11results about How to "Reduce data size" patented technology

The invention relates to the technical field of dissolved oxygen prediction, and provides a dissolved oxygen prediction method based on data decomposition and related equipment, and the method comprises the steps: obtaining a plurality of water quality indexes of a target water body, and determining a plurality of target water quality indexes from all the water quality indexes; according to all the target water quality indexes, generating a dissolved oxygen data sequence of the target water body, and decomposing the dissolved oxygen data sequence to obtain a trend component and a seasonal component; predicting the trend component by using a trend prediction model to obtain a first dissolved oxygen predicted value, and predicting the seasonal component by using a seasonal prediction model to obtain a second dissolved oxygen predicted value; and fusing the first dissolved oxygen predicted value and the second dissolved oxygen predicted value to obtain a final dissolved oxygen predicted value of the target water body. According to the method, the dissolved oxygen prediction accuracy can be improved.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for identifying labels for a data set without disclosing the data set to any individual computing system. A method can include receiving, by a first computing system in a multi-party computation (MPC) system, a query including a first share and a second share of a given user profile. The second share is encrypted with a key that prevents the first computing system from accessing the second share. The second share is transmitted to a second computing system in the MPC system. The first computing system and the second computing system generate a machine learning model and identify respective first and second labels. The first computing system receives the second label from the second computing system as a response. The first computing system responds to the query with a response including the first label and the second label.

This invention provides a method and system for acoustic data compression and transmission for marine buoys, comprising the following steps: fusing floating-point data output from multiple channels into a single data stream; dividing all data in the single data stream into M frames of fixed length (N data points per frame), and performing data compression processing on each data point in each frame to compress the floating-point value of each data point into a three-digit integer code; encoding all data points in each frame to form a data packet, the single data stream forming M data packets, and transmitting the M data packets back to the ground station via satellite; this invention has the following advantages: by optimizing the data encoding and compression mechanism, this invention significantly reduces the data size while maintaining key acoustic characteristics, enabling the processed acoustic signal amplitude data to be reliably output under limited serial communication and low-bandwidth satellite channel conditions, thereby improving the availability and data transmission efficiency of the marine acoustic monitoring system.

The invention provides a network node processing method and device, electronic equipment and a computer program product, belongs to the field of network security, and aims to solve the problem that the existing method is difficult to quickly sense and respond to network security threats. The method comprises the following steps: preprocessing each node in a network, and determining candidate network nodes; identifying and evaluating network nodes which are not preprocessed in the network, and determining supplementary network nodes; taking the candidate network node and the supplementary network node as target network nodes; and obtaining target data of the target network node, analyzing the target data, and determining a network security risk according to an analysis result.

The present disclosure provides a data reconstruction method based on Radon domain sparse representation and related equipment, relating to the technical field of communication. The method comprises: obtaining low-resolution Radon coefficients; inputting the low-resolution Radon coefficients into a neural network of an encoding-decoding structure to obtain first high-resolution Radon coefficients; and increasing the sparsity of the first high-resolution Radon coefficients through an adaptive soft threshold function cascaded at the back end of the neural network to obtain second high-resolution Radon coefficients. The method can reduce the data size, operation time, and operation cost of time-domain inversion of reduced-time variable Radon transform, and improve the stability and resolution of reconstructed data.

The invention discloses a data networking terminal unbalanced data intersection method and a related device, and the method comprises the steps: screening the data of a first data party, and obtaining a sample data set; sending the sample data set to a second data party, and receiving hit information and a second data set returned by the second data party; sending hit information to the first data party, and receiving a first data set returned by the first data party; and carrying out intersection on the first data set and the second data set. The data of the first data party and the data of the second data party are simplified before intersection, the first data set and the second data set are obtained, furthermore, intersection is conducted on the first data set and the second data set, the scale of data needing to be processed in the intersection process is greatly reduced, and the efficiency of unbalanced data intersection is improved.

