8046 results about "Data administration" patented technology

The invention discloses an interactive question intelligent agent system based on a large language model, and relates to the technical field of dialogue interaction systems. Aiming at the technical defects of the traditional BI tool, the technical scheme is as follows: a heterogeneous data management engine realizes unified access and secure access of cross-source data; the NLP semantic recognition engine converts a natural language into structured semantics through multiple steps, drives the hybrid SQL generation engine and provides visual parameters; the generation engine realizes precise generation from semantics to SQL through a two-stage architecture based on metadata and authority rules; and the visual management console is combined with multi-party configuration and parameters to visually build a number-asking agent. The method is used for realizing intelligent conversion from a natural language to a structured query language (SQL) and a data service interface, and automatically generating an interactive data visualization result.

The invention provides a block chain data management method and system, and relates to the technical field of block chains, and the method comprises the steps: receiving and preprocessing an electronic file; encrypting the archive by using a public key and calculating a hash value; packaging the encrypted file and the hash value into a block chain transaction and broadcasting the block chain transaction; acquiring block information and safely storing the private key; verifying the integrity of the electronic file; recording a full life cycle operation log; the log is stored in an on-chain and off-chain combined mode; auditing the electronic file; and realizing access authority automatic management based on the intelligent contract. According to the method, the security, traceability and management efficiency of the electronic archives are improved.

The invention provides a commodity tracing method and system for a cross-border e-commerce supply chain. The method comprises the following steps: designing a block chain network in which multiple parties participate in the cross-border e-commerce supply chain by adopting an alliance chain architecture; designing a hierarchical data storage scheme, and storing high-frequency transaction data in an off-chain database; integrating the graph neural network model in the block chain network; constructing a reinforcement learning model, and modeling a supply chain operation process as a Markov decision process; a data management scheme based on the block chain and the Internet of Things is designed for the demand of supply chain full-process tracking; a hybrid architecture is deployed in a distributed environment, and a containerization technology and micro-service design are adopted; for the interpretability demand of a complex architecture, an attention mechanism and a causal reasoning technology are introduced, and visual interpretation is carried out on the decision process of the model. According to the invention, the efficiency and profitability of the supply chain are improved, and a new direction and solution are provided for commodity traceability of cross-border logistics.

Systems and methods for decentralized data management across interoperable distributed platforms are disclosed. A computing system receives input data associated with a unique decentralized identifier (DID) representing an entity or event. The computing system segments the input data into encrypted data segments, each cryptographically linked to the DID, and distributes these encrypted segments across decentralized storage nodes according to a redundancy scheme. A cryptographic lineage record, including segment identifiers, timestamps, and hashes linked to the DID, is stored in a decentralized ledger. In response to authenticated access requests, the computing system reconstructs the input data by retrieving, decrypting, and cryptographically verifying the distributed data segments against the lineage record. Authorized entities access the reconstructed data through interfaces enforcing cryptographically secured access permissions defined within the decentralized ledger, providing enhanced security, provenance verification, and data resilience.

The present invention discloses a blockchain-based Industrial Internet of Things (IIoT) data management system and method, where the system includes a physical layer, an edge layer, a network interface layer and a cloud layer; the physical layer includes a plurality of different IIoT device monitoring systems; the edge layer is configured to build an IIoT blockchain network; the cloud layer includes cloud servers which are configured to be deployed in a real blockchain network environment to improve performance and effectiveness of the blockchain network. The present invention can effectively solve the problem of parameter optimization lag in industrial production applications.

The invention discloses a distributed multi-tenant data security isolation system and method, and relates to the technical field of data isolation, and the system comprises a data isolation module which is responsible for distributing independent container instances and hardware resources for each tenant, and adjusting the data access authority according to an access control strategy; the dynamic access control module is responsible for generating an access control strategy according to the user identity, the authority, the tenant strategy and the access behavior; the distributed data management module is responsible for storing data fragments on different storage nodes; the resource scheduling and optimizing module is responsible for collecting resource demand data of each tenant, calling an intelligent scheduling algorithm, performing dynamic prediction and analysis on resource demands, and then automatically adjusting a resource allocation strategy according to a prediction result; and the security auditing and monitoring module is responsible for collecting operation logs and event records of each module and carrying out comprehensive analysis. The invention aims to solve the problems of data security and resource management in a multi-tenant environment.

