169 results about "Background data" patented technology

The invention discloses a water regimen data acquisition dual-machine redundancy method and system, and the system comprises a main machine and a standby machine which are directly connected through an independent heartbeat interface. The main machine periodically sends heartbeat messages and local network configuration information to the standby machine through a heartbeat interface; and the standby machine monitors heartbeat in real time, judges that the main machine is abnormal once not receiving the heartbeat within a preset time, automatically takes over the IP address of the main machine, actively sends an address resolution protocol message according to pre-stored network configuration information so as to quickly update a forwarding table of the network equipment, immediately switches the state of the standby machine to be the main state, and synchronizes the state to a database. According to the method, automatic sub-second fault switching is achieved, the risk of key data loss is greatly reduced, continuity and integrity of water regimen telemetering data are guaranteed, meanwhile, the operation load of a background database is remarkably reduced through a main and standby mode, and the reliability of water regimen telemetering is improved. The problems that the load of the database is too heavy and automatic seamless switching of network channel data acquisition cannot be realized are solved.

The invention discloses an in-vitro liquid level measurement method and device based on millimeter wave radar and a medium, and relates to the technical field of liquid level measurement, and the method comprises the steps: collecting geometric parameters of a container, building a container coordinate system, and forming static background data; the millimeter wave radar array is controlled to radiate millimeter wave signals in sequence, a receiving channel receives reflection echoes, amplification, frequency mixing, filtering and sampling processing are carried out, and array time sequence data are obtained; according to the array time sequence data, generating a distance direction frequency spectrum data set, combining static background data to carry out background deduction, executing an incident direction estimation algorithm, obtaining scattering point cloud under a container coordinate system, and generating a liquid level two-dimensional contour; based on the two-dimensional contour of the liquid level and the geometric parameters of the container, effective bottom surface grids are screened, the estimated value of the liquid volume in the container is obtained and converted into the equivalent liquid level height, and the final liquid level height is obtained. The two-dimensional fluctuation form of the liquid level is finely described, and the liquid volume and liquid level height measurement precision is improved.

The invention relates to the technical field of satellite communication, and discloses an efficient encoding and decoding and distribution transmission method for satellite image data, which comprises the following steps of: acquiring satellite epoch parameters, estimating a downlink channel capacity sequence, decomposing the image data into a basic feature code stream and a background residual code stream, and distributing a transmission priority, and mapping the basic feature code stream to the most significant bit of the modulation symbol, mapping the background residual code stream to the least significant bit of the modulation symbol, and implementing nonlinear displacement stretching on the coordinate of the constellation point where the modulation symbol is located according to the carrier frequency shift change rate. A core semantic bit phase tolerance boundary is expanded by compressing a background data judgment space, high-fidelity transmission of key image features in a severe phase distortion environment is ensured, and the information transparent transmission capacity in a high-dynamic link is improved.

The invention provides a POS application security signature system and method based on cloud service. The system architecture is clearly divided into a front-end service area and a high-security trusted area. The front-end service area is deployed in a special network management area which is logically isolated from the Internet and comprises a Web management background and a Web management background database; the high-security trusted area is a trusted environment, and an application signature server, an application signature server database and a hardware security module are deployed in the high-security trusted area. An application developer accesses the system through a controlled client environment. According to the method, responsibility separation of a submitter, a security officer and a key administrator is realized through role-based access control, hierarchical strong identity authentication is adopted, and a rigorous process is followed; a submitter verifies the hash of a file and then creates a task, the task data is synchronized to a high-security credible area after two security officers approve the task independently in sequence, and two key administrators execute dual control to start an HSM key to complete signature. The whole process operation is recorded in an auditing log which cannot be tampered. According to the invention, automation, high security and compliance of the cloud signature process are realized.

