32 results about "Signature matrix" patented technology

The invention provides a method and system combining functional genomic and genetic, proteomic, anatomic neuroimaging, functional neuroimaging, behavioral and clinical measurements and data analyses for autism pediatric population screening, diagnosis or prognosis. More specifically, the invention provides a weighted gene and feature test for autism which uses a weighted gene signature matrix for comparison to a reference database of healthy and afflicted individuals. The invention also provides normalized gene expression value signatures for comparison to a reference database. The invention additionally combines either the weighted gene or the normalized gene analysis with comparisons to a gene-networks signature matrix, a multi-modal signature matrix, and a collateral features signature matrix for improved accuracy in screening, diagnostic and prognostic relevance for autism, particularly for newborns, babies ages birth to 1 year, toddlers ages 1 to 2 years, toddlers ages 2 to 3 years and young children ages 3 through 4 years.

The invention relates to artificial intelligence, and provides a service system anomaly detection method and device, computer equipment and a storage medium, and the method comprises the steps: constructing a multi-scale signature matrix according to the multivariate time sequence data of each index generated by a service system; inputting the multi-scale signature matrix into a convolution layerto encode a spatial mode of the multi-scale signature matrix, and outputting a spatial feature map; inputting the spatial feature map into an attention-based convolutional long-short-term memory network layer, and updating the hidden state of the spatial feature map through the attention-based convolutional long-short-term memory network layer to obtain an updated spatial feature map; inputting the updated spatial feature map into a deconvolution layer to decode and reconstruct the updated spatial feature map to obtain a reconstructed signature matrix; comparing the reconstructed signature matrix with the multi-scale signature matrix, and determining an abnormal index of the service system. In addition, the invention also relates to a blockchain technology, and the multivariate time seriesdata can be stored in the blockchain. By adopting the method, the anomaly detection accuracy can be improved.

A method is described for generating a minimal set of Analytical Redundancy Relations representing a system to which a plurality of sensors is associated for the observation of variables indicative of operating conditions and adapted to enable detection and isolation of faults.The minimal set of Analytical Redundancy Relations is derived from a complete set of Analytical Redundancy Relations in implicit form, for which an associated binary Fault Signature Matrix is specified, and comprises the relations associated to a minimal subset of rows of the original matrix, which has the same number of non-zero columns and the same number of distinct columns as the original matrix.

Methods and systems for anomaly detection and correction include generating original signature matrices that represent a state of a system of multiple time series. The original signature matrices are encoded using convolutional neural networks. Temporal patterns in the encoded signature matrices are modeled using convolutional long-short term memory neural networks for each respective convolutional neural network. The modeled signature matrices using deconvolutional neural networks. An occurrence of an anomaly is determined using a loss function based on a difference between the decoded signature matrices and the original signature matrices. A corrective action is performed responsive to the determination of the occurrence of the anomaly.

The invention provides a construction data self-checking method and system, and the method comprises the steps of obtaining all construction data in a construction scene, and constructing a construction data matrix; calculating relevancy between data fields in the construction data matrix to obtain a signature matrix; performing feature extraction on the signature matrix by using a pre-trained data anomaly detection model to obtain an output matrix; calculating a mean square error between the output matrix and the signature matrix; and according to the mean square error, determining a self-inspection result of all construction data in the construction scene. According to the construction data self-checking method and system provided by the invention, the association relationship between the construction data in the same construction scene is extracted, the data anomaly detection model is constructed, automatic detection of the abnormal data is realized according to the mean square error between the input and the output of the model, false data and invalid data are prevented from existing, the self-checking precision of the construction data is effectively improved, and the self-checking efficiency is greatly improved.

The invention discloses a revocable palm print feature generation method and system based on a minimum signature. The method comprises the following steps of obtaining an original palm print image, extracting a palm print region of interest (ROI) in the original palm print image, and extracting the orthogonal features of the palm print ROI; randomly generating a chaotic matrix as a secret key, andperforming XOR calculation on the chaotic matrix and the orthogonal matrix to obtain an initial characteristic matrix; and randomly generating a plurality of hash functions to generate a first signature matrix, carrying out scanning calculation on the initial feature matrix according to the hash functions, and replacing the maximum value in the signature matrix with the minimum value to obtain asecond signature matrix serving as the revocable palm print feature; and finally, carrying out scanning calculation on the initial feature matrix by utilizing irreversibility of a Hash function, and generating a final minimum Hash signature matrix as a final revocable palm print feature. According to the present invention, the security and the privacy of palm print biological characteristics are effectively protected, and the security and the privacy can be improved under the condition that the recognition rate is ensured.

