Abstract: An attachable movement-notification device is provided. The device is comprised of a body with at least one fastener that allows the device to be discretely attached to any portion of an object, item, etc. The device is comprised of at least one sensor that is preferably a motion sensor that detects motion of the device (and motion of the object the device is attached to). When motion is detected, a transmitter of the body communicates with a mobile application to alert a user that the object the device is attached to has been moved.

Abstract: An apparatus for performing continuous actions includes a memory storing instructions, and a processor configured to execute the instructions to obtain a first action of an agent, based on a current state of the agent, using a cross-entropy guided policy (CGP) neural network, and control to perform the obtained first action. The CGP neural network is trained using a cross-entropy method (CEM) policy neural network for obtaining a second action of the agent based on an input state of the agent, and the CEM policy neural network is trained using a CEM and trained separately from the training of the CGP neural network.

Abstract: An apparatus for estimating a trajectory of a tool may include: a memory storing instructions; and a processor configured to execute the instructions to: receive a task to be performed by the tool on a target object; receive a grayscale image and a depth image of the target object; and estimate a tool trajectory for performing the task, from the grayscale image and the depth image, via a pixels-to-plans neural network that is trained based on a labeled tool trajectory that is generated from a point cloud model of the target object.

Abstract: An apparatus for representing a three-dimensional (3D) object, the apparatus includes a memory storing instructions, and a processor configured to execute the instructions to transmit a two-dimensional (2D) image to an external device, based on the 2D image being transmitted, receive, from the external device, mapping function parameters that are obtained using a first neural network, set a mapping function of a second neural network, based on the received mapping function parameters, and based on 3D samples, obtain the 3D object corresponding to the 2D image, using the second neural network of which the mapping function is set.

Abstract: An apparatus for representing a three-dimensional (3D) object, the apparatus includes a memory storing instructions, and a processor configured to execute the instructions to transmit a two-dimensional (2D) image to an external device, based on the 2D image being transmitted, receive, from the external device, mapping function parameters that are obtained using a first neural network, set a mapping function of a second neural network, based on the received mapping function parameters, and based on 3D samples, obtain the 3D object corresponding to the 2D image, using the second neural network of which the mapping function is set.

Abstract: An apparatus for representing a three-dimensional (3D) object, the apparatus includes a memory storing instructions, and a processor configured to execute the instructions to transmit a two-dimensional (2D) image to an external device, based on the 2D image being transmitted, receive, from the external device, mapping function parameters that are obtained using a first neural network, set a mapping function of a second neural network, based on the received mapping function parameters, and based on 3D samples, obtain the 3D object corresponding to the 2D image, using the second neural network of which the mapping function is set.

Abstract: An apparatus for representing a three-dimensional (3D) object, the apparatus includes a memory storing instructions, and a processor configured to execute the instructions to transmit a two-dimensional (2D) image to an external device, based on the 2D image being transmitted, receive, from the external device, mapping function parameters that are obtained using a first neural network, set a mapping function of a second neural network, based on the received mapping function parameters, and based on 3D samples, obtain the 3D object corresponding to the 2D image, using the second neural network of which the mapping function is set.

Abstract: An apparatus for estimating a trajectory of a tool may include: a memory storing instructions; and a processor configured to execute the instructions to: receive a task to be performed by the tool on a target object; receive a grayscale image and a depth image of the target object; and estimate a tool trajectory for performing the task, from the grayscale image and the depth image, via a pixels-to-plans neural network that is trained based on a labeled tool trajectory that is generated from a point cloud model of the target object.

Abstract: An apparatus for performing continuous actions includes a memory storing instructions, and a processor configured to execute the instructions to obtain a first action of an agent, based on a current state of the agent, using a cross-entropy guided policy (CGP) neural network, and control to perform the obtained first action. The CGP neural network is trained using a cross-entropy method (CEM) policy neural network for obtaining a second action of the agent based on an input state of the agent, and the CEM policy neural network is trained using a CEM and trained separately from the training of the CGP neural network.

Abstract: Microorganisms such as micro algae are collected and separated from a host medium such as water. Cellular walls and membranes of the microorganisms are then ruptured to release their lipids using a lipid extraction unit. Thereafter, the lipids from the host medium are collected and separated using a lipid collection and separation unit. Related apparatus, systems, techniques and articles are also described.

Abstract: Microorganisms such as microalgae are collected and separated from a host medium such as water. Cellular walls and membranes of the microorganisms are then ruptured to release their lipids using a lipid extraction unit. Thereafter, the lipids from the host medium are collected and separated using a lipid collection and separation unit. Related apparatus, systems, techniques and articles are also described.

Abstract: Microorganisms such as microalgae are collected and separated from a host medium such as water. Cellular walls and membranes of the microorganisms are then ruptured to release their lipids using a lipid extraction unit. Thereafter, the lipids from the host medium are collected and separated using a lipid collection and separation unit. Related apparatus, systems, techniques and articles are also described.

Abstract: Microorganisms such as microalgae are collected and separated from a host medium such as water. Cellular walls and membranes of the microorganisms are then ruptured to release their lipids using a lipid extraction unit. Thereafter, the lipids from the host medium are collected and separated using a lipid collection and separation unit. Related apparatus, systems, techniques and articles are also described.

Abstract: Microorganisms such as microalgae are collected and separated from a host medium such as water. Cellular walls and membranes of the microorganisms are then ruptured to release their lipids using a lipid extraction unit. Thereafter, the lipids from the host medium are collected and separated using a lipid collection and separation unit. Related apparatus, systems, techniques and articles are also described.

Abstract: A Phase Locked Loop (PLL) that has a substantially constant gain over a wide frequency range. The frequency range over which the PLL operates is divided into a number of frequency sub-ranges. The circuit includes a mechanism for adjusting the loop gain profile as the PLL moves from one frequency sub-range to another. When the PLL switches to a new frequency sub-range, the loop gain profile is adjusted to a pre-established value. Changes of frequency within each sub-range are then accomplished with the loop gain varying within a pre-established range.

Abstract: A crystal oscillator circuit which does not produce runt pulses when the oscillator is turned on or off. The circuit includes a crystal oscillator, an integrator which integrates the energy in a plurality of pulses, a threshold circuit which is active when the output of the integrator reaches a pre-specified threshold and gating circuits which gate the output of the crystal oscillator to the output terminal only when the threshold circuit has reached the specified threshold.

Abstract: A method for generating parameters for adjusting the frequency of a VCO. A desired carrier frequency may be based off the output of the VCO. The method determines parameters that are operable to adjust the frequency of the VCO, based on the channel number. The channel number may be input into combinatorial logic to determine the parameters. Offsets, which may be scaled, may be added to the channel number before determining the parameters, wherein the frequency of the VCO is further adjusted based on the offset(s). A first parameter may be operable to select a frequency scalar in a circuit with the VCO. A second parameter may be operable to generate a feedback signal for adjusting the frequency of the VCO.