The invention discloses an intelligent monitoring management method and system based on archive digitization, and relates to the technical field of data management, and the method comprises the steps: collecting and preprocessing multi-source archive data, employing a multi-mode BERT model to carry out the feature fusion of different data sources, and generating a unified semantic representation; semantic labeling is performed on archive data through a multi-label classification model, a semantic graph of archive content is constructed by using a graph database, an association relationship between archives is represented, a semantic index tree is constructed based on the semantic graph, and rapid positioning and calling of the archive content are optimized; and recording the change of each file version, positioning the change position based on a semantic index tree, identifying the semantic change of the file through a semantic difference comparison algorithm, recording hash, carrying out granularity division on the file content through the semantic boundary of each level of node in the index tree, and generating a user access strategy. According to the invention, dynamic perception and risk early warning of user behaviors are realized, and the intellectualization and safety of the archive management system are effectively improved.

The invention discloses a distributed storage method and system for data security, and belongs to the technical field of data storage security, the method comprises the following steps: firstly, fragmenting original data, and generating a unique identifier for each data fragment; for each fragment, an encryption algorithm and key credentials are adaptively selected, and the key credentials are stored in a key management system. By performing homomorphic encryption on the key voucher, an encryption handle is generated, and efficient positioning and retrieval of the key are realized. According to the method, a differentiated encryption strategy is adopted, a most suitable encryption scheme is selected according to fragment characteristics, and encrypted data fragments are dispersed and stored in a plurality of distributed storage nodes. A global mapping index is constructed in a metadata management server, and a corresponding relation between an original data global identifier and metadata of each data fragment is recorded, including information such as identifiers before and after encryption, a storage position, an encryption algorithm, a key handle and the like. According to the method, the data leakage risk is effectively reduced, and the safety and reliability of the storage system are improved.

The invention discloses an intelligent management method and system for port and navigation Internet of Things data, and the method comprises the steps: generating a standardized data flow through a multi-modal data fusion model according to the heterogeneous features of ship navigation data, port equipment operation data and cargo information; generating an anti-interference transmission channel based on the standardized data stream; according to the real-time data received by the anti-interference transmission channel, dynamically generating a tamper-proof storage index through a trusted execution environment; extracting multi-source data based on the storage index, and generating a ship arrival time prediction model and a port resource scheduling strategy; and according to the port resource scheduling strategy, constructing a cross-department data sharing network through a federated learning framework and a zero-knowledge proof protocol, and generating a verifiable shared data set. According to the embodiment of the invention, port and navigation Internet of Things data management with reliable transmission, safe storage and collaborative intelligence can be realized, and the data management efficiency is improved.

The invention relates to the technical field of agricultural product quality tracing, and discloses an agricultural product quality tracing system based on a block chain technology, and the system comprises a data collection module which is used for collecting environment data, quality detection data and position information of agricultural products in the links of planting, processing, transportation, storage and the like through Internet of Things equipment; the encryption module is used for performing preliminary symmetric encryption processing on the collected data and encrypting sensitive data through a homomorphic encryption algorithm; and the intelligent contract module is used for automatically executing data storage, authority control, zero-knowledge proof verification and cross-chain data management on the block chain. According to the method, the authenticity and security of data in each link are ensured through automatic execution of data storage and authority control by using a distributed account book and a tamper-resistant characteristic of the block chain and through an intelligent contract, and meanwhile, an I PFS distributed storage system is combined with the block chain, so that the integrity of the data is further ensured, and the security of the data is improved. Therefore, all parties can share and query the tracing information trustingly.

