Category: Script Library
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Rijndael / AES (128 bit) in VB.net, PHP, Python
Being able to transport encrypted data is important in some of my projects at work. One-way hashes using MD5 usually suffice for most encryption purposes but Symmetric Encryption algorithms are important for encrypting and then decrypting data. For this, we use the Rijndael and AES algorithm in a few different languages.
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Removing the BuddyPress Admin Bar
A short script to remove that pesky BuddyPress Admin Bar in Wordpress 3.4.2 and BuddyPress 1.6.1
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Cosine Similarity in MS SQL
Cosine similarity measures the angle between two vectors and can be used to perform similarity between text strings. In the following code, the two input strings are vectorized and the similarity is returned as a floating point value between 0 and 1.
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Rewiring the RSS icon link for Platform
Step-by-step instructions for rewiring where your RSS link icon points to within the Platform theme (by PageLines) for Wordpress (Updated 2012-06-21)
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Estimating Lyapunov Spectra of ODEs using Python
Python code is shown that estimates the Lyapunov spectra for the Rossler and Lorenz systems. This code is written in a way that makes it adaptable for other continuous-time systems.
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Modelling Chaotic Systems using Support Vector Regression and Python
Support Vector Regression is a technique in machine learning that can be used to model chaotic data. A program is shown to work on Delayed Henon Map data.
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Automatically Link Text using VB.Net
Automatically add HTML to link any words with http:// or https:// within text using this VB.net script
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Generating Poincaré Sections and Return Maps
Using the iterative 4-th order Runge-Kutta method as described here, we can create low dimensional slices of the system’s attractor known as Poincare Sections, Return maps, or Recurrence maps. We will use the Rossler attractor for this example, with a, b, and c set to 0.2, 0.2, and 5.7, respectively. Poincare sections are important for visualizing…
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Generating time series for Ordinary Differential Equations
We can produce a time series from ordinary differential equations by solving the equations using the iterative 4-th order Runge-Kutta method and plugging each of the solutions back into the equations.