5120 results about "Data records" patented technology

A method to be executed on a computing device comprising (i) accessing and / or modifying a database to be automatically curated, (ii) optionally accessing additional data or information sources for further useful data or information, (iii) using one or more pre-trained large language models (LLMs) accessed via API or other connections, issuing prompts and retrieving prompt-answers and executing database curation requests that specify database curation tasks to be performed on at least one sub-structure of the database, the tasks comprising (a) a database enrichment task to compute new data records to be inserted into the database sub-structure, (b) a database verification task to verify, using the one or more LLMs, data contained in the sub-structure, and identify incorrect data, (c) a database update, and (d) a null-value or a missing value replacement task. The requested tasks are automatically performed via a computation comprising an adaptively generated prompt sequence.

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.

Database systems and methods are provided for personalized automation agents. One method involves determining an action to be performed on behalf of a user, identifying a relevant subset of data in a database of the database system associated with the user based on the action, generating a personalized input prompt for an execution plan for the action using the using that subset of data, providing the personalized input prompt to a service configurable to generate a personalized conversational response, receiving the personalized conversational response comprising textual content indicative of a sequence of steps of the execution plan from the service, automatically executing the execution plan in accordance with the sequence using the service to perform the action with respect to a data record in the database, and automatically providing a response to the client device indicative of the action with respect to the data record.

In an embodiment, a workflow automation computer system comprises one or more hardware processors; one or more network interfaces that are communicatively coupled to one or more internetworks and capable of network communication with a browser extension hosted on an agent computer, a relational database system, and a support ticket system; and one or more non-transitory computer-readable storage media coupled to the one or more hardware processors and storing one or more trained machine learning models having been trained to output predictions of actions of web-based applications based on input specifying a plurality of browser events from interactions with the web-based applications; and one or more sequences of instructions which, when executed using one or more processors, cause the one or more processors to execute receiving, from the browser extension, one or more browser event objects corresponding to user input signals arising from interactions of the agent computer with the web-based applications, extracting attribute values from the one or more browser event objects, and storing, in the relational database system, the one or more browser event objects and attribute values as a plurality of events of user action time series records; clustering the plurality of events and performing action analysis on the plurality of events by executing a first inference stage of the one or more trained machine learning models over the one or more events to output suggestions of associations of user actions corresponding to the one or more events; forming one or more training data records based on the associations of user actions corresponding to the one or more events; re-training the one or more trained machine learning models based on the associations of user actions to produce one or more re-trained machine learning models.

A dynamic generative-AI enhanced leadership coaching platform includes an agent, an authentication module, an event processor, a user interface module, a router, a generative AI module having a prompt compiler module, a post-conversation analysis module, a prompt template library, an API interface module, a memory management module having a vector-search module, a vectorized database module configured to store vectorized data records and be accessible to the memory management module, a vectorization module configured to vectorize data, a knowledge base database module configured to catalogue vectorized data, and a user profile stored in the user database including a dynamic data point, a personalized conversation starter, and a user permission set.

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 relates to the technical field of supply chain management, in particular to a block chain-based culture product tracing method and system, and the method comprises the following steps: collecting the type, producing area and growth cycle data of culture products, distributing an identifier for each data item, coding the data and the associated identifiers in an upload format, and storing the data and the associated identifiers in a database; and uploading the data to a block chain network through an encryption channel, and generating a coded data record. According to the method, the timestamps and the data records are bound, each record is processed by using the hash function, and the security of each supply chain node is verified, so that not only is the integrity of data processing improved, but also an effective verification means is provided for consumers, and the security of the consumers is improved by decrypting and verifying the encrypted data. The security and privacy protection of data in storage and transmission are ensured, the production and circulation process of products is tracked through a block chain query function, the food security is improved, the supervision compliance is enhanced, and a powerful tool is provided for solving fraud and pollution problems in a supply chain.

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.

