86 results about "Unified system" patented technology

A unified platform for multi-modal data compression and decompression that enables efficient processing of correlated data streams while preserving relationships between different modalities. The platform employs a virtual management layer to analyze and route input streams, implementing correlation analysis to identify temporal and spatial relationships between streams. Multiple compression methods, including neural network-based approaches, are utilized to compress data sets while maintaining cross-modal dependencies. A neural upsampling system leverages learned correlations between streams to enhance reconstruction quality. The platform includes a synchronization manager that maintains temporal alignment and relationship preservation throughout processing. By integrating correlation-aware compression with neural upsampling techniques, the platform provides comprehensive multi-modal compression capabilities while preserving critical relationships between different data types. The system is particularly suited for applications involving synchronized audio-visual data, sensor streams, and other multi-modal content.

The invention discloses a source network load storage route adjusting method based on an AI control strategy, and relates to the technical field of power system control, and the method comprises the steps: collecting a source side signal, a network side signal, a load side signal, a storage side signal and an exogenous signal, and generating a unified system state of confidence weight and topology embedding; the state is used for digital twinning online calibration, a feasible range and a constraint set are extracted, and a projection operator and guaranteed operation curve set is generated; generating a unified energy routing vector in the feasible range by a hierarchical strategy; performing simulation checking calculation in the digital twinning and compiling into a final instruction and execution plan table; performing closed-loop issuing and receipt checking, and performing event write-back to update guardrails and strategies; the method realizes collaboration, improves on-site consumption of new energy, reduces comprehensive cost, enhances boundary compliance and traceability, is suitable for parks, micro-grids and the like, and is convenient for deployment, operation, maintenance, expansion and upgrading.

The invention discloses an intelligent numerical control machine tool contour error prediction compensation system and a control method thereof, and belongs to the technical field of industrial control and intellectualization, the intelligent numerical control machine tool contour error prediction compensation system comprises a parameter setting module used for setting system parameters and processing parameters of a numerical control machine tool and importing external planning data and configuration files; the online planning module is used for acquiring planning data online; the core control module is used for controlling the executing mechanism to realize multiple motion modes; the data monitoring module is used for dynamically collecting real-time monitoring data in the machining process of the executing mechanism; the neural network prediction module is used for performing tracking error prediction on the plurality of processing single axes based on a neural network model; and the error intelligent control module is used for carrying out iterative optimization on the processing track. Through modular design, all links of numerical control machining are integrated into a unified system, so that the technical problems that a control system of a traditional numerical control machine tool is poor in function expansibility, low in resource utilization rate, high in development threshold, tedious in process and the like are solved.

The invention discloses a video acquisition method and device based on modular low coupling, and relates to the technical field of video processing. The method comprises the following steps: initializing a video processing system, creating a unified system resource management interface, and realizing centralized management of video acquisition, encoding, decoding, OSD control and NPU push modules; based on a modular design principle, video acquisition, coding, decoding, OSD control and NPU push functions are packaged into independent modules, and data interaction between the modules is realized through a standardized interface. The video processing system is modularly designed, and a unified standardized interface is provided, so that the effect of greatly reducing project code coupling is achieved, a developer does not need to pay attention to underlying logic when calling the interface, and module function independence is guaranteed; by means of the modular interface design, developers can rapidly integrate platform functions, development work can be completed without deeply knowing the whole code library, and therefore the project development efficiency is improved.

The invention discloses a task scheduling method for a unified system sky-ground network. The task scheduling method comprises the following steps: constructing a task-oriented communication scene in the unified system sky-ground network; determining a target problem of task scheduling, and modeling the target problem as a Markov decision process; constructing a strategy-value neural network architecture based on multi-agent near-end strategy optimization; and training the constructed strategy-value neural network architecture to obtain a trained strategy-value neural network, interacting with a real environment based on the trained strategy-value neural network, dynamically updating the information age # imgabs0 #, and applying the strategy according to real-time feedback. According to the method, the scheduling efficiency can be effectively improved and the task allocation can be optimized by combining a reinforcement learning framework aiming at network architecture characteristics and time-varying constraints.

