Digital Commons Network^™

Towards Robust Artificial Intelligence Systems, Sunny Raj

Electronic Theses and Dissertations, 2020-2023

Adoption of deep neural networks (DNNs) into safety-critical and high-assurance systems has been hindered by the inability of DNNs to handle adversarial and out-of-distribution input. State-of-the-art DNNs misclassify adversarial input and give high confidence output for out-of-distribution input. We attempt to solve this problem by employing two approaches, first, by detecting adversarial input and, second, by developing a confidence metric that can indicate when a DNN system has reached its limits and is not performing to the desired specifications. The effectiveness of our method at detecting adversarial input is demonstrated against the popular DeepFool adversarial image generation method. On a …

The Susceptibility Of Deep Neural Networks To Natural Perturbations, Mesut Ozdag

Electronic Theses and Dissertations, 2020-2023

Deep learning systems have achieved great success in various types of applications in recent years. They are increasingly being adopted for safety-critical tasks such as face recognition, surveillance systems, speech recognition, and autonomous driving. On the other hand, it has been found that deep neural networks (DNNs) can easily be fooled by adversarial input samples. These imperceptible perturbations on images can lead any machine learning system to misclassify the objects with high confidence. Furthermore, they can be almost indistinguishable to a human observer. These systems can also be exposed to adverse weather conditions such as fog, rain, and snow. This …

Sorption Of U(Vi) Onto Manganese Oxides In The Presence Of Siderophore Desferrioxamine-B, Morgan Snyder

Electronic Theses and Dissertations, 2020-2023

Anthropogenic activities, such as uranium mining and the production of nuclear energy and nuclear weapons, have led to significant uranium contamination of the environment, leaving populations vulnerable to negative health effects. In order to effectively remediate uranium contamination, the mobility of uranium in the environment and its natural attenuation through sorption with active mineral phases, needs to be studied in depth first. This study aims to determine how U(VI) mobility is affected by manganese oxides in the presence and absence of siderophore Desferrioxamine-B (DFOB). Experiments focused on two common manganese minerals, pyrolusite (ß-MnO2) and manganite (γ-MnOOH). Adsorption experiments with U(VI)-DFOB …

Food, Familiarity, And Forecasting: Modeling Coups With Computational Methods, Joshua Lambert

Electronic Theses and Dissertations, 2020-2023

Military coups are the most consequential breakdown of civil-military relations. This dissertation contributes to the explanation and prediction of coups through three independent quantitative analyses. First, I argue that food insecurity is an important determinant of coups. The presence of hunger can generate discontent in society and subsequently alter coup plotter opportunities. Furthermore, I show that the presence of chronic hunger can condition the effect of increasing development. While increasing levels of development have been shown to limit coup proclivity, a state experiencing chronic hunger will recognize the fundamental failure of basic needs provision. As development increases, the presence of …

Communication Administration As A Tri-Voiced Sustainable Community, Ronald C. Arnett

Journal of the Association for Communication Administration

Books and authors have challenged the focus on “me” alone, rejecting “individualism” that seeks to stand above social context and constraints (Tocqueville, 1955; Arnett, 2019; Arnett, 2020), “narcissism” that falls in love with one’s own image (Lasch, 1985), and “emotivism” that limits decision making to personal preferences (MacIntyre, 1984). Contrary to a focus on an individual abstracted from a social context, one finds an emphasis on community (Arnett, 1986). When, however, a conception of community embraces only those empirically present, it becomes an abstraction oblivious of the phenomenological considerations of persons before and after the present moment. This essay textures …

Mentoring Faculty And Bolstering Students’ Emotional And Cognitive Interest: The Impact Of Perceived Homophily In The College Classroom, Robert J. Sidelinger, Leeanne M. Bell Mcmanus

Journal of the Association for Communication Administration

For this study, expectancy violations theory was used to explore the associations among instructors’ inappropriate conversations, perceived homophily (similarity), and college students’ emotional and cognitive interest. Results found that students’ perceptions of instructor perceived homophily moderated the relationships between students’ reports of instructors’ enactment of inappropriate conversations and students’ emotional and cognitive interest. These results offer further understanding of the ways in which inappropriate conversations and perceived homophily affect perceptual outcomes in the college classroom, which can inform college faculty, administrators, and mentors. Limitations and future research directions are discussed.

