1533 results about "Multi-user" patented technology

The invention discloses a multi-user sharing-oriented multimedia network video recommendation method, which comprises the following steps: firstly, constructing multi-user characteristics by utilizing collected program information in a multi-user sharing environment, and constructing a leading user label according to the similarity of the program characteristics and the continuity of user watching behaviors, so that separation of multi-user mixed logs is realized; performing periodic multi-user identification prediction of future sessions; secondly, building a user interest mining model based on a time-varying LinUCB algorithm to learn interest changes of a user for each program theme, and enhancing the personalized ability and efficiency of a recommendation system from three aspects of parallel calculation, adaptive control of an exploration coefficient and incremental updating based on LSTM; and finally, establishing an article quality model based on a non-time-varying LinUCB algorithm to further ensure the program quality, and integrating the two algorithms into a final recommendation system model by adopting a cross weighting strategy to form a final program recommendation list. The novelty and accuracy of the recommendation result are ensured.

The invention belongs to the technical field of intelligent control, particularly relates to a deep learning-driven intelligent home scene dynamic adaptation method, and aims to solve the problem that an existing intelligent home system is difficult to realize high-precision personalized scene adaptation in a multi-user and multi-device environment due to dependence on a static rule. The method comprises the steps of collecting multi-source heterogeneous user behavior data and performing semantic enhancement preprocessing, constructing a hierarchical time sequence behavior coding model to extract local time sequence dependence and cross-equipment long-range association features, clustering to generate a dynamic scene prototype and mapping the dynamic scene prototype into an executable condition-action rule, after the rules are deployed, a closed-loop optimization mechanism is constructed through explicit and implicit user feedback, and online incremental updating and self-adaptive evolution of the behavior model and the scene rules are achieved. According to the technical scheme, the user complex behavior mode can be deeply understood, the scene adaptation precision is continuously optimized, the individuation level, logic consistency and system robustness of intelligent services are improved, and meanwhile privacy safety and real-time response are guaranteed through edge calculation.

The invention provides a wireless resource scheduling method and device used in a scene in which a mobile phone is directly connected with a satellite, and relates to the technical field of satellite communication, and the method comprises the steps: constructing an electromagnetic map which represents the corresponding relation of a geographic position, a physical resource block and ground interference power in a satellite beam coverage area; link budgeting is carried out on the multiple user terminals in combination with the real-time orbit geometric parameters of the satellite and the electromagnetic map, and the signal to interference plus noise ratio of each user terminal on each physical resource block is predicted; based on the predicted signal to interference plus noise ratio, adopting a proportional fair marginal gain greedy algorithm to allocate an optimal continuous spectrum resource block for each user terminal; on the allocated spectrum resources, optimizing and reallocating the total transmitting power of the satellites by adopting a water injection algorithm; and a final spectrum-power joint scheduling scheme is generated, and subsequent link self-adaption and data transmission are guided. According to the invention, the spectrum efficiency, throughput and connection stability of the system are obviously improved.

The invention relates to the technical field of man-machine interaction, in particular to a multi-user-based ring pairing and left and right hand judgment method and system and a medium, and the method comprises the steps: firstly collecting azimuth angles, distances and historical tracks of a plurality of rings, and clustering the azimuth angles, the distances and the historical tracks into different user clusters; shoulder breadth geometric constraint, posture consistency, micro-motion synchronism and historical prior are fused in the cluster, paired scores are calculated, and paired rings are identified by using a greedy strategy; and then, calculating a judgment score to distinguish the left hand and the right hand by counting the rotation deviation of the angular velocity of the gyroscope on the horizontal plane projection and combining the spatial position score of the ring relative to the human body center line with the historical consistency. A steady-state mode and an event-driven wake-up mechanism are also introduced to balance power consumption. According to the invention, through multi-modal fusion, automatic ring pairing and accurate left and right hand judgment are realized.

