144 results about "Digital analysis" patented technology

The invention relates to the technical field of pipeline stress fatigue detection, and discloses a natural gas station elbow tee joint stress fatigue digital intelligent analysis method and system and a product. The method comprises the following steps: establishing a multi-physics field coupling digital twinborn model of the elbow tee joint, integrating a geometric structure, material attributes and a fluid-solid coupling mechanism, and simulating flow-induced vibration stress and corrosion fatigue interaction; collecting real-time multi-source data of the elbow tee joint; real-time multi-source data is utilized to update boundary conditions and parameters of the digital twin model, and material constants are dynamically corrected through machine learning, so that self-calibration of the model is realized; performing stress distribution analysis based on the updated model to obtain stress field data, and performing fatigue crack propagation prediction in combination with real-time multi-source data to generate a prediction result; and based on the prediction result, evaluating fatigue failure risks, including crack growth rate, residual life evaluation and failure probability, and outputting alarm information or optimization decision information.

The invention discloses a market data analysis method and system based on a digital platform, and relates to the field of market data digital analysis. In combination with key technical means such as a disturbance causal graph, a time hypergraph convolutional network, an inverse distance diffusion kernel function and Vioras-Rips Complex topology modeling, a forming mechanism of sales risk nodes can be dug in a multi-dimensional and hierarchical manner. The explainable traceability analysis of the sales volume risk is realized through a graph backtracking algorithm, and the accuracy of anomaly recognition and the perspectiveness of risk response are remarkably improved.

The present disclosure provides systems and methods for analyzing a mixed population of cells. In particular, the present disclosure provides systems and methods for digital cytometry of a biological sample, digital analysis of a biological sample, digital purification of a biological sample, evaluation of a disease in an individual, and prediction of a clinical outcome of a disease therapy.

The invention relates to the technical field of electric digital data processing, in particular to an intelligent monitoring system for civil construction equipment of a thermal power plant, which comprises a digital acquisition module, a digital processing module, a digital analysis module, an anomaly identification module and an optimization module. The digital acquisition module deploys a sensor at a key position of construction equipment, executes end-side noise filtering and feature extraction, and outputs a standardized feature vector. The digital processing module constructs a digital twinborn body, calibrates sensor coordinate deviation and timestamp deviation through multi-body dynamics simulation, and generates a multi-modal synchronous data stream. And the optimization module generates an adversarial sample by using the false alarm record, updates model parameters through federated learning and deploys the model parameters to an edge end. According to the method, through edge preprocessing, twin calibration, dynamic fusion and closed-loop optimization, the problem of real-time fusion of heterogeneous sensor data is solved, and the real-time performance and accuracy of abnormal state recognition are improved.

The invention discloses a text travel content analysis method and system based on semantic recognition, and relates to the technical field of text travel data intelligent analysis, and the method comprises the steps: obtaining a multi-source UGC text travel material set, and constructing a grid time-space domain module set according to a target region grid set and a continuous historical time window; each multi-source UGC text travel material is distributed to a corresponding grid time-space domain module; extracting a grid text semantic center vector of the grid time-space domain module, and calculating a semantic drift amount of the target area grids so as to screen at least one candidate hot spot area grid from each target area grid; and calculating a corresponding grid visual semantic center vector, and calculating a cross-modal semantic similarity in combination with the second grid text semantic center vector of the candidate hot spot region grid to screen a target hot spot region grid, and generating a travel destination recommendation list. Therefore, the method can quickly focus on geographic areas with active recent contents and increased discussion popularity, and is beneficial to exploring micro-destinations of newly-emerging tourism hotspots.

This disclosure provides for devices, methods, and systems for generating a plurality of droplets within a collecting container at an extremely high rate (e.g., of at least 1 million droplets per minute, etc.), each of the plurality of droplets comprising an aqueous mixture for a digital analysis, wherein upon generation, the plurality of droplets is stabilized in position within a region of the collecting container. The inventions enable partitioning of samples for digital analyses at unprecedented rates, where readout of signals from targets within such partitions can still be achieved in accordance with various assays.

The invention provides a method and system for identifying an omissive hydrocarbon reservoir of an old oil field based on rock debris and optical fiber monitoring, and the method comprises the steps: carrying out the multi-mode digital analysis of the stock rock debris of a target well of the old oil field, and obtaining the rock physical characteristic parameters of the rock debris; the method comprises the following steps: obtaining stratum dynamic response parameters through a distributed optical fiber sensing system arranged in a sleeve of a target well of an old oil field in advance; historical logging data of the target well of the old oil field are called, and standardization processing is conducted on the historical logging data to obtain a historical logging parameter set; static errors of a historical logging parameter set are corrected through rock physical characteristic parameters, and real-time dynamic constraints are provided through stratum dynamic response parameters; according to the type characteristics of the reservoir where the target well of the old oil field is located, the corresponding multi-parameter fusion identification method is adopted to obtain the position of the missing oil and gas reservoir, and the accuracy and reliability of missing oil and gas reservoir identification are improved.

