50results about How to "Effectively delete" patented technology

The invention discloses a method for automatically matching multisource space-borne SAR (Synthetic Aperture Radar) images based on an RFM (Rational function model). The method comprises the following steps of: calculating respective RPC (Rational Polynominal Coefficient) parameter of images; performing forecast of initial positions of points to be matched, matching of approximate epipolar line geometric establishment constraints and geometric rough correction of matched window images by using the RPC parameters of the images on every pyramid image layer, deleting wrong matching points from the image matching result of every layer of pyramid by adopting regional computer network error compensation based on an RFM model; refining the RPC parameters of the images and calculating the object space coordinates of the matching points; refining the matching result to the original image layer by layer; and refining a matching result by using a least square image matching method to realize automatic and reliable matching of common points of multisource space-borne SAR images. In the method, the RFM model is introduced into automatic matching of the multisource space-borne SAR images, and the regional computer network error compensation of the RFM model is blended into the image matching process of every layer pyramid, so that wrong matching points in the matching process can be effectively deleted, and the workload of manual measurement of common points is effectively lowered.

The invention provides a method for obtaining an operation area of an agricultural machine, and the method comprises the steps: S1, classifying the original track points of the agricultural machine according to a moving direction of the agricultural machine, and obtaining a plurality of track point sets; S2, obtaining the operation track points of the agricultural machine according to the mean moving speed of the agricultural machine in the track point sets; S3, gathering the operation track points of the agricultural machine, obtaining a bounding polygon of the operation of the agricultural machine, and generating a buffering region through the bounding polygon; S4, obtaining the operation area of the agricultural machine according to the coordinates of the buffering region. The method provided by the invention effectively eliminates the non-operation track points through calculating the mean moving speed of the agricultural machine in the track point sets, obtains more accurate operation track points of the agricultural machine, obtains the buffering region according to the operation track points of the agricultural machine, obtaining the operation area of the agricultural machine according to the buffering region, improves the obtaining precision of the operation area and the automation degree of the agricultural machine.

The invention provides a data de-duplication method of a backup server. The data de-duplication method specifically comprises the following steps that a logical volume of a hard disk module of the backup server is divided to form a partition which is used for temporally storing data needing to be backed up on the server, and the partition has the data buffering function; block segmentation is carried out the buffered data in the partition, and the hash value of the buffered data is worked out with one block as a calculation unit and stored in a database; the hash values are compared, in other words, the hash value of the new data backed up each time is compared with the existing hash value in the database, if the hash value of the new data is the same as the existing hash value in the database, the new data and the data in the database are repeating data, or otherwise, the new data and the data in the database are not repeating data, and the hash value of the data block is added into a hash library. Compared with the prior art, the data de-duplication method of the backup server has the advantages that the repeating data can be effectively deleted, the storage space is greatly saved, the storage space is saved to a certain degree, and the operating cost of enterprises is reduced.

The invention discloses a rapid method and a rapid system for removing notification bar information of a mobile terminal. The method includes: S1, detecting whether a notification bar receives new notification information or not in real time, and displaying the new notification information on the notification bar if yes; S2, detecting whether a double-click is available in a notification bar area or not, judging whether time of the double-click signal is within a preset time interval or not; S3, when the time of the double-click signal is within the preset time interval, removing the new notification information in the notification bar. When a screen of the mobile terminal is lightened, a status bar area is clicked doubly, and when the area receives the double-click signal and the double-click signal is judged as an effective double-click signal, a deletion command is executed; a notification whitelist is set, when the deletion command is executed, an application notification in the whitelist is reserved, a user is allowed to check and process the notification conveniently in time and delete other push information effectively without pulling down the notification bar, user time is saved, checking efficiency is increased, and user experience is improved.

