315 results about "Object model" patented technology

The invention relates to an intelligent equipment access system and access method based on an AI large model, and relates to the field of artificial intelligence and Internet of Things. According to the technical scheme, a dynamically adaptive universal object model access framework is constructed, functional attributes, control instructions and data formats of intelligent devices of different brands and protocols are mapped into a standardized logic model, meanwhile, a multi-mode AI large model engine is combined, high-precision voice recognition, voiceprint feature detection and multi-level semantic intention analysis capabilities are integrated, and the intelligent devices of different brands and protocols can be obtained. And an intelligent interaction closed loop of end-cloud collaboration is formed. Semantic analysis adopts a mixed strategy, a natural language instruction is converted through function mapping, a local knowledge base is utilized to match user scene requirements, and external data is queried by means of cloud networking to optimize instruction logic. According to the scheme, the multi-device access and operation and maintenance cost is remarkably reduced, the semantic understanding accuracy and scene adaptability are improved, and the method is widely applied to the fields of smart home, smart medical treatment and industrial Internet of Things.

A computing system is disclosed for generating and optimizing schema-conformant object models. The system obtains input data from multiple sources in structured, semi-structured, or unstructured formats and processes the data using parsing logic to derive a structured rule set defining spatial relationships and constraint conditions. The system generates schema-conformant object representations comprising parametric assemblies, applies the constraint conditions using machine-executed resolution logic, and produces candidate object models through iterative modification of spatial components, dimensional parameters, and adjacency relationships. Performance values are computed for the candidate models using quantitative evaluation of spatial efficiency, material usage, and constraint compliance. An optimized object model is selected based on the computed performance values and may be used to generate construction project plans including technical drawings, material specifications, and scheduling instructions.

The invention relates to the technical field of industrial Internet of Things, in particular to a secondary development system and method based on an industrial Internet of Things gateway. Comprising a client and an industrial Internet of Things gateway. The client issues equipment information and variable information of the configured script equipment to the industrial Internet of Things gateway; the industrial Internet of Things gateway comprises a secondary development module; an initialization module; an object model module; a variable module; and a Python SDK module. According to the invention, system modular decoupling is realized through a publishing and subscribing mechanism of a built-in MQTT server, dynamic extension of multi-industrial protocol conversion and edge computing capability is supported, and a low-code Python SDK development environment is provided. Compared with the prior art, according to the scheme, the edge secondary development period is greatly shortened, the development efficiency is improved, and the core pain points of poor protocol expansibility, openness limitation, high secondary development starting difficulty, large workload and the like in the field of the industrial Internet of Things are effectively solved.

A method, a system, and a computer program product for generation of templates for electronic documents. A first template is generated based on a plurality of electronic documents. The first template defines a first structural arrangement of one or more portions extracted from the electronic documents and includes one or more portions. A machine learning model determines the first structural arrangement. An update to at least one portion is received. A second template is generated based on the first template and the received update. The second template defines a second structural arrangement of the portions as determined based on the first structural arrangement and the received update. An object model representative of at least one of: the first template, the second template, and a difference between the first and second templates is stored.

The invention discloses an object model access parameter dynamic optimization method and system based on reinforcement learning. According to the method, a multi-agent reinforcement learning model is constructed, a device-level state and a network-level state of the Internet of Things terminal device are used as environment state input, access parameters of the terminal device are modeled as an action decision of a reinforcement learning decision model, and the reinforcement learning decision model outputs optimized access parameters according to the current environment state. And continuously updating the strategy network through a reward function. And finally, the control platform deploys the trained strategy model, automatically selects the optimal access parameter configuration when the terminal equipment accesses, and adjusts the access strategy in real time according to the state change of the equipment and the network. Compared with an existing static strategy, the method has the advantages that efficient, low-time-delay and low-power-consumption access of the power internet-of-things terminal equipment can be achieved, and the system resource utilization rate and the communication reliability are remarkably improved.

Method for determining a grasping hand model suitable for grasping an object by receiving an image including at least one object; obtaining an object model estimating a pose and shape of the object from the image of the object; selecting a grasp class from a set of grasp classes by means of a neural network, with a cross entropy loss, thus, obtaining a set of parameters defining a coarse grasping hand model; refining the coarse grasping hand model, by minimizing loss functions referring to the parameters of the hand model for obtaining an operable grasping hand model while minimizing the distance between the finger of the hand model and the surface of the object and preventing interpenetration; and obtaining a mesh of the hand represented by the enhanced set of parameters.

