275 results about "Network code" patented technology

The invention relates to the technical field of cold-chain logistics information, and discloses a multi-mode AIGC cold-chain logistics information processing method and system, and the method comprises the steps: carrying out the feature extraction and feature enhancement of video data, temperature data and position data in a cold-chain logistics system based on a logistics information AIGC model, and obtaining an enhanced feature matrix; carrying out digital twinborn modeling to obtain a digital twinborn model of the logistics system, and constructing a state parameter space; performing deep reinforcement learning and information delay index calculation to generate a real-time data synchronization scheme; constructing a distribution network graph structure, and performing depth map network coding on the distribution network graph structure to obtain a distribution network representation vector; and performing multi-agent collaborative decision-making on the distribution network representation vector to obtain a cold chain distribution scheduling scheme, and updating the cold chain distribution scheduling scheme to the logistics system digital twinborn model. Therefore, intelligent scheduling and accurate control of the cold-chain logistics system in a complex scene are realized.

The invention discloses a goaf unmanned aerial vehicle inspection system based on monitoring and early warning, and the system comprises an observation data collection module which is used for collecting settlement and fracture main variables to form a time stamp observation set; the data fusion module is used for generating a unified monitoring data set by adopting a fractal small-world network coding consensus algorithm; the initial route planning module is used for constructing a route sequence based on a main variable evolution tensor and a risk map; the flight path execution module is used for collecting a flight path and environment data; the fault-tolerant control module triggers a fractional order sliding mode fault-tolerant and degradation mechanism based on the consistency error; and the closed-loop optimization module is used for dynamically updating the main variable tensor and the path cost function and outputting an optimized track and a structured early warning result. The system has high dynamic responsiveness and multi-source risk adaptability.

Methods, systems, and devices for wireless communications are described. A transmitting device may receive one or more service data units (SDUs) at a layer two (L2) layer of the transmitting device. The transmitting device may encode, at the L2 layer, the one or more SDUs according to one or more network coding parameters to obtain at least one encoded protocol data unit (PDU), the one or more network coding parameters comprising a rateless code. The transmitting device may generate, for the at least one encoded PDU, at least one corresponding PDU header. The transmitting device may output the at least one encoded PDU and the at least one corresponding PDU header from the L2 layer to a lower layer of the transmitting device for transmission to one or more receiving devices.

The invention discloses a remote sensing image semantic segmentation-oriented spatial spectrum context feature enhancement method and device. The method comprises the following steps of: constructing a neural network model based on an encoder-decoder architecture; inputting the preprocessed remote sensing image set into a feature coding block, and extracting hierarchical features; according to the model, spectrum attention and position self-attention mechanisms are integrated through a collaborative attention module, and the sensitivity of network spectrum and spatial context information is remarkably enhanced; the network coding module efficiently compresses and codes the features before entering a decoding stage; a cross fusion module is applied to intelligently fuse features between a coding block and a decoding block to ensure that information is not lost in a decoding process; the feature map is mapped into a pixel-level category label through a Softmax layer, precise semantic segmentation is achieved, and a high-quality classification result is obtained. According to the method, through collaborative modeling of the spectrum and the spatial context, high-frequency details are effectively reserved, and the precision of semantic segmentation is improved.

The invention discloses a recommendation system and method for keeping semantic integrity based on a large language model. According to the method, user-article interaction data and text information are fused, a prompt template of a user and an article is constructed, a configuration file with rich semantics is generated by utilizing a large language model, and initial embedded representation is extracted. Then, two-stage dimensionality reduction transformation is carried out through principal component analysis and a multi-layer perceptron, semantic information is reserved, and low-dimensional embedding is generated; on the basis of the embedding, cosine similarity is calculated, a user-user and article-article similar graph is constructed, and final embedding representation is generated through graph convolutional network coding. Meanwhile, collaborative filtering is combined to capture an interaction relationship and optimize a joint learning target, including recommendation loss, cross-modal comparison loss and regularization terms, so as to align semantics and collaborative filtering embedding, and finally generate a high-precision personalized recommendation result. The method effectively improves the semantic comprehension ability and recommendation accuracy of a recommendation system, and is suitable for various recommendation scenes.

Methods and systems for physical layer network coding based on two-dimensional (2D) joint coding are described. In some methods, first and second packets are obtained. A set of one or more cross-packet check blocks is generated, where each cross-packet check block is generated based on a set of cross-packet bits including at least one bit from each of the first and second packets. At least one cross-packet check block is transmitted to a first communication node.

