29results about How to "Simplify the acquisition process" patented technology

The invention belongs to the technical field of artificial intelligence, and relates to a power document intelligent question and answer method and system based on a large language model. The method comprises the steps of obtaining document data according to a preset period; preprocessing the document data to obtain an adaptive document; constructing a vector retrieval library through an embedded model according to the adaptive document; obtaining a user query question, inputting the user query question into a vector retrieval library, performing retrieval based on a vector similarity retrieval method and a keyword retrieval method to obtain related text blocks, and screening out the most related text block from the related text blocks through a two-stage rearrangement technology; a user queries the question and the most relevant text block and inputs the question and the most relevant text block into the large language model to obtain preliminary intelligent answer information; and correcting the preliminary intelligent answer information based on a preset self-provincial inversion mechanism to obtain final intelligent answer information. Multiple rounds of questions and answers and context understanding are supported based on a correction mechanism, context consistency can be kept in continuous query of complex technical questions, and the accuracy of multiple rounds of questions and responses is ensured.

The invention discloses a zero sample image classification method and device, and belongs to the field of image recognition. According to the method, a category description document is generated through a large language model, global and local feature information of an image and the document is obtained through a visual encoder and a text encoder, then decoupling is performed through a visual semantic decomposition module and a text semantic decomposition module, and visual semantic embedding and text semantic embedding are generated; through joint training of the modules, optimizing total loss composed of local-to-semantic mapping variance loss, multi-semantic diversity loss, decomposition semantic alignment loss and local semantic alignment loss; and the training is used for image category prediction in the reasoning stage after completion of training. According to the invention, the difficulty of zero sample image classification can be reduced, and the classification accuracy and efficiency are improved.

The invention discloses a transformer hotspot inversion method based on a time convolutional neural network, and electronic equipment. The method comprises the steps that a first training data set is acquired, and the first training data set is constructed based on an orthogonal design mode and a finite element simulation mode; performing data dimension reduction processing on the first training data set to obtain a target training data set; training the initial hotspot inversion model by using the target training data set, and determining a target hotspot inversion model; and using the target hot spot inversion model to predict hot spot data of the target transformer to obtain a prediction result, the prediction result including a target hot spot temperature value and a target hot spot position. According to the invention, the technical problems of low accuracy and high cost of the determination method of the hot spot temperature value and the hot spot position when the three phases of the transformer are unbalanced in the prior art are solved.

The invention discloses a multi-view fusion emotion recognition method under a sleep deprivation condition, and the method comprises the steps: constructing and training a recognition model which comprises a Transform network based on multi-view fusion in an offline stage, carrying out the multi-view fusion of an input signal through employing the trained recognition model in an online stage, and achieving the real-time detection. According to the method, the accuracy of emotion recognition under a single mode (EEG signal) is improved by introducing the multi-view fusion Transform model, the dependence on multi-mode data is reduced, and the influence of the sleep state on the emotion is evaluated more accurately by improving the experimental design and eliminating the interference of material fixation on the result.

The invention discloses a plug-in-based real-time acquisition and manual analysis method for webpage data without a fixed format. Real-time integrated operation of data acquisition, labeling and uploading is realized through a browser plug-in. A user selects target data through a floating window interface, and a plug-in automatically extracts content, identifies a platform source, performs quick labeling in combination with a preset analysis label and uploads the data to a background. According to the method, the flexibility of manual judgment and the high efficiency of an automation technology are fused, and the method can adapt to multiple platforms including high-protection dynamic webpages without developing a customized tool for a target website. The floating window supports operations such as dragging and zooming, so that the user experience is improved; the labeling is completed by data acquisition, so that the processing chain is effectively shortened, and the efficiency and accuracy are remarkably improved. The system supports authority management, encrypted transmission and real-time statistical analysis, and ensures data security and efficient utilization.

