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How humans can build better teamwork with robots

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As human interaction with robots and artificial intelligence increases exponentially in areas like healthcare, manufacturing, transportation, space exploration, defense technologies, information about how humans and autonomous systems work within teams remains scarce.
Recent findings from human systems engineering research demonstrate that human-autonomy teaming comes with interaction limitations that can leave these teams less efficient than all-human teams.
Existing knowledge about teamwork primarily is based on human-to-human or human-to-automation interaction, which positions humans as supervisors of automated partners.
But as autonomy has increasingly developed decision-making skills based on spontaneous situation assessments, it can become a teammate rather than a servant. These shared decision interactions are identified as human-autonomy teaming, or HAT. ....

United States , Nancy Cooke , Research Laboratory , American Association For The Advancement Of Science , Global Security Initiative , Polytechnic School At Arizona State University , Polytechnic School , Arizona State University , American Association , Artificial Intelligence , Robot Teaming , Air Force Research Laboratory , Business Economics , Technology Engineering Computer Science , Robotry Artificial Intelligence , ஒன்றுபட்டது மாநிலங்களில் , நான்சி சமைக்க , ஆராய்ச்சி ஆய்வகம் , உலகளாவிய பாதுகாப்பு முயற்சி , பாலிடெக்நிக் பள்ளி இல் அரிசோனா நிலை பல்கலைக்கழகம் , பாலிடெக்நிக் பள்ளி , அரிசோனா நிலை பல்கலைக்கழகம் , அமெரிக்கன் சங்கம் , செயற்கை உளவுத்துறை , ரோபோ குழு , அேக படை ஆராய்ச்சி ஆய்வகம் ,

Argonne Training Program on Extreme-Scale Computing seeks applications for 2021 | US Department of Energy Science News

DOE/Argonne National Laboratory
Attendees at ATPESC, an annual training program that provides specialized, in-depth training to doctoral students, postdocs and computational scientists on today s most powerful supercomputers. (Image taken in 2019 by Argonne National Laboratory.)
Apply by March 1 for an opportunity to learn the tools and techniques needed to carry out research on the world s most powerful supercomputers.
The architecture and software environments of today s most powerful supercomputers are complex, posing significant challenges to researchers interested in using them to advance scientific discoveries. To meet these challenges and facilitate breakthrough science and engineering on these amazing resources, the annual Argonne Training Program on Extreme-Scale Computing (ATPESC) hosted by the U.S. Department of Energy s (DOE) Argonne National Laboratory provides specialized, in-depth training to doctoral students, postdocs and computational scientists ....

United States , Ray Loy , Aleksandra Pachalieva , William Gropp , National Center , University Of Illinois At Urbana Champaign , National Nuclear Security Administration , Los Alamos National Laboratory , Us Department Of Energy , Office Of Science User Facility , University Of Saskatchewan , Argonne Training Program On , Oak Ridge National Laboratory , Argonne National Laboratory , Training Program , Extreme Scale Computing , Argonne National , Argonne Training Program , Argonne Leadership Computing Facility , Science User , Urbana Champaign , Supercomputing Applications , Kevin Green , Exascale Computing Project , Advanced Scientific Computing Research Program , National Nuclear Security ,

Deepfake detectors can be defeated, computer scientists show for the first time

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VIDEO: XceptionNet, a deep fake detector, labels an adversarial video created by the researchers as real.
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Credit: University of California San Diego
Systems designed to detect deepfakes videos that manipulate real-life footage via artificial intelligence can be deceived, computer scientists showed for the first time at the WACV 2021 conference which took place online Jan. 5 to 9, 2021.
Researchers showed detectors can be defeated by inserting inputs called adversarial examples into every video frame. The adversarial examples are slightly manipulated inputs which cause artificial intelligence systems such as machine learning models to make a mistake. In addition, the team showed that the attack still works after videos are compressed. ....

Paarth Neekhara , Shehzeen Hussain , Technology Engineering Computer Science , Computer Science , System Security Hackers , பார்த் நீக்கர , தொழில்நுட்பம் பொறியியல் கணினி அறிவியல் , கணினி அறிவியல் , அமைப்பு பாதுகாப்பு ஹேக்கர்கள் ,

Researchers develop data tool that may improve care

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IMAGE: Medical director of high-risk populations and outcomes, UPMC Wolff Center; associate professor of surgery, University of Pittsburgh School of Medicine.
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Credit: UPMC
PITTSBURGH, Feb. 8, 2021 - With the aid of sophisticated machine learning, researchers at UPMC and the University of Pittsburgh School of Medicine demonstrated that a tool they developed can rapidly predict mortality for patients facing transfer between hospitals in order to access higher-acuity care. This research, published today in
PLOS One, could help physicians, patients and their families avoid unnecessary hospital transfers and low-value treatments, while better focusing on the goals of care expressed by patients. ....

United States , Tamrae Minnier , Stefaniec Altieri Dunn , Mary Kay Wisniewski , Matthewe Harinstein , Jeffreyd Borrebach , Johannae Bellon , Wendy Zellner , Courtney Caprara , Andrew Bilderback , Joelb Nelson , Jacobc Hodges , Daniele Hall , School Of Medicine , Wolff Center , Vascular Institute , University Of Pittsburgh School Medicine , National Institutes Of Health , National Science Foundation , Insurance Services Division , Pitt School Of Medicine , Pittsburgh School , Safe Nonelective Emergent Transfers , Pittsburgh Schools , Health Sciences , World Report ,

Shuffling bubbles reveal how liquid foams evolve

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IMAGE: A rearrangement event in a monodisperse foam. Note how bubbles move in the same direction along the same row, or in exactly the opposite direction in adjacent rows over long.
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Credit: Tokyo Metropolitan University
Tokyo, Japan - Researchers from Tokyo Metropolitan University studied the dynamics of foams. When a drop of water was added to a foam raft, the bubbles rearranged themselves to reach a new stable state. The team found that bubble movement was qualitatively different depending on the range of bubble sizes present. Along with analogies with soft-jammed materials, these findings may inspire the design of new foam materials for industry. ....

Scientific Research , Research Fellowship For Young Scientists , Tokyo Metropolitan University , Rei Kurita , Young Scientists , Chemistry Physics Materials Sciences , Mathematics Statistics , Technology Engineering Computer Science , Biomedical Environmental Chemical Engineering , Industrial Engineering Chemistry , Nanotechnology Micromachines , அறிவியல் ஆராய்ச்சி , ஆராய்ச்சி கூட்டுறவு க்கு இளம் விஞ்ஞானிகள் , டோக்கியோ பெருநகர பல்கலைக்கழகம் , ரே குரிதா , இளம் விஞ்ஞானிகள் , வேதியியல் இயற்பியல் பொருட்கள் அறிவியல் , கணிதம் புள்ளிவிவரங்கள் , தொழில்நுட்பம் பொறியியல் கணினி அறிவியல் , உயிர் மருத்துவ சுற்றுச்சூழல் இரசாயன பொறியியல் , தொழில்துறை பொறியியல் வேதியியல் ,