Global and Local Optimization Algorithms for Optimal Signal Set Design
Kearsley, Anthony J.
2001-01-01
The problem of choosing an optimal signal set for non-Gaussian detection was reduced to a smooth inequality constrained mini-max nonlinear programming problem by Gockenbach and Kearsley. Here we consider the application of several optimization algorithms, both global and local, to this problem. The most promising results are obtained when special-purpose sequential quadratic programming (SQP) algorithms are embedded into stochastic global algorithms.
Globally optimal trial design for local decision making.
Eckermann, Simon; Willan, Andrew R
2009-02-01
Value of information methods allows decision makers to identify efficient trial design following a principle of maximizing the expected value to decision makers of information from potential trial designs relative to their expected cost. However, in health technology assessment (HTA) the restrictive assumption has been made that, prospectively, there is only expected value of sample information from research commissioned within jurisdiction. This paper extends the framework for optimal trial design and decision making within jurisdiction to allow for optimal trial design across jurisdictions. This is illustrated in identifying an optimal trial design for decision making across the US, the UK and Australia for early versus late external cephalic version for pregnant women presenting in the breech position. The expected net gain from locally optimal trial designs of US$0.72M is shown to increase to US$1.14M with a globally optimal trial design. In general, the proposed method of globally optimal trial design improves on optimal trial design within jurisdictions by: (i) reflecting the global value of non-rival information; (ii) allowing optimal allocation of trial sample across jurisdictions; (iii) avoiding market failure associated with free-rider effects, sub-optimal spreading of fixed costs and heterogeneity of trial information with multiple trials. PMID:18435429
Global and Local Sparse Subspace Optimization for Motion Segmentation
NASA Astrophysics Data System (ADS)
Yang, M. Ying; Feng, S.; Ackermann, H.; Rosenhahn, B.
2015-08-01
In this paper, we propose a new framework for segmenting feature-based moving objects under affine subspace model. Since the feature trajectories in practice are high-dimensional and contain a lot of noise, we firstly apply the sparse PCA to represent the original trajectories with a low-dimensional global subspace, which consists of the orthogonal sparse principal vectors. Subsequently, the local subspace separation will be achieved via automatically searching the sparse representation of the nearest neighbors for each projected data. In order to refine the local subspace estimation result, we propose an error estimation to encourage the projected data that span a same local subspace to be clustered together. In the end, the segmentation of different motions is achieved through the spectral clustering on an affinity matrix, which is constructed with both the error estimation and sparse neighbors optimization. We test our method extensively and compare it with state-of-the-art methods on the Hopkins 155 dataset. The results show that our method is comparable with the other motion segmentation methods, and in many cases exceed them in terms of precision and computation time.
New methods for large scale local and global optimization
NASA Astrophysics Data System (ADS)
Byrd, Richard; Schnabel, Robert
1994-07-01
We have pursued all three topics described in the proposal during this research period. A large amount of effort has gone into the development of large scale global optimization methods for molecular configuration problems. We have developed new general purpose methods that combine efficient stochastic global optimization techniques with several new, more deterministic techniques that account for most of the computational effort, and the success, of the methods. We have applied our methods to Lennard-Jones problems with up to 75 atoms, to water clusters with up to 31, molecules, and polymers with up to 58 amino acids. The results appear to be the best so far by general purpose optimization methods, and appear to be leading to some interesting chemistry issues. Our research on the second topic, tensor methods, has addressed several areas. We have designed and implemented tensor methods for large sparse systems of nonlinear equations and nonlinear least squares, and have obtained excellent test results on a wide range of problems. We have also developed new tensor methods for nonlinearly constrained optimization problem, and have obtained promising theoretical and preliminary computational results. Finally, on the third topic, limited memory methods for large scale optimization, we have developed and implemented new, extremely efficient limited memory methods for bound constrained problems, and new limited memory trust regions methods, both using our-recently developed compact representations for quasi-Newton matrices. Computational test results for both methods are promising.
A reconciliation of local and global models for bone remodeling through optimization theory.
Subbarayan, G; Bartel, D L
2000-02-01
Remodeling rules with either a global or a local mathematical form have been proposed for load-bearing bones in the literature. In the local models, the bone architecture (shape, density) is related to the strains/energies sensed at any point in the bone, while in the global models, a criterion believed to be applicable to the whole bone is used. In the present paper, a local remodeling rule with a strain "error" form is derived as the necessary condition for the optimum of a global remodeling criterion, suggesting that many of the local error-driven remodeling rules may have corresponding global optimization-based criteria. The global criterion proposed in the present study is a trade-off between the cost of metabolic growth and use, mathematically represented by the mass, and the cost of failure, mathematically represented by the total strain energy. The proposed global criterion is shown to be related to the optimality criteria methods of structural optimization by the equivalence of the model solution and the fully stressed solution for statically determinate structures. In related work, the global criterion is applied to simulate the strength recovery in bones with screw holes left behind after removal of fracture fixation plates. The results predicted by the model are shown to be in good agreement with experimental results, leading to the conclusion that load-bearing bones are structures with optimal shape and property for their function. PMID:10790832
Optimal Design of Grid-Stiffened Composite Panels Using Global and Local Buckling Analysis
Ambur, D.R.; Jaunky, N.; Knight, N.F. Jr.
1996-04-01
A design strategy for optimal design of composite grid-stiffened panels subjected to global and local buckling constraints is developed using a discrete optimizer. An improved smeared stiffener theory is used for the global buckling analysis. Local buckling of skin segments is assessed using a Rayleigh-Ritz method that accounts for material anisotropy and transverse shear flexibility. The local buckling of stiffener segments is also assessed. Design variables are the axial and transverse stiffener spacing, stiffener height and thickness, skin laminate, and stiffening configuration. The design optimization process is adapted to identify the lightest-weight stiffening configuration and pattern for grid stiffened composite panels given the overall panel dimensions, design in-plane loads, material properties, and boundary conditions of the grid-stiffened panel.
Optimal Design of Grid-Stiffened Composite Panels Using Global and Local Buckling Analysis
NASA Technical Reports Server (NTRS)
Ambur, Damodar R.; Jaunky, Navin; Knight, Norman F., Jr.
1996-01-01
A design strategy for optimal design of composite grid-stiffened panels subjected to global and local buckling constraints is developed using a discrete optimizer. An improved smeared stiffener theory is used for the global buckling analysis. Local buckling of skin segments is assessed using a Rayleigh-Ritz method that accounts for material anisotropy and transverse shear flexibility. The local buckling of stiffener segments is also assessed. Design variables are the axial and transverse stiffener spacing, stiffener height and thickness, skin laminate, and stiffening configuration. The design optimization process is adapted to identify the lightest-weight stiffening configuration and pattern for grid stiffened composite panels given the overall panel dimensions, design in-plane loads, material properties, and boundary conditions of the grid-stiffened panel.
SU-E-J-130: Automating Liver Segmentation Via Combined Global and Local Optimization
Li, Dengwang; Wang, Jie; Kapp, Daniel S.; Xing, Lei
2015-06-15
Purpose: The aim of this work is to develop a robust algorithm for accurate segmentation of liver with special attention paid to the problems with fuzzy edges and tumor. Methods: 200 CT images were collected from radiotherapy treatment planning system. 150 datasets are selected as the panel data for shape dictionary and parameters estimation. The remaining 50 datasets were used as test images. In our study liver segmentation was formulated as optimization process of implicit function. The liver region was optimized via local and global optimization during iterations. Our method consists five steps: 1)The livers from the panel data were segmented manually by physicians, and then We estimated the parameters of GMM (Gaussian mixture model) and MRF (Markov random field). Shape dictionary was built by utilizing the 3D liver shapes. 2)The outlines of chest and abdomen were located according to rib structure in the input images, and the liver region was initialized based on GMM. 3)The liver shape for each 2D slice was adjusted using MRF within the neighborhood of liver edge for local optimization. 4)The 3D liver shape was corrected by employing SSR (sparse shape representation) based on liver shape dictionary for global optimization. Furthermore, H-PSO(Hybrid Particle Swarm Optimization) was employed to solve the SSR equation. 5)The corrected 3D liver was divided into 2D slices as input data of the third step. The iteration was repeated within the local optimization and global optimization until it satisfied the suspension conditions (maximum iterations and changing rate). Results: The experiments indicated that our method performed well even for the CT images with fuzzy edge and tumors. Comparing with physician delineated results, the segmentation accuracy with the 50 test datasets (VOE, volume overlap percentage) was on average 91%–95%. Conclusion: The proposed automatic segmentation method provides a sensible technique for segmentation of CT images. This work is
Global-Local Analysis and Optimization of a Composite Civil Tilt-Rotor Wing
NASA Technical Reports Server (NTRS)
Rais-Rohani, Masound
1999-01-01
This report gives highlights of an investigation on the design and optimization of a thin composite wing box structure for a civil tilt-rotor aircraft. Two different concepts are considered for the cantilever wing: (a) a thin monolithic skin design, and (b) a thick sandwich skin design. Each concept is examined with three different skin ply patterns based on various combinations of 0, +/-45, and 90 degree plies. The global-local technique is used in the analysis and optimization of the six design models. The global analysis is based on a finite element model of the wing-pylon configuration while the local analysis uses a uniformly supported plate representing a wing panel. Design allowables include those on vibration frequencies, panel buckling, and material strength. The design optimization problem is formulated as one of minimizing the structural weight subject to strength, stiffness, and d,vnamic constraints. Six different loading conditions based on three different flight modes are considered in the design optimization. The results of this investigation reveal that of all the loading conditions the one corresponding to the rolling pull-out in the airplane mode is the most stringent. Also the frequency constraints are found to drive the skin thickness limits, rendering the buckling constraints inactive. The optimum skin ply pattern for the monolithic skin concept is found to be (((0/+/-45/90/(0/90)(sub 2))(sub s))(sub s), while for the sandwich skin concept the optimal ply pattern is found to be ((0/+/-45/90)(sub 2s))(sub s).
Donner, René; Menze, Bjoern H; Bischof, Horst; Langs, Georg
2013-12-01
The accurate localization of anatomical landmarks is a challenging task, often solved by domain specific approaches. We propose a method for the automatic localization of landmarks in complex, repetitive anatomical structures. The key idea is to combine three steps: (1) a classifier for pre-filtering anatomical landmark positions that (2) are refined through a Hough regression model, together with (3) a parts-based model of the global landmark topology to select the final landmark positions. During training landmarks are annotated in a set of example volumes. A classifier learns local landmark appearance, and Hough regressors are trained to aggregate neighborhood information to a precise landmark coordinate position. A non-parametric geometric model encodes the spatial relationships between the landmarks and derives a topology which connects mutually predictive landmarks. During the global search we classify all voxels in the query volume, and perform regression-based agglomeration of landmark probabilities to highly accurate and specific candidate points at potential landmark locations. We encode the candidates' weights together with the conformity of the connecting edges to the learnt geometric model in a Markov Random Field (MRF). By solving the corresponding discrete optimization problem, the most probable location for each model landmark is found in the query volume. We show that this approach is able to consistently localize the model landmarks despite the complex and repetitive character of the anatomical structures on three challenging data sets (hand radiographs, hand CTs, and whole body CTs), with a median localization error of 0.80 mm, 1.19 mm and 2.71 mm, respectively. PMID:23664450
Software for global optimization
Mockus, L.
1994-12-31
The interactive graphical software that implements numeric methods and other techniques to solve global optimization problems is presented. The Bayesian approach to the optimization is the underlying idea of numeric methods used. Software is designed to solve deterministic and stochastic problems of different complexity and with many variables. It includes global and local optimization methods for differentiable and nondifferentiable functions. Implemented numerical techniques for global optimization vary from simple Monte-Carlo simulation to Bayesian methods by J. Mockus and extrapolation theory based methods by Zilinskas. Local optimization techniques includes simplex method of Nelder and Mead method of nonlinear programming by Shitkowski, and method of stochastic approximation with Bayesian step size control by J. Mockus. Software is interactive, it allows user to start and stop chosen method of global or local optimization, define and change its parameters and examine the solution process. Out-put from solution process is both numerical and graphical. Currently available graphical features are the projection of the objective function on a chosen plane and convergence plot. Both these features let the user easily observe solution process and interactively modify it. More features can be added in a standard way. It is up to the user how many graphical and numerical output features activate or deactivate at any given time. Software is implemented in C++ using X Windows as graphical platform.
Local search for optimal global map generation using mid-decadal landsat images
Khatib, L.; Gasch, J.; Morris, R.; Covington, S.
2007-01-01
NASA and the US Geological Survey (USGS) are seeking to generate a map of the entire globe using Landsat 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) sensor data from the "mid-decadal" period of 2004 through 2006. The global map is comprised of thousands of scene locations and, for each location, tens of different images of varying quality to chose from. Furthermore, it is desirable for images of adjacent scenes be close together in time of acquisition, to avoid obvious discontinuities due to seasonal changes. These characteristics make it desirable to formulate an automated solution to the problem of generating the complete map. This paper formulates a Global Map Generator problem as a Constraint Optimization Problem (GMG-COP) and describes an approach to solving it using local search. Preliminary results of running the algorithm on image data sets are summarized. The results suggest a significant improvement in map quality using constraint-based solutions. Copyright ?? 2007, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.
NASA Astrophysics Data System (ADS)
Shoemaker, C. A.; Singh, A.
2008-12-01
This paper will describe some new optimization algorithms and their application to hydrologic models. The approaches include a parallel version of a new heuristic algorithm combined with tabu search and a mathematically derived global optimization method that is based on trust region methods. The goals of these methods are to find optimal solutions to calibration problems and to design problems with relatively few simulations or (in a parallel environment) relatively little wallclock time. This is important because currently it is not possible to apply global optimization methods like genetic algorithms to computationally expensive simulation models like partial differential equations (with many nodes in groundwater) because it is not feasible to do thousands of simulations to evaluate the objective/fitness function. Results of the application of the algorithms to some complex models of groundwater contamination and phosphorous transport in watersheds will be presented.
NASA Astrophysics Data System (ADS)
Theos, F. V.; Lagaris, I. E.; Papageorgiou, D. G.
2004-05-01
We present two sequential and one parallel global optimization codes, that belong to the stochastic class, and an interface routine that enables the use of the Merlin/MCL environment as a non-interactive local optimizer. This interface proved extremely important, since it provides flexibility, effectiveness and robustness to the local search task that is in turn employed by the global procedures. We demonstrate the use of the parallel code to a molecular conformation problem. Program summaryTitle of program: PANMIN Catalogue identifier: ADSU Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADSU Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Computer for which the program is designed and others on which it has been tested: PANMIN is designed for UNIX machines. The parallel code runs on either shared memory architectures or on a distributed system. The code has been tested on a SUN Microsystems ENTERPRISE 450 with four CPUs, and on a 48-node cluster under Linux, with both the GNU g77 and the Portland group compilers. The parallel implementation is based on MPI and has been tested with LAM MPI and MPICH Installation: University of Ioannina, Greece Programming language used: Fortran-77 Memory required to execute with typical data: Approximately O( n2) words, where n is the number of variables No. of bits in a word: 64 No. of processors used: 1 or many Has the code been vectorised or parallelized?: Parallelized using MPI No. of bytes in distributed program, including test data, etc.: 147163 No. of lines in distributed program, including the test data, etc.: 14366 Distribution format: gzipped tar file Nature of physical problem: A multitude of problems in science and engineering are often reduced to minimizing a function of many variables. There are instances that a local optimum does not correspond to the desired physical solution and hence the search for a better solution is required. Local optimization techniques can be
NASA Astrophysics Data System (ADS)
Matott, L. S.; Gray, G. A.
2011-12-01
Pump-and-treat systems are a common strategy for groundwater remediation, wherein a system of extraction wells is installed at an affected site to address pollutant migration. In this context, the likely performance of candidate remedial systems is often assessed using groundwater flow modeling. When linked with an optimizer, these models can be utilized to identify a least-cost system design that nonetheless satisfies remediation goals. Moreover, the resulting design problems serve as important tools in the development and testing of optimization algorithms. For example, consider EAGLS (Evolutionary Algorithm Guiding Local Search), a recently developed derivative-free simulation-optimization code that seeks to efficiently solve nonlinear problems by hybridizing local and global search techniques. The EAGLS package was designed to specifically target mixed variable problems and has a limited ability to intelligently adapt its behavior to given problem characteristics. For instance, to solve problems in which there are no discrete or integer variables, the EAGLS code defaults to a multi-start asynchronous parallel pattern search. Therefore, to better understand the behavior of EAGLS, the algorithm was applied to a representative dual-plume pump-and-treat containment problem. A series of numerical experiments were performed involving four different formulations of the underlying pump-and-treat optimization problem, namely: (1) optimization of pumping rates, given fixed number of wells at fixed locations; (2) optimization of pumping rates and locations of a fixed number of wells; (3) optimization of pumping rates and number of wells at fixed locations; and (4) optimization of pumping rates, locations, and number of wells. Comparison of the performance of the EAGLS software with alternative search algorithms across different problem formulations yielded new insights for improving the EAGLS algorithm and enhancing its adaptive behavior.
NASA Astrophysics Data System (ADS)
Cai, X.; Zhang, X.; Zhu, T.
2014-12-01
Global food security is constrained by local and regional land and water availability, as well as other agricultural input limitations and inappropriate national and global regulations. In a theoretical context, this study assumes that optimal water and land uses in local food production to maximize food security and social welfare at the global level can be driven by global trade. It follows the context of "virtual resources trade", i.e., utilizing international trade of agricultural commodities to reduce dependency on local resources, and achieves land and water savings in the world. An optimization model based on the partial equilibrium of agriculture is developed for the analysis, including local commodity production and land and water resources constraints, demand by country, and global food market. Through the model, the marginal values (MVs) of social welfare for water and land at the level of so-called food production units (i.e., sub-basins with similar agricultural production conditions) are derived and mapped in the world. In this personation, we will introduce the model structure, explain the meaning of MVs at the local level and their distribution around the world, and discuss the policy implications for global communities to enhance global food security. In particular, we will examine the economic values of water and land under different world targets of food security (e.g., number of malnourished population or children in a future year). In addition, we will also discuss the opportunities on data to improve such global modeling exercises.
Rattenborg, Niels C; Lima, Steven L; Lesku, John A
2012-10-01
In most animals, sleep is considered a global brain and behavioral state. However, recent intracortical recordings have shown that aspects of non-rapid eye movement (NREM) sleep and wakefulness can occur simultaneously in different parts of the cortex in mammals, including humans. Paradoxically, however, NREM sleep still manifests as a global behavioral shutdown. In this review, the authors examine this paradox from an evolutionary perspective. On the basis of strategic modeling, they suggest that in animals with brains composed of heavily interconnected and functionally interdependent units, a global regulator of sleep maintains the behavioral shutdown that defines sleep and thereby ensures that local use-dependent functions are performed in a safe and efficient manner. This novel perspective has implications for understanding deficits in human cognitive performance resulting from sleep deprivation, sleep disorders such as sleepwalking, changes in consciousness that occur during sleep, and the function of sleep itself. PMID:22572533
Pfeffer, A; Das, S; Lawless, D; Ng, B
2006-10-10
Many dynamic systems involve a number of entities that are largely independent of each other but interact with each other via a subset of state variables. We present global/local dynamic models (GLDMs) to capture these kinds of systems. In a GLDM, the state of an entity is decomposed into a globally influenced state that depends on other entities, and a locally influenced state that depends only on the entity itself. We present an inference algorithm for GLDMs called global/local particle filtering, that introduces the principle of reasoning globally about global dynamics and locally about local dynamics. We have applied GLDMs to an asymmetric urban warfare environment, in which enemy units form teams to attack important targets, and the task is to detect such teams as they form. Experimental results for this application show that global/local particle filtering outperforms ordinary particle filtering and factored particle filtering.
