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Electronic Theses and Dissertations

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Articles 211 - 240 of 4194

Full-Text Articles in Physical Sciences and Mathematics

Insights Into The Structural And Electronic Properties Of 2d Polar Sic/Gec Heterostructures And Asxp1−X Alloys., Kazi Jannatul Tasnim Aug 2023

Insights Into The Structural And Electronic Properties Of 2d Polar Sic/Gec Heterostructures And Asxp1−X Alloys., Kazi Jannatul Tasnim

Electronic Theses and Dissertations

Due to the unique structural and electronic properties along with the practical applications in current and near future, investigations about the group-IV graphene-like two-dimensional (2D) sheets have been accelerated. Among them, 2D SiC and GeC sheets are polar materials with in-plane charge transfer from Si (Ge) to C atoms. An interesting question is how the electrostatic force, triggered by such in-plane charge transfer, plays a role in stabilizing the vertical heterostructures formed by 2D SiC and GeC sheets beyond vdW interaction. To answer this question, we have systematically investigated, in my PhD research projects, the effects of the electrostatic interaction …

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Dinitroxides In Rapid Scan Electron Paramagnetic Resonance Imaging, Lukas B. Woodcock Aug 2023

Dinitroxides In Rapid Scan Electron Paramagnetic Resonance Imaging, Lukas B. Woodcock

Electronic Theses and Dissertations

Local tissue physiology is an important parameter in understanding disease behavior. Rapid Scan (RS) electron paramagnetic resonance (EPR) offers a unique, non-invasive tool for investigation of these so-called microenvironments through EPR Imaging (EPRI). Research into advancement of EPRI falls into many categories. Not least among those are advances in instrumentation and methodology. Presented here are updates to a benchtop EPRI instrument operating at 1 GHz targeted at pre-clinical EPRI applications. Newly developed methods for reducing RS-EPR background through inversion of the magnetic field are also demonstrated. EPR applications are limited in native biological systems due to the miniscule concentration of …

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Do-It-Together: Informal Transformative Sustainability Education, Derek Brannon Aug 2023

Do-It-Together: Informal Transformative Sustainability Education, Derek Brannon

Electronic Theses and Dissertations

The Climate Crisis is an urgent and inescapable reality students are thrust into. Learners must be prepared adequately for their futures, not only for their sakes but also because collective and transformative change is required. Transformative sustainability education provides one pathway to this transformation and focuses on radically altering students’ perceptions about the world and their agency in effecting change on ecological issues. The field of transformative sustainability education is emergent and thus is still fragmented, leaving gaps in the literature. Little research has been conducted on how informal and nonformal university spaces can be used to create transformative experiences …

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Statistical Methods For Assessing Treatment Effects On Ordinal Outcomes And Selecting Optimal Treatment On Survival Outcomes Using Observational Data., Huirong Hu Aug 2023

Statistical Methods For Assessing Treatment Effects On Ordinal Outcomes And Selecting Optimal Treatment On Survival Outcomes Using Observational Data., Huirong Hu

Electronic Theses and Dissertations

This dissertation consists of two projects investigating statistical methods in causal inference and personalized medication using observational data. In the first project, we propose a parametric marginal structural ordinal logistic regression model (MS-OLRM) to assess treatment effects on ordinal outcomes. Average treatment effect (ATE) is used to measure the difference of the mean outcomes if all patients would have been treated compared with the outcomes if they would not have been treated. Many statistical methods have been developed to estimate ATE when the outcome is continuous or binary. The methodology on assessing treatment effect for an ordinal outcome is less …

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A Data-Driven Multi-Regime Approach For Predicting Real-Time Energy Consumption Of Industrial Machines., Abdulgani Kahraman Aug 2023

A Data-Driven Multi-Regime Approach For Predicting Real-Time Energy Consumption Of Industrial Machines., Abdulgani Kahraman

