112 results about "Configuration selection" patented technology

The invention belongs to application of a virtual reality technology in the field of automobile exhibition, and particularly relates to an automobile exhibition interactive experience method based on virtual reality. Firstly, a virtual exhibition hall and a vehicle type three-dimensional model are constructed and optimized, so that a user checks the appearance and the internal structure of a vehicle in an immersive manner; recording browsing behaviors, and analyzing preferences through a recommendation algorithm to generate personalized vehicle model recommendation; after a user selects a vehicle, configuration selection and real-time rendering display can be carried out, test driving can be selected, and the system loads different driving scenes to simulate control experience; and finally, capturing a user attention area based on a line-of-sight tracking technology of a clustering algorithm to generate a visual heat map so as to identify preference key points, and providing data support for marketing and exhibition planning. According to the method, the reality sense of virtual display is improved through multiple technologies, interactivity is enhanced, test driving experience is enriched, user preferences are accurately captured, and the defects of an existing automobile exhibition display mode are effectively overcome.

The invention relates to a traffic engineering BIM (Building Information Modeling) and VR (Virtual Reality) technology combined interactive design and simulation system, which relates to the field of traffic engineering and comprises an interactive configuration module used for selecting simulation configuration to obtain user feedback information; the route mining module is used for performing networking frequent mining to obtain a mobile route case set; the virtual driving module is used for starting simulated driving and obtaining a three-dimensional dynamic time sequence diagram of a vehicle and heart rate monitoring time sequence information of a user; the safety scoring module is used for receiving a user driving safety score through the user side; the risk evaluation module is used for obtaining a driving risk evaluation value set; and the safety identification module is used for performing safety identification and then sending the information to the traffic engineering design end. Through combination of BIM and VR technologies, virtual simulation acquisition and analysis of user driving behaviors are realized, so that the driving risk of a design scheme is evaluated in a targeted manner, traffic engineering optimization design is guided, and the safety of traffic engineering design is improved.

The invention is suitable for the technical field of medical equipment, and provides a medical equipment configuration management method and system, a storage medium and medical device.The method comprises the steps that in response to a selection operation instruction of a user for a target configuration file, all parameter configuration items in the target configuration file are read and analyzed, displaying the current values of all the parameter configuration items in a configuration preview interface in a structured mode; performing anomaly detection when the target configuration file is analyzed, and highlighting an abnormal parameter item in the configuration preview interface when the abnormal parameter item is detected; receiving a parameter configuration value selected by a user to update the target configuration file in response to a modification operation instruction of the user on the parameter configuration item in the target configuration file; and in response to a configuration application instruction of a user on the target configuration file, loading the updated configuration parameters into the medical equipment. The problems that the existing parameter configuration selection efficiency is low and the change of the configuration file cannot be known in time are solved.

The invention belongs to the technical field of virtual automobile exhibition, and particularly relates to a virtual automobile exhibition system based on digital twinning. The system comprises a digital twinning construction module which generates a lightweight model and supports first-person visual angle dynamic updating; the user behavior analysis module is used for mapping data such as a sight track into a weighted directed graph, and predicting vehicle types and configuration requirements by using a multi-head graph attention network; the personalized configuration selection module is used for generating a configuration scheme in combination with digital twinborn parameters; the virtual test driving module is used for providing immersive experience based on the configuration scheme and the scene; and the background data analysis module integrates the data to generate a user portrait so as to optimize the exhibition content. According to the system, dynamic virtual-real mapping, accurate demand prediction and data-driven intelligent exhibition are realized, and the user interaction depth and the car purchase efficiency are improved.

Aspects of embodiments pertain to a method for determining an Input / Output (I / O) device configuration for a music teaching system. The method may comprise receiving a plurality of I / O device configurations of a music teaching system; receiving, for a given I / O device of the music teaching system, an initial I / O device configuration; and determining an updated I / O device configuration for the given I / O Device, based on the initial I / O device configuration of the given I / O Device and at least one of the plurality of received I / O device configurations. The determining is performed such that the updated I / O device configuration has improved device performance compared to the initial I / O device configuration.

The invention belongs to the technical field of 3D printing, and particularly relates to an intelligent photocuring 3D printing model optimization method which covers the whole process from obtaining of data representation of a three-dimensional design form to final printing configuration selection. Firstly, spatial distribution characteristics are analyzed based on data representation, then internal and surface fragile areas are identified, and customized structure strengthening processing is implemented. Then, wall layer thickness parameters are adjusted according to strengthening treatment, and the supporting structure is corrected to meet new requirements. Thirdly, virtual printing process simulation is conducted through the corrected supporting structure, and the influence of optimization measures on a printing result is evaluated; finally, an optimal configuration is selected for manufacturing based on the evaluation result. According to the method, through automatic analysis and customization strategies, the weak area of the model is enhanced, the wall thickness and support are dynamically adjusted, the precision and reliability of a printed piece are improved, material waste is reduced, and the preparation time is shortened, so that the production efficiency and the printing quality are improved.

