13 results about "Data coherence" patented technology

The invention discloses a block chain-based carbon emission factor data traceability management system, particularly relates to the technical field of cross-supply-chain carbon data management, and is used for solving the problem that cross-enterprise / cross-industry effective association of carbon emission data under an existing single-chain architecture cannot be realized. The problems that the whole life cycle carbon emission data of the same product is repeatedly calculated and accounting boundaries are overlapped are solved; the method comprises the following steps: acquiring a carbon emission factor data packet of each participant through a data acquisition module; the block evidence storage module writes the data packet into a block chain to generate a non-tampering block; the cross-chain identification module creates a cross-chain traceability identifier containing a product batch number and an arrangement stage mark for the block; the coherence detection module analyzes data coherence during cross-chain request, and if the data coherence is lower than a threshold value, cross-chain verification based on matching of the mark and the batch number is triggered; the batch verification module executes repeatability verification on data in different stages of the same batch after verification is passed; and the traceability integration module integrates the verification data to generate a global carbon footprint traceability record and stores the global carbon footprint traceability record to a cross-chain shared account book.

The invention relates to the technical field of three-dimensional modeling, in particular to a building measurement system and method based on unmanned aerial vehicle surveying and mapping, and the system comprises an environment sensing and monitoring module which collects real-time illumination intensity, air temperature and humidity data, records environment changes, carries out the analysis according to the difference between the real-time data and a standard threshold value, dynamically adjusts the parameters of an unmanned aerial vehicle camera, and carries out the measurement of the unmanned aerial vehicle. Comprising exposure and sensitivity, matching the current environment, and recording environment acquisition parameters. According to the method, illumination, air temperature and humidity are collected, equipment parameters are dynamically adjusted, multi-scene adaptability is improved, a filtering strategy is set according to environment variables, abnormal data are removed, interpolation is carried out on a point cloud fracture area based on space continuity, data coherence is improved, a building structure is recognized through feature library comparison, and structural damage is recognized in combination with an image. And on the basis of form and trend prediction change, a process covers acquisition and analysis, closed-loop linkage is constructed, and environmental adaptability, data integrity and recognition precision are enhanced.

The invention relates to the technical field of data processing, in particular to a river pollution monitoring management method fused with environmental information perception. According to the method, monitoring points are classified according to information collected in a non-rainfall period, and a plurality of monitoring point clusters are obtained. In the target rainfall period, the rainfall influence degree of the monitoring points is determined by analyzing pollutant concentration data changes before and after analysis and rainfall information, and then the target monitoring points needing data correction are screened out. A time correction method is adopted, reference time periods are selected in the non-rainfall time periods, the reference weight of each reference time period is determined by analyzing the time sequence position of the reference time periods and the rainfall influence degree of the latest rainfall time period, and then time correction is conducted; and further performing space correction by using other monitoring points in the monitoring point cluster obtained by classification to finally obtain corrected pollutant concentration data. According to the method, the influence of rainfall on pollutant concentration data is eliminated, and the data reference is increased while the data coherence is ensured.

The invention discloses a multifunctional comprehensive testing machine for mechanical property and durability of fiber concrete, which comprises a testing machine base with a test box assembled on the upper end face; the stand columns are vertically and symmetrically fixed in the test box; the loading units are installed on the stand columns and located on the opposite end faces of the two stand columns; the salt mist spraying unit is arranged in the test box, and the salt mist spraying unit is located between the two loading units; the supporting top shaft is vertically fixed at the central position in the test box; according to the invention, mechanical loading functions of axial tension and compression, bending, torsion, dynamic fatigue and the like and environmental simulation functions of salt spray erosion, temperature and humidity control and the like are highly integrated in a closed test box, so that one-stop test is realized, movement damage and state change of a test piece are avoided, and the test efficiency, data coherence and result comparability are greatly improved.

The invention discloses a Tibetan antelope real-time track monitoring system and method based on an infrared image, particularly relates to the field of infrared image analysis, is used for solving the Tibetan antelope migration track monitoring problem, and is characterized in that Tibetan antelope hot spots are extracted through an infrared camera array, a multi-scale kernel density estimation and self-adaptive secant segmentation technology is combined, a hot spot set is finely processed, and a Tibetan antelope migration track is obtained. The individual and group identification precision is improved; through joint evaluation of inter-cluster velocity direction discreteness and internal flow velocity volatility, and Jensen-Shannon divergence is supplemented to synthesize a co-directional turbulent entropy, accurate combination of moving units is realized, and continuity and integrity of a track are ensured; besides, the hair cycle thermospectral mapping correction utilizes historical data to enhance the monitoring robustness, and the application of the Kalman prediction and Hungary matching algorithm in the sliding time window generates a continuous migration trajectory sequence, realizes refined target identification and long-time data coherence, and brings stable and reliable monitoring means and decision support for field ecological research.

The present invention discloses a carbon emission factor data traceability management system based on blockchain, which specifically relates to the technical field of cross-supply chain carbon data management. It is used to solve the problem that carbon emission data cannot be effectively linked across enterprises / industries under the existing single-chain architecture, resulting in repeated calculation of carbon emission data of the same product throughout its life cycle and overlapping accounting boundaries. The data acquisition module obtains the carbon emission factor data packet of each participant; the block evidence module writes the data packet into the blockchain to generate an unalterable block; the cross-chain identification module creates a cross-chain traceability identifier for the block that includes the product batch number and emission stage mark; the coherence detection module analyzes the data coherence when requesting across the chain, and triggers cross-chain verification based on matching of mark and batch number if it is lower than the threshold; the batch verification module performs repeatability verification on data of the same batch at different stages after verification; the traceability integration module integrates the verified data to generate a global carbon footprint traceability record and stores it in a cross-chain shared account book.

