222 results about "Data dictionary" patented technology

The invention discloses a multi-modal heterogeneous medical equipment data fusion and decision support method and device, and aims to solve the problems that the fusion precision is low due to space-time semantic difference of medical equipment multi-modal heterogeneous data (equipment operation parameters, clinical records, fault signals and the like), equipment management decisions depend on experience, and standards are not uniform. According to the method, breakthrough is achieved through three-level data alignment of'time-space-semantics', hierarchical fusion of'data level-feature level-decision level ', three-level decision driven by a knowledge graph and dynamic feedback optimization: time alignment uses a dynamic time warping algorithm, space alignment depends on a unified data dictionary, and semantic alignment introduces an attention mechanism; the feature level fusion quantifies the feature support degree based on the D-S evidence theory; the decision-making layer constructs a'rule-case-prediction 'three-level system, and combines cosine similarity retrieval and information entropy quantification uncertainty. The method and device can support medical equipment maintenance, clinical diagnosis and treatment and other scenes, and the medical service standardization level and the equipment management efficiency are improved.

The invention relates to a low-code visualization optimization method and system for power credential development, and the method comprises the following steps: S1, obtaining data in a credential environment, recognizing the interface difference and performance bottleneck points between components through a compatibility test matrix, and building a standardized adaptive interface specification; s2, obtaining a standardized business object model based on the standardized adaptive interface specification; based on the business object model, defining attributes, relationships and constraint rules of each business entity, and forming a data dictionary and an interface specification special for the electric power field; s3, on the basis of the data dictionary and the interface specification special for the power field, constructing a DSL (field specific language) of power visualization; s4, a dragging type interactive design is adopted, and the visual operation is converted into a DSL configuration file; and S5, automatically converting the DSL configuration into a React or Vue component code through a code generation engine, and carrying out compatibility optimization on the kernel of the creative browser. According to the invention, the power credential development efficiency is effectively improved.

The invention provides a method and device for extracting report data based on a large model technology, and relates to the field of batch data processing, and the method comprises the steps: carrying out the intelligent table splitting processing of obtained report image data through a pre-constructed intelligent report prompt word project, and obtaining an effective target report; carrying out metadata dynamic extraction processing on the effective target report by utilizing a pre-constructed data extraction cue word project to obtain a report label; performing multi-dimensional data integration processing on the effective target report by utilizing a pre-constructed data integration prompt word project and the report label to obtain a report data dictionary; and performing subject semantic mapping on the effective target report according to the report data dictionary to obtain a required data report. According to the method, a complete automatic processing flow can be constructed, and intelligent report splitting, metadata dynamic extraction, multi-dimensional data integration, subject semantic mapping and the like are realized by combining an optical symbol recognition technology with a large model technology.

In one aspect, a computerized method for document extraction workflow for unstructured documents includes the steps of implementing a text mining operation on a set of digital documents the incoming documents. This is done by defining a document type of each digital document. Based on the document type, the method defines a set of data dictionaries to extract any data from each digital document. The method uses the defined set of data dictionaries to extract any data from each digital document.

Disclosed in the present invention is an intelligent energy efficiency management system for an LNG dual-fuel powered trailing suction hopper dredger, comprising: an online intelligent LNG energy efficiency monitoring module, configured to collect energy efficiency key factor parameters of a main energy consumption device of the LNG dual-fuel powered trailing suction hopper dredger to form a unified LNG powered trailing suction hopper dredger energy efficiency data dictionary; an intelligent energy efficiency analysis and evaluation module, configured to construct, on the basis of the LNG powered trailing suction hopper dredger energy efficiency data dictionary, an operating condition identification model, an energy efficiency indicator calculation model, a carbon emission calculation model, an energy efficiency level model and a periodic energy efficiency analysis model to form an energy efficiency analysis and evaluation system; and a dredging operation energy efficiency auxiliary decision-making module, configured to construct an energy consumption prediction model for ten-thousand cubic meters of soil on the basis of soil type, design dredging depth, construction parameters and historical fuel consumption data, and recommending a dredging construction operation parameter combination by means of an optimization algorithm. Also disclosed is an intelligent energy efficiency management method for an LNG dual-fuel powered trailing suction hopper dredger. The present invention increases the energy efficiency.

