190 results about "Occurrence data" patented technology

The invention discloses a dynamic key threshold fragmentation privacy tracing method based on block chain collaborative verification, and belongs to the field of information security. According to the method, a dynamic key is taken as a hub, decentralized identity, zero-knowledge verification, deep watermark and threshold collaborative decryption are deeply coupled, a temporary key generated by each conference is split into a plurality of fragments, the fragments are stored in a distributed manner by a block chain node and a tracing unit, only a hash fingerprint combined by the fragments is subjected to chaining and evidence storage, and the dynamic key is subjected to zero-knowledge verification and deep watermark and threshold collaborative decryption. A light evidence chain which cannot be tampered but has no privacy exposure is formed; participants are anonymously accessed through a verifiable certificate without leaking specific information, and truth of anonymous identity is ensured through signature of a trusted unit; when data leakage occurs, the tracing unit extracts a watermark, compares a zero knowledge proof, verifies the relevance between a leaked ciphertext and a chain fingerprint, triggers a multi-party threshold decryption recovery key, and finally accurately positions a person in charge in combination with the encrypted and stored DID mapping table without exposing irrelevant information in the whole process.

The invention relates to the technical field of data processing, in particular to an electric energy meter fault detection method based on multi-sensor data fusion, and the method comprises the steps: judging whether an electric energy meter generates data drift abnormity or not in a current time period according to the data change trend of each monitoring index in the current time period; if the data drift abnormity of the electric energy meter occurs in the current time period, acquiring historical abnormal data of the data drift abnormity of each monitoring index, and acquiring the historical abnormal data influenced by the temperature under each monitoring index according to the own performance of each piece of historical abnormal data; according to the method, the relation curve of the temperature and the historical abnormal data influenced by the temperature under each monitoring index and the real-time data performance of each monitoring index in the current time period are integrated, the reason of the data drift abnormity of the electric energy meter in the current time period is determined, then fault detection is carried out on the electric energy meter, and the maintenance efficiency of the electric energy meter is improved.

The invention provides an avalanche disaster risk method, system and device and a medium, and relates to the technical field of avalanche disaster response and prevention. The method comprises the following steps: acquiring avalanche occurrence data and disaster-pregnancy background data of a target area, and determining avalanche disaster-pregnancy factors according to the disaster-pregnancy background data; based on the avalanche occurrence data of the target area, taking an avalanche point as a positive sample, collecting a non-avalanche point as a negative sample, constructing training data, constructing a random forest model, and training the random forest model by using the training data to obtain an avalanche dynamic evaluation model; and based on the avalanche dynamic evaluation model, evaluating the avalanche disaster risk of the target area. The problem of how to obtain a dynamic avalanche risk assessment model by focusing on the change of meteorological factors in the snow season avalanche high-incidence period and provide key factors needing to be monitored for avalanche early warning in different months of the snow season is solved.

The invention discloses an altered rock mass engineering geologic feature rapid identification method, and belongs to the technical field of engineering rock mass identification. Comprising the steps of obtaining topographic data of a rock mass feature region to be recognized, obtaining an earth surface plane model by fitting the topographic data, and generating a three-dimensional route based on the obtained earth surface plane model; controlling the unmanned aerial vehicle to fly close to the surface of the rock mass through the three-dimensional route, and shooting an image according to a preset position; performing data preprocessing on the shot image, performing image segmentation on the preprocessed image, and constructing a structural plane occurrence data set; and performing data processing based on the structural plane occurrence data set, and obtaining a rock mass feature recognition result through an FCM-WOA algorithm of structural plane occurrence automatic clustering and grouping. According to the method, the normal vector robust estimation method is optimized to improve the region growth efficiency and accuracy of the rock mass structural plane, the region growth algorithm is improved to optimize the initial structural plane recognition result, and the rock mass structural plane is quickly and accurately recognized from mass point cloud data of the rock mass outcrop.