Teacher Trainees’ Reasoning About Teaching Mathematics To English Learners In An Era Of Core Content State Standards, Sultan Turkan, Megan Schramm-Possinger

Journal of English Learner Education

Research has indicated over the years that English learners (ELs) are not supported to achieve their goals in learning academic content and acquiring English. Despite a growing body of research on the essential teacher knowledge-base for teaching ELs and effective linguistically-responsive teacher education, there is still a dearth of research on candidate content teachers’ reasoning and instructional decision-making especially regarding teaching mathematics to ELs. This paper explored how a group of ten future mathematics teachers reasoned about a handful of scenarios illustrative of teaching mathematics to ELs. Qualitative analyses of the candidates’ discourse revealed that pre-service mathematics teachers’ perceptions of …

Building A Life Science Transfer Community: The Transfer-Student Research And Integration Program (Trip), Ken Teter, Ian Biazzo, Kimberly Schneider, Ken Fedorka

Florida Statewide Symposium: Best Practices in Undergraduate Research

The Transfer-student Research and Integration Program (TRIP) prepares life science students for placement in graduate school or the STEM workforce by supporting their professional development and integration into the UCF community. TRIP students also receive a team-based research experience and an opportunity to present at regional conferences. An $8,000 scholarship distributed over the course of the 2-year program reduces financial barriers and encourages students to spend more time on campus and in a research environment. This poster provides an overview of the challenges facing transfer students, the solutions offered by TRIP, and early outcomes from the first cohort of our …

Seminole State College Cure Research Program: From The Classroom To Collaboration, Maya Patrice Byfield Phd

Florida Statewide Symposium: Best Practices in Undergraduate Research

It is believed that if students are taught inductively in their first 2 years, it could induce many of them to seek research experiences later in their academic careers. To do this, we initiated an effort to promote engagement in research topics and faculty development. First, collaboration between one faculty member at SSC and a Principal Investigator at the Sanford-Burnham Institute was developed. This collaboration resulted in the creation of several internships at the Institute for students in the newly developed STEM research class. Second, to increase student engagement, the biology department developed a research focused colloquium series. Each fall …

Environmental And Economic Implications Of Energy Efficiency In New Residential Buildings: A Multi-Criteria Selection Approach, Florida Solar Energy Center, Delia D'Agostino

FSEC Energy Research Center®

The choice of the most appropriate technologies in buildings is often a challenge at the design stage, especially when many different criteria are taken into account. Consequently, the decision process relies often on one criterion only, such as costs or energy savings. We propose a multi-criteria approach based on multi-attribute utility theory to assess alternative energy efficiency measures, explicitly considering both environmental and economic criteria. We apply it to the design of a new residential building in Milan (Italy), with the aim to maximize CO₂ emission savings related to electricity and gas consumption, and to minimize embodied energy and …

Anticipating Widespread Augmented Reality: Insights From The 2018 Ar Visioning Workshop, Gregory F. Welch, Gerd Bruder, Peter Squire, Ryan Schubert

Faculty Scholarship and Creative Works

In August of 2018 a group of academic, government, and industry experts in the field of Augmented Reality gathered for four days to consider potential technological and societal issues and opportunities that could accompany a future where AR is pervasive in location and duration of use. This report is intended to summarize some of the most novel and potentially impactful insights and opportunities identified by the group.

Our target audience includes AR researchers, government leaders, and thought leaders in general. It is our intent to share some compelling technological and societal questions that we believe are unique to AR, and …

Prince & Knight, Natasha Vinson

Diverse Families Bookshelf Lesson Plans and Activities

No abstract provided.

Looking Back As An Adult On My Parents’ Advice, Nicole Wills

UCF Forum

I imagine I was like most kids growing up when it came to my parents’ advice: dismissive at best. As a typical angsty pre-teen, I was convinced that I was always right.

Engineering Noble-Metal Nanostructures For Biosensing Applications, Haihang Ye

Electronic Theses and Dissertations

The ability to engineer noble-metal nanostructures (NMNSs) in a controllable manner and to understand the structure-dependent properties greatly boost our knowledge in rational design of biosensing technologies. In particular, as a type of highly efficient peroxidase mimics, NMNSs hold promising potential to break through the bottleneck of conventional enzyme-based in vitro diagnostics. During the time of my Ph.D. study, I have successfully: 1) directed a two-step method involving seed-mediated growth and chemical etching for the synthesis of Ru nanoframes (RuNFs) with face-centered cubic crystal phase and enhanced catalytic activities; 2) demonstrated, for the first time, the inherent peroxidase-like activity of …

Leaning Robust Sequence Features Via Dynamic Temporal Pattern Discovery, Hao Hu

Electronic Theses and Dissertations

As a major type of data, time series possess invaluable latent knowledge for describing the real world and human society. In order to improve the ability of intelligent systems for understanding the world and people, it is critical to design sophisticated machine learning algorithms for extracting robust time series features from such latent knowledge. Motivated by the successful applications of deep learning in computer vision, more and more machine learning researchers put their attentions on the topic of applying deep learning techniques to time series data. However, directly employing current deep models in most time series domains could be problematic. …

Methodological Improvements In The Mrna Profiling Assays For Incorporation Into Dna Casework Workflows, Paris Volk

