75 results about "Hardware software" patented technology

The invention discloses a test environment availability intelligent monitoring method and system based on AI drive, and belongs to the technical field of test environment monitoring, in the invention, infrastructure indexes, application logs and network flow data are simultaneously acquired by the system through a multi-modal data fusion technology, and an omnibearing monitoring system covering hardware, software and a network layer is constructed. The AI model carries out deep analysis on time sequence data, and through combination with a space-time association algorithm, single index abnormity can be detected in real time, and a cross-node and cross-service composite fault mode can be identified. For example, through service call chain topology analysis, the system can accurately position a fault propagation path, and cascade problem diffusion is avoided. The closed-loop self-healing mechanism further converts the fault response from manual intervention into automatic processing, for example, automatic restarting of an abnormal container or adjustment of resource allocation, so that the fault repair time is greatly shortened, the environment availability reaches an extremely high level, and the strict requirement of the cloud native architecture for stability is met.

The invention discloses an intelligent system failure analysis method based on fault recognition, and relates to the technical field of intelligent system reliability analysis, and the analysis method comprises the specific steps: employing Modelica to construct a multi-physical domain digital twinborn model, combing historical data, and building a structured fault mode library; developing a fault injection algorithm to acquire data to form a standardized data set; preprocessing data to construct a causal link and a probability flow network; carding task scenes to construct a reliability evaluation model and training the reliability evaluation model; inputting actual parameters to trace faults, generating an optimization plan, and outputting an analysis report and a plan after verification; according to the method, the problem of insufficient fault correlation analysis caused by modeling scale splitting in a traditional method is solved by constructing a multi-physical domain digital twinborn model covering microcosmic, mesoscopic and macroscopic and establishing a structured fault mode library of a standardized feature description system containing three types of faults of hardware, software and environment interaction.

The invention discloses a system and a method for behavior analysis and anomaly detection of an industrial personal computer, and relates to the technical field of behavior analysis of the industrial personal computer. A structured behavior sequence matrix is generated by collecting hardware, software and network multi-dimensional time series data and using parameters such as a state transition coefficient and a noise variance for noise reduction processing, so that the data accuracy is improved; a real-time updated normal behavior reference is constructed based on dynamic time warping and similarity calculation, behavior deviation is accurately evaluated, dynamic changes of an operation mode of the industrial personal computer are adapted, an anomaly severity score is calculated through multi-dimensional deviation value weighting, differential processing of slight and serious anomalies is achieved in combination with a hierarchical response strategy, and the safety of the industrial personal computer is improved. According to the method, excessive response or lag is avoided, key abnormal time sequence fragments and potential root causes are quickly positioned by means of gradient weight visualization, the accuracy of abnormal detection and fault processing efficiency of the industrial personal computer are remarkably improved, and the requirement for high reliability of an industrial control scene is met.

The invention discloses an industrial control system security protection capability assessment method and system. The method comprises the following steps: acquiring key chip models, operating systems, monitoring software version information and service port information of n selected industrial control systems; the method comprises the following steps: acquiring a vulnerability list under a decision-making layer index and a corresponding threat value, constructing a fuzzy consistency judgment matrix from a target layer to a decision-making layer and from the decision-making layer to a scheme layer, performing fuzzy consistency verification on the constructed judgment matrix, calculating the weight of the decision-making layer index for the matrix passing the consistency verification, forming a weight matrix, and determining the vulnerability list according to the weight matrix. The evaluation results of the safety protection capability of the selected n industrial control systems are calculated through a fuzzy analytic hierarchy process, an analytic hierarchy model including hardware, software, protocols and other multi-dimensional indexes is constructed, vulnerability database retrieval and field test data are combined, a quantitative evaluation system is established through the fuzzy analytic hierarchy process, and the safety protection capability of the industrial control systems is evaluated. The method has the advantages of improving evaluation index systematicness, realizing multi-dimensional safety factor quantitative analysis and improving evaluation result objectivity.

