68 results about "Objective analysis" patented technology

The invention discloses a synchronous analysis method, device and equipment based on multi-person postures and dynamic time warping and a computer readable storage medium, and the method comprises the steps: carrying out the processing of a video stream containing a plurality of individuals, so as to detect and output a face bounding box of each individual in a scene; for each face bounding box, generating an independent skeleton point sequence uniquely corresponding to each individual; based on each independent skeleton point sequence, constructing an independent action sequence of a plurality of individuals; calculating and outputting an individual similarity score of each individual according to each independent action sequence and the corresponding standard action template; performing statistical variance calculation on the set of the similarity scores of all the individuals to obtain a group synchronism index representing group action synchronism; and generating an analysis report containing the evaluation result of the individual performance and the group synchronism. The method has the advantages that the key points of the individuals in the multi-target scene are accurately associated, and the collaboration of group actions is objectively analyzed.

The invention discloses a wind power generation variable pitch load suppression method and system, and relates to the technical field of wind power generation variable pitch load suppression, and the method comprises the steps of basic data acquisition, basic data analysis, power generation rate analysis, load data analysis and load abnormity processing. Whether hydraulic variable pitch operation is carried out or not is judged, then whether the power generation rate of the wind driven generator is qualified or not is judged, the wind load, the inertia load, the gravity load and the hydraulic cylinder load of each blade are combined for analysis, then the load coupling value of each blade is obtained, and the load abnormal condition of the wind driven generator is obtained through analysis; the problem of limitation existing in the current wind power generation variable-pitch load suppression analysis process is solved, comprehensive and objective analysis of wind power generation variable-pitch load suppression analysis is achieved, and reliability and authenticity of a wind power generation variable-pitch load suppression analysis result are guaranteed.

The invention discloses a college dormitory noise multi-dimensional evaluation method based on psychoacoustic and sound field simulation, and belongs to the field of building environment and noise control. The objective of the invention is to solve the problem that an existing dormitory noise evaluation method is single in index and neglects subjective perception and spatial distribution heterogeneity. The method comprises the following steps: acquiring physical data and original audio of dormitory noise through multi-point synchronous acquisition; calculating loudness, sharpness, roughness, fluctuation intensity and comprehensive psychoacoustic annoyance (PA) by using a psychoacoustic model, and scientifically quantifying subjective interference of noise; meanwhile, sound field simulation is carried out based on the accurately established three-dimensional dormitory model, a sound pressure level distribution cloud picture is generated, and a standing wave phenomenon and a sound energy accumulation area are visually revealed; and finally, generating a targeted noise reduction optimization strategy by integrating subjective and objective and spatial analysis results. According to the method, full-chain diagnosis of physical characteristics-subjective perception-spatial distribution of dormitory noise is realized, and a scientific basis is provided for accurate and efficient noise treatment.

The invention relates to the technical field of computer vision, in particular to a fabric color fastness analysis method and system based on image processing. Comprising the following steps: acquiring a multispectral image of a to-be-detected fabric, and synchronously acquiring multi-factor data; processing the multispectral image to generate an enhanced image; performing image recognition on the gray sample card in the enhanced image to generate a calibration image; performing spectral data projection on the calibration image through a dimension reduction algorithm, and performing color analysis and quantification on color change to generate color difference features; extracting texture features by using a conditional generative adversarial network, carrying out image recognition and calculation on the calibration image through a decoupling algorithm, and generating a region credibility graph; and inputting the chromatic aberration features, the texture features, the multi-factor data and the regional credibility map into an image feature fusion model for mapping, performing analysis through gradient visualization, and outputting an abnormal feature saliency map. According to the method, a color fastness objective analysis closed loop is created, so that the accuracy and the universality of an analysis result are improved.

The invention provides a dynamic management method and system for nuclear medicine split charging activity. The method comprises the following steps: constructing a multi-dimensional safety dynamic graph; performing time sequence aggregation analysis based on the multi-dimensional security dynamic graph, predicting activity change of each subpackage node, and generating a node activity prediction value; according to the node activity predicted value and the multi-dimensional safety dynamic graph, multi-target analysis is carried out, and a scheduling strategy of sub-packaging tasks is generated and comprises a sub-packaging sequence of each task node, a transportation path of each sub-packaging task and a sub-packaging time window; performing simulation verification on the generated scheduling strategy, correcting an abnormal or potential risk, and generating a corrected scheduling strategy; and taking the corrected scheduling strategy as a control signal to execute a subpackage task, collecting activity, transportation path risk and time information in real time to form a feedback data set, and performing intelligent optimization according to the feedback data set.

