National Academies Communication Fair 2009
“On June 23, 2009 the National Academies Office of Communications, in cooperation with Staff Development Programs and the communications officers from the various program divisions here at the Academies, presented the third Communications Fair for National Academies staff.
“This year the fair featured an exciting new format with two panel discussions and a mid-day speaker to inspire new and creative ways to communicate science. We invite you to take part in what we’ve learned about communicating science by listening to podcasts of the events.”
…from the Journal of Energy Security…
“The study focuses on a risk analysis of the BTC pipeline and integrates state-of-the-art technologies for a comprehensive advanced security analysis (ASA) that includes critical issues such as the geographical and socio-political context along the BTC pipeline. This was addressed in the GIS (Geographical Information System) developed for purpose of integrating satellite imagery together with a number of map layers reflecting both physical and human factors along the BTC pipeline (road networks, topography, vegetation, population density, etc.).
“During the course of this analysis, the BTC pipeline was sabotaged by PKK insurgents in August 6th 2008. The geographical and socio-political factors of this sabotage have been weighted and extrapolated to the whole of the pipeline by a geospatial analysis on the GIS layers. As a result, the pipeline has been segmented into several degrees of risks which may prompt additional security actions as proposed in this paper.”
A Case Study of Woodford County, Kentucky
Authors: Bailey, Keiron; Grossardt, Ted H; Ripy, John; Mink, Philip; Shields, Carl; Davis, Dan; and Hixon, James
Transportation Research Board Annual Meeting 2009, Paper #09-2475
“Analytic predictive archaeological models can have great utility for state Departments of Transportation, but it is difficult to model the likelihood of prehistoric settlement using geographical proxy predictor variables because of the complexity of how settlement choices were actually made, and the complex interaction between these variables using GIS. In many cases classic statistical modeling approaches require too much data to be useful. This research reports on a preliminary predictive model that combines spatial analysis and fuzzy logic modeling to capture expert archaeological knowledge and convert this into predictive surface. A test area was defined in Woodford County, Kentucky, and five influencing factors were defined and calculated using the ArcGIS platform. Points were sampled and probabilities estimated using both small and large group structured processes from a broad range of archeologists that fed a forward-backward fuzzy logic induction process. It was used to generate and refine a knowledge base that mapped all inputs to an output probability function. These data were extracted from the fuzzy logic model to a lookup table and then geocoded into the ArcGIS platform, generating output surfaces showing the probability of encountering artifacts across the entire study area. The predictive results were tested using a blind control protocol with known archaeological data and established model testing statistics. The six models delivered predictive efficiencies that equaled and exceeded comparable statistical predictive models while using a much smaller number of variables as inputs.”