Physical Sciences and Mathematics Commons^™

Monarch Science Observer, Volume 9, College Of Sciences, Old Dominion University

College of Sciences Newsletter

Spring 2021 issue of Monarch Science Observer, ODU College of Sciences Newsletter.

Do Users Care About Ad's Performance Costs? Exploring The Effects Of The Performance Costs Of In-App Ads On User Experience, Cuiyun Gao, Jichuan Zeng, Federica Sarro, David Lo, Irwin King, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Context: In-app advertising is the primary source of revenue for many mobile apps. The cost of advertising (ad cost) is non-negligible for app developers to ensure a good user experience and continuous profits. Previous studies mainly focus on addressing the hidden performance costs generated by ads, including consumption of memory, CPU, data traffic, and battery. However, there is no research on analyzing users’ perceptions of ads’ performance costs to our knowledge.Objective: To fill this gap and better understand the effects of performance costs of in-app ads on user experience, we conduct a study on analyzing user concerns about ads’ performance …

Machine Learning Based Approaches Towards Robust Android Malware Detection, Jiayun Xu

Dissertations and Theses Collection (Open Access)

The Android platform is becoming increasingly popular and numerous applications (apps) have been developed by organizations to meet the ever increasing market demand over years. Naturally, security and privacy concerns on Android apps have grabbed considerable attention from both academic and industrial
communities. Many approaches have been proposed to detect Android malware in different ways so far, and most of them produce satisfactory performance under the given Android environment settings and labelled samples. However, existing approaches suffer the following robustness problems:

In many Android malware detection approaches, specific API calls are used to build the feature sets, and their feature …

Disparities In Meeting Uspstf Breast, Cervical, And Colorectal Cancer Screening Guidelines Among Women In The United States, Gabriel A. Benavidez, Anja Zgodic, Whitney E. Zahnd, Jan Marie Eberth

Faculty Publications

Introduction

Many sociodemographic factors affect women’s ability to meet cancer screening guidelines. Our objective was to examine which sociodemographic characteristics were associated with women meeting US Preventive Services Task Force (USPSTF) guidelines for breast, cervical, and colorectal cancer screening.

Methods

We used 2018 Behavioral Risk Factor Surveillance System data to examine the association between sociodemographic variables, such as race/ethnicity, rurality, education, and insurance status, and self-reported cancer screening for breast, cervical, and colorectal cancer. We used multivariable log-binomial regression models to estimate adjusted prevalence ratios and 95% CIs.

Results

Overall, the proportion of women meeting USPSTF guidelines for breast, cervical, …

Reconstructing Surface Water Carbonate Ion Concentration Changes In The Eastern Equatorial Pacific Across Glacial Transitions, Lenzie Gail Ward

OES Theses and Dissertations

Today, the eastern equatorial Pacific (EEP) plays a critical role in the global CO₂ budget as a major source of CO₂ to the atmosphere, but recent studies suggest the region may shift to a sink for atmospheric CO₂ under different climate states. Here, I focus on two transitional periods, the last deglaciation (25 kyr to present) and last glaciation (the Marine Isotope Stage (MIS) 5a-4 transition, 96 to 60 kyr), to investigate how the carbon system in the EEP responds to major climate changes. I measured B/Ca ratios in the planktic foraminifera Globigerina bulloides from core MV1014-17JC …

Feature Extraction And Design In Deep Learning Models, Daniel Perez

Computational Modeling & Simulation Engineering Theses & Dissertations

The selection and computation of meaningful features is critical for developing good deep learning methods. This dissertation demonstrates how focusing on this process can significantly improve the results of learning-based approaches. Specifically, this dissertation presents a series of different studies in which feature extraction and design was a significant factor for obtaining effective results. The first two studies are a content-based image retrieval system (CBIR) and a seagrass quantification study in which deep learning models were used to extract meaningful high-level features that significantly increased the performance of the approaches. Secondly, a method for change detection is proposed where the …

Predictions Of Knee Joint Contact Forces Using Only Kinematic Inputs With A Recurrent Neural Network, Kaileigh Elisabeth Estler

Human Movement Studies & Special Education Theses & Dissertations

BACKGROUND: Knee joint contact (bone on bone) forces are commonly estimated using surrogate measures such as external knee adduction moments (with limited success) or musculoskeletal modeling (more successful). Despite its capabilities, modeling is not optimal for clinicians or persons with limited experience and knowledge. Therefore, the purpose of this study was to design a novel prediction method for knee joint contact forces that is equal or more accurate than modeling, yet simplistic in terms of required inputs. METHODS: This study included all six subjects’ (71.3±6.5kg, 1.7±0.1m) data from the opensource “Grand Challenge” datasets (simtk.org) and two subjects from the "CAMS" …

