Abstract: Examples disclosed herein relate to an autonomous driving system in an ego vehicle. The autonomous driving system includes a radar system configured to detect a target in a path and a surrounding environment of the ego vehicle and produce radar data with a first resolution that is gathered over a continuous field of view on the detected target. The system includes a super-resolution network configured to receive the radar data with the first resolution and produce radar data with a second resolution different from the first resolution using first neural networks. The system also includes a target identification module configured to receive the radar data with the second resolution and to identify the detected target from the radar data with the second resolution using second neural networks. Other examples disclosed herein include a method of operating the radar system in the autonomous driving system of the ego vehicle.

Abstract: Examples disclosed herein relate to a radar system in an autonomous vehicle for object detection and classification. The radar system has a radar module having a dynamically controllable beam steering antenna and a perception module. The perception module includes a machine learning module trained on a first set of data and retrained on a second set of data to generate a set of object locations and classifications, and a classifier to use velocity information combined with the set of object locations and classifications to output a set of classified data.

Abstract: A computer network implemented system for improving the operation of one or more biofeedback computer systems is provided.

Abstract: Systems and methods for setting service appointments in an automated conversation system, ensuring data fidelity, return on investment (ROI) analysis, accelerating response times, and scraping third party system to populate the conversation system are all provided. These systems and methods automatically schedules appointments for services, and performs all necessary follow-up activity, ensures target duplication isn't present in conversations, ensures that representatives are incorporated into the system, enhances speeds by altering processing, response generation and sending queues if timing won't meet goals, presents suitably noteworthy ROI metrics and scrapes a third party databases using phantom scripts. All this activity improves the automated conversation experience, and its ability to effectuate business objectives.

Abstract: An ion guide is disclosed that comprises a plurality of electrodes arranged to form a multipole ion guide and one or more rigid support members. The plurality of electrodes comprises one or more groups of electrodes, and each group of electrodes comprises plural electrodes that are axially spaced apart from one another. The electrodes of one or more groups of electrodes are attached to one of the one or more rigid support members. One or more of the electrodes comprises a curved metal sheet, plate or strip.

Abstract: The invention determines an efficiency value (E) denoting preferably the relative period of muscle fiber activity during a recorded period of exercise, and a strength value (S) representing the number of muscle fibers recruited during a movement as part of the exercise or of a muscle contraction, and a temporal value (T) representing the frequency with which muscle fibers are activated repeatedly during exercise, and finally combines the efficiency value (E), the strength value (S) and the temporal value (T) by a linear combination to obtain an index value (ESTi) indicative of the fitness level of the individual. The obtained ESTi Score is useful for assessing the training level of an animal or human individual and the individual's potential for different types of sports and other activity. Also the effect of past training or diet can be assessed, and the possible need for changes in training or diet can be assessed.

Abstract: A computer network implemented system for improving the operation of one or more biofeedback computer systems is provided.

Abstract: Examples disclosed herein relate to an autonomous driving system in an ego vehicle. The autonomous driving system includes a radar system to detect a target in a path and a surrounding environment of the ego vehicle and produce radar data with a first resolution that is gathered over a continuous field of view on the detected target. The system includes a recurrent super-resolution network having recurrent encoder layers to receive the radar data with the first resolution and produce radar data with a second resolution using first neural networks. The recurrent encoder layers perform recurrence operations prior to a max pooling operation. The radar data with the second resolution may be produced from at least an output of the recurrent encoder layers. Other examples disclosed herein include a method of operating the radar system in the autonomous driving system of the ego vehicle.

Abstract: A pressurising system for bolt tensioning, comprising: an inlet for receiving compressed gas; a fluid outlet for connection to a bolt tensioning device; a pump for pumping fluid for increasing the pressure at the fluid outlet, the pump being coupled to the inlet for being driven by compressed gas received at the inlet; a negative pressure generator coupled to the outlet for decreasing the pressure at the fluid outlet, the negative pressure generator being coupled to the inlet for being driven by compressed gas received at the inlet.

Abstract: Examples disclosed herein relate to an autonomous driving system in an ego vehicle. The autonomous driving system includes a radar system configured to detect a target in a path and a surrounding environment of the ego vehicle and produce radar data with a first resolution that is gathered over a continuous field of view on the detected target. The system includes a super-resolution network configured to receive the radar data with the first resolution and produce radar data with a second resolution different from the first resolution using first neural networks. The system also includes a target identification module configured to receive the radar data with the second resolution and to identify the detected target from the radar data with the second resolution using second neural networks. Other examples disclosed herein include a method of operating the radar system in the autonomous driving system of the ego vehicle.

