Author: peterjang73

A nerdy father of two, a husband of a beautiful and understanding wife, an engineer who loves anime and tinkering with PCs and games, but most of all, loves God.
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Whill’s all-terrain wheelchair is built for rough surfaces

Danielle Kent rode her wheelchair toward a black ramp at the Las Vegas Convention Center, where CES is taking place. She gently pressed on a small controller on the right armrest before the powered wheelchair went over a three-inch bump to climb the incline. Seconds later, Kent made a smooth turn onto a stone-covered path. The personal vehicle, designed by a wheelchair-making company called Whill, navigated the bumpy end of the ramp with ease.

Over two million people rely on wheelchairs in the US alone. Still, accessibility vehicles like wheelchairs have seen little improvements over the years. While some companies have been building powerful machines that can help people with disability navigate the streets, most electric wheelchairs continue to be too bulky for public doorways and tend to get stuck on turns and rough surfaces. The limitations keep many manual wheelchair users from switching over to powered machines. The latest model from Whill, however, is designed to instill confidence in the users so that they’re able to move independently.

Model M is an all-terrain EV with omni-wheels and a sturdy build. It enables people with multiple sclerosis and spinal cord injuries to use the same machine both indoors and outdoors. According to Kent, the director of product marketing at Whill, the new design takes up almost the same amount of room as her old manual wheelchair. The compact machine pushes the wheelchair to run at three speed modes plus a stationary mode that keeps it stable in case someone knocks into it. But that’s not all the machine will do.

The company also has plans to introduce autonomous driving for people with disabilities, suggesting the built-in software has the potential to evolve as driverless technologies become more capable of moving wheelchairs. Additionally, Whill has a mobile app in the making that will wirelessly help control navigation for safer mobility.

Click here to catch up on the latest news from CES 2017.

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Netflix Made a Free Video Game Featuring Characters From Its Shows, Play It Now

Streaming giant Netflix has made and released a video game. Netflix Infinite Runner, as it’s called, is a retro-themed endless running game featuring characters from the network’s original shows (via Engadget).

No Caption Provided

You can choose to play as Pablo Escobar (Narcos), Marco Polo (Marco Polo), Piper Chapman (Orange is the New Black), or Mike Wheeler (Stranger Things). You’ll play a different level based on your selection. For example, choose Escobar and you’ll sprint through the Colombian jungle, while the Stranger Things game eventually challenges you to escape the Demogorgon.

Your character runs automatically, so all you have to do is press the space bar to jump; you can also perform a double jump. There is chip-tune music based on songs from each show, which is a nice touch.

Go play Netflix Infinite Runner here.

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New Camera Can See Around Corners

  • And that raises an interesting question: how much more can these devices do?

    Today we get an answer of sorts thanks to the work of Bin Bai and co at Xi’an Jiaotong University in China, who have built a single pixel camera that can see around corners. Their new device can photograph objects even when they are not in direct view.

    The technique is similar to that used with other single pixel cameras. The trick is to first randomize the light that the pixel detects, record the resulting light intensity, and then repeat this process thousands of times.

    It’s easy to think that this randomization makes the task of creating an image even harder, but the reverse is true.

    The randomization process changes the intensity of light each time the pixel records it. These differences in intensity are not random but instead correlated with the scene in front of the pixel. So producing an image is simply a question of mining this data to find the correlation. And the more data that is collected, the better the image becomes.

    So by recording the intensity of light many times, it is possible to create a high-resolution picture with a single pixel.

    And that’s how Bin and co have used their camera to peer round corners. What they mean by this is that they have produced a picture using light from an object that is scattered off a wall. The pixel records the scattered light but cannot see the object directly. 

    The setup is simple. The team begins by illuminating a toy airplane with light from a beamer that projects a random pattern of illuminated squares. This random pattern changes with each exposure.

    The airplane is next to a white diffuse wall that scatters light toward a single pixel that cannot otherwise “see” the plane. This pixel records the light intensity from the wall. The team repeats this imaging process some 50,000 times. Finally, the team uses a data-mining algorithm to crunch the resulting data set and to create the image of the plane shown here.

    The results are impressive. “All results show that the single-pixel camera can image the diffuse object when the camera cannot look at object directly,” say Bin and co.

    The airplane is clearly visible in the image and the team says further improvements are possible by, for example, optimizing the algorithm and by reducing the size of the squares in the random pattern of projected light. “When the size of speckle patterns becomes smaller, the resolution of the image becomes higher,” say Bin and co.

    An interesting question is how quickly it is possible to take 50,000 images, since this places an important limit on how the camera can image moving objects.

    The Chinese team doesn’t suggest potential applications for the device, but it’s not hard to think of ways it might be used. Single-pixel cameras are tiny, simple to make, and cheap to build.

    One way or another, single-pixel cameras are set to have significant impact in the not too distant future.

    Ref: http://ift.tt/2htaBRv: Imaging Around Corners with Single-Pixel Detector by Computational Ghost Imaging

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    3,000 Ride-Sharing Vehicles Could Replace 13,500 Taxis in NYC

    New York City taxis, they ain’t so smart — yet.
    A new study from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) estimates that just 3,000 ride-sharing cars guided by an algorithm could serve the needs of busy New Yorkers. That’s compared to the roughly 13,500 taxis currently in operation in the city, famous for its frenzied rush hours.
    May I Have This Ride?
    The researchers used taxi data from the University of Illinois spanning 2010-2013 for their analysis, and co

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