Understanding The Effect Of Internal Climate Variability On 20th Century Indian Ocean Sea Level: Results From Newly Reconstructed Sea Level Data, Praveen Kumar

OES Theses and Dissertations

Densely populated low-lying coastal zones of countries that border the Indian Ocean are at risk due to sea level rise. However, sea level change in the Indian Ocean is poorly understood primarily due to short and sparse tide gauge observations. Although satellite altimetry provides accurate basin-wide sea level measurements, trends computed from its relatively short (~27-year) data record are heavily influenced by interannual to multi-decadal variability. To accurately project future Indian Ocean sea level trends using altimeter data it is imperative that trends associated with fluctuating internal variability (interannual-decadal) be identified and extracted, which in turn requires long (~100-year) data. …

Biophysical Characterization Of The Par-4 Tumor Suppressor: Evidence Of Structure Outside The Coiled Coil Domain And Interactions With Platinum Chemotherapeutics, Andrea Megan Clark

Chemistry & Biochemistry Theses & Dissertations

Prostate apoptosis response-4 (Par-4) is an apoptosis-inducing tumor suppressor protein. Full-length Par-4 has previously been shown to be a predominantly intrinsically disordered protein (IDP) under neutral conditions, with significant regular secondary structure evident only within the C-terminal coiled coil domain. However, IDPs can gain ordered structure through the process of induced folding, which often occurs under non-neutral conditions. Previous work has shown that the Par-4 leucine zipper, which is a subset of the C-terminal coiled coil domain, is disordered under neutral conditions, but forms a dimeric coiled coil at acidic pH. Increase in ionic strength was also shown to increase …

Computational And Experimental Investigation Into The Determinants Of Protein Structure, Folding, And Stability In The Β-Grasp Superfamily, John T. Bedford Ii

Chemistry & Biochemistry Theses & Dissertations

Elucidating the mechanisms of protein folding and unfolding is one of the greatest scientific challenges in basic science. The overarching goal is to predict three-dimensional structures from their amino acid sequences. Understanding the determinants of protein folding and stability can be facilitated through the study of evolutionarily related but diverse proteins. Insights can also be gained through the study of proteins from extremophiles that may more closely resemble the primordial proteins. In this doctoral research, three aims were accomplished to characterize the structure, folding and unfolding behavior within the β-grasp superfamily. We propose that the determinants of structure, stability, and …

Investigating Pre-Service Teachers’ Perceptions Of The Virginia Computer Science Standards Of Learning: A Qualitative Multiple Case Study, Valerie Sledd Taylor

Educational Leadership & Workforce Development Theses & Dissertations

Computer science education is being recognized globally as necessary to better prepare students in all grade levels, K-12, for future success. As a result of this focus on computer science education in the United States and around the world, there is an increased demand for highly qualified teachers with content and pedagogical knowledge to successfully support student learning. As a result, there is a call to include and improve the computer science training offered to pre-service teachers in their educator preparation programs from methods courses to practicum and student teaching experiences. Thus, it is important to understand how pre-service teachers …

Use Of Anthraquinone Derivatives And Methods Of Efficient Syntheses, Alex Crespo

Senior Honors Theses

While the bromination of aromatic compounds is a well-researched topic, AQ and hydroxy substituted AQ derivatives, with two carbonyl groups acting as strong deactivators for electrophilic substitution, are notoriously difficult to brominate.¹¹ Although there are well defined ways to brominate an AQ or hydroxy substituted AQ dating back to 1921,¹² in order to synthesize more complex AQ derivatives, a method for halogenating AQ derivatives already bonded to more complicated or unstable functional groups is needed in order for the compound to carry out desirable activities. This represents an area of great need in research. The purpose of this …

Stability Of Low Crested And Submerged Breakwaters: A Reanalysis And Model Development, Christopher P. Burgess

Civil & Environmental Engineering Theses & Dissertations

Low-crested and submerged structures (LCS) play an integral part in the stabilization of shorelines for recreational purposes, yet there are a plethora of empirical models and gaps in the understanding of their stability and damage progression. The objectives were: i) to evaluate the present formulae, ii) explore variable importance, iii) formulate a stability model, iv) extend the current datasets and v) explore a new model for LCS. The literature points to an increasing understanding of the initiation of damage of LCS and recent exploration of the shear stress-induced erosion (van Rijn, 2019). Assessment of two existing models (Kramer, 2006 and …