The invention discloses an intelligent automatic labeling method and system based on multi-variety mixed production, and relates to the technical field of intelligent labeling, precise labeling is achieved through three core processes, the first step is that a hardware-software-data three-layer intelligent operation system is constructed, and posture and position analysis is conducted on SKU commodities transmitted to labeling equipment; and marking the to-be-labeled commodities meeting the conditions. 2, a to-be-labeled commodity is transmitted to a visual collection area, an algorithm reasoning mode is evaluated, and appearance characteristic parameters and dynamic parameters of a single-module reasoning commodity are accurately extracted; and step 3, analyzing and generating a label template, labeling position coordinates, labeling pressure and labeling speed according to the extracted parameters, and finally integrating into a labeling execution parameter set containing specific numerical values, constraint conditions and execution priorities, so as to meet the efficient and accurate labeling requirements of multi-variety mixed production.

The invention discloses a millimeter wave dual-polarization phased-array antenna beam forming method and device, and relates to the technical field of high-frequency communication, and the method comprises the following steps: obtaining a complex weight signal of each array element in an antenna array under a horizontal polarization channel and a vertical polarization channel, respectively carrying out amplitude response and phase response acquisition and calibration processing on the complex weight signal; performing dynamic extraction and modeling on amplitude errors and phase errors of each array element in different polarization channels; on the basis of error estimation, constructing a machine learning prediction module comprising a time sequence prediction model; performing joint estimation on a real-time error estimation result and a prediction error result; constructing a hardware-software collaborative calibration structure comprising a dynamic gain control module on the basis of the compensation weight; beam focusing of the target space area is realized; according to the invention, the hidden problems of beam offset, sidelobe lifting, gain loss and the like caused by inconsistency of polarization channels are solved.

This invention belongs to the field of intelligent agent large language model service technology, and discloses a chip computing system, device and application for intelligent agent large language model. Through the collaborative design of hardware architecture and software scheduling, it systematically solves the core technical challenges faced by intelligent agent large language model services. Specifically, it includes a hardware and software collaborative implementation scheme for resource partitioning, key-value cache management and runtime scheduling of pre-filling, decoding and tool call related workloads in a multi-chip encapsulation and inconsistent memory access environment.

The invention discloses an AES encryption and decryption hardware implementation method based on an RISCV vector encryption and decryption expansion architecture, and belongs to the technical field of data encryption, and the method comprises the steps that an RISCV instruction set carries out vector expansion on AES encryption and decryption, in the AES encryption process, an initial round corresponds to a vaesz.vs instruction, a middle round corresponds to a vaesem.[ vv, vs] instruction, a final round corresponds to a vaesef.[ vv, vs] instruction, in the AES decryption process, the initial round corresponds to the vaesz.vs instruction, and in the AES decryption process, the middle round corresponds to the vaesef.[ vv, vs] instruction. The middle round corresponds to a vaesdm. [vv, vs] instruction, and the final round corresponds to a vaesdf. [vv, vs] instruction, so that the area of a chip can be reduced, the cost is reduced, the flexibility, modularization and extensible architecture design of hardware and software are enhanced, different platforms from embedded computing to high-performance computing can be easily adapted, and a solid foundation is provided for evolution and customization of a future cryptographic algorithm; and the encryption processor architecture is promoted to develop towards a more efficient, more open and more customizable direction.

An information handling system may include a main physical storage resource and a bootstrap physical storage resource. The information handling system may be configured to: boot from a bootstrap operating system (OS) stored on the bootstrap physical storage resource; install, by the bootstrap OS, a main OS onto the main physical storage resource; expose the bootstrap physical storage resource as a drive that is accessible from the main OS; and in response to a change in hardware, software, or firmware of the information handling system, update the bootstrap OS from the main OS.

