68 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 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 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.

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.

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.

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.

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.

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.

A method for performing indoor location estimation with angle of arrival (AoA) information in a wireless communication system and associated apparatus such as a wireless transceiver device are provided, where the wireless transceiver device is capable of detecting at least one signal from at least one other device in the wireless communication system. The method may include: in an online positioning phase among multiple phases of the wireless transceiver device, detecting, by using an antenna array of the wireless transceiver device, an AoA of any signal among the at least one signal from the at least one other device to determine the AoA information corresponding to the at least one other device; and in the online positioning phase, based on an AoA-related database which is established in an offline calibration phase among the multiple phases, estimating an indoor location of the wireless transceiver device according to the AoA information.

Systems, methods, and computer-readable media are provided for providing access, via a read-optimized database service, to functionally oriented pre-built metadata based logical objects. Each logical object provides access to a set of resources defined by a logical schema relevant to a functional area. Each logical schema is determined based at least in part on a read-optimized, synchronized version of one or more underlying related database structures stored to a read-optimized database accessible via the logical schema using the read-optimized database service, with the logical schema being different than the database schema of the underlying database structures. Requests to the read-optimized database service from a consumer of a particular functional area are evaluated against a particular set of logical resources associated with the functional area and translated to map to relevant underlying database structures, thus eliminating the requirement for consumer to understand underlying complex database structures as well as to shield consumers from underlying database structure changes in the future. Further some of the key text data in reference logical objects can be vectorized for usage in LLM-RAG use cases for assisting in semantic / similarity search of user queries. An attribute defaulting configuration interface and process is also described.

The application discloses a foundry compactness optimization system and method based on sand moisture and clay blue absorption amount synergistic regulation and control, relates to the technical field of foundry control, and synchronously collects sand high-frequency eddy current signals and multi-frequency spectrum near-infrared signals in a sand mixing process through a self-cleaning wear-resistant alloy probe, inputs a pre-trained support vector machine regression signal fusion model, and obtains real-time moisture content and clay blue absorption amount; in combination with a preset compactness target threshold value, a compactness-sand parameter correlation database is queried to determine a parameter target interval, a deviation value is calculated, and a regulation and control instruction is generated to control a water adding device and a clay conveying device to adjust the dosages; the compactness of the foundry product after regulation and control is detected, and if the compactness does not reach the standard, the model output weight is iteratively optimized for correction until the compactness reaches the standard; the system comprises a detection module, a signal processing module, an execution regulation and control module, a compactness detection and correction module and a central control module, realizes closed-loop control, and improves the compactness stability of the foundry product.

The present application provides a method and system for inferring an electron temperature from a hollow cathode plume color, applicable to diagnosis and inference of the electron temperature distribution of the hollow cathode under in-orbit or other vacuum environments. The method includes extraction of plume color data of the hollow cathode, two-dimensional processing of the plume color data, establishment of a correlation database between gridded colors and electron temperatures, and inference of the electron temperature distribution using the gridded colors. The inferred data of the electron temperature obtained in the present application exhibits trends consistent with measurement data obtained using a Langmuir probe, with diagnostic deviations within 30%. Based on the present application, researchers can directly leverage hollow cathode plume images to perform rapid, non-contact diagnosis of the electron temperature distribution characteristics.

The invention relates to the technical field of artificial intelligence, solves the technical problems that in the prior art, limitation of physical laws is prone to being neglected, complex coupling effects cannot be captured, large-scale strategy exploration is difficult to support, and geothermal energy overpressure mining occurs due to local optimum, and particularly relates to a development decision management method and system for geothermal energy. The method comprises the steps that geothermal multi-source data in a geothermal system is collected, a geothermal associated database is obtained through preprocessing and integration, a high-fidelity data set covering multiple scenes is generated through parameter uncertainty sampling, and a built physical sensing simulator can achieve the multi-scene high-fidelity data set while keeping the coupling physical law. The time consumption of single simulation is compressed from several hours to a second level, dynamic optimization of a development strategy under physical constraints is achieved through connection interaction of the DQN and the physical perception simulator, and the problems that the model falls into local optimum or violates the physical constraints to cause overpressure mining and the like are avoided.

This invention relates to the field of optical experimental instrument technology and discloses a method for reconstructing high-temperature flow fields based on fiber optic image bundle coupled hyperspectral imaging. The method includes: establishing a temperature correlation database; constructing a measurement system; joint calibration of the measurement system; acquiring multi-angle hyperspectral images using a single exposure of a hyperspectral camera to obtain the projected radiation intensity under each line of sight; discretizing the cross-section of the flow field to be measured into a grid; reconstructing the local emission coefficients of two characteristic bands using algebraic reconstruction techniques based on the projected radiation intensity and projection weight matrix; calculating the ratio of the local emission coefficients of the two characteristic bands for each grid; substituting this ratio into the temperature correlation database for interpolation to obtain the temperature of that grid, thus obtaining the two-dimensional temperature field distribution. This invention creatively utilizes the flexible bifurcated structure of the fiber optic image bundle to map the multi-angle spatial information of the flow field onto a single exposure of a hyperspectral camera, achieving simultaneous acquisition of spatial, angular, and spectral multi-dimensional information.

