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Ce 360-103: Sustainable Civil Engineering Materials, Matthew Adams

Civil and Environmental Engineering Syllabi

No abstract provided.

Tran 603-101: Introduction To Urban Transportation Planning, I Jy Chien

Civil and Environmental Engineering Syllabi

No abstract provided.

Tran 650-851: Urban Systems Engineering, Lazar Spasovic

Civil and Environmental Engineering Syllabi

No abstract provided.

Chem 336-101: Physical Chemistry Iii, Farnaz Shakib

Chemistry, Environmental and Forensic Science Syllabi

No abstract provided.

Chem 658-101: Advanced Physical Chemistry, Farnaz Shakib

Chemistry, Environmental and Forensic Science Syllabi

No abstract provided.

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 …

Live Media Production: Multicast Optimization And Visibility For Clos Fabric In Media Data Centers, Ammar Latif

Dissertations

Media production data centers are undergoing a major architectural shift to introduce digitization concepts to media creation and media processing workflows. Content companies such as NBC Universal, CBS/Viacom and Disney are modernizing their workflows to take advantage of the flexibility of IP and virtualization.

In these new environments, multicast is utilized to provide point-to-multi-point communications. In order to build point-to-multi-point trees, Multicast has an established set of control protocols such as IGMP and PIM. The existing multicast protocols do not optimize multicast tree formation for maximizing network throughput which lead to decreased fabric utilization and decreased total number of admitted …

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 …

A Comprehensive And Absolute Corporate Sustainability Assessment And Enhanced Input Output Life Cycle Assessment, Joseph M. Wright

Dissertations

Stresses due to economic activity are threatening to exceed environmental and societal limits with the potential to jeopardize local communities and create global crises. This research proposes new methodologies and analytic techniques to comprehensively assess corporate sustainability and enhance the efficiency of estimating environmental and social impacts with Input Output Life Cycle Assessment (IOLCA).

Sustainability assessments and management require consideration of both social and environmental impacts as outflows of economic activity. There are a number of assessment tools available to gain insight into environmental and social impacts; but in most cases, these approaches lack essential components for a comprehensive and …

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 …

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 …

1,4-Dioxane Biodegradation In Propanotrophs: Molecular Foundations And Implications For Environmental Remediation, Li Fei

Dissertations

1,4-Dioxane (dioxane) has emerged with an escalating concern given its human carcinogenicity and widespread occurrence in groundwater. Bioremediation is promising as an effective and cost-efficient treatment alternative for in situ or ex situ cleanup of dioxane and co-existing pollutants in the field. Soluble di-iron monooxygenases (SDIMOs) are reputed for their essential roles in initiating the cleavage of dioxane and other pollutants. In this doctoral dissertation, molecular foundations for SDIMOs-mediated dioxane biodegradation are untangled to promote the development and implication of site-specific bioremediation and natural attenuation strategies. This dissertation focused on propanotrophic bacteria given their pivotal roles in dioxane metabolism and …

Investigating The Combined Effects Of Whole Body Vibration And Vestibular Stimulation On Spasticity And Dystonia In Cerebral Palsy, Peter A. Michael

Dissertations

This study identifies and addresses three voids and potential shortcomings associated with the classification, assessment and management of Cerebral Palsy (CP). These concerns should not undermine the significant advancement that has been made in this specific branch of rehabilitation, but addressing them is necessary. Cerebral Palsy is a group of motor impairments due to hypoxic-ischemic brain damage around the time of birth and very commonly manifests as excessive muscle tone and poor motor control. There are classifications within CP including spasticity and dystonia.

First, a level of discrepancy is present in the classification of CP between the clinical and research …

Mind Maps And Machine Learning: An Automation Framework For Qualitative Research In Entrepreneurship Education, Yasser Farha

Dissertations

Entrepreneurship Education researchers often measure entrepreneurial motivation of college students. It is important for stakeholders, such as policymakers and educators, to assert if entrepreneurship education can encourage students to become entrepreneurs, as well as to understand factors that influence entrepreneurial motivation. For that purpose, researchers have used different methods and instruments to measure students' entrepreneurial motivation. Most of these methods are quantitative, e.g., closed-ended surveys, whereas qualitative methods, e.g., open-ended surveys, are rarely used.

