20 results about "Data independence" patented technology

The invention relates to the technical field of electrical variable measurement, solves the technical problems that in the prior art, path planning is lack of dynamics, mechanical wear is caused by frequent acceleration and deceleration of a probe, and key features are easy to omit in a complex multi-path environment, and particularly relates to a method and system for coping with an antenna performance test and a storage medium. The method comprises the steps of collecting target test frequency point data and standard signal modulation data of a target antenna, and generating synchronous excitation signal data through multi-dimensional signal processing and synchronous adjustment. The sampling efficiency and the data quality are remarkably improved through multi-stage collaborative optimization, a sampling domain is primarily selected in combination with a theoretical directional diagram and interference distribution, and the synchronous excitation signal data are generated. The method has the advantages that invalid area measurement is avoided, learning is reinforced to dynamically plan a path to reduce mechanical loss, redundancy is reduced by refining point locations, data independence and coverage are ensured by weighted evaluation, adaptability in a dynamic channel environment is higher, and the method is particularly suitable for millimeter wave and other high-dimensional antenna test scenes.

The invention provides an unmanned aerial vehicle-assisted Internet of Things data acquisition method for multi-mechanism overlapping deployment, and the method comprises the steps: enabling an unmanned aerial vehicle of each mechanism to collect a local observation state, and obtaining an output action after the local observation state is converged into a global observation state of a current time step; after the unmanned aerial vehicles execute actions, local observation states are collected and converged to obtain the global observation state of the next step, and the award of the current time step is calculated; wherein a reward function is designed by taking minimization of the average AoI of all the Internet of Things devices as a training target; an experience tuple composed of the global observation state of the current time step, the joint action, the reward and the global observation state of the next step is stored in an experience playback pool, training data are taken out from the experience playback pool to complete model training based on MADDPG, and then the trained Actor network is used for performing unmanned aerial vehicle path planning deployment of data acquisition. According to the invention, the problem that data acquisition between mechanisms needs to maintain data independence and also needs to cooperate with each other to reduce the average information age of the system is solved.

The invention provides an object storage volume management method, device and equipment and a readable storage medium, and the method comprises the steps: responding to a write-in request associated with a clone volume, and obtaining a data state of a data object in the clone volume associated with the write-in request; writing data associated with the write-in request in a data area associated with the write-in request in a data object according to an acquisition result that the data state of the data object in the clone volume associated with the write-in request is unready; and marking or keeping marking the data object as a clone object. Through the technical scheme of the specification, the state of the data object is dynamically identified, and local writing and marking are carried out when necessary, so that the overhead of reading and copying full data in copy-on-write is avoided, the writing delay of the clone object is remarkably reduced, the writing operation performance is improved, and meanwhile, the data independence and the space efficiency of the clone volume are kept.

The application discloses an intelligent Internet of Things gateway system supporting edge computing deployment functions, and relates to the technical field of Internet of Things application.The gateway has wide adaptability, can be applied to various application scenarios such as intelligent factories, smart homes and smart agriculture, realizes end-to-end capability from a sensing device to an application, guarantees data independence and security, can flexibly deploy functions in gateways of different levels according to requirements, provides edge computing capability, supports unified access of heterogeneous devices, provides various deployment modes, and is high in flexibility, dynamically establishes a route between data and an application, realizes flexible integration of data transmission and processing, and realizes loose coupling between Internet of Things applications and between Internet of Things applications and the gateway.

The invention discloses a weak network point detection method based on a course angle and a WiFi sequence, and the method comprises the steps: constructing a motion track according to a course angle feature sequence generated in the moving process of a user, recording the motion track in a preorder path of a weak network point region and WiFi signal strength evolution data when the user enters the weak network point, and carrying out the detection of the weak network point. Establishing a space-time correlation model between the trajectory model and the signal strength evolution data, constructing a weak network scene feature template library, and when the user moves again, predicting whether the user is about to enter a weak network area by analyzing the similarity between the change trend of the current wireless signal and historical features in the weak network scene feature template library. And a network switching mechanism is started in advance. The joint recognition model is established on the basis of keeping independence of two types of data, specific position information of a user does not need to be obtained, prediction and judgment are achieved by analyzing internal association of moving behaviors and signal changes, and the method can be widely applied to complex building environments such as shopping malls, transportation hubs and underground spaces.

