Physical Sciences and Mathematics Commons^™

Investigations Of Physical Properties Of Novel Magnetic And Non- Magnetic Two-Dimensional (2d) Alloys., Mohammed Ameen Irziqat

Electronic Theses and Dissertations

This research work reports investigations of structural and physical properties of novel magnetic and non-magnetic 2D alloys. Three techniques were utilized in this investigation: Angle-resolved polarized Raman spectroscopy (ARPRS), Electrical &Thermoelectric power measurements, Magneto-optic Kerr effect (MOKE) spectroscopy. ARPRS and MOKE experiments were constructed during the course of this work. ARPRS was used to study the anisotropy of 2-dimensional black-arsenic phosphors (b-AsxP1-x) as a function of arsenic concentration (x). It was observed experimentally that all Raman modes of the studied samples with x=0, 0.4, 0.8 exhibit polarization dependence. More interestingly, the polarization dependence of Raman modes due to the vibrations …

Strategy-Proof Social Choice Functions On Condorcet Domains., Flannery Marie Musk Wells

Electronic Theses and Dissertations

A social choice function is said to be strategy-proof if no voter has any motivation to lie about their true preference. Strategy-proofness is a desirable property of social choice functions so we consider here functions that always satisfy this property. We add to this property the additional desirable conditions of anonymity and neutrality and present domains on which we can get a characterization of majority rule as the only social choice function that satisfies these three properties. Furthermore, we consider what functions look like when we drop the condition of anonymity.

Using Dynamic Schemas For Query Optimization Over Json Data., Tomas Felipe Llano-Rios

Electronic Theses and Dissertations

Query optimization in document stores has traditionally relied on rule-based approaches, but recent research advocates for a shift towards cost-based optimization. However, this transition is hindered by the fragmented nature of existing approaches, stemming from the early development stage of cost-based query optimization for document databases. A key challenge lies in the absence of a standardized query language and semantics, exacerbated by the diverse and schema-less nature of JSON document collections. To tackle these challenges, the literature has proposed dynamic schemas, primarily utilized at parsing time. However, these schemas lack a formal foundation that describes meaningful semantics for query optimization. …

3d-Printed Microfluidic Devices For Electrochemiluminescence Detection Of Mirna, Oscar Clement

Honors Scholar Theses

This thesis outlines the research conducted over the past two years on the production and application of microfluidic devices (MFDs) in electrochemiluminescent-based bioanalytical assays. The work is categorized into two main projects: designing and manufacturing MFDs and developing electrochemiluminescent (ECL) assays for detecting Alzheimer's disease (AD) associated microRNAs (miRNAs) using CRISPR technology. The process of learning to design MFDs involved acquiring proficiency in computer-aided design (CAD) software, stereolithography (SLA) 3D printing, and iterative design techniques. The development of the ECL-based assay for AD miRNA was a multidisciplinary endeavor, combining elements of inorganic and biological chemistry. Although the research on the …

Optimization Of Xrf Experimental Protocol For Bruker Picofox, Tyler Ashcraft

Undergraduate Honors Theses

The research performed was to improve the precision and accuracy of sample measurements made with the Bruker Picofox X-ray fluorescence spectrometer. The initial method of sample preparation using a 10 μL drop spotted onto an acrylic plate and then drying in an oven at 80˚C produced inconsistent results even when processing replicates or the same sample multiples times. Multiple experiments were conducted to determine the effects of different sample preparation conditions on the resulting accuracy. The conditions tested were drop size, plate composition, and drying temperature. For each experiment an internal standard (gallium) was used at concentrations similar to that …

Comparing And Assessing Four Ai Chatbots' Competence In Economics, Patrik T. Hultberg, David Santandreu Calonge, Firuz Kamalov, Linda Smail

All Works

Artificial Intelligence (AI) chatbots have emerged as powerful tools in modern academic endeavors, presenting both opportunities and challenges in the learning landscape. They can provide content information and analysis across most academic disciplines, but significant differences exist in terms of response accuracy for conclusions and explanations, as well as word counts. This study explores four distinct AI chatbots, GPT-3.5, GPT-4, Bard, and LLaMA 2, for accuracy of conclusions and quality of explanations in the context of university-level economics. Leveraging Bloom’s taxonomy of cognitive learning complexity as a guiding framework, the study confronts the four AI chatbots with a standard test …

