453 results about "Statistical analysis" patented technology

An apparatus and method for real-time assessment and mapping of quality of life indicators includes: selecting a set of quality of life dimensions, receiving objective quality of life indicators based on the quality of life dimensions, receiving subjective quality of life indicators based on the quality of life dimensions, performing a statistical analysis on the objective quality of life indicators and the subjective quality of life indicators, storing the objective quality of life indicators, the subjective quality of life indicators, and the results of the statistical analysis in a database, and outputting the objective quality of life indicators, the subjective quality of life indicators, and the results of the statistical analysis.

The application discloses a kind of based on running state determination continuous material processing equipment energy efficiency regulation and control method, it is related to industrial automation and process control technical field, this method includes: real-time acquisition equipment operating parameter, material state parameter and environmental parameter, form multisource operation data set, obtain the load state, health state and efficiency state of equipment, form the safety operation constraint boundary of current time, optimization is carried out by heuristic optimization algorithm, obtain optimal energy efficiency operating parameter set.Energy efficiency regulation and control instruction sequence is generated, control response deviation is calculated and corrected, and the parameter value range in threshold parameter and energy efficiency evaluation function is adjusted by periodic statistical analysis.The application realizes continuous material processing equipment energy consumption optimization by the closed-loop regulation and control method of multisource data fusion, state determination rule chain and comprehensive energy efficiency evaluation, improves the stability of system operation, control precision and working condition adaptability, enhances the reliability of long-term operation.

The present application relates to the technical field of cell function detection, and particularly relates to a method for evaluating cell function of HL-60 in monocyte activation test. The method comprises the following steps: (1) preparing HL-60 cell suspension; (2) stimulating with pyrogen; (3) quantifying total protein; (4) detecting by Western blotting; and (5) evaluating cell function. The method is based on Western blotting technology, and combines statistical analysis to realize objective and quantitative determination of the core functional index of the ability of synthesizing IL-6 protein under pyrogen stimulation, can accurately identify cells with pyrogen response function defects, provides clear experimental reference for selection of HL-60 cell generations, can pre-screen qualified cells, reduces pyrogen detection deviation caused by unqualified cell function and improper generations from the source, and effectively improves the reliability and repeatability of pyrogen detection results.

This invention belongs to the field of bridge quality inspection technology, specifically a method for evaluating the quality of box girders based on the MH wavelet average evolved power spectrum. The method includes: selecting a qualified standard beam, deploying vibration sensors to collect vertical acceleration time-history signals; preprocessing the signals by performing wavelet transform, calculating the squared modulus of the wavelet coefficients and normalizing them to obtain a three-dimensional evolved power spectrum, and then averaging the time dimension to obtain the average evolved power spectrum; extracting three characteristic parameters—frequency at maximum power, half-power bandwidth, and skewness—using the standard beam spectrum as a benchmark; repeating the above steps on the beam to be evaluated, comparing the deviations of the characteristic parameters, and combining a grading threshold and a differentiated review process to determine the quality, and statistically analyzing the batch data dispersion to provide feedback on the stability of the beam manufacturing process. This invention achieves non-destructive, batch, and accurate evaluation of box girder quality, and can effectively identify hidden defects such as insufficient elastic modulus of concrete and prestress loss.

The application provides a ship production line welding operation training system based on a digital twin model, comprising a model establishing module, a data display view module, a safety training module, a fault simulation training module and a statistical analysis module; the model establishing module is used for establishing a virtual digital twin model based on a ship welding production line, collecting multi-source data through a data interface, and mapping and updating the virtual digital twin model in real time by using the multi-source data; the data display view module comprises a production management view unit and an operation view unit; the safety training module comprises an operation demonstration unit, a process demonstration unit and an interactive training unit; the fault simulation training module comprises a fault handling simulation training unit and a fault handling process demonstration unit; and the statistical analysis module is used for statistically analyzing multi-source data and outputting optimization suggestions. The system provided by the application is helpful to improve the welding production line training efficiency.

