Physical Sciences and Mathematics Commons^™

Lsc Fabrication And Design: Bulk Polymerization And Ultrathin Architectures, Justin T. Doyle

WWU Graduate School Collection

Renewable energy technologies that access underutilized spaces in the built environment will need to be implemented, on a large scale, to curtail trending increases in global temperature. Luminescent Solar Concentrators (LSCs) are one such technology. They employ luminophores doped into polymer sandwiched in between glass plates, that redirect sunlight to the device periphery where photovoltaics are attached, producing power. Current devices do not have high enough efficiencies for commercialization. One of the biggest barriers is fluorophore aggregation which causes waveguide refractive index fluctuations which result in parasitic losses from the waveguide. In this work Copper Indium Disulfide/Zinc Sulfide (CIS/ZnS) quantum …

Spatially Variable Syn- And Post-Orogenic Exhumation Of The Appalachian Mountains From Apatite And Zircon (U-Th)/He Thermochronology, Luke Coughtry Basler

Honors Projects

We present zircon and apatite (U-Th)/He (ZHe, closure temperature = 150-200ºC; AHe, closure temperature = 45-80ºC) results from two study regions in the Appalachians Mountains to investigate the timing, rates, and spatial trends of exhumation during Alleghanian orogenesis, Atlantic rifting, and post-rift passive margin conditions. Within West Virginia and Virginia, 10 ZHe dates along an across-orogen transect display an eastward younging trend, from ~425 million years (Ma) in the western Appalachian Plateau province, to ~250-300 Ma in the central Valley-Ridge fold-thrust belt, and 163 ± 29 Ma in the eastern Piedmont. Inverse thermal modeling of ZHe data using external geologic …

Public Perception Of Different Planting Techniques Using Augmented Reality, Sultana Quader Tania

Electronic Theses and Dissertations

The objective of this study was to measure public perception of the different planting techniques (block and matrix), which are used at visitor information centers (VICs) and other rights of way (ROW) areas. The main factors that affect public perception of planting techniques were identified through an extensive literature review and qualitative survey from four welcome centers in the state of Georgia. The ranking of those indicators, based on public preferences, was discovered through a quantitative survey. During the first phase of the quantitative survey, images of block and matrix were used. An iOS-based user-friendly and cost-effective augmented reality (AR) …

Nonparametric Misclassification Simulation And Extrapolation Method And Its Application, Congjian Liu

Electronic Theses and Dissertations

The misclassification simulation extrapolation (MC-SIMEX) method proposed by Küchenho et al. is a general method of handling categorical data with measurement error. It consists of two steps, the simulation and extrapolation steps. In the simulation step, it simulates observations with varying degrees of measurement error. Then parameter estimators for varying degrees of measurement error are obtained based on these observations. In the extrapolation step, it uses a parametric extrapolation function to obtain the parameter estimators for data with no measurement error. However, as shown in many studies, the parameter estimators are still biased as a result of the parametric extrapolation …

Explicit Pseudo-Kähler Metrics On Flag Manifolds, Thomas A. Mason Iii

Electronic Theses and Dissertations

The coadjoint orbits of compact Lie groups each carry a canonical (positive definite) Kähler structure, famously used to realize the group's irreducible representations in holomorphic sections of certain line bundles (Borel-Weil theorem). Less well-known are the (indefinite) invariant pseudo-Kähler structures they also admit, which can be used to realize the same representations in higher cohomology of the sections (Bott), and whose analogues in a non-compact setting lead to new representations (Kostant-Langlands). The purpose of this thesis is to give an explicit description of these metrics in the case of the unitary group G=U_n.