The invention discloses a household appliance and a control method thereof. The method comprises the following steps: acquiring multi-modal data; analyzing the multi-modal data by using a large language model to obtain an intention result corresponding to the multi-modal data; querying a condition triggering rule and object model information according to the intention result to obtain a target rule; and determining a corresponding intelligent agent based on the intention result and the target rule by using an intelligent agent manager, and allocating a task to the intelligent agent, so that the intelligent agent controls the corresponding household appliance according to the task. By means of the mode, household appliance control with higher flexibility and higher intelligence is achieved.

The invention provides a flight environment simulation control system multi-mode simulation method, and belongs to the technical field of aero-engines, and the method comprises the steps: selecting a full-digital simulation experiment or a semi-physical simulation experiment, a running object model and a control model, and the control model comprises a feedforward controller, an active disturbance rejection controller and an extended state observer; the feedforward controller calculates a feedforward control quantity according to an engine speed change rate output by the object model, the extended state observer estimates the total disturbance of the system to obtain an estimated value, the estimated value is fed back to the active anti-disturbance controller, and an initial control quantity is obtained through calculation; superposing the initial control quantity with the feedforward control quantity and the estimated value to obtain a final control quantity, and inputting the final control quantity into a hydraulic regulating valve flow model in an object model; the control parameters of the control model are set through a full-digital simulation experiment, and the set control parameters are optimized through a semi-physical simulation experiment, so that the simulation confidence and efficiency are improved, and the cost is reduced.

An example device for retrieving media data includes a memory for storing media data; and a processing system implemented in circuitry and configured to: retrieve data representing a three-dimensional (3D) object model and one or more levels of detail (LODs) for the 3D object model; send a request to the server device to access data for the 3D object model at one of the LODs, the data for the 3D object model at the one of the LODs including a size, complexity, and components of the 3D object model for the one of the LODs; and receive the data for the 3D object model at the one of the LODs in response to the request, the data for the 3D object model at the one of the LODs having the size, the complexity, and the components of the 3D object model for the one of the LODs.

The invention discloses a template turnover calculation application software design method based on an intelligent algorithm. The method comprises the steps that a data source is transferred from an original turnover area to a target area and from an excess material library to the target area; the fixing rule comprises template use frequency constraint, turnover constraint of different types of templates and leftover material definition; the variable rule comprises a turnover template carrying distance constraint and a turnover template cutting proportion constraint; turnover calculation, turnover object model pairing and paired model inner template calculation; and the turnover result gradually solidifies the rule according to different scenes. The method has the advantages that through the integrated calculation module, automatic calculation of the template turnover efficiency is achieved, manual intervention is not needed, and the calculation efficiency and accuracy are greatly improved; an advanced algorithm and a data processing technology are adopted, the accuracy of a calculation result is ensured, template turnover calculation requirements in different scenes can be met, and the resource utilization rate is improved and the operation cost is reduced by accurately calculating the template turnover efficiency.

The invention provides a dynamic human-machine interface generation system for a power conversion device, and the system comprises a configuration file which is used for defining interface elements, attributes and layout rules of an HMI in a structured language; the configuration analysis module is used for reading and analyzing the configuration file and converting the configuration file into a structured object model containing control types, attributes and layout information; the control factory module is connected to the configuration analysis module and is used for dynamically creating a corresponding control instance according to the control type information in the structured object model and injecting the analyzed attribute information into the control instance; the layout engine module is connected to the control factory module and is used for automatically arranging and positioning the control instances according to the layout information in the structured object model; and the rendering output module is connected to the layout engine module and is used for rendering and outputting the interface of which the layout is completed to display equipment. According to the method, diversified HMIs are dynamically generated according to different requirements, and the purpose of improving code quality and development efficiency is achieved.

