Physical Sciences and Mathematics Commons^™

Coordination, Adaptation, And Complexity In Decision Fusion, Weiqiang Dong

Dissertations

A parallel decentralized binary decision fusion architecture employs a bank of local detectors (LDs) that access a commonly-observed phenomenon. The system makes a binary decision about the phenomenon, accepting one of two hypotheses (H0 (“absent”) or H1 (“present”)). The k 1 LD uses a local decision rule to compress its local observations yk into a binary local decision uk; uk = 0 if the k 1 LD accepts H0 and uk = 1 if it accepts H1. The k 1 LD sends its decision uk over a noiseless dedicated channel to a Data Fusion Center (DFC). The DFC combines the …

Drone-Assisted Emergency Communications, Di Wu

Dissertations

Drone-mounted base stations (DBSs) have been proposed to extend coverage and improve communications between mobile users (MUs) and their corresponding macro base stations (MBSs). Different from the base stations on the ground, DBSs can flexibly fly over and close to MUs to establish a better vantage for communications. Thus, the pathloss between a DBS and an MU can be much smaller than that between the MU and MBS. In addition, by hovering in the air, the DBS can likely establish a Line-of-Sight link to the MBS. DBSs can be leveraged to recover communications in a large natural disaster struck area …

A Deep Machine Learning Approach For Predicting Freeway Work Zone Delay Using Big Data, Abdullah Shabarek

Dissertations

The introduction of deep learning and big data analytics may significantly elevate the performance of traffic speed prediction. Work zones become one of the most critical factors causing congestion impact, which reduces the mobility as well as traffic safety. A comprehensive literature review on existing work zone delay prediction models (i.e., parametric, simulation and non-parametric models) is conducted in this research. The research shows the limitations of each model. Moreover, most previous modeling approaches did not consider user delay for connected freeways when predicting traffic speed under work zone conditions. This research proposes Deep Artificial Neural Network (Deep ANN) and …

Dances And Escape Of The Vortex Quartet, Brandon Behring

Dissertations

This dissertation considers the linear stability of a one-parameter family of periodic solutions of the four-vortex problem known as 'leapfrogging' orbits. These solutions, which consist of two pairs of identical yet oppositely-signed vortices, were known to W. Gröbli (1877) and A. E. H. Love (1883) and can be parameterized by a dimensionless parameter related to the geometry of the initial configuration. Simulations by Acheson and numerical Floquet analysis by Tophøj and Aref both indicate, to many digits, that the bifurcation occurs at a value related to the inverse square of the golen ratio. Acheson observed that, after an initial period …

Characterizing Reactive Iron Mineral Coatings And Their Roles In Natural Attenuation At A Site With Historical Contamination, Han Hua

Dissertations

Reactive iron mineral coatings in redox transition zones play an important role in contaminant attenuation. These mineral coatings include poorly crystalline to crystalline iron sulfides, carbonates, and oxyhydroxides, and are a signature of the biogeochemical processes occurring. To better understand these processes, reactive iron mineral coatings are characterized in an 18-m Anaerobic Core collected from a contaminated industrial site. This study targets redox transition zones uncovered in the core. A suite of complementary analyses is applied to distinguish the surface coating mineralogy using X-ray Diffraction, X-ray fluorescence, and field-emission scanning electron microscopy (FESEM) with energy dispersive X-ray analyzer (EDX). In …

The Aging And Impacts Of Atmospheric Soot: Closing The Gap Between Experiments And Models, Ogochukwu Yvonne Enekwizu

Dissertations

The main goal of this dissertation is to generate data and parameterizations to accurately represent soot aerosols in atmospheric models. Soot from incomplete combustion of fossil fuels and biomass burning is a major air pollutant and a significant contributor to climate warming. The environmental impacts of soot are strongly dependent on the particle morphology and mixing state, which evolve continuously during atmospheric transport via a process known as aging. To make predictions of soot impacts on the environment, most atmospheric models adopt simplifications of particle structure and mixing state, which lead to substantial uncertainties. Using an experimentally constrained modeling approach, …

Performance Optimization Of Big Data Computing Workflows For Batch And Stream Data Processing In Multi-Clouds, Huiyan Cao

Dissertations

Workflow techniques have been widely used as a major computing solution in many science domains. With the rapid deployment of cloud infrastructures around the globe and the economic benefits of cloud-based computing and storage services, an increasing number of scientific workflows have migrated or are in active transition to clouds. As the scale of scientific applications continues to grow, it is now common to deploy various data- and network-intensive computing workflows such as serial computing workflows, MapReduce/Spark-based workflows, and Storm-based stream data processing workflows in multi-cloud environments, where inter-cloud data transfer oftentimes plays a significant role in both workflow performance …