Electronic Theses and Dissertations

This thesis focuses on methods for improving energy consumption prediction performance in complex industrial machines. Working with real-world industrial machines brings several challenges, including data access, algorithmic bias, data privacy, and the interpretation of machine learning algorithms. To effectively manage energy consumption in the industrial sector, it is essential to develop a framework that enhances prediction performance, reduces energy costs, and mitigates air pollution in heavy industrial machine operations. This study aims to assist managers in making informed decisions and driving the transition towards green manufacturing. The energy consumption of industrial machinery is substantial, and the recent increase in CO2 …

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New Species Of Dryolestoid From The Late Cretaceous Allen Formation And Implications For South American Faunal Diversity., Brigid Erin Connelly Aug 2023

New Species Of Dryolestoid From The Late Cretaceous Allen Formation And Implications For South American Faunal Diversity., Brigid Erin Connelly

Electronic Theses and Dissertations

Dryolestoids are extinct cladotherians mammals from the Jurassic and Cretaceous periods. I describe a collection of dryolestoid specimens from the Late Cretaceous localities of Cerro Tortuga (Allen Formation), Anfiteatro 1, and Shining (both La Colonia Formation) from Patagonia, Argentina. Using comparative morphology, I identify a new species of meridiolestidan dryolestoid based on eleven specimens across both formations. The new species’ recovery from La Colonia Formation represents the first dryolestoid connection between the two approximately contemporaneous formations. The species’ morphology may represent an ecological shift within Meridiolestida from insectivory to herbivory, showing a transition in characters between the plesiomorphic sharp-toothed meridiolestidans …

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Terrain And Adversary-Aware Autonomous Robot Navigation, Aniekan Ufot Inyang Aug 2023

Terrain And Adversary-Aware Autonomous Robot Navigation, Aniekan Ufot Inyang

Electronic Theses and Dissertations

In autonomous robot navigation, the robot is able to understand the environment around it for intelligent navigation. From its world model of this environment, it generates a global plan for navigation from a position to a goal based on different factors. This research aims to implement autonomous robot navigation by learning terrain affordances: traversability (moving quickly) and concealment (staying hidden from an adversary) using the Preference-based Inverse Reward Learning (PbIRL) methodology. The PbIRL methodology reduces the barrier of generating initial demonstration data to learn the terrain affordances by using a human expert’s preferences to learn individual weights over the terrain …

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Unilinear Residuated Lattices, Xiao Zhuang Aug 2023

Unilinear Residuated Lattices, Xiao Zhuang

Electronic Theses and Dissertations

We characterize all residuated lattices that have height equal to 3 and show that the variety they generate has continuum-many subvarieties. More generally, we study unilinear residuated lattices: their lattice is a union of disjoint incomparable chains, with bounds added. We give the characterization of all unilinear residuated lattices. By presenting the constructions and axiomatizations for different classes of unilinear residuated lattices, we conclude that the study of unilinear residuated lattices can be reduced to the study of the ⊤-unital ones. Using the classification of unilinear residuated lattices, the idempotent unilinear residuated lattices are studied and amalgamation property and strong …

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Extending The Work Of Dt-Fixup: Examining The Effects Of Powernorm And Madgrad Optimization On Dt-Fixup Performance, Prem Shanker Mohan Jul 2023

Extending The Work Of Dt-Fixup: Examining The Effects Of Powernorm And Madgrad Optimization On Dt-Fixup Performance, Prem Shanker Mohan

Electronic Theses and Dissertations

With the introduction of the attention technique, the Bidirectional Encoder Representations from Transformers (BERT) have greatly advanced the study of solving sequence-to-sequence tasks in Natural Language Processing (NLP). When the task-specific annotations are limited, the NLP tasks are commonly performed by pre-training a model using the transformer technique on large-scale general corpora, followed by fine-tuning the model on domain-specific data. Instead of using shallow neural components for fine-tuning, additional transformer layers could be introduced into the architecture. Recent research shows that, by resolving some initialization and optimization issues, these augmented transformer layers could lead to performance gains despite of the …

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The Characterization Of Riparian Vegetation In Agriculture Drains Impacted By Phragmites Australis And Drain Management: A Southwestern Ontario, Canada Case Study, Ryan Mackenzie Graham Jul 2023

The Characterization Of Riparian Vegetation In Agriculture Drains Impacted By Phragmites Australis And Drain Management: A Southwestern Ontario, Canada Case Study, Ryan Mackenzie Graham

