A Guiding Evolutionary Algorithm with Greedy Strategy for Global Optimization Problems.

PubMed

Cao, Leilei; Xu, Lihong; Goodman, Erik D

2016-01-01

A Guiding Evolutionary Algorithm (GEA) with greedy strategy for global optimization problems is proposed. Inspired by Particle Swarm Optimization, the Genetic Algorithm, and the Bat Algorithm, the GEA was designed to retain some advantages of each method while avoiding some disadvantages. In contrast to the usual Genetic Algorithm, each individual in GEA is crossed with the current global best one instead of a randomly selected individual. The current best individual served as a guide to attract offspring to its region of genotype space. Mutation was added to offspring according to a dynamic mutation probability. To increase the capability of exploitation, a local search mechanism was applied to new individuals according to a dynamic probability of local search. Experimental results show that GEA outperformed the other three typical global optimization algorithms with which it was compared.

Global Optimality of the Successive Maxbet Algorithm.

ERIC Educational Resources Information Center

Hanafi, Mohamed; ten Berge, Jos M. F.

2003-01-01

It is known that the Maxbet algorithm, which is an alternative to the method of generalized canonical correlation analysis and Procrustes analysis, may converge to local maxima. Discusses an eigenvalue criterion that is sufficient, but not necessary, for global optimality of the successive Maxbet algorithm. (SLD)

A Guiding Evolutionary Algorithm with Greedy Strategy for Global Optimization Problems

PubMed Central

Cao, Leilei; Xu, Lihong; Goodman, Erik D.

2016-01-01

A Guiding Evolutionary Algorithm (GEA) with greedy strategy for global optimization problems is proposed. Inspired by Particle Swarm Optimization, the Genetic Algorithm, and the Bat Algorithm, the GEA was designed to retain some advantages of each method while avoiding some disadvantages. In contrast to the usual Genetic Algorithm, each individual in GEA is crossed with the current global best one instead of a randomly selected individual. The current best individual served as a guide to attract offspring to its region of genotype space. Mutation was added to offspring according to a dynamic mutation probability. To increase the capability of exploitation, a local search mechanism was applied to new individuals according to a dynamic probability of local search. Experimental results show that GEA outperformed the other three typical global optimization algorithms with which it was compared. PMID:27293421

Autonomous Modelling of X-ray Spectra Using Robust Global Optimization Methods

NASA Astrophysics Data System (ADS)

Rogers, Adam; Safi-Harb, Samar; Fiege, Jason

2015-08-01

The standard approach to model fitting in X-ray astronomy is by means of local optimization methods. However, these local optimizers suffer from a number of problems, such as a tendency for the fit parameters to become trapped in local minima, and can require an involved process of detailed user intervention to guide them through the optimization process. In this work we introduce a general GUI-driven global optimization method for fitting models to X-ray data, written in MATLAB, which searches for optimal models with minimal user interaction. We directly interface with the commonly used XSPEC libraries to access the full complement of pre-existing spectral models that describe a wide range of physics appropriate for modelling astrophysical sources, including supernova remnants and compact objects. Our algorithm is powered by the Ferret genetic algorithm and Locust particle swarm optimizer from the Qubist Global Optimization Toolbox, which are robust at finding families of solutions and identifying degeneracies. This technique will be particularly instrumental for multi-parameter models and high-fidelity data. In this presentation, we provide details of the code and use our techniques to analyze X-ray data obtained from a variety of astrophysical sources.

A local segmentation parameter optimization approach for mapping heterogeneous urban environments using VHR imagery

NASA Astrophysics Data System (ADS)

Grippa, Tais; Georganos, Stefanos; Lennert, Moritz; Vanhuysse, Sabine; Wolff, Eléonore

2017-10-01

Mapping large heterogeneous urban areas using object-based image analysis (OBIA) remains challenging, especially with respect to the segmentation process. This could be explained both by the complex arrangement of heterogeneous land-cover classes and by the high diversity of urban patterns which can be encountered throughout the scene. In this context, using a single segmentation parameter to obtain satisfying segmentation results for the whole scene can be impossible. Nonetheless, it is possible to subdivide the whole city into smaller local zones, rather homogeneous according to their urban pattern. These zones can then be used to optimize the segmentation parameter locally, instead of using the whole image or a single representative spatial subset. This paper assesses the contribution of a local approach for the optimization of segmentation parameter compared to a global approach. Ouagadougou, located in sub-Saharan Africa, is used as case studies. First, the whole scene is segmented using a single globally optimized segmentation parameter. Second, the city is subdivided into 283 local zones, homogeneous in terms of building size and building density. Each local zone is then segmented using a locally optimized segmentation parameter. Unsupervised segmentation parameter optimization (USPO), relying on an optimization function which tends to maximize both intra-object homogeneity and inter-object heterogeneity, is used to select the segmentation parameter automatically for both approaches. Finally, a land-use/land-cover classification is performed using the Random Forest (RF) classifier. The results reveal that the local approach outperforms the global one, especially by limiting confusions between buildings and their bare-soil neighbors.

Enhancing Polyhedral Relaxations for Global Optimization

ERIC Educational Resources Information Center

Bao, Xiaowei

2009-01-01

During the last decade, global optimization has attracted a lot of attention due to the increased practical need for obtaining global solutions and the success in solving many global optimization problems that were previously considered intractable. In general, the central question of global optimization is to find an optimal solution to a given…

Automated parameterization of intermolecular pair potentials using global optimization techniques

NASA Astrophysics Data System (ADS)

Krämer, Andreas; Hülsmann, Marco; Köddermann, Thorsten; Reith, Dirk

2014-12-01

In this work, different global optimization techniques are assessed for the automated development of molecular force fields, as used in molecular dynamics and Monte Carlo simulations. The quest of finding suitable force field parameters is treated as a mathematical minimization problem. Intricate problem characteristics such as extremely costly and even abortive simulations, noisy simulation results, and especially multiple local minima naturally lead to the use of sophisticated global optimization algorithms. Five diverse algorithms (pure random search, recursive random search, CMA-ES, differential evolution, and taboo search) are compared to our own tailor-made solution named CoSMoS. CoSMoS is an automated workflow. It models the parameters' influence on the simulation observables to detect a globally optimal set of parameters. It is shown how and why this approach is superior to other algorithms. Applied to suitable test functions and simulations for phosgene, CoSMoS effectively reduces the number of required simulations and real time for the optimization task.

Parasail: SIMD C library for global, semi-global, and local pairwise sequence alignments

DOE PAGES

Daily, Jeffrey A.

2016-02-10

Sequence alignment algorithms are a key component of many bioinformatics applications. Though various fast Smith-Waterman local sequence alignment implementations have been developed for x86 CPUs, most are embedded into larger database search tools. In addition, fast implementations of Needleman-Wunsch global sequence alignment and its semi-global variants are not as widespread. This article presents the first software library for local, global, and semi-global pairwise intra-sequence alignments and improves the performance of previous intra-sequence implementations. As a result, a faster intra-sequence pairwise alignment implementation is described and benchmarked. Using a 375 residue query sequence a speed of 136 billion cell updates permore » second (GCUPS) was achieved on a dual Intel Xeon E5-2670 12-core processor system, the highest reported for an implementation based on Farrar’s ’striped’ approach. When using only a single thread, parasail was 1.7 times faster than Rognes’s SWIPE. For many score matrices, parasail is faster than BLAST. The software library is designed for 64 bit Linux, OS X, or Windows on processors with SSE2, SSE41, or AVX2. Source code is available from https://github.com/jeffdaily/parasail under the Battelle BSD-style license. In conclusion, applications that require optimal alignment scores could benefit from the improved performance. For the first time, SIMD global, semi-global, and local alignments are available in a stand-alone C library.« less

Parasail: SIMD C library for global, semi-global, and local pairwise sequence alignments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daily, Jeffrey A.

Sequence alignment algorithms are a key component of many bioinformatics applications. Though various fast Smith-Waterman local sequence alignment implementations have been developed for x86 CPUs, most are embedded into larger database search tools. In addition, fast implementations of Needleman-Wunsch global sequence alignment and its semi-global variants are not as widespread. This article presents the first software library for local, global, and semi-global pairwise intra-sequence alignments and improves the performance of previous intra-sequence implementations. As a result, a faster intra-sequence pairwise alignment implementation is described and benchmarked. Using a 375 residue query sequence a speed of 136 billion cell updates permore » second (GCUPS) was achieved on a dual Intel Xeon E5-2670 12-core processor system, the highest reported for an implementation based on Farrar’s ’striped’ approach. When using only a single thread, parasail was 1.7 times faster than Rognes’s SWIPE. For many score matrices, parasail is faster than BLAST. The software library is designed for 64 bit Linux, OS X, or Windows on processors with SSE2, SSE41, or AVX2. Source code is available from https://github.com/jeffdaily/parasail under the Battelle BSD-style license. In conclusion, applications that require optimal alignment scores could benefit from the improved performance. For the first time, SIMD global, semi-global, and local alignments are available in a stand-alone C library.« less

Spanish as a World Language: The Interplay of Globalized Localization and Localized Globalization

ERIC Educational Resources Information Center

Nino-Murcia, Mercedes; Godenzzi, Juan Carlos; Rothman, Jason

2008-01-01

This article argues that two movements in constant interplay operate within the historical trajectory of the Spanish language: the localization that becomes globalized and the globalization that becomes localized. Equally, this article illustrates how, at the same time that Spanish is expanding in the world, new idiosyncratic and localized forms…

A Novel Hybrid Firefly Algorithm for Global Optimization.

PubMed

Zhang, Lina; Liu, Liqiang; Yang, Xin-She; Dai, Yuntao

Global optimization is challenging to solve due to its nonlinearity and multimodality. Traditional algorithms such as the gradient-based methods often struggle to deal with such problems and one of the current trends is to use metaheuristic algorithms. In this paper, a novel hybrid population-based global optimization algorithm, called hybrid firefly algorithm (HFA), is proposed by combining the advantages of both the firefly algorithm (FA) and differential evolution (DE). FA and DE are executed in parallel to promote information sharing among the population and thus enhance searching efficiency. In order to evaluate the performance and efficiency of the proposed algorithm, a diverse set of selected benchmark functions are employed and these functions fall into two groups: unimodal and multimodal. The experimental results show better performance of the proposed algorithm compared to the original version of the firefly algorithm (FA), differential evolution (DE) and particle swarm optimization (PSO) in the sense of avoiding local minima and increasing the convergence rate.

A Novel Hybrid Firefly Algorithm for Global Optimization

PubMed Central

Zhang, Lina; Liu, Liqiang; Yang, Xin-She; Dai, Yuntao

2016-01-01

Global optimization is challenging to solve due to its nonlinearity and multimodality. Traditional algorithms such as the gradient-based methods often struggle to deal with such problems and one of the current trends is to use metaheuristic algorithms. In this paper, a novel hybrid population-based global optimization algorithm, called hybrid firefly algorithm (HFA), is proposed by combining the advantages of both the firefly algorithm (FA) and differential evolution (DE). FA and DE are executed in parallel to promote information sharing among the population and thus enhance searching efficiency. In order to evaluate the performance and efficiency of the proposed algorithm, a diverse set of selected benchmark functions are employed and these functions fall into two groups: unimodal and multimodal. The experimental results show better performance of the proposed algorithm compared to the original version of the firefly algorithm (FA), differential evolution (DE) and particle swarm optimization (PSO) in the sense of avoiding local minima and increasing the convergence rate. PMID:27685869

Computational methods for global/local analysis

NASA Technical Reports Server (NTRS)

Ransom, Jonathan B.; Mccleary, Susan L.; Aminpour, Mohammad A.; Knight, Norman F., Jr.

1992-01-01

Computational methods for global/local analysis of structures which include both uncoupled and coupled methods are described. In addition, global/local analysis methodology for automatic refinement of incompatible global and local finite element models is developed. Representative structural analysis problems are presented to demonstrate the global/local analysis methods.

Parameterizing sorption isotherms using a hybrid global-local fitting procedure.

PubMed

Matott, L Shawn; Singh, Anshuman; Rabideau, Alan J

2017-05-01

Predictive modeling of the transport and remediation of groundwater contaminants requires an accurate description of the sorption process, which is usually provided by fitting an isotherm model to site-specific laboratory data. Commonly used calibration procedures, listed in order of increasing sophistication, include: trial-and-error, linearization, non-linear regression, global search, and hybrid global-local search. Given the considerable variability in fitting procedures applied in published isotherm studies, we investigated the importance of algorithm selection through a series of numerical experiments involving 13 previously published sorption datasets. These datasets, considered representative of state-of-the-art for isotherm experiments, had been previously analyzed using trial-and-error, linearization, or non-linear regression methods. The isotherm expressions were re-fit using a 3-stage hybrid global-local search procedure (i.e. global search using particle swarm optimization followed by Powell's derivative free local search method and Gauss-Marquardt-Levenberg non-linear regression). The re-fitted expressions were then compared to previously published fits in terms of the optimized weighted sum of squared residuals (WSSR) fitness function, the final estimated parameters, and the influence on contaminant transport predictions - where easily computed concentration-dependent contaminant retardation factors served as a surrogate measure of likely transport behavior. Results suggest that many of the previously published calibrated isotherm parameter sets were local minima. In some cases, the updated hybrid global-local search yielded order-of-magnitude reductions in the fitness function. In particular, of the candidate isotherms, the Polanyi-type models were most likely to benefit from the use of the hybrid fitting procedure. In some cases, improvements in fitness function were associated with slight (<10%) changes in parameter values, but in other cases

QuickVina: accelerating AutoDock Vina using gradient-based heuristics for global optimization.

PubMed

Handoko, Stephanus Daniel; Ouyang, Xuchang; Su, Chinh Tran To; Kwoh, Chee Keong; Ong, Yew Soon

2012-01-01

Predicting binding between macromolecule and small molecule is a crucial phase in the field of rational drug design. AutoDock Vina, one of the most widely used docking software released in 2009, uses an empirical scoring function to evaluate the binding affinity between the molecules and employs the iterated local search global optimizer for global optimization, achieving a significantly improved speed and better accuracy of the binding mode prediction compared its predecessor, AutoDock 4. In this paper, we propose further improvement in the local search algorithm of Vina by heuristically preventing some intermediate points from undergoing local search. Our improved version of Vina-dubbed QVina-achieved a maximum acceleration of about 25 times with the average speed-up of 8.34 times compared to the original Vina when tested on a set of 231 protein-ligand complexes while maintaining the optimal scores mostly identical. Using our heuristics, larger number of different ligands can be quickly screened against a given receptor within the same time frame.

Optimizer convergence and local minima errors and their clinical importance

NASA Astrophysics Data System (ADS)

Jeraj, Robert; Wu, Chuan; Mackie, Thomas R.

2003-09-01

Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization.

Optimizer convergence and local minima errors and their clinical importance.

PubMed

Jeraj, Robert; Wu, Chuan; Mackie, Thomas R

2003-09-07

Two of the errors common in the inverse treatment planning optimization have been investigated. The first error is the optimizer convergence error, which appears because of non-perfect convergence to the global or local solution, usually caused by a non-zero stopping criterion. The second error is the local minima error, which occurs when the objective function is not convex and/or the feasible solution space is not convex. The magnitude of the errors, their relative importance in comparison to other errors as well as their clinical significance in terms of tumour control probability (TCP) and normal tissue complication probability (NTCP) were investigated. Two inherently different optimizers, a stochastic simulated annealing and deterministic gradient method were compared on a clinical example. It was found that for typical optimization the optimizer convergence errors are rather small, especially compared to other convergence errors, e.g., convergence errors due to inaccuracy of the current dose calculation algorithms. This indicates that stopping criteria could often be relaxed leading into optimization speed-ups. The local minima errors were also found to be relatively small and typically in the range of the dose calculation convergence errors. Even for the cases where significantly higher objective function scores were obtained the local minima errors were not significantly higher. Clinical evaluation of the optimizer convergence error showed good correlation between the convergence of the clinical TCP or NTCP measures and convergence of the physical dose distribution. On the other hand, the local minima errors resulted in significantly different TCP or NTCP values (up to a factor of 2) indicating clinical importance of the local minima produced by physical optimization.

Effect of local minima on adiabatic quantum optimization.

PubMed

Amin, M H S

2008-04-04

We present a perturbative method to estimate the spectral gap for adiabatic quantum optimization, based on the structure of the energy levels in the problem Hamiltonian. We show that, for problems that have an exponentially large number of local minima close to the global minimum, the gap becomes exponentially small making the computation time exponentially long. The quantum advantage of adiabatic quantum computation may then be accessed only via the local adiabatic evolution, which requires phase coherence throughout the evolution and knowledge of the spectrum. Such problems, therefore, are not suitable for adiabatic quantum computation.

An Evaluation of the Sniffer Global Optimization Algorithm Using Standard Test Functions

NASA Astrophysics Data System (ADS)

Butler, Roger A. R.; Slaminka, Edward E.

1992-03-01

The performance of Sniffer—a new global optimization algorithm—is compared with that of Simulated Annealing. Using the number of function evaluations as a measure of efficiency, the new algorithm is shown to be significantly better at finding the global minimum of seven standard test functions. Several of the test functions used have many local minima and very steep walls surrounding the global minimum. Such functions are intended to thwart global minimization algorithms.

Pneumothorax detection in chest radiographs using local and global texture signatures

NASA Astrophysics Data System (ADS)

Geva, Ofer; Zimmerman-Moreno, Gali; Lieberman, Sivan; Konen, Eli; Greenspan, Hayit

2015-03-01

A novel framework for automatic detection of pneumothorax abnormality in chest radiographs is presented. The suggested method is based on a texture analysis approach combined with supervised learning techniques. The proposed framework consists of two main steps: at first, a texture analysis process is performed for detection of local abnormalities. Labeled image patches are extracted in the texture analysis procedure following which local analysis values are incorporated into a novel global image representation. The global representation is used for training and detection of the abnormality at the image level. The presented global representation is designed based on the distinctive shape of the lung, taking into account the characteristics of typical pneumothorax abnormalities. A supervised learning process was performed on both the local and global data, leading to trained detection system. The system was tested on a dataset of 108 upright chest radiographs. Several state of the art texture feature sets were experimented with (Local Binary Patterns, Maximum Response filters). The optimal configuration yielded sensitivity of 81% with specificity of 87%. The results of the evaluation are promising, establishing the current framework as a basis for additional improvements and extensions.

On Global Optimal Sailplane Flight Strategy

NASA Technical Reports Server (NTRS)

Sander, G. J.; Litt, F. X.

1979-01-01

The derivation and interpretation of the necessary conditions that a sailplane cross-country flight has to satisfy to achieve the maximum global flight speed is considered. Simple rules are obtained for two specific meteorological models. The first one uses concentrated lifts of various strengths and unequal distance. The second one takes into account finite, nonuniform space amplitudes for the lifts and allows, therefore, for dolphin style flight. In both models, altitude constraints consisting of upper and lower limits are shown to be essential to model realistic problems. Numerical examples illustrate the difference with existing techniques based on local optimality conditions.

Particle swarm optimization and its application in MEG source localization using single time sliced data

NASA Astrophysics Data System (ADS)

Lin, Juan; Liu, Chenglian; Guo, Yongning

2014-10-01

The estimation of neural active sources from the magnetoencephalography (MEG) data is a very critical issue for both clinical neurology and brain functions research. A widely accepted source-modeling technique for MEG involves calculating a set of equivalent current dipoles (ECDs). Depth in the brain is one of difficulties in MEG source localization. Particle swarm optimization(PSO) is widely used to solve various optimization problems. In this paper we discuss its ability and robustness to find the global optimum in different depths of the brain when using single equivalent current dipole (sECD) model and single time sliced data. The results show that PSO is an effective global optimization to MEG source localization when given one dipole in different depths.

PS-FW: A Hybrid Algorithm Based on Particle Swarm and Fireworks for Global Optimization

PubMed Central

Chen, Shuangqing; Wei, Lixin; Guan, Bing

2018-01-01

Particle swarm optimization (PSO) and fireworks algorithm (FWA) are two recently developed optimization methods which have been applied in various areas due to their simplicity and efficiency. However, when being applied to high-dimensional optimization problems, PSO algorithm may be trapped in the local optima owing to the lack of powerful global exploration capability, and fireworks algorithm is difficult to converge in some cases because of its relatively low local exploitation efficiency for noncore fireworks. In this paper, a hybrid algorithm called PS-FW is presented, in which the modified operators of FWA are embedded into the solving process of PSO. In the iteration process, the abandonment and supplement mechanism is adopted to balance the exploration and exploitation ability of PS-FW, and the modified explosion operator and the novel mutation operator are proposed to speed up the global convergence and to avoid prematurity. To verify the performance of the proposed PS-FW algorithm, 22 high-dimensional benchmark functions have been employed, and it is compared with PSO, FWA, stdPSO, CPSO, CLPSO, FIPS, Frankenstein, and ALWPSO algorithms. Results show that the PS-FW algorithm is an efficient, robust, and fast converging optimization method for solving global optimization problems. PMID:29675036

Constructing IGA-suitable planar parameterization from complex CAD boundary by domain partition and global/local optimization

NASA Astrophysics Data System (ADS)

Xu, Gang; Li, Ming; Mourrain, Bernard; Rabczuk, Timon; Xu, Jinlan; Bordas, Stéphane P. A.

2018-01-01

In this paper, we propose a general framework for constructing IGA-suitable planar B-spline parameterizations from given complex CAD boundaries consisting of a set of B-spline curves. Instead of forming the computational domain by a simple boundary, planar domains with high genus and more complex boundary curves are considered. Firstly, some pre-processing operations including B\\'ezier extraction and subdivision are performed on each boundary curve in order to generate a high-quality planar parameterization; then a robust planar domain partition framework is proposed to construct high-quality patch-meshing results with few singularities from the discrete boundary formed by connecting the end points of the resulting boundary segments. After the topology information generation of quadrilateral decomposition, the optimal placement of interior B\\'ezier curves corresponding to the interior edges of the quadrangulation is constructed by a global optimization method to achieve a patch-partition with high quality. Finally, after the imposition of C1=G1-continuity constraints on the interface of neighboring B\\'ezier patches with respect to each quad in the quadrangulation, the high-quality B\\'ezier patch parameterization is obtained by a C1-constrained local optimization method to achieve uniform and orthogonal iso-parametric structures while keeping the continuity conditions between patches. The efficiency and robustness of the proposed method are demonstrated by several examples which are compared to results obtained by the skeleton-based parameterization approach.

Optimal correction and design parameter search by modern methods of rigorous global optimization

NASA Astrophysics Data System (ADS)

Makino, K.; Berz, M.

2011-07-01

Frequently the design of schemes for correction of aberrations or the determination of possible operating ranges for beamlines and cells in synchrotrons exhibit multitudes of possibilities for their correction, usually appearing in disconnected regions of parameter space which cannot be directly qualified by analytical means. In such cases, frequently an abundance of optimization runs are carried out, each of which determines a local minimum depending on the specific chosen initial conditions. Practical solutions are then obtained through an often extended interplay of experienced manual adjustment of certain suitable parameters and local searches by varying other parameters. However, in a formal sense this problem can be viewed as a global optimization problem, i.e. the determination of all solutions within a certain range of parameters that lead to a specific optimum. For example, it may be of interest to find all possible settings of multiple quadrupoles that can achieve imaging; or to find ahead of time all possible settings that achieve a particular tune; or to find all possible manners to adjust nonlinear parameters to achieve correction of high order aberrations. These tasks can easily be phrased in terms of such an optimization problem; but while mathematically this formulation is often straightforward, it has been common belief that it is of limited practical value since the resulting optimization problem cannot usually be solved. However, recent significant advances in modern methods of rigorous global optimization make these methods feasible for optics design for the first time. The key ideas of the method lie in an interplay of rigorous local underestimators of the objective functions, and by using the underestimators to rigorously iteratively eliminate regions that lie above already known upper bounds of the minima, in what is commonly known as a branch-and-bound approach. Recent enhancements of the Differential Algebraic methods used in particle

Computationally optimized ECoG stimulation with local safety constraints.

PubMed

Guler, Seyhmus; Dannhauer, Moritz; Roig-Solvas, Biel; Gkogkidis, Alexis; Macleod, Rob; Ball, Tonio; Ojemann, Jeffrey G; Brooks, Dana H

2018-06-01

Direct stimulation of the cortical surface is used clinically for cortical mapping and modulation of local activity. Future applications of cortical modulation and brain-computer interfaces may also use cortical stimulation methods. One common method to deliver current is through electrocorticography (ECoG) stimulation in which a dense array of electrodes are placed subdurally or epidurally to stimulate the cortex. However, proximity to cortical tissue limits the amount of current that can be delivered safely. It may be desirable to deliver higher current to a specific local region of interest (ROI) while limiting current to other local areas more stringently than is guaranteed by global safety limits. Two commonly used global safety constraints bound the total injected current and individual electrode currents. However, these two sets of constraints may not be sufficient to prevent high current density locally (hot-spots). In this work, we propose an efficient approach that prevents current density hot-spots in the entire brain while optimizing ECoG stimulus patterns for targeted stimulation. Specifically, we maximize the current along a particular desired directional field in the ROI while respecting three safety constraints: one on the total injected current, one on individual electrode currents, and the third on the local current density magnitude in the brain. This third set of constraints creates a computational barrier due to the huge number of constraints needed to bound the current density at every point in the entire brain. We overcome this barrier by adopting an efficient two-step approach. In the first step, the proposed method identifies the safe brain region, which cannot contain any hot-spots solely based on the global bounds on total injected current and individual electrode currents. In the second step, the proposed algorithm iteratively adjusts the stimulus pattern to arrive at a solution that exhibits no hot-spots in the remaining brain. We

On computing the global time-optimal motions of robotic manipulators in the presence of obstacles

NASA Technical Reports Server (NTRS)

Shiller, Zvi; Dubowsky, Steven

1991-01-01

A method for computing the time-optimal motions of robotic manipulators is presented that considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacles. The optimization problem is reduced to a search for the time-optimal path in the n-dimensional position space. A small set of near-optimal paths is first efficiently selected from a grid, using a branch and bound search and a series of lower bound estimates on the traveling time along a given path. These paths are further optimized with a local path optimization to yield the global optimal solution. Obstacles are considered by eliminating the collision points from the tessellated space and by adding a penalty function to the motion time in the local optimization. The computational efficiency of the method stems from the reduced dimensionality of the searched spaced and from combining the grid search with a local optimization. The method is demonstrated in several examples for two- and six-degree-of-freedom manipulators with obstacles.

Thinking Globally, Acting Locally: Using the Local Environment to Explore Global Issues.

ERIC Educational Resources Information Center

Simmons, Deborah

1994-01-01

Asserts that water pollution is a global problem and presents statistics indicating how much of the world's water is threatened. Presents three elementary school classroom activities on water quality and local water resources. Includes a figure describing the work of the Global Rivers Environmental Education Network. (CFR)

Fast Gaussian kernel learning for classification tasks based on specially structured global optimization.

PubMed

Zhong, Shangping; Chen, Tianshun; He, Fengying; Niu, Yuzhen

2014-09-01

For a practical pattern classification task solved by kernel methods, the computing time is mainly spent on kernel learning (or training). However, the current kernel learning approaches are based on local optimization techniques, and hard to have good time performances, especially for large datasets. Thus the existing algorithms cannot be easily extended to large-scale tasks. In this paper, we present a fast Gaussian kernel learning method by solving a specially structured global optimization (SSGO) problem. We optimize the Gaussian kernel function by using the formulated kernel target alignment criterion, which is a difference of increasing (d.i.) functions. Through using a power-transformation based convexification method, the objective criterion can be represented as a difference of convex (d.c.) functions with a fixed power-transformation parameter. And the objective programming problem can then be converted to a SSGO problem: globally minimizing a concave function over a convex set. The SSGO problem is classical and has good solvability. Thus, to find the global optimal solution efficiently, we can adopt the improved Hoffman's outer approximation method, which need not repeat the searching procedure with different starting points to locate the best local minimum. Also, the proposed method can be proven to converge to the global solution for any classification task. We evaluate the proposed method on twenty benchmark datasets, and compare it with four other Gaussian kernel learning methods. Experimental results show that the proposed method stably achieves both good time-efficiency performance and good classification performance. Copyright © 2014 Elsevier Ltd. All rights reserved.

Global/local methods for probabilistic structural analysis

NASA Technical Reports Server (NTRS)

Millwater, H. R.; Wu, Y.-T.

1993-01-01

A probabilistic global/local method is proposed to reduce the computational requirements of probabilistic structural analysis. A coarser global model is used for most of the computations with a local more refined model used only at key probabilistic conditions. The global model is used to establish the cumulative distribution function (cdf) and the Most Probable Point (MPP). The local model then uses the predicted MPP to adjust the cdf value. The global/local method is used within the advanced mean value probabilistic algorithm. The local model can be more refined with respect to the g1obal model in terms of finer mesh, smaller time step, tighter tolerances, etc. and can be used with linear or nonlinear models. The basis for this approach is described in terms of the correlation between the global and local models which can be estimated from the global and local MPPs. A numerical example is presented using the NESSUS probabilistic structural analysis program with the finite element method used for the structural modeling. The results clearly indicate a significant computer savings with minimal loss in accuracy.

Global/local methods for probabilistic structural analysis

NASA Astrophysics Data System (ADS)

Millwater, H. R.; Wu, Y.-T.

1993-04-01

A probabilistic global/local method is proposed to reduce the computational requirements of probabilistic structural analysis. A coarser global model is used for most of the computations with a local more refined model used only at key probabilistic conditions. The global model is used to establish the cumulative distribution function (cdf) and the Most Probable Point (MPP). The local model then uses the predicted MPP to adjust the cdf value. The global/local method is used within the advanced mean value probabilistic algorithm. The local model can be more refined with respect to the g1obal model in terms of finer mesh, smaller time step, tighter tolerances, etc. and can be used with linear or nonlinear models. The basis for this approach is described in terms of the correlation between the global and local models which can be estimated from the global and local MPPs. A numerical example is presented using the NESSUS probabilistic structural analysis program with the finite element method used for the structural modeling. The results clearly indicate a significant computer savings with minimal loss in accuracy.

Optimal Design of General Stiffened Composite Circular Cylinders for Global Buckling with Strength Constraints

NASA Technical Reports Server (NTRS)

Jaunky, N.; Ambur, D. R.; Knight, N. F., Jr.

1998-01-01

A design strategy for optimal design of composite grid-stiffened cylinders subjected to global and local buckling constraints and strength constraints was developed using a discrete optimizer based on a genetic algorithm. An improved smeared stiffener theory was used for the global analysis. Local buckling of skin segments were assessed using a Rayleigh-Ritz method that accounts for material anisotropy. The local buckling of stiffener segments were also assessed. Constraints on the axial membrane strain in the skin and stiffener segments were imposed to include strength criteria in the grid-stiffened cylinder design. Design variables used in this study were the axial and transverse stiffener spacings, stiffener height and thickness, skin laminate stacking sequence and stiffening configuration, where stiffening configuration is a design variable that indicates the combination of axial, transverse and diagonal stiffener in the grid-stiffened cylinder. The design optimization process was adapted to identify the best suited stiffening configurations and stiffener spacings for grid-stiffened composite cylinder with the length and radius of the cylinder, the design in-plane loads and material properties as inputs. The effect of having axial membrane strain constraints in the skin and stiffener segments in the optimization process is also studied for selected stiffening configurations.

Optimal Design of General Stiffened Composite Circular Cylinders for Global Buckling with Strength Constraints

NASA Technical Reports Server (NTRS)

Jaunky, Navin; Knight, Norman F., Jr.; Ambur, Damodar R.

1998-01-01

A design strategy for optimal design of composite grid-stiffened cylinders subjected to global and local buckling constraints and, strength constraints is developed using a discrete optimizer based on a genetic algorithm. An improved smeared stiffener theory is used for the global analysis. Local buckling of skin segments are assessed using a Rayleigh-Ritz method that accounts for material anisotropy. The local buckling of stiffener segments are also assessed. Constraints on the axial membrane strain in the skin and stiffener segments are imposed to include strength criteria in the grid-stiffened cylinder design. Design variables used in this study are the axial and transverse stiffener spacings, stiffener height and thickness, skin laminate stacking sequence, and stiffening configuration, where herein stiffening configuration is a design variable that indicates the combination of axial, transverse, and diagonal stiffener in the grid-stiffened cylinder. The design optimization process is adapted to identify the best suited stiffening configurations and stiffener spacings for grid-stiffened composite cylinder with the length and radius of the cylinder, the design in-plane loads, and material properties as inputs. The effect of having axial membrane strain constraints in the skin and stiffener segments in the optimization process is also studied for selected stiffening configuration.

Effort in Multitasking: Local and Global Assessment of Effort.

PubMed

Kiesel, Andrea; Dignath, David

2017-01-01

When performing multiple tasks in succession, self-organization of task order might be superior compared to external-controlled task schedules, because self-organization allows optimizing processing modes and thus reduces switch costs, and it increases commitment to task goals. However, self-organization is an additional executive control process that is not required if task order is externally specified and as such it is considered as time-consuming and effortful. To compare self-organized and externally controlled task scheduling, we suggest assessing global subjective and objectives measures of effort in addition to local performance measures. In our new experimental approach, we combined characteristics of dual tasking settings and task switching settings and compared local and global measures of effort in a condition with free choice of task sequence and a condition with cued task sequence. In a multi-tasking environment, participants chose the task order while the task requirement of the not-yet-performed task remained the same. This task preview allowed participants to work on the previously non-chosen items in parallel and resulted in faster responses and fewer errors in task switch trials than in task repetition trials. The free-choice group profited more from this task preview than the cued group when considering local performance measures. Nevertheless, the free-choice group invested more effort than the cued group when considering global measures. Thus, self-organization in task scheduling seems to be effortful even in conditions in which it is beneficiary for task processing. In a second experiment, we reduced the possibility of task preview for the not-yet-performed tasks in order to hinder efficient self-organization. Here neither local nor global measures revealed substantial differences between the free-choice and a cued task sequence condition. Based on the results of both experiments, we suggest that global assessment of effort in addition to

Online 3D Ear Recognition by Combining Global and Local Features.

PubMed

Liu, Yahui; Zhang, Bob; Lu, Guangming; Zhang, David

2016-01-01

The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for online three-dimensional ear acquisition was described. Based on the dataset collected by our scanner, two novel feature classes were defined from a three-dimensional ear image: the global feature class (empty centers and angles) and local feature class (points, lines, and areas). These features are extracted and combined in an optimal way for three-dimensional ear recognition. Using a large dataset consisting of 2,000 samples, the experimental results illustrate the effectiveness of fusing global and local features, obtaining an equal error rate of 2.2%.

Online 3D Ear Recognition by Combining Global and Local Features

PubMed Central

Liu, Yahui; Zhang, Bob; Lu, Guangming; Zhang, David

2016-01-01

The three-dimensional shape of the ear has been proven to be a stable candidate for biometric authentication because of its desirable properties such as universality, uniqueness, and permanence. In this paper, a special laser scanner designed for online three-dimensional ear acquisition was described. Based on the dataset collected by our scanner, two novel feature classes were defined from a three-dimensional ear image: the global feature class (empty centers and angles) and local feature class (points, lines, and areas). These features are extracted and combined in an optimal way for three-dimensional ear recognition. Using a large dataset consisting of 2,000 samples, the experimental results illustrate the effectiveness of fusing global and local features, obtaining an equal error rate of 2.2%. PMID:27935955

Global optimization of multicomponent distillation configurations: 2. Enumeration based global minimization algorithm

DOE PAGES

Nallasivam, Ulaganathan; Shah, Vishesh H.; Shenvi, Anirudh A.; ...

2016-02-10

We present a general Global Minimization Algorithm (GMA) to identify basic or thermally coupled distillation configurations that require the least vapor duty under minimum reflux conditions for separating any ideal or near-ideal multicomponent mixture into a desired number of product streams. In this algorithm, global optimality is guaranteed by modeling the system using Underwood equations and reformulating the resulting constraints to bilinear inequalities. The speed of convergence to the globally optimal solution is increased by using appropriate feasibility and optimality based variable-range reduction techniques and by developing valid inequalities. As a result, the GMA can be coupled with already developedmore » techniques that enumerate basic and thermally coupled distillation configurations, to provide for the first time, a global optimization based rank-list of distillation configurations.« less

Rock climbing: A local-global algorithm to compute minimum energy and minimum free energy pathways.

PubMed

Templeton, Clark; Chen, Szu-Hua; Fathizadeh, Arman; Elber, Ron

2017-10-21

The calculation of minimum energy or minimum free energy paths is an important step in the quantitative and qualitative studies of chemical and physical processes. The computations of these coordinates present a significant challenge and have attracted considerable theoretical and computational interest. Here we present a new local-global approach to study reaction coordinates, based on a gradual optimization of an action. Like other global algorithms, it provides a path between known reactants and products, but it uses a local algorithm to extend the current path in small steps. The local-global approach does not require an initial guess to the path, a major challenge for global pathway finders. Finally, it provides an exact answer (the steepest descent path) at the end of the calculations. Numerical examples are provided for the Mueller potential and for a conformational transition in a solvated ring system.

SGO: A fast engine for ab initio atomic structure global optimization by differential evolution

NASA Astrophysics Data System (ADS)

Chen, Zhanghui; Jia, Weile; Jiang, Xiangwei; Li, Shu-Shen; Wang, Lin-Wang

2017-10-01

As the high throughout calculations and material genome approaches become more and more popular in material science, the search for optimal ways to predict atomic global minimum structure is a high research priority. This paper presents a fast method for global search of atomic structures at ab initio level. The structures global optimization (SGO) engine consists of a high-efficiency differential evolution algorithm, accelerated local relaxation methods and a plane-wave density functional theory code running on GPU machines. The purpose is to show what can be achieved by combining the superior algorithms at the different levels of the searching scheme. SGO can search the global-minimum configurations of crystals, two-dimensional materials and quantum clusters without prior symmetry restriction in a relatively short time (half or several hours for systems with less than 25 atoms), thus making such a task a routine calculation. Comparisons with other existing methods such as minima hopping and genetic algorithm are provided. One motivation of our study is to investigate the properties of magnetic systems in different phases. The SGO engine is capable of surveying the local minima surrounding the global minimum, which provides the information for the overall energy landscape of a given system. Using this capability we have found several new configurations for testing systems, explored their energy landscape, and demonstrated that the magnetic moment of metal clusters fluctuates strongly in different local minima.

Local empathy provides global minimization of congestion in communication networks

NASA Astrophysics Data System (ADS)

Meloni, Sandro; Gómez-Gardeñes, Jesús

2010-11-01

We present a mechanism to avoid congestion in complex networks based on a local knowledge of traffic conditions and the ability of routers to self-coordinate their dynamical behavior. In particular, routers make use of local information about traffic conditions to either reject or accept information packets from their neighbors. We show that when nodes are only aware of their own congestion state they self-organize into a hierarchical configuration that delays remarkably the onset of congestion although leading to a sharp first-order-like congestion transition. We also consider the case when nodes are aware of the congestion state of their neighbors. In this case, we show that empathy between nodes is strongly beneficial to the overall performance of the system and it is possible to achieve larger values for the critical load together with a smooth, second-order-like, transition. Finally, we show how local empathy minimize the impact of congestion as much as global minimization. Therefore, here we present an outstanding example of how local dynamical rules can optimize the system’s functioning up to the levels reached using global knowledge.

Local conformity induced global oscillation

NASA Astrophysics Data System (ADS)

Li, Dong; Li, Wei; Hu, Gang; Zheng, Zhigang

2009-04-01

The game ‘rock-paper-scissors’ model, with the consideration of the effect of the psychology of conformity, is investigated. The interaction between each two agents is global, but the strategy of the conformity is local for individuals. In the statistical opinion, the probability of the appearance of each strategy is uniform. The dynamical analysis of this model indicates that the equilibrium state may lose its stability at a threshold and is replaced by a globally oscillating state. The global oscillation is induced by the local conformity, which is originated from the synchronization of individual strategies.

Global carbon assimilation system using a local ensemble Kalman filter with multiple ecosystem models

NASA Astrophysics Data System (ADS)

Zhang, Shupeng; Yi, Xue; Zheng, Xiaogu; Chen, Zhuoqi; Dan, Bo; Zhang, Xuanze

2014-11-01

In this paper, a global carbon assimilation system (GCAS) is developed for optimizing the global land surface carbon flux at 1° resolution using multiple ecosystem models. In GCAS, three ecosystem models, Boreal Ecosystem Productivity Simulator, Carnegie-Ames-Stanford Approach, and Community Atmosphere Biosphere Land Exchange, produce the prior fluxes, and an atmospheric transport model, Model for OZone And Related chemical Tracers, is used to calculate atmospheric CO2 concentrations resulting from these prior fluxes. A local ensemble Kalman filter is developed to assimilate atmospheric CO2 data observed at 92 stations to optimize the carbon flux for six land regions, and the Bayesian model averaging method is implemented in GCAS to calculate the weighted average of the optimized fluxes based on individual ecosystem models. The weights for the models are found according to the closeness of their forecasted CO2 concentration to observation. Results of this study show that the model weights vary in time and space, allowing for an optimum utilization of different strengths of different ecosystem models. It is also demonstrated that spatial localization is an effective technique to avoid spurious optimization results for regions that are not well constrained by the atmospheric data. Based on the multimodel optimized flux from GCAS, we found that the average global terrestrial carbon sink over the 2002-2008 period is 2.97 ± 1.1 PgC yr-1, and the sinks are 0.88 ± 0.52, 0.27 ± 0.33, 0.67 ± 0.39, 0.90 ± 0.68, 0.21 ± 0.31, and 0.04 ± 0.08 PgC yr-1 for the North America, South America, Africa, Eurasia, Tropical Asia, and Australia, respectively. This multimodel GCAS can be used to improve global carbon cycle estimation.

Hybrid surrogate-model-based multi-fidelity efficient global optimization applied to helicopter blade design

NASA Astrophysics Data System (ADS)

Ariyarit, Atthaphon; Sugiura, Masahiko; Tanabe, Yasutada; Kanazaki, Masahiro

2018-06-01

A multi-fidelity optimization technique by an efficient global optimization process using a hybrid surrogate model is investigated for solving real-world design problems. The model constructs the local deviation using the kriging method and the global model using a radial basis function. The expected improvement is computed to decide additional samples that can improve the model. The approach was first investigated by solving mathematical test problems. The results were compared with optimization results from an ordinary kriging method and a co-kriging method, and the proposed method produced the best solution. The proposed method was also applied to aerodynamic design optimization of helicopter blades to obtain the maximum blade efficiency. The optimal shape obtained by the proposed method achieved performance almost equivalent to that obtained using the high-fidelity, evaluation-based single-fidelity optimization. Comparing all three methods, the proposed method required the lowest total number of high-fidelity evaluation runs to obtain a converged solution.

Global Health Diplomacy, "San Francisco Values," and HIV/AIDS: From the Local to the Global.

PubMed

Kevany, Sebastian

2015-01-01

San Francisco has a distinguished history as a cosmopolitan, progressive, and international city, including extensive associations with global health. These circumstances have contributed to new, interdisciplinary scholarship in the field of global health diplomacy (GHD). In the present review, we describe the evolution and history of GHD at the practical and theoretical levels within the San Francisco medical community, trace related associations between the local and the global, and propose a range of potential opportunities for further development of this dynamic field. We provide a historical overview of the development of the "San Francisco Model" of collaborative, community-owned HIV/AIDS treatment and care programs as pioneered under the "Ward 86" paradigm of the 1980s. We traced the expansion and evolution of this model to the national level under the Ryan White Care Act, and internationally via the President's Emergency Plan for AIDS Relief. In parallel, we describe the evolution of global health diplomacy practices, from the local to the global, including the integration of GHD principles into intervention design to ensure social, political, and cultural acceptability and sensitivity. Global health programs, as informed by lessons learned from the San Francisco Model, are increasingly aligned with diplomatic principles and practices. This awareness has aided implementation, allowed policymakers to pursue related and progressive social and humanitarian issues in conjunction with medical responses, and elevated global health to the realm of "high politics." In the 21st century, the integration between diplomatic, medical, and global health practices will continue under "smart global health" and GHD paradigms. These approaches will enhance intervention cost-effectiveness by addressing and optimizing, in tandem with each other, a wide range of (health and non-health) foreign policy, diplomatic, security, and economic priorities in a synergistic manner

Global/local stress analysis of composite panels

NASA Technical Reports Server (NTRS)

Ransom, Jonathan B.; Knight, Norman F., Jr.

1989-01-01

A method for performing a global/local stress analysis is described, and its capabilities are demonstrated. The method employs spline interpolation functions which satisfy the linear plate bending equation to determine displacements and rotations from a global model which are used as boundary conditions for the local model. Then, the local model is analyzed independent of the global model of the structure. This approach can be used to determine local, detailed stress states for specific structural regions using independent, refined local models which exploit information from less-refined global models. The method presented is not restricted to having a priori knowledge of the location of the regions requiring local detailed stress analysis. This approach also reduces the computational effort necessary to obtain the detailed stress state. Criteria for applying the method are developed. The effectiveness of the method is demonstrated using a classical stress concentration problem and a graphite-epoxy blade-stiffened panel with a discontinuous stiffener.

Local and Global Auditory Processing: Behavioral and ERP Evidence

PubMed Central

Sanders, Lisa D.; Poeppel, David

2007-01-01

Differential processing of local and global visual features is well established. Global precedence effects, differences in event-related potentials (ERPs) elicited when attention is focused on local versus global levels, and hemispheric specialization for local and global features all indicate that relative scale of detail is an important distinction in visual processing. Observing analogous differential processing of local and global auditory information would suggest that scale of detail is a general organizational principle of the brain. However, to date the research on auditory local and global processing has primarily focused on music perception or on the perceptual analysis of relatively higher and lower frequencies. The study described here suggests that temporal aspects of auditory stimuli better capture the local-global distinction. By combining short (40 ms) frequency modulated tones in series to create global auditory patterns (500 ms), we independently varied whether pitch increased or decreased over short time spans (local) and longer time spans (global). Accuracy and reaction time measures revealed better performance for global judgments and asymmetric interference that were modulated by amount of pitch change. ERPs recorded while participants listened to identical sounds and indicated the direction of pitch change at the local or global levels provided evidence for differential processing similar to that found in ERP studies employing hierarchical visual stimuli. ERP measures failed to provide evidence for lateralization of local and global auditory perception, but differences in distributions suggest preferential processing in more ventral and dorsal areas respectively. PMID:17113115

Local Reasons to Give Globally: Identity Extension and Global Cooperation.

PubMed

Buchan, Nancy R; Jeong, Sophia Soyoung; Ward, A K

2017-11-14

Recent political events across the world suggest a retrenchment from globalization and a possible increase in parochialism. This inward-looking threat from parochialism occurs just as the global community faces growing challenges that require trans-national cooperation. In this research, we question if strong identification with an in-group necessarily leads to parochialism and ultimately is detrimental to global cooperation. Building on research on global social identification, we explore whether strong local identification can expand in inclusiveness to global identification, and among whom this is likely to happen. The results of our global public goods study - conducted in South Korea and the United States - show that high levels of social identification with a local group can extend to the global collective, particularly for individuals who are also high in concern-for-others. Furthermore, this identification translates into behavior that benefits the global, anonymous group at a cost to oneself. These results shed light on how to avoid the trap of parochialism and instead engender cooperative behavior with the broader global community.

