Semi-supervised locally discriminant projection for classification and recognition

Semi-supervised dimensional reduction methods play an important role in pattern recognition, which are likely to be more suitable for plant leaf and palmprint classification, since labeling plant leaf and palmprint often requires expensive human labor, whereas unlabeled plant leaf and palmprint is far easier to obtain at very low cost. In this paper, we attempt to utilize the unlabeled data to aid plant leaf and palmprint classification task with the limited number of the labeled plant leaf or palmprint data, and propose a semi-supervised locally discriminant projection (SSLDP) algorithm for plant leaf and palmprint classification. By making use of both labeled and unlabeled data in learning a transformation for dimensionality reduction, the proposed method can overcome the small-sample-size (SSS) problem under the situation where labeled data are scant. In SSLDP, the labeled data points, combined with the unlabeled data ones, are used to construct the within-class and between-class weight matrices incorporating the neighborhood information of the data set. The experiments on plant leaf and palmprint databases demonstrate that SSLDP is effective and feasible for plant leaf and palmprint classification.     

语义驱动的关联规则挖掘算法研究

为了使传统的关联规则挖掘算法在结合到具体领域时具有更强的适应性,提出了DS-Apriori算法。该算法建立在语义本体的基础上,根据项集内部的语义相关度动态的确定该项集的最小支持度,并采用了项集语义相关度的增量计算方法。实验结果表明,DS-Apriori算法在很大程度上提高了关联规则挖掘算法的效率和效果。     

概念空间中上下位关系的意义识别研究

针对上下位关系在分类层级结构建立阶段遇到的多义性问题,给出一种概念空间中上下位关系意义识别的方法.单个概念的意义识别问题被转换为概念空间中上下位关系的意义识别.首先利用并列语境解决语境稀疏问题,获取上下位关系意义的语境.然后利用<同义词词林>对每个语境进行词义修正,以三种特征计算特征词权重,构建"关系一词'的高维向量空间,然后通过潜在语义分析降维,获取上下位关系意义的潜在语义,最后组平均聚类后得到关系的意义划分.在实验中,给出了聚类阈值自动调整函数,分析了词林和潜在语义分析的作用,实验结果证实了方法的有效性.     

动态相位调整技术在FPGA中的设计与实现

提出一种基于FPGA的动态相位调整实现方案。在高速数据传输接口中,由于数据窗缩小以及传输路径不一致,造成数据和时钟信号在FPGA的接收端发生位偏移和字偏移。动态相位调整技术根据当前各数据线物理状态,对各信号线动态进行去偏移操作,克服了静态相位调整中参数不可再调的缺点,使接口不断适应外部环境的变化,从而保证数据的可靠传输。     

Utility function of TCP

Understanding the TCP congestion control mechanism from a global optimization point of view is not only important in its own right, but also crucial to the design of other transport layer traffic control protocols with provable properties. In this paper, we derive a global utility function and the corresponding optimal control law, known as TCP control law, which maximizes the global utility. The TCP control law captures the essential behaviors of TCP, including slow start, congestion avoidance, and the binary nature of congestion feedback in TCP. We find that the utility function of TCP is linear in the slow start phase and is proportional to the additive increase rate and approaches the well-known logarithm function as the data rate becomes large in the congestion avoidance phase. We also find that understanding the slow start phase with a fixed threshold is critical to the design of new transport layer control protocols to enable quality of service features. Finally, as an application, we design a Minimum Rate Guaranteed (MRG) traffic control law that shares the same utility function as the TCP control law. Our simulation study of the MRG control law indicates that it is indeed TCP friendly and can provide minimum rate guarantee as long as the percentage of network resource consumed by the MRG flows is moderately small.     

A new certificateless aggregate signature scheme

Aggregate signatures are useful in special areas where the signatures on many different messages generated by many different users need to be compressed. In this paper, we study aggregate signatures in certificateless public key settings. We first present the notion and security model of certificateless aggregate signature schemes. Then we give an efficient certificateless aggregate signature scheme. Our scheme is existentially unforgeable under adaptive chosen-message attacks assuming the computational Diffie–Hellman problem is hard.     

基于XML的DNA公共数据模型

针对目前DNA数据组织与处理中存在的数据异构问题,提出一个基于XML的DNA公共数据模型（DCDM）。该模型具有很强的可扩展性,能克服一般公共数据模型的作用范围小的缺点,可用于构建DNA研究领域统一的DNA数据描述模式。实验结果表明,该模型能解决DNA数据异构中的语义异构。     

基于OPNET的AdHoc网络建模与仿真

利用OPNET软件自带的支持IEEE802．11标准的节点模型构建AdHoc网络模型。合理配置输入输出接口的参数,使网络达到最佳性能,并对网络的性能进行比较分析。仿真结果表明,网络参数之间存在关联性,网络最优化参数具有唯一性,通过网络负载与标准负载的比较,可选择出网络性能最优化状态。     

GPS软件接收机的模块设计与信号处理

采用Zarlink公司的GP2015对GPS射频前端进行下变频处理,将得到的中频模拟信号转换成数字信号,结合DSP开发技术对中频数字信号进行捕获、跟踪与定位解算,用软件无线电的方法实现GPS软件接收机的模块设计与信号处理。实验结果表明,软件无线电思想能实现算法与软件的高度灵活性,可有效提高GPS接收机的信号处理能力与系统性能。     

基于推理信息量的BN参数学习变量离散化方法

提出推理信息量的概念,将其作为贝叶斯网络连续变量离散化评价标准。在连续变量离散化的过程中,采用遗传算法寻求最优解,设计个体编码方式、交叉算子和变异算子,将推理信息量作为衡量个体适应度的标准。实例分析证明,通过该方法对变量进行离散化后学习得到的贝叶斯网络在推理时能得到更大的推理信息量。