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.

A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.

A system for utilizing models derived from offline historical data in online applications is provided. The system includes a processor and a memory storing machine-readable instructions for determining a set of contexts of the usage data, and for each of the contexts within the set of contexts, collecting service data from services supporting the media service and storing that service data in a database. The system performing an offline testing process by fetching service data for a defined context from the database, generating a first set of feature vectors based on the fetched service data, and providing the first set to a machine-learning module. The system performs an online testing process by fetching active service data from the services supporting the media streaming service, generating a second set of feature vectors based on the fetched active service data, and providing the second set to the machine-learning module.

A method and apparatus for media decoding by a decoder include decoding a first indication indicative of a first conformance point of a coded video sequence. A second indication indicative of a second conformance point of the coded video sequence is decoded. It is determined whether the coded video sequence is decodable by the decoder based on at least one of the first indication and the second indication. The coded video sequence is selectively decoded based on determining whether the decoded video sequence is decodable by the decoder.

A method and apparatus for media decoding by a decoder include decoding a first indication indicative of a first conformance point of a coded video sequence. A second indication indicative of a second conformance point of the coded video sequence is decoded. It is determined whether the coded video sequence is decodable by the decoder based on at least one of the first indication and the second indication. The coded video sequence is selectively decoded based on determining whether the decoded video sequence is decodable by the decoder.

A peripheral device at startup selectively activates one of a plurality of connection profiles for low-energy communication with a central device. The profiles determine the behavior of the peripheral device as viewed by the central device, such as a selected one of a HID, a Reader/Scanner, and a PC/SC-like device. The activated profile is selected based on connection profile state maintained across power cycle events and in view of special button combination events at startup. According to embodiment, the profile can also be selected (in conjunction with a reboot) as commanded under select circumstances by an application running on the central device or based on the peripheral reading a configuration card. According to embodiment, the activated profile corresponds to selected sub-portions of a unified database file of the peripheral device. The unified database includes profile components enabling activation of a selected one a plurality of low-energy communication profiles.

A peripheral device at startup selectively activates one of a plurality of connection profiles for low-energy communication with a central device. The profiles determine the behavior of the peripheral device as viewed by the central device, such as a selected one of a HID, a Reader/Scanner, and a PC/SC-like device. The activated profile is selected based on connection profile state maintained across power cycle events and in view of special button combination events at startup. According to embodiment, the profile can also be selected (in conjunction with a reboot) as commanded under select circumstances by an application running on the central device or based on the peripheral reading a configuration card. According to embodiment, the activated profile corresponds to selected sub-portions of a unified database file of the peripheral device. The unified database includes profile components enabling activation of a selected one a plurality of low-energy communication profiles.

A fireworks kit can have a set of fireworks having multiple fireworks of different types and a plurality of detonators in communication with the fireworks that are configured to launch or detonate a firework attached thereto. A remote controller or mobile device can be in communication with the detonators and operable to provide dynamic or user customizable control of detonation, launching, or ignition of the fireworks.

System, device, and method of adaptive network protection for managed Internet-of-Things (IoT) services. A network traffic monitoring unit monitors data traffic, operations-and-management traffic, and control messages, that relate to cellular communication between an IoT device and a core cellular network. An IoT grouping unit groups multiple IoT devices into a particular IoT group. A baseline behavior determination unit determines a Regular Baseline Cellular Communication Behavior (RBCCB) profile that characterizes the cellular communications that are outgoing from and incoming to each member of the particular IoT group. An outlier detector subsequently detects that a particular IoT device of that particular IoT group, exhibits cellular traffic characteristics that are abnormal relative to the RBCCB profile that was characterized for that particular IoT group. An enforcement actions generator is triggered to selectively perform one or more enforcement operations, notification operations, and quarantine operations.

System, device, and method of adaptive network protection for managed Internet-of-Things (IoT) services. A network traffic monitoring unit monitors data traffic, operations-and-management traffic, and control messages, that relate to cellular communication between an IoT device and a core cellular network. An IoT grouping unit groups multiple IoT devices into a particular IoT group. A baseline behavior determination unit determines a Regular Baseline Cellular Communication Behavior (RBCCB) profile that characterizes the cellular communications that are outgoing from and incoming to each member of the particular IoT group. An outlier detector subsequently detects that a particular IoT device of that particular IoT group, exhibits cellular traffic characteristics that are abnormal relative to the RBCCB profile that was characterized for that particular IoT group. An enforcement actions generator is triggered to selectively perform one or more enforcement operations, notification operations, and quarantine operations.