640 results about "Data combination" patented technology

The invention provides a fragment data cross-modal label generation system and method based on deep transfer learning. The method comprises the following steps: extracting first high-dimensional feature vectors in different modes; mapping the first high-dimensional feature vectors of different modals into the same semantic space through a cross-modal comparison loss function to realize multi-modal alignment and fusion to obtain second high-dimensional feature vectors; labeling semantic tags corresponding to the second high-dimensional feature vectors based on the fragmented data components by adopting a small sample transfer learning algorithm; a multi-channel Hash encoder is adopted, a self-adaptive encoding strategy is called according to different modal data combinations, and the second high-dimensional feature vector is encoded into a multi-channel binary Hash code; in combination with an incremental graph neural network, the binary hash codes and the corresponding semantic tags are dynamically expanded into the historical knowledge graph; matched fine-grained tags are established for semantic differentiation features of different entity combinations in the target knowledge graph, and a cross-modal tag tree is obtained by combining three-matrix hierarchical construction.

The invention relates to a vehicle suspension control method and device, computer equipment and a readable storage medium. The method comprises the following steps: combining obtained vehicle body dynamics time series data, vehicle control time series data and environment perception time series data in a vehicle driving process into time series data of multiple channels, determining a self-adaptive modal number of the time series data under each channel according to the time series data under each channel, and determining the self-adaptive modal number of the time series data under each channel according to the self-adaptive modal number of the time series data under each channel; and performing modal decomposition on the time sequence data based on the adaptive modal number, extracting frequency domain characteristics of the time sequence data, integrating the frequency domain characteristics of the time sequence data of the multiple channels, inputting the frequency domain characteristics into a trained suspension control parameter prediction model to obtain target time sequence characteristics for predicting suspension control parameters, and performing prediction on the suspension control parameters based on the target time sequence characteristics. Vehicle suspension control parameters are obtained through prediction, and a suspension system of the vehicle is controlled based on the vehicle suspension control parameters. By adopting the method, the risk of rollover of the vehicle can be obviously reduced.

Provided are system, method, and device for automatically enhancing future prediction using a reservoir transformer in a machine learning model. According to example embodiments, the system may include: a memory storage storing computer-executable instructions; and at least one processor communicatively coupled to the memory storage, wherein the at least one processor may be configured to execute the instructions to: obtain current input data representing a current state of a complex system; determine a plurality of readout data based on previous input data representing a previous state of the complex system using a plurality of reservoirs; combine the plurality of readout data to form an ensemble reservoir data; and determine predicted output data representing a predicted state of the complex system based on the ensemble reservoir data and the current input data using a transformer.

The invention belongs to the technical field of underground engineering, and discloses an omnibearing intelligent monitoring system, method and device for an underground anchoring pull-out test. According to the method, electromagnetic signals generated in the stress process of the anchor rod are captured in real time through an electromagnetic sensor, and internal stress changes and energy distribution are reflected; the deformation and stress states of the anchor rod in the dynamic environment are evaluated through a strain gauge and accelerometer combined data combination method, the deformation condition of the anchor rod is monitored through the strain gauge, and the stress-strain relation is recorded; an accelerometer is used for detecting the dynamic response of surrounding rock mass so as to evaluate the overall stability of the rock mass; a coupling medium is injected, the computer terminal stores the collected signals locally or in a cloud end and analyzes the signals, stress and deformation parameters in an anchor rod pull-out test are extracted, and an anchor rod stress cloud picture is generated in real time. According to the method, the safety and reliability of underground engineering are remarkably improved, and a new technical support is provided for evaluation of anchoring quality.

Certain aspects of the present disclosure provide techniques for wireless communication by a user equipment. The techniques include receiving, from a backscatter device, first backscatter data during one or more network entity downlink slots; receiving, from the backscatter device, during a network entity uplink slot immediately following the one or more network entity downlink slots, second backscatter data; and combining, at the user equipment, the first backscatter data and the second backscatter data to generate a backscatter data package.

