Physical Sciences and Mathematics Commons^™

Studies Of Two-Phase Flow With Soluble Surfactant, Ryan Peter Atwater

Dissertations

Numerical methods are developed for accurate solution of two-phase flow in the zero Reynolds number limit of Stokes flow, when surfactant is present on a drop interface and in its bulk phase interior. The methods are designed to achieve high accuracy when the bulk Péclet number is large, or equivalently when the bulk phase surfactant has small diffusivity

In the limit of infinite bulk Péclet number the advection-diffusion equation that governs evolution of surfactant concentration in the bulk is singularly perturbed, indicating a separation of spatial scales. A hybrid numerical method based on a leading order asymptotic reduction in this …

A Study Of Information Bots And Knowledge Bots, Amartya Hatua

Dissertations

In this dissertation, a study of different aspects of information bots and knowledge bots is done. The research contributes to a better understanding of the various characteristics of information bots as well as the different patterns and factors responsible for the information diffusion in a social network. This research also shows how these factors can be used to predict information diffusion for a particular topic in a social network. The second part of the research is focused on strategies for improving the knowledge base of knowledge bots, where two different approaches are studied. In the first approach, knowledge is transferred …

Variable Compact Multi-Point Upscaling Schemes For Anisotropic Diffusion Problems In Three-Dimensions, James Quinlan

Dissertations

Simulation is a useful tool to mitigate risk and uncertainty in subsurface flow models that contain geometrically complex features and in which the permeability field is highly heterogeneous. However, due to the level of detail in the underlying geocellular description, an upscaling procedure is needed to generate a coarsened model that is computationally feasible to perform simulations. These procedures require additional attention when coefficients in the system exhibit full-tensor anisotropy due to heterogeneity or not aligned with the computational grid. In this thesis, we generalize a multi-point finite volume scheme in several ways and benchmark it against the industry-standard routines. …

Synthesis Of Alpha-Methylselenocysteine, Its Relevant Analogues, And An Unnatural Glutathione Disulfide Core, Robert J. Wehrle

Dissertations

Selenoproteins, such as glutathione peroxidase, have gained interest for their ability to act as antioxidants, and their potential to act as anti-cancer agents. Synthesizing and studying selenoproteins can be problematic, however, due to their propensity to degrade from over-oxidation. The degradation from over-oxidation can be avoided by the incorporation of the unnatural amino acid, alpha-methylselenocysteine. A synthesis utilizing methyl malonic esters was used to synthesize protected (R)-alpha-methylselenocysteine efficiently (46% over four steps) and in high enantio-purity (88% enantiomeric excess). Using similar procedures, the (S)-enantiomer was also synthesized as well as a beta-analogue.

The use of enzymes …

Empirical Studies Of Deep Learning On Information Diffusion On Social Networks And Collective Task Learning For Swarm Robotics, Trung T. Nguyen

Dissertations

Researchers in multiple disciplines have recently adopted deep learning because of its ability of high accuracy representation learning from big and complex data. My research goal in this thesis is developing deep learning models for information diffusion analysis on social networks and collective tasks learning in swarm robotics. Firstly, the information diffusion on social networks is modeled as a multivariate time series in three dimensions with ten features. Then, we applied time-series clustering algorithms with Dynamic Time Warping to discover different patterns of our models. Then, we build a prediction model based on LSTM, which outperforms traditional time-series prediction methods. …

A 3d Image-Guided System To Improve Myocardial Revascularization Decision-Making For Patients With Coronary Artery Disease, Haipeng Tang

Dissertations

OBJECTIVES. Coronary artery disease (CAD) is the most common type of heart disease and kills over 360,000 people a year in the United States. Myocardial revascularization (MR) is a standard interventional treatment for patients with stable CAD. Fluoroscopy angiography is real-time anatomical imaging and routinely used to guide MR by visually estimating the percent stenosis of coronary arteries. However, a lot of patients do not benefit from the anatomical information-guided MR without functional testing. Single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is a widely used functional testing for CAD evaluation but limits to the absence of anatomical information. …

Machine Learning Approaches For Improving Prediction Performance Of Structure-Activity Relationship Models, Gabriel Idakwo

Dissertations

In silico bioactivity prediction studies are designed to complement in vivo and in vitro efforts to assess the activity and properties of small molecules. In silico methods such as Quantitative Structure-Activity/Property Relationship (QSAR) are used to correlate the structure of a molecule to its biological property in drug design and toxicological studies. In this body of work, I started with two in-depth reviews into the application of machine learning based approaches and feature reduction methods to QSAR, and then investigated solutions to three common challenges faced in machine learning based QSAR studies.

