Tag: Fall 2015

Computational media is important because it allows one to visualize the unseen. Despite their elegant presentation on paper, equations contain massive amounts of information. For anything beyond the most trivial of cases, understanding how different elements in an equation (or set of interlaced equations) influence the development of a solution is impossible. Computers allow one to solve complicated systems and store the approximate solution. This solution is normally displayed visually, but can be represented in other ways. My final project, for example, is a haptic representation of Gauss’s Law. A user can feel the magnitude of the electric field generated by a point charge by moving his or her hand through space. Computational media provides a means to sense how equations behave. Moreover, the tools of computational media allow one to dynamically change equation parameters and see the results in real time. Most of the time this still involves moving sliders on screen and seeing the changes on screen, but the possibility of integrating some physical interaction exists.

Visualization and other means of representation allows for improved understanding of stationary and dynamical systems by decreasing abstraction. Equations are a compact way of expressing relationships between different quantities, such as electric field and charge distribution, or time and position. One can quickly derive new relationships by playing with the symbols in these equations. However, symbols are not easily grounded in intuition. Computing a numerical solution to the equation governing some physical system is a way of opening up the equation, unfurling it in time and or space. It also assigns values to variables, and functions that act on values to symbolic operators. Abstraction is further decreased by taking the solution, at this point a series of values, and giving it some physical property — vibration amplitude or color for instance. This physical representation of the equation is more natural, thus easier to understand. The power of computational media is the ability to display complex relationships in a more readily human-comprehensible form.

 

First of all, this course has really been an eye-opening one for me. Before I came to college, I’d never imagine myself learning to code and make circuits at the same time. Neither did I know about what’s called “Computational Media”. But now it all starts to make more sense to me. Just as our guest from Istanbul said, people don’t know new media until it is introduced to them. From my own understanding,   Computational Media is indeed future-oriented, but it is also tangible and easily accessible so that we could begin to get the sense of it after only 14 weeks of an intro class.

Continue reading “On Computational Media”

I got my vibrating glove to work! By moving a slider in Processing, a user can change the strength of the vibration felt in the three motors on the glove. You can see a video of the glove working here. Its kind of hard to see/hear the vibrations, but you can definitely feel them. The next step is to get a battery and bluetooth hooked up to this bad boy.

Jackal Radio uses a piece of software called SAM broadcaster to create the radio stream. It has a bunch of built in features which don’t really work. You can only hook up one external input, which means that you have to use an external application to mix input from a variety of sources (mic, line in, turntable) which then gets piped into SAM. One thing we’ve been trying to implement lately is soundbites. You know how radio stations always have their characteristic little soundbite? That’s what we want. Stuff like “Jackal Radio: The galaxy’s only college radio station” or “Jackal Radio: Jackal Radio’s Jackal Radio.” I built a little processing sketch that can play these little bits at the press of a button. I made a GIF to demonstrate this. Check it out! As always, why work on your capstone when you can work on radio stuff?

In this assignment, I made a picture by using processing. The basic idea is to create two layers of images after importing two images.  One image is full of words while the other is Scott’s portrait, the gradients of words sketches outline of the portrait. Then I decided to show all of our names on the portrait of Scott, it would be awesome! Here is the work:)

Continue reading “We love Scott and his Cat :)”

Convolving two functions f and g amounts to dragging one function over another. Computing the convolution of two functions involves computing the integral of the product of the two functions as one is shifted while the other is stationary. There is a cool theorem (the convolution theorem) that states that the convolution of two functions is equal to their product in Fourier space. I leverage this theorem in my processing code to compute the convolution of the webcam feed with a gaussian. The position of the gaussian can be shifted by moving the cursor across the frame. By switching modes, one can increase the standard deviation of the gaussian, which results in less blurring. I made a GIF that demonstrates this functionality.