27 results about "Data validation" patented technology

Systems and methods are provided for a prompt and content generation service to validate generated references and training data sets of large language models (LLMs). The prompt and content generation service may determine if a reference generated by an LLM is valid by searching a training dataset for tokens using a prompt, generated answer, and generated reference for content and references in the training data set. If the prompt and content generation service finds content or a valid reference with a certain confidence level, the prompt and content generation service may indicate that the generated content and reference is valid. The prompt and content generation service may additionally validate a saved checkpoint during training of an LLM by executing use case scenarios against the LLM checkpoint and determining if expected answers match generated answers.

The process validation platform disclosed herein enables automated validation of data transformation processes based on simulation-based data. For example, the process validation platform can generate metadata associated with a data transformation environment, evaluate the metadata, and generate test data based on the metadata. The process validation platform can generate test cases (e.g., test records) and associated code samples based on the test data and enables updates and review of the test cases. The process validation platform can transmit the code samples to the data transformation pipeline for execution of the associated data validation tasks.

The invention relates to the technical field of artificial intelligence and education, and discloses a composition AI review improving system and method based on scene deduction, and the method comprises the steps: obtaining the basic information of a learner and the text data of a composition, and carrying out the standardization processing; performing text statistical analysis on the standardized learner basic information set; carrying out scene type identification and task difficulty assessment; establishing a matching relationship between the writing ability of the learner and the task difficulty evaluation result, and obtaining personalized review strategy configuration parameters according to the matching result; processing the personalized review strategy configuration parameters and the to-be-reviewed composition text; verifying the accuracy of the fractal-dimension scoring result and the comprehensive evaluation report in combination with feedback data, and adjusting personalized review strategy configuration parameters according to the verification result; according to the invention, by constructing a scene deduction mechanism and a personalized review strategy, the evaluation standard can be automatically adjusted according to different teaching scenes, learner characteristics and composition types.

A system for providing an interactive inspection map of an inspection surface inspected by an inspection robot includes an inspection circuit structured to interpret inspection data of the inspection surface from the inspection robot and a user interaction circuit structured to interpret a user focus value from a user device. The user focus value includes an activation state value. The system further includes an inspection visualization circuit structured to provide the interactive inspection map to the user device in response to the user focus value. The interactive inspection map is based on the inspection data. Also, the system includes an inspection data validation circuit that determines an inspection data validity description of the inspection data. The inspection data validity description is provided as a display layer on the interactive inspection map to indicate whether the inspection data is valid.

A computer system for performing cloud-based enhanced rules conflict checking is provided. The computer system is programmed to store a plurality of rules for transmitting to a plurality of destination systems and receive a data message for transmission to the plurality of destination systems from a first requesting system. The computer system is programmed to compare the data message to a first set of rules to validate the data message and if the data message is validated for the first set of rules, instruct the first requesting system to transmit the data message to the plurality of destination systems. The computer system is further programmed to receive the data message for transmission to one or more remaining destination systems from a second requesting system and compare the data message to a second set of rules for validating the data message.

Embodiments of the present disclosure are directed to a system for monitoring operating conditions of a saltwater disposal pump system, which includes a processing device that causes a controller to receive an alarm from the at least one machine that exceeds a predetermined alarm level indicative of an abnormal machine operation, receive a plurality of data from a plurality of sensors that are indicative of a current operating conditions of a saltwater disposal pump assembly, derive an expected value utilizing a statistical regression analysis, determine whether the expected value and a history of the plurality of data correlate at a point where the plurality of data exceeds the predetermined alarm level, determine whether a deviation from a predefined operating profile exceeds a predetermined machine data validation threshold value, validate the alarm, output an alert of the deviation and inhibit further operation of the saltwater disposal pump assembly.

A posthumous memory-sharing system including a memory storage system storing user-selected digital content and instructions for communicating with a computing device of a recipient. The memory storage system authenticates death of the user based on receiving biometric data and / or third-party data validation, then transmits verification to the computing device that the death of the user has been authenticated. The memory storage system also receives a unique, recipient-specific encryption key indicating that the recipient wishes to receive at least some of the user-selected digital content or at least one physical item associated with the recipient. In response to receiving the encryption key, the memory storage system sends the user-selected digital content or initiates delivery of the physical item at user-specified or algorithmically determined times. The memory storage system also dynamically adjusts delivery schedules of these items based on recipient availability or real-time interaction feedback.

