70results about How to "Increase sample" patented technology

The invention discloses a point cloud registration method for three-dimensional reconstruction. The point cloud registration method comprises the steps of S101, acquiring three-dimensional point clouds at multiple view angles, and adopting three-dimensional point clouds at two view angles as a source point set and a target point set respectively; S102, constructing a KD-tree; S103, figuring out the normal vectors of all points in the source point set; S104, calculating an average value of the included angles of the normal vectors; S105, classifying points in the source point set and setting amaximum resolution, wherein the initial resolution is 1; S106, calculating the sampling proportion of each stage in the source point set at the current resolution and extracting a sampling point; S107, figuring out the matching point of the sampling point in the target point set on the basis of the matching degree in the method; S108, calculating a rotation matrix and a translation matrix by usinga quaternion method; S109, converting the source point set to obtain a new source point set; S110, repeating the steps from S107 to S109 until a objective function is the minimum; S111, if a preset condition is met, ending the process; otherwise, adding 1 to the current resolution, and returning to the step S106. According to the invention, low-resolution matching points are used for rapidly completing the registration. The high-resolution matching points are used for improving the precision. Meanwhile, matching points are searched for through the matching degree. The registration speed and the registration precision of large-scale point clouds are greatly improved.

Sampling in the process of trans-raster distortion correction is described. The distortion parameterization is analyzed to determine the maximum inflation and deflation (magnification and minification) over the image. The maximum inflation is then used to determine the optimal resolution (dimensions in pixels) of the linear-projected image such that it is not undersampled by the output image. The maximum deflation, coupled with the optimal resolution determined in the inflation step, is then used to configure the filter used in the resampling process such that aliasing due to undersampling is minimized, while simultaneously controlling the computational burden of the filter.

The invention provides a sample weight allocation method. The method comprises the following steps: acquiring training samples, wherein the training samples include a positive sample set and a negative sample set; calculating the distance of each positive sample couple in the positive sample set, and the distance of each negative sample couple in the negative sample set; determining distance distribution of the positive sample set according to the distance of each positive sample couple in the positive sample set; determining distance distribution of the negative sample set according to the distance of each positive sample couple in the negative sample set; and determining weight distribution of the training samples based on the distance distribution of the positive sample set and the distance distribution of the negative sample set. The invention further provides a model training method, electronic equipment and a storage medium. According to the sample weight allocation method disclosed by the invention, the weight of the sample couples with wrong classification can be increased, and contribution of the samples with classification errors to targeted loss is increased in the modeltraining process, so that model parameters can be well corrected, and the expression ability of the model parameters is improved.

The invention discloses a virtual testing platform of a liquid rock engine and a testing method thereof, comprising a test manager module, a test object simulating module, an operation control module, a virtual environment module, a verification evaluating module and a database managing system. By determining a test object and a test proposal, the operation control module controls the simulation process of the test object simulating module, the virtual environment module performs three-dimensional display and entity mapping, the verification evaluating module evaluates a virtual test result, and the database managing system stores and manages data information, thus realizing the combination of the engine testing technology and the computer method, achieving the effect that the virtual testing platform serves as a seamless integrated system of a project, being led to be similar to true test operating practice, and being capable of having functions and performances similar to a true engine igniting test to a certain extent.

The invention relates to a super-sensitivity method, primer group and kit for capturing whole genome of novel coronavirus. The method can conveniently and quickly amplify the whole genome of the novelcoronavirus by using a small amount of RNA, and can directly dock with a second-generation sequencing library-building reagent and a third-generation sequencing platform so as to obtain a whole genome sequence of the novel coronavirus.

A data acquisition system (DAS) (30) for a computed tomography (CT) scanner (12) includes a two-dimensional array (32) of detectors (34) which is arranged to detect x-rays produced by the CT scanner (12). Each detector (34) is divided into two sub-detectors (34a, 34b) along an axial direction (z). A high-speed switching circuit (40) combines selected adjacent sub-detector outputs (34a, 34b), e.g. combining a sub-detector n alternately with sub-detectors (n−1) and (n+1). The high-speed switching circuit (40) switches its configuration between DAS measurements to produce interlaced DAS output signals along the axial direction (z).