First, to improve the prediction accuracy of learning …

Resource Optimization In Support Of Iot Applications, Ihab Ahmed Mohammed

Dissertations

With the rise of the Internet of Things (IoT) and smart communities, managing computation and communication resources required by billions of smart devices becomes a concern. To tackle this problem, we develop algorithms for resource management to ensure better Quality of Service (QoS), safety, and performance. We focus our efforts on three problems.

In the first problem, we studied the strict QoS requirements of applications and differentiated service requirements in different situations of vehicular networks. We propose a generic prioritization and resource management algorithm that can be used to prioritize the processing of received packets in vehicular networks. We formulate …

The Assessment Of Co2 Exposures, Workload Demands, And Musculoskeletal Disorder Risk On Heart Rate For Select Craft Brewery Job Tasks, David L. Huizen

Dissertations

Americans have embraced craft beer, and the ensuing demand has resulted in an ever-increasing number of craft breweries opening over the past 20 years. Craft brewers are generally small employers and, as such, lack the resources necessary to address the safety and health of their employees adequately. Brewers face many safety and health hazards in their work environment. These hazards include exposures to carbon dioxide (CO₂), workload demand, and MSD risk. It is essential to evaluate these hazards in craft breweries as they handle carbon dioxide (CO₂) differently than large breweries by having the CO_{2 …}

A Comprehensive Security Approach On Data Race Detection And Deepfake Defense, Yu Guo

Dissertations

In the past decades, even the computer techniques have a significant improvement. The topic about security will be never out of date.

To meet with the requirement of computation, the number of CPU cores has changed from single core to multi-cores. At the same time, the multi-thread programs are also proposed to maximize the advantages of multi-core computing power. While even the performance has been improved, but it also brings some new issues which were never happened on sequential programs called current bugs. Data race is a major type of current bugs, it is happened when multiple threads access the …

Maia And Admonita: Mandatory Integrity Control Language And Dynamic Trust Framework For Arbitrary Structured Data, Wassnaa Al-Mawee

Dissertations

The expansion of attacks against information systems of companies that operate nuclear power stations and other energy facilities in the United States and other countries, are noticeable with potential catastrophic real-world implications. Data integrity is a fundamental component of information security. It refers to the accuracy and the trustworthiness of data or resources. Data integrity within information systems becomes an important factor of security protection as the data becomes more integrated and crucial to decision-making. The security threats brought by human errors whether, malicious or unintentional, such as viruses, hacking, and many other cybersecurity threats, are dangerous and require mandatory …

Accumulation Of Polar Vorticity On Giant Planets: Towards A Three-Dimensional Theory, Shawn R. Brueshaber

Dissertations

My research investigates the polar atmospheric dynamics of the giant planets: Jupiter and Saturn (gas giants), and Uranus and Neptune (ice giants). I conduct my research modifying and applying the Explicit Planetary Isentropic Coordinate global circulation code to model the polar regions of the four giant planets.

