44results about How to "Build connection" patented technology

The invention provides a method for analyzing waveform similarity body curvature of seismic data, which is a technology for processing and explaining oil seismic exploration data and realizes a method of accurately engraving sedimentary facies zone distribution by using the seismic data. The method for analyzing the waveform similarity body curvature of the seismic data comprises the following steps of: first, carrying out horizon flattening on original three-dimensional seismic data bodies by using a horizon flattening technology or a Wheeler automatic transform technology according to the described horizon so as to eliminate influences of a structure on lithofacies distribution; and then selecting a proper calculated aperture; figuring out a curvature based on a waveform similarity body by using a trend surface analysis method on the basis of extracting a waveform similarity information data so as to obtain multiple waveform similarity body curvature attribute data bodies. By using the method provided by the invention, strata bend, strata sedimentary facies or transverse variation of lithology caused by structure deformation can be effectively identified so as to provide a basis for describing distributional characteristics of reservoir lithology, indicating edges of the sedimentary facies zone and dividing a seismic facies zone.

The invention discloses a coarse particle contraction rule method based on fractal theory. The coarse particle contraction rule method based on fractal theory is suitable for particle grade contraction of water conservation and civil engineering coarse particle, can effectively weaken coarse particle contraction effete. As for naturally formed sand-gravel material and generated blasting heap rockfill material through parameter design, the particle grading basically conform to Talbot grading curve, the particle size accord with fractal distribution, and good compacting performance is possessed. The coarse particle contraction rule method is based on the fractal theory, by introducing a grading parameter and a fractal dimension, and puts forward a contraction grading formula that physical mechanics condition is basically uniform on condition that original grading coarse particle appoints maximum control particle diameter dmax. The coarse particle contraction rule method based on the fractal theory specifically comprises the following steps: (1) calculating fractal dimension DO of the original grading; (2), through a relative density ratio test of corresponding ingredient of maximum control particle diameter, and determining a critical fractal dimension DL; (3) calculating grading parameter A according to relationship between the DO and the DL; (4) substituting the grading parameter A and the DO into the grading formula, and obtaining contracted target grading.

The invention relates to a prediction method for urban PM10 concentration based on a characteristic expansion fusion neural network, which comprises the following steps of: step S1: constructing a model of the concentration prediction of the urban PM10 based on the feature-expanded stack self-encoder and LSTM network; step S2: selecting training data and test data from monitoring data of pollutants and meteorology; step S3: carrying out the training on the feature-expanded stack self-encoder by using the training data; step S4: processing the feature vectors of the output of the stack self-encoder based on the Gaussian function, calculating the corresponding influence weights for the feature vectors of different cities, and weighting and summing to obtain a new feature vector; step S5: inputting the new feature vector into the LSTM to carry out integral training of the model; step S6: inputting test data into a trained model, and measuring the error of the prediction result generated by the test data; step S7: adopting the training and fine-tuning models for air pollutant concentration prediction. Compared with the prior art, the invention has the advantages of accurate predictionand the like.

The invention discloses a competency knowledge extraction method, which comprises the following steps: data collection: acquiring text data from a network and an object connected by the network; datarecognition: processing the text data by adopting a natural language processing method; data understanding: labeling text data processed by natural language according to specific rules; data screening: extracting and screening competency knowledge from the tagged data through a variety of models; data summary: identifying and summarizing the tags in the screened data to obtain the capability knowledge. The invention also discloses a competency knowledge map building method, which comprises the following steps: extracting a competency ontology through data collection, identification, understanding, screening and summary processes; using machine learning to learn the process of extracting competency ontology; classifying and storing the knowledge ontology, and then obtaining the map of competency knowledge. The invention solves the problems of intercommunication and sharing of heterogeneous resources on the Internet of Things, and realizes automation and intelligence of competency ontology extraction.