The invention discloses an IP address filtering method and device. The method comprises the following steps of: based on OSPF (open shortest path first) protocol link state information, obtaining a shortest path from a source router to the current router in a region, wherein an interface of a previous node of the current router in the shortest path is taken as a legal input interface for OSPF route prefix of the source router; and based on the legal input interface, building a message filter rule for the route prefix of the source router, processing IP messages using the OSPF route prefix of the source router as source address prefix, and filtering messages sent by input interfaces except for the legal input interface. Through the technical scheme of the invention, message on faking the source IP address can be effectively filtered; the computation process of the filter rule is simple, the network load is not increased and the safety of the network can be effectively improved.

The invention discloses a plant binary expression vector for inducing embryoid body formation and plant regeneration, which comprises BBM genes and an FLP-FRT site specific recombination system. The FLP-FRT site specific recombination system comprises FLP genes and two identical orientation FRT sites. The BBM genes and the FLP genes are positioned between the two identical orientation FRT sites, the BBM genes are controlled by a constitutive promoter, and the FLP genes are controlled by an inducible promoter. The invention further discloses a method for constructing the plant binary expression vector and a method for inducing embryoid body formation and plant regeneration by using the plant binary expression vector. The invention can not only promote embryoid body formation of a plant callus, induce formation of a transgenic plant, and remarkably improve the transformation frequency and the regeneration frequency of the plant; but also can eliminate the negative impacts of exogenous genes on the transgenic plant. The invention provides a novel genetic transformation strategy for plant species which are difficult for genetic transformation, and has wide application prospect.

The invention provides a homonymous point matching method of heterogenous remote sensing images taking high-order structural characteristics into consideration, and belongs to the field of plotting science and technology. The method comprises that data is prepared before heterogenous images are matched; a characteristic point cluster is divided and extracted; candidate matching points of characteristic points are determined; homonymous points are matched taking the high-order structural characteristics into consideration; a result is matched for each layer of pyramid images, and a local network adjustment based on an RFM model is carried out by utilizing a fusion selecting weight iteration method; and the matching result is refined layer by layer till an original image layer, and the homonymous points of the heterogenous remote sensing images can be matched automatically and reliably. According to the invention, a rational function model and a hypergraph image matching model are used in an integrated manner, geometrical constraint characteristics and the higher-order structural characteristics are introduced to layer-by-layer pyramid image matching, the sparsity of the hypergraph model is ensured, and information loss caused by hyperedge sampling is reduced to the minimum; and the matching reliability and success rate of the heterogenous remote sensing images are improved, and the workload of manual homonymous point measurement is reduced effectively.

The invention discloses a multi-level building rapid three-dimensional reconstruction method based on laser radar point cloud. The method comprises steps of: collecting three-dimensional point cloud data; performing point cloud filtering processing to obtain building point cloud; using an optimized random sampling consistency algorithm to obtain a laser point cloud set; performing Delaunay triangulation to extract the contour points of a building; performing bubble sorting to sort the contour points to generate contour lines; using a key point extraction algorithm to extract key points of a building outline; connecting the key points, and using the orthogonal constraint to regularize the contour lines; and assigning elevation information in the point cloud to the building outline to generate a three-dimensional building model. The method adopts an optimized algorithm to provide higher execution efficiency and can effectively delete building wall points; the Delaunay subdivision methodis used to accurately extract the building outline; and the contour line key point extraction algorithm is used to better extract the key points of the building, and can suppress the interference of the wrong contour points and reduce the generation of pseudo key points.

The invention provides a web crawler service system for a housing library network. According to the system, website mining can be conducted quickly, and data related to housing estates can be extracted. The system comprises a website crawler module, a monitoring service module, a management service module, a deployment service module and a scheduling service module, wherein the website crawler module consists of multiple website crawlers, the website crawlers are in one-to-one correspondence with websites, analyze page elements of the websites, extract website data for semantic analysis and map the website data into preset data entities for storage; the monitoring service module is used for monitoring working conditions of all the website crawlers and judging whether the website crawlers work normally or not and whether data fetching is correct or not; the management service module is used for configuring settings of parameters related to working of the website crawlers, upgrading the website crawlers and managing start-up and stopping of the service system as well as life cycles and working of the website crawlers; the deployment service module is used for allocating and deploying the website crawlers; scheduling modules of the website crawlers are arranged in the scheduling service module and used for performing scheduling management on working modes, time and stopping of the website crawlers.

