2481 results about "Data request" patented technology

The invention discloses a data security sharing method and system, and relates to the technical field of data security, and the method comprises the steps: receiving to-be-shared data uploaded by a data provider; fragmenting the data by adopting a biologically inspired adaptive fragmentation algorithm; generating a digital fingerprint for each fragment by using a multi-dimensional dynamic Hash algorithm; encrypting data fragments by adopting a post-quantum encryption algorithm and storing the data fragments in a decentralized network; recording the access authority, the digital fingerprint and the storage position information to a block chain security account book; when a data request is received, the access permission is verified; carrying out identity verification by adopting multi-mode biological feature recognition; after the verification is passed, obtaining a digital fingerprint and a storage position from the block chain; acquiring the encrypted fragments from the decentralized network and decrypting the encrypted fragments; verifying the integrity by using the digital fingerprint; and recombining the verified fragments to obtain complete data and returning the complete data to the requester. According to the method, efficient data sharing is realized while the data security is guaranteed, and the data value and privacy protection are effectively balanced.

An apparatus for personalization of machine learning models, the apparatus including at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the processor to receive resource data from one or more data acquisition systems, classify the resource data to one or more information categorizations, generate information training data as a function of the classification, train an information machine learning model as a function of the information training data. receive a data request as a function of user input and generate an information output as a function of the data request and the information machine learning model.

The invention discloses a method and a system for realizing mine communication signal improvement based on edge computing, and relates to the technical field of mine communication signal improvement, and the method comprises the following steps: integrating a real-time monitoring system on each edge node, so as to continuously detect the fluctuation of communication flow and data request quantity, the real-time monitoring system identifies a potential communication peak period by collecting real-time data and generates an early warning signal to notify a network administrator or automatically trigger a load management program. According to the invention, through the real-time monitoring and early warning system on the edge node, active monitoring and peak prediction of mine communication are realized, the overload risk caused by traffic surge is reduced, and the stability of data transmission is ensured. And intelligent scheduling and dynamic resource allocation are combined, so that efficient execution of tasks under high load is ensured, and node overload is prevented. A self-adaptive load balancing and feedback mechanism enables the system to dynamically adjust distribution, quickly respond to a bottleneck and improve self-adaptability and stability.

A computer-implemented method is disclosed. The method includes: receiving a request for retrieval of data satisfying one or more criteria, the request including at least one data request parameter; searching a database storing example queries based on the request to identify at least one matching query; providing, to a large language model (LLM), an input prompt to generate a query purporting to retrieve data satisfying the one or more criteria, the input prompt including the at least one data request parameter and the at least one matching query as an example; and receiving, from the LLM, a result including the generated query.

An apparatus for personalization of machine learning models, the apparatus including at least a processor and a memory communicatively connected to the at least a processor, the memory containing instructions configuring the processor to receive resource data from one or more data acquisition systems, classify the resource data to one or more information categorizations, generate information training data as a function of the classification, train an information machine learning model as a function of the information training data. receive a data request as a function of user input and generate an information output as a function of the data request and the information machine learning model.

Techniques relate to generating and / or verifying content based on protocols and / or user input. The techniques can receive protocol data from an entity, including a procedure, guideline, policy, or standard. User input requesting content generation related to specific parameters can also be received. Based on the protocol data, a data request can be generated and sent to a content generation component. Machine-generated content can be received from the content generation component in response. The machine-generated content can be analyzed based on the protocol data. Output content can be generated based on the machine-generated content and provided to a computing device. In examples, this ensures that generated content aligns with entity-specific protocols and / or user-specified parameters, enabling tailored and / or compliant content delivery for various contexts.

Systems, methods, and computer-readable storage media for providing a decentralized network. One method includes generating a plurality of tokens comprising cyber resilience data and assigning a plurality of unique identifiers to the plurality of tokens, at least one unique identifier of the plurality of unique identifiers corresponding with at least one token of the plurality of tokens, the at least one token corresponding with one or more access rights for accessing the cyber resilience data. The method includes broadcasting the at least one unique identifier to a data storage, receiving a request for the cyber resilience data of the at least one token, verifying the request based on one or more access controls of the decentralized cyber identity and the one or more access rights, and accessing the cyber resilience data corresponding with the at least one token via the at least one unique identifier.

