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172results about How to "Good refactoring" patented technology

Multi-vision-based bridge three-dimensional deformation monitoring method

InactiveCN102645173ADo not interfere with the natural stateNot easy to deform monitoringBiological neural network modelsCharacter and pattern recognitionContinuous measurementVision based
The invention provides a multi-vision-based bridge three-dimensional deformation monitoring method which comprises the following steps of: (1) obtaining the images of calibration plates and extracting the feature points on the multiple calibration plates by multiple video cameras respectively; (2) establishing a mapping model based on a BP neural network; (3) obtaining each video camera image at the bridge edge feature points; (4) eliminating the error point pairs by use of RANSAC to obtain the correct matching point pairs; (5) extracting the two-dimensional coordinates of each video camera image at the bridge edge feature points, obtaining the three-dimensional world coordinates of the feature points according to the mapping model based on BP neutral network, and drawing a three-dimensional curve of the bridge surface; and (6) extracting the bridge deformation rule according to the bridge curves of the bridge at different moments, and judging the bridge deformation trend. The method provided by the invention can perform non-contact three-dimensional measurement on the bridge deformation, and has the advantages of continuous measurement, instant measurement, synchronous measurement of multiple points, high precision, repeatability, low cost and the like.
Owner:张文杰

Motion capturing system and method based on CAN bus and inertial sensor

The present invention provides a motion capturing system and method based on a CAN bus and an inertial sensor, for tracking and capturing motion information of a human body in a real-time manner. The system comprises an inertial sensing node combination, a data aggregation node, and a central computer. The inertial sensing node combination contains 18 inertial sensing nodes, collects an accelerated speed, an angular speed, and geomagnetic information data of each bone point part in a real-time manner, and performs attitude estimation by using a complementary integration filtering algorithm, so as to obtain data, such as a quaternion and an euler angle, of an three-dimensional attitude of the current bone point. The data aggregation node is connected to the 18 inertial sensing nodes, is configured to collect, in a time-sharing manner, three-dimensional attitude data of each bone point obtained by the 18 inertial sensing nodes, and send the collected data to the central computer by using a wireless wifi module. A main task of the central computer is to complete functions of collecting motion data transmitted from the data aggregation node and driving a virtual 3D person model by using the motion data.
Owner:JINAN ZHONGJING ELECTRONICS TECH

Self-adaption online dictionary learning super-resolution method

The invention discloses a self-adaption online dictionary learning super-resolution method. The method firstly selects one group of high-resolution training image set and one group of low-resolution training image set,then establishes a relationship on the high-resolution training image set and the low-resolution training image set, and provides more prior information for image reconstructing through high-resolution / low-resolution dictionary to obtain a better reconstructing effect under the condition of high amplification factor, at the same time, the method uses SP (Self Propelled) sparse coding algorithm, overcomes the defect of low reconstructing accuracy due to traditional greedy algorithm and keeps a lower computation complexity. The method has the advantages of overcoming the defects of complex computation and low training speed in the current mainstream dictionary learning algorithms such as MOD (Multimedia On Demand) and K-SVD(k-singular value decomposition) and shortening image reconstructing time in general. Compared with the prior art based on learning image super-resolution, the method of the invention has a higher reconstructing accuracy and a shorter algorithm time.
Owner:NINGBO UNIV

Node merge method based dynamic network topology analysis method

The invention provides a node connected island merge based network topology analysis method. In a network topology map, a connected region formed by a node i and adjacent nodes j and k thereof is called as a connected island of the node I, and a minimum node number of the nodes i, j and k included in the island serves as an island number of the connected island. A two-dimensional array data storage structure capable of storing part of intermediate operation results is adopted, so that the method is adaptable to ring network type and tree network connectivity analysis, and is particularly suitable for plant station configuration parallel topology analysis. When the topology analysis method uses a computer multi-core parallel processing technology for achieving plant station bus configuration topology analysis, data collision due to the fact that multiple processors read and write a same node connected island number simultaneously is avoided, topology analysis operational speed is increased, parallel processing efficiency is improved, and operational speed is high while real-time performance is good.
Owner:HARBIN INST OF TECH

