Battelle Memorial Institute

Amir Rahimi

Katie Liszewski

Jeremy Bellay

Nicholas Darby

Anthony George

Douglas Mooney

Laura Aume

David Collins

Joe Regensburger

Joe Cochran

Joe Regensbuger

A method implemented by a software for a multimodal evaluation engine stored on a memory is provided herein. The software is executable by a processor coupled to the memory to cause the method. The method includes receiving multimodal signatures of an object of interest from inspection elements and processing the multimodal signatures to transform the multimodal signatures into formats. The method also includes generating data representations of the formats and detecting whether anomalies are present within the object of interest based on the data representations.

Data handling and machine learning

A method for evaluating system performance can include comparing a test average of instances of variables of test system variables to a baseline average of a baseline variables. Each of the instances of the variable of the test system variables may be shifted by a shift amount for a subset of the variables. A modified test data set may be generated from the shifted test data set. The modified test data set may be transformed with a sparse principal component analysis into test components. The test components may be compared to baseline components using a Hotelling Tas a test statistic. Performance of the system may be quantified based upon the test statistic.

Evaluating system performance with sparse principal component analysis and a test statistic

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Powell, OH, United States of America

Amir Rahimi