3516 results about "Data records" patented technology

Blockchain synchronization and point-of-sale integration systems are provided in a packet-switched computer network. The POS interfaces through the network with a consumer smartphone and a blockchain validation device. The POS shares a session identifier with the blockchain validation device by transmitting a graphic encoding of a payment request and the session identifier to the smartphone. The camera of the smartphone is configured with an image of the graphical encoding. A payment instruction is encoded to conform to the payment request including the session identifier and is transmitted to the blockchain validation device. The blockchain validation device performs a verification of the correctness and authenticity of the payment instruction encoded in the data record. The POS device receives a confirmation that the correctness and authenticity of the payment instruction encoded in the data record to confirm it has been verified.

Systems and methods for data streaming with attribute-based access control. A client apparatus in a data streaming system receives a message via a data stream, form a data stream provider. The message has a schema version of the schema associated therewith. The client apparatus processes the message to retrieve a record, the record including a data item and a data tag corresponding to the data item. The client apparatus, with reference to the schema version, determine whether an identifier (e.g., client ID) of with the client apparatus has permission to access the data item associated with the data tag. After detecting that the identifier does not have permission to access data associated with the data tag, the client apparatus masks the data item to produce a masked data record. The client apparatus releases the masked data record for further processing by the client apparatus.

Systems, computer program products, and methods are described herein for building material data management. With reference to an example method, the method receives a first dataset formed of first data entries associated with a building material data source and generates a building material data entity based on the building material data source. The method includes outputting a representation of the building material data entity. The first dataset may be formed of data records (e.g., construction documents, user inputs, sensor data, or machines data), and the representation may be a visual representation may include notifications, visual presentations of the building material entity, etc.

The invention relates to a security protection method, system and device for data sharing and exchange and a medium. The method comprises the steps that original data are loaded, sensitive information in the loaded data is recognized, and the original data are classified according to the category of the sensitive information; obtaining user demand information and a corresponding target scene condition, adding noise to the sensitive information through a differential privacy algorithm according to the user demand information and the target scene condition, and generating privacy protection data; transmitting and encrypting the privacy protection data to obtain corresponding encrypted data, transmitting the encrypted data through a corresponding encrypted channel, recording an operation log in a data transmission process, and embedding an invisible watermark to track the use condition of the encrypted data; and analyzing the privacy protection requirement of the target scene condition, dynamically adjusting the privacy protection parameter of the encrypted data according to a preset use specification, and recovering the encrypted data when the life cycle of the encrypted data is ended. The method and the device have the effect of improving the data sharing security.

The invention discloses a financial data intelligent entry and verification method, which comprises the following steps: acquiring an original document image, and processing the original document image by adopting an image enhancement algorithm to obtain an optimized document image; extracting a structured field from the optimized document image, determining field coordinates, and generating a structured data table; performing semantic analysis on the non-standardized text in the structured data table to generate semantic vector representation; identifying missing fields according to the semantic vector representation, querying a historical database, and generating preliminary filling data; comparing the preliminary filling data with historical data through a cross validation mechanism to obtain a validated field value; processing the verified field value by adopting a classification model, and determining a document type; arranging the verified field value according to the document type, and generating a standardized data record; key indexes are extracted from the standardized data records, the index logic relation is verified, and corrected data are obtained.

A computer-implemented method is disclosed for generating structured data representations from unstructured input text sequences through a neural network-based extraction pipeline. The method involves acquiring input text sequences and processing them with an extraction neural network to produce output text sequences. Each output text sequence includes embedded delimiter tokens that annotate specific text segments, mapping them to semantic categories defined within a structured schema. The annotated text segments encapsulate semantically relevant information extracted from the input sequence. The output text sequences are subsequently processed to generate structured data records.

An autonomous agricultural drone system for the precise spraying of pesticides, consisting of: an advanced image recognition camera integrated with an artificial intelligence (AI) module specifically trained on pest and plant health datasets, with the camera configured to detect specific pests, identify pest hotspots, and differentiate between healthy and stressed plants; a real-time decision processor that is operationally connected to the image recognition camera, the processor being configured to: Data received from the image recognition camera is interpreted to assess pest density and plant health. adjusts the pesticide output and spraying patterns of the drone based on real-time field conditions, determines the severity of pest infestation in order to avoid excessive use of pesticides and to apply pesticides precisely and only where they are needed; a multitude of intelligent spray nozzles equipped with sensors and actuators, each nozzle configured to dynamically adjust its spray rate based on pest density and plant species, as determined by the real-time decision processor, thereby minimizing chemical use and environmental impact; characterized by the fact that The drone system includes a multi-liquid injection nozzle system that allows the drone to carry and selectively apply multiple solutions, including pesticides and nutrients, in a single flight, with the system configured to switch between solutions in response to real-time data from the image recognition camera and decision processor.

