The purpose of this project is to create a useful tool for musicians that utilizes the harmonic content of their playing to recommend new, relevant chords to play. This is done by training various Long Short-Term Memory (LSTM) Recurrent Neural Networks (RNNs) on the lead sheets of 100 different jazz standards. A total of 200 unique datasets were produced and tested, resulting in the prediction of nearly 51 million chords. A note-prediction accuracy of 82.1% and a chord-prediction accuracy of 34.5% were achieved across all datasets. Methods of data representation that were rooted in valid music theory frameworks were found to increase the efficacy of harmonic prediction by up to 6%. Optimal LSTM input sizes were also determined for each method of data representation.

This creative is established in the field of business, with an emphasis on fashion, art, and<br/>the creation of a body-positive exhibit. Using qualitative research from experts on fashion<br/>curation, we seek to create, curate and pitch a fashion exhibit. Using the information we gather<br/>from experts from two different museums, we will create a new age exhibit that pushes the<br/>boundaries of fashion as art through our theme of body positivity.

In this paper, I introduce the fake news problem and detail how it has been exacerbated<br/>through social media. I explore current practices for fake news detection using natural language<br/>processing and current benchmarks in ranking the efficacy of various language models. Using a<br/>Twitter-specific benchmark, I attempt to reproduce the scores of six language models<br/>demonstrating their effectiveness in seven tweet classification tasks. I explain the successes and<br/>challenges in reproducing these results and provide analysis for the future implications of fake<br/>news research.

This thesis is concerned with the political implications of two of Jacques-Louis David's paintings: Oath of the Horatii (1784) and The Lictors Bringing to Brutus the Bodies of His Sons (1789). In this thesis, I argue that David’s pre-Revolutionary work contained political anticipations of Revolutionary France articulated in his Neoclassical forms, the classical stories he chose to paint, his own narrative innovations using light, color, gender, unusual scenes and the thematic conflict of the state vs the individual and family.

Human activity recognition is the task of identifying a person’s movement from sensors in a wearable device, such as a smartphone, smartwatch, or a medical-grade device. A great method for this task is machine learning, which is the study of algorithms that learn and improve on their own with the help of massive amounts of useful data. These classification models can accurately classify activities with the time-series data from accelerometers and gyroscopes. A significant way to improve the accuracy of these machine learning models is preprocessing the data, essentially augmenting data to make the identification of each activity, or class, easier for the model. <br/>On this topic, this paper explains the design of SigNorm, a new web application which lets users conveniently transform time-series data and view the effects of those transformations in a code-free, browser-based user interface. The second and final section explains my take on a human activity recognition problem, which involves comparing a preprocessed dataset to an un-augmented one, and comparing the differences in accuracy using a one-dimensional convolutional neural network to make classifications.

Virans is a book comprised of illustrations, hand-written text, and digital elements The book was conceived as an encapsulation of the broad social changes brought on by the COVID-19 pandemic. With a unique art style utilizing distorted human forms, complex line patterns, pointillism, and flat compositions, each of the book's 15 spreads represent an issue observed during the pandemic. These issues include isolation, political concerns, conspiracy theories, and the overall human toll of the pandemic.