Virtual reality panoramic video stream projection method and equipment

ActiveCN107396077AOptimize video reconstruction effectReduced video qualityGeometric image transformationPicture reproducers using projection devicesTransmission bandwidthVideo quality
The embodiments of the invention relate to a method for projecting virtual reality panoramic video stream to a user, comprising the steps of dividing the panoramic video stream into multiple spherical subareas, providing different video qualities for the spherical subareas related to a user perspective and the spherical subareas unrelated to the user perspective according to user perspective information tracked in real time, and moving user observation points, thus realizing an optimal video reproduction effect and reducing the transmission bandwidth. The invention further relates to equipment for projecting virtual reality panoramic video stream to a user.
Owner:SHENZHEN KANDAO TECH CO LTD

Digital holography reconstruction method based on iterated denoising shrinkage-thresholding algorithm

The invention discloses a digital holography reconstruction method based on an iterated denoising shrinkage-thresholding algorithm. The method comprises the following steps of 1, reading an original image, and acquiring diffraction light complex amplitude O(x, y) by using object light information of the original image, wherein the amplitude of the original image is O<0>(Xi, Eta); 2, intervening the diffraction light complex amplitude O(x, y) obtained through fresnel diffraction and reference light R(x, y) added with o and Pi second phase shift quantity to separately achieve light wave complex amplitude U<1>(x, y) / U<2>(x, y) on a holographic plate, laminating the two holographic images I<(1)> and I<(2)> to form a phase shift holographic image I-bar (x, y), constructing a sensing matrix A, and allowing y=Pi I-bar=Pi RO=AO, wherein Pi is a known measurement matrix, R is a spare basis matrix, and y expresses obtained observation data; and 4, figuring out and acquiring a reconstructed image of the original object by using the iterated denoising shrinkage-thresholding algorithm (IDNST). On the basis of TwIST algorithm, dual shrinkage of a threshold value and a regularization parameter are introduced to the IDNST algorithm, the signal-to-noise ratio can be improved, moreover, the convergence speed is increased, the reconstruction precision is improved, and the reproduction quality reaches a more excellent level.
Owner:XI AN JIAOTONG UNIV

Single image super-resolution method based on identical scale structure self-similarity and compressed sensing

Disclosed is a single image super-resolution method based on identical scale structure self-similarity and compressed sensing. Firstly, the interpolation is performed for a low-resolution image and a quasi-high-resolution image is obtained; then, the quasi-high-resolution image is divided into quasi-high-resolution image blocks, vectors corresponding to the quasi-high-resolution image blocks serve as a training sample, a sample matrix is assembled, a K-SVD dictionary studying method is used for a solution and a dictionary is obtained; the low-resolution image is divided into low-resolution image blocks; by the aid of a down-sampling matrix, the dictionary and vectors corresponding to all low-resolution image blocks, an orthogonal matching pursuit (OMP) method is used for a solution, and vectors corresponding to high-resolution reconstruction image blocks; and finally, vectors corresponding to high-resolution reconstruction image blocks are assembled and a high-resolution reconstruction image is formed. According to the super-resolution method based on the identical scale structure self-similarity and the compressed sensing, additional information is added in the high-resolution reconstruction image through a compressed sensing frame, and the space resolution is improved.
Owner:TSINGHUA UNIV

Compressed sensing image reconstructing method based on prior model and 10 norms

The invention discloses a compressed sensing image reconstructing method based on a prior model and 10 norms, mainly used for solving the defects of poor visual effect and long operation time existing in image reconstruction in the prior art. In the technical scheme of the invention, a compressed sensing image reconstruction frame with 10 norms is optimized by utilizing a prior model; and the positioning of sparsity coefficient and solution of the sparsity coefficient value are achieved through two effective steps: step 1, establishing the prior model, and carrying out low frequency coefficient inverse wavelet transform so as to obtain an image with a fuzzy edge, determining the position of the edge by edge detection, and searching the position of wavelet high frequency subband sparsity coefficient through an immunization genetic algorithm by using the prior model of which the wavelet coefficient has inter-scale aggregation; and step 2, solving a corresponding high frequency subband by using an improved clone selective algorithm, and then carrying out the inverse wavelet transform so as to obtain a reconstructed image. Compared with the prior art, the method has the advantages of good visual effect and low calculation complexity, and can be used in the fields of image processing and computer visual.
Owner:XIDIAN UNIV

