12results about How to "Improve long-term performance" patented technology

The invention relates to environment-friendly hydrophobic ink and a preparation method thereof, and belongs to the technical field of water-based ink. A copolymerization modifier capable of being combined in a water-based polyacrylate emulsion in an initiation polymerization mode in the stage of preparing the modified water-based polyacrylate emulsion is prepared, and an o-hydroxy aromatic ketone structure in the copolymerization modifier can endow water-based ink with lasting ultraviolet absorption performance; the trifluoromethyl structure can reduce the surface energy of the water-based ink, and the benzimidazole ring structure can form stable coordinate bonds with metal ions, so that the bonding performance of the water-based ink and a metal substrate is enhanced; when the copolymerization modifier is used for modifying the water-based polyacrylate emulsion, the long-term performance, the hydrophobic and oil-resistant performance and the adhesion performance on the surface of a metal base material of the finished water-based ink can be effectively improved.

The present application relates to the technical field of industrial unmanned aerial vehicle application and intelligent scheduling, and particularly discloses an unmanned aerial vehicle highway inspection task intelligent planning management system, which comprises a task input module, an intelligent planning engine, a task execution management module, a data hub and a feedback optimization module; the task input module receives and checks and analyzes inspection task requirements and highway basic information; the intelligent planning engine decomposes task priorities based on highway multi-dimensional attributes, dynamically allocates unmanned aerial vehicle resources and generates an optimal path meeting multiple constraints; the task execution management module issues adaptive instructions, monitors unmanned aerial vehicle states and processes inspection data; the data hub uniformly stores whole-process data; and the feedback optimization module optimizes a decision model based on historical data. The present application improves inspection planning accuracy and resource utilization, guarantees data quality, realizes self-evolution and ensures efficient and reliable highway inspection.

The invention relates to the technical field of artificial intelligence, and discloses a health management method and device based on artificial intelligence, equipment and a storage medium, and the method comprises the steps: obtaining a multi-modal comprehensive state vector, a multi-dimensional psychological portrait and a context state vector of a user in an interaction process, the multi-modal comprehensive state vector, the multi-dimensional psychological portrait and the context of the current health task form an interaction state; according to the context state vector, matching an excitation action suitable for the user under the current health task; calculating a reward generated by adopting an incentive action for the user in the interaction state; through a reinforcement learning algorithm, generating a target incentive action for the user according to the interaction state, the incentive action and reward learning; and exciting the user to perform a health behavior based on the target excitation action. The method can be applied to individual health management scenes in the field of medical science and technology, and the long-term effect of individual health management can be remarkably improved.

The invention discloses a specialized nurse-oriented blood purification personalized course recommendation method and system, and relates to the technical field of medical teaching. The method comprises the following steps: S1, collecting blood purification operation data, and preprocessing the blood purification operation data; s2, dividing the preprocessed blood purification operation data into four stages, and calculating corresponding operation characteristic values; S3, obtaining operation capability characterization parameters of each stage, constructing a nurse operation evaluation model, and outputting a blood purification operation evaluation value of a nurse; and S4, generating a personalized learning task package based on the hematopurification operation evaluation value and the weight coefficient of each stage, pushing the personalized learning task package to a nurse side, constructing an evaluation difference matrix before and after learning, and performing closed-loop updating of course recommendation. The problem that an existing nurse training system cannot achieve objective evaluation and precise course matching based on multi-dimensional data of the hematology operation process, and consequently learning content is general and insufficient in individuation is solved.

The present application relates to the technical field of image recognition, and specifically discloses a vehicle part recognition method and system, an electronic device and a storage medium. The technical scheme of the present application generates an enhanced image dataset by acquiring multi-angle vehicle images and performing image enhancement processing, and divides the fine-tuning process of a pre-trained visual model into three stages to progressively unfreeze and update the top, middle and bottom layer parameters in sequence. Performance evaluation and threshold determination are introduced during stage conversion, solving the problems of excessive consumption of computing resources and excessively long training time caused by full parameter fine-tuning relying on large-scale datasets in the prior art, and the problems of insufficient recognition accuracy and generalization ability caused by the difficulty of pre-trained models to adapt to multi-angle complex backgrounds. The present application reduces the model training cost, shortens the model training cycle, and improves the vehicle part recognition accuracy and generalization ability.

The application discloses an assembled beam-column joint damping structure and a construction method, the joint comprises a vertical damping structure, a horizontal damping structure and an oblique damping structure; the vertical damping structure comprises a joint upper cylinder, a middle part of the joint upper cylinder is hingedly connected with a connecting rod assembly, a lower end of the connecting rod assembly is elastically connected with a joint lower cylinder in a horizontal direction, a plurality of vertical sliding rods are arranged on the front side and the rear side of the connecting rod assembly, and the lower ends of the vertical sliding rods are elastically connected with the joint lower cylinder in a vertical direction; the horizontal damping structure is symmetrically distributed on the left side and the right side of the joint lower cylinder after penetrating the joint lower cylinder; the structure is connected and combined with the beam and the column through the setting of the energy dissipation component, so that the damping and energy dissipation effect is achieved; under the action of the earthquake, the damping structure can offset a certain amount of seismic energy through the mutual restriction of the deformation, the vertical displacement and the horizontal displacement of the component itself, and the influence of the earthquake on the structure is reduced.

