Physical Sciences and Mathematics Commons^™

Vehicular Crowdsourcing For Congestion Support In Smart Cities, Stephan Olariu

Computer Science Faculty Publications

Under present-day practices, the vehicles on our roadways and city streets are mere spectators that witness traffic-related events without being able to participate in the mitigation of their effect. This paper lays the theoretical foundations of a framework for harnessing the on-board computational resources in vehicles stuck in urban congestion in order to assist transportation agencies with preventing or dissipating congestion through large-scale signal re-timing. Our framework is called VACCS: Vehicular Crowdsourcing for Congestion Support in Smart Cities. What makes this framework unique is that we suggest that in such situations the vehicles have the potential to cooperate with various …

Large Scale Subject Category Classification Of Scholarly Papers With Deep Attentive Neural Networks, Bharath Kandimalla, Shaurya Rohatgi, Jian Wu, C. Lee Giles

Computer Science Faculty Publications

Subject categories of scholarly papers generally refer to the knowledge domain(s) to which the papers belong, examples being computer science or physics. Subject category classification is a prerequisite for bibliometric studies, organizing scientific publications for domain knowledge extraction, and facilitating faceted searches for digital library search engines. Unfortunately, many academic papers do not have such information as part of their metadata. Most existing methods for solving this task focus on unsupervised learning that often relies on citation networks. However, a complete list of papers citing the current paper may not be readily available. In particular, new papers that have few …

Understanding The Impact Of Encrypted Dns On Internet Censorship, Lin Jin, Shuai Hao, Haining Wang, Chase Cotton

Computer Science Faculty Publications

DNS traffic is transmitted in plaintext, resulting in privacy leakage. To combat this problem, secure protocols have been used to encrypt DNS messages. Existing studies have investigated the performance overhead and privacy benefits of encrypted DNS communications, yet little has been done from the perspective of censorship. In this paper, we study the impact of the encrypted DNS on Internet censorship in two aspects. On one hand, we explore the severity of DNS manipulation, which could be leveraged for Internet censorship, given the use of encrypted DNS resolvers. In particular, we perform 7.4 million DNS lookup measurements on 3,813 DoT …

Ranked List Fusion And Re-Ranking With Pre-Trained Transformers For Arqmath Lab, Shaurya Rohatgi, Jian Wu, C. Lee Giles

Computer Science Faculty Publications

This paper elaborates on our submission to the ARQMath track at CLEF 2021. For our submission this year we use a collection of methods to retrieve and re-rank the answers in Math Stack Exchange in addition to our two-stage model which was comparable to the best model last year in terms of NDCG’. We also provide a detailed analysis of what the transformers are learning and why is it hard to train a math language model using transformers. This year’s submission to Task-1 includes summarizing long question-answer pairs to augment and index documents, using byte-pair encoding to tokenize formula and …

Adaptive Physics-Based Non-Rigid Registration For Immersive Image-Guided Neuronavigation Systems, Fotis Drakopoulos, Christos Tsolakis, Angelos Angelopoulos, Yixun Liu, Chengjun Yao, Kyriaki Rafailia Kavazidi, Nikolaos Foroglou, Andrey Fedorov, Sarah Frisken, Ron Kikinis, Alexandra Golby, Nikos Chrisochoides

Computer Science Faculty Publications

Objective: In image-guided neurosurgery, co-registered preoperative anatomical, functional, and diffusion tensor imaging can be used to facilitate a safe resection of brain tumors in eloquent areas of the brain. However, the brain deforms during surgery, particularly in the presence of tumor resection. Non-Rigid Registration (NRR) of the preoperative image data can be used to create a registered image that captures the deformation in the intraoperative image while maintaining the quality of the preoperative image. Using clinical data, this paper reports the results of a comparison of the accuracy and performance among several non-rigid registration methods for handling brain deformation. A …