Electronic Theses and Dissertations

Agricultural drainage systems are important components of regional ecosystems and play key roles in ecosystem functioning. Biodiversity is a service provided by drains which is not fully understood in agriculturally dominated areas and is disrupted consistently by drain management, specifically in drains invaded by Phragmites australis. The objective of this thesis was to characterize the contribution of regional vegetational biodiversity provided by drainage systems, across sites representing a gradient of management frequencies. Drains were separated into management categories: Low (managed +5 years ago), Medium (managed every 3-5 years), or High (managed yearly). Plant abundance was measured and biodiversity indices (Species …

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Reinforcement Learning-Based Data Rate Congestion Control For Vehicular Ad-Hoc Networks, Gnana Shilpa Nuthalapati Jul 2023

Reinforcement Learning-Based Data Rate Congestion Control For Vehicular Ad-Hoc Networks, Gnana Shilpa Nuthalapati

Electronic Theses and Dissertations

Vehicular Ad-Hoc Network(VANET) is an emerging wireless technology vital to the Intelligent Transportation System(ITS) for vehicle-to-vehicle and vehicle-to-infrastructure communication. An ITS is an advanced solution that aims to deliver innovative services pertaining to various transportation modes and traffic management. Its objective is to enhance user awareness, promote safety, and enable more efficient and coordinated utilization of transport networks. ITS aims to mitigate traffic problems and improve the safety of transport by preventing unexpected events. When the vehicle density, i.e., the number of vehicles communicating in a wireless channel, increases, the channel faces congestion resulting in unreliable safety applications. Various decentralized …

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Classifying Galaxy Images Using Improved Residual Networks, Jaykumar Patel Jun 2023

Classifying Galaxy Images Using Improved Residual Networks, Jaykumar Patel

Electronic Theses and Dissertations

The field of astronomy has made tremendous progress in recent years thanks to advancements in technology and the development of sophisticated algorithms. One area of interest for astronomers is the classification of galaxy morphology, which involves categorizing galaxies based on their visual appearance. However, with the sheer number of galaxy images available, it would be a daunting task to manually classify them all. To address this challenge, a novel Residual Neural Network (ResNet) model, called ResNet Var, that can automatically classify galaxy images is proposed in this study. Galaxy Zoo 2 dataset is used in this research, which contains over …

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Personalized Eca Tutoring With Self-Adjusted Pomdp Policies And User Clustering, Ashwitha Vichuly Jawahar Jun 2023

Personalized Eca Tutoring With Self-Adjusted Pomdp Policies And User Clustering, Ashwitha Vichuly Jawahar

Electronic Theses and Dissertations

An Embodied Conversational Agent (ECA) is an intelligent agent that enables realtime human/computer interaction in natural language. For its rich style of communication, ECA is particularly popular and useful in applications such as education, e-commerce, healthcare, finance, marketing, and business, where a human-like conversation is more attractive to users than traditional keyboard-based interaction. The interest in using ECA in e-learning has become even stronger since the COVID-19 outbreak, and a preliminary investigation has been started by our research group to extend collaborative learning in a virtual environment with personalized ECA tutoring. This thesis document first highlights the prior work of …

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Cross-Blockchain Technology For An Interoperable And Scalable Digital Contact Tracing, Farbod Behnaminia Jun 2023

Cross-Blockchain Technology For An Interoperable And Scalable Digital Contact Tracing, Farbod Behnaminia

Electronic Theses and Dissertations

COVID-19 pandemic has highlighted the importance of contact tracing as a tool for controlling the spread of the virus, but it has also raised concerns about the privacy and security of personal information. Blockchain technology, with its immutability and security features, has the potential to address these concerns. However, traditional blockchain solutions may not be sufficient to protect sensitive personal information, especially when it comes to interoperability with other chains that may have different privacy standards. Cross-blockchain technology, such as the interoperability feature of the Polkadot network, allows for the creation of a decentralized and distributed contact tracing system that …

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A Decentralized Data Evaluation Technique In Federated Learning, Laveen Bhatia Jun 2023

