81results about How to "Quick analysis" patented technology

The invention discloses a children autism risk assessment method and system based on multi-modal collaborative reasoning and a vertical domain large model, and the method comprises the steps: collecting the audio data of a to-be-assessed child and a parent in a parent-child interaction link, and collecting the video data through collection equipment; analyzing and marking the collected audio data, and generating a sounding record and a transcription text with a timestamp; performing real-time analysis and labeling on the collected video data, and generating sight line, expression and action recognition records with timestamps; performing independent analysis on the preprocessed multi-modal data, performing feature fusion and collaborative analysis on the multi-modal data such as audio, text and video by using a multi-modal collaborative reasoning method, and generating a scientific data index for autism risk assessment; training a vertical domain large model special for autism risk assessment; and inputting the generated data indexes into a vertical domain large model, and outputting targeted assessment suggestions by the large model in combination with daily information of the children to be assessed obtained by interviews and conversations with parents.

The invention provides a rock mineral micromechanical evolution characterization method based on a convolutional neural network. The rock mineral micromechanical evolution characterization method comprises the following steps: step 1, obtaining rock sample micromechanical properties through a nanoindentation experiment; 2, performing deconvolution statistical analysis by using a Gaussian mixture model, and obtaining mechanical and volume fractions of each phase through a nanoindentation experiment; step 3, utilizing a Mori-Tanaka scale upgrading method to understand a convolution result, and performing rock macromechanical property prediction in combination with a convolutional neural network; and step 4, performing precision checking calculation on an output result of the convolutional neural network model until the prediction precision meets a preset requirement. According to the method, the microscopic mechanical parameters of the rock sample are obtained through the grid nanoindentation, statistical analysis is carried out on the nanoindentation test result by utilizing a deconvolution method, the mechanical property of the macroscale of the rock is obtained in combination with machine learning and a scale upgrading model, and a bridge for connecting the macroscale and the microscale is established; the method can effectively solve the problem of inaccurate prediction of rock micromechanical parameters on the macroscale and the problem of mechanical property characterization caused by scale difference.

The present application relates to the field of dam inspection, especially to a kind of image processing method and system for dam inspection, the present application is by controlling unmanned aerial vehicle to fly over detection area according to predetermined trajectory, when unmanned aerial vehicle is pre-entered detection area, continuously obtain image information and carry out multidimensional analysis, based on the result of multidimensional analysis and mirror surface reflection index, calculate to obtain spectral characteristic interference representation value, set interference label for detection area, subsequent interference label based on the control of unmanned aerial vehicle in detection area adaptively obtains spectral information in monitoring area, subsequent generation perspective adjustment instruction, by sampling determination selection confidence sampling position obtains spectral information, the present application is by image information in advance sensing interference situation of spectral information extraction in detection area, adaptively select spectral information capture mode, under the premise of guaranteeing inspection efficiency, improve the quality and reliability of the obtained spectral information, provide effective data support for subsequent analysis dam potential anomaly.

The present application relates to the field of analytical chemistry, and provide a kind of method for detecting complex matrix of agricultural products in guanidine morpholino salt hydrochloride.The extraction solvent of the present application uses acetonitrile+acid+aqueous solution, different acid is selected according to the water content of sample, trifluoroacetic acid is used for high water content sample, and formic acid is used for low water content sample;In purification, pH value is adjusted according to the oil content of sample, ammonia is used to adjust pH to 8.5 for high oil content sample, and pH value can not be adjusted for low oil content sample.In the method, NaCl is not added to make organic phase and aqueous phase in extraction liquid stratified, through the way of extracting three times repeatedly, the recovery rate of the method is guaranteed;And using ultra-high phase liquid chromatography triple quadrupole mass spectrometry technology, guanidine morpholino salt hydrochloride in complex matrix of agricultural products is successfully detected, the extraction method is fast and simple, the quantitative limit of guanidine morpholino salt hydrochloride in tea is 0.1mg / kg, and the quantitative limit in other matrix is 0.05mg / kg, which is suitable for routine analysis, and can meet the quantitative detection requirements of guanidine morpholino salt hydrochloride in complex matrix of agricultural products.

