基于CICQ结构的变长分组交换调度算法研究

在Crossbar交换单元的交叉节点加少量缓存的C ICQ(Comb ined Input-Crosspoint-Queued)交换结构是一种调度简单并能够支持变长分组的交换结构。但是,简单的权重轮询调度算法会造成输入队列服务不公平性。为此,提出了一种改进的权重调度算法———最小配额优先算法(MQF:M in imum Quotient F irst)。通过选择恰当的分组队列调度配额,充分发挥了C ICQ结构先天性支持变长分组交换的优势。通过仿真证明,该算法在均匀和非均匀业务到达下,可以获得近100%的吞吐率和较低的平均分组时延。     

计算机化自适应诊断测验双重约束变长终止规则

提出3种变长CD-CAT终止规则,在DINA模型、4种属性层级结构下,采用ED选题策略,讨论提出的3种方法与常用CD-CAT终止规则在7个评价指标上的优劣。研究结果显示:新的3种方法较常用终止规则有其自身优势。     

不定长认知诊断计算机化自适应测验终止规则研究

目前大多数认知诊断计算机化自适应测验采用定长终止规则,该文提出3种不定长终止规则。通过实验对比,新方法较已有方法具有如下优势:i）能够较好地保障测验精度;ii）大幅降低了人均测验用题数;iii）人均测验用时也有所下降;iv）项目调用均衡性和题库安全性有所增强。     

虚拟手术中缝合仿真的初步研究

初步实现了一个虚拟缝合仿真系统,可以模拟针穿刺柔性体并牵引所附缝合线穿过柔性体的过程。用户通过Phantom Desktop力反馈设备控制虚拟针的运动。柔性体在针和缝合线的作用下会发生变形。缝合线使用非均匀可变长刚性杆模型和FTL(Follow the Leader)变形算法。柔性体使用线弹性材料和Tensor-Mass变形算法。针穿刺柔性体时柔性体对针运动的阻力传给力反馈设备,而其反作用力则施加于柔性体之上。缝合线在针的牵引下穿过柔性体形成滑动约束点。缝合线的变形将在滑动约束点产生弹性力作用于柔性体之上,而柔性体的变形则反过来影响滑动约束点的位置。将约束点对应的缝合线顶点编号增加和约束点两侧刚性杆长度调整相结合,实现了缝合线光滑穿过柔性体的效果。最后给出对含有切口形状的柔性体模型进行缝合仿真的实验结果,并讨论未来的改进和发展方向。     

基于VLC域的H.264/AVC视频流内容级认证水印算法

针对低比特率的H.264/AVC(Advanced Video Coding)视频流,提出一种新颖的基于VLC(Variable Length Coding)域的内容级的半脆弱水印认证算法.利用视频VLC域中I宏块的预测方式、CBP(Coded Block Pattern)块编码模式,自适应选取提取特征码的宏块,并根据子宏块上量化后系数的低频能量之间的关系,构建基于宏块级别的内容特征码;鉴于子宏块中拖尾系数的特点,通过修改拖尾系数的编码方式实现半脆弱认证水印的嵌入.实验证明,该算法能保持特征码嵌入前后视频良好的不可感知性以及视频流码率的基本恒定;能有效提高视频水印嵌入容量;可有效实现针对视频内容篡改的宏块级别的检测和定位.该算法可应用于视频内容鉴定,版权保护等领域.
     

基于小生境遗传算法的飞行航迹规划

提出了一种基于小生境遗传算法的飞行航迹规划方法.把航迹编码为离散时间上变长度的飞行器速度和航向变化序列,并以此序列作为遗传算法种群中的个体,在这个变化序列中,每一个元素都考虑了飞行器的性能约束,因而,每个变化序列对应的航迹郝是飞行器可飞的.初始种群不是随机生成,而是根据规划起点和终点的相对关系生成的.为了防止种群收敛于局部最优解,采用基于共享函数的小生境技术增加种群的多样性.仿真结果表明,算法能快速有效地在动态环境中规划出近最优的飞行航迹.     

基于链表结构的多维动态数组设计方法

针对动态数组生成中难以适应任意维数、任意数据类型、索引数据不够灵活等问题,提出一种基于链表结构的多维动态数组设计方法.该方法通过链表进行索引,采用变长参数列表技术动态生成数组.结果表明,该方法能够生成任意维动态数组;适用任意的数据类型;既能够直接利用数组下标索引数据,也能够对数据进行线性访问.与以往动态数组生成方法相比,更易于扩展,使用更加灵活.     

Detecting network intrusions by data mining and variable-length sequence pattern matching

Anomaly detection has been an active research topic in the field of network intrusion detection for many years. A novel method is presented for anomaly detection based on system calls into the kernels of Unix or Linux systems. The method uses the data mining technique to model the normal behavior of a privileged program and uses a variable-length pattern matching algorithm to perform the comparison of the current behavior and historic normal behavior, which is more suitable for this problem than the fixed-length pattern matching algorithm proposed by Forrest et al. At the detection stage, the particularity of the audit data is taken into account, and two alternative schemes could be used to distinguish between normalities and intrusions. The method gives attention to both computational efficiency and detection accuracy and is especially applicable for on-line detection. The performance of the method is evaluated using the typical testing data set, and the results show that it is significantly better than the anomaly detection method based on hidden Markov models proposed by Yan et al. and the method based on fixed-length patterns proposed by Forrest and Hofmeyr. The novel method has been applied to practical hosted-based intrusion detection systems and achieved high detection performance.     

Integrated Joint Source-Channel Decoding for H.264 Video Transmission

This paper proposes an integrated joint source-channel decoder （I-JSCD） using Max-Log-MAP method for sources encoded with exp-Golomb codes and convolutional codes, and proposes a system applying this method to decoding the VLC data, e.g. motion vector differences （MVDs）, of H.264 across an AWGN channel. This method combines the source code state-space and the channel code state-space together to construct a joint state-space, develops a 3-D trellis and a maximum a-posterior （MAP） algorithm to estimate the source sequence symbol by symbol, and then uses max-log approximation to simplify the algorithm. Experiments indicate that the proposed system gives significant improvements on peak signal-to-noise ratio （PSNR） （maximum about 15 dB） than a separate scheme. This also leads to a higher visual quality of video stream over a highly noisy channel.     

Variable-length sequential dynamic features-based malware detection①

In order to solve the problem that traditional signature-based malware detection systems are in-efficacious in detecting new malware , a practical malware detection system is constructed to find out new malware .Application programming interface ( API) call sequence is introduced to capture ac-tivities of a program in this system .After that, based on variable-length n-gram, API call order can be extracted from API call sequence as the malicious behavior feature of a software .Compared with tra-ditional methods , which use fixed-length n-gram, the solution can find more new malware .The experi-mental results show that the presented approach improves the accuracy of malware detection .