The invention provides a digital culture product right confirmation and data sharing method and system based on a block chain, and relates to the technical field of digital culture, and the method comprises the steps: generating a comprehensive trust score through a self-adaptive trust evaluation model by fusing timeliness, integrity and consistency trust scores, and constructing a self-evolution data trust network and an encrypted data synchronization channel. After smart contract verification, the access authority of the data requester is determined according to the trust score, access features are extracted through a bidirectional long-short term memory network and a multi-head attention mechanism, a proof chain node is constructed, a mapping relation with an authority confirmation certificate is established by using a graph neural network, and the access contribution degree is calculated through homomorphic encryption and federated learning; and finally, performing income distribution according to a sectional income distribution curve. According to the invention, the problems of difficult right confirmation and low data sharing credibility of digital culture products are effectively solved, and safe and controllable data sharing and income distribution are realized.

The invention discloses a storage node load balancing method and device, equipment and a storage medium, and relates to the technical field of load balancing, and the method comprises the steps: carrying out the real-time monitoring of the state of each storage node, and collecting the real-time load information; predicting the load trend of each storage node based on the real-time load information and the historical load data of each storage node to obtain a corresponding prediction result; and adjusting each storage node and a corresponding data access strategy according to the real-time load information and the prediction result so as to respond to the related data request based on the data copy in the adjusted storage node. Therefore, the storage nodes and the data access strategy can be adjusted in combination with the real-time load information of each storage node and the prediction result of the corresponding load trend; the load change trend of each storage node can be accurately mastered, the storage nodes and access strategies are dynamically optimized, the load balancing capacity of the storage nodes can be improved, and diversified service requirements are met.

The invention provides a streaming communication method and device based on long connection and computer equipment, and the method comprises the steps: building SSE long connection between a server and a large model when the server is started; a WebSocket long connection is established between the client side and the server side; the client sends a user dialogue text with the large model input by a user to the server through WebSocket long connection; the server receives a user dialogue text of the client, processes the user dialogue text, generates a corresponding data request, and sends the data request to the large model through SSE long connection; the large model receives the data request, processes the data request, and transmits model output information back to the server through SSE long connection; and the server receives the model output information, processes the model output information, generates a corresponding response message, and sends the response message to the client through the WebSocket long connection. The method has the beneficial effect that the communication efficiency and real-time performance between the client and the large model are improved.

A management server system may obtain a request for image data from a computing device. The request may identify a subset of image data to be downloaded and / or streamed to the computing device. The management server system can provide an indication of a storage destination for the image data to a gateway device and initiate upload of the image data from the gateway device to the storage destination. The management server system may monitor the upload and, based on the monitoring, determine the upload is complete. The management server system can cause display of a user interface that includes a visualization of the image data for download of the image data from the storage destination to the computing device.

The invention discloses a TSN scheduling optimization method and device based on flow sensing autonomous learning, equipment and a medium. The method comprises the following steps: deploying a lightweight flow detection module in a switch or a router, and after a controller receives a data request, automatically identifying a newly arrived unknown service flow by using the lightweight flow detection module, and judging whether the newly arrived unknown service flow is a periodic TT flow or an unpredictable burst flow; the controller performs classification management on the identified service flow types, collects topological information and flow requirements of the whole network and issues the topological information and the flow requirements to the terminal nodes through a network management interface; the controller constructs an intelligent queue scheduling task based on the collected network topology information and traffic demand and converts the task into a Markov decision process MDP, network resources, queue states and priorities are used as a state space, a scheduling strategy is used as an action space, a reward function is designed in combination with throughput and delay indexes, and an intelligent queue scheduling task is obtained. Driving a dynamic environment through real-time data and training a DRL model; an enhanced queue scheduling mechanism Pro-CQF is adopted, different priority labels are configured according to classified flow types, and then mixed flow scheduling is carried out; the controller periodically collects time delay, packet loss rate and end-to-end transmission delay indexes and feeds back the indexes to the DRL model, and a scheduling strategy is updated online. According to the method, the traffic sensing and scheduling efficiency is greatly improved in a network environment in which multiple service flows coexist and end-side equipment functions are different, and the reliability and the expandability of the TSN in industrial Internet of Things, edge computing and other high-real-time application scenes are remarkably enhanced.

The invention provides a government affair cloud cross-department data security sharing method and device, and relates to the technical field of data security. The method comprises the following steps: a main chain of a block chain performs first-level verification on a requester based on a VerifyCredate contract and an access policy white list set by a department to which government affair data belongs; the access strategy is a dynamic attribute base access strategy generated by a department to which the government affair data belongs based on a dynamic attribute encryption technology; under the condition that the first-level verification is passed, generating an access credential, synchronizing the access credential to a side chain of the block chain, generating a zero-knowledge proof by the side chain according to the operation log, and initiating a zero-knowledge proof verification request to the main chain to perform second-level verification; and under the condition that the main chain passes the second-level verification, determining a cross-domain trust score between the government affair data requesting department and the department to which the government affair data belongs based on the digital certificate submitted by the requester by adopting a federal model, and performing third-level verification according to the cross-domain trust score. According to the invention, the data sharing security can be improved.

