57 results about "Data averaging" patented technology

Systems and methods are disclosed for assessing visual function of a user or patient. The systems and methods may contain steps, including: extracting data from an electrode site of a sensor; obtaining an average of the data across successive video presentations; applying a fast-Fourier transform to the average; determining a signal-to-noise ratio (SNR) of results of the fast-Fourier transform at tagged frequencies; determining a steady-state visual evoked potential (SSVEP) amplitude based on the SNR of the results of the fast-Fourier transform at the tagged frequencies; and determining a ratio of lower to higher spatial frequency SSVEPs to assess the vision function of the user.

The invention relates to the technical field of network communication, and provides a real-time data pushing method for binary format transmission data, and the method comprises the steps: S1, judging whether to start server pushing or not through a pushing decision engine; s2, when the server receives sensor data, converting the structured data into HTTP / 2 frames with priority marks through a binary encoder; s3, scheduling an HTTP / 2 frame transmission sequence through a flow controller according to a current network state, wherein the current network state at least comprises a data volume which can be currently received by the client; and S4, after receiving the HTTP / 2 frame, the client sends a preset confirmation frame to confirm receiving according to the HTTP / 2 frame serial number, and if the server does not receive the preset confirmation frame within the preset timeout time, the server marks that the HTTP / 2 frame is lost and re-uploads the HTTP / 2 frame marked as lost. Compared with WebSocket, the method has the advantages that the protocol overhead is reduced, the transmission efficiency is improved, the average delay of key data is reduced, and the method is compatible with the existing HTTP / 2 client.

Embodiments of the present application disclose a resource selection method, device, equipment and storage medium. The method is applied to a V2X terminal, and comprises: receiving data to be processed issued by an upper layer application; if a current time meets a search condition, determining whether the data to be processed in a search period before the current time meets a Poisson distribution; if the data meets the Poisson distribution, taking a data average receiving time corresponding to the Poisson distribution as a resource selection period, and performing periodic resource selection. The technical scheme of the embodiments of the present application can effectively select periodic resources, reduce the selection frequency of one-time resources, and improve the utilization efficiency of resources in the case that the time interval of data packets of the upper layer application is constantly changed.

The application relates to the technical field of data processing, and discloses an excel data batch processing method and related equipment.The method comprises the following steps: obtaining excel batch data to be processed, analyzing the excel batch data to obtain excel analysis data, and performing data volume statistics on the excel analysis data to obtain an excel data volume; a plurality of threads are created, and a queue corresponding to each thread is created according to the thread; the excel analysis data is equally divided according to the excel data volume to obtain a plurality of excel sub-analysis data, and the excel sub-analysis data is evenly distributed to the normal queue for processing; and the method can improve the document processing efficiency.

The invention relates to a city development talent demand prediction method and device, and a storage medium. The method comprises the following steps: selecting city research time nodes, input elements and output elements; collecting corresponding input element data and output element data of the city at the research time node; based on the input element data and the output element data, adopting a Cobb-Douglas production function to determine the output elasticity of each input element of the city; determining marginal output data and average output data of each input element according to the output elasticity; drawing a total output curve, an element marginal output curve and an average output curve of the city according to the total output data, the marginal output data and the average output data of each research time node of the city; according to the curve position relation, the urban talent development stage is determined, and a prediction result of the talent demand is generated. According to the method, the effects of capital, labor force and technical progress factors in the production process are described from the macroscopic perspective, and the influence of the talent number and quality on urban development is quantified.

The invention relates to the technical field of flood prevention and drainage, and discloses a printing and dyeing drainage state analysis method and system based on sensing data, and the method comprises the steps: obtaining drainage data and generating a curve through deploying sensors which are distributed at equal intervals in groups in a printing and dyeing drainage pipeline; matching the upstream curve by taking the middle / downstream data as a template, and calculating a time difference discrete value to identify sensing abnormality; and according to the upstream data average value, matching an execution instruction, performing hierarchical control on single drainage treatment equipment, multiple drainage treatment equipment in turn or all drainage treatment equipment is started, and performing corresponding pop-up window prompting, early warning or alarming. Meanwhile, environmental interference is corrected through multi-sensor data fusion, database parameters are dynamically optimized to adapt to the production cycle, pipeline undercurrent is recognized in combination with detection particles, and equipment parameters are monitored to early warn faults. According to the method, the printing and dyeing drainage monitoring accuracy and the equipment scheduling intelligence are improved, and the abnormity early warning capability is enhanced.

