56results about How to "Excellent accuracy" patented technology

The present invention relates to at least one method, apparatus and / or system for providing at least one lymph node volume for use in the monitoring of progression, diagnosis or treatment of an inflammatory condition, as well as to a computer program product comprising software code portions for implementing the method in accordance with the invention.

The invention discloses a rice blast resistance gene Pi9 gene specificity molecular marker Pi9SNP as well as preparation and application thereof. The molecular marker Pi9SNP is prepared by amplifying from total DNA (Deoxyribonucleic Acid) of a rice blast resistant variety with rice blast resistance gene Pi9 by using a primer pair F1 and R1 so as to obtain a nucleotide segment I, and carrying out digestion on the nucleotide segment I by using restriction enzyme Hind III, so as to obtain a nucleotide segment II which is in specificity banding pattern with the obtained rice blast resistance gene Pi9. The molecular marker is the first one which is developed for marking Pi9 gene specificity SNP (Signal Nucleotide Polymorphism) for an internal sequence of the Pig gene, and has the following advantages that the specificity is high, the cost is low and the flux is high in practical application, and the molecular marker is widely applied to colonies of different genetic backgrounds. By utilizing the molecular marker, the efficiency in auxiliary molecular marker selective breeding, gene pyramiding breeding and transgenosis breeding is improved.

A method and system provide for temporal fusion of depth maps in an image space representation. A series of depth maps are obtained / acquired from one or more depth sensors at a first time. A first Gaussian mixture model (GMM) is initialized using one of the series of depth maps. A second depth map is obtained from the depth sensors at a second time. An estimate of the motion of the depth sensors, from the first time to the second time, is received. A predictive GMM at the second time is created based on a transform of the first GMM and the estimate of the motion. The predictive GMM is updated based on the second depth map.

The invention discloses a method for checking consistency of a schematic diagram and PCB production data. The method comprises steps as follows: making a standard template of a PCB design software schematic diagram netlist file; making a standard template of an ODB++processing data netlist file; extracting a PCB design software schematic diagram netlist, and extracting a processing data netlist; analyzing the netlists, and storing connecting relation description information, device type information, abidance device information, connection node number, connection nodes and a terminator protocol in a list manner; comparing theschematic diagram netlist file with the processing data netlist file according to a defined data storage protocol; generating a report file according to a comparison result. According to the method, the problems of network loss, short circuit and the like caused by negligence, software bug and the like in a PCB design process are solved, time cost consumed by a designer for connecting relation correction is saved, and the method is better than a currently utilized IPC (inter-process communication) netlist comparison method in the aspects of accuracy and efficiency.

The present invention relates to an FCN retina image blood vessel segmentation through combination of depth separable convolution and channel weighing. The method comprises the steps of: 1) performingCLAHE and Gamma correction to enhance a contrast ratio of a green channel of an eye bottom image; 2) in order to adapt network training, performing partitioning of the enhanced image to expand data;and 3) replacing a standard convolution mode with depth separable convolution to increase the width of the network, and introducing a channel weighing module to explicitly perform modeling of a dependency relation of a feature channel so as to improve the separability of the features. The depth separable convolution and the channel weighing are combined to be applied into the FCN network, an expert manual identification result is taken as supervision to perform experiment in a DRIVE database. The result shows that: the method can accurately perform segmentation of the retina image blood vessels and has high robustness.

A computer-implemented method of behavior prediction includes selecting behavior examples having corresponding antecedent candidates, identifying source text descriptions describing the behavior examples, automatically extracting predictors as common themes across all statements and all behavior examples with a language-independent theme extraction process, flagging each behavior example to indicate a presence or absence of the corresponding extracted antecedents in each of the source text descriptions and creating a data array consisting of antecedent columns and behavior example rows, submitting the data array to a pattern classifier to extract patterns among the antecedent candidates and outcomes by training and validating the pattern classifier and predicting a new occurrence of a target behavior by entering a current state of the antecedents to the trained pattern classifier.

The invention discloses a moving vehicle speed measurement method based on target tracking and feature point matching, and belongs to the field of intelligent traffic. The method mainly comprises the steps that a current image sequence Fn is obtained; a gray level image Y(n) of the current frame is obtained; position information P_Cur of a moving vehicle of the current frame is obtained according to background modeling; track information T of the moving target of the current frame is obtained; feature points are extracted, and information of the feature points is recorded; the feature points are matched, the moving displacement of the target is calculated, and the instant running speed of the target is obtained according to a camera calibration result; scale changes of feature points to be matched and the matched feature points are calculated according to a final matching result and then are analyzed, and algorithm parameters are updated according to the analyzing result; the average value of all instant speeds of the moving target is obtained. The method can efficiently and accurately calculate out the moving displacement of the vehicle and is applicable to the systems such as security vehicle monitoring systems and red light running electronic police systems.

