38results about How to "Automate analysis" patented technology

The invention discloses an automatic test method based on natural language processing, which comprises the following steps: S1, generating a test case: performing semantic analysis on a software requirement document or a test requirement by utilizing a natural language processing technology, extracting key information, and combining the extracted test information and a preset test case template to generate a test case; a preliminary test case is automatically generated; the key information comprises a test purpose, an operation step and an expected result; s2, analyzing the test case; s3, generating a test script; s4, executing the test script; and S5, analyzing a test result. According to the automatic test method based on natural language processing, the test requirements described by the natural language can be automatically analyzed, the test case is generated, the test is automatically executed, and the test report is finally generated, so that the software test efficiency is improved, the workload of manually compiling and executing the test case is reduced, and the test efficiency is improved. And the coverage rate and the accuracy of the test are improved, more software defects can be found, and the quality of software products is guaranteed.

The invention relates to the technical field of big data, in particular to an intelligent service association method based on data consanguinity, which comprises the following steps of: 1, acquiring and forming metadata; tracking and collecting a service activity link to obtain a data consanguinity and a metadata consanguinity; 2, generating a business log; step 3, collecting a business log, and establishing a business atlas based on metadata consanguinity; step 4, defining a service triggering rule, a service decision point and a response rule based on the service atlas; and 5, monitoring the data change in real time, mapping the data change into the associated service map according to a service triggering rule, and carrying out service early warning prompt or associated information change display. According to the invention, automatic tracking and intelligent management of the project business process can be realized, and the utilization rate of enterprise data and the enterprise management efficiency are improved.

The invention belongs to the technical field of detection of defects in small holes, and discloses a method and a system for detecting the quality of a perforated workpiece. The detection method comprises the steps that laser penetrates through a small hole of a workpiece to be detected to form a diffraction image, and the diffraction image is a multi-layer circular bright ring; projecting the diffraction image to an imaging unit; the imaging unit transmits the diffraction image to the processing unit; the processing unit extracts a hot spot central region of the diffraction image, performs polar coordinate system transformation on the original diffraction image according to sub-pixel points of the hot spot central region to obtain a horizontal stripe image, and extracts center line sub-pixel coordinates of the horizontal stripe image; the extracted center line sub-pixel coordinates are converted back to original Cartesian image coordinates to obtain the trajectory center line of each layer of circular ring, and the actual circle center, the actual roundness and the actual diameter of the circular ring are calculated according to the trajectory center line of each layer of circular ring; and the analysis unit analyzes the actual circle center, the actual roundness and the actual diameter to obtain defect information of the workpiece to be detected. According to the invention, tiny defects can be efficiently and accurately detected.

The invention relates to the field of safety supervision, in particular to a food safety supervision system based on a cloud platform, and the system comprises a collection module which collects a contour diagram of a package and a morphological diagram of target food; the fitting degree analysis module is used for determining the contour coincidence degree and the edge distance according to the contour map and the form map, and determining whether the fitting degree of the target food and the package is qualified or not based on the contour coincidence degree and the edge distance; the shake risk analysis module is used for detecting the package with qualified fitting degree to obtain the deformation degree and the distribution condition of the package folds in the transportation process so as to determine whether the shake risk is qualified or not; the packaging material evaluation module is used for carrying out migration test on the package with the qualified shaking risk so as to evaluate the material safety of the package according to the migration condition of substances in the packaging material to the food; and the safety determination module determines that the target food in the package is safe food according to the fitting degree, the shaking risk and the material safety. And comprehensive guarantee is provided for food safety.

The invention relates to the field of automatic control, in particular to a self-adaption-based large casting multi-robot cooperative spraying control method, which comprises the following steps of: acquiring relevant data information of a casting and a spraying process, and establishing a spraying task analysis model; after the multiple robots finish preliminary spraying of the casting, the spraying effect is analyzed and evaluated through all the parameters, obtained through an intelligent sensor, of the sprayed casting, and a spraying effect evaluation neural network model is established; the surface curvature of the casting is combined, and a spraying speed correction parameter is calculated; the spraying speed correction parameter is compared with a preset spraying speed correction parameter, and the spraying speed is adjusted according to a comparison result; according to the obtained nozzle size, the paint viscosity and the adjusted or optimized spraying speed, spraying liquid flow regulation and control parameters are calculated, and the spraying liquid flow is regulated and controlled; and monitoring is carried out according to the regulated spraying speed and the fluctuation condition of the spraying liquid flow, so that the stability of the spraying quality is judged, and the multi-robot spraying process of the large casting is adjusted.

