403 results about "Linked data" patented technology

A block chain double-chain cold chain traceability management system for meat quality fluctuation belongs to the technical field of traceability management systems and comprises a data acquisition and preprocessing module, a composite index module, a security verification module, a federated learning and AI resource management module, a fragmentation and verification architecture module and an automatic error correction module. According to the method, data chain storage environment data hash and transaction chain record operation logs are innovatively separated through a block chain double-chain architecture, hash fingerprints are synchronized in combination with an anchoring technology, cross-chain consistency is ensured, long-term non-tampering of data is realized through an anti-quantum hash algorithm, resource allocation is optimized through hierarchical storage design, and the method is suitable for large-scale popularization and application. The composite index technology is fused with hypergraph dynamic index to trace production batches, vehicles, warehouses and space-time quadtree dynamic subdivision areas, complex query response time is remarkably compressed, path deviation real-time alarm is achieved, the edge node cache hit rate is increased, and full-link data safety and query efficiency are remarkably improved.

The embodiment of the invention discloses an intelligent contract auditing method and device based on a multi-modal large model and a medium, and relates to the technical field of contract auditing, the method comprises the steps that a to-be-audited target contract document is acquired, multi-modal data in the target contract document is analyzed, and the multi-modal data comprises text data, table data and image data; performing feature extraction on the multi-modal data to obtain multi-modal feature data, mapping the multi-modal feature data to a unified dimension space so as to calculate an association weight between each modality through a cross-modal attention mechanism, establishing cross-modal bidirectional link data, and obtaining multi-modal data; the multi-modal feature data comprises any one or more of text semantic features, table relation maps and image visual features; and based on the multi-modal feature data and the cross-modal bidirectional link data, performing single-modal self-consistency verification and cross-modal contradiction detection on the target contract document to generate auditing information of the target contract document.

The invention relates to the technical field of data analysis, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a data consanguinity map processing method, device, equipment and medium, and the method comprises the steps: collecting metadata change information and data operation event information, and building a mixed consanguinity map model; monitoring a metadata change event and a data operation event, and triggering incremental updating based on an event type; and performing data change influence analysis based on the updated blood relationship map model, generating an analysis result, and outputting the mixed blood relationship map model and the data change influence analysis result. According to the invention, by collecting metadata, incrementally updating the blood relationship map and carrying out data change influence analysis, full-link data tracing and influence analysis are realized, the problems of blood relationship breakage and insufficient real-time data tracing in traditional data blood relationship analysis are solved, and the accuracy of data tracing and the timeliness of business decision are improved.

The invention discloses a process parameter tracing and quality collaborative management system for ceramic production, and relates to the technical field of ceramic production, the management system comprises a step of obtaining a plurality of process data and quality data in a ceramic production process, and each group of process data comprises a raw material ratio, a forming pressure, a firing temperature and a firing time. According to the process parameter tracing and quality collaborative management system for ceramic production, a specific process parameter deviation link can be quickly positioned by reversely tracing to a raw material source from a finished product quality problem and combining batch association identifiers and data records of all links; the quality problem solving efficiency is improved, and batch loss caused by traceability lag is avoided; besides, a process quality association relationship constructed by the module is established, a quality detection result is closely associated with process parameters, and multi-dimensional analysis is performed, so that a quality problem can be fed back to process parameter adjustment in time, and targeted measures can be taken according to an analysis result.

The invention provides improved methods and corresponding systems for the sharing, storage, creation and accessing of data stored on a blockchain eg the Bitcoin blockchain. It may form part of a protocol for searching the blockchain for content / data. A method in accordance with the invention may be used for associating or linking data stored within (separate / different) blockchain transactions to enable the identification, retrieval and / or sharing of data stored therein. Additionally, or alternatively, it facilitates identification of transactions (TX) in a blockchain which store content / data that needs to be shared, transmitted, stored and / or accessed by a user. Such a method comprises the step of mapping a mnemonic to: 1) a public key (PK) associated with the transaction (TX); and 2) the transaction ID (TXID) of the transaction (TX).