The invention provides a spark source atomic emission spectrometry determination method for acid-soluble aluminum and inclusion aluminum, and belongs to the technical field of assessment of inclusions in steel. The spark source atomic emission spectrometry determination method for acid-soluble aluminum and inclusion aluminum comprises the following steps: establishing a calibration curve of all aluminum, then determining integral intensities of inclusion aluminum, all aluminum and acid-soluble aluminum in a sample under corresponding conditions, and calculating the intensity of the inclusion aluminum by using a difference value between the integral intensities; selecting two standard samples with adjacent strength according to the strength of aluminum inclusion in the sample, and calculating a calibration coefficient K according to the aluminum content Al% lt; the excitation rate F is calculated according to the peak integral intensity of the inclusion aluminum and the integral intensity of the total aluminum in the 0.0007% standard sample, the inclusion aluminum content Als% is equal to K * F * (IAlt-IAls), and the content of the acid-soluble aluminum is equal to the difference between the content of the total aluminum and the content of the inclusion aluminum. According to the method, the accuracy of a measurement result is effectively improved while high analysis speed, low cost and simplicity and convenience in operation are ensured.

The application relates to the technical field of power distribution control, in particular to an active power distribution network fault self-healing system and a method thereof, which comprises a data sensing module, a fault positioning module, an isolation control module, a fault self-healing module and a power supply recovery module, and realizes intelligent processing of the whole process from fault detection to power supply recovery through cooperation of the multiple modules. The system can quickly position faults based on FTU layout structure and operation data, optimizes analysis efficiency in combination with a GPU computing power dynamic distribution mechanism, and realizes accurate isolation of a fault area, self-healing repair and smooth grid recovery by using intelligent strategy generation and digital twin technology. The application effectively improves the power supply reliability, system stability and operation intelligent level of the power distribution network.

The application relates to a gold nanoparticle array preparation method with strong stability and reusability, high cysteamine-stabilized gold nanoparticles are prepared first, the spacing between the gold nanoparticles is changed by utilizing the coulomb repulsion between the gold nanoparticles, then the gold nanoparticle solution is added dropwise to a glass surface modified by gamma-glycidoxypropyltrimethoxysilane to react, stable covalent bonds are formed, and gold nanoparticle arrays with uniform distribution on the glass surface can be obtained after the reaction. The preparation does not require high temperature, the experimental operation is simple and convenient, the gold nanoparticles are arranged in order and closely, have high detection sensitivity, have strong ultraviolet absorption capacity, good stability, reusability, salt resistance and low background interference, and can be reused. The gold nanoparticle array can realize detection analysis on high-salt-content samples in surface-assisted laser desorption ionization mass spectrometry and be used for rapid analysis of small molecule compounds in positive and negative ion dual modes.

This invention discloses a high-speed communication link transmitter modeling method based on a Transformer decoder. This method parameterizes the input signal and establishes a deep learning model with an encoder-decoder architecture, including a non-sequential encoder and a Transformer sequential decoder, to predict the output signal of the transmitter given the input signal. The encoder processes the input signal parameters, generates a context vector, and then passes it to the decoder. The decoder uses the context vector and the transmitter output signal sequence to generate a class probability distribution for each point in the sequence. The model is trained using a random masking strategy and employs non-autoregressive decoding and filtering techniques for inference, achieving parallel output sequence prediction. The final output is obtained through a single signal filtering step. Compared with traditional simulation techniques, this method significantly improves simulation speed while maintaining a very small error.

The invention relates to the technical field of medical image and artificial intelligence technology crossing, in particular to an intelligent auxiliary diagnosis method and system for a frozen section in a thyroid cancer operation. According to the technical scheme, the method comprises the following steps that a thyroid tissue intraoperative frozen section to be diagnosed is prepared, and the frozen section does not need to be dyed or subjected to section sealing treatment; and scanning the frozen section by using a terahertz near-field imaging system to obtain terahertz near-field image data of the frozen section. According to the method, the terahertz near-field imaging technology is adopted, the situation that cell nucleus morphology is difficult to observe due to ice crystal artifacts in a traditional frozen section is avoided, cancer cells are automatically recognized in combination with an AI model trained based on large-scale labeling data, and the objectivity and consistency of diagnosis are remarkably improved; meanwhile, the steps of dyeing and mounting are omitted, and rapid imaging and analysis are realized, so that the intraoperative diagnosis time is greatly shortened, and a generated visual contour report also provides visual decision support for pathologists.