The invention discloses a crawling detection robot steel wire rope data acquisition and transmission optimization method and system, and the method comprises the steps: building a specification parameter-acquisition strategy mapping model based on adaptive steel wire rope specification parameters and a preset damage grade threshold value, and setting an acquisition frequency, a transmission connection parameter and a verification rule. After the robot is started, probe waveform and encoder position data are read in real time, acquisition frequency is dynamically adjusted, key defects and conventional background data are classified and marked, and position indexes are associated to generate original data blocks. Different types of data are packaged after being subjected to hierarchical compression and are transmitted to an upper computer in batches through a remote link, a check code is synchronously sent, and complete transmission or local retransmission is triggered according to a check result. The upper computer analyzes data, restores waveform and position information, automatically identifies defect points, generates alarm details and corrects time information, and supports real-time playback and report generation. The method enhances the comprehensive detection performance of the robot.

The invention provides a ground penetrating radar deep learning YOLO format sample automatic labeling method, comprising the following steps: S1, saving or saving road hidden disease ground penetrating radar artificial interpretation results in a unified data format, each ground penetrating radar data corresponding to an artificial interpretation result file; s2, reading ground penetrating radar data and corresponding artificial interpretation results, sequentially retrieving starting point coordinates and terminal point coordinates of each disease in the artificial interpretation results in the ground penetrating radar data, and delineating a ground penetrating radar data space corresponding to the road hidden disease; s3, taking a ground penetrating radar data space where the disease is located as a center, properly reserving surrounding ground penetrating radar data as a sample background, and intercepting disease data and surrounding background data as disease sample data; s4, self-adaptive gain adjustment is carried out; and S5, carrying out normalization [0 < 1 >] on the whole sample data space, calculating central point coordinates (x, y) of the disease and width and height of the central point coordinates, and automatically generating a ground penetrating radar deep learning sample conforming to a YOLO (Yttrium-Learning-Oriented Yttrium-Learning-Oriented Yttrium-Learning-Oriented Yttrium-Learning-Oriented Yttrium-Learning-Oriented) format.

Systems and methods provide for optimizing video review using motion recap images. A video review system can identify background image data of a video clip including an amount of motion satisfying a motion threshold. The video review system can generate foreground mask data segmenting foreground image data, representing a moving object in the video clip, from the background image data. The video review system can select a set of instances of the moving object represented in the foreground image data. The video review system can generate a motion recap image by superimposing the set of instances of the moving object represented in the foreground image data onto the background data.

The application discloses a nearshore disaster-bearing body disaster-causing path tracing method based on digital-analog experiments, relates to the technical field of ocean dynamic disaster simulation, determines the ocean dynamic disaster characteristics of a nearshore research area, integrates multi-source historical disaster data, real-time monitoring data and disaster-bearing body background data, and constructs a time-space correlation database; based on a three-dimensional ocean and a third-generation sea wave model, a nearshore storm surge-sea wave coupling numerical model is established and verified. Through the construction of the storm surge-sea wave coupling numerical model, the present application comprehensively considers the nonlinear interaction of multiple disasters, introduces an energy conservation equation to quantify the generation, transmission and dissipation process of disaster energy, solves the limitations of traditional single-disaster linear models, and combines the real-time feedback of the three-dimensional dynamic model of the disaster-bearing body to form a closed energy-damage correlation mechanism, significantly improves the tracing accuracy of the disaster chain propagation path, and ensures that the identification of key nodes and dominant paths is more consistent with physical reality.

The invention discloses a method and device for a webpage component to obtain background data, computer equipment and a storage medium. Specifically, the method comprises the following steps: receiving a data request of a front-end webpage; acquiring corresponding data of a background through an event bus according to a subscription theme of the data request; and distributing the data to a corresponding component of the front-end webpage. Through the method, the event bus can be used as a medium to provide background data for the components of the webpage end, and can be used as the components of the webpage end to uniformly send requirements to the event bus, so that corresponding data feedback is returned, and convenience and unification are realized.

This application relates to a method, system, device, and storage medium for preventing collisions when dropping precast beams using a precast beam lifting equipment. The method includes: correcting distortion in acquired image data using pre-calibrated camera intrinsic parameters; spatially registering point cloud data with image data using pre-calibrated camera intrinsic parameters, LiDAR-camera extrinsic parameters, and the corrected image; cropping the Region of Interest (ROI) of the point cloud data to obtain the cropped ROI region; extracting beam features from the ROI region, calculating beam displacement, and determining the collision risk level; and outputting the beam displacement and collision risk level. This application significantly improves the accuracy of beam boundary extraction. Furthermore, by cropping the point cloud region, background data is reduced, computational redundancy is decreased, and real-time alignment is improved. This embodiment does not require manual observation, greatly reducing safety risks and solving the technical problems of low accuracy and high safety risks in related technologies.

