Physical Sciences and Mathematics Commons^™

Edsc: An Event-Driven Smart Contract Platform, Mudabbir Kaleem, Keshav Kasichainula, Rabimba Karanjai, Lei Xu, Zhimin Gao, Lin Chen, Weidong Shi

Computer Science Faculty Publications and Presentations

This paper presents EDSC, a novel smart contract platform design based on the event-driven execution model as opposed to the traditionally employed transaction-driven execution model. We reason that such a design is a better fit for many emerging smart contract applications and is better positioned to address the scalability and performance challenges plaguing the smart contract ecosystem. We propose EDSC’s design under the Ethereum framework, and the design can be easily adapted for other existing smart contract platforms. We have conducted implementation using Ethereum client and experiments where performance modeling results show on average 2.2 to 4.6 times reduced total …

Sentiment Analysis Of Long-Term Social Data During The Covid-19 Pandemic, Sophanna Ek, Marco Curci, Xiaokun Yang, Beiyu Lin, Pinchao Liu, Hailu Xu

Computer Science Faculty Publications and Presentations

The COVID-19 pandemic has bringing the “infodemic” in the social media worlds. Various social platforms play a significant role in instantly acquiring the latest updates of the pandemic. Social media such as Twitter and Facebook produce vast amounts of posts related to the virus, vaccines, economics, and politics. In order to figure out how public opinion and sentiments are expressed during the pandemic, this work analyzes the long-term social posts from social media and conducts sentiment analysis on tweets within 12 months. Our findings show the trend topics of long-term social communities during the pandemic and express people’s attitudes towards …

Covert Computation In Staged Self-Assembly: Verification Is Pspace-Complete, David Caballero, Timothy Gomez, Robert Schweller, Tim Wylie

Computer Science Faculty Publications and Presentations

Staged self-assembly has proven to be a powerful abstract model of self-assembly by modeling laboratory techniques where several nanoscale systems are allowed to assemble separately and then be mixed at a later stage. A fundamental problem in self-assembly is Unique Assembly Verification (UAV), which asks whether a single final assembly is uniquely constructed. This has previously been shown to be Π^{p}₂-hard in staged self-assembly with a constant number of stages, but a more precise complexity classification was left open related to the polynomial hierarchy.
Covert Computation was recently introduced as a way to compute a function while hiding the input …

Transitioning To An Active Learning Environment For Calculus At The University Of Florida, Darryl Chamberlain, Amy Grady, Scott Keeran, Kevin Knudson, Ian Manly, Melissa Shabazz, Corey Stone

Publications

In this note, we describe a large-scale transition to an active learning format in first-semester calculus at the University of Florida. Student performance and attitudes are compared across traditional lecture and flipped sections.

How To Draft An Sop?, Emily Faulconer

Publications

ERAU offers resources to support SOP development.

We can streamline efforts by learning from the past.

• Do not write an SOP for an individual process or action, it should be a part of the larger process.

• Disregard the first sentence if the material is so dangerous that it needs its own SOP created.

• If you are having trouble, stop and ask for assistance. The process can become frustrating.

• Be specific (what size container, slow/fast pour, what speed to mix at).

• Do not refer to other checklists if at all possible, multiple SOPs/checklists can cause errors/mistakes. …

Novel Methods For Characterizing Conditional Quantiles In Zero-Inflated Count Regression Models, Xuan Shi

Theses and Dissertations--Statistics

Despite its popularity in diverse disciplines, quantile regression methods are primarily designed for the continuous response setting and cannot be directly applied to the discrete (or count) response setting. There can also be challenges when modeling count responses, such as the presence of excess zero counts, formally known as zero-inflation. To address the aforementioned challenges, we propose a comprehensive model-aware strategy that synthesizes quantile regression methods with estimation of zero-inflated count regression models. Various competing computational routines are examined, while residual analysis and model selection procedures are included to validate our method. The performance of these methods is characterized through …

Innovative Statistical Models In Cancer Immunotherapy Trial Design, Jing Wei

Theses and Dissertations--Statistics

A challenge arising in cancer immunotherapy trial design is the presence of non-proportional hazards (NPH) patterns in survival curves. We considered three different NPH patterns caused by delayed treatment effect, cure rate and responder rate of treatment group in this dissertation. These three NPH patterns would violate the proportional hazard model assumption and ignoring any of them in an immunotherapy trial design will result in substantial loss of statistical power.

