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公开(公告)号:US12131142B2
公开(公告)日:2024-10-29
申请号:US17332649
申请日:2021-05-27
发明人: Dustin Garvey , Amit Ganesh , Uri Shaft , Prasad Ravuri , Long Yang , Sampanna Shahaji Salunke , Sumathi Gopalakrishnan , Timothy Mark Frazier , Shriram Krishnan
CPC分类号: G06F8/65 , G06F8/60 , G06F8/61 , G06F9/5055 , G06F16/906 , G06N20/00 , G06N5/022
摘要: Techniques for artificial intelligence driven configuration management are described herein. In some embodiments, a machine-learning process determines a feature set for a plurality of deployments of a software resource. Based on varying values in the feature set, the process clusters each of the plurality of deployments into a cluster of a plurality of clusters. Each cluster of the plurality of clusters comprises one or more nodes and each node of the one or more nodes corresponds to at least a subset of values of the feature set that are detected in at least one deployment of the plurality of deployments of the software resource. The process determines a representative node for each cluster of the plurality of clusters. An operation may be performed based on the representative node for at least one cluster.
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公开(公告)号:US12130907B2
公开(公告)日:2024-10-29
申请号:US18297932
申请日:2023-04-10
CPC分类号: G06F21/46 , G06N5/04 , G06N20/00 , G06Q50/265
摘要: Disclosed herein are system, method, and device embodiments for implementing password suggestion. An embodiment operates by selecting one or more random terms from dictionary information, generating an alphanumeric string based on a password requirement, combining the one or more random terms and the alphanumeric string to form a generated password, determining a password strength of the generated password based on compromised password information, and presenting the generated password for selection by a user device when the password strength meets or exceeds a threshold value.
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公开(公告)号:US12130875B2
公开(公告)日:2024-10-29
申请号:US18008604
申请日:2022-06-02
申请人: Google LLC
发明人: Wei Huang , Arne Mauser
IPC分类号: G06F16/9535 , G06F16/906 , G06N20/00 , H04L67/306 , H04L67/50 , H04L67/55
CPC分类号: G06F16/9535 , G06F16/906 , G06N20/00 , H04L67/306 , H04L67/535 , H04L67/55
摘要: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting and distributing digital components based on predicted user attributes of users are described. In one aspect, a method includes obtaining data indicating content categories of content of the content pages accessed by the user during the user visits. A determination is made for an aggregate measure of each content category based on a quantity of user visits to content pages of the electronic resource of the publisher that included content classified as belonging to the content category. User attribute prediction data indicating previously predicted user attributes of the user is obtained. User attributes are predicted for the current visit of the user to the electronic resource of the publisher that is further used to select digital components for display with the electronic resource on a client device during the current visit.
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公开(公告)号:US12130850B2
公开(公告)日:2024-10-29
申请号:US18147960
申请日:2022-12-29
申请人: Adobe Inc.
发明人: Trung Bui , Yu Gong , Tushar Dublish , Sasha Spala , Sachin Soni , Nicholas Miller , Joon Kim , Franck Dernoncourt , Carl Dockhorn , Ajinkya Kale
CPC分类号: G06F16/3347 , G06F40/30 , G06N5/04 , G06N20/00
摘要: Techniques and systems are described for performing semantic text searches. A semantic text-searching solution uses a machine learning system (such as a deep learning system) to determine associations between the semantic meanings of words. These associations are not limited by the spelling, syntax, grammar, or even definition of words. Instead, the associations can be based on the context in which characters, words, and/or phrases are used in relation to one another. In response to detecting a request to locate text within an electronic document associated with a keyword, the semantic text-searching solution can return strings within the document that have matching and/or related semantic meanings or contexts, in addition to exact matches (e.g., string matches) within the document. The semantic text-searching solution can then output an indication of the matching strings.