The present application relates to aerospace integral closed shroud blade profile measurement and analysis technical field, specifically discloses a kind of integral closed shroud positive and negative splicing fast measurement method, comprising: obtaining the closed shroud to be measured, and establishing positive part coordinate system;In the current positive attitude, the position of each standard ball on the closed shroud to be measured relative to positive part coordinate system and relative to machine tool coordinate system is measured;In positive part coordinate system, obtain the point cloud data of the front surface of the blade to be measured;The closed shroud to be measured is reversed, and the position of each standard ball relative to machine tool coordinate system is measured in the current reverse attitude, and reverse part coordinate system is calculated;In reverse part coordinate system, obtain the point cloud data of the back surface of the blade to be measured;The point cloud data under two kinds of attitudes is spliced and integrated to form the complete profile point cloud data of the closed shroud to be measured.The present application solves the problem of large closed shroud detection blind area and low detection efficiency by positive and negative clamping measurement twice.

The utility model discloses a water quality on -line analysis appearance of quick emptying and cleaning digestion tube can, include: casing, analysis unit, the analysis unit sets up at the surface of casing, the analysis unit includes peristaltic pump, and peristaltic pump one end is linked with three -way solenoid valve no.

The invention discloses an intelligent milk tea machine equipment data monitoring method based on a cloud platform, and relates to the technical field of industrial Internet of Things, and the method comprises the steps: collecting operation data of a milk tea machine, carrying out the preprocessing, and generating a preliminary preprocessing data set; operation parameter optimization analysis is carried out on the fault prediction information and the health state indexes, a dynamic control strategy is generated, an upgrading plan is made, and a hot-pressing film upgrading scheme is generated; issuing the dynamic control strategy and the hot-pressing film upgrading scheme to an end-side milk tea machine, adjusting operation parameters in real time according to the dynamic control strategy, executing the hot-pressing film upgrading scheme, and generating end-side execution data; and according to the end side execution data and the edge feature vector, carrying out iterative updating on the milk tea machine operation model to generate an optimized milk tea machine operation model, and carrying out cooperative closed-loop control to generate real-time operation monitoring data. According to the invention, high-credibility data is provided for real-time control and predictive maintenance, the potential fault risk is reduced, and the operation safety of the milk tea machine is optimized.

This invention relates to the field of unmanned aerial vehicle (UAV) patrol technology, and more particularly to a UAV radar monitoring method and equipment for the sea area near a nuclear power plant's water intake. The UAV radar monitoring method for the sea area near a nuclear power plant's water intake includes: acquiring the monitoring and early warning requirements for floating objects on the sea surface and the target flight area, obtaining the monitoring and early warning threshold and the location range of the UAV's patrol flight area; determining the UAV patrol path and patrol strategy based on the monitoring and early warning threshold and the location range of the UAV's patrol flight area; conducting patrols according to the patrol strategy and the UAV patrol path, and acquiring graphic data of the target patrol path; performing recognition processing on the graphic information of the target patrol path to obtain the recognition result; and determining whether the recognition result meets preset alarm conditions, and issuing an early warning if it does. This invention enables rapid, large-scale patrols, recording, and analysis of the sea area near a nuclear power plant's water intake, improving the accuracy of monitoring floating objects in the large-scale sea area near a nuclear power plant's water intake.

This invention belongs to the field of analytical detection technology and discloses an analytical method for detecting N-nitrosobaricitinib impurities in baricitinib tablets. The method includes solution preparation and detection steps: blank, 0.9 ng / ml reference standard, and test sample solutions are prepared using a 40%–60% acetonitrile aqueous solution as a diluent; an Agilent Poroshell 120 EC-C18 column is used with 0.1% formic acid-methanol gradient elution; mass spectrometry is performed using an AJS ESI ion source in MRM scanning mode; and the content is calculated using the external standard method. This method is simple to operate, rapid in analysis, highly specific, highly sensitive (detection limit 4.30 ppb), and exhibits excellent precision, accuracy, and linearity. It can accurately quantify target impurities, providing reliable technical support for the quality control of baricitinib tablets.