The invention belongs to the technical field of data processing, and discloses an Excel file dynamic analysis and verification method and system based on a rule template and a storage medium. Comprising the steps that a rule template is generated according to configuration information, and the rule template comprises one piece of table unit data and one or more pieces of column metadata; dynamically creating a database business data table for storing the analyzed Excel data based on the column metadata; reading the rule template, obtaining a corresponding form in the to-be-analyzed Excel file according to the table unit data, extracting Excel data in each row and each column in the form according to the column metadata, and storing the Excel data in a business data table; and querying a service data row in the database service data table, obtaining a verification rule according to the column metadata corresponding to the Excel data of each column in the service data row, and verifying the current Excel data according to the verification rule. According to the method, the adaptation capability of verification is enhanced, and meanwhile, customized development cost is not generated, so that the analysis and verification of the Excel are more flexible.

The invention discloses a micro-service full-link gray level traffic management system and method based on PaaS, and relates to the field of traffic management, and the system comprises an intelligent traffic analysis and decision center module, a micro-service arrangement and management platform, a full-link data analysis module, a dynamic safety protection and compliance auditing module, and a distributed configuration center. According to the micro-service full-link gray flow management system and method based on the PaaS, dynamic self-adaptive gray strategy formulation can be carried out, the latest service target, the gray version release plan and the system performance index threshold can be synchronously obtained in cooperation with a distributed configuration center, and the flow management efficiency is improved based on the information and the intelligent screening result of the flow. A routing strategy and a version switching strategy of gray traffic can be dynamically generated, and in the strategy making process, the real-time load condition of a system, the availability of micro-services and key index changes of services are fully considered.

The invention discloses a method, a system and equipment for monitoring weak links of a power distribution network and a storage medium. Comprises: obtaining operation related data of a target power distribution network; performing preliminary state evaluation on each node of the target power distribution network based on the operation related data to generate a preliminary state matrix; and weak link positioning is carried out based on the initial state matrix to obtain weak link data, and an emergency response strategy of the target power distribution network is generated according to the weak link data. Weak link positioning is performed through the initial state matrix to obtain weak link data, so that the part with problems in the power distribution network can be quickly and accurately found out, and the problem finding efficiency is improved. The emergency response strategy is generated according to the weak link data, so that effective countermeasures can be taken quickly when the power distribution network breaks down or is abnormal, the overall operation reliability of the power distribution network is improved, and the stability of power supply is guaranteed. Changes of the power distribution network can be dynamically tracked, and continuously changing power grid operation environments and requirements are adapted.

The invention discloses a distributed supply chain traceability system and method supported by a block chain, and relates to the field of data analysis, and the system comprises a collection module which is used for capturing the original data of a supply chain in real time through an Internet of Things sensor, and cleaning the data; the processing module is used for constructing a distributed account book based on a HyperledgerFabric architecture, performing hash encryption on the data, performing uplink storage on the data, packaging the data into blocks according to a time sequence, and completing data verification between nodes through a BFT consensus mechanism; according to the invention, full-link data of production, logistics and the like are captured in real time through the Internet of Things sensor and encrypted and chained, so that the data cannot be tampered and can be traced in the whole process, and the problems of easy data tampering and many breakpoints in traditional traceability are solved.

The invention relates to the technical field of credible data space, and provides a credible data space platform fusing multiple credible environments and a data use method, and the platform comprises a data credible circulation environment, a plurality of data credible supply environments and a plurality of data credible use environments. The data credible supply environment and the data credible use environment realize supply-demand link through the data credible circulation environment; the data credible circulation environment comprises a data product credible transaction environment and a data information credible delivery environment; a data operation platform is deployed in the data product trusted transaction environment and is used for shelving, browsing and ordering data products; according to the data information credible delivery environment, a block chain data internet is adopted, an encrypted digital asset account is opened on a block chain for each credible object, issued data information assets are stored, data right confirmation is realized through a multi-party encryption technology, and dynamic authorization of the data information assets is realized through a digital envelope technology. The method is not limited by a specific privacy computing technology architecture and is flexible to construct.

