Abstract: A cognitive radio device may include an RF receiver configured to receive interfering RF signals, an RF transmitter configured to be selectively operated, a quantum computing circuit configured to perform quantum subset summing, and a processor. The processor may be configured to generate a game theory reward matrix for a plurality of different deep learning models, cooperate with the quantum computing circuit to perform quantum subset summing of the game theory reward matrix, select a deep learning model from the plurality thereof based upon the quantum subset summing of the game theory reward matrix, and process the received interfering RF signals using the selected deep learning model for selectively operating the RF transmitter.

Abstract: A perturbation radio frequency (RF) signal generator is provided which generates a perturbed RF output signal to cause a signal classification change by an RF signal classifier. The perturbation RF signal generator may include a quantum computing circuit configured to perform quantum subset summing; and a processor. The processor may be configured to generate a game theory reward matrix for a plurality of different deep learning signal perturbation models, cooperate with the quantum computing circuit to perform quantum subset summing of the game theory reward matrix, select a deep learning signal perturbation model from the plurality thereof based upon the quantum subset summing of the game theory reward matrix, and generate the perturbed RF output signal based upon the selected deep learning signal perturbation model to cause the signal classification change in the RF signal classifier.

Abstract: A hydraulic tool that executes a sequence of operations includes: a motor; a pump; hydraulic fluid driven by the pump; a chamber in fluid communication with the hydraulic fluid; a ram movably positioned at least partially in the chamber according to the hydraulic fluid and pressure thereof; a primary trigger configured to cause, upon actuation thereof, activation of the motor thereby causing: the pump to move hydraulic fluid from the reservoir into the ram chamber, extending the ram; a control system; and at least one sensor in communication the control system. When the primary trigger is user actuated and the ram is fully extended or the tool is clamped around a work piece, the pump continues to pump fluid, under at least partial control by the control system, until a threshold condition is determined by the at least one control system using the at least one sensor.

Abstract: A change detection device may include a variational autoencoder (VAE) configured to encode image data to generate a latent vector and decode the latent vector to generate new image data, at least one quantum computing circuit configured to perform quantum subset summing, and a controller. The controller may be configured to cooperate with the at least one quantum computing circuit to generate a quantum reward matrix for a plurality of quantum neural network models using the at least one quantum computing circuit, select a quantum neural network model from the plurality of quantum neural network models based upon the new image data and the quantum reward matrix, and process the new image data using the selected quantum neural network model to detect changes therein.

Abstract: An object detection device may include a variational autoencoder (VAE) configured to encode image data to generate a latent vector, and decode the latent vector to generate new image data, at least one quantum computing circuit configured to perform quantum subset summing, and a processor. The processor may be configured to cooperate with the at least one quantum computing circuit to train a plurality of deep learning models based upon a Quantum Neural Network (QNN), generate a game theory reward matrix for the plurality of deep learning models, perform quantum subset summing of the game theory reward matrix, select a deep learning model from the plurality thereof based upon the quantum subset summing of the game theory reward matrix, and process the new image data using the selected deep learning model for object detection.

Abstract: A radio frequency (RF) signal classification device may include an RF receiver configured to receive RF signals, a quantum computing circuit configured to perform quantum subset summing, and a processor. The processor may be configured to generate a game theory reward matrix for a plurality of different deep learning models, cooperate with the quantum computing circuit to perform quantum subset summing of the game theory reward matrix, select a deep learning model from the plurality thereof based upon the quantum subset summing of the game theory reward matrix, and process the RF signals using the selected deep learning model for RF signal classification.

Abstract: Systems and methods are described for denoising, or filtering out, unwanted noise or interference, from biological or physiological parameter signals or waveforms such as ECG signals caused by application of electromagnetic energy (e.g., electrical stimulation) in a vicinity of sensors configured to obtain the biological or physiological parameter signals.

Abstract: A quantum computing circuit may include a plurality of column subset qubit registers and a plurality of row subset qubit registers, a reward matrix register configured to receive a reward matrix, and an adder coupled to the column subset qubit registers, the row subset qubit registers, and the reward matrix register. The adder may be configured to perform subset summing to generate reward matrix sums from column and row subset qubits and the reward matrix. The quantum computing circuit may further include a plurality of row action qubit registers, and a comparator coupled to the adder and the row action qubit registers and configured to generate an output based thereon.

Abstract: Diagnostic devices can be used for diagnosing lymphedema. The diagnostic devices may include an array of sensors, which can at least include a durometer, temperature sensor, and dielectric sensor, to measure parameters of tissue. The measurements may be used to generate a tissue health score to diagnose lymphedema and monitor tissue heath.

Abstract: A cognitive radio device may include a radio frequency (RF) detector operable over an RF spectrum, an RF jammer having a selectable jamming frequency window within the RF spectrum, and a controller. The controller may be configured to cooperate with the RF detector and RF jammer to detect an RF transmission, determine different Quadratic Unconstrained Binary Optimization (QUBO) inputs based upon the detected RF transmission, process the QUBO inputs with a QUBO objective function to determine a new jamming frequency window, and operate the RF jammer at the new jamming frequency window.

