Shot peening effect on surface properties and pitting corrosion resistance of biomedical structural steel AISI 316L

AISI 316L is used in biomedical engineering as bone implant materials. The mechanical properties and corrosion resistance of this material can be improved by shot peening. The aim of this research is to investigate the effect of shot peening on surface roughness, hardness, wettability, and pitting corrosion resistance of AISI 316L in 0,9 % NaCl solution. The shot-peening was performed on AISI 316L surfaces with duration of 0, 2, 4, 10, 20, 30 minutes using steel balls with a diameter of 0,6 mm and hardness of 40 - 50 HRC. The results show that shot peening increase roughness after 2 minutes then decrease the roughness with increasing time. The longer duration of shot peening will increase the pitting corrosion resistance

Investigation of the new cataclysmic variable 1RXS J180834.7+101041

We present the results of our photometric and spectroscopic studies of the new eclipsing cataclysmic variable star 1RXS J180834.7+101041. Its spectrum exhibits double-peaked hydrogen and helium emission lines. The Doppler maps constructed from hydrogen lines show a nonuniform distribution of emission in the disk similar to that observed in IP Peg. This suggests that the object can be a cataclysmic variable with tidal density waves in the disk. We have determined the component masses (M_WD =0.8 \pm 0.22 M_sun and M_RD =0.14 \pm 0.02 M_sun) and the binary inclination (i =78 \pm 1.5 deg) based on well-known relations between parameters for cataclysmic variable stars. We have modeled the binary light curves and showed that the model of a disk with two spots is capable of explaining the main observed features of the light curves.Comment: 22 pages, 9 figures, 2 tables, published in Astronomy Letters, 2011, 37, 845-85

The COST292 experimental framework for TRECVID 2007

In this paper, we give an overview of the four tasks submitted to TRECVID 2007 by COST292. In shot boundary (SB) detection task, four SB detectors have been developed and the results are merged using two merging algorithms. The framework developed for the high-level feature extraction task comprises four systems. The first system transforms a set of low-level descriptors into the semantic space using Latent Semantic Analysis and utilises neural networks for feature detection. The second system uses a Bayesian classifier trained with a “bag of subregions”. The third system uses a multi-modal classifier based on SVMs and several descriptors. The fourth system uses two image classifiers based on ant colony optimisation and particle swarm optimisation respectively. The system submitted to the search task is an interactive retrieval application combining retrieval functionalities in various modalities with a user interface supporting automatic and interactive search over all queries submitted. Finally, the rushes task submission is based on a video summarisation and browsing system comprising two different interest curve algorithms and three features

The COST292 experimental framework for TRECVID 2007

In this paper, we give an overview of the four tasks submitted to TRECVID 2007 by COST292. In shot boundary (SB) detection task, four SB detectors have been developed and the results are merged using two merging algorithms. The framework developed for the high-level feature extraction task comprises four systems. The first system transforms a set of low-level descriptors into the semantic space using Latent Semantic Analysis and utilises neural networks for feature detection. The second system uses a Bayesian classifier trained with a "bag of subregions". The third system uses a multi-modal classifier based on SVMs and several descriptors. The fourth system uses two image classifiers based on ant colony optimisation and particle swarm optimisation respectively. The system submitted to the search task is an interactive retrieval application combining retrieval functionalities in various modalities with a user interface supporting automatic and interactive search over all queries submitted. Finally, the rushes task submission is based on a video summarisation and browsing system comprising two different interest curve algorithms and three features