Recognition Reception | An indirect approach to human rights? | Course development seed grants


Penn State Department of Geography’s graduate wetlands class spent the Earth Day weekend exploring a gradient of wetlands in southern New Jersey from freshwater Atlantic White Cedar swamps of the Pinelands to coastal salt marshes of Delaware Bay. Here, the two come together where sea level rise is forcing salt marshes to invade the low-lying cedar swamps. Rot-resistant cedar tree trunks can be seen in the background protruding from the encroaching salt marsh. Their Society of Wetland Scientists matching t-shirts display their support for the March for Science. From right to left are: Rob Brooks (instructor), Peter Backhaus, Zheng Lin, Kyle Clark, Josh Wisor, Jesus Ruiz-Plancarte, Travis Young, and Ramzi Tubbeh (not pictured: Tim Gould and Tara Mazurczyk were involved in other contributing activities over the weekend).


Meg Boyle is serving as a panelist tonight (April 25), at the “Teach-in on Climate Change and Environmental Policy in the Age of Trump,” 6:30-8:00 p.m. Foster Auditorium, Paterno Library.

The department’s annual Recognition Reception takes place Friday, April 28 in Walker Building.

Diane Felmlee (Sociology), Alan MacEachren, Stephen Mathews, and Justine Blanford received a Seed Grant from the Social Science Research Institute.

Yanan Xin and Megan Baumann have been selected as the UROC coordinators for the 2017–18 academic year.

Bronwen Powell was invited to speak at this year’s UN Forum on Forests to be held during the first week of May at UN Headquarters in New York.

Annie Taylor, Director of the Dutton e-Education Institute will become EMS Assistant Dean of Distance Learning and Director, Dutton e-Education Institute.

Liping Yang, Guido Cervone, and Alan M. MacEachren won an NVIDIA GPU Grant (NVIDIA Awarded one Titan X Pascal GPU card).


When using the phrase ‘human rights’ hinders human-rights initiatives
A. Marie Ranjbar noticed a peculiar pattern in the conversations she was having as part of her dissertation research. A doctoral candidate in geography and women’s studies at Penn State, Ranjbar was interviewing minority ethnic groups in northwest Iran for research into how certain ethnic groups view a shrinking lake in northwest Iran, Lake Urmia.

Office for General Education announces Integrative Studies Seed Grant awards
Geographers Jennifer Baka, Lorraine Dowler, Chris Fowler, Joshua Inwood, and Karl Zimmerer are among awardees
The Integrative Studies Seed Grant Program, offered through the Penn State Office for General Education, will support 71 different course development projects this summer. In response to the large volume of highly qualified proposals, the budget was generously increased by more than 50 percent by the Office of the Provost and the Office of Undergraduate Education.


Short-term photovoltaic power forecasting using Artificial Neural Networks and an Analog Ensemble
By Cervone, G., Clemente-Harding, L., Alessandrini, S., Monache, L. D.
In Renewable Energy
A methodology based on Artificial Neural Networks (ANN) and an Analog Ensemble (AnEn) is presented to generate 72 h deterministic and probabilistic forecasts of power generated by photovoltaic (PV) power plants using input from a numerical weather prediction model and computed astronomical variables. ANN and AnEn are used individually and in combination to generate forecasts for three solar power plants located in Italy. The computational scalability of the proposed solution is tested using synthetic data simulating 4450 PV power stations. The National Center for Atmospheric Research (NCAR) Yellowstone supercomputer is employed to test the parallel implementation of the proposed solution, ranging from one node (32 cores) to 4450 nodes (141,140 cores). Results show that a combined AnEn + ANN solution yields best results, and that the proposed solution is well suited for massive scale computation.

Source Reconstruction of Atmospheric Release with Limited Meteorological Observations Using Genetic Algorithms
By Petrozziello, A., Cervone, G., Franzese, P., Haupt, S. E., Cerulli, R.
In Applied Artificial Intelligence
Access doi: 10.1080/08839514.2017.1300005
A genetic algorithm is paired with a Lagrangian puff atmospheric model to reconstruct the source characteristics of an atmospheric release. Observed meteorological and ground concentration measurements from the real-world Dipole Pride controlled release experiment are used to test the methodology. A sensitivity study is performed to quantify the relative contribution of the number and location of sensor measurements by progressively removing them. Additionally, the importance of the meteorological measurements is tested by progressively removing surface observations and vertical profiles. It is shown that the source term reconstruction can occur also with limited meteorological observations. The proposed general methodology can be applied to reconstruct the characteristics of an unknown atmospheric release given limited ground and meteorological observations.

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