The invention discloses a steel size and quantity identification method based on deep learning, intelligent equipment and a storage medium. The identification method comprises the following steps of:shooting a plurality of steel pile end face images through a camera, collecting camera aperture values and focal length values corresponding to the steel pile end face images, and performing trainingto obtain a steel number detection and size recognition neural network model by utilizing the plurality of steel pile end face images and the aperture values and focal length values of the cameras corresponding to the steel pile end face images; and shooting an end face image of the steel pile to be identified by using a camera, inputting the end face image of the steel pile to be identified and the aperture value and the focal length value of the corresponding camera into the model, and outputting the steel quantity and size information of the image by the model. Thus, the number, coordinatesand sizes of the steel in the steel pile can be rapidly obtained only by collecting the end face image of the steel pile and the aperture and focal length values of the camera through the camera, theefficiency and accuracy of steel counting and size recognition are effectively improved, and the labor cost and time cost are greatly reduced.

The present invention is an incremental umbrella sampling method to improve the performance of established sampling methods. It is sampling the state space by iteratively generating states xi,t and their weighting factors represented by Formula (a) by fitting the sampling distribution function ρj(x) of the next iteration to at least one weighted property of the already sampled states. This means that ρj(x) is fitted to the product represented by Formula (b), in which Formula (a) is the weighting factor and O(x,i) is a function respectively a property of the states xi,t. The number of states xi,t and the number of weighting factors (see Formula (a)) is incremented with each iteration. In order to have a consistent set of weighting factors (see Formula (a)), the weighting factors are recalculated in each iteration for all, respectively for a set of selected, states. By fitting ρj(x) in the state space it is possible to use all the information of Formula (a) and O(xi,t) for the states xi,t generated so far. The fitting step allows to use different fitting strategies. For example the fitting can bias the sampling away from areas where intensive sampling has been done in the preceding iterations, or the sampling can be directed along local gradients respectively towards local minima or maxima of one or several weighted properties. In each of the iterations, the sampling distribution function is fitted in a way to improve the overall sampling of the state space. The method supports multi-objective optimisations. State space integrals can be solved. It reduces the probability that the system is trapped. The invention is general. It can be used with different sampling methods, in particular with Monte Carlo sampling, Metropolis Monte Carlo sampling, or dynamic simulations. It can be combined with the concepts of simulated annealing and multicanonical sampling. It provides a general framework that can be adapted to the system and the observables of interest.

The invention discloses a pedestrian re-identification method based on an improved YOLOv3 network and feature fusion, and mainly solves the problems of low retrieval precision and low speed of specific pedestrians in a video monitoring scene in the prior art. According to the scheme, the method comprises the steps of 1) constructing a pedestrian picture data set; 2) establishing an improved YOLOv3network; 3) establishing a pedestrian re-identification network fusing global features and multi-scale local features; 4) training an improved YOLOv3 network and a pedestrian re-identification network by using the data set; 5) fusing the two networks trained in the step 2) and the step 3) to obtain a pedestrian re-identification system; and 6) inputting the monitoring video and the to-be-retrieved target pedestrian picture into a pedestrian re-identification system, retrieving the to-be-retrieved target pedestrian, and outputting a re-identification result of the target pedestrian. Accordingto the method, the sensitivity to pedestrians with different postures is enhanced, the retrieval speed and precision of pedestrian re-identification are improved, and the method can be used for regional security and protection, criminal investigation, video monitoring and behavior understanding.

The invention discloses a bearing fault detection method and device. The method comprises that a vibration signal of a bearing is obtained, and preprocessed to obtain a vibration sequential signal to be processed; the vibration sequential signal to be processed is input to a pre-trained fault classification model to obtain a fault classification result of the bearing vibration signal; and the type of highest probability among all the classification results is the detected fault type, and bearing fault detection is completed. According to the method, vibration signal values sampled continuously according to the time sequence is used as a training sample for convolutional neural network directly, a signal feature extraction step in traditional fault recognition is not needed, influence of feature extraction on accuracy of a fault identification result is reduced, parameter training is carried out the whole network in a monitored way by combining labels, and thus, accurate bearing fault detection is realized.

