115 results about "Correlation database" patented technology

The invention discloses a casting density optimization system and method based on cooperative regulation and control of molding sand moisture and clay blue absorption amount, and relates to the technical field of casting control. According to the method, a self-cleaning wear-resistant alloy probe is used for synchronously collecting a molding sand high-frequency eddy current signal and a multi-spectrum near-infrared signal in the sand mixing process; inputting a pre-training support vector machine regression signal fusion model to obtain a real-time moisture content and a clay blue absorption amount; a preset density target threshold value is combined, a density-molding sand parameter association database is inquired to determine a parameter target interval, a regulation and control instruction is generated after a deviation value is calculated, and a water adding device and a clay conveying device are controlled to adjust the use amount; the density of the casting after regulation and control is detected, if the density does not reach the standard, model output weight iteration optimization is corrected until the density reaches the standard, the system comprises a detection module, a signal processing module, a regulation and control execution module, a density detection and correction module and a central control module, closed-loop control is achieved, and the density stability of the casting is improved.

The invention discloses an image data management method and system for high-precision size visual inspection, and relates to the technical field of image data, the image data management method for high-precision size visual inspection comprises the following steps: S1, collecting a data set, and carrying out region segmentation processing; s2, correcting and enhancing the data set, and extracting contour feature parameters; s3, mapping association is carried out, and screening classification is carried out; s4, parameters are optimized and adjusted, and a standardized size detection feature set is generated; s5, constructing a size detection model to obtain a target size quantification detection result; and S6, performing accuracy verification, and establishing an image feature size parameter association database. According to the invention, through synchronous acquisition of a multi-view image data set and a physical size calibration data set, and in combination with calibration reference of a geometric quantity standard appliance, the problems of incomplete information and large physical size mapping deviation of a traditional single-view image are solved.

The invention discloses a square billet on-line fixed-length and fixed-weight adjusting method based on a visual technology, which comprises the following steps of: acquiring an end face image of a square billet through a high-resolution industrial camera, calculating the area of the end face, combining parameters such as steel rolling weighing data, pulling speed, steel grade components and the like, establishing an associated database, and dynamically adjusting the cutting fixed-length length of the square billet. The problem that in the prior art, the fixed-length and fixed-weight precision is insufficient due to changes of steel grade components, the pulling speed and the like is solved, high-precision fixed-length and fixed-weight control is achieved, and the device has the advantages of being non-contact, resistant to high temperature, high in accuracy, high in adaptability and the like. The machine vision technology is applied to end face area detection and calculation and introduced into fixed length and fixed weight of a continuous casting billet, the fixed length of the square billet is dynamically adjusted according to the change value of the end face area of the square billet, the target of the same standard fixed weight of each square billet needed by a steel rolling mill is achieved, and the target of 2kg / t control precision can be achieved.

The invention discloses a molten metal fluidity improving method and system in the V-method casting process, and relates to the technical field of casting, a high-pressure airflow and mechanical brush composite mode is adopted for cleaning a casting mold cavity and preheating the casting mold cavity, and precoated sand is selected for preparing a sand mold through vacuum negative-pressure compaction; a sectional type negative pressure regulation and control strategy is adopted, and the stepped composite pouring gate structure is optimized; degassing the molten metal by argon or nitrogen, controlling the temperature, and adding an inoculant and a flow promoter in proportion; the casting speed is controlled according to the three-section type rate through the casting table with the adjustable inclination angle; arranging an insulated riser at the thick and large part of the casting, maintaining a negative pressure field after casting, and covering an insulating material; dividing cooling areas according to wall thickness, and gradually relieving pressure after cooling to a set temperature; and after shot blasting and flaw detection, recording data and establishing a process parameter-flowability association database. Through mold preheating, negative pressure gradient regulation and control and pouring gate design improvement, the molten metal fluidity is remarkably improved, and the casting quality stability and the production efficiency are greatly improved.

