231results about How to "Simplify the deployment process" patented technology

The invention belongs to the technical field of image recognition, and relates to a small sample learning method for task-adaptive association learning, which comprises the following steps of: S1, assisting the original prompt by using a specific prompt word of a task; s2, enhancing the discrimination of the training features by using comparative learning; s3, using diversified image enhancement means to enhance the contrast of the image; according to the method, the generalization ability of the model is enhanced through rich description of a natural language, so that the CLIP can be more efficient even if the CLIP faces the unmet category or complex concept. Therefore, the method not only reduces the dependence on a large-scale annotation data set, but also improves the learning ability of the model under the condition of small samples and even zero samples, enhances the adaptability and generalization ability of the model to a new environment, greatly simplifies the deployment process of the model, and improves the deployment efficiency of the model. The method becomes a powerful tool for solving a series of challenges in image recognition and description tasks.

The invention provides a network slice management method and a storage medium, and relates to the technical field of communication. The method is applied to a network management server and is configured to comprise a data connection configuration list, and the data connection configuration list comprises a mapping relation among an equipment address of industrial equipment, a wireless resource configuration parameter set in a base station and a network slice identifier. Acquiring a user permanent identifier of a target terminal corresponding to the target industrial equipment; and sending a wireless sub-slice configuration request to a base station according to the user permanent identifier of the target terminal, so that the base station attaches a protocol data unit PDU session of an Ethernet type established by the target terminal to a target wireless sub-slice corresponding to the target industrial equipment according to the wireless sub-slice configuration request, the establishment of the wireless sub-slices can be completed in the base station only by providing the wireless sub-slice configuration information in the network management server by an industrial user, and the method has the characteristic of simple configuration.

The invention discloses a cloud platform rapid deployment system and method. The system comprises a Docker, a container arrangement tool, a database service, a cloud platform application, a monitoring and management tool, a network infrastructure and a security component. The Docker is responsible for managing the complete life cycle of the container and providing a virtualization environment; the container arrangement tool is used for managing and arranging a Docker container; the database service is used for storing information in the cloud platform and carrying out communication through the network service of the Docker; the cloud platform application is a set of service logic and functions deployed in a Docker container; the monitoring and management tool is used for monitoring a running state and managing log information; the network infrastructure is used for ensuring network interconnection between the servers and supporting network communication of the Docker container; and the security component is used for protecting the cloud platform from external attacks and internal threats. According to the method, the deployment process can be simplified, the deployment time is shortened, manual intervention is reduced, the deployment efficiency is improved, resources are optimized, and the operation cost is reduced.

The invention provides a multi-camera hard synchronization method based on a microcontroller, and relates to the technical field of camera synchronization, and the method comprises the steps: enabling a plurality of cameras to be sequentially connected through a synchronization interface, and enabling each camera to be connected with a switch; defining a synchronization source; when each pixel clock runs, the microcontroller of each camera is taken as a core, the microcontroller detects whether a synchronization pulse exists or not, if yes, synchronization is carried out, and when an asynchronous phenomenon occurs, the next camera can receive a synchronization signal sync in of the previous camera, and the microcontroller can judge whether the current synchronization time point is a proper synchronization time point or not; if the synchronization time point is not suitable, waiting for the current camera to capture the current frame and waiting for the next synchronization time point to perform synchronization, if the camera does not receive the synchronization signal sync in of the previous camera, performing internal synchronization after capturing one frame by the microcontroller, and after the internal synchronization is completed, retaining the synchronization state information of this time; and checking in the next execution period.

The invention discloses a Selenium automatic script generation method and system based on an AI algorithm, and relates to the technical field of script generation. Preliminary setting of a neural network model is performed based on a target task, and a trained automatic script and a loss function are used to optimize neural network model parameters, so that the accuracy of the neural network model is improved; and applying the pre-trained neural network model to a new task by using a transfer learning technology, representing a performance index of the current neural network model through a state space, representing an adjustable parameter or structure of the neural network model through an action space, and performing reward or punishment according to the expression of the neural network model through a positive and negative feedback mechanism. And enabling the neural network model to output a final automation script. The script is automatically generated through the AIGC technology, the requirement for manual coding is reduced, the script generation efficiency is greatly improved, the pre-trained neural network model can quickly adapt to a new task, the workload of training from zero is reduced, and the task change coping capacity is improved.

