47results about How to "Preserve structural features" patented technology

The invention provides a gait recognition method based on a partitioned matrix. Firstly, extracting single-frame images from a video, then carrying out grey scale transformation on the single-frame images, using the background subtraction method to extract person body targets, using mathematical morphology to fill the holes of binary images, and extracting profiles of the person by means of single connection analysis so that the person bodies are positioned in the middle and are uniformly in the size of 64 * 64 pixels; observing the periodic change of the gait according to elliptical short axis and eccentricity fitted in image regions after the standard centralization of each frame image in a gait video sequence; using a gait energy diagram to extract the integral characteristic of the gait in the one period, dividing GEI into sub-blocks by means of the partitioned matrix, eliminating the sub-blocks which are useless to classification in a self-adapting manner, and adopting the method, which combines the two-dimensional principal component analysis of a sub-block mode with the two-dimensional linear discriminant analysis, to further extract local characteristics; and integrating the characteristics of each effective sub-block into a whole during the classification recognition, and adopting a nearest neighbor classifier to perform identification judgment. The method is effective for the recognition of the gait of knapsack change.

The invention provides a preparation method of organic silicon modified polyether polyol. The preparation method comprises following steps: step one, preparing terminal hydrogen containing silicone oil; step two, preparing allyl polyether; and step three, preparing organic silicon modified polyether polyol. The preparation method has the advantages that the structural characteristics of common polyether polyol are maximally preserved; the speed of reactions between modified polyether polyol and isocyanate is similar with that of reactions between common polyether polyol and isocyanate; modified polyether polyol can completely or partially replace common polyether polyol; modified polyether polyol can be used with polyester polyol to synthesize polyurethane, moreover, the reaction process is mild and easily controllable, the synthesized polyurethane is used to paint a material, the coated material is smooth and has a good wear resistant performance, and no surface migration happens.

The invention provides a finger vein identifying method based on characteristic value normalization and bidirectional weighting. The method comprises the following steps of: (1) collecting finger vein images by an image collecting device; (2) carrying out preprocessing on the collected finger vein images, wherein the preprocessing comprises the steps of graying the color images, extracting finger areas, respectively eliminating salt and pepper noise and Gauss noise by adopting a combined filter, segmenting and binarizing the images by adopting a local dynamic threshold algorithm, de-noising by adopting an area eliminating method, extracting the finger vein venation images by finger contour markers, and standardizing the sizes of the images into that of the uniform images; (3) extracting a finger vein characteristic by a two-dimensional main component analyzing algorithm with weighting in two directions of the line; and (4) matching and identifying by a most adjacent classifier. The invention is used for a finger vein identifying system, obviously enhances the identifying speed of the finger veins, and has stable and high identifying rate.

The invention relates to a storage system reference evaluation program generating method and apparatus and belongs to the high-performance computing performance evaluation field. The storage system reference evaluation program generating method includes the following steps that: intermediate codes are obtained from a standardized source program; slicing starting points of the intermediate codes are identified; static program slicing is carried out based on identified slicing starting points; and simplified codes can be generated based on obtained static program slices. The method is based program slicing technology; data dependence, control dependence and communication dependence are analyzed in a compiler; all statement operation related to input and output is automatically extracted so as to form the compilable, executable, manually-readable and transplantable simplified program codes; the simplified program can faithfully reflect input and output load characteristics of an original application program, and less time and fewer resources are needed to execute the simplified program, and therefore, rapid evaluation can be facilitated. The simplified program generating method is very effective in fast evaluation of the performance of a high-performance storage system and design assistance of the storage system.

The invention provides an analytic method for eliminating a metal artifact of a CT image. With the method, the iterative operation can be avoided. The method comprises: a metal image is segmented from an image reconstructed based on projection data on the multi-energy-spectrum-ray condition; a projection image is solved; an approximate value of an energy spectrum function is searched; an expression of an artifact function is obtained and an artifact image is obtained; the artifact image is subtracted from an original image to obtain a corrected image as shown in an attached drawing. The method is characterized in that the band shaped artifact can be eliminated and the structural feature of original information can be kept; and no priori knowledge of the energy spectrum and original projection data are needed according to the correction method and the reconstruction speed is fast.