A Tool For Segmentation Of Secondary Structures In 3d Cryo-Em Density Map Components Using Deep Convolutional Neural Networks, Yongcheng Mu, Salim Sazzed, Maytha Alshammari, Jiangwen Sun, Jing He

Computer Science Faculty Publications

Although cryo-electron microscopy (cryo-EM) has been successfully used to derive atomic structures for many proteins, it is still challenging to derive atomic structures when the resolution of cryo-EM density maps is in the medium resolution range, such as 5–10 Å. Detection of protein secondary structures, such as helices and β-sheets, from cryo-EM density maps provides constraints for deriving atomic structures from such maps. As more deep learning methodologies are being developed for solving various molecular problems, effective tools are needed for users to access them. We have developed an effective software bundle, DeepSSETracer, for the detection of protein secondary structure …

Ssentiaa: A Self-Supervised Sentiment Analyzer For Classification From Unlabeled Data, Salim Sazzed, Sampath Jayarathna

Computer Science Faculty Publications

In recent years, supervised machine learning (ML) methods have realized remarkable performance gains for sentiment classification utilizing labeled data. However, labeled data are usually expensive to obtain, thus, not always achievable. When annotated data are unavailable, the unsupervised tools are exercised, which still lag behind the performance of supervised ML methods by a large margin. Therefore, in this work, we focus on improving the performance of sentiment classification from unlabeled data. We present a self-supervised hybrid methodology SSentiA (Self-supervised Sentiment Analyzer) that couples an ML classifier with a lexicon-based method for sentiment classification from unlabeled data. We first introduce LRSentiA …

Fluid-Wall Interactions In Pseudopotential Lattice Boltzmann Models, Cheng Peng, Luis F. Ayala, Orlando M. Ayala

Engineering Technology Faculty Publications

Designing proper fluid-wall interaction forces to achieve proper wetting conditions is an important area of interest in pseudopotential lattice Boltzmann models. In this paper, we propose a modified fluid-wall interaction force that applies for pseudopotential models of both single-component fluids and partially miscible multicomponent fluids, such as hydrocarbon mixtures. A reliable correlation that predicts the resulting liquid contact angle on a flat solid surface is also proposed. This correlation works well over a wide variety of pseudopotential lattice Boltzmann models and thermodynamic conditions.

Numerical Simulations Of Capsule Deformation Using A Dual Time-Stepping Lattice Boltzmann Method, Charles Armstrong, Yan Peng

Mathematics & Statistics Faculty Publications

In this work a quasisteady, dual time-stepping lattice Boltzmann method is proposed for simulation of capsule deformation. At each time step the steady-state lattice Boltzmann equation is solved using the full approximation storage multigrid scheme for nonlinear equations. The capsule membrane is modeled as an infinitely thin shell suspended in an ambient fluid domain with the fluid structure interaction computed using the immersed boundary method. A finite element method is used to compute the elastic forces exerted by the capsule membrane. Results for a wide range of parameters and initial configurations are presented. The proposed method is found to reduce …

Interaction Between Genetic Risk Scores For Reduced Pulmonary Function And Smoking, Asthma And Endotoxin, Sinjini Sikdar, Annah B. Wyss, Mi Kyeong Lee, Thanh T. Hoang, Marie Richards, Laura E. Beane Freeman, Christine Parks, Peter S. Thorne, John L. Hankinson, David M. Umbach, Alison Motsinger-Reif, Stephanie J. London

Mathematics & Statistics Faculty Publications

Rationale Genome-wide association studies (GWASs) have identified numerous loci associated with lower pulmonary function. Pulmonary function is strongly related to smoking and has also been associated with asthma and dust endotoxin. At the individual SNP level, genome-wide analyses of pulmonary function have not identified appreciable evidence for gene by environment interactions. Genetic Risk Scores (GRSs) may enhance power to identify gene–environment interactions, but studies are few.