The invention relates to the technical field of medical data management, in particular to a medical data document classification and marking system which comprises a document structure analysis module, a semantic information identification module, a classification and marking module and a document intelligent label module. According to the method, document visualization and retrieval efficiency is improved by analyzing document content and extracting titles, texts and appendixes, analytic performance and operability of data are enhanced by identifying key information and semantic relations and accurately extracting and labeling medical terms, medicine research data and medical record records, storage is optimized according to priorities in combination with classification and marking, and the method is high in practicability and easy to popularize and use. Clinical values and application scenes of documents are clarified, document management processes are refined, management compatible with clinical data formats is formed through structured storage of marked data and classification label generation, storage normalization and retrieval efficiency are improved, the requirement for accurate information calling in clinical tests is met, document management capacity is improved, and the document management efficiency is improved. And support is provided for improvement of clinical decision-making and research efficiency.

The invention relates to the technical field of management and control systems, in particular to a digital intelligence system applied to collaborative management and control of water-power engineering construction participating units, which comprises a project data management module covering water-power engineering construction full life cycle management, extracting multi-source information data from various subsystems, and constructing a project view and a project management information base; the project risk analysis module is used for constructing an intelligent risk analysis model for risk analysis and generating a dynamic evaluation result, a graded early warning notification and an auxiliary decision scheme; the project collaborative management module is used for processing graded early warning notification and auxiliary decision-making schemes by using a multi-layer perceptron model, and generating finalizing service achievements and management process records; and the project document management module is used for performing compliance automatic checking and processing on the electronic documents needing to be archived, and dynamically updating and optimizing the project management information base. Through the closed-loop management and control system, the cooperative management and control efficiency of water-power engineering construction participation units is improved.

The invention relates to the technical field of data management, in particular to an information digital management system based on an intensive care medicine department. The system is used for executing the following steps: inputting information data of a patient in the intensive care medicine department by using terminal equipment; missing field value filling processing is carried out on the information data of the patient in the severe medicine department to obtain complete data of the critical patient; performing physiological index time risk analysis on the complete critical patient data to obtain physiological index abnormal risk data; performing intelligent risk early warning according to the abnormal risk data of the physiological indexes, and generating intelligent illness state risk early warning data; performing risk intervention opportunity reasoning on the intelligent disease risk early warning data to obtain risk intervention opportunity decision data; and performing medical resource optimization adjustment according to the risk intervention opportunity decision data to obtain an individualized diagnosis and treatment aid decision strategy. Individual intervention opportunity decision making is realized through intelligent illness risk early warning in the system, and the management efficiency and the resource utilization rate of the intensive care medicine department are remarkably improved.

The invention discloses a block chain-based medical data management method, system and device, and a medium, and relates to the field of information management. The method comprises the following steps: acquiring medical data, analyzing content attributes and context information of the medical data through a first smart contract on a block chain, and generating a first sensitivity level identifier; based on the first sensitivity level identifier, performing differential encryption on the medical data through a second smart contract on the block chain, and generating verification information; partitioning the differentially encrypted medical data, constructing a data structure together with the verification information, and storing the data structure into a block chain; in response to the received access request, verifying an authority certificate in the access request and the type of the access request through a third smart contract on the block chain, and generating an access authorization certificate; and outputting target medical data corresponding to the access request based on the access authorization certificate. By implementing the technical scheme provided by the invention, the full-life-cycle safety management and control of the medical data from collection, storage to sharing is realized.

This disclosure includes a process for merging legacy databases having different data schema into a principal data store. A computing device retrieves a legacy database from each of a plurality of domains of an organization to form a plurality of legacy databases, where at least two legacy databases in the plurality of legacy databases have a different data schema. For each of the plurality of legacy databases, the computing device retrieves data from the respective legacy database, places the data from the respective legacy database into a respective unstructured database, and merges the respective unstructured database into a principal data store designed to hold data for every domain of the plurality of domains.

