23results about How to "Avoid resources" patented technology

This invention discloses a task scheduling and motion control method for collaborative operation of a robotic arm and an AGV, belonging to the field of intelligent manufacturing and automation control. The method includes: a central scheduling module receiving task requests and decomposing them into a set of subtasks; allocating subtasks to corresponding execution devices using a combination of auction mechanisms and cost function optimization; determining whether task conflicts exist; if so, executing a re-task process; otherwise, executing a collaborative control process. The collaborative control process includes generating a global trajectory using a hybrid path planning method and real-time correction of the local trajectory by a local control module; and achieving synchronous control of the robotic arm and AGV at the handover point using a state machine-based handshake protocol. This invention effectively solves the problem of task conflicts and resource competition among multiple devices through a unified task scheduling and collaborative control mechanism, improving the handover accuracy and operational efficiency of the grasping-delivery process, and is applicable to complex scenarios such as pharmaceutical research and development and chemical production.

This invention discloses a request processing method, apparatus, device, and storage medium, comprising: when the matching result is determined to be a matching failure, inferring the user request using a synchronous direct transmission mode through the target instance to obtain a first key-value cache, and determining the storage method of the first key-value cache based on its cost; when the matching result is determined to be a match with the target key-value cache, inferring the user request using a prefetch incremental mode through the target instance to obtain a second key-value cache, and directly saving the second key-value cache to a storage center. In the synchronous direct transmission mode, the cost of the key-value cache obtained through user request inference is calculated, and key-value caches that meet the cost requirements are saved to the storage center, avoiding invalid space occupation in the storage center and improving the inference efficiency of subsequent user requests. In the prefetch incremental mode, when a key-value cache hit meets the cost requirements, it is directly used to improve inference efficiency and avoid redundant calculations and waste of computing resources.

The present disclosure provides a data processing method based on a distributed system, a data processing device based on a distributed system, an electronic device and a computer readable storage medium, belonging to the field of computer technology. The method comprises: obtaining the number of nodes of the data processing node, obtaining the number of distributed models included in the first model for processing data; the first model is processed in parallel through the distributed system; the distributed model is a part of the first model; determine the target step according to the number of nodes and the number of models; the subtasks of different time steps in the data processing task are allocated to the corresponding data processing nodes; the processing results of the subtasks are interacted according to the target step, so that the data processing node executes the subtasks of the subsequent time steps according to the processing results. The present disclosure can effectively and reasonably process data in a distributed system.

This application relates to a method, apparatus, equipment, and storage medium for optimizing decision-making in post-disaster casualty rescue. The method includes: acquiring multidimensional physiological parameters and individual environmental factors of the casualties; using an improved START classification method and fuzzy comprehensive evaluation for initial injury quantification; and using a Markov state transition model to predict the injury evolution trend, generating a dynamic priority queue. A collaborative optimization model integrating rescue order, rescue route, and rescue method is constructed, aiming to maximize the expected number of survivors. A decomposition-coordination strategy is used to jointly solve the model, generating a globally optimized rescue plan. An event-driven mechanism is used to trigger rescheduling based on collected dynamic environmental data. Rolling time-domain optimization is performed based on the predictive control of the collaborative optimization model, and incremental updates are used to replan only the local plans affected by disturbances, outputting adaptively adjusted rescue instructions. This method can effectively improve the expected number of survivors and overall rescue efficiency.

This invention provides a conflict-aware transactional reconstruction method and apparatus for vehicular networks, belonging to the field of vehicular network configuration and scheduling control technology. It solves problems such as multi-node time slot conflicts, cross-device submission asynchrony, and inability to quickly roll back after update failures in existing vehicular network transactional reconstruction processes. The method includes: upon receiving a reconstruction request, generating a set of scheduling update operations based on the reconstruction request and the latest scheduling status table of each device node in the vehicular network; establishing a conflict graph and a dependency graph based on the scheduling update operation set; determining a set of transaction execution layers and the corresponding hierarchical execution sets for each transaction execution layer based on the conflict graph and dependency graph; and performing transactional reconstruction on each device node based on the set of transaction execution layers and the corresponding hierarchical execution sets, including differential patch pre-writing, atomic pointer switching triggered by a unified timestamp, and distributed consistency monitoring.