An MRI k-space data set is acquired using a series of shell k-space sampling trajectories of different radii. Off-resonance effects are reduced and fat-suppression can be improved by using a shorter TR for pulse sequences that sample at smaller radii. At larger radii sampling is repeated with the central axis of the shell sampling trajectory tilted such that the polar regions of shells acquired at the same radii are sampled by the other shell.

Attenuation correction in SPECT studies such as cardiac function imaging is carried out using an iterative statistically-based transmission projection reconstruction algorithm that is capable of modeling overlapping transmission beams from a line source array of radiation emitters. Downscatter between emission and transmission photons is additively corrected for in the algorithm. Optimal line source spacing techniques and source collimation angle selection are derived to improve performance and reduce cost.

The invention discloses a fabric defect detection method and device. The method comprises the following steps: acquiring a ResNet50 model; replacing a first classifier of the ResNet50 model with a second classifier; obtaining a characteristic value of the fabric defect sample image; extracting a weight parameter of the ResNet50 model as an initial value; carrying out transfer learning on the ResNet50 model according to the characteristic value and the initial value to obtain a plurality of defect category identification models; and detecting the to-be-detected fabric image according to the multiple defect category recognition models. According to the embodiment of the invention, the problem that defect image samples are extremely lacked is solved by adopting transfer learning; specifically, ResNet50 model parameters trained on a large image data set ImageNet are adopted as improved ResNet50 network initial parameters in the embodiment of the invention, and then a top convolutional network is continuously retrained in a fabric defect sample image set, so that the top convolutional network is more suitable for fabric defect detection.

The invention relates to a verifiable multi-party kmeans federated learning method witha privacy protection function, and belongs to the technical field of data mining. The data is horizontally distributed on multiple users, and each user encrypts and uploads the respective data to the cloud server; the cloud server randomly selects an initial centroid, and calculates the square of the Euclidean distance between the data and the initial centroid by using a secure multiplication protocol and a secure distance calculation protocol; the cloud server performs distance comparison by using a security bit decomposition protocol and a security comparison protocol, and divides the data; each user updates the clustering center by using a secret sharing protocol, encrypts the clustering center and uploads the clustering center to the cloud server; and the cloud server calculates the distance between the new clustering center and the original clustering center, if the distance is smaller than a threshold value, clustering operation is ended, and otherwise, the clustering center is updated for next iteration.

The invention discloses a new energy lithium battery surface defect detection method based on adaptive deep learning. The method comprises the following steps: carrying out nonlinear mapping on a lithium battery surface grayscale image; transforming the decoupled irradiation component and reflection component to a frequency domain; performing filtering, inverse Fourier transform and exponential transform on the frequency domain data to obtain a reconstructed lithium battery image; based on morphological processing and background differencing, enhancing gray scale response at the defect; carrying out image segmentation and connected domain analysis and screening processing, and taking a result as a labeled image; designing an operator to simulate illumination details, and carrying out sample enhancement operation on the surface grayscale image of the lithium battery; training a deep convolutional neural network based on the enhanced sample image set and the labeled image; and achievinglithium battery surface defect detection based on the trained network. By utilizing the method, the detection efficiency can be improved and the false detection rate can be reduced in a lithium battery surface defect detection scene.

The invention relates to the technical field of computed tomography (CT), and discloses a method and a device for acquiring data scanned by a flying focus CT machine. The method comprises the following steps of: scanning a detected body in a three-focus flying mode, and acquiring scanned data; performing circulation processing on the acquired flying scanned data by taking the number of each circulation period as a basic operation unit, and reconstructing projection view data; and interpolating the scanned data of different focuses during processing by each basic operation unit to obtain data of four projection views. By using the method and the device, the rotation time of a stander is relatively short; the data scanned by the CT machine can be easily sampled; and the resolution in each direction can be guaranteed.