Methods We analysed 2844 individuals of European ancestry with 1000 Genomes imputed GWAS data from a case–control study of adult asthma nested within a US agricultural cohort. Pulmonary function traits were FEV₁, …

Predicting The Winning Percentage Of Limited-Overs Cricket Using The Pythagorean Formula, Hasika K. W. Senevirathne, Ananda B.W. Manage

Mathematics & Statistics Faculty Publications

The Pythagorean Win-Loss formula can be effectively used to estimate winning percentages for sporting events. This formula was initially developed by baseball statistician Bill James and later was extended by other researchers to sports such as football, basketball, and ice hockey. Although one can calculate actual winning percentages based on the outcomes of played games, that approach does not take into account the margin of victory. The key benefit of the Pythagorean formula is its utilization of actual average runs scored and actual average runs allowed. This article presents the application of the Pythagorean Win-Loss formula to two different types …

Stable And Convergent Difference Schemes For Weakly Singular Convolution Integrals, Wesley Davis, Richard D. Noren

Mathematics & Statistics Faculty Publications

We obtain new numerical schemes for weakly singular integrals of convolution type called Caputo fractional order integrals using Taylor and fractional Taylor series expansions and grouping terms in a novel manner. A fractional Taylor series expansion argument is utilized to provide fractional-order approximations for functions with minimal regularity. The resulting schemes allow for the approximation of functions in C^γ [0, T], where 0 < γ <= 5. A mild invertibility criterion is provided for the implicit schemes. Consistency and stability are proven separately for the whole-number-order approximations and the fractional-order approximations. The rate of convergence in the time variable is shown …

Using Ai For Management Of Field Emission In Srf Linacs, A. Carpenter, P. Degtiarenko, R. Suleiman, C. Tennant, D. Turner, L. S. Vidyaratne, Khan Iftekharuddin, Md. Monibor Rahman

Electrical & Computer Engineering Faculty Publications

Field emission control, mitigation, and reduction is critical for reliable operation of high gradient superconducting radio-frequency (SRF) accelerators. With the SRF cavities at high gradients, the field emission of electrons from cavity walls can occur and will impact the operational gradient, radiological environment via activated components, and reliability of CEBAF’s two linacs. A new effort has started to minimize field emission in the CEBAF linacs by re-distributing cavity gradients. To measure radiation levels, newly designed neutron and gamma radiation dose rate monitors have been installed in both linacs. Artificial intelligence (AI) techniques will be used to identify cavities with high …

Assessment Of Cu(In, Ga)Se₂ Solar Cells Degradation Due To Water Ingress Effect On The Cds Buffer Layer, Deewakar Poudel, Benjamin Belfore, Shankar Karki, Grace Rajan, Sina Soltanmohammad, Angus Rockett, Sylvain Marsillac

Electrical & Computer Engineering Faculty Publications

The effect of water ingress on the surface of the buffer layer of a Cu(In, Ga)Se2 (CIGS) solar cell was studied. Such degradation can occur either during the fabrication process, if it involves a chemical bath as is often the case for CdS, or while the modules are in the field and encapsulants degrade. To simulate the impact of this moisture ingress, devices with a structure sodalime glass/Mo/CIGS/CdS were immersed in deionized water. The thin films were then analyzed both pre and post water soaking. Dynamic secondary ion mass spectroscopy (SIMS) was performed on completed devices to analyze impurity diffusion …

Tri-Molybdenum Phosphide (Mo3P) And Multi-Walled Carbon Nanotube Junctions For Volatile Organic Compounds (Vocs) Detection, Baleeswaraiah Muchharla, Praveen Malali, Brenna Daniel, Alireza Kondori, Mohammad Asadi, Wei Cao, Hani E. Elsayed-Ali, Mickaël Castro, Mehran Elahi, Adetayo Adedeji, Kishor Kumar Sadasivuni, Muni Raj Mauya, Kapil Kumar, Abdennaceur Karoui, Bijandra Kumar

