Abstract: The present disclosure generally relates to providing a centralized controller for actuators within electronic control systems of a vehicle. An electronic control system within a vehicle computer system, having a first actuator for performing a first vehicle function, a second actuator for a performing second vehicle function and a controller coupled to the first actuator and the second actuator for controlling the first and second actuators is provided such that the controller is not embedded in either the first or second actuator. Embodiments of a centralized controller and a non-transitory machine-readable medium on which a program is stored for providing instructions to a controller that may utilize the 1-Wire® and/or PoE protocols are also provided. Advantages include, but are not limited to centralized manufacturing, simplified diagnostics, and streamlined software upgrades, all of which result in reduce costs.

Abstract: The present disclosure relates to a device for predicting, detecting, monitoring, and controlling epilepsy and methods thereof. In particular, the present disclosure relates to early detection and control of epileptic seizures using sensor-based device. In some embodiments, the sensor-based device is wearable.

Abstract: Temperature-regulating fabrics composed of natural fibers that are wearable in all seasons and provide high-performance thermal regulation and excellent wicking and absorbency properties. The temperature-regulating natural fabrics disclosed herein are composed of a blend of cotton, hemp, and linen present in an amount of between 84% and 100% of the total composition. In some embodiments, the temperature-regulating natural fabric displays a high amount of stretch and a low amount of growth.

Abstract: Systems and methods for measuring cross-modal similarity between mass spectra and peptides are provided. A deep learning network can be used and, by training on a variety of labeled spectra, the network can embed both spectra and peptides onto a Euclidean subspace where the similarity is measured by the L2 distance between different points. The network can be trained on a novel loss function, which can calculate the gradients from sextuplets of data points.

Abstract: The present disclosure generally relates to providing a centralized controller for actuators within electronic control systems of a vehicle. An electronic control system within a vehicle computer system, having a first actuator for performing a first vehicle function, a second actuator for a performing second vehicle function and a controller coupled to the first actuator and the second actuator for controlling the first and second actuators is provided such that the controller is not embedded in either the first or second actuator. Embodiments of a centralized controller and a non-transitory machine-readable medium on which a program is stored for providing instructions to a controller that may utilize the 1-Wire® and/or PoE protocols are also provided. Advantages include, but are not limited to centralized manufacturing, simplified diagnostics, and streamlined software upgrades, all of which result in reduce costs.

Abstract: A method includes adapting the universal generative model of local descriptors to a first camera to obtain a first camera-dependent generative model. The same universal generative model is also adapted to a second camera to obtain a second camera-dependent generative model. From a first image captured by the first camera, a first image-level descriptor is extracted, using the first camera-dependent generative model. From a second image captured by the second camera, a second image-level descriptor is extracted using the second camera-dependent generative model. A similarity is computed between the first image-level descriptor and the second image-level descriptor. Information is output, based on the computed similarity. The adaptation allows differences between the image-level descriptors to be shifted towards deviations in image content, rather than the imaging conditions.

Abstract: A method includes adapting the universal generative model of local descriptors to a first camera to obtain a first camera-dependent generative model. The same universal generative model is also adapted to a second camera to obtain a second camera-dependent generative model. From a first image captured by the first camera, a first image-level descriptor is extracted, using the first camera-dependent generative model. From a second image captured by the second camera, a second image-level descriptor is extracted using the second camera-dependent generative model. A similarity is computed between the first image-level descriptor and the second image-level descriptor. Information is output, based on the computed similarity. The adaptation allows differences between the image-level descriptors to be shifted towards deviations in image content, rather than the imaging conditions.