A cross-layer framework for video-on-demand service in multi-hop WiMax mesh networks

In this work, we introduce a cross-layer framework to favor the video-on-demand service in multi-hop WiMax mesh networks. We first propose a joint solution of admission control and channel scheduling for video streams. The proposed approach guarantees that the required data rate is achieved for video streams, which is crucial for multimedia streaming applications. An efficient and light-weight multicast routing technique is also proposed to minimize the bandwidth cost of joining a multicast tree. Furthermore, we adopt the Patching technique in the application layer to improve the capacity of the video server. Overall, the quality of the video-on-demand service is dramatically improved with the help of the efficient cooperation between the techniques proposed in different layers of the network. Simulation study shows that with the proposed approach, true video-on-demand in WiMax mesh networks can be achieved under high video request arrival rate.     

Eigenfeature regularization and extraction in face recognition

This work proposes a subspace approach that regularizes and extracts eigenfeatures from the face image. Eigenspace of the within-class scatter matrix is decomposed into three subspaces: a reliable subspace spanned mainly by the facial variation, an unstable subspace due to noise and finite number of training samples and a null subspace. Eigenfeatures are regularized differently in these three subspaces based on an eigenspectrum model to alleviate problems of instability, over-fitting or poor generalization. This also enables the discriminant evaluation performed in the whole space. Feature extraction or dimensionality reduction occurs only at the final stage after the discriminant assessment. These efforts facilitate a discriminative and stable low-dimensional feature representation of the face image. Experiments comparing the proposed approach with some other popular subspace methods on the FERET, ORL, AR and GT databases show that our method consistently outperforms others.     

An Improved (and Practical) Parameterized Algorithm for the Individual Haplotyping Problem MFR with Mate-Pairs

The Individual Haplotyping MFR problem is a computational problem that, given a set of DNA sequence fragment data of an individual, induces the corresponding haplotypes by dropping the minimum number of fragments. Bafna, Istrail, Lancia, and Rizzi proposed an algorithm of time O(2^2k m ² n+2^3k m ³) for the problem, where m is the number of fragments, n is the number of SNP sites, and k is the maximum number of holes in a fragment. When there are mate-pairs in the input data, the parameter k can be as large as 100, which would make the Bafna-Istrail-Lancia-Rizzi algorithm impracticable. The current paper introduces a new algorithm PM-MFR of running time , where k ₁ is the maximum number of SNP sites that a fragment covers (k ₁ is smaller than n), and k ₂ is the maximum number of fragments that cover a SNP site (k ₂ is usually about 10). Since the time complexity of the algorithm PM-MFR is not directly related to the parameter k, the algorithm solves the Individual Haplotyping MFR problem with mate-pairs more efficiently and is more practical in real biological applications. This research was supported in part by the National Natural Science Foundation of China under Grant Nos. 60433020 and 60773111, the Program for New Century Excellent Talents in University No. NCET-05-0683, the Program for Changjiang Scholars and Innovative Research Team in University No. IRT0661, and the Scientific Research Fund of Hunan Provincial Education Department under Grant No. 06C526.     

Fault tolerant multiple event detection in a wireless sensor network

With an increasing acceptance of Wireless Sensor Networks (WSNs), the health of individual sensor is becoming critical in identifying important events in the region of interest. One of the key challenges in detecting event in a WSN is how to detect it accurately transmitting minimum information providing sufficient details about the event. At the same time, it is also important to devise a strategy to handle multiple events occurring simultaneously. In this paper, we propose a Polynomial-based scheme that addresses these problems of Event Region Detection (PERD) by having a aggregation tree of sensor nodes. We employ a data aggregation scheme, TREG (proposed in our earlier work) to perform function approximation of the event using a multivariate polynomial regression. Only coefficients of the polynomial (P$P$) are passed instead of aggregated data. PERD includes two components: event recognition and event report with boundary detection. This can be performed for multiple simultaneously occurring events. We also identify faulty sensor(s) using the aggregation tree. Performing further mathematical operations on the calculated P$P$ can identify the maximum (max) and minimum (min) values of the sensed attribute and their locations. Therefore, if any sensor reports a data value outside the [min, max] range, it can be identified as a faulty sensor. Since PERD is implemented over a polynomial tree on a WSN in a distributed manner, it is easily scalable and computation overhead is marginal. Results reveal that event(s) can be detected by PERD with error in detection remaining almost constant achieving a percentage error within a threshold of 10%$10\%$ with increase in communication range. Results also show that a faulty sensor can be detected with an average accuracy of 94%$94\%$ and it increases with increase in node density.     

