公开(公告)号：US12117915B1

公开(公告)日：2024-10-15

申请号：US18131337

申请日：2023-04-05

Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC

Inventor： Nazmiye Ceren Abay ,  Nikolay Sergeyevich Rovinskiy ,  Dhawal Dilip Parkar ,  Vijaykumar Kuberappa Aski ,  Neil Tenenholtz

IPC: G06F11/30 ,  G06F11/34

CPC classification number: G06F11/3075 ,  G06F11/3447

Abstract: The disclosed techniques pertain to the dynamic control of select functions that are applied to a time series dataset based on the detection of stationary time series grains. In some configurations, a system selectively applies select functions, e.g., the application of a differencing function, to a dataset in response to determining that a number of stationary time series grains detected in the dataset meets one or more criteria with respect to a threshold. If a system determines that the number of stationary time series grains meets one or more criteria with respect to a threshold, the system can apply a differencing function to the entire dataset. By controlling the differencing function based on the detection of stationary time series grains with respect to a threshold, the system can increase the accuracy and the efficiency of a machine learning system or any other system that utilizes time series datasets.

公开(公告)号：US12093160B1

公开(公告)日：2024-09-17

申请号：US17543585

申请日：2021-12-06

Applicant: Amazon Technologies, Inc.

Inventor： Vaibhav Bhushan Sharma ,  Andrew Jude Gacek ,  Michael William Whalen ,  Saswat Padhi ,  Andrew Apicelli ,  Raveesh Yadav ,  Samuel Bayless ,  Roman Pruzhanskiy ,  Rajat Gupta ,  Harshil Rajeshkumar Shah ,  Fernando Dias Pauer ,  Ankush Das ,  Dhivashini Jaganathan

IPC: G06F11/00 ,  G06F11/30 ,  G06F11/34 ,  G06F11/36 ,  H04L67/62

CPC classification number: G06F11/3447 ,  G06F11/3013 ,  G06F11/3476 ,  G06F11/3604 ,  H04L67/62

Abstract: System and methods for IoT event detector correctness verification. Detector models (e.g., state-based models including variables, states, transitions and actions) take IoT device data as input and detect, based on the data, events that triggers actions. To verify a correctness of the models prior to deploying the models at scale, an event detector model correctness checker obtains a representation of a definition of the model, verifies, based on analysis of the model definition, whether the model complies with correctness properties, and generates a report indicating whether the model complies. Example correctness properties include a reachability correctness property that indicates that respective states or actions are reachable according to the definition of the event detector model. The analysis may be accessed via an interface element and may result in generation of a report that identifies a location of non-compliance within the model definition.

公开(公告)号：US12072779B2

公开(公告)日：2024-08-27

申请号：US18334042

申请日：2023-06-13

Applicant: UncommonX Inc.

Inventor： Raymond Hicks ,  Ryan Michael Pisani ,  Thomas James McNeela

IPC: G06F11/07 ,  G06F11/26 ,  G06F11/30 ,  G06F11/34 ,  G06F11/36 ,  G06F16/23 ,  G06F21/57 ,  G06Q10/0639 ,  H04L9/40

CPC classification number: G06F11/26 ,  G06F11/0709 ,  G06F11/076 ,  G06F11/079 ,  G06F11/0793 ,  G06F11/3006 ,  G06F11/3409 ,  G06F11/3447 ,  G06F11/3476 ,  G06F11/3495 ,  G06F11/3668 ,  G06F16/2379 ,  G06F21/577 ,  G06Q10/06393 ,  H04L63/1416 ,  H04L63/1425 ,  H04L63/1433 ,  H04L63/20 ,  G06F2221/034

Abstract: A method includes determining, by an analysis system, a system aspect of a system for an issue recovery communications evaluation. The method further includes determining, by the analysis system, at least one evaluation perspective and at least one evaluation viewpoint for use in performing the issue recovery communications evaluation on the system aspect. The method further includes obtaining, by the analysis system, issue recovery communications data regarding the system aspect in accordance with the at least one evaluation perspective and the at least one evaluation viewpoint. The method further includes calculating, by the analysis system, an issue recovery communications rating as a measure of system issue recovery communications maturity for the system aspect based on the issue recovery communications data, the at least one evaluation perspective, the at least one evaluation viewpoint, and at least one evaluation rating metric.

公开(公告)号：US20240281356A1

公开(公告)日：2024-08-22

申请号：US18427700

申请日：2024-01-30

Applicant: Skilljar, Inc.

Inventor： Niran Kundapur ,  Sandi Lin ,  Jason Stewart

IPC: G06F11/34

CPC classification number: G06F11/3428 ,  G06F11/3438 ,  G06F11/3447

Abstract: Training programs (e.g., for training a user to use a company's products) may be flexibly benchmarked by first identifying user interactions with one or more of the training programs and converting the user interactions into user activity data objects associated with user identifiers. The user activity data may then be made anonymous by removing the user identifiers from the data before examining the data. The anonymized user activity data may then be aggregated with respect to each of the training programs. A benchmark model for evaluating the training programs may then be determined based on a flexible benchmark schema of selectable benchmark metrics for evaluating aspects of the training programs. Benchmarks may then be calculated for each of the training programs based on the aggregated user activity data and the benchmark model. The benchmarks may then be displayed and/or analyzed to generate insights or suggestions for improving the training programs.