The application relates to the technical field of computing power cooperative scheduling management, and specifically discloses a cloud-edge-end heterogeneous computing power cooperative scheduling system and method based on intention driving, which obtains intention semantic vectors, video stream data, buffer occupancy rates and heterogeneous computing power state data, generates an intra-frame intention heat map by fusion when the buffer is overloaded, splits the video stream into core intention and non-core background data streams, and estimates computing power consumption. The computing power consumption is input into a game cycle model, intention retention rate and overflow risk are iteratively calculated, the feature retention range is reduced when the risk is too high, and secondary task computing power is borrowed for compensation when the retention rate is insufficient, until a double-optimal state is reached. The dynamic balance of system load and information value is achieved. Finally, a scheduling decision matrix is generated, the core intention original drawing is transmitted, and redundant background is discarded, effectively solving the problem of key information loss in a resource-limited scene, and significantly improving the response efficiency and business fidelity of the cloud-edge-end cooperative system.

The application discloses a high-definition playing method based on video background separation, comprising the following steps: S1, a streaming module pulls original data and sends the original data to a transcoding device; S2, the transcoding device performs secondary compression on the received original stream, extracts background content in the original stream and makes the background content into SEI segments; S3, the transcoding device transmits the secondary compressed data to the streaming module, at this time, the streaming module comprises the original stream and the compressed stream; S4, if a user watches a real-time stream, at this time, the compressed stream is transmitted to a client through a streaming media device, the client detects SEI, re-integrates the SEI segments, restores clear YUV background data, and superimposes the clear YUV background data on each frame of data of the compressed stream, so that the compressed stream is played in a clear state; the compressed stream enters a recording module and is stored, and in the recording process, an index module detects SEI frames carrying background data in real time and records indexes in disk storage, and the indexes correspond to recording segments.

The invention relates to the technical field of Internet of Things, in particular to an electronic price tag management method based on a hardware-independent architecture, which comprises the following steps: S1, basic information of an electronic price tag is maintained in a digital store system, the electronic price tag is registered as an Alicloud IoT device, and the basic information comprises a hierarchical relationship among a shelf, a shelf layer, a guide rail, an RFID and the electronic price tag device; s2, receiving a commodity information updating request through the abstract interface layer, selecting a corresponding supplier adapter according to the ID of the electronic price tag equipment, and converting the commodity information into a standardized format irrelevant to hardware to obtain standardized commodity information; and S3, sending the standardized commodity information to an electronic price tag device through an Alicloud IoT platform, and monitoring a message processing state to ensure reliable transmission and final consistency of messages. Decoupling of a service system and specific hardware equipment is achieved, multi-supplier equipment can be managed in a unified mode, and reliable synchronization of mass price tag display content and background data is guaranteed.

This invention discloses a method for protecting the integrity of access control record storage based on commercial cryptographic algorithms, comprising: collecting access control records and concatenating them into complete record data A1 according to a predetermined format; calling a PCI-E cryptographic card and calculating the MAC value M1 of A1 using HMAC technology based on the SM3 national cryptographic algorithm, and storing A1 and M1 together in a background database; when it is necessary to verify the integrity of the access control record, reading the current record data A2 and the originally stored MAC value M1 from the background database; calling a PCI-E cryptographic card and calculating the MAC value M2 of A2 using the same algorithm; comparing M1 and M2, if they match, the record is determined to be complete; if they do not match, the record is determined to have been tampered with and an alarm message is generated. This invention has the advantages of high security, strong compliance, superior performance, and good economy, and can be widely used in access control systems with security levels of Level 3 and above.