Information-theoretic Approaches Based on Sequential Monte Carlo to Collaborative Distributed Sensors for Mobile Robot Localization

We consider the Sequential Monte Carlo (SMC) method for Bayesian inference applied to the problem of information-theoretic distributed sensor collaboration in complex environments. The robot kinematics and sensor observation under consideration are described by nonlinear models. The exact solution to this problem is prohibitively complex due to the nonlinear nature of the system. The SMC method is, therefore, employed to track the probabilistic kinematics of the robot and to make the corresponding Bayesian estimates and predictions. To meet the specific requirements inherent in distributed sensors, such as low-communication consumption and collaborative information processing, we propose a novel SMC solution that makes use of the particle filter technique for data fusion, and the density tree representation of the a posterior distribution for information exchange between sensor nodes. Meanwhile, an efficient numerical method is proposed for approximating the information utility in sensor selection. A further experiment, obtained with a real robot in an indoor environment, illustrates that under the SMC framework, the optimal sensor selection and collaboration can be implemented naturally, and significant improvement in localization accuracy is achieved when compared to conventional methods using all sensors.     

基于软硬件分区的AVS高清视频解码器结构

硬件的强大处理能力及软件的灵活性和可编程性,使得视频解码芯片的结构从硬件转向软硬件分区结构.作为新兴的标准,AVS视频标准对解码器的软硬件分区结构提出新的挑战.从AVS视频标准算法和实现复杂度入手,提出一种AVS高清视频解码器软硬件分区结构,实现满足基准档次6.0级别的AVS高清视频码流的实时解码,支持灵活的音视频同步、错误恢复、缓冲区管理和系统控制机制.已经在AVS101芯片上实现,硬件采用7阶宏块级同步流水,软件任务在RISC处理器上实现,可以在148.5MHz工作频率下对NTSC,PAL,720p(60f/s),直至1080i(60field/s)节目的实时解码显示.     

一种新的适用于面向对象程序设计语言的保守式垃圾收集机制

主要研究了在缺乏运行时环境支持的情况下,如何为面向对象程序设计语言构建保守式垃圾收集机制的问题.传统的解决方案存在两大主要缺陷:1)指针定位不准确,容易出现内存泄漏;2)应用传统的标记-清扫算法,在清扫阶段执行效率低下.结合面向对象程序设计语言的特点提出了一种新的保守式垃圾收集机制,能够有效地解决这些问题,从而提高了程序运行的鲁棒性和效率,并以C 语言为例进行了具体实现.     

基于SH4 7751开发平台的Linux移植

描述了将Linux2.6内核移植到新开发板上的方法与过程,并且通过实际项目实践来验证,重点突出了代码构架及相关编码.     

模糊C-均值(FCM)聚类算法的实现

传统的FCM算法能够将靠近边界的具有固有形状的两个簇合并成为一个大的簇.然而,对于一些稍微复杂的数据,如果没有其它的像去除小簇之类的机制的话,FCM算法很难将非常接近的类聚类到一起.给出的聚类算法是在传统FCM算法的循环之后添加了去除掉空簇的步骤,解决了上述很难将非常接近的类聚到一个簇中的问题.另外,为便于选出最优结果,在递归之后又添加了计算聚类有效性的步骤.最后用Java实现了该算法并在数据集上进行了实验,证实了改进方法的有效性.     

无码间串扰传输特性动态仿真分析与研究

码间串扰和信道噪声是影响基带传输系统性能的两个主要因素。因此,如何消除它们的影响,使系统的误码率达到规定的要求是数字基带系统中必须研究的两个问题。奈奎斯特第一准则为消除码间串扰奠定了理论基础。本文将以此为依据,通过使用Systemview和MATLAB软件实现对基带传输系统的仿真,并根据所得图形从消除码间串扰的角度来定性地分析无码间串扰系统函数的传输特性。实验中所得结果将对我们的理解和实践均有一定的指导作用。