Abstract: Disclosed are methods and devices for a gesture-enabled tool that enables a user to assemble a data bundle using a single continuous gesture to select items for the data bundle from a plurality of menus or lists and to deliver the data bundle to a recipient as part of the single continuous gesture.

Abstract: A framework to manage coexistence of multiple technologies over multiple channels is desired. The apparatus may be a user equipment (UE). The UE detects whether a second technology different from a first communication technology utilized by the UE is active on a first channel. The UE performs, based on the detection, an action associated with assigning the first communication technology to at least one of the first channel or a second channel.

Abstract: Apparatuses, methods and storage medium associated with scheduling of threads and/or virtual machines, are disclosed herein. In embodiments, an apparatus is provided with a scheduler of an operating system and/or a virtual machine monitor. The scheduler is to retrieve or receive capabilities of the cores of one or more multi-core processors of the apparatus with diverse capabilities, and schedule a plurality of threads for execution on selected one or ones of the cores, based at least in part on the capabilities of the cores and characteristics of the plurality of threads. The virtual machine monitor is to retrieve or receive capabilities of the cores, and schedule a plurality of virtual machines for execution on selected one or ones of the cores, based at least in part on the capabilities of the cores and respective priorities of the virtual machines. Other embodiments may be described and/or claimed.

Abstract: A multi-modal meter of a vehicle obtains information from multiple sources to determine the most accurate values of motion parameters of the vehicle. The multi-modal meter obtains data describing motion of a vehicle from various sources including an on-board diagnostics (OBD) and global positioning system (GPS.) The dynamically evaluates the signal sources for their accuracy as the vehicle travels. The multi-modal meter selects different signal sources for different portions of a ride and uses the data from the selected signal sources to determine the most accurate motion parameters. The multi-modal meter use machine learning techniques to generate metadata used by an engine configured to determine the most accurate values of motion parameters of the vehicle.

Abstract: A system receives one or more messages including information related to one or more issues associated with a software application installed on a user device. In response to receiving the message, a processor in the system identifies a user context associated with the user device, wherein the user context comprises usage information related to the software application. The processor further analyzes the received information and the user context associated with the user device to determine one or more errors associated with the software application. One or more software updates that are available and associated with the one or more errors are determined. The system automatically installs one or more of the determined software updates on the user device. Embodiments of the present invention further include a method and computer program product for managing and installing one or more software updates in substantially the same manner as is described above.

Abstract: An exemplary embodiment herein is a method including comparing a cache hit rate ratio of a unified cache to a first pre-determined threshold, incrementing an alert counter in response to the cache hit rate ratio being lower than the first pre-determined threshold, comparing the alert counter to a pre-determined limit, preventing a first receipt of a type of data by the unified cache in response to the alert counter being equal to the pre-determined limit, causing a second receipt of metadata by the unified cache, comparing the cache hit rate ratio to a second pre-determined threshold, and allowing the first receipt of the type of data by the unified cache in response to the cache hit rate ratio being greater than the second pre-determined threshold.

Abstract: The disclosure includes embodiments for establishing millimeter wave vehicle-to-vehicle communications for data sharing. In some embodiments, a method includes receiving, at an ego vehicle, a first beacon from a first vehicle, wherein the first beacon includes first scheduling information and first localization information and the first beacon is broadcast as a millimeter wave (mmWave) communication. The method includes determining a schedule based on the first scheduling information. The method includes broadcasting a second beacon based on the schedule. The method includes establishing a current link between the ego vehicle and the first vehicle. The method includes transmitting data to the first vehicle using the current link based on the schedule.

Abstract: Example method includes: detecting, by a network device, a first wireless communication channel in a first wireless band that a mesh portal node communicates on; establishing, by the network device, a first backhaul connection to the mesh portal node with a first radio of a mesh point node using the first wireless communication channel in the first wireless frequency band; assigning, by the network device, a second and different radio to communicate on a second and different wireless communication channel in the first wireless frequency band; and establishing, by the network device, a second backhaul connection to another mesh point node with the second and radio on the second wireless communication channel.

Abstract: A counterfeit detection system provides an artificial intelligence (AI) platform that implements a Generative Adversarial Network (GAN) to classify an image as one of a fake or genuine item and integrates a Classification Activation Module (CAM) to refine counterfeit detection. The GAN may include a generator that generates simulated counterfeit images for a discriminator. The discriminator may be trained to identify faked items by learning from the simulated counterfeit images and/or images of actual faked items. The discriminator may implement a deep neural network of convolutional layers that each analyze a region of an image and produce a weighted output that contributes to the classification based on the analyzed region. The CAM may identify the regions and weights relied upon by the discriminator, provide corresponding heatmaps to subject matter experts, receive annotations from the subject matter experts, and use the annotations as feedback to refine the classifier of the discriminator.

