Researchers at PNNL teamed up to find out if deep learning--a distinct subset of machine learning--can do a better job at identifying clouds in lidar data than the current physics-based algorithms. The answer: A clear 'yes.' The new model is much closer to the answers scientists arrive at but in just a fraction of the time.
Researchers from NYU Tandon School of Engineering and Politecnico di Torino, Italy, have developed a mathematical model that could cure the potential to underestimate how quickly diseases spread. The team discovered that current predictive models may miss the influence of a critical aspect of the social behavior of individuals called 'burstiness.'
The 2011 Las Conchas mega-fire in New Mexico burned more than 150,000 acres and threatened the Los Alamos National Laboratory. Now, using data from the fire, researchers at Los Alamos have created an experimental model that will help us better understand the interactions of fire and water in the soil.
A team of researchers has developed an algorithm for predicting the effect of an external electromagnetic field on the state of complex molecules. The new algorithm, presented in a paper in The Journal of Chemical Physics, enables researchers to look inside large polyatomic molecules, observe and potentially control electron motion therein.
A research team at Osaka University created a system that uses a convolutional neural network to learn the features distinguishing different cancer cells, based on images from a phase-contrast microscope. This system accurately differentiated human and mouse cancer cells, as well as their radioresistant clones. This novel approach can improve the speed and accuracy of cancer diagnosis by avoiding the laboriousness and potential errors associated with equivalent analyses by humans.
Researchers have discovered a 'blind spot' in atomic force microscopy -- a powerful tool capable of measuring the force between two atoms, imaging the structure of individual cells and the motion of biomolecules.
LSTM's Professor Joseph Valadez is senior author on a new study published today in the Proceedings of the National Academy of Sciences, which outlines proposals for a more accurate estimator of health data.
New research could shed light on the 'missing' dark matter and dark energy that make up 95 percent of our universe and yet are wholly invisible to us.
As with most crime, the highest rates of burglary occur in urban communities. However, existing mathematical models typically examine burglaries in residential, suburban environments. In an article publishing tomorrow in the SIAM Journal on Applied Dynamical Systems, Joan Saldaña, Maria Aguareles, Albert Avinyó, Marta Pellicer, and Jordi Ripoll present a nonlinear model of urban burglary dynamics that accounts for the deterring effect of police presence and emphasizes timing of criminal activity.
In 2012, consumers paid $32 billion in overdraft fees, which represented the single largest source of revenue for banks from demand deposit accounts, while leading to significant levels of consumer dissatisfaction and attracting attention from government regulators. In a recent study, researchers have found that it may be possible to help correct this problem through the application of sophisticated data analytics.