Pinning adaptive synchronization of a general complex dynamical network

There are two challenging fundamental questions in pinning control of complex networks: (i) How many nodes should a network with fixed network structure and coupling strength be pinned to reach network synchronization? (ii) How much coupling strength should a network with fixed network structure and pinning nodes be applied to realize network synchronization? To fix these two questions, we propose a general complex dynamical network model and then further investigate its pinning adaptive synchronization. Based on this model, we attain several novel adaptive synchronization criteria which indeed give the positive answers to these two questions. That is, we provide a simply approximate formula for estimating the detailed number of pinning nodes and the magnitude of the coupling strength for a given general complex dynamical network. Here, the coupling-configuration matrix and the inner-coupling matrix are not necessarily symmetric. Moreover, our pinning adaptive controllers are rather simple compared with some traditional controllers. A Barabási-Albert network example is finally given to show the effectiveness of the proposed synchronization criteria.     

基于FLDA、CPCA与HMM的人脸识别

为了获得具有较高识别率的算法,提出了一种将Fisher线性鉴别分析(Fisher Linear Discriminant Analysis)、复主分量分析(Principal Analysis in the Complex Space)与隐马尔可夫模型(Hidden Markov Models)相结合进行人脸识别的方法。对于输入的不同光照、人脸表情和姿势的图像先进行归一化处理,然后将归一化后的图像转化成一维向量,再用FLDA方法提取每幅图像的特征,形成新的复向量空间;通过运用复主分量分析,来抽取人脸图像的有效鉴别特征;最后通过HMM对这些特征进行训练,得到一个优化的HMM并应用于识别。在ORL人脸数据库中进行实验,实验结果表明,该方法具有较高的识别率。     

Spatial-temporal analysis of safety risks in trajectories of construction workers based on complex network theory

Understanding the traffic patterns of construction workers on high-risk construction sites is important for implementing behaviour-based safety management. However, safety risks in worker trajectories are a complex system with high uncertainty. This resulted in few studies focusing on analysing the spatial–temporal risk in workers' trajectories from a systematic perspective. This study designs a new framework to explore the spatial–temporal patterns of safety risks in the trajectories of construction workers based on complex network theory. First, an integrated site safety risk classification method by combining hazard sources and group trajectory distribution is developed to accurately describe the spatial distribution of site risks. Second, a new complex network chronnet is used to construct complex networks containing risk information for spatial–temporal analysis. Finally, key risk areas and risk transition patterns are identified through the analysis of network measures. The study also developed a computational program that allows the network to be constructed and analysed in real-time. The feasibility and effectiveness of the method are verified through a case study. The results show that the method can reveal the risk distribution at the micro level, and explore the risk clustering and transition features in worker trajectories at the macro level. The study allows for an accurate analysis of dynamic risk patterns in construction workers' trajectories from a systematic perspective. It can also provide theoretical and practical support for personalized and adaptive behaviour-based safety management for construction workers.     

Iron working at Zambana el Vato (TN), Italy

ABSTRACT

The workshop of Zambana el Vato (region Trentino, Northern Italy), is dated to the period between the 7th-6th and the 5th century BC. Iron working activities are clearly recognizable from the various finds. Among them there are working slag, heated clay, fragments of hearth or forge, hammerscale and more residues that can be referred to iron technology. A number of selected specimens were sectioned and mounted for photomicroscopy to identify the structure and some of the mounted samples were also examined by scanning electron microscopy (SEM) using both a back scattered electron detector and energy dispersive (EDS) x-ray analysis. This paper presents the results of these studies. The hearths were regularly repaired, as their fragments were found mixed with working slag. The hammerscale samples indicate that there were three iron-working areas. The fragments of forge with traces of tuyeres indicate that bellows were employed. Refining slag was identified among the debris. This is particularly significant as for the moment no iron refining centers are known in this area.     

