55 results about "Data architecture" patented technology

The application discloses a prediction method, system and storage medium for patient drug reactions. The method comprises: constructing a data architecture of a drug reaction prediction model according to pre-input source domain data, target domain data and drug attribute information; based on the data architecture of the drug reaction prediction model, performing training on the drug reaction prediction model according to a target training function to determine execution parameters of the drug reaction prediction model; and determining drug reaction prediction parameters according to the execution parameters, the source domain data and the target domain data to determine a prediction result of the patient drug reaction. The application places the representation alignment process of the patient sample and the cell line sample in the specific drug context fusion information through drug conditionalization alignment, thereby reducing the cross-domain distribution difference. In addition, the drug priority prediction result is generated in units of patients by using the drug reaction prediction parameters, the risk of model degradation into drug identity memory is reduced, and the generalization prediction ability for drugs is enhanced.

The invention relates to the technical field of data encryption, in particular to a transmission encryption method based on a Beidou communication data architecture, which comprises the following steps of: S1) adjusting related communication data and calibrating the related communication data as a data item to be filled or a data item to be missing based on the related communication data needing to be transmitted in the stage and an adaptive data transmission channel in the related data architecture; s2) performing priority processing on the to-be-missing data items, selecting part of data from the corresponding to-be-missing data items based on changed capacity data of the to-be-missing data items, calibrating the part of data as to-be-filled data, then determining to-be-transmitted missing items, performing related filling on the to-be-filled data items, and preferentially confirming filling capacity data corresponding to the to-be-filled data items; relevant data are selected from the to-be-filled data, and then to-be-transmitted filling items are determined; and S3) performing data transmission based on the determined data transmission channel of the corresponding data item, and determining an encryption key of the corresponding data item based on the transmission delay of each group of different data items in the transmission process.

The invention relates to a business system updating method and device, computer equipment, a computer readable storage medium and a computer program product, relates to the technical field of databases, and can improve the adaptation degree of a data architecture and a business current situation. The method comprises the following steps: acquiring a database table of a business system of an enterprise, determining a logic entity corresponding to the database table, and storing the logic entity into an enterprise architecture management system; determining a conceptual entity corresponding to the business object of the enterprise based on a pre-acquired business architecture of the enterprise; determining a first association relationship between the logic entity and the concept entity; based on the first association relationship and a second association relationship between the logic entities, determining a data architecture of the enterprise, and storing the data architecture into an enterprise architecture management system; and based on the data architecture, updating the database table in the business system to obtain an updated business system.

The application discloses a kind of production line unit modeling methods for digital twin monitoring, comprising the following steps: S1, establish production line scene data architecture;S2, establish warehouse production line system requirement diagram and monitoring application requirement diagram;S3, establish warehouse production line structure diagram, equipment structure diagram, value definition diagram, establish warehouse production line activity diagram, equipment activity diagram, equipment mathematical model;S4, establish the object node and variable of OPC UA information model;S5, establish equipment three-dimensional model in Solidwork, import three-dimensional simulation software VC in intermediate format STP;S6, define the operation flow of production line, the operation constraint relationship between each equipment;Define the independent and dependent relationship between each motion structure;S7, according to equipment mathematical model, establish corresponding data structure, determine the data source to collect data and update OPC UA information model.The application has good visualization and interactivity, and production line state feedback is timely, can effectively help manager to understand production line state, improve management efficiency.

The invention discloses a radiation source recognition reasoning question-answering system and method based on graph retrieval enhancement generation, and belongs to the technical field of artificial intelligence and signal processing. The system comprises a data processing module, a knowledge graph construction module, a retrieval and reasoning module, a graph retrieval enhancement generation module and an output module. The method comprises the following steps: preprocessing multivariate data through a three-layer data architecture to generate a structured triple; constructing a dynamic knowledge graph; top-to-bottom accurate retrieval and bottom-to-top context optimization are realized by adopting a U-retrieval strategy; generating a traceable recognition analysis and processing suggestion based on the retrieval sub-graph in combination with a large language model; and outputting a final result with reference and term interpretation. According to the method, the problems that knowledge updating is lagged and reasoning cannot be explained in a traditional radiation source identification system are solved, the identification accuracy, the real-time performance and the result interpretability are remarkably improved, and the method is suitable for radiation source intelligent identification and reasoning tasks in a complex electromagnetic environment.

