Physical Sciences and Mathematics Commons^™

Predictive Machine Learning And Its Future In Professional Basketball, Zachary Harmon

Honors College Theses

Artificial Intelligence (AI) is an ever-evolving field, transforming various aspects of contemporary life. From language models to immersive gaming experiences, AI technologies have become integral to our daily existence. Among the most promising arenas for AI integration is the world of sports. This research delves into the application of machine learning models to predict NBA game outcomes, shedding light on the profound impact of machine learning in the realm of professional basketball. Beyond the scope of game prediction, this study explores the broader implications, such as optimizing the selection of televised games, assisting players in showcasing their skills, and much …

Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan

Computer Science Senior Theses

We introduce a framework that combines Gaussian Process models, robotic sensor measurements, and sampling data to predict spatial fields. In this context, a spatial field refers to the distribution of a variable throughout a specific area, such as temperature or pH variations over the surface of a lake. Whereas existing methods tend to analyze only the particular field(s) of interest, our approach optimizes predictions through the effective use of all available data. We validated our framework on several datasets, showing that errors can decline by up to two-thirds through the inclusion of additional colocated measurements. In support of adaptive sampling, …

Algorithmic Bias: Causes And Effects On Marginalized Communities, Katrina M. Baha

Undergraduate Honors Theses

Individuals from marginalized backgrounds face different healthcare outcomes due to algorithmic bias in the technological healthcare industry. Algorithmic biases, which are the biases that arise from the set of steps used to solve or analyze a problem, are evident when people from marginalized communities use healthcare technology. For example, many pulse oximeters, which are the medical devices used to measure oxygen saturation in the blood, are not able to accurately read people who have darker skin tones. Thus, people with darker skin tones are not able to receive proper health care due to their pulse oximetry data being inaccurate. This …

Universal Back-End Design, Jason Kalili

LMU/LLS Theses and Dissertations

Accessibility in back-end development is often overlooked, with the majority of discussions and efforts centered on front-end design. To make applications usable for a wider audience, developers must also prioritize incorporating accessibility from the back-end. Back-end web accessibility encompasses the design and development of web-based systems and applications that are accessible to all users, including those with disabilities. This involves optimizing the underlying code and infrastructure for accessibility and implementing features that enable users with disabilities to navigate and interact with the site or application. Ensuring back-end web accessibility is crucial for creating an inclusive online environment accessible to everyone, …

Making Music Social: Creating A Spotify-Based Social Media Platform, Dalton J. Craven

Senior Theses

DKMS is a new type of social media platform for music lovers and groups of friends. It integrates tightly with Spotify, one of the largest music streaming services in the world. Users of DKMS can see what their friends are listening to, receive recommendations of new songs to listen to, and analyze their several key numerical metrics (happiness, danceability, loudness, and energy) of their top songs.

DKMS was built as part of the year-long Capstone senior design course at the University of South Carolina. A deployed app is visible at https://dkms.vercel.app, and the open-source code is visible at https://github.com/SCCapstone/DKMS.

Making Sense Of Big (Kinematic) Data: A Comprehensive Analysis Of Movement Parameters In A Diverse Population, Naomi Wilma Nunis

University of the Pacific Theses and Dissertations

OBJECTIVE

The purpose of this study was to determine how kinematic, big data can be evaluated using computational, comprehensive analysis of movement parameters in a diverse population.

METHODS

Retrospective data was collected, cleaned, and reviewed for further analysis of biomechanical movement in an active population using 3D collinear resistance loads. The active sample of the population involved in the study ranged from age 7 to 82 years old and respectively identified as active in 13 different sports. Moreover, a series of exercises were conducted by each participant across multiple sessions. Exercises were measured and recorded based on 6 distinct biometric …

Obstacles In Learning Algorithm Run-Time Complexity Analysis, Bailey Licht

Theses/Capstones/Creative Projects

Algorithm run-time complexity analysis is an important topic in data structures and algorithms courses, but it is also a topic that many students struggle with. Commonly cited difficulties include the necessary mathematical background knowledge, the abstract nature of the topic, and the presentation style of the material. Analyzing the subject of algorithm analysis using multiple learning theories shows that course materials often leave out key steps in the learning process and neglect certain learning styles. Students can be more successful at learning algorithm run-time complexity analysis if these missing stages and learning styles are addressed.

Understanding User Perceptions Of Voice Personal Assistants, Ha Young Kim

All Theses

As the artificial intelligence (AI) technique improves, voice assistant (smart speaker) such as Amazon Alexa and Google Assistant are quickly, surely permeating into people's daily lives. With its powerful and convenient benefits and the circumstances that people started to stay at their home longer due to the pandemic, reliance on smart speakers has increased rapidly. But at the same time, concerns of security on smart speakers have increased.