The invention relates to the technical field of communication data transmission, and discloses a radio frequency interference data transmission protection system and method, and the system comprises a radio frequency interference communication base station, a communication channel searching module, a radio frequency interference communication channel communication quality analysis module, and a radio frequency interference communication path selection module. According to the data volume of the communication data packets at the transmitting end and the data volume of the communication data packets at the receiving end, accurately analyzing and processing the communication quality of the communication channel of the communication base station at the transmitting end to realize digital analysis of radio-frequency interference prevention capability of a communication data transmission path; based on communication quality evaluation information of a communication channel of a communication base station of a transmitting end, screening, dynamic and scientific selection of an optimal communication path of communication data transmission for preventing radio frequency interference from the transmitting end to a receiving end is carried out, accurate planning of a communication data transmission path for preventing radio frequency interference is realized, and the reliability of communication data transmission is improved. And the communication quality and the user experience of the communication system are improved.

The invention relates to a pipeline elongation calculation method and system and a storage medium, and the method comprises the steps: sequentially carrying out the digital analysis, image enhancement and noise elimination processing of an input pipeline drawing, and improving the quality and consistency of original data; geometric parameters, text annotations and scale information are extracted by using an AI recognition model, and a mapping relation between a pixel coordinate system and a physical world coordinate system is established, so that automatic and intelligent extraction and structuring of engineering information are realized; constructing a three-dimensional parameterized model of the pipeline system based on the structured data, and forming a digital twin fusing geometric and material attributes; according to the method, thermal expansion calculation is carried out on each feature unit in the model based on the thermodynamic principle, correction is carried out according to the coupling relation between the feature units, accurate simulation is achieved, full-automatic digital closed loop from drawing recognition to result output is achieved, the problems that manual operation is low in efficiency and prone to making mistakes are solved, and the method is suitable for large-scale popularization and application. And the accuracy, the reliability and the engineering applicability of the calculation of the pipeline elongation are obviously improved.

The invention relates to the technical field of artificial intelligence, and discloses a material resource intelligent recommendation method based on theme coding and multi-layer feedback. The method comprises the following steps: performing digital analysis on a material and generating a unique theme code; classified storage is carried out based on theme codes; calculating topic correlation between the input material and a topic library; content correlation calculation is carried out based on the subject correlation degree, the text content correlation degree and the user feedback correlation degree; and outputting a recommendation result in combination with the personalized preference of the user. The calculation efficiency is improved through unique theme coding and XOR matching operation, the recommendation accuracy is improved through adaptive weight optimization driven by multiple layers of feedback data sources, and intelligent and accurate recommendation of material resources is achieved.

The invention discloses a geothermal resource assessment method and system based on big data analysis, and is applied to the technical field of digital analysis. The method comprises the following steps of obtaining multi-source heterogeneous data of historical drilling engineering, performing data preprocessing and feature engineering, and establishing a drilling success probability intelligent prediction-risk quantification model; in combination with geospatial information and environmental multi-source data, identifying an earth surface thermal anomaly region as a target region to perform geothermal potential assessment, and completing preliminary grading assessment of the target region; integrating seismic active band high-frequency monitoring data, inverting deep structure features by using a seismic wave velocity tomography technology, and performing multi-mode correlation matching with a target region; the coupling model realizes accurate evaluation and grading screening of a target region; and constructing a geothermal target area digital twinborn model fused with geologic and geophysical constraints, and realizing dynamic evaluation and productivity prediction of geothermal resources. Automatic geothermal resource evaluation is achieved, and efficient development and reasonable utilization of geothermal resources are promoted.

The application discloses a traffic management platform construction method and device and a traffic management method and system, acquires traffic basic data and carries out digital analysis to construct a traffic management semantic library, constructs a traffic management element periodic table from the semantic library, and the traffic management element periodic table is composed of various preset traffic management elements and traffic basic data corresponding to each type of traffic management element; the traffic management element is randomly combined to generate a corresponding traffic management scene library; the traffic management scenes in the traffic management scene library are randomly combined to generate a traffic management business library; and the traffic management platform for digital traffic management is constructed according to the traffic management semantic library, the traffic management element periodic table, the traffic management scene library and the traffic management business library, so that the programmable and calculable traffic management full chain can be realized, and templates and demonstrations can be provided for the construction of traffic management command centers in various places.

