Physical Sciences and Mathematics Commons^™

Overcoming Foreign Language Anxiety In An Emotionally Intelligent Tutoring System, Daneih Ismail

College of Computing and Digital Media Dissertations

Learning a foreign language entails cognitive and emotional obstacles. It involves complicated mental processes that affect learning and emotions. Positive emotions such as motivation, encouragement, and satisfaction increase learning achievement, while negative emotions like anxiety, frustration, and confusion may reduce performance. Foreign Language Anxiety (FLA) is a specific type of anxiety accompanying learning a foreign language. It is considered a main impediment that hinders learning, reduces achievements, and diminishes interest in learning.

Detecting FLA is the first step toward reducing and eventually overcoming it. Previously, researchers have been detecting FLA using physical measurements and self-reports. Using physical measures is direct …

Interposition Based Container Optimization For Data Intensive Applications, Rohan Tikmany

College of Computing and Digital Media Dissertations

Reproducibility of applications is paramount in several scenarios such as collaborative work and software testing. Containers provide an easy way of addressing reproducibility by packaging the application's software and data dependencies into one executable unit, which can be executed multiple times in different environments. With the increased use of containers in industry as well as academia, current research has examined the provisioning and storage cost of containers and has shown that container deployments often include unnecessary software packages. Current methods to optimize the container size prune unnecessary data at the granularity of files and thus make binary decisions. We show …

Attention Visual, Baris Dingil

College of Computing and Digital Media Dissertations

This research presents an innovative approach to improving visual-spatial attention using a research tool based on the web. Recognizing the significant role visual-spatial attention plays in everyday life and cognitive function for humans, this research was undertaken with the aim of developing a user-friendly, accessible web-based tool called Attention Visual (attentionvisual.com) to enhance this crucial cognitive skill. This tool also facilitates data collection, potentially accelerating the pace and enhancing the quality of related research. Both qualitative and quantitative methods were utilized for data collection and analysis. In order to stimulate improvements in visual-spatial attention, the tool’s algorithm was structured to …

Implementation And Assessment Of A Course-Based Undergraduate Research Experience (Cure) In General Chemistry, Alissa Potts

College of Science and Health Theses and Dissertations

Course-based undergraduate research experiences (CUREs) are growing in popularity in the chemistry community to replace traditional laboratory courses. This approach creates a research experience for a larger number of students than traditional research mentorship experiences offered at universities. CUREs can help students take ownership of projects, learn to design and troubleshoot experimental setups, problem-solve experiments that don’t have a “known answer”, and gain confidence in the laboratory. To assess the effectiveness of a general chemistry laboratory-based CURE course with DePaul students, the Experimental Design Ability Test (EDAT) and the Meaningful Learning in the Laboratory Instrument (MLLI) survey were given to …

Optical Variability Of Green Pea Galaxies, Julissa Marie Sarmiento

College of Science and Health Theses and Dissertations

In this thesis, I am investigating the optical variability of Green Pea galaxies (GPs). GPs are good analogs to high-redshift galaxies, enabling us to learn more about the first galaxies in the universe. One of their key properties is their strong emission lines, some of which indicate the presence of an active galactic nucleus (AGN). An effective way to identify AGN is to look for stochastic variability in the optical light from the galaxy. Finding AGN in these galaxies would help us learn more about the formation and evolution of the supermassive black holes that power AGN. In this thesis, …

Towards Generalizable Machine Learning Models For Computer-Aided Diagnosis In Medicine, Yiyang Wang

College of Computing and Digital Media Dissertations

Hidden stratification represents a phenomenon in which a training dataset contains unlabeled (hidden) subsets of cases that may affect machine learning model performance. Machine learning models that ignore the hidden stratification phenomenon--despite promising overall performance measured as accuracy and sensitivity--often fail at predicting the low prevalence cases, but those cases remain important. In the medical domain, patients with diseases are often less common than healthy patients, and a misdiagnosis of a patient with a disease can have significant clinical impacts. Therefore, to build a robust and trustworthy CAD system and a reliable treatment effect prediction model, we cannot only pursue …

