Sunday 9 June 2019

Researchers find ways to hackproof smart meters

Smart electricity meters are useful because they allow energy utilities to efficiently track energy use and allocate energy production. But because they're connected to a grid, they can also serve as back doors for malicious hackers.

* This article was originally published here

A 3-D printer powered by machine vision and artificial intelligence

Objects made with 3-D printing can be lighter, stronger, and more complex than those produced through traditional manufacturing methods. But several technical challenges must be overcome before 3-D printing transforms the production of most devices.

* This article was originally published here

Thousands demonstrate against cruise ships in Venice

Thousands of people took to the streets in Venice on Saturday calling for a ban on large cruise ships in the city following last week's collision between a massive vessel and a tourist boat.

* This article was originally published here

Protecting our energy infrastructure from cyberattack

Almost every day, news headlines announce another security breach and the theft of credit card numbers and other personal information. While having one's credit card stolen can be annoying and unsettling, a far more significant, yet less recognized, concern is the security of physical infrastructure, including energy systems.

* This article was originally published here

Scientists feel chill of crackdown on fetal tissue research

To save babies from brain-damaging birth defects, University of Pittsburgh scientist Carolyn Coyne studies placentas from fetuses that otherwise would be discarded—and she's worried this kind of research is headed for the chopping block.

* This article was originally published here

US-China trade war sparks worries about rare minerals

Rising trade tensions between the U.S. and China have sparked worries about the 17 exotic-sounding rare earth minerals needed for high-tech products like robotics, drones and electric cars.

* This article was originally published here

Infusing machine learning models with inductive biases to capture human behavior

Human decision-making is often difficult to predict and delineate theoretically. Nonetheless, in recent decades, several researchers have developed theoretical models aimed at explaining decision-making, as well as machine learning (ML) models that try to predict human behavior. Despite the achievements associated with some of these models, accurately predicting human decisions remains a significant research challenge.

* This article was originally published here