大振幅波非线性相互作用的谱分解法研究

针对两波非线性相互作用中大振幅波幅度及能量的变化问题,采用了谱分解方法对其进行了研究.对高低频波频率比为整数的两波非线性相互作用情况进行了讨论,研究非线性相互作用中各参数对作用结果的影响,并进行了计算机仿真计算.计算结果表明:在非线性相互作用后,低频波能量随作用距离的增加而降低;能量降低的大小与高低频波频率比、高频波能量大小等因素有关.将两波非线性相互作用的谱分解法计算结果,与经典的Fen lon理论计算结果进行对比,两种方法的计算结果具有较好的一致性.     

应用模糊综合评价法进行城市布局的评判研究

针对城市布局评价问题,讨论了多种评价方法的优缺点,指出了它们各自的适用范围,在此基础上构建了城市布局的评价指标体系,采用模糊综合评价法,对某城市的布局进行了评价,其评价结果可为城市布局提供参考。     

MIG焊电弧声信号采集与分析系统设计

针对目前制约MIG焊熔透状态自适应控制发展而亟待解决的熔透状态信号获取问题,采用图形化编程语言LabVIEW,设计了一套集电弧声信号采集与分析于一体的系统软件.系统具备身份验证、参数配置与记录、采集预览、数据存盘重载、信号降噪以及特征提取等功能.试验表明,该系统能实时高效地完成对电弧声信号的采集、处理和分析,而且实现简单、界面友好、性能稳定可靠,为利用电弧声信号进行熔透状态自适应控制提供理论和应用基础.     

基于距离矢量路由协议的网络故障快速恢复方法

为了有效提高距离矢量路由协议处理网络故障的能力,提高网络的可用性,提出了一种基于 距离矢量路由协议的网络故障快速恢复机制,该机制包括基于预先计算生成的每目的多可行 下一跳的本地重路由策略和基于网络稳定性的触发更新策略. 分析和仿真结果显示,该机制可 以实现距离矢量路由网络的快速故障恢复,并能提高网络的稳定性和可用性.     

与协议无关的Winsock API编程研究

Internet正悄然无声地发生着一项重大的技术革命,这就是IPv4向IPv6的逐步演进。在IPv4／IPv6过渡时期,如何开发出能够适应IPv4／IPv6过渡环境的网络应用程序,这是目前所面临的一个重要问题。本文在深刻理解纯IPv4网络编程和纯IPv6网络编程的基础上,通过比较两者的异同点,抛弃它们的差异性,吸收它们的共同点,实现了一种与协议无关的Winsock API编程方法,并在自行搭建的一个IPv4／IPv6过渡实验平台上,成功开发了一个与协议无关的网络聊天程序,具有很强的实际应用价值。     

树枝状荧光探针设计制备及荧光特性初步研究

树枝状荧光探针是将荧光染料引入树枝状化合物（dendrimer）端基的一类化合物,具有良好的稳定性及光谱特性．笔者以2,2-二甲氧基乙胺为核,采用发散合成法合成了一端含活性氨基的扇形树枝状化合物,并将羧基噻唑橙染料（TO—COOH）引入树枝状化合物的端基,制备出树枝状荧光分子．初步研究了其荧光特性,讨论了反应温度、反应时间等条件对反应收率的影响．     

1-丁基-3-甲基咪唑碘对染料敏化太阳电池的影响

采用季铵化反应合成了1-丁基-3-甲基咪唑碘([Bmim]I).以此制备了DSCs用液体电解质.通过对比不同浓度的1-丁基-3-甲基咪唑碘、碘化钾、碘,研究其对电池性能的影响.经过优化后,当cIL=0.9 mol.L-1、cKI=0.5 mol.L-1、cI2=0.12 mol.L-1时,所组装的离子液体DSCs在AM1.5,100 mW.cm-2下,DSCs的短路电流密度为15.97 mA.cm-2、开路电压为0.71 V、填充因子为0.55、光电转换效率可达6.34%.     

Research on technology of desktop virtualization based on SPICE protocol and its improvement solutions

Increasingly mature cloud computing technology promotes virtual desktop technology, which can solve many problems existing in traditional computing models. However, virtual desktop solutions introduce the thorny problem of how to deliver a real desktop experience to users, as if they are using it locally, especially when playing video. The SPICE （simple protocol for independent computing environments） virtual desktop solution provides several image compression algorithms to address this problem with the purpose of making virtual desktops as real as possible. Although different compression algorithms can contribute their own abilities to different images to a large extent, switching between them is a big problem that consumes a large amount of resources to detect the different type of image and also causes jitter of the virtual desktop. This paper proposes a new solution, called SPICEx, using the JPEG2000 compression algorithm with dynamic compression ratios to solve the problem and finally validates that the performance is better than that of SPICE. With better quality of user experience and also reducing bandwidth consumption, SPICEx solution is meaningful in virtual desktop fields and can be widely used.     

A secure routing model based on distance vector routing algorithm

Distance vector routing protocols have been widely adopted as an efcient routing mechanism in current Internet,and many wireless networks.However,as is well-known,the existing distance vector routing protocols are insecure as it lacks of efective authorization mechanisms and routing updates aggregated from other routers.As a result,the network routing-based attacks become a critical issue which could lead to a more deteriorate performance than other general network attacks.To efciently address this issue,this paper,through analyzing the routing model and its security aspect,and presents a novel approach on guaranteeing the routing security.Based on the model,we present the security mechanism including the message exchange and update message security authentication mechanism.The suggested approach shows that the security mechanism can efectively verify the integrity and validate the freshness of routing update messages received from neighbor nodes.In comparison with exiting mechanisms(SDV,S-RIP etc),the proposed model provides enhanced security without introducing significant network overheads and complexity.     

基于生成对抗网络的无监督图像风格迁移

无监督的图像风格迁移是计算机视觉领域中一个非常重要且具有挑战性的问题.无监督的图像风格迁移旨在通过给定类的图像映射到其他类的类似图像.一般情况下成对匹配的数据集很难获得,这极大限制了图像风格迁移的转换模型.因此,为了避免这种限制,对现有的无监督的图像风格迁移的方法进行改进,采用改进的循环一致性对抗网络进行无监督图像风格迁移.首先为了提升网络的训练速度,避免梯度消失的现象出现,在传统的循环一致性网络生成器部分引入DenseNet网络;在提高生成器的性能方面,生成器网络部分引入attention机制来输出效果更好的图像;为了减少网络的结构风险,在网络的每一个卷积层都使用谱归一化.为了验证本文方法的有效性,在monet2photo、vangogh2photo和facades数据集上进行了实验,实验结果表明,该方法在Inception score平均分数和FID距离评价指标上均有所提高.