36 results about "Heterogeneous source" patented technology

The invention relates to the technical field of electric digital data processing, and discloses an intelligent data processing method for clinical research. The method comprises the following steps: constructing a basic clinical knowledge graph fused with an international medical ontology; the method comprises the following steps: performing deep learning driven entity recognition and knowledge graph linking on original data from heterogeneous sources such as an electronic medical record and an inspection system; executing cross-source entity alignment and knowledge fusion based on the graph attention network; performing automatic data quality verification and restoration according to clinical logic rules embedded in the atlas; and finally, extracting and generating a standardized analysis ready data set from the enhanced atlas according to research requirements. According to the technical scheme, high-quality, automatic and semantic integration and flexible delivery of clinical research data are realized, and the data processing efficiency and research reliability are improved.

The application provides a multi-level index calculation system and method based on configuration, and relates to the technical field of data processing, and comprises an acquisition module, a rule configuration module and an index calculation module; the acquisition module is configured with a metadata model; the acquisition module is used for acquiring a plurality of heterogeneous source data and extracting field metadata by using the metadata model; the rule configuration module is used for configuring a calculation rule for a target index based on the index type of the target index; the index calculation module is used for matching the field metadata of the plurality of heterogeneous source data according to each calculation rule, and determining the heterogeneous source data with matched field metadata as index calculation data required for calculating the target index; and in the order from high to low of the calculation priority, the statistical calculation method of the corresponding calculation rule is sequentially executed on the index calculation data to obtain index result data of the target index. The whole process dynamic generation from original data to multi-level indexes is realized.

The invention discloses a method for integrating and analyzing heterogeneous data (3) from a heterogeneous source application (2). The method is used for solving the inherent non-standardization problem of a data model used by a Web-based database platform. All platforms adopt different data configurations, so that a unified and standard data presentation mode cannot be followed, and structural aggregation of information is not facilitated. In order to achieve the purpose, the computer implementation method comprises the steps that a calculation data collection program (1) is executed to access and load heterogeneous source data (3); providing a heterogeneous data integration module (4) for converting the heterogeneous source data (3) into target data (5); performing a data analysis process (6) based at least on the target data (5) to generate output data (7); and writing the output data (7) to the normalized database (8).

This invention relates to a fault early warning system for hydro-generator units based on CEGD-FNN. The system includes: a feature extraction module for early fault signals of the hydro-generator unit, a fault diagnosis module for the hydro-generator unit, a status assessment module for the hydro-generator unit, a fault prediction module for the hydro-generator unit, and a human-machine interface module. These modules are sequentially connected. This invention employs a unified data platform integrating heterogeneous source information and a unified platform for open knowledge resource sharing. It can promptly obtain heterogeneous data from distributed systems and knowledge resources from different users, thereby achieving intelligent collaborative diagnosis of equipment faults and reducing losses caused by insufficient timely handling of emergency faults.

The application provides a connection code generation method and device, electronic equipment, computer readable storage medium and computer program product; the method comprises the following steps: determining a plurality of uniform interface models in the memory for a plurality of source heterogeneous source files corresponding to a plurality of hardware modules; based on each uniform interface model, a hierarchical signal tree is constructed for each hardware module; based on a plurality of signal trees, determine the signal pair to be matched, and determine the bit width topology characteristics of the interface signal in the signal pair to be matched; calculate the similarity between the names of the interface signals in the signal pair to be matched, and the compatibility score of the direction; based on the bit width topology characteristics, the similarity and the compatibility score, determine the consistency score of the signal pair to be matched, and when the consistency score is greater than the score threshold, it is determined that the signal pair to be matched has a connection matching relationship; based on the connection matching relationship, a first connection code is generated. Through the application, the generation accuracy of the connection code of the interface signal can be improved.

The application provides a data management method, comprising: acquiring heterogeneous source data; the heterogeneous source data comprises basic information and power consumption data of an enterprise; performing data adaptation on the heterogeneous source data to obtain first data; performing standardization on the first data to obtain second data; performing quality evaluation on the second data; and generating a quality report according to the result of the quality evaluation. By adapting and standardizing the data, the type of data that can be analyzed is increased, the adaptability of analysis is expanded, the heterogeneous source data is comprehensively analyzed, and the efficiency of data processing is improved.