The invention discloses an enterprise-level architecture modeling and layer-by-layer decomposition method based on a unified meta-model, which comprises the following steps: constructing the unified meta-model covering business architecture, data architecture, application architecture, technical architecture and security architecture domains, including defining core element types and cross-domain association relationship types of each architecture domain; according to the unified meta-model, enterprise-level overall architecture modeling is carried out, and an enterprise-level architecture asset library including multi-architecture-domain standard assets and dependency relationships thereof is generated; and step-by-step architecture decomposition design is carried out on a project to be implemented based on the unified meta-model and the enterprise-level architecture asset library, and a project-level architecture blueprint aligned with the overall architecture, a refined project demand specification and a landing technology design scheme are sequentially output. Through a unified meta-model and a layer-by-layer decomposition tracing mechanism, the problem of disjunction of semantic segmentation and strategic execution in cross-domain architecture modeling is solved, and collaboration, alignment and controllability of cross-domain architecture design are achieved.

The invention belongs to the technical field of new energy power generation prediction and monitoring, and provides an integrated management method for distributed power prediction systems, which comprises the following steps: acquiring operation monitoring data of each distributed power prediction system; performing data architecture analysis on each distributed power prediction system, and establishing a three-level data model taking station-equipment-parameter as a data architecture; performing cross-system data association and aggregation operation on the operation monitoring data of each distributed power prediction system according to the three-level data model to obtain global integration parameters; and according to the operation monitoring data, the three-level data model and the global integration parameters, establishing a multi-class data statistical graph, and visually displaying the multi-class data statistical graph in the same interface. According to the scheme provided by the invention, the global collaboration, response timeliness and accuracy of the management link of the distributed power prediction system are improved.

The invention relates to the field of natural language processing and information visual analysis, and discloses a data architecture and visual analysis method based on a multi-level medical text.The method comprises the steps that a medical document is subjected to paragraph division, and a multi-level text data set containing the medical document, paragraphs, an entity set and entities is constructed; a model based on comparative learning framework supervision training is adopted, a multi-level text is generated into a high-quality text vector, the high-quality text vector is stored in a vector database, and efficient semantic retrieval and topic clustering are achieved; on the basis of a clustering result, the multi-level medical text is constructed into a graph structure, and multi-hop query and correlation analysis are achieved; a multi-force-oriented star map layout and constellation focusing visualization method is combined, and progressive visual analysis and interactive exploration of the medical text in the aspects of a macroscopic theme structure and microscopic content are achieved. According to the method, the accuracy of multilayer medical text structure semantics and the scale of analyzable data are effectively improved, so that a user can deeply analyze a complex large-scale multilayer medical text.

The application provides a data trusted computing framework based on a consortium blockchain, entities include a data demander, a data provider, a consensus node and a certificate authority; a structure is divided into a data registration layer, a data trusted layer, a data consensus layer, a data processing layer and a data delivery layer. The data registration layer adopts a data architecture paradigm based on the consortium blockchain, divides data into identification, characteristic data and data entities to standardize a data registration process, provides a unified access mode for heterogeneous, heterogeneous and heterogeneous data resources and integrates data resources; the data trusted layer uses a data trusted computing mechanism, so that the data provider provides a data resource analysis and processing result for the data demander without contacting original data; the data consensus layer includes a data trusted traceability mechanism, guarantees safety and integrity of data flow; the application can change a traditional data hosting / exchange as a service mode into a data processing as a service mode and realizes data "available but invisible".

The invention discloses a data architecture generation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining micro-service data and class model data of a target project, generating a physical model of a data architecture based on the micro-service data and the class model data, and generating a data architecture file in a target format based on the physical model. According to the method, upstream design results such as micro-service data and class model data of a target project can be imported, and a conversion request can be generated through one-key operation of a client, so that a physical model of a data architecture is generated based on the micro-service data and the class model data, and a user does not need to design the data architecture from a design document; on the one hand, the problem of low accuracy caused by inconsistent understanding of design documents by different users is avoided, the efficiency and accuracy of data architecture design are improved, on the other hand, the user can select the output format of the data architecture file and can use and browse the data architecture file without installing a professional tool, and the user experience is improved. And development and communication of data architecture design are facilitated.

