69 results about "Data resources" patented technology

This application provides a pre-verification method and a computing device, applied to a computing device. The method includes: obtaining a verification request; the verification request is used to verify whether a first scenario has the preconditions for executing a business process; determining the first configuration information corresponding to the first scenario in a rule set configuration file based on the scenario identifier of the first scenario in the verification request; the rule set configuration file includes multiple scenario identifiers and configuration information corresponding to each scenario identifier; the first configuration information is used to indicate verification rules, data resource information on which the verification rules depend, and a result display template; obtaining object data on which the verification rules depend based on the data resource information; determining the verification result corresponding to the verification request based on the verification rules and the object data, and generating a result display interface based on the verification result and the result display template; the result display interface is used to display the verification result. This method helps reduce the operational complexity of the pre-verification process.

This invention provides a multi-task AI intelligent agent cost estimation system and method adapted to hydropower engineering cost estimation scenarios, relating to the field of hydropower engineering cost estimation technology. It utilizes a visual task interaction module to input basic hydropower engineering information and multi-task instructions. A multi-task AI intelligent agent decouples the input basic hydropower engineering information and multi-task instructions to obtain a task list and task priorities. Based on the tasks, it calls the corresponding data resource sub-libraries, and according to the corresponding calculation logic and priorities, combines the data resource sub-libraries to complete multi-task calculations, outputting the calculation results for each task. This invention solves the problems of information silos, low efficiency, and high error rates in existing cost estimation systems and is applicable to hydropower engineering cost estimation.

This application discloses a geographic data processing method, geographic data processing device, and computer program product, comprising: acquiring map information of a target visible area, the map information including location information of a target Internet of Things (IoT) device located within the target visible area; generating a plurality of target overlay images matching the target visible area based on the location information of the target IoT device; acquiring a target map image corresponding to the target visible area from map data resources; and adding the plurality of target overlay images to the corresponding positions of the target map image to complete the display of the target IoT device on the target map image.

The application discloses a kind of variable scale performance prediction methods of fuel cell system combined with neural network, construct the proton exchange membrane fuel cell model combined with neural network algorithm, realize the variable scale performance prediction of proton exchange membrane fuel cell system, and the proton exchange membrane fuel cell model includes air supply module, hydrogen supply module, water-thermal management module, battery stack module and neural network fitting module;Actual output power of fuel cell system is calculated;After all module combination connection, it is constituted into a variable scale numerical simulation model of proton exchange membrane fuel cell system combined with neural network algorithm.The application combines the advantages of neural network and mathematical modeling, uses limited amount of data resources, computer resources and time cost, completes high-precision simulation modeling of proton exchange membrane fuel cell, to provide guidance for the application of proton exchange membrane fuel cell in aviation field.

The application discloses a traffic law enforcement resource scheduling method and system based on multi-source real-time data, which comprises the following steps: acquiring multi-source real-time data, wherein the multi-source real-time data at least comprises law enforcement task data, law enforcement resource data and environmental support data; pre-processing and fusing the multi-source real-time data to construct a standardized scheduling data resource pool; based on the scheduling data resource pool, structurally analyzing the law enforcement task and determining a task priority sequence; based on the scheduling data resource pool, constructing a dynamic portrait of law enforcement resources; inputting the task priority sequence and the dynamic portrait into a preset intelligent scheduling decision model, and performing multi-objective optimization calculation combined with law enforcement compliance constraint conditions to generate a target scheduling scheme; and outputting the target scheduling scheme to perform dynamic scheduling of law enforcement resources. The traffic law enforcement resource is accurately matched, quickly responded and compliantly scheduled in a dynamic scene, and the law enforcement disposal efficiency and resource utilization rate are significantly improved.

This invention relates to the field of data governance technology, specifically to an intelligent inventory system for medical data resources. The system comprises: first, performing connection testing, collection scope detection, and access permission assessment on the target data source, and collecting medical metadata to form a metadata set; then, performing semantic association analysis and data lineage analysis on the metadata set, and generating classification results and corresponding evidence chains by combining data classification standards, data classification rules, and an intelligent recognition model; finally, outputting the data resource inventory results, and performing verification and feedback updates when inconsistencies are identified or when manual confirmation instructions are received. This invention can improve the completeness of metadata collection, classification accuracy, and result traceability.

