According to one embodiment, a calculating device includes a nonlinear oscillator. The nonlinear oscillator includes a circuit part including a first Josephson junction and a second Josephson junction, and a conductive member including a first terminal. An electrical signal is input to the first terminal. The electrical signal includes a first signal in a first operation. The first signal includes a first frequency component having a first frequency, and a second frequency component having a second frequency. The first frequency is 2 times an oscillation frequency of the nonlinear oscillator. An absolute value of a difference between the first frequency and the second frequency is not more than 0.3 times the first frequency.

An embodiment includes a combine having a feeder housing for receiving harvested crop, a separating system for threshing the harvested crop to separate grain from residue, a grain bin for storing the separated grain, a bin level sensor for detecting grain in the grain bin; and a controller that controls the combine. The controller is configured to generate a usable operating range by discarding a selected range of values from an operating range of the bin level sensor, generate a shifted operating range by shifting the usable operating range by a shift value, receive a first value indicating a level of grain in the grain bin, generate a second value by shifting the first value by the shift value, and present the second value to an operator of the combine.

A method of improving sustainable agriculture includes collecting machine data, determining a sustainability measure, and providing a sustainability recommendation. A computing system includes a processor and a memory storing instructions that, when executed by the processor, cause the computing system to collect machine data; determine a sustainability measure; and provide a sustainability recommendation. A non-transitory computer readable medium contains program instructions that when executed, cause a computer to collect machine data; determine a sustainability measure; and provide a sustainability recommendation.

An operator's proximity to an automotive vehicle being inspected is tracked and recorded. An audio and/or a visual representation of the automotive vehicle being inspected, inspection zones, and components within the inspection zones are rendered. A representation of the automotive vehicle being inspected is updated to reflect a condition of the vehicle being inspected, a condition of the inspection zones, and the numbers of defects for each of inspection zones. The audio and visual representations shown as part of any defects of the vehicle being inspected may be recorded. During a vehicle inspection, a visual indication of a driver's location in proximity to a visual representation of the automotive vehicle being inspected may be displayed.

A vehicle control device includes a braking unit 15 for braking a vehicle, an obstacle detection sensor for detecting an obstacle in front of the vehicle, a braking control unit for controlling a braking of the vehicle by the braking unit on the basis of a detection condition of the obstacle, an acquisition unit for acquiring position information indicating a position of the vehicle, and a storage control unit for storing, in a storage unit, braking history information that includes the position information acquired when the braking of the vehicle is performed by the braking unit under control of the braking control unit.

Systems and methods for distributed training of deep learning models are disclosed. An example local device to train deep learning models includes a reference generator to label input data received at the local device to generate training data, a trainer to train a local deep learning model and to transmit the local deep learning model to a server that is to receive a plurality of local deep learning models from a plurality of local devices, the server to determine a set of weights for a global deep learning model, and an updater to update the local deep learning model based on the set of weights received from the server.

A method for operating a brake system of a motor vehicle includes actuating a first actuating device of the brake system, exerting an electromechanical braking force to decelerate the motor vehicle in an event of a fault in the hydraulic braking device and when the first actuating device is actuated, and generating the electromechanical braking force after a start of the actuation of the first actuating device for a minimum generation period and/or generating the electromechanical braking force after an end of the actuation of the first actuating device for an additional continued generation period. The brake system includes a hydraulic braking device, an electromechanical braking device, and a first actuating device, in particular a brake pedal.

A peer network may include nodes corresponding to different clinicians. An edge may interconnect the two nodes based on the corresponding clinicians sharing at least one common attribute such as for example, treating the same patients and/or interacting with the same medical devices. A machine-learning model may be applied to identify, in the peer network, one or more peer communities of clinicians. The activity pattern of a clinician may be compared to the activity patterns of other clinicians in the same peer community to determine whether that clinician exhibits anomalous behavior. An investigative workflow may be triggered when the clinician is determined to exhibit anomalous behavior. The investigative workflow may include generating an alert, activating surveillance devices, and/or isolating medication accessed by the clinician.

The present disclosure provide a method for recognizing a space frequency block code (SFBC), including: obtaining a cross-correlation function of a reception signal, and obtaining a Fourier transformation of the cross-correlation function; obtaining data containing labels by labeling a sample containing a real part and an imaginary part of the Fourier transformation, and inputting the data containing labels into an initial CNN-LSTM network for training until convergence is reached, to obtain a final CNN-LSTM network; and obtaining unlabeled data to be recognized, and inputting the data to be recognized into the final CNN-LSTM network to obtain a SFBC recognition result.

A traction control system for a pallet truck includes a traction motor, an operator controlled input device configured to selectively accelerate the pallet truck in both a forward direction of vehicle travel and a reverse direction of vehicle travel, and an operator controlled actuation device configured to place the pallet truck in an auxiliary mode of operation. A vehicle controller may monitor a speed of the pallet truck and, in response to receiving an actuation signal, command the traction motor to maintain the speed of the pallet truck at an intermediate rate of travel without actuation of the operator controlled input device.