Weekly Tech News related to Machine Learning Predicting Cardiac Arrest, New Potential Present-Day Utility of Tesla’s Inventions, Converting Waste Plastics to Jet Fuel, Converting WiFi Signals, Safer Cities with AI, Avoiding 3D-Printing Pitfall, E-Scooters
Note: None of the news bits (and cover picture) given here are written/owned by NewAnced's authors. The links on each of the news bits will redirect to the news source. Content given under each headline is a basic gist and not the full story.
Source: BMJ 17 May 2021
A branch of artificial intelligence (AI), called machine learning, can accurately predict the risk of an out of hospital cardiac arrest--when the heart suddenly stops beating--using a combination of timing and weather data, finds research. The risk of a cardiac arrest was highest on Sundays, Mondays, public holidays and when temperatures dropped sharply within or between days, the findings show.
Source: New York University 17 May 2021
A valve invented by engineer Nikola Tesla a century ago is not only more functional than previously realized, but also has other potential applications today, a team of researchers has found after conducting a series of experiments on replications of the early 20th-century design.
Source: Washington State University 17 May 2021
Researchers have developed an innovative way to convert plastics to ingredients for jet fuel and other valuable products, making it easier and more cost effective to reuse plastics. The researchers in their reaction were able to convert 90% of plastic to jet fuel and other valuable hydrocarbon products within an hour at moderate temperatures and to easily fine-tune the process to create the products that they want.
Original written by: Tina Hilding
Source: National University of Singapore 18 May 2021
A research team has developed a technology that uses tiny smart devices known as spin-torque oscillators (STOs) to harvest and convert wireless radio frequencies into energy to power small electronics. In their study, the researchers had successfully harvested energy using WiFi-band signals to power a light-emitting diode (LED) wirelessly, and without using any battery.
Source: University of Texas at Austin, Texas Advanced Computing Center 19 May 2021
A team of researchers from the NSF NHERI SimCenter, has developed a suite of tools called BRAILS — Building Recognition using AI at Large-Scale — that can automatically identify characteristics of buildings in a city and even detect the risks that a city's structures would face in an earthquake, hurricane, or tsunami. The researchers say the project grew out of a need to quickly and reliably characterize the structures in a city.
Original written by: Aaron Dubrow
Source: National Institute of Standards and Technology (NIST) 19 May 2021
A research team has found that a method commonly used to skirt one of metal 3D printing’s biggest problems may be far from a silver bullet. Their results show that a printing pattern often used in industry to decrease residual stress, known as island scanning, had the worst showing among the approaches studied, defying the team’s expectations. The data they produced could help manufacturers test and improve predictive models for 3D printing, which, if accurate, could steer them away from destructive levels of residual stress.
Source: University of Texas at Austin 20 May 2021
Realizing the potential of self-driving cars hinges on technology that can quickly sense and react to obstacles and other vehicles in real time. Engineers have created a new first-of-its-kind light detecting device that can more accurately amplify weak signals bouncing off of faraway objects than current technology allows, giving autonomous vehicles a fuller picture of what’s happening on the road.
Source: Singapore-MIT Alliance for Research and Technology (SMART) 20 May 2021
A new study has found that e-scooters, while considered by some to be a hazard to pedestrians and others, provide an important alternative mode of transit, particularly in urban areas. This study sheds important light on the growing utility of e-scooters as a micro-mobility service in Singapore, and will also inform operators, planners, and policymakers on how best to harness and regulate this growing mode of mobility.