Physical Sciences and Mathematics Commons^™

Lifelong Learning-Based Optimal Trajectory Tracking Control Of Constrained Nonlinear Affine Systems Using Deep Neural Networks, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article presents a novel lifelong integral reinforcement learning (LIRL)-based optimal trajectory tracking scheme using the multilayer (MNN) or deep neural network (Deep NN) for the uncertain nonlinear continuous-time (CT) affine systems subject to state constraints. A critic MNN, which approximates the value function, and a second NN identifier are together used to generate the optimal control policies. The weights of the critic MNN are tuned online using a novel singular value decomposition (SVD)-based method, which can be extended to MNN with the N-hidden layers. Moreover, an online lifelong learning (LL) scheme is incorporated with the critic MNN to mitigate …

Deep Learning For Uav Detection And Classification Via Radio Frequency Signal Analysis, Prajoy Podder, Maciej Zawodniok, Sanjay Madria

Electrical and Computer Engineering Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs) are advertised as great tool that benefits society and humanity. However, UAVs also pose significant security threats ranging from privacy invasions, to interfering with commercial aircraft landing and takeoff, to accidently crashing into vehicles or people, to military or terrorist attacks. Consequently, there is a pressing need to detect and identify UAVs to mitigate such potential risks. While image-based methods are crucial for UAV detection, radio frequency (RF) emissions offer additional valuable insights. Analyzing RF signals, such as those used in UAV-ground station communications, can provide information about UAV types based on distinct frequency usage or …

The Attitudes And Practices Of United Arab Emirates Consumers Towards Food Waste: A Nationwide Cross-Sectional Study, Lynne Kennedy, Samir Safi, Tareq M. Osaili, Ala Al Rajabi, Ayesha Alblooshi, Dima Al Jawarneh, Ahmed Al Kaabi, Fakhra Al Rubaei, Maitha Albreiki, Maryam Alfadli, Aseilah Alhefeiti, Moez Al Islam Ezzat Faris, Kholoud Allaham, Sameeha Junaidi, Moien A.B. Khan

All Works

Background: Reducing global food waste is an international environmental, health, and sus-tainability priority. Although significant reductions have been achieved across the food chain, progress by UAE households and consumers remain inadequate. This study seeks to understand the association between consumer attitudes, knowledge, and awareness relating to food waste practice of residents living in the UAE. to help inform policy and action for addressing this national priority. Methods: A cross-sectional study was conducted using a validated semi-structured online questionnaire through stratified sampling (n =1052). The Spearman correlation coefficient was performed to determine the correlations. Two independent regression analysis were used to …

Assessing The Impact Of Chatbot-Human Personality Congruence On User Behavior: A Chatbot-Based Advising System Case, Mohammad Amin Kuhail, Mohamed Bahja, Ons Al-Shamaileh, Justin Thomas, Amina Alkazemi, Joao Negreiros

All Works

Chatbot personality has been demonstrated to influence user behavior, such as trust and intended engagement. However, previous research on chatbot-user personality congruence’s influence on user behavior is scant despite its significance in human-human conversations. This study explores the effect of chatbot-human personality trait congruence on user behavior in the context of a chatbot-based advising system. In this study, 54 college students interacted with chatbots with three different personalities (extraversion, agreeableness, and conscientiousness) and rated their trust, usage intention, and intended engagement with the chatbots. Additionally, 18 participants were interviewed to gain further insights into their perceptions and evaluations of the …

Advancing The Understanding Of Clinical Sepsis Using Gene Expression–Driven Machine Learning To Improve Patient Outcomes, Asrar Rashid, Feras Al-Obeidat, Wael Hafez, Govind Benakatti, Rayaz A. Malik, Christos Koutentis, Javed Sharief, Joe Brierley, Nasir Quraishi, Zainab A. Malik, Arif Anwary, Hoda Alkhzaimi, Syed Ahmed Zaki, Praveen Khilnani, Raziya Kadwa, Rajesh Phatak, Maike Schumacher, M. Guftar Shaikh, Ahmed Al-Dubai, Amir Hussain

All Works

Sepsis remains a major challenge that necessitates improved approaches to enhance patient outcomes. This study explored the potential of machine learning (ML) techniques to bridge the gap between clinical data and gene expression information to better predict and understand sepsis. We discuss the application of ML algorithms, including neural networks, deep learning, and ensemble methods, to address key evidence gaps and overcome the challenges in sepsis research. The lack of a clear definition of sepsis is highlighted as a major hurdle, but ML models offer a workaround by focusing on endpoint prediction. We emphasize the significance of gene transcript information …

