16results about How to "Reduce time delay" patented technology

The application relates to a vehicle-end data processing method, a vehicle-end device and a vehicle-end data processing system. The method comprises the following steps: obtaining a target communication message in a communication line during vehicle operation; in the case that a current computing task is received from a cloud server, converting the current computing task into a current processing instruction; processing the target communication message according to the current processing instruction to obtain a current computing result, and uploading the current computing result to the cloud server. The method can realize real-time processing of the target communication message, reduce the time delay of data transmission to the cloud for processing, timely monitor abnormal conditions of the vehicle state, avoid leakage of vehicle-end privacy information, and ensure data security.

This invention relates to the field of high-altitude work equipment technology and discloses a method for reconstructing the flow field in a supersonic isolation section by integrating CNN and FCNN. The method includes the following steps: acquiring wall pressure data and schlieren image sequences in a wind tunnel test system; using synchronous light signals for time alignment and preprocessing; constructing a training dataset containing normalized pressure feature vectors and a matrix of real flow field schlieren images; constructing a parallel dual-branch deep learning model; using a convolutional neural network branch to reshape the pressure data into a matrix to extract spatial structure features; and using a fully connected neural network branch to directly extract numerical correlation features. The outputs of both are merged in a feature fusion layer. After optimizing the model parameters using the training dataset, the real-time acquired wall pressure is input into the trained model, and the reconstructed flow field grayscale image is output. This invention solves the problem of difficulty in reconstructing complex flow fields from sparse pressure data and achieves high-precision real-time monitoring of the flow field in a supersonic isolation section.

The invention discloses a parenteral nursing medicine formula optimization system based on data fusion, and relates to the technical field of parenteral nursing. Constructing an infusion amount change curve of different preparation components, performing time sequence alignment on the target physiological parameters and the infusion amount change curve, extracting a fusion feature vector, and inputting the fusion feature vector into a patient metabolism model to output a deviation index, extracting local fusion feature vectors of different preparation components, combining the local fusion feature vectors with the patient metabolism model to output a contribution index, generating an evaluation result according to the deviation index and the contribution index, updating model parameters in the patient metabolism model, and generating formula optimization suggestions; multi-source data can be integrated, the metabolic state of a patient can be monitored in real time, a medication formula is dynamically optimized, and the safety and effectiveness of parenteral nursing are improved.

Embodiments of the present application provide a vehicle-cloud collaborative perception defense method, electronic equipment, storage medium and program product. It relates to the technical field of vehicle-cloud collaboration. The method is applied to a vehicle client, a local model is deployed on the vehicle client, the local model is used for attack detection and active defense response, and the vehicle-cloud collaborative perception defense method comprises the following steps: feature extraction and reasoning are performed on multi-source sensor data by the local model to obtain a predicted logic value and a local prediction probability distribution corresponding to the predicted logic value; a variational free energy is calculated based on a global knowledge prior distribution received from a cloud server and the local prediction probability distribution; the variational free energy and the predicted logic value are sent to the cloud server, and a global logic value and a global prediction probability distribution returned by the cloud server are received; and parameter optimization is performed on the local model with the aim of minimizing a composite loss. The present application is used to improve the detection performance of the global model and enhance the effect of vehicle-cloud collaborative perception defense capability.

The application discloses a multi-transmit CPU instruction splicing method, comprising: an early splicing step, used for splicing instructions according to PC information and Fetch Group information predicted by a branch prediction part and writing the Fetch Group information into a Fetch Group queue in a fetch stage; and a read Fetch Group queue and then optimize splicing timing through multiple continuous time periods; a speculation splicing step, used for performing instruction splicing processing on the Fetch Group information to obtain a branch prediction result in a branch prediction pipeline and a fetch pipeline parallel process; wherein branch prediction information is given in stages in the first N cycles of the branch prediction pipeline; and the fetch pipeline dynamically updates the Fetch Group information according to the branch prediction information. The application performs instruction splicing preparation according to branch prediction information in the fetch stage in advance, and significantly reduces time delay in a subsequent processing stage. According to the length and transmission bandwidth of the Fetch Group information, the application dynamically adjusts a data reading and splicing method in multiple continuous time periods, and maximizes utilization of resources.

