16 results about "Marker analysis" patented technology

The invention belongs to the field of big data, and particularly relates to a case detection optimization method based on big data. Acquiring case information for data preprocessing, and summarizing the data to a dynamic database in real time; identifying and associating data in the dynamic database, and establishing an index database with association logic; automatically constructing an evidence chain through an inference model and an index database; logic detection is carried out on the evidence chain, the evidence chain with strong logic association of time, figures and material evidences is reserved as a reference evidence chain, and abnormal points of the reference evidence chain are marked; and performing analysis and prediction based on abnormal point marks of the reference evidence chain, and giving at least one prediction direction to guide case detection. Data summarization is carried out through a big data technology, associated data is rapidly extracted through an index database, multiple evidence chains are automatically constructed for screening, investigation direction expansion is carried out through mark analysis and prediction of abnormal points, and the case solving efficiency is improved through data driving.

The invention discloses a methane leakage microbial marker mining method based on multi-source data fusion and related equipment, according to the embodiment of the invention, a multi-dimensional feature space is constructed by fusing microbial gene data, spatial information and environmental geochemical data, and the data dimension and reliability of marker mining are improved; moreover, according to the embodiment of the invention, a mode of combining random forest and regression modeling is adopted, so that quantitative screening of the markers is realized, and manual intervention and subjective deviation are reduced; specifically, according to the embodiment of the invention, the markers are graded on the basis of comprehensive scores of three dimensions of importance, stability and universality, so that priority selection in subsequent practical application is facilitated; the embodiment of the invention is suitable for methane leakage identification of different sea areas and different geological backgrounds, has good generalizability and practicability, and can be widely applied to the technical field of marker analysis.

This invention discloses a method for testing the corrosion crack propagation path of floating structures based on digital twins, relating to the field of path testing. The method includes the following steps: acquiring basic information about the floating structure, setting up a three-dimensional virtual structure model, and marking key nodes; setting up an intelligent sensor network to acquire real-time monitoring data at each key node; performing labeling and analysis on the historical monitoring data at each node within the three-dimensional virtual structure model to obtain a longitudinal and transverse label dataset; performing longitudinal and transverse analysis on the longitudinal and transverse label dataset to obtain the interaction relationship between seawater corrosion and crack propagation at each key node in three dimensions: time, space, and degree of influence; constructing a monitoring verification model and a crack propagation model based on the analysis results; verifying and analyzing the real-time monitoring data using the monitoring verification model; and performing path analysis on the verification analysis results based on the crack propagation model. This invention improves the accuracy of the crack propagation path testing process.

The invention relates to a spectroscopic imaging and spectrometer system comprising at least two channels, the system being connectable to smartphones. The system is configured to simultaneously determine the optical properties, including reflectance, transmittance, color, and luminescence characteristics, of solids, liquids, and gases. The invention is particularly advantageous for forensic investigations and applications requiring the use of encrypted markers. The system operates by splitting the image of an object into two parts by means of a prism and subsequently employing optical filters and diffraction gratings. Furthermore, the system incorporates software compatible with external devices such as smartphones or computers. Said software enables the cameras of a smartphone to function as a spectrometer, thereby allowing spectra to be acquired through high-resolution imaging.

The application discloses an NCCL migration method based on a resource pool, relates to the technical field of high-performance computing communication optimization, and comprises the following steps: obtaining thread identification records, synchronization timestamp markers and thread state information from the resource pool by scanning the multithread running environment of the NCCL communication program based on the resource pool at a source end; generating a thread state snapshot in combination with data packet transmission progress, constructing a data transmission state file containing transmission interruption recovery points and synchronization signal priorities, and determining an initialized synchronization marker data set; transmitting the thread state snapshot and a data check code value to a target end according to the initialized synchronization marker data set, decoding the synchronization marker by using an inheritance marker analysis rule, generating a control module state cache of the target end, and obtaining a preliminary synchronization marker inheritance result; and the NCCL migration method based on the resource pool significantly improves the migration efficiency, data link continuity and overall running stability of the NCCL communication program in a high-load scene.