This application provides a method, apparatus, device, and medium for heterogeneous code translation. The method includes: acquiring heterogeneous source code running on a source heterogeneous hardware system; compiling the heterogeneous source code to generate an intermediate representation of the source heterogeneous hardware system; mapping the intermediate representation of the source heterogeneous hardware system to obtain an LLVM intermediate representation; and mapping the LLVM intermediate representation to obtain RISC-V extended code, which is used to run on a target hardware system. This application improves the compatibility between code and target hardware systems.

The invention discloses a mammary gland endoscope preoperative anatomical variation identification method and system, and relates to the technical field of computer data processing. The method comprises the following steps: S1, acquiring heterogeneous source data, and performing spatial registration and data standardization fusion to generate a multi-dimensional fusion data set; s2, performing basic topological feature extraction based on the multi-dimensional fusion data set, and calculating edge weight information to construct a target topological graph; s3, matching and comparing the target topological graph with a preset standard topological database, and calculating topological compliance parameters based on comparison differences; s4, identifying a parameter abnormal region according to the spatial distribution characteristics of the topological compliance parameters, and generating a spatial security constraint model in combination with local spatial medium attributes; and S5, based on the spatial security constraint model, outputting structure abnormal information and corresponding optimized path planning parameters. And through multi-channel tensor quantization variation characteristics, safety constraints are constructed by using an anisotropic bounding box, and a path is optimized in combination with a potential field algorithm, so that high-precision automatic obstacle avoidance is realized.

This invention provides a method, device, and storage medium for generating and utilizing a multimodal discourse tree (MMDT). [Solution] The method generates an Extended Discourse Tree (EDT) from a text corpus (e.g., from a Discourse Tree (DT) or Communication DT (CDT)), links data records (e.g., records containing numerical data) to the Extended Discourse Tree, and generates a Multimedia Discourse Tree (MMDT). The MMDT links any suitable text / records from heterogeneous sources. For example, entities identified from the basic discourse units of the EDT are matched with entities in the data records. The method also identifies causal links between EDTs and / or between data records, identifies rhetorical relationships for each entity match / causal link match, and merges the data records with the EDT to generate the MMDT.

The invention relates to the field of intelligent doorplate management, and particularly discloses an intelligent doorplate dynamic management system and method based on an LORA technology, which are characterized in that external heterogeneous source data such as OA, educational administration and the like are grabbed, cleaned and packaged in a standardized manner at a front end through protocol adaptation and data engine technologies, and information islands are broken to realize automatic content production; the transmission layer reconstructs network data into high-penetrability LORA radio-frequency signals for wide-area broadcasting by utilizing a cloud compiling and gateway protocol conversion mechanism; and the terminal side adopts a periodic wake-up strategy based on a CAD mechanism, and drives the electronic ink screen to refresh and immediately and automatically cut off the power supply only after the verification of the effective signaling is passed. Therefore, real-time synchronization of the physical identification and the digital service is realized without manual intervention through full-link data closed-loop circulation, and meanwhile, extremely-low-power-consumption long-term operation of the system is ensured by utilizing a bistable display characteristic.

This invention proposes a heterogeneous data mapping optimization method, relating to the field of software development technology. It constructs a JSON Schema model library containing business and credential objects by acquiring heterogeneous source data. The construction process includes parsing the data format, extracting features, and completing the construction and classification storage using DSL rules and visual editing. Based on this model library, a mapping relationship description document is generated using a preset abstract mapping rule template and extended JSON Schema syntax. The mapping engine parses the document to construct a field-level dependency graph, and performs data transformation accordingly. The transformation process employs lazy execution and caching mechanisms. The transformed data and mapping process are verified using a combination of static pre-verification and incremental verification. Furthermore, the mapping rules are dynamically adjusted and version managed based on the verification results or model changes. This invention improves the efficiency, flexibility, and accuracy of data mapping and optimizes system performance through the above steps.

