多目标优化理论在蜂窝夹芯结构设计中的应用

在确定了设计变量及目标函数的基础上,根据结构本身的要求,推导出用于多目标优化的5个约束条件.根据多目标优化理论,采用乘除法对蜂窝夹芯结构进行了评价函数的构造,并用VC语言编制了钢质蜂窝夹芯减振板结构的优化程序,该程序可实现结构尺寸及性能的优化,并计算出各目标函数的最终值.     

机械镀锌过程中先导金属的研究

通过多次试验观察，借助于扫描电子显微镜，结合物理化学、电化学的基础理论知识，对机械镀锌过程中先导金属进行了研究。分析了先导金属在镀层中的分布以及先导金属对机械镀锌形层过程的影响。结果表明机械镀锌过程中的确有先导金属存在，在机械镀锌过程的不同阶段，有着不同的金属起着先导金属的作用。先导金属可以促进机械镀锌镀层的结合强度。     

基于Feeds的社交网络活跃度分析

从用户产生和消费Feeds的角度分析社交网络变得不活跃的原因,通过分析人人网某大学社区用户长周期的Feeds行为来探讨该社区用户活跃度的变化。通过对用户活跃性周期和Feeds时间间隔的分析,发现越来越多的用户产生Feeds的活跃度在下降,并导致其他用户接收到的信息流的流速和多样性下降。社交网络用户由于各种原因离开或变得不活跃,并通过信息流对其朋友圈形成负向反馈,这可能是社交网络变得不活跃的深层原因。模拟实验表明,30%的初始不活跃用户会使得整个社区的信息流快速下降,并导致整个社区不活跃。     

一种面向空地一体化组网的体系架构

空间网络是空地一体化组网中地面网络延伸的重要组成部分。针对空间网络为移动星座的场景,传统的空地一体化组网模型将空间网络视为独立自治域,利用边界网关协议将空间网络与地面自治域互联起来,最大化同地面网络保持兼容。然而,传统组网模型存在边界网关面临频繁会话中断或大量路由更新等问题。通过重新审视空间网络的角色定位和边界划定问题,提出一种面向空地一体化组网的体系架构Slink。Slink的核心思想是空间网络为地面网络提供互联通道,利用星地网关隔离空地两网间的路由更新。实验仿真表明,Slink体系架构能够有效减小对空间路由器的路由存储空间需求,降低星地网络间的带宽消耗。     

多种类病毒相互作用下网络信道破坏程度估计

在多种类病毒的相互作用下,网络信道破坏程度呈现较强的非线性特点,不能准确约束病毒在相互作用下的破坏性.传统的网络破坏程度估计的过程中,仅仅以单一病毒破坏程度叠加的方式去计算参数,计算具有较强的主观性,没有准确描述不同病毒的破坏作用,对评估结果误差影响较大.为解决上述问题,提出一种基于粒子滤波算法的多种类病毒相互作用下网络信道破坏程度估计方法,利用欧式距离方法对全部病毒进行分类,获取不同类型病毒的网络信道破坏程度值.通过粒子滤波算法对单一个体约束的优势,将每一个不同类型的病毒看作一个粒子,并进行训练.根据训练结果,利用粒子滤波算法对当前时刻网络信道破坏程度进行估计,完成整体评估.实验结果表明,利用改进算法进行多种类病毒相互作用下网络信道破坏程度估计,能够有效提高估计的准确率.     

Optimizing content placement in a peer-assisted VoD architecture

Recently, a new peer-assisted architecture to build content delivery systems has been presented. This architecture is based on the use of the storage capacity of end-users’ set-top boxes (STBs), connected in a peer-to-peer (P2P) manner in order to help the content servers in the delivery process. In these systems, the contents are usually split into a set of smaller pieces, called sub-streams, which are randomly injected at the STBs. The present paper is focused on Video on Demand (VoD) streaming and it is assumed that the STB-based content delivery system is deployed over the global Internet, where the clients are distributed over different ISP networks. In this scenario, three different strategies are studied for increasing the percentage of data uploaded by peers, in order to offload the content servers as much as possible. First of all, a new mechanism is presented which determines which sub-stream has to be placed at which STB by a Non-Linear Programming (NLP) formulation. A different strategy for reducing the content server load is to take advantage of the available bandwidth in the different ISP networks. In this sense, two new mechanisms for forwarding the VoD requests to different ISP networks are presented. Finally, the present paper also shows that in some situations the available uplink bandwidth is associated with STBs that do not have the required sub-streams. Regarding this concern, a new mechanism has been designed that dynamically re-allocates some streams, which are being transmitted from specific STBs, to different STBs, in order to find the necessary resources to start new streaming sessions.     

A kernel-based framework for image collection exploration

While search engines have been a successful tool to search text information, image search systems still face challenges. The keyword-based query paradigm used to search in image collection systems, which has been successful in text retrieval, may not be useful in scenarios where the user does not have the precise way to express a visual query. Image collection exploration is a new paradigm where users interact with the image collection to discover useful and relevant pictures. This paper proposes a framework for the construction of an image collection exploration system based on kernel methods, which offers a mathematically strong basis to address each stage of an image collection exploration system: image representation, summarization, visualization and interaction. In particular, our approach emphasizes a semantic representation of images using kernel functions, which can be seamlessly harnessed across all system components. Experiments were conducted with real users to verify the effectiveness and efficiency of the proposed strategy.     

Nonsmooth identification of mechanical systems with backlash-like hysteresis

Backlash-like hysteresis is one of the nonsmooth and multi-valued nonlinearities usually existing in mechanical systems. The traditional identification method is quite difficult to be used to model the systems involved with such complex nonlinearities. In this paper, a nonsmooth recursive identification algorithm for the systems with backlash-like hysteresis is proposed. In this method, the concept of Clarke subgradient is introduced to approximate the gradients at nonsmooth points and the so-called bundle method is used to obtain the optimization search direction in nonsmooth cases. Then, a recursive algorithm based on the idea of bundle method is developed for parameter estimation. After that, the convergence analysis of the algorithm is investigated. Finally, simulation results to validate the proposed method on a simulated mechanical transmission system are presented.