Patents by Inventor Eric S. Chan

Eric S. Chan has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20220153765
    Abstract: The present disclosure relates to (a) carbidopa prodrugs, (b) pharmaceutical combinations and compositions comprising a carbidopa prodrug and/or an L-dopa prodrug, and (c) methods of treating Parkinson's disease and associated conditions comprising administering a carbidopa prodrug and an L-dopa prodrug to a subject with Parkinson's disease.
    Type: Application
    Filed: July 16, 2021
    Publication date: May 19, 2022
    Inventors: Benoit Cardinal-David, Vincent S. Chan, Kassibla Dempah, Brian P. Enright, Rodger F. Henry, Raimundo Ho, Ye Huang, Alexander D. Huters, Russell C. Klix, Scott W. Krabbe, Philip R. Kym, Yanbin Lao, Xiaochun Lou, Sean E. Mackey, Mark A. Matulenko, Peter T. Mayer, Christopher P. Miller, James Stambuli, Valentino J. Stella, Eric A. Voight, Zhi Wang, Geoff G. Zhang
  • Patent number: 11327797
    Abstract: Embodiments provide techniques for estimating seasonal indices for multiple periods. Some embodiments can receive a signal comprising a plurality of measures sampled over a span of time from an environment in which one or more processes are being executed. Some embodiments may then extract a seasonal effector and a de-seasonalized component from the signal. Next, some embodiments can apply one or more spline functions to the seasonal effector to generate a first model. Some embodiments may then apply a linear regression technique to the de-seasonalized component to generate a second model. Some embodiments may then initiate actions associated with the code. Some embodiments may then generate a forecast of the signal based on the first model and the second model. Next, some embodiments may initiate, based at least in part on the forecast, one or more actions associated with the environment.
    Type: Grant
    Filed: May 5, 2017
    Date of Patent: May 10, 2022
    Assignee: Oracle International Corporation
    Inventor: Eric S. Chan
  • Publication number: 20220019467
    Abstract: Embodiments identify heap-hoarding stack traces to optimize memory efficiency. Some embodiments can determine a length of time when heap usage by processes exceeds a threshold. Some embodiments may then determine heap information of the processes for the length of time, where the heap information comprise heap usage information for each interval in the length of time. Next, some embodiments can determine thread information of the one or more processes for the length of time, wherein determining the thread information comprises determining classes of threads and wherein the thread information comprises, for each of the classes of threads, thread intensity information for each of the intervals. Some embodiments may then correlate the heap information with the thread information to identify code that correspond to the heap usage exceeding the threshold. Some embodiments may then initiate actions associated with the code.
    Type: Application
    Filed: September 8, 2021
    Publication date: January 20, 2022
    Applicant: Oracle International Corporation
    Inventor: Eric S. Chan
  • Publication number: 20210334139
    Abstract: Embodiments provide a thread classification method that represents stack traces in a compact form using classification signatures. Some embodiments can receive a stack trace that includes a sequence of stack frames. Some embodiments may generate, based on the sequence of stack frames, a trace signature that represents the set. Some embodiments may receive one or more subsequent stack traces. For each of the one or more subsequent stack traces, some embodiments may determine whether a subsequent trace signature has been generated to represent the sequence of stack frames included within the subsequent stack trace. If not, some embodiments may generate, based on the trace signature and other subsequent trace signatures that were generated based on the trace signature, the subsequent trace signature to represent the subsequent sequence of stack frames.
    Type: Application
    Filed: July 2, 2021
    Publication date: October 28, 2021
    Applicant: Oracle International Corporation
    Inventor: Eric S. Chan
  • Patent number: 11144352
    Abstract: Embodiments identify heap-hoarding stack traces to optimize memory efficiency. Some embodiments can determine a length of time when heap usage by processes exceeds a threshold. Some embodiments may then determine heap information of the processes for the length of time, where the heap information comprise heap usage information for each interval in the length of time. Next, some embodiments can determine thread information of the one or more processes for the length of time, wherein determining the thread information comprises determining classes of threads and wherein the thread information comprises, for each of the classes of threads, thread intensity information for each of the intervals. Some embodiments may then correlate the heap information with the thread information to identify code that correspond to the heap usage exceeding the threshold. Some embodiments may then initiate actions associated with the code.
