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公开(公告)号：US20180212834A1
公开(公告)日：2018-07-26
申请号：US15899607
申请日：2018-02-20
申请人： Aptima, Inc.
CPC分类号： H04L41/12 , G06Q50/01 , H04L41/14 , H04L41/142
摘要： Example embodiments of systems and methods for network pattern matching provide the ability to match hidden networks from noisy data sources using probabilistic matching analysis. The algorithms may map roles and patterns to observed entities. The outcome is a set of plausible network models. The pattern-matching methodology of these systems and methods may enable the solution of three challenges associated with social network analysis, namely network size and complexity, uncertain and incomplete data, and dynamic network structure.
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公开(公告)号：US11651285B1
公开(公告)日：2023-05-16
申请号：US17067895
申请日：2020-10-12
申请人： Aptima, Inc.
发明人： Georgiy Levchuk , Nathan Schurr , Darby Hering , Mitch Zakin
IPC分类号： G06N20/00 , H04B17/391 , G06F1/3203 , G06F1/3206 , G06F1/3228 , H04W52/22
CPC分类号： G06N20/00 , G06F1/3203 , G06F1/3206 , G06F1/3228 , H04B17/391 , H04W52/223
摘要： Methods to infer user behavior are disclosed comprising a process of predefining one or more activities for a user application, providing a processor based device and user interface configured to operate with the device to support the user with tasks using the user application, the user application communicating an intent message to a transformative power management (TPM) application and the TPM configured to define and output an instruction for the application given the intention and the predefined activities. In some embodiments, the methods are implemented on a processor based device. In some embodiments, the systems and methods apply pattern recognition algorithms and pattern learning algorithms to manage the power allocation to power consuming devices.
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公开(公告)号：US20140195475A1
公开(公告)日：2014-07-10
申请号：US14143410
申请日：2013-12-30
发明人： Georgiy Levchuk , Jared Freeman , Wayne Shebilske
IPC分类号： G06N7/00
摘要： Embodiments of this invention comprise modeling a subject's state and the influence of training treatments, or actions, on that state to create a training policy. Both state and effects of actions are modeled as probabilistic using Partially Observable Markov Decision Process (POMDP) techniques. Utilizing this model and the resulting training policy with subjects creates an effective decision aid for instructors to improve learning relative to a traditional scenario selection strategy.
摘要翻译： 本发明的实施例包括对受试者的状态进行建模，以及训练治疗或动作对该状态的影响以创建训练策略。 动态的状态和效果都使用部分可观测马尔可夫决策过程（POMDP）技术进行建模。 利用这一模式和由此产生的培训策略为教师创造了有效的决策辅助，以提高相对于传统场景选择策略的学习。
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公开(公告)号：US09965725B1
公开(公告)日：2018-05-08
申请号：US14557435
申请日：2014-12-01
申请人： Aptima, Inc.
发明人： Georgiy Levchuk , Nathan Schurr , Darby Hering , Mitch Zakin
CPC分类号： G06N99/005 , G06F1/3203 , G06F1/3206 , G06F1/3228 , H04B17/391 , H04W52/223
摘要： A method for power management comprising inferring a user behavior from an action, inferring a mission state from the action and an event, forecasting a forecasted action from the user behavior and the mission state and outputting an instruction to modify a power resource allocation based on the forecasted action. A processor based assembly for power management of at least one device comprising a means to infer a user behavior from an action, a means to infer a mission state from the action and an event, a means to forecast and a means to plan power management from the inferred information. In some embodiments, the systems and methods apply pattern recognition algorithms and pattern learning algorithms to manage the power allocation to power consuming devices.
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公开(公告)号：US20210142200A1
公开(公告)日：2021-05-13
申请号：US17101184
申请日：2020-11-23
发明人： Georgiy Levchuk , Jared Freeman , Wayne Shebilske
摘要： Embodiments of this invention comprise modeling a team's state and the influence of training treatments, or actions, on that state to create a training policy. Both state and effects of actions are modeled as probabilistic using Partially Observable Markov Decision Process (POMDP) techniques. Utilizing this model and the resulting training policy with teams creates an effective decision aid for instructors to improve learning relative to a traditional scenario selection strategy.
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公开(公告)号：US09917739B2
公开(公告)日：2018-03-13
申请号：US14379503
申请日：2012-12-31
申请人： Aptima, Inc.
CPC分类号： H04L41/12 , G06Q50/01 , H04L41/14 , H04L41/142
摘要： Example embodiments of systems and methods for network pattern matching provide the ability to match hidden networks from noisy data sources using probabilistic multi-attribute graph matching analysis. The algorithms may map roles and patterns to observed entities. The outcome is a set of plausible network models. The pattern-matching methodology of these systems and methods may enable the solution of three challenges associated with social network analysis, namely network size and complexity, uncertain and incomplete data, and dynamic network structure.
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公开(公告)号：US20150049634A1
公开(公告)日：2015-02-19
申请号：US14379503
申请日：2012-12-31
申请人： Aptima, Inc.
IPC分类号： H04L12/24
CPC分类号： H04L41/12 , G06Q50/01 , H04L41/14 , H04L41/142
摘要： Example embodiments of systems and methods for network pattern matching provide the ability to match hidden networks from noisy data sources using probabilistic multi-attribute graph matching analysis. The algorithms may map roles and patterns to observed entities. The outcome is a set of plausible network models. The pattern-matching methodology of these systems and methods may enable the solution of three challenges associated with social network analysis, namely network size and complexity, uncertain and incomplete data, and dynamic network structure.
摘要翻译： 用于网络模式匹配的系统和方法的示例实施例提供使用概率多属性图匹配分析来匹配来自噪声数据源的隐藏网络的能力。 算法可以将角色和模式映射到观察到的实体。 结果是一组合理的网络模型。 这些系统和方法的模式匹配方法可以使解决与社会网络分析相关的三个挑战，即网络规模和复杂性，不确定和不完整的数据以及动态网络结构。
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公开(公告)号：US11627048B2
公开(公告)日：2023-04-11
申请号：US15899607
申请日：2018-02-20
申请人： Aptima, Inc.
IPC分类号： H04L12/24 , H04L41/12 , G06Q50/00 , H04L41/14 , H04L41/142
摘要： Example embodiments of systems and methods for network pattern matching provide the ability to match hidden networks from noisy data sources using probabilistic matching analysis. The algorithms may map roles and patterns to observed entities. The outcome is a set of plausible network models. The pattern-matching methodology of these systems and methods may enable the solution of three challenges associated with social network analysis, namely network size and complexity, uncertain and incomplete data, and dynamic network structure.
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公开(公告)号：US10803405B1
公开(公告)日：2020-10-13
申请号：US15952305
申请日：2018-04-13
申请人： Aptima, Inc.
发明人： Georgiy Levchuk , Nathan Schurr , Darby Hering , Mitch Zakin
IPC分类号： G06F1/26 , G06N20/00 , G06F1/3203
摘要： Methods for power management are disclosed comprising a process of predefining one or more power mode for a user application, providing a processor based device and user interface configured to operate with the device to support the user with tasks using the user application, the user application communicating an intent message to a transformative power management (TPM) application and the TPM configured to define and output a power mode instruction for the application given the intention and the predefined power modes. In some embodiments, the methods are implemented on a processor based device. In some embodiments, the systems and methods apply pattern recognition algorithms and pattern learning algorithms to manage the power allocation to power consuming devices.
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