This invention belongs to the field of medical data processing technology and provides a graphene physiotherapy data processing system and method for comparing the effects of acupoints on dysmenorrhea. Based on preset physiotherapy parameters, it records physiotherapy execution data for acupoint groups and non-acupoint groups. Multi-dimensional data of subjects are collected according to preset time nodes. Subjects are randomly divided into acupoint groups and non-acupoint groups according to preset rules, and the baseline data of the grouped subjects is used as benchmark data. The benchmark data is classified, and corresponding statistical analysis methods are used to analyze the classification results for different categories. Combining the benchmark data, the physiotherapy execution data, and the multi-dimensional data, the specificity quantification results of the acupoint effects in the acupoint groups and non-acupoint groups are calculated according to the specificity quantification formula. A standardized data report is generated based on the statistical analysis results and the specificity quantification results of the acupoint effects. This achieves objective collection, precise processing, and quantitative analysis of physiotherapy effect data for acupoints and non-acupoints.

The application provides a kind of based on knowledge graph's automobile parts supply and demand intelligent matching recommendation method and system, belongs to artificial intelligence technical field, the application synchronously obtains the transfer volume upper limit and transfer time limit of logistics node, the historical order data of demand node and supply and demand node knowledge graph, the fluctuation coefficient of historical order is formed demand matrix by statistical analysis and demand saturation, and the transfer volume upper limit and transfer time limit are respectively as capacity constraint and line edge weight to build topological graph. According to demand matrix, determine the procurement quota of each demand node, expand iteration bidding with edge weight as conversion cost, flow arbitration is carried out through transfer volume threshold value and adjusts bidding score, and supply and demand flow direction graph is generated with transaction volume as weight after allocation balance. Extract target path from flow direction graph, calculate recommended value combining transaction volume and transfer time limit and output the final supply and demand matching scheme. The application realizes dynamic flow optimization and intelligent matching recommendation of transport path in automobile parts supply and demand network.

The application belongs to the technical popularization technical field, and provides an interactive method, system and propaganda cart with technical popularization, which comprises the following steps: adopting a K-means clustering algorithm, performing clustering analysis on user data according to a preset propaganda type, and outputting a clustering cluster; based on any clustering cluster, determining a popular time period by performing time sequence statistical analysis on user historical behavior data; acquiring an existing propaganda type, comparing and analyzing the existing propaganda type with the preset propaganda type, judging whether there is a lack of the existing propaganda type compared with the preset propaganda type, and generating a first popularization sequence list; if there is a lack, performing feature similarity analysis on the missing propaganda type and the non-missing propaganda type, identifying similar propaganda types in the non-missing propaganda type, and generating a second popularization sequence list; and the application tilts key resources to high-potential user clusters and optimal popularization time periods, thereby reducing popularization cost and improving popularization cost performance.

The application discloses an audio effect evaluation method and device, equipment and a storage medium. The application inputs a preset reference sound source into an audio device to be tested for playing, wherein the preset reference sound source is a sound source determined by statistical analysis of sound sources, in combination with a parameter corrected according to a preset evaluation result and a peak factor corresponding to a music playing platform; collects audio to be tested output by the audio device to be tested when playing the preset reference sound source; determines a relative frequency response and an estimated loudness value according to a spectrum corresponding to the audio to be tested and a spectrum corresponding to the preset reference sound source; and generates an audio effect evaluation result of the audio device to be tested according to the relative frequency response and the estimated loudness value. The application evaluates the audio effect of the audio device to be tested by using the reference sound source constructed in advance, solves the problem of traditional sweep frequency signal tuning deviation, greatly reduces the number of repeated trial and error, and significantly improves the efficiency, accuracy and reliability of audio product tuning work.

This invention proposes a method for correcting abnormally high values ​​in remote sensing satellite nighttime light imagery, belonging to the field of remote sensing image processing technology. Addressing the problem of low accuracy in existing nighttime light image correction techniques, this invention acquires remote sensing satellite nighttime light imagery and preprocesses it; acquires target area boundary data and adjusts the preprocessed light imagery; statistically analyzes all light values ​​in the adjusted light imagery to identify abnormal light value intervals; performs isolated analysis on the light values ​​within the abnormal intervals to determine abnormally high values; classifies the abnormally high values ​​into at least one distribution combination based on their distribution pattern; uses a local mean fitting method to calculate correction values ​​based on the normal light values ​​surrounding the abnormally high values; and replaces each abnormally high value with its corresponding correction value to generate a corrected nighttime light image of the target area. This invention achieves high accuracy in nighttime light image correction.

