Digital Commons Network^™

Manipulative, Dark, And Unethical Design Practices In Ui & Ux Design, Ryan Edward Brown

Honors Theses

This thesis examines the pervasive and detrimental effects of manipulative user interface and user experience design (UI/UX) practices on individuals and society. Focusing on three critical areas – accessibility, dark patterns, and polarization – the study employs a mixed-methods approach, combining findings from a comprehensive literature review, an analysis of specific design patterns and methods, and a survey of user experiences.
The literature review covers topics such as the importance of accessibility in design education, the prevalence of dark patterns in mobile and desktop sites, the role of personalization algorithms in shaping user experiences, and the formation of echo chambers …

Theoretical Spectroscopic Predictions Of Electronically Excited States, Noah R. Garrett

Honors Theses

The quest for faster computation of anharmonic vibrational frequencies of both ground and excited electronic states has led to combining coupled cluster theory harmonic force constants with density functional theory (DFT) cubic and quartic force constants for defining a quartic force field (QFF) utilized in conjunction with vibrational perturbation theory at second order (VPT2). This work shows that explicitly correlated coupled cluster theory at the singles, doubles, and perturbative triples level [CCSD(T)-F12] provides accurate anharmonic vibrational frequencies and rotational constants when conjoined with any of B3LYP, CAM-B3LYP, BHandHLYP, PBE0, and ωB97XD for roughly one-quarter of the computational time of the …

Learning Scene Semantics For 3d Scene Retrieval, Natalie Gleason

Honors Theses

This project presents a comprehensive exploration into semantics-driven 3D scene retrieval, aiming to bridge the gap between 2D sketches/images and 3D models. Through four distinct research objectives, this project endeavors to construct a foundational infrastructure, develop methodologies for quantifying semantic similarity, and advance a semantics-based retrieval framework for 2D scene sketch-based and image-based 3D scene retrieval. Leveraging WordNet as a foundational semantic ontology library, the research proposes the construction of an extensive hierarchical scene semantic tree, enriching 2D/3D scenes with encoded semantic information. The methodologies for semantic similarity computation utilize this semantic tree to bridge the semantic disparity between 2D …

Reviving The Past: Enhancing Language Models With Historical Text Optimization, Heather D. Broome

Honors Theses

Recent advancements in Natural Language Processing (NLP) have brought attention to the significant potential that exists for widespread applications of Large Language Models (LLMs). As demands and expectations for LLMs rise, ensuring efficiency and accuracy becomes paramount. Addressing these challenges requires more than just optimizing current techniques; it urges novel approaches to NLP as a whole. This study investigates novel data preprocessing methods designed to enhance LLM performance by mitigating inefficiencies rooted in natural language, particularly by simplifying the complexities presented by historical texts. Utilizing the classical text The Odyssey by Homer, two preprocessing techniques are introduced: tokenization of names …

Guardians Of The Data: Government Use Of Ai And Iot In The Digital Age, Jannat Saeed

Honors Theses

The exponential growth of technology, epitomized by Moore's Law – “the observation that the number of transistors on an integrated circuit will double every two years”– has propelled the swift evolution of Artificial Intelligence (AI) and Internet of Things (IoT) technologies. This phenomenon has revolutionized various facets of daily life, from smart home devices to autonomous vehicles, reshaping how individuals interact with the world around them. However, as governments worldwide increasingly harness these innovations to monitor and collect personal data, profound privacy concerns have arisen among the general populace. Despite the ubiquity of AI and IoT in modern society, formal …

Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, Rebecca Clark

Honors Theses

Cyberattacks are increasing in size and scope yearly, and the most effective and common means of attack is through malicious software executed on target devices of interest. Malware threats vary widely in terms of behavior and impact and, thus, effective methods of detection are constantly being sought from the academic research community to offset both volume and complexity. Rootkits are malware that represent a highly feared threat because they can change operating system integrity and alter otherwise normally functioning software. Although normal methods of detection that are based on signatures of known malware code are the standard line of defense, …

Sign-A-Mander: A Mobile App That Enhances Asl Learning With Computer Vision, Sandrine Adap

