Research on improved integrated FDD/FTC with effectiveness factors

This paper investigates the integrated fault detection and diagnosis(FDD) with fault tolerant control(FTC) method of the control system with recoverable faults.Firstly,a quasi-linear parameter-varying(QLPV) model is set up,in which effectiveness factors are modeled as time-varying parameters to quantify actuators and sensors faults.Based on the certainty equivalency principle,replacing the real time states in the nonlinear term of the QLPV model with the estimated states,the parameters and states can be estimated by a two-stage Kalman filtering algorithm.Then,a polynomial eigenstructure assignment(PEA) controller with time-varying parameters and states is designed to guarantee the performance of the system with recoverable faults.Finally,mathematical simulation is performed to validate the solution in a satellite closed-loop attitude control system,and simulation results show that the solution is fast and effective for on-orbit real-time computation.     

Fuzzy neural network image filter based on GA

A new nonlinear image filter using fuzzy neural network based on genetic algorithm is proposed. The learning of network parameters is performed by genetic algorithm with the efficient binary encoding scheme. In the following, fuzzy reasoning embedded in the network aims at restoring noisy pixels without degrading the quality of fine details. It is shown by experiments that the filter is very effective in removing impulse noise and significantly outperforms conventional filters.     

New cooperative frequency domain differential modulation and demodulation

An innovative method of cooperative frequency domain differential modulation and demodulation is presented.This method applies the prior knowledge of channel propagation to selecting the variable differential length and carrying out frequency domain modulation.This strategy optimizes the design of system parameters to effectively improve the anti-interference ability of the differential system in time-varied multipath channel circumstance without making the execution more complicating.The simulations and comparisons demonstrate the proposed method is effective,and the results show that it is especially suitable for the fading channel with strong propagation and fast time-variation.     

Parameter selection of support vector machine for function approximation based on chaos optimization

The support vector machine （SVM） is a novel machine learning method, which has the ability to approximate nonlinear functions with arbitrary accuracy. Setting parameters well is very crucial for SVM learning results and generalization ability, and now there is no systematic, general method for parameter selection. In this article, the SVM parameter selection for function approximation is regarded as a compound optimization problem and a mutative scale chaos optimization algorithm is employed to search for optimal paraxneter values. The chaos optimization algorithm is an effective way for global optimal and the mutative scale chaos algorithm could improve the search efficiency and accuracy. Several simulation examples show the sensitivity of the SVM parameters and demonstrate the superiority of this proposed method for nonlinear function approximation.     

Global minimization of adaptive local image fitting energy for image segmentation

The active contour model based on local image fitting （LIF） energy is an effective method to deal with intensity inhomo- geneities, but it always conflicts with the local minimum problem because LIF has a nonconvex energy function form. At the same time, the parameters of LIF are hard to be chosen for better per- formance. A global minimization of the adaptive LIF energy model is proposed. The regularized length term which constrains the zero level set is introduced to improve the accuracy of the bound- aries, and a global minimization of the active contour model is presented, in addition, based on the statistical information of the intensity histogram, the standard deviation σ with respect to the truncated Gaussian window is automatically computed according to images. Consequently, the proposed method improves the performance and adaptivity to deal with the intensity inhomo- geneities. Experimental results for synthetic and real images show desirable performance and efficiency of the proposed method.     

Robust exponential stabilization of uncertain nonholonomic chained systems based on visual feedback

The visual serving stabilization for a kind of nonholonomic mobile robots with uncalibrated camera parameters is investigated based on the visual feedback and the state and input transformations. The authors obtain a new uncertain model of the nonholonomic kinematic system in the image plane,which is a chained form with uncalibrated visual parameters,from the camera robotic system. A new time varying feedback controller is proposed for the exponential stabilization of the nonholonomic chained system with unknown parameters by using state-scaling and switching technique.The exponential stability of the closed loop system is rigorously proved.Simulation results demonstrate the effectiveness of the proposed methods.     

Parameter estimation for dual-rate sampled Hammerstein systems with dead-zone nonlinearity

The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data.Firstly,the auxiliary model identification principle is used to estimate the unmeasurable variables,and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the parameters of the dynamic linear system model.Then,the convergence of the proposed identification algorithm is analyzed by using the martingale convergence theorem.It is proved theoretically that the estimated parameters can converge to the real values under the condition of continuous excitation.Finally,the validity of the proposed algorithm is proved by the identification of the dual-rate sampled nonlinear systems.     

