Physical Sciences and Mathematics Commons^™

Data Assimilation For Conductance-Based Neuronal Models, Matthew Moye

Dissertations

This dissertation illustrates the use of data assimilation algorithms to estimate unobserved variables and unknown parameters of conductance-based neuronal models. Modern data assimilation (DA) techniques are widely used in climate science and weather prediction, but have only recently begun to be applied in neuroscience. The two main classes of DA techniques are sequential methods and variational methods. Throughout this work, twin experiments, where the data is synthetically generated from output of the model, are used to validate use of these techniques for conductance-based models observing only the voltage trace. In Chapter 1, these techniques are described in detail and the …

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 …

Calculating Elastic Properties Of Confined Simple Fluids, Christopher D. Dobrzanski

Dissertations

Confinement in nanoporous materials is known to affect many properties of the fluids confined within their pores. The elastic properties are no exception. This dissertation begins with an overview of the relevant literature on ways of obtaining elastic properties of confined fluids. It outlines some fundamental gaps in our understanding. The chapters following address some of these gaps in understanding elastic properties of the confined fluid, in particular, how the shape of the confining pore matters, how supercriticality effects the properties, how an equation of state designed for confined fluids can be used to calculate elastic properties, and if an …

Pegylated Block Copolymer For Cancer Imaging And Treatment, Sweety Singh

Dissertations

Gene theranostics have emerged as an important tool for the treatment of cancer as well as other diseases. Among the challenges in this field is the lack of effective vectors to chaperone plasmids into cells while the vector itself exhibits minimal toxicity. Herein, the synthesis, cellular uptake, and gene delivery using a biocompatible norbornene-based block copolymer is reported. This block copolymer, bearing polyethylene glycol moieties along with primary amines is functionalized with both a boron dipyrromethene (BODIPY) fluorophore for fluorescence tracking and a folic acid derivative for cancer cell targeting.

Stoichiometry control afforded residual unreacted amine functional groups available to …

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 …

Construct Local Quasi-Interpolation Operators Using Linear B-Splines, Abeer Alzahrani

Dissertations

The data interpolating problem is a fundamental problem in data analysis, and B-splines are frequently used as the basis functions for data interpolation. In the real-world applications, the real-time processing is very important. To achieve that, we cannot use any matrix inversion for large amount of data, and we also need to avoid using any global operator. To solve this problem, we develop a new method based on a local quasi-interpolation operator. To construct the local quasi-interpolation operator, we need to factorize the Shoenberg-Whitney matri- ces for the given data samples. Furthermore, our local quasi-interpolation operator should correspond to a …

An Atomistic Study Of The Effects On Mechanical Properties And Bonding Interactions Of Carbon Nanofillers In Nylon 6 Nanocomposites, Michael Roth

Dissertations

Polymers have potential for a wide range of applications. The effectiveness of polymers can be further enhanced through the addition of nanofillers that improve thermal, mechanical, and electrical properties of the polymer. Carbon based nanofillers such as carbon nanotube (CNT), graphene, and carbon nanofibre (CNF) are of particular interest due to their high properties and high aspect ratios. However, limited understanding of the governing interactions of these nanofillers with polymers limits the effectiveness of the final nanocomposite.

The first facet of this dissertation focuses on determining the dominating interactions between pristine CNT and graphene with nylon 6 monomer and the …

Effect Of Selfsame Microparticles On Epoxide Amine Network Formation And Matrix Mechanics, Travis Palmer

Dissertations

Epoxide amine matrices are widely utilized in aerospace carbon fiber reinforced polymer (CFRP) composites having engendered significant reductions in weight and fuel consumption. This dissertation focuses on the effect of constrained space during network formation on the matrix mechanics of these highly complex composite systems. Precipitation polymerization conditions are developed to prepare epoxide amine microparticles (EMs) based on tetraglycidyl-4,4’-methylenedianiline (TGDDM) and isophorone diamine (IPDA). Surface functionality of EMs is tuned via control of epoxide to reactive amine hydrogen ratio, where unreactive, amine- and epoxide-functional EMs are prepared. We demonstrate that EMs are polydisperse, but can be filtered, yielding low dispersity …

A Dynamic F5 Algorithm, Candice Mitchell

Dissertations

Gröbner bases are a “nice” representation for nonlinear systems of polynomials, where by “nice” we mean they have good computation properties. They have many useful applications, including decidability (whether the system has a solution or not), ideal membership (whether a given polynomial is in the system or not), and cryptography. Traditional Gröbner basis algorithms require as input an ideal and an admissible term ordering. They then determine a Gröbner basis with respect to the given ordering. Some term orderings lead to a smaller basis, but finding them traditionally requires testing many orderings and hoping for better results. A dynamic algorithm …

