Physical Sciences and Mathematics Commons^™

Mechanism And Kinetics Of Photocatalytic Partial Oxidation Of Methane On Single Site Mox Reaction Centers., Clint Evrard

Electronic Theses and Dissertations

Single-site transition-metal doped photocatalysts are a class of materials in which small transition-metal oxide clusters are embedded onto the surface of zeolites, graphene, and bulk semiconductors. Experimental findings demonstrate that VO4, CrO4, NbO4, and WO4 clusters embedded on an MCM- 41 mesoporous amorphous SiO2 are effective photocatalysts for oxidative reactions. The selective direct partial oxidation of methane (POM) to form methanol is essential for efficiently utilizing natural gas. Photocatalytic methane oxidation has advantages over traditional thermal catalysis as it can be deployed at small-scale facilities to reduce methane release into the atmosphere due to flaring potentially. Our work has aimed …

Modeling, Simulation And Control Of Microrobots For The Microfactory., Zhong Yang

Electronic Theses and Dissertations

Future assembly technologies will involve higher levels of automation in order to satisfy increased microscale or nanoscale precision requirements. Traditionally, assembly using a top-down robotic approach has been well-studied and applied to the microelectronics and MEMS industries, but less so in nanotechnology. With the boom of nanotechnology since the 1990s, newly designed products with new materials, coatings, and nanoparticles are gradually entering everyone’s lives, while the industry has grown into a billion-dollar volume worldwide. Traditionally, nanotechnology products are assembled using bottom-up methods, such as self-assembly, rather than top-down robotic assembly. This is due to considerations of volume handling of large …

Improving The Performance Of Automatic Target Recognition Using Data Augmentation., Rolando Holmes

Electronic Theses and Dissertations

Automatic Target Recognition (ATR) is a task that aims to recognize targets based on data obtained from visual sensors such as Infrared cameras. Machine learning, in particular Deep Learning, has been the dominate approach to solve this task. However, in order to achieve high performance, Deep Learning requires a large amount of data that may not be available, which poses an issue when developing robust models. In this thesis, we propose the use of data augmentation from an automatic detector as an alternative source to supplement the need for more training data. We use a two stage approach to develop …

Wearable Sensor Gait Analysis For Fall Detection Using Deep Learning Methods, Haben Girmay Yhdego

Electrical & Computer Engineering Theses & Dissertations

World Health Organization (WHO) data show that around 684,000 people die from falls yearly, making it the second-highest mortality rate after traffic accidents [1]. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. In light of the recent widespread adoption of wearable sensors, it has become increasingly critical that fall detection models are developed that can effectively process large and sequential sensor signal data. Several researchers have recently developed fall detection algorithms based on wearable sensor data. However, real-time fall detection remains challenging because of the wide …

An Investigation On The Effect Of Conserved Hinge Histidine On Influenza Hemagglutinin(Ha2) Protein Conformation Using Md Simulations, Nada Tolba

Chemistry & Biochemistry Undergraduate Honors Theses

Hemagglutinin is a protein on the surface of Human Influenza Viruses.¹ It is composed of two glycopolypeptide domains, the HA1 and HA2 domains. Previous studies have found that across different strains of Influenza viruses, HIS435 residues remain conserved.⁴ In studies where mutations occurred in hinge-site histadine residues, the Influenza virus was inactive.⁴ These investigations indicated a significant role of HIS435 (hinge-site histadines) in virulence. Four systems were created using Molecular dynamics (MD) simulations. Each system was composed of an Isolated HA2 trimer solvated in a 150 mM NaCl rectangular water box at 310 K under isobaric and …

Hydroclimate Effects On Great Salt Lake Decline Since 1980, Siiri Joy Bigalke

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

As a terminal basin lake, the Great Salt Lake (GSL) is known to act as a barometer for low frequency climate variability for the Western United States. As thus, there are naturally occurring large changes to GSL elevation levels that vary on time scales from years to decades. However, amongst these naturally occurring interannual changes there has been a significant declining trend in the elevation levels since a string of anomalous pluvial years in the early 1980s. In the summer of 2022, the Great Salt Lake reached its lowest levels in recorded history, which coincided with a two-decades long regional …

Re-Evaluating Natural Intelligence In The Face Of Chatgpt, Elvin T. Lim, Tze K Koh

Research Collection College of Integrative Studies

How will new technologies impact the nature of higher education? Before ChatGPT, the world witnessed major shifts led by innovations in information storage and transmission. Papyrus in ancient Egypt, the Gutenberg press in 15th-century Europe, and the internet in the 20th century were all milestones in the mass dissemination of knowledge.