Provide a system. 【Solution means】 When planning a gathering by parents, a receiving means for receiving information through a communication medium, An analysis means for analyzing the received information and extracting requirements based on the type, schedule, and budget of the event, A collection means for collecting information from a related database in consideration of the extracted requirements, A generating and notifying means for generating a proposal for the event based on the collected information and notifying the parents via a communication medium, A correcting means for receiving the parent's feedback on the proposal and correcting the content of the proposal, An adjusting and transmitting means for adjusting the schedule, generating the final schedule and related information, and transmitting them to the parents, A notifying means for receiving voice using a voice recognition device and notifying the user of the proposal by voice and display, A system including...

The application provides a CAR-T cell therapy toxicity management optimization method and system, relates to the technical field of artificial intelligence, and comprises the following steps: acquiring clinical data of a blood tumor patient receiving a CAR-T cell therapy; performing missing value interpolation and standardization processing on baseline characteristic information and process monitoring data to obtain a standardized data set; obtaining a calibrated virtual patient physiological model according to a preset tumor cell kinetics model, an immune cell kinetics model and a toxicity reaction model; taking the calibrated virtual patient physiological model as an interactive environment to obtain a correlation database; constructing a deep Q network intelligent agent with a maximum reward function as a target to obtain an optimized deep Q network intelligent agent; and inputting the process monitoring data into the optimized deep Q network intelligent agent to obtain a target strategy, so that the individualized CAR-T treatment strategy balancing the therapeutic effect and toxicity can be automatically output by inputting the real-time monitoring data of the patient.

The invention discloses a steel pipe straightening process and equipment, and belongs to the technical field of steel pipe machining. The process comprises the following steps: selecting a to-be-straightened steel pipe, detecting the surface roughness of the to-be-straightened steel pipe, positioning and clamping, carrying out multi-dimensional runout measurement, calculating straightening parameters, carrying out closed-loop control straightening, carrying out remeasurement, taking the pipe and carrying out process monitoring. In the run-out measurement process, steel pipe surface illumination reflection intensity data are synchronously collected, a correlation judgment model is constructed in combination with surface roughness data, the validity of run-out measurement data is judged and processed, and abnormal information is fed back to a straightening parameter calculation link to adjust parameters in a targeted mode; meanwhile, an associated database of surface anomaly and straightening parameter fine adjustment can be constructed, and rapid parameter adaptation and dynamic model optimization are achieved. According to the invention, the separation logic of conventional measurement and straightening is broken through, the straightening precision and efficiency are improved, the problem of straightening deviation caused by abnormal measurement data in the existing straightening process is solved, and the device is simple in structure and adapts to the existing processing flow.

The invention provides a deep groove ball bearing outer ring sealing groove quality control and process optimization method, and the method comprises the steps: optimizing a measurement tool: replacing a traditional pistol meter with an inner diameter meter, and flexibly adjusting the measurement height in a manner of fastening a measurement point through a nut; the multi-procedure machining capacity of a numerical control lathe is utilized, and sealing groove turning machining is synchronously completed in the same procedure for machining the plane, the outer diameter and the channel of the outer ring of the bearing; heat treatment process optimization: firstly, carrying out a system test, collecting taper change data in a heat treatment process, and establishing an associated database so as to realize taper pre-judgment and differential processing; during heat treatment, the workpiece is placed with the mark facing upwards; and optimizing the detection frequency: performing whole-process inspection. According to the quality control and process optimization method for the sealing groove of the outer ring of the deep groove ball bearing, accurate control over the quality of the sealing groove is achieved through comprehensive optimization of the measuring tool, the machining procedure, the heat treatment process and the detection frequency.

The invention relates to a compressed air energy storage configuration simulation platform design method, and the method comprises the steps: constructing a correlation database containing a new energy scene and a compressed air energy storage equipment model, and automatically matching the multi-source heterogeneous data of the new energy scene and the compressed air energy storage equipment model; designing a multi-objective optimization framework fusing dynamic weight adjustment and a self-correction function, and dynamically distributing the weight of the whole life cycle cost and the weight of the new energy consumption rate according to the new energy permeability and the load peak valley characteristic; an integrated platform integrating data management, algorithm decision and simulation verification is constructed, an operation framework including scene management, parameter configuration and task scheduling is established, and scheme simulation, result visualization and multi-scheme interaction are carried out, so that a whole-process compressed air energy storage configuration simulation system is obtained. Therefore, the problems that in existing compressed air energy storage configuration simulation, data association is low in efficiency, decision adaptability is poor, and result display is not visual are solved.

The invention discloses construction of a teenager suicide self-injury grading early warning system based on an XGBoost model, and relates to the technical field of suicide self-injury grading early warning, and the technical scheme is characterized in that the teenager suicide self-injury grading early warning system comprises a data acquisition module, a data storage module, a data processing module and a result output module. The data acquisition module is used for inputting related data of psychological states of teenagers acquired by various psychological test scales; the data storage module is used for storing the collected related data of the psychological state of the teenagers and constructing a related database; the data processing module analyzes the related data of the psychological state of the teenager through an XGBoost model, and analyzes the suicide and self-injury probability of the teenager; and the result output module outputs the analysis result of the XGBoost model and divides the suicide and self-injury risk levels of the teenagers into 1-4 levels. The system can effectively evaluate the psychological state of teenagers according to the existing psychological state evaluation scale, and predicts individuals or groups with suicide and self-injury behaviors.