Provided herein is a process that converts unprotected data into protected data based on permissions defined using logical operators. As such, user permissions can be managed with a simple string of data. In one example, the method may include receiving a request for data from a user device, identifying a permission object corresponding to the user device, retrieving a string comprising a logical expression with a logical operator and one or more values from the permission object, wherein the logical expression defines access permissions of the user device with respect to a database, executing a database query on the database based on the request to generate results, and filtering the results from the database query based on the logical expression to generate filtered results and outputting the filtered results to the user device.

The invention discloses a big language model generation content security test system and method in a black box scene. The system comprises a jailbreak prompt word library module used for storing jailbreak prompt words for performing security test on a big language model; the violation question and answer pair module is used for storing violation question and answer pairs covering different types; the response acquisition module is used for obtaining a data request packet according to query content formed by the jailbreak prompt word and the query request; the security analysis module is used for calculating the similarity between response data corresponding to the query request and an expected violation answer, taking the similarity as a security score, and inputting the security score into the adaptive optimization module; and the adaptive optimization module is used for optimizing the jailbreak prompt words output by the jailbreak prompt word bank module by using a genetic algorithm according to the security score output by the security analysis module. According to the method and the device, the security of the large language model generation content can be effectively tested.

Various aspects of the present disclosure relate to an authentication server function (AUSF) that receives an authentication request from a security anchor function (SEAF), and transmits a data request for authentication data to unified data management (UDM). The AUSF can receive the authentication data from the UDM for primary authentication, and set an expiration time for security information associated with the primary authentication being successful. The AUSF can then transmit an authentication message of authentication information that includes the security information and the expiration time to an authentication and key management for applications (AKMA) anchor function (AAnF) that registers the expiration time. The AUSF can also initiate reauthentication based at least in part on expiry of the authentication information.

The invention provides a priority resetting method of a cache line and an artificial intelligence chip, and relates to the technical field of artificial intelligence chips, the method comprises the following steps: detecting that a cache group contains a cache line of a first priority state (namely, the priority is greater than a preset level), and in addition, detecting that the cache group contains the cache line of the first priority state (namely, the priority is greater than the preset level); detecting a request state between the processing core and the cache when the target duration (namely the interval duration from the previous access of the data request carrying the priority prompt to the cache group) is greater than the preset duration; when the request state is that the data request sent by the processing core is not detected, spontaneously initiating a priority resetting process, and adjusting the priority of the cache line in the first priority state in the cache group to a preset level; in this way, hardware can automatically reset the priority of the cache line, the situation that the cache line with the high priority occupies the cache space for a long time is avoided, the cache space reserved for non-important data access is improved, the overall performance of the cache is improved, and meanwhile processing of a data request (normal access) of a processing core is not affected.

Methods, computer systems, and computer-storage media are provided for generating and using context briefs to identify relevant chat responses. In embodiments, a context template associated with an intent is obtained. The context template includes a data reference referencing dynamic data and content providing context for the dynamic data. Thereafter, a context brief associated with the intent is generated by obtaining the dynamic data and incorporating the dynamic data with the content. Upon obtaining an input data request indicating a user intent, the context brief is identified as corresponding with the user intent of the input data request based on the intent associated with the context brief. A prompt to be input into a large language model is generated. The prompt includes the input data request and the context brief. A response relevant to the input data request is obtained as output from the large language model.

The invention relates to a decentralized information safe and efficient storage and sharing method supporting data verification. The method comprises the following steps: 1) an initialization stage; 2) generating and uploading a ciphertext; 3) evaluating the size of the uploaded ciphertext; if the size of the ciphertext exceeds 256 KB, the IPFS carries out fragmentation processing on the ciphertext, stores the fragments in node servers distributed globally, and generates a unique address identifier at the same time; 4) splicing into a new plaintext; 5) the data provider selects an encryption strategy and performs attribute encryption on the new plaintext; (6) the data requester submits an access application to the Hyperledger Fabric before using the data; 7) verifying the legality of the data request; 8) acquiring a symmetrically encrypted ciphertext; and 9) decrypting to obtain the privacy data of the patient. According to the invention, the paralysis state of the whole system caused by faults of some nodes can be avoided.