Divergence-Conforming Velocity And Vorticity Approximations For Incompressible Fluids Obtained With Minimal Facet Coupling, Jay Gopalakrishnan, Lukas Kogler, Philip L. Lederer, Joachim Schöberl

Mathematics and Statistics Faculty Publications and Presentations

We introduce two new lowest order methods, a mixed method, and a hybrid discontinuous Galerkin method, for the approximation of incompressible flows. Both methods use divergence-conforming linear Brezzi–Douglas–Marini space for approximating the velocity and the lowest order Raviart–Thomas space for approximating the vorticity. Our methods are based on the physically correct viscous stress tensor of the fluid, involving the symmetric gradient of velocity (rather than the gradient), provide exactly divergence-free discrete velocity solutions, and optimal error estimates that are also pressure robust. We explain how the methods are constructed using the minimal number of coupling degrees of freedom per facet. …

Assessment Of Phytoplankton Assemblages And Harmful Algal Blooms In New Jersey, Yaritza Acosta Caraballo

Theses, Dissertations and Culminating Projects

Urbanization, industrialization, and climate change have played a major role in the pollution of waterways, leading to a global increasing trend of harmful algal blooms (HAB) while jeopardizing water quality. Phytoplankton and HAB were evaluated within the highly urbanized and historically polluted state of New Jersey to help provide statewide baseline data for HAB and water quality management. A total of three studies were included in this dissertation. In the first study, phytoplankton communities were characterized in freshwaters of New Jersey during the cyanobacterial HAB season and their relationships to water quality at both statewide and ecoregion levels were examined. …

Seasonal Variations In Nutrient And Total Suspended Solids Sources And Fluxes In Rivers Of Northern New Jersey And Newark Bay, Usa, Jing Nie

Theses, Dissertations and Culminating Projects

In recent decades, aquatic systems have experienced major problems with water quality due to high nutrient concentrations from both point and non-point sources resulting from industrialization, urbanization, and population growth. While nutrient pollution due to land use change cannot be ignored, point sources such as combined sewer overflows and discharging sites have also contributed to the problem. Integrated hydrodynamic, chemical, and biological models have been developed to simulate nutrient transportation from both sources. This paper reviews and analyzes water quality data from published literature to evaluate nutrient pollution in aquatic systems and emphasizes the need for a continuously developed integrated …

The Fate Of Fraxinus Spp. In New Jersey : A Physioeconomic Evaluation Of The Forest System And Infrastructure Implications, Erik W. Lyttek

Theses, Dissertations and Culminating Projects

Though the impacts of pest infestation on forested ecosystems vary, the natural factors that facilitate outbreaks are of concern across multiple disciplines across the USA, affecting such diverse fields as economics, ecology, hydrology, atmospheric sciences, and pedology. Emerald Ash Borer (EAB) is a typical example of an aggressive invasive forest pest; it has proven difficult to eliminate, resistant to natural predators, and damaging to local flora. EAB has recently proliferated through the northern and mid-western forests of the USA, devastating the native population of ash trees (Fraxinus spp.), and has invaded an estimated 28% of all susceptible trees. In New …

Antarctic Peninsula Ice Sheet Dynamics In The Pliocene From Sedimentological Interpretation Of Ocean Drilling Program Site 1097, Ridley Joseph

Theses, Dissertations and Culminating Projects

Studying ice sheet behavior during the Pliocene Epoch is of great importance. The Early Pliocene was characterized by warm climatic conditions, similar carbon dioxide levels and high sea levels compared to the present. This time frame provides essential information on the foreseeable future of Earth’s cryosphere, particularly if climate change continues to persist. The sedimentary record of the Antarctic Peninsula Ice Sheet (APIS) is the focus of this study. At Ocean Drilling Program (ODP) Site 1097, cores were drilled into Pliocene strata at a shallow depth on the Antarctic Peninsula continental shelf. Sedimentary facies were interpreted, and twenty samples were …

