Global exponential stability of non-autonomous FCNNs with Dirichlet boundary conditions and reaction–diffusion terms

In this paper, we investigate the global exponential stability of non-autonomous fuzzy cellular neural networks (FCNNs) with Dirichlet boundary conditions and reaction–diffusion terms. By constructing a suitable Lyapunov functional and utilizing some inequality techniques, we obtain some sufficient conditions for the uniqueness and global exponential stability of the equilibrium solution. The result is easy to check and plays an important role in the design and applications of globally exponentially stable fuzzy neural circuits. Finally, the utility of our result is illustrated via a numerical example.     

Revised multi-choice goal programming for multi-period,multi-stage inventory controlled supply chain model with popup stores in Guerrilla marketing

In this paper, we consider a supply chain network design problem with popup stores which can be opened for a few weeks or months before closing seasonally in a marketplace. The proposed model is multi-period and multi-stage with multi-choice goals under inventory management constraints and formulated by 0–1 mixed integer linear programming. The design tasks of the problem involve the choice of the popup stores to be opened and the distribution network design to satisfy the demand with three multi-choice goals. The first goal is minimization of the sum of transportation costs in all stages; the second is to minimization of set up costs of popup stores; and the third goal is minimization of inventory holding and backordering costs. Revised multi-choice goal programming approach is applied to solve this mixed integer linear programming model. Also, we provide a real-world industrial case to demonstrate how the proposed model works.     

Nanoporous Nanocomposite Hydrogels Composed of Polyvinyl Alcohol and Na-montmorillonite

Polyvinyl alcohol nanoporous nanocomposite hydrogels containing various levels of Na-montmorillonite were prepared by a cyclic freezing–thawing technique. An exfoliated morphology of silicate layers was observed for the nanocomposite hydrogels. The uniaxial tensile test indicated that the tensile modulus and tensile strength of the nanocomposite hydrogels increased with increasing Na-montmorillonite content, while their elongation-at-break values decreased. The results showed that by adding 15 wt% of montmorillonite to polyvinyl alcohol hydrogels, the molecular weight of polymer chains between two adjacent cross-links decreased to 56% and the effective cross-linking density increased up to 353%. It is also indicated that all nanocomposite hydrogel samples had nanoscale pore diameters and network mesh sizes less than 30 nm. The nanoporous structure of the nanocomposite hydrogels was confirmed by transmission electron microscopy observations and mercury intrusion porosimetry tests.     

Dynamic Mechanical Properties of Aged Filled Rubbers

Abstract

It is well known that the macromolecular structure and the microstructure of the fillers play an important role in the mechanical properties of filled rubbers. This paper focuses on the dependence of the complex modulus of aged natural rubber vulcanizates on the filler network and polymer structure. Dynamic mechanical analysis (DMA) at 30°C, 50°C, and 70°C on the aged rubbers with/without prestrain showed the Payne effect, i.e., a storage modulus drop with increasing amplitude, and the appearance of a loss tangent maximum at strain of about a few percent. The storage modulus increased with the aging time at 70°C, 24 < 72 < 240 hr, in the case of nonprestrain. When the prestrain was applied, strain‐induced crystallization was generated that enhanced the storage modulus. As time passed, the prestrain relaxed and the crystalline structures began to disappear. After 72 hr, the crystalline structures had almost disappeared, and they had only a weak effect. Consequently, there existed a higher modulus for an aging time of 24 hr than 72 hr at testing temperatures of 30°C and 50°C. It was concluded that the storage modulus was determined by the postvulcanization, strain‐induced crystallization, aging, and relaxing time.     

Simulation of Electrical Resistivity of Carbon Black Filled Rubber under Elongation

It has been known that the carbon black (CB) network is responsible for the electrical and mechanical behaviors of filled rubber. Due to the complexity involved in the filled rubber in relation to the conductive mechanism of the CB network, there has been little work concerned with simulation of the electrical behavior at large strains. Based upon an infinite circuit model, the electrical resistivity of CB filled rubber under elongation is simulated. For CB (N330) filled natural rubber with volume fraction of 27.5%, the simulated electrical resistivity increases with elongation at small stains, corresponding to the breakup of the agglomerates. The reduction in resistivity at larger strains corresponds to the decrease of the junction width, which results in a decrease of the contact resistance. Good agreement is found between the simulations and the experimental data available in the literature. The simulated results confirm the effects of the breakdown of the CB network and the alignment of CB aggregates under strain on the electrical resistivity.     

