Abstract: A method includes identifying, at an electronic device a candidate name responsive to user input indicating a salutational trigger during composition of a body of a message of a messaging application. Identifying the candidate name including at least one of: parsing a recipient-specific portion of a recipient message address of the message; parsing a display name associated with the recipient message address; parsing a content of the message body; parsing an attachment name associated with an attachment field of the message; identifying the candidate name from a contact record selected from a contacts database based on a recipient-specific portion of a recipient message address of the message; and parsing user-readable content of an application from which composition of the message was triggered. The method further includes facilitating composition of a recipient name in the body of the message based on the candidate name.

Abstract: In some embodiments, a method comprises receiving, at a processor of an autonomous vehicle and from at least one sensor, sensor data distributed within a time window. A first event being a first event type occurring at a first time in the time window is identified by the processor using a software model based on the sensor data. At least one first attribute associated with the first event is extracted by the processor. A second event being the first event type occurring at a second time in the time window is identified by the processor based on the at least one first attribute. In response to determining that the second event is not yet recognized as being the first event type, a first label for the second event is generated by the processor.

Abstract: An apparatus includes a processor configured to be disposed with a vehicle and a memory coupled to the processor. The memory stores instructions to cause the processor to receive, at least two of: radar data, camera data, lidar data, or sonar data. The sensor data is associated with a predefined region of a vicinity of the vehicle while the vehicle is traveling during a first time period. At least a portion of the vehicle is positioned within the predefined region during the first time period. The method also includes detecting that no other vehicle is present within the predefined region. An environment of the vehicle during the first time period is classified as one state from a set of states that includes at least one of dry, light rain, heavy rain, light snow, or heavy snow, based on at least two of the sensor data to produce an environment classification. An operational parameter of the vehicle based on the environment classification is modified.

Abstract: Various embodiments for customizing a dynamic navigation system are described herein. An embodiment operates by receiving a request from a support user device for debug access to an application. A predetermined time period for which to provision a set of computing resources is identified and the set of computing resources are provisioned for a pod on a server. Both a first container including access to a new instance of the application and a second container providing access to a debugger program are generated for the pod. Upon determining that the predetermined time period has expired, access to the provisioned set of computing resources of the pod is revoked, and the provisioned set of computing resources to be made available for other processes of the server.

Abstract: Embodiments herein describe computer-implemented methods, computer program products, and computer systems for updating data templates. In an embodiment, one or more processors may be configured for receiving change data from tenant spaces configured to update tenant data templates of the tenant spaces; generating metadata for each of the tenant spaces corresponding to the change data; determining least common change data based on the metadata; generating change request data for a multi-cloud management platform (MCMP) data template based on the least common change data; and transmitting the change request data to the one or more tenant data templates. The method may further include initializing the MCMP configured to execute a multi-tenant deployment model having the MCMP data template, wherein the MCMP is connected to the tenant spaces.

Abstract: Techniques described herein relate to a method for managing financial service requests. The method includes obtaining, by a prediction manager, a financial service request (FSR) from a client; obtaining historical information associated with the FSR; generating prediction model inputs using the FSR and the historical information; identifying FSR agent comments associated with the FSR; generating a request vector using the FSR agent comments; generating an FSR authenticity index using the request vector and the prediction model inputs; applying a first machine learning model to the FSR authenticity index and the prediction model inputs to generate a first prediction; providing the first prediction to a first approver; and obtaining first approver comments from the first approver.

Abstract: A machine implemented method and system, including: receiving at a near real-time processor module, one or more tenant-specific business objects from a message handler module; receiving at the near real-time processor module, contextual data related to the received one or more tenant-specific business objects from a platform analytics module; forming at the near real-time processor module, one or more events by applying one or more pre-defined analytic models to the received contextual data and the received one or more tenant-specific business objects; receiving at a message publisher module, one or more events from the near real-time processor module; and transmitting the received one or more events to one or more subscribers for the one or more events.

Abstract: An apparatus includes a processor configured to be disposed with a vehicle and a memory coupled to the processor. The memory stores instructions to cause the processor to receive, at least two of: radar data, camera data, lidar data, or sonar data. The sensor data is associated with a predefined region of a vicinity of the vehicle while the vehicle is traveling during a first time period. At least a portion of the vehicle is positioned within the predefined region during the first time period. The method also includes detecting that no other vehicle is present within the predefined region. An environment of the vehicle during the first time period is classified as one state from a set of states that includes at least one of dry, light rain, heavy rain, light snow, or heavy snow, based on at least two of the sensor data to produce an environment classification. An operational parameter of the vehicle based on the environment classification is modified.

Abstract: A computer vision processor of a camera generates hyperzooms for persons or vehicles from image frames captured by the camera. The hyperzooms include a first hyperzoom associated with the persons or vehicles. The computer vision processor tracks traffic patterns of the persons or vehicles while obviating network usage by the camera by predicting positions of the persons or vehicles using a Kalman Filter from the first hyperzoom. The persons or vehicles are detected in the second hyperzoom. The positions of the persons or vehicles are updated based on detecting the persons or vehicles in the second hyperzoom. The first hyperzoom is removed from the camera. Tracks of the persons or vehicles are generated based on the updated positions. The second hyperzoom is removed from the camera. Track metadata is generated from the tracks for storing in a key-value database located on a non-transitory computer-readable storage medium of the camera.