Systems, methods, and computer-readable media are provided for providing access, via a read-optimized database service, to functionally oriented pre-built metadata based logical objects. Each logical object provides access to a set of resources defined by a logical schema relevant to a functional area. Each logical schema is determined based at least in part on a read-optimized, synchronized version of one or more underlying related database structures stored to a read-optimized database accessible via the logical schema using the read-optimized database service, with the logical schema being different than the database schema of the underlying database structures. Requests to the read-optimized database service from a consumer of a particular functional area are evaluated against a particular set of logical resources associated with the functional area and translated to map to relevant underlying database structures, thus eliminating the requirement for consumer to understand underlying complex database structures as well as to shield consumers from underlying database structure changes in the future. Further some of the key text data in reference logical objects can be vectorized for usage in LLM-RAG use cases for assisting in semantic / similarity search of user queries. An attribute defaulting configuration interface and process is also described.

This invention relates to the interdisciplinary technical field of government data governance, natural language processing, and database retrieval. It provides a method and device for constructing a multi-constraint fusion six-tuple dataset for government Text2SQL, aiming to build a multi-constraint fusion dataset GovSQL for government scenarios. It forms a tuple data architecture through a four-stage human-machine collaborative annotation strategy, while introducing an explicit mapping mechanism between policy text and business rules, as well as a constraint annotation process that combines large models and manual annotation, thus solving the semantic distortion problem that is common in the construction of Text2SQL datasets.

The invention relates to a method for supporting automatic batch upgrading of off-line test data of rail transit, electronic equipment and a storage medium. The method comprises the following steps: configuring an off-line route map data architecture; configuring the to-be-upgraded input data in combination with the path of the input data; configuring the batch newly added, deleted and replaced files; generating a uniform structure template from the files in different formats, and placing the uniform structure template in a path where uniform structure configuration is located for configuration; and upgrading the selected input data in batches to realize automatic batch upgrading of the rail transit off-line test data. Compared with the prior art, the method has the advantages of improving test efficiency, being high in adaptability and flexibility, improving test data upgrading accuracy and the like.

Methods, apparatuses, or computer program products provide for assessing performance of a data architecture model via an automated comparison framework. In some examples, techniques disclosed herein include receiving a first structured data object generated by a first data architecture model, receiving a second structured data object generated by a second data architecture model, executing a comparison of the first structured data object generated by the first data architecture model and the second structured data object generated by the second data architecture model, generating, based at least in part on the comparison of the first structured data object and the second structured data object, performance monitoring data associated with the second data architecture model, and refining the second data architecture model based at least in part on the performance monitoring data.

A metadata-driven enterprise data architecture system for automated data collection, processing, and reporting, consisting of: a centralized metadata control repository configured to store canonical enterprise data models and business semantic definitions, source-destination mapping rules and transformation logic, data quality thresholds and matching parameters, governance policies and compliance controls, data provenance relationships and audit tracking rules, security and access control configurations, planning instructions and reporting specifications; an execution and orchestration engine that is operationally connected to the metadata control repository and configured to dynamically interpret metadata definitions, automatically implements data ingestion pipelines to extract data from legacy systems, cloud platforms, application interfaces, files, and streaming sources, performs transformation operations such as normalization, enrichment, deduplication, aggregation, and format harmonization to align the ingested data with the canonical enterprise data model, applies metadata-driven data quality validation, exception handling, and reconciliation processes to ensure accuracy and consistency, and enforces metadata-defined security policies, including role-based access control, encryption, and data masking.Automatic capture of complete data provenance and audit records across all processing stages and creation of standardized operational, analytical, and regulatory reports based on metadata-defined reporting structures and business metrics; where changes to metadata definitions automatically modify the collection, processing, governance, security, and reporting behavior without requiring manual redesign of data pipelines or application code.

