699 results about "Data conversion" patented technology

The invention discloses a heterogeneous data conversion method and system based on a multi-modal large model, and aims to solve the problems of single-modal limitation, high migration cost and the like in traditional heterogeneous data processing. The method comprises the following steps: firstly, carrying out format adaptation and classification preprocessing on multi-source heterogeneous data such as images, texts, audios and videos; then, through a ViT, BERT and Transform cross attention mechanism, deep analysis and cross-modal semantic association of visual, text and audio features are realized, and visual-text-audio semantic mapping is established; and based on a dynamic prompt project, guiding the multi-modal large model to generate structured data according to a preset Schema zero sample. And then error correction and format normalization are carried out through a Drools rule engine to ensure that the data meet the business standard. And finally, supporting multi-format output of JSON / XML / database table and the like, and meanwhile, associating original data storage to realize data traceability. According to the method, the limitation of single-modal processing is broken through, and cross-modal data deep association is realized.

The invention discloses a cross-platform equipment alarm information acquisition method, and particularly relates to the field of information acquisition, the method adapts to different platform equipment through a standardized interface layer, the interface layer comprises an equipment connection protocol library and a unified data conversion unit, and an original log of the equipment is analyzed in real time based on a preset alarm rule template; extracting key information and generating an alarm event object; converting the alarm key information into an alarm event in a unified format, and adding equipment identification metadata; alarm events are asynchronously transmitted to a central processing server by utilizing a high-reliability message queue, and the transmission reliability is guaranteed by adopting various mechanisms; performing duplicate removal, priority classification and persistent storage on the alarm events in the central server, and ensuring data consistency by adopting a hierarchical storage architecture; the whole processing link is provided with perfect monitoring indexes, and automatic capacity expansion and contraction are achieved.

The invention discloses a power distribution network fault identification method and device based on artificial intelligence, and the method comprises the steps: obtaining the multi-source fault characterization information of a power distribution network, and the multi-source fault characterization information comprises telemetering data and telecommand data; performing expert database-based normalization processing on the multi-source fault representation information to generate a standardized fault data sample; matching and checking the standardized fault data sample to generate checked fault data; performing graph data conversion processing on the checked fault data according to a power distribution network graph model to generate fault graph data; and based on the fault graph data, reasoning the fault of the power distribution network through the fault reasoning model to obtain the speculated fault of the power distribution network. The multi-source information is obtained, the limitation of a single channel is broken, data differences are eliminated through expert database normalization, data accuracy is guaranteed through matching checking, graph data conversion is associated with topology, artificial intelligence reasoning gets rid of manual dependence, and efficiency and accuracy are improved.

A display device may include a display panel which includes pixels, a data driver which provides data voltages corresponding to output image data to the pixels, and a data converter which generates a compensation grayscale from reference compensation values for compensating at least one selected from a color shift and a luminance shift corresponding to a temperature based on an input temperature, an input grayscale included in input image data, and an input luminance, and converts the input image data into the output image data based on the compensation grayscale.

The invention provides a structured data representation method, a structured data conversion method, a structured data scheduling method, a structured data conversion device, a structured data scheduling device, a structured data conversion system, a medium and electronic equipment. The representation method comprises the following steps: responding to an operation of dragging a module from a module library to a visual editing canvas by a user to form a node corresponding to the dragged module; responding to the operation that a user establishes visual connection between input ports and output ports of different nodes on the canvas to form edges, wherein the edges define a data flow and calculation dependency relationship between the nodes; a structured data representation of a machine-readable AI model structure is generated based on all the nodes on the canvas and user-configured parameters thereof, and a set of edges defining the edge interconnection relationship. According to the representation method, conversion from graphical representation to structured data of the artificial intelligence model is completed.

The invention provides a multi-database automatic synchronization method under an AI platform, and belongs to the technical field of database automatic synchronization. The captured change records are converted into synchronous messages in a unified format, the synchronous messages are input into an intelligent scheduling optimization model for dependency analysis and transaction reordering based on dynamic programming, data conversion rules are dynamically generated according to mode version differences, and data consistency is verified through a Merkle tree hierarchical structure; the multi-stage self-adaptive compression transmission and data writing are completed after the target node executes conflict detection and circular dependency processing, and finally the final consistency among the multiple databases is guaranteed through a periodic full-amount account checking task, so that the technical problem of synchronization performance bottleneck caused by low transaction scheduling efficiency in the automatic synchronization process of the multiple databases is solved.