The invention relates to the technical field of underground pipe gallery digital management, and discloses a BIM-based underground pipe gallery asset digital management platform, which comprises a data acquisition module, a dynamic digital twinborn body module, an event processing engine, a self-iteration data bus module, a spatial topology driving module and a self-healing logic triggering module. For the industry pain point of insufficient data real-time performance under the long-distance and multi-node scene of the underground pipe gallery, geometric attributes of a BIM model and sensor data are deeply bound through a dynamic digital twinborn body module, twinborn nodes synchronously bearing space coordinates, physical attributes and real-time state labels are constructed, the limitation of traditional BIM static visualization is broken through, and the real-time performance of the underground pipe gallery is improved. Second-level state synchronization and full-link data traceability of high-risk events such as leakage and equipment faults are achieved, collaborative design of lightweight architecture and edge computing is achieved, the low-cost modification requirement of the old pipe gallery is met, and the real-time performance and reliability of asset management are remarkably improved.

The invention relates to the technical field of big data management and data analysis, and discloses a visual data platform full-link data flow traceability method, system and device and a medium, and the method comprises the steps: monitoring a job scheduling process submission event, analyzing the input and output configuration information of each job node, converting the information into a data flow model, and storing the data flow model in a traceability database; static analysis is conducted on node scripts and codes, and analysis results are stored in a traceability database; generating a unique identifier for each data record, and recording related information in a data circulation process; and writing the data flow relationship into a graph database Neo4j through a Kafka asynchronous message, and performing data traceability query by a user through a visual interface. The method has the beneficial effects that the data quality and safety are improved, and the limitation and complexity of a mainstream open source tool in the aspect of a data blood relationship analysis function are solved.

The invention relates to the technical field of informatization management systems, and particularly discloses an AI-aid decision-making product full-life-cycle informatization management system which comprises a full-link data sensing module, a digital main line construction module, an AI decision-making center module, a service execution interface module and a man-machine collaborative interaction module. The method comprises the following steps: collecting multi-source heterogeneous data of each stage of a full life cycle of a product through a full-link data sensing module to form a full-amount data sequence with a space-time stamp; and in combination with a data fusion engine, an association graph construction unit and a twinborn model driving unit of the digital main line construction module, data cleaning, alignment, semantic fusion and cross-stage association are realized, a dynamically updated product digital twinborn model is constructed, real-time mapping of a physical entity and a virtual model is achieved, and the real-time mapping of the physical entity and the virtual model is realized. Unified and complete data support is provided for full-link decision making, and the problems of data fragmentation and prominent collaborative barriers of a traditional system are thoroughly solved.

The invention relates to the technical field of canteen management, and discloses a canteen management method and system based on big data, Internet of Things and image analysis, and the method comprises the steps: collecting, preprocessing and storing all link data of a dining area and a meal preparation area of a canteen in real time, the link data comprising image information and non-image information; data analysis and image analysis are carried out on the preprocessed link data, the number of diners, identity information of the diners and dinning dish information in a future period of time are predicted, and therefore automatic management is carried out on canteen operation in combination with a preset management strategy; abnormal actions of workers and diners and possible faults of equipment are recognized, and alarm and / or parameter adjustment are / is carried out after the abnormal actions and / or faults are recognized. According to the method and the system, the management efficiency can be improved.

The invention relates to the technical field of network security, and discloses a network attack tracing and evidence fixing method and system based on full-link data, and the method comprises the steps: collecting multi-source heterogeneous data; cleaning and standardizing the collected data, and extracting attack feature information; constructing a full-link data association model, and connecting scattered attack behaviors in series into a complete attack chain through time sequence analysis and node relation graph technologies; based on the attack chain, determining an attack source and a potential motivation thereof by using a multi-level threat intelligence matching algorithm; and the traceability result is in butt joint with an evidence fixing module, a network attack electronic evidence file is generated, and the evidence is stored in a non-tampering manner through a block chain technology. The system corresponds to the method. The method and the system have remarkable technical advantages in the aspects of data integration, traceability precision, evidence fixation, storage optimization, visual display and the like, and can effectively cope with security challenges in a complex network environment.