The invention relates to the technical field of artificial intelligence health consultation, and discloses a remote health consultation method and system based on artificial intelligence. The method comprises the following steps: receiving a health consultation request submitted by a user through terminal equipment, wherein the request comprises basic health information of the user and a specific consultation question; the basic health information is preprocessed to generate a standardized health data record, and the problems that existing health information is not uniform in format and difficult to efficiently analyze are solved; the standardized data are input into the trained health assessment model, and comprehensive and objective analysis of the health condition of the user is completed; retrieving associated medical knowledge nodes from a medical knowledge graph according to a model analysis result, and providing a professional medical basis for a consultation scheme; and in combination with the medical knowledge node and the user consultation question, constructing a personalized health consultation scheme and sending the personalized health consultation scheme to the user terminal equipment. The method can quickly respond to the consultation demand of the user, guarantee the scientificity and pertinence of the consultation scheme, and effectively improve the remote health consultation experience.

The disclosure related to methods and systems for image data analysis for objectively analyzing joint motion data. In one embodiment, the methods and system disclosed herein use automated methods to capture image data, extract motion data, and determine an objective score for one or more joints in one or more motions. The system and methods disclosed herein comprise a motion capture system with one or more image capture devices to obtain motion data for a subject and using one or more regression models and analysis techniques, various objective scores can be generated related to the subject's joint motion.

The invention discloses a respiratory support aided decision-making method and system, and the method comprises the steps: obtaining lung image data of a patient, and carrying out the preprocessing of the lung image data, so as to extract a lung region of interest; inputting the lung region of interest into a prediction model to obtain image quantitative analysis data including lesion information; acquiring clinical index data of the patient, and fusing the clinical index data with the image quantitative analysis data to generate respiratory support comprehensive evaluation parameters; and outputting respiratory support decision auxiliary information based on the respiratory support comprehensive evaluation parameters. The respiratory support aided decision-making method and system provided by the invention aim at realizing automatic and objective analysis of the lung image, intelligently fusing the analysis result with the clinical indexes, and providing quantitative decision-making support for use of a respirator.

The present application relates to the technical field of teaching evaluation, and provides a class evaluation method and apparatus, a device, and a medium. The method comprises: acquiring class data and class objective information of a class to be evaluated; converting the class data into a text to be input; receiving an objective analysis instruction for said class; inputting said text and the class objective information into a preset model, so that the preset model processes said text and the class objective information according to the objective analysis instruction, to output an evaluation result of said class. By using the technical solution, the goal of executing a question-answer dialogue analysis task, a class interaction analysis task and a course standard implementation analysis task for classes can be achieved, without requiring in-person class attendance, thereby improving the class evaluation efficiency; additionally, according to the present solution, class evaluation is carried out on the basis of the class objective information, thereby ensuring the objectivity and accuracy of evaluation results.

The uncertainty analysis method of the environmental impact accounting of electrocatalytic membranes based on Monte Carlo simulation relates to the field of environmental evaluation of electrocatalytic membranes. The present invention aims to solve the problems of complex operation, time-consuming and labor-intensive in traditional methods. The present invention is based on the Monte Carlo random sampling method, adopts the total environmental impact load evaluation model of the electrocatalytic membrane, obtains the influence of resources and energy on environmental impact indicators during the life cycle of the electrocatalytic membrane, screens out key factors through sensitivity analysis, and then performs uncertainty analysis through Monte Carlo simulation to obtain the uncertainty range of the environmental impact of the electrocatalytic membrane. The present invention can quantitatively and objectively analyze the environmental impact of each indicator during the life cycle of the electrocatalytic membrane, judge the main environmental impact and uncertainty range of the electrocatalytic membrane, has accurate evaluation, convenient operation, small subjective influence, and broad application prospects. It has certain mathematical and physical meanings, high reliability, can be extended to other models, and has certain practical value.