The invention relates to a gesture recognition and projection fusion non-contact interaction method and device, equipment and a medium. The method comprises the steps of obtaining multi-user gesture original image data, extracting geometric features and boundary features of a hand contour after image preprocessing and noise removal, and generating recognition result data; secondly, on the basis of three-dimensional coordinate information in the recognition result, a tracking trajectory is analyzed through trajectory continuity, a user identity identifier is matched in combination with a user identity feature library, and user space positioning information is generated; then, a three-dimensional track point sequence is extracted from the user space positioning information, an initial projection area is divided by adopting a dynamic area segmentation algorithm, and an operation area mapping relation is formed; and finally, analyzing the operation area mapping relation to extract gesture action features, generating a control instruction set in combination with a preset rule, and scheduling a conflict instruction to generate an instruction execution sequence. By adopting the method, the scene limitation of traditional contact type interaction can be broken through, and the stability and practicability of non-contact interaction in a multi-user environment are improved.

A system and method for generating and updating a posegraph for multi-user augmented reality experiences. The system receives initial pose data from multiple client devices and generates a posegraph based on this data. When client devices come within proximity of each other, the system detects this and receives relative pose observations from the devices. The system then updates the posegraph based on these observations, assigning confidence values to improve accuracy. This approach enables efficient synchronization of spatial information across devices, allowing for seamless shared AR experiences in large-scale environments without the need for complete map sharing or pre-mapped areas.

The invention provides a multi-user near-field secure communication method based on stacked intelligent metasurfaces, and relates to the technical field of wireless communication. The method comprises the following steps: obtaining an equivalent beamforming matrix and a first-layer channel transmission matrix of an SIM according to parameters of the SIM in a base station; according to the transmission distance between the SIM and the user and the transmission distance between the SIM and the eavesdropper and the parameters of the SIM, modeling a near-field channel to obtain a near-field channel model; obtaining a data transmission rate in combination with a beamforming vector of the base station, and further determining the security and the rate; and by taking maximization of the safety and the rate as a target, constructing an optimization model and decomposing the optimization model into two sub-problems to carry out alternate iterative optimization so as to obtain an optimized equivalent beam forming matrix and an optimized beam forming vector. An SIM is introduced, the freedom degree of beam regulation and control is increased, optimization is carried out on the basis of a near-field channel model by taking maximization of safety and rate as targets, legal users and eavesdroppers are effectively distinguished, signal energy is accurately guided to the legal users, and the communication safety is improved.

The invention relates to the technical field of computer graphics and virtual reality, and discloses a meta-universe social space generation method and system. The method comprises the following steps: acquiring multi-modal input data of a user and constructing an intention vector; extracting social relation characteristics based on the intention vector, and generating a multi-dimensional scene constraint condition; generating a three-dimensional virtual environment and optimizing a topological structure by adopting a generative adversarial network according to a scene constraint condition; and fusing the scene data with the user social behavior data, and outputting a multi-terminal interactive rendering result. The system comprises a data acquisition and intention modeling module, a scene constraint mapping and environment generation module and a fusion rendering and interactive output module. According to the invention, multi-user immersive social space interaction can be realized on the VR head-mounted display, the AR glasses and the mobile terminal, and the method has the advantages of low delay, high simulation degree and cross-platform synchronization.

The invention discloses an intelligent backboard interaction method supporting terminal interconnection, a medium and an intelligent backboard. The intelligent backboard interaction method comprises the following steps: collecting user space motion data to generate a space-time trajectory sequence and binding a user identity label, segmenting a multi-user shooting action data stream in real time, extracting dynamic association features and combining sphere trajectory data to construct a multi-dimensional feature matrix; inputting the matrix into a distributed intention understanding engine, and fusing voice, a touch event and historical data to generate an interactive decision instruction; a dynamic content generation module is driven according to the instruction, a training difficulty coefficient and a tactical matching degree are calculated in real time, and a multi-terminal cooperative control signal is output; and aggregating multi-user and sphere state feedback data, and continuously adjusting a collaborative strategy of a shooting action evaluation standard, a multi-user confrontation rule and terminal display content. According to the method, accurate distinguishing and collaborative intention understanding of multi-user actions are realized, and the training individuation level and the self-adaptive real-time control capability of multi-user interaction are effectively improved.