A method for determining a data average wind speed value point in the cross section of the air duct. The method includes using, by a controlling, monitoring, and analysis unit A, the air volume flowmeter set in a big data air volume measurement dynamic sensing device in the cross section of the air duct, uniformly distributing preset points in the cross section of the air duct in all-around, measuring the air volume under a monitored load value for each preset point, and calculating an data average value under the monitored load value. The method includes accumulating the wind speed values of all preset points, and dividing by the number of the preset points; and amplifying a data average wind speed error value of a set air duct, until at least one preset point falls within a range of the data average wind speed error value of the set air duct.

The present invention discloses a cache prefetching method for shortening the average response time of video data in a named data network, comprising: calculating the association relationship of video data by classifying the video data in the network, wherein the association of continuous video is calculated using the position of the video data, and the association of ordinary video data is calculated using the Apriori algorithm, generating a video data association relationship table, and recording the association relationship table in each cache node; a cache prefetching strategy, wherein when a video data request occurs, the name of the video data is obtained, and based on the type of the video data, the video data associated with the video data is found, and multiple prefetched video data are simultaneously sent to the intermediate node for pre-caching. The pre-caching strategy, wherein the CS of the cache node is divided into two levels, namely, a main cache and a sub-cache, wherein the data requested by the consumer is cached in the main cache and the pre-fetched data is cached in the sub-cache.

The application belongs to the technical field of transportation, and particularly relates to a traffic prediction method based on multi-graph gated convolution and Conv-LSTM. The DTWN similarity value filling module is used to calculate the similarity between time series, and the average value of K data with high similarity is taken to fill in the missing data, so as to ensure the integrity of the traffic data. The traffic data is decomposed into approximate coefficients and detail coefficients through DWT. The approximate coefficients reflect the long-term trend of traffic flow, and the detail coefficients contain short-term fluctuation information. Different models are combined to process the data obtained through DWT. The detail coefficients are processed through the multi-graph gated dilated convolution MGDCN to capture the short-term fluctuation, and the approximate coefficients are processed through the Conv-LSTM to capture the long-term trend. Compared with the existing traffic prediction model, the application can fully fill in the missing data, capture the short-term fluctuation and long-term trend of traffic, effectively reduce the error in traffic prediction, and improve the accuracy of traffic prediction.

The present invention relates to the field of three-dimensional scanning technology, and particularly to a method for determining the three-dimensional scanning distance and range under given precision conditions. Through systematic calibration tests and detailed data analysis, the precision of the three-dimensional scanner within a specified range at different distances is determined, reliable scanning parameter selection is provided, and it is widely applied in fields such as building surveying, industrial inspection, and cultural heritage protection. The present invention avoids the subjectivity and blindness of scanning parameter selection through a scientific parameter selection method, and at the same time improves the working efficiency of scanning operations. Multiple tests and data averaging reduce accidental errors, provide comprehensive data, clarify the influencing factors and laws of scanning precision, optimize the scanning process, improve the efficiency and the accuracy of the results, and solve the problem that limits the precision reliability of existing three-dimensional scanning systems in practical applications.

This invention provides an airflow measurement and correction system for non-uniform wind field ducts, comprising an airflow measurement system based on big data analysis and an airflow measurement system based on the average wind speed value of the data points, with airflow meters set at these locations. By setting up the airflow measurement system based on big data analysis and the airflow measurement system based on the average wind speed value of the data points in different cross-sections of the non-uniform wind field duct, the airflow velocity values ​​Fdps and Fpps are measured simultaneously. If the difference between Fdps and Fpps is large, the airflow measurement value is taken as Fdps, or the location of the airflow meter at the average wind speed value point is manually or automatically readjusted. The two systems complement each other and verify each other, accurately and reliably solving the problem of inaccurate and unreliable measurement of duct airflow by the geometric mean wind speed value in existing airflow measurement devices.