A system incorporates a platform for analysis of electronic files relating to an old insurance policy using computer protocols such as visual analytics tools to identify attributes of the insurance policy. A policy migration process automates typically complex custom migrations in a methodical workflow employing a simplified metrics-driven process. Layers of a data migration and policy transformation workflow include source policies layer, normalization layer, and target policies layer. The normalization layer includes an extraction, transformation, and loading (ETL) engine. The ETL engine inputs configuration files that incorporate mapping rules for mapping source policies to normalized values within a data dictionary. Systems of the disclosure incorporate built-in personas that cater migration features to a specific set of migration execution team roles such as policy edit and QA. A cloud-based policy migration model includes a UI for inputs by migration team members, and back end components including the ETL engine.

Embodiments of the present disclosure provide large language models (LLMs) and large multimodal models (LMMs) for managing imaging data. An example method includes extracting a database schema and a data dictionary associated with a medical imaging database that maintains medical images and non-image data associated with a plurality of clinical studies; extracting object attributes associated with the medical images that are descriptive of the medical images and corresponding studies; and training an LLM to generate search queries from natural language requests based on a training dataset that includes: the database schema, the data dictionary, the object attributes, a prompt template including partial instructions for the LLM, and a plurality of example natural language requests and corresponding expected search queries. The trained LLM can then be used to generate a first search query from a first natural language request.

The invention discloses a structured data-oriented multi-source feature modeling and multi-granularity intelligent grading and classifying method, and belongs to the technical field of computers. The method comprises the following steps: inputting standardized data to be graded and classified into a currently trained coarse-grained classification model for classification; determining whether the to-be-graded and classified data is subjected to manual auditing or is not subjected to manual auditing; based on a predefined sensitive data dictionary and the final rough classification result, determining a classification result of the data to be graded and classified, and taking the classification result as a fine classification result; using the updated training sample set to perform enhancement training on the currently trained coarseness classification model, and updating the currently trained coarseness classification model based on an enhancement training result; and performing attribution analysis on the fine classification result. According to the method, a set of complete and efficient structured data multi-granularity intelligent grading classification is formed.

Systems, computer program products, and methods are described herein for generating and mapping unicode for cross-distributed network data transmissions. The present disclosure is configured to identify a cross-distributed network data transmission comprising source ledger code; generate a core schema for a destination ledger, wherein the destination ledger is based on data of the cross-distributed network data transmission; generate, by a ledger transformation module, a data dictionary, wherein the ledger transformation module receives ledger code from a large language model (LLM); generate code mapping instructions for the cross-distributed network data transmission based on the core schema for the destination ledger; convert the source ledger code to a unicode; receive, by a receiver schema mapping module, the unicode and the code mapping instructions; and generate, by the receiver schema mapping module, an intermediary ledger comprising the unicode and based on the code mapping instructions.

The invention relates to the technical field of gastrointestinal tumor chemotherapy risk assessment, and particularly discloses a gastrointestinal tumor chemotherapy risk scoring model and a construction method thereof, and the method comprises the steps: obtaining the individualized feature data and basic physiological data of a historical patient, and constructing an individualized difference library with a unique ID, and a core influence library; the method comprises the following steps: standardizing and coding double-library data, synchronizing clinical data containing treatment effect codes, forming a data dictionary, acquiring and coding current gastrointestinal tumor patient data, and matching the data dictionary to judge individual difference abnormity; when the first data set is abnormal, constructing a first data set, screening core independent variables through Logistic regression, and constructing a scoring model by using an LSTM (Long Short Term Memory) model; when no abnormity exists, redundant codes are removed to obtain a second data set, and modeling is conducted through the same method. Through double-library linkage and scene-divided modeling, the three-level toxicity risk prediction precision is improved, data support is provided for clinical chemotherapy dose adjustment and toxicity prevention, and the risk of excessive treatment or insufficient treatment is reduced.

