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Drone Waiters-Boss Magazine
According to Forbes, payroll costs consume up to 25 per cent of a restaurant’s profit. Restaurateurs in Sydney and other parts of Australia hope to combat that expense by following in the footsteps of venues in Asia that have used drone waiters instead of human wait staff.

Faster and Human-Free Waiter drones are robotic devices that soar through the air with platters of food and glasses of beverages perched on top. Customers place their orders via electronic devices or other means, then the kitchen sends out their food on trays carried by machines rather than humans. Each drone can carry up to 4.4 pounds of cargo.

Sensors on the sides of the drones prevent them from crashing into objects or people as they navigate busy restaurants. While this strategy eliminates the human element that many experts believe is essential to the hospitality industry, the waiter drones’ success in Asia suggests they might prove a valuable contribution to restaurants in Australia.

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In the movie “Ant-Man,” the title character can shrink in size and travel by soaring on the back of an insect. Now researchers at the University of Washington have developed a tiny wireless steerable camera that can also ride aboard an insect, giving everyone a chance to see an Ant-Man view of the world.

The camera, which streams video to a smartphone at 1 to 5 frames per second, sits on a mechanical arm that can pivot 60 degrees. This allows a viewer to capture a high-resolution, panoramic shot or track a moving object while expending a minimal amount of energy. To demonstrate the versatility of this system, which weighs about 250 milligrams—about one-tenth the weight of a playing card—the team mounted it on top of live beetles and insect-sized robots.

The results will be published July 15 in Science Robotics.

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SYDNEY, Australia — When you look up at the night sky, which constellations can you make out? Can you spot the Big Dipper? Do you see Orion’s Belt? Counting stars is pretty difficult in areas with lots of light, like major cities. A study says even in the clearest skies, you’re still seeing turbulence in the atmosphere that makes stars twinkle. Want a truly perfect view of outer space? An international research team has found the spot, but you’ll need to bundle up. It’s in Antarctica!

Stars aren’t supposed to twinkle?

According to the University of New South Wales, turbulence causes light coming from stars to bend as it reaches the Earth’s surface. That instability in the air gives stars their trademark twinkling effect.

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face_with_colon_three yay closer to foglet bodies: 3.

Is the T-1000 no longer science fiction?

It is a human dream to realize a robot with automatic mechanical functions similar to the robots presented in several science-fiction movies and series such as “Ex Machina”, “Black Mirror”, “The Terminator”, etc.

More specifically, the idea of a liquid-metal-based robot able to transform its structure from solid to liquid, slip through narrow channels, and self-repair from any physical damage has always fascinated the scientific community engaged in cutting-edge technological discoveries. Beside the science-fiction background, micromachines able to gain energy from chemical reactions are attracting lots of attention as they emerged as ideal candidates for microrobots used in the field of microfabrication, detection/sensing, and personalized drug delivery.

Continue reading “Liquid-Metal-Driven Micromachines for the Next Cutting-edge Technology” | >

Scientists are ramping up their efforts in the search for signs of alien life.

Experts at the SETI Institute, an organization dedicated to tracking extraterrestrial intelligence, are developing state-of-the-art techniques to detect signatures from space that indicate the possibility of extraterrestrial existence.

These so-called “technosignatures” can range from the chemical composition of a planet’s atmosphere, to laser emissions, to structures orbiting other stars, among others, they said.

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A comet has been captured on camera streaking across the skies over Stonehenge.

Comet Neowise has been spotted by stargazers across the UK and around the world as it heads past Earth.

It was discovered in late March and became one of the few comets in the 21st century that can be seen with the naked eye as it approached the sun.

Continue reading “Comet Neowise streaks over Stonehenge night sky” | >

Invisible radio signals from the cosmos have revealed previously unknown phenomena from prebiotic molecules in a starburst about 250 million light-years from Earth to the true rotation of Mercury. But the most famous occurred on August 6, 1967, when a squiggly stretch of high-speed recordings occupying less than a quarter-inch of astronomer Jocelyn Bell Burnell’s radio-telescope readouts revealed the first sign of something strange — an unknown cosmic mystery.

The minuscule signal appeared over and over again in the same part of the sky and she realized she was looking at a cosmic mystery — a repeating string of radio pulses spaced a bit more than a second apart that were unlike anything anyone had ever seen before. Bell-Burnell had detected the first evidence of a pulsar LGM-1 for Little Green Men. They thought the pulses could possibly be a beacon from an alien source.

Fast forward to today — mysterious circles of radio waves have left astronomers who are part of a pilot survey for a new project called the Evolutionary Map of the Universe (EMU) baffled with no idea how they formed, or even how big or far away they are. They don’t seem to match anything that has been seen before in the cosmos. The researchers dubbed them Odd Radio Circles, or ORCs.

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The presence of outliers in a classification or regression dataset can result in a poor fit and lower predictive modeling performance.

Identifying and removing outliers is challenging with simple statistical methods for most machine learning datasets given the large number of input variables. Instead, automatic outlier detection methods can be used in the modeling pipeline and compared, just like other data preparation transforms that may be applied to the dataset.

In this tutorial, you will discover how to use automatic outlier detection and removal to improve machine learning predictive modeling performance.

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