The invention discloses a cross-network convergence transmission method and device based on network coding, and relates to the technical field of communication. According to the application type, selecting a coding mode to code the original data packet to obtain a plurality of to-be-transmitted data packets; determining a scheduling scheme based on the network state; according to the data transmission method and device, the coding mode is selected according to the application type, cross-network fusion transmission can be completed based on network coding, and the time delay is reduced while the bandwidth of data transmission is improved.

The invention discloses a hydropower station water level detection method and system. The method comprises the steps that an original water flow characteristic parameter set is obtained through multiple sets of Doppler effect radar flow measuring devices; performing segmentation extraction to obtain a water flow feature sub-data set; inputting a Transform network coding layer to generate a water flow feature coding vector; outputting a preliminary water level predicted value sequence through a decoding layer; a radar flow measurement model is called for correction to obtain a correction sequence; time sequence integration is carried out to obtain a water level change curve. The system comprises a multi-source Doppler radar signal acquisition unit, a spatial-temporal feature segmentation extraction unit, a Transform coding processing unit, a water level preliminary prediction unit, a radar model correction unit and a time sequence integration output unit. According to the method and system, multi-source parameters are deeply fused, the environmental adaptability is improved, the continuity and reliability of a detection result are enhanced, the water level of the hydropower station can be accurately monitored, and support is provided for scheduling decision and safety prevention and control.

Systems, methods, apparatuses, and computer program products for network coding are provided. One method may include receiving, at a second packet data convergence protocol (PDCP) entity, one or more original packet data convergence protocol (PDCP) protocol data units (PDUs) from a first PDCP entity for a radio bearer. The method may also include coding, at the second packet data convergence protocol (PDCP) entity, the original packet data convergence protocol (PDCP) protocol data units (PDUs) to produce one or more network coded packet data convergence protocol (PDCP) protocol data units (PDUs).

The invention discloses an industrial equipment residual life prediction method fusing a pre-training large language model, and belongs to the technical field of deep learning, large language models, time series data feature extraction and the like. For complexity and high-dimensional features of industrial equipment time series data, firstly, original data are processed through a time series data preprocessing module; the method comprises the following steps of: obtaining independently segmented degradation data, coding the degradation data by using a mark code, a position code and a time code input into an embedding module, and then realizing feature alignment of a pre-trained large-scale language model and a time sequence through a pre-trained large-scale language model parameter fine tuning module; and the pre-training weight is transmitted to a pre-training large model additional network coding module, so that the number of parameters needing to be adjusted is reduced, the generalization ability and accuracy of the model are improved, and finally a prediction result of the residual life of the industrial equipment is obtained through an output layer.

The invention relates to a real-time reliable control-oriented network coding communication method, which comprises the following steps of: S1, initializing encoder parameters, establishing an end-to-end analog channel for data packet transmission, carrying out finite field-based random coefficient coding on a data packet transmitted from an upper layer, and packaging a corresponding data packet header, and sending the data to a corresponding receiving end through a UDP protocol. And S2, initializing decoder parameters, acquiring transmitted coded data by monitoring a UDP (User Datagram Protocol) port, de-encapsulating a data packet, and carrying out corresponding decoding operation according to packet header information so as to recover the data packet lost in the transmission process. According to the method, under the condition of not depending on feedback retransmission, when the communication environment of the industrial Internet of Things is severe, high real-time performance lower than 1 ms in-sequence time delay (the blocking time of a data packet in a decoder) is achieved, and high-reliability data transmission with the error rate smaller than 10 <-5 > is achieved.

The invention discloses an unmanned aerial vehicle cluster authentication method based on a certificateless homomorphic network coding signature, and belongs to the field of cryptography and network security. In an unmanned aerial vehicle network system comprising a KGC, a source node, an intermediate node and an authentication server CS, the following steps are executed: the KGC generates system parameters and a master key; the source node registers to the KGC and requests part of private keys; the source node carries out vector splitting and expansion on the authentication message, randomly selects a message identifier, executes a signature algorithm to respectively calculate the signature of each vector, and sends the vectors and the signatures to the intermediate node; and the intermediate node executes a verification algorithm to judge the validity of the currently received data packet, discards the invalid data packet, calculates to obtain a signature of the combined vector, and forwards the signature to the adjacent intermediate node. When the CS obtains a sufficient number of valid data packets, the original authentication message can be recovered and an authentication success message is sent to the source node unmanned aerial vehicle. According to the invention, the transmission performance and reliability of the unmanned aerial vehicle network are improved.

