63 results about "Secondary analysis" patented technology

The invention discloses a waistband type falling protection early warning device for old people living alone, and belongs to the technical field of intelligent wearable equipment. The problems that an existing device is single in early warning mode and cannot effectively guarantee the safety of old people living alone are solved, corresponding action results are matched for various data of the old people through the convolutional neural network and the lightweight decision tree model, and if a preliminary judgment result conforms to a normal mode, a judgment result is directly output; if not, triggering a secondary analysis mechanism to further judge whether the old people fall down or not; the GPS positioner is also used for analyzing whether falling behaviors occur at the same position for many times, and if a high-risk position is found, when the old people approach the high-risk position, the warning lamp and the alarm are used for reminding and paying attention to action behaviors; the fall detection accuracy is improved, the possibility of false alarm and missing alarm is reduced, the old people can be actively prevented from falling again in a high-risk area, and a more comprehensive safety guarantee is provided for the old people living alone.

The invention provides a welding spot cavity and bridging defect intelligent automatic test system, and relates to the technical field of defect detection, and the method comprises the steps: a data collection module is used for collecting image data of a to-be-detected welding spot, carrying out the standardization processing, and obtaining standard image data; the void defect detection module is used for identifying a low-density region in a standard image data welding spot, calculating an area proportion, and if the area proportion exceeds a preset area threshold value, judging that the welding spot is a void defect; the bridging defect detection module is used for calculating the minimum distance between standard image data welding spots, and if the minimum distance is smaller than a preset distance threshold value, a bridging defect is judged; the confidence coefficient analysis module is used for obtaining the detection confidence coefficient and re-collecting image data for secondary analysis of a detection result lower than a confidence coefficient threshold value; and the report generation module is used for generating a structured detection report comprising the defect type and the defect severity level. The technical problem that in the prior art, welding spot cavities and bridging defect detection accuracy is not high is solved.

The invention relates to the technical field of uranium mineralization prediction, in particular to a uranium ore positioning method for oil and gas dissipation channel control, which comprises the following steps: for a drilling point preliminarily meeting a uranium mineralization standard, determining whether a temperature range of a gas generation threshold meets a mineralization achievement condition or not, and transferring a preliminary drilling area according to a fluid activity path; the direction of moving the preliminary drilling area is determined, and the initial drilling parameters are adjusted; fluid property classification is carried out, and it is determined that the uranium metallogenic potential of the paleoenvironment where the sample is located meets expectation or secondary analysis of the uranium metallogenic potential is needed when the sample is formed; determining composition characteristic types of the samples, judging whether the causes of the samples are related to biological action or not according to the proportions of the samples in different composition characteristic types, and adjusting a judgment standard for determining uranium mineralization potential; and when the uranium mineralization potential meets the expectation or the cause of the sample is irrelevant to the biological action, the coexistence of the uranium ore and the hydrocarbon inclusion is verified through drilling. According to the invention, efficient uranium ore positioning is realized by identifying the oil-gas dissipation channel and the associated ore control elements.

The invention provides a traffic load monitoring management method and system for an electric power communication network, and the method comprises the steps: carrying out the initial multilayer analysis of a collected traffic data package based on a DPI probe, and obtaining the initial analysis data of the traffic; performing windowing processing on the flow initial analysis data based on the time sliding windows to obtain a flow load index and a service load index corresponding to each time sliding window, and associating the flow load indexes with the service load indexes to form structured flow feature data; inputting the structured traffic feature data into an anomaly detection model to obtain an anomaly recognition result output by the anomaly detection model; carrying out secondary analysis on an original abnormal data packet extracted from the traffic data packet based on an abnormal identification result, associating with the traffic primary analysis data, and constructing an abnormal traffic traceability chain; and determining a load regulation and control strategy based on the abnormal traffic traceability chain in combination with a pre-constructed traffic load regulation and control decision library. The fault recovery efficiency of the power communication network is improved.

