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Full-Text Articles in Physical Sciences and Mathematics

A New Model For Predicting The Drag And Lift Forces Of Turbulent Newtonian Flow On Arbitrarily Shaped Shells On The Seafloor, Carley R. Walker, James V. Lambers, Julian Simeonov May 2022

A New Model For Predicting The Drag And Lift Forces Of Turbulent Newtonian Flow On Arbitrarily Shaped Shells On The Seafloor, Carley R. Walker, James V. Lambers, Julian Simeonov

Dissertations

Currently, all forecasts of currents, waves, and seafloor evolution are limited by a lack of fundamental knowledge and the parameterization of small-scale processes at the seafloor-ocean interface. Commonly used Euler-Lagrange models for sediment transport require parameterizations of the drag and lift forces acting on the particles. However, current parameterizations for these forces only work for spherical particles. In this dissertation we propose a new method for predicting the drag and lift forces on arbitrarily shaped objects at arbitrary orientations with respect to the direction of flow that will ultimately provide models for predicting the sediment sorting processes that lead to ...


An Analysis On Network Flow-Based Iot Botnet Detection Using Weka, Cian Porteous Jan 2022

An Analysis On Network Flow-Based Iot Botnet Detection Using Weka, Cian Porteous

Dissertations

Botnets pose a significant and growing risk to modern networks. Detection of botnets remains an important area of open research in order to prevent the proliferation of botnets and to mitigate the damage that can be caused by botnets that have already been established. Botnet detection can be broadly categorised into two main categories: signature-based detection and anomaly-based detection. This paper sets out to measure the accuracy, false-positive rate, and false-negative rate of four algorithms that are available in Weka for anomaly-based detection of a dataset of HTTP and IRC botnet data. The algorithms that were selected to detect botnets ...


Dark Patterns: Effect On Overall User Experience And Site Revisitation, Deon Soul Calawen Jan 2022

Dark Patterns: Effect On Overall User Experience And Site Revisitation, Deon Soul Calawen

Dissertations

Dark patterns are user interfaces purposefully designed to manipulate users into doing something they might not otherwise do for the benefit of an online service. This study investigates the impact of dark patterns on overall user experience and site revisitation in the context of airline websites. In order to assess potential dark pattern effects, two versions of the same airline website were compared: a dark version containing dark pattern elements and a bright version free of manipulative interfaces. User experience for both websites were assessed quantitatively through a survey containing a User Experience Questionnaire (UEQ) and a System Usability Scale ...


Measuring And Comparing Social Bias In Static And Contextual Word Embeddings, Alan Cueva Mora Jan 2022

Measuring And Comparing Social Bias In Static And Contextual Word Embeddings, Alan Cueva Mora

Dissertations

Word embeddings have been considered one of the biggest breakthroughs of deep learning for natural language processing. They are learned numerical vector representations of words where similar words have similar representations. Contextual word embeddings are the promising second-generation of word embeddings assigning a representation to a word based on its context. This can result in different representations for the same word depending on the context (e.g. river bank and commercial bank). There is evidence of social bias (human-like implicit biases based on gender, race, and other social constructs) in word embeddings. While detecting bias in static (classical or non-contextual ...


Evaluating The Performance Of Vision Transformer Architecture For Deepfake Image Classification, Devesan Govindasamy Jan 2022

Evaluating The Performance Of Vision Transformer Architecture For Deepfake Image Classification, Devesan Govindasamy

Dissertations

Deepfake classification has seen some impressive results lately, with the experimentation of various deep learning methodologies, researchers were able to design some state-of-the art techniques. This study attempts to use an existing technology “Transformers” in the field of Natural Language Processing (NLP) which has been a de-facto standard in text processing for the purposes of Computer Vision. Transformers use a mechanism called “self-attention”, which is different from CNN and LSTM. This study uses a novel technique that considers images as 16x16 words (Dosovitskiy et al., 2021) to train a deep neural network with “self-attention” blocks to detect deepfakes. It creates ...


