47 results about "Functional networks" patented technology

The invention discloses an epilepsy abnormal brain network identification method based on a multi-scale static-dynamic fusion network, and belongs to the field of brain image analysis. The method comprises the following steps: firstly, constructing a static function connection weighted graph and a dynamic function connection graph; and fusing the static and dynamic representations by adopting a cross attention module. In order to describe a multi-scale spatial relationship, performing lexical meta-processing on brain connection according to anatomical partition and a functional network; and the local-global fusion module is used for integrating the fine granularity and the macroscopic relationship, so that the brain region with diagnostic significance is highlighted. In the training stage, cross entropy, reverse contrast loss and sparse regularization based on contrast graph adjacency matrix entropy are jointly used. The method is verified on multi-center functional magnetic resonance data, compared with other mainstream depth models, the classification accuracy, generalization and interpretability are remarkably improved, an abnormal brain region consistent with an epilepsy network can be positioned, and brain image markers with biological significance can be connected and recognized.

The present application relates to a zero trust-based service system access control method and apparatus, a device, and a medium. The method comprises: triggering, among core network functional network elements of a network, a session management function network element or an AAA server to send a user re-authentication request to a user terminal, so that the user terminal returns current user information to the AAA server; upon the AAA server verifying that current user identity information is consistent with user identity information corresponding to a target user, determining an identity authentication success result; on the basis of the identity authentication success result and the current user identity information, the AAA server initiating a biometric authentication request to the user terminal, so that the AAA server checks whether most recent biometric information of the target user returned by the user terminal matches pre-stored biometric information of the target user, and if so, returns a biometric authentication success result to the user terminal, so as to authorize the target user to continue accessing a target service system. The present application can prevent several security issues, such as unauthorized control over authorized devices.

The invention relates to a depression risk detection method based on self-adaptive multi-scale neighborhood perception fusion space-time diagram convolution, and aims to solve the problems that traditional depression diagnosis is subjective and existing electroencephalogram detection space-time feature modeling is insufficient. The method comprises the following steps: acquiring electroencephalogram signals of a testee, and extracting frequency spectrum features through a frequency domain feature extraction module; in combination with an adjacent matrix (independent of an electrode physical distance) which is adaptively learned and normalized in training, embedded features are generated through a graph convolutional neural network; and then capturing long-time-history dependence through a dynamic feature extraction module, realizing feature multi-level fusion by means of a multi-cascade multi-scale convolution module, finally integrating local and global features through an adaptive feature fusion module, and inputting a prediction layer to output a detection result. According to the method, electroencephalogram signal time-space domain joint modeling is achieved, brain region function connection dynamic and multi-scale neural features are effectively captured, information redundancy and key feature loss are avoided, classification accuracy and generalization ability are remarkably improved, depression-related key brain region and function network features can be revealed, and the method has high interpretability and potential clinical application value.

The invention provides an automatic test system and method for a third-party high-power repeater, and relates to the technical field of automatic test equipment, and the system comprises an integrated reconfigurable passive link box, a control host, a vector signal generator and a vector signal analyzer. The integrated reconfigurable passive link box comprises a box body, a radio frequency switch matrix network, an embedded function network, a control port, an input port, an output port, an uplink interface and a downlink interface. The radio frequency switch matrix network and the embedded function network are arranged in the box body. The input port, the output port, the uplink interface and the downlink interface are arranged on the surface of the box body. The vector signal generator is connected with the input port, the vector signal analyzer is connected with the output port, and a third-party high-power repeater to be tested is arranged between the uplink interface and the downlink interface. According to the invention, the radio frequency switch matrix network and the embedded function network are packaged in the integrated reconfigurable passive link box, and the control host is utilized to carry out automatic testing on the third-party high-power repeater according to the preset process, so that frequent operation processes are avoided, and damage to instruments is reduced.

