1251 results about "Multiple applications" patented technology

The invention discloses a large-model-driven intelligent calculation method and system for a water conservancy mechanism model. According to the method, natural language input, structured conversion and intelligent optimization calculation of a scheduling target are realized by integrating a field-enhanced large language model and a water conservancy professional mechanism model. The method comprises the steps of receiving a calculation target expressed by a user in a natural language, and analyzing and converting the calculation target into a constraint condition and a target function which can be recognized by a water conservancy mechanism model; a hydrological model, a hydraulic model, a hydrodynamic model and other models are called based on a workflow engine, and reverse calculation is carried out by adopting a hybrid optimization strategy of'coarse adjustment-fine adjustment-verification '; synchronously and visually displaying the parameter change and the result convergence state in the calculation process; and outputting a calculation result including parameter adjustment logic, standard conformity analysis and multi-scheme comparison. The system comprises a natural language interaction module, a target conversion module, an intelligent calculation engine module, a visualization module and a result generation module, and supports multiple application scenes such as multi-target scheduling, emergency decision making and ecological guarantee. Compared with a traditional scheme, the method has the advantages that the model use threshold is lowered, the dispatching efficiency and calculation transparency are improved, and the method is suitable for complex hydraulic engineering calculation tasks such as reservoir dispatching, cross-basin water transfer and flood control emergency.

While AI models, like large language models, are powerful tools with multiple applications, they can be complex to use and can require a lot of resources to operate. The disclosed systems and methods provide tools to generate customized models (or AI agents) that are configured with features like tailored knowledge, capabilities, and instructions that make them faster, more efficient, and use less computational resources. AI agents may offer several technical advantages of improved efficiency, resource use, and connectivity. This disclosure describes systems and methods to configure, evaluate, generate, and deploy the custom models that can more efficiently run specific tasks. Disclosed systems and methods are configured to, for example, receive a query to generate a custom model, generate the AI agent custom model with the information in the query, and then resolve user queries more efficiently using the custom model.

Described herein are methods and systems for a conversational assistant that may be configured for use with one or more applications. The disclosed systems and methods may be configured as an outer loop / inner loop architecture incorporating one or more large language models (LLMs) and / or RAG functionality to support dialog-based interactions.

The present invention extends to methods, systems, and computer program products for optimizing resource allocation in view of predicted network traffic patterns and predicted power consumption. Network packets defining a network traffic flow can be received at a platform over time. Metrics can be derived from one or more applications executing on resources of the platform and processing data contained in the network data packets. Model training data can be formulated from the metrics. A resource adjustment model can be trained using the model training data. Executing the model can be automated to adjust resource allocation at the platform. Additional network packets defining an additional network traffic flow can be received at a platform over time. Data contained in the additional network packets can be processed using the adjusted resource allocation.

Methods, systems, and computer-readable storage media for restoring microservice persistencies. A disruptive event potentially affecting a computing system functionality and data synchronization of one or more applications and one or more microservices is determined. Each application and microservice stores respective data records in separate data tables. A restoration of the computing system functionality is determined. A synchronization process is initiated by using a synchronization identification engine. Data record synchronization is verified across a plurality of data tables, by matching record identifiers according to a call mapping between the applications and the microservices. The data record synchronization is restored across the plurality of data tables. An access to the applications and the microservices is reactivated.

The invention discloses a solution for intelligent low-code construction and automatic deployment of a multi-terminal application full stack, belongs to the technical field of software development, and solves the problems that an existing low-code development platform is high in use threshold, does not support customized development and is disjunction in application construction and application use. The invention provides an intelligent low-code construction platform. The intelligent low-code construction platform comprises a low-code construction platform, an application rendering unit, an application deployment unit and a display interaction unit, the low-code construction platform is used for constructing a plurality of application pages according to the developer personalized configuration information, and associating the plurality of application pages according to set association logic information among the plurality of application pages to obtain an application program; generating application data according to the application program, and storing the application data; the page cross-end rendering unit is used for performing Web end and App end rendering on the application program according to a defined page rendering protocol to obtain a Web end application and an App end application; and the display interaction unit is used for displaying the interaction function and the application logic of the Web end application and the App end application.

