5results about How to "Overcoming real-time" patented technology

The application provides an intraoperative real-time optical coherence imaging guided laser ablation treatment system, which comprises an optical guiding module, a laser treatment module and a real-time monitoring and feedback module; high-resolution three-dimensional information and blood vessel function information obtained by the optical coherence imaging guiding module are used to accurately segment the region of a tumor site, and the power and irradiation time of a radiation laser light source are accurately controlled according to the information; meanwhile, a temperature sensor monitors the tissue temperature at any time, and the system pauses laser diagnosis and treatment when the temperature exceeds the set threshold range, so that precise laser ablation treatment is realized; the application aims to overcome the problems that the current laser ablation treatment lacks real-time and accurate segmentation of tumor regions and lacks real-time monitoring and feedback of the tissues around the tumor during the operation, so that real-time and accurate laser ablation treatment of the tumor site during the operation is realized.

The present application relates to the technical field of automatic driving and unmanned driving, and particularly provides a vehicle positioning method, computer equipment, a server, a storage medium and a vehicle, aiming to solve the problem of reducing the real-time performance and reliability of positioning caused by too long loading time and large memory resource occupation. The method provided by the present application comprises loading a serialized file formed by serializing a data structure of a point cloud probability distribution map, the data structure being formed by encapsulating a voxel index of a point cloud map and normal distribution parameters of point clouds in the voxel; performing deserialization processing on the serialized file to obtain the data structure; and using a positioning method based on an NDT algorithm to perform point cloud registration on a laser radar point cloud frame collected by the vehicle according to the data structure, so as to determine the pose of the vehicle. Through the above method, the data loading time can be greatly reduced, and after the loading is completed, too much memory resource will not be occupied, and finally the real-time performance and reliability of vehicle positioning are improved.

The invention discloses a robot multi-layer cooperation method and system for grotto cultural relic protection and guide, and the method comprises the steps: collecting the multi-dimensional data of grotto cultural relics and surroundings through distributed sensing nodes, carrying out the classified storage, and calling a cultural relic defect hierarchical recognition and evaluation model to complete the preliminary screening and type judgment of defects, the method comprises the following steps: scheduling a detection robot to execute refined detection and defect level quantitative evaluation based on a multi-layer cooperative dynamic task allocation mechanism of the robot, starting a style migration model for a wall painting fading defect to carry out color reconstruction and style adaptation, and planning an optimal path through a dynamic avoidance algorithm based on environment obstacle information; and integrating various data to generate personalized navigation content and transmitting the personalized navigation content to the navigation robot to execute a task. Through multi-step cooperation and model algorithm support, intelligent linkage of defect identification, fading repair, path planning and navigation service is realized, and the cooperation efficiency of grotto cultural relic protection and navigation is improved.

The invention provides a railway bridge construction operation and maintenance method and system based on carbon emission optimization, relates to the technical field of traffic infrastructures, and aims to construct a bridge digital twin model in a construction stage to simulate and predict carbon emission dynamics. And carrying out correlation analysis on the carbon emission influence factors by using a space-time diagram network. The carbon emission is globally optimized through a quantum annealing algorithm, construction scheduling is optimized in combination with a quantum decision tree, dynamic regulation and control of the carbon emission are achieved, and meanwhile the influence on bridge material attenuation is determined. And an operation and maintenance stage: inputting the bridge structure attenuation information and the bridge structure data obtained in the operation and maintenance stage into a convolutional neural network, predicting a bridge structure state, and generating a dynamic maintenance decision according to the bridge structure state. The method can accurately monitor and optimize the carbon emission in the construction, operation and maintenance stages of the railway bridge, and provides technical support and decision basis for the industry to realize low-carbon and sustainable development targets.