Abstract: A networking device may determine that communications that is it receiving or sending to a computing device would not use all of the bandwidth of a channel when those communications are being sent or received. The networking device may determine other communications from the computing device or other computing devices to send communications to or from. The networking device may allocate different portions of the bandwidth for each of those communications to be sent or received by the networking device.

Abstract: A system and method for estimating free space and assigning free space probabilities in point cloud data associated with an autonomous vehicle traveling on a surface, including taking into account sensor noise, sensor availability, obstacle heights, and distance of obstacles from the sensor. System and method can include determining surface planes and classifying point cloud points according to whether or not the points fall on surface planes, among other factors.

Abstract: Methods and systems provide for providing video-based chapter generation for a communication session. In one embodiment, the system receives a transcript and video content of a communication session between participants, the transcript including timestamps for a number of utterances associated with speaking participants; processes the video content to extract one or more pieces of textual content visible within the frames of the video content; segments frames of the video content into a number of contiguous topic segments; determines a title for each topic segment from one or more of: the transcript, and the extracted textual content; assigns a category label for each topic segment from a prespecified list of category labels; and transmits, to one or more client devices, the list of topic segments with determined title and assigned category label for each of the merged topic segments.

Abstract: A method for tilt correction of a video by an electronic device. The method may include receiving a user selection of the video. The method may include identifying a sequence of image frames of the video representing a scene in the video. The method may include determining a degree of tilt in each image frame of the sequence of image frames. The method may include determining whether cause of tilt in the sequence of image frames is un-intentional by analyzing the degree of tilt in each image frame using a trained Artificial Intelligence (AI) model. The method may include performing the tilt correction on the sequence of image frames based on the cause of tilt being un-intentional.

Abstract: A method performed by an apparatus is described. The method includes receiving map data that is based on first image data, second image data, and a similarity metric. The first image data can be received from a first vehicle and represent an object. The second image data can be received from a second vehicle and represent the object. The similarity metric can be associated with the object represented in the first image data and the object represented in the second image data. The method can also include storing, by a vehicle, the received map data and localizing the vehicle based on the stored map data.

Abstract: A system and method for estimating free space and assigning free space probabilities in point cloud data associated with an autonomous vehicle traveling on a surface, including taking into account sensor noise, sensor availability, obstacle heights, and distance of obstacles from the sensor. System and method can include determining surface planes and classifying point cloud points according to whether or not the points fall on surface planes, among other factors.

Abstract: Methods, systems, apparatuses, and computer program products for displaying electromagnetic spectrum information for UAV navigation are disclosed. In a particular embodiment, a method of displaying electromagnetic spectrum information for UAV navigation includes an electromagnetic spectrum awareness controller, of a control device associated with a UAV, that generates a first map layer based on electromagnetic spectrum map data; and displays, on a display of the control device, the first map layer overlaid on a base image.

Abstract: Methods, systems, apparatuses, and computer program products for geofence management with an unmanned aerial vehicle (UAV) are disclosed. In a particular embodiment, a method of geofence management with a UAV includes a geofence manager utilizing a first set of sensor data collected by a first set of in-flight UAVs of the UAV system to detect a first object. In this embodiment, the geofence manager also utilizes the first set of sensor data to determine a first location of the detected first object and determines whether the first location of the detected first object is within a geofence of an area.

Abstract: Methods and systems provide for real-time meeting notes within a communication session.

Abstract: In described examples, an integrated circuit (IC) includes an isolation, an input/output (IO), and a low power mode (LPM) control logic. The isolation includes a level shift with pull-down configured to weakly pull down the voltage of signals that travel through the isolation. The IO includes an input and a physical connector for coupling to a power management IC. The IO provides an asserted-low LPM enable signal to the physical connector in response to the IO input. An output of the LPM control logic is coupled via the isolation to the input of the IO. The LPM control logic provides a high voltage signal to the input of the IO as a default during power on reset (POR) of the IC. The pull-down pulls the LPM enable signal voltage to the asserted low voltage in response to a voltage of the LPM enable signal falling below a threshold.

Abstract: This disclosure proposes systems and methods for leveraging entity-related language models in speech processing. A system can receive audio data corresponding to an utterance and perform automatic speech recognition (ASR) on a first portion of the audio data using a general language model. Based on the results, the system may identify a specific language model for processing a second portion of the audio data. The specific language model may include entities belonging to a common subject or class. The specific language model may, in some cases, provide better results than the general language model. While the general language model may describe a whole sentence, the specific language model may describe only a portion of a sentence. Thus, a top-level model may “activate” the specific language model when it may provide useful results. The resulting data may include results from both the general language model and the specific language model.