Test verification code generation may be automated. Automating the generation of the test verification code may include generating an integrated circuit design for an integrated circuit that includes the object model and generating the verification code based on the object model. The object model is used by a parser to generate a verification code. The object model may include field values including a protection parameter field and a sequence field. The protection parameter field may include information that identifies node(s) that are associated with an intended protected region in the integrated circuit design and indicates characteristics of an encoding scheme applied in the intended protected region. The sequence field may include information representing a list of signals that can report an error. The verification code may be configured to inject the error during simulation of the integrated circuit design to verify that the system correctly responds to the error.

The invention provides a robot simulation task generation method, a medium and equipment, and belongs to the technical field of data processing. The method comprises the steps that natural language task description is obtained, task requirement information of a simulation task is extracted from the natural language task description, and the task requirement information comprises a target object needing to be grabbed by a robot, a related object and the position relation between the target object and the related object; querying a target object model matched with the target object from a preset object library; querying a target scene matched with the related object and a target operation space of the target scene from a preset scene library; and forming layout constraint information of the target object model in the target operation space based on the position relationship and the volumes of the target object and the interferent, and generating at least one simulation task meeting the task requirement information under the layout constraint information. The robot simulation task generation efficiency and the robot simulation task generation quality can be improved.

The invention discloses an object-level environment reconstruction method based on a hyper-quadric surface, and the method specifically comprises the steps: constructing four core assemblies, namely a visual data collection module, a semantic preprocessing module, an object modeling and optimization module, and a data association and loopback detection module, based on an ROS2 frame and employing a modular design; the visual data acquisition module adopts a monocular camera to capture RGB image flow in real time and publish an original image, the semantic preprocessing module carries out semantic information extraction based on decoupling type instance segmentation, the object modeling and optimization module carries out super-quadratic surface initialization and outer point elimination, and then carries out super-quadratic surface optimization, and the object modeling and optimization module carries out super-quadratic surface optimization. Obtaining the precisely fitted geometric representation of the object; and the data association and loopback detection module performs dynamic data association and loopback detection enhancement. According to the method, the object modeling error is reduced, the pose estimation precision is improved, the environment perception capability is enhanced, the real-time processing capability can be maintained, and high-level semantic environment cognition support is provided for autonomous navigation of the robot.

An apparatus for reconstructing a non-rigid object comprises a depth sensor (204); a processor configured to repeatedly perform the following steps: capturing a point cloud using the depth sensor, wherein a first point cloud is set as a canonical model; estimating a scene flow (403) using the captured point cloud and a previous point cloud; pre-warping the captured point cloud using the estimated scene flow; estimating a deformation parameter of the captured point cloud; warping the pre-warping point cloud using the deformation parameter; merging the warped point cloud into the canonical model. The apparatus enables accurate and stable modeling of non-rigid objects.

The present application relates to a method, apparatus, computer device, storage medium, and computer program product for three-dimensional reconstruction of an object. The method comprises: extracting image features from a target object image to obtain multiple target feature maps; detecting key points based on the multiple target feature maps to obtain a two-dimensional position heat map corresponding to each key point of the target object; predicting parent vectors based on the two-dimensional position heat map of each key point and each target feature map to obtain a parent vector heat map corresponding to each key point under each three-dimensional coordinate axis; predicting three-dimensional positions based on the parent vector heat map corresponding to each key point and each target feature map to obtain three-dimensional position information corresponding to each key point; and performing three-dimensional reconstruction based on the three-dimensional position information of each key point to obtain a three-dimensional object model of the target object. The present method can improve the accuracy of three-dimensional reconstruction.

A virtual machine (VM) management utility tool may deploy an object model that may persist one or more virtual machine dependencies and relationships. Through a web front-end interface, for example, the VMs may be started in a specific order or re-booted, and the tool automatically determines the additional VMs that need to be re-booted in order to maintain the integrity of the environment. Through the web interface, for example, the object model may be managed, and start-up orders or VM dependencies may be updated. For VMs that may not start under load, the object model may block access to the VM until the VM is fully initialized.

