Matching Items (15)
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- All Subjects: Creative Project
- All Subjects: artificial intelligence
- Resource Type: Text
Description
We created an Android application, Impromp2, which allows users to search for and save events of interest to them in the Phoenix area. The backend, built on the Parse platform, gathers events daily using Web services and stores them in a database. Impromp2 was designed to improve upon similarly-purposed apps available for Android devices in several key ways, especially in user interface design and data interaction capability. This is a full-stack software project that explores databases and their performance considerations, Web services, user interface design, and the challenges of app development for a mobile platform.
ContributorsNorth, Joseph Robert (Author) / Balasooriya, Janaka (Thesis director) / Nakamura, Mutsumi (Committee member) / Faucon, Philippe (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
"The Legal Adventures of Frankie and Rosie" is a creative project that explores the nontraditional format of comics to express creative nonfiction. The project is a set of 30 independent comics that focuses on two primary college-going students who are based off of the authors. The characters, Frankie and Rosie narrate their stories through dialogue. The authors use this narrative model to archive their college experience at ASU. Representing creative nonfiction through comics yields an amalgamated format that can be challenging for both the writers to produce as well as for the readers to consume. Ultimately, the project serves as an attempt to test whether or not the comic medium can stand by itself as an appropriate format to express creative nonfictional narratives without becoming a diluted combination of its purer predecessors.
ContributorsBennewitz, Dana (Co-author) / Ray, Payel (Co-author) / Martin, Thomas (Thesis director) / Scott Lynch, Jacquelyn (Committee member) / Civil, Environmental and Sustainable Engineering Programs (Contributor) / Barrett, The Honors College (Contributor) / School of Geographical Sciences and Urban Planning (Contributor) / Electrical Engineering Program (Contributor) / School of Social Transformation (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
Rainbow Connection is an integrated choir with members on and off the autism spectrum. It was founded in the spring of 2012 by Barrett students Ali Friedman, Megan Howell, and Victoria Gilman as part of an honors thesis creative project. Rainbow Connection uses the rehearsal process and other creative endeavors to foster natural relationship building across social gaps. A process-oriented choir, Rainbow Connection's main goals concern the connections made throughout the experience rather than the final musical product. The authors believe that individual, non-hierarchical relationships are the keys to breaking down systemized gaps between identity groups and that music is an ideal facilitator for fostering such relationships. Rainbow Connection operates under the premise that, like colors in a rainbow, choir members create something beautiful not by melding into one homogenous group, but by collaboratively showcasing their individual gifts. This paper will highlight the basic premise and structure of Rainbow Connection, outline the process of enacting the choir, and describe the authors' personal reactions and takeaways from the project.
ContributorsFriedman, Alexandra (Co-author) / Gilman, Victoria (Co-author) / Howell, Megan (Co-author) / Rio, Robin (Thesis director) / Schildkret, David (Committee member) / Barrett, The Honors College (Contributor) / School of Music (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2014-12
Description
The title means nothing because the stories have little in common, aside from the fact that I wrote them. The common theme of anxiety was unintentional, though it is prevalent in the stories, poetry and my life. Each story is written from a different style, with a different interest in mind. The poetry that breaks up the stories is mine, and also free of common bonds. People whom I love inspired some of them; others stem from people with whom I was (or still am) angry. Some of them are just me trying to write poetry like other successful poets, who seem to know something I don't. I wrote this set of stories and poems because I wanted to see if I could do it. I wanted to challenge myself in a new medium (two new mediums really, if you separate literature and poetry). I wanted to prove to myself that I could do it, if I really set my mind to it. I wanted to have some wealth of words, which I could record myself reading. Overall, I hope that you enjoy these stories and words. I wrote them to entertain myself, and they seem to do that pretty well. If you don't like them, stop reading. If you do like them, keep reading and tell everyone you know about this collection. I'm proud of my work here, so anything beyond that is icing on my cake.