The invention belongs to the field of GPU multi-card interconnection communication, and relates to a full-exchange GPU communication method and system. According to the method, the data stored in each GPU is averagely divided into N blocks, and each block of data corresponds to a specific data block needing to be sent to the target GPU; constructing a data symmetric matrix, and determining a total communication round according to the total number N of the GPUs; in each round of communication, two-way data transmission is carried out between the two GPUs based on a pairing rule of a symmetric matrix; and through multi-round iteration, complete exchange transmission of all data blocks is completed, so that each GPU obtains a complete data set from all GPUs. According to the method, a connection topology scheme of the GPUs does not need to be changed at all, the symmetric matrix of the GPUs only needs to be generated according to the number of the GPUs, and the condition that the GPUs communicate with other GPUs at the same time is reduced under the condition that the data transmission quantity is not increased, so that the congestion possibility of the GPUs is reduced, and the communication performance is improved.

The invention discloses a magnetic circular dichroism spectrum and magnetic rotation dispersion simultaneous measurement method. Substituting test data of a magnetic circular dichroism spectrum and magnetic rotation dispersion simultaneous measurement device based on a time sequence polarization measurement method into a spectrograph CCD (Charge Coupled Device) receiving light relative intensity principle formula, establishing an equation set, and solving a normalized Stokes parameter average value of sample transmission light; and obtaining a test result according to the relationship between the magnetic circular dichroism and magnetic circular birefringence quantization parameters and the Stokes parameter. According to the test method disclosed by the invention, test results of two characteristics of the magnetic circular dichroism spectrum and the magnetic rotation dispersion of the material can be obtained in one test; the test principle is direct, the test method is simple, rapid and effective, the required device is relatively simple, the actual wave plate retardation function and the spectrometer polarization effect are considered, and a large amount of data is averaged; and the test result is idealized and high in accuracy. The test method is beneficial to integration of related test functions of the composite equipment, and is beneficial to popularization in the related scientific research and test technical field.

The application discloses a kind of task data processing method and system, first result data and its type are obtained after upstream node processing task data ends, center node sets corresponding type label for downstream node after obtaining first result data and its type, and the type label of downstream node is synchronized to upstream node, so upstream node can send specific type first result data to corresponding downstream node. Meanwhile, upstream node is sequentially sent first result data to downstream node, so downstream node can only process specific type data related to task. Compared with the method that upstream node needs to divide data to downstream node in prior art, in the present application, data is not needed to be evenly divided to each downstream node for processing each time, thereby reducing the number of network interactions and network IO occupation of upstream and downstream, and also reducing the amount of data received by center node from downstream node. In this way, the probability of network failure during task processing is reduced.

The invention relates to the technical field of solder paste management, and provides a solder paste multi-dimensional data fusion management method and system, and the method comprises the steps: creating a quality label corresponding to each batch of solder paste; continuously receiving temperature and humidity data from the temperature and humidity sensors in all the areas in the refrigerated cabinet, and preprocessing the temperature and humidity data to correct the temperature and humidity data which are higher than the data average value of all the areas but do not reach a preset abnormal alarm threshold value; calculating and updating a quality label according to the preprocessed temperature and humidity data, solder paste material characteristics and storage environment parameters; evaluating the sensitivity of each production task to the solder paste quality in the production process to obtain a sensitivity level; according to the sensitivity level and the updated accumulative microstress damage value, the solder paste batch is dispatched; and according to the updated accumulative microstress damage value, issuing a process adjustment suggestion to production equipment. The method has the effect of improving the management precision and efficiency of the full life cycle of the solder paste.

