When is search for a static target among dynamic distractors efficient?

Intuitively, dynamic visual stimuli, such as moving objects or flashing lights, attract attention. Visual search tasks have revealed that dynamic targets among static distractors can indeed efficiently guide attention. The present study shows that the reverse case, a static target among dynamic distractors, allows for relatively efficient selection in certain but not all cases. A static target was relatively efficiently found among distractors that featured apparent motion, corroborating earlier findings. The important new finding was that static targets were equally easily found among distractors that blinked on and off continuously, even when each individual item blinked at a random rate. However, search for a static target was less efficient when distractors abruptly varied in luminance but did not completely disappear. The authors suggest that the division into the parvocellular pathway dealing with static visual information, on the one hand, and the magnocellular pathway common to motion and new object onset detection, on the other hand, allows for efficient filtering of dynamic and static information. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Scapholunate dissociation: a practical approach for the emergency physician

The development of new techniques in sequencing nuclei acids has produced a great amount of sequence data and has led to the discovery of new relationships. In this paper, we study a method for parallelizing the algorithm WORDUP, which detects the presence of statistically significant patterns in DNA sequences. WORDUP implements an efficient method to identify the presence of statistically significant oligomers in a non-homologous group of sequences. It is based on a modified version of the Boyer-Moore algorithm, which is one of the fastest algorithms for string matching available in the literature. The aim of the parallel version of WORDUP presented here is to speed up the computational time and allow the analysis of a greater set of longer nucleotide sequences, which is usually impractical with sequential algorithms.     

Contact interactions method: a new algorithm for protein folding simulations

Computer simulations of simple exact lattice models are an aid in the study of protein folding process; they have sometimes resulted in predictions experimentally proved. The contact interactions (CI) method is here proposed as a new algorithm for the conformational search in the low-energy regions of protein chains modeled as copolymers of hydrophobic and polar monomers configured as self-avoiding walks on square or cubic lattices. It may be regarded as an extension of the standard Monte Carlo method improved by the concept of cooperativity deriving from nonlocal contact interactions. A major difference with respect to other algorithms is that criteria for the acceptance of new conformations generated during the simulations are not based on the energy of the entire molecule, but cooling factors associated with each residue define regions of the model protein with higher or lower mobility. Nine sequences of length ranging from 20 to 64 residues were used on the square lattice and 15 sequences of length ranging from 46 to 136 residues were used on the cubic lattice. The CI algorithm proved very efficient both in two and three dimensions, and allowed us to localize energy minima not localized by other searching algorithms described in the literature. Use of this algorithm is not limited to the conformational search, because it allows the exploration of thermodynamic and kinetic behavior of model protein chains.     

基于万有引力优化的支持向量机模型在板形识别中的应用

 针对目前板形模式识别模型泛化能力不高、训练速度慢等缺陷,以1次、2次、3次、4次勒让德正交多项式为板形缺陷基本模式,提出了由支持向量回归机（SVR）构建的模式识别模型;为了提高该模型的精确度,引入万有引力算法（GSA）优化SVR的参数,由此构成GSA-SVR预测模型。仿真试验结果表明:GSA-SVR模型不仅识别结果精度高,而且与PSO-BP神经网络模型相比泛化能力更强,训练速度更快,其识别结果可以为板形控制提供有效的依据。     

Multiple domain protein diagnostic patterns

We have implemented an iterative algorithm for the identification of diagnostic patterns from sets of multiple-domain proteins, where domains need not be common to all the proteins in the defining set. Our algorithm was applied to sequences gathered using a variety of methods, including BLAST, common keywords, and common E.C. numbers. In all cases, useful diagnostic patterns were obtained, possessing both high sensitivity and specificity. The patterns were found to correlate in several cases with both functional and structural domains. Patterns generated from a large number of sequence families were analyzed for probable multiple-domain structure.     