The application belongs to the technical field of solid-state remote power distribution device uniform type of aircraft electromechanical system, and particularly relates to a solid-state remote power distribution device uniform type design method and system. First, system requirements are collected, all power loads needing solid-state remote power distribution device secondary power distribution are divided according to locations, the rated current of all SSPC channels is obtained, and the rated current is upwardly compatible. The SSPC channels in the bus control mode and the SSPC channels in the override control mode are collectively classified as type 1. Each power output of the solid-state remote power distribution device is only bound with the power busbar input in the current location and is decoupled with the power supply on the aircraft. The uniform type is performed from four aspects of power distribution load area, SSPC channel current size, SSPC channel control mode and SSPC channel belonging busbar, so as to ensure that the hardware and software of the same type device are completely the same, the device is installed in different locations according to the recognition of the machine position, different software is executed, and the design cost, later stage support cost and management cost can be reduced.

The invention provides a Baijiu production method and system based on machine learning, and the method comprises the steps: constructing a multi-source heterogeneous data collaborative collection system, and collecting various data in a Baijiu production process; carrying out intelligent processing on the collected data; a hybrid model architecture and a transfer learning strategy are adopted, a dynamic adaptive model optimization mechanism is established, and the model performance is monitored in real time. Compared with the prior art, on the aspect of data, a multi-source heterogeneous acquisition system is constructed, and an advanced data management technology is adopted, so that the data quality and the value mining capability are improved; in the aspect of the model, the adaptability is enhanced by the hybrid architecture, the rapid customization of the model is realized, a dynamic adaptive optimization mechanism is established, and the continuous and efficient operation of the model is ensured; cost and risks are reduced in multiple dimensions such as hardware, software and a decision-making mechanism, and feasibility and reliability of technology application are enhanced.

The utility model relates to the technical field of control development boards, in particular to a C language teaching development board based on a microcontroller technology, and aims to closely combine C language teaching with hardware development so as to overcome the limitation of C language teaching in a traditional computer software environment. The development board comprises a power supply module, a microcontroller module, an LED module, a key module, a USB-UART module, a nixie tube module, a rotary encoder module, an EEPROM module and a temperature sensor module. Through the modules, students can learn how to use the C language to perform programming control on hardware in practice, so that understanding of a hardware-software interaction mechanism is deepened. In addition, the development board further supports teaching of communication protocols such as SPI and IIC, serial port communication between the development board and a computer is allowed, and program debugging and data exchange are facilitated. According to the utility model, not only is the teaching effect of C language improved, but also the opportunity of practical practice is provided for students, and the combination of theoretical knowledge and practical application is promoted.

Embodiments of the present disclosure relate to a unified framework for multi-modal similarity search. Disclosed herein is a technique for enhanced similarity search. In implementations, a search environment includes one or more computing hardware, software, and / or firmware components to support enhanced similarity search. The one or more components identify a modality of a similarity search relative to the query object. The component generates an embedding for the query object based on the modality and based on connections between the query object and neighboring nodes in the graph. The embedding of the query object provides a basis for the search of similar objects.

Computerized systems and methods are described for managing multi-tiered subscription-based models of technology products, including hardware, software, and cloud services. The system performs automated optimizing of subscription models and pricing using a Real-Time Data Mesh (RTDM) and Advanced Analytics and Machine Learning (AAML) Module. The system employs a Single Pane of Glass User Interface (SPoG UI) to enhance user interaction and subscription management. Automated processes facilitate dynamic adjustment of subscription terms, pricing, and configurations based on real-time data and analytics. API integrations for perform data exchange for comprehensive management of multi-tiered subscriptions within a unified ecosystem.

The application discloses a kind of modular configurable tooling detection methods, belong to tooling detection field, specifically include: module configuration step, automatic detection step, detection result processing step.Before detection, detection group leader configures detection hardware according to detection plan, software platform.When the unit to be detected is placed in the area to be detected, detection personnel start main control machine, and start automatic detection process according to the configuration parameters of detection scheme module, detection strategy module and detection alarm module after authentication.After detection, whether the detection data is entered into database according to the parameters configured by data analysis module is processed by main control software;Whether detection report is saved or printed;The application is adapted to the detection needs of the unit to be detected constantly upgrading iteration by the modularization and configurability of detection hardware and software platform, and the problem that error reproduction is difficult, error chain is deep and difficult to locate is solved by error tracing module.