The invention belongs to the technical field of cloud computing, and discloses a lightweight multi-domain hyper-fusion platform construction method compatible with heterogeneous hardware resources, which adopts a lightweight hyper-fusion platform architecture compatible with the heterogeneous hardware resources, converts physical resources into virtual resources on a virtual machine based on a KVM (Kernel-based Virtual Machine), shields the difference of underlying hardware, and improves the performance of the platform. According to the method, heterogeneous storage resources are integrated based on Ceph, and storage devices of different manufacturers are integrated into a unified storage pool through a distributed storage technology without being limited by types of bottom hardware devices. Through the SDN technology, the OpenStack network service can decouple a network control plane and hardware, and unified management of different network devices is realized. Through a virtualization technology and an automatic management tool, a simplified elastic expansion solution is provided, and changes of resource demands are easily coped with.

The invention provides an exercise evaluation method and device, electronic equipment and a storage medium, and belongs to the technical field of exercise evaluation.The method comprises the steps that in the preparation stage, a preset human shape detection model is called to detect an input image frame so as to position a human body frame, and a tester located in a take-off area is determined according to the human body frame; in the take-off stage, a preset human body posture estimation model and a preset key frame positioning model are called, and whether the tester starts to take off or not is judged, so that a take-off frame is determined; in the flying stage and the landing stage, based on the take-off frame, the human body posture estimation model and the key frame positioning model are called, whether the tester starts to land or not is judged so as to determine a landing frame, the landing point of the tester is determined according to the landing frame, and the standing long jump score is calculated. Through automatic and intelligent technical means, the problems existing in traditional standing long jump evaluation are effectively solved, and a more accurate, objective and convenient evaluation scheme is provided.

The invention provides a system and a method for real-time development, debugging and deployment of a server-free application, which are used for solving the problems of separation of a local environment and a cloud environment, difficulty in debugging and the like in the development process of the server-free application. The system comprises a local integrated development environment, a cloud server-free execution environment, a real-time synchronization module, a remote debugging module, a connection agent module and a deployment module. Wherein the real-time synchronization module realizes real-time increment synchronization of a local code and a cloud code through an increment synchronization algorithm, a Hash index algorithm and an encrypted transmission protocol; the remote debugging module supports debugging operations such as breakpoint debugging, variable checking and single-step execution on the cloud application in the local IDE; the connection agent module is used for establishing two-way communication between the local IDE and the cloud instance; the deployment module can execute the construction and deployment of the application at the cloud, and the deployment process is simplified. According to the invention, seamless integration of a local development environment and a cloud operation environment is realized, the debugging limitation of a server-free architecture is overcome, and the development efficiency and the application quality are improved.

The present invention relates to the technical field of information system integration, and in particular to an ERP system launch method. The method comprises the following steps: obtaining ERP demand data; performing ERP related function module analysis according to the ERP demand data to generate ERP related function modules; performing ERP system architecture analysis based on the ERP related function modules to establish the ERP system architecture; obtaining historical enterprise source data; performing historical enterprise decision feature analysis based on the historical enterprise source data to generate historical enterprise decision feature data; performing intelligent business practice engine design based on the historical enterprise decision feature data to generate an intelligent business practice engine; performing intelligent business practice function configuration processing of the system architecture on the ERP system architecture based on the intelligent business practice engine to generate an ERP system, and transmitting the ERP system to a cloud server to execute the ERP system launch operation. The present invention realizes intelligent business management of the ERP system.

The invention discloses a chicken epidemic disease detection method and device based on audio data enhancement and feature fusion. The method comprises the steps that sound data of a chicken flock is collected and preprocessed; performing data enhancement on the preprocessed sound data to obtain a chicken flock audio training sample; frequency spectrum features and original audio features are extracted from the chicken flock audio training samples; splicing all the spectrum feature maps to obtain a spliced spectrum feature map; inputting the extracted original audio features into a network formed by combining two front-end acoustic models and a pre-training model to obtain a first semantic feature map and a second semantic feature map; fusing all the features to obtain a fused feature map; and inputting the fused feature map into a preset lightweight multilayer perceptron, and outputting a chicken epidemic disease detection result. By introducing data enhancement and feature fusion technologies, the limitation of a single feature extraction means is overcome, and the accuracy and robustness of sound signal processing are improved, so that the chicken epidemic disease is detected more effectively.

