二维任意形状寄生电阻电容的边界元计算

由于集成电路技术高速发展,精确提取任意形状寄生电阻电容变得十分重要,本文以直接边界元素法为基础,利用圆弧样条插值近似任意曲线边界,使插值曲线具有整体一阶连续性,并克服了大挠度与多值的困扰。在直线边界使用线性连续元,在曲线边界使用二次连续无。对两邻国为直线的角点,我们曾提出处理角点处存在多重法的导数的一种方法。这里,它被推广到角点邻边含曲线段的情形。数值结果表明模拟器是可行的。     

An enhanced model framework of personalized material flow services

A growing concern about the consumer behavior in Internet economy has spurred the study of Material Flow, resulting in a unique type of consumer behavioral analysis. This research proposes an enhanced conceptual model for Personalized Material Flow Services for consumer behavior. In the era of Internet information technology, customer’s taste tends to be personalized for their market demand. It is observed that there are number of “Long Tail” phenomena in several successful e-commerce business cases. However, the Long Tail phenomenon is an open question for our research in terms of its role in e-commerce marketing. In the proposed model-X-Party Personalized Material Flow Services, three elements are discussed. They are “providing”, “locating” and “obtaining” based on X-Party Material Flow theory for which the concept of virtual collector, information filter and Material Flow coordinator are discussed. Business examples of Amazon, Dangdang and Taobao are used to analyze the elements of the virtual collector, information filter and Material Flow coordinator of the Personalized Material Flow Service system.     

Innovative product design based on customer requirement weight calculation model

In the processes of product innovation and design, it is important for the designers to find and capture customer's focus through customer requirement weight calculation and ranking. Based on the fuzzy set theory and Euclidean space distance, this paper puts forward a method for customer requirement weight calculation called Euclidean space distances weighting ranking method. This method is used in the fuzzy analytic hierarchy process that satisfies the additive consistent fuzzy matrix. A model for the weight calculation steps is constructed; meanwhile, a product innovation design module on the basis of the customer requirement weight calculation model is developed. Finally, combined with the instance of titanium sponge production, the customer requirement weight calculation model is validated. By the innovation design module, the structure of the titanium sponge reactor has been improved and made innovative.     

A virtual subnet scheme on clustering algorithms for mobile ad hoc networks

Resolving the broadcast storm problem is an important issue in mobile ad hoc networks (MANETs). In this paper, we propose an approach for constructing a virtual subnet whose nodes are logically related. The virtual subnet can be spread upon clusters of a MANET. An intelligent agent with a routing filtering table is proposed to assist the best known clustering algorithms, the original Least ID algorithm and the original Highest Connection Cluster (HCC) algorithm, to improve group communication efficiency. Our simulation covers the network factors of hop count, deprave rate, and delay time. The simulation results show that when the proposed intelligent agent is used with the HCC algorithm, the delay time was reduced by 81.84% as compared with flooding, and by 49.25% as compared with the Ad Hoc On-Demand Distance Vector (AODV) routing algorithm. The delay time for the Least ID algorithm assisted by the proposed agents reduced by 81.84% compared to that of flooding and by 50% compared to that of AODV.     

Further results of recursive evaluation for compound distribution with the severity distribution of mixed type

Yang et al. [J.P. Yang, S.H. Cheng, Q. Wu, Recursive equations for compound distribution with the severity distribution of the mixed type, Science in China Series A 48 (2005) 594-609] investigated a recursive procedure for a kind of compound distributions with the number of claims belonging to (a,b)-family and the severity distribution of the mixed type. In this paper, we extend their results by assuming that the claim number belongs to a larger class. As applications, the excess-of-loss reinsurance treaty is discussed and concrete examples are considered in some detail.     

Continuous and impulsive vaccination of SEIR epidemic models with saturation incidence rates

In this paper, two delayed SEIR epidemic models with continuous and impulsive vaccination and saturating incidence are investigated. The dynamical behaviors of the disease are analyzed. For continuous vaccination, we obtain a basic reproductive number _R1$R_1$ and prove that if _R1≤1$R_1\le 1$ then the disease-free equilibrium is globally attractive and if _R1>1$R_1>1$ then the disease is permanent by using the Lyapunov functional method. For impulsive vaccination, we obtain two thresholds R^∗$R^{\ast }$ and _R∗$R_{\ast }$ and prove that if R^∗<1$R^{\ast }<1$ then the disease-free periodic solution is globally attractive and if _R∗>1$R_{\ast }>1$ then the disease is permanent by using the comparison theorem of impulsive differential equation and the Lyapunov functional method. Lastly, we compared the effects of two vaccination strategies.     

Stable local dimensionality reduction approaches

Dimensionality reduction is a big challenge in many areas. A large number of local approaches, stemming from statistics or geometry, have been developed. However, in practice these local approaches are often in lack of robustness, since in contrast to maximum variance unfolding (MVU), which explicitly unfolds the manifold, they merely characterize local geometry structure. Moreover, the eigenproblems that they encounter, are hard to solve. We propose a unified framework that explicitly unfolds the manifold and reformulate local approaches as the semi-definite programs instead of the above-mentioned eigenproblems. Three well-known algorithms, locally linear embedding (LLE), laplacian eigenmaps (LE) and local tangent space alignment (LTSA) are reinterpreted and improved within this framework. Several experiments are presented to demonstrate the potential of our framework and the improvements of these local algorithms.     

A controllable and accountable state-oriented Card-Aided Firewall

This paper proposes a new approach, named Card-Aided Firewall (CAF) that combines the simplified firewall and the state-oriented smart card technologies to construct a controllable and accountable Internet access framework. The idea suggests that a client computer, protected by a light-weight firewall, could establish diversified authenticated communication channels, controlled and accounted by “legal” states of the smart card.The program of a smart card is state-oriented or a state machine, which defines a chain of events involving various state transitions. The “legal” states of a smart card program are defined to be legal to communicate with surfing targets. A predefined Access Control List (ACL), stored in the same card, is necessary. An ACL is a sequential list of permit or deny statements that apply to addresses or upper-layer protocols. The proposed firewall decides acceptance or rejection messages by matching the current state of the card program and the ACL. In addition, a complete surfing account for tracing back is recorded. It is a by-product of the smart card authentication.The proposed Card-Aided Firewall framework is implemented to demonstrate its effectiveness. The implementation is done at the driver level. It keeps up with the high line speed. The driver takes 39K bytes and works well with other firewalls. The average packet processing time of the CAF driver is 31.74 μs. On the premise of secure authentication within the smart card, the Card-Aided Firewall would facilitate various rapidly growing applications in campus cards, family cards, and employee cards, etc. that require accurate controllability and accountability in the surfing boundary.     

Constructive approximation to real function by wavelet neural networks

We present a type of single-hidden layer feed-forward wavelet neural networks. First, we give a new and quantitative proof of the fact that a single-hidden layer wavelet neural network with n + 1 hidden neurons can interpolate n + 1 distinct samples with zero error. Then, without training, we constructed a wavelet neural network X _a (x, A), which can approximately interpolate, with arbitrary precision, any set of distinct data in one or several dimensions. The given wavelet neural network can uniformly approximate any continuous function of one variable.