The invention discloses a selenium-rich solid beverage production whole-process intelligent quality control system and method, and relates to the technical field of food processing and intelligent manufacturing, the selenium-rich solid beverage production whole-process intelligent quality control system comprises a data acquisition module, a process mark analysis module, a feedback control module and a quality control report generation module, the data acquisition module is in communication connection with the process mark analysis module, and the process mark analysis module is in communication connection with the feedback control module; the data acquisition module is used for synchronously acquiring multi-source real-time process parameter data including temperature, humidity, pressure, mixing torque, spraying rotating speed and online selenium content detection value from a plurality of key working sections in the selenium-rich solid beverage production process; the process mark analysis module is used for adding a process flow position label to the acquired data and establishing a process behavior track of the current batch; the system has the advantages of being high in practicability and high in intelligent degree.

The application discloses a kind of predictable phaseolus vulgaris response melatonin regulation SSR molecular markers and its application, it is related to biotechnology field.The application carries out the effectiveness identification of ordinary phaseolus vulgaris natural germplasm resources to melatonin treatment, the efficiency of melatonin treatment-cell wall-salt tolerance in ordinary phaseolus vulgaris germplasm resources is analyzed, and using the reference genome in Esembl plants database, a complete set of SSR molecular markers is developed, and according to transcriptome information, the SSR marker near response gene is mined, through polymorphism analysis and single marker analysis, two SSR markers with significant difference associated with melatonin traits are screened, can be used as the molecular marker for predicting phaseolus vulgaris response melatonin regulation, and provides technical support for the function prediction of melatonin treatment in the sprouting stage of ordinary phaseolus vulgaris.

The present invention relates to a material analysis method, which may include: (a) preparing a test specimen for analyzing its structure; (b) training an artificial intelligence model with training images labeled with the structure of any test specimen; (c) using the trained artificial intelligence model to analyze a plurality of unlabeled analysis images of the test specimen and removing analysis images classified as pre-defined noisy structure patterns; and (d) using the trained artificial intelligence model to analyze the analysis images from which the noisy structure patterns have been removed and classify them into at least one target structure pattern.

The application relates to the technical field of medical data analysis, in particular to an immune marker analysis system based on machine learning, which comprises an entropy density flow change module, a boundary dynamic labeling module, a collaborative tensor modeling module and a marker discrimination module.In the application, three-dimensional immune data is processed through kernel density estimation and spatial information entropy is calculated, multi-source heterogeneous medical data spatial features are integrated, a gradient graph is generated by combining a sliding average method to capture a marker concentration change trend, a boundary topology model is constructed based on directional derivative detection and morphological closing operation to identify morphological boundary features, a three-order tensor modeling is used to fuse immune subtypes, time dimensions and marker expression data, a dimension self-adaptive tensor decomposition is used to extract a core factor matrix to improve the integrity of marker correlation analysis, Manhattan distance is used to quantize collaborative expression intensity and combine residual matrix Hadamard product, and single threshold determination is crossed to multi-dimensional collaborative discrimination in immune marker quantitative analysis.

This invention discloses a multi-marker analysis method for the classification and origin tracing of peripheral blood target cells, relating to the medical field. This method involves capturing target cells from peripheral blood samples, identifying them as tumor cells using tumor markers, and then further analyzing them using tissue-specific markers to achieve classification and origin tracing. This invention not only traces the origin of peripheral blood tumor cells but also confirms the tissue and organ source of the tumor cells, making the classification and origin tracing of target cells possible and more accurate.