Hacker, Influencer, Counter-Culture Spy: Cyberspace Actors’ Models Of Misinformation And Counter-Operations, Benjamin Kessell

College of Computing and Digital Media Dissertations

As misinformation continues to spread on social media, its residents have begun to fight back, independent of any platform. This organic resistance to the diffusion of misinformation is a clearly observable phenomenon with roots in Anonymous’ distributed campaigns from the 2010s outwards. Hacker and information security communities are acting in defense of some of their favorite spaces, most notably, Twitter. Security researchers of all stripes use it for sharing indicators of compromise but, as the diffusion of misinformation becomes more problematic it becomes more difficult to find signals in the noise.

These actors’ response to the issues at hand is …

Code Generation Based On Inference And Controlled Natural Language Input, Howard R. Dittmer

College of Computing and Digital Media Dissertations

Over time the level of abstraction embodied in programming languages has continued to grow. Paradoxically, most programming languages still require programmers to conform to the language's rigid constructs. These constructs have been implemented in the name of efficiency for the computer. However, the continual increase in computing power allows us to consider techniques not so limited. To this end, we have created CABERNET, a Controlled Natural Language (CNL) based approach to program creation. CABERNET allows programmers to use a simple outline-based syntax. This syntax enables increased programmer efficiency.

CNLs have previously been used to document requirements. We have taken this …

Predicting Code Refactoring Via Analyzing The History Of Quality Metrics And Code Anti-Patterns, Sarah Alanqari

College of Computing and Digital Media Dissertations

Code refactoring is the process of improving the internal structure of existing code without altering its functionality. Refactoring can help to reduce technical debt, enhance the quality of the code and make the code easy to evolve. However, the manual identification of the proper code refactoring operations to apply can be time-consuming and not scalable. In this thesis, we propose an approach based on data mining and machine learning techniques to analyze historical data and predict refactoring operations that may occur in a future release of a project. The approach uses a combination of techniques to identify patterns in the …

High Mass Star Formation And Methanol Masers, Nathanael Wilson

College of Science and Health Theses and Dissertations

Class I and Class II methanol (CH3OH) masers are believed to be good indicators for regions where high mass stars are being formed. High mass stars are important because they inuence the evolution of the Galaxy, but many details of their formation remain unknown. I present an investigation into the association of Class I and Class II CH3OH masers with high mass star formation in our Galaxy, in particular the evolutionary stages at which they occur. To do so, I have compared data on high mass star forming regions from the ATLASGAL survey with catalogs of Class I and Class …

Empirical Assessment Of Big Data Technology Adoption Factors For Organizations With Data Storage Systems, Ahmad B. Alnafoosi

College of Computing and Digital Media Dissertations

Many organizations have on-premises data storage systems. Data storage systems are evolving in multiple ways. One way is the adoption of Big Data. Big Data is a data storage system with the ability to analyze large volumes, velocity, and a variety of data. Per the Economist, data is now the most valuable resource (Parkins, 2017). Big Data holds the promise of unlocking a substantial value of data stored. Yet many organizations are not implementing Big Data. There is a need to identify key factors affecting adoption for such organizations. The literature review revealed multiple gaps in studied adoption factors (un-studied …

Analyzing Domain Of Convergence For Broyden’S Method, Michael Bonthron

College of Science and Health Theses and Dissertations

Broyden’s method is a quasi-Newton iterative method used to find roots of non-linear systems of equations. Research has shown and improved the rate of convergence for special cases and specific applications of the method. However, there is limited literature regarding the well-posedness of the method. In practice, a numerical method must reliably converge to the appropriate root. This paper will discuss the domain of attraction for the roots of a system found by using Broyden’s method. A method of approximating the radius of convergence of a root will be described which considers the largest disk centered at the root such …

"Examining Continent-Scale Variation In Aerial Arbuscular Mycorrhizal Fungi Communities Using Edna, Raechel Hearth

