Physical Sciences and Mathematics Commons^™

A Critical Review Of Climate Change On Coastal Infrastructure Systems, Gregory J. Howland Jr.

Theses and Dissertations

This thesis is a response to climate threats identified by DoD report on Climate Change in 2019. A critical review of climate change literature related to coastal infrastructure was conducted to synthesize past research and to inform future research. This review intends to inform how climate change may impact infrastructure systems, how those impacts are evaluated, can the investigation be improved, and what can stakeholders learn from the outcomes. The end goal is to find climate change mitigation strategies and adaptation measures, or identify the easiest path to get to that end. The compiled information will inform civilian and military …

Climate Change Risk To Coastal Airfield Stormwater Systems, Jedidiah R. Langlois

Theses and Dissertations

Climate change is resulting in rising sea levels and increased rainfall, posing new challenges to stormwater management, particularly along coastlines. The airfield stormwater systems of Tyndall Air Force Base discharge directly into an interior bay of the Gulf of Mexico through tidal canals and ditches, creating a risk of system inundation from high tidewater conditions from sea-level rise (SLR). This study explores the performance and consequences of an inundated stormwater system from SLR during rainfall events using the EPA’s Stormwater Management Model (SWMM). One hundred and fifty-three combinations of SLR and return year storms were applied to a model of …

Natural Infrastructure Alternatives Mitigate Hurricane-Driven Flood Vulnerability: Application To Tyndall Air Force Base, Kiara L. Vance

Theses and Dissertations

Hurricane frequency and magnitude intensification are expected over the remainder of the twenty-first century. Uncertainty in future projections requires that coastal communities approach adaptation decisions with caution. Traditional approaches are costly and inflexible. Soft policy adaptations are largely unenforceable. Hard, natural adaptations have emerged as an opportunity to partially mitigate the growing risk of extreme flooding, without the large investments required for traditional approaches, where natural infrastructure already exists. Existing literature for natural adaptations has not leveraged intensification expectations for hurricane events. This research uses multihazard damage evaluation software and spatial analysis to investigate placement of dredged sediment as a …

Characterization Of Environmental Conditioning Of Lithium Hydride Using Spectroscopy And Machine Learning, Ryan E. Pinson

Theses and Dissertations

Lithium compounds such as lithium hydride (LiH) and anhydrous lithium hydroxide (LiOH) have various applications in industry but are highly reactive when exposed to moisture and CO₂. These reactions create new molecular forms, including compounds such as lithium oxide (Li₂O), lithium hydroxide monohydrate (LiOH ·H₂O), and lithium carbonate (Li₂CO₃). These new compounds degrade the effectiveness in applications using these compounds. The negative effects induced by new lithium compounds creates a need for the ability to characterize the in-growth of such compounds. To study these in-growths, this work will present environmental …

Formulation And Characterization Of Fast-Curing Plastic Scintillators With High-Z Loading, Theodore W. Stephens

Theses and Dissertations

Development of novel fast-curing plastic scintillators is highly advantageous due to their potential to be manufactured via 3D printing. Several formulations were developed that exhibit enhanced photon sensitivity, producing modest but discernible photopeaks at an incident gamma energy of 122 keV. The photon sensitivity is achieved via bismuth high-Z loading; however, this practice typically results in diminished light yields. Subsequent formulations, which varied the photoinitiator concentration and curing time, demonstrated successful curing with sufficient plastic hardness, reduced purple discoloration, reduced heat buildup during curing, and resulted in less cracking during the curing process, all of which were correlated with lower …

Burn Probability And Climate Change: A Quantitative Evaluation Of The Temporal Alterations Of Wildfire, David N. Robinson

Theses and Dissertations

The intensity of extreme weather events, specifically wildfires, along the West Coast has slowly grown overtime due to atmospheric changes caused by climate change. The Air Force, though aware of the threat that is wildfire, does not currently have a quantitative way to assess the hazard to base locations. In this paper, burn probability is quantitatively calculated through the geospatial analysis programs to provide a means of assessing wildfire vulnerability. The FlamMap fire simulator generated burn probabilities for Vandenberg Air Force Base using climate data generated by the remote automated weather station on the base to highlight how the burn …

Aligning Recovery Objectives With Organizational Capabilities, Jude C. Ejiobi

Masters Theses & Doctoral Dissertations

To reduce or eliminate the impact of a cyber-attack on an organization, preparations to recover a failed system and/or data are usually made in anticipation of such an attack. To avoid a false sense of security, these preparations should, as closely as possible, reflect the organization’s capabilities, in order to inform future improvement and avoid unattainable goals. There is an absence of a strong basis for the selection of the metrics that are used to measure preparation. Informal and unreliable processes are widely used, and they often result in metrics that conflict with the organization’s capabilities and interests. The goal …