The invention discloses a cross-system heterogeneous metadata intelligent acquisition method and system based on LLM, and the method comprises the following steps: S1, collecting and preprocessing heterogeneous system data, and constructing a heterogeneous graph; s2, analyzing nodes by the large language model, and splicing structural features to form initial representation of the nodes; s3, constructing a heterogeneous graph Transform, executing multi-layer propagation and low-rank decomposition, and outputting final node representation; s4, generating a field alignment path, an interface mapping path and a dependency path, and planning an acquisition path and an acquisition sequence; and S5, executing an acquisition task, converting a structured format, writing into a metadata center, and performing closed-loop optimization. According to the method, intelligent acquisition, semantic analysis and automatic integration of cross-system heterogeneous metadata are realized, and the efficiency and intelligent level of metadata management in a multi-source data environment are greatly improved.

The invention discloses a dynamic authority management system and method based on multi-source salary data integration, and relates to the technical field of salary data management, and the method comprises the following steps: collecting role names, authority boundaries and operation granularity information from a plurality of business systems, and generating structured role semantic ontology entries based on a field-level semantic annotation mode; and disassembling the to-be-mapped role according to the authority dimension, calculating a semantic similarity index between the to-be-mapped role and the standard role based on the role semantic ontology library, and outputting a role consistency scoring matrix. According to the method, the authority difference is identified through the role semantic ontology and the similarity score, the minimum authorization judgment is realized in combination with the rule engine and reinforcement learning, the audit traceability and anomaly detection are guaranteed by using the block chain and the dynamic graph, and finally a strategy self-evolution closed loop is constructed. And the problems of permission mismatching and data leakage caused by role semantic inconsistency are effectively solved.

The invention discloses a remote regulation and control LED lighting system based on the Internet of Things, and relates to the technical field of LED lighting systems, comprising an LED lighting equipment module which comprises an efficient lamp, a microcontroller, an Internet of Things communication module, a remote control terminal module supporting multi-protocol and encryption, having Mesh networking, a multi-terminal control, having multiple functions and innovation formulas, and a sensor module; the intelligent LED lighting control system has the advantages that environment information is collected, the data management and analysis module stores and analyzes data, energy-saving management and the like are achieved, all the modules work cooperatively, and the functions of remote intelligent regulation and control, fault self-inspection, butt joint with other systems and the like of LED lighting are achieved. Through collaborative innovation of multiple modules, remote intelligent regulation and control of LED lighting are realized, the lighting quality and user experience are improved, energy is saved, consumption is reduced, the system has the functions of fault self-checking and alarming and the like, the reliability and compatibility of the system are improved, and the diversified requirements of modern lighting systems are met.

The invention relates to a medical information processing and intelligent data management technology, and discloses a hospital multi-source heterogeneous data integration management system and method based on an EMPI, and the system carries out the real-time subscription and batch extraction of the data of an HIS, an EMR, an LIS, a PACS, a DRG and a pre-hospital first-aid system through an interface adapter, and generates a unified main index identifier through the matching of the EMPI, and carries out the real-time subscription and batch extraction of the data of the HIS, the EMR, the LIS, the PACS, the DRG and the pre-hospital first-aid system. Field-level cleaning, standardization and semantic mapping are carried out on the free text and the structured data, an intermediate standardized record set is formed, an event graph is constructed, event cluster recognition is carried out in combination with time, clinical entities, doctor seeing scenes and department similarity, consistency judgment and EM iterative fusion are carried out on the basis of data source reliability, and event cluster recognition is carried out. And outputting a unified patient file set and a downstream service interface. According to the invention, high-precision integration, standardized management and traceable application of multi-source data are realized, and a reliable data basis is provided for clinical decision support, medical insurance management and scientific research.

