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University of Vermont Libraries Center for Digital Initiatives

Scenes From the History of Snow Removal

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University of Vermont Libraries Center for Digital Initiatives

In some areas, the weather outside is pretty frightful. And since you've no place to go but outside to shovel, get cozy and read about snow removal in the good old days.

On A Roll

For a good stretch of American history, getting rid of snow was of no great concern. In fact, people actually wanted it around. While this might blow the minds of modern Northeasterners and Midwesterners, keep in mind that these were the days of the horse-drawn vehicle, not the Prius. To improve travel in winter conditions, horse carts and coaches traded their wheels in for ski-like runners. With those things on, the more packed snow on the roads, the better! Historian and weather geek Eric Sloane wrote that, in the 18th and 19th centuries, "snow was never a threat" to road travel, "but rather it was an asset."

To keep roads in optimal snowy condition, many municipalities employed a "snow warden" to pack and flatten the snow with a crude vehicle called a snow roller—essentially a giant, wide wheel weighed down with rocks and pulled by oxen or horses. A far cry from the winter road work we see today, it was more like maintaining a ski slope or smoothing out an ice rink. Stranger still, snow wardens actually had to install snow on the pathways of covered bridges so that travel would not be interrupted.

Plow About That

Photo Courtesy Schwartz Boiler Shop

By the mid 1800s, several different inventors had patented their own versions of a horse-drawn snow plow meant for clearing alleys and residential streets that saw more foot traffic than carriages. In 1862, Milwaukee became the first major municipality to try one out, and it was a hit. Over the next few years, the plows hit the streets in cities throughout the Snow Belt.

But horse-drawn plows didn't stand a chance against the Blizzard of 1888, which bludgeoned the East Coast from the Chesapeake Bay up to Maine. After three days, some places were buried in up to 50 inches of snow, and high winds caused drifts up to 40 feet tall to form. The plow-pulling horses, like everyone else, had no choice but to stay inside and wait for the snow to melt. Cities in the region learned a valuable lesson about preparation, and the following year many implemented measures like hiring more plows and giving them assigned routes, and sending the plows out to start clearing the roads in the early stages of the storm.

Blown Away

The Jull Centrifugal Snow Plough. Photo Courtesy of Made In Canada

Around the same time, on the other side of the country, the rotary snowplow—or as we know it, the snow blower—was getting its start in an unlikely place far removed from the suburban driveways where they're now normally seen. In the Canadian West, railroad men were having a hard time keeping their tracks clear of snow. The railroad snowplows used back east and on the prairies were the wedge-shaped cow-catcher type that pushed the snow to the sides of the track, and they just didn't work in the deep, heavy snow of the western mountains.

J.W. Elliott, a Toronto dentist, had been tinkering with a plow design he thought might work well on a train. His plow had a rotary engine that drove a wheel rimmed with flat blades. As the plow went down the track, snow collected in a housing on the plow and then got funneled up to the blades, which tossed the snow out through an opening at the top of the housing. The railroads passed on it, but Elliot persisted. He hooked up with inventor Orange Jull to improve the design and commission a full-scale working model. The next winter, they convinced the Canadian Pacific Railroad to road-test the new plow on its line near Toronto. The plow cleared the track easily, tossing snow as far as 200 feet out of the way, and the railroad managers were impressed enough to buy eight plows and put them to work. Over the few decades, snowblowers got cheaper, smaller, and easier to use, with truck-mounted models and, eventually, human-powered ones for home use hitting the market.

Car-Plow

Photo Courtesy of the National Archives of Norway

As automobiles replaced horses and carriages on the roads of the U.S., the snow problem got flipped on its head. It wouldn't be enough to clear the alleys and pack down the snow on the main roads anymore. Cars required dry, safe streets. Motorized salt spreaders were introduced, but they often didn't do enough, and urban sprawl meant most cities were just too big for horse-drawn plows to clean all the streets. In the early 1920s, Norwegian brothers Hans and Even Overaasen and New Yorker Carl Frink independently came up with designs for car-mounted snow plows. These were, apparenty the perfect solution to the modern snow problem, and the company Frink started is still producing plows today.

As for the snow removal tool the average Joe is most familiar with, 100-plus patents have been granted for snow shovel designs since the 1870s. One of the first designs that hit upon the "scrape and scoop" combo was invented in 1889 by—get this—a woman named Lydia Fairweather.

This post originally appeared in 2012.

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iStock // Ekaterina Minaeva
technology
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Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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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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Stephen Missal
crime
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New Evidence Emerges in Norway’s Most Famous Unsolved Murder Case
May 22, 2017
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A 2016 sketch by a forensic artist of the Isdal Woman
Stephen Missal

For almost 50 years, Norwegian investigators have been baffled by the case of the “Isdal Woman,” whose burned corpse was found in a valley outside the city of Bergen in 1970. Most of her face and hair had been burned off and the labels in her clothes had been removed. The police investigation eventually led to a pair of suitcases stuffed with wigs and the discovery that the woman had stayed at numerous hotels around Norway under different aliases. Still, the police eventually ruled it a suicide.

Almost five decades later, the Norwegian public broadcaster NRK has launched a new investigation into the case, working with police to help track down her identity. And it is already yielding results. The BBC reports that forensic analysis of the woman’s teeth show that she was from a region along the French-German border.

In 1970, hikers discovered the Isdal Woman’s body, burned and lying on a remote slope surrounded by an umbrella, melted plastic bottles, what may have been a passport cover, and more. Her clothes and possessions were scraped clean of any kind of identifying marks or labels. Later, the police found that she left two suitcases at the Bergen train station, containing sunglasses with her fingerprints on the lenses, a hairbrush, a prescription bottle of eczema cream, several wigs, and glasses with clear lenses. Again, all labels and other identifying marks had been removed, even from the prescription cream. A notepad found inside was filled with handwritten letters that looked like a code. A shopping bag led police to a shoe store, where, finally, an employee remembered selling rubber boots just like the ones found on the woman’s body.

Eventually, the police discovered that she had stayed in different hotels all over the country under different names, which would have required passports under several different aliases. This strongly suggests that she was a spy. Though she was both burned alive and had a stomach full of undigested sleeping pills, the police eventually ruled the death a suicide, unable to track down any evidence that they could tie to her murder.

But some of the forensic data that can help solve her case still exists. The Isdal Woman’s jaw was preserved in a forensic archive, allowing researchers from the University of Canberra in Australia to use isotopic analysis to figure out where she came from, based on the chemical traces left on her teeth while she was growing up. It’s the first time this technique has been used in a Norwegian criminal investigation.

The isotopic analysis was so effective that the researchers can tell that she probably grew up in eastern or central Europe, then moved west toward France during her adolescence, possibly just before or during World War II. Previous studies of her handwriting have indicated that she learned to write in France or in another French-speaking country.

Narrowing down the woman’s origins to such a specific region could help find someone who knew her, or reports of missing women who matched her description. The case is still a long way from solved, but the search is now much narrower than it had been in the mystery's long history.

[h/t BBC]

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