1305 results about "End user" patented technology

The invention discloses a hierarchical optimization scheduling method for deep peak regulation of thermal power generating units, and the method comprises the following steps: system layering: dividing a power system into a plurality of subsystems, each subsystem comprising a thermal power generating unit cluster and differentiated load demands; subsystem-level prediction: generating a basic scheduling plan; dynamic preference-driven multi-target collaborative optimization: receiving multi-target data from each subsystem, carrying out multi-target collaborative optimization, modeling three targets of a power grid company, an environmental protection department and a terminal user as game participants, quantifying the priority of each party by adopting a fuzzy membership function, generating a dynamic game solution through a Nash equilibrium solver, and carrying out multi-target collaborative optimization; screening out a Pareto optimal solution giving consideration to interests of multiple parties; performing online verification on the dynamic security domain; virtual synchronous machine cooperative support: simulating operation characteristics of a synchronous generator; and global coordination and iterative optimization: uploading the optimal scheduling scheme of each subsystem to a scheduling center through a message queue telemetry transmission protocol, and performing global constraint verification.

Embodiments include methods, electronic device, storage medium, and computer program to implement a dedicated queue based on a user request. In one embodiment, a method comprises: receiving a first message to optimize one or more data flows based on a quality-of-service request for an end user; enabling a first queue dedicated to the one or more data flows sourced for the end user in the network node based on the first message; and upon a determination of congestion in the network, marking packets in the one or more data flows stored in the first queue as candidates to drop based on a queue size of the first queue, wherein the marking is to set explicit congestion notification bits of the packets.

Disclosed herein is an audio system that can be customized by the user (including the developer) and that may allow the user to control more than just the sound levels and may allow the user to select more than one of a few pre-determined settings. Disclosed herein is a development platform that allows manufacturers (including the developers) to test various different parameters, settings, algorithms, functions, processes, accessories, and the like. The development platform allows the manufacturer to simulate the performances from possible options for the audio system, and then load the selected option from the development platform to the audio system. Additionally, the development platform that enables the end user to have the same level of control and ability to access, upload, and control plugins on the end user's device(s).

Systems and methods for management of generative AI. An example method includes intercepting, via a gateway implemented by the system, a client request associated with a tool invocation via a model context protocol (MCP) server, wherein the gateway operates as a proxy server between a plurality of MCP servers and a plurality of agents or consoles utilized by end-users; accessing policy information associated with MCP, the policy information reflecting, at least, an allowlist and a denylist associated with MCP servers and / or tools; implementing the policy information, wherein implementing includes: adjusting the client request to replace an MCP server included in the client request with a different MCP server, or adjusting the client request to update a schema associated with a tool identified in the client request; and forwarding the client request for receipt by an approved MCP server.

The invention provides a personalized learning path planning system and method, and belongs to the technical field of emerging software and emerging technical services, and the system comprises a data acquisition module which is used for collecting learning behavior data of a terminal user, obtaining a learner portrait package based on the learning behavior data, and sending the learner portrait package to a server; the path planning module is used for carrying out node matching on the learning ability feature vector and a pre-constructed knowledge and skill map, outputting a to-be-learned content node set, dividing learning advanced levels and generating learning path description containing to-be-learned nodes and the advanced levels, and the path generation module is used for generating a primary path planning scheme, the scheme feasibility verification module is used for carrying out scheme feasibility verification in combination with the learning advanced level and the path adaptation parameters, and then outputting a final executable path scheme, and the scheme execution module is used for executing the final executable path scheme and controlling learning content pushing and progress adjustment. The problems that in the prior art, personalized learning path planning is not high in precision, not high in adaptability, lack of dynamic optimization and the like are solved.