The invention discloses a novel digital hybrid coding method based on a large model. The method comprises the following steps: S1, preprocessing to-be-coded data; s2, performing feature coding on the preprocessed data by adopting a diffusion model driven feature learning method; s3, performing neural network coding on the feature coding data, and dynamically adjusting the coding bit number based on a variable bit rate quantization method; s4, performing adaptive entropy coding on the neural network coding data, and performing probability density transformation based on a normalized flow entropy coding method; s5, discrete transform coding is carried out on entropy coding data, and hierarchical quantization is carried out on different frequency components by adopting a hierarchical sub-block quantization method; and S6, based on the code length distribution and entropy coding parameters of the A3C optimization transformation coding data, extracting a lightweight coding model from the diffusion model by using a knowledge distillation method, and generating final optimization coding data. Through the hybrid coding and dynamic optimization strategy, the data compression efficiency and the coding quality are remarkably improved.

Systems and methods are described for execution of multiple tasks associated with a set of code in an on-demand network code execution system. A user may provide a set of code that is associated with the multiple tasks. The system may generate a first virtual machine instance for execution of a first task. The system may determine that a second task is associated with the first task and may identify a location of the first virtual machine instance. The system may further identify a second virtual machine instance for execution of the second task based on the location of the first virtual machine instance. For example, the system may identify the first virtual machine instance from a plurality of pre-generated virtual machine instances and / or may generate the first virtual machine instance.

Embodiments relate to a delay control system for improving network coding of bidirectional traffic, and more particularly to a delay control system for improving network coding of bidirectional traffic that sets a path with a constraint on time in an IIOT network and controls new network coding-aware routing capable of efficiently utilizing opportunities for network coding, and the delay control system for improving network coding of bidirectional traffic includes an intermediate node request collector configured to receive a route request (RREQ) packet transmitted from a source node, an intermediate node calculator configured to calculate a deadline between the source node and a destination node based on the RREQ packet received by the intermediate node request collector, and an intermediate node request transmitter configured to transmit the RREQ packet through an optimal path between the source node and the destination node based on the deadline.

The invention discloses a neural architecture search method based on a diffusion evolution algorithm, and the method comprises the steps: firstly constructing a supernet which comprises subnets, and enabling each subnet to give a weight to each operation on each connection edge through continuous coding; then obtaining different types of pictures to construct a data set; and finally, performing alternative optimization on the super-network weight and the sub-network codes, stopping optimization until constraint conditions are met, obtaining optimal sub-network codes, and further obtaining the architecture of the neural network. According to the method, an iterative denoising mechanism of a diffusion model and a global search strategy of an evolutionary algorithm are creatively fused, a super network is constructed by combining the denoising mechanism of the diffusion model and the global search capability of the evolutionary algorithm, and network weight and subnetwork coding are alternately optimized; through adaptive noise scheduling and density estimation, population diversity is enhanced, local optimum is avoided, and an optimal neural network architecture suitable for a task can be better found.

The invention discloses a heterogeneous network embedding method based on dynamic heterogeneous network decomposition and a hierarchical space-time attention mechanism. The method comprises the following steps: dynamic network decomposition: decomposing a heterogeneous network sequence into independent subgraph sets according to edge types; multi-order node attention aggregation: for each sub-graph, fusing information of nodes and different edge types; semantic level attention is embedded, wherein global semantic embedding is generated in combination with global relation type weight and meta-path long-short-term memory network coding; time dynamic modeling: respectively calculating a time attention weight and a Monte Carlo sampling approximate Horkes intensity, and then aggregating and splicing results of the time attention weight and the Monte Carlo sampling approximate Horkes intensity to obtain a final embedding result. According to the method, through cross-granularity semantic modeling and efficient time sequence dependence learning, an innovative solution is provided for node representation of the dynamic heterogeneous network.

Systems and methods are described for providing an application-level gateway that allows computing devices to utilize an on-demand network code execution system. An on-demand network code execution system may allow users to submit code to be executed in a serverless environment, and may provide an interface for executing the user-submitted code on demand. The interface may require that users authenticate, provide input in a particular format, or meet other criteria when sending a request to execute the code. An application-level gateway may thus provide an interface that implements these functions, thereby allowing computing devices to interact with the code as though it were running on a server (e.g., by using the Hypertext Transport Protocol). The application-level gateway may also use on-demand code execution to provide load balancing for servers that are running the user-submitted code, and seamlessly provide access to code that runs on both server-based and serverless environments.