The invention provides a multi-mode PDF (Portable Document Format) document analysis method, device and equipment and a medium, and the method comprises the following steps: loading a PDF document and carrying out preprocessing, including page splitting and content cleaning, to generate standardized document data; dynamically extracting contents in the standardized document data, wherein the contents comprise paragraphs, pictures and table elements; processing the dynamically extracted pictures, including shielding meaningless pictures based on a preset rule, and analyzing picture contents by using a multi-modal model to generate readable picture information; processing the dynamically extracted table, including optimizing and merging the table structure into a single element format to generate structured table data; combining paragraphs, readable picture information and structured table data, converting the paragraphs, the readable picture information and the structured table data into a complete structured document format, and inserting in key positions to enhance coherence context description; and outputting the complete structured document format as a final analysis result. According to the method, the analysis precision and the knowledge extraction efficiency of the complex PDF document can be remarkably improved.

The invention relates to the technical field of flight management, in particular to a flight departure guarantee resource allocation scheduling optimization management method, which comprises the following steps: according to a runway, a running sequence and a time interval corresponding to a flight shift list, constructing a flight state diagram for the flight shift list in a preorder and postorder manner; determining the transfer cost of each state in the flight state transfer process by taking the maximum capacity and the minimum adjustment time interval of each node in the flight state diagram in a unit time period as constraint conditions, and sequencing the flights into a time-adjusted flight list according to the transfer cost; performing iterative solution by using the timing flight list, determining an optimal adjustment time interval in unit time, and determining an adjustment quantity in a unit time period according to the adjustment time interval in combination with time slot allocation; when the adjustment quantity accords with a preset constraint rule, performing data combination on the corresponding flights, and regarding the combined data as an output adjustment scheme; the efficiency and the performability of flight scheduling processing are realized.

The invention discloses an electrical equipment defect detection method, system and equipment based on multi-modal alignment, and particularly relates to the technical field of electrical equipment detection. Obtaining a spatial feature difference and a time feature difference between every two pieces of modal data; performing logistic regression processing on the spatial feature difference and the time feature difference to obtain an alignable coefficient between each two modal data, and determining a to-be-aligned data combination for electrical equipment defect detection based on the alignable coefficients; and performing data alignment on the to-be-aligned data combination to obtain aligned modal data, and performing defect detection analysis on the power equipment by using the time sequence model according to the aligned modal data to obtain a defect detection result of the power equipment.

The invention relates to the technical field of hydrological data processing, in particular to a water conservancy intelligent internet-of-things sensing method and system, and the method comprises the following steps: combining statistical data into a feature set based on hydrological monitoring data including flow, water level and rainfall information, judging whether the data accords with normal distribution, and generating a data distribution feature vector set. According to the method, the change trend of the data is captured through multi-level data distribution characteristic analysis, and the monitoring precision of the data exception is enhanced. In the prediction process, new data and weight adjustment are gradually fused, so that the model can adapt to environmental changes in real time, and the hydrological state in a future short period is accurately predicted. Besides, abnormal data can be identified in real time based on analysis of quantiles, potential problems can be quickly found, and state division of different levels can be carried out according to abnormal degrees. In sampling scheduling, the priority of data acquisition is adjusted according to a probability model of state transition, so that monitoring resources are efficiently configured.

The invention discloses an individual health risk dynamic assessment system based on multi-modal biological feature fusion, and relates to the technical field of medical health information processing. The method comprises the following steps: constructing a high / low-dimension data combination rule; dynamically adjusting the feature fusion weight according to the clinical feature importance weight and the medical efficiency value calculated by the detection time interval; a cost difference value formula is introduced to quantify the economical efficiency of combined evaluation and independent evaluation; calculating a health risk comprehensive coefficient of the monitoring scene by combining the health data credibility score and the index type / amplitude / duration weighted risk value; the risk level is rechecked through expert assessment or a secondary model, so that the assessment accuracy is ensured; updating the individual credibility score according to the evaluation result; and for the result exceeding the confidence interval, classifying and optimizing a feature fusion algorithm, a model parameter or a data combination strategy. The system realizes accurate, economic and real-time individual health risk dynamic assessment, and is suitable for scenes of chronic disease management, health intervention and the like.