The invention relates to the field of power dispatching systems, in particular to a user power consumption behavior prediction and intelligent dispatching system based on a deep learning model, which comprises a multi-source data acquisition and preprocessing module, a deep fusion prediction model and an intelligent dispatching optimization algorithm module, and integrates the modules or models into a unified system platform through a micro-service architecture. The system platform is in real-time butt joint with a power grid monitoring and dispatching center of an electric power company; and the intelligent scheduling optimization algorithm module establishes a multi-objective optimization model by taking load balance of the power system, maximization of power utilization satisfaction of users and minimization of energy consumption as comprehensive optimization objectives. The invention aims to provide a user power consumption behavior prediction and intelligent scheduling system based on a deep learning model, the user power consumption behavior is accurately predicted through innovative model construction and algorithm design, the optimized intelligent scheduling of power resources is realized on the basis, and the overall operation efficiency and the energy utilization efficiency of a power system are improved.

The invention relates to a coal machine spare part similarity identification and coding unification system and method and a storage medium. The system comprises a data acquisition module for extracting coal machine spare part data from a plurality of systems; the cleaning and preprocessing module is used for carrying out unified formatting processing on the spare part data; the feature extraction and matching engine is used for performing multi-dimensional feature extraction on the preprocessed data, including text similarity features, semantic features, structural features and attribute features; the similarity calculation and clustering module is used for calculating the comprehensive similarity of spare part data through a deep fusion network according to the multi-dimensional features, and performing automatic clustering according to the similarity; and the master data generation and system docking module is used for generating unified spare part master data for each cluster and synchronizing the spare part master data to a plurality of systems. According to the method, a large model and deep learning are utilized, multi-dimensional features are extracted and fused for multi-source spare part data, spare part similarity matching is carried out, dependence on a spare part coding format is broken through, and the accuracy and robustness of cross-system matching are improved.

The invention belongs to the technical field of multi-agent cooperative intelligent control, and particularly relates to a multi-mechanical-arm cooperative control method under unknown disturbance, which comprises the following steps: establishing a dynamic model of a strict feedback nonlinear multi-mechanical-arm cooperative system; constructing a communication topological structure of the system through a virtual coupling mechanism; constructing a unified system collaborative error model; introducing a preset time function and a global preset performance function, mapping errors to an adjustable constraint performance space, and ensuring that all error signals are dynamically converged in a performance range set by a user; a task layer shape control force and a pose control force are designed under a distributed gradient descent method framework, a task layer overall control force is constructed, and multiple mechanical arms are driven to move cooperatively and keep a stable formation in a task space; designing a joint layer distributed adaptive control law under unknown disturbance through passive characteristics of a nonlinear system; according to the method, cooperative convergence and stable control of the multi-mechanical-arm system within the preset time can be achieved under unknown disturbance.

The invention discloses an articulated coordinate measuring machine error prediction compensation method and system based on a digital twin model. The method comprises the following steps: constructing a real-time synchronous articulated arm digital twinborn model; probability modeling is carried out on a plurality of error sources of the articulated coordinate measuring machine through a Monte Carlo method, and then error statistical characteristics are obtained. And inputting the error statistical characteristics, the joint angle during measurement of the real joint type coordinate measuring machine and the environmental parameters into an error compensation network. And the error compensation network outputs the end position compensation amount of the current coordinate measurement result. According to the method, the digital twinborn model of the articulated coordinate measuring machine is constructed, measurement point distribution is simulated, high-frequency online real-time compensation is realized in cooperation with an error compensation network, the whole process of'measurement-simulation-prediction-compensation 'can be completed through a unified system, and the real-time performance of error compensation is remarkably improved.