According to the training data synthesis method of the voice assistant model, the voice assistant system and the computer equipment, online actual user data of the current voice assistant model are collected, and the actual user data comprise voice text data received by the current voice assistant model; and based on preset prompt information, the large model is adopted to perform data screening on the actual user data to obtain screened data, and the preset prompt information comprises data integrity, data definition and data coherence. And synthesizing target iterative data according to the screened data by adopting a large model. Using a large model to add a purpose label to the target iteration data; checking the target iteration data subjected to the purpose labeling, and modifying the purpose labeling for the target iteration data which is not qualified through checking; training a voice assistant model by adopting the audited target iteration data; and replacing the current voice assistant model with the trained voice assistant model, and updating the collected actual user data.

This invention discloses a data security assessment method and system based on clustering processing. The method includes data acquisition, data coherence detection, clustering processing, and data security assessment. This invention belongs to the field of data processing, specifically referring to a data security assessment method and system based on clustering processing. This scheme calculates the correlation between each pair of buses and introduces a graph model to represent the power network, which helps to identify critical paths and potential fault points. Adaptive genetic operations further optimize the partitioning of the initial anomaly region, dynamically updating the weight matrix based on real-time data and the influence of external factors, improving the ability to cope with complex and changing power system environments. Anomalies in the detected region are accurately assessed based on adaptive projection metrics, thereby improving the data security assessment effect.

The invention relates to a behavior analysis method and system for yak breeding, and the method comprises the steps: responding to an obtained image, and extracting a yak object in the image; marking the yak objects to obtain yak objects with identity marks, and marking the yak objects as characteristic yak objects; recording moving tracks and behavior characteristics of the characteristic yak objects; performing similarity analysis on the moving tracks and the behavior characteristics of the characteristic yak objects in the time dimension to obtain a similarity analysis result; and grouping the feature yak objects according to a similarity analysis result to obtain a normal group and an abnormal group. According to the behavior analysis method and system for yak breeding disclosed by the invention, coherence behavior analysis is carried out on yaks by using a mode of combining local multi-point identification with group difference analysis, and the data richness of individual yaks is improved by improving data coherence; and meanwhile, different individuals are found through group difference analysis.

The invention discloses a verification method for a conversion field type between data sources and a related device, and belongs to the technical field of data conversion verification. The method comprises the following steps: acquiring field source information and field converted information of data to be verified; based on a pre-trained field type mapping verification model, in combination with the field source information of the to-be-verified data and the information after field conversion, analyzing a field semantic feature set of the to-be-verified data, including a field type semantic data set and a field content semantic data set; and based on the field semantic feature set of the to-be-verified data, a field type conversion verification feature value and a field content coherence feature value of the to-be-verified data are analyzed, and the to-be-verified data are subjected to joint verification processing based on the field type conversion verification feature value and the field content coherence feature value. Therefore, double-layer collaborative verification of semantic consistency and content stability is realized, and comprehensive guarantee of a field conversion result in the aspects of semantic interpretation and data coherence is further realized.

The invention discloses a data security assessment method and system based on clustering processing. The method comprises the steps of data acquisition, data coherence detection, clustering processing and data security assessment. The invention belongs to the field of data processing, and particularly relates to a data security assessment method and system based on clustering processing, according to the scheme, the correlation between each pair of buses is calculated, and a graph model is introduced to represent a power network, so that key paths and potential fault points can be identified; the partition of the preliminary abnormal area is further optimized through self-adaptive genetic manipulation, a weight matrix is dynamically updated based on the influence of real-time data and external factors, and the capacity of coping with a complex and changing electric power system environment is improved; the abnormal condition of the to-be-detected area is accurately evaluated based on the adaptive projection measurement, so that the data security evaluation effect is improved.

A method, system, and storage medium for archiving files for a real-time database. The storage method includes the following steps: receiving written snapshot data through data middleware and creating an archive file for a corresponding time range; storing the snapshot data in a data page of a set size, and archiving the data after the set number of data pages are filled; storing the data to be archived in units of data pages into an archive file within the current corresponding time range; determining whether the time range of the data page to be archived exceeds the time range of the current archive file; if not, stopping data archiving; if so, stopping the current archive file storage and switching to a new archive file for the next time range. The present invention also provides an archive file storage system and computer-readable storage medium for a real-time database. The present invention can ensure that snapshot data will not be lost during archiving, ensuring data integrity, while also ensuring data coherence and consistency.

This invention discloses a UVM verification method and system for processor core bus protocol to AXI protocol conversion. The method includes: extending the general interface UVC to obtain a directional interface UVC adapted to both the processor core bus protocol and the AXI protocol; inputting an excitation sequence to the design under test (DUT) through the directional interface UVC, acquiring the signals output by the DUT and converting them into data frames; processing the original bus protocol request, outputting a reference data frame, and comparing the acquired data frame with the reference data frame; performing data coherence detection on the DUT using a storage model; and determining whether the verification passes by combining the comparison result and the data coherence detection result. This invention effectively solves the technical problems of the lack of a dedicated verification method for the processor core bus protocol to AXI protocol conversion module, the difficulty of data coherence verification, and the long verification convergence period.