The invention provides an expression vector containing a recombined blue algae antiviral protein N nucleotide sequence, a host cell containing the expression vector and a method for preparing recombined blue algae antiviral protein on the basis to obtain the recombined blue algae antiviral protein and further proves that the expression vector and / or the host cell and / or the recombined blue algae antiviral protein can be applied to prepare an antiviral medicament. The method of the invention overcomes the disadvantages of low yield, an easily formed inclusion body and difficult purification and the like in the prior art. Peptide mass fingerprinting of the recombined CVN protein prepared by the method is totally consistent with theoretical peptide mass fingerprinting; and an antiviral experiment proves that the recombined protein has good antiviral activity.

The invention discloses a spectral data dimension reduction method for optimizing kernel independent components based on a sparrow search algorithm. The spectral data dimension reduction method comprises the following steps: acquiring near infrared spectral data of a tested sample; selecting a kernel function, determining a kernel parameter optimization problem and constructing a fitness function;setting initial parameters of the sparrow population, and generating an initial position matrix and a fitness matrix of the sparrow population; updating the optimal position and the optimal fitness value of the sparrow population according to the predation and anti-predation behaviors of the sparrows; applying the optimal kernel parameter matrix meeting the convergence condition to a kernel function; performing spheroidization decomposition preprocessing on the spectral data; and solving an unmixing matrix in independent component analysis to realize effective dimensionality reduction of spectral data. According to the method, blindness of kernel function parameter selection in a spectral data dimension reduction process by applying a kernel independent component analysis method is avoided, effective dimension reduction of near-infrared spectrum high-dimensional nonlinear data is realized, and the method is excellent in performance, high in practicability, stable in calculation process and easy to realize.

The invention discloses an image impulse noise suppression method based on two-stage interpolation, which mainly solves the problem that the prior art can not retain image detail information in the de-noising process and also can not recover distinct images under the large noise density. The noise suppression method comprises the following steps of: carrying out noise detection and analysis on a noising image by utilizing a histogram and acquiring a low-resolution image through downsampling; carrying out first-stage interpolation by utilizing statistical properties of pixels without noise interference, completing amplitude information of pixels with impulse noise interference in the low-resolution image after the downsampling, and carrying out pre-filtering on the low-resolution image by adopting lifting wavelets on the self-adaption direction; and carrying out two-stage interpolation on the pre-filtered low-resolution image by adopting an improved segmental autoregressive model and utilizing the image structure characteristics to obtain a full-resolution image without the impulse noise. The invention has the objective evaluation and the subjective visual effect under different noise densities superior to the prior art, can be used for suppressing high-density impulse noise and improve the image quality.

The invention provides a method for extracting, matching and recognizing characteristics of finger veins, which comprises the following steps: acquiring a finger vein image by an infrared image acquiring device, preprocessing the image, extracting the characteristics, recognizing and analyzing, wherein the preprocessing step comprises the concrete steps of graying a color image, extracting a finger area, adopting direction filtering and enhancing, extracting a finger vein grain according to a finger outline mark and binarizing, de-noising by an area eliminating method, and standardizing the image size to a uniform image size; the characteristic extracting method comprises the steps of carrying out sub-block partitioning on the finger vein grain image, and extracting the characteristics ofeach sub-block image by a bidirectional two-dimensional principal component analysis method of bidirectional characteristic value weighting partitioning; and the recognizing and analyzing step recognizes the characteristics of each sub-block as a whole by a nearest neighbor sorter. The invention can reduce the calculated amount of a high dimensional image matrix in recognition of the finger veins, can obviously improve the recognition speed of the finger vein, and the recognition rate is stable and high.

The invention discloses a malachite green hapten, an artificial antigen and an application of the artificial antigen in fluorescence quantitative immunochromatography. The structure of the hapten hastwo malachite green molecule structures at the same time, so a space position of the hapten in a carrier protein is more prominent, recognition sites are increased, the immunogenicity of the small-molecular hapten is effectively improved, and the titer of the artificial antigen is also improved; the malachite green artificial antigen is combined with an ELISA detection technology, and the lowest detection limit of malachite green is 0.04 [mu]g / L; a fluorescence quantitative immunochromatographic test strip prepared by the artificial antigen cooperates with a detection method, malachite green can be detected quickly and conveniently, and the detection sensitivity can reach 0.2 [mu]g / L.

