171 results about "Quality check" patented technology

A method for quality inspection of an etching paste material based on a spectral response difference, including: identifying a position of density mutation boundary through spectral collection and density gradient analysis. Applying a specific frequency beam to obtain the resonance response parameter, generating stress field reconstruction data. Performing a reverse optical tracking to obtain a defect formation path, generating degradation prediction data. Establishing a self-organizing optical monitoring grid, to form a hierarchical spectral fingerprint library. Constructing a multi-point linked defect blocking network, to form an interconnected optical energy field. Monitoring a cooperative response to obtain network stability data, Identifying abnormal position coordinates based on a material quality grade and the network stability data, obtaining the abnormal position coordinates. Performing a phase adjustment to obtain a phase difference spectral set, conducting a phase comparison marking on the abnormal position coordinates, completing the quality inspection of the etching paste material.

The invention provides a data weaving platform-oriented self-service data preparation method, which comprises the following steps of: accessing original data and associated structured metadata of a target data source into a data weaving platform to generate standardized accessed original data and associated structured metadata; based on a semantic model of the data weaving platform, performing classified semantic annotation on the associated structured metadata, and positioning a transfer node of the associated structured metadata to generate a data blood relationship record; performing bidirectional quality verification on the data consanguinity record according to semantics and path continuity, and matching with a federated governance rule of a data weaving platform to generate a metadata governance list; and generating a unified metadata directory based on the metadata governance list, so that a user of the data knitting platform can obtain key segments containing complete data consanguinity records. According to the method, the problem of insufficient accuracy and efficiency in self-service data preparation can be effectively relieved, and the efficient preparation requirement of a data weaving platform for multi-source data is met.

The invention provides a 10kV cable accessory manufacturing quality inspection report generation method and system, and relates to the technical field of power equipment quality detection and reliability evidence storage. According to the method, original detection data is acquired and structured in multiple dimensions, and data sources, operators and equipment identifiers are bound, so that context integrity and traceability are realized; initial and enhanced data fingerprints are generated through block classification, standardization and Hash operation, and a dynamic fingerprint chain is constructed by using a chain structure, so that whole-course data has content and process dual integrity identifiers; a multi-level verification sequence is embedded in each stage of report generation, finally, a block chain is utilized to record a data packet abstract, an anchor point on the chain is bound with report metadata, a transaction ID is embedded into a report document, and a checking two-dimensional code is generated. According to the method, the non-tampering performance and the verifiability of the content and the generation process of the detection report and the traceability of the whole circulation process are improved.

The invention discloses a medical review and publication quality control system based on deep learning and medical knowledge, and relates to the technical field of medical information processing, and the system comprises a medical knowledge enhancement module which is used for carrying out the named entity recognition and relation extraction technology based on a multi-source fusion medical knowledge system, constructing a structured medical knowledge graph and carrying out intensive training; the multi-dimensional examination and analysis module is used for performing multi-dimensional evaluation on the manuscript based on the medical knowledge graph; the intelligent interaction and feedback module is used for displaying the evaluation result of each dimension through a visual interface; and the publishing quality management and control module is used for sequentially executing whole-process publishing supervision of standardized monitoring, quality inspection and abnormal intervention on the manuscripts passing the examination and analysis. The manuscript reviewing efficiency is greatly improved, and the requirements of high-frequency and rapid publishing of medical scientific research are met; the problem of review difference caused by subjective factors of a manuscript reviewer is solved, and the stability and reliability of the assessment result of the same manuscript are ensured through a standardized and quantitative assessment system.

