Physical Sciences and Mathematics Commons^™

Molecular Mechanism Of Cyanobacteria Circadian Clock Oscillator And Effect Of Co Factors On Its Oscillation, Manpreet Kaur

Dissertations

The circadian rhythms arise as an adaptation to the environmental 24-hour day and night cycle due to Earth's rotation. These rhythms prepare organisms to align their internal biological activities and day to day behavior or events with the environmental change of the 24-hour day and night cycle. Circadian rhythms are found widely in all living kingdoms of life on Earth. Cyanobacteria are photosynthetic prokaryotes which first used to study these circadian rhythms. Among cyanobacterial species, Synechococcus elongatus PCC 7942 (henceforth, S. Elongatus) is the simplest organism with a durable and sturdy circadian clock and is study as a model organism. …

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 …

Supporting User Interaction And Social Relationship Formation In A Collaborative Online Shopping Context, Yu Xu

Dissertations

The combination of online shopping and social media allow people with similar shopping interests and experiences to share, comment, and discuss about shopping from anywhere and at any time, which also leads to the emergence of online shopping communities. Today, more people turn to online platforms to share their opinions about products, solicit various opinions from their friends, family members, and other customers, and have fun through interactions with others with similar interests. This dissertation explores how collaborative online shopping presents itself as a context and platform for users' interpersonal interactions and social relationship formation through a series of studies. …

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 …

Small-Scale Dynamics Of Photospheric Magnetic Activities And Their Chromospheric Responses, Jiasheng Wang

Dissertations

The evolution of photospheric magnetic fields is considered as the fundamental source of forming atmospheric structures and triggering most solar activities, including flares and mass ejections on various scales (CMEs, jets, etc.). With the implementation of high-resolution observational instruments, small-scale details of magnetic features are recognized that can provide important information regarding the evolution in active regions and the connection between photospheric magnetic reconnection and jet-like ejections in the quiet Sun. This research takes advantage of the exceptionally high-resolution measurements of vector magnetic field and imaging observations by the Goode Solar Telescope, and UV/EUV imaging observations from space-based instruments. The …

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 …

Novel Applications Of Mass Spectrometry For Quantitation And Reaction Mechanism Elucidation, Pengyi Zhao

Dissertations

Mass spectrometry (MS) has been growing as one of the most widely used tools in the field of analytical chemistry. Various applications have been developed to harness the high sensitivity and specificity of mass spectrometric analysis. In this dissertation, two major challenges are addressed. By developing mass spectrometric-based methods, absolute quantitation of proteins/peptides have been achieved. Elucidation of various reaction mechanisms are also enabled. These are the focuses of this dissertation.

In Chapters 2 to 4, a novel quantitation method is developed, titled as coulometric mass spectrometry (CMS). The strength of this method is that no reference standard or isotope-labeled …

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 …

Convergence Of The Boundary Integral Method For Interfacial Stokes Flow, Keyang Zhang

Dissertations

Boundary integral numerical methods are among the most accurate methods for interfacial Stokes flow, and are widely applied. They have the advantage that only the boundary of the domain must be discretized, which reduces the number of discretization points and allows the treatment of complicated interfaces. Despite their popularity, there is no analysis of the convergence of these methods for interfacial Stokes flow. In practice, the stability of discretizations of the boundary integral formulation can depend sensitively on details of the discretization and on the application of numerical filters. A convergence analysis of the boundary integral method for Stokes flow …

Efficient Time-Stepping Approaches For The Dispersive Shallow Water Equations, Linwan Feng

Dissertations

This dissertation focuses on developing efficient and stable (high order) time-stepping strategies for the dispersive shallow water equations (DSWE) with variable bathymetry. The DSWE extends the regular shallow water equations to include dispersive effects. Dispersion is physically important and can maintain the shape of a wave that would otherwise form a shock in the shallow water system.

In some cases, the DSWE may be simplified when the bathymetry length scales are small (or large) in relation to other length scales in the shallow water system. These simplified DSWE models, which are related to the full DSWEs, are also considered in …

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 …

Enrichment Of Ontologies Using Machine Learning And Summarization, Hao Liu

Dissertations

Biomedical ontologies are structured knowledge systems in biomedicine. They play a major role in enabling precise communications in support of healthcare applications, e.g., Electronic Healthcare Records (EHR) systems. Biomedical ontologies are used in many different contexts to facilitate information and knowledge management. The most widely used clinical ontology is the SNOMED CT. Placing a new concept into its proper position in an ontology is a fundamental task in its lifecycle of curation and enrichment.

