Abstract: In an electromagnetic environment analysis system, an image creation unit creates an image for displaying information relevant to a measurement value in a position associated with a measurement position of each of the measurement values. A partition judgment unit judges a partition corresponding to the measurement position of each of the measurement values in a plurality of partitions forming a display range of the information relevant to the measurement value in the image, based on position information. A display information determination unit determines information relevant to the display of the partition, based on the measurement value corresponding to the partition. In a case where two or more measurement values measured at timings different from each other correspond to one partition, the display information determination unit calculates a representative value from the two or more measurement values, and determines information to be displayed in the partition, based on the representative value.

Abstract: A method of generating a question-answer learning model through adversarial learning may include: sampling a latent variable based on constraints in an input passage; generating an answer based on the latent variable; generating a question based on the answer; and machine-learning the question-answer learning model using a dataset of the generated question and answer, wherein the constraints are controlled so that the latent variable is present in a data manifold while increasing a loss of the question-answer learning model.

Abstract: Systems, apparatuses, and methods are provided for identifying a corresponding string stored in memory based on an incomplete input string. A system can analyze and produce phonetic and distance metrics for a plurality of strings stored in memory by comparing the plurality of strings to an incomplete input string. These similarity metrics can be used as the input to a machine learning model, which can quickly and accurately provide a classification. This classification can be used to identify a string stored in memory that corresponds to the incomplete input string.

Abstract: Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of: monitoring first activities of a user over a first time period; based on the first activities of the user over the first time period, identifying, using a Markov model, a first probability of the user being in a first state; determining when the first probability is above a first probability predefined threshold; in response to determining when the first probability is above the first probability predefined threshold, automatically customizing first content on a graphical user interface for the first state to create a first graphical user interface on an electronic device of the user while the user is determined to be in the first state; monitoring second activities of the user over a second time period occurring after the first time period and after the user has been determined to be in the first

Abstract: An Artificial Intelligence (AI) ergonomic assessment and positioning system that analyzes remote workspace data, identifies objects that are improperly positioned, oriented, and/or have undesirable settings, and automatically adjusts, moves, sets, and/or provides automatic guidance for the adjustment, movement, and/or setting of target objects in the remote workspace.

Abstract: Adaptive sampling of pixels is disclosed. In some embodiments, convergence of pixels of a rendering is evaluated by removing texture from the rendering to eliminate non-convergence due to texture complexity and determining whether pixels values satisfy convergence criteria associated with pixel sampling. Those pixels of the rendering that have not converged are sampled with one or more additional samples. The completed rendering is output. Pixels of the completed rendering satisfy the convergence criteria and are not uniformly sampled.

Abstract: A distributed, online machine learning system is presented. Contemplated systems include many private data servers, each having local private data. Researchers can request that relevant private data servers train implementations of machine learning algorithms on their local private data without requiring de-identification of the private data or without exposing the private data to unauthorized computing systems. The private data servers also generate synthetic or proxy data according to the data distributions of the actual data. The servers then use the proxy data to train proxy models. When the proxy models are sufficiently similar to the trained actual models, the proxy data, proxy model parameters, or other learned knowledge can be transmitted to one or more non-private computing devices. The learned knowledge from many private data servers can then be aggregated into one or more trained global models without exposing private data.

Abstract: Systems, methods and apparatus of intelligent bandwidth allocation to different types of operations to access storage media in a data storage device. For example, a data storage device of a vehicle includes: storage media components; a controller configured to store data into and retrieve data from the storage media components according to commands received in the data storage device; and an artificial neural network configured to receive, as input and as a function of time, operating parameters indicative a data access pattern, and generate, based on the input, a prediction to determine an optimized bandwidth allocation scheme for controlling access by different types of operations in the data storage device to the storage media components. The controller is configured to schedule the operations of the different types to access the one or more storage media components according to the optimized bandwidth allocation scheme.

Abstract: Example implementations described herein are directed to a system for manufacturing dispatching using reinforcement learning and transfer learning. The systems and methods described herein can be deployed in factories for manufacturing dispatching for reducing job-due related costs. In particular, example implementations described herein can be used to reduce massive data collection and reduce model training time, which can eventually improve dispatching efficiency and reduce factory cost.

Abstract: A tangible, non-transitory, computer-readable medium includes instructions that, when executed by processing circuitry, are configured to cause the processing circuitry to receive sensory datasets associated with an industrial automation system, determine context information based on a sensory dataset and representative of an environmental condition, predict an intent of a user to complete a task associated with the industrial automation system based on the sensory datasets and the context information, present first output representative data via an extended reality device based on the intent and a setting, the setting including a data presentation format for presenting the sensory datasets, receive inputs indicative of changes to the data presentation format, present second output representative data via the extended reality device in response to receiving the inputs, and update the setting based on the inputs and historical data indicative of users changing the data presentation format of the first output r

Abstract: This application relates to systems and methods for automatically detecting and correcting image quality based on a set of quality standards. In some examples, a plurality of quality parameters of an image are determined based on receiving an image. It is then determined that at least one of the plurality of quality parameters is below a predetermined threshold. The predetermined threshold may be based on a required quality standard for images. In response to determining that the at least one of the plurality of quality parameters is below the predetermined threshold, feature of the image is adjusted such that the at least one of the plurality of quality parameters is at or above the predetermined threshold.