In this thesis, we conducted an online user survey of smart speaker users with five different perspectives – 1) Users’ engagement with privacy policy; 2) Awareness of different policy requirements defined by …

Simulating Polistes Dominulus Nest-Building Heuristics With Deterministic And Markovian Properties, Benjamin Pottinger

Undergraduate Honors Theses

European Paper Wasps (Polistes dominula) are social insects that build round, symmetrical nests. Current models indicate that these wasps develop colonies by following simple heuristics based on nest stimuli. Computer simulations can model wasp behavior to imitate natural nest building. This research investigated various building heuristics through a novel Markov-based simulation. The simulation used a hexagonal grid to build cells based on the building rule supplied to the agent. Nest data was compared with natural data and through visual inspection. Larger nests were found to be less compact for the rules simulated.

Cook-It!: A Web Application For Easy Meal Planning, Carol Juneau

Senior Theses

Cook-it! is a web application for meal planning based on the Django framework and deployed on the Heroku platform. This application has an intuitive interface to make it easy to use. The project has been developed over two semesters, roughly separated into a planning phase and an implementation phase. Cook-it! incorporates a robust feature set and an attractive design. Its core purpose is to make it easy for users to plan meals, interact with other users, and keep track of user information such as a grocery list.

Optimal Eavesdropping In Quantum Cryptography, Atanu Acharyya Dr.

Doctoral Theses

Quantum key distribution (QKD) has raised some promise for more secured communication than its classical counterpart. It allows the legitimate parties to detect eavesdropping which introduces error in the channel. If disturbed, there are ways to distill a secure key within some threshold error-rate. The amount of information gained by an attacker is generally quantified by (Shannon) mutual information. Knowing the maximum amount of information that an intruder can gain is important for post-processing purposes, and we mainly focus on that side in the thesis. Renyi information is also useful especially when post-processing is considered. The scope of this thesis …

Utilization Of Virtual Reality For General Education Purposes, Amit Lal

University of the Pacific Theses and Dissertations

The use of Virtual Reality (VR) in a variety of professional, military, governmental, and educational fields has continued to expand over the past several decades, and the recent Covid-19 pandemic has brought attention to this field. This study surveys 154 college students over 23 questions that include various demographics that can be used to look for discriminators, multiple-choice VR-related questions, as well as a few free-form questions about use of VR in learning environments. The students’ experience with, interest in, and thoughts on how to best use VR vary considerably. The Covid-19 pandemic is found to have limited impact thus …

Space Science And Social Media: Automating Science Communication On Twitter, Maia Williams

Honors Projects

This project analyzes how social media is used to engage general audiences in astronomy and space science, as well as ways to improve engagement through automation. Tweets from five space science organizations were sampled. The engagement rate for each tweet was calculated from the number of interactions it received. Accounts that tweet more per day had more followers, and accounts with more followers received more interactions. This project also investigated how to build a Twitter bot to automate science communication. Using NASA Application Programming Interfaces, a Twitter bot was written in Python to tweet images taken by the NASA Mars …

Actors For The Internet Of Things, Arjun Shukla

Boise State University Theses and Dissertations

The actor model is a model for concurrent computation, centered around message passing between entities in a system. It is well suited for distributed programming, due to its semantics including very little guarantees or assumptions of reliability. Actor model implementations have grown more widespread in many languages.

The library Akka (written in Scala) is one of the most popular actor libraries. However, Akka is missing some key features. Our goal is to create our own actor library called Aurum, which not only has these features but exhibits higher performance. The new features include easy ways to forge references, configure and …

Investigating Pre-Service Teachers’ Perceptions Of The Virginia Computer Science Standards Of Learning: A Qualitative Multiple Case Study, Valerie Sledd Taylor

Educational Foundations & Leadership Theses & Dissertations

Computer science education is being recognized globally as necessary to better prepare students in all grade levels, K-12, for future success. As a result of this focus on computer science education in the United States and around the world, there is an increased demand for highly qualified teachers with content and pedagogical knowledge to successfully support student learning. As a result, there is a call to include and improve the computer science training offered to pre-service teachers in their educator preparation programs from methods courses to practicum and student teaching experiences. Thus, it is important to understand how pre-service teachers …

Automated Test Generation For Validating Systemc Designs, Bin Lin

Dissertations and Theses

Modern system design involves integration of all components of a system on a single chip, namely System-on-a-Chip (SoC). The ever-increasing complexity of SoCs and rapidly decreasing time-to-market have pushed the design abstraction to the electronic system level (ESL), in order to increase design productivity. SystemC is a widely used ESL modeling language that plays a central role in modern SoCs design process. ESL SystemC designs usually serve as executable specifications for the subsequent SoCs design flow. Therefore, undetected bugs in ESL SystemC designs may propagate to low-level implementations or even final silicon products. In addition, modern SoCs design often involves …

