Abstract: An electric motor includes a housing with an inner surface and an outer surface positioned radially outward from the inner surface. The electric motor includes a stator coupled to the inner surface, an electrical component coupled to the outer surface, and a cooling channel positioned within the housing between the inner surface and the outer surface. The housing is additively manufactured with the cooling channel formed therein. The electric motor includes a bus bar assembly formed as an axial stack.

Abstract: A mechanism for interpreting spatiotemporal data from augmented reality devices and virtual reality devices based on an analysis performed by one or more predictive machines. The predictive machines may implement machine learning techniques and/or algorithms to predict a heart rate for a user, from which user calorie expense can be calculated. In operation, a virtual reality or augmented reality device can receive positional data over time, for example derived from image data from a camera. The positional data can be averaged over time, and the averages can be rolled-up, and the averaged and rolled-up data can be fed into a predictive machine to generate a heart rate prediction. The heart rate prediction is used to generate a user heart rate, from which calories for the user's corresponding motion is determined.

Abstract: Technologies for providing real-time visualizations of a behavior of an autonomous vehicle (AV) associated with a ride request. In some examples, a method for providing real-time visualizations of a behavior of an AV associated with a ride request can include receiving a user request for a ride from an AV, wherein the user request specifies a pick-up location associated with a user; receiving sensor data from one or more sensors associated with the AV; determining, based on the sensor data, a state and context of the AV while the AV is en route to the pick-up location; and presenting, at a display interface, a map depicting one or more visual indicators of the state and context of the AV, the state and context of the AV including a location of the AV and one or more AV operations.

Abstract: Technologies for providing real-time visualizations of a behavior of an autonomous vehicle (AV) associated with a ride request. In some examples, a method for providing real-time visualizations of a behavior of an AV associated with a ride request can include receiving a user request for a ride from an AV, wherein the user request specifies a pick-up location associated with a user; receiving sensor data from one or more sensors associated with the AV; determining, based on the sensor data, a state and context of the AV while the AV is en route to the pick-up location; and presenting, at a display interface, a map depicting one or more visual indicators of the state and context of the AV, the state and context of the AV including a location of the AV and one or more AV operations.

Abstract: A mechanism for interpreting spatiotemporal data from augmented reality devices and virtual reality devices based on an analysis performed by one or more predictive machines. The predictive machines may implement machine learning techniques and/or algorithms to predict a heart rate for a user, from which user calorie expense can be calculated. In operation, a virtual reality or augmented reality device can receive positional data over time, for example derived from image data from a camera. The positional data can be averaged over time, and the averages can be rolled-up, and the averaged and rolled-up data can be fed into a predictive machine to generate a heart rate prediction. The heart rate prediction is used to generate a user heart rate, from which calories for the user's corresponding motion is determined.

Abstract: Technologies for providing real-time visualizations of a behavior of an autonomous vehicle (AV) associated with a ride request. In some examples, a method for providing real-time visualizations of a behavior of an AV associated with a ride request can include receiving a user request for a ride from an AV, wherein the user request specifies a pick-up location associated with a user; receiving sensor data from one or more sensors associated with the AV; determining, based on the sensor data, a state and context of the AV while the AV is en route to the pick-up location; and presenting, at a display interface, a map depicting one or more visual indicators of the state and context of the AV, the state and context of the AV including a location of the AV and one or more AV operations.

Abstract: Technologies for providing real-time visualizations of a behavior of an autonomous vehicle (AV) associated with a ride request. In some examples, a method for providing real-time visualizations of a behavior of an AV associated with a ride request can include receiving a user request for a ride from an AV, wherein the user request specifies a pick-up location associated with a user; receiving data indicating a state and/or context of the AV while the AV is en route to the pick-up location; generating, based on the data indicating the state and/or context of the AV, one or more visual indicators of the state and/or context of the AV; and presenting, at a display interface, a map depicting the one or more visual indicators of the state and/or context of the AV, the state and/or context of the AV including a location of the AV and/or one or more AV operations.

Abstract: A method of constructing a tower structure by assembling a set of coaxial telescopic sections 2, 3a, 3b in position on site and then raising the assembled sections using hydraulic crawler jacks 8 and tendons 5. The telescopic sections are assembled or constructed in situ, starting with the inner section and then each subsequent section around the outside of the previously constructed sections. Each individual tower section may be cast in situ or assembled from multiple pre-fabricated segments. This method permits the construction of very tall structures while obviating the need for very large cranes. It also removes the design constraints on the height of the individual telescopic sections.

Abstract: A method of constructing a tower structure by assembling a set of coaxial telescopic sections 2, 3a, 3b in position on site and then raising the assembled sections using hydraulic crawler jacks 8 and tendons 5. The telescopic sections are assembled or constructed in situ, starting with the inner section and then each subsequent section around the outside of the previously constructed sections. Each individual tower section may be cast in situ or assembled from multiple pre-fabricated segments. This method permits the construction of very tall structures while obviating the need for very large cranes. It also removes the design constraints on the height of the individual telescopic sections.

Abstract: An apparatus and method are proposed for incremental casting of concrete cantilever bridge sections (7, 12). The main trusses which form the load-bearing frames (3) of the apparatus are angularly splayed so that they are positioned outwards of the main load bearing webs of the to-be-constructed section (7) of the bridge, while still being supported on the webs of the already-constructed section (12) of the bridge. In this way, the region above and below the construction space is kept free for improved access.