The invention discloses a method for diagnosing parameters of a deep fractured reservoir based on distributed optical fiber temperature measurement data. The method comprises the following steps: acquiring actually measured bottom hole temperature and pressure data of the deep fractured reservoir by using a distributed optical fiber sensor; obtaining approximate analytic solutions of the bottom hole pressure at the early stage and the later stage of reservoir production; constructing a reservoir production early stage heat transfer model, and obtaining an approximate analytic solution of the production early stage bottom hole temperature; constructing a reservoir production later-stage heat transfer model, and obtaining an approximate analytical solution of the bottom hole temperature in the production later-stage; establishing a deep fractured reservoir parameter diagnosis method by using the bottom hole temperature approximate analytic solutions at the early stage and the later stage of production and the bottom hole pressure approximate analytic solutions at the later stage; and according to the actually measured bottom hole temperature and pressure data of the reservoir and a reservoir parameter diagnosis method, determining solved values of the reservoir parameters. The method provided by the invention is simple and easy to understand, has strong operability, and can improve the diagnosis efficiency of the deep fractured reservoir parameters.

The invention discloses a training method for a self-supervised microscopic image processing neural network, and the method comprises the steps: obtaining a fluorescent microscopic image data set through employing an optical microscopic imaging system with a time-dependent single photon counting function, and enabling the fluorescent microscopic image data set to comprise a photon counting distribution set {Gmn (t)} MN for M * N pixel points, m and N are respectively integers greater than 1, m is from 1 to M, n is from 1 to N, and t represents time; and constructing a training data set for a neural network comprising a fluorescence lifetime prediction convolution module and / or a denoising convolution module from the photon counting distribution set of the M * N pixel points in a photon flow redistribution mode.

The invention provides an antibody screening method and system based on a differential evolution algorithm and an artificial intelligence model. The method comprises the following steps: S1, acquiring data of an antibody-antigen compound sequence and affinity; s2, encoding the antibody and antigen sequences by using a language model, and converting the encoded antibody and antigen sequences into a matrix M; s3, training a machine learning model by using the matrix M and the affinity parameters to obtain a trained optimal machine learning model; s4, predicting the antigen affinity of the antibody by utilizing the trained optimal machine learning model; and S5, carrying out affinity optimization on the antibody sequence based on a differential evolution algorithm, and carrying out further filtration by predicting the druggability of the antibody so as to screen the antibody with high affinity and good drug properties.

The utility model discloses a dynamic resistance strain signal acquisition device, which comprises a detection seat, two ends of the detection seat are respectively provided with an installation part, a detection arm is arranged between the two installation parts, a detection hole is arranged in the middle of the detection arm, and four resistance strain gauges are uniformly arranged in the detection hole; a storage groove is formed in the side face of the installation part on one side, and a signal conditioning control panel is installed in the storage groove and electrically connected with the resistance strain gauges. According to the utility model, the full-bridge resistance strain gauge and the signal conditioning control board are integrated together, so that collected strain signals can be directly amplified, then converted into digital signals and directly output in a 485 form, the data collection process is further simplified, and connection and data interaction with other equipment are facilitated; the efficiency and flexibility of data acquisition are improved, and the method is more suitable for actual application scenes such as bridge monitoring.

The invention belongs to the technical field of burn wound analysis. According to the skin burn analysis method and system based on contrast agent blood perfusion, firstly, a fluorescence sequence after a contrast agent is injected is obtained, and a preprocessing sequence is generated through area cutting and down-sampling; a fluorescence intensity time curve of each pixel point is extracted, peak time is determined, and statistics is carried out to construct a peak time histogram; performing smooth denoising, extreme value detection and weak peak removal on the histogram, and adaptively selecting a threshold value for distinguishing normal and burnt tissues; generating an initial mask by using the threshold value, and performing connected domain analysis and morphological post-processing to obtain a target burn area mask; and finally, generating a pseudo-color image in combination with peak time. According to the method, the time dynamic characteristic of blood perfusion is fully utilized, the burn area can be accurately segmented and the microcirculation disturbance degree can be visually presented without depending on skin textures or a large amount of training data, and the objectivity and accuracy of burn depth evaluation are remarkably improved.