The invention discloses a chronic wound nursing scheme recommendation method and system based on clustering and a knowledge graph, and relates to the technical field of chronic wound nursing, chronic wound nursing associated data is collected to obtain chronic wound nursing multi-source data, and the chronic wound nursing multi-source data is preprocessed; and analyzing the preprocessed chronic wound nursing multi-source data, clustering the core demand problem and the nursing scheme data, and establishing a correlation database between the core demand problem and the nursing scheme. Through a technical path from multi-source data fusion to semantic cluster generation by layer clustering to cluster-level map construction to dynamic semantic matching, three major pain points of knowledge fragmentation, inaccurate demand matching and lack of recommendation basis in chronic wound nursing are solved. Compared with a traditional method, image volume accumulation captures multi-dimensional association, and semantic noise is reduced through cluster mapping; the evidence chain runs through the whole process of problems, schemes, wound types and literature sources.

The invention discloses a bridge engineering bidding and bidding quotation risk early warning and cost dynamic regulation and control system and method. The system comprises a data acquisition module, a data preprocessing module, a risk early warning module, a cost dynamic regulation and control module, a linkage execution module, a data storage and update module and a man-machine interaction module. On one hand, a multi-dimensional data acquisition system of bridge exclusive basic data, market dynamic data, policy and regulation data, bidding transaction data and construction pre-judgment data is covered, cooperative operation of static feature risk association factor extraction and dynamic time sequence risk change trend capture is realized, and the accuracy of risk assessment is improved; and meanwhile, a risk-cost closed-loop linkage mechanism is established, a cost-risk association database is constructed, and differential cost regulation and control strategies are formulated in combination with management and control targets of different stages of bidding and tendering, so that the technical problems of low regulation and control efficiency and poor adaptability are solved.

The invention relates to the technical field of industrial detection, and discloses a lithium niobate metasurface defect intelligent identification method based on reactive ion beam etching, which systematically solves the problem of scarcity of experimental data through physical driving simulation and a physics-based rendering algorithm, and provides large-scale field specific training data for a deep learning model. The bidirectional coupling simulation model generates defect morphology prediction data conforming to an etching dynamics law based on real process parameters and material parameters, the prediction data is converted into a synthetic image with real microscopic image statistical characteristics by a physical rendering algorithm, and the quality and consistency of the synthetic data are ensured by an automatic labeling and statistical verification process. According to the method, the number of samples of the ternary association database is multiplied, and extreme process conditions and rare defect modes which are difficult to obtain through experimental collection are covered.

The invention discloses an outdoor box video monitoring method, device and system based on multi-dimensional fusion. The system has the advantages that the visible light camera adopted by the main lens collects the physical state of the surface of the box body and the peripheral visible dynamic state, and the short-wave infrared equipment is adopted by the auxiliary lens to collect invisible characteristics and temperature distribution; feature points are extracted to calculate similarity, pixel-level matching is realized through a constructed perspective transformation matrix, and a correlation database is constructed; based on the multispectral data, three types of interaction events of biological interference, natural action and environmental transaction are identified in combination with deep learning, a fault and event association data set is constructed, a weight is assigned, a baseline threshold is set, and early warning is triggered when the threshold is exceeded; after early warning, the starting time and position of an event are positioned, a risk network is constructed to calculate the contribution degree of the event to determine a core risk source, three levels of risks are divided, a traceability map is generated, a differentiated operation and maintenance scheme is generated, monitoring is optimized, and the accuracy and operation and maintenance efficiency of outdoor box monitoring are improved.

The present invention relates to a system (1) which enables the time series of usage rates in the subsequent time interval to be estimated by determining the characteristics of the relevant database servers (V) by retrieving data in the form of usage rates, number of active queries, prolongation time of queries, total resource ratio parameters consumed by queries in database servers (V) in certain periods and processing them with an artificial intelligence model; the estimation results to be monitored by authorized persons through an interface (2); authorized persons to perform resource recommendations and, if needed, to perform resource (CPU and RAM) optimization on servers.