The invention relates to a construction method of a coefficient prediction model, a coefficient prediction method and a storage medium, and the construction method comprises the steps: carrying out the modeling of a bridge prestressed beam through finite element numerical software, simulating a tensioning process, constructing a bridge parameter coefficient array, dividing the bridge parameter coefficient array into a training data set and a verification data set, performing data standardization and tensor data conversion, and constructing a data loader; an AND-based full-connection multi-layer multi-task neural network is constructed, and a standardizing device, a forward propagation function, a loss function, a learning rate scheduler and an optimizer are arranged; and carrying out model training, packaging a prediction function, and integrating a standardizing device and the trained prediction model. The prediction method comprises the step of predicting the friction resistance loss coefficient and the pipeline deviation coefficient according to the prediction model. According to the method and the device, coefficient prediction can be quickly, efficiently and accurately realized by only needing several on-site easy-to-measure parameters.

The invention discloses an electric power multi-protocol data conversion method and system based on object model dynamic mapping, and the method comprises the steps: receiving an original protocol message, recognizing a protocol type, extracting a logic name as a unique identifier of equipment, extracting an object identifier as a measurement point identifier, and extracting an electric energy array as a measurement point value; according to the protocol type and the equipment unique identifier, matching a corresponding object model template from a unified object model library; mapping the equipment unique identifier, the measuring point identifier, the measuring point numerical value and the acquisition timestamp obtained by analysis to corresponding fields in a template; and generating an object model data object conforming to a standard format, packaging the object into a message, executing an encryption authentication mechanism of a network layer and a transmission layer through the power Internet of Things security access gateway, and sending the message to an Internet of Things management platform. According to the invention, standardized, automatic and secure access of different protocol terminals is realized through protocol analysis and the unified object model library.

The invention provides a multi-platform informatization construction system and method based on a computer, and solves the problems that existing multi-platform data synchronization is not timely, formats are not compatible and the like. The system comprises a real-time data capture module, and a data change event is generated in real time through database transaction log monitoring; the intelligent routing decision module optimizes a transmission path in combination with rules and machine learning; the data conversion adaptation module realizes automatic adaptation of a format and an interface by utilizing dynamic template matching; the conflict detection and resolution module guarantees data consistency based on version control and priority judgment; the data synchronization execution module transmits data according to an optimized path, and the monitoring management module monitors the whole process in real time. The method comprises the steps of data capture, routing decision, format conversion, synchronous execution and monitoring feedback. According to the scheme, the data synchronization efficiency and accuracy are improved, the multi-platform integration operation and maintenance cost is reduced, and the method is suitable for multi-scene informatization construction of enterprises, government affairs and the like.

The invention belongs to the technical field of cloud computing security, and discloses a multi-cloud security management center system and method based on AI. Aiming at the problems of difficulty in asset management, low safety operation efficiency, high labor cost and the like in a multi-cloud environment, the system lightens AI Agent through a data acquisition layer, acquires core resource data in real time by a differentiation strategy, and constructs a three-dimensional dynamic knowledge graph after standardization of a cross-cloud data conversion engine; the intelligent analysis layer integrates five-dimensional data such as logs and traffic by using a multi-modal fusion engine, and realizes attack link dynamic deduction (the accuracy rate reaches 98%) and intelligent alarm noise reduction (the false alarm rate is reduced to below 10%) based on a graph neural network; the strategy management layer generates a cross-cloud unified strategy in combination with domestic and overseas large-scale boards and a natural language processing technology; and the automatic execution layer realizes automatic vulnerability repair (the success rate is not lower than 90%) and AKSK authority dynamic management. The method comprises the whole process of data acquisition, knowledge graph construction, risk analysis, strategy generation and automatic disposal. According to the method, the asset management time can be shortened to 1 minute, the vulnerability repair period is shortened to 30 minutes from 48 hours, the safety operation labor cost is reduced by 70%, and an efficient, intelligent and low-cost safety management scheme is provided for the enterprise multi-cloud environment.