Abstract: An object detection device may include a variational autoencoder (VAE) configured to encode image data to generate a latent vector, and decode the latent vector to generate new image data. The object detection device may also include a quantum computing circuit configured to perform quantum subset summing, and a processor. The processor may be configured to generate a game theory reward matrix for a plurality of different deep learning models, cooperate with the quantum computing circuit to perform quantum subset summing of the game theory reward matrix, select a deep learning model from the plurality thereof based upon the quantum subset summing of the game theory reward matrix, and process the new image data using the selected deep learning model for object detection.

Abstract: A cognitive radio device may include a radio frequency (RF) detector operable over an RF spectrum, an RF transmitter having a selectable hopping frequency decoy window within the RF spectrum, and a controller. The controller may be configured to cooperate with the RF detector and RF transmitter to detect a jammer signal affecting a current hopping frequency decoy window, determine different Quadratic Unconstrained Binary Optimization (QUBO) inputs based upon the detected jammer signal, process the QUBO inputs with a QUBO objective function to determine a new hopping frequency decoy window, and operate the RF decoy transmitter at the new hopping frequency decoy window.

Abstract: A cognitive radio device may include a radio frequency (RF) detector operable over an RF spectrum, an RF transmitter having a selectable hopping frequency window within the RF spectrum, and a controller. The controller may be configured to cooperate with the RF detector and RF transmitter to detect a jammer signal affecting a current hopping frequency window, determine different Quadratic Unconstrained Binary Optimization (QUBO) inputs based upon the detected jammer signal, process the QUBO inputs with a QUBO objective function to determine a new hopping frequency window, and operate the RF transmitter at the new hopping frequency window.

Abstract: A computational fluid dynamics system may include a quantum computing circuit and a processor. The processor may be configured to generate and store a union mesh table representing a plurality of point groups, with at least some points being shared among different groups, and each point having a same property. The processor may be further configured to cooperate with the quantum computing circuit to perform a fluid dynamic computation based on a streaming fluid velocity vector and the union mesh table.

Abstract: A hydraulic tool that executes a sequence of operations includes: a motor; a pump; hydraulic fluid driven by the pump; a chamber in fluid communication with the hydraulic fluid; a ram movably positioned at least partially in the chamber according to the hydraulic fluid and pressure thereof; a primary trigger configured to cause, upon actuation thereof, activation of the motor thereby causing: the pump to move hydraulic fluid from the reservoir into the ram chamber, extending the ram; a control system; and at least one sensor in communication the control system. When the primary trigger is user actuated and the ram is fully extended or the tool is clamped around a work piece, the pump continues to pump fluid, under at least partial control by the control system, until a threshold condition is determined by the at least one control system using the at least one sensor.

Abstract: An image pixel classification device may include a quantum computing circuit configured to perform quantum subset summing, and a processor. The processor may be configured to generate a pairwise game theory reward matrix for a plurality of different classes of an image pixel, with each class corresponding to a respective type of land feature from among a plurality of different types of land features, cooperate with the quantum computing circuit to perform quantum subset summing on the pairwise game theory reward matrix. The processor may further select a class for the image pixel based upon the quantum subset summing, and classify the image pixel as the corresponding type of land feature for the selected class.

Abstract: Systems and methods for managing patient temperature are disclosed. Temperature management systems that are suitable for an out-of-hospital setting are disclosed. Temperature management systems having a low power requirement are disclosed. Temperature management systems that include a disposable, single-use reservoir are disclosed.

Abstract: The disclosure describes various aspects of an automated external defibrillator (AED) system, including shock generating electronics, a battery configured for providing power to the shock generating electronics, power management circuitry configured for managing the shock generating electronics and the battery, at least one environmental sensor configured for monitoring environmental conditions in which the AED system is placed, and a controller configured for controlling the power management circuitry and the at least one environmental sensor. The at least one environmental sensor includes a temperature sensor configured for providing a temperature measurement, and the controller is further configured for adjusting operations of the power management circuitry in accordance with the temperature measurement provided by the temperature sensor. The disclosure further describes associated methods of using the AED system.

Abstract: An object detection device may include a variational autoencoder (VAE) configured to encode image data to generate a latent vector, and decode the latent vector to generate new image data. The object detection device may also include a quantum computing circuit configured to perform quantum subset summing, and a processor. The processor may be configured to generate a game theory reward matrix for a plurality of different deep learning models, cooperate with the quantum computing circuit to perform quantum subset summing of the game theory reward matrix, select a deep learning model from the plurality thereof based upon the quantum subset summing of the game theory reward matrix, and process the new image data using the selected deep learning model for object detection.

Abstract: Systems and methods for managing patient temperature are disclosed. Temperature management systems that are suitable for an out-of-hospital setting are disclosed. Temperature management systems having a low power requirement are disclosed. Temperature management systems that include a disposable, single-use reservoir are disclosed.