19results about How to "Achieve accurate identification" patented technology

The invention discloses a knowledge base document blocking method and device based on layout analysis and a medium, and relates to the technical field of artificial intelligence, and the method comprises the following steps: carrying out document image preprocessing on a to-be-stored document to obtain a document standard image; performing layout structure analysis on the document standard image to determine a layout structure layout; based on the layout structure layout, obtaining a structural logic relationship of layout elements through layout structure analysis; according to the structural logic relationship, performing layout partitioning on the layout of the to-be-stored document, and determining a first layout partition; block quality evaluation is carried out on the first layout blocks to determine the block quality of the first layout blocks, and block optimization is carried out on the blocks with the block quality lower than a preset threshold value to obtain second layout blocks. By means of the method, the technical problem that intelligent partitioning cannot be achieved in knowledge base document partitioning through layout analysis in the prior art is solved.

The application discloses a phosphoric acid modified protein or polypeptide, a preparation method thereof and application thereof in vaccines, and belongs to the field of protein phosphoric acid modification. The preparation method of the phosphoric acid modified protein or polypeptide is as follows: a compound containing an aldehyde group and a phosphate group is subjected to nucleophilic reaction with a protein or polypeptide to form a Schiff base; a reducing agent is used to reduce the Schiff base, and after post-treatment, the phosphoric acid modified protein or polypeptide is obtained. After the phosphoric acid modified protein product prepared by the method is prepared into a vaccine with an aluminum hydroxide adjuvant and mice are immunized, the antibody titer is significantly increased. This is of great significance for increasing the immune effect, reducing the inoculation dose, saving the antigen amount and improving the immune response of some people or in specific conditions.

The application discloses a method and device for identifying a seismic horizon and a storage medium, and belongs to the technical field of seismic interpretation. The method comprises the following steps: acquiring a seismic data body and a multi-target horizon identification sample set seismic data body, and using the multi-target horizon identification sample set seismic data body to generate a sample seismic profile W r The multi-target horizon identification sample set comprises artificial interpretation seismic horizons obtained after marking and processing the sample seismic profile W r , and at least four auxiliary seismic horizons related to the artificial interpretation seismic horizons; a convolutional neural network is trained according to the sample seismic profile W r and the multi-target horizon identification sample set, and a multi-target horizon identification network Net L is obtained; a to-be-identified seismic profile is substituted into the multi-target horizon identification network Net L , and a transition seismic horizon and at least four auxiliary seismic horizons related to the transition seismic horizon are obtained, and then a target seismic horizon is determined through fusion processing. The method can accurately identify the seismic horizon and improve the accuracy of seismic interpretation.

The present disclosure provides a transposon insertion marker specific to tropical japonica rice and its application. First, the insertion site of the transposon insertion marker specific to tropical japonica rice is located between the 20,300,698th and 20,300,699th nucleotides of chromosome 5 of the Nipponbare reference genome of version IRGSP-1.0; the variety of tropical japonica rice contains a 140 bp long transposon insertion at the insertion site, while the varieties of other rice groups do not contain the transposon insertion. Further, the above transposon insertion marker is provided for identifying tropical japonica rice. The transposon insertion marker specific to tropical japonica rice has important application value in precise identification of rice groups, classification of germplasm resources, screening of breeding materials, purity detection of hybrid rice germplasm, etc., and can significantly improve the efficiency of molecular marker assisted selection and shorten the breeding cycle.

This invention provides a method and system for automatically generating parking lot maps based on point cloud and semantic features, belonging to the field of parking lot map construction technology. The method includes: acquiring the original LiDAR point cloud of the parking lot and preprocessing it to obtain a ground point cloud; extracting parking space line point clouds based on the reflection intensity of each point from the obtained ground point cloud; clustering and segmenting the parking space line point clouds to obtain multiple independent parking space line point cloud clusters; performing straight line fitting on each parking space line point cloud cluster to obtain parking space boundary lines and parking space dividing lines; generating parking space boxes based on the intersections of the parking space boundary lines and parking space dividing lines, and outputting the parking lot map. This invention uses a reflection intensity threshold segmentation method to extract parking space line point clouds, overcoming the influence of illumination changes on parking space line extraction; by combining density clustering and a two-step straight line fitting strategy based on geometric constraints, it effectively solves the problems of ineffective differentiation of continuous parking space boundaries and insufficient fitting accuracy of dividing lines.

This invention discloses a primer-probe combination for detecting multiple types of Lactobacillus and its applications, belonging to the field of biotechnology. The primer-probe combination includes a primer-probe combination for detecting *Lactobacillus casei*, a primer-probe combination for detecting *Lactobacillus paracasei*, and a primer-probe combination for detecting *Lactobacillus rhamnosus*. The primer-probe combination of this invention can be used for both singleton and multiplex PCR detection, and can accurately detect *Lactobacillus casei*, *Lactobacillus paracasei*, and *Lactobacillus rhamnosus*, enabling the authentication of products containing Lactobacillus. This invention provides a more convenient method for detecting *Lactobacillus casei*, *Lactobacillus paracasei*, and *Lactobacillus rhamnosus*.