The invention relates to a test central control method and system for a test station of a transformer manufacturer, and belongs to the technical field of test control. Control demand information of current test equipment is acquired, control equipment is initially selected for control according to the control demand information of the current test equipment, and an initialization control result is generated; the method comprises the following steps: initializing a control result of each piece of control equipment, acquiring real-time state data information of each piece of control equipment, performing secondary analysis on the initialized control result according to the real-time state data information of each piece of control equipment to generate a secondary control result, and finally performing control interference analysis on the secondary analysis control result to generate a final control result. And the test equipment is controlled according to the final control result. According to the condition of the control equipment, the phenomenon of misoperation when the test equipment needing to be controlled in the central control network system of the test station of the transformer manufacturing plant is controlled is avoided, so that the control equipment can be in order.

The application discloses a quantitative analysis method of tobacco medium-polarity VOCs, which comprises the following steps: S1, inert gas is used to purge tobacco, and meanwhile, the tobacco is heated and sampled, so that the medium-polarity VOCs in the tobacco are collected; and S2, the medium-polarity VOCs in the tobacco are enriched by using MWCNTs-COOH / rGO, then, the medium-polarity VOCs are subjected to thermal desorption, and then, the medium-polarity VOCs are subjected to secondary enrichment and secondary analysis by using a cold trap, and finally, the medium-polarity VOCs are subjected to quantitative analysis by using GC-MS. When the MWCNTs-COOH / rGO is used as the adsorption medium of the thermal desorption of the purge and trap method, the flow rate, time and secondary enrichment temperature of the inert gas purging during the enrichment of the medium-polarity VOCs in the tobacco are simultaneously controlled, so that the quantitative analysis method of the medium-polarity VOCs in the tobacco is established. The enrichment effect of the medium-polarity VOCs in the tobacco is improved, and the accuracy of the quantitative analysis of the medium-polarity VOCs in the tobacco is also improved.

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.

The invention discloses an acetaldehyde rectification process based on remote supervision of Internet of Things and a residual liquid recovery method, relates to the technical field of acetaldehyde rectification, and aims to solve the problems that the existing acetaldehyde rectification process is incomplete and the residual liquid recovery effect is poor. By monitoring the residual capacity of the channel in real time, it is ensured that the selected channel can bear the data transmission quantity, transmission can be completed at the fastest speed, data congestion and transmission delay are avoided, the continuity and integrity of production data are ensured through a timing acquisition mechanism, key node data can be accurately captured through an event triggering mechanism, and the data transmission efficiency is improved. The two acquisition mechanisms are complementary, data omission and delay are avoided, preliminary and secondary analysis results and standard data are compared and evaluated, a scientific and unified quality judgment standard is established, subjectivity of manual judgment is avoided, and it is ensured that each batch of acetaldehyde meets the quality requirement.

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.

The invention discloses an AI-based competition teaching quality evaluation method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: carrying out the feature matching of a competition teaching video through taking the knowledge field with the least score of a student during competition as a feature, and determining whether the competition teaching video of the knowledge field with the least score exists or not; and performing secondary analysis on the competition teaching video to determine the competition teaching quality. The method comprises the following steps: firstly, determining the knowledge field with the least scores of students during competition, then, determining competition teaching contents by analyzing competition teaching videos for multiple times, and finally, comprehensively analyzing the knowledge field with the least scores of the students during competition and the competition teaching contents to determine whether the competition teaching quality reaches the standard or not. According to the method, the problem that teachers are only required to improve the competition teaching quality is solved, reasons for low scores of some knowledge points are determined, the corresponding teaching schemes are designed for the knowledge points, and rationalization of competition teaching is achieved.

The invention provides a Markov chain-based data analysis method and device, and the method comprises the steps: obtaining to-be-analyzed data, and carrying out the basic analysis of the to-be-analyzed data, so as to obtain a plaintext database and an encrypted database; the plaintext database comprises unencrypted plaintext data in the data to be analyzed and an analysis result of the unencrypted plaintext data; calling a pre-stored secondary analysis program, and performing secondary analysis on the encrypted file in the encrypted database to obtain an analysis result of the encrypted file; and performing data summarization on the analysis result of the unencrypted plaintext data and the analysis result of the encrypted file to obtain a summarized result. The device can perform effective data analysis on common data and encrypted data, thereby providing effective data support for intranet data security.

