10 results about "Peak response" patented technology

The application relates to a low-complexity adaptive beamforming method based on phase apodization cross-correlation, and belongs to the technical field of ultrasonic imaging. The method comprises the following steps: focusing and Hilbert transforming a sampling echo signal to obtain a complex echo signal; constructing multiple groups of amplitude apodization functions with different side lobe levels and peak response, weighting the echo signal, calculating and comparing the estimated variances of the apodized signals; constructing multiple groups of complementary phase apodization function pairs, phase apodizing the apodized signal with the minimum estimated variance, and calculating the real part similarity coefficient matrix of the phase-apodized signal pair; summing and averaging the multiple groups of thresholded similarity coefficient matrices and performing two-dimensional mean filtering; and multiplying the sum result of the apodized signal with the minimum variance estimation and the filtered similarity coefficient matrix to obtain the output of a beamformer and form an image. The application has the advantages of low calculation complexity, high robustness, etc., and can significantly improve the resolution and contrast of an ultrasonic image.

This invention relates to the field of medical device testing technology, specifically to the application of LC-MS / MS in determining the content of indophenol sulfate and p-cresol sulfate in a hemoperfusion device. The method includes: mixing plasma and acetonitrile, vortexing and centrifuging, collecting the supernatant, eluting the supernatant through a C18 solid-phase extraction column, collecting the eluent, mixing the eluent with water and filtering to obtain the test solution; performing liquid chromatography and mass spectrometry on the test solution, wherein the mobile phase A of the liquid chromatography is a 3-8 mmol / L gradient concentration ammonium acetate solution containing 0.05% ammonium formate by volume, and the mobile phase B is methanol; S3: calculating the concentrations of indophenol sulfate and p-cresol sulfate in the test solution based on the labeled curve. This invention, through dual purification pretreatment and multi-ion-pair threshold matching technology, can effectively remove more than 95% of interfering protein-binding toxoids. The interference peak response value in blank plasma is less than 5% of the target analyte response value, solving the detection error problem caused by interference in traditional methods.

The invention discloses a high performance liquid chromatography detection method of ethiprole, which comprises the following steps: preparing a standard solution, preparing a sample solution, and adopting a common solvent methanol for reversed-phase liquid chromatography as a diluent; a 0.5% acetic acid solution and acetonitrile are used as mobile phases for gradient elution; a C18 reversed-phase chromatographic column with porous particles on the surface and high-density coverage is adopted; respectively detecting the standard solution and the test solution according to the conditions, and comparing the spectrum and the main peak response value with the standard spectrum and the response value of the standard solution in the step S7 to calculate the mass fraction of ethiprole in the test solution. The ethiprole is efficiently and accurately detected through gradient elution optimization, acidic mobile phase combination, short column efficient separation, wavelength specificity and the like.

This invention relates to the field of intelligent monitoring technology, specifically to an intelligent monitoring method and system for water leakage in underground buildings. The method includes the following steps: collecting humidity signals, identifying source nodes, expanding the path chain, classifying response levels, and outputting a monitoring map. In this invention, by continuously collecting humidity change signals at multiple monitoring nodes and setting a baseline state offset to identify the starting node, real-time capture of leakage events can be achieved. Dynamic analysis of the humidity numerical sequence determines abrupt changes and, combined with peak response intervals, locates key nodes, effectively determining the source response location. Based on path expansion and trend judgment, a spatially hierarchical node response chain is established, and a hierarchical regional positioning map is constructed, enabling a visual representation of the leakage impact range. This method possesses the ability to quickly identify leakage sources, accurately define leakage areas, and efficiently track propagation paths, thereby improving the intelligence, precision, and response efficiency of underground building leakage monitoring.

The invention provides a mass spectrometer sample analysis process simulation method and system based on digital twinning, and the method comprises the steps: extracting a molecular structure feature vector, molecular mass and an ionization preference tag of a to-be-analyzed sample, and coding the molecular structure feature vector, molecular mass and ionization preference tag into a sample attribute vector representing the characteristics of the sample; based on the sample attribute vector and a group of preset experimental parameters, generating a simulation spectrogram vector through a digital twin model; performing quality evaluation on the simulated spectrogram vector, and calculating to obtain a spectrogram quality score; based on the main peak response intensity, constructing a weight adjustment scoring function for the spectrogram quality score to calculate an updated spectrogram quality score; searching in a preset experimental parameter space based on the updated spectrogram quality score to obtain an optimal recommended experimental parameter combination for the sample; and converting the recommended experiment parameter combination into a control instruction which can be identified by the mass spectrometer, and writing the control instruction into the mass spectrometer for execution when the equipment state is allowed. The method has wide engineering application prospects and industrial popularization value.