The invention discloses a software deployment method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: acquiring basic information of to-be-deployed software; according to the basic information, generating a code library interaction instruction, so that the software deployment system uses the code library interaction instruction to obtain the to-be-deployed software, and the software deployment system compiles the to-be-deployed software to obtain a corresponding mirror image file; and obtaining resource configuration information of the to-be-deployed software, and determining a deployed target container according to the resource configuration information, so that the software deployment system generates a deployment arrangement process for deploying the to-be-deployed software in the target container and executes the deployment arrangement process based on the mirror image file. According to the implementation mode, full-automatic software deployment is realized, the problem that manual intervention is needed in existing software deployment is solved based on the capability of generating the code library interaction instruction and automatically determining the target container, the deployment efficiency is improved, the deployment process is simplified, and labor force is liberated.

The invention discloses a data service method and system based on a domestic autonomous controllable environment, and relates to the technical field of enterprise data management. The method comprises the following steps: converging data from different service systems based on plug-in architecture design; through analysis and processing of the gathered source data, standardized management of the data is realized; performing index processing based on the gathered source data in combination with service requirements to obtain an index library; and packaging and publishing the treated standard data as standardized API interface data, and providing a data sharing service in combination with the index library. According to the invention, the distance from data to business can be shortened, the diversity requirements of business are met, a user is helped to conveniently and fully use the data, and the data generates business value, so that the problem of enterprise data islands in a domestic autonomous controllable environment is solved.

The invention discloses an automatic high-precision assembly system and method based on visual feedback, belongs to the technical field of automatic assembly, and solves the problem that an existing scheme is insufficient in the aspects of automatic integration and actual usability. Comprising an embedded control unit, an XYZ Cartesian sliding table, a limiting sensor, a visual sensor, a visual mark and an upper computer processing unit, the embedded control unit is connected with the upper computer processing unit, and the embedded control unit is used for receiving a control instruction and feeding back state information. The embedded control unit is connected with a motor driver of the XYZ Cartesian sliding table and used for sending a motion control signal, and the embedded control unit is connected with the limiting sensor and used for receiving a switch signal. Working space boundary recognition and automatic calibration of the camera-robot hand-eye relation are achieved, the configuration and deployment process of a visual guidance system on the XYZ sliding table is greatly simplified, the requirement for professional skills of operators is lowered, and deployment efficiency is improved.

The invention relates to the field of intelligent monitoring, and discloses a machine room wild animal intelligent defense system based on a millimeter wave radar, which comprises a signal capture module, a signal processing module, a feature extraction module, a classification tracking module and an alarm linkage module, the signal capturing module collects target reflection signals through a millimeter wave radar, the signal processing module carries out multi-target separation and interference suppression on the signals, the feature extraction module extracts time-frequency characteristics and motion track characteristics of targets, and the classification tracking module classifies the targets and tracks the motion states of the targets in real time. And the alarm linkage module evaluates the threat level according to the classification result and triggers corresponding defense measures. The system can accurately identify and track targets, timely respond and execute defense actions, has the advantages of high precision, multi-target monitoring, real-time dynamic tracking, intelligent defense and the like, and can effectively guarantee safe operation of machine room equipment.

The invention provides a multi-reflection superposition enhanced microwave displacement measurement method and system, and the method comprises the steps: S1, constructing a microwave multi-reflection propagation path, enabling a microwave radar to transmit electromagnetic waves to the microwave multi-reflection propagation path as a transmission signal, and receiving a corresponding echo signal; s2, extracting length change information of a microwave multi-reflection propagation path according to the echo signal; s3, establishing a linear superposition relation model between the total length of the microwave propagation path and respective displacements of W reflection surfaces in the microwave multi-reflection propagation path; w2; and S4, based on the linear superposition relation model, displacement information of the corresponding reflection surface is obtained and output. According to the invention, a larger phase variation can be obtained under the condition of small displacement or weak vibration, so that the measurement sensitivity is improved and the signal-to-noise ratio is improved.

