52 results about "Sequence reconstruction" patented technology

Exemplary embodiments provide methods and systems for diploid genome assembly and haplotype sequence reconstruction. Aspects of the exemplary embodiment include generating a fused assembly graph from reads of both haplotypes, the fused assembly graph including identified primary contigs and associated contigs; generating haplotype-specific assembly graphs using phased reads and haplotype aware overlapping of the phased reads; merging the fused assembly graph and haplotype-specific assembly graphs to generate a merged assembly haplotype graph; removing cross-phasing edges from the merged assembly haplotype graph to generate a final haplotype-resolved assembly graph; and reconstructing haplotype-specific contigs from the final haplotype-resolved assembly graph resulting in haplotype-specific contigs.

The invention discloses a training sequence reconstruction-based channel estimation method and a training sequence reconstruction-based channel estimation system. The method comprises the following steps: acquiring a known channel estimation result; according to the known channel estimation result, constructing linear convolution of former frame transmitted data and a channel and the linear convolution of a transmitted training sequence and a channel impulse response; eliminating inter-block interference of data on a training sequence; obtaining a cyclic convolution, of the training sequence and the channel impulse response, serving as a reconstruction item; according to the reconstruction item, reconstructing the training sequence; and performing channel estimation by utilizing the reconstructed training sequence, and updating a channel estimation result. The method and the system of the invention can ensure that a TDS-OFDM system can also obtain relatively accurate channel estimation when maximum delay extension of the channel exceeds the guard space length of the training sequence, simultaneously improves the accuracy of the channel estimation and improves the spectrum utilization ratio and the mobility performance of the system.

The invention discloses a method for synchronously reconstructing a dynamic PET image and a tracer kinetic parameter on the basis of TV (total variation) and sparse constraint. The method introduces a dictionary based on sparse constraint and a TV operator to carry out a whole reconstruction process by establishing a mathematic model for synchronously estimating the dynamic PET image and the kinetic parameter, wherein a dynamic PET sequence reconstruction subproblem provided with the total variation operator is subjected to iterative optimization solution by an ADMM algorithm, and a PET kinetic parameter estimation subproblem in combination with the dictionary based on sparse constraint is solved by a soft threshold iterative algorithm. The method solves a problem for simultaneously estimating the dynamic PET image sequence and the kinetic parameter, introduces the TV operator to improve the low result resolution and noise interference proneness in the PET image reconstruction process, and may obtain a better reconstruction result compared with other algorithms which individually reconstructs the PET image or estimates the kinetic parameter.

Methods and systems for determining a sequence of energy interactions in a detector. A plurality of discrete energy interactions is received in a plurality of detector voxels. A plurality of possible sequences of interaction is formed based on the received plurality of discrete energy interactions. For each of the plurality of possible sequences of interaction, an a posteriori probability is computed, where the a posteriori probability is based on a likelihood that the possible sequence of interaction is consistent with the received plurality of discrete energy interactions. Additionally or alternatively, the a posteriori probability may be based on an a priori probability. One of the formed plurality of possible sequences of interaction is selected based on the computed a posteriori probability.

A system and method for generating separations between jobs in a batch of scanned pages are provided. The method includes, for each of a set of jobs, capturing an image of a representative page of the job. Thereafter, the method includes scanning the set of jobs as a batch to generate a set of scanned pages. The captured images are compared with scanned pages in the set of scanned pages to identify, for at least one captured image, a respective scanned page which matches the captured image. At least one separator is generated for separating the set of scanned pages based on a location of the matching scanned page(s).

The invention relates to a construction method and system of a pipeline three-dimensional model, and a medium. The method comprises the following steps: obtaining an initial point cloud data sequenceof the inner wall of a target pipeline, carrying out the denoising and pipeline center correction of the initial point cloud data sequence, and obtaining a target point cloud data sequence; and performing three-dimensional network construction according to the target point cloud data sequence by adopting a preset gridding reconstruction method to obtain a target pipeline three-dimensional model. Various corrections can be carried out on the directly collected initial point cloud data sequence of the inner wall of the pipeline, the defects in original data are overcome, the accurate three-dimensional model of the pipeline is reconstructed according to the corrected target point cloud data sequence, three-dimensional visualization of the pipeline is achieved, the accuracy is high, the modeling efficiency is higher, and the cost is lower.

