2532 results about "Multi-user" patented technology

An autonomous environmental regulation and behavioral monitoring system is disclosed, configured to adapt temperature, lighting, and acoustic conditions based on real-time emotional and physiological data. The system includes a dual-redundant central processor, hierarchical communication networks, multi-angle visual acquisition units, infrared thermometers, and modular environmental subsystems. It detects posture, gestures, facial expressions, and thermal signals to classify user states and apply individualized airflow, light, and sound modulation without relying on external internet connectivity. The system also monitors connected appliances using voltage-based pressure analysis to forecast device degradation. With integrated gesture recognition, privacy-preserving data handling, and predictive adaptation, the invention enables multi-user personalization, long-term learning, and uninterrupted operation within residential, administrative, or healthcare infrastructures.

The invention provides an AI-based multi-user data storage docking and secure transmission method, which comprises the following steps of: acquiring a propagation path of a hot topic according to a multi-modal content association graph, performing fragmentation storage on the propagation path by adopting a clustering algorithm, and generating a fragmentation storage index table; when the relevance of different modal contents is higher than a preset threshold value, determining that the sensitivity grading result is consistent with the multi-modal relevance, performing dynamic rule adjustment by adopting a deep learning model, generating a dynamic auditing rule set, and obtaining boundary judgment parameters of the rule set; and distributing the dynamic auditing rule set and the decision transparency index to each service line by adopting a cross-platform data synchronization protocol according to the auditing decision log, generating a cross-platform consistency auditing standard, and obtaining a synchronization log of standard execution.

The invention belongs to the technical field of power system load prediction, and discloses a cross-dimension multi-scale fusion load prediction method based on multi-user load time-space correlation, which comprises the following steps of: firstly, preprocessing user load statistical data, extracting time sequence dependence and periodic characteristics in a time sequence, and calculating the time sequence dependence and periodic characteristics of the user load statistical data; introducing a channel attention mechanism to adaptively mine key variable information; then, a multi-scale space-time fusion module is combined with frequency domain analysis and a graph convolutional network to realize depth feature interaction under different time scales and space levels; and finally, outputting a load prediction result under a plurality of time granularities in the future through a linear projection structure. Compared with an existing method, the method has the remarkable advantages in the aspects of capturing a complex load mode, improving model prediction precision and enhancing generalization ability, and is suitable for various application scenes such as power consumer energy consumption management and power grid load dispatching.

The invention discloses a virtual-real fusion exhibition display interaction system and a multi-mode perception method, and belongs to the technical field of exhibition display interaction. The system collects audience eyeball fixation points, gesture actions and ambient light data through AR / VR equipment, analyzes coordinates of a region of interest through an eyeball fixation point attention mechanism, a gesture space-time encoder and a multi-modal fusion unit, triggers holographic projection explanation and virtual exhibition stand light and shadow dynamic adjustment (including illumination intensity, color, Gaussian blur and the like) based on a threshold value, and performs real-time display on the virtual exhibition stand. And multi-user collaborative interaction is realized through federal learning. According to the method, reinforcement learning is adopted to optimize an event-driven threshold value, and virtual and real visual splitting is eliminated in combination with ambient light adaptive mapping. The problems of low participation degree, insufficient single-mode interaction information and multi-user cooperation of traditional exhibition are solved, interest analysis accuracy is improved through multi-mode fusion, personalized experience is enhanced through dynamic interaction, the method is suitable for multiple scenes such as museums and science and technology museums, and exhibition intellectualization, immersion and group interaction efficiency are effectively improved.

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 provides a multi-party collaborative anti-quantum signature method and system based on homomorphic Hash, and relates to the technical field of digital signatures, the system comprises a plurality of participants and a verification party, and the method is specifically as follows: each participant generates a pair of public and private keys, the public key is composed of a total public key, a total signature matrix and a total Hash matrix of all participants; based on the public and private keys, all participants perform multi-party signature on the target message through a homomorphic hash function, and a generated signature is composed of total hash challenge values of all participants, total response vectors of all participants and commitment value high-order difference values of all participants; according to the signature, the verifier recovers the high order of the total commitment value, further calculates the total hash challenge value, and verifies the validity of the signature through comparison of the total hash challenge value; according to the method, multi-user collaborative signature is realized, and the security of resisting malicious opponents under a quantum computer is obtained.