The invention discloses a method for mapping a two-dimensional (2D) projected image to a three-dimensional (3D) model. The mapping method comprises the following steps: step one, acquiring the 3D model through a 3D scanner; step two, preprocessing the 3D model to obtain the preprocessed 3D model; step three, normalizing the preprocessed 3D model to obtain a bounding box of the 3D model; step four, establishing a 3D model OBB bounding box; and step five, establishing the contact between the 2D projected image and the 3D model. Through the mapping method disclosed by the invention, the defect that the 3D model and the projected image thereof are relatively independent in the prior art is overcome, the contact between the 3D model and the projected image is effectively established; the problem that the 3D model and the 2D projected image simultaneously have the scalability is overcome, and the problems of pattern scaling and the 3D model scaling are solved.

The invention discloses an ontology mapping method for a food material / recipe knowledge graph. The ontology mapping method comprises the steps of obtaining instance data and constructing an ontology set; selecting a first ontology O1 and a second ontology O2 which need to be mutually mapped from the ontology set, and generating a to-be-mapped instance pair set IP and a to-be-mapped concept pair set CP; performing instance mapping on the set IP of the to-be-mapped instance pair based on the decision tree model and obtaining an instance mapping result; performing concept mapping on the to-be-mapped concept pair set CP based on the support vector machine model and obtaining a concept mapping result; obtaining an ontology mapping result according to the instance mapping result and the conceptmapping result; wherein the instance data is food material instance data, and the ontology set is a food material ontology set; or, the instance data is recipe instance data, and the ontology set is arecipe ontology set. According to the method, mapping between ontologies can be realized, and the method is used for constructing the knowledge graph. The invention further discloses an ontology mapping method for the food material / recipe knowledge graph.

Disclosed is a unique concept of a physical training apparatus which applies resistance to a trainee during athletic movements from a set position in the natural environment of the sporting activity to aid in enhancing speed and acceleration. The said physical training apparatus is designed to be used in conjunction with a starting apparatus to allow the trainee to execute resistive movements with identical technique to a sporting activity. The versatility of design of the disclosed invention allows the trainee to better translate the benefits of a resistive exercise into a sporting activity by incorporating the use of common athletic elements. Further benefits stem for the reduction of time and movement between a resistive exercise and an unrestrained athletic routine due to the ability of the disclosed invention to be utilized within the environment of the sporting activity.

The invention provides a spatial information processing service automatic composition method with dynamics. The method has the following beneficial effects: relations among spatial information processing services can be more accurately established through semantic matching on the basis of semantic descriptions of the spatial information processing services; through automatic search of paths from original data to terminal user task demanded products, the hypothetical problems are solved in the network environment and a spatial information processing flow model can be automatically constructed in a dynamic manner; and the reliable service automatic composition result can be provided.

The invention provides a strong lubricant oil oxidation test device and a test method, and belongs to the technical field of engineering machines. The strong lubricant oil oxidation test device comprises a first oxidation bin 1 and a heater 2 used for heating the first oxidation bin 1, wherein the first oxidation bin 1 is arranged in the heater 2, the first oxidation bin 1 comprises a sealing chamber 11 containing lubricating oil and a sampling tube 12, the sampling tube 12 is arranged on the sealing chamber 11, one end of the sampling tube 12 is arranged in the sealing chamber 11, and the other end of the sampling tube is positioned outside the sealing chamber 11. The test method comprises the steps of heating the first oxidation bin 1 by the heater 2, and taking the sampling tube 12 out to be measured. The strong lubricant oil oxidation test device is provided with the oxidation bin capable of adjusting test conditions, so that a plurality of lubricant oil samples can be simultaneously tested, the test time can be added or reduced, and multiple properties of lubricant oil can be tested.

