11 results about "Validation test" patented technology

The invention relates to an automatic program repairing method based on data flow driving, which takes an error file and a method signature as input, and reports error information in a defect positioning tool or an integrated development environment. Secondly, handing over error information and original defect codes to a large language model, extracting an element list related to defects from the large language model, then constructing defect contexts, using a search tool to retrieve key element definitions and dependency relationships, integrating control flow and error mode information, and finally obtaining defect information; then, the retrieved information, the original defect codes and the potential defect types are integrated into cue words, and the cue words are submitted to a large language model to generate candidate patches. And then the candidate patch is verified, and if the candidate patch does not pass the verification, error reporting information during the verification is combined with the candidate patch to carry out iterative optimization until the candidate patch successfully passes all test verification or the maximum number of iterations is reached. According to the method, context semantics are enhanced by means of data flow analysis, and the repairing accuracy and efficiency are improved.

The disclosure provides a pricing test method, device, equipment and medium for a charging system, and belongs to the technical field of function test. The method comprises the following steps: generating verification test sample data, wherein the verification test sample data comprises verification test user data, verification test call data and result verification data; determining whether a first condition is met; providing the verification test user data and the verification test call data to the charging system; obtaining execution result data of the charging system in performing pricing test on the verification test call data according to the verification test user data; and determining a pricing test result of the charging system according to the result verification data and the execution result data. The disclosure can effectively improve the verification accuracy of the verification result of the pricing correctness, and effectively reduce the verification time and the verification workload.

The invention discloses an optometry method for high-precision multi-type combination, which is characterized by comprising the following steps: S1, acquiring an objective refraction parameter set through an automatic optometry unit; s2, implementing interactive subjective optometry based on a virtual reality interface, and generating a subjective correction parameter set; s3, acquiring high-order aberration data by adopting a wavefront aberrometer; s4, performing a refractive adaptability test in a dynamic visual scene to obtain a dynamic compensation parameter; s5, generating an initial optometry scheme through a multi-modal data fusion algorithm; s6, optimizing a lens parameter combination based on a genetic algorithm; s7, implementing a double-blind verification test and obtaining a visual quality score; and S8, iteratively optimizing the final prescription according to the verification result. The problem of subjective or objective data splitting in traditional optometry is solved through a multi-modal fusion algorithm, accurate adaptation of a dynamic visual scene is achieved through eye movement tracking and virtual reality verification, and safety and efficiency of ophthalmic optical optometry are guaranteed.

The present invention relates to an optometry device for testing an eye of an individual, the optometry device comprising a computer having one or more processors programmed to perform a sequence of subjective tests comprising at least a first predetermined subjective test and a second predetermined subjective test, the one or more processors are programmed to: a) perform the first predetermined subjective test, thereby determining a temporary value of a first refractive characteristic of the eye of the individual, b) perform a verification test at the end of the first predetermined subjective test, and c) determine a value of a second refractive characteristic of the eye of the individual. And c) determining a next subjective test to be performed or ending the sequence of subjective tests on the basis of the result of the verification test in order to detect a potential error in said temporary value of the first refractive characteristic determined in step a), and c) determining a next subjective test to be performed or ending the sequence of subjective tests on the basis of the result of said verification test.

The invention discloses a test fixture for a DBC automatic test machine, and the fixture comprises a housing which is internally connected with a pedestal through a reset mechanism. According to the test fixture for the DBC automatic test machine, through rotation of the cam handle and combination with the first mounting hole, the base ascends and descends, the stroke of the floating plate is reduced when the fixture is locked, contact between a probe card and the test fixture is generated, the test result is qualified, a probe of the test fixture and the DBC base are opposite to each other, the probe card is fixed through a screw, and the test efficiency is improved. A blank area and a fixing opening used for being buckled with a DBC base are reserved at the position of the probe, the testing jig can complete testing on any testing machine through a corresponding testing line through the device, testing data can be verified in a cross mode, cost is low, the weight is light, and moving is flexible. A test jig of a compatible test machine is adapted to various DBC cross validation test machines; no other variables exist, and data verification is more reliable.