A Decentralized Data Evaluation Technique In Federated Learning, Laveen Bhatia

Electronic Theses and Dissertations

Deep Learning is one of the most revolutionary concepts in the field of Artificial Intelligence, allowing us to train a Machine Learning model for almost any type of problem using any type of data. Federated Learning (FL) is a type of distributed Deep Learning framework in which the model is trained locally on each device, and only the trained gradients, also known as “local updates”, are sent to a central server that aggregates them and creates a global model. This helps in preserving the data privacy of the user as the local data never leaves the local device. It has …

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Macroinvertebrate And Bacteria Community Responses To Tributary Inputs At Coastal Wetlands Of The Detroit River, Ontario, Canada, Jessica Robson Jun 2023

Macroinvertebrate And Bacteria Community Responses To Tributary Inputs At Coastal Wetlands Of The Detroit River, Ontario, Canada, Jessica Robson

Electronic Theses and Dissertations

The Detroit River is a Great Lakes Area of Concern with five monitored wetlands in the Canadian jurisdiction. Habitat assessments have indicated possible stress at wetlands receiving inflow from Turkey Creek and River Canard tributaries. These assessments are made within the tributaries. Yet, macrophyte beds extend into the river upstream and downstream and are important biodiversity habitats. This thesis examines benthic macroinvertebrate and sediment bacteria community compositions for differences with respect to tributaries by two means. First, we examine inter-wetland differences for resemblance to water quality. We had found by NMDS and PERMANOVA that neither taxonomic group resembled water quality …

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Graphwords: Enhancing Word Vectors Using Graphs, Mrulay Sureshbhai Mistry Jun 2023

Graphwords: Enhancing Word Vectors Using Graphs, Mrulay Sureshbhai Mistry

Electronic Theses and Dissertations

In the domain of Natural Language Processing (NLP), the representation of words according to their distribution in the vector, form is a crucial task. In the representation space, when words that are similar to each other according to human interpretation are placed closer to each other, a notable increase can be observed in the performance and accuracy of NLP tasks. Previous word embedding methods put emphasis on passing the word tokens in an iterative manner through a Neural Language model to capture the context of the words. These methods can capture word relatedness, but only within the given context length. …

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Optimization Of Equilibrated Headspace Technique For Compositional And Isotopic Analysis Of Dissolved Gases, Michelle Tsuey-Yee Quan Jun 2023

Optimization Of Equilibrated Headspace Technique For Compositional And Isotopic Analysis Of Dissolved Gases, Michelle Tsuey-Yee Quan

Electronic Theses and Dissertations

Dissolved gas analysis has been used to quantify concentrations of natural gas and carbon dioxide in solutions for many years, giving insight into bioremediation processes and potential natural gas releases. However, due to the lack of universal dissolved gas methods, there is room for interpretation during sampling, storage, and analysis, causing variation in the data obtained between laboratories, especially as these techniques are often not applicable to stable isotope analysis, which can be used to determine the source of the elevated concentration obtained. Thus, one portion of this thesis aims to gain a greater understanding of the effect of headspace …

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Approximating Average Bounded-Angle Minimum Spanning Trees, Patrick Stephen Devaney Jun 2023

Approximating Average Bounded-Angle Minimum Spanning Trees, Patrick Stephen Devaney

Electronic Theses and Dissertations

Motivated by the problem of orienting directional antennas in wireless communication networks, we study average bounded-angle minimum spanning trees. Let P be a set of points in the plane and let α be an angle. An α-spanning tree (α-ST) of P is a spanning tree of the complete Euclidean graph induced by P with the restriction that all edges incident to each point p in P lie in a wedge of angle α with apex p. An α-minimum spanning tree (α-MST) of P is an α-ST with minimum total edge length. An average-α-spanning tree (denoted by avg-α-ST) is a spanning …

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Patient Movement Monitoring Based On Imu And Deep Learning, Mohsen Sharifi Renani Jun 2023

Patient Movement Monitoring Based On Imu And Deep Learning, Mohsen Sharifi Renani