In this dissertation, four models to deal with NPH patterns are discussed. First, a piecewise proportional hazards model is proposed to incorporate delayed treatment effect into the trial design consideration. …

Estimating And Testing Treatment Effects With Misclassified Multivariate Data, Zi Ye

Theses and Dissertations--Statistics

Clinical trials are often used to assess drug efficacy and safety. Participants are sometimes pre-stratified into different groups by diagnostic tools. However, these diagnostic tools are fallible. The traditional method ignores this problem and assumes the diagnostic devices are perfect. This assumption will lead to inefficient and biased estimators. In this era of personalized medicine and measurement-based care, the issues of bias and efficiency are of paramount importance. Despite the prominence, only few researches evaluated the treatment effect in the presence of misclassifications in some special cases and most others focus on assessing the accuracy of the diagnostic devices. In …

Simulations Of Single- And Two-Tone Tm-Doped Optical Fiber Laser Amplifiers, Tathagata Goswami, J. Grosek, Jay Gopalakrishnan

Mathematics and Statistics Faculty Publications and Presentations

This work uses numerical simulations of a thulium-doped optical fiber amplifier to predict various performance characteristics such as peak temperatures, expected output powers and efficiencies, presence of amplified spontaneous emission (ASE), and transverse mode instability (TMI) onset power thresholds. Single- and two-tone configurations are studied. In the latter case, the two laser sources are separated in frequency by the amount that corresponds to the peak Raman gain, and a few seed ratios at various total seed powers are examined. The goal is to provide the field with pertinent information on what is feasible for this type of amplifier.

Torsion And Curvature In Continuously Defective Solid Crystals, Marek Z. Elźanowski

Mathematics and Statistics Faculty Publications and Presentations

I show how one can utilize the concept of a canonical connection on a homogeneous space to describe defectiveness of a continuous elastic crystal solid.

New Amphibian And Reptile Distribution Records From Eastern South Dakota, Usa, Drew R. Davis

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

Over recent years, the continued collection of voucher specimens has helped to better document the distributions of South Dakota’s amphibians and reptiles. Despite large increases in our knowledge of these distributions, it remains clear that gaps in our understanding remain. Here, I report 17 new county records of six species of amphibians and reptiles from eastern South Dakota (east of the Missouri River) that are the result of fieldwork conducted in September 2020. The majority of these records are from the northern portions of the James River Lowland, Missouri Coteau, and Drift Plains ecoregions (Bryce et al. 1998), which are …

Machine Learning And Bioinformatic Insights Into Key Enzymes For A Bio-Based Circular Economy, Japheth E. Gado

Theses and Dissertations--Chemical and Materials Engineering

The world is presently faced with a sustainability crisis; it is becoming increasingly difficult to meet the energy and material needs of a growing global population without depleting and polluting our planet. Greenhouse gases released from the continuous combustion of fossil fuels engender accelerated climate change, and plastic waste accumulates in the environment. There is need for a circular economy, where energy and materials are renewably derived from waste items, rather than by consuming limited resources. Deconstruction of the recalcitrant linkages in natural and synthetic polymers is crucial for a circular economy, as deconstructed monomers can be used to manufacture …

Residual Spatial Autocorrelation In Macroecological And Biogeographical Modeling: A Review, Guetchine Gaspard