The invention provides a component-level collaborative editing control method, which is applied to a multi-user collaborative editing control system, and the system comprises a plurality of front-end engines and a back-end server. A front-end engine obtains user editing operation data and a rear-end real-time version snapshot, component structure difference comparison is carried out, and a component operation list is generated; and performing component conflict judgment based on the operation list, merging and editing operation data according to a conflict judgment result and a preset conflict resolution strategy, generating processed version snapshots, sending the processed version snapshots to a rear end, storing the processed version snapshots by a rear-end server, and sending the processed version snapshots to each front-end engine. Compared with the prior art, the method has the advantages that the data transmission quantity and the load of the rear-end server are reduced by a lightweight architecture through the front-end component level difference comparison and the preset conflict resolution strategy, the rear-end server does not need to be frequently requested for conflict resolution and data merging, the response speed and the collaborative editing efficiency are remarkably improved, and the user experience is improved. And better user experience is brought to the user. The system has the same beneficial effects.

The invention relates to a PLC-bridging gateway internet-of-things automatic identification method, system and device and a medium. The method comprises the following steps: sequentially sending handshake detection signals to a plurality of PLC devices and receiving response messages; forming a candidate handshake data combination set, and completing handshake matching through a priority algorithm and an adaptive polling mechanism; verifying the response frame, analyzing the equipment information, and confirming the active state and communication parameters of the PLC equipment; generating a drive binding strategy according to a matching result, and distributing a session identifier for the drive binding strategy; generating a session identifier of the target PLC equipment, and updating a session routing table in the bridging gateway; and translating the industrial data collected by the target PLC device into an Internet of Things protocol data packet and uploading the Internet of Things protocol data packet to a cloud data center. According to the invention, automatic identification and rapid adaptation of various interfaces and protocols can be realized; the communication stability and real-time performance are improved through dynamic scheduling and route updating; uniform data uploading is supported, and efficient deployment of cloud analysis and the industrial Internet of Things is facilitated.

The invention discloses a multi-stage wind power abnormal data combination cleaning method, and belongs to the field of new energy power generation data processing. Aiming at the problems of various types of abnormal values of wind power original data, serious interference and low cleaning precision, and single anomaly detection means, easy missing detection and misjudgment and the like in the prior art, the invention provides a staged combined cleaning strategy, which comprises the following steps of: firstly, dividing equal interval sections of wind speed and power, and eliminating isolated point type anomalies in distribution by using double quartile analysis; a CFSFDP density peak value clustering algorithm is introduced, low-density anomaly clusters are mined according to a density-distance joint criterion, and the recognition capability of structural aggregation anomaly is improved through two rounds of clustering; performing segmentation modeling on a wind speed-power relation by using upper and lower envelope line fitting based on a function, and removing envelope outer drift type noise; and finally, complementing edge missing data by using an interpolation algorithm. According to the method, the systematicness, precision and adaptability of the wind power data cleaning process are remarkably enhanced, high-quality data are provided for subsequent power prediction and energy optimization scheduling, and the application prospect is wide.

The invention discloses a multi-granularity generation type video compression method, which comprises the following steps of: acquiring a video frame sequence, performing spatial-temporal characteristic decomposition, decomposing and mapping a video signal to three potential subspaces to obtain a first potential subspace representation, a second potential subspace representation and a third potential subspace representation, the second potential subspace represents space-time motion features in the video, and the third potential subspace represents high-frequency detail information in the video; and encoding the first, second and third encoded data to generate corresponding first, second and third encoded data, and combining the first, second and third encoded data to generate a compressed code stream. According to the method, the problem of unbalanced code rate distribution is effectively solved, and content self-adaptive efficient compression is realized; the multi-scale feature extraction capability is enhanced, the problem of sub-band matching mismatching is avoided, and the compression performance is improved.

The invention relates to the technical field of model testing, in particular to a model testing method and device and electronic equipment, and is used for solving the problems of long test data combination time consumption and low coverage rate of a model testing mode in the related technology. The multiple features are classified, a core feature set, a common feature set and an edge feature set are obtained, and the model can be a deep learning model; generating a test set of the model according to a differentiated data generation strategy of feature importance on the basis of the rule set of the service type adapted to the model, the core feature set, the common feature set and the edge feature set, and performing model performance test on the model by using the test set to obtain a test report; therefore, the efficiency of model algorithm testing is improved.