Human face expression recognition method based on Curvelet transform and sparse learning

InactiveCN106980848AImprove discrimination abilityGood refactoring abilityAcquiring/recognising facial featuresMultiscale geometric analysisSparse learning
The invention discloses a human face expression recognition method based on Curvelet transform and sparse learning. The method comprises the following steps: 1, inputting a human face expression image, carrying out the preprocessing of the human face expression image, and cutting and obtaining an eye region and a mouth region from the human face expression image after processing; 2, extracting the human face expression features through Curvelet transform, carrying out the Curvelet transform and feature extraction of the human face expression image after preprocessing, the eye region and the mouth region, carrying out the serial fusion of the three features, and obtaining fusion features; 3, carrying out the classification recognition based on the sparse learning, and respectively employing SRC for classification and recognition of the human face Curvelet features and fusion features; or respectively employing FDDL for classification and recognition of the human face Curvelet features and fusion features. The Curvelet transform employed in the method is a multi-scale geometric analysis tool, and can extract the multi-scale and multi-direction features. Meanwhile, the method employs a local region fusion method, and enables the fusion features to be better in imaging representing capability and feature discrimination capability.
Owner:HANGZHOU DIANZI UNIV

End member learning based hyperspectral image sparse unmixing method

The invention discloses an end member learning based hyperspectral image sparse unmixing method, which mainly solves the problems of low hyperspectral image unmixing precision, poor reconstruction effect, long consumed time and low efficiency during a low-signal-noise-ratio hyperspectral image unmixing process in the prior art. The method comprises the steps of: inputting hyperspectral data; synthesizing hyperspectral base data; performing end member learning; solving a hyperspectral data abundance matrix; calculating a reconstruction error of the hyperspectral data abundance matrix; and outputting an unmixing result. The method adopts a new solving mode, introduces an end member learning thought, has the advantages of high unmixing precision, good reconstruction effect and high efficiency, is simple in solving step and explicit in principle, and can be used for understanding interpretation of hyperspectral images.
Owner:XIDIAN UNIV

Image structure model-based compressed sensing image reconstruction method

The invention discloses an image structure model-based compressed sensing image reconstruction method, which mainly solves the problems that image structure information is not considered and blind iteration is carried out in the conventional method. The method comprises the following steps of: inputting an image A, and performing Fourier transform on the image A to obtain a Fourier coefficient matrix X1 of the input image A; sampling the Fourier coefficient matrix X1 according to a density variable sampling model for fully sampling Fourier coefficients at low frequency to obtain an observation vector f; performing inverse Fourier transform on the observation vector f to obtain a transformed image X2; performing edge detection on the transformed image X2 to obtain an edge detection image X3; performing Wavelet transform and Curvelet transform on the edge detection image X3, finding an edge position and positions of large coefficients, and finding corresponding coefficients in the transformed image X2 according to the obtained positions; and performing Wavelet-curvelet frame-based Split Bregman reconstruction algorithm to iterate for 20 times and finally obtaining the required reconstructed image. The method has the advantages of higher accuracy, better effect and shorter time for image reconstruction.
Owner:XIDIAN UNIV

Multivariate compressive sensing reconstruction method based on wavelet HMT (Hidden Markov Tree) model

ActiveCN103077510AGood refactoringAutomatically determine non-zero supportsImage enhancementReconstruction methodCompressed sensing
The invention discloses a multivariate compressed sensing reconstruction method based on a wavelet HMT (Hidden Markov Tree) model. The multivariate compressive sensing reconstruction method comprises the following steps of: carrying out wavelet transformation on an image, preserving a low-frequency transform coefficient, and carrying out multivariate compressive sampling on a high-frequency transform coefficient to obtain a multivariate measurement vector Y; reconstructing an initial image by using the existing MPA (Multivariate Pursuit Algorithm); calculating the posterior state probability of the high-frequency transform coefficient of the reconstructed image in a large magnitude state; updating a weighted value of the high-frequency transform coefficient; reconstructing the image by using a WMPA algorithm; returning to the second step if the condition that an appointed repeated interation weighting reconstruction times I is equal to 2 is not obtained; or else, obtaining the reconstructed image of the original image. The multivariate compressive sensing reconstruction method based on the wavelet HMT model, disclosed by the invention, has a good reconstruction effect and is applicable to both medical images and natural images.
Owner:CHINA JILIANG UNIV