The invention discloses a fresh food supply chain full-link traceability and loss early warning method based on a block chain, and the method comprises the steps: 1, carrying out the lightweight collection of full-link data, processing the data, and obtaining a standardized data source, and 2, carrying out the construction of a block chain bottom-layer architecture based on the standardized data source; step 3, establishing a dynamic reputation consensus mechanism, and establishing a trusted environment for data sharing through reputation score driving node collaboration based on a block chain bottom layer architecture; 4, constructing a federated learning network; step 5, risk prediction modeling: performing multi-dimensional risk prediction by utilizing model output of collaborative modeling and combining real-time data; step 6, graded early warning response: based on a risk prediction result, realizing graded automatic response through a grading rule; step 7, dynamic decision optimization; the beneficial effects of the invention are that the dynamic decision optimization function adjusts the strategy of each link of the supply chain according to the early warning result, achieves the intelligent scheduling of logistics, inventory and production, and reduces the loss and cost.

The invention relates to the technical field of grain safety management, and particularly discloses a grain safety traceability system and method, and a distributed data collection module obtains data in real time through an Internet of Things sensor network. And the multi-source data fusion engine performs standardization processing on the heterogeneous data by adopting a space-time alignment algorithm to generate a traceability data packet. And the block chain evidence storage node adopts fragmentation storage, and the traceability data packet is stored in a multi-chain parallel structure in a distributed manner. And the risk early warning analysis platform constructs a quality safety evolution model based on deep reinforcement learning, establishes an automatic triggering mechanism, and automatically sends a risk early warning data packet with a block chain evidence to the supervision platform when it is detected that grain is abnormal. According to the method, standardized processing, space-time consistency calibration and cross-link data collaborative analysis of heterogeneous data are realized by utilizing a multi-source data fusion engine; and the risk early warning analysis platform sends a risk early warning data packet to the supervision platform in time by using an automatic triggering mechanism, so that a powerful means is provided for grain safety risk prevention and control.

The invention relates to the technical field of satellite communication, in particular to a multi-link data transmission method, device and system in a low-orbit satellite network. According to the invention, a multi-link data transmission mechanism is adopted, so that the satellite antenna is allowed to establish multiple communication connections with multiple satellites at the same time, and the limitation of single-link communication in the prior art is broken. Compared with an existing single-link transmission mode, bandwidth resources of multiple satellite links can be utilized to the maximum extent, and waste of link resources is avoided. By introducing the LSTM to predict the network performance, the problem of instability caused by network state fluctuation in the prior art is solved. The LSTM model can predict a future network state through historical data, so that when the network performance is about to deteriorate, a data distribution strategy can be adjusted in advance, and network instability caused by bandwidth fluctuation or satellite switching is avoided. Therefore, continuity and stability of data transmission can still be kept when the number of users is suddenly increased or satellites are switched.

The invention relates to the technical field of catch safety tracing, and discloses a block chain verification method for catch quality safety tracing. The method comprises the following steps: acquiring environmental parameter data of catches in the links of fishing, transportation and storage through a distributed sensor network, and encrypting according to a timestamp sequence to generate a catches environmental data chain; key environment indexes are extracted based on the data chain, an abnormal deviation degree is calculated by using a dynamic weight distribution algorithm, and a catch quality risk score is generated; dividing risk levels according to the risk scores, mapping data of different risk levels to a block chain differentiation storage layer, and constructing a fragment storage structure; performing redundancy verification on the high-risk data through an intelligent contract triggering mechanism, and calling a consensus node to perform cross verification to generate a verification result; and performing association analysis on the verification result and the risk score, updating the risk tag and synchronizing the risk tag to a block chain distributed account book. According to the method, full-link data tracing and verification of the catches are realized, and the data credibility and the quality control accuracy are improved.

The invention relates to the technical field of supply chain management, in particular to a multi-dimensional data visualization supply chain process optimization method and system based on big data, and provides a supply chain dynamic optimization thought based on multi-source heterogeneous data fusion and intelligent decision closed loop. By constructing an end-to-end multi-source heterogeneous data real-time cooperative processing and intelligent decision closed-loop architecture, dynamic integration, intelligent analysis and automatic response and update optimization of full-link data of the supply chain are realized, so that the real-time analysis capability and dynamic adjustment capability of the supply chain are remarkably improved.

