Physical Sciences and Mathematics Commons^™

Physics And Applications Of Space-Time Wave Packets, Murat Yessenov

Electronic Theses and Dissertations, 2020-2023

Space-time wave packets (STWP) constitute a broad class of pulsed optical fields that are rigidly transported in linear media without diffraction or dispersion, and are therefore propagation-invariant in absence of optical nonlinearities or waveguiding structures. Such wave packets exhibit unique characteristics, such as controllable group velocities in free space and exotic refractive phenomena. At the root of these behaviors is a fundamental feature underpinning STWP: their spectra are not separable with respect to the spatial and temporal degrees of freedom. Indeed, the spatio-temporal structure is endowed with angular dispersion, in which each spatial frequency is associated with a single prescribed …

Diffractive Liquid Crystal Optical Elements For Near-Eye Displays, Jianghao Xiong

Electronic Theses and Dissertations, 2020-2023

Liquid crystal planar optics (LCPO) with versatile functionalities is emerging as a promising candidate for overcoming various challenges in near-eye displays, like augmented reality (AR) and virtual reality (VR), while maintaining a small form factor. This type of novel optical element exhibits unique properties, such as high efficiency, large angular/spectral bandwidths, polarization selectivity, and dynamic modulation. The basic molecular configuration of these novel reflective LCPO is analyzed, based on the simulation of molecular dynamics. In contrast to previously assumed planar-twist structure, our analysis predicts a slanted helix structure, which agrees with the measured results. The optical simulation model is established …

Development Of Holographic Phase Masks For Wavefront Shaping, Nafiseh Mohammadian

Electronic Theses and Dissertations, 2020-2023

This dissertation explores a new method for creating holographic phase masks (HPMs), which are phase transforming optical elements holographically recorded in photosensitive glass. This novel hologram recording method allows for the fast production of HPMs of any complexity, as opposed to the traditional multistep process, which includes the design and fabrication of a master phase mask operating in the UV region before the holographic recording step. We holographically recorded transmissive HPMs that are physically robust (they are recorded in a silicate glass volume), can handle tens of kilowatts of continuous wave (CW) laser power, are un-erasable, user defined, require no …

Reticular Design And Synthesis Of Metal-Organic Frameworks With Targeted Emergent Properties, David Fairchild

Electronic Theses and Dissertations, 2020-2023

The research presented in this dissertation describes the design and synthesis of substitutional-solid-solution-based multivariate metal-organic frameworks (SSS-based MTV MOFs) with functionalized organic linkers to study their emergent properties in the crystalline solid state. The synthetic versatility and tunability of organic chemistry coupled with the predictable organization of inorganic structures enables MTV MOF systems to further the fundamental understanding of structure-composition-property relationships for the targeted design of applied materials due to their ability to control the structure, composition, and property independently. To begin, a set of terphenyl linkers with varied steric and electronic properties were crystallized as a family of UiO-type …

Control Of Coherence In Attosecond Atomic Ionization, Saad Mehmood

Electronic Theses and Dissertations, 2020-2023

The motion of electrons in atoms, molecules, and in condensed matter unfolds on a time scale from the attosecond (1 as = 10-18 s) to several femtoseconds (1 fs= 10-15 s). The advent of attosecond light pulses has opened the way to the time-resolved study of electronic motion and of ionization processes using pump-probe spectroscopy. In this thesis, we examine three aspects of the ionization dynamics in poly-electronic atoms: i) the coherence of the emerging charged fragments, ii) two-photon ionization pathways, and iii) the reconstruction of photoionization amplitudes from experimental observable. We focus on the role of autoionizing states and …

Applications For Machine Learning On Readily Available Data From Virtual Reality Training Experiences, Alec Moore

Electronic Theses and Dissertations, 2020-2023

The purpose of the research presented in this dissertation is to improve virtual reality (VR) training systems by enhancing their understanding of users. While the field of intelligent tutoring systems (ITS) has seen value in this approach, much research into making use of biometrics to improve user understanding and subsequently training, relies on specialized hardware. Through the presented research, I show that with machine learning (ML), the VR system itself can serve as that specialized hardware for VR training systems. I begin by discussing my explorations into using an ecologically valid, specialized training simulation as a testbed to predict knowledge …

