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Gizmorama - May 9, 2016

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What is cloud-seeding? And how are drones being utilized in this new precipitous process? Both questions will be answered below.

Learn about this and more interesting stories from the scientific community in today's issue.

Until Next Time,

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* Researchers test cloud-seeding drone in Nevada *

RENO, Nev. - This week, engineers with the Desert Research Institute announced that their Drone America Savant unmanned aircraft had successfully ascended to 400 feet and deployed two silver-iodide flares.

The 18-minute test flight occurred late last week, proving -- researchers say -- that the unmanned aerial vehicle is ready for the cloud-seeding work for which it was designed.

Silver iodide is similar in structure to ice, and cloud-seeding scientists believe it encourages ice crystal formation, triggering clouds to produce precipitation.

"This is a tremendous accomplishment for the state of Nevada and everyone involved," Adam Watts, lead scientist on the project, said in a news release.

The drone, which boasts a wingspan of just under 12 feet and weighs 55 pounds, was built to test cloud-seeding technologies.

"We have reached another major milestone in our effort to reduce both the risks and the costs in the cloud seeding industry and help mitigate natural disasters caused by drought, hail and extreme fog," said Mike Richards, president and CEO of Drone America.

Designers at Drone America and DRI say Savant's low profile makes it resistant to wind and ideal for use in adverse weather conditions.

Researchers say they will now begin to employ the Savant drone to study weather patterns and build forecast models as well as test a variety of cloud-seeding technologies.

*-- Scientists prove system noise can identify electronic devices --*

ORLANDO, Fla. - Almost all electronic devices -- laptops, tablets, smartphones -- emit radio frequencies.

The output may seem random, but scientists at Disney Research recently proved a device's so-called system noise can be used to identify it -- like a fingerprint.

"The idea that these electronic devices have such distinctive RF emissions is astounding," Jessica Hodgins, vice president at Disney Research, said in a news release. "Our researchers were able not only to discover this phenomenon, but to develop a means of using it to identify devices right out of the box."

Researchers devised a method called EM-ID to analyze, recognize and differentiate between RF emissions.

"Electromagnetic emissions are highly structured and a direct manifestation of the circuits that generate them," Disney Research's Chouchang Yang and said. "But variations in the manufacturing of all components and in final assembly create differences in the EM signal that enable us to differentiate, for example, a laptop computer from another laptop of the same make and model."

Yang and research partner Alanson P. Sample demonstrated the EM-ID process at the IEEE International Conference held this week in Orlando, Fla.

The method employs a low-cost software-defined radio to pick up and record the system noise. The frequencies are are digitized and fed into a computer where an algorithm parses the patterns. Low-frequency background noise is stripped away, leaving frequency peaks consisting of 1,000 to 2,000 elements.

The algorithm uses a two-tier analysis strategy. Focusing first on frequency distribution to place the new device within a general category of electronic devices -- power tools, computers, household appliances, automobiles. To differentiate devices within a category, the software analyzes frequency and magnitude.

Testing proved the novel method can identify individual electronic devices with an accuracy rate of 95 percent.

"But even though we can't ensure that EM-IDs are always unique, we have a reliable algorithm for predicting the identification success rate," Sample added. "So when a new device is registered and entered into an inventory system, it can alert the user whether the device's EM-ID is unique enough to be read or if an alternative strategy is needed."


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