Constructing up to G 2 continuous curve on freeform surface

This paper presents new methods for G ¹ and G ² continuous interpolation of an arbitrary sequence of points on an implicit or parametric surface with prescribed tangent direction and both tangent direction and curvature vector, respectively, at every point. We design a G ¹ or G ² continuous curve in three-dimensional space, construct a so-called directrix vector field using the space curve and then project a special straight line segment onto the given surface along the directrix vector field. With the techniques in classical differential geometry, we derive a system of differential equations for the projection curve. The desired interpolation curve is just the projection curve, which can be obtained by numerically solving the initial-value problems for a system of first-order ordinary differential equations in the parametric domain associated to the surface representation for the parametric case or in three-dimensional space for the implicit case. Several shape parameters are introduced into the resulting curve, which can be used in subsequent interactive modification such that the shape of the resulting curve meets our demand. The presented method is independent of the geometry and parameterization of the base surface, and numerical experiments demonstrate that it is effective and potentially useful in patterns design on surface.     

Transient model of induction machine using rotating magnetic field approach

Most simulation models of electric machines use the coupled circuit approach, where the machine is considered as an electric circuit element with time-varying inductances (abc model) or with constant inductances (dq0 model). On the other hand, the rotating magnetic field approach, which considers the electric machine as two groups of windings producing rotating magnetic fields and can give insight into internal phenomena of the machines, has not yet received much attention in electric machines modeling, especially for machine transient analysis. Based on the rotating magnetic field approach, this paper presents a transient model of the induction machine including main flux saturation effect. Based on the direct computation of the magnetizing fluxes of all machine windings, the model represents instantaneous main flux saturation by simply introducing a main flux saturation factor. No iteration process is involved to incorporate the saturation effects. The model combines the advantages of the dq0 and abc models advantages, such as rapid computation time and nonsymmetrical conditions simulation, respectively. The simulation results and the experimental tests show advantages and verification of the model.     

Exponential stability and exponential stabilization of singularly perturbed stochastic systems with time‐varying delay

In this paper, the problems of exponential stability and exponential stabilization for linear singularly perturbed stochastic systems with time‐varying delay are investigated. First, an appropriate Lyapunov functional is introduced to establish an improved delay‐dependent stability criterion. By applying free‐weighting matrix technique and by equivalently eliminating time‐varying delay through the idea of convex combination, a less conservative sufficient condition for exponential stability in mean square is obtained in terms of ε‐dependent linear matrix inequalities (LMIs). It is shown that if this set of LMIs for ε=0 are feasible then the system is exponentially stable in mean square for sufficiently small ε?0. Furthermore, it is shown that if a certain matrix variable in this set of LMIs is chosen to be a special form and the resulting LMIs are feasible for ε=0, then the system is ε‐uniformly exponentially stable for all sufficiently small ε?0. Based on the stability criteria, an ε‐independent state‐feedback controller that stabilizes the system for sufficiently small ε?0 is derived. Finally, numerical examples are presented, which show our results are effective and useful. Copyright © 2010 John Wiley & Sons, Ltd.     

PDE Toolbox和最小二乘法在导热问题中的应用

设计金属加热的控制策略,首先要获得金属导热体的开环系统模型.针对一个带有矩形孔的金属薄板上的热传导问题,采用PDE Toolbox进行求解和仿真,并用最小二乘方法进行热传导系统的建模与仿真,以获得模型中的参数.将此参数与求解微分方程方法所得到的数据进行对比,结果表明,采用最小二乘法可以更清楚地了解金属板的外部特性,并获得输入输出信号的差分方程,而求解微分方程的方法则显示了金属板的内部特性,两种方法是等效的.     

安全事件模糊等量约束的因果关联算法研究

通过对异构网络的安全事件特点的深入分析,指出在大量不完整、模糊的安全事件中准确地定位潜在的安全威胁,对态势和威胁及其重要程度进行全面及时的评估,是当前安全管理的一个技术难题.提出一种基于时间关联窗口的安全事件模糊关联算法,在一定程度上解决安全事件的漏报与领域知识的不完备性问题,对当前的安全态势、安全威胁及其重要程度进行全面及时评估提供有力的支持.     