A system is provided.SOLUTION: The system includes means for a user to input a request using a device, means for a server to receive and analyze the user's request, means for the server to collect necessary information from relevant databases and external APIs, means for the server to generate content with a generative AI model based on the collected information, means for the server to review and modify the generated content, means for the server to deliver the final content to the user's device, and means for the user to confirm, edit, and publish the received content.SELECTED DRAWING: Figure 1

Provided is a quality management system for an energy device that is composed of a plurality of electrode layers and an electrolyte layer, the quality management system making it possible to efficiently acquire a feature amount of an intermediate article that strongly affects the performance of the energy device without significantly reducing the operation rate of a manufacturing line in a manufacturing process of the energy device, and to manage the performance quality of the energy device at the time of shipment inspection. A quality management system for an energy device for determining the quality of an intermediate product in an energy device manufacturing process comprises: a first inspection data acquisition device that acquires first inspection data related to a material of the intermediate product; a second inspection data acquisition device that acquires second inspection data, which is a feature amount related to the intermediate product; a data storage / calculation device that calculates a performance prediction value of the energy device on the basis of correlation data that has been accumulated in the past, using the first inspection data and the second inspection data as inputs; and a data output device that outputs the first inspection data, the second inspection data, and the performance prediction value, the quality management system being characterized in that: the intermediate product is a functional sheet that functions as an electrode layer or a carrier conductive layer of the energy device, and a slurry in which a functional material, a solvent, and a binder that constitute the functional sheet are mixed; and the data storage / calculation device has a correlation database in which performance information of the energy device and manufacturing conditions and structure information of the functional sheet and the slurry are accumulated, the data storage / calculation device calculating the performance prediction value of the energy device by inputting the structure information of the intermediate product acquired from at least one of the first inspection data and the second inspection data into the correlation database, and determining the quality of the intermediate product.

A network vulnerability rapid scanning system and method, comprising a rapid scanning command module for initiating network system vulnerability rapid scanning instructions; a first scanning judgment module for receiving rapid scanning command module instructions to determine whether to perform a first scan on the network system; a comprehensive scanning module for calling all vulnerability detection programs in the vulnerability database to perform a comprehensive scan on the network system when a first scan is required, and analyzing the results; a partial scanning module for calling part of the vulnerability detection programs in the vulnerability database to perform a rapid scan on the network system based on the last scan result and the vulnerability correlation database when a first scan is not required, and generating a scan result after the scan is completed. The above scheme realizes rapid scanning of the network system, is efficient and has relatively high reliability, and further improves the user experience.

The application relates to the technical field of full-face tunnel boring machines, in particular to a TBM cutterhead rotating speed self-adaptive control method. The method adjusts the rotating speed of the cutterhead according to real-time parameters by establishing a relevant database and a random forest algorithm optimization model, realizes self-adaptive control of the rotating speed of the cutterhead, and can greatly improve the efficiency of advancing construction and the operation accuracy of the TBM.

This invention claims protection for a method for selectively heating multilayer materials using microwaves based on a preferred frequency, comprising the following steps: S1, constructing a microwave heating system model based on the structure, dielectric properties, and geometric model of the microwave heating cavity of the multilayer material; S2, dividing a preset microwave frequency range into several frequency steps, obtaining temperature distribution data of each layer of the material at each frequency through multiphysics simulation, and establishing a frequency-temperature distribution correlation database; S3, calculating the temperature difference between the target layer and the non-target layer at different frequencies, and constructing an interlayer temperature difference control function; S4, selecting a preferred frequency sequence that maximizes the temperature difference between the target layer and the non-target layer through the interlayer temperature difference control function, and dynamically adjusting the frequency sequence according to the interlayer temperature difference threshold; S5, sequentially outputting microwave frequency control signals according to the preferred frequency sequence to perform time-segmented frequency-varying heating of the multilayer material, obtaining the result that the target layer is selectively heated while the temperature of the non-target layer remains at a low level.

In some embodiments, the present invention provides for an exemplary computer system which includes at least the following components: an adaptive self-trained computer engine programmed, during a training stage, to electronically receive an initial speech audio data generated by a microphone of a computing device; dynamically segment the initial speech audio data and the corresponding initial text into a plurality of user phonemes; dynamically associate a plurality of first timestamps with the plurality of user-specific subject-specific phonemes; and, during a transcription stage, electronically receive to-be-transcribed speech audio data of at least one user; dynamically split the to-be transcribed speech audio data into a plurality of to-be-transcribed speech audio segments; dynamically assigning each timestamped to-be-transcribed speech audio segment to a particular core of the multi-core processor; and dynamically transcribing, in parallel, the plurality of timestamped to-be-transcribed speech audio segments based on the user-specific subject-specific speech training model.