The invention belongs to the technical field of cloud platform operation, and particularly relates to a method, a system, a terminal and a storage medium for a cloud platform to automatically adapt to a computing node, comprising the following steps: automatically collecting hardware configuration information and software configuration information of a to-be-adapted computing node through a pre-stored multi-dimensional feature fingerprint identification method; constructing a feature vector which uniquely identifies the computing node; according to the method, hardware data are acquired cooperatively through a Redfish protocol and a system-level diagnosis command, and layered feature vectors containing known feature layers, unknown feature layers and confidence weights are constructed in combination with software stack layered detection and software-hardware association mapping, so that global unique identification of multi-architecture and multi-manufacturer computing nodes is realized. Through matching with similarity comparison of an incremental fingerprint knowledge base, unknown hardware / software features can be accurately identified, the adaptive coverage range of heterogeneous computing nodes is greatly expanded, and the problem that a traditional method is insufficient in adaptation to novel hardware and small software environments is solved.

The invention discloses a cultural creative robot based on an AI large model and ROS2 and a control method. The cultural creative robot comprises a robot body, a hardware module arranged on the robot body and a software module built in the hardware module. The hardware module comprises a sensor module and an execution module which are connected with the main controller; the software module comprises a motion control unit, a voice function unit, an ROS2 unit and an interaction unit. The control method comprises steps S1 to S7. Through the design of the hardware, the software and the mechanical structure of the creative and creative robot, innovation of the robot in creative and creative and functional aspects is provided, and the emotional value and functional requirements of people are further met.

The invention relates to a large secondary active cockpit operation and maintenance method based on a power distribution automation system, and belongs to the field of automatic operation and maintenance of power systems. According to the method, a'hardware-software-terminal-service link 'full-dimension stereoscopic monitoring system is constructed. Specifically, an SNMPv3 protocol and edge calculation are adopted to collect equipment operation data in real time, and a core index calculation formula (such as a distribution network secondary active defect elimination rate and a morning operation application rate) is adopted to realize data quantitative analysis; a four-level alarm mechanism is constructed based on a severity-urgency matrix, and potential faults are pre-warned 72 hours in advance in combination with an LSTM prediction model; a defect closed-loop management and control process is innovated, master station type defect one-key defect elimination and terminal type defect cross-platform linkage are supported, and the defect disposal period is shortened by 60% or above. Meanwhile, the operation and maintenance state is visually presented through a system health index quantitative model (basic score 100-alarm score deduction), data can be seamlessly connected with a cloud platform, and intelligent operation and maintenance support is provided for a novel electric power system.

The invention discloses a damage early warning device capable of automatically scanning, detecting and evaluating space complex electromagnetic radiation. Through integration of a broadband antenna, a two-degree-of-freedom holder and a real-time safety evaluation alarm module, three core advantages of broadband domain high-precision measurement, dynamic scanning real-time evaluation and one-button portable operation are realized through hardware-software collaborative innovation, and national standard compliance detection requirements in complex electromagnetic environments such as 5G and Internet of Things are met.

The invention relates to the technical field of image data processing, solves the problems that traditional 3D display is low in image quality, needs to depend on peripherals such as glasses / helmets, is troublesome to use and operate, and lacks targeted image optimization for the application field, and discloses a naked eye 3D image quality optimization system which comprises a 3D display module serving as a system hardware carrier; the hardware sensing layer is modularly integrated on the 3D display module and comprises an environment sensing array used for collecting environment illumination, color temperature and screen surface reflectivity parameters in real time; the iris tracking unit outputs the interpupillary distance, the three-dimensional space coordinates and the visual angle vector of the viewer in real time; and the data processing layer comprises a multi-parameter processing engine, is connected with the environment sensing array and the iris tracking unit, and comprises a multi-mode color gamut conversion module, a self-adaptive gamma correction module and a dynamic backlight control module. The method has the advantages that the image quality is comprehensively improved through a hardware-software collaborative architecture, the pure naked eye 3D display image is optimized, and the cross-domain adaptability of pure naked eye 3D display is improved.