Fully Differential Investigation Of Two-Center Interference In Dissociative Capture In P+ H2 Collisions, S. Bastola, M. Dhital, B. Lamichhane, A. Silvus, R. Lomsadze, J. Davis, A.(Ahmad) Hasan, A. Igarashi, Michael Schulz

Physics Faculty Research & Creative Works

We Have Measured and Calculated Fully Differential Cross Sections for Vibrational Dissociation Following Capture in 75-KeV P+H2 Collisions. for a Molecular Orientation Perpendicular to the Projectile Beam Axis and Parallel to the Transverse Momentum Transfer We Observe a Pronounced Interference Structure. the Positions of the Interference Extrema Suggest that the Interference Term is Afflicted with a Phase Shift Which Depends on the Projectile Scattering Angle. However, No Significant Dependence on the Kinetic-Energy Release Was Observed. Considerable Discrepancies between Our Calculations and Experimental Data Were Found.

Understanding Cybercrime Offending And Victimization Patterns From A Global Perspective, Jin R. Lee

International Journal of Cybersecurity Intelligence & Cybercrime

Cybercrime research within criminology and criminal justice sciences has increased over the past few decades, improving the knowledge and evidence-base around cybercrime offending and victimization generally. While earlier cybercrime studies were based primarily in the United States, there has been a recent surge in studies using international samples and multidisciplinary approaches to understand cybercrime patterns. The current issue of the International Journal of Cybersecurity Intelligence and Cybercrime consists of four articles that seek to advance our understanding of cybercrime behaviors from a global perspective. To that end, the objective of this paper is to provide a brief overview of the …

Cybersecurity Risk In U.S. Critical Infrastructure: An Analysis Of Publicly Available U.S. Government Alerts And Advisories, Zachary Lanz

International Journal of Cybersecurity Intelligence & Cybercrime

As threat actor operations become increasingly sophisticated and emphasize the targeting of critical infrastructure and services, the need for cybersecurity information sharing will continue to grow. Escalating demand for cyber threat intelligence and information sharing across the cybersecurity community has resulted in the need to better understand the information produced by reputable sources such as U.S. CISA Alerts and ICS-CERT advisories. The text analysis program, Profiler Plus, is used to extract information from 1,574 U.S. government alerts and advisories to develop visualizations and generate enhanced insights into different cyber threat actor types, the tactics which can be used for cyber …

An Algorithm For Identifying Eigenvectors Exhibiting Strong Spatial Localization, Jeffrey S. Ovall, Robyn Reid

Mathematics and Statistics Faculty Publications and Presentations

We introduce an approach for exploring eigenvector localization phenomena for a class of (unbounded) selfadjoint operators. More specifically, given a target region and a tolerance, the algorithm identifies candidate eigenpairs for which the eigenvector is expected to be localized in the target region to within that tolerance. Theoretical results, together with detailed numerical illustrations of them, are provided that support our algorithm. A partial realization of the algorithm is described and tested, providing a proof of concept for the approach.

Contrasting Styles Of Inter-Caldera Volcanism In A Peralkaline System: Case Studies From Pantelleria (Sicily Channel, Italy), Pierangelo Romano, John C. White, Silvio G. Rotolo, Nina J. Jordan, Rosolino Cirrincione, Giovanni De Giorgio, Patrizia Fiannacca, Epifanio Vaccaro

EKU Faculty and Staff Scholarship

The recent (<190 ka) volcanic history of Pantelleria is characterized by the eruption of nine peralkaline ignimbrites, ranging in composition from comenditic trachyte to comendite to pantellerite. The ~46 ka Green Tuff (GT) was the last of these ignimbrites, which was followed by many effusive and explosive low-volume eruptions of pantellerite from vents within the caldera moat and along the caldera rim. Although recent studies have shed additional light on the age, petrochemistry, and volcanology of the older ignimbrites, there is very little knowledge of magmatism that occurred between these older ignimbrites, primarily due to the very scarce exposures. In this paper, we present new field descriptions and geochemical data for three local peralkaline centers never studied before, two pre-GT and one post-GT, which share a similar setting with respect to the caldera scarps but differ in terms of their age, composition, and eruptive style. These centers include: (i) the older (~125 ka) Giache center (comenditic trachyte), (ii) the ~67 ka Attalora center (comendite, pantellerite), and (iii) the younger (~14 ka) Patite center (pantellerite).

