Zobrazeno 1 - 10
of 88
pro vyhledávání: '"John D. Hedengren"'
Autor:
Bryce E. Berrett, Cory A. Vernon, Haley Beckstrand, Madi Pollei, Kaleb Markert, Kevin W. Franke, John D. Hedengren
Publikováno v:
Drones, Vol 5, Iss 4, p 136 (2021)
Unmanned aerial vehicles (UAV) enable detailed historical preservation of large-scale infrastructure and contribute to cultural heritage preservation, improved maintenance, public relations, and development planning. Aerial and terrestrial photo data
Externí odkaz:
https://doaj.org/article/38404ab7ecbd4ae8a727cc1ed7b8f9d8
Publikováno v:
Algorithms, Vol 13, Iss 12, p 315 (2020)
Simple and easy to use methods are of great practical demand in the design of Proportional, Integral, and Derivative (PID) controllers. Controller design criteria are to achieve a good set-point tracking and disturbance rejection with minimal actuato
Externí odkaz:
https://doaj.org/article/ea1974ee43ae47f9b0206de589297aae
Autor:
Samuel Arce, Cory A. Vernon, Joshua Hammond, Valerie Newell, Joseph Janson, Kevin W. Franke, John D. Hedengren
Publikováno v:
Remote Sensing, Vol 12, Iss 13, p 2169 (2020)
Unsupervised machine learning algorithms (clustering, genetic, and principal component analysis) automate Unmanned Aerial Vehicle (UAV) missions as well as the creation and refinement of iterative 3D photogrammetric models with a next best view (NBV)
Externí odkaz:
https://doaj.org/article/e4fd7d2f894f4ca6a70513d9cdab2971
Autor:
Joshua E. Hammond, Cory A. Vernon, Trent J. Okeson, Benjamin J. Barrett, Samuel Arce, Valerie Newell, Joseph Janson, Kevin W. Franke, John D. Hedengren
Publikováno v:
Remote Sensing, Vol 12, Iss 14, p 2285 (2020)
Remote sensing with unmanned aerial vehicles (UAVs) facilitates photogrammetry for environmental and infrastructural monitoring. Models are created with less computational cost by reducing the number of photos required. Optimal camera locations for r
Externí odkaz:
https://doaj.org/article/d795f0e626304e5f98713999758ea495
Autor:
Trent J. Okeson, Benjamin J. Barrett, Samuel Arce, Cory A. Vernon, Kevin W. Franke, John D. Hedengren
Publikováno v:
Sensors, Vol 19, Iss 12, p 2703 (2019)
This study presents a novel multi-scale view-planning algorithm for automated targeted inspection using unmanned aircraft systems (UAS). In industrial inspection, it is important to collect the most relevant data to keep processing demands, both huma
Externí odkaz:
https://doaj.org/article/6c0db959ebb145db961297eac73d23a4
Publikováno v:
Remote Sensing, Vol 8, Iss 1, p 26 (2015)
This work demonstrates the use of genetic algorithms in optimized view planning for 3D reconstruction applications using small unmanned aerial vehicles (UAVs). The quality of UAV site models is currently highly dependent on manual pilot operations or
Externí odkaz:
https://doaj.org/article/8cbc1f7f70ca43a09ca1c68b54ad8545
Publikováno v:
Journal of Process Control. 120:129-149
Publikováno v:
Processes; Volume 11; Issue 1; Pages: 197
Transfer learning is a machine learning technique that takes a pre-trained model that has already been trained on a related task, and adapts it for use on a new, related task. This is particularly useful in the context of model predictive control (MP
Publikováno v:
International Journal of Hydrogen Energy. 46:31143-31157
In this study, a nuclear hybrid energy system (NHES) with large-scale hydrogen storage integrated with a gas turbine cycle is proposed as a flexible system for load following. The proposed system consists of a nuclear reactor, a steam Rankine cycle,
Publikováno v:
Journal of Energy Storage. 63:106943