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Reducing the Time Complexity of the Derandomized Evolution Strategy with Covariance Matrix Adaptation (CMA-ES)
A novel evolutionary optimization strategy based on the derandomized evolution strategy with covariance matrix adaptation (CMA-ES) to reduce the number of generations required for convergence to the optimum, resulting in a highly parallel algorithm which scales favorably with large numbers of processors. Expand
Feature point tracking and trajectory analysis for video imaging in cell biology.
A computationally efficient, two-dimensional, feature point tracking algorithm for the automated detection and quantitative analysis of particle trajectories as recorded by video imaging in cell biology. Expand
Vortex methods - theory and practice
The book Vortex Methods: Theory and Practice presents a comprehensive account of the numerical technique for solving fluid flow problems, and goes into some detail on the more recent developments that attempt to account for viscous effects. Expand
High-resolution simulations of the flow around an impulsively started cylinder using vortex methods
The development of a two-dimensional viscous incompressible flow generated from a circular cylinder impulsively started into rectilinear motion is studied computationally. An adaptative numericalExpand
TScratch: a novel and simple software tool for automated analysis of monolayer wound healing assays.
TScratch, a new, freely available image analysis technique and associated software tool that uses the fast discrete curvelet transform to automate the measurement of the area occupied by cells in the images, helps to significantly reduce the time needed for analysis and enables objective and reproducible quantification of assays. Expand
A Method for Handling Uncertainty in Evolutionary Optimization With an Application to Feedback Control of Combustion
It is demonstrated that their online optimization with the proposed methodology enhances, in an automated fashion, the online performance of the controllers, even under highly unsteady operating conditions, and it also compensates for uncertainties in the model-building and design process. Expand
Accelerating evolutionary algorithms with Gaussian process fitness function models
The Gaussian process model is described and proposed using it as an inexpensive fitness function surrogate and clearly outperforms other evolutionary strategies on standard test functions as well as on a real-world problem: the optimization of stationary gas turbine compressor profiles. Expand
Simulations of optimized anguilliform swimming
The results of the present simulations support the hypothesis that anguilliform swimmers modify their kinematics according to different objectives and provide a quantitative analysis of the swimming motion and the forces experienced by the body. Expand
On the Water−Carbon Interaction for Use in Molecular Dynamics Simulations of Graphite and Carbon Nanotubes
A systematic molecular dynamics study shows that the contact angle of a water droplet on graphite changes significantly as a function of the water−carbon interaction energy. Together with theExpand
Optimization based on bacterial chemotaxis
Comparisons show that on average, the bacteria chemotaxis algorithm performs similar to standard evolution strategies and worse than evolution strategies with enhanced convergence properties. Expand