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公开(公告)号：US11460500B2
公开(公告)日：2022-10-04
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
Abstract: Detecting whether a target 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.
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公开(公告)号：US20230137596A1
公开(公告)日：2023-05-04
申请号：US17716489
申请日：2022-04-08
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Matthew T. Gerdes , James Rohrkemper , Sanjeev R. Sondur , Kenny C. Gross , Guang C. Wang
IPC: H05K7/20
Abstract: Systems, methods, and other embodiments associated with unified control of cooling in computers are described. In one embodiment, a method locks operation of first and second cooling mechanisms configured to cool one or more components in the computer. In response to a first condition, the method unlocks the operation of the first cooling mechanism to allow the first cooling mechanism to make cooling adjustments while the operation of the second cooling mechanism is locked. In response to a second condition, the method unlocks the operation of the second cooling mechanism to allow the second cooling mechanism to make cooling adjustments while the operation of the first cooling mechanism is locked. In the method, the first cooling mechanism and the second cooling mechanism are prevented from making the cooling adjustments simultaneously.
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公开(公告)号：US20220383043A1
公开(公告)日：2022-12-01
申请号：US17334392
申请日：2021-05-28
Applicant: Oracle International Corporation
Inventor： Matthew T. Gerdes , Guang C. Wang , Kenny C. Gross , Timothy David Cline
Abstract: The disclosed system produces synthetic signals for testing machine-learning systems. During operation, the system generates a set of N composite sinusoidal signals, wherein each of the N composite sinusoidal signals is a combination of multiple constituent sinusoidal signals with different periodicities. Next, the system adds time-varying random noise values to each of the N composite sinusoidal signals, wherein a standard deviation of the time-varying random noise values varies over successive time periods. The system also multiplies each of the N composite sinusoidal signals by time-varying amplitude values, wherein the time-varying amplitude values vary over successive time periods. Finally, the system adds time-varying mean values to each of the N composite sinusoidal signals, wherein the time-varying mean values vary over successive time periods. The time-varying random noise values, amplitude values and mean values can be selected through a roll-of-the-die process from a library of values, which are learned from industry-specific signals.
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公开(公告)号：US12260304B2
公开(公告)日：2025-03-25
申请号：US17205445
申请日：2021-03-18
Applicant: Oracle International Corporation
Inventor： Neelesh Kumar Shukla , Saurabh Thapliyal , Matthew T. Gerdes , Guang C. Wang , Kenny C. Gross
Abstract: The disclosed embodiments provide a system that detects sensor anomalies in a univariate time-series signal. During a surveillance mode, the system receives the univariate time-series signal from a sensor in a monitored system. Next, the system performs a staggered-sampling operation on the univariate time-series signal to produce N sub-sampled time-series signals, wherein the staggered-sampling operation allocates consecutive samples from the univariate time-series signal to the N sub-sampled time-series signals in a round-robin ordering. The system then uses a trained inferential model to generate estimated values for the N sub-sampled time-series signals based on cross-correlations with other sub-sampled time-series signals. Next, the system performs an anomaly detection operation to detect incipient sensor anomalies in the univariate time-series signal based on differences between actual values and the estimated values for the N sub-sampled time-series signals. Whenever an incipient sensor anomaly is detected, the system generates a notification.
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公开(公告)号：US11729940B2
公开(公告)日：2023-08-15
申请号：US17716489
申请日：2022-04-08
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Matthew T. Gerdes , James Rohrkemper , Sanjeev R. Sondur , Kenny C. Gross , Guang C. Wang
CPC classification number: H05K7/20209 , H05K7/207 , H05K7/20136 , H05K7/20627
Abstract: Systems, methods, and other embodiments associated with unified control of cooling in computers are described. In one embodiment, a method locks operation of first and second cooling mechanisms configured to cool one or more components in the computer. In response to a first condition, the method unlocks the operation of the first cooling mechanism to allow the first cooling mechanism to make cooling adjustments while the operation of the second cooling mechanism is locked. In response to a second condition, the method unlocks the operation of the second cooling mechanism to allow the second cooling mechanism to make cooling adjustments while the operation of the first cooling mechanism is locked. In the method, the first cooling mechanism and the second cooling mechanism are prevented from making the cooling adjustments simultaneously.
