Patents Assigned to Aptima, Inc
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Patent number: 8407026Abstract: Embodiments of methods and systems are described that provide methods for quantifying an entity's reaction to one or more communication signals by quantifying a probabilistic relationship between the communication signal and a known relationship of an attribute to the communication signal. With this quantification, the entity's reaction can be modeled as probability distributions that can be compared to the communication signal and known relationship. With this information, an entity's reactions can be compared to an ideal algorithm that optimally integrates the known relationships and communication signals to arrive at an optimal reaction. By making this comparison between the entity's reaction and an optimal reaction, a quantitative calibration measure can be determined. The meaning of the communication signals, or relationships to an attribute, may or may not be known and in embodiments the quantification of reactions can provide an ability to estimate an unknown attribute from the communication signals.Type: GrantFiled: November 29, 2010Date of Patent: March 26, 2013Assignee: Aptima, Inc.Inventor: Erik J. Schlicht
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Publication number: 20120208152Abstract: Systems and methods to define a scenario of conditions comprising the steps of defining at least one condition for at least one educational objective, the at least one condition being represented by a constraint and scheduling the conditions into a scenario of conditions. In some embodiments, the scheduling is performed by analyzing the constraints using constraint programming. In some embodiments, the constraints comprise mathematical or computational constraints representing a range of variables. Also disclosed are systems and methods to monitor a scenario of conditions.Type: ApplicationFiled: November 4, 2010Publication date: August 16, 2012Applicant: APTIMA, INC.Inventors: E. Webb Stacy, John Colonna-Romano
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Patent number: 8180777Abstract: The present invention relates in general to methods and systems for comparing and maximizing the optimal selection of a first set of one or more data objects to a set of second data objects. In one embodiment, the first set of data objects represent one or more tasks to be fulfilled by a set of capabilities represented by the second data objects. In one embodiment, methods and systems are provided that apply topic modeling and similarity metrics to determine the optimal selection. In one embodiment, methods and systems are provided to determine the appropriateness of a set of second data objects to satisfy the requirements of a first data object given interaction attributes. Embodiments may be used to compare mission requirements with potential team members to determine the appropriateness of team members and teams for a given mission based on interaction attributes of the team members and teams.Type: GrantFiled: October 24, 2010Date of Patent: May 15, 2012Assignee: Aptima, Inc.Inventors: Andrew Duchon, Kari Kelton, Pacey Foster, Kara Orvis, Robert McCormack
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Publication number: 20120116987Abstract: A method for modeling a process comprising receiving a first formatted data input representing a process element and a second formatted data input representing a process element, executing a simulation and determining a measure representing the simulation of the process element given the entity element. In some embodiments, the process element represents a business process and the entity element represents a resource unit and the simulation comprises a temporal simulation. Some embodiments further comprise the measure being a completeness measure associated with a decay rate or a repair rate. Some embodiments also include the measure comprising an information product completeness measure. Some embodiments also include automatically determining the process element and the entity element. Systems, to include processor based embodiments having a computer program product to perform the methods are also disclosed.Type: ApplicationFiled: July 16, 2010Publication date: May 10, 2012Applicant: APTIMA, INC.Inventors: Darby E. Hering, Charles Kapopoulos, Mark Weston, Jared Freeman
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Publication number: 20110276310Abstract: Embodiments of methods and systems are described that provide methods for quantifying an entity's reaction to one or more communication signals by quantifying a probabilistic relationship between the communication signal and a known relationship of an attribute to the communication signal. With this quantification, the entity's reaction can be modeled as probability distributions that can be compared to the communication signal and known relationship. With this information, an entity's reactions can be compared to an ideal algorithm that optimally integrates the known relationships and communication signals to arrive at an optimal reaction. By making this comparison between the entity's reaction and an optimal reaction, a quantitative calibration measure can be determined. The meaning of the communication signals, or relationships to an attribute, may or may not be known and in embodiments the quantification of reactions can provide an ability to estimate an unknown attribute from the communication signals.Type: ApplicationFiled: November 29, 2010Publication date: November 10, 2011Applicant: Aptima, Inc.Inventor: Erik J. SCHLICHT
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Publication number: 20110231349Abstract: A processor based system and method of generating cognitive pattern knowledge of a sensory input is disclosed. The method comprising the steps of receiving sensory input to create at least one concrete pattern, receiving at least one abstract pattern comprising abstract segments and vertically blending the concrete pattern with the abstract pattern by selectively projecting abstract segments to create a vertically blended pattern whereby the vertically blended pattern represents cognitive pattern knowledge of the sensory input. In some embodiments, the systems and methods further comprise creating a measure of a degree of vertical blending and when the measure of the degree of vertical blending exceeds a threshold, horizontally blending at least two abstract patterns to create a horizontally blended abstract pattern.Type: ApplicationFiled: March 21, 2011Publication date: September 22, 2011Applicant: Aptima, Inc.Inventors: E. Webb Stacy, Alexandra Geyer
