Abstract: Various embodiments of the present disclosure improve existing multi-layer and other network technologies by routing and processing client requests that require machine learning based on the machine learning capabilities of each network device and/or other computer resource characteristics of different network devices. This ensures that network latency and throughput, among other computer resource consumption characteristics, will be improved as machine learning processing can occur at the most suitable network device or be distributed among various suitable network devices.

Abstract: Novel tools and techniques are provided for implementing encoding or decoding of adaptive bitrate streams. In various embodiments, one or more first computing systems may divide a live media content stream into one or more segments, each segment might include a starting segment boundary and an ending segment boundary. The one or more first computing systems might encode the one or more segments into one or more primary adaptive bitrate streams. The one or more first computing systems might also divide the one or more segments of the live media content stream into one or more subsegments. Each subsegment might be less than a length of a corresponding segment of the one or more segments. The one or more first computing systems might the encode and/or a second computing system might decode the one or more subsegments into or from one or more secondary adaptive bitrate streams.

Abstract: A vehicle control module includes a vehicle device and a vehicle network interface. The vehicle device is operable to perform a vehicle function. The vehicle network interface facilitates communication regarding the vehicle function between the vehicle device and a vehicle network fabric in accordance with a global vehicle network communication protocol.

Abstract: Novel tools and techniques are provided for implementing encoding or decoding of adaptive bitrate streams. In various embodiments, one or more first computing systems may divide a live media content stream into one or more segments, each segment might include a starting segment boundary and an ending segment boundary. The one or more first computing systems might encode the one or more segments into one or more primary adaptive bitrate streams. The one or more first computing systems might also divide the one or more segments of the live media content stream into one or more subsegments. Each subsegment might be less than a length of a corresponding segment of the one or more segments. The one or more first computing systems might the encode and/or a second computing system might decode the one or more subsegments into or from one or more secondary adaptive bitrate streams.

Abstract: A network may include multiple allocations. The allocations may include: a first allocation encompassing central infrastructure, such as central office servers, data centers, or other core infrastructure; an second allocation encompassing gateway elements or other central consumer premises network infrastructure; and a third allocation encompassing nodes, such as client devices, terminals, or other nodes. A virtualization management engine may coordinate resources from the various allocations to support virtual functions distributed over multiple allocations of the network. The virtualization management engine may determine the distribution across the allocations for the virtual functions. The virtualization management engine may be implemented as a virtual function and be distributed across the allocations of the network.

Abstract: A method is provided that includes setting, by a controller, a first bit-rate level for a next video segment, and comparing a fill level of a playback buffer to a first threshold. If the fill level of the playback buffer satisfies the first threshold, the first bit-rate level for the next video segment is replaced by setting a second bit-rate level for the next video. A first request is issued to a server for the next video segment encoded at the first bit-rate level or, if the fill level of the playback buffer satisfies the first threshold, encoded at the second bit-rate level and downloading of the requested next video segment and storing the requested video segment in the playback buffer. A decoder decodes the next video segment from the playback buffer for playback on a display device after the next video segment has been downloaded and stored in the playback buffer.

Abstract: A semiconductor product being convertible or converted from a customizable configuration into a selectable or selected one of a plurality of different customized configurations, wherein the semiconductor product comprises a customizing unit configured for customizing the semiconductor product into one of the customized configurations selected by a received customizing data structure specifying a selected application of the semiconductor product, and a plurality of functional blocks each configured for providing an assigned functionality and all being deactivated when the semiconductor product is not in one of the customized configurations, wherein the customizing unit is configured for activating only a subgroup of the functional blocks based on the received customizing data structure.

Abstract: A system for integrating video content and data provision includes an upstream signal path to process upstream data traffic received from a first transmission network for transmission to a second transmission network, and a downstream signal path to process downstream data traffic and downstream video traffic for transmission from the second transmission network to the first transmission network. The upstream signal path includes an analog-to-digital converter (ADC) and an upstream demodulator, and the downstream signal path includes an Ethernet processor, a digital-signal-processor (DSP) and a digital-to-analog converter (DAC).

Abstract: Novel tools and techniques are provided for implementing encoding or decoding of adaptive bitrate streams. In various embodiments, one or more first computing systems may divide a live media content stream into one or more segments, each segment might include a starting segment boundary and an ending segment boundary. The one or more first computing systems might encode the one or more segments into one or more primary adaptive bitrate streams. The one or more first computing systems might also divide the one or more segments of the live media content stream into one or more subsegments. Each subsegment might be less than a length of a corresponding segment of the one or more segments. The one or more first computing systems might the encode and/or a second computing system might decode the one or more subsegments into or from one or more secondary adaptive bitrate streams.

Abstract: Disclosed are a silicon-aluminum alloy and its preparation method. The method comprises: adding aluminum metal or molten aluminum into a container, wherein the temperature of the molten aluminum is between 700° C. and 800° C.; adding a semi-metallic silicon raw material to the molten aluminum, closing a furnace cover, carrying out vacuumization, and introducing argon, to ensure that the interior of a magnetic induction furnace is in a positive-pressure state, and stirring the aluminum metal or molten aluminum with a graphite stirring head; powering on and heating so that the aluminum metal or molten aluminum is heated to 1000° C. or above and molten, and holding the temperature between 1000° C. and 1500° C.; and after alloying is completed, cooling the molten aluminum to 1000° C. or below, opening the furnace cover, pouring the silicon-aluminum alloy into a corresponding mold, and cooling for molding.