Abstract: A system and method may be provided for associating bio-signal data (e.g. EEG brain scan data) from at least one user with at least one music data item (e.g. song, or piece of music). By associating bio-signal data, or emotions determined therefrom, with music, the system may establish a data store of music associated with emotions. That database may then be leveraged upon determining that a user is feeling a particular emotion through an EEG scan. When a particular emotion is detected in EEG data of a user, the system may then respond based at least partly on the same or similar emotion being associated with one or more music data items in the system. For example, the system may recommend a particular song associated with the same emotion presently being experienced by the user.

Abstract: A method is provided, performed by a wearable computing device comprising at least one bio-signal measuring sensor, the at least one bio-signal measuring sensor including at least one brainwave sensor, comprising: acquiring at least one bio-signal measurement from a user using the at least one bio-signal measuring sensor, the at least one bio-signal measurement comprising at least one brainwave state measurement; processing the at least one bio-signal measurement, including at least the at least one brainwave state measurement, in accordance with a profile associated with the user; determining a correspondence between the processed at least one bio-signal measurement and at least one predefined device control action; and in accordance with the correspondence determination, controlling operation of at least one component of the wearable computing device, such as modifying content displayed on a display of the wearable computing device.

Abstract: Examples disclosed herein relate to an autoencoder assisted radar for target identification. The radar includes an Intelligent Metamaterial (“iMTM”) antenna module to radiate a transmission signal with an iMTM antenna structure and generate radar data capturing a surrounding environment, a data pre-processing module having an autoencoder to encode the radar data into an information-dense representation, and an iMTM perception module to detect and identify a target in the surrounding environment based on the information-dense representation and to control the iMTM antenna module. An autoencoder for assisting a radar system and a method for identifying a target with an autoencoder assisted radar in a surrounding environment are also disclosed herein.

Abstract: Examples disclosed herein relate to an autonomous driving system in an ego vehicle. The autonomous driving system includes a radar system configured to detect and identify a target in a path and a surrounding environment of the ego vehicle. The autonomous driving system also includes a sensor fusion module configured to receive radar data on the identified target from the radar system and compare the identified target with one or more targets identified by a plurality of perception sensors that are geographically disparate from the radar system. Other examples disclosed herein include a method of operating the radar system in the autonomous driving system of the ego vehicle.

Abstract: A foodstuffs preparation device suitable for preparing breadstuff-based goods, the device comprises a hollow cylindrical tube having an open first end, a second end and a side wall, the side wall defining a tube channel, the first end including a cutting arrangement, the side wall defining an elongate aperture with an anterior end proximal to the first end and a posterior end distal from the first end, wherein the aperture is suitable for the insertion of a foodstuff into the tube channel.

Abstract: A computer system or method may be provided for modulating content based on a person's brainwave data, including modifying presentation of digital content at at least one computing device. The content may also be modulated based on a set of rules maintained by or accessible to the computer system. The content may also be modulated based on user input, including through receipt of a presentation control command that may be processed by the computer system of the present invention to modify presentation of content. Content may also be shared with associated brain state information.

Abstract: A computer system or method may be provided for modulating content based on a person's brainwave data, including modifying presentation of digital content at at least one computing device. The content may also be modulated based on a set of rules maintained by or accessible to the computer system. The content may also be modulated based on user input, including through receipt of a presentation control command that may be processed by the computer system of the present invention to modify presentation of content. Content may also be shared with associated brain state information.

Abstract: A system and method may be provided for associating bio-signal data (e.g. EEG brain scan data) from at least one user with at least one music data item (e.g. song, or piece of music). By associating bio-signal data, or emotions determined therefrom, with music, the system may establish a data store of music associated with emotions. That database may then be leveraged upon determining that a user is feeling a particular emotion through an EEG scan. When a particular emotion is detected in EEG data of a user, the system may then respond based at least partly on the same or similar emotion being associated with one or more music data items in the system. For example, the system may recommend a particular song associated with the same emotion presently being experienced by the user.

Abstract: A method is provided, performed by a wearable computing device comprising at least one bio-signal measuring sensor, the at least one bio-signal measuring sensor including at least one brainwave sensor, comprising: acquiring at least one bio-signal measurement from a user using the at least one bio-signal measuring sensor, the at least one bio-signal measurement comprising at least one brainwave state measurement; processing the at least one bio-signal measurement, including at least the at least one brainwave state measurement, in accordance with a profile associated with the user; determining a correspondence between the processed at least one bio-signal measurement and at least one predefined device control action; and in accordance with the correspondence determination, controlling operation of at least one component of the wearable computing device, such as modifying content displayed on a display of the wearable computing device.