1268 results about "Configuration system" patented technology

The invention discloses a patent disclosure auxiliary writing method and system based on multi-agent collaboration. The method comprises the steps that a multi-agent system composed of a collaboration agent, an agent agent and an expert agent is constructed, a knowledge base and a decision module of each agent are configured, and a collaboration architecture of a task scheduler, an arbiter and a shared information space is established; the method comprises the following steps: receiving an original technical scheme of a user, and constructing a structured intermediate representation through multi-agent parallel semantic analysis and feature extraction; based on the representation, a writing task sequence is generated through dynamic task decomposition, intelligent agent division is coordinated through a contract network protocol, and content generation and verification are completed based on a multi-round debate mechanism; performing multi-dimensional consistency detection on the generated draft, and eliminating logic conflicts and expressing defects through iterative revision; and finally, an interest portrait is generated based on the user technical scheme and the optimized draft, interest retrieval is performed, a technical content report is output, and the efficiency and quality of disclosure book writing are improved.

The invention relates to the technical field of computer system structures and storage, in particular to a non-volatile memory quick recovery method based on metadata priority and on-demand loading. The method comprises the following steps: in response to a system fault signal detected by a voltage monitoring unit, freezing a processor context and traversing a page table structure to extract system configuration information; writing the system configuration information and business data codes in the volatile memory into a nonvolatile medium to generate a persistent state mirror image; analyzing the persistent state mirror image, extracting address conversion metadata, and reconstructing a mapping relation from a virtual address to a physical page frame in a volatile memory; and generating an address mapping table, wherein the physical page frame pointed by the address mapping table is set to be in an existing state but is not associated with the effective service data. According to the method, decoupling of the control flow and the data flow is realized by constructing a virtual ready state, and quick starting of the system and immediate response of key services are realized on the premise of not depending on the total capacity of a memory.

The invention provides a code agent construction system, a construction method thereof and a code generation method, and relates to the technical field of computers, in particular to the technical field of artificial intelligence such as large models. According to the specific implementation scheme, the code agent construction system comprises an intelligent cooperation engine, a layered template library, a semantic understanding and layered retrieval system, a T-RAG generation and optimization system and a closed loop verification system; wherein the layered template library comprises a project-level template, a function-level template and an API-level template; the semantic understanding and hierarchical retrieval system is configured as follows: analyzing user requirements through a natural language understanding module to generate an intention vector, and sequentially executing project-level, function-level and API-level three-level progressive template retrieval; and the T-RAG generation and optimization system is configured to inject the hierarchical retrieval result into the cue word of the large language model to generate deployable codes containing front-end and rear-end logics.

The invention relates to the field of data processing, in particular to a multi-parameter collaborative optimization method and system based on a data center cooling system, and the method comprises the steps: obtaining a cooling subsystem of a computing equipment integrated cabinet, and carrying out the short-time temperature analysis of the computing equipment integrated cabinet based on infrared monitoring data and temperature sensing data, if it is confirmed that the limiting temperature of the component is not higher than the corresponding preset temperature threshold value according to the current temperature distribution, and it is confirmed that the continuous heating temperature is lower than the preset temperature change threshold value based on the temperature change trend, the temperature change trend and the current temperature distribution are obtained; if yes, returning to the step of executing multi-modal data acquisition on the computing equipment integration cabinet and the cooling subsystem, and otherwise, synthesizing the predicted temperature data, obtaining a cooling subsystem configuration strategy and setting the cooling subsystem. According to the invention, the cooling monitoring and adjustment of the computing equipment of the data center are realized by integrating the data collected by the temperature sensor and the thermal imaging probe which are reasonably arranged.

The invention discloses a data center infrastructure personnel intelligent configuration system, and belongs to the technical field of data center operation and maintenance management. Comprising an acquisition module, a man-hour prediction module, a configuration module and a feedback module, the man-hour prediction module is used for calculating the health coefficient of the equipment according to the equipment list and performing man-hour prediction; the configuration module is used for configuring the number of personnel according to the prediction result; the feedback module is used for outputting an executable personnel configuration scheme through a preset scheduling system; according to the method, a multi-dimensional configuration scheme meeting the SLA requirement is output through a real-time optimization algorithm of precise man-hour modeling and fusion of dynamic factors, real-time generation of the scheme is achieved, and traditional manual measurement and calculation which consumes several days are replaced.