The invention discloses a classification method for multivariable medical sensing data streams. The method comprises the following steps that firstly, a signature matrix which can capture the correlation among time sequences and represent the time sequences, and has robustness to noise is constructed; then, for individual unbalanced categories, an auxiliary classifier is adopted to generate an adversarial network ACGAN to generate enough signature matrixes corresponding to the categories; finally, a bidirectional convolution long-term and short-term memory (BPCLSTM) lightweight network classification model based on an attention Attention mechanism is constructed to realize accurate classification of multivariable medical sensing data streams, and the classification model not only can improve the classification accuracy, but also can reduce the scale of an original classification model.

A method for generating a minimal set of Analytical Redundancy Relations representing a system to which a plurality of sensors is associated for the observation of variables indicative of operating conditions and adapted to enable detection and isolation of faults. The minimal set of Analytical Redundancy Relations is derived from a complete set of Analytical Redundancy Relations in implicit form, for which an associated binary Fault Signature Matrix is specified, and comprises the relations associated to a minimal subset of rows of the original matrix, which has the same number of non-zero columns and the same number of distinct columns as the original matrix.

The invention discloses a terminal access method and device, and the method and device are used for solving a problem that the system performance of a conventional SCMA multi-terminal access mechanism is reduced because of collision, and a possible retransmission problem of a system. The method comprises the steps that a terminal is determined to enter a competitive access stage; the terminal determines a first signature according to a random number seed and a signature matrix during the transmission of binary data at each time, and enabling the binary data to be mapped to a multi-dimensional symbol for transmission according to the first signature, wherein the first signatures selected during the transmission of binary data at each time are different.

The invention relates to a method for merging and optimizing based on Lucene index segments, and belongs to the technical field of computer indexing. It includes the following steps: combining the load information of the current node and the segment information of the index, constructing a merge analysis module to judge whether the merge condition is satisfied. According to the dictionary files contained in each index segment, the feature matrix of the index segment in the index is obtained, and then combined with the minHash algorithm and the minimum hash signature algorithm to calculate the signature matrix of the index segment. Combined with the signature matrix of the index segment and the Jaccard similarity principle, the similarity coefficient between each index segment is calculated, and the index segment is divided into different similar sets according to the similarity coefficient. Use the similarity evaluation model to score each similar set, and sort according to the set score, and select one or more sets with the highest score to be merged by the merge thread. The optimization method of the invention can reduce the impact of the merge operation on the performance of the index function and the retrieval function and can effectively improve the speed of retrieval.

The invention relates to the technical field of artificial intelligence, and discloses a resume duplicate checking method and device, equipment and a medium. The method comprises: acquiring a to-be-duplicated resume; performing word segmentation according to the to-be-duplicated resume, and performing hash signature matrix calculation on a word segmentation result to obtain a to-be-duplicated hashsignature matrix; according to the to-be-duplicated hash signature matrix, and carrying out similar resume query from a resume library according to information classification to obtain a candidate resume set; respectively constructing a resume pair feature vector for the to-be-duplicated resume and each resume in the candidate resume set to obtain a plurality of to-be-predicted resume pair feature vectors; inputting the to-be-predicted resume pair feature vectors into the classification prediction model for similarity probability prediction to obtain probability prediction values of the to-be-predicted resume pair feature vectors; and determining a target repeated resume pair according to the probability prediction values of the plurality of to-be-predicted resume pair feature vectors. According to the invention, the duplicate checking efficiency is improved, similar rules do not need to be set manually, and the accuracy of determining the target repeated resume pairs is guaranteed.

