88 results about "Profile analysis" patented technology

The invention discloses a code reconstruction method, system and device based on function recognition and a medium, and the method specifically comprises the steps: scanning a project file topological structure, and constructing a knowledge graph based on a code import relation and a technology stack feature; performing context enhancement by analyzing the code function description and combining with the knowledge graph to generate a code modification instruction set; based on the code modification instruction set, in combination with data stream sensitivity marking and performance portrait analysis, evaluating the target code to obtain an evaluation result; based on an evaluation result, matching a historical optimal practice mode through a graph neural network, and generating an optimization scheme which retains an original design style; by comparing abstract syntax tree differences between original codes and verified optimization schemes, only functional logic nodes are replaced, and legal code style features are reserved. According to the method, the efficiency and quality of code reconstruction and optimization are improved, and a more convenient, efficient and intelligent code processing tool is provided for software developers.

The invention provides a bedding structure rock finite element model reconstruction method based on a rock core digital image, and belongs to the technical field of digital rock cores, and the method comprises the following steps: S1, obtaining a gray level image of a rock sample; s2, calculating a transverse mean value of the analysis area to obtain a longitudinal gray level distribution curve; s3, applying moving average filtering and smooth filtering to obtain a smooth gray curve; s4, first-order difference is carried out on the smooth gray level curve, the position with the absolute difference value larger than a threshold value is taken as an initial stripe boundary candidate, and starting and stopping pixels, the width and the average gray level of each stripe are determined; s5, mapping each clustering label interval into a physical interval based on FEM grid partition; and S6, constructing a sample finite element model, and generating a reconstructed finite element model with real partition information. According to the method, the macrostructure features of the rock can be efficiently recognized and extracted by directly utilizing the pictures and combining gray profile analysis, and efficient and low-cost reconstruction of the finite element model of the bedding structure rock is achieved.

The invention discloses an oil leakage detection and traceability method and system for an oil-immersed power transformer, and belongs to the technical field of transformer detection. Irradiating the surface of the transformer by adopting an ultraviolet light source with controllable power to obtain an oil leakage characteristic image of the surface of the transformer; carrying out oil leakage feature image preprocessing through graying, 3 * 3 convolution kernel Gaussian filtering, 3 * 3 weighted median filtering and a contrast-limited adaptive histogram equalization algorithm in sequence; an improved double-threshold maximum between-class variance algorithm is adopted to determine a background and a fluorescence region, and oil stains are accurately extracted through connected region analysis and texture feature screening; a diffusion main direction is determined through a gradient vector weighted voting algorithm, candidate sources are screened from an easy leakage part database in combination with a K nearest neighbor algorithm, and a final leakage source is determined through gray profile analysis and verification. Through multi-algorithm cooperation, the oil leakage detection precision and traceability accuracy are effectively improved, the method is suitable for daily operation and maintenance of the transformer, and the equipment fault risk is reduced.

The invention discloses a forming method for a bent blade of a stamping and welding centrifugal pump, and relates to the field of centrifugal pump blades, which comprises the following steps: S1, three-dimensional modeling and plane unfolding; s2, wire cutting; s3, mold forming; s4, performing three-dimensional scanning; s5, arc analysis; s6, contour analysis; s7, clamping adaptation and gap detection; and S8, molding quality verification. According to the method, a stamping forming process and a three-dimensional scanning feedback technology system are combined, a closed-loop precision control system is formed, after stamping forming, a three-dimensional scanner is used for rapidly obtaining actual profile point cloud data of the blade, the actual profile point cloud data is compared with a design model in a high-precision mode, and profile deviation caused by springback is accurately quantified. And based on the deviation data, carrying out reverse compensation correction on the molded surface of the mold. The problems of profile out-of-tolerance and welding assembly clearance caused by springback are solved, and high-precision, high-efficiency and high-consistency manufacturing of the centrifugal pump bent blade is achieved.

