Abstract: A system, apparatus, method and computer program product are provided for determining a mobile device integrity status. Images of a mobile device captured by the mobile device and using a reflective surface are processed with various trained models, such as neural networks, to verify authenticity, detect damage, and to detect occlusions. A mask is generated to enable identification of concave occlusions or blocked corners of an object, such as a mobile device, in an image. Images of the front and/or rear of a mobile device are processed to determine the mobile device integrity status such as verified, not verified, or inconclusive. A user is prompted to remove covers, remove occlusions, and/or move the mobile device closer to the reflective surface. A real-time response relating to the mobile device integrity status may be provided. The trained models may be trained to improve the accuracy of the mobile device integrity status.

Abstract: A system, apparatus, method and computer program product are provided for determining a mobile device integrity status. Images of a mobile device captured by the mobile device and using a reflective surface are processed with various trained models, such as neural networks, to verify authenticity, detect damage, and to detect occlusions. A mask may be generated to enable identification of concave occlusions or blocked corners of an object, such as a mobile device, in an image. Images of the front and/or rear of a mobile device may be processed to determine the mobile device integrity status such as verified, not verified, or inconclusive. A user may be prompted to remove covers, remove occlusions, and/or move the mobile device closer to the reflective surface. A real-time response relating to the mobile device integrity status may be provided. The trained models may be trained to improve the accuracy of the mobile device integrity status.

Abstract: Embodiments of the present disclosure provided herein include systems, apparatuses, and methods for network analysis. In various embodiments, a network may include an area wide network and a plurality of user electronic devices. Example embodiments of network analysis include area wide network analysis, user electronic device analysis, and troubleshooting and diagnostics associated with the area wide network and the user electronic devices. In various embodiments the network analysis may be based on network event or a fault.

Abstract: Embodiments of the present disclosure provided herein include methods, computer readable mediums, apparatus, and systems for facilitating diagnosis and repair of one or more performance states associated with a computing device.

Abstract: Embodiments of the present disclosure provided herein include methods, computer readable mediums, apparatus, and systems for facilitating diagnosis and repair of one or more performance states associated with a computing device.

Abstract: A system, apparatus, method and computer program product are provided for determining a mobile device integrity status. Images of a mobile device captured by the mobile device and using a reflective surface are processed with various trained models, such as neural networks, to verify authenticity, detect damage, and to detect occlusions. A mask may be generated to enable identification of concave occlusions or blocked corners of an object, such as a mobile device, in an image. Images of the front and/or rear of a mobile device may be processed to determine the mobile device integrity status such as verified, not verified, or inconclusive. A user may be prompted to remove covers, remove occlusions, and/or move the mobile device closer to the reflective surface. A real-time response relating to the mobile device integrity status may be provided. The trained models may be trained to improve the accuracy of the mobile device integrity status.

Abstract: In some examples, a device includes a selector circuit configured to deliver power to a first driver circuit, where the first driver circuit is configured to activate and deactivate a first switch of a postregulator. The device also includes a startup regulator and a controller configured to cause the selector circuit to deliver power from the startup regulator to the first driver circuit. The controller is also configured to determine that a boost regulator is operational after delivering power from the startup regulator to the first driver circuit. The controller is further configured to cause the selector circuit to deliver power from the boost regulator to the first driver circuit in response to determining that the boost regulator is operational.

Abstract: Various embodiments of the disclosure provide apparatuses, methods, and computer program products for network-centric augmented reality processing. Various embodiments provide advantages in network analytics, and additional advantages in positioning devices and/or objects in a premises to improve network quality at position(s) in the premises. Example embodiments process received camera data to map positions in an augmented reality environment to a networked device set, a network access device set, an object set, and/or a corner set indicted in the camera data. Additionally or alternatively, some embodiments generate an environment plot based on the processed camera data. Some embodiments additionally or alternatively enable initiation of a session for servicing of one or more devices in the premises, and/or providing device protection program information associated with the one or more devices.