Well-conditioning global-local analysis using stable generalized/extended finite element method for linear elastic fracture mechanics

NASA Astrophysics Data System (ADS)

Malekan, Mohammad; Barros, Felicio Bruzzi

2016-11-01

Using the locally-enriched strategy to enrich a small/local part of the problem by generalized/extended finite element method (G/XFEM) leads to non-optimal convergence rate and ill-conditioning system of equations due to presence of blending elements. The local enrichment can be chosen from polynomial, singular, branch or numerical types. The so-called stable version of G/XFEM method provides a well-conditioning approach when only singular functions are used in the blending elements. This paper combines numeric enrichment functions obtained from global-local G/XFEM method with the polynomial enrichment along with a well-conditioning approach, stable G/XFEM, in order to show the robustness and effectiveness of the approach. In global-local G/XFEM, the enrichment functions are constructed numerically from the solution of a local problem. Furthermore, several enrichment strategies are adopted along with the global-local enrichment. The results obtained with these enrichments strategies are discussed in detail, considering convergence rate in strain energy, growth rate of condition number, and computational processing. Numerical experiments show that using geometrical enrichment along with stable G/XFEM for global-local strategy improves the convergence rate and the conditioning of the problem. In addition, results shows that using polynomial enrichment for global problem simultaneously with global-local enrichments lead to ill-conditioned system matrices and bad convergence rate.

Thriving locally in the global economy.

PubMed

Kanter, Rosabeth Moss

2003-08-01

More and more small and midsize companies are joining corporate giants in striving to exploit international growth markets. At the same time, civic leaders worry about their communities' economic future in light of the impact of global forces on the operation and survival of business. How can communities retain local vitality yet still link their business to the global economy? Harvard professor Rosabeth Moss Kanter addresses that question in this classic HBR article, orginally published in 1995. To avoid a clash between international economic interests and local political interests, globalizing business must learn how to be responsive to the communities in which they operate, Kanter says. And communities must determine how to create a civic culture that will attract and retain footloose companies. The author surveyed five U.S. regions with direct connections to the global economy--Boston, Cleveland, Miami, Seattle, and the Spartanburg-Greenville region of South Carolina--to determine their business and civic leader's strategies for improving their constituent's quality of life. She identified ways in which the global economy can work locally by capitalizing on the resources that distinguish one place from another. Kanter argues that regions can invest in capabilities that connect their local populations to the global economy in one of three ways: as thinkers, makers, or traders. She points to the Spartanburg-Greenville region as a good example of a world-class makers, with its exceptional blue-collar workforce that has attracted more than 200 companies from 18 countries. The history of the economic development of this region is a lesson for those seeking to understand how to achieve world-class status and bring local residents into the world economy.

Unconscious Local Motion Alters Global Image Speed

PubMed Central

Khuu, Sieu K.; Chung, Charles Y. L.; Lord, Stephanie; Pearson, Joel

2014-01-01

Accurate motion perception of self and object speed is crucial for successful interaction in the world. The context in which we make such speed judgments has a profound effect on their accuracy. Misperceptions of motion speed caused by the context can have drastic consequences in real world situations, but they also reveal much about the underlying mechanisms of motion perception. Here we show that motion signals suppressed from awareness can warp simultaneous conscious speed perception. In Experiment 1, we measured global speed discrimination thresholds using an annulus of 8 local Gabor elements. We show that physically removing local elements from the array attenuated global speed discrimination. However, removing awareness of the local elements only had a small effect on speed discrimination. That is, unconscious local motion elements contributed to global conscious speed perception. In Experiment 2 we measured the global speed of the moving Gabor patterns, when half the elements moved at different speeds. We show that global speed averaging occurred regardless of whether local elements were removed from awareness, such that the speed of invisible elements continued to be averaged together with the visible elements to determine the global speed. These data suggest that contextual motion signals outside of awareness can both boost and affect our experience of motion speed, and suggest that such pooling of motion signals occurs before the conscious extraction of the surround motion speed. PMID:25503603

Global-local methodologies and their application to nonlinear analysis

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.

1989-01-01

An assessment is made of the potential of different global-local analysis strategies for predicting the nonlinear and postbuckling responses of structures. Two postbuckling problems of composite panels are used as benchmarks and the application of different global-local methodologies to these benchmarks is outlined. The key elements of each of the global-local strategies are discussed and future research areas needed to realize the full potential of global-local methodologies are identified.

Particle swarm optimization-based local entropy weighted histogram equalization for infrared image enhancement

NASA Astrophysics Data System (ADS)

Wan, Minjie; Gu, Guohua; Qian, Weixian; Ren, Kan; Chen, Qian; Maldague, Xavier

2018-06-01

Infrared image enhancement plays a significant role in intelligent urban surveillance systems for smart city applications. Unlike existing methods only exaggerating the global contrast, we propose a particle swam optimization-based local entropy weighted histogram equalization which involves the enhancement of both local details and fore-and background contrast. First of all, a novel local entropy weighted histogram depicting the distribution of detail information is calculated based on a modified hyperbolic tangent function. Then, the histogram is divided into two parts via a threshold maximizing the inter-class variance in order to improve the contrasts of foreground and background, respectively. To avoid over-enhancement and noise amplification, double plateau thresholds of the presented histogram are formulated by means of particle swarm optimization algorithm. Lastly, each sub-image is equalized independently according to the constrained sub-local entropy weighted histogram. Comparative experiments implemented on real infrared images prove that our algorithm outperforms other state-of-the-art methods in terms of both visual and quantized evaluations.

Think global, act local: Preserving the global commons

PubMed Central

Hauser, Oliver P.; Hendriks, Achim; Rand, David G.; Nowak, Martin A.

2016-01-01

Preserving global public goods, such as the planet’s ecosystem, depends on large-scale cooperation, which is difficult to achieve because the standard reciprocity mechanisms weaken in large groups. Here we demonstrate a method by which reciprocity can maintain cooperation in a large-scale public goods game (PGG). In a first experiment, participants in groups of on average 39 people play one round of a Prisoner’s Dilemma (PD) with their two nearest neighbours on a cyclic network after each PGG round. We observe that people engage in “local-to-global” reciprocity, leveraging local interactions to enforce global cooperation: Participants reduce PD cooperation with neighbours who contribute little in the PGG. In response, low PGG contributors increase their contributions if both neighbours defect in the PD. In a control condition, participants do not know their neighbours’ PGG contribution and thus cannot link play in the PD to the PGG. In the control we observe a sharp decline of cooperation in the PGG, while in the treatment condition global cooperation is maintained. In a second experiment, we demonstrate the scalability of this effect: in a 1,000-person PGG, participants in the treatment condition successfully sustain public contributions. Our findings suggest that this simple “local-to-global” intervention facilitates large-scale cooperation. PMID:27808222

The Global Photonics Education Network: another way to think globally and act locally

NASA Astrophysics Data System (ADS)

Roychoudhuri, Chandrasekhar; Nantel, Marc

2003-10-01

As the world gets smaller through globalization and telecommunication, it also gets richer in possibilities. Empowering the educators to exchange ideas on successes and mistakes continually on the global stage while working to improve the education on their local stages can galvanize those potential richness. Our goal is to enhance this global inter-connectedness by facilitating the local intra-connectedness among the regional educators and their organizations, which can form local education clusters.

Optimal global value of information trials: better aligning manufacturer and decision maker interests and enabling feasible risk sharing.

PubMed

Eckermann, Simon; Willan, Andrew R

2013-05-01

Risk sharing arrangements relate to adjusting payments for new health technologies given evidence of their performance over time. Such arrangements rely on prospective information regarding the incremental net benefit of the new technology, and its use in practice. However, once the new technology has been adopted in a particular jurisdiction, randomized clinical trials within that jurisdiction are likely to be infeasible and unethical in the cases where they would be most helpful, i.e. with current evidence of positive while uncertain incremental health and net monetary benefit. Informed patients in these cases would likely be reluctant to participate in a trial, preferring instead to receive the new technology with certainty. Consequently, informing risk sharing arrangements within a jurisdiction is problematic given the infeasibility of collecting prospective trial data. To overcome such problems, we demonstrate that global trials facilitate trialling post adoption, leading to more complete and robust risk sharing arrangements that mitigate the impact of costs of reversal on expected value of information in jurisdictions who adopt while a global trial is undertaken. More generally, optimally designed global trials offer distinct advantages over locally optimal solutions for decision makers and manufacturers alike: avoiding opportunity costs of delay in jurisdictions that adopt; overcoming barriers to evidence collection; and improving levels of expected implementation. Further, the greater strength and translatability of evidence across jurisdictions inherent in optimal global trial design reduces barriers to translation across jurisdictions characteristic of local trials. Consequently, efficiently designed global trials better align the interests of decision makers and manufacturers, increasing the feasibility of risk sharing and the expected strength of evidence over local trials, up until the point that current evidence is globally sufficient.

Contextual cueing in naturalistic scenes: Global and local contexts.

PubMed

Brockmole, James R; Castelhano, Monica S; Henderson, John M

2006-07-01

In contextual cueing, the position of a target within a group of distractors is learned over repeated exposure to a display with reference to a few nearby items rather than to the global pattern created by the elements. The authors contrasted the role of global and local contexts for contextual cueing in naturalistic scenes. Experiment 1 showed that learned target positions transfer when local information is altered but not when global information is changed. Experiment 2 showed that scene-target covariation is learned more slowly when local, but not global, information is repeated across trials than when global but not local information is repeated. Thus, in naturalistic scenes, observers are biased to associate target locations with global contexts. Copyright 2006 APA, all rights reserved.

LDRD Final Report: Global Optimization for Engineering Science Problems

DOE Office of Scientific and Technical Information (OSTI.GOV)

HART,WILLIAM E.

1999-12-01

For a wide variety of scientific and engineering problems the desired solution corresponds to an optimal set of objective function parameters, where the objective function measures a solution's quality. The main goal of the LDRD ''Global Optimization for Engineering Science Problems'' was the development of new robust and efficient optimization algorithms that can be used to find globally optimal solutions to complex optimization problems. This SAND report summarizes the technical accomplishments of this LDRD, discusses lessons learned and describes open research issues.

Optimizing human activity patterns using global sensitivity analysis.

PubMed

Fairchild, Geoffrey; Hickmann, Kyle S; Mniszewski, Susan M; Del Valle, Sara Y; Hyman, James M

2014-12-01

Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule's regularity for a population. We show how to tune an activity's regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations.

Optimizing human activity patterns using global sensitivity analysis

PubMed Central

Hickmann, Kyle S.; Mniszewski, Susan M.; Del Valle, Sara Y.; Hyman, James M.

2014-01-01

Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule’s regularity for a population. We show how to tune an activity’s regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimization problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. We use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations. PMID:25580080

Educational Linguistics in Practice: Applying the Local Globally and the Global Locally

ERIC Educational Resources Information Center

King, Kendall A.; Hult, Francis M.

2011-01-01

This volume provides a state-of-the-art snapshot of language and education research and demonstrates ways in which local and global processes are intertwined with language learning, use, and policies. Reflecting but also expanding on Nancy Hornberger's ground-breaking contributions to educational linguistics, this book brings together leading…

Automatic 3D liver segmentation based on deep learning and globally optimized surface evolution

NASA Astrophysics Data System (ADS)

Hu, Peijun; Wu, Fa; Peng, Jialin; Liang, Ping; Kong, Dexing

2016-12-01

The detection and delineation of the liver from abdominal 3D computed tomography (CT) images are fundamental tasks in computer-assisted liver surgery planning. However, automatic and accurate segmentation, especially liver detection, remains challenging due to complex backgrounds, ambiguous boundaries, heterogeneous appearances and highly varied shapes of the liver. To address these difficulties, we propose an automatic segmentation framework based on 3D convolutional neural network (CNN) and globally optimized surface evolution. First, a deep 3D CNN is trained to learn a subject-specific probability map of the liver, which gives the initial surface and acts as a shape prior in the following segmentation step. Then, both global and local appearance information from the prior segmentation are adaptively incorporated into a segmentation model, which is globally optimized in a surface evolution way. The proposed method has been validated on 42 CT images from the public Sliver07 database and local hospitals. On the Sliver07 online testing set, the proposed method can achieve an overall score of 80.3+/- 4.5 , yielding a mean Dice similarity coefficient of 97.25+/- 0.65 % , and an average symmetric surface distance of 0.84+/- 0.25 mm. The quantitative validations and comparisons show that the proposed method is accurate and effective for clinical application.

Global/Local: What Does It Mean for Global Health Educators and How Do We Do It?

PubMed

Rowthorn, Virginia

2015-01-01

There has been dramatic growth in the number of innovative university programs that focus on social justice and teach community-based strategies that are applicable both domestically in North America and internationally. These programs often are referred to as global/local and reflect an effort to link global health and campus community engagement efforts to acknowledge that a common set of transferable skills can be adapted to work with vulnerable populations wherever they may be. However, the concepts underlying global/local education are undertheorized and universities struggle to make the global/local link without a conceptual framework to guide them in this pursuit. This study reports on the outcomes of a 2015 national meeting of 120 global health educators convened to discuss the concepts underlying global/local education, to share models of global/local programs, and to draft a preliminary list of critical elements of a meaningful and didactically sound global/local educational program. A qualitative analysis was conducted of the discussions that took place at the national meeting. The analysis was supported by videorecordings made of full-group discussions. Results were categorized into a preliminary list of global/local program elements. Additionally, a synthesis was developed of critical issues raised at the meeting that warrant future discussion and study. A preliminary list was developed of 7 program components that global health educators consider essential to categorize a program as global/local and to ensure that such a program includes specific critical elements. Interest is great among global health educators to understand and teach the conceptual link between learning on both the global and community levels. Emphasis on this link has high potential to unite the siloed fields of global health and domestic community public health and the institutions, funding options, and career pathways that flow from them. Future research should focus on

Joint global optimization of tomographic data based on particle swarm optimization and decision theory

NASA Astrophysics Data System (ADS)

Paasche, H.; Tronicke, J.

2012-04-01

In many near surface geophysical applications multiple tomographic data sets are routinely acquired to explore subsurface structures and parameters. Linking the model generation process of multi-method geophysical data sets can significantly reduce ambiguities in geophysical data analysis and model interpretation. Most geophysical inversion approaches rely on local search optimization methods used to find an optimal model in the vicinity of a user-given starting model. The final solution may critically depend on the initial model. Alternatively, global optimization (GO) methods have been used to invert geophysical data. They explore the solution space in more detail and determine the optimal model independently from the starting model. Additionally, they can be used to find sets of optimal models allowing a further analysis of model parameter uncertainties. Here we employ particle swarm optimization (PSO) to realize the global optimization of tomographic data. PSO is an emergent methods based on swarm intelligence characterized by fast and robust convergence towards optimal solutions. The fundamental principle of PSO is inspired by nature, since the algorithm mimics the behavior of a flock of birds searching food in a search space. In PSO, a number of particles cruise a multi-dimensional solution space striving to find optimal model solutions explaining the acquired data. The particles communicate their positions and success and direct their movement according to the position of the currently most successful particle of the swarm. The success of a particle, i.e. the quality of the currently found model by a particle, must be uniquely quantifiable to identify the swarm leader. When jointly inverting disparate data sets, the optimization solution has to satisfy multiple optimization objectives, at least one for each data set. Unique determination of the most successful particle currently leading the swarm is not possible. Instead, only statements about the Pareto

Global processing takes time: A meta-analysis on local-global visual processing in ASD.

PubMed

Van der Hallen, Ruth; Evers, Kris; Brewaeys, Katrien; Van den Noortgate, Wim; Wagemans, Johan

2015-05-01

What does an individual with autism spectrum disorder (ASD) perceive first: the forest or the trees? In spite of 30 years of research and influential theories like the weak central coherence (WCC) theory and the enhanced perceptual functioning (EPF) account, the interplay of local and global visual processing in ASD remains only partly understood. Research findings vary in indicating a local processing bias or a global processing deficit, and often contradict each other. We have applied a formal meta-analytic approach and combined 56 articles that tested about 1,000 ASD participants and used a wide range of stimuli and tasks to investigate local and global visual processing in ASD. Overall, results show no enhanced local visual processing nor a deficit in global visual processing. Detailed analysis reveals a difference in the temporal pattern of the local-global balance, that is, slow global processing in individuals with ASD. Whereas task-dependent interaction effects are obtained, gender, age, and IQ of either participant groups seem to have no direct influence on performance. Based on the overview of the literature, suggestions are made for future research. (c) 2015 APA, all rights reserved).

On strong homogeneity of a class of global optimization algorithms working with infinite and infinitesimal scales

NASA Astrophysics Data System (ADS)

Sergeyev, Yaroslav D.; Kvasov, Dmitri E.; Mukhametzhanov, Marat S.

2018-06-01

The necessity to find the global optimum of multiextremal functions arises in many applied problems where finding local solutions is insufficient. One of the desirable properties of global optimization methods is strong homogeneity meaning that a method produces the same sequences of points where the objective function is evaluated independently both of multiplication of the function by a scaling constant and of adding a shifting constant. In this paper, several aspects of global optimization using strongly homogeneous methods are considered. First, it is shown that even if a method possesses this property theoretically, numerically very small and large scaling constants can lead to ill-conditioning of the scaled problem. Second, a new class of global optimization problems where the objective function can have not only finite but also infinite or infinitesimal Lipschitz constants is introduced. Third, the strong homogeneity of several Lipschitz global optimization algorithms is studied in the framework of the Infinity Computing paradigm allowing one to work numerically with a variety of infinities and infinitesimals. Fourth, it is proved that a class of efficient univariate methods enjoys this property for finite, infinite and infinitesimal scaling and shifting constants. Finally, it is shown that in certain cases the usage of numerical infinities and infinitesimals can avoid ill-conditioning produced by scaling. Numerical experiments illustrating theoretical results are described.

Global Optimal Trajectory in Chaos and NP-Hardness

NASA Astrophysics Data System (ADS)

Latorre, Vittorio; Gao, David Yang

This paper presents an unconventional theory and method for solving general nonlinear dynamical systems. Instead of the direct iterative methods, the discretized nonlinear system is first formulated as a global optimization problem via the least squares method. A newly developed canonical duality theory shows that this nonconvex minimization problem can be solved deterministically in polynomial time if a global optimality condition is satisfied. The so-called pseudo-chaos produced by linear iterative methods are mainly due to the intrinsic numerical error accumulations. Otherwise, the global optimization problem could be NP-hard and the nonlinear system can be really chaotic. A conjecture is proposed, which reveals the connection between chaos in nonlinear dynamics and NP-hardness in computer science. The methodology and the conjecture are verified by applications to the well-known logistic equation, a forced memristive circuit and the Lorenz system. Computational results show that the canonical duality theory can be used to identify chaotic systems and to obtain realistic global optimal solutions in nonlinear dynamical systems. The method and results presented in this paper should bring some new insights into nonlinear dynamical systems and NP-hardness in computational complexity theory.

Global/local methods research using the CSM testbed

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Ransom, Jonathan B.; Griffin, O. Hayden, Jr.; Thompson, Danniella M.

1990-01-01

Research activities in global/local stress analysis are described including both two- and three-dimensional analysis methods. These methods are being developed within a common structural analysis framework. Representative structural analysis problems are presented to demonstrate the global/local methodologies being developed.

Auditory global-local processing: effects of attention and musical experience.

PubMed

Ouimet, Tia; Foster, Nicholas E V; Hyde, Krista L

2012-10-01

In vision, global (whole) features are typically processed before local (detail) features ("global precedence effect"). However, the distinction between global and local processing is less clear in the auditory domain. The aims of the present study were to investigate: (i) the effects of directed versus divided attention, and (ii) the effect musical training on auditory global-local processing in 16 adult musicians and 16 non-musicians. Participants were presented with short nine-tone melodies, each comprised of three triplet sequences (three-tone units). In a "directed attention" task, participants were asked to focus on either the global or local pitch pattern and had to determine if the pitch pattern went up or down. In a "divided attention" task, participants judged whether the target pattern (up or down) was present or absent. Overall, global structure was perceived faster and more accurately than local structure. The global precedence effect was observed regardless of whether attention was directed to a specific level or divided between levels. Musicians performed more accurately than non-musicians overall, but non-musicians showed a more pronounced global advantage. This study provides evidence for an auditory global precedence effect across attention tasks, and for differences in auditory global-local processing associated with musical experience.

Local and global dynamical effects of dark energy

NASA Astrophysics Data System (ADS)

Chernin, A. D.

Local expansion flows of galaxies were discovered by Lemaitre and Hubble in 1927-29 at distances of less than 25-30 Mpc. The global expansion of the Universe as a whole was predicted theoretically by Friedmann in 1922-24 and discovered in the 1990s in observations at truly cosmological distances of more than 1 000 Mpc. On all these spatial scales, the flows follow a (nearly) linear velocity-distance relation, known now as Hubble's law. This similarity of local and global phenomena is due to the universal dark energy antigravity which dominates the cosmic dynamics on both local and global spatial scales.

A shifted hyperbolic augmented Lagrangian-based artificial fish two-swarm algorithm with guaranteed convergence for constrained global optimization

NASA Astrophysics Data System (ADS)

Rocha, Ana Maria A. C.; Costa, M. Fernanda P.; Fernandes, Edite M. G. P.

2016-12-01

This article presents a shifted hyperbolic penalty function and proposes an augmented Lagrangian-based algorithm for non-convex constrained global optimization problems. Convergence to an ?-global minimizer is proved. At each iteration k, the algorithm requires the ?-global minimization of a bound constrained optimization subproblem, where ?. The subproblems are solved by a stochastic population-based metaheuristic that relies on the artificial fish swarm paradigm and a two-swarm strategy. To enhance the speed of convergence, the algorithm invokes the Nelder-Mead local search with a dynamically defined probability. Numerical experiments with benchmark functions and engineering design problems are presented. The results show that the proposed shifted hyperbolic augmented Lagrangian compares favorably with other deterministic and stochastic penalty-based methods.

Walking the Filament of Feasibility: Global Optimization of Highly-Constrained, Multi-Modal Interplanetary Trajectories Using a Novel Stochastic Search Technique

NASA Technical Reports Server (NTRS)

Englander, Arnold C.; Englander, Jacob A.

2017-01-01

Interplanetary trajectory optimization problems are highly complex and are characterized by a large number of decision variables and equality and inequality constraints as well as many locally optimal solutions. Stochastic global search techniques, coupled with a large-scale NLP solver, have been shown to solve such problems but are inadequately robust when the problem constraints become very complex. In this work, we present a novel search algorithm that takes advantage of the fact that equality constraints effectively collapse the solution space to lower dimensionality. This new approach walks the filament'' of feasibility to efficiently find the global optimal solution.

A global optimization algorithm for protein surface alignment

PubMed Central

2010-01-01

Background A relevant problem in drug design is the comparison and recognition of protein binding sites. Binding sites recognition is generally based on geometry often combined with physico-chemical properties of the site since the conformation, size and chemical composition of the protein surface are all relevant for the interaction with a specific ligand. Several matching strategies have been designed for the recognition of protein-ligand binding sites and of protein-protein interfaces but the problem cannot be considered solved. Results In this paper we propose a new method for local structural alignment of protein surfaces based on continuous global optimization techniques. Given the three-dimensional structures of two proteins, the method finds the isometric transformation (rotation plus translation) that best superimposes active regions of two structures. We draw our inspiration from the well-known Iterative Closest Point (ICP) method for three-dimensional (3D) shapes registration. Our main contribution is in the adoption of a controlled random search as a more efficient global optimization approach along with a new dissimilarity measure. The reported computational experience and comparison show viability of the proposed approach. Conclusions Our method performs well to detect similarity in binding sites when this in fact exists. In the future we plan to do a more comprehensive evaluation of the method by considering large datasets of non-redundant proteins and applying a clustering technique to the results of all comparisons to classify binding sites. PMID:20920230

Global Response to Local Ionospheric Mass Ejection

NASA Technical Reports Server (NTRS)

Moore, T. E.; Fok, M.-C.; Delcourt, D. C.; Slinker, S. P.; Fedder, J. A.

2010-01-01

We revisit a reported "Ionospheric Mass Ejection" using prior event observations to guide a global simulation of local ionospheric outflows, global magnetospheric circulation, and plasma sheet pressurization, and comparing our results with the observed global response. Our simulation framework is based on test particle motions in the Lyon-Fedder-Mobarry (LFM) global circulation model electromagnetic fields. The inner magnetosphere is simulated with the Comprehensive Ring Current Model (CRCM) of Fok and Wolf, driven by the transpolar potential developed by the LFM magnetosphere, and includes an embedded plasmaspheric simulation. Global circulation is stimulated using the observed solar wind conditions for the period 24-25 Sept 1998. This period begins with the arrival of a Coronal Mass Ejection, initially with northward, but later with southward interplanetary magnetic field. Test particles are launched from the ionosphere with fluxes specified by local empirical relationships of outflow to electrodynamic and particle precipitation imposed by the MIlD simulation. Particles are tracked until they are lost from the system downstream or into the atmosphere, using the full equations of motion. Results are compared with the observed ring current and a simulation of polar and auroral wind outflows driven globally by solar wind dynamic pressure. We find good quantitative agreement with the observed ring current, and reasonable qualitative agreement with earlier simulation results, suggesting that the solar wind driven global simulation generates realistic energy dissipation in the ionosphere and that the Strangeway relations provide a realistic local outflow description.

A Novel Particle Swarm Optimization Algorithm for Global Optimization

PubMed Central

Wang, Chun-Feng; Liu, Kui

2016-01-01

Particle Swarm Optimization (PSO) is a recently developed optimization method, which has attracted interest of researchers in various areas due to its simplicity and effectiveness, and many variants have been proposed. In this paper, a novel Particle Swarm Optimization algorithm is presented, in which the information of the best neighbor of each particle and the best particle of the entire population in the current iteration is considered. Meanwhile, to avoid premature, an abandoned mechanism is used. Furthermore, for improving the global convergence speed of our algorithm, a chaotic search is adopted in the best solution of the current iteration. To verify the performance of our algorithm, standard test functions have been employed. The experimental results show that the algorithm is much more robust and efficient than some existing Particle Swarm Optimization algorithms. PMID:26955387

Global-local visual biases correspond with visual-spatial orientation.

PubMed

Basso, Michael R; Lowery, Natasha

2004-02-01

Within the past decade, numerous investigations have demonstrated reliable associations of global-local visual processing biases with right and left hemisphere function, respectively (cf. Van Kleeck, 1989). Yet the relevance of these biases to other cognitive functions is not well understood. Towards this end, the present research examined the relationship between global-local visual biases and perception of visual-spatial orientation. Twenty-six women and 23 men completed a global-local judgment task (Kimchi and Palmer, 1982) and the Judgment of Line Orientation Test (JLO; Benton, Sivan, Hamsher, Varney, and Spreen, 1994), a measure of visual-spatial orientation. As expected, men had better performance on JLO. Extending previous findings, global biases were related to better visual-spatial acuity on JLO. The findings suggest that global-local biases and visual-spatial orientation may share underlying cerebral mechanisms. Implications of these findings for other visually mediated cognitive outcomes are discussed.

Research on particle swarm optimization algorithm based on optimal movement probability

NASA Astrophysics Data System (ADS)

Ma, Jianhong; Zhang, Han; He, Baofeng

2017-01-01

The particle swarm optimization algorithm to improve the control precision, and has great application value training neural network and fuzzy system control fields etc.The traditional particle swarm algorithm is used for the training of feed forward neural networks,the search efficiency is low, and easy to fall into local convergence.An improved particle swarm optimization algorithm is proposed based on error back propagation gradient descent. Particle swarm optimization for Solving Least Squares Problems to meme group, the particles in the fitness ranking, optimization problem of the overall consideration, the error back propagation gradient descent training BP neural network, particle to update the velocity and position according to their individual optimal and global optimization, make the particles more to the social optimal learning and less to its optimal learning, it can avoid the particles fall into local optimum, by using gradient information can accelerate the PSO local search ability, improve the multi beam particle swarm depth zero less trajectory information search efficiency, the realization of improved particle swarm optimization algorithm. Simulation results show that the algorithm in the initial stage of rapid convergence to the global optimal solution can be near to the global optimal solution and keep close to the trend, the algorithm has faster convergence speed and search performance in the same running time, it can improve the convergence speed of the algorithm, especially the later search efficiency.

Electronic neural networks for global optimization

NASA Technical Reports Server (NTRS)

Thakoor, A. P.; Moopenn, A. W.; Eberhardt, S.

1990-01-01

An electronic neural network with feedback architecture, implemented in analog custom VLSI is described. Its application to problems of global optimization for dynamic assignment is discussed. The convergence properties of the neural network hardware are compared with computer simulation results. The neural network's ability to provide optimal or near optimal solutions within only a few neuron time constants, a speed enhancement of several orders of magnitude over conventional search methods, is demonstrated. The effect of noise on the circuit dynamics and the convergence behavior of the neural network hardware is also examined.

Construction of nested maximin designs based on successive local enumeration and modified novel global harmony search algorithm

NASA Astrophysics Data System (ADS)

Yi, Jin; Li, Xinyu; Xiao, Mi; Xu, Junnan; Zhang, Lin

2017-01-01

Engineering design often involves different types of simulation, which results in expensive computational costs. Variable fidelity approximation-based design optimization approaches can realize effective simulation and efficiency optimization of the design space using approximation models with different levels of fidelity and have been widely used in different fields. As the foundations of variable fidelity approximation models, the selection of sample points of variable-fidelity approximation, called nested designs, is essential. In this article a novel nested maximin Latin hypercube design is constructed based on successive local enumeration and a modified novel global harmony search algorithm. In the proposed nested designs, successive local enumeration is employed to select sample points for a low-fidelity model, whereas the modified novel global harmony search algorithm is employed to select sample points for a high-fidelity model. A comparative study with multiple criteria and an engineering application are employed to verify the efficiency of the proposed nested designs approach.

A Particle Swarm Optimization-Based Approach with Local Search for Predicting Protein Folding.

PubMed

Yang, Cheng-Hong; Lin, Yu-Shiun; Chuang, Li-Yeh; Chang, Hsueh-Wei

2017-10-01

The hydrophobic-polar (HP) model is commonly used for predicting protein folding structures and hydrophobic interactions. This study developed a particle swarm optimization (PSO)-based algorithm combined with local search algorithms; specifically, the high exploration PSO (HEPSO) algorithm (which can execute global search processes) was combined with three local search algorithms (hill-climbing algorithm, greedy algorithm, and Tabu table), yielding the proposed HE-L-PSO algorithm. By using 20 known protein structures, we evaluated the performance of the HE-L-PSO algorithm in predicting protein folding in the HP model. The proposed HE-L-PSO algorithm exhibited favorable performance in predicting both short and long amino acid sequences with high reproducibility and stability, compared with seven reported algorithms. The HE-L-PSO algorithm yielded optimal solutions for all predicted protein folding structures. All HE-L-PSO-predicted protein folding structures possessed a hydrophobic core that is similar to normal protein folding.

A new local-global approach for classification.

PubMed

Peres, R T; Pedreira, C E

2010-09-01

In this paper, we propose a new local-global pattern classification scheme that combines supervised and unsupervised approaches, taking advantage of both, local and global environments. We understand as global methods the ones concerned with the aim of constructing a model for the whole problem space using the totality of the available observations. Local methods focus into sub regions of the space, possibly using an appropriately selected subset of the sample. In the proposed method, the sample is first divided in local cells by using a Vector Quantization unsupervised algorithm, the LBG (Linde-Buzo-Gray). In a second stage, the generated assemblage of much easier problems is locally solved with a scheme inspired by Bayes' rule. Four classification methods were implemented for comparison purposes with the proposed scheme: Learning Vector Quantization (LVQ); Feedforward Neural Networks; Support Vector Machine (SVM) and k-Nearest Neighbors. These four methods and the proposed scheme were implemented in eleven datasets, two controlled experiments, plus nine public available datasets from the UCI repository. The proposed method has shown a quite competitive performance when compared to these classical and largely used classifiers. Our method is simple concerning understanding and implementation and is based on very intuitive concepts. Copyright 2010 Elsevier Ltd. All rights reserved.

Tensor voting for image correction by global and local intensity alignment.

PubMed

Jia, Jiaya; Tang, Chi-Keung

2005-01-01

This paper presents a voting method to perform image correction by global and local intensity alignment. The key to our modeless approach is the estimation of global and local replacement functions by reducing the complex estimation problem to the robust 2D tensor voting in the corresponding voting spaces. No complicated model for replacement function (curve) is assumed. Subject to the monotonic constraint only, we vote for an optimal replacement function by propagating the curve smoothness constraint using a dense tensor field. Our method effectively infers missing curve segments and rejects image outliers. Applications using our tensor voting approach are proposed and described. The first application consists of image mosaicking of static scenes, where the voted replacement functions are used in our iterative registration algorithm for computing the best warping matrix. In the presence of occlusion, our replacement function can be employed to construct a visually acceptable mosaic by detecting occlusion which has large and piecewise constant color. Furthermore, by the simultaneous consideration of color matches and spatial constraints in the voting space, we perform image intensity compensation and high contrast image correction using our voting framework, when only two defective input images are given.

Optimizing human activity patterns using global sensitivity analysis

DOE PAGES

Fairchild, Geoffrey; Hickmann, Kyle S.; Mniszewski, Susan M.; ...

2013-12-10

Implementing realistic activity patterns for a population is crucial for modeling, for example, disease spread, supply and demand, and disaster response. Using the dynamic activity simulation engine, DASim, we generate schedules for a population that capture regular (e.g., working, eating, and sleeping) and irregular activities (e.g., shopping or going to the doctor). We use the sample entropy (SampEn) statistic to quantify a schedule’s regularity for a population. We show how to tune an activity’s regularity by adjusting SampEn, thereby making it possible to realistically design activities when creating a schedule. The tuning process sets up a computationally intractable high-dimensional optimizationmore » problem. To reduce the computational demand, we use Bayesian Gaussian process regression to compute global sensitivity indices and identify the parameters that have the greatest effect on the variance of SampEn. Here we use the harmony search (HS) global optimization algorithm to locate global optima. Our results show that HS combined with global sensitivity analysis can efficiently tune the SampEn statistic with few search iterations. We demonstrate how global sensitivity analysis can guide statistical emulation and global optimization algorithms to efficiently tune activities and generate realistic activity patterns. Finally, though our tuning methods are applied to dynamic activity schedule generation, they are general and represent a significant step in the direction of automated tuning and optimization of high-dimensional computer simulations.« less

Decoupling global biases and local interactions between cell biological variables

PubMed Central

Zaritsky, Assaf; Obolski, Uri; Gan, Zhuo; Reis, Carlos R; Kadlecova, Zuzana; Du, Yi; Schmid, Sandra L; Danuser, Gaudenz

2017-01-01

Analysis of coupled variables is a core concept of cell biological inference, with co-localization of two molecules as a proxy for protein interaction being a ubiquitous example. However, external effectors may influence the observed co-localization independently from the local interaction of two proteins. Such global bias, although biologically meaningful, is often neglected when interpreting co-localization. Here, we describe DeBias, a computational method to quantify and decouple global bias from local interactions between variables by modeling the observed co-localization as the cumulative contribution of a global and a local component. We showcase four applications of DeBias in different areas of cell biology, and demonstrate that the global bias encapsulates fundamental mechanistic insight into cellular behavior. The DeBias software package is freely accessible online via a web-server at https://debias.biohpc.swmed.edu. DOI: http://dx.doi.org/10.7554/eLife.22323.001 PMID:28287393

Gender differences in global-local perception? Evidence from orientation and shape judgments.

PubMed

Kimchi, Ruth; Amishav, Rama; Sulitzeanu-Kenan, Anat

2009-01-01

Direct examinations of gender differences in global-local processing are sparse, and the results are inconsistent. We examined this issue with a visuospatial judgment task and with a shape judgment task. Women and men were presented with hierarchical stimuli that varied in closure (open or closed shape) or in line orientation (oblique or horizontal/vertical) at the global or local level. The task was to classify the stimuli on the basis of the variation at the global level (global classification) or at the local level (local classification). Women's classification by closure (global or local) was more accurate than men's for stimuli that varied in closure on both levels, suggesting a female advantage in discriminating shape properties. No gender differences were observed in global-local processing bias. Women and men exhibited a global advantage, and they did not differ in their speed of global or local classification, with only one exception. Women were slower than men in local classification by orientation when the to-be-classified lines were embedded in a global line with a different orientation. This finding suggests that women are more distracted than men by misleading global oriented context when performing local orientation judgments, perhaps because women and men differ in their ability to use cognitive schemes to compensate for the distracting effects of the global context. Our findings further suggest that whether or not gender differences arise depends not only on the nature of the visual task but also on the visual context.

Global/local stress analysis of composite structures. M.S. Thesis

NASA Technical Reports Server (NTRS)

Ransom, Jonathan B.

1989-01-01

A method for performing a global/local stress analysis is described and its capabilities are demonstrated. The method employs spline interpolation functions which satisfy the linear plate bending equation to determine displacements and rotations from a global model which are used as boundary conditions for the local model. Then, the local model is analyzed independent of the global model of the structure. This approach can be used to determine local, detailed stress states for specific structural regions using independent, refined local models which exploit information from less-refined global models. The method presented is not restricted to having a priori knowledge of the location of the regions requiring local detailed stress analysis. This approach also reduces the computational effort necessary to obtain the detailed stress state. Criteria for applying the method are developed. The effectiveness of the method is demonstrated using a classical stress concentration problem and a graphite-epoxy blade-stiffened panel with a discontinuous stiffener.

Rapid communication: Global-local processing affects recognition of distractor emotional faces.

PubMed

Srinivasan, Narayanan; Gupta, Rashmi

2011-03-01

Recent studies have shown links between happy faces and global, distributed attention as well as sad faces to local, focused attention. Emotions have been shown to affect global-local processing. Given that studies on emotion-cognition interactions have not explored the effect of perceptual processing at different spatial scales on processing stimuli with emotional content, the present study investigated the link between perceptual focus and emotional processing. The study investigated the effects of global-local processing on the recognition of distractor faces with emotional expressions. Participants performed a digit discrimination task with digits at either the global level or the local level presented against a distractor face (happy or sad) as background. The results showed that global processing associated with broad scope of attention facilitates recognition of happy faces, and local processing associated with narrow scope of attention facilitates recognition of sad faces. The novel results of the study provide conclusive evidence for emotion-cognition interactions by demonstrating the effect of perceptual processing on emotional faces. The results along with earlier complementary results on the effect of emotion on global-local processing support a reciprocal relationship between emotional processing and global-local processing. Distractor processing with emotional information also has implications for theories of selective attention.

Effects of global and local contexts on chord processing: An ERP study.

PubMed

Zhang, Jingjing; Zhou, Xuefeng; Chang, Ruohan; Yang, Yufang

2018-01-31

In real life, the processing of an incoming event is continuously influenced by prior information at multiple timescales. The present study investigated how harmonic contexts at both local and global levels influence the processing of an incoming chord in an event-related potentials experiment. Chord sequences containing two phrases were presented to musically trained listeners, with the last critical chord either harmonically related or less related to its preceding context at local and/or global levels. ERPs data showed an ERAN-like effect for local context in early time window and a N5-like component for later interaction between the local context and global context. These results suggest that both the local and global contexts influence the processing of an incoming music event, and the local effect happens earlier than the global. Moreover, the interaction between the local context and global context in N5 may suggest that music syntactic integration at local level takes place prior to the integration at global level. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Globally Optimal Particle Tracking Technique for Stereo Imaging Velocimetry Experiments

NASA Technical Reports Server (NTRS)

McDowell, Mark

2008-01-01

An important phase of any Stereo Imaging Velocimetry experiment is particle tracking. Particle tracking seeks to identify and characterize the motion of individual particles entrained in a fluid or air experiment. We analyze a cylindrical chamber filled with water and seeded with density-matched particles. In every four-frame sequence, we identify a particle track by assigning a unique track label for each camera image. The conventional approach to particle tracking is to use an exhaustive tree-search method utilizing greedy algorithms to reduce search times. However, these types of algorithms are not optimal due to a cascade effect of incorrect decisions upon adjacent tracks. We examine the use of a guided evolutionary neural net with simulated annealing to arrive at a globally optimal assignment of tracks. The net is guided both by the minimization of the search space through the use of prior limiting assumptions about valid tracks and by a strategy which seeks to avoid high-energy intermediate states which can trap the net in a local minimum. A stochastic search algorithm is used in place of back-propagation of error to further reduce the chance of being trapped in an energy well. Global optimization is achieved by minimizing an objective function, which includes both track smoothness and particle-image utilization parameters. In this paper we describe our model and present our experimental results. We compare our results with a nonoptimizing, predictive tracker and obtain an average increase in valid track yield of 27 percent

Discourse Communities--Local and Global.

ERIC Educational Resources Information Center

Killingsworth, M. Jimmie

1992-01-01

Argues that rhetorical theory needs to keep alive competing concepts of discourse communities, so that alternatives exist in the description and analysis of discourse practices. Proposes distinguishing between two kinds of discourse communities--the local and the global--so that rhetorical analysis can achieve the necessary critical edge,…

Local communities obstruct global consensus: Naming game on multi-local-world networks

NASA Astrophysics Data System (ADS)

Lou, Yang; Chen, Guanrong; Fan, Zhengping; Xiang, Luna

2018-02-01

Community structure is essential for social communications, where individuals belonging to the same community are much more actively interacting and communicating with each other than those in different communities within the human society. Naming game, on the other hand, is a social communication model that simulates the process of learning a name of an object within a community of humans, where the individuals can generally reach global consensus asymptotically through iterative pair-wise conversations. The underlying network indicates the relationships among the individuals. In this paper, three typical topologies, namely random-graph, small-world and scale-free networks, are employed, which are embedded with the multi-local-world community structure, to study the naming game. Simulations show that (1) the convergence process to global consensus is getting slower as the community structure becomes more prominent, and eventually might fail; (2) if the inter-community connections are sufficiently dense, neither the number nor the size of the communities affects the convergence process; and (3) for different topologies with the same (or similar) average node-degree, local clustering of individuals obstruct or prohibit global consensus to take place. The results reveal the role of local communities in a global naming game in social network studies.

Strategies for global optimization in photonics design.

PubMed

Vukovic, Ana; Sewell, Phillip; Benson, Trevor M

2010-10-01

This paper reports on two important issues that arise in the context of the global optimization of photonic components where large problem spaces must be investigated. The first is the implementation of a fast simulation method and associated matrix solver for assessing particular designs and the second, the strategies that a designer can adopt to control the size of the problem design space to reduce runtimes without compromising the convergence of the global optimization tool. For this study an analytical simulation method based on Mie scattering and a fast matrix solver exploiting the fast multipole method are combined with genetic algorithms (GAs). The impact of the approximations of the simulation method on the accuracy and runtime of individual design assessments and the consequent effects on the GA are also examined. An investigation of optimization strategies for controlling the design space size is conducted on two illustrative examples, namely, 60° and 90° waveguide bends based on photonic microstructures, and their effectiveness is analyzed in terms of a GA's ability to converge to the best solution within an acceptable timeframe. Finally, the paper describes some particular optimized solutions found in the course of this work.

The effect of sadness on global-local processing.

PubMed

von Mühlenen, Adrian; Bellaera, Lauren; Singh, Amrendra; Srinivasan, Narayanan

2018-05-04

Gable and Harmon-Jones (Psychological Science, 21(2), 211-215, 2010) reported that sadness broadens attention in a global-local letter task. This finding provided the key test for their motivational intensity account, which states that the level of spatial processing is not determined by emotional valence, but by motivational intensity. However, their finding is at odds with several other studies, showing no effect, or even a narrowing effect of sadness on attention. This paper reports two attempts to replicate the broadening effect of sadness on attention. Both experiments used a global-local letter task, but differed in terms of emotion induction: Experiment 1 used the same pictures as Gable and Harmon-Jones, taken from the IAPS dataset; Experiment 2 used a sad video underlaid with sad music. Results showed a sadness-specific global advantage in the error rates, but not in the reaction times. The same null results were also found in a South-Asian sample in both experiments, showing that effects on global/local processing were not influenced by a culturally related processing bias.

Thinking/acting locally/globally: Western science and environmental education in a global knowledge economy

NASA Astrophysics Data System (ADS)

Gough, Noel

2002-11-01

This paper critically appraises a number of approaches to 'thinking globally' in environmental education, with particular reference to popular assumptions about the universal applicability of Western science. Although the transnational character of many environmental issues demands that we 'think globally', I argue that the contribution of Western science to understanding and resolving environmental problems might be enhanced by seeing it as one among many local knowledge traditions. The production of a 'global knowledge economy' in/for environmental education can then be understood as creating transnational 'spaces' in which local knowledge traditions can be performed together, rather than as creating a 'common market' in which representations of local knowledge must be translated into (or exchanged for) the terms of a universal discourse.

An Improved Teaching-Learning-Based Optimization with the Social Character of PSO for Global Optimization.

PubMed

Zou, Feng; Chen, Debao; Wang, Jiangtao

2016-01-01

An improved teaching-learning-based optimization with combining of the social character of PSO (TLBO-PSO), which is considering the teacher's behavior influence on the students and the mean grade of the class, is proposed in the paper to find the global solutions of function optimization problems. In this method, the teacher phase of TLBO is modified; the new position of the individual is determined by the old position, the mean position, and the best position of current generation. The method overcomes disadvantage that the evolution of the original TLBO might stop when the mean position of students equals the position of the teacher. To decrease the computation cost of the algorithm, the process of removing the duplicate individual in original TLBO is not adopted in the improved algorithm. Moreover, the probability of local convergence of the improved method is decreased by the mutation operator. The effectiveness of the proposed method is tested on some benchmark functions, and the results are competitive with respect to some other methods.

Think Globally and Act Locally.

ERIC Educational Resources Information Center

Alger, Chadwick F.

1985-01-01

Suggests ways teachers can involve themselves and their students in local action as a means of furthering effective and practical global education. Considers possible barriers related to the ideology of the state system, and current breakthroughs, e.g., the nuclear freeze movement, anti-apartheid activism, and the sanctuary movement for Salvadoran…

Engineering Amorphous Systems, Using Global-to-Local Compilation

NASA Astrophysics Data System (ADS)

Nagpal, Radhika

Emerging technologies are making it possible to assemble systems that incorporate myriad of information-processing units at almost no cost: smart materials, selfassembling structures, vast sensor networks, pervasive computing. How does one engineer robust and prespecified global behavior from the local interactions of immense numbers of unreliable parts? We discuss organizing principles and programming methodologies that have emerged from Amorphous Computing research, that allow us to compile a specification of global behavior into a robust program for local behavior.

Global trends of local ecological knowledge and future implications

PubMed Central

Lemahieu, Anne; Sauer, Warwick H. H.