The invention provides a text retrieval enhancement generation method and device, equipment and a readable storage medium, and the method comprises the steps: obtaining document original data, and storing the document original data to a first database; performing text vectorization processing on the document original data to obtain document vector data, and storing the document vector data to a second database; retrieving a plurality of document related data from the first database and the second database based on question information input by a user; and generating a target keyword based on the related data of each document, and analyzing the target keyword through a large model to obtain a reply text for the question information. By adopting the method, the normal generation of the reply text is ensured, and the reliability, effectiveness and accuracy of the generation of the reply text are ensured.

The invention relates to a model deployment method, a fault diagnosis method, a system, equipment and a medium. The method comprises the following steps: acquiring historical working data of the intelligent cabinet; preprocessing the historical working data; providing an initial fault diagnosis model; training the initial fault diagnosis model based on the training set data; performing verification optimization on the trained initial fault diagnosis model based on verification set data; testing the verified and optimized initial fault diagnosis model based on the test set data to obtain a to-be-optimized fault diagnosis model; performing compression optimization on the to-be-optimized fault diagnosis model to obtain a fault diagnosis model; configuring a cloud server; and deploying the fault diagnosis model in a cloud server. The training and deployment process of the fault diagnosis model can be greatly simplified, manual intervention is reduced, and when the deployed fault diagnosis model is used for fault diagnosis of the intelligent cabinet, the accuracy and timeliness of fault diagnosis can be improved, and the operation and maintenance efficiency of the intelligent cabinet is improved.

The invention discloses an installation method of an operating system, a cluster system, a server and a medium, and relates to the technical field of computers. And determining a server type and a target operating system corresponding to each client according to the identification information corresponding to the target demand, and configuring a startup mirror image corresponding to each server type. The server model is automatically identified through the identification information, so that the target operating systems of different platforms can be installed subsequently, the operating systems of specific types of platforms can be installed, and the operating systems of different platforms meeting target requirements can be installed subsequently in batches. According to the embodiment of the invention, each update object of the starting environment corresponding to the target operating system is packaged in a modular manner, and the whole operating system does not need to be manually deleted for updating during subsequent update iteration, so that the starting environment to be updated is determined in the modular manner; and running the to-be-updated starting environment to perform installation processing on the starting mirror image by using the packaged module information, thereby realizing version updating iteration operation, and improving the deployment efficiency of batch deployment and installation of the operating systems by the server.

The invention discloses an intelligent load balancing method based on a zero-sample hybrid expert model, and the method comprises the steps: creating a task spectrum mapping relation through zero-sample learning, generating a virtual label, refining the demands of a new task into a resource demand feature spectrum through multi-dimensional feature cross projection, and carrying out the optimization of the resource demand feature spectrum. Predicting a multi-dimensional resource demand of the new load balancing task; establishing a multi-view hybrid expert dynamic integration mechanism, configuring a multi-view hybrid collaborative expert for a task, applying a plurality of expert model combinations to different demand dimensions, creating a virtual image sample of a new task, simulating a resource demand and a load effect thereof in a virtual environment, and generating an initial resource allocation scheme; for dynamic load fluctuation, task cells are distributed to nodes with sufficient resources; according to the method, the robustness and efficiency of the system are improved, the implementation process is simplified, and the method has wide application prospects and practical value.

The invention provides a large-array intelligent metasurface codebook optimization and switching method and device, and belongs to the technical field of wireless communication. Aiming at the problem of low efficiency of a traditional codebook selection method in a high-speed moving scene of a user, the invention provides an intelligent optimization method and device, which can efficiently position optimal codebook configuration in a codebook library through a quick search mechanism. According to the method, in combination with signal-to-noise ratio feedback driving, multiple groups of configurations in a codebook library are tested step by step, and a gain optimization module is combined, so that the optimal beam forming effect is achieved, and the method does not need to depend on accurate position information of a user. Besides, a clockwise adjacent codebook test strategy is introduced, the redundancy calculation and traversal time is shortened, and it is ensured that in the user moving process, codebooks can be rapidly switched, and stable communication quality is kept. The algorithm has the advantages of real-time response and complexity reduction, is suitable for 5G and other high-speed mobile communication scenes, and effectively improves the signal transmission efficiency and the communication reliability.