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)
Homotopy optimization methods for global optimization.
Dunlavy, Daniel M.; O'Leary, Dianne P.
2005-12-01
We define a new method for global optimization, the Homotopy Optimization Method (HOM). This method differs from previous homotopy and continuation methods in that its aim is to find a minimizer for each of a set of values of the homotopy parameter, rather than to follow a path of minimizers. We define a second method, called HOPE, by allowing HOM to follow an ensemble of points obtained by perturbation of previous ones. We relate this new method to standard methods such as simulated annealing and show under what circumstances it is superior. We present results of extensive numerical experiments demonstrating performance of HOM and HOPE.
Intervals in evolutionary algorithms for global optimization
Patil, R.B.
1995-05-01
Optimization is of central concern to a number of disciplines. Interval Arithmetic methods for global optimization provide us with (guaranteed) verified results. These methods are mainly restricted to the classes of objective functions that are twice differentiable and use a simple strategy of eliminating a splitting larger regions of search space in the global optimization process. An efficient approach that combines the efficient strategy from Interval Global Optimization Methods and robustness of the Evolutionary Algorithms is proposed. In the proposed approach, search begins with randomly created interval vectors with interval widths equal to the whole domain. Before the beginning of the evolutionary process, fitness of these interval parameter vectors is defined by evaluating the objective function at the center of the initial interval vectors. In the subsequent evolutionary process the local optimization process returns an estimate of the bounds of the objective function over the interval vectors. Though these bounds may not be correct at the beginning due to large interval widths and complicated function properties, the process of reducing interval widths over time and a selection approach similar to simulated annealing helps in estimating reasonably correct bounds as the population evolves. The interval parameter vectors at these estimated bounds (local optima) are then subjected to crossover and mutation operators. This evolutionary process continues for predetermined number of generations in the search of the global optimum.
Global optimization methods for engineering design
NASA Technical Reports Server (NTRS)
Arora, Jasbir S.
1990-01-01
The problem is to find a global minimum for the Problem P. Necessary and sufficient conditions are available for local optimality. However, global solution can be assured only under the assumption of convexity of the problem. If the constraint set S is compact and the cost function is continuous on it, existence of a global minimum is guaranteed. However, in view of the fact that no global optimality conditions are available, a global solution can be found only by an exhaustive search to satisfy Inequality. The exhaustive search can be organized in such a way that the entire design space need not be searched for the solution. This way the computational burden is reduced somewhat. It is concluded that zooming algorithm for global optimizations appears to be a good alternative to stochastic methods. More testing is needed; a general, robust, and efficient local minimizer is required. IDESIGN was used in all numerical calculations which is based on a sequential quadratic programming algorithm, and since feasible set keeps on shrinking, a good algorithm to find an initial feasible point is required. Such algorithms need to be developed and evaluated.
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…
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…
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.
Global Design Optimization for Fluid Machinery Applications
NASA Technical Reports Server (NTRS)
Shyy, Wei; Papila, Nilay; Tucker, Kevin; Vaidyanathan, Raj; Griffin, Lisa
2000-01-01
Recent experiences in utilizing the global optimization methodology, based on polynomial and neural network techniques for fluid machinery design are summarized. 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. Another advantage is that these methods do not need to calculate the sensitivity of each design variable locally. 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. Examples of applications selected from rocket propulsion components including a supersonic turbine and an injector element and a turbulent flow diffuser are used to illustrate the usefulness of the global optimization method.
Yang, Zili
2009-03-19
In the duration of this project, we finished the main tasks set up in the initial proposal. These tasks include: collecting needed data of regional aerosol emissions (mainly SO2); building the RICES model; conducting preliminary simulation runs on some policy scenarios. We established a unified and transparent IA modeling platform that connecting climate change and local air pollution. The RICES model is the pioneering IA model that treats climate change and local air pollution as correlated global and local stock externalities.
Local optimization of neuron arbors.
Cherniak, C
1992-01-01
How parsimoniously is brain wiring laid out, that is, how well does a neuron minimize costs of connections among its synapses? Neural optimization of dendritic and axonic arbors can be evaluated using a generalization of the Steiner tree concept from combinatorial network optimization theory. Local branch-junction geometry of neuronal connecting structures fits a volume minimization model well. In addition, volume of the arborizations at this neighborhood level is significantly more strongly minimized than their length, signal propagation speed, or surface area. The mechanism of this local volume optimization resembles those involved in formation of nonliving tree structures such as river junctions and electric-discharge patterns, and appears to govern initial nerve growth-cone behavior through vector-mechanical energy minimization. PMID:1586674
Global versus local adsorption selectivity
NASA Astrophysics Data System (ADS)
Pauzat, Françoise; Marloie, Gael; Markovits, Alexis; Ellinger, Yves
2015-10-01
The origin of the enantiomeric excess found in the amino acids present in the organic matter of carbonaceous meteorites is still unclear. Selective adsorption of one of the two enantiomers existing after a racemic formation could be part of the answer. Hereafter we report a comparative study of the adsorption of the R and S enantiomers of α-alanine and lactic acid on the hydroxylated { } chiral surface of α-quartz using numerical simulation techniques. Structurally different adsorption sites were found with opposite R versus S selectivity for the same molecule-surface couple, raising the problem of whether to consider adsorption as a local property or as a global response characteristic of the whole surface. To deal with the second term of this alternative, a statistical approach was designed, based on the occurrence of each adsorption site whose energy was calculated using first principle periodic density functional theory. It was found that R-alanine and S-lactic acid are the enantiomers preferentially adsorbed, even if the adsorption process on the quartz { } surface stays with a disappointingly poor enantio-selectivity. Nevertheless, it highlighted the important point that considering adsorption as a global property changes perspectives in the search for more efficient enantio-selective supports and more generally changes the way to apprehend adsorption processes in astro-chemistry/biology.
An approximation based global optimization strategy for structural synthesis
NASA Technical Reports Server (NTRS)
Sepulveda, A. E.; Schmit, L. A.
1991-01-01
A global optimization strategy for structural synthesis based on approximation concepts is presented. The methodology involves the solution of a sequence of highly accurate approximate problems using a global optimization algorithm. The global optimization algorithm implemented consists of a branch and bound strategy based on the interval evaluation of the objective function and constraint functions, combined with a local feasible directions algorithm. The approximate design optimization problems are constructed using first order approximations of selected intermediate response quantities in terms of intermediate design variables. Some numerical results for example problems are presented to illustrate the efficacy of the design procedure setforth.
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.
Local cooling despite global warming
NASA Astrophysics Data System (ADS)
Girihagama, Lakshika Nilmini Kumari
How much warmer is the ocean surface than the atmosphere directly above it? Part 1 of the present study offers a means to quantify this temperature difference using a nonlinear one-dimensional global energy balance coupled ocean--atmosphere model ("Aqua Planet"). The significance of our model, which is of intermediate complexity, is its ability to obtain an analytical solution for the global average temperatures. Preliminary results show that, for the present climate, global mean ocean temperature is 291.1 K whereas surface atmospheric temperature is 287.4 K. Thus, the surface ocean is 3.7 K warmer than the atmosphere above it. Temporal perturbation of the global mean solution obtained for "Aqua Planet" showed a stable system. Oscillation amplitude of the atmospheric temperature anomaly is greater in magnitude to those found in the ocean. There is a phase shift (a lag in the ocean), which is caused by oceanic thermal inertia. Climate feedbacks due to selected climate parameters such as incoming radiation, cloud cover, and CO2 are discussed. Warming obtained with our model compares with Intergovernmental Panel on Climate Change's (IPCC) estimations. Application of our model to local regions illuminates the importance of evaporative cooling in determining derived air-sea temperature offsets, where an increase in the latter increases the systems overall sensitivity to evaporative cooling. In part 2, we wish to answer the fairly complicated question of whether global warming and an increased freshwater flux cause Northern Hemispheric warming or cooling. Starting from the assumption of the ocean as the primary source of variability in the Northern hemispheric ocean--atmosphere coupled system, we employed a simple non--linear one--dimensional coupled ocean--atmosphere model similar to the "Aqua Planet" model but with additional advective heat transports. The simplicity of this model allows us to analytically predict the evolution of many dynamical variables of interest
Thinking Globally when Teaching Locally
ERIC Educational Resources Information Center
Van Reken, Ruth E.; Rushmore, Sally
2009-01-01
Advances in science and technology, globalization of trade, international competition for markets, ethnic conflicts, and the limits of the planet's ecosystem have brought global issues and the people of the world to doorsteps and classrooms. With the increasing interaction among peoples of the world, skills in cross-cultural communication,…
Application of clustering global optimization to thin film design problems.
Lemarchand, Fabien
2014-03-10
Refinement techniques usually calculate an optimized local solution, which is strongly dependent on the initial formula used for the thin film design. In the present study, a clustering global optimization method is used which can iteratively change this initial formula, thereby progressing further than in the case of local optimization techniques. A wide panel of local solutions is found using this procedure, resulting in a large range of optical thicknesses. The efficiency of this technique is illustrated by two thin film design problems, in particular an infrared antireflection coating, and a solar-selective absorber coating. PMID:24663856
THE LOCAL LIMIT OF GLOBAL GYROKINETIC SIMULATIONS
CANDY J; WALTZ RE; DORLAND W
2003-10-01
OAK-B135 Global gyrokinetic simulations of turbulence include physical effects that are not retained in local flux-tube simulations. nevertheless, in the limit of sufficiently small {rho}* (gyroradius compared to system size) it is expected that a local simulation should agree with a global one (at the local simulation radius) since all effects that are dropped in the local simulations are expected to vanish as {rho}* {yields} 0. In this note, global simulations of a well-established test case are indeed shown to recover the flux-tube limit at each radius.
A Memetic Algorithm for Global Optimization of Multimodal Nonseparable Problems.
Zhang, Geng; Li, Yangmin
2016-06-01
It is a big challenging issue of avoiding falling into local optimum especially when facing high-dimensional nonseparable problems where the interdependencies among vector elements are unknown. In order to improve the performance of optimization algorithm, a novel memetic algorithm (MA) called cooperative particle swarm optimizer-modified harmony search (CPSO-MHS) is proposed in this paper, where the CPSO is used for local search and the MHS for global search. The CPSO, as a local search method, uses 1-D swarm to search each dimension separately and thus converges fast. Besides, it can obtain global optimum elements according to our experimental results and analyses. MHS implements the global search by recombining different vector elements and extracting global optimum elements. The interaction between local search and global search creates a set of local search zones, where global optimum elements reside within the search space. The CPSO-MHS algorithm is tested and compared with seven other optimization algorithms on a set of 28 standard benchmarks. Meanwhile, some MAs are also compared according to the results derived directly from their corresponding references. The experimental results demonstrate a good performance of the proposed CPSO-MHS algorithm in solving multimodal nonseparable problems. PMID:26292352
Global optimality of extremals: An example
NASA Technical Reports Server (NTRS)
Kreindler, E.; Newman, F.
1980-01-01
The question of the existence and location of Darboux points is crucial for minimally sufficient conditions for global optimality and for computation of optimal trajectories. A numerical investigation is presented of the Darboux points and their relationship with conjugate points for a problem of minimum fuel, constant velocity, and horizontal aircraft turns to capture a line. This simple second order optimal control problem shows that ignoring the possible existence of Darboux points may play havoc with the computation of optimal trajectories.
Bayesian approach to global discrete optimization
Mockus, J.; Mockus, A.; Mockus, L.
1994-12-31
We discuss advantages and disadvantages of the Bayesian approach (average case analysis). We present the portable interactive version of software for continuous global optimization. We consider practical multidimensional problems of continuous global optimization, such as optimization of VLSI yield, optimization of composite laminates, estimation of unknown parameters of bilinear time series. We extend Bayesian approach to discrete optimization. We regard the discrete optimization as a multi-stage decision problem. We assume that there exists some simple heuristic function which roughly predicts the consequences of the decisions. We suppose randomized decisions. We define the probability of the decision by the randomized decision function depending on heuristics. We fix this function with exception of some parameters. We repeat the randomized decision several times at the fixed values of those parameters and accept the best decision as the result. We optimize the parameters of the randomized decision function to make the search more efficient. Thus we reduce the discrete optimization problem to the continuous problem of global stochastic optimization. We solve this problem by the Bayesian methods of continuous global optimization. We describe the applications to some well known An problems of discrete programming, such as knapsack, traveling salesman, and scheduling.
Local Literacies, Global Scales: The Labor of Global Connectivity
ERIC Educational Resources Information Center
Stornaiuolo, Amy; LeBlanc, Robert Jean
2014-01-01
While connecting students and teachers in new configurations using digital technologies offers great promise for literacy and learning, this column considers the complexities of negotiating local and global literacies in global collaborations. It introduces the theoretical concept of "scaling" to highlight the ways teachers actively and…
Local Decisions and Global Networks
ERIC Educational Resources Information Center
King, David C.; Long, Cathryn J.
1976-01-01
Impact of economic and urban planning on the natural environment can be studied through local situations: California conservation students realized the detrimental effects of a seemingly beneficial dam project. Students were inspired to initiate community-state action to correct damage to wildlife, sanitation, and farming. (AV)
Applications of parallel global optimization to mechanics problems
NASA Astrophysics Data System (ADS)
Schutte, Jaco Francois
Global optimization of complex engineering problems, with a high number of variables and local minima, requires sophisticated algorithms with global search capabilities and high computational efficiency. With the growing availability of parallel processing, it makes sense to address these requirements by increasing the parallelism in optimization strategies. This study proposes three methods of concurrent processing. The first method entails exploiting the structure of population-based global algorithms such as the stochastic Particle Swarm Optimization (PSO) algorithm and the Genetic Algorithm (GA). As a demonstration of how such an algorithm may be adapted for concurrent processing we modify and apply the PSO to several mechanical optimization problems on a parallel processing machine. Desirable PSO algorithm features such as insensitivity to design variable scaling and modest sensitivity to algorithm parameters are demonstrated. A second approach to parallelism and improving algorithm efficiency is by utilizing multiple optimizations. With this method a budget of fitness evaluations is distributed among several independent sub-optimizations in place of a single extended optimization. Under certain conditions this strategy obtains a higher combined probability of converging to the global optimum than a single optimization which utilizes the full budget of fitness evaluations. The third and final method of parallelism addressed in this study is the use of quasiseparable decomposition, which is applied to decompose loosely coupled problems. This yields several sub-problems of lesser dimensionality which may be concurrently optimized with reduced effort.
Similarity-based global optimization of buildings in urban scene
NASA Astrophysics Data System (ADS)
Zhu, Quansheng; Zhang, Jing; Jiang, Wanshou
2013-10-01
In this paper, an approach for the similarity-based global optimization of buildings in urban scene is presented. In the past, most researches concentrated on single building reconstruction, making it difficult to reconstruct reliable models from noisy or incomplete point clouds. To obtain a better result, a new trend is to utilize the similarity among the buildings. Therefore, a new similarity detection and global optimization strategy is adopted to modify local-fitting geometric errors. Firstly, the hierarchical structure that consists of geometric, topological and semantic features is constructed to represent complex roof models. Secondly, similar roof models can be detected by combining primitive structure and connection similarities. At last, the global optimization strategy is applied to preserve the consistency and precision of similar roof structures. Moreover, non-local consolidation is adapted to detect small roof parts. The experiments reveal that the proposed method can obtain convincing roof models and promote the reconstruction quality of 3D buildings in urban scene.
Consuming Globalization, Local Identities, and Common Experiences
ERIC Educational Resources Information Center
Filax, Gloria
2004-01-01
In articulating global and local forms of sexuality and its impact on how people conceptualise conceptualised LGBT issues in education, the author explores three timely texts: (1) Dennis Altman's "Global Sex" (2000); (2) Vanessa Baird's "The No-Nonsense Guide to Sexual Diversity" (2001); and (3) an edited volume by Evelyn Blackwood and Saskia…
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…
Local and Global Thinking in Statistical Inference
ERIC Educational Resources Information Center
Pratt, Dave; Johnston-Wilder, Peter; Ainley, Janet; Mason, John
2008-01-01
In this reflective paper, we explore students' local and global thinking about informal statistical inference through our observations of 10- to 11-year-olds, challenged to infer the unknown configuration of a virtual die, but able to use the die to generate as much data as they felt necessary. We report how they tended to focus on local changes…
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.
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.
Orbit design and optimization based on global telecommunication performance metrics
NASA Technical Reports Server (NTRS)
Lee, Seungwon; Lee, Charles H.; Kerridge, Stuart; Cheung, Kar-Ming; Edwards, Charles D.
2006-01-01
The orbit selection of telecommunications orbiters is one of the critical design processes and should be guided by global telecom performance metrics and mission-specific constraints. In order to aid the orbit selection, we have coupled the Telecom Orbit Analysis and Simulation Tool (TOAST) with genetic optimization algorithms. As a demonstration, we have applied the developed tool to select an optimal orbit for general Mars telecommunications orbiters with the constraint of being a frozen orbit. While a typical optimization goal is to minimize tele-communications down time, several relevant performance metrics are examined: 1) area-weighted average gap time, 2) global maximum of local maximum gap time, 3) global maximum of local minimum gap time. Optimal solutions are found with each of the metrics. Common and different features among the optimal solutions as well as the advantage and disadvantage of each metric are presented. The optimal solutions are compared with several candidate orbits that were considered during the development of Mars Telecommunications Orbiter.
Thriving locally in the global economy.
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. PMID:12884672
Global source optimization for MEEF and OPE
NASA Astrophysics Data System (ADS)
Matsui, Ryota; Noda, Tomoya; Aoyama, Hajime; Kita, Naonori; Matsuyama, Tomoyuki; Flagello, Donis
2013-04-01
This work describes freeform source optimization considering mask error enhancement factor (MEEF), optical proximity effect (OPE), process window, and hardware-specific constraints. Our algorithm allows users to define maximum allowed MEEF and OPE error as constraints without defining weights among the metrics. We also consider hardware specific constraints, so that the optimized source is suitable to be realized in Nikon's Intelligent Illumination hardware. Our approach utilizes a global optimization procedure to arrive at a freeform source shape solution, and since each source grid-point is assigned as variable, the source solution encompasses the maximum amount of degrees of freedom.
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.
Some comments on global-local analyses
NASA Technical Reports Server (NTRS)
Atluri, Satya N.
1989-01-01
The main theme concerns methods that may be classified as global (approximate) and local (exact). Some specific applications of these methods are found in: fracture and fatigue analysis of structures with 3-D surface flaws; large-deformation, post-buckling analysis of large space trusses and space frames, and their control; and stresses around holes in composite laminates.
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)
Exploring Local to Global Leadership Education Assessment
ERIC Educational Resources Information Center
Dugan, John P.
2012-01-01
From individual student learning outcomes to full-scale program enhancement, assessment is critical in developing and sustaining leadership education. This chapter will look at assessment techniques and trends spanning from local to global frameworks. International Leadership Association overarching Outcomes and Assessment Guiding Question: "What…
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.
A Novel Particle Swarm Optimization Algorithm for Global Optimization
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
A Novel Particle Swarm Optimization Algorithm for Global Optimization.
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 search algorithm for optimal control
NASA Technical Reports Server (NTRS)
Brocker, D. H.; Kavanaugh, W. P.; Stewart, E. C.
1970-01-01
Random-search algorithm employs local and global properties to solve two-point boundary value problem in Pontryagin maximum principle for either fixed or variable end-time problems. Mixed boundary value problem is transformed to an initial value problem. Mapping between initial and terminal values utilizes hybrid computer.