A method of reconstructing a damaged sequence of symbols where some symbols are missing is provided in which statistical parameters of the sequence are used with confidence windowing techniques to quickly and efficiently reconstruct the damaged sequence to its original form. Confidence windowing techniques are provided that are equivalent to generalized hidden semi-Markov models but which are more easily used to determine the most likely missing symbol at a given point in the damaged sequence being reconstructed. The method can be used to reconstruct communications consisting of speech, music, digital transmission symbols and others having a bounded symbol set which can be described by statistical behaviors in the symbol stream.

The invention discloses an infrared gesture recognition method and apparatus based on region sequence reconstruction. The method comprises the steps of establishing a coordinate system, normalizing distances between at least four arranged infrared distance measuring sensors and the X axis and the Y axis, and determining coordinates of each sensor; measuring the distance between a hand of a user and each infrared distance measuring sensor when the hand of the user is detected to enter in effective ranges of the infrared distance measuring sensors; calculating coordinates of the hand of the user; and determining the quadrant where the hand of the user is located according to the coordinates of the hand of the user, and recognizing the gesture type of the user according to variation of the quadrant. According to the infrared gesture recognition method and apparatus based on region sequence reconstruction, three-dimensional motion coordinates of the gesture can be reproduced according to arrangement relationship of the infrared sensor array and infrared distance measuring values, the regions through which the gesture passes are determined to recognize the gesture motion, the regions are determined without being influenced by abnormity of individual points, anti-interference capability is high, and recognition rate is high.

The invention discloses an FPGA (Field Programmable Gate Array)-based spike potential signal parallel detection device and a method. The device comprises parallel modules, wherein each module comprises a signal receiver, a signal decomposition / reconfiguration device, a coefficient buffer, a coefficient processor, a signal detector and a signal output device. The method comprises the following steps of: receiving a signal sequence to be detected, and decomposing the signal sequence to be detected to obtain a decomposed coefficient sequence; and processing the decomposed coefficient sequence, carrying out signal sequence reconstruction to the processed coefficient sequence, detecting the reconstructed signal sequence to obtain a spike potential signal, and outputting the spike potential signal. According to the invention, the signal processing speed is improved by realizing the operation mode of the pipeline processing of the signal decomposition / reconstruction, and the multi-channel parallel detection is realized by a modularized design of the FPGA-based single-channel spike potential signal parallel detection device, so that the processing efficiency of a system is improved.

The invention relates to an enterprise carbon emission prediction method and device, computer equipment and a storage medium. The method comprises the following steps: obtaining to-be-analyzed data, wherein the to-be-analyzed data comprises at least one of a per capita domestic total production value, energy intensity, an added value of an industry to which a target enterprise belongs, total energy consumption of the industry to which the target enterprise belongs, main business income of the target enterprise, revenue profit of the target enterprise and power consumption of the target enterprise; performing empirical mode decomposition on the to-be-analyzed data to obtain a plurality of subsequences with different frequencies and a residual component sequence; inputting a plurality of sequences formed by the subsequences and the residual component sequence into a carbon emission prediction model to obtain sequence prediction results corresponding to the sequences; and performing sequence reconstruction on each obtained sequence prediction result to obtain a reconstruction result, and determining an enterprise carbon emission prediction result corresponding to the target enterprise based on the reconstruction result. By adopting the method, the carbon emission prediction precision can be improved.

