649 results about "Data export" patented technology

The embodiment of the invention provides a distributed server cluster log processing method and device, and the method comprises the steps: constructing a distributed server cluster log collection network, and dynamically distributing collection tasks through a load balancing scheduling center. An incremental data acquisition channel is designed, efficient transmission is realized by using a websocket long connection pool, and the transmission efficiency is optimized in combination with real-time compression coding and a repeated data detection mechanism. An intelligent log analysis model is constructed, the intelligent log analysis model comprises an anomaly detection sub-model, a mode recognition sub-model and an event association analysis sub-model, anomaly score calculation, log classification labeling and multi-dimensional association analysis are achieved based on a deep learning method, and visual display and data export functions are provided. According to the method, the defects of the traditional technology in the aspects of distributed acquisition, data transmission, intelligent analysis and the like are effectively overcome, and the performance and practicability of a log processing system are remarkably improved.

The invention discloses an automatic three-dimensional reconstruction method and system based on power transmission corridor point cloud. The method comprises the following steps: acquiring data and exporting point cloud data; noise points, outliers and ground points are removed from the acquired point cloud data of the power transmission corridor, and down-sampling is performed on the point cloud with a large data volume; performing clustering segmentation on the preprocessed point cloud of the power transmission corridor, positioning the position of a tower, determining a point cloud range of a power line, and removing point clouds of other objects on the ground; aiming at the structural characteristics of a power line and an insulator in the power transmission line, extracting point clouds of the power line, the insulator and a tower by adopting a geometric constraint principal component analysis (PCA) algorithm; performing automatic geometric model reconstruction on the tower, insulator and power line point clouds according to different reconstruction rules to generate each module grid model; and transforming the grid model of each module, restoring the grid model to the original position of the point cloud, and generating a power transmission line digital twin model conforming to the real size. According to the method, automatic segmentation, classification and real-time reconstruction can be accurately carried out on the point cloud of the power transmission corridor.

The invention relates to the field of Web application, in particular to a tree structure data dynamic management method based on node hierarchical attributes and recursive updating. Comprising the following steps: S1, constructing a tree structure data system, and endowing each node with a hierarchical attribute which is used for identifying position information of the node in a tree structure; s2, receiving an operation instruction of a user for the tree structure data, wherein the operation instruction comprises node adding, node batch deleting, node moving, data exporting and importing, node querying and node quantity counting; and S3, according to different operation instructions, executing corresponding processing logic: based on node hierarchy attributes, applying a recursive update mechanism to realize dynamic management of tree structure data, and ensuring data consistency and accuracy.

The invention belongs to the technical field of automatic driving automobile testing, and particularly relates to an intelligent automobile key scene optimization generation method based on large model knowledge guidance. Comprising the following steps: S1, constructing a knowledge expression module, and designing a knowledge result, a large language model application mode and a dynamic updating process from scene theoretical knowledge and scene exploration knowledge; s2, constructing a parameter optimization module, designing a multi-stage optimization strategy including global exploration, local optimization and spatial pruning, and fusing the multi-stage optimization strategy with the knowledge model; s3, establishing a simulation test module, and based on a Carla simulation platform, establishing a scene establishment component, a to-be-tested system component, a simulation execution component and a data export component through LLM-Agent; s4, selecting a model and pre-training a large language model, designing a model selection index and selecting the model; and S5, constructing an evaluation and memory module, evaluating a test result, and storing all test and knowledge data. According to the method, the key scene of the intelligent automobile can be quickly generated through mutual combination of the knowledge model, the large language model and optimization search.

The invention discloses a tunnel face back break visual analysis method based on laser point cloud, and the method comprises the steps: carrying out the scanning operation of a tunnel through a laser scanner, and collecting the specific original rock three-dimensional point cloud model data in a tunnel construction circulation process; exporting the acquired original rock mass three-dimensional point cloud model data, and performing denoising preprocessing on the original rock mass three-dimensional point cloud model data to obtain tunnel rock mass three-dimensional point cloud model data; the rock mass three-dimensional point cloud model data also need to be subjected to space compression processing, so that the quality of the rock mass three-dimensional point cloud model data is improved; based on the rock mass three-dimensional point cloud model data, a tunnel actually-measured excavation section after construction is obtained; and weighting and calculating tunnel over-excavation and under-excavation values based on the point-to-pole distance between the tunnel design section and the tunnel actually-measured excavation section. According to the method, the back-break depth is directly calculated through the point cloud data and is bound as the point cloud attribute, so that the analysis efficiency and the result intuition are remarkably improved.

