Abstract: Methods and systems for image processing are provided. A target image may be acquired, wherein the target image may include a plurality of elements, an element of which may correspond to a pixel or a voxel. The target image may be decomposed into at least one layer, wherein the at least one layer may include a low frequency sub-image and a high frequency sub-image. The at least one layer may be transformed. The transformed layer may be reconstructed into a composite image.

Abstract: A solid-state polymer electrolyte for lithium batteries is provided. The solid-state polymer electrolyte includes a solid-state network polymer electrolyte, formed by a modified poly(ethylene oxide) polymer material and an epoxy alkane crosslinking agent to form a poly(ethylene oxide) network structure, wherein the modified poly(ethylene oxide) high molecular weight material has an amino end, and the solid-state network polymer electrolyte comprises a lithium salt, The ratio of ethylene oxide (EO) to lithium (Li) in the solid-state network polymer electrolyte is 1:1 to 3:1, and a poly(vinylidene fluoride)-based polymer is doped in the solid-state network polymer electrolyte.

Abstract: The present invention belongs to the field of friction stir welding (FSW) temperature detection, and relates to a temperature characterization method of FSW weld zone based on infrared thermal imager. The invention combines theory with experiment. A temperature field simulation model of FSW is established based on DEFORM. The data sets of temperature of surface feature points, the maximum and minimum temperatures in weld zone are obtained according to the simulation model result. Then, Support Vector Regression (SVR) is used to establish a temperature characterization model, which represents the correlation between the temperature of surface feature points and the maximum and minimum temperatures in weld zone. In the actual welding process, an infrared camera is used to measure the temperature of the surface feature point in real-time. Combined with the built temperature characterization model, the characterization of the maximum and minimum temperatures in weld zone is achieved.