1008 results about "Data field" patented technology

The invention relates to the technical field of information and data processing, in particular to an enterprise digitalization-oriented data management and application method, which comprises the following steps of: acquiring multi-source heterogeneous data and recording metadata; establishing a cross-department management system to standardize the treatment process; building an asset catalog based on the business section and the data field classification; formulating unified data description of a multi-level data standard system; designing a quality control rule to filter low-quality data; constructing a business index system and embedding the business index system into a business system; identifying a cross-system and cross-type association mode through a metadata association technology and a rule engine; and dynamically adjusting the treatment process by adopting a multi-objective optimization algorithm in combination with service feedback and treatment parameters. According to the method, the defects of existing data governance in comprehensiveness, depth and business adaptability are overcome, standardized governance and potential value mining of multi-source data are achieved, and effective data support is provided for intelligent decision making of enterprises.

The invention relates to the technical field of data processing, can be applied to the field of science and technology finance / digital medical treatment, and discloses a multi-source heterogeneous data verification and tracing method and device and related equipment. The method comprises the following steps: acquiring multi-source heterogeneous data from a service data source of a target service; preprocessing the multi-source heterogeneous data, extracting a first data field in each data source, and matching the first data fields with the same semantics in different data sources based on a preset semantic mapping rule; performing consistency verification on the matched first data fields to obtain second data fields with inconsistent verification results; performing root cause tracing on the second data field based on a preset difference analysis rule, and determining a difference type corresponding to the second data field according to a root cause tracing result; and generating a multi-source heterogeneous data verification and tracing result according to the business data source, the second data field, the root cause tracing result and the difference type. According to the method, matching, difference identification and root cause positioning of multi-source heterogeneous data are realized.

The invention belongs to the field of data processing, and particularly discloses a method and system for automatically generating a document according to a template and structured data, and the method comprises the steps: processing an archive template file according to a document object model analysis method, extracting the position, the type and the associated tag of a placeholder, and obtaining a placeholder metadata set; according to the placeholder metadata set, traversing a document hierarchical nesting relationship by adopting a depth-first search algorithm to obtain a hierarchical placeholder mapping table; obtaining the structured data of the document repair record through an external data source, judging whether the structured data field corresponds to the tag in the mapping table according to the hierarchical placeholder mapping table, and if so, generating a matching pair list from the field to the placeholder to obtain a preliminary matching data set; the objective of the invention is to solve the problem of a business scene in which complex nested data and file template placeholders cannot be accurately matched in a document repair record in the prior art.

The invention relates to the technical field of mine safety and geological environment evaluation, in particular to a mine goaf geological environment dynamic evaluation method based on digital twinning. The method comprises the following steps: constructing a digital twinborn model of a mine goaf, designing a data structure and a virtual-real mapping rule, collecting multi-source heterogeneous data, and performing spatio-temporal data indexing processing to form a spatio-temporal associated data stream; microseismic travel time data are extracted from the space-time associated data stream; performing parallel ray tracing and rapid inversion on the microseismic travel time data to obtain a wave velocity distribution initial value; carrying out wave velocity field self-adaptive grid refinement on the micro-seismic travel time data by utilizing the wave velocity distribution initial value to obtain a multi-resolution wave velocity field; and carrying out wave velocity change rate analysis on the multi-resolution wave velocity field to obtain a wave velocity variability tensor. According to the method, the abstract energy transfer process is concrete into a data field capable of being quantitatively analyzed, so that the geological environment of the goaf is accurately and dynamically evaluated.

A system for converting a source data feed schema into a canonical data product including a memory for storing computer-executable instructions and a processor for executing the instructions stored on the memory. Execution of the instructions programs the processor to perform operations that include receiving a source data feed having a source schema, identifying a plurality of data fields of the source schema, assigning a data category from a plurality of predefined data categories to each data field of the plurality of data fields, modifying the source schema based on predefined parameters, wherein the source schema is modified to match a target schema, comparing the modified source schema to the target schema, and in response to a determination that the modified source schema matches the target schema, converting the source data feed to a canonical data product having the target schema based on the assigned data categories.

The invention discloses a karst stratum tunnel disaster sensing method and system based on multi-source information, and belongs to the technical field of tunnel engineering safety monitoring, and the method comprises the steps: building a monitoring index data set, converging the monitoring index data set to a cloud end, carrying out the time-space registration, and generating a multi-dimensional time sequence data field; calculating data uncertainty of each monitoring area by adopting an information entropy theory, calculating spatio-temporal evolution characteristics, and performing classifier identification by combining a deformation field space gradient to obtain a key monitoring area; adaptively adjusting the acquisition frequency of the sensor, and starting supplementary monitoring equipment for encrypted observation; performing space-time response calculation by adopting a machine learning algorithm to generate a tunnel disaster evolution prediction result; and carrying out grading threshold comparison and numerical simulation verification on the prediction result to realize effective identification and perception of the disaster evolution state. According to the method, the technical means of combining multi-source data fusion, the information entropy theory, machine learning and self-adaptive monitoring is adopted, and dynamic, accurate and predictive perception of the tunnel disaster evolution process can be achieved.