This invention relates to a three-emission ratio fluorescence nanosensor for detecting tetracycline and its preparation method. The sensor uses a carbon dot-gold cluster nanocomposite material as the fluorescence signal. The synthesis steps and detection process of the carbon dot-gold cluster nanocomposite material in this invention are simple, convenient, and rapid, exhibiting rich fluorescence color changes. It does not require the assistance of complexes or coupling reagents. By constructing a three-emission ratio fluorescence sensor, the goal of highly sensitive and selective detection of tetracycline can be achieved.

This invention belongs to the field of drilling stability analysis technology, specifically a wellbore stability evaluation method, electronic equipment, and media. This method establishes a wellbore stability index for the first time, using the average of the wellbore stability indices from multiple wellbore stability sample wells as a threshold. The closer the target well's wellbore stability index is to the threshold, the better the wellbore stability; conversely, the further away, the worse the wellbore stability. This invention's method can evaluate wellbore stability while drilling with high accuracy. The electronic equipment and media based on this invention broaden its application scenarios, making it suitable for evaluating the wellbore stability of horizontal wells in sandstone and mudstone formations.

This invention relates to the technical field of cloud computing, and in particular provides a performance testing method for virtual switches in computing clusters. The method includes creating virtual machines on multiple physical nodes of the computing cluster; deploying a transceiver on the virtual machine of at least one physical node, and a forwarding program on the virtual machines of the remaining physical nodes; controlling the transceiver and the forwarding program to perform a loop forwarding test, so that packets are forwarded by the forwarding program and then returned to the transceiver; recording performance parameters during the loop forwarding test for performance problem analysis. The forwarding program of this invention generates a corresponding forwarding mapping table based on the traffic path and model, and forwards packets according to the mapping table, forming multiple ring flows to achieve ring network forwarding capability across multiple nodes, thereby improving the coverage of virtual switch testing.

The application discloses a fan blade damage rapid detection method based on inverse finite element reconstruction image recognition. The method comprises the following steps: inputting a training strain distribution data set into an inverse finite element strain field reconstruction algorithm model, calibrating the training strain distribution data set by using an inverse finite element strain field reconstruction parameter calibration method according to a calibration strain distribution data set, and outputting a fan blade strain field reconstruction image set; preprocessing to obtain a preprocessed fan blade strain field reconstruction image set; inputting strain distribution data of the fan blade when the fan blade is undamaged and real-time strain distribution data into a trained convolutional neural network image recognition algorithm model, outputting a damage position and a damage degree of the current fan blade, and realizing rapid detection of the fan blade damage. The method can effectively improve the existing fan blade damage detection efficiency and accuracy, and the model does not need to use structural material characteristics and load information, so that the damage detection method has universal applicability under complex working conditions.

The application discloses a kind of underwater acoustic open architecture under underwater acoustic component dynamic configuration management method, belong to underwater acoustic system technical field, comprising: establishing underwater acoustic component warehouse, for carrying out full life cycle tracking management to underwater acoustic component;Establish dynamic access control model, based on component identifier and version number, underwater acoustic component is divided into different security levels and operation categories, and the permission rule of each underwater acoustic component instance is configured dynamically adjustable;When receiving the operation request for target underwater acoustic component, the permission check of the operation request is carried out through dynamic access control model;When executing the operation to any underwater acoustic component, operation log is recorded in real time;When monitoring that the version of currently deployed underwater acoustic component causes system exception, automatically trigger rollback operation.The application can automatically trigger rollback operation when monitoring component defect, quickly restore system to previous stable state, significantly improve the robustness and service continuity of underwater acoustic system.

The application provides a soil component analysis system and device based on a spectrum technology, comprising a light source. In order to solve the problem that the soil samples sent to the laboratory are affected by the environment or are not properly preserved, resulting in errors in the results, the soil component analysis system is built-in the soil component analysis device. Compared with the traditional soil component analysis method, the system can perform rapid and accurate soil component analysis on the spot, without the need to take the samples back to the laboratory for processing, thereby saving time and human resources. When the electric telescopic sleeve and the electric telescopic inner tube are completely contracted, the first rotating assembly and the second rotating assembly are in the same horizontal plane with the L-shaped support column as a whole, which assists the L-shaped support column in supporting the detection assembly as a whole, and plays an auxiliary role in fixing the equipment during detection.