The present invention relates to the field of network communication technology, and in particular to a task management method, route allocation device, equipment, and readable storage medium, wherein the method comprises: when creating a task on a page, assigning a task identifier to the task; wherein the page is pre-configured with a parent route; generating a sub-route corresponding to the task based on the task identifier, wherein the sub-route is connected to a data set associated with the task; and performing management operations on the task through a component instance in the page based on the task identifier and the sub-route. By assigning a dedicated sub-route to each task through the task identifier, data independence between multiple component instances of the same component is achieved, and each task does not need to separately declare and create its own data state in the component's data management state to achieve independent management of data corresponding to each component instance associated with the task, thereby solving the problem of how to avoid affecting other tasks associated with the data of the task within the same component.

The invention relates to the technical field of property management, in particular to a notarization method for property checking, which comprises the following steps: acquiring a checking number timestamp area and an article index to generate a responsibility chain, setting a responsibility index by sorting data, generating sequence data, generating fingerprints by Hash and binding numbers, and marking exceptions in overtime. And obtaining log comparison consistency and completion rate score classification risks, backtracking and calculating influence value attribution responsibilities, summarizing optimization responsibilities, and uploading the optimization responsibilities. According to the method, task sequence and timeliness of counting personnel are tracked through responsibility chain sorting, data are recorded, responsibility initialization indexes are set, data fingerprints are generated through a hash algorithm to guarantee data independence and completeness, time stamps are compared to mine time delay and mark abnormities, and log comparison consistency and completion rate are obtained based on an abnormal data set. Personalized risk assessment and personnel classification are generated, a responsibility chain sequence and a timestamp are backtracked to calculate a responsibility influence value, responsibility attribution analysis and optimization are formed, counting compliance and transparency are improved, and risks are avoided.

This specification discloses a method, apparatus, storage medium, and electronic device for processing deployment tests. The method includes: monitoring service strategy experiment status data and constructing and managing a wide table of user traffic deployment experiment records; upon receiving a target strategy deployment request, obtaining a target set of test user entities, performing pre-contact conflict detection based on the wide table, and removing and isolating entities overlapping with already run test experiments; during the test run phase, periodically monitoring the wide table and the target set, performing runtime conflict detection, and triggering anomaly warnings; after the experiment, performing data overlap detection on the experimental group and the control group, and generating an experimental data independence test report based on the overlap information. This specification embodiment achieves automated conflict management throughout the entire test task lifecycle, effectively avoiding traffic pollution between concurrent experiments on the platform, and improving the independence of experimental data and the confidence of the final results.

The invention provides a multi-modal data intelligent filing management system, and relates to the technical field of multi-modal data processing, and the system comprises a data mapping module which is used for extracting multi-modal data from a native business environment, generating a data unit set, constructing a virtual reference plane, establishing a reference rectangular grid topological structure in the plane, and dividing a dynamic coordinate axis, mapping the data unit set to grid coordinates, and outputting a grid coordinate mapping data unit set; and the attribute tree construction module is used for constructing a multi-dimensional attribute tree according to the density distribution in the grid coordinate mapping data unit set, generating dynamic evaluation nodes, calculating a weight parameter beta value of each node, and outputting an attribute tree structure with the beta value. According to the method, grid coordinate mapping, attribute tree weight evaluation, differentiation processing, block chain evidence storage, hierarchical verification storage and user behavior driven dynamic optimization of the multi-modal data are realized, so that the data independence, security and utilization efficiency are improved, and the management cost is optimized.