A catalyst (17) of a NOx absorbing-and-reducing type is disposed in an exhaust passage (10) of an engine (1). The catalyst (17) absorbs a NOx component in an exhaust gas under an over-oxygen atmosphere and reductively emits the absorbed NOx component according to reduction of oxygen concentration. A control unit (20) of the engine (1) estimates a momentary amount of the absorbed NOx component, and further estimates an integrated amount of the absorbed NOx component according to the integration of the momentary amounts. Then the control unit (20) lets the catalyst (17) to emit the NOx component when the integrated amount is equal to or greater than a predetermined absorption amount. In addition, the control unit (20) corrects the momentary amount to a smaller value in adverse proportion to the increase in the integrated amount.

The invention belongs to the field of video and image processing, and provides a stereoscopic video objective quality evaluation method which is more suitable to the human vision system related characteristic and effective. A new stereoscopic video objective quality evaluation method can more accurately evaluate the quality of the stereoscopic video, and pushes the development of the stereoscopic imaging technology at the same time. An application method of a vision multichannel model in stereoscopic video quality objective evaluation comprises the following steps: modelling the vision multichannel model by use of haar wavelets, firstly performing three-level wavelet transformation on an absolute difference map of a key frame so as to simulate the human eye multichannel characteristic by resolving the absolute difference map into different directions and frequency ingredients; and evaluating the different components obtained through transformation by applying SSIM so as to obtain the corresponding objective quality; obtaining the single quality of each key frame by use of the wavelet inverse transformation; and finally weighting the quality of the key frame by use of the weight of the key frame so as to obtain the complete stereoscopic video quality. The application method of the vision multichannel model is mainly applied to the video and image processing.

A finely patterned silica type ceramic film suitable as an inter-layer dielectric is formed in a short time by applying, onto a substrate, a positive working radiation sensitive polysilazane composition comprising a modified poly(sil sesquiazane) having a number average molecular weight of 100 to 100,000 and containing a basic constituent unit represented by the general formula: —[SiR6(NR7)1.5]— and other constituent units represented by the general formula: —[SiR62NR7]— and / or —[SiR63(NR7)0.5]— (R6 and R7 independently represent a hydrogen atom, a C1-3 alkyl group or a substituted or unsubstituted phenyl group) in a ratio of 0.1 to 100 mol-% to said basic constituent unit, a photo acid generator and preferably a water-soluble compound as a shape stabilizer, then patternwise exposing the resultant coating film, subjecting the exposed part of the coating film to moistening treatment, developing it with an aqueous alkali solution, wholly exposing the coating film to light and moistening treatment again, followed by burning treatment.

The invention belongs to the field of fungus species identification and relates to a reference gene for molecular identification of Termitomyces clypeatus and a molecular identification method. Sequences of adopted primers are RPB2B-f: 5'-CCGCAAAGGCTGGTGTATC-3' and RPB2B-r: 5'-TTCGAATGAGTTCAAGTGT-3', and the primers can be used for amplification of large-subunit gene (RPB2) of RNA (ribonucleic acid) polymerase II of the termitomyces clypeatus to obtain a reference detection gene. The termitomyces clypeatus can be quickly and accurately identified according to RPB2 gene DNA (deoxyribonucleic acid) sequence differences. The RPB2 gene overcomes the defect of difficulty in identification of traditional termitomyces clypeatus forms and has the advantages of universality and easiness in amplification and comparison, reliability and accuracy in identification are greatly improved, and a powerful research implement is provided for excavation, protection and utilization of genetic resources of the termitomyces clypeatus.

The invention discloses a rice blast resistance gene Pi5 function specificity molecular marker named as Pi5InDel and application of the rice blast resistance gene Pi5 function specificity molecular marker. The nucleotide sequence of the rice blast resistance gene Pi5 function specificity molecular marker is shown in the sequence SEQ ID NO.1. The rice blast resistance gene Pi5 function specificity molecular marker is high in specificity, is low in cost and high in throughput in practical application, and can be widely applied groups with different genetic backgrounds to screen rice germplasm containing the rice blast resistance gene Pi. By means of the molecular marker, the utilization efficiency of the molecular marker in molecular marker auxiliary selective breeding, gene pyramiding breeding and transgene breeding can be improved.

