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- All Subjects: Computer Science
- Creators: Barrett, The Honors College
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
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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
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
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
Description
In modern society, computer science (CS) professionals are necessary in the workforce. A growing number of fields and disciplines require the analytical and programming skills that come from a CS education. Despite the growing demand for programmers, the dropout rate within undergraduate CS programs remains high. In an effort to improve retention and make CS more accessible, I prototyped a mobile application that will help students through the principal deterrents that students face in their undergraduate years. Utilizing survey responses from 51 peers I determined the core courses and concepts within the CS curriculum that provoked the most concern to select the topics covered in the mobile application. The results show that the major barrier courses are CSE 310: Data Structures and Algorithms, CSE 340: Principles of Programming Languages, and CSE 355: Introduction to Theoretical Computer Science. Also using interviews and market research, I went through an iterative design process until I arrived at my final prototype that provides users a visual timeline of their program, examples for each individual topic, the ability to interact with other users, and create quizzes covering content they learned. This prototype is intended to lead to a fully developed application that will prepare and encourage students to further their professional careers in CS.
ContributorsRoldan, Jorge (Author) / Ganesh, Tirupalavanam (Thesis director) / Trowbridge, Amy (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Implementing a distributed algorithm is more complicated than implementing a non-distributed algorithm. This is because distributed systems involve coordination of different processes each of which has a partial view of the global system state. The only way to share information in a distributed system is by message passing. Task that are straightforward in a non-distributed system, like deciding on the value of a global system state, can be quite complicated to achieve in a distributed system [1]. On top of the difficulties caused by the distributed nature of the computations, distributed systems typically need to be able to operate normally even if some of the nodes in the system are faulty which further adds to the uncertainty that processes have about the global state. Many factors make the implementation of a distributed algorithms difficult. Design patterns [2] are useful in simplifying the development of general algorithms. A design pattern describes a high level solution to a common, abstract problem that many systems may face. Common structural, creational, and behavioral problems are identified and elegantly solved by design patterns. By identifying features that an algorithm uses, and framing each feature as one of the common problems that a specific design pattern solves, designing a robust implementation of an algorithm becomes more manageable. In this way, design patterns can aid the implementation of algorithms. Unfortunately, design patterns are typically not discussed when developing distributed algorithms. Because correctly developing a distributed algorithm is difficult, many papers (eg. [1], [3], [4]) focus on verifying the correctness of the developed algorithm. Papers that are more practical ([5], [6]) establish the correctness of their algorithm and that their algorithm is efficient enough to be practical. However, papers on distributed algorithms usually make little mention of design patterns. The goal of this work was to gain experience implementing distributed systems including learning the application of design patterns and the application of related technical topics. This was achieved by implementing a currently unpublished algorithm that is tentatively called Bakery Consensus. Bakery Consensus is a replicated state-machine protocol that can tolerate servers with Byzantine faults, but assumes non-faulty clients. The algorithm also establishes non-skipping timestamps for each operation completed by the replicated state-machine. The design of the structure, communication, and creation of the different system parts depended heavily upon the book Design Patterns [2]. After implementing the system, the success of the in implementing its various parts was based upon their ability to satisfy the SOLID [7] principles as well as their ability to establish low coupling and high cohesion [8]. The rest of this paper is organized as follows. We begin by providing background information about distributed algorithms, including replicated state-machine protocols and the Bakery Consensus algorithm. Section 3 gives a background on several design patterns and software engineering principles that were used in the development process. Section 4 discusses the well designed parts of the system that used design patterns, and how these design patterns were chosen. Section 5 discusses well designed system parts that relied upon other technical topics. Section 6 discusses system parts that need redesign. The conclusion summarizes what was accomplished by the implementation process and the lessons learned about design patterns for distributed algorithms.
ContributorsStoutenburg, Tristan Kaleb (Author) / Bazzi, Rida (Thesis director) / Richa, Andrea (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05