357 results about "Data Applied" patented technology

The invention relates to the technical field of data analysis, provides an equipment state data management method and system applied to an automatic radix astragali seu hedysari refined production line, and is used for realizing equipment health precise prediction and active maintenance through whole-process data monitoring management. The method comprises the steps that a production line equipment state data set is acquired, a production line equipment state feature set is extracted from the production line equipment state data set, and the production line equipment state feature set comprises multi-dimensional time sequence features reflecting the equipment operation trend and topological features of the incidence relation between the equipment; training an astragalus membranaceus essence production line state prediction model based on the production line equipment state feature set, wherein the astragalus membranaceus essence production line state prediction model is used for predicting the equipment abnormal probability and the performance degradation trend in a selected time period according to the current equipment state feature; and generating an equipment management strategy set according to an output result of the radix astragali seu hedysari refined production line state prediction model, wherein the equipment management strategy set comprises production parameter adjustment instructions and maintenance node planning schemes for different equipment maintenance priorities.

The invention discloses a lower limb motion data real-time analysis method and system applied to rehabilitation guidance, and the method comprises the steps: calling a personalized model according to user information, converting real-time motion data into historical motion feature vectors, inputting the historical motion feature vectors into a real-time prediction module, and generating multiple frames of future motion feature vectors through coding and decoding; calculating a deviation value between each future motion feature vector and a preset threshold range to obtain a motion deviation value, calculating a motion risk proportion of each future motion feature vector, performing weighted fusion to obtain a motion risk probability, and generating an equipment parameter adjustment value and pose adjustment information through reverse mapping; and finally, according to risk probability assessment training stage promotion, synchronously displaying correction information and adjusting equipment operation parameters. According to the method, the dynamic model is constructed through pre-training, real-time prediction of future motion features is realized in combination with the lightweight LSTM, and the predictability and personalized adaptation ability of rehabilitation guidance are improved.

The invention discloses an AI interactive data protection method and system based on a security context protocol. According to the method, a client application sends a user request carrying a session identifier to an application gateway; the gateway queries a required context range and a security processing strategy according to the request type, and transmits a strategy instruction; after the SCS verifies the gateway permission, the context data is retrieved and processed according to the strategy instruction, and a security context data block is generated; the gateway assembles the user input and the security context data block into a final request according to an SCP protocol, and sends the final request to an AI model; the AI model processes the request and returns a response; after receiving the response, the gateway updates the session context and updates the stored context data; and finally, the gateway returns the response of the AI model to the client application to complete interaction. According to the method, the exposure of the sensitive context data in the system can be reduced to the greatest extent while the AI interaction effect is ensured, so that the data security and compliance of the AI application are improved.

The system and methods for determining the representative samples from a large imperfectly labeled dataset to support data processing and inferences for machine-learning applications. The method includes accessing data samples that may be processed to generate embedded vectors along with a set of reference labels. For each label, clustering is performed to group at least some of the embedded vectors together into clusters based on the associated inherent patterns, followed by a refinement process to select relevant clusters from the clustered patterns. One or more embedded vectors from the selected clusters are passed to a statistical technique to generate representative embedded vectors for each label. The statistical technique is configured such that the weights of selected embedded vectors within each of the cluster are the same. These representative embedded vectors may be further fed into a machine-learning model to predict a label from the set of reference labels for a given prompt.

The invention discloses an intelligent government affair service platform and a data processing method applied by the intelligent government affair service platform, and relates to the technical field of government affair service management, and the method comprises a public configuration module which is used for carrying out hierarchical configuration on system service capability according to a configuration instruction, and the hierarchical configuration comprises capability application management configuration, public template configuration and service model configuration; the service model configuration comprises a service overall planning model and a service implementation model; the reservation rule engine module comprises multi-level reservation rules of a hall reservation rule, a special area reservation rule and an item reservation rule, rule parameters can be dynamically adjusted, and the multi-level reservation rules comprise a reservation time period, a government affair service number allocation strategy and a conflict detection mechanism; the business handling module is used for realizing automatic material verification and document generation in a certificate-free business scene; and carrying out data interaction with an external system through the capability application management module, and carrying out system service capability authorization. The service efficiency of government affair services is improved, and the government affair handling experience of the masses is improved.

