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Full-Text Articles in Engineering
Data Set: The Analysis Of Lava Flow Path Using Remote Sensing Techniques And Geomorphological Techniques: The Case Of Volcano Eruptions In Afar Region Of Ethiopia, Oluwatosin Ayo, Jae Sung Kim
Data Set: The Analysis Of Lava Flow Path Using Remote Sensing Techniques And Geomorphological Techniques: The Case Of Volcano Eruptions In Afar Region Of Ethiopia, Oluwatosin Ayo, Jae Sung Kim
Michigan Tech Research Data
Natural disasters pose significant threats to the environment and make land unsuitable for man. The lava from volcanic eruptions rapidly moves on the Earth surface and affects both natural and man-made features on the Earth. Remote sensing is relevant in extracting information about the areas affected by lava flows without physically visiting such areas. The objective of this study is to develop a workflow for determining the optimal ground sample distance of a digital elevation model to delineate the lava flow paths using object-based image analysis and geomorphologic analysis. For the experiment, the satellite images and digital elevation model of …
Intelligen Superpro Designer Files For Economic Simulation Of Batch And Continuous Aqueous Two-Phase Purification For Viral Products, Natalie Nold, Eric Pearson, Caryn L. Heldt
Intelligen Superpro Designer Files For Economic Simulation Of Batch And Continuous Aqueous Two-Phase Purification For Viral Products, Natalie Nold, Eric Pearson, Caryn L. Heldt
Michigan Tech Research Data
Vaccine manufacturing strategies that lower capital and production costs could improve vaccine access by reducing the cost per dose and encouraging localized manufacturing. Continuous processing is increasingly utilized to drive lower costs in biological manufacturing by requiring fewer capital and operating resources. Aqueous two-phase systems (ATPS) are a liquid-liquid extraction technique that enables continuous processing for viral vectors. To date, no economic comparison between viral vector purifications using traditional methods and ATPS has been published. In this work, economic simulations of traditional chromatography-based virus manufacturing were compared to simulations of ATPS-based virus manufacturing for the same product output in both …
Using Scratch Wound Assay To Study The Effect Of Soil Arsenic On Human Keratinocyte Cell Migration Due To Contact Exposure, Manas Warke, Laura De March, Srinivas Kannan, Madeline English, Rohan Sarkar, Rupali Datta, Smitha Rao
Using Scratch Wound Assay To Study The Effect Of Soil Arsenic On Human Keratinocyte Cell Migration Due To Contact Exposure, Manas Warke, Laura De March, Srinivas Kannan, Madeline English, Rohan Sarkar, Rupali Datta, Smitha Rao
Michigan Tech Research Data
The scratch wound assay was performed on Human immortalized keratinocytes (HaCaT) cells to observe the effect on cell migration due to contact exposure to arsenic-contaminated Immokalee soil. The cell migration was observed through a microscope for 72 h. HaCaT cells were seeded in 48-well plate. On day 3, treatment media was added (n=8). The cells were treated with four concentrations of soil As (45, 225, 450, and 900 mg/kg) and two controls - Negative control (NC; Pure media) and control (C; 0 mg/kg soil As) for 72 h. A scratch was made using a pipette tip. The wound healing was …
Using Scratch Wound Assay To Study The Effect Of Soil Arsenic On Human Dermal Fibroblasts Cell Migration Due To Contact Exposure, Manas Warke, Laura De Marchi, Srinivas Kannan, Madeline English, Rohan Sarkar, Rupali Datta, Smitha Rao
Using Scratch Wound Assay To Study The Effect Of Soil Arsenic On Human Dermal Fibroblasts Cell Migration Due To Contact Exposure, Manas Warke, Laura De Marchi, Srinivas Kannan, Madeline English, Rohan Sarkar, Rupali Datta, Smitha Rao
Michigan Tech Research Data
The scratch wound assay was performed on Normal Human Primary Dermal Fibroblasts (HDFa) cells to observe the effect on cell migration due to contact exposure to arsenic-contaminated Immokalee soil. The cell migration was observed through a microscope for 72 h. HDFa cells were seeded in 48-well plate. On day 3, treatment media was added (n=8). The cells were treated with four concentrations of soil As (45, 225, 450, and 900 mg/kg) and two controls - Negative control (NC; Pure media) and control (C; 0 mg/kg soil As) for 72 h. A scratch was made using a pipette tip. The wound …
The Winter Adverse Driving Dataset (Wads) - Sequence 30, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 30, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 15, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 15, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 13, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 13, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 28, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 28, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 17, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 17, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 26, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 26, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 20, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 20, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 34, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 34, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 35, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 35, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 23, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 23, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 24, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 24, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 16, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 16, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 11, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 11, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 18, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 18, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 22, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 22, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 12, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 12, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 76, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 76, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 36, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 36, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 14, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 14, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
The Winter Adverse Driving Dataset (Wads) - Sequence 37, Akhil Kurup, Jeremy Bos
The Winter Adverse Driving Dataset (Wads) - Sequence 37, Akhil Kurup, Jeremy Bos
Michigan Tech Research Data
Collected in the snow belt region of Michigan's Upper Peninsula, WADS is the first multi-modal dataset featuring dense point-wise labeled sequential LiDAR scans collected in severe winter weather. Over 26 TB of multi modal data has been collected of which over 7 GB of LiDAR point clouds (3.6 billion points) have been labeled (semanticKITTI format) and made available here. This outdoor dataset introduces falling snow and accumulated snow along with all the semanticKITTI classes. We believe this dataset will further AV tasks like semantic and panoptic segmentation, object detection and tracking, and localization and mapping in conditions of moderate to …
Supporting Materials From The Program "Development Of A Physically-Based Creep Model Incorporating Eta Phase Evolution For Nickel Base Superalloys", N. R. Mohale, C. L. White, P. G. Sanders, W. W. Milligan, J. P. Shingledecker, P. A. Bridges
Supporting Materials From The Program "Development Of A Physically-Based Creep Model Incorporating Eta Phase Evolution For Nickel Base Superalloys", N. R. Mohale, C. L. White, P. G. Sanders, W. W. Milligan, J. P. Shingledecker, P. A. Bridges
Michigan Tech Research Data
This research was funded by the US Department of Energy, Fossil Energy Program, Grant Number DE-FE0027822, with Omer Bakshi as the Program Manager. The grant conditions required that all supporting data and materials would be made publicly-available. This public repository was created on May 13, 2021.