The invention discloses a traffic congestion evaluation method. The method comprises the following steps of (a) respectively constructing a congestion sense increasing curve and a congestion sense relieving curve according to the change of velocity in a driving process; (b) dividing the driving process into a plurality of congestion states according to the change of the velocity; (c) constructing a congestion state transition diagram which is a front-back linked relationship diagram of congestion sense strengths corresponding to different congestion states, wherein the congestion sense strength of each congestion state is obtained according to the congestion sense increasing curve or the congestion sense relieving curve by using the velocity change between each congestion state and a previous state, the congestion sense increasing curve is selected in case of velocity reduction, and the congestion sense relieving curve is selected in case of velocity increase; (d) obtaining the congestion sense time accumulation of each congestion state in a manner that the congestion sense strength of each congestion state is multiplied by the duration of the congestion sense strength of each congestion state; and (e) summing the congestion sense time accumulation of all the states so as to obtain a congestion sense evaluation value of the whole driving process. According to the traffic congestion evaluation method, the difference of congestion senses caused by vehicle driving change can be given quantitatively.

The invention provides a control method and a system for load balance of discrete wireless access points. The method includes: any wireless access point is selected for load balance configuration, and the wireless access point is controlled to broadcast configuration information of load balance to an adjacent wireless access point in a regular manner; the adjacent wireless access point performs load balance configuration according to the received configuration information of load balance and continuously broadcasts the configuration information of load balance to the adjacent wireless access point; the above steps are repeated until all the discrete wireless access points accomplish load balance configuration; the wireless access point sends load information to the adjacent wireless access points in a regular manner, and the wireless access points receiving the load information update a preset neighborhood load information list; and when the wireless access point receives an access request from an access terminal, whether the access of the access terminal is allowed is determined according to the load information itself and the load information of the adjacent wireless access points. According to the method and the system, the goal of controlling the load balance of the discrete wireless access point can be achieved.

The invention discloses a heterogeneous rock digital rock core modeling method based on a K-means clustering algorithm, and belongs to the field of rock physical mechanics numerical simulation. The method comprises the following steps: firstly, carrying out XRD mineral composition testing, high-pressure mercury injection porosity testing, field emission environment SEM and CT scanning experiments on heterogeneous rocks; counting the mean value of the gray values of each mineral component of the BSE gray image to serve as the initial clustering center of the K-means clustering algorithm; preprocessing the heterogeneous rock CT scanning image; calculating the distance between the gray value of the CT image and the initial clustering center, and judging the membership degree of the gray value belonging to each category; and iteratively updating the clustering center and the gray value membership degree of the CT image to enable the target function to be minimum, completing the gray value classification and image segmentation of the CT image, and constructing the digital core of the heterogeneous rock. According to the method, the problems that the accuracy of a division result of randomly selecting the initial centroid and the k value cannot be determined and segmentation errors are caused by segmenting the image according to a threshold value can be solved, and the heterogeneous rock CT image data are optimally divided.

The invention discloses a rock cohesive force-internal friction angle calculation method based on a digital core technology. The method comprises the following steps: obtaining micro-scale mechanicalparameters of an original rock sample as input parameters of numerical simulation based on a rock nanoindentation experiment result; carrying out a micro-CT scanning test on the rock core to obtain arock micro-pore structure image, and reconstructing a three-dimensional grid model of the rock sample RVE; carrying out triaxial compression numerical simulation research of a rock sample RVE model based on a Moore Coulomb criterion; and obtaining the maximum compressive strength under different confining pressures according to a triaxial compression numerical simulation result, drawing an optimalrelation curve of the axial stress sigma 1 and the confining pressure sigma 3, and then solving the cohesive force and the internal friction angle of a rock matrix on the basis of the principle of aleast square method.

The invention belongs to the technical field of intelligent clothing, and discloses a clothing suit recommendation system and method, and the system comprises an image acquisition unit, an image processing unit, a feature extraction unit, and a clothing recommendation unit. The image acquisition unit is used for acquiring suit images of enough clothes and related text descriptions of the suit images; the image processing unit is used for storing images, texts and feature vectors of the images and the texts in the suit-by-suit clothes in a database; the feature extraction unit is used for preprocessing collected suit images and texts of a large number of clothes, performing feature extraction and fusion on the suit images and texts one by one and generating matching scores of the clothes; and the clothing recommendation unit is used for performing similarity calculation on the extracted image features and features pre-stored in a database, and recommending the most similar clothing. The clothing suit and the description text of the clothing suit are processed by using the convolutional neural network and natural language processing, so that the overall speed of algorithm processing is greatly improved, and the timeliness of the system is improved.