The motivation behind my research is to uncover the reason why giant planet polar atmospheric dynamics differ. Jupiter features multiple circumpolar cyclones arranged in geometrical configurations, whereas Saturn features a single pole-centered cyclone. Uranus and Neptune also appear to have single pole-centered cyclones, albeit, larger than those on Saturn. …

Statistical Downscaling Techniques To Enhance The Spatial Resolution Of The Grace Satellite Data And To Fill Temporal Gaps, Hossein Sahour

Dissertations

The Gravity Recovery and Climate Experiment (GRACE) has been successfully used to monitor variations in terrestrial water storage (GRACE_TWS ) and groundwater storage (GRACE_GWS) across the globe, yet such applications are hindered on local scales by the limited spatial resolution of GRACE data. Using the Lower Peninsula of Michigan as a test site, I developed optimum procedures to downscale GRACE Release-06 monthly mascon solutions. A four-fold exercise is conducted. Cluster analysis is performed to identify the optimum number and distribution of clusters (areas) of contiguous pixels of similar geophysical signals (GRACE_TWS time series); three clusters are …

Inverse Problems For Polynomial And Rational Matrices, Richard Allen Hollister

Dissertations

Inverse problems have long been studied in mathematics not only because there are many applications in science and engineering, but also because they yield new insight into the beauty of mathematics. Central to the subject of linear algebra is the eigenvalue problem: given a matrix, and its eigenvalues (numerical invariants). Eigenvalue problems play a key role in almost every field of scientific endeavor from calculating the vibrational modes of a molecule to modeling the spread of an infectious disease, and so have been studied extensively since the time of Euler in the 18th century.

If a typical matrix eigenvalue problem …

Embedded Gold Nanoparticles For Metal Enhanced Photoluminescence, Hasna Alali

Dissertations

Noble metal nanoparticles (MNPs) have attracted great attention in electronics, solar cells and catalysis. Their unique optical properties and biocompatibility makes them useful in biological applications like imaging, drug delivery, therapy and diagnostic. At the surface of MNPs the collective oscillation of free electrons resonates with a particular wavelength of incident light, generating the Localized Surface Plasmons Resonance (LSPR). LSPR results in absorption and scattering of incident light. Scattering results in reflecting photons and absorption leads to enhanced photoluminescence and quenching of fluorophores, if the fluorophore is in the vicinity of MNPs.

Most of the studies in this regard have …

Application Of Artificial Intelligence And Geographic Information System For Developing Automated Walkability Score, Md Mehedi Hasan

Dissertations

Walking is considered as one of the major modes of active transportation, which contributes to the livability of cities. It is highly important to ensure walk friendly sidewalks to promote human physical activities along roads. Over the last two decades, different walk scores were estimated in respect to walkability measures by applying different methods and approaches. However, in the era of big data and machine learning revolution, there is still a gap to measure the composite walkability score in an automated way by applying and quantifying the activityfriendliness of walkable streets. In this study, a street-level automated walkability score was …

Investigation Of Finite Temperature And Continuum Effects On Nuclear Excitations, Herlik Wibowo

Dissertations

The low-energy nuclear response at finite-temperature significantly affects the radiative neutron capture reaction rates of the r-process nucleosynthesis. In order to address this topic, the first part of this study focuses on the response of compound nuclei or nuclei at finite temperature. The thermal nuclear response satisfies the Bethe-Salpeter equation (BSE) with the static and dynamical kernels of different origins. While the origin of the static kernel is the nearly instantaneous nucleon-meson interaction, the dynamical kernel is induced by the coupling between nucleons and phonons. The presence of singularities in the dynamical kernel makes the BSE unsolvable, however, a time …

Integrating Detailed Petrography, Geochemistry, And Mineralogy To Elucidate Extensive Early Diagenesis In The Eocene Carbonates Of Qatar, Brooks H. Ryan

Dissertations

Eocene carbonates comprising the Umm er Radhuma (UER), Rus, and Dammam Formations, cover 80% of the surface and extend >300 m into the subsurface of Qatar. These rocks record marine sedimentation in shallow sub-tidal to restricted settings. Despite undergoing only shallow burial (<1000 m), extensive diagenetic alteration has occurred. Given that little work on this topic has been published previously, the objectives of this work are to document diagenesis in the Eocene, and to integrate petrography, mineralogy, and geochemistry to delineate the timing and environments of diagenesis of these Eocene carbonates. Detailed petrographic data show that dolomitization occurred early in the UER, before the formation of diagenetic chert, palygorskite, pyrite, calcite, and gypsum cements. Bulk dolomite δ¹⁸O values, coupled with clumped isotope-derived (Δ47) temperatures and dolomitizing fluid δ¹⁸O values, suggest dolomitization took place in near-normal marine fluids, perhaps during shallow burial. These data challenge the current paradigm of large-scale, top-down hypersaline reflux dolomitization in the UER. Associated depth trends of increasing crystal size and with increasing stoichiometry and cation ordering …

