Real-time calculation of current optimal feedbacks for a delay system

A linear optimal control problem for a nonstationary system with a single delay state variable is examined. A fast implementation of the dual method is proposed in which a key role is played by a quasi-reduction of the fundamental matrices of solutions to the homogeneous part of the delay models under analysis. As a result, an iteration step of the dual method involves only the integration of auxiliary systems of ordinary differential equations over short time intervals. A real-time algorithm is described for calculating optimal feedback controls. The results are illustrated by the optimal control problem for a second-order stationary system with a fixed delay.     

Quantum entanglement in an oscillating macroscopic mirror

In this paper, we revisit the problem of quantum entanglement in an oscillating macroscopic mirror previously studied by Marshall et al. consisting of a modified Michelson interferometer where one of the mirrors is free to oscillate about its center of mass. A photon incident upon the oscillating mirror becomes entangled with the mirror, driving the mirror into a superposition of quantum states. Once the photon and mirror decouple, the mirror returns to its initial state. The purpose of our investigations was to optimize the parameter regime, taking into consideration the current state of technology and the demands imposed by the need to maintain a stable environment in the presence of thermal noise. Optimization should not demand ultra-low temperatures and this is reflected in our results. Our results also show that if the separation between states is maintained at 10^-14 m, the mirror size is reduced, making it easier to induce superposition in the mirror. The critical nature of mirror reflectivity and its connection to cavity decay rate was also revealed by our investigations. The results obtained through our investigations could be useful in quantum error correction, where decoherence negatively affects the results of computations performed by quantum computers. Finally, we note that we are only concerned with an isolated system, where no losses to the external environment occur and any decoherence that occurs within the system remains internal to the system; that is, any mention of decoherence refers specifically to recoverable decoherence.     

A methodology for developing Bayesian networks: An application to information technology (IT) implementation

Bayesian Networks (BNs) are probabilistic inference engines that support reasoning under uncertainty. This article presents a methodology for building an information technology (IT) implementation BN from client–server survey data. The article also demonstrates how to use the BN to predict the attainment of IT benefits, given specific implementation characteristics (e.g., application complexity) and activities (e.g., reengineering). The BN is an outcome of a machine learning process that finds the network’s structure and its associated parameters, which best fit the data. The article will be of interest to academicians who want to learn more about building BNs from real data and practitioners who are interested in IT implementation models that make probabilistic statements about certain implementation decisions.     

Efficient Hardware Implementation of Finite Fields with Applications to Cryptography

The paper presents a survey of most common hardware architectures for finite field arithmetic especially suitable for cryptographic applications. We discuss architectures for three types of finite fields and their special versions popularly used in cryptography: binary fields, prime fields and extension fields. We summarize algorithms and hardware architectures for finite field multiplication, squaring, addition/subtraction, and inversion for each of these fields. Since implementations in hardware can either focus on high-speed or on area-time efficiency, a careful choice of the appropriate set of architectures has to be made depending on the performance requirements and available area.     

ASM函数的综合与分析

本文提出数字系统的ASM设计的直接综合法。借此,ASM函数用其图或表,而无需推导能够直接在合适的ROM、PLA或一组MUX模块上加以综合。ASM函数的输入是经过MUX预选后送入到综合结构上的,这样能使系统函数存贮密度减小,从而使综合结构网络简化。本法使整个算法更清晰、更系统、更简化和更有效。     

An asymptotic-numerical analysis for the lower bound dynamic buckling estimates

A finite element asymptotic analysis for determining the lower bound dynamic buckling estimates of imperfection-sensitive structures under step load of infinite duration is presented. The lower bound dynamic buckling loads and the corresponding displacements are sought in the form of asymptotic expansions based on the static stability criterion and they can be determined by solving numerically (FEM) several linear problems with a single nonsingular sub-stiffness matrix. The project supported by the State Education Commission of China     

凹角型区域椭圆边值问题的自然边界归化

In this paper, the natural boundary reduction for some elliptic boundary value problems with concave angle domains and their natural boundary methods are investigated. The natural integral equations and the Poisson integral formulae are given. The finite element methods of the natural integral equations are discussed in details. The convergences of the approximate solutions and their error estimates are obtained. Finally, some numerical examples are presented to show that our methods are effective.     

高度非线性弹塑性模型的改进显式算法数值实现

当采用传统的全显式算法对高度非线性的弹塑性本构模型进行数值实现过程中,存在计算效率低、误差积累、精度较低的缺点.为提高计算效率和改善计算精度,采用四阶的Dormand and Prince Runge-Kutta法代替传统的全显式算法中的向前Euler法,并结合切平面算法形成了改进显式算法.以考虑土体结构性的SANICLAY模型为例,对传统的全显式算法、改进显式算法和隐式算法在计算收敛性、效率和精度方面进行对比.将改进显式算法用于隧道开挖工程多单元计算中.结果表明,与隐式算法相比,传统的全显式算法的计算精度和计算效率均比较低,改进显式算法计算效率和计算精度均比传统的全显式算法高很多.