3results about How to "Improve distribution accuracy" patented technology

The utility model discloses a medicine dispensing system based on process traceability, which comprises a medicine storage rack, a dispensing cart, a transfer medicine box and a mobile terminal, and is characterized in that the medicine storage rack comprises a plurality of unit cabinets, each unit cabinet is used for accommodating medicines, the medicine storage rack is provided with a first display screen for providing a first two-dimensional code, and the first two-dimensional code carries weight information corresponding to the medicines; the dispensing cart is provided with a liftable collecting assembly and a weighing table, the collecting assembly is used for collecting weight information corresponding to the first two-dimensional code, the weighing table is used for metering the weight of the medicine for checking the weight information, and the collecting assembly is used for collecting image information from the medicine storage frame and the weighing table; the transfer medicine box comprises a box body and a box cover which are matched with each other and is used for storing the medicine after weight information checking, and the box cover is provided with an electric control lock and a second display screen for providing a second two-dimensional code; the mobile terminal collects the second two-dimensional code to unlock the electric control lock, the requirements of medicines of more specifications and varieties are met, the paper-free dispensing and traceable dispensing requirements are met, and the medicine dispensing accuracy is improved.

This invention discloses an intelligent content generation and precise distribution method based on AIGC, comprising the following steps: constructing user individual feature vectors; constructing user association graphs; performing community detection processing to obtain user groups and calculate group distribution parameters, and constructing corresponding group semantic resonance fields; calculating group condition vectors, obtaining generation prompt information, and constructing conditional input sequences; using the AIGC model to generate target content consistent with the semantic features of the corresponding user groups; performing semantic projection calculation to obtain content semantic vectors, and calculating group fit and individual matching degree; generating distribution results for different user individuals; collecting user feedback data on the distribution results, and updating user individual feature vectors, user association graphs, and group semantic resonance fields, thereby realizing integrated collaborative processing of content generation and content distribution.