Physical Sciences and Mathematics Commons^™

Private Ethereum Blockchain Implementation And Its Security Features For Smart Home Iot, Hasibul Grande Alam

Theses and Dissertations

The security and privacy of IoT devices have become primary concerns as smart home networks are connected to the internet. Ethereum blockchain can be a solution to mitigate or prevent attacks – sniffing attacks, malware attacks, Eavesdropping, and Distributed Denial of Services (DDoS) attacks. Deploying Ethereum in resource constraint IoT devices is challenging due to resultant energy consumption, computational overhead, and delay. We adopted smart home as a case study to examine our methodology as a model for general IoT applications. This thesis work presents the implementation of private Ethereum blockchain that is optimized and installable on smart home IoT. …

Intellibeehive, Christian Ivan Narcia-Macias

Theses and Dissertations

Utilizing computer vision and the latest technological advancements, in this study, we developed a honey bee monitoring system that aims to enhance our understanding of Colony Collapse Disorder, honey bee behavior, population decline, and overall hive health. The system is positioned at the hive entrance providing real-time data, enabling beekeepers to closely monitor the hive's activity and health through an account-based website. Using machine learning, our monitoring system can accurately track honey bees, monitor pollen-gathering activity, and detect Varroa mites, all without causing any disruption to the honey bees. Moreover, we have ensured that the development of this monitoring system …

Robust And Uncertainty-Aware Image Classification Using Bayesian Vision Transformer Model, Fazlur Rahman Bin Karim

Theses and Dissertations

Transformer Neural Networks have emerged as the predominant architecture for addressing a wide range of Natural Language Processing (NLP) applications such as machine translation, speech recognition, sentiment analysis, text anomaly detection, etc. This noteworthy achievement of Transformer Neural Networks in the NLP field has sparked a growing interest in integrating and utilizing Transformer models in computer vision tasks. The Vision Transformer (ViT) model efficiently captures long-range dependencies by employing a self-attention mechanism to transform different image data into meaningful, significant representations. Recently, the Vision Transformer (ViT) has exhibited incredible performance in solving image classification problems by utilizing ViT models, thereby …

Strategies Community College Mexican American Adult College Algebra Students Use When Graphing Function Transformations, Roxana Pamela Jimenez

Theses and Dissertations

This qualitative case study pursued to describe the different strategies Mexican American adult students in a local community college used to graph function transformations. Participants in the study were purposefully selected using a criterion sampling to ensure participants were atypical, above average students between the ages 18-22, and had a final course average of 89.5-100 in College Algebra. Three research questions were examined 1) In what ways do Mexican American adult college students graph a function transformation? 2) Which strategies do students implement when graphing a function transformation? Qualitative research methods using think aloud semi-structured interviews were used in this …

A Combinatorial Proof Of Supercranks For Partitions With A Fixed Number Of Parts, Jacob J. Gutierrez

Theses and Dissertations

In a previous paper by Eichhorn and Kronholm, a selection of supercranks for p(n,m) was established by generating functions. In this paper we will reprove this result with combinatorial witnesses for the selection of supercranks via integer lattice points.

Attitudes Towards Mathematics Of Developmental Mathematics Students In A Community College, Benjamin Ortiz

Theses and Dissertations

Reformations to developmental mathematics aim to remove barriers for students entering higher education. Challenges like costly multi-course sequences and high failure rates prohibit students’ access to college-level math courses and prevent degree or certification completion. Understanding factors that foster student success is critical to increase student success. This study focuses on students’ attitudes towards mathematics, utilizing the novice-expert continuum through Code et al.’s Mathematical Attitude and Perceptions Survey (MAPS) instrument. Student expertise scores, including all MAPS dimensions and specific dimension scores, were assigned. Kruskal-Wallis Rank-Sum tests identified differences in student populations by course and attitude dimension. …

Case Studies Of Algebra 1 Teachers Selection And Implementation Of Mathematics Tasks Toward Situated Learning, Luis Román Sauceda