2018-01-01

Local and indigenous knowledge is being transformed globally, particularly being eroded when pertaining to ecology. In many parts of the world, rural and indigenous communities are facing tremendous cultural, economic and environmental changes, which contribute to weaken their local knowledge base. In the face of profound and ongoing environmental changes, both cultural and biological diversity are likely to be severely impacted as well as local resilience capacities from this loss. In this global literature review, we analyse the drivers of various types of local and indigenous ecological knowledge transformation and assess the directionality of the reported change. Results of this analysis show a global impoverishment of local and indigenous knowledge with 77% of papers reporting the loss of knowledge driven by globalization, modernization, and market integration. The recording of this loss, however, is not symmetrical, with losses being recorded more strongly in medicinal and ethnobotanical knowledge. Persistence of knowledge (15% of the studies) occurred in studies where traditional practices were being maintained consiously and where hybrid knowledge was being produced as a resut of certain types of incentives created by economic development. This review provides some insights into local and indigenous ecological knowledge change, its causes and implications, and recommends venues for the development of replicable and comparative research. The larger implication of these results is that because of the interconnection between cultural and biological diversity, the loss of local and indigenous knowledge is likely to critically threaten effective conservation of biodiversity, particularly in community-based conservation local efforts. PMID:29621311

Local and global evaluation for remote sensing image segmentation

NASA Astrophysics Data System (ADS)

Su, Tengfei; Zhang, Shengwei

2017-08-01

In object-based image analysis, how to produce accurate segmentation is usually a very important issue that needs to be solved before image classification or target recognition. The study for segmentation evaluation method is key to solving this issue. Almost all of the existent evaluation strategies only focus on the global performance assessment. However, these methods are ineffective for the situation that two segmentation results with very similar overall performance have very different local error distributions. To overcome this problem, this paper presents an approach that can both locally and globally quantify segmentation incorrectness. In doing so, region-overlapping metrics are utilized to quantify each reference geo-object's over and under-segmentation error. These quantified error values are used to produce segmentation error maps which have effective illustrative power to delineate local segmentation error patterns. The error values for all of the reference geo-objects are aggregated through using area-weighted summation, so that global indicators can be derived. An experiment using two scenes of very different high resolution images showed that the global evaluation part of the proposed approach was almost as effective as other two global evaluation methods, and the local part was a useful complement to comparing different segmentation results.

Mechanical Failure Mode of Metal Nanowires: Global Deformation versus Local Deformation

PubMed Central

Ho, Duc Tam; Im, Youngtae; Kwon, Soon-Yong; Earmme, Youn Young; Kim, Sung Youb

2015-01-01

It is believed that the failure mode of metal nanowires under tensile loading is the result of the nucleation and propagation of dislocations. Such failure modes can be slip, partial slip or twinning and therefore they are regarded as local deformation. Here we provide numerical and theoretical evidences to show that global deformation is another predominant failure mode of nanowires under tensile loading. At the global deformation mode, nanowires fail with a large contraction along a lateral direction and a large expansion along the other lateral direction. In addition, there is a competition between global and local deformations. Nanowires loaded at low temperature exhibit global failure mode first and then local deformation follows later. We show that the global deformation originates from the intrinsic instability of the nanowires and that temperature is a main parameter that decides the global or local deformation as the failure mode of nanowires. PMID:26087445

Global/local methods research using a common structural analysis framework

NASA Technical Reports Server (NTRS)

Knight, Norman F., Jr.; Ransom, Jonathan B.; Griffin, O. H., Jr.; Thompson, Danniella M.

1991-01-01

Methodologies for global/local stress analysis are described including both two- and three-dimensional analysis methods. These methods are being developed within a common structural analysis framework. Representative structural analysis problems are presented to demonstrate the global/local methodologies being developed.

Optimizing global liver function in radiation therapy treatment planning

NASA Astrophysics Data System (ADS)

Wu, Victor W.; Epelman, Marina A.; Wang, Hesheng; Romeijn, H. Edwin; Feng, Mary; Cao, Yue; Ten Haken, Randall K.; Matuszak, Martha M.

2016-09-01

Liver stereotactic body radiation therapy (SBRT) patients differ in both pre-treatment liver function (e.g. due to degree of cirrhosis and/or prior treatment) and radiosensitivity, leading to high variability in potential liver toxicity with similar doses. This work investigates three treatment planning optimization models that minimize risk of toxicity: two consider both voxel-based pre-treatment liver function and local-function-based radiosensitivity with dose; one considers only dose. Each model optimizes different objective functions (varying in complexity of capturing the influence of dose on liver function) subject to the same dose constraints and are tested on 2D synthesized and 3D clinical cases. The normal-liver-based objective functions are the linearized equivalent uniform dose (\\ell \\text{EUD} ) (conventional ‘\\ell \\text{EUD} model’), the so-called perfusion-weighted \\ell \\text{EUD} (\\text{fEUD} ) (proposed ‘fEUD model’), and post-treatment global liver function (GLF) (proposed ‘GLF model’), predicted by a new liver-perfusion-based dose-response model. The resulting \\ell \\text{EUD} , fEUD, and GLF plans delivering the same target \\ell \\text{EUD} are compared with respect to their post-treatment function and various dose-based metrics. Voxel-based portal venous liver perfusion, used as a measure of local function, is computed using DCE-MRI. In cases used in our experiments, the GLF plan preserves up to 4.6 % ≤ft(7.5 % \\right) more liver function than the fEUD (\\ell \\text{EUD} ) plan does in 2D cases, and up to 4.5 % ≤ft(5.6 % \\right) in 3D cases. The GLF and fEUD plans worsen in \\ell \\text{EUD} of functional liver on average by 1.0 Gy and 0.5 Gy in 2D and 3D cases, respectively. Liver perfusion information can be used during treatment planning to minimize the risk of toxicity by improving expected GLF; the degree of benefit varies with perfusion pattern. Although fEUD model optimization is computationally inexpensive and

From local perception to global perspective

NASA Astrophysics Data System (ADS)

Lehner, Flavio; Stocker, Thomas F.

2015-08-01

Recent sociological studies show that over short time periods the large day-to-day, month-to-month or year-to-year variations in weather at a specific location can influence and potentially bias our perception of climate change, a more long-term and global phenomenon. By weighting local temperature anomalies with the number of people that experience them and considering longer time periods, we illustrate that the share of the world population exposed to warmer-than-normal temperatures has steadily increased during the past few decades. Therefore, warming is experienced by an increasing number of individuals, counter to what might be simply inferred from global mean temperature anomalies. This behaviour is well-captured by current climate models, offering an opportunity to increase confidence in future projections of climate change irrespective of the personal local perception of weather.

Markovian master equations for quantum thermal machines: local versus global approach

NASA Astrophysics Data System (ADS)

Hofer, Patrick P.; Perarnau-Llobet, Martí; Miranda, L. David M.; Haack, Géraldine; Silva, Ralph; Bohr Brask, Jonatan; Brunner, Nicolas

2017-12-01

The study of quantum thermal machines, and more generally of open quantum systems, often relies on master equations. Two approaches are mainly followed. On the one hand, there is the widely used, but often criticized, local approach, where machine sub-systems locally couple to thermal baths. On the other hand, in the more established global approach, thermal baths couple to global degrees of freedom of the machine. There has been debate as to which of these two conceptually different approaches should be used in situations out of thermal equilibrium. Here we compare the local and global approaches against an exact solution for a particular class of thermal machines. We consider thermodynamically relevant observables, such as heat currents, as well as the quantum state of the machine. Our results show that the use of a local master equation is generally well justified. In particular, for weak inter-system coupling, the local approach agrees with the exact solution, whereas the global approach fails for non-equilibrium situations. For intermediate coupling, the local and the global approach both agree with the exact solution and for strong coupling, the global approach is preferable. These results are backed by detailed derivations of the regimes of validity for the respective approaches.

Porous biodegradable lumbar interbody fusion cage design and fabrication using integrated global-local topology optimization with laser sintering.

PubMed

Kang, Heesuk; Hollister, Scott J; La Marca, Frank; Park, Paul; Lin, Chia-Ying

2013-10-01

Biodegradable cages have received increasing attention for their use in spinal procedures involving interbody fusion to resolve complications associated with the use of nondegradable cages, such as stress shielding and long-term foreign body reaction. However, the relatively weak initial material strength compared to permanent materials and subsequent reduction due to degradation may be problematic. To design a porous biodegradable interbody fusion cage for a preclinical large animal study that can withstand physiological loads while possessing sufficient interconnected porosity for bony bridging and fusion, we developed a multiscale topology optimization technique. Topology optimization at the macroscopic scale provides optimal structural layout that ensures mechanical strength, while optimally designed microstructures, which replace the macroscopic material layout, ensure maximum permeability. Optimally designed cages were fabricated using solid, freeform fabrication of poly(ε-caprolactone) mixed with hydroxyapatite. Compression tests revealed that the yield strength of optimized fusion cages was two times that of typical human lumbar spine loads. Computational analysis further confirmed the mechanical integrity within the human lumbar spine, although the pore structure locally underwent higher stress than yield stress. This optimization technique may be utilized to balance the complex requirements of load-bearing, stress shielding, and interconnected porosity when using biodegradable materials for fusion cages.

ABCluster: the artificial bee colony algorithm for cluster global optimization.

PubMed

Zhang, Jun; Dolg, Michael

2015-10-07

Global optimization of cluster geometries is of fundamental importance in chemistry and an interesting problem in applied mathematics. In this work, we introduce a relatively new swarm intelligence algorithm, i.e. the artificial bee colony (ABC) algorithm proposed in 2005, to this field. It is inspired by the foraging behavior of a bee colony, and only three parameters are needed to control it. We applied it to several potential functions of quite different nature, i.e., the Coulomb-Born-Mayer, Lennard-Jones, Morse, Z and Gupta potentials. The benchmarks reveal that for long-ranged potentials the ABC algorithm is very efficient in locating the global minimum, while for short-ranged ones it is sometimes trapped into a local minimum funnel on a potential energy surface of large clusters. We have released an efficient, user-friendly, and free program "ABCluster" to realize the ABC algorithm. It is a black-box program for non-experts as well as experts and might become a useful tool for chemists to study clusters.

Global and local pitch perception in children with developmental dyslexia.

PubMed

Ziegler, Johannes C; Pech-Georgel, Catherine; George, Florence; Foxton, Jessica M

2012-03-01

This study investigated global versus local pitch pattern perception in children with dyslexia aged between 8 and 11 years. Children listened to two consecutive 4-tone pitch sequences while performing a same/different task. On the different trials, sequences either preserved the contour (local condition) or they violated the contour (global condition). Compared to normally developing children, dyslexics showed robust pitch perception deficits in the local but not the global condition. This finding was replicated in a simple pitch direction task, which minimizes sequencing and short term memory. Results are consistent with a left-hemisphere deficit in dyslexia because local pitch changes are supposedly processed by the left hemisphere, whereas global pitch changes are processed by the right hemisphere. The present data suggest a link between impaired pitch processing and abnormal phonological development in children with dyslexia, which makes pitch pattern processing a potent tool for early diagnosis and remediation of dyslexia. Copyright © 2011 Elsevier Inc. All rights reserved.

Development and verification of global/local analysis techniques for laminated composites

NASA Technical Reports Server (NTRS)

Thompson, Danniella Muheim; Griffin, O. Hayden, Jr.

1991-01-01

A two-dimensional to three-dimensional global/local finite element approach was developed, verified, and applied to a laminated composite plate of finite width and length containing a central circular hole. The resulting stress fields for axial compression loads were examined for several symmetric stacking sequences and hole sizes. Verification was based on comparison of the displacements and the stress fields with those accepted trends from previous free edge investigations and a complete three-dimensional finite element solution of the plate. The laminates in the compression study included symmetric cross-ply, angle-ply and quasi-isotropic stacking sequences. The entire plate was selected as the global model and analyzed with two-dimensional finite elements. Displacements along a region identified as the global/local interface were applied in a kinematically consistent fashion to independent three-dimensional local models. Local areas of interest in the plate included a portion of the straight free edge near the hole, and the immediate area around the hole. Interlaminar stress results obtained from the global/local analyses compares well with previously reported trends, and some new conclusions about interlaminar stress fields in plates with different laminate orientations and hole sizes are presented for compressive loading. The effectiveness of the global/local procedure in reducing the computational effort required to solve these problems is clearly demonstrated through examination of the computer time required to formulate and solve the linear, static system of equations which result for the global and local analyses to those required for a complete three-dimensional formulation for a cross-ply laminate. Specific processors used during the analyses are described in general terms. The application of this global/local technique is not limited software system, and was developed and described in as general a manner as possible.

Stability of mechanical joints in launching vehicles: Local and global stationary values of energy density

NASA Astrophysics Data System (ADS)

Chue, Ching-Hwei

A method was developed for predicting the behavior of mechanical joints in launch vehicles with particular emphasis placed on how the combined effects of loading, geometry, and materials could be optimized in terms of structure instability and/or integrity. What was considered to be essential is the fluctuation of the volume energy density with time in the structure. The peaks and valleys of the volume energy density function will be associated with failure by fracture and/or yielding while the distance between their local and global stationary values govern the structure instability. The Solid Rocket Booster (SRB) of the space shuttle was analyzed under axisymmetric and non-axisymmetric loadings. A semi-analytical finite element program was developed for solving the case of non-axisymmetric loading. Following a dynamic stress analysis, contours of the volume energy density in the structure were obtained as a function of time. The magnitudes and locations of these stationary values were then calculated locally and globally and related to possible failure by fracture. In the case of axisymmetric flight, the local and global instability behavior do not change appreciably. Fluctuations in the energy density and the dynamic stability length parameter become appreciable when the non-axisymmetric loads are considered. The magnitude of the energy in the shell structure is sensitive to alterations in the gas pressure induced by the solid propellant.

A practical globalization of one-shot optimization for optimal design of tokamak divertors

NASA Astrophysics Data System (ADS)

Blommaert, Maarten; Dekeyser, Wouter; Baelmans, Martine; Gauger, Nicolas R.; Reiter, Detlev

2017-01-01

In past studies, nested optimization methods were successfully applied to design of the magnetic divertor configuration in nuclear fusion reactors. In this paper, so-called one-shot optimization methods are pursued. Due to convergence issues, a globalization strategy for the one-shot solver is sought. Whereas Griewank introduced a globalization strategy using a doubly augmented Lagrangian function that includes primal and adjoint residuals, its practical usability is limited by the necessity of second order derivatives and expensive line search iterations. In this paper, a practical alternative is offered that avoids these drawbacks by using a regular augmented Lagrangian merit function that penalizes only state residuals. Additionally, robust rank-two Hessian estimation is achieved by adaptation of Powell's damped BFGS update rule. The application of the novel one-shot approach to magnetic divertor design is considered in detail. For this purpose, the approach is adapted to be complementary with practical in parts adjoint sensitivities. Using the globalization strategy, stable convergence of the one-shot approach is achieved.

Global-local methodologies and their application to nonlinear analysis. [for structural postbuckling study

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.

1986-01-01

An assessment is made of the potential of different global-local analysis strategies for predicting the nonlinear and postbuckling responses of structures. Two postbuckling problems of composite panels are used as benchmarks and the application of different global-local methodologies to these benchmarks is outlined. The key elements of each of the global-local strategies are discussed and future research areas needed to realize the full potential of global-local methodologies are identified.

Exploring Local Approaches to Communicating Global Climate Change Information

NASA Astrophysics Data System (ADS)

Stevermer, A. J.

2002-12-01

Expected future climate changes are often presented as a global problem, requiring a global solution. Although this statement is accurate, communicating climate change science and prospective solutions must begin at local levels, each with its own subset of complexities to be addressed. Scientific evaluation of local changes can be complicated by large variability occurring over small spatial scales; this variability hinders efforts both to analyze past local changes and to project future ones. The situation is further encumbered by challenges associated with scientific literacy in the U.S., as well as by pressing economic difficulties. For people facing real-life financial and other uncertainties, a projected ``1.4 to 5.8 degrees Celsius'' rise in global temperature is likely to remain only an abstract concept. Despite this lack of concreteness, recent surveys have found that most U.S. residents believe current global warming science, and an even greater number view the prospect of increased warming as at least a ``somewhat serious'' problem. People will often be able to speak of long-term climate changes in their area, whether observed changes in the amount of snow cover in winter, or in the duration of extreme heat periods in summer. This work will explore the benefits and difficulties of communicating climate change from a local, rather than global, perspective, and seek out possible strategies for making less abstract, more concrete, and most importantly, more understandable information available to the public.

A global optimization perspective on molecular clusters.

PubMed

Marques, J M C; Pereira, F B; Llanio-Trujillo, J L; Abreu, P E; Albertí, M; Aguilar, A; Pirani, F; Bartolomei, M

2017-04-28

Although there is a long history behind the idea of chemical structure, this is a key concept that continues to challenge chemists. Chemical structure is fundamental to understanding most of the properties of matter and its knowledge for complex systems requires the use of state-of-the-art techniques, either experimental or theoretical. From the theoretical view point, one needs to establish the interaction potential among the atoms or molecules of the system, which contains all the information regarding the energy landscape, and employ optimization algorithms to discover the relevant stationary points. In particular, global optimization methods are of major importance to search for the low-energy structures of molecular aggregates. We review the application of global optimization techniques to several molecular clusters; some new results are also reported. Emphasis is given to evolutionary algorithms and their application in the study of the microsolvation of alkali-metal and Ca 2+ ions with various types of solvents.This article is part of the themed issue 'Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces'. © 2017 The Author(s).

A global optimization perspective on molecular clusters

PubMed Central

Pereira, F. B.; Llanio-Trujillo, J. L.; Abreu, P. E.; Albertí, M.; Aguilar, A.; Pirani, F.; Bartolomei, M.

2017-01-01

Although there is a long history behind the idea of chemical structure, this is a key concept that continues to challenge chemists. Chemical structure is fundamental to understanding most of the properties of matter and its knowledge for complex systems requires the use of state-of-the-art techniques, either experimental or theoretical. From the theoretical view point, one needs to establish the interaction potential among the atoms or molecules of the system, which contains all the information regarding the energy landscape, and employ optimization algorithms to discover the relevant stationary points. In particular, global optimization methods are of major importance to search for the low-energy structures of molecular aggregates. We review the application of global optimization techniques to several molecular clusters; some new results are also reported. Emphasis is given to evolutionary algorithms and their application in the study of the microsolvation of alkali-metal and Ca2+ ions with various types of solvents. This article is part of the themed issue ‘Theoretical and computational studies of non-equilibrium and non-statistical dynamics in the gas phase, in the condensed phase and at interfaces’. PMID:28320902

Atypical Local Interference Affects Global Processing in Children with Neurofibromatosis Type 1.

PubMed

Payne, Jonathan M; Porter, Melanie A; Bzishvili, Samantha; North, Kathryn N

2017-05-01

To examine hierarchical visuospatial processing in children with neurofibromatosis type 1 (NF1), a single gene disorder associated with visuospatial impairments, attention deficits, and executive dysfunction. We used a modified Navon paradigm consisting of a large "global" shape composed of smaller "local" shapes that were either congruent (same) or incongruent (different) to the global shape. Participants were instructed to name either the global or local shape within a block. Reaction times, interference ratios, and error rates of children with NF1 (n=30) and typically developing controls (n=24) were compared. Typically developing participants demonstrated the expected global processing bias evidenced by a vulnerability to global interference when naming local stimuli without a cost of congruence when naming global stimuli. NF1 participants, however, experienced significant interference from the unattended level when naming both local and global levels of the stimuli. Findings suggest that children with NF1 do not demonstrate the typical human bias of processing visual information from a global perspective. (JINS, 2017, 23, 446-450).

Geometrical optimization of a local ballistic magnetic sensor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kanda, Yuhsuke; Hara, Masahiro; Nomura, Tatsuya

2014-04-07

We have developed a highly sensitive local magnetic sensor by using a ballistic transport property in a two-dimensional conductor. A semiclassical simulation reveals that the sensitivity increases when the geometry of the sensor and the spatial distribution of the local field are optimized. We have also experimentally demonstrated a clear observation of a magnetization process in a permalloy dot whose size is much smaller than the size of an optimized ballistic magnetic sensor fabricated from a GaAs/AlGaAs two-dimensional electron gas.

Hierarchical ensemble of global and local classifiers for face recognition.

PubMed

Su, Yu; Shan, Shiguang; Chen, Xilin; Gao, Wen

2009-08-01

In the literature of psychophysics and neurophysiology, many studies have shown that both global and local features are crucial for face representation and recognition. This paper proposes a novel face recognition method which exploits both global and local discriminative features. In this method, global features are extracted from the whole face images by keeping the low-frequency coefficients of Fourier transform, which we believe encodes the holistic facial information, such as facial contour. For local feature extraction, Gabor wavelets are exploited considering their biological relevance. After that, Fisher's linear discriminant (FLD) is separately applied to the global Fourier features and each local patch of Gabor features. Thus, multiple FLD classifiers are obtained, each embodying different facial evidences for face recognition. Finally, all these classifiers are combined to form a hierarchical ensemble classifier. We evaluate the proposed method using two large-scale face databases: FERET and FRGC version 2.0. Experiments show that the results of our method are impressively better than the best known results with the same evaluation protocol.

Albinism, stigma, subjectivity and global-local discourses in Tanzania.

PubMed

Brocco, Giorgio

2016-12-01

Societal ideas and explanations of albinism at the local level in Tanzania are conceived in terms of family history, social relations, economic status, moral-religious positions, global-local flows of information and humanitarian actions on behalf of people with the congenital condition. This paper aims to show how the subjectivities of people with albinism in Tanzania are shaped and re-shaped through local moral conceptions as well as globalizing (bio)medical explanations of albinism. An exemplary case study of a 28-year-old woman, plus episodes from the lives of seven other informants with the condition, are analyzed in order to understand, on the one hand, local social relationships between people with albinism and other individuals in family and community settings, and on the other hand, the interconnections between persons with albinism and global humanitarian actors and the broadcast media. When stigma and marginalizing behaviors are perceived by individuals with albinism in Tanzania as impeding their social lives, they employ different coping strategies and discourses to enhance social acceptance.

Building Sustainable Local Capacity for Global Health Research in West Africa.

PubMed

Sam-Agudu, Nadia A; Paintsil, Elijah; Aliyu, Muktar H; Kwara, Awewura; Ogunsola, Folasade; Afrane, Yaw A; Onoka, Chima; Awandare, Gordon A; Amponsah, Gladys; Cornelius, Llewellyn J; Mendy, Gabou; Sturke, Rachel; Ghansah, Anita; Siberry, George K; Ezeanolue, Echezona E

Global health research in resource-limited countries has been largely sponsored and led by foreign institutions. Thus, these countries' training capacity and productivity in global health research is limited. Local participation at all levels of global health knowledge generation promotes equitable access to evidence-based solutions. Additionally, leadership inclusive of competent local professionals promotes best outcomes for local contextualization and implementation of successful global health solutions. Among the sub-Saharan African regions, West Africa in particular lags in research infrastructure, productivity, and impact in global health research. In this paper, experts discuss strategies for scaling up West Africa's participation in global health evidence generation using examples from Ghana and Nigeria. We conducted an online and professional network search to identify grants awarded for global health research and research education in Ghana and Nigeria. Principal investigators, global health educators, and representatives of funding institutions were invited to add their knowledge and expertise with regard to strengthening research capacity in West Africa. While there has been some progress in obtaining foreign funding, foreign institutions still dominate local research. Local research funding opportunities in the 2 countries were found to be insufficient, disjointed, poorly sustained, and inadequately publicized, indicating weak infrastructure. As a result, research training programs produce graduates who ultimately fail to launch independent investigator careers because of lack of mentoring and poor infrastructural support. Research funding and training opportunities in Ghana and Nigeria remain inadequate. We recommend systems-level changes in mentoring, collaboration, and funding to drive the global health research agenda in these countries. Additionally, research training programs should be evaluated not only by numbers of individuals graduated but

Mid-sagittal plane and mid-sagittal surface optimization in brain MRI using a local symmetry measure

NASA Astrophysics Data System (ADS)

Stegmann, Mikkel B.; Skoglund, Karl; Ryberg, Charlotte

2005-04-01

This paper describes methods for automatic localization of the mid-sagittal plane (MSP) and mid-sagittal surface (MSS). The data used is a subset of the Leukoaraiosis And DISability (LADIS) study consisting of three-dimensional magnetic resonance brain data from 62 elderly subjects (age 66 to 84 years). Traditionally, the mid-sagittal plane is localized by global measures. However, this approach fails when the partitioning plane between the brain hemispheres does not coincide with the symmetry plane of the head. We instead propose to use a sparse set of profiles in the plane normal direction and maximize the local symmetry around these using a general-purpose optimizer. The plane is parameterized by azimuth and elevation angles along with the distance to the origin in the normal direction. This approach leads to solutions confirmed as the optimal MSP in 98 percent of the subjects. Despite the name, the mid-sagittal plane is not always planar, but a curved surface resulting in poor partitioning of the brain hemispheres. To account for this, this paper also investigates an optimization strategy which fits a thin-plate spline surface to the brain data using a robust least median of squares estimator. Albeit computationally more expensive, mid-sagittal surface fitting demonstrated convincingly better partitioning of curved brains into cerebral hemispheres.

Localization/Globalization and the Midwife State: Strategic Dilemmas for State Feminism in Education?

ERIC Educational Resources Information Center

Blackmore, Jill

1999-01-01

Explores implications of the globalization/localization process for state feminism, focusing on Australia. Localization is one response to globalization, exemplified by devolution to self-managing schools. However, global/local relations have gendered effects that resonate cross-nationally. Problems will emerge as the state withdraws from its…

Synchronization of three electrochemical oscillators: From local to global coupling

NASA Astrophysics Data System (ADS)

Liu, Yifan; Sebek, Michael; Mori, Fumito; Kiss, István Z.

2018-04-01

We investigate the formation of synchronization patterns in an oscillatory nickel electrodissolution system in a network obtained by superimposing local and global coupling with three electrodes. We explored the behavior through numerical simulations using kinetic ordinary differential equations, Kuramoto type phase models, and experiments, in which the local to global coupling could be tuned by cross resistances between the three nickel wires. At intermediate coupling strength with predominant global coupling, two of the three oscillators, whose natural frequencies are closer, can synchronize. By adding even a relatively small amount of local coupling (about 9%-25%), a spatially organized partially synchronized state can occur where one of the two synchronized elements is in the center. A formula was derived for predicting the critical coupling strength at which full synchronization will occur independent of the permutation of the natural frequencies of the oscillators over the network. The formula correctly predicts the variation of the critical coupling strength as a function of the global coupling fraction, e.g., with local coupling the critical coupling strength is about twice than that required with global coupling. The results show the importance of the topology of the network on the synchronization properties in a simple three-oscillator setup and could provide guidelines for decrypting coupling topology from identification of synchronization patterns.

An ITK framework for deterministic global optimization for medical image registration

NASA Astrophysics Data System (ADS)

Dru, Florence; Wachowiak, Mark P.; Peters, Terry M.

2006-03-01

Similarity metric optimization is an essential step in intensity-based rigid and nonrigid medical image registration. For clinical applications, such as image guidance of minimally invasive procedures, registration accuracy and efficiency are prime considerations. In addition, clinical utility is enhanced when registration is integrated into image analysis and visualization frameworks, such as the popular Insight Toolkit (ITK). ITK is an open source software environment increasingly used to aid the development, testing, and integration of new imaging algorithms. In this paper, we present a new ITK-based implementation of the DIRECT (Dividing Rectangles) deterministic global optimization algorithm for medical image registration. Previously, it has been shown that DIRECT improves the capture range and accuracy for rigid registration. Our ITK class also contains enhancements over the original DIRECT algorithm by improving stopping criteria, adaptively adjusting a locality parameter, and by incorporating Powell's method for local refinement. 3D-3D registration experiments with ground-truth brain volumes and clinical cardiac volumes show that combining DIRECT with Powell's method improves registration accuracy over Powell's method used alone, is less sensitive to initial misorientation errors, and, with the new stopping criteria, facilitates adequate exploration of the search space without expending expensive iterations on non-improving function evaluations. Finally, in this framework, a new parallel implementation for computing mutual information is presented, resulting in near-linear speedup with two processors.

Social influence on selection behaviour: Distinguishing local- and global-driven preferential attachment.

PubMed

Pan, Xue; Hou, Lei; Liu, Kecheng

2017-01-01

Social influence drives human selection behaviours when numerous objects competing for limited attentions, which leads to the 'rich get richer' dynamics where popular objects tend to get more attentions. However, evidences have been found that, both the global information of the whole system and the local information among one's friends have significant influence over the one's selection. Consequently, a key question raises that, it is the local information or the global information more determinative for one's selection? Here we compare the local-based influence and global-based influence. We show that, the selection behaviour is mainly driven by the local popularity of the objects while the global popularity plays a supplementary role driving the behaviour only when there is little local information for the user to refer to. Thereby, we propose a network model to describe the mechanism of user-object interaction evolution with social influence, where the users perform either local-driven or global-driven preferential attachments to the objects, i.e., the probability of an objects to be selected by a target user is proportional to either its local popularity or global popularity. The simulation suggests that, about 75% of the attachments should be driven by the local popularity to reproduce the empirical observations. It means that, at least in the studied context where users chose businesses on Yelp, there is a probability of 75% for a user to make a selection according to the local popularity. The proposed model and the numerical findings may shed some light on the study of social influence and evolving social systems.

Strategies for Global Optimization of Temporal Preferences

NASA Technical Reports Server (NTRS)

Morris, Paul; Morris, Robert; Khatib, Lina; Ramakrishnan, Sailesh

2004-01-01

A temporal reasoning problem can often be naturally characterized as a collection of constraints with associated local preferences for times that make up the admissible values for those constraints. Globally preferred solutions to such problems emerge as a result of well-defined operations that compose and order temporal assignments. The overall objective of this work is a characterization of different notions of global preference, and to identify tractable sub-classes of temporal reasoning problems incorporating these notions. This paper extends previous results by refining the class of useful notions of global temporal preference that are associated with problems that admit of tractable solution techniques. This paper also answers the hitherto open question of whether problems that seek solutions that are globally preferred from a Utilitarian criterion for global preference can be found tractably.

Multiple-stage ambiguity in motion perception reveals global computation of local motion directions.

PubMed

Rider, Andrew T; Nishida, Shin'ya; Johnston, Alan

2016-12-01

The motion of a 1D image feature, such as a line, seen through a small aperture, or the small receptive field of a neural motion sensor, is underconstrained, and it is not possible to derive the true motion direction from a single local measurement. This is referred to as the aperture problem. How the visual system solves the aperture problem is a fundamental question in visual motion research. In the estimation of motion vectors through integration of ambiguous local motion measurements at different positions, conventional theories assume that the object motion is a rigid translation, with motion signals sharing a common motion vector within the spatial region over which the aperture problem is solved. However, this strategy fails for global rotation. Here we show that the human visual system can estimate global rotation directly through spatial pooling of locally ambiguous measurements, without an intervening step that computes local motion vectors. We designed a novel ambiguous global flow stimulus, which is globally as well as locally ambiguous. The global ambiguity implies that the stimulus is simultaneously consistent with both a global rigid translation and an infinite number of global rigid rotations. By the standard view, the motion should always be seen as a global translation, but it appears to shift from translation to rotation as observers shift fixation. This finding indicates that the visual system can estimate local vectors using a global rotation constraint, and suggests that local motion ambiguity may not be resolved until consistencies with multiple global motion patterns are assessed.

Computational Approaches to Simulation and Optimization of Global Aircraft Trajectories

NASA Technical Reports Server (NTRS)

Ng, Hok Kwan; Sridhar, Banavar

2016-01-01

This study examines three possible approaches to improving the speed in generating wind-optimal routes for air traffic at the national or global level. They are: (a) using the resources of a supercomputer, (b) running the computations on multiple commercially available computers and (c) implementing those same algorithms into NASAs Future ATM Concepts Evaluation Tool (FACET) and compares those to a standard implementation run on a single CPU. Wind-optimal aircraft trajectories are computed using global air traffic schedules. The run time and wait time on the supercomputer for trajectory optimization using various numbers of CPUs ranging from 80 to 10,240 units are compared with the total computational time for running the same computation on a single desktop computer and on multiple commercially available computers for potential computational enhancement through parallel processing on the computer clusters. This study also re-implements the trajectory optimization algorithm for further reduction of computational time through algorithm modifications and integrates that with FACET to facilitate the use of the new features which calculate time-optimal routes between worldwide airport pairs in a wind field for use with existing FACET applications. The implementations of trajectory optimization algorithms use MATLAB, Python, and Java programming languages. The performance evaluations are done by comparing their computational efficiencies and based on the potential application of optimized trajectories. The paper shows that in the absence of special privileges on a supercomputer, a cluster of commercially available computers provides a feasible approach for national and global air traffic system studies.

European Lung Foundation: from local to global.

PubMed

Powell, Pippa; Williams, Sîan; Smyth, Dan

2016-09-01

Although there are many patient organisations in Europe, this is not the case in all countries across the globe.Access to care is one of the main global issues highlighted by the European Lung Foundation International Patient Advisory Committee.The European Respiratory Society/European Lung Foundation Healthy Lungs for Life campaign can be used locally or globally to raise awareness of the risk factors for lung disease.Implementation science is a method that can be used to assess the feasibility of using research findings in routine healthcare in clinical settings in different parts of the world. To show how patient- and public-focussed initiatives and activities can be adapted and modified to be effective in local, national and international settings, and to provide specific examples of these from the European Lung Foundation.

Global Optimization Ensemble Model for Classification Methods

PubMed Central

Anwar, Hina; Qamar, Usman; Muzaffar Qureshi, Abdul Wahab

2014-01-01

Supervised learning is the process of data mining for deducing rules from training datasets. A broad array of supervised learning algorithms exists, every one of them with its own advantages and drawbacks. There are some basic issues that affect the accuracy of classifier while solving a supervised learning problem, like bias-variance tradeoff, dimensionality of input space, and noise in the input data space. All these problems affect the accuracy of classifier and are the reason that there is no global optimal method for classification. There is not any generalized improvement method that can increase the accuracy of any classifier while addressing all the problems stated above. This paper proposes a global optimization ensemble model for classification methods (GMC) that can improve the overall accuracy for supervised learning problems. The experimental results on various public datasets showed that the proposed model improved the accuracy of the classification models from 1% to 30% depending upon the algorithm complexity. PMID:24883382

Global optimization algorithm for heat exchanger networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quesada, I.; Grossmann, I.E.

This paper deals with the global optimization of heat exchanger networks with fixed topology. It is shown that if linear area cost functions are assumed, as well as arithmetic mean driving force temperature differences in networks with isothermal mixing, the corresponding nonlinear programming (NLP) optimization problem involves linear constraints and a sum of linear fractional functions in the objective which are nonconvex. A rigorous algorithm is proposed that is based on a convex NLP underestimator that involves linear and nonlinear estimators for fractional and bilinear terms which provide a tight lower bound to the global optimum. This NLP problem ismore » used within a spatial branch and bound method for which branching rules are given. Basic properties of the proposed method are presented, and its application is illustrated with several example problems. The results show that the proposed method only requires few nodes in the branch and bound search.« less

Identification of inelastic parameters based on deep drawing forming operations using a global-local hybrid Particle Swarm approach

NASA Astrophysics Data System (ADS)

Vaz, Miguel; Luersen, Marco A.; Muñoz-Rojas, Pablo A.; Trentin, Robson G.

2016-04-01

Application of optimization techniques to the identification of inelastic material parameters has substantially increased in recent years. The complex stress-strain paths and high nonlinearity, typical of this class of problems, require the development of robust and efficient techniques for inverse problems able to account for an irregular topography of the fitness surface. Within this framework, this work investigates the application of the gradient-based Sequential Quadratic Programming method, of the Nelder-Mead downhill simplex algorithm, of Particle Swarm Optimization (PSO), and of a global-local PSO-Nelder-Mead hybrid scheme to the identification of inelastic parameters based on a deep drawing operation. The hybrid technique has shown to be the best strategy by combining the good PSO performance to approach the global minimum basin of attraction with the efficiency demonstrated by the Nelder-Mead algorithm to obtain the minimum itself.

A practical globalization of one-shot optimization for optimal design of tokamak divertors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blommaert, Maarten, E-mail: maarten.blommaert@kuleuven.be; Dekeyser, Wouter; Baelmans, Martine

In past studies, nested optimization methods were successfully applied to design of the magnetic divertor configuration in nuclear fusion reactors. In this paper, so-called one-shot optimization methods are pursued. Due to convergence issues, a globalization strategy for the one-shot solver is sought. Whereas Griewank introduced a globalization strategy using a doubly augmented Lagrangian function that includes primal and adjoint residuals, its practical usability is limited by the necessity of second order derivatives and expensive line search iterations. In this paper, a practical alternative is offered that avoids these drawbacks by using a regular augmented Lagrangian merit function that penalizes onlymore » state residuals. Additionally, robust rank-two Hessian estimation is achieved by adaptation of Powell's damped BFGS update rule. The application of the novel one-shot approach to magnetic divertor design is considered in detail. For this purpose, the approach is adapted to be complementary with practical in parts adjoint sensitivities. Using the globalization strategy, stable convergence of the one-shot approach is achieved.« less

Local-global classifier fusion for screening chest radiographs

NASA Astrophysics Data System (ADS)

Ding, Meng; Antani, Sameer; Jaeger, Stefan; Xue, Zhiyun; Candemir, Sema; Kohli, Marc; Thoma, George

2017-03-01

Tuberculosis (TB) is a severe comorbidity of HIV and chest x-ray (CXR) analysis is a necessary step in screening for the infective disease. Automatic analysis of digital CXR images for detecting pulmonary abnormalities is critical for population screening, especially in medical resource constrained developing regions. In this article, we describe steps that improve previously reported performance of NLM's CXR screening algorithms and help advance the state of the art in the field. We propose a local-global classifier fusion method where two complementary classification systems are combined. The local classifier focuses on subtle and partial presentation of the disease leveraging information in radiology reports that roughly indicates locations of the abnormalities. In addition, the global classifier models the dominant spatial structure in the gestalt image using GIST descriptor for the semantic differentiation. Finally, the two complementary classifiers are combined using linear fusion, where the weight of each decision is calculated by the confidence probabilities from the two classifiers. We evaluated our method on three datasets in terms of the area under the Receiver Operating Characteristic (ROC) curve, sensitivity, specificity and accuracy. The evaluation demonstrates the superiority of our proposed local-global fusion method over any single classifier.

Local-global interference is modulated by age, sex and anterior corpus callosum size

PubMed Central

Müller-Oehring, Eva M.; Schulte, Tilman; Raassi, Carla; Pfefferbaum, Adolf; Sullivan, Edith V.

2007-01-01

To identify attentional and neural mechanisms affecting global and local feature extraction, we devised a global-local hierarchical letter paradigm to test the hypothesis that aging reduces functional cerebral lateralization through corpus callosum (CC) degradation. Participants (37 men and women, 26–79 years) performed a task requiring global, local, or global+local attention and underwent structural MRI for CC measurement. Although reaction time (RT) slowed with age, all participants had faster RTs to local than global targets. This local precedence effect together with greater interference from incongruent local information and greater response conflict from local targets each correlated with older age and smaller callosal genu (anterior) areas. These findings support the hypothesis that the CC mediates lateralized local-global processes by inhibition of task-irrelevant information under selective attention conditions. Further, with advancing age smaller genu size leads to less robust inhibition, thereby reducing cerebral lateralization and permitting interference to influence processing. Sex was an additional modifier of interference, in that callosum-interference relationships were evident in women but not in men. Regardless of age, smaller splenium (posterior) areas correlated with less response facilitation from repetition priming of global targets in men, but with greater response facilitation from repetition priming of local targets in women. Our data indicate the following dissociation: Anterior callosal structure was associated with inhibitory processes (i.e., interference from incongruency and response conflict), which are vulnerable to the effects of age and sex, whereas posterior callosal structure was associated with facilitation processes from repetition priming dependent on sex and independent of age. PMID:17335783

Local-global interference is modulated by age, sex and anterior corpus callosum size.

PubMed

Müller-Oehring, Eva M; Schulte, Tilman; Raassi, Carla; Pfefferbaum, Adolf; Sullivan, Edith V

2007-04-20

To identify attentional and neural mechanisms affecting global and local feature extraction, we devised a global-local hierarchical letter paradigm to test the hypothesis that aging reduces functional cerebral lateralization through corpus callosum (CC) degradation. Participants (37 men and women, 26-79 years) performed a task requiring global, local, or global+local attention and underwent structural MRI for CC measurement. Although reaction time (RT) slowed with age, all participants had faster RTs to local than global targets. This local precedence effect together with greater interference from incongruent local information and greater response conflict from local targets each correlated with older age and smaller callosal genu (anterior) areas. These findings support the hypothesis that the CC mediates lateralized local-global processes by inhibition of task-irrelevant information under selective attention conditions. Further, with advancing age smaller genu size leads to less robust inhibition, thereby reducing cerebral lateralization and permitting interference to influence processing. Sex was an additional modifier of interference, in that callosum-interference relationships were evident in women but not in men. Regardless of age, smaller splenium (posterior) areas correlated with less response facilitation from repetition priming of global targets in men, but with greater response facilitation from repetition priming of local targets in women. Our data indicate the following dissociation: anterior callosal structure was associated with inhibitory processes (i.e., interference from incongruency and response conflict), which are vulnerable to the effects of age and sex, whereas posterior callosal structure was associated with facilitation processes from repetition priming dependent on sex and independent of age.

Incremental triangulation by way of edge swapping and local optimization

NASA Technical Reports Server (NTRS)

Wiltberger, N. Lyn

1994-01-01

This document is intended to serve as an installation, usage, and basic theory guide for the two dimensional triangulation software 'HARLEY' written for the Silicon Graphics IRIS workstation. This code consists of an incremental triangulation algorithm based on point insertion and local edge swapping. Using this basic strategy, several types of triangulations can be produced depending on user selected options. For example, local edge swapping criteria can be chosen which minimizes the maximum interior angle (a MinMax triangulation) or which maximizes the minimum interior angle (a MaxMin or Delaunay triangulation). It should be noted that the MinMax triangulation is generally only locally optical (not globally optimal) in this measure. The MaxMin triangulation, however, is both locally and globally optical. In addition, Steiner triangulations can be constructed by inserting new sites at triangle circumcenters followed by edge swapping based on the MaxMin criteria. Incremental insertion of sites also provides flexibility in choosing cell refinement criteria. A dynamic heap structure has been implemented in the code so that once a refinement measure is specified (i.e., maximum aspect ratio or some measure of a solution gradient for the solution adaptive grid generation) the cell with the largest value of this measure is continually removed from the top of the heap and refined. The heap refinement strategy allows the user to specify either the number of cells desired or refine the mesh until all cell refinement measures satisfy a user specified tolerance level. Since the dynamic heap structure is constantly updated, the algorithm always refines the particular cell in the mesh with the largest refinement criteria value. The code allows the user to: triangulate a cloud of prespecified points (sites), triangulate a set of prespecified interior points constrained by prespecified boundary curve(s), Steiner triangulate the interior/exterior of prespecified boundary curve

Global Design Optimization for Aerodynamics and Rocket Propulsion Components

NASA Technical Reports Server (NTRS)

Shyy, Wei; Papila, Nilay; Vaidyanathan, Rajkumar; Tucker, Kevin; Turner, James E. (Technical Monitor)

2000-01-01

Modern computational and experimental tools for aerodynamics and propulsion applications have matured to a stage where they can provide substantial insight into engineering processes involving fluid flows, and can be fruitfully utilized to help improve the design of practical devices. In particular, rapid and continuous development in aerospace engineering demands that new design concepts be regularly proposed to meet goals for increased performance, robustness and safety while concurrently decreasing cost. To date, the majority of the effort in design optimization of fluid dynamics has relied on gradient-based search algorithms. Global optimization methods can utilize the information collected from various sources and by different tools. These methods offer multi-criterion optimization, handle the existence of multiple design points and trade-offs via insight into the entire design space, can easily perform tasks in parallel, and are often effective in filtering the noise intrinsic to numerical and experimental data. However, a successful application of the global optimization method needs to address issues related to data requirements with an increase in the number of design variables, and methods for predicting the model performance. In this article, we review recent progress made in establishing suitable global optimization techniques employing neural network and polynomial-based response surface methodologies. Issues addressed include techniques for construction of the response surface, design of experiment techniques for supplying information in an economical manner, optimization procedures and multi-level techniques, and assessment of relative performance between polynomials and neural networks. Examples drawn from wing aerodynamics, turbulent diffuser flows, gas-gas injectors, and supersonic turbines are employed to help demonstrate the issues involved in an engineering design context. Both the usefulness of the existing knowledge to aid current design

[Medical globalization and local culture.

PubMed

Paci, Eugenio

2017-03-01

Biomedical globalization is a reality in the presence of local worlds with growing human sufferance and inequalities. In this structural and cultural context, characterised by the new communication by Internet and social media, polarisation of medical and scientific debate is enhancing. Based on episodes related to public health issues like vaccines, the quest for better access of Italian professionals and public opinion to an open scientific debate on health research and practice is discussed.