The invention provides a Hopkinson dynamic experiment device with controllable waveform excited by a hydraulic servo testing machine, which comprises a hydraulic servo dynamic load testing machine, a position adjusting mechanism, a Hopkinson incident bar, a Hopkinson transmission bar and a dynamic strain gauge, and is characterized in that a loading disc of the testing machine is arranged in the position adjusting mechanism, and a loading impact shaft is arranged on the loading disc; one end of the Hopkinson incident bar is connected to the loading impact shaft, an experimental sample is mounted between the Hopkinson transmission bar and the Hopkinson incident bar, strain gauges are arranged on the outer walls of the Hopkinson transmission bar, the Hopkinson incident bar and the experimental sample, the dynamic strain gauge is connected with the strain gauges, and the dynamic strain gauge is connected with the Hopkinson transmission bar and the Hopkinson incident bar. According to the method, specific waveform excitation and introduction are realized, stress wave propagation and action processes are truly reduced by virtue of the advantages of a transmission system of the Hopkinson bar, residual wave reflection and oscillation effects are effectively avoided, a relation between stress waves and impact energy is established, and waveform inversion is performed on a fracture behavior of an experimental sample under the action of dynamic impact.

The invention discloses a doubly-fed fan wind power plant frequency modulation capacity evaluation method considering multiple frequency modulation control strategies. According to the method, firstly, the operation condition difference caused by different space-time distribution of each fan in a wind field is simulated, the optimal frequency modulation control strategy of the fan under differentoperation conditions is determined, modeling of different frequency modulation strategies of a fan under different wind speeds is completed, meanwhile, the maximum frequency modulation capacity of various control strategies under the corresponding wind speed condition is evaluated, and finally the maximum frequency modulation capacity evaluation result of the whole wind power plant is obtained ina weighted summation mode on the basis of the wind speed distribution probability. The method aims to quantitatively evaluate the frequency modulation capability of the fan based on the level of the wind field, and can effectively establish the relationship between the active control capability of the fan level and the system scheduling level. And the corresponding evaluation result can be used asa powerful reference basis for system scheduling or wind power plant energy storage capacity configuration.

The invention discloses a neural network decoupling method, which comprises the following steps of: 1, for each convolutional layer of a neural network, selecting a filter participating in calculationaccording to the importance of each filter in the convolutional layer; and 2, training the neural network obtained in the step 1 based on a mutual information loss function, a KL-divergence loss function and a sparse loss function. According to the method, the structure of the neural network is decoupled, so that different calculation paths can be generated for different inputs, the working principle of the neural network is further explained, the inference of the neural network is accelerated, and the robustness of the neural network is enhanced.

The invention discloses a traditional Chinese medicine syndrome type identification method based on a graph attention network, and the method comprises the steps: standardizing a plurality of medical case data, and constructing a training set, namely corpus data; respectively establishing a symptom set and a syndrome set for all non-repeated symptoms and syndromes in the corpus; every two symptoms in each medical case data belonging to the training set being connected to serve as nodes, calculating point mutual information between the two symptoms in the symptom set, and updating nodes in a graph by using a graph attention network; weighting the updated nodes by using an attention mechanism to obtain feature vectors of symptoms; inputting the feature vectors into a linear layer for classification to obtain the probability of each syndrome; calculating a loss function in combination with the probability of each syndrome type and the real condition in the training set; performing back propagation according to the loss function, and completing model iteration; and inputting symptom information to be identified into the trained model to obtain a symptom type identification result. According to the invention, the accuracy of identification of the syndrome type is effectively improved.

