8 results about "Enhanced sensitivity" patented technology

This invention relates to an advanced method for detecting and analyzing scent profiles using an intelligent gas sensor array system. The method involves acquiring an initial data set from a sensor array exposed to a gas mixture, followed by performing a coarse analysis to determine a superset of scent profiles, which includes various subset scent profiles within the gas mixture. Based on this preliminary analysis, a set of refinement parameters is established, leading to the adjustment of operational parameters of the sensor array. These parameters include sampling rate, duration of sensing, sensor selection, heating profile, and energy feed to selected sensors, which are tailored to enhance the specificity and accuracy of the subsequent analysis. The method further includes acquiring an expanded data set under these optimized conditions, allowing for a refined analysis of the gas mixture. This refined analysis is specifically designed to accurately identify the presence of target scent profiles, utilizing the enhanced sensitivity and specificity provided by the adjusted sensor array settings.

The present disclosure provides a vacuum ultraviolet (VUV) detector for use with a liquid chromatography (LC) system (otherwise referred to herein as an LC-VUV detector) for the study of liquids. The LC-VUV detector incorporates an ultra-short pathlength flow cell into the LC-VUV detector to render liquid samples at least semi-transparent to VUV light. The ultra-short pathlength flow cell is specifically designed to: (a) interface with a focused beam of VUV light, (b) provide zero ‘dead’ volume, resulting in perfectly laminar flow through the flow cell, and (c) be modular and removable, allowing flow cells of different pathlength to be used within the LC-VUV detector. Methods for analyzing liquid samples using the LC-VUV detector and flow cell disclosed herein are also provided in the present disclosure.

The invention discloses a cascaded optical fiber temperature and salinity sensor with virtual vernier sensibilization and a measurement method thereof. The measurement method comprises the following steps: obtaining a cascaded interference spectrum through the cascaded optical fiber temperature and salinity sensor with a large dislocation structure and a small dislocation tapering structure; obtaining a corresponding filtering spectrum based on the cascaded interference spectrum; the salinity sensitivity and the first temperature sensitivity of the large dislocation structure are obtained, and the second temperature sensitivity of the small dislocation tapering structure is obtained; and performing two-parameter decoupling based on the sensitivity matrix to obtain the temperature and salinity of the environment to be measured. According to the novel spectrum reconstruction method, the sensitivity is improved by several times after virtual vernier sensitization processing is carried out on the second temperature sensitivity, and high-precision and low-cost synchronous measurement of the seawater temperature and salinity is achieved through the unique single-channel cascade optical fiber structure and the virtual vernier sensitization technology.

Provided herein are systems, devices and methods for the rapid and accurate measurement of analyte particles binding-induced aggregation of reporter particles. In the presence of analyte particles of interest, reporter particles form aggregates which increase in mean particle size as the concentration of analyte increases. From analysis of the mean particle size, determined from sample frames, the presence and / or concentration of analyte can be determined.

The present invention discloses a spectrum sensitivity enhancement method based on the correlation characteristics of nuclear magnetic resonance signals, comprising preprocessing multiple original NMR spectra to obtain an initial two-dimensional matrix; matching the initial two-dimensional matrix with correlation data blocks and obtaining a basic estimated spectrum using three-dimensional transformation, frequency domain hard threshold filtering, and first fusion weighting; matching the correlation data blocks with the basic estimated spectrum and guiding the initial two-dimensional matrix to re-match the correlation data blocks; obtaining a spatial three-dimensional correlation data group after Wiener collaborative filtering through three-dimensional transformation and Wiener collaborative filtering; and performing a second fusion weighting based on the spatial three-dimensional correlation data group after Wiener collaborative filtering to obtain a final NMR spectrum with enhanced sensitivity. The present invention can reduce pseudo-signal oscillations around the edges and avoid the classical ringing effect, while also effectively extracting and retaining the characteristic line shape of the nuclear magnetic resonance spectrum, thereby significantly improving the sensitivity of the NMR spectrum.

Provided herein are systems, devices, and methods for rapid and accurate measurement of analyte particle binding-induced aggregation of reporter particles. In the presence of analyte particles of interest, the reporter particles form aggregates whose average particle size increases with increasing analyte concentration. From analysis of the average particle size determined from the sample frame, the presence and / or concentration of the analyte can be determined.

The invention belongs to the technical field of gas-solid two-phase flow pattern recognition and electrostatic tomography, and particularly discloses a sensitivity optimization method and system of an annular array electrostatic sensor. According to the method, firstly, the influence of the number of annular electrodes, structural parameters of a single electrode and the like on the sensitivity distribution of the cross section of the pipeline is analyzed through a finite element method; secondly, establishing a relationship between sensitivity and sensor structure parameters, and analyzing and optimizing the sensor structure parameters by adopting a factorial test method; performing regression analysis on the factorial test data by adopting an RBF neural network to obtain a prediction model; and finally, optimizing the sensor structure parameters through a chaotic simulated annealing particle swarm algorithm so as to obtain a group of optimal sensor structure parameters. And a fitness value is obtained by using the prediction model in the optimization process. According to the annular array electrostatic sensor optimized through the method, the sensitivity of the annular array electrostatic sensor in the center of a pipeline is obviously improved, the uniformity of the sensitivity is obviously enhanced, and the accuracy of gas-solid two-phase flow pattern detection is obviously improved.

The application relates to the technical field of data security control, and particularly discloses a control system for data sensitivity levels based on dynamic optimization, which comprises an original data stream acquisition module, a sensitive scoring and semantic understanding module, a semantic drift quantitative evaluation module, a scoring enhancement and mapping module and a permission matching module. The original data stream acquisition module is used for acquiring original data request packets, static rule dictionaries and external event streams. The sensitive scoring and semantic understanding module is used for matching and scoring to obtain a basic sensitivity score, and performing feature extraction and vectorization conversion to obtain a data content vector and a global event context vector. The semantic drift quantitative evaluation module is used for performing semantic drift quantitative evaluation to obtain a semantic drift coefficient. The scoring enhancement and mapping module is used for performing dynamic enhancement calculation to obtain an enhanced sensitivity score, and performing boundary truncation and discretization mapping to obtain a dynamic sensitivity level. The permission matching module is used for performing permission matching between the dynamic sensitivity level and a user attribute archive to obtain an access control decision result. The application realizes millisecond-level adaptive reconstruction and accurate permission ruling of the sensitivity level.