Comparison of forecasting methods with an application to predicting excess equity premium

This paper reviews various forecast methods including combination using theoretically optimal weights and those under model selection approaches. In addition, we suggest two modified simple averaging forecast combination methods—a mean corrected and a mean and scale corrected method. We conclude that due to the fact that real data is usually subject to structural breaks, rolling forecasting scheme has a better performance than fixed window and continuously updating scheme. In addition, methods that use less information appear to perform better than methods using all the sample information about the covariance structure of the available forecasts. The mean and scale corrected simple average approach yield smaller mean squared forecast error than the three widely used regression approaches suggested by Granger and Ramanathan [11].     

Online deadline scheduling with preemption penalties

This paper presents a study of the problem of online deadline scheduling under the preemption penalty model of Zheng, Xu, and Zhang (2007). In that model, each preemption incurs a penalty of ρ times the weight of the preempted job, where ρ ? 0 is the preemption penalty parameter. The objective is to maximise the total weight of jobs completed on time minus the total penalty.     

Estimation of distribution algorithm for permutation flow shops with total flowtime minimization

In this paper, an Estimation of Distribution Algorithm (EDA) is proposed for permutation flow shops to minimize total flowtime. Longest Common Subsequence (LCS) is incorporated into the probability distribution model to mine good “genes”. Different from common EDAs, each offspring individual is produced from a seed, which is selected from the population by the roulette method. The LCS between the seed individual and the best solution found so far is regarded as good “genes”, which are inherited by offspring with a probability less than 100% to guarantee the population diversity. An effective Variable Neighborhood Search (VNS) is integrated into the proposed EDA to further improve the performance. Experimental results show that the inheritance of good “genes” obtained by LCS can improve the performance of the proposed EDA. The proposed hybrid EDA outperforms other existing algorithms for the considered problem in the literature. Furthermore, the proposed hybrid EDA improved 42 out of 90 current best solutions for Taillard benchmark instances.     

Multi-sensor calibration through iterative registration and fusion

In this paper, a new multi-sensor calibration approach, called iterative registration and fusion (IRF), is presented. The key idea of this approach is to use surfaces reconstructed from multiple point clouds to enhance the registration accuracy and robustness. It calibrates the relative position and orientation of the spatial coordinate systems among multiple sensors by iteratively registering the discrete 3D sensor data against an evolving reconstructed B-spline surface, which results from the Kalman filter-based multi-sensor data fusion. Upon each registration, the sensor data gets closer to the surface. Upon fusing the newly registered sensor data with the surface, the updated surface represents the sensor data more accurately. We prove that such an iterative registration and fusion process is guaranteed to converge. We further demonstrate in experiments that the IRF can result in more accurate and more stable calibration than many classical point cloud registration methods.     

Deadline division-based heuristic for cost optimization in workflow scheduling

Cost optimization for workflow applications described by Directed Acyclic Graph (DAG) with deadline constraints is a fundamental and intractable problem on Grids. In this paper, an effective and efficient heuristic called DET (Deadline Early Tree) is proposed. An early feasible schedule for a workflow application is defined as an Early Tree. According to the Early Tree, all tasks are grouped and the Critical Path is given. For critical activities, the optimal cost solution under the deadline constraint can be obtained by a dynamic programming strategy, and the whole deadline is segmented into time windows according to the slack time float. For non-critical activities, an iterative procedure is proposed to maximize time windows while maintaining the precedence constraints among activities. In terms of the time window allocations, a local optimization method is developed to minimize execution costs. The two local cost optimization methods can lead to a global near-optimal solution. Experimental results show that DET outperforms two other recent leveling algorithms. Moreover, the deadline division strategy adopted by DET can be applied to all feasible deadlines.