Modeling Mass Transfer And Chemical Reaction In Industrial Nitrocellulose Manufacturing Processes, Francis Patrick Sullivan

Dissertations

A series of models are proposed to describe the production of military grade nitrocellulose from dense cellulose materials in mixtures of nitric acid, sulfuric acid, and water. This effort is conducted to provide a predictive capability for analyzing the rate and extent of reaction achieved under a range of reaction conditions used in the industrial nitrocellulose manufacturing process for sheeted cellulose materials. Because this capability does not presently exist, nitrocellulose producers have historically relied on a very narrow range of cellulose raw materials and resorted to trial and error methods to develop processing conditions for new materials. This tool enables …

Countering Internet Packet Classifiers To Improve User Online Privacy, Sina Fathi-Kazerooni

Dissertations

Internet traffic classification or packet classification is the act of classifying packets using the extracted statistical data from the transmitted packets on a computer network. Internet traffic classification is an essential tool for Internet service providers to manage network traffic, provide users with the intended quality of service (QoS), and perform surveillance. QoS measures prioritize a network's traffic type over other traffic based on preset criteria; for instance, it gives higher priority or bandwidth to video traffic over website browsing traffic. Internet packet classification methods are also used for automated intrusion detection. They analyze incoming traffic patterns and identify malicious …

Blast Shock-Wave Characterization In Experimental Shock Tubes, Sudeepto Kahali

Dissertations

Blast-induced traumatic brain injuries have affected U.S. soldiers deployed for extended periods in the gulf and Afghanistan wars. To identify the biomechanical and biochemical mechanisms of injury, critical in the identification of diagnostic and therapeutic tools, compressed gas-driven shock tubes are used by investigators to study shockwave-animal specimen interactions and its biological consequences. However, shock tubes are designed and operated in a variety of geometry with a range of process parameters, and the quality of shock wave characteristics relevant to field conditions and therefore the study of blast-induced traumatic brain injuries suffered by soldiers is affected by those conditions. Lab-to-lab …

Semantic, Integrated Keyword Search Over Structured And Loosely Structured Databases, Xinge Lu

Dissertations

Keyword search has been seen in recent years as an attractive way for querying data with some form of structure. Indeed, it allows simple users to extract information from databases without mastering a complex structured query language and without having knowledge of the schema of the data. It also allows for integrated search of heterogeneous data sources. However, as keyword queries are ambiguous and not expressive enough, keyword search cannot scale satisfactorily on big datasets and the answers are, in general, of low accuracy. Therefore, flat keyword search alone cannot efficiently return high quality results on large data with structure. …

Development Of Novel Membranes For Nanocarbon Enhanced Separation With Application In Biofuels And Solvent Recover, Oindrila Gupta

Dissertations

Pharmaceutical industries historically have had one of the highest amounts of solvent waste generated per unit of drug manufactured. Energy requirements and carbon footprint of current solvent recycling processes tend to be quite high, and the incineration of the solvents for waste disposal produces toxic air emissions. Also, rapidly increasing demand for energy and strict regulation on engine pollutant emissions have necessitated the use of alcohol as carbon-neutral fuels. Thermal distillation is one of the most common methods for the separation of alcohol-water mixtures. However, its application is limited due to energy requirements and high operating costs, and heating to …

Practical Adhesion Measurements In Organic Coatings; Advancing Understanding And Mechanical Methods Development, Diana Gottschalk

Dissertations

“Adhesion” can be considered either a mechanical or chemical phenomenon. The mechanical interpretation describes the difficulty of separating surfaces and is useful for quantifying performance within applications that depend on bulk and interfacial properties. Chemical adhesion describes interfacial resistance to chemical attack and does not depend on bulk properties. Predicting chemical failure through mechanical measurement is confounded by the influence of bulk properties. However, the prospect is attractive because of the robust tolerance for sample geometries, allowing experiments to resemble an end-use system. The present work's primary goal was to elevate mechanical methods to provide a detailed interfacial characterization of …

Hybrid Deep Neural Networks For Mining Heterogeneous Data, Xiurui Hou

Dissertations

In the era of big data, the rapidly growing flood of data represents an immense opportunity. New computational methods are desired to fully leverage the potential that exists within massive structured and unstructured data. However, decision-makers are often confronted with multiple diverse heterogeneous data sources. The heterogeneity includes different data types, different granularities, and different dimensions, posing a fundamental challenge in many applications. This dissertation focuses on designing hybrid deep neural networks for modeling various kinds of data heterogeneity.