The invention provides a multi-modal emotion recognition fusion method based on a multi-head attention mechanism, and the method comprises the steps: carrying out the feature extraction and fusion of various data, capturing the internal relation of a modal through the multi-head attention mechanism, achieving the information complementation between modals through cross-modal interaction, and dynamically adjusting the weight according to the quality of the modals. And a self-built database containing a large amount of Chinese data is constructed, and a culture adaptation optimization strategy is combined, so that the generalization performance and culture adaptability of the model in Chinese user groups are improved. The system is deployed on a cloud server, optimized hardware and software configuration is adopted, efficient model reasoning and multi-user concurrent processing are achieved, and the large-scale real-time application requirement is met. The emotion of the user can be monitored in real time and early warning can be provided in scenes such as psychological counseling and group emotion monitoring, professionals are assisted in better understanding the emotion state of the user, and the service effect is improved.

The invention relates to the technical field of music score collaborative editing, in particular to a multi-user collaborative editing method and system for a music score, and the method comprises the steps: an editing signal records at least one ideology element and an ideology form of the ideology element; generating a cooperation level for the at least one user according to the cooperation state; the cooperation state comprises the editing authority of at least one user or the tone deviation degree of at least one user; selecting at least one rule from a rule base for the user according to the cooperation level to form a rule combination; wherein the detection rule is provided with a recommendation tag, and the recommendation tag records a recommended cooperation level; judging whether the editing signal accords with a rule combination; when the judgment result is yes, the editing signal is displayed in a first display mode; if not, generating a prompt signal according to the rule combination and the editing signal; and displaying the editing signal and / or the prompting signal in a second display mode. According to the method, the music score collaborative editing efficiency can be greatly improved.

The invention provides a method for assisting a movable antenna to realize secure communication by STAR-RIS, and relates to the technical field of wireless communication. According to the method, the safety and the rate of the system are maximized by jointly optimizing the beam forming of the base station, the position of the movable antenna and the STAR-RIS coefficient matrix. The method specifically comprises the following steps: constructing a downlink MIMO system and establishing a joint optimization problem; decomposing the joint optimization problem into three sub-problems by adopting an alternate optimization framework; respectively utilizing a particle swarm optimization algorithm and a weighted minimum mean square error method to be combined with a Majoritization-Minimalization algorithm to solve each sub-problem, and respectively utilizing the particle swarm optimization algorithm and the weighted minimum mean square error method to be combined with the Majoritization-Minimalization algorithm to solve each sub-problem; and alternately executing related steps until system security and rate convergence to obtain a solution of the joint optimization problem. By the adoption of the method, the safety communication performance of the system is remarkably improved, full-space coverage and precise beam regulation are achieved, the algorithm convergence is high, the solving efficiency is high, and the method is suitable for a downlink system with multiple users and multiple eavesdropping nodes.

The invention discloses a reconfigurable intelligent surface (RIS)-assisted multiple-input-multiple-output (MIMO) implicit channel estimation method based on a graph attention network, which is used for efficient downlink transmission in a multi-user scene. Firstly, a graph attention network is designed, user nodes and RIS nodes are modeled in a unified mode, received pilot signals serve as initial features, spatial feature expression is enhanced in combination with user three-dimensional position information, and therefore interference between users and a spatial correlation structure are accurately represented; secondly, end-to-end feature aggregation is achieved based on a message passing mechanism, a base station beam forming matrix and an RIS reflection coefficient are directly predicted under the condition that explicit channel estimation is not needed, and the total transmitting power constraint and the unit mode constraint are met through normalization processing so as to complete joint optimization; according to the method, the users and the speed of the system can be remarkably improved under limited pilot frequency overhead, and the method has excellent generalization performance and robustness in a multi-user complex propagation environment.

An electronic device including a receiver configured to receive a first Subscriber Identity Module (SIM); a receiver configured to receive a second SIM; and circuitry configured to receive data from the first SIM; and send a request, to a first public land mobile network (PLMN), to register the electronic device to the first PLMN, wherein the request indicates that the electronic device is a multi-SIM device and the request includes multi-SIM assistance information, and wherein the multi-SIM assistance information informs the first PLMN of the electronic device's preference for multi-SIM operations.