The invention discloses a high-resolution peak value positioning method based on multi-pulse superposition and offset clock cooperation, and belongs to the technical field of laser radar ranging. Aiming at the problems that a traditional laser radar depends on a high-sampling-rate ADC, so that hardware cost is high, power consumption is large, and sampling errors are likely to be caused by echo jitter, the method does not need to replace an existing ADC, and the technical breakthrough is achieved through the following core steps that firstly, the basic sampling rate X Hz and the target equivalent sampling rate improvement multiple N of the ADC are determined; laser pulses are emitted to a target object for N times, during Kth emission, ADC sampling is started by delaying (K-1) / (X * N) seconds, and N groups of echo data with time sequence offset are obtained; performing cross combination on the N groups of data, and constructing an N-time equivalent high-sampling-rate data sequence; repeating the sampling and combining process for S times, and performing alignment superposition and averaging on S groups of data to suppress echo jitter and noise; and estimating initial parameters (amplitude, mean value and standard deviation) of a Gaussian model based on the superposed data, optimizing the parameters through an LM nonlinear optimization algorithm, and finally taking the optimized mean value as a high-precision peak position of an echo signal to realize accurate measurement of the laser flight time. Under the condition of low-sampling-rate hardware, through the collaborative design of clock skew and multi-pulse superposition, the physical limitation of the sampling rate is broken through, low cost, low power consumption and high ranging precision are taken into account, and the method is adaptive to multi-scene application of automatic driving, industrial ranging and the like.

The invention discloses a machine tool running state collection and evaluation method and system, and relates to the field of intelligent machine tools, and the method comprises the steps: collecting machine tool multi-dimensional data through a multi-channel collection device; performing time alignment on different sampling frequency signals by adopting a dynamic synchronization algorithm of clock drift compensation; executing noise suppression, feature extraction and compressed encoding at the edge computing node to generate local state abstract data; sending the abstract data to a central server through a distributed message queue, and realizing multi-application concurrent access based on load dynamic scheduling; and the central server performs fusion analysis on the abstract data by using a multi-modal fusion deep network model, and outputs a health degree index and an overall operation score of the key parts of the machine tool, thereby realizing intelligent evaluation and health prediction of the operation state of the machine tool. The method realizes global perception and intelligent evaluation of the machine tool operation state, and can be widely applied to operation monitoring and health management of high-end numerical control machine tools, complex machining centers and unmanned production lines.

The invention provides a method for automatically deploying artificial intelligence models, which simplifies a model building process through systematic data preprocessing, model selection, parameter optimization and performance monitoring mechanisms, and dynamically updates or switches models in an application environment to maintain overall prediction performance at the best state while improving the performance of the model in multiple application environments.

A method is performed at a computer system that is in communication with a display generation component and one or more input devices. A first window and a second window are concurrently displayed. An input that changes a spatial arrangement of the first window is received at the computer system. In response, in accordance with a determination that the change in the spatial arrangement of the first window would cause the first window to occlude the second window such that less than a predetermined amount of the second window would be visible, moving the second window so that, after the second window is moved, at least the predetermined amount of the second window is visible.

The subject technology implements a unified query frame that may retrieve identity records from multiple, asymmetric identity spaces. The unified queries of the unified query framework may include one or more steps, one or more paths, and a resolution scheme that may extract sets of identity records from multiple identity spaces. The unified query framework may be implemented in a graph analysis system that generates one or more identity subgraphs using the extracted sets of identity records. One or more aspects of the unified queries and or identity subgraphs may be configured to customize the data retrieval process for one or more applications. One or more search operations of the graph analysis system may be optimized to improve the speed and efficiency of data retrieval and reduce compute resources and cost.