The application discloses a nearshore disaster-bearing body disaster-causing path tracing method based on digital-analog experiments, relates to the technical field of ocean dynamic disaster simulation, determines the ocean dynamic disaster characteristics of a nearshore research area, integrates multi-source historical disaster data, real-time monitoring data and disaster-bearing body background data, and constructs a time-space correlation database; based on a three-dimensional ocean and a third-generation sea wave model, a nearshore storm surge-sea wave coupling numerical model is established and verified. Through the construction of the storm surge-sea wave coupling numerical model, the present application comprehensively considers the nonlinear interaction of multiple disasters, introduces an energy conservation equation to quantify the generation, transmission and dissipation process of disaster energy, solves the limitations of traditional single-disaster linear models, and combines the real-time feedback of the three-dimensional dynamic model of the disaster-bearing body to form a closed energy-damage correlation mechanism, significantly improves the tracing accuracy of the disaster chain propagation path, and ensures that the identification of key nodes and dominant paths is more consistent with physical reality.

The application discloses a sea wave missing data prediction method based on a double-variable long short-term memory algorithm, and specifically comprises the following steps: firstly, acquiring buoy data A, using a machine learning method to interpolate the continuously lost buoy data, using a regression model method to interpolate the single lost buoy data, and forming a new buoy data set B; using a sea wave variable correlation database, finding out the variables matched with the prediction variables in the buoy data set B and constructing a double-variable set V, and simultaneously determining the training set and the verification set of each double variable; inputting the training set data of each double variable into the long short-term memory algorithm for training, obtaining the corresponding double-variable LSTM model, and finally testing the model results by using the verification set data and determining the optimal prediction model. The method can interpolate and correct the short-term missing data of the buoy, can also predict the long-term missing variables, and effectively improves the accuracy of the buoy data.

According to a molecular comparison system and a method thereof provided by the present disclosure, after a substance analysis result is obtained, on the basis of a molecular list and matching degree values as well as related questions and corresponding weights in a knowledge management system, a correlation database is used to determine and calculate by means of an AI LLM, so as to further determine the molecular species of a compound causing damage.

This disclosure provides techniques for detecting / inhibiting corrosion of in distribution / recirculation service lines and for using tin dioxide as a surfactant to coat at-risk piping surfaces. For example, disclosed techniques can be used to correlate corrosive conditions with fluid type, source and other environmental parameters, and to treat piping so as to insulate corroding areas. A stannous dosing system, and optionally, associated downstream filtration, can be used to efficiently deliver tin throughout piping surfaces at interest, and thereby facility local tin dioxide surfactant buildup to target thicknesses, at difficult to reach locations. In one embodiment, disclosed systems can be used to build a correlation database that can be used in the automated control of systems taught herein.

The invention relates to a stability on-line analysis method and system for a power system, and the method comprises the steps: building the correlation between the operation parameters of a plurality of power devices in a target power system through the historical operation data of the target power system, so as to judge whether the power devices are in operation or not. The change of the operating parameter value can cause the change rule of the operating parameter value of other power equipment. And constructing a correlation graph and a correlation database by using the rule. And before the operation parameters of the power equipment at the current moment are utilized to perform system stability analysis, the association map and the association database are utilized to verify the values of the operation parameters of the multiple pieces of power equipment, and whether the values of the operation parameters meet the operation rules of the association map and the association database or not is checked. And if not, inferring that the sensor has a fault, and re-acquiring the operating parameters. Parameters collected by the sensor are verified according to the rule, so that wrong data are prevented from being input into the model, and a wrong analysis result is obtained.