The invention provides a database log analysis and recovery method and device, equipment, a medium and a program product, and relates to the field of data processing. Periodically generating a snapshot file of cache record data involved in a database log analysis process, and recording a snapshot identifier corresponding to the snapshot file; updating version information of a data dictionary, and binding the snapshot identifier with the version information of the data dictionary; when database log analysis is interrupted, matching corresponding target version information from the data dictionary according to a target snapshot identifier; recovering the state of the cache record data based on the target version information, and determining the initial position of database log analysis; according to the method, the snapshot file of the cache record data is periodically generated, and the snapshot identifier and the data dictionary version information are bound, so that the cache data state and the analysis starting position are quickly recovered based on the latest snapshot after the database log analysis is interrupted, and the fault tolerance and the recovery efficiency of log analysis are improved.

The application discloses a kind of based on the dynamic calling method and system of AI big model and heterogeneous system of MCP protocol, belong to supply chain intelligent management field, the method includes: according to entity in cold chain warehouse, the data dictionary of cold chain warehouse is constructed to expand standard MCP protocol, identify and extract the system corresponding to entity, and the communication protocol and API of system;Resource pool is constructed in cloud;Dynamic calling layer is constructed in cloud, and dynamic calling layer is called the data of data pool in resource pool by dynamic calling mathematical model, and decision suggestion is generated in combination with AI model in model pool and preset rule set, decision result is encapsulated as MCP instruction message;MCP instruction message is issued to edge gateway, and edge gateway converts MCP instruction message into local instruction executable by system, and is issued to equipment in cold chain warehouse.The application adopts multi-model parallel calling mechanism, realizes the efficient use of system resource and the quick response of task.

The invention relates to an enterprise data analysis method and device, and relates to the technical field of data governance, and the method comprises the steps: carrying out the Text2SQL task fine tuning of a large language model through a low-rank adaptation technology, constructing a structured knowledge base containing an enterprise data dictionary, a field calling relation and a national standard, converting the unstructured industry specification into a structured data standard knowledge base, and realizing knowledge vectorization storage by using an M3E-base vector model; sampling representative samples based on to-be-sorted data fields and retrieving related rules, integrating the representative samples into thinking chain cues, inputting the thinking chain cues into a fine tuning model to generate a labeling classification result, and outputting a data sorting result after multi-model evaluation and verification; generating a regular expression through a retrieval data standard to screen non-standard data, sampling to generate an SQL conversion code, iteratively cleaning until the standard is reached, and outputting standardized data; and finally, executing index optimization and anomaly detection based on the fine tuning model, and receiving natural language query to generate an SQL and a visual report.

The invention provides a user-defined type data access method and system of a database system, and belongs to the technical field of databases. The method comprises the following steps: acquiring a creation service request of a user-defined type structure, establishing a creation request object according to the creation service request, and storing the user-defined type structure of the creation request object to a data dictionary table; then obtaining a read service request, querying and matching a corresponding custom object in the data dictionary table, and generating a read request object capable of executing data storage according to the custom object; executing reading of the request object, and creating a temporary data storage table in a database to store user input data; and assembling all the user input data in the temporary table according to a preset format and returning to the client for display. According to the method, the user can create and read the user-defined type meeting the requirement according to the requirement, and the problem that the standard type of an existing standard database is fixed and inflexible is solved.