The invention relates to the technical field of power system state monitoring and operation and maintenance, and discloses a power distribution network equipment state intelligent sensing and predictive maintenance decision-making method, system, equipment and medium, and the method comprises the steps: collecting equipment operation data, monitoring data and environment data through a power distribution automation system, an online monitoring device, an environment sensor and other channels; performing time synchronization and quality verification on the multi-source data; extracting multi-dimensional characteristic parameters reflecting the running state of the equipment, and performing normalization processing and fusion analysis on the characteristics; establishing an equipment state evaluation model by using a deep learning algorithm, and carrying out quantitative scoring on the current health condition of the equipment; constructing a time sequence prediction model, and predicting the future degradation trend and residual life of the equipment; and establishing a multi-objective optimization model, and generating an optimal maintenance decision scheme. The whole process is from data acquisition, state perception and fault prediction to decision optimization, and intelligent management of power distribution network equipment is realized.

The invention discloses a high-speed rail canopy steel structure corrosion image recognition and evaluation method based on deep learning, and the method comprises the following steps: obtaining and calibrating a multi-view image, and organizing the multi-view image into an observation sequence; performing normalization and quality checking on the observation sequence, and extracting a state vector and an observation driving vector; constructing an energy function and a structure matrix in the Hamiltonian neural network, and promoting state vector time evolution to obtain an evolved corrosion state vector; inputting the evolution result into a decoder, generating a pixel-level corrosion mask and a boundary position, and obtaining a corrosion segmentation result; the corrosion type is judged based on the segmentation result, and corrosion severity indexes are calculated and graded; and extrapolating and predicting the severity index by using time evolution, outputting a predicted maintenance time window and priority, and finally generating a detection report. According to the method, the Hamiltonian neural network is introduced to realize identification, grading and evolution prediction of steel structure corrosion, and the detection stability and the engineering availability are improved.

The embodiment of the invention discloses an image auditing method and device based on a co-creation annotation mode, equipment and a medium. A specific embodiment of the method comprises the following steps: acquiring medical film and television data as initial data; preprocessing the initial data to obtain a task image set; distributing the task image set to at least one student terminal; in response to the detected annotation information sent by the student terminal, generating annotation feedback information according to the annotation information; sending the labeled feedback information to the student terminal; in response to the received annotation task image submitted by the student terminal, performing preliminary quality inspection on the annotation task image; sending the preliminary quality inspection result to an expert end; and in response to received auditing information corresponding to the preliminary quality inspection result sent by the expert terminal, sending the auditing information to the student terminal. According to the embodiment, a co-creation annotation mode is combined with a deep learning technology, so that efficient, accurate and high-quality image annotation auditing is realized, and the overall quality of annotation data is improved.

The invention relates to an intelligent risk monitoring and management and control method, and belongs to the technical field of intelligent risk monitoring and management and control. At present, problems such as operation jitter and safety risk are easy to occur. The method comprises the steps of performing cleaning, alignment and quality verification on operation data, equipment data and environment information under a unified time reference to form three types of read-only inputs of an equipment portrait, an environment portrait and a primary topology snapshot; performing abnormal preliminary screening based on internal and external bistable baselines, performing open set identification and rejection on samples crossing a robust band, performing modal consistency check on multi-modal evidence, outputting interval confidence, and generating a structured candidate event record; the method comprises the following steps: performing hierarchical disposal judgment by combining node topology criticality and disposal cooperative sensitivity, performing radial threshold and angle gating mapping on the node topology criticality and the disposal cooperative sensitivity in a polar coordinate domain to obtain a disposal level, and inhibiting jitter of a critical interval through asymmetric hysteresis and minimum residence time. And the accuracy of exception identification, the robustness of decision processing and the security of system operation are effectively improved.

Systems and methods for verifying the quality of patient specific implants are disclosed. A system can generate implant data, such as design files or fabrication instructions, for manufacturing the implant. The system can manage access to the implant data based on authentication levels. Based on the determined authentication level of the user requesting access to the implant data, the system can permit the user to access some or all of the implant data. The system can perform a quality check on a manufactured implant by scanning the manufactured implant to identify any errors in the manufactured implant.