Abstract: Embodiments of the present disclosure provide for predicted operational support data object selection and provision functionality. Predicted operational support data object(s) may be selected and provided to address particular malfunction classification(s) affecting networked device(s) on a dynamic home communications network. Some embodiments include identifying, in real-time, a device identification data set associated with a networked device set communicable with the dynamic home communications network; retrieving a device activity data set associated with the networked device set; applying a malfunction classification data model to the device activity data set to select the predicted operational support data object from the device operational support management repository; and outputting the predicted operational support data object to a client device in communication with the dynamic home communications network.

Abstract: A system, apparatus, method and computer program product are provided for determining a mobile device integrity status. Images of a mobile device captured by the mobile device and using a reflective surface are processed with various trained models, such as neural networks, to verify authenticity, detect damage, and to detect occlusions. A mask may be generated to enable identification of concave occlusions or blocked corners of an object, such as a mobile device, in an image. Images of the front and/or rear of a mobile device may be processed to determine the mobile device integrity status such as verified, not verified, or inconclusive. A user may be prompted to remove covers, remove occlusions, and/or move the mobile device closer to the reflective surface. A real-time response relating to the mobile device integrity status may be provided. The trained models may be trained to improve the accuracy of the mobile device integrity status.

Abstract: A system, method, and computer program product for identifying location-specific faults are provided. Some embodiments may include receiving first device status data associated with a first computing device and the first device status data may comprise first location-indicative data indicative of a location. Some embodiments may include comparing the first device status data with second device status data associated with one or more second computing devices and the second device status data may comprise second location-indicative data indicative of the location. In some embodiments, based on the comparison of the first device status data and the second device status data, determining that the first computing device is affected by one or more of a device-specific fault or a location-specific fault. Some embodiments may include causing information regarding the device-specific fault or the location-specific fault to be displayed via a graphical user interface.

Abstract: This disclosure describes a protection circuit configured to protect a power converter. The protection circuit may be configured to determine when the power converter is operating in a tristate mode, and upon determining that the power converter is operating in the tristate mode, to disable a supply to the power converter based on a comparison of a switch node voltage on a switch node of the power converter to a feedback node voltage on an output node of the power converter.

Abstract: In some examples, a device includes a selector circuit configured to deliver power to a first driver circuit, where the first driver circuit is configured to activate and deactivate a first switch of a postregulator. The device also includes a startup regulator and a controller configured to cause the selector circuit to deliver power from the startup regulator to the first driver circuit. The controller is also configured to determine that a boost regulator is operational after delivering power from the startup regulator to the first driver circuit. The controller is further configured to cause the selector circuit to deliver power from the boost regulator to the first driver circuit in response to determining that the boost regulator is operational.

Abstract: This disclosure describes a protection circuit configured to protect a power converter. The protection circuit may be configured to determine when the power converter is operating in a tristate mode, and upon determining that the power converter is operating in the tristate mode, to disable a supply to the power converter based on a comparison of a switch node voltage on a switch node of the power converter to a feedback node voltage on an output node of the power converter.

Abstract: Embodiments of the present disclosure provided herein include methods, computer readable mediums, apparatus, and systems for facilitating diagnosis and repair of one or more performance states associated with a computing device.

Abstract: A system, apparatus, method and computer program product are provided for determining a mobile device integrity status. Images of a mobile device captured by the mobile device and using a reflective surface are processed with various trained models, such as neural networks, to verify authenticity, detect damage, and to detect occlusions. A mask may be generated to enable identification of concave occlusions or blocked corners of an object, such as a mobile device, in an image. Images of the front and/or rear of a mobile device may be processed to determine the mobile device integrity status such as verified, not verified, or inconclusive. A user may be prompted to remove covers, remove occlusions, and/or move the mobile device closer to the reflective surface. A real-time response relating to the mobile device integrity status may be provided. The trained models may be trained to improve the accuracy of the mobile device integrity status.