The invention relates to the field of rock mass structural surface recognition, in particular to a high and steep slope rock mass structural surface intelligent recognition method based on double clustering. According to the method, high-precision image data of a high and steep slope is obtained through an unmanned aerial vehicle approaching photogrammetry technology, and a three-dimensional digital model of the high and steep slope is constructed by utilizing a three-dimensional reconstruction and calculation technology. And calculating normal vectors of all triangular surfaces based on the triangular surface vertex information of the model, and performing clustering analysis to divide structural surface groups with similar occurrence. And further performing clustering analysis according to the surface center coordinates of the triangular surface, and dividing to obtain the structural surface. And finally, calculating the inclination angle, inclination direction and trend data of the structural surface through an accurate mathematical model. According to the method, the flexibility and the safety of high and steep slope structural plane measurement operation are enhanced, a measurement area of any scale can be completely covered, objective, accurate, rapid and low-cost structural plane intelligent identification and attitude data acquisition are realized, and the method has important significance in engineering application related to high and steep slopes.

The invention discloses a file marking method and device, equipment and a storage medium, and relates to the technical field of financial science and technology. The method comprises the following steps: acquiring watermark information of a to-be-marked file, wherein the watermark information at least comprises time information; the watermark information is processed, and the watermark information is converted into invisible characters; and inserting the invisible character corresponding to the watermark information into the to-be-marked file to obtain a marked file corresponding to the to-be-marked file. According to the technical scheme, the invisible characters corresponding to the watermark information are inserted into the to-be-marked file to obtain the marked file corresponding to the to-be-marked file, marking of the to-be-marked file is achieved under the condition that data in the to-be-marked file is kept unchanged, and invisible marking of the to-be-marked file is achieved; therefore, a tracing basis is established for the data in the file, once data leakage occurs, the operation time of the data can be determined by converting invisible characters into watermark information, a leakage channel is positioned through the operation time, and the security and traceability of the data are improved.

The invention relates to the technical field of pest control, in particular to a forest pest prediction system based on data analysis, which comprises a data preprocessing module, a dynamic weight distribution module, a pest feature recognition module, a prediction model training module and a prediction result output module. According to the method, the feature weight is dynamically adjusted through error distribution analysis, the influence of each feature on a pest event is accurately quantified, the adaptability of weight distribution is improved, multi-feature correlation analysis is combined, key features highly related to pest and disease damage are screened, interference of irrelevant factors is reduced, the model input quality is enhanced, and the weight error change trend is dynamically calculated. According to the method, time sequence optimal weight configuration is formed, high-precision prediction of the occurrence trend of diseases and insect pests is realized, the risk distribution trend is quantified and risk areas are divided based on comparison of prediction data and actual occurrence data, a scientific space-time evaluation result is provided for prevention and control of diseases and insect pests, and accurate prevention and control resource configuration is facilitated.

The invention relates to the technical field of document management, and relates to a legal document key point automatic extraction and association method and system.The new legal document data of a target case is obtained, a preset document fingerprint algorithm is used for automatically comparing the new legal document data with a historical reference document, differential text data fragments are extracted, and the text data fragments are extracted; the method comprises the following steps of: performing deep semantic analysis on different text data fragments to generate candidate triple data containing entities and relationships, intelligently mapping the candidate triple data into a pre-constructed case knowledge graph, quickly positioning graph anchor nodes with data change, and then, performing data change on the basis of change types of the different text data fragments. And executing atomic updating operation on the map anchor node, including updating the dynamic mark of the node state attribute, and finally generating the change source node data with the latest state identifier. The problems that the current legal case data updating depends on manpower, is low in efficiency and is easy to make mistakes are effectively solved.

A method for performing attribute constrained queries for event sequence visualization may include receiving an event sequence dataset including event sequences. The method further includes determining singleton events in the dataset, where each singleton event is associated with an attribute. The method also includes generating event pattern sets corresponding to different distinct singleton events and that maintain a fixed positional order for each event sequence. The event pattern sets include pattern occurrence data for each event sequence positioned according to the fixed positional order. The method also includes identifying the fixed positional order maintained by each event pattern set, and generating an attribute constraint search structure, such as a B-tree, B+tree, or table, that includes keys and pointer values. The method may also include searching the search structure to identify key values satisfying a received attribute constraint, and outputting the sequence identifiers corresponding to the identified key values.