The invention discloses a peanut drought-resistant gene associated molecular marker screening optimization system and method, and relates to the technical field of agricultural biology. The system comprises a data acquisition module, a molecular marker analysis module and a data integration and evaluation subsystem, peanut DNA, physiological indexes and environmental data can be acquired, candidate markers are identified through PCR amplification and high-throughput sequencing, and a comprehensive evaluation model is constructed to calculate correlation coefficients. The method comprises the steps of sample preparation and pretreatment, molecular marker preliminary screening, marker verification and optimization and application verification, setting of a drought and normal moisture control environment, elimination of false positive markers through repeated verification, screening of high-correlation markers with a correlation coefficient greater than or equal to 0.6, and application accuracy greater than or equal to 85%. The method solves the problems of low accuracy, poor environmental suitability and the like in the prior art, improves the marker screening accuracy and stability, can efficiently assist in cultivation of new drought-resistant peanut varieties and relieve the restriction of drought on the peanut industry, and has important scientific research and application values.

The invention discloses an unmanned aerial vehicle autonomous landing system and method suitable for an unattended scene, and belongs to the field of unmanned aerial vehicles, and the method comprises the steps: carrying out the staged landmark recognition, which comprises high-altitude global recognition and low-altitude mark tracking; performing dynamic pose estimation, including high-altitude angular point matching and low-altitude mark analysis; environment adaptive flight control, including multi-sensor data fusion and near-earth landing control; and intelligent emergency processing, including abnormity monitoring and dynamic decision making. According to the method, the accuracy of landmark recognition and the precision of pose estimation are improved by adopting a staged landmark recognition and pose estimation method, and the requirement for height change in the autonomous landing process of the unmanned aerial vehicle and the requirement for landing of the unmanned aerial vehicle in an unattended scene are met. The reliability and safety of vertical landing and autonomous landing of the unmanned aerial vehicle are improved. According to the invention, various emergencies can be dealt with in real time, and property losses such as unmanned aerial vehicle damage and cargo damage caused by a landing problem are reduced.

The embodiment of the application provides an analysis method, a page marking method, a platform, equipment, a medium and a product, relates to the technical field of computers, and the method comprises the following steps: acquiring a recommended marking scheme and a current marking scheme of a target page, the recommended marking scheme comprising at least one marking analysis event and at least one analysis parameter of the marking analysis event; the current marking scheme comprising at least one marking event and at least one marking parameter of the marking event; constructing a first association relationship between the at least one marking analysis event and the at least one marking event, and a second association relationship between the at least one analysis parameter and the at least one marking parameter; and displaying an event analysis result of the marking analysis event, wherein the event analysis result is generated based on the marking event associated with the marking analysis event and the parameter value of the marking parameter associated with the analysis parameter of the marking analysis event. The technical scheme of the embodiment of the application can inject a marking scheme meeting data analysis requirements in the development stage of software application.

The present invention relates to a material analysis method, which may include: (a) preparing a test specimen for analyzing its structure; (b) training an artificial intelligence model with training images labeled with the structure of any test specimen; (c) using the trained artificial intelligence model to analyze a plurality of unlabeled analysis images of the test specimen and removing analysis images classified as pre-defined noisy structure patterns; and (d) using the trained artificial intelligence model to analyze the analysis images from which the noisy structure patterns have been removed and classify them into at least one target structure pattern.

A method for manufacturing battery electrodes with enhanced traceability using fiducial markers. The method includes applying tracing codes and position codes to a substrate, synchronizing measurement profiles with accompanying tracing codes, and dynamically adjusting manufacturing parameters based on marker analysis. The invention improves quality control and traceability in battery electrode production.

The application discloses a methane seepage microbial marker mining method based on multi-source data fusion and related equipment, and the embodiment of the application fuses microbial gene data, spatial information and environmental geochemical data, constructs a multi-dimensional feature space, and improves the data dimension and reliability of marker mining; moreover, the embodiment of the application adopts a combination of random forest and regression modeling, realizes quantitative screening of the marker, and reduces manual intervention and subjective bias; specifically, the embodiment of the application grades the marker based on the comprehensive score of the three dimensions of importance, stability and universality, facilitating priority selection in subsequent practical applications; the embodiment of the application is suitable for methane seepage identification in different sea areas and different geological backgrounds, has good generalizability and practicality, and can be widely applied in the technical field of marker analysis.