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Full-Text Articles in Physical Sciences and Mathematics
Machine Learning - Hail Awareness Spatial Analysis Toolkit (Hasat), Haoruo Fu M.S., Joseph P. Hupy Ph.D., Chien-Tsung Lu Ph.D., Zhenglei Ji M.S.
Machine Learning - Hail Awareness Spatial Analysis Toolkit (Hasat), Haoruo Fu M.S., Joseph P. Hupy Ph.D., Chien-Tsung Lu Ph.D., Zhenglei Ji M.S.
Journal of Aviation/Aerospace Education & Research
The National Airspace System (NAS) is a sophisticated network of air traffic control, navigation, and communication systems that play a critical role in ensuring the safe and efficient flow of air traffic across the United States. However, the occurrence of severe weather conditions, particularly hailstorms, poses a significant threat to flight safety within the NAS. To mitigate the risks associated with hail, aviation organizations have implemented a range of safety measures. This study utilized Esri’s ArcGIS as a mapping software to conduct a geospatial analysis of the impact of severe weather, particularly hail, on the NAS. The Hail Awareness Spatial …
Wearable Sensor-Based Walkability Assessment At Ferry Terminal Using Machine Learning: A Case Study Of Mokpo, Korea, Jungyeon Choi, Hwayoung Kim
Wearable Sensor-Based Walkability Assessment At Ferry Terminal Using Machine Learning: A Case Study Of Mokpo, Korea, Jungyeon Choi, Hwayoung Kim
Journal of Marine Science and Technology
Walkability assessments are becoming more popular, as walking offers numerous health, environmental, and economic benefits to communities. However, previous studies on ferry terminal walkability assessment have been inadequate. This study aimed to develop a wearable sensor system to automatically assess walkability at ferry terminals without conducting surveys. We applied seven machine learning (ML) classifiers to detect different walking environments, including flat ground (FG), downhill slope (DS), uphill slope (US), and uneven surface (UE). The ML models were evaluated across different combinations of classes: 2-class (FG vs. UE), 3-class (U) (FG vs. US vs. UE), 3-class (D) (FG vs. DS vs. …
Atmospheric Contrail Detection With A Deep Learning Algorithm, Nasir Siddiqui
Atmospheric Contrail Detection With A Deep Learning Algorithm, Nasir Siddiqui
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
Aircraft contrail emission is widely believed to be a contributing factor to global climate change. We have used machine learning techniques on images containing contrails in hopes of being able to identify those which contain contrails and those that do not. The developed algorithm processes data on contrail characteristics as captured by long-term image records. Images collected by the United States Department of Energy’s Atmospheric Radiation Management user facility(ARM) were used to train a deep convolutional neural network for the purpose of this contrail classification. The neural network model was trained with 1600 images taken by the Total Sky Imager(TSI) …