The invention provides an AP choosing method based on WLAN indoor positioning, comprising steps of measuring signal intensity of all access points in the position by a user, obtaining a complex vector for describing AP signal characteristics according to the AP signal by the system, eliminating AP candidates which are invalid for positioning according to the characteristics of the complex characteristics, calculating an optimal signal measurement strategy based on a simulation annealing algorithm according to the user-given measurement times, performing measurement on the signal of the access point according to the calculated strategy, uploading the measurement result to the server according, calculating the position of the user by the server according to the signal measurement result and returning the result back to the user. On one hand, the invention effectively eliminates the invalid AP candidate and reduces the complexity, and, on the other hand, the invention provides the optimal strategy based on the simulation annealing algorithm and effectively improves the positioning accuracy under the condition that the measurement times are limited.

The invention discloses a fast density clustering double-layer network recommendation method based on graph structure filtering. The method comprises the steps that (1) analog comment data is automatically generated through TextGAN according to historical user comment information to serve as false comments which are accurately annotated with a class mark and extremely similar to real samples; (2)historical real comments and the analog comments marked as the false comments are used as input, a graph-based virtual information filter for studying user access records is designed considering thatthe generated false comments are extremely similar to the real comments, and false users and false comments are detected through continuous iteration of confidence of users, stores and comments; and (3) in order to solve the problem of sparsity of result recommendation data, the recommendation method based on a fast density clustering double-layer network is designed. Through the method, self-adaptive selection of parameters can be realized, a good clustering result can be obtained, therefore, more effective personalized recommendation lists of users can be obtained, and the accuracy of recommendation is improved. An adversarial generative network is utilized to generate false samples extremely similar to the real comment data, and the fast density clustering double-layer network recommendation method based on graph structure filtering is efficient and reliable.

The invention discloses a method for compressing animation scene files. During a progress when three-dimensional animation scenes are made by using maya, the finally generated scenes usually comprise a large number of useless historical nodes due to repeatability of a production cycle and uneven ability of production staffs, as a result, scene files are so large that the scenes are very inconvenient to store and use. According to the method for compressing animation scene files disclosed by the invention, by calculating a projection range of a scene camera, models which are not in the projection range can be deleted on a basis that necessary models and animation curves for the scene are kept, so that the size of the scene files can be compressed greatly.

The invention discloses an indoor positioning fusion algorithm, and relates to an indoor positioning technology, in particular to a method for carrying out comprehensive positioning according to Bluetooth signals, inertial navigation data and geomagnetic data. A terminal sends a Bluetooth signal at regular time, and screens a Bluetooth receiving label through a game theory method according to theinertial navigation positioning position; and after fingerprint matching is obtained, the fingerprint combination is screened according to the inertial navigation positioning position and the geomagnetic positioning position, a Bluetooth positioning position is obtained according to the screened fingerprint combination, and a final positioning point is obtained according to the inertial navigationpositioning position and the Bluetooth positioning position. By adopting the method provided by the invention, the Bluetooth receiving tag interfered by the multipath effect can be effectively deleted, and only the normally received Bluetooth receiving tag is selected for fingerprint matching; the final positioning point is comprehensively corrected by the Bluetooth positioning position and the inertial navigation positioning position, and several positioning technologies compensate each other, so that the positioning is accurate.

Provided is a magnetic head including a bottom pole, a top pole spaced a predetermined distance apart from the bottom pole, an inductive write coil for forming a magnetic field at the bottom and top poles, and a magnetic shield layer positioned over the top pole.