A user device, UE, for a wireless communication network, is connectable to two or more of a plurality of network slices of the wireless communication network, wherein a slice specific random access channel, RACH, resource configuration is associated with one or more of the plurality of slices. Responsive to a first RACH event associated with a first slice, the UE is to determine whether there is an ongoing RACH procedure triggered by a second RACH event associated with a second slice. In case of an ongoing RACH procedure, the UE is toprohibit an additional RACH procedure triggered by the first RACH event associated with the first slice, and / orsuspend the additional RACH procedure for a certain time, and / orstop the ongoing RACH procedure and start the additional RACH procedure, and / ormodify the ongoing RACH procedure, and / ormodify the ongoing RACH procedure to start the additional RACH procedure.

In automated machine learning, an approximate best configuration can be selected among multiple candidate machine-learning configurations by progressively sampling training and test datasets for the iterative training and testing of the configurations while progressively pruning the set of candidate configurations based on associated estimated confidence intervals for their respective performance.

The invention relates to the technical field of software testing, and provides a custom configuration data checking and creating method and platform, electronic equipment and a storage medium, and the method comprises the following steps: carrying out SQL statement pre-configuration of data checking and creating; selecting a number checking condition, and executing the SQL statement of the variable enumeration value; obtaining a query result, and judging whether the query result meets requirements; and if the requirements are not met, calling an automatic script for data creation. According to the technical scheme, the wanted preposed data is searched in a number checking mode, and the traditional manual preparation time is greatly shortened. The platform is compatible with and adapts to different service lines, one-time development is completed, almost zero maintenance is achieved, all the service lines can be used, and customized development investment is greatly reduced; different service requirements are met, an interface automation platform is butted, a number checking and creating closed loop can be formed, and the continuous availability of the platform is kept.

The invention provides an OEM information customization method and device, and relates to the technical field of computers, and the technical scheme is characterized in that an actual hardware component list of a to-be-configured notebook computer is acquired; screening out a group of candidate hardware configuration packets from a plurality of predefined hardware configuration packets; analyzing metadata of each hardware configuration packet in the candidate hardware configuration packets, and determining a hardware configuration packet subset of a final application and an application sequence of each hardware configuration packet in the subset from the candidate hardware configuration packets; and executing the execution instruction embedded in the hardware configuration packet subset of the final application. The OEM information customization method and device provided by the invention have the advantages of adapting to the change of the actual hardware component list, selecting the configuration package based on the actual hardware component list, determining the application sequence of the configuration package according to the rule, completing the configuration matched with the actual hardware component list, reducing the mismatching of the configuration, supporting the processing of hardware combination, and improving the user experience. Automatic configuration selection and application are realized; and a configuration management structure is provided.

The embodiment of the invention discloses a control channel monitoring method and device, a chip, equipment and a storage medium, and relates to the technical field of communication. Comprising the steps that downlink control information sent by network equipment is received, the downlink control information comprises configuration selection information, and the configuration selection information is used for indicating adopted antenna switching configuration; determining the number of target receiving antennas based on the antenna switching configuration indicated by the configuration selection information; and performing control channel monitoring through the antennas with the target number of receiving antennas. By adopting the scheme provided by the embodiment of the invention, the balance between the monitoring quality and the power consumption of the control channel can be realized.

A first terminal device receives a software development kit SDK resource package sent by a second terminal device, and stores the SDK resource package in a storage, where the SDK resource package is obtained by the second terminal device from a cloud server; and in response to SDK configuration selection, loads an SDK selected through the SDK configuration selection into a memory, and displays, on a home screen, an icon corresponding to the SDK loaded into the memory. Each SDK resource package and a standard application are developed according to a predefined unified standard, to ensure that the standard application is capable of successfully invoking, for binding and use, the SDK loaded into the memory.

An integrated circuit configuration selection device (300) selects circuit configurations for realizing a plurality of predefined interconnected functions by using an interconnected integrated circuit (200) obtained by interconnecting a plurality of juxtaposed integrated circuits (20, 30, 40) in which a plurality of FPGAs (10a-10i) for realizing functions are juxtaposed. Said configuration is either one or both of a plurality of interconnected paths and a plurality of function arrangements of the FPGAs (10a-10i). A configuration selection unit (52a) for selecting a circuit configuration in which the number of juxtaposed integrated circuits (20, 30, 40) is minimized from among the plurality of circuit configurations for realizing the plurality of interconnected functions is provided.

