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公开(公告)号:US12130720B2
公开(公告)日:2024-10-29
申请号:US17664050
申请日:2022-05-19
Applicant: Healtech Software India Pvt. Ltd.
Inventor: Atri Mandal , Sudhir Shetty , Arpit Rathi
CPC classification number: G06F11/3476 , G06F11/079 , G06F11/3409 , G06N7/01 , G06N7/02 , G06F11/0793 , G06F11/3447
Abstract: Proactive avoidance of performance issues in computing environments. In one embodiment, a causal dependency graph representing the usage dependencies among the various components of a computing environment is formed, the components being associated with key performance indicators (KPIs). A probabilistic model is trained with prior incidents that have occurred in the components to correlate outliers of KPIs in associated components to prior incidents. The training includes determining the correlation based on the causal dependency graph. Upon detecting the occurrence of outliers for performance metrics, an imminent performance issue likely to occur in a specific component is identified based on the probabilistic model and the detected outliers. A preventive action is performed to avoid the occurrence of the imminent performance issue in the specific component.
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公开(公告)号:US12106657B2
公开(公告)日:2024-10-01
申请号:US16855664
申请日:2020-04-22
Applicant: Intergraph Corporation
CPC classification number: G08B25/005 , G06N7/02 , G06N20/00 , H04L67/12
Abstract: Exemplary embodiments of the present invention provide a virtual dispatch assist system in which various types of Intelligent Agents are deployed (e.g., as part of a new CAD system architecture or as add-ons to existing CAD systems) to analyze vast amounts of historic operational data and provide various types of dispatch assist notifications and recommendations that can be used by a dispatcher or by the CAD system itself (e.g., autonomously) to make dispatch decisions.
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公开(公告)号:US20240320486A1
公开(公告)日:2024-09-26
申请号:US18347095
申请日:2023-07-05
Applicant: MING CHUAN UNIVERSITY
Inventor: DAVID CHUNHU LI
Abstract: Disclosed are a method of establishing a charging capacity prediction model based on meteorological factors and charging facility failures and its prediction method and system. The method includes: receiving charging capacity data of a charging facility and meteorological data of its location; extracting the number of random failures based on time from the charging capacity data, and obtaining the probability of failure from the probability mass function; performing a correlation test of the meteorological data with the charging capacity in the charging capacity data to obtain at least one feature factor; decomposing the time series of the charging data, and transforming to obtain the time series of charging data based on the time domain after noise reduction; and establishing a prediction model, using the probability values and feature factors as reference features, and using the charging time series data as a predictive target to train the prediction model.
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公开(公告)号:US20240289542A1
公开(公告)日:2024-08-29
申请号:US18655858
申请日:2024-05-06
Inventor: Hans-Jurgen Greiner
IPC: G06F40/174 , G06F3/0481 , G06N5/048 , G06N7/02 , G06N20/00 , G06Q20/12
CPC classification number: G06F40/174 , G06F3/0481 , G06N5/048 , G06N7/02 , G06N20/00 , G06Q20/12
Abstract: Disclosed are various embodiments for an online purchase autofill plug-in. Various embodiments can access an electronic form from a domain and then scan the electronic form for a plurality of fields. Various embodiments can receive data from an API engine which can correspond to at least one field of the plurality of fields of the electronic form. Various embodiments can then populate the at least one field in the electronic form using the data from the API engine. In at least some embodiments, the data from the API engine can be account information for a user, which can be used to fill out a payment form.
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公开(公告)号:US12069143B2
公开(公告)日:2024-08-20
申请号:US17700210
申请日:2022-03-21
Applicant: People.ai, Inc.