The application provides a method and system for checking the cross-modal information consistency of a maintenance plan based on a large model, and relates to the technical field of big data analysis. The method comprises the following steps: identifying a target maintenance plan through a power large model, determining key maintenance content, an unstructured proportion, and an attachment type complexity; obtaining a text data complexity and a business risk index based on key maintenance content analysis, as a first checking difficulty coefficient and a second checking difficulty coefficient; determining a third checking difficulty coefficient according to the unstructured proportion and the attachment type complexity evaluation; taking the expected review time limit of the target maintenance plan as a constraint, formulating an adaptive checking depth and an adaptive checking breadth based on the first checking difficulty coefficient, the second checking difficulty coefficient, and the third checking difficulty coefficient; and performing cross-modal information consistency checking on the target maintenance plan according to the adaptive checking depth and the adaptive checking breadth. The dynamic allocation of resources for checking the cross-modal information consistency of a maintenance plan is achieved.

The application discloses a kind of multi-radar resource management methods based on risk assessment, belong to radar signal processing technical field.First, the joint state space model of fusing motion state and classification state is constructed, state estimation is carried out using extended Kalman filter, and the misjudgment cost of target classification is modeled by introducing statistical risk function;Subsequently, the expected risk difference before and after observation is calculated, and the expected risk reduction value of the quantitative target current observation value is obtained;Boolean scheduling variable is introduced to construct scheduling optimization model, and the global ERR is maximized as objective function;Finally, local search and conflict resolution strategy are iteratively solved, and the optimal allocation result is quickly converged.The application realizes the scheduling target of key target priority observation, sensor resource efficient utilization and overall risk minimization.

This invention belongs to the interdisciplinary field of machine learning and data center thermal management, specifically disclosing a machine learning-based intelligent control method for data center cooling systems. This method configures each cooling unit as an intelligent agent with perception and decision-making capabilities, achieving distributed collaboration through a digital pheromone communication mechanism. It autonomously adjusts the opening of air and water valves based on pheromone concentration gradients and optimizes energy consumption and temperature deviation using a local reinforcement learning model. In the event of a fault, neighboring agents can automatically identify the anomaly and take over the cooling task. Through the above technical solution, this invention achieves sub-second real-time control, highly reliable self-healing operation, and a significant improvement in cooling energy efficiency.

The portable disassembly and transportation monitoring equipment placing device of the application comprises a power supply box, a continuous monitoring equipment fixing module, an external equipment suspension module, an unmanned aerial vehicle landing / laser radar installation platform and a module interfixing structure; the device can maximize the utilization of functions, save space, reduce costs, play a greater role in extreme conditions and harsh sites in the field, has the advantages of multi-mode power access, short time endurance, external expansion, high expandability of the module, high compactness of the structure, reduction of space occupation, high strength and impact resistance of the structure, high safety of the structure, certain waterproofness of the whole equipment, naked use in rainy and snowy weather, cost reduction, repeated use of each module, high universality, avoidance of cost and resource waste caused by non-universal structural parts and high stability of the system.

This invention provides a method for recovering silver from waste silver plating solution, belonging to the field of heavy metal industrial wastewater treatment technology. The invention involves adding sodium hypophosphite to waste silver plating solution containing complexed silver. After the sodium hypophosphite dissolves, the pH of the system is adjusted to alkaline. A reduction reaction is then carried out under heating conditions to generate elemental silver particles. This invention utilizes the in-situ generation of hydrogen free radicals from sodium hypophosphite under alkaline heating conditions to achieve direct reduction and complex breaking of stable silver nicotinic acid complexes and elemental silver conversion. This process is completed in one step, simplifying the traditional complex multi-step process of "oxidation-complex breaking-ion release-chemical precipitation" into a single reduction step, significantly shortening the treatment process and improving the reaction rate and treatment efficiency.

The application discloses a portable charging pile and belongs to the technical field of charging piles. The portable charging pile comprises a box body, a wall-penetrating terminal and an output connector are arranged on the box body. The wall-penetrating terminal and the output connector provide interfaces for external power supply access and power output, so that the portable charging pile can be freely moved to the vicinity of the external power supply for connection and charging operation. Further, a circuit breaker is arranged in the box body and is electrically connected with the wall-penetrating terminal. A charging assembly is also arranged in the box body, and the charging assembly comprises a charging module, the charging module has an alternating-current terminal and a direct-current terminal, the alternating-current terminal is electrically connected with the circuit breaker, can receive external three-phase alternating current and convert the three-phase alternating current into direct current suitable for charging of an automobile battery. The direct-current terminal is connected with a direct-current side assembly, and the direct-current side assembly is electrically connected with the output connector. The direct-current side assembly is used for conducting the direct current converted by the charging module, and finally transmits the power to a user load through the output connector, so that the charging function is realized.