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 relates to the technical field of charging pile management and power dispatching, and particularly discloses a charging pile operation management method and system. The method comprises the following steps: acquiring charging request data and power grid load data, and generating and cleaning a task vector data set; predicting a charging demand based on the data set and generating electricity price gradient information; a multi-objective optimization scheduling function is constructed and solved, and a task allocation scheduling scheme is generated; executing power control according to the scheduling scheme and collecting charging state data; executing dynamic contract charging and incentive generation according to the state data; and finally, performing Hash packaging and privacy processing on an execution result, and performing uplink to generate a credible record. According to the method, the resource allocation efficiency and the charging incentive intelligence level in a multi-user multi-period concurrent charging scene can be improved, and efficient cooperation and credible execution of the whole charging scheduling and settlement process are realized.

A computing system includes at least one processing circuit having at least one processor and at least one memory device. The processing circuit performs operations including: providing a chat interface to allow a plurality of travelers to initiate a chat session in which the plurality of travelers collaborate to plan a trip; receiving, via the chat session, input from the plurality of travelers related to the trip; and automatically interacting, via a chatbot, with the plurality of travelers within the chat session to plan the trip by: processing, using a machine learning model, a content of the chat session to generate one or more recommendations for the trip, wherein processing the content of the chat session includes generating the one or more recommendations using the input from the plurality of travelers; and providing the generated one or more recommendations to the plurality of travelers within the chat session.

The invention relates to the technical field of real-time rendering, cloud edge collaboration and three-dimensional visualization, in particular to a multi-instance cloud edge collaboration rendering method based on an unreal engine. Through cloud centralized scheduling and edge node plug flow collaborative architecture, on-demand distribution, dynamic start and stop and life cycle management of rendering instances are realized, and the resource utilization efficiency is remarkably improved; the system combines a relay agent mechanism of TURN and Nginx, gets through access restrictions among a public network, a local area network and a plurality of subnetworks, and realizes unified access and high-adaptability pixel flow transmission capability. Through edge-side integrated pixel flow and signaling service, distributed instance management and load balancing scheduling, the concurrent processing capability and horizontal expansibility of the system are enhanced, and the requirements of complex three-dimensional application scenes such as multiple users, real-time interaction and high-performance rendering are met. Through a cloud edge separation architecture, a relay forwarding mechanism and instance dynamic scheduling, efficient and stable pushing of unreal engine pixel streams in a multi-network environment is realized.

The invention relates to an unmanned aerial vehicle emergency communication spectrum scheduling method and system based on dynamic entropy optimization, and the method comprises the steps: 1, constructing an emergency communication system, and calculating the gain of a received signal; 2, constructing a spectrum sensing and user access model; step 3, evaluating the channel quality in the emergency communication system; 4, establishing a state, an action and a reward of deep reinforcement learning according to spectrum sensing, a user access model and channel quality evaluation; 5, constructing a deep reinforcement learning model, and performing training to obtain a trained deep reinforcement learning model; and step 6, obtaining an optimal strategy of unmanned aerial vehicle emergency communication spectrum scheduling in a spectrum environment by using the trained deep reinforcement learning model, and realizing multi-user aggregation spectrum access. According to the invention, through intelligent distributed spectrum management, the problems of limited spectrum resources and energy, multi-user dynamic competition and the like in a disaster rescue scene are solved, and the spectrum utilization efficiency and the communication reliability are remarkably improved.

The invention discloses a video stream concurrent access front-end dynamic scheduling control system and method based on a digital twinborn scene, and relates to the technical field of computer software and network communication, the system comprises three core modules: a self-adaptive request queue module manages UE rendering resources based on a session token pool, distributes tokens through preemptive scheduling, and sends the tokens to a server; in combination with a GPU frame rate feedback dynamic adjustment strategy, queuing through a Promise asynchronous queue when the request fails; the front-end fusing and backoff retry module monitors the connection failure rate, when the connection failure rate reaches a threshold value, fusing is triggered, retry is delayed by adopting an exponential backoff strategy, and a semi-open state tends to recover; and the local cache collaboration module intercepts the request through Service Worker, caches the latest video clip, pushes the local content when the request is delayed, and ensures the freshness through ETag verification. The method and the device are used for efficiently managing loading and interaction of multiple users on real-time rendering pictures at a browser end.