ContributorsRagatz, Zachariah Edward (Author) / Scott, Jason Davids (Thesis director) / Espinosa, Micha (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Film, Dance and Theatre (Contributor)
Created2015-05
Description
Is it possible to treat the mouth as a natural environment, and determine new methods to keep the microbiome in check? The need for biodiversity in health may suggest that every species carries out a specific function that is required to maintain equilibrium and homeostasis within the oral cavity. Furthermore, the relationship between the microbiome and its host is mutually beneficial because the host is providing microbes with an environment in which they can flourish and, in turn, keep their host healthy. Reviewing examples of larger scale environmental shifts could provide a window by which scientists can make hypotheses. Certain medications and healthcare treatments have been proven to cause xerostomia. This disorder is characterized by a dry mouth, and known to be associated with a change in the composition, and reduction, of saliva. Two case studies performed by Bardow et al, and Leal et al, tested and studied the relationships of certain medications and confirmed their side effects on the salivary glands [2,3]. Their results confirmed a relationship between specific medicines, and the correlating complaints of xerostomia. In addition, Vissink et al conducted case studies that helped to further identify how radiotherapy causes hyposalivation of the salivary glands [4]. Specifically patients that have been diagnosed with oral cancer, and are treated by radiotherapy, have been diagnosed with xerostomia. As stated prior, studies have shown that patients having an ecologically balanced and diverse microbiome tend to have healthier mouths. The oral cavity is like any biome, consisting of commensalism within itself and mutualism with its host. Due to the decreased salivary output, caused by xerostomia, increased parasitic bacteria build up within the oral cavity thus causing dental disease. Every human body contains a personalized microbiome that is essential to maintaining health but capable of eliciting disease. The Human Oral Microbiomics Database (HOMD) is a set of reference 16S rRNA gene sequences. These are then used to define individual human oral taxa. By conducting metagenomic experiments at the molecular and cellular level, scientists can identify and label micro species that inhabit the mouth during parasitic outbreaks or a shifting of the microbiome. Because the HOMD is incomplete, so is our ability to cure, or prevent, oral disease. The purpose of the thesis is to research what is known about xerostomia and its effects on the complex microbiome of the oral cavity. It is important that researchers determine whether this particular perspective is worth considering. In addition, the goal is to create novel experiments for treatment and prevention of dental diseases.
ContributorsHalcomb, Michael Jordan (Author) / Chen, Qiang (Thesis director) / Steele, Kelly (Committee member) / Barrett, The Honors College (Contributor) / College of Letters and Sciences (Contributor)
Created2015-05
Description
This creative project centers on creating evaluative writing about film, in the form of a film review blog. Preliminary writing was done, in which the distinction was made between critical film writing and movie reviewing, as well as an analysis of how film critics have honed in their criticism and what makes their content effective for their audience. The rest of the writing for this project consists of a total of 15 reviews for 15 different movies released in 2017 and 2018. In these reviews, there is a brief introduction of the plot and context in which the film is made, followed by an evaluative analysis of what made the film effective or ineffective in achieving its artistic goals. The reviews involve an amalgamation of the content and topics taught in the Film and Media Studies program at Arizona State University, from screenwriting to cinematography. This process of writing reviews and being edited by the Director and Second Reader allows for the opportunity to find a unique writing voice and create content that is accessible for the wide audience that would be reading the work. All of the writing completed for this project (except for the "My Favorite Film Critics" piece) is compiled together in a WordPress blog, in an easily readable and accessible format. The blog itself serves as a way to reach the desired audience, as well as entice them to engage with the writing and the films being written about. This includes providing images and trailers for each respective film, to add a visual component to the writing. The final product is a unique way to engage with the content taught in the Film and Media Studies program, while simultaneously building a portfolio of writing that will be expanded upon and continued in the future.
ContributorsPolich, Brennan Taylor (Author) / Green, Michael (Thesis director) / Bernstein, Gregory (Committee member) / Department of English (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
I, Christopher Negrich, am the sole author of this paper, but the tools described were designed in collaboration with Andrew Hoetker. ConstrictR (constrictor) and ConstrictPy are an R package and python tool designed together. ConstrictPy implements the functions and methods defined in ConstrictR and applies data handling, data parsing, input/output (I/O), and a user interface to increase usability. ConstrictR implements a variety of common data analysis methods used for statistical and subnetwork analysis. The majority of these methods are inspired by Lionel Guidi's 2016 paper, Plankton networks driving carbon export in the oligotrophic ocean. Additional methods were added to expand functionality, usability, and applicability to different areas of data science. Both ConstrictR and ConstrictPy are currently publicly available and usable, however, they are both ongoing projects. ConstrictR is available at github.com/cnegrich and ConstrictPy is available at github.com/ahoetker. Currently, ConstrictR has implemented functions for descriptive statistics, correlation, covariance, rank, sparsity, and weighted correlation network analysis with clustering, centrality, profiling, error handling, and data parsing methods to be released soon. ConstrictPy has fully implemented and integrated the features in ConstrictR as well as created functions for I/O and conversion between pandas and R data frames with a full feature user interface to be released soon. Both ConstrictR and ConstrictPy are designed to work with minimal dependencies and maximum available information on the algorithms implemented. As a result, ConstrictR is only dependent on base R (v3.4.4) functions with no libraries imported. ConstrictPy is dependent upon only pandas, Rpy2, and ConstrictR. This was done to increase longevity and independence of these tools. Additionally, all mathematical information is documented alongside the code, increasing the available information on how these tools function. Although neither tool is in its final version, this paper documents the code, mathematics, and instructions for use, in addition to plans for future work, for of the current versions of ConstrictR (v0.0.1) and ConstrictPy (v0.0.1).