The objective of the present invention is to provide a mobile terminal in which a layout of execution screens of two or more applications displayed together can be automatically changed to be suited for a user's viewing. According to an aspect of the present invention, provided is a mobile terminal comprising: a body; a display coupled to the body such that a display area viewed from the front of the body can be changed according to the switching between an extension display mode and a contraction display mode; and a control unit for controlling such that a layout for two or more application execution screens displayed together on the display is changed in response to the switching from the extension display mode to the contraction display mode.

A processor of a wearable device, according to an embodiment, may be configured to display, on a display, an area comprising at least one parameter for controlling an application screen and a speaker. The processor may identify an input for connecting the application screen and the area to each other. After identifying the input, the processor may output, through the speaker, an audio signal having a volume included in the at least one parameter, in response to audio data corresponding to the application screen. Certain example embodiments may be associated with a metaverse service for enhancing interconnectivity between an actual object and a virtual object. For example, the metaverse service may be provided through a network that is based on fifth generation (5G) and / or sixth generation (6G).

The present disclosure generally relates to viewing and updating application views. A device receives a user input, the input, when received initiating display of a plurality of application views of a set of application views. The device, in response to receiving the user input, displays the plurality of application views of the set of application views, wherein the set of application views includes preselected application views and an adaptive view that corresponds to a most recently opened application that is not one of the preselected application views.

A system, method, and computer-program product includes obtaining, via an application programming interface (API), a test object that includes application usage data of a deployed AI application for a target time span, executing, in real-time by one or more computer processors, one or more application behavior tests that assess an operational behavior of the deployed AI application, detecting, by the one or more computer processors, that a misbehavior occurred in the deployed AI application during the target time span and one or more deviant features contributing to the misbehavior in response to executing the one or more application behavior tests, and returning, by the one or more computer processors, the one or more deviant features contributing to the misbehavior to a subscribing entity associated with the deployed AI application.

The utility model discloses a forklift fuel cell system and relates to the field of fuel cells. Comprising a fuel cell system module, a solid-state metal hydrogen storage module and a power cell module, and the fuel cell system module, the solid-state metal hydrogen storage module and the power cell module are all fixed in a forklift box body. According to the utility model, the whole system is divided into three modules, namely the fuel cell system module, the solid metal hydrogen storage module and the power cell module which are mutually independent, clear in boundary and free from mutual influence, so that the whole system can simultaneously take into account a solid metal hydrogen storage form and a gas hydrogen storage bottle form, and meanwhile, the power cell can also take into account various sizes and specifications; therefore, the whole system has a plurality of integration modes and a plurality of application scenes, and the extension and application range is wide.

The invention discloses a carbon emission flow analysis method for carbon emission evaluation in multiple application scenes, belongs to the technical field of power system carbon emission modeling and evaluation, constructs a connection relationship among nodes, branches and a power supply in a power system, and collects output data and type information of a power generation power supply and a power flow result in multiple operation conditions. The method comprises the following steps: calculating carbon emission of a power generation node, distributing the carbon emission to a load node according to a power flow path, identifying a carbon emission source of the load node by adopting a power tracking method, and calculating carbon emission intensity and a carbon potential index; a transmission structure of carbon emission in a power grid is defined, step-by-step distribution and flow direction tracking of the carbon emission are realized, and the defect that a carbon emission path is unobservable in the prior art is overcome; the identification precision of the carbon emission composition is improved, and a basis is provided for the priority division of energy-saving and emission-reducing measures; a carbon emission path mapping matrix and a transition probability matrix are constructed, dynamic identification of path changes is realized, and discovery of key paths and nodes is facilitated.