Exposing And Fixing Causes Of Inconsistency And Nondeterminism In Clustering Implementations, Xin Yin Dec 2021

Exposing And Fixing Causes Of Inconsistency And Nondeterminism In Clustering Implementations, Xin Yin

Dissertations

Cluster analysis aka Clustering is used in myriad applications, including high-stakes domains, by millions of users. Clustering users should be able to assume that clustering implementations are correct, reliable, and for a given algorithm, interchangeable. Based on observations in a wide-range of real-world clustering implementations, this dissertation challenges the aforementioned assumptions.

This dissertation introduces an approach named SmokeOut that uses differential clustering to show that clustering implementations suffer from nondeterminism and inconsistency: on a given input dataset and using a given clustering algorithm, clustering outcomes and accuracy vary widely between (1) successive runs of the same toolkit, i.e., nondeterminism ...


Model Checks For Two-Sample Location-Scale, Atefeh Javidialsaadi Dec 2021

Model Checks For Two-Sample Location-Scale, Atefeh Javidialsaadi

Dissertations

Two-sample location-scale refers to a model that permits a pair of standardized random variables to have a common distribution. This means that if X1 and X2 are two random variables with means µ1 and µ2 and standard deviations ?1 and ?2, then (X1 - µ1)/?1 and (X2 - µ2)/?2 have some common unspecified standard or base distribution F0. Function-based hypothesis testing for these models refers to formal tests that would help determine whether or not two samples may have come from some location-scale family of distributions, without specifying the standard distribution ...


Hydrophobically Modified Isosorbide Dimethacrylates As Biomaterials For Bisphenol A Free Dental Fillings, Bilal Marie Dec 2021

Hydrophobically Modified Isosorbide Dimethacrylates As Biomaterials For Bisphenol A Free Dental Fillings, Bilal Marie

Dissertations

Amalgam and Bisphenol A glycerolate dimethacrylate (BisGMA) are the main dental filling materials in use today. Because of the negative perception of amalgam and its lower esthetic appeal, as well as the desire to replace the endocrine disruptor Bisphenol A, which is the building block of BisGMA, there has been a critical need to search for safer alternatives to these dental filling materials.

Isosorbide is a sugar-based molecule generally recognized as safe. It has been extensively studied as a replacement to the Bisphenol A core in various materials. However, isosorbide is extremely hygroscopic, and water uptake in dental fillings causes ...


Coherent Control Of Dispersive Waves, Jimmie Adriazola Dec 2021

Coherent Control Of Dispersive Waves, Jimmie Adriazola

Dissertations

This dissertation addresses some of the various issues which can arise when posing and solving optimization problems constrained by dispersive physics. Considered here are four technologically relevant experiments, each having their own unique challenges and physical settings including ultra-cold quantum fluids trapped by an external field, paraxial light propagation through a gradient index of refraction, light propagation in periodic photonic crystals, and surface gravity water waves over shallow and variable seabeds. In each of these settings, the physics can be modeled by dispersive wave equations, and the technological objective is to design the external trapping fields or propagation media such ...


Private And Federated Deep Learning: System, Theory, And Applications For Social Good, Han Hu Dec 2021

Private And Federated Deep Learning: System, Theory, And Applications For Social Good, Han Hu

Dissertations

During the past decade, drug abuse continues to accelerate towards becoming the most severe public health problem in the United States. The ability to detect drug­abuse risk behavior at a population scale, such as among the population of Twitter users, can help to monitor the trend of drug­abuse incidents. However, traditional methods do not effectively detect drug­abuse risk behavior in tweets, mainly due to the sparsity of such tweets and the noisy nature of tweets. In the first part of this dissertation work, the task of classifying tweets as containing drug­abuse risk behavior or not, is ...


