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公开(公告)号:US11900277B2
公开(公告)日:2024-02-13
申请号:US17744980
申请日:2022-05-16
摘要: Industrial smart data tags conforming to structured data types serve as the basis for creating a digital twin of an industrial asset. The digital twin can comprise an automation model and a mechanical model or other type of non-automation model, both of which reference the smart tags in connection with digitally modeling the industrial asset. The structured data topology offered by the smart tags allows the digital twin to be readily interfaced with artificial intelligence (AI) systems. AI analysis can leverage the smart tags to discover new relationships between key performance indicators and other variables of the asset and encode these relationships in the smart tags themselves. These enhanced smart tags can also be leveraged to perform AI-based validation the digital twin. Additional contextualization provided by the enhanced smart tags can simplify AI analysis and assist in quickly converging on desired analytic results.
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公开(公告)号:US20240037428A1
公开(公告)日:2024-02-01
申请号:US17872982
申请日:2022-07-25
申请人: Gravystack, Inc.
发明人: Scott Donnell , Travis Adams , Chad Willardson
摘要: The invention is direct towards generating an expert template. The expert template is associated with an expert who can help guide a user. A user is associated with user goal data and a user goal. A user goal is an objective that the user wants to complete. A user is matched with an expert that matches the expert's field of expertise with the user's goals. An expert may provide input to the user regarding guidance and goals.
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公开(公告)号:US11861515B2
公开(公告)日:2024-01-02
申请号:US17961822
申请日:2022-10-07
发明人: Daniel Erenrich , Anirvan Mukherjee
IPC分类号: G06N5/048 , G06Q30/01 , G06F16/2455 , G06Q30/0202 , G06N7/00 , G06Q30/0201 , G06N7/01
CPC分类号: G06N5/048 , G06F16/2455 , G06N7/01 , G06Q30/01 , G06Q30/0202 , G06Q30/0201
摘要: Systems and methods are disclosed for determining a propensity of an entity to take a specified action. In accordance with one implementation, a method is provided for determining the propensity. The method includes, for example, accessing one or more data sources, the one or more data sources including information associated with the entity, forming a record associated with the entity by integrating the information from the one or more data sources, generating, based on the record, one or more features associated with the entity, processing the one or more features to determine the propensity of the entity to take the specified action, and outputting the propensity.
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公开(公告)号:US20230400443A1
公开(公告)日:2023-12-14
申请号:US18332018
申请日:2023-06-09
发明人: Zewei AN , Yanshi HU , Xia ZENG , Zhi DENG , Wenguan WU , Han CHENG , Jialin FANG
CPC分类号: G01N33/0098 , G06N5/048
摘要: A method for evaluating cold tolerance of Hevea brasiliensis includes: (1) taking different one-year-old germplasm plants of the Hevea brasiliensis with second whorls of leaves entering a stable period as materials, firstly culturing the materials at a normal temperature, then treating the materials at a low temperature, and finally respectively measuring relative electrical conductivities of the materials cultured at the normal temperature and physiological indexes of the cold tolerance of the materials treated at the low temperature, where a variety 93114 is used as a cold tolerance control and a Reyan 73397 is used as a sensitive control; and (2) according to changes of the physiological indexes of the cold tolerance in the germplasm plants of the Hevea brasiliensis, comprehensively evaluating the cold tolerance of the materials by using a fuzzy membership function method. When comprehensive indexes of the cold tolerance are larger, the cold tolerance of the materials is better.
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公开(公告)号:US11840176B2
公开(公告)日:2023-12-12
申请号:US17862348
申请日:2022-07-11
申请人: Robert D. Pedersen
发明人: Robert D. Pedersen
IPC分类号: B60Q9/00 , G10L25/78 , H04W4/90 , G08G1/048 , G10L21/0232 , H04R1/40 , G08G1/01 , G10L15/26 , G10L15/22 , G08G1/16 , G06N5/02 , H04W4/80 , G08G1/0967 , G08G1/00 , H04R3/00 , H04W4/02 , H04W4/40 , G06N5/048 , H04B5/00 , H04M1/72454 , H04M1/72463 , G06V20/56 , G06V20/59 , G10L21/0216 , H04B7/06
CPC分类号: B60Q9/008 , G06N5/02 , G06N5/048 , G06V20/56 , G06V20/597 , G08G1/012 , G08G1/0116 , G08G1/0129 , G08G1/0141 , G08G1/048 , G08G1/096716 , G08G1/096741 , G08G1/096775 , G08G1/096783 , G08G1/166 , G08G1/167 , G08G1/205 , G10L15/22 , G10L15/26 , G10L21/0232 , G10L25/78 , H04B5/0056 , H04B5/0081 , H04M1/72454 , H04M1/72463 , H04R1/406 , H04R3/005 , H04W4/023 , H04W4/40 , H04W4/80 , H04W4/90 , G10L2021/02166 , H04B5/0043 , H04B7/0617 , H04R2201/403 , H04R2499/13
摘要: Specifically programmed, integrated motor vehicle dangerous driving warning and control system and methods comprising at least one specialized communication computer machine including electronic artificial intelligence expert system decision making capability further comprising one or more motor vehicle electronic sensors for monitoring the motor vehicle and for monitoring activities of the driver and/or passengers including activities related to the use of cellular telephones and/or other wireless communication devices and further comprising electronic communications transceiver assemblies for communications with external sensor networks for monitoring dangerous driving situations, weather conditions, roadway conditions, pedestrian congestion and motor vehicle traffic congestion conditions to derive warning and/or control signals for warning the driver of dangerous driving situations and/or for controlling the motor vehicle driver use of a cellular telephone and/or other wireless communication devices.
