627results about How to "Increase sample size" patented technology

A sound measuring apparatus for measuring a sound-arrival delay time from a speaker to a microphone on the basis of a result obtained by outputting a test signal from the speaker and picking up the test signal using the microphone includes the following elements. A control unit performs control so that the test signal is expanded in a time axis and is then output from the speaker. A delay time measuring unit measures an expansion-based measured delay time on the basis of a delay time that is measured on the basis of a time difference between the test signal expanded in the time axis and output from the speaker and a signal obtained from the microphone by picking up the output expanded test signal, and obtains the sound-arrival delay time as the expansion-based measured delay time.

The present invention is in the field of oral, abuse resistant pharmaceutical compositions of opioid agonists, extended release pharmaceutical compositions of opioid agonists and extended release abuse resistant pharmaceutical compositions of opioid agonists and the use thereof. The present invention is also directed to extended release pharmaceutical compositions and the use thereof for preventing or minimizing the risk of abuse and / or toxicity from either intentional or unintentional tampering. The present invention is further directed at a method of preventing or minimizing the risk of abuse and / or toxicity from either intentional or unintentional tampering.

A sound measuring apparatus for measuring a sound-arrival delay time from a speaker to a microphone on the basis of a result obtained by outputting a test signal from the speaker and picking up the test signal using the microphone includes the following elements. A control unit performs control so that the test signal is expanded in a time axis and is then output from the speaker. A delay time measuring unit measures an expansion-based measured delay time on the basis of a delay time that is measured on the basis of a time difference between the test signal expanded in the time axis and output from the speaker and a signal obtained from the microphone by picking up the output expanded test signal, and obtains the sound-arrival delay time as the expansion-based measured delay time.

The present invention is in the field of oral, abuse resistant pharmaceutical compositions of opioids, extended release pharmaceutical compositions of opioids and extended release abuse resistant pharmaceutical compositions of opioids and the use thereof for the treatment of pain. The present invention is also directed to extended release pharmaceutical compositions and the use thereof for preventing or minimizing the risk of opioid abuse and / or opioid toxicity from either intentional or unintentional tampering. The present invention is further directed at a method of preventing or minimizing the risk of opioid abuse and / or opioid toxicity from either intentional or unintentional tampering.

The invention discloses a method for obtaining a resident travel characteristic parameter based on mobile phone positioning data. The method comprises the following steps of: (1) collecting mobile phone positioning data; (2) filtering the mobile phone positioning data, matching the mobile phone positioning data to traffic zones, and obtaining the matched mobile phone positioning data; (3) using users as units, ordering the matched mobile phone positioning data in one day by time, merging the continuous data in the same one traffic zone into one piece, and obtaining mobile phone positioning pretreatment data; (4) according to the number of emerged pieces and influence duration, judging residing points, restoring a travel path between two residing points, and obtaining the travel distance and the travel speed, and then obtaining a travel log table of all users; (5) on the basis of the matched mobile phone positioning data, statistically obtaining a place of residence and workplace result table; and (6) and conjointly analyzing the travel log table and the place of residence and workplace result table, and obtaining resident travel characteristic parameters. The method has the characteristics of low cost, large sample quantity, high precision and high time validity.

The invention relates to a bidirectionally isolating type series resonance DC / DC converter (100) which comprises voltage-stabilizing capacitors (22, 32), high-frequency converters (20, 50), series resonance circuits (30, 40), a high-frequency transformer (28) and an energy storage unit (60), wherein the voltage-stabilizing capacitors (22, 32) are used for enhancing the stability of a DC voltage; the high-frequency converters (20, 50) have the same structure and comprise four switching elements inversely connected in parallel with a rapid diode and can be used for inversion and rectification; the series resonance circuits are used for converting three kinds of discrete levels output by corresponding high-frequency converters into sinusoidal waveforms and can be used for softly switching the switching elements of the corresponding high-frequency converters, at the same time, only one series resonance circuit (30 or 40) acts; and the high-frequency transformer (28) can be used for isolation and transformation. The transformer (100) can be used for greatly converting the DC voltage, has high efficiency, and can be applied to an electric vehicle power supply, standby power supplies of large-scale equipment, and the like.

Systems and methods are provided for selecting survey questions and response for inclusion in a survey using a survey software application. Survey questions may be selected based on the response variance or inclusion value of each survey question. A non-inclusive list of survey responses may be selected based on the selection rate of each survey response. The response rates may be adjusted to correct for instances where survey participants selected a response indicating that none of the provided responses was adequate because a hidden response was not provided. Selected survey questions and responses may be provided to a survey participant.

