Physical Sciences and Mathematics Commons^™

Late Pleistocene And Early Holocene Sea-Level History And Glacial Retreat Interpreted From Shell-Bearing Marine Deposits Of Southeastern Alaska, Usa, James F. Baichtal, Alia J. Lesnek, Risa J. Carlson, Nicholas S. Schmuck, Jane L. Smith, Dennis J. Landwehr, Jason P. Briner

Publications and Research

We leverage a data set of >720 shell-bearing marine deposits throughout southeastern Alaska (USA) to develop updated relative sea-level curves that span the past ~14,000 yr. This data set includes site location, elevation, description when avail-able, and 436 14C ages, 45 of which are published here for the first time. Our sea-level curves suggest a peripheral forebulge developed west of the retreating Cordilleran Ice Sheet (CIS) margin between ca. 17,000 and 10,800 calibrated yr B.P. By 14,870 ± 630 to 12,820 ± 340 cal. yr B.P., CIS mar-gins had retreated from all of southeastern Alaska’s fjords, channels, and passages. At …

Identification Of An Intermediate Species Along The Nitrile Hydratase Reaction Pathway By Epr Spectroscopy, Wasantha Lankathilaka Karunagala Pathiranage, Natalie Gumataotao, Adam T. Fiedler, Richard C. Holz, Brian Bennett

Physics Faculty Research and Publications

A new method to trap catalytic intermediate species was employed with Fe-type nitrile hydratase from Rhodococcus equi TG328-2 (ReNHase). ReNHase was incubated with substrates in a 23% (w/w) NaCl/H₂O eutectic system that remained liquid at −20 °C, thereby permitting the observation of transient species that were present at electron paramagnetic resonance (EPR)-detectable levels in samples frozen while in the steady state. Fe^III-EPR signals from the resting enzyme were unaffected by the presence of 23% NaCl, and the catalytic activity was ∼55% that in the absence of NaCl at the optimum pH of 7.5. …

Development Of Sensor, Sensory System And Signal Processing Algorithm For Intelligent Sensing Applications, Xingzhe Zhang

Dissertations

Sensors have been receiving significant attention in the last decade and the demand for sensory systems has increased in recent years due to the rapid growth in the field of artificial intelligence (AI). Sensors can improve people’s awareness by providing them with real-time information on the environment and their immediate health conditions. This dissertation presents the fulfilment of three main projects and focuses on the development of a sensor, a sensory system, and a sensor signal recognition system for AI applications by employing printed electronics, analog circuit design, and digital signal processing techniques.

In the first project, a multi-channel stethograph …

Protection Of Patient Privacy On Mobile Device Machine Learning, Matthew Nguyen

Cybersecurity Undergraduate Research Showcase

An existing StudentLife Study mobile dataset was evaluated and organized to be applied to different machine learning methods. Different variables like user activity, exercise, sleep, study space, social, and stress levels are optimized to train a model that could predict user stress level. The different machine learning methods would test if both patient data privacy and training efficiency can be ensured.

Internet Of Things: Cybersecurity In Small Businesses, Zobair Wali

Cybersecurity Undergraduate Research Showcase

Small businesses are the most vital part of a nation’s economy. In today’s world, as we are moving towards digitizing almost everything around us, cybersecurity is essential and vital for our digitalized world to function. Small businesses are no exception. All businesses collect, use, and store information. They store employees’ information, tax information, customers’ information, business transaction information, and all other operational information that is needed for a business to function. Without an appropriate cybersecurity program, these businesses are vulnerable and can be easily impacted by cyber incidents and malicious attacks. Businesses are putting resources to protect their systems against …

Self-Supervised Perceptual Ad-Blocker, Killian Robinson

Cybersecurity Undergraduate Research Showcase

This project proposes a new self-supervised ad-blocker to minimize the amount of human effort required to effectively combat pushed advertisements. Current ad-blocker models are expensive to develop and not always effective in identifying advertisements. We investigated the possibility of solving these problems with the introduction of a deep learning, self-supervised ad-blocker model. More specifically, the proposed ad-blocker will be trained in a self-supervised fashion to tackle the issue of lacking labelled training data. The proposed solution was prototyped using Pytorch and achieved a detection accuracy of 81% on a diverse selection of popular websites.

