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Monarch Science Observer, Volume 13, College Of Sciences, Old Dominion University

College of Sciences Newsletter

Spring 2022, issue of Monarch Science Observer, ODU Colleges of Sciences Newsletter.

Habitat Restoration Restores Underwater Soundscapes And Larval Recruitment, Jack Butler, Emily R. Anderson, Mark J. Butler

Biological Sciences Faculty Publications

Habitat degradation alters many ecosystem processes, and the potential for the reestablishment of ecosystem function through restoration is an area of active research. Among marine systems, coastal habitats are particularly vulnerable to anthropogenic degradation and, in response, are the focus of marine ecological restoration. One of the crucial functions of structurally complex coastal habitats (e.g., saltmarshes, seagrass meadows, kelp forests, coral reefs) are as nurseries to coastal and offshore species, many of whose larvae utilize sound to locate suitable nursery habitat. However, the effect of habitat degradation and subsequent restoration on underwater soundscapes and their function as navigational cues for …

Monitoring Extinction Risk And Threats Of The World's Fishes Based On The Sampled Red List Index, Rafael Miranda, Imanol Miqueleiz, William Darwall, Catherine Sayer, Nicholas K. Dulvy, Kent E. Carpenter, Beth Polidoro, Nadia Dewhurst-Richman, Caroline Pollock, Craig Hilton-Taylor, Robin Freeman, Ben Collen, Monika Böhm

Biological Sciences Faculty Publications

Global biodiversitytargets require us to identify species at risk of extinction and quantify status and trends of biodiversity. The Red List Index (RLI) tracks trends in the conservation status of entire species groups over time by monitoring changes in categories assigned to species. Here, we calculate this index for the world’s fishes in 2010, using a sampled approach to the RLI based on a randomly selected sample of 1,500 species, and also present RLI splits for freshwater and marine systems separately. We further compare specific traits of a worldwide fish list to our sample to assess its representativeness. Overall, 15.1% …

Using Repeated Reading And Previewing Vocabulary Interventions With Elementary-Aged Struggling Readers To Improve Fluency And Comprehension, Khaled S. Alotaibi

Communication Disorders & Special Education Theses & Dissertations

Students with Learning disabilities and at risk for reading difficulties often face challenges in reading fluency and comprehension that impact negatively on academic success. Repeated reading (RR) is an intervention designed to increase reading fluency and comprehension skills among students at risk and diagnosed with disabilities. The purpose of this review was to investigate the effectiveness of the repeated reading (RR) and vocabulary previewing (VP) interventions on the fluency and comprehension skills of elementary school students. The review yielded a modest number of research articles published between 2008 and 2019. The results of these studies suggested that RR can have …

Development Of Guidelines For Collecting Transit Ridership Data, Hong Yang, Kun Xie, Sherif Ishak, Qingyu Ma, Yang Liu

Computational Modeling & Simulation Engineering Faculty Publications

Transit ridership is a critical determinant for many transit applications such as operation optimizations and project prioritization under performance-based funding mechanisms. As a result, the quality of ridership data is of utmost importance to both transit administrative agencies and transit operators. Many transit operators in Virginia report their ridership data to the Department of Rail and Public Transportation (DRPT) and the National Transit Database (NTD). However, with no specific guidelines available to transit agencies in Virginia for collecting ridership data, the heterogeneous mixture of diverse data collection methods and technologies has often raised concerns about the consistency and quality of …

Did They Really Tweet That?, Caleb Bradford, Michael L. Nelson (Mentor)

Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics

No abstract provided.

Networks Of Disinformation: The Proliferation Of Hate Speech In Chile And Colombia During The Venezuelan Migration Crisis, Isabelle Valdes, Erika Frydenlund (Mentor)

Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics

No abstract provided.

Fake Review Detection, Michael Husk, Faryaneh Poursardar (Mentor)

Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics

No abstract provided.

Module 1: Introduction To Technology Foresight, Risk Management, And Insurtech, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar

Developing Technology Foresight: Case Study of AI in InsurTech

Instructional Module 1 for course, Developing Technology Foresight: Case Study of AI in InsurTech.

Module 2: Case Studies Of Ai And Insurtech, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar

Developing Technology Foresight: Case Study of AI in InsurTech

Instructional Module 2 for course, Developing Technology Foresight: Case Study of AI in InsurTech.

Module 3: Technology Foresight And Insurtech, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar

Developing Technology Foresight: Case Study of AI in InsurTech

Instructional Module 3 for course, Developing Technology Foresight: Case Study of AI in InsurTech.