This application discloses a new energy industrial control system platform with real-time early warning function applied in the sampling field. This system platform, through the setting of a zero-trust security model, is significantly different from traditional protection in that all entities in the network, regardless of whether they are on the external or internal network, are considered untrusted by default and require authentication and authorization. This allows for trust assessment and dynamic access control of all access from both inside and outside the enterprise, thereby achieving finer-grained access control, significantly reducing the network attack surface, and achieving the goal of protecting enterprise data resources. Furthermore, in conjunction with the setting of a network disconnection alarm strip, when access is made internally or externally or when a network attack occurs, the central controller controls the network disconnection alarm to inflate, disconnecting the network cable on the target access terminal, thus effectively preventing information leakage and improving confidentiality. Simultaneously, the audible and visual alarm is activated, providing real-time early warning of potential information leakage risks.

This application discloses a visualization method, system, and medium for bidirectional linking of data resource catalogs and storage. The method includes: obtaining the logical data catalog and physical storage structure, where the catalog contains logical objects and the storage contains physical objects; receiving the user-selected mapping mode and configuring corresponding mapping rules; constructing a bidirectional reversible mapping relationship between logical and physical objects based on the rules, including forward and reverse mapping functions; persistently storing the mapping relationship in a mapping relationship database and generating version information. This application overcomes the drawbacks of independent catalogs and storage, allowing business personnel to locate physical storage locations from the catalog and technical personnel to locate business items from fields. Version management enables change recording, retrospection, and accountability, laying a technical foundation for data lineage and collaborative governance.

This invention relates to a method and system for access control of power grid control data interfaces based on graph neural networks, belonging to the field of anomaly detection technology, and solving the problem of overly simplistic and mechanical anomaly detection in existing technologies. The method includes: constructing a graph model of the power grid control data system using user nodes, data interface nodes, and data resource nodes from historical data; obtaining the edge weight access strength from the user node to be analyzed to the target resource node based on the constructed graph model; performing three-stage corrections on the attention coefficients based on causal constraints, adversarial robustness, and interpretability based on a graph attention neural network, obtaining the embedding vector representations of the user node to be analyzed and the target resource node; predicting the access control probability score of the user node to be analyzed to the target resource node based on the embedding vector representation and the edge weight access strength; and assigning corresponding operation permissions to the user node to be analyzed based on the probability score. This invention can effectively resist potential attacks and significantly improve the efficiency of power grid access control.

The application provides a kind of city road network data resource directory generation method and system combined with service atlas, it is related to city traffic data management technical field, first access city road network service association conduction source and road network basic data generate service data association conduction pool;Then, based on the service association conduction logic deduces the road network data association derivative relationship, forms data association derivative network;According to the dynamic adaptation of data association derivative network, the dynamic directory unit is constructed by combining road network data;Based on the service conduction attribute of dynamic directory unit, the association conduction link is generated;Finally, the dynamic directory unit and the association conduction link are integrated to form a closed-loop city road network data resource directory that can be dynamically updated, which effectively improves the management efficiency and utilization value of city road network data resources.

The present disclosure provides an identity identification generation method, a device, a storage medium, and a computer program product. The method comprises: receiving first data feature information of a data resource sent by a second network node; determining, on the basis of the first data feature information, first identification information corresponding to the data resource, and sending the first identification information to the second network node; and receiving a data resource sent by the second network node and global identity identification information corresponding to the data resource, wherein the global identity identification information is generated by the second network node on the basis of the first identification information and second data feature information of the acquired data resource, and the global identity identification information is used for managing and controlling the data resource during data resource circulation.

The application relates to the technical field of edge computing storage, and discloses a distributed data storage dynamic optimization method based on edge computing. The method acquires data storage state data and data access request data of distributed edge nodes, and constructs a data resource distribution model according to the data; the method combines preset optimization conditions with the model to determine a system resource early warning state, enters a dynamic optimization mode when the early warning is triggered, and generates a data migration priority queue, and executes a data migration operation according to the queue; the method updates the data resource distribution model according to a migration result, determines a system resource exit state based on the updated model, exits the dynamic optimization mode when the exit state is triggered, and transmits the optimized storage state data to a central management system. The method dynamically adjusts data distribution by real-time sensing of node states and access demands, adapts to edge node heterogeneity and data access dynamics, and improves distributed data storage efficiency.

The application discloses a data resource scheduling method based on multi-agent game cooperation, which comprises the following steps: collecting running state data to generate scheduling state data set; constructing a hierarchical agent structure based on the scheduling state data set and generating an initial parameter set; obtaining an initial strategy network set based on the hierarchical agent structure and the initial parameter set; freezing the current strategy parameters based on the initial strategy network set to obtain a local Nash response strategy combination; constructing a joint optimization objective function based on the local Nash response strategy combination and the initial strategy network set; outputting an updated strategy network set by using a multi-agent reinforcement learning algorithm; collecting feedback information to form scheduling execution feedback data; and repeatedly executing an iteration process based on the scheduling execution feedback data and the updated strategy network set. The hierarchical agent game reinforcement learning realizes the cooperative scheduling of data resources.