The invention discloses a test scene intelligent simulation method, system and device for a real-time control system and a medium, and the method comprises the steps: receiving a test demand, carrying out the analysis of the test demand based on a large language model and a test domain knowledge graph, and generating a structured test demand; calling a corresponding generative artificial intelligence model, and generating a cross-modal test data set associated in time sequence and semantics; based on a structured test requirement, a cross-modal test data set and a test domain knowledge graph rule, automatically generating a test script and arranging a time sequence test scene process so as to drive the real-time control system and collect response of the real-time control system; and analyzing a test execution result, optimizing decision logic of data generation or protocol simulation through reinforcement learning based on the analysis result, and updating the decision logic to the test domain knowledge graph. Compared with the prior art, full-link automation of real-time control system testing from scene construction and execution to autonomous evolution is achieved.

This invention discloses a virtual human-computer interaction system and method for brand promotion, relating to the field of human-computer interaction technology. The system includes: S1: collecting multimodal data from users during the interaction process via a user terminal and performing real-time analysis to generate real-time user status information; S2: generating comprehensive interaction context instructions; S3: based on the comprehensive interaction context instructions, executing a virtual human adaptive generation step and a brand content dynamic generation step in parallel; S4: forming and outputting an interaction response for the current user; S5: collecting user behavior data related to the interaction effect and updating and optimizing rules based on the user behavior data. The advantages of this invention are: through multimodal perception and context analysis, it achieves real-time personalized dynamic generation of virtual human image, interaction style, and promotional content, enabling brand promotion to accurately adapt to the real-time status and historical preferences of different users, greatly improving the naturalness, attractiveness, and user resonance of the interaction.

The invention relates to a slope surface mortar cushion structure and a construction method thereof, and the construction method comprises the following steps: slope surface treatment: removing surface soil and sundries on the slope surface, and sprinkling water for wetting; formwork installation, wherein square steel is adopted to be assembled into a modular formwork system; measuring and lofting: carrying out encrypted measurement on elevation and slope surface control points through a total station; m10 mortar preparation and pouring: M10 strength grade mortar is adopted, the consistency is 30-50 mm, the water retention rate is larger than or equal to 80%, and the M10 strength grade mortar is warehoused through a chute or a truck-mounted crane; surface treatment is conducted, specifically, secondary leveling is conducted through an aluminum alloy guiding rule and a wood trowel; curing: covering a curing blanket and spraying water for curing, wherein the curing time is not less than 7 days; construction joints are treated, wherein laitance of the joints is removed, and pouring is continued after mortar with the same proportion is brushed. By means of the slope mortar cushion construction method, the construction quality can be effectively improved, the long-term performance can be improved, the maintenance period can be prolonged, and the slope mortar cushion construction method is more suitable for large water conservancy projects.

The invention discloses a self-adaptive navigation method and system for an unmanned distribution vehicle in a complex road condition. The method comprises the steps of constructing and updating a dynamic passing cost map, executing global path planning, executing local track optimization and control, and monitoring and re-planning. A dynamic passing cost map is constructed by fusing dynamic cost generated by sensing obstacles in real time and historical experience cost based on historical data learning, global cost optimal path planning and local rolling track optimization are performed based on the map, a control instruction is generated, global path cost is monitored at the same time, and the optimal path planning and local rolling track optimization are realized. And when a self-adaptive threshold condition based on historical experience is met, global re-planning is triggered, and self-optimization is carried out through an emergency cooperation mechanism and system parameters when local planning fails, so that the passing efficiency, the safety and the overall intelligent level of the unmanned distribution vehicle in a dynamic uncertain environment are improved; the problems of poor environmental adaptability and low decision-making efficiency in the prior art are solved.

This invention provides a method and system for autonomous iteration and real-time control of forging process based on machine vision for extracting time-frequency map features. The method transforms the thermal and deformation history data during forging into a time-frequency map through time-frequency transformation, and establishes a mapping relationship between the time-frequency map and the microstructure using a convolutional neural network (CNN). Then, a generative model is used to construct a bidirectional mapping model between process parameters and the time-frequency map. Based on this, combined with a model predictive control (MPC) framework, the process parameters are optimized in real time with microstructure targets as constraints. After the process is completed, the model parameters are iteratively updated autonomously, thereby achieving iterative optimization of the microstructure quality of the forging. This invention can effectively extract deep features of the thermal deformation history, establish a reliable mapping relationship between "process parameters - thermal deformation history - microstructure," and achieve online optimization of process parameters during forging, providing an intelligent production process optimization solution for the high-end equipment manufacturing field.

The application provides a multi-agent collaboration-based vocational education whole-process intelligent generation and optimization method and system, and particularly relates to the field of intelligent teaching technology based on artificial intelligence. The method acquires a real-time learning state of a learner and a teaching task target; based on the learning state, the target and a context memory network, a meta-coordination agent generates a coordination instruction, specifies a main interaction agent and an auxiliary interaction agent from a set of collaborative teaching agents and configures a strategy; the main interaction agent is controlled to interact with the learner and collect results; based on the results, a strategy effectiveness index is generated and the context memory network is updated; an intervention adjustment instruction is generated by the meta-coordination agent to dynamically adjust the agent role, timing or strategy, including switching the dominant right. The application solves the problem that static role configuration is difficult to dynamically contextualize interaction, realizes smooth cooperation like educational drama, and improves the immersion and long-term effect of personalized teaching.