A communication system includes a server operable to communicate with vehicles located remote from the server. The server is operable to receive an indication of an event that occurs remote from the server. The indication identifies a location associated with the event. The server, responsive to receiving the indication of the event, establishes a geofence that bounds the location associated with the event. The server transmits information pertaining to the established geofence to at least one of the group consisting of (i) a vehicle within the established geofence and (ii) a vehicle within a threshold distance of the established geofence. When a vehicle that received the transmitted information is within the established geofence, the server receives, from the respective vehicle within the established geofence, information derived from sensor data captured by at least one sensor of the vehicle within the established geofence.

The embodiment of the invention relates to the technical field of information, and discloses an intelligent data acquisition method and device, a medium and a product, the intelligent data acquisition method comprises the following steps: acquiring artificial demonstration data through an exoskeleton system, the artificial demonstration data comprising video stream data, motion data and force sense data; importing the video stream data into a first large language-vision model, segmenting the video stream data into a plurality of independent task fragments, and generating independent task fragment descriptions; importing the independent task fragment description into a large language model, and generating a task label based on natural language description; and exporting the independent task segments, the task labels and the corresponding motion data and force sense data to generate intelligent data. Therefore, a low-cost, high-efficiency and large-scale intelligent data acquisition and processing method is established, and automatic conversion from human operation data to high-quality VLA training data is realized.

The invention provides a method and system for dynamically exporting Excel based on asynchronous streaming block data, and belongs to the technical field of large data volume export. Comprising the following steps: receiving a user export request, and generating a unique request ID; an export task is generated based on the export request, a task ID is returned, and an asynchronous response is made; submitting the task to a thread pool queue, and obtaining block data from a database in batches through streaming query; wherein the core thread count and the maximum thread count of the thread pool are adjusted based on a dynamic resource allocation method, and load change is smoothed in combination with a sliding window algorithm; writing the block data into an Excel file batch by batch by adopting a streaming writing technology; and after the task is completed, pushing a notification to the user side. According to the method, the rapidity, the availability and the safety during data export can be ensured when large data volume export is performed.

The invention provides a storage network planning method and a logistics simulation system for energy enterprise materials, and relates to the field of energy enterprise material planning, user data is received through an interactive interface, and the user data is pre-processed and stored in a database; after a user triggers a solving instruction, a back end calls a solver to construct a mixed integer programming model, a warehouse network layout scheme is iteratively optimized based on a constraint satisfaction algorithm, and a result is stored back to a database; the support visualization module generates a multi-dimensional chart to display data before and after optimization, provides a data export function to output a portable document according to a preset format, integrates business rules, algorithm solution and visual interaction, supports dynamic optimization and rapid verification of an energy storage network, realizes dynamic collaborative optimization of storage site selection, inventory decision and transportation planning, and improves the efficiency of the energy storage network. And through introduction of multi-scene and multi-dimensional simulation analysis capability, an integrated optimization and simulation platform and a human-computer interaction friendly visual decision-making interface are constructed.

The invention discloses a method for constructing a 3D Tiles data structure. The method comprises the following steps: acquiring data of different sources and different types; constructing a corresponding data storage table for each type of data, reading information of each type of data, and storing the information in the corresponding data storage table; converting the coordinate system of each type of data into the same coordinate system; exporting each type of data after coordinate system conversion as a glTF model; the method comprises the following steps: constructing a 3D Tiles extension data structure consisting of an index file and a data file, adding schema attributes in the index file, and defining a plurality of data types in the schema attributes; adding a minimum unit attribute field in the root attribute of the index file to record a corresponding data type and an attribute value; and based on the constructed 3D Tiles extension data structure and the glTF model of each type of data, integrating each type of data into 3D Tiles format data.

In various examples, occupant assessment using multi-modal sensor fusion for monitoring systems and applications are provided. In some embodiments, an occupant monitoring system comprises an occupant evaluation function that may predict at least one characteristic representative of a size of the occupant. The occupant evaluation function may include a first processing path that generates a representation of features corresponding to the occupant based on optical image data, and a second processing path that performs operations to determine a depth corresponding to the one or more features based on depth data derived from the optical image data and the point cloud depth data. In some embodiments, a three-dimensional pose detection model generates a three-dimensional pose estimate of the occupant using the optical image data, and the three-dimensional pose estimate is scaled to an absolute pose based on the point cloud depth data.