The invention discloses an immunoblotting data classification system based on feature engineering, relates to the technical field of data processing, and solves the problem that whether a protein band exists in an original immunoblotting image is difficult to identify; secondly, feature parameters of an original immunoblotting image and immunoblotting data are difficult to extract; secondly, a feature matrix is difficult to generate according to the feature parameters, and data classification is difficult to carry out after feature subsets are screened out according to a selection algorithm; and finally, the characteristic parameters in the characteristic subsets are difficult to comprehensively analyze. The system comprises the following modules: a data acquisition module, a data processing module, a feature extraction module, a feature processing module, a data classification module and a data analysis module. Through feature engineering and a classification model, classification of immune data is realized.

The present invention belongs to the field of computer technology, and provides an AIOps-based fault automatic recovery method and system. The method includes: extracting log templates and log parameters from received unstructured original log files, where log parameters are a set of variable values ​​when the program is running, and when extracting the log template, parsing the log entries in the original log file based on a dynamic analysis tree with a fixed depth to obtain the log template; detecting the obtained log template and log parameters, and during the detection, judging whether the log sequence of the log template is abnormal based on an LSTM network, and detecting the log parameters based on a parameter outlier algorithm and a parameter value first-order difference outlier algorithm to identify abnormal log parameters; based on a pre-created expert library, finding matching items corresponding to abnormal log templates and log parameters, and recovering the fault based on the matching item strategy; therefore, the present invention can solve the problem that it is difficult to automatically detect system anomalies through a large number of logs.

The invention discloses a real vehicle automatic test technology method and application, and the method comprises the following steps: use case analysis, automatic script configuration, test data configuration, test data configuration, use case association script, test task, test task execution and test report. According to the system, automatic testing of a cloud diagnosis RDS software program is carried out on a real vehicle, main application function testing is carried out, and comprehensive testing of the vehicle RDS software function is achieved by compiling an automatic testing script, configuring a testing environment and carrying out automatic control and data acquisition on the real vehicle, and the system has the advantages of being high in integration and intellectualization. According to the invention, automatic analysis and processing of management of test data and scripts can be realized, convenient test services are provided for testers, the efficiency and accuracy of real vehicle test can be greatly improved, the test cost is reduced, and a powerful guarantee is provided for smooth promotion of cloud diagnosis projects in the automobile industry.

The application discloses a simulation result optimization method and application in chip verification and relates to the technical field of chip development.The method comprises the following steps: starting simulation on a to-be-tested chip to generate a simulation file;forming a signal line group by grabbing the signal lines of relevant signals in the simulation file based on a specified RTL layer;packing the signal values in the signal line group to form a data packet, extracting a key data packet from the data packet, comparing the values of the signal lines in the key data packet with expected values, and / or comparing the combined logic among the multiple signal lines in the key data packet with expected signal line combined logic;and generating a key data verification result text file according to the comparison result.The application realizes automatic analysis and checking of the simulation result of the required signal within a set range, improves the simulation result checking efficiency, and reduces the labor and computing resource cost of simulation debugging.

The invention relates to the technical field of medical literature data processing and artificial intelligence, and discloses a random contrast test (RCT) bias risk automatic evaluation method and system, and the method comprises the steps: obtaining RCT literature data containing a text, a table and a flow chart, and a RoB2 evaluation problem set; a problem reconstruction module injected through medical knowledge; performing position decision and multi-modal coordination analysis on the RCT literature through a multi-modal document analysis module; the reconstructed evaluation problem and the analyzed context information are input into a multi-expert cooperation module, cooperative reasoning is performed through a multi-reasoning unit, results are fused through a decision unit, and item-level, field-level and overall bias risk evaluation results are generated. The invention also constructs bias risk entry level and domain level data sets for supporting the training and verification of the method. The system comprises a data acquisition module, a problem reconstruction module, a document analysis module and a collaborative evaluation module, all the modules work cooperatively, automatic evaluation of RoB2 whole-process bias risks is achieved, and the system can be applied to scenes such as evidence-based medical research, system evaluation and clinical research quality control.