Honors Theses

Several machine learning researchers have developed algorithms recognizing American Sign Language (ASL), but few have applied the algorithms to real-world situations, such as with portable ASL learning applications. This project develops a beta version of a mobile application designed to allow beginner ASL learners to practice basic ASL vocabulary and receive feedback about their signing accuracy. Building on Dongxu Li et al.’s I3D sign language recognition algorithm and 2000-word dataset, the app seeks to determine whether the I3D algorithm can sufficiently recognize a user’s motions when recorded from a mobile device and accurately classify whether or not the user signed …

Andrews University Pre-Professional Students Preparedness For A Future With Artificial Intelligence, Zachary Alignay

Honors Theses

Artificial Intelligence technology has advanced considerably over the past four years. With such rapid technological development, the question has to be asked if students are adequately educated on the implications and abilities of artificial intelligence. Are Andrews University pre-professional students prepared for future careers with artificial intelligence? To approach this question, a survey of students across multiple perspectives was conducted to sample if there was a consensus, or lack thereof, on the perception of ethics regarding artificial intelligence, to ask students how using artificial intelligence has changed their education, what purposes it can be used or cannot be used, personal …

5675 Wiredcats Scouting Hub, Sebastian Smiley

Honors Theses

The WiredCats Scouting Hub was created to provide FIRST team 5675 with an application that allows them to make more informed strategic decisions regarding their competitive play. The app synthesizes data from multiple sources, parsing multiple data formats into a single source of truth. It also presents data to users through graphs and charts and provides interactive tables. The application meets the requirements set forth by the leadership of team 5675, effectively providing the capabilities they seek.

Kalamazoo Nature Center Mobile Application, Jacob Tebben

Honors Theses

This project aimed to address the challenge of enhancing visitor engagement and information dissemination at the Kalamazoo Nature Center (KNC) through the development of an integrated mobile and desktop application system. This initiative arose due to the limitations posed by traditional mobile applications which often become outdated and need to be updated by a dedicated software team. This project was designed for any user of the KNC desktop app to be able to update content on the mobile app, without the need of a dedicated software team.

The mobile application was designed for visitor use, enabling them to access up-to-date …

Privacy Within Autonomous Vehicle Cameras, Joshua Montgomery

Honors Theses

In recent years, cameras have become ubiquitous in daily life, constantly surveilling, and taking in information. This leads to a potential security risk of the invasion in one’s privacy without their knowledge or any ability to prevent the privacy threat. While cameras alone are an issue, they are often only in locations where a user has some expectation of a loss of privacy, such as public locations with security systems. However, systems that rely on cameras to operate correctly, including autonomous vehicles, are becoming a more prominently used technology while often appearing in places where an average person has some …

Ensuring Non-Repudiation In Long-Distance Constrained Devices, Ethan Blum

Honors Theses

Satellite communication is essential for the exploration and study of space. Satellites allow communications with many devices and systems residing in space and on the surface of celestial bodies from ground stations on Earth. However, with the rise of Ground Station as a Service (GsaaS), the ability to efficiently send action commands to distant satellites must ensure non-repudiation such that an attacker is unable to send malicious commands to distant satellites. Distant satellites are also constrained devices and rely on limited power, meaning security on these devices is minimal. Therefore, this study attempted to propose a novel algorithm to allow …

Economic Value Of User Interface Design, Anna Kruse

Honors Theses

The economic value of well-designed user interfaces (UI) and user experiences (UX) is challenging to quantify, a topic that the current literature does not sufficiently explore. Those responsible for deciding whether to invest resources in UI/UX typically base these decisions on monetary considerations. The link between effective UI/UX design and profit may not be immediately clear to most, yet it is universally acknowledged that satisfied customers lead to successful business. To underscore the importance of investing in UI/UX, it is crucial to define the relationship between effective design and economic success in a way that can be understood by designers, …

Identifying Key Activity Indicators In Rats' Neuronal Data Using Lasso Regularized Logistic Regression, Avery Woods

Honors Theses

This thesis aims to identify timestamps of rats’ neuronal activity that best determine behavior using a machine learning model. Neuronal data is a complex and high-dimensional dataset, and identifying the most informative features is crucial for understanding the underlying neuronal processes. The Lasso regularization technique is employed to select the most relevant features of the data to the model’s prediction. The results of this study provide insights into the key activity indicators that are associated with specific behaviors or cognitive processes in rats, as well as the effect that stress can have on neuronal activity and behavior. Ultimately, it was …