The invention discloses a workpiece contour projection extraction method and system based on ordered point cloud, and is applied to the technical field of three-dimensional precision measurement. The method comprises the following steps of obtaining high-precision ordered point cloud data of a target workpiece and performing preprocessing; geometric analysis is carried out through the three-dimensional visual point cloud model, and section parameters are defined; performing rapid gridding processing on the ordered point cloud data through an efficient triangulation algorithm; calculating to obtain an intersection discrete point set of the cross section and the triangular mesh; and establishing a section plane local coordinate system and implementing two-dimensional projection transformation to obtain the contour projection of the target workpiece. According to the method, high-precision, high-efficiency and automatic extraction of the section contour of the workpiece can be realized, the actual requirements of industrial field online detection and quality control are met, and the method can be applied to scenes such as part size detection, reverse engineering, quality control and contour analysis in industrial manufacturing.

The invention discloses a method for evaluating and strengthening interface characteristics of a copper-based composite material, and relates to the technical field of copper-based composite materials. A soil solution and carbon quantum dots are prepared, and the carbon quantum dots are added into the soil solution; the method comprises the following steps: simulating a corrosion process of copper-based composite materials with different aluminum contents in soil solutions with different carbon quantum dot contents, and carrying out polarization curve and electrochemical impedance spectroscopy analysis on the corroded copper-based composite materials by adopting an electrochemical workstation to obtain charge transfer resistance and impedance modulus values of the copper alloy composite materials; meanwhile, SEM, EDS and three-dimensional surface contour analysis are combined, and the surface morphology and roughness of the copper-based composite material are obtained; according to the method, the electrochemical method and the corrosion surface characterization method are combined, the change of the surface and interface characteristics of the copper-based composite material corresponding to different matching materials can be rapidly evaluated, so that the purpose of protecting the alloy material is achieved, and aluminum and carbon quantum dots are found to be capable of synergistically promoting the protection of the copper-based composite material.

The invention discloses a line laser 3D contourgraph working method integrating various stray light suppression algorithms, and the method comprises the steps: constructing a stray light sensitivity weight map based on a multi-exposure image sequence through the combination of a deep convolutional neural network and a point spread function; guiding Gaussian Laplacian pyramid adaptive filtering by using the weight map, and adjusting the filtering intensity by using a residual stability index to generate a purification intensity image; performing one-dimensional profile analysis based on the purified image and the original height map, calculating a morphological distortion index, extracting an energy concentration ratio through three-level wavelet packet decomposition, and triggering morphological restoration; performing center line extraction and motion blur correlation degree calculation on the repaired image, and performing anisotropic smoothing on the height map when a threshold value is exceeded; and registering the processed multi-frame height map, constructing geometric fidelity as a feedback driving genetic algorithm to optimize an initial parameter, and restarting a whole process until the fidelity meets a precision requirement. According to the invention, the precision of 3D imaging is improved through various stray light suppression algorithms.

The application provides a bearing health state online evaluation method and system based on morphological profile analysis and federal evolution hypergraph, aiming at solving the problems of poor model self-adaptability, difficult cross-device knowledge migration and easy to be submerged early weak fault characteristics of the prior art under dynamic working conditions. The method captures the geometric profile evolution of bearing micro-damage by constructing a morphological multi-scale profile feature extraction engine, topologically preserving morphological decomposition of the vibration signal; adopts a Bayesian Poisson online learning algorithm to realize dynamic threshold adaptive updating and early warning of the health index; introduces an evolutionary hypergraph neural network to model the high-order multi-element fault propagation relationship between the bearing and the adjacent components; finally, through a federal edge collaborative framework, the incremental aggregation and knowledge migration of the cross-device model are realized under the premise of protecting data privacy. The application significantly improves the robustness of bearing fault diagnosis under variable working conditions and the sensitivity of early warning, and provides a lightweight and evolving solution for intelligent operation and maintenance in distributed industrial scenarios.

A method for managing collection of assets includes obtaining, using an action optimization manager, debtor information, associated with a set of debtor devices each executing on a computing device, from a data source, generating a set of state spaces based on debtor attributes of the debtor information, wherein each of the set of state spaces is a vector comprising debtor features obtained from the debtor information, applying an action-reward analysis on the set of debtor devices using the set of state spaces to generate state-action values for each of the set of debtor devices, applying, using the state action values, a profile analysis to obtain, for each of a set of collection devices, a debtor portfolio, and implementing collection actions based on the debtor portfolio for each of the set of debtor devices.