Parameter Optimization For Excitable Cell Models, Amrit Parmar

Theses, Dissertations and Culminating Projects

The electrophysiology of nodose ganglia neurons is of great interest in the analysis of cell membrane currents and action potential behavior. This behavior was initially outlined in the Hodgkin-Huxley conductance model [1] using a system of nonlinear differential equations. Later, Schild et al. [2] developed an extension of the Hodgkin-Huxley model to provide a more exhaustive description of ion channels involved in nodose neuronal action potential activity. We consider a variety of methods to fit the parameters of both the Hodgkin-Huxley and Schild et al. models to an empirical stimulus response dataset. Our methods were validated using synthetic datasets, as …

Potential Of Increased Thermal Tolerance As A Response To Acute Heat Stress In A Disease-Transmitting Mosquito Species, Nicole Ashley Scanlon

Theses, Dissertations and Culminating Projects

Each year hundreds of millions of people are infected with mosquito-borne illnesses. West Nile Virus is the leading cause of mosquito-borne diseases in the United States (McDonald et al., 2021). The first case of West Nile Virus was detected in the United States in 1999 (Sejvar, 2003). Since that time the number of cases has dramatically risen. Mosquitoes are ectotherms which means their body temperature is dependent on the thermal conditions outside of their body. Because of this they are very sensitive to changes in their environment. The Earth’s average temperature has been slowly but steadily rising. This small but …

The Identification Of Rogue Access Points Using Channel State Information, Irene Mcginniss

Theses, Dissertations and Culminating Projects

Today's wireless networks (Wi-Fi) handle more significant numbers of connections, deploy efficiently, and provide increased reliability and high speeds at low cost. The ability of rogue access points (RAPs) to mimic legitimate APs makes them the most critical threat to wireless security. APs are found in coffee shops, supermarkets, stadiums, buses, trains, airports, hospitals, theaters, and shopping malls.

Rogue access points (RAP) are unauthorized devices that connect to legitimate access points and networks and bypass authorized security procedures. RAP detection has been attempted using hardware and software-based solutions requiring the developing of dedicated tools or beacon frame modification. (Arisandi, 2021). …

The Interconnected Roles Of Residues N189, E168, And S220 In M. Tuberculosis Indole-3-Glycerol Phosphate Synthase Catalysis, Erik Domlija

Theses, Dissertations and Culminating Projects

Tuberculosis (TB) is an infectious disease caused by the bacteria Mycobacterium tuberculosis that primarily attacks the lungs. Drug resistance for M. tuberculosis is emerging and therefore new drug targets need to be identified. One way to target TB is through the inhibition of the tryptophan biosynthetic pathway of M. tuberculosis since production of tryptophan is essential for the replication of M. tuberculosis. The enzyme Indole-3-glycerol phosphate synthase (MtIGPS) was chosen as a potential drug target due to its role in tryptophan biosynthesis. Residue N189 interacts with active site residues E168 and S220. It is inferred from previous studies done with …

First-Principal Investigations Of The Electronic, Magnetic, And Thermoelectric Properties Of Crtirhal Quaternary Heusler Alloy, Shuruq Alsayegh

Graduate Theses and Dissertations

Density functional theory calculations are performed to investigate the electrical electronic, magnetic, and thermoelectric properties of CrTiRhAl quaternary Heusler alloy (QHA). The type-I atomic configuration is found to be the most stable structure of this alloy. The CrTiRhAl QHA exhibits a half-metallic ferromagnetic structure with a narrow band gap at one spin channel (semiconductor), and a metallic behavior at the other spin channel. This corresponds to a 100% spin-polarization, making it ideal for potential spintronic applications. Applying the semi-classical Boltzmann theory, the Seebeck coefficient, electrical conductivity, and electronic thermal conductivity of CrTiRhAl alloy were calculated. The predicted figure of merit …

