公开(公告)号：US20210270884A1

公开(公告)日：2021-09-02

申请号：US16804531

申请日：2020-02-28

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Edward R. WETHERBEE ,  Rui ZHONG ,  Kenny C. GROSS ,  Guang C. WANG

IPC: G01R31/00 ,  G01R29/08 ,  G06F21/44

Abstract: Detecting a counterfeit status of a target utility device by: selecting a set of frequencies that best reflect load dynamics or other information content of a reference utility device while undergoing a power test sequence; obtaining target electromagnetic interference (EMI) signals emitted by the target utility device while undergoing the same power test sequence; creating a sequence of target kiviat plots from the amplitude of the target EMI signals at each of the set of frequencies at observations over the power test sequence to form a target kiviat tube EMI fingerprint; comparing the target kiviat tube EMI fingerprint to a reference kiviat tube EMI fingerprint for the reference utility device undergoing the power test sequence to determine whether the target utility device and the reference utility device are of the same type; and generating a signal to indicate a counterfeit status based at least in part on the results of the comparison.

公开(公告)号：US20210247442A1

公开(公告)日：2021-08-12

申请号：US16784506

申请日：2020-02-07

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Edward R. WETHERBEE ,  Guang C. WANG ,  Kenny C. GROSS ,  Michael DAYRINGER ,  Andrew LEWIS ,  Matthew T. GERDES

IPC: G01R31/28 ,  G06F21/55 ,  G01R31/302 ,  G06K9/62

Abstract: Detecting whether a target utility device that includes multiple electronic components is genuine or suspected counterfeit by: performing a test sequence of energizing and de-energizing the target device and collecting electromagnetic interference (EMI) signals emitted by the target device; generating a target EMI fingerprint from the EMI signals collected; retrieving a plurality of reference EMI fingerprints from a database library, each of which corresponds to a different configuration of electronic components of a genuine device of the same make and model as the target device; iteratively comparing the target EMI fingerprint to the retrieved reference EMI fingerprints and generating a similarity metric between each compared set; and indicating that the target device (i) is genuine where the similarity metric for any individual reference EMI fingerprint satisfies a threshold test, and is a suspect counterfeit device where no similarity metric for any individual reference EMI fingerprint satisfies the test.

公开(公告)号：US20240303754A1

公开(公告)日：2024-09-12

申请号：US18666387

申请日：2024-05-16

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Edward R. WETHERBEE ,  Kenny C. GROSS

IPC: G06Q50/06 ,  G06F17/18 ,  G06N5/04 ,  G06Q10/0635 ,  G06Q10/20

CPC classification number: G06Q50/06 ,  G06F17/18 ,  G06N5/04 ,  G06Q10/0635 ,  G06Q10/20

Abstract: Systems and methods are described that estimate a remaining useful life (RUL) of an electronic device. Time-series signals gathered from sensors in the electronic device are received. Statistical changes are detected in the set of time-series signals that are deemed as anomalous signal patterns. Anomaly alarms are generated, wherein an anomaly alarm is generated for each of the anomalous signal patterns. An irrelevance filter is applied to the set of anomaly alarms to produce filtered anomaly alarms, wherein the irrelevance filter removes anomaly alarms associated with anomalous signal patterns that are not correlated with previous failures of similar electronic devices. A notification may be generated indicating that the electronic device has a limited remaining useful life based on at least the anomalous signal patterns associated with the filtered anomaly alarms.

公开(公告)号：US20240281043A1

公开(公告)日：2024-08-22

申请号：US18654133

申请日：2024-05-03

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： James ROHRKEMPER ,  Sanjeev R. SONDUR ,  Kenny C. GROSS ,  Guang C. WANG

IPC: G06F1/20 ,  H05K7/20

CPC classification number: G06F1/206 ,  H05K7/20136 ,  H05K7/20718 ,  H05K7/20836

Abstract: Systems, methods, and other embodiments associated with detecting feedback control instability in computer thermal controls are described herein. In one embodiment, a method includes executing a workload on the computing system, wherein the workload varies between a minimum and a maximum at a workload frequency. The method includes recording thermal telemetry from the computing system during execution of the workload. The method includes converting the recorded thermal telemetry into a frequency domain. The method includes detecting whether thermal control of the computing system exhibits feedback control instability based on dissimilarity in the frequency domain between the transformed thermal telemetry and the workload frequency. And, the method includes generating an electronic alert that indicates whether the thermal control of the computing device exhibits the feedback control instability.

公开(公告)号：US20240256959A1

公开(公告)日：2024-08-01

申请号：US18226522

申请日：2023-07-26

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Keyang RU ,  Kenneth P. BACLAWSKI ,  Richard P. SONDEREGGER ,  Dieter GAWLICK ,  Anna CHYSTIAKOVA ,  Guang Chao WANG ,  Matthew T. GERDES ,  Kenny C. GROSS

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: Systems, methods, and other embodiments associated with detecting unfairness in machine learning outcomes are described. In one embodiment, a method includes generating outcomes for transactions with a machine learning tool to be tested for bias. Then, actual values for a test subset of the outcomes that is associated with a test value for a demographic classification are compared with estimated values for the test subset of outcomes. The estimated values are generated by a machine learning model that is trained with a reference subset of the outcomes that are associated with a reference value for the demographic classification. The method then detects whether the machine learning tool is biased or unbiased based on dissimilarity between the actual values and the estimated values for the test subset of the outcomes. The method then generates an electronic alert that the ML tool is biased or unbiased.