The application provides an image processing method, device and equipment and a computer readable storage medium. The method comprises: obtaining an input image to be processed and natural language reference text; mapping the input image to a visual token set and mapping the natural language reference text to a text token set; filtering the visual token set based on each text token in the text token set to obtain a candidate visual token subset corresponding to each text token; performing semantic analysis on the natural language reference text to obtain a logical constraint condition; performing alignment processing on the text token in the text token set and the visual token in the candidate visual token subset based on the logical constraint condition to obtain a mapping relationship; and determining target position information of the natural language reference text in the input image based on the mapping relationship. Through the application, the redundant calculation overhead of cross-modal interaction can be reduced, fine-grained matching can be guided by the logical constraint, and the accuracy of semantic alignment between the text and the image can be improved.

The invention relates to the technical field of carbon emission monitoring, and discloses a carbon emission monitoring and early warning analysis system based on edge calculation. The system comprises a dynamic topology mapping module which is used for establishing dynamic topology mapping of an emission source in a monitoring area and recording a state transition path; the self-adaptive probe deployment module is used for deploying a probe associated with the monitoring dimension and the path according to the mapping at the edge node; the early warning identification module is used for comparing the time slice sequence with a path identification early warning point; the evolution trajectory generation module is used for generating a parameter evolution trajectory; the stage analysis and traceability module is used for distinguishing a steady state stage from a transient stage and executing inertia and sudden change analysis; and the autonomous optimization module is used for constructing a double-layer parameter correction model and driving the monitoring process to be optimized.

The application discloses a single station terminal fingerprint positioning method based on a square weighted K nearest neighbor algorithm and belongs to the technical field of fingerprint positioning. The method comprises the following steps: based on a channel frequency response (CFR) matrix, a position fingerprint matrix (FRCPM) with higher positioning precision is extracted; a fingerprint compression is performed on the fingerprint matrix (FRCPM) to obtain a compressed fingerprint (FCPV) with smaller data scale and being more beneficial to improving positioning speed; and a square weighted K nearest neighbor matching method with higher positioning precision is obtained by improving the weighted K nearest neighbor method.

The application discloses a three-dimensional point cloud semantic segmentation method, device, equipment, medium and product, and relates to the technical field of computer vision and three-dimensional point cloud processing. The method comprises the following steps: performing sparse voxelization processing on three-dimensional point cloud data to establish a point-to-voxel mapping relationship; performing geometric feature extraction on each non-empty voxel; adopting a clustering algorithm to aggregate voxel features, and determining a k-nearest neighbor graph based on the center coordinates of super points; performing parallel coding processing of feature extraction by adopting a double-flow coding strategy to obtain voxel flow local features and super point flow global features; projecting the super point flow global features back to the voxel dimension, and splicing and fusing the voxel flow local features; performing enhancement processing on the fused features based on a self-attention mechanism, splicing the attention features obtained after the enhancement processing with the fused features, and then performing semantic classification; and determining a prediction result of semantic segmentation according to the classification category. The application can improve segmentation accuracy while ensuring computing efficiency.

The application discloses a bidirectional dynamic constraint Euclidean-DBSCAN point cloud clustering and segmentation method and device, which comprises the following steps: acquiring original three-dimensional point clouds around a low-speed unmanned vehicle, uniformly downsampling and filtering the original three-dimensional point clouds through a voxel grid filter with adaptive resolution parameters to obtain an effective detection point cloud set; outputting a first-level rough clustering cluster set for the effective detection point cloud set; initializing a final target point cloud cluster set for storing a final clustering result, and the initial state is an empty set; serially traversing each first-level rough clustering cluster in the first-level rough clustering cluster set, and performing bidirectional dynamic constraint decision; solving the geometric center of each point cloud cluster in the final target point cloud cluster set F by using principal component analysis, performing multi-angle scanning calculation of the best heading angle in a preset yaw angle search space, accurately solving the length, width and height of the directional enclosing sum, and publishing the result after coordinate system mirror mapping conversion. The application mainly applies to the technical field of vehicles.