The invention provides a congestion control method, a communication device and a storage medium, relates to the field of communication, and is used for performing congestion control on data transmission between communication nodes to avoid data congestion. The method is applied to a first node and comprises the following steps: acquiring flow configuration information of a data flow; and under the condition that the transmission scheduling of the data flow cannot meet the requirement of the flow configuration information, congestion control information is sent to the second node, and the congestion control information is used for indicating congestion control of the data flow.

The invention relates to a watermark tracing method and device, electronic equipment and a computer storage medium, and belongs to the technical field of data security, and the watermark tracing method comprises the steps: obtaining the identity feature information of each data receiver and the data feature information of to-be-transmitted source data when a data transmission request of the to-be-transmitted source data is received; adding watermark data in the to-be-transmitted source data based on the identity feature information and the data feature information of each data receiver, and generating to-be-transmitted data corresponding to each data receiver; and when the to-be-transmitted data leaks, leakage tracing is carried out based on the watermark data in the to-be-transmitted data. According to the method, the watermark data is generated by combining the feature information of the data and the identity feature information of different data receivers, the identity features of the data receivers are reserved, meanwhile, the confidentiality of the watermark data is improved, and when the data leaks, the data receivers with data leakage can be determined through the identity feature information in the watermark data.

The present disclosure relates to a data processing method for a spreadsheet, a medium, an electronic device and a program product, which relate to the field of computer technology. In the method, a first data amount of target table data for which a data change occurs in a spreadsheet is determined, and the target table data is sent to a client according to a data sending mode corresponding to the first data amount of the target table data, so that the client performs data update on the spreadsheet according to the target table data. In this way, the target table data can be sent to the client in different scenarios using different data sending modes, so as to ensure the reliable transmission of the table data between a server and the client, thereby ensuring the timeliness and integrity of the table data.

The invention discloses a social group member dynamic management method and system, and relates to the field of social network analysis, and the method comprises the steps: obtaining online interaction data and offline co-occurrence data of social group members, cleaning the online interaction data and the offline co-occurrence data, and converting the cleaned online interaction data and offline co-occurrence data into a structured data set; importing the structured data set into a graph database to obtain an initial weight, calculating a dynamic attenuation weight, and constructing a basic relation network; and converting an edge weight matrix in the basic relation network into a quantum bit entanglement state, measuring the quantum bit entanglement state to form a quantum probability amplitude, setting a quantum entanglement judgment threshold, and generating a quantum relation thermodynamic diagram through a Grover algorithm. Through the technical scheme of combining quantum calculation and dynamic entropy analysis, accurate management and risk prevention and control of the social group membership are realized, an edge weight matrix of a basic relation network is converted into a quantum bit entanglement state, and a quantum relation thermodynamic diagram is generated by using quantum measurement and a Grover algorithm.

The invention relates to the technical field of full-link monitoring, and discloses a Skwalking-based micro-service system full-link monitoring method, which comprises the following steps of: 1, automatically collecting full-link tracking data without invasion, loading an Agent probe through a bytecode enhancement technology when a micro-service instance is started, and loading the Agent probe through a bytecode enhancement technology; and the Agent probe automatically intercepts service calling under the condition of not modifying a service code. According to the technical scheme, a Kafka cluster is introduced between a data acquisition end and a processing platform to serve as a buffer channel, and an L1 and L2 distributed OAP processing architecture capable of being horizontally expanded is designed, so that the technical effect of guaranteeing the integrity and real-time performance of mass monitoring data in a super-large-scale micro-service environment is achieved; compared with a transmission architecture in which a monitoring probe is directly connected with a central server in the prior art, the transmission architecture solves the problem that the accuracy of a monitoring result is damaged due to the fact that data congestion, delay and even packet loss are easy to occur during data peak flood due to the lack of an effective buffering and peak clipping mechanism.