The application discloses a power equipment defect detection method, system and device based on multi-modal alignment, and particularly relates to the technical field of power equipment detection, and the technical points are as follows: the method comprises the following steps: in the collected visible light image, infrared image and ultrasonic signal, the spatial feature difference and the time feature difference between every two modal data are obtained; the spatial feature difference and the time feature difference are subjected to logic regression processing, the alignable coefficient between every two modal data is obtained, the to-be-aligned data combination for power equipment defect detection is determined based on the alignable coefficient; the to-be-aligned data combination is subjected to data alignment, the aligned modal data is obtained, and according to the aligned modal data, the time sequence model is used for defect detection analysis on the power equipment, so that the power equipment defect detection result is obtained.

The invention discloses a communication method and system for multiple battery modules, and relates to the technical field of communication methods, and the method comprises the steps: determining a corresponding short priority code according to first communication data and the current working state of an electric vehicle; and the target battery module and the remaining battery modules are determined based on the short priority code, the primary communication relationship and the current working states of the plurality of battery modules, so that the accuracy of the target battery module is improved, and the priority communication right of the target battery module to the first communication data is ensured. If the target battery module has the priority communication right and fails to read the first communication data, performing autonomous communication on the first communication data based on the remaining battery modules, and determining a combination of the battery module and the first communication data; the communication priority relationship of the plurality of battery modules is determined according to the previous communication events and the working states of the battery modules, so that the communication accuracy of the first communication data is improved, and the accuracy of the communication priority relationship of the plurality of battery modules is ensured.

The invention provides a multi-modal data archiving processing system based on cloud computing, and relates to the technical field of data processing, and the system is used for obtaining an archiving request and an archiving task, determining an archiving type, a processing priority and a task number according to the archiving request and the archiving task, recording a memory identifier, an execution path and a cache address of a processing node, and storing the memory identifier, the execution path and the cache address of the processing node; the method comprises the following steps: extracting a structured field group and an unstructured content block of an archiving task, mapping the structured field group according to fields to generate a structure reference table, segmenting the unstructured content block according to a time sequence to generate a content time stream, recording each field mapping and time segmentation operation, and determining a reference relationship between each field mapping and time segmentation operation and a processing node; and determining a task number, a resource state and a data fragment of each processing node to obtain state anchoring data, combining the structure reference table and the content time stream with the state anchoring data into a double-layer archiving component, and archiving the double-layer archiving component. According to the method, content backtracking and operation backtracking can be carried out on the multi-modal data archiving process.

The invention provides an electric power monitoring data general transmission method and system based on a Beidou short message, and relates to the technical field of electric power monitoring systems. The method includes; a substation collects power monitoring data of a power system, classifies and evaluates the power monitoring data, allocates priorities, and generates classified monitoring data with priority marks; the substation determines a data item value corresponding to the power monitoring data based on the priority mark, screens out a corresponding data combination when the transmission benefit is maximized, and encapsulates the data combination into a transmission frame with an LPDU frame structure, and the transmission benefit is formed by superposing the data item values corresponding to the power monitoring data contained in the data combination; the substation sends the transmission frame to the master station by using a self-adaptive transmission strategy model; and the master station performs intention analysis and intention verification on the transmitted power monitoring data, generates a control instruction and issues the control instruction to the substation. According to the invention, the problem of efficient data coding under the limited frame length is solved.

A system and a method for automatically assisting physicians during patient encounters includes transcribing and diarizing physician-patient interactions, extracting clinical concepts, and combining data with patient history data to provide suggestions to the physicians. A speech and gesture recognition module captures audio from patient-doctor interactions and transcribes the audio into text in real-time. A natural language processing module diarizes the transcribed text to attribute speech. A clinical concept extraction module identifies and extracts clinical concepts from transcription. A clinical recommendation module integrates real-time data with historical patient records and analyzes the combined data set to generate evidence-based suggestions to the physician. A physician's own historical data is validated to generate a unique profile for each physician. Interactions with the physician are analyzed to understand decision-making patterns. The physician's profile is updated and future physician decisions are forecast based on past behavior.