The invention relates to a cervical vertebra rehabilitation system based on virtual reality. The cervical vertebra rehabilitation system comprises a virtual reality display module, a cervical vertebra action detection module, a central processing module, a rehabilitation training control module and a data recording and analyzing module. The virtual reality display module provides an immersive rehabilitation environment for a patient through a head-mounted display device, and the cervical vertebra motion detection module captures cervical vertebra motion data of the patient in real time through an accelerometer, a gyroscope and a magnetometer. And the central processing module fuses the multi-dimensional data through a Kalman filtering algorithm, accurately estimates the cervical vertebra posture of the patient, and synchronizes the action of the patient to a virtual environment. The rehabilitation training control module dynamically adjusts the training content according to the actual rehabilitation progress of the patient, provides a personalized rehabilitation scheme, and enhances interactivity and interestingness. The data recording and analyzing module records training data of the patient in real time and generates a rehabilitation report to help doctors to perform scientific evaluation.

A system and method for near real time detection of cybersecurity threats in a computing environment. The method includes: detecting an event in a data log, the data log including a plurality of data records, each data record corresponding to at least an event; parsing a data record corresponding to the event to detect a data value; detecting a node in a security graph, the node corresponding to the detected data value, wherein the security graph includes a representation of the computing environment; initiating inspection of a resource corresponding to the node.

Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and / or the like for generating a plurality of training embeddings based on a pre-training dataset, wherein the plurality of training embeddings comprises one or more of descriptive embeddings, sequential ordering embeddings, age / time embeddings, locale embeddings, or encounter number embeddings; generating one or more initialized weights associated with respective one or more layers of a machine learning model based on the plurality of training embeddings; generating one or more fine-tuned weights for the machine learning model by updating at least a portion of the one or more initialized weights using a fine-tuning dataset associated with a target classification; and generating, using the machine learning model, one or more prediction scores for one or more prediction encounter data elements associated with the target classification, based on one or more input temporal sequence of encounters data records.

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.

The invention relates to the technical field of intelligent locks, in particular to an electric power facility intelligent lock remote control and authority management system which comprises an intelligent lock module, an identity verification module, an authority management module, a multi-device collaborative optimization module and a data recording and analyzing module. The intelligent lock module is physically connected with a lock of an electric power facility through a prefabricated mounting interface; the identity verification module is used for carrying out multi-mode identity verification on an operator; the authority management module dynamically allocates authority levels of operators; the multi-device collaborative optimization module optimizes operation and resource allocation among devices; and the data recording and analyzing module records an operation log of the intelligent lock in real time, analyzes the operation log, detects an abnormal behavior and automatically performs permission adjustment. According to the invention, high-efficiency cooperation of equipment and safety, flexibility and operation efficiency of the system are ensured, and complex electric power facility management requirements are effectively met.

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 method, system, computer program product of providing a FiniteStateMachine (FSM) with embedded business rules, processing data & events, where each state is individually saved to blockchain ledger, a data record including a unique identifier / name, a set of input field(s) or input data slots, state rules in a rule language, and set of output field names or output data slots, method including: executing of a Smart Contract by identifying state by id or name, loading corresponding Component State from blockchain, adding / executing code for processing the State's behavior, where the code includes rules for the state in the rule language (e.g., but not limited to. Open Policy Agent, Rego, Prolog, DataLog, RuleML, Drools Rule Language, NRules, and JavaScriptObjectNotation(JSON), etc.). System includes processor(s), application program interface (API(s)) for communicating, blockchain, rule processor, and memory. This enhances transparency, immutability, and secure execution of business rules within FSM architecture.

The invention discloses a database-based data indexing and query optimization system and method, belongs to the technical field of databases, and aims to solve the technical problem of how to improve the data indexing efficiency and query performance of a database system. According to the technical scheme, the system comprises a query optimization module, an index construction module and a data storage module; the data storage module is used for storing data records in a database; data records are stored in a column mode, the data compression rate and query performance storage are improved, and disk I / O operation is reduced; the index construction module is used for constructing an index according to the data record in the data storage module, the index adopts a B + tree design, and the number of I / O operations during data transmission between a disk and a memory is reduced; and the query optimization module is used for receiving a query request and optimizing a query path according to the index constructed by the index construction module.