Various aspects of the present disclosure relate to group frequency hopping for ambient Internet of Things (AIoT) devices. For example, a non-orthogonal multiple access mechanism for AIoT devices enabling a group of devices to simultaneously and non-orthogonally transmit different transport blocks (TBs) to a receiver device (a base station, UE, and so on). The group of UEs may perform group frequency hopping to transmit data blocks at different frequencies and time slots. A receiver device may then detect the transmissions (e.g., superimposed signals) using multi-user detection techniques.

A human-machine interface (HMI) development system leverages a generative AI model to assist in development of HMI projects in accordance with specified functional requirements, which can be provided to the development system as intuitive natural language spoken or written text. The system can formulate and implement HMI project edits during design time based on analysis of this natural language design input. After the HMI project is deployed as a runtime application, the system can also receive and process natural language requests to modify the runtime HMI in accordance with described modification criteria.

The invention discloses a real-time software deformation interaction method based on a physical engine in an environment. The real-time software deformation interaction method comprises the following steps: S1, establishing a virtual environment and a software model; s2, constructing an interactive perception and collision detection network; s3, receiving and analyzing a multi-modal interaction instruction; s4, real-time deformation calculation based on a physical engine; s5, performing multi-user collaborative state synchronization and rendering feedback; and S6, carrying out fault state simulation on the software object. According to the method, real-time and high-precision simulation of software deformation is realized through deep fusion of software dynamics calculation of a physical engine and an interaction instruction stream, and through hierarchical physical attribute binding and client prediction, the network synchronization data volume is greatly reduced while the millimeter-level deformation precision is ensured, so that the network synchronization efficiency is improved. And low-delay and high-consistency experience under multi-person cooperative operation is ensured.

The invention provides a sleep assisting system based on photoacoustic magnetic vibration wave resonance, and relates to the technical field of sleep assisting. The system comprises an acquisition unit, a processing unit, a stimulation unit and an evaluation feedback unit. Determining a sleep stage of the user, analyzing phases of multi-scale electroencephalogram rhythm components such as slow waves and spindle waves in a cross-scale manner, and extrapolating and predicting a phase value of a target electroencephalogram rhythm at a future moment in combination with a recent phase trajectory; taking the predicted phase as a target state, mapping a rising / falling slope of a slow wave form into an intensity change parameter of photoacoustic and magnetic vibration stimulation by constructing a mapping channel, and selecting an optimal stimulation combination for output through a decision model based on the intensity change parameter; calculating a phase locking effect index, and adjusting a phase prediction model parameter by using an optimization algorithm according to the index so as to optimize subsequent stimulation; and linkage regulation and control of an external environment are supported, and centralized monitoring of sleep states of multiple users can be realized. According to the invention, self-adaptive guidance of sleep brain rhythms is realized, and the sleep quality is effectively improved.

The invention relates to the technical field of computers, discloses a production command case-oriented interactive deduction method and system, and aims to solve the problems of static solidification of deduction cases, low degree of freedom of interaction, disjunction with real-time production data and low case construction efficiency in the prior art. The method comprises the following steps: constructing a digital twinborn model synchronized with a physical environment in real time; receiving an event injection or parameter adjustment instruction input by a user; driving a multi-agent simulation engine to simulate production process evolution based on the instruction, and generating process simulation data; analyzing the simulation data and quantifying the influence of the decision on the production indexes to form a performance evaluation report; searching a semantic matched historical case knowledge graph, and extracting a disposal plan; according to the scheme, scientific deduction and intelligent assistance of production command decisions are realized, emergency response efficiency is improved, precipitation and reuse of command experience are promoted, multi-user collaborative deduction is supported, and team decision collaborative ability is enhanced.

The invention relates to the technical field of data storage, and discloses a solid state disk compatibility testing method which comprises the following steps: after a solid state disk is started, automatically collecting basic performance information of the solid state disk based on a Python script and generating a standardized log file; running performance operation of the solid state disk in a preset time period, and simultaneously executing multi-user or multi-task concurrent test operation based on the automated script; a script is used for calling a system startup command or a shutdown command, the next startup process is automatically triggered after shutdown, a startup and shutdown cycle test mechanism is formed, and the startup time, the initialization duration and the abnormal interruption record of the solid state disk are synchronously collected in each startup and shutdown process; when the system runs, the Python script is used for safely removing and reinserting the solid state disk. The problem that an existing test method is narrow in platform coverage range is solved.