Partial K space sequence image reconstruction method based on self-adapted double-dictionary learning

The invention discloses a partial K space sequence image reconstruction method based on self-adapted double-dictionary learning, and the method is mainly used for solving the problems of an existing method that the quality of a reconstructed image is more seriously reduced under the condition of sampling under 10 times. The partial K space sequence image reconstruction method comprises the following main steps of: collecting partial K space data and utilizing the correlation between the partial K space data to be integrated into complete K space data; obtaining a training image by the complete K space data; utilizing a KSVD (Kernel Singular Value Decomposition) algorithm to train the training image to obtain dictionaries with high and low resolution ratios; and utilizing a relation between the dictionaries with the high and low resolution ratios to reconstruct the input partial K space data, and carrying out residual error compensation on the reconstructed image to obtain a more accurate reconstruction result. According to the partial K space sequence image reconstruction method disclosed by the invention, the quality of the reconstructed image can be effectively improved under the condition of sampling under 10 times; and the partial K space sequence image reconstruction method can be used for reconstructing MRI (Magnetic Resonance Imaging) sequence images of a plurality of parts.
Owner:XIDIAN UNIV

Distributed video compressed sensing system and method based on non-feedback bit rate control

The invention discloses a distributed video compressed sensing system and method based on non-feedback bit rate control. The system is composed of a coder, a non-feedback bit rate controller and a decoder. Compressed sensing frames in the coder provide block measurement value residual error information for the non-feedback bit rate controller. The non-feedback bit rate controller carries out blockbit rate allocation on first compressed sensing frames (CS frames) through combination of a measurement rate-quantization parameter distortion model according to the block measurement value residualerror information and a target bit rate, provides a measurement rate and a quantization parameter of a current coding block and trains a BP neural network of a 2*3*2 structure through utilization of an allocation result. The image block CS measurement rates and quantization parameters of the CS frames are predicted through adoption of the trained BP neural network. The decoder decodes the measurement rates and the quantization parameters of received bit streams and then carries out joint decoding. According to the system and the method, the deficiency that in the prior art, only the measurement rates are allocated when the compressed sensing frames are coded is overcome, and the reconstruction effect of the compressed sensing frames is good.
Owner:南通河海大学海洋与近海工程研究院 +1

Object software oriented automatic refactoring method

The invention provides an object software oriented automatic refactoring method and relates to the technical field of software quality improvement. According to the method, a to-be-refactored software system is established as a class level multilayer dependency directed network model; refactoring preprocessing is carried out; class level network connecting components are combined; each class level network connecting component is converted into an entity set of the same class; semantic and structure coupling relationships among the entity set elements are analyzed; a method level coupling undirected network model is established; weight coefficients of different classes of coupling relationships among the nodes of the undirected network are determined; community division is carried out on each method level network; refactoring suggestions are generated; and the to-be-refactored software system is refactored. According to the method, starting from the angles of global cohesion and coupling of the whole software system, through combination of a semantic similarity, a structure similarity and a hierarchical clustering algorithm, a move function, a move attribute and extraction class refactoring operation suggestions are generated at the same time, and the intelligibility, reusability and maintainability of the code are effectively improved.
Owner:NORTHEASTERN UNIV

Finite impulse response (FIR) filter

The invention discloses a finite impulse response (FIR) filter, which consists of a filtering coefficient buffer, a to-be-filtered data buffer, a multiplier, an accumulator, an accumulating register and a comparator, wherein the filtering coefficient buffer is used for buffering coefficients which are used in the filter; the to-be-filtered data buffer is used for buffering data to be filtered; the multiplier is used for computing a product of a single filter coefficient multiplied by BS data to be filtered; the accumulator is used for computing a sum of the output of the multiplier and the output of the accumulating register; the accumulating register is used for storing a result of the accumulator; and the output of the comparator is used for indicating whether the current output of the accumulator is filtering output. By adoption of the FIR filter, high efficiency of parallel computation can be realized.
Owner:BEIJING SMART LOGIC TECH CO LTD