Inference Of Surface Velocities From Oblique Time Lapse Photos And Terrestrial Based Lidar At The Helheim Glacier, Franklyn T. Dunbar Ii

Graduate Student Theses, Dissertations, & Professional Papers

Using time dependent observations derived from terrestrial LiDAR and oblique
time-lapse imagery, we demonstrate that a Bayesian approach to glacial motion es-
timation provides a concise way to incorporate multiple data products into a single
motion estimation procedure effectively producing surface velocity estimates with
an associated uncertainty. This approach brings both improved computational effi-
ciency, and greater scalability across observational time-frames when compared to
existing methods. To gauge efficacy, we apply these methods to a set of observa-
tions from the Helheim Glacier, a critical actor in contemporary mass loss trends
observed in the Greenland Ice Sheet. We find that …

Computational Simulation And Analysis Of Neuroplasticity, Madison E. Yancey

Browse all Theses and Dissertations

Homeostatic synaptic plasticity is the process by which neurons alter their activity in response to changes in network activity. Neuroscientists attempting to understand homeostatic synaptic plasticity have developed three different mathematical methods to analyze collections of event recordings from neurons acting as a proxy for neuronal activity. These collections of events are from control data and treatment data, referring to the treatment of neuron cultures with pharmacological agents that augment or inhibit network activity. If the distribution of control events can be functionally mapped to the distribution of treatment events, a better understanding of the biological processes underlying homeostatic synaptic …

New Methods For Deep Learning Based Real-Valued Inter-Residue Distance Prediction, Jacob Barger

Theses

Background: Much of the recent success in protein structure prediction has been a result of accurate protein contact prediction--a binary classification problem. Dozens of methods, built from various types of machine learning and deep learning algorithms, have been published over the last two decades for predicting contacts. Recently, many groups, including Google DeepMind, have demonstrated that reformulating the problem as a multi-class classification problem is a more promising direction to pursue. As an alternative approach, we recently proposed real-valued distance predictions, formulating the problem as a regression problem. The nuances of protein 3D structures make this formulation appropriate, allowing predictions …

An Analysis Of Syntax Exercises On The Performance Of Cs1 Students, Shelsey B. Sullivan

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Students in introductory programming classes (CS1) generally have a difficult time learning the rules of programming. Although the general concepts of programming are relatively easy to learn, it can be difficult to learn what exactly can be typed in what order, which is known as syntax. To attempt to help students overcome this barrier, a study was conducted that introduced exercises into a CS1 class which taught the programming syntax in simple steps. The results of this study were obtained by analyzing the keys the students pressed, the errors of their code, their midterm exam scores, and their responses to …

Improving Convolutional Neural Network Robustness To Adversarial Images Through Image Filtering, Natalie E. Bogda

Masters Theses

The field of computer vision and deep learning is known for its ability to recognize images with extremely high accuracy. Convolutional neural networks exist that can correctly classify 96\% of 1.2 million images of complex scenes. However, with just a few carefully positioned imperceptible changes to the pixels of an input image, an otherwise accurate network will misclassify this almost identical image with high confidence. These perturbed images are known as \textit{adversarial examples} and expose that convolutional neural networks do not necessarily "see" the world in the way that humans do. This work focuses on increasing the robustness of classifiers …

A Computer Science Academic Vocabulary List, David Roesler

Dissertations and Theses

This thesis documents the development of the Computer Science Academic Vocabulary List (CSAVL), a pedagogical tool intended for use by English-for-specific-purpose educators and material developers. A 3.5-million-word corpus of academic computer science textbooks and journal articles was developed in order to produce the CSAVL. This study draws on the improved methodologies used in the creation of recent lemma-based word lists such as the Academic Vocabulary List (AVL) and the Medical Academic Vocabulary List (MAVL), which take into account the discipline-specific meanings of academic vocabulary. The CSAVL provides specific information for each entry, including part of speech and CS-specific meanings in …

Identifying Knowledge Gaps Using A Graph-Based Knowledge Representation, Daniel P. Schmidt

Browse all Theses and Dissertations

Knowledge integration and knowledge bases are becoming more and more prevalent in the systems we use every day. When developing these knowledge bases, it is important to ensure the correctness of the information upon entry, as well as allow queries of all sorts; for this, understanding where the gaps in knowledge can arise is critical. This thesis proposes a descriptive taxonomy of knowledge gaps, along with a framework for automated detection and resolution of some of those gaps. Additionally, the effectiveness of this framework is evaluated in terms of successful responses to queries on a knowledge base constructed from a …