The invention discloses a video significance region searching method applied to video quality evaluation. The method includes the following steps that a three-dimensional relevant region of a key frame and a former frame is taken out; frequency domain display of the three-dimensional region is obtained; an amplitude spectrum and a phase spectrum of a frequency domain are respectively taken out; a spectrum residual error and a phase difference are obtained; the phase difference is processed to be in a prescribed range; spatial domain display of the spectrum residual error and the phase difference is obtained; Gaussian filtering is carried out on the obtained spatial domain; a significance result map of the video key frame is obtained. Relevance of videos on time and space is considered, and a time pipeline adapted to the significance result map of the video key frame is determined according to human eye visual characteristics; meanwhile, vital functions of the amplitude spectrum and the phase spectrum of the video key frame when a significance model is set are considered; a region with a still background can be comparatively accurately removed according to the spectrum residual error and the phase difference, and key structural feathers are reserved.

The invention discloses a preparation method of a decellularized tendon material. The preparation method comprises the following steps of 1, taking fresh tendon and carrying out cleaning, 2, compressing the tendon along the thickness direction at a compression ratio of 60-90%, 3, carrying out repeated freezing-thawing on the compressed tendon, and 4, treating the tendon subjected to the step 3 by nuclease and carrying out cleaning. The invention also discloses the decellularized tendon material obtained by the preparation method and a use thereof. The decellularized tendon material realizes thorough decellularization and has low immunogenicity, good biomechanical properties and good biocompatibility. The preparation method has simple processes, a low cost and a good application prospect.

The invention discloses a preparation method of a diamond-like carbon film containing nano-gold particles. The method prepares a tetrahydrofuran precursor solution containing polycarbobenzene-chloroauric acid, and then coats the mixed solution on the surface of single-crystal silicon by spin coating. After the organic solvent is volatilized, chloroauric acid-polyauric acid is formed on the silicon surface Carbon benzene film; the silicon wafer coated with the film is treated at 500-700 DEG C for 1-2 hours under the protection of argon gas, and then naturally cooled to room temperature to obtain a diamond-like carbon film containing gold nanoparticles. The invention is characterized in that the preparation process is simple and the diamond-like composite film containing metal nano-particles is synthesized in one step. The film is expected to be used in mechanical friction, electrochemical electrodes, metal catalysis, optics, and other fields.

The invention discloses a user characteristic prediction method based on a user purchase behavior, and the method comprises the steps: collecting target user characteristic information, historical order information and order commodity information, obtaining triple knowledge related to a commodity from a public knowledge graph through the order commodity information, constructing a knowledge sub-graph, aggregating entity neighbor local features by using a graph convolutional neural network, and fully learning representation vectors of entities. In the user feature prediction model, the similarity between the target user and different commodities and the similarity between the target user and users with similar purchase behaviors are learned according to different commodity features and different features of the users with similar purchase behaviors, feature vectors of the target user and the users with similar purchase behaviors are learned fully according to the similarity between theusers and the similarity between user entities, and personalized requirements of the users are met. According to the method, the accuracy of user feature prediction is improved, so that the user features can be predicted more accurately, and a more complete user portrait is constructed.

The invention provides a modified zeolite molecular sieve as well as a preparation method and application thereof. The modified zeolite molecular sieve is obtained through modification treatment on anX type molecular sieve, wherein the modification treatment refers to the modification on the X type molecular sieve in an organic acid alcoholic solution. The zeolite molecular sieve provided by theinvention can be used as an adsorption agent for hopance in a geological sample, and is used for enriching the hopance in the geological sample. The zeolite molecular sieve can be subjected to effective and controllable modification according to requirements.

Embodiments of the invention disclose a graph-based RDF data management method and apparatus, and a storage medium. The method comprises the steps of creating an RDF graph based on to-be-stored RDF data; respectively storing nodes corresponding to elements in the triple on the RDF graph in different storage units on the SSD; and storing a physical storage address list comprising the physical storage addresses of all the lower-level nodes corresponding to the upper-level node in a storage unit stored in the upper-level node, and storing a corresponding relation between each node and the physical storage addresses of the storage unit stored in each node in a node address index table. Through the implementation of the method and the device, the RDF data is converted into the graph data to bemanaged, the structural characteristics of the RDF data are better reserved, the data can be conveniently explored from any node, the realization of comprehensive and extensible RDF data management isfacilitated, the high parallelism of the SSD is fully utilized, and the data management performance on the SSD is greatly improved.