Group consensus for multiple networked Euler-Lagrange systems with parametric uncertainties

In this paper,a group consensus problem is investigated for multiple networked agents with parametric uncertainties where all the agents are governed by the Euler-Lagrange system with uncertain parameters.In the group consensus problem,the agents asymptotically reach several different states rather than one consistent state.A novel group consensus protocol and a time-varying estimator of the uncertain parameters are proposed for each agent in order to solve the couple-group consensus problem.It is shown that the group consensus is reachable even when the system contains the uncertain parameters.Furthermore,the multi-group consensus is discussed as an extension of the couple-group consensus,and then the group consensus with switching topology is considered.Simulation results are finally provided to validate the effectiveness of the theoretical analysis.     

Novel approach for identifying Z-axis drift of RLG based on GA-SVR model

This paper describes a novel approach for identifying the Z-axis drift of the ring laser gyroscope （RLG） based on ge-netic algorithm （GA） and support vector regression （SVR） in the single-axis rotation inertial navigation system （SRINS）. GA is used for selecting the optimal parameters of SVR. The latitude error and the temperature variation during the identification stage are adopted as inputs of GA-SVR. The navigation results show that the proposed GA-SVR model can reach an identification accuracy of 0.000 2 （？）/h for the Z-axis drift of RLG. Compared with the ra-dial basis function-neural network （RBF-NN） model, the GA-SVR model is more effective in identification of the Z-axis drift of RLG.     

A calculus for services innovation

Innovation in the services area - especially in the electronic services （e-services） domain - can be systematically developed by first considering the strategic drivers and foci, then the tactical principles and enablers, and finally the operational decision attributes, all of which constitute a process or calculus of services innovation. More specifically, there are four customer drivers （i.e., collaboration, customization, integration and adaptation）, three business foci （i.e., creation-focused, solution-focused and competition-focused）, six business principles （i.e., reconstruct market boundaries, focus on the big picture not numbers, reach beyond existing demand, get strategic sequence right, overcome organizational hurdles and build execution into strategy）, eight technical enablers （i.e., software algorithms, automation, telecommunication, collaboration, standardization, customization, organization, and globalization）, and six attributes of decision informatics （i.e., decision-driven, information-based, real-time, continuously-adaptive, customer-centric and computationally-intensive）. It should be noted that the four customer drivers are all directed at empowering the individual - that is, at recognizing that the individual can, respectively, contribute in a collaborative situation, receive customized or personalized attention, access an integrated system or process, and obtain adaptive real-time or just-in-time input. The developed process or calculus serves to identify the potential white spaces or blue oceans for innovation. In addition to expanding on current innovations in services and related experiences, white spaces are identified for possible future innovations; they include those that can mitigate the unforeseen consequences or abuses of earlier innovations, safeguard our rights to privacy, protect us from the always-on, interconnected world, provide us with an authoritative search engine, and generate a GDP metric that can adequately measure the growing knowledge economy,     

网络系统可靠性研究现状与展望

首先探讨了网络系统可靠性的发展历程、概念与特点,进而从度量参数、建模、分析、优化4个方面系统综述了网络系统可靠性的研究现状,最后对网络系统可靠性研究未来的发展进行了展望。     

HEALTHCARE： A COMPLEX SERVICE SYSTEM

Healthcare is indeed a complex service system, one requiring the technobiology approach of systems engineering to underpin its development as an integrated and adaptive system. In general, healthcare services are carried out with knowledge-intensive agents or components which work together as providers and consumers to create or co-produce value. Indeed, the engineering design of a healthcare system must recognize the fact that it is actually a complex integration of human-centered activities that is increasingly dependent on information technology and knowledge. Like any service system, healthcare can be considered to be a combination or recombination of three essential components — people (characterized by behaviors, values, knowledge, etc.), processes (characterized by collaboration, customization, etc.) and products (characterized by software, hardware, infrastructures, etc.). Thus, a healthcare system is an integrated and adaptive set of people, processes and products. It is, in essence, a system of systems which objectives are to enhance its efficiency (leading to greater interdependency) and effectiveness (leading to improved health). Integration occurs over the physical, temporal, organizational and functional dimensions, while adaptation occurs over the monitoring, feedback, cybernetic and learning dimensions. In sum, such service systems as healthcare are indeed complex, especially due to the uncertainties associated with the human-centered aspects of these systems. Moreover, the system complexities can only be dealt with methods that enhance system integration and adaptation.     

Is Hypermobility a Challenge for Transport Ethics and Systemicity?