Huisgen 1,3-Dipolar Azide-Alkyne Cycloaddition “Click” Reaction In Polymer Synthesis And Curing, Jie Wu

Dissertations

This dissertation’s key focus is on utilizing Huisgen 1,3-dipolar azide-alkyne cycloaddition (AAC) reaction in copolymer synthesis and modification, including thermoplastic block copolymer and commercially available two-component polyurethane system. It can be divided into two major projects, introduced as follows.

The first project involves the development of a modular synthetic approach toward polyisobutylene (PIB)-based triphasic pentablock thermoplastic elastomer with enhanced moisture permeability. This terpolymer consists of a poly(styrene-b-isobutylene-b-styrene) (SIBS) core and appended hydrophilic polymer blocks (HBs). The SIBS core was synthesized via living cationic polymerization (LCP) of isobutylene followed by sequential addition of styrene. AAC was utilized …

Geochemical Tracers Of Arctic Ocean Processes: A Study Of Gallium, Barium, And Vanadium, Laura M. Whitmore

Dissertations

The Arctic Ocean is linked to the global oceans and climate through its connectivity with the North Atlantic Ocean and the regional thermohaline deep water formation sites. It’s also a region undergoing rapid environmental change. To inform the community of potential changes in geochemical and biogeochemical cycles, this dissertation addresses three dissolved geochemical tracers (gallium, barium, and vanadium) as indicators of Arctic Ocean processes. Gallium is tested as a replacement for nutrient-type tracers in an effort to deconvolve Pacific and Atlantic derived waters in the Arctic Ocean basins. These water masses carry different heat and salt content and can influence …

Cross Language Information Transfer Between Modern Standard Arabic And Its Dialects – A Framework For Automatic Speech Recognition System Language Model, Tiba Zaki Abdulhameed

Dissertations

Significant advances have been made with Modern Standard Arabic (MSA) Automatic Speech Recognition (ASR) applications. Yet, dialectal conversation ASR is still trailing behind due to limited language resources. As is the case in most cultures, the formal Modern Standard Arabic language is not used in daily life. Instead, varieties of regional dialects are spoken, which creates a dire need to address dialect ASR systems. Processing MSA language naturally poses considerable challenges that are passed on to the processing of its derived dialects. In dialects, many words have gradually morphed from MSA pronunciations and at many times have different usages. Also, …

Extremal Problems On Induced Graph Colorings, James Hallas

Dissertations

Graph coloring is one of the most popular areas of graph theory, no doubt due to its many fascinating problems and applications to modern society, as well as the sheer mathematical beauty of the subject. As far back as 1880, in an attempt to solve the famous Four Color Problem, there have been numerous examples of certain types of graph colorings that have generated other graph colorings of interest. These types of colorings only gained momentum a century later, however, when in the 1980s, edge colorings were studied that led to vertex colorings of various types, led by the introduction …

High Performance And Machine Learning Algorithms For Brain Fmri Data, Taban Eslami

Dissertations

Brain disorders are very difficult to diagnose for reasons such as overlapping nature of symptoms, individual differences in brain structure, lack of medical tests and unknown causes of some disorders. The current psychiatric diagnostic process is based on behavioral observation and may be prone to misdiagnosis.

Noninvasive brain imaging technologies such as Magnetic Resonance Imaging (MRI) and functional Magnetic Resonance Imaging (fMRI) make the process of understanding the structure and function of the brain easier. Quantitative analysis of brain imaging data using machine learning and data mining techniques can be advantageous not only to increase the accuracy of brain disorder …

Computer Simulations Of Muscle Driven Undulatory Locomotion, Ye Luo

Dissertations

A novel muscle driven method is developed to mimic contracting and expanding of muscles, in a fish-like swimming body, which cause its body flapping in the transversal direction and create thrust force to push its body to cruise in the longitudinal direction. The muscle deformation is realized by using the RATTLE constraint algorithm. The turbulent fluids are treated by a multi-relaxation time lattice Boltzmann method with a large eddy simulation. The fish body is dealt with a lattice spring model and interactions between fluids and solid structures are handled by a direct-forcing immersed boundary method. Validations are conducted by comparing …