Transforming Businesses With E-Commerce Intelligence, Yuanto Kusnadi, Gary Pan

Research Collection School Of Accountancy

2020 had been an extraordinary year as the Covid-19 pandemic struck almost all countries in the world and created an extraordinary impact on businesses worldwide. Singapore and many other Southeast Asian countries were not spared and had to implement lockdowns swiftly. To cope with physical store closures and the increased volume of online transactions, most businesses tried to revamp their business models and set up online stores to capitalise on the rise of the e-commerce wave. With the growing trend of online transactions, it has become imperative for companies operating in the Fast Moving Consumer Goods (FMCG) industry to track …

Uncertainty Analysis For Ccd-Augmented Casi® Brdf Measurement System, Todd V. Small, Samuel D. Butler, Michael A. Marciniak

Faculty Publications

This work presents a measurement uncertainty analysis for a system designed to simultaneously capture specular in-plane and out-of-plane bidirectional reflectance distribution function (BRDF) data with high spatial resolution by augmenting the Complete Angle Scatter Instrument (CASI®) with a charge-coupled device (CCD) camera. Various scatter flux, incident flux, scatter angle, and detector solid angle uncertainty contributions are considered and evaluated based on imperfectly known system parameters. In particular, incident flux temporal fluctuation, detector noise and non-linearity, and out-of-plane aperture misalignment considerations each require significant adjustment from original CASI® uncertainty analysis, and expressions for neutral density (ND) filter, scatter angle, and solid …

Risk Communication In The Tourism Industry, Lindsay E. Usher, Ashley Schroeder

Human Movement Studies & Special Education Faculty Publications

This chapter focuses on risk communication in the tourism sector. Tourism organizations must communicate with a variety of stakeholders when conveying messages about impending severe weather or disasters, which are increasing due climate change and sea level rise. There is also an increased need to distribute information to tourism stakeholders about preparing for, continuing service during, and recovering from, disasters. Stakeholders involved with the tourism industry include business owners, government officials and tourists, all of whom have differing degrees of vulnerability in a destination when a threat occurs. Different messages regarding disaster preparation and recovery must be communicated to the …

Risk Management And Biases In How Drivers Respond To Nuisance Flooding, Saige Hill, Juita-Elena (Wie) Yusuf, Burton St. John Iii, Pragati Rawat, Carol Considine

School of Public Service Faculty Publications

Nuisance flooding, or recurrent flooding, occurs during high tide and may be exacerbated when combined with other events such as heavy precipitation, strong winds, or storm surge. Sea level rise has contributed to increased frequency and duration of nuisance flooding in low-lying coastal areas and is causing community-specific impacts such as transportation disruption, road closures, compromises to life and property, overwhelmed storm water systems, and infrastructure damage. This chapter focuses on how drivers respond during nuisance flooding events. Specifically, we discuss how drivers in the Hampton Roads region of southeastern coastal Virginia obtain information about road flooding, how they respond, …

Engaging Residents In Policy And Planning For Sea Level Rise: Application Of The Action-Oriented Stakeholder Engagement For A Resilient Tomorrow (Asert) Framework, Juita-Elena (Wie) Yusuf, J. Gail Nicula, Daniel P. Richards, Ogechukwu Agim, Michelle Covi, Khairul A. Anuar

School of Public Service Faculty Publications

This chapter describes the application of the Action-oriented Stakeholder Engagement for a Resilient Tomorrow (ASERT) framework for communicating with and engaging both residents and community stakeholders in their localities’ efforts to prepare for and to respond to flooding and sea level rise. The application of ASERT incorporates communication, education/learning, and gamification elements that can be embedded into community meetings. We describe the way in which ASERT community meetings are designed (1) to provide an inclusive and engaging process that will allow residents to participate in their city’s resilience efforts; (2) to provide information about resilience in an environment that encourages …

Communicating And Co-Producing Information With Stakeholders: Examples Of Participatory Mapping Approaches Related To Sea Level Rise Risks And Impacts, Pragati Rawat, Khairul A. Anua, Juita-Elena (Wie) Yusuf, Jon Derek Loftis, Ren-Neasha Blake

School of Public Service Faculty Publications

This chapter discusses practical approaches for using participatory mapping as a tool to visualize and communicate sea level rise (SLR) and climate change risks, to share information about the vulnerability to, and threats of, climate change, and to co-produce knowledge with stakeholders. The examples presented in this chapter are from demonstrated applications in communities in Virginia (USA) that involve participatory mapping and that utilize a web-Geographic Information System (GIS). The web-GIS is innovatively combined with other technologies and participatory processes to create low-cost high-tech approaches so that even people with little to no knowledge of GIS can interact with maps …

Options For Prioritizing Sites For Biodiversity Conservation With Implications For “30 By 30”, R. Travis Belote, Kevin Barnett, Matthew S. Dietz, Laura Burkle, Clinton Jenkins, Lindsay Dreiss, Jocelyn L. Aycrigg, Gregory H. Aplet