An automated self-precision validation accelerometer is configured for machine diagnosis for efficient and accurate vibration readings from the machine. The accelerometer sensor system conducts self-precision validation test and diagnosis. The accelerometer sensor system comprises two accelerometer sensors for more data acquisition. The usage of two tri-axial accelerometers identify ill-health of the sensors through a self-precision validation test conducted by a firmware module configured in the microcontroller unit that triggers the accelerometers to conduct in built self-test at specific constraints. The system 300 for self-precision validation accelerometer sensor comprises a power supply unit 301, a self-test sensor assembly 302, a wireless interface unit 303, and an external device 304. The firmware module 302c further sends a report on the test to the external device 304 through a wireless interface unit 303 advising for the replacement of sensor.

A diversified validation test suite application (DVTSA) for a generative artificial intelligence (AI) driven tool or a large language model (LLM) tool includes at least a first control logic, a second control logic, and a third control logic. The first control logic receives a seed test input or a user input, analyzes the seed test input or the user input, and extracts varying key elements. The second control logic performs an overlay measurement of the output of the first control logic. The third control logic causes the human verifier to evaluate an output of the second control logic with respect to a predefined coverage metric, and selectively and continuously iterating such that the output of the second control logic increases LLM tool input robustness and output robustness from a first level to a second level greater than the first level during production and pre-production LLM tools.

This invention discloses a drilling lithology identification method based on enhanced dynamic behavioral features. Addressing the shortcomings of traditional methods that rely solely on instantaneous parameters and struggle to capture the dynamic evolution of the drilling process, this method first collects drilling engineering parameter sequences and constructs a depth-domain parameter matrix using a sliding window. Then, it extracts dynamic behavioral features such as parameter change rates, local fluctuation intensity, and dynamic coupling relationships between parameters, and concatenates these features with the original parameters. Next, it constructs a Transformer encoder, utilizing a self-attention mechanism to capture long-range dependencies in the depth sequence. The encoded features are then processed through average pooling and a fully connected layer to output lithology classification probabilities. Finally, a cross-entropy loss function weighted by dynamic responses is used to optimize the model. In validation tests on six wells in the Volve oilfield, this method significantly improved the accuracy of lithology classification and the stability of the model, providing reliable technical support for intelligent drilling.

The present invention relates to a method for validating the ability of a test filter unit to produce a sterile effluent. The method according to the present disclosure has the advantage that it allows simulating cumulative stress incurred by the filter during use with consideration to time and pressure, as closely as is feasible. A further advantage of the method according to the present disclosure is that it allows evaluating the impact of the stress incurred by the process filter during PUPSIT, while factoring in lab scale equipment / limitations and differing objectives, e.g., performing PUPSIT during manufacturing vs. filter validation.

The invention provides a method for identifying true and false beef based on a micromolecule fingerprint spectrum, and relates to the technical field of micromolecule fingerprint spectrums.The method comprises the following steps of sample pretreatment and micromolecule extraction, specifically, a beef sample to be detected is subjected to standardization treatment, and after surface impurities are removed, the beef sample is frozen and ground into homogenate; acquiring mass spectrum data and constructing a spectrum; generating a three-dimensional micro-molecular fingerprint spectrum; screening characteristic molecular markers; identification model construction and training: training the marker data set; and performing model verification test. According to the method, low-content adulterated meat can be stably recognized through non-targeted screening, multi-marker collaborative judgment and combination of a machine learning dynamic threshold value, the accuracy rate is still kept in a high-accuracy-rate state after cooking, and compared with a traditional method, the sensitivity is greatly improved; through lipidome-metabolome multi-dimensional analysis, animal source adulteration and plant source substitutes can be synchronously distinguished, a larger range of adulteration types can be covered, and the blind area of the traditional technology is solved.

The invention relates to the technical field of solid state disk testing, in particular to a solid state disk testing index optimization method and device, equipment and a storage medium. Comprising the following steps: setting part of to-be-tested products as a sample group, and obtaining a first test parameter set and a multi-environment parameter matrix; performing a preliminary screening test and multiple rounds of verification tests on the sample group, collecting sample test data, identifying sensitive parameters, performing sensitivity grading, and updating a selection probability according to a grading result to obtain a second test parameter set; fitting the sample test data to obtain a bathtub curve, and extracting stage features as a stage feature set; and generating an environment adaptation test strategy according to the stage feature set and the environment parameter matrix, and testing all the to-be-tested products in combination with the second test parameter set and the environment adaptation test strategy to obtain a total test result. According to the method, sensitive parameter precision of solid state disk test index optimization, test strategy full-period and scene coverage diversification can be realized.