The invention relates to the technical field of radio long wave communication technology, and specifically relates to an extremely-ultra low frequency channel atmosphere noise suppression method based on variance median filtering. The extremely-ultra low frequency channel atmosphere noise suppression method based on variance median filtering includes the steps: constructing a multi-reference magnetic vector sensing system, synchronously receiving extremely-ultra low frequency signals through multi channels, and obtaining a magnetic induction output sampling point matrix X; according to the channel sampling point sequence, grouping X, estimating the variance of each group, and obtaining the variance matrix D; based on a large number decision criterion, performing pulse detection and two-stage adaptive median filtering on D; according to output of the second stage median filtering and input of the first stage median filtering, performing sequence reconstruction, and obtaining an output matrix Y; and performing power frequency harmonic interference and remaining atmosphere noise suppression on Y. As the extremely-ultra low frequency channel atmosphere noise suppression method based on variance median filtering taking the variance of the sampling point group as input of the adaptive median filter, the impulsiveness is improved. As the extremely-ultra low frequency channel atmosphere noise suppression method based on variance median filtering determines the pulse state of each element of the variance matrix based on the large number decision criterion, the pulse detection accuracy is improved and the defect that the performance is low when the median filtering is in the local high density pulse noise condition in the traditional method.

A system and method for generating separations between jobs in a batch of scanned pages are provided. The method includes, for each of a set of jobs, capturing an image of a representative page of the job. Thereafter, the method includes scanning the set of jobs as a batch to generate a set of scanned pages. The captured images are compared with scanned pages in the set of scanned pages to identify, for at least one captured image, a respective scanned page which matches the captured image. At least one separator is generated for separating the set of scanned pages based on a location of the matching scanned page(s).

The invention discloses a speech emotion recognition method based on time slicing. The method comprises a first step of speech equal length complementing: setting the maximum time length of a sound and performing time complementing of a read-in speech signal by white noise; a second step of speech signal slicing: slicing the speech signal obtained in the first step, that is, performing the time equal length slicing and speech envelope unit slicing, and the like; a third step of speech segment time-frequency analysis by using a time-frequency analysis tool; a fourth step of sequence reconstruction; a fifth step of emotion marking; a sixth step of image feature extraction; a seventh step of emotion training; an eighth step of speech emotion recognition: obtaining an emotion feature set by using the first to sixth steps for the newly input speech signal, inputting the emotion feature set into an emotion classification model obtained in the seventh step, and finally obtaining the emotion type of the current speech. The method adopts the time slice convolution and deep learning for the speech emotion classification, and well improves the recognition efficiency.

The invention discloses a PN sequence reconstruction-based frequency offset estimation method, which comprises the following steps: reconstructing the received PN sequence with length of N, forming a new PN sequence; utilizing frequency offset information in the formed new PN sequence to obtain a frequency offset rough estimation value, finishing the rough estimation process of frequency offset; compensating the frequency offset rough estimation value to the originally received PN sequence with length of N to calculate a fine frequency offset estimation value, and obtaining the final frequency offset estimation value. By reconstructing the PN sequence, the estimation precision of the frequency offset estimation method is improved by obtaining average value of a plurality of estimation values and performing rough and fine estimation processes.

The invention discloses an adaptive channel modeling method and system for enhancing a conditional generative adversarial network, and the method comprises the following steps: S1, initializing a generative adversarial network model, and obtaining a channel sample sequence; s2, a potential variable method is set through priori knowledge, and a potential variable sequence is obtained; s3, obtaining a reconstructed sample sequence meeting neural network processing requirements through a complex sequence reconstruction method; s4, obtaining a penalty sample sequence through a penalty sample construction method; s5, obtaining an input sequence and a generative adversarial network objective function through an enhancement condition generative adversarial network error function optimization method; and S6, performing network adversarial training, and outputting a generator model capable of simulating real channel data distribution. According to the method, the improved generative adversarial network is selected to accurately capture random channel behaviors, and self-adaptive channel modeling without manually assuming a physical model is realized.

Methods and systems for determining a sequence of energy interactions in a detector. A plurality of discrete energy interactions is received in a plurality of detector voxels. A plurality of possible sequences of interaction is formed based on the received plurality of discrete energy interactions. For each of the plurality of possible sequences of interaction, an a posteriori probability is computed, where the a posteriori probability is based on a likelihood that the possible sequence of interaction is consistent with the received plurality of discrete energy interactions. Additionally or alternatively, the a posteriori probability may be based on an a priori probability. One of the formed plurality of possible sequences of interaction is selected based on the computed a posteriori probability.

