331 results about "Ancillary data" patented technology

The invention provides a multi-source data fused SAR sea surface significant wave height deep learning inversion method, and belongs to the technical field of remote sensing ocean, and the method specifically comprises the steps: preprocessing buoy data, and obtaining sea wave significant wave height data observed by a buoy; acquiring dual-polarization single-view complex SAR data collected in an interference wide-width mode; preprocessing the SAR data, and taking significant wave height data obtained by buoy observation as a label of the SAR data; acquiring auxiliary data corresponding to the SAR data, wherein the auxiliary data comprises wind speed, wind direction data, rainfall data and OCN data; and constructing a multi-source data-fused SAR significant wave high-depth learning inversion model, training the multi-source data-fused SAR significant wave high-depth learning inversion model, and testing and verifying the trained model by using the test set and the verification set to obtain a final significant wave height inversion result. According to the method, the SAR data inversion capability of the model is improved.

The invention relates to the technical field of plastic extrusion molding control, and particularly discloses a self-adaptive energy efficiency steady-state control method and system in a plastic extrusion molding process, and the method comprises the steps: collecting multi-dimensional data of the plastic extrusion molding process, the multi-dimensional data comprises process data representing the current production state, aging characteristic data representing the equipment health degree and auxiliary data; and performing preprocessing and feature fusion on the multi-dimensional data, calculating to obtain an equipment aging comprehensive index, constructing an aging trend prediction model based on a long-short-term memory network, and outputting an aging trend prediction value and aging rates of the screw and the machine barrel. According to the method, multi-dimensional data are collected in real time, the equipment aging comprehensive index and trend prediction model is constructed, the multivariable coupling coefficient and the multi-objective optimization function are dynamically corrected, and self-adaptive energy efficiency steady-state control under the equipment aging condition is achieved.

A device to process data associated with a surgical event of a surgery may include a processor. The processor may be configured to receive multiple data streams during the surgical event. The processor may be configured to select a primary data stream based on a surgical data interface via which the primary data stream is received. The processor may be configured to select a secondary data stream based on a surgical data interface via which the second data stream is received. The processor may be configured to identify the surgical data interfaces. The processor may be configured to generate situational data associated with the primary data stream based on the secondary data stream. The situational data may indicate a medical decision-making factor of the surgical event. The primary data stream and the situational data may be sent during the surgical event.

The invention relates to a soil erosion amount dynamic monitoring method and system based on multi-source remote sensing data fusion. The method comprises the following steps: acquiring multi-source remote sensing data and auxiliary data, and performing geometric fine correction and atmospheric correction on an image based on high-resolution digital elevation data to obtain a data set with consistent space; performing inversion based on the data set to obtain a corrected terrain factor and a water and soil conservation measure factor; generating a time sequence rainfall erosivity factor and a time sequence vegetation coverage factor in combination with the multi-temporal satellite rainfall data; and calculating a preliminary soil erosion modulus in combination with the soil type map, and correcting by using multi-stage high-resolution digital elevation data to obtain a dynamic monitoring result of the soil erosion amount. By adopting the method, the problem of multi-source data fusion matching can be solved, and the factor inversion precision is improved, so that the accuracy of a dynamic monitoring result of the soil erosion amount is improved.

A wireless device receives, from a base station, a system information block (SIB) indicating time information for when a cell, provided via non-terrestrial network, stops serving an area. The wireless device receives, from a location management function (LMF), a provide assistance data message, for a multi-round transmission time (RTT) positioning, indicating at least one downlink positioning reference signal (DL PRS) resource. The wireless device starts a measurement period for measuring user-equipment (UE) reception-transmission (Rx−Tx) time difference measurements. The wireless device initiates, based on the time information indicated by the SIB, a satellite switch, wherein the satellite switch is to switch satellites without changing a physical cell identifier (PCI). In response to the satellite switch occurring during the measurement period, the wireless device suspends, during an interruption time for the satellite switch, measuring the at least one DL PRS resource.

The invention provides a multi-modal data acquisition and intelligent analysis application method based on AI glasses. The method comprises the steps that the AI glasses collect text data through a camera and an OCR assembly, collect image video data through a binocular camera and an infrared sensor, collect audio data through an array microphone, and collect auxiliary data through an I MU and an eye movement tracking sensor; according to the AI glasses, a local lightweight AI model is used for basic analysis, and complex tasks are uploaded to a cloud large model for cooperative processing, including information summarization, deep mining and knowledge extraction; the AI glasses realize real-time pushing, scene assistance and content generation and output through an information application module according to an analysis result; according to the AI glasses, an end-cloud collaboration module and a federated learning framework are adopted, a local cloud processing strategy is dynamically adjusted, only feature parameters are uploaded, and it is ensured that original data are locally reserved.