The application discloses a remote sensing image shadow index performance evaluation method based on multiple scenes and multiple criteria, so as to evaluate the performance of different shadow indexes in urban and mountain scenes. The method comprises the following steps: data preparation, shadow extraction, sample selection, multiple criteria evaluation and comprehensive scoring. In the multiple criteria evaluation process, the shadow extraction accuracy evaluation is for the urban and mountain scenes; the separability of the shadow and the easily confused ground objects is for the urban scene, and is quantitatively evaluated by a 1.5 interquartile range (1.5IQR) separation ratio; the sensitivity of the shadow to the light intensity is for the mountain scene, and is quantitatively evaluated by the correlation between the shadow index and the cosine value of the solar incident angle (cosi). The method disclosed by the application can avoid the problems of single scene and single criterion in the traditional evaluation method, the evaluation result is intuitive and reliable, and the method has important scientific significance for objectively analyzing and evaluating the performance of the shadow index.

The present invention relates to: a composition for validating next generation sequencing (NGS) panels, comprising homozygote DNA and control genomic DNA; a kit for validation of NGS panels, comprising the composition; a validation method for NGS panels through the analysis of false negative variants, limit of detection, and false positive variants; and a method for providing information to enhance the specificity of NGS panels. In particular, the validation method of the present invention enables the objective analysis of the frequency of false negative variants, the frequency of false positive variants, and the limit of detection for NGS panels, making it effectively usable in the validation of NGS panels.

The invention provides a lesion characteristic hepatic region spatial distribution analysis method and system of a hepatic tissue pathological image. A layered framework is constructed based on hepatic tissue physiological structure logic. According to the system, the internal region of an analysis object of a pathological image, the analysis object and a hepatic lobule object are accurately segmented through an object segmentation model, and analysis object lesion features, analysis object units and relative spatial position information of the analysis object are respectively extracted. Lesion features and relative spatial position information are further fused, a hepatic region coordinate algorithm is constructed, hepatic region coordinate calculation of all sites in the whole pathological image is achieved, and subjectivity and quantization errors of a traditional method are overcome. And finally, the system counts and analyzes the lesion features of the object and the coordinate information of the hepatic region, establishes and realizes accurate and objective analysis of the lesion features in the hepatic tissue pathological image along with the spatial distribution of the hepatic region, and solves the technical bottleneck of total-graph quantitative analysis of the spatial distribution of the hepatic region in the hepatic tissue pathological image.

According to the method for judging the blasting reason of the high-pressure bypass pipeline, provided by the invention, high-precision positioning of a blasting source and objective analysis of a failure mechanism are realized through a multi-source data fusion technology in combination with crack form quantitative analysis, wall thickness reduction spatial distribution modeling and a dynamic weight distribution model. According to the method, a crack propagation path inversion technology is combined with stress field simulation, a blasting point positioning error is reduced, contribution degree weights of core factors such as wall thickness reduction and material deterioration are dynamically distributed by establishing a spatial correlation analysis model of evaluation parameters, the problem that traditional experience sorting is high in subjectivity is solved, and the method is suitable for large-scale popularization and application. Furthermore, based on a quantitative judgment rule of creep-fatigue competitive failure, the failure mode diagnosis accuracy is improved, and the service life of equipment is prolonged.

This invention discloses a water pollution data monitoring method and system based on multi-objective analysis, belonging to the field of water pollution source tracing technology. The method includes: collecting a GIS map of the target watershed and time series data on rainfall, flow, and water quality; hydrologically segmenting the flow series according to the opening and closing status of dams to obtain surface runoff and baseflow components; constructing a two-dimensional water quality observation matrix, setting pulse and delay constraints in conjunction with rainfall and runoff components, and using a non-negative matrix factorization algorithm with ratio constraints for source analysis to obtain a source feature matrix and a source contribution time coefficient matrix; identifying pollution source emission attributes based on the ammonia nitrogen to total phosphorus ratio and the correlation between the source contribution coefficient and rainfall in the source feature matrix, and marking them on the GIS map. This invention integrates dam-controlled hydrological segmentation with matrix factorization based on physicochemical constraints to achieve refined source tracing, improving the accuracy and interpretability of pollution source identification.