The invention relates to the technical field of satellite positioning, and discloses a high-precision Beidou positioning terminal device and system, and the device comprises a Beidou multi-frequency positioning module which receives B1C, B2a and B3I frequency band signals of Beidou satellites, and generates centimeter-level original observation data; the heterogeneous data fusion access engine is used for carrying out space-time alignment on multi-source sensing data by dynamically accessing laser point cloud, visual SLAM (Simultaneous Localization and Mapping) and UWB (Ultra Wideband) positioning data; the neuromorphic space-time alignment algorithm module unifies a multi-source data coordinate system; the block chain trusted data pool module is used for anchoring the Beidou positioning data and encrypting and storing the sensing data; and a scene semantic decision module. Carrier phase dynamic characteristics are encoded into a pulse sequential sequence by a neuromorphic module in real time, a physical signal is converted into a time-space event understandable by an algorithm, a cross-modal attention mechanism is driven to automatically improve a laser point cloud weight, visual interference is suppressed, and errors of satellite denial scene positioning are reduced.

The invention provides a shuttlecock serving and picking all-in-one machine based on vision. The shuttlecock serving and picking all-in-one machine structurally comprises a moving device, a main control system, a serving device, a vision system and a picking device, the main control system and the serving device are positioned at the upper end of the moving device, the vision system is carried on the top of the serving device, and the picking device is further arranged on the back of the serving device; the limitation of traditional single-function equipment is broken through by combining a Bluetooth module and a computer underlying principle of the main control system with knowledge modules such as a sensor, an electronic element and robot control, a pitching machine and a ball picking machine are integrated into a unified system, a training-recycling closed loop is realized, and manual intervention is reduced; according to the multi-dimensional ball path control system, precise ball serving at any angle (the elevation angle of-30 degrees to 70 degrees) and in any direction (the horizontal rotation of 0-360 degrees) and a self-adaptive ball serving algorithm are achieved; according to the position of a player, the ball serving falling point is dynamically adjusted, a real confrontation scene is simulated, and the ball speed is adjusted in a stepless mode (20-120 km / h), so that different requirements from beginners to professional players are met.

A method, computer program product, and computing system for providing on-demand high-availability service on a storage cluster. A new single-node appliance is added to the storage cluster, the storage cluster includes one or more original single-node appliances and an internal remote system configured to facilitate intra-cluster orchestration operation. A remote system object representing the new single-node appliance is generated in the internal remote system. An appliance identifier for the remote system object representing the new single-node appliance is determined. In response to determining that the appliance identifier is a non-zero appliance identifier, an internal remote session between the remote system object and the storage cluster is established. The one or more original single-node appliances and the new single-node appliance are presented as a unified system. Protected storage volumes are provisioned on any of the single-node appliances included in the unified system.

This invention discloses a method and system for flattening a multi-level hybrid model in the X language, belonging to the field of model compilation technology. The method comprises: obtaining an X language coupling model; and recursively flattening the coupling models within the X language coupling model. By recursively flattening the coupling models within the X language coupling model, the present invention can integrate and flatten continuous models at different levels of a multi-level continuous-discrete hybrid model established in the X language, connected by equations, into a unified system of equations, thereby facilitating the underlying solution and simulation of the X language hybrid model.

The present invention provides a secret computing technology that effectively unifies the exponent of floating point. → a]] P ,[[ → ρ]] Q )( → a=(a0,…,a m‑1 ), → ρ=(ρ0,…,ρ m‑1 )) to calculate the fraction of floating-point vectors with unified exponents ([[ → b]] P ,[[ → ρ max ]] Q )( → b=(b0,…,b m‑1 ), → ρ max =(ρ max ,…,ρ max )(ρ max =max{ρ0,…,ρ m‑1}), satisfying 2 ρ_i a i ≒2 ρ_max b i ) secret exponent unified system, including: the mantissa calculation unit, according to the share [[ → a]] P The i-th element and the share [[ → ρ dif ]] Q =[[ → ρ]] Q ‑[[ → ρ max ]] Q Convert to a share of the replication secret << → ρ dif >> Q The i-th element of i The share of i ]] P (b i =2 ‑ρ_dif,i a i ), from which the share [[ → b]] P .