Linear contact algorithm for rigid-plastic finite element simulation

The rigid-plastic finite element analysis of metal forming processes is known to be much more efficient and stable than the elastic-plastic one. This efficiency results from the absence of kinematical nonlinearities in the formulation. Contact algorithms used in rigid-plastic models must agree with this fact, otherwise the efficiency can be damaged seriously. The aim of this paper is to present a linear contact algorithm designed specially for rigid-plastic analysis of metal forming problems. The linearization is achieved by dictating constancy of boundary conditions during one increment according to the requirement of the variational principle by Markov. The algorithm consists of two parts: the contact search and the contact control. The procedure has been implemented for two-dimensional cases. However, the generalization to three dimensions is straightforward. The efficiency and the stability of the proposed procedure has been validated by means of examples of application such as extrusion and forging. Furthermore, parametric studies of the contact variables have been performed.     

Liquid metal cooling: A new solidification technique

This paper describes a new and highly efficient directional solidification process using liquid metal as a coolant. A laboratory version of this process is reviewed in detail. The selection of a coolant is also discussed. Process thermal characteristics such as thermal gradient, growth rate and cooling rate are measured and compared with established directional solidification processing. Microstructural refinement of primary dendrites, secondary dendrite arms and MC carbides is demonstrated in the case of Ni-base super-alloys. Special advantages of the process, such as a lack of interdependence of growth rate and thermal gradient are discussed. Liquid Metal Cooling (LMC) offers a wide range of rate-gradient combinations and i therefore the most flexible directional solidification process discovered to date. The high levels of thermal gradient which are available make LMC a natural choice for the growth of eutectics. Alternatively, growth rates of dendritic materials can be substantially increased leading to significantly finer microstructures. Thus, LMC promises to be a highly useful process. Formerly with Pratt & Whitney Aircraft.     

FASTPAT: a fast and efficient algorithm for string searching in DNA sequences

A new string searching algorithm is presented aimed at searching for the occurrence of character patterns in longer character texts. The algorithm, specifically designed for nucleic acid sequence data, is essentially derived from the Boyer-Moore method (Comm. ACM, 20, 762-772, 1977). Both pattern and text data are compressed so that the natural 4-letter alphabet of nucleic acid sequences is considerably enlarged. The string search starts from the last character of the pattern and proceeds in large jumps through the text to be searched. The data compression and searching algorithm allows one to avoid searching for patterns not present in the text as well as to inspect, for each pattern, all text characters until the exact match with the text is found. These considerations are supported by empirical evidence and comparisons with other methods.     

对提高有向图全路径穷举算法效率的研究

文章对复杂有向图全路径穷举问题的算法与算法效率作了较为详尽的研究和分析,提出了提高效率的办法,并提出了一种新的簇集搜索算法,同时对新算法的时间复杂度进行了分析计算,为更高效的算法研究提供了理论依据。     

Efficient Spreadsheet Algorithm for First-Order Reliability Method

A new spreadsheet-cell-object-oriented algorithm for the first-order reliability method is proposed and illustrated for cases with correlated nonnormals and explicit and implicit performance functions. The new approach differs from the writers earlier algorithm by obviating the need for computations of equivalent normal means and equivalent normal standard deviations. It obtains the solution faster and is more efficient, robust, and succinct. Other advantages include ease of initialization prior to constrained optimization, ease of randomization of initial values for checking robustness, and fewer required optimization constraints during spreadsheet-automated search for the design point. Two cases with implicit performance functions, namely an asymmetrically loaded beam on Winkler medium and a strut with complex supports are analyzed using the new approach and discussed. Comparisons are also made between the proposed approach and that based on Rosenblatt transformation.     