The invention provides a brain function network causal analysis method based on phase-space reconstruction and unified GCA, and relates to the field of functional brain network analys.The method comprises the steps that fMRI data are collected and preprocessed, and a time sequence of interested nodes is extracted from the preprocessed fMRI data; for extracting time sequences X and Y of any two to-be-analyzed interested nodes, constructing a variable time delay unified Granger causal model based on phase space reconstruction; and traversing all to-be-analyzed node pairs of interest, calculating the causal direction and strength between each pair of nodes to construct a whole-brain directed causal connection matrix, and performing network metric attribute analysis. According to the method, phase-space reconstruction is taken as a core, a causal analysis framework is provided by unifying GCA, and end-to-end modeling is realized. The final target is to generate a high-fidelity fMRI data model, so that the causal connection relationship is closer to a brain real neural mechanism, and the reliability and the application value of functional brain network research are improved.

The invention relates to a brain anomaly network positioning method and system based on functional connection network mapping in the technical field of neural image data processing. The brain abnormal network positioning method comprises the following steps: calculating a whole brain function network diagram connected with each abnormal site by using resting state function connection data of large-scale health subjects based on a plurality of dispersed abnormal sites reported in previous literatures; then superposing the function network diagrams to obtain a network probability graph; and finally, filtering the probability graph through a threshold value to obtain a final core anomaly network graph. According to the method, the inherent functional connection architecture of the brain is used as a reference system, abnormal sites which seem to be uncorrelated in different researches are successfully traced and unified to a common and stable functional network, and compared with a single brain region marker, the generated network-level biomarker integrates more source evidences, so that the network-level biomarker has the advantages that the network-level biomarker can be widely applied to the field of biomarkers of the brain region. Therefore, the problems of result heterogeneity and inconsistency in brain abnormality discovery are solved.

The application relates to the technical field of wireless communication, in particular to a service providing method and device, a computer device and a storage medium. The method comprises the following steps: receiving an initial service request sent by a service demander; performing address inverse transformation on a target FQDN to obtain a service network address; replacing the target FQDN in the initial service request with the service network address to obtain a target service request; and sending the target service request to a service provider, so that the service provider provides services to the service demander according to a functional network element corresponding to the service network address. The application realizes the sending of the service network address under the condition that only the SEPP network element performs address inverse transformation on the target FQDN to obtain the service network address, without the functional adjustment of other network elements, so that the communication mechanism does not need to additionally construct a DNS or a database, the management and maintenance cost of maintaining the mapping relationship between the domain network FQDN and the service network address is reduced, and the risk of service transmission interruption is also reduced.

The application relates to a method and device for predicting the risk of depression of a post-stroke patient, a medium and an electronic device. The method comprises: acquiring a brain image of the post-stroke patient and a standard graph of a depression functional network, the standard graph of the depression functional network being used to represent a brain functional network related to post-stroke depression; calculating a network damage score of the post-stroke patient according to the brain image and the standard graph of the depression functional network; acquiring a standard graph of depression structural disconnection, the standard graph of the depression structural disconnection being used to represent a brain disconnection distribution related to post-stroke depression; calculating a structural disconnection score of the post-stroke patient according to the brain image and the standard graph of the depression structural disconnection; inputting the network damage score, the structural disconnection score and clinical information data of the post-stroke patient into a prediction model to determine the risk of depression of the post-stroke patient after several months of onset through the prediction model. The application can predict the risk of depression according to the direct impact of a stroke lesion on a brain network responsible for emotion regulation in the brain.

The application belongs to the technical field of communication, and particularly relates to a network performance testing method, a network performance testing device, a computer readable medium, an electronic device and a computer program product. The method comprises the following steps: establishing a network performance testing channel for communication connection with a specified network element, wherein the specified network element is a functional network element specified in a core network of a communication system; and performing data communication with the specified network element based on the network performance testing channel, so as to obtain network performance parameters of communication traffic. The application can improve the accuracy of network performance optimization.

A modular spacecraft includes a backbone support structure to provide structural support and integrate various functional networks. The backbone support structure is equipped with mechanical connectors for the secure attachment of multiple modules, and supports a plurality of network systems that includes power distribution, data transmission, and a thermal fluid loop. This modular design allows for the flexible and scalable assembly of the modular spacecraft, enabling different configurations and facilitating the integration of various modules with distinct functions or payloads. The backbone support structure's integrated networks ensure that all modules operate cohesively, enhancing the modular spacecraft's operational efficiency and adaptability.