    Type: Grant
    Filed: December 12, 2019
    Date of Patent: October 12, 2021
    Assignee: Oracle International Corporation
    Inventor: Eric S. Chan
  • Patent number: 11093285
    Abstract: Embodiments provide a thread classification method that represents stack traces in a compact form using classification signatures. Some embodiments can receive a stack trace that includes a sequence of stack frames. Some embodiments may generate, based on the sequence of stack frames, a trace signature that represents the set. Some embodiments may receive one or more subsequent stack traces. For each of the one or more subsequent stack traces, some embodiments may determine whether a subsequent trace signature has been generated to represent the sequence of stack frames included within the subsequent stack trace. If not, some embodiments may generate, based on the trace signature and other subsequent trace signatures that were generated based on the trace signature, the subsequent trace signature to represent the subsequent sequence of stack frames.
    Type: Grant
    Filed: October 30, 2019
    Date of Patent: August 17, 2021
    Assignee: Oracle International Corporation
    Inventor: Eric S. Chan
  • Publication number: 20200401607
    Abstract: Embodiments of the invention provide systems and methods for managing and processing large amounts of complex and high-velocity data by capturing and extracting high-value data from low value data using big data and related technologies. Illustrative database systems described herein may collect and process data while extracting or generating high-value data. The high-value data may be handled by databases providing functions such as multi-temporality, provenance, flashback, and registered queries. In some examples, computing models and system may be implemented to combine knowledge and process management aspects with the near real-time data processing frameworks in a data-driven situation aware computing system.
    Type: Application
    Filed: June 30, 2020
    Publication date: December 24, 2020
    Applicant: Oracle International Corporation
    Inventors: Eric S. Chan, Dieter Gawlick, Adel Ghoneimy, Zhen Hua Liu
  • Patent number: 10740358
    Abstract: Embodiments of the invention provide systems and methods for managing and processing large amounts of complex and high-velocity data by capturing and extracting high-value data from low value data using big data and related technologies. Illustrative database systems described herein may collect and process data while extracting or generating high-value data. The high-value data may be handled by databases providing functions such as multi-temporality, provenance, flashback, and registered queries. In some examples, computing models and system may be implemented to combine knowledge and process management aspects with the near real-time data processing frameworks in a data-driven situation aware computing system.
    Type: Grant
    Filed: March 23, 2015
    Date of Patent: August 11, 2020
    Assignee: Oracle International Corporation
    Inventors: Eric S. Chan, Dieter Gawlick, Adel Ghoneimy, Zhen Hua Liu
  • Patent number: 10699007
    Abstract: The disclosed embodiments relate to a system for analyzing telemetry data. During operation, the system obtains telemetry data gathered from sensors during operation of a monitored system. Next, the system applies a univariate model to the telemetry data to identify an operational phase for the monitored system, wherein the univariate model analyzes an individual signal in the telemetry data without reference to other signals in the telemetry data. The system then selects a phase-specific multivariate model based on the identified operational phase, wherein the phase-specific multivariate model was previously trained based on telemetry data gathered while the system was operating in the identified operational phase. Finally, the system uses the phase-specific multivariate model to monitor the telemetry data to detect incipient anomalies associated with the operation of the monitored system.
    Type: Grant
    Filed: March 13, 2017
    Date of Patent: June 30, 2020
    Assignee: Oracle International Corporation
    Inventors: Kenny C. Gross, Eric S. Chan, Dieter Gawlick
  • Publication number: 20200117506
    Abstract: Embodiments identify heap-hoarding stack traces to optimize memory efficiency. Some embodiments can determine a length of time when heap usage by processes exceeds a threshold. Some embodiments may then determine heap information of the processes for the length of time, where the heap information comprise heap usage information for each interval in the length of time. Next, some embodiments can determine thread information of the one or more processes for the length of time, wherein determining the thread information comprises determining classes of threads and wherein the thread information comprises, for each of the classes of threads, thread intensity information for each of the intervals. Some embodiments may then correlate the heap information with the thread information to identify code that correspond to the heap usage exceeding the threshold. Some embodiments may then initiate actions associated with the code.
