21results about How to "Reduce processing delay" patented technology

This invention discloses an HPAM-DMT-NOMA method based on time-domain preprocessing, comprising: At the transmitting end, PAM modulation is performed on the input user transmission bits to generate PAM symbols; after power superposition, serial-to-parallel conversion, and Hermitian symmetry, the symbols are allocated to two signal components for HPAM-DMT transmission; the frequency domain signals of PAM-DMT and RPAM-DMT are calculated; an IFFT operation is performed to obtain the time domain signal; the time-domain preprocessed signal is calculated; the RPAM-DMT time domain signal is calculated and superimposed on the clipped PAM-DMT signal for synchronous transmission to obtain a mixed signal; a reconstructed signal is introduced, processed, and input to drive an LED for illumination; at the receiving end, the received signal is processed to generate a frequency domain signal, and finally, the multi-user signal is recovered. This scheme eliminates clipping noise interference between the mixed signal components, avoids error propagation problems, and achieves high spectral efficiency and power efficiency.

This invention discloses a requirement tracking method, apparatus, device, and medium based on a large language model, relating to the field of artificial intelligence technology. The method includes: performing hierarchical structure tracking and nested table linearization on the document to be processed, and semantically segmenting it; submitting each text block in parallel to a large language model to extract structured requirement items according to preset fields; calculating the cosine similarity between requirement items using an embedding model to recall a candidate matching set; then using the large language model to perform semantic association matching and coverage determination to obtain association mapping data; using the large language model to perform multi-level semantic matching on the requirement items, constructing a multi-level tracking link that supports cross-level matching between non-adjacent documents; and parsing the test item result description text and mapping it to a completed state when the link ends and contains a test document. This invention can improve the automation and accuracy of requirement item extraction, association matching, coverage determination, and full-link tracking, and enhance the fault tolerance of the tracking link.

This invention provides a perception fusion arbitration method and system based on vehicle-to-everything (V2X) communication. The method includes: acquiring a ground truth model of the perception system for the road environment and meteorological information; acquiring perception information and data quality parameters from each sensor in the vehicle-mounted perception system; retrieving the influence coefficients of each sensor corresponding to the meteorological information and calculating the perception quality score of each sensor based on the data quality parameters to determine the optimal sensor; selecting candidate arbitration ratios from a pre-set perception fusion arbitration ratio case library; performing simulated fusion calculations on the perception information; comparing the matching degree of each fusion result with the ground truth model of the perception system to determine the optimal arbitration ratio; and sending the result to the vehicle controller. This invention achieves adaptive output of the optimal vehicle-mounted sensor fusion weight ratio according to the specific meteorological environment, significantly reducing the perception misidentification rate in adverse environments such as rain, snow, fog, and sandstorms, ensuring the perception prediction accuracy of the autonomous driving system in all weather conditions.

The application discloses a dynamic charging coordination method, system, equipment and medium under open sea grid monitoring, relates to the technical field of open sea monitoring and energy management, and comprises grid dynamic division and equipment priority allocation; the light receiving efficiency is optimized by adjusting the inclination angle of the photovoltaic film, a task adjustment and energy management balance mechanism is constructed, and abnormal detection and cooperative response are carried out based on a multi-sensor fusion technology. The method disclosed by the application carries out grid dynamic division and equipment priority allocation, optimizes the grid boundary by using a hierarchical quadtree algorithm and real-time data, improves the utilization rate and monitoring accuracy of monitoring resources, optimizes the inclination angle of the photovoltaic film and the task energy management balance mechanism, improves the task completion efficiency while ensuring long-time endurance of the equipment, and accurately identifies complex abnormal events and quickly allocates response tasks based on the abnormal detection and cooperative response of the multi-modal sensor fusion technology, thereby improving the efficiency and intelligent level of the monitoring system as a whole.