Enhancing Decision-Making In Higher Education: Exploring The Integration Of Chatgpt And Data Visualization Tools In Data Analysis, Tristan Jiang, Elina Liu, Tasawar Baig, Qingrong Li

University Administration Publications

This chapter explores the potential of integrating conversational AI tools such as ChatGPT with data visualization (DV) tools such as Power BI in higher education settings. A brief history of chatbots is summarized and challenges and opportunities in higher education are outlined. The highlights include AI's prospects for enhancing data-informed decision-making while needing safeguards to mitigate risks. Through a pioneering exercise, we integrated ChatGPT's conversational capabilities with Power BI's interface via API and tested functionality. Suggestions for good practice and implications for higher education are discussed.

Using Phenology To Unravel Differential Soil Water Use And Productivity In A Semiarid Savanna, Blake Steiner, Russell L. Scott, Jia Hu, Natasha Mcbean, Andrew Richardson, David J. P. Moore

University Administration Publications

Savannas are water-limited ecosystems characterized by two dominant plant types: trees and an understory primarily made up grass. Different phenology and root structures of these plant types complicate how savanna primary productivity responds to changes in water availability. We tested the hypothesis that productivity in savannas is controlled by the temporal and vertical distribution of soil water content (SWC) and differences in growing season length of understory and tree plant functional types. To quantify the relationship between tree, understory, and savanna-wide phenology and productivity, we used PhenoCam and satellite observations surrounding an eddy covariance tower at a semiarid savanna site …

Enzymatic Degradation Of Plastic Waste: A Review Of Microbial Strategies And Future Perspectives, David Gonçalves

Seton Hall Biochemistry II Annals of Student Reviews

It is said that humans generate 2.01 billion tons of municipal waste every year and this number is projected to explode to a massive 3.40 billion tons annually by the year 2050 (Ellis, 2018). This increase in waste production perfectly underscores a growing reliance on materials that persist in ecosystems long-term. This contamination, generated from large-scale industrial practices to doing your laundry at home, is best exemplified by the proliferation of microplastics throughout the environment.

What are microplastics? The first documented use of the term microplastics can be traced to a 1990 publication in the South African Journal of Science …

Physical, Chemical, And Biological Methods Of Large-Scale Water Decontamination, Belmin Kolenovic

Seton Hall Biochemistry II Annals of Student Reviews

Considering water is the solvent of life, there is a lack of attention to what is added to it and how it impacts not only the environment but also society at large. In recent years, public scrutiny of the actions of individuals and industries concerning their negative actions on the environment has increased. General trends have seen a shift toward reusability and the reduction of pollutants. Examples include the use of reusable water bottles and the shift to biodegradable straws and paper cups. A plastic bottle casually floating atop a river is easily noticeable as a form of pollution but …

Note From The Editor, Gregory Wiedman

Seton Hall Biochemistry II Annals of Student Reviews

No abstract provided.

Ethical Decision-Making In Older Drivers During Critical Driving Situations: An Online Experiment, Amandeep Singh, Sarah Yahoodik, Yovela Murzello, Samuel Petkac, Yusuke Yamani, Siby Samuel

Psychology Faculty Publications

The present study examined the impact of aging on ethical decision-making in simulated critical driving scenarios. 204 participants from North America, grouped into two age groups (18–30 years and 65 years and above), were asked to decide whether their simulated automated vehicle should stay in or change from the current lane in scenarios mimicking the Trolley Problem. Each participant viewed a video clip rendered by the driving simulator at Old Dominion University and pressed the space-bar if they decided to intervene in the control of the simulated automated vehicle in an online experiment. Bayesian hierarchical models were used to analyze …

Les-C Turbulence Models And Fluid Flow Modeling: Analysis And Application To Incompressible Turbulence And Fluid-Fluid Interaction, Kyle J. Schwiebert

Dissertations, Master's Theses and Master's Reports

In the first chapter of this dissertation, we give some background on the Navier-Stokes equations and turbulence modeling. The next two chapters in this dissertation focus on two important numerical difficulties arising in fluid flow modeling: poor mass-conservation and nonphysical oscillations. We investigate two different formulations of the Crank-Nicolson method for the Navier-Stokes equations. The most attractive implementation, second order accurate for both velocity and pressure, is shown to introduce non-physical oscillations. We then propose two options which are shown to avoid the poor behavior. Next, we show that grad-div stabilization, previously assumed to have no effect on the target …