Global time optimal motions of robotic manipulators in the presence of obstacles
NASA Technical Reports Server (NTRS)
Shiller, Zvi; Dubowsky, Steven
1988-01-01
A practical method to obtain the global time optimal motions of robotic manipulators is presented. This method takes into account the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacles. Previously developed methods of optimizing manipulator motions along given paths and a local path optimization are utilized. A set of best paths is obtained first in a global search over the manipulator workspace, using graph search and hierarchical pruning techniques. These paths are used as initial conditions for a continuous path optimization to yield the global optimal motion. Examples of optimized motions of a six-degree-of-freedom manipulator, operating in a three-dimensional space with obstacles, are presented.
Localizing global hedgehogs on the brane
NASA Astrophysics Data System (ADS)
Cho, Inyong
2004-10-01
We investigate the localization of 4D topological global defects on the brane embedded in 5D. The defects are induced by 5D scalar fields with a symmetry-breaking potential. Taking an Ansatz which separates the scalar field into the 4D and the extra-D part, we find that the static-hedgehog configuration is accomplished and the defects are formed only in the AdS4/AdS5 background. In the extra dimension, the localization amplitude for the 4D defects is high where the warp factor is high.
Localizing global hedgehogs on the brane
Cho, Inyong
2004-10-15
We investigate the localization of 4D topological global defects on the brane embedded in 5D. The defects are induced by 5D scalar fields with a symmetry-breaking potential. Taking an Ansatz which separates the scalar field into the 4D and the extra-D part, we find that the static-hedgehog configuration is accomplished and the defects are formed only in the AdS{sub 4}/AdS{sub 5} background. In the extra dimension, the localization amplitude for the 4D defects is high where the warp factor is high.
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.
Global optimization algorithm for heat exchanger networks
Quesada, I.; Grossmann, I.E. )
1993-03-01
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 is 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.
Global optimization of bilinear engineering design models
Grossmann, I.; Quesada, I.
1994-12-31
Recently Quesada and Grossmann have proposed a global optimization algorithm for solving NLP problems involving linear fractional and bilinear terms. This model has been motivated by a number of applications in process design. The proposed method relies on the derivation of a convex NLP underestimator problem that is used within a spatial branch and bound search. This paper explores the use of alternative bounding approximations for constructing the underestimator problem. These are applied in the global optimization of problems arising in different engineering areas and for which different relaxations are proposed depending on the mathematical structure of the models. These relaxations include linear and nonlinear underestimator problems. Reformulations that generate additional estimator functions are also employed. Examples from process design, structural design, portfolio investment and layout design are presented.
Competing intelligent search agents in global optimization
Streltsov, S.; Vakili, P.; Muchnik, I.
1996-12-31
In this paper we present a new search methodology that we view as a development of intelligent agent approach to the analysis of complex system. The main idea is to consider search process as a competition mechanism between concurrent adaptive intelligent agents. Agents cooperate in achieving a common search goal and at the same time compete with each other for computational resources. We propose a statistical selection approach to resource allocation between agents that leads to simple and efficient on average index allocation policies. We use global optimization as the most general setting that encompasses many types of search problems, and show how proposed selection policies can be used to improve and combine various global optimization methods.
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)
Solving global optimization problems on GPU cluster
NASA Astrophysics Data System (ADS)
Barkalov, Konstantin; Gergel, Victor; Lebedev, Ilya
2016-06-01
The paper contains the results of investigation of a parallel global optimization algorithm combined with a dimension reduction scheme. This allows solving multidimensional problems by means of reducing to data-independent subproblems with smaller dimension solved in parallel. The new element implemented in the research consists in using several graphic accelerators at different computing nodes. The paper also includes results of solving problems of well-known multiextremal test class GKLS on Lobachevsky supercomputer using tens of thousands of GPU cores.
Global optimization of actively morphing flapping wings
NASA Astrophysics Data System (ADS)
Ghommem, Mehdi; Hajj, Muhammad R.; Mook, Dean T.; Stanford, Bret K.; Beran, Philip S.; Snyder, Richard D.; Watson, Layne T.
2012-08-01
We consider active shape morphing to optimize the flight performance of flapping wings. To this end, we combine a three-dimensional version of the unsteady vortex lattice method (UVLM) with a deterministic global optimization algorithm to identify the optimal kinematics that maximize the propulsive efficiency under lift and thrust constraints. The UVLM applies only to incompressible, inviscid flows where the separation lines are known a priori. Two types of morphing parameterization are investigated here—trigonometric and spline-based. The results show that the spline-based morphing, which requires specification of more design variables, yields a significant improvement in terms of propulsive efficiency. Furthermore, we remark that the average value of the lift coefficient in the optimized kinematics remained equal to the value in the baseline case (without morphing). This indicates that morphing is most efficiently used to generate thrust and not to increase lift beyond the basic value obtained by flapping only. Besides, our study gives comparable optimal efficiencies to those obtained from previous studies based on gradient-based optimization, but completely different design points (especially for the spline-based morphing), which would indicate that the design space associated with the flapping kinematics is very complex.
Evolution of local and global monopole networks
Martins, C. J. A. P.; Achucarro, A.
2008-10-15
We present an extension of the velocity-dependent one-scale model for cosmic string evolution, which is suitable for describing the evolution of local and global monopole networks. We discuss the key dynamical features that need to be accounted for, in particular, the fact that the driving force is due to the other monopoles (rather than being due to local curvature as in the case of extended objects) and new forms of energy-loss terms due to monopole-antimonopole capture and annihilation. For the case of local monopoles we recover and generalize the results of Preskill, suggesting that the scaling law for the monopole correlation length is very sensitive to the annihilation rate. On the other hand, for global monopoles the long-range forces generically lead to linear scaling (just like in the case of local cosmic strings). In this case we also find good qualitative agreement between our results and the numerical simulations of Bennett and Rhie and Yamaguchi, although future high-resolution simulations will be needed for quantitative comparisons.
Efficient global optimization of a limited parameter antenna design
NASA Astrophysics Data System (ADS)
O'Donnell, Teresa H.; Southall, Hugh L.; Kaanta, Bryan
2008-04-01
Efficient Global Optimization (EGO) is a competent evolutionary algorithm suited for problems with limited design parameters and expensive cost functions. Many electromagnetics problems, including some antenna designs, fall into this class, as complex electromagnetics simulations can take substantial computational effort. This makes simple evolutionary algorithms such as genetic algorithms or particle swarms very time-consuming for design optimization, as many iterations of large populations are usually required. When physical experiments are necessary to perform tradeoffs or determine effects which may not be simulated, use of these algorithms is simply not practical at all due to the large numbers of measurements required. In this paper we first present a brief introduction to the EGO algorithm. We then present the parasitic superdirective two-element array design problem and results obtained by applying EGO to obtain the optimal element separation and operating frequency to maximize the array directivity. We compare these results to both the optimal solution and results obtained by performing a similar optimization using the Nelder-Mead downhill simplex method. Our results indicate that, unlike the Nelder-Mead algorithm, the EGO algorithm did not become stuck in local minima but rather found the area of the correct global minimum. However, our implementation did not always drill down into the precise minimum and the addition of a local search technique seems to be indicated.
p-MEMPSODE: Parallel and irregular memetic global optimization
NASA Astrophysics Data System (ADS)
Voglis, C.; Hadjidoukas, P. E.; Parsopoulos, K. E.; Papageorgiou, D. G.; Lagaris, I. E.; Vrahatis, M. N.
2015-12-01
A parallel memetic global optimization algorithm suitable for shared memory multicore systems is proposed and analyzed. The considered algorithm combines two well-known and widely used population-based stochastic algorithms, namely Particle Swarm Optimization and Differential Evolution, with two efficient and parallelizable local search procedures. The sequential version of the algorithm was first introduced as MEMPSODE (MEMetic Particle Swarm Optimization and Differential Evolution) and published in the CPC program library. We exploit the inherent and highly irregular parallelism of the memetic global optimization algorithm by means of a dynamic and multilevel approach based on the OpenMP tasking model. In our case, tasks correspond to local optimization procedures or simple function evaluations. Parallelization occurs at each iteration step of the memetic algorithm without affecting its searching efficiency. The proposed implementation, for the same random seed, reaches the same solution irrespectively of being executed sequentially or in parallel. Extensive experimental evaluation has been performed in order to illustrate the speedup achieved on a shared-memory multicore server.
Tabu search method with random moves for globally optimal design
NASA Astrophysics Data System (ADS)
Hu, Nanfang
1992-09-01
Optimum engineering design problems are usually formulated as non-convex optimization problems of continuous variables. Because of the absence of convexity structure, they can have multiple minima, and global optimization becomes difficult. Traditional methods of optimization, such as penalty methods, can often be trapped at a local optimum. The tabu search method with random moves to solve approximately these problems is introduced. Its reliability and efficiency are examined with the help of standard test functions. By the analysis of the implementations, it is seen that this method is easy to use, and no derivative information is necessary. It outperforms the random search method and composite genetic algorithm. In particular, it is applied to minimum weight design examples of a three-bar truss, coil springs, a Z-section and a channel section. For the channel section, the optimal design using the tabu search method with random moves saved 26.14 percent over the weight of the SUMT method.
Combinatorics of locally optimal RNA secondary structures.
Fusy, Eric; Clote, Peter
2014-01-01
It is a classical result of Stein and Waterman that the asymptotic number of RNA secondary structures is 1.104366∙n-3/2∙2.618034n. Motivated by the kinetics of RNA secondary structure formation, we are interested in determining the asymptotic number of secondary structures that are locally optimal, with respect to a particular energy model. In the Nussinov energy model, where each base pair contributes -1 towards the energy of the structure, locally optimal structures are exactly the saturated structures, for which we have previously shown that asymptotically, there are 1.07427∙n-3/2∙2.35467n many saturated structures for a sequence of length n. In this paper, we consider the base stacking energy model, a mild variant of the Nussinov model, where each stacked base pair contributes -1 toward the energy of the structure. Locally optimal structures with respect to the base stacking energy model are exactly those secondary structures, whose stems cannot be extended. Such structures were first considered by Evers and Giegerich, who described a dynamic programming algorithm to enumerate all locally optimal structures. In this paper, we apply methods from enumerative combinatorics to compute the asymptotic number of such structures. Additionally, we consider analogous combinatorial problems for secondary structures with annotated single-stranded, stacking nucleotides (dangles). PMID:23263300
A novel support vector machine with globality-locality preserving.
Ma, Cheng-Long; Yuan, Yu-Bo
2014-01-01
Support vector machine (SVM) is regarded as a powerful method for pattern classification. However, the solution of the primal optimal model of SVM is susceptible for class distribution and may result in a nonrobust solution. In order to overcome this shortcoming, an improved model, support vector machine with globality-locality preserving (GLPSVM), is proposed. It introduces globality-locality preserving into the standard SVM, which can preserve the manifold structure of the data space. We complete rich experiments on the UCI machine learning data sets. The results validate the effectiveness of the proposed model, especially on the Wine and Iris databases; the recognition rate is above 97% and outperforms all the algorithms that were developed from SVM. PMID:25045750
Potential Representation - Global vs. Local Trial Functions
NASA Astrophysics Data System (ADS)
Michel, Volker
2014-05-01
Many systems of trial functions are available for representing potential fields on the sphere or parts of the sphere. We distinguish global trial functions (such as spherical harmonics) from localized trial functions (such as spline basis functions, scaling functions, wavelets, and Slepian functions). All these systems have their own pros and cons. We discuss the advantages and disadvantages of several selected systems of trial functions and propose criteria for their applicability. Moreover, we present an algorithm which is able to combine different types of trial functions. This yields a sparser solution which combines the features of the different basis systems which are used.
NASA Technical Reports Server (NTRS)
Dong, Stanley B.
1989-01-01
An important consideration in the global local finite-element method (GLFEM) is the availability of global functions for the given problem. The role and mathematical requirements of these global functions in a GLFEM analysis of localized stress states in prismatic structures are discussed. A method is described for determining these global functions. Underlying this method are theorems due to Toupin and Knowles on strain energy decay rates, which are related to a quantitative expression of Saint-Venant's principle. It is mentioned that a mathematically complete set of global functions can be generated, so that any arbitrary interface condition between the finite element and global subregions can be represented. Convergence to the true behavior can be achieved with increasing global functions and finite-element degrees of freedom. Specific attention is devoted to mathematically two-dimensional and three-dimensional prismatic structures. Comments are offered on the GLFEM analysis of NASA flat panel with a discontinuous stiffener. Methods for determining global functions for other effects are also indicated, such as steady-state dynamics and bodies under initial stress.
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.
Local and global superconductivity in bismuth
NASA Astrophysics Data System (ADS)
Baring, Luis A.; da Silva, Robson R.; Kopelevich, Yakov
2011-10-01
We performed magnetization M(H, T) and magnetoresistance R(T, H) measurements on powdered (grain size ˜149 μm) as well as highly oriented rhombohedral (A7) bismuth (Bi) samples consisting of single crystalline blocks of size ˜1 × 1 mm in the plane perpendicular to the trigonal c axis. The obtained results revealed the occurrence of (1) local superconductivity in powdered samples with Tc(0) = (8.75 ± 0.05) K, and (2) global superconductivity at Tc(0) = (7.3 ± 0.1) K in polycrystalline Bi triggered by low-resistance ohmic contacts with silver (Ag) normal metal. The results provide evidence that the superconductivity in Bi is localized in a tiny volume fraction, probably at intergrain or Ag/Bi interfaces. On the other hand, the occurrence of global superconductivity observed for polycrystalline Bi can be accounted for by enhancement of the superconducting order parameter phase stiffness induced by the normal metal contacts, the scenario proposed in the context of "pseudogap regime" in cuprates [E. Berg et al., Phys. Rev. B 78, 094509 (2008)].
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.
Anderson localization makes adiabatic quantum optimization fail
Altshuler, Boris; Krovi, Hari; Roland, Jérémie
2010-01-01
Understanding NP-complete problems is a central topic in computer science (NP stands for nondeterministic polynomial time). This is why adiabatic quantum optimization has attracted so much attention, as it provided a new approach to tackle NP-complete problems using a quantum computer. The efficiency of this approach is limited by small spectral gaps between the ground and excited states of the quantum computer’s Hamiltonian. We show that the statistics of the gaps can be analyzed in a novel way, borrowed from the study of quantum disordered systems in statistical mechanics. It turns out that due to a phenomenon similar to Anderson localization, exponentially small gaps appear close to the end of the adiabatic algorithm for large random instances of NP-complete problems. This implies that unfortunately, adiabatic quantum optimization fails: The system gets trapped in one of the numerous local minima. PMID:20616043
Multi-fidelity global design optimization including parallelization potential
NASA Astrophysics Data System (ADS)
Cox, Steven Edward
The DIRECT global optimization algorithm is a relatively new space partitioning algorithm designed to determine the globally optimal design within a designated design space. This dissertation examines the applicability of the DIRECT algorithm to two classes of design problems: unimodal functions where small amplitude, high frequency fluctuations in the objective function make optimization difficult; and multimodal functions where multiple local optima are formed by the underlying physics of the problem (as opposed to minor fluctuations in the analysis code). DIRECT is compared with two other multistart local optimization techniques on two polynomial test problems and one engineering conceptual design problem. Three modifications to the DIRECT algorithm are proposed to increase the effectiveness of the algorithm. The DIRECT-BP algorithm is presented which alters the way DIRECT searches the neighborhood of the current best point as optimization progresses. The algorithm reprioritizes which points to analyze at each iteration. This is to encourage analysis of points that surround the best point but that are farther away than the points selected by the DIRECT algorithm. This increases the robustness of the DIRECT search and provides more information on the characteristics of the neighborhood of the point selected as the global optimum. A multifidelity version of the DIRECT algorithm is proposed to reduce the cost of optimization using DIRECT. By augmenting expensive high-fidelity analysis with cheap low-fidelity analysis, the optimization can be performed with fewer high-fidelity analyses. Two correction schemes are examined using high- and low-fidelity results at one point to correct the low-fidelity result at a nearby point. This corrected value is then used in place of a high-fidelity analysis by the DIRECT algorithm. In this way the number of high-fidelity analyses required is reduced and the optimization became less expensive. Finally the DIRECT algorithm is
Global versus local quantum squeezing in composite systems
Yang Yang; Wang Xiaoguang; Liu Wanfang; Sun Zhe
2009-05-15
We investigate relations between the global squeezing of composite systems and the local squeezing of subsystems. For the pure symmetric product states, the global squeezing parameter is found to be equal to the local one for both spin and bosonic systems. Hence, a pure symmetric state is entangled if the global parameter is not equal to the local one. Two origins of the global squeezing are identified: one is from the local squeezing and the other from quantum correlations. For both spin and bosonic systems, we find that the entanglement can lead to a smaller global squeezing parameter; namely, the global squeezing is enhanced.
Optimal Jammer Placement in Wireless Localization Systems
NASA Astrophysics Data System (ADS)
Gezici, Sinan; Bayram, Suat; Kurt, Mehmet Necip; Gholami, Mohammad Reza
2016-09-01
In this study, the optimal jammer placement problem is proposed and analyzed for wireless localization systems. In particular, the optimal location of a jammer node is obtained by maximizing the minimum of the Cramer-Rao lower bounds (CRLBs) for a number of target nodes under location related constraints for the jammer node. For scenarios with more than two target nodes, theoretical results are derived to specify conditions under which the jammer node is located as close to a certain target node as possible, or the optimal location of the jammer node is determined by two of the target nodes. Also, explicit expressions are provided for the optimal location of the jammer node in the presence of two target nodes. In addition, in the absence of distance constraints for the jammer node, it is proved, for scenarios with more than two target nodes, that the optimal jammer location lies on the convex hull formed by the locations of the target nodes and is determined by two or three of the target nodes, which have equalized CRLBs. Numerical examples are presented to provide illustrations of the theoretical results in different scenarios.
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.
On computational schemes for global-local stress analysis
NASA Technical Reports Server (NTRS)
Reddy, J. N.
1989-01-01
An overview is given of global-local stress analysis methods and associated difficulties and recommendations for future research. The phrase global-local analysis is understood to be an analysis in which some parts of the domain or structure are identified, for reasons of accurate determination of stresses and displacements or for more refined analysis than in the remaining parts. The parts of refined analysis are termed local and the remaining parts are called global. Typically local regions are small in size compared to global regions, while the computational effort can be larger in local regions than in global regions.
Globally optimal surface mapping for surfaces with arbitrary topology.
Li, Xin; Bao, Yunfan; Guo, Xiaohu; Jin, Miao; Gu, Xianfeng; Qin, Hong
2008-01-01
Computing smooth and optimal one-to-one maps between surfaces of same topology is a fundamental problem in computer graphics and such a method provides us a ubiquitous tool for geometric modeling and data visualization. Its vast variety of applications includes shape registration/matching, shape blending, material/data transfer, data fusion, information reuse, etc. The mapping quality is typically measured in terms of angular distortions among different shapes. This paper proposes and develops a novel quasi-conformal surface mapping framework to globally minimize the stretching energy inevitably introduced between two different shapes. The existing state-of-the-art inter-surface mapping techniques only afford local optimization either on surface patches via boundary cutting or on the simplified base domain, lacking rigorous mathematical foundation and analysis. We design and articulate an automatic variational algorithm that can reach the global distortion minimum for surface mapping between shapes of arbitrary topology, and our algorithm is sorely founded upon the intrinsic geometry structure of surfaces. To our best knowledge, this is the first attempt towards numerically computing globally optimal maps. Consequently, our mapping framework offers a powerful computational tool for graphics and visualization tasks such as data and texture transfer, shape morphing, and shape matching. PMID:18467756
Global network influences on local functional connectivity
Snyder, Adam C.; Morais, Michael J.; Willis, Cory M.; Smith, Matthew A.
