333 results about "Data verification" patented technology

The application discloses a kind of based on transparent soil and pile-soil interface micro evolution measurement method of multi-source sensing, it is related to geotechnical engineering test field.The present application includes the following steps: constructing transparent soil model, pile body pre-embedded sensor arrangement, multi-source sensor calibration and parameter optimization, load application and multi-source data acquisition, improved DIC algorithm's pile-soil interface micro displacement calculation, pile-soil interface pore and particle density calculation, multi-source sensing data's heterogeneous fusion, pile-soil interface micro evolution characteristic quantitative inversion and visualization, test end and data verification.The present application simulates real soil environment by constructing transparent soil model, in combination with image recognition, digital image correlation, fiber-optic sensing and resistance sensor and other multi-source sensing technology, the micro deformation, stress distribution and failure evolution process of pile-soil interface in loading process are monitored and analyzed in real time with high precision, realize the high-precision, full-process, visual measurement of pile-soil interface micro evolution, improve measurement precision.

The present disclosure relates to a data verification correction method and device, medium, electronic equipment and program product, and relates to the field of data processing. The method comprises: obtaining actual energy consumption data in the process of coal mining; inputting target coal production into a data relationship model to output reference energy consumption data corresponding to the target coal production through the data relationship model; the data relationship model is a data relationship model of coal production and energy consumption data; determining whether the actual energy consumption data is an outlier according to the deviation value of the actual energy consumption data and the reference energy consumption data; in the case that the actual energy consumption data is not an outlier, determining that the actual energy consumption data is valid data; in the case that the actual energy consumption data is an outlier, replacing the actual energy consumption data with the reference energy consumption data. Through verification and correction of energy consumption data in the process of coal mining, accurate data basis can be provided for carbon emission accounting, and the accuracy of carbon emission accounting can be improved.

A data registration apparatus (200) processes original data saved in a data source and registers the processed data. A data verification apparatus (300) computes a digest value of reference combined data which is generated based on a digest value of the original data and a digest value of the processed data as a reference digest value. The data verification apparatus computes a digest value of the registered processed data as a provisional digest value, retrieves digest value saved in the data source as a provisional digest value, computes a digest value of verification combined data which is generated based on the provisional digest value of the original data and the provisional digest value of the processed data as a verification digest value, and compares the verification digest value with the reference digest value.

The application discloses a data verification system implementation method based on a block chain and zero-knowledge proof. In the data verification stage, the data use end pays the corresponding data verification fee to the on-chain smart contract according to the verification requirement, and the demand satisfaction and data real possession are verified through the interaction with the smart contract; in the data declaration stage, the data owner carries out the Merkle tree on the data and generates the characteristic zero-knowledge proof, and the on-chain verification and evidence storage of the data are completed through the interaction with the smart contract, and in the data verification stage, the data owner responds to the challenge of the data real possession, generates the existence proof of the challenge data block set and carries out the on-chain verification and evidence storage, so that the data verification can be independently executed without relying on the third-party service executable environment or the trusted hardware, the independence and safety of the data verification are ensured, and in the whole data real possession verification process, the data is always saved in the local security environment of the data owner, and the complete non-flow of the data is realized.

The application discloses a kind of emotion evaluation and intervention method and system based on multi-modal data.Through terminal synchronous acquisition voice, face, screen tremor and so on multi-modal data;Reaction mode vector is generated based on context information and data verification fusion;The composite emotional state of user is determined using emotional emergence model.At the same time, personalized emotional causal diagram is constructed and updated, and the enhanced state vector is generated by extracting key causal path features.The vector is input into the intervention agent to output intervention actions;After execution, the emotional state is evaluated again and the reward is calculated, and the system model is updated online.The application realizes accurate emotion evaluation and closed-loop adaptive intervention that strikes the root.