The invention discloses a data asset management method and device based on a knowledge graph, terminal equipment and a storage medium, and belongs to the field of knowledge graphs. The method comprises the steps that all data sources serve as federated learning nodes, initial local models are constructed, and all initial local model parameters are aggregated through a federated aggregation algorithm; generating initial global model parameters, repeatedly carrying out iterative updating operation on the initial local model, generating a global knowledge graph, and obtaining change data when determining that a target data source with a data change event exists by monitoring the data change event of the data source; and according to the change data, updating the current global knowledge graph, and generating an updated target global knowledge graph. Therefore, by implementing the method and the device, the problem of data leakage when the multi-source knowledge graph is constructed at present can be solved.

A method for performing time constrained queries for event sequence visualization may include receiving an event sequence dataset including event sequences. Each event sequence includes at least two sequentially occurring events. The method further includes generating a forward index having event pattern sets that include pattern occurrence data for each event sequence positioned according to a fixed positional order. The method includes generating a time constraint search structure, such as a B−tree, B+tree, or table, that includes keys and pointer values. The method also includes inserting, into the search structure, a sequence identifier corresponding to each event sequence based on the fixed positional order and time interval data for the at least two sequentially occurring events of each event sequence. The method may also include searching the search structure to identify key values satisfying a received time interval constraint, and outputting the sequence identifiers corresponding to the identified key values.

The invention discloses an electric energy meter abnormity monitoring and early warning method based on real-time electrical logging data change and a terminal. The method comprises the following steps: analyzing a master station configuration command to determine a target electric energy meter and an electrical logging data item and an anomaly type thereof, and setting a data acquisition frequency and an anomaly judgment parameter; periodically collecting real-time data of an electrical logging data item of the target electric energy meter; the method comprises the following steps of: (1) comparing real-time data with historical data, and if a difference value or a change rate exceeds a threshold range, judging that data jump abnormity occurs; (2) counting the continuous communication failure times of the target electric energy meter in the acquisition period, judging whether the continuous communication failure times exceed a time threshold value in the abnormal judgment parameters or not, and if yes, determining that communication fault abnormity occurs; and generating a corresponding early warning message and reporting the message to a master station in real time. According to the invention, the first-time field abnormal state sensing capability is provided for the main station, and the active operation and maintenance level and the risk early warning capability of the intelligent power utilization information acquisition system are remarkably improved.

This invention discloses a deep learning-based method for predicting the phenological synchronization of specialized butterflies and their host plants, belonging to the interdisciplinary field of biodiversity conservation, ecological prediction, and deep learning technology. The method includes: collecting environmental climate variables, butterfly occurrence data, and phenological time-series data of their host plants; preprocessing the data to create training and validation sets; constructing a dual-label system with the day of year (DOY) of butterfly occurrence peaks (e.g., emergence peak, egg-laying peak) as the primary label and the normalized value of synchronization deviation as the secondary label; building a deep learning model with ecological weights, including an embedding layer, an LSTM layer, and a fusion layer; inputting a vector concatenated from daily or weekly climate time-series features and ecological dynamic features; and outputting the primary and secondary labels through a dual-output layer; designing a hybrid loss function that integrates the main regression loss, ecological synchronization constraint loss, and small-sample regularization loss; training the model using the Adam optimizer and implementing an early stopping mechanism; and validating and evaluating the model using regression accuracy and ecological synchronization accuracy indicators. The method includes modules for data acquisition, preprocessing, label construction, model training, prediction evaluation, and storage. This invention improves the accuracy of phenological synchronous prediction by embedding ecological dynamic feature weights and dual-label constraints, adapts to small sample scenarios, and provides technical support for the monitoring and protection management of rare butterfly species (such as the Golden Birdwing and the Chinese Tiger Swallowtail).

The present disclosure relates to a data analysis method, device, storage medium and electronic equipment, so as to reduce the calculation amount of data analysis request and improve the data analysis efficiency. The method comprises: receiving a data analysis request; in response to the data analysis request, updating the data analysis result of a pre-stored first business model according to the changed data corresponding to the target pheromone, to obtain the updated data analysis result corresponding to the first business model, the target pheromone being the pheromone recording the data change in response to the business data change, the first business model being a business model including the target pheromone, and the business data change including changing the data in part of the pheromones; and outputting at least the updated data analysis result corresponding to the first business model.

