NUS deep-learning AI system puts Singapore on global map of big data analytics

⎯ A team of researchers from the National University of Singapore (NUS) has put Singapore on the global map of Artificial Intelligence (AI) and big data analytics. Their open-source project, called Apache SINGA, “graduated” from the Apache Incubator on 16 October 2019 and is now Southeast Asia’s first Top-Level Project (TLP) under the Apache Software Foundation, the world’s largest open-source software community.

Machine Learning Leads to Novel Way to Track Tremor Severity in Parkinson’s Patients

Physical exams only provide a snapshot of a Parkinson’s patient’s daily tremor experience. Scientists have developed algorithms that, combined with wearable sensors, can continuously monitor patients and estimate total Parkinsonian tremor as they perform a variety of free body movements in their natural settings. This new method holds great potential for providing a full spectrum of patients’ tremors and medication response, providing clinicians with key information to effectively manage and treat their patients with this disorder.

What 26,000 books reveal when it comes to learning language

What can reading 26,000 books tell researchers about how language environment affects language behavior? Brendan T. Johns, an assistant professor of communicative disorders and sciences at UB has published a computational modeling study that suggests our experience and interaction with specific learning environments, like the characteristics of what we read, leads to differences in language behavior that were once attributed to differences in cognition.

Machine-Learning Analysis of X-ray Data Picks Out Key Catalytic Properties

Scientists seeking to design new catalysts to convert carbon dioxide (CO2) to methane have used a novel artificial intelligence (AI) approach to identify key catalytic properties. By using this method to track the size, structure, and chemistry of catalytic particles under real reaction conditions, the scientists can identify which properties correspond to the best catalytic performance, and then use that information to guide the design of more efficient catalysts.

AACN grants support clinical research to influence high-acuity and critical care nursing practice

Nurses 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.

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.

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.

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.

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…

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.

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…