The application discloses a low-power self-organizing network positioning method based on Bluetooth quick pairing, and relates to the technical field of self-organizing network Bluetooth locators, and specifically comprises the following steps: first, the locators are divided into nodes and master locators, key parameters are configured, and the locators are deployed in an area; a positioning node sends a broadcast, a master locator selects a connection according to signal strength and an area position, and a Bluetooth self-organizing network is formed; the positioning node is connected with a target device and signal strength data is collected, the signal strength data is regularly transmitted to the master locator, and is then collected to a management background; and the background combines the node position and the target device distance, and determines the target position by using a three-side positioning algorithm. The application draws lessons from the quick pairing technology of TWS earphones, optimizes a connection process, greatly shortens network forming time, meets quick deployment requirements, regularly transmits data by the positioning node, centrally reports by the master locator, reduces energy consumption and maintenance costs, and by using a model and a three-side positioning algorithm, combines background data processing, realizes positioning operation, and is applicable to positioning scenes of different scales.

The invention discloses an intelligent annotation and management system for image data of cultural collection, and relates to the technical field of electric digital data processing, the system comprises an annotation module and a management module, the annotation module extracts feature data from the image data of the collection, generates first annotation information according to the feature data, and sends the first annotation information to the management module; the first annotation information is adjusted according to the interaction data, second annotation information is obtained, the second annotation information, the feature data and historical background data are matched, third annotation information is obtained, the management module conducts synchronous retrieval on the image data, the feature data and the third annotation information, visual feature data and structural feature data are fused, and the visual feature data and the structural feature data are integrated. Multi-level labeling optimization is realized through regularized automatic labeling, quantitative correction and supplement by combining interactive data with a literature and blog knowledge base, and historical background association and conflict correction, and the collection image labeling quality is greatly improved.

The application provides a gun positioning management system, comprising: an electronic tag; a locator and a background data management platform, the locator comprising a reader module, a satellite positioning module, a motion state detection module, an alarm module, a control module and a communication module; the control module determines whether to send an alarm control instruction according to information detected by the reader module and / or the satellite positioning module and / or the motion state detection module; and / or, in the case that the control module determines to send the alarm control instruction, the control module controls the alarm module to send an alarm signal; and / or, in the case that the control module determines to send the alarm control instruction, the control module transmits the alarm control instruction to the background data management platform through the communication module, and sends an alarm instruction through the background data management platform. Through the technical scheme provided by the application, the technical problem that the position information of a gun cannot be monitored in time in the prior art can be solved.

An electric power spot transaction decision support system based on multi-dimensional market analysis relates to the field of electric power spot transaction, and comprises a display layer which supports complex interaction through a Web end, large-screen cockpit command center monitoring and small program mobile end access, and realizes interaction result multi-terminal output. The application layer is communicated with the display layer, comprises a market analysis module and is used for processing multi-dimensional external market data to generate standardized background data; a user side load prediction module generates a user load day-ahead prediction result through an ARIMAX model based on historical power consumption and external factors, predicts monthly power by combining multiple linear regression and other models, and dynamically allocates weights by adopting an error reciprocal normalization method; and the day-ahead price prediction module cleans and preprocesses data such as historical electricity prices, and outputs a result through multi-model price comparison evaluation. The bottom layer is integrated with a scheduling management system through a data interaction interface, is in butt joint with a power grid operation environment and supports efficient decision-making of energy business.

The invention relates to a big data analysis-based full-domain full-flow closed-loop control method for a mechanical extraction time rate, belonging to the technical field of oil and gas field big data application and industrial automation control, and comprising the following steps: S1, collecting data by a well stopping alarm instrument; s2, performing data management; s3, carrying out data classification; s4, carrying out influence factor identification; and S5, carrying out platform management and control. Comprising the following steps of: 1, acquiring a motion signal of the oil pumping unit by adopting a well stopping alarm instrument, uploading the motion signal to a server through a special wireless channel meeting the requirements of a network, and entering a background database; secondly, the server removes bad data through a data cleaning program independently developed by a background, data management is completed, and effective data capable of truly reflecting the field operation state is formed; and step 3, carrying out classification statistical analysis on the characteristics of the data by utilizing a clustering algorithm. According to the method, the oil extraction time rate of the oil pumping unit is scientifically and accurately calculated and is used for guiding production, and the whole-process closed-loop control of the oil extraction time rate is realized.

