General Electric Company

Genworth Financial, Inc.

Lockheed Martin Corporation

Other

Electric Power Research Institute Incorporated

Martin Marietta Corporation

Genworth Holdings, Inc.

Piero Patrone Bonissone

Yu-To Chen

Naresh Sundaram Iyer

Rajesh Venkat Subbu

Weizhong Yan

Neil Holger White Eklund

Anil Varma

Richard Paul Messmer

John Erik Hershey

Kai F Goebel

Rasiklal Punjalal Shah

Feng Xue

Mark Edward Dausch

Kareem Sherif Aggour

Srinivas Bollapragada

Kete Chalermkraivuth

Xiao Liang Hu

Avinash Vinayak Taware

Peter Henry Tu

Christopher Donald Johnson

Vivek Venugopal Badami

Dashan Gao

Paul Kenneth Houpt

John Michael Lizzi

Kunter Seref Akbay

Ting Yu

Kedar Anil Patwardhan

Corey Nicholas Bufi

Yi Yao

Robert J Mitchell, Jr

James Kenneth Aragones

John L Schneiter

Charles Erklin Seeley

Walter Whipple

Michael Joseph Schutten

Robert P Alley

Robert Frank Hoskin

Pratap Shankar Khedkar

Marc Pavese

Dan Yang

William Estel Cheetham

Viswanath Avasarala

Phillip Edward Steen

Vipin Kewal Ramani

Diane Marie Russell

John Andrew Johnson

Angela Patterson

William Michael Durham

Anindya Chakraborty

Ramesh Ramachandran

Antonio A Mogro-Campero

James Baldwin Comly

Kenneth H-c Chiang

Charles Terrance Hatch

Hai Qiu

James Joseph Schmid

Vrinda Rajiv

Neil Colin Widmer

Mahesh Kumar Asati

Johan Michael Reimann

Mark David Osborn

Matthew Allen Nelson

Gianni Mochi

Richard J Mitchell

Lincoln Mamoru Fujita

Noemie Dion Ouellet

Chad Eric Knodle

Joseph M Weiss

Michael Craig Clark

Neil H Eklund

Bernard J Carey

Paul Alex Ardis

Lise M Pfau

Kenneth A Marcelle

Kenneth Hsin-Chao Chiang

David Bianucci

Varma Anil

Lorenzo Salusti

Alessio Fabbri

Alberto Pieri

David Clarence Golibersuch

Ramesh Ramchandran

Seref Akbay Kunter

John Michael Jr Lizzi

Kai Frank Goebel

The system and method disclosed herein provides an integrated and automated workflow, sensor, and reasoning system that automatically detects breaches in protocols, appropriately alarms and records these breaches, facilitates staff adoption of protocol adherence, and ultimately enables the study of protocols for care comparative effectiveness. The system provides real-time alerts to medical personnel in the actual processes of care, thereby reducing the number of negative patient events and ultimately improving staff behavior with respect to protocol adherence.

System and method for protocol adherence

A method, system, and non-transitory computer-readable medium, the method including determining automatically, by a processor, whether behavior for a model representing a plurality of entities and relationships therebetween deviates from a reference behavior for the model; determining, in response to the determination that the model does deviate from the reference behavior, at least one basis for the deviation; automatically forecasting an estimate of a remaining useful life for the model; and modifying the model to compensate for the deviation by at least one of modifying the model to accommodate the deviation and updating the model based on at least one new requirement.

Method and system to automate the maintenance of data-driven analytic models

Method, system and computer software for diagnosing a compressor. The method includes generating a feature vector of the compressor, the feature vector of the compressor including components describing states of various parts of the compressor; determining, based on fuzzy constraints, an aggregated anomaly vector corresponding to the feature vector; defining rules for a preset list of possible faults/failure modes of the compressor; calculating a corroborating measure between the aggregated anomaly vector and the rules; and identifying a fault/failure mode of the compressor based on a result of the corroborating measure.

Method and system for diagnosing compressors

A method for determining fleet conditions and operational management thereof, performed by a central system includes receiving fleet data from at least one distributed data repository. The fleet data is substantially representative of information associated with a fleet of physical assets. The method also includes processing the received fleet data for the fleet using at least one process of a plurality of processes. The plurality of processes assess the received fleet data into processed fleet data. The method additionally includes determining a fleet condition status using the processed fleet data and the at least one process of the plurality of processes. The method further includes generating a fleet response. The fleet response is substantially representative of a next operational step for the fleet of physical assets. The method also includes transmitting the fleet response to at least one of a plurality of fleet response recipients.

Computer-implemented methods and systems for determining fleet conditions and operational management thereof

A system for at least a partial underwriting of insurance policies is described. Various rules are created, along with a degree of satisfaction for each rule. Rules may be directed toward various insurance underwriting components (e.g., cholesterol levels, blood pressure, etc.). Based on the degree of satisfaction for each rule, a component may be assigned to a category. Based on the category for each component, the insurance application may be assigned an underwriting category.