The present invention relates to an electronic camera which images an object image and records image data. Particularly, the present invention relates to technology to record image data in a good shooting state, such as with little blurring due to hand shaking. The invention has an image pick-up means 1 which continuously images an object, a temporary memory means 2 which temporarily stores a plurality of frames of image data which are continuously imaged by the image pick-up means 1, a shooting evaluation means 3 which evaluates a good or bad shooting state of the image data imaged by the image pick-up means 1, a still image selection means 4 which selects the image data with the highest evaluation of the shooting evaluation means 3 among the image data which are stored in the temporary memory means 2, and an image saving means 5 which saves the image data which is selected by the still image selection means 4.

A high aspect ratio biopsy needle achieves reliable performance with large solid sample size by means of a variety of features and combinations thereof, including support to prevent bending, reinforcement of the needle, and cutting edges arranged to resist deformation.

A high aspect ratio biopsy needle achieves reliable performance with large solid sample size by means of a variety of features and combinations thereof, including support to prevent bending, reinforcement of the needle, and cutting edges arranged to resist deformation.

The invention relates to a multi-channel portable colloidal gold test paper strip quick test device, which mainly comprises a detector, wherein the detector comprises a detecting part, an electrical part and a software detecting part; the detecting part comprises a plurality of mutually independent detecting channels; the electrical part comprises an ARM data processor, a keyboard and an LCD; image data detected by the detecting part are processed and displayed by the electrical part; and the software detecting part controls detecting steps. The device has a multi-channel detecting structure, and four channels can carry out the same detection item as well as different detection items. The device has the advantages of high detection speed, large amount of samples and great practical value.

The invention discloses a face multi-area fusion expression recognition method based on depth learning, which comprises the following steps of detecting a face position with a detection model; obtaining the coordinates of the key points by using the key point model; aligning the eyes according to the key points of the eyes, then aligning the face according to the coordinates of the key points of the whole face, and clipping the face region by affine transformation; cutting the eye and mouth areas of the image to a certain proportion; dividing the convolution neural network into one backbone network and two branch networks; carrying out the feature fusion in the last convolution layer, and finally obtaining the expression classification results by the classifier. The method of the inventionutilizes the priori information, besides the whole face, the eyes and mouth regions are also used as the input of the network, and the network can learn the whole semantic features of facial expressions and the local features of facial expressions through model fusion, so that the method simplifies the difficulty of facial expression recognition, reduces the external noise, and has strong robustness, high accuracy, low complexity of the algorithm and so on.

The invention provides a public transport card passenger commuter OD (origin and destination) distribution estimation method based on APTS (advanced public transportation systems). The method includes collecting APTS data, obtaining station information where public transport passengers getting on according to association between public transport IC (intelligent card) data and intelligent scheduling system data, judging public transport commuters according to travel frequency of morning and evening peaks, and determining places of residence and places of work according to time and space characteristics of commuter traveling. The public transport card passenger commuter OD distribution estimation method has the advantages of high accuracy and strong operability, a novel manner for obtaining public transport commuter OD distribution rapidly and economically is provided, ratio of the commuters traveling by public transport can be increased, and the urban traffic congestion problem can be relived effectively.

The present invention is directed at methods for preventing or minimizing the intensity of the serotonin syndrome in humans and lower animals which comprises administering proserotonergic agents and serotonin surge protectors. The present invention is also directed to pharmaceutical compositions comprising proserotonergic agents and serotonin surge protectors useful for carrying out the method of the present invention.

The invention discloses a tree species identification method based on transfer learning, comprising the following steps: S1, collecting tree images and making tree species image data sets; S2, data enhancement is performed on the original data set image to expand the number of pictures; S3, acquiring more than one pre-training model based on convolution neural network trained on large image dataset, S4, training the pre-training model with tree species image dataset, optimizing one or several full connection layers of the pre-training model in the training process, thereby training a pluralityof classifiers based on convolution neural network; Test the accuracy of each classifier and select the classifier with the highest accuracy. S5 performs tree species identification using the classifier selected in step S4, thereby obtaining an identification result. The invention recognizes tree species based on the transfer learning mode, so that a model with good generalization ability can betrained under the condition of limited sample size of tree species, and the tree species recognition rate under the complex background is greatly improved.

The invention discloses a double-label joint sequence for detection of tumor mutation, and is characterized in that the joint sequence is synthesized by a joint primer P5 and a joint primer P7, wherein the joint primer P5 has the sequence shown in SEQ ID NO:1, and the joint primer P7 has the sequence shown in SEQ ID NO:2. The invention also provides a database building method and a sequencing method. With use of a double-label joint, the tumor mutation rate of 1*10<-5> can be accurately detected, the tumor mutation detection sensitivity is effectively improved, and with combination of the flux of high-flux sequencing, one-time sequencing can detect multiple mutation loci of multiple genes.