A disposable electrochemical test sensor designed to facilitate sampling of fluid samples. It has a fluid chamber having a novel extra wide sampling entrance, but no additional air escape vent. The chamber provides a reservoir from which a sample fluid can be drawn into the chamber through capillary action. The extra wide sampling entrance provided by the present invention can draw blood into the chamber through any part of the opening, thus it allows easy targeting the samples with small volume, picking up smeared samples and it is more tolerant to users who jam the tip of the sensor into users' finger.

The present invention relates to disposable test sensors having improved sample application and measuring properties and their uses for detection, preferably, quantitative measurement, of analyte in a liquid sample like blood. In particular, the invention provides for an electrochemical biosensor which has a thin-layer fluid chamber having funnel-like shape with a novel extra wide opening as sampling entrance and a vent opening at the tip of the chamber for air escape. The thin-layer fluid chamber provides a reservoir from which a sample fluid can be drawn into it through capillary action. The extra wide sampling entrance provided by the present invention can draw blood into the chamber through any part of the opening, thus it allows easy targeting the samples with small volume, picking up smeared samples and it is more tolerant to users who jam the tip of the sensor into users' finger.

The invention designs a rotary type laser ceilometer for observing cloud amount. A fixed zenith angle is changed into a rotary transmitting and receiving system in a certain three-dimensional space angle, and clouds at different positions are sampled. The rotary type laser ceilometer can increase sampling on the clouds in the sky so as to improve the observation precision of the cloud amount; and one set of the laser ceilometer is utilized to realize the observation of two basic parameters including a cloud height and the cloud amount. The rotary type laser ceilometer comprises a laser transmitting system and a laser receiving system; the laser transmitting system comprises a laser device and a beam expander; the laser receiving system comprises a telescope, a convex lens, a narrow-band filtering sheet and a photomultiplier; the convex lens, the narrow-band filtering sheet and the photomultiplier are mounted in a lens cone of the telescope; the laser device and the beam expander are mounted on the outer wall of the lens cone of the telescope; the rotary type laser ceilometer further comprises a bottom bracket, a rotary shaft, a first motor and a second motor; the lens cone of the telescope is fixedly connected with the rotary shaft; the two ends of the rotary shaft are erected in the bottom bracket through a bearing seat; the rotary shaft is in transmission connection with the first motor and the first motor is mounted on the bottom bracket; and the bottom bracket is in transmission connection with the second motor.

The objective of the invention lies in providing a method and device for carrying out Doppler estimation in a high-speed mobile system, especially an LTE system or other systems based on the OFDM. Compared with the prior art, the method comprises the steps: respectively carrying out the channel estimation of signals of a plurality of pieces of equipment according to receiving signals from the plurality of pieces of equipment, so as to obtain channel estimation values of the plurality of pieces of equipment; and jointly carrying out the Doppler estimation of the plurality of pieces of equipment based on a normalized post-processing / pre-processing method according to the channel estimation values. The method greatly enlarges a training signal sample, and can improve the accuracy of parameter estimation through a classical theory. Meanwhile, the method meets the demands for a shorter period. A combined Doppler estimation algorithm can improve the performance of the high-speed mobile system, and has no loss. The method can increase the number of pieces of access UE of one cell. The method saves the transmission power of a single piece of user equipment, and prolongs the service life of the user equipment.

A detection device includes a carrying unit, at least a reaction unit, a wire transporting unit, and a guiding unit. The carrying unit includes at least a hole, and the reaction unit is disposed on one side of the hole. The reaction unit includes at least a reaction area, which includes a hydrophilic material containing a detection reagent. The wire transporting unit is disposed on the other side of the hole and includes a sampling end and a transporting end. The guiding unit is in contact with the reaction unit and the transporting end. The guiding unit collects a test sample through the transporting end and provides at least a part of the test sample to react with the detection reagent. The detection device adopts the wire transporting unit to replace the pipette for collecting the test sample without directly contacting the detection area with the sample source.

A scaling device for an image processor includes an image enlarging device and an integer divider. The image enlarging device receives an input image data, and enlarges the input image data, outputting an enlarging image data and a sample signal. The integer divider receives the enlarging image data, and samples the enlarging image data, outputting an object image data. By only adding an external integer divider at the output of the image enlarging device for obtain the scaling function of the image processor, a simpler circuit for image scaling is presented.

