Computer Engineering Commons^™

In Situ Water Sensing Systems: Research On Advancements In Environmental Monitoring, Abigail Seibel

Honors Theses

In this work, two sensing systems were researched in order to improve in situ environmental monitoring. The first is a pH and Total Alkalinity sensor used to determine these characteristics of sea water. I explored the facets of this sensor over a 7-week internship with Dr. Ellen Briggs in her lab in summer of 2023. The second is a more holistic sensing system that reads temperature, turbidity, and pressure used for studying environmental characteristics of Alaskan bever ponds. Both systems were developed in close collaboration with scientists who are collecting data to better understand the impacts of climate change. Better …

Modern Practices For Responsive Web Design And Web Accessibility, Keyaun Washington

Honors Theses

Responsive web design and web accessibility play crucial roles in ensuring an optimal user experience on the web. By designing websites with responsiveness and accessibility in mind, more opportunities are opened up for a wider audience to access and interact with our content. Through modern practices, responsive web design allows websites to reach several different devices ranging from compact smartwatches to expansive television screens. Designing for accessibility provides accommodations for individuals with impairments while also providing benefits for individuals without impairments. However, designing for responsiveness and accessibility can present challenges; a poor attempt at providing accessibility features can worsen a …

The Effects Of Social Media On Mental Health And Career Planning, Spencer A. Rowan

Honors Theses

Social media use is prevalent and necessary in society—nearly anything can be accomplished with a mobile device or smartphone. Among the US population, two thirds of American adults admit to using social media (Perrin, 2015) and in 2022, Georgiev (2023) found Americans spent an average of two and a half hours daily on social media. Furthermore, social media use is tied to mental well-being, work confidence levels, and feelings of being an imposter (Johnson et al., 2020; Uram & Skalski, 2022; Hernandez & Chalk, 2021; Myers, 2021; Ramm, 2019).

This project examined the role of social media use among college …

The Effects Of Virtual Reality On Mental Health Software User Satisfaction And Retention, William Hooten

Honors Theses

Mental health issues have become increasingly important in today's society. With that being said, researchers and consumers are looking for new ways to manage and treat mental health using new technologies in labs and the consumer space. This innovation has led to the presence of mobile self-help mental health applications, applications for peoples’ phones that are used to manage symptoms of mental health problems, such as depression and anxiety, track goals, meditate, and more. However, mobile mental health applications, and mobile applications in general, have a problem concerning user satisfaction and overall user retention – studies have shown that 95% …

An Ios Application For Visually Impaired Individuals To Assist With Crossing Roads, Ali Khan

Honors Theses

In day-to-day life, visually impaired individuals face the problem of crossing roads by themselves. This project was designed and built to solve this key issue. The system is supposed to give the user a warning before approaching a crosswalk for their safety and also give information about when it is safe to cross the road. An iOS application was developed to address the problem since recent studies have discovered that a vast number of visually impaired individuals are using smartphones (iPhones in particular) due to the ease and convenience it brings to their daily life. The application should be able …

Examining The Wording Of Digital Synthesizer Presets To Help Novice Producers, Nicholas O'Toole

Honors Theses

My research looks into the use of ”presets” in digital synthesizers, which alter the timbre (quality) of the synthesizer’s sound by loading in pre-selected configurations of settings. My study compares imagery- based and feelings-based preset names – for example, Cloud City Keys and Mellow lead, respectively – in an attempt to see which better predicts the sound it represents. Through my results, I will then explain how the wording of these preset names affected my subjects’ perception of certain sounds. The results I found lead me to believe that imagery-based preset names could be representative of their respective presets’ sounds.