Electronic Theses and Dissertations

Osteoarthritis (OA) is the leading cause of disability among the aging population in the United States and is frequently treated by replacing deteriorated joints with metal and plastic components. Developing better quantitative measures of movement quality to track patients longitudinally in their own homes would enable personalized treatment plans and hasten the advancement of promising new interventions. Wearable sensors and machine learning used to quantify patient movement could revolutionize the diagnosis and treatment of movement disorders. The purpose of this dissertation was to overcome technical challenges associated with the use of wearable sensors, specifically Inertial Measurement Units (IMUs), as a …

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Novel Approach For Non-Invasive Prediction Of Body Shape And Habitus, Emma Young Jun 2023

Novel Approach For Non-Invasive Prediction Of Body Shape And Habitus, Emma Young

Electronic Theses and Dissertations

While marker-based motion capture remains the gold standard in measuring human movement, accuracy is influenced by soft-tissue artifacts, particularly for subjects with high body mass index (BMI) where markers are not placed close to the underlying bone. Obesity influences joint loads and motion patterns, and BMI may not be sufficient to capture the distribution of a subject’s weight or to differentiate differences between subjects. Subjects in need of a joint replacement are more likely to have mobility issues or pain, which prevents exercise. Obesity also increases the likelihood of needing a total joint replacement. Accurate movement data for subjects with …

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An Investigation Into Machine Learning Techniques For Designing Dynamic Difficulty Agents In Real-Time Games, Ryan Adare Dunagan Jun 2023

An Investigation Into Machine Learning Techniques For Designing Dynamic Difficulty Agents In Real-Time Games, Ryan Adare Dunagan

Electronic Theses and Dissertations

Video games are an incredibly popular pastime enjoyed by people of all ages world wide. Many different kinds of games exist, but most games feature some elements of the player overcoming some challenge, usually through gameplay. These challenges are insurmountable for some people and may turn them off to video games as a pastime. Games can be made more accessible to players of little skill and/or experience through the use of Dynamic Difficulty Adjustment (DDA) systems that adjust the difficulty of the game in response to the player’s performance. This research seeks to establish the effectiveness of machine learning techniques …

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Thermal, Magnetic, And Electrical Properties Of Thin Films And Nanostructures: From Magnetic Insulators To Organic Thermoelectrics, Michael J. M. Roos Jun 2023

Thermal, Magnetic, And Electrical Properties Of Thin Films And Nanostructures: From Magnetic Insulators To Organic Thermoelectrics, Michael J. M. Roos

Electronic Theses and Dissertations

Modern fabrication and growth techniques allow for the development of increasingly smaller and more complex solid state structures, the characterization of which require highly specialized measurement platforms. In this dissertation I present the development of techniques and instrumentation used in magnetic, thermal, and electrical property measurements of thin films and nanostructures. The understanding of trapped-flux induced artifacts in SQUID magnetometry of large paramagnetic substrates allows for the resolution of increasingly small moments. Using these methods, the antiferromagnetic coupling of the interface between a Y3Fe5O12 film and Gd3Ga5O12substrate is quantitatively …

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Dta+Vae: Drug Target Affinity Prediction With Selfies String Via Variational Autoencoder And Transformer6 Protein Model, Yakin Patel Jun 2023

Dta+Vae: Drug Target Affinity Prediction With Selfies String Via Variational Autoencoder And Transformer6 Protein Model, Yakin Patel

Electronic Theses and Dissertations

A crucial step in drug discovery is identifying drug-target interactions. Over the years, there have been many computational methods to determine whether a drug and a target will interact or not. Drug-target binding affinity can also be determined by predicting the strength of the binding interaction between the drug and the target. Drug target binding affinity consider a lot of information that is left out by drug target interaction. There have been many methods to predict the binding affinity, all the methods use SMILES representation, learning accurate drug representations is essential for tasks such as computational drug repositioning, drug target …

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Guided Rotational-Based Graph Embeddings For Error Detection In Noisy Knowledge Graphs, Regina Khalil Jun 2023

Guided Rotational-Based Graph Embeddings For Error Detection In Noisy Knowledge Graphs, Regina Khalil