    Type: Application
    Filed: December 12, 2019
    Publication date: April 16, 2020
    Applicant: Oracle International Corporation
    Inventor: Eric S. Chan
  • Publication number: 20200065144
    Abstract: Embodiments provide a thread classification method that represents stack traces in a compact form using classification signatures. Some embodiments can receive a stack trace that includes a sequence of stack frames. Some embodiments may generate, based on the sequence of stack frames, a trace signature that represents the set. Some embodiments may receive one or more subsequent stack traces. For each of the one or more subsequent stack traces, some embodiments may determine whether a subsequent trace signature has been generated to represent the sequence of stack frames included within the subsequent stack trace. If not, some embodiments may generate, based on the trace signature and other subsequent trace signatures that were generated based on the trace signature, the subsequent trace signature to represent the subsequent sequence of stack frames.
    Type: Application
    Filed: October 30, 2019
    Publication date: February 27, 2020
    Applicant: Oracle International Corporation
    Inventor: Eric S. Chan
  • Patent number: 10534643
    Abstract: Embodiments identify heap-hoarding stack traces to optimize memory efficiency. Some embodiments can determine a length of time when heap usage by processes exceeds a threshold. Some embodiments may then determine heap information of the processes for the length of time, where the heap information comprise heap usage information for each interval in the length of time. Next, some embodiments can determine thread information of the one or more processes for the length of time, wherein determining the thread information comprises determining classes of threads and wherein the thread information comprises, for each of the classes of threads, thread intensity information for each of the intervals. Some embodiments may then correlate the heap information with the thread information to identify code that correspond to the heap usage exceeding the threshold. Some embodiments may then initiate actions associated with the code.
    Type: Grant
    Filed: May 5, 2017
    Date of Patent: January 14, 2020
    Assignee: Oracle International Corporation
    Inventor: Eric S. Chan
  • Patent number: 10467123
    Abstract: Embodiments provide a thread classification method that represents stack traces in a compact form using classification signatures. Some embodiments can receive a stack trace that includes a sequence of stack frames. Some embodiments may generate, based on the sequence of stack frames, a trace signature that represents the set. Some embodiments may receive one or more subsequent stack traces. For each of the one or more subsequent stack traces, some embodiments may determine whether a subsequent trace signature has been generated to represent the sequence of stack frames included within the subsequent stack trace. If not, some embodiments may generate, based on the trace signature and other subsequent trace signatures that were generated based on the trace signature, the subsequent trace signature to represent the subsequent sequence of stack frames.
    Type: Grant
    Filed: May 5, 2017
    Date of Patent: November 5, 2019
    Assignee: ORACLE INTERNATIONAL CORPORATION
    Inventor: Eric S. Chan
  • Patent number: 10417111
    Abstract: Methods, systems and computer readable medium are provided for sequentially analyzing a series of thread dump samples to estimate the intensity statistic of newly classified stack segments of stack frames. According to one embodiment, a branch point along one or more linearly connected stack frames of a stack segment can be detected, where the stack segment is associated with one or more thread intensity statistic parameters. Upon detecting the branch point along the one or more linearly connected stack frames of the stack segment, the system can split the stack segment into a plurality of new stack segments that each include a subset of the stack frames, where the plurality of new stack segments are referenced by the stack segment. The system can then initialize the one or more thread intensity statistic parameters for each of the new stack segments.
    Type: Grant
    Filed: May 5, 2017
    Date of Patent: September 17, 2019
    Assignee: ORACLE INTERNATIONAL CORPORATION
    Inventor: Eric S. Chan
  • Patent number: 10333798
    Abstract: Data can be categorized into facts, information, hypothesis, and directives. Activities that generate certain categories of data based on other categories of data through the application of knowledge which can be categorized into classifications, assessments, resolutions, and enactments. Activities can be driven by a Classification-Assessment-Resolution-Enactment (CARE) control engine. The CARE control and these categorizations can be used to enhance a multitude of systems, for example diagnostic system, such as through historical record keeping, machine learning, and automation. Such a diagnostic system can include a system that forecasts computing system failures based on the application of knowledge to system vital signs such as thread or stack segment intensity and memory heap usage. These vital signs are facts that can be classified to produce information such as memory leaks, convoy effects, or other problems.