Disclosed are a data processing method, an electronic device, and a computer-readable storage medium. The data processing method may include: determining, in response to acquiring at least one source data packet, a first network coding mode for the at least one source data packet according to a pre-configured first network coding parameter; encoding the at least one source data packet according to the first network coding mode to obtain a first encoded data packet; and sending the first encoded data packet to a first receiving end, such that the first receiving end processes the first encoded data packet.

The embodiment of the invention provides a network-on-chip design method and device, electronic equipment and a readable storage medium, and the method comprises the steps: constructing a target behavior model based on a target design demand; generating a target code based on the target behavior model and a preset code library; under the condition that the target code does not meet the preset constraint target, the target behavior model is optimized, and the target code is updated based on the optimized target behavior model until the target code meets the preset constraint target; and generating an on-chip network code file based on the target code meeting the preset constraint target. Through the mode of performing constraint verification on the target code in the design process and optimizing and adjusting the target behavior model, the code optimization and adjustment range in the design process is narrowed, the code modification cost is reduced, and on the premise of ensuring that the target design requirement of the network-on-chip and the preset constraint target are verified to meet the expectation, the optimization and adjustment efficiency of the network-on-chip is improved. And the code generation efficiency of the network-on-chip is improved.

The invention discloses a guard type cross-network git code synchronization method, system and device and a storage medium. The method comprises the steps that a browser logs in a vpn, and a timed refreshing program is started; and meanwhile, a git code synchronization program is scheduled regularly. The git codes are scheduled and synchronized regularly, so that the labor investment is reduced, and the execution efficiency is high.

There is provided a method of wireless transmission of protocol data units over one or more radio link modules, the method comprising:splitting a service data unit, received from an upper layer, into a plurality of data packets;obtaining combined data packets, by applying a Network Coding to the data packets, wherein padding is added, if necessary, to the service data unit or to data packets to have data packets of equal length to which is applied the Network Coding;encapsulating the combined data packets into at least one protocol data unit, wherein each protocol data unit comprises a header and wherein the header contains a padding indication for indicating whether padding has been added or not, andtransmitting the at least one protocol data unit over the one or more radio link modules.

Apparatuses, methods, and systems are disclosed for configuring based on network coding (“NC”) and multiplexing. One method includes receiving a multiplexing configuration of at least one network-coded logical channel and at least one non-network-coded logical channel multiplexed for transmissions scheduled over at least one transport block (“TB”). The method includes receiving a NC configuration corresponding to each network-coded logical channel of the at least one network-coded logical channel corresponding to each TB of the at least one TB. The method includes determining, for each network-coded logical channel of the at least one network-coded logical channel corresponding to each TB of the at least one TB, a code block (“CB”) threshold based at least on the NC configuration and the multiplexing configuration.

The invention relates to the field of Internet of Things equipment security upgrading, and discloses an intelligent washing machine embedded software online upgrading method and system, and the method comprises the following steps: 1, a server side stores an encrypted upgrading program file and calculates a verification value, issues the verification value in a wireless manner at a set time, generates an equipment uniqueness voucher based on a physical unclonable function, and sends the equipment uniqueness voucher to the server side; establishing equipment identity binding; 2, dynamically calculating a network coding parameter based on the equipment uniqueness voucher according to a real-time channel quality parameter; and 3, based on the network coding parameters, carrying out dynamic block network coding transmission on the upgrade data, and generating an encrypted upgrade data packet by adopting chaotic encryption in the transmission process. According to the invention, an end-to-end security authentication system is realized by binding the unique voucher of the equipment and establishing an encrypted transmission channel. According to the scheme, the unauthorized access and firmware tampering are effectively prevented by utilizing the dual guarantee of hardware features and a cryptographic algorithm.

The invention relates to the technical field of satellite communication, in particular to a wireless multicast satellite network topology construction and genetic algorithm flow distribution method capable of remarkably improving the network capacity, a plurality of data streams on a satellite can be compressed through a coding process, so that the use of communication and storage resources is reduced to the greatest extent, and in addition, the network capacity is improved. In addition, a topological construction and flow distribution method based on a genetic algorithm is introduced to improve the performance of network coding, and a simulation result shows that optimization is added to the topological structure, so that the network capacity can be remarkably improved.