The invention discloses a pedestrian re-recognition method based on pixels and a channel attention mechanism. The pedestrian re-recognition method comprises the steps of extracting global features ofpedestrians according to a boundingbox (retrieval box) of a person; averagely dividing the pedestrian picture into two parts and three parts, and respectively extracting local features of pedestrians;and matching the extracted character features with the character information in the Galertness, and finding out the required character information. A channel and a pixel attention module are used forfeature extraction, so that the influence of background information on a retrieval result is effectively reduced; meanwhile, middle-layer supervision is further designed for the neural network, in the feature extraction process, a multi-loss function is used for supervising middle-layer feature information, and network convergence is accelerated; according to the pedestrian re-recognition networkbased on the channel attention mechanism, the pixel attention mechanism and the middle layer supervision, redundant information in figure boundbox can be effectively deleted, figure information is effectively aggregated, and therefore retrieval precision is remarkably improved.

The embodiment of the invention provides a node organization management method and device, electronic equipment and a readable storage medium, and aims to improve the supervision capability of a cross-chain technology. The node organization comprises at least one node, the method is applied to a node of a main blockchain network, and the method comprises the following steps: obtaining endorsement information of a node organization deletion transaction and endorsement information of a plurality of endorsement nodes for the node organization deletion transaction; verifying the legality of the node organization deletion transaction according to the endorsement information; under the condition that the node organization deletion transaction is legal, deleting node information belonging to a to-be-deleted node organization from a local view by executing the node organization deletion transaction; and sending the node organization deletion transaction to each sub-blockchain network, so that each node of each sub-blockchain network deletes node information belonging to a to-be-deleted node organization from a local view by executing the node organization deletion transaction.

The invention discloses a fingerprint core point fast robust positioning method, comprising the following steps: images are input and divided; a direction field is calculated; the direction field is smoothed; edge detection is carried out; edge pixel is deleted; for edge pixel points, 4 neighborhoods thereof are applied to calculate gradient information and if the 4 gradient magnitudes calculated are not in the range of a given threshold value (Tl, Th), the pixel is deleted from the edge; the core point is positioned: the outermost pixel of a 3 multiplied by 3 neighborhood window is utilized, the Con, dx and dy values of the rest edge points are calculated respectively and the conditions for positioning the core point are that: when dx is more than Alpha and dy is less than Beta, a point with minimum selected direction consistency is the Lower core point, and when dx is less than Beta and dy is more than Alpha, a point with minimum selected direction consistency is the Upper core point. The method of the invention can not only effectively restrain effect brought by noise, but also can quickly and accurately position the core point of the fingerprint, and reliably detect the core point for all types of fingerprints.

The invention provides a fuzzy reasoning-based single-class classification method and classifier, which fuzzifies a feature vector, generates a fuzzy rule set and corrects the fuzzy rule set. The specific method is as follows: after a target rule set is generated, rule correction needs to be carried out if the same judgment condition appears but the judgment results are different. And the single-class classifier can accurately identify abnormal samples. Firstly, data processing is carried out, then fuzzification is carried out on the data, then a fuzzy rule set is established, and rule correction is carried out. After the rule set is established, a test sample can be used for testing the rule set, and when the rule generated after the sample of the test set is subjected to data processingof the same mapping is different from the existing rule, the sample is considered as an abnormal sample and then classified into an unknown category. According to the method, the number of data set samples in the aspect of single-class classification is increased. Meanwhile, a better classification effect can be achieved by applying a more optimized algorithm, and the training speed is increased.

The invention provides an intelligent terminal collaborative screen capture method and system based on blockchain, an electronic device and a computer readable storage medium, and the method comprisesthe steps: searching printing equipment connected with a first terminal, and distinguishing the types of PDF files which can be printed by the printing equipment; if the permission of printing the interface content as the text PDF exists, printing the interface content as the text PDF, wherein at the moment, the text PDF obtained through printing does not contain blind watermark information, thenthe printing equipment converts the text PDF into the first screenshot picture, and the first screenshot picture is obtained through the second screenshot picture. Therefore, the extraction of all displayable contents of the current interface and the storage of the picture form are realized, so that the effect of obtaining the screenshot without executing the screenshot operation is achieved. Otherwise, the picture PDF is scanned, the information of the blind watermark in the picture in the picture PDF after scanning can be ignored, and the obtained first screenshot picture can effectively delete the information of the blind watermark.