The invention discloses a vehicle-mounted fault diagnosis system, method and device and a storage medium, and relates to the technical field of rail transit, and the method comprises the steps: configuring system basic parameters through a data preloading module, so as to control the system to start and operate according to the system basic parameters; the log analysis module receives the running log of the train, analyzes the log, obtains abnormal events of a train subsystem and a vehicle-mounted controller, and obtains basic fault information based on the abnormal events; the alarm module performs verification and fault hardware positioning on the basic fault information, obtains a fault positioning result and generates alarm information; the database management module queries a downtime log or / and an event log according to a fault positioning result, and constructs an event curve to determine a fault reason; the parameter tracking module tracks the event curve and judges whether the fault has cross-system influence or not; accurate and reliable fault correlation analysis in a complex scene of multi-system interaction of the train is realized, so that the fault diagnosis and operation and maintenance efficiency is improved.

The present disclosure relates generally to robotic systems, and more specifically to systems and methods for specifying a robot task configuration by means of annotating a visual workspace representation in coordination with a waypoint optimization process. This system enables a much broader use of robotic automation by saving time and reducing technical complexity. This system can be used to configure any visually enabled robotic task, such as tasks in warehouse management, manufacturing, delivery, inspection, logistics, etc.

An infection control tool for a building HVAC system includes processing circuitry configured to receive one or more inputs defining a HVAC system configuration for each of a baseline scenario and one or more other scenarios. The processing circuitry is also configured to estimate infection risk and at least one of energy consumption or operating cost for each of the one or more other scenarios relative to the baseline scenario. The processing circuitry is also configured to operate a display to provide the infection risk and at least one of the energy consumption or operating cost to a user.

An information technology system for a distributed manufacturing network includes an additive manufacturing platform configured to manage workflows for a set of distributed manufacturing network entities associated with the distributed manufacturing network. The information technology system includes a set of digital twins generated by the additive manufacturing platform. The information technology system includes an artificial intelligence system configured to be executed by a data processing system in communication with the additive manufacturing platform. The artificial intelligence system is trained to generate process parameters for the workflows managed by the additive manufacturing platform using data collected from the set of distributed manufacturing network entities. The information technology system includes a control system configured to adjust the process parameters during an additive manufacturing process performed by at least one of the set of distributed manufacturing network entities.

In some aspects, a cloud-based computer system includes: a quantum computing system comprising a quantum processing unit; a container management and execution system configured to receive a container and execute a program within the container; and a communication channel between the container management and execution system and the quantum computing system for providing program instructions to the quantum computing system. The container management and execution system and the quantum computer system may be co-located in a data center or located in different data centers. The latency of the communication channel may be selected to optimize cost for a required computer performance.

A configurable power supply bay system. The configurable power supply bay system includes a power supply bay and a power supply bay system configuration component, the power supply bay configuration component being configured to be mounted to the power supply bay, the power supply configuration component configuring the power supply bay to mount a plurality of types of power supply units within the power supply bay, each of the plurality of types of power supply units having respective external characteristics.

The invention discloses a starting display method of electronic equipment, equipment, a medium and a product, and relates to the technical field of starting display, and the starting display method comprises the following steps: in the starting process of the electronic equipment, in response to execution of a power-on self-test stage, displaying a power-on self-test stage interface on a display component of the electronic equipment, the power-on self-test stage interface comprises at least two first display areas, and the at least two first display areas display at least one of the following information: first system configuration information and starting execution information. According to the method, the key hardware configuration and the real-time starting state are visually presented in the starting process without additionally entering a BIOS interface and executing a complex instruction, so that the problem of low operation efficiency caused by tedious operation of obtaining starting related information of the electronic equipment in a starting display method of the electronic equipment in the related technology can be solved, and the starting efficiency of the electronic equipment is improved. And the operation efficiency of obtaining the starting related information is obviously improved.

The invention discloses a lip language-to-voice conversion method and device, a computer storage medium and a terminal, and aims to solve the problems that a lip language-to-voice conversion technology cannot be deployed on terminal equipment and voice quality cannot meet application requirements. The method is combined with a neural vocoder which reduces calculation complexity and resource requirements, system configuration requirements are reduced while system parameters are reduced, a design basis is provided for deploying a lip language-to-speech method on terminal equipment, and context-related visual feature sequences and user audio embedding vectors are fused, so that the user audio-to-speech conversion efficiency is improved, and the user audio-to-speech conversion efficiency is improved. A Mel spectrum acoustic feature sequence used for being converted into a voice waveform is obtained, and a user audio vector fused with the Mel spectrum acoustic feature sequence is obtained, so that the output voice waveform is more consistent with the real voice of a user; according to the embodiment of the invention, technical support is provided for deploying and applying the lip language-to-speech method meeting the speech quality requirement on the terminal equipment.

