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Mississippi’s Phantom Barber of Pascagoula

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If you want to learn about someplace, you can always pick up a textbook. But if you want to get to know a place, you're going to have to dig a little deeper. And what you find there might be a little strange. The Strange States series will take you on a virtual tour of America to uncover the unusual people, places, things, and events that make this country such a unique place to call home.

This week we’re in the Magnolia State—Mississippi—the home of Jim Henson, B.B. King, and The King himself, Elvis Presley.

In the early days of World War II, warship construction helped the tiny fishing town of Pascagoula, Mississippi grow from a population of 5000 to nearly 15,000, seemingly overnight. Although a larger population meant an economic boost for local businesses, it also meant the police force was struggling to keep the larger population in line. Aside from the expected uptick in drunken brawls and burglaries, there was one menace wandering the streets that kept people awake at night—The Phantom Barber of Pascagoula.

His reign of terror began on Friday, June 5, 1942, when young Mary Evelyn Briggs and Edna Marie Hydel at the Our Lady of Victories convent were shocked to find a man climbing out of their bedroom window. The two girls were unharmed, although each of them was missing a lock of hair. Briggs later described the man as “sorta short, sorta fat, and he was wearing a white sweatshirt.”

The Barber struck again on Monday at the Peattie home, where he cut a slit in the window screen and crawled inside to snip the hair of little 6-year old Carol Peattie as she lay sleeping next to her twin brother. This time the Phantom Barber had accidentally left a clue—a sandy footprint near the window.

The next incident occurred the following Friday night, when the home of Mr. and Mrs. Heidelberg was invaded. Like before, the window screen was cut and the invader came inside. But instead of taking his typical trophy tuft, he used a heavy iron bar to attack the couple, taking out some of Mrs. Heidelberg’s front teeth and knocking her husband unconscious. Unfortunately, it all happened so quickly that neither could describe their attacker.

The police deputized six men and brought in bloodhounds to pick up a scent. The dogs followed the trail to a pair of bloodstained gloves in the nearby woods, but that was as far as they got. The police theorized that the assailant might have stashed a bicycle in the woods to make his escape.

The final attack came on a Sunday night, when the hair of Mrs. R.R. Taylor was cut. She said she had been woken up by “something with a sickening smell” passing over her nose. The next thing she remembered, was waking up and getting violently ill. Police later determined the Barber must have cut the window screen, stuck a chloroform-soaked rag over Taylor’s face, and then collected his lock of hair.

For two more months, residents lived in fear, though no additional Barber attacks occurred. Then, suddenly, police announced they had caught the Phantom Barber—William Dolan, a 57-year old chemist. Dolan had sparred with Mr. Heidelberg’s father, a local magistrate, over a legal issue, so it was thought he attacked the couple to seek revenge. Although this didn’t directly tie him to the Phantom Barber invasions, police claimed a large bundle of human hair was found behind his home. The FBI later identified some of the hair as belonging to Carol Peattie, the Barber’s youngest victim.

Despite his insistence of innocence, Dolan was quickly found guilty of attempted murder and sentenced to 10 years in prison. He was never charged with any crimes related to the hair snatching incidents, but in the eyes of the public he was the Phantom Barber.

Six years later, Mississippi Governor Fielding Wright reviewed the case and asked that Dolan take a lie-detector test. Upon passing, Dolan was given a limited suspended sentence and then eventually set free in 1951.

In hindsight, some modern historians wonder if Dolan was guilty of any crime at all. He was arrested at a time when the public was in a state of panic and the police were desperate to close the Phantom Barber cases. It would have been very easy to plant the hair during Dolan’s arrest and then tamper with the evidence sent to the FBI for analysis. In addition, Dolan was a known German sympathizer and considered a traitor by many townsfolk, so his arrest for the attack on the Heidelbergs was met with little resistance; good riddance to bad rubbish, as the old saying goes. Was Dolan the Phantom Barber of Pascagoula, or a patsy who took the fall to quell the anxieties of a small town? We may never know for sure.

Have the scoop on an unusual person, place or event in your state? Tell me about it on Twitter (@spacemonkeyx) and maybe I’ll include it in a future edition of Strange States!

Peruse the whole Strange States series here.

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iStock // Ekaterina Minaeva
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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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Name the Author Based on the Character
May 23, 2017
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