The present application relates to the technical field of data security, in particular to a serialization traceability data verification method based on block chain, comprising: collecting physical features of labeling and packaging equipment to generate a dynamic capture pulse entropy source, and constructing a label sequence identity coupling fingerprint containing instruction stream bias and physical state texture; combining traceability code and action time offset to perform XOR packaging to generate label sequence instantaneous credentials, and introducing historical feedback values to generate label sequence topology entropy chain through hash iteration; using distributed ledger consensus nodes to analyze the entropy chain, verifying the extracted logical feature vector and hardware base state characteristics, comparing the global state root closed loop to generate a logical anchor credential, and triggering asynchronous evidence storage accordingly. Through the deep coupling of physical entropy source and recursive topology chain, the present application realizes cross-dimensional verification of equipment identity, action timing, and physical terminal and block chain nodes, ensuring the authenticity and non-tamperability of traceability data in the generation and circulation process.

The application relates to the technical field of intelligent data analysis, in particular to a questionnaire data intelligent analysis processing system based on a large language model, which comprises a target analysis module, a dynamic coding table construction module, a coding table optimization module, an automatic coding mapping module, a verification and retry processing module and an intelligent analysis module. The core target and analysis dimension are identified by relying on a context perception algorithm, coding instructions are dynamically constructed, preliminary coding is completed in parallel in fragments, the coding structure is optimized through logical verification and semantic deduplication, and automatic coding mapping of full-quantity questionnaire data is completed. Through multiple rounds of data verification combined with an exponential backoff strategy, error data retry coding is completed, and out-of-limit abnormal data is marked, cross analysis and deep correlation analysis are carried out in combination with a preset framework. The scheme realizes adaptive adjustment of questionnaire coding and closed-loop processing of data errors, improves the standardization of questionnaire data coding, and stabilizes the operation quality of data analysis.

A system and method for implicit user authentication using data from multiple wearable devices is disclosed. Two or more wearable devices associated with a user collect physiological and activity-related data, which is transmitted to an authentication platform that computes and selects influential features for model development. The platform generates device-level and aggregated models using machine learning classifiers to verify user identity based on the collected data. If model confidence score falls below a defined threshold, an explicit authentication step is initiated. The disclosed approach enhances security and usability by enabling continuous, burden-free authentication in Internet of Things (IoT) environments.

The application provides an aircraft mass estimation method based on an intended height. Wind speed of each track point and the influence of wind on aircraft mass estimation are calculated by interpolation; the height difference between barometric height and intended height is compared with the threshold value to filter abnormal track points affecting mass estimation; a mass sequence is set, mass error under different masses is calculated, and the mass with the minimum error is taken as the estimated mass of the aircraft; a height layer sequence is set, the estimated mass of the aircraft under different height layers is calculated, data verification is performed, abnormal mass is removed, and the mean value of the normal mass is taken as the stable estimated mass of the aircraft. The application fully considers the influence of wind on aircraft mass estimation, filters track points according to intended height and height buffer time, removes abnormal track points affecting the mass result, and obtains more stable aircraft estimated mass through implementation of aircraft mass estimation at multiple height layers. The application has wide application prospects in the field of flight four-dimensional trajectory prediction.

This invention relates to an image-based configuration file embedding and recovery system for industrial vision software. The system includes a configuration data processing module, an encryption / decryption module, an image embedding module, an image output module, an image acquisition and recognition module, a configuration recovery module, a scene restoration module, and a data verification module. The core innovation lies in using images as the storage and transmission medium for configuration files. Through a composite embedding method of "customized QR code + LSB steganography," standardized and encrypted configuration data is embedded into the carrier image to generate an embedded image. This invention features high robustness, high security, and ease of operation, and can adapt to complex industrial environments, significantly improving the deployment and maintenance efficiency of industrial vision systems.

The application discloses a biomedical test strip detection data analysis method and system based on multiple algorithms. The method comprises the following steps: obtaining related data of a test paper to be detected, wherein the related data comprises T-line related data, B-line related data and C-line related data; verifying whether the lengths of three curves corresponding to the related data are consistent, if not, determining that the detection result is invalid, if yes, analyzing sample adding characteristics to determine whether there is sample adding sequence error or no sample adding; distinguishing sample types according to chromatography speed according to the related data; when the sample type is a whole blood type, calculating the length of a sample type identification point corresponding to three lines, adjusting and cutting off, and if the total length exceeds a set threshold, determining that a hemolysis phenomenon leads to an invalid detection result. The method of the application particularly focuses on processing the hemolysis phenomenon and other user operation related problems, thereby enhancing the reliability and efficiency of the overall detection system.

