18results about How to "Efficient analysis" patented technology

This disclosure relates to distributed hardware tracing. A computer-implemented method executed by one or more processors includes: monitoring the execution of program code executed by a first processor component; and monitoring the execution of program code executed by a second processor component. The computing system stores data identifying hardware events in a memory buffer. The stored events occur across processor units including at least first and second processor components. Each hardware event includes an event timestamp and metadata characterizing the event. The system generates a data structure identifying the hardware events. The data structure arranges the events in a time-ordered sequence and associates the events with at least the first or second processor component. The system stores the data structure in a repository on a host device and uses the data structure to analyze the performance of program code executed by the first or second processor component.

The application discloses a kind of electric vehicle travel feature construction methods based on double-layer clustering architecture, it is related to electric vehicle travel feature mining technical field, the method includes: constructing city benchmark feature library;The historical operation data of target electric vehicle is preprocessed, and travel segment is divided based on vehicle state change, and the basic information of each travel segment is extracted;Based on city benchmark feature library, construct unified multidimensional feature vector;Application double-layer clustering architecture, first layer clustering uses variation bayes Gaussian mixture model to cluster normalized single travel feature vector, identify micro travel mode, second layer clustering is based on user behavior portrait vector, using the division clustering algorithm of improved initial center point selection to the user group is grouped, identify macroscopic travel habit;When the amount of travel data newly accumulated reaches preset condition, update city benchmark feature library.The feature construction method of the application can realize cross-city, hierarchical fine description.

This application discloses a method and related equipment for confocal endoscope image processing, relating to the field of image processing. The method includes: inputting the image to be processed into an Inception V3 network and an SPP structure to obtain a first feature, a second feature, and a third feature; extracting a first spatial domain attention map, a first channel domain attention map, and a first mixed domain attention map corresponding to the first feature, the second feature, and the third feature, respectively; performing non-maximum suppression operation on the first spatial domain attention map, the first channel domain attention map, and the first mixed domain attention map to obtain a second spatial domain attention map, a second channel domain attention map, and a second mixed domain attention map; performing a fusion operation on the second spatial domain attention map, the second channel domain attention map, and the second mixed domain attention map to obtain fused features; and performing recognition based on the fused features and a target classifier to obtain a valid image.

The present application relates to the technical field of automobile emission testing, and specifically discloses a testing method for real-time determination of excessive fueling emission of a vehicle, which comprises collecting vehicle data by using a vehicle-mounted emission detection device; arranging the vehicle data to generate a corresponding fueling emission test condition set; sorting each fueling emission test condition in the fueling emission test condition set according to the order of fueling time; calculating the pollutant emission limit value under the single fueling amount in each fueling emission test condition and the final result value of the pollutant emission test during the fueling process; and comparing and determining whether the current corresponding fueling emission test condition is excessive according to the calculated pollutant emission limit value and final result value. The present application can solve the problem that the vehicle cannot be determined and warned in time when the vehicle fueling process causes excessive pollutants.

This application relates to the field of data transmission technology and discloses a method and apparatus for testing infrared data transmission based on LED light. The method includes: acquiring transmission test data from a data transmission system and analyzing the transmission environment to obtain a target transmission environment; calculating the encoding performance data of multiple LED light sources and the decoding performance data of an infrared receiver; performing network initialization settings on a spatiotemporal graph convolutional network; constructing an encoding-decoding performance relationship curve and performing feature extraction and feature normalization to obtain multiple normalized performance features; performing data transmission performance anomaly analysis through a data transmission performance analysis model to obtain data transmission performance anomaly evaluation indicators; and generating a target anomaly handling strategy based on the data transmission performance anomaly evaluation indicators. This application improves the accuracy of infrared data transmission testing using LED light.

A rare earth crystal observation method based on a deep learning model combined with a watershed algorithm, comprising the following steps: step 1: preparing a rare earth crystal structure image dataset, dividing the entire dataset into a training set and a test set; step 2: data augmentation is performed on the training set images; step 3: the improved Unet3+ deep learning model is trained using the training set, and the segmentation model is evaluated on the test set according to the image segmentation evaluation index, to obtain the final image segmentation model, which is used to predict the crystal structure image to obtain the original segmentation result image; step 4: for the original segmentation result image, a post-processing is performed thereon by using a watershed algorithm; and step 5: the final segmentation result image obtained after the post-processing in step 4 is observed, and the feature information of all connected regions is counted by using an OpenCV library. The present application can provide faster and more accurate crystal segmentation and statistical analysis.

