1777 results about "Data Matrix" patented technology

The present invention provides an electronic message management system (EMS) that includes a real-time feedback loop where data is collected from the electronic messages on incoming connection attempts, outgoing delivery attempts, and message content analysis, and written to a centralized data matrix. A separate process accesses the data matrix and analyzes trends in that data. The detected data patterns, trends or behavior is based on configuration parameters for the recipient. Based on these determinations, the process is able to instruct components in the EMS to accept, redirect, refuse, modify, defer, or otherwise dispose of the connection request, the delivery attempt, or the message. Associated methods for managing the transmission of electronic messages are also disclosed.

The present invention is directed to a method for inferring / estimating missing values in a data matrix d(q, r) having a plurality of rows and columns comprises the steps of: organizing the columns of the data matrix d(q, r) into affinity folders of columns with similar data profile, organizing the rows of the data matrix d(q, r) into affinity folders of rows with similar data profile, forming a graph Q of augmented rows and a graph R of augmented columns by similarity or correlation of common entries; and expanding the data matrix d(q, r) in terms of an orthogonal basis of a graph Q×R to infer / estimate the missing values in said data matrix d(q, r).on the diffusion geometry coordinates.

The invention comprises transformation of a section of a data block independently of the transformation of separate or overlapping data blocks to determine a property related to the original matrix, where each of the separate or overlapping data blocks are derived from an original data matrix. The transformation enhances parameters of a first data block over a given region of an axis of the data matrix, such as signal-to-noise, without affecting analysis of a second data block derived from the data matrix. This allows for enhancement of analysis of an analyte property, such as concentration, represented within the original data matrix. A separate decomposition and factor selection for each selected data matrix is performed with subsequent score matrix concatenization. The combined score matrix is used to generate a model that is subsequently used to estimate a property, such as concentration represented in the original data matrix.

The invention computes frequency-domain channel gains by compiling a set of estimated channel gains as a function of pilot sequences, a set of analytical channel gains variables, and a set of weighting coefficients variables. A plurality of weighting coefficients are computed as a function of time and frequency correlation functions, a noise correlation matrix, and pilot sequences. A weighting matrix is computed from the weighting coefficients. After receiving a training sequence from at least one transmitter, a received data matrix is computed from the training sequence. The weighting matrix and the received data matrix are used to compute the frequency-domain channel gains. The invention also provides a method for reducing the computational complexity of estimating the time and frequency response of at least one desired signal received by at least one antenna. Also, the time and frequency response of at least one desired signal received by at least one antenna can be both interpolated and predicted with the present invention.

Systems, methods are provided for augmenting functions of a computing device by a controlling computing device. The method comprises receiving a command and a data matrix from the controlling computing device. The data matrix contains data that when installed enables the subordinate computing device to accomplish additional functions. The method further comprises calling a first SEAM by the computing device to receive the command and the data matrix, calling a second SEAM by the computing device to create a SDS extension in its volatile memory, and populating the one or more volatile extensions with the data from the data matrix.

The present invention is directed to a method for inferring / estimating missing values in a data matrix d(q, r) having a plurality of rows and columns comprises the steps of: organizing the columns of the data matrix d(q, r) into affinity folders of columns with similar data profile, organizing the rows of the data matrix d(q, r) into affinity folders of rows with similar data profile, forming a graph Q of augmented rows and a graph R of augmented columns by similarity or correlation of common entries; and expanding the data matrix d(q, r) in terms of an orthogonal basis of a graph Q×R to infer / estimate the missing values in said data matrix d(q, r) on the diffusion geometry coordinates.