Inventor: Oleg Rogynskyy , Dylan Halladay , Stefan Hermanek , Yurii Brunets
IPC: G06F16/00 , G06F7/14 , G06F9/54 , G06F11/30 , G06F11/34 , G06F16/11 , G06F16/17 , G06F16/178 , G06F16/182 , G06F16/21 , G06F16/215 , G06F16/22 , G06F16/23 , G06F16/245 , G06F16/2455 , G06F16/2457 , G06F16/2458 , G06F16/25 , G06F16/26 , G06F16/27 , G06F16/28 , G06F16/29 , G06F16/31 , G06F16/335 , G06F16/35 , G06F16/901 , G06F16/903 , G06F16/9035 , G06F16/906 , G06F16/9535 , G06F21/62 , G06F40/20 , G06F40/237 , G06F40/295 , G06N3/08 , G06N5/025 , G06N5/04 , G06N7/02 , G06Q10/04 , G06Q10/0631 , G06Q10/0639 , G06Q10/107 , G06Q10/109 , G06Q10/1091 , G06Q10/1093 , G06Q50/22 , G16H50/20 , H04L41/14 , H04L43/00 , H04L43/026 , H04L43/045 , H04L43/062 , H04L43/065 , H04L43/067 , H04L43/0876 , H04L51/046 , H04L51/212 , H04L51/234 , H04L51/42 , H04L61/45 , H04L67/125 , H04L67/30 , H04L67/303 , H04L67/306 , H04L67/50 , H04M3/436 , H04M15/00 , G06F40/205 , G06N20/00 , G06Q10/10 , G16H15/00 , G16H50/30 , H04L12/14 , H04L101/00 , H04L101/35 , H04L101/37 , H04M3/22 , H04M3/56
CPC classification number: H04L67/535 , G06F7/14 , G06F9/542 , G06F11/3024 , G06F11/3452 , G06F11/3495 , G06F16/122 , G06F16/1734 , G06F16/178 , G06F16/182 , G06F16/212 , G06F16/215 , G06F16/219 , G06F16/22 , G06F16/221 , G06F16/2228 , G06F16/2264 , G06F16/2272 , G06F16/23 , G06F16/235 , G06F16/2358 , G06F16/2365 , G06F16/2379 , G06F16/2386 , G06F16/245 , G06F16/24558 , G06F16/24564 , G06F16/2457 , G06F16/24575 , G06F16/24578 , G06F16/2477 , G06F16/254 , G06F16/256 , G06F16/26 , G06F16/27 , G06F16/273 , G06F16/28 , G06F16/285 , G06F16/288 , G06F16/289 , G06F16/29 , G06F16/313 , G06F16/337 , G06F16/355 , G06F16/901 , G06F16/9024 , G06F16/90344 , G06F16/9035 , G06F16/906 , G06F16/9535 , G06F21/6218 , G06F21/6245 , G06F40/20 , G06F40/237 , G06F40/295 , G06N3/08 , G06N5/025 , G06N5/04 , G06N7/02 , G06Q10/04 , G06Q10/063114 , G06Q10/06312 , G06Q10/06315 , G06Q10/06393 , G06Q10/06398 , G06Q10/107 , G06Q10/109 , G06Q10/1091 , G06Q10/1095 , G06Q50/22 , G16H50/20 , H04L41/14 , H04L43/026 , H04L43/045 , H04L43/062 , H04L43/065 , H04L43/067 , H04L43/0876 , H04L43/14 , H04L51/046 , H04L51/212 , H04L51/234 , H04L51/42 , H04L61/45 , H04L67/125 , H04L67/30 , H04L67/303 , H04L67/306 , H04M3/436 , H04M15/755 , G06F40/205 , G06N20/00 , G06Q10/10 , G16H15/00 , G16H50/30 , H04L12/1407 , H04L2101/00 , H04L2101/35 , H04L2101/37 , H04M3/2218 , H04M3/56
Abstract: The present disclosure relates to systems and methods for determining an engagement profile of a participant by associating electronic activities to a profile. It may generate the engagement profile based on analysis of the electronic activity level. An example implementation may contain the following steps. The system may access for a first record object a plurality of electronic activities linked with the first record object. The system may identify for a participant from the plurality of electronic activities a set of electronic activities including the participant. The system may determine an engagement profile of the participant based on a first number of electronic activities of the set of electronic activities sent by the participant, a second number of the set of electronic activities received by the participant and a temporal distribution of the set of electronic activities. The system may store the engagement profile in one or more data structures.
