220 results about "Data consolidation" patented technology

The invention discloses a nursing scene data enhancement and generation method for intention recognition model training, and belongs to the technical field of artificial intelligence and smart old-age care. The method aims at solving the problems that in the prior art, high-quality nursing scene training data is deficient, and the obtaining cost is high. According to the core technical scheme, the method comprises the steps that firstly, a staring sequence and other context information (such as time, place and physiological signals) of a user are processed through a multi-modal information fusion model, and a structured initial situation vector is generated; secondly, inputting the vector into a scene generation model combined with a nursing knowledge base, and automatically generating a batch of basic nursing scene data with intention labels; key points are that a data enhancement module is introduced, and a plurality of innovative strategies such as situation element disturbance, virtual physiological data synthesis, gaze path variation and virtual scene deduction are adopted to deeply process basic data, so that the diversity and complexity of a data set are greatly enriched; and finally, combining the basic data with the enhanced data to construct a final comprehensive training data set. According to the method, large-scale and high-fidelity training data can be generated in a low-cost and high-efficiency manner, and the accuracy and robustness of the intention recognition model in a real nursing environment are remarkably improved.

The invention provides a knowledge question-answering method and device based on a large model and a medium, and relates to the technical field of knowledge questions.The method comprises the steps that a data query period corresponding to a question text is obtained through a first large language model; if the duration of the data query time period is smaller than the preset duration, determining a target operation and maintenance tool from a plurality of preset operation and maintenance tools through a second large language model; controlling the target operation and maintenance tool to perform data acquisition, and taking the acquired data as intermediate data corresponding to the target operation and maintenance tool; performing data compression on the intermediate data based on the character number of the intermediate data to obtain target data; merging the target data into the context information, and obtaining an answer text according to the context information and a specified large language model after merging is completed; according to the method, input overflow, model reasoning failure or response delay caused by too large data volume or exceeding of the context length limit of the large language model can be avoided, the stability of answer generation is ensured, and the user experience is improved.

Systems and methods for the amalgamation of data from different sources for processing by an algorithm is provided. A synthetic data steward receives an encrypted algorithm from the algorithm developer via a core management system. Likewise, two or more data stewards may encrypt their data sets and provide them to the synthetic data steward. The sensitive data being operated upon is compiled into a unified / amalgamated dataset. Within the synthetic data steward is a sequestered computing node. This allows the algorithm and the various sensitive data sets to be decrypted within the sequestered computing node, and computations be performed on the amalgamated data, without the synthetic data steward (or any party for that matter) from having access to the algorithm and / or sensitive data sets while ‘sealed’ in the vault like sequestered computing node.

The invention discloses a TBR implementation method of a desktop GPU for mobile 3D application optimization, which comprises the following steps: defining block metadata of screen blocks in a Mesa driver, establishing a block manager, when a mobile application context is detected, acquiring GPU core parameters by the block manager, calculating the size of a basic block, dividing a screen into areas corresponding to shader arrays in number, and storing the areas in a memory; establishing a mapping table of a basic block, a computing unit and an L2 cache slice, generating a resource hash table, analyzing block metadata and the mapping table after whole frame rendering is started, determining a hardware channel according to the mapping table, scheduling rendering tasks according to priorities, and configuring a GPU rendering state. Then executing a vertex shader, rasterization, a fragment shader, depth testing and color mixing to complete block rendering, updating block metadata, merging intermediate data into a final frame buffer according to geometric information after rendering of all basic blocks is completed, and submitting the final frame buffer to a window system to complete single-frame display. And the operation efficiency of the mobile operation system and the mobile terminal 3D application on the desktop platform is optimized.

Provided are a frequency-domain data merging method and apparatus, a storage medium, and an electronic apparatus. The method includes: respectively performing up-conversion on baseband data of a plurality of frequency bands in a frequency domain, so as to obtain frequency-domain received data of each frequency band from among the plurality of frequency bands that has been subjected to up-conversion; and merging the frequency-domain received data of each frequency band that has been subjected to up-conversion, so as to obtain merged frequency-domain received data.

