Brother Tenecious Underwood is a Spring 2018 initiate of the Gamma Delta chapter who is charting a path to success that is uniquely his own. The senior computer information systems major began his academic year with the coveted honor of being selected as one of 44 White House HBCU Competitive Scholars in the nation, based on academic achievement, campus and civic involvement and entrepreneurial ethos. This is the highest student recognition by the White House Initiative on Historically Black Colleges and Universities that illustrate that HBCUs produce – often against the odds – strong, impressive educational, economic and societal results that impact the communities in which they serve. Everyone knows that a frog says “ribbit,” but did you know that their calls have a deeper, more impactful meaning? Frogs are considered “canaries in the coal mine,” for their ability to indicate ecological or environmental crises before humans notice a broader impact. Frogs have permeable skin, making them vulnerable to even small changes in their aquatic environment. As a result, 32 percent of frogs are in decline due to a combination of habitat loss, disease and climate change. This statistic worries scientists, so ecologists across the nation are eager to study declining frog populations.Brother Underwood had the distinct opportunity to participate in the Jetstream Research Experience for Undergraduates (REU) and present his findings at the world’s largest supercomputing conference, SC19, in November in Denver, Colorado. The Jetstream REU invites students to work with Indiana University researchers and staff on mentored research projects that involve the Jetstream platform. Led by the Indiana University Pervasive Technology Institute (PTI), Jetstream is a national science and engineering cloud that provides on-demand high-performance computing (HPC) and data analysis resources for research and education. Brother Underwood and his cohort in the Jetstream REU are bringing machine learning and HPC to the problem of identifying frog migration patterns.
“It is imperative that national frog surveyors are able to accurately identify where frogs are and where they are moving,” Brother Underwood said. “The entire scope of the project is to make artificial intelligence useful in fields that make up the long-tail of science.”
From students to frog surveyors
The Jetstream REU team wanted to identify amphibians specifically from the Indiana region – Spring Peepers, Chorus Frogs, Green Frogs and American Toads. They gathered sample calls from Cornell’s Macaulay Library archive of wildlife sounds – 85% of the calls were used as training data and the remaining 15% served as testing data.
Brother Underwood and the team then created three neural networks to process their data: one audio-based recurrent neural network (RNN), and two convolutional neural networks (CNN) – one audio-based and one image-based. The latter analyzed spectrograms created from the audio files. The result? Computer frog surveyors are much more accurate than their carbon-based counterparts. The CNN image-based model came out on top as being the most accurate and most efficient. It also took up less space and took less time to process.
“Human national surveyors accurately predict 80 percent of the frog calls species. The image-based CNN produced over 97 percent accuracy, with the four frog species,” Brother Underwood said. “The CNN audio and the RNN audio both produced nearly 90 percent accuracy. All three are what you could call superhuman.” Processing the more than 5,000 audio files they had recorded would have taken up to 20 hours on a laptop computer. Thanks to Jetstream, it took only minutes. “We couldn’t have accomplished anything without Jetstream,” Brother Underwood said. “It made the process more efficient and effective, and allowed us to be able to do a lot more.”