The application discloses a log downloading method, system, device and medium, wherein the method comprises: performing space-time constraint verification on a log collection request, generating a task identifier based on a verification result, and allocating temporary storage space for the task identifier; according to topology information of a container cluster, asynchronously and in parallel, issuing a log collection instruction corresponding to the log collection request to each master node of the container cluster; based on a time window parameter in the log collection instruction, determining each target file; extracting a log compression file matched with the corresponding target file from each master node locally, and storing all the log compression files in the temporary storage space; when at least one master node is detected to complete the extraction, performing aggregated compression on all the log compression files in the temporary storage space to obtain a single log aggregation file; and downloading the single log aggregation file. The method of the application realizes stable downloading of the container cluster log.

The utility model relates to the technical field of waste water crystallization treatment, and discloses a waste water heating, crystallizing and separating treatment device which comprises a crystallizing tank, a scraper blade is connected in the crystallizing tank through a rotating assembly, an electric heating tube is fixedly connected to the inner wall of the crystallizing tank, and an electromagnetic valve is fixedly connected to the lower side of the right end of the crystallizing tank. A first support is fixedly connected to the outer surface of the lower end of the crystallizing tank, a connecting pipe is fixedly connected to the outer surface of the top end of the crystallizing tank, a filter box is fixedly connected to the upper end of the connecting pipe, a box door is slidably connected to the right end of the filter box, and a filter plate is connected to the inner wall of the filter box through a linkage assembly. The top end of the filter box is fixedly connected with a water inlet pipe. According to the device, floating objects are intercepted through the filter plate, the hydraulic rod pushes the extrusion plate to clean and extrude the floating objects, blockage is prevented, and secondary pollution is reduced; the spiral scraper scrapes crystals on the inner wall of the crystallizing tank and conveys and collects the crystals, so that the process is simplified and the cleaning trouble is avoided.

The invention provides a bleed air pressure evaluation method, which is used for evaluating the bleed air pressure of a bleed air position of an intermediate casing outlet of a gas compressor, and comprises the following steps: acquiring the average total pressure and the reduced flow of the bleed air position, determining the wall surface static pressure of the bleed air position through a static pressure determination formula, and then evaluating the bleed air pressure by assisting the determined wall surface static pressure. The invention also provides a bleed air pressure evaluation system for realizing the bleed air pressure evaluation method. According to the bleed pressure evaluation method, the bleed pressure of the bleed position of the outlet of the middle casing of the gas compressor can be quickly evaluated.

The application discloses a kind of active implantable medical device in-vivo radio frequency response modeling method based on equivalent lumped element model, by constructing and matching the electromagnetic characteristics of the actual conductive path of AIMD and surrounding tissue, equivalent lumped element model (LEM), the key factors such as the multiscale electrical characteristics of the geometry size of implantable medical device and its in homogeneous, non-uniform even real anatomic tissue environment are parameterized characterization, so as to quickly and accurately reconstruct the radio frequency transfer function of implant.The method of the application effectively breaks through the bottleneck of the existing Tier 3 evaluation method, meets the technical requirements of the latest standard based on Tier 4 evaluation method for modeling the radio frequency transfer function of implant in the environment closely related to clinical tissue, and provides a new technical path and implementation means for efficient and accurate evaluation of the radio frequency heating risk of implantable medical device in the magnetic resonance environment.

The application discloses a kind of spatial registration method and system of visible light image and infrared image, it is related to spatial registration technical field, the position coordinate in the position coordinate in the coordinate system of second bird's-eye view obtained by visible light camera is registered with the position coordinate in the position coordinate in the coordinate system of second bird's-eye view obtained by infrared camera, more accurate conversion relationship can be obtained, and the acquisition process of conversion relationship is simpler than prior art, does not need a large number of training images, low in cost, strong practicality.

