Notes on codes, projects and everything
To test our understanding in RSA public key cryptosystem, we were being asked to develop a computer program to demonstrate the cryptosystem. The whole system consists of a random number generator, an encoding module that is able to encode characters into numbers, an encryption module as well as decryption module and finally an RSA cryptosystem cracking module.
The program is written in Microsoft® Visual C6, the reason why Visual C6 is being selected is because we wanted to do something simple. There is no GUI being implemented as we wanted to spend more time in enhancing the program.
To generate random number, we used Blum-Blum-Shub random number generator as we found it to be the easiest to implement.
I happened to find a general solution suggestion on a Wikipedia entry when I was browsing the internet around to find a solution to modular exponential problem. The code snippet posted on the wikipedia entry claimed that it came from …
RSA is a cryptosystem …
Folksonomy is a neologism of two words, ’folk’ and ’taxonomy’ which describes conceptual structures created by users [4, 5]. A folksonomy is a set of unstructured collaborative usage of tags for content classification and knowledge representation that is popularized by Web 2.0 and social applications [1, 5]. Unlike taxonomy that is commonly used to organize resources to form a category hierarchy, folksonomy is non-hierarchical and non-exclusive . Both content hierarchy and folksonomy can be used together to better content classification.
So I first heard about Panda probably a year ago when I was in my previous job. It looked nice, but I didn’t really get the chance to use it. So practically it is a library that makes data looks like a mix of relational database table and excel sheet. It is easy to do query with it, and provides a way to process it fast if you know how to do it properly (no, I don’t, so I cheated).
While JSON is a fine data-interchange format, however it does have some limitations. It is well-known for its simplicity, that even a non-programmer can easily compose a JSON file
(but humanity will surprise you IRL). Therefore, it is found almost everywhere, from numerous web APIs, to geospatial data (GeoJSON), and even semantic web (RDF/JSON).
I really don’t know how to start explaining what is a Dragon Curve. However, I find it is interesting enough after finding out that there’s actually a fixed pattern of occurrence. Therefore I spent some time writing a series of scripts to plot the generated fractal into a graph. What I didn’t expect is, the series get really complicated after a while.
One of my recent tasks involving crawling a lot of geo-tagged data from a given service. The most recent one is crawling files containing a point cloud for a given location. So I began by observing the behavior in the browser. After exporting the list of HTTP requests involved in loading the application, I noticed there are a lot of requests fetching resources with a common