The invention provides a method and device for automatically generating script codes, electronic equipment and a medium. The method comprises the steps that a source file containing to-be-processed data is obtained; receiving a mapping relation from the source file to a target file input by a user, wherein the mapping relation is used for defining a conversion rule and a path of source file data; and based on the mapping relationship, generating a corresponding SQL script code through a preset algorithm. And the time of manually writing the SQL script by a developer is shortened, especially when a repetitive task needing a large number of similar codes is processed. Through an automatic process, a standardized code can be quickly generated, manpower and material resources are greatly saved, and a development team can concentrate on higher-level innovation and optimization work. In addition, the automatically generated SQL script follows a consistent structure and style, which helps to improve the readability and maintainability of codes. The unified code standard reduces the complexity of maintenance work, and reduces errors caused by inconsistent styles or disordered structures, thereby improving the stability and development efficiency of the whole project.

The invention discloses an application program deployment method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: acquiring a dependent toolkit of an application program during running, and distributing a classification attribute corresponding to the dependent toolkit for the application program; generating dependency information of the application program based on the dependency toolkit, determining a compiling mode of the application program according to the classification attribute, compiling the application program according to the compiling mode, and generating a compiling package of the application program; and adjusting a deployment environment of the application program according to the dependency information, and deploying a compiling package of the application program in the adjusted deployment environment. According to the embodiment, standard and normalized application program deployment is realized, the influence of factors such as a programming language and an operation framework of the application program on deployment online is shielded, the deployment process is simplified, and the deployment efficiency is improved.

The invention discloses an automatic advertisement screenshot and container automatic expansion method and system in a virtual desktop environment. A virtual display capable of exporting a DMA-BUF is created by deploying a Virtual Display Driver in a kernel of a host machine, and after Chrome is driven by Puppeteer to complete hardware acceleration rendering in a container, zero-copy desktop-level screenshot is carried out on a shared memory frame buffer by utilizing desktop-script-native; and meanwhile, a Kubernetes CRD unified database task and a declarative API are adopted, a Redis Stream second-level index and a predictive HPA algorithm are combined to realize advanced delta t capacity expansion of Pod, and the P99 queuing delay is ensured to be less than 2s. According to the method, single-node concurrency is improved by 3.2 times without extra hardware cost, CPU occupation is reduced by 45%, WebGL / Flash advertisement fidelity is 100%, and the method is suitable for cloud advertisement verification, brand security and programmed creative monitoring scenes.

The invention discloses a method and a system for calling local functions among different Web applications under the same Tomcat instance, and relates to the technical field of computer software, a plurality of Web applications are deployed under the same Tomcat instance, and the applications needing to provide local function calling are set to be started preferentially; in the Web application which is started preferentially, a new class is generated, and an object instance is created; the new class and the object instance are loaded to a system class loader, so that other Web applications can globally access the new class and the object instance; when other Web applications in the Tomcat are started, obtaining an object instance from the system class loader, and distributing the object instance to a target instance variable in the proxy class; other Web applications call the object instance through the proxy class; and the proxy class returns the calling result of the target instance variable, so that network delay and performance overhead caused by traditional remote procedure calling are avoided, and the calling efficiency between applications is greatly improved.

The invention provides a device, a method and equipment for small target image detection and classification. The device for small target image detection and classification comprises an image input module, a feature extraction module and a detection or classification module. The image input module is used for processing an acquired image and inputting the image to the feature extraction module; the feature extraction module is used for extracting the features of the image through a feature extraction model to obtain the coordinate information of the small target; and the detection or classification module is used for cutting out local feature blocks on the feature map according to the coordinate information of the small targets and inputting the local feature blocks into a decision head to obtain the feature information of all the small targets in the image. The method can avoid the repeated calculation of the same features, thereby reducing the calculation amount, and improving the utilization rate of calculation resources.

