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Lyle N. Long

Affiliations: 
Pennsylvania State University, State College, PA, United States 
Area:
Aerospace Engineering, Robotics Engineering, Artificial Intelligence
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"Lyle Long"
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Parents

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Children

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Frederic J. Souliez grad student 2002 Penn State
Anupam Sharma grad student 2004 Penn State
Emre Alpman grad student 2006 Penn State
Nilay Sezer-Uzol grad student 2006 Penn State
Scott D. Hanford grad student 2011 Penn State
Gregory Sinsley grad student 2012 Penn State

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Publications

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Skocik MJ, Long LN. (2014) On the capabilities and computational costs of neuron models. Ieee Transactions On Neural Networks and Learning Systems. 25: 1474-83
Hanford SD, Long LN. (2014) Development of a mobile robot system based on the soar cognitive architecture Journal of Aerospace Information Systems. 11: 714-725
Hill MJ, Kunz RF, Medvitz RB, et al. (2011) CFD analysis of gear windage losses: Validation and parametric aerodynamic studies Journal of Fluids Engineering, Transactions of the Asme. 133
Long LN, Kelley TD. (2010) Review of consciousness and the possibility of conscious robots Journal of Aerospace Computing, Information and Communication. 7: 68-84
Long LN, Hanford SD, Janrathitikarn O. (2010) Cognitive robotics using vision and mapping systems with Soar Proceedings of Spie - the International Society For Optical Engineering. 7710
Hanford SD, Long LN. (2010) Integration of maps into the cognitive robotic system Aiaa Infotech At Aerospace 2010
Hanford AD, Long LN. (2009) The direct simulation of acoustics on Earth, Mars, and Titan. The Journal of the Acoustical Society of America. 125: 640-50
Hanford SD, Janrathitikarn O, Long LN. (2009) Control of mobile robots using the soar cognitive architecture Journal of Aerospace Computing, Information and Communication. 6: 69-71
Alpman E, Long LN. (2009) An unstructured grid reynolds stress model for separated turbulent flow simulations International Journal of Computational Fluid Dynamics. 23: 377-389
Hanford AD, O'Connor PD, Anderson JB, et al. (2008) Predicting absorption and dispersion in acoustics by direct simulation Monte Carlo: Quantum and classical models for molecular relaxation. The Journal of the Acoustical Society of America. 123: 4118-26
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