Nanotribological study of PECVD DLC and reactively sputtered Ti containing carbon films

Amorphous carbon film, also known as DLC film, is a promising material for tribological application. It is noted that properties relevant to tribological application change significantly depending on the method of preparation of these films. These properties are also altered by the compositions of these films. DLC films are well known for their self-lubricating properties, as well. In view of this, the objective of the present work is to compare the tribological properties of diamond like carbon (DLC) film obtained by plasma enhanced chemical vapour deposition (PECVD) with the Ti containing nanocrystalline carbon (Ti/a-C:H) film obtained by unbalanced magnetron sputter deposition (UMSD) in nN load range. Towards that purpose, DLC and Ti/a-C:H films are deposited on silicon substrate by PECVD and UMSD processes respectively. The microstructural features and the mechanical properties of these films are determined by scanning electron microscope (SEM), transmission electron microscope (TEM) and nano indenter. The surface topographies and the friction force surfaces of these films are evaluated by means of an atomic force microscope (AFM). The results show that although PECVD DLC film has higher elastic modulus and higher hardness than UMSD Ti/a-C:H film, the surface roughness and the friction coefficient of PECVD film is significantly higher than that of UMSD Ti/a-C:H film.     

Synthesis of chaoite-like macrotubes at low temperature and ambient pressure

Chaoite-like carbon was prepared by quenching the pyrolysate of acetylene gas at 873 K and ambient pressure. Its morphology is carbon macrotubes (CMTs) with 20–60 μm in diameter and up to 8 mm in length. Microstructure analysis revealed that sp-bonded carbon (SPBC) chains in CMTs are kinked and the crystal orientation is anisotropic along the length and circumference directions of CMTs. A SPBC belt scrolling model was proposed for explaining the formation process of CMTs.     

A general non-local denoising model using multi-kernel-induced measures

Noises are inevitably introduced in digital image acquisition processes, and thus image denoising is still a hot research problem. Different from local methods operating on local regions of images, the non-local methods utilize non-local information (even the whole image) to accomplish image denoising. Due to their superior performance, the non-local methods have recently drawn more and more attention in the image denoising community. However, these methods generally do not work well in handling complicated noises with different levels and types. Inspired by the fact in machine learning field that multi-kernel methods are more robust and effective in tackling complex problems than single-kernel ones, we establish a general non-local denoising model based on multi-kernel-induced measures (GNLMKIM for short), which provides us a platform to analyze some existing and design new filters. With the help of GNLMKIM, we reinterpret two well-known non-local filters in the united view and extend them to their novel multi-kernel counterparts. The comprehensive experiments indicate that these novel filters achieve encouraging denoising results in both visual effect and PSNR index.     

Decentralized control: Status and outlook

This paper reviews state of the art in the area of decentralized networked control systems with an emphasis on event-triggered approach. The models or agents with the dynamics of linear continuous-time time-invariant state-space systems are considered. They serve for the framework for network phenomena within two basic structures. The I/O-oriented systems as well as the interaction-oriented systems with disjoint subsystems are distinguished. The focus is laid on the presentation of recent decentralized control design and co-design methods which offer effective tools to overcome specific difficulties caused mainly by network imperfections. Such side-effects include communication constraints, variable sampling, time-varying transmission delays, packet dropouts, and quantizations. Decentralized time-triggered methods are briefly discussed. The review is deals mainly with decentralized event-triggered methods. Particularly, the stabilizing controller–observer event-based controller design as well as the decentralized state controller co-design are presented within the I/O-oriented structures of large scale complex systems. The sampling instants depend in this case only on a local information offered by the local feedback loops. Minimum sampling time conditions are discussed. Special attention is focused on interaction-oriented system architecture. Model-based approach combined with event-based state feedback controller design is presented, where the event thresholds are fully decentralized. Finally, several selected open decentralized control problems are briefly offered as recent research challenges.     

An FAR-SW based approach for webpage information extraction

Automatically identifying and extracting the target information of a webpage, especially main text, is a critical task in many web content analysis applications, such as information retrieval and automated screen reading. However, compared with typical plain texts, the structures of information on the web are extremely complex and have no single fixed template or layout. On the other hand, the amount of presentation elements on web pages, such as dynamic navigational menus, flashing logos, and a multitude of ad blocks, has increased rapidly in the past decade. In this paper, we have proposed a statistics-based approach that integrates the concept of fuzzy association rules (FAR) with that of sliding window (SW) to efficiently extract the main text content from web pages. Our approach involves two separate stages. In Stage 1, the original HTML source is pre-processed and features are extracted for every line of text; then, a supervised learning is performed to detect fuzzy association rules in training web pages. In Stage 2, necessary HTML source preprocessing and text line feature extraction are conducted the same way as that of Stage 1, after which each text line is tested whether it belongs to the main text by extracted fuzzy association rules. Next, a sliding window is applied to segment the web page into several potential topical blocks. Finally, a simple selection algorithm is utilized to select those important blocks that are then united as the detected topical region (main texts). Experimental results on real world data show that the efficiency and accuracy of our approach are better than existing Document Object Model (DOM)-based and Vision-based approaches.     

Fault-tolerant shortest connection topology design for formation control

This paper studies the fault tolerant formation keeping problem of multi-agent systems with consideration of shortest connection topology. This is motivated by the requirement of low communication cost which largely depends on the communication length. Given a formation shape, a connection topology design method and its reconfiguration strategy are proposed in the sense that the whole connection path is shortest despite of communication faults. A control framework that combines the individual formation controller of each agent and connection topology is further presented. The stability of the whole system process is analyzed by switched system theories. Simulation results of unmanned aerial vehicles (UAVs) show the effectiveness of the proposed strategy.     

基于梯度的受限空间安全定位方法

现有的无线传感器网络定位技术消耗了大量的计算和处理资源,并且受到了环境因素以及对手攻击等干扰,在受限空间中定位精度较低,无法满足定位需求。为了提高受限空间中的定位精度,提出了一种基于梯度的安全定位算法,算法在双曲线定位模型基础上,引入梯度的概念,降低了算法的计算复杂度,使算法能够适应受限空间的环境要求,实现高效高精度的定位;为了提高算法的安全性,增加了对不一致性测量的选择性剪枝过程,增强了算法对恶意攻击的抵抗能力。最后,以室内走廊为实验环境进行了仿真验证,通过主频计时策略,提高了算法的定位精度。分析结果表明,在室内受限空间中,提出的算法在定位精度、能量消耗和抗干扰能力上优于现有算法。     

基于线性动态系统稀疏编码的异常事件检测

线性动态系统模型结合稀疏编码实现异常事件检测。线性动态系统可有效地捕捉动态纹理在时间和空间的转移信息,描述视频的时空小块。然而,线性动态系统属于非欧氏空间,无法直接用传统的稀疏编码进行异常检测。基于约束凸优化公式,将相似性变换与稀疏编码结合,可实现线性动态系统稀疏编码的优化求解。实验表明,所提出的方法具有更好的性能。     

基于量子克隆的二面体群隐含子群问题量子算法的研究

基于最短向量问题的格公钥密码体制是典型的抗量子计算密码体制。格的唯一最短向量问题可转化为二面体群的隐含子群问题。有效地求解二面体群的隐含子群问题可攻破基于格的唯一最短向量问题的公钥密码体制。Kuperberg提出了二面体群隐含子群问题的半指数级量子算法。通过研究Kuperberg量子算法,利用概率量子克隆,文中提出了二面体群隐含子群问题的多项式时间量子算法。