Techniques are provided for implementing liquid tolerance for a touch device. A sensor array of the touch device is scanned to generate response signals. In response to a response signal exceeding a touch threshold, a signal profile analysis is performed. The signal profile analysis includes sorting the response signals according to ascending order of delta positions to generate sorted signals. An extended vector of the sorted signals is formed. The extended vector of the sorted signals is analyzed using a fitted curve. In response to a feature of the fitted curve satisfying a criteria, the response signal is reported as a touch event. In response to the feature not satisfying the criteria, the response signal is rejected as a false touch.

An object of a system according to an embodiment is to analyze profile information and a desired condition of a user and perform optimal matching.SOLUTION: A system according to an embodiment includes a profile analysis unit, a matching unit, a communication support unit, a date plan suggestion unit, an advice providing unit, and a feedback collection unit. The profile analysis unit analyzes the profile information and the desired condition of the user using the generated AI. The matching unit performs optimum matching based on the profile information analyzed by the profile analysis unit and the desired condition. The communication support unit supports communication between the users matched by the matching unit. The date plan proposing unit proposes a date plan based on the desire or interest of the user. The advice providing unit provides the user with advice related to love and excitement. The feedback collection unit collects feedback from users to help improve the service.SELECTED DRAWING: Figure 1

The application discloses a straight line inspection method and system for visual positioning, and relates to the technical field of image processing. The method comprises the following steps: setting a search area according to the expected direction of a straight line, performing binarization and line segmentation in parallel to obtain a binary image and a line segmentation image; performing contour screening, candidate line segment fitting and collinear connection on the line segmentation image to obtain a line connection image; extracting the longest contour and fitting to obtain the end points of the straight line; combining the binary image, performing systematic sampling along the normal direction of the straight line, calculating the line width through profile analysis, and identifying the defects of broken line, too thin and too thick; and finally, quantitatively evaluating and automatically determining the effective length, the average line width and the defect proportion according to the preset quality standard. The method can screen reliable and complete straight line features for high-precision visual positioning, and significantly improves the robustness and practicability of the industrial visual system in complex scenes.

This invention relates to the field of intrinsic ability prediction technology and discloses a method for predicting the intrinsic ability characteristics of the elderly based on machine learning. First, intrinsic ability score data of the elderly in five dimensions, including cognition and psychology, are acquired, and heterogeneity classification is performed using latent profile analysis. Using the classification results as labels, random forest and LASSO regression are used in parallel to screen key predictive factors to form a feature subset. A classification prediction model is built based on XGBoost, and hyperparameters are optimized through cross-validation and grid search. The SHAP and LIME algorithms are integrated to achieve both global and local interpretability. Finally, the model is deployed on an online interactive platform, where inputting individual characteristics outputs the IC propensity classification, probability, and feature contribution explanation. This invention achieves accurate classification and interpretable prediction of the intrinsic abilities of the elderly, reduces the dependence of assessment on professionals and the environment, and is suitable for large-scale application in grassroots elderly care scenarios.

The application provides an age signal platform automatic deep profile analysis method based on a change point analysis, and belongs to the technical field of stratum age profile analysis. The method comprises the following steps: obtaining an original age depth sequence, pre-processing the original age depth sequence to obtain depth profile time sequence data; establishing an improved penalty value, and using a pruning accurate linear time algorithm to identify change points through dynamic programming and backtracking to obtain an optimal change point sequence and define an initial age signal platform; screening the initial age signal platform based on age background, internal difference, analysis duration and crystallization sequence to obtain a screened age signal platform; and performing inversion calculation on the screened age signal platform based on the optimal change point sequence by using a Bayesian segmentation regression model to obtain a verified age signal platform. The application solves the problems of the existing age signal platform interpretation method, such as lack of unified quantitative standard, low processing efficiency, difficulty in scaling and limited identification accuracy.