Exemplary embodiments provide methods and systems for diploid genome assembly and haplotype sequence reconstruction. Aspects of the exemplary embodiment include generating a fused assembly graph fromreads of both haplotypes, the fused assembly graph including identified primary contigs and associated contigs; generating haplotype-specific assembly graphs using phased reads and haplotype aware overlapping of the phased reads; merging the fused assembly graph and haplotype- specific assembly graphs to generate a merged assembly haplotype graph; removing cross-phasing edges from the merged assembly haplotype graph to generate a final haplotype-resolved assembly graph; and reconstructing haplotype-specific contigs from the final haplotype-resolved assembly graph resulting in haplotype-specific contigs.

The invention discloses a three-dimensional facial expression migration method and system, and the method comprises the steps: obtaining a current three-dimensional facial model of a controller, and obtaining a current three-dimensional facial model of a controlled person; performing feature extraction on the current three-dimensional face model of the controller to obtain a source basic expression model sequence; performing feature extraction on the current three-dimensional face model of the controlled person to obtain a target basic expression model sequence and a target model detail feature vector; mapping the source basic expression model sequence to a low dimension by using a source sequence mapping function to obtain a low-dimension source basic expression model sequence; transmitting the low-dimensional source basic expression model sequence to a target basic expression model sequence by utilizing a target sequence reconstruction function to obtain a target model with a sourceexpression; and performing detail recovery on the target model with the source expression by utilizing the detail feature vector of the target model.

The invention provides a continuous brain slice image three-dimensional registration method based on shape constraint, and relates to the technical field of image registration. The method comprises the following steps: S1, aligning a to-be-registered two-dimensional brain image sequence to obtain a two-dimensional alignment sequence, and reconstructing the two-dimensional alignment sequence into an initial three-dimensional body; S2, linearly registering the standard brain atlas to the initial three-dimensional body to obtain a reference brain atlas, registering pictures of the two-dimensionalalignment sequence to tangent planes of corresponding positions in the reference brain atlas one by one to obtain a two-dimensional correction sequence, and reconstructing a corrected three-dimensional body; and S3, obtaining reverse deformation parameters of each pixel point in the corrected three-dimensional body, and performing spatial offset adjustment on the corrected three-dimensional bodyaccording to the reverse deformation parameters to obtain a refined three-dimensional body. The reference brain atlas is used as a constraint condition of the global shape, so that the correct shape of the real brain tissue is introduced into correction three-dimensional body reconstruction, and the problem of axial offset caused by lack of a spatial position relationship and global shape information in the prior art is solved.

The present invention discloses a method for illegal invasion identification base on wireless network signal CO complexity, and relates to the information safety protection field. The method comprises the following steps: firstly, performing signal direct current subtracting processing of an original wireless network signal sequence, obtaining a direct current subtracting signal sequence, performing signal Fourier transform processing, and obtaining a Fourier transform sequence; secondary, according to a threshold energy value, performing sequence reconstruction of the Fourier transform sequence, and solving the estimation value of the CO complexity; and finally, employing a nearest neighbor method to perform identification of the illegal invasion. Besides, the present invention further discloses a system for illegal invasion identification base on the wireless network signal CO complexity. The method and system for illegal invasion identification base on the wireless network signal CO complexity do not depend on traditional wireless network safety protection means such as passwords, MAC address verification, digital watermarking and the like to thoroughly solve the safety threats such as password leakage, MAC address falsification or digital watermarking and the like; and moreover, the calculation efficiency is high, and processing delay is little.

The invention provides a vegetation index time sequence reconstruction method in combination with matrix completion and trend filtering, which comprises the following steps of: firstly, determining a missing position in time sequence data through quality marker data in a vegetation index product; the method comprises the following steps of: converting a one-dimensional vector into a two-dimensional matrix through matrix change, establishing an optimal energy equation for low-rank matrix completion for a matrix after each pixel is converted, and realizing matrix completion through an imprecise augmented Lagrange algorithm to obtain a time sequence completion matrix which does not contain data missing preliminarily; and finally, vectorizing the completion matrix, establishing an energy optimization equation of weighted trend filtering on the basis of a one-dimensional vector, and solving the model through an alternating direction multiplier method so as to further filter residual noise and obtain smooth and clean high-quality vegetation index time sequence data. And high-precision reconstruction of the long-time remote sensing vegetation index sequence is realized.