The invention discloses an object identification method and device based on an improved grey wolf algorithm, equipment and a medium. The method comprises the steps that a traditional grey wolf algorithm is optimized through a search strategy based on dimension learning hunting, and an improved grey wolf algorithm is obtained; acquiring historical identification reference data in the process control scene, and performing clustering processing on the historical identification reference data to obtain clustering data corresponding to a plurality of control working conditions; for the clustering data corresponding to each control working condition, performing parameter searching through an improved grey wolf algorithm to obtain a target object model corresponding to each control working condition; determining a transition transfer model between the two control working conditions in each working condition association group based on the target object model corresponding to each working condition association group with the transition relationship, and determining a multi-working-condition object model according to the target object model corresponding to each control working condition and the transition transfer model between the two control working conditions in each working condition association group. According to the embodiment of the invention, the identification efficiency of the controlled object can be improved.

Method for determining a grasping hand model suitable for grasping an object by receiving an image including at least one object; obtaining an object model estimating a pose and shape of the object from the image of the object; selecting a grasp class from a set of grasp classes by means of a neural network, with a cross entropy loss, thus, obtaining a set of parameters defining a coarse grasping hand model; refining the coarse grasping hand model, by minimizing loss functions referring to the parameters of the hand model for obtaining an operable grasping hand model while minimizing the distance between the finger of the hand model and the surface of the object and preventing interpenetration; and obtaining a mesh of the hand represented by the enhanced set of parameters.

The application provides a method and device for generating a proxy model in a virtual scene, a computer device and a storage medium. The method comprises the following steps: obtaining potential visible set information of a virtual scene and object models in the virtual scene; obtaining a visible bounding box of the object models based on the potential visible set information of the virtual scene; obtaining a model bounding box of the object models; clustering the object models according to the model bounding box and the visible bounding box of the object models to obtain a plurality of target object clusters; generating a visible bounding box of the target object clusters according to the visible bounding box of each object model under the target object clusters; generating a proxy model corresponding to the target object clusters; and determining a model application position point of the proxy model based on the visible bounding box of the target object clusters. The proxy model corresponding to each target object cluster and the application position range thereof are used to reduce DrawCall and game picture loading overhead while ensuring the picture effect of the game picture and avoiding the degradation of the game picture.

The invention relates to a twin modeling method for a modular object production line, and the method comprises the steps: obtaining a characteristic parameter of each component of a modular object as a first input, and obtaining an environment parameter of a target working environment of the modular object as a second input; creating an initial virtual contour of the modular object based on at least a portion of the first input; importing the first input, the second input and the initial virtual contour into a simulation system; in the simulation system, training the first input, the second input and the initial virtual contour by using a model-free reinforcement learning model, and automatically adjusting the first input, the second input and the initial virtual contour at the same time; at least one of a first output associated with the first input, a second output associated with the second input, and a finished virtual contour associated with the initial virtual contour is calculated. The method supports self-creation of a modular object model, also supports modification of existing entity modular objects, and realizes simulation similar to the real world.

The application relates to a data processing method and device based on a configuration management system, computer equipment and a storage medium. The method comprises the following steps: acquiring an object model, an attribute model and a relationship model in the configuration management system; determining a first association relationship between the object model and the attribute model and a second association relationship between the object model and the relationship model based on object coding corresponding to each object; constructing a relationship architecture of the configuration management system based on the first association relationship and the second association relationship; and performing data processing on the configuration management system based on data processing parameters corresponding to a data processing operation and the relationship architecture. Through the above method, data management is directly performed based on the data processing operation, and the data management of the configuration management system is simplified.

The application relates to a construction method for obtaining a viewpoint evaluation object model, and belongs to the field of public opinion analysis. An event abstract text generation model is established, which is used for inputting information text containing event content to obtain event abstract text; a sentence annotation model is established, which is used for inputting viewpoint text for evaluating the event and the event abstract text to obtain a viewpoint with the event abstract text as semantic guidance; wherein the viewpoint is a sentence sequence extracted from the viewpoint text; a viewpoint evaluation object extraction model is established, which is used for inputting the viewpoint and the event abstract text to obtain an evaluation object of the viewpoint; wherein the evaluation object is a word sequence extracted from the event abstract text. The application can accurately obtain a viewpoint with the event as an evaluation object, and improves the analysis performance.

