Wolfram Computation Meets Knowledge

Date Archive: 2014 November

Computation & Analysis

Benedict Cumberbatch Can Charm Humans, but Can He Fool a Computer?

The Imitation Game, a movie portraying Alan Turing’s life (who would have celebrated his 100th birthday on Mathematica's 23rd birthday---read our blog post), was released this week, which we've been looking forward to. Turing machines were one of the focal points of the movie, and we launched a prize in 2007 to determine whether the 2,3 Turing machine was universal. So of course, Cumberbatch's promotional video where he impersonates other beloved actors reached us as well, which got me wondering, could Mathematica's machine learning capabilities recognize his voice, or could he fool a computer too?
Education & Academic

Deck the Halls with Lines of Coding

Thanksgiving is just around the corner, and that means you only have five weeks left to knock out your holiday shopping. Never fear, Wolfram is delivering amazing deals to customers across the globe, including North and South America, Australia, and parts of Asia and Africa to inspire a whole new year of computational creativity.
Computation & Analysis

Removing Haze from a Color Photo Image Using the Near Infrared with the Wolfram Language

For most of us, taking bad pictures is incredibly easy. Band-Aid or remedy, digital post-processing can involve altering the photographed scene itself. Say you're trekking through the mountains taking photos of the horizon, or you're walking down the street and catch a beautiful perspective of the city, or it's finally the right time to put the new, expensive phone camera to good use and capture the magic of this riverside... Just why do all the pictures look so bad? They're all foggy! It's not that you're a bad photographer---OK, maybe you are---but that you've stumbled on a characteristic problem in outdoor photography: haze. What is haze? Technically, haze is scattered light, photons bumped around by the molecules in the air and deprived of their original color, which they got by bouncing off the objects you are trying to see. The problem gets worse with distance: the more the light has to travel, the more it gets scattered around, and the more the scene takes that foggy appearance. What can we do? What can possibly help our poor photographer? Science, of course. Wolfram recently attended and sponsored the 2014 IEEE International Conference on Image Processing (ICIP), which ended October 30 in Paris. It was a good occasion to review the previous years' best papers at the conference, and we noticed an interesting take on the haze problem proposed by Chen Feng, Shaojie Zhuo, Xiaopeng Zhang, Liang Shen, and Sabine Süsstrunk [1]. Let's give their method a try and implement their "dehazing" algorithm. The core idea behind the paper is to leverage the different susceptibilities of the light being scattered, which depend on the wavelength of the light. Light with a larger wavelength, such as red light, is more likely to travel around the dust, the smog, and all the other particles present in the air than shorter wavelength colors, like green or blue. Therefore, the red channel in an image carries better information about the non-hazy content of the scene. But what if we could go even further? What prevents us from using the part of the spectrum slightly beyond the visible light? Nothing really---save for the fact we need an infrared camera. Provided we are well equipped, we can then use the four channels of data (near infrared, red, green, and blue) to estimate the haze color and distribution and proceed to remove it from our image.
Announcements & Events

2014 Wolfram Innovator Award Winners

Now in its fourth year, the Wolfram Innovator Awards are an established tradition and one of our favorite parts of the annual Wolfram Technology Conference. This year, Stephen Wolfram presented seven individuals with the award. Join us in celebrating the innovative ways the winners are using Wolfram technologies to advance their industries and fields of research.
Computation & Analysis

Fractal Fun: Tweet-a-Program Mandelbrot Code Challenge

This week Wolfram will be celebrating Benoit Mandelbrot's birthday and his contributions to mathematics by holding a Tweet-a-Program challenge. In honor of Mandelbrot, tweet us your favorite fractal-themed lines of Wolfram Language code. Then, as with our other challenges, we'll use the Wolfram Language to randomly select winning tweets (along with a few of our favorites) to pin, retweet, and share with our followers. If you win, we'll send you a free Wolfram T-shirt! In Tweet-a-Program's first few exciting months, we've already seen a number of awesome fractal examples like these:
Computation & Analysis

Announcing the Winners of the 2014 One-Liner Competition

This year's Wolfram Technology Conference once again included the One-Liner Competition, an opportunity for some of the world's most talented Wolfram Language developers to show us the amazing things you can do with tiny pieces of Wolfram Language code. In previous years, One-Liner submissions were allowed 140 characters and 2D typesetting constructs. This year, in the spirit of Tweet-a-Program, we limited entries to 128-character, tweetable Wolfram Language programs. That's right: we challenged them to write a useful or entertaining program that fits in a single tweet. And the participants rose to the occasion. Entries were blind-judged by a panel of Wolfram Research developers, who awarded two honorable mentions and first, second, and third prizes. One honorable mention went to Michael Sollami for his "Mariner Valley Flyby," which takes you on a flight through the terrain of the Mariner Valley on Mars. The judges were greatly impressed by the idea and the effect. Unfortunately, a small glitch in the program is visible at the start of the output, due to an error in the code. Since Michael's submission is right up against the 128-character limit, it would have taken some clever tweaking to fix it.
Products

Using Arduinos as SystemModeler Components

Explore the contents of this article with a free Wolfram SystemModeler trial. With the new, free ModelPlug library for Wolfram SystemModeler, you can connect Arduino boards to simulations in SystemModeler. Arduinos interface easily with input and output components, so you can integrate them into SystemModeler models, for example, to operate lights, run servos, and monitor sensors, switches, and potentiometers. With the ModelPlug library, you can freely mix hardware and software components in your simulations and use the Arduino as a data acquisition board. If you want to follow along, you can download a trial of SystemModeler. It's also available with a student license, or you can buy a home-use license. All hardware used in this blog post can be bought for less than $50.
Best of Blog

Modeling a Pandemic like Ebola with the Wolfram Language

Data is critical for an objective outlook, but bare data is not a forecast. Scientific models are necessary to predict pandemics, terrorist attacks, natural disasters, market crashes, and other complex aspects of our world. One of the tools for combating the ongoing and tragic Ebola outbreak is to make computer models of the virus's possible spread. By understanding where and how quickly the outbreak is likely to appear, policy makers can put into place effective measures to slow transmissions and ultimately bring the epidemic to a halt. Our goal here is to show how to set up a mathematical model that depicts a global spread of a pandemic, using real-world data. The model would apply to any pandemic, but we will sometimes mention and use current Ebola outbreak data to put the simulation into perspective. The results should not be taken as a realistic quantitative projection of current Ebola pandemic.