News by Subject Technology & Engineering

New machine learning technology, developed by a multi-disciplinary team based at University of California, Berkeley, has devised a machine learning system to tap the problem-solving potential of satellite imaging. The low-cost, easy-to-use technology could bring satellite image access and analytical power to researchers and governments worldwide.

Autonomous vehicle researchers at Carnegie Mellon University believe they are the first to tackle navigating a crowded, narrow street, with cars parked on both sides, and not enough space for vehicles traveling in both directions to pass each other.

Scientists at Berkeley Lab and UC Berkeley have created an ultrathin magnet that operates at room temperature. The ultrathin magnet could lead to new applications in computing and electronics - such as high-density, compact spintronic memory devices - and new tools for the study of quantum physics.

The Xerces blue butterfly is generally accepted as the first American insect species destroyed by urban development, but there are lingering questions about whether it was really a species to begin with, or just a sub-population of another common butterfly. In a new study, researchers analyzed the DNA of a 93-year-old Xerces blue specimen in museum collections, and confirmed that it was a unique species.

The most promising method to achieve real-world BCI applications is through electroencephalography, a method of monitoring the brain's electrical activity. EEG-based BCIs will require a number of technological advances prior to widespread use, but more importantly, they will raise a variety of social, ethical, and legal concerns. Researchers conducted a review of modern commercial brain-computer interface devices and discuss the primary technological limitations and humanitarian concerns of these devices in APL Bioengineering.

In the Journal of Renewable and Sustainable Energy, researchers describe a real-time method for potentially helping turbine farms realize additional power from the clustering of their turbines. Their method requires no new sensors to identify which turbines at any given time could increase power production if yaw control is applied, and validation studies showed an increase of 1%-3% in overall power gain.