The invention relates to an on-satellite disaster risk area lightweight extraction method and system, and belongs to the cross technical field of satellite remote sensing data processing and emergency disaster response. The method comprises the following steps: receiving a satellite remote sensing image and performing on-satellite preprocessing, and then performing on-satellite extraction and geospatial data conversion on a disaster risk area; performing data lightweight: performing boundary simplification on the data subjected to format conversion by using a boundary simplification function, performing centroid extraction by using a centroid calculation function, and generating simplified vector data; and downloading data based on the Beidou short message, and receiving and visually displaying ground data. According to the invention, core processing can be completed on a satellite, lightweight data is adapted to Beidou, and minute-level downloading to the ground is realized, and the timeliness bottleneck of disaster emergency response is broken through.

The invention provides a heterogeneous data mapping optimization method, and relates to the technical field of software development. A JSON Schema model library containing business and voucher objects is constructed by obtaining heterogeneous source data, the construction process comprises data format analysis and feature extraction, and construction and classified storage are completed by means of DSL rules and visual editing; based on the model library, generating a mapping relation description document by utilizing a preset abstract mapping rule template and an expanded JSON Schema grammar; a mapping engine analyzes the document to construct a field-level dependency graph, data conversion is executed according to the field-level dependency graph, and an inerting execution and caching mechanism is adopted in the conversion process; and verifying the converted data and the mapping process by adopting a mode of combining static pre-verification and incremental verification, dynamically adjusting a mapping rule according to a verification result or model change, and performing version management. Through the steps, the data mapping efficiency, flexibility and accuracy are improved, and the system performance is optimized.

The invention relates to the technical field of cross-platform collaboration of an ERP (Enterprise Resource Planning) system, in particular to an ERP operation method for realizing cross-platform collaboration, which comprises a data conversion module, a protocol adaptation module, a task scheduling module and a resource allocation module. The data conversion module unifies heterogeneous data formats, the protocol adaptation module analyzes communication protocols, the task scheduling module dynamically adjusts task priorities, and the resource allocation module coordinates calculation and storage resources. According to the method, through improvements of a weight distribution algorithm, dynamic mapping updating, security verification, load balancing and the like, data integration and task collaboration among multiple platforms are optimized. The flexibility and adaptability of the system can be improved, the technical threshold is reduced, and the efficient and intelligent operation requirement of enterprises is met.

The invention relates to the technical field of large language model deployment, and discloses a large language model weight inverse quantization reasoning device and method.The method comprises the steps that low-precision weight data is transmitted to a high-bandwidth storage from a host and then transmitted to an on-chip storage through the high-bandwidth storage; data conversion from a low-precision format to a high-precision format is completed in the on-chip memory, the data is multiplied by an inverse quantization factor to obtain recovered high-precision weight data, and the functional unit is responsible for executing general matrix multiplication of input data and the high-precision weight data after inverse quantization. And pipeline parallel execution of the inverse quantization operation and the general matrix multiplication operation is realized through a double-buffering technology. According to the invention, on the basis of a dual-path inverse quantization architecture of the vector processing unit and a dual-buffer mechanism in the on-chip memory, the problem of hardware adaptation of low-precision calculation is solved, and efficient execution of a low-precision conversion algorithm is realized under the condition of limited hardware resources.

The invention provides a graphic display agent device based on a PCIE (Peripheral Component Interface Express) bus, which is characterized in that an instruction analysis module receives a graphic drawing instruction containing an operation type and a corresponding coordinate parameter through a PCIE bus interface, and generates first pixel data based on the instruction; meanwhile, the data conversion module receives original image data containing pixel position information and sensor echo information through a radar video interface, analyzes the original image data and converts the original image data into second pixel data consistent with the first pixel data in format, and the format difference of the two types of data is eliminated to meet the superposition condition; a graph superposition processing module generates a primary and secondary clear composite image according to the logic that the first pixel data covers the second pixel data; then, the image output control module receives the synthesized image by using a first buffer area and a second buffer area which alternately work to ensure that a complete image frame is transmitted to a subsequent module; and finally, the video signal generation module converts the complete image frame into an analog video signal conforming to a preset video time sequence and outputs the analog video signal.