The invention relates to the field of data communication, in particular to an oil and gas station heterogeneous data integration method and device, electronic equipment and a computer readable storage medium. The method comprises the following steps: acquiring heterogeneous source data generated by each data source through a source channel corresponding to each data source; environment interference intensity in the oil and gas station is collected; adjusting each source channel according to the environmental interference intensity so as to reduce the packet loss rate of the heterogeneous source data; and mapping the heterogeneous source data to a standard data form based on a preset mapping rule to obtain standard source data in one-to-one correspondence with the heterogeneous source data, and fusing all the standard source data. According to the oil and gas station heterogeneous data integration method and device, the electronic equipment and the computer readable storage medium, the technical effect of improving the data quality of the data obtained through multi-source heterogeneous data integration and fusion in the oil and gas station can be achieved.

The invention belongs to the technical field of data processing, and provides a scientific research domain knowledge graph construction method, system and device and a storage medium, and the method comprises the steps: building a database, employing a dynamic data strategy, employing a BERT-wwm model to solve entity ambiguity, constructing a domain dictionary tree, and forming a heterogeneous source database processing system; constructing a hierarchical progressive reasoning framework which comprises a basic relation layer, a business relation layer and a dynamic evolution layer; an entity relation network is stored through Neo4j, time sequence change data is recorded by using TTDengine, a dynamic relation topology is established, and a knowledge graph is generated. According to the method, a hierarchical progressive reasoning framework combining a basic relation layer, a business relation layer and a dynamic evolution layer is constructed, so that the limitation of a traditional knowledge graph in the aspects of dynamics and business adaptability is effectively solved. Not only is the capture capability of static association enhanced, but also domain characteristics and implicit logic are deeply analyzed, and the reasoning accuracy in scenes such as scientific research supply chain optimization and the like is remarkably improved.

The invention provides a multi-region interconnection system carbon emission factor calculation method considering multivariate heterogeneous source load access. The method comprises the steps that a topological structure of a multi-region interconnection system, operation parameters of all source load devices and carbon emission basic data are acquired; calculating a carbon emission factor of the energy storage element by adopting an electric quantity pack sequence model, dynamically adjusting an electric quantity pack sequence according to a magnitude relationship between a discharge demand and the extracted electric quantity of the electric quantity pack, and determining a discharge carbon emission factor based on the carbon emission factor corresponding to the extracted electric quantity pack; based on the real-time carbon emission intensity of the system, a flexible allocation coefficient is dynamically generated through a nonlinear correlation mechanism, and the carbon emission responsibility corresponding to the power loss power in the region is bidirectionally allocated to a load side and a power supply side; and according to the distribution result of the network loss carbon emission responsibility, constructing a virtual lossless network, and based on the virtual lossless network, correcting the carbon emission factors of each node between the regions and in the regions and outputting the carbon emission factors.

The invention relates to the technical field of large model application, and discloses a data visualization narrating method and system based on a large model. The method comprises the steps of obtaining structured original data in an ERP system, a CRM system and IoT equipment; generating a unified event set; performing synchronous identification of cross-source events; constructing a heterogeneous event graph; outputting a causal chain set based on a graph attention path decoding model; and outputting the visual narrative template and the display instruction set. In the prior art, causal modeling is carried out mainly depending on a single-mode data flow or a static business rule, and especially under the condition that an enterprise has multi-business system collaboration and semantic description is inconsistent, high-credibility causal chain reconstruction and structured narrative output cannot be realized. Due to the fact that a graph attention mechanism driven path decoding and cross-modal event recognition mechanism is introduced, dynamic causal path extraction and visual structured reconstruction of complex business events between heterogeneous sources are achieved.

A system for determining a degree of dependence on screens of a user, includingat least one software module embedded in a set of information processing apparatuses, adapted for collecting first measurements about the behavior of the applications installed on said information processing apparatuses and second measurements about the behavior of said information processing apparatuses;a database for storing said measurements;a server for periodically determining an aggregation of said measurements and a degree of dependence on screens according to said aggregation.