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公开(公告)号:US12069142B2
公开(公告)日:2024-08-20
申请号:US17683245
申请日:2022-02-28
Applicant: People.ai, Inc.
Inventor: John Wulf , Sathya Hariesh Prakash , Yurii Brunets , Oleg Rogynskyy , Rajit Kurien Joseph , Yury Markovsky
IPC: H04L67/50 , G06F7/14 , G06F9/54 , G06F11/30 , G06F11/34 , G06F16/11 , G06F16/17 , G06F16/178 , G06F16/182 , G06F16/21 , G06F16/215 , G06F16/22 , G06F16/23 , G06F16/245 , G06F16/2455 , G06F16/2457 , G06F16/2458 , G06F16/25 , G06F16/26 , G06F16/27 , G06F16/28 , G06F16/29 , G06F16/31 , G06F16/335 , G06F16/35 , G06F16/901 , G06F16/903 , G06F16/9035 , G06F16/906 , G06F16/9535 , G06F21/62 , G06F40/20 , G06F40/237 , G06F40/295 , G06N3/08 , G06N5/025 , G06N5/04 , G06N7/02 , G06Q10/04 , G06Q10/0631 , G06Q10/0639 , G06Q10/107 , G06Q10/109 , G06Q10/1091 , G06Q10/1093 , G06Q50/22 , G16H50/20 , H04L41/14 , H04L43/00 , H04L43/026 , H04L43/045 , H04L43/062 , H04L43/065 , H04L43/067 , H04L43/0876 , H04L51/046 , H04L51/212 , H04L51/234 , H04L51/42 , H04L61/45 , H04L67/125 , H04L67/30 , H04L67/303 , H04L67/306 , H04M3/436 , H04M15/00 , G06F40/205 , G06N20/00 , G06Q10/10 , G16H15/00 , G16H50/30 , H04L12/14 , H04L101/00 , H04L101/35 , H04L101/37 , H04M3/22 , H04M3/56
CPC classification number: H04L67/535 , G06F7/14 , G06F9/542 , G06F11/3024 , G06F11/3452 , G06F11/3495 , G06F16/122 , G06F16/1734 , G06F16/178 , G06F16/182 , G06F16/212 , G06F16/215 , G06F16/219 , G06F16/22 , G06F16/221 , G06F16/2228 , G06F16/2264 , G06F16/2272 , G06F16/23 , G06F16/235 , G06F16/2358 , G06F16/2365 , G06F16/2379 , G06F16/2386 , G06F16/245 , G06F16/24558 , G06F16/24564 , G06F16/2457 , G06F16/24575 , G06F16/24578 , G06F16/2477 , G06F16/254 , G06F16/256 , G06F16/26 , G06F16/27 , G06F16/273 , G06F16/28 , G06F16/285 , G06F16/288 , G06F16/289 , G06F16/29 , G06F16/313 , G06F16/337 , G06F16/355 , G06F16/901 , G06F16/9024 , G06F16/90344 , G06F16/9035 , G06F16/906 , G06F16/9535 , G06F21/6218 , G06F21/6245 , G06F40/20 , G06F40/237 , G06F40/295 , G06N3/08 , G06N5/025 , G06N5/04 , G06N7/02 , G06Q10/04 , G06Q10/063114 , G06Q10/06312 , G06Q10/06315 , G06Q10/06393 , G06Q10/06398 , G06Q10/107 , G06Q10/109 , G06Q10/1091 , G06Q10/1095 , G06Q50/22 , G16H50/20 , H04L41/14 , H04L43/026 , H04L43/045 , H04L43/062 , H04L43/065 , H04L43/067 , H04L43/0876 , H04L43/14 , H04L51/046 , H04L51/212 , H04L51/234 , H04L51/42 , H04L61/45 , H04L67/125 , H04L67/30 , H04L67/303 , H04L67/306 , H04M3/436 , H04M15/755 , G06F40/205 , G06N20/00 , G06Q10/10 , G16H15/00 , G16H50/30 , H04L12/1407 , H04L2101/00 , H04L2101/35 , H04L2101/37 , H04M3/2218 , H04M3/56
Abstract: The present disclosure relates to methods, systems, and storage media for detecting events based on updates to node profiles from electronic activities. Exemplary implementations may access an electronic activity transmitted or received via an electronic account associated with a data source provider; generate a plurality of activity field-value pairs; maintain a plurality of node profiles; identify a first state of a first node profile of the plurality of node profiles; update the first node profile using the electronic activity; identify a second state of the first node profile subsequent to updating the first node profile using the electronic activity; detect a state change of the first node profile based on the first state and the second state; determine that the state change satisfies an event condition; and store an association between the first node profile and an event type corresponding to the event condition.