The application discloses a data collection method and device, related equipment, a storage medium and a computer program product. The method comprises the following steps: an access network device receives first information sent by a first function, the first information is used for indicating that data related to a first task is collected, the first task is related to digital twinning, and the first function is used for processing at least user plane data; second information is sent to one or more terminals, the second information is used for indicating that data related to the first task is collected; first data reported by the one or more terminals is received, the first data contains one or more first vectors, and the first vector comprises a vector obtained by performing feature characterization on the collected data by the terminal; the received one or more first data and second data are fused and characterized to obtain a second vector, the second data contains data related to the first task locally stored in the access network device; and third data containing the second vector is sent to the first function.

The application discloses a data shunting method and device, related equipment and a computer readable storage medium. The method comprises the following steps: obtaining first information; the first information represents user plane information of at least one first user; the first information comprises at least one of the following: GTP-U tunnel identification information; IP address information of a UE; associating the first information with identity identification information of the corresponding first user to obtain second information; the second information represents association information of the first information and the identity identification information of the corresponding first user; and reporting the second information to a shunting device; the shunting device is used for shunting data by using the second information. In the application, the user plane information is dynamically allocated when a user logs in a network, and the user plane information needs to be dynamically allocated again when the user logs in the network again, so that the difficulty of obtaining the user plane information of a local user by an illegal user is greatly increased, and the security of a local application is enhanced.

This invention provides an obstacle segmentation method, apparatus, electronic device, and storage medium, relating to the field of target recognition technology. The method includes: acquiring translational and rotational extrinsic parameters of multiple sensing devices in a device coordinate system, wherein the multiple sensing devices are positioned on a device under test corresponding to the device coordinate system; the translational extrinsic parameters are determined based on the spatial position parameters of each sensing device in the device coordinate system, and the rotational extrinsic parameters are determined based on the attitude tilt angle parameters of each sensing device in the device coordinate system; calculating a global point cloud based on the translational and rotational extrinsic parameters, wherein the global point cloud is a stitched result of the point clouds of multiple sensing devices in the device coordinate system; performing ground segmentation on the global point cloud, removing the ground point cloud to obtain an obstacle point cloud; projecting the obstacle point cloud into a two-dimensional grid map, and determining the obstacles corresponding to the obstacle point cloud based on the two-dimensional grid map. This application can meet the stable perception requirements of autonomous driving systems in complex environments.

This application provides a method, apparatus, and network element for transmitting GTP-U messages. The method includes: a first user plane function sending relevant parameters of a GTP-U message to a first network function by invoking a service-based operation between the user plane and a first network function; by invoking a service-based operation once, relevant parameters of one or more paths or tunnels can be carried, which greatly reduces the overhead and resource waste of sending multiple GTP-U messages under multiple paths or tunnels, and can also reduce message processing latency.

The invention provides a mine micro-seismic background noise suppression method and system based on an FCN and a residual attention mechanism, and the method comprises the steps: carrying out the preprocessing of simulated micro-seismic data and actual measurement micro-seismic data, and constructing a training data set and a test data set according to the obtained noise-containing simulated image data and noise-containing actual measurement image data; constructing a hybrid deep learning model based on a full convolutional network FCN and a residual attention mechanism; training the hybrid deep learning model by using the training data set, the test data set and the composite loss function; and inputting to-be-processed noisy mine microseismic data into the trained model to obtain a denoised microseismic signal, and verifying the noise suppression effect of the model. According to the method, through cooperative processing of the convolutional neural network and the multi-head self-attention mechanism, homologous noise can be effectively separated, and efficient suppression of complex background noise in a microseismic signal is realized.

This invention relates to the field of the Internet of Things (IoT) for power systems, providing a collaborative reasoning method, system, and electronic device for power edge intelligence. The method includes: predicting the computational complexity of a task based on acquired task data by edge intelligent nodes; determining whether to offload the task to multiple edge intelligent nodes in an edge computing network for distributed collaborative reasoning based on the task's computational complexity; when determining to offload the task to multiple edge intelligent nodes for distributed collaborative reasoning, acquiring the status information of the currently available edge intelligent nodes in the edge computing network, and determining a task partitioning strategy among the currently available edge intelligent nodes based on the status information; offloading the task to the currently available edge intelligent nodes according to the task partitioning strategy; and completing the task's reasoning computation collaboratively through the collaboration of the currently available edge intelligent nodes. This invention enables power edge cluster collaboration, optimizing inference latency and load balancing.

