Image-processing-based model for surface roughness evaluation in titanium based alloys using dual tree complex wavelet transform and radial basis function neural networks.

In this study, we examine the assessment of surface roughness on turned surfaces of Ti 6Al 4V using a computer vision system. We utilize the Dual-Tree Complex Wavelet Transform (DTCWT) to break down the images of the turned surface into sub-images oriented in directions. Three different methods of feature generation have been compared, i.

The role of cobalt doping in tuning the band gap, surface morphology and third-order optical nonlinearities of ZnO nanostructures for NLO device applications.

The work presented here reported the effect of doping cobalt (Co) in ZnO thin films. The thin films were prepared using the spray pyrolysis technique with 0, 1, 5 and 10 wt% cobalt doping concentrations to study the morphological, optical and third-order nonlinear optical (NLO) properties. X-ray diffraction revealed the crystalline nature of the prepared thin films, and the crystallite size was found to increase with the concentration of doped Co.