Exploration Of Feature Selection Techniques In Machine Learning Models On Hptlc Images For Rule Extraction, Bozidar-Brannan Kovachev

Honors Theses

Research related to Biology often utilizes machine learning models that are ultimately uninterpretable by the researcher. It would be helpful if researchers could leverage the same computing power but instead gain specific insight into decision-making to gain a deeper understanding of their domain knowledge. This paper seeks to select features and derive rules from a machine learning classification problem in biochemistry. The specific point of interest is five species of Glycyrrhiza, or Licorice, and the ability to classify them using High-Performance Thin Layer Chromatography (HPTLC) images. These images were taken using HPTLC methods under varying conditions to provide eight …

Digital Dna: The Ethical Implications Of Big Data As The World’S New-Age Commodity, Clark H. Dotson

Honors Theses

In the emerging digital world that we find ourselves in, it becomes apparent that data collection has become a staple of daily life, whether we like it or not. This research discussion aims to bring light to just how much one’s own digital identity is valued in the technologically-infused world of today, with distinct research and local examples to bring awareness to the ethical implications of your online presence. The paper in question examines anecdotal and research evidence of the collection of data, both through true and unjust means, as well as ethical implications of what this information truly represents. …

Designing Programming Languages For Writing Maintainable Software, Aaron Friesen

Honors Theses

Maintainability is crucial to the long-term success of software projects. Among other factors, it is affected by the programming language in which the software is written. Programming language designers should be conscious of how their design decisions can influence software maintainability. Non-functional properties of a language can affect the readability of source code in ways beyond the control of programmers. Language features can cause or prevent certain classes of bugs, and runtime issues especially can require significant maintenance effort. Tools external to the language, especially those developed and distributed by language implementers, can aid in the creation of maintainable software. …

Computer Organization And Assembly Language Embedded Firmware Overhaul, Elaine Yun Ru Chan

Honors Theses

The WMU Computer Organization and Assembly Language class has encountered some difficulties in the past several years regarding the procurement of required hardware and software for the curriculum. This has led to a number of challenges for students, including:

• Difficulty in obtaining the necessary hardware and software

• Inability to complete assignments and projects due to hardware or software failures

• Frustration and anxiety caused by the challenges of the course

To address these challenges, a new choice of embedded firmware was researched and developed. This firmware allows for more reliable flashing of the MSP430 Microcontroller and remains reliable on modern operating …

Tracking System Effectiveness For Texas Police Departments In Low-Income Communities, Jakob Scarcelli

Honors Theses

No abstract provided.

On The Pursuit Of Developer Happiness: Webcam-Based Eye Tracking And Affect Recognition In The Ide, Tamsin Rogers

Honors Theses

Recent research highlights the viability of webcam-based eye tracking as a low-cost alternative to dedicated remote eye trackers. Simultaneously, research shows the importance of understanding emotions of software developers, where it was found that emotions have significant effects on productivity, code quality, and team dynamics. In this paper, we present our work towards an integrated eye-tracking and affect recognition tool for use during software development. This combined approach could enhance our understanding of software development by combining information about the code developers are looking at, along with the emotions they experience. The presented tool utilizes an unmodified webcam to capture …

The Implementation Of Augmented Reality And Low Latency Protocols In Musical Instrumental Collaborations, Qixiao Zhu

Honors Theses

Past projects involving musical software have been completely virtual, while these software do well in entertainment and education, there is the question of whether these software are playable to the same extent as physical musical instruments. The software presented in this paper, "AR Jam", utilizes various software and hardware tools to form a networked mixed reality system for the users to play music on. The intention of this project is to seek new ways to explore more playable musical instruments in the digital world. The paper presents the software's implementation, challenges such as optimization problems of the synthesizer, and the …

Critically Observing The Challenges And Changes: An Analysis On Covid-19’S Impact With An Emphasis On Students In Higher Education, Landon Perkins