A magnetic resonance (MR) imaging apparatus and technique exploits spatial information inherent in a surface coil array to increase MR image acquisition speed, resolution and / or field of view. Magnetic resonance response signals are acquired simultaneously in the component coils of the array and, using an autocalibration procedure, are formed into two or more signals to fill a corresponding number of lines in the signal measurement data matrix. In a Fourier embodiment, lines of the k-space matrix required for image production are formed using a set of separate, preferably linear combinations of the component coil signals to substitute for spatial modulations normally produced by phase encoding gradients. One or a few additional gradients are applied to acquire autocalibration (ACS) signals extending elsewhere in the data space, and the measured signals are fitted to the ACS signals to develop weights or coefficients for filling additional lines of the matrix from each measurement set. The ACS lines may be taken offset from or in a different orientation than the measured signals, for example, between or across the measured lines. Furthermore, they may be acquired at different positions in k-space, may be performed at times before, during or after the principal imaging sequence, and may be selectively acquired to optimized the fitting for a particular tissue region or feature size. The in vivo fitting procedure is readily automated or implemented in hardware, and produces an enhancement of image speed and / or quality even in highly heterogeneous tissue. A dedicated coil assembly automatically performs the calibration procedure and applies it to measured lines to produce multiple correctly spaced output signals. One application of the internal calibration technique to a subencoding imaging process applies the ACS in the central region of a sparse set of measured signals to quickly form a full FOV low resolution image. The full FOV image is then used to determine coil sensitivity related information and dealias folded images produced from the sparse set.

Embodiments of an X-ray diagnostic imaging system comprise a plurality of coded 2D and / or 3D markers associated with surfaces of system components. The position and coding of at least some of the coded markers can be determined by a position detection system. In some embodiments, a coded marker is assigned a reference point having a known position on the surface of the system component. The positions of the system components in space can be calculated based at least in part on a reference point network determined from the position of the individual reference points measured with the position detection system. In some embodiments, the coded markers represent information with a data matrix code (DMC).

A wireless combination time, frequency and spectral shaping communications method that transmits data in convolution unit matrices (data frames) of N×N (N2), where generally either all N2 data symbols are received over N spreading time intervals (each composed of N time slices), or none are. To transmit, the N2 sized data frame matrix is multiplied by a first N×N time-frequency shifting matrix, permuted, and then multiplied by a second N×N spectral shaping matrix, thereby mixing each data symbol across the entire resulting N×N matrix (TFSSS data matrix). Columns from this N2 TFSSS data matrix are selected, modulated, and transmitted, on a one element per time slice basis. At the receiver, the replica TFSSS matrix is reconstructed and deconvoluted, revealing the data. The method can accommodate multiple users at once, can adapt to changing channel conditions, and is particularly useful for coping with channel impairments such as Doppler shifts.

A method and system for distributing data from one or more main data sources to one or more consumer nodes. An abstract data matrix layer is provided between a producer layer and a consumer layer. A producer node multicasts data updates to selected data matrix nodes in the data matrix layer, and a consumer node registers with the data matrix layer to receive designated data updates. One or more data matrix nodes then serve the requested data updates on the requesting consumer node.

In a method and system for the dynamic analysis of data represented in distinct matrices, if two data matrices X and Y are present in which corresponding rows of X and Y each refer to the same underlying object, a relationship can developed between the X and Y data matrices, which allows for a prediction of responses in Y on the basis of inputted X-data. And, if a third data matrix Z is present in which corresponding columns of Y and row of Z each refer to the same underlying object, a relationship can developed between the X Y and Z data matrices, which allows for link between X and Z through Y.

A material processing system including a process tool and a process performance prediction system. The performance prediction system includes sensors coupled to the tool to measure tool data and a controller coupled to the sensors to receive tool data, where the controller is configured to predict the process performance for the tool using the tool data. A method for detecting a fault in a material processing system using a process performance prediction model is also provided. The method includes preparing the tool, initiating a process in the tool, and recording tool data to form to a tool data matrix. The method also includes performing a matrix multiplication of the tool data matrix and a correlation matrix to form predicted process performance data, where the correlation matrix includes the performance prediction model, comparing the predicted data with target data, and determining a fault condition of the processing system from the comparing step.