This invention discloses a multifunctional electric firing device for unmanned equipment, characterized by reliable operation, convenient assembly, the ability to switch between firing and firing states, and a certain degree of anti-theft function. It includes a servo motor mounting base and a cover plate, which are located on both sides of the trigger guard of a firearm. The servo motor mounting base and cover plate are connected by clamping screws and clamped and fixed to the trigger guard. Servo motors A and B are mounted on the servo motor mounting base. A selector lever cover is mounted on the output shaft of servo motor A, and the selector lever cover is fitted onto the firearm's selector knob. The selector lever cover is used to rotate the firearm's selector knob. A servo motor arm is mounted on the output shaft of servo motor B, and the servo motor arm cooperates with the front part of the firearm trigger for pulling the trigger.

This application provides an embedded SDK that adapts to cross-framework systems, methods, media, program products, and terminals. Through framework environment adaptation, this application enables a single SDK to simultaneously support mainstream frameworks such as React, Vue, and Angular, significantly improving development efficiency and resource utilization. The framework type identification and adaptation mechanism allows developers to use the same SDK in different framework projects without needing to worry about underlying framework differences. Lifecycle adaptation effectively avoids resource leaks and memory overflow issues, and the lifecycle conflict detection and handling mechanism significantly reduces runtime errors caused by lifecycle problems. The standardized state management bridging layer improves the efficiency of state synchronization between the SDK and the host application, reducing the incidence of state inconsistencies. The pre-defined event handling abstraction layer eliminates differences in event handling between different frameworks, improving event response consistency and providing a smoother interactive experience for end users.

The application discloses a land use change detection system based on remote sensing cloud computing. The system comprises a remote sensing data acquisition module, a spectral shift compensation module, a response field construction module, a confidence evaluation module, a multi-scale segmentation optimization module and a sub-pixel boundary optimization module. The application firstly realizes accurate spectral alignment by using invariant ground feature spectral reference, then establishes a spatial confidence evaluation model through change direction consistency and amplitude dispersion analysis to filter core change pixels; and based on boundary stability and internal homogeneity, the optimal segmentation scale is automatically determined, and the change area boundary is accurately corrected through sub-pixel spectral decomposition technology, which significantly improves the reliability and accuracy of land use change detection, greatly reduces the false change detection rate, effectively enhances the boundary positioning accuracy, adapts to complex change scenes and improves the processing efficiency.

The application relates to the technical field of construction safety management, and discloses a power engineering construction safety management system, which comprises a real-time risk assessment scheduling unit, a forward-looking human factor risk perception unit and a risk simulation mapping unit. The real-time risk assessment scheduling unit is used for generating a safety state characteristic map based on heterogeneous safety data of a construction site, identifying a risk event of the construction site through the safety state characteristic map, and generating an intervention instruction and a resource scheduling scheme to optimize the construction site. The application can comprehensively capture multi-dimensional information of the construction site by collecting personnel biological characteristics, equipment operation logs, environmental indexes and work video streams and other heterogeneous safety data through a multi-modal perception unit, breaks the limitation of single and one-sided data collection in the traditional management mode, and enables management personnel to obtain more rich and comprehensive on-site safety information, so that the overall safety condition of the construction site can be more clearly understood.

The application provides an intelligent card acceleration method and system for the field of weather forecasting, and relates to the technical field of data processing. First, the application obtains historical observation data and historical prediction data in a prediction period; second, meteorological element sequences are extracted from the historical observation data; then, according to the spatial grid and time step information contained in the historical prediction data, the calculation scheduling scheme of the meteorological element sequences in the intelligent card is determined; then, the meteorological element sequences are processed according to the calculation scheduling scheme to obtain multi-dimensional data blocks; finally, the multi-dimensional data blocks are input into the intelligent card, and asynchronous pipeline calculation is performed according to the calculation scheduling scheme to obtain a prediction acceleration result. The technical scheme provided by the application realizes the deep binding of the calculation task and the hardware resource through data reorganization and instruction pre-arrangement, drives the intelligent card to process different time step data in an asynchronous pipeline mode, realizes the efficient cooperation of the data flow and the calculation flow, and improves the throughput efficiency of the meteorological numerical calculation.