Honors Theses

This project involves comparing different visualizations related to COVID-19 and higher education in order to determine key impacts of the COVID-19 pandemic on students in higher education, as well as higher education as a whole. The main metrics used to determine the impact were mental health indicators for anxiety or depressive disorders, enrollment numbers by control type (public, private non-profit, or private for-profit) and state for 2020 and 2021, and state mandate lift dates for a variety of mandates implemented across the United States. These metrics were analyzed both individually and against each other to determine if they had any …

Improving Adjacency List Storage Methods For Polypeptide Similarity Analysis, Arianna Swensen

Honors Theses

Protein design is a complex biomolecular and computational problem. Working on increasingly large protein folding problems requires an improvement in current analysis methods available. This work first discusses various methods of protein design, including de novo protein design, which is the primary focus of this thesis. Then, a new approach utilizing a B+ tree to effectively store and query a graph of keys and vertices is proposed in order to store the number of times two polypeptides are considered to be similar. This approach is found to have a reduction in time complexity from current mapping methods and thus provides …

Impact Of Movements On Facial Expression Recognition, Zhebin Yin

Honors Theses

The ability to recognize human emotions can be a useful skill for robots. Emotion recognition can help robots understand our responses to robot movements and actions. Human emotions can be recognized through facial expressions. Facial Expression Recognition (FER) is a well-established research area, how- ever, the majority of prior research is based on static datasets of images. With robots often the subject is moving, the robot is moving, or both. The purpose of this research is to determine the impact of movement on facial expression recognition. We apply a pre-existing model for FER, which performs around 70.86% on a given …

Tracking Xenophobic Terminology On Twitter Using Nlp, Harper Lyon

Honors Theses

Social media is a major driver of political thought, with platforms like Facebook, Twitter, and TikTok having a massive impact on how people think and vote. For this reason we should take seriously any large shifts in the language used to describe issues or groups on social media, as these are likely to either denote a change in political thought or even forecast the same. Of particular interest, given the international reach of social media, is the way that discussions around foreign relations and immigration play out. In the United States of America online spaces have become the default space …

Corrective Feedback Timing In Kanji Writing Instruction Apps, Phoenix Mulgrew

Honors Theses

The focus of this research paper is to determine the correct time to provide corrective feedback to people who are learning how to write Japanese kanji. To do this, we developed a system that is able to recognize Japanese kanji that is handwritten onto an iPad screen and check for errors such as wrong stroke order. Previous research has achieved success in developing similar systems, but this project is unique because the research question involves the timing of corrective feedback. In particular, we are looking at whether immediate or delayed corrective feedback results in better learning.

Investigation Of Python Variable Privacy, Joshua Bartholomew

Honors Theses

This study looks at the relative security of Python regarding private variables and functions used in most other programming languages. Python has only grown in popularity due to its simple syntax and developing capabilities. However, little research has been published about how secure Python code and programs compiled from Python code actually are. This research seeks to expose vulnerabilities in Python code and determine what must be done for these vulnerabilities to be exploited by hackers to abuse potentially sensitive information contained within the program.

The proposed methodology includes examining the private variable concept in other programming languages and conducting …

Real Time Call-Flagging System To Respond To Suicidal Ideation In Call Centers, Vishnu Menon, Joseph Carrigan, Charles Floeder, Thomas Walton, Devin Mcguire

Honors Theses

The 2021-2022 Signature Performance Design Studio team developed a live audio call-flagging system that enables faster responses and new response pathways to veteran crises by call service representatives and their management team. Using a custom made deep learning model, live audio streaming server, and Teams broadcasting add-on, the system empowers Signature Performance call service representatives to make quicker and more well informed decisions to provide veteran’s the best care possible.

Analysis Of The Effectiveness Of Different Techniques For Creating Cross-Platform Compatible Software, Michael Westberg

Honors Theses

Creating cross-platform compatible software is a major issue in a world where users utilize a variety of devices and platforms. To ensure that a piece of software is accessible to as many users as possible, software must be cross-platform compatible. There are four main approaches that can be done to achieve this state of being cross-platform compatible, each with both advantages and disadvantages. These methods are: creating the software as separate binaries, using a scripting language with a cross-platform interpreter, compiling to an intermediate language, and creating the software as a web application. This paper will discuss how each of …

A Framework Comparison: .Net And Laravel, Guy Richard

Honors Theses

No abstract provided.