ECG Identification System Using Neural Network with Global and Local Features

ERIC Educational Resources Information Center

Tseng, Kuo-Kun; Lee, Dachao; Chen, Charles

2016-01-01

This paper proposes a human identification system via extracted electrocardiogram (ECG) signals. Two hierarchical classification structures based on global shape feature and local statistical feature is used to extract ECG signals. Global shape feature represents the outline information of ECG signals and local statistical feature extracts the…

Social influence on selection behaviour: Distinguishing local- and global-driven preferential attachment

PubMed Central

Pan, Xue; Liu, Kecheng

2017-01-01

Social influence drives human selection behaviours when numerous objects competing for limited attentions, which leads to the ‘rich get richer’ dynamics where popular objects tend to get more attentions. However, evidences have been found that, both the global information of the whole system and the local information among one’s friends have significant influence over the one’s selection. Consequently, a key question raises that, it is the local information or the global information more determinative for one’s selection? Here we compare the local-based influence and global-based influence. We show that, the selection behaviour is mainly driven by the local popularity of the objects while the global popularity plays a supplementary role driving the behaviour only when there is little local information for the user to refer to. Thereby, we propose a network model to describe the mechanism of user-object interaction evolution with social influence, where the users perform either local-driven or global-driven preferential attachments to the objects, i.e., the probability of an objects to be selected by a target user is proportional to either its local popularity or global popularity. The simulation suggests that, about 75% of the attachments should be driven by the local popularity to reproduce the empirical observations. It means that, at least in the studied context where users chose businesses on Yelp, there is a probability of 75% for a user to make a selection according to the local popularity. The proposed model and the numerical findings may shed some light on the study of social influence and evolving social systems. PMID:28406984

Cache Locality Optimization for Recursive Programs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lifflander, Jonathan; Krishnamoorthy, Sriram

We present an approach to optimize the cache locality for recursive programs by dynamically splicing--recursively interleaving--the execution of distinct function invocations. By utilizing data effect annotations, we identify concurrency and data reuse opportunities across function invocations and interleave them to reduce reuse distance. We present algorithms that efficiently track effects in recursive programs, detect interference and dependencies, and interleave execution of function invocations using user-level (non-kernel) lightweight threads. To enable multi-core execution, a program is parallelized using a nested fork/join programming model. Our cache optimization strategy is designed to work in the context of a random work stealing scheduler. Wemore » present an implementation using the MIT Cilk framework that demonstrates significant improvements in sequential and parallel performance, competitive with a state-of-the-art compile-time optimizer for loop programs and a domain- specific optimizer for stencil programs.« less

Cerebral responses to local and global auditory novelty under general anesthesia

PubMed Central

Uhrig, Lynn; Janssen, David; Dehaene, Stanislas; Jarraya, Béchir

2017-01-01

Primate brains can detect a variety of unexpected deviations in auditory sequences. The local-global paradigm dissociates two hierarchical levels of auditory predictive coding by examining the brain responses to first-order (local) and second-order (global) sequence violations. Using the macaque model, we previously demonstrated that, in the awake state, local violations cause focal auditory responses while global violations activate a brain circuit comprising prefrontal, parietal and cingulate cortices. Here we used the same local-global auditory paradigm to clarify the encoding of the hierarchical auditory regularities in anesthetized monkeys and compared their brain responses to those obtained in the awake state as measured with fMRI. Both, propofol, a GABAA-agonist, and ketamine, an NMDA-antagonist, left intact or even enhanced the cortical response to auditory inputs. The local effect vanished during propofol anesthesia and shifted spatially during ketamine anesthesia compared with wakefulness. Under increasing levels of propofol, we observed a progressive disorganization of the global effect in prefrontal, parietal and cingulate cortices and its complete suppression under ketamine anesthesia. Anesthesia also suppressed thalamic activations to the global effect. These results suggest that anesthesia preserves initial auditory processing, but disturbs both short-term and long-term auditory predictive coding mechanisms. The disorganization of auditory novelty processing under anesthesia relates to a loss of thalamic responses to novelty and to a disruption of higher-order functional cortical networks in parietal, prefrontal and cingular cortices. PMID:27502046

Optimal design of piezoelectric transformers: a rational approach based on an analytical model and a deterministic global optimization.

PubMed

Pigache, Francois; Messine, Frédéric; Nogarede, Bertrand

2007-07-01

This paper deals with a deterministic and rational way to design piezoelectric transformers in radial mode. The proposed approach is based on the study of the inverse problem of design and on its reformulation as a mixed constrained global optimization problem. The methodology relies on the association of the analytical models for describing the corresponding optimization problem and on an exact global optimization software, named IBBA and developed by the second author to solve it. Numerical experiments are presented and compared in order to validate the proposed approach.

Local Approximation and Hierarchical Methods for Stochastic Optimization

NASA Astrophysics Data System (ADS)

Cheng, Bolong

In this thesis, we present local and hierarchical approximation methods for two classes of stochastic optimization problems: optimal learning and Markov decision processes. For the optimal learning problem class, we introduce a locally linear model with radial basis function for estimating the posterior mean of the unknown objective function. The method uses a compact representation of the function which avoids storing the entire history, as is typically required by nonparametric methods. We derive a knowledge gradient policy with the locally parametric model, which maximizes the expected value of information. We show the policy is asymptotically optimal in theory, and experimental works suggests that the method can reliably find the optimal solution on a range of test functions. For the Markov decision processes problem class, we are motivated by an application where we want to co-optimize a battery for multiple revenue, in particular energy arbitrage and frequency regulation. The nature of this problem requires the battery to make charging and discharging decisions at different time scales while accounting for the stochastic information such as load demand, electricity prices, and regulation signals. Computing the exact optimal policy becomes intractable due to the large state space and the number of time steps. We propose two methods to circumvent the computation bottleneck. First, we propose a nested MDP model that structure the co-optimization problem into smaller sub-problems with reduced state space. This new model allows us to understand how the battery behaves down to the two-second dynamics (that of the frequency regulation market). Second, we introduce a low-rank value function approximation for backward dynamic programming. This new method only requires computing the exact value function for a small subset of the state space and approximate the entire value function via low-rank matrix completion. We test these methods on historical price data from the

Globalization and pollution: tele-connecting local primary PM2.5 emissions to global consumption.

PubMed

Meng, Jing; Liu, Junfeng; Xu, Yuan; Guan, Dabo; Liu, Zhu; Huang, Ye; Tao, Shu

2016-11-01

Globalization pushes production and consumption to geographically diverse locations and generates a variety of sizeable opportunities and challenges. The distribution and associated effects of short-lived primary fine particulate matter (PM 2.5 ), a representative of local pollution, are significantly affected by the consumption through global supply chain. Tele-connection is used here to represent the link between production and consumption activity at large distances. In this study, we develop a global consumption-based primary PM 2.5 emission inventory to track primary PM 2.5 emissions embodied in the supply chain and evaluate the extent to which local PM 2.5 emissions are triggered by international trade. We further adopt consumption-based accounting and identify the global original source that produced the emissions. We find that anthropogenic PM 2.5 emissions from industrial sectors accounted for 24 Tg globally in 2007; approximately 30% (7.2 Tg) of these emissions were embodied in export of products principally from Brazil, South Africa, India and China (3.8 Tg) to developed countries. Large differences (up to 10 times) in the embodied emissions intensity between net importers and exporters greatly increased total global PM 2.5 emissions. Tele-connecting production and consumption activity provides valuable insights with respect to mitigating long-range transboundary air pollution and prompts concerted efforts aiming at more environmentally conscious globalization.

Globalization and pollution: tele-connecting local primary PM2.5 emissions to global consumption

NASA Astrophysics Data System (ADS)

Meng, Jing; Liu, Junfeng; Xu, Yuan; Guan, Dabo; Liu, Zhu; Huang, Ye; Tao, Shu

2016-11-01

Globalization pushes production and consumption to geographically diverse locations and generates a variety of sizeable opportunities and challenges. The distribution and associated effects of short-lived primary fine particulate matter (PM2.5), a representative of local pollution, are significantly affected by the consumption through global supply chain. Tele-connection is used here to represent the link between production and consumption activity at large distances. In this study, we develop a global consumption-based primary PM2.5 emission inventory to track primary PM2.5 emissions embodied in the supply chain and evaluate the extent to which local PM2.5 emissions are triggered by international trade. We further adopt consumption-based accounting and identify the global original source that produced the emissions. We find that anthropogenic PM2.5 emissions from industrial sectors accounted for 24 Tg globally in 2007; approximately 30% (7.2 Tg) of these emissions were embodied in export of products principally from Brazil, South Africa, India and China (3.8 Tg) to developed countries. Large differences (up to 10 times) in the embodied emissions intensity between net importers and exporters greatly increased total global PM2.5 emissions. Tele-connecting production and consumption activity provides valuable insights with respect to mitigating long-range transboundary air pollution and prompts concerted efforts aiming at more environmentally conscious globalization.

Globalization and pollution: tele-connecting local primary PM2.5 emissions to global consumption

PubMed Central

Meng, Jing; Xu, Yuan; Guan, Dabo; Liu, Zhu; Huang, Ye; Tao, Shu

2016-01-01

Globalization pushes production and consumption to geographically diverse locations and generates a variety of sizeable opportunities and challenges. The distribution and associated effects of short-lived primary fine particulate matter (PM2.5), a representative of local pollution, are significantly affected by the consumption through global supply chain. Tele-connection is used here to represent the link between production and consumption activity at large distances. In this study, we develop a global consumption-based primary PM2.5 emission inventory to track primary PM2.5 emissions embodied in the supply chain and evaluate the extent to which local PM2.5 emissions are triggered by international trade. We further adopt consumption-based accounting and identify the global original source that produced the emissions. We find that anthropogenic PM2.5 emissions from industrial sectors accounted for 24 Tg globally in 2007; approximately 30% (7.2 Tg) of these emissions were embodied in export of products principally from Brazil, South Africa, India and China (3.8 Tg) to developed countries. Large differences (up to 10 times) in the embodied emissions intensity between net importers and exporters greatly increased total global PM2.5 emissions. Tele-connecting production and consumption activity provides valuable insights with respect to mitigating long-range transboundary air pollution and prompts concerted efforts aiming at more environmentally conscious globalization. PMID:27956874

Coupled Low-thrust Trajectory and System Optimization via Multi-Objective Hybrid Optimal Control

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Englander, Jacob Aldo; Ghosh, Alexander R.

2015-01-01

The optimization of low-thrust trajectories is tightly coupled with the spacecraft hardware. Trading trajectory characteristics with system parameters ton identify viable solutions and determine mission sensitivities across discrete hardware configurations is labor intensive. Local independent optimization runs can sample the design space, but a global exploration that resolves the relationships between the system variables across multiple objectives enables a full mapping of the optimal solution space. A multi-objective, hybrid optimal control algorithm is formulated using a multi-objective genetic algorithm as an outer loop systems optimizer around a global trajectory optimizer. The coupled problem is solved simultaneously to generate Pareto-optimal solutions in a single execution. The automated approach is demonstrated on two boulder return missions.

Global dynamic optimization approach to predict activation in metabolic pathways.

PubMed

de Hijas-Liste, Gundián M; Klipp, Edda; Balsa-Canto, Eva; Banga, Julio R

2014-01-06

During the last decade, a number of authors have shown that the genetic regulation of metabolic networks may follow optimality principles. Optimal control theory has been successfully used to compute optimal enzyme profiles considering simple metabolic pathways. However, applying this optimal control framework to more general networks (e.g. branched networks, or networks incorporating enzyme production dynamics) yields problems that are analytically intractable and/or numerically very challenging. Further, these previous studies have only considered a single-objective framework. In this work we consider a more general multi-objective formulation and we present solutions based on recent developments in global dynamic optimization techniques. We illustrate the performance and capabilities of these techniques considering two sets of problems. First, we consider a set of single-objective examples of increasing complexity taken from the recent literature. We analyze the multimodal character of the associated non linear optimization problems, and we also evaluate different global optimization approaches in terms of numerical robustness, efficiency and scalability. Second, we consider generalized multi-objective formulations for several examples, and we show how this framework results in more biologically meaningful results. The proposed strategy was used to solve a set of single-objective case studies related to unbranched and branched metabolic networks of different levels of complexity. All problems were successfully solved in reasonable computation times with our global dynamic optimization approach, reaching solutions which were comparable or better than those reported in previous literature. Further, we considered, for the first time, multi-objective formulations, illustrating how activation in metabolic pathways can be explained in terms of the best trade-offs between conflicting objectives. This new methodology can be applied to metabolic networks with arbitrary

Perception of shapes targeting local and global processes in autism spectrum disorders.

PubMed

Grinter, Emma J; Maybery, Murray T; Pellicano, Elizabeth; Badcock, Johanna C; Badcock, David R

2010-06-01

Several researchers have found evidence for impaired global processing in the dorsal visual stream in individuals with autism spectrum disorders (ASDs). However, support for a similar pattern of visual processing in the ventral visual stream is less consistent. Critical to resolving the inconsistency is the assessment of local and global form processing ability. Within the visual domain, radial frequency (RF) patterns - shapes formed by sinusoidally varying the radius of a circle to add 'bumps' of a certain number to a circle - can be used to examine local and global form perception. Typically developing children and children with an ASD discriminated between circles and RF patterns that are processed either locally (RF24) or globally (RF3). Children with an ASD required greater shape deformation to identify RF3 shapes compared to typically developing children, consistent with difficulty in global processing in the ventral stream. No group difference was observed for RF24 shapes, suggesting intact local ventral-stream processing. These outcomes support the position that a deficit in global visual processing is present in ASDs, consistent with the notion of Weak Central Coherence.

Gradient gravitational search: An efficient metaheuristic algorithm for global optimization.

PubMed

Dash, Tirtharaj; Sahu, Prabhat K

2015-05-30

The adaptation of novel techniques developed in the field of computational chemistry to solve the concerned problems for large and flexible molecules is taking the center stage with regard to efficient algorithm, computational cost and accuracy. In this article, the gradient-based gravitational search (GGS) algorithm, using analytical gradients for a fast minimization to the next local minimum has been reported. Its efficiency as metaheuristic approach has also been compared with Gradient Tabu Search and others like: Gravitational Search, Cuckoo Search, and Back Tracking Search algorithms for global optimization. Moreover, the GGS approach has also been applied to computational chemistry problems for finding the minimal value potential energy of two-dimensional and three-dimensional off-lattice protein models. The simulation results reveal the relative stability and physical accuracy of protein models with efficient computational cost. © 2015 Wiley Periodicals, Inc.

Global Education and Local School Change.

ERIC Educational Resources Information Center

Otero, George

1983-01-01

Change strategies that focus on improving local schools' abilities to manage change are described, and examples of how the strategies can be applied to help the schools prepare students for life in a global society are furnished. Specific strategies are based on the work of Las Palomas de Taos, an agency promoting change in the Southwest. (PP)

"Glocalization": Going beyond the Dichotomy of Global versus Local through Additive Multilingualism

ERIC Educational Resources Information Center

Joseph, Michael; Ramani, Esther

2012-01-01

This article interrogates the notion of "glocalization" (Moja, 2004, based on Castells, 2001) as a concept that seeks to integrate the local and the global to address both the need for social justice and the need to participate in a global market economy. The article argues that the relation between the global and the local cannot be…

Combining global and local approximations

NASA Technical Reports Server (NTRS)

Haftka, Raphael T.

1991-01-01

A method based on a linear approximation to a scaling factor, designated the 'global-local approximation' (GLA) method, is presented and shown capable of extending the range of usefulness of derivative-based approximations to a more refined model. The GLA approach refines the conventional scaling factor by means of a linearly varying, rather than constant, scaling factor. The capabilities of the method are demonstrated for a simple beam example with a crude and more refined FEM model.

Attentional selection of relative SF mediates global versus local processing: evidence from EEG.

PubMed

Flevaris, Anastasia V; Bentin, Shlomo; Robertson, Lynn C

2011-06-13

Previous research on functional hemispheric differences in visual processing has associated global perception with low spatial frequency (LSF) processing biases of the right hemisphere (RH) and local perception with high spatial frequency (HSF) processing biases of the left hemisphere (LH). The Double Filtering by Frequency (DFF) theory expanded this hypothesis by proposing that visual attention selects and is directed to relatively LSFs by the RH and relatively HSFs by the LH, suggesting a direct causal relationship between SF selection and global versus local perception. We tested this idea in the current experiment by comparing activity in the EEG recorded at posterior right and posterior left hemisphere sites while participants' attention was directed to global or local levels of processing after selection of relatively LSFs versus HSFs in a previous stimulus. Hemispheric asymmetry in the alpha band (8-12 Hz) during preparation for global versus local processing was modulated by the selected SF. In contrast, preparatory activity associated with selection of SF was not modulated by the previously attended level (global/local). These results support the DFF theory that top-down attentional selection of SF mediates global and local processing.

Global and local music perception in children with Williams syndrome.

PubMed

Deruelle, Christine; Schön, Daniele; Rondan, Cécilie; Mancini, Josette

2005-04-25

Musical processing can be decomposed into the appreciation of global and local elements. This global/local dissociation was investigated with the processing of contour-violated and interval-violated melodies. Performance of a group of 16 children with Williams syndrome and a group of 16 control children were compared in a same-different task. Control participants were more accurate in detecting differences in the contour-violated than in the interval-violated condition while Williams syndrome individuals performed equally well in both conditions. This finding suggests that global precedence may occur at an early perceptual stage in normally developing children. In contrast, no such global precedence is observed in the Williams syndrome population. These data are discussed in the context of atypical cognitive profiles of individuals with Williams syndrome.

Global and local curvature in density functional theory.

PubMed

Zhao, Qing; Ioannidis, Efthymios I; Kulik, Heather J

2016-08-07

Piecewise linearity of the energy with respect to fractional electron removal or addition is a requirement of an electronic structure method that necessitates the presence of a derivative discontinuity at integer electron occupation. Semi-local exchange-correlation (xc) approximations within density functional theory (DFT) fail to reproduce this behavior, giving rise to deviations from linearity with a convex global curvature that is evidence of many-electron, self-interaction error and electron delocalization. Popular functional tuning strategies focus on reproducing piecewise linearity, especially to improve predictions of optical properties. In a divergent approach, Hubbard U-augmented DFT (i.e., DFT+U) treats self-interaction errors by reducing the local curvature of the energy with respect to electron removal or addition from one localized subshell to the surrounding system. Although it has been suggested that DFT+U should simultaneously alleviate global and local curvature in the atomic limit, no detailed study on real systems has been carried out to probe the validity of this statement. In this work, we show when DFT+U should minimize deviations from linearity and demonstrate that a "+U" correction will never worsen the deviation from linearity of the underlying xc approximation. However, we explain varying degrees of efficiency of the approach over 27 octahedral transition metal complexes with respect to transition metal (Sc-Cu) and ligand strength (CO, NH3, and H2O) and investigate select pathological cases where the delocalization error is invisible to DFT+U within an atomic projection framework. Finally, we demonstrate that the global and local curvatures represent different quantities that show opposing behavior with increasing ligand field strength, and we identify where these two may still coincide.

A voting-based star identification algorithm utilizing local and global distribution

NASA Astrophysics Data System (ADS)

Fan, Qiaoyun; Zhong, Xuyang; Sun, Junhua

2018-03-01

A novel star identification algorithm based on voting scheme is presented in this paper. In the proposed algorithm, the global distribution and local distribution of sensor stars are fully utilized, and the stratified voting scheme is adopted to obtain the candidates for sensor stars. The database optimization is employed to reduce its memory requirement and improve the robustness of the proposed algorithm. The simulation shows that the proposed algorithm exhibits 99.81% identification rate with 2-pixel standard deviations of positional noises and 0.322-Mv magnitude noises. Compared with two similar algorithms, the proposed algorithm is more robust towards noise, and the average identification time and required memory is less. Furthermore, the real sky test shows that the proposed algorithm performs well on the real star images.

Managing for interactions between local and global stressors of ecosystems.

PubMed

Brown, Christopher J; Saunders, Megan I; Possingham, Hugh P; Richardson, Anthony J

2013-01-01

Global stressors, including climate change, are a major threat to ecosystems, but they cannot be halted by local actions. Ecosystem management is thus attempting to compensate for the impacts of global stressors by reducing local stressors, such as overfishing. This approach assumes that stressors interact additively or synergistically, whereby the combined effect of two stressors is at least the sum of their isolated effects. It is not clear, however, how management should proceed for antagonistic interactions among stressors, where multiple stressors do not have an additive or greater impact. Research to date has focussed on identifying synergisms among stressors, but antagonisms may be just as common. We examined the effectiveness of management when faced with different types of interactions in two systems--seagrass and fish communities--where the global stressor was climate change but the local stressors were different. When there were synergisms, mitigating local stressors delivered greater gains, whereas when there were antagonisms, management of local stressors was ineffective or even degraded ecosystems. These results suggest that reducing a local stressor can compensate for climate change impacts if there is a synergistic interaction. Conversely, if there is an antagonistic interaction, management of local stressors will have the greatest benefits in areas of refuge from climate change. A balanced research agenda, investigating both antagonistic and synergistic interaction types, is needed to inform management priorities.

Local and global Λ polarization in a vortical fluid

DOE PAGES

Li, Hui; Petersen, Hannah; Pang, Long -Gang; ...

2017-09-25

We compute the fermion spin distribution in the vortical fluid created in off-central high energy heavy-ion collisions. We employ the event-by-event (3+1)D viscous hydrodynamic model. The spin polarization density is proportional to the local fluid vorticity in quantum kinetic theory. As a result of strong collectivity, the spatial distribution of the local vorticity on the freeze-out hyper-surface strongly correlates to the rapidity and azimuthal angle distribution of fermion spins. We investigate the sensitivity of the local polarization to the initial fluid velocity in the hydrodynamic model and compute the global polarization of Λ hyperons by the AMPT model. The energymore » dependence of the global polarization agrees with the STAR data.« less

Local and global Λ polarization in a vortical fluid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Hui; Petersen, Hannah; Pang, Long -Gang

We compute the fermion spin distribution in the vortical fluid created in off-central high energy heavy-ion collisions. We employ the event-by-event (3+1)D viscous hydrodynamic model. The spin polarization density is proportional to the local fluid vorticity in quantum kinetic theory. As a result of strong collectivity, the spatial distribution of the local vorticity on the freeze-out hyper-surface strongly correlates to the rapidity and azimuthal angle distribution of fermion spins. We investigate the sensitivity of the local polarization to the initial fluid velocity in the hydrodynamic model and compute the global polarization of Λ hyperons by the AMPT model. The energymore » dependence of the global polarization agrees with the STAR data.« less

Global and local processing near the left and right hands

PubMed Central

Langerak, Robin M.; La Mantia, Carina L.; Brown, Liana E.

2013-01-01

Visual targets can be processed more quickly and reliably when a hand is placed near the target. Both unimodal and bimodal representations of hands are largely lateralized to the contralateral hemisphere, and since each hemisphere demonstrates specialized cognitive processing, it is possible that targets appearing near the left hand may be processed differently than targets appearing near the right hand. The purpose of this study was to determine whether visual processing near the left and right hands interacts with hemispheric specialization. We presented hierarchical-letter stimuli (e.g., small characters used as local elements to compose large characters at the global level) near the left or right hands separately and instructed participants to discriminate the presence of target letters (X and O) from non-target letters (T and U) at either the global or local levels as quickly as possible. Targets appeared at either the global or local level of the display, at both levels, or were absent from the display; participants made foot-press responses. When discriminating target presence at the global level, participants responded more quickly to stimuli presented near the left hand than near either the right hand or in the no-hand condition. Hand presence did not influence target discrimination at the local level. Our interpretation is that left-hand presence may help participants discriminate global information, a right hemisphere (RH) process, and that the left hand may influence visual processing in a way that is distinct from the right hand. PMID:24194725

The q-G method : A q-version of the Steepest Descent method for global optimization.

PubMed

Soterroni, Aline C; Galski, Roberto L; Scarabello, Marluce C; Ramos, Fernando M

2015-01-01

In this work, the q-Gradient (q-G) method, a q-version of the Steepest Descent method, is presented. The main idea behind the q-G method is the use of the negative of the q-gradient vector of the objective function as the search direction. The q-gradient vector, or simply the q-gradient, is a generalization of the classical gradient vector based on the concept of Jackson's derivative from the q-calculus. Its use provides the algorithm an effective mechanism for escaping from local minima. The q-G method reduces to the Steepest Descent method when the parameter q tends to 1. The algorithm has three free parameters and it is implemented so that the search process gradually shifts from global exploration in the beginning to local exploitation in the end. We evaluated the q-G method on 34 test functions, and compared its performance with 34 optimization algorithms, including derivative-free algorithms and the Steepest Descent method. Our results show that the q-G method is competitive and has a great potential for solving multimodal optimization problems.

Towards global optimization with adaptive simulated annealing

NASA Astrophysics Data System (ADS)

Forbes, Gregory W.; Jones, Andrew E.

1991-01-01

The structure of the simulated annealing algorithm is presented and its rationale is discussed. A unifying heuristic is then introduced which serves as a guide in the design of all of the sub-components of the algorithm. Simply put this heuristic principle states that at every cycle in the algorithm the occupation density should be kept as close as possible to the equilibrium distribution. This heuristic has been used as a guide to develop novel step generation and temperature control methods intended to improve the efficiency of the simulated annealing algorithm. The resulting algorithm has been used in attempts to locate good solutions for one of the lens design problems associated with this conference viz. the " monochromatic quartet" and a sample of the results is presented. 1 Global optimization in the context oflens design Whatever the context optimization algorithms relate to problems that take the following form: Given some configuration space with coordinates r (x1 . . x) and a merit function written asffr) find the point r whereftr) takes it lowest value. That is find the global minimum. In many cases there is also a set of auxiliary constraints that must be met so the problem statement becomes: Find the global minimum of the merit function within the region defined by E. (r) 0 j 1 2 . . . p and 0 j 1 2 . . . q.

Multidisciplinary optimization of controlled space structures with global sensitivity equations

NASA Technical Reports Server (NTRS)

Padula, Sharon L.; James, Benjamin B.; Graves, Philip C.; Woodard, Stanley E.

1991-01-01

A new method for the preliminary design of controlled space structures is presented. The method coordinates standard finite element structural analysis, multivariable controls, and nonlinear programming codes and allows simultaneous optimization of the structures and control systems of a spacecraft. Global sensitivity equations are a key feature of this method. The preliminary design of a generic geostationary platform is used to demonstrate the multidisciplinary optimization method. Fifteen design variables are used to optimize truss member sizes and feedback gain values. The goal is to reduce the total mass of the structure and the vibration control system while satisfying constraints on vibration decay rate. Incorporating the nonnegligible mass of actuators causes an essential coupling between structural design variables and control design variables. The solution of the demonstration problem is an important step toward a comprehensive preliminary design capability for structures and control systems. Use of global sensitivity equations helps solve optimization problems that have a large number of design variables and a high degree of coupling between disciplines.

Cultural variations in global versus local processing: a developmental perspective.

PubMed

Oishi, Shigehiro; Jaswal, Vikram K; Lillard, Angeline S; Mizokawa, Ai; Hitokoto, Hidefumi; Tsutsui, Yoshiro

2014-12-01

We conducted 3 studies to explore cultural differences in global versus local processing and their developmental trajectories. In Study 1 (N = 363), we found that Japanese college students were less globally oriented in their processing than American or Argentine participants. We replicated this effect in Study 2 (N = 1,843) using a nationally representative sample of Japanese and American adults ages 20 to 69, and found further that adults in both cultures became more globally oriented with age. In Study 3 (N = 133), we investigated the developmental course of the cultural difference using Japanese and American children, and found it was evident by 4 years of age. Cultural variations in global versus local processing emerge by early childhood, and remain throughout adulthood. At the same time, both Japanese and Americans become increasingly global processors with age. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Global, Multi-Objective Trajectory Optimization With Parametric Spreading

NASA Technical Reports Server (NTRS)

Vavrina, Matthew A.; Englander, Jacob A.; Phillips, Sean M.; Hughes, Kyle M.

2017-01-01

Mission design problems are often characterized by multiple, competing trajectory optimization objectives. Recent multi-objective trajectory optimization formulations enable generation of globally-optimal, Pareto solutions via a multi-objective genetic algorithm. A byproduct of these formulations is that clustering in design space can occur in evolving the population towards the Pareto front. This clustering can be a drawback, however, if parametric evaluations of design variables are desired. This effort addresses clustering by incorporating operators that encourage a uniform spread over specified design variables while maintaining Pareto front representation. The algorithm is demonstrated on a Neptune orbiter mission, and enhanced multidimensional visualization strategies are presented.

Localization of multilayer networks by optimized single-layer rewiring.

PubMed

Jalan, Sarika; Pradhan, Priodyuti

2018-04-01

We study localization properties of principal eigenvectors (PEVs) of multilayer networks (MNs). Starting with a multilayer network corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired multilayer network becomes more localized. The framework allows us to scrutinize structural and spectral properties of the networks at various localization points during the rewiring process. We show that rewiring only one layer is enough to attain a MN having a highly localized PEV. Our investigation reveals that a single edge rewiring of the optimized MN can lead to the complete delocalization of a highly localized PEV. This sensitivity in the localization behavior of PEVs is accompanied with the second largest eigenvalue lying very close to the largest one. This observation opens an avenue to gain a deeper insight into the origin of PEV localization of networks. Furthermore, analysis of multilayer networks constructed using real-world social and biological data shows that the localization properties of these real-world multilayer networks are in good agreement with the simulation results for the model multilayer network. This paper is relevant to applications that require understanding propagation of perturbation in multilayer networks.

Localization of multilayer networks by optimized single-layer rewiring

NASA Astrophysics Data System (ADS)

Jalan, Sarika; Pradhan, Priodyuti

2018-04-01

We study localization properties of principal eigenvectors (PEVs) of multilayer networks (MNs). Starting with a multilayer network corresponding to a delocalized PEV, we rewire the network edges using an optimization technique such that the PEV of the rewired multilayer network becomes more localized. The framework allows us to scrutinize structural and spectral properties of the networks at various localization points during the rewiring process. We show that rewiring only one layer is enough to attain a MN having a highly localized PEV. Our investigation reveals that a single edge rewiring of the optimized MN can lead to the complete delocalization of a highly localized PEV. This sensitivity in the localization behavior of PEVs is accompanied with the second largest eigenvalue lying very close to the largest one. This observation opens an avenue to gain a deeper insight into the origin of PEV localization of networks. Furthermore, analysis of multilayer networks constructed using real-world social and biological data shows that the localization properties of these real-world multilayer networks are in good agreement with the simulation results for the model multilayer network. This paper is relevant to applications that require understanding propagation of perturbation in multilayer networks.

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks.

PubMed

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-05-21

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods.

Efficient Convex Optimization for Energy-Based Acoustic Sensor Self-Localization and Source Localization in Sensor Networks

PubMed Central

Yan, Yongsheng; Wang, Haiyan; Shen, Xiaohong; Leng, Bing; Li, Shuangquan

2018-01-01

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods. PMID:29883410

An artifact caused by undersampling optimal trees in supermatrix analyses of locally sampled characters.

PubMed

Simmons, Mark P; Goloboff, Pablo A

2013-10-01

Empirical and simulated examples are used to demonstrate an artifact caused by undersampling optimal trees in data matrices that consist mostly or entirely of locally sampled (as opposed to globally, for most or all terminals) characters. The artifact is that unsupported clades consisting entirely of terminals scored for the same locally sampled partition may be resolved and assigned high resampling support-despite their being properly unsupported (i.e., not resolved in the strict consensus of all optimal trees). This artifact occurs despite application of random-addition sequences for stepwise terminal addition. The artifact is not necessarily obviated with thorough conventional branch swapping methods (even tree-bisection-reconnection) when just a single tree is held, as is sometimes implemented in parsimony bootstrap pseudoreplicates, and in every GARLI, PhyML, and RAxML pseudoreplicate and search for the most likely tree for the matrix as a whole. Hence GARLI, RAxML, and PhyML-based likelihood results require extra scrutiny, particularly when they provide high resolution and support for clades that are entirely unsupported by methods that perform more thorough searches, as in most parsimony analyses. Copyright © 2013 Elsevier Inc. All rights reserved.

Self-Orientation Modulates the Neural Correlates of Global and Local Processing.

PubMed

Liddell, Belinda J; Das, Pritha; Battaglini, Eva; Malhi, Gin S; Felmingham, Kim L; Whitford, Thomas J; Bryant, Richard A

2015-01-01

Differences in self-orientation (or "self-construal") may affect how the visual environment is attended, but the neural and cultural mechanisms that drive this remain unclear. Behavioral studies have demonstrated that people from Western backgrounds with predominant individualistic values are perceptually biased towards local-level information; whereas people from non-Western backgrounds that support collectivist values are preferentially focused on contextual and global-level information. In this study, we compared two groups differing in predominant individualistic (N = 15) vs collectivistic (N = 15) self-orientation. Participants completed a global/local perceptual conflict task whilst undergoing functional Magnetic Resonance Imaging (fMRI) scanning. When participants high in individualistic values attended to the global level (ignoring the local level), greater activity was observed in the frontoparietal and cingulo-opercular networks that underpin attentional control, compared to the match (congruent) baseline. Participants high in collectivistic values activated similar attentional control networks o only when directly compared with global processing. This suggests that global interference was stronger than local interference in the conflict task in the collectivistic group. Both groups showed increased activity in dorsolateral prefrontal regions involved in resolving perceptual conflict during heightened distractor interference. The findings suggest that self-orientation may play an important role in driving attention networks to facilitate interaction with the visual environment.

Neoliberal Optimism: Applying Market Techniques to Global Health.

PubMed

Mei, Yuyang

2017-01-01

Global health and neoliberalism are becoming increasingly intertwined as organizations utilize markets and profit motives to solve the traditional problems of poverty and population health. I use field work conducted over 14 months in a global health technology company to explore how the promise of neoliberalism re-envisions humanitarian efforts. In this company's vaccine refrigerator project, staff members expect their investors and their market to allow them to achieve scale and develop accountability to their users in developing countries. However, the translation of neoliberal techniques to the global health sphere falls short of the ideal, as profits are meager and purchasing power remains with donor organizations. The continued optimism in market principles amidst such a non-ideal market reveals the tenacious ideological commitment to neoliberalism in these global health projects.

Various oscillation patterns in phase models with locally attractive and globally repulsive couplings.

PubMed

Sato, Katsuhiko; Shima, Shin-ichiro

2015-10-01

We investigate a phase model that includes both locally attractive and globally repulsive coupling in one dimension. This model exhibits nontrivial spatiotemporal patterns that have not been observed in systems that contain only local or global coupling. Depending on the relative strengths of the local and global coupling and on the form of global coupling, the system can show a spatially uniform state (in-phase synchronization), a monotonically increasing state (traveling wave), and three types of oscillations of relative phase difference. One of the oscillations of relative phase difference has the characteristic of being locally unstable but globally attractive. That is, any small perturbation to the periodic orbit in phase space destroys its periodic motion, but after a long time the system returns to the original periodic orbit. This behavior is closely related to the emergence of saddle two-cluster states for global coupling only, which are connected to each other by attractive heteroclinic orbits. The mechanism of occurrence of this type of oscillation is discussed.

Emotional state and local versus global spatial memory.

PubMed

Brunyé, Tad T; Mahoney, Caroline R; Augustyn, Jason S; Taylor, Holly A

2009-02-01

The present work investigated the effects of participant emotional state on global versus local memory for map-based information. Participants were placed into one of four emotion induction groups, crossing high and low arousal with positive and negative valence, or a control group. They then studied a university campus map and completed two memory tests, free recall and spatial statement verification. Converging evidence from these two tasks demonstrated that arousal amplifies symbolic distance effects and leads to a globally-focused spatial mental representation, partially at the expense of local knowledge. These results were found for both positively- and negatively-valenced affective states. The present study is the first investigation of emotional effects on spatial memory, and has implications for theories of emotion and spatial cognition.

A global/local analysis method for treating details in structural design

NASA Technical Reports Server (NTRS)

Aminpour, Mohammad A.; Mccleary, Susan L.; Ransom, Jonathan B.

1993-01-01

A method for analyzing global/local behavior of plate and shell structures is described. In this approach, a detailed finite element model of the local region is incorporated within a coarser global finite element model. The local model need not be nodally compatible (i.e., need not have a one-to-one nodal correspondence) with the global model at their common boundary; therefore, the two models may be constructed independently. The nodal incompatibility of the models is accounted for by introducing appropriate constraint conditions into the potential energy in a hybrid variational formulation. The primary advantage of this method is that the need for transition modeling between global and local models is eliminated. Eliminating transition modeling has two benefits. First, modeling efforts are reduced since tedious and complex transitioning need not be performed. Second, errors due to the mesh distortion, often unavoidable in mesh transitioning, are minimized by avoiding distorted elements beyond what is needed to represent the geometry of the component. The method is applied reduced to a plate loaded in tension and transverse bending. The plate has a central hole, and various hole sixes and shapes are studied. The method is also applied to a composite laminated fuselage panel with a crack emanating from a window in the panel. While this method is applied herein to global/local problems, it is also applicable to the coupled analysis of independently modeled components as well as adaptive refinement.

Model-based synthesis of locally contingent responses to global market signals

NASA Astrophysics Data System (ADS)

Magliocca, N. R.

2015-12-01

Rural livelihoods and the land systems on which they depend are increasingly influenced by distant markets through economic globalization. Place-based analyses of land and livelihood system sustainability must then consider both proximate and distant influences on local decision-making. Thus, advancing land change theory in the context of economic globalization calls for a systematic understanding of the general processes as well as local contingencies shaping local responses to global signals. Synthesis of insights from place-based case studies of land and livelihood change is a path forward for developing such systematic knowledge. This paper introduces a model-based synthesis approach to investigating the influence of local socio-environmental and agent-level factors in mediating land-use and livelihood responses to changing global market signals. A generalized agent-based modeling framework is applied to six case-study sites that differ in environmental conditions, market access and influence, and livelihood settings. The largest modeled land conversions and livelihood transitions to market-oriented production occurred in sties with relatively productive agricultural land and/or with limited livelihood options. Experimental shifts in the distributions of agents' risk tolerances generally acted to attenuate or amplify responses to changes in global market signals. Importantly, however, responses of agents at different points in the risk tolerance distribution varied widely, with the wealth gap growing wider between agents with higher or lower risk tolerance. These results demonstrate model-based synthesis is a promising approach to overcome many of the challenges of current synthesis methods in land change science, and to identify generalized as well as locally contingent responses to global market signals.

A global optimization approach to multi-polarity sentiment analysis.

PubMed

Li, Xinmiao; Li, Jing; Wu, Yukeng

2015-01-01

Following the rapid development of social media, sentiment analysis has become an important social media mining technique. The performance of automatic sentiment analysis primarily depends on feature selection and sentiment classification. While information gain (IG) and support vector machines (SVM) are two important techniques, few studies have optimized both approaches in sentiment analysis. The effectiveness of applying a global optimization approach to sentiment analysis remains unclear. We propose a global optimization-based sentiment analysis (PSOGO-Senti) approach to improve sentiment analysis with IG for feature selection and SVM as the learning engine. The PSOGO-Senti approach utilizes a particle swarm optimization algorithm to obtain a global optimal combination of feature dimensions and parameters in the SVM. We evaluate the PSOGO-Senti model on two datasets from different fields. The experimental results showed that the PSOGO-Senti model can improve binary and multi-polarity Chinese sentiment analysis. We compared the optimal feature subset selected by PSOGO-Senti with the features in the sentiment dictionary. The results of this comparison indicated that PSOGO-Senti can effectively remove redundant and noisy features and can select a domain-specific feature subset with a higher-explanatory power for a particular sentiment analysis task. The experimental results showed that the PSOGO-Senti approach is effective and robust for sentiment analysis tasks in different domains. By comparing the improvements of two-polarity, three-polarity and five-polarity sentiment analysis results, we found that the five-polarity sentiment analysis delivered the largest improvement. The improvement of the two-polarity sentiment analysis was the smallest. We conclude that the PSOGO-Senti achieves higher improvement for a more complicated sentiment analysis task. We also compared the results of PSOGO-Senti with those of the genetic algorithm (GA) and grid search method. From

Behavioral and Physiological Findings of Gender Differences in Global-Local Visual Processing

ERIC Educational Resources Information Center

Roalf, David; Lowery, Natasha; Turetsky, Bruce I.

2006-01-01

Hemispheric asymmetries in global-local visual processing are well-established, as are gender differences in cognition. Although hemispheric asymmetry presumably underlies gender differences in cognition, the literature on gender differences in global-local processing is sparse. We employed event related brain potential (ERP) recordings during…

Tsunamis: Global Exposure and Local Risk Analysis

NASA Astrophysics Data System (ADS)

Harbitz, C. B.; Løvholt, F.; Glimsdal, S.; Horspool, N.; Griffin, J.; Davies, G.; Frauenfelder, R.

2014-12-01

The 2004 Indian Ocean tsunami led to a better understanding of the likelihood of tsunami occurrence and potential tsunami inundation, and the Hyogo Framework for Action (HFA) was one direct result of this event. The United Nations International Strategy for Disaster Risk Reduction (UN-ISDR) adopted HFA in January 2005 in order to reduce disaster risk. As an instrument to compare the risk due to different natural hazards, an integrated worldwide study was implemented and published in several Global Assessment Reports (GAR) by UN-ISDR. The results of the global earthquake induced tsunami hazard and exposure analysis for a return period of 500 years are presented. Both deterministic and probabilistic methods (PTHA) are used. The resulting hazard levels for both methods are compared quantitatively for selected areas. The comparison demonstrates that the analysis is rather rough, which is expected for a study aiming at average trends on a country level across the globe. It is shown that populous Asian countries account for the largest absolute number of people living in tsunami prone areas, more than 50% of the total exposed people live in Japan. Smaller nations like Macao and the Maldives are among the most exposed by population count. Exposed nuclear power plants are limited to Japan, China, India, Taiwan, and USA. On the contrary, a local tsunami vulnerability and risk analysis applies information on population, building types, infrastructure, inundation, flow depth for a certain tsunami scenario with a corresponding return period combined with empirical data on tsunami damages and mortality. Results and validation of a GIS tsunami vulnerability and risk assessment model are presented. The GIS model is adapted for optimal use of data available for each study. Finally, the importance of including landslide sources in the tsunami analysis is also discussed.

Coastal Adaptation Planning for Sea Level Rise and Extremes: A Global Model for Adaptation Decision-making at the Local Level Given Uncertain Climate Projections

NASA Astrophysics Data System (ADS)

Turner, D.

2014-12-01

Understanding the potential economic and physical impacts of climate change on coastal resources involves evaluating a number of distinct adaptive responses. This paper presents a tool for such analysis, a spatially-disaggregated optimization model for adaptation to sea level rise (SLR) and storm surge, the Coastal Impact and Adaptation Model (CIAM). This decision-making framework fills a gap between very detailed studies of specific locations and overly aggregate global analyses. While CIAM is global in scope, the optimal adaptation strategy is determined at the local level, evaluating over 12,000 coastal segments as described in the DIVA database (Vafeidis et al. 2006). The decision to pursue a given adaptation measure depends on local socioeconomic factors like income, population, and land values and how they develop over time, relative to the magnitude of potential coastal impacts, based on geophysical attributes like inundation zones and storm surge. For example, the model's decision to protect or retreat considers the costs of constructing and maintaining coastal defenses versus those of relocating people and capital to minimize damages from land inundation and coastal storms. Uncertain storm surge events are modeled with a generalized extreme value distribution calibrated to data on local surge extremes. Adaptation is optimized for the near-term outlook, in an "act then learn then act" framework that is repeated over the model time horizon. This framework allows the adaptation strategy to be flexibly updated, reflecting the process of iterative risk management. CIAM provides new estimates of the economic costs of SLR; moreover, these detailed results can be compactly represented in a set of adaptation and damage functions for use in integrated assessment models. Alongside the optimal result, CIAM evaluates suboptimal cases and finds that global costs could increase by an order of magnitude, illustrating the importance of adaptive capacity and coastal policy.

Drawing Connections Between Local and Global Observations: An Essential Element of Geoscience Education

NASA Astrophysics Data System (ADS)

Manduca, C. A.; Mogk, D. W.

2002-12-01

One of the hallmarks of geoscience research is the process of moving between observations and interpretations on local and global scales to develop an integrated understanding of Earth processes. Understanding this interplay is an important aspect of student geoscience learning which leads to an understanding of the fundamental principles of science and geoscience and of the connections between local natural phenomena or human activity and global processes. Several techniques that engage students in inquiry and discovery (as recommended in the National Science Education Standards, NRC 1996, Shaping the Future of Undergraduate Earth Science Education, AGU, 1997) hold promise for helping students make these connections. These include the development of global data sets from local observations (e.g. GLOBE); studying small scale or local phenomenon in the context of global models (e.g. carbon storage in local vegetation and its role in the carbon cycle); or an analysis of local environmental issues in a global context (e.g. a comparison of local flooding to flooding in other countries and analysis in the context of weather, geology and development patterns). Research on learning suggests that data-rich activities linking the local and global have excellent potential for enhancing student learning because 1) students have already developed observations and interpretations of their local environment which can serve as a starting point for constructing new knowledge and 2) this context may motivate learning and develop understanding that can be transferred to other situations. (How People Learn, NRC, 2001). Faculty and teachers at two recent workshops confirm that projects that involve local or global data can engage students in learning by providing real world context, creating student ownership of the learning process, and developing scientific skills applicable to the complex problems that characterize modern science and society. Workshop participants called for

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization.

PubMed

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-03-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors' memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm.

Parameter Selection and Performance Comparison of Particle Swarm Optimization in Sensor Networks Localization

PubMed Central

Cui, Huanqing; Shu, Minglei; Song, Min; Wang, Yinglong

2017-01-01

Localization is a key technology in wireless sensor networks. Faced with the challenges of the sensors’ memory, computational constraints, and limited energy, particle swarm optimization has been widely applied in the localization of wireless sensor networks, demonstrating better performance than other optimization methods. In particle swarm optimization-based localization algorithms, the variants and parameters should be chosen elaborately to achieve the best performance. However, there is a lack of guidance on how to choose these variants and parameters. Further, there is no comprehensive performance comparison among particle swarm optimization algorithms. The main contribution of this paper is three-fold. First, it surveys the popular particle swarm optimization variants and particle swarm optimization-based localization algorithms for wireless sensor networks. Secondly, it presents parameter selection of nine particle swarm optimization variants and six types of swarm topologies by extensive simulations. Thirdly, it comprehensively compares the performance of these algorithms. The results show that the particle swarm optimization with constriction coefficient using ring topology outperforms other variants and swarm topologies, and it performs better than the second-order cone programming algorithm. PMID:28257060

Global and local disturbances interact to modify seagrass palatability.

PubMed

Jiménez-Ramos, Rocío; Egea, Luis G; Ortega, María J; Hernández, Ignacio; Vergara, Juan J; Brun, Fernando G

2017-01-01

Global change, such as warming and ocean acidification, and local anthropogenic disturbances, such as eutrophication, can have profound impacts on marine organisms. However, we are far from being able to predict the outcome of multiple interacting disturbances on seagrass communities. Herbivores are key in determining plant community structure and the transfer of energy up the food web. Global and local disturbances may alter the ecological role of herbivory by modifying leaf palatability (i.e. leaf traits) and consequently, the feeding patterns of herbivores. This study evaluates the main and interactive effects of factors related to global change (i.e. elevated temperature, lower pH levels and associated ocean acidification) and local disturbance (i.e. eutrophication through ammonium enrichment) on a broad spectrum of leaf traits using the temperate seagrass Cymodocea nodosa, including structural, nutritional, biomechanical and chemical traits. The effect of these traits on the consumption rates of the generalist herbivore Paracentrotus lividus (purple sea urchin) is evaluated. The three disturbances of warming, low pH level and eutrophication, alone and in combination, increased the consumption rate of seagrass by modifying all leaf traits. Leaf nutritional quality, measured as nitrogen content, was positively correlated to consumption rate. In contrast, a negative correlation was found between feeding decisions by sea urchins and structural, biomechanical and chemical leaf traits. In addition, a notable accomplishment of this work is the identification of phenolic compounds not previously reported for C. nodosa. Our results suggest that global and local disturbances may trigger a major shift in the herbivory of seagrass communities, with important implications for the resilience of seagrass ecosystems.

Multiscale Spatial Modeling of Human Exposure from Local Sources to Global Intake.

PubMed

Wannaz, Cedric; Fantke, Peter; Jolliet, Olivier

2018-01-16

Exposure studies, used in human health risk and impact assessments of chemicals, are largely performed locally or regionally. It is usually not known how global impacts resulting from exposure to point source emissions compare to local impacts. To address this problem, we introduce Pangea, an innovative multiscale, spatial multimedia fate and exposure assessment model. We study local to global population exposure associated with emissions from 126 point sources matching locations of waste-to-energy plants across France. Results for three chemicals with distinct physicochemical properties are expressed as the evolution of the population intake fraction through inhalation and ingestion as a function of the distance from sources. For substances with atmospheric half-lives longer than a week, less than 20% of the global population intake through inhalation (median of 126 emission scenarios) can occur within a 100 km radius from the source. This suggests that, by neglecting distant low-level exposure, local assessments might only account for fractions of global cumulative intakes. We also study ∼10 000 emission locations covering France more densely to determine per chemical and exposure route which locations minimize global intakes. Maps of global intake fractions associated with each emission location show clear patterns associated with population and agriculture production densities.