Disclosed in the embodiments of the present application are a data storage method and apparatus, a device, and a non-transitory readable storage medium. According to the embodiments of the present application, F parity blocks occupying blank storage areas are added to a RAID system, which not only increases error tolerance but also eliminates the need for additional parity disks. During data storage, corresponding original check codes are solved according to an original encoding method, and additional check codes located on the parity blocks are solved simultaneously. Thus, it is possible to recover more erroneous data based on the original check codes and the additional check codes. When an error occurs in a disk in which any block in a stripe is located and data loss occurs in other blocks of the same stripe, the corresponding data can still be recovered.

The application discloses a kind of magnetic disk array data leakage detection method, product, equipment and medium, it is related to computer technical field, including obtaining audit log content information, data leakage detection of operating behavior is carried out to audit log content information, obtain first detection result;In the case where first detection result is no data leakage risk, the outgoing data packet generated by disk array system is acquired;Data leakage detection of data feature is carried out to outgoing data packet, and second detection result is obtained;In the case where second detection result is no data leakage risk, it is determined that data leakage does not occur in disk array system;In the case where first detection result is there is data leakage risk, and / or second detection result is there is data leakage risk, it is determined that data leakage occurs in disk array system, solve the technical problem that disk array data leakage detection accuracy is low, resource overhead is too large, reach the technical effect of improving detection accuracy, reduce resource overhead.

The invention discloses a buried point data processing method and device, a vehicle and a storage medium, and the method comprises the steps: responding to the triggering of a target buried point event of the vehicle, and obtaining buried point data corresponding to the target buried point event; target storage arrays corresponding to the target burying point events in the burying point data storage file are determined, and the storage arrays corresponding to different burying point events are different; and storing burying point data corresponding to the target burying point event in the target storage array. According to the method, after the target burying point event is triggered, the target storage array corresponding to the target burying point event is determined from the burying point data storage file, and the burying point data corresponding to the target burying point event is stored in the target storage array, so that the phenomenon of data loss of the burying point data before the burying point data is uploaded to the server is avoided; the accuracy of data analysis performed by the server according to the uploaded burying point data is improved, so that the accuracy of follow-up problem investigation is ensured.

According to the privacy computing data processing method in the data element market provided by the invention, the collected data is encrypted, so that the security of the data in the transmission and storage process is ensured; by adopting a safe storage mode, the safety of the data in the storage process is ensured; according to characteristics and requirements of data, privacy protection algorithms including homomorphic encryption and differential privacy are selected, and calculation and analysis of encrypted data are achieved. Healthy development of the data element market is promoted through data sharing and utilization; when data leakage occurs, measures including stopping using related data and informing a data source party are taken in time so as to reduce loss; in a data processing process, data security risk assessment is carried out regularly, and potential risk points and data leakage risks in risk assessment are identified; and when the data life cycle is ended, the data are safely deleted, so that the data are ensured not to be leaked and abused any more.

The invention discloses an important data error correction method suitable for an aerospace power supply and distribution single machine. According to the method, the Hamming code principle and the binary coding principle are utilized, and the characteristics of a microcontroller of the aerospace power supply and distribution stand-alone are combined, so that an error correction coding and decoding method is designed. According to the method, the single-machine micro-control system can correct a certain degree of data bit flipping errors under the condition that the data bit flipping errors occur under the influence of space environments such as space single particles, errors of important data caused by the space environments are reduced, and then part of autonomous control operations threatening spacecraft safety are prevented from occurring.

Embodiments of the present application disclose a data processing method, device, equipment, medium and program product. The method comprises: in the case where it is detected that a second window has data update, acquiring first data information sent by the second window, the first data information comprising data updated by the second window; comparing the first data information with subscription data information of each subscription information in a plurality of subscription information set in advance to determine target subscription information, the subscription information comprising subscription data information and identification information of a subscription object, the subscription object comprising a subscription component and / or a subscription page; determining a target subscription object according to the identification information of the subscription object in the target subscription information; and sending the first data information to the target subscription object for data update by the target subscription object according to the first data information. The embodiments of the present application can reduce the risk of page lagging under the premise of realizing data synchronization between windows, thereby improving user experience.

