34 results about "Secondary analysis" patented technology

The present application relates to the technical field of flow monitoring, and discloses a method and system for real-time monitoring of flow in an At-211 column separation process, the method comprising: collecting the conductivity of eluent in the outlet pipeline of the At-211 chromatographic column in real time, continuously analyzing the conductivity, and generating a state flag; wherein when it is detected that the eluent is switched to anhydrous ethanol phase, the state flag is valid; otherwise, the state flag is invalid; by collecting the conductivity and generating the state flag, the timing of anhydrous ethanol phase switching is accurately determined, the collected pressure time series data is analyzed to generate a steady-state pressure value, then secondary analysis is performed to obtain a pressure memory value, the stable state of pressure and the continuous influence of flow are comprehensively captured, and finally a flow stability index is generated, which can evaluate the flow state of the whole alcohol phase elution process. The present application does not need to rely on the continuity of the conductivity signal, effectively filters transient interference, and improves the accuracy of flow monitoring.

A determination system includes: a log obtainer that obtains log information; a preprocessor that generates preprocessed log information from the log information; a primary analyzer that generates primary determination result information by performing primary analysis on the preprocessed log information; a prompt generator that generates a prompt for generative artificial intelligence (AI) based on the preprocessed log information; a secondary analyzer that performs, as secondary analysis, a process of obtaining secondary determination result information by inputting the prompt to the generative AI; an overall determiner that generates overall determination result information based on the primary determination result information and the secondary determination result information; and an outputter that outputs a determination result report that includes a determination result indicated by the overall determination result information.

The application provides a data processing method, device, equipment and medium. Data of multiple heterogeneous systems is collected multiple times, and the data of the multiple heterogeneous systems collected each time is transmitted to an analysis system respectively. Each analysis system runs different unsupervised learning algorithms and outputs corresponding analysis results. Each analysis result includes a first interworking heterogeneous system matched by each heterogeneous system. Then, each analysis result is integrated into a classification matrix. Rows of the classification matrix include matching results of each heterogeneous system under different analysis systems, and columns of the classification matrix include matching results of each heterogeneous system under each analysis system. Secondary analysis is performed on data in each row of the classification matrix to analyze analysis results of each heterogeneous system under different analysis systems, and a second interworking heterogeneous system matched by each heterogeneous system is obtained, so that an interworking heterogeneous system can be effectively obtained.

This invention relates to a method and system for disaster overlay analysis in nuclear power plants, comprising the following steps: acquiring standard specifications and experience feedback data of the nuclear power plant; conducting preliminary screening analysis based on the standard specifications, experience feedback data, and screening criteria to obtain a preliminary screening list of disaster overlays; and conducting secondary analysis based on the preliminary screening list of disaster overlays and in conjunction with a list of overlay disaster analysis scopes to obtain a disaster overlay list. This invention, through preliminary screening analysis, obtains a preliminary screening list of disaster overlays, achieving a comprehensive and effective review of possible disaster overlay types and avoiding omissions; simultaneously, through secondary analysis, it achieves a comprehensive and effective review and determination of the disaster overlay types that need to be considered, further ensuring the comprehensiveness and effectiveness of the disaster overlay analysis and avoiding omissions.

The invention relates to the technical field of data processing in an automatic recruitment system (ATS), in particular to a double-stage asynchronous processing-based resume analysis optimization method in the ATS, which comprises the following steps: S1, a primary analysis stage: quickly extracting key fields in a resume by adopting a lightweight analysis module formed on the basis of regular rules, entity recognition and other technologies, and carrying out secondary analysis on the key fields in the resume; comprising name, gender, contact information, graduation colleges, educational background and professional information; the module has high real-time performance and can return an analysis result within a second level; s2, user response and business promotion: returning a primary analysis result to a user interface in real time and storing the primary analysis result into a system, and supporting the user to carry out subsequent operation without delay, the user experience is remarkably improved, the user does not need to wait for a long-time analysis process, and non-inductive import of'completion once submission 'is realized; the analysis quality is greatly improved; the accurate extraction of deep and complex fields is realized through a multi-modal large model, and the data basis of the subsequent man-post matching and screening process is improved.