Systems and methods for capturing and analyzing significant parameter data from vehicle systems whenever a diagnostic trouble code (DTC) is triggered. A multi-dimensional matrix is constructed, with vehicles, DTCs, and parameter data comprising three dimensions of the matrix. The data matrix is populated with DTC and parameter data from many different vehicles, either when vehicles are taken to a dealer for service, or via wireless data download. Time can be added as a fourth dimension of the matrix, providing an indication of whether a particular system or component is temporally degrading. When sufficient data is accumulated, the data matrix is pre-processed, features are extracted from the data, and the features are classified, using a variety of mathematical techniques. Trained classifiers are then used to diagnose the root cause of any particular fault signal, and also to provide a prognosis of system health and remaining useful life.

A method for correcting error of pressure transducer includes setting up data model of pressure transducer, collecting N numbers of different temperatures and M numbers of output values from pressure transducer to form N x M transducer data matrix, setting up pressure transducer model according to output data, dividing temperature compensation region to be a numbers of revision temperature regions, detailing pressure transducer model to calculate out compensation coefficient, obtaining transducer output value according to revision formula and using microprocessor to fetch value in storage space of revision coefficient.

An efficient digital video (DV) decoder process that utilizes a specially constructed quantization matrix allowing an inverse quantization subprocess to perform parallel computations, e.g., using SIMD processing, to efficiently produce a matrix of DCT coefficients. The present invention utilizes a first look-up table (for 8x8 DCT) which produces a 15-valued quantization scale based on class number information and a QNO number for an 8x8 data block ("data matrix") from an input encoded digital bit stream to be decoded. The 8x8 data block is produced from a deframing and variable length decoding subprocess. An individual 8-valued segment of the 15-value output array is multiplied by an individual 8-valued segment, e.g., "a row," of the 8x8 data matrix to produce an individual row of the 8x8 matrix of DCT coefficients ("DCT matrix"). The above eight multiplications can be performed in parallel using a SIMD architecture to simultaneously generate a row of eight DCT coefficients. In this way, eight passes through the 8x8 block are used to produce the entire 8x8 DCT matrix, in one embodiment consuming only 33 instructions per 8x8 block. After each pass, the 15-valued output array is shifted by one value position for proper alignment with its associated row of the data matrix. The DCT matrix is then processed by an inverse discrete cosine transform subprocess that generates decoded display data. A second lookup table can be used for 2x4x8 DCT processing.

To track a large number of tools, the tools are kept in sets with each set having a container. A silhouette of each tool stored in the container is printed at the point of storage along with a data matrix code that has stored in binary code a description of the too, the part number, and an identification of the kit of which it is a part. The associated tool has etched into the surface thereof a data matrix code containing the same information as the code printed at the point of storage. The data matrix codes are readable by a scanner and a record of all the tools is maintained on a computer.

A system and method for simultaneously obtaining a plurality of images of an object or pattern from a plurality of different viewpoints is provided. In an exemplary embodiment, proper image contrast is obtained by replacing the light sources of earlier systems with equivalent light sensitive devices and replacing the cameras of earlier systems with equivalent light sources. With such a system, bright-field images and dark-field images may be simultaneously obtained. In one aspect of the invention, a light source is positioned to illuminate at least a portion of an object. A plurality of light guides having input ends are positioned to simultaneously receive light reflected from the object and transmit the received light to a plurality of photodetectors. The light guides are arranged such that their respective input ends are spaced substantially equally along at least a portion of a surface of an imaginary hemisphere surrounding the object. The signals generated by the photodetectors (as a result of light detection) are processed and a plurality of images of the object are formed. Another aspect of the invention provides a method for generating composite images from simultaneously obtained images. Equivalent regions of each image (corresponding to geographically identical subpictures) are compared. The subpicture having the highest entropy is selected and stored. This process continues until all subpictures have been considered. A new composite picture is generated by pasting together the selected subpictures. In another aspect of the invention, the vector of relative light values gathered for each pixel or region of an object illuminated or scanned (i.e., one value for each photodetector) is used to determine reflectance properties of points or regions illuminated on the object or pattern. The reflectance properties may be stored in a matrix and the matrix used to read, for example, a Bar Code of a data matrix symbol.