The invention discloses an electronic bill data management system and method based on artificial intelligence, and belongs to the technical field of artificial intelligence. The method comprises the following steps: collecting bill data in an electronic bill, extracting features from the bill data by using a feature extraction algorithm, classifying article names in transaction article details through a predefined article classification model, and matching the article names with standard codes in a commodity database; checking whether the bill data has a modification trace or not, comparing historical data, detecting consistency, and returning the electronic bill and marking a corresponding collection user when an exception is found; when the bill data is not abnormal or inconsistent, analyzing whether the amount of money in the electronic bill exceeds a conventional transaction range or not, and generating a risk rating of the bill data; performing risk rating on the receiving users, and analyzing the price interval of the same type of the receiving users in a period of time; and carrying out weighted integration to generate an electronic bill comprehensive risk rating, and transmitting the electronic bill data to a reimbursement platform.

The invention discloses a data security management method and system based on cloud computing, and relates to the technical field of data management, and the method comprises the following steps: S1, making a security policy; s2, performing security assessment on the cloud infrastructure; s3, performing identity authentication and access control; s4, data encryption and key management; s5, data classification and level-to-level management; s6, data leakage detection and defense; s7, performing auditing and compliance management; s8, abnormal behavior monitoring and threat response; and S9, an elastic backup and recovery mechanism. According to the data security governance method and system based on cloud computing, the elasticity and dynamic response capability of data security are remarkably improved by setting the distributed key management system and the intelligent monitoring model. The distributed key management system dispersedly stores the keys in different physical areas, so that the risk of single-point fault and attack is reduced; the AI-based intelligent behavior monitoring system analyzes user behaviors in real time, predicts abnormal operation and automatically responds.

The invention provides an integrated metadata management method and system based on data source expandability, and relates to the technical field of data sources, and the method comprises the steps: executing real-time detection on a plurality of heterogeneous data sources through a PF4J plug-in framework, collecting connection information, and establishing a dynamic connection pool; obtaining a table structure, a field attribute and an association relationship list, and assembling the table structure, the field attribute and the association relationship list into JSON format data; performing analysis and standardization processing on the data, and constructing an association degree calculation matrix; generating a standardized data structure description file; establishing a three-layer index directory, and detecting structure change and updating; and calculating a data table reference dependency relationship, and generating a DAG data flow path. According to the method, efficient integration and management of heterogeneous data sources are realized, and the metadata processing efficiency is improved.

The invention belongs to the technical field of data storage, and discloses a multi-source marine environment data storage method and system based on HDF5. According to the method, a hierarchical storage framework is constructed, a domain-type-source three-level directory architecture is constructed, a space-time dimension dynamic extension mechanism is executed, and space-time composite coding is performed; designing an HDF5 nested packet storage architecture, wherein grid topological structure definition, dynamic resolution self-adaptive storage, multi-source data processing and metadata management are carried out; constructing distributed data association and indexes, including data standardization preprocessing and cross-source data association; the storage performance is optimized and expanded, wherein density sensitive blocking and layered compression are carried out. According to the method, redundant storage of a high-latitude region is greatly reduced, and dynamic adaptation of a local encryption grid is supported. According to the invention, open circulation and collaborative utilization of interdisciplinary data resources are facilitated.

The invention discloses a data management system and method based on distributed cloud storage, and relates to the technical field of distributed cloud storage, and the system comprises an access log collection module, a node state monitoring module, a data thermal evaluation module, a redundancy strategy decision module and a storage execution scheduling module. A fragmentation access behavior is recorded through an access log acquisition module, a node state monitoring module acquires a node resource state in real time, and a data thermal evaluation module constructs a three-dimensional thermal model based on an access frequency, a network hop count and a storage cost to calculate a thermal value and supports dynamic weight adjustment; the redundancy strategy decision module divides the fragments into high frequency, medium frequency and low frequency according to the thermodynamic value, and single copy + local cache, erasure code storage and dynamic adjustment strategies are adopted respectively; the storage execution scheduling module executes fragmentation operation and optimizes reading node selection, and data access efficiency is improved through load awareness and a bandwidth-delay joint model; according to the invention, dynamic balance between data access efficiency and storage cost is realized.

