44 results about "Deep structure" patented technology

The invention discloses a super-resolution face recognition method based on deep belief networks, and relates to the technical field of face recognition. From a cognitive perspective, it is believed that an intrinsic relation exists between mutually corresponding face images differing in resolutions. But previous studies show that the method for expressing the intrinsic relation by linear approximation is restricted by linear approximation. Therefore, it is believed that the intrinsic relation is nonlinear. In view of outstanding performances of an artificial neural network on the nonlinear classification problem, a neural network algorithm is adopted to capture the nonlinear relation of the mutually corresponding face images differing in resolutions under the condition of posture change. Both theoretical research and neurophysiological research show that a deep structure, such as a system constructed by multiple layers of nonlinear processing units, should be constructed to build an intelligent processing system. According to the face recognition method, deep belief networks are adopted to extract a common nonlinear structure shared by mutually corresponding face images differing in resolutions.

A method is disclosed herein that includes an act of causing a processor to receive a sample, wherein the sample is one of spoken utterance, an online handwriting sample, or a moving image sample. The method also comprises the act of causing the processor to decode the sample based at least in part upon an output of a combination of a deep structure and a context-dependent Hidden Markov Model (HMM), wherein the deep structure is configured to output a posterior probability of a context-dependent unit. The deep structure is a Deep Belief Network consisting of many layers of nonlinear units with connecting weights between layers trained by a pretraining step followed by a fine-tuning step.

The present invention is preparation process of complicated tissue organ precursor and belongs to the field of biological tissue engineering technology. Seed cell or gene and matrix material are prepared into micro colloid bead or 3D multi-canal structure; and cell and rack are located in space accurately via fast computer aided formation, coating, injecting, etc. The said process is superior to available tissue engineering process, which is time consuming and has uneven distribution of cells in rack, hard permeation of cell to deep structure and other demerits. By means of part combination, the present invention can reach the requirement of complicated organ, and realize organ reconstruction for repair and regeneration.

The invention discloses a hyperspectral remote sensing data feature extraction method based on a convolution neural network, belongs to the technical field of remote sensing data feature extraction and aims to solve the problems that when the hyperspectral remote sensing data features are extracted by the existing method, the acquired feature data are not provided with deep structures and the post image processing is not benefited. The method includes firstly, performing bad band removal, data transformation and reconstruction and data pre-processing on the hyperspectral original data, and acquiring standardized input data; performing convolution on the standardized input data by different filters through localized receptive fields; performing sub sampling on the convolution results; stacking the convolution layer and the sub sampling layer, acquiring standardized input data state response, and implementing the hyperspectral remote sensing data feature extraction. The method is applied to the hyperspectral remote sensing data feature extraction.

Methods and systems for estimating values of process parameters, structural parameters, or both, based on x-ray scatterometry measurements of high aspect ratio semiconductor structures are presented herein. X-ray scatterometry measurements are performed at one or more steps of a fabrication process flow. The measurements are performed quickly and with sufficient accuracy to enable yield improvement of an on-going semiconductor fabrication process flow. Process corrections are determined based on the measured values of parameters of interest and the corrections are communicated to the process tool to change one or more process control parameters of the process tool. In some examples, measurements are performed while the wafer is being processed to control the on-going fabrication process step. In some examples, X-ray scatterometry measurements are performed after a particular process step and process control parameters are updated for processing of future devices.

Disclosed is a planetary gear box intelligent diagnosis method based on a stacking automatic encoding machine. The method includes firstly utilizing a data acquisition system to acquire frequency domains of a planetary gear box, and establishing a stacking automatic encoding machine classification module with a deep structure; utilizing weight to connect to the stacking automatic encoding machine to perform sequential p retraining on all hidden layers of the stacking automatic encoding machine, and assisting the stacking automatic encoding machine in extracting fault information of the spectrum in a self adaption manner; performing fine tuning on the parameters of the stacking automatic encoding machine after p retraining by the error back propagation method, optimizing the feature extracting process of the stacking automatic encoding machine, establishing the complex nonlinear mapping relationship between the spectrum of the planetary gear box and the fault types, and completing the training of the stacking automatic encoding machine; finally, utilizing the determined stacking automatic encoding machine model to perform intelligent diagnosis of the planetary gear box in big data. By the aid of the method, the self adaption extraction of the fault features of the planetary gear box in big data and the intelligent diagnosis of the fault types can be implemented accurately and reliably.