Theses and Dissertations

Mathematical tasks are vital in active learning, especially in situated learning. Adequate selection and appropriate implementation of tasks are steps toward success in engaging students for active learning. This study explored how a professional development (PD) workshop influences teacher participants’ capabilities in selecting, redesigning, implementing, and reflecting on mathematical tasks to promote situated and active learning. The teacher participants were Algebra 1 teachers from a South Texas secondary school. During the workshop, participants developed and implemented activities after being shown situated learning strategies to promote student-centered learning. They were required to design hypothetical dialogues to simulate their class practice before …

Quasipolynomials And The Unimodality Of Gaussian Polynomials, Paul Marsh

Theses and Dissertations

We illustrate a method to prove the unimodality of Gaussian polynomials ${N+m \brack m}$ for $m = 5$ and $6$, building upon Dr. Brandt Kronholm's work, which proved unimodality for $m = 2,3,$ and $4$. Our approach involves viewing coefficients $p(n,m,N)$ of Gaussian polynomials $N+m \brack m$ based on how far away $n$ is from the central coefficient $p(\lfloor\frac{mN}{2}\rfloor,m,N)$ and then creating generating functions for those coefficients. We then take the difference of neighboring generating functions and change those generating functions into quasipolynomials to verify that their coefficients are non-negative. While the generalization of these generating functions for the coefficients …

An Automatic Solver For Optimal Control Problems, Marcel Efren Benitez

Theses and Dissertations

Optimal control theory is a study that is used to find a control for a dynamical system over a period of time such that a objection function is optimized. In this study we will be looking at optimal control problems for ordinary differential equations or ODEs and see that we can use an automatic solver using the forward-backward sweep using Matlab to solve for them from an 1 dimension to bounded cases and to nth dimension cases.

Mathematical Evaluation Of Ulnar Nerve Somatosensory Evoked Potentials (Sseps), Maribel Carmen Gomez

Theses and Dissertations

As the number of individuals suffering with low back and neck pain rises, we find people undergoing spinal procedures more often. In means, of safeguarding the patient and their neurological structures during the procedure intraoperative neuro-physiological monitoring (I.O.M) has been more widely used amongst surgeons orthopedic and neuro alike. During these procedures, a modality widely used for both low back and neck surgery is somatosensory evoked potentials (SSEPs). The aim of neuro-technicians is to obtain a baseline waveform that can be considered present and reliable. When obtaining SSEPs the technician can encounter obstacles with ’noisy’ wave-forms due to …

Publication Of Undergraduate Experiments, Development Of Additional X-Ray Crystallography Experiments, And Proof-Of-Concept Cyclopropanation Reactions, Alain Beauparlant

Electronic Theses and Dissertations

Single crystal X-ray crystallography instructional materials were developed using a variety of compounds including sugar, Epsom salt, pyrite, copper(II) acetate, and rhodium(II) acetate. Rhodium(II) acetate was reacted with a variety of functionalized benzonitriles, and when crystals were obtained, characterized using single crystal X-ray crystallography. Rhodium(II) acetate with adducts of 4-nitrobenzonitrile and 4-(dimethylamino)benzonitrile were also characterized using proton NMR spectroscopy and Fourier Transform Infrared Spectroscopy. Rhodium(II) acetate with adducts of 4-(dimethylamino)benzonitrile was used as a catalyst in a proof-ofconcept reaction to determine if it acts as a catalyst in cyclopropanation reactions. Further, the new rhodium(II) acetate dinitrile compounds were investigated to …

Synthesis Of Bacterial Glycerophospholipids For Biomembrane Model Studies: A Means To Advanced Biofuels, Felix Adulley

Electronic Theses and Dissertations

To reduce reliance on fossil fuels, sustainable biofuels are being pursued, especially advanced biofuels like 1-butanol that have higher energy content and greater compatibility with existing infrastructure than ethanol. A persistent challenge is the yield-limiting toxicity of biofuels and process solvents, such as tetrahydrofuran, to the microbes that ferment biomass into biofuel. The cell membrane is a focal point of toxicity, and understanding how it interacts with fuels and solvents is key to improving yield. Phospholipid bilayers are the core of biomembranes, and model biomembranes of defined composition provide the ideal platform for biophysical studies. To this end, glycerophospholipids characteristic …

Comparative Analysis Of Teacher Effects Parameters In Models Used For Assessing School Effectiveness: Value-Added Models & Persistence, Merlin J. Kamgue

