39 results about "Network pattern" patented technology

The invention relates to the technical field of IPv6 self-configuration, in particular to an IPv6 network mode self-adaptive configuration method and system based on an RA message. In the method, a finite-state machine establishes a state transition path according to the combination relation of M and O flag bits in an RA message cache set and prefix field content, converts a network mode recognition process into a quantifiable state judgment sequence, and sends the state judgment sequence to the RA message cache set; configuration ambiguity caused by flag bit fluctuation in traditional static judgment is eliminated, pattern recognition under network environment changes has continuity and self-consistency, the classification regression tree constructs a branch judgment path with the duration, the advertisement interval and the prefix consistency of an RA source as characteristic variables, an optimal node is selected through a hierarchical splitting algorithm, and the judgment accuracy is improved. The dynamic mapping of stateful and stateless configuration paths is realized, the misjudgment rate of configuration branches is reduced, and the address allocation delay is optimized, so that the IPv6 self-configuration has a structured decision-making capability and a parameter mapping self-optimization characteristic, and the connection reliability, the address generation speed and the configuration accuracy are improved.

The invention discloses an optimized ventilation corridor construction method for urban heat exposure mitigation and related equipment, and can be applied to the technical field of geographic planning. According to the method, the dominant cooling cold source and the thermal exposure relieving cold source are identified according to the basic data of the target research area, the ventilation comprehensive resistance surface of the target research area is constructed according to the resistance factors in the basic data, and then the ventilation target corridor and the corridor optimization node of the target research area are identified by combining the two cold sources. A ventilation network structure of the target research area is corrected and adjusted according to the dominant cooling cold source, the thermal exposure relieving cold source, the ventilation target corridor and the corridor optimization node, so that an optimized ventilation corridor system of the target research area under the guidance of thermal exposure is formed, and therefore, the priority service of the high-heat exposure area is realized; and ventilation blocking positions and corridor optimization nodes can be determined, so that a ventilation network pattern capable of guiding staged cooling and micro-updating of a city can be formed, and the experience requirements of people can be met.

This invention provides a method for providing CNI support for a Docker container engine, relating to the field of container runtime technology. The method includes configuring a custom runtime component docker-cni in the Docker container engine; specifying the custom runtime component docker-cni as the runtime when creating a container and setting it to a network-free mode (none); injecting a pre-start hook and a stop hook into the container's configuration file during the container creation phase; the hooks are used to trigger the custom runtime component docker-cni to perform CNI network operations; when the container starts and triggers the pre-start hook, calling the CNI plugin's add network operation according to the command injected in the pre-start hook to complete the container network configuration; when the container stops and triggers the stop hook, calling the CNI plugin's delete network operation according to the command injected in the stop hook to clean up the container network configuration.

The present invention relates to a padel racket that is strung on its two striking surfaces instead of being solid. Thus, the resulting racket has the following elements: A) a handgrip or gripping handle covered by a grip adapted in size to the player, in order to control muscle tension and allow smooth wrist movement; B) the heart or throat of the racket provided with a bridge and reinforcement, which acts as a connecting link between the handgrip and the head and does not present any distinctive features in the present invention; and C) two striking surfaces or faces which in the present invention are strung, so that both faces are configured by a double string network system, each of the faces being a network pattern or grid parallel to the opposite face.

The application discloses an improved network management method based on AUTOSAR, wherein the network node state comprises a network mode and a sleep mode; the node receives and sends network management messages in the network mode; when the number of errors in sending or receiving network management messages exceeds a threshold value, or a network management message with a sleep flag is received, the node enters a fault detection state; the node stops communication work in the sleep mode; if the duration of no communication work exceeds a certain time, the node enters the sleep mode; if the expected stay time of the node in the sleep mode is less than a preset time, the node enters a light sleep mode; if the expected stay time of the node in the sleep mode is greater than the preset time or the duration of the node in the light sleep mode exceeds a certain time, the node enters a deep sleep mode. The application adds a fault detection stage, a light sleep mode and a deep sleep mode to the original network node state, and improves the accuracy and flexibility of network management.