The invention discloses a method for increasing a seismic imaging resolution ratio and is applied to reflection seismic data processing in seismic exploration . The method includes that by performing frequency-dependent amplitude recovery and frequency dispersion correction on migration stack data volume, the resolution ratio of imaging is increased integrally, and the imaging resolution ratios of middle and deep structures are enabled to be close to the imaging resolution ratio of a shallow structure; amplitude recovery and frequency dispersion correction are performed based on a viscoelastic theory, but a nonuniform Q value field does not need to be provided in advance; viscous absorption of seismic waves is described by introducing an equivalence Q value, and the nonuniform equivalent Q value field needed for calculation is acquired by establishing a single numerical indicator and by utilizing parameter scanning. Compared with methods like unsteady-state deconvolution, the method has the advantages that high-frequency information is restored while frequency dispersion correction is completed; a stable control algorithm is introduced, so that stability of calculation is guaranteed. By the method, breaking of the middle and deep structures and stratum deposition forms can be indicated better; and the method has important application value for oil-gas and mineral resource exploration.

The invention belongs to the technical field of medicines and in particular relates to application of an indol-ethylene substituted quinoline derivative in preparing drug-resistance bacterium medicines. The invention provides application of the indol-ethylene substituted quinoline derivative of formula (I) as shown in the specification in preparing drug-resistance bacterium medicines. The indol-ethylene substituted quinoline derivative provided by the invention has a remarkable inhibition function upon multiple drug-resistance bacteria, and is capable of remarkably inhibiting growth and propagation of vancomycin-resistant enterococcus, drug-resistant escherichia coli and methicillin-resistant staphylococcus aureus. Deep structure and function study shows that the indol-ethylene substitutedquinoline derivative provided by the invention has an action target of a bacterium split protein FtsZ, because of differences of FtsZ and human micro-tube protein sequences, drug-resistance bacteriummedicines which can selectively act upon bacteria FtsZ without interfering host cells can be designed, and the derivative is good in antibacterial activity, is capable of reducing amounts of single medicines, then reducing toxic and side effects and reducing drug resistance, and has the prospect of being developed into novel antibiotic medicines.

The invention provides a deep belief network image classification protocol based on a bottom layer fusion feature. The deep belief network image classification protocol comprises the steps of firstly extracting colors, textures and shape features in a sample image to form a multi-feature fusion weight matrix; then normalizing the weight matrix; and finally training and testing the deep belief network by taking the normalized weight matrix as original data to obtain a classification result. The deep belief network is a structure formed by connecting a plurality of restricted Boltzmann machine (RBM) models together and a deep structure formed by a BP (Back Propagation) network; connecting RBMs of each layer, and forming the whole deep belief network by taking output of a previous layer RBM as input of a next layer RBM and output of a final layer RBM as input of the BP network; inputting the original data to the first layer RBM, and utilizing output of the BP network as the classification result. The deep belief network image classification protocol has good expandability, the classification correct rate is improved through multi-feature fusion and the deep belief network improves the classification efficiency.

