Abstract: A hydraulic engineered cementitious composite (ECC) material and an application thereof are provided. The ECC material includes 25-34 wt % of cement, 23-30 wt % of fly ash, 15-20 wt % of silica fume, 26-32 wt % a fine aggregate, 1.25-1.7% of a composite fiber mesh, 0.1-0.24 wt % of a water reducer, and 0.03-0.07 wt % of a thickener. The composite fiber mesh is prepared by dipping a composite fiber in a water-borne epoxy resin with a curing agent, performing uniform mixing, taking out and spreading the composite fiber, and then cutting or crushing the composite fiber into a small piece of mesh structure; and the composite fiber includes a PVA fiber and a carbon fiber, or a PVA fiber and a basalt fiber, at a weight ratio of (0.3-0.6):1.

Abstract: The present disclosure relates to a vehicle tracking method, a computer readable storage medium, and an electronic device. The method includes: determining a predicted value of state information of a target tracking vehicle based on a sequential Kalman filtering model according to a most recently acquired tracking value of the state information of the target tracking vehicle, wherein the state information at least includes location information; obtaining a detected value of the state information of the target tracking vehicle; and in response to the obtained detected value, acquiring a new tracking value of the state information of the target tracking vehicle based on the sequential Kalman filtering model according to the detected value and the most recently determined predicted value. Through the above technical solution, the tracking value of the state information of the target tracking vehicle may be determined more accurately.

Abstract: The present disclosure relates to a target object detection method, a readable storage medium and an electronic device. The method is periodically executed and the method includes: identifying a target object based on first N frames of image data obtained within a current execution period, wherein N is a positive integer, and N is less than the total number of frames of image data that can be obtained within the current execution period; and if the target object is identified, tracking the target object based on the obtained image data within the remaining time period of the current execution period. In the above technical solution, when the target object is identified, the identified target object is tracked within the remaining time period of the current execution period, so that the data calculation amount can be effectively reduced.

Abstract: The present disclosure relates to a vehicle tracking method, a computer readable storage medium, and an electronic device. The method includes: determining a predicted value of state information of a target tracking vehicle based on a sequential Kalman filtering model according to a most recently acquired tracking value of the state information of the target tracking vehicle, wherein the state information at least includes location information; obtaining a detected value of the state information of the target tracking vehicle; and in response to the obtained detected value, acquiring a new tracking value of the state information of the target tracking vehicle based on the sequential Kalman filtering model according to the detected value and the most recently determined predicted value. Through the above technical solution, the tracking value of the state information of the target tracking vehicle may be determined more accurately.

Abstract: The present disclosure relates to a target object detection method, a readable storage medium and an electronic device. The method is periodically executed and the method includes: identifying a target object based on first N frames of image data obtained within a current execution period, wherein N is a positive integer, and N is less than the total number of frames of image data that can be obtained within the current execution period; and if the target object is identified, tracking the target object based on the obtained image data within the remaining time period of the current execution period. In the above technical solution, when the target object is identified, the identified target object is tracked within the remaining time period of the current execution period, so that the data calculation amount can be effectively reduced.