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- Member of: Barrett, The Honors College Thesis/Creative Project Collection
Description
In order to adequately introduce students to computer science and robotics in an exciting and engaging manner certain teaching techniques should be used. In recent years some of the most popular paradigms are Visual Programming Languages. Visual Programming Languages are meant to introduce problem solving skills and basic programming constructs inherent to all modern day languages by allowing users to write programs visually as opposed to textually. By bypassing the need to learn syntax students can focus on the thinking behind developing an algorithm and see immediate results that help generate excitement for the field and reduce disinterest due to startup complexity and burnout. The Introduction to Engineering course at Arizona State University supports this approach by teaching students the basics of autonomous maze traversing algorithms and using ASU VIPLE, a Visual Programming Language developed to connect with and direct real-world robots. However, some startup time is needed to learn how to interface with these robots using ASU VIPLE. That is why the HTML5 Autonomous Robot Web Simulator was created -- by encouraging students to use the simulator the problem solving behind autonomous maze traversing algorithms can be introduced more quickly and with immediate affirmation. Our goal was to improve this simulator and add features so that the simulator could be accessed and used for a more wide variety of introductory Computer Science lessons. Features scattered across past implementations of robotic simulators were aggregated in a cross platform solution. Upon initial development, a classroom test group revealed usability concerns and a demonstration of students' mental models. Mean time for task completion was 8.1min - compared to 2min for the authors. The simulator was updated in response to test group feedback and new instructor requirements. The new implementation reduces programming overhead while maintaining a learning environment with support for even the most complex applications.
ContributorsRodewald, Spencer (Co-author, Co-author) / Patel, Ankit (Co-author) / Chen, Yinong (Thesis director) / Chattin, Linda (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
The objective of this creative project was to gain experience in digital modeling, animation, coding, shader development and implementation, model integration techniques, and application of gaming principles and design through developing a professional educational game. The team collaborated with Glendale Community College (GCC) to produce an interactive product intended to supplement educational instructions regarding nutrition. The educational game developed, "Nutribots" features the player acting as a nutrition based nanobot sent to the small intestine to help the body. Throughout the game the player will be asked nutrition based questions to test their knowledge of proteins, carbohydrates, and lipids. If the player is unable to answer the question, they must use game mechanics to progress and receive the information as a reward. The level is completed as soon as the question is answered correctly. If the player answers the questions incorrectly twenty times within the entirety of the game, the team loses faith in the player, and the player must reset from title screen. This is to limit guessing and to make sure the player retains the information through repetition once it is demonstrated that they do not know the answers. The team was split into two different groups for the development of this game. The first part of the team developed models, animations, and textures using Autodesk Maya 2016 and Marvelous Designer. The second part of the team developed code and shaders, and implemented products from the first team using Unity and Visual Studio. Once a prototype of the game was developed, it was show-cased amongst peers to gain feedback. Upon receiving feedback, the team implemented the desired changes accordingly. Development for this project began on November 2015 and ended on April 2017. Special thanks to Laura Avila Department Chair and Jennifer Nolz from Glendale Community College Technology and Consumer Sciences, Food and Nutrition Department.
ContributorsNolz, Daisy (Co-author) / Martin, Austin (Co-author) / Quinio, Santiago (Co-author) / Armstrong, Jessica (Co-author) / Kobayashi, Yoshihiro (Thesis director) / Valderrama, Jamie (Committee member) / School of Arts, Media and Engineering (Contributor) / School of Film, Dance and Theatre (Contributor) / Department of English (Contributor) / Computer Science and Engineering Program (Contributor) / Computing and Informatics Program (Contributor) / Herberger Institute for Design and the Arts (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
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
Virtual reality gives users the opportunity to immerse themselves in an accurately
simulated computer-generated environment. These environments are accurately simulated in that they provide the appearance of- and allow users to interact with- the simulated environment. Using head-mounted displays, controllers, and auditory feedback, virtual reality provides a convincing simulation of interactable virtual worlds (Wikipedia, “Virtual reality”). The many worlds of virtual reality are often expansive, colorful, and detailed. However, there is one great flaw among them- an emotion evoked in many users through the exploration of such worlds-loneliness.