The invention relates to the technical field of network information security, in particular to a sequence similarity segmentation-based WireGuard multi-behavior traffic classification method and system, and the method comprises the steps: traffic collection: capturing encrypted traffic transmitted by a user through a WireGuard protocol; flow segmentation: dividing the feature sequence into equal sub-sequence fragments to form a plurality of sub-sequence sets with different sub-sequence lengths; calculating the similarity between the interior of the quantum sequence and the adjacent sub-sequences based on the maximum mean value difference function; adopting a greedy strategy to select connection points between K most dissimilar adjacent subsequences as segmentation points; feature extraction: constructing a multi-dimensional flow path based on the segmented subsequences; extracting path signature features on the multi-dimensional flow path by adopting a sliding window method; and traffic classification: inputting the path signature features into an LSTM model for time sequence modeling, and realizing classification of user behaviors through a full connection layer. According to the method, automatic, lightweight and fine-grained accurate classification of multi-user behaviors in encrypted traffic is realized.

The invention discloses a table collaborative editing method and system, and relates to the technical field of artificial intelligence, and the method comprises the following steps: during multi-user collaborative editing, receiving user editing operations, packaging each user editing operation into an independent operation sequence, summarizing all the operation sequences, and performing unified operation on the operation sequences, the operation sequence comprises content information and parameter information of user editing behaviors; performing operation conflict detection based on the operation sequence, and if an operation conflict is detected, dividing the conflict into a direct conflict, a structure conflict, a style conflict and a dependency conflict through a conflict classifier; corresponding strategies are matched and executed for different conflict types through the intelligent conflict solver, the strategies comprise the automatic merging strategy, the user selection strategy and the delay processing strategy, and the problems that in the prior art, cell merging intelligent verification cannot be achieved, and conflict solving cannot be achieved during multi-user collaborative editing are solved are solved.

Estimated and actual processor runtimes improve computer functioning in fairly sharing computing resources. Today's computers and cloud-based services serve many users and many software applications sharing CPU resources. An operating system thus implements a scheduling policy that fairly allocates CPU time. A scheduler thread implements the scheduling policy based on estimated processor runtimes, and actual processor runtimes, associated with tasks. The operating system may maintain running tallies or totals for a user / group / organization based on credits (e.g., the estimated processor runtimes) and / or on penalties (e.g., the actual processor runtimes). The scheduler thread may select tasks for worker threads based on the credits and / or the penalties, thus ensuring that no user / group / organization unfairly consumes CPU time.

The invention discloses a GNN signal detection method based on an attention mechanism in a cellular-removed large-scale MIMO system, and belongs to the technical field of wireless communication. Aiming at the problem that the traditional EP algorithm adopts independent Gaussian approximation for multi-user posterior distribution and cannot effectively capture interference association among users, the method is combined with a graph neural network and a 2D MHA module, the 2D MHA module captures the interference relation between users through the time attention sub-block, the frequency attention sub-block captures the correlation between different features, the two outputs are spliced and subjected to linear projection to form enhanced feature representation, and meanwhile the fusion capacity of prior and likelihood information is enhanced through the EP module. According to the method, the low calculation complexity is kept while the detection precision is improved, and the adaptability and robustness of the algorithm in different channel and network environments are remarkably enhanced.

A spatial adaptive multi-user service modulation and demodulation method suitable for various channel environments is characterized in that an uplink channel is configured with multiple paths of general carriers and multiple paths of helicopter special carriers in a frequency division mode, and the general carriers support uplink adaptive information transmission of terminals of various types and sizes in an MF-TDMA (Multimedia Frequency-Time Division Multiple Access) system; the on-satellite demodulator obtains a modulation coding mode of a burst data segment by identifying mode word information in a physical layer frame header, and demodulates a corresponding mode; the carrier special for the helicopter uses a continuous carrier mode, and multi-rate channel error correction coding and decoding under rotor wing shielding are supported in a channel interleaving mode. Downlink transmission is carried out in a fixed time slot and free time slot time division mode, and downlink information transmission for universal multi-type terminals and helicopter terminals can be supported at the same time. Compared with a common spatial modulation and demodulation method, the modulation and demodulation scheme provided by the invention can support adaptive transmission of general services of multiple types of terminals and helicopter service information on both an uplink and a downlink by using one satellite-borne modem.