This invention relates to the field of database technology and discloses a dynamic data management method oriented towards business complexity. This method parses business logs to construct a real-time business interaction topology graph, calculates the structural entanglement degree representing logical coupling and the access discrete entropy representing the degree of hotspot dispersion, and generates a business state vector. It uses a time series model to predict future states, employs a recursive cost function considering lock blocking diffusion and resource contention effects to calculate execution costs, and generates policy instructions when the net utility meets a lag threshold. Responding to the instructions, it executes dynamic materialized views or transient vertical splitting operations including hot / cold separation, and performs nonlinear adaptive synchronous flow control based on real-time load. This invention quantifies business complexity through graph theory features and combines a predictive decision-making mechanism to achieve proactive data architecture optimization, effectively solving the performance degradation problem in highly coupled and hotspot scenarios.

The invention provides a virtual power plant unified operation platform architecture comprising a service architecture cooperating with a first network platform and a second network platform; the technical architecture is based on distributed micro-service and adopts modular configuration to support decoupling development and deployment of different service functions; the data architecture comprises a distributed storage framework, a computing framework and a data encryption framework; the application architecture is provided with a plurality of functional modules supporting terminal access, and the functions of the plurality of functional modules relate to the fields of resource management, scheduling optimization, transaction management and user service; deploying an integrated architecture, which is centrally deployed in an environment in which private cloud and public cloud are combined, and is used for providing computing power by using edge computing node equipment, supporting containerization and automatic operation and maintenance, and realizing rapid expansion and dynamic deployment; and the bus architecture is respectively connected with the service architecture, the technical architecture, the data architecture, the application architecture and the deployment integration architecture and is used for realizing data interaction among different architectures.

The present application relates to the technical field of production scheduling and resource scheduling management, and discloses a proofing room production scheduling and resource scheduling management system for baking product processing, which comprises a management module for generating a work order pool without preset time and duration, and a scheduling module for triggering administrative matchmaking to assign work orders in response to a factually available event of available physical resources, and updating the resources to a state of doubt in the event of loss of events through an administrative fault-tolerant cycle, wherein the data architecture of separation of scheduling and scheduling is adopted to avoid duration prediction, to synchronize management decisions and non-deterministic physical sites in real time, to solve the decoupling problem of management data and physical reality, and to guarantee the administrative robustness of the management system in the event of loss of events.

The application discloses a kind of decoupling methods, devices and storage medium of enterprise data architecture, it is related to the technical field of data management, the method of the application comprises: obtaining data object in target data architecture and the dependent relationship between the data object;According to the data object and the dependent relationship, data architecture directed graph is constructed;According to the data architecture directed graph, the multidimensional centrality index and weight value of each data object are calculated;According to the multidimensional centrality index and the weight value, determine target coupling node, and execute corresponding decoupling strategy for the target coupling node.The application determines the corresponding decoupling node by abstracting data architecture into directed graph and applying graph theory centrality principle, and executes corresponding decoupling scheme, solves the problem that data model coupling degree is high in enterprise-level data warehouse, link is rigid, improves the maintainability of data architecture and the reuse value of model.

A multi-layer facial recognition collection system for real-time facial recognition including a legally adaptive, multi-layer facial recognition data architecture designed to collect facial recognition data without violating federal or state biometric or privacy laws. The multi-layer facial recognition system uses rotating, time-bound facial recognition data collection applications that continuously, independently and temporarily collect, store and then purge facial recognition data on fixed time schedules (e.g., every 30-90 days). An Artificial Intelligence (AI) layer controls all facial recognition matching and lookup attempts with no human intervention and no human access to the collected and stored facial recognition data.

The present invention relates to the field of computers, and more specifically to a matrix data broadcast architecture. Systems, apparatuses, and methods are disclosed for efficiently executing multiple work units in a processor in parallel by reducing the number of memory accesses. A computing system includes a processor core having a parallel data architecture. The processor core executes a software application with matrix operations. The processor core supports broadcasting shared data to multiple compute units of the processor core. A compiler or other code assigns a thread group to a compute unit based on detecting shared data between compute units. The processor core generates a single access request instead of sending multiple read accesses to a memory subsystem to fetch the shared data. The single access request includes information identifying the multiple compute units to receive the shared data when broadcast by the processor core.

