242 results about "Virtual user" patented technology

An advanced AI system, known as Bayesian Graph-Based Retrieval-Augmented Generation with Synthetic Feedback Loop (BG-RAG-SFL), combines Bayesian evaluation, graph-based retrieval, and synthetic data feedback to create a continuously improving AI platform. The present invention integrates multiple LLMs, optimizing their performance while managing complexities across different models. Key features include a knowledge graph-based RAG system, a Bayesian evaluation network, a secondary ground-truth graph for verification, synthetic data generation for ongoing improvement, and a multi-agent verification system. The system also functions as an AI operating system capable of acting as a virtual user with screen I / O control and managing multiple computers as an intelligent process automation system.

The invention discloses an Internet of Things cross-domain payment method with a privacy protection function. The method comprises the steps of initialization, storage, uploading, verification, cross-chain interaction, settlement and timeout. According to the method, the validity of the content can be verified under the condition of not leaking any content by adopting the zero-knowledge proof technology, the specific position of group members, namely each site, can be hidden by adopting the group signature technology, the position information of a user is hidden, and the position privacy of the user is protected; the anonymous block chain technology hides the transfer relationship between the real user and the corresponding virtual user, so that the user identity privacy is effectively protected; according to the cross-chain channel technology, information transfer between sites on different block chains is realized, the cross-chain interaction efficiency is improved, and the cross-domain payment requirements between different block chains in different industries are met; the intelligent contract, the zero-knowledge certification technology and the group signature technology realize privacy protection and realize distributed automatic verification of information with relatively low chain cost, so that verification efficiency is improved, and computing resources and cost are saved.

An advanced AI system, known as Bayesian Graph-Based Retrieval-Augmented Generation with Synthetic Feedback Loop (BG-RAG-SFL), combines Bayesian evaluation, graph-based retrieval, and synthetic data feedback to create a continuously improving AI platform. The present invention integrates multiple LLMs, optimizing their performance while managing complexities across different models. Key features include a knowledge graph-based RAG system, a Bayesian evaluation network, a secondary ground-truth graph for verification, synthetic data generation for ongoing improvement, and a multi-agent verification system. The system also functions as an AI operating system capable of acting as a virtual user with screen I / O control and managing multiple computers as an intelligent process automation system.

A display improvement support method and device for improving a display in accordance with the user's conscious reaction is provided. [Solution] In the display object improvement support device, the generation AI control unit executes the following steps: a reaction prediction prompt generation step of generating a reaction prediction prompt that instructs the generation AI to predict the reaction that will occur in the mind of a virtual user having user profile information of at least one of age, sex, occupation, height, and weight when the virtual user uses the display object; a reaction acquisition step of inputting the reaction prediction prompt into the generation AI and acquiring reaction information, which is information related to the reaction, from the generation AI; a screen operation prediction prompt generation step of generating a screen operation prediction prompt that instructs the generation AI to predict the screen operations that the user will perform on the screen of an information device based on the reaction information; and a screen operation acquisition step of inputting the screen operation prediction prompt into the generation AI and acquiring screen operation information, which is information related to screen operations, from the generation AI.

Embodiments of the present disclosure provide a system for provide experience to real time feel of trail of actual clothes to a user is disclosed. The system is utilized in online as well as physical stores. The system utilizes a camera communicatively coupled with a body scanner. The system is further communicatively coupled with a mobile device for providing details of the user. The mobile device may transmit a trigger to a body scanner after receiving an input from the user. The input indicates selection of a cloth from a plurality of clothes available in the store. After receiving the trigger from the mobile device, the body scanner may initiate the camera and determine details of the user. The mobile device may overlap the selected cloth on to a dummy user created using the details of the user.

An Adaptive Tangible User Interface (ATUI) for use in an extended reality environment in which tangible interfaces are composed in real time based on identified affordances of existing objects in the physical environment and the input tasks of a user. An extended reality system can be provided with instructions executable by one or more processors to perform processing including: generating a representation of the real-world environment within a field of view of the user; identifying physical objects within the real-world environment; generating a set of possible performable gestures afforded by available object affordance factors; determining potential input tasks; composing performable gestures for the potential input tasks; and selecting a physical object for use as an adaptive tangible user interface. Techniques for designing a virtual user interface, overlaying the virtual user interface on a selected ATUI physical object, and maintaining alignment of the virtual user interface, are also provided.