Chemical Synthesis Of Sensitive Dna, Komal Chillar

Dissertations, Master's Theses and Master's Reports

Over the past decades, researchers have tried various chemical methods to synthesize modified oligodeoxynucleotides (ODNs, i.e. short segments of DNAs). Traditional ODN synthesis methods require strong basic, and nucleophilic conditions for the deprotection and cleavage of the ODN from the solid support. However, the sensitive ODNs containing labile functionalities are vulnerable to such harsh conditions. Sensitive ODNs have a wide range of applications in research and pharmaceuticals. To synthesize sensitive ODNs, researchers devised different strategies but no practical methods have been developed. To overcome these challenges, we developed alkyl Dim alkyl Dmoc technology. This innovative technology uses weakly basic and …

Study Of Particle Accelerators In The Universe With The Hawc Observatory, Rishi Babu

Dissertations, Master's Theses and Master's Reports

HESS J1809-193 is an unidentified TeV source discovered in 2007 by the High Energy Stereoscopic System(H.E.S.S.) Collaboration. The emission originates in a region that is rich in cosmic-ray accelerators, including several supernova remnants and pulsars, including SNR G11.1+0.1, SNR G11.0-0.0, and the young radio pulsar PSR J1809-1917. Originally classified as a pulsar wind nebula candidate, recent studies show the peak of the TeV region overlapping with a system of molecular clouds and revising the original classification for other scenarios, including a pure hadronic scenario. This dissertation presents the morphological and spectral study of HESS J1809-193 using 2139 days of data …

Sea Level Rise Driven Groundwater Inundation: Effects Of Island Hydrogeology On Freshwater Lens Dynamics, Lauren K. Mancewicz

Dissertations, Master's Theses and Master's Reports

Groundwater inundation due to sea level rise poses a threat to fresh groundwater availability in coastal areas, and small islands are particularly vulnerable. On an island, when sea level rises, the freshwater lens also rises due to the difference in density between the salt and fresh groundwater. As the water table rises above the land surface it forms a lake and the water is exposed to additional evaporative losses, reducing the amount of fresh water available. This work aims to improve our understanding of groundwater inundation due to sea level rise and the impact of different hydrogeologic settings and phenomena …

Data Driven And Machine Learning Based Modeling And Predictive Control Of Combustion At Reactivity Controlled Compression Ignition Engines, Behrouz Khoshbakht Irdmousa

Dissertations, Master's Theses and Master's Reports

Reactivity Controlled Compression Ignition (RCCI) engines operates has capacity to provide higher thermal efficiency, lower particular matter (PM), and lower oxides of nitrogen (NOx) emissions compared to conventional diesel combustion (CDC) operation. Achieving these benefits is difficult since real-time optimal control of RCCI engines is challenging during transient operation. To overcome these challenges, data-driven machine learning based control-oriented models are developed in this study. These models are developed based on Linear Parameter-Varying (LPV) modeling approach and input-output based Kernelized Canonical Correlation Analysis (KCCA) approach. The developed dynamic models are used to predict combustion timing (CA50), indicated mean effective pressure (IMEP), …

Reverse-Engineering Of Disinformation Campaigns During The War In Ukraine, Lora Pitman, Ava Baratz, Kelly Morgan, Marcy Alvarado

School of Cybersecurity Faculty Publications

Information operations have long been a part of warfare. Disinformation campaigns, in particular, are usually launched by states in order to mislead and confuse populations in adversarial countries, but also to obtain support for their actions from domestic audiences. These campaigns threaten human security, at the individual level, but also state- and even international security. The invasion of Ukraine by Russia came with a new wave of disinformation not only in Ukraine itself, but also in countries from various other continents. This paper studies the characteristics of the spread of disinformation from the first day of the war in February …

Deep Transfer Learning-Based Bird Species Classification Using Mel Spectrogram Images, Mrinal Kanti Baowaly, Bisnu Chandra Sarkar, Md.Abul Ala Walid, Md. Martuza Ahamad, Bikash Chandra Singh, Eduardo Silva Alvarado, Imran Ashraf, Md. Abdus Samad

School of Cybersecurity Faculty Publications

The classification of bird species is of significant importance in the field of ornithology, as it plays an important role in assessing and monitoring environmental dynamics, including habitat modifications, migratory behaviors, levels of pollution, and disease occurrences. Traditional methods of bird classification, such as visual identification, were time-intensive and required a high level of expertise. However, audio-based bird species classification is a promising approach that can be used to automate bird species identification. This study aims to establish an audio-based bird species classification system for 264 Eastern African bird species employing modified deep transfer learning. In particular, the pre-trained EfficientNet …