This invention discloses a data verification method, apparatus, and related equipment. The method includes: configuring data verification rules that support multiple data sources based on business requirements, wherein the multiple data sources include at least two data source types among file, single table, cross-table, and cross-database; acquiring the data change trend of the business data within a preset historical time period, and dynamically adjusting the data verification rules based on the data change trend using an adaptive rule engine; loading the adjusted data verification rules to perform data verification on the data to be verified, and generating data verification results.

An authorization system for data verification and approval in a communication platform is disclosed. The system includes a workflow engine comprising one or more processors and at least one storage element for storing instructions. The workflow engine maintains a client identifier associated with the communication content. A client device communicates with the workflow engine. The communication platform receives communication content generated by a computer system and encrypted by the workflow engine. The encrypted communication content is visually encoded as an authentication image and displayed within the communication platform. An electronic device also communicates with the workflow engine and includes an authentication identifier reader. The reader decrypts the client identifier from the authentication image, and the decrypted client identifier is verified by the workflow engine to authenticate the intended user. The authenticated communication content is displayed on the client device, and authorization to access the communication content is transmitted to the workflow engine.

This invention discloses a method, system, and storage medium for verifying instrument data records. Based on a received data verification command, each record in the instrument data record table is sequentially retrieved. The corresponding screen layout information is retrieved from the instrument information database according to the instrument model. Then, the display features in the screen image are identified and analyzed, and compared with the screen area shape and measurement data layout information stored in the instrument information database. If they are not similar, an instrument model entry error message is triggered. If they are similar, the identified instrument measurement parameters are compared with the recorded parameters in the data record. If they are not the same, a measurement parameter entry error message is triggered. By using screen image content to automatically verify and verify the instrument model and measurement parameters in electronic experimental records, the inefficiency and error-prone nature of existing manual verification methods are overcome.

This application relates to an IoT lock circuit based on a national cryptographic chip, comprising: a core board, a W5500 network communication module, a USB interface, a security encryption chip U7, a door status module, and a motor drive circuit; one end of the USB interface is electrically connected to the core board, and the other end of the USB interface is suitable for connecting a USB electronic key; the security encryption chip U7 is bidirectionally electrically connected to the core board; the W5500 network communication module is bidirectionally electrically connected to the core board, and the core board is suitable for communicating with the IoT lock central platform through the W5500 network communication module; the output end of the door switch module is electrically connected to the input end of the core board; the input end of the motor driver is electrically connected to the output end of the core board, and the output end of the motor drive circuit is suitable for being electrically connected to the power supply of the door lock motor; the circuit is suitable for unlocking the door lock by driving the motor drive circuit to work when a USB electronic key is inserted into the USB interface and the security encryption chip U7 verifies the data of the USB electronic key.

The application provides an RFID tag identification control method for transformer information collection, and belongs to the technical field of tag identification control, which comprises the following steps: 1, real-time detection and feature analysis of electromagnetic interference on the RFID reader for transformer information collection; 2, parameter self-adaptive adjustment of the RFID reader for transformer information collection; 3, multi-antenna collaborative identification control of the RFID reader for transformer information collection; and 4, data transmission and verification optimization of the RFID reader for transformer information collection. Through the collaborative control strategy of dynamic interference detection, self-adaptive parameter adjustment, multi-antenna collaborative identification and data verification optimization, stable, long-distance and high-success-rate identification of the RFID tag in a strong electromagnetic interference environment is realized.

The embodiment of the application provides a kind of digital certificate application verification method, signature data verification method, device and equipment, it is related to digital signature technical field.The method comprises: in response to the digital certificate application of certificate applicant, and the corresponding certificate application request data and certificate application cooperation data are acquired;Digital certificate application is carried out multiple verification operations based on certificate application request data and certificate application cooperation data;In the case where all verification operations are verified, the digital certificate is issued to certificate applicant.This embodiment of the application can realize the function of the third party password cooperation service verifiable by increasing certificate application cooperation data and other information in digital certificate application, so as to meet the needs of different private key holding mode certificate application to implement differentiated verification management.