Parameter Estimation And Inference Of Spatial Autoregressive Model By Stochastic Gradient Descent, Gan Luan Dec 2021

Parameter Estimation And Inference Of Spatial Autoregressive Model By Stochastic Gradient Descent, Gan Luan

Dissertations

Stochastic gradient descent (SGD) is a popular iterative method for model parameter estimation in large-scale data and online learning settings since it goes through the data in only one pass. While SGD has been well studied for independent data, its application to spatially-correlated data largely remains unexplored. This dissertation develops SGD-based parameter estimation and statistical inference algorithms for the spatial autoregressive (SAR) model, a common model for spatial lattice data.

This research contains three parts. (I) The first part concerns SGD estimation and inference for the SAR mean regression model. A new SGD algorithm based on maximum likelihood estimator (MLE ...


Experimental And Computational Studies Of Functionalized Carbon Nanotubes For Use In Energy Storage Devices And Membranes, Emine S. Karaman Dec 2021

Experimental And Computational Studies Of Functionalized Carbon Nanotubes For Use In Energy Storage Devices And Membranes, Emine S. Karaman

Dissertations

Electrolytes with good interfacial stability are a crucial component of any electrochemical device. The development of novel gel polymer electrolytes (GEs) with good interface stability and better manufacturability is important for the development of the next generation electrochemical devices. Gel electrolytes are hybrid electrolyte materials, combining benefits of both liquid and solid systems. Compared with liquid and solid electrolytes, GEs open new design opportunities and do not require rigorous encapsulation methods. In this dissertation, studies on functionalized carbon nanotubes (fCNTs) and graphene oxide (GO) doped polyvinyl alcohol (PVA) based gel electrolytes (GEs) are reported. The ionic conductivity and mechanical strength ...


On Performance Optimization And Prediction Of Parallel Computing Frameworks In Big Data Systems, Haifa Alquwaiee Dec 2021

On Performance Optimization And Prediction Of Parallel Computing Frameworks In Big Data Systems, Haifa Alquwaiee

Dissertations

A wide spectrum of big data applications in science, engineering, and industry generate large datasets, which must be managed and processed in a timely and reliable manner for knowledge discovery. These tasks are now commonly executed in big data computing systems exemplified by Hadoop based on parallel processing and distributed storage and management. For example, many companies and research institutions have developed and deployed big data systems on top of NoSQL databases such as HBase and MongoDB, and parallel computing frameworks such as MapReduce and Spark, to ensure timely data analyses and efficient result delivery for decision making and business ...


A Practical Approach To Automated Software Correctness Enhancement, Aleksandr Zakharchenko Dec 2021

A Practical Approach To Automated Software Correctness Enhancement, Aleksandr Zakharchenko

Dissertations

To repair an incorrect program does not mean to make it correct; it only means to make it more-correct, in some sense, than it is. In the absence of a concept of relative correctness, i.e. the property of a program to be more-correct than another with respect to a specification, the discipline of program repair has resorted to various approximations of absolute (traditional) correctness, with varying degrees of success. This shortcoming is concealed by the fact that most program repair tools are tested on basic cases, whence making them absolutely correct is not clearly distinguishable from making them relatively ...


Mechanisms And Applications Of Improved Protein Analysis By Desorption Electrospray Ionization Mass Spectrometry (Desi-Ms), Roshan Javanshad Dec 2021

Mechanisms And Applications Of Improved Protein Analysis By Desorption Electrospray Ionization Mass Spectrometry (Desi-Ms), Roshan Javanshad

Dissertations

Electrospray ionization mass spectrometry (ESI-MS) is a soft ionization technique that allows detection of macromolecules, such as intact proteins, by the formation of multiply charged ions from solutions. Desorption electrospray ionization mass spectrometry (DESI-MS) is an ambient ionization technique that directly samples analyte from a surface during ESI-MS analysis. Although DESI-MS is highly accomplished at the analyses of metabolites, lipids, and other small molecules, it is far more limited when it comes to protein analysis. While most of the field in ambient ionization MS has moved towards primarily applications, our approach has been to explore the use of DESI-MS and ...


