Physical Sciences and Mathematics Commons^™

Exploring Post-Covid-19 Health Effects And Features With Advanced Machine Learning Techniques, Muhammad N. Islam, Md S. Islam, Nahid H. Shourav, Iftiaqur Rahman, Faiz A. Faisal, Md M. Islam, Iqbal H. Sarker

Research outputs 2022 to 2026

COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a range of outcomes including recovery, continued health issues, and the loss of life. Among those who have recovered, many experience negative health effects, particularly influenced by demographic factors such as gender and age, as well as physiological and neurological factors like sleep patterns, emotional states, anxiety, and memory. This research aims to explore various health factors affecting different demographic profiles and establish significant correlations among physiological and neurological factors in the post-COVID-19 state. To achieve these objectives, we have identified the post-COVID-19 health factors and …

Machine Learning As A Tool For Early Detection: A Focus On Late-Stage Colorectal Cancer Across Socioeconomic Spectrums, Hadiza Galadima, Rexford Anson-Dwamena, Ashley Johnson, Ghalib Bello, Georges Adunlin, James Blando

Community & Environmental Health Faculty Publications

Purpose: To assess the efficacy of various machine learning (ML) algorithms in predicting late-stage colorectal cancer (CRC) diagnoses against the backdrop of socio-economic and regional healthcare disparities. Methods: An innovative theoretical framework was developed to integrate individual- and census tract-level social determinants of health (SDOH) with sociodemographic factors. A comparative analysis of the ML models was conducted using key performance metrics such as AUC-ROC to evaluate their predictive accuracy. Spatio-temporal analysis was used to identify disparities in late-stage CRC diagnosis probabilities. Results: Gradient boosting emerged as the superior model, with the top predictors for late-stage CRC diagnosis being anatomic site, …

Last Millennium Hurricane Activity Linked To Endogenous Climate Variability, Wenchang Yang, Elizabeth Wallace, Gabriel A. Vecchi, Jeffrey P. Donnelly, Julien Emile-Geay, Gregory J. Hakim, Larry W. Horowitz, Richard M. Sullivan, Robert Tardif, Peter J. Van Hengstum, Tyler S. Winkler

OES Faculty Publications

Despite increased Atlantic hurricane risk, projected trends in hurricane frequency in the warming climate are still highly uncertain, mainly due to short instrumental record that limits our understanding of hurricane activity and its relationship to climate. Here we extend the record to the last millennium using two independent estimates: a reconstruction from sedimentary paleohurricane records and a statistical model of hurricane activity using sea surface temperatures (SSTs). We find statistically significant agreement between the two estimates and the late 20th century hurricane frequency is within the range seen over the past millennium. Numerical simulations using a hurricane-permitting climate model suggest …

Large-Scale Identification And Analysis Of Factors Impacting Simple Bug Resolution Times In Open Source Software Repositories, Elia Eiroa-Lledo, Rao Hamza Ali, Gabriela Pinto, Jillian Anderson, Erik Linstead

Engineering Faculty Articles and Research

One of the most prominent issues the ever-growing open-source software community faces is the abundance of buggy code. Well-established version control systems and repository hosting services such as GitHub and Maven provide a checks-and-balances structure to minimize the amount of buggy code introduced. Although these platforms are effective in mitigating the problem, it still remains. To further the efforts toward a more effective and quicker response to bugs, we must understand the factors that affect the time it takes to fix one. We apply a custom traversal algorithm to commits made for open source repositories to determine when “simple stupid …

Tenvr: Matlab-Based Toolbox For Environmental Research, Aleksandar I. Goranov, Rachel L. Sleighter, Dobromir A. Yordanov, Patrick G. Hatcher

Chemistry & Biochemistry Faculty Publications

With the advancements in science and technology, datasets become larger and more multivariate, which warrants the need for programming tools for fast data processing and multivariate statistical analysis. Here, the MATLAB-based Toolbox for Environmental Research "TEnvR" (pronounced "ten-ver") is introduced. This novel toolbox includes 44 open-source codes for automated data analysis from a multitude of techniques, such as ultraviolet-visible, fluorescence, and nuclear magnetic resonance spectroscopies, as well as from ultrahigh resolution mass spectrometry. Provided are codes for processing data (e.g., spectral corrections, formula assignment), visualization of figures, calculation of metrics, multivariate statistics, and automated work-up of large datasets. TEnvR allows …

Opioid Use Disorder Prediction Using Machine Learning Of Fmri Data, A. Temtam, Liangsuo Ma, F. Gerard Moeller, M. S. Sadique, K. M. Iftekharuddin, Khan M. Iftekharuddin (Ed.), Weijie Chen (Ed.)