The invention relates to a coupling technique of city watercourse dredging and sequence reestablishment from a shoal to a deep pool. The coupling technique of the city watercourse dredging and the sequence reestablishment from the shoal to the deep pool is characterized in that a sequence from the shoal to the deep pool of a river is reestablished on a city watercourse crook portion where a river bank is upright and sclerotic by combining the watercourse dredging with a bottom mud solidification technique. According to the coupling technique of the city watercourse dredging and the sequence reestablishment from the shoal to the deep pool, the shoal can provide appropriate growing environment for submerged plants and aquatic animals, and the submerged plants not only can purify water and inhibit growth of algae, but also can provide good habitat environment for the aquatic animals, and thereby further improves self cleaning capacity of a watercourse; the sequence from the shoal to the deep pool can strengthen hydrodynamic force of the watercourse, improve dissolution oxygen content in a water body, mitigate anoxic status of lower layers of the city watercourse, and improve biological activity of bottom mud, and thereby improves self cleaning capacity of the water body.

The invention discloses an omega-transaminase mutant based on ancestor sequence reconstruction, and relates to the technical field of molecular biology. The mutant is obtained by mutation of omega-transaminase from Aspergillus terreus, and the amino acid sequence of the omega-transaminase mutant is as shown in SEQ ID NO. 4 or SEQ ID NO. 6. The invention further discloses a preparation method of the mutant. Compared with a wild type enzyme, the half-life period of the omega-transaminase mutant is more than 24 hours, the half-life period of the wild type enzyme is only 6.90 minutes, the half-inactivation temperatures of the mutant are 49.00 DEG C and 49.03 DEG C respectively and are about 11 DEG C higher than that of the wild type enzyme (37.89 DEG C), and the thermal stability is remarkably improved.

The invention provides a three-dimensional magnetic resonance image super-resolution reconstruction method, electronic equipment and a storage medium. The three-dimensional magnetic resonance image super-resolution reconstruction method comprises the steps of determining a three-dimensional magnetic resonance image; determining a first slice sequence of the three-dimensional magnetic resonance image in the first slice direction, performing two-dimensional super-resolution reconstruction on the first slice sequence to obtain a first reconstruction sequence, and reconstructing a first three-dimensional image based on the first reconstruction sequence; and determining a second slice sequence of the first three-dimensional image in the second slice direction, performing two-dimensional super-resolution reconstruction on the second slice sequence to obtain a second reconstruction sequence, and reconstructing the high-resolution three-dimensional image based on the second reconstruction sequence. According to the method, the electronic equipment and the storage medium provided by the invention, two-dimensional super-resolution reconstruction is alternately carried out in two directions, so that the continuity of a super-resolution reconstruction result is ensured. In the process, the realization of two-dimensional super-resolution reconstruction does not need to provide and apply a high-resolution three-dimensional image, so that the acquisition difficulty and the acquisition cost of the training sample are greatly reduced, and the practicability of the method is improved.

The invention relates to a long-chain molecule sequence mathematical reconstruction method, and specifically relates to a mathematical sequence reconstruction method for long-chain molecules, for geneDNA sequencing, protein amino acid sequencing or other long-chain structural chemical detection. The mathematical sequence reconstruction method for long-chain molecules includes the steps: 1) providing at least two DNA molecular chains, 2) breaking the at least two DNA molecular chains into fragment sequences to form X gene libraries, 3) sequencing gene fragments of the gene libraries to obtainlibrary fragment information; 4) performing full arrangement and splicing on the fragments of the library fragments, and obtaining a set of possibilities; 5) solving an intersection; and 6) judging the number of elements in the intersection to get a correct gene sequence map. The mathematical sequence reconstruction method for long-chain molecules belongs to a mathematical algorithm technology, and can realize sequencing and reconstruction of gene sequences, and sequencing and reconstruction of proteins, polysaccharides or other polymers having a single structure, thereby improving the accuracy in current gene sequencing, and the mathematical sequence reconstruction method for long-chain molecules is not probability speculation, but is based on rigorous mathematical algorithms, thus beinghigh in accuracy of sequencing structure.