The embodiment of the invention provides a data processing method and a hardware fault prediction method. The method comprises the steps that when it is monitored that a preset trigger event occurs, a data export module obtains first data from a target register; wherein the preset trigger event is used for triggering the data exporting module to execute data exporting operation; the target register is a register which needs to export data in the plurality of registers; and the data export module stores the first data into the static memory, so that the processor reads the target data from the static memory and sends the target data to firmware in communication connection with the system-on-chip. Obtaining to-be-analyzed data of the target system-on-chip; and inputting the to-be-analyzed data into a preset fault prediction model to obtain fault prediction information corresponding to the target system-on-chip. The method is used for achieving the effects of completely storing real-time changing data in the register and carrying out hardware fault prediction according to the changing data in the register.

The invention discloses a data exporting method and device based on EasyExcel annotations and a storage medium, and belongs to the technical field of computers. The method comprises the following steps: acquiring a data export template, wherein the data export template defines a data export structure; under the condition that the data export template meets a preset condition, generating a receiving object comprising the annotation according to the data export template; the receiving object comprises an object class bearing data, and the annotation is used for controlling the export behavior of the data; assembling the data to be exported into a receiving object; and exporting the to-be-exported data in the receiving object into the data exporting template based on the annotation. Through the predefined data export template, when the data export template meets the preset condition, the receiving object containing the annotation can be automatically generated, a developer only needs to pay attention to data assembly and business logic, data export can be achieved, a large number of tedious redundant codes do not need to be written, the workload of manual coding is reduced, and the data export efficiency is improved. And the data export efficiency is improved.

A cloud-based edge-as-as-service (EaaS) system allows edge gateways to be easily configured and deployed on the cloud for collection, contextualization, and egress of industrial data to downstream applications, including analytic applications, work order management systems, or visualization systems. The EaaS system uses predefined device profiles to automatically discover relevant data items on plant floor devices and present these data items to a user. Model configuration interfaces served by the EaaS system allow the user to map selected data items to predefined models for organizing or contextualizing the selected data, and for egressing the contextualized data to the target applications. These model configurations can be deployed on the cloud platform as edge gateways that use the resulting information models to collect and contextualize relevant items of device data during runtime and to export the modeled data to the target application.

The invention provides a data dynamic exporting method and system based on template configuration. The method comprises the steps that a data exporting request for exporting data in a data source in a report form is obtained; verifying the user permission data in the request to generate a verification result; when the verification result is that the verification is passed, generating a dynamic SQL statement according to template metadata corresponding to the template classification data; executing paging query according to the dynamic SQL statement, and performing data processing and streaming writing on data acquired from a data source to which data to be exported belongs in batches; and when the paging query is finished and data processing and streaming writing of the data obtained in the last batch are completed, generating a temporary file, and returning a downloading link to the client for triggering downloading of the data in the temporary file and generating a report corresponding to the data export request. According to the method and the system, the template adjustment efficiency is improved, the memory consumption is reduced, and the big data export success rate is greatly improved.

The invention discloses a data outbound-oriented low-overhead multi-source risk information acquisition method and system in the technical field of data cross-border. The method comprises the following steps: S1, intelligent screening of main business risk acquisition points: based on dynamic risk entropy, business criticality and flow fluctuation are taken as screening key acquisition points; s2, linkage of communication behavior classification and risk assessment: capturing key acquisition point communication metadata based on an improved random forest algorithm, and realizing abnormal behavior detection and classification through a cooperative mechanism of feature extraction, model training, dynamic classification and feedback optimization; s3, dynamically regulating and controlling an acquisition strategy and a transmission queue, namely dynamically regulating the acquisition granularity and the transmission priority according to the risk level and the queue load, and balancing the resource overhead and the monitoring requirement; and S4, sample bias correction and closed-loop optimization: correcting sample distribution deviation through inverse probability weight, and feeding back a false alarm rate and a load state to acquisition point selection and model parameters.

The invention discloses a multi-field coupling concrete dam parameter intelligent inversion method, system and device based on deep learning and a medium, and belongs to the technical field of dam engineering safety monitoring and computational mechanics crossing. The geometry and boundary modeling unit is used for uniformly expressing a dam body-dam foundation geometric region and a boundary type; simultaneously representing a state field and a parameter field by utilizing PINN inversion, calculating a physical residual error, and implementing parameter physical feasibility constraint and prior regularization; the organization optimizer, residual drive sampling and weight self-adaption are used for training scheduling, and result review, visualization and data export are carried out through the verification and output unit. According to the method, end-to-end parameter field inversion is realized on the premise of not depending on frequent mesh generation, the calculation cost of multiple forward modeling is reduced, the non-uniqueness of inversion is inhibited, and the method has higher recognition capability for engineering concerned areas such as permeation channels and degraded zones.