Cholera Transmission Dynamic Model With Environmental Impacts Of Plankton Reservoirs, Sweety Sarker

Electronic Theses and Dissertations, 2020-2023

Cholera is an acute disease that is a global threat to the world and can kill people within a few hours if left untreated. In the last 200 years, seven pandemics occurred, and, in some countries, it remains endemic. The World Health Organization (WHO) declared a global initiative to prevent cholera by 2030. Cholera dynamics are contributed by several environmental factors such as salinity level of water, water temperature, presence of plankton especially zooplankton such as cladocerans, rotifers, copepods, etc. Vibrio cholerae (V. cholerae) bacterium is the main reason behind the cholera disease and the growth of V. cholerae depends …

Atmospheric Retrieval: Bayesian Methods, Machine Learning, And Application To Exoplanets, Michael Himes

Electronic Theses and Dissertations, 2020-2023

Atmospheric retrieval is the inverse modeling method where atmospheric properties are constrained based on measured spectra. Due to the low signal-to-noise ratios of exoplanet observations, exoplanetary retrieval codes pair a radiative transfer (RT) simulator with a Bayesian statistical framework in order to characterize the distribution of atmospheric parameters that could explain the observations (the posterior distribution). This requires on the order of 106 RT model evaluations, which requires hours to days of compute time depending on model complexity. In this work, I investigate atmospheric retrieval methods and apply them to observations of hot Jupiters. Chapter 2 presents a set of …

The Effects Of Antecedents And Mediating Factors On Cybersecurity Protection Behavior, Ling Li, Li Xu, Wu He

Information Technology & Decision Sciences Faculty Publications

This paper identifies opportunities for potential theoretical and practical improvements in employees' awareness of cybersecurity and their motivational behavior to protect themselves and their organizations from cyberattacks using the protection motivation theory. In addition, it contributes to the literature by examining additional variables and mediators besides the core constructs of the Protection Motivation Model (PMT). This article uses empirical data and structural equation modeling to test the antecedents and mediators of employees' cybersecurity motivational behavior. The study offers theoretical and pragmatic guidance for cybersecurity programs. First, the model developed in this study can partially explain how people may change their …

Climate Change And Cop26: Are Digital Technologies And Information Management Part Of The Problem Or The Solution? An Editorial Reflection And Call To Action, Yogesh K. Dwivedi, Laurie Hughes, Arpan Kumar Kar, Abdullah M. Baabdullah, Purva Grover, Roba Abbas, Daniela Andreini, Iyad Abumoghli, Yves Barlette, Deborah Bunker, Leona Chandra Kruse, Ioanna Constantiou, Robert M. Davison, Rahul De', Rameshwar Dubey, Henry Fenby-Taylor, Babita Gupta, Wu He, Mitsuru Kodama, Matti Mäntymäki, Bhimaraya Metri, Katina Michael, Johan Olaisen, Niki Panteli, Samuli Pekkola, Rohit Nishant, Ramakrishnan Raman, Nripendra P. Rana, Frantz Rowe, Suprateek Sarker, Brenda Scholtz, Maung Sein, Jeel Dharmeshkumar Shah, Thompson S.H. Teo, Manoj Kumar Tiwari, Morten Thanning Vendelø, Michael Wade

Information Technology & Decision Sciences Faculty Publications

The UN COP26 2021 conference on climate change offers the chance for world leaders to take action and make urgent and meaningful commitments to reducing emissions and limit global temperatures to 1.5 °C above pre-industrial levels by 2050. Whilst the political aspects and subsequent ramifications of these fundamental and critical decisions cannot be underestimated, there exists a technical perspective where digital and IS technology has a role to play in the monitoring of potential solutions, but also an integral element of climate change solutions. We explore these aspects in this editorial article, offering a comprehensive opinion based insight to a …

Polymer Derived Ceramic For Lithium-Ion Storage, And Electrospun Polyelectrolyte Fiber For Heavy Metal Ions Removal, Zeyang Zhang