The present invention belongs to the technical field of federated learning. Disclosed are an efficient heterogeneous federated learning method and system based on hybrid distillation, and a device and a medium. The method comprises: a server initializing a global model parameter, and setting a preset total number of training rounds and the number of clients participating in each round of training; in each client, loading a corresponding local dataset, executing random transformation on the local dataset, and generating client distillation data; sampling several sub-networks from an original network of each client, training each sub-network on the client distillation data to obtain an updated local model parameter, and uploading the local model parameter to the server; and the server receiving the local model parameter, and then, in combination with a preset auxiliary dataset, performing server distillation, so as to obtain an updated global model parameter, and sending same to the client. The technical solution of the present invention can overcome the heterogeneity issue in federated learning, and can also improve the communication efficiency and robustness against attacks while avoiding privacy leakage.

The invention provides a cable terminal assembly and a cable terminal abnormal heating monitoring system, and relates to the technical field of power cables, and the method comprises the steps: collecting the operation data and environment auxiliary data of a conductor connection point, an insulating layer, a shielding layer and a grounding terminal in a preset monitoring period, and carrying out the time alignment processing, and obtaining the standardized multi-dimensional time series data. Time domain features are calculated, frequency domain features are extracted through fast Fourier transform, and the time domain features and the frequency domain features form single-dimensional time sequence features. Constructing a data association matrix, screening strong association data pairs according to Pearson's correlation coefficients and mutual information values, and calculating dynamic covariance by adopting a sliding window method to form cross-dimension association features. And splicing the two types of features and performing dimension reduction to obtain fusion feature vectors, splicing the fusion feature vectors of the current monitoring period and the previous monitoring period and the next monitoring period into a time sequence input sequence, and inputting the time sequence input sequence into an improved LSTM model to output an abnormal probability value, thereby realizing abnormal heating monitoring of the cable terminal.

The invention relates to a spacecraft maneuver detection method based on TLE data and kernel density estimation. The invention relates to the technical field of spacecraft maneuver detection. The method comprises the following steps: acquiring and inputting satellite historical TLE data; gaussian filtering denoising is carried out on the input data; based on the de-noised data, propagation forecasting is carried out through an SGP4 model; constructing a joint residual sequence, and carrying out error distribution modeling and sample scoring; determining a maneuvering threshold value, and judging to obtain abnormal data; and aggregating abnormal data and carrying out maneuvering identification. The method can still realize accurate and stable track maneuver automatic detection under the constraint conditions of unstable TLE data, complex error distribution, no external auxiliary data and the like. The method has good adaptability, robustness and interpretability, and is a track anomaly detection technical scheme which is complete in structure, rigorous in logic and capable of achieving engineering landing.

The invention discloses a contact network inspection data consistency verification method applied to 2C inspection, and relates to the technical field of railway automatic inspection. The method comprises the following steps: acquiring a 2C inspection image, and analyzing the 2C inspection image to obtain defect information; matching multi-source auxiliary data according to the defect information, and performing multi-source cross validation on the defect information based on the multi-source auxiliary data; firstly, defect information is obtained by analyzing a 2C inspection image, then multi-source auxiliary data with consistent time and space are matched for independent defect detection, confidence coefficients of consistent detection results are subjected to weighted fusion to obtain auxiliary confidence coefficients, and finally the auxiliary confidence coefficients and original confidence coefficients are subjected to weighted fusion to update the defect information; according to the method, through multi-source data collaborative verification, the problem of insufficient reliability caused by influence of a collection environment and an equipment state on a single 2C inspection image is solved, the probability of missing judgment and misjudgment of defects is effectively reduced, the accuracy of defect type recognition and the reasonability of confidence evaluation are improved, and more accurate data support is provided for overhead line system maintenance work.

