和谐人生:军队政治工作的价值诉求

军队政治工作就是做人的工作,要把关注广大官兵的“和谐人生”作为基本的价值诉求。军队政治工作应认真引导和帮助广大官兵确立和谐的人生理念,建立和谐的人际关系,调适和谐的心理机能,着力解决人生旅程中的现实问题,不断促进官兵的全面发展。     

一种完全分布式的空间服务及组合模型

针对服务组合中控制流和数据流的不同协调机制,可将组合模型分为4种类型,分别是控制流集中式且数据流集中式、控制流集中式且数据流分布式、控制流分布式且数据流集中式、控制流分布式且数据流分布式.空间服务组合流程需处理较大规模的数据流,采用控制流分布式和数据流分布式的协调机制能有效降低组合过程中系统整体通信规模并减少空间服务组合响应时间.通过对各种不同组合类型建模的定量分析对上述观点进行了正确性论证.模拟实验证明,定量分析结果可信.     

A model of supply-chain decisions for resource sharing with an application to ventilator allocation to combat COVID-19

We present a stochastic optimization model for allocating and sharing a critical resource in the case of a pandemic. The demand for different entities peaks at different times, and an initial inventory for a central agency are to be allocated. The entities (states) may share the critical resource with a different state under a risk-averse condition. The model is applied to study the allocation of ventilator inventory in the COVID-19 pandemic by FEMA to different U.S. states. Findings suggest that if less than 60% of the ventilator inventory is available for non-COVID-19 patients, FEMA's stockpile of 20 000 ventilators (as of March 23, 2020) would be nearly adequate to meet the projected needs in slightly above average demand scenarios. However, when more than 75% of the available ventilator inventory must be reserved for non-COVID-19 patients, various degrees of shortfall are expected. In a severe case, where the demand is concentrated in the top-most quartile of the forecast confidence interval and states are not willing to share their stockpile of ventilators, the total shortfall over the planning horizon (until May 31, 2020) is about 232 000 ventilator days, with a peak shortfall of 17 200 ventilators on April 19, 2020. Results are also reported for a worst-case where the demand is at the upper limit of the 95% confidence interval. An important finding of this study is that a central agency (FEMA) can act as a coordinator for sharing critical resources that are in short supply over time to add efficiency in the system. Moreover, through properly managing risk-aversion of different entities (states) additional efficiency can be gained. An additional implication is that ramping up production early in the planning cycle allows to reduce shortfall significantly. An optimal timing of this production ramp-up consideration can be based on a cost-benefit analysis.     

基于马尔科夫决策的目标选择策略

目标选择是军事计划的关键要素之一。基于马尔科夫决策方法,解决具有复杂目标间关联的多阶段目标选择问题。使用与或树描述目标体系各层状态间的影响关联,并以目标体系整体失效为求解目的,建立了基于离散时间MDP的多阶段打击目标选择模型。在LRTDP算法基础上提出一种启发式方法,通过判断从当前目标体系状态到达体系失效状态的演化过程中的可能资源消耗和失败概率,来提供对当前状态的评估值,该方法能有效排除问题搜索空间中不能到达体系失效目的的中间状态,压缩了由于目标间复杂关联而增长的巨大状态空间。用实验验证了该方法有效性,实验结果表明,该方法直观实用,对目标间具有复杂关联关系的目标打击决策有一定参考价值。     

不确定数据流多维建模方法*

由于不确定数据流应用的出现,给传统的精确、静态数据环境下的多维建模带来了巨大挑战。针对不确定数据流动态、无限和不确定等特征,提出了一种不确定数据流多维模型。该模型中引入了不确定对象来描述不确定事实元组,并且通过定义时间维度的层次时间窗口,很好地反映了数据流的动态性和无限性,最后还对此多维不确定数据流模型的基本代数操作和分析代数操作进行了形式化定义,为不确定数据流多维查询与分析提供了理论依据。     