The invention relates to an intelligent winding control method of a lithium battery automatic cutting and winding machine in the field of winding machines, which aims at the inertia effect of a material in a high-speed winding process, establishes a material dynamic model, comprehensively considers the quality, rigidity and damping parameters of the material, predicts the dynamic response characteristics of the material in the winding process, and controls the winding speed of the material. A feed-forward compensation mechanism is introduced into a control system, and control instruction correction is performed on an execution mechanism according to a prediction result of a material dynamic model, so that the influence of a material inertia effect on position control precision is inhibited; in a man-machine interaction interface of the winding machine, information display and operation guide functions are provided, key parameters and equipment state information in the winding process are displayed in real time, monitoring and management by operators are facilitated, a perfect data recording and tracing system is established, production process data of each roll of battery cells are completely recorded and stored, and the production efficiency of the battery cells is improved. A traceable quality management chain is formed, and data support is provided for product quality analysis and improvement.

The invention discloses an intelligent wireless charging power distribution method and system, and aims to improve the efficiency and safety of simultaneous charging of multiple devices, and the system design comprises a plurality of key modules: a device detection and recognition module automatically recognizes the charging devices and collects the power demands of the charging devices; the power demand analysis module calculates the power demand of each device according to the device electric quantity and the charging mode, and the power distribution control module dynamically adjusts the power output according to the priority, the distance and other factors; the real-time monitoring and feedback module ensures the stability and safety of the charging process, and the data recording and learning optimization module optimizes the charging strategy by analyzing historical data. Through cooperative work of the modules, the system can adjust the charging power in real time, optimize the charging efficiency, improve the user experience, and ensure the safety of the charging process. The system shows good adaptability in a multi-device environment, and important reference and application prospects are provided for development of a wireless charging technology.

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 relates to the technical field of safety evaluation, in particular to an ultra-deep soft soil foundation pit safety evaluation method and system, and the method comprises the following steps: obtaining the geological data of an ultra-deep soft soil foundation pit, recording the soil type, soil density, underground water level and temperature data, carrying out the data arrangement and formatting, and generating a geological data record sheet. According to the method, the detailed geological data of the ultra-deep soft soil foundation pit are acquired and arranged, the accuracy and the applicability of the basic data are enhanced, so that subsequent analysis is carried out according to clear actual conditions, and the timeliness and the accuracy of risk prediction are ensured by directly associating prediction of mechanical behaviors with risk assessment; the risk assessment model can be dynamically adjusted, the effectiveness and accuracy of early warning are improved, the risk dependency relationship model and the monitoring scheme are integrated, theoretical and actual operations are effectively linked, the systematicness and adaptability of construction safety management are effectively improved, and the accident prevention capability is remarkably improved.

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.

Systems and methods including an interface for routing data transmissions in response to dynamic queuing of service requests. A data processing system includes the interface in which one or more medical service providers within structured data records, such as electronic health records (EHR) or electronic medical records (EMR), can indicate that they are available to provide services to one or more patients. When a medical service provider indicates that he or she is available to provide additional medical services, one or more patients who have requested a corresponding medical service can be automatically routed to that medical service provider.

The invention belongs to the technical field of information communication, and discloses an optical fiber logic link intelligent identification and early warning system, which comprises an optical fiber sensor, a data acquisition module, a processing unit and a communication module, the system is characterized in that the processing unit comprises a data processing module, a state identification module, an early warning mechanism and a data recording and analyzing module. The method has the main beneficial technical effects that a user can intuitively see the change trend of each parameter and the current link state, so that the user is ensured to know the potential fault or degradation risk at the first time. In the aspect of real-time monitoring, the system not only records current data, but also analyzes historical data by using an intelligent recognition algorithm, and recognizes the health state and the possible deterioration trend of the optical fiber link. The early warning system not only enhances the security of the optical fiber communication network, but also provides powerful information support for users, and assists the intelligent management of the optical fiber network.