A method for tracking coronary artery motion includes constructing (11) a centerline model of a vascular structure in a base phase image in a sequence of 2D images of coronary arteries acquired over a cardiac phase, computing (12), for each pixel in a region-of-interest in each subsequent image, a velocity vector that represent a change in position between the subsequent image and base phase image, calculating (13) positions of control points in each phase using the velocity vectors, and applying (14) PCA to a P×2N data matrix XT constructed from position vectors (x, y) of N centerline control points for P phases to identify d eigenvectors corresponding to the largest eigenvalues of XXT to obtain a d-dimensional linear motion model {circumflex over (α)}p, in which a centerline model for a new image at phase p+1 is estimated by adding {circumflex over (α)}p to each centerline control point of a previous frame at phase p.

The invention provides a dynamic beam scheduling method based on deep reinforcement learning, which belongs to the field of multi-beam satellite communication systems. The dynamic beam scheduling method comprises the steps of: firstly, modeling a dynamic beam scheduling problem into a Markov decision process, wherein states of each time slot comprise a data matrix, a delay matrix and a channel capacity matrix in a satellite buffer, actions represent a dynamic beam scheduling strategy, and a target is the long-term reduction of accumulated waiting delay of all data packets; and secondly, solving a best action strategy by utilizing a deep reinforcement learning algorithm, establishing a Q network of a CNN+DNN structure, training the Q network, using the trained Q network to make action decisions, and acquiring the best action strategy. According to the dynamic beam scheduling method, a satellite directly outputs a current beam scheduling result according to the environment state at the moment through a large amount of autonomous learning, maximizes the overall performance of the system in the long term, and greatly reduces the transmission waiting delay of the data packets while keeping the system throughput almost unchanged.

A method for accelerating data acquisition in MRI with N-dimensional spatial encoding has a first method step in which a transverse magnetization within an imaged object volume is prepared having a non-linear phase distribution. Primary spatial encoding is thereby effected through application of switched magnetic fields. Two or more RF receivers are used to simultaneously record MR signals originating from the imaged object volume, wherein, for each RF receiver, an N-dimensional data matrix is recorded which is undersampled by a factor Ri per selected k-space direction. Data points belonging to a k-space matrix which were not recoded by a selected acquisition schema are reconstructed using a parallel imaging method, wherein reference information concerning receiver coil sensitivities is extracted from a phase-scrambled reconstruction of the undersampled data matrix. The method generates a high-resolution image free of artifacts in a time-efficient manner by improving data sampling efficiency and thereby reducing overall data acquisition time.

The invention discloses a bilateral constraint self-adaptive wavebeam forming method for a multiple-input-multiple-output (MIMO) radar, which can constrain both transmitting signals and receiving signals. Firstly, a plurality of transmitting signal data can be recorded, and the corresponding echo signals can be sampled, all vectors which are obtained by the recorded transmitting signal data and the sampled echo signals are respectively ranked by row to form a data matrix, and an optimal weight vector required for forming the wavebeam is calculated by the dual iterative calculation method, finally, the calculated optimal weight can be used to form the wavebeam. The method can overcome the shortcomings of large sample number and complex calculation in traditional self-adaptive wavebeam-forming method which is applied to the MIMO radar. Compared with the traditional self-adaptive wavebeam-forming method, the obtained antenna array pattern is provided with lower side lobe and better wavebeam shape preserving ability. The performance by using the method to perform Doppler frequency detection for movable object after the received MIMO radar data is filtered in spatial field also exceeds that of the traditional self-adaptive wavebeam-forming method.

A forecasting apparatus for predicting future events includes a forecast processing data configuring section for configuring a data matrix including previously accumulated historical data and unknown forecast data, the data matrix having the unknown forecast data as missing elements, and a forecast processing section for estimating values of the missing elements representative of the unknown forecast data by performing singular value decomposition of the data matrix configured by the forecast processing data configuring section.