The content in these worlds is impressive, immersive, and entertaining. Without other people to share in these experiences, however, one can find themselves lonely. Users discover a feeling that no matter how many objects and colors surround them in countless virtual worlds, every world feels empty. As humans are social beings by nature, they feel lost without a sense of human connection and human interaction. Multiplayer experiences offer this missing element into the immersion of virtual reality worlds. Multiplayer offers users the opportunity to interact with other live people in a virtual simulation, which creates lasting memories and deeper, more meaningful immersion.
simulated computer-generated environment. These environments are accurately simulated in that they provide the appearance of- and allow users to interact with- the simulated environment. Using head-mounted displays, controllers, and auditory feedback, virtual reality provides a convincing simulation of interactable virtual worlds (Wikipedia, “Virtual reality”). The many worlds of virtual reality are often expansive, colorful, and detailed. However, there is one great flaw among them- an emotion evoked in many users through the exploration of such worlds-loneliness.
The content in these worlds is impressive, immersive, and entertaining. Without other people to share in these experiences, however, one can find themselves lonely. Users discover a feeling that no matter how many objects and colors surround them in countless virtual worlds, every world feels empty. As humans are social beings by nature, they feel lost without a sense of human connection and human interaction. Multiplayer experiences offer this missing element into the immersion of virtual reality worlds. Multiplayer offers users the opportunity to interact with other live people in a virtual simulation, which creates lasting memories and deeper, more meaningful immersion.
ContributorsJorgensen, Caitlin Nicole (Co-author) / Jorgensen, Nicholas (Co-author) / Ehgner, Arnaud (Thesis director) / Selgrad, Justin (Committee member) / Graphic Information Technology (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Charleston, South Carolina currently faces serious annual flooding issues due to tides and rainfall. These issues are expected to get significantly worse within the next few decades reaching a projected 180 days a year of flooding by 2045 (Carter et al., 2018). Several permanent solutions are in progress by the City of Charleston. However, these solutions are years away at minimum and faced with development issues. This thesis attempts to treat some of the symptoms of flooding, such as navigation, by creating an iPhone application which predicts flooding and helps people navigate around it safely. Specifically, this thesis will take into account rainfall and tide levels to display to users actively flooded areas of downtown Charleston and provide routing to a destination from a user’s location around these flooded areas whenever possible.
ContributorsSalisbury, Mason (Author) / Balasooriya, Janaka (Thesis director) / Faucon, Christophe (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
This honors thesis is focused on two separate catalysis projects conducted under the mentorship of Dr. Javier Pérez-Ramírez at ETH Zürich. The first project explored ethylene oxychlorination over supported europium oxychloride catalysts. The second project investigated alkyne semihydrogenation over nickel phosphide catalysts. This work is the subject of a publication of which I am a co-author, as cited below.
Project 1 Abstract: Ethylene Oxychlorination
The current two-step process for the industrial process of vinyl chloride production involves CuCl2 catalyzed ethylene oxychlorination to ethylene dichloride followed by thermal cracking of the latter to vinyl chloride. To date, no industrial application of a one-step process is available. To close this gap, this work evaluates a wide range of self-prepared supported CeO2 and EuOCl catalysts for one-step production of vinyl chloride from ethylene in a fixed-bed reactor at 623 773 K and 1 bar using feed ratios of C2H4:HCl:O2:Ar:He = 3:3 6:1.5 6:3:82 89.5. Among all studied systems, CeO2/ZrO2 and CeO2/Zeolite MS show the highest activity but suffer from severe combustion of ethylene, forming COx, while 20 wt.% EuOCl/γ-Al2O3 leads to the best vinyl chloride selectivity of 87% at 15.6% C2H4 conversion with complete suppression of CO2 formation and only 4% selectivity to CO conversion for over 100 h on stream. Characterization by XRD and EDX mapping reveals that much of the Eu is present in non-active phases such as Al2Eu or EuAl4, indicating that alternative synthesis methods could be employed to better utilize the metal. A linear relationship between conversion and metal loading is found for this catalyst, indicating that always part of the used Eu is available as EuOCl, while the rest forms inactive europium aluminate species. Zeolite-supported EuOCl slightly outperforms EuOCl/γ Al2O3 in terms of total yield, but is prone to significant coking and is unstable. Even though a lot of Eu seems locked in inactive species on EuOCl/γ Al2O3, these results indicate possible savings of nearly 16,000 USD per kg of catalyst compared to a bulk EuOCl catalyst. These very promising findings constitute a crucial step for process intensification of polyvinyl chloride production and exploring the potential of supported EuOCl catalysts in industrially-relevant reactions.