The invention relates to a multi-stage reducing reaming-while-drilling drilling rig and method based on a radio frequency identification technology. The multi-stage reducing reaming-while-drilling drilling rig and method are suitable for deep structure coal seam horizontal well underground multi-stage reaming. The multi-stage reducing reaming-while-drilling drilling rig includes a radio frequencyidentification excitation mechanism, an electro-hydraulic control mechanism and a multi-stage reaming recovery mechanism. The multi-stage reaming recovery mechanism is utilized to complete primary andsecondary expansion and recovery of a reaming knife wing; for reaming activation, an RFID system is adopted to activate the electro-hydraulic control mechanism, needed reaming conditions are changedby changing an electronic tag ball placed down, and remote control of the reaming is achieved; on the premise of no replacement of the drilling rig, reaming drilling in multiple modes such as a horizontal well, a vertical well and an inclined shaft is achieved in a soft formation such as deformed coal, and multi-stage reaming operation in a certain hole section can also be completed according to engineering needs; an excitation and reaming mechanism is reliable in structure, a reaming mode of the reaming-while-drilling drilling rig is reliable, the hole expansion rate is high, large-diameter pore forming can be achieved, the reaming stability is good, and the degree of automation is high.

The invention discloses a transformer fault diagnosis method and a transformer fault diagnosis device. The transformer fault diagnosis method comprises a first gray scale image corresponding to an infrared image of a to-be-diagnosed transformer is acquired, and according to the pixel value of the first gray scale image, whether the to-be-diagnosed transformer is faulted is determined; when faults exist, the characteristic images of the transformer parts of the to-be-diagnosed transformer are acquired, and comprise gray scale images; the first deep structure characteristics of the characteristic images are determined; the first deep structure characteristics are used to reflect the appearance characteristics, the texture characteristics, and the fault position characteristics of the transformer parts; second deep structure characteristics matched with the first deep structure characteristics are determined according to a predetermined corresponding relation, and the part names corresponding to the determined second deep structure characteristics are used as the names of the transformer parts having the overheating faults. According to the invention, the names of the transformer parts having the concrete faults are determined.

A method is disclosed herein that includes an act of causing a processor to access a deep-structured, layered or hierarchical model, called deep convex network, retained in a computer-readable medium, wherein the deep-structured model comprises a plurality of layers with weights assigned thereto. This layered model can produce the output serving as the scores to combine with transition probabilities between states in a hidden Markov model and language model scores to form a full speech recognizer. The method makes joint use of nonlinear random projections and RBM weights, and it stacks a lower module's output with the raw data to establish its immediately higher module. Batch-based, convex optimization is performed to learn a portion of the deep convex network's weights, rendering it appropriate for parallel computation to accomplish the training. The method can further include the act of jointly substantially optimizing the weights, the transition probabilities, and the language model scores of the deep-structured model using the optimization criterion based on a sequence rather than a set of unrelated frames.

The present invention provides a facial action unit strength estimation-based expression analysis method. The method mainly comprises the content of structured depth condition random field, one-element potential, paired potential, learning and deduction, and comprises the process that the structured depth condition random field has two settings, in the first setting, an input facial image is given, a pre-defined convolutional neural network layer is applied to the (normalization) input image to generate a characteristic graph, and the second setting is to use a data enhancement learning method to utilize the information coming from a plurality of data sets; the one-element node potential is defined in a structural depth condition random field, when the random variables are discrete, the joint distribution can be constructed for the discrete variables, and an objective function of the learned and generated structural depth condition random field is enhanced from the plurality of data sets. The expression analysis method of the present invention utilizes the deep structured learning, can process the high-dimension input characteristics, and enables the image characteristics to be improved substantially, the performances to be improved remarkably and the facial action unit strength estimation accuracy to be improved.

The embodiment of the invention provides a user question and knowledge point matching method and device. The method comprises the following steps: taking the user question as the input of a pre-trained natural language processing model; obtaining a matching node set formed by semantic nodes matched with the user question in a pre-established service guide graph, when the matching node set is matched with a plurality of links of the service guide map, the service guide map is matched; adding the knowledge points mounted on the leaf node of each link into a knowledge point set matched with the question of the user; taking the user question and the knowledge point title of each knowledge point in the knowledge point set as the input of a pre-trained deep structured semantic model; obtaining the similarity between the user question and the knowledge point title of each knowledge point in the knowledge point set; according to the similarity between the user question and the knowledge pointtitle of each knowledge point in the knowledge point set, the knowledge points matched with the user question are determined, the matching effect between the user question and the knowledge points canbe improved, and the service quality of the intelligent customer service is correspondingly improved.