This application proposes an offline navigation method and system for smart terminals in dense forest environments. The method includes: performing multimodal scanning of the surrounding dense forest environment to obtain first collected data, and filtering candidate features from the first collected data in conjunction with environmental sensor data; determining the target guidance area and collection mode based on the candidate features, and adjusting the collection parameters of the data collection module according to the collection mode; guiding multimodal scanning to obtain second collected data, verifying the candidate features based on the second collected data, and obtaining effective features; deriving the relative orientation based on the effective features, and outputting the navigation result in conjunction with the local offline map. This application relies on the hardware characteristics of smart terminals to construct a dedicated offline navigation logic for dense forests. By mining the natural features commonly found in dense forest environments as the core basis for navigation, and combining multimodal collection with environmental adaptation optimization, it achieves high-precision, high-stability, and long-endurance offline navigation in dense forest environments.

The present invention provides a management system in which a client b who uses manufactured biochar joins a project operated by an administrator a, and the administrator a makes an application to a certification authority d for a credit relating to the biochar used by the client b, and manages the certified credit. A biochar production system including a biochar production device purchased or leased by the client b or the administrator a includes various measuring instruments for measuring biochar production-related data, and a CPU capable of communicating with the various measuring instruments, and a server A of the administrator a can acquire the biochar production-related data during biochar production from the various measuring instruments via the CPU. A device B of the client b transmits a biochar usage amount to the server A, the server A transmits credit exchange application data created on the basis of the biochar usage amount and the biochar production-related data to a device D, and the device D certifies the credit on the basis of the credit exchange application data and transmits the credit to the server A.

This invention discloses a computing power multiplication pre-storage system, method, and embedded device, belonging to the field of computing architecture and data reuse technology. Addressing the problems of redundant repetitive computation, conflict risks and irreparable damage in data integrity verification, and inefficient request-response modes in existing technologies, this invention proposes a closed-loop "pre-storage-reuse-verification" system. The system includes: a hotspot identification and adaptive pre-storage module, used to identify high-frequency computing tasks, dynamically adjust the pre-storage range, and automatically eliminate low-frequency data, achieving self-evolution and convergence of the data set; a multi-level trusted caching module, adopting a layered storage architecture to achieve layered management of data value, and possessing automatic backfilling between layers, periodic consistency verification, and automatic repair mechanisms; a mathematically based integrity verification module, configuring corresponding differential or recursive verification logic for a wide range of computing tasks, from basic data types and various mathematical functions to operational operators, providing a zero-conflict, reversible, and repairable lightweight data verification and restoration method; and an asynchronous push processing engine, which immediately returns after receiving a request, submitting the computing task to a background lock-free queue for batch processing, achieving decoupling between computation and requests. This invention pioneers the deep integration of differential verification and computation acceleration, reconstructing the traditional "request-computation-response" logic into a "pre-store-query-retrieve" push-pull interaction logic. By reusing repeated calculations through module collaboration, it not only significantly reduces computation latency, but more importantly, it improves the effective utilization of computing power, greatly saves hardware resources and energy consumption, and ensures data credibility and integrity. It is applicable to fields such as artificial intelligence, scientific computing, engineering simulation, financial technology, and video processing.

The application discloses a data integrity multiple verification method and system of a double-channel safety control system, relates to the technical field of data verification of safety control systems, and comprises the following steps: performing inboard double-channel cross voting on input signals obtained by double channels of a board card, performing one cycle redundancy check on voting result data, and performing cycle redundancy check code packaging based on a communication protocol to obtain a protocol data packet containing double cycle redundancy check codes; performing secondary cycle redundancy check based on the double cycle redundancy check codes after analyzing the protocol data packet in a main control board to obtain effective data; performing cross check and voting on the effective data of double channels of the main control board to generate a channel local voting result; performing board card level check on the channel local voting result and then performing global check, judging global data consistency based on a global check code, and identifying system faults. The application improves the comprehensiveness and effectiveness of data check, and solves the problem that single point faults or data errors cannot be avoided.