Self-Orientation Modulates the Neural Correlates of Global and Local Processing

PubMed Central

Liddell, Belinda J.; Das, Pritha; Battaglini, Eva; Malhi, Gin S.; Felmingham, Kim L.; Whitford, Thomas J.; Bryant, Richard A.

2015-01-01

Differences in self-orientation (or “self-construal”) may affect how the visual environment is attended, but the neural and cultural mechanisms that drive this remain unclear. Behavioral studies have demonstrated that people from Western backgrounds with predominant individualistic values are perceptually biased towards local-level information; whereas people from non-Western backgrounds that support collectivist values are preferentially focused on contextual and global-level information. In this study, we compared two groups differing in predominant individualistic (N = 15) vs collectivistic (N = 15) self-orientation. Participants completed a global/local perceptual conflict task whilst undergoing functional Magnetic Resonance Imaging (fMRI) scanning. When participants high in individualistic values attended to the global level (ignoring the local level), greater activity was observed in the frontoparietal and cingulo-opercular networks that underpin attentional control, compared to the match (congruent) baseline. Participants high in collectivistic values activated similar attentional control networks o only when directly compared with global processing. This suggests that global interference was stronger than local interference in the conflict task in the collectivistic group. Both groups showed increased activity in dorsolateral prefrontal regions involved in resolving perceptual conflict during heightened distractor interference. The findings suggest that self-orientation may play an important role in driving attention networks to facilitate interaction with the visual environment. PMID:26270820

Climate-soil Interactions: Global Change, Local Properties, and Ecological Sites

USDA-ARS?s Scientific Manuscript database

Global climate change is predicted to alter historic patterns of precipitation and temperature in rangelands globally. Vegetation community response to altered weather patterns will be mediated at the site level by local-scale properties that govern ecological potential, including geology, topograph...

Conscious Vision Proceeds from Global to Local Content in Goal-Directed Tasks and Spontaneous Vision.

PubMed

Campana, Florence; Rebollo, Ignacio; Urai, Anne; Wyart, Valentin; Tallon-Baudry, Catherine

2016-05-11

The reverse hierarchy theory (Hochstein and Ahissar, 2002) makes strong, but so far untested, predictions on conscious vision. In this theory, local details encoded in lower-order visual areas are unconsciously processed before being automatically and rapidly combined into global information in higher-order visual areas, where conscious percepts emerge. Contingent on current goals, local details can afterward be consciously retrieved. This model therefore predicts that (1) global information is perceived faster than local details, (2) global information is computed regardless of task demands during early visual processing, and (3) spontaneous vision is dominated by global percepts. We designed novel textured stimuli that are, as opposed to the classic Navon's letters, truly hierarchical (i.e., where global information is solely defined by local information but where local and global orientations can still be manipulated separately). In line with the predictions, observers were systematically faster reporting global than local properties of those stimuli. Second, global information could be decoded from magneto-encephalographic data during early visual processing regardless of task demands. Last, spontaneous subjective reports were dominated by global information and the frequency and speed of spontaneous global perception correlated with the accuracy and speed in the global task. No such correlation was observed for local information. We therefore show that information at different levels of the visual hierarchy is not equally likely to become conscious; rather, conscious percepts emerge preferentially at a global level. We further show that spontaneous reports can be reliable and are tightly linked to objective performance at the global level. Is information encoded at different levels of the visual system (local details in low-level areas vs global shapes in high-level areas) equally likely to become conscious? We designed new hierarchical stimuli and provide the

Implications of optimization cost for balancing exploration and exploitation in global search and for experimental optimization

NASA Astrophysics Data System (ADS)

Chaudhuri, Anirban

Global optimization based on expensive and time consuming simulations or experiments usually cannot be carried out to convergence, but must be stopped because of time constraints, or because the cost of the additional function evaluations exceeds the benefits of improving the objective(s). This dissertation sets to explore the implications of such budget and time constraints on the balance between exploration and exploitation and the decision of when to stop. Three different aspects are considered in terms of their effects on the balance between exploration and exploitation: 1) history of optimization, 2) fixed evaluation budget, and 3) cost as a part of objective function. To this end, this research develops modifications to the surrogate-based optimization technique, Efficient Global Optimization algorithm, that controls better the balance between exploration and exploitation, and stopping criteria facilitated by these modifications. Then the focus shifts to examining experimental optimization, which shares the issues of cost and time constraints. Through a study on optimization of thrust and power for a small flapping wing for micro air vehicles, important differences and similarities between experimental and simulation-based optimization are identified. The most important difference is that reduction of noise in experiments becomes a major time and cost issue, and a second difference is that parallelism as a way to cut cost is more challenging. The experimental optimization reveals the tendency of the surrogate to display optimistic bias near the surrogate optimum, and this tendency is then verified to also occur in simulation based optimization.

Local and Global Gestalt Laws: A Neurally Based Spectral Approach.

PubMed

Favali, Marta; Citti, Giovanna; Sarti, Alessandro

2017-02-01

This letter presents a mathematical model of figure-ground articulation that takes into account both local and global gestalt laws and is compatible with the functional architecture of the primary visual cortex (V1). The local gestalt law of good continuation is described by means of suitable connectivity kernels that are derived from Lie group theory and quantitatively compared with long-range connectivity in V1. Global gestalt constraints are then introduced in terms of spectral analysis of a connectivity matrix derived from these kernels. This analysis performs grouping of local features and individuates perceptual units with the highest salience. Numerical simulations are performed, and results are obtained by applying the technique to a number of stimuli.

Global optimization of cholic acid aggregates

NASA Astrophysics Data System (ADS)

Jójárt, Balázs; Viskolcz, Béla; Poša, Mihalj; Fejer, Szilard N.

2014-04-01

In spite of recent investigations into the potential pharmaceutical importance of bile acids as drug carriers, the structure of bile acid aggregates is largely unknown. Here, we used global optimization techniques to find the lowest energy configurations for clusters composed between 2 and 10 cholate molecules, and evaluated the relative stabilities of the global minima. We found that the energetically most preferred geometries for small aggregates are in fact reverse micellar arrangements, and the classical micellar behaviour (efficient burial of hydrophobic parts) is achieved only in systems containing more than five cholate units. Hydrogen bonding plays a very important part in keeping together the monomers, and among the size range considered, the most stable structure was found to be the decamer, having 17 hydrogen bonds. Molecular dynamics simulations showed that the decamer has the lowest dissociation propensity among the studied aggregation numbers.

Inequality measures perform differently in global and local assessments: An exploratory computational experiment

NASA Astrophysics Data System (ADS)

Chiang, Yen-Sheng

2015-11-01

Inequality measures are widely used in both the academia and public media to help us understand how incomes and wealth are distributed. They can be used to assess the distribution of a whole society-global inequality-as well as inequality of actors' referent networks-local inequality. How different is local inequality from global inequality? Formalizing the structure of reference groups as a network, the paper conducted a computational experiment to see how the structure of complex networks influences the difference between global and local inequality assessed by a selection of inequality measures. It was found that local inequality tends to be higher than global inequality when population size is large; network is dense and heterophilously assorted, and income distribution is less dispersed. The implications of the simulation findings are discussed.

MDTri: robust and efficient global mixed integer search of spaces of multiple ternary alloys: A DIRECT-inspired optimization algorithm for experimentally accessible computational material design

DOE PAGES

Graf, Peter A.; Billups, Stephen

2017-07-24

Computational materials design has suffered from a lack of algorithms formulated in terms of experimentally accessible variables. Here we formulate the problem of (ternary) alloy optimization at the level of choice of atoms and their composition that is normal for synthesists. Mathematically, this is a mixed integer problem where a candidate solution consists of a choice of three elements, and how much of each of them to use. This space has the natural structure of a set of equilateral triangles. We solve this problem by introducing a novel version of the DIRECT algorithm that (1) operates on equilateral triangles insteadmore » of rectangles and (2) works across multiple triangles. We demonstrate on a test case that the algorithm is both robust and efficient. Lastly, we offer an explanation of the efficacy of DIRECT -- specifically, its balance of global and local search -- by showing that 'potentially optimal rectangles' of the original algorithm are akin to the Pareto front of the 'multi-component optimization' of global and local search.« less

MDTri: robust and efficient global mixed integer search of spaces of multiple ternary alloys: A DIRECT-inspired optimization algorithm for experimentally accessible computational material design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graf, Peter A.; Billups, Stephen

Computational materials design has suffered from a lack of algorithms formulated in terms of experimentally accessible variables. Here we formulate the problem of (ternary) alloy optimization at the level of choice of atoms and their composition that is normal for synthesists. Mathematically, this is a mixed integer problem where a candidate solution consists of a choice of three elements, and how much of each of them to use. This space has the natural structure of a set of equilateral triangles. We solve this problem by introducing a novel version of the DIRECT algorithm that (1) operates on equilateral triangles insteadmore » of rectangles and (2) works across multiple triangles. We demonstrate on a test case that the algorithm is both robust and efficient. Lastly, we offer an explanation of the efficacy of DIRECT -- specifically, its balance of global and local search -- by showing that 'potentially optimal rectangles' of the original algorithm are akin to the Pareto front of the 'multi-component optimization' of global and local search.« less

Sustained Attention to Local and Global Target Features Is Different: Performance and Tympanic Membrane Temperature

ERIC Educational Resources Information Center

Helton, William S.; Hayrynen, Lauren; Schaeffer, David

2009-01-01

Vision researchers have investigated the differences between global and local feature perception. No one has, however, examined the role of global and local feature discrimination in sustained attention tasks. In this experiment participants performed a sustained attention task requiring either global or local letter target discriminations or…

Applications of New Surrogate Global Optimization Algorithms including Efficient Synchronous and Asynchronous Parallelism for Calibration of Expensive Nonlinear Geophysical Simulation Models.

NASA Astrophysics Data System (ADS)

Shoemaker, C. A.; Pang, M.; Akhtar, T.; Bindel, D.

2016-12-01

New parallel surrogate global optimization algorithms are developed and applied to objective functions that are expensive simulations (possibly with multiple local minima). The algorithms can be applied to most geophysical simulations, including those with nonlinear partial differential equations. The optimization does not require simulations be parallelized. Asynchronous (and synchronous) parallel execution is available in the optimization toolbox "pySOT". The parallel algorithms are modified from serial to eliminate fine grained parallelism. The optimization is computed with open source software pySOT, a Surrogate Global Optimization Toolbox that allows user to pick the type of surrogate (or ensembles), the search procedure on surrogate, and the type of parallelism (synchronous or asynchronous). pySOT also allows the user to develop new algorithms by modifying parts of the code. In the applications here, the objective function takes up to 30 minutes for one simulation, and serial optimization can take over 200 hours. Results from Yellowstone (NSF) and NCSS (Singapore) supercomputers are given for groundwater contaminant hydrology simulations with applications to model parameter estimation and decontamination management. All results are compared with alternatives. The first results are for optimization of pumping at many wells to reduce cost for decontamination of groundwater at a superfund site. The optimization runs with up to 128 processors. Superlinear speed up is obtained for up to 16 processors, and efficiency with 64 processors is over 80%. Each evaluation of the objective function requires the solution of nonlinear partial differential equations to describe the impact of spatially distributed pumping and model parameters on model predictions for the spatial and temporal distribution of groundwater contaminants. The second application uses an asynchronous parallel global optimization for groundwater quality model calibration. The time for a single objective

Hemispheric specialization for global and local processing: A direct comparison of linguistic and non-linguistic stimuli.

PubMed

Brederoo, Sanne G; Nieuwenstein, Mark R; Lorist, Monicque M; Cornelissen, Frans W

2017-12-01

It is often assumed that the human brain processes the global and local properties of visual stimuli in a lateralized fashion, with a left hemisphere (LH) specialization for local detail, and a right hemisphere (RH) specialization for global form. However, the evidence for such global-local lateralization stems predominantly from studies using linguistic stimuli, the processing of which has shown to be LH lateralized in itself. In addition, some studies have reported a reversal of global-local lateralization when using non-linguistic stimuli. Accordingly, it remains unclear whether global-local lateralization may in fact be stimulus-specific. To address this issue, we asked participants to respond to linguistic and non-linguistic stimuli that were presented in the right and left visual fields, allowing for first access by the LH and RH, respectively. The results showed global-RH and local-LH advantages for both stimulus types, but the global lateralization effect was larger for linguistic stimuli. Furthermore, this pattern of results was found to be robust, as it was observed regardless of two other task manipulations. We conclude that the instantiation and direction of global and local lateralization is not stimulus-specific. However, the magnitude of global,-but not local-, lateralization is dependent on stimulus type. Copyright © 2017 Elsevier Inc. All rights reserved.

Assimilation of global versus local data sets into a regional model of the Gulf Stream system. 1. Data effectiveness

NASA Astrophysics Data System (ADS)

Malanotte-Rizzoli, Paola; Young, Roberta E.

1995-12-01

The primary objective of this paper is to assess the relative effectiveness of data sets with different space coverage and time resolution when they are assimilated into an ocean circulation model. We focus on obtaining realistic numerical simulations of the Gulf Stream system typically of the order of 3-month duration by constructing a "synthetic" ocean simultaneously consistent with the model dynamics and the observations. The model used is the Semispectral Primitive Equation Model. The data sets are the "global" Optimal Thermal Interpolation Scheme (OTIS) 3 of the Fleet Numerical Oceanography Center providing temperature and salinity fields with global coverage and with bi-weekly frequency, and the localized measurements, mostly of current velocities, from the central and eastern array moorings of the Synoptic Ocean Prediction (SYNOP) program, with daily frequency but with a very small spatial coverage. We use a suboptimal assimilation technique ("nudging"). Even though this technique has already been used in idealized data assimilation studies, to our knowledge this is the first study in which the effectiveness of nudging is tested by assimilating real observations of the interior temperature and salinity fields. This is also the first work in which a systematic assimilation is carried out of the localized, high-quality SYNOP data sets in numerical experiments longer than 1-2 weeks, that is, not aimed to forecasting. We assimilate (1) the global OTIS 3 alone, (2) the local SYNOP observations alone, and (3) both OTIS 3 and SYNOP observations. We assess the success of the assimilations with quantitative measures of performance, both on the global and local scale. The results can be summarized as follows. The intermittent assimilation of the global OTIS 3 is necessary to keep the model "on track" over 3-month simulations on the global scale. As OTIS 3 is assimilated at every model grid point, a "gentle" weight must be prescribed to it so as not to overconstrain

Fast globally optimal segmentation of 3D prostate MRI with axial symmetry prior.

PubMed

Qiu, Wu; Yuan, Jing; Ukwatta, Eranga; Sun, Yue; Rajchl, Martin; Fenster, Aaron

2013-01-01

We propose a novel global optimization approach to segmenting a given 3D prostate T2w magnetic resonance (MR) image, which enforces the inherent axial symmetry of the prostate shape and simultaneously performs a sequence of 2D axial slice-wise segmentations with a global 3D coherence prior. We show that the proposed challenging combinatorial optimization problem can be solved globally and exactly by means of convex relaxation. With this regard, we introduce a novel coupled continuous max-flow model, which is dual to the studied convex relaxed optimization formulation and leads to an efficient multiplier augmented algorithm based on the modern convex optimization theory. Moreover, the new continuous max-flow based algorithm was implemented on GPUs to achieve a substantial improvement in computation. Experimental results using public and in-house datasets demonstrate great advantages of the proposed method in terms of both accuracy and efficiency.

Recurrent Activation of Neural Circuits during Attention to Global and Local Visual Information.

PubMed

Iglesias-Fuster, Jorge; Piña-Novo, Daniela; Ontivero-Ortega, Marlis; Lage-Castellanos, Agustín; Valdés-Sosa, Mitchell

2018-05-28

The attentional selection of different hierarchical level within compound (Navon) figures has been studied with event related potentials (ERPs), by controlling the ERPs obtained during attention to the global or the local echelon. These studies, using the canonical Navon figures, have produced contradictory results, with doubts regarding the scalp distribution of the effects. Moreover, the evidence about the temporal evolution of the processing of these two levels is not clear. Here, we unveiled global and local letters at distinct times, which enabled separation of their ERP responses. We combine this approach with the temporal generalization methodology, a novel multivariate technique which facilitates exploring the temporal structure of these ERPs. Opposite lateralization patterns were obtained for the selection negativities generated when attending global and local distracters (D statistics, p < .005), with maxima in right and left occipito-temporal scalp regions, respectively (η2 = .111, p < .01; η2 = .042, p < .04). However, both discrimination negativities elicited when comparing targets and distractors at the global or the local level were lateralized to the left hemisphere (η2 = .25, p < .03 and η2 = .142, p < .05 respectively). Recurrent activation patterns were found for both global and local stimuli, with scalp topographies corresponding to early preparatory stages reemerging during the attentional selection process, thus indicating recursive attentional activation. This implies that selective attention to global and local hierarchical levels recycles similar neural correlates at different time points. These neural correlates appear to be mediated by visual extra-striate areas.

Bringing the Global Home: Students Research Local Areas through Postcolonial Perspectives

ERIC Educational Resources Information Center

Hammer, Ricarda

2018-01-01

This article describes a class that draws on postcolonial insights to create a global sociological imagination. Postcolonial approaches can make visible how global connections have shaped our local environments even if these relations are not always immediately visible. Specifically, students in this class highlight how global relations, such as…

Residue-level global and local ensemble-ensemble comparisons of protein domains.

PubMed

Clark, Sarah A; Tronrud, Dale E; Karplus, P Andrew

2015-09-01

Many methods of protein structure generation such as NMR-based solution structure determination and template-based modeling do not produce a single model, but an ensemble of models consistent with the available information. Current strategies for comparing ensembles lose information because they use only a single representative structure. Here, we describe the ENSEMBLATOR and its novel strategy to directly compare two ensembles containing the same atoms to identify significant global and local backbone differences between them on per-atom and per-residue levels, respectively. The ENSEMBLATOR has four components: eePREP (ee for ensemble-ensemble), which selects atoms common to all models; eeCORE, which identifies atoms belonging to a cutoff-distance dependent common core; eeGLOBAL, which globally superimposes all models using the defined core atoms and calculates for each atom the two intraensemble variations, the interensemble variation, and the closest approach of members of the two ensembles; and eeLOCAL, which performs a local overlay of each dipeptide and, using a novel measure of local backbone similarity, reports the same four variations as eeGLOBAL. The combination of eeGLOBAL and eeLOCAL analyses identifies the most significant differences between ensembles. We illustrate the ENSEMBLATOR's capabilities by showing how using it to analyze NMR ensembles and to compare NMR ensembles with crystal structures provides novel insights compared to published studies. One of these studies leads us to suggest that a "consistency check" of NMR-derived ensembles may be a useful analysis step for NMR-based structure determinations in general. The ENSEMBLATOR 1.0 is available as a first generation tool to carry out ensemble-ensemble comparisons. © 2015 The Protein Society.

Residue-level global and local ensemble-ensemble comparisons of protein domains

PubMed Central

Clark, Sarah A; Tronrud, Dale E; Andrew Karplus, P

2015-01-01

Many methods of protein structure generation such as NMR-based solution structure determination and template-based modeling do not produce a single model, but an ensemble of models consistent with the available information. Current strategies for comparing ensembles lose information because they use only a single representative structure. Here, we describe the ENSEMBLATOR and its novel strategy to directly compare two ensembles containing the same atoms to identify significant global and local backbone differences between them on per-atom and per-residue levels, respectively. The ENSEMBLATOR has four components: eePREP (ee for ensemble-ensemble), which selects atoms common to all models; eeCORE, which identifies atoms belonging to a cutoff-distance dependent common core; eeGLOBAL, which globally superimposes all models using the defined core atoms and calculates for each atom the two intraensemble variations, the interensemble variation, and the closest approach of members of the two ensembles; and eeLOCAL, which performs a local overlay of each dipeptide and, using a novel measure of local backbone similarity, reports the same four variations as eeGLOBAL. The combination of eeGLOBAL and eeLOCAL analyses identifies the most significant differences between ensembles. We illustrate the ENSEMBLATOR's capabilities by showing how using it to analyze NMR ensembles and to compare NMR ensembles with crystal structures provides novel insights compared to published studies. One of these studies leads us to suggest that a “consistency check” of NMR-derived ensembles may be a useful analysis step for NMR-based structure determinations in general. The ENSEMBLATOR 1.0 is available as a first generation tool to carry out ensemble-ensemble comparisons. PMID:26032515

Optimizing low latency LIGO-Virgo localization

NASA Astrophysics Data System (ADS)

Chen, Hsin-Yu; Holz, Daniel

2015-04-01

Fast and effective localization of gravitational wave (GW) events could play a crucial role in identifying possible electromagnetic counterparts, and thereby help usher in an era of GW multi-messenger astronomy. We discuss an algorithm for accurate and very low latency (<< 1 second) localization of GW sources using only the time of arrival and signal-to-noise ratio at each detector. The algorithm is independent of distances, masses, and waveform templates of the sources to leading order, and applies to all discrete sources detected by ground-based detector networks. For the two detector configuration (LIGO Hanford+Livingston) expected in late 2015 we find a median 50% localization of 150 deg2 for binary neutron stars (for SNR threshold of 12), consistent with previous findings. We explore the improvement in localization resulting from high SNR events, finding that the loudest out of the first four events reduces the median sky localization area by a factor of 1.8. We also discuss some strategies to optimize electromagnetic follow-up of GW events. We specifically explore the case of multi-messenger joint detections coming from independent (and possibly highly uncertain) localizations, such as for short gamma-ray bursts observed by Fermi GBM and neutrinos captured by IceCube.

Global/local processing style: Explaining the relationship between trait anxiety and binge eating.

PubMed

Becker, Kendra R; Plessow, Franziska; Coniglio, Kathryn A; Tabri, Nassim; Franko, Debra L; Zayas, Lazaro V; Germine, Laura; Thomas, Jennifer J; Eddy, Kamryn T

2017-11-01

Anxiety is a risk factor for disordered eating, but the mechanisms by which anxiety promotes disordered eating are poorly understood. One possibility is local versus global cognitive processing style, defined as a relative tendency to attend to details at the expense of the "big picture." Anxiety may narrow attention, in turn, enhancing local and/or compromising global processing. We examined relationships between global/local processing style, anxiety, and disordered eating behaviors in a transdiagnostic outpatient clinical sample. We hypothesized that local (vs. global) processing bias would mediate the relationship between anxiety and disordered eating behaviors. Ninety-three participants completed the eating disorder examination-questionnaire (EDE-Q), State-Trait Anxiety Inventory (STAI)-trait subscale, and the Navon task (a test of processing style in which large letters are composed of smaller letters both congruent and incongruent with the large letter). The sample was predominantly female (95%) with a mean age of 27.4 years (SD = 12.1 years). Binge eating, but not fasting, purging, or excessive exercise, was correlated with lower levels of global processing style. There was a significant indirect effect between anxiety and binge eating via reduced global level global/local processing. In individuals with disordered eating, being more generally anxious may encourage a detailed-oriented bias, preventing individuals from maintaining the bigger picture and making them more likely to engage in maladaptive behaviors (e.g., binge eating). © 2017 Wiley Periodicals, Inc.

Global/local processing style: Explaining the relationship between trait anxiety and binge eating

PubMed Central

Becker, Kendra R.; Plessow, Franziska; Coniglio, Kathryn A.; Tabri, Nassim; Franko, Debra L; Zayas, Lazaro V.; Germine, Laura; Thomas, Jennifer J.; Eddy, Kamryn T.

2018-01-01

Objective Anxiety is a risk factor for disordered eating, but the mechanisms by which anxiety promotes disordered eating are poorly understood. One possibility is local versus global cognitive processing style, defined as a relative tendency to attend to details at the expense of the “big picture.” Anxiety may narrow attention, in turn, enhancing local and/or compromising global processing. We examined relationships between global/local processing style, anxiety, and disordered eating behaviors in a transdiagnostic outpatient clinical sample. We hypothesized that local (vs. global) processing bias would mediate the relationship between anxiety and disordered eating behaviors. Method Ninety-three participants completed the eating disorder examination—questionnaire (EDE-Q), State-Trait Anxiety Inventory (STAI)—trait subscale, and the Navon task (a test of processing style in which large letters are composed of smaller letters both congruent and incongruent with the large letter). The sample was predominantly female (95%) with a mean age of 27.4 years (SD = 12.1 years). Results Binge eating, but not fasting, purging, or excessive exercise, was correlated with lower levels of global processing style. There was a significant indirect effect between anxiety and binge eating via reduced global level global/local processing. Discussion In individuals with disordered eating, being more generally anxious may encourage a detailed-oriented bias, preventing individuals from maintaining the bigger picture and making them more likely to engage in maladaptive behaviors (e.g., binge eating). PMID:28963792

Local/Global Cognitive Interfaces within Industrial Districts: An Italian Case Study

ERIC Educational Resources Information Center

Grandinetti, Roberto

2011-01-01

Purpose: With the advance of globalization the competitive chances of industrial districts depends increasingly on their ability to connect to the cognitive circuits of the global economy. This challenge demands the presence of local actors capable of acting as cognitive interfaces between the district context and the global environment. The paper…

The Mountain Invasion Research Network (MIREN): Linking Local and Global Scales for Addressing an Ecological Consequence of Global Change

Treesearch

Christoph Kueffer; Curtis Daehler; Hansjörg Dietz; Keith McDougall; Catherine Parks; Aníbal Pauchard; Lisa Rew

2014-01-01

Many modern environmental problems span vastly different spatial scales, from the management of local ecosystems to understanding globally interconnected processes, and addressing them through international policy. MIREN tackles one such “glocal” (global/local) environmental problem – plant invasions in mountains – through a transdisciplinary, multi-scale learning...

Zooming into creativity: individual differences in attentional global-local biases are linked to creative thinking.

PubMed

Zmigrod, Sharon; Zmigrod, Leor; Hommel, Bernhard

2015-01-01

While recent studies have investigated how processes underlying human creativity are affected by particular visual-attentional states, we tested the impact of more stable attention-related preferences. These were assessed by means of Navon's global-local task, in which participants respond to the global or local features of large letters constructed from smaller letters. Three standard measures were derived from this task: the sizes of the global precedence effect, the global interference effect (i.e., the impact of incongruent letters at the global level on local processing), and the local interference effect (i.e., the impact of incongruent letters at the local level on global processing). These measures were correlated with performance in a convergent-thinking creativity task (the Remote Associates Task), a divergent-thinking creativity task (the Alternate Uses Task), and a measure of fluid intelligence (Raven's matrices). Flexibility in divergent thinking was predicted by the local interference effect while convergent thinking was predicted by intelligence only. We conclude that a stronger attentional bias to visual information about the "bigger picture" promotes cognitive flexibility in searching for multiple solutions.

The role of health promotion: between global thinking and local action.

PubMed

King, Lesley

2006-12-01

The persistence of health inequities provides an ongoing challenge for health promotion. The dictum 'think globally, act locally' fails to recognise the significance of infrastructure and policy in linking global issues and local practices as a means of addressing health inequities. Commentary and opinion. Through analytic tools and methods, health promotion has much to contribute to facilitating health-improving changes in social, economic and physical environments. Local actions provide excellent illustrations of organisational change and intersectoral action, and present the possibility that such actions could be widely implemented. While this has occurred on some issues, this is not usually the case. Political support, policy and infrastructure are required to link global ideas and local actions and overcome the impasse. Media advocacy is one example of an approach with potential to make these links and mobilise political support. Reframing media and political discussion, away from the dichotomy of individual responsibility and government intervention and towards acknowledging the social context of human behaviour, could contribute to policy and social environments with greater capacity to address inequities.

Fostering Local Knowledge and Human Development in Globalization of Education

ERIC Educational Resources Information Center

Cheng, Yin Cheong

2004-01-01

Since there are increasing international concerns with both the positive and negative impacts of globalization on indigenous and national development, how to manage the realities and practices of globalization and localization in education for maximizing the benefits and minimizing the disadvantages for the development of individuals and their…

Cultural Variations in Global versus Local Processing: A Developmental Perspective

ERIC Educational Resources Information Center

Oishi, Shigehiro; Jaswal, Vikram K.; Lillard, Angeline S.; Mizokawa, Ai; Hitokoto, Hidefumi; Tsutsui, Yoshiro

2014-01-01

We conducted 3 studies to explore cultural differences in global versus local processing and their developmental trajectories. In Study 1 ("N" = 363), we found that Japanese college students were less globally oriented in their processing than American or Argentine participants. We replicated this effect in Study 2 ("N" =…

Interior search algorithm (ISA): a novel approach for global optimization.

PubMed

Gandomi, Amir H

2014-07-01

This paper presents the interior search algorithm (ISA) as a novel method for solving optimization tasks. The proposed ISA is inspired by interior design and decoration. The algorithm is different from other metaheuristic algorithms and provides new insight for global optimization. The proposed method is verified using some benchmark mathematical and engineering problems commonly used in the area of optimization. ISA results are further compared with well-known optimization algorithms. The results show that the ISA is efficiently capable of solving optimization problems. The proposed algorithm can outperform the other well-known algorithms. Further, the proposed algorithm is very simple and it only has one parameter to tune. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Global effects of local food-production crises: a virtual water perspective

PubMed Central

Tamea, Stefania; Laio, Francesco; Ridolfi, Luca

2016-01-01

By importing food and agricultural goods, countries cope with the heterogeneous global water distribution and often rely on water resources available abroad. The virtual displacement of the water used to produce such goods (known as virtual water) connects together, in a global water system, all countries participating to the international trade network. Local food-production crises, having social, economic or environmental origin, propagate in this network, modifying the virtual water trade and perturbing local and global food availability, quantified in terms of virtual water. We analyze here the possible effects of local crises by developing a new propagation model, parsimonious but grounded on data-based and statistically-verified assumptions, whose effectiveness is proved on the Argentinean crisis in 2008–09. The model serves as the basis to propose indicators of crisis impact and country vulnerability to external food-production crises, which highlight that countries with largest water resources have the highest impact on the international trade, and that not only water-scarce but also wealthy and globalized countries are among the most vulnerable to external crises. The temporal analysis reveals that global average vulnerability has increased over time and that stronger effects of crises are now found in countries with low food (and water) availability. PMID:26804492

Global effects of local food-production crises: a virtual water perspective.

PubMed

Tamea, Stefania; Laio, Francesco; Ridolfi, Luca

2016-01-25

By importing food and agricultural goods, countries cope with the heterogeneous global water distribution and often rely on water resources available abroad. The virtual displacement of the water used to produce such goods (known as virtual water) connects together, in a global water system, all countries participating to the international trade network. Local food-production crises, having social, economic or environmental origin, propagate in this network, modifying the virtual water trade and perturbing local and global food availability, quantified in terms of virtual water. We analyze here the possible effects of local crises by developing a new propagation model, parsimonious but grounded on data-based and statistically-verified assumptions, whose effectiveness is proved on the Argentinean crisis in 2008-09. The model serves as the basis to propose indicators of crisis impact and country vulnerability to external food-production crises, which highlight that countries with largest water resources have the highest impact on the international trade, and that not only water-scarce but also wealthy and globalized countries are among the most vulnerable to external crises. The temporal analysis reveals that global average vulnerability has increased over time and that stronger effects of crises are now found in countries with low food (and water) availability.

Global effects of local food-production crises: a virtual water perspective

NASA Astrophysics Data System (ADS)

Tamea, Stefania; Laio, Francesco; Ridolfi, Luca

2016-01-01

By importing food and agricultural goods, countries cope with the heterogeneous global water distribution and often rely on water resources available abroad. The virtual displacement of the water used to produce such goods (known as virtual water) connects together, in a global water system, all countries participating to the international trade network. Local food-production crises, having social, economic or environmental origin, propagate in this network, modifying the virtual water trade and perturbing local and global food availability, quantified in terms of virtual water. We analyze here the possible effects of local crises by developing a new propagation model, parsimonious but grounded on data-based and statistically-verified assumptions, whose effectiveness is proved on the Argentinean crisis in 2008-09. The model serves as the basis to propose indicators of crisis impact and country vulnerability to external food-production crises, which highlight that countries with largest water resources have the highest impact on the international trade, and that not only water-scarce but also wealthy and globalized countries are among the most vulnerable to external crises. The temporal analysis reveals that global average vulnerability has increased over time and that stronger effects of crises are now found in countries with low food (and water) availability.

Multiple measures of dispositional global/local bias predict attentional blink magnitude.

PubMed

Dale, Gillian; Arnell, Karen M

2015-07-01

When the second of two targets (T2) is presented temporally close to the first target (T1) in a rapid serial visual presentation stream, accuracy to identify T2 is markedly reduced-an attentional blink (AB). While most individuals show an AB, Dale and Arnell (Atten Percept Psychophys 72(3):602-606, 2010) demonstrated that individual differences in dispositional attentional focus predicted AB performance, such that individuals who showed a natural bias toward the global level of Navon letter stimuli were less susceptible to the AB and showed a smaller AB effect. For the current study, we extended the findings of Dale and Arnell (Atten Percept Psychophys 72(3):602-606, 2010) through two experiments. In Experiment 1, we examined the relationship between dispositional global/local bias and the AB using a highly reliable hierarchical shape task measure. In Experiment 2, we examined whether three distinct global/local measures could predict AB performance. In both experiments, performance on the global/local tasks predicted subsequent AB performance, such that individuals with a greater preference for the global information showed a reduced AB. This supports previous findings, as well as recent models which discuss the role of attentional breadth in selective attention.

Optimal design of geodesically stiffened composite cylindrical shells

NASA Technical Reports Server (NTRS)

Gendron, G.; Guerdal, Z.

1992-01-01

An optimization system based on the finite element code Computations Structural Mechanics (CSM) Testbed and the optimization program, Automated Design Synthesis (ADS), is described. The optimization system can be used to obtain minimum-weight designs of composite stiffened structures. Ply thickness, ply orientations, and stiffener heights can be used as design variables. Buckling, displacement, and material failure constraints can be imposed on the design. The system is used to conduct a design study of geodesically stiffened shells. For comparison purposes, optimal designs of unstiffened shells and shells stiffened by rings and stingers are also obtained. Trends in the design of geodesically stiffened shells are identified. An approach to include local stress concentrations during the design optimization process is then presented. The method is based on a global/local analysis technique. It employs spline interpolation functions to determine displacements and rotations from a global model which are used as 'boundary conditions' for the local model. The organization of the strategy in the context of an optimization process is described. The method is validated with an example.

Method for using global optimization to the estimation of surface-consistent residual statics

DOEpatents

Reister, David B.; Barhen, Jacob; Oblow, Edward M.

2001-01-01

An efficient method for generating residual statics corrections to compensate for surface-consistent static time shifts in stacked seismic traces. The method includes a step of framing the residual static corrections as a global optimization problem in a parameter space. The method also includes decoupling the global optimization problem involving all seismic traces into several one-dimensional problems. The method further utilizes a Stochastic Pijavskij Tunneling search to eliminate regions in the parameter space where a global minimum is unlikely to exist so that the global minimum may be quickly discovered. The method finds the residual statics corrections by maximizing the total stack power. The stack power is a measure of seismic energy transferred from energy sources to receivers.

Three-dimensional unstructured grid generation via incremental insertion and local optimization

NASA Technical Reports Server (NTRS)

Barth, Timothy J.; Wiltberger, N. Lyn; Gandhi, Amar S.

1992-01-01

Algorithms for the generation of 3D unstructured surface and volume grids are discussed. These algorithms are based on incremental insertion and local optimization. The present algorithms are very general and permit local grid optimization based on various measures of grid quality. This is very important; unlike the 2D Delaunay triangulation, the 3D Delaunay triangulation appears not to have a lexicographic characterization of angularity. (The Delaunay triangulation is known to minimize that maximum containment sphere, but unfortunately this is not true lexicographically). Consequently, Delaunay triangulations in three-space can result in poorly shaped tetrahedral elements. Using the present algorithms, 3D meshes can be constructed which optimize a certain angle measure, albeit locally. We also discuss the combinatorial aspects of the algorithm as well as implementational details.

CFD simulation of local and global mixing time in an agitated tank

NASA Astrophysics Data System (ADS)

Li, Liangchao; Xu, Bin

2017-01-01

The Issue of mixing efficiency in agitated tanks has drawn serious concern in many industrial processes. The turbulence model is very critical to predicting mixing process in agitated tanks. On the basis of computational fluid dynamics(CFD) software package Fluent 6.2, the mixing characteristics in a tank agitated by dual six-blade-Rushton-turbines(6-DT) are predicted using the detached eddy simulation(DES) method. A sliding mesh(SM) approach is adopted to solve the rotation of the impeller. The simulated flow patterns and liquid velocities in the agitated tank are verified by experimental data in the literature. The simulation results indicate that the DES method can obtain more flow details than Reynolds-averaged Navier-Stokes(RANS) model. Local and global mixing time in the agitated tank is predicted by solving a tracer concentration scalar transport equation. The simulated results show that feeding points have great influence on mixing process and mixing time. Mixing efficiency is the highest for the feeding point at location of midway of the two impellers. Two methods are used to determine global mixing time and get close result. Dimensionless global mixing time remains unchanged with increasing of impeller speed. Parallel, merging and diverging flow pattern form in the agitated tank, respectively, by changing the impeller spacing and clearance of lower impeller from the bottom of the tank. The global mixing time is the shortest for the merging flow, followed by diverging flow, and the longest for parallel flow. The research presents helpful references for design, optimization and scale-up of agitated tanks with multi-impeller.

Children inhibit global information when the forest is dense and local information when the forest is sparse.

PubMed

Krakowski, Claire-Sara; Borst, Grégoire; Vidal, Julie; Houdé, Olivier; Poirel, Nicolas

2018-09-01

Visual environments are composed of global shapes and local details that compete for attentional resources. In adults, the global level is processed more rapidly than the local level, and global information must be inhibited in order to process local information when the local information and global information are in conflict. Compared with adults, children present less of a bias toward global visual information and appear to be more sensitive to the density of local elements that constitute the global level. The current study aimed, for the first time, to investigate the key role of inhibition during global/local processing in children. By including two different conditions of global saliency during a negative priming procedure, the results showed that when the global level was salient (dense hierarchical figures), 7-year-old children and adults needed to inhibit the global level to process the local information. However, when the global level was less salient (sparse hierarchical figures), only children needed to inhibit the local level to process the global information. These results confirm a weaker global bias and the greater impact of saliency in children than in adults. Moreover, the results indicate that, regardless of age, inhibition of the most salient hierarchical level is systematically required to select the less salient but more relevant level. These findings have important implications for future research in this area. Copyright © 2018 Elsevier Inc. All rights reserved.

Correlation and network topologies in global and local stock indices

NASA Astrophysics Data System (ADS)

Nobi, Ashadun; Lee, Sungmin; Kim, Doo Hwan; Lee, Jae Woo

2014-07-01

We examined how the correlation and network structure of the global indices and local Korean indices have changed during years 2000-2012. The average correlations of the global indices increased with time, while the local indices showed a decreasing trend except for drastic changes during the crises. A significant change in the network topologies was observed due to the financial crises in both markets. The Jaccard similarities identified the change in the market state due to a crisis in both markets. The dynamic change of the Jaccard index can be used as an indicator of systemic risk or precursors of the crisis.

Local and global responses in complex gene regulation networks

NASA Astrophysics Data System (ADS)

Tsuchiya, Masa; Selvarajoo, Kumar; Piras, Vincent; Tomita, Masaru; Giuliani, Alessandro

2009-04-01

An exacerbated sensitivity to apparently minor stimuli and a general resilience of the entire system stay together side-by-side in biological systems. This apparent paradox can be explained by the consideration of biological systems as very strongly interconnected network systems. Some nodes of these networks, thanks to their peculiar location in the network architecture, are responsible for the sensitivity aspects, while the large degree of interconnection is at the basis of the resilience properties of the system. One relevant feature of the high degree of connectivity of gene regulation networks is the emergence of collective ordered phenomena influencing the entire genome and not only a specific portion of transcripts. The great majority of existing gene regulation models give the impression of purely local ‘hard-wired’ mechanisms disregarding the emergence of global ordered behavior encompassing thousands of genes while the general, genome wide, aspects are less known. Here we address, on a data analysis perspective, the discrimination between local and global scale regulations, this goal was achieved by means of the examination of two biological systems: innate immune response in macrophages and oscillating growth dynamics in yeast. Our aim was to reconcile the ‘hard-wired’ local view of gene regulation with a global continuous and scalable one borrowed from statistical physics. This reconciliation is based on the network paradigm in which the local ‘hard-wired’ activities correspond to the activation of specific crucial nodes in the regulation network, while the scalable continuous responses can be equated to the collective oscillations of the network after a perturbation.

WATER CONSERVATION: LOCAL SOLUTIONS TO A GLOBAL PROBLEM

EPA Science Inventory

Water conservation issues are discussed. Local solutions to a global problem include changing old habits relating to the usage and abuse of water resources. While the suggested behavioral changes may not solve the world's pending water crisis, they may ease the impact of the l...

Evaluation Methodology between Globalization and Localization Features Approaches for Skin Cancer Lesions Classification

NASA Astrophysics Data System (ADS)

Ahmed, H. M.; Al-azawi, R. J.; Abdulhameed, A. A.

2018-05-01

Huge efforts have been put in the developing of diagnostic methods to skin cancer disease. In this paper, two different approaches have been addressed for detection the skin cancer in dermoscopy images. The first approach uses a global method that uses global features for classifying skin lesions, whereas the second approach uses a local method that uses local features for classifying skin lesions. The aim of this paper is selecting the best approach for skin lesion classification. The dataset has been used in this paper consist of 200 dermoscopy images from Pedro Hispano Hospital (PH2). The achieved results are; sensitivity about 96%, specificity about 100%, precision about 100%, and accuracy about 97% for globalization approach while, sensitivity about 100%, specificity about 100%, precision about 100%, and accuracy about 100% for Localization Approach, these results showed that the localization approach achieved acceptable accuracy and better than globalization approach for skin cancer lesions classification.

Pivot methods for global optimization

NASA Astrophysics Data System (ADS)

Stanton, Aaron Fletcher

A new algorithm is presented for the location of the global minimum of a multiple minima problem. It begins with a series of randomly placed probes in phase space, and then uses an iterative redistribution of the worst probes into better regions of phase space until a chosen convergence criterion is fulfilled. The method quickly converges, does not require derivatives, and is resistant to becoming trapped in local minima. Comparison of this algorithm with others using a standard test suite demonstrates that the number of function calls has been decreased conservatively by a factor of about three with the same degrees of accuracy. Two major variations of the method are presented, differing primarily in the method of choosing the probes that act as the basis for the new probes. The first variation, termed the lowest energy pivot method, ranks all probes by their energy and keeps the best probes. The probes being discarded select from those being kept as the basis for the new cycle. In the second variation, the nearest neighbor pivot method, all probes are paired with their nearest neighbor. The member of each pair with the higher energy is relocated in the vicinity of its neighbor. Both methods are tested against a standard test suite of functions to determine their relative efficiency, and the nearest neighbor pivot method is found to be the more efficient. A series of Lennard-Jones clusters is optimized with the nearest neighbor method, and a scaling law is found for cpu time versus the number of particles in the system. The two methods are then compared more explicitly, and finally a study in the use of the pivot method for solving the Schroedinger equation is presented. The nearest neighbor method is found to be able to solve the ground state of the quantum harmonic oscillator from a pure random initialization of the wavefunction.

Zooming into creativity: individual differences in attentional global-local biases are linked to creative thinking

PubMed Central

Zmigrod, Sharon; Zmigrod, Leor; Hommel, Bernhard

2015-01-01

While recent studies have investigated how processes underlying human creativity are affected by particular visual-attentional states, we tested the impact of more stable attention-related preferences. These were assessed by means of Navon’s global-local task, in which participants respond to the global or local features of large letters constructed from smaller letters. Three standard measures were derived from this task: the sizes of the global precedence effect, the global interference effect (i.e., the impact of incongruent letters at the global level on local processing), and the local interference effect (i.e., the impact of incongruent letters at the local level on global processing). These measures were correlated with performance in a convergent-thinking creativity task (the Remote Associates Task), a divergent-thinking creativity task (the Alternate Uses Task), and a measure of fluid intelligence (Raven’s matrices). Flexibility in divergent thinking was predicted by the local interference effect while convergent thinking was predicted by intelligence only. We conclude that a stronger attentional bias to visual information about the “bigger picture” promotes cognitive flexibility in searching for multiple solutions. PMID:26579030

Optimal Verification of Entangled States with Local Measurements

NASA Astrophysics Data System (ADS)

Pallister, Sam; Linden, Noah; Montanaro, Ashley

2018-04-01

Consider the task of verifying that a given quantum device, designed to produce a particular entangled state, does indeed produce that state. One natural approach would be to characterize the output state by quantum state tomography, or alternatively, to perform some kind of Bell test, tailored to the state of interest. We show here that neither approach is optimal among local verification strategies for 2-qubit states. We find the optimal strategy in this case and show that quadratically fewer total measurements are needed to verify to within a given fidelity than in published results for quantum state tomography, Bell test, or fidelity estimation protocols. We also give efficient verification protocols for any stabilizer state. Additionally, we show that requiring that the strategy be constructed from local, nonadaptive, and noncollective measurements only incurs a constant-factor penalty over a strategy without these restrictions.

Cooperative global optimal preview tracking control of linear multi-agent systems: an internal model approach

NASA Astrophysics Data System (ADS)

Lu, Yanrong; Liao, Fucheng; Deng, Jiamei; Liu, Huiyang

2017-09-01

This paper investigates the cooperative global optimal preview tracking problem of linear multi-agent systems under the assumption that the output of a leader is a previewable periodic signal and the topology graph contains a directed spanning tree. First, a type of distributed internal model is introduced, and the cooperative preview tracking problem is converted to a global optimal regulation problem of an augmented system. Second, an optimal controller, which can guarantee the asymptotic stability of the augmented system, is obtained by means of the standard linear quadratic optimal preview control theory. Third, on the basis of proving the existence conditions of the controller, sufficient conditions are given for the original problem to be solvable, meanwhile a cooperative global optimal controller with error integral and preview compensation is derived. Finally, the validity of theoretical results is demonstrated by a numerical simulation.

