Ed's Big Plans

Computing for Science and Awesome

I’m bringing back my site

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So much has changed in the last five years.

I’ve finished all of the requirements needed to graduate earlier this year. I’ve decided it’s time to bring my site back, and populate it with the coolest stuff I learned in the last few years.

Eddie Ma

April 8th, 2018 at 8:41 am

Posted in Life

On SSL/TLS and HTTPS — Briefings for my Computer Security class

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Brief: This is a technical briefing I made for fellow students in a Computer Security class (Winter 2011) about Secure Socket Layer [SSL] (now Transport Layer Security [TLS]). These briefings fit in nicely since it came after Dr. Obimbo explained the number theory behind RSA (modulus prime exponentiation). I went to the primary source on this topic to write this document: thanks to the Internet Engineering Task Force. I’ve posted this document as a consumable reference for anyone who needs it.

>>> Download: A Network Security Spotlight on SSL/TLS and HTTPS (pdf) <<<

Figure $_: A Schematic of the SSL/TLS Handshaking Procedure.

This document is licensed under Creative Commons Attribution 3.0 Unported. The enclosed figures are further released into the public domain.

Eddie Ma

February 16th, 2012 at 1:29 pm

Fuzzy c-means for greylevel image segmentation

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Here’s a script I threw together to do grey-level segmentation using fuzzy c-means. This appeared as a small part of a project in the image processing course I took. The algorithm deployed was really a proof of concept meant to replicate and verify the results of another author — as such, I don’t recommend ever using fuzzy c-means for this task as it’s pretty inefficient. This software will handle any number of grey-level-segments you desire, but I recommend eight as a maximum.

The code and course project paper are originally dated April 20th, 2011.

>>> Download: FCMProjectPaper.pdf | FCMProject.tgz <<<

( Requires pypng — Python PNG encoder/decoder )

Here are the examples included in the above archive. I like pictures.

Sunny in 8-bit greyscale, 3-bit greyscale, 2-bit greyscale.

Auryo in 8-bit greyscale, 3-bit greyscale, 2-bit greyscale.

Enjoy 😀

Eddie Ma

December 20th, 2011 at 11:21 pm

My talk at Barcode of Life, Adelaide (2011)

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I’ve just finished my presentation in Adelaide. This is the first real biology-heavy conference I’ve been to. Sujeevan has brought me along with the BOLD team from BIO in order to present my work — and more importantly — to acquire some resolution about the barcoding culture and its biological significance. The Consortium for The Barcode of Life (CBOL) co-hosted this event with many biodiversity parties in Australia. Another huge group present was the International Barcode of Life (iBOL) project. The Barcode of Life Conference is held every other year and is attended by researchers interested in the concerted international barcoding effort. I presented my preliminary findings with a data analysis session and had excellent feedback — it’s pretty clear where to go next with my thesis! My talk describes the first steps to automating barcode (contig-like) assembly from ab1 sequencer trace files. This talk describes the present need for automation, trends that we can readily detect in currently assembled data and most importantly — detectable patterns in how human experts perform manual barcode assembly.

The full name of the conference is Fourth International Barcode of Life Conference.

>>> Download: ( pdf: EddieMaBOL2011Adelaide.pdf | zip: EddieMaBOL2011Adelaide.pdf.zip ) <<<

Slides 6, 16, 24 from my presentation — The need for automation; Compositional bias and human edits [null hypothesis]; Where are human edits occurring [in Lepidoptera]?

This has been a very enjoyable conference 😀

Eddie Ma

December 3rd, 2011 at 5:12 pm

My talk at Complex Adaptive Systems, Chicago (2011)

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I’ve just returned from the Complex Adaptive Systems conference on Wednesday after an eight hour drive — well, most of the driving was done by Dr. Obimbo and Haochen. I presented my paper An evolutionary computation attack on one-round TEA. This paper is built on top of my course project in Computer Security (University of Guelph, Winter 2011). This is my first cryptanalysis paper, and is an aside to the bioinformatics focus of my thesis.

My slides introduce Tiny Encryption Algorithm (TEA) pretty well, along with Genetic Algorithm (GA) and Harmony Search (HS). The slides detailing the results aren’t quite as self-explanatory, but are bearable since the theme is fairly easy to establish: simpler keys are easier to break than more complicated ones.

>>> Download: CAS2011Chicago.pdf — my presentation from Chicago. <<<

I might look at cryptanalysis again in future — but I’ll certainly use Evolutionary Computation (EC) again. It’s just too readily available in my toolkit, and is far too easy to deploy. One of the major lessons of this project that became very clear through during discussion with the audience is that the operators that are part of an EC algorithm should reflect the kind of problem we’re trying to solve. This might seem obvious at first, but I think it’s more subtle than that. For this project, HS enabled the EC to probe a keyspace with many repetitions — something that GA operators alone didn’t provide us.

In general however, the solution space is lumpy enough that using ECs against stronger encryption schemes is just not viable — unless the EC had some magic to overcome the linearly inseparable lumps. I haven’t yet met such an operator and am not convinced one way or another about its existence. I’ll certainly introduce you if I ever do bump into it 😛

Partial Derivatives for Residuals of the Gaussian Function

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I needed to get the partial derivatives for the residuals of the Gaussian Function this week. This is needed for a curve fit I’ll use later. I completely forgot about Maxima, which can do this automatically — so I did it by hand (Maxima is like Maple, but it’s free). I’ve included my work in this post for future reference. If you want a quick refresh on calculus or a step-by-step for this particular function, enjoy :D. The math below is rendered with MathJax.

The Gaussian Function is given by …

$$ f(x) = ae^{-\frac{(x-b)^2}{2c^2}} $$

  • a, b, c are the curve parameters with respect to which we differentiate the residual function
  • e is Euler’s number

Given a set of coordinates I’d like to fit (xi, yi), i ∈ [1, m], the residuals are given by …

$$ r_i = y_i – ae^{-\frac{(x_i-b)^2}{2c^2}} $$

We want to get …

$$ \frac{\partial{r}}{\partial{a}}, \frac{\partial{r}}{\partial{b}}, \frac{\partial{r}}{\partial{c}} $$

Read the rest of this entry »

Eddie Ma

October 10th, 2011 at 11:40 am