A low distortion image enhancement scheme based on multi-resolutions analysis in next generation network

With the advent of Next Generation Network (NGN), services that are currently provided by multiple specific network-centric architectures. NGN provides AAA (Anytime, Anywhere and Always on) access to users from different service providers with consistent and ubiquitous provision of services as necessary. This special issue of NGN includes pervasive, grid, and peer-to-peer computing to provide computing and communication services at anytime and anywhere. In fact, the application of NGN includes digital image processing, multimedia systems/services, and so on. Here we focus on the digital image processing technology in NGN environments. Low-contrast structure and heavy noise in NGN environments can be found in many kinds of digital images, which makes the images vague and uncertainly, especially in x-ray images. As result, some useful tiny characteristic are weakened—which are difficult to distinguish even by naked eyes. Based on the combination of no-linear grad-contrast operator and multi-resolution wavelet analysis, a kind of image enhancement processing algorithm for useful tiny characters is presented. The algorithm can enhance the tiny characters while confine amplifying noise. The analysis of the results shows that local regions of the image are enhanced by using the concept of the grad contrast to make image clearer adaptively. Experiments were conducted on real pictures, and the results show that the algorithm is flexible and convenient.     

Extension of the DEMATEL method in an uncertain linguistic environment

The decision making trial and evaluation laboratory (DEMATEL) method is a useful tool for analyzing correlations among factors using crisp values. However, the crisp values are inadequate to model real-life situations due to the fuzziness and uncertainty that are frequently involved in judgments of experts. The aim of this paper is to extend the DEMATEL method to an uncertain linguistic environment. In this paper, the correlation information among factors provided by experts is in the form of uncertain linguistic terms. A formula is first presented to transform correlation information from uncertain linguistic terms to trapezoidal fuzzy numbers. Then, we aggregate the transformed correlation information of each expert into group information using the operations of trapezoidal fuzzy numbers. The importance and classification of factors are determined via fuzzy matrix operations. Furthermore, a causal diagram is constructed to vividly show the different roles of factors. Finally, an example is used to illustrate the procedure of the proposed method.     

Centroid Iteration algorithm for image tracking

A simple and elegant tracking algorithm called Centroid Iteration algorithm is proposed. It employs a new Background-Weighted similarity measure which can greatly reduce the influence from the pixels shared by the target template and background on localization. Experiments demonstrated the Background-Weighted measure performs much better than the other similarity measures like Kullback–Leibler divergence, Bhattacharyya coefficient and so on. It has been proved that this measure can compute the similarity value contribution of each pixel in the target candidate, based on which, a new target search method called Centroid Iteration is constructed. The convergence of the method has been demonstrated. Theory analysis and visual experiments both validated the new algorithm.     

Stochastic TCP friendliness: Expanding the design space of TCP-friendly traffic control protocols

While the current definition of TCP friendliness has enabled a wide variety of traffic control protocols other than TCP, it still considerably restricts the design space of TCP-friendly traffic control protocols. For example, some multimedia streaming applications prefer a smooth sending rate on a time scale of tens of seconds, however, a UDP flow maintaining such a long smoothness time scale is naturally not TCP friendly by the current definition. In this paper, we propose an innovative method to relatively compare the degrees of TCP friendliness of different traffic control protocols, and use it to define a new class of TCP friendliness definitions, called stochastic TCP friendliness (STF). STF greatly expands the design space of TCP-friendly traffic control protocols, while still effectively maintaining the desired fairness of the Internet. To demonstrate the expanded design space, we also develop a new congestion control protocol, called TCP-friendly CBR-Like Rate Control (TFCBR), for multimedia streaming applications which do not require a high sending rate but prefer a smooth sending rate on a time scale of tens of seconds. TFCBR is stochastically TCP friendly, however, it is not TCP friendly by the current definition.     

Stability of Impulsive Stochastic Neutral Partial Differential Equations With Infinite Delays

In this paper, we study the existence and asymptotic stability in the pth moment of the mild solutions to impulsive stochastic neutral partial differential equations with infinite delays. Sufficient conditions ensuring the stability of the impulsive stochastic system are established. The results are obtained via the Banach fixed point theorem.     

A Polynomial Algorithm for Computing Elementary Siphons in a Class of Petri Nets

A set of elementary siphons plays a key role in the development of deadlock prevention policies for automated manufacturing systems. This paper addresses the computation problem for elementary siphons in a subclass of Petri nets which are basic systems of simple sequential processes with resources (BS³PR) and can model many automated manufacturing systems. An algorithm for enumerating elementary siphons is established by the one‐to‐one relationship between maximal perfect resource‐transition circuits (MPCs) and strict minimal siphons. A set of MPCs is first computed, followed by a set of elementary siphons in a BS³PR. The presented algorithm is proved to have polynomial‐time complexity. An example is used to illustrate the algorithm.     

基于改进LS-SVM的制粉出力软测量建模

针对火电厂双进双出钢球磨煤机制粉出力较难直接测量的问题,拟建立其最小二乘支持向量机(LS-SVM)模型实现软测量.由于LS-SVM算法缺乏“稀疏性”,采用经Remez算法优化后的FIR数字滤波器与LS-SVM相结合,形成一种新的软测量建模方法——FIR-LSS-VM.仿真结果表明,经Remez优化后的FIR滤波效果更好.将该软测量方法应用于火电厂双进双出钢球磨煤机直吹式制粉系统,通过现场实验对比可知,改进的软测量模型学习速度较快且误差较小,更加适用于在线学习.     

高速动车组驾驶室设计中的人机界面分析

在高速动车组驾驶室的人机关系分析与设计中,驾驶室的空间尺度关系、视野、操纵设备的分布和人机环境等因素,将直接影响列车行驶的安全、效率、舒适和健康。应用人机关系分析与研究,合理地配置驾驶室室内环境以及操作和显示设备,将有效地提高司机操作的安全性、便利性和作业效率,从而给司机提供一个方便舒适的操作空间,减少体力、心理疲劳,降低人为误操作带来的安全隐患,提高系统运行的可靠性,使人-机匹配达到最优,以保证车辆行驶的安全。     

VB程序在铁路货车制造行业中小设备中的应用

介绍利用VB语言在铁路货车制造行业中小设备中的软件开发方案的实现,以及对铁路货车制造行业相关专业性要求适应的实现。     

基于分形扫描的高灰度平板显示的硬件实现

本文将分形算法应用于2048级高灰度平板显示的扫描映射,使用平板显示系统灰度图像的最优扫描结构及分形模型,以解决平板显示系统扫描形成灰度图像过程中的时间冗余问题。由分形扫描核心模块,得到了相应的每个扫描时间对应的子空间码和位码序列进行扫描,然后通过检测模块验证了2048级高灰度分形扫描方法的准确性,最终由硬件系统验证了2048级高灰度分形扫描的可实现性。