The invention discloses a hardware causal chain tracking and zero-contact self-healing system, which comprises a firmware-level tracking agent module, a simulation sandbox self-healing verification module, a knowledge graph construction module, a data fusion module and an early warning module, the firmware-level tracking agent module is deployed in BMC firmware and used for capturing hardware and software causal chain information, and the output end of the firmware-level tracking agent module is electrically connected with the input end of the knowledge graph construction module; the knowledge graph construction module constructs an abnormal mode knowledge graph based on a domestic operating system, and the output end of the knowledge graph construction module is electrically connected with the input end of the data fusion module. According to the method, a fault source is accurately positioned through hardware-level tracking and a knowledge graph, so that the diagnosis accuracy is improved; and automatic generation and pre-verification of the repair strategy are realized, the repair risk is reduced, the success rate is improved, and stable operation of the domestic server is guaranteed.

The invention discloses a collaborative analysis method for security threats of intelligent equipment, which comprises the following steps of: extracting a training sample of a large language model from a TARA data set and an HARA data set of the intelligent equipment, finely adjusting the large language model, and then collecting information security threat intelligence data and functional security threat intelligence data of the intelligent equipment; the method comprises the following steps: constructing an information security knowledge graph and a function security knowledge graph, then integrating into a fusion knowledge graph, constructing a hierarchical fusion security network according to a hardware software architecture of intelligent equipment, and finally analyzing based on the fusion knowledge graph and the hierarchical fusion security network to obtain assets, function systems and corresponding keyword sets. And inputting the fine-tuned large language model to generate a corresponding threat scene description text. According to the method, the knowledge graph fusing information security and functional security threat intelligence is constructed, the multi-source heterogeneous security information is analyzed in a collaborative manner, the security threat of the intelligent equipment is automatically analyzed by using the large language model, and the coverage degree and efficiency of threat analysis are improved.

The application discloses a computing power optimization method and system in power data maintenance, and relates to the technical field of data center and power grid cooperation, which comprises the following steps: collecting and standardizing the hardware, software, energy consumption and power supply data of the computing power center through a unified interface protocol, and forming a data stream after security processing; constructing a comprehensive resource model of the integrated computing power supply and power demand in the region based on the data stream; then, establishing a digital twin model of the coupling of the computing power center and the power system, and realizing real-time mapping of the physical entity and the virtual model; generating a dynamic twin body supporting multi-dimensional visual display through synchronous real-time monitoring data; simulating different computing power scheduling strategies based on the twin body, and automatically generating a decision scheme of the cooperation optimization of the computing power resource and the power supply. The application realizes joint modeling and cooperative simulation optimization of the computing power and the power system.

A network includes a platform provider having a centralized operating environment including a combination of hardware, software, and a communication device configured to receive information from a plurality of enterprise networks each configured to independently communicate information to the platform provider. The information includes customer information, device information, requested enrollment or application information, requested transaction information, completed enrollment or application information, or completed transaction information, or a combination thereof. The platform provider is configured to validate and record the information in a secure ledger. The platform provider is further configured to, based on the information, identify incentives, advertisements, or other communications to provide a customer, deliver incentives, advertisements, or other communications to a customer, calculate a fee owed by one enterprise network to one of the platform provider, another enterprise network, or a customer, or assess a probability that a requested consumer, device, enrollment, application, or transaction is fraudulent.