A deep learning-based method and system for statistical analysis of fluorescence proportion information in microfluidic droplet arrays, belonging to the field of ddPCR detection technology, includes the following steps: S1 acquiring a three-dimensional fluorescence volume image of the droplets and performing preprocessing; S2 constructing a DropletSegNet model; S3 pre-training the DropletSegNet model constructed in S2; S4 using the three-dimensional fluorescence volume image to be tested as input to the DropletSegNet model, and transforming the original output of the DropletSegNet model into droplet analysis results with physical meaning and biological interpretability. A droplet stacking topology decoupling module is designed, modeling the adhesion decoupling as an edge classification problem on a graph structure, and using a graph neural network (GCN) for structured post-processing. This achieves accurate decoupling and segmentation even in cases of tight droplet stacking or adhesion, improving the accuracy of nucleic acid concentration calculation and positive proportion statistics.

This invention discloses a random field probability prediction method for long-term settlement of shield tunnels in heterogeneous strata, belonging to the field of underground engineering structural health monitoring and risk assessment. The method first inverts the micromechanical parameters of the strata through shield tunneling parameters, then constructs a three-dimensional anisotropic random field model, generates random field samples through K-L series expansion, and calculates the settlement field using a three-dimensional fluid-structure interaction finite element model and Monte Carlo simulation. Statistical analysis is used to predict the settlement probability, and finally, the probability of settlement exceeding limits is calculated based on reliability theory to complete the risk assessment. This invention breaks through the homogenization assumption, quantifies settlement risk, adapts to complex heterogeneous strata, provides a scientific decision-making basis for the whole life cycle management of tunnels, and has strong engineering applicability.

This invention discloses a method, system, and equipment for identifying the construction progress of roller-compacted concrete dam surfaces: It acquires multi-camera video of the roller-compacted concrete dam surface, performs time synchronization, camera calibration, coordinate unification, regional modeling, and rasterization, and preprocesses the surface video; it detects, identifies, segments, and tracks construction equipment targets and surface conditions, mapping machine trajectories and work footprints to the construction plane, thereby completing statistical analysis of coverage area, number of compaction passes, dwell time, compliance status, and abnormal events; it calculates construction progress and efficiency indicators, compares them with the plan, and outputs progress diagnosis results, early warning information, scheduling suggestions, and report interface data. This invention utilizes on-site monitoring video, improving robustness under complex lighting, occlusion, and dust conditions through multi-camera spatiotemporal registration and deduplication fusion, reducing manual inspection costs, and enhancing the objectivity, timeliness, and traceability of progress perception.

The present application relates to the field of computer data security and encryption technology, and particularly relates to a cloud government affair sensitive data encryption protection method.A cloud government affair sensitive data encryption protection method comprises the following steps: S1: obtaining a full-amount data asset composition original data set in a target cloud government affair environment, and determining a data attribute combination set according to the original data set; S2: constructing a data set for statistical analysis based on the original data set, and performing sensitivity calculation on the data attribute combination set according to the data set to obtain a sensitivity calculation result.The present application realizes accurate classification and encryption of government affair data by dynamic sensitivity evaluation and file classification, and constructs a joint sensitive probability model; and the present application combines a basic protection and a strategy inheritance double architecture, dynamically adjusts a key, and effectively improves the protection capability of temporary and time-effective files and cloud self-adaptability.

A kind of zirconium alloy water environment corrosion microscopic mechanism analysis method based on ab initio molecular dynamics, 1, construct the multi-phase interface model of metal substrate model and corrosion medium layer model combination, obtain the size information of simulation box;2, set simulation parameters for multi-phase interface model;3, carry out geometry structure optimization to multi-phase interface model and eliminate local internal stress, then carry out ab initio molecular dynamics simulation, obtain atomic evolution track and corrosion product structure;4, carry out data post-processing and statistical analysis to ab initio molecular dynamics simulation result, obtain corrosion elementary reaction path and calculate reaction energy barrier, the interaction mechanism of corrosion group and surface is analyzed by DFT method.The method can complete accurate zirconium alloy corrosion process dynamic simulation under periodic boundary condition, has higher calculation precision and is more reasonable to the description of interatomic force in system, and can also analyze the interaction mechanism between alloy and corrosion medium from atomic electronic scale.

A computer-implemented method involves receiving input with information about treatments for targets. A large language model (LLM) agent identifies tools for configuring treatments, selecting targets, and allocating treatments. The LLM agent generates and provides application programming interface (API) inputs to the tools. The LLM agent receives results from the tools, determines if the results satisfy a condition, and outputs an indication based on the results. The method includes generating computer code for treatments, applying treatments, and performing statistical analysis. The system iteratively adjusts treatments, targets, or allocations until conditions are met. The system identifies ambiguities and obtains clarifications, training the LLM agent accordingly. The processing system includes memory and processors to execute instructions, receive input, identify tools, generate API inputs, provide inputs to tools, receive results, determine conditions, and output indications.

