Abstract: One embodiment provides a multi-scale simulation-based functionally graded material design method for a high temperature environment. According to one embodiment, since the characteristics of a functionally graded material (FGM) may be predicted through multi-scale simulation in advance and optimal conditions may be derived, it is possible to reduce the costs required for experiment and manufacture and shorten the manufacturing time.

Abstract: The present disclosure provides a method and a device for image quality enhancement based on a super-resolution neural network. The present disclosure in at least one embodiment provides an image quality enhancement method optimized for distortion characteristics of a target image, including generating one or more training datasets with one or more distortions, obtaining training distortion characteristic values respectively by inputting the one or more training datasets into a degradation encoder neural network (DEN), obtaining a service distortion characteristic value by inputting a service dataset comprising image patches of the target image into the degradation encoder neural network, computing a similarity between each of the training distortion characteristic values and the service distortion characteristic value, and selecting the training dataset having the highest similarity to the service distortion characteristic value.

Abstract: The purpose of the invention is to provide a hard coating for cutting tools, wherein the hard coating is excellent in wear resistance and oxidation resistance, as well as in hardness properties. In order to achieve the purpose, the invention may provide a cutting tool which includes a hard substrate and a hard coating formed on the hard substrate, wherein the hard coating has a structure in which a first sub-coating having a composition range represented by [Formula 1] below and having a cubic structure, and a second sub-coating having a composition range represented by [Formula 2] below and having a cubic structure are alternately stacked. Al1-xMnxN(0.005?x?0.