The invention relates to a control method for a continuous casting process of stainless steel, which comprises the following steps of: acquiring first information of defects of a continuous casting billet and time sequence parameters of a casting process of the continuous casting billet, and establishing a correlation database of each defect and the corresponding time sequence parameters according to the first information and the time sequence parameters; according to the correlation database, obtaining a model in which each defect is correlated with the time sequence parameters; the model comprises the following second information: an influence weight of a time sequence parameter corresponding to each defect on the defect, a cause path of each defect and a confidence coefficient corresponding to the cause path; and controlling the continuous casting process of the stainless steel according to the model to reduce the generation of defects. The method is used for continuous casting production control, and the purposes of producing high-quality stainless steel continuous casting billets, reducing the grinding ratio of the continuous casting billets and reducing the stainless steel production cost can be achieved.

The application provides a kind of intelligent semiconductor wafer spray control method and system, comprising: according to the material and surface roughness of the wafer, obtain the recommended cleaning time range of the wafer from the preset spray time-wafer attribute correlation database;The sub-area spray parameters obtained in the first three steps are integrated to form a wafer surface cleaning scheme, the cleaning scheme includes the nozzle layout, nozzle quantity, spray liquid composition and temperature of each sub-area, and the cleaning scheme is transmitted to the spray control unit;After cleaning, compare the wafer surface image with the preset standard image, calculate the similarity of the two, if the similarity is lower than the preset threshold, the number and cleaning parameters of the wafer are recorded in the abnormal cleaning log, and the wafer is transferred to the unqualified product buffer area, the spray control of the application improves the cleaning efficiency and quality, reduces the waste of resources, and provides an advanced cleaning solution for semiconductor manufacturing.

The invention discloses a pharmacogenomics report generation method and device, a medium and a product, and relates to the field. The method comprises the following steps: in response to the completion of a drug genome experiment of a first object, obtaining experimental result data of the drug genome experiment, and determining experimental result interpretation data based on a first drug gene association database; inputting the experimental result interpretation data, the object attribute information corresponding to the first object, the medical record information and the first medicine information into a pre-trained medication risk assessment model to obtain a medication risk assessment result of the first object; and generating a pharmacogenomics report of the first object based on the medication risk assessment result, the experimental result interpretation data, the object attribute information, the medical record information and the first drug information. According to the technical scheme of the invention, the problems of high threshold and low efficiency of the existing pharmacogenomics report generation are solved, the pharmacogenomics report can be automatically generated, the accuracy of the report content is improved, and the report generation cost is reduced.

Embodiments of the present invention provide systems and methods for recovering from a crash while transmitting messages between multiple devices of a communications network, or multiple nodes of a multiprocessor system, for example. The messages can include instructions related to transactions such as reading and / or writing values to a database, and a clock value and / or clock rate of one or more of the devices can be used to confirm the parties to the transaction before completing or authorizing the transaction and modifying the related database.

The application discloses a respiratory infectious disease population flow network construction and feature mining method and device based on multi-source heterogeneous traffic big data. The method collects multi-source traffic travel data such as railways, civil aviation, highways and mobile signaling and pre-processes, constructs a time-space correlation database, and generates multiple standard data tables through cleaning, desensitization, time-space alignment standardization processing. Based on the standardized data, the network topology parameters are defined, the multi-traffic mode OD flow matrix is generated, and the multiple verification and calibration are completed, the civil aviation, railway and highway hierarchical networks are respectively built, the network edge weight is fused through node alignment and interlayer coupling, the super-adjacency matrix is constructed, the multi-dimensional topological features of the multi-layer network are mined, and finally the exclusive feature data set suitable for respiratory infectious disease cross-regional transmission prediction is generated. The scheme can efficiently fuse standardized multi-source heterogeneous data, accurately construct the population flow network, and effectively improve the accuracy and timeliness of the infectious disease transmission risk assessment.