This invention discloses a hypergraph representation method for brain functional networks. The steps include: preprocessing resting-state functional magnetic resonance imaging (fMRI) to obtain time series data for all brain regions; dividing the entire time series into multiple overlapping sub-sequence segments using a sliding window; constructing a dynamic brain functional network and transforming it into an optimization model; constructing a hypergraph of the dynamic brain functional network using the nearest neighbor algorithm; dynamically modifying the hypergraph structure through convolution operations and extracting features to obtain a new dynamic hypergraph; extracting the Laplacian matrix of the dynamic hypergraph; constructing the manifold regularization term of the Laplacian matrix and simultaneously introducing the manifold regularization term and the L1 norm regularization term into the optimization model to obtain the hypergraph representation of the brain functional network. This invention is used to represent functional interactions and higher-order relationships between multiple brain regions, determine discriminative brain functional network classification features, and effectively improve the classification performance of brain disease features.

Method for analyzing a mechatronic system, wherein the mechatronic system has one or more functions, the functions comprising one or more hardware and / or software functions, and in the method - a first network (20) in the form of a tree graph with several hierarchy levels and nodes (201, 202, 203, 204, 205, 206) arranged in the hierarchy levels is provided, wherein the nodes (201-206) are each representative of one of the functions of the mechatronic system and are linked to each other via one or more logical operators, such that the tree graph represents dependencies between the functions represented by the nodes (201-206), wherein the top hierarchy level has a single node (201) as the initial node, - a node of the tree graph of the first network (20) is specified as the first trigger node, - Software network data is provided that is representative of the software functions of the mechatronic system and their dependencies, - depending on the first trigger node and the software network data, a second network (30) in the form of a tree graph with several hierarchy levels and nodes (301, 302, 303, 304, 305) arranged in the hierarchy levels is determined, wherein the nodes (301-305) are each representative of one of the software functions of the mechatronic system and are linked to each other via one or more logical operators, such that the tree graph represents dependencies between the software functions represented by the nodes (301-305), wherein the top hierarchy level has a single node (301) as the initial node, and - depending on the first network of action (20) and the second network of action (30), the mechatronic system is analyzed, wherein an analysis of the mechatronic system includes that - the first network (20) is extended by the second network (30) such that the first trigger node of the first network (20) corresponds to the initial node of the second network (30), and - the mechatronic system is analyzed depending on the extended first network of action (40), wherein the mechatronic system has one or more diagnostic functions that are representative of one or more software functions for diagnosing the mechatronic system, in which - a node of the tree graph of the extended first network (40) is specified as the second trigger node, - one of the diagnostic functions is specified and assigned to the second trigger node, - Diagnostic network data is provided that is representative of the diagnostic functions of the mechatronic system and their dependencies, - depending on the second trigger node and the diagnostic network data, a third network (50) is determined in the form of a tree graph with several hierarchy levels and nodes (501, 502, 503, 504, 505) arranged in the hierarchy levels, wherein the nodes (501-505) are each representative of one of the diagnostic functions of the mechatronic system and are linked to each other via one or more logical operators, such that the tree graph represents dependencies between the diagnostic functions represented by the nodes (501-505), wherein the top hierarchy level has a single node (501) as the initial node, such that the second trigger node of the extended first network (40) corresponds to the initial node of the third network (50), and - depending on the extended first network (40) and the third network (50) the mechatronic system is analyzed.

The invention discloses a functional network structure design method and application of a high-thermal-conductivity wave-absorbing composite material. The method comprises the following steps: S1, adding wave-absorbing functional particles into a polymer matrix by a melt blending or solution mixing method to obtain a wave-absorbing composite material; and crushing or crushing the wave-absorbing composite material to obtain the wave-absorbing functional particles. S2, mixing the wave-absorbing functional particles with the heat-conducting functional particles, so that the wave-absorbing functional particles are coated with the heat-conducting functional particles to form composite particles; and then loading the composite particles into a mold, pre-pressing to discharge gas among the particles, then carrying out hot pressing, and cooling to obtain the composite material with the three-dimensional communicated heat-conducting and wave-absorbing dual-function network structure. According to the invention, the heat-conducting functional particles are selectively distributed at a polymer particle micro-area interface through a hot-pressing process to construct an isolation structure, a continuous heat-conducting network is formed, and the composite material with excellent heat-conducting property and wave-absorbing property is obtained and can be used as an electronic chip packaging material and used in the field of electromagnetic compatibility.