A disposable electrochemical test sensor designed to facilitate sampling of fluid samples. It has a fluid chamber having a novel extra wide sampling entrance, but no additional air escape vent. The chamber provides a reservoir from which a sample fluid can be drawn into the chamber through capillary action. The sampling entrance provided can draw fluid into the chamber through any part of the opening, allowing easy targeting the samples with small volume, picking up smeared samples, and added tolerance to users who jam the tip of the sensor into users' finger. The sampling entrance also serves as air escape vent. Such one opening sensor alleviates over-flow issue often encountered in convenient sensors.

The invention relates to the technical field of agricultural production, and particularly discloses a large greenhouse PD control system and method based on a neural network, and the system comprises an acquisition terminal which comprises a data acquisition control module and a plurality of sensor groups arranged in a greenhouse; the data acquisition control module is used for controlling the sensor group to acquire the internal environment information of the greenhouse in different time sequences; the user terminal is used for sending crop information of crops planted in the greenhouse to the server; an error feedback module is used for calculating an error feedback value according to the expected environment information and the internal environment information; a control parameter analysis module is used for performing control parameter analysis on the environment information and the expected environment information through a preset control parameter analysis model to obtain control parameters, and the control parameters comprise adjustment parameters of illumination intensity, temperature and humidity; and a PD control module is used for performing PD control on the environment adjusting equipment according to the control parameters and the error feedback values. By adopting the technical scheme of the invention, the time for controlling and adjusting the PD is shortened.

A disposable electrochemical test sensor designed to facilitate sampling of fluid samples. It has a fluid chamber having a novel extra wide sampling entrance, but no additional air escape vent. The chamber provides a reservoir from which a sample fluid can be drawn into the chamber through capillary action. The sampling entrance provided can draw fluid into the chamber through any part of the opening, allowing easy targeting the samples with small volume, picking up smeared samples, and added tolerance to users who jam the tip of the sensor into users' finger. The sampling entrance also serves as air escape vent. Such one opening sensor alleviates over-flow issue often encountered in convenient sensors.

The present disclosure discloses a voice remote controller and a power supplying method thereof. The voice remote controller comprises: a noise gathering module for gathering ambient noise at the periphery of the voice remote controller by using a sound aperture array; a sound-electricity converting module for converting the ambient noise gathered by the noise gathering module into an electrical signal; and an energy storing module for storing the electrical signal converted by the sound-electricity converting module as electric energy and supplying power to the voice remote controller. According to the present disclosure, ambient noise is gathered by a sound aperture array and converted into electricity used as the working energy, thereby avoiding battery replacing or frequent charging. When a voice function of a voice remote controller is turned off, all of the gathered ambient noise is converted into electricity, thereby improving the energy utilization rate. By adjusting the number of opened sound apertures in the sound aperture array and changing the noise gathering angle, ambient noise can be separated from a voice signal of the user, and by inverting a noise waveform and superimposing the same onto the voice signal, ambient noise in the voice signal can be filtered out, thereby reducing the negative effects of ambient noise on the voice remote controller.

A method and a data-transmission system for transmitting data encoded in a signal between a transmitting user and a receiving user of the data-transmission system via a network structure of the data-transmission system. The data encoded in the signal are serially transmitted bit-by-bit in data frames having a defined structure. Each bit of the data encoded in the signal is sampled in the receiving user. Due to the transmission via the network structure, the signal is delayed asymmetrically. To compensate for the asymmetrical delay on the physical layer in the transmission channel, it is provided that the asymmetrical delay of the signal is determined at at least one point in the network structure, and is at least partially compensated prior to the receiving user sampling the bits of the data encoded in the signal. A measuring and compensating device is provided to measure and compensate for the asymmetrical delay.

Apparatuses and methods for biopsying body vessels having small lumen, such as Fallopian tubes. In particular, described herein are apparatuses (e.g., systems and devices) and methods that evert a textile biopsying member to sample tissue from a vessel or conduit such as the fallopian tubes without applying substantial shear force.