The invention belongs to the technical field of chip design, and discloses a three-dimensional stacked heterogeneous in-memory computing system and a data interaction processing method thereof.The three-dimensional stacked heterogeneous in-memory computing system comprises a storage chip layer and an AI processing chip layer located below the storage chip layer, the storage chip layer is electrically connected with the AI processing chip layer, and the AI processing chip layer is electrically connected with the storage chip layer. The AI processing chip layer is of a heterogeneous storage and calculation integrated structure integrating an RRAM storage and calculation array and an SRAM storage and calculation array, and the RRAM storage and calculation array is used for storing system configuration data; and the SRAM memory array is used for writing read-write data of the memory chip layer and completing data processing in the array. According to the three-dimensional stacking heterogeneous storage and calculation integrated device, through heterogeneous cooperation of the RRAM and the SRAM storage and calculation integrated array, key problems existing in the prior art are fully balanced and considered, finally, the optimal design of a system architecture level is achieved, and core obstacles are cleared away for large-scale application of the three-dimensional stacking technology in the field of AI chips.

The invention discloses a server configuration system and method, and relates to the technical field of server configuration. The first end of the first server node is connected with the substrate management controller; wherein under the condition that the server configuration mode of the server configuration system is a single-path server mode, the second end of the first server node is suspended; and under the condition that the server configuration mode of the server configuration system is a two-way server mode, the server configuration system further comprises a second server node, and the input end of the second server node is connected with the output end of the first server node. According to the invention, the use scene of server configuration is expanded.

The invention provides a dynamic risk control method and system based on streaming processing, and the method comprises the steps: carrying out the rule configuration operation for a graphic rule configuration interface to configure a risk control rule, and generating a risk analysis code of a risk control task based on a preset template engine and the risk control rule; and then compiling and packaging the risk analysis code to generate a program package of a risk control task, pushing the program package to a preset distributed stream processing cluster, obtaining an event message generated by a service system from a target data source through the preset distributed stream processing cluster, and running the program package to realize risk analysis of the event message. And storing the risk analysis result through the preset memory database, so that the business system asynchronously obtains the risk analysis result from the preset memory database. By adopting the risk control system, the problems of high programming capability requirement and complicated operation of the existing risk control system in the system configuration level can be relieved.

The invention discloses a system-on-chip, a system-on-chip configuration method and electronic equipment. The system on chip comprises a multi-core RISC-V processor and a field programmable gate array (FPGA), the FPGA is configured to send an initial configuration completion signal to the multi-core RISC-V processor after the initial configuration is completed by power-on starting; the multi-core RISC-V processor is configured to start a bootloader according to the initial configuration completion signal, and the bootloader is configured to start the bootloader according to the initial configuration completion signal; under the condition that an FPGA reconfiguration event occurs, a reconfiguration request signal is sent to the FPGA; the FPGA is further configured to set a storage position to obtain new configuration data, and after reconfiguration is completed, a reconfiguration completion signal is sent to the multi-core RISC-V processor; the multi-core RISC-V processor is further configured to execute system interface reinitialization and / or configuration parameter updating according to the reconfiguration completion signal. According to the scheme of the invention, a bidirectional configuration mechanism between the FPGA and the RISC-V is realized based on the standardized interaction signal, and the dynamic configuration / upgrading requirements of system functions are fully met.

The invention relates to the technical field of optical line terminal configuration, in particular to a method and system for automatically configuring optical line terminals of different manufacturers based on artificial intelligence. The method comprises the steps of collecting multi-source heterogeneous data to train a deep learning model, constructing a Transform or RNN-based architecture of a TensorFlow framework, performing cross validation and model compression, then performing optimization through a TensorRT inference engine, developing an intelligent configuration application system, deploying the intelligent configuration application system to a control host, and providing algorithm support for automatic configuration. By constructing an automatic configuration system based on artificial intelligence, the problems of heterogeneous compatibility and intelligent configuration of OLT equipment of multiple manufacturers are systematically solved. In a configuration optimization link, a virtual simulation environment is constructed based on a real network topology, a configuration effect is evaluated through multi-dimensional indexes such as throughput and time delay, potential conflicts are detected in combination with an AI algorithm, an optimization scheme is generated, and the configuration error rate of manual operation is reduced.