Robustsentembed: Robust Sentence Embeddings Using Adversarial Self-Supervised Contrastive Learning, Javad Rafiei Asl, Prajwal Panzade, Eduardo Blanco, Daniel Takabi, Zhipeng Cai

School of Cybersecurity Faculty Publications

Pre-trained language models (PLMs) have consistently demonstrated outstanding performance across a diverse spectrum of natural language processing tasks. Nevertheless, despite their success with unseen data, current PLM-based representations often exhibit poor robustness in adversarial settings. In this paper, we introduce RobustSentEmbed, a self-supervised sentence embedding framework designed to improve both generalization and robustness in diverse text representation tasks and against a diverse set of adversarial attacks. Through the generation of high-risk adversarial perturbations and their utilization in a novel objective function, RobustSentEmbed adeptly learns high-quality and robust sentence embeddings. Our experiments confirm the superiority of RobustSentEmbed over state-of-the-art representations. Specifically, …

Quantification Of Antiviral Drug Tenofovir (Tfv) By Surface-Enhanced Raman Spectroscopy (Sers) Using Cumulative Distribution Functions (Cdfs), Marguerite R. Butler, Jana Hrncirova, Meredith Clark, Sucharita Dutta, John B. Cooper

Chemistry & Biochemistry Faculty Publications

Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive spectroscopic technique that generates signal-enhanced fingerprint vibrational spectra of small molecules. However, without rigorous control of SERS substrate active sites, geometry, surface area, or surface functionality, SERS is notoriously irreproducible, complicating the consistent quantitative analysis of small molecules. While evaporatively prepared samples yield significant SERS enhancement resulting in lower detection limits, the distribution of these enhancements along the SERS surface is inherently stochastic. Acquiring spatially resolved SERS spectra of these dried surfaces, we have shown that this enhancement is governed by a power law as a function of analyte concentration. Consequently, by definition, …

Cumulative Distribution Function And Spatially Resolved Surface-Enhanced Raman Spectroscopy For The Quantitative Analysis Of Emtricitabine, Jana Hrncirova, Marguerite R. Butler, Sucharita Dutta, Meredith R. Clark, John B. Cooper

Chemistry & Biochemistry Faculty Publications

Surface-enhanced Raman spectroscopy (SERS) has exceptional analytical sensitivity and selectivity. However, SERS irreproducibility presents an obstacle when using it for precise quantitative measurements. In this study, colloidal nanoparticles evaporated to dryness are used as a SERS active surface for the detection of the HIV drug emtricitabine (FTC; trade name Emtriva). Despite the irreproducibility of the SERS resulting from the stochastic process of evaporation, using a SERS scanning instrument, the SERS enhancement factors of spatially resolved spectra have a well-defined distribution of signals for a given analyte concentration. This distribution follows a power law function ranging from weak (very abundant signals) …

Byzantine Consensus In Abstract Mac Layer, Lewis Tseng, Callie Sardina

Computer Science

This paper studies the design of Byzantine consensus algorithms in an asynchronous single-hop network equipped with the “abstract MAC layer” [DISC09], which captures core properties of modern wireless MAC protocols. Newport [PODC14], Newport and Robinson [DISC18], and Tseng and Zhang [PODC22] study crash-tolerant consensus in the model. In our setting, a Byzantine faulty node may behave arbitrarily, but it cannot break the guarantees provided by the underlying abstract MAC layer. To our knowledge, we are the first to study Byzantine faults in this model. We harness the power of the abstract MAC layer to develop a Byzantine approximate consensus algorithm …

P.U.S.H. For Life Among The Stars: A Scientific And Philosophical Quest For Conceptualizing Uncertainty, Jacinta Creel Vallejo

Senior Projects Spring 2024

This senior project tackles how to deal with uncertainty in the search for life. Defining this uncertainty is tricky, and scientific efforts to do so are crucial. Such efforts include analyzing the data and biases of past, present, and future missions searching for exoplanets: planets outside our solar system. From there, the next step would be to infer what exoplanets have an atmosphere. This is a crucial, but not sufficient step, as having an atmosphere is a good sign of encountering life. However, finding an atmosphere is not an easy task, and this step will undeniably come with some amount …

A Party Of Particles: Constructing A Cyclotron To Accelerate Protons, Luke Christopher Ingraham