Electronic Theses and Dissertations

Currently, DNA profiling is the gold standard to identify an individual. However, determining body fluid origin is important in criminal investigations, offering additional information surrounding the circumstances of a crime. However, crime labs can only definitively identify blood and semen and presumptively saliva using techniques that consume time and sample and do not simultaneously identify all forensically relevant body fluids. This causes many crime labs to want to bypass body fluid identification altogether. Therefore, advances into more definitive molecular-based body fluid methods are necessary. One such technique is mRNA profiling because it provides a highly sensitive and specific approach to …

Analysis Of Hydrodynamic And Bathymetric Gradients In Canaveral National Seashore Following Living Shoreline And Oyster Restorations, David Spiering

Electronic Theses and Dissertations

Coastal vulnerability has been gaining recognition as a critical issue, especially with the increasing predictions of sea level rise. Susceptibility to extreme events, eutrophication, and shoreline modification has left many coastal regions in a degraded state. Shoreline protection has traditionally taken the form of seawalls and offshore breakwaters which can be detrimental to both the local ecosystems and adjoining shorelines. The objective of this thesis is to analyze the hydrodynamic and bathymetric variation that occurs within Mosquito Lagoon, Florida following living shoreline and oyster reef restorations. The shoreline sites were sampled using a Before-After-Control-Impact (BACI) design and data were analyzed …

Game-Theoretic Frameworks And Strategies For Defense Against Network Jamming And Collocation Attacks, Ahmed Hemida

Electronic Theses and Dissertations

Modern networks are becoming increasingly more complex, heterogeneous, and densely connected. While more diverse services are enabled to an ever-increasing number of users through ubiquitous networking and pervasive computing, several important challenges have emerged. For example, densely connected networks are prone to higher levels of interference, which makes them more vulnerable to jamming attacks. Also, the utilization of software-based protocols to perform routing, load balancing and power management functions in Software-Defined Networks gives rise to more vulnerabilities that could be exploited by malicious users and adversaries. Moreover, the increased reliance on cloud computing services due to a growing demand for …

Light Matter Interaction In Single Molecule Magnets, Rebecca Cebulka

Electronic Theses and Dissertations

This dissertation includes a series of experimental realizations which focus on studying the coupling between photons and single-molecule magnets (SMMs) in both the weak and strong coupling regimes. In the weak coupling regime, the aim is to achieve coherent control over the time evolution of the spin of SMMs while applying rapid microwave pulses at sub-Kelvin temperatures, where polarization of the spin bath may be achieved without large magnetic fields, allowing the suppression of dipolar dephasing. The continuing results of this experiment will be to provide a window into fundamental sources of decoherence in single-crystal SMMs in an energy range …

A Study Of Nonlinear Dynamics Of Eeg Responses To Simulated Unmanned Vehicle Tasks, Ziqing Xu

Electronic Theses and Dissertations

In the contemporary world, mental workload becomes higher as technology evolves and task demand becomes overwhelming. The operators of a system are usually required to complete tasks with higher complicity within a shorter period of time. Continuous operation under a high level of mental workload can be a major source of risk and human error, thus put the operator in a hazardous working environment. Therefore, it is necessary to monitor and assess mental workload. In this study, an unmanned vehicle operation with visual detection tasks was investigated by means of nonlinear analysis of EEG time series. Nonlinear analysis is considered …

Applications Of Deep Learning Models For Traffic Prediction Problems, Rezaur Rahman

Electronic Theses and Dissertations

Deep learning coupled with existing sensors based multiresolution traffic data and future connected technologies has immense potential to improve traffic operation and management. But to deal with complex transportation problems, we need efficient modeling frameworks for deep learning models. In this study, we propose two different modeling frameworks using Deep Long Short-Term Memory Neural Network (LSTM NN) model to predict future traffic state (speed and signal queue length). In our first problem, we present a modeling framework using deep LSTM NN model to predict traffic speeds in freeways during regular traffic condition as well as under extreme traffic demand, such …

Classifying And Predicting Walking Speed From Electroencephalography Data, Allen Rahrooh

Electronic Theses and Dissertations

Electroencephalography (EEG) non-invasively records electrocortical activity and can be used to understand how the brain functions to control movements and walking. Studies have shown that electrocortical dynamics are coupled with the gait cycle and change when walking at different speeds. Thus, EEG signals likely contain information regarding walking speed that could potentially be used to predict walking speed using just EEG signals recorded during walking. The purpose of this study was to determine whether walking speed could be predicted from EEG recorded as subjects walked on a treadmill with a range of speeds (0.5 m/s, 0.75 m/s, 1.0 m/s, 1.25 …

Student Community Detection And Recommendation Of Customized Paths To Reinforce Academic Success, Yuan Shao