Achieving Causal Fairness In Recommendation, Wen Huang

Graduate Theses and Dissertations

Recommender systems provide personalized services for users seeking information and play an increasingly important role in online applications. While most research papers focus on inventing machine learning algorithms to fit user behavior data and maximizing predictive performance in recommendation, it is also very important to develop fairness-aware machine learning algorithms such that the decisions made by them are not only accurate but also meet desired fairness requirements. In personalized recommendation, although there are many works focusing on fairness and discrimination, how to achieve user-side fairness in bandit recommendation from a causal perspective still remains a challenging task. Besides, the deployed …

Dpd Guided Insight On The Formation Process Of Polyethersulfone Membranes By Nonsolvent Induced Phase Separation And The Effects Of Additives, Eric Ledieu

Graduate Theses and Dissertations

Dissipative particle dynamics (DPD), a coarse grain simulation method, was applied to the membrane formation process of non-solvent induced phase separation (NIPS) to gain further insight on the mechanism of certain variables and how they affect the final morphology. NIPS involves two solutions, an organic polymer dissolved in an organic solvent colloquially called the dope and an aqueous coagulation bath, brought into contact with one another. The solvents then mix, causing the polymer to fall out of solution as an asymmetric membrane with a dense surface layer and a more open subsurface layer in response to the decreasing solubility. Polyethersulfone …

The Terroir Of Swiss Cheese: A Temporal And Geomorphological Investigation Of The Martian Co2 Sublimation Pits, Racine D. Cleveland

Graduate Theses and Dissertations

Observations by NASA Mars Global Surveyor showed evidence of rough topography on the South Pole of Mars. The topography is the result of CO2 sublimation processes that occur through the changing seasons on the red planet. These sublimation areas are known to scientists as Swiss Cheese Features (SCF). SCF are erosional degradation pits that have been studied for over two decades. Studies show that these SCF increase in area over time, but these values are collected by hand on a per feature basis. Models for the pit evolution have also played a part in understanding these SCF. This work is …

Asymptotic Properties And Separation Rates For Navier-Stokes Flows, Patrick Michael Phelps

Graduate Theses and Dissertations

In this dissertation, we investigate asymptotic properties of local energy solutions to the Navier-Stokes equations and develop an application which controls the separation of non-unique solutions in this class. Specifically, we quantify the rate at which two, possibly unique solutions evolving from the same data may separate pointwise away from a singularity. This is motivated by recent results on non-uniqueness for forced and unforced Navier-Stokes and analytical and numerical evidence suggesting non-uniqueness in the Leray class. Our investigation begins with discretely self-similar solutions known to exist globally in time and to be regular outside a space-time paraboloid. We prove decay …

Effects Of Landscape And Yard Features On Mammals In Residential Yards In Northwest Arkansas, Emily Johansson

Graduate Theses and Dissertations

The human footprint is rapidly expanding, and wildlife habitat is continuously being converted to human residential properties. Most wildlife residing in developing areas are displaced to nearby undeveloped areas. However, some animals can coexist with humans and acquire the necessary resources (food, water, shelter) within the human environment. This may be particularly true when development is low intensity, as in suburban yards. Due to the wide variety in how homeowners utilize their yards, they can be considered individually managed “greenspaces.” These yards can provide a range of food (e.g., bird feeders, compost, gardens), water (bird baths and garden ponds), and …

Improving Classification In Single And Multi-View Images, Hadi Kanaan Hadi Salman

Graduate Theses and Dissertations

Image classification is a sub-field of computer vision that focuses on identifying objects within digital images. In order to improve image classification we must address the following areas of improvement: 1) Single and Multi-View data quality using data pre-processing techniques. 2) Enhancing deep feature learning to extract alternative representation of the data. 3) Improving decision or prediction of labels. This dissertation presents a series of four published papers that explore different improvements of image classification. In our first paper, we explore the Siamese network architecture to create a Convolution Neural Network based similarity metric. We learn the priority features that …

Quantum Multi-Solution Bernoulli Search With Applications To Bitcoin’S Post-Quantum Security, Alexandru Cojocaru, Juan Garay, Fang Song, Petros Wallden

Computer Science Faculty Publications and Presentations

A proof of work (PoW) is an important cryptographic construct which enables a party to convince other parties that they have invested some effort in solving a computational task. Arguably, its main impact has been in the setting of cryptocurrencies such as Bitcoin and its underlying blockchain protocol, which have received significant attention in recent years due to its potential for various applications as well as for solving fundamental distributed computing questions in novel threat models. PoWs enable the linking of blocks in the blockchain data structure, and thus the problem of interest is the feasibility of obtaining a sequence …