The invention discloses an outpatient nursing evaluation system. Relates to the technical field of outpatient nursing. Comprising a multi-source data acquisition module, a medical knowledge graph module, an intelligent evaluation module and a result analysis module, the multi-source data acquisition module is used for acquiring outpatient nursing whole-process data; the medical knowledge graph module processes the outpatient nursing full-process data, and establishes and updates a knowledge graph according to a processing result; the intelligent evaluation module completes comprehensive evaluation through a mixed evaluation model based on the updated knowledge graph and outputs an evaluation result; and the result analysis module analyzes the evaluation result, visually presents the evaluation result and generates an improvement suggestion. The evaluation data can be guaranteed to be comprehensive and accurate, and the evaluation basis is tamped; the construction of the double-track knowledge graph realizes semantic association modeling, so that the evaluation subjectivity is reduced, and the result consistency is improved; the hybrid evaluation model fuses subjective weight and objective analysis, outputs an accurate result with a confidence interval, and balances scientificity and practicability.

This invention discloses a method and system for assessing the autonomous capabilities of ground unmanned equipment, a computing device, and a storage medium. The method first constructs an assessment system for the autonomous capabilities of ground unmanned equipment, then evaluates the system using a fuzzy optimization model, a grey relational model, and fuzzy interaction entropy. The assessment results of the three models are then used as different information sources and fused using D-S evidence theory to obtain the final assessment result. The advantages of this invention are that it can accurately and quantitatively evaluate the grey, fuzzy, and difficult-to-quantify factors present in the assessment of autonomous capabilities, thereby providing a basis for objective analysis of the autonomous capability level of ground unmanned equipment.

The invention relates to an offshore platform ship collision probability calculation method and system, processing equipment and a storage medium. The method comprises the following steps: identifying an air route in a research range of a to-be-evaluated offshore platform; determining the ship traffic flow data of each identified air route, and carrying out statistics on the ship flow density of each air route in the research range of the offshore platform to be evaluated; calculating the ship flow density of each section of the air route with the specified length in the research range of the offshore platform to be evaluated; determining the corresponding ship flow occupied by the collision radius on each air route section in the research range of the to-be-evaluated offshore platform; calculating the probability of navigation lookout or early warning failure of the ship within the research range of the offshore platform to be evaluated; calculating the alarm failure probability of the offshore platform or the guard ship to be evaluated; according to the method, subjective deviation can be eliminated, objective analysis is realized, and the method can be widely applied to the field of safety production of offshore oil.

The invention discloses a method and device for objectively dividing meteorological event intensity grades and a storage medium, and the method comprises the steps: carrying out the sorting processing of a meteorological event data set of a to-be-divided region, obtaining a linearized data sequence, endowing each data sample of the data sequence with a corresponding serial number, and obtaining the serial number of each data sample; establishing a fitting model of the data sequence by adopting a least square method and taking the serial number of each data sample as an independent variable, and substituting the serial number of each data sample of the data sequence into the fitting model for calculation to obtain a fitting sequence; calculating a difference value between each data sample of the data sequence and each data sample of the fitting sequence to obtain a difference sequence; analyzing a data sample of the difference sequence, and determining an intersection point set; and dividing the meteorological event data set according to the intersection point set to obtain a series of intervals of meteorological event intensity levels. The method can objectively analyze the internal statistical law and sudden change characteristics of the data from the data, and achieves the objective division of the meteorological event intensity grade.

The invention relates to the technical field of intelligent lawn maintenance and robot perception, and discloses a lawn health monitoring and diagnosis method based on machine vision and multi-sensor fusion, and the method comprises the steps: 1, starting a machine vision module to monitor a lawn, and collecting the image information of the lawn in real time; meanwhile, a soil humidity sensor is started to detect soil humidity of different positions of the lawn in real time, and soil humidity data is acquired; the image information comprises a color index, a density index and a health condition index of the lawn; and 2, processing the image information acquired in the step 1. A machine vision module and a soil humidity sensor are adopted to automatically collect image and humidity data, objective analysis and diagnosis are carried out through an image processing and data fusion algorithm, automatic, high-precision and all-weather lawn health monitoring is achieved, and the problems that in the prior art, subjective judgment depends on manual inspection, time and labor are consumed, subjectivity is high, and management efficiency is low are solved.