Disclosed in the present application are a data processing method based on a large language model, and a large language model, an electronic device, a computer-readable storage medium and a computer program product. The method is applied to a user terminal, wherein a large language model is deployed on the user terminal, and weight parameters of linear calculation layers of the large language model are pre-quantized into format data of an integer data type. The method comprises: acquiring input data; performing vector conversion on the input data by means of an embedding layer of a large language model, so as to obtain a floating-point query vector of a floating-point data type corresponding to the input data; converting the floating-point query vector into an integer query vector of an integer data type; and performing an operation by means of weight parameters of linear calculation layers and the integer query vector, so as to obtain a query result corresponding to the input data. By means of the solution provided in the present application, a large language model can be smoothly run on a user terminal, such that the user terminal can provide services for users without needing network connectivity, and can better ensure the privacy of the users.

The invention relates to the technical field of Internet of Things, and discloses a remote diagnosis system and method for a complex system in an Internet of Things environment, and the system comprises a data collection module which is used for collecting the operation state information of the complex system; the data transmission module is used for transmitting the running state information to the cloud processing center; the cloud processing center is used for performing fault analysis according to the received operation state information based on a machine learning algorithm, generating a fault diagnosis result and a corresponding maintenance suggestion and transmitting the fault diagnosis result and the corresponding maintenance suggestion to the user terminal; and the user terminal is used for receiving the fault diagnosis result and the maintenance suggestion, remotely accessing the system state report of the complex system and remotely controlling the complex system. According to the invention, efficient remote monitoring, accurate fault diagnosis and real-time maintenance guidance of the complex system in the Internet of Things environment can be realized, the maintenance cost is reduced while the maintenance efficiency is improved, and thus the maintainability and safety of the complex system are enhanced.

Various aspects of the subject technology relate to systems, methods, and machine-readable media for automating the recording of an evidentiary history (e.g., versions audit trail) of a graphical user interface with an embedded clickwrap agreement. The snapshot server captures and outputs snapshot records of a graphical user interface displaying the click-wrap agreement on an end user computing platform. The snapshot records are created using a virtual machine that emulates an end user computing platform for navigation of an application rendered on the platform. Aspects may also include generating a snapshot record of metadata associated with the captured snapshot image.

In general, techniques are described that enable a computing system to execute an artificial intelligence model for data security analysis. A computing system that includes a memory and processing circuitry may be configured to implement the techniques. The memory may store a query from an end user regarding security services provided by the data platform. The processing circuitry may parse the query to identify one or more intents, and process the one or more intents to retrieve data for formulating a natural language response to the query. The processing circuitry may also process, using a large language model, the intents and the data to generate the natural language response, and output the natural language response to a user interface for display to the end user.

The invention relates to the technical field of network communication, in particular to a DNS (Domain Name Server) hierarchical cache resolution acceleration method and system based on a prefetching mechanism, which comprises the following steps: by constructing a hierarchical cache model comprising a client layer, a local DNS server layer and an upstream DNS server layer, caching a resolved domain name and a corresponding resolution result into each layer of cache; a DNS request of a terminal user is received, whether the request hits the cache or not is judged, and corresponding operation is adopted; historical query logs are collected, a next DNS request is predicted in combination with a prefetching mechanism of real-time network topology perception, and an analysis result of the domain name is cached to a local DNS server layer in advance; a cross-layer collaborative cache updating mechanism is adopted to ensure synchronous updating of cache data of different levels; and a symmetric encryption algorithm and a TLS protocol are introduced, so that the security of the data in the storage and transmission process is ensured. According to the method, the response of DNS analysis is accelerated through a prefetching mechanism and layered caching.

A computer-implemented method for execution by a software service provider providing a software service to a plurality of end users, the method comprising: receiving message from an end user; generating a search string based on the received message; inputting the search string to a searching mechanism configured to rank a text descriptor of each member of a set of processing functions according to semantic proximity to the search string; generating and outputting an LLM prompt comprising the received message, and the text descriptors of only a subset of the set of processing functions, the subset being the top n results for semantic proximity to the search string, and requesting that the LLM return a selection of a processing function of the subset for which the text descriptor best matches the intent expressed in the received message content; causing the selected processing function to execute.