The application relates to a user identity authentication system, method, device, network equipment and storage medium. The system comprises at least one network, the network comprises a distributed network and a functional network, the distributed network comprises a visiting network, wherein the visiting network is used for receiving a service request sent by a user terminal, and forwarding the service request to a target network corresponding to a target service in the case that the visiting network cannot provide the target service corresponding to the service request; the target network is used for sending an authentication request to the user terminal according to the service request; the target network is also used for receiving a terminal digital certificate sent by the user terminal in response to the authentication request, checking the terminal digital certificate, and providing the target service for the user terminal in the case that the terminal digital certificate passes the check. The system can make other networks authenticate the identity of the user terminal when the user needs to use the network other than the visiting network.

Functional networks are mapped for individuals and group populations based on magnetic resonance imaging, and the resulting functional mapping data (e.g., probabilistic maps of functional networks and / or integration zones where multiple functional networks overlap and / or interact) are used to guide or otherwise monitor the delivery of neuromodulation therapies. Individual-specific functional network maps can be generated based on an overlapping template matching that is capable of assigning multiple networks to a given grayordinate.

The invention discloses a CoWoS packaging bottom filling material and a preparation method thereof, and relates to the technical field of semiconductor packaging materials, and the filling material comprises the following components by mass: 50-80 wt% of a polyaryletherketone matrix; 20-50 wt% of a hybrid filler; the hybrid filler is prepared from nickel-plated graphene nanosheets, silicon carbide whiskers, boron nitride nanosheets and graphene quantum dots; wherein the nickel-plated graphene nanosheets account for 30-50 wt% of the hybrid filler, the silicon carbide whiskers account for 25-40 wt% of the hybrid filler, the boron nitride nanosheets account for 20-35 wt% of the hybrid filler, and the graphene quantum dots account for 1-5 wt% of the hybrid filler; by optimizing the composition and interface design of the hybrid filler, different fillers have a synergistic effect, the heat conduction and mechanical properties are improved, and the high-density packaging requirement is met; quantum dot modification, in-situ polymerization and melt blending processes are integrated, the structure and performance of the material are accurately regulated and controlled, a continuous functional network is formed, the purity and stability are improved through post-treatment, the material adapts to a high-temperature environment, and long-term reliable operation is guaranteed.

A functional network map of the somatomotor cognitive action network (SCAN) is generated from magnetic resonance data based on a template matching of time-course signals with one or more functional network templates. A first network map is generated using correlations of the time-course signals with the functional network template(s) at a first threshold value. The first network map is then updated by reassigning grayordinates in the first network map based on correlations generated using a second threshold value that is higher than the first threshold value. A network confidence map can be generated to indicate the confidence in network assignments. The network confidence map is generated using a permutation-based analysis in which dense time series data are partitioned, the partitioned shuffled based on a number of permutations. Network assignments are generated for each permutation and compared across shuffles to assess network confidence.

Provided in the embodiments of the present application are ephemeris data processing methods, a communication device, a storage medium and a product. A method comprises: acquiring ephemeris data on the basis of communication association information, and storing the ephemeris data in an ephemeris database (310); and on the basis of an ephemeris data acquisition request, acquiring, from the ephemeris database, target ephemeris data corresponding to the ephemeris data acquisition request, and sending the target ephemeris data to a target functional network element corresponding to the ephemeris data acquisition request (320).

The embodiment of the invention provides a quota management method and device, and relates to the technical field of core network charging and the like, the method comprises the following steps: sending a first request message corresponding to first equipment to a second functional network element in a visited network, the first equipment being equipment in a roaming state; and receiving first quota information configured by the second function network element, wherein the first quota information is used for indicating the quota of the first equipment. The method and the device are used for improving timeliness of providing roaming service for first equipment.