The invention relates to a radio frequency transceiving multichannel amplitude-phase calibration system, which comprises a radio frequency receiver, a radio frequency transmitter, a data converter, an FPGA (Field Programmable Gate Array) processor and a clock network, wherein the radio frequency receiver adopts a zero intermediate frequency architecture and is used for receiving a multichannel radio frequency signal and down-converting the multichannel radio frequency signal into an analog baseband signal; the radio frequency transmitter adopts a zero intermediate frequency architecture and is used for up-converting the analog baseband signal into a radio frequency signal and transmitting the radio frequency signal; the data converter is connected with the radio frequency receiver and the radio frequency transmitter and is used for realizing conversion between an analog signal and a digital signal; the FPGA processor is connected with the data converter through a JESD204B interface and is used for aligning the data of each receiving and transmitting channel; and the clock network consists of a clock chip with JESD204B characteristics and a clock Buffer, and is used for providing a synchronous clock and an SYSREF signal for the whole system and supporting an SYNC synchronous trigger signal. By adopting the method, the problem of multi-channel amplitude-phase consistency can be solved.

The invention discloses a printing color closed-loop control system based on spectral analysis, and relates to the technical field of computer processing, and the system comprises the following steps: S01, collecting the spectral reflectivity data of a plurality of key color blocks on a printed matter measurement and control strip in real time through an online high-speed spectrometer at the frequency of not less than 100 color blocks per second; s02, constructing a color prediction model, wherein the model receives the spectral reflectivity data and outputs absorption scattering characteristics, the spectral transmittance of ink and dot expansion, trapping and overprinting effects in the printing process; s03, setting a dynamic tolerance threshold value delta Et based on a chromatic aberration formula according to the color precision requirement of the printed matter, and judging the absorption and scattering characteristics, the spectral transmittance of the ink and a grading tolerance interval in which the dot expansion, trapping and overprinting effects in the printing process are consistent with visual perception; and S04, converting the spectral reflectivity data acquired in real time into a CIELAB color space irrelevant to equipment, and comparing the spectral reflectivity data with a preset standard color target value. According to the method, the problems of different standards and color drift caused by artificial experience difference and visual fatigue are solved.

A communication-middleware-implemented architecture system and control method applicable to an automatic parking planning and control algorithm. By using an SOA concept to perform service-oriented division on data conversion logic, and by optimizing the real-time performance of software by means of EventLoop and dynamic thread pool technology, a high-performance general-purpose middleware solution compatible with a plurality of vendor perception solutions is implemented to ensure the decoupling of an automatic parking algorithm from upstream perception data, such that a vendor can freely access, in the form of a standard part, middleware designed in the present application, thereby greatly shortening a vehicle model adaptation period and reducing the mass production costs for automatic parking.

An image processing apparatus comprises: a superimposition unit that performs superimposition processing for superimposing an object on first image data of a first dynamic range, the first image data being associated with a first gain map for converting the first dynamic range into a second dynamic range, to generate superimposed image data; a generating unit that obtains a conversion characteristic for converting image data of the object into image data of the second dynamic range based on a luminance of the object, and generates a second gain map for converting the superimposed image data into second image data of the second dynamic range using the conversion characteristic; and an updating unit that updates an image file consisting of the first image data and the first gain map by using the superimposed image data and the second gain map.

The invention discloses a two-color printing method based on a thermal printer. The two-color printing method comprises the steps that a two-color printing mode is started; performing color configuration on different types of to-be-printed information, and respectively setting the to-be-printed information as a first color and a second color; converting the character data to be printed into dot matrix data; according to the color configuration, converting the dot matrix data into double-color printing dot matrix data according to a double-color printing data encoding format; the control chip of the thermal printer separates second color printing data from the two-color printing dot matrix data, and respectively restores all the two-color printing dot matrix data and the second color printing data into 1-bit single-color printing dot matrix data; calculating the first color heating time and the second color heating time of the double-color thermo-sensitive paper according to the restored double-color printing dot matrix data and the second color printing data; and according to the first color heating time and the second color heating time, the printing head is controlled to heat the two-color thermo-sensitive paper in a time-sharing mode, and two-color printing is achieved. The printing information identification degree can be improved.