The invention discloses an ignition charge-free electronic detonator and a quality prediction and control method thereof. The detonator structurally comprises a wire clamp, an injection molding plug, an electronic control module and a basic detonator, a leg wire for connecting the electric ignition head and the exploder is arranged in the injection molding plug; an elastic piece is arranged on the surface of the electronic control module. The method comprises the following steps: S1, collecting production raw material data of the non-ignition charge electronic detonator; s2, cleaning and standardizing the collected data; s3, constructing a feature extraction model and a special prediction model, and outputting a sensitivity index prediction result and quality risk early warning; and S4, according to a large model output result, executing a subsequent production process on a qualified batch, and carrying out secondary analysis on a risk batch. Complete support is provided by collecting production whole process quality related data, the abnormal value risk weight is marked in combination with historical fault reworking data to improve the effectiveness of the model, risks can be solved in advance, waste is reduced, and the quality stability and production efficiency of the ignition charge-free electronic detonator are improved.

This invention relates to a robustness analysis method and system for accident operation procedures, comprising the following steps: acquiring all information used by the accident operation procedures in handling accident conditions; performing the following operations on each piece of information: determining whether the information to be analyzed is reliable; if reliable, determining that the information to be analyzed is robust; if unreliable, performing a secondary analysis on the information to be analyzed. This invention achieves full-range robustness analysis of the accident operation procedures by extracting and robustly analyzing all information used by the accident operation procedures in handling accident conditions, avoiding problems caused by information loss or failure, ensuring the fault tolerance of the reliability of the accident operation procedures, and further improving the safety and stability of nuclear power plant reactors.

Disclosed herein are systems and methods for performing secondary analysis of nucleotide sequencing data in a time-efficient manner. Some embodiments include iteratively performing secondary analysis as sequence reads are generated by a sequencing system. Secondary analysis can include alignment of sequence reads to a reference sequence (e.g., a human reference genome sequence) and use of the alignment to detect differences between a sample and the reference. Secondary analysis can be capable of detecting genetic differences, variant calling and genotyping, identifying single nucleotide polymorphisms (SNPs), small insertions and deletions (indels), and structural changes in DNA, such as copy number variations (CNVs) and chromosomal rearrangements.

The application discloses an edge MEC event secondary analysis method and system and a storage medium, and belongs to the technical field of intelligent traffic. The method comprises the following steps: S1, a device calibration stage; S2, a target tracking stage; S3, an event detection stage, defining an event representation rule, then judging whether a target vehicle in a video sequence has a target event according to the event representation rule, if the target vehicle has the target event, recording to obtain an event representation; S4, an event secondary analysis stage, performing secondary analysis on the event representation, filtering out event representations that do not pass multiple authentications, and retaining event representations that pass multiple authentications to obtain final event representations; and S5, an event exposure stage, uploading the final event representations to a business side for analysis and use. The deep learning model is used for secondary confirmation of an event target, secondary authentication of event key attributes such as position information and an event type, automatic all-weather completion of event secondary analysis, reduction of human consumption, and improvement of the working efficiency of the business side.

The present application relates to the technical field of test application, in particular to a state type data efficient universal interpretation method, which meets different equipment state type data interpretation requirements through flexible configuration of five-element state type interpretation templates; and realizes efficient interpretation of state type data through secondary hierarchical interpretation of state words, i.e. firstly, overall interpretation of state type data, if normal, no secondary analysis interpretation is performed, if abnormal, secondary analysis interpretation is performed again.

The invention discloses an enterprise data intelligent insight method, system and device, a storage medium and a product, and the method comprises the steps: obtaining enterprise report data from an enterprise report system, carrying out the cleaning, processing, conversion and integration, forming a report data set meeting the attribution analysis requirements, and carrying out the attribution analysis according to the input report data, data dimensions and attribution targets. Analyzing indexes, attribution dimensions and / or attribution formulas, selecting an adaptive attribution algorithm, carrying out attribution calculation in combination with a report data set, executing ad hoc processing on report data according to instant inquiry requirements of a user, forming an attribution calculation analysis result, presenting the result in a visual form, obtaining structured data and carrying out secondary analysis; and outputting an analysis result and a text insight for report data, performing semantic analysis and interpretation on the oral question of the user by using a large model, and converting the oral question into an analysis index and an attribution dimension. By adopting the technical scheme of the invention, enterprise report data analysis can be efficiently and accurately realized.

The application discloses a kind of unified driving behavior analysis equipment accuracy based on secondary identification method.For overcoming the problem that the prior art lacks secondary analysis to DSM uploaded video, leading to false alarm to driver's illegal operation, the application includes that behavior analysis equipment collects video data in the time interval before and after alarm time and uploads to secondary analysis platform;Secondary analysis platform processes video data to generate several slices, compares the score of corresponding slice with the preset score, determines and records abnormal early warning slice;Secondary analysis platform sets early warning calculation rule according to the type of abnormal early warning slice, and determines the correct alarm of corresponding video data combined with the number of abnormal early warning slices.The alarm video generated by DSM equipment is calculated by the unified algorithm of platform secondary identification, and then the alarm is presented to the transportation management department;The application confirms through platform secondary identification, ensures unified algorithm and improves the accuracy of dangerous driving behavior identification.

