2results about How to "Avoiding Combinatorial Explosion Problems" patented technology

This invention discloses a pure vision-based 3D reconstruction and adaptive completion method in a collapse environment, belonging to the field of computer vision and emergency rescue 3D reconstruction technology. The method completes initial 3D reconstruction by acquiring data through binocular vision, constructs an anisotropic point cloud density distribution field to achieve accurate detection of low-density blind spots, establishes safe and reachable spatial constraints based on an implicit distance field, and optimizes the completion viewpoint by fusing an observability model. Map iteration is completed through local reconstruction and point cloud updates, and a closed-loop completion mechanism is formed using point cloud density as feedback until the reconstructed model meets the integrity requirements. This invention solves the problems of permanent voids in reconstruction caused by viewpoint blind spots, poor consistency between completion results and the real scene, and insufficient safety in the reconstruction process in existing technologies in collapse environments. It can achieve complete and high-precision autonomous reconstruction of 3D models of collapse disaster sites, providing reliable spatial data support for emergency rescue decision-making.

The present invention discloses a compound combination screening method based on key genes for resisting parasitic infections, comprising: 1. After preprocessing biological data, a single-layer differential interaction network is constructed for each individual infected by parasites, and a multi-layer gene interaction network is constructed by connecting the corresponding gene nodes of multiple single-layer networks to achieve the fusion of multiple networks, and then the PageRank algorithm of the multi-layer network is used to calculate the score of the gene in each layer of the network, and the average score of the corresponding same gene in all layers is used to sort and identify the key gene; 2. Based on the key gene and the known FDA-approved compounds and the target gene set of each compound, a multi-objective optimization function model is designed, and a multi-objective optimization algorithm is used to obtain a better compound combination. The present invention can improve the time efficiency of screening the compound combination for resisting parasitic infections and screen out a better compound combination.