The invention provides an intelligent auxiliary decision-making method and system for power load management operation and maintenance detection. The method comprises the following steps: collecting real-time detection data of a power load management system terminal and a control loop; according to the real-time detection data, generating a detection report and an improvement suggestion through a pre-trained intelligent auxiliary decision-making system; the detection report and the improvement suggestion are used as intelligent auxiliary strategies to be displayed to operation and maintenance detection personnel; the intelligent auxiliary decision-making system can rapidly process and analyze real-time detection data, generate professional detection reports and improvement suggestions, shorten analysis and detection time, improve overall detection efficiency, help operation and maintenance personnel to rapidly position and solve problems, improve overall operation and maintenance quality and efficiency, and improve the operation and maintenance efficiency. The stability and safety of the power load management system are guaranteed, the dependence on high-skill professionals is reduced by the intelligent auxiliary decision-making system, the detection and analysis efficiency is improved, the training and operation and maintenance cost is reduced, and a large amount of manpower and time cost is saved.

The invention discloses an anodic oxide film detection system which comprises a conveying module, a preprocessing module, a multi-dimensional detection module, a data processing module, a sorting module and a central control module. The conveying module is used for conveying an anodic oxide film workpiece to be detected to each functional module according to a preset speed and path; the pretreatment module is arranged on a conveying path of the conveying module and is used for cleaning and drying the surface of a to-be-detected workpiece; and the multi-dimensional detection module is arranged on the conveying path behind the preprocessing module and is used for carrying out multi-parameter detection on the preprocessed workpieces. According to the anodic oxide film detection system disclosed by the invention, the problems of low detection efficiency, poor detection precision, single detection parameter, insufficient pretreatment, weak data processing capability, low sorting efficiency and the like in anodic oxide film detection in the prior art are solved.

The invention discloses a software code coverage rate testing method and a terminal, and the method comprises the steps: obtaining and recording the real-time execution information of a script code of target software in a running state during testing, and obtaining an actual execution path according to the real-time execution information; performing static analysis on the source code of the script code, and obtaining all possible paths according to a static analysis result; and calculating the coverage rate of the script code of the target software in combination with the actual execution path and all possible paths. According to the method, the execution condition of the script code of the target software is analyzed from two levels of a running stage and a static state, and then the coverage rate of the script code of the target software is calculated by combining an actual execution path and all possible paths, so that the conditions of new and old codes can be more comprehensively considered, the script code coverage rate is quickly analyzed, and the efficiency is improved. Therefore, whether potential problems exist or not is analyzed, and the quality and reliability of codes are ensured.

The embodiment of the application provides a detection test paper. It relates to the technical field of detection. The detection test paper comprises a base layer and a colorimetric detection layer. The colorimetric detection layer is arranged on the base layer, and the colorimetric detection layer comprises a carrier layer and at least two colorimetric detection parts arranged on the carrier layer. The color development time interval of the at least two colorimetric detection parts is less than 10s. Since the at least two colorimetric detection parts are all located on the carrier layer, sample liquid enters the at least two colorimetric detection parts at the same time, there is no time interval for the different colorimetric detection parts to start detection, meanwhile, the color development time interval of the at least two colorimetric detection parts is less than 10s, when the color development time interval of the different colorimetric detection parts is short, the multiple colorimetric detection parts develop color almost at the same time, which enables the user to read the detection results of multiple parameters at the same time point. The synchronism improves the response speed of the overall detection.

This invention discloses a moisture management platform and method for tobacco processing based on an Excel server, relating to the field of tobacco processing management technology. The method includes collecting key parameters from the centralized control system of the tobacco processing workshop and preprocessing them; constructing a moisture management platform for the tobacco processing process based on an Excel server; using the preprocessed historical key parameters as samples, selecting input and output variables, constructing a moisture prediction model using a regression prediction algorithm, validating the moisture prediction model, and adjusting the model parameters to meet the prediction error; calling the moisture prediction model to obtain the predicted moisture value, and combining it with the generated key parameter trend analysis chart to adjust the tobacco processing parameters for moisture control. This invention is developed without code based on an Excel server, featuring low cost and easy promotion, significantly improving product stability, shortening the process optimization cycle, and saving energy costs by dynamically adjusting energy consumption parameters.