Methods, apparatuses, devices, media, and program products for payment are provided. The method includes: in response to receiving a payment request from an agent, determining a matching degree between the payment request and intention description information, the intention description information being constructed based on natural language input triggering the payment request; and processing the payment request based on the matching degree. In this way, it can be judged whether the payment request initiated by the agent still belongs to the user's current task goal and task scope before the payment is executed, thereby supporting differentiated payment processing with a quantitative matching degree.

This invention relates to the field of computer data processing, and discloses a method and system for multi-agent task data processing. The method includes acquiring asynchronous task data submitted by other agents and evaluating its semantic completeness level. When the level does not reach a preset threshold, an interface template is matched from a historical abstract syntax tree template library and concatenated with the asynchronous task data to generate virtual branch context data for look-ahead inference. After acquiring structured supplementary data, real context data is constructed. If there are differences between the real context data and the virtual branch context data, the program dependency graphs of the two are extracted for topological comparison, the difference features are determined, local recalculation is performed, and the updated result is output. This invention solves the problems of ineffective computational resource consumption and excessively high cost of full recalculation in a single agent under semantic fragmentation.

This invention discloses a collaborative offloading method, apparatus, system, and storage medium for mobile edge computing networks, comprising: step S1, constructing a target optimization function based on a semantic-based task model, communication model, and computing model; step S2, optimizing the A-MAPPO algorithm using a multi-agent attention strategy incorporating an attention mechanism based on the target optimization function, thereby achieving joint optimization of offloading decision, semantic compression ratio, and bandwidth allocation. The technical solution of this invention can significantly reduce system task processing latency in extremely constrained scenarios, providing a complete and feasible technical implementation path for highly reliable, low-latency collaborative computing offloading services in resource-constrained MEC networks.

The application relates to the field of equipment state monitoring, and particularly discloses an oil depot pump set abnormality identification system and method, which comprises a multi-type data acquisition module, an adaptive threshold adjustment module, a multi-modal deep learning fusion identification module, an abnormality trend prediction module and a correlation decision support module; the multi-type data acquisition module is used for acquiring vibration signals, physical state signals of an oil depot pump set and characteristic parameters of an operation environment and a load where the oil depot pump set is located, converting the vibration signals into two-dimensional time-varying spectrum features, converting the physical state signals into standard time sequence data, and transmitting the standard time sequence data to the multi-modal deep learning fusion identification module; the technical scheme can reduce false alarm and missed alarm probabilities, realize deep fusion of data body features of multi-type sensors, and can guide maintenance decisions according to state monitoring.

The application discloses a packet data scheduling optimization system and method for value-based payment, and belongs to the technical field of data processing. The system comprises a data resource evaluation module, a data resource initial allocation module, a data resource scheduling module and a value-based payment processing module. The data resource evaluation module is used for obtaining resource demand of each data group. The data resource initial allocation module is used for obtaining a first data resource set. The data resource scheduling module is used for obtaining an expected decision instruction. If the expected decision instruction is normal processing, then the secondary scheduling data group continues to wait for processing according to a preset rule. Otherwise, the data resource secondary scheduling processing is performed to obtain a second data resource set. The secondary scheduling data group is a residual data group when the data resource initial allocation is performed. The value-based payment processing module is used for obtaining an audit result data after settlement. The application solves the problem that in the prior art, due to the static resource mode, resources are scattered and cut, and when a high complexity task appears, there is a lack of continuous resource bearing, thereby causing low overall data processing efficiency.

This invention relates to the field of IoT resource scheduling technology, specifically a computational resource scheduling method for IoT data acquisition platforms based on reinforcement learning. The invention constructs an IoT data acquisition platform, determines its state space, action space, reward function, and objective equation; introduces the Double DQN algorithm to construct a reinforcement learning network; and trains the reinforcement learning network to obtain the optimal intelligent scheduling scheme for computational resources. This invention utilizes the Double DQN algorithm to improve the task scheduling method of building IoT data acquisition platforms, significantly improving task scheduling efficiency, reducing processing latency, and effectively lowering the operating costs of building IoT data acquisition platforms.