Theses and Dissertations--Geography

Macroecological and biogeographical modelers have predicted the distribution of species across space relying on the relationship between biotic processes and environmental variables. Such a method employs data associated, for instance, with species abundance or presence/absence, climate, geomorphology, and soils. Statistical analyses found in previous studies have highlighted the importance of accounting for the effects of spatial autocorrelation (SAC), which indicates a level of dependence between pairs of nearby observations. A consensus has existed that residual spatial autocorrelation (rSAC) can substantially impact modeling processes and inferences. However, more emphasis should be put on identifying the sources of rSAC and the degree …

Dimension Reduction Techniques In Regression, Pei Wang

Theses and Dissertations--Statistics

Because of the advances of modern technology, the size of the collected data nowadays is larger and the structure is more complex. To deal with such kinds of data, sufficient dimension reduction (SDR) and reduced rank (RR) regression are two powerful tools. This dissertation focuses on these two tools and it is composed of three projects. In the first project, we introduce a new SDR method through a novel approach of feature filter to recover the central mean subspace exhaustively along with a method to determine the dimension, two variable selection methods, and extensions to multivariate response and large p …

Winter Measurements Of Heavy-Duty Vehicles To Characterize The Cold Temperature Effectiveness Of Selective Catalytic Reductions Catalyst In Controlling Oxide Of Nitrogen Emissions, Gary A. Bishop, Molly J. Haugen, Brian C. Mcdonald

Fuel Efficiency Automobile Test Publications

No abstract provided.

Detection Of Amyotrophic Lateral Sclerosis Disease By Variational Modedecomposition And Convolution Neural Network Methods From Event-Relatedpotential Signals, Fatma Lati̇foğlu, Firat Orhan Bulucu, Rami̇s İleri̇

Turkish Journal of Electrical Engineering and Computer Sciences

Amyotrophic lateral sclerosis (ALS), also known as motor neuron disease, is a neurological disease that occurs as a result of damage to the nerves in the brain and restriction of muscle movements. Electroencephalography (EEG) is the most common method used in brain imaging to study neurological disorders. Diagnosis of neurological disorders such as ALS, Parkinson's, attention deficit hyperactivity disorder is important in biomedical studies. In recent years, deep learning (DL) models have been started to be applied in the literature for the diagnosis of these diseases. In this study, event-related potentials (ERPs) were obtained from EEG signals obtained as a …

Weak And Injective Dimensional Analogues Of Kaplansky's And Auslander's Lemmas For Purity, Laszlo Fuchs, Sang Bum Lee

Turkish Journal of Mathematics

We prove a stronger form of an analogue of a Kaplansky lemma on homological dimensions by showing that in a pure-exact sequence $0 \to A \to B \to C \to 0$, the weak dimensions of the modules satisfy $ {\rm w.d.} B = \max\{{\rm w.d.} A, {\rm w.d.} C\}$. We also show that the same equality holds for the injective dimensions whenever the ring is noetherian. In addition, a version of Auslander's lemma for chains of pure submodules $M_{\rho}$ is proved: the weak dimension of the union of the chain equals the supremum of the weak dimensions of the factor …

A Third-Order P-Laplacian Boundary Value Problem On An Unbounded Domain, Samuel Azubuike Iyase, Ogbu Famous Imaga

Turkish Journal of Mathematics

In this work, we apply Leray-Schauder continuation principle to establish the existence of at least one solution to the third order p-Laplacian boundary value problem on an unbounded domain of the form \begin{equation*} (w(t) \varphi_{p}( u^{\prime\prime}(t)))^{\prime} = K ( t, u(t) , u^{\prime}(t), u^{\prime\prime}(t) ) , t \in ( 0, \infty) \end{equation*} \begin{equation*} u(0)= 0, \, u^{\prime} (0) = \sum^{m}_{i=1} \alpha _{i} \int_{0}^{\xi_{i}} u(t) dt, \, \lim_{t \rightarrow\infty} ( w(t)\varphi_{p} ( u^{\prime \prime} (t)) = 0 \end{equation*} under the nonresonant condition $ \sum_{i=1}^{m} \alpha_{i} \xi^{2} \neq 2. $