A novel immune genetic algorithm based on quasi secondary response

Combining the advantages of a genetic algorithm and an artificial immune system,a novel genetic algorithm named immune genetic algorithm based on quasi secondary response(IGA-QSR) is proposed. IGA-QSR employs a database to simulate the standard secondary response and the quasi secondary response. Elitist strategy,automatic extinction,clonal propagation,diversity guarantee,and selection based on comprehensive fitness are also used in the process of IGA-QSR.Theoretical analysis,numerical examples of three benchmark mathematical optimization problems and a traveling salesman problem all demonstrate that IGA-QSR is more effective not only on convergence speed but also on convergence probability than a simple genetic algorithm with the elitist strategy (SGA-ES). Besides,IGA-QSR allows the designers to stop and restart the optimization process freely without losing the best results that have already been obtained.These properties make IGA-QSR be a feasible,effective and robust search algorithm for complex engineering problems.     

The temporal dynamics of strategy execution in cognitive skill learning.

The transition from algorithmic to memory-based performance is a core component of cognitive skill learning. There has been debate about the temporal dynamics of strategy execution, with some models assuming a race (i.e., independent, capacity unconstrained parallel processing) between algorithm and retrieval, and others assuming a choice mechanism. The authors investigated this issue using a new approach that allows the latency of each algorithm step to be measured, in turn providing new insight into (a) whether there is slowing of 1 or more algorithm steps on trials immediately preceding the 1st retrieval trial for an item, as might be expected if there is a competitive strategy execution process of some type other than a race, and (b) whether there is partial algorithm completion on retrieval trials, as would be expected if the 2 strategies are executed in parallel. Results are uniquely consistent with a strategy choice mechanism involving a competition between the retrieval strategy and the 1st step of the algorithm. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Domain-by-Domain Algorithm for Nonlinear Finite-Element Analysis of Structures

Parallel and distributed computers have been shown to provide the necessary computational power to solve large-scale engineering problems. However, in order for this computation style to be effectively used, efficient computational algorithms must be devised. In this work, a domain-by-domain algorithm is developed for the parallel solution of nonlinear structural dynamics problems. In the proposed algorithm, the original structure is partitioned into a number of subdomains. Each subdomain is solved independently and, therefore, concurrently using a traditional direct-solution method. Finally, the solution for the interface degrees of freedom between neighboring subdomains is obtained by enforcing compatibility and equilibrium using an iterative procedure. The nonlinear version of the algorithm involves two iterations: The nonlinear dynamic equilibrium iteration and the interface equilibrium and compatibility iteration. The integration of these two iterations is investigated and two strategies are developed. It is found that the strategy in which the two iterations are isolated is the most efficient. As a demonstration, the fully nonlinear transient analysis of a 20-story model building is carried out. Excellent accuracy in the solution and significant speed up values are obtained.     

Superior Exploration–Exploitation Balance in Shuffled Complex Evolution

Numerous applications within water resources require a robust and efficient optimization algorithm. Given that these applications involve multimodal nonconvex and discontinuous search spaces, evolutionary algorithms (EAs)—which are known to possess global optimization properties—have been widely used for this purpose. For an evolutionary algorithm to be successful, two important facets of the search—exploration and exploitation of the search space—need to be addressed. In this study, we address the issue of achieving a superior exploration–exploitation tradeoff in an extensively used EA, the shuffled complex evolution (SCE-UA). A scheme to improve the exploration capability of the SCE-UA in finding the global optimum is suggested. The scheme proposed a systematically located initial population instead of a randomly generated one used in SCE-UA. On a suite of commonly used test functions, the robustness and efficiency of the modified SCE-UA algorithm was compared with the original SCE-UA. It is observed that when the points in the initial population are strategically placed, it leads to better exploration of the search space, and hence, yields a superior balance between exploration and exploitation. This in turn results in a significant improvement in the robustness of the SCE-UA algorithm.     

