University of Washington researchers have developed a method that uses a gaming graphics card to control plasma formation in their prototype fusion reactor.
Researchers from the University of Southern California and NVIDIA have unveiled a new simulator for robotic cutting that can accurately reproduce the forces acting on a knife as it slices through common foodstuffs, such as fruit and vegetables. The system could also simulate cutting through human tissue, offering potential applications in surgical robotics. The paper was presented at the Robotics: Science and Systems (RSS) Conference 2021 on July 16.
Researchers at the NYU Center for Cyber Security at the NYU Tandon School of Engineering are rethinking basic functions that drive the ability of neural networks to make inferences on encrypted data.
A collaboration across three continents at the frontiers of physics, biology, and engineering co-led by Maurizio Porfiri at NYU Tandon, applied super computing muscle and special software to a novel simulation of the Venus' flower basket sponge.
Wearable devices can detect people's stress, according to new Washington State University research, opening potential new interventions for people with addictions. In a paper in the Journal of Medical Internet Research, a WSU research team found that wearable wristbands measure physiological responses to stress in real-time and real-world situations, providing a potential method to help people avoid slipping back into old behaviors.
Although photovoltaic systems constitute a promising way of harnessing solar energy, power grid managers need to accurately predict their power output to schedule generation and maintenance operations efficiently. Scientists from Incheon National University, Korea, have developed a machine learning-based approach that can more accurately estimate the output of photovoltaic systems than similar algorithms, paving the way to a more sustainable society.
Implementing algorithms that can simultaneously track multiple objects is essential to unlock many applications, from autonomous driving to advanced public surveillance. However, it is difficult for computers to discriminate between detected objects based on their appearance. Now, researchers at the Gwangju Institute of Science and Technology (GIST) adapted deep learning techniques in a multi-object tracking framework, overcoming short-term occlusion and achieving remarkable performance without sacrificing computational speed.
Creating new procedures that improve mass drone traffic is the purpose of LABYRINTH, a European research project coordinated by the Universidad Carlos III de Madrid (UC3M) with the participation of 13 international organisations within the R&D&I, transport, emergency, and auxiliary services fields. Researchers hope to use these drone swarm applications to improve civil road, train, sea, and air transport, making it safer, more efficient, and more sustainable.
Xatkit, a new UOC spin-off, offers pre-trained bots that automatically recognize a shop's product catalogue.
Protein design researchers have created a freely available method, RoseTTAFold, to provide access to highly accurate protein structure prediction. Scientists around the world are using it to build protein models to accelerate their research. The tool uses deep learning to quickly predict protein structures based on limited information, thereby compressing the time for what would have taken years of lab work on just one protein. Predicting intricate shapes of proteins vital to specific biological processes could speed treatment development for many diseases.