Computer processing and outcome prediction systems and methods used to generate algorithm time prediction polynomials, inverse algorithm time prediction polynomials, determine race conditions, determine when a non-linear algorithm can be treated as if it were linear, as well as automatically generate parallel and quantum solutions from classical software or from the relationship between monotonic attribute values.

In data communications, a suitably designed contrast coding scheme, comprising a process of contrast encoding (108) at a transmitter end (101) and a process of contrast decoding (120) at a receiver end (103), may be used to create contrast between the bit error rates BERs experienced by different classes of bits. Contrast coding may be used to tune the BERs experienced by different subsets of bits, relative to each other, to better match a plurality of forward error correction FEC schemes (104, 124) used for transmission of information bits (102), which may ultimately provide a communications system (100) having a higher noise tolerance, or greater data capacity, or smaller size, or lower heat.

An apparatus for detecting leakage of a pipe by using a distance difference-frequency analysis includes: vibration detecting sensors, which are mounted at a predetermined distance in a longitudinal direction of a pipe and are configured to measure vibration signals of the pipe; and a control unit, which is configured to calculate a cross-correlation function by using the vibration signals, to reveal time delay information in the frequency domain by calculating time-delay frequency analysis diagram for the cross-correlation function, to calculate a distance difference-frequency analysis diagram by applying compensation conversion using frequency-dependent propagation speed information to the time-delay frequency analysis diagram, and to detect a leakage component of the pipe in the distance difference-frequency analysis diagram.

Data analysis for structural health monitoring relating to a method of modal identification for structures with non-proportional damping based on extended sparse component analysis. Hilbert transform constructs analytical signal of acceleration response. Analytical signal is transformed into time-frequency domain using short-time-Fourier transform. The criterion is taken as the correlation coefficient of adjacent frequency points is close to 1. Points contributed by only one mode are detected from the time-frequency plane. Phases calculated at single-source-points are used to remove local outliers through local outlier factor method. Amplitudes of complex-valued mode shapes are estimated by Hierarchical clustering of amplitudes for time-frequency coefficients at single-source-points. Averaged phases of grouped single-source-points are estimated phases of complex-valued mode shapes. Finally, complex-valued mode shapes are acquired. Modal responses are estimated by sparse reconstruction method. This method extends application range of sparse component analysis method, and can identify complex modes of non-proportionally damped structures.

A method of controlling a robot within a volume, the method comprising: receiving a three dimensional model including a model of the robot and a model of the volume in which the robot is configured to move within; defining a plurality of positions within the model of the volume to which the robot is moveable to, the plurality of positions being identified by an operator; receiving scanned three dimensional data of the robot and at least a part of the volume; determining a transformation algorithm using the three dimensional model and the scanned three dimensional data; applying the transformation algorithm to one or more positions of the plurality of positions to provide one or more transformed positions; and controlling movement of the robot using one or more of the transformed positions.

A method of analyzing a vibratory signal derived from rotation of at least one moving part belonging to a rotary mechanism forming all or part of a drive train for transmitting drive torque, the rotary mechanism being fitted to an aircraft and the method comprising at least one first measurement step including measuring vibration in at least one direction and generating a vibratory signal representative of the operation of the rotary mechanism as a function of time, the first measurement step being performed by means of at least one vibration sensor; and at least one second measurement step including measuring an angular position of the moving part, the moving part having at least one degree of freedom to move in rotation about a respective axis of rotation Z. Such an analysis method makes it possible to determine at least one usable range for the vibratory signal.

The present disclosure provides a method for ultrafastly obtaining a two-dimensional J-resolved NMR spectrum with a high-resolution against an inhomogeneous magnetic field. The method utilizes the selective excitation module and the reunion sampling module jointly, which breaks through the limitations of existing methods for obtaining the two-dimensional J-resolved NMR spectrum and effectively eliminates an influence of the inhomogeneous magnetic field along an encoding direction. At the same time, an inhomogeneous magnetic field along x and y directions is theoretically eliminated by a slow rotation of the sample. As a consequence, a two-dimensional J-resolved NMR spectrum with a high resolution is obtained by a single-scanning sampling under the inhomogeneous magnetic field, thus significantly shortening experimental duration and expanding application fields of the two-dimensional J-resolved NMR spectrum. The present disclosure further provides a method using multi-band sampling, which is used to obtain J-resolved NMR spectrum with improved signal-to-noise ratio.

An apparatus for detecting leakage of a pipe by using a distance difference-frequency analysis includes: vibration detecting sensors, which are mounted at a predetermined distance in a longitudinal direction of a pipe and are configured to measure vibration signals of the pipe; and a control unit, which is configured to calculate a cross-correlation function by using the vibration signals, to reveal time delay information in the frequency domain by calculating time-delay frequency analysis diagram for the cross-correlation function, to calculate a distance difference-frequency analysis diagram by applying compensation conversion using frequency-dependent propagation speed information to the time-delay frequency analysis diagram, and to detect a leakage component of the pipe in the distance difference-frequency analysis diagram.

Data analysis for structural health monitoring, relating to a method of estimating the number of modes for sparse component analysis based structural modal identification. First, structural responses are transformed into time-frequency domain using short-time Fourier transform method. Single-source-point detection method is applied to the time-frequency coefficients to pick out the single-source-points where only one mode makes contribution. The single-source-point vectors are normalized to the upper half unit circle. Three statistics are given to analyze the statistical property. The suggested number of subintervals is given. Through counting, the approximate probabilities in subintervals are calculated and then smoothed through the weighted average procedure. The local maximum values of the averaged probability curve are detected and the number of active modes is equal to the number of local maximum values.

The present invention discloses an automatic modulation classification method based on deep learning network fusion, comprising: acquiring a WBFM sample signal within a data set RML 2016.10a, and selecting a proper threshold ? to separate a WBFM signal during a silence period; expanding a new WBFM signal to 1000 by adopting a data enhancement method, and expanding an original data set; dividing the data set expanded in the step S2 into a training set, a verification set and a test set; respectively calculating amplitude, phase and a fractional order Fourier transformation result for data in the step S3; building a multi-channel feature fusion network model composed of an LSTM network and an FPN network; performing network model training, after the end of training, inputting verification set data into a trained network model for verification, and calculating prediction accuracy; and performing parameter fine adjustment on the network model through said test set, improving prediction precision, and taking a final model as an automatic modulation classification model. The present invention enables the improvement to the average classification accuracy rate of communication signals.