Abstract: An image reconstruction method includes: determining singles rates of radiation detectors in a frame of imaging data detected by the radiation detectors; determining an energy correction factor (Nwgt) for each radiation detector based on an energy spectrum distribution of gamma rays incident on the radiation detector during acquisition of the frame of imaging data; determining a singles live time correction factor for each radiation detector from the singles rate and the energy correction factor; determining a system coincidence live time correction factor from the system singles rate; for each line of response (LOR) connecting pairs of radiation detectors, determining a live time correction factor for the LOR from the determined singles live time correction factors of the pair of radiation detectors connected by the LOR and the determined system coincidence live time correction factor; and reconstructing the frame of imaging data using the determined LOR live time correction factors.

Abstract: A method for extracting and correcting a ringing component in a dynamic pressure measurement signal of a shock wave flow field includes: adaptively decomposing a dynamic pressure measurement signal of a shock wave flow field through an empirical mode decomposition (EMD) method, and extracting a ringing component in the dynamic pressure measurement signal of the shock wave flow field; constructing a ringing component distortion correction model through a convolutional neural network (CNN) and a dataset through a staggered spanning dataset construction method; and predicting a time series of a segment with mode mixing in the ringing component, to accurately extract a ringing component in a dynamic pressure response signal. The method combines advantages of an adaptive signal decomposition method and a CNN model identification method.

Abstract: A battery assembly, a battery pack, and a vehicle are provided. The battery assembly includes an inner housing and a battery module. Multiple grooves are defined in the inner housing. A space defined in each of the grooves is an accommodation cavity, to enable multiple accommodation cavities to be defined in the inner housing. The multiple accommodation cavities form an accommodation space. The battery module is arranged in each of the accommodation cavities, to enable the battery module to be arranged in the accommodation space.

Abstract: An electronic device supporting power consumption reduction can be operated in a power saving mode or in an active mode, and the electronic device includes a first processor and a second processor. The first processor is configured to be powered off when the electronic device is in the power saving mode. The second processor is configured to, when the electronic device is in the power saving mode, control peripheral hardware associated with a local bus of the first processor. The peripheral hardware includes at least one of the following: a display unit, an input unit, a BLUETOOTH unit, and a sensing unit.

Abstract: An electronic device supporting power consumption reduction can be operated in a power saving mode or in an active mode, and the electronic device includes a first processor and a second processor. The first processor is configured to be powered off when the electronic device is in the power saving mode. The second processor is configured to, when the electronic device is in the power saving mode, control peripheral hardware associated with a local bus of the first processor. The peripheral hardware includes at least one of the following: a display unit, an input unit, a BLUETOOTH unit, and a sensing unit.