This invention discloses a device and method for measuring the thickness of oil pipe couplings, as well as a method for analyzing the connection strength of oil pipe couplings, belonging to the field of oil-specific thread testing technology. The oil pipe coupling thickness measuring device includes a mounting bracket, a digital display, a movable probe with a displacement sensor, and a fixed measuring shoe. The fixed measuring shoe includes a movable frame and a measuring shoe head mounted on the movable frame. The movable frame is telescopically connected to the mounting bracket, and the measuring shoe head is used to position the thread of the coupling to be measured. The movable probe with the displacement sensor is used to radially abut against the outer diameter of the coupling during thickness measurement. The displacement sensor on the movable side measures the coupling thickness based on the displacement change of the movable probe. This invention solves the problem in the prior art that there is no device for directly measuring coupling thickness and that coupling connection strength can be analyzed through coupling thickness measurement, achieving efficient and accurate measurement of oil pipe coupling thickness and reasonable analysis of coupling connection strength.

This application discloses methods, apparatus, equipment, and media for interlaboratory quality assessment or data analysis in medical laboratories, relating to the field of medical laboratory testing technology. The methods include: generating a corresponding reference standard deviation based on randomly generated reference target values ​​and reference coefficients of variation; performing normal distribution random sampling to obtain reference reported values; linearly fitting the reference target values ​​and reference reported values ​​to obtain reference coefficients of determination; determining a new step size for the reference coefficient of variation to initiate a new external loop until the external loop ends; generating relative coefficients of variation based on the reference standard deviation; constructing a target mapping relationship matrix between each relative coefficient of variation and the reference coefficient of determination; determining the target relative coefficient of variation based on the target mapping relationship matrix and using the actual coefficients of determination of each actual sample; and obtaining the target sigma metric value using the target relative coefficient of variation, thereby obtaining the analytical and quantitative results of the actual interlaboratory quality assessment. This improves the accuracy and efficiency of interlaboratory quality assessment analysis.

The present application relates to the field of image processing, and specifically to an intestinal necrosis feature recognition system based on image analysis and a storage medium, wherein a computer program in the storage medium performs the following steps: obtaining medical images of a patient and dividing them into an expiration phase subset and an inspiration phase subset; performing spatial registration and motion artifact correction on the expiration phase subset and the inspiration phase subset to obtain multi-modal images; extracting a blood vessel obstruction feature, a perfusion injury feature and a cell necrosis feature in the multi-modal images; constructing a causal hierarchical relationship among the blood vessel obstruction feature, the perfusion injury feature and the cell necrosis feature based on an intestinal necrosis pathological mechanism; and determining a risk level of the patient having intestinal necrosis and a probability corresponding to the risk level based on the causal hierarchical relationship, the blood vessel obstruction feature, the perfusion injury feature and the cell necrosis feature using a random forest algorithm. The present application solves the problem of insufficient accuracy in recognizing intestinal necrosis features in the prior art.

The application discloses a kind of UN powder's quick preparation method, solve the carbon-thermal reduction-nitriding reaction method in prior art difficult to obtain high-purity UN powder, arc smelting method high cost, long cycle problem.A kind of UN powder's quick preparation method of the application, UO2 powder is reduced into metal uranium using metal reduction method, then using reaction heat makes metal uranium and nitrogen gas nitriding reaction, obtains UN powder.The application is more efficient, the reaction process is faster, more sufficient, UN production cycle is compared with arc smelting method greatly shortened, even shorter than carbon-thermal reduction method, can realize the batch preparation of high-purity UN powder in very short time.

Embodiments of the present application provide a method and device for constructing a server digital twin model and electronic equipment, wherein the method comprises: obtaining target device data transmitted by a basic input / output system of a server through a baseboard management controller of the server, wherein the target device data is device association information of a group of devices on the server described by using a structured markup language; analyzing the target device data through the baseboard management controller to obtain the device association information of the group of devices; and constructing a digital twin model according to the device association information of the group of devices through the baseboard management controller to obtain the digital twin model of the server. Through the present application, the problem of difficult data analysis and poor data readability in the related art method for constructing a server digital twin model is solved.

This invention relates to a non-targeted identification method for mycotoxin metabolites in wine based on mass spectrometry coupled with chromatography, specifically for the detection and identification of ochratoxin A and its metabolites in wine. Through sample pretreatment, chromatographic separation, mass spectrometry detection, data screening, and fragment ion confirmation of wine samples, non-targeted detection of ochratoxin A and its metabolites can be achieved without relying on standards. In the sample pretreatment stage, the target analyte is extracted using acidified acetonitrile solution, and impurities are removed by salting out and centrifugation. Separation of ochratoxin A and its metabolites is achieved by coupling high-performance liquid chromatography with time-of-flight mass spectrometry using a reversed-phase C18 column for gradient elution. The mass spectrometry analysis uses full-scan mode and alternates between positive and negative ion modes to ensure high resolution and high sensitivity, making it suitable for the detection of mycotoxins in wine and other foods, meeting food safety regulatory requirements.