Ecological Monitoring Program At Vims Esl: Annual Report 2021, Paige G. Ross, Richard A. Snyder

Reports

An Ecological Monitoring Program (EMP) has been established at the Virginia Institute of Marine Science Eastern Shore Laboratory (VIMS ESL) for the coastal environment near the Wachapreague lab. The goals of the initiative are to 1) provide status and trends information to scientists who study and regulators who manage Virginia’s marine resources, 2) provide a scientific context for short-term research and grant proposals 3) provide pedagogical enrichment for educators to use in their classes, and 4) build capacity in staff expertise and training of interns and students at VIMS ESL.

The program formalizes and standardizes data collection for a long-term …

4,6-O-Phenylethylidene Acetal Protected D-Glucosamine Carbamate-Based Gelators And Their Applications For Multi-Component Gels, Pooja Sharma, Guijun Wang

Chemistry & Biochemistry Faculty Publications

The self-assembly of carbohydrate-based low molecular weight gelators has led to useful advanced soft materials. The interactions of the gelators with various cations and anions are important in creating novel molecular architectures and expanding the scope of the small molecular gelators. In this study, a series of thirteen new C-2 carbamates of the 4,6-O-phenylethylidene acetalprotected D-glucosamine derivatives has been synthesized and characterized. These compounds are rationally designed from a common sugar template. All carbamates synthesized were found to be efficient gelators and three compounds are also hydrogelators. The resulting gels were characterized using optical microscopy, atomic force microscopy, …

Comparative Evaluation Of Physicochemical And Fermentative Responses Of Three Sorghum Varieties From Dryland And Irrigated Land And The Properties Of Proteins From Distillers’ Grains, Jikai Zhao, Thomas Weiss, Zhenjiao Du, Shan Hong, Scott R. Bean, Yonghui Li, Donghai Wang

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

Three sorghum varieties [waxy sorghum (WS), high protein sorghum (HPS), and normal sorghum (NS)] grown under dryland and irrigated conditions were evaluated with respect to the physicochemical and fermentative properties. The proteins were extracted from wet distillers' grains with solubles (WDGS) and characterized in terms of purity and in vitro digestibility. Starch, crude protein, crude fat, and fiber contents of the sorghums ranged from 64.16 to 68.05 g/100 g, 11.49–13.54 g/100 g, 2.45–2.98 g/100 g, and 1.62–1.80 g/100 g, respectively. For the same variety, the sorghums grown under dryland conditions had higher protein (0.33–0.91 g/100 g) and lower …

Directionally Sensitive Gamma Imaging Using Rotating Scatter Masks And Inexpensive, Scintillation Detectors, Christopher S. Charles

Theses and Dissertations

This work demonstrates the first instantiation of the FitzGerald Rotating Scatter Mask (RSM) as a proof-of-concept for two-dimensional source direction determination using a single, inexpensive, non-cooled scintillator, as well as an alternate mask design for comparison. A large RSM was additively manufactured from low-Z, acrylic like material, and rotated around the ubiquitous standard 3" x 3" NaI(Tl) or NaI(Tl)/CsI(Tl) phoswich detector, set internally to the mask. Smaller versions of the FitzGerald and alternate RSM designs were 3D printed for testing and used in conjunction with a LaBr detector to characterize the RSM system with a size and weight reduction applied. …

Monocular Pose Estimation For Automated Aerial Refueling Via Perspective-N-Point, James C. Lynch

Theses and Dissertations

Any Automated Aerial Refueling (AAR) solution requires the quick and precise estimation of the relative position and rotation of the two aircraft involved. This is currently accomplished using stereo vision techniques augmented by Iterative Closest Point (ICP), but requires post-processing to account for environmental factors such as boom occlusion. This paper proposes a monocular solution, combining a custom-trained single-shot object detection Convolutional Neural Network (CNN) and Perspective-n-Point (PnP) estimation to calculate a pose estimate with a single image. This solution is capable of pose estimation at contact point (22m) within 7cm of error and a rate of 10Hz, regardless of …

Memory Capacity In A System Of Swelling Particles, David T. Keating

Physics

A system has the ability to store memory if one is able to write, retrieve, and erase information from it. Some systems are capable of storing multiple transient memories; with no noise in these systems, at long time, the memories degrade until one or two remain. The addition of noise to these systems can extend the retention of multiple memories, in some cases indefinitely [2, 3]. While this behavior was first observed in simulations of charge density waves, it has since appeared in other systems [1].

