More than twenty years of advancements on Frontiers in handwriting recognition

In this paper the results of the research in handwriting/handwritten character recognition in about the last quarter of a century are reported, illustrating the results presented during the International Workshop on Frontiers in Handwriting Recognition (IWFHR) and the International Conference on Frontiers in Handwriting Recognition (ICFHR).     

Fractional-order embedding canonical correlation analysis and its applications to multi-view dimensionality reduction and recognition

Due to the noise disturbance and limited number of training samples, within-set and between-set sample covariance matrices in canonical correlation analysis (CCA) usually deviate from the true ones. In this paper, we re-estimate within-set and between-set covariance matrices to reduce the negative effect of this deviation. Specifically, we use the idea of fractional order to respectively correct the eigenvalues and singular values in the corresponding sample covariance matrices, and then construct fractional-order within-set and between-set scatter matrices which can obviously alleviate the problem of the deviation. On this basis, a new approach is proposed to reduce the dimensionality of multi-view data for classification tasks, called fractional-order embedding canonical correlation analysis (FECCA). The proposed method is evaluated on various handwritten numeral, face and object recognition problems. Extensive experimental results on the CENPARMI, UCI, AT&T, AR, and COIL-20 databases show that FECCA is very effective and obviously outperforms the existing joint dimensionality reduction or feature extraction methods in terms of classification accuracy. Moreover, its improvements for recognition rates are statistically significant on most cases below the significance level 0.05.     

An efficient parallel-network packet pattern-matching approach using GPUs

In the past few years, the increase in interest usage has been substantial. The high network bandwidth speed and the large amount of threats pose challenges to current network intrusion detection systems, which manage high amounts of network traffic and perform complicated packet processing. Pattern matching is a computationally intensive process included in network intrusion detection systems. In this paper, we present an efficient graphics processing unit (GPU)-based network packet pattern-matching algorithm by leveraging the computational power of GPUs to accelerate pattern-matching operations and subsequently increase the overall processing throughput. According to the experimental results, the proposed algorithm achieved a maximal traffic processing throughput of over 2 Gbit/s. The results demonstrate that the proposed GPU-based algorithm can effectively enhance the performance of network intrusion detection systems.     

离散小波变换Haar-LL的行人检测研究

提出一种基于二维离散Haar小波变换的局部二值模式(LBP)与局部梯度模式(LGP)的特征融合方法。对图像进行二维离散Haar小波变换,得到4个不同频率的子图像,对低频部分子图像提取LBP特征,对3个高频部分子图像提取LGP特征,将3个LGP特征并接融合后与LBP特征串接融合进行行人检测。在Matlab环境下利用支持向量机(SVM)对INRIA数据集进行5组实验,分别将该方法与梯度方向直方图(HOG)、金字塔梯度方向直方图(PHOG)、LBP、LGP进行检测率、检测时间、光照鲁棒性以及噪声鲁棒性对比。综合各项实验数据表明,该方法在光照鲁棒性以及噪声鲁棒性方面都能取得更好的效果。     

动态受限区域内的单纯型连续近邻链查询方法

受限区域内的单纯型连续近邻链查询在空间数据挖掘、数据的相似分析和推理、空间数据库等方面具有重要的作用。为了弥补已有方法的不足,详细研究了动态受限区域内的单纯型连续近邻链查询方法。基于计算几何中的Voronoi图给出了VOR_IN_CRSCNNC算法、VOR_EX_CRSCNNC算法和VOR_DE_CRSCNNC算法。进一步进行了实验比较和分析。理论研究和实验分析表明,所提出的算法在查询过程中减少了数据逐一筛选和判断的冗余计算,在处理空间数据量较大、初始受限区域数据量较多、受限区域形状较为复杂的单纯型连续近邻链查询方面具有较大的优势。     

SSI:一种IPv6/IPv4多址同源识别模型

IPv6/IPv4共存环境下多址同源识别是共存网络管理与拓扑发现的一个关键问题。现有研究主要集中于子网内部的双栈发现及单一IP协议栈中的别名解析,难以识别远程IPv6/IPv4共存网络中的多址同源。通过分析同源地址间的本质联系,提出一种IPv6/IPv4多址同源识别模型(SSI),该模型综合利用特殊地址格式匹配、TCP时钟指纹比对和上层协议短时致瘫等多种方式来提高同源地址的识别能力。实验结果表明,上述方法均可有效识别IPv6/IPv4多址同源;SSI模型具有较理想的识别率和正确率。     

Effect of the geometry and pattern of the flow channel on the performance of polymer electrolyte membrane fuel cell

This research focuses on the effect of the geometry and patterns of the gas flow channel on the PEM fuel cell performance. Simulation was conducted and the results were verified by experiments. Three-dimensional, single phase, compressible and isothermal models of 5 cm² electrodes, anode and cathode, were developed and studied by utilizing a commercial Computational Fluid Dynamics (CFD) software, FLUENT 4.5. Two types of gas flow channel were investigated: conventional and interdigitated. The results showed that the flow channel pattern does not have a significant effect on the anode cell performance, whereas it has a strong effect/influence on the cathode cell performance. The interdigitated design provides a higher limiting current density and cell performance than the conventional design on the cathode side. Moreover, the cell performance does not depend on the inlet and outlet channel widths. On the contrary, for the interdigitated design, it was influenced by the shoulder width. Finally, experiments were conducted to validate the simulation results.     

电子商务模式的多维分类体系研究

电子商务模式的开展是实现电子商务应用的重要问题之一.为充分探讨电子商务模式的体系建立,在总结已有成果基础上,本文基于电子商务模式的分类讨论十大类基本的电子商务模式,分析构建多维电子商务模式分类体系.     

基于IPv6的网络入侵检测技术研究

IPv6技术是下一代互联网的核心技术。通过分析现有网络安全系统的基本原理,针对IPv6网络的特点,提出在IPv6环境下采用基于协议分析和模式匹配技术相结合的入侵检测系统架构。采用该系统架构能够更快、更有效地处理信息数据帧和连接,同时能够判断一个通信的实际内容及具体含义,具有抗躲避性强、系统资源占用小、检测速度高、误报率低的特点。     

警用移动信息系统安全解决方案

当前,在社会矛盾复杂化、警务工作效率必须不断提高的大背景下,我国各地方公安机关陆续将警用移动信息系统纳入信息化建设的重要指标。为了向公安各部门一线民警提供快捷、方便的实现信息共享渠道,就必须在现有的公安信息系统的基础上,发展出可移动的信息处理系统。由于各地公安机关都是各自开发所需的相关业务的专项警务信息系统,容易在安全设计上存在只注重功能轻视安全问题的错误,警务人员在使用这些系统提高工作效率时存在公安警务工作泄密、公安资料不安全等问题。因此,在以现代无线通讯技术和互联网技术相结合产生的移动互联网技术的飞速发展中,为警用移动信息系统提出安全解决方案提供了必要的技术基础。在分析警用移动信息系统网络架构、安全需求及建设现状的基础上,本文设计并实现了以移动3G技术为基础的Socket方式访问的警用移动信息系统。