This invention discloses a PVDC coating method, electronic device, and system based on finite element analysis, comprising the following steps: First, simulating the coating process using finite element analysis, obtaining different coating qualities based on different coating standards and coating parameters; then, establishing and training a BP network model; next, optimizing the coating quality based on the trained BP network model according to different coating standards, and establishing a database based on coating standards, coating parameters, and coating quality; finally, matching the coating parameters in the database with the coating standards of the material to be coated, and performing coating based on the coating parameters. This method uses finite element analysis to simulate the coating process and establishes a relevant database. During actual coating processes, coating parameters are determined based on actual coating standards, enabling intelligent matching of coating parameters, thereby improving coating efficiency and ensuring coating quality.

The application discloses a network security vulnerability knowledge graph construction method based on HPO-BiLSTM-CRF, which comprises the following steps: collecting public vulnerability data from related databases in the network space security field, preprocessing, and constructing a data set; analyzing and extracting existing data source feature information, and constructing a network security vulnerability domain ontology model CSVDO; based on the optimized bidirectional long short-term memory network and the conditional random field fusion model HPO-BiLSTM-CRF, realizing named entity recognition and relationship extraction; adopting an integrated entity alignment method for knowledge fusion, matching different instances of the same object in different ontologies based on an improved similarity measurement algorithm, and constructing a knowledge graph; carrying out knowledge graph embedding, storing the result into a graph database, and completing knowledge graph construction and graphic visualization. The application can improve the efficiency of entity recognition and relationship extraction in network security vulnerability knowledge, and has the advantages of high efficiency and high accuracy compared with other graph construction methods.

The invention discloses a calibration method based on a blasting vibration acquisition instrument, which comprises the following steps of: data acquisition: performing blasting tests at different delay times, recording vibration waveform data by using the acquisition instrument, synchronously counting bulk distribution after blasting, and establishing an associated database of the delay times and crushing effects; calibrating by an improved linear superposition method: decomposing an actually measured single-hole waveform by using Fourier series, adding a random variable to generate a simulation waveform, calculating a theoretical particle peak vibration velocity mean value at different delay times through Monte Carlo simulation, and comparing the actually measured particle peak vibration velocity of the acquisition instrument with a theoretical value; verifying the rock crushing effect: carrying out regression analysis on the calibrated vibration data and the rock crushing effect; testing stability and repeatability: repeatedly blasting under the same delay time, checking repeatability errors of data of the acquisition instrument, and analyzing the influence of background noise on the acquired data; and calibration result output: establishing a delay time-vibration parameter-crushing effect calibration curve.

A device receives sensor measurements associated with a location and inputs to a first trained model that processes given sensor measurements and outputs indications of deviations from compliance metrics in the given sensor measurements. An indication of such a deviation is received from the first model, and the device correlates with one or more database records associated with the location. The indication of the deviation and the database record(s) are input to a second trained model that processes the deviation and correlated database records, and outputs scores indicative of respective impact of the deviation on the correlated database records. Such a score is received from the second model, and when the score does not meet a given compliance threshold score, the device generates and / or updates an operational protocol to reduce the deviation, and electronically deploys the operational protocol, in association with the location, to reduce such deviations at the location.

The invention provides a data acquisition system and a data acquisition method for self-adaptive memory testing, and belongs to the technical field of memory testing. The system comprises a test decision engine built in or connected with a memory test model and an uncertainty evaluation module, the model outputs a memory test strategy and analyzes a test result, and the evaluation module quantifies the confidence of the memory test strategy and identifies a test information demand gap; the dynamic acquisition controller is used for receiving the acquisition request sent by the test decision engine and analyzing the acquisition request into a hardware control instruction; the multi-mode sensor array is used for executing data acquisition of the memory according to the instruction; the edge feature extraction and compression module is used for processing the collected original data in real time and generating a test feature vector; and the data fusion and association database is used for receiving and storing the test feature vectors and uniformly marking timestamps and event tags for the test decision engine to call. According to the method, accurate tracing from logic errors to physical roots is realized, and the memory testing efficiency is improved.