The application discloses a kind of photovoltaic power station cluster power synergic optimization control methods based on artificial intelligence, and the original data of operation and environment are collected by the sensor of photovoltaic power generation unit local, and the local load power data of each grid-connected point is obtained from external power grid energy management system, is combined into original data set, is formed standardized input feature vector after exception elimination and normalization, constructs model with reducing cluster total power fluctuation, improves the output balance between units as target and meets constraint, solves using particle swarm optimization algorithm of fusion simulated annealing mechanism, exports power adjustment instruction set to clarify each unit planned output target value;Through communication network, issue instruction to each unit local controller, drive photovoltaic inverter to adjust active power output, collect actual operation data after execution, calculate cluster synergic energy efficiency index, load supply-demand ratio and other indexes to evaluate effect, to dynamically adjust algorithm key parameters.

The invention relates to a data processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method is applied to a data sending device and comprises the steps of obtaining target data to be sent to a data receiving device; performing data interception on the target data to obtain first intercepted data and second intercepted data; generating a first key key corresponding to the first intercepted data based on the second intercepted data, and encrypting the first intercepted data based on the first key key to obtain first encrypted data; based on the first encrypted data, determining a second key key corresponding to the second intercepted data, and based on the second key key, encrypting the second intercepted data to obtain second encrypted data; and merging the first encrypted data and the second encrypted data to obtain merged data, and sending the merged data to the data receiving equipment, so that the data security is improved.

A system for a website, includes a processor and a unit running on the processor to capture interactions between a user of the website and at least one third party application embedded as an instance in a page of the website and to use the interactions to update a contact record associated with a user. The unit includes a data extractor to extract contact related information from the interactions; and a data merger to merge at least two contact records where the at least two contact records have an association with the same identified user and to merge the extracted contact related information to that of an existing contact record for the identified user according to predefined merging rules.

The application relates to the technical field of data management, in particular to a battery temperature data management method and system. The method comprises the following steps: based on all battery temperature data in an original data set, at least two continuous battery temperature data of the same process are combined to obtain a pretreatment data group; based on the starting time and the ending time of each pretreatment data group, a first interval duration of each adjacent pretreatment data group is obtained; a preset duration threshold is acquired, and adjacent pretreatment data groups with a first interval duration less than the duration threshold are combined to obtain a target data group; the target data group is used for indicating the classification of the battery temperature data of the same process and continuity. The method can improve the management efficiency of the battery temperature data.

The application discloses a kind of numerical control processing surface roughness prediction method, comprising the following steps: processing experiment is carried out, and cutting and segmentation are carried out, obtain the three-dimensional cutting force signal data of each sample, and obtain the processing surface roughness numerical value;Adopt time series dimension reduction algorithm to obtain the three-dimensional cutting force data of consistent length;With the three-dimensional cutting force data of consistent length as feature vector, with the processing surface roughness numerical value as label value, data merging is carried out, and three groups of prediction data sets are formed;Convolutional neural network prediction model is built, model training and structure evaluation are carried out, and the cutting force direction and convolutional neural network prediction model with the highest prediction accuracy are screened out;Roughness prediction is carried out using the screened convolutional neural network prediction model.The application has the beneficial effects that: reduce human intervention, improve the intelligent degree of prediction process;Reduce workload, improve prediction efficiency and promote the improvement of production efficiency.

The application provides a large language model-based electronic form standardization processing method and system, and belongs to the technical field of data processing, and specifically comprises the following steps: a file acquisition module is responsible for intelligently screening a target worksheet set containing valid data; a slicing module is responsible for partitioning the content of the worksheet to obtain a plurality of data slices; the table header of each data slice and sample data are input into a large language model workflow to intelligently identify the dimension type and structural characteristics of the data; an execution module is responsible for generating management strategies and prompt words, calling a large language model to dynamically generate a targeted data processing function code, executing the generated function code through a function execution engine, and standardizing and converting the data slices; and all successfully processed data is combined and exported as a standardized electronic form, thereby improving the efficiency of the standardization processing of the electronic form.

This specification provides methods, apparatus, and a distributed machine learning model training system for optimizing machine learning model training. In response to obtaining gradient information of model parameters after completing local model computation, each member processing device slices the gradient information into a first number of gradient information slices; and together with all other member processing devices of its respective distributed training node, performs data merging processing using its respective gradient information slices. Each numbered member processing device obtains a first gradient information slice merging result after data merging processing using the gradient information slices with the corresponding number. Subsequently, each member processing device, together with all other member processing devices of other distributed training nodes with the same number, performs data merging processing using its respective first gradient information slice merging result to obtain a second gradient information slice merging result; and stores the second gradient information slice merging result in the storage space allocated to that member processing device.

