A Michigan Tech engineer has created a method to fill in the gaps of available connected vehicle data, which will give transportation planners a more accurate picture of traffic in their cities. It is also a more cost-effective data gathering system than what is currently available.
Researchers from Lawrence Berkeley National Laboratory and CEA Saclay have developed a particle-in-cell simulation tool that is enabling cutting-edge simulations of laser/plasma coupling mechanisms. More detailed understanding of these mechanisms is critical to the development of ultra-compact particle accelerators and light sources that could solve long-standing challenges in medicine, industry, and fundamental science.
Computer scientists at the University of California San Diego have developed FitRec, a recommendation tool powered by deep learning, that is able to better estimate runners' heart rates during a workout and predict and recommend routes. The team will present their work at the WWW 19 conference May 13-17 in San Francisco.
Debates over gun regulations make headlines across the world, but there's an underground operation for weapons that has drawn very little attention -- until now. Researchers from Michigan State University crept into the dark web to investigate how firearms are anonymously bought and sold around the world.
A powerful computational study of southern California seismic records has revealed detailed information about a plethora of previously undetected small earthquakes, giving a more precise picture about stress in the earth's crust.
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.'
A neural network developed at MIT and elsewhere can "read" scientific research papers and generate plain-English summaries of their contents.
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.
Scientists for the first time compared complete genome data of different ethnic groups in Russia. Using a special algorithm, they traced the development history for some groups. In the future, such data can be used in other important studies: for example, it can help to identify genetic risk factors in various populations of Russian people. The results are published in Genomics.
Adjusting the frequency and dosage of Parkinson's patients' medication is complex. In their 'ON' state they respond positively to medication and in their 'OFF' state symptoms return. Addressing these fluctuations requires a clinical exam, history-taking or a patient's self-report, which are not always practical or reliable. A new technology that combines an algorithm with a senor-based system using wearable motion sensors, automatically, continuously and reliably detects a patient's medication ON and OFF states without patient or physician engagement.