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September 2008 Archives

September 8, 2008

Intro: Graph Theory - Class Notes

Elements:
Node:a connection point in the network; unit of a network
Edge:connection btw nodes ( links?)
Degree: the incoming connections that come to a node

Represent Relationships:

Direction: uni or bidirectional- use arrows
Weight: what is more important

Types of Networks:
Transmission
Interaction
Atributional
Affiliation
konigsbergbridgesweb.gif



Graph Theory: Euler's Konigsberg Bridges

Saw the bridges problem as a graph, a collection of nodes connected by links. Land areas are nodes and the bridges links.
" Graphs and networks have properties, hidden in their construction, that limit or enhance our ability to do things with them... Small changes in the topology, affecting only a few of the nodes or links, can open up hidden doors, allowing new possibilities to emerge"

First Assignment : Sketching Networks

Network: Boring Days
(mapping places I inhabit during school heavy work days) (coming soon)

Directional Network: I love you, I love you not
( mapping love relationships)
(coming soon)

petra.jpg

Weight Network: Everyday movements and actions
(mapping actions of one day)

September 10, 2008

Examples: Inter Discommunication Machine

inter.jpg


This is one of my favorites projects that I had experience in terms of interactive art. Why? Because it was the project that made me experience something that we don't experience in our everyday life in terms of perception: see my self, see me outside of my body ( a bit trip mode but amazing ) and experience the feel of the sense of my body at the same time that i was seeing by body walking around in my front. It was scary but an amazing experience.

Two players wear head-mounted video cameras and backpack transmitters with wings. Incredibly, out of this clunky gear springs a delightful, futuristic play world. The most fantastic element of this interactive paradise is its visual trickery. Each player views his or her own image retransmitted through the other player's headgear.

"Once in his world, our old standards and perceptions become mere illusions that we can manipulate and enjoy as we will. "

link

September 16, 2008

Conflux

Wildernets are portable mesh structures that create experiences of wilderness in public spaces.
by Doris Cacoilo, Mouna Andraos & Sonali Sridhar

mouna1.jpg

mouna2.jpg


mouna3.jpg

LIght Mobs by Jerry
decoding

Inquisitive Devices by Jonah Brucker-Cohen
johan.jpg


botanicalls.jpg

park.jpg


map2.jpg

map3.jpg

map4.jpg

swing1.jpg

swing2.jpg

Second Assignment : Typologies of Networks

Decentralized Network:
my_desktop

desktop.jpg

desktop_applet.jpg

desktop1_applet.jpg


links: Graph ML | Applet

Distributed Network:
BabelTree + Circuit

babelcircuit1.jpg

circuit1_applet.jpg

links: Graph ML | Applet

babelcircuit.jpg

circuit2_applet.jpg

links: Graph ML | Applet

Fully-Connected Network:
my best friends

friends.jpg

friends_applet.jpg

links: Graph ML | Applet

100 Nodes Network:
my_desktop_one_step_beyond

desktop100.jpg

desktop100_1.jpg


links:
Graph ML file | Applet

September 18, 2008

Week 2 -Unintentional actions of your body

For this week assignment I decided to measure how many times I smile during my everyday. I think I am very conscious that I smile a lot but maybe too much??

Picture%209.png

Let's see. One way to measure the smile and facial expressions is using video tracking but I wanted to think of a sensor that allowed me to do it in another way. I choose a stretch sensor that measures changes in resistance ( variable resistor) if pushed/ stretch. The more stretched, higher is the resistance. It seemed for me that its use was more as an experience that a possible solution. ( and it's true!!). Not perfect at all but i got some results.

First I measured the resistance of the sensor using a multimeter in order to know how much of resistance I should use for the pull-down(up) resistor. The sensor that I used was giving me values which range(max, min) was very small but I decided to go on and experiment.

On the Arduino code, I used a smoothing (average of 20 readings) since the values of the readings of the sensor were fluctuating a lot.

I send the data from the sensor through serial to processing to demonstrate visually the act of smiling. After a while and passing through some small problems (mapping the values) I got a satisfied result :), even if the range is very small... (not enough significant difference btw min and mx values - normal state and smiling)

Picture%2010.png


Arduino Code:

int analogPin = 3;
int sensor;

#define NUMREADINGS 30
int readings[NUMREADINGS]; // the readings from the analog input
int index = 0; // the index of the current reading
int total = 0; // the running total
int average = 0; // the average


void setup() {
Serial.begin(9600);
for (int i = 0; i < NUMREADINGS; i++){
readings[i] = 0; // initialize all the readings to 0
}

}

void loop()
{
sensor = analogRead(analogPin)/2;

total -= readings[index]; // subtract the last reading
readings[index] = sensor; // read from the sensor
total += readings[index]; // add the reading to the total
index = (index + 1); // advance to the next index
if (index >= NUMREADINGS) // if we're at the end of the array...
index = 0; // ...wrap around to the beginning
average = total / NUMREADINGS; // calculate the average
Serial.print(average,BYTE); // send it to the computer (as ASCII digits)
}

Processing Code:

import processing.serial.*;
Serial myPort;
float sensor;

void setup(){
size(400,400);
println(Serial.list());
String portname = Serial.list()[0];
myPort = new Serial(this, portname, 9600);
sensor = 230;
}

void draw(){
background(255);
smooth();
fill(255,0,200);
noStroke();
ellipseMode(CENTER);
ellipse(200,200,350,350);
fill(0);
rect(120,150,30,30);
rect(250,150,30,30);
noFill();
stroke(0);
strokeWeight(20);
strokeCap(SQUARE);
bezier(80,230,120,sensor,280,sensor,320,230);

//mouseY 371(smile) - 250 ( liso) max = 374 initial position = 230
}

void serialEvent(Serial myPort) {
int sensorInput = myPort.read();
println(sensorInput);
sensor = map(sensorInput,88,95,230,371);
// VER OS VALORES QUE ESTAO A DAR E MUDAR 88 e 95
if(sensor < 230){
sensor = 230;
}
if ( sensor > 371){
sensor = 371;
}
println("sensor" + sensor);
}


September 22, 2008

Third Assignment: Centrality

3.png

links: Graph ML | Applet

September 29, 2008

Forth Assignment - Distance

To do this assignment I did another network - of cities in Portugal- just as an exercise

cities.png


Part 1 - Betweenness centrality

Me::Lisbon, Porto, Leiria
Computer:: Lisbon 36, Leiria 28, Porto 12

cities_1.png

links: Graph ML | Applet


Part 2 - Remove nodes or edges - Betweenness centrality

cities_2.png

links: Graph ML | Applet

Part 3 - Merge your network with a friend’s network - Amazon Network

amazon.png

links: Graph ML | Applet

About September 2008

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