dynamic biomechanical simulation of thoracic cage

Introduction A client asked me to build a dynamic engineering model of the thoracic cage with which we can run “what if?” scenarios against. Applying Newton’s laws of motion and Runge-Kutta, I produced the following results. Following the videos presented below, I partially detail my methodology and propose steps for improving the work: Results The […]

a graph-based, large-scale data model for NLP cross-referencing

I find myself in a situation where my team needs to combine several natural language processing (NLP) [1] techniques, each conducted upon the same large set of texts, to derive critical business conclusions. Particularly, we need a way to cross-reference analyses based on common key words across sentences. Toward that end, I designed the following […]

blockchain is punk

Wide distribution of power lies at the heart of anarchistic thinking. While “punk” and “anarchy” do not necessarily imply one another, they often overlap. Punks tend to balk at centralized authority, as do anarchists. A short leap of logic concludes that we therefore dislike centralized technology. Concentration in technology long parallels concentration in political power. […]

fans control the music: using AI to measure fan enthusiasm at EDC

We invented technology to enhance the fan/performer connection. Vote for Team Ambience at EDC! DJs and more traditional musicians require realtime audience feedback during performances. However, often we cannot see our audience—their movement, their facial expressions, etc.—during shows due to stage lighting. Therefore we cannot gauge their enthusiasm, and therefore cannot alter our performance to respond. […]

women’s style recommendation with artificial intelligence (part #2)

In “women’s style recommendation with artificial intelligence (part #1)”, I introduced my work toward developing artificial intelligence (AI) for fashion and style recommendation. Essentially, its an expert system built on a Bayesian belief network. Now I discuss model validation and next steps in the design iteration process. I first wanted to see if the trained […]

women’s style recommendation with artificial intelligence (part #1)

Introduction We know several basic style “rules” (ha!) based on body shape: Skirts: “Apple” Body Shape: IF body shape is apple AND skirt has front zipper THEN don’t wear IF body shape is apple AND skirt has side zipper THEN wear IF body shape is apple AND skirt has no zipper THEN wear “Rectangular” Body […]

machine learning in FOREX (part one: establishing a performance baseline)

Introduction We’ve been applying machine learning to FOREX price prediction. The performance of our models varies widely, so to establish a baseline we created a simple linear regression model with which we can compare performance of more sophisticated models against. What We Are Trying To Do Given a time-series of 26 four-hour price samples, we […]

demonstrating a simple expert system with cascading effects (Clojure version)

We originally implemented this demonstration in CLIPS (see this post) but decided Clojure would provide a better platform due to advantages discussed below. “An expert system is a program capable of pairing up a set of facts with a set of rules to those facts, and execute some actions based on the matching rules. [1]” […]

encoding fashion rules into mathematical data structures (part one)

As we build our fashion recommendation engine, we seek rules to populate it with. With few exceptions (e.g. [1]), we find these rules encoded in prose or infographic form, rather than a semantic web form suitable for computation. For example, [2] provides written advice on dressing fabulously for a “rectangular” women’s body type. The writers […]