Inflammation in the body has been linked to the intensity of tobacco smoking among people with HIV, according to a team of University of Massachusetts Amherst researchers.
It's a common assumption among marketers that if you can customize any form of marketing, particularly mobile advertising, you'll get better results. With this in mind, mobile marketing relies significantly on user tracking data as a cornerstone advertising strategy.
A deep-learning algorithm developed by MIT researchers is designed to help machines navigate in the real world, where imperfect or "adversarial" inputs may cause uncertainty.
Dr Bran Knowles, a senior lecturer in data science at Lancaster University, says: "I'm certain that the public are incapable of determining the trustworthiness of individual AIs... but we don't need them to do this. It's not their responsibility to keep AI honest."
Modeling shows the true cost of heat on PV system performance.
A research group led by KAUST Associate Professor Andrea Fratalocchi has discovered that silicon nanoshapes act as feed-forward neural networks with the ability to be trained in a supervised learning model to perform user-defined tasks at lightspeed. The new flat optics opens the door to a major technological revolution by offering small, cheap, flexible alternatives to current processors and to an entirely new generation of devices.
The process of egg formation in fruit flies relies on physical phenomena analogous to the exchange of gases between balloons of different sizes, according to a study by MIT biologists and mathematicians.
A team of scientists from Geisinger and Tempus have found that artificial intelligence can predict risk of new atrial fibrillation (AF) and AF-related stroke.
A researcher from Kanazawa University devised a way to speed up a fundamental task in computer vision and graphics known as non-rigid point set registration. Unlike previous registration techniques, the proposed method is computationally efficient even for large data sets. Moreover, the computing times for this method are shorter than those for a state-of-the-art approach. The results of this study could have implications for various fields, such as autonomous driving, medical imaging, and robotic manipulation.
Researchers have developed a new quantum version of a 150-year-old thermodynamical thought experiment that could pave the way for the development of quantum heat engines.