The invention provides an analysis method of an in-situ leaching process, and belongs to the technical field of process mineralogy. According to the method, multi-scale penetration power parameter determination (ore structure and ore structure) is carried out by combining mineralogy characteristic digital analysis (mineral leaching property and mineral granularity characteristics), and finally quantitative indexes of the in-situ leaching process are determined. According to the method, automatic mineralogy analysis and seepage mechanics depth are coupled, closed-loop prediction of'mineral composition-leaching kinetics-economic indexes' is quantitatively analyzed, and a new analysis method is provided for low-grade resource development. Compared with a traditional trial and error method, related data of other metallurgical processes does not need to be determined through complex tests, the theoretical recovery rate can be rapidly measured, the index prediction efficiency is improved, and a basis can be provided for subsequent production and design optimization.

The invention discloses a data processing method and device for image transmission of an unmanned aerial vehicle. The method comprises the steps that in the FPV unmanned aerial vehicle image transmission process, to-be-processed signal detection data are acquired, and the to-be-processed signal detection data are data used for representing detection of unmanned aerial vehicle simulation image transmission signals; performing signal screening processing based on time-frequency conversion on the to-be-processed signal detection data to obtain unmanned aerial vehicle image transmission signal data; and performing signal processing based on video signal recovery on the unmanned aerial vehicle image transmission signal data to obtain image transmission video data. The FPV unmanned aerial vehicle simulation image transmission is digitally analyzed through the software defined radio method, the problem that in the prior art, it is difficult for a special IC chip to support multiple frequency bands and multiple systems in the digital analysis process is solved, and digital analysis of image transmission of multiple types of unmanned aerial vehicles is achieved.

This disclosure provides for devices, methods, and systems for generating a plurality of droplets within a collecting container at an extremely high rate (e.g., of at least 1 million droplets per minute, etc.), each of the plurality of droplets comprising an aqueous mixture for a digital analysis, wherein upon generation, the plurality of droplets is stabilized in position within a region of the collecting container. The inventions enable partitioning of samples for digital analyses at unprecedented rates, where readout of signals from targets within such partitions can still be achieved in accordance with various assays.

This disclosure provides for devices, methods, and systems for generating a plurality of droplets within a collecting container at an extremely high rate (e.g., of at least 1 million droplets per minute, etc.), each of the plurality of droplets comprising an aqueous mixture for a digital analysis, wherein upon generation, the plurality of droplets is stabilized in position within a region of the collecting container. The inventions enable partitioning of samples for digital analyses at unprecedented rates, where readout of signals from targets within such partitions can still be achieved in accordance with various assays.

The invention discloses a historical paper tide record chart digitalization method and device and computer equipment, and the method comprises the steps: converting a historical paper tide record chart into an electronic format to generate a tide table image, and carrying out the geometric calibration; establishing a vector line layer based on the geometrically calibrated tide table image, and collecting a tide curve in the tide table image in an interactive digital mode; adjusting the ordinate of the tide curve, and splicing to obtain a complete tide curve; selecting a tide level record array and a high-low tide array at the hourly moment to accurately correct the complete tide curve to obtain tide level curve data consistent with an actual record value; and evaluating the precision of the tide level curve data according to the tide level record array at the hourly moment, and obtaining water level data at equal time intervals to obtain a digital tide data set. According to the method, the historical paper tide record chart can be processed in batches, the missing part can be automatically filled, the precision of the tide level curve data is improved, and digital analysis of historical tide data is facilitated.

The invention discloses a controllable nanorod array SERS (Surface Enhanced Raman Scattering) chip-based digital detection device for a serous ovarian cancer exosome phenotype as well as a detection method and application thereof, and relates to the technical field of biological detection. The device comprises a controllable nanorod array module, a high-sensitivity SERS probe module, an integrated microfluidic platform module and a digital analysis module. The controllable nanorod array module is used for accurately capturing a single exosome; the SERS probe module realizes specific recognition of multiple biomarkers on the surface of the exosome by conjugating a specific antibody and a Raman reporter molecule; the micro-fluidic platform module integrates filtering, reaction and imaging functions, so that high-throughput and automatic detection is realized; and the digital analysis module completes qualitative and quantitative analysis of exosome phenotypes. The problems that a traditional detection technology cannot analyze the phenotype difference of single exosomes, the sensitivity is low and the flux is insufficient are solved, early accurate diagnosis of the serous ovarian cancer can be achieved, and the kit has wide clinical application prospects.