The present disclosure relates to a data sending method and device, electronic equipment and storage medium. The method comprises: in the scenario of uplink resource allocation exception, selecting a plurality of target subcarriers from a plurality of alternative subcarriers, the alternative subcarriers being subcarriers available for sending data, the number of the plurality of target subcarriers being less than the number of the plurality of alternative subcarriers; and sending data based on the plurality of target subcarriers. In the method, each target subcarrier has more power to support data sending, reducing the decoding failure of the network device, reducing the bit error rate, improving the data sending efficiency, avoiding the problems of resource waste and data flow interruption, and improving the user experience.

This invention provides a method for accelerating real-time inference of multimodal large models, relating to the field of data processing technology. The method includes: Step 1, generating a minimum envelope ellipse using the peak point of the first visual attention weight, the second visual coordinate point, and the third visual association point as boundary points, and calculating the ratio of the area to the perimeter of the ellipse as a spatial clustering index. This invention effectively improves the efficiency, accuracy, and resource utilization of real-time inference of multimodal large models by selectively enhancing spatial features, evaluating multidimensional constraint computing power and dynamically scheduling resources, lightweight cross-modal fusion, and multi-step inference attention calibration, combined with real-time decision-making and full-process data-driven evaluation parameters and dynamic updates of the model library. This ensures the real-time performance and reliability of inference results, while continuously optimizing system computing power evaluation and model adaptation, making multimodal inference more aligned with the resource constraints of heterogeneous computing and the real-time and accuracy requirements of actual business operations.

This invention relates to the fields of computer vision and edge computing technology, and discloses a multi-computing-power collaborative video structured analysis method. The method includes: acquiring multiple raw video streams and synchronously decoding them; using gradient analysis to assess the quality of the decoded raw video streams and selecting a combination of preprocessing algorithms based on quality feature vectors; establishing a data transmission channel using an asynchronous communication protocol and a multi-level caching system; performing content complexity analysis and obtaining scheduling decisions through model matching based on the analysis; distributing the model and performing pipelined inference on the deployed model; fusing the pipelined inference results and verifying the consistency of the fused results; and optimizing system configuration parameters based on the video structured analysis results to achieve video structured analysis. This invention improves the real-time performance, accuracy, and system stability of video analysis.

This application provides an apparatus and method for preparing dissolved gas in insulating oil based on pressure adaptive control. The apparatus includes a gas source, a circulation chamber, a detection container, a detection sensor, a drive pump, and a control module. The gas source provides the target gas. The circulation chamber is selectively connected to the gas source. The detection container holds the insulating oil and is selectively connected to the circulation chamber, forming a circulation loop. The detection sensor monitors the pressure within the circulation loop. The drive pump is connected to the circulation loop and drives the target gas to circulate between the circulation chamber and the detection container. This application, through the circulation loop formed between the circulation chamber and the detection container, combined with the forced drive of the target gas by the drive pump, enables the gas to flow repeatedly within a closed system and fully contact the insulating oil, significantly accelerating the permeation process of gas molecules into the oil and greatly shortening the time required to reach the target concentration through dissolution.

A multi-agent context sharing method, system, and medium are disclosed, comprising: parsing the context content output by a first agent to generate corresponding metadata; associating the context content with the corresponding metadata and storing it in a distributed cache; establishing a topic set indexed by a session identifier in the distributed cache and adding the topic identifiers to the topic set; responding to a task to be executed by a second agent, obtaining the topic set corresponding to the current session identifier, reading the topic descriptions corresponding to each topic identifier in the topic set, and generating a list of topic descriptions; inputting the task to be executed and the corresponding list of topic descriptions into a large language model, receiving the topic identifier set returned by the large language model as the target topic identifiers semantically related to the task to be executed; and reading the corresponding context content from the distributed cache according to the target topic identifiers, associating the context content with the task to be executed, and inputting it into the second agent.

The application discloses a model training method, an object identification method, related equipment and a storage medium. The model training method mainly comprises the following steps: performing strategy hit detection on N object pre-detection strategies by using attribute description data of each initial object according to each keyword indicated by the N object pre-detection strategies; selecting, from a plurality of initial objects, initial objects corresponding to attribute description data that hits at least one object pre-detection strategy as sample objects; performing object type-based data clustering processing on the attribute description data of each sample object based on an object type corresponding to an object pre-detection strategy hit by the attribute description data of each sample object, to obtain a plurality of data sets; and performing model training on a benchmark object identification model by using each data set, to obtain a target object identification model under each object type. The application can improve the performance of the target object identification model and improve the accuracy of object identification.