A unified platform for multi-modal data compression and decompression that enables efficient processing of correlated data streams while preserving relationships between different modalities. The platform employs a virtual management layer to analyze and route input streams, implementing correlation analysis to identify temporal and spatial relationships between streams. Multiple compression methods, including neural network-based approaches, are utilized to compress data sets while maintaining cross-modal dependencies. A neural upsampling system leverages learned correlations between streams to enhance reconstruction quality. The platform includes a synchronization manager that maintains temporal alignment and relationship preservation throughout processing. By integrating correlation-aware compression with neural upsampling techniques, the platform provides comprehensive multi-modal compression capabilities while preserving critical relationships between different data types. The system is particularly suited for applications involving synchronized audio-visual data, sensor streams, and other multi-modal content.

This invention provides a method, system, medium, and device for RTE optimization of multi-sensor data synchronization, belonging to the field of autonomous driving technology. The method receives multi-sensor data, adds a unified system timestamp, and encapsulates the system timestamp, sensor ID, and the data entity itself to generate a data packet. The data packet is stored in a shared sorting buffer according to the system timestamp. The sorting buffer is checked to determine if a preset release trigger condition is met. When the release trigger condition is met, all data packets that meet the time alignment requirements are retrieved from the sorting buffer and assembled into a synchronization data frame. The synchronization data frame is released through the runtime environment interface. The synchronization data frame is received and directly fused. This method significantly reduces the complexity and development / maintenance costs of application-layer software; achieves deterministic and minimized end-to-end processing latency; improves system resource utilization; and has good versatility and reusability.

The invention discloses a multi-standard CAN bus data unification system and method based on dynamic protocol identification, and aims at solving the technical problems that an existing CAN bus terminal protocol is poor in compatibility, data analysis and carbon metering errors are large, and multi-protocol concurrency conflicts exist. The system comprises a CAN FD physical layer controller, a programmable protocol identification engine, a dynamic data mapping module and a TDMA conflict arbitration unit. According to the method, on-line identification and lossless conversion of 12 mainstream CAN protocols are realized through hardware reconstruction (CAN FD + FPGA) and algorithm optimization. A protocol identification engine combines hardware ID filtering and machine learning classification, a dynamic data mapping module adaptively adjusts signal offset based on a metadatabase, and a TDMA arbitration mechanism processes data streams in a time-sharing manner. Test verification shows that the protocol compatibility is improved by 300%, the carbon metering deviation is compressed to be smaller than or equal to 0.5%, the bus load rate is reduced by 40%, the high-precision requirement for mobile source carbon emission monitoring can be met, the method is suitable for industrial scenes such as commercial vehicle mixed plaiting vehicle teams, the ISO14064 carbon emission certification standard is met, and the method has remarkable practical value and popularization prospects.

A plant diagram unification system includes a processor configured to define a unified object that unifies different display modes of objects of same type, acquire a diagram that is used for construction, operation, and maintenance of a plant, detect an object that is included in the diagram, replace a detected object with the unified object, and generate an object unified diagram in which the display modes of the objects of the same type are unified.

The application relates to the computer technical field, in particular to a global data compliance configuration method and system, electronic equipment and program product, wherein the method comprises the following steps: judging whether a data configuration request is received; if the data configuration request is received, determining a target deployment region according to the data configuration request, and building an initial system of the target deployment region; and connecting the initial system with a preset data compliance configuration center, and generating a new localization system meeting the deployment requirements of the target deployment region. Therefore, the problem that enterprises in different countries have different data management systems, the differentiation increases over time, and the operation and maintenance cost increases is solved, and unified configuration and unified system of platform data compliance in different countries can be realized, so that unified operation is realized.