The present disclosure relates to the technical field of satellite communications, and relates to a handover control method, a functional network element, a communication system and an electronic device. The handover control method in the present disclosure is executed by a first functional network element, and comprises: receiving a handover target determination request sent by a second functional network element, wherein the handover target determination request comprises location information of a user equipment, a service time range and an identifier of a currently accessed satellite; on the basis of the location information of the user equipment, the identifier of the currently accessed satellite and change information of a topology structure of a satellite network, determining one or more target satellites for the user equipment to perform continuous handover within the service time range; and sending a handover target determination response to the second functional network element, wherein the handover target determination response comprises identifiers of the one or more target satellites, such that the second functional network element controls the handover of the user equipment on the basis of the identifiers of the one or more target satellites.

The invention provides a carrier phase measurement quantity reporting method and device and a storage medium, and the method is applied to first communication equipment, and comprises the steps: obtaining a first signal which is a signal obtained by modulating an excitation signal through Internet of Things equipment; determining a carrier phase measurement quantity corresponding to the excitation signal based on the first signal; and sending the carrier phase measurement quantity to a first functional network element, wherein the carrier phase measurement quantity is used for positioning the Internet of Things equipment. According to the scheme of the invention, the calculation and reporting of the carrier phase measurement quantity in the positioning scene of the Internet of Things equipment can be realized.

This application provides a communication method and a communication device, relating to the field of communication technology. The method includes: obtaining the quality of service (QoS) result between each of the M user plane functional network elements and an access network device, where M is an integer greater than or equal to 1; and determining a first user plane functional network element among the M user plane functional network elements based on the QoS result between each of the M user plane functional network elements and the access network device. The method in this application helps to select a suitable user plane functional network element, thereby achieving a better transmission path and improving the transmission performance of services.

The application discloses an electromagnetic shielding semiconductor heat-conducting adhesive with wave-absorbing function, and relates to the technical field of functional adhesive.The electromagnetic shielding semiconductor heat-conducting adhesive with wave-absorbing function is composed of the following components in parts by mass: 90-110 parts of base resin, 40-55 parts of wave-absorbing and electromagnetic shielding composite filler, 25-40 parts of heat-conducting filler, 2-6 parts of coupling agent, 8-16 parts of curing system and 3-9 parts of auxiliary agent.The application breaks through the limitation that traditional functional adhesive can only realize heat conduction or electromagnetic shielding, and through unique composite filler system design, the adhesive no longer needs to be selected or simply superimposed between different functions, but forms a double functional network structure, can simultaneously cope with the electronic equipment heat management demand and the complex electromagnetic environment interference, and meets the urgent demand of high-end electronic packaging on multifunctional integrated materials.

The present application discloses a sensing delay management method and device. The method comprises: a first functional network element receiving a sensing service request, the sensing service request comprising delay requirements of a sensing service; sending first information to a second functional network element, the first information being used for indicating delay requirements for the second functional network element to execute a sensing-related operation that comprises at least one of the following: acquiring original sensing data, calculating sensing data, transmitting sensing data, and storing sensing data; and sending second information to a third functional network element, the second information being used for indicating delay requirements for the third functional network element to execute a sensing-related operation that comprises at least one of the following: calculating sensing data, transmitting sensing data, and storing sensing data. In the method of embodiments of the present application, delay slicing and management are performed for each operational process of a sensing service according to delay requirements of the sensing service, thereby ensuring reliability of an execution process of the sensing service.

This invention relates to the field of medical image processing technology, specifically a method for constructing a brain functional network based on a large language model. First, the functional magnetic resonance imaging (fMRI) data of the subject is preprocessed, brain regions are divided based on a pre-defined atlas, and average time series data are extracted. Then, a large language model is used, referencing a neuroscience knowledge base, to generate prior knowledge text descriptions for each brain region. Simultaneously, instance-level text descriptions are generated based on the activation state and correlation of the time series data. The prior knowledge text and instance-level text are fused and converted into node feature vectors using a professional text encoder. Furthermore, this method constructs a brain map containing node features and edge connections, which is then input into a graph neural network for feature learning and classification training. By deeply integrating prior textual knowledge from the medical field with image data, a brain functional network rich in semantic information is constructed, significantly improving the accuracy of brain disease identification and the model's generalization ability.