This invention relates to the field of data analysis, and more particularly to a cloud-based agricultural input information management system, comprising: a profile analysis unit for determining whether to perform target analysis on target users based on historical search status; a data analysis unit for determining the confirmation method of recommendation coefficient based on the coverage balance value of each term cluster; a cluster update unit for determining whether each term cluster should undergo association update analysis based on periodic status; an information push unit for determining recommended information based on recommendation coefficient under a first preset recommendation condition and recording the term clusters of related users as term clusters of target users under a second preset recommendation condition; and a cloud storage unit for storing the search terms and term clusters corresponding to each target user. This invention effectively improves the accuracy of agricultural input information recommendation management.

The invention relates to the technical field of medical rehabilitation information, in particular to a rheumatism rehabilitation intelligent evaluation system based on an ICF concept and a classification system, and the system comprises a multi-source data module which is used for collecting and integrating multi-dimensional data; the dynamic evaluation module is used for constructing a dynamic weight distribution model based on an ICF theory and updating an evaluation result and a radar map according to the multi-dimensional data; the data feature module is used for performing high-dimensional feature dimension reduction processing according to the evaluation result and the radar map on the basis of a potential profile analysis algorithm, and identifying a hidden subtype; and the causal intervention module is used for nesting multi-dimensional dynamic coupling evaluation of an ICF theory, subtype identification of subtype analysis and causal modeling of a structural equation model to be applied to rheumatism rehabilitation decision making based on the hidden subtype when the rheumatism rehabilitation decision making system is used. The problems that traditional evaluation dimensions are single, data are statically isolated and are difficult to adapt to individual differences are solved, and the accuracy of an intervention strategy and the rehabilitation effect of a patient are improved.

1. The name of the design product: electronic device pipeline analysis graphical user interface. 2. The use of the design product: for electronic devices. 3. The design features of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design features: front view. 5. The use of the graphical user interface: for pipeline accident analysis, including pipeline profile analysis, pipeline elevation analysis and analysis of surrounding elements. 6. The human-computer interaction mode of the graphical user interface: in the main view, clicking the menu bar content on the left side of the interface can display the corresponding content, and clicking "exit" in the upper right corner can exit the current interface. 7. Other circumstances that need to be explained: the single color block coating area in the view is the content picture, and X represents replaceable text.

The invention discloses a biomarker prediction system based on multi-omics data integration, a storage medium and a method, and relates to the technical field of data processing and bioinformatics, the system is used for performing gene mutation, CNV difference and transcriptome expression profile analysis on feature data, identifying differential expression genes related to biomarker states, and predicting biomarkers according to the differential expression genes. Obtaining a differential expression gene set; based on the gene set, an XGBoost algorithm is adopted to construct a prediction model, grid search and K-fold cross validation are combined to optimize model parameters so as to improve generalization ability and prevent overfitting, quantitative interpretation is performed on model feature importance by means of an SHAP algorithm, and an optimal key gene feature combination is screened out through multiple training validation to serve as a biomarker prediction panel. The technical effect of automatically discovering small and precise biomarker combinations from complex multi-omics data in a high-stability and high-interpretability mode is achieved, and a transparent and reliable basis is provided for clinical decisions.

The invention relates to the field of health behavior prediction and rehabilitation management, and discloses construction and application of a stroke patient home functional exercise compliance risk prediction model. The method comprises the following steps: collecting demographic and clinical data and scale evaluation data of a stroke patient, and carrying out missing value processing and preprocessing; identifying a compliance potential category by adopting potential profile analysis, and determining an optimal cutoff value of a total score of a scale through subject working characteristic curve analysis to form a dichotomy result; key predictive factors are screened in a training set by applying LASSO regression, and a'non-good compliance 'predictive model is established by incorporating the key predictive factors into multivariate Logistic regression; an online dynamic column graph webpage calculator is developed based on the Shiny technology, and a user is supported to input variables in real time and output a prediction probability and a confidence interval; and the discrimination degree, the calibration degree and the clinical net income are analyzed and evaluated through five-fold cross validation, Hosmer-Lemeshop test and decision curve analysis. According to the invention, rapid identification and hierarchical management of high-risk patients can be realized, and a basis is provided for follow-up visit and individualized intervention.