A gas sensor, for example for use in air conditioning systems, has a gas-sensitive layer that includes a material that is sensitive to carbon dioxide. The material has a cross-sensitivity to air humidity. This is compensated for by measurement at two different temperatures. The measured gas values are calculated together, with the assumption that the sensitivity of the gas sensor to carbon dioxide exhibits a different curve with the temperature of the gas sensor than the sensitivity to water.

An intelligent electrocardiogram data classification method based on voting ensemble learning in the invention is characterized by being realized through the following steps: a) carrying out data preprocessing; b) establishing a logistic regression model; c) establishing a decision tree model; d) establishing a support vector machine; e) establishing a naive Bayesian model; f) establishing a neuron model; g) establishing a k proximity model; and h) carrying out model integration. Finally, a model with the accuracy of not less than 80% is obtained, and the effect of the model is better than theeffect of the single model established in the steps b) to g). According to the intelligent electrocardiogram data classification method, enough data are firstly acquired from ccdd and are divided into a training set and a test set, then various models are established, and the model with accuracy of not less than 80% is finally obtained, thereby realizing intelligent identification and classification of normal, atrial fibrillation, atrial premature beat, accidental atrial premature beat, frequent atrial premature beat, atrial tachycardia and atrial fibrillation accompanied with rapid ventricular rate, and realizing early discovery and early treatment of cardiovascular diseases.

The invention belongs to the technical field of copy number variation (CNV) detection, and discloses a copy number variation detection method based on single-sample next-generation sequencing data. The method comprises the steps of: performing preprocessing of data in an earlier stage, filtering invalid locations, performing gC content calibration, data equalization and data denoising, performingsegmentation processing on the data, wherein part of data is used for fitting a model, the other part of data is used as detected data, and the cross detection of two parts of the data enables variation to be detected in the model; calculating the probability value of each piece of the data, selecting a significance level ([alpha]), and predicting the CNV by adopting a hypothesis testing method. In order to further verify the effectiveness of the method, simulation data samples are detected and compared with several existing popular methods, and the best performance is shown. The method is efficient in detection, accurate, easy to operate and high in detection speed; and the accuracy and recall rate of low-purity data testing are greatly superior to those of a comparison algorithm.

The invention discloses a high-resolution remote sensing image intersection automatic identification method. The method comprises the following steps: S1, road element extraction; S2, communicating road frameworks: connecting adjacent road elements to form a complete road framework; S3, candidate intersection coordinates are generated, specifically, refining operation is conducted on the extractedroad skeleton, and road skeleton intersection points are obtained and serve as the candidate intersection coordinates; S4, constructing an intersection similarity index; and S5, identifying the intersection based on the block rectangular rotation model. According to the method, manual intervention is not needed, the intersection can be automatically extracted, and the extraction accuracy and integrity are superior to those of existing similar research results.

The invention discloses an AHP (analytic hierarchy process) and GA (genetic algorithm)-based parameter optimization method applied to the participation of an energy storage device in power grid frequency modulation. The method includes the following steps that: the energy storage device and a controller thereof are added into a regional frequency modulation model; the analytic hierarchy process is utilized to determine the weight of the factors of the controller that influence a control effect, so that a fitness function can be obtained; the genetic algorithm is utilized to optimize control parameters, so that optimized parameters can be obtained; and the optimized parameters are screened according to the fitness function, optimized individuals are obtained; and the optimized individuals are transported to the energy storage device to control the output power of the energy storage device. According to the AHP (analytic hierarchy process) and GA (genetic algorithm)-based parameter optimization method applied to the participation of the energy storage device in power grid frequency modulation of the invention, an energy storage device assisted AGC frequency modulation mode is adopted, and therefore, frequency modulation performance can be effectively improved, frequency disturbance can be suppressed effectively, the frequency deviation of a system can be effectively reduced, and adjustment time can be shortened; and the analytic hierarchy process and genetic algorithm are adopted to set the parameters of the controller, so that high accuracy and high flexibility can be realized.

The invention discloses a narrowband interference resisting system and a narrowband interference resisting method based on adaptive signal processing. The narrowband interference resisting system based on the adaptive signal processing is located at the front end of a digital baseband, performs filtering processing on a digital intermediate frequency signal received by the narrowband interference resisting system based on the adaptive signal processing, and outputs the signal to the digital baseband after interference of the signal is filtered out. The narrowband interference resisting system based on the adaptive signal processing comprises a power spectrum estimation module of an interference signal, an interference reference signal generation module and an adaptive signal processing module. The narrowband interference resisting method based on the adaptive signal processing is directed at narrowband noise and continuous wave interference, and used to accurately detect, track and filter the interference signal. According to the narrowband interference resisting system and the narrowband interference resisting method based on the adaptive signal processing, useful signal components are retained to the utmost on the premise of filtering out the interference signal.