    Type: Grant
    Filed: May 6, 2015
    Date of Patent: June 25, 2019
    Assignee: Oracle International Corporation
    Inventors: Eric S. Chan, Rafiul Ahad, Adel Ghoneimy, Adriano Covello Santos
  • Patent number: 10248561
    Abstract: The disclosed embodiments provide a system that detects anomalous events in a virtual machine. During operation, the system obtains time-series garbage-collection (GC) data collected during execution of a virtual machine in a computer system. Next, the system generates one or more seasonal features from the time-series GC data. The system then uses a sequential-analysis technique to analyze the time-series GC data and the one or more seasonal features for an anomaly in the GC activity of the virtual machine. Finally, the system stores an indication of a potential out-of-memory (OOM) event for the virtual machine based at least in part on identifying the anomaly in the GC activity of the virtual machine.
    Type: Grant
    Filed: June 18, 2015
    Date of Patent: April 2, 2019
    Assignee: ORACLE INTERNATIONAL CORPORATION
    Inventors: Dustin R. Garvey, Sampanna S. Salunke, Lik Wong, Xuemei Gao, Yongqiang Zhang, Eric S. Chan, Kenny C. Gross
  • Patent number: 10205640
    Abstract: Data can be categorized into facts, information, hypothesis, and directives. Activities that generate certain categories of data based on other categories of data through the application of knowledge which can be categorized into classifications, assessments, resolutions, and enactments. Activities can be driven by a Classification-Assessment-Resolution-Enactment (CARE) control engine. The CARE control and these categorizations can be used to enhance a multitude of systems, for example diagnostic system, such as through historical record keeping, machine learning, and automation. Such a diagnostic system can include a system that forecasts computing system failures based on the application of knowledge to system vital signs such as thread or stack segment intensity and memory heap usage. These vital signs are facts that can be classified to produce information such as memory leaks, convoy effects, or other problems.
    Type: Grant
    Filed: December 17, 2013
    Date of Patent: February 12, 2019
    Assignee: Oracle International Corporation
    Inventors: Eric S. Chan, Rafiul Ahad, Adel Ghoneimy, Adriano Covello Santos
  • Publication number: 20180260560
    Abstract: The disclosed embodiments relate to a system for analyzing telemetry data. During operation, the system obtains telemetry data gathered from sensors during operation of a monitored system. Next, the system applies a univariate model to the telemetry data to identify an operational phase for the monitored system, wherein the univariate model analyzes an individual signal in the telemetry data without reference to other signals in the telemetry data. The system then selects a phase-specific multivariate model based on the identified operational phase, wherein the phase-specific multivariate model was previously trained based on telemetry data gathered while the system was operating in the identified operational phase. Finally, the system uses the phase-specific multivariate model to monitor the telemetry data to detect incipient anomalies associated with the operation of the monitored system.
    Type: Application
    Filed: March 13, 2017
    Publication date: September 13, 2018
    Applicant: Oracle International Corporation
    Inventors: Kenny C. Gross, Eric S. Chan, Dieter Gawlick
  • Publication number: 20180074854
    Abstract: Certain techniques are disclosed for sequentially analyzing a series of thread dump samples to estimate the intensity statistics of newly classified stack segments of stack frames. Embodiments can detect a branch point along one or more linearly connected stack frames of a stack segment, where the stack segment is associated with a filter state. Upon detecting the branch point along the one or more linearly connected stack frames of the stack segment, some embodiments can split the stack segment into a plurality of new stack segments that each include a subset of the stack frames, where the plurality of new stack segments are referenced by the stack segment. Embodiments can then initialize a filter state for each of the new stack segments based at least in part on the filter state of the stack segment.
    Type: Application
    Filed: May 5, 2017
    Publication date: March 15, 2018
    Applicant: Oracle International Corporation
    Inventor: Eric S. Chan
  • Publication number: 20170337085
    Abstract: Embodiments identify heap-hoarding stack traces to optimize memory efficiency. Some embodiments can determine a length of time when heap usage by processes exceeds a threshold. Some embodiments may then determine heap information of the processes for the length of time, where the heap information comprise heap usage information for each interval in the length of time. Next, some embodiments can determine thread information of the one or more processes for the length of time, wherein determining the thread information comprises determining classes of threads and wherein the thread information comprises, for each of the classes of threads, thread intensity information for each of the intervals. Some embodiments may then correlate the heap information with the thread information to identify code that correspond to the heap usage exceeding the threshold. Some embodiments may then initiate actions associated with the code.
    Type: Application
    Filed: May 5, 2017
    Publication date: November 23, 2017
    Applicant: Oracle International Corporation
    Inventor: Eric S. Chan