The present invention relates to the technical field of electronic digital data processing, and particularly relates to a method and system for monitoring the operating state of an injection molding device, including: collecting the multi-dimensional operating parameter time series of the injection molding device at different times, aggregating the parameters of the same dimension into a data set, and constructing an isolation tree based on each data set; after sorting the tree nodes of the isolation tree according to the data average value, assigning a tree node serial number to each item of data; regarding the combination of parameters of each dimension at the same time as a data point, calculating their degree of being in the same group by comparing the distribution relationship of any two data points on the isolation tree, and classifying the data points with a degree of being in the same group higher than a set threshold into the same group; calculating the degree of abnormality of the data points; if the degree of abnormality exceeds the set threshold, determining it as an abnormal data point and simultaneously sending out an alarm. The present invention solves the problem of low accuracy and reliability of state detection.

The invention discloses a secret key using method and device and a storage medium. The method comprises the steps that n data processing processes are created and used for conducting concurrent processing on data; obtaining n unused key files with the length of L from the key files with the total length of M according to the data average length L within a past period of time T, and sequentially and correspondingly distributing the n key files to corresponding data processing processes; and distributing the to-be-processed data to the corresponding data processing process for encryption processing. According to the invention, a segment of key is preset in each data processing process, so that the data processing process can immediately execute encryption operation when receiving the to-be-processed data without waiting to request to distribute the key to a key file; particularly, under the condition that the length of the data to be processed is smaller than the length of the preset key, encryption can be completed by directly using the preset key, the encryption preparation time is remarkably shortened, and the real-time performance of data processing is improved.

The present application discloses a baseline processing method, an identification method, and a processing device for pulse signals. The baseline processing method includes: sequentially obtaining data of each sampling point in the pulse signal to be processed; obtaining the average value of the data of the current sampling point and multiple sampling points within its predetermined range; determining whether the data of the current sampling point is greater than the corresponding average value; if so, using the baseline value at the position of the previous sampling point as the baseline value at the position of the current sampling point; otherwise, obtaining the baseline value at the position of the current sampling point by using the baseline value of the previous sampling point, the data of the previous sampling point, and the hysteresis; wherein, the hysteresis is from the same source as the pulse signal to be processed and is related to the pulse signal after the baseline has been removed; subtracting the corresponding baseline value from the data of the current sampling point. By the above method, the baseline value obtained at the current sampling point can better follow the baseline, and at the same time, the computational amount in the process of processing the baseline of the pulse signal can be effectively reduced, releasing more FPGA computing space.

The application belongs to the field of smart meter fault detection, and discloses a smart meter fault diagnosis method based on distributed data set compression. First, the fault data of the meters at multiple sites is uniformly collected to generate a labeled data set, and then the data is evenly distributed to each client. The local model is trained to extract features and encapsulate information, and the representative samples are selected by the gain maximization strategy to maintain the distribution coverage and intra-class diversity. Then, batch normalization trajectory matching, multi-cropping and adversarial distillation are used to mine difficult samples and reduce the model difference by using soft labels to generate high-value compressed data. Finally, the fault diagnosis model is retrained on the integrated data, which significantly reduces the storage and transmission costs and improves the detection accuracy, providing an efficient solution for large-scale meter operation and maintenance. The method takes into account the safety and scalability, has great popularization value, broad prospects and significant benefits.

The application provides a health diagnosis method suitable for a GNSS receiver, and the method comprises the following steps: determining to-be-diagnosed sites, and acquiring calculation data and original data of GNSS receivers of each to-be-diagnosed site within a preset time period; acquiring a standard deviation of the calculation data of the GNSS receivers of each to-be-diagnosed site within the preset time period; acquiring a data average value of each quality parameter in the original data of the GNSS receivers of each to-be-diagnosed site within the preset time period; acquiring a correlation coefficient of each quality parameter and the standard deviation; acquiring quality parameters corresponding to the correlation coefficients in the top 50%; obtaining a normalized data average value of each quality parameter; and judging an influencing factor of GNSS receiver accuracy based on the normalized data average value of each quality parameter, so as to complete the health diagnosis of the GNSS receiver. The application can solve the technical problem that it takes too long to judge the authenticity of ground surface deformation by using manual work in the prior art.

