Abstract: A multi-user flexible Ethernet fine granularity time slot allocation method and apparatus. The method is specifically: providing two time slot resource allocation and deployment schemes according to user demands, where the first scheme performs time slot allocation based only on an objective of global minimization of jitter of time slot allocated to all the users and can improve resource allocation equity and improve whole performance of a network. The second scheme performs weighted sum of delay and jitter minimization based time slot allocation on each user according to the quantity of time slots required for the users in sequence from large to small on the premise of most user input data in the current time slot assignment period being transmitted in the current time slot assignment period.

Abstract: A converged data exchange method and a time-sensitive network switch are provided in the present disclosure. The network switch device performs sensitivity identification for the data to be forwarded. For the switching transmission of non-time-sensitive data, the push port queue and the pop port queue perform cut-through switching for the data, which reduces the residence time of the data packet in the switch device. For time-sensitive data, the push port queue and pop port queue forward the data according to the corresponding priority scheduling policies.

Abstract: The present invention discloses a real-time license plate detection and recognition method and device based on color augmentation, the method comprises: step 1: obtaining car images containing license plates as a license plate detection training set, inferring license plate detection results through the trained license plate detection model; step 2: performing view correction transformation on the detected license plates to obtain frontal view images of the license plates; step 3, using the obtained frontal view images of the license plates as a training set for license plate recognition, using a license plate recognition model based on deep neural network for license plate recognition to obtain license plate recognition results; step 4: displaying the license plate detection results and the license plate recognition results on the original test images or outputting them as needed, completing the detection and recognition of the license plates in the images.

Abstract: An exception handling system and method for a space environment, and a detection device are provided. The exception handling system includes: a detection device, an interrupt controller, and a to-be-detected storage device, the to-be-detected storage device includes a statistical unit and registers; the statistical unit is configured to read monitoring data from a specified position of the to-be-detected storage device, generate statistical data based on the monitoring data and reference data written into the specified position in advance, and store the statistical data in the registers; the detection device is configured to read the statistical data from the registers, determine an exception detection result, generate an interrupt signal based on the exception detection result, and send the interrupt signal to the interrupt controller; and the interrupt controller is configured to perform an exception handling based on the interrupt signal.

Abstract: Disclosed are a parallel method and device for convolution computation and data loading of a neural network accelerator. The method needs two input feature maps and two convolution kernel cache blocks, and sequentially stores the input feature maps and 64 convolution kernels into cache sub-blocks according to a loading length, so as to execute convolution computation and simultaneously load data of a next group of 64 convolution kernels.

Abstract: The present application discloses a fiber optic sensor and a measurement method, apparatus, and storage medium. By performing, based on the microwave signal, intensity modulation on the optical signal, then inputting the modulated optical signal into the fiber optic containing the weak reflection grating array, a reflected signal is obtained. Thereafter by performing dispersion compensation on the amplified partial reflected signal, and based on the dispersion-compensated reflected signal and the non-dispersion-compensated reflected signal, the change amounts respectively corresponding to positions in the fiber optic containing the weak reflection grating array are determined.

Abstract: An event prediction method based on a satellite orbit threat domain knowledge graph is provided. By constructing a knowledge graph of the satellite orbit threat domain, and utilizing steps such as meta-path extraction, hyperedge construction, feature encoding, and feature aggregation, target features that can comprehensively and accurately describe each entity and the complex relationships between each entity in the satellite orbit threat domain are obtained, and a prediction model is trained by using the target features of each entity.

Abstract: An asymmetric cross-modal large-model knowledge transfer method for remote sensing includes: acquiring a training sample pairs including a sample RGB image and a sample MS image corresponding to a same scene classification; inputting the sample MS image into a teacher model; determining a first image feature extracted by the teacher model from the sample MS image; determining a first scene classification, obtained by the teacher model according to the first image feature, as a pseudo label; inputting the sample RGB image into a student model; determining a second image feature extracted by the student model from the sample RGB image; determining a second scene classification obtained by the student model according to the second image feature; and training the student model according to a difference between the second image feature and the first image feature and a difference between the second scene classification and the pseudo label.

Abstract: The present application discloses a fiber optic sensor and a measurement method, apparatus, and storage medium. By performing, based on the microwave signal, intensity modulation on the optical signal, then inputting the modulated optical signal into the fiber optic containing the weak reflection grating array, a reflected signal is obtained. Thereafter by performing dispersion compensation on the amplified partial reflected signal, and based on the dispersion-compensated reflected signal and the non-dispersion-compensated reflected signal, the change amounts respectively corresponding to positions in the fiber optic containing the weak reflection grating array are determined.

Abstract: An information propagation prediction method based on a sequential hypergraph neural network with co-attention fusion. The method includes three modules: a user feature learning module learning a user embedding by utilizing a graph convolutional neural network; a cascade feature learning module constructing a sequential hypergraph neural network based on equivariant diffusion to capture a complex cascade irregular connection so as to learn a cascade embedding of internal and external features of an encapsulated cascade structure; and a feature fusion and prediction module learning an interdependence between cascade features and user features by means of a co-attention mechanism so as to capture a complex relationship and interaction between the cascade features and the user features, and then calculating a possibility of potential user infection.