The invention discloses an event alarm reporting processing method for large-scale ONVIF equipment access, and belongs to the field of security and protection video monitoring. Registering channel static information to the data sharing center after the ONVIF equipment is online; the ONVIF equipment access service sends an event subscription request carrying an event receiving service unified address and an equipment identification subscription code to the equipment; after the equipment triggers the event, stateless connection is initiated to the uniform address, and the event is dynamically forwarded to any event receiving service instance by the platform load balancer; and the event receiving service analyzes the event to obtain the channel identifier, queries the data sharing center to obtain complete channel information, and reports the information to the platform alarm center after integration. According to the invention, decoupling of event subscription and processing is realized, and through stateless service, unified port and centralized data management, the problems of poor reliability, many exposed ports, uneven load and complex capacity expansion under large-scale access are solved.

The present invention discloses an intelligent load balancing method based on a zero-sample hybrid expert model, comprising the steps of: creating a task spectrum mapping relationship through zero-sample learning, generating virtual labels, refining the requirements of new tasks into resource requirement feature spectra through multi-dimensional feature cross-projection, and predicting the multi-dimensional resource requirements of new load balancing tasks; establishing a multi-perspective hybrid expert dynamic integration mechanism, configuring multi-perspective hybrid collaborative experts for tasks, applying a combination of several expert models to different demand dimensions, creating virtual image samples of new tasks, simulating resource requirements and their load effects in a virtual environment, and generating an initial resource allocation plan; in the face of dynamic load fluctuations, distributing task cells to nodes with sufficient resources; the method improves the robustness and efficiency of the system, simplifies the implementation process, and has broad application prospects and practical value.

The invention discloses a dual-mode carrier communication system and method based on a security encryption ad hoc network, and provides a solution capable of automatically constructing and maintaining network connection by combining an ad hoc network technology, a carrier communication technology, a security encryption technology and a standardized protocol. The system not only supports the plug and play of equipment and simplifies the network deployment and management, but also improves the data transmission efficiency and the capability of supporting large-scale terminal equipment by adopting the orthogonal frequency division multiplexing modulation technology and the IPv6 protocol; a built-in security chip and a domestic cryptographic algorithm are used for realizing strong and effective bidirectional identity authentication and data encryption, so that the security and the reliability of communication are ensured; the application of deep learning routing further optimizes the network performance, dynamically adjusts the optimal path according to the real-time network condition, and enhances the flexibility and robustness of the system. Generally speaking, the system significantly improves the stability and safety of broadband power line carrier communication, and provides solid technical support for smart power grid application scenarios.

The invention discloses a hot-rolled plate structure toughness prediction method and system combined with an impact energy change curve, and belongs to the technical field of metal material structure performance evaluation.The method comprises the steps that an impact test is conducted on a hot-rolled plate sample, and an impact force-displacement curve and an energy absorption-time curve are collected in real time; preprocessing the impact force-displacement curve and the energy absorption-time curve, and extracting characteristic parameters; acquiring hardness distribution data of the hot-rolled plate sample, acquiring hardness gradient data by using the hardness distribution data, and taking the hardness gradient data as a correction factor of the curve characteristics; constructing a structure toughness prediction model based on the characteristic parameters and the correction factors, and predicting the toughness grade and the structure state of the hot-rolled plate; and outputting the toughness grade and the structure state of the hot-rolled plate. According to the method, the limitation that traditional metallographic detection consumes too long time and an impact test only provides a single value is solved, double evaluation results can be obtained within 30 seconds after the impact test, and the method is suitable for rapid online quality monitoring and process adjustment of hot rolling production.

The invention relates to a compiling method based on zero codes, which belongs to the field of system development and comprises the following steps that: (1) a user selects a compiling item as required; (2) performing program compiling based on the selected compiling project, wherein an executable program file required by the program compiling is provided through a project compiling warehouse; and (3) program burning is carried out, and a user downloads the program. The method has the advantages that usability is achieved, a user can select compiling items without compiling codes, the programming threshold is greatly lowered, and non-technical users can also participate in the program compiling process. And rapid development: through a preset compiling project, a user can rapidly start a program compiling process, and the starting stage of a software development cycle is accelerated. The compiling process is simplified into several basic steps, complexity in traditional programming and compiling is reduced, and the whole development process is clearer and easier to manage.