The invention relates to the technical field of data analysis, and discloses a business analysis and decision support method and system, and the method comprises the steps: collecting purchase-related business data from a plurality of data sources, and carrying out the preprocessing; storing the preprocessed data in a centralized data warehouse, and performing management based on a preset data governance strategy; performing multi-dimensional analysis on the structured data based on a statistical analysis model and a machine learning algorithm, and generating a key performance indicator KP I and a trend prediction result; providing a customized visual display interface according to a user role, and presenting the KP I and a trend prediction result through an interactive instrument panel; and generating a purchase optimization suggestion based on the analysis result, evaluating the influence of different purchase strategies through analogue simulation, and outputting corresponding decision support information. The system effectively solves the problems of weak analysis capability, insufficient decision support and the like in an existing purchase decision system, and is suitable for multiple application scenes such as enterprise purchase management and the like.

While AI models, like large language models, are powerful tools with multiple applications, they can be complex to use and can require a lot of resources to operate. The disclosed systems and methods provide tools to generate customized models (or AI agents) that are configured with features like tailored knowledge, capabilities, and instructions that make them faster, more efficient, and use less computational resources. AI agents may offer several technical advantages of improved efficiency, resource use, and connectivity. This disclosure describes systems and methods to configure, evaluate, generate, and deploy the custom models that can more efficiently run specific tasks. Disclosed systems and methods are configured to, for example, receive a query to generate a custom model, generate the AI agent custom model with the information in the query, and then resolve user queries more efficiently using the custom model.

The invention relates to the technical field of comprehensive energy management, and discloses an energy storage coordinated regulation and control method and device, and the method comprises the steps: determining an operation mode of an energy storage station, and packaging the operation mode of the energy storage station as an option; on the basis of the options and the semi-Markov model, constructing a semi-Markov model integrated with the options; and constructing a layered option evaluation model based on the semi-Markov model of the fused options, and solving an optimal energy storage coordinated regulation and control scheme corresponding to the operation mode of the energy storage station in the multivariate application scene based on the layered option evaluation model. According to the method, the station operation mode is packaged in the options, the algorithm solving efficiency is improved, in addition, the parameter quantity and the calculation cost are reduced by adopting the model of the layered structure, and coordinated regulation and control of energy storage under multiple application scenes are achieved in a short time.

The invention relates to the technical field of software, and discloses a dynamic audio buffer management method and system and a medium. The method comprises the following steps: presetting a white list library of a plurality of application scenes, and matching a package name of a current foreground running application with the white list library to determine a current application scene; acquiring system performance state parameters in real time, wherein the parameters comprise at least one of a CPU occupancy rate, a memory occupancy rate and a temperature control and frequency limiting state; generating a buffer adjustment variable according to a statistical result of the audio lagging times; inputting the current application scene, the system performance state parameter and the buffer area adjustment variable into a preset strategy model, and outputting a buffer area gear value; and dynamically adjusting the size of a buffer area of an audio driving layer according to the gear value so as to adapt to the performance change of the system. According to the invention, the problem of lagging or delay caused by a fixed buffer area can be solved.

The invention discloses an energy storage power station capacity measuring and calculating method considering the power grid bearing capacity and multiple application scenes. The method comprises the following steps: firstly, performing fitting correction on a scene by adopting a scene aggregation correction technology based on least square fitting; and constructing an energy storage power station capacity optimal measurement and calculation model considering the power grid bearing capacity and multiple application scenes, finally carrying out linear transformation on the energy storage power station capacity optimal measurement and calculation model, and solving by adopting commercial optimization software. According to the calculation model, multiple application scenes are introduced, and peak regulation, frequency modulation and standby multiple dimensions are considered, so that the operation and income calculation of the energy storage power station are more comprehensive, the behavior of investing the energy storage power station on the user side can be better simulated, and the influence of energy storage access on the power grid can be better evaluated. According to the scene aggregation correction technology, fitting correction is carried out on the scene by introducing the least square method, more efficient and accurate scene expression is achieved, and the problem solving scale and solving difficulty are reduced.

