An Analysis of an SIRS Epidemic Model with General Direct Immunization in Networks北大核心CSCD

We consider an SIRS epidemic model with a general direct immunization rate on networks. By constructing suitable Lyapunov functions, we find that the dynamical behvaior of the model is completely determined by the epidemic threshold λc. When λ≤λc, the disease-free equilibrium is globally asymptotically stable; when λ>λc, the endemic equilibrium is globally asymptotically stable. In addition, we propose a uniform direct immunization and a targeted direct immunization. The results show that under the same average immunization rate s there exists a critical immunization-lost rate δc so that the epidemic threshold of the targeted direct immunization is smaller (larger) than that of the uniform direct immunization if δ<δc(δ>δc). © 2017, The Journal of Agency of Complex Systems and Complexity Science. All right reserved.     

组合市场中消费者联盟形成及多方博弈的研究

关注电子商务的进一步发展,研究组合贸易中的消费者联盟形成及多方博弈问题.在给出一种多Agent中介系统控制的组合市场模型的基础上,使用群集分析方法对组合市场中大量消费者联盟形成过程的宏观动态特性进行仿真,通过数值仿真实验为组合市场中不同角色在贸易中所起的作用进行定量的分析,并为不同角色间的市场博弈提供定量分析的方法.     

Design of continuous long slot leaky-wave antenna for millimeter wave application

A simple and efficient design scheme of the continuous long slot leaky-wave antenna is developed. The key steps involved in the scheme are summarized. First, the cut-off frequencies of slot waveguides with different slot offsets are obtained by 3D finite-difference time-domain (FDTD) method. Second, the attenuation function αra is estimated by the aperture distribution, and the attenuation function αrs is determined by the slot radiation.Finally, the attenuation function αra is combined with the attenuation function αrs by the coefficient K. And an example in Ka band is presented. Moreover, the return loss of the E-plane Tee-junction (ET) and the radiation pattern of leaky-wave antenna are simulated. The scheme is verified by comparing with the experimental result.     

Resilient predictive control for a class of uncertain time-delay systems

In practice, gain perturbations of controllers which are caused by actuator degradation and other reasons often lead to performance degradation. They are capable of violating the closed-loop stability. For a system with constrained inputs, the actual controllers might exceed their limits because of gain perturbations. By the reason, this article considers the problem of resilient predictive control for a class of uncertain time-delay systems. By describing the gain perturbation as a time-varying uncertainty, the sufficient conditions to ensure the closedloop stability and the input constraints are derived. Additionally, an approach to design the resilient predictive controllers is presented in terms of LMI. Finally, the simulation shows that the proposed approach is very effective.     

Adaptive control method for nonlinear time-delay processes

Two complex properties,varying time-delay and block-oriented nonlinearity,are very common in chemical engineering processes and not easy to be controlled by routine control methods.Aimed at these two complex properties,a novel adaptive control algorithm the basis of nonlinear OFS(orthonormal functional series) model is proposed.First,the hybrid model which combines OFS and Volterra series is introduced.Then,a stable state feedback strategy is used to construct a nonlinear adaptive control algorithm that can guarantee the closed-loop stability and can track the set point curve without steady-state errors.Finally,control simulations and experiments on a nonlinear process with varying time-delay are presented.A number of experimental results validate the efficiency and superiority of this algorithm.     

The self-organizing worm algorithm

A new multi-modal optimization algorithm called the self-organizing worm algorithm (SOWA) is presented for optimization of multi-modal functions.The main idea of this algorithm can be described as followsdisperse some worms equably in the domain;the worms exchange the information each other and creep toward the nearest high point;at last they will stop on the nearest high point.All peaks of multi-modal function can be found rapidly through studying and chasing among the worms.In contrast with the classical multi-modal optimization algorithms,SOWA is provided with a simple calculation,strong convergence,high precision,and does not need any prior knowledge.Several simulation experiments for SOWA are performed,and the complexity of SOWA is analyzed amply.The results show that SOWA is very effective in optimization of multi-modal functions.     

A FRAMEWORK FOR REAL-VALUED CIPHER SYSTEMS

Most cipher systems designed thus far are binary-valued or integer-valued cipher systems. Their security relies on the assumption that one-way functions exist. Though the existence of one-way functions has not been proved yet, most cryptographic researchers believe that one-way functions exist. In addition, many candidates for one-way functions have been proposed. Therefore, the key step for developing real-valued cipher systems is to define real one-way functions and to propose candidates for them. In this paper, based on computational complexity theory over the real field, we give two definitions of real one-way functions; one is for digital one-way functions and the other is for general one-way functions. Candidates for these two classes of one-way functions are also proposed. Moreover, we present two examples to demonstrate that the candidates for both digital one-way functions and general one-way functions can be applied to construct secure real-valued cipher systems.     

System deployment optimization in architecture design

Optimization of architecture design has recently drawn research interest. System deployment optimization （SDO） refers to the process of optimizing systems that are being deployed to activi- ties. This paper first formulates a mathematical model to theorize and operationalize the SDO problem and then identifies optimal so- lutions to solve the SDO problem. In the solutions, the success rate of the combat task is maximized, whereas the execution time of the task and the cost of changes in the system structure are mini- mized. The presented optimized algorithm generates an optimal solution without the need to check the entire search space. A novel method is finally proposed based on the combination of heuristic method and genetic algorithm （HGA）, as well as the combination of heuristic method and particle swarm optimization （HPSO）. Experi- ment results show that the HPSO method generates solutions faster than particle swarm optimization （PSO） and genetic algo- rithm （GA） in terms of execution time and performs more efficiently than the heuristic method in terms of determining the best solution.     

Method of adaptive PLL bandwidth adjustment without phase slipping

In a system based on the phase lock loop（PLL）, a trade-off must be made between the tracking precision and the dynamic performance if constant parameters are adopted. To overcome this drawback, a new method called no phase slipping adaptive bandwidth（NPS-AB） is proposed, which can adjust the loop bandwidth adaptively for different working conditions. As a result, both the tracking precision and the dynamic performance can be achieved concurrently. NPS-AB has two features to keep the loop stable： one is the capability of quick response to dynamics; the other is a series of additional constraints when the bandwidth is switched. Compared with other methods, there is no phase slipping during the adjustment process for NPS-AB. The phase integer ambiguity can be avoided and the phase value is kept valid. It is meaningful for carrier ranging systems. Simulation results show that NPS-AB can deal with sudden dynamics and keep the pseudo-range value stable in the entire dynamic process.     

层式通风房间垂直温度分布预测方法

基于层式通风房间室内空气流动特性建立了室内垂直温度分布预测模型.该模型将室内空气流动特性与热质平衡方程有机结合,并反映了室内热源强度、墙体辐射及送风参数等边界条件对室内垂直温度分布的影响.通过将模型计算结果与实验数据进行对比分析,发现室内垂直温度预测值与实验数据吻合较好,并在趋势上反映出层式通风房间室内垂直温度的变化特征.因此,本文提出的模型具有较好的预测精度,能够很好地用来指导层式通风系统的实际应用及能耗分析.