The invention discloses an electric power marketing management information platform daily electric power fitting method and related equipment, and relates to the technical field of electric power data management, and the method comprises the steps: obtaining historical load data, external environment data and equipment operation state data of a target region; constructing an initial load fitting model based on the historical load data; extracting a date characteristic factor according to a preset time classification rule, and dynamically correcting the initial load fitting model based on the date characteristic factor to generate a corrected load model; generating a multi-source fusion feature based on the external environment data and the equipment operation state data; and inputting the multi-source fusion features into the corrected load model, and outputting a target load prediction result.

The invention relates to the technical field of data management, in particular to a low-altitude economic flight data management method and system based on edge computing, and the system comprises edge computing nodes deployed on an aircraft and a ground base station, a sensor for collecting multi-source data, a module for preprocessing the data, and an annular data queue caching mechanism. The system comprises a composite biological feature code generation module, a distributed storage edge node, an abnormal fluctuation feature extraction module, an equipment health state and trend analysis and calculation module, a virtual power supply manager, a main power supply, a standby power supply, an abnormal behavior monitoring module and a defense strategy library. After preprocessing and caching, feature codes are generated and encrypted distributed storage is carried out, dynamic resource adjustment is realized through state evaluation and a digital twinning and optimization algorithm, a neural network is utilized to manage a power supply, data security is guaranteed in combination with abnormal monitoring, and a whole-process management system is formed.

A management server system may obtain data associated with a vehicle. The management server system may obtain the data from a plurality of data sources associated with the vehicle. The data may include a plurality of subsets of data that each correspond to correspond to a particular driver assignment category. Each subset of data may identify a particular persona as a driver of a vehicle. The management server system may determine a driver of the vehicle based on each subset of data and a hierarchical plurality of driver assignment categories. Based on the determination of the driver of the vehicle, the management server system can dynamically map the driver to a particular event. The management server system may generate a user interface identifying the driver and the event.

Methods and systems for managing operations of a data processing system are disclosed. To manage operations of the data processing system, a management controller of the data processing system may obtain validated location data for the data processing system via an out-of-band communication channel. The management controller may identify applicable policies based on the validated location data. If the management controller identifies a policy applicable to a geographical location of the data processing system, then the management controller may perform an action set to manage operation of the data processing system based on instructions associated with the applicable policy. The updated operation of the data processing system may increase the security of sensitive data managed by the data processing system.

The invention discloses a supply and demand data management system based on human resources, and relates to the technical field of human resource management, and the system comprises a human resource management center which is in communication connection with a data collection module, a knowledge graph construction module, a post supply and demand matching module, a dynamic adjustment optimization module and a user interaction module. Wherein the modules are connected through electric signals, and the data collection module is used for collecting and preprocessing human resource supply and demand data from different channels. By constructing the knowledge graph based on recruitment data and employee information, the matching relationship between post demands and job seeker skills can be accurately identified, the efficiency of human resource allocation is remarkably improved, and compared with a traditional manual matching mode, the system can quickly analyze a large amount of data, automatically generate post matching coefficients, and improve the efficiency of human resource allocation. And the matching degree is quantitatively evaluated, so that the key post is ensured to obtain the most appropriate talent configuration, and the recruitment cycle is shortened.

The invention discloses an adaptive protocol stack reconstruction and transaction-level data control method for 5G communication, and aims to solve the technical problems of fixed protocol stack structure, coarse transmission control granularity and the like of an existing communication module. The method comprises the following steps: firstly, analyzing an application layer communication session initialization instruction, generating a communication task label, acquiring 5G network environment state data in real time, and constructing a network state feature vector; then, the communication task label and the network state feature vector are input into a protocol mapping decision map, a protocol reconstruction instruction is generated, loading and unloading of a protocol module in a protocol stack resource pool are controlled, a dynamically-adaptive protocol path is constructed, and a transaction identifier is allocated to the protocol path; and establishing a transaction-level data buffer area based on the transaction identifier, performing priority marking on the data packet, and executing differentiated dynamic flow control operation according to the network state feature vector and the priority label, thereby realizing high-reliability and low-delay 5G communication data management.