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.

Provided in the present invention is a ship hatch data management method based on point cloud technology. The method is implemented by means of a constructed ship hatch data management system, and the system comprises a ship scanning module, an automatic hatch identification and calculation module, a ship attitude data compensation module, and a hatch data calibration and accumulation module. In the present invention, by means of processing data of a scanner and analyzing point cloud data, a point cloud model of a ship to be subjected to operation is generated in combination with mechanism parameters of a ship loader, the position of a ship hatch is automatically identified, the spatial coordinates of the ship hatch in a rectangular coordinate system of wharf space are automatically calculated, hatch identification data for current berthing is calibrated on the basis of historical hatch data records from the same hull number after berthing in a database, and the ship loader is guided to realize unmanned and automated operation modes by means of the calculated hatch position, thereby enhancing the level of port automation.

A coal mine risk early warning system based on big data analytics, the coal mine risk early warning system comprising: a data collection module, used for collecting data in real time during coal mine operation; a data storage module, configured to store historical data records collected by the data collection module; a data processing module, which uses big data analytics technology to process the stored data and identify potential risk factors; a risk assessment module, which assesses the risk level of coal mine operation on the basis of analysis results of the data processing module, there being three risk levels: low, medium, and high; and an early warning module, which sends an early warning signal to relevant personnel when the risk level reaches a preset threshold.

An automated system for the detection of pests and diseases in crops using image processing based on deep learning, which includes the following: ◯ an image acquisition unit (101) configured to capture high-resolution images of crops; ◯ a preprocessing unit (102) for improving image quality by applying noise reduction, contrast enhancement and segmentation techniques; ◯ a convolutional neural network (CNN) model(103) trained on a dataset of annotated images of pests and diseases and configured to extract features and classify detected anomalies; ◯ a decision unit (104) that, based on the detected pests or diseases, generates diagnostic reports and provides treatment recommendations; ◯ an integrated mobile (105) and web-based application interface that provides real-time analytics, historical data tracking and recommendations for farmers and agricultural experts.

A system and method for root cause analysis in incident processing, including root cause change detection, is presented. The method includes processing a plurality of event records, including a plurality of alert records and a plurality of change records, each event record generated based on an event in a computing environment; parsing each alert record based on a predetermined data field; extracting from each predetermined data field a data value; correlating a group of alert records of the plurality of alert records based on at least an extracted data value; generating an incident data record based on the extracted data values of the correlated group of alert records; detecting a change record of the plurality of change records related to the incident data record; determining that the change record is a root cause change of the incident data record; and initiating a mitigation action based on the root cause change.

The invention discloses an intelligent data management system and method based on multi-source data collection, and relates to the technical field of data processing. Multi-source data from multiple data sources are obtained, an original data set with credibility marks is generated, data records in the original data set are classified according to data types, and for time series data, data records in the original data set are classified according to credibility marks. Extracting trend features by applying a segmented multi-model time sequence feature extraction framework; for the data of the unstructured data, extraction of unstructured features is carried out through a feature extraction model based on a multi-layer perceptron; for structured data, a knowledge graph technology is adopted to establish an adaptive association relationship, association relationship data is generated, trend features, unstructured features and the association relationship data are used as input of a data value evaluation model, and data asset performance evaluation of dynamic weight is generated; and intelligent management and value evaluation of the multi-source heterogeneous data are realized.

