ATRI Research Examines Safety Impacts Of Driver Simulator Training DigitalJournal.com 13, 2014 /PRNewswire-USNewswire/ -- A new research white paper examining safety impacts of simulator training for truck drivers was released yesterday by the...
This chapter explores the context for the new paradigm of learning emerging in education, in relation to key critical concepts that centre around gamification, immersion, interface and social interactivity.
Researchers at the San Diego Supercomputer Center at the University of California, San Diego, have developed software that greatly expands the types of multi-scale QM/MM (mixed quantum and molecular mechanical) simulations of complex chemical...
Matthew Jubelius's insight:
The ability to simulate chemical reactions and test hypotheses is fascinating. Less waste, cost effective, reduced injury potential and so on. These types of simulations have the ability to conduct greater research!
For the first time, scientists at Carnegie Mellon University have identified which emotion a person is experiencing based on brain activity.
The study, published in the June 19 issue of PLOS ONE, combines functional magnetic resonance imaging (fMRI) and machine learning to measure brain signals to accurately read emotions in individuals. Led by researchers in CMU’s Dietrich College of Humanities and Social Sciences, the findings illustrate how the brain categorizes feelings, giving researchers the first reliable process to analyze emotions. Until now, research on emotions has been long stymied by the lack of reliable methods to evaluate them, mostly because people are often reluctant to honestly report their feelings. Further complicating matters is that many emotional responses may not be consciously experienced.
Identifying emotions based on neural activity builds on previous discoveries by CMU’s Marcel Just and Tom M. Mitchell, which used similar techniques to create a computational model that identifies individuals’ thoughts of concrete objects, often dubbed “mind reading.”
“This research introduces a new method with potential to identify emotions without relying on people’s ability to self-report,” said Karim Kassam, assistant professor of social and decision sciences and lead author of the study. “It could be used to assess an individual’s emotional response to almost any kind of stimulus, for example, a flag, a brand name or a political candidate.”