The invention discloses a low-altitude field multi-source heterogeneous data unified conversion method and system based on Beidou grid codes, and relates to the technical field of data processing.The method comprises the steps that a constructed multi-source heterogeneous data set is analyzed, and key information is extracted; on the basis of Beidou grid codes, coding precision is dynamically adjusted according to data types, and time-space stamps of the analyzed data are converted into unified Beidou grid time-space coordinates; establishing a mapping relationship between the multi-source heterogeneous data set and a preset uniform data format, and converting the aligned data into data conforming to the uniform data format according to the mapping relationship; and performing quality verification on the converted data conforming to the unified data format to obtain high-quality data conforming to the unified data format, and performing associated storage on the high-quality data and the corresponding Beidou grid codes. According to the method, a data barrier can be broken, efficient fusion and accurate expression of data under a unified framework are realized, and high-quality data support is provided for intelligent management and decision-making in the low-altitude field.

The invention belongs to the technical field of forest seedling traceability, and discloses a forest seedling traceability system and method.The system supports storage and association of unstructured data such as pictures, videos and PDF (such as quarantine evidences), and specifically comprises seedling process evidences: 'archive management 'upload seedling process pictures, quarantine proof upload'quarantine certificate' pictures or PDF files; all the files can correspond to the items to form a traceability file of characters and images; quality inspection certificates: seedling outplanting, supporting self-inspection code calling, automatically extracting key information (such as a quarantine permit number and a qualified rate), and avoiding manual input errors; the problem tracing basis is as follows: if the seedlings have quality problems (such as low survival rate after afforestation, incorrect variety and no result), related archives such as seed / scion sources, seedling culture management, field management, self-checking records and the like can be retrieved through a system, and responsibility links, such as impure camellia oleifera scion variety, too late grafting time and the like, can be quickly positioned.

A method of calibrating an imaging device adapted to characterize a feature of a sample container, such as a cap color or cap type. The method includes providing a calibration tube including an imaging surface at an imaging location of a first imaging apparatus; illuminating the imaging surface with light emitted from multiple front light sources; adjusting a drive current to each of the multiple front light sources to establish a substantially uniform intensity of the imaging surface; recording drive current values for the multiple front light sources; replacing the calibration tube with a calibration tool having a calibration surface of a known reflectance; and measuring target intensity values of the calibration tool at the respective drive current values. Calibration tools, imaging apparatus, quality check modules, and health check methods are provided, as are other aspects.

The invention discloses a multi-modal reasoning algorithm based on bidirectional chain type thinking enhancement. The method comprises the following steps: firstly, performing bidirectional thinking chain generation and quality verification on original multi-modal question and answer data, constructing a multi-modal thinking chain data set (MCD), and providing standardized reasoning process data for a model; secondly, three types of annotation labels of knowledge types, question types and reasoning types are added on the basis of the MCD, and a knowledge-enhanced multi-modal thinking chain dataset (KMD) is obtained and used for model supervision fine tuning (SFT) to constrain model reasoning; and finally, generating multiple candidate outputs by using KMCD in combination with the structured cue word, and obtaining a strong model with complex reasoning ability through reinforcement learning training of two-dimensional adaptive reward strategy optimization (Di-GRPO). According to the method, the problems of low data quality and insufficient training focusing of the existing multi-modal reasoning task thinking chain are effectively relieved, and the reliability and the accuracy of multi-modal reasoning are improved.

Techniques of automated quality control for digital pathology whole slide images are presented. The techniques include obtaining a thumbnail image derived from a whole slide image of a pathology slide; determining whether the whole slide image includes an artifact in a first class of artifacts by providing the thumbnail image to an electronic neural network trained to detect artifacts in the first class of artifacts by analyzing a plurality of labeled training thumbnail images; generating a tissue mask representing tissue depicted in the thumbnail image; determining whether the whole slide image includes an artifact in a second class of artifacts by performing a comparison using the tissue mask; and providing an indication of whether the whole slide image includes an artifact in the first class of artifacts or an artifact in the second class of artifacts.