Project 2 Abstract: Alkyne Semihydrogenation
Despite strongly suffering from poor noble metal utilization and a highly toxic selectivity modifier (Pb), the archetypal catalyst applied for the three-phase alkyne semihydrogenation, the Pb-doped Pd/CaCO3 (Lindlar catalyst), is still being utilized at industrial level. Inspired by the very recent strategies involving the modification of Pd with p-block elements (i.e., S), this work extrapolates the concept by preparing crystalline metal phosphides with controlled stoichiometry. To develop an affordable and environmentally-friendly alternative to traditional hydrogenation catalysts, nickel, a metal belonging to the same group as Pd and capable of splitting molecular hydrogen has been selected. Herein, a simple two-step synthesis procedure involving nontoxic precursors was used to synthesize bulk nickel phosphides with different stoichiometries (Ni2P, Ni5P4, and Ni12P5) by controlling the P:Ni ratios. To uncover structural and surface features, this catalyst family is characterized with an array of methods including X-ray diffraction (XRD), 31P magic-angle nuclear magnetic resonance (MAS-NMR) spectroscopy, and X-ray photoelectron spectroscopy (XPS). Bulk-sensitive techniques prove the successful preparation of pure phases while XPS analysis unravels the facile passivation occurring at the NixPy surface that persists even after reductive treatment. To assess the characteristic surface fingerprints of these materials, Ar sputtering was carried out at different penetration depths, reveling the presence of Ni+ and P-species. Continuous-flow three-phase hydrogenations of short-chain acetylenic compounds display that the oxidized layer covering the surface is reduced under reaction conditions, as evidenced by the induction period before reaching the steady state performance. To assess the impact of the phosphidation treatment on catalytic performance, the catalysts were benchmarked against a commercial Ni/SiO2-Al2O3 sample. While Ni/SiO2-Al2O3 presents very low selectivity to the alkene (the selectivity is about 10% at full conversion) attributed to the well-known tendency of naked nickel nanoparticles to form hydrides, the performance of nickel phosphides is highly selective and independent of P:Ni ratio. In line with previous findings on PdxS, kinetic tests indicate the occurrence of a dual-site mechanism where the alkyne and hydrogen do not compete for the same site.
This work is the subject of a publication of which I am a co-author, as cited below.