Embodiments of the present application provide a report processing method, device, equipment and medium. The method comprises: identifying the to-be-merged account data generated by the internal transaction of an enterprise from a plurality of single reports, then performing a merging and offsetting processing on each group of to-be-merged account data, generating a corresponding merging and offsetting voucher, storing the offsetted account data in a preset offsetting information storage area, and generating an offsetting account single report. Finally, a final merging report is generated according to the single report data and the offsetting account single report data. Through the above method, the account data merging efficiency is effectively improved, and the reporting period of the merging report is shortened.

The invention relates to a data screening method and device based on hardware processing capacity and a medium. The invention provides a data screening method based on hardware processing capability. The data screening method comprises the following steps: acquiring N pieces of data to be processed and a target quantity K from a large language model; dividing the N data into G data groups based on the hardware processing capability, the hardware processing capability comprising a maximum number M of data that can be processed in parallel by a hardware computing unit; screening out candidate data from each data group by using the hardware computing unit based on a preset group screening ratio P, and merging the candidate data of all the data groups into a candidate data set; and screening the target number K of target data from the candidate data set by using the hardware computing unit.

Embodiments of the present application provide a structured data context isolation addressing and multi-layer cache analysis method, device and electronic equipment for large language model Agent tool invocation, which relates to the field of artificial intelligence data processing. The method comprises: calling a data acquisition tool to obtain a structured data set of an analysis object and a data set index Key thereof; based on the data set index Key, concurrently starting multiple independent analysis tracks, and after completion of analysis, storing analysis result data to a persistent index layer and an object storage layer, and generating an analysis result identification Key; and based on the analysis result identification Key of each track, the server autonomously reads each dimension analysis result data from the persistent index layer and the object storage layer, and after merging and processing, generates a structured comprehensive analysis report. The technical solution solves problems such as context window pollution, cross-tool data transmission redundancy, lack of efficient cache mechanism for LLM analysis results, and lack of fault tolerance and breakpoint resume capability for analysis pipeline.

The present invention relates to a measurement method for high-density three-dimensional composite urban form characteristics, and a computing apparatus and a storage medium. The measurement method comprises: delineating a three-dimensional identification boundary, and acquiring raw map data; performing screening processing on the raw map data, and performing three-dimensional modeling within the identification boundary; calculating three-dimensional characteristic measurement indices; selecting three-dimensional base coverage rate and three-dimensional base plot ratio to construct a coordinate system, and classifying sample indices into hierarchies according to distribution characteristics; using a hierarchical clustering algorithm to constantly perform iteration until all data is combined into one category; and storing the data, building a three-dimensional urban database, and keeping the data updated. The present invention is aimed at the form characteristics of three-dimensional composite urban development during the renewal of high-density cities, and solves the problems in the prior art of it not being possible to precisely express three-dimensional urban forms and it also not being possible to perform effective quantitative analysis on the three-dimensional urban forms during urban design.

A health status platform includes a receiving component that receives a test result a test of a biological sample collected from a human patient. The test result includes an indication of a presence of an infectious disease in the patient, and an identification and a verification of the patient. The platform includes a certificate component that issues a certificate of origin of the biological sample; and a data merging component that cooperates with a venue access manager that controls access to a venue. The data merging component implements a distributed ledger system that stores encrypted test results of the patient and the identification and verification of the patient, and an end-to-end encryption system that receives an encrypted venue access request from a venue access manager, decrypts the access request, determines if an access request is valid, and if valid, provides an encrypted certificate of origin to the venue access manager.

The invention relates to network interface device-based memory access. An apparatus is disclosed comprising a network interface device comprising: a processor to implement network interface device functionality, and communication protocol engine circuitry, where the network interface device is to: receive a request to write data to a memory node, the memory node communicatively coupled to the network interface device; identifying network information corresponding to the request, where the network information includes at least one of a Quality of Service (QoS), a Physical Function (PF), a Virtual Function (VF), a Name Space Identifier (NSID), a Flow ID, a Service Level Target (SLO), or a Process Address Space ID (PASID); identifying a characteristic of the memory node, where the characteristic includes at least a page size of the memory node; and merging the data with other data on the memory node based on the network information and the characteristics.

