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A common challenge faced by students is that they often have questions about course material that they cannot ask during lecture time. There are many ways for students to have these questions answered, such as office hours and online discussion boards. However, office hours may be at inconvenient times or locations, and online discussion boards are difficult to navigate and may be inactive. The purpose of this project was to create an Alexa skill that allows users to ask their Alexa-equipped device a question concerning their course material and to receive an answer retrieved from discussion board data. User questions are mapped to discussion board posts by use of the cosine similarity algorithm. In this algorithm, posts from the discussion board and the user’s question are converted into mathematical vectors, with each term in the vector corresponding to a word. The values of these terms are computed based on the word’s frequency within the vector’s corresponding document, the frequency of that word within all the documents, and the length of the document. After the question and candidate posts are converted into vectors, the algorithm determines the post most similar to the user’s question by computing the angle between the vectors. With the most similar discussion board post determined, the user receives the replies to the post, if any, as their answer. Users are able to indicate to their Alexa device whether they were satisfied by the answer, and if they were unsatisfied then they are given the opportunity to either rephrase their question or to have the question sent to a database of unanswered questions. The professor can view and answer the questions in this database on a website hosted by use of Amazon’s Simple Storage Service. The Alexa skill does well at answering questions that have already been asked in the discussion board. However, the skill depends heavily on the user’s word choice. Two questions that are semantically identical but different in phrasing are often given different answers. This is because the cosine algorithm measures similarity on the basis of word overlap, not semantic meaning, and thus the application never truly “understands” what type of answer the user desires. Improving the performance of this Alexa skill will require a more advanced question answering algorithm, but the limitations of Amazon Web Services as a development platform make implementing such an algorithm difficult. Nevertheless, this project has created the basis of a question answering Alexa skill by demonstrating a feasible way that the resources offered by Amazon can be utilized in order to build such an application.
ContributorsBaker, Matthew Elias (Author) / Chen, Yinong (Thesis director) / Balasooriya, Janaka (Committee member) / Historical, Philosophical & Religious Studies (Contributor) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Carbon allotropes are the basis for many exciting advancements in technology. While sp² and sp³ hybridizations are well understood, the sp¹ hybridized carbon has been elusive. However, with recent advances made using a pulsed laser ablation in liquid technique, sp¹ hybridized carbon allotropes have been created. The fabricated carbon chain is composed of sp¹ and sp³ hybridized bonds, but it also incorporates nanoparticles such as gold or possibly silver to stabilize the chain. The polyyne generated in this process is called pseudocarbyne due to its striking resemblance to the theoretical carbyne. The formation of these carbon chains is yet to be fully understood, but significant progress has been made in determining the temperature of the plasma in which the pseudocarbyne is formed. When a 532 nm pulsed laser with a pulsed energy of 250 mJ and pulse length of 10ns is used to ablate a gold target, a peak temperature of 13400 K is measured. When measured using Laser-Induced Breakdown spectroscopy (LIBS) the average temperature of the neutral carbon plasma over one second was 4590±172 K. This temperature strongly suggests that the current theoretical model used to describe the temperature at which pseudocarbyne generates is accurate.
ContributorsWala, Ryland Gerald (Co-author) / Wala, Ryland (Co-author) / Sayres, Scott (Thesis director) / Steimle, Timothy (Committee member) / Drucker, Jeffery (Committee member) / Historical, Philosophical & Religious Studies (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Department of Physics (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Tempe Town Lake is the site of fifteen years’ worth of chemical data collection by ASU researchers. In 2018 the dataSONDE, an instrument capable of measuring different water quality parameters every thirty minutes for a month at a time was installed in the lake. The SONDE has the potential to completely reduce the need for sampling by hand. Before the SONDE becomes the sole means of gathering data, it is important to verify its accuracy. In this study, the measurements gathered by the SONDE (pH, dissolved oxygen, temperature, conductivity and colored dissolved organic matter) were compared to measurements gathered using the verified methods from the past fifteen years.
ContributorsSauer, Elinor Rayne (Author) / Hartnett, Hilairy (Thesis director) / Glaser, Donald (Committee member) / Shock, Everett (Committee member) / Historical, Philosophical & Religious Studies (Contributor) / School of Molecular Sciences (Contributor) / School of Life Sciences (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2020-12