The invention provides a self-adaptive book checking system and method based on RFID and vision bimodal fusion, and aims to solve the problems that in an existing checking system, a single technology is poor in robustness and low in recognition rate in a complex library environment, and accurate wrong shelf / missing scanning judgment cannot be achieved. According to the method, real-time detection and active probing of book missing scanning are achieved through bimodal sequence cross validation, metal interference is dynamically diagnosed through mobile scanning RFID signal profile analysis, the contribution degree of RFID and visual recognition is adaptively adjusted through a real-time quality evaluation and dynamic weight fusion mechanism, and an autonomous learning mechanism is introduced to continuously optimize system performance. According to the system, the technologies are integrated on a mobile checking robot platform, a four-wheel omnidirectional mobile chassis and a controllable lifting device are utilized, path planning is performed in combination with laser navigation, high-precision, high-robustness, self-adaptive and evolvable automatic book checking in a complex indoor environment is finally realized, and the checking efficiency and the data integrity are remarkably improved.

An object of a system according to an embodiment is to enable a user who uses a dating site or an application to effectively perform pre-face-to-face communication or speaking.SOLUTION: A system according to an embodiment includes a conversation substitute part, a speech substitute part, a profile analysis part, a reaction analysis part, and a date plan proposal part. The conversation substitute unit generates a conversation content based on a user's instruction. The dictation acting part generates a dictation phrase on the basis of the conversation content generated by the conversation acting part. The profile analysis unit analyzes a profile of a user. The reaction analysis unit analyzes the reaction of the other party. The date plan proposing section proposes a date plan.SELECTED DRAWING: Figure 1

The invention relates to the technical field of image processing, in particular to an automatic inspection method and system for concrete dam cracks. According to the method, visible light and multispectral images of a dam are synchronously obtained through an unmanned aerial vehicle, a crack topology network diagram is constructed based on the visible light images, and hydrological change features are extracted based on the multispectral images; extending a section for each pixel point in the crack topology network diagram, analyzing the distribution of hydrological change characteristics in the section, calculating the seepage activity confidence coefficient of each crack, performing risk grade division and generating a concrete dam crack grade division diagram, thereby overcoming the defect that the prior art lacks the ability to analyze the seepage state of the crack, and improving the reliability of the concrete dam crack grade division diagram. Accurate diagnosis and risk assessment of fracture seepage activity are realized.

The present application relates to a kind of oil and gas exploration and development technical field, a kind of unconventional reservoir double sweet spot quantitative evaluation method, device, including in the same development horizon of the region to be evaluated, select m well to carry out fracturing test, downhole television test and production fluid profile analysis;Take the correlation degree of each double sweet spot reservoir sample with the multiple characteristic factors of logging data information is high, based on the weight coefficient of each characteristic factor obtained by grey correlation method;Determine the double sweet spot reservoir quality factor of each double sweet spot reservoir sample, when drilling geosteering, preferentially select the formation drilled by double sweet spot reservoir quality factor, when fracturing cluster design, preferentially select the cluster by double sweet spot reservoir quality factor for fracturing.The present application solves the problem that the sweet spot reservoir is directly evaluated by relying on logging static data, leading to the large deviation of the capacity of sweet spot reservoir and fracturing reconstruction, improves the matching rate of double sweet spot evaluation result and production after fracturing, improves the drilling rate of this kind of reservoir, realizes the effective fracturing of this kind of reservoir.

The application provides a bedding structure rock finite element model reconstruction method based on a core digital image, and belongs to the technical field of digital cores and comprises the following steps: S1: acquiring a gray image of a rock sample; S2: calculating and analyzing the horizontal mean value of a region to obtain a longitudinal gray distribution curve; S3: applying a sliding average filter and a smoothing filter to obtain a smoothed gray curve; S4: performing first-order differentiation on the smoothed gray curve, taking positions with an absolute difference value greater than a threshold value as initial strip boundary candidates, and determining the start and end pixels, the width and the average gray of each strip; S5: mapping each clustering label interval to a physical interval based on FEM grid partition; and S6: constructing a sample finite element model to generate a reconstructed finite element model with real partition information. The application can directly utilize a photo in combination with gray profile analysis, efficiently identify and extract macroscopic structure characteristics of rock, and realize efficient and low-cost reconstruction of a bedding structure rock finite element model.