The invention discloses a discrete manufacturing multi-view BOM dynamic derivation method and system based on a tree-shaped network structure, and belongs to the technical field of intelligent manufacturing and product data management. The method comprises the following steps: constructing a tree body as a single product data source, and storing a hierarchical relationship, attribute definition and engineering semantics of a product in a tree structure; based on the tree body, dynamically matching derivation rules through a mesh mapping relation library; executing rule matching, semantic verification, structure reconstruction and dictionary verification by utilizing a dynamic view derivation engine to generate a target BOM view; semantic constraint and verification are carried out on the derivation process through a BOM data dictionary module; and realizing access control and audit based on role, scene and data sensitivity through the security and authority control module. According to the method, a new generation of xBOM dynamic derivation architecture which takes a tree form as an ontology, takes a net form as mapping, is configurable in rule and is strong in data specification is constructed; the fundamental problem of discrete manufacturing multi-view BOM management is solved, and engineering rationality and service flexibility are both achieved.

The invention provides a model-based software development method and device, electronic equipment and a storage medium, and the method comprises the steps: determining whether a data dictionary cache file which corresponds to a target vehicle-mounted software model and is in a native storage format exists under a first cache address in response to an import instruction for the vehicle-mounted software model; if the target vehicle-mounted software model exists, mapping the data dictionary cache file in the native storage format to operate the target vehicle-mounted software model; and if the target vehicle-mounted software model does not exist, acquiring a data dictionary file which is in a general storage format and corresponds to the target vehicle-mounted software model under the second cache address, decompressing the data dictionary file, and performing data analysis and format conversion on a decompression result to operate the target vehicle-mounted software model. By generating the data dictionary cache file in the native storage format in the hard disk in advance and importing the data dictionary cache file into the working space, the data importing speed can be remarkably increased, the simulation running time of the vehicle-mounted software model is shortened, and the development efficiency of the vehicle-mounted software is improved.

The application discloses a kind of based on knowledge base data standard domain automatic generation method and system, it is related to data standard domain generation technical field, method includes: obtaining data dictionary field, retrieve matching candidate standard item from knowledge base and build standard item evidence package containing semantic matching score and evidence source type;Candidate standard item is mapped to standard domain, domain support is calculated and is eliminated by evidence unit exclusion allocation to eliminate shared evidence, and the initial domain distribution of revised domain support is obtained, according to which the initial mode of single domain or multi-domain mode is judged;Calibration is carried out based on domain constraint image, domain change cost coefficient and uncertainty penalty coefficient are generated adaptively according to determination score and conflict score, score function is constructed, refined candidate domain set is filtered out according to initial mode and distribution is reorganized, post-calibration and backflow determination are carried out, and finally single-domain or multi-domain standard domain result is output;The application improves the accuracy and automation degree of data standard domain generation.

The application discloses a host system security emergency response method and device, equipment and medium, and relates to the technical field of network security. The method comprises the following steps: receiving attack trace encrypted data packets; the attack trace encrypted data packets are obtained by performing format conversion and encryption compression on target collected data through a local portable collection program of a target host; the target collected data are obtained by performing attack trace extraction in an offline or online manner based on a preset attack trace collection knowledge graph through the portable collection program; after the attack trace encrypted data packets are decrypted, data cleaning and formatting are performed to obtain attack trace data dictionaries; a preset data analysis model is used to identify security abnormal behaviors according to the attack trace data dictionaries, and an attack behavior relationship graph is obtained by reconstructing an attack chain timeline; the preset data analysis model comprises a preset rule engine and a preset large language model reasoning engine; and a security analysis report is generated based on the attack behavior relationship graph, so that security emergency response operations can be performed.

The application relates to the technical field of databases and digital medical treatment, and provides a metadata-based database DDL updating method, device, equipment and medium. The method comprises the following steps: generating a metadata dictionary in response to a metadata configuration instruction, the metadata dictionary being used for indicating the corresponding relationship between a source end and each database; generating a routing file of a target database based on the metadata dictionary in response to an updating request for the target database; acquiring the table structure of the target database and the table structure of the source end according to the routing file; comparing the difference between the table structure of the target database and the table structure of the source end; and updating the DDL statement of the target database according to the difference. The method provided by the application can quickly and automatically locate the corresponding database, reduces human intervention, and thus improves the DDL updating efficiency of each database.