The application provides a method for realizing high-multiple water flooding core microcosmic residual oil dynamic characterization, which comprises the following steps: reconstructing digital images of pore space distribution and two-phase fluid distribution by using image processing method according to core microcosmic distribution images at different displacement moments obtained in the displacement process; taking the pore space at the initial displacement moment as a benchmark, calculating the local size of the pore structure, determining the critical cross section of different pore regions according to the derivative of the maximum local region of the core pore size change, and dividing the core microcosmic structure into pore regions; and statistically analyzing the dynamic change characteristics of the core microcosmic properties and fluid distribution at different displacement moments in the divided local pore regions, so as to realize the core microcosmic displacement dynamic characterization. The pore region division method provided by the application can decompose the complex core microcosmic pore structure into multiple pore regions, and can directly quantitatively characterize the dynamic response of the displacement core microcosmic properties and internal fluid characteristics from the local structure.

The invention discloses a compound grease feed additive for improving breeding quality of channa maculata and application. The method comprises the following steps: (1) preparing experimental feed; the method comprises the following steps: respectively preparing an experimental group ARA 1.5 added with 1.5% of arachidonic acid and an experimental group ARA + PC added with 1.5% of arachidonic acid and 1.5% of phosphatidylcholine; (2) feeding; (3) after the culture experiment is finished, treating and detecting the channa maculata; (4) carrying out an artificial propagation test; (5) carrying out ovarian steroid synthesis related gene expression detection; and (6) carrying out data statistical analysis. By adding arachidonic acid (ARA) and phosphatidylcholine (PC) into the feed, the breeding performance of channa maculata and the quality of fry are improved, and the feed has very important significance for improving the aquatic product efficiency of high-quality fry of channa maculata in aquaculture.

A method for analyzing fashion attributes using large amounts of pieces of image data is provided. The method includes: collecting image data including at least one item; statistically analyzing on the image data based on an attribute classification AI model; and visualizing the results of the statistical analysis, wherein the attribute classification AI model is a model for detecting said at least one item included in the image data, and for recognizing, labeling and classifying fashion attributes of the at least one item.

This application provides a multi-dimensional sensing and predictive Bluetooth adaptive frequency modulation optimization method and device, relating to the field of wireless communication technology. It includes: initiating a Bluetooth adaptive frequency modulation loop; performing physical layer noise sensing and link layer statistical analysis on each communication channel; if the channel noise is normal, acquiring the time-frequency status of an external mobile wireless system; when the external mobile wireless system is in a transmitting state, performing harmonic interference prediction mapping to obtain harmonic interference prediction results; when the external mobile wireless system is in an idle state, acquiring a fine-grained channel quality classification report reported by the slave device; fusing physical layer prior labels, link layer statistical results, MWS coexistence harmonic interference prediction results, and slave device channel quality data to generate an adaptive frequency modulation channel mapping table; and applying a new frequency hopping sequence to complete channel switching at the immediate effective time. This application can achieve predictive interference avoidance, fine-grained channel management, and efficient spectrum utilization.

Disclosed are a clinical research data analysis method capable of real-time analysis and a device therefor. The clinical research data analysis method according to an embodiment of the present invention may comprise: a data collection step for collecting clinical research data input to an electronic data collection system; a data analysis processing step for generating a data analysis result by performing real-time analysis or statistical analysis by using the collected clinical research data as an input; and a service processing step for converting the data analysis result into a preset report format and providing same to at least one clinical research-related institution.

This invention discloses a kidney pathology image processing method integrating multi-tissue segmentation and quantitative lesion analysis, belonging to the field of medical image processing technology. The method includes the following steps: acquiring and preprocessing PAS-stained whole-slice images of kidney pathology; fine-tuning the segmentation model using an unsupervised domain adaptive strategy to address batch-to-batch staining differences; inputting the preprocessed image into a multi-class semantic segmentation neural network to obtain tissue segmentation results; training the network based on pixel-level annotations, employing a Class-Token mechanism, encoder-decoder architecture, and multi-scale feature fusion, and optimizing the Dice loss and binary cross-entropy loss based on joint weighting of categories and boundaries; performing statistical analysis based on the segmentation results and outputting quantitative analysis results. This invention provides an objective, reproducible, and intelligent auxiliary tool for the accurate assessment and large-scale clinical research of chronic kidney disease.