The embodiment of the invention discloses an intelligent interaction method, electronic equipment, a computer storage medium and a program product. The electronic equipment can display information of two or more application programs on the screen of the electronic equipment at the same time, and the information of the application programs can be efficiently and dynamically interacted. According to the scheme provided by the embodiment of the invention, barriers among different information displayed on the screen can be broken, screen contents visible to a user are linked, brand-new intelligent interaction experience and result display are provided for the user, and the multi-task processing capability and efficiency in the electronic equipment are improved.

Systems and methods include obtaining application data for a plurality of applications of an enterprise, wherein the application data relates to applications present in an enterprises network; obtaining log data for a plurality of users of an enterprise where the user data relates to usage of the plurality of applications by the plurality of users; determining i) app-segments that are groupings of application of the plurality of applications and ii) user-groups that are groupings of users of the plurality of users; and providing access policy of the plurality of applications based on the user-groups and the app-segments.

Anycast addressing is utilized to support the connection of multiple application connectors fronting an application(s) to a network element and anycast routing of network traffic destined for the application(s). When an application is indicated for onboarding in a tenant's network fabric, a network controller allocates virtual and anycast addresses to the application. Allocation of anycast addresses is per domain name and port / protocol combination. Upon determining that the application is available, the application connector(s) advertises reachability of the application via the anycast address. The network controller orchestrates configuration of a domain name system entry that resolves the application name to its virtual Internet Protocol (IP) address and destination network address translation rules that translate the virtual IP address to the anycast address and the anycast address to the application's private IP address. Application network traffic can thus be forwarded to the application via any application connector that advertised the anycast address.

Example embodiments of systems and methods for data transmission between a contactless card, a client device, and one or more servers are provided. One or more applets of the contactless card are configured to dynamically generate an encrypted payload appended to a link, wherein the contactless card is configured to transmit the link with the appended payload to the client device via one or more gestures. The one or more servers are configured to receive the payload from the client device via one or more applications, parse and decrypt the payload after launch of one or more applications, and transmit one or more notifications to the client device based on a status associated with decryption of the payload. The client device is granted access to a plurality of services associated with the one or more servers based on the one or more notifications received from the one or more servers.

The invention discloses a data permission control method and device, a storage medium and electronic equipment. The method comprises the following steps: acquiring authority detail information through an authority configuration interface, establishing association based on the authority detail information and user information, and generating an authority rule; forming a permission configuration set based on the permission rule, wherein the permission configuration set is accessed to at least one application module; and in response to a data request of the application module, matching a target permission rule from the permission configuration set, and performing data filtering based on the target permission rule to obtain a data display result. According to the method and the device, the invasiveness to the application modules is reduced, the permission control consistency of the application modules is improved, the reusability of the permission configuration set is high, and the development cost and the maintenance cost of the permission configuration set can be reduced.

Embodiments herein provide techniques related to a NEF. An example technique includes identifying, from an AF that implements a ML model, a request related to reservation of resources for a plurality of AF sessions, wherein the plurality of AF sessions relate to respective UEs of a plurality of UEs, and wherein the request includes an indication of addresses of respective UEs of the plurality of UEs and a QoS parameter; transmitting, to a BSF of the cellular network, a discovery request related to discovery of respective PCFs that are serving the respective UEs of the plurality of UEs; identifying, based on the discovery request, a discovery response that includes indications of the PCFs; identifying, based on the indications of the PCFs and the QoS parameter, a result related to the reservation of resources; and transmitting, to the AF, an indication of the result. Other embodiments may be described and / or claimed.

An example computer system includes a transactional database configured to store multiple data sources each corresponding to one of multiple applications, a standby database configured to store multiple rule schemas and multiple data schemas, and processor hardware configured to execute instructions to monitor for a change to stored data in one of the multiple data sources, via a change data capture process, replicate data from the transactional database to the standby database in response to an update indicated by the change data capture process, identify encrypted data in at least one data object of an updated data table of one of the data schemas of the standby database, extract data from the at least one data object to store decrypted data, wherein the standby database is an external database for the data extraction engine, and reload the decrypted data to one of the data schemas of the standby database.