The invention discloses a radar high-resolution range profile recognition method based on a graph neural network, and the method comprises the following steps: S1, data preprocessing, S2, feature extraction, S3, classification result output, and S4, repeating the steps S1-S3 to complete a test, classifying HRRP test data through the step S1-1, and then sending the data into a model trained in the steps S1-S3 to perform a test. By adopting the technical scheme, the invention provides a sequence construction graph (seq2graph) method, the relation weight between the nodes is extracted from transformer, and the relation weight and the node features form graph structure data, so that a graph neural network method is conveniently utilized for processing, and a foundation is laid for improving the recognition effect and reducing the calculation amount.

The invention discloses an aviation part point cloud denoising method based on deep learning. The method comprises the steps of: artificially increasing different degrees of Gaussian noise based on atheoretical data model of an aviation part, generating a height map for each point in the model, and constructing a deep learning training set; training a deep learning network based on the constructed deep learning training set to obtain a deep learning network model used for predicting normal information of each point in the point cloud data; scanning a real aviation part by a laser scanner to obtain actually measured point cloud data, and predicting normal information of the actually measured point cloud based on the trained deep learning network model; and further performing position updating on each point in the point cloud based on the predicted normal information, thereby realizing de-noising of the actually measured point cloud. According to the invention, the problem that the noise of scanned point cloud of an aviation part cannot be accurately and efficiently removed in the prior art is solved, and the efficiency and accuracy of aviation part detection and analysis are further improved.

The invention discloses a multi-level image style conversion method and device based on sparse representation. The method includes: converting a color image to be converted into a first grayscale image, and extracting the relationship between the first grayscale image and the target style image. The edge features reconstruct the structure layer of the first grayscale image as the second grayscale image and the texture layer as the third grayscale image, obtain the salient areas and non-salient areas in the color image, and use different weights in the salient areas and non-salient areas. The second grayscale image and the third grayscale image are value-fused to obtain a fourth grayscale image, and the saturation contrast of the fourth grayscale image is adjusted according to the target style image to obtain a color image with the same style as the target style image. This method not only retains the structural characteristics of the image to be converted, but also adds the texture characteristics of the target style image, realizing the style conversion of the image to be converted through a target style image, demonstrating good visual effects.

The invention discloses a montmorillonite composite material and application thereof in adsorbing heavy metals. The montmorillonite composite material comprises montmorillonite and ferrihydrite, wherein the ferrihydrite is dispersed on the outer surface of the montmorillonite. The montmorillonite composite material disclosed by the invention has a relatively large BET specific surface area and a multi-stage pore structure characteristic, not only retains the pore structure characteristic of montmorillonite, but also has the pore structure characteristic of ferrihydrite; the ferrihydrite particles with positive charges and the montmorillonite particles with negative charges on the surface are firmly combined to form a stable montmorillonite composite material; and the composite material has typical structural characteristics of silicate minerals and ferrihydrite with a layered structure, and ferrihydrite nanoparticles are of a spherical particle structure and are wrapped by montmorillonite sheets. The montmorillonite composite material disclosed by the invention is applied to a water body or site soil environment containing various heavy metals, and the heavy metals in the environment can be effectively removed.

The invention discloses a method and a system for improving the resolution of a single-frame infrared image. The method comprises the following steps of: 1, acquiring single-frame low-resolution infrared image data; 2, dividing the single-frame low-resolution infrared image data into two paths, and respectively sending the two paths to an image super-division branch and a gradient super-division branch for data processing to respectively obtain an image super-division reconstruction result and a gradient super-division reconstruction result; and 3, fusing the image super-division reconstruction result and the gradient super-division reconstruction result to obtain high-quality high-resolution infrared image data. According to the method and the system, the overall super-resolution reconstruction quality can be improved, and the structure information in the image is better reserved.

The invention discloses an image impulse noise suppression method based on two-stage interpolation, which mainly solves the problem that the prior art can not retain image detail information in the de-noising process and also can not recover distinct images under the large noise density. The noise suppression method comprises the following steps of: carrying out noise detection and analysis on a noising image by utilizing a histogram and acquiring a low-resolution image through downsampling; carrying out first-stage interpolation by utilizing statistical properties of pixels without noise interference, completing amplitude information of pixels with impulse noise interference in the low-resolution image after the downsampling, and carrying out pre-filtering on the low-resolution image by adopting lifting wavelets on the self-adaption direction; and carrying out two-stage interpolation on the pre-filtered low-resolution image by adopting an improved segmental autoregressive model and utilizing the image structure characteristics to obtain a full-resolution image without the impulse noise. The invention has the objective evaluation and the subjective visual effect under different noise densities superior to the prior art, can be used for suppressing high-density impulse noise and improve the image quality.