A large biomedical ontology, which typically consists of many tens of thousands of concepts and relationships, can be viewed as a complex network with concepts as …

Crowdsourcing Atop Blockchains, Yuan Lu

Dissertations

Traditional crowdsourcing systems, such as Amazon's Mechanical Turk (MTurk), though once acquiring great economic successes, have to fully rely on third-party platforms to serve between the requesters and the workers for basic utilities. These third-parties have to be fully trusted to assist payments, resolve disputes, protect data privacy, manage user authentications, maintain service online, etc. Nevertheless, tremendous real-world incidents indicate how elusive it is to completely trust these platforms in reality, and the reduction of such over-reliance becomes desirable.

In contrast to the arguably vulnerable centralized approaches, a public blockchain is a distributed and transparent global "consensus computer" that is …

Mathematical Models And Tools To Understand Coupled Circadian Oscillations And Limit Cycling Systems, Guangyuan Liao

Dissertations

The circadian rhythm refers to an internal body process that regulates many body processes including the sleep-wake cycle, digestion and hormone release. The ability of a circadian system to entrain to the 24-hour light-dark cycle is one of the most important properties. There are several scenarios in which circadian oscillators do not directly receive light-dark forcing. Instead they are part of hierarchical systems in which, as \peripheral" oscillators, they are periodically forced by other \central" circadian oscillators that do directly receive light input. Such dynamics are modeled as hierarchical coupled limit cycle systems. Those models usually have a large population, …

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 …

Machine Learning For Scientific Data Mining And Solar Eruption Prediction, Hao Liu

Dissertations

This dissertation explores new machine learning techniques and adapts them to mine scientific data, specifically data from solar physics and space weather studies. The dissertation tackles three important problems in heliophysics: solar flare prediction, coronal mass ejection (CME) prediction and Stokes inversion.

First, the dissertation presents a long short-term memory (LSTM) network for predicting whether an active region (AR) would produce a certain class of solar flare within the next 24 hours. The essence of this approach is to model data samples in an AR as time series and use LSTMs to capture temporal information of the data samples. The …

Efficient Approximations For Stationary Single-Channel Calcium Nanodomains, Yinbo Chen

Dissertations

Mathematical and computational modeling plays an important role in the study of local Ca2+ signals underlying many fundamental physiological processes such as synaptic neurotransmitter release and myocyte contraction. Closed-form approximations describing steady-state distribution of Ca2+ in the vicinity of an open Ca2+ channel have proved particularly useful for the qualitative modeling of local Ca2+ signals. This dissertation presents several simple and efficient approximants for the equilibrium Ca2+ concentration near a point source in the presence of a mobile Ca2+ buffer, which achieve great accuracy over a wide range of model parameters. Such approximations provide an efficient method for estimating Ca2+ …

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 …

Flare Emission Observed In High Resolution And Comparison With Numerical Modeling, Nengyi Huang

Dissertations

As one of the most intense activities on the solar surface, flares have been extensively observed and studied ever since the first report. The standard model of solar flares has been established and commonly accepted. However, many limitations from the researching tools have left some of the problems unsolved or controversial. For example, the density of electrons in the corona is lower than it is required to activate the observed emission in HXR, and the mechanism that these electron beams can penetrate down to lower chromosphere is unclear. Many theoretical scenarios were suggested, and more observations had been in need. …

Global Optimization Algorithms For Image Registration And Clustering, Cuicui Zheng

Dissertations

Global optimization is a classical problem of finding the minimum or maximum value of an objective function. It has applications in many areas, such as biological image analysis, chemistry, mechanical engineering, financial analysis, deep learning and image processing. For practical applications, it is important to understand the efficiency of global optimization algorithms. This dissertation develops and analyzes some new global optimization algorithms and applies them to practical problems, mainly for image registration and data clustering.

First, the dissertation presents a new global optimization algorithm which approximates the optimum using only function values. The basic idea is to use the points …

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 …

An Automated Feedback System To Support Student Learning Of Conceptual Knowledge In Writing-To-Learn Activities, Ye Xiong

Dissertations

As a pedagogical strategy, Writing-to-Learn (WTL) intends to use writing to improve students’ understanding of course content. However, most of the existing feedback systems for writing are mainly focused on improving students’ writing skills rather than their conceptual development. In this dissertation, an automatic approach is proposed to generate timely, actionable, and individualized feedback based on comparing knowledge representations extracted from lecture slides and individual students’ writing assignments. The novelty of the proposed approach lies in the feedback generation: to help students assimilate new knowledge into their existing knowledge better, their current knowledge is modeled as a set of matching …