Electronic Theses and Dissertations

Knowledge graphs (KGs) use triples to describe real-world facts. They have seen widespread use in intelligent analysis and applications. However, the automatic construction process of KGs unavoidably introduces possible noises and errors. Furthermore, KG-based tasks and applications assume that the knowledge in the KG is entirely correct, which leads to potential deviations. Error detection is critical in KGs, where errors are rare but significant. Various error detection methodologies, primarily path ranking (PR) and representation learning, have been proposed to ad- dress this issue. In this thesis, we introduced the Enhanced Path Ranking Guided Embedding (EPRGE), which is an improved version …

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The Minimum Consistent Spanning Subset Problem On Trees, Parham Khamsepour Jun 2023

The Minimum Consistent Spanning Subset Problem On Trees, Parham Khamsepour

Electronic Theses and Dissertations

Given a vertex-colored edge-weighted graph, the minimum consistent subset (MCS) problem asks for a minimum subset S of vertices such that every vertex v not in S has the same color as its nearest neighbor in S. This problem has applications in clustering and classification algorithms, specially in finding the optimal number of clusters in k-clustering algorithms. This problem is NP-complete. A recent result of Dey, Maheshwari, and Nandy (2021) gives a polynomial-time algorithm for the MCS problem on trees. In thesis we study the MCS problem on different settings, and discuss some of the shortcomings of the MCS problem …

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An Analysis Of All-Cause Mortality On Patients With Sickle Cell Disease And Kidney Disease Using Propensity Score Matching, Adam Garrison May 2023

An Analysis Of All-Cause Mortality On Patients With Sickle Cell Disease And Kidney Disease Using Propensity Score Matching, Adam Garrison

Electronic Theses and Dissertations

In this work, we provide an overview of the Cox proportional hazards model for time to event or survival analysis and the notion of propensity score matching to deal with confounding factors. A full analysis is reported in Chapter 2 concerning mortality for in-center dialysis patients with sickle cell disease to demonstrate the application of a general analysis strategy that has some logistical benefits over more traditional approaches to accounting for confounding variables. We also provide some insight and discussions on the challenges and future research questions that will emerge when trying to implement this strategy as a monitoring tool …

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Blockchain Security: Double-Spending Attack And Prevention, William Henry Scott Iii May 2023

Blockchain Security: Double-Spending Attack And Prevention, William Henry Scott Iii

Electronic Theses and Dissertations

This thesis shows that distributed consensus systems based on proof of work are vulnerable to hashrate-based double-spending attacks due to abuse of majority rule. Through building a private fork of Litecoin and executing a double-spending attack this thesis examines the mechanics and principles behind the attack. This thesis also conducts a survey of preventative measures used to deter double-spending attacks, concluding that a decentralized peer-to-peer network using proof of work is best protected by the addition of an observer system whether internal or external.

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Restrictions On Topological Symmetry Groups Of The 3-Rung Möbius Ladder On The Torus, Logan Willhoite May 2023

Restrictions On Topological Symmetry Groups Of The 3-Rung Möbius Ladder On The Torus, Logan Willhoite

Electronic Theses and Dissertations

In this work, we discuss properties of the 3-rung Möbius ladder embedded on the surface of a torus. We present proofs on restrictions of topological symmetry groups of the Möbius ladder with and without the assumption of preserving orientation. Specifically, we show that Z2 is the only possible non-trivial orientation-preserving topological symmetry groups, and also that Z2 and D2 are the only possible nontrivial topological symmetry groups.

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Do Integrated Circuits Make For An Integrated Supply Chain? A Network Analysis Of Trade Flows, Noah Martens May 2023

Do Integrated Circuits Make For An Integrated Supply Chain? A Network Analysis Of Trade Flows, Noah Martens

Electronic Theses and Dissertations

Integrated circuits (colloquially referred to as chips) are an increasingly critical commodity experiencing continuous and substantial rises in demand. These increases in demand recently resulted in shortages. This paper seeks to understand the market for chips and construct a framework by which a network analysis of trade flows can evaluate concentration in the international market for a particular product category. Leveraging this framework and proposing a new model, I evaluate the level and nature of concentration in the chips sector, as well as two key inputs to the manufacturing process, silicon and chip fabricators. I find moderate-to-high levels of concentration …

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