Methods of characterizing a nucleic acid library by digital assay.

A method for inferring the photoelectric absorption of a formation by directly mapping spectroscopic measurements of gamma rays induced in the formation using a fast neutron source. The mapping is accomplished by creating a polynomial function based on counts of gamma-ray events in the gamma-ray energy spectrum; the coefficients of the polynomial function are determined in known calibration environments, and the value of the polynomial is the inferred photoelectric absorption parameter. The spectroscopic measurements are preferably generated by sorting gamma-ray counts of the gamma-ray spectrum into a plurality of energy-dependent channels, and measuring these gamma-ray energy distributions during different portions of the firing cycle where different types of dominant gamma-ray production reactions occur.

The invention provides an automatic micro-expression identification method of a macro-to-micro conversion model based on depth learning. The method comprises steps that A, micro-expression sample processing, 1), a micro-expression data set sample and a macro-expression data set sample are pre-processed; 2), sample pairs of a cross-modal tuple loss function are constructed; B, cross-modal macro-to-micro conversion model training, 3), the AU detection network is trained, an AU detection network parameter is initialized, and a flexible maximum value loss function is trained; 4), the AU detection network parameter is fixed, a cross-modal macro-to-micro conversion model parameter is initialized, and the cross-modal macro-to-micro conversion model is trained; and C, micro-expression identification, according to a trained convolutional neural network model, a test parameter is initialized, a test sample is inputted to the trained convolutional neural network model, and an identification rate is outputted after forward network propagation. The method is advantaged in that robustness is realized compared with methods in the prior art.

The invention discloses a weak supervised text classification method and device based on active learning. The method comprises steps of firstly, extracting a first sample serving as a cluster center of a sample cluster from an unlabeled sample set; forming an initial training set based on the first samples, training a reference model by using the initial training set to obtain an initial classification model, and forming the initial training set by using the first samples, thereby not only reducing the number of training samples, but also ensuring the accuracy of the classification model at the initial stage; repeatedly utilizing the classification model to obtain the initial classification and confidence coefficient of the remaining samples in the sample set, so that manual labeling is not needed; extracting a second sample from the remaining samples according to the confidence coefficient, and performing data enhancement processing on the second sample to update the training set, thereby improving the generalization capability and robustness of the model; and finally, training the classification model by using the updated target training set until the classification model meets apreset condition, thereby realizing multi-round active training of the classification model.

The invention relates to an internet-based intelligent planting device, system and method. The internet-based intelligent planting device comprises a base, a display / operation module, a transparent cover, a planting basin, an integration control system, a camera and an environment sensor. The integration control system is arranged in the base. The display / operation module is arranged outside the base and connected with the integration control system. The planting base is arranged on the base. The transparent cover is arranged on the base. The base is provided with a support to be used for mounting the camera and the environment sensor. The camera and the environment sensor are arranged on the support in a pluggable mode. A data line is hidden in the support and connected with the integration control system in the base. By means of the internet-based intelligent planting device, system and method, the mass growers are helped in knowing the plant information to plant healthy plants, professional plant research personnel can be helped in obtaining the plant samples through the internet, analysis and research are facilitated, data support is provided, the planting environment is improved, and the planting efficiency is improved.

In an embodiment of the present invention, a modified version of the PHASE model is implemented that is substantially more accurate than the FastPHASE model. Modifications in an embodiment of the present invention include using a parameterization EM algorithm similar to that of the FastPHASE model, and to perform optimization on haplotypes rather than MCMC sampling. In an embodiment, the imputed haplotypes themselves are used as hidden states in the HMM because this is believed to be important for the PHASE model's accuracy. This increase in accuracy becomes more pronounced with increasing sample size. This difference is attributed to the PHASE model's likelihood which produces long, shared haplotypes between pairs of individuals.

Systems and techniques for intra-block copy (IBC) prediction in processing video data include the use of one or more virtual search areas (VSAs) which can be generated to include one or more references to one or more pixels stored in a physical memory. The one or more VSAs can provide references to additional reconstructed sample values that are derived from previously decoded blocks without incurring physical memory use for storage of the additional reconstructed samples. A search area for performing the IBC prediction for a current block of the video data can be extended to include the one or more VSAs. Extending the search area to include the one or more VSAs provides the IBC prediction with additional search area for finding one or more prediction blocks or prediction samples without having to utilize physical memory to store the additional reconstructed samples from previously decoded blocks.