This invention provides a method for detecting illegitimate accounts on Ethereum based on a heterogeneous graph transformation network. First, a network model of an account-centric heterogeneous information network describing account activity information is defined. Then, a graph transformation network is used to automatically mine meta-paths and calculate multi-hop connections. The resulting relation matrix is ​​input into a convolutional neural network to obtain node embeddings, thereby detecting illegitimate accounts. This method can be used to describe the activity information of Ethereum accounts, including account transactions, balances, block information, etc. The invention proposes using a graph transformation network to learn meta-paths to obtain a relation matrix, which is then used as input to a convolutional network, transforming the illegitimate account detection task into a node embedding classification task based on a graph neural network. Experimental results show that the proposed model achieves a node classification accuracy of up to 95%, outperforming other account detection schemes, with a single detection time of approximately one minute, demonstrating both high efficiency and accuracy.

The invention discloses a rapid networking method and device based on radio frequency communication and electronic equipment, which are applied to a network node with a network access function. The method comprises the following steps: receiving basic information of a plurality of first child nodes in a radio frequency mode, and sending the basic information to user equipment; respectively sending the first network distribution information to a plurality of target sub-nodes based on the indication of the user equipment, wherein the target sub-nodes are selected by the user; based on the indication of the user equipment, indicating the plurality of target child nodes to exit the radio frequency mode and enter the first network mode based on second network distribution information, the second network distribution information at least comprising the first network distribution information; when the plurality of target sub-nodes enter the first network mode, exiting the radio frequency mode and entering the first network mode based on the second network distribution information; and in the first network mode, performing networking process interaction of the first network with the plurality of target child nodes entering the first network mode. In this way, the network node can quickly identify the child node.

The present disclosure sets forth systems, apparatuses, and methods that autonomously adapt networks to acquire additional capabilities and / or optimize current capabilities. An example system comprises processors and memory that stores instructions to be executed to monitor first performance metrics of a first network, determine, based on the monitored first performance metrics, network patterns indicative of network inefficiencies or inabilities, determine, based on the determined network patterns, a network mutation, create, based on the first network and the network mutation, a second network, compare the first performance metrics of the first network to second performance metrics of the second network, and based on determining that the second performance metrics are an improvement over the first performance metrics by a threshold amount, apply the network mutation to the first network.

The invention relates to the field of urban planning and management, in particular to a multi-target composite ecological network construction and local synergy method, device and equipment, and innovatively provides a composite ecological network integrating double targets of an urban cold island effect and habitat quality. On the basis of a hierarchical optimization method of'macroscopic network pattern constraint-machine learning interpretation-spatial threshold regulation ', capturing a complex nonlinear relationship between a landscape index and a dual ecological target by utilizing a high-dimensional nonlinear fitting capability of a machine learning model in a heterogeneity composite ecological network; and the SHAP model is introduced to identify a synergistic dominant driving factor and a quantization threshold thereof in the composite ecological network, so that an abstract model prediction result is inverted into a planning control index with clear physical significance, a targeted local synergistic optimization strategy is generated, and the ecological restoration efficiency and the refined control effect are greatly improved.

Techniques for a container orchestration system are disclosed. A system executes a virtual agent in a cloud network on a virtual node of a container orchestration system. The virtual node hosts multiple container instances within the cloud environment. The system executes a first container instance within the virtual node and connects the first container instance to a first subnet. The system executes a second container instance within the same virtual node and connects the second container instance to a second subnet distinct from the first subnet. The system enables access to the first container instance through the first subnet and enables access to the second container instance via the second subnet. This architecture allows for flexible network configurations within a single virtual node, enhancing resource utilization and network segmentation capabilities in containerized environments.

The invention discloses a power network design method and device for a redistribution layer, electronic equipment and a medium, and the method comprises the steps: obtaining a first potential via hole setting position of the redistribution layer according to an arrangement pattern of a plurality of first power lines of a target metal layer; obtaining a first power supply network pattern of the redistribution layer according to the position of the contact in the redistribution layer and the setting position of the first potential via hole, the first power supply network pattern being overlapped with the setting position of the first potential via hole as much as possible; and according to the overlapping position of the first power supply network pattern and the first potential via hole setting positions, and according to a network design rule of the redistribution layer, removing positions which do not meet requirements in the first potential via hole setting positions, and obtaining first target via hole setting positions, corresponding to the plurality of first power lines, of the redistribution layer. The method can adaptively obtain the redistribution layer for the top power supply network.

