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Anand K. Gramopadhye
Researcher at Clemson University
Publications - 175
Citations - 3456
Anand K. Gramopadhye is an academic researcher from Clemson University. The author has contributed to research in topics: Visual inspection & Aircraft maintenance. The author has an hindex of 26, co-authored 174 publications receiving 2862 citations. Previous affiliations of Anand K. Gramopadhye include University at Buffalo & University College of Engineering.
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Journal ArticleDOI
Healthcare information on YouTube: A systematic review
TL;DR: The need to design interventions to enable consumers to critically assimilate the information posted on YouTube with more authoritative information sources to make effective healthcare decisions is recognized.
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Using virtual reality technology for aircraft visual inspection training: presence and comparison studies.
Jeenal Vora,Santosh Nair,Anand K. Gramopadhye,Andrew T. Duchowski,Brian J. Melloy,Barbara G. Kanki +5 more
TL;DR: A significant goal of this project was to explore subjective presence as it affects task performance and it indicated that the VR system scored high on the issues related to the degree of presence felt by subjects in a virtual environment simulator.
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A survey of automation-enabled human-in-the-loop systems for infrastructure visual inspection
TL;DR: In this article, the authors reviewed peer-reviewed research publications investigating automated visual inspection technologies following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.
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Assessment of the Human Factors Analysis and Classification System (HFACS): intra-rater and inter-rater reliability
Awatef Ergai,Tara N. Cohen,Julia L. Sharp,Douglas A. Wiegmann,Anand K. Gramopadhye,Scott A. Shappell +5 more
TL;DR: In this paper, the authors examined the inter- and intra-rater reliability of the Human Factors Analysis and Classification System (HFACS) data classification process and revealed additional opportunities for improving HFACS training and implementation.
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Musculoskeletal computational analysis of the influence of car-seat design/adjustments on long-distance driving fatigue
TL;DR: In this article, the main causes of long-distance driving fatigue experienced by vehicle drivers are investigated computationally using musculoskeletal modeling and simulation methods, and a rigid-body model of a prototypical adjustable car seat is constructed as a part of the present work.