Qualitative Differences Between Conscious and Nonconscious Processing? On Inverse Priming Induced by Masked Arrows.

In general, both consciously and unconsciously perceived stimuli facilitate responses to following similar stimuli. However, masked arrows delay responses to following arrows. This inverse priming has been ascribed to inhibition of premature motor activation, more recently even to special processing of nonconsciously perceived material. Here, inverse priming depended on particular masks, was insensitive to contextual requirements for increased inhibition, and was constant across response speeds. Putative signs of motor inhibition in the electroencephalogram may as well reflect activation of the opposite response. Consequently, rather than profiting from inhibition of primed responses, the alternative response is directly primed by perceptual interactions of primes and masks. Thus there is no need to assume separate pathways for nonconscious and conscious processing. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

D-S证据理论在数据融合中失效问题的研究

D S方法作为一种重要的处理不确定性问题的数据融合方法,已经广泛应用于各种数据融合系统中。解决D S融合公式在处理冲突证据时的失效问题一直是研究的热点。国内外的各种改进方法主要分为对融合公式的改进和对融合模型的改进2个方向。对各种方法进行理论上和数据上的比较分析表明:修改模型的方式效果明显优于修改融合公式。     

基于K均值的迭代局部搜索聚类算法

K均值聚类算法(KM)是解决聚类问题的一个常用的方法,该方法的主要缺点是其找到的局部极小值与全局最优值的偏差往往较大。论文构造一种基于KM算法的迭代局部搜索算法(称之为IKM)。该算法以KM算法所得到的解作为初始解,从该初始解开始作局部搜索,在搜索过程中接受部分劣解。当解无法改进时,算法对所得到的局部极小解做适当强度的扰动后进行下一次的迭代,以跳出局部极小,从而拓展了搜索的范围。试验结果表明IKM算法得到的聚类结果比KM算法得到的聚类结果有明显的改进,平均改进达100%以上。当数据集越大,簇的个数越多时,改进的效果越是显著,可以达到300%以上。因而,IKM算法是一个确实可行的有效的方法。     

Overlay网络上的服务部署问题的研究(一)

论文形式化描述了Overlay网络上的服务部署问题,给出了一对一单因子服务部署问题的数学模型和求解该问题的启发式算法,并通过数值模拟表明了算法的有效性。     

冷卷热处理生产调度模型的启发式算法

主要讨论某钢铁公司冷轧厂热处理车间冷卷热处理生产调度问题,将其归结为一类不允许等待的混合流水车间排序问题进行研究,建立相应的数学模型,设计求解其模型的启发式算法。     

Utilization Bounds for EDF Scheduling on Real-Time Multiprocessor Systems

The utilization bound for earliest deadline first (EDF) scheduling is extended from uniprocessors to homogeneous multiprocessor systems with partitioning strategies. First results are provided for a basic task model, which includes periodic and independent tasks with deadlines equal to periods. Since the multiprocessor utilization bounds depend on the allocation algorithm, different allocation algorithms have been considered, ranging from simple heuristics to optimal allocation algorithms. As multiprocessor utilization bounds for EDF scheduling depend strongly on task sizes, all these bounds have been obtained as a function of a parameter which takes task sizes into account. Theoretically, the utilization bounds for multiprocessor EDF scheduling can be considered a partial solution to the bin-packing problem, which is known to be NP-complete. The basic task model is extended to include resource sharing, release jitter, deadlines less than periods, aperiodic tasks, non-preemptive sections, context switches, and mode changes.     

Numerical computation of cross‐coupled algebraic Riccati equations related to H2/H∞ control problem for singularly perturbed systems

In this paper, we present a numerical algorithm to the cross‐coupled algebraic Riccati equations(CARE) related to H₂/H_∞ control problems for singularly perturbed systems (SPS) by means of Newton's method. The resulting algorithm can be widely used to solve Nash game problems and robust control problems because the CARE is solvable even if the quadratic term has an indefinite sign. We prove that the resulting iterative algorithm has the property of the quadratic convergence. Using the solution of the CARE, we construct the high‐order approximate H₂/H_∞ controller. Copyright © 2004 John Wiley & Sons, Ltd.     

A nonlinear minimization approach to multiobjective and structured controls for discrete‐time systems

In this paper, a nonlinear minimization approach is proposed for multiobjective and structured controls for discrete‐time systems. The problem of finding multiobjective and structured controls for discrete‐time systems is represented as a quadratic matrix inequality problem. It is shown that the problem is reduced to a nonlinear minimization problem that has a concave objective function and linear matrix inequality constraints. An algorithm for the nonlinear minimization problem is proposed, which is easily implemented with existing semidefinite programming algorithms. The validity of the proposed algorithm is illustrated by comparisons with existing methods. In addition, applications of this work are demonstrated via numerical examples. Copyright © 2004 John Wiley & Sons, Ltd.     

A practical implementation of stochastic programming: an application to the evaluation of option contracts in supply chains

Stochastic programming is a powerful analytical method in order to solve sequential decision-making problems under uncertainty. We describe an approach to build such stochastic linear programming models. We show that algebraic modeling languages make it possible for non-specialist users to formulate complex problems and have solved them by powerful commercial solvers. We illustrate our point in the case of option contracts in supply chain management and propose a numerical analysis of performance. We propose easy-to-implement discretization procedures of the stochastic process in order to limit the size of the event tree in a multi-period environment.     

CP methods of higher order for Sturm-Liouville and Schrödinger equations

The algorithm upon which the code SLCPM12, described in Computer Physics Communications 118 (1999) 259-277, is based, is extended to higher order. The implementation of the original algorithm, which was of order {12,10} (meaning order 12 at low energies and order 10 at high energies), was more efficient than the well-established codes SL02F, SLEDGE and SLEIGN. In the new algorithm the orders {14,12}, {16,14} and {18,16} are introduced. Besides regular Sturm-Liouville and one-dimensional Schrödinger problems also radial Schrödinger equations are considered with potentials of the form V(r)=S(r)/r+R(r), where S(r) and R(r) are well behaved functions which tend to some (not necessarily equal) constants when r→0 and r→∞. Numerical illustrations are given showing the accuracy, the robustness and the CPU-time gain of the proposed algorithms.