Abstract: A method of dry reforming of methane (CH4) is provided. The method includes contacting at a temperature of 500 to 1000 degree Celsius (° C.) a reactant gas mixture including methane and carbon dioxide (CO2) with a bimetallic supported catalyst. The bimetallic supported catalyst includes a porous catalyst support and a bimetallic catalyst. The porous catalyst support includes aluminum oxide (Al2O3) and magnesium oxide (MgO). The bimetallic catalyst includes nickel (Ni) and copper (Cu) disposed on the porous catalyst support. The method further includes collecting a product gas mixture including hydrogen (H2) and carbon monoxide (CO). The bimetallic supported catalyst includes 8 to 16 weight percent (wt. %) nickel and 2 to 14 wt. % copper, each based on a total weight of bimetallic supported catalyst.

Abstract: A method of dry reforming of methane (CH4) is provided. The method includes contacting at a temperature of 500 to 1000 degree Celsius (° C.) a reactant gas mixture including methane and carbon dioxide (CO2) with a bimetallic supported catalyst. The bimetallic supported catalyst includes a porous catalyst support and a bimetallic catalyst. The porous catalyst support includes aluminum oxide (Al2O3) and magnesium oxide (MgO). The bimetallic catalyst includes nickel (Ni) and copper (Cu) disposed on the porous catalyst support. The method further includes collecting a product gas mixture including hydrogen (H2) and carbon monoxide (CO). The bimetallic supported catalyst includes 8 to 16 weight percent (wt. %) nickel and 2 to 14 wt. % copper, each based on a total weight of bimetallic supported catalyst.

Abstract: Systems and methods include a reduced computation, computer-based management of point-of-care (POC) on-site ultrasound (ULS) imaging resources. At a digital computation resource of a POC site, a ULS tissue reflection sample data is received from a hand-held ULS scanning device. A digital computation resource of the POC site, applies a reduced computation tissue ULS reflection speckle noise (SN) physics model—blurring noise (BN) physics model based deep learning (DL) trained convolutional neural network (CNN) denoising process to the ULS tissue reflection sample data outputting an estimated denoised ULS tissue reflection image data. A visual rendering of the estimated denoised ULS tissue reflection image data is displayed on a display resource of the POC site.

Abstract: Examples include receiving and storing samples of target frequency bands filtered from EEG measurement of a subject's brain waves in an NFB training session. In an example, upon storing a time window of the samples, unsupervised adaptive adjusting an NFB reward threshold is automatic. The adjusting includes, in examples, determining neuromarker values in the time window, which indicate peak values of the target frequency bands over the time window. The adjusting computes the mean value of the neuromarker values and, utilizing same, automatically proceeds to unsupervised computing an adaptive adjusted reward threshold. The unsupervised computing, in examples, includes a multiplication product of a reward threshold adjustment factor, a training protocol value, and the computed mean value of the neuromarker values. Examples proceed to communicating the adaptive adjusted reward threshold to a controller for threshold based feedback reward to the NBF subject.

Abstract: Methods, systems and wearable devices for real-time mental stress assessment are provided. The methods and systems employ deep learning using a Gated Recurrent Unit (GRU) gating mechanism in a recurrent neural network with a sliding window approach applied to raw EEG data.

Abstract: A device, method, and non-transitory computer readable medium to perform a method of blind equalization implemented by a filter bank multi-carrier with offset quadrature amplitude modulation (FBMC-OQAM) transmission system. A first matrix W is obtained by dividing a second matrix V by a receiver waveform matrix G. The second matrix V is obtained by calculating a total objective function J until the total objective function J is either constant or below a threshold error margin. The calculation of the total objective function J includes iterating calculations with a plurality of combination of a frequency bin p and a time slot q. Weights of the obtained first matrix W are applied to an equalizer. A received signal in the equalizer is processed using the applied weights. The weights of the obtained first matrix W are configured to minimize a total outage probability Pout, TOTAL.

Abstract: Memristor based chaotic oscillators exhibit complex dynamics. They are often chosen for secure communication owing to their interesting feature. In chaos-based secure communication applications using the master-slave configuration, synchronization is a central issue. Most of the synchronization methods proposed in the literature are asymptotic. In practice, it is desirable that synchronization be established in a predefined time. This invention provides new developments in the design of high-gain observers with an unknown input dedicated for predefined-time synchronization of memristor based chaotic systems. The proposed predefined-time extended high gain observer is constructed on the basis of a time-dependent coordinates transformation based on modulating functions that annihilate the effect of initial conditions on the synchronization time. Both noise-free channel and noisy channel are considered. Simulations performed on a numerical example illustrated the efficiency of proposed approaches.

Abstract: A method of treating a landfill leachate containing ammoniacal nitrogen and phosphate by mixing with seawater to precipitate magnesium ammonium phosphate (MAP) also known as struvite. Effects of pH, temperature, stirring speed, and magnesium to ammonia molar ratio on leachate properties such as COD, ammoniacal nitrogen, phosphate content, color, turbidity, amount of magnesium, iron and zinc are disclosed. The method provides high removal efficiency for removal of ammoniacal nitrogen, phosphate, COD, color and turbidity. The method provides a cost-effective system for treatment of landfill leachate and recovery of MAP.

Abstract: A filter bank multi-carrier (FBMC)-offset quadrature amplitude modulation (OQAM) system is disclosed. The FBMC-OQAM system includes a processing circuitry which is configured to receive a signal over a transmission medium, equalize the signal by a convolution neural network (CNN) equalizer, wherein the CNN equalizer is configured to estimate the received signal without performing channel estimation, and output the estimated signal as a bit stream.

