18results about How to "Small data size" patented technology

The invention discloses a new energy station cross-gatekeeper remote data acquisition method and system, and the method comprises the following steps: a station first area data acquisition server collects data from new energy station equipment, and carries out the analysis and conversion of the data, and forms standardized station real-time data; 2, according to the standardized station real-time data, the data are transmitted in a one-way mode through an isolation device, and the station data are set to be transmitted from the inside to the outside; step 3, according to the data transmitted by the isolation device, the station three-area data forwarding server performs deep standardization processing on the data of different protocols, uniformly converts the data into an internal format, and adjusts a data forwarding strategy according to a dynamic configuration requirement; and step 4, according to the data in the unified internal standardized format, publishing the data by using message middleware, and carrying out serialized compression by using a Probuf technology for data acquisition and transmission in a new energy station cross-gatekeeper environment. The efficiency of operation and maintenance personnel is improved, and the reliability management level of auxiliary equipment is improved.

The embodiment of the invention provides a target file generation method and device, equipment, a medium and a product. The method comprises the following steps: extracting longitude and latitude grid data corresponding to a plurality of target meteorological variables from original meteorological data according to a target area and a target resolution in a service demand; and extracting data corresponding to a plurality of moments from the longitude and latitude grid data corresponding to the plurality of target meteorological variables, the earth surface potential data of the target area and the sea-land distribution data according to the time interval in the business demand, and obtaining array files corresponding to the plurality of moments. And generating a target file according to the plurality of array files, and outputting the target file, the target file being used for generating a background field in the WRF. In the application, the target file is generated based on the business demand, and the target meteorological variable included in the original meteorological data is the necessary meteorological variable when the background field is generated by the WRF, so that useless data in the target file is less, the data volume is small, and the efficiency of subsequently processing the target file can be improved.

The present invention provides a modeling method, device, computer equipment and readable storage medium for a building model. The modeling method for the building model comprises: determining a standard layer and a mapping layer in the floors of the building model; obtaining component data of the standard layer; using the component data to create the components of the standard layer in the mapping layer to obtain the mapping components; and in response to the editing operation of the standard layer, modifying the components of the standard layer, and updating the mapping components in linkage according to the components of the modified standard layer. Through the present invention, the user experience in the process of modeling and designing a three-dimensional building model can be improved.

The invention discloses a ship-shore data lightweight communication system and method based on a hybrid compression algorithm, and relates to the technical field of ship-shore data communication, and the system comprises a main control processing module which is used for obtaining ship navigation data suitable for lossy compression and ship navigation data suitable for lossless compression; the data compression module is used for obtaining corresponding ship navigation data adopting lossy compression and ship navigation data adopting lossless compression; the wireless transmission module is used for transmitting the ship navigation data subjected to lossy compression and the ship navigation data subjected to lossless compression to the shore end monitoring module through a wireless channel; and the shore end monitoring module is used for correspondingly decompressing the ship navigation data subjected to lossy compression and the ship navigation data subjected to lossless compression. According to the invention, the pressure of network load and equipment power consumption caused by large data transmission between the ship and the shore is solved, and the safety and reliability of ship-shore data communication are ensured.

The present application discloses a multi-UAV task planning method and device based on shared threat data, the method comprising: classifying prior data and / or threat data, and storing them in storage blocks respectively to form a shared threat data pool; assigning target tasks to target UAVs, and iteratively executing route planning steps until the task is completed; including: determining the data category required by the target UAV, and retrieving the corresponding target threat data from the shared threat data pool; planning the target route of the target UAV according to the target threat data; classifying the new threat data detected by the target UAV and storing them in the corresponding storage blocks, updating the shared threat data pool, and executing the route planning steps. The method solves the problem that the existing processing of shared threat data of UAVs is cumbersome and difficult to meet its real-time requirements, realizes accurate retrieval of required data information, improves the efficiency of data transmission and processing, and improves the timeliness and reliability of the UAV cluster during the task process.

The embodiments of the present specification provide an anonymous identity authentication method and device. According to the method, a first device generates a binary indication vector and an auxiliary vector having a predetermined relationship with the indication vector according to the sequence index of a first account in a target account set; and generates a signature value C according to the indication vector, the auxiliary vector and a private key of the first account. A first public key vector is also calculated according to a first random number selected by a verification device and a public key sequence of the target account set, and a blinding value is calculated based on the first public key vector and a random number array selected by the first device. The first device further generates a first and second group of commitment values according to the indication vector, the auxiliary vector and a challenge array and a variable value selected by the verification device. The first device provides the signature value C, the blinding value and the first and second group of commitment values to the verification device, and the verification device verifies whether the first account belongs to the target account set according to the foregoing.