Bernstein Polynomials Method For Solving Multi-Order Fractional Neutral Pantograph Equations With Error And Stability Analysis, M. H. T. Alshbool

All Works

In this investigation, we present a new method for addressing fractional neutral pantograph problems, utilizing the Bernstein polynomials method. We obtain solutions for the fractional pantograph equations by employing operational matrices of differentiation, derived from fractional derivatives in the Caputo sense applied to Bernstein polynomials. Error analysis, along with Chebyshev algorithms and interpolation nodes, is employed for solution characterization. Both theoretical and practical stability analyses of the method are provided. Demonstrative examples indicate that our proposed techniques occasionally yield exact solutions. We compare the algorithms using several established analytical methods. Our results reveal that our algorithm, based on Bernstein series …

Factors Predictive Of The Development Of Surgical Site Infection In Thyroidectomy, A Replication Study Of Myssiorek (2018), Kaitlyn M. Kenig

Capstone Experience

The original study aimed to show that thyroidectomy does not result in surgical site infection (SSI) in most cases, and thus routine prescription of antibiotics is not necessary. The study looked to see what risk factors could predict the incidence of SSI. This would highlight those individuals who were at most risk of developing SSI, and then antibiotics would only be prescribed to these individuals instead of all or most individuals who undergo thyroidectomy.

This study used NSQIP data to look at incidence of SSI and look for risk factors that may be predictive of SSI. Only surgeries that were …

The Use Of Laja In Construction In Ancient Mesoamerica: A View From The Southern Gulf Lowlands Of Veracruz, Mexico, Lauren Smith

Honors College Theses

The archaeology of the southern Gulf lowlands of Veracruz, Mexico is notable for its research pertaining to the Olmec culture (Jaime-Riveron 2016; Loughlin 2012; Pool 2006). The region was home to the Colossal Olmec Heads: large, easily identifiable sculptures crafted from the volcanic rock of the Tuxtlas Volcanic Field. The use of volcanic resources in such grand presentations may instill a bias in the research of some archaeologists, but it is important to consider how these and other volcanic resources might have been used in everyday life (e.g., Jaime-Riveron 2016: 86). The consolidated volcanic ash in this region is referred …

Predictability Of The Overland Reintensification Of North Atlantic Tropical Cyclone Erin (2007), Ariel Tickner-Ernst

Theses and Dissertations

Tropical cyclones (TC) typically decrease in intensity upon interacting with land because of increased surface roughness and decreased surface evaporation. However, several studies have documented cases in which TCs maintain their intensity or even intensify over land within non- or weakly baroclinic environments. Yet, our understanding of the precise physical processes that support maintenance or intensification over land in non- or weakly baroclinic environments remains limited, and the predictive skill for these outcomes has yet to be quantified.

We begin this process by quantifying the predictive skill and forecast uncertainty of the overland intensification of North Atlantic Tropical Storm Erin …

Which Vole Is Which: Dna-Based Species Identification For Wisconsin’S Three Microtus Species, Madeline Noel Opie

Theses and Dissertations

Accurate species identification is necessary to implement conservation strategies in the wild. When traditional morphology-based species identification is challenging due to phenotypic plasticity, overlapping characteristics, or the species are otherwise cryptic, DNA-based species identification may be more suitable. Of the three species of Microtus in Wisconsin, two are listed as threatened at the state level. Both M. ochrogaster and M. pinetorum have stable population levels at the national level but are along the northern edge of their ranges in Wisconsin. Small and vulnerable populations of M. ochrogaster and M. pinetorum are limited to isolated patches in the southwestern portion of …

Classification And Explanation Of Iron Deficiency Anemia From Complete Blood Count Data Using Machine Learning, Siddartha Pullakhandam

Theses and Dissertations

Anemia is a global health problem, and over 2 billion people are affected. Although, the major cause of anemia is iron deficiency (IDA), global estimates suggest that only about half of anemia could be attributed to ID. The typical test of anemia involves measurement of hemoglobin using Complete Blood Count (CBC) test, which also gives additional information on blood cell numbers and morphology. The diagnosis of iron deficiency anemia (IDA, both anemic and ID co-exist in a subject) requires additional expensive serum ferritin test. However, blood cell count, and morphology can also be utilized for diagnosis of IDA. The goal …

