Research Papers

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Generative Deep Learning for Virtuosic Classical Music: Generative Adversarial Networks as Renowned Composers

Dec. 2020 - arXiv:2101.00172

ABSTRACT: Current AI-generated music lacks fundamental principles of good compositional techniques. By narrowing down implementation issues both programmatically and musically, we can create a better understanding of what parameters are necessary for a generated composition nearly indistinguishable from that of a master composer.


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Optimizing Data Cube Visualization for Web Applications: Performance and User-Friendly Data Aggregation

Dec. 2020 - arXiv:2101.00171

ABSTRACT: Current open source applications which allow for cross-platform data visualization of OLAP cubes feature issues of high overhead and inconsistency due to data oversimplification. To improve upon this issue, there is a need to cut down the number of pipelines that the data must travel between for these aggregation operations and create a single, unified application which performs efficiently without sacrificing data, and allows for ease of usability and extension.


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Visualization Techniques with Data Cubes: Utilizing Concurrency for Complex Data

Oct. 2020 - arXiv:2101.00170

ABSTRACT: With web and mobile platforms becoming more prominent devices utilized in data analysis, there are currently few systems which are not without flaw. In order to increase the performance of these systems and decrease errors of data oversimplification, we seek to understand how other programming languages can be used across these platforms which provide data and type safety, as well as utilizing concurrency to perform complex data manipulation tasks.


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Chunk List

Feb. 2017 - arXiv:2101.00172

ABSTRACT: Chunking data is obviously no new concept; however, I had never found any data structures that used chunking as the basis of their implementation. I figured that by using chunking alongside concurrency, I could create an extremely fast run-time in regards to particular methods as searching and/or sorting. By using chunking and concurrency to my advantage, I came up with the chunk list - a dynamic list-based data structure that would separate large amounts of data into specifically sized chunks, each of which should be able to be searched at the exact same time by searching each chunk on a separate thread. As a result of implementing this concept into its own class, I was able to create something that almost consistently gives around 20x-300x faster results than a regular ArrayList. However, should speed be a particular issue even after implementation, users can modify the size of the chunks and benchmark the speed of using smaller or larger chunks, depending on the amount of data being stored.


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Research Papers

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An Introduction to Film Scoring in Horror Movies

Jan. 2020 - Paperback

DESCRIPTION: The horror movie genre is one of complexity, both in design and story. The style of screenwriting and use of visual and aural nuances has developed into a rich, exciting form of entertainment that plays on the viewer's mind, body, and morals. In terms of visuals, horror movies play on classic psychological fears and utilize them in ways that may be gruesome or traumatizing, yet impossible to look away from. However, one of the biggest tools used to create the sense of fear in the movies is of course the specific use of sound and music to build and develop tension and emphasize horrific scenes. From the usage of drums to imitate a pounding heartbeat to strings playing harsh, discordant and unexpected sounds meant to imitate the screams of frightened animals, and the crashing, staccato chords that strike into instinctive fears, the composer/film scorer of the horror genre plays an extremely important role in delivering the full effect of the film that often goes unnoticed.

ISBN-10: 1794899219

ISBN-13: 978-1794899216


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Undergraduate Musicology Research: Studies in Music History

Nov. 2019 - Paperback

DESCRIPTION: This book contains a collection of three research papers during undergraduate coursework by Daniel Szelogowski. The works recall three lesser-known composers: Francesco Landini, Frederic Chopin, and Karol Szymanowski -- all of which have many sources of misinformation or lack of information overall.

ISBN-10: 1794731350

ISBN-13: 978-1794731356


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