Neurodevelopment Correlates With Gut Microbiota In A Cross-Sectional Analysis Of Children At 3 Years Of Age In Rural China, Sarah E. Rothenberg, Qiurong Chen, Yanfen Nong, Hua Nong, Eva P. Trinh, Fred J. Biasini, Jihong Liu, Xiaoyun Zeng, Yunfeng Zou, Fengxiu Ouyang, Susan A. Korrick

Faculty Publications

We investigated cross-sectional associations between children’s neurodevelopment and their gut microbiota composition. Study children (36 months of age) lived in rural China (n = 46). Neurodevelopment was assessed using the Bayley Scales of Infant Development, 2nd Edition, yielding the Mental Developmental Index (MDI) and Psychomotor Developmental Index (PDI). Children's gut microbiota was assessed using 16S rRNA gene profiling. Microbial diversity was characterized using alpha diversity patterns. Additionally, 3 coabundance factors were determined for the 25 most abundant taxa. Multivariable linear regression models were constructed to examine the relationships between Bayley scores (MDI and PDI) and children's gut microbiota. In adjusted …

Vims Ferry Pier Ambient Water Monitoring Data, Salinity And Temperature, Daily Summary 1947-2003, Gary F. Anderson

Data

Bulk water parameters of Temperature and Salinity were measured at the VIMS Ferry Pier from 1947 to 2003. Initial methods were undocumented but likely automated with an instrument and chart recorder since the data consists of a daily high and low measurement from which a mean value was derived.

Beginning in 1971 an automated instrument recorded continuously from which 2-hour measurements were made and daily minimum and maxima were derived. Beginning in 1986 an Inter-Ocean CTD instrument placed at mid-depth was interfaced to a digital data logger (Campbell Scientific CRJ) that recorded data every six minutes, resulting in 240 measurements …

Data-Limited Domain Adaptation And Transfer Learning For Learning Latent Expression Labels Of Child Facial Expression Images, Megan Witherow, Winston Shields, Manar Samad, Khan Iftekharuddin

College of Engineering & Technology (Batten) Posters

While state-of-the-art deep learning models have demonstrated success in adult facial expression classification by leveraging large, labeled datasets, labeled data for child facial expression classification is limited. Due to differences in facial morphology and development in child and adult faces, deep learning models trained on adult data do not generalize well to child data. Recent deep domain adaptation approaches have improved the generalizability of models trained on a source domain to a target domain with few labeled samples. We propose that incorporating steps of deep transfer learning, e.g. weights initialization from the pre-trained source model and freezing model layers, may …

Analysis Of Reading Patterns Of Scientific Literature Using Eye-Tracking Measures, Gavindya Jayawardena, Sampath Jayarathna, Jian Wu

College of Sciences Posters

Scientific literature is crucial for researchers to inspire novel research ideas and find solutions to various problems. This study presents a reading task for novice researchers using eye-tracking measures. The study focused on the scan paths, fixation, and pupil dilation frequency of the participants. In this study, 3 participants were asked to read a pre-selected research paper while wearing an eye-tracking device (PupilLabs Core 200Hz). We specified sections of the research paper as areas of interest (title, abstract, motivation, methodology, conclusion)to analyze the eye-movements. Then we extracted eye-movements data from the recordings and processed them using an eye-movement processing pipeline. …

Nanopore Guided Regional Assembly, Eleni Adam, Desh Ranjan, Harold Riethman

College of Sciences Posters

The telomeres are the “caps” of the chromosomes and their vital role is to protect them. Possible telomere dysfunction caused by telomere rearrangements can be fatal for the cell and result in age-related diseases, including cancer. The telomeres and subtelomeres are regions that are hard to investigate. The current technology cannot provide their complete sequence, instead the DNA is given in multiple pieces. Current methods of assembling the pieces of these regions are not accurate enough due to the region’s high variability and complex repeated patterns. We propose a hybrid assembly method, the NPGREAT, which utilizes two of the latest …

Design, Commissioning And Preliminary Results Of A Magnetic Field Scanning System For Superconducting Radiofrequency Cavities, Ishwari Parajuli, Jeffrey Nice, Gianluigi Ciovati, William Clemens, Jean Delayen, Alex Gurevich