Disclosed is an electronic authentication system and method of supporting multi-signature. The method includes: designating a user group including a plurality of users to participate in multi-signature; further including a virtual user in the user group according to a predetermined policy or a request of one or two or more users of the plurality of users; generating a communication channel for communication with the user group; receiving a public key for each user of the user group through the communication channel, and sharing the received public key with the user or virtual user of the user group; and sharing a local signature generated by the user of the user group through the communication channel.

A computing system. a method for operating a computer system, a computer program, a computer-readable medium and a data carrier signal with improved communication between remote user devices (RU) and an artificial intelligence (AGI) by way of different virtual users (AVU).

The invention provides an intelligent agent training management method, system and device, and belongs to the technical field of intelligent agents, and the method specifically comprises the steps: taking an interaction demand type between a virtual user and an intelligent agent as a basis, combining the change conditions of interaction user data in different time periods, and carrying out the training management of the intelligent agent; determining an available interaction time period between the virtual object and the intelligent agent, and determining an analysis processing strategy of interaction data between the interaction user and the intelligent agent according to the data of the available interaction time period; according to the method, the interaction management strategy of the virtual object in the time period except the available interaction time period is determined according to the analysis processing result of the interaction data of the virtual object in the available interaction time period and the interaction data between the interaction user and the intelligent agent, so that the updating processing efficiency of the intelligent agent is improved, and meanwhile, the influence on a normal business process is also reduced.

The invention discloses an online health management method and system based on big data, and relates to the technical field of online health management, a virtual user executes a selected health service to simulate the process that a real virtual user participates in a health activity in actual life, and after the virtual user completes the health service, the virtual user can take part in the health activity. The pheromone concentration is updated according to the effect of the plan, the virtual user carries out selection and execution of the health care service and updating of the pheromone concentration according to the pheromone concentration and a heuristic rule, convergence is carried out after a preset number of iterations is achieved, natural attenuation of the pheromone concentration is simulated based on the volatilization rate of the pheromone concentration, and the health care service is obtained. After the last round of iteration is completed, according to the pheromone concentration and the health care service effect, the optimal health care service is selected as the final personalized recommendation. The management system effectively generates more personalized health and care services for the virtual users, progressive optimization helps the management system continuously adapt to health changes and demand evolution of the virtual users, and the long-term effectiveness of the health and care services is improved.

The invention relates to a position privacy protection method based on virtual track generation, and belongs to the technical field of position privacy protection. According to the method, two generative adversarial networks are constructed, travel habits of users and track information of real users are learned respectively, and virtual user LBS query service and corresponding track data are generated. By comprehensively considering the influence of the user behavior pattern and the geographic topological structure, the generated virtual track is more real and credible, and a better privacy protection effect is achieved.

This document describes methods, devices, systems, and means for managing a virtual user equipment, UE, set by a network entity, the network entity registering multiple user equipment to the virtual UE set, generating a virtual-UE-set session context, and sending a virtual-UE-set context notification to a base station, directing the base station to transmit the virtual-UE-set session context to each of the multiple user equipment in the virtual UE set. The network entity determines that a first user equipment in the virtual UE set is in-focus for aa first instance of an application, applies a first set of capabilities associated with the first UE to a session for the first instance of the application, and based on the relaying, relays data between the first instance of the application and an application server based on the first set of capabilities.

A novel electronic system provides automated recognition, registration, and location tracking of physical, holographic, and / or virtual user items that can be visualized in a computer graphics-infused augmented-reality or mixed-reality environment with an electronic visualization device. The novel electronic system is also capable of executing intelligent machine valuation of user items and reflecting dynamic changes in valuation based on peer interests within the augmented-realty or mixed-reality environment. Each user item identified in the user's visual perspective through the electronic visualization device connected to the novel electronic system undergoes object extractions, class categorizations, and image segmentations by the novel electronic system to determine whether a particular item is substantive and worthy of location tracking, based on the item owner's preferences. The item is paired with related metadata and stored in a system database, and later retrieved by a search command in the augmented-reality or mixed-reality environment to display its known location.