The invention discloses an intelligent cooperative control system for a coal mining process based on digital twinning, and particularly relates to the technical field of coal mining, which comprises a multi-source heterogeneous acquisition module, an anti-impact vibration sensor and a multi-protocol edge gateway implanted at key sites of a coal mine area, a mining system total factor perception system is constructed through an embedded sensor network and industrial Internet of Things protocol fusion technology, coal mining data is collected in real time, data robustness is enhanced through fault-tolerant Kalman filtering, and a spatial original data set is constructed; according to the invention, a total-factor perception system is constructed through the multi-source heterogeneous acquisition module to acquire data, and a multi-dimensional influence coefficient is output through fusion analysis of the data processing module, so that the problem of data independence is solved, deep association mining of equipment operation, environment and geological data is realized, and the data utilization rate is improved.

The application discloses a kind of factory outside warehouse allocation, warehousing, warehouse and cargo right transfer integrated implementation method based on table value parameter, belong to industrial intelligent manufacturing and ERP / MES integrated management technical field.The application adopts heavy back end, light front end architecture, with custom table value parameter as unified data transmission carrier, through single storage procedure centralized control allocation, warehousing, warehouse, auditing, cargo right transfer and other full-service operations, all write operations are included in database atomic transaction guarantee data consistency.With core business wide table as data backbone, through only batch number, document number realizes factory warehouse and factory outside warehouse full-link data through, innovatively realizes the management mode of cargo right transfer and physical warehouse separation, while supporting warehouse information and enterprise organization post information automatic linkage, front end only retains extremely simple interactive function.The application solves the pain points of traditional factory outside warehouse management data independence, interface dispersion, batch operation inefficiency, poor data consistency and cargo right transfer limitation, has been completely landed in actual industrial MES / ERP integrated system, with the advantages of stable architecture, efficient processing, strong maintainability, industrialization promotion value is outstanding, suitable for manufacturing enterprises factory outside warehouse large-scale, standardization, intelligent operation demand.The application has been completely landed in actual industrial ERP system, can be long-term stable operation in real production environment, with mature engineering value and industrialization promotion ability.

The invention discloses a productization method of a Flowable workflow engine. The productization method comprises the following steps: carrying out multi-data source configuration based on a Springboot framework; determining an authority system introduction mechanism; and uniformly opening interfaces. The isolation of the double data sources ensures the data independence of the engine service and the business service, avoids mutual interference, and improves the security and processing efficiency of the data. According to the method, a clear permission introduction path is established, generation of permission vulnerabilities is avoided, only authorized users can perform corresponding operation on the workflow, and the security and reliability of the system are improved.

The invention discloses an oil field water quality on-line detection system database design method, which comprises the following steps: 1) database selection and configuration: configuring a corresponding database according to system stability and data security, and carrying out regular data backup on water quality data; 2) data verification, wherein cyclic redundancy verification and MD5 verification are adopted to verify the correctness of data transmission; 3) data packaging and caching: for the received water quality data information in the sensor module, packaging different types of sensor data information into corresponding fixed frame formats; 4) designing a data model, establishing water quality classification meeting standards for the received water quality data transmitted by the remote monitoring equipment, and classifying the water quality data; 5) data encryption and decryption; and (6) data transmission: performing data transmission and access by adopting high-concurrency optimization processing. According to the invention, database management is carried out on the water quality indexes of the water injection detection points, so that data sharing and data independence are realized, and the redundancy of water quality data is reduced.

The invention relates to encryption operation, in particular to an operation method of encrypted data. The invention relates to a secret state data independence test method, which comprises the steps of user side encryption uploading, cloud computing and user result obtaining and decryption, and is characterized in that the encryption uploading comprises the steps of data arrangement, statistical result binarization, data encryption and secret state data sending to a cloud server, and the data is finally uploaded in a data table form. Comprising a serial number, a group and a type, the type data is 0 or 1, and the data is encrypted; the cloud computing comprises the steps of firstly establishing a connection list by using secret state data, then computing a theoretical frequency number, and finally respectively computing a statistical magnitude and a degree of freedom; and the user side decrypts the statistical magnitude and the degree-of-freedom data returned by the cloud side after obtaining the statistical magnitude and the degree-of-freedom data, looks up a table by using a decryption result, and judges whether the two variables are related according to a table lookup result. Data security of the user can be guaranteed, and the user can enjoy low-cost computing power provided by the cloud platform.

