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6 Tyrannical Bosses Far Worse Than Yours

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We've all had those days (weeks"¦ months"¦) at work. Nothing seems to go right. Anything that can possibly go wrong does go wrong. Stuff you didn't even know could go wrong goes wrong. But before you throw in the towel, check out these tyrannical bosses and think to yourself, "At least I haven't been beheaded"¦ yet"¦"

1. Faye & Ray Copeland

When I retire, I look forward to traveling, spending a lot of time volunteering at a no-kill animal shelter, writing"¦ the usual stuff. Faye and Ray Copeland, however, decided that when they retired they would become serial killers. From 1986 to 1989, the elderly couple hired workers to help them around their farm in Missouri. After being tipped off by a former neighbor, police searched the farm and found five bodies buried. Faye insisted she was innocent, but evidence against her included a list in her handwriting of farmhands hired "“ 12 of them had X's scrawled next to their names. Of those 12, five of them were found dead. Police also found a cozy quilt inside the house made of the clothing of the men the Copelands had killed. Ray and Faye were the oldest couple ever sentenced to death in the United States at the ages of 75 and 69 respectively.

2. Elizabeth Báthory

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No matter how good the pay was at Elizabeth Báthory's castles, it wasn't worth it: the Hungarian countess killed hundreds of girls and women, many who were employed as maids and servants on her property. She didn't just kill her victims, oh no. She tortured them first. During her trials, it was discovered that the methods she used to kill included starving, freezing, beating, burning and biting. Oddly, though, she was never sentenced to death. Her accomplices were, but Elizabeth was merely bricked up inside of a room at her house for the rest of her life. A small slit was left open so she could receive food. She was put under house arrest at the end of 1610; she died in August of 1614.

3. Rolandas Milinavicius

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After reading this you might think twice about asking for a raise this year. In July 2007, a Georgia business owner shot and killed his only two employees when they asked for a little more compensation on their paychecks. Rolandas Milinavicius told police that he was stressed out because the business was accruing a lot of debt and the talk about raises just pushed him over the edge. I would assume that legal fees and not having an income at all due to being in prison would probably hamper his finances more than anything else he could have done. I could be wrong though; I've never owned a business.

4. Henry Clay Frick

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Back in 1892, Henry Clay Frick was not a boss you wanted to cross. Frick and his business partner Andrew Carnegie ended their working relationship when Frick reacted a little"¦ rashly"¦ to the Homestead Steel Strike. In 1892, a labor strike impacted the Homestead Works of the Carnegie Steel Company. Frick was staunchly anti-union and thought he would thwart picketing workers by having Pinkerton agents access the grounds via the river. When the agents got close enough, they fired into the crowd which was enough to start a full-blown riot. By the time the chaos was broken up by the state militia, several men were killed and many were wounded. Thanks, boss.

5. Henry VIII

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It's common knowledge that Henry VIII had no qualms with having people close to him killed "“ wives, employees, friends, contemporaries, whatever. He had Sir Thomas More beheaded when More dared to disagree with King Henry's religious ideas. Prior to his death, More had served as Henry's Lord Chancellor. Another employee was the king's minister, Thomas Cromwell. He supported Henry when he was tired of Anne Boleyn and wanted to marry Jane Seymour. Jane died soon after childbirth and Cromwell quickly urged Henry to marry Anne of Cleves. The marriage was a disaster. Cromwell divorced them, but being of no further used to Henry, he was sentenced to death for treason. The young executioner hacked at Cromwell's head three times before he finally succeeded in beheading him. After that, Cromwell's head was boiled and place on a spike on London Bridge.

6. Leona Helmsley

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Obviously real estate mogul Leona Helmsley would have been pretty horrifying to work for "“ she wasn't called the Queen of Mean for nothing. Stories of her ruthlessness abound. Lawyer Alan Dershowitz said he once had breakfast with Leona at one of the Helmsley hotels and the waiter brought him a cup of tea with a tiny bit of water spilled on the saucer. Alan says Leona grabbed the cup from him and smashed it on the floor, then demanded that the waiter get down on his hands and knees and beg for his job. Some stories claimed she would fire maids on the spot if she found so much as a crooked lampshade in a hotel room. One maid, when working through lunch, snagged an apple from the kitchen to quell her hunger. Of course, Leona fired her.

See, your job really isn't that bad. Or is it? What are your bad boss horror stories?

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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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