The invention relates to the field of enterprise application integration, in particular to a supply chain finance-oriented multi-protocol conversion and semantic verification system and method, which comprises a protocol adaptation layer, a core processing layer, a management support layer and a distributed data storage layer, the protocol adaptation layer adopts a plug-in and metadata driving design, and a protocol plug-in is an independent JAR packet and supports multi-protocol encoding and decoding and hot updating; the core processing layer realizes data standardization and financial-level semantic verification through a general message model, a dynamic routing engine, a visual data conversion module and a rule engine; and the management support layer provides a low-code portal and supports rule configuration, simulation testing and full-link monitoring. According to the technical scheme, through the seven steps of configuration, decoding, routing, conversion, verification, coding and auditing, the method adapts to a multi-specification heterogeneous system, data intercommunication accuracy and compliance are improved, docking cost is reduced, and supply chain financial service requirements are met.

The invention discloses an alkaline electrolytic cell multi-physics field distribution prediction system and method based on deep learning, and in the prediction system, a multi-physics field coupling simulation module is used for obtaining unstructured multi-physics field coupling simulation data of an alkaline electrolytic cell; the grid data conversion module is used for acquiring structured grid data, geometric features and a symbol distance matrix, and constructing a data form required by a subsequent deep learning model; the deep learning training module is used for training the structured grid data through a deep convolutional neural network to generate a multi-physics field prediction model; and the prediction and visualization module is used for loading the trained model for real-time prediction and realizing visual presentation of a result. The method can be used for real-time prediction and design optimization of the running state of the alkaline electrolytic cell.

The invention relates to the technical field of flow field dynamic simulation, and particularly provides a drainage test data fused underground water flow field dynamic simulation method and system near a fault, and the method comprises the steps: generating a fault three-dimensional water conductivity parameter field according to transient water level response data of a monitoring well in a drainage test; realizing conversion of dynamic data of the exploration method to a fault non-uniform quality model; integrating migration path data of a tracing test, fracture network geometric data of ultrasonic logging and a fault three-dimensional water conductivity parameter field, and constructing a heterogeneous graph structure taking a fault as a core node; establishing association between the multi-modal exploration data and the dynamic representation of the fault structure; and outputting a high-resolution spatio-temporal evolution graph of the flow field parameters of the fault disturbance area in the future period, and realizing dynamic visual closed-loop feedback of the flow field near the fault driven by real-time data of the exploration method. The system comprises a data conversion module, a representation association module and a closed-loop feedback module. According to the invention, a breakthrough from static description to dynamic simulation of the flow field near the fault is realized.

The present application relates to a kind of on-orbit disaster risk area lightweight extraction method and system, belong to the cross technical field of satellite remote sensing data processing and emergency disaster response.First, satellite remote sensing image is received and preprocessed on-orbit, then disaster risk area is extracted on-orbit, geographic spatial data conversion;Data lightweight: after the data of conversion format are respectively simplified using boundary simplification function, centroid is extracted using centroid calculation function, and simplified vector data is generated;Data download based on beidou short message, ground data receiving and visual display steps.The present application can realize "on-orbit complete core processing, lightweight data adapt beidou, minute level download to ground", break through the timeliness bottleneck of disaster emergency response.

The invention relates to an interface adaptation method and system for reconstruction and integration of a complex information system module. The method comprises the following steps: acquiring a protocol mapping rule and constructing a rule base; monitoring and receiving a calling request which is sent by a source module through a transmission layer protocol and carries source module side interface protocol format data; analyzing the request, stripping a source module side transport layer protocol header to extract application layer data, and packaging the application layer data into an internal general data model; performing structure mapping, data conversion and dynamic logic processing on the model through a rule execution engine according to a request mapping rule of a rule base, reconstructing the model into target request data according to a target module interface format, and sending the target request data to a target module through a target side transport layer protocol; receiving target response data, stripping a transport layer protocol header of the target response data, analyzing the target response data to the internal general data model, and performing reverse conversion according to a response mapping rule to enable the data to conform to a source side interface format; and packaging the back-to-source module side transport layer protocol back to the source module. By adopting the method, the adaptation flexibility and the maintenance efficiency can be improved.

