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How to Clean a 94-Foot Blue Whale Model

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Photos by Christian Jensen

As Exhibition Maintenance Manager at the American Museum of Natural History in New York City, Brittany Janaszak spends most of her time doing triage. "I'm a one person department, responsible for everything that's on display in the entire museum—temporary shows included," she tells mental_floss. "Typically my scheduled dustings and fixes are postponed due to issues that arise daily, so I deal with graphics breaking, prints falling off walls, objects falling off mounts, and dust. Lots and lots of dust." And once a year, she undertakes her biggest dusting of all, hopping in an aerial lift, strapping on a safety harness, and vacuuming off the museum's 94-foot-long blue whale, which hangs above the Milstein Hall of Ocean Life. mental_floss was there as Janaszak performed part of the cleaning.

Janaszak has been the museum's official whale cleaner since 2011, when she got the job as Exhibit Maintenance Manager; previously, she had worked in Exhibition. Though in the past the job was accomplished with scaffolding and several cleaners, these days, Janaszak goes it solo, using just an OMME lift, a specialized vacuum with variable speed control and extension tubes, and a support propped under the whale's chin to get the job done.

Cleaning the whale doesn't just require special equipment, but also a special set of skills: "Strong shoulders and arms are beneficial, as vacuuming for that length of time while mostly holding the vacuum extensions horizontally can be tiring—and the vacuum eventually produces a surprising amount of heat," Janaszak says. "A strong sense of spatial reasoning is also important, particularly when maneuvering the lift around the fins."

It's also important to vacuum gently: The 21,000 pound fiberglass and polyurethane whale is anchored into the ceiling in a single spot, "which is an incredible engineering feat," says Dean Markosian, ‎Director of Project Management at the American Museum of Natural History, "but because we have this huge amount of cantilever sticking out, it can bounce [during cleaning]." The chin support keeps it from bouncing.

When you're vacuuming something that's 94 feet long, you have to have a plan. Janaszak formulates hers around moving the lifter, "which can be time consuming," she says. "Preferably, I'd start on one side of the face and body, move the lift to the tail end of the same side, vacuum the tail end of the opposite side and finish with the face." Using this strategy, she only needs to move the lift four times.

The cleaning takes place over the course of three days. "We could probably do it in maybe two days, but we add a little buffer time just in case," Markosian says. During the cleaning, the bottom level of the Milstein Hall of Ocean Life is closed, though visitors still have access to the mezzanine level. "We frequently have events in the Hall of Ocean Life, so trying to block off a few consecutive days can be challenging," Janaszak says. "Other than that, our movers and electricians are all amazing to work with and they set me up with the lift so I can get in and get rolling right away."

The whale is cleaned once a year, and it's clear as Janaszak vacuums just how much dust piles up in that time. Still, she says, "the dust accumulation wasn't too bad. After a year it certainly gets dust enough that it completely changes color when it's vacuumed."

The most difficult part of the whale to clean is its tail. "Even when on the lift it's difficult to see over the edge so I need someone on the mezzanine to let me know when I've missed," she says. "Maneuvering around the fins is also difficult."

The blue whale was installed in 1969. At that time, men had walked on the moon, but hadn't yet studied a living blue whale! The model is based on a female blue whale found in 1925 off the southern tip of South America. Still, it wasn't quite accurate: During a 2003 facelift, sculptors whittled down the model's eye sockets so they didn't bulge, added a navel, and made the tail more tapered, which reflected the latest in blue whale research. They also tweaked the color, which was originally Battleship Gray. You get an idea of what that color might have looked like before Janaszak gets to dusting!

And in case you're wondering: Yeah, it can be a little weird to clean a massive blue whale in front of museum visitors—at least for the first few minutes. "After those initial nerves cool down, I really just settle in to the lift basket and focus on getting the job done as efficiently as possible," Janaszak says. "Other than when I have a decision to make regarding where I should place the lift basket to optimize my reach, I'm on autopilot. I settle into a state of zen when doing a lot of dusting here, actually."

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iStock // Ekaterina Minaeva
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Why Your iPhone Doesn't Always Show You the 'Decline Call' Button
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iStock

When you get an incoming call to your iPhone, the options that light up your screen aren't always the same. Sometimes you have the option to decline a call, and sometimes you only see a slider that allows you to answer, without an option to send the caller straight to voicemail. Why the difference?

A while back, Business Insider tracked down the answer to this conundrum of modern communication, and the answer turns out to be fairly simple.

If you get a call while your phone is locked, you’ll see the "slide to answer" button. In order to decline the call, you have to double-tap the power button on the top of the phone.

If your phone is unlocked, however, the screen that appears during an incoming call is different. You’ll see the two buttons, "accept" or "decline."

Either way, you get the options to set a reminder to call that person back or to immediately send them a text message. ("Dad, stop calling me at work, it’s 9 a.m.!")

[h/t Business Insider]

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