The invention provides an image processing method and device, electronic equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: acquiring a control signal and an observation view angle vector for a target object model; decoding based on the control signal to obtain a dynamic neural texture map of a first area in the target object model in an appearance dimension; decoding based on the observation view angle vector to obtain a view angle neural texture map of the first region in the view angle dimension; and fusing the dynamic neural texture map, the visual angle neural texture map and a pre-trained diffusion neural texture map to obtain a texture map of the first region. According to the invention, the detail expression capability of the texture for rendering the image can be improved.

The invention provides an intelligent association method and system for a protocol template and an object model based on a large model, and relates to the technical field of intelligent conversion. The method comprises the steps that an input protocol template XML file is loaded and analyzed, and first key feature information is extracted; converting the extracted first key feature information into data in a structured intermediate representation form; loading a standard object model from a local object model library, and extracting second key feature information of the standard object model; and according to the target large model, matching the second key feature information with the data in the structured intermediate representation form by calculating semantic similarity in combination with a cue word optimization method, and generating a standardized XML format association relationship table. The problem that in the prior art, a manual analysis method is difficult to meet the rapid and accurate processing requirement is solved.

The execution-time reporting of telemetry of execution of a software program includes identifying a software program and accessing an event stream with multiple event entries associated with the software's components. An object model is generated that comprises a hierarchy of objects and properties associated with the events by creating objects for the software's components, including identifiers, properties, and timestamps. When an AI entity is instantiated for use during the software's execution, an AI object is created with an identifier and properties. The AI object is dynamically modified to reflect events associated with the AI entity during operation of the software program. The telemetry associated with the AI entity is reported according to subscriptions for the telemetry sessions.

Automating testing or use of an application under test (AUT) is greatly simplified when domain object model (DOM) information is available. However, DOM information is not always available. Systems and methods are provided wherein graphical elements are identified and converted to computer code. The computer code is applied to a transparent layer and as a user visually interacts with the AUT, the transparent layer identifies the inputs and the root graphical elements. The inputs are then forwarded to the root graphical elements. The inputs and target graphical elements may be recorded and played back (as-is or modified) on the same or different AUT. The playback then allows a specific graphical element to receive a particular input, even if DOM information remains unavailable.

The embodiment of the invention discloses a scene rendering method and device, computer equipment and a computer readable storage medium, and the method comprises the steps: obtaining a coverage weight map corresponding to a scene model, the coverage weight map being used for indicating the weight of different positions of the scene model covered by a target covering object; according to the position of a target object model contained in the scene model in the scene model, determining an image mapping area of the target object model in the coverage weight map; according to the image mapping area, determining the coverage condition of the target covering object to the target object model; and rendering the scene model based on the coverage condition to obtain a rendering result, and for the target object model which indicates that the coverage condition is not covered by the target covering object, performing rendering based on other model materials except the covering object material corresponding to the target covering object to obtain a target object model which is not covered by the target covering object. According to the method, the target object model which is not covered by the target covering object can be determined based on the covering weight map, and the covering object material of the target object model is closed, so that the waste of computer resources is reduced.

The invention discloses a subcritical coal-fired unit coordination control model identification method and system, and the method comprises the steps: collecting the data of the target operation parameters of a subcritical coal-fired unit, forming historical data, and building two neural network models based on the historical data; selecting historical data under different load change conditions, reconstructing the selected historical data, and respectively inputting the reconstructed historical data into the corresponding trained neural network models to obtain simulation values of the main steam pressure and the main steam flow; and based on the simulation values and historical data of the main steam pressure and the main steam flow, calculating a dynamic relationship among different variables in the controlled object model of the coordination control system of the subcritical coal-fired unit by using an optimization algorithm. According to the method, the problems that the subcritical coal-fired unit cannot be switched to the manual state to carry out the open-loop test in the AGC mode and an engineering calculation method is inaccurate due to variable loads are solved, the identification precision is improved, the on-site debugging time of engineers is shortened, and the working efficiency is improved.

A computer-implemented method includes generating a user interface; receiving a set of object models; processing the received object models; and rendering the document model via a viewport. A non-transitory computer readable medium contains program instructions that when executed, cause a computer to generate a user interface; receive a set of object models; process the received object models; and render the document model via a viewport. A computing system includes a processor and a memory having stored thereon instructions that when executed by the process, cause the computing system to generate a user interface; receive a set of object models; process the received object models; and render the document model via a viewport.