Systems and methods for determining uniqueness of device identifiers are provided. The uniqueness of a device identifier may be indicated by a device quality score or grade that is calculated based on a plurality of parameters associated with a device identifier as well as evaluation rules derived based on historical data. The plurality of parameters may be associated with a network event or transaction associated with the device identifier. The evaluation rules may be derived using machine learning techniques. Based on uniqueness of a device identifier, a suitable action or measure may be taken.

The invention discloses an HTTP (Hyper Text Transport Protocol) text restoration method based on DPDK (Data Platform Development Kit), which relates to the technical field of computer networks, and adopts a multi-process decoupling architecture to respectively run processes such as flow collection and protocol analysis, fragmentation recombination and text restoration, formatted message splicing, text restoration timeout waiting and the like in independent CPU (Central Processing Unit) cores; and efficient and lock-free data transmission is carried out by using a ring mechanism of the DPDK. Different from a traditional memory splicing scheme, the data offset is calculated based on the TCP serial number, the load content is directly written into the corresponding position of the file, the problems of message disorder, packet loss, retransmission and the like are effectively solved, an atomic renaming mechanism from the file ID1 (intermediate state) to the file ID2 (complete state) is adopted, and accurate migration of the file state is ensured. Besides, the invention innovatively provides a bidirectional asynchronous scheduling mechanism based on data export and text restoration state monitoring, so that the data export process can continuously keep high throughput, and the overall processing capacity of the system is ensured.

The invention relates to the technical field of message management, in particular to a log management tracking method based on message middleware. The method comprises the following steps: constructing a message sending log recording mechanism so as to write a message generation log table when a message producer sends a message to message middleware; constructing a message consumption log recording mechanism at the message consumer node to perform repeatability verification when the message is transmitted to the consumer node through the message middleware, and transmitting the message to the actual service processing logic; updating the message state in the message consumption table after the execution of the business processing logic is completed, and generating an error processing task record at the same time; constructing a distributed log aggregation index system to establish an associated index, and forming a message full-link tracking view; and constructing a visual log management interface based on the message full-link tracking view to provide log retrieval, log data export and abnormal message retransmission control functions. According to the invention, efficient management and accurate tracking of the message middleware log can be realized.

Embodiments of the invention relate to the technical field of data processing, and disclose a PDF document generation method and apparatus, an electronic device and a storage medium, the method comprising: obtaining first page data, the first page data being determined by first HTML data input by a user on a target layout style; according to the first page data, a double linked list is constructed, and nodes in the double linked list are used for storing types, contents and styles of HTML elements; converting nodes in the double linked list into document object model (DOM) elements; and generating the PDF document according to the DOM element. By applying the technical scheme, the accuracy of exporting the HTML data into the PDF document can be improved.

The embodiment of the invention provides a data synchronization method and device, electronic equipment and a storage medium, and belongs to the technical field of data synchronization. The method comprises the following steps: if a data import end and a data export end are in an abnormal connection state, mounting a mobile device to the data export end, performing information query at the data export end according to a preset export rule, obtaining a query result, generating target migration data according to the query result, and transmitting the target migration data to the mobile device; and mounting the mobile device to a data import end, and importing the target migration data to the data import end through a preset import rule. According to the scheme provided by the invention, the data import end and the data export end synchronously update the data in time under the condition that the network is limited, so that the data synchronization efficiency and reliability are improved.

The invention, which relates to the technical field of small watershed data management, discloses a multi-source data small watershed air-ground integrated intelligent monitoring and management system comprising a satellite remote sensing data acquisition subsystem, an unmanned aerial vehicle monitoring subsystem, a ground monitoring subsystem, a multi-source heterogeneous data fusion subsystem and a data intelligent supervision platform. The satellite remote sensing data acquisition subsystem is used for carrying out large-scale hydrological and ecological monitoring by utilizing a satellite remote sensing technology, and carrying out accurate retrieval according to a geographic position, a time range and a sensor type so as to find a specific data set meeting requirements; a user is allowed to browse a remote sensing image online, zoom-in and zoom-out operation is carried out on a specific area, meanwhile, multiple kinds of layer information are overlaid, the layer information comprises a topographic map, an administrative map and a road traffic map, and data export options are arranged in a subsystem of the system and comprise an original data file, a preprocessed product and a customized data packet.