The present invention relates to an electronic camera which images an object image and records image data. Particularly, the present invention relates to technology to record image data in a good shooting state, such as with little blurring due to hand shaking. The invention has an image pick-up means 1 which continuously images an object, a temporary memory means 2 which temporarily stores a plurality of frames of image data which are continuously imaged by the image pick-up means 1, a shooting evaluation means 3 which evaluates a good or bad shooting state of the image data imaged by the image pick-up means 1, a still image selection means 4 which selects the image data with the highest evaluation of the shooting evaluation means 3 among the image data which are stored in the temporary memory means 2, and an image saving means 5 which saves the image data which is selected by the still image selection means 4.

The invention relates to a binocular depth estimation method based on a depth neural network, which comprises the following steps: 1) preprocessing the input left and right viewpoint images to enhancedata; 2) constructing a multi-scale network model for binocular depth estimation, wherein the model comprises a plurality of convolution layers, an activation layer, a residual connection, a multi-scale pooling connection and a linear upsampling layer; 3) Designing the loss function to minimize the results in the continuous training process, so as to obtain the optimal network weights; 4) inputting the image to be processed into the network model to obtain the corresponding depth map, and repeatedly repeating the above steps until the network converges or reaches the training times. The invention adopts the idea of unsupervised learning, and only the left and right viewpoint images obtained by the binocular camera are used as network input. The adaptive design of the network sets the internal and external parameters of the camera as a single model parameter, so it can be applied to multiple camera systems without modifying the network.

The present disclosure presents a unified system to phase a personal genome for downstream clinical interpretation. In an embodiment, an initial phasing is generated using public datasets, such as haplotypes from the 1000 Genomes Project, and a phasing toolkit. A local perturbation algorithm is applied to improve long range phasing. If available, a Mendelian inheritance pipeline is applied to identify phasing of novel and rare variants. These datasets are merged, followed by correction by any experimental data. This allows for full clinical interpretation of the role of a group of variants in a gene, whether inherited or de novo variants.

The invention discloses an aircraft structure safe life determining method based on testing and serving use data fusion. The aircraft structure safe life determining method includes an air fleet safe life determining method when testing fatigue life data and serving use fatigue life data of same-type aircrafts under different load spectrums are in lognormal distribution, and an air fleet safe life determining method of the same-type aircrafts under the same testing load spectrum. The air fleet safe life determining method when the testing fatigue life data and the serving use fatigue life data of the same-type aircrafts under the different load spectrums are in lognormal distribution includes the steps of obtaining the fatigue life data of any right truncation tail of each aircraft structure, calculating fatigue life distribution function parameters of the aircraft structures, and calculating the fatigue life dispersion coefficients and the safe life of an aircraft air fleet. The air fleet safe life determining method of the same-type aircrafts under the same testing load spectrum includes the steps of calculating fatigue damage values, equivalent flight hours or rising and falling times of the serving aircraft structures, obtaining the fatigue life data of any right truncation tail of each aircraft structure, calculating fatigue life distribution function parameters of the aircraft structures, and calculating the fatigue dispersion coefficients and the safe life of the aircraft air fleet.

Relating to the technical field of intelligent traffic, the invention provides a method and system for time-delay path planning. The method includes: acquiring the personalized information recorded by each client in real time; converting the personalized information recorded by each client into semantic information, and extracting mobile pre-judgement information of users according to the semantic information; forecasting the traffic information of each road section in each period of time according to the mobile pre-judgement information of all the users; planning an initial path to a destination in a specific period of time by a current client according to the traffic information of each road section in each period of time and the individualized information of itself; and in the driving process, adjusting the initial path in real time according to the traffic information obtained by continuous forecast. The method and the system provided by the invention has the characteristics of large data sample size, wide data range and data timeliness, can reduce the prediction result deviation, and can more comprehensively, more accurately and more timely forecast the driving road section with good traffic conditions within certain period of time in the future for users, thus enhancing the accuracy of path forecast and adjustment.

A technique for assessing the viability of several concepts for new / different products, services, or bundles of products and / or services, using discrete choice modeling, or a combination of discrete choice modeling and monadic concept testing. The core of the invention involves one or more of the following: a methodological technique for combining monadic and discrete choice data, a method for gathering monadic and discrete choice data at the same time during a single fielding, a method for gathering specific diagnostic information, a method for using discrete choice modeling to generate specific diagnostic information, a unique web-enabled interface that helps individuals make quick and accurate choices by displaying concepts at low and high resolution at the same time, a unique web-enabled interface that permits gathering choice data on multiple dimensions for each set of concepts shown, methodological innovations permitting hierarchical and / or Bayesian analysis of discrete choice data using data for multiple dimensions within the same model, and methods and apparatus for storing, organizing, and reporting input and output from this system.