Electronic Theses and Dissertations, 2020-2023

This dissertation includes two major projects. The first project investigated the great potential of polymer-derived ceramics (PDCs) as lithium-ion battery anode materials with good cycling stability and large capacity. SiCNO ceramic nanoparticles were produced by pyrolysis of polysilazane nanoparticles synthesized via an oil-in-oil emulsion crosslinking. The SiCNO nanoparticles had an average particle size of around 9 nm and contained graphitic carbon, Si3N4, and SiO2 domains. The electrochemical behavior of SiCNO nanoparticles anode was investigated to evaluate the Li-ion storage performance and understand its mechanism of Li-ion storage. The lithiation of SiCNO was observed at ~0.385 V versus Li/Li+. The anode …

Jparsec - A Parser Combinator For Javascript, Sida Zhong

Master's Projects

Parser combinators have been a popular parsing approach in recent years. Compared with traditional parsers, a parser combinator has both readability and maintenance advantages.

This project aims to construct a lightweight parser construct library for Javascript called Jparsec. Based on the modular nature of a parser combinator, the implementation uses higher-order functions. JavaScript provides a friendly and simple way to use higher-order functions, so the main construction method of this project will use JavaScript's lambda functions. In practical applications, a parser combinator is mainly used as a tool, such as parsing JSON files.

In order to verify the utility of …

Proxy Re-Encryption In Blockchain-Based Application, Wangcheng Yuan

Master's Projects

Nowadays, blockchain-based technology has risen to a new dimension. With the advantage of the decentralized identity, data are transferred through decentralized and public ledgers. Those new contracts provide great visibility. However, there is still a need to keep some data private in many cases. Those private data should be encrypted while still benefiting from the decentralized on-chain protocol. Securing those private data in such a decentralized blockchain-based system is thus a critical problem. Our solution provides a decentralized protocol that lets users grant access to their private data with proxy re-encryption in SpartanGold (a blockchain-based cryptocurrency). We implement a third-party …

Empirical Evaluation Of The Shift And Scale Parameters In Batch Normalization, Yashna Peerthum

Master's Projects

Batch Normalization (BatchNorm) is a technique that enables the training of deep neural networks, especially Convolutional Neural Networks (CNN) for computer vision tasks. It has been empirically demonstrated that BatchNorm increases per- formance, stability, and accuracy, although the reasons for these improvements are unclear. BatchNorm consists of a normalization step with trainable shift and scale parameters. In this paper, we examine the role of normalization and the shift and scale parameters in BatchNorm. We implement two new optimizers in PyTorch: a version of BatchNorm that we refer to as AffineLayer, which includes the shift and scale transform without normalization, and …

Predicting Externally Visible Traits From A Dna Sample For Law Enforcement Applications, Niraj Pandkar

Master's Projects

A large majority of crimes such as homicides, sexual assaults and missing person cases are not solved within a reasonable timeframe and become cold cases. The ability to predict visual appearance and ancestry from a DNA sample will provide an unprecedented advancement in such criminal investigations. DNA based prediction of craniofacial features, phenotypes and ancestry can be used to reduce the pool of candidates onto which to perform further investigations. To achieve the above goal, it is first essential to substantiate, model and measure the intrinsic relationship between the genomic markers and phenotypic features. The first step is to standardize …

Robustness Of Image-Based Malware Analysis, Katrina Tran

Master's Projects

Being able to identify malware is important in preventing attacks. Image-based malware analysis is the study of images that are created from malware. Analyzing these images can help identify patterns in malware families. In previous work, "gist descriptor" features extracted from images have been used in malware classification problems and have shown promising results. In this research, we determine whether gist descriptors are robust with respect to malware obfuscation techniques, as compared to Convolutional Neural Networks (CNN) trained directly on malware images. Using the Python Image Library, we create images from malware executables and from malware that we obfuscate. We …

Investigating Lattice-Based Cryptography, Michaela Molina

Master's Projects

Cryptography is important for data confidentiality, integrity, and authentication. Public key cryptosystems allow for the encryption and decryption of data using two different keys, one that is public and one that is private. This is beneficial because there is no need to securely distribute a secret key. However, the development of quantum computers implies that many public-key cryptosystems for which security depends on the hardness of solving math problems will no longer be secure. It is important to develop systems that have harder math problems which cannot be solved by a quantum computer.