The invention discloses an equipment operation efficiency evaluation method, an intelligent agent and a computer readable storage medium, and relates to the technical field of automation equipment.The intelligent agent comprises an equipment end and a cloud end, and the equipment operation efficiency evaluation method comprises the steps that the cloud end receives and stores equipment operation data from the equipment end; and when a preset triggering condition is responded, analyzing the stored equipment operation data to generate a primary analysis result and a secondary analysis result, and generating an equipment operation efficiency evaluation report according to the primary analysis result and / or the secondary analysis result. By adopting the scheme of the invention, data acquisition, analysis and operation efficiency tracking of the equipment in the full life cycle are realized, the analysis result is more accurate, and after the operation efficiency is found to be abnormal, automatic notification and optimization correction can be carried out, so that the effect of predictive maintenance is realized, and the loss of the equipment caused by fault shutdown is avoided.

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 invention discloses a Chinese and English literature grammar processing method based on a mixed grammar model, which is characterized by comprising the following steps of: (1) segmenting an original literature text into words or phrases by using a word segmentation and language recognition module, and simultaneously recognizing that the language attribute of each word or phrase is Chinese or English; (2) inputting the text segmented into words or phrases into a mixed grammar model module for primary analysis; the mixed grammar model module comprises a rule sub-model and a statistical sub-model; (3) the results of the primary analysis are fused, and then total confidence Ctotal scoring is carried out; if Ctotal is greater than or equal to 0.95, the analysis result is credible; and if the Ctotal is less than 0.95, repeating the step (2) to carry out secondary analysis, tertiary analysis and the like to carry out optimization until the Ctotal is greater than or equal to 0.95. The method solves the problem that in the prior art, the literature grammar analysis precision is reduced when Chinese and English mixed long and difficult sentences and terminologies are used.

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.

Described herein are systems, apparatus, methods, and / or computer program product embodiments, and / or combinations and sub-combinations thereof which enables automated determination of index sequence(s) during DNA sequencing data analysis. As a particular application of such, embodiments of methods, systems, and media for automatically determining index sequences are disclosed herein so that sequencing results from multiple samples can be sorted and separated accurately for downstream analysis, such as secondary analysis.

For suitable compression of fluorescence signal data, provided with: a compression range setting unit (105) that detects a fluorescence signal originating from an analysis object and a fluorescence signal originating from an analysis exclusion object, distinguishing them from fluorescence signals contained in the fluorescence signal data, and sets a compression range for frames of the fluorescence signal data based on a result of the detection; a compression ratio calculation unit (106) that calculates a compression ratio based on a maximum value of the fluorescence signal intensity contained in the compression range and a maximum value of the signal intensity usable for secondary analysis;and a compression unit (107) that generates compressed fluorescence signal data by compressing the fluorescence signal data based on the compression ratio and outputs the generated compressed fluorescence signal data.;

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 the technical field of AR, and provides a reading method and device based on AR equipment, and the AR equipment. The method comprises the following steps: when the AR equipment is in a reading mode, acquiring reading data of the AR equipment at the current moment, and extracting target information from the reading data; and starting a search function of the AR equipment to search associated information associated with the target information, and displaying the associated information on the AR equipment. In this way, AR equipment data display is achieved, more detailed and specific description can be provided for displayed content in real time, and the problem that the experience of a user for reading by using AR equipment is reduced due to the fact that existing AR equipment cannot conduct secondary analysis on displayed information in a reading scene is solved.

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 discloses a machine vision-based hippocampus sex and pregnancy recognition method and an automatic sorting system, and relates to the field of image recognition, and the method comprises the steps: synchronously collecting hippocampus images and motion data through an industrial camera and an infrared sensor, and extracting form, texture and motion posture features after denoising and standardization processing; different features are learned based on a multi-branch fusion model, and model parameters are optimized through cross validation; adopting a dynamic reasoning mechanism to carry out secondary analysis on a low-confidence prediction result; and after identification, differential grabbing strategies are made for the female hippocampus, the non-pregnant male hippocampus and the pregnant male hippocampus, so that safe sorting and automatic transfer to corresponding breeding areas are ensured. The method has the advantages that efficient and accurate recognition and safe sorting of the female and male states and the pregnancy states of the hippocampus are achieved by synchronously collecting and processing data, extracting features in multiple dimensions, building a multi-branch fusion model and conducting rigorous evaluation and optimization and combining secondary reasoning and differentiated grabbing and sorting strategies.

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.