System for rule-based insurance underwriting suitable for use by an automated system

A semi-automated method for interactively analyzing a patent landscape in one embodiment includes retrieving a plurality of relevant patents indicative of a predetermined conceptual region of the patent landscape from a patent repository using a query. Competitive analysis of the plurality of relevant patents is conducted using an interactive network-based visualization technique. The competitive analysis is used for intellectual property enforcement, due diligence, and strategic investment analysis.

Semi-automated and inter-active system and method for analyzing patent landscapes

A method for advanced condition monitoring of an asset system includes sensing actual values of an operating condition for an operating regime of the asset system using at least one sensor; estimating sensed values of the operating condition by using an auto-associative neural network; determining a residual vector between the estimated sensed values and the actual values; and performing a fault diagnostic on the residual vector. In another method, an operating space of the asset system is segmented into operating regimes; the auto-associative neural network determines estimates of actual measured values; a residual vector is determined from the auto-associative neural network; a fault diagnostic is performed on the residual vector; and a change of the operation of the asset system is determined by analysis of the residual vector. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

System and method for advanced condition monitoring of an asset system

The systems and methods of the invention are directed to portfolio optimization and related techniques. For example, the invention provides a method for multi-objective portfolio optimization for use in investment decisions based on competing objectives and a plurality of constraints constituting a portfolio problem, the method comprising: generating an initial population of solutions of portfolio allocations; committing the initial population of solutions to an initial population archive; performing a multi-objective process, based on the initial population archive and on multiple competing objectives, to generate an efficient frontier, the multi-objective process including a evolutionary algorithm process, the evolutionary algorithm process utilizing a dominance filter, the efficient frontier being used in investment decisioning.

Systems and methods for multi-objective portfolio analysis using pareto sorting evolutionary algorithms

A method and system for fusing a collection of classifiers used for an automated insurance underwriting system and/or its quality assurance is described. Specifically, the outputs of a collection of classifiers are fused. The fusion of the data will typically result in some amount of consensus and some amount of conflict among the classifiers. The consensus will be measured and used to estimate a degree of confidence in the fused decisions. Based on the decision and degree of confidence of the fusion and the decision and degree of confidence of the production decision engine, a comparison module may then be used to identify cases for audit, cases for augmenting the training/test sets for re-tuning production decision engine, cases for review, or may simply trigger a record of its occurrence for tracking purposes. The fusion can compensate for the potential correlation among the classifiers. The reliability of each classifier can be represented by a static or dynamic discounting factor, which will reflect the expected accuracy of the classifier. A static discounting factor is used to represent a prior expectation about the classifier's reliability, e.g., it might be based on the average past accuracy of the model, while a dynamic discounting is used to represent a conditional assessment of the classifier's reliability, e.g., whenever a classifier bases its output on an insufficient number of points it is not reliable.

System and process for a fusion classification for insurance underwriting suitable for use by an automated system

A method for advanced condition monitoring of an asset system includes monitoring a variable of an asset system using the at least one sensor of a smart sensor system; determining whether the asset system has departed from normal operation; and identifying the variable of the asset system indicating the departure from normal operation. In another method, the time sequential values of the monitored variable is analyzed by using a Rank Permutation Transformation test, a Hotelling's Tstatistic test, and a Likelihood Ratio Test; and a change of an operating condition of the asset system is determined using the analyzed values. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

The systems and methods of the invention are directed to portfolio optimization and related techniques. For example, the invention provides a method for multi-objective portfolio optimization for use in investment decisions based on competing objectives and a plurality of constraints constituting a portfolio problem, the method comprising: generating an initial population of solutions of portfolio allocations, the generating the initial population of solutions of portfolio allocations including systematically generating the initial population of solutions to substantially cover the space defined by the competing objectives and the plurality of constraints; and generating an efficient frontier in the space based on the initial population, the efficient frontier for use in investment decisioning.

Systems and methods for initial sampling in multi-objective portfolio analysis

A process is described for evaluating the decision-making confidence of a process and system for at least a partial underwriting of insurance policies where placement of an insurance application to an underwriting category is based on its similarity to previous insurance applications. The confidence factor computed is a measure of the correctness of the decision for a given application for insurance.

Process for determining a confidence factor for insurance underwriting suitable for use by an automated system

A method and system for creating healthy operating envelope from only data samples obtained during normal operation/behavior of dynamic systems is provided. This method determines healthy operating envelope by clustering a stream of discrete event code sequences from the underlying system under normal operation condition only. The method is unsupervised, that is, requiring no prior knowledge of event code patterns corresponding to different operation conditions. Such created envelope can be used for fault detection and health monitoring of dynamic systems.

Method and system of creating health operating envelope for dynamic systems by unsupervised learning of a sequence of discrete event codes

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Schenectady, NY, United States of America

Piero Patrone Bonissone