Towards Social Radiology as an Information Infrastructure: Reconciling the Local With the Global

PubMed Central

2014-01-01

The current widespread use of medical images and imaging procedures in clinical practice and patient diagnosis has brought about an increase in the demand for sharing medical imaging studies among health professionals in an easy and effective manner. This article reveals the existence of a polarization between the local and global demands for radiology practice. While there are no major barriers for sharing such studies, when access is made from a (local) picture archive and communication system (PACS) within the domain of a healthcare organization, there are a number of impediments for sharing studies among health professionals on a global scale. Social radiology as an information infrastructure involves the notion of a shared infrastructure as a public good, affording a social space where people, organizations and technical components may spontaneously form associations in order to share clinical information linked to patient care and radiology practice. This article shows however, that such polarization establishes a tension between local and global demands, which hinders the emergence of social radiology as an information infrastructure. Based on an analysis of the social space for radiology practice, the present article has observed that this tension persists due to the inertia of a locally installed base in radiology departments, for which common teleradiology models are not truly capable of reorganizing as a global social space for radiology practice. Reconciling the local with the global signifies integrating PACS and teleradiology into an evolving, secure, heterogeneous, shared, open information infrastructure where the conceptual boundaries between (local) PACS and (global) teleradiology are transparent, signaling the emergence of social radiology as an information infrastructure. PMID:25600710

A survey of compiler optimization techniques

NASA Technical Reports Server (NTRS)

Schneck, P. B.

1972-01-01

Major optimization techniques of compilers are described and grouped into three categories: machine dependent, architecture dependent, and architecture independent. Machine-dependent optimizations tend to be local and are performed upon short spans of generated code by using particular properties of an instruction set to reduce the time or space required by a program. Architecture-dependent optimizations are global and are performed while generating code. These optimizations consider the structure of a computer, but not its detailed instruction set. Architecture independent optimizations are also global but are based on analysis of the program flow graph and the dependencies among statements of source program. A conceptual review of a universal optimizer that performs architecture-independent optimizations at source-code level is also presented.

Patch-based automatic retinal vessel segmentation in global and local structural context.

PubMed

Cao, Shuoying; Bharath, Anil A; Parker, Kim H; Ng, Jeffrey

2012-01-01

In this paper, we extend our published work [1] and propose an automated system to segment retinal vessel bed in digital fundus images with enough adaptability to analyze images from fluorescein angiography. This approach takes into account both the global and local context and enables both vessel segmentation and microvascular centreline extraction. These tools should allow researchers and clinicians to estimate and assess vessel diameter, capillary blood volume and microvascular topology for early stage disease detection, monitoring and treatment. Global vessel bed segmentation is achieved by combining phase-invariant orientation fields with neighbourhood pixel intensities in a patch-based feature vector for supervised learning. This approach is evaluated against benchmarks on the DRIVE database [2]. Local microvascular centrelines within Regions-of-Interest (ROIs) are segmented by linking the phase-invariant orientation measures with phase-selective local structure features. Our global and local structural segmentation can be used to assess both pathological structural alterations and microemboli occurrence in non-invasive clinical settings in a longitudinal study.

A fingerprint classification algorithm based on combination of local and global information

NASA Astrophysics Data System (ADS)

Liu, Chongjin; Fu, Xiang; Bian, Junjie; Feng, Jufu

2011-12-01

Fingerprint recognition is one of the most important technologies in biometric identification and has been wildly applied in commercial and forensic areas. Fingerprint classification, as the fundamental procedure in fingerprint recognition, can sharply decrease the quantity for fingerprint matching and improve the efficiency of fingerprint recognition. Most fingerprint classification algorithms are based on the number and position of singular points. Because the singular points detecting method only considers the local information commonly, the classification algorithms are sensitive to noise. In this paper, we propose a novel fingerprint classification algorithm combining the local and global information of fingerprint. Firstly we use local information to detect singular points and measure their quality considering orientation structure and image texture in adjacent areas. Furthermore the global orientation model is adopted to measure the reliability of singular points group. Finally the local quality and global reliability is weighted to classify fingerprint. Experiments demonstrate the accuracy and effectivity of our algorithm especially for the poor quality fingerprint images.

Translating Globalization and Democratization into Local Policy: Educational Reform in Hong Kong and Taiwan

NASA Astrophysics Data System (ADS)

Law, Wing-Wah

2004-11-01

The past two decades have witnessed three important international trends: an increase in the number of democratic states; economic globalization; and educational reforms in light of the challenges of the new millennium. A great deal of research has addressed educational change in relation to either globalization or democratization, but little has been said about the complex interactions among all three processes. In view of recent educational reforms in Hong Kong and Taiwan, the present contribution examines the local nature of education policy in a globalized age. It challenges those globalization theories which minimize the role of the state and exaggerate the power of globalization over local factors. In particular, it explores how the governments of these two Chinese societies have employed democratization to generate and legitimate reform proposals and have used economic globalization to justify educational reforms. The study concludes by discussing the complex interrelations of these processes, including tensions between global and local concerns in educational reform.

Proposal of Evolutionary Simplex Method for Global Optimization Problem

NASA Astrophysics Data System (ADS)

Shimizu, Yoshiaki

To make an agile decision in a rational manner, role of optimization engineering has been notified increasingly under diversified customer demand. With this point of view, in this paper, we have proposed a new evolutionary method serving as an optimization technique in the paradigm of optimization engineering. The developed method has prospects to solve globally various complicated problem appearing in real world applications. It is evolved from the conventional method known as Nelder and Mead’s Simplex method by virtue of idea borrowed from recent meta-heuristic method such as PSO. Mentioning an algorithm to handle linear inequality constraints effectively, we have validated effectiveness of the proposed method through comparison with other methods using several benchmark problems.

Global and Local Pitch Perception in Children with Developmental Dyslexia

ERIC Educational Resources Information Center

Ziegler, Johannes C.; Pech-Georgel, Catherine; George, Florence; Foxton, Jessica M.

2012-01-01

This study investigated global versus local pitch pattern perception in children with dyslexia aged between 8 and 11 years. Children listened to two consecutive 4-tone pitch sequences while performing a same/different task. On the different trials, sequences either preserved the contour (local condition) or they violated the contour (global…

Testing neuropsychological hypotheses for cognitive deficits in psychopathic criminals: a study of global-local processing.

PubMed

Kosson, David S; Miller, Sarah K; Byrnes, Katherine A; Leveroni, Catherine L

2007-03-01

Competing hypotheses about neuropsychological mechanisms underlying psychopathy are seldom examined in the same study. We tested the left hemisphere activation hypothesis and the response modulation hypothesis of psychopathy in 172 inmates completing a global-local processing task under local bias, global bias, and neutral conditions. Consistent with the left hemisphere activation hypothesis, planned comparisons showed that psychopathic inmates classified local targets more slowly than nonpsychopathic inmates in a local bias condition and exhibited a trend toward similar deficits for global targets in this condition. However, contrary to the response modulation hypothesis, psychopaths were no slower to respond to local targets in a global bias condition. Because psychopathic inmates were not generally slower to respond to local targets, results are also not consistent with a general left hemisphere dysfunction account. Correlational analyses also indicated deficits specific to conditions presenting most targets at the local level initially. Implications for neuropsychological conceptualizations of psychopathy are considered.

GLOBAL SOLUTIONS TO FOLDED CONCAVE PENALIZED NONCONVEX LEARNING

PubMed Central

Liu, Hongcheng; Yao, Tao; Li, Runze

2015-01-01

This paper is concerned with solving nonconvex learning problems with folded concave penalty. Despite that their global solutions entail desirable statistical properties, there lack optimization techniques that guarantee global optimality in a general setting. In this paper, we show that a class of nonconvex learning problems are equivalent to general quadratic programs. This equivalence facilitates us in developing mixed integer linear programming reformulations, which admit finite algorithms that find a provably global optimal solution. We refer to this reformulation-based technique as the mixed integer programming-based global optimization (MIPGO). To our knowledge, this is the first global optimization scheme with a theoretical guarantee for folded concave penalized nonconvex learning with the SCAD penalty (Fan and Li, 2001) and the MCP penalty (Zhang, 2010). Numerical results indicate a significant outperformance of MIPGO over the state-of-the-art solution scheme, local linear approximation, and other alternative solution techniques in literature in terms of solution quality. PMID:27141126

Implications for local and global climate of alternative forest management strategies in Norway

NASA Astrophysics Data System (ADS)

Bright, Ryan M.; Antón-Fernández, Clara; Astrup, Rasmus; Cherubini, Francesco; Kvalevåg, Maria; Hammer Strømman, Anders

2014-05-01

We applied a mix of observation and empirical models to evaluate both local and global climate effects of three realistic alternative forest management scenarios in the boreal forests of Norway's largest logging region. The alternative management scenarios embraced strategies aimed at increasing harvest intensities and allowing harvested conifer sites to regenerate naturally with broadleaved species. Stand-level analysis was firstly executed to attribute differences in daily, seasonal, and annual mean surface temperatures to differences in surface intrinsic biophysical properties across coniferous, deciduous, and clear-cut sites. Relative to a coniferous site, we observed a slight local cooling of 0.13 °C at a deciduous site and 0.25 °C at a clear-cut site over a 6-year period which was mostly attributed to a higher albedo throughout the year. When monthly mean albedo trajectories over the entire managed forest landscape were taken into consideration, we found that strategies promoting natural regeneration of coniferous sites with native deciduous species led to substantial global direct climate cooling benefits relative to those maintaining current silviculture regimes - despite predicted long-term regional warming feedbacks and a reduced albedo in spring and autumn months. The magnitude and duration of the cooling benefit depended largely on whether management strategies simultaneously promoted an enhanced material supply over business-as-usual levels. While additional climate impact linked to changes in life-cycle emissions and to changes in the global supply and demand of timber products ought to be factored into any mitigation-oriented climate policy involving the forestry sector, our analysis demonstrates that - within the boundaries of the managed forest ecosystem - excluding important biogeophysical considerations like surface albedo change may lead to sub-optimal climate policy.

Global/local processing of hierarchical visual stimuli in a conflict-choice task by capuchin monkeys (Sapajus spp.).

PubMed

Truppa, Valentina; Carducci, Paola; De Simone, Diego Antonio; Bisazza, Angelo; De Lillo, Carlo

2017-03-01

In the last two decades, comparative research has addressed the issue of how the global and local levels of structure of visual stimuli are processed by different species, using Navon-type hierarchical figures, i.e. smaller local elements that form larger global configurations. Determining whether or not the variety of procedures adopted to test different species with hierarchical figures are equivalent is of crucial importance to ensure comparability of results. Among non-human species, global/local processing has been extensively studied in tufted capuchin monkeys using matching-to-sample tasks with hierarchical patterns. Local dominance has emerged consistently in these New World primates. In the present study, we assessed capuchins' processing of hierarchical stimuli with a method frequently adopted in studies of global/local processing in non-primate species: the conflict-choice task. Different from the matching-to-sample procedure, this task involved processing local and global information retained in long-term memory. Capuchins were trained to discriminate between consistent hierarchical stimuli (similar global and local shape) and then tested with inconsistent hierarchical stimuli (different global and local shapes). We found that capuchins preferred the hierarchical stimuli featuring the correct local elements rather than those with the correct global configuration. This finding confirms that capuchins' local dominance, typically observed using matching-to-sample procedures, is also expressed as a local preference in the conflict-choice task. Our study adds to the growing body of comparative studies on visual grouping functions by demonstrating that the methods most frequently used in the literature on global/local processing produce analogous results irrespective of extent of the involvement of memory processes.

Local Feature Selection for Data Classification.

PubMed

Armanfard, Narges; Reilly, James P; Komeili, Majid

2016-06-01

Typical feature selection methods choose an optimal global feature subset that is applied over all regions of the sample space. In contrast, in this paper we propose a novel localized feature selection (LFS) approach whereby each region of the sample space is associated with its own distinct optimized feature set, which may vary both in membership and size across the sample space. This allows the feature set to optimally adapt to local variations in the sample space. An associated method for measuring the similarities of a query datum to each of the respective classes is also proposed. The proposed method makes no assumptions about the underlying structure of the samples; hence the method is insensitive to the distribution of the data over the sample space. The method is efficiently formulated as a linear programming optimization problem. Furthermore, we demonstrate the method is robust against the over-fitting problem. Experimental results on eleven synthetic and real-world data sets demonstrate the viability of the formulation and the effectiveness of the proposed algorithm. In addition we show several examples where localized feature selection produces better results than a global feature selection method.

From local to global measurements of nonclassical nonlinear elastic effects in geomaterials

DOE PAGES

Lott, Martin; Remillieux, Marcel C.; Le Bas, Pierre-Yves; ...

2016-09-07

Here, the equivalence between local and global measures of nonclassical nonlinear elasticity is established in a slender resonant bar. Nonlinear effects are first measured globally using nonlinear resonance ultrasound spectroscopy (NRUS), which monitors the relative shift of the resonance frequency as a function of the maximum dynamic strain in the sample. Subsequently, nonlinear effects are measured locally at various positions along the sample using dynamic acousto elasticity testing (DAET). Finally, after correcting analytically the DAET data for three-dimensional strain effects and integrating numerically these corrected data along the length of the sample, the NRUS global measures are retrieved almost exactly.

Local flow regulation and irrigation raise global human water consumption and footprint.

PubMed

Jaramillo, Fernando; Destouni, Georgia

2015-12-04

Flow regulation and irrigation alter local freshwater conditions, but their global effects are highly uncertain. We investigated these global effects from 1901 to 2008, using hydroclimatic observations in 100 large hydrological basins. Globally, we find consistent and dominant effects of increasing relative evapotranspiration from both activities, and decreasing temporal runoff variability from flow regulation. The evapotranspiration effect increases the long-term average human consumption of fresh water by 3563 ± 979 km(3)/year from 1901-1954 to 1955-2008. This increase raises a recent estimate of the current global water footprint of humanity by around 18%, to 10,688 ± 979 km(3)/year. The results highlight the global impact of local water-use activities and call for their relevant account in Earth system modeling. Copyright © 2015, American Association for the Advancement of Science.

Attending Globally or Locally: Incidental Learning of Optimal Visual Attention Allocation

ERIC Educational Resources Information Center

Beck, Melissa R.; Goldstein, Rebecca R.; van Lamsweerde, Amanda E.; Ericson, Justin M.

2018-01-01

Attention allocation determines the information that is encoded into memory. Can participants learn to optimally allocate attention based on what types of information are most likely to change? The current study examined whether participants could incidentally learn that changes to either high spatial frequency (HSF) or low spatial frequency (LSF)…

A global optimization algorithm inspired in the behavior of selfish herds.

PubMed

Fausto, Fernando; Cuevas, Erik; Valdivia, Arturo; González, Adrián

2017-10-01

In this paper, a novel swarm optimization algorithm called the Selfish Herd Optimizer (SHO) is proposed for solving global optimization problems. SHO is based on the simulation of the widely observed selfish herd behavior manifested by individuals within a herd of animals subjected to some form of predation risk. In SHO, individuals emulate the predatory interactions between groups of prey and predators by two types of search agents: the members of a selfish herd (the prey) and a pack of hungry predators. Depending on their classification as either a prey or a predator, each individual is conducted by a set of unique evolutionary operators inspired by such prey-predator relationship. These unique traits allow SHO to improve the balance between exploration and exploitation without altering the population size. To illustrate the proficiency and robustness of the proposed method, it is compared to other well-known evolutionary optimization approaches such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Firefly Algorithm (FA), Differential Evolution (DE), Genetic Algorithms (GA), Crow Search Algorithm (CSA), Dragonfly Algorithm (DA), Moth-flame Optimization Algorithm (MOA) and Sine Cosine Algorithm (SCA). The comparison examines several standard benchmark functions, commonly considered within the literature of evolutionary algorithms. The experimental results show the remarkable performance of our proposed approach against those of the other compared methods, and as such SHO is proven to be an excellent alternative to solve global optimization problems. Copyright © 2017 Elsevier B.V. All rights reserved.

A framework for parallelized efficient global optimization with application to vehicle crashworthiness optimization

NASA Astrophysics Data System (ADS)

Hamza, Karim; Shalaby, Mohamed

2014-09-01

This article presents a framework for simulation-based design optimization of computationally expensive problems, where economizing the generation of sample designs is highly desirable. One popular approach for such problems is efficient global optimization (EGO), where an initial set of design samples is used to construct a kriging model, which is then used to generate new 'infill' sample designs at regions of the search space where there is high expectancy of improvement. This article attempts to address one of the limitations of EGO, where generation of infill samples can become a difficult optimization problem in its own right, as well as allow the generation of multiple samples at a time in order to take advantage of parallel computing in the evaluation of the new samples. The proposed approach is tested on analytical functions, and then applied to the vehicle crashworthiness design of a full Geo Metro model undergoing frontal crash conditions.

Robust active contour via additive local and global intensity information based on local entropy

NASA Astrophysics Data System (ADS)

Yuan, Shuai; Monkam, Patrice; Zhang, Feng; Luan, Fangjun; Koomson, Ben Alfred

2018-01-01

Active contour-based image segmentation can be a very challenging task due to many factors such as high intensity inhomogeneity, presence of noise, complex shape, weak boundaries objects, and dependence on the position of the initial contour. We propose a level set-based active contour method to segment complex shape objects from images corrupted by noise and high intensity inhomogeneity. The energy function of the proposed method results from combining the global intensity information and local intensity information with some regularization factors. First, the global intensity term is proposed based on a scheme formulation that considers two intensity values for each region instead of one, which outperforms the well-known Chan-Vese model in delineating the image information. Second, the local intensity term is formulated based on local entropy computed considering the distribution of the image brightness and using the generalized Gaussian distribution as the kernel function. Therefore, it can accurately handle high intensity inhomogeneity and noise. Moreover, our model is not dependent on the position occupied by the initial curve. Finally, extensive experiments using various images have been carried out to illustrate the performance of the proposed method.

Toward Optimal Manifold Hashing via Discrete Locally Linear Embedding.

PubMed

Rongrong Ji; Hong Liu; Liujuan Cao; Di Liu; Yongjian Wu; Feiyue Huang

2017-11-01

Binary code learning, also known as hashing, has received increasing attention in large-scale visual search. By transforming high-dimensional features to binary codes, the original Euclidean distance is approximated via Hamming distance. More recently, it is advocated that it is the manifold distance, rather than the Euclidean distance, that should be preserved in the Hamming space. However, it retains as an open problem to directly preserve the manifold structure by hashing. In particular, it first needs to build the local linear embedding in the original feature space, and then quantize such embedding to binary codes. Such a two-step coding is problematic and less optimized. Besides, the off-line learning is extremely time and memory consuming, which needs to calculate the similarity matrix of the original data. In this paper, we propose a novel hashing algorithm, termed discrete locality linear embedding hashing (DLLH), which well addresses the above challenges. The DLLH directly reconstructs the manifold structure in the Hamming space, which learns optimal hash codes to maintain the local linear relationship of data points. To learn discrete locally linear embeddingcodes, we further propose a discrete optimization algorithm with an iterative parameters updating scheme. Moreover, an anchor-based acceleration scheme, termed Anchor-DLLH, is further introduced, which approximates the large similarity matrix by the product of two low-rank matrices. Experimental results on three widely used benchmark data sets, i.e., CIFAR10, NUS-WIDE, and YouTube Face, have shown superior performance of the proposed DLLH over the state-of-the-art approaches.

Optimization and performance of bifacial solar modules: A global perspective

DOE PAGES

Sun, Xingshu; Khan, Mohammad Ryyan; Deline, Chris; ...

2018-02-06

With the rapidly growing interest in bifacial photovoltaics (PV), a worldwide map of their potential performance can help assess and accelerate the global deployment of this emerging technology. However, the existing literature only highlights optimized bifacial PV for a few geographic locations or develops worldwide performance maps for very specific configurations, such as the vertical installation. It is still difficult to translate these location- and configuration-specific conclusions to a general optimized performance of this technology. In this paper, we present a global study and optimization of bifacial solar modules using a rigorous and comprehensive modeling framework. Our results demonstrate thatmore » with a low albedo of 0.25, the bifacial gain of ground-mounted bifacial modules is less than 10% worldwide. However, increasing the albedo to 0.5 and elevating modules 1 m above the ground can boost the bifacial gain to 30%. Moreover, we derive a set of empirical design rules, which optimize bifacial solar modules across the world and provide the groundwork for rapid assessment of the location-specific performance. We find that ground-mounted, vertical, east-west-facing bifacial modules will outperform their south-north-facing, optimally tilted counterparts by up to 15% below the latitude of 30 degrees, for an albedo of 0.5. The relative energy output is reversed in latitudes above 30 degrees. A detailed and systematic comparison with data from Asia, Africa, Europe, and North America validates the model presented in this paper.« less

Optimization and performance of bifacial solar modules: A global perspective

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Xingshu; Khan, Mohammad Ryyan; Deline, Chris

With the rapidly growing interest in bifacial photovoltaics (PV), a worldwide map of their potential performance can help assess and accelerate the global deployment of this emerging technology. However, the existing literature only highlights optimized bifacial PV for a few geographic locations or develops worldwide performance maps for very specific configurations, such as the vertical installation. It is still difficult to translate these location- and configuration-specific conclusions to a general optimized performance of this technology. In this paper, we present a global study and optimization of bifacial solar modules using a rigorous and comprehensive modeling framework. Our results demonstrate thatmore » with a low albedo of 0.25, the bifacial gain of ground-mounted bifacial modules is less than 10% worldwide. However, increasing the albedo to 0.5 and elevating modules 1 m above the ground can boost the bifacial gain to 30%. Moreover, we derive a set of empirical design rules, which optimize bifacial solar modules across the world and provide the groundwork for rapid assessment of the location-specific performance. We find that ground-mounted, vertical, east-west-facing bifacial modules will outperform their south-north-facing, optimally tilted counterparts by up to 15% below the latitude of 30 degrees, for an albedo of 0.5. The relative energy output is reversed in latitudes above 30 degrees. A detailed and systematic comparison with data from Asia, Africa, Europe, and North America validates the model presented in this paper.« less

The Development of Global and Local Processing: A Comparison of Children to Adults

ERIC Educational Resources Information Center

Peterson, Eric; Peterson, Robin L.

2014-01-01

In light of the adult model of a hemispheric asymmetry of global and local processing, we compared children (M [subscript age] = 8.4 years) to adults in a global-local reaction time (RT) paradigm. Hierarchical designs (large shapes made of small shapes) were presented randomly to each visual field, and participants were instructed to identify…

A Game Theoretic Optimization Method for Energy Efficient Global Connectivity in Hybrid Wireless Sensor Networks

PubMed Central

Lee, JongHyup; Pak, Dohyun

2016-01-01

For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743

Development and verification of local/global analysis techniques for laminated composites

NASA Technical Reports Server (NTRS)

Griffin, O. Hayden, Jr.

1989-01-01

Analysis and design methods for laminated composite materials have been the subject of considerable research over the past 20 years, and are currently well developed. In performing the detailed three-dimensional analyses which are often required in proximity to discontinuities, however, analysts often encounter difficulties due to large models. Even with the current availability of powerful computers, models which are too large to run, either from a resource or time standpoint, are often required. There are several approaches which can permit such analyses, including substructuring, use of superelements or transition elements, and the global/local approach. This effort is based on the so-called zoom technique to global/local analysis, where a global analysis is run, with the results of that analysis applied to a smaller region as boundary conditions, in as many iterations as is required to attain an analysis of the desired region. Before beginning the global/local analyses, it was necessary to evaluate the accuracy of the three-dimensional elements currently implemented in the Computational Structural Mechanics (CSM) Testbed. It was also desired to install, using the Experimental Element Capability, a number of displacement formulation elements which have well known behavior when used for analysis of laminated composites.

Infrared and visible images registration with adaptable local-global feature integration for rail inspection

NASA Astrophysics Data System (ADS)

Tang, Chaoqing; Tian, Gui Yun; Chen, Xiaotian; Wu, Jianbo; Li, Kongjing; Meng, Hongying

2017-12-01

Active thermography provides infrared images that contain sub-surface defect information, while visible images only reveal surface information. Mapping infrared information to visible images offers more comprehensive visualization for decision-making in rail inspection. However, the common information for registration is limited due to different modalities in both local and global level. For example, rail track which has low temperature contrast reveals rich details in visible images, but turns blurry in the infrared counterparts. This paper proposes a registration algorithm called Edge-Guided Speeded-Up-Robust-Features (EG-SURF) to address this issue. Rather than sequentially integrating local and global information in matching stage which suffered from buckets effect, this algorithm adaptively integrates local and global information into a descriptor to gather more common information before matching. This adaptability consists of two facets, an adaptable weighting factor between local and global information, and an adaptable main direction accuracy. The local information is extracted using SURF while the global information is represented by shape context from edges. Meanwhile, in shape context generation process, edges are weighted according to local scale and decomposed into bins using a vector decomposition manner to provide more accurate descriptor. The proposed algorithm is qualitatively and quantitatively validated using eddy current pulsed thermography scene in the experiments. In comparison with other algorithms, better performance has been achieved.

Turkish Elementary School Students' Perceptions of Local and Global Terrorism

ERIC Educational Resources Information Center

Aricak, Tolga; Bekci, Banu; Siyahhan, Sinem; Martinez, Rebecca

2008-01-01

Introduction: Historically, terrorism has occurred in various regions of the world and has been considered a local problem until the September, 11 terrorist attacks on the United States in 2001. After 9/11, terrorism has become a global concern. The definition of terrorism has changed from a violent act of a group of local people against their…

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

DOE PAGES

Xi, Maolong; Lu, Dan; Gui, Dongwei; ...

2016-11-27

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

NASA Astrophysics Data System (ADS)

Xi, Maolong; Lu, Dan; Gui, Dongwei; Qi, Zhiming; Zhang, Guannan

2017-01-01

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so as to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.

Calibration of an agricultural-hydrological model (RZWQM2) using surrogate global optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xi, Maolong; Lu, Dan; Gui, Dongwei

Robust calibration of an agricultural-hydrological model is critical for simulating crop yield and water quality and making reasonable agricultural management. However, calibration of the agricultural-hydrological system models is challenging because of model complexity, the existence of strong parameter correlation, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time, which greatly restricts the successful application of the model. The goal of this study is to locate the optimal solution of the Root Zone Water Quality Model (RZWQM2) given a limited simulation time, so asmore » to improve the model simulation and help make rational and effective agricultural-hydrological decisions. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first used advanced sparse grid (SG) interpolation to construct a surrogate system of the actual RZWQM2, and then we calibrate the surrogate model using the global optimization algorithm, Quantum-behaved Particle Swarm Optimization (QPSO). As the surrogate model is a polynomial with fast evaluation, it can be efficiently evaluated with a sufficiently large number of times during the optimization, which facilitates the global search. We calibrate seven model parameters against five years of yield, drain flow, and NO 3-N loss data from a subsurface-drained corn-soybean field in Iowa. Results indicate that an accurate surrogate model can be created for the RZWQM2 with a relatively small number of SG points (i.e., RZWQM2 runs). Compared to the conventional QPSO algorithm, our surrogate-based optimization method can achieve a smaller objective function value and better calibration performance using a fewer number of expensive RZWQM2 executions, which greatly improves computational efficiency.« less

Global and Local Evaluations of Public Speaking Performance in Social Anxiety

PubMed Central

Cody, Meghan W.; Teachman, Bethany A.

2012-01-01

Differences in the relative use of global and local information (seeing the forest versus the trees) may explain why people with social anxiety often do not benefit from corrective feedback, even though they pay close attention to details in social situations. In the current study, participants high (n = 43) or low (n = 47) in social anxiety symptoms gave a series of brief speeches, and then self-rated their speaking performance on items reflecting global and local performance indicators (self assessment) and also received standardized performance feedback from an experimenter. Participants then completed a questionnaire asking how they thought the experimenter would rate their performance based on the feedback provided (experimenter assessment). Participants completed the self and experimenter assessments again after three days, in addition to a measure of post-event processing (repetitive negative thinking) about their speech performance. Results showed that, as hypothesized, the high social anxiety group rated their performance more negatively than the low social anxiety group did. Moreover, the high social anxiety group’s ratings of global aspects of their performance became relatively more negative over time, compared to their ratings of local aspects and the low social anxiety group’s ratings. As expected, post-event processing mediated the relationship between social anxiety group status and worsening global performance evaluations. These findings point to a pattern of progressively more negative global evaluations over time for persons high in social anxiety. PMID:22035989

A Functional Near-Infrared Spectroscopy Study of Sustained Attention to Local and Global Target Features

ERIC Educational Resources Information Center

De Joux, Neil; Russell, Paul N.; Helton, William S.

2013-01-01

Despite a long history of vigilance research, the role of global and local feature discrimination in vigilance tasks has been relatively neglected. In this experiment participants performed a sustained attention task requiring either global or local shape stimuli discrimination. Reaction time to local feature discriminations was characterized by a…

Impairment in local and global processing and set-shifting in body dysmorphic disorder

PubMed Central

Kerwin, Lauren; Hovav, Sarit; Helleman, Gerhard; Feusner, Jamie D.

2014-01-01

Body dysmorphic disorder (BDD) is characterized by distressing and often debilitating preoccupations with misperceived defects in appearance. Research suggests that aberrant visual processing may contribute to these misperceptions. This study used two tasks to probe global and local visual processing as well as set shifting in individuals with BDD. Eighteen unmedicated individuals with BDD and 17 non-clinical controls completed two global-local tasks. The embedded figures task requires participants to determine which of three complex figures contained a simpler figure embedded within it. The Navon task utilizes incongruent stimuli comprised of a large letter (global level) made up of smaller letters (local level). The outcome measures were response time and accuracy rate. On the embedded figures task, BDD individuals were slower and less accurate than controls. On the Navon task, BDD individuals processed both global and local stimuli slower and less accurately than controls, and there was a further decrement in performance when shifting attention between the different levels of stimuli. Worse insight correlated with poorer performance on both tasks. Taken together, these results suggest abnormal global and local processing for non-appearance related stimuli among BDD individuals, in addition to evidence of poor set-shifting abilities. Moreover, these abnormalities appear to relate to the important clinical variable of poor insight. Further research is needed to explore these abnormalities and elucidate their possible role in the development and/or persistence of BDD symptoms. PMID:24972487

Global and Local Translation Designs of Quantum Image Based on FRQI

NASA Astrophysics Data System (ADS)

Zhou, Ri-Gui; Tan, Canyun; Ian, Hou

2017-04-01

In this paper, two kinds of quantum image translation are designed based on FRQI, including global translation and local translation. Firstly, global translation is realized by employing adder modulo N, where all pixels in the image will be moved, and the circuit of right translation is designed. Meanwhile, left translation can also be implemented by using right translation. Complexity analysis shows that the circuits of global translation in this paper have lower complexity and cost less qubits. Secondly, local translation, consisted of single-column translation, multiple-columns translation and translation in the restricted area, is designed by adopting Gray code. In local translation, any parts of pixels in the image can be translated while other pixels remain unchanged. In order to lower complexity when the number of columns needing to be translated are more than one, multiple-columns translation is proposed, which has the approximate complexity with single-column translation. To perform multiple-columns translation, three conditions must be satisfied. In addition, all translations in this paper are cyclic.

Learning Human Actions by Combining Global Dynamics and Local Appearance.

PubMed

Luo, Guan; Yang, Shuang; Tian, Guodong; Yuan, Chunfeng; Hu, Weiming; Maybank, Stephen J

2014-12-01

In this paper, we address the problem of human action recognition through combining global temporal dynamics and local visual spatio-temporal appearance features. For this purpose, in the global temporal dimension, we propose to model the motion dynamics with robust linear dynamical systems (LDSs) and use the model parameters as motion descriptors. Since LDSs live in a non-Euclidean space and the descriptors are in non-vector form, we propose a shift invariant subspace angles based distance to measure the similarity between LDSs. In the local visual dimension, we construct curved spatio-temporal cuboids along the trajectories of densely sampled feature points and describe them using histograms of oriented gradients (HOG). The distance between motion sequences is computed with the Chi-Squared histogram distance in the bag-of-words framework. Finally we perform classification using the maximum margin distance learning method by combining the global dynamic distances and the local visual distances. We evaluate our approach for action recognition on five short clips data sets, namely Weizmann, KTH, UCF sports, Hollywood2 and UCF50, as well as three long continuous data sets, namely VIRAT, ADL and CRIM13. We show competitive results as compared with current state-of-the-art methods.

Global effects of land use on local terrestrial biodiversity.

PubMed

Newbold, Tim; Hudson, Lawrence N; Hill, Samantha L L; Contu, Sara; Lysenko, Igor; Senior, Rebecca A; Börger, Luca; Bennett, Dominic J; Choimes, Argyrios; Collen, Ben; Day, Julie; De Palma, Adriana; Díaz, Sandra; Echeverria-Londoño, Susy; Edgar, Melanie J; Feldman, Anat; Garon, Morgan; Harrison, Michelle L K; Alhusseini, Tamera; Ingram, Daniel J; Itescu, Yuval; Kattge, Jens; Kemp, Victoria; Kirkpatrick, Lucinda; Kleyer, Michael; Correia, David Laginha Pinto; Martin, Callum D; Meiri, Shai; Novosolov, Maria; Pan, Yuan; Phillips, Helen R P; Purves, Drew W; Robinson, Alexandra; Simpson, Jake; Tuck, Sean L; Weiher, Evan; White, Hannah J; Ewers, Robert M; Mace, Georgina M; Scharlemann, Jörn P W; Purvis, Andy

2015-04-02

Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.

Global effects of land use on local terrestrial biodiversity

NASA Astrophysics Data System (ADS)

Newbold, Tim; Hudson, Lawrence N.; Hill, Samantha L. L.; Contu, Sara; Lysenko, Igor; Senior, Rebecca A.; Börger, Luca; Bennett, Dominic J.; Choimes, Argyrios; Collen, Ben; Day, Julie; de Palma, Adriana; Díaz, Sandra; Echeverria-Londoño, Susy; Edgar, Melanie J.; Feldman, Anat; Garon, Morgan; Harrison, Michelle L. K.; Alhusseini, Tamera; Ingram, Daniel J.; Itescu, Yuval; Kattge, Jens; Kemp, Victoria; Kirkpatrick, Lucinda; Kleyer, Michael; Correia, David Laginha Pinto; Martin, Callum D.; Meiri, Shai; Novosolov, Maria; Pan, Yuan; Phillips, Helen R. P.; Purves, Drew W.; Robinson, Alexandra; Simpson, Jake; Tuck, Sean L.; Weiher, Evan; White, Hannah J.; Ewers, Robert M.; Mace, Georgina M.; Scharlemann, Jörn P. W.; Purvis, Andy

2015-04-01

Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.

WaterWorld, a spatial hydrological model applied at scales from local to global: key challenges to local application

NASA Astrophysics Data System (ADS)

Burke, Sophia; Mulligan, Mark

2017-04-01

WaterWorld is a widely used spatial hydrological policy support system. The last user census indicates regular use by 1029 institutions across 141 countries. A key feature of WaterWorld since 2001 is that it comes pre-loaded with all of the required data for simulation anywhere in the world at a 1km or 1 ha resolution. This means that it can be easily used, without specialist technical ability, to examine baseline hydrology and the impacts of scenarios for change or management interventions to support policy formulation, hence its labelling as a policy support system. WaterWorld is parameterised by an extensive global gridded database of more than 600 variables, developed from many sources, since 1998, the so-called simTerra database. All of these data are available globally at 1km resolution and some variables (terrain, land cover, urban areas, water bodies) are available globally at 1ha resolution. If users have access to better data than is pre-loaded, they can upload their own data. WaterWorld is generally applied at the national or basin scale at 1km resolution, or locally (for areas of <10,000km2) at 1ha resolution, though continental (1km resolution) and global (10km resolution) applications are possible so it is a model with local to global applications. WaterWorld requires some 140 maps to run including monthly climate data, land cover and use, terrain, population, water bodies and more. Whilst publically-available terrain and land cover data are now well developed for local scale application, climate and land use data remain a challenge, with most global products being available at 1km or 10km resolution or worse, which is rather coarse for local application. As part of the EartH2Observe project we have used WFDEI (WATCH Forcing Data methodology applied to ERA-Interim data) at 1km resolution to provide an alternative input to WaterWorld's preloaded climate data. Here we examine the impacts of that on key hydrological outputs: water balance, water quality

A global/local affinity graph for image segmentation.

PubMed

Xiaofang Wang; Yuxing Tang; Masnou, Simon; Liming Chen

2015-04-01

Construction of a reliable graph capturing perceptual grouping cues of an image is fundamental for graph-cut based image segmentation methods. In this paper, we propose a novel sparse global/local affinity graph over superpixels of an input image to capture both short- and long-range grouping cues, and thereby enabling perceptual grouping laws, including proximity, similarity, continuity, and to enter in action through a suitable graph-cut algorithm. Moreover, we also evaluate three major visual features, namely, color, texture, and shape, for their effectiveness in perceptual segmentation and propose a simple graph fusion scheme to implement some recent findings from psychophysics, which suggest combining these visual features with different emphases for perceptual grouping. In particular, an input image is first oversegmented into superpixels at different scales. We postulate a gravitation law based on empirical observations and divide superpixels adaptively into small-, medium-, and large-sized sets. Global grouping is achieved using medium-sized superpixels through a sparse representation of superpixels' features by solving a ℓ0-minimization problem, and thereby enabling continuity or propagation of local smoothness over long-range connections. Small- and large-sized superpixels are then used to achieve local smoothness through an adjacent graph in a given feature space, and thus implementing perceptual laws, for example, similarity and proximity. Finally, a bipartite graph is also introduced to enable propagation of grouping cues between superpixels of different scales. Extensive experiments are carried out on the Berkeley segmentation database in comparison with several state-of-the-art graph constructions. The results show the effectiveness of the proposed approach, which outperforms state-of-the-art graphs using four different objective criteria, namely, the probabilistic rand index, the variation of information, the global consistency error, and the

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter

PubMed Central

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Gu, Chengfan

2018-01-01

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation. PMID:29415509

Multi-Sensor Optimal Data Fusion Based on the Adaptive Fading Unscented Kalman Filter.

PubMed

Gao, Bingbing; Hu, Gaoge; Gao, Shesheng; Zhong, Yongmin; Gu, Chengfan

2018-02-06

This paper presents a new optimal data fusion methodology based on the adaptive fading unscented Kalman filter for multi-sensor nonlinear stochastic systems. This methodology has a two-level fusion structure: at the bottom level, an adaptive fading unscented Kalman filter based on the Mahalanobis distance is developed and serves as local filters to improve the adaptability and robustness of local state estimations against process-modeling error; at the top level, an unscented transformation-based multi-sensor optimal data fusion for the case of N local filters is established according to the principle of linear minimum variance to calculate globally optimal state estimation by fusion of local estimations. The proposed methodology effectively refrains from the influence of process-modeling error on the fusion solution, leading to improved adaptability and robustness of data fusion for multi-sensor nonlinear stochastic systems. It also achieves globally optimal fusion results based on the principle of linear minimum variance. Simulation and experimental results demonstrate the efficacy of the proposed methodology for INS/GNSS/CNS (inertial navigation system/global navigation satellite system/celestial navigation system) integrated navigation.

An Improved Quantum-Behaved Particle Swarm Optimization Algorithm with Elitist Breeding for Unconstrained Optimization.

PubMed

Yang, Zhen-Lun; Wu, Angus; Min, Hua-Qing

2015-01-01

An improved quantum-behaved particle swarm optimization with elitist breeding (EB-QPSO) for unconstrained optimization is presented and empirically studied in this paper. In EB-QPSO, the novel elitist breeding strategy acts on the elitists of the swarm to escape from the likely local optima and guide the swarm to perform more efficient search. During the iterative optimization process of EB-QPSO, when criteria met, the personal best of each particle and the global best of the swarm are used to generate new diverse individuals through the transposon operators. The new generated individuals with better fitness are selected to be the new personal best particles and global best particle to guide the swarm for further solution exploration. A comprehensive simulation study is conducted on a set of twelve benchmark functions. Compared with five state-of-the-art quantum-behaved particle swarm optimization algorithms, the proposed EB-QPSO performs more competitively in all of the benchmark functions in terms of better global search capability and faster convergence rate.

Attention to Local Health Burden and the Global Disparity of Health Research

PubMed Central

Evans, James A.; Shim, Jae-Mahn; Ioannidis, John P. A.

2014-01-01

Most studies on global health inequality consider unequal health care and socio-economic conditions but neglect inequality in the production of health knowledge relevant to addressing disease burden. We demonstrate this inequality and identify likely causes. Using disability-adjusted life years (DALYs) for 111 prominent medical conditions, assessed globally and nationally by the World Health Organization, we linked DALYs with MEDLINE articles for each condition to assess the influence of DALY-based global disease burden, compared to the global market for treatment, on the production of relevant MEDLINE articles, systematic reviews, clinical trials and research using animal models vs. humans. We then explored how DALYs, wealth, and the production of research within countries correlate with this global pattern. We show that global DALYs for each condition had a small, significant negative relationship with the production of each type of MEDLINE articles for that condition. Local processes of health research appear to be behind this. Clinical trials and animal studies but not systematic reviews produced within countries were strongly guided by local DALYs. More and less developed countries had very different disease profiles and rich countries publish much more than poor countries. Accordingly, conditions common to developed countries garnered more clinical research than those common to less developed countries. Many of the health needs in less developed countries do not attract attention among developed country researchers who produce the vast majority of global health knowledge—including clinical trials—in response to their own local needs. This raises concern about the amount of knowledge relevant to poor populations deficient in their own research infrastructure. We recommend measures to address this critical dimension of global health inequality. PMID:24691431

Attention to local health burden and the global disparity of health research.

PubMed

Evans, James A; Shim, Jae-Mahn; Ioannidis, John P A

2014-01-01

Most studies on global health inequality consider unequal health care and socio-economic conditions but neglect inequality in the production of health knowledge relevant to addressing disease burden. We demonstrate this inequality and identify likely causes. Using disability-adjusted life years (DALYs) for 111 prominent medical conditions, assessed globally and nationally by the World Health Organization, we linked DALYs with MEDLINE articles for each condition to assess the influence of DALY-based global disease burden, compared to the global market for treatment, on the production of relevant MEDLINE articles, systematic reviews, clinical trials and research using animal models vs. humans. We then explored how DALYs, wealth, and the production of research within countries correlate with this global pattern. We show that global DALYs for each condition had a small, significant negative relationship with the production of each type of MEDLINE articles for that condition. Local processes of health research appear to be behind this. Clinical trials and animal studies but not systematic reviews produced within countries were strongly guided by local DALYs. More and less developed countries had very different disease profiles and rich countries publish much more than poor countries. Accordingly, conditions common to developed countries garnered more clinical research than those common to less developed countries. Many of the health needs in less developed countries do not attract attention among developed country researchers who produce the vast majority of global health knowledge--including clinical trials--in response to their own local needs. This raises concern about the amount of knowledge relevant to poor populations deficient in their own research infrastructure. We recommend measures to address this critical dimension of global health inequality.

An efficient global energy optimization approach for robust 3D plane segmentation of point clouds

NASA Astrophysics Data System (ADS)

Dong, Zhen; Yang, Bisheng; Hu, Pingbo; Scherer, Sebastian

2018-03-01

Automatic 3D plane segmentation is necessary for many applications including point cloud registration, building information model (BIM) reconstruction, simultaneous localization and mapping (SLAM), and point cloud compression. However, most of the existing 3D plane segmentation methods still suffer from low precision and recall, and inaccurate and incomplete boundaries, especially for low-quality point clouds collected by RGB-D sensors. To overcome these challenges, this paper formulates the plane segmentation problem as a global energy optimization because it is robust to high levels of noise and clutter. First, the proposed method divides the raw point cloud into multiscale supervoxels, and considers planar supervoxels and individual points corresponding to nonplanar supervoxels as basic units. Then, an efficient hybrid region growing algorithm is utilized to generate initial plane set by incrementally merging adjacent basic units with similar features. Next, the initial plane set is further enriched and refined in a mutually reinforcing manner under the framework of global energy optimization. Finally, the performances of the proposed method are evaluated with respect to six metrics (i.e., plane precision, plane recall, under-segmentation rate, over-segmentation rate, boundary precision, and boundary recall) on two benchmark datasets. Comprehensive experiments demonstrate that the proposed method obtained good performances both in high-quality TLS point clouds (i.e., http://SEMANTIC3D.NET)

"Global Human Resource Development" and Japanese University Education: "Localism" in Actor Discussions

ERIC Educational Resources Information Center

Yoshida, Aya

2017-01-01

The aim of this paper is to analyse the actions of various actors involved in "global human resource development" and to clarify whether discussions on global human resources are based on local perspectives. The results of the analysis are as follows: 1) after the year 2000 began, industry started discussions on global human resources in…

The Hartree product and the description of local and global quantities in atomic systems: A study within Kohn-Sham theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garza, Jorge; Nichols, Jeffrey A.; Dixon, David A.

2000-01-15

The Hartree product is analyzed in the context of Kohn-Sham theory. The differential equations that emerge from this theory are solved with the optimized effective potential using the Krieger, Li, and Iafrate approximation, in order to get a local potential as required by the ordinary Kohn-Sham procedure. Because the diagonal terms of the exact exchange energy are included in Hartree theory, it is self-interaction free and the exchange potential has the proper asymptotic behavior. We have examined the impact of this correct asymptotic behavior on local and global properties using this simple model to approximate the exchange energy. Local quantities,more » such as the exchange potential and the average local electrostatic potential are used to examine whether the shell structure in an atom is revealed by this theory. Global quantities, such as the highest occupied orbital energy (related to the ionization potential) and the exchange energy are also calculated. These quantities are contrasted with those obtained from calculations with the local density approximation, the generalized gradient approximation, and the self-interaction correction approach proposed by Perdew and Zunger. We conclude that the main characteristics in an atomic system are preserved with the Hartree theory. In particular, the behavior of the exchange potential obtained in this theory is similar to those obtained within other Kohn-Sham approximations. (c) 2000 American Institute of Physics.« less

The Role of Global and Local Visual Information during Gaze-Cued Orienting of Attention.

PubMed

Munsters, Nicolette M; van den Boomen, Carlijn; Hooge, Ignace T C; Kemner, Chantal

2016-01-01

Gaze direction is an important social communication tool. Global and local visual information are known to play specific roles in processing socially relevant information from a face. The current study investigated whether global visual information has a primary role during gaze-cued orienting of attention and, as such, may influence quality of interaction. Adults performed a gaze-cueing task in which a centrally presented face cued (valid or invalid) the location of a peripheral target through a gaze shift. We measured brain activity (electroencephalography) towards the cue and target and behavioral responses (manual and saccadic reaction times) towards the target. The faces contained global (i.e. lower spatial frequencies), local (i.e. higher spatial frequencies), or a selection of both global and local (i.e. mid-band spatial frequencies) visual information. We found a gaze cue-validity effect (i.e. valid versus invalid), but no interaction effects with spatial frequency content. Furthermore, behavioral responses towards the target were in all cue conditions slower when lower spatial frequencies were not present in the gaze cue. These results suggest that whereas gaze-cued orienting of attention can be driven by both global and local visual information, global visual information determines the speed of behavioral responses towards other entities appearing in the surrounding of gaze cue stimuli.

A global carbon assimilation system based on a dual optimization method

NASA Astrophysics Data System (ADS)

Zheng, H.; Li, Y.; Chen, J. M.; Wang, T.; Huang, Q.; Huang, W. X.; Li, S. M.; Yuan, W. P.; Zheng, X.; Zhang, S. P.; Chen, Z. Q.; Jiang, F.