The invention relates to a multi-model fusion surface water new pollutant tracing method based on causal inference. The method comprises the following steps: collecting monitoring data and environmental factors of new pollutants to obtain a result variable group Y through a hydrodynamic force-water quality model; inputting social economic and environmental background data, and obtaining a covariable group W through a machine learning model; calculating a correlation coefficient matrix of a pollution source component spectrum analyzed by the receptor model and theoretical pollution discharge intensity of each industry, and then constructing a processing variable group T; and Y, W and T are imported into the causal inference machine learning model to trace the new pollutants. The device comprises an acquisition module, an input module, a calculation module and an import module. The invention further comprises electronic equipment and a storage medium. According to the multi-model fusion surface water new pollutant tracing method and device based on causal inference, the electronic equipment and the storage medium designed by the invention, the problems of data scarcity, insufficient quality, insufficient model adaptability and interpretability and insufficient causal inference and correlation analysis during new pollutant tracing can be solved.

The invention provides a method for cooperatively detecting an air leakage channel and a high-temperature point of a composite goaf based on a tracer gas and radon measurement technology, and relates to the technical field of coal mine ventilation and mine fire prevention and control, comprising the following steps of: arranging at least two monitoring points on an air inlet side and an air return side of the composite goaf and on a roadway communicated with the composite goaf; according to the composite goaf air leakage channel and high-temperature point cooperative detection method based on the tracer gas and radon measurement technology, a plurality of monitoring points are arranged on the air inlet side and the air return side of a composite goaf and related roadways, a tracer gas sampling device and a radon measurement device are arranged on each monitoring point, and ventilation parameters of corresponding time periods are synchronously obtained. The tracer gas sampling device and the radon measuring device are arranged, radon baseline concentration data are collected under stable working conditions, radon background constraints are established, the gas mass mixing time period can be accurately recognized, the background data stability in the collection period is ensured, and a reliable data basis is provided for accurate detection of an air leakage channel and a high-temperature point.

The invention provides a construction method of a hypertension-cerebral hypoperfusion composite cerebral small vascular disease rat model. The construction method comprises the steps of experimental animal and grouping, hypertension model induction, cerebral hypoperfusion model induction and model evaluation system. According to the model, hereditary hypertension is replaced by 'L-NAME-induced drug-induced hypertension', and the model is combined with bilateral carotid artery occlusion surgery, so that clinical common hypertension and cerebral hypoperfusion dual pathological processes are successfully simulated. Compared with an SHR model, drug-induced hypertension is adopted to replace hereditary hypertension, and the method has the remarkable advantages in the aspects of period-cost-controllability-flux, 1, the modeling period is shortened to 8 weeks, and about 2 / 3 of time is saved; (2) the cost of a single animal is less than 1 / 3 of that of SHR, and the method is suitable for large-sample and multi-batch research; (3) the dosage of the L-NAME is adjustable, and the two-way intervention research of'hypertension driving 'and'blood pressure normalization' is supported; background data of the SD rats are complete and sufficient in supply, and multi-center repeated experiments are facilitated.

The invention relates to a teaching agent system based on a large scene model, and the system comprises a physical layer which comprises a SkillLink workstation for students to log in and carry out the operation training, and the SkillLink workstation records the operation training data and uploads a result file; the operation and maintenance support layer comprises a teaching task management system and a teaching agent, the teaching task management system is provided with a school terminal, a teacher terminal and a student terminal, the school terminal is correspondingly provided with a school account, and the school account can set a teacher account and a student account and configure operation authority by logging in the teaching task management system through the school terminal; the teaching agent performs technical evaluation on the result file uploaded by the SkillLink workstation and associates and sends an evaluation result to a corresponding teacher account and a student account; and the digital layer comprises a background database for storing the result file and the training data and a data statistical system connected with the background database.