One example method includes receiving a set of requirements for aspects of a network, identifying a gap between one of the aspects of the network and a zero trust (ZT) requirement, determining a solution set comprising potential solutions for reducing or eliminating the gap, associating a respective cost with each of the solutions, determining an extent to which the solutions of the solution set comply with requirements, recommending a best solution from the solutions of the solution set, determining a priority of the gap relative to respective priorities of other gaps, and outputting a list of the gaps, sorted by priority, and the recommended best solution.

The application provides a test method of a low-power wide-area network, which is applied to a test terminal and comprises the following steps: selecting a test request and a test target, wherein the test target comprises a network mode selection instruction of a low-power wide-area network to be tested or the test target comprises a selection instruction of an MQTT test scene; the network mode selection instruction comprises any one of a network mode of an unlicensed frequency spectrum, a network mode of a licensed frequency spectrum and a hybrid network mode; according to the network mode selection instruction, data of Internet of Things nodes in different network modes are collected and transmitted according to test paths of the respective network modes; the service quality of the transmitted data is tested according to the test paths; when a user selects a test target comprising a selection instruction of an MQTT test scene, test data sets are generated according to the MQTT test scene selected by the user, and the test data sets are input into an intrusion detection system built in an MQTT agent to test the intrusion detection system.

A semiconductor structure includes a fin-shaped structure protruding from a substrate and including a fin base and a stack of channel layers over the fin base, an isolation feature disposed adjacent to the fin base, a first dielectric layer disposed over the isolation feature, a metal gate structure wrapping around the stack of channel layers, a gate spacer disposed over the isolation feature and along a sidewall of the metal gate structure, a second dielectric layer disposed over the fin base and adjacent to the stack of channel layers, and a source / drain feature disposed over the second dielectric layer and connected to the stack of channel layers. The metal gate structure and the gate spacer are disposed over a portion of the first dielectric layer. From a top view, the first dielectric layer and the second dielectric layer form a checkerboard pattern or a strip network pattern.

The application discloses a point of interest recommendation method based on meta-path enhanced view contrast learning, and the method comprises the following steps: constructing an initial position social network and generating node initial features; determining and generating corresponding enhanced edges according to whether the geographical distance between node pairs based on different correlation relationships meets the corresponding preset threshold, so as to obtain an enhanced position social network; constructing a network mode view, a meta-path view and a meta-path enhanced view; performing meta-path level view contrast and graph level view contrast, and respectively calculating corresponding contrast losses; calculating the total loss of model training by linearly weighting the meta-path level contrast loss and the graph level contrast loss; and generating a user point of interest recommendation after optimizing model parameters. The application realizes the construction of enhanced edges by integrating time and space information to alleviate data sparsity, and improves the network representation learning quality and the point of interest recommendation accuracy by means of multi-level feature aggregation and multi-level view contrast.

The application provides a communication method of a display device, the display device, a circuit board and a storage medium. The method relates to the technical field of communication. The method comprises the following steps: receiving an opening instruction of a target network mode in the display device; if the target network mode is a peer-to-peer network mode, performing data transmission with a target device through a first process; if the target network mode is a client mode, performing data transmission with the target device through a second process; wherein the first process and the second process are independent processes. The method can avoid the delay problem existing in data transmission in the case that the client mode and the peer-to-peer network mode are parallel.

The invention relates to the technical field of abnormal object recognition, in particular to an abnormal object dynamic behavior pattern recognition method based on a graph neural network, a medium and equipment, and the method comprises the steps: enabling the feature representation of each node to be capable of continuously fusing the weighted information of multi-order neighbors through a multi-layer iteration and edge weight-based message transmission mechanism, and enabling the feature representation of each node to be more accurate. Therefore, local and direct association is expanded into global and potential network mode representation, and behavior collaboration of direct / indirect association objects is captured. Similarity calculation and clustering analysis are performed on the Nth-layer intermediate feature vector generated in the graph neural network, and nodes with similar behavior patterns and similar structure roles in the network can be automatically collected into a cluster, so that individual anomaly can be judged, and the probability of individual anomaly can be reduced. And accurate locking and mode classification of the whole hidden collaborative abnormal gang which has no strong direct connection but highly collaborative behaviors can be realized, so that the accuracy and comprehensiveness of an identification result are greatly improved.