The invention discloses a data transaction security assessment method and system, and relates to the technical field of data security and intelligent assessment. The method comprises the steps of performing feature analysis on a data field, determining a sensitivity weight and generating a sensitivity vector; the fields are graded according to the sensitivity vectors, and dynamic adjustment is carried out in combination with transaction related information to obtain a grading result; calculating a data content risk, a field association risk, and a transaction environment risk based on the sensitivity feature set; determining a weight according to a transaction scene, and weighting various risks to obtain a comprehensive score; and judging the risk level according to the comprehensive score and a threshold value dynamically determined based on historical data. According to the invention, through hierarchical sensitivity modeling and dynamic risk calculation, fine-grained security assessment of different types and sensitivity data is realized, and the risk result can be adaptively adjusted along with changes of data contents, transmission paths and transaction environments, so that the accuracy, real-time performance and scene adaptability of assessment are improved, and the risk assessment efficiency is improved. The defects of a static evaluation method in the prior art are overcome.

The invention discloses a dynamic digital twinning three-dimensional Gaussian splash rendering system and a dynamic digital twinning three-dimensional Gaussian splash rendering method. According to the system, a static scene is reconstructed by utilizing a three-dimensional Gaussian splashing technology through a semantic scene reconstruction module, semantic information is associated to Gaussian primitives in combination with spatial alignment and semantic injection, and a model with a semantic identifier is generated; multi-source dynamic data are fused and converted into a dynamic data field which can be accessed by a GPU through a multi-mode spatio-temporal data processing module; and through a rendering attribute dynamic modulation module, screening a target primitive according to the semantic identifier, and directly modulating internal rendering attributes such as color, transparency or shape of the target primitive based on a data field query value, thereby realizing internal rendering and visualization of dynamic data. According to the method, the problems that in the prior art, rendering reality and real-time performance are difficult to give consideration to and data and scene fusion is superficial are solved, and dynamic digital twinning rendering with high reality and strong immersion is realized.

One or more data objects from at least one of HR data system may each contain data fields storing HR information. A graphical user interface (GUI) may present primitive coding blocks representing standard graphic programming functions and custom business blocks representing high-level operations customly directed to the one or more data objects. A visual workflow may be constructed using at least one block selected, by a user of the GUI, wherein the at least one block represents operations linking the data fields of the one or more data objects to corresponding input fields of the at least one block. The at least one block of the visual workflow may be translated into a custom data connector comprising executable instructions for obtaining values for the corresponding input fields from the linked data fields and generating, based on the values, at least one corresponding data object storing the HR information.

The application provides a power line icing simulation and prediction method based on data assimilation and artificial intelligence, comprising the following steps: step 1, meteorological elements affecting power line icing generation are predicted; step 2, the initial field of the meteorological mode prediction is adjusted, and the result of the numerical mode prediction in step 1 is optimized; step 3, the result of the numerical mode prediction after the optimization in step 2 is subjected to bias correction processing; step 4, whether icing is generated is determined, and the geographical position where power line icing is likely to occur is marked to form icing spatial distribution information field of the concerned area; and step 5, the warning result of the regional icing thickness is output. The application uses an artificial intelligence integrated constraint model to correct the meteorological prediction data field, obtains corrected meteorological information, calculates the icing spatial distribution field by using a mathematical method, and outputs the icing thickness prediction result, thereby assisting in solving the power line icing warning problem.

The invention provides a UI interface automatic generation method and system based on natural language description, and the method comprises the steps: receiving a natural language demand description text, carrying out the guided completion of fuzzy description in the demand description text, and outputting a standardized demand text; semantic analysis is carried out on the standardized demand text, functional association nodes of UI components and data fields in the text are positioned, analysis deviation is corrected through a domain knowledge graph, and key information including component parameters, field verification rules and component priorities is obtained; calling a design specification library comprising a sub-scene visual standard and a dynamic layout algorithm, and a component library comprising a parameterized configuration function; performing component matching and parameter adjustment based on the key information, a design specification library and a component library to obtain a target component, and generating a front-end code or a low-code blueprint of the target component; and rendering to obtain a UI interface. According to the method and the device, the problems of low demand transmission efficiency, high development threshold and difficulty in multi-terminal adaptation in the prior art are solved.