The invention relates to a method for dating the isotope of limestone Re-Os, and belongs to the technical field of isotope geochronology. The problems that the sampling method is unscientific, the dating samples are blindly selected, the success rate of dating is low, the sample digestion is incomplete and takes a long time, and the impurity interference caused by a dissolution scheme causes the poor accuracy and precision of the limestone Re-Os isotope age results. The method comprises the following steps: collecting a limestone sample and crushing the sample; selecting a limestone dating sample deposited in a reducing environment; pre-digesting the limestone dating sample, and dissolving a pre-digesting solution of the limestone dating sample with a mixed solution of hydrochloric acid and hydrogen peroxide; separating and purifying a dissolution solution Re-Os of the limestone dating sample; performing the Re-Os isotope thermal ionization mass spectrometry; processing the Re-Os isotope data to obtain the final limestone Re-Os isotopic age. The analysis method provided by the invention has the advantages of improving the success rate, accuracy, precision and the operation efficiency of the experimental process of the limestone Re-Os isotope dating.

The invention discloses a high-voltage direct-current power transmission line fault distance measurement method. The method comprises the following steps: S1, decoupling a power transmission line equation in a Bergeron model, and respectively obtaining a transient voltage component of a high-voltage direct-current power transmission line and transient current components of a rectification side andan inversion side; S2, determining voltage and current distribution along the line based on the obtained transient voltage and the transient current components of the rectification side and the inversion side, and calculating voltage and current ratio distribution along the line according to the obtained voltage and current distribution along the line; and S3, sampling the voltage-current ratio distribution along the line, calculating the standard deviation of the voltage-current ratio along the line obtained by sampling, and taking the distance corresponding to the voltage-current ratio along the line with the minimum standard deviation as a fault distance. According to the method, a filtering algorithm does not need to be involved, the inversion side auxiliary increasing current is introduced when the fault current is determined, the required data time window is short, and when fault distance measurement is carried out in a complex environment, the accuracy of fault distance measurement is high; and the method has better stable distance measurement performance.

Output power of Raman pump light is measured indirectly, and parameters of each pump laser are configured and managed. The characters are that measured output power of backlight of pump laser is as feedback control signal. After process of resolving intercept and compensating slope, the sampled value P1 of pump output power is obtained. Output powers of multiple lasers are configured and controlled automatically by using a feedback loop control circuit including microprocessor, which collects P1 as a controlling reference. The controlling and configuring functions are realized through adjusting current for driving pump laser by using microprocessor.

The embodiment of the invention provides a method for realizing pulmonary nodule adaptive matching based on CT image skeleton registration. The method comprises the following steps of data preparation, lung and skeleton point cloud data extraction, three-dimensional point cloud data registration and pulmonary nodule adaptive matching. . Firstly, lung image data and pulmonary nodule data are subjected to three-dimensional point cloud rigid transformation registration based on the characteristic of small human skeleton change characteristics, so that alignment of the lung and pulmonary nodule data before and after follow-up visit is realized. Secondly, an FGR algorithm is adopted, so that the method is obviously superior to ICP and other local refinement algorithms in the aspects of operation speed and registration accuracy. Thirdly, RMSE is adopted as a lung point cloud registration error, adaptive matching of pulmonary nodules is achieved, manual intervention of pulmonary nodule registration is little, the automation degree is high, and the registration result is accurate; and fourthly, normalization processing is carried out on the CT image data, so that the robustness of the algorithm can be improved, and the method can be widely applied to different types of CT equipment and DICOM data with different pixel spacing values.

The invention discloses a method for accelerating neural network structure selection, and relates to the technical field of neural networks, the method comprises the following steps of: reading a global.txt file by using a main thread M; judging whether the number of the neural network structures recorded in the file is smaller than t or not; if so, judging whether a neural network structure whichis not recorded in the global.txt file exists line by line or not; if so, querying an idle display card; enabling the main thread M to start a sub-thread; putting an unrecorded neural network structure on an idle display card for training through the sub-thread; after the main thread M is dormant for a certain time, continuously judging whether a neural network structure which is not recorded inthe global.txt file exists or not; and writing the unrecorded neural network structure into the global.txt file after the sub-thread training is completed, and selecting the optimal neural network structure corresponding to the current scene from the updated global.txt file. According to the method, the accurate neural network structure with the optimal performance is obtained, and the cost is relatively low.

