Computer Sciences Commons^™

Soft Law 2.0: An Agile And Effective Governance Approach For Artificial Intelligence, Gary E. Marchant, Carlos Ignacio Gutierrez

Minnesota Journal of Law, Science & Technology

No abstract provided.

Do Plants Have The Cognitive Complexity For Sentience?, Ricard V. Solé

Animal Sentience

Are plants sentient? Like other aspects of the cognitive potential of plants, this is a controversial issue, often driven by analogies and seldom supported on solid theoretical grounds. Sentience is understood in cognitive sciences as the capacity to feel. I suggest that because of plants’ evolved adaptations to morphological plasticity, sessile nature and ecological constraints, they are unlikely to have the requisite cognitive complexity for sentience.

Self-Supervised Hierarchical Metrical Structure Modeling, Junyan Jiang, Gus Xia

Machine Learning Faculty Publications

We propose a novel method to model hierarchical metrical structures for both symbolic music and audio signals in a self-supervised manner with minimal domain knowledge. The model trains and inferences on beat-aligned music signals and predicts an 8-layer hierarchical metrical tree from beat, measure to the section level. The training procedure does not require any hierarchical metrical labeling except for beats, purely relying on the nature of metrical regularity and inter-voice consistency as inductive biases. We show in experiments that the method achieves comparable performance with supervised baselines on multiple metrical structure analysis tasks on both symbolic music and audio …

Procedural Level Generation For A Top-Down Roguelike Game, Kieran Ahn, Tyler Edmiston

Honors Thesis

In this file, I present a sequence of algorithms that handle procedural level generation for the game Fragment, a game designed for CMSI 4071 and CMSI 4071 in collaboration with students from the LMU Animation department. I use algorithms inspired by graph theory and implementing best practices to the best of my ability. The full level generation sequence is comprised of four algorithms: the terrain generation, boss room placement, player spawn point selection, and enemy population. The terrain generation algorithm takes advantage of tree traversal methods to create a connected graph of walkable tiles. The boss room placement algorithm randomly …

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. …

Partitions Of R^N With Maximal Seclusion And Their Applications To Reproducible Computation, Jason Vander Woude

Department of Mathematics: Dissertations, Theses, and Student Research

We introduce and investigate a natural problem regarding unit cube tilings/partitions of Euclidean space and also consider broad generalizations of this problem. The problem fits well within a historical context of similar problems and also has applications to the study of reproducibility in randomized computation.

Given $k\in\mathbb{N}$ and $\epsilon\in(0,\infty)$, we define a $(k,\epsilon)$-secluded unit cube partition of $\mathbb{R}^{d}$ to be a unit cube partition of $\mathbb{R}^{d}$ such that for every point $\vec{p}\in\R^d$, the closed $\ell_{\infty}$ $\epsilon$-ball around $\vec{p}$ intersects at most $k$ cubes. The problem is to construct such partitions for each dimension $d$ with the primary goal of minimizing …

Utilizing Machine Learning Techniques To Predict Credit Card Payment Defaults, Madison Guerra

Theses and Dissertations

The question of accurately predicting credit card defaulters has been explored in numerous studies in the past. In these studies, the researchers utilized various machine learning theories and techniques to make the determination the extent of defaults. Unfortunately, some constraints were encountered, and the limitations that existed from the previous works have been discussed. This project attempted to address these issues with special attention given to more recently available data. Specifically, in this project, we looked at data provided by one Kaggle user, which utilized the data from the American Express credit card competition, which ranges from late March 2018 …

Augmented & Virtual Reality: Advancement Of Technology And Its Impacts On Medicine, Education, And Other Industries, Yassine Chahid

Publications and Research

Throughout the early 2000s, the ways in which the World Wide Web was used would undergo major changes. The introduction of these changes around this time period would be collectively known as Web 2.0. With Web 2.0, accessibility and distribution of applications became more simplified. During the 2000s, much has evolved from hard capabilities to the internet and its widespread usage amongst companies and general consumers. In contemporary times, multiple technologies, both hardware and digital are becoming more advanced, with general consumers either rejecting or accepting these gradual shifts in what may become everyday technology. Web 3.0, the theoretical advancement …

Music On Canvas: A Quest To Generate Art That Evokes The Feeling Of Music, My Linh (Lucy) Tran

Mathematics, Statistics, and Computer Science Honors Projects

Although the idea of connecting music and art dates back to ancient Greece, recent advancements in computing have made automating this feasible. This project represents a quest to transform music into art, using three methodologies where each is an improvement towards generating images that convey our feelings and imaginations during music listening. The three methods respectively involve:

1. An element-wise mapping of sound and colors
2. Using song tags
3. Tuning an Artificial Intelligence (AI) model to generate pictorial text captions.