The invention provides a method for allele matching of donor mesenchymal stem cells and a receptor. The method comprises the following steps: S10, separating mesenchymal stem cells from perinatal tissue of a donor; s20, extracting genome DNA (deoxyribonucleic acid) of the mesenchymal stem cells, and performing HLA (human leukocyte antigen) genetic typing; s30, performing HLA (human leukocyte antigen) genetic typing on the DNA of the receptor; s40, performing allele spectrum comparison on the HLA gene of the receptor and the HLA gene of the mesenchymal stem cell, and calculating the matching degree; s50, judging the matching degree of the receptor and the mesenchymal stem cells according to the matching degree; and S60, storing the HLA genotyping result of the mesenchymal stem cells and the matching degree in a database, and establishing a matching library for matching the donor mesenchymal stem cells and the receptor. According to the method, a set of standardized system is established, compatibility evaluation of a donor and a receptor at the allele level is achieved, the immunological rejection risk caused by HLA mismatching is effectively predicted and avoided before treatment, and the in-vivo survival and implantation efficiency of MSCs is improved.

The invention discloses a method for calculating DNB type critical heat flux density of a high-flux reactor arc-plate-shaped fuel assembly. The method comprises the following steps of: 1, carrying out geometric modeling and grid division on a coolant channel of the arc-plate-shaped fuel assembly; 2, solving a two-fluid model control equation and a turbulence model to obtain phase field and flow field distribution; 3, solving a bubble number density group balance equation to calculate bubble diameter distribution; 4, based on the near wall surface flow field, a bubble stress balance dynamic model is adopted to solve bubble characteristic parameters; 5, calculating each heat flow component by adopting an improved wall surface heat flow distribution model; 6, establishing a heat conduction-convection-turbulence superposition interphase heat transfer model and calculating a phase change mass source item; 7, medium physical properties and boundary conditions are set, and the gas-liquid integral number, the speed, the pressure and the temperature are solved in a coupling mode; 8, calculating the density of the stepped loading heat flow; and 9, determining the critical heat flux density according to the boiling curve turning point, the critical void fraction and the outlet bubble group distribution. According to the method, the critical heat flux density of the high-flux reactor arc plate-shaped fuel assembly can be effectively predicted.

The application provides a method for spatial domain identification based on spatial multi-omics data, belongs to the technical field of bioinformatics, and solves the problems that the prior art cannot fully utilize spatial multi-omics data and cannot identify discrete spatial domains, and comprises the following steps: step 1, obtaining a spatial multi-omics comprehensive data set and performing pretreatment; step 2, constructing a deep neural network model; step 3, training the deep neural network model based on the pretreated spatial multi-omics comprehensive data set; and step 4, inputting to-be-detected data into the trained deep neural network model to perform spatial domain identification.

The invention discloses a complex network high-order module and link prediction method based on low-order network reconstruction, and the method comprises the steps: complementing a missing network structure through low-order link prediction, recognizing a potential high-order module in a prediction network, combining the topological features of nodes and edges, and discriminating a real high-order structure through a machine learning model. And finally, high-order network reconstruction is realized. According to the method, a low-order and high-order structure collaborative modeling mechanism is established, and the limitation that only binary interaction is processed traditionally is broken through; the method is suitable for various high-order network modeling tasks, does not depend on a fixed motif form, and has good universality and expandability.

The application discloses an air target single-photon laser three-dimensional histogram feature extraction method, and the operation steps are composed of a time correlation noise reduction module, a histogram accumulation module and a histogram feature extraction module. The application can extract target features under the conditions that the scale of a detector pixel is limited, single imaging point cloud data is sparse and there is atmospheric turbulence interference, and the stability of the features is enhanced.

The application relates to a device abnormal state general identification method and device based on power quality data, a computer device, a storage medium and a computer program product. The method comprises the following steps: acquiring a trained identification model, and a labeling accuracy of each state label corresponding to the trained identification model, and determining a model accuracy corresponding to the trained identification model. The trained identification model is used for performing state identification on each target frequency spectrum, and a corresponding predicted state type is obtained. In the case that the predicted state type is an abnormal state, a state label matched with the abnormal state is used as a to-be-verified state type, and based on the labeling accuracy and the model accuracy, an abnormal probability corresponding to the to-be-verified state type is obtained through cumulative probability distribution calculation. The abnormal probability is subjected to effectiveness verification, and whether the target power device is abnormal is determined based on the effectiveness verification result, so that the effectiveness of determining whether the target power device is abnormal is greatly improved.

The present disclosure provides a specific transposon insertion marker of japonica subspecies and its application. First, the specific transposon insertion marker is located in the nucleotide region from 23,880,821 to 23,881,056 of chromosome 6 of the Nipponbare reference genome version IRGSP-1.0, which is a transposon with a length of 236 bp, and the varieties of japonica subspecies contain the transposon insertion, while the varieties of other rice subspecies do not contain the transposon insertion. Further, the application of the above specific transposon insertion marker is provided. The specific transposon insertion marker of japonica subspecies of the present disclosure has important application value in the precise identification of rice subspecies, the classification of germplasm resources, the screening of breeding materials, the purity detection of hybrid rice germplasm, and the like, and can significantly improve the efficiency of molecular marker assisted selection and shorten the breeding period.

