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The functional programming paradigm is able to provide clean and concise solutions to many common programming problems, as well as promote safer, more testable code by encouraging an isolation of state-modifying behavior. Functional programming is finding its way into traditionally object-oriented and imperative languages, most notably with the introduction of Java 8 and in LINQ for C#. However, no functional programming language has achieved widespread adoption, meaning that students without a formal computer science background who learn technology on-demand for personal projects or for business may not come across functional programming in a significant way. Programmers need a reason to spend time learning these concepts to not miss out on the subtle but profound benefits they provide. I propose the use of a video game as an environment in which learning functional programming is the player's goal. In this carefully constructed video game, learning functional programming is the key to progression. Players will be motivated to learn and will be given an immediate chance to test and demonstrate their understanding. The game, named Lambda Starship (stylized as (lambda () starship)), is a 3D first-person video game. It takes place in a spaceship that, due to extreme magnetic interference, has lost all on-board software while leaving the hardware completely intact. The player is tasked to write software using functional programming paradigms to replace the old software and bring the spaceship back to a working state. Throughout the process, the player is guided by an in-game manual and other descriptive resources. The game is implemented in Unity and scripted using C#. The game's educational and entertainment value was evaluated with a study case. 24 undergraduate students at Arizona State University (ASU) played the game and were surveyed detailing their experience. During play, user statistics were recorded automatically, providing a data-driven way to analyze where players struggled with the concepts introduced in the game. Reception was neutral or positive in both the entertainment and educational sides of the game. A few players expressed concerns about the manual in its form factor and engagement value.
ContributorsCompton, Tyler Alexander (Author) / Gonzalez-Sanchez, Javier (Thesis director) / Bansal, Srividya (Committee member) / Software Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Brains and computers have been interacting since the invention of the computer. These two entities have worked together to accomplish a monumental set of goals, from landing man on the moon to helping to understand how the universe works on the most microscopic levels, and everything in between. As the years have gone on, the extent and depth of interaction between brains and computers have consistently widened, to the point where computers help brains with their thinking in virtually infinite everyday situations around the world. The first purpose of this research project was to conduct a brief review for the purposes of gaining a sound understanding of how both brains and computers operate at fundamental levels, and what it is about these two entities that allow them to work evermore seamlessly as the years go on. Next, a history of interaction between brains and computers was developed, which expanded upon the first task and helped to contribute to visions of future brain-computer interaction (BCI). The subsequent and primary task of this research project was to develop a theoretical framework for a potential brain-aiding device of the future. This was done by conducting an extensive literature review regarding the most advanced BCI technology in modern times and expanding upon the findings to argue feasibility of the future device and its components. Next, social predictions regarding the acceptance and use of the new technology were made by designing and executing a survey based on the Unified Theory of the Acceptance and Use of Technology (UTAUT). Finally, general economic predictions were inferred by examining several relationships between money and computers over time.
ContributorsThum, Giuseppe Edwardo (Author) / Gaffar, Ashraf (Thesis director) / Gonzalez-Sanchez, Javier (Committee member) / College of Integrative Sciences and Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Intelligence is a loosely defined term, but it is a quality that we try to measure in humans, animals, and recently machines. Progress in artificial intelligence is slow, but we have recently made breakthroughs by paying attention to biology and neuroscience. We have not fully explored what biology has to offer us in AI research, and this paper explores aspects of intelligent behavior in nature that machines still struggle with.
ContributorsLahtinen, David (Author) / Gaffar, Ashraf (Thesis director) / Sanchez, Javier Gonzalez (Committee member) / Software Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Affective computing allows computers to monitor and influence people’s affects, in other words emotions. Currently, there is a lot of research exploring what can be done with this technology. There are many fields, such as education, healthcare, and marketing, that this technology can transform. However, it is important to question what should be done. There are unique ethical considerations in regards to affective computing that haven't been explored. The purpose of this study is to understand the user’s perspective of affective computing in regards to the Association of Computing Machinery (ACM) Code of Ethics, to ultimately start developing a better understanding of these ethical concerns. For this study, participants were required to watch three different videos and answer a questionnaire, all while wearing an Emotiv EPOC+ EEG headset that measures their emotions. Using the information gathered, the study explores the ethics of affective computing through the user’s perspective.
ContributorsInjejikian, Angelica (Author) / Gonzalez-Sanchez, Javier (Thesis director) / Chavez-Echeagaray, Maria Elena (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
As autonomous vehicle development rapidly accelerates, it is important to not lose sight of what the worst case scenario is during the drive of an autonomous vehicle. Autonomous vehicles are not perfect, and will not be perfect for the foreseeable future. These vehicles will shift the responsibility of driving to the passenger in front of the wheel, regardless if said passenger is prepared to do so. However, by studying the human reaction to an autonomous vehicle crash, researchers can mitigate the risk to the passengers in an autonomous vehicle. Located on the ASU Polytechnic campus, there is a car simulation lab, or SIM lab, that enables users to create and simulate various driving scenarios using the Drive Safety and HyperDrive software. Using this simulator and the Window of Intervention, the time a driver has to avoid a crash, vital research into human reaction time while in an autonomous environment can be safely performed. Understanding the Window of Intervention is critical to the development of solutions that can accurately and efficiently help a human driver. After first describing the simulator and its operation in depth, a deeper look will be offered into the autonomous vehicle field, followed by an in-depth explanation into the Window of Intervention and how it is studied and an experiment that looks to study both the Window of Intervention and human reactions to certain events. Finally, additional insight from one of the authors of this paper will be given documenting their contributions to the study as a whole and their concerns about using the simulator for further research.
ContributorsSalceda, Rhiannon (Co-author) / Baratti, Alexander (Co-author) / Gaffar, Ashraf (Thesis director) / Gonzalez Sanchez, Javier (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
DescriptionThis document explains the design of a traffic simulator based on an integral-based state machine. This simulator is different from existing traffic simulators because it is driven by a flexible model that supports many different light configurations and has a user-friendly interface.
ContributorsSapp, Curtis Mark (Author) / Gaffar, Ashraf (Thesis director) / Gonzalez Sanchez, Javier (Committee member) / Software Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
In this paper, I explore practical applications of neural networks for automated skin lesion identification. The visual characteristics are of primary importance in the recognition of skin diseases, hence, the development of deep neural network models proven capable of classifying skin lesions can potentially change the face of modern medicine by extending the availability and lowering the cost of diagnostic care. Previous work has demonstrated the effectiveness of convolutional neural networks in image classification in general, with even higher accuracy achievable by data augmentation techniques, such as cropping, rotating, and flipping input images, along with more advanced computationally intensive approaches. In this research, I provide an overview of Convolutional Neural Networks (CNN) and CNN implementation with TensorFlow and Keras API in context of image recognition and classification. I also experiment with custom convolutional neural network model architecture trained using HAM10000 dataset. The dataset used for the case study is obtained from Harvard Dataverse and is maintained by Medical University of Vienna. The HAM10000 dataset is a large collection of multi-source dermatoscopic images of common pigmented skin lesions and is available for academic research under Creative Commons Attribution-Noncommercial 4.0 International Public License. With over ten thousand dermatoscopic images of seven classes of benign and malignant skin lesions, the dataset is substantial for academic machine learning purposes for multiclass image classification. I discuss the successes and shortcomings of the model in respect to its application to the dataset.
ContributorsKaraliova, Natallia (Author) / Bansal, Ajay (Thesis director) / Gonzalez-Sanchez, Javier (Committee member) / Software Engineering (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05