2015-01-01
A central neuroscientific pursuit is understanding neuronal interactions that support computations underlying cognition and behavior. Although neurons interact across disparate scales – from cortical columns to whole-brain networks – research has been restricted to one scale at a time. We measured local interactions through multi-neuronal recordings while accessing global networks using scalp EEG in rhesus macaques. We measured spike count correlation, an index of functional connectivity with computational relevance, and EEG oscillations, which have been linked to various cognitive functions. We found a surprising non-monotonic relationship between EEG oscillation amplitude and spike count correlation, contrary to the intuitive expectation of a direct relationship. With a widely-used network model we replicated these findings by incorporating a private signal targeting inhibitory neurons, a common mechanism proposed for gain modulation. Finally, we report that spike count correlation explains nonlinearities in the relationship between EEG oscillations and response time in a spatial selective attention task. PMID:25799040
Optimal design of auxetic hexachiral metamaterials with local resonators
NASA Astrophysics Data System (ADS)
Bacigalupo, Andrea; Lepidi, Marco; Gnecco, Giorgio; Gambarotta, Luigi
2016-05-01
A parametric beam lattice model is formulated to analyze the propagation properties of elastic in-plane waves in an auxetic material based on a hexachiral topology of the periodic cell, equipped with inertial local resonators. The Floquet–Bloch boundary conditions are imposed on a low-order linear model, suitably reduced to the only dynamically active degrees-of-freedom through a quasistatic stiffness condensation. Since the resonators can be designed to open and shift band gaps, an optimal design, focused on the largest possible gap in the low-frequency range, is achieved by solving a maximization problem in the bounded space of the significant geometrical and mechanical parameters. A local optimized solution, for the lowest pair of consecutive dispersion curves, is found by employing the globally convergent version of the method of moving asymptotes, combined with Monte Carlo and quasi-Monte Carlo multi-start techniques.
LDRD Final Report: Global Optimization for Engineering Science Problems
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.
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.
Global Optimization of Low-Thrust Interplanetary Trajectories Subject to Operational Constraints
NASA Technical Reports Server (NTRS)
Englander, Jacob A.; Vavrina, Matthew A.; Hinckley, David
2016-01-01
Low-thrust interplanetary space missions are highly complex and there can be many locally optimal solutions. While several techniques exist to search for globally optimal solutions to low-thrust trajectory design problems, they are typically limited to unconstrained trajectories. The operational design community in turn has largely avoided using such techniques and has primarily focused on accurate constrained local optimization combined with grid searches and intuitive design processes at the expense of efficient exploration of the global design space. This work is an attempt to bridge the gap between the global optimization and operational design communities by presenting a mathematical framework for global optimization of low-thrust trajectories subject to complex constraints including the targeting of planetary landing sites, a solar range constraint to simplify the thermal design of the spacecraft, and a real-world multi-thruster electric propulsion system that must switch thrusters on and off as available power changes over the course of a mission.
Global Optimization Techniques for Fluid Flow and Propulsion Devices
NASA Technical Reports Server (NTRS)
Shyy, Wei; Papila, Nilay; Vaidyanathan, Raj; Tucker, Kevin; Griffin, Lisa; Dorney, Dan; Huber, Frank; Tran, Ken; Turner, James E. (Technical Monitor)
2001-01-01
This viewgraph presentation gives an overview of global optimization techniques for fluid flow and propulsion devices. Details are given on the need, characteristics, and techniques for global optimization. The techniques include response surface methodology (RSM), neural networks and back-propagation neural networks, design of experiments, face centered composite design (FCCD), orthogonal arrays, outlier analysis, and design optimization.
GenMin: An enhanced genetic algorithm for global optimization
NASA Astrophysics Data System (ADS)
Tsoulos, Ioannis G.; Lagaris, I. E.
2008-06-01
A new method that employs grammatical evolution and a stopping rule for finding the global minimum of a continuous multidimensional, multimodal function is considered. The genetic algorithm used is a hybrid genetic algorithm in conjunction with a local search procedure. We list results from numerical experiments with a series of test functions and we compare with other established global optimization methods. The accompanying software accepts objective functions coded either in Fortran 77 or in C++. Program summaryProgram title: GenMin Catalogue identifier: AEAR_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAR_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 35 810 No. of bytes in distributed program, including test data, etc.: 436 613 Distribution format: tar.gz Programming language: GNU-C++, GNU-C, GNU Fortran 77 Computer: The tool is designed to be portable in all systems running the GNU C++ compiler Operating system: The tool is designed to be portable in all systems running the GNU C++ compiler RAM: 200 KB Word size: 32 bits Classification: 4.9 Nature of problem: A multitude of problems in science and engineering are often reduced to minimizing a function of many variables. There are instances that a local optimum does not correspond to the desired physical solution and hence the search for a better solution is required. Local optimization techniques are frequently trapped in local minima. Global optimization is hence the appropriate tool. For example, solving a nonlinear system of equations via optimization, employing a least squares type of objective, one may encounter many local minima that do not correspond to solutions (i.e. they are far from zero). Solution method: Grammatical evolution and a stopping rule. Running time: Depending on the
NASA Technical Reports Server (NTRS)
Yamaleev, N. K.; Diskin, B.; Nielsen, E. J.
2009-01-01
.We study local-in-time adjoint-based methods for minimization of ow matching functionals subject to the 2-D unsteady compressible Euler equations. The key idea of the local-in-time method is to construct a very accurate approximation of the global-in-time adjoint equations and the corresponding sensitivity derivative by using only local information available on each time subinterval. In contrast to conventional time-dependent adjoint-based optimization methods which require backward-in-time integration of the adjoint equations over the entire time interval, the local-in-time method solves local adjoint equations sequentially over each time subinterval. Since each subinterval contains relatively few time steps, the storage cost of the local-in-time method is much lower than that of the global adjoint formulation, thus making the time-dependent optimization feasible for practical applications. The paper presents a detailed comparison of the local- and global-in-time adjoint-based methods for minimization of a tracking functional governed by the Euler equations describing the ow around a circular bump. Our numerical results show that the local-in-time method converges to the same optimal solution obtained with the global counterpart, while drastically reducing the memory cost as compared to the global-in-time adjoint formulation.
Parasail: SIMD C library for global, semi-global, and local pairwise sequence alignments
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
Multi-organ localization with cascaded global-to-local regression and shape prior.
Gauriau, Romane; Cuingnet, Rémi; Lesage, David; Bloch, Isabelle
2015-07-01
We propose a method for fast, accurate and robust localization of several organs in medical images. We generalize the global-to-local cascade of regression random forest to multiple organs. A first regressor encodes the global relationships between organs, learning simultaneously all organs parameters. Then subsequent regressors refine the localization of each organ locally and independently for improved accuracy. By combining the regression vote distribution and the organ shape prior (through probabilistic atlas representation) we compute confidence maps that are organ-dedicated probability maps. They are used within the cascade itself, to better select the test voxels for the second set of regressors, and to provide richer information than the classical bounding boxes result thanks to the shape prior. We propose an extensive study of the different learning and testing parameters, showing both their robustness to reasonable perturbations and their influence on the final algorithm accuracy. Finally we demonstrate the robustness and accuracy of our approach by evaluating the localization of six abdominal organs (liver, two kidneys, spleen, gallbladder and stomach) on a large and diverse database of 130 CT volumes. Moreover, the comparison of our results with two existing methods shows significant improvements brought by our approach and our deep understanding and optimization of the parameters. PMID:25974326
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
A unified approach to global and local beam position feedback
Chung, Y.
1994-08-01
The Advanced Photon Source (APS) will implement both global and local beam position feedback systems to stabilize the particle and X-ray beams for the storage ring. The global feedback system uses 40 BPMs and 40 correctors per plane. Singular value decomposition (SVD) of the response matrix is used for closed orbit correction. The local feedback system uses two X-ray BPMS, two rf BPMS, and the four-magnet local bump to control the angle and displacement of the X-ray beam from a bending magnet or an insertion device. Both the global and local feedback systems are based on digital signal processing (DSP) running at 4-kHz sampling rate with a proportional, integral, and derivative (PID) control algorithm. In this paper, we will discuss resolution of the conflict among multiple local feedback systems due to local bump closure error and decoupling of the global and local feedback systems to maximize correction efficiency. In this scheme, the global feedback system absorbs the local bump closure error and the local feedback systems compensate for the effect of global feedback on the local beamlines. The required data sharing between the global and local feedback systems is done through the fiber-optically networked reflective memory.
Local Optimization Strategies in Urban Vehicular Mobility.
Mastroianni, Pierpaolo; Monechi, Bernardo; Liberto, Carlo; Valenti, Gaetano; Servedio, Vito D P; Loreto, Vittorio
2015-01-01
The comprehension of vehicular traffic in urban environments is crucial to achieve a good management of the complex processes arising from people collective motion. Even allowing for the great complexity of human beings, human behavior turns out to be subject to strong constraints--physical, environmental, social, economic--that induce the emergence of common patterns. The observation and understanding of those patterns is key to setup effective strategies to optimize the quality of life in cities while not frustrating the natural need for mobility. In this paper we focus on vehicular mobility with the aim to reveal the underlying patterns and uncover the human strategies determining them. To this end we analyze a large dataset of GPS vehicles tracks collected in the Rome (Italy) district during a month. We demonstrate the existence of a local optimization of travel times that vehicle drivers perform while choosing their journey. This finding is mirrored by two additional important facts, i.e., the observation that the average vehicle velocity increases by increasing the travel length and the emergence of a universal scaling law for the distribution of travel times at fixed traveled length. A simple modeling scheme confirms this scenario opening the way to further predictions. PMID:26656106
Local Optimization Strategies in Urban Vehicular Mobility
Mastroianni, Pierpaolo; Monechi, Bernardo; Liberto, Carlo; Valenti, Gaetano; Servedio, Vito D. P.; Loreto, Vittorio
2015-01-01
The comprehension of vehicular traffic in urban environments is crucial to achieve a good management of the complex processes arising from people collective motion. Even allowing for the great complexity of human beings, human behavior turns out to be subject to strong constraints—physical, environmental, social, economic—that induce the emergence of common patterns. The observation and understanding of those patterns is key to setup effective strategies to optimize the quality of life in cities while not frustrating the natural need for mobility. In this paper we focus on vehicular mobility with the aim to reveal the underlying patterns and uncover the human strategies determining them. To this end we analyze a large dataset of GPS vehicles tracks collected in the Rome (Italy) district during a month. We demonstrate the existence of a local optimization of travel times that vehicle drivers perform while choosing their journey. This finding is mirrored by two additional important facts, i.e., the observation that the average vehicle velocity increases by increasing the travel length and the emergence of a universal scaling law for the distribution of travel times at fixed traveled length. A simple modeling scheme confirms this scenario opening the way to further predictions. PMID:26656106
Fusing global and local features for face verification
NASA Astrophysics Data System (ADS)
Zhou, Ji; Xiao, Biahua; Wang, Chunheng; Cai, Xinyuan; Chen, Xue
2013-07-01
In the literature of neurophysiology and computer vision, global and local features have both been demonstrated to be complementary for robust face recognition and verification. In this paper, we propose an approach for face verification by fusing global and local discriminative features. In this method, global features are extracted from whole face images by Fourier transform and local features are extracted from ten different component patches by a new image representation method named Histogram of Local Phase Quantization Ordinal Measures (HOLPQOM). Experimental results on the Labeled Face in Wild (LFW) benchmark show the robustness of the proposed local descriptor, compared with other often-used descriptors.
Think Globally, Act Locally (Focus on Teaching).
ERIC Educational Resources Information Center
Vesper, Joan F.
1994-01-01
Describes a project, carried out jointly between a business communication class and a local chamber of commerce, that brings students into partnership with international merchants in the local community. (SR)
Optimizing a global alignment of protein interaction networks
Chindelevitch, Leonid; Ma, Cheng-Yu; Liao, Chung-Shou; Berger, Bonnie
2013-01-01
Motivation: The global alignment of protein interaction networks is a widely studied problem. It is an important first step in understanding the relationship between the proteins in different species and identifying functional orthologs. Furthermore, it can provide useful insights into the species’ evolution. Results: We propose a novel algorithm, PISwap, for optimizing global pairwise alignments of protein interaction networks, based on a local optimization heuristic that has previously demonstrated its effectiveness for a variety of other intractable problems. PISwap can begin with different types of network alignment approaches and then iteratively adjust the initial alignments by incorporating network topology information, trading it off for sequence information. In practice, our algorithm efficiently refines other well-studied alignment techniques with almost no additional time cost. We also show the robustness of the algorithm to noise in protein interaction data. In addition, the flexible nature of this algorithm makes it suitable for different applications of network alignment. This algorithm can yield interesting insights into the evolutionary dynamics of related species. Availability: Our software is freely available for non-commercial purposes from our Web site, http://piswap.csail.mit.edu/. Contact: bab@csail.mit.edu or csliao@ie.nthu.edu.tw Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24048352
New Algorithms for Global Optimization and Reaction Path Determination.
Weber, D; Bellinger, D; Engels, B
2016-01-01
We present new schemes to improve the convergence of an important global optimization problem and to determine reaction pathways (RPs) between identified minima. Those methods have been implemented into the CAST program (Conformational Analysis and Search Tool). The first part of this chapter shows how to improve convergence of the Monte Carlo with minimization (MCM, also known as Basin Hopping) method when applied to optimize water clusters or aqueous solvation shells using a simple model. Since the random movement on the potential energy surface (PES) is an integral part of MCM, we propose to employ a hydrogen bonding-based algorithm for its improvement. We show comparisons of the results obtained for random dihedral and for the proposed random, rigid-body water molecule movement, giving evidence that a specific adaption of the distortion process greatly improves the convergence of the method. The second part is about the determination of RPs in clusters between conformational arrangements and for reactions. Besides standard approaches like the nudged elastic band method, we want to focus on a new algorithm developed especially for global reaction path search called Pathopt. We started with argon clusters, a typical benchmark system, which possess a flat PES, then stepwise increase the magnitude and directionality of interactions. Therefore, we calculated pathways for a water cluster and characterize them by frequency calculations. Within our calculations, we were able to show that beneath local pathways also additional pathways can be found which possess additional features. PMID:27497166
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.
Global smoothing and continuation for large-scale molecular optimization
More, J.J.; Wu, Zhijun
1995-10-01
We discuss the formulation of optimization problems that arise in the study of distance geometry, ionic systems, and molecular clusters. We show that continuation techniques based on global smoothing are applicable to these molecular optimization problems, and we outline the issues that must be resolved in the solution of large-scale molecular optimization problems.
Not National but Local and Global
ERIC Educational Resources Information Center
Rosenberg, David
2008-01-01
The author describes the theory and practice of a project that took place in Summer 2007 in four classes within three inner city primary schools, that brought together History, Geography and Global citizenship within a progressive educational framework.
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.
Gradient gravitational search: An efficient metaheuristic algorithm for global optimization.
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. PMID:25779670
Parallel global optimization with the particle swarm algorithm
Schutte, J. F.; Reinbolt, J. A.; Fregly, B. J.; Haftka, R. T.; George, A. D.
2007-01-01
SUMMARY Present day engineering optimization problems often impose large computational demands, resulting in long solution times even on a modern high-end processor. To obtain enhanced computational throughput and global search capability, we detail the coarse-grained parallelization of an increasingly popular global search method, the particle swarm optimization (PSO) algorithm. Parallel PSO performance was evaluated using two categories of optimization problems possessing multiple local minima—large-scale analytical test problems with computationally cheap function evaluations and medium-scale biomechanical system identification problems with computationally expensive function evaluations. For load-balanced analytical test problems formulated using 128 design variables, speedup was close to ideal and parallel efficiency above 95% for up to 32 nodes on a Beowulf cluster. In contrast, for load-imbalanced biomechanical system identification problems with 12 design variables, speedup plateaued and parallel efficiency decreased almost linearly with increasing number of nodes. The primary factor affecting parallel performance was the synchronization requirement of the parallel algorithm, which dictated that each iteration must wait for completion of the slowest fitness evaluation. When the analytical problems were solved using a fixed number of swarm iterations, a single population of 128 particles produced a better convergence rate than did multiple independent runs performed using sub-populations (8 runs with 16 particles, 4 runs with 32 particles, or 2 runs with 64 particles). These results suggest that (1) parallel PSO exhibits excellent parallel performance under load-balanced conditions, (2) an asynchronous implementation would be valuable for real-life problems subject to load imbalance, and (3) larger population sizes should be considered when multiple processors are available. PMID:17891226
Academic Inbreeding: Local Challenge, Global Problem
ERIC Educational Resources Information Center
Altbach, Philip G.; Yudkevich, Maria; Rumbley, Laura E.
2015-01-01
"Academic inbreeding"--involving the appointment of faculty members who graduated from the institution employing them--is considered a small and peripheral aspect of the academic profession but is quite widespread globally. This paper analyzes the nature of inbreeding and its impact on universities. Data from eight countries where…
Think Globally, Act Locally: A Library Perspective
ERIC Educational Resources Information Center
Clausen, Beth E.
2015-01-01
In this article, the author presents observations learned while "on loan" from Northwestern University (NU), Evanston, Illinois, to the campus library in Doha, Qatar, (NU-Q) Middle East. The author's ongoing experience is helping her see how important global exposure can be to a library professional's attaining a deeper and wider level…
Global Optimization and Broadband Analysis Software for Interstellar Chemistry (GOBASIC)
NASA Astrophysics Data System (ADS)
Rad, Mary L.; Zou, Luyao; Sanders, James L.; Widicus Weaver, Susanna L.
2016-01-01
Context. Broadband receivers that operate at millimeter and submillimeter frequencies necessitate the development of new tools for spectral analysis and interpretation. Simultaneous, global, multimolecule, multicomponent analysis is necessary to accurately determine the physical and chemical conditions from line-rich spectra that arise from sources like hot cores. Aims: We aim to provide a robust and efficient automated analysis program to meet the challenges presented with the large spectral datasets produced by radio telescopes. Methods: We have written a program in the MATLAB numerical computing environment for simultaneous global analysis of broadband line surveys. The Global Optimization and Broadband Analysis Software for Interstellar Chemistry (GOBASIC) program uses the simplifying assumption of local thermodynamic equilibrium (LTE) for spectral analysis to determine molecular column density, temperature, and velocity information. Results: GOBASIC achieves simultaneous, multimolecule, multicomponent fitting for broadband spectra. The number of components that can be analyzed at once is only limited by the available computational resources. Analysis of subsequent sets of molecules or components is performed iteratively while taking the previous fits into account. All features of a given molecule across the entire window are fitted at once, which is preferable to the rotation diagram approach because global analysis is less sensitive to blended features and noise features in the spectra. In addition, the fitting method used in GOBASIC is insensitive to the initial conditions chosen, the fitting is automated, and fitting can be performed in a parallel computing environment. These features make GOBASIC a valuable improvement over previously available LTE analysis methods. A copy of the sofware is available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (ftp://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/585/A23
Global-local finite element analysis of composite structures
Deibler, J.E.
1992-06-01
The development of layered finite elements has facilitated analysis of laminated composite structures. However, the analysis of a structure containing both isotropic and composite materials remains a difficult problem. A methodology has been developed to conduct a ``global-local`` finite element analysis. A ``global`` analysis of the entire structure is conducted at the appropriate loads with the composite portions replaced with an orthotropic material of equivalent materials properties. A ``local`` layered composite analysis is then conducted on the region of interest. The displacement results from the ``global`` analysis are used as loads to the ``local`` analysis. the laminate stresses and strains can then be examined and failure criteria evaluated.
Global-local finite element analysis of composite structures
Deibler, J.E.
1992-06-01
The development of layered finite elements has facilitated analysis of laminated composite structures. However, the analysis of a structure containing both isotropic and composite materials remains a difficult problem. A methodology has been developed to conduct a global-local'' finite element analysis. A global'' analysis of the entire structure is conducted at the appropriate loads with the composite portions replaced with an orthotropic material of equivalent materials properties. A local'' layered composite analysis is then conducted on the region of interest. The displacement results from the global'' analysis are used as loads to the local'' analysis. the laminate stresses and strains can then be examined and failure criteria evaluated.