The invention discloses a method and system for predicting infant brain function connection based on morphological characteristics and a diffusion model, a storage medium and electronic equipment. The method in the formula comprises the following steps: extracting cortex morphological characteristics in an infant structure magnetic resonance image (sMRI), constructing a morphological similarity network (MSN), and realizing infant brain function full-connection layer prediction by utilizing a diffusion model in combination with classifier irrelevant guidance and a cross-modal attention mechanism. According to the method, individual development features are stably captured by using a longitudinal information extraction module, accurate mapping from morphological features to function connection is realized in combination with a classifier irrelevant guidance diffusion model and a morphological guidance attention mechanism, the prediction precision and stability are remarkably improved, and the prediction efficiency is improved. The problem that infant functional magnetic resonance imaging (fMRI) data is scarce or low in quality can be effectively solved, functional networks in different development stages are accurately reconstructed, and the accuracy of infant early brain development monitoring is improved.

The application provides a MXene-based braiding functional composite fiber and a preparation method thereof, and belongs to the technical field of functional fiber materials. The MXene-based braiding functional composite fiber provided by the application can realize the synergistic improvement of braiding and functionality. The TPU macromolecular chain serves as a flexible skeleton, promotes fiber forming and macro flexibility. The few-layer MXene nanosheet uniformly dispersed in the TPU macromolecular chain builds an initial conductive network in the core layer. The PPy skin layer grown through in-situ polymerization not only contributes to high electrochemical activity and increases the interlayer spacing of the MXene, but also forms a synergistic effect with the MXene to improve the electrochemical performance, and builds a three-dimensional synergistic conductive structure in the fiber, which is connected from inside to outside and stable. The structure ensures that the conductive and functional network of the fiber is not easily damaged when the fiber bears the mechanical action of textile processing, so that the mechanical durability and electrochemical performance are achieved.

The invention relates to the technical field of communication, in particular to a service verification method and device, and aims to guarantee the efficiency and accuracy of service verification and improve the range of service verification through a virtual-real combination mode of a digital twin network and a physical twin network. The method comprises the following steps: acquiring a service verification request, wherein the service verification request comprises a service demand of a network service; according to the service verification request, a verification environment corresponding to the network service is configured based on a digital twin network and a physical twin network corresponding to the physical network; obtaining a verification result of the network service, wherein the verification result is determined by verifying the service capability of the network service in the verification environment; wherein the verification environment comprises a first verification environment constructed based on a digital twin network and a second verification environment constructed based on a physical twin network; alternatively, the verification environment is constructed based on at least one digital twin function network element in the digital twin network and at least one physical twin function network element in the physical twin network.

The invention discloses a preparation method of composite molding conductive silica gel, and belongs to the technical field of functional polymer composites.The preparation method of the composite molding conductive silica gel comprises a silica gel matrix; the functional network is integrated in the silica gel substrate, the functional network comprises a sensing unit, the sensing unit is configured to generate a detectable resistance signal in response to mechanical deformation, and the resistance signal presents a negative pressure resistance effect in an initial stretching stage. According to the invention, stable and adjustable'negative pressure resistance-positive pressure resistance 'asymmetric response is realized in conductive silica gel, the limitation that a traditional sensor can only provide monotonic signals is changed, a solid hardware foundation is provided for capturing high-dimensional information sensing of strain size, rate and mode, and through an exquisite microstructure design, the sensor can be used for sensing high-dimensional information of strain size, rate and mode. The material not only realizes high sensitivity and high signal-to-noise ratio, but also has unique strain rate sensitivity, so that the material can accurately capture dynamic information which cannot be identified by a traditional sensor.

The present disclosure relates to the technical field of communications, and provides an access permission management method and apparatus, and a storage medium. The method is applied to a first functional network element, and comprises: receiving a digital identifier sent by a first network device, the digital identifier being a digital identifier of a terminal; on the basis of the digital identifier, determining structured information of the terminal; and sending the structured information to the first network device, the digital identifier and the structured information being used for determining whether the terminal has permission to access the first network device. According to the solution of the present disclosure, the efficiency of access permission management can be improved.