1. Name of the product in this design: Guided operation graphical user interface for electronic devices. 2. Intended use of this design: for use in an electronic device. 3. The key design feature of this product is its graphical user interface. 4. The image or photograph that best illustrates the design's key points: the front view. 5. Uses of graphical user interface: Used in international logistics, warehouses and other scenarios to guide personnel operations and facilitate human-computer interaction. 6. Description of the changing states of the graphical user interface: Based on the main view, click any icon in the main view to jump to the changing state diagram 1; enter data in the input box in the changing state diagram 1 to jump to the changing state diagram 2; the changing state diagram 2 is the data validation process; if the validation is successful, jump to the changing state diagram 3; click the button in the lower right corner of the changing state diagram 3 to jump to the changing state diagram 4. The front view reference diagram is the reference diagram for the front view, and the change state reference diagram 1-4 is the reference diagram for the change state diagram 1-4. The “XX” in each view represents text and / or numbers.

The invention belongs to the technical field of data verification, and particularly relates to a data verification rule configuration method and system and a data distribution system. The configuration method comprises the following steps: S1, a programmer uses a unified code writing logic in advance to build a running environment of a configuration module; s2, business personnel convert the business demand into logical operation among a plurality of basic demands; and S3, the business personnel in the configuration module reserves the logical operation among the basic demands, converts each basic demand into the logical operation among the plurality of basic verification units, and completes verification rule configuration for the current business demand in the configuration module. According to the data verification method and device, business personnel can conveniently and independently complete configuration and maintenance of the verification rules, the data verification efficiency and verification effect are improved, and meanwhile the stability of data verification is guaranteed.

Examples described herein include implementations for big-data validation. One aspect includes generating a configuration file including dynamic matching data describing a first plurality of data entries and a second plurality of data entries, and generating a data action file. A plurality of data queries are generated based on the dynamic matching data indicated in the configuration file. The plurality of data queries are dynamically executed in parallel, including execution of a plurality of simultaneous data queries to the data source system. Fields of the first plurality of data entries and the second plurality of data entries are matched using the key type and the value structure, corresponding fields of the first data fields and the second data fields having a data mismatch are identified, and a mismatch database entry for the corresponding fields having the data mismatch is automatically generated.

A method and a system for performing schema-based data validation are disclosed. The method includes receiving a first dataset that comprises a plurality of entries, the first dataset is received from at least one data source. Next, the method includes receiving a second dataset that comprises a predefined set of instructions corresponding to a set of conformity standards for validation of the first dataset. Next, the method includes applying the predefined set of instructions to the received first dataset. Next, the method includes validating each of the plurality of entries of the first dataset based on the applying of the predefined set of instructions. Thereafter, the method includes generating a consolidated assessment report based on the validation, and displaying, using a display unit, the generated consolidated assessment report.

An example operation may include one or more of storing a model of training data of an artificial intelligence (AI) model in a storage of a software application, receiving a request to execute an AI pipeline including the AI model on input data via the software application, determining that the input data is not valid data based on a comparison of the input data to the model of the training data, retrieving additional input data from the storage of the software application, determining that the additional input data is valid data based on a comparison of the additional input data to the model of the training data, and executing the AI pipeline including the AI model on the additional input data to generate a predictive output.

An automated, multi-layered QA system for cloud-native machine learning pipelines, including: a data validation module configured to receive input data from one or more data sources and evaluate the data for quality, completeness, consistency, and schema compliance; a preprocessing validation module that is functionally coupled with the data validation module and configured to check the correctness of data transformations, feature engineering, and normalization processes; a pipeline orchestration interface configured to coordinate the execution of pipeline components within containerized environments; a model validation module that is functionally coupled with the preprocessing validation module and configured to evaluate the performance, accuracy, robustness, and reproducibility of machine learning models during training and inference; a deployment validation module configured to validate the correctness, compatibility, and stability of model deployment in cloud-native environments; a monitoring and anomaly detection module configured to continuously track pipeline behavior and detect anomalies including data drift, model drift, and performance degradation; and a feedback and adaptive learning module configured to dynamically update validation rules and test strategies based on historical data and detected anomalies, the system is configured to provide continuous, end-to-end, and multi-layered quality assurance across all phases of the machine learning pipeline within cloud-native infrastructures.

Embodiments described herein are generally directed to client / server software application development frameworks, and are particularly directed to systems and methods for supporting portable and extensible dynamic user interfaces and data validation. An application development framework is provided, wherein a rules engine component and rules are provided at both the client-side and the server-side, for use with a particular application. The rules engine and rules can be different implementations at each end. The client and server can communicate to exchange the latest versions of the rules; however the rules themselves are agnostic as to which (client-side or server-side) engine they are run on. The system allows users to configure policies associated with a client-side user interface and a backend server, that operate together to provide application portability and extensibility, for example to control the presentation, logic, defaulting, and operation of a data set associated with a dynamic user interface.