Mind maps are an attractive qualitative survey tool because they capture the individual's reflections, thoughts, and experiences. For Entrepreneurship Education, mind maps can be utilized to …

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 …

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. …

Analyzing And Assisting Patient Decision-Making In Online Health Communities, Mingda Li

Dissertations

In recent years, many users have joined online health communities (OHC) to seek information, suggestions and social support. However, little has been studied about the roles of OHCs in patients' decision-making processes. The aim of this research is to analyze OHC data to better understand patient decision-making processes, and to provide assistance to OHC users in their decision-making.

In order to analyze or assist patients in their decision-making, a novel classification model is designed to identify discussion threads in OHC that are related to decision making. This is achieved by building a two-step combined deep learning model. Empirical evaluation shows …

Exploration Of Novel Ferroelectric Systems: Determination Of The Underlying Mechanisms, Sizhan Liu

Dissertations

Modern environmental and sustainability issues, as well as the growing demand for applications in sensing and data storage, require the discovery and development of new functional materials. Ferroelectrics and multiferroics are materials that have played a central role in this arena. Because the central function of ferroelectrics is governed by spontaneous polarization response, understanding both the electronic and atomic response to external stimuli is important. In this work, a broad set of model systems were explored to determine the fundamental mechanisms involved in the formation of the ferroelectric phase.

Understanding atomic-level changes in structure is important for improving the properties …

Graphene Based Barrier Membrane For Gas Separation Processes, Cheng Peng

Dissertations

Novel graphene oxide (GO) flake-based composite lamellar membrane structure is being developed as a potential component of a garment for protection against chemical warfare agents (CWAs) represented here by simulants, dimethyl methyl phosphonate (DMMP) (a sarin-simulant) and 2-chloroethyl ethyl sulfide (2-CEES) (a simulant for sulfur mustard), yet allowing a high moisture transmission rate. GO flakes of dimensions 300-800 nm, 0.7-1.2 nm thickness and dispersed in an aqueous suspension are formed into a membrane by vacuum filtration on a porous polyethersulfone (PES) or poly (ether-ether-ketone) (PEEK) support membrane for noncovalent π-π interactions with GO flakes. After physical compression of such a …

Accurate Patient Health Condition Identification And Risk Prediction From Health Data, Jinhe Shi

Dissertations

Online Health communities (OHCs), Electronic Health Records (EHRs) and Claims data contain rich patient information. Accurate identification of patient's health conditions is critical for providing effective and safe health care service and for trustable knowledge discovery. This dissertation proposes several deep-learning based techniques on identifying patient health conditions and predicting adverse drug event (ADE) risks using various health data.

First, this dissertation presents a novel patient experience mining model to differentiate the data expressing user experiences from the one describing hearsays. Indeed, OHCs contain information with varying degrees of quality. Identifying information that describes patient health experience from OHCs is …

Comparison Of Longitudinal Changes In Resting State Functional Magnetic Resonance Imaging Between Alzheimer’S And Healthy Controls, Berk Can Yilmaz

Theses

Resting State Functional Magnetic Resonance Imaging (rs-fMRI) is a technique that is widely used for analyzing brain function using different approaches and methods. This study involves rs-fMRI analysis of Blood Oxygenation Level Dependent (BOLD) signals acquired from Alzheimer’s disease (AD) Patients and Healthy Controls (HC). Each subject in the study had both functional and anatomical images with at least one rs-fMRI scan with their Anatomical (T1) scans. Previous rs-fMRI studies have demonstrated that AD shows differences in Amplitude of Low Frequency (<0.1 Hz) Fluctuations (ALFF), and Regional Homogeneity (ReHo) measures according to HCs.

The aim of the study is to investigate individual and group level differences using ReHo and mALFF related …

Team Formation Using Recommendation Systems, Shreyas Patil

Theses

The importance of team formation has been realized since ages, but finding the most effective team out of the available human resources is a problem that persists to the date. Having members with complementary skills, along with a few must-have behavioral traits, such as trust and collaborativeness among the team members are the key ingredients behind team synergy and performance. This thesis designs and implements two different algorithms for the team formation problem using ideas adapted from the recommender systems literature. One of the proposed solutions uses the Glicko-2 rating system to rate the employees’ skills which can easily separate …