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公开(公告)号:US12130611B2
公开(公告)日:2024-10-29
申请号:US17484691
申请日:2021-09-24
发明人: Jordan C. Reynolds , John J. Hagerbaumer , Troy W. Mahr , Jeffrey S. Sperling , Thomas K. Jacobsen , Giancarlo Scaturchio
IPC分类号: G06N20/00 , G05B19/418 , G06N20/20
CPC分类号: G05B19/41845 , G05B19/4183 , G06N20/20
摘要: Various embodiments of the present technology generally relate to solutions for integrating machine learning models into industrial automation environments. More specifically, embodiments include systems and methods for implementing machine learning models within industrial control code to improve performance, increase productivity, and add capability to existing programs. In an embodiment, a system comprises: a control component configured to run a closed-loop industrial process comprises a first machine learning model; a measurement component configured to measure a gap between outcome data predicted by the first machine learning model and actual outcome data; a determination component configured to determine, based on the gap, that the first machine learning model has degraded; and a management component configured to replace the first machine learning model with a second machine learning model, wherein the second machine learning model is trained based at least in part on the actual outcome data.
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公开(公告)号:US12130610B2
公开(公告)日:2024-10-29
申请号:US16181194
申请日:2018-11-05
申请人: R4N63R Capital LLC
发明人: Prasad Narasimha Akella , Ananya Honnedevasthana Ashok , Zakaria Ibrahim Assoul , Krishnendu Chaudhury , Sameer Gupta , Sujay Venkata Krishna Narumanchi , David Scott Prager , Devashish Shankar , Ananth Uggirala , Yash Raj Chhabra
IPC分类号: G06F16/24 , G05B19/418 , G06F9/448 , G06F9/48 , G06F11/07 , G06F11/34 , G06F16/22 , G06F16/23 , G06F16/2455 , G06F16/901 , G06F16/9035 , G06F16/904 , G06F30/20 , G06F30/23 , G06N3/008 , G06N3/04 , G06N3/044 , G06N3/045 , G06N3/08 , G06N3/084 , G06N7/01 , G06N20/00 , G06Q10/06 , G06Q10/0631 , G06Q10/0639 , G06T19/00 , G06V10/25 , G06V10/44 , G06V10/82 , G06V20/52 , G06V40/20 , G09B19/00 , B25J9/16 , G01M99/00 , G05B19/423 , G05B23/02 , G06F18/21 , G06F111/10 , G06F111/20 , G06N3/006 , G06Q10/083 , G06Q50/26 , G16H10/60
CPC分类号: G05B19/4183 , G05B19/41835 , G06F9/4498 , G06F9/4881 , G06F11/0721 , G06F11/079 , G06F11/3452 , G06F16/2228 , G06F16/2365 , G06F16/24568 , G06F16/9024 , G06F16/9035 , G06F16/904 , G06F30/20 , G06F30/23 , G06N3/008 , G06N3/04 , G06N3/044 , G06N3/045 , G06N3/08 , G06N3/084 , G06N7/01 , G06N20/00 , G06Q10/06 , G06Q10/063112 , G06Q10/06316 , G06Q10/06393 , G06Q10/06395 , G06Q10/06398 , G06T19/006 , G06V10/25 , G06V10/454 , G06V10/82 , G06V20/52 , G06V40/20 , G09B19/00 , B25J9/1664 , B25J9/1697 , G01M99/005 , G05B19/41865 , G05B19/423 , G05B23/0224 , G05B2219/32056 , G05B2219/36442 , G06F18/217 , G06F2111/10 , G06F2111/20 , G06N3/006 , G06Q10/083 , G06Q50/26 , G16H10/60
摘要: The systems and methods provide an action recognition and analytics tool for use in manufacturing, health care services, shipping, retailing and other similar contexts. Machine learning action recognition can be utilized to determine cycles, processes, actions, sequences, objects and or the like in one or more sensor streams. The sensor streams can include, but are not limited to, one or more video sensor frames, thermal sensor frames, infrared sensor frames, and or three-dimensional depth frames. The analytics tool can provide for automatic creation of certificates for each instance of a subject product or service. The certificates can string together snippets of the sensor streams along with indicators of cycles, processes, action, sequences, objects, parameters and the like captured in the sensor streams.