The invention relates to the technical field of flow monitoring, and discloses a flow real-time monitoring method and system in the At-211 column separation process, and the method comprises the steps: collecting the conductivity of an eluent in an At-211 chromatographic column outlet pipeline in real time, carrying out the continuous analysis of the conductivity, and generating a state flag; wherein when it is detected that the eluent is switched to the absolute ethyl alcohol phase, the state mark is effective; otherwise, the state flag is invalid; the method comprises the following steps: acquiring conductivity, generating a state flag, accurately judging the phase switching opportunity of absolute ethyl alcohol, analyzing acquired pressure time sequence data to generate a steady-state pressure value, performing secondary analysis to obtain a pressure memory value, comprehensively capturing a pressure stable state and flow continuous influence, and finally generating a flow stability index. According to the scheme, the flow state in the whole alcohol phase elution process can be evaluated, the scheme does not need to depend on conductivity signal continuity, transient interference is effectively filtered, and the accuracy of flow monitoring is improved.

The invention relates to a registration doctor-seeing analysis scheduling method, which comprises the following steps of: aiming at a doctor-seeing sign-in sequence formed by patients under initial sign-in and back-visit sign-in in real time, taking longest waiting time analysis as a sequential triggering condition, and triggering a first-visit patient and a back-visit patient distinguished by aiming at a patient analysis design, so as to obtain a first-visit sign-in sequence and a second-visit sign-in sequence; the method comprises the following steps: contacting completed historical treatment records of each historical patient treated by a target doctor registered by a patient, designing and executing primary analysis scheduling to update a treatment sign-in sequence, and further triggering and contacting each completed historical treatment record of each historical patient treated by other doctors in a department where the target doctor is located; in this way, according to the design scheme, multi-dimensional factor analysis is integrated, a two-stage analysis scheduling scheme is designed progressively, the doctor-seeing waiting time of the patient is shortened to the maximum extent while the doctor-seeing quality is guaranteed, and the doctor-seeing efficiency is improved.

The invention relates to the technical field of metal washer detection, and discloses a metal washer full-automatic detection method based on industrial vision, which comprises the following steps: detecting a target washer to preliminarily judge whether the target washer is qualified or not, forming a preliminary detection conclusion, performing secondary analysis or preliminary misjudgment analysis according to the preliminary detection conclusion, and determining whether the target washer is qualified or not. According to the full-automatic detection method for the metal washer based on the industrial vision, blindness of traditional manual sampling inspection is replaced, quality risks are converted from'post discovery 'to'pre-prevention', the misjudgment rate is reduced, waste of qualified products is reduced, the quality cost of enterprises is reduced, the credibility of a detection system is improved, and the detection efficiency is improved. The method has the advantages that the internal defect detectability is improved, the problem of traditional visual leak detection is quickly screened out, the early failure after the metal gasket is installed is avoided, the detection intensity is automatically matched, the detection cost is reduced, the one-step excessive detection is avoided, the optimal configuration of detection resources is realized, and the precision of a detection system is promoted to be continuously improved.

The invention provides an intelligent image research and judgment method and system based on an artificial intelligence secondary analysis architecture, and relates to the technical field of artificial intelligence, and the method comprises the steps: receiving an analysis task which comprises to-be-analyzed image information and a target scene list; performing first-stage rapid preliminary screening on the to-be-analyzed image information, and generating a preliminary screening result containing a target category, coordinates and a confidence value through a lightweight target detection model; determining a bounding box range based on coordinate information of each target in the preliminary screening result, dividing a target region into a plurality of feature analysis units, and extracting feature statistics of each unit to form local features; obtaining a confidence coefficient correction coefficient based on the local features; and performing weighted fusion calculation based on the confidence correction coefficient and the confidence value to obtain an optimized confidence value. According to the invention, through a two-stage funnel type processing architecture, efficient filtering and analysis of mass image data are realized, a structured research and judgment result is finally output, and the processing efficiency is improved.