航空时敏制导炸弹增程弹道组合优化设计

为增强航空时敏制导炸弹在中制导段的滑翔能力,将极小值原理与自适应进化粒子群算法相结合,提出了一种适用于航空时敏制导炸弹增程弹道的组合优化设计方法。基于纵向平面内质心运动模型,推导了性能指标泛函及各不等式约束函数。引入Lagrange乘子矢量并建立相应的Hamilton函数实现无约束泛函极值问题的转换,推导出兼顾各优化目标函数的满意优化模型。利用自适应进化粒子群算法对该段增程弹道进行了攻角与弹翼张合档位双设计变量的组合优化。数值仿真算例表明,在满足状态方程约束的条件下,双变量的增程效果比常规单变量控制时显著提高,其优化结果可为制导炸弹弹道规划设计的研究提供一定的理论参考。     

努力争当知识型开拓型有为型自律型领导型干部

在新的历史起点上,我们的干部要努力争当学习力强、知识面广、业务上精的知识型干部;争当视野开阔、勇于创新、充满激情的开拓型干部;争当心无旁骛想干事、素质过硬能干事、不辱使命干成事的有为型干部;争当善于律心、心理不失衡,长于律言、言语不失规,严于律行、行为不失范的自律型干部;争当能说会道、让人信服,公道正派、让人诚服,硕果...     

Multi-scale traffic vehicle detection based on faster R-CNN with NAS optimization and feature enrichment

It well known that vehicle detection is an important component of the field of object detection. However, the environment of vehicle detection is particularly sophisticated in practical processes. It is compara-tively difficult to detect vehicles of various scales in traffic scene images, because the vehicles partially obscured by green belts, roadblocks or other vehicles, as well as influence of some low illumination weather. In this paper, we present a model based on Faster R-CNN with NAS optimization and feature enrichment to realize the effective detection of multi-scale vehicle targets in traffic scenes. First, we proposed a Retinex-based image adaptive correction algorithm (RIAC) to enhance the traffic images in the dataset to reduce the influence of shadow and illumination, and improve the image quality. Second, in order to improve the feature expression of the backbone network, we conducted Neural Architecture Search (NAS) on the backbone network used for feature extraction of Faster R-CNN to generate the optimal cross-layer connection to extract multi-layer features more effectively. Third, we used the object Feature Enrichment that combines the multi-layer feature information and the context information of the last layer after cross-layer connection to enrich the information of vehicle targets, and improve the robustness of the model for challenging targets such as small scale and severe occlusion. In the imple-mentation of the model, K-means clustering algorithm was used to select the suitable anchor size for our dataset to improve the convergence speed of the model. Our model has been trained and tested on the UN-DETRAC dataset, and the obtained results indicate that our method has art-of-state detection performance.     

战争观念的语源原型

本文从汉字语源出发,根据荣格心理学的原型观念,通过汉字“战”的语源分析,探寻蕴含在汉字深处(因而也是汉文化底层)的战争观念。文字学认为,“战”()字中单为声符,戈为形符,而作为声符的单系“战”字的隐义,亦即“战”的战争原型。古文字研究表明“单”为鳄类爬行动物,象征着人性中凶猛残暴的兽性;而脑科学研究表明,大脑深处的主管攻击、暴力的部分正是原始脑的“爬虫复合体”(鳄类)。这些研究成果与无意识心理学中的阴影原型(人性中的兽性)不谋而合。因此通过文字学与心理学我们找到了战争冲动的原始意象,也从中发现了相应的化解方法。     

一种能量高效和均衡的无线传感器网络分簇数据融合算法

在无线传感器网络中,如果传感器节点之间的能耗不均衡,一些能耗进度较快的节点会过快失效,继而导致网络过早无法正常工作。为了解决分簇无线传感器网络在数据收集过程中所存在的节点之间能耗不均衡问题,提出了一种新的分簇数据融合算法。该算法将网络划分为大小不等的栅格,并根据剩余能量使簇首分别在每个栅格的节点中轮转。簇首消耗的能量越多,其所在的栅格也越大,栅格内有更多节点参与簇首的轮换以分担能量负载。通过该方式,算法能够提高节点的能耗均衡程度。另外,考虑到无线传感器网络的能量受限,算法还采取了一系列措施以节约能量。仿真实验结果表明,算法在能量使用效率、网络生命周期以及能耗均衡程度三个方面都具有较好的性能。