Abstract: Mechanisms are provided for training a classifier to identify adversarial input data. A neural network processes original input data representing a plurality of non-adversarial original input data and mean output learning logic determines a mean response for each intermediate layer of the neural network based on results of processing the original input data. The neural network processes adversarial input data and layer-wise comparison logic compares, for each intermediate layer of the neural network, a response generated by the intermediate layer based on processing the adversarial input data, to the mean response associated with the intermediate layer, to thereby generate a distance metric for the intermediate layer. The layer-wise comparison logic generates a vector output based on the distance metrics that is used to train a classifier to identify adversarial input data based on responses generated by intermediate layers of the neural network.

Abstract: Systems and methods provide a nonreciprocal nanophotonic modulator. In some examples, the modulator utilizes acoustic pumping, instead of optical pumping with lasers, and is capable of achieving GHz bandwidth.

Abstract: Disclosed is a method for making shelf-stable nitrogenous organic acid (e.g., creatine) ingredients for products such as nutritional bars, liquids, and/or powders.

Abstract: Various implementations described herein are directed to an integrated circuit having memory circuitry with an array of bitcells. The integrated circuit may include read-write circuitry that is coupled to the memory circuitry to perform read operations and write operations for the array of bitcells. The integrated circuit may include write assist circuitry that is coupled to the memory circuitry and the read-write circuitry. The write assist circuitry may receive a control signal from the read-write circuitry. Further, the write assist circuitry may sense write operations based on the control signal and may drive the write operations for the array of bitcells.

Abstract: The disclosure includes embodiments for performing beam alignment for non-line of sight (NLOS) scenarios. The method includes receiving, at a first vehicle, one or more wireless messages that include vehicle data, wherein the vehicle data describes a second vehicle position, a second vehicle speed, and a second vehicle heading. The method also includes determining sensor data. The method also includes determining an NLOS path based on the vehicle data and the sensor data so that the NLOS path avoids a potential blockage. The method also includes determining whether the NLOS path is predicted to succeed based on a beam transmission percentage satisfying a threshold percentage. The method also includes responsive to the NLOS path being predicted to succeed, performing beam alignment between the first vehicle and the second vehicle based on the NLOS path before the potential blockage is predicted to occur.

Abstract: An example of an apparatus including a network interface to receive enrollment data from a device, wherein the device is identified by a device identifier. The apparatus further includes a memory storage unit connected to the network interface. The memory storage unit receives device history data associated with the device identifier while the device is enrolled. The memory storage unit is also to maintain a database to store the device history data associated with the device identifier. The apparatus also includes a processor to receive a de-enrollment command associated with the device via the network interface. The de-enrollment command causes the processor to modify the device identifier stored in the database.

Abstract: A computing device includes at least one hardware processor and a machine-readable storage medium. The machine-readable storage medium stores instructions executable by the processor to: perform empirical mode decomposition of utilization data for a computing resource to generate a plurality of component functions; generate a plurality of neural networks via the plurality of component functions; generate, via the plurality of neural networks, a composite utilization forecast for the computing resource; and allocate the computing resource based on the composite utilization forecast.

Abstract: A neural network is configured to suppress an output of a mitigation node in a mitigation layer of the neural network. The neural network is pre-configured to recognize objects from inputs when operating using a processor and a memory. An actual input is sent to the neural network for object recognition, the actual input is an altered input. By suppressing the output of the mitigation node, the neural network is caused to avoid falsely recognizing an object from the actual input, where the altered input is configured to cause the neural network to falsely recognize the object from the actual input.

Abstract: An aftertreatment component's shape, entrance geometry, and/or position within an aftertreatment assembly can be modified for local and/or bulk exhaust flow control. In some implementations, a body of the aftertreatment component has a non-circular cross-section, a non-circular opening, and/or a variable face geometry. The non-circular cross-section and/or opening can be a variety of different shapes.

Abstract: A charging system for an Implantable Medical Device (IMD) is disclosed having a charging coil and one or more sense coils preferably housed in a charging coil assembly coupled to an electronics module by a cable. The charging coil is preferably a wire winding, while the sense coils are preferably formed in one or more traces of a circuit board. One or more voltages induced on the one or more sense coils can be used to determine a phase angle between the voltage and a driving signal for the charging coil. The determined phase angle can then be used to determine the position of the charging coil relative to the IMD. Additionally, more than one parameter (phase angle, magnitude, resonant frequency) may be determined using the voltage may be used to determine position, including the radial offset and depth of the charging coil relative to the IMD.

Abstract: The proposed invention provides a method for calibrating a HMD device of a user in a vehicle. The method includes detecting user movements while viewing VR content in the vehicle and checking if these motions meet user movement criteria. The method also includes detecting if the vehicle is stationary or moving. Further, on detecting that the vehicle is stationary dynamically calibrating the HMD device based on the movements of the user and on detecting that the vehicle is in motion dynamically calibrating the HMD device based on vehicle movements and the movements of the user.