Shenyang Ligong University

About: Shenyang Ligong University is a education organization based out in Shenyang, Liaoning, China. It is known for research contribution in the topics: Photocatalysis & Adsorption. The organization has 3827 authors who have published 3275 publications receiving 14491 citations. The organization is also known as: Shěnyáng Lǐgōng Dàxué.

Transition of twinning behavior in CoCrFeMnNi high entropy alloy with grain refinement

Abstract: Fully recrystallized CoCrFeMnNi high entropy alloys (HEAs) with different grain sizes ranging from 503 nm to 88.9 µm were fabricated by cold rolling and controlled annealing. Tensile tests were conducted at ambient temperature, and deformation microstructures were investigated using electron channeling contrast imaging (ECCI) and transmission electron microscopy (TEM) techniques. It is found that strain-hardening curves changed dramatically with grain refinement. Deformation twinning prevails when the grain size is coarse, but it is absent when the grain size falls in the ultrafine-grained (UFG) regime. The transition of twinning behavior is supposed to be determined by the increased twinning stress with grain refinement. It is indicated that the twinning behavior of the HEAs is strongly dependent on the competition between the flow stress and critical twinning stress with grain refinement.

Fractional calculus in image processing: a review

Abstract: Over the last decade, it has been demonstrated that many systems in science and engineering can be modeled more accurately by fractional-order than integer-order derivatives, and many methods are developed to solve the problem of fractional systems. Due to the extra free parameter order, fractional-order based methods provide additional degree of freedom in optimization performance. Not surprisingly, many fractional-order based methods have been used in image processing field. Herein recent studies are reviewed in ten sub-fields, which include image enhancement, image denoising, image edge detection, image segmentation, image registration, image recognition, image fusion, image encryption, image compression and image restoration. In sum, it is well proved that as a fundamental mathematic tool, fractional-order derivative shows great success in image processing.