The invention discloses a fan blade fault diagnosis method and device based on predictive coding, and the method comprises the steps: obtaining the high-dimensional image information of a fan blade, and converting the high-dimensional image information into a low-dimensional image feature vector; processing the low-dimensional image feature vector to obtain prediction representation information, and obtaining an error feature according to the prediction representation information and a preset reference tag feature; under the condition that the convergence condition is not met, a prediction error is determined according to the error characteristics, and the steps of processing the low-dimensional image characteristic vector and obtaining prediction representation information are executed again according to the prediction error until the convergence condition is met; and predicting the fault type of the fan blade according to the final error characteristics obtained when the convergence condition is satisfied.

The invention provides a data acquisition optimization method, system, device, equipment and program product, and relates to the technical field of intelligent driving. The method comprises the steps that a data collection log is obtained, and the data collection log comprises vehicle intelligent driving data collected based on a data collection demand; determining the data subscription of each log type according to the data acquisition log; obtaining a data subscription strategy optimized according to the data subscription amount of each log type; and adjusting the data acquisition demand based on the optimized data subscription strategy. The problem that in the prior art, intelligent driving data collection efficiency and quality are insufficient is solved.

The invention discloses a data consistency analysis method, device and equipment and a readable storage medium, and is applied to the technical field of data storage, and the method comprises the following steps: determining a prefix, a suffix and an offset position corresponding to error report data according to the error report data of a data consistency tool and a configuration file; wherein the error report data comprises data related to the error data, and the offset position is offset in the storage object; determining a target object name based on the prefix, the suffix and the offset position, and querying data position information of the error report data based on the target object name; obtaining read-out data based on the data position information, and comparing the read-out data with the error report data to obtain a comparison result; and performing analysis based on the comparison result and the log information corresponding to the error report data, and determining an error report analysis report.

The invention discloses a power grid convergence application terminal access device based on cloud computing and an implementation method, and particularly relates to the technical field of power grid convergence communication. Comprising a power grid terminal data communication interaction module, a power grid terminal communication monitoring module, a power grid terminal data access efficiency monitoring module, a power grid terminal data access risk analysis module, a power grid terminal data fusion risk assessment module and a power grid terminal access communication performance optimization module. According to the method, communication monitoring data of the power grid integration application terminal is acquired through a data acquisition period set by a bound API gateway plug-in, a power grid terminal data access processing efficiency index is calculated, a power grid integration application terminal access safety risk coefficient is analyzed, and the power grid integration application terminal access safety risk coefficient is calculated through calculating a power grid terminal data communication performance index. And the abnormal communication of the power grid integration application terminal is switched to this, so that a data communication task scheduling strategy of the power grid integration application terminal is realized, and the operation efficiency and the resource utilization rate of the power grid integration application terminal are improved.

The method and system for automatic detection of kidney diseases based on machine learning include a kidney image collection module, a kidney image management module, a kidney image intelligent diagnosis module and a kidney disease classification module. The kidney images with kidney disease diagnosis labels collected by the kidney image collection module are stored and updated in the kidney image management module according to the kidney disease type. The kidney disease type is inferred by the kidney image intelligent diagnosis module using a machine learning algorithm. The kidney disease classification module classifies the diagnosed kidney diseases according to different types of kidney diseases, thereby achieving efficient and accurate diagnosis of various types of kidney diseases, which is of great significance for the diagnosis and early screening of kidney diseases.

The invention relates to the field of acquisition and transmission data analysis, in particular to an acquisition and transmission data comparative analysis method based on parameter real-time monitoring. The technical problems that in the prior art, most of collected and transmitted data comparative analysis methods depend on manual data analysis, lack intelligent data processing and exception recognition capabilities, lack advanced algorithm support, incomplete data models and limitation of system architecture, and consequently complex data analysis and processing tasks are difficult to complete automatically are solved; according to the technical scheme, the acquisition and transmission data comparative analysis method based on parameter real-time monitoring comprises the steps that a parameter threshold value and a standard range are set, comparative analysis is conducted on real-time data and historical data, and abnormal points and trend changes in the data are recognized; according to the method, the data is sorted and sorted according to the time sequence, the real-time data and the historical data are compared and analyzed, the influence of interference factors on the data is eliminated through an algorithm model, and the identified abnormal data and trend are analyzed to realize automatic analysis of the data.

