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Articles 1 - 8 of 8
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Developing Unmanned Aerial Systems Skills Through A Creative Project, Jesse Giampaolo, James Jeffery Hines
Developing Unmanned Aerial Systems Skills Through A Creative Project, Jesse Giampaolo, James Jeffery Hines
The Journal of Purdue Undergraduate Research
No abstract provided.
Applying Clustering To Optimize Markovian Models In Human-Machine Interactions, Griffon Mcmahon
Applying Clustering To Optimize Markovian Models In Human-Machine Interactions, Griffon Mcmahon
The Journal of Purdue Undergraduate Research
No abstract provided.
Quantifying Changes In Muscle Force In The Presence Of Fatigue, Emily Bywater
Quantifying Changes In Muscle Force In The Presence Of Fatigue, Emily Bywater
The Journal of Purdue Undergraduate Research
No abstract provided.
Characterization Of Neuronal Differentiation And Activity In Human-Induced Pluripotent Neural Stem Cells, Allison Biddinger
Characterization Of Neuronal Differentiation And Activity In Human-Induced Pluripotent Neural Stem Cells, Allison Biddinger
The Journal of Purdue Undergraduate Research
No abstract provided.
High Wind Alerts: A System Created With Observations From The X-Band Teaching And Research Radar, Lauren Warner
High Wind Alerts: A System Created With Observations From The X-Band Teaching And Research Radar, Lauren Warner
The Journal of Purdue Undergraduate Research
Following the August 13, 2011, Indiana State Fair stage collapse tragedy, caused by a wind gust from an approaching thunderstorm, Purdue University enforced a wind speed restriction of 30 mph (13 m s-1) for tents at outdoor events. During these events, volunteers stand outside with handheld anemometers, measuring and reporting when the wind speeds exceed this limit. In this study, we report testing of a new system to automate high-wind alerts based on observations from a Doppler radar, the X-band Teaching and Research Radar (XTRRA), near Purdue’s campus. XTRRA scans over campus at low elevations approximately every 5 minutes. Using …
Human Factors Analysis And Classification System (Hfacs): As Applied To Asiana Airlines Flight 214, Alex Small
Human Factors Analysis And Classification System (Hfacs): As Applied To Asiana Airlines Flight 214, Alex Small
The Journal of Purdue Undergraduate Research
The Human Factors Analysis and Classification System (HFACS) is a safety tool that aids in the identification and analysis of organizational factors that contribute to aircraft accidents. By using the HFACS model, safety investigators can better understand the existing conditions that contribute to accidents, which then allows for the development and implementation of safety programs to prevent these conditions. In this study, the HFACS framework was utilized to identify the human factors that contributed to the Asiana Airlines flight 214 accident that occurred on July 6, 2013. The results of this study indicate that inadequate pilot training, lack of upper-level …
Comparison Of Machine Learning Models: Gesture Recognition Using A Multimodal Wrist Orthosis For Tetraplegics, Charlie Martin
Comparison Of Machine Learning Models: Gesture Recognition Using A Multimodal Wrist Orthosis For Tetraplegics, Charlie Martin
The Journal of Purdue Undergraduate Research
Many tetraplegics must wear wrist braces to support paralyzed wrists and hands. However, current wrist orthoses have limited functionality to assist a person’s ability to perform typical activities of daily living other than a small pocket to hold utensils. To enhance the functionality of wrist orthoses, gesture recognition technology can be applied to control mechatronic tools attached to a novel fabricated wrist brace. Gesture recognition is a growing technology for providing touchless human-computer interaction that can be particularly useful for tetraplegics with limited upper-extremity mobility. In this study, three gesture recognition models were compared—two dynamic time-warping models and a hidden …
Navigating In Numerous Video Data: User Interface Design For An On-Camera Video Analytics Engine, Sabriya Maryam Alam
Navigating In Numerous Video Data: User Interface Design For An On-Camera Video Analytics Engine, Sabriya Maryam Alam
The Journal of Purdue Undergraduate Research
Video analytics powered by artificial intelligence shows high promise in making our society smarter. Harnessing large amounts of video data, however, requires the development of processing systems demonstrating high performance and high efficiency. To this end, this work has contributed to a video analytics system powered by artificial intelligence for object detection and recognition. Rather than streaming all the video frames to the cloud, the system analyzes images on-camera and only returns those of interest to the cloud. This edge analytics research-grade software is available, but it lacks a simple web interface for general use by scientists, engineers, and other …