The invention discloses a client selection and resource allocation strategy for the Internet of Vehicles, which is based on the combination of a Deep Reinforming Learning algorithm and a Federated Learning algorithm. The client selection and resource allocation strategy for the Internet of Vehicles is used for the Internet of Vehicles. The method comprises the following steps: firstly, constructing a three-layer collaborative architecture consisting of a vehicle, an edge server and a cloud server; and secondly, proposing an FLMADDPG algorithm which is based on the combination of Deep Reinformation Learning and Federated Learning and is used for a client selection and resource allocation strategy of the Internet of Vehicles, wherein the FLMADDPG algorithm is used for the client selection of the Internet of Vehicles and the resource allocation strategy of the Internet of Vehicles. And then, obtaining a client selection and resource allocation strategy based on an FLMADDPG algorithm. And finally, when the client is selected to participate in federal aggregation, personalized differential privacy noise is added to the transmitted model parameters.

The application discloses a kind of three-dimensional digital asset intelligent generation data processing method and system, the method includes: receiving multi-source data, respectively mapping as each source data corresponding feature vector, all feature vectors are weighted and fused, and generate structured latent variable vector.According to structured latent variable vector, generate sparse space unit set, establish local latent variable on each unit, calculate structure activation result according to local latent variable, and then determine the effective space unit set participating in three-dimensional structure construction.In effective space unit, generate material attribute vector according to corresponding local latent variable, and form three-dimensional asset intermediate result with structure activation result, combined with structured latent variable, execute local change detection, obtain to-be-updated space unit set.Perform local incremental update to to-be-updated space unit set, obtain updated three-dimensional asset result, carry out standardization packaging processing, to generate three-dimensional digital asset data package.

The invention discloses a portable miniature magnetic electrocardiosignal detection probe system, and relates to the technical field of biomedical engineering and weak magnetic signal detection. Comprising a miniature magnetic environment control subsystem, a weak signal acquisition subsystem and a real-time data processing subsystem, and the miniature magnetic environment control subsystem comprises a cylindrical miniature shielding cavity, a three-axis double-plane coil assembly and a measuring probe composed of a main measurement TMR sensor. The reference probe is composed of a cylindrical miniature shielding cavity, a three-axis double-plane coil assembly and a reference TMR sensor; the weak signal acquisition subsystem is used for acquiring measurement data of the main measurement TMR sensor and background reference data of the reference TMR sensor; and the real-time data processing subsystem is used for processing the acquired measurement data and background reference data to obtain a magnetocardiogram signal. According to the invention, a local low-magnetic-noise measurement space is constructed in the probe, the dependence on a large-scale building-level magnetic shielding room is reduced, and the availability in bedside and mobile scenes is improved.

This disclosure relates to the field of computer technology, and more particularly to a control method and apparatus for an embodied robot. The method includes: acquiring audio and video data collected by a collection device via a dedicated synchronous communication protocol for the embodied robot; processing the audio and video data and environmental perception data using a multimodal large model to obtain a data sequence; identifying and processing the data sequence using a mapping model to obtain control commands corresponding to the embodied robot; executing control operations corresponding to the control commands; and adjusting the software and hardware parameters of the embodied robot using the control commands. Using this disclosure can improve the naturalness, stability, and security of audio and video interaction in embodied robots.

Embodiments of the present application provide a method, device and readable storage medium for connection establishment, and relate to the technical field of communication. The method is applied to a session management function (SMF), and includes: receiving data sent by a second user equipment (UE) to a first UE, the data carrying an identifier of the first UE; sending, to the first UE, a first request message to the first UE or an access and mobility management function (AMF), the first request message being used to request the first UE to establish a protocol data unit (PDU) session or to activate a user plane of the PDU session; and establishing a connection between the first UE and the second UE after determining that the first UE has established the PDU session or activated the user plane of the PDU session. The method of the embodiments of the present application can support a scenario in which a UE has downlink data, but the UE has not established a PDU session for transmitting the downlink data, or can reduce the processing delay of a scenario in which a user plane of an established PDU session is deactivated.