The invention discloses a wind speed prediction method based on a complex numerical value forward neural network, and the method comprises the steps: obtaining a training set and a prediction set for wind speed prediction, constructing the complex numerical value forward neural network, and initializing a parameter vector; introducing a GroupLasso regularization item into a target function trained by the complex numerical value forward neural network, converting training into solution of a constraint optimization problem, training the complex numerical value forward neural network by adopting a training set and a customized complex numerical value projection quasi-Newton algorithm, and ending training until a preset condition is met to obtain a trained complex numerical value forward neural network, and inputting the prediction set into the trained complex numerical value forward neural network to obtain a wind speed prediction result. According to the method, the GroupLasso regularization item is introduced, and the complex numerical value forward neural network is trained by using the customized complex numerical value projection quasi-Newton algorithm to realize optimization of the network structure and parameters, so that the network structure is compact, the generalization performance is high, and meanwhile, the accuracy of wind speed prediction is improved.

The invention discloses a user portrait construction method, system and device and a storage medium. The method comprises the steps of S1, obtaining user data; s2, processing the user data by adopting a word embedding model to obtain an embedded word vector; s3, performing clustering analysis on the embedded word vector by using a Kmeans clustering algorithm to obtain a clustering result; s4, using a KNN model to classify the anonymous users embedded in the word vectors, and marking corresponding labels to obtain labels of all the users; and S5, constructing a user portrait model according to the embedded word vector, the clustering result and the label of the user. False users can be effectively deleted, the authenticity of data is improved, and an accurate and real-time user portrait model is constructed.

In the mobile phone 100 having e-mail sending and receiving functions, the control unit 106 acquires the history information of the e-mails sent by the mobile phone 100 from the history information recording unit 1082, and determines whether there is an e-mail as the sending source based on the acquired history information. The received e-mail at the e-mail address of the mobile phone 100 is actually an e-mail sent by the mobile phone 100, thereby determining whether the e-mail is an unsolicited e-mail.

The invention discloses a customer screening method based on big data, and aims to solve the technical problems that in the prior art, potential customers cannot be mined, the conversion rate of the customers is low, data is not crawled from a network, the data volume is relatively small, and the referable range is relatively small, so that the customer screening precision is not low during decision making or marketing. The method comprises the following steps: S1, crawling data from a website and an APP, and storing the data; S2, according to the crawled data, analyzing user basic information from the aspect of user static attributes, and performing user static attribute grade division. Data is crawled from the network, the cardinal number of the data size is larger, the screening precision of clients is higher, potential clients with low conversion rate are effectively deleted, the advertisement putting cost is reduced, higher profits are achieved, meanwhile, old clients are screened, and the quality of the old clients is graded, so that the advertisement putting efficiency is improved in a targeted manner. And a corresponding marketing strategy is made.

The invention discloses a method for compressing animation scene files. During a progress when three-dimensional animation scenes are made by using maya, the finally generated scenes usually comprise a large number of useless historical nodes due to repeatability of a production cycle and uneven ability of production staffs, as a result, scene files are so large that the scenes are very inconvenient to store and use. According to the method for compressing animation scene files disclosed by the invention, by calculating a projection range of a scene camera, models which are not in the projection range can be deleted on a basis that necessary models and animation curves for the scene are kept, so that the size of the scene files can be compressed greatly.

The invention provides a method for obtaining an operation area of an agricultural machine, and the method comprises the steps: S1, classifying the original track points of the agricultural machine according to a moving direction of the agricultural machine, and obtaining a plurality of track point sets; S2, obtaining the operation track points of the agricultural machine according to the mean moving speed of the agricultural machine in the track point sets; S3, gathering the operation track points of the agricultural machine, obtaining a bounding polygon of the operation of the agricultural machine, and generating a buffering region through the bounding polygon; S4, obtaining the operation area of the agricultural machine according to the coordinates of the buffering region. The method provided by the invention effectively eliminates the non-operation track points through calculating the mean moving speed of the agricultural machine in the track point sets, obtains more accurate operation track points of the agricultural machine, obtains the buffering region according to the operation track points of the agricultural machine, obtaining the operation area of the agricultural machine according to the buffering region, improves the obtaining precision of the operation area and the automation degree of the agricultural machine.