An electromagnetic data acquisition system and an associated method for measuring subsurface structures with electromagnetic fields is employed for removing near surface effects from borehole to surface electromagnetic data. Preferably, the system is used to obtain information about deep, target structures located deep below the Earth, especially in oil and gas fields, while mitigating the effect of near surface geological shallow structures on collected electromagnetic (EM) data by using a series of electromagnetic measurements and data treatments that preferentially illuminate near surface geologic shallow structures so that the shallow structures may be recovered separately from deep structures of interest.

The invention discloses an artificial cultivation method for camphor trees, and belongs to the technical field of afforestation. The artificial cultivation method specifically comprises five steps ofselecting an afforestation land, cutting grass and conducting controlled burning, conducting soil preparation on a furrow zone, transplanting and conducting tending management. By adopting controlledburning and soil preparation on the furrow zone, quick acting nutrients can be greatly increased, the soil fertility can be improved, expelling of harmful animals is facilitated, pests and diseases are reduced, the sanitation status of the afforestation land is improved, the deep structure of soil is improved, water permeability and soil aeration are improved, water and fertilizer retention capacity is improved, and microbial activities are promoted to improve the fertility of the soil, so that the root development of the camphor trees and the rapid growth of overground parts are facilitated,the survival rate of cultivation is 95% or above, the process is simple, the labor intensity is small, and seedlings grow rapidly after transplanting.

The invention relates to a single-blade lateral milling method based on torsional ultrasonic vibration. The single-blade lateral milling method is characterized in that an ultrasound single-blade lateral milling device is driven by a machine tool spindle to rotate, a workpiece is fed on a machine tool workbench, normal contact between a tool bit and a machining face is always maintained during machining, the turning radius of a tool bit and workpiece contact point is smaller than the curvature radius of the contact point on the workpiece, the vibration direction is the tangential direction ofrotation of a single-blade milling cutter, and a single-blade lateral milling mode under torsional ultrasonic vibration is realized. The single-blade lateral milling method has the advantages that themethod is novel, the structure is unique, the process is practical, and reliability is high; the ultrasound single-blade lateral milling device is simplified in structure, downsized and convenient tomount; single-blade milling impact is improved, the method is adapted to milling of narrow and deep structures, frequency variation of a sound and vibration system is overcome, and heat radiation ofthe sound and vibration system is omitted; the problem of milling difficulty of high-hardness high-precision complex undercut hook faces and high-hardness variable-pitch spiral grooves is solved undercommon technological conditions, and the application prospect is abroad.

The invention discloses an electric power defect level identification method based on deep semantic matching, and relates to the technical field of electric power defect level identification. A traditional text classification model has a vector space model based on Boolean values, the defects that deep context semantics cannot be considered, vectors are sparse, interpretability does not exist andthe like are overcome, and the classification precision is not high for defective texts of power equipment. According to the method, a deep neural network is adopted to divide sentences into five layers of structures including an input layer, a representation layer, a matching layer, a sorting layer and an output layer, and a deep structure semantic model is achieved; then, the text is preprocessed on the input layer based on word hashing and a word segmentation model; on the basis of the deep neural network, an input layer, a representation layer and a matching layer are trained in sequence to obtain a low-dimensional representation vector of the defect text; and finally, obtaining the average defect level of the to-be-classified text based on the semantic similarity of the cosin distanceand the TopK sorting model. The level identification rate of the defect text is effectively improved, and high-precision power defect level identification is realized.

An optical cannula configured for implantation in biological tissue or other samples provides minimal invasiveness while accessing image deep structures within the sample. The cannula has a stabilizer portion that is used to affix the cannula to the sample, and an extension portion that protrudes into the sample and is either formed by, or contains, an optical probe that images a target area within the sample to an object image provided to an external optical device. The cannula has an integrated coupler portion that detachably connects to a connector of the external device, providing removable and interchangeable connection to external optical systems.