Singlet Fission In A Hexacene Dimer: Energetics Dictate Dynamics, Samuel N. Sanders, Elango Kumarasamy, Kealan J. Fallon, Matthew Y. Sfeir, Luis M. Campos

Publications and Research

Singlet fission (SF) is an exciton multiplication process with the potential to raise the efficiency limit of single junction solar cells from 33% to up to 45%. Most chromophores generally undergo SF as solid-state crystals. However, when such molecules are covalently coupled, the dimers can be used as model systems to study fundamental photophysical dynamics where a singlet exciton splits into two triplet excitons within individual molecules. Here we report the synthesis and photophysical characterization of singlet fission of a hexacene dimer. Comparing the hexacene dimer to analogous tetracene and pentacene dimers reveals that excess exoergicity slows down singlet fission, …

Double Inclusive Small-X Gluon Production And Their Azimuthal Correlations In A Biased Ensemble, Gary Kapilevich

Publications and Research

We consider double gg → g production in the presence of a bias on the unintegrated gluon distribution of the colliding hadrons or nuclei. Such bias could be due to the selection of configurations with a greater number of gluons or higher mean transverse momentum squared or, more generally, due to a modified spectral shape of the gluon distribution in the hadrons. Hence, we consider reweighted functional averages over the stochastic ensemble of small-x gluons. We evaluate explicitly the double inclusive gluon transverse momentum spectrum in high-energy collisions, and their azimuthal correlations, for a few simple examples of biases.

Deriving Statistical Inference From The Application Of Artificial Neural Networks To Clinical Metabolomics Data, Kevin M. Mendez

Theses: Doctorates and Masters

Metabolomics data are complex with a high degree of multicollinearity. As such, multivariate linear projection methods, such as partial least squares discriminant analysis (PLS-DA) have become standard. Non-linear projections methods, typified by Artificial Neural Networks (ANNs) may be more appropriate to model potential nonlinear latent covariance; however, they are not widely used due to difficulty in deriving statistical inference, and thus biological interpretation. Herein, we illustrate the utility of ANNs for clinical metabolomics using publicly available data sets and develop an open framework for deriving and visualising statistical inference from ANNs equivalent to standard PLS-DA methods.

Web Content Management System And Accessibility Awareness: A Comparative Study Of Novice Users And Accessibility Outcomes, Fatima Artiba Diaz

Theses: Doctorates and Masters

Since its creation, the Web has progressively developed and become a vital source of information in every domain and for almost all people. It is crucial to guarantee that the information contained on the Web is available for everyone, especially for people with special needs. Removing accessibility barriers is fundamentally based on tools, skills and support of all contributors, particularly the content creators, to ensure information is navigable and usable in the context of the end users experience. Web Content Management Systems play a significant role in structuring, storing and provision content to the Web and have evolved to address …

An Investigation Into The Spatial Distribution, Habitat Selection And Resource Usage Of The Red Fox (Vulpes Vulpes) Inhabiting Urban Reserves Within Perth, Western Australia, Michael Thomas Main

Theses: Doctorates and Masters

I attempted to track a population of urban foxes in Kings Park, but due to collar failure, only one collar was retrieved. The GPS telemetry data from this fox produced home range estimates for minimum convex polygon (MCP) and kernel density (KD) of 0.302 km² and 0.331 km², respectively. The fox was predominantly active at night, with a ten-fold increase in movement during nocturnal periods when compared to daytime movements. Roads and man-made tracks were important for facilitating movement of the fox through its home range, with almost 97% of location fixes recorded within 100m of these features. The fox …

Local Binary Pattern Based Algorithms For The Discrimination And Detection Of Crops And Weeds With Similar Morphologies, Vi Nguyen Thanh Le

Theses: Doctorates and Masters

In cultivated agricultural fields, weeds are unwanted species that compete with the crop plants for nutrients, water, sunlight and soil, thus constraining their growth. Applying new real-time weed detection and spraying technologies to agriculture would enhance current farming practices, leading to higher crop yields and lower production costs. Various weed detection methods have been developed for Site-Specific Weed Management (SSWM) aimed at maximising the crop yield through efficient control of weeds. Blanket application of herbicide chemicals is currently the most popular weed eradication practice in weed management and weed invasion. However, the excessive use of herbicides has a detrimental impact …

Memory And Resource Leak Defects And Their Repairs In Java Projects, Mohammadreza Ghanavati, Diego Costa, Janos Seboek, David Lo, Artur Andrzejak

Research Collection School Of Computing and Information Systems

Despite huge software engineering efforts and programming language support, resource and memory leaks are still a troublesome issue, even in memory-managed languages such as Java. Understanding the properties of leak-inducing defects, how the leaks manifest, and how they are repaired is an essential prerequisite for designing better approaches for avoidance, diagnosis, and repair of leak-related bugs. We conduct a detailed empirical study on 452 issues from 10 large opensource Java projects. The study proposes taxonomies for the leak types, for the defects causing them, and for the repair actions. We investigate, under several aspects, the distributions within each taxonomy and …