Electrical & Computer Engineering Faculty Publications

Detection and analysis of volatile organic compounds’ (VOCs) biomarkers lead to improvement in healthcare diagnosis and other applications such as chemical threat detection and food quality control. Here, we report on tri-molybdenum phosphide (Mo₃P) and multi- walled carbon nanotube (MWCNT) junction-based vapor quantum resistive sensors (vQRSs), which exhibit more than one order of magni- tude higher sensitivity and superior selectivity for biomarkers in comparison to pristine MWCNT junctions based vQRSs. Transmission electron microscope/scanning tunneling electron microscope with energy dispersive x-ray spectroscopy, x-ray diffraction, and x-ray photo- electron spectroscopy studies reveal the crystallinity and the presence of Mo and …

Transient Behavior Of Drift And Ionization In Atmospheric Pressure Nitrogen Discharge, S. K. Dhali

Electrical & Computer Engineering Faculty Publications

The fluid models are frequently used to describe a non-thermal plasma such as a streamer discharge. The required electron transport data and rate coefficients for the fluid model are parametrized using the local field approximation (LFA) in first order models and the local-mean-energy approximation (LMEA) in second order models. We performed Monte Carlo simulations in Nitrogen gas with step changes in the E/N (reduced electric field) to study the behavior of the transport properties in the transient phase. During the transient phase of the simulation, we extract the instantaneous electron mean energy, which is different from the steady state mean …

Rapid Quantification Of Biofouling With An Inexpensive, Underwater Camera And Image Analysis, Matthew R. First, Scott C. Riley, Kazi Aminul Islam, Victoria Hill, Jiang Li, Richard C. Zimmerman, Lisa A. Drake

Electrical & Computer Engineering Faculty Publications

To reduce the transport of potentially invasive species on ships' submerged surfaces, rapid-and accurate-estimates of biofouling are needed so shipowners and regulators can effectively assess and manage biofouling. This pilot study developed a model approach for that task. First, photographic images were collected in situ with a submersible, inexpensive pocket camera. These images were used to develop image processing algorithms and train machine learning models to classify images containing natural assemblages of fouling organisms. All of the algorithms and models were implemented in a widely available software package (MATLAB^©). Initially, an unsupervised clustering model was used, and three …

Formal Power Series Approach To Nonlinear Systems With Static Output Feedback, G.S. Venkatesh, W. Steven Gray

Electrical & Computer Engineering Faculty Publications

The goal of this paper is to compute the generating series of a closed-loop system when the plant is described in terms of a Chen-Fliess series and static output feedback is applied. The first step is to reconsider the so called Wiener-Fliess connection consisting of a Chen-Fliess series followed by a memoryless function. Of particular importance will be the contractive nature of this map, which is needed to show that the closed-loop system has a Chen-Fliess series representation. To explicitly compute the generating series, two Hopf algebras are needed, the existing output feedback Hopf algebra used to describe dynamic output …

Continuity Of Chen-Fliess Series For Applications In System Identification And Machine Learning, Rafael Dahmen, W. Steven Gray, Alexander Schmeding

Electrical & Computer Engineering Faculty Publications

Model continuity plays an important role in applications like system identification, adaptive control, and machine learning. This paper provides sufficient conditions under which input-output systems represented by locally convergent Chen-Fliess series are jointly continuous with respect to their generating series and as operators mapping a ball in an Lp-space to a ball in an Lq-space, where p and q are conjugate exponents. The starting point is to introduce a class of topological vector spaces known as Silva spaces to frame the problem and then to employ the concept of a direct limit to describe convergence. The proof of the main …

High Voltage Design And Evaluation Of Wien Filters For The Cebaf 200 Kev Injector Upgrade, Gabriel Palacios-Serrano, Helmut Baumgart, C. Hernández-García, P. Adderley, J. Benesch, D. Bullard, J. Grames, A. Hofler, D. Machie, M. Poelker, M. Stutzman, R. Suleiman