The invention discloses a multi-user emotion recognition and digital human feedback method based on behavior data, and belongs to the field of artificial intelligence emotion calculation. Sensing user approaching, identifying and confirming the identity of a registered user, distributing an identifier, distributing an identifier for a visitor, and establishing an independent session channel in a multi-user scene; capturing time sequence dialogue behavior data containing voice rhythm features, dialogue interaction modes and linguistic features in real time; inputting the data into a sequence information processing model based on a state space theory and provided with a data dependence selection mechanism and an emotion analysis model spliced by static context features, and outputting multi-dimensional emotion and cognitive state tags; generating an emotion support strategy through a decision-making model in combination with the personal file of the user; and generating a multi-mode control instruction, and driving the digital human to synchronously present special effects such as expressions and the like. According to the method, privacy concerns are eliminated through non-intrusive collection, the method is adaptive to multi-user scenes, deep cognitive states can be recognized, and interaction effectiveness is improved for a long time.

Provided are a spatial reuse method and apparatus. The method includes: receiving a radio frame and determining whether the radio frame carries a trigger frame configured to trigger uplink multi-user transmission according to indication information of the trigger frame in a physical signaling field of the radio frame; when the trigger frame is determined to be carried in the radio frame, receiving, by a station, the trigger frame, and acquiring first spatial reuse information of the trigger frame; at an end of a radio frame reception process, determining whether to perform first spatial reuse according to the first spatial reuse information. The present disclosure solves the problem in the related art of low spatial reuse efficiency when a station performs spatial reuse on a radio frame and achieves a technical effect of improving network performance.

The invention relates to a hardware simulation accelerator multi-user access method, system and device and a storage medium, and is applied to the technical field of hardware simulation accelerators, and the method comprises the following steps: distributing a plurality of resource blocks for different users in a hardware simulation accelerator to obtain a user resource block corresponding table; virtualizing the plurality of PCIe devices in the host interface card to obtain a plurality of mutually independent virtual function devices; constructing a plurality of device driving programs corresponding to the plurality of virtual function devices in the host server; binding a plurality of corresponding equipment driving programs for different users in the host server to obtain equipment driving program binding information; and performing multi-user access of the hardware simulation accelerator according to the user resource block corresponding table, the device driver binding information and the plurality of virtual function devices. The method has the technical effect that the multi-user access to the hardware simulation accelerator can be realized faster and more stably.

An embodiment provides for a base station (BS) in a wireless network, the BS including memory and a processor coupled to the memory. The processor can cause the BS to determine a first gain region of a first beam index associated with serving a first user equipment (UE) and determine a first interference region of the first beam index associated with serving a second user equipment (UE). The processor can further calculate a beamforming weight of the first beam index using an analog null algorithm wherein the first gain region and the first interference region are inputs to the analog null algorithm to optimize for a threshold criterion. The processor can also transmit a first beam having the beamforming weight of the first beam index as part of a multi-user multiple-input multiple-output (MU-MIMO) operation.

The invention relates to the field of data transmission, and discloses a scheduling method for parallel transmission of multi-user video streams, which comprises the following steps of: decomposing each user video stream in a frame sequence layer, a code rate layer and a network buffer layer, and establishing a mapping unit for decomposed segments in a multi-dimensional state domain; based on the initial transmission situation map, asynchronous disturbance injection is carried out on the high-priority fragments; continuously monitoring the disturbance trajectory of the dynamic dependency scheduling layer in the flow, and identifying a delay abnormal region; mapping the generated semi-adaptive bandwidth allocation factor to a transmission node corresponding to each video stream in a network topology, and performing real-time regulation and control on a shunting proportion, a caching strategy and a priority weight of the transmission node through a nonlinear regulation function; in a dynamic scheduling topology convergence stage, joint integration is performed on a local bandwidth adjustment gradient and node topology weight attenuation. The method has the advantage of improving the continuity of multi-user video playing.