MEASUREMENT AND OPTIMIZATION OF LOCAL COUPLING FROM RHIC BPM DATA.
CALAGA, R.; ABEYTUNGE, S.; BAI, M.; FISCHER, W.; ET AL.
2005-05-16
Global coupling in RHIC is routinely corrected by using three skew quadrupole families to minimize the tune split ({Delta}Q{sub min}). In this paper we propose to re-optimize transverse coupling by minimizing the resonance driving terms (RDT's) and the coupling matrix (|{bar C}|/{gamma}{sup 2}) in two steps: (1) Identify locations with coupling sources by inspection of the driving terms and the C-matrix around the ring and minimize the discontinuities and (2) Find the best configuration of the three skew quadrupole families to minimize both {Delta}Q{sub min} and RDTs (f{sub 1001}). The measurements of f{sub 1001} and |{bar C}|/{gamma}{sup 2} at injection and top energy to identify local coupling sources are presented.
Governing the global commons with local institutions.
Bodnar, Todd; Salathé, Marcel
2012-01-01
Most problems faced by modern human society have two characteristics in common--they are tragedy-of-the-commons type of problems, and they are global problems. Tragedy-of-the-commons type of problems are those where a commonly shared resource is overexploited by free riders at the expense of everyone sharing the resource. The exploitation of global resources such as clean air and water, political stability and peace, etc. underlies many of the most pressing human problems. Punishment of free riding behavior is one of the most frequently used strategies to combat the problem, but the spatial reach of sanctioning institutions is often more limited than the spatial effects of overexploitation. Here, we analyze a general game theoretical model to assess under what circumstances sanctioning institutions with limited reach can maintain the larger commons. We find that the effect of the spatial reach has a strong effect on whether and how the commons can be maintained, and that the transitions between those outcomes are characterized by phase transitions. The latter indicates that a small change in the reach of sanctioning systems can profoundly change the way the global commons can be managed. PMID:22509269
Contextualizing the global relevance of local land change observations
NASA Astrophysics Data System (ADS)
Magliocca, N. R.; Ellis, E. C.; Oates, T.; Schmill, M.
2014-02-01
To understand global changes in the Earth system, scientists must generalize globally from observations made locally and regionally. In land change science (LCS), local field-based observations are costly and time consuming, and generally obtained by researchers working at disparate local and regional case-study sites chosen for different reasons. As a result, global synthesis efforts in LCS tend to be based on non-statistical inferences subject to geographic biases stemming from data limitations and fragmentation. Thus, a fundamental challenge is the production of generalized knowledge that links evidence of the causes and consequences of local land change to global patterns and vice versa. The GLOBE system was designed to meet this challenge. GLOBE aims to transform global change science by enabling new scientific workflows based on statistically robust, globally relevant integration of local and regional observations using an online social-computational and geovisualization system. Consistent with the goals of Digital Earth, GLOBE has the capability to assess the global relevance of local case-study findings within the context of over 50 global biophysical, land-use, climate, and socio-economic datasets. We demonstrate the implementation of one such assessment - a representativeness analysis - with a recently published meta-study of changes in swidden agriculture in tropical forests. The analysis provides a standardized indicator to judge the global representativeness of the trends reported in the meta-study, and a geovisualization is presented that highlights areas for which sampling efforts can be reduced and those in need of further study. GLOBE will enable researchers and institutions to rapidly share, compare, and synthesize local and regional studies within the global context, as well as contributing to the larger goal of creating a Digital Earth.
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.
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
Optimizing global liver function in radiation therapy treatment planning.
Wu, Victor W; Epelman, Marina A; Wang, Hesheng; Edwin Romeijn, H; 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 ([Formula: see text]) (conventional '[Formula: see text] model'), the so-called perfusion-weighted [Formula: see text] ([Formula: see text]) (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 [Formula: see text], fEUD, and GLF plans delivering the same target [Formula: see text] 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 [Formula: see text] more liver function than the fEUD ([Formula: see text]) plan does in 2D cases, and up to [Formula: see text] in 3D cases. The GLF and fEUD plans worsen in [Formula: see text] 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 often
ABCluster: the artificial bee colony algorithm for cluster global optimization.
Zhang, Jun; Dolg, Michael
2015-10-01
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. PMID:26327507
A Guiding Evolutionary Algorithm with Greedy Strategy for Global Optimization Problems
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
A Guiding Evolutionary Algorithm with Greedy Strategy for Global Optimization Problems.
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
Modeling and Global Optimization of DNA separation
Fahrenkopf, Max A.; Ydstie, B. Erik; Mukherjee, Tamal; Schneider, James W.
2014-01-01
We develop a non-convex non-linear programming problem that determines the minimum run time to resolve different lengths of DNA using a gel-free micelle end-labeled free solution electrophoresis separation method. Our optimization framework allows for efficient determination of the utility of different DNA separation platforms and enables the identification of the optimal operating conditions for these DNA separation devices. The non-linear programming problem requires a model for signal spacing and signal width, which is known for many DNA separation methods. As a case study, we show how our approach is used to determine the optimal run conditions for micelle end-labeled free-solution electrophoresis and examine the trade-offs between a single capillary system and a parallel capillary system. Parallel capillaries are shown to only be beneficial for DNA lengths above 230 bases using a polydisperse micelle end-label otherwise single capillaries produce faster separations. PMID:24764606
Modeling and Global Optimization of DNA separation.
Fahrenkopf, Max A; Ydstie, B Erik; Mukherjee, Tamal; Schneider, James W
2014-05-01
We develop a non-convex non-linear programming problem that determines the minimum run time to resolve different lengths of DNA using a gel-free micelle end-labeled free solution electrophoresis separation method. Our optimization framework allows for efficient determination of the utility of different DNA separation platforms and enables the identification of the optimal operating conditions for these DNA separation devices. The non-linear programming problem requires a model for signal spacing and signal width, which is known for many DNA separation methods. As a case study, we show how our approach is used to determine the optimal run conditions for micelle end-labeled free-solution electrophoresis and examine the trade-offs between a single capillary system and a parallel capillary system. Parallel capillaries are shown to only be beneficial for DNA lengths above 230 bases using a polydisperse micelle end-label otherwise single capillaries produce faster separations. PMID:24764606
Global and local pitch perception in children with developmental dyslexia.
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. PMID:22204845
Local Ionospheric Modeling Using the Localized Global Ionospheric Map and Terrestrial GPS
NASA Astrophysics Data System (ADS)
Sharifi, Mohammad Ali; Farzaneh, Saeed
2016-02-01
Global ionosphere maps are generated on a daily basis at CODE using data from about 200 GPS/GLONASS sites of the IGS and other institutions. The vertical total electron content is modeled in a solar-geomagnetic reference frame using a spherical harmonics expansion up to degree and order 15. The spherical Slepian basis is a set of bandlimited functions which have the majority of their energy concentrated by optimization inside an arbitrarily defined region, yet remain orthogonal within the spatial region of interest. Hence, they are suitable for decomposing the spherical harmonic models into the portions that have significant strength only in the selected areas. In this study, the converted spherical harmonics to the Slepian bases were updated by the terrestrial GPS observations by use of the least-squares estimation with weighted parameters for local ionospheric modeling. Validations show that the approach adopted in this study is highly capable of yielding reliable results.
NASA Astrophysics Data System (ADS)
Verburg, P.; Eitelberg, D.; Ornetsmueller, C.; van Vliet, J.
2015-12-01
Global land use models are driven by demands for food and urban space. However, at the same time many transitions in land use and land cover are driven by societal changes and the demand for a wide range of landscape functions or ecosystem services, including the conservation of biodiversity, regulation of climate and floods, and recreation. Some of these demands lead to tele-connected land use change through the transport of good and services, others are place-based and shape the local realities of land system change. Most current land use change models focus on land cover changes alone and ignore the importance of changes in land management and landscape configuration that affect climate, biodiversity and the provisioning of ecosystem services. This talk will present an alternative approach to global land use modelling based on the simulation of changes in land systems in response to a wide set of ecosystem service demands. Simulations at global scale illustrate that accounting for demands for livestock products, carbon sequestration and biological conservation (following the Aichi targets) leads to different outcomes of land change models and allows the identification of synergies between carbon and biodiversity targets. An application in Laos indicates the complex transitions in land systems and landscapes that occur upon the transition from shifting cultivation to permanent agriculture and tree-crop plantations. We discuss the implications of such land system representations for Earth system modelling.
The Implications of the Local Context in Global Online Education
ERIC Educational Resources Information Center
Rye, Stale Angen; Stokken, Anne Marie
2012-01-01
This paper investigates how features in students' everyday life influence their participation in online global collaboration, and it suggests that students' local context should be recognised as a significant part of their educational space. In this exploratory case study of students engaged in a global online master's programme, the discussion is…
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" =…
Contextual Cueing in Naturalistic Scenes: Global and Local Contexts
ERIC Educational Resources Information Center
Brockmole, James R.; Castelhano, Monica S.; Henderson, John M.
2006-01-01
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…
Nonlinear Global Optimization Using Curdling Algorithm
Energy Science and Technology Software Center (ESTSC)
1996-03-01
An algorithm for performing curdling optimization which is a derivative-free, grid-refinement approach to nonlinear optimization was developed and implemented in software. This approach overcomes a number of deficiencies in existing approaches. Most notably, it finds extremal regions rather than only single external extremal points. The program is interactive and collects information on control parameters and constraints using menus. For up to four dimensions, function convergence is displayed graphically. Because the algorithm does not compute derivatives,more » gradients or vectors, it is numerically stable. It can find all the roots of a polynomial in one pass. It is an inherently parallel algorithm. Constraints are handled as being initially fuzzy, but become tighter with each iteration.« less
Neural network training with global optimization techniques.
Yamazaki, Akio; Ludermir, Teresa B
2003-04-01
This paper presents an approach of using Simulated Annealing and Tabu Search for the simultaneous optimization of neural network architectures and weights. The problem considered is the odor recognition in an artificial nose. Both methods have produced networks with high classification performance and low complexity. Generalization has been improved by using the backpropagation algorithm for fine tuning. The combination of simple and traditional search methods has shown to be very suitable for generating compact and efficient networks. PMID:12923920
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…
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…
Dispositional optimism and terminal decline in global quality of life.
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
2015-06-01
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 global QOL and optimism measure were analyzed. Growth curve models were examined. Competing models were contrasted using model fit criteria. On average, levels of global QOL decreased with both higher age and closer proximity to death (e.g., M(score) = 7.7 eight years prior to death vs. M(score) = 6.1 one year prior to death). A decline in global QOL was better modeled as a function of distance to death (DtD) than as a function of chronological age (Bayesian information criterion [BIC](DtD) = 22,964.8 vs. BIC(age) = 23,322.6). Optimism was a significant correlate of both linear (estimate(DtD) = -0.01, SE(DtD) = 0.005; ρ = 0.004) and quadratic (estimate(DtD) = -0.006, SE(DtD) = 0.002; ρ = 0.004) terminal decline in global QOL so that death-related decline in global QOL was steeper among those with a high level of optimism than those with a low level of optimism. We found that dispositional optimism helps to maintain positive psychological perspective in the face of age-related decline. Optimists maintain higher QOL compared with pessimists when death-related trajectories were considered; however, the gap between those with high optimism and those with low optimism progressively attenuated with closer proximity to death, to the point that is became nonsignificant at the time of death. PMID:25938553
From local to global changes in proteins: a network view.
Vuillon, Laurent; Lesieur, Claire
2015-04-01
To fulfill the biological activities in living organisms, proteins are endowed with dynamics, robustness and adaptability. The three properties co-exist because they allow global changes in structure to arise from local perturbations (dynamics). Robustness refers to the ability of the protein to incur such changes without suffering loss of function; adaptability is the emergence of a new biological activity. Since loss of function may jeopardize the survival of the organism and lead to disease, adaptability may occur through the combination of two local perturbations that together rescue the initial function. The review highlights the relevancy of computational network analysis to understand how a local change produces global changes. PMID:25791607
Global localization from monocular SLAM on a mobile phone.
Ventura, Jonathan; Arth, Clemens; Reitmayr, Gerhard; Schmalstieg, Dieter
2014-04-01
We propose the combination of a keyframe-based monocular SLAM system and a global localization method. The SLAM system runs locally on a camera-equipped mobile client and provides continuous, relative 6DoF pose estimation as well as keyframe images with computed camera locations. As the local map expands, a server process localizes the keyframes with a pre-made, globally-registered map and returns the global registration correction to the mobile client. The localization result is updated each time a keyframe is added, and observations of global anchor points are added to the client-side bundle adjustment process to further refine the SLAM map registration and limit drift. The end result is a 6DoF tracking and mapping system which provides globally registered tracking in real-time on a mobile device, overcomes the difficulties of localization with a narrow field-of-view mobile phone camera, and is not limited to tracking only in areas covered by the offline reconstruction. PMID:24650980
Local, Optimization-based Simplicial Mesh Smoothing
Energy Science and Technology Software Center (ESTSC)
1999-12-09
OPT-MS is a C software package for the improvement and untangling of simplicial meshes (triangles in 2D, tetrahedra in 3D). Overall mesh quality is improved by iterating over the mesh vertices and adjusting their position to optimize some measure of mesh quality, such as element angle or aspect ratio. Several solution techniques (including Laplacian smoothing, "Smart" Laplacian smoothing, optimization-based smoothing and several combinations thereof) and objective functions (for example, element angle, sin (angle), and aspectmore » ratio) are available to the user for both two and three-dimensional meshes. If the mesh contains invalid elements (those with negative area) a different optimization algorithm for mesh untangling is provided.« less
Geophysical Inversion With Multi-Objective Global Optimization Methods
NASA Astrophysics Data System (ADS)
Lelièvre, Peter; Bijani, Rodrigo; Farquharson, Colin
2016-04-01
We are investigating the use of Pareto multi-objective global optimization (PMOGO) methods to solve numerically complicated geophysical inverse problems. PMOGO methods can be applied to highly nonlinear inverse problems, to those where derivatives are discontinuous or simply not obtainable, and to those were multiple minima exist in the problem space. PMOGO methods generate a suite of solutions that minimize multiple objectives (e.g. data misfits and regularization terms) in a Pareto-optimal sense. This allows a more complete assessment of the possibilities and provides opportunities to calculate statistics regarding the likelihood of particular model features. We are applying PMOGO methods to four classes of inverse problems. The first are discrete-body problems where the inversion determines values of several parameters that define the location, orientation, size and physical properties of an anomalous body represented by a simple shape, for example a sphere, ellipsoid, cylinder or cuboid. A PMOGO approach can determine not only the optimal shape parameters for the anomalous body but also the optimal shape itself. Furthermore, when one expects several anomalous bodies in the subsurface, a PMOGO inversion approach can determine an optimal number of parameterized bodies. The second class of inverse problems are standard mesh-based problems where the physical property values in each cell are treated as continuous variables. The third class of problems are lithological inversions, which are also mesh-based but cells can only take discrete physical property values corresponding to known or assumed rock units. In the fourth class, surface geometry inversions, we consider a fundamentally different type of problem 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. Surface geometry inversion can be
Local and global contributions to hemodynamic activity in mouse cortex.
Pisauro, M Andrea; Benucci, Andrea; Carandini, Matteo
2016-06-01
Imaging techniques such as functional magnetic resonance imaging seek to estimate neural signals in local brain regions through measurements of hemodynamic activity. However, hemodynamic activity is accompanied by large vascular fluctuations of unclear significance. To characterize these fluctuations and their impact on estimates of neural signals, we used optical imaging in visual cortex of awake mice. We found that hemodynamic activity can be expressed as the sum of two components, one local and one global. The local component reflected presumed neural signals driven by visual stimuli in the appropriate retinotopic region. The global component constituted large fluctuations shared by larger cortical regions, which extend beyond visual cortex. These fluctuations varied from trial to trial, but they did not constitute noise; they correlated with pupil diameter, suggesting that they reflect variations in arousal or alertness. Distinguishing local and global contributions to hemodynamic activity may help understand neurovascular coupling and interpret measurements of hemodynamic responses. PMID:26984421
Local and global contributions to hemodynamic activity in mouse cortex
Pisauro, M. Andrea; Benucci, Andrea
2016-01-01
Imaging techniques such as functional magnetic resonance imaging seek to estimate neural signals in local brain regions through measurements of hemodynamic activity. However, hemodynamic activity is accompanied by large vascular fluctuations of unclear significance. To characterize these fluctuations and their impact on estimates of neural signals, we used optical imaging in visual cortex of awake mice. We found that hemodynamic activity can be expressed as the sum of two components, one local and one global. The local component reflected presumed neural signals driven by visual stimuli in the appropriate retinotopic region. The global component constituted large fluctuations shared by larger cortical regions, which extend beyond visual cortex. These fluctuations varied from trial to trial, but they did not constitute noise; they correlated with pupil diameter, suggesting that they reflect variations in arousal or alertness. Distinguishing local and global contributions to hemodynamic activity may help understand neurovascular coupling and interpret measurements of hemodynamic responses. PMID:26984421
Optimizing human activity patterns using global sensitivity analysis
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
Optimizing human activity patterns using global sensitivity analysis
Fairchild, Geoffrey; Hickmann, Kyle S.; Mniszewski, Susan M.; Del Valle, Sara Y.; Hyman, James 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 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. 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.
Optimal Object Localization Using Dual Number Quaternions
NASA Astrophysics Data System (ADS)
Walker, Michael W.; Shao, Lejun; Volz, Richard A.
1989-03-01
This paper presents a new algorithm for determining the position and orientation of objects. The problem is formulated as an optimization problem using dual number quaternions. It is shown that this reduces to an eigenvalue problem for which standard software library routines can be used to obtain the solution.
Nallasivam, Ulaganathan; Shah, Vishesh H.; Shenvi, Anirudh A.; Huff, Joshua; Tawarmalani, Mohit; Agrawal, Rakesh
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
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.
Communication: Optimal parameters for basin-hopping global optimization based on Tsallis statistics
Shang, C. Wales, D. J.
2014-08-21
A fundamental problem associated with global optimization is the large free energy barrier for the corresponding solid-solid phase transitions for systems with multi-funnel energy landscapes. To address this issue we consider the Tsallis weight instead of the Boltzmann weight to define the acceptance ratio for basin-hopping global optimization. Benchmarks for atomic clusters show that using the optimal Tsallis weight can improve the efficiency by roughly a factor of two. We present a theory that connects the optimal parameters for the Tsallis weighting, and demonstrate that the predictions are verified for each of the test cases.
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 and local music perception in children with Williams syndrome.
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. PMID:15812322
Emergence of global preferential attachment from local interaction
NASA Astrophysics Data System (ADS)
Li, Menghui; Gao, Liang; Fan, Ying; Wu, Jinshan; Di, Zengru
2010-04-01
Global degree/strength-based preferential attachment is widely used as an evolution mechanism of networks. But it is hard to believe that any individual can get global information and shape the network architecture based on it. In this paper, it is found that the global preferential attachment emerges from the local interaction models, including the distance-dependent preferential attachment (DDPA) evolving model of weighted networks (Li et al 2006 New J. Phys. 8 72), the acquaintance network model (Davidsen et al 2002 Phys. Rev. Lett. 88 128701) and the connecting nearest-neighbor (CNN) model (Vázquez 2003 Phys. Rev. E 67 056104). For the DDPA model and the CNN model, the attachment rate depends linearly on the degree or vertex strength, whereas for the acquaintance network model, the dependence follows a sublinear power law. It implies that for the evolution of social networks, local contact could be more fundamental than the presumed global preferential attachment.