The invention relates to the technical field of virtualization and trusted computing, and discloses a TPCM-based virtual machine full life cycle instance static measurement method. A novel virtual machine full life cycle model is defined, and a request instance measurement module is added in each life stage processing function of a virtual machine based on the model and is used for realizing a measurement request initiation function; a strategy file located in a local protection component is constructed and used for specifying how to organize instance core data used for measurement, and a hardware trusted cryptography module located in the protection component is called to perform hash operation on the instance core data. According to the method, the following three problems existing in an existing virtual machine instance static measurement scheme are solved: (1) virtual machine instance static measurement operation cannot cover the full life cycle of a virtual machine; (2) the measurement overhead caused by virtual machine instance expansion is too large; and (3) the trusted measurement service provided by the TPM has the risk of being bypassed, so that the security of measurement operation is difficult to guarantee.

The application belongs to the technical field of Internet, and particularly relates to an industrial Internet cross-domain metadata trusted fusion method and system, comprising the following steps: collecting structured metadata, time series metadata and relationship metadata of each industrial domain node, and constructing an intra-domain metadata graph based on field attributes and call relationships; performing semantic coding and time series coding on the intra-domain metadata graph, obtaining corresponding semantic representations and time series representations, and calculating inter-field consistency; identifying stable field clusters, drift field clusters and abnormal nodes according to the inter-field consistency in each industrial domain node; and performing segmented aggregation on the stable field clusters and the drift field clusters by each industrial domain node to generate anchor field summaries and drift trajectory summaries. The application combines metadata graph coding, field clustering and federal dynamic weighting, and realizes industrial cross-domain metadata private trusted fusion through abnormal compensation correction.

This invention discloses a face recognition method and apparatus based on millimeter-wave radar phase features. The method includes: acquiring face radar echo signals; selecting target points in the frequency domain; using the target point data as data to be processed containing face information; extracting phase features from the data to be processed; performing a deconvolution operation on the phase features to obtain the phase change difference of the target points; performing 3D convolution and max pooling on the phase change differences of all target points to obtain dimensionality-reduced phase features; downsampling the dimensionality-reduced phase features using a convolutional autoencoder; and inputting the downsampled data into a convolutional neural network to achieve face recognition. Unlike vision-based face recognition, this invention uses millimeter-wave radar, which has higher resolution, is not limited by lighting conditions, and can effectively protect user privacy.

A front-end and back-end combined hidden danger analysis system and method thereof, the system comprising: a front-end camera module, a video target recognition module, an image definition recognition module, an image similarity recognition module, a front-end slice compression module, a back-end image analysis module, a back-end hidden danger analysis result module and a front-end loudspeaker module, the method comprising: one: image acquisition; two: hidden danger target recognition; three: image definition recognition; four: image similarity recognition; five: video slice compression; six: image analysis; seven: hidden danger analysis; eight: hidden danger broadcast reminder; the video frame is preliminarily detected through the front-end video target recognition module, only the frame containing the hidden danger target is reserved for subsequent processing; combined with the image definition recognition module and the image similarity recognition module, further eliminate the fuzzy and repeated frames, generate high-quality video segments, effectively reduce the image data amount required to be processed by the back-end multi-modal large model, thereby greatly reduce the consumption of token.

This invention relates to the field of artificial intelligence interactive data processing technology, including at least one smart terminal. The smart terminal has a built-in dual-partition storage module, a permission management module, a data compression module, and a cross-device migration module. The invention includes the following steps: S1, dual-partition storage system initialization stage; S2, hierarchical permission control rule configuration stage; S3, lightweight migration data package generation stage; S4, end-to-end offline cross-device migration stage; S5, data synchronization and process closure stage. This invention, through a dual-partition isolated storage architecture design, achieves physical layer isolation between personalized user private data and general AI model algorithms. Combined with a hierarchical and independent permission control mechanism, it effectively avoids the risk of user privacy data leakage due to unauthorized access. Furthermore, the end-to-end encrypted transmission mode eliminates the need for third-party cloud servers, reducing the risk of leakage of user private data during transmission.

The invention discloses a three-dimensional modeling method and device, electronic equipment, a storage medium and a program product, and belongs to the technical field of three-dimensional modeling. The three-dimensional modeling method comprises the following steps: based on multiple frames of original images corresponding to a target scene, obtaining an initial three-dimensional model corresponding to the target scene and camera parameters corresponding to the original images; inputting the initial three-dimensional model and the camera parameters into a neural rendering model to obtain target texture data output by the neural rendering model; and processing the low-surface-number three-dimensional model corresponding to the initial three-dimensional model based on the target texture data to obtain a target three-dimensional model corresponding to the target scene. According to the three-dimensional modeling method, secondary creation does not need to be carried out manually to improve the image quality, the labor cost is saved, the volume of data needing to be processed by the neural rendering model is reduced, and the high-fidelity rendering effect is achieved on the basis of ensuring the image fluency.