To create artistic images, methods two and three utilize an existing text-to-image generative AI.

Designing Programming Languages For Writing Maintainable Software, Aaron Friesen

Honors Program: Senior Projects (Public)

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. …

Improving Multi-Modal Food Detection System With Transfer Learning, Shivani Gowda

LMU Theses and Dissertations

Self-assessment of food intake is important for preventing and treating obesity. The current self-assessment methods of food intake are inaccurate and hard to use. In this thesis, we explore ways to improve machine learning (ML) food classification methods which are the core technical problem of food intake self-assessment. We present a food detection system that utilizes a state-of-the art multi-modal architecture called Vision and Language Transformer (ViLT). This architecture combines both food appearance via the image modality, and description via the textual modality to improve the accuracy of food classification. To further enhance the performance, we incorporate other improvements such …

Programming An Autonomous Robot, Maxwell Brueggeman

Honors College Theses

Ravaged by hurricanes, Florida needed help restoring its natural beauty and returning its wildlife to their homes. This was the task for the IEEE SoutheastCon 2023 Hardware Competition. Florida’s restoration was simulated by returning various ducks and pillars that lay strewn across a game board to their proper places. Ducks needed to return to their pond, pillars needed to be stacked to create statues, and food needed to be placed in the manatee and alligator aquariums. Competing teams were challenged to create an autonomous robot capable of performing these tasks. During the first semester, sensor selection was tackled. Research was …

Topic Modeling And Future Prediction Of Aid Data In Development Studies Using Lda And Bert, Uttamasha Anjally Oyshi

Theses and Dissertations

This thesis presents a study on topic modeling and future prediction of aid data in development studies using LDA and BERT. The goal of this study is to explore the aid data from four sectors: Government and civil society, Government and civil society general, Conflict prevention and resolution, peace and security, and Women, and to identify the latent topics that are present in the data. The LDA and BERT algorithms were used for the topic modeling, and coherence scores were computed to evaluate the quality of the models. The results of the study show that the LDA and BERT models …

What Senior U.S. Leaders Say We Should Know About Cyber, Dr. Joseph H. Schafer

Military Cyber Affairs

On April 6, 2023, the Atlantic Council’s Cyber Statecraft Initiative hosted a panel discussion on the new National Cybersecurity Strategy. The panel featured four senior officials from the Office of the National Cyber Director (ONCD), the Department of State (DoS), the Department of Justice (DoJ), and the Department of Homeland Security (DHS). The author attended and asked each official to identify the most important elements that policymakers and strategists must understand about cyber. This article highlights historical and recent struggles to express cyber policy, the responses from these officials, and the author’s ongoing research to improve national security cyber policy.

Combining Frameworks To Improve Military Health System Quality And Cybersecurity, Dr. Maureen L. Schafer, Dr. Joseph H. Schafer

Military Cyber Affairs

Existing conceptual frameworks and commercially available technology could be considered to rapidly operationalize the use of Quality Measures (QM) within military health systems (Costantino et al. 2020). Purchased healthcare as well as digital healthcare services have paved the way for data collection from multiple information systems thus offering stakeholders actionable intelligence to both guide and measure healthcare outcomes. However, the collection of data secondary to Smart Devices, disparate information systems, cloud services, and the Internet of Medical Things (IOMT) is a complication for security experts that also affect clients, stakeholders, organizations, and businesses delivering patient care. We have combined three …

Analyzing And Computing Complete Solution For Dots And Boxes Game, Carl Mcaninch

Graduate Dissertations and Theses

This thesis improves a process that analyzes all the states of a game of Dots and Boxes. We use retrograde analysis and simulations to create a solution that provides significant performance improvements over our previous best solution. Expanding upon a previous 4x4 solution using rotations, reflections, better optimization, and cloud computing to limit the processing time and gather more data efficiently. We compute a file and the number of states associated with each file and process every state starting with a completely filled board. We optimized the data for cloud computing by running simulations to find the most efficient number …

Fair Enough: Standardizing Evaluation And Model Selection For Fairness Research In Nlp, Xudong Han, Timothy Baldwin, Trevor Cohn