A method includes receiving an indication that a record has been updated and determining a confidence score. The method includes, in response to a determination that the confidence score has not met a threshold, filtering a set of communications. The method includes determining whether the record change has met one or more of a set of validity criteria. The method includes, in response to a determination that the user record change has not met the set of validity criteria, based on a first outcome of a set of reporting criteria, automatically generating a prompt with a first suggested revision of the first change. The method includes, in response to a determination that the record change has not met the set of validity criteria, based on a second outcome of the set of reporting criteria, automatically revising the first change with the first suggested revision.

The application relates to a flow upgrade execution and rollback method based on verification lag confirmation, which comprises the following steps: S1, upgrade flow initialization; S2, upgrade data receiving and segment division; S3, upgrade data prewriting; S4, background verification processing; S5, upgrade data validation control; S6, upgrade exception processing and rollback. The device comprises an upgrade management module, an upgrade execution module, a verification module, a validation control module and a rollback control module. The flow upgrade execution and rollback method and device based on verification lag confirmation have the advantages that the prewritten upgrade data segments do not need to wait for verification completion, background independent verification processing is executed, verification results are used for accurately controlling data validation states and rollback operations, the upgrade efficiency is improved, the upgrade time is reduced, the accurate rollback mechanism is realized, and therefore the system reliability and stability are improved.

The invention provides a page configurable generation system and method based on a dynamic rendering engine, and the system comprises a dynamic canvas rendering engine which completes the dynamic rendering of a page based on JSON configuration, and supports the free dragging and position adjustment of a component in a canvas; the financial industry-level component library is used for providing configurable financial business components for the canvas; the permission sandbox module is used for carrying out parameter verification, interface fault isolation and permission control of the movable component on component configuration; and the configuration management system is used for dynamically loading a corresponding attribute configuration panel according to the component selected on the canvas, and supporting real-time preview, configuration synchronization and data persistent storage. Through a multi-level permission verification and data verification mechanism, the compliance and safety of financial marketing activities are ensured, the operation risk and the data leakage risk are effectively prevented, and good safety and reliability are achieved.

Embodiments described herein are generally directed to client / server software application development frameworks, and are particularly directed to systems and methods for supporting portable and extensible dynamic user interfaces and data validation. An application development framework is provided, wherein a rules engine component and rules are provided at both the client-side and the server-side, for use with a particular application. The rules engine and rules can be different implementations at each end. The client and server can communicate to exchange the latest versions of the rules; however the rules themselves are agnostic as to which (client-side or server-side) engine they are run on. The system allows users to configure policies associated with a client-side user interface and a backend server, that operate together to provide application portability and extensibility, for example to control the presentation, logic, defaulting, and operation of a data set associated with a dynamic user interface.

A data processing system implements obtaining a string representing a JSON object at a JSON validator; obtaining a JSON schema for validating the JSON object using the JSON validator, the JSON schema specifying one or more first constraints on the data of the JSON object must be satisfied in order for the JSON object to be valid against the JSON schema; determining, using the JSON validator, that the JSON schema references one or more JSON subschemas, the one or more JSON subschemas specifying one or more second constraints on the data of the JSON object must be satisfied in order for the JSON object to be valid; validating the JSON object using the JSON schema and the one or more JSON subschemas; and performing one or more actions using the JSON object in response to validating the JSON object.

A hybrid cloud bridge system (100) for synchronizing legacy data between on-premises IBM i systems and AWS cloud instances, the system comprising: an on-premises legacy interface module configured to connect to one or more IBM i (AS / 400) systems via native data access protocols, including Distributed Relational Database Architecture and Distributed Data Management, the module further comprising a journal read component for capturing change data in real time from IBM i journal subsystems; a data transformation engine operatively coupled with the on-premises legacy interface module and configured to convert data between the EBCDIC encoding native to IBM i systems and the UTF-8 encoding required by cloud-native applications, the engine comprising an EBCDIC-to-UTF-8 converter, a schema mapping processor, a data validation unit, and a format serializer;a secure communication gateway that establishes encrypted communication channels between the on-premises network and the AWS cloud environment using mutual Transport Layer Security authentication with a pure outbound connection model; a cloud integration module deployed within the AWS cloud environment that includes service adapters for connecting to AWS services; a synchronization controller configured to coordinate bidirectional data synchronization operations via data change detection mechanisms; and a conflict resolution module that implements vector-clock-based versioning to detect and resolve conflicts during concurrent changes;characterized by the fact that the system acts as an intermediary bridge, performing bidirectional real-time synchronization between IBM i legacy systems and AWS cloud instances through integrated data format transformation, secure tunneled communication, and vector clock-based conflict resolution, without requiring any changes to the legacy application code or database schemas.