This disclosure provides a hot data push system and method. The hot data push system includes: a data acquisition module configured to acquire data generated by an external device; a data identification module configured to receive the acquired data and identify the acquired data according to a hot data dictionary; a hot data push module configured to receive the identified hot data and push it; and a data reading node configured to cache the pushed hot data and update the pushed hot data to the data cache dictionary.

The application discloses a marine product inspection digital application system and method based on a lightweight database and a configurable interface, an electronic device and a medium. The method can include: an enterprise user runs a client, initiates enterprise authentication to a CA authentication; after the client is authenticated, the enterprise's product basic data, inspection item list and corresponding data dictionary configuration are automatically obtained from the server end; the enterprise user applies for product inspection on the client; the client automatically assembles the locally stored structured data into a message conforming to the interface specification according to the data dictionary configuration, and submits it to the server through the CA authentication channel; after the inspection is completed on the server, the product certificate is sent to the client of the enterprise and stored locally. The application integrates a lightweight database, a configurable interface and a secure authentication mechanism, realizes seamless connection of enterprise and classification society data, guarantees data quality and safety, and implements marine product inspection digital specification.

This application provides a method for processing multi-fleet reliability data based on the ATASPEC2000 specification. The method includes acquiring different types of raw reliability data files from multiple fleets; parsing the raw reliability data files to obtain a raw reliability data table; configuring a data cleaning template for the raw reliability data table using a CSDD data dictionary and performing data cleaning processing to obtain a reliability data cache table; and configuring a data transformation template for the reliability data cache table using a CSDD data dictionary and performing data transformation processing to obtain a reliability data specification table. The data cleaning template includes a first mapping between fields in the raw table and fields in the cache table, as well as data cleaning rules associated with the cache table fields. The data transformation template includes a second mapping between fields in the cache table and fields in the specification table, as well as data transformation rules associated with the specification table fields.

The invention provides a data consanguinity analysis method and equipment, and is applied to the field of data governance. The method comprises the steps of obtaining a data dictionary corresponding to a target database; wherein the target database comprises a plurality of data tables; foreign key information is extracted from the target database, the foreign key information is used for representing the relation among the multiple data tables, and the foreign key information is obtained; performing data correlation analysis on the target database based on a correlation coefficient algorithm to obtain a correlation analysis result; and based on the data dictionary, the foreign key information and the correlation analysis result, constructing a data blood relationship map. As the data correlation analysis is performed on the target database based on the correlation coefficient algorithm, not only can the correlation between the data fields be accurately quantified, but also the correlation analysis result for revealing the potential data dependency relationship between the fields and the business logic can be obtained, so that the data correlation analysis efficiency is improved. The data blood relationship map constructed based on the data dictionary, the foreign key information and the correlation analysis result can reveal potential data dependency and business logic, and the accuracy is high.

The invention relates to the technical field of reconstructed image anomaly detection, in particular to an image data anomaly point detection and correction method and system based on magnetic resonance fingerprints, and the method comprises the steps: generating a simulation data dictionary containing random anomaly points based on a magnetic resonance scanning plane; obtaining a to-be-detected reconstructed image, extracting a reconstructed image signal evolution curve, and matching the reconstructed image signal evolution curve with the simulation data dictionary to obtain an abnormal point position in the to-be-detected reconstructed image; and correcting the image data according to the positions of the abnormal points in the to-be-detected reconstructed image to obtain a corrected image. According to the method, the scanned and acquired data is matched with the pre-generated data dictionary containing the random abnormal points, so that whether the abnormal points are contained or not can be detected, the abnormal points are corrected, related image artifacts are eliminated, reconstructed image anomaly detection can be realized without an AI model, manpower and material resources are saved, the stability is better, and the detection efficiency is improved. Deployment and implementation can be carried out in magnetic resonance imaging equipment.