Provided is a policy information processing device capable of discriminating factors contributing to the effectiveness of a policy. 【Solution means】 A policy information processing device including a processor for processing information related to a policy, wherein the processor obtains first policy data related to one or more first policies, environmental data related to the environment in which the first policy was executed, person data related to the people present in the environment at the time of execution of the first policy, and evaluation data related to evaluation indicators of the execution result of the first policy, and obtains first policy result data including the same, and generates a first learning model generated based on at least a part of the first policy data and the first policy result data, and based on the second policy data related to the second policy, derives factor data related to factors for improving the evaluation indicators of the execution result of the second policy and contribution degree data related to the contribution degree of the factor data to the evaluation indicators of the second policy, to generate a first learning model, obtains the second policy data, and based on the second policy data and the first learning model, derives the factor data and the contribution degree data of the second policy.

An example operation may include at least one of producing, by a class-conditioned sample generator executing on at least one processor communicatively coupled to a memory on a host platform, a synthetic feature set based on a label sequence and class information derived from received data, transmitting, by the host platform, a finalized synthetic sample to a computing device when the synthetic feature set satisfies a fidelity threshold, generating, by the computing device, a fidelity score based on a comparison of the finalized synthetic sample to the label sequence and the class information, retraining, by the computing device, the class-conditioned sample generator based on the fidelity score, and validating, by the computing device, the class-conditioned sample generator by transmitting a test prompt to the host platform, receiving a synthetic response generated by the class-conditioned sample generator, and comparing the synthetic response to previously stored synthetic data to validate the class-conditioned sample generator.

The present disclosure relates to the field of signal acquisition, and in particular, to a system and method for high-density electromyographic signal synchronous acquisition. In the system, a signal acquisition module and a base station are electrically connected via a pogo pin connector and are mechanically connected via an electromagnetic lock. The pogo pin connector comprises various communication protocols and functional ports and supports various synchronous operations. Module charging, data export, state reading, parameter configuration, firmware upgrading, time synchronization, and other functions can be completed by simply inserting the module into the base station, featuring ease to use and compactness. The electromagnetic lock locks the module inserted into the base station to ensure reliable communication between the module and the base station and the safety and integrity of data files. The method is automatically implemented in the condition that the module is inserted into the base station, so as to ensure the real-time synchronization of all modules inserted in the base station with the base station. The electromyographic signal acquisition process does not depend on wireless networks or limit the scene of use to areas with network coverage, thus reducing the wireless connection power consumption, increasing the cost-efficiency, and greatly improving the synchronization reliability.

In one implementation, a device may obtain a set of OpenTelemetry data generated by instrumenting an online application. The device may form a group of OpenTelemetry data associated with a common event and comprising at least a portion of the set of OpenTelemetry data. The device may derive, using the group of OpenTelemetry data, information for display to a user interface regarding the event. The device may provide the group of OpenTelemetry data for sampling, after deriving the information for display.

The invention relates to the technical field of data visualization and report generation, and provides a complex data dynamic export method based on template configuration, a computer program product and a system.The method comprises the steps that report layout and database information are recognized by extracting metadata of historical Excel files, and an Excel template file and a corresponding JSON configuration file are generated according to the report layout and the database information; then JSON configuration is converted into a corresponding dynamic SQL statement according to selection operation of a user on the Excel template file so as to execute query, configuration only needs to be updated instead of recoding and publishing, and the development efficiency and the instant configuration capability are improved; in the data exporting process, the output sequence is determined by analyzing formula elements, and the final report data is output in batches by adopting a streaming data pipeline technology, so that the big data exporting success rate is improved. According to the complex data dynamic exporting method, the capability of flexibly and stably dynamically exporting the complex data into the Excel report can be provided for an enterprise.

The invention relates to the technical field of artificial intelligence, and discloses a data processing method and device based on a mirror data layer, computer equipment and a storage medium, and the method comprises the steps: obtaining to-be-submitted data, generating submission batch information for the to-be-submitted data based on a data exit layer, and carrying out the partition management of the to-be-submitted data, and submitting the to-be-submitted data to a specified mechanism, when it is detected that the to-be-submitted data is submitted successfully, obtaining storage receipt information returned by the specified mechanism after receiving the to-be-submitted data; and when determining that the to-be-submitted data is successfully stored based on the storage receipt information, writing the to-be-submitted data into the mirror image data layer, and performing partition management on the to-be-submitted data according to the submission batch information to complete data submission of the to-be-submitted data. In the financial insurance field, especially in the life insurance business, the mirror image data layer provides a reliable data basis for data auditing and compliance inspection, the accuracy in the data management process is ensured, manual intervention is reduced, and an insurance company is helped to meet supervision requirements.