Original image

Massive Wartime Decoys and Camouflage Operations

Original image

Military units have used camouflage of one kind or another since antiquity. However, with the invention of the airplane and the rise of aerial warfare, camouflage (to hide targets) and decoys (to draw fire away from real targets or to intimidate the enemy) became bigger and bigger. How big? Read on and see.

Starfish Sites

Britain was the target of heavy Luftwaffe bombing long before the U.S. was drawn into World War II. The Germans were fond of nighttime bombing raids, so the British developed Q sites and Starfish sites as decoys. Q sites were areas of lights designed to attract bombs away from military installations such as airfields. The actual sites were under blackout conditions. Starfish sites followed, which were decoys of lights in the countryside that mimicked lights of cities. The earliest site, installed near Bristol in 1940, was code-named Starfish, so the term was used for the other decoy towns that followed.

Operation Bertram

As Field Marshal Montgomery faced Erwin Rommel and his German forces in North Africa in 1942, British Brigadier Dudley Clarke launched Operation Bertram, in which fake equipment and munitions (made with palm fronds, sticks, and fabric) tricked the enemy into thinking the forces were miles from where they actually were. At the same time, the real artillery was hidden under fake supply trucks and other structures that appeared to be either useless or badly-camouflaged dummies. The deception was enhanced with false radio transmissions. German intelligence was convinced that the Allies' attack would come later, from a different direction, and involve at least one more armored division than they actually had. The deception contributed greatly to the victory in the Second Battle of El Alamein.

Ghost Divisions

In the U.S., the the 23rd Headquarters Special Troops was charged with intimidating the German army by convincing them that the Allies had more troops and equipment than they actually had. The 23rd created a "ghost army" of transport vehicles, troop carriers, tanks, and munitions, all made of inflatable balloons, complete with sound effects.

The U.S. Rubber Company even built inflatable airplanes (along with tanks and boats) to draw German fire away from the actual D-Day landing sites.

Lockheed Airplane Factory

Col. John F. Ohmer studied the camouflage and decoy techniques of the British in 1940, and wanted to reproduce them to protect the installations at Pearl Harbor. His proposal was rejected as too expensive. The attack on Pearl Harbor changed all that, and Ohmer was put in charge of a camouflage unit for U.S. targets on the West Coast. Among those targets was the Lockheed airplane factory in Burbank, California. Ohmer enlisted the help of Hollywood set builders and prop designers, as well as many civilian laborers and military personnel, to cover the factory with a fake residential neighborhood

Underneath it all, business went on as usual.

Boeing Factory

The Boeing airplane factory in Seattle also got the fake neighborhood treatment. The women shown are walking on a suburban landscape made of chicken wire and planks, positioned overtop the roof of the factory. Underneath, B-17s were being built for the war effort.

Sham Paris

As impressive and elaborate as the above projects are, they weren't the first of their kind. Airplanes were bombing cities in World War I. In 1917 and 1918, the city of Paris scrambled to build a decoy city, a complete replica of Paris, several miles north of the actual city. Built mostly of wood and fabric, the "Sham Paris" had buildings (homes, factories, and landmarks), streets, a faux railroad, and most importantly, lights. Electrical engineer Fernand Jacopozzi worked out the best combination of colored lights to mimic a working city. Sham Paris was never completed, as construction ceased when the war ended in November of 1918.

Razzle Dazzle Ships

Camouflage at sea is a whole other ball of wax. The reflection of the water, lack of landmarks, movement, and the enemy's technology all combine to make hiding a ship vastly different from land-based disguises. During World War I, German U-Boats fired torpedoes not at the ship itself, but where the ship was expected to be by the time the torpedo got there. By disguising not the ship, but the ship's speed, you could cause those torpedoes to miss their targets. To do this, British naval officer Norman Wilkinson developed Dazzle camouflage to confuse the enemy's eye into miscalculating the size and speed of a target. Forms of this camouflage are still used today.

Original image
iStock // Ekaterina Minaeva
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
Original image
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!

Original image
Nick Briggs/Comic Relief
What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
Original image
Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]