The invention discloses an Internet of Things card intelligent management method and system based on multiple operators, and relates to the field of multi-operator network collaborative management, and the method comprises the steps: collecting network service quality data, a network state, a multi-operator network and an available bandwidth index, encrypting a device identifier and a service type, and transmitting the encrypted device identifier and service type to an intelligent management platform; distributing a virtual user identification module identity, and generating a terminal exclusive key; an operator trains a local long-short-term memory network quality prediction model based on local network data to obtain a model gradient, and encrypts the model gradient generated by terminal exclusive key training to obtain an encrypted model gradient; and performing decryption and aggregation calculation on the encryption model gradient through a security aggregation algorithm to generate global network quality prediction model parameters. According to the invention, through an innovative federal learning encryption gradient aggregation mechanism and a block chain intelligent settlement system, efficient collaborative management of the Internet of Things cards of multiple operators is realized.

The invention provides a virtual user simulation method and system for dialogue testing, and the method comprises the steps: obtaining a plurality of pieces of effective multi-round dialogue data from a to-be-tested system, and carrying out the multi-label labeling, so as to construct a basic sample data set containing user portrait labels, the key sample data set further comprises user emotion tags; constructing a group optimization strategy model, performing cold start training based on the basic sample data set, and performing intensive training by using a multi-dimensional composite reward function based on the key sample data set to obtain a dialogue generation model with an emotion cognition-verbal skill expression decoupling architecture; and taking a historical round of dialogue of the to-be-tested system aiming at the current interaction as input of a dialogue generation model, and generating a next round of user reply consistent with the user emotion and the user portrait. According to the invention, deep, efficient and automatic adversarial testing is carried out on the task-oriented dialogue system, so that system defects which are difficult to find by a traditional testing method are effectively exposed.

The invention discloses a UI design scheme generation method and device, and the method comprises the steps: generating a user experience UE process based on a business demand document through a large language model LLM; generating a UI (User Interface) design scheme based on the UE process through AIGC (Artificial Intelligence Generation Content); creating a virtual user environment based on a UI design scheme through digital twinning, simulating an interactive behavior between a user and the UI, and collecting behavior pattern data of the user in the process of simulating the interactive behavior; performing emotion analysis based on the behavior mode data to obtain an emotion state of the user; and updating the UI design scheme based on the emotional state. According to the method, from demand interpretation to design generation to user interaction simulation and emotion analysis, full-process automation of UE design / UI design is realized.

The invention discloses a software performance test system, method and device in a high-concurrency scene, and relates to the field of software testing, the system comprises a scene intelligent construction module used for generating a concurrency scene through a behavior tree modeling and time sequence prediction algorithm according to service demand parameters and historical traffic data; the distributed test environment scheduling module is used for constructing a distributed test environment by adopting a container arrangement technology; the virtual user load generation module is used for simulating concurrent user requests by adopting a coroutine pool technology; the real-time performance data acquisition module is used for acquiring multi-source performance data of the tested software in real time; the intelligent performance analysis module is used for calculating a core performance index according to the multi-source performance data and carrying out anomaly detection and trend prediction; and the performance bottleneck positioning module is used for mining a dependency relationship among the core performance indexes and generating a bottleneck positioning report and an optimization suggestion document. According to the method, the accuracy, the efficiency and the stability of software performance testing in a high-concurrency scene are improved.

The invention discloses an automatic testing method and device for the number of connectable users of user front-end equipment, and the method comprises the steps: generating a plurality of virtual users, and configuring a unique MAC address for each virtual user; a first message is constructed according to the MAC address of each virtual user, all first messages are sent to a network in a multi-thread mode, and the first message comprises the requested IP address; monitoring and collecting a second message sent by the user front-end equipment, the second message being sent by the user front-end equipment after the user front-end equipment receives the first message, and the second message comprising the requested IP address; extracting the requested IP addresses in all the second messages and counting the number of the extracted requested IP addresses; and obtaining a test result according to the number of the extracted requested IP addresses and a preset number threshold. According to the invention, efficient and automatic testing of the CPE equipment in a multi-user environment is realized, and the testing speed and precision are greatly improved.