Assessment Of The Impact Of Climate Change On Land Use In The Emirate Of Abu Dhabi - An Environmental And Socio-Economic Perspective, Latifa Saeed Al Blooshi

Dissertations

This dissertation focuses on the impact of climate change on land use in the Emirate of Abu Dhabi – UAE. Climate change is a significant challenge resulting from natural and anthropogenic causes. Land use can stimulate changes in communities under climate change. The main objective of this dissertation is to assess the impact of climate change from an environmental and socio-economic perspective. In 2001, coastal sabkhas, mixed class and urbanized areas experienced an increase in temperature by (0.67, 1.14 and 1.16°C) respectively. In cities, urban areas are warmer than neighbouring rural areas. Unexpectedly, urbanization in desert areas in UAE led …

Activated Carbon Nanofibers From Renewable (Lignin) And Waste Resources (Recycled Pet) And Their Adsorption Capacity Of Refractory Sulfur Compounds From Fossil Fuels, Efstratios Svinterikos

Dissertations

Dementia is a condition in which higher mental functions are disrupted. It currently affects an estimated 57 million people throughout the world. Dementia diagnosis is difficult since neither anatomical indicator nor functional testing are currently sufficiently sensitive or specific. There remains a long list of outstanding issues that must be addressed. First, multimodal diagnosis has yet to be introduced into the early stages of dementia screening. Second, there is no accurate instrument for predicting the progression of pre-dementia. Third, non-invasive testing cannot be used to provide differential diagnoses. By creating ML models of normal and accelerated brain aging, we intend …

New Catalytic Reactions In Carbohydrate Chemistry, Scott Geringer

Dissertations

Carbohydrates or sugars are some of the most diverse and abundant biological molecules. They are involved in a multitude of processes in the body such as fertilization, cell-cell communication, and cancer metathesis. Because of these vital functions, the study of sugars is rapidly growing field. The field however is limited due to the complex nature of sugars which results in difficulties in obtaining large quantities for study.

Protecting group manipulation is a large emphasis area in carbohydrate chemistry due to the need to selectively protect different functional groups of each molecule during synthesis. Catalytic and selective cleavage of protecting groups …

High-Order Adaptive Synchrosqueezing Transform, Jawaher Alzahrani

Dissertations

The prevalence of the separation of multicomponent non-stationary signals across many elds of research makes this concept an important subject of study. The synchrosqueezing transform (SST) is a particular type of reassignment method. It aims to separate and recover the components of a multicomponent non-stationary signal. The short time Fourier transform (STFT)-based SST (FSST) and the continuous wavelet transform (CWT)based SST (WSST) have been used in engineering and medical data analysis applications. The current study introduces the dierent versions of FSST and WSST to estimate instantaneous frequency (IF) and to recover components. It has a good concentration and reconstruction for …

Noise Reduction Of Eeg Signals Using Autoencoders Built Upon Gru Based Rnn Layers, Esra Aynali

Dissertations

Understanding the cognitive and functional behaviour of the brain by its electrical activity is an important area of research. Electroencephalography (EEG) is a method that measures and record electrical activities of the brain from the scalp. It has been used for pathology analysis, emotion recognition, clinical and cognitive research, diagnosing various neurological and psychiatric disorders and for other applications. Since the EEG signals are sensitive to activities other than the brain ones, such as eye blinking, eye movement, head movement, etc., it is not possible to record EEG signals without any noise. Thus, it is very important to use an …

An Evaluation Of Text Representation Techniques For Fake News Detection Using: Tf-Idf, Word Embeddings, Sentence Embeddings With Linear Support Vector Machine., Sangita Sriram

Dissertations

In a world where anybody can share their views, opinions and make it sound like these are facts about the current situation of the world, Fake News poses a huge threat especially to the reputation of people with high stature and to organizations. In the political world, this could lead to opposition parties making use of this opportunity to gain popularity in their elections. In the medical world, a fake scandalous message about a medicine giving side effects, hospital treatment gone wrong or even a false message against a practicing doctor could become a big menace to everyone involved in …

Drug Reviews: Cross-Condition And Cross-Source Analysis By Review Quantification Using Regional Cnn-Lstm Models, Ajith Mathew Thoomkuzhy

Dissertations

Pharmaceutical drugs are usually rated by customers or patients (i.e. in a scale from 1 to 10). Often, they also give reviews or comments on the drug and its side effects. It is desirable to quantify the reviews to help analyze drug favorability in the market, in the absence of ratings. Since these reviews are in the form of text, we should use lexical methods for the analysis. The intent of this study was two-fold: First, to understand how better the efficiency will be if CNN-LSTM models are used to predict ratings or sentiment from reviews. These models are known …

