News by Subject Technology & Engineering

A content recommendation system based on the user's brain model would be ideal for targeted advertising. Creating such a brain model, however, is computationally expensive. In a new study, researchers from Japan propose and validate a machine learning scheme to infer a user's brain model from their profile with high accuracy while optimizing the information collection cost using a feature selection technique, providing hope for its real-world application following further optimizations.

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.

Autonomous vehicle researchers at Carnegie Mellon University believe they are the first to tackle navigating a crowded, narrow street, with cars parked on both sides, and not enough space for vehicles traveling in both directions to pass each other.

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.

A team of researchers, led by Yale-NUS College Associate Professor of Science (Computer Science) Robby Tan, who is also from the National University of Singapore's Faculty of Engineering, has developed novel approaches using computer vision and deep learning to resolve the problem of low-level vision in videos caused by rain and night-time conditions, as well as improve the accuracy of 3D human pose estimation in videos.

UC Riverside engineers made a pneumatic RAM chip using microfluidic valves instead of electronic transistors. The valves remain sealed against a pressure differential even when disconnected from an air supply line, creating trapped pressure differentials that function as memories and maintain the states of a robot's actuators. Dense arrays of these valves can perform advanced operations and reduce the expensive, bulky, and power-consuming electronic hardware typically used to control pneumatic robots.

A team of researchers from the University of Maryland has 3D printed a soft robotic hand that is agile enough to play Nintendo's Super Mario Bros. - and win!

Developed by two researchers at the University of Malaga, This methodology enables the reduction of costs and time in engineering design optimisation thanks to artificial intelligence