The present application is applicable to the field of communication technology, a method of communication between applications, a terminal device and a computer readable storage media are provided. The method comprises: the first application establishes a connection with the server based on an interface provided by the first client, the second application establishes a connection with the serverbased on an interface provided by the second client, As such, a communication connection is established between that first application and the second application, the first application then sends a first communication message to the second application through the communication connection, the second application may return a second communication message to the first application through the communication connection, after the communication connection between the first application and the second application is completed, the communication connection between the first application and the second application is disconnected by the release request, and since the interface provided by the client has information for converting the data of the application to conform to the communication protocol. The communication method development period between the applications is short and the stability is good.

The invention discloses a battery cell simulation type state sensing and feedback method and system, and the method comprises the steps: providing a simulation battery cell detection device which flows on a production line along with an actual battery cell; the device is provided with a shell matched with an actual battery cell in boundary dimension, a film pressure sensor covering the surface of the shell, and a built-in collector, in the circulation process, the sensor collects pressure data applied by the production line equipment in real time; the built-in collector stores data and sends the data to the upper computer processing system in a wireless mode; and the upper computer processing system receives and analyzes the pressure data, judges abnormity according to a preset pressure threshold value and generates a report. By simulating the real stress condition of the battery cell, comprehensive, real-time and automatic monitoring of the pressure state in the production process is realized, the abnormal reason can be accurately positioned, the problems of lack of monitoring means and difficulty in problem tracing in the prior art are solved, the product quality and the production efficiency are effectively improved, and the potential quality hazard is reduced.

The invention provides an equipment state data analysis method and system applied to automated electrical equipment, and the method comprises the steps: obtaining a historical operation data set of target equipment, and constructing a multi-level state analysis model based on the historical operation data set, the multi-level state analysis model comprises at least one first analysis level and at least one second analysis level, key operation parameters are extracted from the real-time operation data flow of the target equipment through an operation parameter screening strategy in the first analysis level, and a parameter screening result is generated according to the key operation parameters; inputting a parameter screening result into a state evaluation strategy in a second analysis hierarchy, and generating a state evaluation index of the target equipment in combination with a dynamic threshold range corresponding to the key operation parameter; and outputting a real-time operation state grade of the target equipment according to a comparison result of the state evaluation index and a preset state threshold value. According to the invention, efficient monitoring and accurate early warning of the equipment health state can be realized.

A system and method include tuning hyperparameters for an ARIMA model using a derivative free approach by determining a set of initial hyperparameter values, fitting an ARIMA model to the set of initial hyperparameter values, selecting a tuning method for the set of hyperparameters, responsive to selecting a single-objective method, computing a first objective function value from time-series data applied to the ARIMA model based on the set of initial hyperparameter values, or responsive to selecting a multi-objective method, computing at least a second objective function value and a third objective function value from the time-series data applied to the ARIMA model based on the set of initial hyperparameter values, determining whether a stopping criterion for tuning the set of hyperparameters has reached, responsive to determining that the stopping criteria has reached, outputting a set of tuned hyperparameter values.

The invention discloses a multifunctional integrated service terminal and a data processing method applied by the same, and relates to the technical field of intelligent office equipment.The method comprises the steps that the cooperative relation between a multi-mode interaction module and a business processing module is determined, and the mapping relation from the business processing module to different scene service output is determined; an integrated control center is constructed based on a multi-modal fusion framework corresponding to the cooperative relation and an intelligent decision engine corresponding to the mapping relation, the multi-modal fusion framework comprises an environment perception algorithm, and the intelligent decision engine comprises an intention recognition model; obtaining a training data set containing interaction data in a complex noise environment; training an integrated control center based on the training data set, and combining an environment perception algorithm and an intention recognition model for joint optimization; inputting a to-be-served multi-mode input signal into the integrated control center, and outputting a directional sound recording file, a business handling instruction and an office service response; the office efficiency of the multifunctional all-in-one machine product is improved, and the user experience is improved.

In various examples, a technique for generating simulation data includes generating, via one or more simulations, simulation data associated with operation of a first machine in an environment. The technique also includes determining a command to the first machine based at least on the simulation data and a goal associated with the first machine and updating the simulation data based at least on the command. The technique further includes storing the simulation data, the command, and the updated simulation data in one or more data records, and causing a second machine to perform one or more actions based at least on the one or more data records.