The invention discloses a port graph-based water network modeling and analysis method, and belongs to the technical field of water network modeling and analysis. Collecting landform data, water network vector data and flow direction data of each river reach of the to-be-analyzed area; establishing each river reach as a minimum port graph containing a single inlet and a single outlet to obtain a river network unit; merging the river network units into river basin river network units step by step based on the connection relation and the topological characteristics among the river network units; establishing a tree structure of the drainage basin; related analysis parameters are obtained through recursive calculation according to the drainage basin river network units and the tree structures of the drainage basin river network units; and analyzing a basin water network topological structure and a water network pattern according to an analysis and calculation result, and supporting recursive parameter calculation to obtain key analysis parameters. According to the invention, a novel river water network modeling and analysis scheme is realized.

The present application relates to a kind of for slitting photovoltaic cell and its slitting piece, photovoltaic module, printing screen plate.The photovoltaic cell has first area, second area, third area, each area is arranged along first direction, and there is cutting seam between adjacent two areas along second direction;First area is printed with noble metal grid line network pattern on the front and back of cell, and noble metal terminal point is arranged on the upper edge of noble metal grid line network pattern on the front or back in the area along second direction;Second area is printed with noble metal grid line network pattern on the front of cell, and base metal grid line network pattern is printed on the back of cell;Third area is printed with noble metal grid line network pattern on the front and back of cell, and noble metal terminal point is arranged on the lower edge of noble metal grid line network pattern on the front or back in the area along second direction.

Some embodiments of the present application provide an intelligent set-top box and a network mode modification method. The method comprises: obtaining newly added service account information supporting the intelligent set-top box to realize network connection issued by a network server; if the newly added service account information is different from current service account information, controlling the intelligent set-top box to perform network connection according to the newly added service account information, so that the network mode of the intelligent set-top box is a newly added network mode, and multicast detection is performed on the intelligent set-top box, and a video playing mode is sent to a video platform through a probe mode. The method compares the newly added service account information with the current service account information, automatically selects a corresponding network mode for network connection according to a comparison result, so as to realize the function of automatically modifying the network mode of the intelligent set-top box; and after the network mode is modified, the video playing mode of the intelligent set-top box is obtained through multicast detection and sent to the video platform, and the video platform is adapted, so as to improve the success rate of video playing.

The invention relates to the technical field of mode recognition, in particular to an optical fiber driven neural network mode recognition method and system, and the method comprises the following steps: obtaining an optical interference signal, dividing a period group, extracting an amplitude and phase track, constructing a cooperative track group, recognizing a synchronous evolution mode, generating a structure mapping graph, extracting a track code, and inputting the track code into a neural network recognition layer; and detecting the interference pattern disturbance removal unstable path, and outputting an identification result of optical power matching. According to the method, path trajectory division is carried out on input data by introducing periodic structure characteristics of light interference signals, a co-evolution structure is established by using a multi-dimensional change trend of amplitude and phase, the ability of depicting an internal relation between dynamic signal characteristics is enhanced, and the recognition precision of an evolution mode is effectively improved in combination with a neural network retrieval mechanism; and by analyzing the matching relationship between the probability output and the optical power fluctuation in the identification path, it is ensured that the identification output result has higher response consistency and classification effectiveness.

The embodiment of the present application provides a starting method and device of a container, comprising: detecting whether the network mode of the container is a host network mode; if the network mode is the host network mode, obtaining a plurality of container ports of the container; obtaining a host port which is not occupied; establishing a mapping relationship between the plurality of container ports and the host port which is not occupied, and starting the container based on the established mapping relationship. By using the technical scheme provided by the embodiment of the present application, the plurality of container ports of one container will not be mapped to the same host port, thereby reducing the degree of port conflict when a plurality of applications run in the container in the host network mode.

A system for detecting anomalous network patterns based on analyzing network traffic data and method thereof are disclosed. The system comprises a flow aggregator subsystem, a flow feature generation subsystem, an anomaly detection subsystem, a dynamic score subsystem, and a calibration subsystem. The system is configured to receive the network traffic data from one or more network endpoints for aggregating the network traffic data into network flow data. The system is configured to generate one or more flow features for each packet associated with the aggregated network traffic data based on a rolling window-based analysis of the one or more attributes. The system is configured to analyze the one or more flow features by utilizing one or more deep-learning models to detect the one or more anomalous network patterns.

A method for providing data exchange using secure tunnel in a multi-tenant cloud native control plane system. A request is received by cloud control plane for accessing data. The cloud control plane provisions network connection to service endpoint at cloud provider for providing access using data plane and control plane. The control plane identifies routing information of network traffic from multiple end-user devices to establish the connection. Resiliency of the network is identified based on control plane or data plane failure and maintains the connection. Network patterns are identified for network traffic. These patterns are used by the cloud control plane to determine network policy for data access and routing. The secure tunnel is chosen from multiple tunnels based on the network policy, routing information. Data packets are forwarded by the data plane on the secure tunnel and data access is provided to the client endpoint using the secure tunnel.