The present invention relates to a method for operating a project distributed development framework service by using a computer system having a server computer, the method comprising the steps of: (a) receiving new project generation information from a project owner terminal and transmitting the new project generation information to a planning partner terminal; (b) receiving planning document information created according to the new project generation information from the planning partner terminal and transmitting the planning document information to an engineering design partner terminal; (c) receiving engineering design document information created according to the planning document information from the engineering design partner terminal and transmitting the engineering design document information to an API development partner terminal; (d) receiving API development information created according to the engineering design document information from the API development partner terminal and transmitting the API development information to a quality inspection partner terminal; and (e) receiving inspection result information of the API development information from the quality inspection partner terminal and transmitting the inspection result information to the project owner terminal or an operator terminal.

A system and method for authenticating an image is given. The method encompasses capturing a first image comprising at least one first human object and a second ID image; detecting at least one face of one first human object and processing the first human object based on face attribute checks, face quality checks, and face manipulation checks; performing a liveness check of the identification document to crop and align the region of interest; detecting a face of the at least one second human object; performing ID quality checks and ID tampering checks on the region of interest of the identification document; determining the image face feature vector and an ID card face feature vector; determining a match score between the image face feature vector and the ID card face feature vector and a status indicating one of authentication success, authentication failure, or a requirement for manual review of the image.

The embodiment of the invention provides a power grid asset quality management method based on a data center, and belongs to the technical field of power grid data processing. The management method comprises the steps that metadata information of various power grid assets is acquired to form an asset metadata information base, and the metadata information comprises all attribute information in the whole life process of the assets and all attribute information concerned by a business department; constructing an asset quality verification rule base according to the asset meta-database and the business characteristics; carding a source end service system involved in power grid assets, and completing source end data access based on a data intermediate station; calling the asset quality verification rule base, verifying source end data, and judging data which does not accord with the rule as suspected abnormal data so as to form a suspected abnormal data annotation information base; annotating annotation information in an information base according to the suspected abnormal data. According to the management method, a rule base about power grid knowledge can be constructed so as to realize management of power grid assets.

The invention relates to a data quality checking method and device based on graph embedding, and belongs to the technical field of computers.The method comprises the steps that service data nodes and service domain nodes are input into a graph embedding module to obtain service data node vectors and service domain node vectors respectively; inputting the business data node vector and the business domain node vector into a feature conversion module, performing feature extraction, and then outputting an updated business data node vector and an updated business domain node vector; and constructing an edge vector of the updated service data node vector and the service domain node vector through a node aggregation module, performing feature extraction and prediction based on the edge vector, outputting a prediction score of an edge existing in the service data node and the service domain node, and determining a check result of the service data according to the prediction score. According to the method and the device, the automatic quality check of the irregularly input data is realized, the labor cost is saved, and the accuracy and the credibility of the data quality check are improved.

A method of characterizing a specimen to be analyzed in an automated diagnostic analysis system provides a segmentation determination and / or an HILN (hemolysis, icterus, lipemia, normal) determination of the specimen while providing characterization training updates based on the accuracy and / or confidence in the determinations. The method includes identifying an incorrect or low confidence segmentation or HILN determination, forwarding the incorrect or low confidence determination from the HILN network to a database, and providing one or more training images to the HILN network based on the incorrect or low confidence determination. Quality check modules and systems configured to carry out the method are also described, as are other aspects.

This invention discloses a photovoltaic module production quality monitoring system based on digital twins, belonging to the technical field of production quality monitoring systems. The system includes a dynamic monitoring interval division module for generating dynamic monitoring time intervals; a multi-source data fusion module for collecting equipment operation data and quality inspection data from each process stage within the dynamic monitoring time interval to generate fused data; a digital twin virtual mapping module for constructing a virtual model of the photovoltaic production line based on the fused data and outputting virtual mapping relationships; an intelligent quality control module for generating equipment control commands based on the virtual mapping relationships; a physical equipment execution module for executing equipment control commands and outputting equipment operating parameters; and a real-time feedback module for collecting equipment operating parameters and feeding them back to the dynamic monitoring interval division module. This invention solves the problems of transient feature dilution and insufficient sampling caused by traditional fixed time intervals by generating monitoring time intervals.

