Natural Language Processing - Sentiment Analysis

We investigated how different Natural Language Processing (NLP) techniques could be used to perform sentiment analysis on real user generated text data from the Sentiment140 dataset [1]. First we investigated an LSTM model before deciding on using the self-attention network code from [2] because of the possible speed and accuracy advantages. Our contributions included investigating how the training batch size and dropout rate affected the accuracy of the model and validating an existing model by reproducing it and using it with a different dataset.

A Selective Laser Sintering Creation - Wind Powered Tops

We designed a spinning top that is novel, aesthetically pleasing, durable, spins well, and whose unique fan assembly can only be made using SLS. Our design incorporates a modular top system that allows for interchangeable designs to be attached to the universal base. We designed two UT-themed attachable tops, one that is a replica of the UT model tower and the other that is a replica of the UT seal. The universal base has wind turbine blades in its center so that air can be blown through it to keep it spinning even with a large top installed.

Decompositions Algorithms Broken Down and Explained

This post explores how to use various decomposition techniques to solve LPs and MIPs. I have written these using Gurobi as a solver and as the mathematical formulation software. This is a reproducible example if you have R Studio just make sure you have installed the correct packages. library(gurobi) ## Warning: package ‘slam’ was built under R version 4.1.2 library(tictoc) library(Matrix) library(ggplot2) ## Warning: package ‘ggplot2’ was built under R version 4.

Benders Decomposition Algorithm Explained

This post explores how to use Benders Decomposition to solve LPs and MIPs. I have written these using Gurobi as a solver and as the mathematical formulation software. This is a reproducible example if you have R Studio just make sure you have installed the correct packages. library(gurobi) ## Warning: package ‘slam’ was built under R version 4.1.2 library(lpSolveAPI) library(tictoc) library(Matrix) library(ggplot2) ## Warning: package ‘ggplot2’ was built under R version 4.

Quadratic Programming Examples and Algorithms

Background This post explores how to solve QPs by hand and with Gurobi. I have written these using Gurobi as a solver and as the mathematical formulation software. This is a reproducible example if you have R Studio just make sure you have installed the correct packages. library(gurobi) ## Warning: package ‘slam’ was built under R version 4.1.2 library(tictoc) library(Matrix) library(ggplot2) ## Warning: package ‘ggplot2’ was built under R version 4.