The invention discloses an intelligent warehouse management method and system for hazardous wastes, and the method comprises the steps: carrying out the real-time monitoring of the state of an object in a hazardous waste warehouse through a deployment sensor network, obtaining the basic data of the position of the object and the environment parameter, and transmitting the basic data to a central processing platform, thereby obtaining a preliminary data set; performing integration processing on multi-source information by adopting a data fusion technology according to the preliminary data set, eliminating redundancy and noise, and determining a standardized data record; aiming at the standardized data record, dynamically analyzing the distribution of goods locations in the warehouse by utilizing a path optimization algorithm, and if the change of the occupation state of the goods locations is detected, adjusting a goods location allocation scheme in real time, and outputting an optimal storage location combination; according to the optimal storage position combination, a dynamic route planning scheme is generated in combination with warehouse layout information, and the optimal moving track of the operation equipment is obtained; according to the invention, intelligent management of the hazardous waste warehouse is realized, and the storage efficiency and safety are improved.

The invention discloses a CPLD-driven IGBT short-circuit current dynamic monitoring method and system, and relates to the technical field of power electronics, and the method comprises the specific steps of S100 real-time data acquisition, S200 dynamic threshold calculation, S300 short-circuit state judgment, S400 rapid protection execution, and S500 fault data recording and uploading. Accurate and prospective judgment of the short circuit state of the IGBT is achieved, two stress parameters including the direct-current bus voltage and the junction temperature serve as independent variables, when the bus voltage rises, the voltage stress borne by the IGBT in the turn-off period is increased, meanwhile, the current peak at the short circuit moment is more remarkable, early warning is conducted in advance by dynamically lowering the threshold value, and therefore the short circuit state of the IGBT is accurately judged. According to the mechanism, the monitoring system does not simply respond to the occurred overcurrent, but can pre-judge the safety boundary of the device under the current working condition, so that intervention is implemented before the current really reaches a dangerous peak value, and a protection blind area under a severe working condition is effectively avoided.

The invention relates to the technical field of textile, in particular to a digital textile equipment management method based on big data, and the method comprises the following steps: 1, an equipment connection and data initialization stage: checking the data interface type of equipment in each link of a textile process, and connecting the data interface type to a workshop data collection network, establishing an electronic file for each device, setting initial data acquisition parameters, and carrying out pre-operation test and calibration on the devices; 2, a production process monitoring and data recording stage; according to the scheme, the equipment performance evaluation model is established by using a big data analysis technology, multiple factors such as energy consumption efficiency, a production stability index and an equipment failure rate trend are comprehensively considered, and the equipment performance is comprehensively and accurately evaluated, so that sudden equipment failures are effectively avoided, the risk of production interruption is reduced, and the production efficiency is improved. The overall management efficiency and the operation stability of the equipment are improved, the continuity of the production process is guaranteed, and the cost increase caused by equipment faults is reduced.

A machine learning-based clinical workflow system processes patient encounter data to generate structured data records and predicted diagnosis classification codes. The system may obtain an input record, generate vector embeddings, and identify reference records using vector similarity operations. A machine learning (ML) component may generate a structured data record based on the input and reference records. The system may also generate an ML instruction, identify reference codes, and produce a predicted code. The predicted code may include a predicted diagnosis classification code, a predicted procedural code, or a billing code. Vector databases storing embeddings of medical codes and records may facilitate efficient retrieval of relevant information. Some implementations may include prediction of billing codes to address revenue capture. Some implementations may utilize specialty-specific processes and data to enhance accuracy for particular medical fields. The system may incorporate clinician feedback to continuously improve performance and adapt to evolving healthcare practices.

The invention relates to the technical field of information retrieval, in particular to an artificial intelligence digital science and technology platform based on big data analysis, which comprises a data uncertainty modeling module for receiving a big data stream, determining a confidence interval boundary for each data item to represent the uncertainty of the data item, generating a data item uncertainty parameter set, and combining each data item with the corresponding data item uncertainty parameter set, and then storing the data item and the corresponding data item uncertainty parameter set to form a structured probability data record. According to the method, by independently establishing an uncertain parameter structure for each data item in the data stream, tight binding of the data items and the corresponding uncertain parameters is realized, a structured probability data record is generated, the precision and reliability of the data in the query and calling process are guaranteed, and retrieval errors caused by isolated storage of the data items are avoided; through probability attribute grouping of a preset space and a numerical range and establishment of a multi-dimensional probability index structure, the search space and the filtering difficulty of probability data are reduced.