This invention provides a method for optimizing and constructing a human-machine collaborative full-process quality management system, comprising: real-time collection of multi-source heterogeneous industrial data from each process node in the production process to construct a quality data resource pool for human-machine collaboration; constructing a multi-process quality deviation coupling and propagation model based on a deviation propagation matrix, and introducing an expert experience correction mechanism to form a human-machine collaborative deviation propagation model, so as to trace and quantitatively characterize the propagation of quality deviations in the entire process chain; constructing an industrial digital twin for full-process quality management, generating collaborative optimization decision schemes through quality risk quantitative assessment and human-machine two-way decision fusion, and implementing dynamic adaptive control of process parameters throughout the entire process; and constructing a full-process quality feedback mechanism and a continuous iterative optimization mechanism. This invention aims to solve the technical problems in the prior art where quality prediction models rely on training data, expert experience is difficult to quantify and integrate, and the full-process deviation propagation mechanism is missing.

The application discloses a data read-write processing method and an electronic device in a storage system, relates to the technical field of computer storage, and realizes the asynchronization and isolation of read-write operations by constructing a three-layer resource processing architecture, decoupling host read-write requests into independent controllable processing stages. The first resource focuses on recording metadata, the second resource serves as a temporary carrier for data transfer, and the third resource serves as a persistent cache management center. This architecture enables the write operation to return a response to the host as soon as the data reaches the second resource, greatly reducing the write delay; the read operation realizes non-blocking access through the concurrent control mechanism of the third resource. Overall, the response speed and throughput of the storage system are improved, and the performance bottleneck of mutual blocking of read and write due to competition for the same data resource in the related architecture is solved.

The application discloses a kind of seismic remote sensing data management method and system, it is related to earth science information technology field, including, access multi-source seismic remote sensing data, define the standardized metadata description format to each type of multi-source seismic remote sensing data, store multi-source seismic remote sensing data and corresponding standardized metadata description into data resource library;Real-time monitoring of earthquake event information, when target earthquake event is captured, the epicenter of target earthquake event is generated as dynamic space-time range, according to dynamic space-time range, aggregate multi-source seismic remote sensing data from data resource library, and construct dynamic data cube for target earthquake event;Based on dynamic data cube, generate data product through data processing workflow, record the complete processing process log of data product.The application forms integrated management scheme from data intelligent aggregation, product quality controllable to problem accurate traceability and closed-loop correction.

The application discloses a data read-write processing method and an electronic device in a storage system, relates to the technical field of computer storage, and realizes the asynchronization and isolation of read-write operations by constructing a three-layer resource processing architecture, decoupling host read-write requests into independent controllable processing stages. The first resource focuses on recording metadata, the second resource serves as a temporary carrier for data transfer, and the third resource serves as a persistent cache management center. This architecture enables the write operation to return a response to the host as soon as the data reaches the second resource, greatly reducing the write delay; the read operation realizes non-blocking access through the concurrent control mechanism of the third resource. Overall, the response speed and throughput of the storage system are improved, and the performance bottleneck of mutual blocking of read and write due to competition for the same data resource in the related architecture is solved.

This application discloses a data processing system, method, apparatus, storage medium, and electronic device, relating to the field of data processing technology. The data processing system includes a case information push module, a photo data storage module, and a remote inspection and damage assessment module. Specifically, the case information push module first determines the insurance company covering the vehicle based on the information of the parties involved and the vehicle, and then pushes the case information. The photo data storage module classifies and stores photos and videos of the accident scene and the dismantling and inspection site based on the case information. The remote inspection and damage assessment module performs remote damage assessment based on the photos and videos of the accident scene and the dismantling and inspection site. Compared with existing technologies, this application comprehensively applies cloud computing and digital technologies to achieve efficient and accurate online damage assessment of vehicles involved in traffic accidents, thereby improving the effective connection and use of data resources from all parties, enhancing the accuracy of materials related to traffic accident handling, and improving accident handling efficiency and user experience.

The present application relates to resource management technical field, especially to a kind of business environment data resource management platform.The present application includes application security module, data security module, host security module, network security module and boundary security module;The application security module is responsible for the security protection of audit log and system application;The data security module realizes data backup security by timing increment and full data backup;The host security module provides security protection for server equipment through various protection measures;The network security module ensures the safety of network channel environment, and realizes the monitoring of network channel security protection;The boundary security module ensures the security of boundary and audits the tracking of intrusion detection event.The purpose of the present application is to provide a kind of business environment data resource management platform, to protect the safety of network channel, network channel environment, and handle intrusion event while protecting data security in time.