Provided is a recordable optical recording medium that comprises a substrate, a recording layer, and a reflective layer, wherein the recording layer and the reflective layer are formed on the substrate, the recording layer is formed of an inorganic material, and information is recorded on the recordable optical recording medium by use of an irreversible change at the recording layer caused by irradiating blue laser light.

The invention discloses a fundus image blood vessel segmentation method based on full convolutional neural network multi-scale features. The fundus image blood vessel segmentation method comprises thefollowing steps of 1) preprocessing a fundus retina image; 2) segmenting the preprocessed image into image blocks for data expansion; 3) constructing a convolutional neural network model, and performing network training by using the expanded data; and 4) testing the trained model to obtain a segmentation result. According to the invention, one encoding structure and two different decoding structures are connected; the method provided by the invention can overcome the defects of low segmentation precision and the like caused by a small number of blood vessel image data sets and low image quality by adopting multiple skipping connections, more fully fuses the characteristics of different depths, effectively alleviates the problem of gradient disappearance caused by network depth increase, and has higher accuracy and higher robustness.

The invention provides a rice blast resistance gene Piz-t functional specific molecular marker and a detection method and application thereof. The molecular marker shows a specific banding pattern of the rice blast resistance gene Piz-t amplified from a rice genome DNA through primer pairs SEQ ID NO.1 and the SEQ ID NO.2. The rice blast resistance gene Piz-t gene specific molecular maker provided by the invention has important application values, and the utilization efficiency of the gene in each of germplasm resource screening, molecular marker-assisted selective breeding, gene pyramiding breeding and transgenic breeding can be improved by use of the marker.

The invention discloses a network penetration identification method based on interactive behavior analysis, and the method comprises the steps: employing a Seek client to collect the interactive behavior data of a honeypot machine as an analysis object, carrying out feature extraction and cleaning, feature classification and feature coding on collected data to form a feature sequence; according tothe characteristic that an interactive behavior characteristic sequence has uncertain length and time sequence, adopting an LSTM model as an attack recognition classifier, analyzing an activation function, a loss function and a gradient descent algorithm respectively, selecting an appropriate model to be used as the model, and then optimizing a training model through multiple times of hyper-parameter parameter adjustment. Modeling is carried out according to the time sequence of capturing behavior data features, the features are screened to reduce the feature dimension, and the training speedand precision of the model are improved through feature coding. Through repeated parameter tuning training, the penetration attack identification accuracy and the false alarm rate of the model are obviously superior to those of other models.

The invention discloses a method for removing video watermarks based on deep learning, which is characterized by comprising the following steps: 1) video processing; 2) data enhancement; 3) model training; and 4) realizing watermark elimination. The method has the advantages that the efficiency of processing massive video watermarks can be improved, the video watermarks can be rapidly removed in batches, no trace is left for watermark removal, and frames are not lost in original image quality after the watermarks are removed.

The invention discloses a coaxiality detection and regulation method, which comprises the following steps of code scanning, positioning, coaxiality measurement, coaxiality regulation, coaxiality secondary measurement, qualification judgment, screw tightening, measurement after the screwing, assembly qualification judgment and completion. The quantitative regulation is performed through an image measuring instrument; the automatic measurement and the automatic regulation of the coaxiality of assembled components are realized; the precision degree, the reliability and the like of the coaxialitymeasurement and coaxiality regulation are obviously superior to the precision degree, the reliability and the like of an original measurement and regulation method; the assembly quality can be effectively improved; the assembly efficiency is improved; after the assembly, the rework rate of workpieces is greatly reduced.

The invention discloses a high-voltage vacuum circuit breaker mechanical fault diagnosis method and system. The method comprises the steps: obtaining vibration signals at two different positions of ahigh-voltage vacuum circuit breaker of an electromagnetic repulsion mechanism through an acceleration sensor; carrying out time-frequency analysis on the obtained vibration signals at the two different positions in the same group through S transformation, and obtaining an S transformation mode matrix; and extracting energy entropy from the S transformation mode matrix as a feature vector to traina vector machine model, and obtaining a support vector machine training model. By means of the characteristic that the S transformation time-frequency resolution is high, energy distribution of the signals in a time-frequency plane can be visually seen after the vibration signals are subjected to S transformation, and the distinguishability in different states is high; the proposed fault diagnosismodel achieves a better diagnosis effect, and a new idea is provided for the mechanical fault diagnosis of the high-voltage vacuum circuit breaker under a small sample; and the mechanical fault occurring in the high-voltage vacuum circuit breaker of the electromagnetic repulsion mechanism can be accurately, reliably and quickly identified.