A copilot platform for identity security governance and lifecycle management, used for capturing the complexity and relatedness of identity security data. The copilot platform integrates Knowledge Graphs and Large Language Model to enhance data exploration and understanding. The LLM converts natural language queries into Cypher queries, enabling interaction with graph databases. The copilot platform includes query annotation to facilitate LLM for recognized entities and for enduring necessary correctness to those entities if required and that increases overall accuracy of the Copilot. The LLMs and data metrics are used to summarize the data for the end user. The copilot platform uses an AI system for interacting with a user to learn about the state of user identity security, take action when required and, given the complexity of IGA data, including information on differentiated dashboards and custom reports, for allowing the user to visualize and manage the information effectively.

The invention discloses a whole network reference unified Beidou B2b constant deviation estimation method, which comprises the following steps of: firstly, performing Beidou B2b clock error reference transformation by applying Beidou B2b service DCB information to realize constant deviation parameterization separation; secondly, adding a single-station virtual reference, and constructing a constant deviation full-rank estimation model based on a single station; then, the constant deviation information of the whole network is integrated, the reference difference of a plurality of single station solutions is eliminated, and B2b constant deviation estimation with the unified reference of the whole network is achieved; and finally, under the constant deviation constraint of the unified reference, the performance of terminal positioning convergence speed, precision and the like is improved. According to the method, constant deviation estimation based on the whole network is realized, the stability and availability of Beidou B2b constant deviation estimation are improved, the problems of to-be-estimated parameter hopping and even filtering divergence possibly caused when a user side adopts constant deviations of different references are avoided, and then rapid convergence and instantaneous horizontal decimeter-level positioning of a terminal user are guaranteed.

Systems and methods for end user elevation and anonymous administrative login are disclosed. An agent executing on a client device can provide a graphical element within a user interface presented by the client device upon detection of a request for elevated user privileges. Upon an interaction with the graphical element, the agent transmits, to a server, data corresponding to the request for elevated user privileges, and receives, from the server, a message indicating approval of the request for elevated user privileges. The agent provides, to the operating system of the client device, an indication that the request for elevated user privileges is approved.

Approaches for evaluating user devices are disclosed. Devices that are physically proximate to a user device are determined. A first geolocation is determined based on the devices that are physically proximate to a user device. Data communications involving the user are evaluated. A second geolocation is determined based on an evaluation of the data communications involving the user. A proximity of the first geolocation with respect to the second geolocation is determined. The proximity of the first geolocation and the second geolocation are evaluated with respect to a threshold value to determine if the first geolocation and the second geolocation are sufficiently proximate.

Implementations are described herein for detecting deepfakes in digital media while preserving the privacy of the source computing device. In various implementations, sensor fingerprints and / or security tokens that signal software-introduced alterations, e.g., introduced by hardware abstraction layers (HALs) or virtual machines (VMs) may be utilized to detect such deepfakes. These signals may be used, separately and / or in combination, for various purposes, such as flagging digital content to a user as being a deepfake, preventing or blocking receipt and / or playback of digital content deemed to be a deepfake, allowing an end user to disable aspect(s) (e.g., layers) of digital content that are determined to be synthetic, etc.

The present invention relates to the technical field of verification management. Disclosed are a verification full-process tracking method and system for multi-end users. The method comprises: acquiring port information, and performing identification to determine merchant information; on the basis of the port information and the merchant information, locating data storage information, and invoking a merchant verification record sub-library; acquiring a verification tracking request, performing information decomposition on the verification tracking request, and determining an order identification factor; on the basis of account information, using the order identification factor to traverse the merchant verification record sub-library to obtain matched verification information; and determining a full-process tracking permission on the basis of the account information, screening the matched verification information, and matching a tracking and localization result for feedback. The present invention solves the technical problem of being unable to accurately grasp the verification statuses of various orders due to the inability to intelligently and automatically perform tracking query and localization on real-time order information in existing verification full-process tracking.

Aspects of the subject disclosure may include, for example, accessing device usage data that can be generated when end user devices connect with the network; and analyzing the device usage data according to identification information of the deployable cell site, which enables determining or estimating a location of the deployable cell site. In one embodiment, this analysis can be based on device usage reports and network performance data. A performance report and / or location map can be generated for an area associated with the deployable cell site. Other embodiments are disclosed.