Abstract: A computer vision processor of a camera extracts attributes of persons or vehicles from hyperzooms generated from image frames. The hyperzooms represent traffic patterns. The extracting is performed using a feature extractor of an on-camera convolutional neural network (CNN) including an inverted residual structure. The attributes include at least colors of clothing of the persons or colors of the vehicles. Mobile semantic segmentation models of the CNN are generated using the hyperzooms and the attributes. Attribute analytics are generated by executing the mobile semantic segmentation models while obviating network usage by the camera. The attribute analytics are stored in a key-value database located on a memory card of the camera. A query is received from the server instance specifying one or more of the attributes. The attribute analytics are filtered using the one or more of the attributes to obtain a portion of the traffic patterns.

Abstract: Aspects of the present disclosure control aging of a signal path in an idle mode to mitigate aging. In one example, an input of the signal path is alternately parked low and high over multiple idle periods to balance the aging of devices (e.g., transistors) in the signal path. In another example, a clock signal (e.g., a clock signal with a low frequency) is input to the signal path during idle periods to balance the aging of devices (e.g., transistors) in the signal path. In another example, the input of the signal path is parked high or low during each idle period based on an aging pattern.

Abstract: An electronic device, computer program product, and method enable selection and presentation of media content associated with a person identified in a monitored space. The electronic device includes a device interface that is communicatively coupled to a media output device that presents media content in the monitored area. A controller of the electronic device is communicatively coupled to sensor(s) and the media output device. The controller presents a default selection of media content on the media output device. The controller monitors the sensor(s) to detect a presence of a person within or approaching the monitored area. The controller identifies the person. The controller selects, from among a plurality of available media content, media content that is associated with the identified person. The controller presents the selected media content on the media output device.

Abstract: Automatic license plate recognition occurs when a light sensor that continually captures video detects motion as a vehicle is driven through a gate. The light sensor detects the vehicle and license plate in the video stream captured by the light sensor. An algorithm associated with the video stream of the light sensor is trained to detect license plates. The light sensor starts executing the recognition algorithm when it detects motion. Recognition of characters in the license plate is based upon an aggregation of several captured video frames in which a license plate is detected.

Abstract: In some embodiments, a method comprises receiving, at a processor of an autonomous vehicle and from at least one sensor, sensor data distributed within a time window. A first event being a first event type occurring at a first time in the time window is identified by the processor using a software model based on the sensor data. At least one first attribute associated with the first event is extracted by the processor. A second event being the first event type occurring at a second time in the time window is identified by the processor based on the at least one first attribute. In response to determining that the second event is not yet recognized as being the first event type, a first label for the second event is generated by the processor.

Abstract: Embodiments herein describe computer-implemented methods, computer program products, and computer systems for updating data templates. In an embodiment, one or more processors may be configured for receiving change data from tenant spaces configured to update tenant data templates of the tenant spaces; generating metadata for each of the tenant spaces corresponding to the change data; determining least common change data based on the metadata; generating change request data for a multi-cloud management platform (MCMP) data template based on the least common change data; and transmitting the change request data to the one or more tenant data templates. The method may further include initializing the MCMP configured to execute a multi-tenant deployment model having the MCMP data template, wherein the MCMP is connected to the tenant spaces.

Abstract: Disclosed is a method for boosting (e.g., improving) graphics performance of an electronic device. The method for boosting graphics performance of an electronic device comprises: determining a context of the electronic device for boosting the graphics performance, determining a current state of the electronic device, determining at least one graphics configuration of hardware components of the electronic device and at least one application of the electronic device based on the context of the electronic device and the current state of the electronic device and generating a virtual display for displaying the at least one application based on the at least one graphics configuration of the hardware components and the at least one application.

Abstract: A computer vision processor of a camera extracts attributes of persons or vehicles from hyperzooms generated from image frames. The hyperzooms represent traffic patterns. The extracting is performed using a feature extractor of an on-camera convolutional neural network (CNN) including an inverted residual structure. The attributes include at least colors of clothing of the persons or colors of the vehicles. Mobile semantic segmentation models of the CNN are generated using the hyperzooms and the attributes. Attribute analytics are generated by executing the mobile semantic segmentation models while obviating network usage by the camera. The attribute analytics are stored in a key-value database located on a memory card of the camera. A query is received from the server instance specifying one or more of the attributes. The attribute analytics are filtered using the one or more of the attributes to obtain a portion of the traffic patterns.

Abstract: Various methods and systems are provided for an ultrasound transducer structure for an ultrasound probe and methods of manufacturing thereof. In one example, the ultrasound transducer structure may include a lens, an acoustic stack disposed on the lens, and an acoustic backing material bonded to a side of the acoustic stack facing away from the lens without any intervening layer between the acoustic backing material and the acoustic stack, such that the acoustic backing material is in face-sharing contact with the side of the acoustic stack, wherein the acoustic backing material is composed of a solidified blend comprising a backing polymer.

Abstract: A test management system utilizes an adaptive cohort selection technique to dynamically select and update a cohort of clients for testing a feature of a computer security application. The test management system selects an initial cohort based on high level parameters of the test including the feature to be evaluated and the statistical confidence level for the outcome. During the test, the test management system obtains real-time telemetry data relevant to evaluating the test. Depending on how the test is tracking relative to the test objectives, test management system may dynamically modify the cohort by expanding the size of the cohort or changing the cohort membership.

Abstract: Techniques for improved analysis and simulation of an IC design are disclosed. Simulation activity for an integrated circuit (IC) design is identified using one or more processors. One or more potential improvements to a simulation of the IC design are generated based on the simulation activity, the one or more potential improvements relating to at least one of signal activity or process activity, during simulation, reflected in the simulation activity. A hardware description language (HDL) design file corresponding to the IC design is modified to indicate the one or more potential improvements to the simulation.