The invention relates to the technical field of signal processing, and discloses a novel signal processing method for calculating a low-power-consumption AI processor, a chip and a medium, and the method comprises the steps: carrying out the neural mimicry conversion operation of an input signal flow of the low-power-consumption AI processor, and obtaining signal feature data; executing neuron computing resource allocation, and allocating to different resource groups according to computing task complexity to obtain a resource allocation scheme; performing pulse neural network coding operation on the signal to obtain a signal feature matrix; heterogeneous computing unit allocation operation is executed, computing tasks are allocated to a CPU unit, a GPU unit and an NPU unit, and a computing task allocation result is obtained; performing parallel signal processing operation to obtain working parameters of the processor; and executing performance evaluation calculation, generating processor operation state data, and reallocating neuron resources to obtain optimal configuration parameters. Therefore, the signal processing efficiency is improved, and the dynamic balance between the performance and the energy consumption of the processor is realized.

The invention provides a wireless Mesh network reliability guarantee method based on adaptive network coding. The method comprises the steps of routing initialization, dynamic weight adjustment, link selection, network coding and data transmission. The method comprises the following steps: firstly, in a routing initialization step, each node discovers a neighbor node and establishes a Mesh network structure; in the dynamic weight adjustment step, a weight matrix is adjusted according to different service types (such as video streams and audio streams) so as to optimize the transmission reliability and the resource utilization rate; in the link selection step, an optimal link path is selected by constructing a state matrix and adopting an E-D algorithm, so that the transmission reliability and efficiency are improved; in the network coding and data transmission steps, the optimal coding degree and redundancy are calculated through a Gaussian process (GP) model so as to adapt to the dynamic change of the network environment and improve the transmission robustness. According to the invention, the software defined network (SDN) controller is utilized to manage the routing in a unified manner, and the link selection strategy can be flexibly adjusted according to service requirements. By collecting the state information of each node in the network, the system adaptively adjusts the coding parameters and weight configuration of the nodes, and selects the optimal route according to the performance of the nodes. According to the method, the packet loss rate and delay in the data packet transmission process are effectively reduced, and the transmission efficiency and reliability of the multi-hop wireless Mesh network are improved.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a base station, configuration information indicating that network coding is enabled for initial transmissions associated with a multicast / broadcast service (MBS) and indicating that network coding is enabled for retransmissions associated with the MBS. The UE may receive, via a multicast traffic channel or a dedicated traffic channel, an initial transmission associated with the MBS, wherein the initial transmission is associated with a first set of encoded packets. The UE may transmit a radio link control (RLC) status feedback message associated with the initial transmission. The UE may receive, via the multicast traffic channel or the dedicated traffic channel, a retransmission associated with the initial transmission, wherein the retransmission is associated with a second set of encoded packets. Numerous other aspects are described.

The invention discloses a power dispatching master station robot autonomous inspection method and system based on SLAM and multi-mode perception. The method comprises the following steps: performing SLAM joint estimation through data fusion of a 3D LiDAR, a visual sensor and an IMU, performing inter-frame pose solution based on three-dimensional point set matching by adopting coordinate alignment and scale recovery, and introducing the IMU to perform cross-sensor consistency verification and adaptive pose optimization so as to solve the problem of positioning drift in a complex scene; meanwhile, natural language instructions are coded through a GRU network, visual features are extracted in combination with a residual network with an attention mechanism, time sequence fusion and modeling are carried out, and autonomous navigation decision making in a dynamic environment is achieved. The system comprises a corresponding SLAM estimation module, a multi-modal fusion decision module and an execution mechanism. According to the method, the positioning robustness, the navigation precision and the task adaptive capacity in the complex environment of the power dispatching master station are remarkably improved.

The invention discloses an unmanned aerial vehicle network multipath selection and network coding redundancy transmission method. The method comprises the following steps that each unmanned aerial vehicle carries out node state perception and link prediction; the source node initiates a multi-path routing discovery process based on the extended AOMDV routing protocol, performs path quality measurement, and selects a plurality of paths with the highest path quality as active transmission paths; the source node divides an original data block to be sent into a plurality of original data packets and encodes the original data packets respectively; performing optimal distribution based on a water injection algorithm; data forwarding and decoding receiving are carried out according to an optimal distribution result; and continuously detecting that the link communication actively triggers the maintenance process before the link is actually broken. According to the method, high-reliability, low-delay and energy-balanced data transmission is realized in a highly dynamic unmanned aerial vehicle network through a rigorous evaluation and optimization system, and the overall survival time of the network is effectively prolonged; and predictive route maintenance and fast route switching are carried out through the extended routing table.