This application discloses a method, apparatus, and device for security authentication, relating to the field of security protection technology. Before establishing a communication connection between the main control unit and the upper-layer software, the main control unit verifies the legitimacy of the upper-layer software's identity based on a software identity certificate. The upper-layer software verifies the legitimacy of the hardware circuit's identity based on a hardware identity certificate, and sends a random challenge value to the main control unit. The main control unit generates corresponding real-time response information based on the PUF circuit. Due to the physical non-cloning characteristic of the PUF circuit, cloned or simulated counterfeit hardware circuits cannot reproduce the correct real-time response information. Therefore, the upper-layer software can verify the authenticity of the hardware circuit's identity based on the real-time response information, preventing the hardware circuit from being a counterfeit product. Since the upper-layer software and hardware circuit are both legitimate, and the hardware circuit is authentic, a communication connection is established between the upper-layer software and the main control unit only when their identities are legitimate, preventing the access of unauthorized hardware / software.

The invention relates to the technical field of server fault diagnosis, belongs to a software and hardware information monitoring and fault diagnosis method applied to an AI server, provides a topological structure applied to software and hardware state monitoring of the AI server on one hand, and provides a software and hardware information monitoring and fault diagnosis method applied to the AI server on the other hand. According to the technical scheme, hardware key information of main board cards (a mainboard, an exchange board, a GPU board and the like) in the server is collected, and the monitoring function of hardware signals is achieved; main running state data of system software are collected, and the function of monitoring the running state of server software is achieved; a trained AI large model is embedded in the fault diagnosis module, so that the functions of quickly positioning hardware and software faults and generating fault processing suggestions are realized.

The invention discloses a platform door intelligent simulation training system based on digital twinning and AI, and belongs to the technical field of rail transit training. The invention discloses a platform door intelligent simulation training system based on digital twinning and AI. The platform door intelligent simulation training system comprises a system architecture module, a hardware composition module, a software composition module and a core function module. The platform door simulation training system solves the problems that an existing platform door training mode depends on physical equipment and is single in function, complex fault scenes are difficult to simulate, and intelligent teaching assistance is lacked, high-precision control is achieved by constructing a hardware and software collaborative simulation training system and adopting a three-layer distributed control framework, and the platform door simulation training system is high in practicability. A digital twinning technology is combined to restore a real platform door structure and an operation state in a 1: 1 manner, AI voice interaction and a professional knowledge base are integrated, fault simulation, principle teaching, practical operation drilling and intelligent question and answer are supported, the immersion, interactivity and teaching efficiency of training are effectively improved, and the urgent demand of modern rail transit for professional and intelligent training is met.

The application discloses a kind of high reliability multiple redundancy virtualization methods based on microkernel, belongs to virtualization reliability technical field, to solve the problem that redundant system needs additional hardware, software and computing resources to support backup function, which needs to consume a large amount of system resources, which will have negative impact on the performance and resource utilization of the whole system, in the application, multiple redundancy technology is used to provide backup virtual machine for the main virtual machine, and the backup virtual machine seamlessly continues to provide services when the main virtual machine cannot work normally, improving the reliability of the system, and the backup virtual machine uses a microkernel operating system, which greatly reduces resource occupation according to the characteristics and functions of the services in the main server.

The utility model relates to an air-cooling heat dissipation circuit of a switching power supply. The air-cooling heat dissipation circuit comprises at least one fan with a PWM speed regulation function. At least one heat-sensitive sensor; the single chip microcomputer U1E is used for controlling the rotating speed of the fan according to the detected temperature; a divider resistor RE1; the working voltage of the single-chip microcomputer U1E is connected with one end of the heat-sensitive sensor, the other end of the RET is connected to one end of the divider resistor RE1 and then connected to the signal input end of the single-chip microcomputer U1E, and the other end of the divider resistor RE1 is grounded; the PWM signal access port of the fan is connected to the PWM signal output end of the single-chip microcomputer U1E, and the single-chip microcomputer controls the rotating speed of the fan through PWM signals. According to the invention, the switching power supply can be subjected to intelligent air-cooled heat dissipation by adopting a hardware and software hybrid control mode through the air-cooled heat dissipation circuit of the switching power supply in combination with the heat dissipation method. The rotating speed of the cooling fan is adjusted according to the change of the working heat of the power supply. The rotating speed noise is controlled, and the service life of the fan is prolonged. And the power supply works more reliably.