Layout Design of Irrigation Networks in Highly Parcelled Territories Using Geographical Information System

Traditional irrigation zones in the east of Spain have been denoted by the high level of parcellation. The layout of the irrigation network design in highly parcelled territories presents an important degree of difficulty, the previous experience of the designer in this task being crucial in the final result. In this work, a new heuristic algorithm for layout of the irrigation network design is presented. We start from a classical graph theory algorithm (Dijkstra’s algorithm) used for solving the shortest path spanning tree problem. This algorithm is modified to assign weights to the arcs and plot limits are used as if they were the arcs of a graph. The algorithm is implemented on a geographical information system, thus creating an application that automatically generates the layout of the irrigation network design. The only necessary initial data are the origin of the network (supply point) and the hydrants (delivery points). The advantage of this heuristic is that the subjectivity introduced for the designer is removed. Moreover, it allows for solving complex problems, and therefore it is applicable to highly parcelled zones, where the number of vertices and edges is so high that it would inhibit calculating capacity of any optimization process. A practical example is presented, in which the layout design obtained by applying the heuristic is compared with the original existing layout.     

Using Elitist Particle Swarm Optimization to Facilitate Bicriterion Time-Cost Trade-Off Analysis

The present study develops a new optimization algorithm to find the complete time-cost profile (Pareto front) over a set of feasible project durations, i.e., it solves the time-cost trade-off problem. To improve existing methods, the proposed algorithm aims to achieve three goals: (1) to obtain the entire Pareto front in a single run; (2) to be insensitive to the scales of time and cost; and (3) to treat all existing types of activity time-cost functions, such as linear, nonlinear, discrete, discontinuous, and a hybrid of the above. The proposed algorithm modifies a population-based search procedure, particle swarm optimization, by adopting an elite archiving scheme to store nondominated solutions and by aptly using members of the archive to direct further search. Through a fast food outlet example, the proposed algorithm is shown effective and efficient in conducting advanced bicriterion time-cost analysis. Future applications of the proposed algorithm are suggested in the conclusion.     

Subsurface Biological Activity Zone Detection Using Genetic Search Algorithms

Use of generic search algorithms for detection of subsurface biological activity zones (BAZ) is investigated through a series of hypothetical numerical biostimulation experiments. Continuous injection of dissolved oxygen and methane with periodically varying concentration stimulates the cometabolism of indigenous methanotropic bacteria. The observed breakthroughs of methane are used to deduce possible BAZ in the subsurface. The numerical experiments are implemented in a parallel computing environment to make possible the large number of simultaneous transport simulations required by the algorithm. Our results show that genetic algorithms are very efficient in locating multiple activity zones, provided the observed signals adequately sample the BAZ.     

基于自适应搜索的免疫粒子群算法

经典粒子群算法由于多样性差而陷入局部最优,从而造成早熟停滞现象.为克服上述缺点,本文结合人工免疫算法,提出一种基于自适应搜索的免疫粒子群算法.首先,该算法改善了浓度机制;然后由粒子最大浓度值来控制子种群数目以充分利用粒子种群资源;最后对劣质子种群进行疫苗接种,利用粒子最大浓度值调节接种疫苗的搜索范围,不仅避免了种群退化现象,而且提高了算法的收敛精度和全局搜索能力.仿真结果表明该算法求解复杂函数优化问题的有效性和优越性.      

Gradually Varied Flow Computation in Cyclic Looped Channel Networks

A novel and computationally efficient algorithm is presented to compute the water surface profiles in steady, gradually varied flows of open channel networks. This algorithm allows calculation of flow depths and discharges at all sections of a cyclic looped open channel network. The algorithm is based on the principles of (1) classifying the computations in an individual channel as an initial value problem or a boundary value problem; (2) determining the path for linking the solutions from individual channels; and (3) an iterative Newton–Raphson technique for obtaining the network solution, starting from initial assumptions for discharges in as few channels as possible. The proposed algorithm is computationally more efficient than the presently available direct method by orders of magnitude because it does not involve costly inversions of large matrices in its formulation. The application of this algorithm is illustrated through an example network.