College of Science and Health Theses and Dissertations

Arbuscular mycorrhizal (AM) fungi form an important symbiosis with plants that make these fungi critical for plant health and ecosystem functioning. Although previous studies have shown that AM fungi disperse through the air, few studies have examined which environmental factors may be impacting their dispersal and aerial community composition, especially at large geographical scales. The goal of this study was to determine which environmental factors influenced air-dispersed AM fungal species composition across five different research sites in the Midwest and Western regions of the United States. By collecting dust at three different heights in the air, using modified Wilson and …

Text Summarization Towards Scientific Information Extraction, Abigail Keller

College of Computing and Digital Media Dissertations

Despite the exponential growth in scientific textual content, research publications are still the primary means for disseminating vital discoveries to experts within their respective fields. These texts are predominantly written for human consumption resulting in two primary challenges; experts cannot efficiently remain well-informed to leverage the latest discoveries, and applications that rely on valuable insights buried in these texts cannot effectively build upon published results. As a result, scientific progress stalls. Automatic Text Summarization (ATS) and Information Extraction (IE) are two essential fields that address this problem. While the two research topics are often studied independently, this work proposes to …

Synthesis And Styrene Copolymerization Of Octyl 2-Cyano-3-(R-Phenyl)-2-Propenoates, Martin S. Wasilewski

College of Science and Health Theses and Dissertations

Novel alkyl ring-substituted octyl phenylcyanoacrylates (OPCA), RPhCH=C(CN)CO₂CH₂(CH₂)₆CH₃, where R is H, 2-methyl, 3-methyl, 4-methyl, 4-ethyl, 4-propyl, 4-i-propyl, 4-butyl, 4-t-butyl, 4-i-butyl) were prepared and copolymerized with styrene. The ethylenes were synthesized by the piperidine catalyzed Knoevenagel condensation of ring-substituted benzaldehydes and octyl cyanoacetate, and characterized by CHN analysis, IR, ¹H and ¹³C NMR. All the ethylenes were copolymerized with styrene in solution with radical initiation (ABCN) at 70°C. The compositions of the copolymers were calculated from nitrogen analysis. Compositions of ST-OPCA copolymers ranged from 18.6 % to 27.4% of …

Data-Driven Damage Initiation Criteria For Carbon Fiber Reinforced Polymer Composites, Alexander Richard Post

College of Computing and Digital Media Dissertations

Computational progressive failure analysis (PFA) is vital for the design, verification, and validation of carbon fiber reinforced polymer (CFRP) composites. However, the computational cost of PFA is usually high due to the complexity of the model. The damage initiation criterion is one of the essential components of a PFA code to determine the transition of a material’s state from pristine or microscopically damaged to macroscopically damaged. In this thesis, data-driven models are developed to determine the matrix damage initiation based on the Mohr-Coulomb model and Hashin model. For 2D plane stress states, the computational cost for determining damage initiation can …

Facilitating Heuristic Evaluation For Novice Evaluators, Anas Abulfaraj

College of Computing and Digital Media Dissertations

Heuristic evaluation (HE) is one of the most widely used usability evaluation methods. The reason for its popularity is that it is a discount method, meaning that it does not require substantial time or resources, and it is simple, as evaluators can evaluate a system guided by a set of usability heuristics. Despite its simplicity, a major problem with HE is that there is a significant gap in the quality of results produced by expert and novice evaluators. This gap has made some scholars question the usefulness of the method as they claim that the evaluation results are a product …

Wavelet Packet Power Spectrum Of The Sdss Lyman-Alpha Forest: A Tool For Large-Scale Structure Detection, Jason Pero

College of Science and Health Theses and Dissertations

One of the goals of astrophysics is to obtain a full understanding how the Universe is organized on large scales and how structure evolved. In this thesis we develop a method of detecting structure on Mpc scales by measuring the one-dimensional power spectrum of the transmitted ux in the Lyman- forest. The method is based on the wavelet packet transform (WPT), which has several advantages over the Fourier transform. This includes reduced noise, resulting in less data manipulation and scrubbing in the early stages of analysis. Another advantage is localization of outliers in the data, which allows the general trend …

Anthraquinone Extraction And Quantification, Modification Of The Pictet-Spengler Reaction For The Creation Of Useful Isotopes And Use In Protein Ligation, Jermell Williams

College of Science and Health Theses and Dissertations

The Pictet-Spengler reaction rates of three species known to exhibit the alpha effect will be compared to the rate of the amine functional group. This is part of a larger effort to to generate a bifunctional tool for protein ligation by attaching an alkyne or azide group to the amine. With this, the aldehyde tag method can be used to modify proteins in biological conditions cheaply, specifically, and efficiently.

