Exciting things I learned and read during the week (11 Oct – 17 Oct) beside my current hard workload of reading papers in my topics for PhD:
How to draw Sierpinski’s curve using code. Math opens my eyes in several things. Here is the wikipedia page explaining Sierpinski’s curve. In the page above, there is also a video clip explaining how to draw Sierpinski’s curve by Eddie Woo. Another person applied code to draw Sierpinski’s curve.
2/ The difference between research and academic lobbying
This has raised a debate, how a research could be more ‘friendly’ towards policy making.
“TOO OFTEN, WE END OUR PAPERS WITH THE PHRASE: ‘WE NEED MORE RESEARCH.’ THIS IS OKAY IN ACADEMIC WRITING, BUT IT’S A DEATH SENTENCE IN POLICY.”
3/ Complexity and traffic games
This article describes how a scientist uses complexity theory to beat with traffic jams in Mexico. People, for a long time, have tried to predict how traffic system works, but this scientist he explained that we cannot predict how long a car will arrive in the destination because there will be many variables, he will have to adapt with the system, based on the interaction of other cars to control his behavior. Therefore, he used a complexity approach by applying interaction, adaptation to make self-organizing traffic lights, which car waits for the instruction from the traffic lights, but traffic lights also depend on car activity through their sensor. However, one thing should be noticed that he mentioned about why these traffic lights could not work in some countries because of politics. This raised some questions in how for engineers, policy makers, politics, academic to collabrate and work more effectively.