Abstract: A rotating electric machine includes an inner housing and an outer housing. An inner circumferential surface of the outer housing includes a first cylindrical surface contacting first sealing member, a second cylindrical surface contacting a second sealing member, and a third cylindrical surface in which an end part of the inner housing is press-fitted into. The second cylindrical surface has a smaller diameter than the first cylindrical surface and the third cylindrical surface has a smaller diameter than the second cylindrical surface and is provided closer to the bottom than the second cylindrical surface. The first sealing member contacts the first cylindrical surface and the second sealing member contacts the second cylindrical surface to form a gap in an axial direction between the end part of the inner housing and the third cylindrical surface where the inner housing has been inserted into the outer housing.

Abstract: A managing device, a method and a non-transitory computer-readable storage medium are provided for screen time management. The managing device collects screen time data from each of one or more managed devices, and stores the screen time data, the one or more managed devices being managed by the managing device. The managing device calculates overall screen usage time based on the screen time data across a desired subset of the one or more managed device. In response to a screen usage time query, The managing device provides the calculated overall screen usage time to a querying device.

Abstract: Nuclear reactors produce large amounts of spent fuel during operation. In addition to recyclable materials such as uranium and plutonium, spent fuel also contains significant amounts of fission products and highly radioactive transuranic (TRU) elements. Homogenization of nuclides in traditional post-processing technology hinders efficient fuel recycling. In order to improve the efficiency of spent fuel recycling, and to reduce the inevitable “highly radioactive waste” produced in existing spent fuel recycling processes, a novel method for pre-separating nuclides in spent fuel is disclosed. Specifically, we have developed a physical method, wherein an artificially created large temperature gradient drives the migration of fission gas bubbles in spent metallic nuclear reactor fuel. The fission gas bubbles preferentially carry fission products and transuranic elements to achieve effective pre-separation of these elements from spent fuel, lowering cost and improving efficiency of spent fuel recycling.

Abstract: The present disclosure provides embodiments for joint twist generation for animation. The system can utilize a neural network, also referred to as a deep neural network, which utilizes machine learning processes in order to create animation data that are more life-like and realistic. The system can obtain a set of axis vectors for a rig of a virtual character model; obtain a twist model for the rig; input the set of axis vectors to the twist model to obtain a set of twist vectors; and determine animation data based on the set of axis vectors and the set of twist vectors.

Abstract: Embodiments of this disclosure provide techniques used in a location sensing service and a timeline service implemented in a host device for providing location history. In particular, the location sensing service may passively collect location coordinates of the device using requests made by third party applications. The location sensing service may receive a signal comprising an intent for a location request in response to a change in the user activity or in response to a change in a cellular identification of the device. The device may determine that a time elapsed from a previous location request and a time corresponding with receiving one or more of the signals exceed a time threshold and, based thereon, request a location coordinate of the device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for leveraging Internet of things (IoT) devices that can communicate and interact with one another. In some implementations, at least one external device within proximity to an end-user device is determined. Context information of the end-user device is determined. Based on the context information of the end-user device, a connection with the at least one external device is established. Functionality corresponding to the at least one external device is identified. A virtual device associated with the at least one external device is identified. The identified virtual device is provided to the end-user device for performing the functionality of the at least one external device by the end-user device.

Abstract: Systems and methods are provided for enhanced animation generation based on generative control models. An example method includes accessing an autoencoder trained based on character control information generated using motion capture data, the character control information indicating, at least, trajectory information associated with the motion capture data, and the autoencoder being trained to reconstruct, via a latent feature space, the character control information. First character control information associated with a trajectory of an in-game character of an electronic game is obtained. A latent feature representation is generated and the latent feature representation is modified. A control signal is output to a motion prediction network for use in updating a character pose of the in-game character.

Abstract: Battery node diagnostic data may be received from a battery system. One or more outlier detection machine learning models may be selected based on profile information included in the battery node diagnostic data. The profile information may identify a battery node operation profile associated with some or all of the battery node diagnostic data. One or more of the battery nodes may be identified as outliers by applying the one or more outlier detection machine learning models to identify one or more differences between first diagnostic data for the designated subset of the battery nodes and a population-level representation of the battery node diagnostic data. Outcome values may be determined by applying one or more predetermined rules to the battery node diagnostic data. A battery node may be identified as exhibiting a fault based on the designated subset of the battery nodes and the plurality of outcome values.

Abstract: Signal data may be received from battery node controllers corresponding with battery nodes in a battery system operating in a charging or discharging state. A battery node controller may selectively couple a power bus in the battery system with a battery node including a respective one or more battery cells. Candidate events may be identified as anomalous based on a discontinuous changes in the signal data. The candidate events may correspond to a respective battery node and a respective period of time. When one or more candidate events are identified as anomalous, diagnostic data may be sent to a remote computing system over the internet via a communication interface. An indication of a designated battery node as defective based on one or more machine learning models applied to the diagnostic data at the remote computing system may be received. A battery node operation profile associated with the designated battery node may be updated.

Abstract: Battery system diagnostic data may be generated at battery node controllers in a battery system. A battery node controller may selectively couple a power bus with a battery node including one or more battery cells. An unsupervised machine learning model may be trained based on the battery system diagnostic data. Outlier values may be determined by applying the machine learning model to the battery node diagnostic data. A battery node may be identified as anomalous based on a comparison of a designated outlier value associated with the designated battery node with the plurality of outlier values. A battery node operation profile controlling operation of the designated battery node may be updated.