An Assessment Of Scientific Claim Verification Frameworks: Final Presentation, Ethan Landers, Jian Wu (Mentor)

Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics

No abstract provided.

Allied Dental Students' Dvi Learning Outcomes Following A Multimedia Module, Samantha Vest, Brenda Bradshaw, Marsha Voelker, Ann Bruhn, Tara L. Newcomb, Sinjini Sikdar

College of Health Sciences Posters

This pilot project assessed cognitive and affective learning outcomes of allied dental students following a disaster victim identification (DVI) multi-media learning module.

A convenience sample (n=41) of senior dental hygiene and dental assisting students from two institutions completed an IRB-exempt descriptive pretest/posttest study to assess cognitive and affective changes resulting from exposure to a multimedia DVI learning module of a PowerPoint presentation with audio/video recordings. After completing the learning module, participants were presented with 10 sets of mismatched antemortem (AM) and postmortem (PM) digital bitewing radiographs to test their cognitive ability to indicate identification matches. The pretest/posttest survey was a …

Insurtech And Distribution, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar

Developing Technology Foresight: Case Study of AI in InsurTech

Questions regarding InsurTech and distribution.

Disinformation About Mental Health On Tiktok, Dani Graber, Anne Perrotti (Mentor)

Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics

No abstract provided.

Protecting Blind Screen-Reader Users From Deceptive Content, Ash Dobrenen, Vikas Ashok (Mentor)

Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics

Visually impaired people who want to use a computer rely on screen readers to independently do this. This research focuses on beginning to build a chrome extension in order to help users more safely navigate the internet using a screen reader. to begin collecting the data, a screen reader was used to help determine items in the website that might take the user somewhere they did not mean to go since the link or image was not sufficiently able to be described by the screen reader. Next, those items were tagged with ’data-attribute=”deceptive”’. After, those data-attributes were extracted and tagged …

Human Interaction With Fake News, Autumn Woodson, Sampath Jayarathna (Mentor)

Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics

No abstract provided.

Point Cloud-Based Mapper For Qcd Analysis, Tareq Alghamdi, Yasir Alanazi, Manal Almaeen, Nobuo Sato, Yaohang Li

The Graduate School Posters

In many scientific applications, Inverse problems are challenging. An inverse problem is the process of inferring unknown parameters from observable ones. In this poster, we present our prototype using Point Cloud-based Variational Autoencoder mapping. Data that connects parameters to detector level events is used to train the proposed model. A point cloud is used to describe a series of events that keeps the permutation invariant property and geometric correlations of the events while being flexible with the number of events in the input. The trained Point Cloud-based Variational Autoencoder functions as an effective inverse function from detector level events to …

Insurtech And Actuarial, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar

Developing Technology Foresight: Case Study of AI in InsurTech

Questions regarding InsurTech and actuarial work.

Discovering The Traces Of Disinformation On Instagram, Haley Bragg, Michele C. Weigle (Mentor)

Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics

Disinformation, which is fabricated, misleading content spread with the intent to deceive others, is accumulating substantial engagements and reaching a vast audience on Instagram. However, the temporary nature of the platform and the security guidelines that remove malicious content make studying this disinformation a challenge. The only way to access removed content and banned accounts that are no longer on the live web is by searching the web archives. In this study, we set out to quantify the replayability and quality of past captures of Instagram accounts, specifically focusing on a group of of anti-vax content creators known as the …

Introduction To The Course, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar

Developing Technology Foresight: Case Study of AI in InsurTech

This PDF document describes the course, Developing Technology Foresight: Case Study of AI in InsurTech, and includes learning outcomes and a course outline.

Insurtech And Underwriting, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar

Developing Technology Foresight: Case Study of AI in InsurTech

Questions regarding InsurTech and underwriting work.

Insurtech And Claims, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar

Developing Technology Foresight: Case Study of AI in InsurTech

Questions related to InsurTech and claims.