D. Albani; K. Karajovic; B. Tata; Q. Li; S. Mitchell; N. López; J. Pérez-Ramírez. Ensemble Design in Nickel Phosphide Catalysts for Alkyne Semi-Hydrogenation. ChemCatChem 2019. doi.org/10.1002/cctc.201801430
Project 1 Abstract: Ethylene Oxychlorination
The current two-step process for the industrial process of vinyl chloride production involves CuCl2 catalyzed ethylene oxychlorination to ethylene dichloride followed by thermal cracking of the latter to vinyl chloride. To date, no industrial application of a one-step process is available. To close this gap, this work evaluates a wide range of self-prepared supported CeO2 and EuOCl catalysts for one-step production of vinyl chloride from ethylene in a fixed-bed reactor at 623 773 K and 1 bar using feed ratios of C2H4:HCl:O2:Ar:He = 3:3 6:1.5 6:3:82 89.5. Among all studied systems, CeO2/ZrO2 and CeO2/Zeolite MS show the highest activity but suffer from severe combustion of ethylene, forming COx, while 20 wt.% EuOCl/γ-Al2O3 leads to the best vinyl chloride selectivity of 87% at 15.6% C2H4 conversion with complete suppression of CO2 formation and only 4% selectivity to CO conversion for over 100 h on stream. Characterization by XRD and EDX mapping reveals that much of the Eu is present in non-active phases such as Al2Eu or EuAl4, indicating that alternative synthesis methods could be employed to better utilize the metal. A linear relationship between conversion and metal loading is found for this catalyst, indicating that always part of the used Eu is available as EuOCl, while the rest forms inactive europium aluminate species. Zeolite-supported EuOCl slightly outperforms EuOCl/γ Al2O3 in terms of total yield, but is prone to significant coking and is unstable. Even though a lot of Eu seems locked in inactive species on EuOCl/γ Al2O3, these results indicate possible savings of nearly 16,000 USD per kg of catalyst compared to a bulk EuOCl catalyst. These very promising findings constitute a crucial step for process intensification of polyvinyl chloride production and exploring the potential of supported EuOCl catalysts in industrially-relevant reactions.
Project 2 Abstract: Alkyne Semihydrogenation
Despite strongly suffering from poor noble metal utilization and a highly toxic selectivity modifier (Pb), the archetypal catalyst applied for the three-phase alkyne semihydrogenation, the Pb-doped Pd/CaCO3 (Lindlar catalyst), is still being utilized at industrial level. Inspired by the very recent strategies involving the modification of Pd with p-block elements (i.e., S), this work extrapolates the concept by preparing crystalline metal phosphides with controlled stoichiometry. To develop an affordable and environmentally-friendly alternative to traditional hydrogenation catalysts, nickel, a metal belonging to the same group as Pd and capable of splitting molecular hydrogen has been selected. Herein, a simple two-step synthesis procedure involving nontoxic precursors was used to synthesize bulk nickel phosphides with different stoichiometries (Ni2P, Ni5P4, and Ni12P5) by controlling the P:Ni ratios. To uncover structural and surface features, this catalyst family is characterized with an array of methods including X-ray diffraction (XRD), 31P magic-angle nuclear magnetic resonance (MAS-NMR) spectroscopy, and X-ray photoelectron spectroscopy (XPS). Bulk-sensitive techniques prove the successful preparation of pure phases while XPS analysis unravels the facile passivation occurring at the NixPy surface that persists even after reductive treatment. To assess the characteristic surface fingerprints of these materials, Ar sputtering was carried out at different penetration depths, reveling the presence of Ni+ and P-species. Continuous-flow three-phase hydrogenations of short-chain acetylenic compounds display that the oxidized layer covering the surface is reduced under reaction conditions, as evidenced by the induction period before reaching the steady state performance. To assess the impact of the phosphidation treatment on catalytic performance, the catalysts were benchmarked against a commercial Ni/SiO2-Al2O3 sample. While Ni/SiO2-Al2O3 presents very low selectivity to the alkene (the selectivity is about 10% at full conversion) attributed to the well-known tendency of naked nickel nanoparticles to form hydrides, the performance of nickel phosphides is highly selective and independent of P:Ni ratio. In line with previous findings on PdxS, kinetic tests indicate the occurrence of a dual-site mechanism where the alkyne and hydrogen do not compete for the same site.
This work is the subject of a publication of which I am a co-author, as cited below.