Abstract: A method for detecting network attack based on kernel operating characteristics of a software switch, comprising: collecting kernel operating characteristic data of the software switch during network management and packet forwarding of the software switch, wherein the kernel operating characteristic data of the software switch can reflect characteristic data of a fine-grained operating state of a network; preprocessing the kernel operating characteristic data of the software switch; and inputting the preprocessed kernel operating characteristic data of the software switch into a pre-trained attack detection model to detect a potential attack behavior in a network. The method is applicable to all scenarios where the software switch is applicable, especially a software-defined network and a cloud data center, an industrial Internet, 5G, edge computing based on the software-defined network.

Abstract: The present invention discloses a two-dimensional photonic convolutional acceleration system and device for convolutional neural network, comprising: a multi-wavelength light source, a signal source to be convolved, a modulator, a dispersion module, a 1×M power divider, an optical fiber delay array, a microring weighting array chip, a convolutional kernel matrix control unit, a trans-impedance amplifier array, and an acquisition and processing unit. The present invention realizes two-dimensional convolutional acceleration based on wavelength-time interleaving technology, a single modulator can realize the optical domain loading of the signal, and the convolutional operation speed is only limited to the speed of the modulator.

Abstract: A method and device for interpreting a graph neural network based on FPGA acceleration propose to use FPGA hardware to accelerate interpretation process of the graph neural network oriented to node classification in parallel, and improve node traversal and shortest path search of BFS, thereby optimizing requirements of algorithm calculation and storage, and accelerating generation of interpretation results. During calculating HN values, the present disclosure optimizes multiplication operation using the matrix characteristics, transforms the dense matrix multiplication into sparse-dense matrix multiplication, and optimizes the resource occupation using multi-PE parallel processing, greatly improving performance of graph neural network interpretation acceleration.

Abstract: The present disclosure discloses a method and an apparatus for data processing, a storage medium and an electronic device, where for each second unit in the embodiments of the present disclosure, a plurality of communication links are provided between the first unit and the second unit. The first unit, in response to a data operation request, sends the data operation request to the second unit through the plurality of communication links between the first unit and the second unit. The second unit processes the target data to be processed according to the data operation instruction in the data operation request to obtain a processing result, and sends the processing result to the first unit via a plurality of communication links. The first unit executes a response strategy for the data operation request based on the processing result.

Abstract: An endogenous security protection method for configuration data in an operating system of a network node includes: when a data backup module receives a network message flow, target configuration data is backed up in the data backup module, a distribution module send the received network message flow to each dynamic heterogeneous redundant executer respectively, each dynamic heterogeneous redundant executer stores the target configuration data, a synchronization module read the target configuration data stored by each dynamic heterogeneous redundant executer respectively, a judgment module performs consistency judgment, the synchronization module performs online-offline scheduling on the executers based on a judgment result, a target executer with data disorder is taken offline, a candidate executer is brought online, and the candidate executer obtains the target configuration data from the data backup module.

Abstract: A training data effectiveness evaluation method includes: acquiring a training set, where the training set is acquired by uniform downsampling from target data; acquiring a test set, where the test set includes at least one benchmark test set and at least one correlated test set; training a probe model based on the training set; testing the probe model based on the test set, and recording test metrics; generating an observation plot based on the test metrics, where the generating the observation plot includes: establishing a Cartesian coordinate system with a test metric of the benchmark test set as a horizontal axis and a test metric of the correlated test set as a vertical axis, and plotting key points in the Cartesian coordinate system based on the test metrics; and evaluating effectiveness of the target data based on the observation plot. The present disclosure has the following advantages.

Abstract: A method of signaling interaction in 5G space-ground integrated heterogeneous network architecture is provided, which enables publicly available data for trusted satellite discovery to be registered to the 5G core network based on the function framework of the 5G core network. When searching for satellites, a gNB can utilize the publicly available data of the trusted satellite registered in the 5G core network to speed up satellite searching, improve satellite link services, and filter out untrusted satellites.

Abstract: A process for generating an intermediate representation methodically compiles a neural network into a computation graph. First, a distinct node is built for every tensor variable within the graph, and this node is linked to a collection of pointers that reference the variable. Next, the method undertakes an analysis of the constraint relationships among these tensor variables. Using this information, it iteratively builds a topological graph that serves as the intermediate representation. Finally, this representation allows for the crucial step of analyzing variables that use different aliases but point to the same memory location, enabling the system to efficiently allocate a register for these aliased tensor variables.

Abstract: A method for incremental metapath storage and dynamic maintenance is provided, which includes, reformatting metapath instances, from a designated heterogeneous graph and of a designated metapath type, into path graphs; executing graph updating tasks and performing dynamic maintenance on the updated path graphs, traversing the path graph to obtain the location of metapath updates and update the path graph; for metapaths with length greater than 2 and with symmetrical central portion, central merge operation is performed to simplify path graph and perform subsequent restoration operation; and directly perform restoration operation on path graphs that do not meet the merging conditions. The present disclosure utilizes characteristics of graph update to obtain locality of metapath updates, and combines internal relationship characteristics of metapath instances to greatly speed up metapath generation and achieve real-time inference of dynamic heterogeneous graph models.

Abstract: An adaptive adjustment method of packet-level transmission priority for delay guarantee in programmable networks. The method realizes the adaptive adjustment of packet-level transmission priority in programmable networks from three aspects to satisfy the preset transmission delay requirements, namely: adaptive adjustment of priority in programmable switches based on processing delay state and switch queuing state, adaptive adjustment of priority among programmable switches based on transmission delay in upstream switches, and adaptive adjustment of global parameters based on packet transmission delay satisfaction, so as to realize the packet-level transmission delay guarantee in different positions with different time scales.