Using Natural Language Processing To Categorize Fictional Literature In An Unsupervised Manner, Dalton J. Crutchfield

Electronic Theses and Dissertations

When following a plot in a story, categorization is something that humans do without even thinking; whether this is simple classification like “This is science fiction” or more complex trope recognition like recognizing a Chekhov's gun or a rags to riches storyline, humans group stories with other similar stories. Research has been done to categorize basic plots and acknowledge common story tropes on the literary side, however, there is not a formula or set way to determine these plots in a story line automatically. This paper explores multiple natural language processing techniques in an attempt to automatically compare and cluster …

The Perceptions And Lived Experiences Of Female Students In A Computer Science Program At A Community College, Terry Voldase

Walden Dissertations and Doctoral Studies

America's higher education institutions have aligned computer science curricula with today's modern technology. Despite these efforts, data have shown that there is slow growth among young women majoring in computer science and even slower growth in this area at community colleges. Higher education institutions have also acknowledged a gap between men and women entering the computer science field and a need to explore options for computer science programs to engage women in the industry. The purpose of this phenomenological study was to gain an understanding of the perceptions and lived experiences of female students enrolled in computer classes at New …

Examination Of Practices Used By Ap Computer Science Teachers With Higher Than Average Female Enrollment, Derek J. Miller

Graduate Research Theses & Dissertations

This dissertation examines the practices employed by AP Computer Science A teachers that can help recruit and retain female students in computer science. A survey was sent to teachers to see what practices they used in their classrooms and what practices they thought had the biggest influence on female student recruitment and retention. Of the five practice categories (recruitment, pedagogical, curricular, extracurricular, and mentoring), the survey respondents thought recruitment was the most influential and curricular was the least influential. After the survey, 12 teachers were chosen for interviews because they had a higher enrollment of female students than the rest …

Social Media Based Algorithmic Clinical Decision Support Learning From Behavioral Predispositions, Radhika V. Medury

Doctoral Dissertations

Behavioral disorders are disabilities characterized by an individual’s mood, thinking, and social interactions. The commonality of behavioral disorders amongst the United States population has increased in the last few years, with an estimated 50% of all Americans diagnosed with a behavioral disorder at some point in their lifetime. AttentionDeficit/Hyperactivity Disorder is one such behavioral disorder that is a severe public health concern because of its high prevalence, incurable nature, significant impact on domestic life, and peer relationships. Symptomatically, in theory, ADHD is characterized by inattention, hyperactivity, and impulsivity. Access to providers who can offer diagnosis and treat the disorder varies …

Prediction Of Sudden Cardiac Death Using Ensemble Classifiers, Ayman Momtaz El-Geneidy

CCE Theses and Dissertations

Sudden Cardiac Death (SCD) is a medical problem that is responsible for over 300,000 deaths per year in the United States and millions worldwide. SCD is defined as death occurring from within one hour of the onset of acute symptoms, an unwitnessed death in the absence of pre-existing progressive circulatory failures or other causes of deaths, or death during attempted resuscitation. Sudden death due to cardiac reasons is a leading cause of death among Congestive Heart Failure (CHF) patients. The use of Electronic Medical Records (EMR) systems has made a wealth of medical data available for research and analysis. Supervised …

A Pcnn Framework For Blood Cell Image Segmentation, Carol D. Lenihan

CCE Theses and Dissertations

This research presents novel methods for segmenting digital blood cell images under a Pulse Coupled Neural Network (PCNN) framework. A blood cell image contains different types of blood cells found in the peripheral blood stream such as red blood cells (RBCs), white blood cells (WBCs), and platelets. WBCs can be classified into five normal types – neutrophil, monocyte, lymphocyte, eosinophil, and basophil – as well as abnormal types such as lymphoblasts and others. The focus of this research is on identifying and counting RBCs, normal types of WBCs, and lymphoblasts. The total number of RBCs and WBCs, along with classification …

An Adversarial Framework For Deep 3d Target Template Generation, Walter E. Waldow

Browse all Theses and Dissertations

This paper presents a framework for the generation of 3D models. This is an important problem for many reasons. For example, 3D models are important for systems that are involved in target recognition. These systems use 3D models to train up accuracy on identifying real world object. Traditional means of gathering 3D models have limitations that the generation of 3D models can help overcome. The framework uses a novel generative adversarial network (GAN) that learns latent representations of two dimensional views of a model to bootstrap the network’s ability to learn to generate three dimensional objects. The novel architecture is …