The present application relates to the technical field of wheat disease detection, and more particularly to a wheat disease detection method based on a lightweight multi-scale CNN model; comprising the following steps: S1, collecting wheat disease images by using a shooting device, unifying the size of the wheat disease images, and classifying and labeling each type of disease; S2, expanding the wheat disease data by rotating, symmetrically inverting, and improving the contrast, expanding the original data set to 8495; dividing the data set according to the ratio of training set: verification set: test set = 6:2:2; S3, designing a network model for wheat disease image detection; S4, training the wheat disease training samples obtained in S2 in the network model designed in S3 and testing on the test set; the present application has simple structure, small amount of calculation, and wide applicability.

The invention discloses a primer probe combination for detecting various bifidobacteria and application of the primer probe combination, and belongs to the field of molecular biological detection. The primer probe combination provided by the invention comprises a primer probe group for detecting bifidobacterium breve, a primer probe group for detecting bifidobacterium bifidum and a primer probe group for detecting bifidobacterium adolescentis. Based on the primer probe combination, the invention respectively develops a single PCR detection method and a triple PCR detection method for detecting the three bifidobacteria. Experimental results show that the detection method provided by the invention can be used for accurately detecting bifidobacterium breve, bifidobacterium bifidum and bifidobacterium adolescentis. According to the invention, a foundation is laid for authenticity identification of products containing bifidobacterium breve, bifidobacterium bifidum and bifidobacterium adolescentis, and a more convenient method is provided for detection of bifidobacterium breve, bifidobacterium bifidum and bifidobacterium adolescentis.

The present application relates to the technical field of data check processing, and particularly relates to a consistency check method and system applied to multi-source communication data. The technical scheme of the present application obtains historical data of various communication parameters of multiple data sources and target data for consistency check of the target parameters by the historical data; obtains influence strength indexes of various communication parameters on the deviation of the target parameters based on fluctuation correlation characteristic analysis of the historical data and the target data; performs influence weight analysis according to the differences between the influence strength indexes and the operation requirement values of the various communication parameters to obtain weighted difference scores of inconsistent performances between the data sources; combines the weighted difference scores and the untrustworthiness of the data sources in the historical period to correct the deviation caused by the historical stability difference; and marks real-time data according to the inconsistency scores corresponding to the data sources when the target parameters perform the check task, so that accurate identification of abnormal data is realized.

The invention provides a method for constructing a kelp core germplasm and identifying the germplasm based on an SNP (Single Nucleotide Polymorphism) molecular marker. According to the method, kelp gametophyte germplasm with complete and accurate source information is collected, SNP site detection and screening are performed, and an optimal core germplasm group is determined by utilizing an EN-MR / CE model and combining genetic diversity comparison; 130 SNP markers which are uniformly distributed on chromosomes and rich in polymorphism are obtained through further screening, and accurate identification of 91 core germplasm can be realized. Meanwhile, the core SNP marker can be used for effectively distinguishing germplasm materials from different kelp cultivated strains. According to the method, the genetic diversity background of the kelp germplasm bank can be truly reflected, the core germplasm is efficiently screened, the germplasm material is identified, and technical support is provided for improving the storage and utilization efficiency of the kelp germplasm.

The invention belongs to the technical field of computer software, and particularly relates to a multi-source heterogeneous data fusion-based intelligent responsibility judgment method and system for a pick-up behavior, and the method comprises the steps: collecting a driver track, a communication recording text, environment information, driver reporting and order metadata, and generating a structured pick-up event through space-time alignment; extracting travel, environment, semantics and behavior reputation multi-dimensional features based on the event, and training a gradient boosting decision tree model; real-time lightweight risk intervention and off-line high-precision responsibility judgment are executed through the model, real-time intervention rapidly triggers reminding based on high-timeliness characteristics, and off-line judgment outputs violation probability based on full-quantity characteristics; artificial rechecking, appeal and arbitration results are returned to drive incremental learning of the model; and finally, differentially weighting the responsibility judgment result according to the historical reputation of the driver and generating an interpretable natural language basis. Through multi-source data fusion and a double-track responsibility judgment mechanism, the problem of high misjudgment rate caused by single data in a traditional method is solved.

The application provides an NLP-based line loss intelligent analysis method and system, and relates to the technical field of power system operation and maintenance. The method comprises the following steps: obtaining monitoring information of a target object and constructing an information sequence; analyzing feature items in the information sequence and calculating risk increment values of the target object under different evaluation dimensions; accumulating and updating state scores of each evaluation dimension of the target object based on the risk increment values to obtain a dynamic state of the target object; monitoring the evolution sequence of the state scores of each evaluation dimension in the dynamic state over time, and matching the evolution sequence with a preset gradual failure mode, and outputting risk warning information when the matching is successful. The method aims to solve the problems in the prior art that it is difficult to accurately evaluate risks, lacks state continuity and cannot deeply identify systematic defects, improve the accuracy and timeliness of line loss analysis, realize preventive maintenance, reduce early warning lag and deeply identify systematic risks.