The invention discloses an abnormal driving behavior online identification method based on an Encoder-Decoder attention network and an LSTM (Long Short Term Memory). The method is composed of three main modules, namely an encoder-decoder based on LSTM, an attention mechanism and a classifier based on SVM, and comprises the steps of input encoding, attention learning, feature decoding, sequence reconstruction, residual calculation and driving behavior classification. According to the method, on the basis of mobile phone multi-sensor fusion data, on the basis of driving behavior data characteristics and behavior pattern analysis, an Encoder-Decoder deep learning model, an Attention attention mechanism and an SVM classification model are fused to recognize abnormal driving behaviors. The method has the advantages of being easy in data acquisition, non-intrusive, low in cost and the like, not only considers the time correlation of the driving behaviors, but also considers the difference of different moments, can perform online identification on abnormal driving behaviors in an end-to-end mode, can provide a method basis for driving behavior evaluation and safety early warning, and has a good application prospect. The method has significant meaning for intelligent driving system design and traffic safety decision making.

The invention discloses a single-photon counting heterodyne detection method based on sequence reconstruction, which belongs to the field of lidar detection and comprises the following steps: 1. receiving photons with a photon counting detector, generating a photon pulse sequence, and recording the time interval of the pulse sequence 2. Reconstruct the photon pulse sequence on the basis of the pulse sequence time interval to obtain the reconstructed pulse sequence; 3. Carry out Fourier transform to the reconstructed pulse sequence in step 2, after obtaining the power spectrum, take the maximum The value is determined as the heterodyne signal frequency, and the invention solves the problem that the mismatched time interval generated by the existing single-photon heterodyne detection technology interferes with the heterodyne signal waveform corresponding to the photon interval and weakens the signal amplitude strength.

Synthetic representative HCV subtypes, including a 1a and 1b genome, dubbed Bole1a and Bole1b, are provided using an inventive method of Bayesian phylogenetic tree analysis, ancestral sequence reconstruction and covariance analysis. Bole1a branches centrally among 390 full-genome sequences used in its design, a carefully curated 143 sequence full-genome dataset, and separate genomic regions including an independent set of 214 E1E2 sequences from a Baltimore cohort. Bole1a is phylogenetically representative of widely circulating strains. Full genome non-synonymous diversity comparison and 9-mer peptide coverage analysis showed that Bole1a is able to provide more coverage (94% and 78% respectively) than any other sequence in the dataset including H77, a traditional reference sequence. Bole1a also provides unsurpassed epitope coverage when compared to all known T cell epitopes.

The invention relates to the technical field of radio long wave communication technology, and specifically relates to an extremely-ultra low frequency channel atmosphere noise suppression method based on variance median filtering. The extremely-ultra low frequency channel atmosphere noise suppression method based on variance median filtering includes the steps: constructing a multi-reference magnetic vector sensing system, synchronously receiving extremely-ultra low frequency signals through multi channels, and obtaining a magnetic induction output sampling point matrix X; according to the channel sampling point sequence, grouping X, estimating the variance of each group, and obtaining the variance matrix D; based on a large number decision criterion, performing pulse detection and two-stage adaptive median filtering on D; according to output of the second stage median filtering and input of the first stage median filtering, performing sequence reconstruction, and obtaining an output matrix Y; and performing power frequency harmonic interference and remaining atmosphere noise suppression on Y. As the extremely-ultra low frequency channel atmosphere noise suppression method based on variance median filtering taking the variance of the sampling point group as input of the adaptive median filter, the impulsiveness is improved. As the extremely-ultra low frequency channel atmosphere noise suppression method based on variance median filtering determines the pulse state of each element of the variance matrix based on the large number decision criterion, the pulse detection accuracy is improved and the defect that the performance is low when the median filtering is in the local high density pulse noise condition in the traditional method.