Systematic Classification Of Attackers Via Bounded Model Checking, Eric Rothstein-Morris, Jun Sun, Sudipta Chattopadyay

Research Collection School Of Computing and Information Systems

In this work, we study the problem of verification of systems in the presence of attackers using bounded model checking. Given a system and a set of security requirements, we present a methodology to generate and classify attackers, mapping them to the set of requirements that they can break. A naive approach suffers from the same shortcomings of any large model checking problem, i.e., memory shortage and exponential time. To cope with these shortcomings, we describe two sound heuristics based on cone-of-influence reduction and on learning, which we demonstrate empirically by applying our methodology to a set of hardware benchmark …

Lightweight Sharable And Traceable Secure Mobile Health System, Yang Yang, Ximeng Liu, Robert H. Deng, Yingjiu Li

Research Collection School Of Computing and Information Systems

Mobile health (mHealth) has emerged as a new patient centric model which allows real-time collection of patient data via wearable sensors, aggregation and encryption of these data at mobile devices, and then uploading the encrypted data to the cloud for storage and access by healthcare staff and researchers. However, efficient and scalable sharing of encrypted data has been a very challenging problem. In this paper, we propose a Lightweight Sharable and Traceable (LiST) secure mobile health system in which patient data are encrypted end-to-end from a patient’s mobile device to data users. LiST enables efficient keyword search and finegrained access …

Experimenting With A Biologically Plausible Neural Network, Dmitri Murphy

University Honors Theses

We present research on an implementation of a biologically inspired Bayesian Confidence Propagation Neural Network (BCPNN). Based on previous work by Christopher Johansson and Anders Lansner, our implementation seeks to test and understand the various properties of this model. The floating-point implementation we built uses discrete time and bit-vectors as input/output. We found that the column based BCPNN model is able to memorize a decent number of input vectors and is able to restore noisy versions of these vectors with relatively high accuracy. We examine the model’s capacity, noise recovery ability and cross-column connection influence, among other attributes. The clearest …

Association Rules Patterns Discovery From Mixed Data, Welendawa Acharige Charith A. Elson

Electronic Theses and Dissertations

Finding Association Rules has been a popular unsupervised learning technique for dis covering interesting patterns in commercial data for well over two decades. The method seeks groups of data attributes and their values where their probability density of these attributesattherespectivevaluesismaximized. Therearecurrentlywell-establishedmeth ods for tackling this problem for data with categorical (discrete) attributes. However, for the cases of data with continuous variables, the techniques are largely focusing on cate gorizing continuous variables into intervals of interest and then relying on the categorical data methods to address the problem. We address the problem of finding association rules patterns in mixed data by …

Experiments On The Neural Network Approach To The Handwritten Digit Classification Problem, William Meissner

Electronic Theses and Dissertations

When the MNIST dataset was introduced in 1998, training a network was a multiple week problem in order to receive results far less accurate than an average CPU can produce within a couple of hours today. While this indicates that training a network on such a dataset is not the complicated problem it may have been twenty years ago, the MNIST dataset makes a good tool for study and testing with beginner and medium complexity neural networks. This paper follows along with the work presented in the online textbook “Neural Networks and Deep Learning” by Michael Nielson and an updated …

Intelligent Cinematic Camera Control For Real-Time Graphics Applications, Ian Harris Meeder

Master's Theses

E-sports is currently estimated to be a billion dollar industry which is only growing in size from year to year. However the cinematography of spectated games leaves much to be desired. In most cases, the spectator either gets to control their own freely-moving camera or they get to see the view that a specific player sees. This thesis presents a system for the generation of cinematically-pleasing views for spectating real-time graphics applications. A custom real-time engine has been built to demonstrate the effect of this system on several different game modes with varying visual cinematic constraints, such as the rule …