Modern modes of transport, in the developed world, were designed to achieve higher mobility (or speed) and increased accessibility, all in the name of growth and human progress. However, in the course of providing for this higher mobility, through the rapid expansion of the transport system, we have ended up with a condition of imbalanced mobility, which we refer to as "hypermobility," particularly with reference to the automobile mode. Ironically, this very expansion of the transport network, with the objective of providing higher transport speeds, has resulted in traffic congestion that has drastically reduced mobility and accessibility, thereby lowering business productivity, increasing fuel consumption, increasing pollution, and robbing the public of billions of hours of valuable time. In light of the present unsustainable conditions, we examine and analyze the concepts of mobility through an inquiry of time, space, human freedom, and social justice from an ethical and systemic viewpoint. We conclude that if hypermobility is not dealt with both as an individual and as a collective responsibility, the challenge to transport ethics and its systemicity could be further impaired.     

Enterprise resource planning implementation decision & optimization models

To study the uncertain optimization problems on implementation schedule, time-cost trade-off and quality in enterprise resource planning (ERP) implementation, combined with program evaluation and review technique (PERT), some optimization models are proposed, which include the implementation schedule model, the timecost trade-off model, the quality model, and the implementation time-cost-quality synthetic optimization model. A PERT-embedded genetic algorithm (GA) based on stochastic simulation technique is introduced to the optimization models solution. Finally, an example is presented to show that the models and algorithm are reasonable and effective, which can offer a reliable quantitative decision method for ERP implementation.     

电子商务信息安全人员的素质测评指标体系

为了确保电子商务业务过程中的信息安全,分析了电子商务信息安全工作具有保密性、完整性、真实性、灵活性、合法性、有效性等特征及其对电子商务从业人员的素质要求,建立了包括品德、智能、态度、资历、个性、身体等方面的素质结构指标体系,并运用了模糊数学模型和德尔菲法去确定各个测评项目及所属的各个测评指标的评价等级及权重,最后建立并分析了电子商务信息安全人员素质综合评价矩阵,帮助企业识别和甄选符合电子商务信息安全职务任职资格的优秀人员.     

有色Petri网在系统分析中的应用

Coloured Petri网(简称CP-nets或CPN)是一种用于设计、详细说明、仿真和检验的面向 图形的语言。它特别适合于那些通讯、同步、资源共享非常重要的系统。例如应用程序间的通讯协 议、分布式系统、嵌入式系统、自动化生产系统、工作流分析和超大规模集成电路芯片。     

电子产品多物理场耦合仿真方法研究

多物理场耦合涉及机械、电磁、流体、热、声等学科,对产品性能有直接影响。针对电子产品,研究其共同属性、基本场及耦合模式、各场间耦合关系,提出一种面向电子产品的多场耦合协同仿真方法和仿真框架,并以机架式服务器为例,提出了协同仿真流程和内容,并采用Pro/E、FLOTHERM和FLUENT等软件进行了多场耦合仿真,特别是气—声耦合的噪声分析。仿真结果验证了多场耦合协同仿真方法,对预测和优化产品性能具有一定指导意义。     

当前仿真方法学发展中的若干问题

近十年来，由于对巨型复杂系统的研究，促使仿真方法学有了新的发展，本文讨论了一些有关问题，包括：定时仿真；面向对象的仿真，分布交互式仿真，虚拟现实等。     

农田系统研究进展

2004-2010年中央的一号文件都是关于＂三农＂问题。中国农业发展历史悠久,在世界具有独特性。河南省作为全国第一人口、农业、粮食、粮食加工大省,在全国农田系统研究中更具代表性和特殊性。已有文献从4个方面对农田系统开展研究：第一,地形视角,分为山地、平原区、丘陵区农田系统;第二,研究内容方面,施肥、养分及其流失,化感作用,碳平衡,受污农田,生物多样性,LUCC变化;第三,耕作方式视角,可划分为轮作、间作、免耕等农田系统类型;第四,研究方法上,有经济学方法、生态学方法、物理学方法、3S技术方法等。目前成果尚存在以下不足：第一,对传统农区关注不够;第二,3S技术应用范围急需扩展;第三,田野调查方法运用不足;第四,微观视角研究欠缺。并且,在农田与环境相互作用机理、农田区位理论、农田结构及其动态分化研究、研究方法的综合运用、不同尺度农田系统运行模式的总结、中国农田系统研究等方面尚待加强。进一步提出了农田的发展趋势：数量进一步减少;产出逐渐提高、但弱势地位难以改观;产出差异扩大;发展模式更趋多元化;集聚经济将重现活力;影响因素更趋复杂。