The first part of this dissertation concerns modeling diverse data types, the first kind of data heterogeneity. Specifically, image data and …

Resonant Triad Interactions In One And Two-Layer Systems, Malik Chabane

Dissertations

This dissertation is a study of the weakly nonlinear resonant interactions of a triad of gravity-capillary waves in systems of one and two fluid layers of arbitrary depth, in one and two-dimentions. For one-layer systems, resonant triad interactions of gravity-capillary waves are considered and a region where resonant triads can be always found is identified, in the two-dimensional wavevector angles-space. Then a description of the variations of resonant wavenumbers and wave frequencies over the resonance region is given. The amplitude equations correct to second order in wave slope are used to investigate special resonant triads that, providing their initial amplitude …

Energy And Performance-Optimized Scheduling Of Tasks In Distributed Cloud And Edge Computing Systems, Haitao Yuan

Dissertations

Infrastructure resources in distributed cloud data centers (CDCs) are shared by heterogeneous applications in a high-performance and cost-effective way. Edge computing has emerged as a new paradigm to provide access to computing capacities in end devices. Yet it suffers from such problems as load imbalance, long scheduling time, and limited power of its edge nodes. Therefore, intelligent task scheduling in CDCs and edge nodes is critically important to construct energy-efficient cloud and edge computing systems. Current approaches cannot smartly minimize the total cost of CDCs, maximize their profit and improve quality of service (QoS) of tasks because of aperiodic arrival …

Changing The Focus: Worker-Centric Optimization In Human-In-The-Loop Computations, Mohammadreza Esfandiari

Dissertations

A myriad of emerging applications from simple to complex ones involve human cognizance in the computation loop. Using the wisdom of human workers, researchers have solved a variety of problems, termed as “micro-tasks” such as, captcha recognition, sentiment analysis, image categorization, query processing, as well as “complex tasks” that are often collaborative, such as, classifying craters on planetary surfaces, discovering new galaxies (Galaxyzoo), performing text translation. The current view of “humans-in-the-loop” tends to see humans as machines, robots, or low-level agents used or exploited in the service of broader computation goals. This dissertation is developed to shift the focus back …

Towards Practical Homomorphic Encryption And Efficient Implementation, Gyana R. Sahu

Dissertations

Cloud computing has gained significant traction over the past few years and its application continues to soar as evident from its rapid adoption in various industries. One of the major challenges involved in cloud computing services is the security of sensitive information as cloud servers have been often found to be vulnerable to snooping by malicious adversaries. Such data privacy concerns can be addressed to a greater extent by enforcing cryptographic measures. Fully homomorphic encryption (FHE), a special form of public key encryption has emerged as a primary tool in deploying such cryptographic security assurances without sacrificing many of the …

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 …

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 …

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. …

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 …

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. …

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 …

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 …

Modeling Single Microtubules As A Colloidal System To Measure The Harmonic Interactions Between Tubulin Dimers In Bovine Brain Derived Versus Cancer Cell Derived Microtubules, Arooj Aslam

Dissertations

The local properties of tubulin dimers dictate the properties of the larger microtubule assembly. In order to elucidate this connection, tubulin-tubulin interactions are be modeled as harmonic interactions to map the stiffness matrix along the length of the microtubule. The strength of the interactions are measured by imaging and tracking the movement of segments along the microtubule over time, and then performing a fourier transform to extract the natural vibrational frequencies. Using this method the first ever reported experimental phonon spectrum of the microtubule is reported. This method can also be applied to other biological materials, and opens new doors …

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 …

Numerical And Analytical Methods To Predict Behavior Of Reinforced Ductile Concrete Composites, Mandeep Pokhrel

Dissertations

Structural components constructed with ductile concrete composites, such as high-performance fiber-reinforced cementitious composites (HPFRCC), are known to perform exceptionally well under extreme mechanical and environmental loading conditions compared to traditional concrete. HPFRCC flexural components exhibit enhanced performance in terms of displacement ductility, energy dissipation capacity, and damage tolerance capacity. However, recent research suggests that the flexural behavior of reinforced HPFRCCs in terms of crack progression, reinforcement plasticity, and failure mechanism is significantly different than conventional reinforced concrete. Specifically, the failure mode of flexural members is found to be predominantly through the fracture of longitudinal reinforcement rather than compression crushing of …

Coding Against Stragglers In Distributed Computation Scenarios, Malihe Aliasgari

Dissertations

Data and analytics capabilities have made a leap forward in recent years. The volume of available data has grown exponentially. The huge amount of data needs to be transferred and stored with extremely high reliability. The concept of "coded computing", or a distributed computing paradigm that utilizes coding theory to smartly inject and leverage data/computation redundancy into distributed computing systems, mitigates the fundamental performance bottlenecks for running large-scale data analytics.

In this dissertation, a distributed computing framework, first for input files distributedly stored on the uplink of a cloud radio access network architecture, is studied. It focuses on that decoding …