An artificial intelligence digital assistant that retrieves and consolidates data from diverse sources is described. After a system initiates a response to an information request received from a user, a language model generates a high-dimensional vector that represents the information request from the user. The language model identities data access tools that access corresponding data types identified for the information request. The system executes the identified data access tools that retrieve, from corresponding data sources, data values from corresponding data records represented by corresponding unique high-dimensional vectors that have similarities, which exceed a confidence level, to the high-dimensional vector that represents the information request. The system sends a consolidation of the data values in the response to the user.

The invention relates to the technical field of equipment full-life-cycle management, in particular to an equipment full-life-cycle tracing and management and control system based on digital threads. Comprising a digital thread generation unit which is used for generating a dynamic digital thread penetrating through the whole life cycle of technical improvement purchasing, operation maintenance and decommissioning of equipment; a full life cycle data integration unit; and a business process management and control unit. According to the method, a dynamic digital thread which runs through the whole life cycle of technical improvement purchasing, operation overhaul and decommissioning of equipment is constructed, and a multi-dimensional data anchoring algorithm fused with weighted Bayesian estimation is combined, so that probabilistic association matching between heterogeneous physical data in each stage and a corresponding physical scene is realized; and a unique device identifier is bound to form dynamic association of physical state-data record-time node, so that the problems of fragmentation of data in the whole life cycle of the device and lack of association between the data and a physical scene in the prior art are solved.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for filtering a collection of structured data records generated by an extraction neural network to enable generation of a response to a query. According to one aspect, there is provided a method that includes receiving a request to generate an article directed to a topic, where the request includes a target text string for a semantic category, standardizing the target text string for the semantic category, filtering the collection of structured data records based on the standardized target text string to identify a subset of structured data records that are relevant to the topic, and processing the subset of structured data records to generate the article directed to the topic.

Blockchain synchronization and point-of-sale integration systems are provided in a packet-switched computer network. The POS interfaces through the network with a consumer smartphone and a blockchain validation device. The POS shares a session identifier with the blockchain validation device by transmitting a graphic encoding of a payment request and the session identifier to the smartphone. The camera of the smartphone is configured with an image of the graphical encoding. A payment instruction is encoded to conform to the payment request including the session identifier and is transmitted to the blockchain validation device. The blockchain validation device performs a verification of the correctness and authenticity of the payment instruction encoded in the data record. The POS device receives a confirmation that the correctness and authenticity of the payment instruction encoded in the data record to confirm it has been verified.

A system and method for reducing data record processing in incident report generation is provided. The method includes: accessing a plurality of event records, each event record generated based on an event in a computing environment; parsing each event record based on a predetermined data field; extracting from each predetermined data field a data value; correlating a group of event records of the plurality of event records based on at least an extracted data value; generating an incident data record based on the extracted data values of the correlated group of event records; generating a prompt based on the incident data record; and generating an incident report by configuring a large language model (LLM) to execute the generated prompt.

Systems and methods of the present disclosure may receive, from a user computing device, a user-provided data record query including a natural language request for information associated with one or more data sources. User persona attributes of the user may be determined, such as a user role or security parameters or both. Based on the user persona attributes a context query may be generated to obtain context attributes associated with the user-provided query. The natural language request and the context attributes are input into the model orchestration large language model (LLM) to output instructions to machine learning (ML) agents based on the context attributes. The ML agents output responses associated with the user-provided data record query based on the instructions, and the responses are input into the model orchestration LLM to output to the user computing device a natural language response based on the context attributes.

The invention provides a photovoltaic wind power energy storage intelligent management method and system for a building. The method comprises the following steps: acquiring operation parameters, environmental conditions and historical fault data records of system equipment, and preprocessing the acquired data; establishing health assessment indexes by using the comprehensive wind and light energy storage equipment performance model, and determining the health degrees of different equipment; the fault abnormity level is judged according to the fault alarm signal sending time and frequency of the system equipment; through combination of an autoregressive differential moving average model and a long-short-term memory model, the photovoltaic and wind power comprehensive electric quantity is predicted, and the loss abnormity level is judged; and in combination with the health degree, the fault abnormity level and the loss abnormity level of the equipment, making a patrol inspection and daily maintenance work plan, and sending out reminding and early warning. By analyzing and diagnosing key equipment and core performance of the system and early warning key events, energy waste and equipment damage caused by improper maintenance can be effectively avoided.