The invention relates to the technical field of data management, and discloses a carbon data management system and method, and the system comprises a basic information module, an accounting configuration module, a data association module, a content maintenance module, an automatic collection module, a data filling module, a visual analysis module, and a report generation module. The basic information module is used for configuring enterprise basic information, product information, a parameter factor library and equipment information; and the accounting configuration module is used for setting boundaries for enterprise carbon data management, wherein the boundaries comprise a legal person boundary, a process boundary and an emission plan. The method covers multiple carbon data association aspects of materials, procedures, equipment and emission factors of enterprise production activities, achieves complete data acquisition coverage, can accurately and comprehensively achieve enterprise carbon data coverage, can enable enterprises to achieve automatic acquisition and automatic analysis of carbon data, greatly reduces the participation of human factors, and improves the production efficiency. The enterprise carbon data management efficiency is effectively improved, and the management cost is reduced.

The application discloses a source code pollution detection method, device and equipment and a storage medium. The source code to be detected is subjected to syntax analysis to generate an abstract syntax tree. The type of each node in the abstract syntax tree is determined, and an enhanced control flow graph corresponding to the source code is constructed according to the type of each node. The abstract syntax tree is subjected to sensitive pollution analysis to determine a sensitive data source. The pollution propagation path of the sensitive data source is tracked in the enhanced control flow graph to form a pollution propagation path graph. The pollution propagation path graph is matched with each vulnerability feature graph constructed in advance, a successfully matched vulnerability feature graph is determined, and the line number, pollution type, propagation path and corresponding segment of the pollution in the enhanced control flow graph of the pollution of the source code are determined according to the successfully matched vulnerability feature graph. The application makes the pollution positioning more fine-grained, improves the pollution detection precision in all directions, and is beneficial to user data, system and network security.

The application provides a target identification method and system suitable for military management, and relates to the field of automatic target identification; the method comprises the following steps: dividing a target identification grid template according to a three-dimensional entity model of a target identification area; acquiring standard remote sensing images corresponding to a plurality of time periods in a geographic information database and environment characteristics of each standard remote sensing image; for any target identification grid template, performing image fusion on the behavior characteristics and the standard remote sensing images according to the behavior characteristics of a target of interest, so as to obtain a template image of each target of interest; constructing a convolutional neural network model, performing model training and optimization according to the template image, and obtaining a target identification model; and identifying the target of interest according to the target identification model; the application divides the target identification area into grids, and uses the behavior characteristics of the target of interest to predict the behavior of the target, so as to use the predicted behavior as training data to train the model, and then realize high-accuracy identification of the target.

The invention relates to the technical field of artificial intelligence, and particularly provides a hardware equipment driving strategy generation method and device, a storage medium and a program product, and the hardware equipment driving strategy generation method based on multimedia content comprises the steps: analyzing the multimedia content, and obtaining the feature information of the multimedia content; generating driving strategy information associated with the multimedia content based on the feature information; wherein the driving policy information is used for indicating one or more hardware devices associated with the multimedia content, and driving predetermined processing executed by the one or more hardware devices. According to the hardware equipment driving strategy generation method disclosed by the invention, the automatic analysis of the multimedia content in the on-demand scene and the live broadcast scene and the automatic generation of the related hardware equipment driving strategy are realized, and the real-time linkage based on the multimedia content is provided.

The invention discloses a water sample detection system and method of a reverse osmosis membrane element, and the water sample detection system of the reverse osmosis membrane element comprises a reverse osmosis membrane shell, an integrated reverse osmosis water production joint and a reverse osmosis membrane element detection device, the reverse osmosis membrane shell is used for accommodating a reverse osmosis membrane element, and one end of the reverse osmosis membrane shell is provided with a reverse osmosis membrane shell end cover; the integrated reverse osmosis water production joint is connected with the reverse osmosis membrane shell end cover; the reverse osmosis membrane element detection device is connected with the reverse osmosis membrane element in the reverse osmosis membrane shell through the integrated reverse osmosis water production connector and is used for collecting a water sample in the reverse osmosis membrane element and detecting and analyzing the water sample. According to the invention, collection and analysis of water samples at different positions in the reverse osmosis membrane element can be realized.