Electrical & Computer Engineering Faculty Publications

High-energy nuclear physics experiments at the Jefferson Lab Continuous Electron Beam Accelerator Facility (CEBAF) require highly spin-polarization electron beams, produced from strained super-lattice GaAs photocathodes, activated to negative electron affinity in a photogun operating at 130 kV dc. A pair of Wien filter spin rotators in the injector defines the orientation of the electron beam polarization at the end station target. An upgrade of the CEBAF injector to better support the upcoming MOLLER experiment requires increasing the electron beam energy to 200 keV, to reduce unwanted helicity correlated intensity and position systematics and provide precise control of the polarization orientation. …

Initial Studies Of Cavity Fault Prediction At Jefferson Laboratory, L.S. Vidyaratne, A. Carpenter, R. Suleiman, C. Tennant, D. Turner, Khan Iftekharuddin, Md. Monibor Rahman

Electrical & Computer Engineering Faculty Publications

The Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Laboratory is a CW recirculating linac that utilizes over 400 superconducting radio-frequency (SRF) cavities to accelerate electrons up to 12 GeV through 5-passes. Recent work has shown that, given RF signals from a cavity during a fault as input, machine learning approaches can accurately classify the fault type. In this paper we report on initial results of predicting a fault onset using only data prior to the failure event. A data set was constructed using time-series data immediately before a fault (’unstable’) and 1.5 seconds prior to a fault (’stable’) gathered …

Covid-19 And Biocybersecurity's Increasing Role On Defending Forward, Xavier Palmer, Lucas N. Potter, Saltuk Karahan

Electrical & Computer Engineering Faculty Publications

The evolving nature of warfare has been changing with cybersecurity and the use of advanced biotechnology in each aspect of the society is expanding and overlapping with the cyberworld. This intersection, which has been described as “biocybersecurity” (BCS), can become a major front of the 21st-century conflicts. There are three lines of BCS which make it a critical component of overall cybersecurity: (1) cyber operations within the area of BCS have life threatening consequences to a greater extent than other cyber operations, (2) the breach in health-related personal data is a significant tool for fatal attacks, and (3) health-related misinformation …

Biocybersecurity: A Converging Threat As An Auxiliary To War, Lucas Potter, Orlando Ayala, Xavier-Lewis Palmer

Engineering Technology Faculty Publications

Biodefense is the discipline of ensuring biosecurity with respect to select groups of organisms and limiting their spread. This field has increasingly been challenged by novel threats from nature that have been weaponized such as SARS, Anthrax, and similar pathogens, but has emerged victorious through collaboration of national and world health groups. However, it may come under additional stress in the 21st century as the field intersects with the cyberworld-- a world where governments have already been struggling to keep up with cyber attacks from small to state-level actors as cyberthreats have been relied on to level the playing field …

Multivariate Distributions Of Correlated Binary Variables Generated By Pair-Copulas, Huihui Lin, N. Rao Chaganty

Mathematics & Statistics Faculty Publications

Correlated binary data are prevalent in a wide range of scientific disciplines, including healthcare and medicine. The generalized estimating equations (GEEs) and the multivariate probit (MP) model are two of the popular methods for analyzing such data. However, both methods have some significant drawbacks. The GEEs may not have an underlying likelihood and the MP model may fail to generate a multivariate binary distribution with specified marginals and bivariate correlations. In this paper, we study multivariate binary distributions that are based on D-vine pair-copula models as a superior alternative to these methods. We elucidate the construction of these binary distributions …

Morphology-Dependent Resonances In Two Concentric Spheres With Variable Refractive Index In The Outer Layer: Analytic Solutions, Umaporn Nuntaplook, John A. Adam

Mathematics & Statistics Faculty Publications

In many applications constant or piecewise constant refractive index profiles are used to study the scattering of plane electromagnetic waves by a spherical object. When the structured media has variable refractive indices, this is more of a challenge. In this paper, we investigate the morphology dependent resonances for the scattering of electromagnetic waves from two concentric spheres when the outer shell has a variable refractive index. The resonance analysis is applied to the general solutions of the radial Debye potential for both transverse magnetic and transverse electric modes. Finally, the analytic conditions to determine the resonance locations for this system …