The invention discloses a structural earthquake vulnerability analysis method based on RBFNN and CSM. The method comprises the following steps: firstly, establishing a finite element model, determining an input parameter value range and a sample number so as to determine a total data set, selecting a training set by applying uniform design, and obtaining training set output parameters through CSM; inputting the training set into the RBFNN for training; verifying the accuracy of the RBFNN, comparing the fitting effect of the training set with the prediction effect of the test set, judging through a verification index R2, if R2 is greater than or equal to 0.9, determining the RBFNN, and if R2 is less than 0.9, adjusting the width parameter of the RBFNN until the requirement is met; the peak response considering the parameter uncertainty is obtained by applying the determined RBFNN, and a vulnerability curve is obtained by applying a logarithmic linear fitting method based on a probability earthquake demand model in theoretical vulnerability analysis, so that efficient and accurate pre-earthquake evaluation on the structure and the component is realized, and a theoretical basis is provided for subsequent seismic reinforcement.

The invention relates to a single-point rapid mass spectrometry quantitative method based on composite internal standards, which comprises the following steps: selecting one or more composite internal standards, setting the concentration of the composite internal standards, and selecting the concentration of the composite internal standards in a linear interval of a substance to be detected; when the number of the composite internal standard is one, the charge ratios of the internal standard and the substance to be detected are different; adding the internal standard into the to-be-detected sample, constructing a linear model passing through the original point and the internal standard data point, and obtaining the concentration of the to-be-detected sample; when the number of the composite internal standards is multiple, the mass-to-charge ratios of the to-be-detected object, the first internal standard to the nth internal standard are different; the internal standards with different concentrations are added into a to-be-detected sample, and the concentration of the to-be-detected sample is obtained by constructing a mass spectrum peak response value linear model of the internal standards. The method overcomes the defects that a traditional method needs multi-point calibration and needs long time, the detection efficiency is remarkably improved while the accuracy is guaranteed, and the method is particularly suitable for a small portable mass spectrometer in high-throughput rapid detection scenes such as acute poisoning, judicial expertise and food and drug safety supervision.

The application discloses a shield construction drilling coherent noise obstacle monitoring method and system, relates to the technical field of geophysical prospecting and underground engineering construction monitoring, and comprises the following steps: establishing an elastic wave discrete model based on geological survey data, defining an obstacle area through an obstacle mask function, and obtaining a three-dimensional elastic wave discrete model; taking the three-dimensional elastic wave discrete model as a propagation medium, performing propagation simulation on a time-varying spatial coherent noise field, setting a damping absorption layer at a boundary, and outputting a time sequence three-dimensional matrix; calculating a main peak time delay field of an enhanced cross-correlation function, calculating a spatial gradient field of time delay drift, extracting a gradient anomaly area through spatial filtering, judging an obstacle boundary, and outputting a visual result; introducing a coherence modulation mechanism in the noise field modeling stage, effectively enhancing the main peak response and propagation consistency of the stratum signal, and realizing real-time monitoring and early warning of the stratum obstacle body.

A weakly supervised instance segmentation method based on peak mining and filtering includes the following steps: 1) sample processing stage; 2) network configuration stage; 3) training stage; 4) test stage. The peak mining and filtering strategy designed in the application introduces feature fusion, adversarial erasing and clustering analysis to enhance the diversity and integrity of the peak response map, and through iterative retrieval and confidence update, more accurate segmentation masks are retrieved. Compared with existing weakly supervised instance segmentation methods, the segmentation algorithm of the application can realize more complete and accurate segmentation of objects of different sizes in the image, thereby effectively improving the accuracy of instance segmentation.

This invention relates to the field of brain function monitoring and discloses a closed-loop transcranial photostimulation (tPBM) modulation method and system based on near-infrared brain response characteristics. First, fNIRS signals of the target brain region of the subject are acquired. After the fNIRS signals pass through the data pathway, preprocessing and windowing calculations are performed to extract dynamic response characteristics. By setting the difference detection between the baseline and stimulation periods, blood oxygen response indicators are calculated, and based on these indicators, the current brain region is identified as having enhanced, sluggish, inhibited, or fatigued responses, yielding the change in HbO. Through the real-time acquisition of HbO changes, features such as the instantaneous rate of change and peak response of indicators like Δ[HbO] and Δ[HbR] are extracted to construct an individual's "baseline-response" curve model for parameter optimization and control, completing the tPBM stimulation modulation. This invention solves the problems of equipment redundancy, spatial interference, poor synchronization, difficulty in achieving real-time coordination between intervention and imaging, and poor measurement stability and accuracy in existing technologies.