Systems and methods for producing domain-specific data for training generative AI models as described herein systematically acquire, validate, and fine-tune AI models using domain-specific data. In embodiments, this comprises identifying seed documents, extracting keywords, performing refined searches, and scraping relevant content. The data is then pre-processed, chunked, and indexed. Using a retrieval-augmented generation approach, the system evaluates the quality and relevance of the data, ensuring efficient computational resource use and improved model training outcomes. By leveraging expert knowledge and systematic data validation, the accuracy and reliability of domain-specific AI models is enhanced.

Systems and methods for using data reference links to maintain data validation are disclosed. The method may include: initiating, via a trial server, a trial session for a user; determining, via the trial server, a validated instrument to be accessed for the trial session; transmitting, to an instrument library and via the trial session, a request for an instance of the validated instrument; receiving, from the instrument library, a data reference object that is operable as a data reference link to the validated instrument stored in the instrument library, such that the data reference object is operable to execute the validated instrument without generating a copy of the validated instrument; and causing a Graphical User Interface (GUI) of the trial session to operate the data reference object, such that a user device executes the validated instrument by reference.

The present disclosure relates to the field of data validation, in particular to the validation of access data associated with the usage of material data associated with a material by a data consumer. The disclosure relates to a method, an apparatus and a computer element for validating access data including usage rule data associated with the usage of the material data by a data consumer. The disclosure further relates to a method, an apparatus and a computer element for generating agreement data associated with the material data, a material associated with agreement data and a method, an apparatus and a computer element for providing material data associated with material(s) via a decentral network to a data consumer. The disclosure further relates to the use of the accessed material data in the production of a product using material(s) associated with the accessed material data.

This application is directed to data validation in an electronic device having a memory device. The memory device receives an inquiry for a validity condition of a page of the memory device from a memory controller that is coupled to the memory device in a memory system. In response to the inquiry, the memory device selects a subset of the page of the memory device to represent the page. The subset of the page stores a set of memory data. The memory device obtains integrity data corresponding to the set of memory data, applies a plurality of validation operations on the set of memory data and the integrity data corresponding to the set of memory data to generate a plurality of validity results. The memory device determines an error parameter of the page locally based on the plurality of validity results and provides the error parameter to the memory controller.

A method includes receiving an indication that a record has been updated and determining a confidence score. The method includes, in response to a determination that the confidence score has not met a threshold, filtering a set of communications. The method includes determining whether the record change has met one or more of a set of validity criteria. The method includes, in response to a determination that the user record change has not met the set of validity criteria, based on a first outcome of a set of reporting criteria, automatically generating a prompt with a first suggested revision of the first change. The method includes, in response to a determination that the record change has not met the set of validity criteria, based on a second outcome of the set of reporting criteria, automatically revising the first change with the first suggested revision.

A system includes memory hardware configured to store instructions and processor hardware configured to execute the instructions stored by the memory hardware. The instructions include retrieving a set of protocol data and retrieving a set of user data associated with an individual. The set of user data includes historical data and current data associated with the individual. The instructions include determining, a set of standards and comparing the set of standards and the set of user data. The instructions include, in response to a determination that the set of standards has been met, presenting an indication with a first formatting. The instructions include, in response to a determination that one or more standards of the set of standards has not been met, presenting a second indication with a second formatting.

The invention discloses a dual-mode self-adaptive earthwork calculation method and a dual-mode self-adaptive earthwork calculation system. The method comprises the following steps: acquiring land use range boundary and elevation point data; verifying data validity and calculating area and elevation standard deviation; calculating a basic threshold value based on the area and the target point density, and calculating an adaptive threshold value in combination with the elevation standard deviation, the ratio of the actual point density to the target point density and the precision coefficient; and automatically selecting a triangulation network method or a square grid method for calculation by comparing the number of effective elevation points with a self-adaptive threshold value. The triangulation network method directly utilizes all elevation points to construct a triangulation network to calculate the earthwork volume; regular grids are generated according to the square grid rule, and interpolation calculation is carried out. According to the method, the optimal calculation mode can be adaptively selected according to the area of the engineering site, the terrain complexity and the data density, the calculation efficiency and precision are considered, and the automation degree and accuracy of earthwork calculation are effectively improved.