聚丁二烯/聚甲基丙烯酸甲酯接枝共聚物的合成及表征

以顺酐为“桥连剂”,通过顺酐与端羟基(PMMA)的酯化反应,合成了大分子表面改性剂聚丁二烯/聚甲基丙烯酸甲酯接枝共聚物。探索了反应规律,并用IR、NMR、TGA对其结构和热性能进行表征。结果表明:接枝共聚物的热稳定性随着PMMA含量及侧链PMMA长度的增加而下降,接枝共聚物具有良好耐热性和择优表面迁移特性,适合于作为聚丙烯的大分子表面改性剂。     

中国传统建筑的屋顶文化

当屋顶作为建筑重要的语言形式时,建筑不单是一种形式,更是一种艺术与文化．对中国传统屋顶的形式与特点进行了阐述,并充分挖掘了封建社会等级制度下建筑所蕴藏的文化内涵,这些都值得现代建筑借鉴与发扬．     

利用蜜罐技术架构网络战训练虚拟靶场环境

从蜜罐技术的分类与功能出发,结合网络战虚拟靶场环境建设的目标,探讨了蜜罐技术在虚拟靶场中运用的具体设计与构建.讨论了用蜜罐技术架构网络战虚拟靶场环境的设计要素,给出了相应的模块结构图.在目前流行的蜜罐技术基础上,利用相关工具软件设计了用一个蜜网构成的网络战虚拟靶场环境.     

主链型不饱和聚磷酸酯交联体系体外降解性能

研究了主链重复结构单元中含富马酸酯的不饱和聚磷酸酯（UPPE）与N-乙烯基吡咯烷酮（NVP）交联体系的体外降解过程,采用扫描电镜观察了降解一定时间后试样断面的形态结构．结果表明：交联体系试样是按照先表层、后中心。由外至内的规律进行降解,降解过程包括表层扩散溶出和基体降解两部分．在表层扩散溶出占主导阶段。交联试样中聚乙烯基吡咯烷酮（PVP）和NVP快速溶出,试样失重明显,试样吸水率、长度、直径也迅速增大;在基体降解占主导阶段,试样降解比较缓慢,试样失重、吸水率、长度和直径变化较小．     

高频PWM DC/DC 转换器设计

设计了一种基于2．5μm 40V双极工艺的高频低功耗的PWM升压型DC／DC转换芯片．采用了恒定频率、电流模式的控制结构以提供优秀的电源和负载稳压．同时内部的电流监视电路可以保护功率开关以及连接到芯片上的外部元件．通过对开关脉冲宽度的调节,加快了升压速度,减小了稳压状态的输出纹波,提高了转换效率．仿真结果表明,在2．7～12．0V的输入电压范围内,芯片的开关频率为1．2MHz,开关电流限制值为1．2A,转换效率可达85％以上．使用很小体积的外围元件就可获得满意的输出纹波,在很小的电路板面积上产生大电流输出,降低了电路尺寸和成本．     

考虑关键性的多约束下辐射干扰对消装备随舰备件配置优化方法

可用度是评估备件对装备完好性影响的重要指标,针对备件关键性对装备可用性造成影响而又难以将其考虑在内建立可用度模型的问题,以舰载通信电台辐射干扰对消装备为对象,采用对备件关键性实行专家打分的方法,将备件关键性作为备件配置优化的约束之一,建立以备件费用、备件体积、备件关键性为约束的备件配置优化模型。在备件费用、体积及关键性归一化的基础上,采用权重因子方法将多约束转化为单一约束,并给出了权重因子更新方法。列举案例,分别计算了费用约束、体积约束、关键性约束和多约束下的备件方案,并对比了装备改进前后的备件配置方案,将装备使用过程中的备件保障延伸至装备可靠性设计阶段。案例分析结果表明:备件配置方法在考虑了体积、费用等限制约束下,能同时兼顾备件关键性对装备完好性的影响;装备可靠性设计时,提高装备可靠性低的现场可更换单元(line replaceable unit, LRU)等薄弱点,能有效减少装备维修保障资源。     

基于概率图的作战任务智能规划方法

针对人工调配作战资源及规划方案效率低下的问题,本文提出一种基于概率图的作战任务智能规划方法,通过统计分析判定任务间因果关系,采用GNN抽取任务中的关键事件构建概率图并计算任务规划方案成功的概率,进而基于时间序列方法预测战场态势变化,实现辅助指挥员智能决策。最后,本文在某联合登岛案例中开展了方法验证,结果表明,所提出的方法可成功实现任务规划并具有可解释性,可实现对战场态势变化的预测和快速响应,在战场上为军队提供强有力的支持。     

Adaptive Control of the Structural Balance for a Class of Complex Dynamical Networks

In social networks, the structural balance is a state of a group of individuals(nodes) with established mutual relationships(connection relationships) between them. It is easy to see that a social network can be described by a complex dynamical network model composed of the nodes subsystem(NS) and the connection relationships subsystem(CS), where the two subsystems are usually coupled with each other. It implies that the dynamic changes of nodes' states may cause the structural balance in CS. However, few papers have discussed the relationship between the structural balance and the specific dynamic changes of the nodes' states. This paper proposes a model of complex dynamical networks, and mainly focuses on the dynamic changes of states in NS which can lead to the structural balance in CS. It is proved that if each state in NS is doing a specific dynamic motion via the controller with the parameter adaptive law, then the CS can track a given structural balance matrix via the effective coupling and the structural balance can be achieved. Such a result can be regarded as an explanation of the relationship between the structural balance and the specific dynamic changes of the nodes' states. Finally, the simulations verify the effectiveness of the proposed method.     

物联网中区块链技术的应用与挑战

随着物联网技术的快速发展和广泛应用,分布式网络环境下的身份验证、数据隐私、网络安全等问题变得更加重要,而这些问题可以通过引入区块链技术来得到有效解决.该文简述了区块链的基本概念,介绍了区块链在物联网中的应用场景,并对当前一些相关工作的成果进行了综述;介绍了针对物联网场景下区块链底层技术的研究以及区块链物联网所面临的问题与挑战,希望能对未来区块链物联网的研究有一定的参考价值.     

The industrial asymmetry of the stock price prediction with investor sentiment: Based on the comparison of predictive effects with SVR

As a representative emerging financial market, the Chinese stock market is more prone to volatility because of investor sentiment. It is reasonable to use efficient predictive methods to analyze the influence of investor sentiment on stock price forecasting. This paper conducts a comparative study about the predictive performance of artificial neural network, support vector regression (SVR) and autoregressive integrated moving average and selects SVR to study the asymmetry effect of investor sentiment on different industry index predictions. After studying the relevant financial indicators, the results divide the Shenwan first-class industries into two types and show that the industries affected by investor sentiment are composed of young companies with high growth and high operative pressure and there are a great number of investment bubbles in those companies.