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Analyzing Social Networks of Colonial Boston Revolutionaries with the Wolfram Language

As the Fourth of July approaches, many in America will celebrate 241 years since the founders of the United States of America signed the Declaration of Independence, their very own disruptive, revolutionary startup. Prior to independence, colonists would celebrate the birth of the king. However, after the Revolutionary War broke out in April of 1775, some colonists began holding mock funerals of King George III. Additionally, bonfires, celebratory cannon and musket fire and parades were common, along with public readings of the Declaration of Independence. There was also rum. Today, we often celebrate with BBQ, fireworks and a host of other festivities. As an aspiring data nerd and a sociologist, I thought I would use the Wolfram Language to explore the Declaration of Independence using some basic natural language processing. Using metadata, I'll also explore a political network of colonists with particular attention paid to Paul Revere, using built-in Wolfram Language functions and network science to uncover some hidden truths about colonial Boston and its key players leading up to the signing of the Declaration of Independence.
Swede White, Public Relations Manager
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Create a Tracker to Analyze Gas Mileage Using Wolfram Tech

When I first started driving in high school, I had to pay for my own gas. Since I was also saving for college, I had to be careful about my spending, so I started manually tracking how much I was paying for gas in a spreadsheet and calculating how much gas I was using. Whenever I filled my tank, I kept the receipts and wrote down how many miles I'd traveled and how many gallons I'd used. Every few weeks, I would manually enter all of this information into the spreadsheet and plot out the costs and the amount of fuel I had used. This process helped me both visualize how much money I was spending on fuel and manage my budget. Once I got to college, however, I got a more fuel-efficient car and my schedule got a lot busier, so I didn't have the time to track my fuel consumption like this anymore. Now I work at Wolfram Research and I'm still really busy, but the cool thing is that I can use our company technology to more easily accomplish my automotive assessments.
Andrew Steinacher, Lead Developer, Wolfram|Alpha Scientific Content
Computation & Analysis

Brain, Neurons, Cognition: Computational Neuroscience

As the next phase of Wolfram Research's endeavor to make biology computable, we are happy to announce the recent release of neuroscience-related content. The most central part of the human nervous system is the brain. It contains roughly 100 billion neurons that act together to process information, subdivided functionally and structurally into areas specialized for certain tasks. The brain's anatomy, the characteristics of neurons and cognitive maps are used to represent some key aspects of the functional organization and processing abilities of our nervous system. Our new neuroscience content will give you a sneak peek into the amazing world of neuroscience with some facts about brains, neurons and cognition.
Keiko Hirayama, Wolfram|Alpha Developer, Wolfram|Alpha Scientific Content
Education & Academic

New Books on Applications of the Wolfram Language

We're always excited to see new books that illustrate applications of Wolfram technology in a wide range of fields. Below is another set of recently published books using the Wolfram Language to explore computational thinking. From André Dauphiné's outstanding geographical studies of our planet to Romano and Caveliere's work on the geometric optics that help us study the stars, we find a variety of fields served by Wolfram technology.
Michael Gammon, Blog Administrator, Document & Media Systems
Computation & Analysis

How Many Animals and Arp-imals Can One Find in a Random 3D Image?

And How Many Animals, Animal Heads, Human Faces, Aliens and Ghosts in Their 2D Projections?

Introduction

In my recent Wolfram Community post, "How many animals can one find in a random image?," I looked into the pareidolia phenomenon from the viewpoints of pixel clusters in random (2D) black-and-white images. Here are some of the shapes I found, extracted, rotated, smoothed and colored from the connected black pixel clusters of a single 800x800 image of randomly chosen, uncorrelated black-and-white pixels.
Michael Trott, Chief Scientist, Wolfram|Alpha Scientific Content
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Analyzing and Translating an Alien Language: Arrival, Logograms and the Wolfram Language

If aliens actually visited Earth, world leaders would bring in a scientist to develop a process for understanding their language. So when director Denis Villeneuve began working on the science fiction movie Arrival, he and his team turned to real-life computer scientists Stephen and Christopher Wolfram to bring authentic science to the big screen. Christopher specifically was tasked with analyzing and writing code for a fictional nonlinear visual language. On January 31, he demonstrated the development process he went through in a livecoding event you can watch on YouTube.
Michael Gammon, Blog Administrator, Document & Media Systems
Best of Blog

Exploring a Boxing Legend’s Career with the Wolfram Language: Ali at 75

Muhammad Ali (born Cassius Marcellus Clay Jr.; January 17, 1942--June 3, 2016) is considered one of the greatest heavyweight boxers in history, with a record of 56 wins and 5 losses. He remains the only three-time lineal heavyweight champion, so there's no doubt why he is nicknamed "The Greatest." I used the Wolfram Language to create several visualizations to celebrate his work and gain some new insights into his life. Last June, I wrote a Wolfram Community post about Ali's career. On what would have been The Greatest's 75th birthday, I wanted to take a minute to explore the larger context of Ali's career, from late-career boxing stats to poetry. First, I created a PieChart showing Ali's record:
Jofre Espigulé-Pons, Machine Learning
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