Zipkin E.F., Rossman S., Yackulic C., Wiens J.D., Thorson J.T., Davis R.J., and Grant E.H.C. 2017. Integrating count and detection-nondetection data to model population dynamics. Ecology. 98: 1640-1650.
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Updated
May 3, 2019 - R
Zipkin E.F., Rossman S., Yackulic C., Wiens J.D., Thorson J.T., Davis R.J., and Grant E.H.C. 2017. Integrating count and detection-nondetection data to model population dynamics. Ecology. 98: 1640-1650.
A maximum occupancy traffic light system created for a Hackathon.
Occupancy Prediction using Residential Training Data Collected via Interactive Learning
Seminar report and presentation: Convolutional Occupancy Networks publication
Prototype java application for using building sensor data to produce utilization reports and provide live viewing of building capacity. Copied from original gitlab repo. Created for the class CIS*4450 at the University of Guelph
Zylstra, E. R., D. E. Swann, B. R. Hossack, E. Muths, and R. J. Steidl. 2019. Drought-mediated extinction of an arid-land amphibian: insights from a spatially explicit dynamic occupancy model. Ecological Applications 29:e01859
Unofficial port of the R package unmarked
cabspotting case study
Matter Occupancy Sensor based on the Nordic nRF5340 DK / nRF7002 DK and the Infineon S2GO RADAR BGT60LTR11
Wright, A.D., Grant, E.H.C., & Zipkin, E.F. 2020. A hierarchical analysis of habitat area, connectivity, and quality on amphibian diversity across spatial scales.
In this project I analyzed data from AirBnB listings in Singapore from 2018 to 2022 to see how room types, location, and pandemic-induced trends have shaped Airbnb listings in Singapore over the four years. I have also created visualizations to demonstrate and explain the insights that I have gathered from the analyses.
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