The invention provides a dynamic cloud side-end security collaborative unloading method, system and device and a medium, and belongs to the technical field of edge computing. The method comprises the steps that original data are collected through terminal equipment, differential privacy processing is carried out, and preprocessing task data with multi-dimensional feature marks are generated; analyzing the feature marks through an edge cloud gateway, and performing task grading and hierarchical mapping by using a rule engine to generate a scheduling instruction; executing corresponding security processing according to the task level and generating task result data; monitoring a node resource state in real time, dynamically adjusting a node role based on a preset condition, and updating a resource topology; collecting system operation data and dynamically adjusting a scheduling strategy through an optimization algorithm; and finally, a task result is delivered to an application end, an operation log is written into the block chain, and system configuration is continuously optimized based on historical data. According to the invention, accurate matching of tasks and resources, full-link security protection and dynamic optimization of system resources are realized, and the efficiency and security of cloud side-end collaboration are improved.

The invention discloses an intelligent verbal skill process configuration system and method based on a dynamic rule engine, and the system comprises a configuration analysis module, a process engine module, an execution engine module and a large model intention recognition module. The problems of rule solidification, high maintenance cost and low intention recognition accuracy in existing verbal skill process configuration are solved. The configuration analysis module analyzes a JSON format verbal skill rule configuration file to realize visual definition and dynamic update of the rule; the process engine module completes rule instantiation through variable replacement and drives dynamic routing based on an intention recognition result; the execution engine module instantiates a service class by using a reflection mechanism to realize decoupling of rules and service logic; the large model intention recognition module innovatively adopts a semantic similarity weighting algorithm, and intention recognition accuracy is remarkably improved by calculating semantic vector cosine similarity of user input and branch intention and combining service weight and context correlation degree.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for managing and adapting monitoring programs. In some implementations, a system communicates with a set of remote devices involved in a monitoring program that involves collection of data from the remote devices over a communication network. The system determines a set of attributes associated with an outcome or condition that has occurred for multiple of the remote devices. The system generates parameters to adapt the monitoring program, and the system selects a second group of remote devices to involve in the adapted monitoring program based on profiles or sets of attributes of users associated with the remote devices. The system configures the remote devices in the selected second group to perform monitoring for the adapted monitoring program, including acquiring data for the adapted monitoring program and providing the acquired data to a server over the communication network.

Systems and methods for adaptive threat detection system configuration based on advanced environmental security ranking. A method includes real-time adjustment of system components, including EDR agents, event scoring units, and event enrichment units, in response to changing threat landscapes and network environments. A method further includes retraining machine learning models, controlling thresholds, and selecting event datasets for training and testing. Additionally, a system configuration manager dynamically adjusts detection engine parameters, including correlation levels, rule-based detector settings, and the depth of analysis.

The invention relates to the field of data processing, and provides a software cost method and system based on dynamic configuration and hierarchical analysis. The method comprises the following steps: dynamically loading corresponding configuration parameters and algorithms by evaluating a method identification field; constructing a standardized cost parameter configuration system, including configuring an estimated function point reference value, an estimated function point weight coefficient and a scale adjustment factor; based on the evaluation method, a tree budget configuration table is preset, hierarchical node design is adopted, a budget tree is constructed, and a tree budget configuration and cost declaration / evaluation header is formed; transferring the configuration right of the tree budget configuration and the cost declaration / evaluation header to the back end, so that the back end dynamically loads a preset header template according to the enabled cost standard, and synchronously injects field attribute rules and calculation formula metadata; obtaining an unstructured document uploaded by a user, and analyzing the unstructured document and the header template by adopting a large language model to obtain software cost details; and generating an evaluation report through the expert review software cost details.

The invention relates to the technical field of computer vision and edge computing, and discloses a multi-computing-power collaborative video structured analysis method, which comprises the following steps of: acquiring a plurality of paths of original video streams, and synchronously decoding the plurality of paths of original video streams; gradient analysis is adopted to evaluate the decoded multiple paths of original video streams, and a preprocessing algorithm combination is selected based on a quality feature vector; establishing a data transmission channel, and adopting an asynchronous communication protocol and a multi-level cache system; performing content complexity analysis, and performing model matching according to the content complexity analysis to obtain a scheduling decision; carrying out distributed deployment, and carrying out pipeline reasoning on the deployed model; pipeline reasoning results are fused, and consistency constraint verification is carried out on fusion results; optimizing system configuration parameters according to a video structured analysis result to realize video structured analysis; the real-time performance, the accuracy and the system stability of video analysis are improved.

