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UrduNurses are invited to apply for AACN research grants by Nov. 1, 2019, with total available funding of $160,000. Projects funded in 2019 address PICS, telemedicine, virtual reality for onboarding new nurses, and machine learning and pressure injuries.
Tag: Machine Learning
InnovationXLab Summit brings industry, national laboratories together around artificial intelligence
The recent InnovationXLab℠ Summit on AI raised the profile of the national laboratories’ work in AI and forged new partnerships between industry and the national labs.
Using Machine Learning to Hunt Down Cybercriminals
MIT’s Computer Science & Artificial Intelligence Laboratory (CSAIL) and the Center for Applied Internet Data Analysis (CAIDA) at the San Diego Supercomputer Center have used machine learning to identify “serial hijacking” of IP addresses.
PNNL, Sandia, and Georgia Tech Join Forces in AI Effort
Scientists from DOE’s Pacific Northwest National Laboratory, DOE’s Sandia National Laboratories, and the Georgia Institute of Technology will collaborate on solutions to some of the most challenging problems in AI today, thanks to $5.5 million in funding from DOE.
AI technique does double duty spanning cosmic and subatomic scales
While high-energy physics and cosmology seem worlds apart in terms of sheer scale, physicists and cosmologists at Argonne are using similar machine learning methods to address classification problems for both subatomic particles and galaxies.
Artificial intelligence helps open new window on complex urban issues
The complexity of cities and the interrelationships of urban systems makes them ideal candidates for research using machine learning, which Argonne scientists are deploying to improve cities.
Department of Energy Announces $21.4 Million for Quantum Information Science Research
The following news release was issued on Aug. 26, 2019 by the U.S. Department of Energy (DOE). It announces funding that DOE has awarded for research in quantum information science related to particle physics and fusion energy sciences. Scientists at DOE’s Brookhaven National Laboratory are principal investigators on two of the 21 funded projects.
Prediction System Significantly Increases Palliative Care Consults
A trigger system powered by predictive analytics increased palliative care consultations by 74 percent after implementation
ORNL develops, deploys AI capabilities across research portfolio
To accelerate promising artificial intelligence applications in diverse research fields, ORNL has established a labwide AI Initiative. This internal investment brings the lab’s AI expertise, computing resources and user facilities together to facilitate analyses of massive datasets.
Artificial Intelligence/Machine Learning are rapidly changing. The materials research community is just beginning to utilize AI and ML in the research process, and it is already clear that this represents a potentially game changing development.
Dr. Benji Maruyama is a Principal Materials Research Engineer in the Air Force Research Laboratory, Materials & Manufacturing Directorate. He is the Leader of the Flexible Materials and Processes Research Team, and leads research on the synthesis and processing science…
Lynne Ecker: A Nuclear Materials Scientist
Ecker became chair of Brookhaven’s Nuclear Science and Technology Department in October 2018, bringing expertise in nuclear reactor materials.
Machine learning in agriculture: scientists are teaching computers to diagnose soybean stress
Machine learning could lead to automated processes that would allow soybean producers to diagnose crop stresses more efficiently. A multi-disciplinary team at Iowa State University recently received a grant to develop the technology, which could lead to unmanned aerial vehicles surveying fields and automatically analyzing crop images.
Supercomputers Pave the Way for New Machine Learning Approach
Researchers have developed a machine learning approach called transfer learning that lets them model novel materials by learning from data collected about millions of other compounds. The new approach can be applied to new molecules in milliseconds, enabling research into a far greater number of compounds over much longer timescales.
A glimpse into the future: accelerated computing for accelerated particles
A team of scientists led by Fermilab has prototyped a method to use machine learning to analyze data from the Large Hadron Collider.
How ergonomic is your warehouse job? Soon, an app might be able to tell you
Researchers at the UW have used machine learning to develop a new system that can monitor factory and warehouse workers and tell them how ergonomic their jobs are in real time.
Machine Learning Helps Create Detailed, Efficient Models of Water
A team devised a way to better model water’s properties. They developed a machine-learning workflow that offers accurate and computationally efficient models.
IDEMIA Identity & Security USA licenses ORNL advanced optical array
IDEMIA Identity & Security USA has licensed an advanced optical array developed at the Department of Energy’s Oak Ridge National Laboratory. The portable technology can be used to help identify individuals in challenging outdoor conditions.
Artificial Intelligence Could be ‘Game Changer’ in Detecting, Managing Alzheimer’s Disease
Study Introduces Machine Learning as New Tactic in Assessing Cognitive Brain Health and Patient Care Worldwide, about 44 million people are living with Alzheimer’s disease (AD) or a related form of dementia. Although 82 percent of seniors in the United…