The network threat knowledge graph construction method and related equipment provided by the embodiments of the present application comprise: obtaining report image data and report text data from a same network attack report, and respectively performing classification mapping on the report image data and the report text data based on a threat intelligence type set to obtain image categories and text categories; performing content extraction on the report image data based on the image categories to obtain image entity relationship data, and performing content extraction on the report text data based on the text categories to obtain text entity relationship data; performing alignment verification on the image entity relationship data and the text entity relationship data belonging to a same network threat type to obtain an alignment verification result; when there is a difference between the image and text data in a representation entity data verification group, performing multi-dimensional conflict processing to obtain target entity relationship data, and constructing a network threat knowledge graph, thereby effectively improving the data accuracy of network threat knowledge graph construction.

The application discloses a power consumption data verification and repair method and device, equipment and medium, which are applied to a power data processing system, and relate to the field of smart power grids. The method comprises the following steps: receiving user power consumption data of a target user collected by a preset collection terminal, and predicting the power consumption data of the target user by using a target power consumption prediction model; determining a current target power consumption dynamic threshold based on obtained target predicted power consumption data and historical power consumption data of the target user, and determining whether a target difference between the user power consumption data and the target predicted power consumption data is greater than the target power consumption dynamic threshold; if the target difference is greater than the target power consumption dynamic threshold, performing abnormal analysis on the user power consumption data to determine an abnormal type of the user power consumption data, and performing corresponding abnormal alarm based on the abnormal type; and performing data repair on the user power consumption data based on the abnormal type to obtain repaired user power consumption data. Therefore, automatic abnormal identification and repair of power data can be realized.

This invention discloses a dynamic payroll calculation method and system for the entire business chain based on AI rule adaptation. The invention acquires end-to-end data through a bidirectional linkage data acquisition module and performs reverse integrity checks; it uses a feature extraction model to categorize orders into existing scenarios or cluster new scenarios; it establishes a scenario-rule association through an AI rule adaptation engine, autonomously matching scenario-based payroll calculation sub-rules; after fingerprint and logical cross-verification by multi-source heterogeneous modules, the AI ​​engine performs dynamic payroll calculation; for results exceeding abnormal thresholds, it initiates reverse backtracking self-correction or hierarchical early warning, and completes autonomous rule iteration. This invention breaks through the static and fixed payroll calculation framework, achieving intelligent adaptation to business scenarios, automatic cross-domain data verification, and closed-loop self-correction throughout the entire process, significantly improving payroll calculation accuracy and automation.

The present application relates to the technical field of remote sensing information extraction and snow monitoring, and particularly relates to a sub-pixel snow mapping method based on medium-resolution remote sensing data, comprising the following steps: obtaining medium-resolution remote sensing images, a digital elevation model, and ground meteorological station snow observation data, and preprocessing the remote sensing images to obtain surface reflectivity; identifying cloud-covered pixels, filling in the cloud-free dataset by temporal and spatial interpolation and ground object spectral similarity matching; selecting snow, vegetation, and water as spectral endmembers and extracting features; constructing a linear mixing model, and using the least square method to retrieve the snow proportion in the pixel to obtain preliminary data; and generating a high temporal and spatial accuracy snow distribution map through meteorological station data verification, digital elevation model terrain correction, and model parameter optimization, which solves the problems of mixed pixels, cloud coverage, terrain errors, and the lack of accuracy verification.

This specification discloses a method for air-to-ground transmission of flight record data with high temporal integrity, comprising: encapsulating target data to obtain a data assembly containing a header information portion, a data content portion, and a tail information portion; enabling the ground subject to perform data verification operations based on the header information portion and / or the tail information portion after receiving the data assembly; comprising: decomposing the target data into data packets; calculating the feature value of any data packet and determining the flag bit of the data packet for each data packet; setting the header information portion of the first data packet to preset information for the first data packet; using the feature value and flag bit of the previous data packet as the header information portion for any non-first data packet; generating a check code corresponding to the combination of the header information portion and the data content portion as the tail information portion; and forming a data assembly containing the header information portion, the data content portion, and the tail information portion.