Abstract: Disclosed are an iron-aluminum alloy and its preparation method. The iron-aluminum alloy comprises, by weight, 50% to 80% of iron and the balance of aluminum. The method comprises: adding metal aluminum or molten aluminum to a container, wherein the temperature of the molten aluminum is between 700° C. and 800° C.; adding a metal iron raw material to the molten aluminum, closing a furnace cover, measuring the pressure, and introducing argon to ensure that the interior of a magnetic induction furnace is in a positive-pressure state, and stirring the mixture with a graphite stirring head; powering on and heating so that the metal aluminum or the molten aluminum is heated to 1000° C. or above and molten, and holding the temperature between 1000° C. and 1500° C.; and after alloying is completed, cooling to about 1000 t, opening the furnace cover, and taking the iron-aluminum alloy out.

Abstract: A system and method are disclosed for provisioning IP features in a system-on-chip. A plurality of identical chips are fabricated, each of which is capable of have a number of features enabled or disabled. As a default, all features are disabled. A production process is later carried out, in which the chip is installed in a greater device. During this process, the manufacturer requests a license the IP owner for enablement of various features. Using secure communications, a license is granted identifying the features to be enabled, and a volume of units permitted to be manufactured. The license information is encrypted using a key already known to the chip, and sent to the manufacturer. The chip receives the license information during provisioning, extracts relevant provisioning information using the key, and a secure processing system provisions the relevant features. Log information is generated to allow the IP owner to verify license compliance.

Abstract: A system for determining the servicing needs of a vehicle. In various embodiments, the system includes a remote server and a vehicle control module of the vehicle. The vehicle control module includes a first communication interface to enable communications with at least one vehicle device via a network fabric of the vehicle. The vehicle control module is configured to receive status data, from the vehicle device, relating to a performance status or operational status of the vehicle. The vehicle control module further includes a second communication interface that enables wireless communications with the remote server. The wireless communications include sending status data to the remote server. The remote server is configured to receive and interpret the status data to determine if the vehicle requires service, and send a response to the vehicle. When service is required, the response may cause the vehicle to provide a service indication.

Abstract: An apparatus and method for providing ML processing for one or more ML applications operating on one or more Internet of Things (IoT) devices includes receiving a ML request from an IoT device. The ML request can be generated by a ML application operating on the IoT device and include input data collected by the first ML application. A ML model to perform ML processing of the input data included in the ML request is identified and provided to an ML core for ML processing along with the input data included in the first ML request. The ML core produces ML processing output data based on ML processing by the ML core of input data included in the ML request using the ML model. The ML processing output data can be transmitted to the IoT device.

Abstract: Disclosed are a manganese-aluminum alloy and its preparation method. The manganese-aluminum alloy comprises, by weight, 5% to 90% of manganese and the balance of aluminum. The method comprises: adding metal aluminum or molten aluminum to a container, the temperature of the molten aluminum being between 700° C. and 800° C.; adding a metal manganese raw material to the molten aluminum, closing a furnace cover, measuring the pressure, and introducing argon to ensure that the interior of a magnetic induction furnace is in a positive-pressure state, and stirring the mixture with a graphite stirring head; powering on and heating the metal aluminum or the molten aluminum to 1000° C. or above, melting, and holding the temperature between 1000° C. and 1500° C.; and after alloying is completed, cooling to 850° C. or below, opening the furnace cover, and taking a manganese-aluminum alloy out.

Abstract: Various embodiments of the present disclosure improve existing multi-layer and other network technologies by routing and processing client requests that require machine learning based on the machine learning capabilities of each network device and/or other computer resource characteristics of different network devices. This ensures that network latency and throughput, among other computer resource consumption characteristics, will be improved as machine learning processing can occur at the most suitable network device or be distributed among various suitable network devices.

Abstract: Systems, methods and apparatus for processing video can include a processor. The processor can be configured to perform object detection to detect visual indications of potential objects of interest in a video scene, to receive a selection of an object of interest from the potential objects of interest, and to provide enhanced video content within the video scene for the object of interest indicated by the selection.

Abstract: A system and method are disclosed for provisioning IP features in a system-on-chip. A plurality of identical chips are fabricated, each of which is capable of have a number of features enabled or disabled. As a default, all features are disabled. A production process is later carried out, in which the chip is installed in a greater device. During this process, the manufacturer requests a license the IP owner for enablement of various features. Using secure communications, a license is granted identifying the features to be enabled, and a volume of units permitted to be manufactured. The license information is encrypted using a key already known to the chip, and sent to the manufacturer. The chip receives the license information during provisioning, extracts relevant provisioning information using the key, and a secure processing system provisions the relevant features. Log information is generated to allow the IP owner to verify license compliance.

Abstract: Various embodiments of the present disclosure improve existing multi-layer and other network technologies by routing and processing client requests that require machine learning based on the machine learning capabilities of each network device and/or other computer resource characteristics of different network devices. This ensures that network latency and throughput, among other computer resource consumption characteristics, will be improved as machine learning processing can occur at the most suitable network device or be distributed among various suitable network devices.

Abstract: A system for controlling power distribution within a vehicular communication network, including a power source equipment comprising a first port in communication with a network node module of a device, and a Power over Ethernet (POE) management module. The POE management module is configured to enable POE to the device via the first port, monitor a current draw of the device, determine whether the current draw of the device exceeds a threshold, and disable POE to the device, responsive to determining that the current draw exceeds the threshold.