This application discloses an automatic code generation method and system for SOME / IP data types, relating to the field of vehicle system development. The method includes: S1, data dictionary reading: obtaining the data dictionary for SOME / IP protocol communication; S2, data type classification, identification, and processing: opening the Excel file from step S1, classifying each row of data in the worksheet, and performing specific parsing processing for different types; S3, multi-round iterative dependency resolution: using a multi-round scanning strategy to resolve nested dependencies between various data types; S4, naming standardization processing: standardizing the names of each parsed data type according to preset naming rules; S5, standard code generation and output: converting all data types that have undergone naming standardization processing into type definition code conforming to C language specifications; simultaneously converting the value range, precision, unit, and Chinese description metadata in the data dictionary of the Excel file into code comments, generating a C language header file that can be included in the compilation project.

The invention discloses a data dictionary name intelligent standardization method based on natural language generation, which relates to the technical field of natural language processing, combines a deep reinforcement learning technology, analyzes input context information through a generation model, generates candidate terms, and compares the candidate terms with predefined standardized terms to obtain a data dictionary name intelligent standardization result. Three reward mechanisms including precision reward, recall reward and context consistency reward are adopted, and through the comprehensive action of the three mechanisms, the generation model continuously optimizes the strategy and adjusts the generation process, so that more accurate term generation is realized. The method can flexibly adapt to terms in the emerging field, the standardization of the terms is ensured by automatically adjusting the generation strategy, and particularly, the efficiency and accuracy of term generation can be effectively improved in the technical field of constantly changing and updating of the terms, so that the requirement of rapid change is met.

The embodiment of the invention provides a data compression method and device, a logic chip and electronic equipment, and relates to the technical field of data processing, and the method comprises the steps: carrying out the hash transformation of a to-be-processed data segment, and obtaining a first hash value; a second number of first initial positions recorded in the data dictionary are inquired with the first hash value as an index, the first initial positions are the positions of the data segments with the hash dictionary value being the first hash value in the original data, and the second number is larger than or equal to 2; if each first initial position is an invalid position, encoding the byte to be encoded, and updating any first initial position to a second initial position of the data segment to be processed in the original data; and if the valid initial position exists, performing byte-by-byte comparison from the valid first initial position and the second initial position to the data tail direction to obtain a continuous repetition length, and based on continuous repetition length coding, updating the position to be updated in the first initial position by using the second initial position. The data compression ratio can be improved.

The present disclosure provides a general data dictionary determination method, which can be applied to the field of big data technology in the financial field. The method comprises: obtaining the compression capability evaluation result of each financial data center on M data dictionaries of the same compression type, obtaining the compression capability evaluation result group of the M data dictionaries, wherein the compression capability evaluation result represents the compression capability of the data dictionary on the business data of the business category contained in the financial data center, and the M data dictionaries correspond to the M financial data centers one by one; determining the general compression evaluation result of the M data dictionaries based on the compression capability evaluation result group of the M data dictionaries; determining the general data dictionary from the M data dictionaries based on the general compression evaluation result of the M data dictionaries, and sending the general data dictionary to each financial data center. The present disclosure also provides a general data dictionary determination device, equipment, medium and program product.

The invention discloses an information management net value mail cleaning and analyzing method and system based on a large model, and the method comprises the steps: obtaining a mail of a user mailbox, and extracting and storing the metadata of the mail; performing multiple identification on the mails based on a large model, confirming net value mails, and excluding non-net value mails; aiming at net value mail contents in different formats, adopting a corresponding extraction mode and carrying out data verification; standardizing the extracted net value data according to a preset term mapping table and a standardized data dictionary; performing automatic analysis based on the net value data after standardization processing; and carrying out visual display on the analysis result. According to the method, automatic identification and acquisition of net value mails are realized, net value data in mails in different formats can be extracted and automatically analyzed, and analysis results such as income trend and risk assessment are generated in real time. The method solves the problems that in the prior art, the efficiency of obtaining and analyzing the net value data in the asset management mail is low, errors are prone to occurring, format adaptation is difficult, and a dynamic analysis result is difficult to generate in time.