Exploring The Complex Relationship Between Engineering Students Math Experiences And Identity Formation, Jill Davishahl, Joseph Brobst, Elizabeth Litzler, Andrew Klein, Sura Alqudah

Division of Research and Economic Development Faculty & Staff Publications

This paper shares the experiences of a group of S-STEM scholarship students as they progressed through their first year of undergraduate mathematics education including a math placement exam, a math focused bridge program, and calculus course(s). In addition, connections between student experiences and their math identity development were investigated with the goal of better understanding math identity formation. The authors used a mixed-methods approach to explore the math-related experiences of 12 students over the first year of participation in an NSF-funded S-STEM program. Data includes answers to select survey questions and transcripts of student focus groups. First, each student case …

Estimating Efforts For Various Activities In Agile Software Development: An Empirical Study, Lan Cao

Information Technology & Decision Sciences Faculty Publications

Effort estimation is an important practice in agile software development. The agile community believes that developers’ estimates get more accurate over time due to the cumulative effect of learning from short and frequent feedback. However, there is no empirical evidence of an improvement in estimation accuracy over time, nor have prior studies examined effort estimation in different development activities, which are associated with substantial costs. This study fills the knowledge gap in the field of software estimation in agile software development by investigating estimations across time and different development activities based on data collected from a large agile project. This …

Machine Learning In Requirements Elicitation: A Literature Review, Cheligeer Cheligeer, Jingwei Huang, Guosong Wu, Nadia Bhuiyan, Yuan Xu, Yong Zeng

Engineering Management & Systems Engineering Faculty Publications

A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation. We answer the following research questions: (1) What requirement elicitation activities are supported by ML? (2) What data sources are used to build ML-based requirement solutions? (3) What technologies, algorithms, and tools are used to build ML-based requirement elicitation? (4) How to construct an ML-based requirements elicitation method? (5) What are the available tools to support ML-based requirements elicitation methodology? Keywords …

A Probabilistic Perspective Of Human-Machine Interaction, Mustafa Canan, Mustafa Demir, Samuel Kovacic

Engineering Management & Systems Engineering Faculty Publications

Human-machine interaction (HMI) has become an essential part of the daily routine in organizations. Although the machines are designed with state-of-the-art Artificial Intelligence applications, they are limited in their ability to mimic human behavior. The human-human interaction occurs between two or more humans; when a machine replaces a human, the interaction dynamics are not the same. The results indicate that a machine that interacts with a human can increase the mental uncertainty that a human experiences. Developments in decision sciences indicate that using quantum probability theory (QPT) improves the understanding of human decision-making than merely using classical probability theory (CPT). …

On The Geometry Of The Multiplier Space Of ℓPA, Christopher Felder, Raymond Cheng

Mathematics & Statistics Faculty Publications

For p ∊ (1, ∞)\ {2}, some properties of the space M_p of multipliers on ℓ^p_A are derived. In particular, the failure of the weak parallelogram laws and the Pythagorean inequalities is demonstrated for M_p. It is also shown that extremal multipliers on the ℓ^p_A spaces are exactly the monomials, in stark contrast to the p = 2 case.

Opioid Medication Use And Blood Dna Methylation: Epigenome-Wide Association Meta-Analysis, Mikyeong Lee, Roby Joehanes, Daniel L. Mccartney, Minjung Kho, Anke Hüls, Annah B. Wyss, Chunyu Liu, Rosie M. Walker, Sharon L.R. Kardia, Thomas S. Wingo, Adam Burkholder, Jiantao Ma, Archie Campbell, Aliza P. Wingo, Tianxiao Huan, Sinjini Sikdar, Amena Keshawarz, David A. Bennett, Jennifer A. Smith, Kathryn L. Evans, Daniel Levy, Stephanie J. London

Mathematics & Statistics Faculty Publications

Aim: To identify differential methylation related to prescribed opioid use. Methods: This study examined whether blood DNA methylation, measured using Illumina arrays, differs by recent opioid medication use in four population-based cohorts. We meta-analyzed results (282 users; 10,560 nonusers) using inverse-variance weighting. Results: Differential methylation (false discovery rate <0.05) was observed at six CpGs annotated to the following genes: KIAA0226, CPLX2, TDRP, RNF38, TTC23 and GPR179. Integrative epigenomic analyses linked implicated loci to regulatory elements in blood and/or brain. Additionally, 74 CpGs were differentially methylated in males or females. Methylation at significant CpGs correlated with gene expression in blood and/or brain. Conclusion: This study identified DNA …

Examining Trends And Experiences Of The Last Four Years Of Socially Engineered Ransomware Attacks, William Seymour

Cybersecurity Undergraduate Research Showcase

This study examines and reports the trends of social engineering-based ransomware attacks over the past four years from three major technology corporations. The focus of the reports was on major threat actors and their attacks against the corporations and their clients. The data were organized chronologically by year, and prevalent or abnormal findings were shared in this report. It was found that social engineering attacks were tremendously effective. Many ransomware attacks stemmed from Phishing. Social engineering approaches allowed attackers to conduct breaches using ransomware applications like GandCrab and Ryuk. Humans are incredibly susceptible and fall for social engineering tactics- primarily …