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Patent Agency Ranking
公开(公告)号：US20230121897A1
公开(公告)日：2023-04-20
申请号：US17506200
申请日：2021-10-20
Applicant: ORACLE INTERNATIONAL CORPORATION
Inventor： Yixiu Liu , Matthew T. Gerdes , Guang C. Wang , Kenny C. Gross , Hariharan Balasubramanian
Abstract: Systems, methods, and other embodiments associated with autonomous discrimination of operation vibration signals are described herein. In one embodiment, a method includes partitioning a frequency spectrum of output into a plurality of discrete bins, wherein the output is collected from vibration sensors monitoring a reference device; generating a representative time series signal for each bin while the device is operated in a deterministic stress load; generating a PSD for each bin by converting each signal from the time domain to the frequency domain; determining a maximum power spectral density value and a peak frequency value for each bin; selecting a subset of the bins that have maximum PSD values exceeding a threshold; assigning the representative time series signals from the selected subset of bins as operation vibration signals indicative of operational load on the reference device; and configuring a machine learning model based on at least the operation vibration signals.
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公开(公告)号：US12189715B2
公开(公告)日：2025-01-07
申请号：US17334392
申请日：2021-05-28
Applicant: Oracle International Corporation
Inventor： Matthew T. Gerdes , Guang C. Wang , Kenny C. Gross , Timothy David Cline
IPC: G06F18/214 , G06F1/02 , G06N3/08
Abstract: The disclosed system produces synthetic signals for testing machine-learning systems. During operation, the system generates a set of N composite sinusoidal signals, wherein each of the N composite sinusoidal signals is a combination of multiple constituent sinusoidal signals with different periodicities. Next, the system adds time-varying random noise values to each of the N composite sinusoidal signals, wherein a standard deviation of the time-varying random noise values varies over successive time periods. The system also multiplies each of the N composite sinusoidal signals by time-varying amplitude values, wherein the time-varying amplitude values vary over successive time periods. Finally, the system adds time-varying mean values to each of the N composite sinusoidal signals, wherein the time-varying mean values vary over successive time periods. The time-varying random noise values, amplitude values and mean values can be selected through a roll-of-the-die process from a library of values, which are learned from industry-specific signals.
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公开(公告)号：US11663369B2
公开(公告)日：2023-05-30
申请号：US17090131
申请日：2020-11-05
Applicant: Oracle International Corporation
Inventor： Matthew T. Gerdes , Kenny C. Gross , Guang C. Wang , Shreya Singh , Aleksey M. Urmanov
CPC classification number: G06F21/88
Abstract: During operation, the system uses N sensors to sample an electromagnetic interference (EMI) signal emitted by a target asset while the target asset is running a periodic workload, wherein each of the N sensors has a sensor sampling frequency f, and wherein the N sensors perform sampling operations in a round-robin ordering with phase offsets between successive samples. During the sampling operations, the system performs phase adjustments among the N sensors to maximize phase offsets between successive sensors in the round-robin ordering. Next, the system combines samples obtained through the N sensors to produce a target EMI signal having an EMI signal sampling frequency F=f×N. The system then generates a target EMI fingerprint from the target EMI signal. Finally, the system compares the target EMI fingerprint against a reference EMI fingerprint for the target asset to determine whether the target asset contains any unwanted electronic components.
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公开(公告)号：US11367018B2
公开(公告)日：2022-06-21
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
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.
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10.发明申请公开(公告)号：US20220138358A1
公开(公告)日：2022-05-05
申请号：US17090131
申请日：2020-11-05
Applicant: Oracle International Corporation
Inventor： Matthew T. Gerdes , Kenny C. Gross , Guang C. Wang , Shreya Singh , Aleksey M. Urmanov
IPC: G06F21/88
Abstract: During operation, the system uses N sensors to sample an electromagnetic interference (EMI) signal emitted by a target asset while the target asset is running a periodic workload, wherein each of the N sensors has a sensor sampling frequency f, and wherein the N sensors perform sampling operations in a round-robin ordering with phase offsets between successive samples. During the sampling operations, the system performs phase adjustments among the N sensors to maximize phase offsets between successive sensors in the round-robin ordering. Next, the system combines samples obtained through the N sensors to produce a target EMI signal having an EMI signal sampling frequency F=f×N. The system then generates a target EMI fingerprint from the target EMI signal. Finally, the system compares the target EMI fingerprint against a reference EMI fingerprint for the target asset to determine whether the target asset contains any unwanted electronic components.
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