Program Testing And Synthesis By Program Semantics, Lin Cheng

Dissertations

GUIs are event-driven applications where the flow of the program is determined by user actions such as mouse clicks and key presses. GUI testing is a challenging task not only because of the combinatorial explosion in the number of event sequences, but also because of the difficulty to cover the large number of data values. To tackle this problem, we propose two algorithms: GUICat and GUICat2.

GUICat is a white-box GUI testing tool that augments traditional sequence generation techniques with concolic execution. It also has a cloud-based parallel algorithm for mitigating both event sequence explosion and data value explosion, by …

Statistical Properties And Applications Of Press Statistic, Ida Marie Alcantara

Dissertations

The most popularly used statistic R^₂ has a fundamental weakness in model building: it favors adding more predictors to the model because R² can only increase. In effect, the additional predictors start fitting the noise in data. Other criterion in selecting a regression model such as R² _adj , AIC, SBC, and Mallow’s C_p does not guarantee the model selected will also make better prediction of future values. To avoid this, data scientists withhold a percentage of the data for validation purposes. The PRESS statistic does something similar by withholding each observation in calculating its own …

An Integrated Approach (Remote Sensing, Hydrogeology, Gis, And Statistical Modeling) To Identify The Distribution Of Shallow Groundwater Occurrences Over Southwest Saudi Arabia, Fahad Khudier Alshehri

Dissertations

Identifying shallow (near-surface) groundwater in arid and hyper-arid areas has significant societal benefits, yet it is a costly operation when traditional methods (geophysics and drilling) are applied over large domains. In this study, we developed and successfully applied methodologies that rely heavily on readily available temporal, visible and near-infrared, radar, and thermal remote sensing data sets and field data, as well as statistical approaches to map the distribution of shallow (1–5 m deep) groundwater occurrences in Al Qunfudah Province, Saudi Arabia and to identify the factors controlling their development. A four-fold approach was adopted: (1) constructing a digital database to …

On Codes Over Rings: The Macwilliams Extension Theorem And The Macwilliams Identities, Noha Abdelghany

Dissertations

The MacWilliams extension theorem for code equivalence and the MacWilliams identities for weight enumerators of a code and its dual code are two of the most important results in classical coding theory. In this thesis, we study how much these two results could be extended to codes over more general alphabets, beyond finite fields. In particular, we study the MacWilliams extension theorem and the MacWilliams identities for codes over rings and modules equipped with general weight functions.

A Unified Decentralized Trust Framework For Detection Of Iot Device Attacks In Smart Homes, Hussein Salim Qasim Alsheakh

Dissertations

Trust in Smart Home technology security is a primary concern for consumers, which can prevent them from adopting smart home services. Such concerns are due to following reasons; (i) nature of IoT devices– which due to their limited computational and resource capabilities, cannot support traditional on-device security controls (ii) any breach to cyber-attacks have an immediate impact on the smart homeowner, compared to traditional cyber-attacks (iii) a large variety of different applications and services under the umbrella of make an overarching security framework for smart homes fundamentally challenging for both providers to offer and owners to manage.