This invention relates to a standardized method and system for discovering clues to ecological and environmental problems. It addresses the technical problems of the lack of standardization and low processing efficiency in existing clue discovery methods. The method includes: ranking and sampling deterioration trends to determine the final monitoring unit; generating standardized comparison data of spatial constraints and prohibited issues based on geographic vector data and prohibited issues in the zoning control requirements list; conducting compliance verification of dynamic map patch resources based on the standardized comparison data, and identifying suspected violation problem patches through semantic matching and spatial relationship verification; and solidifying evidence based on the suspected violation problem patches corresponding to the prohibited issues and the comparison data resources, and generating a problem clue report through standardized output. This establishes standard operating procedures, achieving the organic integration of business flow, data flow, and rule flow, and is applied to ecological and environmental zoning control operations, realizing the process-oriented, standardized, and efficient discovery of problem clues, and improving the consistency and reusability of regulatory results.

This invention discloses an AI-based intelligent system for identifying security risks in smart cities, belonging to the field of smart city security technology. The system includes: a data acquisition and fusion module, a spatiotemporal anomaly identification module, a physical verification module, an AI prediction and early warning module, and a response and linkage module. By integrating video surveillance, IoT sensors, geographic information, and meteorological data, this invention constructs a security data resource pool covering the entire city, breaking the limitations of traditional security systems that rely on a single data source. Based on a spatiotemporal curvature attention model, the system can deeply extract spatiotemporal features from video streams, accurately identify abnormal behaviors and scenes, and generate a highly reliable list of anomaly samples. This combination of multi-source data fusion and intelligent analysis not only improves the comprehensiveness of anomaly detection but also significantly reduces the false alarm rate, providing more reliable technical support for urban security.

The present application relates to the technical field of data generation for sparse scenes, and discloses a data set generation method and system for a sparse scene. The method comprises: inputting an actually acquired target sparse scene image into a target detection model to obtain bounding boxes of a target foreground and a background; using the bounding boxes of the target foreground and the background as prompt words for a preset large-scale segmentation model to perform model inference to respectively obtain masks of the target foreground and the background, and, on the basis of the masks of the target foreground and the background, obtaining coordinate information of a target foreground image and a background region; and using an adaptive image fusion technique to integrate the coordinate information of the target foreground image and the background region to generate a new target sparse scene image, and adding the newly generated target sparse scene image to a training data set of the target detection model. The present application only requires a small number of target objects and background images to generate a large number of new high-quality images, thereby solving the problem of scarce scene data, and providing rich data resources for subsequent model training.

The application discloses a complex gesture behavior analysis method based on machine learning, and relates to the technical field of gesture recognition.The application solves the technical problem that there is a lack of unified and effective integration and analysis means, the efficiency is low when processing large-scale gesture data, and it is difficult to realize accurate and comprehensive gesture behavior understanding and interpretation in actual application.The application can accurately extract similar gesture data from a large amount of complex gesture data through a similarity calculation and screening method, and further combines the similar gesture data to obtain same-type gesture data and same-type feature data, effectively integrates data resources, improves the utilization efficiency and analysis value of the data, can better cope with the diversity and complexity of gesture data, reduces the subjectivity of manual intervention and feature design, and thus provides a more representative and accurate data basis for subsequent model training.

This invention discloses a method for accelerating the development of PDK parameterized units for large-scale language models, relating to the field of integrated circuit layout design automation. It solves the technical problems of low development efficiency, unstable quality, and difficulty in knowledge transfer associated with traditional PDK parameterized unit development. The method includes: S11: collecting data resources and preprocessing them to obtain the training dataset and auxiliary database required for the model; S12: selecting a model and training and optimizing it; S13: merging and lightweighting the weights of the trained and optimized model; S14: locally deploying and applying the merged and lightweighted model; S15: validating and optimizing the locally deployed and applied model to obtain feedback data, and inputting the feedback data back into S11 for re-collection. This invention can effectively shorten the code generation time of PDK parameterized units and significantly improve code development efficiency for PDK parameterized units with complex structures.