Methods, systems, and apparatus, including computer programs, for performing incremental secondary analysis of nucleic acid sequence reads are provided.SOLUTION: Obtaining first data descriptive of a plurality of first reads generated by a nucleic acid sequencing device during a first read interval, obtaining second data descriptive of a plurality of second reads generated by the nucleic acid sequencing device during a second read interval performed after the first read interval, and while obtaining the second data, the nucleic acid sequencing device providing the first data as input to a mapping and alignment unit; Alignment results are received from the mapping and alignment unit and stored, and the mapping and alignment unit is instructed to initiate alignment of second data representing the second plurality of reads to a reference sequence.SELECTED DRAWING: Figure 2

This electrophoresis system is characterized by including: a compression range setting unit (105) which, in order to perform appropriate compression of fluorescence signal data, distinguishes between and detects fluorescence signals attributable to an analysis target and fluorescence signals attributable to factors other than the analysis target, for fluorescence signals included in the fluorescence signal data, and sets a compression range for a frame of the fluorescence signal data on the basis of the detection result; a compression rate calculating unit (106) that calculates a compression rate on the basis of the maximum value of the fluorescence signal intensity included in the compression range and the maximum value of the signal intensity that can be used in a secondary analysis; and a compressing unit (107) that generates fluorescence signal compressed data by compressing the fluorescence signal data on the basis of the compression rate, and outputs the generated fluorescence signal compressed data.

The invention discloses a digital point inspection and online reinspection system and method for visual inspection equipment on an industrial production line. The system comprises a digital point inspection module, an intelligent reinspection module and a data management and tracing module, the digital point inspection module carries out high-frequency state verification and algorithm validity verification on visual inspection equipment at each station of the packaging machine through cooperation of an automatic execution mechanism and an intelligent algorithm; the intelligent reinspection module performs secondary analysis and judgment on the suspected defective products identified by the detection equipment; and the data management and tracing module is used for recording point inspection and reinspection related data, realizing data visualization and retrieval, and performing centralized management and optimization updating on the detection model. The system realizes real-time data interaction with the PLC control cabinet and the visual inspection equipment at each station through an industrial Ethernet wired or wireless transmission network.

The invention relates to the technical field of network operation and maintenance management, and discloses a network operation and maintenance management system based on big data analysis, and the system comprises a user data analysis module which comprises a user behavior deviation analysis unit, a link environment interference analysis unit and an abnormal congestion analysis unit. And when abnormity occurs, an abnormal congestion analysis unit is scheduled to perform secondary analysis. According to the system, a user habit list in a user data acquisition module is read, a user behavior deviation coefficient is analyzed and constructed for primary judgment, a waiting period is set in the primary judgment process, an abnormal congestion coefficient is constructed in the waiting period, and the construction of the abnormal congestion coefficient can ensure that when a user behavior deviation analysis unit waits, the user behavior deviation analysis unit does not wait. And entering a secondary risk assessment process, so that resource waste caused by long-time waiting when the user behavior deviates from the analysis unit for judgment and is always in a waiting state is avoided, and a system can be forced to make a decision.

The invention relates to the technical field of cloth detection, in particular to a cloth defect online detection method based on multispectral imaging and AI fusion, which comprises the following steps: carrying out positioning interception and image correction on cloth in an image to be detected, and outputting a new cloth test set and a corrected image set; training a cloth surface flaw recognition model through the corrected image set, and judging the surface flaw state of the cloth image; feeding back the flaw position to a to-be-detected image in the cloth test set in a coordinate transformation form; and judging the surface defect type of the cloth, performing data summarization, verifying the recognition capability of the cloth surface defect recognition model, and determining that the recognition capability of the cloth surface defect recognition model meets the standard, or determining that the recognition capability does not meet the standard and analyzing the reason for the non-conforming to the standard, or performing secondary analysis on the recognition capability. According to the method, the adaptability to different types of cloth surface flaws on the cloth surface is improved by adjusting the detection parameters according to the flaw types.

This invention discloses a method for switching day and night modes in a camera. The method first acquires the camera's image brightness and exposure information, analyzes the brightness information to determine if brightness conditions are met, then performs a secondary analysis of the chromaticity information to determine if chromaticity conditions are met, and finally analyzes whether the current switching conditions are stable, thereby switching the camera's day and night modes. This invention fully considers the difference in ambient light between day and night modes, which can lead to difficulties in determining the current light source, ensuring that the camera can accurately identify whether the current scene is illuminated by visible light or infrared light when the light changes. By combining this with further calculation and analysis of effective white balance information, it can achieve better adaptation to different scenes. This invention avoids increased hardware costs and solves the problem of poor adaptability and repeated switching between day and night modes caused by threshold judgment.