2014-10-01

Ecological models are effective tools to simulate the distribution of global carbon sources and sinks. However, these models often suffer from substantial biases due to inaccurate simulations of complex ecological processes. We introduce a set of scaling factors (parameters) to an ecological model on the basis of plant functional type (PFT) and latitudes. A global carbon assimilation system (GCAS-DOM) is developed by employing a Dual Optimization Method (DOM) to invert the time-dependent ecological model parameter state and the net carbon flux state simultaneously. We use GCAS-DOM to estimate the global distribution of the CO2 flux on 1° ×1° grid cells for the period from 2000 to 2007. Results show that land and ocean absorb -3.69 ± 0.49 Pg C year-1 and -1.91 ± 0.16 Pg C year-1, respectively. North America, Europe and China contribut -0.96 ± 0.15 Pg C year-1, -0.42 ± 0.08 Pg C year-1 and -0.21 ± 0.28 Pg C year-1, respectively. The uncertainties in the flux after optimization by GCAS-DOM have been remarkably reduced by more than 60%. Through parameter optimization, GCAS-DOM can provide improved estimates of the carbon flux for each PFT. Coniferous forest (-0.97 ± 0.27 Pg C year-1) is the largest contributor to the global carbon sink. Fluxes of once-dominant deciduous forest generated by BEPS is reduced to -0.79 ± 0.22 Pg C year-1, being the third largest carbon sink.

A global carbon assimilation system based on a dual optimization method

NASA Astrophysics Data System (ADS)

Zheng, H.; Li, Y.; Chen, J. M.; Wang, T.; Huang, Q.; Huang, W. X.; Wang, L. H.; Li, S. M.; Yuan, W. P.; Zheng, X.; Zhang, S. P.; Chen, Z. Q.; Jiang, F.

2015-02-01

Ecological models are effective tools for simulating the distribution of global carbon sources and sinks. However, these models often suffer from substantial biases due to inaccurate simulations of complex ecological processes. We introduce a set of scaling factors (parameters) to an ecological model on the basis of plant functional type (PFT) and latitudes. A global carbon assimilation system (GCAS-DOM) is developed by employing a dual optimization method (DOM) to invert the time-dependent ecological model parameter state and the net carbon flux state simultaneously. We use GCAS-DOM to estimate the global distribution of the CO2 flux on 1° × 1° grid cells for the period from 2001 to 2007. Results show that land and ocean absorb -3.63 ± 0.50 and -1.82 ± 0.16 Pg C yr-1, respectively. North America, Europe and China contribute -0.98 ± 0.15, -0.42 ± 0.08 and -0.20 ± 0.29 Pg C yr-1, respectively. The uncertainties in the flux after optimization by GCAS-DOM have been remarkably reduced by more than 60%. Through parameter optimization, GCAS-DOM can provide improved estimates of the carbon flux for each PFT. Coniferous forest (-0.97 ± 0.27 Pg C yr-1) is the largest contributor to the global carbon sink. Fluxes of once-dominant deciduous forest generated by the Boreal Ecosystems Productivity Simulator (BEPS) are reduced to -0.78 ± 0.23 Pg C yr-1, the third largest carbon sink.

Participatory monitoring to connect local and global priorities for forest restoration.

PubMed

Evans, Kristen; Guariguata, Manuel R; Brancalion, Pedro H S

2018-06-01

New global initiatives to restore forest landscapes present an unparalleled opportunity to reverse deforestation and forest degradation. Participatory monitoring could play a crucial role in providing accountability, generating local buy in, and catalyzing learning in monitoring systems that need scalability and adaptability to a range of local sites. We synthesized current knowledge from literature searches and interviews to provide lessons for the development of a scalable, multisite participatory monitoring system. Studies show that local people can collect accurate data on forest change, drivers of change, threats to reforestation, and biophysical and socioeconomic impacts that remote sensing cannot. They can do this at one-third the cost of professionals. Successful participatory monitoring systems collect information on a few simple indicators, respond to local priorities, provide appropriate incentives for participation, and catalyze learning and decision making based on frequent analyses and multilevel interactions with other stakeholders. Participatory monitoring could provide a framework for linking global, national, and local needs, aspirations, and capacities for forest restoration. © 2018 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Global optimization of ionic Mg(n)F(2n) (n=1-30) clusters.

PubMed

Francisco, E; Martín Pendás, A; Blanco, M A

2005-12-15

The global optimization basin-hopping (BH) method has been used to locate the global minima (GM) of Mg(n)F(2n) (n=1-30) clusters using a Born-Mayer-type potential. Some of the GM were particularly difficult to find, requiring more than 1.5 x 10(4) BH steps. We have found that both the binding energy per MgF2 unit and the effective volume of the GM isomers increase almost linearly with n, and that cluster symmetry decreases with cluster size. The data derived from the BH runs reveal a growing density of local minima just above the GM as n increases. Despite this, the attraction basin around each GM is relatively large, since after all their atomic coordinates are randomly displaced by values as high as 2.0 bohrs, the perturbed structures, upon reoptimization, relax back to the GM in more than 50% of the cases (except for n=10 and 11). The relative stabilities derived from energy second differences suggest that n=8,10,13,15, and 20 are probably the magic numbers for these systems. Mass spectrum experiments would be very useful to clarify this issue.

Going Glocal: Adaptive Education for Local and Global Citizenship

ERIC Educational Resources Information Center

Harth, Chris

2010-01-01

Technological advances in communications, transportation, and information processing have deepened and broadened connections on multiple levels, local through global, thickening the webs of interactivity that bind us to each other economically, politically, militarily, socially, culturally, environmentally, and ethically. As with most complex…

Global standards and local knowledge building: Upgrading small producers in developing countries

PubMed Central

Perez-Aleman, Paola

2012-01-01

Local knowledge building is a crucial factor for upgrading small producers and improving their market competitiveness and livelihoods. The rise of global standards affecting food safety and environmental sustainability in agriculture sparks debates on the impact on smallholders in developing countries. This article presents a perspective on the links of international standards to knowledge and institution building for developing the capabilities of small producers. Interacting with global practices, indigenous private and public actors create local institutions to develop capabilities for product and process innovations that contribute to economic development and enhance food security. Local innovation depends on collective strategic efforts through increasing networks among small producers and other organizations, including firms, nongovernmental organizations, and government, that foster knowledge circulation and bring diverse resources and support to build local capabilities. PMID:21670309

Global standards and local knowledge building: upgrading small producers in developing countries.

PubMed

Perez-Aleman, Paola

2012-07-31

Local knowledge building is a crucial factor for upgrading small producers and improving their market competitiveness and livelihoods. The rise of global standards affecting food safety and environmental sustainability in agriculture sparks debates on the impact on smallholders in developing countries. This article presents a perspective on the links of international standards to knowledge and institution building for developing the capabilities of small producers. Interacting with global practices, indigenous private and public actors create local institutions to develop capabilities for product and process innovations that contribute to economic development and enhance food security. Local innovation depends on collective strategic efforts through increasing networks among small producers and other organizations, including firms, nongovernmental organizations, and government, that foster knowledge circulation and bring diverse resources and support to build local capabilities.

Global optimization of minority game by intelligent agents

NASA Astrophysics Data System (ADS)

Xie, Yan-Bo; Wang, Bing-Hong; Hu, Chin-Kun; Zhou, Tao

2005-10-01

We propose a new model of minority game with intelligent agents who use trail and error method to make a choice such that the standard deviation σ2 and the total loss in this model reach the theoretical minimum values in the long time limit and the global optimization of the system is reached. This suggests that the economic systems can self-organize into a highly optimized state by agents who make decisions based on inductive thinking, limited knowledge, and capabilities. When other kinds of agents are also present, the simulation results and analytic calculations show that the intelligent agent can gain profits from producers and are much more competent than the noise traders and conventional agents in original minority games proposed by Challet and Zhang.

Local and Global Cross-Modal Influences between Vision and Hearing, Tasting, Smelling, or Touching

ERIC Educational Resources Information Center

Forster, Jens

2011-01-01

It is suggested that the distinction between global versus local processing styles exists across sensory modalities. Activation of one-way of processing in one modality should affect processing styles in a different modality. In 12 studies, auditory, haptic, gustatory or olfactory global versus local processing was induced, and participants were…

Joint Geophysical Inversion With Multi-Objective Global Optimization Methods

NASA Astrophysics Data System (ADS)

Lelievre, P. G.; Bijani, R.; Farquharson, C. G.

2015-12-01

Pareto multi-objective global optimization (PMOGO) methods generate a suite of solutions that minimize multiple objectives (e.g. data misfits and regularization terms) in a Pareto-optimal sense. Providing a suite of models, as opposed to a single model that minimizes a weighted sum of objectives, allows a more complete assessment of the possibilities and avoids the often difficult choice of how to weight each objective. We are applying PMOGO methods to three classes of inverse problems. The first class are standard mesh-based problems where the physical property values in each cell are treated as continuous variables. The second class of problems are also mesh-based but cells can only take discrete physical property values corresponding to known or assumed rock units. In the third class we consider a fundamentally different type of inversion in which a model comprises wireframe surfaces representing contacts between rock units; the physical properties of each rock unit remain fixed while the inversion controls the position of the contact surfaces via control nodes. This third class of problem is essentially a geometry inversion, which can be used to recover the unknown geometry of a target body or to investigate the viability of a proposed Earth model. Joint inversion is greatly simplified for the latter two problem classes because no additional mathematical coupling measure is required in the objective function. PMOGO methods can solve numerically complicated problems that could not be solved with standard descent-based local minimization methods. This includes the latter two classes of problems mentioned above. There are significant increases in the computational requirements when PMOGO methods are used but these can be ameliorated using parallelization and problem dimension reduction strategies.

Cuckoo Search with Lévy Flights for Weighted Bayesian Energy Functional Optimization in Global-Support Curve Data Fitting

PubMed Central

Gálvez, Akemi; Iglesias, Andrés; Cabellos, Luis

2014-01-01

The problem of data fitting is very important in many theoretical and applied fields. In this paper, we consider the problem of optimizing a weighted Bayesian energy functional for data fitting by using global-support approximating curves. By global-support curves we mean curves expressed as a linear combination of basis functions whose support is the whole domain of the problem, as opposed to other common approaches in CAD/CAM and computer graphics driven by piecewise functions (such as B-splines and NURBS) that provide local control of the shape of the curve. Our method applies a powerful nature-inspired metaheuristic algorithm called cuckoo search, introduced recently to solve optimization problems. A major advantage of this method is its simplicity: cuckoo search requires only two parameters, many fewer than other metaheuristic approaches, so the parameter tuning becomes a very simple task. The paper shows that this new approach can be successfully used to solve our optimization problem. To check the performance of our approach, it has been applied to five illustrative examples of different types, including open and closed 2D and 3D curves that exhibit challenging features, such as cusps and self-intersections. Our results show that the method performs pretty well, being able to solve our minimization problem in an astonishingly straightforward way. PMID:24977175

Cuckoo search with Lévy flights for weighted Bayesian energy functional optimization in global-support curve data fitting.

PubMed

Gálvez, Akemi; Iglesias, Andrés; Cabellos, Luis

2014-01-01

The problem of data fitting is very important in many theoretical and applied fields. In this paper, we consider the problem of optimizing a weighted Bayesian energy functional for data fitting by using global-support approximating curves. By global-support curves we mean curves expressed as a linear combination of basis functions whose support is the whole domain of the problem, as opposed to other common approaches in CAD/CAM and computer graphics driven by piecewise functions (such as B-splines and NURBS) that provide local control of the shape of the curve. Our method applies a powerful nature-inspired metaheuristic algorithm called cuckoo search, introduced recently to solve optimization problems. A major advantage of this method is its simplicity: cuckoo search requires only two parameters, many fewer than other metaheuristic approaches, so the parameter tuning becomes a very simple task. The paper shows that this new approach can be successfully used to solve our optimization problem. To check the performance of our approach, it has been applied to five illustrative examples of different types, including open and closed 2D and 3D curves that exhibit challenging features, such as cusps and self-intersections. Our results show that the method performs pretty well, being able to solve our minimization problem in an astonishingly straightforward way.

Links between global and local shape perception, coloured backgrounds, colour discrimination, and non-verbal IQ.

PubMed

Dore, Patricia; Dumani, Ardian; Wyatt, Geddes; Shepherd, Alex J

2018-03-16

This study explored associations between local and global shape perception on coloured backgrounds, colour discrimination, and non-verbal IQ (NVIQ). Five background colours were chosen for the local and global shape tasks that were tailored for the cone-opponent pathways early in the visual system (cardinal colour directions: L-M, loosely, reddish-greenish; and S-(L + M), or tritan colours, loosely, blueish-yellowish; where L, M and S refer to the long, middle and short wavelength sensitive cones). Participants also completed the Farnsworth-Munsell 100-hue test (FM100) to determine whether performance on the local and global shape tasks correlated with colour discrimination overall, or with performance on the L-M and tritan subsets of the FM100 test. Overall performance on the local and global shape tasks did correlate with scores on the FM100 tests, despite the colour of the background being irrelevant to the shape tasks. There were also significantly larger associations between scores for the L-M subset of the FM100 test, compared to the tritan subset, and accuracy on some of the shape tasks on the reddish, greenish and neutral backgrounds. Participants also completed the non-verbal components of the WAIS and the SPM+ version of Raven's progressive matrices, to determine whether performance on the FM100 test, and on the local and global shape tasks, correlated with NVIQ. FM100 scores correlated significantly with both WAIS and SPM+ scores. These results extend previous work that has indicated FM100 performance is not purely a measure of colour discrimination, but also involves aspects of each participant's NVIQ, such as the ability to attend to local and global aspects of the test, part-whole relationships, perceptual organisation and good visuomotor skills. Overall performance on the local and global shape tasks correlated only with the WAIS scores, not the SPM+. These results indicate that those aspects of NVIQ that engage spatial comprehension of local-global

Multidisciplinary Optimization and Damage Tolerance of Stiffened Structures

NASA Astrophysics Data System (ADS)

Jrad, Mohamed

THE structural optimization of a cantilever aircraft wing with curvilinear spars and ribs and stiffeners is described. For the optimization of a complex wing, a common strategy is to divide the optimization procedure into two subsystems: the global wing optimization which optimizes the geometry of spars, ribs and wing skins; and the local panel optimization which optimizes the design variables of local panels bordered by spars and ribs. The stiffeners are placed on the local panels to increase the stiffness and buckling resistance. During the local panel optimization, the stress information is taken from the global model as a displacement boundary condition on the panel edges using the so-called "Global-Local Approach". Particle swarm optimization is used in the integration of global/local optimization to optimize the SpaRibs. Parallel computing approach has been developed in the Python programming language to reduce the CPU time. The license cycle-check method and memory self-adjustment method are two approaches that have been applied in the parallel framework in order to optimize the use of the resources by reducing the license and memory limitations and making the code robust. The integrated global-local optimization approach has been applied to subsonic NASA common research model (CRM) wing, which proves the methodology's application scaling with medium fidelity FEM analysis. The structural weight of the wing has been reduced by 42% and the parallel implementation allowed a reduction in the CPU time by 89%. The aforementioned Global-Local Approach is investigated and applied to a composite panel with crack at its center. Because of composite laminates' heterogeneity, an accurate analysis of these requires very high time and storage space. A possible alternative to reduce the computational complexity is the global-local analysis which involves an approximate analysis of the whole structure followed by a detailed analysis of a significantly smaller region of

Multilevel algorithms for nonlinear optimization

NASA Technical Reports Server (NTRS)

Alexandrov, Natalia; Dennis, J. E., Jr.

1994-01-01

Multidisciplinary design optimization (MDO) gives rise to nonlinear optimization problems characterized by a large number of constraints that naturally occur in blocks. We propose a class of multilevel optimization methods motivated by the structure and number of constraints and by the expense of the derivative computations for MDO. The algorithms are an extension to the nonlinear programming problem of the successful class of local Brown-Brent algorithms for nonlinear equations. Our extensions allow the user to partition constraints into arbitrary blocks to fit the application, and they separately process each block and the objective function, restricted to certain subspaces. The methods use trust regions as a globalization strategy, and they have been shown to be globally convergent under reasonable assumptions. The multilevel algorithms can be applied to all classes of MDO formulations. Multilevel algorithms for solving nonlinear systems of equations are a special case of the multilevel optimization methods. In this case, they can be viewed as a trust-region globalization of the Brown-Brent class.

The Role of Musical Experience in Hemispheric Lateralization of Global and Local Auditory Processing.

PubMed

Black, Emily; Stevenson, Jennifer L; Bish, Joel P

2017-08-01

The global precedence effect is a phenomenon in which global aspects of visual and auditory stimuli are processed before local aspects. Individuals with musical experience perform better on all aspects of auditory tasks compared with individuals with less musical experience. The hemispheric lateralization of this auditory processing is less well-defined. The present study aimed to replicate the global precedence effect with auditory stimuli and to explore the lateralization of global and local auditory processing in individuals with differing levels of musical experience. A total of 38 college students completed an auditory-directed attention task while electroencephalography was recorded. Individuals with low musical experience responded significantly faster and more accurately in global trials than in local trials regardless of condition, and significantly faster and more accurately when pitches traveled in the same direction (compatible condition) than when pitches traveled in two different directions (incompatible condition) consistent with a global precedence effect. In contrast, individuals with high musical experience showed less of a global precedence effect with regards to accuracy, but not in terms of reaction time, suggesting an increased ability to overcome global bias. Further, a difference in P300 latency between hemispheres was observed. These findings provide a preliminary neurological framework for auditory processing of individuals with differing degrees of musical experience.

Preliminary Analysis of Low-Thrust Gravity Assist Trajectories by An Inverse Method and a Global Optimization Technique.

NASA Astrophysics Data System (ADS)

de Pascale, P.; Vasile, M.; Casotto, S.

The design of interplanetary trajectories requires the solution of an optimization problem, which has been traditionally solved by resorting to various local optimization techniques. All such approaches, apart from the specific method employed (direct or indirect), require an initial guess, which deeply influences the convergence to the optimal solution. The recent developments in low-thrust propulsion have widened the perspectives of exploration of the Solar System, while they have at the same time increased the difficulty related to the trajectory design process. Continuous thrust transfers, typically characterized by multiple spiraling arcs, have a broad number of design parameters and thanks to the flexibility offered by such engines, they typically turn out to be characterized by a multi-modal domain, with a consequent larger number of optimal solutions. Thus the definition of the first guesses is even more challenging, particularly for a broad search over the design parameters, and it requires an extensive investigation of the domain in order to locate the largest number of optimal candidate solutions and possibly the global optimal one. In this paper a tool for the preliminary definition of interplanetary transfers with coast-thrust arcs and multiple swing-bys is presented. Such goal is achieved combining a novel methodology for the description of low-thrust arcs, with a global optimization algorithm based on a hybridization of an evolutionary step and a deterministic step. Low thrust arcs are described in a 3D model in order to account the beneficial effects of low-thrust propulsion for a change of inclination, resorting to a new methodology based on an inverse method. The two-point boundary values problem (TPBVP) associated with a thrust arc is solved by imposing a proper parameterized evolution of the orbital parameters, by which, the acceleration required to follow the given trajectory with respect to the constraints set is obtained simply through

Global and Local Collaborators: A Study of Scientific Collaboration.

ERIC Educational Resources Information Center

Pao, Miranda Lee

1992-01-01

Describes an empirical study that was conducted to examine the relationship among scientific co-authorship (i.e., collaboration), research funding, and productivity. Bibliographic records from the MEDLINE database that used the subject heading for schistosomiasis are analyzed, global and local collaborators are discussed, and scientific…

Local Libraries: Global Awareness. A Librarian's Guide to Global Programming for a Sustainable Future.

ERIC Educational Resources Information Center

Global Learning, Inc., Union, NJ.

This guide seeks to provide public and school librarians with a variety of practical resources and activities for contributing to the public's understanding of major global trends and relationships that affect local communities. The guide contains four sections geared towards children, young adults, adults, and school settings. The children's…

IVF policy and global/local politics: the making of multiple-embryo transfer regulation in Taiwan.

PubMed

Wu, Chia-Ling

2012-08-01

This paper analyzes the regulatory trajectory of multiple-embryo transfer in in-vitro fertilization (IVF) in Taiwan. Taking a latecomer to policy-making as the case, it argues the importance of conceptualizing the global/local dynamics in policy-making for assisted reproductive technology (ART). The conceptual framework is built upon recent literature on standardization, science policy, and global assemblage. I propose three interrelated features that reveal the "global in the local": (1) the power relationships among stakeholders, (2) the selected global form that involved actors drew upon, and (3) the re-contextualized assemblage made of local networks. Data included archives, interviews, and participant observation. In different historical periods the specific stakeholders selected different preferred global forms for Taiwan, such as Britain's code of ethics in the 1990s, the American guideline in the early 2000s, and the European trend in the mid-2000s. The global is heterogeneous. The failure to transfer the British regulation, the revision of the American guideline by adding one more embryo than it specified, and the gap between the cited European trend and the "no more than four" in Taiwan's 2007 Human Reproduction Law all show that the local network further transforms the selected global form, confining it to rhetoric only or tailoring it to local needs. Overall, Taiwanese practitioners successfully maintained their medical autonomy to build a 'flexible standardization'. Multiple pregnancy remains the most common health risk of IVF in Taiwan. Copyright © 2012 Elsevier Ltd. All rights reserved.

Optimal Control via Self-Generated Stochasticity

NASA Technical Reports Server (NTRS)

Zak, Michail

2011-01-01

The problem of global maxima of functionals has been examined. Mathematical roots of local maxima are the same as those for a much simpler problem of finding global maximum of a multi-dimensional function. The second problem is instability even if an optimal trajectory is found, there is no guarantee that it is stable. As a result, a fundamentally new approach is introduced to optimal control based upon two new ideas. The first idea is to represent the functional to be maximized as a limit of a probability density governed by the appropriately selected Liouville equation. Then, the corresponding ordinary differential equations (ODEs) become stochastic, and that sample of the solution that has the largest value will have the highest probability to appear in ODE simulation. The main advantages of the stochastic approach are that it is not sensitive to local maxima, the function to be maximized must be only integrable but not necessarily differentiable, and global equality and inequality constraints do not cause any significant obstacles. The second idea is to remove possible instability of the optimal solution by equipping the control system with a self-stabilizing device. The applications of the proposed methodology will optimize the performance of NASA spacecraft, as well as robot performance.

Identity Formation of American Indian Adolescents: Local, National, and Global Considerations

ERIC Educational Resources Information Center

Markstrom, Carol A.

2011-01-01

A conceptual model is presented that approaches identity formation of American Indian adolescents according to 3 levels of social contextual influence--local, national, and global--relative to types of identity, dynamics of identity, and sources of influence. Ethnic identity of American Indians is embedded within the local cultural milieu and…

Global and local threshold in a metapopulational SEIR model with quarantine

NASA Astrophysics Data System (ADS)

Gomes, Marcelo F. C.; Rossi, Luca; Pastore Y Piontti, Ana; Vespignani, Alessandro

2013-03-01

Diseases which have the possibility of transmission before the onset of symptoms pose a challenging threat to healthcare since it is hard to track spreaders and implement quarantine measures. More precisely, one main concerns regarding pandemic spreading of diseases is the prediction-and eventually control-of local outbreaks that will trigger a global invasion of a particular disease. We present a metapopulation disease spreading model with transmission from both symptomatic and asymptomatic agents and analyze the role of quarantine measures and mobility processes between subpopulations. We show that, depending on the disease parameters, it is possible to separate in the parameter space the local and global thresholds and study the system behavior as a function of the fraction of asymptomatic transmissions. This means that it is possible to have a range of parameters values where although we do not achieve local control of the outbreak it is possible to control the global spread of the disease. We validate the analytic picture in data-driven model that integrates commuting, air traffic flow and detailed information about population size and structure worldwide. Laboratory for the Modeling of Biological and Socio-Technical Systems (MoBS)

Effects of Age and Attention on Auditory Global-Local Processing in Children with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Foster, Nicholas E. V.; Ouimet, Tia; Tryfon, Ana; Doyle-Thomas, Krissy; Anagnostou, Evdokia; Hyde, Krista L.

2016-01-01

In vision, typically-developing (TD) individuals perceive "global" (whole) before "local" (detailed) features, whereas individuals with autism spectrum disorder (ASD) exhibit a local bias. However, auditory global-local distinctions are less clear in ASD, particularly in terms of age and attention effects. To these aims, here…

Economic optimization of a global strategy to address the pandemic threat.

PubMed

Pike, Jamison; Bogich, Tiffany; Elwood, Sarah; Finnoff, David C; Daszak, Peter

2014-12-30

Emerging pandemics threaten global health and economies and are increasing in frequency. Globally coordinated strategies to combat pandemics, similar to current strategies that address climate change, are largely adaptive, in that they attempt to reduce the impact of a pathogen after it has emerged. However, like climate change, mitigation strategies have been developed that include programs to reduce the underlying drivers of pandemics, particularly animal-to-human disease transmission. Here, we use real options economic modeling of current globally coordinated adaptation strategies for pandemic prevention. We show that they would be optimally implemented within 27 y to reduce the annual rise of emerging infectious disease events by 50% at an estimated one-time cost of approximately $343.7 billion. We then analyze World Bank data on multilateral "One Health" pandemic mitigation programs. We find that, because most pandemics have animal origins, mitigation is a more cost-effective policy than business-as-usual adaptation programs, saving between $344.0.7 billion and $360.3 billion over the next 100 y if implemented today. We conclude that globally coordinated pandemic prevention policies need to be enacted urgently to be optimally effective and that strategies to mitigate pandemics by reducing the impact of their underlying drivers are likely to be more effective than business as usual.

A Comparison of Local and Global Formulations of Thermodynamics

ERIC Educational Resources Information Center

DeVoe, Howard

2013-01-01

Several educators have advocated teaching thermodynamics using a"global" approach in place of the conventional "local" approach. This article uses four examples of experiments to illustrate the two formulations and the definitions of heat and work associated with them. Advantages and disadvantages of both approaches are…

A deterministic global optimization using smooth diagonal auxiliary functions

NASA Astrophysics Data System (ADS)

Sergeyev, Yaroslav D.; Kvasov, Dmitri E.

2015-04-01

In many practical decision-making problems it happens that functions involved in optimization process are black-box with unknown analytical representations and hard to evaluate. In this paper, a global optimization problem is considered where both the goal function f (x) and its gradient f‧ (x) are black-box functions. It is supposed that f‧ (x) satisfies the Lipschitz condition over the search hyperinterval with an unknown Lipschitz constant K. A new deterministic 'Divide-the-Best' algorithm based on efficient diagonal partitions and smooth auxiliary functions is proposed in its basic version, its convergence conditions are studied and numerical experiments executed on eight hundred test functions are presented.

Global gene expression analysis by combinatorial optimization.

PubMed

Ameur, Adam; Aurell, Erik; Carlsson, Mats; Westholm, Jakub Orzechowski

2004-01-01

Generally, there is a trade-off between methods of gene expression analysis that are precise but labor-intensive, e.g. RT-PCR, and methods that scale up to global coverage but are not quite as quantitative, e.g. microarrays. In the present paper, we show how how a known method of gene expression profiling (K. Kato, Nucleic Acids Res. 23, 3685-3690 (1995)), which relies on a fairly small number of steps, can be turned into a global gene expression measurement by advanced data post-processing, with potentially little loss of accuracy. Post-processing here entails solving an ancillary combinatorial optimization problem. Validation is performed on in silico experiments generated from the FANTOM data base of full-length mouse cDNA. We present two variants of the method. One uses state-of-the-art commercial software for solving problems of this kind, the other a code developed by us specifically for this purpose, released in the public domain under GPL license.

The factor of local cultural specificity and process of globalization.

PubMed

Rudnev, Viacheslav

2012-12-01

Cultural polymorphism is a difficult phenomenon, which has multiform influence on the society's life. The active interest of society to local folk knowledge in life-support activities and Nature using is one of the distinctive marks of modern time. This interest has fallen on the period of active transformations of environment as a result of industrial society's pressing on Nature, and the generating of new approaches in the studying of Nature and human activity based on the "technologies" of wild life. The success of humankind in creating artificial surroundings has led to both great success in improving the quality of peoples' lives, and also to problems with renewable resources and human health and to changing for the worse ecology. In 1992 the Unites Nations Conference on Environment and Development (Rio de Janeiro, Brazil) set fixed standards defining global violations of the environment. The zAgenda 21', adopted at this Conference, focused on the necessity of new solutions for problems of the relationships between Nature and Society, mentioning interdisciplinary research as a positive way to search for solutions to new problems, and citing as a goal a zbalance of Nature, Society and Humans'. Pre-industrial society had a different experience in using Nature and solving problems of life-support activity under a regime of sparing nature. Experience has shown that Folk knowledge and Folk technology can, in a number of instances, actually assist in solving high level problems caused by human impact on the environment, e.g., farming methods, and, as a result offering possibilities for a more sound and at the same time effective basis for long-term sustainable production at the local level. The traditional cultures of Eurasia were engaged in agricultural pursuits and had acquired unique experiences in maintaining soil fertility and a technology which limited the impact they were having on the environment. The value of Folk heritage in exploiting the environment

Global optimization for quantum dynamics of few-fermion systems

NASA Astrophysics Data System (ADS)

Li, Xikun; Pecak, Daniel; Sowiński, Tomasz; Sherson, Jacob; Nielsen, Anne E. B.

2018-03-01

Quantum state preparation is vital to quantum computation and quantum information processing tasks. In adiabatic state preparation, the target state is theoretically obtained with nearly perfect fidelity if the control parameter is tuned slowly enough. As this, however, leads to slow dynamics, it is often desirable to be able to carry out processes more rapidly. In this work, we employ two global optimization methods to estimate the quantum speed limit for few-fermion systems confined in a one-dimensional harmonic trap. Such systems can be produced experimentally in a well-controlled manner. We determine the optimized control fields and achieve a reduction in the ramping time of more than a factor of four compared to linear ramping. We also investigate how robust the fidelity is to small variations of the control fields away from the optimized shapes.

2-D to 3-D global/local finite element analysis of cross-ply composite laminates

NASA Technical Reports Server (NTRS)

Thompson, D. Muheim; Griffin, O. Hayden, Jr.

1990-01-01

An example of two-dimensional to three-dimensional global/local finite element analysis of a laminated composite plate with a hole is presented. The 'zoom' technique of global/local analysis is used, where displacements of the global/local interface from the two-dimensional global model are applied to the edges of the three-dimensional local model. Three different hole diameters, one, three, and six inches, are considered in order to compare the effect of hole size on the three-dimensional stress state around the hole. In addition, three different stacking sequences are analyzed for the six inch hole case in order to study the effect of stacking sequence. The existence of a 'critical' hole size, where the interlaminar stresses are maximum, is indicated. Dispersion of plies at the same angle, as opposed to clustering, is found to reduce the magnitude of some interlaminar stress components and increase others.

Age-Related Change in Shifting Attention between Global and Local Levels of Hierarchical Stimuli

ERIC Educational Resources Information Center

Huizinga, Mariette; Burack, Jacob A.; Van der Molen, Maurits W.

2010-01-01

The focus of this study was the developmental pattern of the ability to shift attention between global and local levels of hierarchical stimuli. Children aged 7 years and 11 years and 21-year-old adults were administered a task (two experiments) that allowed for the examination of 1) the direction of attention to global or local stimulus levels;…

Subcritical transition scenarios via linear and nonlinear localized optimal perturbations in plane Poiseuille flow

NASA Astrophysics Data System (ADS)

Farano, Mirko; Cherubini, Stefania; Robinet, Jean-Christophe; De Palma, Pietro

2016-12-01

Subcritical transition in plane Poiseuille flow is investigated by means of a Lagrange-multiplier direct-adjoint optimization procedure with the aim of finding localized three-dimensional perturbations optimally growing in a given time interval (target time). Space localization of these optimal perturbations (OPs) is achieved by choosing as objective function either a p-norm (with p\\gg 1) of the perturbation energy density in a linear framework; or the classical (1-norm) perturbation energy, including nonlinear effects. This work aims at analyzing the structure of linear and nonlinear localized OPs for Poiseuille flow, and comparing their transition thresholds and scenarios. The nonlinear optimization approach provides three types of solutions: a weakly nonlinear, a hairpin-like and a highly nonlinear optimal perturbation, depending on the value of the initial energy and the target time. The former shows localization only in the wall-normal direction, whereas the latter appears much more localized and breaks the spanwise symmetry found at lower target times. Both solutions show spanwise inclined vortices and large values of the streamwise component of velocity already at the initial time. On the other hand, p-norm optimal perturbations, although being strongly localized in space, keep a shape similar to linear 1-norm optimal perturbations, showing streamwise-aligned vortices characterized by low values of the streamwise velocity component. When used for initializing direct numerical simulations, in most of the cases nonlinear OPs provide the most efficient route to transition in terms of time to transition and initial energy, even when they are less localized in space than the p-norm OP. The p-norm OP follows a transition path similar to the oblique transition scenario, with slightly oscillating streaks which saturate and eventually experience secondary instability. On the other hand, the nonlinear OP rapidly forms large-amplitude bent streaks and skips the phases

The Tunneling Method for Global Optimization in Multidimensional Scaling.

ERIC Educational Resources Information Center

Groenen, Patrick J. F.; Heiser, Willem J.

1996-01-01

A tunneling method for global minimization in multidimensional scaling is introduced and adjusted for multidimensional scaling with general Minkowski distances. The method alternates a local search step with a tunneling step in which a different configuration is sought with the same STRESS implementation. (SLD)

Combining local and global limitations of visual search.

PubMed

Põder, Endel

2017-04-01

There are different opinions about the roles of local interactions and central processing capacity in visual search. This study attempts to clarify the problem using a new version of relevant set cueing. A central precue indicates two symmetrical segments (that may contain a target object) within a circular array of objects presented briefly around the fixation point. The number of objects in the relevant segments, and density of objects in the array were varied independently. Three types of search experiments were run: (a) search for a simple visual feature (color, size, and orientation); (b) conjunctions of simple features; and (c) spatial configuration of simple features (rotated Ts). For spatial configuration stimuli, the results were consistent with a fixed global processing capacity and standard crowding zones. For simple features and their conjunctions, the results were different, dependent on the features involved. While color search exhibits virtually no capacity limits or crowding, search for an orientation target was limited by both. Results for conjunctions of features can be partly explained by the results from the respective features. This study shows that visual search is limited by both local interference and global capacity, and the limitations are different for different visual features.

GLOBAL PROPERTIES OF FULLY CONVECTIVE ACCRETION DISKS FROM LOCAL SIMULATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bodo, G.; Ponzo, F.; Rossi, P.

2015-08-01

We present an approach to deriving global properties of accretion disks from the knowledge of local solutions derived from numerical simulations based on the shearing box approximation. The approach consists of a two-step procedure. First, a local solution valid for all values of the disk height is constructed by piecing together an interior solution obtained numerically with an analytical exterior radiative solution. The matching is obtained by assuming hydrostatic balance and radiative equilibrium. Although in principle the procedure can be carried out in general, it simplifies considerably when the interior solution is fully convective. In these cases, the construction ismore » analogous to the derivation of the Hayashi tracks for protostars. The second step consists of piecing together the local solutions at different radii to obtain a global solution. Here we use the symmetry of the solutions with respect to the defining dimensionless numbers—in a way similar to the use of homology relations in stellar structure theory—to obtain the scaling properties of the various disk quantities with radius.« less

Global Properties of Fully Convective Accretion Disks from Local Simulations

NASA Astrophysics Data System (ADS)

Bodo, G.; Cattaneo, F.; Mignone, A.; Ponzo, F.; Rossi, P.

2015-08-01

We present an approach to deriving global properties of accretion disks from the knowledge of local solutions derived from numerical simulations based on the shearing box approximation. The approach consists of a two-step procedure. First, a local solution valid for all values of the disk height is constructed by piecing together an interior solution obtained numerically with an analytical exterior radiative solution. The matching is obtained by assuming hydrostatic balance and radiative equilibrium. Although in principle the procedure can be carried out in general, it simplifies considerably when the interior solution is fully convective. In these cases, the construction is analogous to the derivation of the Hayashi tracks for protostars. The second step consists of piecing together the local solutions at different radii to obtain a global solution. Here we use the symmetry of the solutions with respect to the defining dimensionless numbers—in a way similar to the use of homology relations in stellar structure theory—to obtain the scaling properties of the various disk quantities with radius.

Topology Optimization of an Aircraft Wing

DTIC Science & Technology

2015-06-11

Fraction VWT Virtual Wind Tunnel xvi TOPOLOGY OPTIMIZATION OF AN AIRCRAFT WING I. Introduction 1.1 Background Current aircraft wing design , which...ware in order to optimize the design of individual spars and wing-box structures for large commercial aircraft . They considered a hybrid global/local...weight in an aircraft by eliminating unnecessary material. An optimized approach has the potential to streamline the design process by allowing a

Sub-seasonal predictability of water scarcity at global and local scale

NASA Astrophysics Data System (ADS)

Wanders, N.; Wada, Y.; Wood, E. F.

2016-12-01

Forecasting the water demand and availability for agriculture and energy production has been neglected in previous research, partly due to the fact that most large-scale hydrological models lack the skill to forecast human water demands at sub-seasonal time scale. We study the potential of a sub-seasonal water scarcity forecasting system for improved water management decision making and improved estimates of water demand and availability. We have generated 32 years of global sub-seasonal multi-model water availability, demand and scarcity forecasts. The quality of the forecasts is compared to a reference forecast derived from resampling historic weather observations. The newly developed system has been evaluated for both the global scale and in a real-time local application in the Sacramento valley for the Trinity, Shasta and Oroville reservoirs, where the water demand for agriculture and hydropower is high. On the global scale we find that the reference forecast shows high initial forecast skill (up to 8 months) for water scarcity in the eastern US, Central Asia and Sub-Saharan Africa. Adding dynamical sub-seasonal forecasts results in a clear improvement for most regions in the world, increasing the forecasts' lead time by 2 or more months on average. The strongest improvements are found in the US, Brazil, Central Asia and Australia. For the Sacramento valley we can accurately predict anomalies in the reservoir inflow, hydropower potential and the downstream irrigation water demand 6 months in advance. This allow us to forecast potential water scarcity in the Sacramento valley and adjust the reservoir management to prevent deficits in energy or irrigation water availability. The newly developed forecast system shows that it is possible to reduce the vulnerability to upcoming water scarcity events and allows optimization of the distribution of the available water between the agricultural and energy sector half a year in advance.

Hybridization of decomposition and local search for multiobjective optimization.

PubMed

Ke, Liangjun; Zhang, Qingfu; Battiti, Roberto

2014-10-01

Combining ideas from evolutionary algorithms, decomposition approaches, and Pareto local search, this paper suggests a simple yet efficient memetic algorithm for combinatorial multiobjective optimization problems: memetic algorithm based on decomposition (MOMAD). It decomposes a combinatorial multiobjective problem into a number of single objective optimization problems using an aggregation method. MOMAD evolves three populations: 1) population P(L) for recording the current solution to each subproblem; 2) population P(P) for storing starting solutions for Pareto local search; and 3) an external population P(E) for maintaining all the nondominated solutions found so far during the search. A problem-specific single objective heuristic can be applied to these subproblems to initialize the three populations. At each generation, a Pareto local search method is first applied to search a neighborhood of each solution in P(P) to update P(L) and P(E). Then a single objective local search is applied to each perturbed solution in P(L) for improving P(L) and P(E), and reinitializing P(P). The procedure is repeated until a stopping condition is met. MOMAD provides a generic hybrid multiobjective algorithmic framework in which problem specific knowledge, well developed single objective local search and heuristics and Pareto local search methods can be hybridized. It is a population based iterative method and thus an anytime algorithm. Extensive experiments have been conducted in this paper to study MOMAD and compare it with some other state-of-the-art algorithms on the multiobjective traveling salesman problem and the multiobjective knapsack problem. The experimental results show that our proposed algorithm outperforms or performs similarly to the best so far heuristics on these two problems.

Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep.

PubMed

Deco, Gustavo; Tagliazucchi, Enzo; Laufs, Helmut; Sanjuán, Ana; Kringelbach, Morten L

2017-01-01

A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states.

Early differential sensitivity of evoked-potentials to local and global shape during the perception of three-dimensional objects.

PubMed

Leek, E Charles; Roberts, Mark; Oliver, Zoe J; Cristino, Filipe; Pegna, Alan J

2016-08-01

Here we investigated the time course underlying differential processing of local and global shape information during the perception of complex three-dimensional (3D) objects. Observers made shape matching judgments about pairs of sequentially presented multi-part novel objects. Event-related potentials (ERPs) were used to measure perceptual sensitivity to 3D shape differences in terms of local part structure and global shape configuration - based on predictions derived from hierarchical structural description models of object recognition. There were three types of different object trials in which stimulus pairs (1) shared local parts but differed in global shape configuration; (2) contained different local parts but shared global configuration or (3) shared neither local parts nor global configuration. Analyses of the ERP data showed differential amplitude modulation as a function of shape similarity as early as the N1 component between 146-215ms post-stimulus onset. These negative amplitude deflections were more similar between objects sharing global shape configuration than local part structure. Differentiation among all stimulus types was reflected in N2 amplitude modulations between 276-330ms. sLORETA inverse solutions showed stronger involvement of left occipitotemporal areas during the N1 for object discrimination weighted towards local part structure. The results suggest that the perception of 3D object shape involves parallel processing of information at local and global scales. This processing is characterised by relatively slow derivation of 'fine-grained' local shape structure, and fast derivation of 'coarse-grained' global shape configuration. We propose that the rapid early derivation of global shape attributes underlies the observed patterns of N1 amplitude modulations. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Ringed Seal Search for Global Optimization via a Sensitive Search Model.

PubMed

Saadi, Younes; Yanto, Iwan Tri Riyadi; Herawan, Tutut; Balakrishnan, Vimala; Chiroma, Haruna; Risnumawan, Anhar

2016-01-01

The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global

Ringed Seal Search for Global Optimization via a Sensitive Search Model

PubMed Central

Saadi, Younes; Yanto, Iwan Tri Riyadi; Herawan, Tutut; Balakrishnan, Vimala; Chiroma, Haruna; Risnumawan, Anhar

2016-01-01

The efficiency of a metaheuristic algorithm for global optimization is based on its ability to search and find the global optimum. However, a good search often requires to be balanced between exploration and exploitation of the search space. In this paper, a new metaheuristic algorithm called Ringed Seal Search (RSS) is introduced. It is inspired by the natural behavior of the seal pup. This algorithm mimics the seal pup movement behavior and its ability to search and choose the best lair to escape predators. The scenario starts once the seal mother gives birth to a new pup in a birthing lair that is constructed for this purpose. The seal pup strategy consists of searching and selecting the best lair by performing a random walk to find a new lair. Affected by the sensitive nature of seals against external noise emitted by predators, the random walk of the seal pup takes two different search states, normal state and urgent state. In the normal state, the pup performs an intensive search between closely adjacent lairs; this movement is modeled via a Brownian walk. In an urgent state, the pup leaves the proximity area and performs an extensive search to find a new lair from sparse targets; this movement is modeled via a Levy walk. The switch between these two states is realized by the random noise emitted by predators. The algorithm keeps switching between normal and urgent states until the global optimum is reached. Tests and validations were performed using fifteen benchmark test functions to compare the performance of RSS with other baseline algorithms. The results show that RSS is more efficient than Genetic Algorithm, Particles Swarm Optimization and Cuckoo Search in terms of convergence rate to the global optimum. The RSS shows an improvement in terms of balance between exploration (extensive) and exploitation (intensive) of the search space. The RSS can efficiently mimic seal pups behavior to find best lair and provide a new algorithm to be used in global

Teaching and Learning Road Map for Schools: Global and yet Local!

ERIC Educational Resources Information Center

Mehrmohammadi, Mahmoud

2011-01-01

What is a viable theoretical scheme that can guide school curriculum deliberations, maintaining both a global and a local quality OR which curriculum theory has the power of being adopted universally and the versatility of being adapted locally? Can the notion of "Glocal" coined in the field of sociology (2010) be regarded as a meaningful and…

Modulation of Folding Internal Friction by Local and Global Barrier Heights.

PubMed

Zheng, Wenwei; de Sancho, David; Best, Robert B

2016-03-17

Recent experiments have revealed an unexpected deviation from a first power dependence of protein relaxation times on solvent viscosity, an effect that has been attributed to "internal friction". One clear source of internal friction in protein dynamics is the isomerization of dihedral angles. A key outstanding question is whether the global folding barrier height influences the measured internal friction, based on the observation that the folding rates of fast-folding proteins, with smaller folding free energy barriers, tend to exhibit larger internal friction. Here, by studying two alanine-based peptides, we find that systematic variation of global folding barrier heights has little effect on the internal friction for folding rates. On the other hand, increasing local torsion angle barriers leads to increased internal friction, which is consistent with solvent memory effects being the origin of the viscosity dependence. Thus, it appears that local torsion transitions determine the viscosity dependence of the diffusion coefficient on the global coordinate and, in turn, internal friction effects on the folding rate.