This invention provides a data synchronization acquisition system and method for suspended tunnel experiments. The system employs a 10-gigabit fiber optic network, which includes a network layer, a software control layer, and an acquisition layer. The network layer includes 10-gigabit fiber optic cables, 10-gigabit switches, and fiber optic network interface cards (NICs). The software control layer includes a synchronization control terminal, a data server, acquisition clients, and a large display screen. The acquisition layer includes various sensors and lower-level machines installed in the suspended tunnel mechanism test environment. The synchronization control terminal sends data acquisition commands to the acquisition clients. The acquisition clients, upon receiving acquisition commands, send commands to the lower-level machines or sensors and provide feedback on the latest acquired data via the 10-gigabit NIC. Furthermore, the system is used to transmit the acquired data to the data server in real time and to synchronously transmit real-time image signals from the system to the large display screen. This improves the efficiency and stability of network transmission, providing fundamental support for synchronous acquisition control and real-time data storage.

The application discloses a new method for diagnosing shape quality of cold continuous rolling based on causal analysis, which comprises the following steps: reconstructing an attractor manifold according to two features in a same system to obtain a state space; reconstructing an attractor manifold again according to a feature time delay; finding a nearest neighbor point and calculating a nearest neighbor estimation; defining a CME score formula, calculating a CME score, judging whether the CME score converges to a constant or not, and if the CME score converges to a constant, it is indicated that a causal relationship exists between the two features. The application of the diagnosing method to diagnosing shape quality of cold continuous rolling can effectively monitor shape quality abnormality.

This application discloses a method for controlling the settlement of loess dams, comprising: identifying a first region in the loess dam body where the compressive stress exceeds a preset threshold; removing the loess in the first region; filling the first region after loess removal with gravel, the first region after gravel filling being called a gravel-mixed zone; and the loess dam containing the gravel-mixed zone being called a soil-stone composite. This method abandons the traditional method of relying solely on increasing compaction, and adopts the core concept of equal volume replacement. By directly replacing part of the compressible loess volume with rigid gravel particles, it physically reduces the total amount of compressible soil within the loess dam body. Furthermore, the stable framework formed by the gravel effectively bears and transfers the overlying load. This method fundamentally improves the soil structure, thereby suppressing settlement at its source.

This invention provides an automatic air quality monitoring terminal based on BeiDou positioning, comprising a device housing, a sensor module, a data acquisition module, a data display module, and a BeiDou positioning module. The sensor module collects air quality data, and the data acquisition module is connected to the sensor module to acquire the data. The BeiDou positioning module acquires the location information of the monitoring terminal in real time. The data acquisition module fuses the air quality data with the corresponding location information and transmits it to the data display module for display. By integrating BeiDou positioning functionality, this invention can accurately obtain the geographical location information of the monitoring point. Simultaneously, by combining various air quality sensors, it enables effective measurement and analysis of air quality-related parameters. It can be widely applied in atmospheric environmental monitoring, urban air quality assessment, pollution source tracing, environmental science research, and related environmental protection decision-making, providing important data support and technical means for ensuring air quality and improving environmental conditions.

This invention relates to a method for locating defects in forgings, aiming to improve the efficiency and accuracy of defect identification. The method first involves grinding the surface of the forging to ensure its smoothness and flatness. Next, an ultrasonic flaw detector with low-frequency and high-frequency emission capabilities is used to emit ultrasonic waves and acquire signals. Wavelet transform technology is used to process and analyze the acquired signals, extracting amplitude, phase, and frequency features to form a feature set. In the defect feature identification stage, feature vectors are constructed and input into a trained support vector machine (SVM) model, outputting the probability of various defects. The defect type is determined based on a set threshold; if the probability exceeds the threshold, the defect is considered to exist. Finally, samples are cut and subjected to tensile tests based on the detection results to confirm the defect characteristics. This invention combines wavelet transform and machine learning techniques, not only achieving precise location of forging defects but also improving detection efficiency, demonstrating promising application prospects and economic value.

The present application relates to a kind of highway photovoltaic power generation potential evaluation method and device based on unmanned aerial vehicle, method includes: by unmanned aerial vehicle, obtain highway along high-resolution multispectral image, laser point cloud and meteorological observation data;Data is automatically preprocessed and fused to generate feature dataset containing terrain, ground cover and weather information;Based on the dataset, the key factor that influences photovoltaic power generation is analyzed and quantified, and a standardized factor vector is formed;The factor vector is input into the prediction model constructed by the fusion of analytic hierarchy process and neural network, and the photovoltaic power generation potential of each evaluation unit and the whole road is calculated, and a visual evaluation report is automatically generated.The method effectively overcomes the problems of insufficient accuracy of traditional satellite remote sensing and low efficiency of manual survey, realizes efficient, accurate and comprehensive automatic evaluation of highway photovoltaic resources, and provides a reliable basis for photovoltaic project planning and decision-making.