This invention provides a lightweight description method for a nuclear power plant 3D model, comprising: acquiring model information of the original 3D model, including node information, graphical information, and attribute information; generating a node tree based on the node hierarchy in the node information to describe the organizational hierarchy of the original 3D model; generating graphical information and attribute information corresponding to each node based on the model information; and generating a lightweight model data file based on the node tree, the graphical information corresponding to each node, and the attribute information, wherein the node tree information file, the node graphical information file, and the node attribute information file are interconnected by node identifiers. A method for loading a nuclear power plant 3D model is also provided. This lightweight description method for 3D models can reduce data redundancy, optimize model organization, and reduce model space occupation while ensuring model accuracy, while meeting the display requirements of the nuclear power plant 3D model data structure, thereby enabling rapid loading of large-scale nuclear power plant scene models.

The invention relates to the technical field of data acquisition, and provides an equipment terminal data acquisition method, system and device and an equipment terminal. The method comprises the following steps: acquiring target equipment terminal data corresponding to a target data acquisition item according to a target acquisition frequency; filling the target equipment terminal data into a corresponding target data acquisition item in the format template to obtain a data template; compressing the target equipment terminal data in the data template to obtain a data packet; and sending the data packet to the server in response to an acquisition demand of the server. According to the method, the target acquisition frequency is set, the volume and time of data acquisition can be controlled, the target equipment terminal data is actual data not including redundant key value pair information, template filling and compression are performed on the target equipment terminal data, the data volume is further reduced, and the data acquisition efficiency is improved. Therefore, the consumption of network bandwidth, flow and time is reduced in the data transmission process, the occupation of network resources is reduced, and the real-time performance of data acquisition is improved.

The invention discloses an intelligent streaming media safe playing system and method, the system comprises a configuration database, a signal sending system streaming media push service and a streaming media server, the output end of the configuration database is connected with the signal sending system streaming media push service, the second input end of the signal sending system streaming media push service is connected with a video stream and an audio stream, and the second input end of the video stream and the audio stream is connected with the streaming media server. And the output end of the streaming media stream pushing service of the signaling system is connected with a streaming media server. The media playing controller is updated by updating streaming media information and schedules of a signal sending system, media data are pushed by adopting a streaming media pushing technology, the method has the advantages of high real-time performance, small data size, high transmission efficiency, high adaptability, cross-platform performance, high data safety and the like, the high-real-time scene problems of live broadcasting, broadcasting, monitoring and the like can be well solved, and the method is suitable for popularization and application. The method adapts to the future demand of the development of a media signaling system, and can continuously complete and quickly configure the media playing equipment with increasing complexity.

This invention belongs to the field of data management technology, specifically relating to a method and system for managing geographic information mapping data based on multi-source spatiotemporal features. The method includes: acquiring mapping data containing spatiotemporal coordinate attributes and generating time-granularity codes; selecting the optimal child node based on comprehensive cost when inserting data; when a node is overloaded, evaluating the spatiotemporal variability cost of candidate splitting strategies to select the optimal strategy; for newly generated leaf nodes, determining the reference object and differential accuracy level based on the spatiotemporal distribution of internal data objects, and storing the differential values ​​of the data relative to the reference object; extracting query feature vectors and matching historical query patterns to cluster centroids for data prefetching; and asynchronously updating the centroids and adjacency pointer transition probabilities in batches after the query. This invention improves the retrieval response performance of mapping data while effectively compressing data storage space by constructing an index structure and combining differential storage with predictive prefetching.

The invention relates to the technical field of unmanned aerial vehicle cluster cooperative control, and discloses a method, a device, equipment and a medium for cooperative sensing between unmanned aerial vehicles, and the method comprises the steps: obtaining the multi-channel heterogeneous sensor data of a target unmanned aerial vehicle, and carrying out the time synchronization of the multi-channel heterogeneous sensor data, and obtaining the first sensor data with the aligned time sequence; based on the first sensor data, generating a structured description of an environment where the target unmanned aerial vehicle is located, and compressing the structured description to obtain compressed sensor data; the compressed sensor data are transmitted to other unmanned aerial vehicles, and the structured data aligned in time sequence can ensure that all the unmanned aerial vehicles make decisions based on the same time reference and environment model, so that collaborative errors caused by data time difference or format difference are avoided, and collaborative consistency is ensured; moreover, the lightweight data transmission delay is lower, the dynamic environment change can be quickly responded, and the real-time cooperative task of the unmanned aerial vehicle cluster is supported.

The invention relates to the technical field of information processing and personalized recommendation, and discloses an attention weight positioning recommendation method and system for searching and browsing footprints. According to the method, the original historical behavior data is deconstructed and compressed into the standardized search and browsing feature vectors, and the corresponding resource utility score is obtained through the dynamic resource utility evaluation model based on the feature vectors, so that accurate recognition and screening of high-value parts in mass data are realized; therefore, the scale of data participating in core calculation can be directly reduced, the size of a memory working set and I / O pressure are reduced, and the problem of calculation delay caused by storage and processing of a large amount of low-value and high-noise data in a traditional method is solved. By constructing an anti-circulation label topological relation graph and implementing a weight propagation and pruning method under strict resource constraints, it is ensured that memory occupation and calculation delay in the feature construction stage are controllable, and the aim of conducting accurate recommendation within millisecond-level delay is achieved.