Past research has shown that sheared non-Brownian liquid suspensions of particles exhibit similar behavior …

Physical Significance Of Noether Symmetries, Asghar Qadir, Ugur Camci

Arts & Sciences Faculty Publications

In this paper, we will trace the development of the use of symmetry in discussing the theory of motion initiated by Emmy Noether in 1918. Though it started with its use in classical mechanics, and has been heavily used in engineering applications of mechanics, it came into its own in relativity, and quantum theory and their applications in particle physics and field theory. It will be beyond the scope of this article to explain the quantum field theory applications in any detail, but the base for understanding it will be provided here. We will also go on to discuss an …

Adaptive Output Tracking Of Distributed Parameter Systems, İhsan Berk Altiner, Mustafa Doğan, Janset Daşdemi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we consider the unknown trajectory tracking problem for stable distributed parameter systems. The main assumptions are that trajectory signals are generated by an unknown finite-dimensional exosystem that is a marginally stable system and the tracking error is available for measurement. In order to achieve perfect error regulation, a frequency estimator scheme is proposed to estimate unknown exosystem parameters, and the control law that is designed based on geometric output regulation theory is revisited. The success of the proposed method is demonstrated on a parabolic heat equation and a first-order hyperbolic partial differential equation.

Robust Position/Force Control Of Nonholonomic Mobile Manipulator Forconstrained Motion On Surface In Task Space, Güli̇n Eli̇bol Seçi̇l, Serhat Obuz, Osman Parlaktuna

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, a robust controller is developed for a mobile manipulator (MM) to track reference position/force trajectories. Nonholonomic and holonomic constraints are considered for the mobile platform and manipulator, respectively. Additionally, the control design considers the uncertainties in parameters of the dynamics of the mobile manipulator with a bounded time varying additive disturbance (unmodelled effects, external disturbances). A Lyapunov-based stability analysis is used to prove semiglobal uniform ultimate boundedness of the tracking error signals and the position/force of the system track to an arbitrarily small neighborhood of the reference trajectories. Numerical results for a mobile manipulator, which is formed …

Clustering With Density Based Initialization And Bhattacharyya Based Merging, Erdem Köse, Ali̇ Köksal Hocaoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Centroid based clustering approaches, such as k-means, are relatively fast but inaccurate for arbitrary shape clusters. Fuzzy c-means with Mahalanobis distance can accurately identify clusters if data set can be modelled by a mixture of Gaussian distributions. However, they require number of clusters apriori and a bad initialization can cause poor results. Density based clustering methods, such as DBSCAN, overcome these disadvantages. However, they may perform poorly when the dataset is imbalanced. This paper proposes a clustering method, named clustering with density initialization and Bhattacharyya based merging based on the fuzzy clustering. The initialization is carried out by density estimation …

A New Classification Method Using Soft Decision-Making Based On An Aggregation Operator Of Fuzzy Parameterized Fuzzy Soft Matrices, Samet Memi̇ş, Serdar Engi̇noğlu, Uğur Erkan

Turkish Journal of Electrical Engineering and Computer Sciences

Recently, a precise and stable machine learning algorithm, i.e. eigenvalue classification method (EigenClass), has been developed by using the concept of generalised eigenvalues in contrast to common approaches, such as k-nearest neighbours, support vector machines, and decision trees. In this paper, we offer a new classification algorithm called fuzzy parameterized fuzzy soft aggregation classifier (FPFS-AC) to combine the modelling ability of soft decision-making (SDM) and classification success of generalised eigenvalues. FPFS-AC constructs a decision matrix by employing the similarity measures of fuzzy parameterized fuzzy soft matrices fpfs -matrices) and a generalised eigenvalue-based similarity measure. Then, it applies an SDM method …

Biometric Identification Using Panoramic Dental Radiographic Images Withfew-Shot Learning, Musa Ataş, Cüneyt Özdemi̇r, İsa Ataş, Burak Ak, Esma Özeroğlu

Turkish Journal of Electrical Engineering and Computer Sciences

Determining identity is a crucial task especially in the cases of mass disasters such as tsunamis, earthquakes, fires, epidemics, and in forensics. Although there are various studies in the literature on biometric identification from radiographic dental images, more research is still required. In this study, a panoramic dental radiographic (PDR) imagebased human identification system was developed using a customized deep convolutional neural network model in a few-shot learning scheme. The proposed model (PDR-net) was trained on 600 PDR images obtained from a total of 300 patients. As the PDR images of the patients were very different in terms of pose …

Directional Pairwise Class Confusion Bias And Its Mitigation, Sudhashree Sayenju, Ramazan Aygun Phd, Jonathan Boardman, Duleep Prasanna Rathgamage Don, Yifan Zhang Phd, Bill Franks, Sereres Johnston Phd, George Lee, Dan Sullivan, Girish Modgil Phd