Abstract: In some embodiments, the dynamic animation generation system can provide a deep learning framework to produce a large variety of martial arts movements in a controllable manner from unstructured motion capture data. The system can imitate animation layering using neural networks with the aim to overcome challenges when mixing, blending and editing movements from unaligned motion sources. The system can synthesize movements from given reference motions and simple user controls, and generate unseen sequences of locomotion, but also reconstruct signature motions of different fighters. For achieving this task, the dynamic animation generation system can adopt a modular framework that is composed of the motion generator, that maps the trajectories of a number of key joints and root trajectory to the full body motion, and a set of different control modules that map the user inputs to such trajectories.

Abstract: The present disclosure provides a method for pre-separating nuclides in spent fuel, comprising steps: S1. generating a temperature of 1200 to 1600° C. in a center of a fuel element, and at the same time introducing a cooling medium to an outer surface of the fuel element, to introduce a temperature difference to heat the fuel element; S2. soaking cooled spent fuel in an ionic liquid to selectively dissolve fission products and transuranic elements, so that the fission products and the transuranic elements are pre-separated from the spent fuel. The method achieves the effect of pre-separating part of the fission products and transuranic elements by physical methods, and solves the problem that homogenization in traditional post-processing technology causes obstacles to nuclide separation.

Abstract: The disclosed computer-implemented method may include receiving an instruction to distinguish a foreground subject within an image from a background of the image based at least in part on a trimap of the image; determining, for each of the indeterminate pixels, using a chromatic-spatial distance metric, a distance of the indeterminate pixel from one or more of the foreground pixels and a distance of the indeterminate pixel from one or more of the background pixels; and recategorizing a subset of the indeterminate pixels as background pixels based at least in part on the subset of indeterminate pixels being closer to the one or more background pixels than to the one or more foreground pixels according to the chromatic-spatial distance metric. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Systems and methods are provided for enhanced animation generation based on using motion mapping with local bone phases. An example method includes accessing first animation control information generated for a first frame of an electronic game including local bone phases representing phase information associated with contacts of a plurality of rigid bodies of an in-game character with an in-game environment. Executing a local motion matching process for each of the plurality of local bone phases and generating a second pose of the character model based on the plurality of matched local poses for a second frame of the electronic game.

Abstract: Embodiments of the systems and methods described herein provide a dynamic animation generation system that can apply a real-life video clip with a character in motion to a first neural network to receive rough motion data, such as pose information, for each of the frames of the video clip, and overlay the pose information on top of the video clip to generate a modified video clip. The system can identify a sliding window that includes a current frame, past frames, and future frames of the modified video clip, and apply the modified video clip to a second neural network to predict a next frame. The dynamic animation generation system can then move the sliding window to the next frame while including the predicted next frame, and apply the new sliding window to the second neural network to predict the following frame to the next frame.

Abstract: A managing device, a method and a non-transitory computer-readable storage medium are provided for screen time management. The managing device collects screen time data from each of one or more managed devices, and stores the screen time data, the one or more managed devices being managed by the managing device. The managing device calculates overall screen usage time based on the screen time data across a desired subset of the one or more managed device. In response to a screen usage time query, The managing device provides the calculated overall screen usage time to a querying device.

Abstract: In some embodiments, the dynamic animation generation system can provide a deep learning framework to produce a large variety of martial arts movements in a controllable manner from unstructured motion capture data. The system can imitate animation layering using neural networks with the aim to overcome challenges when mixing, blending and editing movements from unaligned motion sources. The system can synthesize movements from given reference motions and simple user controls, and generate unseen sequences of locomotion, but also reconstruct signature motions of different fighters. For achieving this task, the dynamic animation generation system can adopt a modular framework that is composed of the motion generator, that maps the trajectories of a number of key joints and root trajectory to the full body motion, and a set of different control modules that map the user inputs to such trajectories.

Abstract: The present disclosure provides embodiments for joint twist generation for animation. The system can utilize a neural network, also referred to as a deep neural network, which utilizes machine learning processes in order to create animation data that are more life-like and realistic. The system can obtain a set of axis vectors for a rig of a virtual character model; obtain a twist model for the rig; input the set of axis vectors to the twist model to obtain a set of twist vectors; and determine animation data based on the set of axis vectors and the set of twist vectors.

Abstract: Systems and methods are provided for enhanced animation generation based on using motion mapping with local bone phases. An example method includes accessing first animation control information generated for a first frame of an electronic game including local bone phases representing phase information associated with contacts of a plurality of rigid bodies of an in-game character with an in-game environment. Executing a local motion matching process for each of the plurality of local bone phases and generating a second pose of the character model based on the plurality of matched local poses for a second frame of the electronic game.

Abstract: Embodiments of the systems and methods described herein provide a dynamic animation generation system that can apply a real-life video clip with a character in motion to a first neural network to receive rough motion data, such as pose information, for each of the frames of the video clip, and overlay the pose information on top of the video clip to generate a modified video clip. The system can identify a sliding window that includes a current frame, past frames, and future frames of the modified video clip, and apply the modified video clip to a second neural network to predict a next frame. The dynamic animation generation system can then move the sliding window to the next frame while including the predicted next frame, and apply the new sliding window to the second neural network to predict the following frame to the next frame.