Abstract: A method is provided of optimizing multi-cell association for a downlink multi-user, multiple-input, multiple-output (MU-MIMO) system that includes a plurality of base stations corresponding to C number of cells which serve K user terminals. Each user terminal connects with at least two cells. The method includes determining which cells for each user to connect with based on minimizing an objective function that is dependent on at least weight parameters for each kth user connected to each cth cell. Based on the determination, the user terminals are connected to their respective cells and the weight parameters are applied toward a beamforming configuration for the plurality of base stations. A device is also provided having processing circuitry configured to perform the method.

Abstract: Beamformers and beamforming methods are disclosed which involve diagonal loading (regularization). Features may include the automatic determination of the regularization parameter using a linearly constrained minimum power (LCMP) bounded perturbation regularization (BPR) approach.

Abstract: A speaker identification system and method to identify a speaker based on the speaker's voice is disclosed. In an exemplary embodiment, the speaker identification system comprises a Gaussian Mixture Model (GMM) for speaker accent and dialect identification for a given speech signal input by the speaker and an Artificial Neural Network (ANN) to identify the speaker based on the identified dialect, in which the output of the GMM is input to the ANN.

Abstract: A method and system that includes a wearable device having a plurality of EEG sensors to detect an EEG signal in a window of a predetermined length, a bandpass filter to remove frequency bands of the EEG signal to obtain a combined signal of remaining frequency bands, and a wireless device connection for wireless transmission of information from the wearable device. The information including the EEG signal and the combined signal. A mobile device includes a communication device for receiving the transmitted information, at least one processor for processing a machine learning model. The machine learning model classifies the combined signal to obtain a classification result of mental stress or not mental stress, and a display device displays a mental stress assessment based on the EEG signal and the classification result.

Abstract: A method and system for set point control of a liquid level in a conical tank is disclosed. The method includes receiving set point signal, R(s), summing the set point signal, R(s), with a negative feedback signal, d{tilde over (f)}(s), and generating set point error signal, E(s), which is used as feedback at the input to drive the liquid level in the conical tank to a desired set point, thus controlling the liquid level of conical tank so that external disturbance, df(s), is minimized.

Abstract: A method and system that includes a wearable device having a plurality of EEG sensors to detect an EEG signal in a window of a predetermined length, a bandpass filter to remove frequency bands of the EEG signal to obtain a combined signal of remaining frequency bands, and a wireless device connection for wireless transmission of information from the wearable device. The information including the EEG signal and the combined signal. A mobile device includes a communication device for receiving the transmitted information, at least one processor for processing a machine learning model. The machine learning model classifies the combined signal to obtain a classification result of mental stress or not mental stress, and a display device displays a mental stress assessment based on the EEG signal and the classification result.

Abstract: Beamformers and beamforming methods involve diagonal loading (regularization). Significant features include the automatic determination of the regularization parameter using a linearly constrained minimum power (LCMP) bounded perturbation regularization (BPR) approach. More specifically, the method has the advantage of efficient beamforming when the desired signal is from a moving source. After determining an initial regularization parameter, each data window (i.e., snapshot) uses the regularization parameter of the prior window to recursively determine the next regularization parameter.

Abstract: A device, method, and non-transitory computer readable medium for identification of stress resilience. The method for identification of stress resilience includes stimulating a human subject by at least one of a plurality of stressful events in a virtual reality environment, acquiring multichannel real-time electroencephalograph (EEG) signals by an EEG monitor worn by a human subject, recording the real-time EEG signals received during the stressful event, transmitting the real-time EEG signals to a computing device. The computing device generates a plurality of filtered brain wave frequencies related to the stressful event by filtering the multichannel real-time EEG signals, classifies the brain wave frequencies by frequency level by applying the filtered brain wave frequencies to the deep learning model, applies each frequency level associated with the stressful event to the convolutional neural network, and identifies a level of stress resilience of the human subject associated with the stressful event.

Abstract: A method and system for set point tracking control of an nth order integer control system. A first feedback compensated input signal is generated from an input signal, r(t), and a first negative feedback signal. A fractional order controller generates a set point modified signal from the first feedback compensated input signal. A second feedback compensated input signal is generated from the set point modified signal and a second negative feedback signal. A process variable is generated from the second feedback compensated input signal and applied to a non-linear plant which is affected by a disturbance which carries over into an output signal, y(t). An extended state observer receives the process variable and the output signal and generates the first second negative feedback and the second negative feedback signal to cancel the disturbance.

Abstract: A device, method, and non-transitory computer readable medium for fractional order dynamic inversion control of nonlinear systems under the influence of a disturbance. The method for fractional order dynamic inversion control includes receiving a mathematical model of a controlled device, the mathematical model including a set of movement trajectories, wherein the movement trajectories include control objectives, formulating a first set of linear, time-varying, fractional order differential equations from the mathematical model, the first set including dynamic constraints on the control objectives, transforming the first set into linear equations by differentiating a norm measure function along the movement trajectories, thus generating a second set of fractional order differential equations, and determining a control signal for controlling the movement trajectories in the presence of disturbances by dynamically inverting the second set of fractional order differential equations.

Abstract: A method, system, and apparatus for a linear active disturbance rejection control with a fractional order integral (FOI-LADRC) action for set-point tracking of a process variable is disclosed. The FOI-LADRC method includes receiving and multiplying a reference signal by a first feedback signal, applying, by a set-point tracking controller, fractional order integration to the reference signal, amplifying and multiplying the reference signal by a series of second feedback signals and a third feedback signal, dividing the reference signal by a static gain, and generating a process control variable, inputting the process control variable and applying a disturbance to the plant to output an output signal, feeding back the output signal, as the first feedback signal, generating the series of second feedback signals and a third feedback signal by an extended state observer, ESO, and tuning the set-point tracking controller and the ESO to eliminate the disturbance, from the output signal.