不同网络负载的Ad Hoc网络路由协议性能分析

通过实验对一种表驱动路由协议(DSDV)以及其中两种按需式路由协议(DSR和AODV)协议的性能进行比较和分析.利用NS-2仿真软件,设计了基于不同网络负载的多组仿真模型,并根据模型进行仿真.之后从分组投递率、时延和路由负荷三个性能指标参数对仿真结果进行了比较.实验结果表明:按需式路由协议DSR和AODV要优于基于表驱动的路由协议DSDV;在两种按需式路由协议之间,随着不同网络负载的加重,AODV协议比DSR协议的性能优势越来越明显.同时分析了造成不同协议之间性能差距的原因,针对AODV协议提出了今后的改进方向.     

MATLAB在弹道仿真中的应用

在导弹的设计、研究中,弹道仿真是一项必不可少的实验工具.如何能够高效地运用Matlab软件进行弹道全数字仿真是文中主要探讨的问题.针对这一问题,首先分析了弹道仿真数学模型的特点,并以滑翔增程弹为例,详细研究了在M文件、simulink工具箱以及两者交互使用环境下建立外弹道质心运动系统仿真模型的方法和优缺点.最后给出了一定条件下的弹道仿真结果,以此证明该仿真算法对弹道进行仿真研究具有模型设计简单、参数易于修改和结果直观等特点.     

基于最大似然准则Hausdorff距离的跟踪算法

针对视频处理中运动物体的检测和跟踪问题,提出一种基于最大似然准则Hausdorff距离的目标跟踪算法,首先利用基于GVF的Snake方法获得物体模型;然后采用基于最大似然准则的Hausdorff距离匹配后续帧中的目标,搜索策略采用类似于Rucklidge提出的多分辨率搜索方法,在不影响搜索成功率和目标定位精度的情况下, 可以显著地缩短搜索时间;最后使用Snake方法完成运动物体的轮廓更新.实验表明该方法可以较好地跟踪刚性和非刚性物体,同时对部分被遮挡的目标也有良好的跟踪效果.     

Weight distribution and dual distance

Several results in coding theory (e.g. the Carlitz-Uchiyama bound) show that the weight distributions of certain algebraic codes of lengthn are concentrated aroundn/2 within a range of width n. It is proved in this article that the extreme weights of a linear binary code of sufficiently high dual distance cannot be too close ton/2, the gap being of order n. The tools used involve the Pless identities and the orthogonality properties of Krawtchouk polynomials, as well as estimates on their zeroes. As a by-product upper bounds on the minimum distance of self-dual binary codes are derived.     

车辆防碰预警系统的设计

介绍了一种以ATmega16单片机为控制核心的车辆防碰预警系统,提出了解决收发一体式超声波测距电路难题的新方法;由于温度对超声波波速的影响,增加了温度补偿电路来消除误差;设计的自动增益控制(AGC)电路,有效地解决了回波信号过于微弱而导致系统测量误差加大的难题;在此基础上,设计了相应的超声波测距系统的软件;对系统进行了测试,如主要试验参数:灵敏度、测距、频率等;并将所测数据与实际数据进行了对比;结果表明,该预警系统具有较高的测量精度。     

Global optimization of tool path for five-axis flank milling with a conical cutter

In this paper, optimum positioning of the conical cutter for five-axis flank milling of slender surfaces is addressed from the perspective of approximating the tool envelope surface to the data points on the design surface following the minimum zone criterion recommended by ANSI and ISO standards for tolerance evaluation. Based on the observation that a conical surface can be treated as a canal surface, i.e. envelope surface of one-parameter family of spheres, the swept envelope of a conical cutter is represented as a sphere-swept surface. Then, an approach is presented to efficiently compute the signed distance between a point in space and the swept surface without constructing the swept surface itself. The first order differential increment of the signed point-to-surface distance with respect to the differential deformation of the tool axis trajectory surface is derived. By using the distance function, tool path optimizations for semi-finish and finish millings are formulated as two constrained optimization problems in a unified framework, and a sequential approximation algorithm along with a hierarchical algorithmic structure is developed for the optimization. Numerical examples are given to confirm the validity and efficiency of the proposed approach. Comparing with the existing approaches, the present one improves the machining accuracy greatly. The rationale developed applies to general rotary cutters.     

Generalized iterative RELIEF for supervised distance metric learning

The RELIEF algorithm is a popular approach for feature weighting. Many extensions of the RELIEF algorithm are developed, and I-RELIEF is one of the famous extensions. In this paper, I-RELIEF is generalized for supervised distance metric learning to yield a Mahananobis distance function. The proposed approach is justified by showing that the objective function of the generalized I-RELIEF is closely related to the expected leave-one-out nearest-neighbor classification rate. In addition, the relationships among the generalized I-RELIEF, the neighbourhood components analysis, and graph embedding are also pointed out. Experimental results on various data sets all demonstrate the superiority of the proposed approach.     

基于多代理的个性化推荐学习系统

针对现有学习系统存在信息过载、缺乏个性化服务能力、不能提供检索服务的问题,提出基于多代理构建个性化推荐学习系统。该系统利用JADE设计学习者Agent与推荐Agent,采用Lucene设计带有个性化能力的搜索引擎支持推荐,并融合3种推荐方法发挥多Agent间协商与协作的优势。实验结果表明,相比单一推荐方法,该系统具有较好的推荐效果和效率。     

Kernel-kNN: 基于信息能度量的核k-最近邻算法

提出一种核k最近邻算法. 首先给出用于最近邻学习的信息能度量方法, 该方法克服了高维数据不便于用传统距离度量表示的困难, 提高了数据间类别相似性和距离的一致性. 在此基础上, 将传统的kNN扩展为非线性形式, 并采用半正定规划学习全局最优的度量矩阵. 算法主要特点是: 能较好地适用于高维数据, 并有效提升kNN 的分类性能. 多个数据集的实验和分析表明, 本文的Kernel-kNN算法与传统的kNN算法比较, 在低维数据上, 分类准确率相当; 在高维数据上, 分类性能有明显提高.     

Investigating acceptance toward mobile learning to assist individual knowledge management: Based on activity theory approach

Mobile devices could facilitate human interaction and access to knowledge resources anytime and anywhere. With respect to wide application possibilities of mobile learning, investigating learners’ acceptance towards it is an essential issue. Based on activity theory approach, this research explores positive factors for the acceptance of m-learning systems. In the research, we developed an m-learning system for learners’ knowledge management and invited 152 participants who knew how to use the m-learning system then report on their experience. The results show that enhancing learners’ satisfaction, encouraging learners’ autonomy, empowering system functions, and enriching interaction and communication activities have a significant positive influence on the acceptance of m-learning systems.