The invention discloses an e-commerce platform system supporting multi-type commodity, service release and order processing, which belongs to the technical field of data processing, and the core of the system is that a data architecture based on an independent domain model is adopted, and exclusive data tables are respectively established for various commodity types such as physical, virtual and non-transactional information. The system comprises a mixed shopping cart module which allows users to add commodities in a cross-type manner and can generate a unified total order. And after the order is successfully paid, the system intelligently routes to the corresponding performance process according to the commodity type identifier of the sub-order, such as logistics delivery, content authorization or authority unlocking. The method solves the problems of limited commodity form support, business process splitting, system performance bottleneck and the like of an existing e-commerce platform, is particularly suitable for comprehensive vertical fields such as science and education products, online education and the like in which multiple business forms need to be fused and processed, and realizes double improvement of user experience and system efficiency.

A method for dynamic data visualization and updating of subsea pipelines integrating BeiDou positioning is disclosed, relating to the field of marine engineering digitization and 3D visualization technology. This method constructs a marine digital twin data architecture consisting of a perception layer, a data layer, a fusion layer, a model layer, and an application layer. The perception layer integrates BeiDou positioning terminals, pressure sensors, temperature sensors, and sonar detection equipment deployed along the subsea pipeline to collect pipeline position coordinate sequences, environmental parameters, and seabed topography data in real time. The data layer standardizes, cleans, and encrypts multi-source heterogeneous data for storage. The fusion layer employs an adaptive Kalman filter algorithm to tightly couple BeiDou positioning data and inertial navigation data to obtain centimeter-level accuracy in the dynamic spatial position of the pipeline. By constructing a real-time fusion architecture of high-precision BeiDou positioning data and multi-source sensor data, dynamic visualization updates and secure interaction of the subsea pipeline's spatial position, operational status, and structural morphology are achieved.

Systems, methods, and computer-readable media are provided for providing access, via a read-optimized database service, to functionally oriented pre-built metadata based logical objects. Each logical object provides access to a set of resources defined by a logical schema relevant to a functional area. Each logical schema is determined based at least in part on a read-optimized, synchronized version of one or more underlying related database structures stored to a read-optimized database accessible via the logical schema using the read-optimized database service, with the logical schema being different than the database schema of the underlying database structures. Requests to the read-optimized database service from a consumer of a particular functional area are evaluated against a particular set of logical resources associated with the functional area and translated to map to relevant underlying database structures, thus eliminating the requirement for consumer to understand underlying complex database structures as well as to shield consumers from underlying database structure changes in the future. Further some of the key text data in reference logical objects can be vectorized for usage in LLM-RAG use cases for assisting in semantic / similarity search of user queries. An attribute defaulting configuration interface and process is also described.

The application belongs to the technical field of equipment digital modeling, and particularly relates to an equipment digital main line construction method based on product decomposition structure. The method comprises the following steps: constructing an aircraft forward research and development global data architecture based on an aircraft product decomposition structure, decomposing the aircraft product into a multi-layer structure, each layer comprising a requirement transmission data chain, a product research and development data chain and a requirement verification data chain; determining the requirement transmission relationship of each layer for the requirement transmission process, and penetrating the requirement transmission data chain of each layer from top to bottom; determining the interaction relationship between the task domain, scheme domain, product domain, manufacturing domain and support domain of each layer for the product research and development process, and establishing a product research and development data chain penetrating the whole process; and establishing a requirement verification data chain connecting the requirement verification method, requirement verification task, requirement verification scene and requirement verification result for the requirement verification process. The application can realize global correlation analysis of the aircraft research and development whole-process model data.

