Abstract: A semiconductor structure comprising: a semiconductor membrane, the semiconductor membrane having at least one amorphised area and an active area wherein the at least one amorphised area is adjacent the active area such that the at least one amorphised area exerts strain on the active area and a method of introducing strain into a crystalline semiconductor membrane by ion implantation.

Abstract: Unsupervised cross-domain data augmentation techniques for long-text document based prediction and explanation are provided. In one aspect, a system for long-document based prediction includes: an encoder for creating embeddings of long-document texts with hierarchical sparse self-attention, and making predictions using the embeddings of the long-document texts; and a multi-source counterfactual augmentation module for generating perturbed long-document texts using unlabeled sentences from at least one external source to train the encoder. A method for long-document based prediction is also provided.

Abstract: A computer-implemented method is provided of using a machine learning model for disentanglement of prosody in spoken natural language. The method includes encoding, by a computing device, the spoken natural language to produce content code. The method further includes resampling, by the computing device without text transcriptions, the content code to obscure the prosody by applying an unsupervised technique to the machine learning model to generate prosody-obscured content code. The method additionally includes decoding, by the computing device, the prosody-obscured content code to synthesize speech indirectly based upon the content code.

Abstract: Methods and system are provided to select a battery control strategy for a hybrid battery of a hybrid electric vehicle. The methods comprise receiving forecast weather information at a first location, determining an operational parameter of the hybrid battery, and selecting a first battery control strategy based on the forecast weather information and the operational parameter of the hybrid battery, wherein the control strategy comprises a state of charge target for the hybrid battery required for a next start sequence.

Abstract: A particular method includes storing a manifest file and a parameters file at a data store. The manifest file and the parameters file are associated with a software deployment package. An application associated with the software deployment package is published to a first remote computing device and to a second remote computing device. The method includes receiving first parameter values from the first remote computing device and receiving second parameter values from the second remote computing device. The first parameter values are stored in a first region of the data store that is specific to the first computing device. The second parameter values are stored in a second region of the data store that is specific to the second computing device.

Abstract: A graph with a plurality of nodes, a plurality of edges, and a plurality of node features is obtained and node representations for the node features are generated. A plurality of structure learning scores is generated based on the node representations, each structure learning score corresponding to one of the plurality of edges. A subset of the plurality of edges that identify a subgraph is selected, each edge of the subset having a structure learning score that is greater than a given threshold. The subgraph is inputted to a representation learner and an inferencing operation is performed using the representation learner based on the subgraph.

Abstract: According to one embodiment, a method, computer system, and computer program product for placing an application window is provided. The embodiment may include receiving a window opening event for the application window. In response to determining that the application window can be repositioned and resized, the embodiment may include identifying one or more active areas of a computing device screen. An active area is an area of the computing device screen which is currently displaying one or more other windows and their respective interactive elements. The embodiment may include utilizing one or more search algorithms to identify a least active area of the one or more active areas of the computing device screen. The embodiment may include displaying the application window within the least active area.

Abstract: A method includes: creating a training data set based on user input, the training data set including time series data of a price of an asset and stochastic event data of events related to the asset; creating an event intensity model that models an event intensity parameter of one of the events related to the asset, wherein the event intensity model comprises a proximal graphical event model (PGEM), and the creating the event intensity model includes learning parameters of the PGEM using machine learning and the training data set; creating a probabilistic time series model that predicts a probability distribution of a return of the asset, wherein the creating the probabilistic time series model includes learning parameters of the probabilistic time series model using machine learning and the training data set; and predicting a future return of the asset for a future time period using the probabilistic time series model.

Abstract: A method includes: creating a training data set based on user input, the training data set including time series data of a price of an asset and stochastic event data of events related to the asset; creating an event intensity model that models an event intensity parameter of one of the events, wherein the event intensity model is based on a multivariate Hawkes process, and the creating the event intensity model includes learning parameters of the event intensity model using machine learning and the training data set; creating a probabilistic time series model that predicts a probability distribution of a return of the asset, wherein the creating the probabilistic time series model includes learning parameters of the probabilistic time series model using machine learning and the training data set; and predicting a future return of the asset for a future time period using the probabilistic time series model.

Abstract: Methods and systems are provided to control a regenerative braking system comprising a battery, e.g., of a vehicle. The regenerative braking system harvests energy from a braking event. The energy can be stored in the battery, used to power a plurality of devices in the vehicle, or the battery can be preconditioned to provide more capacity to account for a braking event. The vehicle system may comprise one or more electrical loads configured to use power from the battery. The method comprises detecting a regenerative braking event of the vehicle and activating a first electrical load to consume the energy from the regenerative braking event.