The invention discloses a digital employee collaborative screening method and system, and belongs to the technical field of artificial intelligence, and the method comprises the steps: receiving multi-user concurrent requests, carrying out semantic isolation, generating an adjustment factor in combination with user portrait features, generating an initial semantic vector through two-channel semantic coding, and carrying out semantic conflict detection, thereby effectively avoiding semantic cross and confusion, and improving the user experience. The intention analysis of multi-user concurrent requests is realized; acquiring request features in real time, calculating computing power demand levels of different requests, sequencing the requests with the same computing power demand level, and performing resource allocation; a user adjustment instruction is obtained through a front end, a demand difference is identified, an incremental calculation scheme is generated, and state synchronization control is carried out; according to the method, digital employees are divided into analytic, computational and feedback intelligent agents, collaborative screening is carried out, feedback verification is carried out, it is ensured that a screening result better meets user requirements, and real-time capability iteration of a digital employee cluster is achieved.

The invention discloses a method for sharing a host based on multiple input devices, and belongs to the technical field of computers, and the method comprises the following steps: after a management user logs in a multi-seat configuration tool, creating second seats with the same number as new input devices according to a Udev rule, and enabling the management user to be a user operating the input device corresponding to a first seat of the host; according to a binding instruction sent by the management user, the second seats and the new input devices are bound one by one, and operation users of the input devices corresponding to the second seats are common users; according to a permission configuration instruction sent by the management user, configuring an application window permission for each common user; and sending the binding relationship between the second seat and the new input device and the application window authority to a window manager, so that the window manager manages the application window according to the binding relationship and the application window authority. According to the invention, the problems of disordered management and complex configuration when multiple users share one host window are solved, and more flexible and efficient equipment management experience is provided for the users.

The invention relates to a joint optimization method and system for a multi-unmanned aerial vehicle auxiliary ISAC system. The joint optimization method comprises the steps that a target area is dispersed into a plurality of hexagonal grids; constructing a multi-unmanned aerial vehicle auxiliary ISAC system model, including constructing a perception effect function, and setting constraint conditions according to the perception effect function by taking maximization of the perception effect as an optimization target; the maximum sensing effect under the constraint condition is decomposed into two sub-problems, the two sub-problems are communication sensing scheduling optimization and UAV track and beam forming vector optimization respectively, and communication sensing scheduling and UAV track and beam forming vector optimization are alternately optimized until a sensing effect function is converged. According to the method, energy consumption waste caused by invalid flight of the unmanned aerial vehicle is effectively avoided, and the requirements of multi-user communication and multi-target perception can be met at the same time; the communication rate and the sensing effect are improved, and the energy consumption of the unmanned aerial vehicle is reduced.

The invention discloses a multi-user-oriented smart home resource conflict negotiation and allocation method, which comprises the following steps of: detecting equipment use conflicts caused by at least two users by constructing a structural causal model for representing a causal relationship of a plurality of variables in a smart home environment, generating a candidate decision strategy set comprising resource isolation and alternative compensation, and allocating the candidate decision strategy set to the smart home environment; carrying out anti-fact inference by utilizing a causal model, quantifying the causal effect of each strategy on the user state, and selecting an optimal strategy for execution based on a minimum negative effect and a Pareto optimal principle; besides, the method ensures that the system dynamically adapts to user habit changes through online monitoring of prediction errors and correction of the causal model, and compared with the prior art, the method improves the decision accuracy through causal reasoning, realizes fair and personalized user resource allocation, and improves the user experience and long-term effectiveness of the smart home system.

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 discloses a time division duplex multi-carrier synchronous transmission method based on 5G, which relates to the technical field of communication, and comprises the following steps of: establishing a carrier mapping table, respectively mapping a plurality of logic carriers to predefined physical resource blocks, and marking uplink and downlink switching time slots according to a time division mode; after a user terminal receives a synchronization signal, alignment is carried out through a high-precision local clock and the reference time of a main base station, and a synchronization reference point is recorded with a nanosecond-level time resolution. According to the invention, through the dynamic synchronization control and frequency domain interference suppression technology, the synchronization stability and the data transmission reliability in a high-speed scene are significantly improved; a synchronous load scoring mechanism is introduced to realize efficient scheduling and conflict avoidance of synchronous resources in a multi-user concurrent environment; and in combination with interference weight estimation and an adaptive filtering strategy, the anti-interference capability and environment adaptability of the system are effectively enhanced, and the requirements of key services such as the Internet of Vehicles and industrial control on low-delay and high-reliability communication are comprehensively met.

Implementations relate to training one or more generative models to determine whether to generate a response responsive to a user input received in a multi-user conversation. For example, a trained generative model can be utilized to process a user input and / or associated metadata, to generate a model output. The user input may be directed to another user in the multi-user conversation. In this case, the model output of the trained generative model that corresponds to the user input can indicate no response for the user input needs to be generated. The user input may alternatively be directed to a virtual assistant representing the application / service that enables the multi-user conversation. In this case, the model output of the trained generative model can be processed to derive a response responsive to the user input. Such response can be rendered and viewed by all users in the multi-user conversation.