Global search acceleration in the nested optimization scheme
NASA Astrophysics Data System (ADS)
Grishagin, Vladimir A.; Israfilov, Ruslan A.
2016-06-01
Multidimensional unconstrained global optimization problem with objective function under Lipschitz condition is considered. For solving this problem the dimensionality reduction approach on the base of the nested optimization scheme is used. This scheme reduces initial multidimensional problem to a family of one-dimensional subproblems being Lipschitzian as well and thus allows applying univariate methods for the execution of multidimensional optimization. For two well-known one-dimensional methods of Lipschitz optimization the modifications providing the acceleration of the search process in the situation when the objective function is continuously differentiable in a vicinity of the global minimum are considered and compared. Results of computational experiments on conventional test class of multiextremal functions confirm efficiency of the modified methods.
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.
Kiran, M; Nagarajaram, H A
2016-08-16
Hubs, the highly connected nodes in protein-protein interaction networks (PPINs), are associated with several characteristic properties and are known to perform vital roles in cells. We defined two classes of hubs, global (housekeeping) and local (tissue-specific) hubs. These two categories of hubs are distinct from each other with respect to their abundance, structure and function. However, how distinct are the spatial expression pattern and other characteristics of their interacting partners is still not known. Our investigations revealed that the partners of the local hubs compared with those of global hubs are conserved across the tissues in which they are expressed. Partners of local hubs show diverse subcellular localizations as compared with the partners of global hubs. We examined the nature of interacting domains in both categories of hubs and found that they are promiscuous in global hubs but not so in local hubs. Deletion of some of the local and global hubs has an impact on the characteristic path length of the network indicating that those hubs are inter-modular in nature. Our present study has, therefore, shed further light on the characteristic features of the local and global hubs in human PPIN. This knowledge of different topological aspects of hubs with regard to their types and subtypes is essential as it helps in better understanding of roles of hub proteins in various cellular processes under various conditions including those caused by host-pathogen interactions and therefore useful in prioritizing targets for drug design and repositioning. PMID:27400769
Optimizing human activity patterns using global sensitivity analysis
Fairchild, Geoffrey; Hickmann, Kyle S.; Mniszewski, Susan M.; Del Valle, Sara Y.; Hyman, James 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
Managing for interactions between local and global stressors of ecosystems.
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. PMID:23776542
Combined discriminative global and generative local models for visual tracking
NASA Astrophysics Data System (ADS)
Zhao, Liujun; Zhao, Qingjie; Chen, Yanming; Lv, Peng
2016-03-01
It is a challenging task to develop an effective visual tracking algorithm due to factors such as pose variation, rotation, and so on. Combined discriminative global and generative local appearance models are proposed to address this problem. Specifically, we develop a compact global object representation by extracting the low-frequency coefficients of the color and texture of the object based on two-dimensional discrete cosine transform. Then, with the global appearance representation, we learn a discriminative metric classifier in an online fashion to differentiate the target object from its background, which is very important to robustly indicate the changes in appearance. Second, we develop a new generative local model that exploits the scale invariant feature transform and its spatial geometric information. To make use of the advantages of the global discriminative model and the generative local model, we incorporate them into Bayesian inference framework. In this framework, the complementary models help the tracker locate the target more accurately. Furthermore, we use different mechanisms to update global and local templates to capture appearance changes. The experimental results demonstrate that the proposed approach performs favorably against state-of-the-art methods in terms of accuracy.
NASA Astrophysics Data System (ADS)
Yang, Dixiong; Liu, Zhenjun; Zhou, Jilei
2014-04-01
Chaos optimization algorithms (COAs) usually utilize the chaotic map like Logistic map to generate the pseudo-random numbers mapped as the design variables for global optimization. Many existing researches indicated that COA can more easily escape from the local minima than classical stochastic optimization algorithms. This paper reveals the inherent mechanism of high efficiency and superior performance of COA, from a new perspective of both the probability distribution property and search speed of chaotic sequences generated by different chaotic maps. The statistical property and search speed of chaotic sequences are represented by the probability density function (PDF) and the Lyapunov exponent, respectively. Meanwhile, the computational performances of hybrid chaos-BFGS algorithms based on eight one-dimensional chaotic maps with different PDF and Lyapunov exponents are compared, in which BFGS is a quasi-Newton method for local optimization. Moreover, several multimodal benchmark examples illustrate that, the probability distribution property and search speed of chaotic sequences from different chaotic maps significantly affect the global searching capability and optimization efficiency of COA. To achieve the high efficiency of COA, it is recommended to adopt the appropriate chaotic map generating the desired chaotic sequences with uniform or nearly uniform probability distribution and large Lyapunov exponent.
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. PMID:27057157
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. PMID:27057157
The study to enhance the mask global CD uniformity by removing local CD variation
NASA Astrophysics Data System (ADS)
Choi, Yongkyoo; Kim, Munsik; Han, Oscar
2007-03-01
As pattern size is shrinking, required mask CD specification is tighter and its effect on wafer patterning is more severe. Recent study showed that the effect of mask local CD variation of mask on wafer is much smaller than that of global CD variation.[1] To enhance the device performance, wafer CD uniformity should be enhanced and controlled by mask global CD uniformity. Mask global CD uniformity usually can be enhanced by mask process and optimal fogging effect correction. To enhance the mask global CD uniformity on mask, resist process and FEC (Fogging Effect Correction), reliable CD measurement tool and methods are necessary. Recently, group CD using OCD(Spectroscopic Ellipsometer) or AIMS(Aerial Image Measurement and Simulation) or polynomial fitting method is introduced to represent global CD variation on mask.[2][3][4] These methods are removing local CD variation on mask. The local CD variation will be remained as residual CD after approximation. In this paper, local CD variation of mask and wafer is evaluated and 2 kinds of methods are used to measure CD on mask and wafer, and the correlation of global CD of mask and field CD of wafer are evaluated. And the repeatability of field to field CD uniformity of wafer is evaluated to correct the fields CD uniformity of wafer by controlling the selective changing of transmittance of mask or to feed back to mask process. Higher correlation between fields of wafer, more accurate correction can be possible.
Motion Estimation for Dynamic Texture Videos Based on Locally and Globally Varying Models.
Sakaino, Hidetomo
2015-11-01
Motion estimation, i.e., optical flow, of fluid-like and dynamic texture (DT) images/videos is an important challenge, particularly for understanding outdoor scene changes created by objects and/or natural phenomena. Most optical flow models use smoothness-based constraints using terms such as fluidity from the fluid dynamics framework, with constraints typically being incompressibility and low Reynolds numbers (Re ). Such constraints are assumed to impede the clear capture of locally abrupt image intensity and motion changes, i.e., discontinuities and/or high Re over time. This paper exploits novel physics-based optical flow models/constraints for both smooth and discontinuous changes using a wave generation theory that imposes no constraint on Re or compressibility of an image sequence. Iterated two-step optimization between local and global optimization is also used: first, an objective function with varying multiple sine/cosine bases with new local image properties, i.e., orientation and frequency, and with a novel transformed dispersion relationship equation are used. Second, the statistical property of image features is used to globally optimize model parameters. Experiments on synthetic and real DT image sequences with smooth and discontinuous motions demonstrate that the proposed locally and globally varying models outperform the previous optical flow models. PMID:26099146
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.
A global optimization paradigm based on change of measures.
Sarkar, Saikat; Roy, Debasish; Vasu, Ram Mohan
2015-07-01
A global optimization framework, COMBEO (Change Of Measure Based Evolutionary Optimization), is proposed. An important aspect in the development is a set of derivative-free additive directional terms, obtainable through a change of measures en route to the imposition of any stipulated conditions aimed at driving the realized design variables (particles) to the global optimum. The generalized setting offered by the new approach also enables several basic ideas, used with other global search methods such as the particle swarm or the differential evolution, to be rationally incorporated in the proposed set-up via a change of measures. The global search may be further aided by imparting to the directional update terms additional layers of random perturbations such as 'scrambling' and 'selection'. Depending on the precise choice of the optimality conditions and the extent of random perturbation, the search can be readily rendered either greedy or more exploratory. As numerically demonstrated, the new proposal appears to provide for a more rational, more accurate and, in some cases, a faster alternative to many available evolutionary optimization schemes. PMID:26587268
Simple proof of the global optimality of the Hohmann transfer
NASA Technical Reports Server (NTRS)
Prussing, John E.
1992-01-01
The case of two-impulse transfer between coplanar circular orbits is considered. The global optimality of the Hohmann transfer among the class of two-impulse transfers is proved via ordinary calculus by using the familiar orbital elements, eccentricity e and parameter (semilatus rectum) p. It is noted that this proof is simpler than existing proofs in the literature.
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.
A global optimization paradigm based on change of measures
Sarkar, Saikat; Roy, Debasish; Vasu, Ram Mohan
2015-01-01
A global optimization framework, COMBEO (Change Of Measure Based Evolutionary Optimization), is proposed. An important aspect in the development is a set of derivative-free additive directional terms, obtainable through a change of measures en route to the imposition of any stipulated conditions aimed at driving the realized design variables (particles) to the global optimum. The generalized setting offered by the new approach also enables several basic ideas, used with other global search methods such as the particle swarm or the differential evolution, to be rationally incorporated in the proposed set-up via a change of measures. The global search may be further aided by imparting to the directional update terms additional layers of random perturbations such as ‘scrambling’ and ‘selection’. Depending on the precise choice of the optimality conditions and the extent of random perturbation, the search can be readily rendered either greedy or more exploratory. As numerically demonstrated, the new proposal appears to provide for a more rational, more accurate and, in some cases, a faster alternative to many available evolutionary optimization schemes. PMID:26587268
Global processing takes time: A meta-analysis on local-global visual processing in ASD.
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. PMID:25420221
Improved Particle Swarm Optimization for Global Optimization of Unimodal and Multimodal Functions
NASA Astrophysics Data System (ADS)
Basu, Mousumi
2015-07-01
Particle swarm optimization (PSO) performs well for small dimensional and less complicated problems but fails to locate global minima for complex multi-minima functions. This paper proposes an improved particle swarm optimization (IPSO) which introduces Gaussian random variables in velocity term. This improves search efficiency and guarantees a high probability of obtaining the global optimum without significantly impairing the speed of convergence and the simplicity of the structure of particle swarm optimization. The algorithm is experimentally validated on 17 benchmark functions and the results demonstrate good performance of the IPSO in solving unimodal and multimodal problems. Its high performance is verified by comparing with two popular PSO variants.
Efficient algorithms for multidimensional global optimization in genetic mapping of complex traits
Ljungberg, Kajsa; Mishchenko, Kateryna; Holmgren, Sverker
2010-01-01
We present a two-phase strategy for optimizing a multidimensional, nonconvex function arising during genetic mapping of quantitative traits. Such traits are believed to be affected by multiple so called quantitative trait loci (QTL), and searching for d QTL results in a d-dimensional optimization problem with a large number of local optima. We combine the global algorithm DIRECT with a number of local optimization methods that accelerate the final convergence, and adapt the algorithms to problem-specific features. We also improve the evaluation of the QTL mapping objective function to enable exploitation of the smoothness properties of the optimization landscape. Our best two-phase method is demonstrated to be accurate in at least six dimensions and up to ten times faster than currently used QTL mapping algorithms. PMID:21918629
Global equilibrium and local thermodynamics in stationary spacetimes
NASA Astrophysics Data System (ADS)
Panerai, Rodolfo
2016-05-01
In stationary spacetimes global equilibrium states can be defined, applying the maximum entropy principle, by the introduction of local thermodynamic fields determined solely by geometry. As an example, we study a class of equilibrium states for a scalar field in Einstein's static universe, characterized by inhomogeneous thermodynamic properties and nonvanishing angular momentum.
Designing for Local and Global Meanings of Randomness
ERIC Educational Resources Information Center
Paparistodemou, Efi; Noss, Richard
2004-01-01
This research aims to study the ways in which "local" events of randomness, based on experiencing the outcome of individual events, can be developed into "global" understandings that focus on an aggregated view of probability (e.g. probability of an event). The findings reported in the paper are part of a broader study that adopted a strategy of…
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 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 previously…
Factors Affecting the Comprehension of Global and Local Main Idea
ERIC Educational Resources Information Center
Wang, Danhua
2009-01-01
This study investigated factors that would affect a reader's understanding of the main idea at the global level and explicit and implicit main ideas at the local level. Fifty-seven first-year university students taking a college reading course took a comprehension test on an expository text. Statistical analyses revealed that text structure had a…
Global and Local Sensitivity Analysis Methods for a Physical System
ERIC Educational Resources Information Center
Morio, Jerome
2011-01-01
Sensitivity analysis is the study of how the different input variations of a mathematical model influence the variability of its output. In this paper, we review the principle of global and local sensitivity analyses of a complex black-box system. A simulated case of application is given at the end of this paper to compare both approaches.…
WATER CONSERVATION: LOCAL SOLUTIONS TO A GLOBAL PROBLEM
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...
Global/local finite element analysis for textile composites
NASA Technical Reports Server (NTRS)
Woo, Kyeongsik; Whitcomb, John
1993-01-01
Conventional analysis of textile composites is impractical because of the complex microstructure. Global/local methodology combined with special macro elements is proposed herein as a practical alternative. Initial tests showed dramatic reductions in the computational effort with only small loss in accuracy.
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…
ICCE/ICCAI 2000 Full & Short Papers (Globalization vs. Localization).
ERIC Educational Resources Information Center
2000
This document contains two papers on globalization versus localization from ICCE/ICCAI 2000 (International Conference on Computers in Education/International Conference on Computer-Assisted Instruction). The first paper, "Implementing Modern Approaches to Teaching Computer Science: A Cross-Cultural Perspective" (Jill Slay and Kam W. Li), examines…
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. PMID:24929345
Obstetricians’ Opinions of the Optimal Caesarean Rate: A Global Survey
Cavallaro, Francesca L.; Cresswell, Jenny A.; Ronsmans, Carine
2016-01-01
Background The debate surrounding the optimal caesarean rate has been ongoing for several decades, with the WHO recommending an “acceptable” rate of 5–15% since 1997, despite a weak evidence base. Global expert opinion from obstetric care providers on the optimal caesarean rate has not been documented. The objective of this study was to examine providers’ opinions of the optimal caesarean rate worldwide, among all deliveries and within specific sub-groups of deliveries. Methods A global online survey of medical doctors who had performed at least one caesarean in the last five years was conducted between August 2013 and January 2014. Respondents were asked to report their opinion of the optimal caesarean rate—defined as the caesarean rate that would minimise poor maternal and perinatal outcomes—at the population level and within specific sub-groups of deliveries (including women with demographic and clinical risk factors for caesareans). Median reported optimal rates and corresponding inter-quartile ranges (IQRs) were calculated for the sample, and stratified according to national caesarean rate, institutional caesarean rate, facility level, and respondent characteristics. Results Responses were collected from 1,057 medical doctors from 96 countries. The median reported optimal caesarean rate was 20% (IQR: 15–30%) for all deliveries. Providers in private for-profit facilities and in facilities with high institutional rates reported optimal rates of 30% or above, while those in Europe, in public facilities and in facilities with low institutional rates reported rates of 15% or less. Reported optimal rates were lowest among low-risk deliveries and highest for Absolute Maternal Indications (AMIs), with wide IQRs observed for most categories other than AMIs. Conclusions Three-quarters of respondents reported an optimal caesarean rate above the WHO 15% upper threshold. There was substantial variation in responses, highlighting a lack of consensus around
Electronic-structure calculation for metals by local optimization
Woodward, C.; Min, B.I.; Benedek, R.; Garner, J.
1989-03-15
Recent work by Car and Parrinello has generated considerable interest in the calculation of electronic structure by nonlinear optimization. The technique introduced by these authors, dynamical simulated annealing, is designed for problems that involve energy barriers. When local optimization suffices to determine the energy minimum, more direct methods are available. In this paper we apply the algorithm suggested by Williams and Soler to calculate the electronic structure of metals, using a plane-wave expansion for the electronic orbitals and an electron-ion pseudopotential of the Kleinman-Bylander form. Radial pseudopotentials were taken from the compilation of Bachelet, Hamann, and Schlueter. Calculations are performed to optimize the electronic structure (i) with fixed atomic configuration, or (ii) with the atomic volume being optimized simultaneously. It is found that the dual optimization (ii) converges in essentially the same number of steps as the static lattice optimization (i). Numerical results are presented for Li, K, Al, and simple-cubic P.
Hybrid methods using genetic algorithms for global optimization.
Renders, J M; Flasse, S P
1996-01-01
This paper discusses the trade-off between accuracy, reliability and computing time in global optimization. Particular compromises provided by traditional methods (Quasi-Newton and Nelder-Mead's simplex methods) and genetic algorithms are addressed and illustrated by a particular application in the field of nonlinear system identification. Subsequently, new hybrid methods are designed, combining principles from genetic algorithms and "hill-climbing" methods in order to find a better compromise to the trade-off. Inspired by biology and especially by the manner in which living beings adapt themselves to their environment, these hybrid methods involve two interwoven levels of optimization, namely evolution (genetic algorithms) and individual learning (Quasi-Newton), which cooperate in a global process of optimization. One of these hybrid methods appears to join the group of state-of-the-art global optimization methods: it combines the reliability properties of the genetic algorithms with the accuracy of Quasi-Newton method, while requiring a computation time only slightly higher than the latter. PMID:18263027
Global optimization in systems biology: stochastic methods and their applications.
Balsa-Canto, Eva; Banga, J R; Egea, J A; Fernandez-Villaverde, A; de Hijas-Liste, G M
2012-01-01
Mathematical optimization is at the core of many problems in systems biology: (1) as the underlying hypothesis for model development, (2) in model identification, or (3) in the computation of optimal stimulation procedures to synthetically achieve a desired biological behavior. These problems are usually formulated as nonlinear programing problems (NLPs) with dynamic and algebraic constraints. However the nonlinear and highly constrained nature of systems biology models, together with the usually large number of decision variables, can make their solution a daunting task, therefore calling for efficient and robust optimization techniques. Here, we present novel global optimization methods and software tools such as cooperative enhanced scatter search (eSS), AMIGO, or DOTcvpSB, and illustrate their possibilities in the context of modeling including model identification and stimulation design in systems biology. PMID:22161343
Globally Optimal Segmentation of Permanent-Magnet Systems
NASA Astrophysics Data System (ADS)
Insinga, A. R.; Bjørk, R.; Smith, A.; Bahl, C. R. H.
2016-06-01
Permanent-magnet systems are widely used for generation of magnetic fields with specific properties. The reciprocity theorem, an energy-equivalence principle in magnetostatics, can be employed to calculate the optimal remanent flux density of the permanent-magnet system, given any objective functional that is linear in the magnetic field. This approach, however, yields a continuously varying remanent flux density, while in practical applications, magnetic assemblies are realized by combining uniformly magnetized segments. The problem of determining the optimal shape of each of these segments remains unsolved. We show that the problem of optimal segmentation of a two-dimensional permanent-magnet assembly with respect to a linear objective functional can be reduced to the problem of piecewise linear approximation of a plane curve by perimeter maximization. Once the problem has been cast into this form, the globally optimal solution can be easily computed employing dynamic programming.
