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Full-Text Articles in Poultry or Avian Science
Functional Morphology Of Gliding Flight Ii. Morphology Follows Predictions Of Gliding Performance, Jonathan Rader, Tyson L. Hedrick, Yanyan He, Lindsay D. Waldrop
Functional Morphology Of Gliding Flight Ii. Morphology Follows Predictions Of Gliding Performance, Jonathan Rader, Tyson L. Hedrick, Yanyan He, Lindsay D. Waldrop
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
The evolution of wing morphology among birds, and its functional consequences, remains an open question, despite much attention. This is in part because the connection between form and function is difficult to test directly. To address this deficit, in prior work we used computational modeling and sensitivity analysis to interrogate the impact of altering wing aspect ratio, camber, and Reynolds number on aerodynamic performance, revealing the performance landscapes that avian evolution has explored. In the present work, we used a dataset of three-dimensionally scanned bird wings coupled with the performance landscapes to test two hypotheses regarding the evolutionary diversification of …
Functional Morphology Of Gliding Flight I. Modeling Reveals Distinct Performance Landscapes Based On Soaring Strategies, Lindsay D. Waldrop, Yanyan He, Tyson L. Hedrick, Jonathan Rader
Functional Morphology Of Gliding Flight I. Modeling Reveals Distinct Performance Landscapes Based On Soaring Strategies, Lindsay D. Waldrop, Yanyan He, Tyson L. Hedrick, Jonathan Rader
Biology, Chemistry, and Environmental Sciences Faculty Articles and Research
The physics of flight influences the morphology of bird wings through natural selection on flight performance. The connection between wing morphology and performance is unclear due to the complex relationships between various parameters of flight. In order to better understand this connection, we present a holistic analysis of gliding flight that preserves complex relationships between parameters. We use a computational model of gliding flight, along with analysis by uncertainty quantification, to 1) create performance landscapes of gliding based on output metrics (maximum lift-to-drag ratio, minimum gliding angle, minimum sinking speed, lift coefficient at minimum sinking speed); and 2) predict what …
Artificial Intelligence And Covid-19: Deep Learning Approaches For Diagnosis And Treatment, M. B. Jamshidi, A. Lalbakhsh, J. Talla, Z. Peroutka, F. Hadjilooei, P Lalbakhsh, M. Jamshidi, L. La Spada, M. Mirmozafari, M. Dehghani, A. Sabet, Sa. Roshani, So. Roshani, N. Bayat-Makou, B. Mohamadzade, Z. Malek, A. Jamshidi, S. Kiani, H. Hashemi-Dezaki, W. Mohyuddin
Artificial Intelligence And Covid-19: Deep Learning Approaches For Diagnosis And Treatment, M. B. Jamshidi, A. Lalbakhsh, J. Talla, Z. Peroutka, F. Hadjilooei, P Lalbakhsh, M. Jamshidi, L. La Spada, M. Mirmozafari, M. Dehghani, A. Sabet, Sa. Roshani, So. Roshani, N. Bayat-Makou, B. Mohamadzade, Z. Malek, A. Jamshidi, S. Kiani, H. Hashemi-Dezaki, W. Mohyuddin
Faculty Publications
COVID-19 outbreak has put the whole world in an unprecedented difficult situation bringing life around the world to a frightening halt and claiming thousands of lives. Due to COVID-19 & x2019;s spread in 212 countries and territories and increasing numbers of infected cases and death tolls mounting to 5,212,172 and 334,915 (as of May 22 2020), it remains a real threat to the public health system. This paper renders a response to combat the virus through Artificial Intelligence (AI). Some Deep Learning (DL) methods have been illustrated to reach this goal, including Generative Adversarial Networks (GANs), Extreme Learning Machine (ELM), …