1. Name of the product in this design: Graphical User Interface for Industrial Reports in Electronic Equipment. 2. Purpose of this design: For displaying information and interaction on electronic devices. 3. The key design features of this product are its graphical user interface. 4. The image or photograph that best illustrates the design's key features: the front view. 5. Purpose of the graphical user interface: The interface of this design uses a graphical presentation method for industrial report style design, data sequence filling, data rendering configuration selection, data entry rule configuration, data filtering rule configuration, etc. 6. Human-computer interaction method of graphical user interface: The main view is the home page of report operation. Clicking "Data" under "Related Data" in the main view will enter the interface change state diagram 1. Clicking "Collection System" in the interface change state diagram 1 will enter the interface change state diagram 2. Clicking "All Categories" in the interface change state diagram 2 will enter the interface change state diagram 3. Clicking "A1 Steel Group Steelmaking Process" in the interface change state diagram 3 will enter the interface change state diagram 4. Clicking "Blast Furnace" in the interface change state diagram 4 will enter the interface change state diagram 5. Clicking "Sintering" in the interface change state diagram 5 will enter the interface change state diagram 6. Drag the data in the interface change state diagram 6 into the "Total Hardness" data column to enter the interface change state diagram 7. Clicking the second icon from the bottom to the top on the right side of the interface change state diagram 7 will enter the interface change state diagram 8.

A system for managing data includes an application configurator that is configured to obtain, from the client device, a request for a new generated application, wherein the set of configured models is based on a baseline model. In response to the request, the application configurator initiates a guided setup using an user interface to obtain a set of configuration selections for generating the set of configured models, generates the set of configured models based on the set of configuration selections, and apply a set of application programming interface (API) calls to the baseline model to generate a data hub and a spoke model. The data hub and spoke model is provided to a client device requesting the set of configured models.

A vehicle configuration option method, device and equipment and a computer readable storage medium relate to the technical field of vehicle configuration, and comprise the following steps: for each target option package corresponding to a target vehicle type, determining a main option sign and a subordinate option sign for an option sign corresponding to option equipment contained in the target option package; constructing a driving relationship between the main optional sign and the subordinate optional sign; generating an instantiated vehicle type code of the target vehicle type based on the basic vehicle type code of the target vehicle type and the main optional sign; and analyzing and generating target instantiated vehicle type equipment through the instantiated vehicle type code and the driving relationship. According to the method and the device, the workload of selective loading is reduced, and the incidence relation between the vehicle type and the selective loading package is optimized, so that the structure and the management mode of the vehicle type code are effectively simplified, errors and omissions in the configuration process can be reduced, the accuracy and the consistency of vehicle configuration are improved, and the management efficiency and the quality of the instantiated vehicle type are improved.

The invention discloses a self-adaption energy storage demand control method based on prediction confidence, and the method comprises the following steps: a preparation stage: carrying out scene recognition and configuration selection, recognizing the current date type, and loading a corresponding configuration parameter according to a recognition result; in the execution stage, a rolling execution closed-loop control mechanism is adopted, the closed-loop process of'prediction-evaluation-adjustment-optimization-execution-feedback 'is completely executed in each first time period, and real-time accurate regulation and control of the energy storage system are achieved through dynamic iteration; in the learning stage, after the execution stage is completed, incremental updating is conducted on the prediction model through the actual operation data of the whole period of the day. The technical problems that an existing energy storage demand control method is lack of robustness to prediction errors, unreasonable in safety boundary strategy and lack of multi-scene adaptability due to the fact that the load prediction errors are large are solved.

The invention discloses a dynamic equipment layout method based on a quasi-object strategy and a multi-target ant colony optimization algorithm. The method comprises the steps of layout initialization, layout legalization operation, a movement strategy based on reference equipment, configuration optimization operation and Pareto optimal configuration selection based on a maximum and minimum target distance method. N configurations Xl (l = 1, 2,..., n) are randomly generated, each ant l represents one configuration Xl, and initial configurations of the n ants are obtained; performing legalization operation on the configuration X1 by adopting a gradient method based on dynamic step length, executing a movement strategy based on reference equipment to obtain a group of compact and legal configurations, and recording the configurations as a configuration library BL; selecting all non-dominated configurations in the set BL, and storing the non-dominated configurations in an external document CS; and for the current ant l, generating a random number o, and judging the size relationship between the random number o and the parameter p to select an optimization strategy, when o is greater than p, selecting to execute a local search strategy based on improved pseudo-random proportion, otherwise, using a global optimization strategy based on ecological niche.