Electrochemical Studies Of Organic And Organometallic Compounds In The Pursuit Of Electrocatalytic Carbon Dioxide Reduction, Joshua J. Ludtke

College of Science and Health Theses and Dissertations

Carbon dioxide is the main contributor to the greenhouse effect in the world today; developing renewable energy sources and addressing anthropogenic CO₂ release into the atmosphere are two key ways of addressing its increasing impact. Electrocatalytic reduction to products like methanol or carbon monoxide is one useful path to address the rapid increase of carbon dioxide, and the fac-M(bpy-R)(CO)₃X family of complexes (M = Mn or Re; bpy-R = substituted 2,2’-bipyridine; X = Cl, Br, etc.) is one class of effective CO₂ reduction catalysts. Although the capability of the rhenium complex Re(PyBimH)(CO)₃Cl (PyBimH …

Long Term Variation Of Class I Methanol Masers, Nycole Wenner

College of Science and Health Theses and Dissertations

Class I methanol masers in high mass star forming regions are generally found in outflows. There, shocks provide the collisional pumping that causes the population inversion necessary for maser action. Less is known about Class I methanol masers compared to Class II. A better understanding of Class I masers will allow them to be used as more effective probes of high mass star formation, about which much remains to be learned. In particular, the variability of these masers could potentially be used to investigate activity in high mass star forming regions. I present an investigation of the long-term variability of …

Analyzing Nanoscale Thermal Transport Using Time-Resolved X-Ray Diffraction, James Grammich

College of Science and Health Theses and Dissertations

Classical models of thermal transport breakdown at lengthscales below a few microns in many materials, including the surfaces of bulk semiconductors. This presents difficulties in the analysis and design of small electronic devices, where unexpected thermal effects can occur such as hot spots that deteriorate performance and limit speed. Time-resolved x-ray diffraction has been proposed as one method to investigate this regime of nanoscale thermal transport, especially inside semiconductor materials where other techniques can not penetrate or yield quantitative results. Towards this goal, this thesis benchmarks a new, portable, and fast open-source x-ray dynamical diffraction code (TRXD) for strained crystals …

Threshold Concepts In Web Development: The Impact Of Education And Experience On The Perceptions Of Practitioners, Michael Lee Mick

College of Computing and Digital Media Dissertations

The Threshold Concepts (TCs) framework posits characteristics of critical concepts that enable a learner to see things in a new and unforgettable way that allows the incorporation of cognitive approaches and skills needed by professionals in the discipline. All previous research has been qualitatively oriented toward discovery of candidate TCs, without, so far, quantitative studies of the candidate TCs recognition within the professional ranks. An underrepresented group in previous research is that of Web development professionals.

This proposal describes initial quantitative research utilizing the TCs framework in the Web development area to measure the perception of candidate TCs by professionals …

Speckle Correlation Using A Deep Learning Algorithm On Newtonian Fluids, Sanskar Basnet

College of Science and Health Theses and Dissertations

In soft-matter physics, Dynamic Light Scattering (DLS) stands out as the non-invasive technique designed to measure the size and distribution of particles using speckle correlation. Traditional DLS analysis performs a one-to-one mapping of the size with diffusion which is computationally costly, in addition to lacks in generalisation to seek deeper relationships amongst speckle patterns. A recent advancement in double-pulse speckle imaging allows for the temporal-correlation problem presented by DLS to be transformed into an image classification problem. In this prototype study, I probe the feasibility and efficacy of DLS data analysis of speckle correlation using Deep Learning (DL). To reduce …