Abstract: Disclosed are techniques for determining a motion state of a target object. In an aspect, an on-board computer of an ego vehicle detects the target object in one or more images, determines one or more first attributes of the target object based on measurements of the one or more images, determines one or more second attributes of the target object based on measurements of a map of a roadway on which the target object is travelling, and determines the motion state of the target object based on the one or more first attributes and the one or more second attributes of the target object.

Abstract: The present disclosure relates to a pre-5th-Generation (5G) or 5G communication system to be provided for supporting higher data rates Beyond 4th-Generation (4G) communication system such as long term evolution (LTE). Methods and systems for optimizing computation of log-likelihood ratio (LLR) for decoding modulated symbols. A method disclosed herein involves receiving at least one symbol transmitted from at least one device, wherein the received at least one symbol is encoded and modulated symbol including a plurality of data bits. The method further includes computing a log-likelihood ratio (LLR) of each bit in the received at least one symbol for decoding the received at least one symbol using a centroid method that involves exploiting a symmetry of a constellation of code words and/or a uncertainty region defined on a constellation of code words.

Abstract: Methods, systems, apparatuses, and computer program products for incentivizing UAV use are disclosed. In a particular embodiment, incentivizing UAV use includes UAV pilot recommendation by a computing system. In this embodiment, the computing system receives at least one parameter related to a prospective UAV mission and retrieves UAV flight records of a plurality of UAV pilots. According to this embodiment, the computing system recommends, based on the at least one parameter and the UAV flight records, at least one UAV pilot for the prospective UAV flight.

Abstract: Example implementations relate to performing automated hierarchical configuration tuning for a multi-layer service. According to an example, a service definition and optimization criteria are received for tuning a configuration of a service. The service definition includes information regarding multiple of layers of the service and corresponding configuration groups. An acyclic dependency graph is created including nodes representing each of the of layers and each of the corresponding configuration groups.

Abstract: Methods, systems, apparatuses, and computer program products for UAV module management are disclosed. In a particular embodiment, UAV module management includes software module library management by a computing system. In this embodiment, the computing system presents information representing a plurality of UAV software modules, receives information representing a UAV software module selection, and adds the UAV software module identified by the information representing a UAV software module selection to a UAV software module library. According to this embodiment, the computing system adds, based on a selection of a UAV software module, the selected UAV module to a UAV software module library.

Abstract: Methods, systems, apparatuses, and computer program products for predictive maintenance of an unmanned aerial vehicle (UAV) are disclosed. In a particular embodiment, a method of predictive maintenance of a UAV includes a maintenance controller detecting a deviation in an expected behavior of a UAV and determining whether to attribute the deviation to any environmental interferences. In this example embodiment, after determining to not attribute the deviation to any environmental interferences, the maintenance controller schedules the UAV for maintenance.

Abstract: Methods, systems, apparatuses, and computer program products for increasing awareness of an environmental condition for an unmanned aerial vehicle (UAV) are disclosed. In a particular embodiment, a method of increasing awareness of an environmental condition for a UAV includes an environmental awareness controller utilizing data associated with a first UAV to detect an environmental condition at a location associated with the first UAV. In this embodiment, the environmental awareness controller also updates environmental condition information associated with the location to indicate detection of the environmental condition at the location and provides the updated environmental condition information to a device associated with second UAV.

Abstract: Methods, apparatuses, system, devices, and computer program products for unmanned aerial vehicle (UAV) response to object detection are disclosed. In a particular embodiment, a detection response controller receives data generated by one or more sensors of a UAV. Based on the generated data, the detection response controller determines a presence and an identification of an object in a proximity of the UAV. Based on the presence and the identification of the object, the detection response controller determines one or more actions for the UAV to perform.

Abstract: Methods, systems, apparatuses, and computer program products for multi-objective mission planning and execution for an unmanned aerial vehicle (UAV) are disclosed. In a particular embodiment, multi-objective mission planning and execution for a UAV includes a computing device detecting a mode change event associated with a UAV executing a mission in a first mission mode. In this embodiment, the computing device determines, based on the mode change event, a second mission mode for the UAV and switches a current mission mode of the UAV from the first mission mode to the second mission mode.