A method, apparatus and computer program product are provided for identifying an unknown subject using face recognition. In particular, upon receiving a plurality of images depicting a subject, the method may include deriving and storing a common component image and a gross innovation component image associated with the subject, wherein the subject can later be identified in a new image using these two stored images. The common component image may capture features that are common to all of the received images depicting the subject, whereas the gross innovation component image may capture a combination of the features that are unique to each of the received images. The method may further include deriving and storing a low-rank data matrix associated with the received images, wherein the low-rank data matrix may capture any illumination differences and / or occlusions associated with the received images.

An accelerated erasure coding system includes a processing core for executing computer instructions and accessing data from a main memory, and a non-volatile storage medium for storing the computer instructions. The processing core, storage medium, and computer instructions are configured to implement an erasure coding system, which includes: a data matrix for holding original data in the main memory; a check matrix for holding check data in the main memory; an encoding matrix for holding first factors in the main memory, the first factors being for encoding the original data into the check data; and a thread for executing on the processing core. The thread includes: a parallel multiplier for concurrently multiplying multiple entries of the data matrix by a single entry of the encoding matrix; and a first sequencer for ordering operations through the data matrix and the encoding matrix using the parallel multiplier to generate the check data.

A system and method for machining data management is provided. Vibration and operation data are gathered from a machine tool and sent to a processing unit. The processing unit defines operation-specific vibration profiles, and generates an operation-specific data line for each profile. The data lines are stored in a memory for later retrieval. An output device is used to retrieve the data lines and plot them over a time domain to create an operation-specific data matrix useful in manufacturing operations analysis.

This invention discloses a group of instructions, block4 and block4v, in a matrix processor 16 that rearranges data between vector and matrix forms of an A×B matrix of data 120 where the data matrix includes one or more 4×4 sub-matrices of data 160-166. The instructions of this invention simultaneously swaps row or columns between the first 140, second 142, third 144, and fourth 146 matrix registers according to the instructions that perform predefined matrix tensor operations on the data matrix that includes one of the following group of operations: swapping rows between the different individual matrix registers, or swapping columns between the different individual matrix registers. Additionally, successive iterations or combinations of the block4 and or block4v instructions perform standard tensor matrix operations from the following group of matrix operations: transpose, shuffle, and deal.

The invention discloses a near infrared spectrum analyzing method based on the isolated component analysis and genetic neural network, which comprises the following steps for the acquired near infrared spectrum: firstly, effectively compressing spectrum data by using wavelet transform; secondly, extracting an independent component and a corresponding mixed coefficient matrix of a near infrared spectrum data matrix by using an isolated component analysis method; thirdly, building a three-layer BP neutral network, using the mixed coefficient matrix of a training sample as the input and correspondingly measured component concentration matrix as the output, and optimizing a neutral network structure by adopting a genetic algorithm, and obtaining a GA-BP neutral network by the training of the training sample; fourthly, predicting and analyzing the measured component concentration of the predicted set sample by using the GA-BA neutral network. The method enriches the chemical measurement method, widens the application range of the isolated component analysis and has favorable application prospect.

A secret sharing apparatus according to the present invention is based on a (k,n)-threshold scheme with a threshold of at least 4. The secret sharing apparatus generates a generator matrix (G) of GF(2) in which any k of n column vectors are at a full rank, divides secret information into n−1 pieces to generate divided secret data (K(1), . . . , K(n−1)), generates random data (U(0,1), . . . , U(k−2,n−1)), calculates the product of matrixes of the divided secret data, the random data, and the generator matrix (G), assigns the j×(n−1)+ith column of the calculation result to sharing partial data (D(j,i)) to calculate sharing partial data (D(j,1)), generates header information (H(j)), and individually distributes n pieces of sharing information (D(0), . . . , D(n−1)) made up of the header information (H(j)) and sharing partial data (D(j,i)) to n storage apparatuses.

A unified system for the structured collection, management, translation, and publication of multi-lingual information that is based on industry standards for information structures. Self-contained information units are stored in a single source and mapped onto a multiple dimensional data matrix in which the axes represent information types, objects, variants, and language. Linking through the matrix to a unique storage location for information facilities data entry, editing, access control, quality control, and automated publication of stored information.