Synthesis Of Thermoresponsive Poly(N-Isopropyl Acrylamide) Based Core-Shell And Hollow Shell Nanogel With Tunable Core And Shell Thickness, Mohamad Hijazi, Molla R. Islam

Student Scholar Symposium Abstracts and Posters

Nanogels have emerged as a notably safer and more effective means for drug delivery, primarily due to their adjustable drug-loading capabilities. Hollow-core nanoparticles offer some unique properties that are desirable for drug delivery applications. Initially, silica core nanoparticles were synthesized using the Stöber process at different temperatures where Tetraethoxysilane (TEOS) undergoes hydrolysis in the presence of ethanol and then a condensation reaction to form silica nanoparticles. Scanning Electron Microscopy (SEM) and Optical Microscopy (OM) analysis revealed that the size of silica core particles varied with the synthesis temperature (300 nm at 30°C to 150 at 60°C). The core silica particles …

Computational Linguistics And Multilingualism: A Comparative Analysis With Spanish And English Data, Evelyn Lawrie

Student Scholar Symposium Abstracts and Posters

Computational linguistics is an increasingly ubiquitous field, serving as the basis for artificial intelligence and machine translation. It aims to analyze the syntax and semantics of individual words and phrases. While there have been in-depth advancements in computational linguistics strategies for the English language, others have not been developed as thoroughly. This lack of emphasis on multilingualism has contributed to the disappearance of Hispanic perspectives in the digital world. Especially those of indigenous heritage, as the decline of many indigenous languages has been exacerbated by the lack of digital translation services. Sentiment analysis is a branch of computational linguistics that …

Dancetag: Using Sensors To Improve Feedback Given To Dance Students, Yanelly Mego

Student Scholar Symposium Abstracts and Posters

The structure of dance classrooms has remained unchanged for several years. Very little, if any, technology has been incorporated to improve the quality of teaching. This has motivated our research project, whose goal is to capture dance movements with wearable sensors, to develop DANCETAG (Data Analytics and Notation with Captured Event Tagging). This is a platform that allows the gathering of data captured by Sony’s Mocopi sensors and annotating them with the dancer's movements. The Mocopi sensors make up a motion capture system. It is comprised of six small, round sensors that can be attached to velcro straps and clips. …

The Non-Vanishing Of The Trace Of T ₃, Liubomir Chiriac, Daphne Kurzenhauser, Erin Williams

Mathematics and Statistics Faculty Publications and Presentations

A generalized Lehmer conjecture predicts that, for every positive integer n, the trace of the Hecke operator T_n in level one does not vanish, unless the space of cusp forms acted upon is trivial. So far, this has only been established for n = 2. In this paper, we use p-adic methods to prove the statement for n = 3.

Skimming Genomes For Systematics And Dna Barcodes Of Corals, Andrea M. Quattrini, Luke J. Mccartin, Erin E. Easton, Jeremy Horowitz, Herman H. Wirshing, Hailey Bowers, Kenneth Mitchell, María Del P. González-García, Makiri Sei, Catherine S. Mcfadden

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

Numerous genomic methods developed over the past two decades have enabled the discovery and extraction of orthologous loci to help resolve phylogenetic relationships across various taxa and scales. Genome skimming (or low-coverage genome sequencing) is a promising method to not only extract high-copy loci but also 100s to 1000s of phylogenetically informative nuclear loci (e.g., ultraconserved elements [UCEs] and exons) from contemporary and museum samples. The subphylum Anthozoa, including important ecosystem engineers (e.g., stony corals, black corals, anemones, and octocorals) in the marine environment, is in critical need of phylogenetic resolution and thus might benefit from a genome-skimming approach. We …

Year-Round Co2 Emissions From The Drawdown Area Of A Tropical Reservoir: Strong Seasonal And Spatial Variation, Ícaro Barbosa, José R. Paranaíba, Sebastian Sobek, Sarian Kosten, Rafael M. Almeida, Vitor Duque, Natália Mendonça, Nathan Barros, Raquel Mendonça

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

Highlights

• Drawdown areas emitted 80% of reservoir CO2 with just 1/5 area.