This invention discloses a method and device for displaying calligraphy and painting using augmented reality (AR), relating to the field of AR technology. The method includes: scanning the display screen of calligraphy and painting works on an eye-tracking digital terminal and constructing a dense geometric layer and a sparse tracking layer of a two-layer data architecture; extracting information anchor points of specific elements and generating a set of information anchor points; performing eye tracking and gaze point calculation on the user to obtain precise gaze point coordinates, and performing hit determination and activation to obtain the target anchor point hit by the user's gaze; constructing a substrate and potential field environment and activating a multi-target enzyme-based optimization algorithm to solve for the user's three-dimensional pose coordinates; and dynamically overlaying and rendering the target digital information data package onto the display screen of the calligraphy and painting works based on the three-dimensional pose coordinates, achieving a fusion display of calligraphy and painting. This invention solves the problems of AR tag occlusion, rigid layout, cumbersome interaction, and low rendering efficiency in existing technologies.

The application relates to a matrix data architecture, comprising a matrix head and a matrix block; the matrix head comprises a matrix row, a column number, a non-zero element number, a matrix block number and a vectorization length S VVec ; the matrix block comprises a matrix block element; the length of an x vector pixel geometry block corresponding to each of the matrix blocks is S ImgB ; the structure of the matrix block is at least two, which are a fixed-length dense VxG block and a fixed-length sparse VxG block. A method for accelerating sparse matrix vector multiplication (SPMV) based on compressed sparse columns is used to convert the matrix format of an input sparse matrix A into the above-mentioned matrix data architecture, which is a sparse matrix storage format; the SPMV calculation is performed on a local temporary y vector reordering and full vectorization. The data architecture has the characteristics of small space occupation. In combination with the method for accelerating SPMV based on compressed sparse columns, hardware vectorization calculation instructions and memory bandwidth can be efficiently utilized, so that the SPMV can run at a faster speed, and the purpose of acceleration is achieved.

The invention relates to the technical field of electric power material supply chain management and data processing, and discloses a power grid material internal collection transaction full-process tracing and abnormal behavior identification method, which comprises the following steps: collecting power grid material purchase full-process multi-terminal data, constructing a multi-dimensional and multi-coordinate-axis composite data architecture, and generating an internal collection data set; inputting the data into a decision rule for judgment, establishing a clean and error standard data pool, and executing a progressive convergence closed loop for repairing and rejudging repairable error data; monitoring an error data volume in real time, mining an error mode by using a clustering model, and reversely updating a decision rule to realize self-adaptive evolution of the rule; constructing a supplier association network map, calculating the percolation conductivity of the entity and the association edge based on the percolation theory, and generating a comprehensive evaluation value; and finally, comparing the evaluation value with a preset section to generate a graded early warning signal and executing treatment. According to the method, the data quality is effectively improved, and deep penetration identification and dynamic defense of the supply chain implicit association risk are realized.

The invention provides a data acquisition monitoring system suitable for a power grid container cluster and industrial control equipment, and relates to the technical field of power grid monitoring, and the system comprises a data acquisition module which collects multi-dimensional operation data of the power grid container cluster and associated industrial control equipment through a dynamic sampling mechanism; the cloud native scheduling module is used for realizing acquisition task distribution and resource dynamic capacity expansion and contraction; the mimicry protection module is used for forming a defense barrier by dynamically changing the form of a monitoring node, and processing the collected data by adopting a four-layer data architecture; the hierarchical data processing module is used for processing the acquired data by adopting a four-layer data architecture; the industrial control intelligent monitoring module is fused with an industrial control fingerprint technology and a baseline comparison model to realize asset monitoring and anomaly tracing; the link guarantee module is used for guaranteeing link stability based on health degree assessment and a self-healing mechanism; according to the invention, through a dynamic sampling frequency mode combining the container load coefficient and the equipment importance grading, adaptive adjustment of the sampling frequency is realized, and resource redundancy consumption is reduced.

The application relates to an in-process change handling method and device based on a modular data architecture, comprising: obtaining a main line design configuration product structure according to preset basic rules; creating a corresponding change handling sheet for a specific flight change, and identifying a flight validity interval to which the change handling sheet is applicable; determining a design module associated with the change handling sheet of the specific flight change according to a preset flight validity interval calculation rule; identifying an in-process change required to be carried out on the design module by comparing the change handling sheet and the associated design module; and completing single-machine EBOM analysis according to a preset validity calculation rule.