This invention provides an optical disc storage device for hierarchical data resource management, comprising: a storage box with multiple sets of symmetrically formed sliding grooves on its inner side; a mounting plate with sliders symmetrically fixed on both sides, the sliders slidingly embedded in the sliding grooves, and a placement groove on the inner side of the mounting plate; an optical disc body installed inside the placement groove; and a ejection assembly including a protrusion, a second spring, and a receiving sleeve, the protrusion being fixedly installed in the middle of the inner side of the placement groove. This invention allows the optical disc body to be placed on the receiving sleeve, and then the receiving sleeve is pressed down, causing it to be magnetically attracted and fixed, thereby moving the optical disc body into the placement groove for storage. By pulling the receiving sleeve, it is released from the magnetic attraction, and the elasticity of the second spring allows the receiving sleeve to remove the optical disc body from the placement groove, effectively preventing the optical disc body from touching the mounting plate during retrieval and thus avoiding damage to the optical disc body.

This invention provides a control method for a multi-core processor. The method includes: a master core monitoring a slave core in real time; when the slave core is in a cache coherence failure state, saving the slave core's execution information and sending a reset command to the slave core; the slave core responding to the reset command sent by the master core repairing its cache unit according to the standby command in the storage unit; and after the repair is completed, entering a sleep state; and the slave core responding to a wake-up command sent by the master core resuming execution of its original task based on the execution information in the wake-up command. This invention ensures the normal access and use of cached data resources by the slave core, improving processor operating efficiency. Furthermore, this solution eliminates the need to pre-define fallback paths to the Uncached area for various potential error scenarios, resulting in lower software development costs.

The embodiment of the present specification provides a data management and control method, system and device, electronic equipment, storage medium and program product. The scheme provided by the embodiment is that, after receiving a use application for a target data resource initiated by a data user, the use application is checked for security based on a digital contract related to the target data resource, to check whether the use application meets the security constraints specified in the data management and control policy in the digital contract; and after the security check is passed, the data user is allowed to access and use the target data resource. The above-mentioned digital contract includes a data management and control policy configured for at least one data resource (one of which is the target data resource). The data access control policy included in the data management and control policy is used to specify the security constraints that need to be met for accessing the data resource, and the data use control policy included is used to specify the security constraints that need to be followed for using the data resource after obtaining access permission.

The application discloses a data distribution method and device, equipment, medium and product, and relates to the field of resource distribution algorithm, and determines a user trust graph based on a communication request initiated by a request initiator to a request receiver, initial trust values of the request initiator and the request receiver, and a user library; determines a target trust value by updating the initial trust values in the user trust graph in real time based on a distribution task identifier, user registration information of the request initiator and the request receiver, a transfer request between the request initiator and the request receiver, and a third-party database; and distributes a to-be-distributed object to the request initiator and the request receiver based on the target trust value and a trust value threshold. By introducing the user trust graph on the block chain and the real-time updating mechanism, the technical scheme can ensure the reasonable distribution of a large amount of data resources and solve the problem of ensuring the effective distribution of data resources in a high-concurrency scenario.

This invention relates to the fields of data circulation and artificial intelligence technology, specifically to a method and system for optimizing data circulation in a trusted data space combined with AI. It addresses the problems of unintelligent data circulation paths, difficulty in balancing security and efficiency, and fragmented value creation chains in a trusted data space environment. The system includes a data provider connector, a data user connector, and a trusted data space service platform. The specific method is as follows: S1: Construct and dynamically update a global intelligent data resource catalog; S2: Perform dynamic negotiation and generate executable digital contracts; S3: Construct a federated data sandbox and execute computational tasks; S4: Perform real-time monitoring, anomaly analysis, and dynamic risk intervention. This invention achieves a dynamic optimal balance between data circulation efficiency and security, significantly reducing operating costs and risks, establishing an intelligent closed loop from data resources to AI value creation, and improving data configuration efficiency and empowerment effects.

The application discloses an aquatic pet cloud primary screening and on-site treatment whole-cycle management system and method based on artificial intelligence, which comprises an offline service terminal used for collecting multi-modal data of aquatic pets and performing on-site service operations; a cloud hub system is in communication connection with the offline service terminal through a mobile communication network, is used for receiving offline service terminal data and performing data processing, decision-making and resource scheduling processing, and comprises an AI computing cluster, which is used for analyzing the multi-modal data to generate diagnosis suggestion information; an intelligent service scheduling module is used for acquiring the diagnosis suggestion information and on-site resource states fed back by the offline service terminal, generating and issuing a service execution scheme to the offline service terminal; and the offline service terminal receives the service execution scheme and performs corresponding on-site service operations. The application constructs an aquatic pet multi-modal AI primary screening diagnosis module based on data resources accumulated by a national aquatic animal pathogen library, and significantly improves disease identification accuracy and diagnosis efficiency.