This invention relates to the field of intelligent manufacturing technology and discloses an artificial intelligence-based intelligent manufacturing production line collaborative control system, including a multi-source data sensing module, a digital twin virtual-real mapping module, a multi-agent collaborative decision-making module, and a human-machine interaction module. The multi-source data sensing module collects and preprocesses multi-source heterogeneous data across the entire production line, constructing a real-time database. The digital twin virtual-real mapping module builds a 1:1 high-precision digital twin model of the production line based on real-time data, enabling bidirectional real-time data interaction between the virtual and real worlds. It also determines the disturbance level of the production line by calculating multi-dimensional disturbance coefficients and introducing a time decay function to accumulate the effective disturbance influence coefficient. The multi-agent collaborative decision-making module matches and executes hierarchical collaborative control strategies according to the disturbance level, generating a comprehensive collaborative control scheme. This achieves accurate quantification and hierarchical collaborative response to production disturbances, significantly improving the adaptive capability and operational stability of the intelligent manufacturing production line.

Embodiments of the present application provide a data access method and device, electronic equipment and storage medium. The data access method is applied to a computer device. An operating system of the computer device includes a user-mode file system, an interceptor, a sandbox and a first cache area. The interceptor, the sandbox and the first cache area are all set in a kernel mode of the operating system. The method comprises the following steps: receiving data access information sent by an application program through the interceptor, and sending the data access information to the sandbox; acquiring target data in the first cache area and sending the target data to the interceptor through the sandbox when it is detected according to the data access information that the target data exists in the first cache area; the user-mode file system comprises a second cache area set in a user mode of the operating system, and the first cache area shares data in the second cache area; and returning the target data to the application program through the interceptor. The data access path can be reduced, the access delay can be reduced, and the data access efficiency can be improved.

The application discloses an image transformation method, system, chip and storage medium. The application improves the calculation performance by performing coordinate transformation on output pixel points in an output image in advance. Specifically, the corresponding target input pixel points are obtained by performing coordinate transformation on the output pixel points in advance, and the target input pixel points obtained by transformation are used to manage the local cache so that the corresponding target image data is stored in the local cache. Therefore, when subsequent target image processing is required for the output pixel points, the target image data corresponding to the output pixel points has been stored in the local cache, so it is not necessary to wait for the local cache to read and store the corresponding target image data from a storage entity, time delay is reduced, processing efficiency is improved, and the design index of high performance can be met.

The invention relates to the technical field of ship intelligent edge computing, and discloses a multi-source heterogeneous ship intelligent gateway edge computing method and system. According to the method, a heterogeneous data acquisition channel is established, a navigation state evaluation network is constructed, and a dynamic evaluation vector is generated; and the sampling frequency and the transmission priority of data acquisition are reversely adjusted according to the vector, so that closed-loop control is formed. Fusing the evaluation vectors of the ship and the adjacent ship to generate a collaborative situation awareness field; and dynamically allocating edge computing resources, and creating a special computing container. And processing the event data in the container, generating a structured risk snapshot, and comparing the structured risk snapshot with a historical mode to trigger early warning. And finally a standard report is generated and uploaded. According to the method, adaptive optimization of data acquisition and intelligent pre-allocation of computing resources are realized, and the resource utilization efficiency and the collaborative situation awareness capability are improved.

The invention relates to the technical field of thermal power plant safety monitoring, and particularly discloses a thermal power plant global Internet of Things safety monitoring system and method based on the Internet of Things. A data acquisition module acquires equipment operation data, environmental parameter data and personnel activity data in real time to generate a standardized data stream; the data analysis module executes multi-source data fusion analysis, identifies an abnormal mode and a security risk trend, and outputs a dynamic security state evaluation result; the safety evaluation module determines the comprehensive safety level of the whole domain of the thermal power plant and generates a safety evaluation report; and the early warning response module automatically triggers an early warning signal according to the comprehensive safety level determined by the safety evaluation module, and executes a response measure matched with the early warning level. The comprehensive integrated intelligent safety monitoring system is constructed based on the Internet of Things architecture, so that the overall safety monitoring level of the thermal power plant is improved.

The application provides a vehicle rescue management method and system based on a cloud platform and edge computing, and relates to the field of data processing.The method comprises the following steps: determining a vehicle rescue service station setting scheme and an edge computing configuration scheme of a target area according to historical vehicle rescue data of the target area, setting multiple vehicle rescue service stations in the target area, and setting multiple edge computing stations in the target area; determining a vehicle rescue resource dynamic scheduling scheme and an edge computing dynamic scheduling scheme according to real-time road information of the target area through a cloud platform; scheduling the multiple edge computing stations to determine vehicle rescue demand of the target area according to the real-time road information of the target area based on the edge computing dynamic scheduling scheme; receiving vehicle rescue requests through the multiple edge computing stations; and performing vehicle rescue through the multiple edge computing stations according to the vehicle rescue demand and the vehicle rescue requests of the target area, so that the vehicle rescue efficiency and quality are improved.

