Sub-packet forward error correction mechanism for video streaming over wireless networks

Traditional Forward Error Correction (FEC) mechanisms can be divided into Packet level FEC (PFEC) mechanisms and Byte level FEC (BFEC) mechanisms. The PFEC mechanism of recovering from errors in a source packet requires an entire FEC redundant packet even though the error involves a few bit errors. The recovery capability of the BFEC mechanism is only half of the FEC redundancy. Accordingly, an adaptive Sub-Packet FEC (SPFEC) mechanism is proposed in this paper to improve the quality of video streaming data over wireless networks, simultaneously enhancing the recovery performance and reducing the end-to-end delay jitter. The SPFEC mechanism divides a packet into n sub-packets by means of the concept of a virtual packet. The SPFEC mechanism uses a checksum in each sub-packet to identify the position of the error sub-packet. Simulation experiments show the adaptive SPFEC mechanism achieves high recovery performance and low end-to-end delay jitter. The SPFEC mechanism outperforms traditional FEC mechanism in terms of packet loss rate and video Peak Signal-to-Noise Ratio (PSNR). SPFEC offers an alternative for improved efficiency video streaming that will be of interest to the designers of the next generation environments.     

Robust stability of nonlinear plants with a non-symmetric Prandtl-Ishlinskii hysteresis model

In this paper, robust stability of nonlinear plants represented by non-symmetric Prandtl-Ishlinskii (PI) hysteresis model is studied. In general, PI hysteresis model is the weighted superposition of play or stop hysteresis operators, and the slopes of the operators are considered to be the same. In order to make a hysteresis model, a modified form of non-symmetric play hysteresis operator with unknown slopes is given. The hysteresis model is described by a generalized Lipschitz operator term and a bounded parasitic term. Since the generalized Lipschitz operator is unknown, a new condition using robust right coprime factorization is proposed to guarantee robust stability of the controlled plant with the hysteresis nonlinearity. As a result, based on the proposed robust condition, a stabilized plant is obtained. A numerical example is presented to validate the effectiveness of the proposed method.     

Fire detection based on hidden Markov models

In this paper, a novel method of real-time fire detection based on HMMs is presented. First, we present an analysis of fire characteristics that provides evidence supporting the use of HMMs to detect fire; second, we propose an algorithm for detecting candidate fire pixels that entails the detection of moving pixels, fire-color inspection, and pixels clustering. The main contribution of this paper is the establishment and application of a hidden Markov fire model by combining the state transition between fire and non-fire with fire motion information to reduce data redundancy. The final decision is based on this model which includes training and application; the training provides parameters for the HMM application. The experimental results show that the method provides both a high detection rate and a low false alarm rate. Furthermore, real-time detection has been effectively realized via the learned parameters of the HMM, since the most time-consuming components such as HMM training are performed off-line.     

Modeling and simulation of powered hip orthosis by pneumatic actuators

In this study, a simulation model for a powered hip orthosis (PHO) with air muscles to predict the gait of paraplegics is presented which can be used as a design tool for hip orthoses. Before simulation, mathematical models for a human dummy with an orthosis and a pneumatic muscle actuator were generated. For the air muscle, coefficients required were obtained by static and dynamic experiments of the air muscle and experiments for the valve controlling the air pressure. The computation was conducted on the ADAMS package together with MATLAB. Computer simulation of the flexion of hip joints by the pneumatic muscle results in similar values to those from gait analysis. With the development of a simulation model for a PHO, the gait simulation model using pneumatic muscles can be used to analyze and evaluate the characteristics and efficiency of a PHO by setting the input and boundary conditions.     

虚拟式语音信号实时采集与识别平台

提出了基于LabVIEW和MATLAB混合编程的虚拟式语音信号采集、分析与识别平台设计方案;该平台通过PC机声卡完成对语音信号的实时采集和回放,并对语音信号进行时频分析、端点检测和倒谱分析,进而实现语音识别;为提高识别的正确性和灵活性,提出孤立字列举识别算法和词库编码连续语音识别算法;结果表明,两种算法都能有效识别同音字和读音相似的字;其中,词库编码识别算法不仅效率高,还具有一定的纠错能力,更具有应用价值.     

基于WEB嵌入式自适应智能控制系统的研究与开发

提出一种基于WEB嵌入式自适应智能控制系统设计方案,提供了各组成模块软硬件的详细设计与具体实现;系统采用主流的S3C2410作为处理器,通过I2C总线实现各硬部件的连接;开发的嵌入式WEB服务器模块,使得用户能够对温度传感器读数进行互联网远程监测和多路数字、模拟量输出智能控制;并且神经网络模块能够自适应地学习和控制温度读数与制冷设备输出数之间的关系。实验结果显示改进后的Hopfield算法的收敛性和记忆性得到了提高,并使该系统具有较大的应用价值。     

基于LABVIEW的数据采集与分析系统

介绍了以LabVIEW 8.5为软件开发平台,以PC机、数据采集（DAQ）卡和各种气象因素传感器为主要硬件,构建了虚拟气象仪器系统。系统对6种天气数据进行实时的采集、图形化显示,并可实现对历史天气的分析与浏览。系统易于扩展到分布式天气信息的采集与处理,试用表明该系统性能稳定,具有易开发、界面直观、易扩展等特点,适合在气象科研领域中应用。     

多频段无线传感器网络实验平台构建

无线传感器网络作为一种新兴的技术具有广泛的研究价值和实际应用价值。设计并实现了一个多频段的无线传感器网络实验平台。该平台包括2.4GHz和433MHz的两个子网。两个子网分别通过网关与PC机相连,PC机完成对不同子网的数据包分析和解包,并可对各子网下达指令。实验结果表明,该平台能够完成胜任一般实验的需求,对于理论研究和实际应用都具有十分重要的意义。     

基于MVP模式的进销存系统的软件架构设计

随着企业信息化的快速进展和网络的日益普及,企业实现基于计算机的进销存系统管理是中小企业普遍关注的热点问题.当前该类软件系统普遍基于两层C/S结构,未解决其业务逻辑的不灵活及安全的问题.该系统结构采用基于MVP模式的三层架构,给出了关键的C#程序代码,后台数据库基于SQLServer2008.实践表明系统的可伸缩性强,使用效果可靠稳定,有一定的实用推广价值.     

A new linguistic MCDM method based on multiple-criterion data fusion

Multiple-criteria decision-making (MCDM) is concerned with the ranking of decision alternatives based on preference judgements made on decision alternatives over a number of criteria. First, taking advantage of data fusion technology to comprehensively consider each criterion data is a reasonable idea to solve the MCDM problem. Second, in order to efficiently handle uncertain information in the process of decision making, some well developed mathematical tools, such as fuzzy sets theory and Dempster Shafer theory of evidence, are used to deal with MCDM. Based on the two main reasons above, a new fuzzy evidential MCDM method under uncertain environments is proposed. The rating of the criteria and the importance weight of the criteria are given by experts’ judgments, represented by triangular fuzzy numbers. Then, the weights are transformed into discounting coefficients and the ratings are transformed into basic probability assignments. The final results can be obtained through the Dempster rule of combination in a simple and straight way. A numerical example to select plant location is used to illustrate the efficiency of the proposed method.