Twisted Space-Frequency And Space-Time Partially Coherent Beams, Milo W. Hyde Iv

Faculty Publications

We present partially coherent sources that are statistically twisted in the space-frequency and space-time domains. Beginning with the superposition rule for genuine partially coherent sources, we derive source plane expressions for the cross-spectral density (CSD) and mutual coherence functions (MCFs) for twisted space-frequency and space-time Gaussian Schell-model (GSM) beams. Using the Fresnel approximation to the free-space Green’s function, we then paraxially propagate the CSD and MCF to any plane z> 0. We discuss the beams’ behavior as they propagate, with particular emphasis on how the beam shape rotates or tumbles versus z. To validate our analysis, we simulate the generation …

K-Means Stock Clustering Analysis Based On Historical Price Movements And Financial Ratios, Shu Bin

CMC Senior Theses

The 2015 article Creating Diversified Portfolios Using Cluster Analysis proposes an algorithm that uses the Sharpe ratio and results from K-means clustering conducted on companies' historical financial ratios to generate stock market portfolios. This project seeks to evaluate the performance of the portfolio-building algorithm during the beginning period of the COVID-19 recession. S&P 500 companies' historical stock price movement and their historical return on assets and asset turnover ratios are used as dissimilarity metrics for K-means clustering. After clustering, stock with the highest Sharpe ratio from each cluster is picked to become a part of the portfolio. The economic and …

Understanding And Measuring Net Positive Business Strategies, Luke Ruffner Robinson

Graduate Student Theses, Dissertations, & Professional Papers

Despite their attempts to mitigate ecological impacts through sustainability initiatives, businesses are a major cause of the world's ecological problems. Some progressive businesses are attempting to move beyond “net zero” in terms of achieving neutral environmental impacts and instead are now pursuing a goal of net positive. Net positive refers to the idea that business activities could contribute value-added benefits to earth’s ecological systems, for example, by using technologies that sequester and store carbon. However, except for a handful of high-profile corporate case studies, little is known about how companies are developing their strategies to become net positive and …

Assessing Program Outcomes Of An M.Ed. Curriculum And Instruction Program: A Comparison Of Face-To-Face To Completely Online Deliverables, James A. Telese, Gregory Chamblee

Teaching and Learning Faculty Publications and Presentations

Many mathematics education degree programs, especially at the graduate level, are now transitioning to an online format. There is a need to document how mathematics content and content pedagogy are assessed in an online environment. The objectives of this chapter are to document how a public higher education institution in Texas transitioned their master's degree program for mathematics teachers from a face-to-face program to an online program and how this transition impacted the assessment process related to the learning of content and pedagogical content knowledge.

Virtual Reality Accessibility With Predictive Trails, Dani Paul Hove

Honors Projects

Comfortable locomotion in VR is an evolving problem. Given the high probability of vestibular-visual disconnect, and subsequent simulator sickness, new users face an uphill battle in adjusting to the technology. While natural locomotion offers the least chance of simulator sickness, the space, economic and accessibility barriers to it limit its effectiveness for a wider audience. Software-enabled locomotion circumvents much of these barriers, but has the greatest need for simulator sickness mitigation. This is especially true for standing VR experiences, where sex-biased differences in mitigation effectiveness are amplified (postural instability due to vection disproportionately affects women).

Predictive trails were developed as …

How Machine Learning And Probability Concepts Can Improve Nba Player Evaluation, Harrison Miller

CMC Senior Theses

In this paper I will be breaking down a scholarly article, written by Sameer K. Deshpande and Shane T. Jensen, that proposed a new method to evaluate NBA players. The NBA is the highest level professional basketball league in America and stands for the National Basketball Association. They proposed to build a model that would result in how NBA players impact their teams chances of winning a game, using machine learning and probability concepts. I preface that by diving into these concepts and their mathematical backgrounds. These concepts include building a linear model using ordinary least squares method, the bias …

Prioritizing Parcels For Conservation Easements Using Least-Cost Path Analyses Of Land Ownership: Case Study Within Theorized Grizzly Bear Migration Corridors Of Western Montana, Joseph H. Offer