In this project, two public-key cryptosystems which …

Developing And Validating A Standard Operating Procedure For Quantitative Analysis Using Central Washington University's X-Ray Diffractometer, Katherine Lucas

Undergraduate Honors Theses

X-ray diffraction (XRD) is widely applied in a variety of disciplines to identify crystalline solids in a powdered sample. Recent software advances have made quantitative analysis of samples easier and more accessible, but the quality of the result depends on the sample preparation and data collection procedure. This project focuses on testing methods of sample preparation and XRD data collection and analysis to lay the groundwork for refinement of the existing standard operating procedures at CWU. First, I determined the ball mill grinding time necessary to powder different mineral samples. The addition of hand grinding to ball mill-ground samples produced …

Software Engineering Approaches For Tinyml Based Iot Embedded Vision: A Systematic Literature Review, Shashank Bangalore Lakshman, Nasir U. Eisty

Computer Science Faculty Publications and Presentations

Internet of Things (IoT) has catapulted human ability to control our environments through ubiquitous sensing, communication, computation, and actuation. Over the past few years, IoT has joined forces with Machine Learning (ML) to embed deep intelligence at the far edge. TinyML (Tiny Machine Learning) has enabled the deployment of ML models for embedded vision on extremely lean edge hardware, bringing the power of IoT and ML together. However, TinyML powered embedded vision applications are still in a nascent stage, and they are just starting to scale to widespread real-world IoT deployment. To harness the true potential of IoT and ML, …

Putting The Fire Out: An Analytical Analysis Into The Bureau Of Land Management’S New Protest Petition Law, Lyndsey Antos

Kentucky Journal of Equine, Agriculture, & Natural Resources Law

No abstract provided.

Buffering Streams: Incentivizing Riparian Buffers In The Bluegrass, Harrison J.B. Chittenden

Kentucky Journal of Equine, Agriculture, & Natural Resources Law

No abstract provided.

Rethinking Reforestation: Sustainable And Economic Management Of Kentucky’S Forests, Braydan Roark

Kentucky Journal of Equine, Agriculture, & Natural Resources Law

No abstract provided.

Surficial Geologic Map Of The Flaherty 7.5-Minute Quadrangle, Kentucky, Ann Hislop, Matthew Massey, Maxwell L. Hammond Iii, Antonia E. Bottoms, Michele Mchugh, Emily Morris

Contract Reports--KGS

The Flaherty 7.5-minute quadrangle is located southwest of Louisville and northwest of Elizabethtown along the boundary between Hardin and Meade Counties. The quadrangle includes mostly the Pennyroyal region of the Mississippian Plateau and also smaller areas of the Mammoth Cave plateau and the highly dissected Dripping Springs escarpment in the western half of the map area (McDowell, 1986). Topography is mostly characterized by pervasive sinkhole development in a lower elevation and low-relief plain, and high-relief plateaus, ridges, and knobs of the Dripping Springs escarpment scattered along the west side of the quadrangle. Swadley (1963) mapped the bedrock geology of the …

Surficial Geologic Map Of The Millerstown 7.5-Minute Quadrangle, Kentucky, Matthew Massey, Maxwell L. Hammond Iii, Antonia Bottoms, Ann Hislop, Michele Mchugh, Emily Morris

Contract Reports--KGS

The Millerstown 7.5-minute quadrangle is located south of Louisville and southwest of Elizabethtown along the boundaries between Hardin, Grayson, and Hart Counties and within the Mississippian Plateau physiographic region (McDowell, 1986). Topography is characterized by the low relief Pennyroyal plain that sits at altitudes below about 650 ft above sea level, the low relief Mammoth Cave plateau at altitudes above about 650 ft, and steep slopes of and isolated knobs of the incised Dripping Springs escarpment that separates the two plains. Moore (1965) mapped the bedrock geology of the quadrangle, which was later digitized by Johnson (2006). Mississippian bedrock and …

Effects Of Vacancies And Electron Temperature On The Electron Phonon Coupling In Cubic Silicon Carbide And Their Connection To The Inelastic Thermal Spike, Salah Al-Smairat

Doctoral Dissertations

“The electron-phonon interaction is an important interaction in many solids as it influences transport phenomena and related quantities such as the electrical and thermal conductivities, especially in nuclear and space applications. The importance of the electron-phonon interaction in primary damage production in 3C-SiC is the subject of this research.