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公开(公告)号:US12045824B2
公开(公告)日:2024-07-23
申请号:US17016866
申请日:2020-09-10
Applicant: Early Warning Services, LLC
Inventor: Laura Weinflash
CPC classification number: G06Q20/4016 , G06F18/22 , G06N7/02 , H04L9/0825 , G06Q2220/00 , H04L2209/56
Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform various acts. The acts can include: (a) receiving a payment authorization, through a network, from a sender financial institution; (b) obtaining, in real-time after receiving the payment authorization, a sender status based on sender information of the payment authorization; (c) when the sender status is preauthorized, instructing, through the network and in real-time after obtaining the sender status, a recipient financial institution to bypass a transaction fraud detection mechanism; and (d) instructing, through the network, the recipient financial institution to post a payment amount of the payment authorization to a recipient account in real-time. Other embodiments are described.
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公开(公告)号:US20240171649A1
公开(公告)日:2024-05-23
申请号:US18427768
申请日:2024-01-30
Applicant: People.ai, Inc.
Inventor: Oleg ROGYNSKYY , Yurii BRUNETS , Eric JESKE , Nicholas DINGWALL
IPC: H04L67/50 , G06F7/14 , G06F9/54 , G06F11/30 , G06F11/34 , G06F16/11 , G06F16/17 , G06F16/178 , G06F16/182 , G06F16/21 , G06F16/215 , G06F16/22 , G06F16/23 , G06F16/245 , G06F16/2455 , G06F16/2457 , G06F16/2458 , G06F16/25 , G06F16/26 , G06F16/27 , G06F16/28 , G06F16/29 , G06F16/31 , G06F16/335 , G06F16/35 , G06F16/901 , G06F16/903 , G06F16/9035 , G06F16/906 , G06F16/9535 , G06F21/62 , G06F40/20 , G06F40/205 , G06F40/237 , G06F40/295 , G06N3/08 , G06N5/025 , G06N5/04 , G06N7/02 , G06N20/00 , G06Q10/04 , G06Q10/0631 , G06Q10/0639 , G06Q10/10 , G06Q10/107 , G06Q10/109 , G06Q10/1091 , G06Q10/1093 , G06Q50/22 , G16H15/00 , G16H50/20 , G16H50/30 , H04L12/14 , H04L41/14 , H04L43/00 , H04L43/026 , H04L43/045 , H04L43/062 , H04L43/065 , H04L43/067 , H04L43/0876 , H04L51/046 , H04L51/212 , H04L51/234 , H04L51/42 , H04L61/45 , H04L67/125 , H04L67/30 , H04L67/303 , H04L67/306 , H04L101/00 , H04L101/35 , H04L101/37 , H04M3/22 , H04M3/436 , H04M3/56 , H04M15/00
CPC classification number: H04L67/535 , G06F7/14 , G06F9/542 , G06F11/3024 , G06F11/3452 , G06F11/3495 , G06F16/122 , G06F16/1734 , G06F16/178 , G06F16/182 , G06F16/212 , G06F16/215 , G06F16/219 , G06F16/22 , G06F16/221 , G06F16/2228 , G06F16/2264 , G06F16/2272 , G06F16/23 , G06F16/235 , G06F16/2358 , G06F16/2365 , G06F16/2379 , G06F16/2386 , G06F16/245 , G06F16/24558 , G06F16/24564 , G06F16/2457 , G06F16/24575 , G06F16/24578 , G06F16/2477 , G06F16/254 , G06F16/256 , G06F16/26 , G06F16/27 , G06F16/273 , G06F16/28 , G06F16/285 , G06F16/288 , G06F16/289 , G06F16/29 , G06F16/313 , G06F16/337 , G06F16/355 , G06F16/901 , G06F16/9024 , G06F16/90344 , G06F16/9035 , G06F16/906 , G06F16/9535 , G06F21/6218 , G06F21/6245 , G06F40/20 , G06F40/237 , G06F40/295 , G06N3/08 , G06N5/025 , G06N5/04 , G06N7/02 , G06Q10/04 , G06Q10/063114 , G06Q10/06312 , G06Q10/06315 , G06Q10/06393 , G06Q10/06398 , G06Q10/107 , G06Q10/109 , G06Q10/1091 , G06Q10/1095 , G06Q50/22 , G16H50/20 , H04L41/14 , H04L43/026 , H04L43/045 , H04L43/062 , H04L43/065 , H04L43/067 , H04L43/0876 , H04L43/14 , H04L51/046 , H04L51/212 , H04L51/234 , H04L51/42 , H04L61/45 , H04L67/125 , H04L67/30 , H04L67/303 , H04L67/306 , H04M3/436 , H04M15/755 , G06F40/205 , G06N20/00 , G06Q10/10 , G16H15/00 , G16H50/30 , H04L12/1407 , H04L2101/00 , H04L2101/35 , H04L2101/37 , H04M3/2218 , H04M3/56
Abstract: The present disclosure relates to systems and methods for determining an engagement profile of a participant by associating electronic activities to a profile. It may generate the engagement profile based on analysis of the electronic activity level. An example implementation may contain the following steps. The system may access for a first record object a plurality of electronic activities linked with the first record object. The system may identify for a participant from the plurality of electronic activities a set of electronic activities including the participant. The system may determine an engagement profile of the participant based on a first number of electronic activities of the set of electronic activities sent by the participant, a second number of the set of electronic activities received by the participant and a temporal distribution of the set of electronic activities. The system may store the engagement profile in one or more data structures.
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公开(公告)号:US11979468B2
公开(公告)日:2024-05-07
申请号:US17102397
申请日:2020-11-23
Applicant: People.ai, Inc.
Inventor: John Wulf , Sathya Hariesh Prakash , Tetiana Lutsaievska , Oleg Rogynskyy
IPC: G06F16/00 , G06F7/14 , G06F9/54 , G06F11/30 , G06F11/34 , G06F16/11 , G06F16/17 , G06F16/178 , G06F16/182 , G06F16/21 , G06F16/215 , G06F16/22 , G06F16/23 , G06F16/245 , G06F16/2455 , G06F16/2457 , G06F16/2458 , G06F16/25 , G06F16/26 , G06F16/27 , G06F16/28 , G06F16/29 , G06F16/31 , G06F16/335 , G06F16/35 , G06F16/901 , G06F16/903 , G06F16/9035 , G06F16/906 , G06F16/9535 , G06F21/62 , G06F40/20 , G06F40/237 , G06F40/295 , G06N3/08 , G06N5/025 , G06N5/04 , G06N7/02 , G06Q10/04 , G06Q10/0631 , G06Q10/0639 , G06Q10/107 , G06Q10/109 , G06Q10/1091 , G06Q10/1093 , G06Q50/22 , G16H50/20 , H04L41/14 , H04L43/00 , H04L43/026 , H04L43/045 , H04L43/062 , H04L43/065 , H04L43/067 , H04L43/0876 , H04L51/046 , H04L51/212 , H04L51/234 , H04L51/42 , H04L61/45 , H04L67/125 , H04L67/30 , H04L67/303 , H04L67/306 , H04L67/50 , H04M3/436 , H04M15/00 , G06F40/205 , G06N20/00 , G06Q10/10 , G16H15/00 , G16H50/30 , H04L12/14 , H04L101/00 , H04L101/35 , H04L101/37 , H04M3/22 , H04M3/56