Graduate Theses and Dissertations

Longitudinal measures for students have become increasingly popular to estimate the effects of individual teachers and schools. Value-added models are one of the approaches using longitudinal data to evaluate teachers and schools. In the value-added model (VAM) literature, many statistical approaches have been developed and used to estimate teacher or school effects on student learning. This study opted to use a Bayesian multivariate model for evaluating teacher effects. The generalized persistence models can handle longitudinal data, not vertically scaled, allowing for a below-par teacher’s effects correlation across test administrations. This study first generated longitudinal students’ test score data and used …

Butte Priority Soils Operable Unit Uncontrolled Surface Flow Areas Draft Remedial Design Work Plan (Rdwp), Woodard & Curran

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Electrodeposition Studies Of Gold Nanoparticles And Alginate Hydrogel Films., Harikrishnan Nambiathan Nambiar

Electronic Theses and Dissertations

This dissertation investigates the electrochemical deposition (ECD) and electrophoretic deposition (EPD) processes involving citrate (cit)-stabilized Au nanoparticles (NPs) and calcium alginate (Ca-Alg-Au NP) hydrogel films. The first part of the dissertation investigates the influence of NP size, surface area (SA) coverage, and ligand stabilizers on the electrochemical growth of Au on Au NPs, aiming to enhance our understanding of the growth process during the nucleation and growth of metal NPs. The growth kinetics depend on Au NP size (4 nm > 15 nm > 50 nm) for a constant SA coverage, as determined by the overpotentials for ECD. The growth rate increases …

Design And Characterization Of A Novel Eef2k Degrader With Potent Therapeutic Efficacy Against Triple-Negative Breast Cancer, Changxin Zhong, Rongfeng Zhu, Ting Jiang, Sheng Tian, Xiaobao Zhao, Xiaoya Wan, Shilong Jiang, Zonglin Chen, Rong Gong, Linhao He, Jin-Ming Yang, Na Ye, Yan Cheng

Markey Cancer Center Faculty Publications

Dysregulated eEF2K expression is implicated in the pathogenesis of many human cancers, including triple-negative breast cancer (TNBC), making it a plausible therapeutic target. However, specific eEF2K inhibitors with potent anti-cancer activity have not been available so far. Targeted protein degradation has emerged as a new strategy for drug discovery. In this study, a novel small molecule chemical is designed and synthesized, named as compound C1, which shows potent activity in degrading eEF2K. C1 selectively binds to F8, L10, R144, C146, E229, and Y236 of the eEF2K protein and promotes its proteasomal degradation by increasing the interaction between eEF2K and the …

Adversarially Reweighted Sequence Anomaly Detection With Limited Log Data, Kevin Vulcano

All Graduate Theses and Dissertations, Fall 2023 to Present

In the realm of safeguarding digital systems, the ability to detect anomalies in log sequences is paramount, with applications spanning cybersecurity, network surveillance, and financial transaction monitoring. This thesis presents AdvSVDD, a sophisticated deep learning model designed for sequence anomaly detection. Built upon the foundation of Deep Support Vector Data Description (Deep SVDD), AdvSVDD stands out by incorporating Adversarial Reweighted Learning (ARL) to enhance its performance, particularly when confronted with limited training data. By leveraging the Deep SVDD technique to map normal log sequences into a hypersphere and harnessing the amplification effects of Adversarial Reweighted Learning, AdvSVDD demonstrates remarkable efficacy …

Optimal Stopping Of Multi-Robot Exploration For Unknown, Bounded Environments, Trey D. Crowther

All Graduate Theses and Dissertations, Fall 2023 to Present

Limited resources and uncertainty pose a substantial problem for multi-robot exploration of unknown environments. This research paper looks to determine the optimal time to terminate robot exploration while maximizing information gathered. Whilst making this determination, the system's resources and capabilities must be taken into account. To see if our strategy works, we ran many simulations in varying environments. The results of this research are important for real-world uses like robot exploration, search and rescue missions, and automated surveillance. Determining when to stop exploring can help the system save resources, explore faster, and make better decisions.