Video coding and decoding method based on multiple description CS measurement value

The invention discloses a video coding and decoding method based on multiple description CS measurement value. The coding method comprises steps: a video image sequence is divided into a key frame and a CS frame; block-based measurement, quantization and entropy coding are adopted for the key frame; a multiple description idea is adopted for the CS frame to describe a block-based measurement value in two ways; and quantization and entropy coding are separately carried out. The decoding method comprises steps: after key frame data are received, inverse quantization is firstly carried out on entropy decoding to obtain a measurement value, the key frame block is initially reconstructed, and multiple hypothesis prediction and reconstruction are carried out inside the frame; after CS frame multiple description code stream is received, inverse quantization is carried out on entropy decoding; a measurement value based on multiple description is generated; and CS frame multiple description adaptive inter-frame multiple hypothesis reconstruction is carried out. In the condition of not increasing complexity of the coding end, the reconstruction quality and robustness of a video image are improved.
Owner:HOHAI UNIV CHANGZHOU

Off-grid DOA estimation method based on covariance matrix reconstruction

The invention relates to an off-grid DOA estimation method based on covariance matrix reconstruction, which belongs to the field of signal processing, and aims to solve the problem that DOA estimationhas large estimation errors due to grid mismatch in a sparse representation model. The DOA estimation method is characterized by comprising the following steps of firstly, including offset between DOA and grid points into a constructed received data airspace discrete sparse representation model, establishing a sparse representation convex optimization problem about DOA estimation based on the reconstructed signal covariance matrix, constructing a sampling covariance matrix estimation error convex model, and including the convex set explicit expression into a sparse representation model to improve the sparse signal reconstruction performance, and finally, solving the obtained joint optimization problem by adopting an alternate iteration method to obtain a grid offset parameter and off-gridDOA estimation. The method has the effects of relatively good angle resolution and relatively high DOA estimation precision.
Owner:ZHEJIANG SCI-TECH UNIV

Fault sensor information reconstruction method based on measured value association degree

The invention provides a fault sensor information reconstruction method based on measured value association degree. The method comprises the following steps: S1, aimed at a fault sensor, calculating association degree of response of a measuring point where a sensor is on in normal operation and other measuring points; S2, through comparing association degree values, determining an association model, establishing required response variables; S3, and using a partial least squares to establish a reconstruction model of reconstruction variables and the response variables, and using measured data of structural health monitoring, performing fault sensor response information reconstruction on the fault sensor. The method has very good effect on fault sensor information reconstruction, obviously reduces reconstruction errors, and ensures variation trend of the reconstruction values to keep consistent with variation trends of practical values. The method has obvious integrated structure reliability.
Owner:卢伟

Aerospace engine abnormity intelligent detection method based on hierarchical adversarial training

The invention discloses an aerospace engine abnormity intelligent detection method based on hierarchical adversarial training, and the method comprises the steps: employing a plurality of sensors to collect original signals of an aerospace engine in an operation state as multi-source data, intercepting a time sequence at a fixed length to obtain a multi-channel data sample set, and converting a one-dimensional sequence into a two-dimensional image; dividing the two-dimensional image sample into a training set and a test set; constructing a relative generative adversarial network as an anomalydetection model, and performing hierarchical adversarial training by using the training set; using the training model to evaluate the state of the training set sample, modeling the obtained evaluationscore distribution, and calculating the score threshold of the normal sample; using the model for evaluating the state of a test set, aggregating neighborhood information during testing, and conducting anomaly detection according to a score threshold value. According to the method, the model detection capability is improved through hierarchical adversarial training, multi-source information is fused, neighborhood information is aggregated to improve the result reliability, and finally, intelligent detection of abnormal operation of the aerospace engine can be realized.
Owner:XI AN JIAOTONG UNIV

Millimeter wave channel estimation method based on compressed sensing in height moving scene