The application discloses a kind of converter valve side bushing on-line insulation monitoring method based on multidimensional timing characteristics, belong to the on-line monitoring technical field of capacitive equipment.The application obtains the mapping relationship of multiple harmonic resistance and direct current resistance by carrying out off-line test to converter valve side bushing;While synchronously collecting the leakage current and voltage signal of bushing, the mapping relationship is used to calculate timing resistance, multiple harmonic capacitance, multiple harmonic dielectric loss as insulation characteristic parameter, and then the correlation coefficient between each corresponding timing insulation characteristic parameter of the same batch of bushing is calculated;The correlation coefficient between all bushings is used to form sequence and is normalized to obtain evaluation sequence, find out the position of abnormal value and mark, while generating and updating evaluator, finally accurately locate abnormal bushing through the result of evaluator.So, the application realizes high sensitivity on-line monitoring of abnormal state caused by insulation deterioration by using mutual supervision of multiple insulation characteristic parameters between large quantities of bushings.

The present application relates to absorption spectroscopy technology, and specifically provides a multi-gas measurement method based on GFC wheel, comprising the following steps: A1. obtaining standard deviation R of reference signal in multiple detection periods rsd and standard deviation M of measurement signal rsd ; A2. obtaining offset parameter K=f(R rsd , M rsd , t) according to the standard deviations, t is the absolute value of the difference between the rotation period at the last calibration and the current rotation period; A3. comparing the offset parameter K with a set range; if the offset parameter K is normal, no adjustment is needed; if the offset parameter K is abnormal, corresponding adjustment measures are implemented according to the set range where the offset parameter K is located, and the adjustment measures comprise: obtaining complete reference signal and measurement signal, thereby obtaining Δt, and replacing. The present application has the advantages of accurate measurement and the like.

This application discloses a method, system, device, and medium for acquiring information from power equipment, belonging to the field of power electronics technology. The method includes: power equipment responding to a connection request from a pre-installed device by establishing a communication connection with the pre-installed device via an AP hotspot; receiving an inquiry command sent by the pre-installed device; obtaining the response information corresponding to the inquiry command; and sending the response information back to the pre-installed device. This application, by activating the AP hotspot of the WiFi module after the power equipment is powered on, allows the pre-installed device to establish a communication connection with the power equipment via the AP hotspot, obtain the corresponding response information based on the network relationship within the power equipment cluster, and provide feedback. This eliminates the need for manual scanning of QR codes or manual data entry for each power equipment, simplifying the power equipment information collection process, shortening the information acquisition time cycle, and improving the efficiency of power equipment information acquisition.

The invention discloses a clustering-based RIS auxiliary spatial modulation system blind detection method and system, and relates to the technical field of wireless communication, and the method comprises the steps: constructing an RIS auxiliary spatial modulation system, and obtaining a receiving signal of the RIS auxiliary spatial modulation system; reconstructing a received signal by constructing a matrix to obtain a channel model; performing equivalent transformation on the channel model to obtain an equivalent channel model; converting a signal detection problem into a clustering problem through an equivalent channel model; constructing an optimized K-means clustering detector based on the amplitude and phase characteristics; and iterating a clustering problem by optimizing a K-means clustering detector to realize blind detection of the signal. According to the method, the signal detection problem in the RIS auxiliary spatial modulation system is converted into the clustering problem, the amplitude and phase characteristics of the system channel are deeply excavated through the novel K-means clustering detector, the signal detection precision and efficiency are effectively improved, and dependence on channel state information is avoided.

The embodiment of the invention relates to a data management method, electronic equipment, a cloud and a storage medium, the method is applied to the electronic equipment, the electronic equipment comprises equipment data, and the method comprises the following steps: forming an equipment data body based on the equipment data, the equipment data body being equipment data stored in the electronic equipment and associated with the electronic equipment; and sending the device data to the cloud, so that after the cloud receives the device data, a device data shadow is formed based on the device data, and the device data shadow is the device data stored in the cloud and associated with the electronic device. In the data management method, the electronic device directly sends the device data to the cloud, and a device data shadow is formed in the cloud, so that a docking system can directly obtain the device data shadow stored in the cloud without obtaining the device data through other devices. Therefore, unified management of the electronic equipment is facilitated, the acquisition process is simplified, the efficiency is improved, the influence of network stability is reduced, the response speed is improved, and the concurrency is increased.