Systems, methods, and non-transitory computer readable media are configured to perform operations comprising obtaining formatted account data maintained by an entity and associated with an account of a user; accessing in real time account data associated with the account from an institution after the entity has facilitated authentication of the user with the institution; and based on a machine learning model, generating synchronized data that reflects selection of a data field of a data type from the formatted account data maintained by the entity or a data field of the data type from the account data from the institution.

System, method and interface for generating data visualizations are provided. The system receives a user input to specify a natural language command directed to a data source. The system also generates a prompt for generating a data visualization based on relevant data fields and data values, rules that characterize the data visualization, and a context free grammar. The system also prompts a trained large language model using the prompt to generate a structured document following a domain-specific schema based on a shorthand notation. The system also uses a parser that uses the context free grammar to map the structured document to a visual specification. The visual specification specifies the data source, visual variables, and data fields from the data source. The system also generates and displaying a data visualization based on the visual specification, including displaying visual marks representing data, retrieved from the data source, for the data fields.

The invention belongs to the technical field of seismic exploration and artificial intelligence, and relates to a physical perception collaborative fusion-based full waveform inversion neural network construction method, which comprises the steps of required model data construction, full waveform inversion neural network construction, loss function construction, network pre-training, and network fine tuning and application. Physical feature perception and collaborative fusion are carried out through a U-Net network and an adaptive residual learning module, so that the problem that traditional full-waveform inversion depends on synthetic data training and is not matched with an actually measured data field is solved. The designed pre-training strategy not only can get rid of dependence on a large-scale synthetic data set, but also can effectively relieve the domain offset problem through fine adjustment of measured data, thereby improving the generalization ability of the model. And the adaptive residual learning module enables the neural network to adaptively and dynamically optimize feature expression, and improves inversion precision through collaborative fusion of a physical perception mechanism. According to the method, the physical consistency and imaging reliability of speed model prediction can be remarkably improved while the labor cost is reduced.

This disclosure may propose a method for transmitting / receiving a physical protocol data unit (PPDU) with an improved structure and a device related thereto. A station (STA) related to this disclosure can generate an ELR PPDU that includes a data field. The ELR PPDU may include a legacy signal (L-SIG) field containing information related to the length of the ELR PPDU and a universal signal (U-SIG) field containing information for interpreting the ELR PPDU. For example, the L-SIG field, the RL-SIG field, and the U-SIG field may be generated based on the first subcarrier frequency spacing. For example, the ELR PPDU may further include a Short Training Field (STF), a Long Training Field (LTF), an ELR Signal (ELR-SIG) field, and a data field. For example, the STF, the LTF, the ELR-SIG field, and the data field may be generated based on the second subcarrier frequency spacing.

The invention provides a rainstorm flood disaster chain monitoring field knowledge graph construction method, and relates to the technical field of knowledge graph construction, and the method comprises the steps: carrying out the preprocessing of original multi-source disaster data, and obtaining various types of quality-controlled data; calling a disaster field fine-tuning large model and an ontology inference engine based on the preliminary corpus and the multi-class quality-controlled data to generate a core ontology and a sub-document set, screening the sub-document set to construct a document association graph, and calling a mapping model to match a structured data field and a core ontology attribute; performing triple extraction according to the sub-document set and the constructed three-level cue word template; ontology instance attributes are vectorized and clustered, a three-layer collaborative system and an atlas core structure are generated through domain conflict repair and pruning density adjustment, a data calling disaster domain fine-tuning large model is obtained based on a processing process to complement an instance implicit relationship of the atlas core structure, and a target knowledge atlas is constructed. According to the invention, construction of the knowledge graph in the disaster field is realized.

The invention relates to the technical field of ocean remote sensing monitoring, in particular to a remote sensing image-based warm discharge water reference temperature self-adaptive extraction method, which specifically comprises the steps of S01, data acquisition and preprocessing, S02, cumulative histogram generation, S03, curve fitting and smoothing, S04, second derivative calculation and S05, reference temperature determination. According to the method, the reference temperature is determined by analyzing the statistical distribution characteristics of the sea surface temperature data field, namely the form of the accumulative histogram, the physical demarcation point of the background water body and the warm drainage area on the temperature distribution is automatically positioned by using the second derivative, the process is completely driven by data, the interference of subjective factors is eliminated, and the accuracy of temperature distribution is improved. The method can automatically adapt to water areas with different geographical forms and different warm drainage diffusion modes, and objectivity and universality of reference temperature extraction are achieved.