The invention discloses a data response method and device, electronic equipment, a storage medium and a system. According to the method and the device, the sensing operation is executed when the data modification operation is detected through the pre-generated data processing instance, so that whether data change exists at present or not can be accurately judged, and unnecessary total data scanning and comparison are avoided; if data change occurs, change information, including change paths and change types, corresponding to data change operation can be intelligently recorded, and fine context information is provided for subsequent operation; in addition, difference calculation and incremental updating can be executed according to the change information and the corresponding information before change, the difference calculation can accurately find out the data difference before and after change, and the incremental updating is only operated for the difference part, so that re-rendering and processing of total data are avoided, the calculation amount and resource consumption of data updating are reduced, and the data updating efficiency is improved. And the response speed of data change can be improved.

Embodiments of the present application disclose a kind of inter-table data synchronization method, device, electronic equipment and storage medium.The method comprises: determining target business system and the business system of data business in each business system with target business system in target business system;Corresponding proxy table of target database in target business system is created in target business system with the business system of data business;Whether the target entity table for recording the business data of target business system stored in target database is monitored to occur data operation;If yes, then trigger the target trigger pre-established in target business system, data operation is carried out to the proxy table in target database, and the proxy table after data operation is projected to the business system of corresponding data business system stored in the business system of corresponding data business system.This embodiment of the present application can synchronize the data in the business system of data business with the data in target business system in real time, which helps to accurately complete the business operation between business systems.

The present invention relates to the technical field of data processing, and discloses a database processing method and system based on message queue and synchronous processing. The method includes: when data changes occur in the main database, calling the API of Active MQ to insert data change information; collecting the data change information to determine the message queue duration, and collecting all the data change information to construct a message data chain; obtaining the importance data of each data change information, splitting and combining the message data chain into a new message data chain; extracting the feature vectors of each data change message in the priority processing data chain to determine the processing duration, and obtaining the final message data chain according to the processing duration; adding the final message data chain to the List data structure of Redis, and obtaining a distributed lock in the order of the final message data chain for message processing. This application realizes dynamically adjusting the message processing strategy according to business requirements, improves the efficiency and accuracy of data synchronization, and ensures that data synchronization can be achieved in a high-concurrency environment.

This invention relates to the field of data synchronization technology, specifically to a method, device, and storage medium for efficient data synchronization in an office system. The invention collects several changed fields and their attribute data, time-series data, and concurrent operation data of the current business process within the current synchronization cycle, as well as the data of the current business process itself. Based on the changed field attribute data and concurrent operation data, the business weight of each changed field in the current business process is obtained. Atomic synchronization units are constructed by analyzing the closeness of business linkage between each changed field and other changed fields. The exclusivity and overlap rate of atomic synchronization units containing the same changed fields are analyzed to select conflict-free synchronization units. Based on the numerical distribution of the changed field business weights within the conflict-free synchronization units and the timeliness characteristics of the time-series data, the priority scheduling coefficient of the conflict-free synchronization units is obtained. Combined with the basic risk characteristics in the changed field attribute data, this guides the orderly execution of the final update synchronization.

The application relates to the technical field of document management, and relates to a legal document gist automatic extraction and association method and system. Newly added legal document data of a target case is acquired, preset document fingerprint algorithms are used to automatically compare the newly added legal document data with historical benchmark documents, difference text data segments are extracted, deep semantic analysis is performed on the difference text data segments, candidate triple data containing entities and relations are generated, the candidate triple data is intelligently mapped to a pre-constructed case knowledge graph, graph anchor point nodes with changed data are quickly located, and then, based on the change type of the difference text data segments, atomic update operations are performed on the graph anchor point nodes, including dynamic marking update of node state attributes, and finally, change source node data with the latest state identification is generated. The method effectively solves the problems of dependence on manual work, low efficiency and errors in current legal case data updating.