SELF-ADAPTIVE SECURITY FRAMEWORK
    12.
    发明申请

    公开(公告)号:US20170372059A1

    公开(公告)日:2017-12-28

    申请号:US15191469

    申请日:2016-06-23

    Abstract: A self-adaptive security framework for a device is disclosed. A first security level for a device is set wherein the first security level comprises procedures that authenticate a user and allow the user to access the device. Input from sensors associated with the device may be received at a contextual sensing engine, wherein the input at least includes location data, and wherein at least a portion of the input is related to a physical setting where the device is located. A threat level for the device is determined in the physical setting via the contextual sensing engine based on analyzing the input. The first security level is altered to a second security level to provide an altered threat response for the device based on the threat level wherein the second security level has different procedures to authenticate the user compared to the first security level.

    Driver assisted ESD protection apparatus and method

    公开(公告)号:US11444445B2

    公开(公告)日:2022-09-13

    申请号:US17125824

    申请日:2020-12-17

    Abstract: Analog Front End (AFE) driver or transmitter is used for ESD protection of an input-output (IO) pin, thus reducing ESD diode count and subsequently lowering the pad capacitance to achieve high performance in IO circuits like double data rate (DDR) IO, PCI Express (Peripheral Component Interconnect Express), etc. The channel of active devices that constitute AFE driver are used to connect an IO pad to discharge the ESD current to ground, thus providing an alternative path to ESD current and subsequently reducing the ESD diode count. An additional p-type device (Driver Path Enabler (DPE)) is coupled between the IO pad and a gate terminal of the AFE driver. This additional p-type device triggers the channel of the AFE driver. This p-type device is controlled by an RC based structure which cuts the p-type device off during regular operations when power is ramped-up.

    APPARATUS AND METHOD FOR EARLY LIFETIME FAILURE DETECTION SYSTEM

    公开(公告)号:US20220221507A1

    公开(公告)日:2022-07-14

    申请号:US17705765

    申请日:2022-03-28

    Abstract: An on-die early lifetime failure detection system with a reliability mechanism isolation circuit provides an early lifetime failure detection. The system measures and monitors reliability at time-0 (t0) and end-of-life. The measurements enable detection of latent reliability or marginality issues during the lifetime of the product. The system includes: a stress controller to adjust voltage for a power supply and voltage for a ground supply in accordance with one or more sensors; and an aging detector circuitry coupled to the stress controller, wherein the aging detector circuitry comprises a ring oscillator having delay stages, wherein each delay stage comprises an aging monitor circuitry, wherein the stress controller to adjust voltage for a power supply and voltage for a ground supply of the delay stage.

    Apparatus and method for an on-chip reliability controller

    公开(公告)号:US10592331B2

    公开(公告)日:2020-03-17

    申请号:US16110381

    申请日:2018-08-23

    Abstract: An apparatus and method are described for an on-chip reliability controller. For example, one embodiment of a processor comprises: a set of one or more cores to execute instructions and process data; a reliability controller to perform one or more self-test/diagnostic operations, the reliability controller to aggregate reliability data resulting from the self-test/diagnostic operations; a reliability estimator integral to the reliability controller to use the aggregated reliability data to perform a probability analysis to determine reliability estimates for one or more components of the processor; and a control unit integral to the reliability controller to adjust one or more variables and/or circuitry related to operation of the processor responsive to the reliability estimates.

    UNSUPERVISED MACHINE LEARNING TO MANAGE AQUATIC RESOURCES

    公开(公告)号:US20180181876A1

    公开(公告)日:2018-06-28

    申请号:US15388097

    申请日:2016-12-22

    CPC classification number: G06N7/005 G01N33/1886 G06N3/088

    Abstract: Various implementations provide an aquatic conditions optimization management system accesses aquatic sensor data generated by one or more aquatic sensors, identifies a collection of aquatic data that includes data generated by and collected from the aquatic sensor(s), generates a set of cross-correlation matrices based on the collection of aquatic data, executes a set of unsupervised machine learning algorithms using the set of cross-correlation matrices, and determines one or more optimum conditions for one or more aquatic resources based on the executed set of unsupervised machine learning algorithms. The optimum condition(s) may be communicated to one or more individuals and may include one or more corrective actions to improve one or more of the aquatic resources.

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