• Emissions from reservoir shorelines near forests were greater than from areas near grassland.

• CO2 emissions increase with the distance from the water.

• Estimates of reservoir drawdown CO2 flux vary by ∼ 300 % across the seasons examined here.

• There was no discernible difference in CO2 emissions between day and night-time.

• A significant increase in CO2 fluxes was observed 30 min after a rewetting event.

Abstract

A growing body of literature points to drawdown areas as important sources of atmospheric CO2 within reservoirs. Yet seasonal and temporal patterns of …

Automated Cinematographer For Vr Viewing Experiences, Zihan Wu

Dartmouth College Master’s Theses

As the virtual reality (VR) industry continues to evolve, the question of how to effectively capture VR experiences for an audience remains a challenge. The predominant method of showcasing VR applications through first-person recordings lacks cinematic interest, failing to capture other viewpoints and the essence of the moment. Meanwhile, manually setting up cameras and editing videos requires technical expertise on behalf of the user. In this paper, we propose the use of machine learning (ML) to automatically select the most compelling predefined viewpoint in a VR environment, at any given moment. Our models, trained on actor motion and voice volume, …

Humanity Amid Innovation: Exploring Our Relationship To Technology, Sarah Durkee

Senior Theses and Projects

This thesis examines the impacts of technology on fundamental aspects of human nature and experience. Drawing on the works from Kant, Turing, Arendt, Benjamin, and Freud, it explores how rapid technological change is redefining human reason, intelligence, and creativity in the digital age. The first chapter analyzes whether modern online communication platforms realize or undermine Kant's vision of an enlightened public sphere fostering free discourse and critique. It argues that prioritizing engagement over substantive debate, these digital realms corrode the depth of interaction essential for cultivating human reason. The second chapter explores the pursuit of artificial intelligence as a reproduction …

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

Honors Theses

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

Agricultural Groundcover Update March 2024, Justin Laycock

Natural resources published reports

• In March, over 10% (1,577,000 ha) of the arable farmland in the south-west of Western Australia had less than 50% vegetative groundcover, which is inadequate to prevent wind erosion.

• The northern grainbelt had the highest risk of wind erosion and over 20% of this farmland had inadequate groundcover.

• About 1.3% (191,000 ha) of arable land had a high to very high risk of wind erosion because groundcover was less than 30%.

Comparative Predictive Analysis Of Stock Performance In The Tech Sector, Asaad Sendi

University of New Orleans Theses and Dissertations

This study compares the performance of deep learning models, including Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Transformer, in predicting stock prices across five companies (AAPL, CSCO, META, MSFT, and TSLA) from July 2019 to July 2023. Key findings reveal that GRU models generally exhibit the lowest Mean Absolute Error (MAE), indicating higher precision, particularly notable for CSCO with a remarkably low MAE. While LSTM models often show slightly higher MAE values, they outperform Transformer models in capturing broader trends and variance in stock prices, as evidenced by higher R-squared (R2) values. Transformer models generally exhibit higher MAE …

Choreographing The Rhythms Of Observation: Dynamics For Ranged Observer Bipartite-Unipartite Spatiotemporal (Robust) Networks, Edward A. Holmberg Iv

University of New Orleans Theses and Dissertations

Existing network analysis methods struggle to optimize observer placements in dynamic environments with limited visibility. This dissertation introduces the novel ROBUST (Ranged Observer Bipartite-Unipartite SpatioTemporal) framework, offering a significant advancement in modeling, analyzing, and optimizing observer networks within complex spatiotemporal domains. ROBUST leverages a unique bipartite-unipartite approach, distinguishing between observer and observable entities while incorporating spatial constraints and temporal dynamics.