The invention discloses an image processing method, electronic equipment and a computer readable storage medium, and relates to the technical field of image processing, artificial intelligence and large models. The method comprises the following steps: acquiring a two-dimensional image; performing scene depth estimation on the two-dimensional image by adopting a multiple depth estimation strategy to obtain a target depth map, the multiple depth estimation strategy being used for obtaining scene depth information of a given image through different types of depth estimation modes; and generating three-dimensional scene data based on the camera parameters of the two-dimensional image and the target depth map, the three-dimensional scene data being training data applied to three-dimensional perception and understanding of a scene. The technical problems of high acquisition cost, insufficient scene diversity and small scale of a three-dimensional scene data set in related technologies are solved.

The invention discloses a data transmission system, method and device, a storage medium and a computer program product, and relates to the technical field of communication. The data transmission system comprises a virtual machine, a virtual RDMA device and a host, wherein the virtual RDMA device runs between the virtual machine and the host. Wherein the virtual machine is used for running an application; the virtual RDMA equipment is used for registering a virtual memory and a virtual RDMA connection corresponding to the virtual machine, configuring a memory mapping relation between the virtual memory and a physical memory and a connection mapping relation between the virtual RDMA connection and the physical RDMA connection, and issuing the memory mapping relation and the connection mapping relation to the host; and the host is used for transmitting the RDMA data of the application according to the memory mapping relation and the connection mapping relation. Decoupling of the front-end virtual machine and the rear-end host is realized, the expansibility of connection is improved, a data transmission system is more modularized and is easy to manage, and the overhead of the host is reduced.

The invention relates to the technical field of message recovery, and discloses an AI-based iOS device message recovery method and system, and the method comprises the steps: connecting an iOS device, positioning a database file of a message application, and obtaining a database file path list; reading an equipment storage sector, creating a physical mirror image, and analyzing a free block position mark in an APFS container super block; binary classification identification is carried out through an AI data block classification model, an SQLite page type label and a page mapping relation are obtained, deleted messages of a recombined database and a device end are determined, differential comparison is carried out on all historical backup snapshot records of an iCloud account, and cloud end deleted messages are obtained; according to the method and the system, the reorganization success rate of the database and the extraction integrity of the deleted messages are improved, and a technical solution is provided for comprehensive, accurate and efficient recovery of the iOS device messages.

The invention discloses a multi-modal data feature representation optimization method based on comparative learning and two-stage masks. The method comprises the following steps of: firstly, aiming at an input single image-text pair, generating two groups of heterogeneous image-text data with mode missing as two inputs of a model by applying two random mask strategies with different mask areas and proportions; wherein the first group of data applies a high-proportion mask to the image and applies a low-proportion mask to the text; the second group applies a low-scale mask to the image and a high-scale mask to the text. Then, the two groups of data respectively pass through an image encoder and a text encoder which share parameters, and two different multi-modal fusion feature vectors are generated through a cross-modal fusion encoder; according to the method, masked modal information is recovered through a decoder, and the reconstruction loss of the difference between a recovery result and original data is calculated. Meanwhile, two multi-modal fusion feature vectors generated twice are subjected to comparative learning, and the comparative loss of feature representation distances under different enhanced views for approaching the same image-text pair is calculated. And finally, performing weighted summation on the reconstruction loss and the comparison loss to form an overall loss function, and optimizing model parameters through back propagation. When the trained encoder is used for a downstream multi-modal classification task, the classification precision and generalization ability of the model can be effectively improved.

The invention provides an access control method, electronic equipment, a storage medium and a program product, relates to the technical field of computers, and is used for solving the problems that when an application accesses data, the risk of privacy data leakage exists, and the security of privacy data is relatively low. The method comprises the steps of obtaining a parameter gradient of an aggregation model corresponding to a target application, determining a data access permission corresponding to the target application based on the parameter gradient of the aggregation model, and indicating a security level of each data type allowed to be accessed by the target application through the data access permission; and further, determining an access control strategy of the target application based on the data access range and the data access permission of the target application, thereby indicating the data allowed to be accessed by the target application and / or the data forbidden to be accessed by the target application through the access control strategy.

Quantum-based dispatch of workgroups is described. An example of an apparatus includes a computer memory to store data for processing, including data for an application; and one or more processors including a graphical processing unit (GPU), the GPU including multiple chiplets, each of the multiple chiplets including compute containers and a cache, each compute container including a plurality of processing resources, and a dispatcher for dispatching workgroups to the processing resources of the GPU, wherein dispatching workgroups includes dispatching workgroups for the application according to a selected workgroup quantum, the selected workgroup quantum having a certain size and shape.