Examining Dimensions Of Patient Satisfaction With Telemedicine, Robert Garcia

College of Computing and Digital Media Dissertations

During the outbreak of the novel coronavirus (COVID-19) medical institutions and practitioners have drastically increased their adoption of telemedicine. The proliferation of telemedicine systems has sparked renewed interest among IS researchers in evaluating its usage. One of the main indicators used to measure the success of telemedicine services is patient satisfaction. Yet several problems exist with current methods used to evaluate telemedicine satisfaction. Patient satisfaction with telemedicine is frequently evaluated using either single question items or handmade instruments that are seldom assessed for validity. While telemedicine satisfaction is typically evaluated through single measures, satisfaction is considered a complex and multidimensional …

Federated Learning In Gaze Recognition (Fligr), Arun Gopal Govindaswamy

College of Computing and Digital Media Dissertations

The efficiency and generalizability of a deep learning model is based on the amount and diversity of training data. Although huge amounts of data are being collected, these data are not stored in centralized servers for further data processing. It is often infeasible to collect and share data in centralized servers due to various medical data regulations. This need for diversely distributed data and infeasible storage solutions calls for Federated Learning (FL). FL is a clever way of utilizing privately stored data in model building without the need for data sharing. The idea is to train several different models locally …

Quantitative Intersectional Data (Quinta): A #Metoo Case Study, Alicia E. Boyd

College of Computing and Digital Media Dissertations

This research began as an investigation of the #metoo movement, with the initial impetus to illuminate the voices located on the margins, those who often go unheard or are never recognized. This work aimed to understand the intersectional aspects of how these hashtag variations of the hashtag #metoo (i.e. #metoomosque, #churchtoo, #metoodisable, #metooqueer, #metoochina, etc) reveal the inequities of the #metoo movement on Twitter. The proliferation of these hashtag variations has often been ignored by scholars, and therefore absorbed into the larger #metoo movement conversation on Twitter. Therefore, the term `hashtag derivative' was created to describe the variation on the …

Designing An Interactive Theatre Game With Dynamic Asynchronous Play, Ardian Amiti

College of Computing and Digital Media Dissertations

This project proposes the use of asynchronous narrative mechanics and dynamic elements of gameplay to further the player’s sense of interaction with characters and the environment of the game, inspired by interactive theatre performances such as Sleep No More. The player plants seeds in a garden which is maintained by several Non-Playable Characters, influencing both the environment and the narrative. Scenes occur according to the state of the garden, but do not wait for the player to be present. Plants grow and wilt as time passes. Sometimes the player cedes control as the characters tend to or cut down plants, …

Bert Efficacy On Scientific And Medical Datasets: A Systematic Literature Review, Clayton Cohn

College of Computing and Digital Media Dissertations

Bidirectional Encoder Representations from Transformers (BERT) [Devlin et al., 2018] has been shown to be effective at modeling a multitude of datasets across a wide variety of Natural Language Processing (NLP) tasks; however, little research has been done regarding BERT’s effectiveness at modeling domain-specific datasets. Specifically, scientific and medical datasets present a particularly difficult challenge in NLP, as these types of corpora are often rife with technical jargon that is largely absent from the canonical corpora that BERT and other transfer learning models were originally trained on. This thesis is a Systematic Literature Review (SLR) of twenty-seven studies that were …

Ensemble Labeling Towards Scientific Information Extraction (Elsie), Erin Murphy

College of Computing and Digital Media Dissertations

Extracting scientific facts from unstructured text is difficult due to challenges specific to the ambiguity of the language, the complexity of the scientific named entities and relations to be extracted. This problem is well illustrated through the extraction of polymer names and their properties. Even in the cases where the property is a temperature, identifying the polymer name associated with the temperature may require expertise due to the use of acronyms, synonyms, complicated naming conventions and by the fact that new polymer names are being “introduced” to the vernacular as polymer science advances. While there exist domain-specific machine learning toolkits …