General Electric Company

Lockheed Martin Corporation

Daniel Joseph Cleary

LiJie Yu

Paul Edward Cuddihy

Steven Hector Azzaro

Timothy Lee Johnson

Jeffrey Michael Ashe

John Michael Lizzi

Rajesh Venkat Subbu

Tarik Yardibi

Louis John Hoebel

Mark David Osborn

Mark Richard Gilder

Gerald Bowden Wise

Virginia Ann Zingelewicz

Jonathan Dehn

Jeremiah Francis Donoghue

Bradley A Culbertson

Joseph Carl Shultz

Mark David Osborne

Liviu Nedelescu

Paul W Mettus

Methods and systems for monitoring a subject in a resting state using one or more range-controlled radars are presented. The radars non-invasively detect one or more motion and/or physiological parameters corresponding to the subject. The motion parameters comprise one or more activity levels and the physiological parameters comprise one or more of heartbeat and respiration. Further, one or more patterns in the motion parameters detected over a designated motion period of time are determined. Additionally, one or more patterns in the physiological parameters detected over the designated physiological period of time are also determined. The systems then assess a health condition of the subject based on the determined patterns of the motion parameters and/or the determined patterns of the physiological parameters.

Radar based systems and methods for monitoring a subject

A system for providing an optimal motivational response is provided. The system includes an input device configured to receive at least one client input from the client. The system further includes a processor configured to analyze the at least one client input received from the client and generate a current state of the client based on the at least one client input. The processor is further configured to analyze the current state of the client and determine an optimal motivational technique for the client based on the current state of the client and the at least one client input. The processor is also configured to generate an optimal motivational response based on the optimal motivational technique. The system further includes an output device configured to display the optimal motivational response to the client.

System and method for providing an optimal motivational response

A method for diagnosing faults in a particular device within a fleet of devices is provided. The method comprises receiving performance data related to one or more parameters associated with a fleet of devices and processing the performance data to detect one or more trend shifts in the one or more parameters. The method then comprises detrending the one or more parameters to derive noise-adjusted performance data related to a particular parameter associated with a particular device. The method further comprises generating a fleet-based diagnostic model based on trend patterns and data characteristics associated with the fleet of devices. The fleet-based diagnostic model comprises one or more fuzzy rules defining one or more expected trend shift data ranges for the one or more parameters associated with the fleet of devices. The method then comprises computing one or more scaling factors for the particular parameter associated with the particular device and scaling the one or more of fuzzy rules defined for the one or more parameters in the fleet-based diagnostic model, based on the one or more scaling factors, to generate a personalized diagnostic model for the particular parameter associated with the particular device. The method finally comprises evaluating the personalized diagnostic model against the one or more trend shifts detected for the one or more parameters, to diagnose a fault associated with the particular device.

Method and system for diagnosing faults in a particular device within a fleet of devices

Systems and methods for airspace demand prediction with improved sector level demand prediction are provided. In one embodiment, an air traffic demand prediction system () operable to predict demand within an airspace divided into sectors includes an expanded route predictor () operable to generate predicted two-dimensional expanded route information () associated with at least one requested flight (), a trajectory modeler () operable to generate predicted four-dimensional expanded route information (), a sector crossing predictor () operable to generate predicted sector crossing information (), a departure time predictor () operable to generate predicted departure time information (), and a demand modeler () operable to generate a demand model (), the demand model () including predicted time intervals associated with the at least one requested flight indicating when it is expected to be present within one or more sectors of the airspace.

Air traffic demand prediction

The present invention provides a computer implemented method for maintaining a knowledge base. The method taking as input, text examples that are tagged with a structural markup language; and maps knowledge nodes in the knowledge base with the tagged examples to determine: (1) the knowledge nodes that best match the tagged examples, and (2) the knowledge nodes that are best connected to the tagged examples. The results are displayed to the user, who verifies that the tagged examples match the selected knowledge nodes. Based on the user response, indices of the knowledge nodes are updated. The method may further include determining discrepancies between the existing knowledge base and the tagged examples, and further displaying the discrepancies to the user. The user can update the missing information in the knowledge base to remove the discrepancies in the existing knowledge base.

Process for semi-automatic maintenance of a knowledge base using tagged examples

A method for diagnosing and classifying faults in a system is provided. The method comprises acquiring operational data for at least one of a system, one or more subsystems of the system or one or more components of the one or more subsystems. Then, the method comprises analyzing the operational data using one or more diagnostic models. Each diagnostic model uses the operational data to determine a probability of fault associated with at least one of the one or more components or the one or more subsystems. Finally, the method comprises deriving an overall probability of fault for at least one of the system, the one or more subsystems, or the one or more components using the one or more probabilities of fault determined by the one or more diagnostic models and one or more hierarchical relationships between the subsystems and components of the system.

Method and system for hierarchical fault classification and diagnosis in large systems

A method of integrating case based reasoning data and FMECA data for product life cycle support. The method comprises creating an access path to case based data using a FMECA classification. The creating includes receiving a case based record including heading data. The heading data includes data elements and the data elements are correlated with data fields in a FMECA database. The FMECA database is searched for an entry that includes one or more of the data elements. The creating further includes determining if the entry should include a reference to the case based record. A new pointer to the case based record is inserted if the determining results in finding that the entry should include a reference to the case based record. The method for integrating case based reasoning data and FMECA data further comprises receiving a request from a user to access the case based data. The case based data is accessed via the FMECA database using the access path in response to the request.

Method, system and computer product for integrating case based reasoning data and failure modes, effects and corrective action data

Automated systems and methods for diagnosing the cause of a trend shift in performance data associated with a system including selecting a fuzzy model describing how the mean associated with a parameter shifts when a predetermined problem occurs and receiving performance data associated with the system. The diagnostic systems and methods also including applying a preferred set of piecewise regressions. The diagnostic systems and methods further including selecting a start date and selecting data sets near the start date and an end date that have a relatively large size without violating normal scatter. The diagnostic systems and methods still further including measuring the mean shift between a plurality of samples using one or more statistical tests and combining the results with the fuzzy model to achieve a diagnosis.

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Schenectady, NY, United States of America

Daniel Joseph Cleary