Abstract: A computing system may determine, for a current frame, a viewer's current eye position with respect to a waveguide of a display, identify eye positions that collectively form a grid of eye positions surrounding the current eye position, obtain, from a memory on the display, compressed arrays of scaling factors for correcting non-uniformities of the waveguide at the identified eye positions, perform interpolation based on the compressed arrays to generate an array of scaling factors for the current eye position, adjust pixel values of the current frame based on the customized array, and output the current frame with the adjusted pixel values to the display. The compression operation may include dithering or converting pixel values to a different color space. The interpolation may be performed on the compressed arrays or on results of a decompression operation. The customized array may be up-sampled prior to adjusting the pixel values.

Abstract: A high electron mobility transistor (HEMT) includes a substrate; a source on the substrate; a drain on the substrate spaced from the source; and a gate between the source and the drain, wherein the gate has a stem contacting the substrate, the stem having a source side surface and a drain side surface, wherein a source side angle is defined between the source side surface and an upper planar surface of the substrate and a drain side angle is defined between the drain side surface and the upper planar surface of the substrate, and wherein the source side angle and the drain side angle are asymmetric. Methods for making the HEMT are also disclosed.

Abstract: A system maintains a knowledge layout to support the building of event and analytics models in parity. The system uses the event models to provide a snapshot of the relevant conditions present when a challenge event occurs. The system uses the analytics models to select one or more actions (which may include robotic tasks) to respond to the challenge condition. In some cases, the system may render continued response compulsory until a successful response to the challenge event is achieved.

Abstract: A novel and useful neural network (NN) processing core incorporating inter-device connectivity and adapted to implement artificial neural networks (ANNs). A chip-to-chip interface spreads a given ANN model across multiple devices in a seamless manner. The NN processor is constructed from self-contained computational units organized in a hierarchical architecture. The homogeneity enables simpler management and control of similar computational units, aggregated in multiple levels of hierarchy. Computational units are designed with minimal overhead as possible, where additional features and capabilities are aggregated at higher levels in the hierarchy. On-chip memory provides storage for content inherently required for basic operation at a particular hierarchy and is coupled with the computational resources in an optimal ratio. Lean control provides just enough signaling to manage only the operations required at a particular hierarchical level.

Abstract: Methods, devices, media, and other embodiments are described for generating, modifying, and outputting pseudorandom animations that can be synchronized to audio data. In one embodiment, a computer animation model made up of comprising one or more control points is accessed by one or more processors, which associate motion patterns with a first control point of the one or more control points, and associate one or more speed harmonics with the first control point. A set of motion states is identify with a motion state for the combinations of possibilities, and a probability value is assigned to each motion state of the set of motion states. The probability value can be used to probabilistically determine a particular motion state to be part of displayed animation for the computer animation model.

Abstract: A method for determining a focal point depth of a user of a three dimensional (“3D”) display device includes tracking a first gaze path of the user. The method also includes analyzing 3D data to identify one or more virtual objects along the first gaze path of the user. The method further includes when only one virtual object intersects the first gaze path of the user identifying a depth of the only one virtual object as the focal point depth of the user.

Abstract: A semiconductor device includes: a conductive semiconductor substrate in which a trench is formed on the first main surface; a plurality of conductive layers, each of which is either a first conductive layer or a second conductive layer, which are laminated on one another along a surface normal direction of a side surface of the trench; and dielectric layers arranged between a conductive layer closest to the side surface of the trench among the plurality of conductive layers and the side surface of the trench, and between the plurality of corresponding conductive layers. The first conductive layer is electrically insulated from the semiconductor substrate, and the semiconductor substrate that electrically connects to the second conductive layer inside the trench electrically connects to the second electrode.

Abstract: Media content is received for streaming to a user device. A neural network is trained based on a first portion of the media content. Weights of the neural network are updated to overfit the first portion of the media content to provide a first overfitted neural network. The neural network or the first overfitted neural network is trained based on a second portion of the media content. Weights of the neural network or the first overfitted neural network are updated to overfit the second portion of the media content to provide a second overfitted neural network. The first portion and the second portion of the media content are sent with associations to the first overfitted neural network and the second overfitted to the user equipment.

Abstract: A tangible, non-transitory, computer-readable medium includes instructions.