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)
Globally consistent registration of terrestrial laser scans via graph optimization
NASA Astrophysics Data System (ADS)
Theiler, Pascal Willy; Wegner, Jan Dirk; Schindler, Konrad
2015-11-01
In this paper we present a framework for the automatic registration of multiple terrestrial laser scans. The proposed method can handle arbitrary point clouds with reasonable pairwise overlap, without knowledge about their initial orientation and without the need for artificial markers or other specific objects. The framework is divided into a coarse and a fine registration part, which each start with pairwise registration and then enforce consistent global alignment across all scans. While we put forward a complete, functional registration system, the novel contribution of the paper lies in the coarse global alignment step. Merging multiple scans into a consistent network creates loops along which the relative transformations must add up. We pose the task of finding a global alignment as picking the best candidates from a set of putative pairwise registrations, such that they satisfy the loop constraints. This yields a discrete optimization problem that can be solved efficiently with modern combinatorial methods. Having found a coarse global alignment in this way, the framework proceeds by pairwise refinement with standard ICP, followed by global refinement to evenly spread the residual errors. The framework was tested on six challenging, real-world datasets. The discrete global alignment step effectively detects, removes and corrects failures of the pairwise registration procedure, finally producing a globally consistent coarse scan network which can be used as initial guess for the highly non-convex refinement. Our overall system reaches success rates close to 100% at acceptable runtimes < 1 h, even in challenging conditions such as scanning in the forest.
An adaptive metamodel-based global optimization algorithm for black-box type problems
NASA Astrophysics Data System (ADS)
Jie, Haoxiang; Wu, Yizhong; Ding, Jianwan
2015-11-01
In this article, an adaptive metamodel-based global optimization (AMGO) algorithm is presented to solve unconstrained black-box problems. In the AMGO algorithm, a type of hybrid model composed of kriging and augmented radial basis function (RBF) is used as the surrogate model. The weight factors of hybrid model are adaptively selected in the optimization process. To balance the local and global search, a sub-optimization problem is constructed during each iteration to determine the new iterative points. As numerical experiments, six standard two-dimensional test functions are selected to show the distributions of iterative points. The AMGO algorithm is also tested on seven well-known benchmark optimization problems and contrasted with three representative metamodel-based optimization methods: efficient global optimization (EGO), GutmannRBF and hybrid and adaptive metamodel (HAM). The test results demonstrate the efficiency and robustness of the proposed method. The AMGO algorithm is finally applied to the structural design of the import and export chamber of a cycloid gear pump, achieving satisfactory results.
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
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.
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.
Imperialist competitive algorithm combined with chaos for global optimization
NASA Astrophysics Data System (ADS)
Talatahari, S.; Farahmand Azar, B.; Sheikholeslami, R.; Gandomi, A. H.
2012-03-01
A novel chaotic improved imperialist competitive algorithm (CICA) is presented for global optimization. The ICA is a new meta-heuristic optimization developed based on a socio-politically motivated strategy and contains two main steps: the movement of the colonies and the imperialistic competition. Here different chaotic maps are utilized to improve the movement step of the algorithm. Seven different chaotic maps are investigated and the Logistic and Sinusoidal maps are found as the best choices. Comparing the new algorithm with the other ICA-based methods demonstrates the superiority of the CICA for the benchmark functions.
Global optimization using the y-ybar diagram
NASA Astrophysics Data System (ADS)
Brown, Daniel M.
1991-12-01
Software is under development at Teledyne Brown Engineering to represent a lens configuration as a y-ybar or Delano diagram. The program determines third-order Seidel and chromatic aberrations for each configuration. It performs a global search through all valid permutations of configuration space and determines, to within a step increment of the space, the configuration with smallest third-order aberrations. The program was developed to generate first-order optical layouts which promised to reach global minima during subsequent conventional optimization. Other operations allowed by the program are: add or delete surfaces, couple surfaces (for Mangin mirrors), shift the stop position, and display first-order properties and the optical layout (surface radii and thicknesses) for subsequent entry into a conventional lens-design program with automatic optimization. Algorithms for performing some of the key functions, not covered by previous authors, are discussed in this paper.
Geometrical optimization of a local ballistic magnetic sensor
Kanda, Yuhsuke; Hara, Masahiro; Nomura, Tatsuya; Kimura, Takashi
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.
Local origin of global contact numbers in frictional ellipsoid packings.
Schaller, Fabian M; Neudecker, Max; Saadatfar, Mohammad; Delaney, Gary W; Schröder-Turk, Gerd E; Schröter, Matthias
2015-04-17
In particulate soft matter systems the average number of contacts Z of a particle is an important predictor of the mechanical properties of the system. Using x-ray tomography, we analyze packings of frictional, oblate ellipsoids of various aspect ratios α, prepared at different global volume fractions ϕg. We find that Z is a monotonically increasing function of ϕg for all α. We demonstrate that this functional dependence can be explained by a local analysis where each particle is described by its local volume fraction ϕl computed from a Voronoi tessellation. Z can be expressed as an integral over all values of ϕl: Z(ϕg,α,X)=∫Zl(ϕl,α,X)P(ϕl|ϕg)dϕl. The local contact number function Zl(ϕl,α,X) describes the relevant physics in term of locally defined variables only, including possible higher order terms X. The conditional probability P(ϕl|ϕg) to find a specific value of ϕl given a global packing fraction ϕg is found to be independent of α and X. Our results demonstrate that for frictional particles a local approach is not only a theoretical requirement but also feasible. PMID:25933340
Local Origin of Global Contact Numbers in Frictional Ellipsoid Packings
NASA Astrophysics Data System (ADS)
Schaller, Fabian M.; Neudecker, Max; Saadatfar, Mohammad; Delaney, Gary W.; Schröder-Turk, Gerd E.; Schröter, Matthias
2015-04-01
In particulate soft matter systems the average number of contacts Z of a particle is an important predictor of the mechanical properties of the system. Using x-ray tomography, we analyze packings of frictional, oblate ellipsoids of various aspect ratios α , prepared at different global volume fractions ϕg. We find that Z is a monotonically increasing function of ϕg for all α . We demonstrate that this functional dependence can be explained by a local analysis where each particle is described by its local volume fraction ϕl computed from a Voronoi tessellation. Z can be expressed as an integral over all values of ϕl: Z (ϕg,α ,X )=∫Zl(ϕl,α ,X )P (ϕl|ϕg)d ϕl . The local contact number function Zl(ϕl,α ,X ) describes the relevant physics in term of locally defined variables only, including possible higher order terms X . The conditional probability P (ϕl|ϕg) to find a specific value of ϕl given a global packing fraction ϕg is found to be independent of α and X . Our results demonstrate that for frictional particles a local approach is not only a theoretical requirement but also feasible.
The local and global effects of African deforestation
NASA Astrophysics Data System (ADS)
Werth, David; Avissar, Roni
2005-06-01
Using a global climate model (GCM), we simulate the effects of the total deforestation of equatorial Africa, looking specifically at the local and remote precipitation changes caused by such a land-use change. We observe a strong local effect, with a large reduction in African precipitation during the dry season, and little change during either of the two rainy seasons. The effects of African deforestation extend throughout the Tropics and also reach into the midlatitudes. The remote effect is caused by the African geopotential changes being spread beyond the deforested area by the large-scale winds.
Global and Local Distortion Inference During Embedded Zerotree Wavelet Decompression
NASA Technical Reports Server (NTRS)
Huber, A. Kris; Budge, Scott E.
1996-01-01
This paper presents algorithms for inferring global and spatially local estimates of the squared-error distortion measures for the Embedded Zerotree Wavelet (EZW) image compression algorithm. All distortion estimates are obtained at the decoder without significantly compromising EZW's rate-distortion performance. Two methods are given for propagating distortion estimates from the wavelet domain to the spatial domain, thus giving individual estimates of distortion for each pixel of the decompressed image. These local distortion estimates seem to provide only slight improvement in the statistical characterization of EZW compression error relative to the global measure, unless actual squared errors are propagated. However, they provide qualitative information about the asymptotic nature of the error that may be helpful in wavelet filter selection for low bit rate applications.
Reconstruction of biofilm images: combining local and global structural parameters.
Resat, Haluk; Renslow, Ryan S; Beyenal, Haluk
2014-10-01
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 parameters 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. PMID:25377487
Emotional state and local versus global spatial memory.
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. PMID:19100525
Reconstruction of biofilm images: combining local and global structural parameters
Resat, Haluk; Renslow, Ryan S.; Beyenal, Haluk
2014-11-07
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 parameters 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.
Asynchronous global optimization techniques for medium and large inversion problems
Pereyra, V.; Koshy, M.; Meza, J.C.
1995-04-01
We discuss global optimization procedures adequate for seismic inversion problems. We explain how to save function evaluations (which may involve large scale ray tracing or other expensive operations) by creating a data base of information on what parts of parameter space have already been inspected. It is also shown how a correct parallel implementation using PVM speeds up the process almost linearly with respect to the number of processors, provided that the function evaluations are expensive enough to offset the communication overhead.
Optimization of cascade blade mistuning. II - Global optimum and numerical optimization
NASA Technical Reports Server (NTRS)
Nissim, E.; Haftka, R. T.
1985-01-01
The values of the mistuning which yield the most stable eigenvectors are analytically determined, using the simplified equations of motion which were developed in Part I of this work. It is shown that random mistunings, if large enough, may lead to the maximal stability, whereas the alternate mistunings cannot. The problem of obtaining maximum stability for minimal mistuning is formulated, based on numerical optimization techniques. Several local minima are obtained using different starting mistuning vectors. The starting vectors which lead to the global minimum are identified. It is analytically shown that all minima appear in multiplicities which are equal to the number of compressor blades. The effect of mistuning on the flutter speed is studied using both an optimum mistuning vector and an alternate mistuning vector. Effects of mistunings in elastic axis locations are shown to have a negligible effect on the eigenvalues. Finally, it is shown that any general two-dimensional bending-torsion system can be reduced to an equivalent uncoupled torsional system.
Lens Design: An Attempt to Use `Escape Function' as a Tool in Global Optimization
NASA Astrophysics Data System (ADS)
Isshiki, Masaki; Ono, Hiroki; Nakadate, Suezou
1995-01-01
In designing lenses with the damped least squares method, the solution obtained by optimization routine is a local minimum of the merit function. To get out of this and seek a different solution, we propose to use an ‘escape function’ as an additional operand of the lens system, to be controlled. Experiments were made on simple models of merit function and the advantage of this technique was ascertained. We also planted this algorithm into OSLO SIX (lens design software by Sinclair Optics) by means of CCL (C-compatible language) and applied it to actual lens design. Experiments convinced us that the method would be an effective tool for global optimization.
Learning Human Actions by Combining Global Dynamics and Local Appearance.
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. PMID:26353152
Hurricanes and Climate Change: Global Systems and Local Impacts
NASA Astrophysics Data System (ADS)
Santer, J.
2011-12-01
With funding from NOAA, the Miami Science Museum has been working with exhibit software developer Ideum to create an interactive exhibit exploring the global dimensions and local impacts of climate change. A particular focus is on climate-related impacts on coastal communities, including the potential effects on South Florida of ocean acidification, rising sea level, and the possibility of more intense hurricanes. The exhibit is using a 4-foot spherical display system in conjunction with a series of touchscreen kiosks and accompanying flat screens to create a user-controlled, multi-user interface that lets visitors control the sphere and choose from a range of global and local content they wish to explore. The exhibit has been designed to promote engagement of diverse, multigenerational audiences through development of a fully bilingual user interface that promotes social interaction and conversation among visitors as they trade off control of global content on the sphere and related local content on the flat screens. The open-source learning module will be adaptable by other museums, to explore climate impacts specific to their region.
Global and local obstacle avoidance technique for an autonomous vehicle
NASA Astrophysics Data System (ADS)
Gray, Keith W.; Saunders, Kevin S.
1999-07-01
The Center for Self-Organizing and Intelligent Systems (CSOIS) is engaged in developing autonomous ground vehicles. A significant problem for such vehicles is obstacle detection and avoidance. After studying various methods of detection, a scanning laser system was chosen that can detect objects at a distance of up to thirty feet while traveling between five and ten miles per hour. Once an object is detected, the vehicle must avoid it. The project employs a mission-level path planner that predetermines the path of a vehicle. One avoidance scheme is to inform the path planner of the obstacle and then let it re-plan the path. This is the global approach to the problem, which allows the use of existing software for maneuvering the vehicle. However, replanning is time consuming and lacks knowledge of the entire obstacle. An alternative approach is to use local avoidance, whereby a vehicle determines how to get by an obstacle without help from the path planner. This approach offers faster response without requiring the computing resource of the path planner. The disadvantage is that during local avoidance the vehicle ignores the global map of known obstacles and does not know to turn control back to the path planner if mission efficiency is adversely affected. This paper will describe a method for combining the current global path planner with a local obstacle avoidance technique to efficiently complete required tasks in a partially unknown environment.
A Localization Method for Multistatic SAR Based on Convex Optimization
2015-01-01
In traditional localization methods for Synthetic Aperture Radar (SAR), the bistatic range sum (BRS) estimation and Doppler centroid estimation (DCE) are needed for the calculation of target localization. However, the DCE error greatly influences the localization accuracy. In this paper, a localization method for multistatic SAR based on convex optimization without DCE is investigated and the influence of BRS estimation error on localization accuracy is analysed. Firstly, by using the information of each transmitter and receiver (T/R) pair and the target in SAR image, the model functions of T/R pairs are constructed. Each model function’s maximum is on the circumference of the ellipse which is the iso-range for its model function’s T/R pair. Secondly, the target function whose maximum is located at the position of the target is obtained by adding all model functions. Thirdly, the target function is optimized based on gradient descent method to obtain the position of the target. During the iteration process, principal component analysis is implemented to guarantee the accuracy of the method and improve the computational efficiency. The proposed method only utilizes BRSs of a target in several focused images from multistatic SAR. Therefore, compared with traditional localization methods for SAR, the proposed method greatly improves the localization accuracy. The effectivity of the localization approach is validated by simulation experiment. PMID:26566031
A Localization Method for Multistatic SAR Based on Convex Optimization.
Zhong, Xuqi; Wu, Junjie; Yang, Jianyu; Sun, Zhichao; Huang, Yuling; Li, Zhongyu
2015-01-01
In traditional localization methods for Synthetic Aperture Radar (SAR), the bistatic range sum (BRS) estimation and Doppler centroid estimation (DCE) are needed for the calculation of target localization. However, the DCE error greatly influences the localization accuracy. In this paper, a localization method for multistatic SAR based on convex optimization without DCE is investigated and the influence of BRS estimation error on localization accuracy is analysed. Firstly, by using the information of each transmitter and receiver (T/R) pair and the target in SAR image, the model functions of T/R pairs are constructed. Each model function's maximum is on the circumference of the ellipse which is the iso-range for its model function's T/R pair. Secondly, the target function whose maximum is located at the position of the target is obtained by adding all model functions. Thirdly, the target function is optimized based on gradient descent method to obtain the position of the target. During the iteration process, principal component analysis is implemented to guarantee the accuracy of the method and improve the computational efficiency. The proposed method only utilizes BRSs of a target in several focused images from multistatic SAR. Therefore, compared with traditional localization methods for SAR, the proposed method greatly improves the localization accuracy. The effectivity of the localization approach is validated by simulation experiment. PMID:26566031
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.
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.
Global and local curvature in density functional theory
NASA Astrophysics Data System (ADS)
Zhao, Qing; Ioannidis, Efthymios I.; Kulik, Heather J.
2016-08-01
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.
Global and local curvature in density functional theory.
Zhao, Qing; Ioannidis, Efthymios I; Kulik, Heather J
2016-08-01
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. PMID:27497541
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.
NASA Astrophysics Data System (ADS)
Shabbir, Faisal; Omenzetter, Piotr
2014-04-01
Much effort is devoted nowadays to derive accurate finite element (FE) models to be used for structural health monitoring, damage detection and assessment. However, formation of a FE model representative of the original structure is a difficult task. Model updating is a branch of optimization which calibrates the FE model by comparing the modal properties of the actual structure with these of the FE predictions. As the number of experimental measurements is usually much smaller than the number of uncertain parameters, and, consequently, not all uncertain parameters are selected for model updating, different local minima may exist in the solution space. Experimental noise further exacerbates the problem. The attainment of a global solution in a multi-dimensional search space is a challenging problem. Global optimization algorithms (GOAs) have received interest in the previous decade to solve this problem, but no GOA can ensure the detection of the global minimum either. To counter this problem, a combination of GOA with sequential niche technique (SNT) has been proposed in this research which systematically searches the whole solution space. A dynamically tested full scale pedestrian bridge is taken as a case study. Two different GOAs, namely particle swarm optimization (PSO) and genetic algorithm (GA), are investigated in combination with SNT. The results of these GOA are compared in terms of their efficiency in detecting global minima. The systematic search enables to find different solutions in the search space, thus increasing the confidence of finding the global minimum.
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.
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.
Local, Global or Globalized? Child Development and International Child Rights Legislation.
ERIC Educational Resources Information Center
Burman, Erica
1996-01-01
Analyzes three conceptions of children's rights and explores the tensions between them as realized in the U.N. Convention on the Rights of the Child and the development of the "best interest" principle. Advocates reconceptualization of the debate to see local perspectives as functioning in relation to--rather than opposed to--global ones, thus…
Wu, Zong-Sheng; Fu, Wei-Ping; Xue, Ru
2015-01-01
Teaching-learning-based optimization (TLBO) algorithm is proposed in recent years that simulates the teaching-learning phenomenon of a classroom to effectively solve global optimization of multidimensional, linear, and nonlinear problems over continuous spaces. In this paper, an improved teaching-learning-based optimization algorithm is presented, which is called nonlinear inertia weighted teaching-learning-based optimization (NIWTLBO) algorithm. This algorithm introduces a nonlinear inertia weighted factor into the basic TLBO to control the memory rate of learners and uses a dynamic inertia weighted factor to replace the original random number in teacher phase and learner phase. The proposed algorithm is tested on a number of benchmark functions, and its performance comparisons are provided against the basic TLBO and some other well-known optimization algorithms. The experiment results show that the proposed algorithm has a faster convergence rate and better performance than the basic TLBO and some other algorithms as well. PMID:26421005
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.
Global versus local effects on climate change in Asia
NASA Astrophysics Data System (ADS)
Paeth, Heiko; Müller, Markus; Mannig, Birgit
2015-10-01
Regional climate change arises from two processes which, in the real climate system, cannot be separated from each other: local radiative forcing and advection of air masses from regions which themselves have been subject to climate change. In this study, we present an experimental design based on a regional climate model allowing for the assessment of global and local effects on future climate change in Asia. We carry out two runs which are characterized by increasing greenhouse gas concentrations within the model domain, but one (the control run) is one-way nested into a global control run at the lateral and oceanic boundaries while the other (the forced run) is one-way nested into a consistently forced global simulation. The aim is to improve our understanding of the mechanisms of climate change in a regional context. It turns out that temperature and precipitation changes in Asia are indeed mostly related to changes in the advected air masses which enter along the lateral boundaries. Regionally confined greenhouse forcing only affects the atmospheric heating rate while precipitation and atmospheric circulation features remain more or less unchanged. Temperature changes in the forced experiment are partly governed by warmer air masses penetrating the lateral boundaries and partly by a modification of atmospheric circulation processes, including a tendency towards a double-trough structure over Central Asia and changing temperature advection. The trend pattern of precipitation is much more heterogeneous in space but can partly be attributed to changes in horizontal wind divergence and vertical velocity.
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.
Global effects of land use on local terrestrial biodiversity.