This application provides a knowledge content recommendation and push method and related equipment. The method includes: acquiring user characteristics, including user data characteristics, content data characteristics, and background data characteristics; inputting the user characteristics into a knowledge content recommendation model to obtain a knowledge content recommendation table; and pushing knowledge content to the user based on the knowledge content recommendation table. The technical solution of this application, by inputting user-related data characteristics, content data characteristics, and background data characteristics together into a knowledge content recommendation model for comprehensive analysis, obtains knowledge content that better matches the user's interests and needs, forming a knowledge content recommendation table. Pushing knowledge content to the user based on this table can help users quickly find knowledge content of interest in an environment with a large amount of information, thereby reducing the time cost of information filtering.

A data storage device comprises recording heads and magnetic recording media. An initialization process is performed following a logical block address (LBA) remapping operation that remaps LBAs to physical locations on the media. The initialization process comprises initializing a write target LBA in response to a write command by writing data to a physical location on the media that is mapped to the write target LBA, receiving a read command to read data from a read target LBA, reading and returning data from the physical location on the magnetic recording media that is mapped to the read target LBA if the read target LBA has been initialized, and generating and returning a background data pattern if the read target LBA has not been initialized.

The invention relates to a natural experience strategy recommendation method and system and computer equipment. The method comprises the following steps: obtaining individual background information of a user; the individual background information is input into a preset natural contact strategy recommendation model, a recommended natural contact strategy is generated, and the natural contact strategy comprises sensory experience intensity, natural contact duration and environment characteristics; outputting a natural contact strategy; wherein the natural contact strategy recommendation model is a model obtained on the basis of a plurality of mutually independent prediction models and a multi-objective optimization algorithm, and the prediction models are obtained by training a machine learning algorithm on the basis of individual background data, sensory experience intensity data, natural contact duration data, environment characteristic data and healing index data; the plurality of prediction models are respectively used for predicting different healing effect indexes. By adopting the method, precise and personalized natural contact strategy recommendation can be carried out on different users.

Methods and systems for obtaining contextual information about a machine learning model are provided. The method includes: receiving raw data that is usable for training a model; training the by using the raw data; computing a set of common background data based on the raw data; computing a first explanation based on an output of the model and the set of common background data; computing, based on an output of the model, an agnostic model representation of the model; computing, based on the first explanation and the agnostic model representation, a deep, compact, and dense explanation-driven representation of the model; and determining, based on the explanation-driven representation, contextual information that relates to the model.

An image processing device includes an object detecting unit that processes captured image data representing a captured image, which is an image including an object or detection target and a background of the object, to generate processed image data representing a processed image, which is an image in which the object is detected; an expected-data generating unit that generates expected data representing an expected image, which a virtual image in which the object represented by an attribute is placed at a position on the background on the basis of object data representing the position of the object and background data representing the background; and a detection-result determining unit that compares the processed image data and the expected data to determine whether or not the object is detected correctly in the processed image data.

The application discloses a kind of digital twin multi-path reading and writing equipment to realize the system and method of data two-way communication, system includes: front-end data receiving module, front-end data unified processing module, front-end message event interaction module, front-end data distribution module, background data receiving module, background data unified processing module, background message event interaction module and background data distribution module, by front-end data receiving module and background data receiving module simultaneously receiving processing data, module can be directly handled by itself, and the data that cannot be handled is handled by other modules that can be handled and then distributed, front and background cooperate, jointly receive processing distribution data, the system can quickly, simply, effectively solve the data communication problem of digital twin equipment diversity, realizes the real-time data response of digital twin system, and has good scalability and maintainability.

This application provides an infrared detection result correction method, apparatus, electronic device, and storage medium. The method includes: acquiring a grayscale image generated from the thermal radiation signal received by the photosensitive area of ​​the infrared detector and the corresponding ambient temperature; determining a target temperature drift coefficient set and target background data corresponding to the ambient temperature based on a pre-calibrated correspondence between temperature, temperature drift coefficient set, and background data; for each pixel in the grayscale image, determining the corresponding temperature drift amount and reference grayscale value based on the target temperature drift coefficient set and target background data; and correcting the grayscale value of each pixel based on the temperature drift amount and reference grayscale value. By using pre-calibrated data and the temperature during infrared detection, the temperature drift coefficient and reference grayscale value of each pixel are determined, thereby correcting the grayscale value of each pixel to eliminate the influence of temperature drift without a baffle.