Provided herein are methods, systems, and computer-program products for providing a library of base classes to be used by applications to facilitate real-time analytics. In some examples, the library may be a C++ Library that provides a set of primitive operators (e.g., spout base class, tube base class, and sink base class) for user derivation. In some examples, the spout base class may relate to receiving data from a data source, the tube base class may relate to performing one or more operations on the received data, and the sink base class may relate to sending the processed data to a data target. The spout, tube, sink together provide a real-time streaming framework interface that may be extended by the user.

Generation of an executable file derived from a parent executable file having ranges of physical addresses referencing a binary code of at least one core feature (CR), a binary code of a set of native features (F), bytecodes of a set of java features (Pkg), by selecting at least one native feature from the set of native features to be removed, defining the range of physical addresses where the binary code of the selected native feature is stored, selecting at least one java feature from the set of java features to be relocated, and relocating the bytecodes of said at least one selected java feature in the defined range of physical addresses.

Some implementations are directed to adapting a client application on a feature phone based on experiment parameters. Some of those implementations are directed to adapting an assistant client application, where the assistant client application interacts with remote assistant component(s) to provide automated assistant functionalities via the assistant client application of the feature phone. Some implementations are additionally or alternatively directed to determining whether an invocation, of an assistant client application on a feature phone, is a request for transcription of voice data received in conjunction with the invocation, or is instead a request for an assistant response that is responsive to the transcription of the voice data (e.g., includes assistant content that is based on and in addition to the transcription, and that optionally lacks the transcription itself).

A hip joint orthotic that can be used in stages. In the first stage the orthotic includes a stiff relatively brace assembly that can limit the amount of allowed flexion, extension, abduction, and adduction. In the second stage the relatively stiff brace can be removed and the orthotic can be used as a soft wrap. In both stages the orthotic is configured to easily mount and retain a thermal pack in a desired position or positions. In many instances the thermal pack will be a cold pack, but in some cases a hot pack may be used as well.

Embedded systems and methods of reading or writing data or instructions of at least one application in a non-volatile memory are disclosed. A method includes reading or writing data or instructions of at least one application in a non-volatile memory of an embedded system. The data or instructions transit through a memory area and are interpreted by a distinct program of an operating system of the embedded system.

Methods, systems, and computer storage media for providing a set of common flat files in a composite image that can be mounted as a container (i.e., composite container) to support isolation and interoperation of computing resources. Container management is provided for a container management system based on a composite image file system engine that executes composite operations to support resource isolation and operating system (OS) virtualization functionality. In particular, a container engine interface supports creating, mounting, and providing access to and from composite images or composite containers. In operation, a plurality of files for generating a composite image are accessed. The composite image for the plurality of files is generated. The composite image includes a set of common flat files. The composite image is communicated to cause mounting of the composite image, where mounting the composite image is based on a metadata file from the set of common flat files.

A compiler of a computing device is described that identifies a sequence of neural network models frequently invoked by an application of the computing device, compiles the models in that sequence, and loads a static random access memory (SRAM) of a hardware accelerator with the compiled models only when the same compiled models—from another, but same, sequence that was previously invoked—are not already present in the SRAM. This prevents unnecessary reloading of compiled models into the SRAM, thereby increasing runtime speed and conserving computational energy.

The present disclosure provides a method and system for deploying a third-party application to a microcontroller using edge assistance. The method includes: sending an instruction packet to an edge server, applying the instruction packet to an intermediate bytecode content of a current node temporarily stored on the edge server, and compiling an updated intermediate bytecode of a device as a corresponding native instruction set code; assigning a size of each application partition according to a compilation result; and statically or dynamically linking each application to a corresponding position according to an assigned memory address of each application to generate a binary image, and downloading the binary image into an application node, thereby completing update of the application node.

A memory system includes a memory device including plural non-volatile memory cells storing firmware and a controller configured to load the firmware in a volatile memory and employ a plurality of cores, each capable of performing an operation based on the firmware. A core, which is in a standby state or an idle state between the plurality of cores, is configured to check whether an error has occurred in the volatile memory in which the firmware is loaded.

Some implementations are directed to adapting a client application on a feature phone based on experiment parameters. Some of those implementations are directed to adapting an assistant client application, where the assistant client application interacts with remote assistant component(s) to provide automated assistant functionalities via the assistant client application of the feature phone. Some implementations are additionally or alternatively directed to determining whether an invocation, of an assistant client application on a feature phone, is a request for transcription of voice data received in conjunction with the invocation, or is instead a request for an assistant response that is responsive to the transcription of the voice data (e.g., includes assistant content that is based on and in addition to the transcription, and that optionally lacks the transcription itself).