College of Sciences Posters

Superconducting radiofrequency (SRF) cavities are one of the building blocks of modern particle accelerators. Such cavities are typically made of bulk niobium, operate at liquid helium temperature (2 - 4 K) and have some of the highest quality factors found in Nature. One of the leading source of residual losses, which limits the quality factor in SRF cavities, is trapped magnetic flux from either residual ambient magnetic field or thermoelectric currents. The flux trapping mechanism depends on different niobium surface preparations and cool-down conditions. Suitable diagnostic tools are not yet available to study the effects of such conditions on magnetic …

Combine Cryo-Em Density Map And Residue Contact For Protein Structure Prediction: A Case Study, Maytha Alshammari, Jing He

College of Sciences Posters

Although atomic structures have been determined directly from cryo-EM density maps with high resolutions, current structure determination methods for medium resolution (5 to 10 Å) cryo-EM maps are limited by the availability of structure templates. Secondary structure traces are lines detected from a cryo-EM density map for α-helices and β-strands of a protein. A topology of secondary structures defines the mapping between a set of sequence segments in 1D and a set of traces of secondary structures in 3D. In order to enhance the accuracy in ranking secondary structure topologies, we propose a method that combines three sources of information …

Seasonal Variability In Diazotroph Abundance And Gene Expression At A Coastal N2 Fixation Hotspot (Outer Banks, Nc), Katherine Crider, Corday Selden, Kimberly Powell, P. Dreux Chappell

College of Sciences Posters

Marine microbial dinitrogen (N₂) fixation, the conversion of gaseous N₂ to bioavailable species, is the primary source of new oceanic nitrogen (N). N is present in nucleic acids, amino acids, and proteins, and is essential to all life. Long considered to be a primarily oligotrophic ocean process, significant N₂ fixation rates have recently been observed in coastal environments, including along the Cape Hatteras front. To see if elevated N₂ fixation was a persistent feature in this region, N₂ fixation rates and N₂ fixer (diazotroph) abundance and gene expression were investigated through roughly monthly …

2021 April - Tennessee Monthly Climate Report, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Monthly Report

No abstract provided.

Laser Cooling Of Antihydrogen Atoms, C. J. Baker, W. Bertsche, A. Capra, C. Carruth, C. L. Cesar, M. Charlton, A. Christensen, R. Collister, A. Cridland Mathad, S. Eriksson, A. Evans, N. Evetts, J. Fajans, T. Friesen, M. C. Fujiwara, D. R. Gill, P. Grandemange, P. Granum, J. S. Hangst, W. N. Hardy, M. E. Hayden, D. Hodgkinson, E. D. Hunter, C. A. Isaac, M. A. Johnson, J. M. Jones, S. A. Jones, S. Jonsell, A. Khramov, P. Knapp, L. Kurchaninov, N. Madsen, D. Maxwell, J. T. K. Mckenna, S. Menary, J. M. Michan, T. Momose, P. S. Mullan, K. Olchanski, A. Olin, J. Peszka, A. Powell, P. Pusa, C. O. Rasmussen, F. Robicheaux, R. L. Sacramento, M. Sameed, E. Sarid, D. M. Silveira, D, M. Starko, C. So, G. Stutter, Timothy Tharp, A. Thibeault, R. I. Thompson, D. P. Van Der Werf, J. S. Wurtele

Physics Faculty Research and Publications

The photon—the quantum excitation of the electromagnetic field—is massless but carries momentum. A photon can therefore exert a force on an object upon collision¹. Slowing the translational motion of atoms and ions by application of such a force^2,3, known as laser cooling, was first demonstrated 40 years ago^4,5. It revolutionized atomic physics over the following decades^6,7,8, and it is now a workhorse in many fields, including studies on quantum degenerate gases, quantum information, atomic clocks and tests of fundamental physics. However, this technique has not yet been applied to antimatter. Here we …

The Economic And Environmental Effects Of Recycling Plastic In South Carolina, Sophia Gouhin

Senior Theses

The state of South Carolina generated 4,809,041 tons of municipal solid waste during the fiscal year of 2019 (July 1, 2018 to June 30, 2019). During this same period, the state maintained an average municipal solid waste recycling rate of 28.2% (Toomey, 2019b). This thesis gives an in-depth look in to the economic and environmental effects of recycling, specifically plastic, in South Carolina. I have researched and analyzed the process, capabilities, and impact of recycling plastic in South Carolina. This includes all seven types of plastic as classified by their chemical makeup. In addition, I surveyed South Carolina residents to …