The invention relates to an FTTR gateway data configuration method and system and a medium, and the method comprises the steps: carrying out the decompression and decryption of configuration data corresponding to equipment identification information according to the equipment identification information obtained in advance, and loading and verifying the configuration data according to a preset priority sequence. And when the configuration data verification is not passed, loading default reference configuration data. And comparing the configuration data which does not pass the verification with the reference configuration data to obtain differentiated data, and merging the differentiated data into the reference configuration data to obtain target configuration data which is used for adapting to the multi-dimensional difference configuration requirements. And calling the target configuration data according to the current service demand. The problem that FTTR gateway data configuration is low in configuration flexibility in related technologies is solved.

The invention provides a patient primary index management method and system based on a big data algorithm. The method comprises the following steps: acquiring original data of a plurality of historical patients; the method comprises the following steps: constructing a patient main index database containing multi-dimensional features through original data, and performing feature weight configuration on each feature of the multi-dimensional features based on a preset rule; the multi-dimensional features comprise social attribute features, biological attribute features and medical attribute features; multi-dimensional features of a patient to be recognized are obtained, and the comprehensive matching degree of the multi-dimensional features of the patient to be recognized and the existing EMPI in the patient main index database is calculated based on the feature weight, so that the operation of associating the multi-dimensional features to the existing EMPI or registering the multi-dimensional features as a new EMPI is executed; the repeated EMPIs are regularly combined, and the patient main index database is updated. The method solves the problems of feature variability and historical data merging, and has the advantages of high recognition precision and high matching strategy intelligence degree.

The invention discloses a software testing method and device, a medium and a product, and relates to the technical field of software test.The software testing method includes the steps that coverage rate data of unit testing, integration testing and system testing of target software are collected through a code coverage rate analysis tool, and the coverage rate data are converted into target text files; the coverage rate data comprises execution times and coverage rates of the codes; storing each target text file in a corresponding target directory, and reading and analyzing the target text file in each target directory to obtain corresponding analyzed data; the analyzed data comprises a total row number, a total branch number, a total function number, a total coverage row number, a total coverage branch number and a total coverage function number; and merging and storing the analyzed data into a preset nested dictionary, traversing the preset nested dictionary to determine the code coverage rate of the target software based on the traversed analyzed data, and determining the software defect of the target software by using the code coverage rate. The quality and stability of software can be improved through testing.

The application provides a bus data transmission method, device and chip. The method comprises the following steps: obtaining at least one data request from a high-level extensible interface bus; determining at least one data packeting strategy in a preset data packeting strategy set based on data access information of the data request; performing data merging on data in at least one first data packet in a pre-created first queue based on the at least one data packeting strategy to obtain merged data; in response to the merged data meeting a preset transmission condition, determining at least one data unpacking strategy in a preset data unpacking strategy set based on data transmission information of the merged data; performing data unpacking processing on the merged data based on the at least one data unpacking strategy to obtain at least one second data packet; and transmitting the second data packet to a data storage area to be accessed through an on-chip network bus. Through the application, the utilization rate of bus bandwidth can be improved.

An exemplary system for determining whether data sets can be merged together may receive first data labeled with a first variable and second data labeled with a second variable, wherein the first variable represents a first sequence of words and the second variable represents a second sequence of words. One or more machine learning models may generate one or more first candidate words and one or more second candidate words respectively based on the first and second variables. One or more generative machine learning models may generate a predicted first sequence of words and second sequence of words respectively based on the one or more first candidate words and one or more second candidate words. Based on a similarity metric determined based on the predicted sequences and a merging condition, the system may generate a merging instruction indicating whether the first data and the second data are to be merged.

This invention discloses a rapid design tool and its application in process piping and instrumentation diagrams, relating to the field of engineering drawing technology. It includes: a data interaction module for exchanging data between drawing files loaded in the CAD platform and external data files, enabling the export of drawing data and / or drawing updates based on external data; an intelligent positioning module connected to the data interaction module for locating and highlighting corresponding graphic elements in the drawing file based on user-input search criteria; and an Excel integration module connected to the data interaction module for processing Excel data files associated with the drawing file, performing automatic generation of equipment tag numbers and / or merging of data from multiple tables. In summary, the advantages of this invention are: by integrating a lightweight plugin into a mature CAD platform, it achieves bidirectional intelligent interaction and efficient synchronization between drawing data and external table data.