This invention discloses a heterogeneous extension component concurrent loading and dependency coordination architecture. Through concurrent acquisition of heterogeneous sources (remote repositories, temporary injection, pre-embedded components, dynamic inlining), declarative pattern verification of extension component descriptors, multiple heterogeneous source type adapters, offline resource discovery, dependency coordination and degradation, runtime configuration optimization, hierarchical exception management, adaptive dependency resolution, intelligent hot updates, sandbox isolation, dynamic capability negotiation, and predictive preloading, it achieves an efficient, reliable, and secure extension system. The system supports trusted source authentication, access control decisions, and functional unit extraction, and is suitable for command-line tools, integrated development environment extension systems, and extensible application frameworks. This invention effectively solves the shortcomings of existing extension component loading mechanisms in terms of heterogeneous source support, dependency coordination, security isolation, and loading efficiency, and can be widely applied in plug-in systems, modular applications, and microservice architectures.

This disclosure relates to the field of power system technology, and discloses a method and apparatus for joint prediction of electricity price, source, and load for integrated energy systems. The method involves processing heterogeneous load-side data and operating condition information to obtain dynamic conversion coefficients corresponding to various load types; constructing an energy layer representation based on heterogeneous source-side data, dynamic conversion coefficients for various load types, heterogeneous load-side data, and operating condition information over a specified time period; constructing a market layer representation based on electricity price information and operating condition information over a specified time period; processing the energy layer and market layer representations using a bidirectional coupling unit to obtain a cross-layer coupled representation; and using a multi-task sequence prediction decoder to perform prediction processing on the cross-layer coupled representation and combining it with real-time rolling cycle information for correction to obtain a prediction set, which includes predicted electricity price information, predicted source output information, and predicted equivalent load information. This significantly improves the accuracy of electricity price prediction, energy output prediction, and energy consumption prediction.

A processing configuration for adaptive data ingestion and mapping receives and parses data from heterogeneous sources without requiring predefined schemas, processing structured, semi-structured, and unstructured formats. The configuration identifies entities, attributes, and relationships within parsed data and aligns them with an ontological structure using rule-based processing, machine learning, and natural language processing to resolve semantic variations. The aligned data is refined and standardized based on historical patterns, domain-specific rules, and real-time operational context, with transformations adjusted dynamically in response to data changes. Changes in incoming data are detected and differential updates are applied to previously processed data, modifying only affected portions while maintaining computational efficiency. Normalized data is organized into a graph format establishing contextual relationships between entities, and these relationships are mapped to visualization elements for presentation to decision-support systems.

The invention relates to the technical field of decision support systems, in particular to a cloud intelligent decision support system and method supporting heterogeneous data sources, and the system comprises a heterogeneous logic alignment module, a pressure parameter derivation module, a self-adaptive simulation deduction module, a computing power value evaluation module and a decision confidence quantification module. According to the method, by means of numerical field combination calculation and topological structure comparison, an attribute constraint graph is constructed to judge logic isomorphism, the problem that heterogeneous source semantics are fuzzy is solved, gradient disturbance parameters are generated based on sliding window statistical superposition pressure coefficients, and extreme scenes are simulated in a definition domain boundary. A high-frequency log stream and a low-frequency aggregation table are dynamically switched according to index deviation, high-granularity data support is guaranteed during abnormal fluctuation, resource occupation is reduced in a stationary period, the storage efficiency ratio is calculated in combination with CPU instruction cycle consumption and access counting, high-calculation-cost data is prevented from being mistakenly deleted, the risk opening and efficiency ratio is evaluated, the reliability of a decision scheme is quantified, and the reliability of the decision scheme is improved. And an explanatory confidence basis is provided.

The invention discloses a ship sound stealth expert model construction method based on a knowledge graph, and the method comprises the following steps: data extraction: collecting and preprocessing data from various determined heterogeneous sources, converting a processing format, cleaning initial data, and preparing data for subsequent knowledge extraction; knowledge graph construction: taking the preprocessed data as input, and coordinating and creating a sound stealth knowledge graph; and retrieval enhancement generation: providing a user-friendly environment for the expert user based on LLM and GraphRAG to interact with the expert model. The invention discloses a ship sound stealth expert model construction device based on a knowledge graph. The method realizes the vertical field question-answering effect of the ship acoustic stealth specialty, provides professional question-answering service and friendly interaction service for the user, and can be widely applied to the technical field of top acoustic design.