Electronic Theses and Dissertations

Educational Data Mining (EDM) is a research area that analyzes educational data and extracts interesting and unique information to address education issues. EDM implements computational methods to explore data for the purpose of studying questions related to educational achievements. A common task in an educational environment is the grouping of students and the identification of communities that have common features. Then, these communities of students may be studied by a course developer to build a personalized learning system, promote effective group learning, provide adaptive contents, etc. The objective of this thesis is to find an approach to detect student communities …

Mediated Physicality: Inducing Illusory Physicality Of Virtual Humans Via Their Interactions With Physical Objects, Myungho Lee

Electronic Theses and Dissertations

The term virtual human (VH) generally refers to a human-like entity comprised of computer graphics and/or physical body. In the associated research literature, a VH can be further classified as an avatar - a human-controlled VH, or an agent - a computer-controlled VH. Because of the resemblance with humans, people naturally distinguish them from non-human objects, and often treat them in ways similar to real humans. Sometimes people develop a sense of co-presence or social presence with the VH - a phenomenon that is often exploited for training simulations where the VH assumes the role of a human. Prior research …

Decision-Making For Vehicle Path Planning, Jun Xu

Electronic Theses and Dissertations

This dissertation presents novel algorithms for vehicle path planning in scenarios where the environment changes. In these dynamic scenarios the path of the vehicle needs to adapt to changes in the real world. In these scenarios, higher performance paths can be achieved if we are able to predict the future state of the world, by learning the way it evolves from historical data. We are relying on recent advances in the field of deep learning and reinforcement learning to learn appropriate world models and path planning behaviors. There are many different practical applications that map to this model. In this …

Hearing The Voices Of The Deserters: Activist Critical Making In Electronic Literature, Laura Okkema

Electronic Theses and Dissertations

Critical making is an approach to scholarship which combines discursive methods with creative practices. The concept has recently gained traction in the digital humanities, where scholars are looking for ways of integrating making into their research in ways that are inclusive and empowering to marginalized populations. This dissertation explores how digital humanists can engage critical making as a form of activism in electronic literature, specifically in the interactive fiction platform Twine. The author analyzes the making process of her own activist Twine game The Deserters and embeds the project within digital humanities discourses on activism and social justice, hypertext, electronic …

Expanding And Shedding The Self: Processing Selfdom Through Painting, Theresa Lucey

Electronic Theses and Dissertations

The absurd perpetual struggle, although entirely without hope of resolution, is the key to life's meaning, or perhaps, meaninglessness. The artist must work to live and live to work and find their place in an absurd world. Find joy in the questioning act of art making, make no attempt to escape the meaninglessness through pacifism, and face the chaos with awareness. I employ self-portraiture as a means to dig deeply into my experience and response to living. Self-portraiture morphs along with my experiences and keeps a record of my thought patterns. My body of work is the harvest of my …

Framework For Modeling Attacker Capabilities With Deception, Sharif Hassan

Electronic Theses and Dissertations

In this research we built a custom experimental range using opensource emulated and custom pure honeypots designed to detect or capture attacker activity. The focus is to test the effectiveness of a deception in its ability to evade detection coupled with attacker skill levels. The range consists of three zones accessible via virtual private networking. The first zone houses varying configurations of opensource emulated honeypots, custom built pure honeypots, and real SSH servers. The second zone acts as a point of presence for attackers. The third zone is for administration and monitoring. Using the range, both a control and participant-based …

Miami-Dade Task Force: A Content Analysis Of How Coastal Communities View Sea Level Rise As A Threat, Francisco Alvaro

Electronic Theses and Dissertations

Sea level rise (SLR) has become a serious threat for coastal communities in recent years. Many communities, including South Florida, are already having the security of their daily lives impacted as climate change causes SLR and other environmental impacts to worsen. This study reviews the Miami-Dade Sea Level Rise Task Force Report to determine how this coastal county government views SLR as a threat. Using mixed content analysis to analyze the report qualitatively and quantitatively, the Task Force's recommendations are categorized based on their focus on security, infrastructure, economics, and the environment. One finds the concerns of the people to …

A Deep Learning Approach To Diagnosing Schizophrenia, Justin Barry

Electronic Theses and Dissertations

In this article, the investigators present a new method using a deep learning approach to diagnose schizophrenia. In the experiment presented, the investigators have used a secondary dataset provided by National Institutes of Health. The aforementioned experimentation involves analyzing this dataset for existence of schizophrenia using traditional machine learning approaches such as logistic regression, support vector machine, and random forest. This is followed by application of deep learning techniques using three hidden layers in the model. The results obtained indicate that deep learning provides state-of-the-art accuracy in diagnosing schizophrenia. Based on these observations, there is a possibility that deep learning …