A computer-implemented method for characterizing a heterogeneous material comprising dispersed components, particularly particulate components, dispersed within a continuous phase of a condensate comprises the steps of: a) providing or selecting a sample of the heterogeneous material to be analyzed; b) acquiring at least one digital image of the sample by a camera of a computing device, particularly a mobile computing device, or by a camera connected to a computing device, particularly a mobile device, and / or by reading into the computing device at least one digital image previously recorded by a stand-alone camera; and c) determining the following characteristics: size parameters, particularly granularity parameters, shape parameters, and the like, determined by image analysis in the at least one digital image. performing image analysis, in particular image particle analysis, of at least one digital image to extract one or more of the following characteristics: particle shape parameters, in particular particle distribution, orientation parameters, in particular particle orientation parameters, surface parameters, in particular particle surface parameters, roughness parameters, in particular particle roughness parameters, packing density, uneven distribution parameters, color, and / or area fraction of components, in particular particulate components; and / or area fraction of continuous phases identified by image analysis in the at least one digital image; d) making one or more of the extracted characteristics in step c) available via a user interface, via a machine interface, and / or on a data storage medium.

The invention relates to the technical field of biomedical engineering, in particular to an endometrial tissue CD56 detection method and application thereof, and the endometrial tissue CD56 detection method comprises the following steps: S1, obtaining an endometrial tissue sample by adopting a non-invasive or minimally invasive method; s2, carrying out standardization treatment on the collected endometrial tissue sample; s3, performing immunohistochemical staining; s4, performing digital analysis; and S5, judging a result. According to the research, the endometrial tissue is obtained under the endometrial sampler, the expression level of CD56 in the endometrial tissue is detected through immunohistochemistry, and an RSA patient with the too high CD56 level is subjected to immunoregulation treatment, so that the pregnancy outcome is improved, and compared with traditional diagnostic curettage, the endometrial curettage has the advantage of being small in endometrial damage, and the clinical application prospect is broad. Compared with a hysteroscope endometrial biopsy operation, the method has the advantages of being convenient to operate and low in cost.

The application relates to the field of production line monitoring, in particular to a beverage production line intelligent monitoring method and system based on digital analysis, which performs image acquisition on a product to be detected on a production line, acquires N product top views, and obtains a product segmentation image corresponding to each product top view; the N product segmentation images are superimposed to obtain one superimposed image; according to a first target area image and a second target area image divided in the superimposed image, a reference product area image and an error area image are determined; according to pixel points in the reference product area image, the error area image and the first target area image, abnormal monitoring and early warning are performed on the product to be detected; abnormal scoring is performed according to the reference product area and the error area; abnormal evaluation is performed from two directions of horizontal and vertical dimensions; compared with a conventional mode, abnormal conditions influencing the operation of the production line can be more accurately analyzed, so that the accuracy of intelligent monitoring of the production line is improved.

The invention relates to the technical field of biosafety laboratories, and discloses a biosafety laboratory digital analysis method and system based on the Internet of Things, and the method comprises the following steps: carrying out the matching detection step according to a first sensor and a second sensor of a current detection scene; respectively acquiring state data of a first key object and a second key object through two sensors, wherein the first key object is located in a previous level unit of the second key object; extracting action time and action data from the state data, and calculating an action time period, an action time difference, an action continuous value and an action associated value; calculating a first correlation value, a second correlation value and a comprehensive correlation value according to the values; and finally, comparing the comprehensive association value with a preset reference association value, and if the comprehensive association value is small, performing abnormal state early warning. According to the method, the operation state of the biosafety laboratory can be accurately analyzed in real time, abnormity can be found in time, early warning is carried out, and the biosafety of the laboratory is guaranteed.

The invention generally relates to droplet based digital PCR and methods for analyzing a target nucleic acid using the same. In certain embodiments, methods of the invention involve forming sample droplets containing, on average, a single target nucleic acid, amplifying the target in the droplets, excluding droplets containing amplicon from the target and amplicon from a variant of the target, and analyzing target amplicons.

The invention relates to the technical field of power testing, and discloses a converter transformer bushing discharge analysis method, system and device based on multi-physics field data fusion. The invention aims to solve the technical problems that the traditional observation means cannot go deep into the discharge process and the internal mechanism is difficult to reveal. According to the method, a multi-physical field combined observation and analysis framework is constructed, and an instantaneous and irreversible complex physical discharge process is converted into a four-dimensional digital image which can be played back, analyzed and quantized. The core of the method is that a plurality of discrete and mature inversion reconstruction algorithms are integrated under a unified space-time reference for collaborative data processing for the first time. An omnibearing and high-fidelity digital analysis tool is provided for researching the high-voltage discharge physical process, and the depth and efficiency of discharge experiment research are remarkably improved.