Department of Earth and Environment

International and national initiatives aim to conserve at least 30% of lands and waters by 2030. To safeguard biodiversity, conservation actions must be distributed in places that represent ecosystem and species diversity. Various methods of prioritizing sites for conservation have been used in local and global assessments. However, the performance and consequences of alternative methods are usually unknown. Such comparisons are needed to confidently implement national and international conservation initiatives. Here, we compared four widely-used methods of prioritizing sites in the contiguous United States for conserving species of mammals, birds, amphibians, and reptiles. Specifically, we calculated and mapped species richness, …

The Ionic Selectivity Of Lysenin Channels In Open And Sub-Conducting States, Andrew Bogard, Pangaea W. Finn, Fulton Mckinney, Ilinca M. Flacau, Aviana R. Smith, Rosey Whiting, Daniel Fologea

Physics Faculty Publications and Presentations

The electrochemical gradients established across cell membranes are paramount for the execution of biological functions. Besides ion channels, other transporters, such as exogenous pore-forming toxins, may present ionic selectivity upon reconstitution in natural and artificial lipid membranes and contribute to the electrochemical gradients. In this context, we utilized electrophysiology approaches to assess the ionic selectivity of the pore-forming toxin lysenin reconstituted in planar bilayer lipid membranes. The membrane voltages were determined from the reversal potentials recorded upon channel exposure to asymmetrical ionic conditions, and the permeability ratios were calculated from the fit with the Goldman–Hodgkin–Katz equation. Our work shows that …

Traffic Collision Avoidance System: False Injection Viability, John Hannah, Robert F. Mills, Richard A. Dill, Douglas D. Hodson

Faculty Publications

Safety is a simple concept but an abstract task, specifically with aircraft. One critical safety system, the Traffic Collision Avoidance System II (TCAS), protects against mid-air collisions by predicting the course of other aircraft, determining the possibility of collision, and issuing a resolution advisory for avoidance. Previous research to identify vulnerabilities associated with TCAS’s communication processes discovered that a false injection attack presents the most comprehensive risk to veritable trust in TCAS, allowing for a mid-air collision. This research explores the viability of successfully executing a false injection attack against a target aircraft, triggering a resolution advisory. Monetary constraints precluded …

Microstratigraphic Analysis Of Fossil Distribution In The Lower Hornerstown And Upper Navesink Formations At The Edelman Fossil Park, Nj, Kristyn K. Voegele, Paul V. Ullmann, Tara Lonsdorf, Zachary Christman, Michael Heierbacher, Brian J. Kibelstis, Ian Putnam, Zachary Boles, Shane Walsh, Kenneth J. Lacovara

School of Earth & Environment Departmental Research

Maastrichtian–Danian sediments of the Navesink and Hornerstown formations at the Jean and Ric Edelman Fossil Park of Rowan University in Mantua Township, New Jersey, have long intrigued paleontologists. Within the basal Hornerstown Formation occurs the Main Fossiliferous Layer (MFL), a regionally well-known and diverse bonebed. The lithostratigraphic and chronostratigraphic position of this fossil layer have been debated for more than 50 years, fueling debate over its origin. Herein, we present the results of a microstratigraphic analysis of the fossil composition and distribution of the MFL undertaken to rectify these discrepancies. Through methodical top-down excavation, we recorded the three-dimensional position of …

Focus On Sustainable Cities: Urban Solutions Toward Desired Outcomes, M. Georgescu, M. Arabi, Winston T. L. Chow, E. Mack, K. C. Seto

Research Collection School of Social Sciences

Urbanization represents the single most impactful and long-lasting transformation of the Earth system since the dawn of civilization. Cities are simultaneously locations of innovation, social connectivity, and wealth, but they also create local-to-global environmental degradation and socioeconomic disparities. For example, food provision for cities has required significant land-use change and fertilizer input, has altered regional climate, biogeochemical cycles, and degraded marine and landscapes through biodiversity loss, algal blooms and fish kills. To maintain urban livelihoods and the provision of goods and services, cities require vast amounts of energy (e.g. to provide access to transport, cooling systems), which are massive producers …

The Forestecology R Package For Fitting And Assessing Neighborhood Models Of The Effect Of Interspecific Competition On The Growth Of Trees, Albert Y. Kim, David N. Allen, Simon P. Couch