The invention discloses a data integration heterogeneous data consanguinity acquisition and storage method and system, and aims to solve the problems of consanguinity deficiency, difficulty in heterogeneous source tracking and the like in a non-SQL (Structured Query Language) integration scene. The method comprises the following steps: acquiring a JSON (JavaScript Object Notation) operation configuration file for configuring a drive type data integration tool (such as DataX), and analyzing and extracting source end / target end information, field mapping and conversion logic (including Transform plug-in parameters); the monitoring execution log checks and supplements the dynamic execution information; constructing a unified blood relationship model containing nodes (a data source, a data set, a task, a field and a conversion plug-in) and edges (a data flow and conversion relationship); and storing in a graph database and providing a query visualization service. According to the method, SQL analysis limitation is broken through, non-SQL scenes are covered, heterogeneous data source accurate tracking and field-level blood relationship restoration are achieved, a'black box 'of a synchronous task is broken through, the data governance efficiency is improved, and a framework is universal and can be expanded to similar tools.

A computer system is provided that is programmed to select a set of features from a large number of features. The features of the set are selected based on meta-gradient information returned from a machine learning process that has been performed on an earlier selected set of features. The process can iterate until the selected set of features converges or otherwise meets or exceeds a given threshold.

A computer system is provided that is programmed to select feature sets from a large number of features. Features for a set are selected based on metagradient information returned from a machine learning process that has been performed on an earlier selected feature set. The process can iterate until a selected feature set converges or otherwise meets or exceeds a given threshold.

This invention discloses a multimodal data fusion intelligent analysis system and method, including a multimodal data integrated access and acquisition module, a data fusion and intelligent analysis module, and an intelligent decision-making and resource scheduling module. This system integrates medical data from multiple heterogeneous sources and performs fusion analysis and decision support through advanced machine learning models, aiming to improve diagnostic and treatment efficiency, assist clinical decision-making, and optimize the allocation of medical resources.

The invention discloses an unstructured message processing method, system, equipment and medium, and belongs to the technical field of data analysis processing, and the method comprises the steps: constructing a heterogeneous source data model, locking an atomization component sequence, extracting effective elements through feature cutting and cascade recursion analysis, and finally loading the effective elements to a standardized target model. The system comprises a source data model building module, a component sequence locking module, a feature recognition and cutting module, a cascade analysis model building module, a recursive circulation driving module and a structured recombination module. According to the invention, through dynamic arrangement of the atomization component and a multi-level cascade mechanism, precise recursive analysis of the complex nested message is realized. Component hot loading and strategy dynamic updating are supported, and flexible capacity expansion is achieved on the premise that high availability of services is guaranteed. The method gets rid of dependence on complex regularization, the processing efficiency of the unstructured data is remarkably improved, and the maintenance cost is reduced.

The invention relates to the technical field of big data processing, and discloses a distributed data real-time acquisition and management system which comprises a data processing center and a plurality of distributed edge acquisition nodes, the edge acquisition nodes are used for receiving heterogeneous source end original data streams, and protocol adaptation modules, semantic value weight modules and differential flow control modules are integrated in the edge acquisition nodes. The protocol adaptation module constructs a protocol fingerprint by using the Shannon information entropy and byte frequency distribution of the preamble segment to realize adaptive matching and decoding of a heterogeneous protocol; the semantic value weight module distributes a dynamic value weight label for the data record based on a business rule; and the differential flow control module calculates a congestion control coefficient by using a PID algorithm, and differentially adjusts the token generation rate of each level of queue. According to the invention, intelligent access of heterogeneous data sources is realized, and real-time transmission of high-priority data can be guaranteed preferentially when the network is congested.

The application discloses a resource attraction domain characterization method, system, equipment and medium based on Lyapunov theory, and belongs to the technical field of distribution network operation stability analysis, and comprises the following steps: a heterogeneous source-side resource mathematical model is established according to the composition and control mode of different types of source-side resources in a distribution network; the mathematical model is limited according to preset requirements, and a high-order nonlinear model is obtained; the high-order nonlinear model is subjected to fuzzy processing, and a fuzzy model is obtained; a Lyapunov energy function is constructed according to the fuzzy model; and the Lyapunov energy function is analyzed under the constraint of stability conditions to construct the attraction domain of source-side resources in the distribution network. The application solves the problems that the prior art is difficult to adapt to the nonlinear characteristics of source-side resources, is inefficient and cannot form a unified expression.