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Plasma Science and Technology - Progress in Physical States and Chemical Reactions || Plasma-Enhanced Laser Materials Processing
摘要： In the last few years, the combination of laser irradiation with atmospheric pressure plasmas, also referred to as laser–plasma hybrid technology, turned out to be a powerful technique for different materials processing tasks. This chapter gives an overview on this novel approach. Two methods, simultaneous and sequential laser-plasma process‐ ing, are covered. In the first case, both the plasma and the laser irradiation are applied to the substrate at the same time. Depending on the process gas and the discharge type, the plasma provides a number of species that can contribute to the laser process plasma- physically or plasma-chemically. Sequential plasma-enhanced laser processing is based on a plasma-induced modification of essential material properties, thus improving the coupling of laser energy into the material during subsequent laser ablation. Simultane‐ ous plasma-assisted laser processing allows increasing the efficiency of a number of dif‐ ferent laser applications such as cleaning, microstructuring, or annealing processes. Sequential plasma-assisted laser processing is a powerful method for the processing of transparent media due to a reduction in the laser ablation threshold and an increase in the ablation rate at the same time. In this chapter, the possibilities, underlying mecha‐ nisms, performance, and limits of the introduced approaches are presented in detail.
关键词： Laser-plasma-hybrid techniques,microstructuring,atmospheric pressure plasma,modification,cleaning
更新于2025-09-23 15:21:01
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New Evolutionary-Based Techniques for Image Registration
摘要： The work reported in this paper aims at the development of evolutionary algorithms to register images for signature recognition purposes. We propose and develop several registration methods in order to obtain accurate and fast algorithms. First, we introduce two variants of the firefly method that proved to have excellent accuracy and fair run times. In order to speed up the computation, we propose two variants of Accelerated Particle Swarm Optimization (APSO) method. The resulted algorithms are significantly faster than the firefly-based ones, but the recognition rates are a little bit lower. In order to find a trade-off between the recognition rate and the computational complexity of the algorithms, we developed a hybrid method that combines the ability of auto-adaptive Evolution Strategies (ES) search to discover a global optimum solution with the strong quick convergence ability of APSO. The accuracy and the efficiency of the resulted algorithms have been experimentally proved by conducting a long series of tests on various pairs of signature images. The comparative analysis concerning the quality of the proposed methods together with conclusions and suggestions for further developments are provided in the final part of the paper.
关键词： hybrid techniques,image recognition,image registration,firefly technique,evolutionary computing,affine perturbation,evolution strategies,mutual information
更新于2025-09-19 17:15:36