The invention provides a mine drawing CAD data and GIS data conversion and map service publishing method and system, and the method comprises the steps: carrying out the multi-dimensional analysis of mine drawing CAD data, and obtaining an entity data set; the multi-dimensional analysis comprises layer analysis, entity analysis and attribute analysis; performing multi-dimensional vector conversion on the entity data set to obtain a vector shape file; the multi-dimensional vector conversion comprises coordinate conversion, geometric conversion, style conversion and attribute conversion; performing spatial association on the ore map elements in the vector shape file, and performing attribute fusion on the ore map elements after spatial association to obtain a fused element data set; based on the fused element data set, performing map service publishing, and outputting a standardized map service; the standardized map service comprises a WMS service and a WFS service, and lossless conversion and standardized map release are achieved.

The invention provides a defect detection method and system based on artificial intelligence, and belongs to the field of semiconductors. The artificial intelligence-based defect detection method comprises the following steps: providing a GDS file of an original layout and a to-be-detected SEM image; extracting GDS file data corresponding to the SEM image to be detected from the GDS file of the original layout as target data; converting the target data into a reference SEM image; and comparing the reference SEM image with the SEM image to be detected, and judging whether the SEM image to be detected has defects or not. According to the method, the reference SEM image is generated from the GDS file through the first model, and the reference SEM image is compared with the SEM image to be detected through the second model, so that automatic defect detection is performed on the SEM image to be detected, and a real defect is identified and marked. According to the method, the accuracy is ensured, the detection efficiency is greatly improved, an SEM machine table is saved, and the productivity of the SEM machine table is improved.

The invention discloses a structural body and JSON (JavaScript Object Notation) data conversion method and device, and the method comprises the steps: analyzing a target structural body, and extracting the member name, data type and memory offset of each field in the target structural body; generating a metadata structural body corresponding to the target structural body based on the member name, the data type and the memory offset; when the target structural body is serialized into JSON data, accessing each member name through memory offset based on the metadata structural body, and converting the target structural body into a serialized text in a JSON format in combination with a data type; when the JSON data is deserialized into a target structure body, determining a field name and a JSON value corresponding to the JSON data; and when the field name is matched with the metadata structure body, writing the JSON value into a memory position corresponding to the target structure body according to the memory offset and the data type. The automatic conversion between the structural body and the JSON data is realized, and the development efficiency is improved.

The invention discloses an emergency power supply connector with intelligent self-inspection and state display functions, and relates to an emergency power supply connector, the emergency power supply connector comprises a body, the body at least comprises an embedded sensing unit used for acquiring bus electric energy real-time data, and the emergency power supply connector also comprises a data acquisition module, a state display module, a power supply module and a state display module which are arranged on a circuit board in the body, a data processing module; and a data conversion and display module. Through multi-sensor data fusion and an intelligent algorithm, real-time accurate diagnosis of the health state of the emergency power supply connector, active early warning of potential faults and predictive maintenance decision support are achieved, and therefore the reliability, safety and operation and maintenance efficiency of a power supply system are remarkably improved.

This disclosure provides a cross-channel distributed video encoding and decoding method and system based on multidimensional attention, which can be applied to the field of video encoding and decoding technology. The method includes: acquiring a group of video images to be transmitted, the group of video images including a first key reference frame, a second key reference frame, and at least one intermediate video frame; encoding the first key reference frame and the second key reference frame into first encoded data and second encoded data, respectively; encoding each intermediate video frame into third encoded data based on a frame encoder; extracting multi-scale features from each third encoded data based on a multidimensional attention mechanism; processing the multi-scale features into fourth encoded data based on a multi-channel feature extraction mechanism; processing at least one fourth encoded data into a first bitstream; and converting the first encoded data and the second encoded data into a second bitstream, so as to transmit the video image group to the decoder via the first bitstream and the second bitstream.