The embodiment of the invention provides a data recovery method and device, a storage medium and an electronic device.The method comprises the steps that abnormal second data in first data is determined according to a data rule engine, and a data rule applied in the data rule engine is configured according to a data service scene corresponding to the first data; the second data is restored through a preset processing mode, the preset processing mode comprises a data prediction generation algorithm, and the data rule engine and the data prediction generation algorithm are updated in real time through a preset monitoring mode. By the adoption of the technical scheme, the problem that the data restoration effect is poor due to the fact that a data restoration method in the related technology cannot be updated in real time along with changes of the restored data is solved.

A data migration method includes, when a data migration request for a storage unit in a first storage medium is obtained, data in the storage unit is migrated to a storage unit that is in a second storage medium and does not participate in unified addressing. In a migration process, a data access request of an application is routed to the first storage medium or the second storage medium by querying a mapping relationship in a second unit mapping table and a migration state in a migration table. After the migration is completed, an address of a second storage unit is allocated to the application.

The embodiment of the invention provides a data processing method and device based on a graphics processor, equipment and a storage medium, and the method comprises the steps: responding to a data processing request of a large model application, accessing a target file system in a user mode, and obtaining an access position of target data corresponding to the data processing request in the target file system, the target file system is used for managing the storage unit, and the target data is persistent data stored in the storage unit; creating a data transmission path between the storage unit and the graphics processor based on the access position; and based on the data transmission path, calling a graphics processor to process the target data, and generating a request result corresponding to the data processing request. By accessing the target file system for uniformly managing the storage unit, the graphics processor can directly read and write data for the storage unit, and the efficiency of processing the target data corresponding to the data processing request by the graphics processor is improved.

A data compression method, system, and device for a vibration application can involve applying a Fast Fourier Transform (FFT) to raw vibration data to obtain FFT coefficients, classifying the FFT coefficients as high energy coefficients or low energy coefficients based on predetermined thresholds, quantizing the high energy coefficients using a first quantization and the low energy coefficients using a second quantization as quantized coefficients, and generating an indicator array to identify positions of the high energy coefficients and the low energy coefficients for use in packetizing the positions and the quantized coefficients and recovering lossy raw data from the quantized coefficients for data compression of the raw vibration data. The vibration application can include one or more battery-based internet-of-things (IOT) devices that can generate the raw vibration data. The raw vibration data is transferrable over a wireless communications protocol.

The invention discloses a business integrated service platform and a data processing method applied by the business integrated service platform, and relates to the technical field of informatization services, and the business integrated service platform comprises a data fusion module which is used for converging cross-department business data of a full life cycle of an industrial project and constructing a unified full-chain electronic archive library; the supervision model module is used for establishing an industrial project digital monitoring model based on a full-chain archive library, monitoring key links of the project and generating a digital intelligent early warning signal; the service cooperation processing module triggers a flattening cooperation service instruction based on the digital intelligent early warning signal, generates a project blocking point problem and dispatches the project blocking point problem to a responsible department terminal; and the visual decision-making module is used for integrating the acquired investment attraction data, project progress data and approval efficiency data to obtain and display industrial layout, project performance and business environment trend analysis results. The invention discloses a high-efficiency industrial project supervision system capable of cracking data fragmentation dilemma and realizing full-period dynamic monitoring.

The invention relates to the technical field of data analysis, can be applied to the fields of science and technology finance / medical health and the like, and discloses an application data consanguinity analysis method and system, electronic equipment and a storage medium. The method comprises the following steps: acquiring network request data and database operation data of all target applications; converting the network request data and the database operation data into a graph data structure by using a graph database; analyzing the graph data structure to obtain a data blood relationship and a data association range of the target application, and visually displaying the data blood relationship and the data association range; monitoring the network request data, the database operation data and / or the change result data of the database table associated with the target application in real time; and performing analysis according to the change result data, the data blood relationship and the data association range to obtain change association range data, and generating application data blood relationship change early warning information according to the change association range data. According to the method, comprehensive tracking and efficient analysis of the application data blood relationship are realized.

The invention provides a building point cloud high-precision automatic registration method based on multi-source sensor fusion, and relates to the field of data processing. According to the method, building point clouds are obtained through multi-source sensor fusion, a time sequence and coordinates are unified, noise and transient targets are removed through density distribution and an occlusion relation, a three-state point cloud label is generated, rough registration and global and local joint optimization are carried out in combination with semantic classification and a cross-scale semantic association graph, and a high-precision registration result is obtained. And on this basis, dynamic difference labeling is executed to generate a component life cycle map, a result is mapped to a building information model, reverse modeling data with life cycle attributes and an engineering application data set are output, and high-precision modeling and application of the whole construction process are achieved. By implementing the technical scheme provided by the invention, high-precision automatic registration of the multi-source point cloud data is facilitated, so that the data set which can directly serve building information modeling and engineering application is mapped.