The invention relates to the technical field of data processing systems or methods specially suitable for management and supervision, in particular to an information management system based on a cloud platform, which comprises a construction subsystem used for acquiring function requirements and index requirements, constructing function units according to the function requirements and the index requirements, and constructing an enterprise management system according to a plurality of function units; an adjusting subsystem which is used for adding a supplementing unit and establishing a connection between the supplementing unit and the existing unit, and is used for screening a deleting unit and disconnecting the deleting unit from the existing unit; and an index sharing module which is used for uploading the index creation rules for configuring the actual indexes and the acquisition parameters to the cloud platform as sharing rules. By the adoption of the scheme, information intercommunication between all sections of an enterprise can be achieved, and functional units can be increased or decreased according to needs after an enterprise management system is built.

The invention provides an optical fiber fusion splicing structure and loss cloud detection system based on OCT technology. The system uses OCT technology to perform real-time, three-dimensional, fastand high-precision detection on optical fiber fusion splices, which can obtain full-view field structure information of the optical fiber fusion splices, including two-dimensional cross-section information and three-dimensional structure information, and realize accurate detection of practical problems such as fusion splicing dislocation and fusion splicing fault. At the same time, an optical fiber loss detection device consisting of a broadband light source and a spectrometer is used to detect and analyze the loss spectrum of the spliced optical fiber to further study the impact of differentoptical fiber fusion structures on its transmission loss and establish a database associated with the both, thereby providing strong digital technical support for the industrialized large-scale application of the optical fiber technology in the field of optical fiber communication and optical fiber sensing.

The invention relates to a design method for a microwave radio-frequency circuit, in particular to a structure design method for a power distribution circuit of a wideband phase shifter, which can beapplied to a wideband feed network and phase shifter circuit structure design of a mobile communication antenna. The method comprises the steps of determining initial input port impedance Z_in and output port impedance Z_out_i of the power distribution circuit; performing optimization to obtain impedances Z_in_m and Z_out_m_i and electrical lengths L_in_m and L_out_m_i of an impedance conversion section in a working frequency band range, wherein Z_in_m and L_in_m are impedance and electric length of the impedance conversion section between Z_in_c and Z_in; building a corresponding three-dimensional model of a simulation result circuit in circuit simulation software in full wave simulation software, and performing parameter scanning on parameters, influencing characteristic impedance and electric length, of the three-dimensional model to obtain a corresponding three-dimensional model parameter set; taking the three-dimensional model parameter set as initial values of the three-dimensional model parameters; and performing optimization through the full wave simulation software to obtain final parameter sizes of the three-dimensional model of the power distribution circuit.

The invention belongs to the technical field of fiber surface modification, and discloses cellulose nanowhiskers, synthetic fibers, a cement-based composite material and a reinforcing method. According to the functionalized cellulose nanowhisker, surface functional groups are optimally designed through quantum chemical calculation, molecular dynamics simulation and machine learning, and the cellulose nanowhisker with better surface activity is formed. The functionalized cellulose nanowhisker provided by the invention has relatively large specific surface area and reaction activity and optimal adsorption performance with a cement-based material. And the cement can be promoted to hydrate, and the compactness, the mechanical property and the durability of the cement-based material are improved. The functionalized cellulose nanowhisker can be used as a coupling agent to improve the bonding between the fiber and a cement matrix. The existence of the functionalized cellulose nanowhiskers provides chemical activity for the fiber surface, changes the chemical characteristics of the fiber surface, and is more beneficial to improving the interface bonding force.

The invention provides an intelligent interaction system for fingertip force detection and gesture recognition and an intelligent finger ring, the intelligent interaction system comprises an information acquisition module, an information processing module and an image rendering and display module, a convenient man-machine interaction mode can be provided in the fields of AR, VR, intelligent home control and the like, natural and simple gesture interaction is realized by using the specially designed intelligent finger ring, and the intelligent finger ring is convenient to use. And the experience feeling of the user during man-machine interaction is improved. The fingertip gesture and the contact force are identified according to the characteristic that the color distribution under the nail cover changes when the finger pulp is pressed, and meanwhile, the muscle shape and the color change of the fingertip serve as an identification characteristic for joint detection. Gesture categories are clear and practical, and interaction is natural. According to the method, a preprocessing program and a deep neural network are used for extracting features and recognizing gesture types and contact force, a complete interaction system is provided, system separation is achieved through wireless communication, multiple application scenes are provided, and the application prospect and feasibility of the system are improved.