The invention provides a millimeter wave channel estimation method based on compressed sensing in a high-speed moving scene. The method comprises the following steps: step 1, analyzing downlink communication in a high-speed moving scene, considering the influence of Doppler frequency shift, carrying out channel modeling based on the low-rank characteristic and the spatial correlation characteristic of millimeter wave communication, and writing into a matrix form; step 2, after the channel matrix in the step 1 is quantized, designing the channel matrix shows sparse characteristics, and a perception matrix and a measurement matrix; and step 3, performing vectorization processing on the channel matrix presenting the sparse characteristic in the step 2, reconstructing the vectorized channel model based on a compressed sensing algorithm and the sensing matrix and the measurement matrix in the step 2, and calculating a normalized mean square error. The calculation cost is reduced, and the performance is improved.
Owner:SOUTHEAST UNIV

Image super-resolution reconstruction algorithm based on jump connection residual network

The invention relates to an image super-resolution reconstruction algorithm based on a jump connection residual network, and belongs to the technical field of image processing. The method comprises the steps of selecting a training data set, and performing bicubic interpolation on a low-resolution image; constructing a specific structure of the network, and formulating a network training strategy;performing detail extraction on the interpolated image; the dimension of the total feature is reduced, and the single-pixel receptive field is widened; performing multiple iterations on the network training until the maximum number of iterations is reached; and final high-resolution image reconstruction is completed in a global residual error learning mode. According to the method, the residual network based on jumping is combined with the sub-network based on the parallel channels, detail features of the shallow network are fully utilized, rapid learning of the detail features of the depth image is achieved, and rapid convergence of the network is achieved through adjustable gradient clipping.
Owner:KUNMING UNIV OF SCI & TECH

Dried konjac and manufacturing method therefor as well as processed foods using said dried konjac

InactiveUS20120141652A1Good water reconstitution propertyImproved in strange textureFruit and vegetables preservationFood ingredient functionsFiberCellulose
Provided are dried konjac having the contradictory elements of improved water-reconstitution properties and an effect to prevent degeneration when dried along with reduced calories and sugars and which can be anticipated to have blood sugar-suppressing effects, a manufacturing method therefor, and processed foods using said dried konjac.The dried konjac is characterized in that it comprises, by weight ratio, 8-20% of one or more kinds of starch material selected from tapioca, potato, cornstarch, and processed starch, 6-20% konjac powder, 15-40% of one or more kinds of dietary fiber material selected from a dietary fiber material A group including digestion-resistant starch and processed starch comprising a large quantity of dietary fiber, 0-10% of one or more kinds of dietary fiber material selected from a dietary fiber material B group comprising oat fiber, wheat fiber, potato fiber, sugarcane fiber, crystalline cellulose, sodium alginate, carrageenan, guar gum, hydrolyzed guar gum, psyllium seed gum, xanthan gum, tamarind gum, tragacanth gum, and Gellan gum, and 30-50% of digestion-resistant dextrin.
Owner:ASIA BROADCAST SATELLITE

Partitioning compressive sensing reconstruction method based on image block clustering and sparse dictionary learning

ActiveCN104036519ATake advantage of similarity structuresEffective portrayalImage enhancementImage analysisBlock effectImage based
The invention discloses a partitioning compressive sensing reconstruction method based on image block clustering and sparse dictionary learning, and belongs to the technical field of image processing. The method comprises the following steps that an image is read in, and is divided into sub-image blocks; compressive sampling is carried out on the sub-image blocks to achieve measurement; edge images in (K-1) directions are generated, PCA transformation is carried out on the edge images to generate (K-1) PCA bases, and then, a DCT base is taken for forming a union dictionary of K initial direction bases; the typical correlation coefficients between the measurement and the direction bases are calculated, and the sub-images are clustered to form K classes; the sub-image blocks in the K classes are reconstructed through a multivariable tracking algorithm; the reconstructed sub-image blocks are used for updating the K direction bases; whether the maximum number of times of iteration reconstruction is reached or not is judged; the reconstructed sub-image blocks are spliced together to obtain a reconstructed image of the original image; the image is output. According to the partitioning compressive sensing reconstruction method based on image block clustering and sparse dictionary learning, the blocking effect in the reconstructed image can be obviously weakened or removed in two reconstruction modes, and the method has a reconstruction effect on a natural image.
Owner:CHINA JILIANG UNIV