Implementations relate to training one or more generative models to determine whether to generate a response responsive to a user input received in a multi-user conversation. For example, a trained generative model can be utilized to process a user input and / or associated metadata, to generate a model output. The user input may be directed to another user in the multi-user conversation. In this case, the model output of the trained generative model that corresponds to the user input can indicate no response for the user input needs to be generated. The user input may alternatively be directed to a virtual assistant representing the application / service that enables the multi-user conversation. In this case, the model output of the trained generative model can be processed to derive a response responsive to the user input. Such response can be rendered and viewed by all users in the multi-user conversation.

The invention discloses a network data sharing method and system based on dual identity authentication, and the method comprises the steps: a user A logs in a client A through the dual authentication of a password and a digital certificate, and transmits an encrypted file data packet formed after an original file is encrypted to a server; the user A selects target data at the client A and appoints a shared user B, and the server updates a shared file list of the user A; the user B submits a data downloading request on the client B, and the server verifies the authority of the user B and sends the encrypted file data packet to the client B; the client B decrypts the encrypted file data packet to obtain an original file; the system comprises a client module, a storage module and a server module. According to the method, a dynamic key generation mechanism is adopted, the requirement for real-time change of the authority in a multi-user cooperation scene is met, the leakage risk of a preset key is avoided, and the conflict between user privacy and sharing convenience is effectively solved.

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 discloses an office chair cushion temperature and humidity multi-stage regulation and control method and system. The method comprises the steps that the contact state of a cushion and a human body contact interface, the local environment, human body physiological response and external environment multi-dimensional parameters are collected in real time; the parameters are matched with a dynamic reference model constructed by multi-user historical comfort data, the matching degree is calculated, and multi-level discomfort levels of all contact areas of the cushion are divided; in combination with the discomfort level and the environmental condition, generating a personalized strategy corresponding to the multi-level regulation intensity through a multi-objective optimization algorithm; and the temperature and humidity adjusting device is driven to execute multi-stage cooperative regulation according to a strategy, and feedback data is collected to update the model. The system integrates a multi-parameter acquisition module, a data processing module, an execution regulation module and the like, and can realize automatic damp-proof management of the seat cushion after the seat is separated from the seat. The problems that existing regulation and control are single, the dynamic comfort requirement cannot be met, and the hidden danger of moisture after the cushion is separated from the seat is solved, and the comfort, sanitation and durability of the cushion are remarkably improved through full-period and multi-stage precise regulation and control.

Apparatuses, systems, and techniques to detect uplink data in a multi-user multiple input multiple output wireless communication system. In at least one embodiment, uplink data is detected using one or more graphics processing units to perform parallel computations in order to form a consensus belief about information received by one or more base stations in a wireless network.

The invention provides a business hall service system supporting multi-user security data circulation, which relates to the field of electric digital data processing and comprises a multi-user identity and access control module, a security data circulation and isolation module, a data life cycle security management module and a security monitoring and compliance auditing module, the multi-user identity and access control module is responsible for establishing a credible user identity system and realizing fine-grained authority control, and the security data circulation and isolation module ensures encryption protection, integrity verification and effective isolation among multiple users in the transmission process of data; the data life cycle safety management module covers whole-process safety protection of sensitive data from identification, processing to destruction, and the safety monitoring and compliance auditing module ensures that the system continuously meets compliance requirements and timely responds to safety threats through intelligent anomaly detection and whole-link auditing; the system can solve the problems of data security circulation and privacy protection in a business hall service system in a multi-user environment.

The invention discloses a social group simulation method and device based on multi-agent driving. The method comprises the following steps: performing user attribute sampling processing on a real e-commerce user data set, and constructing agent basic attributes based on user attributes in combination with a large language model to obtain agent basic attribute features; performing construction processing on the agent basic behaviors based on a preset memory mechanism in combination with the agent basic attribute features; according to the agent basic attribute features and the agent basic behavior features, performing construction processing on agent interaction behaviors in combination with a large language model; performing relation network construction processing based on a small-world network model on the plurality of agents; and performing simulation processing based on execution agent behaviors on the agent social group model to obtain a multi-user behavior simulation result. By constructing a multi-agent simulation system in an e-commerce scene and combining the multi-agent simulation system with a large language model, social group simulation in a complex e-commerce interaction scene is realized, and the accuracy of social group simulation in the e-commerce scene is improved.