The application discloses a kind of based on artificial intelligence technology's commercial cipher evaluation report automatic generation and quality control system, including multimodal data processing and knowledge graph construction module, based on the multimodal data related to commercial cipher evaluation field, constructs the knowledge graph of cipher evaluation field;Domain large model fine-tuning module is used to construct the instruction fine-tuning dataset of cipher evaluation field, and adopts mixed fine-tuning strategy to carry out field adaptation training to pre-training large language model, generates cipher evaluation field expert large model;Report automatic generation module is based on knowledge graph and expert large model, and automatically generates commercial cipher evaluation report;Quality control module is used to carry out automatic quality check and evaluation to report;System integration and optimization module is used to integrate the above module into an interactive application system, and continuously optimize knowledge graph and expert large model.The application can automatically generate commercial cipher evaluation report and guarantee the correctness and logical consistency of report.

This invention provides a method and system for remote meter reading and water usage information management for smart water meters. The method mainly includes: receiving raw data frames containing information such as cumulative flow values ​​and collection timestamps, and performing multi-dimensional quality checks to generate collection status identifiers; dividing the water usage interval into valid collection intervals and pending confirmation intervals based on the identifiers; calculating the measured water usage in the valid intervals and extracting abnormal features to generate initial abnormal events; generating a completion sequence for the pending confirmation intervals based on boundary flow values, historical water usage characteristics, and regional balance constraints; determining a supplementary reading control strategy and issuing supplementary reading instructions based on the completion sequence and other information; performing secondary verification of the initial abnormal events based on the supplementary data, and outputting the final abnormal result and meter reading data. This method improves the accuracy of water usage anomaly detection and the reliability of meter reading data through data quality grading, interval hierarchical management, and closed-loop verification of abnormal events.

The invention discloses a construction scene-oriented BIM (Building Information Modeling) twinborn model data center construction method based on multi-dimensional BOM (Bill of Material) adaptation, which comprises the following steps of: carrying out data structured definition on a design BOM, a space BOM and a construction BOM to generate standardized multi-dimensional BOM data; uploading, analyzing and storing the BIM model, and carrying out quality verification on components of the BIM model; a mapping rule between the multi-dimensional BOM data and the BIM model component is configured, automatic hooking of the BOM data and the BIM model component is executed according to the mapping rule, and an incidence relation is established; and constructing a twin model based on the hung BIM model and the multi-dimensional BOM data, and carrying out middleware management on the twin model and associated data thereof so as to support data interaction with an external business system. The problems that in the prior art, adaptation of multi-dimensional BOM data and a BIM model is difficult, data islands are serious, and the data requirement of a construction service application scene cannot be met are solved.

A system for measurement quality verification may form part of an installation located at a site that manufactures rubber mixtures. The system may include a weighing platform having a scale for determining a weight loss of the metered raw materials, a metering device having a metering hopper that receives the raw materials required for performing one or more rubber mixing processes and a metering device that meters the raw materials into the metering hopper in real time, an application and removal system that allows for application and removal of one or more calibration weights relative to the weighing platform, and a motion system that facilitates reciprocating vertical movement of the metering device. An installation may incorporate the above system, and a continuous metering process may be performed by the installation.

The invention provides an intelligent official document checking system and method based on AI drive, a storage medium and electronic equipment, and the system comprises a data layer which is used for collecting, storing and preprocessing official document data, and the official document data comprises various standard official document templates, historical official document data and official document processing standard files; the algorithm layer is integrated with a natural language processing module, a machine learning module, a knowledge graph module and a deep learning module and is used for identifying, analyzing and judging official document data; the application layer is used for constructing a format specification checking module, a content quality checking module and a sensitive information screening module based on the algorithm layer; and the interaction layer is used for interacting with a user, receiving an official document uploaded by the user and outputting a verification result to the user. The system provided by the invention can improve the administrative efficiency, improve the document quality, reduce the administrative cost and guarantee the information security.

