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Blog.Hemmings.com

6 People Who Went to Great Lengths for Their Pranks

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Blog.Hemmings.com

Julie Winterbottom is the former editor in chief of Nickelodeon magazine, where she fulfilled her childhood dream of getting paid to write jokes; her book, Pranklopedia: The Funniest, Grossest, Not-Mean Pranks on the Planet! is on sale now. Julie lives in Brooklyn, New York, where she pulls pranks on her boyfriend and cat.

In honor of April Fools’ Day—which is next Monday—here are six people who went to great lengths to pull some one-of-a-kind pranks.

1. A Garden of Mirthly Delights

Hellbrunn.at

Prince Archbishop Markus Sittikus ruled Salzburg from 1612 to 1619. Soon after he ascended the throne, he commissioned a summer palace to be built at the foot of Hellbrunn Mountain. The enormous Italianate mansion was everything you’d expect from a wealthy nobleman—but the garden was another story. Sittikus had the gardens rigged with trick fountains and statues that squirted people with water as they strolled by. A long stone dinner table had nine stools with water nozzles hidden in the seats so Sittikus could give his guests surprise showers. (A tenth stool, reserved for Sittikus, was nozzle-free.) Today Sittikus’s palace is a tourist attraction—and the sprayers still work. So if you end up visiting, watch where you sit.

2. A Rare Breed of Prankster

Feline Historical Foundation

Brian G. Hughes was a New York manufacturer and banker, but according to his 1924 obituary, his true calling was prankster. Hughes liked to hoax prominent people who he believed took themselves too seriously—like the directors of the snooty National Cat Show. In 1895, Hughes bought a stray cat from a hobo for 30 cents, cleaned it up, and a few months later entered it in the show under the name Nicodemus. Hughes told the judges the cat was a rare “Irish Brindle” valued at $3000. Nicodemus won a first prize, at which point Hughes revealed the hoax—and the cat’s real name, Josephine—much to the embarrassment of the judges.

3. Fruit of the Loony

Thinkstock/Bryan Dugan

In 1950, California cartoonist Frank Adams’s wild idea for a prank bore fruit—literally. The National Orange Show had just taken place in San Bernardino, not far from Adams’ home, and there were thousands of oranges left over. Adams managed to get ahold of them and then convinced 25 friends to help him attach all 50,000 oranges to pine trees along a section of the Rim of the World highway. They did the job under cover of night, and the next morning, drivers were amazed to see that the pines trees had magically produced a crop of citrus.

4. All the Way with LBJ

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President Lyndon B. Johnson adored cars and kept a large collection of cherished Lincolns and other vehicles at his Texas ranch. One of his most unusual cars was an Amphicar—it looked like a normal car, but was amphibious and functioned like a motorboat when it entered a body of water. Johnson realized this vehicle was perfect for pranking guests. He would invite his visitors to take a drive around the ranch with him in the blue convertible. When they got to a steep hill at the edge of a lake, Johnson would let the car pick up speed. Then he’d yell, “The brakes don’t work! The brakes won’t hold! We’re going in!” As the car entered the lake, the passengers would panic—until they realized that rather than sinking, they were motoring across the lake. One victim of the prank, Special Assistant to the President Joseph A. Califano, Jr., recalled that his boss teased him later for trying to save his own skin instead of the president’s.

5. A Traffic-Stopping Prank

In 2006, students at Austin High School in Austin, Minnesota engineered a prank that capitalized on the unusual architecture of their school. A busy street separates two buildings on the school’s campus. Students can use the crosswalk or an underground tunnel to get from one building to the other. At an appointed time on the day of the prank, 94 students began filing across the street, using the crosswalk. Then they circled back through the underground tunnel and crossed the street again—and again, and again—creating an endless stream of pedestrians. Traffic was tied up for nearly 10 minutes as cars lined up waiting for the students (including one dressed as a cow and another as a chicken) to finish crossing.

6. Panhandler Party

One evening in August 2012, actor and comedian Gary Lee Mahmoud gave some New York City straphangers the ride of their life. NYC commuters are used to panhandlers coming through the subway cars asking for money or selling candy and other goods. Mahmoud and his co-conspirators took this phenomenon to a hilarious extreme, creating a “panhandler party.” Over the course of four minutes, actors portraying 10 different panhandlers—including an angry Wall Streeter who didn’t get his bonus—invade a single subway car. By the end of the prank, the entire carful of commuters is cracking up.

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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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