Statistical and Data Sciences: Faculty Publications

Neighborhood competition models are powerful tools to measure the effect of interspecific competition. Statistical methods to ease the application of these models are currently lacking. We present the forestecology package providing methods to (a) specify neighborhood competition models, (b) evaluate the effect of competitor species identity using permutation tests, and (cs) measure model performance using spatial cross-validation. Following Allen and Kim (PLoS One, 15, 2020, e0229930), we implement a Bayesian linear regression neighborhood competition model. We demonstrate the package's functionality using data from the Smithsonian Conservation Biology Institute's large forest dynamics plot, part of the ForestGEO global network of research …

Wav-Bert: Cooperative Acoustic And Linguistic Representation Learning For Low-Resource Speech Recognition, Guolin Zheng, Yubei Xiao, Ke Gong, Pan Zhou, Xiaodan Liang, Liang Lin

Research Collection School Of Computing and Information Systems

Unifying acoustic and linguistic representation learning has become increasingly crucial to transfer the knowledge learned on the abundance of high-resource language data for low-resource speech recognition. Existing approaches simply cascade pre-trained acoustic and language models to learn the transfer from speech to text. However, how to solve the representation discrepancy of speech and text is unexplored, which hinders the utilization of acoustic and linguistic information. Moreover, previous works simply replace the embedding layer of the pre-trained language model with the acoustic features, which may cause the catastrophic forgetting problem. In this work, we introduce Wav-BERT, a cooperative acoustic and linguistic …

Aspect-Based Sentiment Analysis In Question Answering Forums, Wenxuan Zhang, Yang Deng, Xin Li, Lidong Bing, Wai Lam

Research Collection School Of Computing and Information Systems

Aspect-based sentiment analysis (ABSA) typically focuses on extracting aspects and predicting their sentiments on individual sentences such as customer reviews. Recently, another kind of opinion sharing platform, namely question answering (QA) forum, has received increasing popularity, which accumulates a large number of user opinions towards various aspects. This motivates us to investigate the task of ABSA on QA forums (ABSA-QA), aiming to jointly detect the discussed aspects and their sentiment polarities for a given QA pair. Unlike review sentences, a QA pair is composed of two parallel sentences, which requires interaction modeling to align the aspect mentioned in the question …

Aspect Sentiment Quad Prediction As Paraphrase Generation, Wenxuan Zhang, Yang Deng, Xin Li, Yifei Yuan, Lidong Bing, Wai Lam

Research Collection School Of Computing and Information Systems

Aspect-based sentiment analysis (ABSA) has been extensively studied in recent years, which typically involves four fundamental sentiment elements, including the aspect category, aspect term, opinion term, and sentiment polarity. Existing studies usually consider the detection of partial sentiment elements, instead of predicting the four elements in one shot. In this work, we introduce the Aspect Sentiment Quad Prediction (ASQP) task, aiming to jointly detect all sentiment elements in quads for a given opinionated sentence, which can reveal a more comprehensive and complete aspect-level sentiment structure. We further propose a novel Paraphrase modeling paradigm to cast the ASQP task to a …

Acoustic/Gravity Wave Phenomena In Wide-Field Imaging: From Data Analysis To A Modeling Framework For Observability In The Mlt Region And Beyond, Jaime Aguilar Guerrero

Doctoral Dissertations and Master's Theses

Acoustic waves, gravity waves, and larger-scale tidal and planetary waves are significant drivers of the atmosphere’s dynamics and of the local and global circulation that have direct and indirect impacts on our weather and climate. Their measurements and characterization are fundamental challenges in Aeronomy that require a wide range of instrumentation with distinct operational principles. Most measurements share the common features of integrating optical emissions or effects on radio waves through deep layers of the atmosphere. The geometry of these integrations create line-of-sight effects that must be understood, described, and accounted for to properly present the measured data in traditional …

Where2change: Change Request Localization For App Reviews, Tao Zhang, Jiachi Chen, Xian Zhan, Xiapu Luo, David Lo, He Jiang

Research Collection School Of Computing and Information Systems

Million of mobile apps have been released to the market. Developers need to maintain these apps so that they can continue to benefit end users. Developers usually extract useful information from user reviews to maintain and evolve mobile apps. One of the important activities that developers need to do while reading user reviews is to locate the source code related to requested changes. Unfortunately, this manual work is costly and time consuming since: (1) an app can receive thousands of reviews, and (2) a mobile app can consist of hundreds of source code files. To address this challenge, Palomba et …

Feasibility Of Development Of Flood Resiliency Clearinghouse Program, Commonwealth Center For Recurrent Flooding Resiliency, Mujde Erten-Unal, Carol Considine, Mark W. Luckenbach, Elizabeth Armistead Andrews

