DEVELOPMENT OF A FRAMEWORK FOR IMPLEMENTING 3D SPATIAL DATA INFRASTRUCTURE IN OMAN – ISSUES AND CHALLENGES

The paper reviews that there are several issues and challenges in order to implement full 2D and 3D Spatial Data Infrastructure (SDI) in Oman. The state of current 2D SDI and 3D geospatial data has been investigated. Currently, Oman has made noticeable progress in 2D SDI but not yet in 3D domain. To date, there are no serious efforts and initiatives by the authority to materialize the 3D SDI. This paper ends by describing a framework for implementing the 3D SDI. We expect, these issues and challenges of 3D SDI in Oman can prompt better services for several potential users

Particle swarm optimization algorithm to enhance the roughness of thin film in tin coatings

Nowadays, lots of disciplines require optimization to determine optimal parameters to accomplish top quality services which include parameters optimization of thin film coating. Modification of sharp tool characteristics and costs are two primary matters in the procedure of Physical Vapour Deposition (PVD). The purpose of this study is to figure out the optimal parameters in PVD coating process for better thin-film roughness. Three input parameters are chosen to describe the solutions over the target data, such as Nitrogen gas pressure (N2), Turntable speed (TT), and Argon gas pressure (Ar), although the surface roughness had been chosen being a result response of the Titanium nitrite (TiN). Atomic Force Microscopy (AFM) tools were applied to describe the roughness of coating layer. Within this research, a process of modelling using Response Surface Method (RSM) was applied for surface roughness of Titanium Nitrite (TiN) coating to get a best result. Particle Swarm Optimization (PSO) was applied as an optimization technique for the coating process to enhance characteristics of thin film roughness. In validation process, different experimental runs of actual data were conducted. It was found that residual error (e) is less than 10, to indicate that the model can accurately predict the surface roughness. Also, PSO could reduce the value of coating roughness at reduction of ≈ 48% to get a minimum value compared to actual data