The invention discloses a decentralized terminal user login management system in an ad hoc network environment, which is embedded in each terminal of the whole network, and each terminal comprises a user login module used for a user to input a user name and a password in the ad hoc network environment to initiate login; the local offline user management module is used for user information authentication of a user in an ad hoc network environment; and the user authentication broadcast confirmation module is used for synchronizing authentication information to other terminals after the user is successfully authenticated in the ad hoc network environment. The invention further discloses a method of the decentralized terminal user login management system in the ad hoc network environment. According to the method, the problems of single-point failure, poor dynamic topology adaptability, incapability of authenticating an offline scene, low synchronization efficiency and the like caused by centralized authentication in a traditional ad hoc network user management system are effectively solved.

The invention discloses a low-voltage distribution area wire user identification method and system based on an improved clustering algorithm, and belongs to the field of low-voltage distribution area wire user identification. According to the method, multi-dimensional information such as voltage amplitude time sequence data, current time sequence data, phase sequence information of each user, primary branch feeder data and the like of a low-voltage bus and each user electric meter in a low-voltage distribution area is comprehensively considered, so that the limitation of dependence on single voltage data is overcome; using an Euclidean distance algorithm to screen and identify head-end user electricity meters, and eliminating the interference of the head-end electricity meters on clustering; the characteristic that the DTW distance algorithm can better process the similarity measurement of the time sequence data is utilized, and the DTW distance algorithm and the clustering algorithm are combined, so that the recognition accuracy is improved; and finally, line user identification is carried out from a global angle, so that the accuracy of line user identification in the low-voltage distribution area is improved, and the problem of low accuracy of line user identification in the low-voltage distribution area caused by dependence on single data and neglect of interference of a head-end ammeter in the prior art is solved.

Systems and methods for an Artificial Intelligence (AI) agent adapted to support end users includes performing monitoring of one or more users via a cloud-based system and logging device metrics based thereon, wherein the device metrics are associated with one or more devices of the one or more users; providing an Artificial Intelligence (AI) agent adapted to troubleshoot issues related to the one or more devices; and responsive to the AI agent being invoked by a user of the one or more users, providing one or more remediation recommendations for one or more issues based on the device metrics.

Methods and systems provide for approaching end-users, collecting their information as it relates to a specific suspect event or set of events, for security events, such as financial events and computer security events, and then applying an Artificial Intelligence (AI) model, to a given security event, to analyze the provided information, to investigate the event or set of events, for validation.

The invention discloses a configuration method for dynamically loading a Vue3 component to construct a front-end user interface under an ExtJS combined JSP architecture, which comprises the following steps of: under the ExtJS combined JSP architecture, newly adding a front-end bridging layer in a Java back-end source code and a compiled and output directory, and configuring a micro front-end engine file and a loading configuration file of a dynamic component loading engine in the front-end bridging layer; an application project directory of the Vue3 component is newly added; a micro-front-end engine file is introduced into a main interface entry JSP file, a loading configuration file of a packaged dynamic component loading engine is introduced, a DOM container of a Vue3 component is arranged in an HTML, and a management object syncExt of a bridging layer of the Vue3 component is customized; and carrying out packaging deployment on the J2EE and a front-end bridging layer by adopting dockerfile configuration, so as to realize cross-framework context communication. The method not only can support stable operation of stock applications, but also can integrate modern front-end framework components and realize framework decoupling.

The invention relates to the field of data processing, and provides a multi-dimensional feature driven B2B2C collaborative recommendation method and system. The method comprises the steps of performing multi-dimensional collection on B-end merchant features, C-end user features and commodity features through a heterogeneous data source interface to obtain standardized multi-dimensional features; performing dynamic weight learning on the standardized multi-dimensional feature data set through a multi-head self-attention mechanism to obtain a fusion feature vector; performing three-layer cooperative matrix construction on the fusion feature vector based on tensor decomposition to obtain a multi-dimensional factor matrix; performing causal relationship modeling on the multi-dimensional factor matrix through a causal graph structure-based collaborative filtering algorithm to obtain a deep collaborative network model; and performing real-time recommendation of to-be-recommended items through the deep collaborative network model to obtain a personalized B2B2C recommendation list. According to the method, the complex mode in the business scene can be captured, and the accuracy of the personalized recommendation result is improved.