Measurement matrix design method based on LDPC matrix

The invention discloses a measurement matrix design method based on an LDPC matrix. The method comprises the following steps: the step one in which the number L of continuous '1' at the beginning of the first row of the matrix is determined at first, and positions of '1' in the following row of the matrix are subjected to translation to the right for L positions successively according to positions of '1' in the previous row so as to ensure that the positions of '1' between every two rows or every two columns in a cycle submatrix are different to construct the cycle submatrix; the step two in which required rows or columns are randomly selected from the cycle submatrix to construct a measurement matrix based on the LDPC matrix; and the step three in which four-side loops are found in the whole matrix through searches of a limited number, and the four-side loops are eliminated to construct the measurement matrix based on the LDPC matrix. The measurement matrix inherits advantages, such as good sparsity, small column correlation values, etc., of the LDPC matrix, and at the same time, the shortage that optimal d values (the average number of '1' in each column) need to be determined for different dimensions of measurement matrixs in advance when the LDPC matrix is used as the compression sensing measurement matrix can be overcome. The matrix has advantages of good sparsity, simple structure, good orthogonality, easy hardware implementation and good reconstruction effect.
Owner:TIANJIN UNIV

Instant noodles and method for producing the same

Instant noodles are produced, which have an excellent reconstitution property, can be reconstituted by pouring of boiling water even if the noodles are thicker than before, and have excellent taste and texture. The instant noodles are produced by: making raw noodle strings each having a multilayer structure including three or more layers; spraying superheated steam to the raw noodle strings; gelatinizing the noodle strings to which the superheated steam has been sprayed; and drying the noodle strings which have been gelatinized. It is preferable to gelatinize the noodle strings by spraying the superheated steam to the noodle strings, supplying moisture in liquid form to the noodle strings, and further heating the noodle strings by using the superheated steam and / or saturated steam.
Owner:NISSIN YORK

Method for reconstructing Chinese character font

The invention discloses a method for reconstructing a character font by editing composite figures or texts. The method overcomes the drawbacks of high cost and low quality of the conventional method for reconstructing the character font. In the method, a mode of software and manual alternate operation is adopted, a round-robin recursive algorithm is applied, decomposition information of template Chinese characters and Chinese characters to be made in a database is utilized to realize the reconstruction of patterns and characters, the font reconstruction quality is guaranteed, the cost is reduced and the efficiency is improved.
Owner:杨光祥

Erasure code storage and reconfiguration optimization method based on redirect-on-write

The invention discloses an erasure code storage and reconfiguration optimization method based on redirect-on-write. The method includes: redirecting data, written in failure data nodes, to an RS array composed of survival node free spaces. The data redirecting process and the data migration process, including failure data node reconfiguration, redirected data migration and check data updating caused by migration, are processed independently, the two processes have fewer competitions for resources such as disk, memory and network bandwidth, the background reconfiguration process is accelerated, and foreground user access performance is optimized.
Owner:HUAZHONG UNIV OF SCI & TECH

Communication device and method for updating software thereof

The invention discloses a communication device and a method for updating software thereof. The method comprises determining each pair of program elements with coupling degree higher than a set value in a target program to respectively serve as focus points; enabling the relevant program elements of any pair focus points to serve as nodes, determining the edges of arrows with directions between the nodes according to the dependent relations between the relevant program elements, and constructing a program dependent graph through the nodes and the edges; performing forward slicing and backward slicing according to a slicing principle with each focus point serving as a starting point respectively according to the constructed program dependent graph, and acquiring the program dependent graph after slicing of the corresponding focus points; and identifying the program elements needing to be reconstructed according to the program dependent graph after slicing. The communication device and the method for updating the software of the communication device construct the dependent graph with the coupling degree serving as an entry point. Compared with cohesion, the coupling degree can reflect the interaction relation between the elements in the program so as to facilitate the reconstruction between analysis classes. The slicing technology is introduced so as to increase the accuracy of measurement.
Owner:DATANG MOBILE COMM EQUIP CO LTD +1
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