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The purpose of this research paper is to address the gap between programmers' capability to develop well-designed websites and the shabby designs of the websites they actually produce. This paper will first address what constitutes a poor website design and what constitutes a good website design. I will research what

The purpose of this research paper is to address the gap between programmers' capability to develop well-designed websites and the shabby designs of the websites they actually produce. This paper will first address what constitutes a poor website design and what constitutes a good website design. I will research what academia and popular opinion state are taboo elements that condemn a website's design choices and what they extoll as good website design choices. This includes an objective evaluation of both poorly-designed websites and well-designed websites. Following that, this paper will observe the cases of acclaimed and basic programmers and developers who produce incredible technologies while their website development work remains shoddy. I hope to glean some insight into why this performance gap exists. Ultimately, I will create wireframe designs for my own website, demonstrating the elements of a well-designed website in order to address everything I have learned.
ContributorsPandey, Ainesh (Author) / Anderson, Dennis (Thesis director) / Mazzola, Daniel (Committee member) / Department of Information Systems (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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DescriptionFoxBox.me is web application development project built on the following technologies, jQuery Mobile, HTML5, CSS, PHP, and MySQL. The primary function of the web application is to enable students across the university to connect, and study together by forming impromptu study groups through a mobile friendly touch interface.
ContributorsHall, Anthony L (Author) / Ahmad, Altaf (Thesis director) / Mazzola, Daniel (Committee member) / Anderson, Dennis (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / School of Accountancy (Contributor)
Created2013-05
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Music streaming services have affected the music industry from both a financial and legal standpoint. Their current business model affects stakeholders such as artists, users, and investors. These services have been scrutinized recently for their imperfect royalty distribution model. Covid-19 has made these discussions even more relevant as touring income

Music streaming services have affected the music industry from both a financial and legal standpoint. Their current business model affects stakeholders such as artists, users, and investors. These services have been scrutinized recently for their imperfect royalty distribution model. Covid-19 has made these discussions even more relevant as touring income has come to a halt for musicians and the live entertainment industry. <br/>Under the current per-stream model, it is becoming exceedingly hard for artists to make a living off of streams. This forces artists to tour heavily as well as cut corners to create what is essentially “disposable art”. Rapidly releasing multiple projects a year has become the norm for many modern artists. This paper will examine the licensing framework, royalty payout issues, and propose a solution.

ContributorsKoudssi, Zakaria Corley (Author) / Sadusky, Brian (Thesis director) / Koretz, Lora (Committee member) / Dean, W.P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description

Anthemy is a web app that I created so that Spotify users could connect with other uses and see their listening statistics. The app has a chat feature that matches concurrent users based on a variety of search criteria, as well as a statistics page that contains a breakdown of

Anthemy is a web app that I created so that Spotify users could connect with other uses and see their listening statistics. The app has a chat feature that matches concurrent users based on a variety of search criteria, as well as a statistics page that contains a breakdown of a user's top artists, songs, albums, and genres as well as a detailed breakdown of each of their liked playlists.

ContributorsJackman, Benjamin (Author) / Roumina, Kavous (Thesis director) / Mazzola, Daniel (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor)
Created2021-12
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ContributorsJackman, Benjamin (Author) / Roumina, Kavous (Thesis director) / Mazzola, Daniel (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor)
Created2021-12
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ContributorsJackman, Benjamin (Author) / Roumina, Kavous (Thesis director) / Mazzola, Daniel (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor)
Created2021-12
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Description
Although Spotify’s extensive library of songs are often seen broken up by “Top 100” and main lyrical genres, these categories are primarily based on popularity, artist and general mood alone. If a user wanted to create a playlist based on specific or situationally specific qualifiers from their own downloaded library,

Although Spotify’s extensive library of songs are often seen broken up by “Top 100” and main lyrical genres, these categories are primarily based on popularity, artist and general mood alone. If a user wanted to create a playlist based on specific or situationally specific qualifiers from their own downloaded library, he/she would have to hand pick songs that fit the mold and create a new playlist. This is a time consuming process that may not produce the most efficient result due to human error. The objective of this project, therefore, was to develop an application to streamline this process, optimize efficiency, and fill this user need.

Song Sift is an application built using Angular that allows users to filter and sort their song library to create specific playlists using the Spotify Web API. Utilizing the audio feature data that Spotify attaches to every song in their library, users can filter their downloaded Spotify songs based on four main attributes: (1) energy (how energetic a song sounds), (2) danceability (how danceable a song is), (3) valence (how happy a song sounds), and (4) loudness (average volume of a song). Once the user has created a playlist that fits their desired genre, he/she can easily export it to their Spotify account with the click of a button.
ContributorsDiMuro, Louis (Author) / Balasooriya, Janaka (Thesis director) / Chen, Yinong (Committee member) / Arts, Media and Engineering Sch T (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05