The application relates to the technical field of petrochemical workwear flame-retardant performance detection, and specifically discloses a petrochemical workwear flame-retardant performance detection system, which comprises a base, a mounting frame arranged on the base, a shell arranged on the base, and a control panel arranged on the shell; an analog assembly, a driving element, an elastic connecting element and a rolling roller, the mounting disc and the driving element are both mounted on the mounting frame, the elastic connecting element is mounted on the mounting frame, the rolling roller is arranged on the elastic connecting element, the rolling roller is in movable abutment with the mounting disc, the driving element drives the elastic connecting element to reciprocatingly swing on the mounting frame, so that the rolling roller repeatedly rolls the workwear sample fixed on the mounting disc; a combustion assembly, a sliding frame and a spray gun used for burning the workwear sample; and a detection assembly, a visual camera, the visual camera can detect the burning condition of the workwear sample in real time. The application has the effects of simulating complex and changeable use environments and improving the accuracy and comprehensiveness of the detection system.

This invention relates to the field of mortar testing, specifically to a mortar consistency testing device for environmentally friendly mortar. It includes a lead screw slide with its output end fixed to a worktable. A cover is located beside the worktable, and a cone-shaped device coaxially and detachably holds the mortar. A vibration mechanism is located at the lower end of the cover. An infrared sensor is fixedly connected to the lead screw slide near the cover, and the infrared sensor is electrically connected to a controller. An electromagnet is fixedly connected to the lead screw slide below the sensor. A support is fixedly connected to the lead screw slide below the electromagnet, and an electric actuator is fixedly connected to the upper end of the support. A retaining ring is fixedly connected to the end of the support away from the lead screw slide, and a guide rod is coaxially connected to the retaining ring. A permanent magnet is fixedly connected to the upper end of the guide rod near the lead screw slide, and a cone-shaped device coaxially with the cone-shaped device is fixed to the lower end of the guide rod. During testing, the cone is filled with mortar and fixed coaxially with the cover cylinder. The vibration mechanism disperses the mortar. The screw slide and electric actuator adjust the position of the cone, and the electromagnet attracts the guide rod. After the power is cut off, the cone falls, the infrared sensor detects the displacement and transmits it to the controller to calculate the consistency, thus achieving accurate testing.

The application provides an optimization method of database index, a storage medium and an equipment. The optimization method comprises the following steps: collecting statistical information of total operations on data in a database running period; wherein the total operations comprise query operations and change operations, and the change operations comprise at least one of adding, deleting and modifying operations; matching indexes in the database with the statistical information, and taking the matched indexes as used indexes; calculating positive values brought by the used indexes according to the query operations of the used indexes; calculating negative values brought by the used indexes according to the change operations of the used indexes and / or occupied disk space; obtaining final values of the used indexes according to the positive values and the negative values; and optimizing the used indexes if the final values are less than a preset threshold. The low-value used indexes are accurately found and optimized to improve the performance of the database system.

The invention belongs to the technical field of smart factories. The invention provides an assembly line monitoring system based on a full-automatic feeding unmanned logistics vehicle. The system comprises a distributed monitoring camera, a scheduling system and the full-automatic feeding unmanned logistics vehicle. Wherein the distributed monitoring camera shoots and obtains high-definition image data related to each material storage node of the assembly line; the scheduling system determines and obtains the material remaining amount of each material storage node based on the high-definition image data, determines and obtains a full-automatic material supplementing unmanned logistics vehicle for supplementing materials to the material storage nodes when the material remaining amount is lower than a preset value, and sends a material supplementing instruction to the corresponding full-automatic material supplementing unmanned logistics vehicle; and the full-automatic material supplementing unmanned logistics vehicle distributes the materials corresponding to the material distribution quantity to the material storage nodes corresponding to the identity information. According to the scheme, an existing distributed monitoring camera in an assembly line production workshop is fully utilized, and assembly line material distribution based on the full-automatic material supplementing unmanned vehicle can be achieved at low cost.