Investigation of Carbon Black Network in Natural Rubber with Different Bound Rubber Contents

A new method was applied to modify the surface activity of virginal carbon black (VCB). LA‐57, one kind of hindered amine light stabilizer, was adsorbed onto the carbon black surface through a strong shear force induced by the screws of a HAAKE internal mixer. The modified carbon black (MCB) was characterized by FT‐IR and thermogravimetric analysis (TGA). The bound rubber content of the natural rubber (NR) compounded with MCB and VCB varied with the fraction of LA‐57 on the MCB surface. The nonlinear effect at small strains, generally referred as the Payne effect, was investigated in the rubber compounds based on the different bound rubber contents. The NR compound containing the lowest bound rubber content had an obvious Payne effect. Based on the bound rubber content, the types of filler network varied from direct contact mode to the joint rubber shell mechanism.     

智能电网的10G-EPON中基于贝叶斯分类的业务感知机制

随着智能电网的发展及其多种信息业务的涌现,10G-EPON作为业务接入技术日益成为重要支撑;然而业务的多元化对10G-EPON的多业务支撑能力提出了重要挑战.为了适应电力系统中多种不同类型业务的需求,本文对智能电网的信息业务特性进行分析,提出了一种基于贝叶斯分类的10G-EPON业务感知机制;并且根据10G-EPON中OLT与ONU的主从式网络架构特点,提出了业务感知的主从式实现方式.该机制使用贝叶斯网络分析数据包的特征,进而确认待传送业务的类型.在贝叶斯业务分类的基础上,通过OLT和ONU之间的交互决定业务的资源分配和传输策略.为了验证新机制的有效性,分别从时延和丢包率两方面进行系统仿真.仿真结果表明,所提出的基于贝叶斯分类的业务感知机制在时延和丢包率具有显著的优势,能够实现业务与10G-EPON的高效匹配,提高10G-EPON在智能电网应用中多业务的区分支持能力.     

基于网络技术的虚拟实验设计

介绍了所设计的虚拟实验系统,对系统方案、基本功能以及在设计过程中所遇到的一些设计问题进行分析并提出了解决方法。     

基于局域相关向量机回归模型的小尺度网络流量的非线性预测

基于非线性时间序列局域预测法与相关向量机回归模型, 本文提出了局域相关向量机预测方法, 并应用于预测实际的小尺度网路流量序列. 应用基于信息准则的局域预测法邻近点的选取方法来选取局域相关向量机回归模型的邻近点个数. 对比分析了局域相关向量机预测法、前馈神经网络模型与局域线性预测法对网络流量序列的预测性能, 其中前馈神经网络模型的参数采用粒子群优化算法来优化. 实验结果表明: 邻近点优化后的局域相关向量机回归模型能够有效地预测小尺度网络流量序列, 归一化均方误差很小; 局域相关向量机回归模型生成的时间序列具有与原网络流量时间序列相一致的概率分布; 局域相关向量机回归模型的预测精度好于前馈神经网络模型的与局域线性预测法的. 关键词： 小尺度网络流量 非线性时间序列预测方法 局域预测法 相关向量机回归模型     

簇间连接方式不同的簇网络的同步过程研究

本文对簇间连接方式不同的三类簇网络的同步能力和同步过程进行研究. 构成簇网络的两个子网均为BA无标度网络, 当簇间连接方式是双向耦合时, 称其为TWD网络模型, 当簇间连接是大子网驱动小子网时, 称其为BDS网络模型, 当簇间连接是小子网驱动大子网时, 称其为SDB网络模型. 研究表明, 当小子网和大子网节点数目的比值大于某一临界值时, TWD网络模型的同步能力大于BDS网络模型的同步能力, 当该比值小于某一临界值时, TWD网络模型的同步能力小于BDS网络模型的同步能力, SDB网络模型的同步能力是三种网络结构中最差的. 对于簇间连接具有方向性的单向驱动网络, 簇网络的整体同步能力与被驱动子网的节点数和簇间连接数有关, 与驱动网络自身节点数无关. 增加簇间连接数在开始时会降低各子网的同步速度, 但最终各子网到达完全同步的时间减少, 网络的整体同步能力增强. 文中以Kuramoto相振子作为网络节点, 研究了不同情况下三种簇网络的同步过程, 证明了所得结论的正确性. 关键词： 簇网络 有向连接 同步能力 Kuramoto振子