This research extends spatiotemporal network theory by introducing novel graph-based measures, including myopic degree, spatial closeness centrality, and edge length proportion. These measures, coupled with advanced clustering techniques like Proximal Recurrence, provide insights into network structure, resilience, and the effectiveness …

Modeling Prices In Limit Order Book Using Univariate Hawkes Point Process, Wenqing Jiang

University of New Orleans Theses and Dissertations

This thesis presents a time-changed geometric Brownian price model with the univariate Hawkes processes to trace the price changes in a limit order book. Limit order books are the core mechanism for trading in modern financial markets, continuously collecting outstanding buy and sell orders from market participants. The arrival of orders causes fluctuations in prices over time. A Hawkes process is a type of point process that exhibits self-exciting behavior, where the occurrence of one event increases the probability of other events happening in the near future. This makes Hawkes processes well-suited for capturing the clustered arrival patterns of orders …

The Pawn System: How Procedurally Adaptive Webbed Narratives Create Stories, Steven T. Bordelon

University of New Orleans Theses and Dissertations

This thesis describes the design, implementation, and testing of a novel procedural narrative system called the Procedurally Adaptive Webbed Narrative (PAWN) system. PAWN procedurally generates characters and, responding to choices made by the player, produces more responsive characters and relationships involving the player and these narrative agents. Initially, this thesis discusses other interactive narrative types that exist, such as emergent or event-driven narratives, along with their strengths and weaknesses. It then examines each aspect of PAWN, starting with initial actor generation, then moving to the capturing of game events and translating them into logical objects called Occurrences. These Occurrences are …

Rapid Parameter Estimation Of Compact Binary Coalescences With Gravitational Waves, Caitlin Rose

Theses and Dissertations

In the age of multi-messenger astrophysics, fast, reliable information about gravitational-wave candidates is crucial for electromagnetic follow-up observations. While sky localization tells astronomers where to observe an event, source classification estimates the probability that the event might have an electromagnetic counterpart. Furthermore, astronomers need to have enough time to point their telescopes towards the fading light. Rapid PE is a low-latency parameter estimation scheme which parallelizes Bayesian inference by fixing the intrinsic parameters to a grid, and marginalizing over the extrinsic parameters at each grid point via Monte Carlo sampling. The gravitational-wave search pipelines identify the highest signal-to-noise ratio (SNR) …

Brain-Inspired Continual Learning: Rethinking The Role Of Features In The Stability-Plasticity Dilemma, Hikmat Khan

Theses and Dissertations

Continual learning (CL) enables deep learning models to learn new tasks sequentially while preserving performance on previously learned tasks, akin to the human's ability to accumulate knowledge over time. However, existing approaches to CL face the challenge of catastrophic forgetting, which occurs when a model's performance on previously learned tasks declines after learning the new task. In this dissertation, we focus on the crucial role of input data features in determining the robustness of CL models to mitigate catastrophic forgetting. We propose a framework to create CL-robustified versions of standard datasets using a pre-trained Oracle CL model. Our experiments show …

A Survey Of Current Perceptions And Actual Use By Students And Faculty Of Generative Artificial Intelligence In Higher Education, Cameron Hasselbaum

Honors College

Generative AI as an emerging new technology may have large-scale impacts on how business is conducted and how schools teach students. OpenAI released ChatGPT to the public in November of 2022. Two similar surveys were conducted one year after ChatGPT was released in December 2023 to measure the perceptions of generative AI and changes in behavior in the academic space among students and faculty at the University of Maine. The survey findings were that student respondents have been quicker to adopt and find utility in the new technology. Still, it has yet to be readily adopted for use as widely …

Knowledge Enhanced Multi-Intent Transformer Network For Recommendation, Ding Zou, Wei Wei, Feida Zhu, Chuanyu Xu, Tao Zhang, Chengfu Huo

Research Collection School Of Computing and Information Systems

Incorporating Knowledge Graphs (KGs) into Recommendation has attracted growing attention in industry, due to the great potential of KG in providing abundant supplementary information and interpretability for the underlying models. However, simply integrating KG into recommendation usually brings in negative feedback in industry, mainly due to the ignorance of the following two factors: i) users' multiple intents, which involve diverse nodes in KG. For example, in e-commerce scenarios, users may exhibit preferences for specific styles, brands, or colors. ii) knowledge noise, which is a prevalent issue in Knowledge Enhanced Recommendation (KGR) and even more severe in industry scenarios. The irrelevant …