The invention relates to the technical field of power grid energy storage regulation and control, in particular to a power grid energy storage regulation and control method and system considering source-storage-load collaborative interaction. The power transmission node information of the power grid system and the power utilization information of each terminal user are acquired, the power grid system is divided into a plurality of virtual energy storage clusters according to the power transmission node information, and load fluctuation characteristic analysis is performed on the power utilization data of all the terminal users of each virtual energy storage cluster; determining a first importance degree of each load area to the electric energy demand; obtaining a second importance degree of each load area in an abnormal state according to the load power change before and after the power generation fault; and according to the first importance degree and the second importance degree of each load area, correspondingly configuring the electric energy guarantee priority of each load area and supplying power until the power generation fault is repaired. According to the technical scheme, after the power grid system has a power generation fault, cooperative adjustment of the energy storage station, the power supply station and the load end is realized, and the accuracy of electric energy distribution is effectively improved.

In one aspect, a method includes using one or more Wi-Fi modules of one or more computing devices to detect movement of an end-user from a first monitored environment of the one or more computing devices to a second, different monitored environment of the one or more computing devices, where the first monitored environment comprises a first Internet of Things (IoT) device, where the second monitored environment comprises a second IoT device, and where the first and second IoT devices are communicatively coupled to the one or more computing devices over an IoT network. The method also includes in response to detecting the movement of the end-user from the first monitored environment to the second monitored environment: triggering a first IoT action at the first IoT device, and triggering a second IoT action at the second IoT device.

A computer-implemented method for executing a processing function in a software service in response to an end user natural language instruction, the method comprising: receiving, via a user interface, message content from an end user expressing an intent; selecting a processing function, from among a set of processing functions, to execute in response to the received message content, the selected processing function being executable by following any one from among a plurality of different executable sequences of component actions; causing the selected processing function to execute by determining and following an execution traversal path in a data graph.

A policy-controlled access security system for managing access security to electronic agents in cloud based multi-tenant systems includes a client device, a mid-link server, and a web server. A local application running on the client device requests access to an electronic agent of a remote application of the web server. Policies are determined for controlled access to the electronic agent. A token for the electronic agent is correlated with a plurality of tokens for identifying a user application associated with the token. The remote application is compared with the user application. A non-compliance of the set of policies is identified by determining enabling of one or more AI devices by the plurality of end users. The set of policies are modified based on the non-compliance and the functionality associated with the electronic agent and the plurality of privileges are updated for the end user based on the modified policies.

The invention relates to the technical field of artificial intelligence and voice dialogue, and discloses a voice interaction method based on retrieval enhancement generation and multi-model collaboration and application thereof. Performing local multi-round intention recognition; performing local RAG retrieval and candidate aggregation; decision making and cloud generation; performing feedback, synthesis and persistence; the invention further provides application of the voice interaction method based on retrieval enhancement generation and multi-model collaboration. According to the method, through local structured intention recognition and RAG retrieval aggregation, in combination with the generation capability of a cloud large model, response timeliness and privacy protection are considered, and the recommendation accuracy and robustness in a multi-round voice interaction scene are remarkably improved; the retrieval redundancy is reduced and the context quality is improved through entity-level combination duplicate removal, rearrangement and fuzzy matching strategies; and the consistency of data updating and the stability of online service are ensured through an offline atom replacement mechanism, so that the terminal user experience is improved, and engineering deployment and expansion are facilitated.

Apparatuses, systems, and methods for artificial intelligence (AI) augmented data analysis can include providing a large language model (LLM), access to a data set. For example, an end user can interact with a user interface on a user device to provide instructions to the LLM to access the data set. In addition, the LLM can be interacted with via the user interface using natural language instructions and LLM output, based on the LLM analysis of the data set, can also be interacted with via the user interface. The LLM output can include one or more visualizations of the data set.