Lxr Acts As A Differentiator In The Regulation Of Fas And G6pdh Gene Expression Under Insulin Resistant Conditions, Jaafar Hachem Dec 2021

Lxr Acts As A Differentiator In The Regulation Of Fas And G6pdh Gene Expression Under Insulin Resistant Conditions, Jaafar Hachem

Dissertations

Diabetes is a chronic disease that effects 10 percent of the world’s population and causes more than 1.5 million deaths a year and billions of dollars in associated health care cost. It can lead to very serious complications such as renal failure, liver cirrhosis, heart attack, and vision loss. The most common type of diabetes is type 2 diabetes. Type 2 diabetes arises when blood glucose levels remain chronically high due to insulin resistance. The reason for this elevation is due to the failure of insulin to allow tissues to uptake glucose causing problems in subsequent metabolic pathways ...


Development Of Sensor, Sensory System And Signal Processing Algorithm For Intelligent Sensing Applications, Xingzhe Zhang Nov 2021

Development Of Sensor, Sensory System And Signal Processing Algorithm For Intelligent Sensing Applications, Xingzhe Zhang

Dissertations

Sensors have been receiving significant attention in the last decade and the demand for sensory systems has increased in recent years due to the rapid growth in the field of artificial intelligence (AI). Sensors can improve people’s awareness by providing them with real-time information on the environment and their immediate health conditions. This dissertation presents the fulfilment of three main projects and focuses on the development of a sensor, a sensory system, and a sensor signal recognition system for AI applications by employing printed electronics, analog circuit design, and digital signal processing techniques.

In the first project, a multi-channel ...


Semi-Empirical Modeling Of Liquid Carbon's Containerless Solidification, Philip Chrostoski Oct 2021

Semi-Empirical Modeling Of Liquid Carbon's Containerless Solidification, Philip Chrostoski

Dissertations

Elemental carbon has important structural diversity, ranging from nanotubes through graphite to diamond. Previous studies of micron-size core/rim carbon spheres extracted from primitive meteorites suggest they formed around such stars via the solidification of condensed carbon-vapor droplets, followed by gas-to-solid carbon coating to form the graphite rims. Similar core/rim particles result from the slow cooling of carbon vapor in the lab. The long-range carbon bond-order potential was used to computationally study liquid-like carbon in (1.8 g/𝐜𝐦𝟑) periodic boundary (tiled-cube supercell) and containerless (isolated cluster) settings. Relaxations via conjugate-gradient and simulatedannealing nucleation and growth simulations using molecular ...


Soliton Based All-Optical Data Processing In Waveguides, Amaria Javed Oct 2021

Soliton Based All-Optical Data Processing In Waveguides, Amaria Javed

Dissertations

The growing demand for higher data processing speed and capacity motivates the replacement of the current electronic data processing by optical data processing in analogy with the successful replacement of electronic data communication by optical data communication. In a quest to achieve comprehensive optical data processing we aim at using solitons in waveguide arrays to perform all-optical data processing operations. Solitons are special nonlinear waves appreciated for their ability to conserve their shape and velocity before and after scattering. They are observed naturally in diverse fields of science, namely, nonlinear physics, mathematics, hydrodynamics, biophysics, and quantum field theory, etc. with ...


Soliton Based All-Optical Data Processing In Waveguides, Amaria Javed Oct 2021

Soliton Based All-Optical Data Processing In Waveguides, Amaria Javed

Dissertations

The growing demand for higher data processing speed and capacity motivates the replacement of the current electronic data processing with optical data processing in analogy with the successful replacement of electronic data communication by optical data communication. In a quest to achieve comprehensive optical data processing we aim at using solitons in waveguide arrays to perform all-optical data processing operations. Solitons are special nonlinear waves appreciated for their ability to conserve their shape and velocity before and after scattering. They are observed naturally in diverse fields of science, namely, nonlinear physics, mathematics, hydrodynamics, biophysics, and quantum field theory, etc. with ...