Identifying Taphonomic Distribution Patterns At The Gray Fossil Site, Shawn Haugrud

Electronic Theses and Dissertations

Since the early days of the discovery of the Gray Fossil Site (GFS), meticulous efforts to preserve the spatial data were a priority. Direct surveying of fossils prior to recovery, as well as grid mapping the site, provided relative spatial data within a square meter. Such efforts meant that even fragments and microfossils, recovered during the screening operations and eventual concentrate picking, maintained some spatial data. Available spatial data are used to identify smaller deposits within the greater system, as well as non-random distribution patterns among a number of GFS taxa. Patterns are particularly pronounced in the large-bodied taxa, Teleoceras …

First Skulls Of Arctomeles Dimolodontus (Mustelidae: Melinae) From The Gray Fossil Site (Early Pliocene, Tn) Reveal Extreme Intraspecific Variation, Charles Bruce

Electronic Theses and Dissertations

Here, a morphological description of the extinct meline badger Arctomeles dimolodontus from the Gray Fossil Site (GFS), Tennessee is provided with comparison to extant Meles meles. Originally described solely on upper teeth of a single individual, the recovery of several crania and jaws provides a sample of at least five individuals, affording the largest known fossil sample in North America of the enigmatic Melinae. Examination of A. dimolodontus skull material reveals extreme intraspecific variation in previously identified diagnostic characters, highlighting the need for caution when identifying fossil taxa based on similarly fragmentary remains. Dental variation is likely a result …

Subgroup Identification Via Interaction Tree And Mixed Model For Repeated Measures With Application To Alzheimer’S Disease, Zhichen Xu

Arts & Sciences Graduate Student Theses and Dissertations

No abstract provided.

Learning-Based Stock Trending Prediction By Incorporating Technical Indicators And Social Media Sentiment, Zhaoxia Wang, Zhenda Hu, Fang Li, Seng-Beng Ho, Erik Cambria

Research Collection School Of Computing and Information Systems

Stock trending prediction is a challenging task due to its dynamic and nonlinear characteristics. With the development of social platform and artificial intelligence (AI), incorporating timely news and social media information into stock trending models becomes possible. However, most of the existing works focus on classification or regression problems when predicting stock market trending without fully considering the effects of different influence factors in different phases. To address this gap, this research solves stock trending prediction problem utilizing both technical indicators and sentiments of the social media text as influence factors in different situations. A 3-phase hybrid model is proposed …

Liloc: Enabling Precise 3d Localization In Dynamic Indoor Environments Using Lidars, Darshana Rathnayake, Meera Radhakrishnan, Inseok Hwang, Archan Misra

Research Collection School Of Computing and Information Systems

We present LiLoc, a system for precise 3D localization and tracking of mobile IoT devices (e.g., robots) in indoor environments using multi-perspective LiDAR sensing. The key differentiators in our work are: (a) First, unlike traditional localization approaches, our approach is robust to dynamically changing environmental conditions (e.g., varying crowd levels, object placement/layout changes); (b) Second, unlike prior work on visual and 3D SLAM, LiLoc is not dependent on a pre-built static map of the environment and instead works by utilizing dynamically updated point clouds captured from both infrastructural-mounted LiDARs and LiDARs equipped on individual mobile IoT devices. To achieve fine-grained, …

Are You Cloud-Certified? Preparing Computing Undergraduates For Cloud Certification With Experiential Learning, Eng Lieh Ouh, Benjamin Gan

Research Collection School Of Computing and Information Systems

Cloud Computing skills have been increasing in demand. Many software engineers are learning these skills and taking cloud certification examinations to be job competitive. Preparing undergraduates to be cloud-certified remains challenging as cloud computing is a relatively new topic in the computing curriculum, and many of these certifications require working experience. In this paper, we report our experiences designing a course with experiential learning to prepare our computing undergraduates to take the cloud certification. We adopt a university project-based experiential learning framework to engage industry partners who provide project requirements for students to develop cloud solutions and an experiential risk …