The invention relates to a memory chip and a semiconductor test system. The storage chip comprises a clock selector, a configuration selector, an on-chip clock source and a storage module; wherein the clock selector is used for determining a working clock signal of the storage chip in an external input clock signal and an on-chip clock signal generated by the on-chip clock source based on a received signal; the configuration selector is used for setting the on-chip clock source and / or the storage module based on the received signal; the on-chip clock source is used for generating at least one on-chip clock signal based on the setting of the configuration selector; and the storage module is used for writing and / or reading data based on the received signal and the work clock signal. By adopting the storage chip, the compatibility and the flexibility can be improved.

In general, the current subject matter relates to configuration selection enhancements for layer 1 / layer 2 (L1 / L2) triggered mobility (LTM). In some implementations, configuration selection enhancements for LTM can include receiving, at a centralized unit control plane (CU-CP) of a base station from a first distributed unit (DU) of the base station, data relevant to prepare a LTM handover (HO) configuration of at least one service for a user equipment (UE), and can include, after receiving the data, requesting, by the CU-CP, a second DU to prepare, considering the data, at least one LTM target cell configuration for the HO of the at least one service for the UE.

The application discloses a global learning optimization method and system for airport scene taxiing scheduling, and the method comprises the following steps: constructing an airport taxiway multi-graph model, converting the taxiway network into a discrete multi-graph structure containing speed configuration selection; establishing a global multi-objective AGM optimization model with the path, speed profile and ground waiting delay of all aircrafts as decision variables, minimizing the total taxiing time and total fuel consumption as the optimization target, and setting multiple constraint conditions; adopting random key hierarchical coding to uniformly represent all aircraft taxiing plans; generating a feasible path through heuristic guided decoding, and combining a time-space repair mechanism to guarantee the feasibility of the solution; constructing a diversified mating pool driven by topological clustering, adaptively activating the mating pool based on a large language model and allocating computing resources; and outputting a Pareto optimal taxiing scheduling scheme through iterative evolution. The application can simultaneously consider the taxiing optimization of all aircrafts and provide a truly selectable Pareto optimal solution set.

The application discloses a kind of based on prediction confidence self-adaptive energy storage demand control method comprising the following steps: preparation stage, scene identification and configuration selection are carried out, current date type is identified, and corresponding configuration parameters are loaded according to the identification result;Execution stage, the closed-loop control mechanism of rolling execution is used, the closed-loop process of "prediction-evaluation-adjustment-optimization-execution-feedback" is completely executed every first time period, and real-time accurate regulation and control to energy storage system is realized by dynamic iteration;Learning stage, when the execution stage is completed, the actual operation data of the whole cycle of the day is used to incrementally update the prediction model.The application solves the technical problems of the existing energy storage demand control method due to large load prediction error, lack of robustness to prediction error, unreasonable safety margin strategy and lack of multi-scenario adaptability.

The invention provides a model conversion method and device and a storage medium. The method comprises the steps of receiving a model conversion request sent by a client based on a designer canvas; the model conversion request comprises a domain model and a model type to be converted; loading a model conversion engine; calling a model conversion engine to convert the domain model into an application class model under the model type; and if the conversion is completed, storing the application class model into a model database. According to the embodiment of the invention, through a mechanism of converting the application model from the domain model and in cooperation with recording and storage functions of the conversion operation, tracing of the model modification history is realized, the user is guided to complete configuration selection and data input through the built-in and predefined model conversion engine, operations such as manual compiling of complex conversion scripts by the user are reduced, and the user experience is improved. The technical operation threshold is greatly reduced, omission or errors possibly caused by manual synchronous operation are effectively reduced through the mechanism, and the consistency maintenance level between different abstract levels is remarkably improved.

The present invention relates to the field of image processing technology, specifically providing a programming method for a telescope image acquisition and camera control system. An automated engineering configuration file is constructed by reading an automated acquisition card configuration file to determine the image acquisition derived class header file and source file involved in compilation. The image acquisition module includes an image acquisition interface class and an image acquisition derived class. The corresponding image acquisition derived class is selected for instantiation based on acquisition card information. During software initialization, a camera communication module selects and instantiates the corresponding camera communication derived class based on the camera brand and model configuration read from the runtime camera configuration file. This method reduces program development workload, code maintenance workload, and program debugging difficulty, improves the scalability of cameras and acquisition cards in the code, and enhances software adaptability.