Estimation Of Odds Ratio In 2 X 2 Contingency Tables With Small Cell Counts, Guohao Zhu Oct 2021

Estimation Of Odds Ratio In 2 X 2 Contingency Tables With Small Cell Counts, Guohao Zhu

Dissertations

This study is focusing on properties of estimators of odds ratio or its logarithm in case of 2x2 tables with small counts. The odds ratio represents the odds that an outcome of interest will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure. Both parameters are often used to quantify the strength of association of two binary variables and are common measurements reported in case-control, cohort, and cross-sectional studies.

Because of their wide applicability, both parameters, odds ratio, and its logarithm, have been intensively studied in the literature. However, most ...


Critical Behavior In Evolutionary And Population Dynamics, Stephen Ordway Sep 2021

Critical Behavior In Evolutionary And Population Dynamics, Stephen Ordway

Dissertations

This study is an exploration of phase transition behavior in evolutionary and population dynamics, and techniques for predicting population changes, across the disciplines of physics, biology, and computer science. Under the looming threat of climate change, it is imperative to understand the dynamics of populations under environmental stress and to identify early warning signals of population decline. These issues are explored here in (1) a computational model of evolutionary dynamics, (2) an experimental system of decaying populations under environmental stress, and (3) a machine learning approach to predict population changes based on environmental factors. Through the lens of critical phase ...


Modeling And Design Optimization For Membrane Filters, Yixuan Sun Aug 2021

Modeling And Design Optimization For Membrane Filters, Yixuan Sun

Dissertations

Membrane filtration is widely used in many applications, ranging from industrial processes to everyday living activities. With growing interest from both industrial and academic sectors in understanding the various types of filtration processes in use, and in improving filter performance, the past few decades have seen significant research activity in this area. Experimental studies can be very valuable, but are expensive and time-consuming, therefore theoretical studies offer potential as a cost-effective and predictive way to improve on current filter designs. In this work, mathematical models, derived from first principles and simplified using asymptotic analysis, are proposed for: (1) pleated membrane ...


Data-Driven Learning For Robot Physical Intelligence, Leidi Zhao Aug 2021

Data-Driven Learning For Robot Physical Intelligence, Leidi Zhao

Dissertations

The physical intelligence, which emphasizes physical capabilities such as dexterous manipulation and dynamic mobility, is essential for robots to physically coexist with humans. Much research on robot physical intelligence has achieved success on hyper robot motor capabilities, but mostly through heavily case-specific engineering. Meanwhile, in terms of robot acquiring skills in a ubiquitous manner, robot learning from human demonstration (LfD) has achieved great progress, but still has limitations handling dynamic skills and compound actions. In this dissertation, a composite learning scheme which goes beyond LfD and integrates robot learning from human definition, demonstration, and evaluation is proposed. This method tackles ...


Shale Softening Based On Pore Network And Laboratory Investigations, Di Zhang Aug 2021

Shale Softening Based On Pore Network And Laboratory Investigations, Di Zhang

Dissertations

This dissertation consists of two major parts: Firstly, experimental investigation of four major shale softening mechanisms and quantifications of structural parameters. Secondly, numerical simulations of nano-scale flow behaviors using the previous experiments determined parameters based on modified pore network modeling.

Hydraulic fracturing is widely applied to economical gas production from shale reservoirs. Still, the gradual swelling of the clay micro/nano-pores due to retained fluid from hydraulic fracturing causes a gradual reduction of gas production. Four different gas-bearing shale samples are investigated to quantify the expected shale swelling due to hydraulic fracturing. These shale samples are subject to heated deionized ...