The invention provides an azimuth transverse wave remote detection data processing method, system and device and a medium. The method comprises the steps that an instrument is adopted to collect novel four-component transverse wave data (xx, xy, yx and yy) of a target well section; under a coordinate system (x, y) of the instrument, synthesizing an XX reflected wave signal with an angle defined relative to the x-axis direction of the instrument by using the orthogonal dipole four-component reflected signal, and defining the XX reflected wave signal as an angle when the reflected wave signal reaches the maximum amplitude; obtaining two cross component signals xy and yx by using novel four-component shear wave data (xx, xy, yx and yy), performing sliding windowing on the cross component signals xy and yx, performing Fourier transform on the signals in the window to obtain phase spectrums, and comparing the phase spectrums of the two cross component signals to obtain an actual phase difference; according to a novel four-component data combination mode, changing the orientation of the reflector, theoretically calculating the theoretical phase difference between the two cross component signals xy and yx, and establishing a rule chart of the cross component signals along with the orientation change of the reflector outside the well based on the theoretical phase difference; and judging the real azimuth angle of the reflector according to the rule plate.

The invention discloses a USB key identity authentication method, system and device based on a digital signature trusted chain and a medium, and belongs to the technical field of information security, and the method comprises the following steps: after a receiving terminal accesses a USB key, reading a digital certificate, collecting a device identifier, a network parameter and geographical location information, generating first environment abstract data through abstract processing, and signing; and the authentication server stores the abstract data after passing the signature verification. In the authentication request stage, the server generates random challenge data; the receiving terminal collects the current environment information to generate second environment abstract data, and the second environment abstract data is signed and sent again after being combined with the challenge data. And the server extracts the second abstract data after signature verification, performs similarity comparison with the first abstract data, and confirms that the identity authentication is valid when conditions are met. According to the method, the binding of the environment characteristics and the identity is realized, the protection capability of the U-type shield authentication system on counterfeiting, cloning and replay attacks is remarkably improved, and the credibility and the stability of an authentication result are enhanced.

A method for forming a prompt for use with a large language model includes receiving an input query, generating query augmentation data relevant to the query, wherein the query augmentation data includes one or more examples of queries and respective responses, wherein the query augmentation data is selected based on the input query, wherein the selecting of the query augmentation data is further based on characteristics of the large language model, and forming the prompt by combining the input query with the query augmentation data.

The invention discloses a federal category forgetting method based on label reconstruction and collaborative compression. The federal category forgetting method comprises the implementation steps that a client performs gradient matching optimization on samples randomly sampled from original data to obtain compressed data; after a forgetting request is received, reconstructing a local data label needing to be forgotten, and combining the data label with non-forgetting compressed data to form a forgetting training set; freezing the original model, finely adjusting an additional low-rank matrix by using a forgotten data set, regularizing by applying an F2 norm, and uploading the trained low-rank matrix to a server; and the server aggregates the low-rank matrix uploaded by the client and performs sparse processing, and then sends the low-rank matrix back to the client for training. According to the method, forgetting of forgotten category data is realized while remaining category performance of the model is kept, and calculation and communication overhead in a federal category forgetting process is greatly reduced.

The invention discloses a vertical superfinishing machine intelligent servo control method based on dynamic parameter identification, and relates to the technical field of servo control. Comprising the steps that first sensing equipment is arranged on a key motion axis of target equipment and used for obtaining vibration data of the motion axis, and vibration information items are obtained; and second sensing equipment is arranged on the oilstone unit, is pressure and temperature integrated sensing equipment and is used for acquiring real-time pressure data and temperature data of the oilstone to obtain a pressure information item and a temperature information item. According to the method, damage sorting is combined, low-damage combinations with different oscillation frequencies and feeding speeds are preferentially selected to serve as equipment execution, updating information of vibration information items, pressure information items and temperature information items is deeply obtained, secondary adjustment is conducted on initial information items, and the accuracy of the equipment is improved. Therefore, oilstone driving control based on dynamic parameter identification of vibration data, temperature data and pressure data combination is realized.