Senior Projects Spring 2024

The first particle accelerators were developed by Ernest Lawrence at University of California, Berkeley nearly one hundred years ago. Lawrence’s creation of the cyclotron has had an everlasting impact on physics and his experiments can be recreated today. A cyclotron is a charged particle accelerator that uses a magnetic field to confine particles to a spiral flight path in a vacuum chamber and an applied electrical field accelerates these particles to high energies. In this senior thesis, I embarked on a journey to build a fully functional cyclotron that is capable of accelerating protons to beyond 60keV. The complexity of …

An Unsupervised Machine Learning Algorithm For Clustering Low Dimensional Data Points In Euclidean Grid Space, Josef Lazar

Senior Projects Spring 2024

Clustering algorithms provide a useful method for classifying data. The majority of well known clustering algorithms are designed to find globular clusters, however this is not always desirable. In this senior project I present a new clustering algorithm, GBCN (Grid Box Clustering with Noise), which applies a box grid to points in Euclidean space to identify areas of high point density. Points within the grid space that are in adjacent boxes are classified into the same cluster. Conversely, if a path from one point to another can only be completed by traversing an empty grid box, then they are classified …

Solid Angle Measure Approximation Methods For Polyhedral Cones, Allison Fitisone

Theses and Dissertations--Mathematics

Polyhedral cones are of interest in many fields, like geometry and optimization. A simple, yet fundamental question we may ask about a cone is how large it is. As cones are unbounded, we consider their solid angle measure: the proportion of space that they occupy. Beyond dimension three, definitive formulas for this measure are unknown. Consequently, devising methods to estimate this quantity is imperative. In this dissertation, we endeavor to enhance our understanding of solid angle measures and provide valuable insights into the efficacy of various approximation techniques.

Ribando and Aomoto independently discovered a Taylor series formula for solid angle …

Pairs Of Quadratic Forms Over P-Adic Fields, John Hall

Theses and Dissertations--Mathematics

Given two quadratic forms $Q_1, Q_2$ over a $p$-adic field $K$ in $n$ variables, we consider the pencil $\mathcal{P}_K(Q_1, Q_2)$, which contains all nontrivial $K$-linear combinations of $Q_1$ and $Q_2$. We define $D$ to be the maximal dimension of a subspace in $K^n$ on which $Q_1$ and $Q_2$ both vanish. We define $H$ to be the maximal number of hyperbolic planes that a form in $\mathcal{P}_K(Q_1, Q_2)$ splits off over $K$. We will determine which values for $(D, H)$ are possible for a nonsingular pair of quadratic forms over a $p$-adic field $K$.

Portable X-Ray Fluorescence Spectrometry For Sensing Salinity And Sodicity In Glacial Northern Great Plains Soils With Machine Learning Models, Adam Devlin

Electronic Theses and Dissertations

Saline and sodic soils are an increasing concern across the Northern Great Plains (NGP) due to factors of climate change and land management that are drawing geologically derived salts to the land surface. Traditional laboratory assessments, such as electrical conductivity (EC) and sodium adsorption ratio (SAR), are time and resource consumptive. Portable X-ray fluorescence (PXRF) may be a viable proximal sensing alternative, as it is able to provide elemental data in minutes, in situ or ex situ, and can directly quantify salinity-associated elements like Ca, Mg, and S. PXRF paired with predictive models has proven useful for a range of …

Rado Numbers For Two Systems Of Linear Equations, Anthony Glackin

Electronic Theses and Dissertations

For any positive integer n and any equation E of either the form x1+x2+· · ·+xn = x0 or x1 + x2 + n = x0, the two-color Rado number R2(E) is the least integer such that any 2-coloring of the natural numbers 1 through R2(E) will contain a monochromatic solution to E. Let Ek be a system of k equations of the aforementioned form, where Ei represents the ith equation in Ek and the set I = {1, 2, . . . , k} is the set of indices of these equations. This thesis shows that the two-color Rado …

Investigation Of Deoxyfluorination Of Alkyl Alcohols Using Pentafluoropyridines Through A Covalent Intermediate, Christopher Allen Bias

Graduate Theses, Dissertations, and Problem Reports

Organofluorines are an omnipresent class of organic molecules, especially in pharmaceuticals. Selective fluorination of drug molecules allows for the influence of properties including metabolic activity, solubility, and intrinsic potency. Deoxyfluorinations are typically performed via generation of nucleophilic fluoride from a deoxyfluorination agent. Traditionally, diethylaminosulfur trifluoride (DAST) is the reagent of choice for these reactions, and it remains a popular reagent today. However, it has a propensity to form elimination side products and explode. Several research groups have recently developed new classes of deoxyfluorination agents including imidazole-based reagents (PhenoFluor) and sulfonyl fluorides (PyFluor) that exhibit better functional group tolerance and much …