This utility model relates to a platform device for collecting reflectance spectra using a desktop reflective film thickness gauge, belonging to the field of integrated circuit or discrete device manufacturing technology. It includes a platform with a vacuum chamber at its bottom and a vacuum connector at the center of the bottom of the platform, the inner cavity of the platform being connected to the vacuum chamber via the vacuum connector; multiple sets of vacuum adsorption holes are formed on the top surface of the platform; a vacuum switch is provided on the vacuum chamber; a rotating bracket is provided between the vacuum chamber and the platform, the rotating bracket being fixed to the bottom of the platform; the rotating bracket can rotate on the vacuum chamber, driving the platform to rotate synchronously; a moving unit is provided below the vacuum chamber, the moving unit having a mirror stage, and an inclined mirror and a plane mirror are provided on the mirror stage. This application simplifies the spectral acquisition process, prevents the sample to be tested from shifting or shaking, improves testing accuracy, and achieves efficient and stable film thickness testing.

The invention discloses a plunger running state and parameter obtaining method for shale gas well drainage gas recovery. The method comprises the steps that a coupling signal generated when a plunger passes through an oil pipe is obtained; according to the matching relation between the coupling signal and a time shaft, plunger operation state parameters are obtained; the operation state parameters comprise the plunger operation position, the operation speed change, the liquid level position in the oil pipe and the liquid column height. Through matching of the dynamic coupling signal and the time axis, the plunger operation state parameters such as the plunger operation position, the operation speed, the liquid level position in the oil pipe and the liquid column height are obtained, the obtaining process is simple, the result is accurate and reliable, development does not need to depend on field experience, the accuracy of the plunger operation dynamic monitoring parameters is improved, and the working efficiency is improved. Reliable basis is provided for plunger type optimization, the implementation efficiency of the plunger drainage and mining process is greatly improved, and the problem that due to the lack of effective plunger operation state parameters and evaluation methods, process designers only carry out well opening and closing system design through field experience is solved.

This invention discloses a method, apparatus, equipment, and storage medium for synchronous display of modular optional quantity and price. It acquires the geometric feature information and engineering attribute information of the target 3D model and each target component. Based on preset association rules, it establishes a dynamic association between business attribute information and the first two types of information. Then, based on the three types of information and preset price mapping rules, it automatically calculates the material price list for each component and forms a comprehensive list for the entire 3D model. Finally, it encapsulates and visualizes the above information. This invention effectively achieves the linkage and connection between component attribute information and quantity and price data, ensuring data consistency and calculation accuracy. Simultaneously, the integrated visualization simplifies the information acquisition process, significantly improves the collaborative efficiency of engineering parameter design and quantity and price management, solves the problems of information isolation and lagging calculation in existing technologies, and adapts to the core business needs of engineering projects.

The application provides a multi-material lip synchronization method and device based on single training of the same real person, which comprises the following steps: S1, constructing sample data containing facial features, speech features and face posture features; S2, training a posture parameter prediction sub-network, so that the face posture features output by the posture parameter prediction sub-network tend to the expected face posture features in the sample data; S3, performing coordinate transformation on the facial features, so as to map the parameters of the facial features to a standard coordinate system under a front view angle; S4, learning a dynamic mapping relationship between the fused features and the lip action through time sequence modeling, and obtaining an LSTM network capable of predicting the next frame of facial features; and S5, outputting the next frame of facial features of a digital person based on the trained LSTM network. The application simplifies the data acquisition process, improves the lip synchronization efficiency, reduces the cost, and improves the stability of the synchronization effect.