The invention relates to the technical field of data processing, in particular to a tsunami disaster risk assessment method and system based on cloud computing and a medium. The method comprises the following steps: accessing and converging data of an earthquake monitoring system, a satellite remote sensing system, a tide level monitoring device and a historical tsunami event library to obtain a multi-source heterogeneous tsunami original data set; performing format standardization, time synchronization and semantic annotation processing on the multi-source heterogeneous tsunami original data set to obtain a unified data model; establishing and registering a data service interface based on the unified data model to obtain a data service set; and calling the data service set to obtain tsunami propagation analog input data. According to the tsunami disaster risk assessment system and method, efficient, accurate, real-time and operable comprehensive management of tsunami disaster risk assessment is realized through multi-source data standardization and semantic fusion, cloud computing parallel processing, multi-dimensional index analysis and dynamic visual display.

The invention relates to a process window screening method for nickel-based high-temperature alloy single crystal preparation. According to the method, based on a double-ellipsoid molten pool analysis heat source model and solidification condition calculation, the geometrical morphology and solidification behavior of the molten pool caused by electron beam scanning can be simulated in a multi-parameter space in a high-flux mode. The grain orientation evolution trend of the material after the powder bed is molten can be accurately predicted by calculating parameters such as the penetration depth, the penetration width, the molten pool leading edge angle and the temperature gradient under different energy input conditions, and a single crystal forming window suitable for the nickel-based superalloy is constructed. By adopting the method, process parameters such as energy input, scanning speed, scanning strategy and the like can be screened and optimized, and a multi-dimensional process window is established so as to identify stable growth conditions required by single crystal preparation. According to the method, the internal relation between the geometric behavior of the molten pool and the preferred orientation of the crystal grains can be disclosed, and technical support is provided for realizing controllable forming of a single-crystal structure, reducing the defect generation risk and improving the structural integrity and performance of an additive manufacturing part.

The application provides a kind of based on multi-task learning's submarine pipeline flow field prediction method and system, comprising: using variable scaling physical information neural network framework, construct the multi-task learning model for solving cylinder flow problem;Total loss function of multi-task learning model is constructed, and the adaptive loss function weighting method based on uncertainty estimation is used and the weight growth factor is introduced, to dynamically allocate weights for each loss term in the total loss function, obtain the final total loss function;Physical information neural network is trained based on the final total loss function, and the trained physical information neural network is obtained;Based on the trained physical information neural network, the target submarine pipeline flow field is predicted, and the prediction result is obtained;Wherein, the prediction result includes the velocity component and pressure distribution of the flow field around the flow field.The application has higher prediction accuracy and reliability compared with the prior art when solving the problem of submarine pipeline hydrodynamic analysis.

This invention discloses a power system frequency prediction method based on coupled state recursive constraints and deep Koopman modeling. The steps include: acquiring simulated frequency data and performing data preprocessing to obtain local fast-changing frequency deviation signals; constructing phase space trajectory vectors through time-delay embedding processing; building a deep Koopman model; using an encoder to elevate the phase space trajectory vectors to the observable space; performing linear state evolution of the frequency state vectors in the observable space using a linear Koopman operator matrix; and projecting the observable space states back to the original state space using a decoder to output predicted values ​​of the local fast-changing frequency deviation data; constructing the total loss; acquiring frequency trajectory data output by grid-following and grid-connected equipment; and training the deep Koopman model; and obtaining the frequency prediction results based on the trained deep Koopman model. This invention can replace full-order electromagnetic transient simulation for rapid analysis in large-scale scenarios, improving computational efficiency.

The utility model provides an artificial intelligence control device for the operation process of a water transportation port. The artificial intelligence control device has various advantages. The positioning holes provide accurate reference for device installation, and installation efficiency and quality are improved; the water transportation port is used for controlling the connecting port and the nickel-plated jack, so that stable and reliable connection, corrosion resistance and water resistance are guaranteed. The APM processor can be controlled to quickly process sensor data, real-time accurate control is achieved, and the operation automation level is improved. And the data storage stores related data, so that subsequent analysis and operation optimization are facilitated. And the wireless communication module is controlled to realize remote monitoring and control, so that the management cost is reduced. The device adopts a multiple waterproof sealing structure, prevents moisture and dust from invading, protects an internal circuit, and ensures stable data transmission. Through real-time monitoring and accurate control, operation parameters can be adjusted according to actual conditions, the safety, efficiency and resource utilization rate of port operation are improved, the cost is reduced, and the overall competitiveness is improved.