The proposed bottom station relates to geophysical exploration, particularly to the geo-electrical seismic survey equipment. It's intended for prediction of hydrocarbons deposits and study of the deep structure of earth's crust. The station comprises a body, a load, a registration device. The station is characterized by placement of sensors in the lower part of body, in combination with the use of the load, having a cavity on the upper surface with a diameter exceeding the corresponding body's diameter. The body is releasably fastened to the load by means of Kevlar ropes. Additional accuracy of the station is achieved by the use of orthogonal three-component sensors, rather than cardan sensors, as well as by incorporating into the station's body an additional acoustic system for control of location of the station. Substitution of a hard drive by a flush memory card in the registration device increases reliability of storing and transmitting information.

A scanning optical head for a catheter is locally controlled by a motor at an insertion end of the catheter uses a hollow motor through which a longitudinal optical path of the catheter passes. This permits the motor to be positioned between a control base of the catheter and avoids rotating the whole fibre, and therefore makes the beam scanning stable and accurate. In addition, because there is no coupling component, it also eliminates the light reflection between additional surfaces as well as varying fiber birefringence, which becomes a cause of noise when imaging the deep structure.

The present invention provides a true ground surface-based pre-stack seismic imaging method. The method includes the following steps that: a pre-stressed seismic trace gather is corrected to a ground surface coherent floating surface, so that a first seismic trace gather is obtained; the first seismic trace gather is dynamically corrected, so that a second seismic trace gather is obtained; the remaining static correction amount of the second seismic trace gather is calculated, and the remaining static correction amount is applied to the first seismic trace gather, so that a third seismic trace gather can be obtained; pre-stack time migration based on a true ground surface and a true vibration amplitude is performed on the third seismic trace gather, so that a post-processing fourth seismic trace gather can be obtained; and a final migration superimposed seismic imaging result is generated according to the post-processing fourth seismic trace gather. The true ground surface-based pre-stack seismic imaging method of the invention is particularly suitable for processing seismic data imaging problems in work areas where topographic relief is severe, deep structures are complex and signal-to-noise ratios are low. The true ground surface-based pre-stack seismic imaging method of the invention has the advantages of clear imaging of structures, better performance in matching a borehole and better performance in identifying associated fractures. The imaging effect of the method of the invention can depict the small fractures of complex fault block regions more clearly.

The embodiment of the invention provides a method and device for recalling standard questions according to user questions, and the method comprises the steps: carrying out the word segmentation of a current user question, and obtaining a word segmentation set corresponding to the current user question; taking the word segmentation set as the input of a pre-trained first convolutional neural network CNN model, and obtaining a first sentence representation vector of the current user question through the output of the first CNN model; obtaining each second sentence representation vector corresponding to each standard question generated according to a pre-trained second CNN model; determining a recalled standard question sentence according to the first sentence representation vector and each second sentence representation vector; wherein the first CNN model and the second CNN model are used as feature extractors in a deep structure semantic model DSSM model, and are obtained by training the DSSM model. The standard questions can be efficiently recalled according to the user questions, and the recalled standard questions have a large probability to meet the requirements of users.

An intelligent diagnosis method for planetary gearboxes based on stacked autoencoders. First, the data acquisition system is used to obtain the frequency domain signals of planetary gearboxes, and a classification model of stacked autoencoders with a deep structure is established; All hidden layers of the autoencoder are pre-trained layer by layer to help the stacked autoencoder adaptively extract fault information in the spectrum; then use the reverse error propagation method to fine-tune the parameters of the pre-trained stacked autoencoder to optimize the stacked autoencoder The feature extraction process of the machine and the complex nonlinear mapping relationship between the spectrum of the planetary gearbox and the fault type are established to complete the training of the stacked autoencoder; finally, the determined stacked autoencoder model is used to carry out the intelligence of the planetary gearbox under the big data Diagnosis, the present invention realizes self-adaptive extraction of planetary gearbox fault features and intelligent diagnosis of fault states under a large amount of data, which is accurate and reliable.