This invention discloses an intelligent form validation and data management method and apparatus based on a component-based architecture. The method receives and parses form field configuration information, including field identifiers and component logical names, through a core form container component; dynamically searches for and loads the corresponding form field component from a preset component registry based on the component logical name for rendering; acquires input information and calls a unified validation rule management system to validate the input data; achieves bidirectional assignment and decoupling between internal data of the form field component and external business data according to preset configuration rules through a preset data mapping mechanism; monitors the status of the core form container component, generates data fingerprints for the form data based on a hash algorithm, and compares these fingerprints to determine whether the form data has changed. This method improves development efficiency, reduces maintenance costs, simplifies the form change detection process, improves the accuracy and stability of detection, and enhances the user experience.

The present application relates to a kind of efficient regeneration method with the larch of north China as explant, the method comprises the following steps: sowing, disinfection, induction culture, elongation culture, rooting culture, seedling and transplanting.According to the technical scheme provided by the present application, the medium with specific formula is used, so that the larch of north China shows significant advantages in the process of propagation: high differentiation efficiency, large proliferation coefficient, good rooting rate.In addition, the method also has the characteristics of short plant growth cycle, strong adaptability after transplanting and the like.The seedling after cultivation presents the characteristics of robust and straight, good growth and uniformity.The technical scheme of the present application significantly reduces the seedling culture period, effectively reduces the production cost.By establishing the adventitious bud induction system with the larch of north China as starting material, and successfully obtaining regenerated plant, a new technical approach is provided for the rapid propagation of the larch of north China.Meanwhile, the present application also lays the foundation for the future establishment of efficient larch of north China transgenic system.

This invention provides a method, apparatus, and electronic device for acquiring calibration data of a PTZ camera, applicable to the field of image data processing technology. The method includes: controlling the PTZ camera to move to an initial position corresponding to the center of the PTZ camera's image and a reference position in the bullet camera's image; determining calibration motion control parameters for the PTZ camera using the reference position in the bullet camera's image and the bullet camera's field of view; wherein the calibration motion control parameters control the PTZ camera to move to a target area corresponding to the center of the PTZ camera's image; controlling the PTZ camera to move to the target position using the calibration motion control parameters and acquiring a calibration image captured by the PTZ camera at the target position; and determining a pair of calibration point data between the bullet camera and the PTZ camera using the target area in the bullet camera's image, the calibration image, and the calibration motion control parameters. This solution simplifies the process of acquiring calibration point data.

The present application belongs to the technical field of three-dimensional phenotype detection, and particularly relates to a full-automatic acquisition and extraction method for three-dimensional phenotypes of corn. The method comprises the following steps: S1: constructing a complete dense three-dimensional point cloud containing a corn plant to be detected and a calibration object based on multi-view image video; S2: inputting the complete dense three-dimensional point cloud into a pre-trained PointNet++ model to obtain a corn plant point cloud to be detected; S3: processing the corn plant point cloud to be detected based on an adaptive Laplace algorithm to obtain a skeleton point cloud of the corn plant to be detected; S4: performing automatic topological analysis on the skeleton point cloud to complete decoupling of stem skeletons and leaf skeletons; S5: based on the decoupled stem skeletons and leaf skeletons, realizing organ-level point cloud segmentation of stems and leaves through constraint inflation operation; and S6: generating a corn phenotype detection standardized report in a unified format. The present application realizes full-automatic extraction of three-dimensional phenotype data of corn.

The invention provides an automatic driving soft recharge method and system and a readable storage medium, and the method comprises the following steps: collecting real vehicle road test data, uploading the real vehicle road test data to a cloud object storage service for classified storage, and forming a cloud data resource pool; preprocessing the real vehicle road test data in the cloud data resource pool, extracting scene features and automatically labeling the scene features, generating structured scene data and storing the structured scene data in a generalization scene library; s3, selecting target scene data from the generalization scene library, scheduling and operating a to-be-tested automatic driving algorithm, recharging the target scene data into the to-be-tested automatic driving algorithm for testing, and automatically generating a test report containing problem data identifiers and performance indexes; judging whether the performance index in the test report meets a preset test passing condition or not; and if yes, outputting a final test report, and completing the soft recharge test.