The first microwave imaging reflectometry (MIR) system for characterization of fluctuating plasma density has been implemented for the TEXTOR tokamak [H. Park et al., Rev. Sci. Instrum. 75, 3787 (2004)]; an improved MIR system will be installed on DIII-D and KSTAR. The central issue remains in preserving phase information by addressing antenna coupling between the reflection layer and the detector array in the presence of plasma turbulence. A synthetic diagnostic making use of coupled full-wave diffractive codes has been developed in geometries and applied to a variety of optical arrangements. The effectiveness of each scheme is quantitatively compared with respect to the fluctuation levels accessible in the simulation.

It is important to evaluate the independent innovation capacity of high-tech industry scientifically, which could accelerate high-tech industry to become the main body of regional economy. In this paper the evaluation indicators of the independent innovation capacity of high-tech industry are reduced with the distinction matrix algorithm of the attribute reduction based on rough set theory. And then, projection pursuit model method based on genetic algorithms is used to get the synthetic evaluation. High-tech industry of Henan province as a specific example is given according to the evaluation index system with 4 primary indicators and 12 secondary indicators for independent innovation capability. It is proved that the evaluation method is feasible and effective.