The application discloses a method for dividing rural landscape ecological units based on a clustering algorithm, and belongs to the field of landscape architecture research; the method comprises the following steps: S1, carrying out grid division on a research region to obtain two types of grid division results A and B; S2, collecting basic information of the research region to establish a basic information database of each region; S3, collating and preprocessing the collected basic information data, and preparing for secondary analysis of the grid; S4, carrying out multi-dimensional clustering analysis on the type A grid; S5, naming and distinguishing the clustering results of the type A grid; S6, taking the classification results of the type A grid as a reference to improve the data of the type B grid; S7, carrying out multi-dimensional clustering analysis on the type B grid, and naming and distinguishing the results; S8, visualizing the analysis result data of the type A and type B grids, and distinguishing the classification results by using color blocks with different gray scales; and S9, merging the grids with the same gray color and adjacent to each other, and generating ecological units according to the analysis results.

The invention provides a sleep monitoring system and method, and the system comprises an electroencephalogram collection module which is used for collecting electroencephalogram original data and head angular acceleration data in the sleep process of a user as first original data; the PPG acquisition module is used for acquiring PPG original data and hand acceleration data in the sleep process of the user as second original data; the local calculation module is used for performing sleep primary analysis according to the first original data and the second original data to obtain a primary analysis result; the cloud computing module is used for performing sleep secondary analysis according to the primary analysis result, the first original data and the second original data to obtain a secondary analysis result; and the user interaction module is used for carrying out visualization processing on the primary analysis result and / or the secondary analysis result for a user to check. According to the method, operation tasks are shared through multi-stage operation, the calculation pressure of each module is reduced, the use cost is low, and the expansibility is good.

The invention relates to the technical field of distributed databases, and discloses a distributed database SQL auditing method which comprises the following steps: acquiring a query request initiated by a user side, and calling an auditing rule table according to the query request; the auditing rule table needs to be adjusted, and corresponding auditing rule data are updated based on the adjusted auditing rule table; obtaining a target auditing SQL submitted by the user side, and distributing auditing nodes according to the environment type of the target auditing SQL; the auditing node analyzes and audits the target auditing SQL according to the updated auditing rule data, and feeds back analysis process data and a preliminary auditing result to an auditing center; and the auditing center performs secondary analysis and structured processing on the analysis process data and the preliminary auditing result to generate a differentiation result. Through dynamic rule management, distributed collaborative auditing and multi-level risk interception, the auditing efficiency is improved, and the risk is reduced.

The invention discloses a method for perceiving self appearance, clothes and scenes through digital separate bodies and a related product. The method comprises the following steps: acquiring digital copy content associated with a digital copy unique identifier; performing legality verification and normalization processing on the digital duplicate content to obtain a standardized material; based on a preset appearance-clothing-scene field set, constructing a structured cue word and a structured constraint, and calling a multi-modal analysis model to reasone the standardized material to obtain a candidate structured result; performing grammar verification, field verification and value domain consistency verification on the candidate structured result to obtain a target structured result; and storing the target structured result and the unique identifier of the digital duplicate in an appearance-clothing-scene setting library in an associated manner, and writing a version number and an update timestamp. By means of the technical scheme, unified processing and field-level structured output of multi-format input are achieved, and uncertainty caused by manual participation and secondary analysis is reduced.

The invention discloses an Android equipment abnormal process detection and analysis method based on an isolated forest and a large language model. The method comprises the following steps: collecting process data of Android equipment; performing unsupervised anomaly detection on the process data by using an isolated forest algorithm, performing real-time anomaly evaluation on each process by constructing a plurality of isolated trees, calculating an anomaly score of each process, and outputting a Boolean anomaly mark according to global distribution, wherein the isolated forest algorithm stabilizes the proportion of the abnormal process within a predetermined range by controlling model parameters; performing secondary analysis on the process of the exception mark by utilizing a large language model, and generating exception type identification, exception reason description and optimization suggestions; and outputting an analysis result, wherein the analysis result comprises a detailed report and a visual chart of the abnormal process. Through combination of unsupervised anomaly detection and AI analysis, research and judgment, the problems of information leakage and the like caused by background abnormal power consumption, abnormal wake-up and resource consumption are solved.

Disclosed herein is a method of analyzing a sample by mass spectrometry. A precursor is acquired from the sample. At least one mass spectrum associated with the precursor is generated based on performing a first level of analysis on the precursor. At least one motif in the precursor is identified based on performing a real-time error-tolerant search of the at least one mass spectrum using stored mass spectral reference data. Based on identifying the at least one motif in the precursor, at least one second level of analysis on the at least one motif is initiated to determine an identity of the precursor.