Engineers at Duke University are developing a smart robotic system for sniffing out pollution hotspots and sources of toxic leaks. Their approach enables a robot to incorporate calculations made on the fly to account for the complex airflows of confined spaces rather than simply 'following its nose.'
Researchers from Sweden and Finland have developed the interactive web-based Maladaptation Game, which can be used to better understand how Nordic farmers make decisions regarding environmental changes and how they negotiate the negative impacts of potentially damaging decisions.
Researchers from the Vrije Universiteit Amsterdam and the Dutch Royal Academy's Humanities Cluster have performed a thorough evaluation of four different name recognition tools on popular 40 novels, including A Game of Thrones. Their analyses, published in PeerJ Computer Science, highlight types of names and texts that are particularly challenging for these tools to identify as well as solutions for mitigating this.
A new learning system developed by MIT researchers improves robots' abilities to mold materials into target shapes and make predictions about interacting with solid objects and liquids. The system, known as a learning-based particle simulator, could give industrial robots a more refined touch -- and it may have fun applications in personal robotics, such as modelling clay shapes or rolling sticky rice for sushi.
A novel technique developed by MIT researchers rethinks hardware data compression to free up more memory used by computers and mobile devices, allowing them to run faster and perform more tasks simultaneously.
Portland State University researcher Nirupama Bulusu wants to prevent counterfeit pharmaceuticals from flooding the market. Bulusu recently published a blockchain protocol that could do just that.
Engineers at the University of California, Berkeley have built a new photonic switch that can control the direction of light passing through optical fibers faster and more efficiently than ever. This optical 'traffic cop' could one day revolutionize how information travels through data centers and high-performance supercomputers that are used for artificial intelligence and other data-intensive applications.
New architecture promises to cut in half the energy and physical space required to store and manage user data.
In response to serious new security flaws found in almost every computer chip on the market today, researchers at Technische Universität Kaiserslautern, Germany, in collaboration with scientists at Stanford, have developed a mathematical algorithm to automate and expedite the process of finding flaws in future designs prior to production.
Algorithm designs optimized machine-learning models up to 200 times faster than traditional methods.