Abstract: This document describes techniques and systems related to a radar system using a machine-learned model for stationary object detection. The radar system includes a processor that can receive radar data as time-series frames associated with electromagnetic (EM) energy. The processor uses the radar data to generate a range-time map of the EM energy that is input to a machine-learned model. The machine-learned model can receive as inputs extracted features corresponding to the stationary objects from the range-time map for multiple range bins at each of the time-series frames. In this way, the described radar system and techniques can accurately detect stationary objects of various sizes and extract critical features corresponding to the stationary objects.

Abstract: Techniques and apparatuses are described that implement object classification using low-level radar data. In particular, a radar system extracts features of a detected object based on low-level data. The radar system analyzes these features using machine learning to determine an object class associated with the detected object. By relying on low-level data, the radar system is able to extract additional information regarding the distribution of energy across range, range rate, azimuth, or elevation, which is not available in detection-level data. With the use of machine learning, the object can be classified quickly (e.g., within a single frame or observation), thereby enabling sufficient time for the autonomous-driving logic to initiate an appropriate action based on the object's class. Furthermore, this classification can be performed without the use of information from other sensors.

Abstract: Techniques and apparatuses are described that implement object classification using low-level radar data. In particular, a radar system extracts features of a detected object based on low-level data. The radar system analyzes these features using machine learning to determine an object class associated with the detected object. By relying on low-level data, the radar system is able to extract additional information regarding the distribution of energy across range, range rate, azimuth, or elevation, which is not available in detection-level data. With the use of machine learning, the object can be classified quickly (e.g., within a single frame or observation), thereby enabling sufficient time for the autonomous-driving logic to initiate an appropriate action based on the object's class. Furthermore, this classification can be performed without the use of information from other sensors.

Abstract: A side outlet device suitable for use in combination with a rainhead to form an overflow assembly is adapted to enable the rainhead to be mounted external to the building in relation to a wall of the building, to one side of a box guttering extending interiorly along the wall, whereby water flowing from the roof is able to pass through the side outlet device to a downpipe via the overflow device. The side outlet device has a respective end section at first and second opposite ends, with the first end section having a form corresponding to the form of a box gutter end section such that, with the side outlet device mounted in relation to the wall, the first end section extends through the wall and is receivable in the gutter receptor of the overflow device. The second end section is adapted for connection to the box guttering to enable water to flow from the box guttering and through the side outlet device to the overflow device.

Abstract: A side outlet device suitable for use in combination with a rainhead to form an overflow assembly is adapted to enable the rainhead to be mounted external to the building in relation to a wall of the building, to one side of a box guttering extending interiorly along the wall, whereby water flowing from the roof is able to pass through the side outlet device to a downpipe via the overflow device. The side outlet device has a respective end section at first and second opposite ends, with the first end section having a form corresponding to the form of a box gutter end section such that, with the side outlet device mounted in relation to the wall, the first end section extends through the wall and is receivable in the gutter receptor of the overflow device. The second end section is adapted for connection to the box guttering to enable water to flow from the box guttering and through the side outlet device to the overflow device.

Abstract: A rainhead (1) comprising: a tub member (3); an internal receptacle (8) in the tub member (3) having an internal wall (7) forming a weir spaced from an external wall (9) of the tub member (3); an inlet (4) arranged to direct water flowing from a gutter into the internal receptacle (8); and, a chute (11) between the internal wall (7) and the external wall (9), the chute (11) being arranged to receive water overflowing from the internal receptacle (8) to allow it to drain from the chute (11) through a chute outlet (13).

Abstract: A rainhead (1) comprising: a tub member (3); an internal receptacle (8) in the tub member (3) having an internal wall (7) forming a weir spaced from an external wall (9) of the tub member (3); an inlet (4) arranged to direct water flowing from a gutter into the internal receptacle (8); and, a chute (11) between the internal wall (7) and the external wall (9), the chute (11) being arranged to receive water overflowing from the internal receptacle (8) to allow it to drain from the chute (11) through a chute outlet (13).

Abstract: A measurement apparatus and method for determining a viscosity of a fluid are disclosed. A predetermined pre-fill portion of a sample of the fluid is injected into a capillary at a predetermined flow rate. The pressure differential across the capillary is determined, and the measurement is aborted when the measured pressure is greater than a predetermined maximum pressure. When the measured pressure is less than the predetermined maximum pressure, the remaining portion of the sample is injected into through the capillary. The viscosity of the sample is calculated based on a pressure within the capillary during the injection of the remaining portion of the sample.

Abstract: The rheology of a colloidal PEG-based shear thickening fluid emulsified with silicone oil is studied in detail. A shear thickening response is observed in the viscosity-shear rate curves for volume fractions as low as 10% of STF in the silicone emulsion. From the log additivity rule, we prove the system to be classified as both a positive and negative deviating blend at zero shear. This interesting behavior is due to phase inversion. The rubbers are formed by emulsifying the shear thickening fluid within the rubber precursors and then adding the catalyzing agent. It was possible to contain STF in each of the silicones tested and the rubbers exhibited different behavior with incased STF. Shear thickening fluid was added to open cell polyurethane to create a Foam-STF composite which was found to exhibit an obvious shear thickening response. The foam composite became solid like and absorbed energy at high strains while still maintaining its fluid-like response at low strain rates.

Abstract: With the object of providing a glass run channel which can accommodate the curvature in both front elevation and plan, and also some degree of twisting, in this invention a glass run channel comprises a metal core of general S shape, the metal core having a continuous unbroken strip and a plurality of transversely extending slits forming between them bars or ribs extending transversely from the unbroken strip, the core being covered with an elastomer.