The invention relates to a carbon sink quantification method and system based on multi-source data fusion and carbon flux large model inversion, and belongs to the technical field of meteorological monitoring, and the method comprises the steps: obtaining multi-source data of a target area and historical inversion data of a carbon flux large model; based on the ground carbon flux detection data and the historical inversion data of the carbon flux large model, performing dynamic calibration and parameter optimization on the pre-trained carbon flux inversion large model in the target region to obtain a region optimization model; inputting carbon-related data and meteorological and soil auxiliary data inverted by satellite remote sensing into the regional optimization model, and performing inversion to generate space-time continuous lattice point carbon flux data of the target region; based on the space-time continuous lattice point carbon flux data of the target region and the lattice point area of the target region, determining the actual carbon sink amount of the target region; and determining the net carbon sink increment of the target area based on the actual carbon sink amount of the target area, the carbon sink amount of the target area under the baseline scene and the carbon leakage evaluation value, thereby improving the carbon sink monitoring effect.

The invention relates to a bridge displacement multi-dimensional calibration method based on inclination angle sensing, and belongs to the technical field of bridge engineering monitoring. The method comprises the following steps: establishing a multi-dimensional displacement reference model based on a space-time coupling reference adaptive mechanism in combination with monitoring section space stress relevance and environment time evolution characteristics, and constructing a full-working-condition parameter mapping library; collecting real-time inclination angle data and multi-source auxiliary data, and generating effective sensing data through a multi-sensing space-time synchronization calibration mechanism; calculating a multi-dimensional displacement component based on the effective data and the reference model, and generating preliminary calibration displacement data through a multi-scale cross check and error traceability linkage mechanism; model parameters and calibration thresholds are dynamically adjusted through trend comparison, a full-working-condition parameter mapping library is updated through a closed-loop feedback mechanism, and displacement data, a change trend report and an error traceability result are output. According to the invention, the anti-interference capability and calibration precision of bridge displacement monitoring are improved, and reliable data support is provided for safety assessment of a bridge structure.

The invention relates to the technical field of remote sensing image processing, computer vision and three-dimensional modeling, discloses a monocular remote sensing image building three-dimensional automatic reconstruction method based on an improved UNet network and a multi-parameter coupling model, and aims to solve the problems that a traditional reconstruction method depends on DSM or laser radar data, and is poor in complex terrain adaptability and low in automation degree. According to the method, a single high-resolution remote sensing image serves as input, building and roof pixel-level segmentation is achieved through an improved UNet network fusing a channel-space-semantic three-mode CBAM attention mechanism and a resolution adaptive SMU activation function, and footprint regularization extraction is completed in combination with contour curvature constraint and Hough transform. And constructing an elevation inversion model based on the roof and footprint offset, the imaging geometric parameters and the terrain correction coefficient, and finally generating a three-dimensional white model through a CGA parametric modeling rule. Experimental verification shows that the average absolute error of the method is about 1.06 m (the mountain scene error is smaller than or equal to 1.2 m), the height error of more than 93% of buildings is smaller than 2 m, the method does not need to depend on additional auxiliary data, the process automation degree is high, the method is adaptive to complex terrain scenes, and the method can be directly connected with a smart city and a digital twin system.

Disclosed are techniques for wireless sensing. In an aspect, a sensing node receives, from a sensing server, a configuration for a sensing session to detect one or more target objects, the configuration including one or more parameters defining the sensing session. The sensing node receives assistance data for the sensing session, wherein the assistance data is determined from a digital twin model of an environment of the sensing node, and wherein the assistance data indicates one or more modeled signal quality metrics of reflections from the one or more target objects of one or more sensing signals to be transmitted by one or more transmitter sensing nodes during the sensing session and received at one or more receiver sensing nodes.

This application relates to the technical field of land subsidence early warning, and particularly to a method, apparatus, device, and storage medium for land subsidence early warning based on synthetic aperture radar (SAR). It includes: acquiring SAR images of a target detection area from the same satellite at different time points and generating time-series deformation data; fusing multi-source auxiliary data with the time-series deformation data to obtain a multi-source data feature set; dividing the multi-source data feature set into a training feature set, a validation feature set, and an input feature set; training and validating a land subsidence prediction model using the training and validation feature sets; inputting the input feature set into the land subsidence prediction model to output subsidence prediction data; updating the subsidence early warning threshold based on the subsidence prediction data and real-time hydrological data; and generating land subsidence early warning information for the target detection area based on the subsidence early warning threshold and the subsidence prediction data. This application improves the reliability and practicality of land subsidence early warning systems.

Some examples described herein provide for display image data reliability and safety, for example end-to-end safety methods, apparatuses, and systems for display systems. One example includes a method, including replacing video frames from input video streams with a set of test frames. The method further includes generating an alpha-blended video stream based on the set of test frames and the input video streams. The method further includes generating and inserting cyclic redundancy check (CRC) information for the set of test frames into secondary data packets associated with the alpha-blended video stream. The method further includes processing the set of test frames and video frames by a display controller to generate an output video stream. The method further includes performing an error detection procedure for the set of test frames using the CRC information to detect an error associated with the set of video frames.