Natural Language Processing Faculty Publications

Modern NLP systems exhibit a range of biases, which a growing literature on model debiasing attempts to correct. However, current progress is hampered by a plurality of definitions of bias, means of quantification, and oftentimes vague relation between debiasing algorithms and theoretical measures of bias. This paper seeks to clarify the current situation and plot a course for meaningful progress in fair learning, with two key contributions: (1) making clear inter-relations among the current gamut of methods, and their relation to fairness theory; and (2) addressing the practical problem of model selection, which involves a trade-off between fairness and accuracy …

Analysis Of A Federated Learning Framework For Heterogeneous Medical Image Data: Privacy And Performance Perspective, Julia Brixey

Computer Science and Computer Engineering Undergraduate Honors Theses

The massive amount of data available in our modern world and the increase of computational efficiency and power have allowed for great advancements in several fields such as computer vision, image processing, and natural languages. At the center of these advancements lies a data-centric learning approach termed deep learning. However, in the medical field, the application of deep learning comes with many challenges. Some of the fundamental challenges are the lack of massive training datasets, unbalanced and heterogenous data between health applications and health centers, security and privacy concerns, and the high cost of wrong inference and prediction. One of …

A Survey And Comparative Study On Vulnerability Scanning Tools, Cassidy Khounborine

Computer Science and Computer Engineering Undergraduate Honors Theses

Vulnerability scanners are a tool used by many organizations and developers as part of their vulnerability management. These scanners aid in the security of applications, databases, networks, etc. There are many different options available for vulnerability scanners that vary in the analysis method they encompass or target for which they scan, among many other features. This thesis explores the different types of scanners available and aims to ease the burden of selecting the ideal vulnerability scanner for one’s needs by conducting a survey and comparative analysis of vulnerability scanners. Before diving into the vulnerability scanners available, background information is provided …

Characterization Of 2d Quantum Materials Using Ai And Large-Scale Quantum Data Collection, Apoorva Bisht

Computer Science and Computer Engineering Undergraduate Honors Theses

2D materials like hexagonal boron nitride, graphene, and tungsten diselenide are widely utilized for studying their unique mechanical and opto-electronic properties to exploit them to make transistors and fabricating a variety of other devices. All these applications require that the 2D materials used be of specific uniform thickness. Until very recently, this process has been largely manual and tedious. However, few applications exploit the characteristic color-to-thickness correspondence of these near-transparent materials. To continue this effort, in this work we create a large-scale dataset for three different materials (hBN, graphene, and WSe$_2$) to train and test an image segmentation model along …

Developing A Multi-Platform Application To Facilitate Internal Campus Hiring, Carissa Patton

Computer Science and Computer Engineering Undergraduate Honors Theses

Undergraduate research has proven to be highly beneficial to students, yet there are many students who do not know how to get involved or who are too timid to approach professors to inquire about potential research opportunities. Our hypothesis is that a cross-platform application has the potential to bridge the gap and help more students get involved in undergraduate research by providing them information about open positions and the faculty or staff members who are mentoring the projects. The key focus of this thesis is to develop an application that provides details about participating faculty or staff including their research …

Effects Of Factors On The Market Price Of The Shares Using Design Of Experiment, Amir Ahmad Dar, Mohammad Shahfaraz Khan, Imran Azad, Tanveer Ahmad Tarray, N. Anuradha, Qaiser Farroq Dar

Applied Mathematics & Information Sciences

When the cost of capital, dividends and the price of the share at the beginning is known, Modigliani and Miller’s model can be used to estimate the price of the share at the end of the period. A design of experiment (Taguchi’s orthogonal array) is used in order to investigate the impact of three parameters on the price of the share at the end of the period. The main aim of this research article is to find which parameter is more significant on the price of the share at the end of the period. Taguchi’s methodology of design of the …

Universal Computation Using Self-Assembling, Crisscross Dna Slats, Jackson S. Bullard

Computer Science and Computer Engineering Undergraduate Honors Theses

I first give a brief introduction to formal models of computation. I then present three different approaches for computation in the aTAM. I later detail generating systems of crisscross slats given an arbitrary algorithm encoded in the form of a Turing machine. Crisscross slats show potential due to their high levels of cooperativity, so it is hoped that implementations utilizing slats are more robust to various growth errors compared to the aTAM. Finally, my software converts arbitrary crisscross slat systems into various physical representations that assist in analyzing their potential to be realized in experiments.