CPC classification number: H04L67/535 , G06F7/14 , G06F9/542 , G06F11/3024 , G06F11/3452 , G06F11/3495 , G06F16/122 , G06F16/1734 , G06F16/178 , G06F16/182 , G06F16/212 , G06F16/215 , G06F16/219 , G06F16/22 , G06F16/221 , G06F16/2228 , G06F16/2264 , G06F16/2272 , G06F16/23 , G06F16/235 , G06F16/2358 , G06F16/2365 , G06F16/2379 , G06F16/2386 , G06F16/245 , G06F16/24558 , G06F16/24564 , G06F16/2457 , G06F16/24575 , G06F16/24578 , G06F16/2477 , G06F16/254 , G06F16/256 , G06F16/26 , G06F16/27 , G06F16/273 , G06F16/28 , G06F16/285 , G06F16/288 , G06F16/289 , G06F16/29 , G06F16/313 , G06F16/337 , G06F16/355 , G06F16/901 , G06F16/9024 , G06F16/90344 , G06F16/9035 , G06F16/906 , G06F16/9535 , G06F21/6218 , G06F21/6245 , G06F40/20 , G06F40/237 , G06F40/295 , G06N3/08 , G06N5/025 , G06N5/04 , G06N7/02 , G06Q10/04 , G06Q10/063114 , G06Q10/06312 , G06Q10/06315 , G06Q10/06393 , G06Q10/06398 , G06Q10/107 , G06Q10/109 , G06Q10/1091 , G06Q10/1095 , G06Q50/22 , G16H50/20 , H04L41/14 , H04L43/026 , H04L43/045 , H04L43/062 , H04L43/065 , H04L43/067 , H04L43/0876 , H04L43/14 , H04L51/046 , H04L51/212 , H04L51/234 , H04L51/42 , H04L61/45 , H04L67/125 , H04L67/30 , H04L67/303 , H04L67/306 , H04M3/436 , H04M15/755 , G06F40/205 , G06N20/00 , G06Q10/10 , G16H15/00 , G16H50/30 , H04L12/1407 , H04L2101/00 , H04L2101/35 , H04L2101/37 , H04M3/2218 , H04M3/56
Abstract: The present disclosure relates to methods, systems, and storage media for detecting events based on updates to node profiles from electronic activities. Exemplary implementations may access an electronic activity transmitted or received via an electronic account associated with a data source provider; generate a plurality of activity field-value pairs; maintain a plurality of node profiles; identify a first state of a first node profile of the plurality of node profiles; update the first node profile using the electronic activity; identify a second state of the first node profile subsequent to updating the first node profile using the electronic activity; detect a state change of the first node profile based on the first state and the second state; determine that the state change satisfies an event condition; and store an association between the first node profile and an event type corresponding to the event condition.
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公开(公告)号:US11954253B2
公开(公告)日:2024-04-09
申请号:US16993083
申请日:2020-08-13
Applicant: Ford Global Technologies, LLC
Inventor: Ali Hassani , Aniruddh Ravindran , Dimitar Filev , Vijay Nagasamy
CPC classification number: G06F3/015 , B60W10/18 , B60W10/20 , B60W40/08 , B60W50/10 , G06N7/02 , B60W2540/22
Abstract: Embodiments describe a system configured with a brain machine interface (BMI) system implemented in a vehicle for performing vehicle functions using electrical impulses from motor cortex activity in a user's brain. The system uses fuzzy states for increased robustness. The fuzzy states are defined by sets of Gaussian kernel-type membership functions that are defined for steering and velocity action function states. The membership functions define fuzzy states that provide overlapping control tiers for increasing and decreasing vehicle functionality. An autonomous vehicle may perform control and governance of transitions between membership functions that may overlap, resulting in smooth transitioning between the states.
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