The embodiment of the invention provides a data processing method and system.The data processing method comprises the steps that to-be-detected data associated with a target service is determined, the to-be-detected data comprises source end data and target end data, and end-to-end connectivity detection can be achieved based on the to-be-detected data and the source end data and the target end data contained in the to-be-detected data. And constructing a logic detection path of a user perspective of the target service and a transmission detection path of a service provider perspective of the target service based on the to-be-detected data. According to the method, the detection auxiliary data is acquired for the detection item of the target service, and path detection is performed on the logic detection path and the transmission detection path based on the detection auxiliary data to obtain the detection data, so that connectivity detection from the source end to the target end is realized, and an accurate detection result is quickly obtained. The detection data is analyzed in at least one analysis dimension, the analysis result is obtained, the analysis result can be the detection result displayed in the form of an analysis report, and the readability of the detection result is improved.

This invention discloses a method and network model for reconstructing missing soil moisture data based on cross-attention, belonging to the fields of remote sensing image processing and artificial intelligence. It involves collecting SMAP, ERA5-Land soil moisture products, and various auxiliary prediction factor data. The auxiliary data is resampled to 9km and preprocessed using multi-source data. A CASTNet model is then constructed. After inputting the preprocessed data into the model, feature extraction, refinement, and enhancement are sequentially performed through modules for spatiotemporal automatic completion, multi-factor feature refinement, and multi-scale attention enhancement. Finally, the model is trained based on a combined loss function composed of global and local losses, and the trained model is used to fill in the missing areas of soil moisture remote sensing data. The CASTNet model contains three cascaded core modules, each implementing preliminary spatiotemporal feature completion, multi-factor feature fusion refinement, and multi-scale feature enhancement, respectively. This invention fully leverages the complementary information of multi-source data, improving the accuracy of soil moisture data reconstruction and ensuring the spatiotemporal continuity and integrity of the reconstructed data.

The invention relates to the technical field of computer vision and natural language processing, in particular to a barrier-free drama-oriented real-time sign language-subtitle-voice three-dimensional synchronous generation system. Comprising a multi-mode drama content collection module, a drama semantic and emotion deep analysis module, a three-dimensional emotional content generation module, a millisecond-level synchronous calibration module, a personalized demand adaptation module, a multi-terminal output module and a feedback iteration module which are linked in sequence. The multi-mode drama content acquisition module supports offline theaters and online live broadcast / recorded broadcast scenes and can acquire line audios, actor performance data and scene auxiliary data, the deep binding of role personalization, plot emotion, scene atmosphere and barrier-free content is realized for the first time, the pain points of'action stiffness and emotion missing 'of a general system are solved, and the system has the advantages of being high in practicability and high in practicability. The sign language / voice / subtitle drama adaptation degree is improved to 95% or above, the overall time delay is controlled within 100 ms through a synchronous calibration algorithm and is far lower than the standard of 200 ms in the industry, and the drama continuity is guaranteed.

Aspects of the disclosure are directed to signaling, to a location server that receives an indication of radio access network (RAN) sharing status information associated with a communications network serving a user equipment (UE). In an aspect, the location server may receive the indication from the UE itself or a RAN node associated with the communications network. In an aspect, the location server may provide assistance data to the UE that is associated with a position estimation session of the UE and is based on the RAN sharing status information. Such aspects may provide various technical advantages, such as improved position estimation latency, accuracy, etc., based on the location server factoring the RAN sharing status information into the assistance data provided to the UE.

The invention relates to a big data information collection method. The method comprises the following steps: collecting retrieval data, browsing data, consulting data and auxiliary data of multiple users in an application system; invalid data removal and noise data filtering are carried out on the collected data, invalid data removal comprises null value and meaningless data removal, duplicate data de-duplication and format standardization processing, and noise data filtering comprises regular filtering and statistical filtering; and constructing an invalid and noise data judgment model based on the processed valid data and invalid and noise data. According to the method, through data preprocessing and double screening of invalid and noise data judgment models, invalid data and noise data can be effectively eliminated, so that the accuracy of data information collection is improved; through automatic judgment of invalid and noise data judgment models and an incremental updating mechanism, the models are continuously optimized along with data accumulation, the manual screening workload of data information collection can be reduced, and the misjudgment rate of automatic judgment is reduced.