Image Instance Segmentation: Using The Cirsy System To Identify Small Objects In Low Resolution Images, Orghomisan William Omatsone

Dissertations

The CIRSY system (or Chick Instance Recognition System) is am image processing system developed as part of this research to detect images of chicks in highly-populated images that uses the leading algorithm in instance segmentation tasks, called the Mask R-CNN. It extends on the Faster R-CNN framework used in object detection tasks, and this extension adds a branch to predict the mask of an object along with the bounding box prediction. Mask R-CNN has proven to be effective ininstance segmentation and object de-tection tasks after outperforming all existing models on evaluation of the Microsoft Common Objects in Context (MS COCO) …

Machine Learning Assisted Gait Analysis For The Determination Of Handedness In Able-Bodied People, Hugh Gallagher

Dissertations

This study has investigated the potential application of machine learning for video analysis, with a view to creating a system which can determine a person’s hand laterality (handedness) from the way that they walk (their gait). To this end, the convolutional neural network model VGG16 underwent transfer learning in order to classify videos under two ‘activities’: “walking left-handed” and “walking right-handed”. This saw varying degrees of success across five transfer learning trained models: Everything – the entire dataset; FiftyFifty – the dataset with enough right-handed samples removed to produce a set with parity between activities; Female – only the female …

An Examination Of The Smote And Other Smote-Based Techniques That Use Synthetic Data To Oversample The Minority Class In The Context Of Credit-Card Fraud Classification, Eduardo Parkinson De Castro

Dissertations

This research project seeks to investigate some of the different sampling techniques that generate and use synthetic data to oversample the minority class as a means of handling the imbalanced distribution between non-fraudulent (majority class) and fraudulent (minority class) classes in a credit-card fraud dataset. The purpose of the research project is to assess the effectiveness of these techniques in the context of fraud detection which is a highly imbalanced and cost-sensitive dataset. Machine learning tasks that require learning from datasets that are highly unbalanced have difficulty learning since many of the traditional learning algorithms are not designed to cope …

Transformer Neural Networks For Automated Story Generation, Kemal Araz

Dissertations

Towards the last two-decade Artificial Intelligence (AI) proved its use on tasks such as image recognition, natural language processing, automated driving. As discussed in the Moore’s law the computational power increased rapidly over the few decades (Moore, 1965) and made it possible to use the techniques which were computationally expensive. These techniques include Deep Learning (DL) changed the field of AI and outperformed other models in a lot of fields some of which mentioned above. However, in natural language generation especially for creative tasks that needs the artificial intelligent models to have not only a precise understanding of the given …

Identifying Online Sexual Predators Using Support Vector Machine, Yifan Li

Dissertations

A two-stage classification model is built in the research for online sexual predator identification. The first stage identifies the suspicious conversations that have predator participants. The second stage identifies the predators in suspicious conversations. Support vector machines are used with word and character n-grams, combined with behavioural features of the authors to train the final classifier. The unbalanced dataset is downsampled to test the performance of re-balancing an unbalanced dataset. An age group classification model is also constructed to test the feasibility of extracting the age profile of the authors, which can be used as features for classifier training. The …

Classification Of Animal Sound Using Convolutional Neural Network, Neha Singh

Dissertations

Recently, labeling of acoustic events has emerged as an active topic covering a wide range of applications. High-level semantic inference can be conducted based on main audioeffects to facilitate various content-based applications for analysis, efficient recovery and content management. This paper proposes a flexible Convolutional neural network-based framework for animal audio classification. The work takes inspiration from various deep neural network developed for multimedia classification recently. The model is driven by the ideology of identifying the animal sound in the audio file by forcing the network to pay attention to core audio effect present in the audio to generate Mel-spectrogram. …

A Comparative Study Of Text Summarization On E-Mail Data Using Unsupervised Learning Approaches, Tijo Thomas

Dissertations

Over the last few years, email has met with enormous popularity. People send and receive a lot of messages every day, connect with colleagues and friends, share files and information. Unfortunately, the email overload outbreak has developed into a personal trouble for users as well as a financial concerns for businesses. Accessing an ever-increasing number of lengthy emails in the present generation has become a major concern for many users. Email text summarization is a promising approach to resolve this challenge. Email messages are general domain text, unstructured and not always well developed syntactically. Such elements introduce challenges for study …