The present invention relates to the field of computer technology and discloses a method, apparatus, device, and computer program for predicting the performance of SQL statements. The present invention inputs the collected indicator data of SQL statements that have been launched and SQL statements to be launched into a trained SQL performance profile analysis model to obtain performance prediction results for the SQL statements that have been launched and the SQL statements to be launched. The final performance prediction results for the SQL statements to be launched are then determined by combining the similarity and performance prediction results of the two, thereby greatly improving the accuracy of SQL statement performance predictions. Furthermore, the present invention predicts the performance of SQL statements before they are launched, avoiding failures after the SQL statements are launched and significantly improving the performance and stability of the database.

The invention relates to the field of data processing, in particular to a multi-source data real-time acquisition and fusion method and system, and the system comprises a portrait analysis unit which is used for determining whether to carry out portrait optimization or not according to the portrait coverage rate and the low-efficiency label proportion; the portrait optimization unit is used for determining a corresponding image optimization mode according to the operation frequency of the target user and the demand stability coefficient to be optimization processing according to the effective demand difference value or optimization processing according to the reference data state; the image analysis unit is used for determining that the portrait supplement parameter is an effective mean value or an image matching coefficient mean value according to the image diversity of the reference source and the target image proportion; the text analysis unit is used for determining a text structure coefficient according to the keyword diversity and the keyword distribution density of the effective keywords, and determining a portrait supplement parameter according to the difference degree of the text structure coefficient corresponding to the reference source; according to the invention, the accuracy of the target user portrait is effectively improved.

The invention discloses a sugarcane lodging identification method, device and equipment based on mottle characteristics of a remote sensing image, and relates to the field of remote sensing image processing, and the method comprises the steps: collecting a multispectral remote sensing image in a research region; classifying pixels in the multispectral remote sensing image by adopting a pre-trained first machine learning model, and determining a sugarcane planting area in the multispectral remote sensing image; calculating canopy coverage according to the category of each pixel in the sugarcane planting area; performing section line analysis on the sugarcane planting area along the horizontal direction and the vertical direction respectively to determine mottle characteristics; the mottle characteristics comprise the maximum background wavelength in the horizontal direction, the maximum crest number in the vertical direction, the crest period variance in the vertical direction and the crest width variance in the vertical direction; and determining the lodging state of the sugarcane in the research area by adopting a pre-trained second machine learning model according to the canopy coverage and mottle characteristics. According to the invention, the identification efficiency and precision of the sugarcane lodging state are improved.

The utility model relates to the technical field of steel rail polishing and maintenance, in particular to a lithium battery steel rail intelligent profiling refiner which comprises a power source, a lithium battery, a lithium battery and a lithium battery. The polishing transmission mechanism is used for transmitting power provided by the power source and polishing the steel rail; the lifting mechanism can drive the grinding wheel to ascend and descend in a manual and electric combined mode so as to control the grinding feeding amount and the feeding precision. The angle deflection mechanism can drive the grinding transmission mechanism and the lifting mechanism to rotate together so as to adjust the grinding angle; the control system is used for controlling the working states of the grinding transmission mechanism, the lifting mechanism and the angle deflection mechanism, monitoring the running state of the whole machine, carrying out profile analysis on a steel rail maintenance part and formulating and executing a grinding scheme; and the walking supporting mechanism is used for carrying the grinding transmission mechanism, the lifting mechanism, the angle deflection mechanism, the power source and the control system and can walk on the steel rail.

The invention relates to a method for the automated inspection of a surface (AS) of a solid object such as, for example, an aircraft surface (AS) (100); the method employing a step of detecting a defect (D) of said surface (AS) represented as a depth map image (S), successive depth profile analyses (DPi) aimed at determining a depth (Pi) for each of said depth profiles (DPi), and then a determination of a "final" depth (P) of a defect from all the depths (Pi) of said profiles. The invention further relates to a system (1) configured to perform the method. Advantageously, it is thus possible to automatically determine the depth of flatness defects in an aircraft surface (AS) (100) with a level of accuracy not yet achieved. Fig. 5