The invention discloses a toothpaste production raw material tracing method and system based on a block chain, and relates to the field of block chains, and the method comprises the steps: distributing a unique identifier for a raw material, binding basic information to form an initial data packet, taking a supplier as an alliance chain node, uploading the initial data packet, and verifying the qualification through an intelligent contract; the transportation data is encrypted in real time through the Internet of Things and edge calculation and is uploaded, and a detection report deviation value is verified during warehousing; raw materials and finished product batches are associated in a production link, and process parameter compliance is automatically checked and then written into a block; in the warehouse logistics link, environment data and transportation information are integrated, and a tracing sub-block is generated after a goods receiver is verified through code scanning; an improved PBFT consensus mechanism and a cryptographic algorithm are adopted to ensure data security, and transparent tracing of consumers, supervisors and enterprises is realized through hierarchical authority management. The method has the advantages that the raw materials and the finished product full-link data are bound through the unique traceability identifier, non-tampering traceability of the toothpaste raw materials from supply to the terminal is achieved, and multi-party hierarchical query requirements and product safety are met.

The embodiment of the invention discloses a data security situation awareness platform construction method and device and electronic equipment. The method comprises the following steps: acquiring network communication data of a to-be-constructed subject, and extracting the network communication data to obtain information transmission data of the to-be-constructed subject; performing analysis according to the information transmission data of the to-be-constructed subject to obtain an information transmission topological structure model; analyzing the information transmission data of the to-be-constructed subject to obtain non-security information transmission data; constructing an abnormal information transmission detection model according to the non-security information transmission data, and performing detection to obtain real-time abnormal information transmission data; integrating the information transmission topological structure model to obtain abnormal node link data; analyzing according to the abnormal node link data and the information transmission data of the to-be-built subject to obtain a security information transmission link structure model; the invention discloses an information transmission security situation awareness platform. According to the invention, data security or network security events can be avoided, and a better network environment is provided.

The invention discloses an industrial building business service management method and device and a medium, and belongs to the technical field of building service management, and the method specifically comprises the steps: constructing a multi-dimensional data fusion model; defining cost, progress, quality and security dimension data ranges and acquisition nodes, and storing the data ranges and the acquisition nodes in a model database after standardization; based on the standardized data of the multi-dimensional data fusion model, analyzing a dimension internal relationship by using an association rule mining algorithm, defining a dimension mapping relationship, and integrating to form an association rule base; establishing a multi-dimensional linkage analysis module; the module is established by taking a model database as a data source and a multi-dimensional data association rule base as a logic support, and a threshold triggering mechanism and a cross-link data calling function are set; constructing a business collaborative decision support module; business requirements of multiple departments are integrated; a multi-dimensional data visualization monitoring platform is built; and designing a linkage trend chart based on a result of the multi-dimensional linkage analysis module.

The invention relates to the technical field of risk management and control, in particular to a traceability management and control method and system based on a bulk commodity trade platform. The method comprises the following steps: obtaining entity transaction data from a bulk commodity trade platform, and constructing a block chain model; performing data acquisition and anomaly detection by using the block chain, identifying an abnormal transaction condition, dividing abnormal accounting nodes, and extracting link structure features of the abnormal accounting nodes to obtain link data of the abnormal accounting nodes; the method comprises the following steps: obtaining logistics data through a bulk commodity trade platform, establishing a logistics sensing network, associating an abnormal accounting node with a logistics link space, and obtaining logistics link data of the abnormal accounting node; carrying out correction by utilizing the logistics link data and the abnormal transaction data, deriving transportation error data, tracing the transportation risk by utilizing a logistics sensing network, and obtaining risk tracing data; and analyzing a compensation strategy based on the risk traceability data, and uploading to a platform to execute a compensation task. According to the invention, the bulk commodity trade management efficiency can be improved.

Methods and systems for generating, publishing, processing, and consuming linked data events and streams being shared by complex systems in order to construct a semantic web of the data and thereby form a consolidated coherent view of the data are provided. A method includes: receiving a set of metadata that relates to a set of events; generating, based on the metadata, an ordered node hierarchy map and a modern data event schema; receiving a set of tabular data; generating, based on the tabular data and the ordered node hierarchy map, the set of events; streaming the set of events over a streaming pipeline; processing the streamed set of events to generate a linked data media format; and outputting the linked data media format.