The invention discloses a simulated inquiry interaction analysis method, device and equipment based on man-machine conversation, and relates to the technical field of artificial intelligence and medical treatment, and the method comprises the steps: obtaining inquiry conversation data generated by interaction between a user object and a virtual user; performing multi-dimensional interaction analysis on the inquiry dialogue data based on a preset medical knowledge graph and preset diagnosis information to generate a corresponding evaluation index and a corresponding index score; and generating and outputting an evaluation report containing the index score and the user object-oriented inquiry dialogue improvement suggestion. According to the method, the objectivity and the accuracy of an evaluation result are ensured, prejudice and inconsistency caused by subjective experience difference in manual evaluation are overcome, the evaluation result is accurate, and a user can clearly know the expression level of the user in each dimension and can also obtain a targeted inquiry optimization direction.

The invention relates to the technical field of management systems, and particularly discloses a three-dimensional industrial design material AI intelligent recommendation management system. Comprising a dynamic knowledge graph module, a multi-source perception input module, a neural symbol fusion engine, a situation self-adaptive output module, a self-evolution optimization module, a recommendation rule updating module, a cold start processing module and a multi-target decision module. The neural symbol fusion engine realizes symbol logical reasoning through Transform, the cold start processing module generates a user portrait through gradient embedding and generates virtual user features through cross-map feature propagation, the situation adaptive output module dynamically switches rendering modes according to a design stage, and the self-evolution optimization module performs meta-learning and concept drift detection; through multi-technology fusion and module cooperation, intelligence, precision and high efficiency of three-dimensional industrial design material recommendation are realized, the design efficiency is remarkably improved, and the project landing risk is reduced.

The embodiment of the invention provides a data access method and device.The method comprises the steps that a data access request sent by a virtual user mode is received, and the virtual user mode accesses storage data of a host machine according to the data access request; determining an access type of the data access request, and extracting read address information and write address information in the data access request when the access type is a bidirectional read-write type; packaging the read address information and the write address information according to a preset drive protocol to obtain a drive read-write request; the driving read-write request is written into a preset description array, a target description array is obtained, and the host machine executes data access operation corresponding to the data access request on the storage data according to the target description array. A single read-write request is allowed to contain read operation and write operation at the same time, the performance overhead brought by the read-write request in a virtualization environment is reduced, and the read-write access efficiency can also be improved.

The invention discloses a resource scheduling method and device based on hybrid cloud and a private cloud management platform. The method comprises the following steps: constructing a hybrid cloud resource pool comprising a private cloud resource pool and a public cloud resource pool; initiating a registration process to the public cloud, and registering a corresponding virtual user in the public cloud for the tenant of the private cloud; and according to a cloud service application initiated by a private cloud user, definition of the cloud service in the cloud service application and a preset rule of matching resources with the cloud service, sending the cloud service in the mixed cloud resource pool, and distributing private cloud resources and / or public cloud resources of a virtual user corresponding to the private cloud user in a public cloud for the private cloud user. According to the invention, the public cloud and the private cloud are managed in a unified manner, and the problems of time consumption, labor consumption and low resource utilization rate when an enterprise manages the hybrid cloud combining the public cloud and the private cloud are solved.

The invention discloses a black box evaluation system for a mobile terminal news recommendation system based on a large model agent. The system is composed of a virtual user layer and a virtual environment layer, the interactive behavior of a specified user group is simulated through a virtual user agent driven by a multi-modal large language model, and continuous interaction with a real news recommendation application online recommendation system is achieved through mobile equipment in the virtual environment layer. The virtual user layer takes a screenshot of a mobile device as input and executes tasks such as content identification and processing, memory storage and retrieval, state response reasoning and interactive behavior decision; the virtual environment layer is responsible for managing a mobile device running a news recommendation application, providing a running state screenshot, and automatically executing corresponding device operation according to an interactive behavior decision of a virtual user; according to the method, the requirements of virtual A / B testing, virtual social experiments and the like of an online recommendation system deployed in a mobile terminal news recommendation application can be met under the black box condition.

The invention discloses a learning progress updating system, method and device and electronic equipment, and relates to the technical field of education, and the system comprises a learning behavior collection module, a behavior change analysis module, a learning progress mapping module and a learning progress adjustment module. The learning behavior acquisition module is used for acquiring learning behavior data of a target student and a first learning progress of at least one virtual user; the behavior change analysis module is used for determining behavior change data of the target student; the learning progress mapping module is used for performing learning progress mapping on the behavior change data to obtain a second learning progress of at least one virtual user; and the learning progress adjustment module is used for generating progress adjustment information corresponding to the at least one virtual user, so that the at least one virtual user is adjusted to a second learning progress. The learning progress of the virtual user is updated based on the behavior change data, the matching degree between the virtual user and the student is improved, and the accompanying learning requirements of the student in different learning stages are met.