The present disclosure relates to a management system and method for managing client connections in a WinCC Unified system, the management system comprising a WinCC Unified system and clients, each client being connected to the WinCC Unified system over a network. Wherein the WinCC Unified system defines a first variable, a second variable and a third variable; opening the starting picture to access the WinCC Unified system, and executing a first loading event of the starting picture so as to record client information of each accessed client into a first variable in an array form; executing a second loading event of removing the picture to load the client information in the first variable to the list box; and selecting the client information in the list box as the client information of the to-be-removed client, assigning a client identifier of the to-be-removed client to the second variable, and setting the third variable as a set value to trigger the removal operation. Therefore, variables, pictures and operation processes are introduced into the WinCC Unified system, so that an effective client management mechanism is realized, and resource allocation is optimized.

The invention discloses a multi-layer air network energy consumption optimization method based on a sensing, communication, calculation and storage mechanism. The method comprises the following steps: S1, establishing a multi-layer air network system model; s2, respectively establishing an unmanned aerial vehicle-wireless equipment perception model, a wireless equipment-unmanned aerial vehicle-high-altitude platform communication model and an unmanned aerial vehicle-high-altitude platform cache model; s3, establishing a system delay calculation model; s4, establishing a system energy consumption calculation model; s5, establishing an optimization model for jointly optimizing a time scheduling proportion, a task unloading proportion, a compression selection proportion, a service cache decision and a UAV trajectory; and S6, carrying out iterative solution to obtain the optimal time scheduling proportion, task unloading proportion, compression selection proportion, service cache decision and UAV trajectory so as to enable the total energy consumption of the multi-layer air network system model to be minimum. According to the method, perception, communication, calculation and caching are integrated into a unified system model, network functions are re-conceived fundamentally, the problem that a traditional ground network is limited is solved, the method is more flexible, and time delay and energy consumption are reduced while service efficiency is improved.

A multi-dimensional integrated monitoring system and method for underground engineering. The system comprises a point monitoring module (1) mounted on a plurality of first monitoring sections (01) of underground engineering, a line monitoring module mounted on a plurality of second monitoring sections (02), an area monitoring module mounted on a tunnel face (03), a volume monitoring module mounted on a plurality of third monitoring sections (04), and a data analysis platform for receiving and analyzing first feature information collected by the point monitoring module (1), second feature information collected by the line monitoring module, third feature information collected by the area monitoring module, and fourth feature information collected by the volume monitoring module. The system provided in the present application solves the problems of incapability of forming a unified system in which monitoring means are integrated to each other in underground engineering and incapability of comprehensively reflecting the overall situation of engineering.

This application relates to the field of data analysis technology, and discloses an operational analysis method, device, and electronic device applicable to different operational activities. Based on a lifecycle model, different operational activities are promoted using corresponding promotion methods, and feedback information under each promotion method is obtained. According to predefined raw indicator data, the raw indicator data corresponding to each operational activity is extracted from the feedback information. According to predefined operational performance indicator data, the raw indicator data of each operational activity is parsed to obtain the corresponding operational performance indicator data. In response to an operational performance viewing command, the operational performance indicator data of the operational activity is retrieved from the database and displayed in a visual form on a display interface. This solves the problem of the lack of unified and systematic operational data analysis in existing operational activities.

Process for selective attention in a conversation with multiple participants, each participant being either a human or an apparatus, including processing outputs from a plurality of sensors, each sensor sensing a different modality, detecting communication modalities of the multiple participants, a communication modality being either speech or sign language, determining a plurality of probability distributions of source participants to whom a specific participant is paying attention, according to a respective plurality of models, fusing the plurality of probability distributions into a confident probability distribution, defining a confidence level for the confident probability distribution, applying natural language processing to convert each participant's communication to text, clustering the participants into conversation groups, deriving an intended source participant to whom the specific participant is paying attention, according to a source participant with a highest expected utility, and suppressing audio received from participants other than from the intended source participant.

