Optimization by random search with jumps

We give a random optimization (RO) algorithm to optimize a real‐valued function of n real variables. During the optimization process, interpolation points are examined to follow valleys, and jumps to new starting points are executed to avoid numerous iterations in local minima. Convergence with probability one to the global minimum of a function is proved. The proposed RO method is a simple, derivative‐free and computationally moderate algorithm, with excellent performance compared to other RO methods. Seven functions, which are commonly used to test the performance of optimization methods, are used to evaluate the performance of the RO algorithm given here. Copyright © 2004 John Wiley & Sons, Ltd.     

Sphere packing with a geometric based compression algorithm

An efficient algorithm for the random packing of spheres can significantly save the cost of the preparation of an initial configuration often required in discrete element simulations. It is not trivial to generate such random packing at a large scale, particularly when spheres of various sizes and geometric domains of different shapes are present. Motivated by the idea of compression complemented by an efficient physical process to increase packing density, shaking, a new approach, termed compression algorithm, is proposed in this work to randomly fill any arbitrary polyhedral or cylindrical domains with spheres of various sizes. The algorithm features both simplicity and high efficiency. Tests show that it takes 181 s on a 1.4-GHz PC to complete the filling of a cylindrical domain with a total number of 26,787 spheres, achieving a packing density of 52.89%.     

When danger lurks in the background: Attentional capture by animal fear-relevant distractors is specific and selectively enhanced by animal fear.

Across 2 experiments, a new experimental procedure was used to investigate attentional capture by animal fear-relevant stimuli. In Experiment 1 (N = 34), unselected participants were slower to detect a neutral target animal in the presence of a spider than a cockroach distractor and in the presence of a snake than a large lizard distractor. This result confirms that phylogenetically fear-relevant animals capture attention specifically and to a larger extent than do non-fear-relevant animals. In Experiment 2 (N = 86), detection of a neutral target animal was slowed more in the presence of a feared fear-relevant distractor (e.g., a snake for snake-fearful participants) than in presence of a not-feared fear-relevant distractor (e.g., a spider for snake-fearful participants). These results indicate preferential attentional capture that is specific to phylogenetically fear-relevant stimuli and is selectively enhanced in individuals who fear these animals. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Mesh-Tree两级层次结构P/G网布线优化方法

本文采用Mesh-Tree两级层次结构作为P／G网布线拓扑结构，并提出了一个对于该结构的线宽优化方法，使超大型P／G网的布线优化速度大大提高。     

A p‐version,first order shear deformation,finite element for geometrically non‐linear vibration of curved beams

A p‐version, hierarchical finite element for curved, moderately thick, elastic and isotropic beams is introduced. The convergence properties of the element are analysed and some results are compared with results published elsewhere or calculated using a commercial finite element package. It is verified that, with the proposed element, shear locking does not affect the computation of the natural frequencies and that low dimensional, accurate models are obtainable. Geometrically non‐linear vibrations due to finite deformations, which occur for harmonic excitations with frequencies close to the first three natural frequencies of vibration, are investigated using Newmark's method. The influence of the thickness, longitudinal inertia and curvature radius on the dynamic behaviour of curved beams are studied. Copyright © 2004 John Wiley & Sons, Ltd.     

Serial deployment of attention during visual search.

This study examined whether objects are attended in serial or in parallel during a demanding visual search task. A component of the event-related potential waveform, the N2pc wave, was used as a continuous measure of the allocation of attention to possible targets in the search arrays. Experiment 1 demonstrated that the relative allocation of attention shifts rapidly, favoring one item and then another. In Experiment 2, a paradigm was used that made it possible to track the absolute allocation of attention to individual items. This experiment showed that attention was allocated to one object for 100-150 ms before attention began to be allocated to the next object. These findings support models of attention that posit serial processing in demanding visual search tasks. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

有环境约束时完成一族跟踪任务的力控制

本文为工业机器人提出了一种极点配置控制法，这种控制方法的优点有：一是它的积分作用消除了机器人的微小扰动和稳态误差；二是能任意设置系统的极点，因此能保证闭环系统的稳定性和规定状态变量的暂态响应；三是加入了加速度反馈，抑制了由电枢电感所引起的机械手的振动，最后，给出了ＰＵＭＡ５６２机器人的计算机仿真和实验结果验证了此控制法的有效性。     

Infinite-horizon Scheduling Algorithms for Optimal Search for Hidden Objects

This paper considers discrete search problems in which a decision-maker has to find objects lost or hidden in a given set of locations so as to minimize the expected losses incurred. Given a chance to look for a hidden object in the same location infinitely many times, this type of problem, in contrast to standard scheduling problems, has an infinite sequence as its solution. Thus we are concerned to find an algorithm that yields an optimal solution, rather than the optimal sequence itself. Using combinatorial techniques, fast optimal algorithms for solving the problems are obtained, and optimality conditions are presented for search criteria, under which the local-search algorithms yield the global optimum.     

Distributed memory systems for simulating artificial neural networks

In executing tasks involving intelligent information processing, the human brain performs better than the digital computer. The human brain derives its power from a large number [O(10¹¹)] of neurons which are interconnected by a dense interconnection network [O(10⁵) connections per neuron]. Artificial neural network (ANN) paradigms adopt the structure of the brain to try to emulate the intelligent information processing methods of the brain. ANN techniques are being employed to solve problems in areas such as pattern recognition, and robotic processing. Simulation of ANNs involves implementation of large number of neurons and a massive interconnection network. In this paper, we discuss various simulation models of ANNs and their implementation on distributed memory systems. Our investigations reveal that communication-efficient networks of distributed memory systems perform better than other topologies in implementing ANNs.     

Rule-based supervisory control of a two-link flexible manipulator

In this paper, we propose a two level hierarchical control strategy to achieve accurate end-point position of a planar two-link flexible manipulator. The upper level consists of a feedforward rule-based supervisory controller that incorporates fuzzy logic, whereas the lower level consists of conventional controllers that combine shaft position-endpoint acceleration feedback for disturbance rejection properties and shaping of the (joint) actuator inputs to minimize the energy transferred to the flexible modes during commanded movements. The effectiveness of this hierarchical control strategy is verified by experimental results for various movements of the links, in various configurations. In particular, we illustrate how the hierarchical intelligent control strategy performs better than conventional control techniques for endpoint position control in the presence of flexure effects.