Colloidal Quantum Dot (Cqd) Based Mid-Wavelength Infrared Optoelectronics, Shihab Bin Hafiz Aug 2021

Colloidal Quantum Dot (Cqd) Based Mid-Wavelength Infrared Optoelectronics, Shihab Bin Hafiz

Dissertations

Colloidal quantum dot (CQD) photodetectors are a rapidly emerging technology with a potential to significantly impact today’s infrared sensing and imaging technologies. To date, CQD photodetector research is primarily focused on lead-chalcogenide semiconductor CQDs which have spectral response fundamentally limited by the bulk bandgap of the constituent material, confining their applications to near-infrared (NIR, 0.7-1.0 um) and short-wavelength infrared (SWIR, 1-2.5 um) spectral regions. The overall goal of this dissertation is to investigate a new generation of CQD materials and devices that advances the current CQD photodetector research toward the technologically important thermal infrared region of ...


Gradient Free Sign Activation Zero One Loss Neural Networks For Adversarially Robust Classification, Yunzhe Xue Aug 2021

Gradient Free Sign Activation Zero One Loss Neural Networks For Adversarially Robust Classification, Yunzhe Xue

Dissertations

The zero-one loss function is less sensitive to outliers than convex surrogate losses such as hinge and cross-entropy. However, as a non-convex function, it has a large number of local minima, andits undifferentiable attribute makes it impossible to use backpropagation, a method widely used in training current state-of-the-art neural networks. When zero-one loss is applied to deep neural networks, the entire training process becomes challenging. On the other hand, a massive non-unique solution probably also brings different decision boundaries when optimizing zero-one loss, making it possible to fight against transferable adversarial examples, which is a common weakness in deep learning ...


Exploring, Understanding, Then Designing: Twitter Users’ Sharing Behavior For Minor Safety Incidents, Mashael Yousef Almoqbel Aug 2021

Exploring, Understanding, Then Designing: Twitter Users’ Sharing Behavior For Minor Safety Incidents, Mashael Yousef Almoqbel

Dissertations

Social media has become an integral part of human lives. Social media users resort to these platforms for various reasons. Users of these platforms spend a lot of time creating, reading, and sharing content, therefore, providing a wealth of available information for everyone to use. The research community has taken advantage of this and produced many publications that allow us to better understand human behavior. An important subject that is sometimes discussed and shared on social media is public safety. In the past, Twitter users have used the platform to share incidents, share information about incidents, victims and perpetrators, and ...


Advances In Modeling Gas Adsorption In Porous Materials For The Characterization Applications, Max A. Maximov Aug 2021

Advances In Modeling Gas Adsorption In Porous Materials For The Characterization Applications, Max A. Maximov

Dissertations

The dissertation studies methods for mesoporous materials characterization using adsorption at various levels of scale and complexity. It starts with the topic introduction, necessary notations and definitions, recognized standards, and a literature review.

Synthesis of novel materials requires tailoring of the characterization methods and their thorough testing. The second chapter presents a nitrogen adsorption characterization study for silica colloidal crystals (synthetic opals). These materials have cage-like pores in the range of tens of nanometers. The adsorption model can be described within a macroscopic approach, based on the Derjaguin-Broekhoff-de Boer (DBdB) theory of capillary condensation. A kernel of theoretical isotherms is ...


Novel Statistical Modeling Methods For Traffic Video Analysis, Hang Shi Aug 2021

Novel Statistical Modeling Methods For Traffic Video Analysis, Hang Shi

Dissertations

Video analysis is an active and rapidly expanding research area in computer vision and artificial intelligence due to its broad applications in modern society. Many methods have been proposed to analyze the videos, but many challenging factors remain untackled. In this dissertation, four statistical modeling methods are proposed to address some challenging traffic video analysis problems under adverse illumination and weather conditions.

First, a new foreground detection method is presented to detect the foreground objects in videos. A novel Global Foreground Modeling (GFM) method, which estimates a global probability density function for the foreground and applies the Bayes decision rule ...