The invention discloses a lock type stitch continuous suture method double-lid blepharoplasty, wherein upper eyelids are turned over after double-lid lines are marked on the upper eyelids, surgical operations are done under direct vision, the needle inlet depth is easy to master, and a levator aponeurosis is precisely sutured on the upper edge of a tarsal plate. Levator aponeuroses on upper eyelid skins and the upper edge of the tarsal plate are connected in a line shape, cutting force of suture lines to tissues nearly is zero, can not affect to build the connection between skins and the levator aponeuroses, and square embedding lines compactly and solidly bound the tissues which comprise the levator aponeuroses, orbicularis oculi muscles and dermis and the like, are more serious in postoperative inflammatory reaction, are wide and firm in bounding range and steady and durable in double lids effect, and are not easy to loss.

The invention discloses a coarse particle contraction rule method based on fractal theory. The coarse particle contraction rule method based on fractal theory is suitable for particle grade contraction of water conservation and civil engineering coarse particle, can effectively weaken coarse particle contraction effete. As for naturally formed sand-gravel material and generated blasting heap rockfill material through parameter design, the particle grading basically conform to Talbot grading curve, the particle size accord with fractal distribution, and good compacting performance is possessed. The coarse particle contraction rule method is based on the fractal theory, by introducing a grading parameter and a fractal dimension, and puts forward a contraction grading formula that physical mechanics condition is basically uniform on condition that original grading coarse particle appoints maximum control particle diameter dmax. The coarse particle contraction rule method based on the fractal theory specifically comprises the following steps: (1) calculating fractal dimension DO of the original grading; (2), through a relative density ratio test of corresponding ingredient of maximum control particle diameter, and determining a critical fractal dimension DL; (3) calculating grading parameter A according to relationship between the DO and the DL; (4) substituting the grading parameter A and the DO into the grading formula, and obtaining contracted target grading.

The invention provides a strong lubricant oil oxidation test device and a test method, and belongs to the technical field of engineering machines. The strong lubricant oil oxidation test device comprises a first oxidation bin 1 and a heater 2 used for heating the first oxidation bin 1, wherein the first oxidation bin 1 is arranged in the heater 2, the first oxidation bin 1 comprises a sealing chamber 11 containing lubricating oil and a sampling tube 12, the sampling tube 12 is arranged on the sealing chamber 11, one end of the sampling tube 12 is arranged in the sealing chamber 11, and the other end of the sampling tube is positioned outside the sealing chamber 11. The test method comprises the steps of heating the first oxidation bin 1 by the heater 2, and taking the sampling tube 12 out to be measured. The strong lubricant oil oxidation test device is provided with the oxidation bin capable of adjusting test conditions, so that a plurality of lubricant oil samples can be simultaneously tested, the test time can be added or reduced, and multiple properties of lubricant oil can be tested.

The invention discloses an SNP marker primer of a scab-resistant related gene TaRLK-B and application thereof. A primer combination for tracking an SNP marker of a disease-resistant candidate gene TaRLK-B of wheat scab-resistant Fhb1 consists of sequences shown in SEQ ID NO. 1-4. PCR amplification is performed in Wangshuibai and Alondra's respectively to obtain two genotypes, which can be used asan SNP marker for the TaRLK-B gene. In the mapping population and the natural population, the label analysis and the disease resistance linkage or association analysis are performed to evaluate the application value of the marker in breeding resistance, thereby indicating that not only TaRLK-B can be specifically identified, but also the scab-resistant gene Fhb1 on 3BS can be specifically tracked.