This dissertation offers …

Universal Constraints Of Kleinian Groups And Hyperbolic Geometry, Hala Alaqad

Dissertations

Recent advances in geometry have shown the wide application of hyperbolic geometry not only in Mathematics but also in real-world applications. As in two dimensions, it is now clear that most three-dimensional objects (configuration spaces and manifolds) are modelled on hyperbolic geometry. This point of view explains a great many things from large-scale cosmological phenomena, such as the shape of the universe, right down to the symmetries of groups and geometric objects, and various physical theories. Kleinian groups are basically discrete groups of isometries associated with tessellations of hyperbolic space. They form the fundamental groups of hyperbolic manifolds. Over the …

Compound Flooding In Coastal Areas Emanating From Inland And Offshore Events, Hamed Behzad Koochaksaraii

Dissertations

The vulnerability of urban populations to natural hazards and climate change is a major theme in many reports on coastal cities with flooding ranking highly among the climate change concerns. Flooding could occur as a result of runoff for inland rainfall that accumulates at the mouth of the estuary to the sea or it could occur due to a storm surge emanating from the ocean. The techniques for modeling the flooding from these events are very different, as they were developed in different scientific fields: hydrology and hydraulic engineering for inland rainfall versus coastal oceanography and coastal engineering for offshore …

Transfer Learning: Bridging The Gap Between Deep Learning And Domain-Specific Text Mining, Chaoran Cheng

Dissertations

Inspired by the success of deep learning techniques in Natural Language Processing (NLP), this dissertation tackles the domain-specific text mining problems for which the generic deep learning approaches would fail. More specifically, the domain-specific problems are: (1) success prediction in crowdfunding, (2) variants identification in biomedical literature, and (3) text data augmentation for domains with low-resources.

In the first part, transfer learning in a multimodal perspective is utilized to facilitate solving the project success prediction on the crowdfunding application. Even though the information in a project profile can be of different modalities such as text, images, and metadata, most existing …

Stress-State And Injection-Rate Dependent Damage Processes During The Hydraulic Fracturing Of Granite, Gayani Sasendrika Gunarathna

Dissertations

Hydraulic fracturing is a well-stimulation technique that is employed in field applications, such as enhanced geothermal systems (EGS) and shale oil/gas extraction. This research experimentally investigates the effect of the state of stress and injection rate on the hydraulic fracturing processes. In addition, a displacement discontinuity method (DDM) code, FROCK, is used to model the crack initiation and propagation in a granite specimen under hydraulic fracturing conditions. In order to conduct the experimental work, a test setup capable of applying a triaxial state of stress and water pressure inside pre-fabricated flaws cut in prismatic granite specimens is developed. Additionally, the …

Subspace Portfolios: Design And Performance Comparison, Anqi Xiong

Dissertations

Data processing and engineering techniques enable people to observe and better understand the natural and human-made systems and processes that generate huge amounts of various data types. Data engineers collect data created in almost all fields and formats, such as images, audio, and text streams, biological and financial signals, sensing and many others. They develop and implement state-of-the art machine learning (ML) and artificial intelligence (AI) algorithms using big data to infer valuable information with social and economic value. Furthermore, ML/AI methodologies lead to automate many decision making processes with real-time applications serving people and businesses. As an example, mathematical …

Efficient Hardware Implementations Of Bio-Inspired Networks, Anakha Vasanthakumaribabu

Dissertations

The human brain, with its massive computational capability and power efficiency in small form factor, continues to inspire the ultimate goal of building machines that can perform tasks without being explicitly programmed. In an effort to mimic the natural information processing paradigms observed in the brain, several neural network generations have been proposed over the years. Among the neural networks inspired by biology, second-generation Artificial or Deep Neural Networks (ANNs/DNNs) use memoryless neuron models and have shown unprecedented success surpassing humans in a wide variety of tasks. Unlike ANNs, third-generation Spiking Neural Networks (SNNs) closely mimic biological neurons by operating …

Nanocarbon Modification Of Membranes For Enhanced Water Desalination And Water Treatment, Worawit Intrchom

Dissertations

Water scarcity is foreseen to be one of the great global issues in the coming decades. The challenges are not only in providing water supply to cope with the growing public demand, but recovering clean water to natural resources. Clean water supply, from brackish and seawater is attractive. Membrane distillation (MD) is an emerging thermal membrane-based process that has been used for desalination and other pollutant separations from water. MD can be operated at low temperature, so low-grade energy sources are a good alternative heat source for MD. High salt rejection and low membrane fouling also make MD interesting for …