To provide a technique for easily processing a print image associated with data in a database.SOLUTION: An information processing device stores information indicating a print image and a database associated therewith. The database includes a link field associated with the print image. The print image includes a link object. The link object indicates one of a plurality of pieces of data in the link field. The information processing device displays an outline image and provides information relating to the print image, to a user. The outline image includes a sample image and a database image. The sample image is a sample of the print image in a state in which a specific piece of data of the plurality of pieces of data is indicated as the link object. The database image indicates the database.SELECTED DRAWING: Figure 3

The invention relates to the technical field of data analysis, in particular to a server remote monitoring management system and method based on the Internet of Things, and the system comprises a data collection module, a database construction module, a data analysis module, a data accounting module, a server monitoring alarm module and an alarm notification module. According to the invention, related data of the server is acquired through the data acquisition module, a related database is established through the database construction module, the database is processed through the data analysis module to obtain a self-influence sequence and an external influence sequence, the self-influence sequence and the external influence sequence are calculated through the data accounting module, and a standard range set is determined. Whether the real-time parameters of the server are abnormal or not is judged based on the standard range set, and whether related warning is carried out or not is determined; by calculating the representation item correlation coefficient of the feature subitems, the representation item of the server is determined, the feature subitems are correlated, the problem of simplification of a data analysis level in monitoring management is solved, and the intelligent remote monitoring effect on the server is optimized.

Systems and related operating methodologies are disclosed. An exemplary operating method obtains sensor data that indicates a physiological characteristic of the user, the sensor data provided by an analyte sensor, and determines that a current level of the physiological characteristic differs from a user-specific target level by a quantifiable amount. The method continues by searching an activity correlation database to locate one or more physical activity events correlated with the quantifiable amount of the physiological characteristic. The activity correlation database is populated with event-correlated physiological responses that associate physical activity events with corresponding changes in the physiological characteristic. A recommendation is provided for the user. The recommendation specifies the one or more physical activity events.

The application relates to the technical field of industrial detection, and discloses a lithium niobate metasurface defect intelligent identification method based on reactive ion beam etching, which systematically solves the problem of experimental data scarcity through physical driving simulation and a physical-based rendering algorithm, and provides large-scale field-specific training data for a deep learning model. A bidirectional coupling simulation model generates defect morphology prediction data conforming to etching dynamics rules based on real process parameters and material parameters, a physical rendering algorithm converts the prediction data into synthetic images with real microscopic image statistical characteristics, and an automatic labeling and statistical verification process ensures the quality and consistency of the synthetic data. The method expands the sample quantity of the ternary correlation database by several times, and covers extreme process conditions and rare defect modes that are difficult to obtain through experimental acquisition.

A system for permanently storing and controlling a file and associated metadata on the blockchain. The system includes: a file deconstruction module configured to receive a file from an engine output and divide the associated metadata into multiple chunks of ASCII where the system generates a code-based reference for each chunk; and an encoding module where the system permanently encodes each chunk and code-based reference and associated metadata on the blockchain, where the blockchain is capable of attribution of the code-based reference and associated metadata in a single transaction, and where the system recalls the file and associated database upon a user request by assembling the chunks from known code-based references stored in a git-hub library.

The invention discloses a state recognition method of an adaptive gene editing laboratory mouse, and aims to solve the problem of insufficient state recognition specificity of the gene editing laboratory mouse in the prior art. The method comprises the following steps: acquiring genotypes, disease model types and experimental environment parameters of laboratory mice; optimizing detection and optical flow analysis parameters, generating a time sequence behavior track map and segmenting a key area; extracting general and pathological specific composite features and standardizing the general and pathological specific composite features; calling a genotype pathological feature association database to calibrate a weight and a threshold value, and inputting a random forest classifier recognition state of transfer learning optimization; scores are calculated through a weighted scoring model, the state is judged, and credibility is calculated through a multi-dimensional confidence evaluation model. The method is suitable for various gene editing laboratory mice and experimental environments, the accuracy and suitability of state recognition are improved, and powerful support is provided for gene therapy research and development and disease mechanism research.