D. Albani; K. Karajovic; B. Tata; Q. Li; S. Mitchell; N. López; J. Pérez-Ramírez. Ensemble Design in Nickel Phosphide Catalysts for Alkyne Semi-Hydrogenation. ChemCatChem 2019. doi.org/10.1002/cctc.201801430
ContributorsTata, Bharath (Author) / Deng, Shuguang (Thesis director) / Muhich, Christopher (Committee member) / Chemical Engineering Program (Contributor, Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Classical planning is a field of Artificial Intelligence concerned with allowing autonomous agents to make reasonable decisions in complex environments. This work investigates
the application of deep learning and planning techniques, with the aim of constructing generalized plans capable of solving multiple problem instances. We construct a Deep Neural Network that, given an abstract problem state, predicts both (i) the best action to be taken from that state and (ii) the generalized “role” of the object being manipulated. The neural network was tested on two classical planning domains: the blocks world domain and the logistic domain. Results indicate that neural networks are capable of making such
predictions with high accuracy, indicating a promising new framework for approaching generalized planning problems.
the application of deep learning and planning techniques, with the aim of constructing generalized plans capable of solving multiple problem instances. We construct a Deep Neural Network that, given an abstract problem state, predicts both (i) the best action to be taken from that state and (ii) the generalized “role” of the object being manipulated. The neural network was tested on two classical planning domains: the blocks world domain and the logistic domain. Results indicate that neural networks are capable of making such
predictions with high accuracy, indicating a promising new framework for approaching generalized planning problems.
ContributorsNakhleh, Julia Blair (Author) / Srivastava, Siddharth (Thesis director) / Fainekos, Georgios (Committee member) / Computer Science and Engineering Program (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
What if unplanned free time could be spent with friends instead of trying to contact them? This app will do that by connecting you with friends who are ready to hang out. Kickback is a mobile app designed to connect individuals with their friends and businesses that offer opportunities to socialize in a group setting. The idea had been floating around in my head for a few years and this creative project gave me the opportunity to try my hand at making the idea into a reality. This thesis is a combination of technical efforts and business know-how that I had to learn in order to keep up along the way.
ContributorsFegard, Nathan (Author) / Sebold, Brent (Thesis director) / Trujillo, Rhett (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Engineering an object means engineering the process that creates the object. Today, software can make the task of tracking these processes robust and straightforward. When engineering requirements are strict and strenuous, software custom-built for such processes can prove essential. The work for this project was developing ICDB, an inventory control and build management system created for spacecraft engineers at ASU to record each step of their engineering processes. In-house development means ICDB is more precisely designed around its users' functionality and cost requirements than most off-the-shelf commercial offerings. By placing a complex relational database behind an intuitive web application, ICDB enables organizations and their users to create and store parts libraries, assembly designs, purchasing and location records for inventory items, and more.
ContributorsNoss, Karl Friederich (Author) / Davulcu, Hasan (Thesis director) / Rios, Ken (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The prevalence of bots, or automated accounts, on social media is a well-known problem. Some of the ways bots harm social media users include, but are not limited to, spreading misinformation, influencing topic discussions, and dispersing harmful links. Bots have affected the field of disaster relief on social media as well. These bots cause problems such as preventing rescuers from determining credible calls for help, spreading fake news and other malicious content, and generating large amounts of content which burdens rescuers attempting to provide aid in the aftermath of disasters. To address these problems, this research seeks to detect bots participating in disaster event related discussions and increase the recall, or number of bots removed from the network, of Twitter bot detection methods. The removal of these bots will also prevent human users from accidentally interacting with these bot accounts and being manipulated by them. To accomplish this goal, an existing bot detection classification algorithm known as BoostOR was employed. BoostOR is an ensemble learning algorithm originally modeled to increase bot detection recall in a dataset and it has the possibility to solve the social media bot dilemma where there may be several different types of bots in the data. BoostOR was first introduced as an adjustment to existing ensemble classifiers to increase recall. However, after testing the BoostOR algorithm on unobserved datasets, results showed that BoostOR does not perform as expected. This study attempts to improve the BoostOR algorithm by comparing it with a baseline classification algorithm, AdaBoost, and then discussing the intentional differences between the two. Additionally, this study presents the main factors which contribute to the shortcomings of the BoostOR algorithm and proposes a solution to improve it. These recommendations should ensure that the BoostOR algorithm can be applied to new and unobserved datasets in the future.
ContributorsDavis, Matthew William (Author) / Liu, Huan (Thesis director) / Nazer, Tahora H. (Committee member) / Computer Science and Engineering Program (Contributor, Contributor) / Department of Information Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12