News by Subject Technology & Engineering

A team of Australian researchers has designed a reliable strategy for testing physical abilities of humanoid robots. Using a blend of machine learning methods and algorithms, the research team succeeded in enabling test robots to effectively react to unknown changes in the simulated environment, improving their odds of functioning in the real world. The findings have promising implications in the broad use of humanoid robots in fields such as healthcare, education, disaster response and entertainment.

MIT researchers have developed a battery-free underwater communication system that uses near-zero power to transmit sensor data. The system could be used to monitor sea temperatures to study climate change and track marine life over long periods -- and even sample waters on distant planets. They are presenting the system at the SIGCOMM conference this week, in a paper that has won the conference's 'best paper' award.

Inspired by Wall Street financial theories used to invest in the stock market, MIT and Microsoft researchers developed a 'risk-aware' model that improves the performance of cloud-computing infrastructure used across the globe.

According to Adar Ovadya, a master's student in BGU's Department of Software and Information Systems Engineering, 'all of the routers we surveyed regardless of brand or price point were vulnerable to at least some cross-network communication once we used specially crafted network packets. A hardware-based solution seems to be the safest approach to guaranteeing isolation between secure and non-secure network devices.'

An artificial intelligence tool developed by USC computer science researchers can characterize a song's genre and provides increased understanding how we perceive and process music. Applications include how music content is marketed, consumed and tagged; neuropsychology and the mechanisms of human thought; and affective computing systems that impact human emotions.

Researchers from the University of Maryland have figured out how to reliably create questions that challenge computers and reflect the complexity of human language through a human-computer collaboration, developing a dataset of more than 1,200 questions that, while easy for people to answer, stump the best computer answering systems today. The system that learns to master these questions will have a better understanding of language than any system currently in existence.