6results about How to "Integrated precision" patented technology

This invention relates to a method and system for automated generation of TSN network configurations based on a reflective agent. The system comprises a network state perception and intent reflection module, a YANG model configuration parameter and structure decision module, and a YANG model intelligent generation module. The network state perception and intent reflection module is responsible for structurally perceiving network state and resource information. The YANG model configuration parameter and structure decision module integrates multi-source knowledge and contextual information, intelligently generating deployable TSN scheduling parameters and YANG configuration structures based on business needs. The YANG model intelligent generation module automatically generates the corresponding YANG configuration model based on the optimized results, performs syntax and semantic verification, and then distributes it to the target device, achieving automated deployment of network configurations. This invention significantly improves the intelligence level and deployment automation capability of TSN network configuration by introducing reflective reasoning and feedback optimization techniques.

The invention discloses a visible light-infrared target detection method based on structured feature extraction and dynamic weight prediction. The method comprises the following steps: carrying out target detection through a visible light-infrared target detection model based on structured feature extraction and dynamic weight prediction; the target detection model comprises a thermal radiation-motion feature extraction module, a multi-granularity visual representation module and a collaborative weight decision module; the thermal radiation-motion feature extraction module is used for capturing thermal radiation information in an infrared image and motion features of a target so as to generate infrared feature representation; the multi-granularity visual representation module is used for performing structured multi-granularity visual feature extraction on the visible light image so as to construct visible light feature representation; and the collaborative weight decision module is used for performing cross integration of infrared feature representation and visible light feature representation through a dynamic weight prediction mechanism. The target detection model provided by the invention has better performance in a visible light-infrared target detection task.

The invention relates to the field of biological information, and discloses a gene library acquisition method for improving single cell amplification genome coverage. Aiming at the problem of insufficient single cell amplification genome coverage, the gene library acquisition method provides a strategy of composite library construction and optimized data integration, and comprises the following steps: constructing at least one original text library and one sub-library with different average fragment lengths for the same single cell sample, and sequencing; performing Barcode resolution and effective single cell identification on the sequencing data through a customizable sequence feature detection method; and further, according to the identification result of the effective single cell, identifying, collecting and merging all sequencing sequence data of the same single cell, generating an integrated sequence data set of the corresponding single cell, and obtaining gene library data of the single cell. The SAG coverage degree of the obtained gene library data is high, and the method has high reliability and application value when being used for genome analysis of the single cell downstream.

The invention relates to the technical field of text processing, and discloses a manuscript generation method and device, equipment and a storage medium. The method comprises the following steps: constructing a template library containing a plurality of template frames and a knowledge base containing a plurality of domain knowledge bases; obtaining use features of a user and each template frame, receiving a free prompt input by the user, and constructing a task feature vector; matching a target template frame based on the first sorting model, and generating a task instruction based on a standard prompt word of the target template frame; if the matching target template frame does not exist, generating a task instruction based on the free prompt word; matching a target knowledge fragment from the knowledge base based on a second sorting model; and forming a large model generation manuscript called by a generation instruction in combination with the target knowledge fragment and the task instruction, correcting the manuscript in response to interaction between a user and the manuscript until a finalized manuscript is generated, and collecting interaction data to perform quality evaluation on the finalized manuscript. According to the method, high-quality, personalized and automatic generation of the manuscripts in the specific field is realized.

The invention provides an embedded large model decision control method and system fusing multi-modal sensing information, and relates to the field of intelligent decision control, and the method comprises the steps: receiving multi-modal data of a space non-cooperative target, carrying out the preprocessing and feature extraction of the multi-modal data, and obtaining a multi-modal sensing information fusion model; deep semantic fusion is realized through unified semantic space projection and a dynamic confidence weighting strategy, and a unified environment representation vector is output; constructing an input representation fusing a time sequence context, domain knowledge Prompt and a sample example, performing target intention recognition and risk level evaluation in stages through a lightweight deployed large model, and generating a structured decision strategy; a structured decision strategy is converted into a spacecraft motion instruction, and a target control sequence is solved through a designed simplified MPC controller. According to the method, the non-cooperative target sensing precision and the data utilization efficiency can be improved, the autonomous intelligent decision-making capability of the terminal is enhanced, and safe and efficient capture and on-orbit service tasks are supported.

The application relates to the technical field of intelligent packaging production line automatic control and multi-station collaborative regulation, and discloses an intelligent packaging production line automatic control method and system, the method comprises the following steps: collecting visual and force feedback data, fusing and preprocessing to obtain multi-station integration information, identifying an abnormal mode, determining product switching, and generating a parameter adjustment scheme; issuing a regulation instruction to correct an execution parameter and analyzing a collaborative deviation; collecting updated data to analyze a deviation value and iteratively optimizing the parameter; executing action coordination and monitoring packaging completeness to obtain an adaptive stable state of the production line. The method realizes multi-station working condition collaborative sensing, intelligent adaptation of product switching and dynamic correction of parameters, solves the problems of response lagging, parameter regulation rigidity and insufficient packaging quality stability of a traditional packaging production line, and improves the operation efficiency and finished product qualification rate of the intelligent packaging production line.