The invention discloses a physiological gating system for a nuclear magnetic resonance environment, and belongs to the field of human body physiological signal acquisition and nuclear magnetic resonance gating. Comprising a physiological signal acquisition module and a physiological signal processing module, the physiological signal acquisition module and the physiological signal processing module are both controlled by an FPGA, and data are wirelessly transmitted between the physiological signal acquisition module and the physiological signal processing module; the physiological signal acquisition module comprises an electrocardio acquisition module, a pressure sensor module, a photoelectric blood oxygen acquisition module, an acquisition module FPGA (Field Programmable Gate Array) and a wireless communication module; the physiological signal processing module comprises a processing module FPGA, a wireless receiving module and a gating output interface. The physiological gating system for the nuclear magnetic resonance environment has the beneficial effects that the physiological gating system for the nuclear magnetic resonance environment is provided, synchronous acquisition of three physiological signals of electrocardio, respiration and blood oxygen is realized, a multifunctional fusion gating strategy is adopted, and the imaging stability is improved.

A power management circuit and a display device are provided. The display device includes a display panel, a data driving circuit, a gate driving circuit, a controller configured to supply image data corresponding to a data voltage to the data driving circuit and to control the data driving circuit and the gate driving circuit, and a power management circuit including a plurality of voltage conversion circuits and a plurality of driving voltage supply circuits, each driving voltage supply circuit configured to supply a driving voltage to at least one of a plurality of sub-pixels, the data driving circuit, the gate driving circuit, and the controller based on an input voltage supplied from a corresponding one of the plurality of voltage conversion circuits. The power management circuit is configured to cause a first driving voltage supply circuit of the plurality of driving voltage supply circuits, which is configured to supply a first driving voltage to the data driving circuit, to be deactivated during at least one first sub-frame in at least one frame corresponding to the image data.

The invention provides a frequency-modulated continuous wave laser radar target information optical domain resolving system, which belongs to the technical field of laser radars, and comprises a signal generation unit used for generating a frequency mixing signal containing target distance and speed information; the optical loading unit is used for loading the frequency mixing signal to a first optical carrier to obtain a modulated optical signal; the optical frequency shift loop is used for performing fixed frequency shift and fixed duration delay on the modulated optical signal to obtain an optical pulse sequence; and the signal processing unit is used for detecting the time interval between the carrier wave and the sideband in the optical pulse sequence and resolving the target distance and speed according to the fixed frequency, the fixed time length and the time interval. According to the invention, the frequency mixing signal of the laser radar is processed through the optical Fourier transform technology, so that the calculation of the target distance and speed is realized, the processing delay of an all-optical calculation mode is lower, and the anti-electromagnetic interference capability is higher.

The invention relates to the technical field of speech semantics, and discloses a speech synthesis method and device based on dynamic style perception, equipment and a medium, and the method comprises the steps: determining a dynamic style context vector through a dynamic style perception model; predicting duration probability distribution of each target phoneme through a preset duration prediction model; generating a phoneme embedding sequence of each target phoneme based on a preset soft duration extension mechanism; and generating target synthetic voice information according to the stream matching acoustic model and the phoneme embedding sequence. Through the above mode, the dynamic style context vector is generated through the dynamic style perception model, and gradient propagation and collaborative optimization of the duration model and the acoustic model are realized through a differentiable soft duration extension mechanism. The method can be applied to the business fields of financial science and technology, medical health, old-age care and the like, and the voice information synthesis accuracy of the voice interaction system for different styles of scenes is improved.

The present application relates to the technical field of data processing, and more particularly to a power supply command guarantee data integration and emergency event disposal method and system, the method collects target multidimensional data through step S1, also integrates multi-source data and spatialized visualization through step S2, also accurately geographically correlates and maps multi-source heterogeneous data and the power grid one map through step S3, also upgrades the static command view to the dynamic calibrated intelligent operation map through step S4, also realizes the automatic identification and intelligent filtering of the power grid emergency event through step S5, also realizes the accurate matching of the emergency event and the surrounding emergency resources through step S6, also realizes the intelligent generation of the disposal strategy through step S7, also constructs the self-adaptive closed-loop optimization mechanism through step S8, and also continuously optimizes the resource matching and the scheduling rule through step S9.