Linux Malware Obfuscation, Brian Roden

Computer Science and Computer Engineering Undergraduate Honors Theses

Many forms of malicious software use techniques and tools that make it harder for their functionality to be parsed, both by antivirus software and reverse-engineering methods. Historically, the vast majority of malware has been written for the Windows operating system due to its large user base. As such, most efforts made for malware detection and analysis have been performed on that platform. However, in recent years, we have seen an increase in malware targeting servers running Linux and other Unix-like operating systems resulting in more emphasis of malware research on these platforms. In this work, several obfuscation techniques for Linux …

Why Inverse Layers In Pavement? Why Zipper Fracking? Why Interleaving In Education? A General Explanation, Edgar Daniel Rodriguez Velasquez, Aaron Velasco, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In many practical situations, if we split our efforts into two disconnected chunks, we get better results: a pavement is stronger if instead of a single strengthening layer, we place two parts of this layer separated by no-so-strong layers; teaching is more effective if instead of concentrating a topic in a single time interval, we split it into two parts separated in time, etc. In this paper, we provide a general explanation for all these phenomena.

Geochemical Analysis And Numerical Modeling Of Central And East Tennessee Mississippi Valley-Type Ore Districts: Constraints On Ore Genesis, Jackson Price Copeland

Geosciences Undergraduate Honors Theses

A simple two-way stochastic mixing model is presented for analysis of the lead (Pb) isotope compositions of the North American Mississippi Valley-Type (MVT) districts of East Tennessee, Central Tennessee, and Central Kentucky. Four distinct mixing scenarios were run to critically evaluate the stochastic model and examine different hypotheses regarding the genesis of Central Tennessee and Central Kentucky MVT deposits. Additionally, Pb isotope analysis was conducted on sphalerite samples from the Central and East Tennessee MVT districts. Model and sampling results suggest that Central Tennessee and Central Kentucky ores likely formed by mixing of three fluids. In contrast to conclusions from …

Reverse Engineering Post-Quantum Cryptography Schemes To Find Rowhammer Exploits, Sam Lefforge

Computer Science and Computer Engineering Undergraduate Honors Theses

Post-quantum cryptography is a necessary countermeasure to protect against attacks from quantum computer. However, the post-quantum cryptography schemes are potentially vulnerable to side channel attacks. One such method of attacking involves creating bit-flips in victim memory through a process called Rowhammer. These attacks can vary in nature, but can involve rowhammering bits to raise the encryption scheme's decryption failure rate, or modifying the scheme's random seed. With a high enough decryption failure rate, it becomes feasible to generate sufficient information about the secret key to perform a key recovery attack. This thesis proposed two attacks on proposed post-quantum cryptography algorithms, …

Realtime In-Network Cyberattack Detection In Power Grid Systems Using A Programmable Network, Luke Waind

Computer Science and Computer Engineering Undergraduate Honors Theses

Power grid communication networks are important systems to detect intrusions from an attacker due to them being necessary to maintain critical infrastructure. This thesis applies recent advancements in P4 technology to detect cyberattacks in SCADA systems. In previous work, a list has been compiled of potential attacks that exploit one of the most common protocols in SCADA systems, DNP3. Solutions for detecting these attacks can be categorized by the broad methods that they use. The two methods that are focused on are single-packet inspection and multiple-packet inspection. For each of these, a specific attack is chosen and a detection algorithm …

Critical Infrastructure Workforce Development Pods For Teaching Cybersecurity Using Netlab+, Gideon Sutterfield

Computer Science and Computer Engineering Undergraduate Honors Theses

As digital automation for Industrial Control Systems has grown, so has its vulnerability to cyberattacks. The world of industry has responded effectively to this, but the world of academia is still lagging as its emphasis is still almost entirely on information technology. Considering this, we created a workforce development pod that serves as a hands-on learning module for teaching students key cybersecurity ideas surrounding operational technology using the NETLAB+ platform. A pod serves as the virtual environment where the learning exercise takes place. This project’s implementation involved the creation of a segmented network within the pod where a student starts …

Physics-Based Human-In-The-Loop Machine Learning Combined With Genetic Algorithm Search For Multi-Criteria Optimization: Electrochemical Co2 Reduction Reaction, Naohiro Fujinuma, Samuel Lofland

College of Science & Mathematics Departmental Research

Machine learning (ML) can be a powerful tool to expedite materials research, but the deployment for experimental research is often hindered by data scarcity and model uncertainty. An human-in-the-loop procedure to tailor the implementation of ML for multicriteria optimization is described. The effectiveness of this procedure in the development of a nafion-based membrane electrode assembly for electrochemical CO2 reduction reaction (CO2RR) into CO for two targets is demonstrated: energy efficiency (EE) and partial current density for CO2RR (). Model-agnostic nonlinear correlation analyses identify the 11 features relevant to those targets. The three studied decision tree-based ML models yield similar cross-validation …