Analysis Of Student Behavior And Score Prediction In Assistments Online Learning, Aswani Yaramala

All Graduate Theses and Dissertations, Fall 2023 to Present

Understanding and analyzing student behavior is paramount in enhancing online learning, and this thesis delves into the subject by presenting an in-depth analysis of student behavior and score prediction in the ASSISTments online learning platform. We used data from the EDM Cup 2023 Kaggle Competition to answer four key questions. First, we explored how students seeking hints and explanations affect their performance in assignments, shedding light on the role of guidance in learning. Second, we looked at the connection between students mastering specific skills and their performance in related assignments, giving insights into the effectiveness of curriculum alignment. Third, we …

Movement Patterns Of A Federally Endangered Minnow In A Fragmented Desert River, Martinique J. Chavez

All Graduate Theses and Dissertations, Fall 2023 to Present

Fishes are unified in their need to move within the systems they occupy, and their movement patterns can be fundamental to their ecology and survival. Many large rivers in North America are fragmented by dams that modify natural flow regimes, compromise connectivity, and imperil freshwater fishes dependent on unrestricted movement in order to complete their life history. Coincident with widespread river fragmentation, are the declines of numerous endemic desert fishes in the American southwest. The Rio Grande Silvery Minnow (Hybognathus amarus, RGSM), has experienced a 95% reduction in its historical range and is now restricted to a highly …

Solar Flare Prediction From Extremely Imbalanced Multivariate Time Series Data Using Minimally Random Convolutional Kernel Transform, Kartik Saini

All Graduate Theses and Dissertations, Fall 2023 to Present

Solar flares are characterized by sudden bursts of electromagnetic radiation from the Sun's surface, and caused by the changes in magnetic field states in solar active regions. Earth and its surrounding space environment can suffer from various negative impacts caused by solar flares ranging from electronic communication disruption to radiation exposure-based health risks to the astronauts. In this paper, we address the solar flare prediction problem from magnetic field parameter-based multivariate time series (MVTS) data using multiple state-of-the-art machine learning classifiers that include MINImally RandOm Convolutional KErnel Transform (MINIROCKET), Support Vector Machine (SVM), Canonical Interval Forest (CIF), Multiple Representations SEQuence …

Reducing Inputs And Adding Value To Turfgrass Systems Through Clover Inclusion And Plant Growth-Promoting Rhizobacteria Applications, Paige E. Boyle

All Graduate Theses and Dissertations, Fall 2023 to Present

Recently, the US has seen an expansion in the amount of turfgrass land cover (lawns, parks, roadsides, sports fields, and golf courses), as well as an interest in reducing fertilizer, water, and pesticide use in these grass systems. To help maintain quality and function while reducing resource inputs, two promising approaches have emerged: planting clover into lawns and applying plant growth-promoting rhizobacteria.

White clover and grass mixtures have been studied for their ability to cut down on fertilizer usage and provide a uniform, dark green lawn, but other clover types have not been as widely studied and may provide similar …

Using Gamification To Foster Student Resilience And Motivation To Learn, And Using Games To Teach Significance Testing Concepts In The Statistics Classroom, Todd Partridge

All Graduate Theses and Dissertations, Fall 2023 to Present

Two studies are outlined in this dissertation.

In the first study, elements of Super Mario Bros. videos games were used to change the way college students in a beginners’ statistics course were graded on their work. This was part of an effort to help students remain optimistic in the face of challenging coursework and even failure on assignments and tests. The study shows that the changes made to the grading structure did help students to keep trying and to use the materials given to them by their professor until they achieved their desired grade in the course, and suggests ways …

Designing And Studying Redox-Active Molecules For Energy Storage And Desalination, Wenda Wu

All Graduate Theses and Dissertations, Fall 2023 to Present

Since the fast growth of the global population, energy scarcity has become a new threat to modern society. Those commonly seen resources like fossil, coal, and natural gas are nonrenewable energies, which cannot be replenished by human-scale time. In contrast, wind, solar, and hydropower are the three main renewable green energies under development with great efforts around the world. However, the intermittent character of these powers raises a new question: how to store them properly on large scales? By 2021, more than 90% of the electricity storage was taken by Lithium-ion batteries (LIBs). The usage of lithium brings concerns about …

Ecology And Management Of Dyer's Woad (Isatis Tinctoria) In Northern Utah, Erin Marie Hettinger

All Graduate Theses and Dissertations, Fall 2023 to Present

Dyer’s woad (Isatis tinctoria L.) is a non-native forb that continues to threaten natural areas throughout Northern Utah and much of the Intermountain West. Once introduced, dyer’s woad can become extremely invasive, decreasing forage quality, and displacing native species. While dyer’s woad is found throughout much of Northern Utah, its range in other states remains limited. If promptly managed, control success in these areas will be much higher and populations may be kept at bay before ecological damage becomes severe.