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 …

Evaluation Of Selected Computer Software For Concussion Recovery And Diagnosis, J.P. Jensen

Honors Theses

Acquired traumatic brain injuries, such as concussions, impact many athletes participating in sports, particularly at the high school, collegiate, and professional levels. The risks posed by concussions – particularly when an athlete suffers repeated injuries – demands that protocols and tools be developed to maximize athlete health and safety. Computer technology can perform critical roles in the analysis and management of concussions. While specialized devices in the areas of imaging and impact sensing, are most associated with concussion management, researchers within the last two decades have increasingly explored the incorporation of various consumer technologies into the identification and treatment of …

Data Management In Web Applications To Balance Performance And Security, Caleb Marcoux

Honors Theses

As web applications become increasingly popular, many are running several calculations and data processing on the client machine, it is important to consider data management practices on the front-end of these web applications. Typically, some data from the server is stored in the client's memory or hard disk. How much data should be stored for how long, as well as many other considerations, influence the time and space performance of the web application, as well as its security. In this thesis, we explore several challenges, solutions, and design patterns in web application data management through the lens of a senior …

Designing A Digital Electronics Lab, Ben Buckwalter

Honors Theses

Hardware electronics tools can be more expensive than a new learner is willing to invest resulting in a barrier to entry. Furthermore, it can be difficult for a new learner to know where to start when learning electronics. To resolve this issue, we first explore current mobile app solutions that provide free electronics tooling. Then, we propose a design for a new mobile app that contains basic function generator and oscilloscope functionality as well as the learning resources necessary in order to guide new learners in the basics of digital electronics.

Design Of Hardware To Aid Smartphone-Based Oscilloscope App, Riddock Moran

Honors Theses

A smartphone-based oscilloscope improves on traditional lab oscilloscopes in accessibility and portability but faces several performance limitations compared to traditional oscilloscopes. Among these, an oscilloscope app that uses the phone’s audio to read voltage signals will have a sampling rate and voltage bottlenecked by the capabilities of the audio codec, which will rarely exceed a rate of 48 kHz and 1 volt, respectively. Additionally, smartphones lack the ability to read line-in audio, allowing only one channel input through the microphone. Direct connections to an audio source may not be possible due to requiring an audio jack connection, and different poles …

Comparative Analysis Of Imputation Methods In Real Estate Data, Connor Donlen

Honors Theses

This project involves comparing different methods of missing data imputation in the context of predicting real estate listing prices. These methods are compared against each other in both their ability to recreate the original data and their effects on a final predictive model. In order to evaluate their effectiveness, first, a predictive model is made using the complete dataset to use as a benchmark for the imputed datasets. Then, a complete dataset is split into 80% training and 20% testing datasets, and missing values are created in the training data using two different missing data mechanisms, missing completely at random …

Privacy-Preserving Blockchain-Based Registration Scheme For Av Parking System, Alexander Haastrup

Honors Theses

Autonomous Vehicles (AV) are a prime example of how innovation and automation are at the forefront of growing technology trends. The concern of parking systems is becoming apparent as research into ways to increase the efficiency and cost-effectiveness of AV continues. To ward against various internet attackers and secure users' sensitive information, an efficient AV parking system must have powerful user privacy and cyber security capabilities. In my work, I present a blockchain-based privacy registration system for AV parking systems that meets the following criteria. The proposed scheme incorporates k-Nearest Neighbor (kNN) - an efficient and lightweight algorithm - for …

Self-Efficacy Development In Elementary-Aged Learners Through Dance As An Algorithmic Thinking Tool, Niva Shrestha

Honors Theses

The purpose of this research is to demonstrate the effectiveness of a transdisciplinary approach in teaching computational thinking through dance to elementary-aged learners, with primary attention to females. With limited literature available on how pre-adolescents begin to construct conceptions of computer science and other engineering domains, including potential career pathways, the incentive of this project was to leverage a day camp for about 20 rising 3rd - 5th-grade learners to assess their identity development in computer science. Modules that teach computational thinking through dance paired with Unruly splats (block-based programmable electronic gadgets) were implemented. By conducting pre-and post-surveys and a …

Computational Analysis Of The Synthesis Of Hydrogels Using The Diels Alder Reaction, Avery Boley

Honors Theses

No abstract provided.