The embodiment of the invention relates to a database access method based on a middleware system and the middleware system. Initialization is firstly executed through data middleware, a database connection request of a service application is analyzed, a target database instance is determined, and an associated application end token is obtained. And the middleware requests a target database connection credential from the configuration center, and the configuration center sends an encryption credential after verifying the token. The middleware decrypts the credential, initiates connection establishment of the target database, encapsulates the target database into a data source after successful connection, and returns the data source to the business application; and the business application indirectly accesses the target database through an interface or an identifier provided by the datastore middleware. On the premise that database connection credentials are not directly exposed, the connection between the service application and the database is safely established.

This disclosure provides systems, methods and apparatuses for a high priority route selection descriptor (RSD) selection timer. A protocol data unit (PDU) session may be established for an application associated with a user equipment (UE). If the PDU session is associated with a lower RSD priority than the highest RSD priority for the application, the UE may initiate an RSD selection timer. After expiration of the RSD selection timer, the UE may try to establish another PDU session for the application with the highest RSD priority for the application. If another PDU session with the highest RSD priority is accepted, the UE may release the initial PDU session with the lower RSD priority and establish a new PDU session with the highest RSD priority. Such implementations may increase data rates, quality of service, and reliability for the application, decrease latency of the application, or decrease power consumption of the UE.

The invention discloses a method for collecting time series data statistical information of a distributed database, and belongs to the technical field of distributed databases in computer science, the method is implemented by comprising the following steps: a database running cluster is provided, and the database cluster of one application comprises a plurality of database running nodes; the database operation node operates data change processing, data change monitoring, statistical information refreshing monitoring and optimizer service; the data change processing module is responsible for processing data operation and synchronizing changes to the database storage engine; the data change monitoring module is responsible for recording the increasing and decreasing quantity of data records of each table; the statistical information refreshing monitoring module is responsible for regularly monitoring the data change condition and determining whether to trigger the updating of the statistical information; a query plan optimization module; a database execution module; a database stores an engine. According to the method, the collection performance of the time sequence data statistical information under the large data volume can be greatly improved, and meanwhile, the service query performance of the application is ensured.

A collective data leakage attacks on a Retrieval-Augmented Generation (RAG) application for a generative artificial intelligence (GenAI) application is detected and prevented based on an analysis of incoming queries to distinguish normal and potentially malicious querying behavior. Similarity distances associated with each query are determined, such as the distances between the query vector embeddings and the nearest neighbors in the vector embedding space, distances between each query vector embedding and other query vector embeddings for other queries from the same user, or distances between each query vector embedding and the nearest neighbor cluster of vector embeddings in the vector space. A data leakage attack on the RAG application may be determined based on the similarity distances associated with each query. In response to the identification of a potential data leakage attack, the release of data from the RAG application may be halted.

A computer-implemented method, according to one approach, includes: receiving information from an edge node, where the information outlines specific retrieval-augmented generation (RAG) data applied at the edge node, as well as a condition of the edge node, in real-time. A knowledge database which maps embeddings of RAG data to various edge node conditions is further updated with the received information. Moreover, one or more trained artificial intelligence based models are used to dynamically evaluate the received information and the knowledge database. The artificial intelligence based models are also used to output a relevant subset of RAG data. The relevant subset of RAG data is further sent to the edge node.

The present application discloses a method and system for protecting AI interactive data based on a secure context protocol. The method comprises the following steps: a client application sends a user request carrying a session identifier to an application gateway; the gateway queries the required context scope and security processing policy according to the request type, and transmits policy instructions; after the SCS verifies the gateway's authority, it retrieves the context data and processes it according to the policy instructions to generate a secure context data block; the gateway assembles the user input and the secure context data block into a final request according to the SCP protocol and sends it to the AI ​​model; the AI ​​model processes the request and returns a response; after receiving the response, the gateway updates the session context and the stored context data; finally, the gateway returns the response of the AI ​​model to the client application to complete the interaction. This method can minimize the exposure of sensitive context data within the system while ensuring the effect of AI interaction, thereby improving the data security and compliance of AI applications.