Generative Graph Dictionary Learning.

Dictionary learning, which approximates data samples by a set of shared atoms, is a fundamental task in representation learning. However, dictionary learning over graphs, namely graph dictionary learning (GDL), is much more challenging than vectorial data as graphs lie in disparate metric spaces. The sparse literature on GDL formulates the problem from the reconstructive view and often learns linear graph embeddings with a high computational cost.

FEM Simulation and Verification of Brazing SiC Ceramic with Novel Zr-Cu Filler Metal.

Zr-Cu filler metal is proposed for SiC ceramic under special working conditions, as a novel type of the active filler metal, the difference of physical and chemical properties between SiC ceramic and Zr-Cu filler metal leads to greater residual stress in the joint, which affects the mechanical properties of brazing SiC ceramic joint. Based on the finite element method (FEM) simulation, the residual stress of the joint is simulated to guide the design of Zr-based filler metal and formulation of brazing process. The residual stress distribution of SiC ceramic joints brazed at 1200 °C with different thickness of the filler metal and cooling rate is simulated by ANSYS software.