Art To Influence Creativity In Algorithmic Composition, Tyler Braithwaite

Honors Theses

Advances in Recurrent Neural Network (RNN) techniques have caused an explosion of problems posed that revolve around the mass analysis and generation of sequential data, including symbolic music. Building off the work of Nathaniel Patterson’s Musical Autocomplete: An LSTM Approach, we extend this problem of continuing a composition by examining the creative impact that injecting latent-space encoded image data, specifically fine art from the WikiArt Dataset, has on the musical output of RNN architectures designed for autocomplete. For comparison purposes with Patterson, we will also be using a corpus of Erik Satie’s piano music for training, validation, and testing.

Ux/U-Eye: Designing Graphical User Interfaces For Exclusive Eye Gaze Control, Timothy Curol

Honors Theses

No abstract provided.

Generative Adversarial Networks Take On Hand Drawn Sketches: An Application To Louisiana Culture And Mardi Gras Fashion, Stephanie Hines

Honors Theses

No abstract provided.

Conditional Variational Autoencoder (Cvae) For The Augmentation Of Ecl Biosensor Data, Matthew Dulcich

Honors Theses

Machine Learning (ML) is vastly improving the world, from computer vision to fully self-driving cars, we are now able accomplish objectives that were thought to only be dreams. In order to train ML models accurately, they require mountains of information to work with, but sometimes it becomes impossible to collect the data needed, so we turn to data augmentation. In this project we use a conditional variational auto encoder to supplement the original video electrochemiluminescence biosensor dataset, in order to increase the accuracy of a future classification model. In other words, using a cVAE we will create unique realistic videos …

Exploring The Efficiency Of Neural Architecture Search (Nas) Modules, Joshua Dulcich

Honors Theses

Machine learning is obscure and expensive to develop. Neural architecture search (NAS) algorithms automate this process by learning to create premier ML networks, minimizing the bias and necessity of human experts. From this recently emerging field, most research has focused on optimizing a promisingly unique combination of NAS’s three segments. Despite regularly acquiring state of the art results, this practice sacrifices computing time and resources for slight increases in accuracy; this also obstructs performance comparison across papers. To resolve this issue, we use NASLib’s modular library to test the efficiency per module in a unique subset of combinations. Each NAS …

Seabem: An Artificial Intelligence Powered Web Application To Predict Cover Crop Biomass, Aime Christian Tuyishime, Andrea Basche

Honors Theses

SEABEM, the Stacked Ensemble Algorithms Biomass Estimator Model, is a web application with a stacked ensemble of Machine Learning (ML) algorithms running on the backend to predict cover crop biomass for locations in Sub-Saharan. The SEABEM model was developed using a previously developed database of crop growth and yield that included site characteristics such as latitude, longitude, soil texture (sand, silt, and clay percentages), temperature, and precipitation. The goal of SEABEM is to provide global farmers, mainly small-scale African farmers, the knowledge they need before practicing and benefiting from cover crops while avoiding the expensive and time-consuming operations that come …

90snet:, Seth Richard

Honors Theses

No abstract provided.

Iot Greenhouse Monitoring System, Raj Basnet

Honors Theses

Our project is a greenhouse monitoring system. The customer states that they need a complete monitoring system for their greenhouse. There are a lot of items within the greenhouse that need to be watered at the right time and kept at a certain temperature. The customer is not always around to check the status of these items due to their busy lifestyle. They would like a system to monitor all these items so they can check it on their smartphone no matter how far away they are from the greenhouse. The customer wants this to be a low-cost and energyefficient …

Iot Garden Frost Alarm, Andrew James

Honors Theses

Home gardeners are faced with yearly challenges due to spring frosts harming young plants. This is frequently mitigated by covering crops with frost blankets, but only on nights when a frost is predicted. In areas with less predictable climate, an unexpected frost can kill vulnerable plants, reducing the amount of food produced. A system is proposed and designed here to use internet of things (IoT) technology to enable a small weather station in the home garden to report current climate data and predict frosts, then alert the gardener in time for them to cover their plants.