A Non-Contact Original-State Online Real-Time Monitoring Method for Complex Liquids in Industrial Processes

Failures are very common during the online real-time monitoring of large quantities of complex liquids in industrial processes, and can result in excessive resource consumption and pollution. In this study, we introduce a monitoring method capable of non-contact original-state online real-time monitoring for strongly coated, high-salinity, and multi-component liquids. The principle of the method is to establish the relationship among the concentration of the target substance in the liquid (C), the color space coordinates of the target substance at different concentrations (L¹, a¹, b¹), and the maximum absorption wavelength (λ_max); subsequently, the optimum wavelength λ_T of the liquid is determined by a high-precision scanning-type monitoring system that is used to detect the instantaneous concentration of the target substance in the flowing liquid. Unlike traditional monitoring methods and existing online monitoring methods, the proposed method does not require any pretreatment of the samples (i.e., filtration, dilution, oxidation/reduction, addition of chromogenic agent, constant volume, etc.), and it is capable of original-state online real-time monitoring. This method is employed at a large electrolytic manganese plant to monitor the Fe³⁺ concentration in the colloidal process of the plant’s aging liquid (where the concentrations of Fe³⁺, Mn²⁺, and (NH₄)₂SO₄ are 0.5–18 mg·L⁻¹, 35–39 g·L⁻¹, and 90–110 g·L⁻¹, respectively). The relative error of this monitoring method compared with an off-line laboratory monitoring is less than 2%.     

Synchronization of complex dynamical networks under recoverable attacks

In this paper, the synchronization of complex dynamical networks (CDNs) under ‘successful’ but recoverable attacks is studied by utilizing the framework of switching systems. ‘Successful’ attacks refer to a class of attacks that break a network into a group of isolated clusters. Recoverable attacks refer to a class of attacks that the network can recover from after a period of time. To facilitate the investigation of the synchronization of a CDN under ‘successful’ but recoverable attacks, the attack frequency and the average recovering time are introduced. By using a piecewise Lyapunov function, the upper bounds of the attack frequency and the average recovering time are obtained to ensure that the whole network can achieve global synchronization under attacks.     

A relativistic extension of the complex scaling method using oscillator basis functions

We develop the complex scaling method within the relativistic framework by expanding the Dirac spinors in the complete set of eigensolutions of a harmonic oscillator potential, and present the theoretical formalism of describing the discrete bound and resonant states on the same footing. Based on a well established and frequently used model, we demonstrate the utility and applicability of the extended method and examine the stability of the results with respect to the variations of the parameters of the model. Satisfactory agreements are found for all the calculated results in comparison with some other calculations in references. Especially, the present calculation in the nonrelativistic limit gives a consistent result with that in the nonrelativistic calculation.     

A systematic method for efficient computation of full and subsets Zernike moments

A new method is proposed for fast and accurate computation of Zernike moments. This method presents a novel formula for computing exact Zernike moments by using exact complex moments where the exact values of complex moments are computed by mathematical integration of the monomials over digital image pixels. The proposed method is applicable to compute the full set of Zernike moments as well as the subsets of individual order, repetition and an individual moment. A comparison with other conventional methods is performed. The results show the superiority of the proposed method.     

Adaptive synchronization of uncertain coupled stochastic complex networks

In this paper, the problem of adaptive synchronization of uncertain coupled complex networks is investigated. Some controllers and adaptive laws are designed to ensure achieving synchronization of a general complex network model. In particular, synchronization of coupled stochastic networks subject to random perturbations is studied, with a referenced node introduced as the target node for synchronization. An example is simulated on delayed neural networks coupled in a small‐world network topology, which demonstrates the feasibility and effectiveness of the proposed adaptive control method. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Q-shift二元树复小波在图像融合中的应用

复小波滤波器的构造较为复杂,采用Q-shift方法构造的二元树能有效地逼近复小波的实部和虚部特征,且具有近似的平移不变性;将二元树复小波变换用于不同传感器图像的融合,对来自不同传感器图像进行Dual-Tree CWT分解,得到2个低频子图和6个高频子图,将低频部分进行加权平均,高频部分采用最大值选取法进行融合。对融合结果的性能采用熵、均方根误差、平均梯度和相关系数进行评估,并与其它融合算法进行比较,结果表明:本融合方法优于同等环境下的其它方法。