Commonwealth Center for Recurrent Flooding Resiliency (CCRFR): Reports

[Introduction]

House Bill 2187ⁱ, introduced by Delegate Keith Hodges in the 2021 session of the Virginia General Assembly, directed the Commonwealth Center for Recurrent Flooding Resiliency (CCRFR), a partnership between Old Dominion University, the Virginia Institute of Marine Science (VIMS) and the William & Mary Law School’s Virginia Coastal Policy Center (VCPC) established by Virginia Chapter 440 of the 2016 Acts of Assembly (HB 903), to evaluate the development of a Flood Resiliency Clearinghouse Program (henceforth Clearinghouse). The bill stipulated that the Center should work with the Department of Conservation and Recreation (DCR) to evaluate solutions that manage …

Nudging Students To Use Stronger Passwords: A Test Of Big Five Personality-Based Messages, Shelia Kennison, Eric Chan-Tin

Computer Science: Faculty Publications and Other Works

Cybersecurity breaches can occur when one uses an easily hacked password. Prior research has investigated 1) possible steps to encourage users to use strong passwords and 2) how personality is related to users using strong passwords.

We investigated whether personality-based nudging messages based on Big Five traits could nudge people to create stronger passwords (c.f., Jones et al., 2021). We also examined how personal characteristics, such as gender, age, personality traits, password knowledge, attitudes, and behavior, and need for cognition, were related to password strength.

We tested the hypothesis that passwords created following messages matching participants’ personality would be stronger …

Tweets R Us: Predicting Personality From Language And Emoji Use On Twitter, Maxwell Meckling, Sarah Shoup, D. E. Chan-Tin, Shelia Kennison

Computer Science: Faculty Publications and Other Works

The research investigated the suggestion from prior research that language and emojis use on Twitter and other social media platforms can predict users’ personality and gender (Adali et al., 2014; Golbeck et al., 2011; Li et al., 2019; Moreno et al., 2019; Raess, 2018). Some studies have also analyzed Twitter language to identify individuals with specific health conditions (e.g., alcohol recovery, Golbeck, 2012; sleep problems, Suarez et al., 2018).

If strategies to predict Twitter users’ characteristics prove to be successful, future efforts to direct persuasive messages related to recommended practices in public health and/or cybersecurity will be possible. Commercial applications …

Transfer-Learned Pruned Deep Convolutional Neural Networks For Efficient Plant Classification In Resource-Constrained Environments, Martinson Ofori

Masters Theses & Doctoral Dissertations

Traditional means of on-farm weed control mostly rely on manual labor. This process is time-consuming, costly, and contributes to major yield losses. Further, the conventional application of chemical weed control can be economically and environmentally inefficient. Site-specific weed management (SSWM) counteracts this by reducing the amount of chemical application with localized spraying of weed species. To solve this using computer vision, precision agriculture researchers have used remote sensing weed maps, but this has been largely ineffective for early season weed control due to problems such as solar reflectance and cloud cover in satellite imagery. With the current advances in artificial …

Fundamental Solutions For The Dirac Equation In Curved Spacetime And Generalized Euler-Poisson-Darboux Equation, Karen Yagdjian, Anahit Galstian

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

We present the fundamental solutions for the spin-1/2 fields propagating in spacetimes with power type expansion/contraction and the fundamental solution of the Cauchy problem for the Dirac equation. The derivation of these fundamental solutions is based on formulas for the solutions to the generalized Euler-Poisson-Darboux equation, which are obtained by the integral transform approach.

Iowa Waste Reduction Center Newsletter, November 2021, University Of Northern Iowa. Iowa Waste Reduction Center.

Iowa Waste Reduction Center Newsletter

Inside this Issue:

--- Iowa Green Brewery Certification Celebrates Five Years
--- Calendar
--- ISGP Webinar
--- Welcome Jordan Evans, Jason Clay & Andrew Kawano!
--- Industry News

Profiling Student Learning From Q&A Interactions In Online Discussion Forums, De Lin Ong, Kyong Jin Shim, Gottipati Swapna

Research Collection School Of Computing and Information Systems

The last two decades have witnessed an explosive growth in technology adoption in education. Proliferation of digital learning resources through Massive Open Online Courses (MOOCs) and social media platforms coupled with significantly lowered cost of learning has brought and is continuing to take education to every doorstep globally. In recent years, the use of asynchronous online discussion forums has become pervasive in tertiary education institutions. Online discussion forums are widely used for facilitating interactions both during the lesson time and beyond. Numerous prior studies have reported benefits of using online discussion forums including enhanced quality of learning, improved level of …