The system as designed …

A Study Of Deep Reinforcement Learning In Autonomous Racing Using Deepracer Car, Mukesh Ghimire

Honors Theses

Reinforcement learning is thought to be a promising branch of machine learning that has the potential to help us develop an Artificial General Intelligence (AGI) machine. Among the machine learning algorithms, primarily, supervised, semi supervised, unsupervised and reinforcement learning, reinforcement learning is different in a sense that it explores the environment without prior knowledge, and determines the optimal action. This study attempts to understand the concept behind reinforcement learning, the mathematics behind it and see it in action by deploying the trained model in Amazon's DeepRacer car. DeepRacer, a 1/18^th scaled autonomous car, is the agent which is trained …

Wearables And Wearable Data In Tele-Health Applications, Jack Mazza

Honors Theses

With the sudden emergence of Covid-19, Tele-Health has been forced into the forefront of healthcare. With no human contact, regular in-person doctor or clinic visits could not be made. Unfortunately, there is a gap in patient data for healthcare professionals when making diagnoses remotely. Fortunately, many users are constantly collecting some primary health data through wearables that have become commonplace in users' homes. Tapping into this unused data could provide healthcare professionals with a better picture of patients' health remotely. In this thesis, I will determine whether this wearable data can be a viable addition to Tele-Health applications, providing additional …

Evaluation Of State-Of-The-Art Nlp Deep Learning Architectures On Commonsense Reasoning Task, Guo Rui (Justin) Lee

Honors Theses

The goal of this project was to explore modern neural network technology in the application of discerning and generating statements that are ‘reasonable’, in what is known as commonsense reasoning. We built off of the work of Saeedi et al. In their work on the 2020 SemEval task, Commonsense Validation and Explanation (ComVE). SemEval is a workshop that creates a variety of semantic evaluation tasks to examine the state of the art in the practical application of natural language processing. This particular task involved three sections: task A, Validation, in which a program tries to select which of two statements …

Non-Linear Dimensionality Reduction Using Auto-Encoder For Optimized Malaria Infected Blood Cell Classifier, Aayush Dhakal

Honors Theses

Neural Networks have been widely used in the problem of Medical Image Analysis. However, when dealing with large images, deep networks easily exhaust computer resources, which in turn hinders training. This paper shows the efficacy of using Auto-Encoders as a dimensionality reduction tool to increase the efficiency of a Malaria Infected Blood Cell Image classifier. We show that using an autoencoder, we can reduce the dimensionality of large blood cell images effectively such that the features in the new space retain all the essential information from the original input. Then we show that the new features obtained from the autoencoder …

Effective Gamification Within Educational Virtual Reality Environments, Adrian Pilkington

Honors Theses

With the advent and now widespread use of mobile phones and computers in educational settings, exploring effective and new ways of using technology in the classroom is important for educating the next generation of students. Innovative technology, like Virtual Reality, has started being discussed and researched for its potential benefits in educational settings. This paper presents a brief history of VR, game theory, and examines two VR educational games from the University of Nebraska-Lincoln College of Nursing’s (UNMC) Senior Design teams. The two games will be used to replace lecture-style classes and to go out and educate the community. We …

The Exploration And Analysis Of Mancala From An Ai Perspective, Trevon J. Hunter

Honors Theses

Through the study of popular games such as Chess and Go, countless artificial intelligence (AI) research has been conducted in an attempt to create algorithms equipped for adversarial search problems. However, there are still a plethora of avenues that offer insight into further development. Mancala is traditionally a two-player board game that originated in the East and offers a unique opponent-based playing experience. This thesis not only attempts to create a competitive AI algorithm for mancala games by analyzing the performance of several different algorithms on this classic board game, but it also attempts to extract applications that may have …