The application discloses a low-altitude digital intelligent management platform based on a UAV, belongs to the technical field of UAV management, and comprises a flight route autonomous planning module, a flight speed regulation module, a safety protection module, a network switching module and a user interaction module.The flight route autonomous planning module plans an optimal flight route; the flight speed regulation module dynamically regulates flight speed according to environmental information and geographic information; the safety protection module protects the UAV management platform and reduces intrusion; the network switching module has two working modes, namely, a traditional wireless network mode and a Mesh self-organizing network mode; and the user interaction module realizes man-machine interaction functions.The application can automatically plan a flight route to improve flight efficiency, and dynamically and accurately adjusts the speed of the UAV according to geographic environment conditions, self-operation conditions and wind speed and other factors during UAV flight, so that the UAV can normally perform a task and flight quality is ensured.

The invention belongs to the technical field of cloud computing, and provides a self-adaptive compiling system and method for multi-modal container network convergence management, and the system comprises a network self-adaptive compiling part, a network multi-modal model library part, a network convergence management part, a multi-network integration part, an interface server part and a metadatabase part. According to the method, a multi-mode network mode is fused to ultra-light micro-cloud platform software for unified management, the setting requirement of a user for a network is efficiently and accurately identified, adaptive network mode screening and target network attachment and binding are carried out, network resource occupation detection and network mode adaptive selection and matching in the whole domain range of the micro-cloud platform are supported, and the network resource utilization rate is improved. Network resource waste caused by redundant configuration of a plurality of networks or network cards for the application container due to different CNI plug-ins is reduced, existing IP network resources are utilized and managed uniformly and efficiently, and the complexity of configuration of the application network on the micro cloud by a user is greatly reduced.

The application relates to the technical field of abnormal object recognition, in particular to an abnormal object dynamic behavior pattern recognition method based on a graph neural network, a medium and equipment, through a multi-layer iteration and edge weight-based message passing mechanism, feature representation of each node can continuously fuse weighted information of multi-order neighbors, thereby expanding local and direct correlation into global and potential network mode representation, and behavior coordination of directly / indirectly correlated objects can be captured; through similarity calculation and clustering analysis on the Nth layer intermediate feature vector generated by the graph neural network, nodes with similar behavior patterns and similar structure roles in the network can be automatically collected into a clustering cluster, so that not only individual abnormalities can be determined, but also the whole implicit cooperative abnormal gang without strong direct connection but with high behavior coordination can be accurately locked and pattern classified, and the accuracy and comprehensiveness of the recognition result are greatly improved.

The invention relates to the technical field of mine data transmission, in particular to a data transmission system based on an intelligent mine safety partition, which comprises a safety I area, and the safety I area comprises an automatic control system which performs data transmission with a preset production control ring network through an industrial control protocol; the safety II area comprises a personnel environment safety system, and the personnel environment safety system uploads data to the safety control area through FTP service based on a preset converged communication center; the safety control area comprises an IT type system, and the IT type system is integrated with the comprehensive management and control platform. According to the invention, mine data transmission is subjected to partition design, so that level-to-level management and safety interaction of an automatic control system, a personnel environment safety system and an IT system are realized. The real-time performance and the reliability of the production control looped network are guaranteed, the data isolation protection capability is improved, and the potential safety hazard in a single network mode is avoided.

The invention relates to a network scheduling method and device, computer equipment, a storage medium and a program product. The method comprises the following steps: determining an edge-edge network mode matched with an edge cluster according to a network state and a service requirement of each edge node in the edge cluster; determining a target cluster from each edge cluster according to the cluster performance description information of each edge node in the edge cluster and an edge-to-edge network mode matched with the edge cluster; generating routing configuration information corresponding to a virtual private cloud instance of a target user under a target edge node according to the edge-to-edge network mode matched with the target cluster and the target edge node in the target cluster; the target edge nodes comprise edge nodes used for executing tasks in the target cluster; and issuing the edge forwarding router to the target edge node, and configuring a routing strategy of the target edge node according to the routing configuration information. By adopting the method, the network performance can be improved.