子机箱模态分析及测试

对某军用电子机箱的固有频率从有限元分析和模态试验测试两个方面进行研究,并将理论分析结果和模态试验测试结果进行对比,确定了电子机箱的固有模态.为今后电子机箱的设计提供了参考依据,为仿真分析提供了有效的有限元建模方法.     

Numerical investigation of the shockwave overpressure fields of multi-sources FAE explosions

Shockwaves from fuel-air explosive (FAE) cloud explosions may cause significant casualties. The ground overpressure field is usually used to evaluate the damage range of explosion shockwaves. In this paper, a finite element model of multi-sources FAE explosion is established to simulate the process of multiple shockwaves propagation and interaction. The model is verified with the experimental data of a fourfold-source FAE explosion, with the total fuel mass of 340 kg. Simulation results show that the overpressure fields of multi-sources FAE explosions are different from that of the single-source. In the case of multi-sources, the overpressure fields are influenced significantly by source scattering distance and source number. Subsequently, damage ranges of overpressure under three different levels are calculated. Within a suitable source scattering distance, the damage range of multi-sources situation is greater than that of the single-source, under the same amount of total fuel mass. This research provides a basis for personnel shockwave protection from multi-sources FAE explosion.     

基于深度强化学习的无人战车自主行为决策

针对高动态强对抗战场环境下,无人战车面临的自主行为决策问题,分析了未来陆战场无人战车实际作战需求,构建了基于马尔可夫决策过程的自主行为决策模型,提出了一种深度强化学习结合行为树的方法,利用行为树的逻辑规则与先验知识降低强化学习问题的难度,保证收敛性和鲁棒性,同时使行为决策模型具有学习能力.构建典型作战场景,验证深度强化学习结合行为树的无人战车自主行为决策方法的有效性.     

Effects of total pressures and equivalence ratios on kerosene/air rotating detonation engines using a paralleling CE/SE method

In this paper, the kerosene/air rotating detonation engines(RDE) are numerically investigated, and the emphasis is laid on the effects of total pressures and equivalence ratios on the operation characteristics of RDE including the initiation, instabilities, and propulsive performance. A hybrid MPI + OpenMP parallel computing model is applied and it is proved to be able to obtain a more effective parallel performance on high performance computing(HPC) systems. A series of cases with the total pressure of 1 MPa, 1.5 MPa, 2 MPa, and the equivalence ratio of 0.9, 1, 1.4 are simulated. On one hand, the total pressure shows a significant impact on the instabilities of rotating detonation waves. The instability phenomenon is observed in cases with low total pressure (1 MPa) and weakened with the increase of the total pressure. The total pressure has a small impact on the detonation wave velocity and the specific impulse. On the other hand, the equivalence ratio shows a negligible influence on the instabilities, while it affects the ignition process and accounts for the detonation velocity deficit. It is more difficult to initiate rotating detonation waves directly in the lean fuel operation condition. Little difference was observed in the thrust with different equivalence ratios of 0.9, 1, and 1.4. The highest specific impulse was obtained in the lean fuel cases, which is around 2700 s. The findings could provide insights into the understanding of the operation characteristics of kerosene/air RDE.