The present invention provides a method, device, and system for pushing information resources based on a real-world metaverse, belonging to the field of deep learning technology. The method comprises: collecting a set of real-world user behavior data; obtaining a training data set based on the user behavior data set, and using the training data set to train a deep learning-based neural network to obtain an information resource push model; collecting a set of virtual user behavior data in a real-world metaverse, inputting the virtual user behavior data set into the information resource push model, and outputting metaverse information resource push information. The present invention obtains user behavior data from the real world to train an information resource push model, and then uses data such as user tags collected from the metaverse to utilize the information resource push model trained in the real world to determine information recommendation results that meet the preferences of metaverse users, thereby realizing personalized services for information resources in the metaverse.

The invention discloses a digital human platform interaction system and method based on artificial intelligence, and relates to the technical field of man-machine interaction, and the method comprises the steps: combining facial features and preferences of a user under different emotions through a digital twinborn technology, and constructing a virtual user image; constructing a digital person independently belonging to each user according to the generated digital person image and voice of each user, and storing the digital person of each user to construct a digital person warehouse; when the user interacts with the digital person, face data of the user is collected in real time to be matched with the virtual user image, and after matching, the digital person independently belonging to the real-time user is selected according to the virtual user image and is displayed; the digital person collects answers in the network according to the interaction question and classifies all the collected answers; selecting an interaction question answer satisfied by the user; and the digital person modifies the answer of the interaction question according to the user emotion and outputs the modified answer to the real-time user.

The invention relates to an interactive training data generation method and device, vehicle-mounted equipment, a storage medium and a program product. According to the method, historical dialogue data of a vehicle user is obtained, a virtual user model corresponding to the vehicle user is constructed according to the historical dialogue data, and then the virtual user model is utilized to initiate multiple rounds of dialogues to an initial intelligent interaction model. And after each round of conversation, adjusting an emotion label of the virtual user model according to reply information of the initial intelligent interaction model, generating conversation content of the next round based on the adjusted emotion label, and then generating interactive training data according to conversation data and corresponding emotion labels in the multi-round conversation process, the interactive training data is used for training the initial intelligent interactive model. According to the method, massive interactive training data with emotion tags can be generated, and thus the intelligence of an intelligent interaction model trained through the interactive training data can be improved.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may transmit mobility history information associated with the UE. The UE may receive radio resource management information that is based at least in part on the mobility history information, wherein the UE is associated with a virtual UE, and wherein the radio resource management information is a same radio resource management information for each UE of a plurality of UEs associated with the virtual UE. Numerous other aspects are described.

An apparatus including circuitry configured for: wireless charging an energy storage device in the apparatus; using energy from wireless charging and / or the energy storage device to render mediated reality content to a user of the apparatus, wherein the mediated reality content rendered to the user is a virtual scene determined by a virtual point of view within a virtual space, wherein a real point of view of the user, defined by a location and orientation of the user in real space, determines, via a mapping between the virtual space and the real space, the virtual point of view within the virtual space of the virtual user; and in dependence upon a wireless charging parameter, changing the mapping between the real space and the virtual space to enable improvement of the wireless charging parameter.

The application relates to the technical field of the cross of artificial intelligence and behavior science, in particular to a market research system based on multi-source data integration and psychological analysis, which comprises a processing module, an RAG module, a retrieval module, a summary module, an analysis module and a verification module; the processing module processes feedback data of market research; the RAG module retrieves to obtain multi-modal data; the retrieval module retrieves to obtain data samples; the summary module extracts data features; the analysis module analyzes the data samples and generates analysis conclusions; and the verification module verifies the results of the analysis module. The application generates multi-modal data of feedback data in the Internet through the retrieval module, and according to the obtained data samples, the analysis module analyzes to obtain analysis conclusions by combining virtual user models of psychology and / or sociology, so that the problem that the system has weak theoretical support and single data dimension is avoided.