Abstract: Methods, systems, and computer program products for translating text using generated visual representations and artificial intelligence are provided herein. A computer-implemented method includes generating a tokenized form of at least a portion of input text in a first language; generating at least one visual representation of at least a portion of the input text using a first set of artificial intelligence techniques; generating a tokenized form of at least a portion of the at least one visual representation; and generating an output including a translated version of the input text into at least a second language by processing, using a second set of artificial intelligence techniques, at least a portion of the tokenized form of the at least a portion of the input text and at least a portion of the tokenized form of the at least a portion of the at least one visual representation.

Abstract: A method, computer program product, and computer system for artboard element positioning in a series of computer-based artboards. The method includes providing multiple target artboards and identifying a common element in at least some of the target artboards, where a common element has at least some consistent attributes. The method includes determining a reference position for the common element. The method includes, in each target artboard containing the common element, comparing an existing position of the common element with the reference position and determining whether to adjust the existing position to match the reference position.

Abstract: Methods and systems are provided for regenerating an after-treatment system of a vehicle. A first operational parameter of a first component of the after-treatment system is monitored and a second operational parameter, different to the first operational parameter, of a second component of the after-treatment system is monitored. It is determined if the first operational parameter of the first component is outside a first threshold range and if the second operational parameter is approaching a second threshold and, in response to the first operational parameter being outside the first threshold range and the second operational parameter being within the second threshold range, a regeneration sequence of the after-treatment system configured to regenerate at least the first component of the after-treatment system is initiated.

Abstract: A generator network of a variational autoencoder can be trained to approximate a simulator and generate a first result. The simulator is associated with input data, based on which the simulator outputs output data. A training data set for the generator network can include the simulator's input data and output data. Based on the simulator's output data and the first result of the generator network, an inference network of the variational autoencoder can be trained to generate a second result. The second result of the trained inference network inverts the first result of the generator and approximates the simulator's input data. The trained inference network can function as an inverted simulator.

Abstract: An embodiment for improving a shutdown sequencing of a computer operating system (OS) is provided. The embodiment may include receiving a command to initiate an OS shutdown. The embodiment may also include creating a first list of running tasks to terminate. The embodiment may further include in response to determining there is no historical data, sending a termination request to a particular running task. The embodiment may also include in response to determining the particular running task requires user input to terminate, increasing a weight of the particular running task. The embodiment may further include in response to determining there is an additional particular running task in the created first list, sending the termination request to the additional particular running task. The embodiment may also include in response to determining the additional particular running task requires the user input to terminate, increasing the weight of the additional particular running task.

Abstract: The present disclosure relates to systems and methods for managing a state of charge of a hybrid vehicle battery using an eCAT. Electrical energy is provided to a hybrid system for storage at the battery of the hybrid system. A first state of charge of the battery of the hybrid system is determined. Upon determining that the first state of charge is within a predetermined upper range, a determination is made as to whether to increase energy supplied to one or more hybrid vehicle components, the one or more hybrid vehicle components comprising at least the eCAT. At least a portion of the electrical energy is consumed at the eCAT.

Abstract: A vehicle includes a power converter that receives power, and has first and second outputs, a low voltage battery that receives power from the power converter via the first output, and a heating element that receives power from the power converter via the second output, and provides heat to a catalyst of an exhaust system. The vehicle also includes a controller that commands the converter to provide power to the heating element via the second output according to a temperature of the catalyst.

Abstract: A method of providing a heating cycle for an after-treatment system is described. The method comprises initiating a pre-charge cycle of a DCDC converter and determining a temperature of the after-treatment system. In response to determining the temperature of the after-treatment system is below a threshold temperature and the pre-charge is complete, the method further comprises operating a solid-state switch to electrically connect a high voltage power source to a heating element to of the after-treatment system, and heating the after-treatment system with the heating element until the after-treatment system reaches the threshold temperature.

Abstract: Methods and system are disclosed for vehicle power control. a first high voltage, HV, demand signal is received from a HV device and a first low voltage, LV, demand signal is received from a LV system of the vehicle. The first HV demand signal can be modified based on the first LV demand signal. An input HV supply is received from an e-machine based on the first LV demand signal and modified HV demand signal. An output LV supply is provided from a first DCDC converter to the LV system of the vehicle and an output HV supply is provided from a second DCDC converter to the HV device.

Abstract: Self-leveling inspection system methods and devices for use in inspecting buried pipes or other cavities are disclosed. The system includes a camera head with an image sensor, an orientation sensor, and a signal processing module including a processing programmed to receive an image from the image sensor, and an orientation signal from the orientation sensor, generate a second image based at least in part on information provided from the orientation sensor, and store the second image in a non-transitory memory.