Does California’S Emfac2017 Vehicle Emissions Model Under-Predict California Light-Duty Gasoline Vehicle Nox Emissions?, Gary A. Bishop

Fuel Efficiency Automobile Test Publications

On-road remote sensing measurements of light and medium-duty gasoline vehicles collected within California’s South Coast Air Basin since 1999 generally fall within the range of observed summer ambient molar NO_x/CO measurements collected during morning rush hours. Compared with ambient and on-road emissions, the California Air Resources Board EMFAC model under predicts 2018 gasoline vehicle NO_x emission factors by more than a factor of 2.6. Contributing to these differences is that vehicles older than model year 2006 have NO_x emission deterioration rates that are up to 4 time’s higher on-road than predicted by the EMFAC model. A …

Statistically Multiplicative Convergence On Locally Solid Riesz Algebras, Abdullah Aydin, Mi̇kai̇l Et

Turkish Journal of Mathematics

In this paper, we introduce the statistically multiplicative convergent sequences in locally solid Riesz algebras with respect to algebra multiplication and solid topology. We study this concept and the notion of $st_m$-bounded sequences, and also, we prove some relations between this convergence and the other convergences such as the order convergence and the statistical convergence in topological spaces. Also, we give some results related to semiprime $f$-algebras.

The Impact Of Initial Snow Conditions On The Numerical Weather Simulation Of A Northern Rockies Atmospheric River, William Rudisill, Alejandro Flores, James Mcnamara

Geosciences Faculty Publications and Presentations

Snow’s thermal and radiative properties strongly impact the land surface energy balance and thus the atmosphere above it. Land surface snow information is poorly known in mountainous regions. Few studies have examined the impact of initial land surface snow conditions in high-resolution, convection-permitting numerical weather prediction models during the midlatitude cool season. The extent to which land surface snow influences atmospheric energy transport and subsequent surface meteorological states is tested using a high-resolution (1 km) configuration of the Weather Research and Forecasting (WRF) Model, for both calm conditions and weather characteristic of a warm late March atmospheric river. A set …

On Performance Analysis Of Multioperator Ran Sharing For Mobile Networkoperators, Yekta Türk, Engi̇n Zeydan

Turkish Journal of Electrical Engineering and Computer Sciences

Enhancing the coverage and eliminating the poor performance is key to balance end-user experience andfuture network investments for mobile network operators (MNOs). Although vast amounts of infrastructure investmentsare provided by MNOs, there are still coverage and capacity planning problems at remote locations. This is because,in most cases, the population density and return-of-investments are low in those areas. In this paper, radio accessnetwork (RAN) sharing paradigm is utilized on experimental sites in Turkey to accommodate user equipment of multiplenetwork operators under the same cell sites. We first investigate characteristics, benefits, and limitations of two differentRAN sharing deployment scenarios. Then, a city-wide …

Quantifying The Increased Resiliency Of Chesapeake Bay Hypoxia To Environmental Conditions: A Benefit Of Nutrient Reductions, Luke Thomas Frankel

Dissertations, Theses, and Masters Projects

Seasonal hypoxia is a characteristic feature of the Chesapeake Bay as a result of anthropogenic eutrophication from agriculture and urban development throughout the watershed. Although in recent years coordinated management efforts have successfully reduced the flux of nutrients into the Bay, the overall goal of sufficient oxygen concentrations below the pycnocline for living resources remains unfulfilled. This was particularly apparent in 2018 and 2019 when the volume of hypoxic water exceeded the long-term (35-year) average due to anomalously high riverine discharge. To quantify the impact of watershed nutrient reductions, conventional statistical methods were employed in concert with a 3-D numerical …