Provided is a method and system for delivering a diagnostic agent to a site in the brain of a subject for imaging at least a portion of the brain site on a medical imaging system. The method and system includes a catheter device with associated lumens having diagnostic agent ports for delivering the diagnostic agent (e.g., infusate) through the lumens and advancing the diagnostic agent so as to exit out from the lumens to at least a portion of the brain site and while sealing a portion of the brain site thereby preventing the exited diagnostic agent from travelling proximally beyond the sealing location, and at the same time imaging at least a portion of the brain site during at least a portion of the sealing duration so that the brain site can be visualized on a medical imaging system. The diagnostic agent (infusate) is able to highlight borders and internal patterns of the deep structures of the brain thereby enabling direct targeting. Ultimately this leads to reduced complications, enhanced therapy, and the elimination of the need for awake surgery. The method and system provides the capability heretofore not possible to visualize the small, often indistinct regions, which will greatly improve clinical outcomes with therapeutic interventions.

The invention discloses a surface water-based preserving agent for GCr15 steel. The surface water-based preserving agent is composed of, by weight, 20-24% of deionized water, 14-18% of corrosion inhibitors, 11-16% of 10% tannic acid solutions, 2-3% of potassium sorbate, 2-4% of sodium carbonate, 6-9% of triethanolamine, 2-3% of polyisobutene, 3-6% of guar gum, 2-5% of sesbania gum, 10-15% of mixed alcohols, 2-6% of strong phosphoric acid, 3-6% of grape saccharin, 2-3% of wetting agents and 1-2% of defoaming agents. According to the surface water-based preserving agent, the selected materials are superior, the scientific processing method is adopted, and rust protection and film formation act together; the deionized water serving as a dispersion medium is matched with the other raw materials, the environment friendliness is high, and pollution is avoided. In addition, the surface water-based preserving agent is free of methylbenzene, ethylbenzene, dimethylbenzene, chromic acid, sodium nitrite and formaldehyde, low in volatile organic compound (VOC), free of pungent smells and harmless to the human body, can be easily absorbed by deep structures, can effectively protect the surface of the steel against corrosion, cavitation and scale formation, can form a protective film layer, can delay the time of generating rusts on the surface of the steel and has remarkable environmental benefits, economic benefits and social benefits.

The invention discloses a geological rock core space posture restoration device which comprises a base table, a rotary table rotationally arranged on the base table, a middle table body rotationally arranged on the rotary table and a rotary chuck rotationally arranged on the middle table body and used for clamping a rock core. The middle platform body is also provided with a displacement measuringdevice which can move along the rotation axis direction of the rotation chuck and is used for measuring the distance from the rotation axis of the rotation chuck to each point on the outer surface ofthe rock core; the rotation axis of the rotary table is perpendicular to the rotation axis of the middle table body, and the rotation axis of the rotary chuck is perpendicular to the rotation axis ofthe middle table body. The device has the characteristics of accurate restoration of the rock core space attitude, reliable parameter test precision and high automation degree, is suitable for original space attitude restoration of the common non-directional geological rock core, and assists in deep rock mass ground stress test and deep structure analysis.

A variety of deep structured decorative patterns originate with mechanical relief or etching. The present method incorporates a deeply patterned or textured etching or relief into a thin film embossing shim to simulate the look of the deep pattern or texture when used to emboss thin film or material. A transparent mold of the relief surface (such as brushed metal, engine-turned patterns, and textured glass) is formed using UV curable liquid and a transparent substrate. The relief copy in the transparent mold or overlay is mapped onto a photoresist surface or plate by shining or expanding one or more laser lights or laser beams through the transparent mold. The different heights of the relief copy of the transparent mold will cause the light to diffract / refract to form a corresponding patterned etching in the photoresist plate. The resulting photoresist plate is then metalized and electroplated to form a thin film embossing shim. The thin film embossing shim is then used with conventional embossing equipment to form thin film embossings. The embossed thin films can then be metalized and laminated onto substrate to create a product that has shifting patterns that reflect at a variety of viewing angles when (observed under normal lighting conditions) exposed to white light.