A method for managing virtual machines (VMs) obtaining, by a metadata file manager, an instant access request for instant access to a backup of a VM to execute in a production host, wherein the backup is stored in a backup storage system, in response to the instant access request: obtaining a configuration selection for the instant access of the backup, obtaining backup metadata associated with the backup, generating, at the production host, a temporary virtual disk based on the configuration selection and the backup metadata, generating, in the metadata file manager, a second virtual disk comprising logical blocks, mapping VM data stored in the backup storage system to the logical blocks in the second virtual disk, configuring the VM to read from the temporary virtual disk, and servicing a write request of the temporary virtual disk using the mapping of the VM data in the second virtual disk.

A data processing system for selecting configurations for virtual functions includes a runtime processor coupled to a reconfigurable processor having arrays of coarse-grained reconfigurable units. The runtime processor receives a virtual function request specifying resource requirements including compute requirements, memory requirements, or performance requirements. The runtime processor analyzes the resource requirements to determine a resource profile characterizing the virtual function's computational needs, evaluates available configuration options that provide different array allocations, and selects a configuration that matches the resource profile to configuration capabilities. Selection is based on comparing the resource profile against capability thresholds, where configurations providing one array per virtual function satisfy low requirements, configurations providing two arrays satisfy medium requirements, and configurations providing four arrays satisfy high requirements. The selected configuration optimizes resource utilization while meeting the virtual function's requirements.

1. Name of the Design Product: Graphical User Interface for Vehicle Ordering and Configuration Selection on Electronic Devices. 2. Use of the Design Product: For an electronic device. 3. Design Key Points of the Design Product: Lies in the graphical user interface. 4. Picture or Photo that Best Illustrates the Design Key Points: Variation State Diagram 1. 5. The carrier is of conventional design, and the rear view, left view, right view, top view, and bottom view are omitted. 6. Use of the Graphical User Interface: This graphical user interface of the design is used for vehicle configuration, including basic vehicle configuration, exterior configuration, wheel configuration, interior configuration, and optional configuration. 7. Explanation of the Variation States of the Graphical User Interface: The main view is the home page interface, used to display vehicle advertisement pictures and reservation entrances. Click the "Reserve Now" button in the main view to jump to Variation State Diagram 1. Among them, the page displayed in Variation State Diagram 1 is the vehicle model option. Click the "Exterior" button in Variation State Diagram 1 to jump to Variation State Diagram 2. Among them, the content displayed in Variation State Diagram 2 is the exterior option. Click "Interior" in State Diagram 2 to jump to Variation State Diagram 3. Among them, the content displayed in Variation State Diagram 3 is the interior option. Click "Rim" in Variation State Diagram 3 to jump to Variation State Diagram 4. Among them, the content displayed in Variation State Diagram 4 is the rim option. Click "Optional" in Variation State Diagram 4 to jump to Variation State Diagram 5. Among them, the content displayed in Variation State Diagram 5 is the optional option. Click the "Next" button in Variation State Diagram 5 to jump to Variation State Diagram 6. Among them, the content displayed in Variation State Diagram 6 is vehicle configuration, etc.

The invention provides a light commercial vehicle product access type inspection configuration optimization method and device, and the method comprises the steps: carrying out the analysis of applicable laws and regulations based on type inspection items, constructing a type inspection configuration parameter library based on an analysis result, filling the parameter library with product configuration parameters to form a plurality of configuration parameter sets, and carrying out the optimization of the product access type inspection configuration of a light commercial vehicle. And constructing an incidence matrix of the filing parameters and the type inspection items, obtaining an optimized configuration parameter set combination through a model based on the configuration parameter set, the corresponding configuration selection matrix and the incidence matrix, and generating a type inspection scheme table based on the configuration parameter set combination. Compared with a traditional manual configuration method, the method has the following beneficial effects: through automatic configuration and optimization, manual intervention is reduced, and the making efficiency of an inspection scheme is greatly improved; an inspection scene is fully covered through an intelligent algorithm, and omission and errors are avoided; resource configuration is automatically optimized, and repeated testing and resource waste are reduced; the flow is uniformly configured, and the comparability and reliability of the test result are improved.

Aspects of the present disclosure relate to automated optimization of machine learning models. Embodiments include determining a set of initial configurations for parameters associated with the machine learning model. Embodiments further include selecting a configuration based on the set of initial configurations and an evolutionary selection process comprising excluding configurations that result in a level of performance for the machine learning model that is below a threshold. Embodiments further include executing the machine learning model using the selected configuration.

In automated machine learning, a near-optimal configuration can be selected among multiple candidate machine learning configurations by progressively sampling training and test datasets for iterative training and testing of the configurations, while progressively pruning the set of candidate configurations based on associated estimated confidence intervals of the corresponding performance.