A Class Of Copula-Based Bivariate Poisson Time Series Models With Applications, Mohammed Alqawba, Dimuthu Fernando, Norou Diawara

Mathematics & Statistics Faculty Publications

A class of bivariate integer-valued time series models was constructed via copula theory. Each series follows a Markov chain with the serial dependence captured using copula-based transition probabilities from the Poisson and the zero-inflated Poisson (ZIP) margins. The copula theory was also used again to capture the dependence between the two series using either the bivariate Gaussian or “t-copula” functions. Such a method provides a flexible dependence structure that allows for positive and negative correlation, as well. In addition, the use of a copula permits applying different margins with a complicated structure such as the ZIP distribution. Likelihood-based inference was …

Fundamentals Of Human-Centric Artificial Intelligence (A.I.): Comparative Analysis Of Europe And The U. S. Landscape, Torré A. Williams

Cybersecurity Undergraduate Research Showcase

This research is a comparative analysis of human-centric Artificial Intelligence (A.I.) in Europe and the U.S. This research establishes fundamentals that are critical to what makes A.I. human-centric. This research contains eight phases: 1) Lawful A.I.; 2) Robust A.I.; 3) Ethical A.I.; 4) Human-centric A.I.; 5) Current State of A.I.; 6) A.I. in Europe; 7) A.I. in the U.S.; 9) Importance of Human-centric A.I. This research shows that there are still ongoing changes with having a human-centric A.I. and why it is very important to society. This research is the beginning of the making of a successful and reliable human-centric …

Parton Distribution Functions From Ioffe Time Pseudodistributions From Lattice Calculations: Approaching The Physical Point, Bálint Joó, Joseph Karpie, Kostas Orginos, Anatoly V. Radyushkin, David G. Richards, Savvas Zafeiropoulos

Physics Faculty Publications

We present results for the unpolarized parton distribution function of the nucleon computed in lattice QCD at the physical pion mass. This is the first study of its kind employing the method of Ioffe time pseudodistributions. Beyond the reconstruction of the Bjorken-x dependence, we also extract the lowest moments of the distribution function using the small Ioffe time expansion of the Ioffe time pseudodistribution. We compare our findings with the pertinent phenomenological determinations.

Wicked Ideas For Wicked Problems: Marine Debris And The Complexity Of Governance, Dawn Helene Driesbach

Graduate Program in International Studies Theses & Dissertations

Myriad challenges regarding earth's common spaces, those unregulated by sovereign state authorities, mount and intensify as resources diminish and competition for commercial, scientific and security advantages increases; the pollution and degradation of those spaces simultaneously expands. Threats to the global commons complicate efforts to achieve international consensus which impedes attempts to develop effective governance. As an example, marine debris is a growing problem and is an existential threat to the global commons.

This dissertation aims to characterize marine debris as a wicked problem and explores the complexity of governance in the global ocean commons by answering two fundamental questions. Under …

The Role Of Traditional Knowledge In Coastal Adaptation Priorities: The Pamunkey Indian Reservation, Nicole S. Hutton, Thomas R. Allen

Political Science & Geography Faculty Publications

Coastal reservations are increasingly vulnerable to hazards exacerbated by climate change. Resources for restoration projects are limited. Storm surge, storms, tidal flooding, and erosion endanger artifacts and limit livelihoods of tribes in coastal Virginia. GIS offers a platform to increase communication between scientists, planners, and indigenous groups. The Pamunkey Indian Tribe engaged in a participatory mapping exercise to assess the role of traditional ecological knowledge (TEK) in coastal management decision-making and its capacity to address flooding. Priorities and strategies were spatially referenced using maps of potential sea level rise for 2040, 2060, and 2080, input into a resilience matrix to …