The invention relates to a storage system reference evaluation program generating method and apparatus and belongs to the high-performance computing performance evaluation field. The storage system reference evaluation program generating method includes the following steps that: intermediate codes are obtained from a standardized source program; slicing starting points of the intermediate codes are identified; static program slicing is carried out based on identified slicing starting points; and simplified codes can be generated based on obtained static program slices. The method is based program slicing technology; data dependence, control dependence and communication dependence are analyzed in a compiler; all statement operation related to input and output is automatically extracted so as to form the compilable, executable, manually-readable and transplantable simplified program codes; the simplified program can faithfully reflect input and output load characteristics of an original application program, and less time and fewer resources are needed to execute the simplified program, and therefore, rapid evaluation can be facilitated. The simplified program generating method is very effective in fast evaluation of the performance of a high-performance storage system and design assistance of the storage system.

The present invention belongs to the field of metrology, and more specifically relates to a spectral basic dimension correction and differential analysis method based on a moving least squares method.The method comprises: performing basic dimension correction on the spectrum obtained from known standard substances (series) by using the moving least squares method; using the corrected spectrum toperform differential analysis, specifically: using multiple spectra obtained from known standard substances (series) to perform cycle subtraction operations to obtain the maximum safety threshold of the system; performing cycle subtraction operations of multiple spectra between the known non-standard substances (series) and the known standard substances (series) to obtain the minimum warning threshold of the system; and performing cycle subtraction operations between the unknown sample spectrum and the known standard substances (series) spectrum, and obtaining a spectrum analysis result aftercomparing the difference values with the maximum safety threshold and the minimum safety threshold.

The present invention belongs to the field of metrology, and more specifically relates to a spectral basic dimension correction and differential analysis method based on a moving least squares method.The method comprises: performing basic dimension correction on the spectrum obtained from known standard substances (series) by using the moving least squares method; using the corrected spectrum toperform differential analysis, specifically: using multiple spectra obtained from known standard substances (series) to perform cycle subtraction operations to obtain the maximum safety threshold of the system; performing cycle subtraction operations of multiple spectra between the known non-standard substances (series) and the known standard substances (series) to obtain the minimum warning threshold of the system; and performing cycle subtraction operations between the unknown sample spectrum and the known standard substances (series) spectrum, and obtaining a spectrum analysis result aftercomparing the difference values with the maximum safety threshold and the minimum safety threshold.

The invention discloses an annular combustion chamber model with an integrated head structure and an assembly method. The combustion chamber model comprises a combustion chamber outer casing, a combustion chamber inner casing, a flame tube outer casing, a flame tube inner casing and a flame tube head. The structural characteristics of engine parts are obvious, and low-cost split printing and combined structures of the flame tube head are achieved on the premise that the requirement for high fineness is met; production and manufacturing are achieved, meanwhile, specific structural features are reserved, the assembly difficulty of a user is simplified, and the problems that a traditional low-cost aero-engine combustion chamber model is too few in details, cannot meet teaching requirements, is too small in size and is difficult to display are solved.

The invention provides a semantic segmentation method and device based on a prior structure, and the method comprises the steps: obtaining a to-be-segmented image, and extracting a feature map of the to-be-segmented image; obtaining a learnable structure token which is generated randomly; inputting the feature map and the structure token into at least one layer of interaction structure, and outputting the structure token after interaction; the interactive structure is used for extracting structural features from the feature map and endowing the structural features with structural tokens; and inputting the structure token after interaction into the convolution block to obtain a segmentation image of the to-be-segmented image. According to the scheme, the structural features of the image can be reserved, and the segmentation image is directly predicted.

The invention discloses a method for predicting user characteristics based on user purchase behavior, the method comprising: collecting target user characteristic information, historical order information, and order commodity information, and using the order commodity information to obtain commodity-related triples from a public knowledge map Knowledge, constructing knowledge subgraphs, using the graph convolutional neural network to aggregate the local features of the entity's neighbors, and fully learning the representation vector of the entity; in the user feature prediction model, the target is learned according to different product features and different features of users with similar purchase behaviors The similarity between users and different commodities and users with similar purchase behaviors is fully based on the similarity between users and user entities to learn their feature vectors to meet the personalized needs of users. The present invention improves the accuracy of user feature prediction, so that user features can be predicted more accurately and a more complete user portrait can be constructed.