The present disclosure provides communication apparatus and communication method for user-specific persistent allocation. A communication apparatus comprises circuitry which, in operation, generates a transmission signal comprising a common field, a user specific field and a data field, the common field including RU information for each of one or more allocations in the data field and the user specific field including one or more user information, each indicating a user-specific allocation among the one or more allocations in the data field; and a transmitter, which, in operation, transmits the generated transmission signal; wherein the user specific field is free from at least one user information for a persistent allocation containing a recurring transmission among the one or more allocations.

The invention relates to the technical field of prefabricated part modeling, in particular to an interaction system for prefabricated part steel bar parameter driving design and a modularization implementation method. Incrementally updating the engine; the model application module is used for acting the change patch sequence on the three-dimensional reinforcement model in a transaction mode and driving display refreshing; the system further comprises a rule base module and an interpretable verification module. The rule base module stores a steel bar arrangement rule and / or a standard verification rule in a constraint declaration form; the interpretable verification module is used for performing compliance verification on the three-dimensional reinforcement model or the derived quantity thereof based on the evidence data field, and outputting a violation item list; the interactive interface comprises parameter panels and a violation interactive area, and the parameter panels are displayed in groups according to component type parameters, geometric parameters, steel bar parameters and specification options and support interactive modification. According to the method, the script dependency is reduced, the dependency graph increment patch is updated in real time, the automatic specification matching and positioning are realized, and the low-cost expansion is governed by the plug-in.

The invention provides a data analysis large screen generation method and device and a data analysis system.The method comprises the steps that an input data analysis requirement text is obtained, and the data analysis requirement text is a text describing a data analysis requirement; the data analysis demand text, the chart type and the data field are matched, a target chart type and a target data field are obtained, the target chart type is the chart type meeting the data analysis demand, and the target data field is the name of data needed by meeting the data analysis demand; matching a chart template according to the target chart type to obtain a target template; acquiring data corresponding to the target data field and filling the data into the target template to obtain a data chart; and generating a data analysis large screen according to the data chart. The problem of low efficiency of data analysis in the prior art is solved.

The invention discloses a financial credit risk assessment and dynamic optimization method based on a fusion graph neural network, and relates to the technical field of financial management data processing. If the risk association degree does not exceed a preset first threshold value, marking the corresponding node as a risk node, and performing multi-round risk propagation simulation according to a difference value between the risk association degree and the preset first threshold value; the risk association degree of the risk nodes is recalculated in the simulation process, a risk association node set is obtained through summarizing and divided into a plurality of data fields, time sequence graph analysis is conducted on each data field, the risk nodes in the corresponding data fields are extracted according to the time sequence graph analysis, and differentiated risk optimization strategies are generated according to the risk nodes. Through a graph neural network and a dynamic optimization mechanism, the accuracy and real-time performance of financial credit risk assessment are remarkably improved, potential risks can be effectively identified, and targeted countermeasures can be formulated.

A blockchain-verified data tracking system provides enhanced data privacy management through selective masking of blockchain ledger fields. Data transactions associated with a data set are detected and recorded in a blockchain ledger, with certain data fields masked based on a blockchain permission scheme. Network nodes can store and transmit blockchain updates, generating a distributed and secure record of data transactions. The selective masking enables different levels of access to sensitive information based on user roles, permissions, or other criteria, facilitating compliance with data protection regulations while supporting data operations and analytics.

Example implementations include a method, apparatus, and computer-readable medium configured for generating codelets. An interface between a user and a large language model receives a natural language intent for a codelet to be executed within a network function to output one or more requested pieces of information from the network function. A codelet generation application generates a prompt to the large language model to write a codelet in an imperative procedural language to output the one or more requested pieces of information, the prompt including a hook point of the network function and one or more data fields of the network function associated with the one or more requested pieces of information. The application receives, in response to the prompt, imperative procedural language code for the codelet. The application statically verifies whether the procedural language code for the codelet satisfies constraints for execution within the network function.

A system and method for automated defective data record resolution is disclosed. The method is performed by a remote digital claim remediation service operating within a distributed network of computers. The method includes receiving adverse digital claim data comprising a plurality of data fields, where at least one data field contributes to an adverse action against a target digital claim. A feature extraction model processes the claim data to extract defect feature data. A machine learning model then computes defect inferences, identifying likely defect types and associated confidence values. The method further evaluates these inferences against predefined routing criteria, routing the claim data either to a remediation or disposal queue. For remediable claims, a machine learning model generates remediation inferences, which are applied to adapt and correct the claim. The defect-free claim is then resubmitted in real-time or near real-time, accelerating claim processing and enhancing system efficiency.