A system and method for the use of digital analysis to filter out extraneous light are disclosed. The system may include a light source to emit a light beam in a smoke detector. The system may include a first light sensor in the smoke detector to receive a reflected light beam corresponding to the light beam reflecting off a smoke particle. The system may include a second light sensor in the smoke detector to receive a noise light corresponding to ambient light in the smoke detector. The system may include a control circuit. The control circuit may be to receive the reflected light signal from a first light sensor indicative of the reflected light beam and to receive a noise signal from the second light sensor indicative of the noise light. The control circuit may be to reduce noise from the reflected light signal based on the noise signal.

The invention generally relates to droplet based digital PCR and methods for analyzing a target nucleic acid using the same. In certain embodiments, a method for determining the nucleic acid make-up of a sample is provided.

The application discloses a landscape gene identification method based on machine learning, relates to the technical field of machine learning and data science, and comprises the following steps: constructing a multi-level landscape gene classification architecture, pre-training a machine learning model based on the multi-level landscape gene classification architecture, and obtaining a landscape feature identification model; then, acquiring landscape element data corresponding to a to-be-identified landscape, calling the landscape feature identification model to analyze the landscape element data, and obtaining a landscape index identification result; then, taking the landscape index identification result as the basis, acquiring a first landscape gene identification result by using a feature deconstruction method, acquiring a second landscape gene identification result by using a prototype-variation theory, and acquiring a third landscape gene identification result by using a digital analysis strategy; and finally, taking the three results as a target landscape gene identification result, so that the efficiency and accuracy of landscape gene text identification and extraction are improved, and the application of the landscape gene is facilitated.

The invention relates to the technical field of vehicles, in particular to a correlation analysis method and device for scene working conditions between vehicles, equipment and a medium, and the method comprises the steps: obtaining a current scene working condition recognition demand, obtaining the operation data of a plurality of to-be-recognized vehicles based on the current scene working condition recognition demand, and inputting the operation data of the plurality of to-be-identified vehicles into a preset torque distribution model to obtain a rotating speed torque distribution diagram and a vehicle speed torque distribution diagram of each to-be-identified vehicle so as to generate a correlation analysis result of scene working conditions among the plurality of to-be-identified vehicles. Therefore, the problem that the accuracy of the torque recognition result is reduced due to the fact that the torque distribution proportion is not clear and fine analysis and digital description of the complex scene are lacked in the related technology in the complex scene is solved, accurate definition and digital analysis of the vehicle torque distribution are achieved by establishing the torque distribution model and the grid distribution definition, and the accuracy of the vehicle torque recognition result is improved. Therefore, correlation analysis of scene working conditions among vehicles is improved.

The present application provides an integrated droplet chip and a droplet multi-index detection method therefor and belongs to the technical field of digital PCR analyzers. The chip comprises a chip body, the chip body being constructed with at least one set of one-to-many mixing and reaction structures, a droplet generating structure and a fluorescence detection area, and each of the one-to-many mixing and reaction structures comprises: a primary reaction chamber, used for performing primary amplification, so that a detection sample with a first concentration in the primary system is amplified to form a detection sample with a second concentration, wherein the second concentration is higher than the first concentration; a plurality of sampling chambers; and the plurality of sampling chambers are controllably connected to the same primary reaction chamber at the same time; a plurality of secondary reaction chambers, which are controllably connected to the plurality of sampling chambers in a one-to-one correspondence, are used to store the droplets generated by the detection sample of the second concentration and the secondary system at the droplet generating structure and perform secondary amplification. The present application effectively increases the concentration of the detection sample. The detection sample having the increased concentration is divided into more detection samples to ensure that each detection sample has a relatively high concentration, thereby achieving multi-index detection of a low-concentration sample, ensuring the sensitivity of sample detection, and improving the accuracy of detection results.

The present invention provides a defect monitoring method and defect monitoring system. The defect monitoring method includes: establishing a digital signal database; acquiring a first optical image of a test wafer layer by layer, manually defining nuisance defects; digitally analyzing the first optical image containing the nuisance defects; and storing the obtained first digital signals in the digital signal database; acquiring a second optical image of a monitoring wafer and digitally analyzing it, outputting a second digital signal of the monitoring wafer; and comparing the second digital signal with a first digital signal in the digital signal database. If the second digital signal is identical to a first digital signal in the digital signal database, the second optical image is filtered out. By establishing a digital signal database and using digital signal analysis and comparison, defect filtering is intelligent, efficient, and highly accurate, effectively improving wafer yield.