Example embodiments of the present disclosure relate to a solution for ensuring consistency of artificial intelligence (AI) / machine learning (ML) processes. A method comprises receiving, from a second apparatus, first assistance information indicating at least one piece of first assistance data to be used by at least one transmission node; receiving, from the second apparatus, geographical change information of the at least one transmission node; performing a first machine learning (ML) stage based on the at least one piece of first assistance data to obtain a dataset and / or a model; and associating the geographical change information with the dataset and / or the model.

A vehicle may be modified to include a secondary data network forming a proprietary communication system used in the operation, maintenance, diagnostics, programming, and logistics of a mobility system. The secondary data network may be coupled to the vehicle's OEM CAN bus via a gateway module. The gateway module can receive and selectively recode data from the OEM CAN bus that is relevant to the mobility system and re-broadcast the recoded data on the secondary data. The gateway module may also receive and selectively recode data from the secondary data network that is relevant to the vehicle and re-broadcast the recoded data on the OEM CAN bus.

Example techniques for providing media assistance data in a telecommunications network (TCN) are described. The media assistance data is received by at least one of a user plane function (UPF) entity of the TCN and a user equipment (UE) connected to the TCN. The media assistance data includes application layer information. Based on the media assistance data, the UPF entity or the UE detects a set of PDUs and determines PDU set information corresponding to the session.

In some implementations, a device may obtain historical orbital data indicative of orbital movement of a set of satellites over a period of time, the set of satellites comprising at least a subset of satellites of the satellite constellation. The device may, for each satellite in the set of satellites, estimate a set of orbital parameter values by fitting an orbital model to the historical data of the respective satellite, wherein at least one orbital parameter value of the set of orbital values is common across a group of satellites within the set of satellites. The device may send assistance data to at least one mobile device, the assistance data indicative of the respective set of orbital parameter values for all satellites of the set of satellites.

The disclosure generally describes methods, software, and systems for integration of attribution reports and auxiliary data sources. Data including aggregated summary reports and event level reports is received from a first system. Additional raw affirmative action data related to the aggregated summary reports and event level reports is received from a second system. A matrix is created with rows for interaction events and columns for raw affirmative action data. Denoised aggregated counts and denoised event counts are determined from the received reports. The matrix fields are optimized by resolving conflicts between raw counts, denoised aggregated counts, and denoised event counts.

A communication method (400) and a communication apparatus (800), relating to the field of communications, which are conducive to reducing the data volume of auxiliary data received by a terminal device, reducing the complexity and power consumption of the terminal device, and saving signaling overhead. The communication method (400) comprises: a network device determines first auxiliary data, the first auxiliary data indicating information of at least one satellite corresponding to a first area, and the first area belonging to a cell of the network device (S401); the network device sends the first auxiliary data, and correspondingly, a first terminal device receives the first auxiliary data (S402); and on the basis of the first auxiliary data, the first terminal device receives a signal from one or more satellites among the at least one satellite (S403).

This disclosure provides a data processing circuit and a semiconductor memory. The data processing circuit includes a parallel-to-serial conversion module for receiving an initial data signal and performing parallel-to-serial conversion on the initial data signal to generate a data signal to be processed and an auxiliary data signal. The initial data signal is a parallel data signal, while the data signal to be processed and the auxiliary data signal are both serial data signals, with the auxiliary data signal delayed by one unit time interval compared to the data signal to be processed. A first driving module receives the data signal to be processed, enhances its driving capability, and outputs a target data signal to a data port. A second driving module receives the data signal to be processed and the auxiliary data signal, and when the potentials of the data signal to be processed and the auxiliary data signal are the same, performs de-emphasis processing on the target data signal. This circuit can reduce the impact of channel loss on signal quality.

Disclosed are techniques for wireless communication. In an aspect, a user equipment (UE) transmits, to a network entity, a Long-Term Evolution (LTE) positioning protocol (LPP) capabilities message, the LPP capabilities message including one or more capability parameters indicating capabilities of the UE to engage in a positioning session with at least one network node, the positioning session comprising an impulse radio ultra-wideband (IR-UWB) ranging procedure between the UE and the at least one network node, receives, from the network entity, an LPP assistance data message, the LPP assistance data message including one or more assistance parameters configuring the UE to perform at least the IR-UWB ranging procedure, and performs at least the IR-UWB ranging procedure based at least on the one or more assistance parameters.