The invention provides a hyperspectral mixed pixel classification method based on neighbor synergistic enhancement, comprising: calculating the spectral signature matrix of multi-target features using marked sample features; designing a multi-category classifier based on spectral features to classify the features Classification; integrate the spatial structure features in the classification results, and extract the neighboring pixels; use the neighboring pixels to collaboratively classify the unmarked hyperspectral objects; use the iterative method to gradually classify and label the unmarked objects; The method of domain extension further fuses the spatial characteristics of the target object to complete the final classification and labeling. The invention uses a multi-category classifier to simultaneously classify the object categories, which solves the problem that the traditional classification method cannot classify the background objects; and uses the method of neighbor synergistic enhancement to gradually mark the unmarked object objects, effectively It combines the spectral characteristics and spatial characteristics of ground objects, and the classification effect is better.

A method for continuously determining mutually corresponding image points between a first camera image and a second camera image, having the steps of capturing (10) the first camera image (101); capturing (11) the second camera image (102); ascertaining (40) at least one first signature matrix element (203) of a first signature matrix (201) on the basis of the first camera image (101); assigning (60) first coordinates to an ascertained signature value of the first signature matrix element (203) in a signature value position table (300); ascertaining (70) at least one signature value of a second signature matrix element (203) having second coordinates of a second signature matrix (202) on the basis of the second camera image (102); and determining (80) at least one element (503) of a correspondence matrix (500, 501, 502) on the basis of the signature value position table (300), the cyclically ascertained signature value of the second signature matrix element (203) and the second coordinates of this second signature matrix element (203), wherein at least one concatenation matrix element (403) of a concatenation matrix (400) is ascertained (50) on the basis of the first signature matrix (201) and the signature value position table (300), and the element (503) of the correspondence matrix (500, 501, 502) is additionally determined (80) on the basis of the ascertained concatenationmatrix (400), the first camera image (101) and the second camera image (102).

This application provides a block chain consensus method and system based on communication activity and asset certification. The consensus method includes the following steps: improving the structure of the existing block, and the improved block includes block header, transaction set and signature Matrix; expand the transaction types on the blockchain. After the expansion, the transaction types on the blockchain include transfer transactions and penalty transactions; use the signature matrix to select the candidate group, and determine the final bookkeeper among the candidates according to the amount of assets , the bookkeeper broadcasts the winning information and releases a new block to the main chain to reach a consensus. This application can avoid the waste of invalid resources caused by computing power competition, and at the same time, it can avoid the power of bookkeeping in the hands of a few people; it can reduce the propagation delay, speed up the message coverage speed of the distributed system, and effectively reduce the possibility of network partition; Provides self-monitoring function for system security, which can meet the application requirements of high throughput.

A transmitter device including a processor in a wireless communication system. In one embodiment, the processor is configured to receive at least one modulated data message and to spread the at least one modulated data message into the transmission signal using a low density signature matrix. The low density signature matrix is ​​an acyclic signature matrix. The receiver device is configured to receive said transmission signal and to detect at least one modulated data message within the received transmission signal. The processor is configured to detect at least one modulated data message in one iteration using the acyclic signature matrix. Such an acyclic signature matrix is ​​constructed as a concatenation of a phase-rotated identity matrix and an all-zero matrix.

A method of using magic square signature to identify true or false of status includes generating a magic square for each article, adding elements of generated magic square on elements of signature magic square to achieve model for obtaining a signature matrix and using this matrix as identification data of article status, sending signature matrix to identifying device with signature magic square for calculating model difference of said matrix to signature magic square and verifying whether matrix is magic square or not, confirming that status having signature matrix is true or otherwise it isfalse if matrix is magic square.

The embodiment of the present invention discloses an information processing method and a server. The method includes: obtaining the first historical behavior data obtained by the first user performing operations on the terminal; performing feature construction according to the first historical behavior data to generate the first feature matrix, the first feature matrix is ​​used to represent the correspondence between the first user and the first information; the first feature matrix is ​​compressed according to the first preset rule to generate a second signature matrix, and the second signature matrix is ​​used to represent The minimum hash value corresponding to the second historical behavior data, the second historical behavior data is obtained after the first historical behavior data is compressed; the second signature matrix is ​​processed according to the second preset rule to generate the first model , the first model is used to represent the degree of correlation between the second historical behavior data; the current behavior data of the second user is obtained, and the current behavior data is input into the first model to obtain the associated data associated with the first user.