Graduate Student Theses, Dissertations, & Professional Papers

As the world’s human population has grown and converted large natural habitats to human dominated landscapes, the planet’s biodiversity has decreased. To combat the loss of biodiversity from human development, many conservation professionals champion the concept of conservation corridors between intact habitats. Conservation corridors, made up of protected land, serve as a connection for wildlife populations to intermix genetics and, subsequently, help reduce the risk of extinction. The ideal geographic location of corridors is generally determined through geographic information system modeling using biophysical conditions and theorized animal movement. However, the resulting corridors are often expansive and protecting entire corridors is …

Modeling Twitter Sentiment As A Function Of Particulate Matter 2.5 For Communities Impacted By Wildfire Across Montana And Idaho, Matthew Kelly

Graduate Student Theses, Dissertations, & Professional Papers

Fine particulate matter (PM2.5) is a known pollutant with clinically detrimental physiological and behavioral effects. We consider Twitter sentiment as a potential indicator for well-being in communities impacted by wildfire-associated PM2.5 across Montana and Idaho spanning 5 years (2014-2018). From these geospatial air quality data and geo-tagged tweets, we trained county level models to examine the power of Twitter sentiment as a function of PM2.5. For all 24 counties sampled, we found between 1 and 8 affective dimensions where a positive �� 2 was detected with a significant F-statistic (�� < 0.05). Specifically, we show that sentiment for anticipation in the wildfire-prone county of Missoula, MT yielded respective training/test set �� 2 of 0.0958 and 0.0686 with a p-value for the F-statistic of 3.09E-07. These analyses support social media sentiment as a potential public health metric by showing one of the first observations of a relationship between PM2.5 and Twitter sentiment.

Discrete Geometry And Covering Problems, Alexander Hsu

CMC Senior Theses

This thesis explores several problems in discrete geometry, focusing on covering problems. We first go over some well known results, explaining Keith Ball's solution to the symmetric Tarski plank problem, as well as results of Alon and F\"uredi on covering all but vertices of a cube with hyperplanes. The former extensively utilizes techniques from matrix analysis, and the latter applies polynomial method. We state and explore the related problem, asking for the number of parallel hyperplanes required to cover a given discrete set of points in $\mathbb{Z}^{d}$ whose entries are bounded, and prove that there exist sets which are ``difficult'' …

Gravity-Drawing Flexible Silicone Filaments As Fiber Optics And Model Foldamers, Katherine Snell

CMC Senior Theses

Here, we present a method of gravity-drawing polydimethylsiloxane (PDMS) silicone fibers with application as fiber optics and as model foldamers. Beginning as a viscous liquid, PDMS is cured using heat until its measured viscosity reaches 4000 mPa•s. The semi-cured elastomer is then extruded through a tube furnace to produce thin (diameters on the order of hundred micrometers) filaments with scalable lengths. PDMS is biocompatible, gas-permeable, flexible, and hydrophobic. Additionally, the PDMS surface hydrophobicity can be modified via UV exposure, O2 plasma, and corona discharge. We demonstrate the patternibility (i.e patterns of hydrophobicity) of PDMS fibers, adding complexity to potential foldamer …

An Exploration Of 5g Wireless Network Attenuation Using Finite Element Analysis In Comsol Multiphysics, Matthew Johnson

CMC Senior Theses

5G, ultra-high frequency wireless networks face numerous hurdles due to significant signal attenuation in materials and large path loss. Empirical research on signal attenuation has been limited to low frequencies or very select high frequencies. This paper utilizes Finite Element Analysis in COMSOL Multiphysics to analyze signal attenuation in materials over a range of the frequency spectrum, from 100Mhz to 40Ghz, which is inclusive of 5G wireless frequencies. The focus of this paper is on glass and dry wood, as well as wet wood (representative of trees), as these materials are some of the most likely to stand in the …

Optimal Execution In Cryptocurrency Markets, Ethan Kurz

CMC Senior Theses

The purpose of this paper is to study the Almgren and Chriss model on the optimal execution of large block orders both on the NYSE and in cryptocurrency exchanges. Their model minimizes execution costs, which include linear temporary and permanent price impacts. We focus on how the stock market microstructure differs from a cryptocurrency exchange microstructure and what that means for how the model functions. Once the model and microstructures are explained, we examine how the Almgren-Chriss model functions with stocks from the NYSE, looking at specifically selling a large number of shares. We then investigate how a large "wholesale" …