This application discloses a method, apparatus, equipment, and storage medium for managing changes to automotive parts, relating to the field of vehicle manufacturing technology. The method includes: constructing a structured knowledge base; receiving and parsing design change input information to obtain key feature information of the design change; based on the key feature information of the design change and according to an interchangeability definition rule base, performing a change judgment to obtain a corresponding change judgment conclusion; and generating a structured report based on the change judgment process information, the change judgment conclusion, and supporting judgment evidence. This application, by constructing a structured knowledge base and rule engine, transforms enterprise standards and engineering experience into executable computer logic, enabling automatic analysis of design change content and outputting interchangeability conclusions and replacement suggestions.

This invention provides a method, apparatus, equipment, and medium for data security analysis of rail transit signaling systems, relating to the field of rail transit technology. The method includes: identifying the subsystems, interfaces, and peripheral systems to be analyzed within the rail transit signaling system; establishing a first correlation between the functions of the subsystems, interfaces, and peripheral systems, and establishing a second correlation between the functions of the subsystems, interfaces, and peripheral systems and the data of the subsystems and interfaces; identifying the top-level accident of the rail transit system, and establishing a third correlation between the top-level accident, pre-set guidance words for the top-level accident, and the functions of the subsystems; and performing data security analysis based on the first, second, and third correlations. This invention effectively realizes automated analysis of data security in rail transit signaling systems, improving the efficiency and accuracy of data security analysis.

The utility model relates to the technical field of particle size analysis, especially to a particle size analyzer, aims at solving the problem that the existing particle size analyzer cannot keep samples. The particle size analyzer provided by the utility model includes stirring mechanism, sample inlet mechanism and sample holding cylinder, the stirring mechanism includes sampling pipeline, stirring subassembly, blanking subassembly and distributor, one end of sampling pipeline communicates with technological pipeline, and the other end is connected with stirring subassembly, blanking subassembly is set below stirring subassembly, distributor is set below blanking subassembly, material passes sampling pipeline, stirring subassembly, blanking subassembly in proper order from technological pipeline, and falls to distributor from blanking subassembly, the lower end of distributor is provided with first sampling port and second sampling port. The particle size analyzer provided by the utility model keeps manual sampling port, namely second sampling port, through setting classifier, and then realizes automatic analysis while being capable of keeping samples, provides support for data review.

The invention discloses an arrhythmia intelligent multi-classification device for dynamic electrocardio. The arrhythmia intelligent multi-classification device comprises a data acquisition preprocessing module, an arrhythmia intelligent multi-classification neural network construction and training module, an automatic coding module and an integration module. The data acquisition and preprocessing module is used for performing feature extraction and preprocessing on electrocardiogram data, an electrocardiosignal data set is constructed and comprises features of the electrocardiosignal data and category label values corresponding to the features of the electrocardiosignal data, and the arrhythmia intelligent multi-classification neural network comprises a plurality of convolution blocks, a normalization layer and an activation function. And training a neural network by using the electrocardiosignal data set to obtain an intelligent arrhythmia multi-classification model. And the automatic coding module takes the characteristic value of the electrocardiosignal data as input to obtain a corresponding classification result. The integration module compares the output of the two models and outputs a final classification result, the classification accuracy can be improved for arrhythmia categories with small data volume, and the device can provide diagnosis reference and basis for clinicians.

The invention belongs to the technical field of security and protection supervision, and particularly relates to an Internet of Things video security and protection supervision system based on artificial intelligence, which comprises an environment analysis module used for analyzing a surrounding environment video acquired in a video acquisition module so as to analyze whether an accident exists in the environment; the road surface analysis module is used for analyzing the road surface video acquired in the video acquisition module so as to analyze whether an accident exists in the road surface or not; and the video playback module is used for intercepting and storing the initial video identified by the environment analysis module and the pavement analysis module. The environment analysis module, the road surface analysis module and the video playback module are arranged, so that accidents can be automatically analyzed, recognized and pre-alarmed when the environment and the road surface are monitored, accident videos can be automatically intercepted, potential safety hazards can be found in advance, workers do not need to manually find the accident videos, and the working efficiency is improved. And the intelligent degree is high.