The utility model provides a real-time and accurate air volume measurement system based on big data analysis, which comprises at least one big data air volume dynamic sensing device arranged in the cross section of an air duct of a non-uniform wind field, an air volume transmitter connected with the big data air volume dynamic sensing device, and a control monitoring analysis unit A for controlling and monitoring the big data air volume dynamic sensing device and the air volume transmitter. A big data air volume measurement dynamic sensing device is arranged in the cross section of the air duct of the non-uniform wind field, preset point positions are evenly distributed in the cross section of the air duct in an omnibearing mode, big data air volume measurement is conducted on the preset point positions, and the average air speed value of the cross section data of the air duct represents the actual air speed of the cross section. The problem that the geometric average wind speed value of an air volume measuring device in the prior art cannot measure the air volume of an air duct accurately is solved.

The present application discloses a method, device and electronic device for compensating the axle weight error of a dynamic weighbridge. After dividing the obtained effective axle weight data corresponding to the weighed axle into N segments, the method calculates the equivalent average slope corresponding to each segment of data, and then compensates the axle weight error corresponding to the weighed axle according to the relationship between these equivalent data average slopes and the axle weight data error compensation coefficient corresponding to the weighed axle. Since each equivalent average slope can reflect the influence of vehicle vibration on the effective axle weight data, therefore, the above method for compensating the axle weight error based on each equivalent average slope corresponding to the equivalent axle weight data of the weighed axle takes into account the main cause of axle weight error, which is vehicle vibration, and improves the accuracy of axle weight error compensation.

The invention discloses a method for processing data loss caused by frequency offset in request-system satellite data transmission, and belongs to the technical field of satellite communication. The two-channel modulator of the dual-channel request system satellite respectively sends request frames to the data processor, and the request frames are combined and then output to the solid-state memory; the solid-state memory sends playback data of a corresponding data frame number of a single path to the data processor according to the frame number of the received request frames; the data processor averagely divides the received single-path playback data into two paths, respectively performs data processing, and generates a full identification signal; after data processing is completed, the data are output to a two-channel modulator according to the number of request frames of the path; when the full identification signal of any one of the two channels is 1, request frame combination is stopped, and at the moment, the solid-state memory pauses data playback. By detecting the capacity of the cached data in the caches in the two coding processing units in real time, the problem of data loss caused by frequency offset of a modulator clock crystal oscillator in satellite request system data transmission is reliably solved in real time.

The utility model provides disinfectant blending equipment, which relates to the technical field of disinfectant blending equipment and comprises a disinfectant blending tank, a connecting pipe, a negative pressure sampler, a scale groove and a stirring spoiler, the device can directly sample the periphery of the inner cavity of the disinfectant blending tank through the negative pressure sampling pipe, and also can penetrate through the connecting pipe to extend to the middle of the inner cavity of the disinfectant blending tank for sampling, and the negative pressure sampling pipe extends to different depths of the inner cavity of the disinfectant blending tank for sampling by taking the scale groove as a reference; obtaining a data average value to obtain more accurate disinfectant concentration detection data; the stirring spoiler is used for spoiling disinfectant vortex stirred to the periphery in the inner cavity of the disinfectant blending tank, so that the concentration difference between the periphery and the middle part of the inner cavity of the disinfectant blending tank is reduced, the accuracy of average value data obtained by multiple sampling is further improved, and the current concentration of the disinfectant in the blending tank can be accurately judged.

The application relates to the technical field of flood prevention drainage, and discloses a printing and dyeing drainage state analysis method and system based on sensing data. The method deploys group sensors with equal intervals in a printing and dyeing drainage pipeline, obtains drainage data, and generates a curve; the upstream curve is matched with the middlestream / downstream data as a template, time difference discrete values are calculated to identify sensing abnormalities; according to the average value of the upstream data, an execution instruction is matched, and the drainage treatment equipment is controlled in stages to continuously work, to rotate and patrol in multiple sets or to start all together, corresponding pop-up prompts, early warnings or alarms are given. Meanwhile, through multi-sensor data fusion, environmental interference is corrected, database parameters are dynamically optimized to adapt to a production cycle, pipeline undercurrent is identified in combination with detection particles, and equipment parameters are monitored to give a fault warning. The method improves the monitoring accuracy of printing and dyeing drainage and the intelligentization of equipment scheduling, and enhances the abnormal early warning capability.