The invention discloses a cold chain full-link data processing method and system, and relates to the technical field of warehouse logistics. A specific embodiment of the method comprises the steps of performing association and fusion processing on attributes of entities corresponding to different data sources based on a pre-created unified data model to obtain an aggregated data set; performing data mining and prediction on the aggregated data set, and determining a target performance index which has the greatest influence on the cold chain quality based on a decision tree algorithm; displaying the aggregated data set and the target performance index on a visual interface; and in response to a received interaction instruction sent by a user through the visual interface, updating the full-link process according to the interaction instruction. According to the implementation mode, the data of the multiple data sources are subjected to fusion analysis and visual display, the preset full-link process scheme is conveniently updated through a visual interface by applying an interactive method so as to optimize the full-link process, and processing analysis and visual analysis of the full-link data of the cold chain in the smart park are realized.

Disclosed in the present invention are a method and apparatus for performing full-link reconciliation on the basis of a snowflake algorithm, and a device and a medium. The method comprises: responding to a cross-border business reconciliation request, and acquiring bill source data from a business terminal; parsing the acquired bill source data, and converting same into target bill data; calling a reconciliation rule engine to acquire a corresponding reconciliation rule and select a corresponding reconciliation algorithm, and executing a full-link reconciliation task for the target bill data, so as to obtain a reconciliation result; transmitting reconciliation imbalance data to a corresponding exception handling system for checking processing of abnormal data; and on the basis of an optimized snowflake algorithm, generating a unique target ID to associate a corresponding bill with the reconciliation result, automatically penetrating full-link data of an information flow and a fund flow on the basis of the corresponding unique target ID in the reconciliation result, and on the basis of the unique target ID, tracing the whole process of the circulation of a corresponding bill between the fund flow and the information flow, so as to achieve a complete reconciliation closed loop. In this way, the reconciliation working efficiency and data accuracy of the full-link reconciliation of a cross-border business are improved.

The invention discloses a data security intelligent treatment method based on data identification. The method comprises the following steps: identifying a data source and identifying the data source; configuring the category and the level of the data, obtaining a classification and grading retrieval rule of the data content, and performing classification prediction on the data content by utilizing the intelligent classification model obtained by training; identifying structured data in various databases, identifying various unstructured data in various file servers, and extracting identification information; various data security protection devices are added and managed, and a security protection strategy based on data identification is configured and issued; collecting logs and identification information, and obtaining an abnormal record or a risk alarm through a security audit strategy; obtaining an abnormal data access behavior of the log, recording abnormal feature information, and generating an abnormal detection result; and carrying out fusion correlation analysis on the obtained abnormal record or risk alarm and the abnormal detection result. According to the invention, efficient, intelligent and system-linked data security management is realized.

The invention relates to the technical field of data management, and discloses a dynamic partitioning and priority scheduling method based on time sequence data, which comprises the following steps: collecting time sequence characteristics of an industrial data source through an edge gateway and carrying out structured storage in Redis, the time sequence characteristics comprising collection frequency, historical peak time period and service priority; load indexes are calculated based on time sequence characteristics, and a distributed message system is driven to execute dynamic partition adjustment of pre-judgment type capacity expansion, hot spot precise splitting and low-peak intelligent capacity reduction; and full-link data priority scheduling is realized through production end route isolation, Broker end resource inclination and consumption end thread pool isolation. According to the invention, the dynamic adaptation of the distributed message system resource and the industrial time series data load is realized, the real-time performance of high-quality data is ensured, the integrity of data transmission and the system adaptability are improved, and the problems of poor load fluctuation adaptation, high-quality data delay and easy data loss due to faults in the prior art are effectively solved.

A system including a media data optimization engine (MDOE) and a method for automatically creating structured data objects for media content rendered in one or more languages in an electronic document of a business entity are provided. The MDOE identifies non-textual objects including media content rendered in one or more languages in the electronic document and generates textual objects in the corresponding language(s) therefrom. The MDOE transforms the textual objects into structured data objects based on configurable criteria and generates a dynamic index-oriented object for the structured data objects specific to the business entity. The MDOE connects the structured data objects to the dynamic index-oriented object by creating linked data nodes therefrom with the dynamic index-oriented object as a core. The MDOE connects the dynamic index-oriented object with the linked data nodes to the electronic document, thereby facilitating dynamic changes to the electronic document and dynamically optimizing the electronic document.