Sediment And Terrestrial Organic Carbon Budgets For The Offshore Ayeyarwady Delta: Establishing A Baseline For Future Change, Evan Rose Flynn

Dissertations, Theses, and Masters Projects

Large river deltas serve as globally important archives of terrestrial and shallow marine biogeochemical signatures because of rapid sediment burial, and have the potential to impact global biogeochemical cycling on modern and geologic timescales. This study investigates modern sediment and terrestrial organic carbon (TerrOC) accumulation within the offshore Ayeyarwady Delta in order to determine sediment and TerrOC budgets for this largely understudied mega-delta. The Ayeyarwady is the world’s third largest delta in terms of sediment supply, and remains one of the last long free-flowing rivers in Asia. However, recent increases in regional anthropogenic impacts risk severe alterations to sediment and …

Poised For Change: University Students Are Positively Disposed Toward Food Waste Diversion And Decrease Individual Food Waste After Programming, Manar Arica Alattar, Jennifer L. Morse

Environmental Science and Management Faculty Publications and Presentations

Eaters (consumers of food) are responsible for 60% of waste along the food cycle in developed countries. Programs that target individual and household food waste behavior change are essential to addressing such waste. School cafeterias worldwide offer an opportune microcosm in which to educate on food and nutrition skills and change related behavior. No Scrap Left Behind, a cafeteria food waste diversion program, was developed, piloted, and assessed based on measures of both direct and indirect food waste behavior, and attitudes, knowledge, and emotions related to food waste. Participants had positive attitudes towards food waste reduction, engaged in food waste …

Solving Relativistic Three-Body Integral Equations In The Presence Of Bound States And Resonances, Taylor R. Powell, Raúl A. Briceño, Andrew W. Jackura

Physics: Accelerator and Nuclear Physics at the Thomas Jefferson National Accelerator Facility in Newport News, Virginia

Three-body interactions play an important role throughout modern-day particle, nuclear, and hadronic physics; many experimentally observed reactions of interest for testing the Standard Model result in final states composed of three particles or more. Due to these issues, a full description of three-body interactions from Quantum Chromodynamics is required. The focus of this project was to extend previous results for a two-body subsystem with a bound state to include resonance channels. We first derived a novel single-variable observable, denoted as an intensity distribution, which is proportional to the probability density of the three-body scattering amplitude. We explored this distribution in …

Odu Professors Study Gulf Stream Decline, News @ Odu

News Items

No abstract provided.

Larry Philip Atkinson 1941-2020, Gregory Cutter, Louis Codispoti

OES Faculty Publications

No abstract provided.

Quandles With Orbit Series Conditions, Alissa Crans

Mathematics, Statistics and Data Science Faculty Works

We introduce the notion of an orbit series in a quandle. Using this notion we define four families of quandles based on finiteness conditions on their orbit series. Intuitively, the classes tOS and tOSn correspond to finitary compositions of trivial quandles while the classes OS and OSn correspond to finitary compositions of connected quandles. We study properties of these four families of quandles and explore their relationships with several previously studied families of quandles: reductive, n-reductive, locally reductive, n-locally reductive, and solvable quandles

Converting Optical Videos To Infrared Videos Using Attention Gan And Its Impact On Target Detection And Classification Performance, Mohammad Shahab Uddin, Reshad Hoque, Kazi Aminul Islam, Chiman Kwan, David Gribben, Jiang Li

Electrical & Computer Engineering Faculty Publications

To apply powerful deep-learning-based algorithms for object detection and classification in infrared videos, it is necessary to have more training data in order to build high-performance models. However, in many surveillance applications, one can have a lot more optical videos than infrared videos. This lack of IR video datasets can be mitigated if optical-to-infrared video conversion is possible. In this paper, we present a new approach for converting optical videos to infrared videos using deep learning. The basic idea is to focus on target areas using attention generative adversarial network (attention GAN), which will preserve the fidelity of target areas. …