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公开(公告)号:US12130604B2
公开(公告)日:2024-10-29
申请号:US17678442
申请日:2022-02-23
IPC分类号: G05B19/042 , G06N20/00
CPC分类号: G05B19/042 , G06N20/00 , G05B2219/2614
摘要: An embodiment includes retrofitting an existing control device with an automation panel that senses manual actuation of a control element of the control device, and automatically actuates the control element in response to a specified control signal. The embodiment collects state data indicative of an actuation state of the control element and context data of conditions at a time that the state data is collected, and generates a training dataset comprising collected state data and sensor data. It then uses this data to train a classification model to predict a control element actuation state based on sensor data. The embodiment deploys the trained classification model to process sensor data and upon detecting a mismatch between a predicted actuation state output from the trained classification model and an actual actuation state of the control element, the embodiment transmits the specified control signal to the automation panel to actuate the control element.
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公开(公告)号:US12130037B2
公开(公告)日:2024-10-29
申请号:US18043447
申请日:2021-09-03
发明人: Tomohiro Noda
摘要: This disclosure aims to provide a technique for improving the accuracy of prediction. An information processing apparatus performs a process including: acquiring a first data set related to a first machine, the first data set including: combined data, made by combining first measurement data with labels set for the first measurement data; and second measurement data for which no labels are set; generating a first trained model for inferring labels for measurement data of the first machine, based on the first data set; and generating a second trained model for inferring the labels for the measurement data of the first machine, based on the first trained model.
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公开(公告)号:US12129783B2
公开(公告)日:2024-10-29
申请号:US17656585
申请日:2022-03-25
发明人: Nathan Kempema , Conner Sharpe , David John Kubinski , Xiao Wu , Mehrdad Shahabi
IPC分类号: F01N3/00 , F01N3/08 , F01N3/20 , G06F18/214 , G06N20/00
CPC分类号: F01N3/2073 , F01N3/0814 , F01N3/206 , G06F18/214 , G06N20/00
摘要: Methods and systems are provided for a vehicle. In one example, a method may include acquiring measurements from at least one exhaust emission sensor of the vehicle, the exhaust emission sensor positioned to measure one of NOx, NH3, and O2 levels in exhaust gas of the vehicle. The measurements may be input into a machine learning model trained to output a predicted real-time amount of at least one exhaust gas constituent in the exhaust gas and operations of an emissions aftertreatment system may be assessed and adjusted based on the predicted real-time amount of the at least one exhaust gas constituent.
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公开(公告)号:US12128135B2
公开(公告)日:2024-10-29
申请号:US16819700
申请日:2020-03-16
发明人: Cetin Cetinkaya
IPC分类号: A61K9/00 , A61J3/00 , A61K9/20 , A61K9/28 , B33Y10/00 , B33Y80/00 , G01N33/15 , G06N3/08 , G06N20/00
CPC分类号: A61K9/0097 , A61J3/00 , A61K9/0053 , A61K9/20 , A61K9/2095 , A61K9/2893 , G01N33/15 , G06N3/08 , G06N20/00 , B33Y10/00 , B33Y80/00
摘要: A solid dosage product having a tailored dissolution profile comprises a carrier block defining a plurality of compartments where each respective compartment is configured to receive one or more active pharmaceutical ingredient and the carrier block being digestible within an animal such that each respective active pharmaceutical ingredient is controllably released; and one or more coating layers applied to the carrier block. A method for manufacturing a solid dosage product having a tailored dissolution comprises manufacturing a digestible carrier block where the carrier block defines a plurality of compartments with each respective compartment configured to receive an active pharmaceutical ingredient; filling a respective compartment with a respective active pharmaceutical ingredient; and coating the carrier block with one or more coating layers.
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