The Small World Experiment: How Preferential Attachment Models Our Interconnectedness

 

In the 1960s, psychologist Stanley Milgram conducted a series of experiments to study the average path length between two randomly chosen people in a social network. The results of the experiment showed that the average path length between two people in the United States was only six steps, which is much shorter than what would be expected if the network were randomly connected.

Geographic crime profiling: Analyzing Rossmo's Formula

 

There are many instances where applied mathematics is used to assist criminal investigators. From identifying suspects to analyzing evidence. For a long time I've been interested in the accuracy and reliability of these systems. After all an incorrect result (Type 1 and Type 2 errors) could ruin an innocent person's life or allow a criminal to go free. There are many recorded instances where mathematics has been applied successfully, but there is also a growing body of evidence that math has been misused or flat out abused in criminal proceedings. I've always had an interest in how technology is applied to the legal system and specifically how it can be tested for efficacy, reliability, accuracy, and precision.

Understanding Data Axes using Image manipulation with Python

I have recently been working on several projects which allowed me to dive into image analysis. What I found was a lot of people still using nested loops to process pixel data. This is fine for small data sets. Once you have amassed several thousand images to process though, you need a better way. For many new data scientists, one of the most confusing aspects of manipulating image data programmatically seems to be understanding the axes layout many libraries (like NumPy and Pandas) rely on. Understanding how the data is laid out, and how you can efficiently process it, can save you hours of waiting for your code to execute. In this post I will explain this layout and how you can leverage it to your programmatic advantage.

The Art Gallery Problem: Mathematical analysis of area coverage

Often times while doing a security analysis of a physical area, I am interested in the efficient placement of assets to monitor and secure an area. In mathematics the placement of security resources within an area is often modeled as a geometric area coverage problem. We can restate our problem as "What is the minimum number of resources required to cover the inside of a given polygon".  Today I will discuss a software for analyzing and planning physical security layouts based off of the insights revealed by studying this problem.

Abusing Git Hooks with Python

Git hooks is one of the lesser talked about features of git. Most Developers get a basic introduction to hooks, maybe once early on when there is so much to take in that the beauty of these little gems goes almost unseen. Today I would like to discuss some ways to use, then abuse, this often forgotten facet. Then conclude with a discussion of detection.

AVCS2: Attitude and Heading Reference System (GY-88 10-DOF) module

The GY-88 packages 3 popular sensors (technically more than 3, but I will cover that later) in a single convenient PCB. Each sensor measures a specific type of spacial data. The module contains a 6-axis accelerometer, a magnometer, and a barometer. All the sensors you need to create a Attitude and Heading Reference System (AHRS). In this post I will go over each sensor in more detail. I will also cover how it can be used to inform an Autonomous Vehicle Control System aimed at multi-rotor flight control.

AVCS1: Sonic Range Finder (HC-SR04) discussion

Th HC-SR04 sonic range finding modules are a popular choice for projects which require sensing the distance to some object. I recently ordered a bunch of them to keep on hand, but I wanted to add one to the Infrared Light Goggle project I built previously. This addition will allow me to add the approximate distance to the HUD.