公开(公告)号：US12061515B2

公开(公告)日：2024-08-13

申请号：US17577329

申请日：2022-01-17

Applicant: VMware LLC

Inventor： Ashot Nshan Harutyunyan ,  Nelli Aghajanyan ,  Lilit Harutyunyan ,  Arnak Poghosyan ,  Tigran Bunarjyan

IPC: G06F11/34 ,  G06F11/07 ,  G06N5/022

CPC classification number: G06F11/0757 ,  G06F11/0709 ,  G06F11/0766 ,  G06F11/3447 ,  G06N5/022

Abstract: The current document is directed to methods and systems that automatically generate training data for machine-learning-based components used by a metric-data processing-and-analysis component of a distributed computer system, a subsystem within a distributed computer system, or a standalone metric-data processing-and-analysis system. The training data sets are labeled using categorical KPI values. The machine-learning-based components are applied to metric data both for predicting anomalous operational behaviors and problems within the distributed computer system and for determination of potential causes of anomalous operational behaviors and problems within the distributed computer system. Training of machine-learning-based components is carried out concurrently and asynchronously with respect to other metric-data collection, aggregation, processing, storage, and analysis tasks.

公开(公告)号：US20240264917A1

公开(公告)日：2024-08-08

申请号：US18635406

申请日：2024-04-15

Applicant: Palantir Technologies Inc.

Inventor： Andres Felipe Orozco ,  Robert Kruszewski ,  Thomas Petracca

IPC: G06F11/30 ,  G06F8/70 ,  G06F11/34

CPC classification number: G06F11/302 ,  G06F8/70 ,  G06F11/3447

Abstract: A computer-implemented method for generating a monitor for at least one software service from a monitor template, includes, in at least some aspects: providing a monitor template. Further, in certain instances, the method includes determining one or more endpoints included in code for a first software service of the at least one software service. In addition, in some aspects, the method includes generating a first monitor for the first software service code using the monitor template based at least upon a first endpoint of the one or more endpoints included in the first software service code.

公开(公告)号：US12055998B2

公开(公告)日：2024-08-06

申请号：US17654456

申请日：2022-03-11

Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor： Jonathan Ian Settle ,  Isabell Sippli

IPC: G06F11/34 ,  G06F11/07

CPC classification number: G06F11/0787 ,  G06F11/0709 ,  G06F11/3447

Abstract: A method, computer system, and a computer program for grouping a plurality of computing system fault events is provided. The present invention may include extracting a summary of computing system fault events based on at least one similarity detected. The present invention may then include generating a plurality of vectors in which each vector corresponds to a summary, clustering the plurality of vectors into a plurality of clusters based on the at least one similarity, and compressing each cluster of the plurality of clusters into at least one cluster centroid. The present invention may further include generating a group centroid for a group including the plurality of clusters based on the at least one cluster centroid. The present invention may also include presenting a correlation statement derived from a result associated with the group centroid and generating a system fault solution based on the correlation statement.

公开(公告)号：US12007879B2

公开(公告)日：2024-06-11

申请号：US17504111

申请日：2021-10-18

Applicant: Rosemount Aerospace Inc.

Inventor： Simone Fulvio Rollini ,  Rob C. North

IPC: G06F11/30 ,  G06F11/34 ,  G06F11/36

CPC classification number: G06F11/3684 ,  G06F11/3447 ,  G06F11/3688 ,  G06F11/3692

Abstract: An algorithm and method for automatically generating test vectors for an LRU by deriving test vectors at the LRU boundary that, when simulated on the LRU, reproduce input and output of given test cases at the boundary of the individual requirements, and for knowing whether there are test cases that cannot be realised, i.e. test vectors cannot be derived at the LRU boundary to reproduce them at the boundary of individual requirements.

公开(公告)号：US20240168860A1

公开(公告)日：2024-05-23

申请号：US18516421

申请日：2023-11-21

Applicant: Travis James Arlitt

Inventor： Travis James Arlitt

IPC: G06F11/34

CPC classification number: G06F11/3447

Abstract: A method for modeling a multi-event process, comprising loading a digitized representation of a plurality of events, wherein the plurality of events comprises a first sub-set of events linked to a sub-set of historical events, generating a first visual representation of the digitized representation of the plurality of events using a display device by generating a plurality of visual indicators, each visual indicator is configured to represent at least a percentage of an event progress of the first sub-set of events, modifying at least one event attribute associated with the plurality of events, computing an event progress profile corresponding to the first sub-set of events as a function of the modified at least one event attribute, and generating a second visual representation of the digitized representation of the plurality of events using the display device.

公开(公告)号：US20240160555A1

公开(公告)日：2024-05-16

申请号：US18409709

申请日：2024-01-10

Applicant: Rebellions Inc.

Inventor： Jinseok Kim

IPC: G06F11/34 ,  G06F15/78

CPC classification number: G06F11/3495 ,  G06F11/3404 ,  G06F11/3409 ,  G06F11/3447 ,  G06F15/781

Abstract: A method for measuring performance of neural processing devices and devices for measuring performance are provided. The method for measuring performance of neural processing devices comprises receiving hardware information of a neural processing device, modeling hardware components according to the hardware information as agents, dividing a calculation task by events for the agents and modeling the calculation task, thereby generating an event model which includes nodes corresponding to the agents and edges corresponding to the events and measuring a total duration of the calculation task through simulation of the event model.