公开(公告)号：US20230135691A1

公开(公告)日：2023-05-04

申请号：US17516975

申请日：2021-11-02

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： James ROHRKEMPER ,  Sanjeev R. SONDUR ,  Kenny C. GROSS ,  Guang C. WANG

IPC: G06F1/20 ,  H05K7/20

Abstract: Systems, methods, and other embodiments associated with detecting feedback control instability in computer thermal controls are described herein. In one embodiment, a method includes for a set of dwell time intervals, wherein the dwell time intervals are associated with a range of periods of time from an initial period to a base period, executing a workload that varies from minimum to maximum over the period on a computer during the dwell time interval; recording telemetry data from the computer during execution of the workload; incrementing the period towards a base period; determining that either the base period is reached or a thermal inertia threshold is reached; and analyzing the recorded telemetry data over the set of dwell time intervals to either (i) detect presence of a feedback control instability in thermal control for the computer; or (ii) confirm feedback control stability in thermal control for the computer.

公开(公告)号：US20220326292A1

公开(公告)日：2022-10-13

申请号：US17672928

申请日：2022-02-16

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Edward R. WETHERBEE ,  Rui ZHONG ,  Kenny C. GROSS ,  Guang C. WANG

IPC: G01R31/00 ,  G01R29/08 ,  G06F21/44

Abstract: Detecting a counterfeit status of a target device by: selecting a set of frequencies that best reflect load dynamics or other information content of a reference device while undergoing a power test sequence; obtaining target electromagnetic interference (EMI) signals emitted by the target device while undergoing the same power test sequence; creating a sequence of target kiviat plots from the amplitude of the target EMI signals at each of the set of frequencies at observations over the power test sequence to form a target kiviat tube EMI fingerprint; comparing the target kiviat tube EMI fingerprint to a reference kiviat tube EMI fingerprint for the reference device undergoing the power test sequence to determine whether the target device and the reference device are of the same type; and generating a signal to indicate a counterfeit status based at least in part on the results of the comparison.

公开(公告)号：US20210174248A1

公开(公告)日：2021-06-10

申请号：US16732558

申请日：2020-01-02

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Edward R. WETHERBEE ,  Kenny C. GROSS ,  Guang C. WANG ,  Matthew T. GERDES

IPC: G06N20/00 ,  G06N5/04 ,  H04L12/24 ,  H04L29/08 ,  G06F3/0482

Abstract: Systems, methods, and other embodiments associated with autonomous cloud-node scoping for big-data machine learning use cases are described. In some example embodiments, an automated scoping tool, method, and system are presented that, for each of multiple combinations of parameter values, (i) set a combination of parameter values describing a usage scenario, (ii) execute a machine learning application according to the combination of parameter values on a target cloud environment, and (iii) measure the computational cost for the execution of the machine learning application. A recommendation regarding configuration of central processing unit(s), graphics processing unit(s), and memory for the target cloud environment to execute the machine learning application is generated based on the measured computational costs.

公开(公告)号：US20240354633A1

公开(公告)日：2024-10-24

申请号：US18133125

申请日：2023-04-11

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Keyang RU ,  Matthew T. GERDES ,  Guang Chao WANG ,  Kenny C. GROSS ,  Ruixian LIU

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: Systems, methods, and other embodiments associated with determining a quantity of exemplar vectors to select from available training vectors are described. In one embodiment, a method includes determining an available quantity of training vectors that are available in a set of time series signals. A boost function is automatically selected from a plurality of different boost functions based on the available quantity of the training vectors. A selection quantity of the exemplar vectors to select from the training vectors is generated by applying the selected boost function to the training vectors. A quantity of the exemplar vectors is selected from the training vectors based on the selection quantity. A machine learning model is trained to detect an anomaly in the time series signals based on the exemplar vectors that were selected.

公开(公告)号：US20240127630A1

公开(公告)日：2024-04-18

申请号：US17967254

申请日：2022-10-17

Applicant: ORACLE INTERNATIONAL CORPORATION

Inventor： Guy G. MICHAELI ,  Mandip S. BHULLER ,  Timothy D. CLINE ,  Kenny C. GROSS

IPC: G06V40/40 ,  G06V20/40 ,  G06V40/16

CPC classification number: G06V40/40 ,  G06V20/46 ,  G06V40/168 ,  G06V40/172

Abstract: Systems, methods, and other embodiments associated with computer deepfake detection are described. In one embodiment, a method includes converting audio-visual content of a person delivering a speech into a set of time series signals. Residual time series signals of residuals that indicate an extent to which the time series signals differ from machine learning estimates of authentic delivery of the speech by the person are generated. Residual values from one synchronous observation of the residual time series signals are placed into an array of residual values for a point in time. A sequential analysis of the residual values of the array is performed to detect an anomaly in the residual values for the point in time. In response to detection of the anomaly, an alert that deepfake content is detected in the audio-visual content is generated.