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公开(公告)号:US11836644B2
公开(公告)日:2023-12-05
申请号:US16532543
申请日:2019-08-06
发明人: Lingyun Wang , Junmei Qu , Xi Xia , Xin Xin Bai , Jin Yan Shao
CPC分类号: G06N5/048 , G01W1/10 , G16Z99/00 , G01N33/0004
摘要: A method, a device and a computer program product for abnormal air pollution emission prediction are proposed. In the method, a first set of features characterizing air condition in a zone is obtained. Whether the zone is subject to abnormal air pollution emission in a future first time period is determined based on the first set of features and using a first prediction classifier. In response to determining that the zone is subject to abnormal air pollution emission in the first time period, a second set of features characterizing air condition in the zone is obtained. A future second time period in which the zone is subject to abnormal air pollution emission is determined based on the second set of features and using a second prediction classifier. The second time period is included in the first time period. In this way, the abnormal air pollution emission in the zone can be accurately and efficiently predicted.
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公开(公告)号:US11811788B2
公开(公告)日:2023-11-07
申请号:US16810988
申请日:2020-03-06
申请人: F-Secure Corporation
发明人: Matti Aksela
IPC分类号: H04L9/40 , G06N20/00 , G06N3/08 , G06N5/048 , G06F18/214 , G06F18/243 , G06N7/01
CPC分类号: H04L63/1408 , G06F18/2148 , G06F18/24323 , G06N3/08 , G06N5/048 , G06N7/01 , G06N20/00 , H04L63/0227 , H04L63/1416 , H04L63/1425 , H04L63/1433 , H04L63/1441 , H04L63/20
摘要: A method comprising: receiving raw data related to one or more network nodes, wherein dissimilar data types are aligned as input events; filtering one or more of the input events by using an adjustable threshold that is based on a filtering score, wherein the filtering score is an estimate of the likelihood that the input event is followed by a security related detection; processing only input events passed through the filtering by an enrichment process; and analysing the data received from the enrichment process for generating a security related decision.
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公开(公告)号:US20230325693A1
公开(公告)日:2023-10-12
申请号:US18194679
申请日:2023-04-03
申请人: INTUIT INC.
发明人: Grace WU , Shashank SHASHIKANT RAO , Susrutha GONGALLA , Ngoc Nhung HO , Carly WOOD , Vaibhav SHARMA
摘要: Aspects of the present disclosure provide techniques for classifying a trip. Embodiments include receiving, from a plurality of users, a plurality of historical trip records. Each of the plurality of historical trip records may comprise one or more historical trip attributes and historical classification information. Embodiments include training a predictive model, using the plurality of historical trip records, to classify trips based on trip records. Training the predictive model may comprise determining a plurality of hot spots based on the historical trip records, each of the plurality of hot spots comprising a region encompassing one or more locations, and associating, in the predictive model, the plurality of hot spots with historical classification information. Embodiments include receiving, from a user, a new trip record comprising a plurality of trip attributes related to a trip and using the predictive model to predict a classification for the trip based on the trip record.
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公开(公告)号:US11748230B2
公开(公告)日:2023-09-05
申请号:US17325602
申请日:2021-05-20
申请人: VMware, Inc.
发明人: Keshav Mathur , Jinyi Lu , Paul Pedersen , Junyuan Lin , Darren Brown , Peng Gao , Leah Nutman , Xing Wang
CPC分类号: G06F11/3442 , G06F9/5027 , G06F11/3006 , G06F11/3447 , G06N5/048
摘要: Various examples are disclosed for transitioning usage forecasting in a computing environment. Usage of computing resources of a computing environment are forecasted using a first forecasting data model and usage measurements obtained from the computing resources. A use of the first forecasting data model in forecasting the usage is transitioned to a second forecasting data model without incurring downtime in the computing environment. After the transition, the usage of the computing resources of the computing environment is forecasted using the second forecasting data model and the usage measurements obtained from the computing resources. The second forecasting data model exponentially decays the usage measurements based on a respective time period at which the usage measurements were obtained.
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公开(公告)号:US11747245B2
公开(公告)日:2023-09-05
申请号:US17354966
申请日:2021-06-22
申请人: Xiangtan University
发明人: Zengsheng Ma , Dian Peng , Yichun Zhou
CPC分类号: G01N3/06 , G01N3/08 , G05B13/0295 , G06N5/048 , G01N2203/0019 , G01N2203/0032
摘要: A load control method and a load control system of an indenter based on fuzzy predictive control, are provided. The method includes acquiring an actual measured force value of a sensor and an expected force value of the nth cycle in the loading stage; calculating a first error and a change rate; establishing and optimizing a fuzzy predictive controller; determining movement steps of a motor in the loading stage; acquiring the actual measured value of the sensor and an expected force value of the nth cycle in the full load stage; controlling the movement of the motor; acquiring the actual measured force value of the sensor and an expected force value of the nth cycle in the unloading stage; calculating a third error and a change rate; and determining the movement steps of the motor in the unloading stage.
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