The embodiment of the invention provides an iridium satellite monitoring and early warning system and method, and belongs to the wireless communication signal monitoring technology. The system comprises a signal acquisition subsystem used for acquiring wireless signals in an iridium communication frequency band; the signal processing subsystem is connected with the signal acquisition subsystem and is used for performing iridium communication characteristic-oriented processing on the wireless signal so as to obtain analyzable effective signal data; the information analysis subsystem is connected with the signal processing subsystem and is used for analyzing the effective signal data and generating communication information for representing iridium communication activity; and the monitoring and early warning subsystem is connected with the information analysis subsystem and is used for executing monitoring analysis based on the communication information and outputting a corresponding monitoring result or early warning information. According to the scheme of the invention, acquisition, processing, analysis, monitoring and early warning of iridium communication signals are integrated in a unified system architecture, and continuous monitoring, structured analysis and timely early warning output of iridium communication activities are realized.

The invention provides a method for constructing a distributed multi-station cooperative system based on simulators, and the method comprises the steps: enabling a simulation controller to achieve the information interaction of multiple simulators through a data bus, the interaction information is data input of the simulation controller and simulation data output of the simulator; mapping the simulation simulator to state data corresponding to different system simulators; and controlling the state data through a simulation controller so as to drive different system simulators. The unified system of the multiple system simulators is constructed, overall regulation and control arrangement and distributed application are achieved, and the technical problem that a unified cooperative system based on the multiple system simulators is lacked in the prior art is solved.

Systems and methods for interactive time series analysis, involving a database managing a plurality of videos; a processor, configured to, for receipt of a query, calculate probability information of at least one object on each frame of a video from the plurality of videos related to the query; calculate a state of the at least one object for a specified time based on the probability information from past to the specified time; and input the state at the specified time to a large language model (LLM) configured to output an analysis and prediction in a natural language output responsive to the query.

Provided are systems and methods and computer-implemented systems for generating synthetic data and optimizing performance of large language models, by integrating semi-automatic synthetic data generation, prompt optimization and continual learning into a unified system, without full fine-tuning of the model, to improve performance of the large language model. The cold start problem of the large language model is solved through a multi-stage process, including: generating a diversified parameter set and natural language sentences; constructing synthetic user queries using feature descriptions, parameter sentences and constraint instructions; bootstrapping with a small amount of samples with the help of a compiler, and iteratively evaluating instruction-example combinations to optimize the large language model module; and combining real-time data and synthetic data to complete continual validation and optimization.

The present application relates to the technical field of small target detection and multi-target tracking, and particularly relates to a vehicle tracking and license plate recognition joint detection method based on improved YOLOv8, which fuses vehicle detection tracking and license plate recognition in a unified system, and realizes joint detection through the following steps: firstly, an improved YOLOv8 algorithm is used to detect vehicles and license plates, then a BOT-SORT tracking algorithm based on the Hungarian algorithm is used for vehicle target tracking, and LPRNet is used for license plate recognition; by using deformable convolution operation instead of standard convolution, the receptive field size can be changed according to the image, and the MHSA attention network is added, which greatly improves the object detection accuracy while ensuring lightweight, and the present application integrates vehicle multi-target tracking and license plate recognition in a system, which is convenient to use and easy to deploy in edge devices.

The invention discloses a regional medical treatment and health integrated management information system based on a cloud platform, and relates to the technical field of information systems, the system is based on the cloud platform technology, various medical treatment and related mechanisms are seamlessly integrated on a comprehensive platform, and an information barrier brought by a traditional independent system is eliminated. Specifically, all information is uploaded to the cloud server in a unified manner and interacts with the cloud server, so that the defects of physical isolation and information dispersion caused by respective establishment of systems are overcome. And meanwhile, standardization of data formats is ensured by a unified system architecture, so that data isolation caused by inconsistent data formats is broken. In addition, the uniformity of information flow and the convenience of management are ensured by the integrated architecture, and the expansion, upgrading and maintenance of the system are facilitated by the interface type decoupling design. The system also provides a visual interactive portal which is visual and easy to use, and ensures that medical workers, patients, system management personnel and maintenance personnel can quickly adapt and effectively use the system.