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. PMID:25832402
Global structual optimizations of surface systems with a genetic algorithm
Chuang, Feng-Chuan
2005-05-01
Global structural optimizations with a genetic algorithm were performed for atomic cluster and surface systems including aluminum atomic clusters, Si magic clusters on the Si(111) 7 x 7 surface, silicon high-index surfaces, and Ag-induced Si(111) reconstructions. First, the global structural optimizations of neutral aluminum clusters Al{sub n} (n up to 23) were performed using a genetic algorithm coupled with a tight-binding potential. Second, a genetic algorithm in combination with tight-binding and first-principles calculations were performed to study the structures of magic clusters on the Si(111) 7 x 7 surface. Extensive calculations show that the magic cluster observed in scanning tunneling microscopy (STM) experiments consist of eight Si atoms. Simulated STM images of the Si magic cluster exhibit a ring-like feature similar to STM experiments. Third, a genetic algorithm coupled with a highly optimized empirical potential were used to determine the lowest energy structure of high-index semiconductor surfaces. The lowest energy structures of Si(105) and Si(114) were determined successfully. The results of Si(105) and Si(114) are reported within the framework of highly optimized empirical potential and first-principles calculations. Finally, a genetic algorithm coupled with Si and Ag tight-binding potentials were used to search for Ag-induced Si(111) reconstructions at various Ag and Si coverages. The optimized structural models of {radical}3 x {radical}3, 3 x 1, and 5 x 2 phases were reported using first-principles calculations. A novel model is found to have lower surface energy than the proposed double-honeycomb chained (DHC) model both for Au/Si(111) 5 x 2 and Ag/Si(111) 5 x 2 systems.
A global optimization approach to multi-polarity sentiment analysis.
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
A Global Optimization Approach to Multi-Polarity Sentiment Analysis
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
On Vertically Global, Horizontally Local Models for Astrophysical Disks
NASA Astrophysics Data System (ADS)
McNally, Colin P.; Pessah, Martin E.
2015-10-01
Disks with a barotropic equilibrium structure, for which the pressure is only a function of the density, rotate on cylinders in the presence of a gravitational potential, so that the angular frequency of such a disk is independent of height. Such disks with barotropic equilibria can be approximately modeled using the shearing box framework, representing a small disk volume with height-independent angular frequency. If the disk is in baroclinic equilibrium, the angular frequency does generally depend on height, and it is thus necessary to go beyond the standard shearing box approach. In this paper, we show that given a global disk model, it is possible to develop approximate models that are local in horizontal planes without an expansion in height with shearing-periodic boundary conditions. We refer to the resulting framework as the vertically global shearing box (VGSB). These models can be non-axisymmetric for globally barotropic equilibria but should be axisymmetric for globally baroclinic equilibria. We provide explicit equations for this VGSB which can be implemented in standard magnetohydrodynamic codes by generalizing the shearing-periodic boundary conditions to allow for a height-dependent angular frequency and shear rate. We also discuss the limitations that result from the radial approximations that are needed in order to impose height-dependent shearing periodic boundary conditions. We illustrate the potential of this framework by studying a vertical shear instability and examining the modes associated with the magnetorotational instability.
Competition between global and local online social networks.
Kleineberg, Kaj-Kolja; Boguñá, Marián
2016-01-01
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. PMID:27117826
Competition between global and local online social networks
Kleineberg, Kaj-Kolja; Boguñá, Marián
2016-01-01
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. PMID:27117826
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.
Effects of local and global network connectivity on synergistic epidemics
NASA Astrophysics Data System (ADS)
Broder-Rodgers, David; Pérez-Reche, Francisco J.; Taraskin, Sergei N.
2015-12-01
Epidemics in networks can be affected by cooperation in transmission of infection and also connectivity between nodes. An interplay between these two properties and their influence on epidemic spread are addressed in the paper. A particular type of cooperative effects (called synergy effects) is considered, where the transmission rate between a pair of nodes depends on the number of infected neighbors. The connectivity effects are studied by constructing networks of different topology, starting with lattices with only local connectivity and then with networks that have both local and global connectivity obtained by random bond-rewiring to nodes within a certain distance. The susceptible-infected-removed epidemics were found to exhibit several interesting effects: (i) for epidemics with strong constructive synergy spreading in networks with high local connectivity, the bond rewiring has a negative role in epidemic spread, i.e., it reduces invasion probability; (ii) in contrast, for epidemics with destructive or weak constructive synergy spreading on networks of arbitrary local connectivity, rewiring helps epidemics to spread; (iii) and, finally, rewiring always enhances the spread of epidemics, independent of synergy, if the local connectivity is low.
A global/local affinity graph for image segmentation.
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
Solving Globally-Optimal Threading Problems in ''Polynomial-Time''
Uberbacher, E.C.; Xu, D.; Xu, Y.
1999-04-12
Computational protein threading is a powerful technique for recognizing native-like folds of a protein sequence from a protein fold database. In this paper, we present an improved algorithm (over our previous work) for solving the globally-optimal threading problem, and illustrate how the computational complexity and the fold recognition accuracy of the algorithm change as the cutoff distance for pairwise interactions changes. For a given fold of m residues and M core secondary structures (or simply cores) and a protein sequence of n residues, the algorithm guarantees to find a sequence-fold alignment (threading) that is globally optimal, measured collectively by (1) the singleton match fitness, (2) pairwise interaction preference, and (3) alignment gap penalties, in O(mn + MnN{sup 1.5C-1}) time and O(mn + nN{sup C-1}) space. C, the topological complexity of a fold as we term, is a value which characterizes the overall structure of the considered pairwise interactions in the fold, which are typically determined by a specified cutoff distance between the beta carbon atoms of a pair of amino acids in the fold. C is typically a small positive integer. N represents the maximum number of possible alignments between an individual core of the fold and the protein sequence when its neighboring cores are already aligned, and its value is significantly less than n. When interacting amino acids are required to see each other, C is bounded from above by a small integer no matter how large the cutoff distance is. This indicates that the protein threading problem is polynomial-time solvable if the condition of seeing each other between interacting amino acids is sufficient for accurate fold recognition. A number of extensions have been made to our basic threading algorithm to allow finding a globally-optimal threading under various constraints, which include consistencies with (1) specified secondary structures (both cores and loops), (2) disulfide bonds, (3) active sites, etc.
PROSPECT: A Computer System for Globally-Optimal Threading
Xu, D.; Xu, Y.
1999-08-06
This paper presents a new computer system, PROSPECT, for protein threading. PROSPECT employs an energy function that consists of three additive terms: (1) a singleton fitness term, (2) a distance-dependent pairwise-interaction preference term, and (3) alignment gap penalty; and currently uses FSSP as its threading template database. PROSPECT uses a divide-and-conquer algorithm to find an alignment between a query protein sequence and a protein fold template, which is guaranteed to be globally optimal for its energy function. The threading algorithm presented here significantly improves the computational efficiency of our previously-published algorithm, which makes PROSPECT a practical tool even for large protein threading problems. Mathematically, PROSPECT finds a globally-optimal threading between a query sequence of n residues and a fold template of m residues and M core secondary structures in O(nm + MnN{sup 1.5C{minus}1}) time and O(nm + nN{sup C{minus}1}) space, where C, the topological complexity of the template fold as we term, is a value which characterizes the overall structure of the considered pairwise interactions in the fold; and N represents the maximum number of possible alignments between an individual core of the fold and the query sequence when its neighboring cores are already aligned. PROSPECT allows a user to incorporate known biological constraints about the query sequence during the threading process. For given constraints, the system finds a globally-optimal threading which satisfies the constraints. Currently PROSPECT can deal with constraints which reflect geometrical relationships among residues of disulfide bonds, active sites, or determined by the NOE constraints of (low-resolution) NMR spectral data.
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.
An Adaptive Unified Differential Evolution Algorithm for Global Optimization
Qiang, Ji; Mitchell, Chad
2014-11-03
In this paper, we propose a new adaptive unified differential evolution algorithm for single-objective global optimization. Instead of the multiple mutation strate- gies proposed in conventional differential evolution algorithms, this algorithm employs a single equation unifying multiple strategies into one expression. It has the virtue of mathematical simplicity and also provides users the flexibility for broader exploration of the space of mutation operators. By making all control parameters in the proposed algorithm self-adaptively evolve during the process of optimization, it frees the application users from the burden of choosing appro- priate control parameters and also improves the performance of the algorithm. In numerical tests using thirteen basic unimodal and multimodal functions, the proposed adaptive unified algorithm shows promising performance in compari- son to several conventional differential evolution algorithms.
A Unified Differential Evolution Algorithm for Global Optimization
Qiang, Ji; Mitchell, Chad
2014-06-24
Abstract?In this paper, we propose a new unified differential evolution (uDE) algorithm for single objective global optimization. Instead of selecting among multiple mutation strategies as in the conventional differential evolution algorithm, this algorithm employs a single equation as the mutation strategy. It has the virtue of mathematical simplicity and also provides users the flexbility for broader exploration of different mutation strategies. Numerical tests using twelve basic unimodal and multimodal functions show promising performance of the proposed algorithm in comparison to convential differential evolution algorithms.
Local versus global scales of organization in auditory cortex.
Kanold, Patrick O; Nelken, Israel; Polley, Daniel B
2014-09-01
Topographic organization is a hallmark of sensory cortical organization. Topography is robust at spatial scales ranging from hundreds of microns to centimeters, but can dissolve at the level of neighboring neurons or subcellular compartments within a neuron. This dichotomous spatial organization is especially pronounced in the mouse auditory cortex, where an orderly tonotopic map can arise from heterogeneous frequency tuning between local neurons. Here, we address a debate surrounding the robustness of tonotopic organization in the auditory cortex that has persisted in some form for over 40 years. Drawing from various cortical areas, cortical layers, recording methodologies, and species, we describe how auditory cortical circuitry can simultaneously support a globally systematic, yet locally heterogeneous representation of this fundamental sound property. PMID:25002236
Local versus global scales of organization in auditory cortex
Kanold, Patrick O.; Nelken, Israel; Polley, Daniel B.
2014-01-01
Topographic organization is a hallmark of sensory cortical organization. Topography is robust at spatial scales ranging from hundreds of microns to centimeters, but can dissolve at the level of neighboring neurons or subcellular compartments within a neuron. This dichotomous spatial organization is especially pronounced in the mouse auditory cortex, where an orderly tonotopic map can arise from heterogeneous frequency tuning between local neurons. Here, we address a debate surrounding the robustness of tonotopic organization in the auditory cortex that has persisted in some form for over forty years. Drawing from various cortical areas, cortical layers, recording methodologies, and species, we describe how auditory cortical circuitry can simultaneously support a globally systematic, yet locally heterogeneous representation of this fundamental sound property. PMID:25002236
Optimal allocation of file servers in a local network environment
NASA Technical Reports Server (NTRS)
Woodside, C. M.; Tripathi, S. K.
1986-01-01
Files associated with workstations in a local area network are to be allocated among two or more file servers. Assuming statistically identical workstations and file servers and a performance model which is a closed multiclass separable queueing network, an optimal allocation is found. It is shown that all the files of each workstation should be placed on one file server, with the workstations divided as equally as possible among the file servers.
Protein tertiary structure recognition using optimized Hamiltonians with local interactions.
Goldstein, R A; Luthey-Schulten, Z A; Wolynes, P G
1992-01-01
Protein folding codes embodying local interactions including surface and secondary structure propensities and residue-residue contacts are optimized for a set of training proteins by using spin-glass theory. A screening method based on these codes correctly matches the structure of a set of test proteins with proteins of similar topology with 100% accuracy, even with limited sequence similarity between the test proteins and the structural homologs and the absence of any structurally similar proteins in the training set. PMID:1409599
Local to global avalanches in sheared granular materials
NASA Astrophysics Data System (ADS)
Weng, Dengming; Wang, Dong; Bertrand, Thibault; Bares, Jonathan; Berhinger, Bob
2015-11-01
Commonly, granular materials yield or flow if sufficiently large shear stress is applied, leading to avalanche-like behavior. Rearrangement phenomenon can produce dramatic events like snow avalanches, land-slides or earthquakes. For experimentally sheared media, we seek to understand the dynamics of the grain rearrangements from the local to the global scale. In this work, force networks and displacement fields are measured on two-dimensional sheared material for cyclically sheared photoelastic circular particles. Avalanches, their size, location and duration are extracted at the global scale from the rapid variation of the macroscopic energy stored in the system whereas at the local scale they are measured from the energy drop, displacement and rotation of each particle. Statistics of those different quantities are computed and correlated to test their intrinsic entanglement and analyze their universal dynamics. These results are quantitatively different from what has been observed for different analytic coarse-grained approaches and permit a clear measurement of the effect of the packing fraction and inter-particle friction coefficient on the statistical behavior.
Local and Global Limits on Visual Processing in Schizophrenia
Tibber, Marc S.; Anderson, Elaine J.; Bobin, Tracy; Carlin, Patricia; Shergill, Sukhwinder S.; Dakin, Steven C.
2015-01-01
Schizophrenia has been linked to impaired performance on a range of visual processing tasks (e.g. detection of coherent motion and contour detection). It has been proposed that this is due to a general inability to integrate visual information at a global level. To test this theory, we assessed the performance of people with schizophrenia on a battery of tasks designed to probe voluntary averaging in different visual domains. Twenty-three outpatients with schizophrenia (mean age: 40±8 years; 3 female) and 20 age-matched control participants (mean age 39±9 years; 3 female) performed a motion coherence task and three equivalent noise (averaging) tasks, the latter allowing independent quantification of local and global limits on visual processing of motion, orientation and size. All performance measures were indistinguishable between the two groups (ps>0.05, one-way ANCOVAs), with one exception: participants with schizophrenia pooled fewer estimates of local orientation than controls when estimating average orientation (p = 0.01, one-way ANCOVA). These data do not support the notion of a generalised visual integration deficit in schizophrenia. Instead, they suggest that distinct visual dimensions are differentially affected in schizophrenia, with a specific impairment in the integration of visual orientation information. PMID:25689281
Global, regional and local health impacts of civil aviation emissions
NASA Astrophysics Data System (ADS)
Yim, Steve H. L.; Lee, Gideon L.; Lee, In Hwan; Allroggen, Florian; Ashok, Akshay; Caiazzo, Fabio; Eastham, Sebastian D.; Malina, Robert; Barrett, Steven R. H.
2015-03-01
Aviation emissions impact surface air quality at multiple scales—from near-airport pollution peaks associated with airport landing and take off (LTO) emissions, to intercontinental pollution attributable to aircraft cruise emissions. Previous studies have quantified aviation’s air quality impacts around a specific airport, in a specific region, or at the global scale. However, no study has assessed the air quality and human health impacts of aviation, capturing effects on all aforementioned scales. This study uses a multi-scale modeling approach to quantify and monetize the air quality impact of civil aviation emissions, approximating effects of aircraft plume dynamics-related local dispersion (˜1 km), near-airport dispersion (˜10 km), regional (˜1000 km) and global (˜10 000 km) scale chemistry and transport. We use concentration-response functions to estimate premature deaths due to population exposure to aviation-attributable PM2.5 and ozone, finding that aviation emissions cause ˜16 000 (90% CI: 8300-24 000) premature deaths per year. Of these, LTO emissions contribute a quarter. Our estimate shows that premature deaths due to long-term exposure to aviation-attributable PM2.5 and O3 lead to costs of ˜21 bn per year. We compare these costs to other societal costs of aviation and find that they are on the same order of magnitude as global aviation-attributable climate costs, and one order of magnitude larger than aviation-attributable accident and noise costs.
Teaching global and local environmental change through Remote Sensing
NASA Astrophysics Data System (ADS)
Mauri, Emanuela Paola; Rossi, Giovanni
2013-04-01
Human beings perceive the world primarily through their sense of sight. This can explain why the use of images is so important and common in educational materials, in particular for scientific subjects. The development of modern technologies for visualizing the scientific features of the Earth has provided new opportunities for communicating the increasing complexity of science both to the public and in school education. In particular, the use of Earth observation satellites for civil purposes, which started in the 70s, has opened new perspectives in the study of natural phenomena and human impact on the environment; this is particularly relevant for those processes developing on a long term period and on a global scale. Instruments for Remote Sensing increase the power of human sight, giving access to additional information about the physical world, which the human eye could not otherwise perceive. The possibility to observe from a remote perspective significant processes like climate change, ozone depletion, desertification, urban development, makes it possible for observers to better appreciate and experience the complexity of environment. Remote Sensing reveals the impact of human activities on ecosystems: this allows students to understand important concepts like global and local change in much more depth. This poster describes the role and effectiveness of Remote Sensing imagery in scientific education, and its importance towards a better global environmental awareness.
The global potential of local peri-urban food production
NASA Astrophysics Data System (ADS)
Kriewald, Steffen; Garcia Cantu Ros, Anselmo; Sterzel, Till; Kropp, Jürgen P.
2013-04-01
One big challenge for the rest of the 21st century will be the massive urbanisation. It is expected that more than 7 out of 10 persons will live in a city by the year 2050. Crucial developments towards a sustainable future will therefore take place in cities. One important approach for a sustainable city development is to re-localize food production and to close urban nutrient cycles through better waste management. The re-location of food production avoids CO2 emissions from transportation of food to cities and can also generate income for inhabitants. Cities are by definition locations where fertility accumulates. As cities are often built along rivers, their soils are often fertile. Furthermore, labour force and the possibility of producing fertilizer from human fecal matter within the city promises sustainable nutrients cycles. Although urban and peri-urban agriculture can be found in many cities worldwide and already have a substantial contribution to food supply, it has not jet been comprehensibly structured by research. We combine several worldwide data sets to determine the supply of cities with regional food production, where regional is defined as a production that occurs very close to the consumption within the peri-urban area. Therefore, urban areas are not defined by administrative boundaries but by connected built-up urban areas, and peri-urban area by the surrounding area with the same size multiplied with a scaling parameter. Both together accumulate to an urban-bio-region (UBR). With regard to national food consumption, a linear program achieves the best possible yield on agricultural areas and allows the computation of the fraction of population, which can be nourished. Additionally, several climate scenarios and different dietary patterns were considered. To close the gap between single case studies and to provide a quantitative overview of the global potential of peri-urban food production we used high resolution land-use data Global Land Cover
Damage localization using experimental modal parameters and topology optimization
NASA Astrophysics Data System (ADS)
Niemann, Hanno; Morlier, Joseph; Shahdin, Amir; Gourinat, Yves
2010-04-01
This work focuses on the development of a damage detection and localization tool using the topology optimization feature of MSC.Nastran. This approach is based on the correlation of a local stiffness loss and the change in modal parameters due to damages in structures. The loss in stiffness is accounted by the topology optimization approach for updating undamaged numerical models towards similar models with embedded damages. Hereby, only a mass penalization and the changes in experimentally obtained modal parameters are used as objectives. The theoretical background for the implementation of this method is derived and programmed in a Nastran input file and the general feasibility of the approach is validated numerically, as well as experimentally by updating a model of an experimentally tested composite laminate specimen. The damages have been introduced to the specimen by controlled low energy impacts and high quality vibration tests have been conducted on the specimen for different levels of damage. These supervised experiments allow to test the numerical diagnosis tool by comparing the result with both NDT technics and results of previous works (concerning shifts in modal parameters due to damage). Good results have finally been achieved for the localization of the damages by the topology optimization.
Local design optimization for composite transport fuselage crown panels
NASA Technical Reports Server (NTRS)
Swanson, G. D.; Ilcewicz, L. B.; Walker, T. H.; Graesser, D.; Tuttle, M.; Zabinsky, Z.
1992-01-01
Composite transport fuselage crown panel design and manufacturing plans were optimized to have projected cost and weight savings of 18 and 45 percent, respectively. These savings are close to those quoted as overall NASA Advanced Composite Technology (ACT) program goals. Three local optimization tasks were found to influence the cost and weight of fuselage crown panels. The effects are summarized of each task and the task associated with a design cost model is described in detail. Studies were performed to evaluate the relationship between manufacturing cost and design details. A design tool was developed to aid in these studies. The development of the design tool included combining cost and performance constraints with a random search optimization algorithm. The resulting software was used in a series of optimization studies that evaluated the sensitivity of design variables, guidelines, criteria, and material selection on cost. The effect of blending adjacent design points in a full scale panel subjected to changing load distributions and local variations was shown to be important. Technical issues and directions for future work were identified.