The present invention provides a detection method for identifying electricity theft based on cumulative probability distribution, including the following steps: Step 1: Obtain power consumption data; Step 2: Establish the probability distribution range of daily power scatter points of users; Step 3: Obtain the corresponding cumulative probability; Step 4: Establish the corresponding fuzzy matrix; Step 5: Calculate the density of all power data in the power dataset; Step 6: Calculate the average distance density value of the power consumption data; Step 7: Classify different cluster distances C X ; Step 8: End clustering when the clustering dataset is an empty set; In Step 9: Update the data center; Step 10: Obtain the cluster center sequence #imgabs0#; Step 11: Calculate the similarity of each cluster center; Step 12: Measure the similarity of the curves; Step 13: When the cumulative result is lower than η , it is considered that the user's power consumption is abnormal. Applying this technical solution can realize inferring whether there is an abnormality in the metering device or user electricity theft.

Aspects of the disclosure relate to using machine learning models to automatically deallocating overallocated database storage. A computing system may retrieve database state data that indicates current states of databases. Further, the computing system may retrieve average storage usage thresholds and peak storage usage threshold for the databases. The average storage threshold for the databases may indicate an average amount of storage used by each database. The peak storage usage threshold for the databases may indicate an amount of storage that is allocatable without causing an abnormal termination. Based on inputting the database state data, the average storage usage threshold, and the peak storage usage threshold into the machine learning models, an amount of overallocated storage of the databases may be determined. Further, the overallocated storage may be deallocated from the databases based on configurations of each of the databases.

The invention belongs to the technical field of oil-gas exploration and interpretation, and discloses a method for enhancing a geological object in a frequency domain based on target orientation. Comprising the following steps: selecting a seismic attribute data volume to be researched, denoising and carrying out energy equalization, carrying out channel-by-channel z transformation, selecting a geological target sample, carrying out data averaging processing, fusing Z-domain data of the attribute volume and average Z-domain data of the geological target sample, and carrying out reverse z transformation on the Z-domain data of the enhanced attribute volume. Different from a traditional time-space domain and frequency-space domain feature enhancement method, the invention provides a geological target enhancement method of a frequency domain, z transformation of a local geological target and z transformation of an overall geological environment are combined, and manual intervention is added, so that attribute enhancement processing is no longer blindly carried out, and an effect of instant effect is achieved.

The present application provides a distributed model training method for deep learning in edge computing, including: collecting data from the historical database of data to be classified to construct an initial data set; the initial data set includes a training set S and a test set Q, and the data in the training set S is evenly divided into N training subsets S i , using one-dimensional convolution to construct N training models based on the ResNet network, and initializing the model parameters; dividing the N training subsets S i data are respectively input into N training models based on the ResNet network for distributed training based on data parallelism; after each batch of data is trained, the model parameters will be aggregated to obtain optimized parameters, and the new parameters will be sent to each network for continued training; when the distributed training times of the training models based on the ResNet network reach a preset threshold, the model parameters are output to obtain the training results. The distributed model training method based on data parallelism in the present application can significantly improve the model training efficiency under the same model accuracy.

The invention relates to an imaging method and system for a dynamic enhanced magnetic resonance image with motion correction, and the method comprises the steps: carrying out the repeated continuous collection of a center K line in a K space in a layer direction through a radial collection mode of a star-shaped stacked golden angle, and obtaining the data of the center K line; and based on the sampling time sequence, averagely distributing the K-line data into a plurality of time amplitudes. One-dimensional Fourier transform is carried out on K-line data to obtain a projection contour, and three-dimensional information is projected to a layer direction. A motion information graph for generating K-line data is evaluated by utilizing a principal component analysis algorithm, and respiratory motion information is directly extracted without depending on gating equipment conditions. And according to the spatial position of the projection contour of each center K line in the graph, performing coordinate point rearrangement on each time frame motion curve, and then controlling a reconstruction model to perform continuous iteration by using a soft weighting low-rank matrix and the rearranged motion curve so as to reconstruct a reconstruction image under each motion state under each time frame. Additional motion dimension information can be provided while suppressing a blurring effect.