This invention discloses an automatic method for extracting ionospheric TEC anomalies based on global seismic events. The method acquires a global seismic event catalog, global ionospheric TEC data, and space weather indices, performs data preprocessing, and for each seismic event, selects those occurring during quiescent periods based on space weather conditions. Ionospheric TEC data within fixed observation windows and space windows are extracted and differiated with contemporaneous background TEC data to obtain ionospheric TEC difference values. Normalized statistical analysis is then performed on the quiescent period TEC difference values ​​and their frequency corresponding to global seismic events to obtain statistical characteristics of ionospheric TEC anomaly rates and frequencies. Random seismic events are generated globally for comparison. This method is comprehensive, programmable, and suitable for automated processing of large global samples, possessing good scientific rigor, scalability, and engineering application value.

This application relates to the field of aquatic environmental pollution monitoring technology, specifically disclosing a method for extracting the area of ​​cyanobacterial blooms in lakes. The method utilizes remote sensing data to calculate the FAI index and abundance value of the monitoring area. Based on slope and statistical analysis, the FAI threshold is determined, yielding the area and spatial distribution of cyanobacterial blooms in the study area based on FAI. The F(S)-L method is used to determine the threshold for extracting cyanobacterial blooms based on abundance, obtaining the area and spatial distribution of cyanobacterial blooms in the study area based on mixed pixel decomposition. A comparative analysis of the results of cyanobacterial bloom extraction using mixed pixel decomposition and FAI shows that the overlapping areas extracted by the two methods represent the true cyanobacterial bloom regions, thus obtaining the area and spatial distribution of cyanobacterial blooms in the study area. This method solves the problem of difficulty in determining the abundance threshold, thereby improving the accuracy of cyanobacterial bloom extraction, and also has the advantages of being rapid, objective, and easy to promote.

This invention discloses a hail identification and tracking method and system for the entire life cycle of hail embryos, relating to the field of meteorological detection. The method includes: S1 acquiring dual-polarization radar volume scan data; S2 identifying hail embryo particles; S3 determining whether the hail embryo particles are new particles, and if so, creating a life profile; S4 tracking target particles in spatiotemporal correlation and updating the life profile; S5 determining whether the target particles have transformed into hail; S6 acquiring the current life profile of the hail particles; S7 determining whether hail precipitation conditions have been triggered, and if so, proceeding to S8, otherwise returning to S1; S8 analyzing the location of the precipitation area; S9 spatially clustering the precipitation area location and generating a probability map of the hail precipitation area and early warning information. By establishing a "life profile" for each hail embryo particle that includes its trajectory, phase evolution, and environmental thermodynamic conditions, the complete process of hail embryo formation from initial formation to final hail precipitation is tracked. Based on the statistical analysis of the life profile, key transformation characteristics of different hail storm types are adaptively identified, thereby achieving early hail warning.

This application relates to a full-process teaching resource service and cloud sharing system for vocational schools, applied in the field of teaching resource management and sharing technology. The system includes: a resource governance module for acquiring original teaching resources and standardizing and integrating them to obtain the teaching resources; a sharing management module for sharing the teaching resources across various platforms via data interfaces; a teaching evaluation module for evaluating teachers' teaching quality and students' learning progress to obtain evaluation results; an intelligent recommendation module for matching and pushing teaching resources based on the evaluation results and curriculum plans; a data statistics module for statistical analysis of teaching data according to regular and ad-hoc needs; and a permission management module for setting access permissions for various roles to different teaching resources according to preset rules. This application has the effect of better utilizing teaching resources to improve teaching quality.

The application discloses a kind of nuclear power plant operation event trend analysis and prediction method and device, for the accuracy of existing statistical analysis method is insufficient in complex nuclear power environment, lack of multivariate nonlinear consideration and real-time analysis capability is short of etc., the application fuses deep learning and big data analysis technology, realizes event trend identification and high-risk area prediction.It includes: collecting operation log, sensor data and other multi-source event data, is stored after cleaning, standardization preprocessing;Extract the key features of event occurrence time, type, severity, etc., and construct a feature set;Through the analysis of time series data based on standardized event data extraction multi-LSTM based on standardized event data extraction multi-neural network model, identify long-term trends and periodic changes;Combined with deep learning and regression analysis, predict the probability of event occurrence and severity, locate high-risk period and area;Generate real-time warning information and provide prevention suggestions.