The electron-phonon coupling factor was calculated using a hybrid Density Functional Perturbation Theory - Classical Electron Gas model. The coupling factor was calculated as a function of electron temperature in pristine and defective 3C-SiC, and relaxed defective cells. The electron-phonon coupling is found to depend strongly on the electronic temperature and …

Representation Learning On Heterogeneous Spatiotemporal Networks, Dakshak Keerthi Chandra

Doctoral Dissertations

“The problem of learning latent representations of heterogeneous networks with spatial and temporal attributes has been gaining traction in recent years, given its myriad of real-world applications. Most systems with applications in the field of transportation, urban economics, medical information, online e-commerce, etc., handle big data that can be structured into Spatiotemporal Heterogeneous Networks (SHNs), thereby making efficient analysis of these networks extremely vital. In recent years, representation learning models have proven to be quite efficient in capturing effective lower-dimensional representations of data. But, capturing efficient representations of SHNs continues to pose a challenge for the following reasons: (i) Spatiotemporal …

Theoretical And Experimental Application Of Neural Networks In Spaceflight Control Systems, Pavel Galchenko

Doctoral Dissertations

“Spaceflight systems can enable advanced mission concepts that can help expand our understanding of the universe. To achieve the objectives of these missions, spaceflight systems typically leverage guidance and control systems to maintain some desired path and/or orientation of their scientific instrumentation. A deep understanding of the natural dynamics of the environment in which these spaceflight systems operate is required to design control systems capable of achieving the desired scientific objectives. However, mitigating strategies are critically important when these dynamics are unknown or poorly understood and/or modelled. This research introduces two neural network methodologies to control the translation and rotation …

Variational Data Assimilation For Two Interface Problems, Xuejian Li

Doctoral Dissertations

“Variational data assimilation (VDA) is a process that uses optimization techniques to determine an initial condition of a dynamical system such that its evolution best fits the observed data. In this dissertation, we develop and analyze the variational data assimilation method with finite element discretization for two interface problems, including the Parabolic Interface equation and the Stokes-Darcy equation with the Beavers-Joseph interface condition. By using Tikhonov regularization and formulating the VDA into an optimization problem, we establish the existence, uniqueness and stability of the optimal solution for each concerned case. Based on weak formulations of the Parabolic Interface equation and …

The Kanarra Fold-Thrust System -- The Leading Edge Of The Sevier Fold-Thrust Belt, Southwest Utah, William Joseph Michael Chandonia

Doctoral Dissertations

“The Jurassic to Eocene Sevier fold-thrust belt is the subject of continued scientific curiosity in tectonics, stratigraphy, and industry. Understanding its development in southwest Utah is hindered in part due to the multiple origins proposed for the Kanarra anticline, a major leading edge structure -- a drag fold along the Hurricane fault, Laramide monocline, Sevier fault propagation fold, or a combination of these -- which have confused its tectonic significance and regional context. This confusion results from the structural complexity of its exposed eastern limb, as well as displacement and burial of its crest and western limb beneath Neogene sediments …

Advances And Applications In High-Dimensional Heuristic Optimization, Samuel Alexander Vanfossan

Doctoral Dissertations

“Applicable to most real-world decision scenarios, multiobjective optimization is an area of multicriteria decision-making that seeks to simultaneously optimize two or more conflicting objectives. In contrast to single-objective scenarios, nontrivial multiobjective optimization problems are characterized by a set of Pareto optimal solutions wherein no solution unanimously optimizes all objectives. Evolutionary algorithms have emerged as a standard approach to determine a set of these Pareto optimal solutions, from which a decision-maker can select a vetted alternative. While easy to implement and having demonstrated great efficacy, these evolutionary approaches have been criticized for their runtime complexity when dealing with many alternatives or …