This invention discloses a method for spatial domain filtering and spectrum correction of broadband signals in the mode domain of a circular array. The method involves performing a Discrete Fourier Transform (DFT) on the received time-domain data to obtain the array element frequency domain data. The broadband signal frequency band data is then extracted and subjected to a Circular Fourier Transform (CFT) to obtain the sub-band data in the mode domain. The distance between frequency points and the zeros of the Bessel function within the broadband signal frequency band is calculated, and a zero-point correction method is used to replace the frequency points. Sub-band frequency points in the mode domain are selected according to the correction results. The sub-band weighting vectors for mode domain beamforming are obtained according to the minimum variance and distortion-free criterion for data independence, and the beamformer is calculated. The sub-band data in the mode domain are weighted and summed based on the weighting vectors of each sub-band to obtain the beam output frequency domain data. Zeros are padded at all frequency points except for the broadband signal frequency domain data. An Inverse Fourier Transform is then performed on the beam output frequency domain data to obtain the beamforming output data sequence. This invention effectively preserves the original spectral components of the broadband signal while improving the signal-to-noise ratio.

This disclosure pertains to a cutting-edge mission orchestration platform designed to address deficiencies in mission data management and processing, ensuring data autonomy and integrity. It involves the novel use of multi-layered inference pathway protocols for the autonomous arbitration of artificial intelligence (AI) models to manage and process mission data. This advanced approach of deploying multi-layered inference pathway protocols facilitates extremely fast data self-organization, enhances data independence in mission platforms, maintains high data integrity, and accelerates the extraction of actionable intelligence from diverse data types sourced in mission orchestration.

The present disclosure relates to a sharp end mission orchestration platform, aiming to address the shortcomings in mission data management and processing, ensuring the autonomy and integrity of data. The platform involves a new application of a multi-layered reasoning path protocol for autonomous arbitration of artificial intelligence models to manage and process mission data. This advanced approach of deploying a multi-layered reasoning path protocol facilitates extremely fast data self-organization, enhances data independence in the mission platform, maintains high data integrity, and accelerates the extraction of actionable information from various data types obtained from mission orchestration.

The invention provides a scalar multiplication operation system and method based on Montgomery, and relates to the field of cryptographic algorithm implementation. According to the technical scheme, a Montgomery scalar multiplication algorithm is adopted to execute point addition and point multiplication operation in parallel, in the operation process, participation of y coordinates is not needed, only one-time y coordinate operation needs to be carried out after the point addition and point multiplication operation is finished, data independence in the point addition and point multiplication operation process is analyzed, the proposed scheduling process is adopted, and the scheduling efficiency is improved. The parallelism of multiplication and modular reduction operation can be remarkably improved, and the calculation efficiency of the algorithm is improved.

The present application provides a task variable causal graph construction method and apparatus, a device, and a medium. The method includes: obtaining a variable set and application task information corresponding to a target application task; determining priori knowledge by using a large language model based on the variable set and the application task information corresponding to the target application task; and determining a best causal graph by using a Monte Carlo tree search method based on the priori knowledge and data independence tests, where nodes in the best causal graph correspond one-to-one to the variables in the variable set, each edge in the best causal graph represents a causal relationship between variables corresponding to two nodes connected by the edge, and the best causal graph is used for root cause analysis of a downstream task. The present application improves the accuracy of causal graphs and the effectiveness of downstream tasks.

The present invention provides a drone-assisted IoT data collection method for overlapping multi-agency deployments. The method involves each agency's drone collecting local observation states, merging them into a global observation state for the current time step, and then generating an output action. After each drone performs an action, it collects local observation states again, merges them into a global observation state for the next step, and calculates a reward for the current time step. A reward function is designed with the training objective of minimizing the average AoI of all IoT devices. An experience tuple consisting of the global observation state for the current time step, the joint action, the reward, and the global observation state for the next step is stored in an experience replay pool. Training data is retrieved from the experience replay pool to complete model training based on MADDPG. The trained actor network is then used to plan and deploy drone paths for data collection. This method addresses the problem of inter-agency data collection requiring both data independence and collaboration to reduce the system's average information age.