A method for dynamically rendering a report on the basis of an index model, relating to the technical field of service systems; the technical problems to be solved thereby are how to solve the problem of the inability to dynamically adjust and render a report during development of the report and how to ensure the consistency and accuracy of data. The method comprises the following steps: on the basis of an application scenario, processing acquired service data, and establishing in a backend a summary physical table, a dimensional physical table, and an association between the summary physical table and the dimensional physical table; on the basis of metadata information in the dimensional physical table, constructing a dimensional data model, on the basis of metadata information in the summary physical table, constructing an index data model, and integrating the dimensional data model, the index data model, and a full-dimensional data model constructed in the backend with a front-end interface; and, on the basis of a data request, loading the dimensional data model and the index data model on the front-end interface to form a service report, rendering the service report, and dynamically displaying same. Further disclosed is a system for dynamically rendering a report on the basis of an index model.

The invention relates to the technical field of mobile positioning calculation, in particular to high-precision positioning mobile terminal equipment for augmented reality inspection of power pipelines, which comprises a PDA (personal digital assistant) handheld terminal, a camera is fixedly connected to one side of the PDA handheld terminal, a display is arranged at one end, far away from the camera, of the PDA handheld terminal, and an electronic compass, a gyroscope and a processing system are arranged in the PDA handheld terminal; the processing system comprises an image acquisition module, a calibration module, a positioning module, an inspection data acquisition module, a GIS (Geographic Information System) data request module, a data standardization processing module, an SAR (Synthetic Aperture Radar) space construction module, a reality rendering enhancement module and a display module. And the GIS two-dimensional spatial data of the electric power pipeline are converted into visual augmented reality SAR data, so that the maintenance difficulty of the urban cable pipeline data is reduced, and the efficiency of cross-department business cooperation in an electric power enterprise is improved.

The invention discloses a power data management method based on a block chain, and relates to the field of block chains, and the method comprises the steps: initiating a data request; randomly selecting a preset number of oracle machine nodes; segmenting a private key of the request task into a plurality of parts by adopting a threshold key segmentation method; acquiring requested power data from an external data source; verifying the obtained power data; a Byzantine fault-tolerant consensus mechanism is adopted to achieve a consensus for the power data; signing the verified power data through a threshold signature method; the oracle machine management contract performs aggregation verification on the received signature data; the oracle machine management contract returns the power data passing the aggregation verification to the intelligent contract of the data requester; the intelligent contract of the data requester obtains the returned power data through an event monitoring mechanism, and executes corresponding business logic and state updating according to the power data; aiming at the low fault-tolerant capability of an oracle machine in power data management in the prior art, the fault-tolerant capability of the system is improved.

In some implementations, a system may receive the data request. The system may obtain a query associated with retrieving the data responsive to the data request, wherein the query is a first output of a large language model (LLM) that is trained based on metadata associated with a plurality of datasets. The system may retrieve, based on the query, the data responsive to the data request, the data being retrieved from at least one dataset of the plurality of datasets. The system may obtain code associated with providing the visualization of the data responsive to the data request for display, wherein the code is a second output of the LLM. The system may cause, based on the code, the visualization of the data responsive to the data request to be provided for display.

The invention discloses a data processing method and device and a nonvolatile storage medium. The method comprises the following steps: collecting a plurality of network data packets forwarded by a plurality of network nodes in a cloud platform of a private network; in the plurality of network data packets, counting the amount of data sent by each application program under the same source IP address within a preset time range; acquiring application priority information and application load information of each application program under the same source IP address, and determining an application score of the application program; and obtaining a load index of the network node at the target moment, and under the condition that the load index is greater than a preset threshold value, performing shunting processing on target traffic corresponding to the target application program under the target source IP address forwarded by the network node. According to the method and the device, the technical problems that the route for forwarding the data request of each access unit to the exclusive cloud is not reasonable enough and the efficiency is low due to the lack of an effective node load monitoring mechanism and a dynamic routing adjustment strategy are solved.

Provided in the embodiments of the present application are a multi-control storage array, a storage system, a data processing method and a storage medium. The storage array comprises a four-control storage module, which comprises two groups of controller pairs and a storage expansion disk cabinet, wherein the two groups of controller pairs are connected on the basis of the Ethernet; either of the two groups of controller pairs comprises two controller nodes, and each controller node is connected to the storage expansion disk cabinet so as to perform shared access to the storage expansion disk cabinet; and a cache unit is provided in each controller node, any controller node determines, after responding to a data write request, a target mirror controller node corresponding to the controller node, and a cache mirror of the controller node is stored in a cache unit of the target mirror controller node.

