Virtual network embedding based on real-time topological attributes

As a great challenge of network virtualization, virtual network embedding/mapping is increasingly important. It aims to successfully and efficiently assign the nodes and links of a virtual network (VN)...     

Obtaining four-dimensional vibration information for vibrating surfaces with a Kinect sensor

In this paper, we present a real-time approach to obtain four-dimensional (4D) information from the surfaces of low-frequency vibrating rigid objects using a Kinect sensor. This consumer-grade range sensing technology is used for markerless tracking on the three-dimensional (3D) coordinate points of object surfaces. The time coordinates are simultaneously defined by the sampling interval converted from the frame rate of 30 frames per second (fps). Then the 4D (defined in the space time) vibration information can be recorded in the form of (x, y, z, t), enabling researchers to investigate the dynamic features of object surfaces efficiently. A comparison of the measurement accuracy and efficiency of a Kinect sensor, a stereo vision system and a contact sensor is carried out. The results confirm the superiority of our approach in efficient measurement and demonstrate that the contrastive amplitude error ranges within 0.6 mm when the frequency is not beyond 15 Hz.     

Dynamic cluster member selection method for multi-target tracking in wireless sensor network简

Multi-target tracking（MTT） is a research hotspot of wireless sensor networks at present.A self-organized dynamic cluster task allocation scheme is used to implement collaborative task allocation for MTT in WSN and a special cluster member（CM） node selection method is put forward in the scheme.An energy efficiency model was proposed under consideration of both energy consumption and remaining energy balance in the network.A tracking accuracy model based on area-sum principle was also presented through analyzing the localization accuracy of triangulation.Then,the two models mentioned above were combined to establish dynamic cluster member selection model for MTT where a comprehensive performance index function was designed to guide the CM node selection.This selection was fulfilled using genetic algorithm.Simulation results show that this method keeps both energy efficiency and tracking quality in optimal state,and also indicate the validity of genetic algorithm in implementing CM node selection.     

基于输出理论的教学模式研究

以二语习得理论为出发点,输出理论为基础,研究能够有效提高学习者二语习得的教学模式。首先阐释了输出理论和输入理论的关系以及研究输出理论的重要性,其次分析了输出理论在二语习得中的重要作用,然后探讨了以输出理论为基础的教学模式,旨在提高二语教学水平和学习者二语习得能力。     

LTE-Advanced中继系统切换优化算法

为了提高LTE-Advanced中继系统的切换性能,提出一种能够提高系统性能的切换优化算法。在切换测量阶段加入测量平均窗口,减小多径效应对接收信号的影响,并考虑用户移动速度对切换测量和切换执行时间的影响;在切换实施阶段,结合LTE-Advanced中继系统中引入的载波聚合技术,采用改进的边缘共享中继方案。经仿真表明,该算法可减少乒乓效应及平均掉话率,简化切换信令流程,降低切换中断时间,提高边缘用户吞吐量。     

校企合作 产教融合 推进地方本科院校转型发展

我国高等教育结构正在进行深刻调整,一批地方本科院校向应用技术型大学转型发展。本文提出了深化校企合作,产教融合,以协同创新推动地方本科院校转型发展的路径,阐明了转型发展的任务,并结合黑龙江工程学院的探索实践提出了转型发展的几点建议。     

基于UML的协同式CASE平台的研究与实现

针对目前软件生产要求的高效率、短周期、高质量及面向团队协作开发等需求,提出一种基于UML(Unified Modeling Language)的协同式开发方法,并基于此方法设计出B/S模式的集成化CASE(Computer Aided Software Engineering)平台。平台采用嵌套式3层架构及面向工作流的基于角色的访问控制,实现了在浏览器界面动态设置角色权限、创建与修改项目数据库及前后台代码自动生成等功能。实验结果表明:该平台能够有效地满足开发过程中的明细分工,高效组合等要求;开发周期缩短,开发效率提高,软件系统的开发成本降低。     

初始聚类中心优化的K-均值项目聚类推荐算法

针对协同过滤推荐系统存在的数据稀疏性和扩展性差问题,提出了初始聚类中心优化的K-均值项目聚类推荐算法。该算法首先采用SlopeOne方法对评分矩阵预测填充来缓解数据稀疏性,然后采用初始聚类中心优化的K-均值算法对项目进行聚类,将相似度高的项目聚到同一个类中,最后根据目标项目所在的聚类搜索其最近邻并产生推荐。实验结果表明,该算法有效改善了数据的稀疏性和扩展性,提高了推荐质量。     

基于协同创新的科技型小微企业竞争优势研究

针对国内科技型小微企业创新的不足,采用文献研究和案例结合的方法,以科技型小微企业为研究核心,构建了协同创新对科技型小微企业竞争优势影响的概念模型,通过对模型运作机制以及效应的分析,指出科技型小微企业实现竞争优势的新路径,并通过实例验证了相应模型.     

虚拟样机协同设计并发控制策略研究 *

针对虚拟样机协同设计中数据量大、事务长、多层嵌套的问题 ,提出了一种基于事务语义的并发控制策略,阐述了并发控制机制中事务结构、事务提交、锁机制和冲突协调等关键性问题。根据数据要求生成复制事务,事务发生改变后 ,其他站点能够实时显示图形、实时读取数据。实例证明 ,基于事务语义的并发控制策略保证协同用户自由地操作共享资源 ,提高了并发控制的可靠性和数据的一致性。