Embodiments of the present application provide a transaction processing method, a device, and a storage medium. For a distributed transaction, it is proposed innovatively that exclusive locks are added to data records involved in a read set of the distributed transaction in a read phase; in a write phase, write operations for a write set can be directly executed based on these exclusive locks, and an exclusive lock on a related data record can be released immediately after a write operation is completed. In the write phase, the exclusive locks added to the data records can maintain the exclusivity of the distributed transaction over these data records, which can avoid the write operation abort problem in the write phase. That is, all write operations of the distributed transaction are bound to succeed, thereby ensuring the atomicity of distributed transaction processing. In addition, since the exclusive lock is released immediately after the write operation is completed, the lock-holding time of the distributed transaction is only the time inherently required to execute transaction logic of the distributed transaction, thereby greatly reducing the lock-holding time of the distributed transaction, effectively increasing the throughput for distributed transactions and improving the transaction processing efficiency.

The invention discloses a computer batch data storage method and system based on a block chain, and relates to the technical field of computer batch data storage.The computer batch data storage method comprises the steps that computer batch data are analyzed through a data classification method, the computer batch data are divided into hot data and cold data according to the access frequency, and a classified data set is obtained; performing encryption processing on the classified data set by adopting a homomorphic encryption method to obtain an encrypted data set; distributing the encrypted data set to a corresponding storage level by adopting intelligent contract definition logic to obtain a data record with a distributed storage position; creating a detailed index record and storing the detailed index record on the block chain to obtain an index record on the block chain; determining a data position when the specific data is retrieved by adopting a method of querying the index record on the block chain, and obtaining verified data; and checking the integrity of the data and the running state of the system by adopting a security auditing method to obtain an auditing result, and adjusting a storage strategy based on the auditing result.

The present invention relates to a knowledge graph construction method and system for complex relational business databases, including concept-level graph modeling, data-level graph modeling, and graph migration and integration. By accessing a business database or importing a model file, the database table structure and its constraint relationship of the business database are automatically analyzed, and a tree-like classification candidate concept list and candidate relationship list are formed according to certain rules, and a concept-level knowledge graph is quickly constructed. The classification and clustering algorithms are used to realize multi-layer classification and grouping of data records, and a data-level knowledge graph is quickly constructed. The constructed business knowledge graph is migrated and integrated, and it supports importing it into a graph database for storage and retrieval. The problem that the existing knowledge graph construction method fails to effectively consider the relevant characteristics of complex relational business databases is solved, the operation complexity is greatly reduced, and the efficiency of knowledge graph construction for complex relational business databases is improved.

The invention relates to the technical field of live broadcast recommendation, in particular to an intelligent live broadcast recommendation method and system based on big data, and the method comprises the following steps: obtaining user social interaction data, recording text comments, picture sharing and like behaviors, extracting keywords and mapping the keywords to interest classifications, combining the like frequency and interest labels to update dynamic interest records, and recommending the like. And matching the time sequence interest tag set to generate a cross-platform interest map, counting distribution of watching contents of social circle members, adding recommended contents, and generating a live broadcast recommendation list. According to the invention, the social interaction data of the user is acquired and the specific behavior is recorded, the creation of the dynamic interest label record can more accurately reflect the current interest and behavior mode of the user, and the watching type and duration of the live broadcast platform and the keyword in the comment are combined to ensure that the recommended live broadcast content is highly matched with the actual interest of the user, so that the user experience is improved. The social correlation of recommendation is enhanced, and the accuracy of live broadcast recommendation and the interaction rate of users are improved.

The invention provides a vehicle driving safety management method and system and a storage medium, and relates to the technical field of vehicle driving safety management, and the method comprises the steps: carrying out the state data collection of a target vehicle through a vehicle-mounted sensor set, and obtaining a vehicle real-time state data set; performing preprocessing to obtain a vehicle standard state data set; according to the vehicle standard state data set, multi-risk synchronous identification is carried out, multiple risk event identification results are obtained, and the multiple risk event identification results have multiple risk scores; according to a preset risk alarm index, carrying out risk grade evaluation on the plurality of risk scores to obtain a plurality of risk grades; and carrying out risk event processing according to the plurality of risk levels and a preset multi-level risk response mechanism. The technical problems that traditional driving safety management mostly depends on manual observation or simple data recording, real-time and comprehensive monitoring cannot be achieved, feedback lagging of bad behaviors of a driver is caused, and then safety is insufficient are solved.