The present invention discloses a method for detecting brick and stone parameters of a brick-built structure wall based on image recognition, belonging to the technical field of brick and stone detection of walls, and solving the problems of low efficiency and large error in manually detecting the brick and stone parameters on the surface of a brick-built structure wall. The present invention calculates the uniformity of brick and stone distribution, the irregularity parameter of shape, and the degree of aggregation and dispersion, quickly detects and evaluates the bricks and stones as well as the wall, reflects the current state of the bricks and stones and the wall, solves the limitations of the current traditional brick and stone of a brick-built structure wall based on manual detection, not only improves the detection efficiency, but also realizes a comprehensive and objective analysis of the feasibility of detecting the bricks and stones of a brick-built structure wall, and ensures the reliability and authenticity of the detection and analysis results of the bricks and stones of a brick-built structure wall.

A method for off-line NVH detection of a speed reducer is as follows: 1) Formulate an off-line NVH detection outline for the speed reducer, clarify the order characteristics of the speed reducer, and determine the installation positions of vibration acceleration sensors according to the order characteristics; 2) Conduct an acceptance check on the stability of off-line NVH detection of the speed reducer; 3) Through self-learning of off-line detection analysis instruments, formulate off-line NVH detection standards for the speed reducer; 4) According to the off-line NVH detection standards for the speed reducer, conduct off-line detection on the speed reducer to be detected. If the detection results meet the detection standards, the speed reducer is qualified and can be shipped out. If the detection results do not meet the detection standards, proceed to step 5); 5) Install the speed reducer that does not meet the detection standards into the vehicle, and conduct subjective driving evaluation and objective analysis of test data.

The invention discloses a blockchain platform transaction risk assessment system based on an unascertained theory, which relates to the technical field of risk assessment and comprises an objective weight analysis unit, a comprehensive weight output unit, a membership calculation unit, a measure matrix construction unit and a risk level judgment unit. According to the method, through a mode of combining subjective and objective weights of indexes, the advantages of the analytic hierarchy process in comprehensive consideration of expert experience and knowledge can be fully played, and the defects of a single method in a weight determination process can be effectively made up by means of the characteristics of the entropy weight method based on data objective analysis; according to the invention, the method achieves the more scientific, reasonable and comprehensive weight result, and builds a'technology-management-behavior 'three-dimensional collaborative dynamic coupling model through the unascertained measurement, thereby quantifying the transaction risk, generating a more accurate and comprehensive risk assessment system, improving the overall stability of the system, and achieving the more scientific and effective evaluation and supervision of all platforms.

The present application relates to the technical field of image processing and style transfer, and specifically discloses a cross-scene special effect style self-adaptive method based on meta-learning, which constructs an implicit high-dimensional meta style prototype vector library offline, dynamically selects and fuses the prototype vector according to the input scene semantic description in real time, and enhances the universality and flexibility of style transfer; scene analysis and saliency detection are used to differentially process different regions with different style transformation tolerance, thereby reducing the risk of distortion of key content; a human-computer interaction interface is introduced to balance automation and subjective setting by combining user subjective style preference with scene objective analysis results, thereby improving the controllability of the results; finally, multi-scale features are extracted through a multi-layer convolutional network, linear affine adjustment is performed in combination with a differential style field, and a target picture that maintains content recognition and is rich in artistic style is rendered. The present application improves the adaptability and effect quality of style transfer.

The invention relates to the technical field of digital gaps, and provides a specific crowd digital gap level analysis table determination method and device and electronic device.The method comprises the steps that initial text data are obtained, and an initial entry pool containing three types of initial entries is generated according to the initial text data, the entry type of the initial entry comprises an access trench entry, a use trench entry and an effect trench entry; consultation information aiming at the initial entry pool is acquired, the initial entry is modified according to the consultation information, and candidate entries and an initial scale are generated; performing multi-dimensional evaluation on each candidate entry in the initial scale, and screening out a target entry from the candidate entries according to a multi-dimensional evaluation result; and verifying whether the target scale reaches the standard or not, and outputting the target scale when the target scale reaches the standard. According to the technical scheme provided by one or more embodiments, a reliable evaluation tool suitable for the digital gap level of the specific crowd can be constructed, and comprehensive and objective analysis of the digital gap level of the specific crowd is realized.