Provided in the present application are a quality checking and correction method and apparatus for static data of autonomous driving. The method comprises: acquiring pre-annotated data and data collected by a sensor; and on the basis of the data collected by the sensor, performing quality checking and correction on N quality checking dimensions of the pre-annotated data, wherein the N quality checking dimensions comprise the n-th quality checking dimension and the (n+1)-th quality checking dimension, a quality checking and correction result of the n-th quality checking dimension is an input of the (n+1)-th quality checking dimension, N>1 and N is an integer, and 1≤n<N and n is an integer. The present application helps to reduce the false alarm rate of errors when performing quality checking on annotated data, and also helps to improve the effectiveness of correcting pre-annotated data.

The invention relates to a full-automatic code programming method and system based on a large model. The full-automatic code programming method comprises the steps that 1, multi-modal requirements are collected, analyzed and expressed in a standardized mode; 2, automatically arranging a development environment; step 3, code candidate generation and quality inspection; 4, compiling / constructing and automatically executing; 5, performing structured evaluation and success judgment; 6, closed-loop error correction and self-optimization control are carried out; and 7, safety and compliance control. The method supports fusion analysis of texts, voices, images and videos, and automatically extracts program specifications and acceptance criteria. According to the method, automatic generation, compiling, execution, evaluation and error correction are achieved, and manual log interpretation and prompt word rewriting are not needed.

This application discloses a data generation method, apparatus, storage medium, and device based on a simulated search environment, relating to the field of communication technology. Its main purpose is to address the problem of poor data validity during the training of existing search environment models. The method includes: acquiring the task content of the data generation task and determining the task type based on the search complexity of the task content; the task type includes extended and refined types; processing the task content based on the task type to obtain multiple candidate tasks, and performing quality checks on the candidate tasks based on a first intelligent agent; if the quality check is passed, then solving the candidate tasks in a simulated search environment multiple times based on a second intelligent agent to generate a solution trajectory, and evaluating the solution trajectory based on a third intelligent agent; the simulated search environment includes a simulated web search environment and a simulated web browsing environment; if the evaluation result matches preset task constraints, generating the target data for the data generation task.

The application provides a data asset quality detection method and device, the method comprising: obtaining a to-be-detected data asset list; extracting keywords from the to-be-detected data asset list to construct a keyword corpus; labeling the keywords in the keyword corpus based on a preset self-defined word library to construct a detection feature keyword library; mapping the detection feature keyword library and the to-be-detected data asset list according to the labeled feature types to generate a feature list of each data asset; and respectively detecting the quality of each data asset feature list based on a preset detection rule list corresponding to each feature type to generate a quality detection result. According to the labeled features as the index of the selected detection rules, when the data quality is detected, the appropriate detection rules can be quickly matched, thereby reducing a large amount of repeated work and improving the work efficiency of data quality detection.

The present application relates to the field of otology disease prediction, and particularly relates to an otology disease prediction method based on multi-modal data fusion and confidence evaluation. The technical scheme comprises: collecting an ear endoscope digital image, wideband tympanometry measurement data, and structured or unstructured clinical information; performing integrity check and quality check on the collected data, checking whether the ear endoscope digital image resolution meets the minimum pixel requirement and whether the information is complete; then performing otology data preprocessing and multi-modal feature extraction, extracting an ear endoscope digital image feature vector, a feature vector representing wideband tympanometry data, and a clinical information feature vector; after feature extraction, fusion is performed, and after fusion, confidence evaluation and recurrence risk prediction are performed. The present application significantly improves the accuracy of otology disease prediction by deeply fusing image, physiological signal and clinical text three modal data through an attention mechanism. The present application is suitable for otology disease prediction.