The invention relates to the technical field of Internet of Things coding, in particular to a communication infrastructure asset digital management and operation and maintenance system based on the Internet of Things, which comprises the steps of acquiring equipment output content, arranging frequency bands and interface identifiers, combining positioning information for verification, generating a unified record structure, expanding coding comparison to form an evolution number, and carrying out management and maintenance. And inserting a character to construct an intergenerational identifier, matching boundary refined region mapping, and aligning and splicing to generate an operation and maintenance identifier. According to the method, a uniform data field structure is formed through sequential combination of frequency band coverage and interface identification and fusion of spatial positioning information, a continuous equipment intergenerational relationship is constructed through splicing of evolution sequence numbers, spatial distribution levels are processed through the number of region registration and boundary rules, and the spatial positioning information is obtained. Uniform identification content is generated through splicing of the intergenerational numbers and the region identifiers, collaborative organization of communication facilities in development states, space attribution and management relations is supported, and the scheduling and management efficiency of asset data is improved.

A system includes a memory configured to store instances of a software application and a quantum processor operably coupled to the memory and configured to receive, from an instance of the software application, a user request to initiate an execution of multiregional interactions. The quantum processor is further configured to determine, based on the user request, structured data items configured to be completed by the user in order to satisfy the user request, identify, based one or more data fields within the structured data items, an input of first user identity verification data for satisfying the user request, extract, based on quantum sensor data obtained from quantum sensors, second user identity verification data, execute one or more quantum machine-learning (QML) models trained to identify whether the second user identity verification data matches to the first user identity verification data, and initiate the execution of the one or more multiregional interactions.

A method is disclosed of a transmitter configured to transmit more than one spatially multiplexed streams having a multi-user physical layer packet for a plurality of users. The plurality of users includes a first type user and a second type user. A first stream is assigned for the first type user and a second stream is assigned for the second type user. The method includes leaving a data field of the physical layer packet empty for the first type user, providing second type user emission strength (in a spatial direction towards the first type user) that falls below a threshold value by controlling a spatial emission pattern associated with the second type user for the physical layer packet, and transmitting the physical layer packet.

A computer-implemented method for generating synthetic data is provided. The method includes receiving user input specifying domain-specific requirements for synthetic data generation and selecting a scenario type. The scenario type is one of Seedless, Seeded, or combination of Seeded and Knowledge Base (KB). The method defines a structured schema based on the user input. The structured schema includes data fields, relationships between data fields, and distributional targets. Based on the structured schema, the method generates an initial set of synthetic data samples using a neural template-driven generation model trained on domain-specific data. The method applies adversarial contrastive sampling. This involves training a discriminator neural network to distinguish between the initial set of synthetic samples and real data samples. The discriminator neural network is used to identify generated samples similar to real data. A contrastive set of samples dissimilar to those identified as similar by the discriminator is generated. The method integrates the initial set of synthetic data samples with the contrastive set to create the synthetic data.

This disclosure provides methods, components, devices, and systems for signaling designs for enhanced long range (ELR) transmissions. Some aspects more specifically relate to preamble field designs of ELR physical layer (PHY) protocol data unit (PPDU) formats. In some implementations, a wireless communication device may transmit, via a universal signal (U-SIG) field, a first indication that a PPDU is associated with an ELR format and a second indication of a station (STA) identifier. Additionally, or alternatively, a wireless communication device may transmit, via a set of ELR symbols within a PPDU, an ELR sequence in accordance with a mapping between basic service sets (BSSs) and ELR sequences. Additionally, or alternatively, a wireless communication device may include one or more subfields within an ELR-signal (ELR-SIG) field in accordance with a location of the ELR-SIG field and employ one or more transmission schemes associated with the ELR-SIG field and an ELR-data field.

The invention relates to the technical field of data integrity verification, in particular to a drug compliance detection method and system for drug supervision, and the method comprises the following steps: extracting a process change data field, eliminating a deviation value and setting a reference, marking and classifying a current batch difference field, recognizing a deviation expansion item, constructing a field mapping path and recognizing an interruption point. And judging whether the interrupt field is missing or not, and generating various result lists. According to the method, through medicine process parameter extraction and abnormal value elimination, a stable reference standard is constructed, representativeness of a comparison standard is guaranteed, classification is performed based on field differences, parameter offset is identified, difference identification precision is improved, continuous offset fields are judged in combination with trend changes, risk early warning timeliness is enhanced, and data inheritance continuity is expressed; according to the method, breakpoint fields are filled and verified, missing information is accurately captured, a closed-loop process of offset identification, trend research and judgment, path tracing and missing verification is integrally formed, and the integrity and sensitivity of data compliance inspection are improved.