Published and Grey Literature from PhD Candidates

Recent advances in Natural Language Processing have led to powerful and sophisticated models like BERT (Bidirectional Encoder Representations from Transformers) that have bias. These models are mostly trained on text corpora that deviate in important ways from the text encountered by a chatbot in a problem-specific context. While a lot of research in the past has focused on measuring and mitigating bias with respect to protected attributes (stereotyping like gender, race, ethnicity, etc.), there is lack of research in model bias with respect to classification labels. We investigate whether a classification model hugely favors one class with respect to another. …

Removing The Veil: Shining Light On The Lack Of Inclusivity In Cybersecurity Education For Students With Disabilities, Felicia Hellems, Sajal Bhatia

School of Computer Science & Engineering Faculty Publications

There are currently over one billion people living with some form of disability worldwide. The continuous increase in new technologies in today's society comes with an increased risk in security. A fundamental knowledge of cybersecurity should be a basic right available to all users of technology. A review of literature in the fields of cybersecurity, STEM, and computer science (CS) has revealed existent gaps regarding educational methods for teaching cybersecurity to students with disabilities (SWD's). To date, SWD's are largely left without equitable access to cybersecurity education. Our goal is to identify current educational methods being used to teach SWD's …

Strangan: Adversarially-Learnt Spatial Transformer For Scalable Human Activity Recognition, Abu Zaher Md Faridee, Avijoy Chakma, Archan Misra, Nirmalya Roy

Research Collection School Of Computing and Information Systems

We tackle the problem of domain adaptation for inertial sensing-based human activity recognition (HAR) applications -i.e., in developing mechanisms that allow a classifier trained on sensor samples collected under a certain narrow context to continue to achieve high activity recognition accuracy even when applied to other contexts. This is a problem of high practical importance as the current requirement of labeled training data for adapting such classifiers to every new individual, device, or on-body location is a major roadblock to community-scale adoption of HAR-based applications. We particularly investigate the possibility of ensuring robust classifier operation, without requiring any new labeled …

Viral Pneumonia Screening On Chest X-Rays Using Confidence-Aware Anomaly Detection, Jianpeng Zhang, Yutong Xie, Guansong Pang, Zhibin Liao, Johan Verjans, Wenxing Li, Zongji Sun, Jian He, Yi Li, Chunhua Shen, Yong Xia

Research Collection School Of Computing and Information Systems

Clusters of viral pneumonia occurrences over a short period may be a harbinger of an outbreak or pandemic. Rapid and accurate detection of viral pneumonia using chest X-rays can be of significant value for large-scale screening and epidemic prevention, particularly when other more sophisticated imaging modalities are not readily accessible. However, the emergence of novel mutated viruses causes a substantial dataset shift, which can greatly limit the performance of classification-based approaches. In this paper, we formulate the task of differentiating viral pneumonia from non-viral pneumonia and healthy controls into a one-class classification-based anomaly detection problem. We therefore propose the confidence-aware …

Jscsp: A Novel Policy-Based Xss Defense Mechanism For Browsers, Guangquan Xu, Xiaofei Xie, Shuhan Huang, Jun Zhang, Lei Pan, Wei Lou, Kaitai Liang

Research Collection School Of Computing and Information Systems

To mitigate cross-site scripting attacks (XSS), the W3C group recommends web service providers to employ a computer security standard called Content Security Policy (CSP). However, less than 3.7 percent of real-world websites are equipped with CSP according to Google’s survey. The low scalability of CSP is incurred by the difficulty of deployment and non-compatibility for state-of-art browsers. To explore the scalability of CSP, in this article, we propose JavaScript based CSP (JSCSP), which is able to support most of real-world browsers but also to generate security policies automatically. Specifically, JSCSP offers a novel self-defined security policy which enforces essential confinements …

Sample-Efficient Iterative Lower Bound Optimization Of Deep Reactive Policies For Planning In Continuous Mdps, Siow Meng Low, Akshat Kumar, Scott Sanner

Research Collection School Of Computing and Information Systems

Recent advances in deep learning have enabled optimization of deep reactive policies (DRPs) for continuous MDP planning by encoding a parametric policy as a deep neural network and exploiting automatic differentiation in an end-toend model-based gradient descent framework. This approach has proven effective for optimizing DRPs in nonlinear continuous MDPs, but it requires a large number of sampled trajectories to learn effectively and can suffer from high variance in solution quality. In this work, we revisit the overall model-based DRP objective and instead take a minorizationmaximization perspective to iteratively optimize the DRP w.r.t. a locally tight lower-bounded objective. This novel …