Embodiments of the present application provide a video quality analysis method, device and program product. The method comprises: in response to a user's operation of putting a file operation area in a main interface, displaying a file identification icon corresponding to a test video and a reference video; in response to performing video quality analysis on the test video in the main interface, obtaining a first evaluation index for representing an objective analysis result of video quality and a second evaluation index for representing a subjective analysis result of video quality; and in response to a second preset operation on a quality analysis result button in the main interface, displaying the first evaluation index and / or the second evaluation index in the main interface. The method realizes the coordinated presentation of the first evaluation index and the second evaluation index.

The invention relates to a nevus flammeus lesion feature extraction method and system based on an OCTA technology. The method comprises the following steps: acquiring a cross-sectional image and a projection image of a focus through an optical coherence tomography angiography technology; extracting the boundary of epidermis and air and the boundary of dermis and epidermis based on the cross-sectional image to obtain the thickness of an epidermis layer; performing threshold segmentation and median filtering on the projection image, generating a binary image, skeletonizing the binary image, and generating a vascular skeleton diagram; calculating the average blood vessel density based on the binarized image, and calculating the average blood vessel diameter and the ratio of the blood vessel lengths of different vessel diameters based on the binarized image and the blood vessel skeleton diagram; dividing a blood vessel layering area by taking a dermis and epidermis boundary as a depth reference plane, and calculating a superficial / deep blood vessel density ratio. According to the binarized image, vertical blood vessels are recognized, and the proportion of the vertical blood vessels is calculated; and all the features are integrated into nevus flammeus lesion features. Characteristic quantification of lesion blood vessels is realized, and objective analysis basis is provided for photodynamic therapy.

The invention discloses a wine brewing rice hull quality digital analysis and discrimination system and method, and relates to the technical field of wine brewing auxiliary material quality analysis and evaluation, and the system comprises a flavor analysis module, a texture analysis module, a data processing module and a quality digital discrimination module. According to the method, GC-IMS flavor detection and texture analyzer quantitative analysis are introduced into wine brewing rice hull quality evaluation for the first time, multi-dimensional and multi-view quality scientific characterization is achieved, the blank of a traditional evaluation technology is filled up, a rice hull quality digital judgment model is constructed based on machine learning, and the evaluation accuracy is improved. Sensory evaluation depending on experience is converted into a quantitative index system based on flavor composition and texture characteristics, objective analysis and data-driven evaluation of rice hull quality are achieved, the bottleneck of traditional evaluation timeliness and precision is broken through, the efficient and accurate screening requirement is met, a scientific foundation is laid for accurate regulation and control and raw material management and control of the rice hull steaming process, and the method is suitable for large-scale popularization and application. A new technical support is provided for guaranteeing the fermentation stability and the flavor consistency of the wine body.

The present invention relates to the field of UAV network security technology, and discloses a method, system, device and medium for evaluating the effect of UAV network security. The method includes: preprocessing the index data related to UAV network security and constructing an index matrix; performing dimensionality reduction processing on the index matrix based on a non-linear incentive learning model, and extracting weight information based on a spatial information dynamic path iteration model to obtain an evaluation threshold vector and its weight vector for UAV network security; calculating a normalized comprehensive threshold based on the evaluation threshold vector and its weight vector; calculating the evaluation vectors of each node in the UAV network and comparing them with the normalized comprehensive threshold, so as to obtain the UAV network security evaluation result. The present invention is applicable to complex network protocol operation mechanisms, and fully combines the model hierarchy to achieve more accurate and objective analysis, achieve a more reliable and comprehensive evaluation effect, and is closer to the actual application scenario of the UAV network.

This invention discloses a driving ability assessment method based on eye movement signals. First, a driving scenario video is produced, and subjects immersively watch the video to distinguish between two situations. A visual stimulus presentation and feedback experiment is designed, and the data is synchronized with the eye movement data recorded by an eye tracker. After data preprocessing, features are extracted and statistically analyzed, and correlation indicators are further screened. A machine learning algorithm is used for modeling and training to determine a benchmark. A targeted attention-based CNN-LSTM feature fusion network is designed to conduct a cross-subject assessment of driving ability, which can effectively distinguish between inexperienced and experienced drivers. Based on the theories of cognitive psychology and combining subjective and objective analysis, this invention has low investment costs and is easy to implement. The subjects have a good experience and the assessment accuracy is high, which has good application prospects.