Multi-Domain Dialogue State Tracking With Recursive Inference, Lizi Liao, Tongyao Zhu, Le Hong Long, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Multi-domain dialogue state tracking (DST) is a critical component for monitoring user goals during the course of an interaction. Existing approaches have relied on dialogue history indiscriminately or updated on the most recent turns incrementally. However, in spite of modeling it based on fixed ontology or open vocabulary, the former setting violates the interactive and progressing nature of dialogue, while the later easily gets affected by the error accumulation conundrum. Here, we propose a Recursive Inference mechanism (ReInf) to resolve DST in multi-domain scenarios that call for more robust and accurate tracking capability. Specifically, our agent reversely reviews the dialogue …

Tour: Dynamic Topic And Sentiment Analysis Of User Reviews For Assisting App Release, Tianyi Yang, Cuiyun Gao, Jingya Zang, David Lo, Michael R. Lyu

Research Collection School Of Computing and Information Systems

App reviews deliver user opinions and emerging issues (e.g., new bugs) about the app releases. Due to the dynamic nature of app reviews, topics and sentiment of the reviews would change along with app release versions. Although several studies have focused on summarizing user opinions by analyzing user sentiment towards app features, no practical tool is released. The large quantity of reviews and noise words also necessitates an automated tool for monitoring user reviews. In this paper, we introduce TOUR for dynamic TOpic and sentiment analysis of User Reviews. TOUR is able to (i) detect and summarize emerging app issues …

Escape From An Echo Chamber, Kuan-Chieh Lo, Shih-Chieh Dai, Aiping Xiong, Jing Jiang, Lun-Wei Ku

Research Collection School Of Computing and Information Systems

An echo chamber effect refers to the phenomena that online users revealed selective exposure and ideological segregation on political issues. Prior studies indicate the connection between the spread of misinformation and online echo chambers. In this paper, to help users escape from an echo chamber, we propose a novel news-analysis platform that provides a panoramic view of stances towards a particular event from different news media sources. Moreover, to help users better recognize the stances of news sources which published these news articles, we adopt a news stance classification model to categorize their stances into “agree”, “disagree”, “discuss”, or “unrelated” …

Homophily Outlier Detection In Non-Iid Categorical Data, Guansong Pang, Longbing Cao, Ling Chen

Research Collection School Of Computing and Information Systems

Most of existing outlier detection methods assume that the outlier factors (i.e., outlierness scoring measures) of data entities (e.g., feature values and data objects) are Independent and Identically Distributed (IID). This assumption does not hold in real-world applications where the outlierness of different entities is dependent on each other and/or taken from different probability distributions (non-IID). This may lead to the failure of detecting important outliers that are too subtle to be identified without considering the non-IID nature. The issue is even intensified in more challenging contexts, e.g., high-dimensional data with many noisy features. This work introduces a novel outlier …

Breaking Neural Reasoning Architectures With Metamorphic Relation-Based Adversarial Examples, Alvin Chan, Lei Ma, Felix Juefei-Xu, Yew-Soon Ong, Xiaofei Xie, Minhui Xue, Yang Liu

Research Collection School Of Computing and Information Systems

The ability to read, reason, and infer lies at the heart of neural reasoning architectures. After all, the ability to perform logical reasoning over language remains a coveted goal of Artificial Intelligence. To this end, models such as the Turing-complete differentiable neural computer (DNC) boast of real logical reasoning capabilities, along with the ability to reason beyond simple surface-level matching. In this brief, we propose the first probe into DNC's logical reasoning capabilities with a focus on text-based question answering (QA). More concretely, we propose a conceptually simple but effective adversarial attack based on metamorphic relations. Our proposed adversarial attack …

Dram Failure Prediction In Aiops: Empirical Evaluation, Challenges And Opportunities, Zhiyue Wu, Hongzuo Xu, Guansong Pang, Fengyuan Yu, Yijie Wang, Songlei Jian, Yongjun Wang

Research Collection School Of Computing and Information Systems

DRAM failure prediction is a vital task in AIOps, which is crucial to maintain the reliability and sustainable service of large-scale data centers. However, limited work has been done on DRAM failure prediction mainly due to the lack of public available datasets. This paper presents a comprehensive empirical evaluation of diverse machine learning techniques for DRAM failure prediction using a large-scale multisource dataset, including more than three millions of records of kernel, address, and mcelog data, provided by Alibaba Cloud through PAKDD 2021 competition. Particularly, we first formulate the problem as a multiclass classification task and exhaustively evaluate seven popular/stateof-the-art …