An AI-based platform for enabling intelligent orchestration and management of at least one operating process is provided herein. The AI-based platform includes an artificial intelligence system that is configured to generate a prediction of an energy pattern associated with the at least one operating process. The AI-based platform is also configured to manage the at least one operating process based on the prediction of the energy pattern.

The invention relates to a park micro-grid distributed power supply and energy storage coordinated optimization configuration method, and belongs to the field of power system computer software application. The method comprises the steps that original data collection and import design is carried out, and a user interaction visual interface is created and used for importing and visualizing original data needed by micro-grid planning; establishing and designing a distributed power generation model, namely establishing a wind power generation model and a photovoltaic power generation model; establishing and designing an energy storage model, and adopting a KiBaM quasi-steady-state battery simulation model; time-of-use electricity price setting design: designing a time-of-use electricity price setting interface; model control and target optimization design, including micro-grid power balance and storage battery charging and discharging power control design; designing a micro-grid operation program, and optimizing system configuration and a scheduling strategy; and carrying out simulation calculation and result data analysis, verifying the effectiveness of a system optimization configuration scheme, and realizing park micro-grid distributed power supply and energy storage coordinated optimal configuration.

The invention discloses a circular region quantum communication channel redundancy configuration system based on AI-block chain collaboration. The system comprises a quantum transmission layer, an AI optimization layer and a block chain layer. The quantum transmission layer is based on a circular area sensor network topology, and comprises a central node, a quantum relay ring and a sensor node; the quantum transmission layer adopts ring topology, a center node is located at the center of a circle, and relay nodes are uniformly distributed according to polar coordinates; bidirectional quantum communication is realized between the sensor node and the central node through a quantum relay ring; the AI optimization layer comprises a channel state sensing module, a quantum graph neural network module, a QoS analysis module, a service priority mapping module, a dynamic scoring engine and a resource arbitration module; the block chain layer constructs a dynamic trust center to form an evaluation-evidence storage-control closed loop. According to the invention, the problems of limited transmission distance, high equipment cost, low key distribution efficiency and low resource utilization rate of quantum communication in a circular area scene are solved.

An illustrative data storage management system comprises a management database that stores administrative preferences and system configurations, as well as results and / or statistics of completed secondary storage operations, i.e., information needed by the system to protect customers' data and to track and recover the protected data, including secondary copies such as backup copies, archive copies, etc. The disclosed data storage management system is configured to protect its own system data subject to a very aggressive (short) Recovery Point Objective (RPO), by using an innovative infrastructure that enables the system's storage manager to fail over to any number of other failover destination storage managers, each one comprising a destination management database. An illustrative database granularly tracks whether each and every transaction log file has been successfully applied to each and every destination management database to synchronize with the source management database.

An enterprise engineering and configuration system includes a common configuration database and support services stored in and executed in a compute fabric of an enterprise. The configuration database and support services use and implement a common configuration data schema to support the configuration of hardware and software in the compute fabric and at multiple different sites or physical locations of the enterprise even when different control and automation systems are used at these different sites or physical locations. The configuration system enables implementing hardware or software configuration changes to various different sites or locations of an enterprise either centrally from a configuration device connected directly to the compute fabric of the enterprise or locally from any physical location or site of the enterprise, while maintaining a single integrated enterprise configuration database that stores configuration data for each of the multiple sites of the enterprise. This configuration system is flexible as it enables engineering and configuration changes to be made by users anywhere in the enterprise for any of the sites of the enterprise and across different sites of the enterprise.

The present disclosure provides a system and method for executing fused neural network layers using a graphics processing unit (GPU). The fused neural network layer combines multiple neural network operations into a single GPU kernel function, for efficient utilization of a GPU shared memory to reduce global memory transactions. The fused neural-network-layer system configures GPU thread blocks to iterate tiles in the GPU shared memory across portions of input tensors, and to perform a sequence of neural network layer operations using the tiles, before storing the results in an output tensor. The neural network layer operations can include element-wise, normalization, and pooling operations. The system also supports fused layers with nested traversals of input tensors, such as matrix multiplication, convolution, and attention mechanisms. The fused neural-network-layer system improves performance and reduces memory overhead compared to executing each layer as a separate GPU kernel, thereby enabling faster training and inference times.