Optimization modeling of U.S. renewable electricity deployment using local input variables

NASA Astrophysics Data System (ADS)

Bernstein, Adam

For the past five years, state Renewable Portfolio Standard (RPS) laws have been a primary driver of renewable electricity (RE) deployments in the United States. However, four key trends currently developing: (i) lower natural gas prices, (ii) slower growth in electricity demand, (iii) challenges of system balancing intermittent RE within the U.S. transmission regions, and (iv) fewer economical sites for RE development, may limit the efficacy of RPS laws over the remainder of the current RPS statutes' lifetime. An outsized proportion of U.S. RE build occurs in a small number of favorable locations, increasing the effects of these variables on marginal RE capacity additions. A state-by-state analysis is necessary to study the U.S. electric sector and to generate technology specific generation forecasts. We used LP optimization modeling similar to the National Renewable Energy Laboratory (NREL) Renewable Energy Development System (ReEDS) to forecast RE deployment across the 8 U.S. states with the largest electricity load, and found state-level RE projections to Year 2031 significantly lower than thoseimplied in the Energy Information Administration (EIA) 2013 Annual Energy Outlook forecast. Additionally, the majority of states do not achieve their RPS targets in our forecast. Combined with the tendency of prior research and RE forecasts to focus on larger national and global scale models, we posit that further bottom-up state and local analysis is needed for more accurate policy assessment, forecasting, and ongoing revision of variables as parameter values evolve through time. Current optimization software eliminates much of the need for algorithm coding and programming, allowing for rapid model construction and updating across many customized state and local RE parameters. Further, our results can be tested against the empirical outcomes that will be observed over the coming years, and the forecast deviation from the actuals can be attributed to discrete parameter

Local and Global Processing: Observations from a Remote Culture

ERIC Educational Resources Information Center

Davidoff, Jules; Fonteneau, Elisabeth; Fagot, Joel

2008-01-01

In Experiment 1, a normal adult population drawn from a remote culture (Himba) in northern Namibia made similarity matches to [Navon, D. (1977). Forest before trees: The precedence of global features in visual perception. "Cognitive Psychology", 9, 353-383] hierarchical figures. The Himba showed a local bias stronger than that has been…

Economic optimization of a global strategy to address the pandemic threat

PubMed Central

Pike, Jamison; Bogich, Tiffany; Elwood, Sarah; Finnoff, David C.; Daszak, Peter

2014-01-01

Emerging pandemics threaten global health and economies and are increasing in frequency. Globally coordinated strategies to combat pandemics, similar to current strategies that address climate change, are largely adaptive, in that they attempt to reduce the impact of a pathogen after it has emerged. However, like climate change, mitigation strategies have been developed that include programs to reduce the underlying drivers of pandemics, particularly animal-to-human disease transmission. Here, we use real options economic modeling of current globally coordinated adaptation strategies for pandemic prevention. We show that they would be optimally implemented within 27 y to reduce the annual rise of emerging infectious disease events by 50% at an estimated one-time cost of approximately $343.7 billion. We then analyze World Bank data on multilateral “One Health” pandemic mitigation programs. We find that, because most pandemics have animal origins, mitigation is a more cost-effective policy than business-as-usual adaptation programs, saving between $344.0.7 billion and $360.3 billion over the next 100 y if implemented today. We conclude that globally coordinated pandemic prevention policies need to be enacted urgently to be optimally effective and that strategies to mitigate pandemics by reducing the impact of their underlying drivers are likely to be more effective than business as usual. PMID:25512538

Global evolutionary isolation measures can capture key local conservation species in Nearctic and Neotropical bird communities

PubMed Central

Redding, David W.; Mooers, Arne O.; Şekercioğlu, Çağan H.; Collen, Ben

2015-01-01

Understanding how to prioritize among the most deserving imperilled species has been a focus of biodiversity science for the past three decades. Though global metrics that integrate evolutionary history and likelihood of loss have been successfully implemented, conservation is typically carried out at sub-global scales on communities of species rather than among members of complete taxonomic assemblages. Whether and how global measures map to a local scale has received little scrutiny. At a local scale, conservation-relevant assemblages of species are likely to be made up of relatively few species spread across a large phylogenetic tree, and as a consequence there are potentially relatively large amounts of evolutionary history at stake. We ask to what extent global metrics of evolutionary history are useful for conservation priority setting at the community level by evaluating the extent to which three global measures of evolutionary isolation (evolutionary distinctiveness (ED), average pairwise distance (APD) and the pendant edge or unique phylogenetic diversity (PD) contribution) capture community-level phylogenetic and trait diversity for a large sample of Neotropical and Nearctic bird communities. We find that prioritizing the most ED species globally safeguards more than twice the total PD of local communities on average, but that this does not translate into increased local trait diversity. By contrast, global APD is strongly related to the APD of those same species at the community level, and prioritizing these species also safeguards local PD and trait diversity. The next step for biologists is to understand the variation in the concordance of global and local level scores and what this means for conservation priorities: we need more directed research on the use of different measures of evolutionary isolation to determine which might best capture desirable aspects of biodiversity. PMID:25561674

Maximal incompatibility of locally classical behavior and global causal order in multiparty scenarios

NASA Astrophysics Data System (ADS)

Baumeler, ńmin; Feix, Adrien; Wolf, Stefan

2014-10-01

Quantum theory in a global spacetime gives rise to nonlocal correlations, which cannot be explained causally in a satisfactory way; this motivates the study of theories with reduced global assumptions. Oreshkov, Costa, and Brukner [Nat. Commun. 3, 1092 (2012), 10.1038/ncomms2076] proposed a framework in which quantum theory is valid locally but where, at the same time, no global spacetime, i.e., predefined causal order, is assumed beyond the absence of logical paradoxes. It was shown for the two-party case, however, that a global causal order always emerges in the classical limit. Quite naturally, it has been conjectured that the same also holds in the multiparty setting. We show that, counter to this belief, classical correlations locally compatible with classical probability theory exist that allow for deterministic signaling between three or more parties incompatible with any predefined causal order.

Optimal dietary patterns designed from local foods to achieve maternal nutritional goals.

PubMed

Raymond, Jofrey; Kassim, Neema; Rose, Jerman W; Agaba, Morris

2018-04-04

Achieving nutritional requirements for pregnant and lactating mothers in rural households while maintaining the intake of local and culture-specific foods can be a difficult task. Deploying a linear goal programming approach can effectively generate optimal dietary patterns that incorporate local and culturally acceptable diets. The primary objective of this study was to determine whether a realistic and affordable diet that achieves nutritional goals for rural pregnant and lactating women can be formulated from locally available foods in Tanzania. A cross sectional study was conducted to assess dietary intakes of 150 pregnant and lactating women using a weighed dietary record (WDR), 24 h dietary recalls and a 7-days food record. A market survey was also carried out to estimate the cost per 100 g of edible portion of foods that are frequently consumed in the study population. Dietary survey and market data were then used to define linear programming (LP) model parameters for diet optimisation. All LP analyses were done using linear program solver to generate optimal dietary patterns. Our findings showed that optimal dietary patterns designed from locally available foods would improve dietary adequacy for 15 and 19 selected nutrients in pregnant and lactating women, respectively, but inadequacies remained for iron, zinc, folate, pantothenic acid, and vitamin E, indicating that these are problem nutrients (nutrients that did not achieve 100% of their RNIs in optimised diets) in the study population. These findings suggest that optimal use of local foods can improve dietary adequacy for rural pregnant and lactating women aged 19-50 years. However, additional cost-effective interventions are needed to ensure adequate intakes for the identified problem nutrients.

Local and global dynamics of Ramsey model: From continuous to discrete time.

PubMed

Guzowska, Malgorzata; Michetti, Elisabetta

2018-05-01

The choice of time as a discrete or continuous variable may radically affect equilibrium stability in an endogenous growth model with durable consumption. In the continuous-time Ramsey model [F. P. Ramsey, Econ. J. 38(152), 543-559 (1928)], the steady state is locally saddle-path stable with monotonic convergence. However, in the discrete-time version, the steady state may be unstable or saddle-path stable with monotonic or oscillatory convergence or periodic solutions [see R.-A. Dana et al., Handbook on Optimal Growth 1 (Springer, 2006) and G. Sorger, Working Paper No. 1505 (2015)]. When this occurs, the discrete-time counterpart of the continuous-time model is not consistent with the initial framework. In order to obtain a discrete-time Ramsey model preserving the main properties of the continuous-time counterpart, we use a general backward and forward discretisation as initially proposed by Bosi and Ragot [Theor. Econ. Lett. 2(1), 10-15 (2012)]. The main result of the study here presented is that, with this hybrid discretisation method, fixed points and local dynamics do not change. For what it concerns global dynamics, i.e., long-run behavior for initial conditions taken on the state space, we mainly perform numerical analysis with the main scope of comparing both qualitative and quantitative evolution of the two systems, also varying some parameters of interest.

Local and global dynamics of Ramsey model: From continuous to discrete time

NASA Astrophysics Data System (ADS)

Guzowska, Malgorzata; Michetti, Elisabetta

2018-05-01

The choice of time as a discrete or continuous variable may radically affect equilibrium stability in an endogenous growth model with durable consumption. In the continuous-time Ramsey model [F. P. Ramsey, Econ. J. 38(152), 543-559 (1928)], the steady state is locally saddle-path stable with monotonic convergence. However, in the discrete-time version, the steady state may be unstable or saddle-path stable with monotonic or oscillatory convergence or periodic solutions [see R.-A. Dana et al., Handbook on Optimal Growth 1 (Springer, 2006) and G. Sorger, Working Paper No. 1505 (2015)]. When this occurs, the discrete-time counterpart of the continuous-time model is not consistent with the initial framework. In order to obtain a discrete-time Ramsey model preserving the main properties of the continuous-time counterpart, we use a general backward and forward discretisation as initially proposed by Bosi and Ragot [Theor. Econ. Lett. 2(1), 10-15 (2012)]. The main result of the study here presented is that, with this hybrid discretisation method, fixed points and local dynamics do not change. For what it concerns global dynamics, i.e., long-run behavior for initial conditions taken on the state space, we mainly perform numerical analysis with the main scope of comparing both qualitative and quantitative evolution of the two systems, also varying some parameters of interest.

Modeling intraspecific adaptation of Abies sachalinensis to local altitude and responses to global warming, based on a 36-year reciprocal transplant experiment.

PubMed

Ishizuka, Wataru; Goto, Susumu

2012-04-01

Intraspecific adaptation in Abies sachalinensis was examined using models based on long-term monitoring data gathered during a reciprocal transplant experiment with eight seed source populations and six transplantation sites along an altitudinal gradient. The consequence of local adaptation was evaluated by testing the home-site advantage for upslope and downslope transplants at five ages. The populations' fitness-linked trait was set as their productivity (tree height × survival rate) at each age. The effects of global warming were evaluated on the basis of the 36-year performance of downslope transplants. Evidence was found for adaptive genetic variation affecting both height and survival from an early age. Increasing the distance between seed source and planting site significantly reduced productivity for both upslope and downslope transplantation, demonstrating the existence of a significant home-site advantage. The decrease in productivity was most distinct for upslope transplantations, indicating strong local adaptation to high altitudes. Global warming is predicted to increase the productivity of high-altitude populations. However, owing to their existing local adaptation, all tested populations exhibited lower productivity under warming than demes that were optimal for the new climate. These negative predictions should be considered when planning the management of locally adapted plant species such as A. sachalinensis.

Kullback-Leibler Divergence-Based Differential Evolution Markov Chain Filter for Global Localization of Mobile Robots.

PubMed

Martín, Fernando; Moreno, Luis; Garrido, Santiago; Blanco, Dolores

2015-09-16

One of the most important skills desired for a mobile robot is the ability to obtain its own location even in challenging environments. The information provided by the sensing system is used here to solve the global localization problem. In our previous work, we designed different algorithms founded on evolutionary strategies in order to solve the aforementioned task. The latest developments are presented in this paper. The engine of the localization module is a combination of the Markov chain Monte Carlo sampling technique and the Differential Evolution method, which results in a particle filter based on the minimization of a fitness function. The robot's pose is estimated from a set of possible locations weighted by a cost value. The measurements of the perceptive sensors are used together with the predicted ones in a known map to define a cost function to optimize. Although most localization methods rely on quadratic fitness functions, the sensed information is processed asymmetrically in this filter. The Kullback-Leibler divergence is the basis of a cost function that makes it possible to deal with different types of occlusions. The algorithm performance has been checked in a real map. The results are excellent in environments with dynamic and unmodeled obstacles, a fact that causes occlusions in the sensing area.

Kullback-Leibler Divergence-Based Differential Evolution Markov Chain Filter for Global Localization of Mobile Robots

PubMed Central

Martín, Fernando; Moreno, Luis; Garrido, Santiago; Blanco, Dolores

2015-01-01

One of the most important skills desired for a mobile robot is the ability to obtain its own location even in challenging environments. The information provided by the sensing system is used here to solve the global localization problem. In our previous work, we designed different algorithms founded on evolutionary strategies in order to solve the aforementioned task. The latest developments are presented in this paper. The engine of the localization module is a combination of the Markov chain Monte Carlo sampling technique and the Differential Evolution method, which results in a particle filter based on the minimization of a fitness function. The robot’s pose is estimated from a set of possible locations weighted by a cost value. The measurements of the perceptive sensors are used together with the predicted ones in a known map to define a cost function to optimize. Although most localization methods rely on quadratic fitness functions, the sensed information is processed asymmetrically in this filter. The Kullback-Leibler divergence is the basis of a cost function that makes it possible to deal with different types of occlusions. The algorithm performance has been checked in a real map. The results are excellent in environments with dynamic and unmodeled obstacles, a fact that causes occlusions in the sensing area. PMID:26389914

Towards enhancement of performance of K-means clustering using nature-inspired optimization algorithms.

PubMed

Fong, Simon; Deb, Suash; Yang, Xin-She; Zhuang, Yan

2014-01-01

Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms help speed up the clustering process by converging into a global optimum early with multiple search agents in action. Inspired by nature, some contemporary optimization algorithms which include Ant, Bat, Cuckoo, Firefly, and Wolf search algorithms mimic the swarming behavior allowing them to cooperatively steer towards an optimal objective within a reasonable time. It is known that these so-called nature-inspired optimization algorithms have their own characteristics as well as pros and cons in different applications. When these algorithms are combined with K-means clustering mechanism for the sake of enhancing its clustering quality by avoiding local optima and finding global optima, the new hybrids are anticipated to produce unprecedented performance. In this paper, we report the results of our evaluation experiments on the integration of nature-inspired optimization methods into K-means algorithms. In addition to the standard evaluation metrics in evaluating clustering quality, the extended K-means algorithms that are empowered by nature-inspired optimization methods are applied on image segmentation as a case study of application scenario.

Optimization of global model composed of radial basis functions using the term-ranking approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, Peng; Tao, Chao, E-mail: taochao@nju.edu.cn; Liu, Xiao-Jun

2014-03-15

A term-ranking method is put forward to optimize the global model composed of radial basis functions to improve the predictability of the model. The effectiveness of the proposed method is examined by numerical simulation and experimental data. Numerical simulations indicate that this method can significantly lengthen the prediction time and decrease the Bayesian information criterion of the model. The application to real voice signal shows that the optimized global model can capture more predictable component in chaos-like voice data and simultaneously reduce the predictable component (periodic pitch) in the residual signal.

Global Parameter Optimization of CLM4.5 Using Sparse-Grid Based Surrogates

NASA Astrophysics Data System (ADS)

Lu, D.; Ricciuto, D. M.; Gu, L.

2016-12-01

Calibration of the Community Land Model (CLM) is challenging because of its model complexity, large parameter sets, and significant computational requirements. Therefore, only a limited number of simulations can be allowed in any attempt to find a near-optimal solution within an affordable time. The goal of this study is to calibrate some of the CLM parameters in order to improve model projection of carbon fluxes. To this end, we propose a computationally efficient global optimization procedure using sparse-grid based surrogates. We first use advanced sparse grid (SG) interpolation to construct a surrogate system of the actual CLM model, and then we calibrate the surrogate model in the optimization process. As the surrogate model is a polynomial whose evaluation is fast, it can be efficiently evaluated with sufficiently large number of times in the optimization, which facilitates the global search. We calibrate five parameters against 12 months of GPP, NEP, and TLAI data from the U.S. Missouri Ozark (US-MOz) tower. The results indicate that an accurate surrogate model can be created for the CLM4.5 with a relatively small number of SG points (i.e., CLM4.5 simulations), and the application of the optimized parameters leads to a higher predictive capacity than the default parameter values in the CLM4.5 for the US-MOz site.

Reinforcement active learning in the vibrissae system: optimal object localization.

PubMed

Gordon, Goren; Dorfman, Nimrod; Ahissar, Ehud

2013-01-01

Rats move their whiskers to acquire information about their environment. It has been observed that they palpate novel objects and objects they are required to localize in space. We analyze whisker-based object localization using two complementary paradigms, namely, active learning and intrinsic-reward reinforcement learning. Active learning algorithms select the next training samples according to the hypothesized solution in order to better discriminate between correct and incorrect labels. Intrinsic-reward reinforcement learning uses prediction errors as the reward to an actor-critic design, such that behavior converges to the one that optimizes the learning process. We show that in the context of object localization, the two paradigms result in palpation whisking as their respective optimal solution. These results suggest that rats may employ principles of active learning and/or intrinsic reward in tactile exploration and can guide future research to seek the underlying neuronal mechanisms that implement them. Furthermore, these paradigms are easily transferable to biomimetic whisker-based artificial sensors and can improve the active exploration of their environment. Copyright © 2012 Elsevier Ltd. All rights reserved.

Attention to local and global levels of hierarchical Navon figures affects rapid scene categorization.

PubMed

Brand, John; Johnson, Aaron P

2014-01-01

In four experiments, we investigated how attention to local and global levels of hierarchical Navon figures affected the selection of diagnostic spatial scale information used in scene categorization. We explored this issue by asking observers to classify hybrid images (i.e., images that contain low spatial frequency (LSF) content of one image, and high spatial frequency (HSF) content from a second image) immediately following global and local Navon tasks. Hybrid images can be classified according to either their LSF, or HSF content; thus, making them ideal for investigating diagnostic spatial scale preference. Although observers were sensitive to both spatial scales (Experiment 1), they overwhelmingly preferred to classify hybrids based on LSF content (Experiment 2). In Experiment 3, we demonstrated that LSF based hybrid categorization was faster following global Navon tasks, suggesting that LSF processing associated with global Navon tasks primed the selection of LSFs in hybrid images. In Experiment 4, replicating Experiment 3 but suppressing the LSF information in Navon letters by contrast balancing the stimuli examined this hypothesis. Similar to Experiment 3, observers preferred to classify hybrids based on LSF content; however and in contrast, LSF based hybrid categorization was slower following global than local Navon tasks.

Random matrix theory and cross-correlations in global financial indices and local stock market indices

NASA Astrophysics Data System (ADS)

Nobi, Ashadun; Maeng, Seong Eun; Ha, Gyeong Gyun; Lee, Jae Woo

2013-02-01

We analyzed cross-correlations between price fluctuations of global financial indices (20 daily stock indices over the world) and local indices (daily indices of 200 companies in the Korean stock market) by using random matrix theory (RMT). We compared eigenvalues and components of the largest and the second largest eigenvectors of the cross-correlation matrix before, during, and after the global financial the crisis in the year 2008. We find that the majority of its eigenvalues fall within the RMT bounds [ λ -, λ +], where λ - and λ + are the lower and the upper bounds of the eigenvalues of random correlation matrices. The components of the eigenvectors for the largest positive eigenvalues indicate the identical financial market mode dominating the global and local indices. On the other hand, the components of the eigenvector corresponding to the second largest eigenvalue are positive and negative values alternatively. The components before the crisis change sign during the crisis, and those during the crisis change sign after the crisis. The largest inverse participation ratio (IPR) corresponding to the smallest eigenvector is higher after the crisis than during any other periods in the global and local indices. During the global financial the crisis, the correlations among the global indices and among the local stock indices are perturbed significantly. However, the correlations between indices quickly recover the trends before the crisis.

Fat water decomposition using globally optimal surface estimation (GOOSE) algorithm.

PubMed

Cui, Chen; Wu, Xiaodong; Newell, John D; Jacob, Mathews

2015-03-01

This article focuses on developing a novel noniterative fat water decomposition algorithm more robust to fat water swaps and related ambiguities. Field map estimation is reformulated as a constrained surface estimation problem to exploit the spatial smoothness of the field, thus minimizing the ambiguities in the recovery. Specifically, the differences in the field map-induced frequency shift between adjacent voxels are constrained to be in a finite range. The discretization of the above problem yields a graph optimization scheme, where each node of the graph is only connected with few other nodes. Thanks to the low graph connectivity, the problem is solved efficiently using a noniterative graph cut algorithm. The global minimum of the constrained optimization problem is guaranteed. The performance of the algorithm is compared with that of state-of-the-art schemes. Quantitative comparisons are also made against reference data. The proposed algorithm is observed to yield more robust fat water estimates with fewer fat water swaps and better quantitative results than other state-of-the-art algorithms in a range of challenging applications. The proposed algorithm is capable of considerably reducing the swaps in challenging fat water decomposition problems. The experiments demonstrate the benefit of using explicit smoothness constraints in field map estimation and solving the problem using a globally convergent graph-cut optimization algorithm. © 2014 Wiley Periodicals, Inc.

Visual Search in ASD: Instructed Versus Spontaneous Local and Global Processing.

PubMed

Van der Hallen, Ruth; Evers, Kris; Boets, Bart; Steyaert, Jean; Noens, Ilse; Wagemans, Johan

2016-09-01

Visual search has been used extensively to investigate differences in mid-level visual processing between individuals with ASD and TD individuals. The current study employed two visual search paradigms with Gaborized stimuli to assess the impact of task distractors (Experiment 1) and task instruction (Experiment 2) on local-global visual processing in ASD versus TD children. Experiment 1 revealed both groups to be equally sensitive to the absence or presence of a distractor, regardless of the type of target or type of distractor. Experiment 2 revealed a differential effect of task instruction for ASD compared to TD, regardless of the type of target. Taken together, these results stress the importance of task factors in the study of local-global visual processing in ASD.

Novel Intrinsic Ignition Method Measuring Local-Global Integration Characterizes Wakefulness and Deep Sleep

PubMed Central

Tagliazucchi, Enzo; Sanjuán, Ana

2017-01-01

Abstract A precise definition of a brain state has proven elusive. Here, we introduce the novel local-global concept of intrinsic ignition characterizing the dynamical complexity of different brain states. Naturally occurring intrinsic ignition events reflect the capability of a given brain area to propagate neuronal activity to other regions, giving rise to different levels of integration. The ignitory capability of brain regions is computed by the elicited level of integration for each intrinsic ignition event in each brain region, averaged over all events. This intrinsic ignition method is shown to clearly distinguish human neuroimaging data of two fundamental brain states (wakefulness and deep sleep). Importantly, whole-brain computational modelling of this data shows that at the optimal working point is found where there is maximal variability of the intrinsic ignition across brain regions. Thus, combining whole brain models with intrinsic ignition can provide novel insights into underlying mechanisms of brain states. PMID:28966977

Global and Local Features Based Classification for Bleed-Through Removal

NASA Astrophysics Data System (ADS)

Hu, Xiangyu; Lin, Hui; Li, Shutao; Sun, Bin

2016-12-01

The text on one side of historical documents often seeps through and appears on the other side, so the bleed-through is a common problem in historical document images. It makes the document images hard to read and the text difficult to recognize. To improve the image quality and readability, the bleed-through has to be removed. This paper proposes a global and local features extraction based bleed-through removal method. The Gaussian mixture model is used to get the global features of the images. Local features are extracted by the patch around each pixel. Then, the extreme learning machine classifier is utilized to classify the scanned images into the foreground text and the bleed-through component. Experimental results on real document image datasets show that the proposed method outperforms the state-of-the-art bleed-through removal methods and preserves the text strokes well.

Content based Image Retrieval based on Different Global and Local Color Histogram Methods: A Survey

NASA Astrophysics Data System (ADS)

Suhasini, Pallikonda Sarah; Sri Rama Krishna, K.; Murali Krishna, I. V.

2017-02-01

Different global and local color histogram methods for content based image retrieval (CBIR) are investigated in this paper. Color histogram is a widely used descriptor for CBIR. Conventional method of extracting color histogram is global, which misses the spatial content, is less invariant to deformation and viewpoint changes, and results in a very large three dimensional histogram corresponding to the color space used. To address the above deficiencies, different global and local histogram methods are proposed in recent research. Different ways of extracting local histograms to have spatial correspondence, invariant colour histogram to add deformation and viewpoint invariance and fuzzy linking method to reduce the size of the histogram are found in recent papers. The color space and the distance metric used are vital in obtaining color histogram. In this paper the performance of CBIR based on different global and local color histograms in three different color spaces, namely, RGB, HSV, L*a*b* and also with three distance measures Euclidean, Quadratic and Histogram intersection are surveyed, to choose appropriate method for future research.

Competition between global and local online social networks.

PubMed

Kleineberg, Kaj-Kolja; Boguñá, Marián

2016-04-27

The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

Competition between global and local online social networks

NASA Astrophysics Data System (ADS)

Kleineberg, Kaj-Kolja; Boguñá, Marián

2016-04-01

The overwhelming success of online social networks, the key actors in the Web 2.0 cosmos, has reshaped human interactions globally. To help understand the fundamental mechanisms which determine the fate of online social networks at the system level, we describe the digital world as a complex ecosystem of interacting networks. In this paper, we study the impact of heterogeneity in network fitnesses on the competition between an international network, such as Facebook, and local services. The higher fitness of international networks is induced by their ability to attract users from all over the world, which can then establish social interactions without the limitations of local networks. In other words, inter-country social ties lead to increased fitness of the international network. To study the competition between an international network and local ones, we construct a 1:1000 scale model of the digital world, consisting of the 80 countries with the most Internet users. Under certain conditions, this leads to the extinction of local networks; whereas under different conditions, local networks can persist and even dominate completely. In particular, our model suggests that, with the parameters that best reproduce the empirical overtake of Facebook, this overtake could have not taken place with a significant probability.

An evaluation of methods for estimating the number of local optima in combinatorial optimization problems.

PubMed

Hernando, Leticia; Mendiburu, Alexander; Lozano, Jose A

2013-01-01

The solution of many combinatorial optimization problems is carried out by metaheuristics, which generally make use of local search algorithms. These algorithms use some kind of neighborhood structure over the search space. The performance of the algorithms strongly depends on the properties that the neighborhood imposes on the search space. One of these properties is the number of local optima. Given an instance of a combinatorial optimization problem and a neighborhood, the estimation of the number of local optima can help not only to measure the complexity of the instance, but also to choose the most convenient neighborhood to solve it. In this paper we review and evaluate several methods to estimate the number of local optima in combinatorial optimization problems. The methods reviewed not only come from the combinatorial optimization literature, but also from the statistical literature. A thorough evaluation in synthetic as well as real problems is given. We conclude by providing recommendations of methods for several scenarios.

Dispositional Optimism and Terminal Decline in Global Quality of Life

ERIC Educational Resources Information Center

Zaslavsky, Oleg; Palgi, Yuval; Rillamas-Sun, Eileen; LaCroix, Andrea Z.; Schnall, Eliezer; Woods, Nancy F.; Cochrane, Barbara B.; Garcia, Lorena; Hingle, Melanie; Post, Stephen; Seguin, Rebecca; Tindle, Hilary; Shrira, Amit

2015-01-01

We examined whether dispositional optimism relates to change in global quality of life (QOL) as a function of either chronological age or years to impending death. We used a sample of 2,096 deceased postmenopausal women from the Women's Health Initiative clinical trials who were enrolled in the 2005-2010 Extension Study and for whom at least 1…

Systems Factorial Technology provides new insights on global-local information processing in autism spectrum disorders.

PubMed

Johnson, Shannon A; Blaha, Leslie M; Houpt, Joseph W; Townsend, James T

2010-02-01

Previous studies of global-local processing in autism spectrum disorders (ASDs) have indicated mixed findings, with some evidence of a local processing bias, or preference for detail-level information, and other results suggesting typical global advantage, or preference for the whole or gestalt. Findings resulting from this paradigm have been used to argue for or against a detail focused processing bias in ASDs, and thus have important theoretical implications. We applied Systems Factorial Technology, and the associated Double Factorial Paradigm (both defined in the text), to examine information processing characteristics during a divided attention global-local task in high-functioning individuals with an ASD and typically developing controls. Group data revealed global advantage for both groups, contrary to some current theories of ASDs. Information processing models applied to each participant revealed that task performance, although showing no differences at the group level, was supported by different cognitive mechanisms in ASD participants compared to controls. All control participants demonstrated inhibitory parallel processing and the majority demonstrated a minimum-time stopping rule. In contrast, ASD participants showed exhaustive parallel processing with mild facilitatory interactions between global and local information. Thus our results indicate fundamental differences in the stopping rules and channel dependencies in individuals with an ASD.

On influences of global and local cues on the rate of synchronization of oscillator networks

PubMed Central

Wang, Yongqiang; Doyle, Francis J.

2011-01-01

Synchronization of connected oscillator networks under global and local cues is ubiquitous in both science and engineering. Over the last few decades, enormous attention has been paid to study synchronization conditions of connected oscillators in chemistry, physics, mechanics, and particularly in biology. However, the influences of global and local cues on the rate of synchronization have not been fully studied. It is widespread that synchronization is achieved in the simultaneous presence of both global and local cues, such as intercellular coupling signals and external entrainment signals in terms of biological oscillators, and inter-neighbor coupling signals between follower nodes and central guiding signals in terms of groups of mobile autonomous agents. We prove in this paper that strength of the global cue is the only determinant of the rate of synchronization. More specifically, we prove that a stronger global cue means a faster rate of synchronization whereas a stronger local cue does not necessarily make the synchronization rate faster. Our results not only apply to the noise free case, but also apply to the case that the oscillator natural frequencies are subject to white noise. The analysis does not require the interplay to be symmetric or balanced. Simulation results are given to illustrate the proposed results. PMID:21607201

Research on global path planning based on ant colony optimization for AUV

NASA Astrophysics Data System (ADS)

Wang, Hong-Jian; Xiong, Wei

2009-03-01

Path planning is an important issue for autonomous underwater vehicles (AUVs) traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization (ACO) were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.

Forecasting an invasive species’ distribution with global distribution data, local data, and physiological information

USGS Publications Warehouse

Jarnevich, Catherine S.; Young, Nicholas E.; Talbert, Marian; Talbert, Colin

2018-01-01

Understanding invasive species distributions and potential invasions often requires broad‐scale information on the environmental tolerances of the species. Further, resource managers are often faced with knowing these broad‐scale relationships as well as nuanced environmental factors related to their landscape that influence where an invasive species occurs and potentially could occur. Using invasive buffelgrass (Cenchrus ciliaris), we developed global models and local models for Saguaro National Park, Arizona, USA, based on location records and literature on physiological tolerances to environmental factors to investigate whether environmental relationships of a species at a global scale are also important at local scales. In addition to correlative models with five commonly used algorithms, we also developed a model using a priori user‐defined relationships between occurrence and environmental characteristics based on a literature review. All correlative models at both scales performed well based on statistical evaluations. The user‐defined curves closely matched those produced by the correlative models, indicating that the correlative models may be capturing mechanisms driving the distribution of buffelgrass. Given climate projections for the region, both global and local models indicate that conditions at Saguaro National Park may become more suitable for buffelgrass. Combining global and local data with correlative models and physiological information provided a holistic approach to forecasting invasive species distributions.

Navigating catastrophes: Local but not global optimisation allows for macro-economic navigation of crises

NASA Astrophysics Data System (ADS)

Harré, Michael S.

2013-02-01

Two aspects of modern economic theory have dominated the recent discussion on the state of the global economy: Crashes in financial markets and whether or not traditional notions of economic equilibrium have any validity. We have all seen the consequences of market crashes: plummeting share prices, businesses collapsing and considerable uncertainty throughout the global economy. This seems contrary to what might be expected of a system in equilibrium where growth dominates the relatively minor fluctuations in prices. Recent work from within economics as well as by physicists, psychologists and computational scientists has significantly improved our understanding of the more complex aspects of these systems. With this interdisciplinary approach in mind, a behavioural economics model of local optimisation is introduced and three general properties are proven. The first is that under very specific conditions local optimisation leads to a conventional macro-economic notion of a global equilibrium. The second is that if both global optimisation and economic growth are required then under very mild assumptions market catastrophes are an unavoidable consequence. Third, if only local optimisation and economic growth are required then there is sufficient parametric freedom for macro-economic policy makers to steer an economy around catastrophes without overtly disrupting local optimisation.

Profile shape optimization in multi-jet impingement cooling of dimpled topologies for local heat transfer enhancement

NASA Astrophysics Data System (ADS)

Negi, Deepchand Singh; Pattamatta, Arvind

2015-04-01

The present study deals with shape optimization of dimples on the target surface in multi-jet impingement heat transfer. Bezier polynomial formulation is incorporated to generate profile shapes for the dimple profile generation and a multi-objective optimization is performed. The optimized dimple shape exhibits higher local Nusselt number values compared to the reference hemispherical dimpled plate optimized shape which can be used to alleviate local temperature hot spots on target surface.

Abnormal functional global and local brain connectivity in female patients with anorexia nervosa

PubMed Central

Geisler, Daniel; Borchardt, Viola; Lord, Anton R.; Boehm, Ilka; Ritschel, Franziska; Zwipp, Johannes; Clas, Sabine; King, Joseph A.; Wolff-Stephan, Silvia; Roessner, Veit; Walter, Martin; Ehrlich, Stefan

2016-01-01

Background Previous resting-state functional connectivity studies in patients with anorexia nervosa used independent component analysis or seed-based connectivity analysis to probe specific brain networks. Instead, modelling the entire brain as a complex network allows determination of graph-theoretical metrics, which describe global and local properties of how brain networks are organized and how they interact. Methods To determine differences in network properties between female patients with acute anorexia nervosa and pairwise matched healthy controls, we used resting-state fMRI and computed well-established global and local graph metrics across a range of network densities. Results Our analyses included 35 patients and 35 controls. We found that the global functional network structure in patients with anorexia nervosa is characterized by increases in both characteristic path length (longer average routes between nodes) and assortativity (more nodes with a similar connectedness link together). Accordingly, we found locally decreased connectivity strength and increased path length in the posterior insula and thalamus. Limitations The present results may be limited to the methods applied during preprocessing and network construction. Conclusion We demonstrated anorexia nervosa–related changes in the network configuration for, to our knowledge, the first time using resting-state fMRI and graph-theoretical measures. Our findings revealed an altered global brain network architecture accompanied by local degradations indicating wide-scale disturbance in information flow across brain networks in patients with acute anorexia nervosa. Reduced local network efficiency in the thalamus and posterior insula may reflect a mechanism that helps explain the impaired integration of visuospatial and homeostatic signals in patients with this disorder, which is thought to be linked to abnormal representations of body size and hunger. PMID:26252451

Abnormal functional global and local brain connectivity in female patients with anorexia nervosa.

PubMed

Geisler, Daniel; Borchardt, Viola; Lord, Anton R; Boehm, Ilka; Ritschel, Franziska; Zwipp, Johannes; Clas, Sabine; King, Joseph A; Wolff-Stephan, Silvia; Roessner, Veit; Walter, Martin; Ehrlich, Stefan

2016-01-01

Previous resting-state functional connectivity studies in patients with anorexia nervosa used independent component analysis or seed-based connectivity analysis to probe specific brain networks. Instead, modelling the entire brain as a complex network allows determination of graph-theoretical metrics, which describe global and local properties of how brain networks are organized and how they interact. To determine differences in network properties between female patients with acute anorexia nervosa and pairwise matched healthy controls, we used resting-state fMRI and computed well-established global and local graph metrics across a range of network densities. Our analyses included 35 patients and 35 controls. We found that the global functional network structure in patients with anorexia nervosa is characterized by increases in both characteristic path length (longer average routes between nodes) and assortativity (more nodes with a similar connectedness link together). Accordingly, we found locally decreased connectivity strength and increased path length in the posterior insula and thalamus. The present results may be limited to the methods applied during preprocessing and network construction. We demonstrated anorexia nervosa-related changes in the network configuration for, to our knowledge, the first time using resting-state fMRI and graph-theoretical measures. Our findings revealed an altered global brain network architecture accompanied by local degradations indicating wide-scale disturbance in information flow across brain networks in patients with acute anorexia nervosa. Reduced local network efficiency in the thalamus and posterior insula may reflect a mechanism that helps explain the impaired integration of visuospatial and homeostatic signals in patients with this disorder, which is thought to be linked to abnormal representations of body size and hunger.

Selecting the selector: Comparison of update rules for discrete global optimization

DOE PAGES

Theiler, James; Zimmer, Beate G.

2017-05-24

In this paper, we compare some well-known Bayesian global optimization methods in four distinct regimes, corresponding to high and low levels of measurement noise and to high and low levels of “quenched noise” (which term we use to describe the roughness of the function we are trying to optimize). We isolate the two stages of this optimization in terms of a “regressor,” which fits a model to the data measured so far, and a “selector,” which identifies the next point to be measured. Finally, the focus of this paper is to investigate the choice of selector when the regressor ismore » well matched to the data.« less

Functional hemispheric asymmetries of global/local processing mirrored by the steady-state visual evoked potential.

PubMed

Martens, Ulla; Hübner, Ronald

2013-03-01

While hemispheric differences in global/local processing have been reported by various studies, it is still under dispute at which processing stage they occur. Primarily, it was assumed that these asymmetries originate from an early perceptual stage. Instead, the content-level binding theory (Hübner & Volberg, 2005) suggests that the hemispheres differ at a later stage at which the stimulus information is bound to its respective level. The present study tested this assumption by means of steady-state evoked potentials (SSVEPs). In particular, we presented hierarchical letters flickering at 12Hz while participants categorised the letters at a pre- cued level (global or local). The information at the two levels could be congruent or incongruent with respect to the required response. Since content-binding is only necessary if there is a response conflict, asymmetric hemispheric processing should be observed only for incongruent stimuli. Indeed, our results show that the cue and congruent stimuli elicited equal SSVEP global/local effects in both hemispheres. In contrast, incongruent stimuli elicited lower SSVEP amplitudes for a local than for a global target level at left posterior electrodes, whereas a reversed pattern was seen at right hemispheric electrodes. These findings provide further evidence for a level-specific hemispheric advantage with respect to content-level binding. Moreover, the fact that the SSVEP is sensitive to these processes offers the possibility to separately track global and local processing by presenting both level contents with different frequencies. Copyright © 2012 Elsevier Inc. All rights reserved.

Contributions of projected land use to global radiative forcing ascribed to local sources

NASA Astrophysics Data System (ADS)

Ward, D. S.; Mahowald, N. M.; Kloster, S.

2013-12-01

With global demand for food expected to dramatically increase and put additional pressures on natural lands, there is a need to understand the environmental impacts of land use and land cover change (LULCC). Previous studies have shown that the magnitude and even the sign of the radiative forcing (RF) of biogeophysical effects from LULCC depends on the latitude and forest ecology of the disturbed region. Here we ascribe the contributions to the global RF by land-use related anthropogenic activities to their local sources, organized on a grid of 1.9 degrees latitude by 2.5 degrees longitude. We use RF estimates for the year 2100, using five future LULCC projections, computed from simulations with the National Center for Atmospheric Research Community Land Model and Community Atmosphere Models and additional offline analyses. Our definition of the LULCC RF includes changes to terrestrial carbon storage, methane and nitrous oxide emissions, atmospheric chemistry, aerosol emissions, and surface albedo. We ascribe the RF to gridded locations based on LULCC-related emissions of relevant trace gases and aerosols, including emissions from fires. We find that the largest contributions to the global RF in year 2100 from LULCC originate in the tropics for all future scenarios. In fact, LULCC is the largest tropical source of anthropogenic RF. The LULCC RF in the tropics is dominated by emissions of CO2 from deforestation and methane emissions from livestock and soils. Land surface albedo change is rarely the dominant forcing agent in any of the future LULCC projections, at any location. By combining the five future scenarios we find that deforested area at a specific tropical location can be used to predict the contribution to global RF from LULCC at that location (the relationship does not hold as well in the extratropics). This information could support global efforts like REDD (Reducing Emissions from Deforestation and Forest Degradation), that aim to reduce greenhouse gas

Global Education: From Thought to Action. The 1991 ASCD Yearbook.

ERIC Educational Resources Information Center

Tye, Kenneth A., Ed.

Viewed as a social movement for change, the global education movement calls for the infusion of a global perspective into all curriculum areas. Two assumptions of global education include the view of the individual school as the optimal unit for change efforts, and the importance of local teacher and school action for lasting school improvement.…

Material discovery by combining stochastic surface walking global optimization with a neural network.

PubMed

Huang, Si-Da; Shang, Cheng; Zhang, Xiao-Jie; Liu, Zhi-Pan

2017-09-01

While the underlying potential energy surface (PES) determines the structure and other properties of a material, it has been frustrating to predict new materials from theory even with the advent of supercomputing facilities. The accuracy of the PES and the efficiency of PES sampling are two major bottlenecks, not least because of the great complexity of the material PES. This work introduces a "Global-to-Global" approach for material discovery by combining for the first time a global optimization method with neural network (NN) techniques. The novel global optimization method, named the stochastic surface walking (SSW) method, is carried out massively in parallel for generating a global training data set, the fitting of which by the atom-centered NN produces a multi-dimensional global PES; the subsequent SSW exploration of large systems with the analytical NN PES can provide key information on the thermodynamics and kinetics stability of unknown phases identified from global PESs. We describe in detail the current implementation of the SSW-NN method with particular focuses on the size of the global data set and the simultaneous energy/force/stress NN training procedure. An important functional material, TiO 2 , is utilized as an example to demonstrate the automated global data set generation, the improved NN training procedure and the application in material discovery. Two new TiO 2 porous crystal structures are identified, which have similar thermodynamics stability to the common TiO 2 rutile phase and the kinetics stability for one of them is further proved from SSW pathway sampling. As a general tool for material simulation, the SSW-NN method provides an efficient and predictive platform for large-scale computational material screening.

Local and global processing of music in high-functioning persons with autism: beyond central coherence?

PubMed

Mottron, L; Peretz, I; Ménard, E

2000-11-01

A multi-modal abnormality in the integration of parts and whole has been proposed to account for a bias toward local stimuli in individuals with autism (Frith, 1989; Mottron & Belleville, 1993). In the current experiment, we examined the utility of hierarchical models in characterising musical information processing in autistic individuals. Participants were 13 high-functioning individuals with autism and 13 individuals of normal intelligence matched on chronological age, nonverbal IQ, and laterality, and without musical experience. The task consisted of same-different judgements of pairs of melodies. Differential local and global processing was assessed by manipulating the level, local or global, at which modifications occurred. No deficit was found in the two measures of global processing. In contrast, the clinical group performed better than the comparison group in the detection of change in nontransposed, contour-preserved melodies that tap local processing. These findings confirm the existence of a "local bias" in music perception in individuals with autism, but challenge the notion that it is accounted for by a deficit in global music processing. The present study suggests that enhanced processing of elementary physical properties of incoming stimuli, as found previously in the visual modality, may also exist in the auditory modality.

On the Performance of Linear Decreasing Inertia Weight Particle Swarm Optimization for Global Optimization

PubMed Central

Arasomwan, Martins Akugbe; Adewumi, Aderemi Oluyinka

2013-01-01

Linear decreasing inertia weight (LDIW) strategy was introduced to improve on the performance of the original particle swarm optimization (PSO). However, linear decreasing inertia weight PSO (LDIW-PSO) algorithm is known to have the shortcoming of premature convergence in solving complex (multipeak) optimization problems due to lack of enough momentum for particles to do exploitation as the algorithm approaches its terminal point. Researchers have tried to address this shortcoming by modifying LDIW-PSO or proposing new PSO variants. Some of these variants have been claimed to outperform LDIW-PSO. The major goal of this paper is to experimentally establish the fact that LDIW-PSO is very much efficient if its parameters are properly set. First, an experiment was conducted to acquire a percentage value of the search space limits to compute the particle velocity limits in LDIW-PSO based on commonly used benchmark global optimization problems. Second, using the experimentally obtained values, five well-known benchmark optimization problems were used to show the outstanding performance of LDIW-PSO over some of its competitors which have in the past claimed superiority over it. Two other recent PSO variants with different inertia weight strategies were also compared with LDIW-PSO with the latter outperforming both in the simulation experiments conducted. PMID:24324383

International trade of health services: global trends and local impact.

PubMed

Lautier, Marc

2014-10-01

Globalization is a key challenge facing health policy-makers. A significant dimension of this is trade in health services. Traditionally, the flow of health services exports went from North to South, with patients travelling in the opposite direction. This situation is changing and a number of papers have discussed the growth of health services exports from Southern countries in its different dimensions. Less attention has been paid to assess the real scope of this trade at the global level and its potential impact at the local level. Given the rapid development of this area, there are little empirical data. This paper therefore first built an estimate of the global size and of the growth trend of international trade in health services since 1997, which is compared with several country-based studies. The second purpose of the paper is to demonstrate the significant economic impact of this trade at the local level for the exporting country. We consider the case of health providers in the South-Mediterranean region for which the demand potential, the economic effects and the consequence for the health system are presented. These issues lead to the overall conclusion that different policy options would be appropriate, in relation to the nature of the demand. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Reconstruction of biofilm images: combining local and global structural parameters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Resat, Haluk; Renslow, Ryan S.; Beyenal, Haluk

2014-10-20

Digitized images can be used for quantitative comparison of biofilms grown under different conditions. Using biofilm image reconstruction, it was previously found that biofilms with a completely different look can have nearly identical structural parameters and that the most commonly utilized global structural parameters were not sufficient to uniquely define these biofilms. Here, additional local and global parameters are introduced to show that these parameters considerably increase the reliability of the image reconstruction process. Assessment using human evaluators indicated that the correct identification rate of the reconstructed images increased from 50% to 72% with the introduction of the new parametersmore » into the reconstruction procedure. An expanded set of parameters especially improved the identification of biofilm structures with internal orientational features and of structures in which colony sizes and spatial locations varied. Hence, the newly introduced structural parameter sets helped to better classify the biofilms by incorporating finer local structural details into the reconstruction process.« less

Bioseguridad in Mexico: Pursuing Security between Local and Global Biologies.

PubMed

Wanderer, Emily Mannix

2017-09-01

In the aftermath of the 2009 outbreak of H1N1 influenza, scientists in Mexico sought to develop bioseguridad, that is, to protect biological life in Mexico by safely conducting research on infectious disease. Drawing on ethnographic research in laboratories and with scientists in Mexico, I look at how scientists make claims about local differences in regulations, infrastructure, bodies, and culture. The scientists working with infectious microbes sought to establish how different microbial ecologies, human immune systems, and political and regulatory systems made the risks of research different in Mexico from other countries. In developing bioseguridad, the idea of globalized biology that animates many public health projects was undermined as scientists attended to the elements of place that affected human health and safety. Scientists argued for the importance of local biologies, generating tension with global public health projects and regulations premised on the universality of biology. © 2016 by the American Anthropological Association.

Downscaling global precipitation for local applications - a case for the Rhine basin

NASA Astrophysics Data System (ADS)

Sperna Weiland, Frederiek; van Verseveld, Willem; Schellekens, Jaap

2017-04-01

Within the EU FP7 project eartH2Observe a global Water Resources Re-analysis (WRR) is being developed. This re-analysis consists of meteorological and hydrological water balance variables with global coverage, spanning the period 1979-2014 at 0.25 degrees resolution (Schellekens et al., 2016). The dataset can be of special interest in regions with limited in-situ data availability, yet for local scale analysis particularly in mountainous regions, a resolution of 0.25 degrees may be too coarse and downscaling the data to a higher resolution may be required. A downscaling toolbox has been made that includes spatial downscaling of precipitation based on the global WorldClim dataset that is available at 1 km resolution as a monthly climatology (Hijmans et al., 2005). The input of the down-scaling tool are either the global eartH2Observe WRR1 and WRR2 datasets based on the WFDEI correction methodology (Weedon et al., 2014) or the global Multi-Source Weighted-Ensemble Precipitation (MSWEP) dataset (Beck et al., 2016). Here we present a validation of the datasets over the Rhine catchment by means of a distributed hydrological model (wflow, Schellekens et al., 2014) using a number of precipitation scenarios. (1) We start by running the model using the local reference dataset derived by spatial interpolation of gauge observations. Furthermore we use (2) the MSWEP dataset at the native 0.25-degree resolution followed by (3) MSWEP downscaled with the WorldClim dataset and final (4) MSWEP downscaled with the local reference dataset. The validation will be based on comparison of the modeled river discharges as well as rainfall statistics. We expect that down-scaling the MSWEP dataset with the WorldClim data to higher resolution will increase its performance. To test the performance of the down-scaling routine we have added a run with MSWEP data down-scaled with the local dataset and compare this with the run based on the local dataset itself. - Beck, H. E. et al., 2016. MSWEP