A computer-implemented method of performing robotic simulation and design may include performing a simulation where a robot interacts with a user, and generating sensor data indicative of the robot interaction with the user during the simulation. The computer-implemented method may include generating discussion data indicative of user feedback from the simulation, generating form data associated with the user feedback from the simulation, and combining the sensor data, the discussion data, and the form data in a multimodal signal. The computer-implemented method may include determining a design characteristic of the robot based on the multimodal signal, and augmenting a robot model to incorporate the design characteristic using a machine learning algorithm.

The invention discloses a peripheral tissue blood flow monitoring method, device, system, equipment, medium and product, and belongs to the technical field of medical data processing. The method comprises the following steps: acquiring an actual self-correlation data combination of peripheral tissue blood flow of a target object in a current sliding window, and simulating a self-correlation data generation process of the peripheral tissue blood flow based on a predetermined simulation model to obtain a theoretical self-correlation data combination; based on the actual self-correlation data combination and the theoretical self-correlation data combination, determining a first root mean square error relative mean value for the self-correlation data; determining a predetermined blood flow index data combination corresponding to the actual autocorrelation data combination, and determining a second root mean square error relative mean value based on the predetermined blood flow index data combination; according to the first root-mean-square error relative mean value and the second root-mean-square error relative mean value, state description data of peripheral tissue blood flow are determined. According to the embodiment of the invention, the universality of the peripheral tissue blood flow monitoring method based on the diffusion correlation spectrum technology can be improved.

The invention discloses a five-axis numerical control machine tool machining control method and system based on visual inspection, and relates to the technical field of visual inspection methods. Multiple pieces of surface data of the machining surface of a workpiece are determined based on detection of a follow-up machining image at the current moment; the dynamic machining grade of the five-axis numerical control machine tool is determined according to the multiple pieces of surface data, the current machining data combination of the five-axis numerical control machine tool and the machining requirement of the workpiece, and the accuracy of the dynamic machining grade of the five-axis numerical control machine tool is improved; optimizing the current processing data combination of the five-axis numerical control machine tool based on the surface state gradient map, the dynamic processing grade of the five-axis numerical control machine tool and the corresponding processing efficiency; determining a dynamic repair event of the five-axis numerical control machine tool according to the machined surface of the workpiece, the surface repair tool of the five-axis numerical control machine tool and the current state of the five-axis numerical control machine tool, and determining a repair-machining synchronous control system according to the dynamic repair event of the five-axis numerical control machine tool, the current machining event and the dynamic stability coefficient of the workpiece.

A computing system is configured to (i) receive input data for a visual interface design, the input data including a target accessibility compliance standard and initial design data for at least two visual interface design elements, (ii) based on the input data, determine a respective set of operations to apply to generate accessibility-compliant design data for each of the visual interface design elements, (iii) apply each respective set of operations to the respective initial design data and thereby generate the accessibility-compliant design data for each of the visual interface design elements, (iv) combine the accessibility-compliant design data for each of the visual interface design elements to thereby generate composite accessibility-compliant design data for a composite visual interface design element, and (v) based on the accessibility-compliant design data for the composite visual interface design element, cause a visual representation of accessibility-compliant content for the composite visual interface design element to be displayed.

Systems for fusing arthroscopic video data are described. A system comprises an arthroscopic assembly, an inertial measurement unit (IMU) mounted on the arthroscopic assembly, a processor, and a processor-readable storage medium. An arthroscopic surgical plan, images from the arthroscopic assembly, and measurements from the IMU may be obtained. The images and the measurements may be combined to form a data combination. The data combination may be filtered to form a fused data set. The fused data set may control a device. A map of an arthroscopic surgical site may be created based on the fused data set, and a position of the arthroscopic assembly with respect to the arthroscopic surgical site may be calculated. The arthroscopic surgical plan may be updated based on at least one of the map of the arthroscopic surgical site and the position of the arthroscopic assembly.