59 results about "Hardware software" patented technology

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 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 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.

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 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 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 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.

A system and method for holistic network cybersecurity evaluation and risk rating that takes into account the operation of the entire target network environment comprising hardware, software, operating systems, and network connections. Not only are the hardware, software, operating system, and network evaluated separately for cybersecurity concerns, their interaction and operation as a whole are also evaluated and scored. The results of such analyses may be used, for example, by underwriters of cybersecurity insurance policies to determine policy terms and rates.

Embodiments of the invention are directed to systems, methods, and devices for providing dynamic applicability management with respect to a testing framework. Executable code segments can be provided in / with various test procedures that include instructions for testing hardware, software, capabilities, features, functionalities, or protocols of a computing device. Each code segment can encapsulate logic that, when executed, identifies whether a corresponding test procedure is applicable to a device given that device's configuration. By executing each code segment, a set of applicable test procedures can be identified. Identifiers or the test procedures may be provided to the device to be tested or a testing platform configured to conduct the test of that device. Transmitting the identifiers and / or procedures configures those devices to perform the test through simulating a legitimate data exchange.

The application relates to a motor train unit CTCS-2 level ATP dynamic test system, which comprises a system hardware and a system software. In the aspect of hardware, the system is composed of a main control microcomputer and an electronic box, the main control microcomputer is a PC or a notebook computer, and the main control microcomputer communicates with the electronic box through an RS422 bus; the electronic box is internally provided with function modules such as digital IO, speed signals, track signals and transponder signals, each module takes an ARM chip as a main processor, is supplemented with an FPGA and a DDS chip, can output high-precision frequency and digital signals, and the electronic box is connected with a measured train-mounted control equipment through a matching cable. In the aspect of software, a program realizes functions such as transponder message generation, encoding and decoding, analysis, line data display, test parameter setting, flow control and data recording. The system can dynamically test a CTCS-2 level ATP equipment, supports 200H, 200C and 300 series ATP hosts, can detect hardware, software control logic and transponder message data of the ATP hosts, and can also be used as an ATP operation training simulation equipment. The system generates transponder messages according to track data, simulates transponder module output signals, drives ATP dynamic operation to complete maintenance test. The system adopts modular design, is small in size, convenient to carry and maintain on site, is high in integrated circuit board design, combines ARM, CPLD / FPGA and other technologies, reduces equipment size and weight, reduces power consumption, and improves portability and functional expansibility.

The invention discloses a gearbox defect image segmentation method and device, and relates to the technical field of industrial automatic detection and deep learning. The method comprises the steps of preprocessing an image, constructing a coding-decoding network, embedding an FSM feature selection module, implementing HEM difficult sample mining, and adopting mixed loss optimization and staged training deployment. The FSM screens features through double-branch attention, the HEM screens difficult cases and emphasizes weight adjustment, and the mixed loss is fused with three types of loss optimization segmentation. The device adopts a hardware + software architecture, integrates multiple modules, and combines hardware acceleration and algorithm optimization to realize industrial-grade performance. The method solves the problems of missing detection of small defects and the like, improves the segmentation accuracy and reliability, can be effectively used for industrial automatic detection, and provides key support for reliable operation of the gearbox.

The application belongs to the technical field of cloud platform operation, and particularly relates to a method, system, terminal and storage medium for automatically adapting a computing node of a cloud platform, comprising automatically collecting hardware configuration information and software configuration information of a computing node to be adapted through a pre-stored multi-dimensional feature fingerprint identification method, and constructing a feature vector uniquely identifying the computing node; the application collects hardware data through a Redfish protocol and a system-level diagnosis command, combines software stack layered detection and software and hardware association mapping, constructs a layered feature vector containing a known feature layer, an unknown feature layer and a confidence weight, and realizes global unique identification of a multi-architecture and multi-vendor computing node. In combination with similarity comparison of an incremental fingerprint knowledge base, unknown hardware / software features can be accurately identified, the adaptation coverage range of a heterogeneous computing node is greatly improved, and the problem of insufficient adaptation of traditional methods to new hardware and small-population software environments is solved.

The application discloses a kind of intelligent equipment security threat collaborative analysis methods, from the TARA data set and HARA data set of intelligent equipment extract the training sample of large language model, fine-tune large language model, then collect information security threat intelligence data and functional safety threat intelligence data of intelligent equipment, information security knowledge graph and functional safety knowledge graph are constructed, then integrated into fusion knowledge graph, then according to the layered fusion security network of hardware software architecture of intelligent equipment, finally based on fusion knowledge graph and layered fusion security network analysis obtains asset and function system and corresponding keyword set, input fine-tuned large language model generates corresponding threat scene description text.The application builds fusion information security and functional safety threat intelligence knowledge graph, collaborative analysis of multi-source heterogeneous security information, realizes the automatic analysis of intelligent equipment security threat using large language model, improves the coverage and efficiency of threat analysis.

An LLM-based method for profiling chatbot users' technical proficiency and performing adaptation in the chatbot response, comprising the step of receiving encountered problem by the troubleshooting chatbot via a user prompt; using a profile inference LLM to obtain inferred profiles of chatbot users' technical proficiency regarding cybersecurity troubleshooting, by analyzing current prompt as entered by the user, from a data storage; the most recently updated user profile, which encapsulates the past user data; troubleshooting-oriented cybersecurity taxonomy consisting of proficiency domains and subdomains; a collection of inferred profiles of all users; hardware, software or networking-related data collected from the user's device; generating a vector of profile scores that quantify troubleshooting-oriented cybersecurity proficiency subdomains; updating the user's inferred profile by sending the inferred profile to the collection; replacing the older profile of the user by an updated profile; sending the inferred profile to a response adaptation LLM, along with the response generated by the chatbot; adapting the technical instructions, produced by the chatbot to the inferred user's profile; sending the profile-adapted response to the user, to follow the chatbot's instructions.

The invention relates to the technical field of data processing, and provides a multi-source sensor data fusion control system and method, and the system comprises an operation resource layer which is used for providing a system operation environment; the data access layer is used for being in butt joint with the at least two sensors through a hardware and software development kit so as to obtain original data transmitted by the at least two sensors; the infrastructure layer is used for constructing a communication link in the system, and the communication link comprises an instruction transmission channel and a data transmission channel which are mutually independent; the service application layer is used for issuing a control instruction to the data access layer through an instruction transmission channel to control sensor hardware and receiving original data through a data transmission channel; the service application layer is also used for performing space-time synchronization and fusion processing on the original data to obtain target data; and the presentation layer is used for receiving the target data through a network protocol and performing visual display.