Abstract: In an embodiment, an integrated circuit may include one or more CPUs, a memory controller, and a circuit configured to remain powered on when the rest of the SOC is powered down. The circuit may be configured to receive audio samples from a microphone, and match those audio samples against a predetermined pattern to detect a possible command from a user of the device that includes the SOC. In response to detecting the predetermined pattern, the circuit may cause the memory controller to power up so that audio samples may be stored in the memory to which the memory controller is coupled. The circuit may also cause the CPUs to be powered on and initialized, and the operating system (OS) may boot. During the time that the CPUs are initializing and the OS is booting, the circuit and the memory may be capturing the audio samples.

Abstract: Video content may be captured by an image capture device during a capture duration. The video content may include video frames that define visual content viewable as a function of progress through a progress length of the video content. Rotational position information may characterize rotational positions of the image capture device during the capture duration. Time-lapse video frames may be determined from the video frames of the video content based on a spatiotemporal metric. The spatiotemporal metric may characterize spatial smoothness and temporal regularity of the time-lapse video frames. The spatial smoothness may be determined based on the rotational positions of the image capture device corresponding to the time-lapse video frames, and the temporal regularity may be determined based on moments corresponding to the time-lapse video frames. Time-lapse video content may be generated based on the time-lapse video frames.

Abstract: Video frames of a video may be marked with visual patterns to identify individual video frames. The video may be changed by applying one or more effects to the video. The accuracy with which the changes were made to the video by the effect(s) may be determined using the visual patterns marked on the video frames.

Abstract: A system and method for a logic device is disclosed. A plurality of substrates are provided. At least one input nanomagnet is disposed over each of the plurality of substrates. The plurality of input nanomagnets are disposed substantially equidistant from each other. The plurality of input nanomagnets are each a single domain nanomagnet. A spacer layer is disposed over the plurality of input nanomagnets. An output magnet is disposed over the spacer layer.

Abstract: Methods, systems, and devices for techniques to manufacture ferroelectric memory devices are described. In some cases, a memory array may be manufactured using a self-aligned manufacturing technique. For example, a continuous layer of dielectric material may be formed over an assembly which includes an array of transistors coupling contacts on the surface of the assembly with a set of digit lines. In some cases, an array of cavities may be etched into the dielectric material, each cavity exposing a set of contacts. A set of bottom electrodes corresponding to the set of contacts may be formed on sidewalls in each cavity, for example by depositing a layer of electrode material and etching the electrode material using a variety of hard masks.

Abstract: Systems, devices, media, and methods are presented for splitting decision trees between server and client. The client of the systems and methods sends a configuration query. The server of the system and method receives the configuration query. The server retrieves Config rule(s) according to the configuration query. Each of the Config rule(s) can be represented by decision tree(s). The server evaluates the decision tree(s). If a definitive True or False cannot be derived from the evaluation using server knowledge, the server prunes the decision tree(s) and returns them to client side for further evaluation.

Abstract: Systems and methods for using a user simulation model to facilitate detection of usage anomalies is disclosed. Usage data is received for a session between a user device and an application or service. The usage data is monitored to detect a usage anomaly, such as unusual or suspicious transactions, unexpected user or device attributes, or abnormal usage patterns. In response to detecting a request to terminate the session, the session is instead handed off to a user simulation model that simulates interactions of a user in the session. The user simulation model can be a machine learning model that is trained, using a training dataset, to simulate user interactions. When the user logs into the application or service, the session can be handed off from the user simulation model to the user, such that the session is perpetual or substantially perpetual.

Abstract: Techniques are described for generating an end-to-end distributed trace in connection with a cloud or datacenter environment. In one example, a server obtains target application telemetry data and external telemetry data associated with one or more correlation identifiers included in one or more network communications provided to a target application in the cloud or datacenter environment. The server aggregates the target application telemetry data and the external telemetry data based on the one or more correlation identifiers to generate an end-to-end distributed trace associated with the one or more network communications.

Abstract: A device may calculate, based on network data associated with a network, key performance indicators (KPIs) for the network. The device may aggregate a first set of KPIs to generate a first aggregated KPI associated with a first functionality of the device and a second set of KPIs to generate a second aggregated KPI associated with a second functionality of the device. The device may receive a selection of a particular KPI from the first aggregated KPI, the first set of KPIs, the second aggregated KPI, or the second set of KPIs. The device may parse text data corresponding to a set of rules, utilized to calculate the particular KPI, to generate a parsed set of rules, and may identify particular metrics utilized to calculate the particular KPI. The device may provide one or more timeline views of the particular metrics correlated with the particular KPI.

Abstract: A method for measuring and reporting performance parameters in a network having at least one originator for generating test protocol data units, and multiple reflectors for relaying the test protocol data units along successive segments of a test path in the network. The method generates the test protocol data units at the originator and transmits the test protocol data unit along a test path that includes multiple reflectors. Each reflector relays the test protocol data unit to the next reflector along the test path. Measurements of performance parameters are collected from the multiple reflectors in the test protocol data unit by inserting timestamps into the test protocol data unit at the originator and each of the reflectors to identify the departure and arrival times for each test protocol data unit at the originator and each of the reflectors in both the downstream and upstream directions along the test path.