The invention discloses an indoor positioning fusion algorithm, and relates to an indoor positioning technology, in particular to a method for carrying out comprehensive positioning according to Bluetooth signals, inertial navigation data and geomagnetic data. A terminal sends a Bluetooth signal at regular time, and screens a Bluetooth receiving label through a game theory method according to theinertial navigation positioning position; and after fingerprint matching is obtained, the fingerprint combination is screened according to the inertial navigation positioning position and the geomagnetic positioning position, a Bluetooth positioning position is obtained according to the screened fingerprint combination, and a final positioning point is obtained according to the inertial navigationpositioning position and the Bluetooth positioning position. By adopting the method provided by the invention, the Bluetooth receiving tag interfered by the multipath effect can be effectively deleted, and only the normally received Bluetooth receiving tag is selected for fingerprint matching; the final positioning point is comprehensively corrected by the Bluetooth positioning position and the inertial navigation positioning position, and several positioning technologies compensate each other, so that the positioning is accurate.

The invention discloses a method for reducing brain wave medical record signals based on a three-layer cross game energy tree. In this method, two adjacent three-layer cross-game energy trees Ti and Tj are firstly designed, and the selfish game is realized in the same main layer and the cross-cooperative game is realized between different main layers. The depth-first search strategy is used to select the two game energy trees. The global optimal elites Elitisti_c and Elitistj_c; then assign the elite energy gain matrix PMENn×n to the optimal elites, and enhance the elites to obtain adaptive Nash energy exploration and development balance performance in the main layer; finally realize the cross-game energy reduction of brainwave medical record signals , so that the optimal elite converges to the optimal Nash equilibrium point of each main layer under the drive of the elite energy vector Γ, and achieves the balance of the reduction accuracy of the brainwave medical record signal, thereby outputting the global optimal brainwave medical record signal. The invention can effectively improve the reduction efficiency of brainwave medical record signals, provide important methods for brainwave signal noise elimination, feature extraction and analysis, etc., and has strong application value for brain disease diagnosis and auxiliary treatment.

The invention discloses a hierarchical reinforcement learning recommendation system based on a dynamic recursion mechanism. The system comprises a user portrait corrector which employs a strategy gradient method of the dynamic recursion mechanism and introduces a parameter dynamic sparse weight to delete noise data and modify a user portrait, wherein the strategy gradient method of the dynamic recursion mechanism comprises a dynamic baseline and recursion reinforcement learning based on a time sequence context, the dynamic baseline being used for improvement of a learning strategy for total income by adopting a dynamic sparse weight; an attention mechanism used for automatically adjusting changes of user preferences; and a recommendation model used for recommending the most relevant articles to the user through the attention mechanism. According to the recommendation system, a parameter dynamic sparse weight is introduced into the strategy gradient method, so that an intelligent agentselects an optimal behavior under a global optimal strategy; and secondly, in combination with hierarchical reinforcement learning of the time context, the method can more reliably converge, so that the stability of model prediction is improved.

The invention belongs to the related technical field of welding automatic control, and discloses a weld joint visual detection device and method based on linear structure light intensity high-frequency modulation, and the weld joint visual detection device comprises a high-frequency intensity laser modulator, a Powell lens, a camera and an industrial computer, and the camera and the industrial computer are connected. The high-frequency intensity laser modulator is used for modulating the light intensity of the laser beam at a preset frequency; the Powell lens is used for converting the modulated laser into laser stripes and projecting the laser stripes to a weldment; the camera is used for collecting weld joint images on the weldment and transmitting an obtained weld joint image sequence to the industrial computer. The industrial computer is used for carrying out Fourier transform on the received weld joint image sequence so as to directly remove random welding noise without fixed frequency in a frequency domain; then, the obtained frequency domain signal is recovered to an image signal through inverse Fourier transform. The welding noise can be effectively eliminated, and the accuracy is improved.