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Publication number: 20110072052Abstract: Embodiments of the subject invention comprise a computer based system and methods to collect and compare the attributes of a group of entities using data representing topic data of the entity and interaction data between entities. Embodiments of the invention comprise using minimally invasive means to automatically collect and model both an entity's attributes such as their knowledge/work/interest as well as model the social interactions of the entity together with a means to identify opportunities to influence changes in the entity attributes. Minimally invasive means to collect and model attributes include semantic analysis and topic modeling techniques. Means to model social interactions include social network analysis techniques that can incorporate location data of the entity. Embodiments of the invention further provide a sharable index of the attributes of the entities and the group of entities.Type: ApplicationFiled: May 27, 2009Publication date: March 24, 2011Applicant: Aptima Inc.Inventors: Bruce Skarin, Andrew Duchon, Paul Allopenna, Rich Dejordy
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Publication number: 20110040764Abstract: The present invention relates in general to methods and systems for comparing and maximizing the optimal selection of a first set of one or more data objects to a set of second data objects. In one embodiment, the first set of data objects represent one or more tasks to be fulfilled by a set of capabilities represented by the second data objects. In one embodiment, methods and systems are provided that apply topic modeling and similarity metrics to determine the optimal selection. In one embodiment, methods and systems are provided to determine the appropriateness of a set of second data objects to satisfy the requirements of a first data object given interaction attributes. Embodiments may be used to compare mission requirements with potential team members to determine the appropriateness of team members and teams for a given mission based on interaction attributes of the team members and teams.Type: ApplicationFiled: October 24, 2010Publication date: February 17, 2011Applicant: Aptima, Inc.Inventors: Andrew DUCHON, Robert McCormack, Kari Kelton, Pacey Foster, Kara Orvis
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Publication number: 20110016067Abstract: Embodiments of this invention comprise modeling a subject's state and the influence of training scenarios, 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. The POMDP is well suited to decision-theoretic planning under uncertainty. Utilizing this model and the resulting training policy with real world subjects creates a surprisingly effective decision aid for instructors to improve learning relative to a traditional scenario selection strategy. POMDP provides a more valid representation of trainee state and training effects, thus it is capable of producing more valid recommendations concerning how to structure training to subjects.Type: ApplicationFiled: March 11, 2009Publication date: January 20, 2011Applicants: APTIMA, INC., WRIGHT STATE UNIVERSITYInventors: Georgiy Levchuk, Jared Freeman, Wayne Sheblinski
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Publication number: 20100280985Abstract: The present invention relate to a method and system to predict the likelihood of data topics that may occur from data sources. The likelihood of the data topics may be predicted over other dimensions of time or over other dimensions. In the present invention, a topic means a defining characteristic, usually represented as a data element, of a single feature, activity, subject, behavior, event or an aggregation of such defining characteristics.Type: ApplicationFiled: January 13, 2009Publication date: November 4, 2010Applicant: Aptima, Inc.Inventors: Andrew E. Duchon, Robert McCormack, William J. Salter, Paul David Allopenna, Shawn Weil, John Colonna-Romano, David Kramer
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Patent number: 7822750Abstract: The present invention relates in general to methods and systems for comparing and maximizing the appropriateness of a first set of one or more data objects to a set of second data objects. In one embodiment, the first set of data objects represent one or more tasks to be fulfilled by a set of capabilities represented by the second data objects. In one embodiment, this invention provides an effective and accurate method and system to compare and maximize the appropriateness between the requirements of a task and the second set's capabilities, while these capabilities and requirements are contained, even if only latently, in data objects such as written documents, electronic databases or other sources of data and information. In one embodiment, topic modeling techniques are utilized to compare the data objects.Type: GrantFiled: January 15, 2008Date of Patent: October 26, 2010Assignee: Aptima, IncInventors: Andrew Duchon, Kari Kelton, Pacey Foster, Kara Orvis
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Publication number: 20090192964Abstract: Embodiments of the disclosed systems and methods establish quantitative and accurate relationships between system features and system objectives. In one embodiment, the systems and methods are particularly suitable to establish the predictive relationships between system fidelity and training objectives. These systems and methods can combine fidelity values defined by end-users, existing theory and research, or objective performance data from experiments. The predictive relationships defined through these methods can feed a model-based decision support tool that helps predict the impact of fidelity on training effectiveness.Type: ApplicationFiled: October 3, 2008Publication date: July 30, 2009Applicant: APTIMA, INC.Inventors: Amy Alexander Horrey, Jamie Estock, Kathryn Engel, Robert Kenneth McCormack, Emily K. M. Stelzer
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Publication number: 20080250064Abstract: The present invention relates in general to methods and systems for comparing and maximizing the appropriateness of a first set of one or more data objects to a set of second data objects. In one embodiment, the first set of data objects represent one or more tasks to be fulfilled by a set of capabilities represented by the second data objects. In one embodiment, this invention provides an effective and accurate method and system to compare and maximize the appropriateness between the requirements of a task and the second set's capabilities, while these capabilities and requirements are contained, even if only latently, in data objects such as written documents, electronic databases or other sources of data and information. In one embodiment, topic modeling techniques are utilized to compare the data objects.Type: ApplicationFiled: January 15, 2008Publication date: October 9, 2008Applicant: APTIMA, INC.Inventors: Andrew Duchon, Kari Kelton, Pacey Foster, Kara Orvis