The invention discloses a live broadcast stream pushing method, which comprises the steps of obtaining a task undertaking instruction used for indicating to undertake a task for pushing a first live broadcast data stream to a client, the first live broadcast data stream being a live broadcast data stream corresponding to a target live broadcast room, and the target live broadcast room corresponding to a plurality of live broadcast data streams; sending a live broadcast material data request message used for requesting to obtain live broadcast material data used for generating the first live broadcast data stream; obtaining live broadcast material data, wherein the live broadcast material data comprises user portrait data, anchor image data, anchor timbre data and first service item data which can be provided for a user by an anchor party; generating the first live broadcast data stream according to the live broadcast material data; and pushing the first live broadcast data stream to the first user side. By adopting the scheme of the invention, different users can see different live broadcast room contents when entering the same live broadcast room, so that the live broadcast room contents and live broadcast styles watched by the users better conform to user preferences.

The invention discloses a cache management system and method, a server, electronic equipment and a storage medium, and relates to the technical field of storage, and the cache management system comprises an acquisition engine used for acquiring a data request stream of an access target; the processing assembly is composed of a load balancer, a plurality of nodes and a processing sub-assembly of each node, the load balancer distributes a data request stream to the plurality of nodes, and the processing sub-assembly is used for providing multi-dimensional features, predicting probability distribution of access targets, determining a pre-fetching target set and determining pre-fetching window parameters at the next moment; and the collaboration component is used for generating a global thermodynamic diagram according to the pre-fetching window parameters of each node at the next moment, finally generating a pre-fetching instruction, pre-fetching the cache from the storage system by using the pre-fetching instruction, and performing multi-dimensional feature fusion through a dynamic window mechanism. The technical problems that a static strategy cannot adapt to a dynamically changing IO mode, resource utilization is low in efficiency and the like in related technologies are solved, and the technical effects of adapting to the dynamic IO mode, improving the resource utilization rate and the like are achieved.

The invention is suitable for the technical field of data circulation, and provides a trusted data space connector layer data circulation method and system, and the method comprises the steps: enabling data to access a trusted data space connector, and carrying out the preprocessing of the data; dynamically configuring an access control strategy according to the identity and authority of the data requester; data are virtualized and circulated among different security domains through a data cross-domain virtualization technology, and in the data circulation process, an end-to-end data encryption transmission technology is adopted; after a data requester obtains the data, the data is processed and analyzed by using a micro-isolation data cross-domain fusion processing technology. According to the method, the fusing index is generated by dynamically fusing the aging feature vector, the frequency risk spectrum and the sensitivity matrix, so that real-time parameter customization and risk adaptive adjustment of the access control strategy are realized, and time sequence change, frequency anomaly and data sensitivity difference in a complex access scene are effectively dealt with; and the dynamic protection capability of cross-domain data circulation is obviously improved.

Disclosed in the embodiments of the present disclosure are a data reading method for a chip, and a chip, a computer device, a storage medium and a computer program product. The method comprises: acquiring a data reading instruction, wherein the data reading instruction is used for instructing data reading to be performed according to reading information and data prefetching to be performed according to prefetching information; on the basis of the data reading instruction, acquiring a first data reading request, wherein the first data reading request includes the reading information and the prefetching information; sending the first data reading request to a cache module, so that in response to the first data reading request, the cache module reads and returns first target data according to the reading information, and pre-fetches and caches second target data according to the prefetching information; and receiving the first target data returned by the cache module. The embodiments of the present disclosure can reduce data request pressure between a request source and a cache module, compress a request bandwidth, improve the performance of a processor, and facilitate flexible control over a prefetching mode on a per-task basis, thereby better satisfying data reading requirements of tasks.

The present disclosure provides an artificial intelligence-based alarm management based on structured time series data and unstructured contextual information where the conventional methods fails to do. Initially, the system receives a user query associated with an industry automation system and classifies into one of a) data request query b) an anomaly detection and diagnosis query c) a log request query and d) feedback for previous response using a query classifier. Simultaneously, the user query is converted into an associated timeseries query representation. Furthermore, a plurality of database queries is generated based on the timeseries query representation using query generator. Further, data pertaining to the user query is retrieved from an associated database based on database queries using Deep Learning models, thereby identifying a critical alarm, and to take appropriate actions if there is any anomaly. Finally, the retrieved data is displayed to the user in a user readable format.