A method, computer program product, and computer system are provided for document annotation processing. The method includes: providing a target document in a digital format; receiving an image of an annotated hard copy of the target document and extracting annotations from the image as an annotation source; processing the extracted annotations to collect extracted annotation information metadata for the image; merging the extracted annotation information metadata for the image with other extracted annotation information metadata from other annotation sources for the target document to generate master annotation metadata; and providing the master annotation metadata for application to the target document.

The invention discloses a claim settlement case distribution method and system based on RPA. The method comprises the step of simulating manual operation to log in a system claim settlement platform through an RPA robot. According to the method, the RPA simulation login and paging query merging technology is adopted, so that the time consumption of manual login, case query and data merging operation is shortened, meanwhile, manual operation errors are avoided, and the accuracy of analysis of fields such as case numbers and case reporting time is ensured; a fairness algorithm dynamically counts the number of personnel cases and preferentially distributes the number of personnel cases to the least load personnel, and the pain point of'busy and idle non-uniformity 'is thoroughly solved by combining processing time comparison and a random polling mechanism; the effect monitoring module generates a fairness report per hour, and when the processing time is lower than a threshold value, the strategy weight is automatically adjusted to form a'monitoring-evaluation-tuning 'dynamic closed loop, so that the average processing time is improved, and the requirements of workers are met.

The application provides an engine strategy data merging method and device, electronic equipment and medium, the data merging method executes a target engine strategy constructed in advance; determines the execution order of each branch node in the target engine strategy, and sequentially stacks the data of each branch node according to the execution order of the branch node; determines the execution order of each summary node in the target engine strategy, and sequentially de-stacks the data of the branch node according to the execution order of the summary node; wherein the data of the branch node corresponding to the summary node executed next is located at the top of the stack; each summary node merges the data of the summary node; in this way, the front-end data is better decoupled from the back-end data, and the algorithm of the back-end is more efficient.

This invention provides a distributed transaction processing method for BOM data in a PLM system, belonging to the technical field of PLM systems. When initiating a BOM data modification transaction, this invention sends a preparation request to participating nodes and performs field-level lock acquisition. A majority vote determines whether the transaction should be committed or rolled back. Transaction logs are batch-aggregated into group commit log blocks according to time windows and copied to persistent memory via RDMA. A closure table is established for the BOM tree structure to store ancestor-descendant relationships. An artificial intelligence model is used to monitor node response latency and log write rate to dynamically adjust parameters. When a network partition is detected, nodes holding a majority lease continue processing the transaction. After partition recovery, data merging is performed using version vector conflict detection and a compensation transaction mode. This solves the problem of data consistency being difficult to guarantee due to network partitions when processing BOM data modification transactions in a distributed PLM system.

The invention discloses a data collection method and device supporting multiple industrial protocols and a medium, and relates to the technical field of industrial data collection, and the method comprises the steps: obtaining protocol type information, loading protocol element description corresponding to the protocol type information, and generating protocol description data; a dynamic time warping algorithm is adopted, protocol device data are analyzed from the protocol description data, timestamps and sampling periods of different protocol device data are converted into a unified time format, and synchronous time data are generated; carrying out data merging on the standard format data, and carrying out priority ranking according to the real-time performance and importance of the protocol equipment data to generate priority scoring data; and performing data transmission monitoring and data integrity verification on the priority scoring data to obtain a data integrity report, and performing data loss analysis to generate a data acquisition state report. According to the overall scheme, the automation level of data acquisition and processing is improved, and the stability and reliability of the system in a multi-protocol environment are enhanced.

A system and method for efficient tracking and rendering of dynamic entities in video games. In order to avoid costly computational loads associated with simulating physics for each dynamic entity independently, then rendering each entity, the system and method stores the pose of dynamic entities after physics calculations and amalgamates pose data into an optimized data structure to allow a graphics processing unit (GPU) to re-create the pose of and display a plurality of dynamic entities as part of a single rendering pass, referring to only a single set of reference data. The method achieves this by recording the position and rotation of a set of pre-defined bones of importance of a skeleton onto a single location, a single image file, which contains all the information necessary for the GPU to pose and display each of the dynamic entities simply by referencing some pre-defined definitions.