This project tested the ability of dyer’s woad seedlings to compete with common rangeland grasslands at varied densities as …

Advanced Caching And Streaming For Large Scale Point Cloud Data Visualization On The Web, Pravin Poudel

All Graduate Theses and Dissertations, Fall 2023 to Present

Point clouds are widely used in various applications such as 3D modeling, geospatial analysis, robotics, and more. One of the key advantages of 3D point cloud data is that, unlike other data formats like texture, it is independent of viewing angle, surface type, and parameterization. Since each point in the point cloud is independent of the other, it makes it the most suitable source of data for tasks like object recognition, scene segmentation, and reconstruction. Point clouds are complex and verbose due to the numerous attributes they contain, many of which may not be always necessary for rendering, making retrieving …

Analyzing The Impacts Of Beaver Dam And Beaver Dam Analog Complexes To Stream Ecology Within The Intermountain West, J. Marshall Wolf

All Graduate Theses and Dissertations, Fall 2023 to Present

Streams, rivers, and their floodplains throughout the world are impaired due to human modifications. Recent research has demonstrated that restoration projects prioritizing the proper functioning of ecosystems have better restoration outcomes than projects which focus on restoring form alone. Throughout North America, beaver-mediated restoration is becoming a leading method for improving the functioning of stream ecosystems that are in a degraded state. In areas where beaver are absent or the habitat is too degraded to currently permit their dam building, man-made beaver dam analogs (BDAs) are being used to restore stream habitat with an eye to future beaver recolonization. However, …

An Ensemble Approach For Mapping Snow Water Equivalent In Utah, Logan Schneider

All Graduate Theses and Dissertations, Fall 2023 to Present

Mountain snowpack is an important resource for water management planning in Utah. Snow water equivalent (SWE) is the amount of water contained in a snowpack. A few organizations predict SWE throughout the United States but struggle making accurate predictions in mountainous regions. Weather stations provide accurate measurements of SWE but have limited spatial coverage that hinders the ability to make accurate estimates statewide. This thesis examines the accuracy of current models and proposes using local weather measurements to improve upon national level predictions. An R statistical software package named rsnodas implements this process while allowing the public access to a …

Multi-Objective Water Management In Idaho's Henrys Fork Watershed: Leveraging Reservoir Operation And Groundwater Pathways To Benefit Aquatic Habitat, Christina N. Morrisett

All Graduate Theses and Dissertations, Fall 2023 to Present

Multi-user water management is a challenging arena further complicated by climate change. This research is based in the Henrys Fork, Snake River, Idaho—an agricultural watershed that exemplifies those throughout the semi-arid American West. This dissertation uses an integrated approach that considers groundwater-river relationships, farm-scale decisions and basin-scale outcomes, upstream reservoir operation for downstream aquatic habitat, water rights, and collaborative stakeholder management to identify drought adaptation strategies accordingly.

Chapter 2 uses an interdisciplinary approach to quantify how improvements to irrigation efficiency at the farm-scale (i.e., converting from flood to sprinkler irrigation) can add up to affect hydrology at the landscape-scale and …

Characterization Of The Long-Distance Dispersal Kernel Of White-Tailed Deer And Evaluating Its Impact On Chronic Wasting Disease Spread In Wisconsin, Mennatallah Gouda

All Graduate Theses and Dissertations, Fall 2023 to Present

Chronic Wasting Disease (CWD) is a fatal, untreatable neurodegenerative disease that infects deer and related species. It is highly contagious and caused by abnormal malfunction and assembly of normal cellular proteins into aggregation-prone proteins. The Centers for Disease Control and prevention report that the prevalence of CWD in free-ranging deer in the US is still relatively low. However, in several states the infection rates exceed 1 deer in 10. Deer may uptake CWD from direct interaction with infected individuals or from the environment. Infected individuals shed CWD into the environment through feces, urine, saliva or carcasses, and long-distance dispersal of …