ContributorsNegrich, Christopher Alec (Author) / Can, Huansheng (Thesis director) / Hansford, Dianne (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
FastStat is a responsive website designed to work on any handheld, laptop, or desktop device. It serves as a first step into statistical calculations, educating the user on the basics of statistical analysis, and guiding them as they perform analyses of their own using built-in calculators. The calculators available can perform z tests, t tests, chi square tests, and analysis of variance tests to determine significant characteristics of the user's data. Outputted data includes means, standard deviations, significance levels, applicable statistics, and worded results indicating the outcome of the performed test. With its clean design, FastStat directs the user in an intuitive manner to fill in the information needed, giving clear indications of what types of values are needed where and flagging descriptive error messages if any inputted values are incorrect. FastStat also implements a halt to calculations if any errors are found, which saves time by avoiding impossible calculations. Once complete, FastStat outputs a variety of information of use to the user in a clearly labeled manner. The calculators are designed in such a way that the user will know what information they will get out of the calculator before performing any calculations at all. Aside from the calculators, FastStat includes introductory pages designed to get users familiar with common statistical terms and the associated tests, solidifying its purpose as an introductory tool. All tests are described by their typical uses, necessary inputs, calculated outputs, and extra notes of importance. Many terms are defined for the purpose of statistics, complete with examples to help educate the user on the concepts. With the information available, even the newest statistician can learn and begin performing tests almost immediately.
ContributorsBroin, Demetri Evan (Author) / Squire, Susan (Thesis director) / Samara, Marko (Committee member) / Graphic Information Technology (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Speech nasality disorders are characterized by abnormal resonance in the nasal cavity. Hypernasal speech is of particular interest, characterized by an inability to prevent improper nasalization of vowels, and poor articulation of plosive and fricative consonants, and can lead to negative communicative and social consequences. It can be associated with a range of conditions, including cleft lip or palate, velopharyngeal dysfunction (a physical or neurological defective closure of the soft palate that regulates resonance between the oral and nasal cavity), dysarthria, or hearing impairment, and can also be an early indicator of developing neurological disorders such as ALS. Hypernasality is typically scored perceptually by a Speech Language Pathologist (SLP). Misdiagnosis could lead to inadequate treatment plans and poor treatment outcomes for a patient. Also, for some applications, particularly screening for early neurological disorders, the use of an SLP is not practical. Hence this work demonstrates a data-driven approach to objective assessment of hypernasality, through the use of Goodness of Pronunciation features. These features capture the overall precision of articulation of speaker on a phoneme-by-phoneme basis, allowing demonstrated models to achieve a Pearson correlation coefficient of 0.88 on low-nasality speakers, the population of most interest for this sort of technique. These results are comparable to milestone methods in this domain.
ContributorsSaxon, Michael Stephen (Author) / Berisha, Visar (Thesis director) / McDaniel, Troy (Committee member) / Electrical Engineering Program (Contributor, Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
In this paper, I will show that news headlines of global events can predict changes in stock price by using Machine Learning and eight years of data from r/WorldNews, a popular forum on Reddit.com. My data is confined to the top 25 daily posts on the forum, and due to the implicit filtering mechanism in the online community, these 25 posts are representative of the most popular news headlines and influential global events of the day. Hence, these posts shine a light on how large-scale social and political events affect the stock market. Using a Logistic Regression and a Naive Bayes classifier, I am able to predict with approximately 85% accuracy a binary change in stock price using term-feature vectors gathered from the news headlines. The accuracy, precision and recall results closely rival the best models in this field of research. In addition to the results, I will also describe the mathematical underpinnings of the two models; preceded by a general investigation of the intersection between the multiple academic disciplines related to this project. These range from social to computer science and from statistics to philosophy. The goal of this additional discussion is to further illustrate the interdisciplinary nature of the research and hopefully inspire a non-monolithic mindset when further investigations are pursued.
ContributorsPriniski, John Hunter (Author) / Haiyan, Wang (Thesis director) / Hazel, Kwon (Committee member) / School of Historical, Philosophical and Religious Studies (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12