Electrical & Computer Engineering Faculty Publications

According to the Centers for Disease Control and Prevention (CDC) more than 932,000 people in the US have died since 1999 from a drug overdose. Just about 75% of drug overdose deaths in 2020 involved Opioid, which suggests that the US is in an Opioid overdose epidemic. Identifying individuals likely to develop Opioid use disorder (OUD) can help public health in planning effective prevention, intervention, drug overdose and recovery policies. Further, a better understanding of prediction of overdose leading to the neurobiology of OUD may lead to new therapeutics. In recent years, very limited work has been done using statistical …

Prediction Of Rapid Early Progression And Survival Risk With Pre-Radiation Mri In Who Grade 4 Glioma Patients, Walia Farzana, Mustafa M. Basree, Norou Diawara, Zeina Shboul, Sagel Dubey, Marie M. Lockheart, Mohamed Hamza, Joshua D. Palmer, Khan Iftekharuddin

Electrical & Computer Engineering Faculty Publications

Rapid early progression (REP) has been defined as increased nodular enhancement at the border of the resection cavity, the appearance of new lesions outside the resection cavity, or increased enhancement of the residual disease after surgery and before radiation. Patients with REP have worse survival compared to patients without REP (non-REP). Therefore, a reliable method for differentiating REP from non-REP is hypothesized to assist in personlized treatment planning. A potential approach is to use the radiomics and fractal texture features extracted from brain tumors to characterize morphological and physiological properties. We propose a random sampling-based ensemble classification model. The proposed …

Relationship Between Dike Injection And B-Value For Volcanic Earthquake Swarms, Allen F. Glazner, Stephen R. Mcnutt

School of Geosciences Faculty and Staff Publications

Dike swarms are the fossil remains of regions of the crust that have undergone repeated magma injections. Volcanic earthquake swarms and geodetic measurements are, at least in part, a record of active injection of fluids (water, gas, or magma) into fractures. Here, we link these two ways of observing magmatic systems by noting that dike thicknesses and earthquake magnitudes share similar scaling parameters. In the Jurassic Independence dike swarm of eastern California median dike thickness is ∼1 m, similar to other swarms worldwide, but glacially polished exposures reveal that a typical dike comprises a number of dikelets that are lognormally …

Exploring The Relationship Between Mandatory Helmet Use Regulations And Adult Cyclists’ Behavior In California Using Hybrid Machine Learning Models, Fatemeh Davoudi Kakhki, Maria Chierichetti

Mineta Transportation Institute

In California, bike fatalities increased by 8.1% from 2015 to 2016. Even though the benefits of wearing helmets in protecting cyclists against trauma in cycling crash has been determined, the use of helmets is still limited, and there is opposition against mandatory helmet use, particularly for adults. Therefore, exploring perceptions of adult cyclists regarding mandatory helmet use is a key element in understanding cyclists’ behavior, and determining the impact of mandatory helmet use on their cycling rate. The goal of this research is to identify sociodemographic characteristics and cycling behaviors that are associated with the use and non-use of bicycle …

Research Artifact: The Potential Of Meta-Maintenance On Github, Hideaki Hata, Raula Kula, Takashi Ishio, Christoph Treude

Research Collection School Of Computing and Information Systems

This is a research artifact for the paper “Same File, Different Changes: The Potential of Meta-Maintenance on GitHub”. This artifact is a data repository including a list of studied 32,007 repositories on GitHub, a list of targeted 401,610,677 files, the results of the qualitative analysis for RQ2, RQ3, and RQ4, the results of the quantitative analysis for RQ5, and survey material for RQ6. The purpose of this artifact is enabling researchers to replicate our mixed-methods results of the paper, and to reuse the results of our exploratory study for further software engineering research. This research artifact is available at https://github.com/NAIST-SE/MetaMaintenancePotential …

Same File, Different Changes: The Potential Of Meta-Maintenance On Github, Hideaki Hata, Raula Kula, Takashi Ishio, Christoph Treude

Research Collection School Of Computing and Information Systems

Online collaboration platforms such as GitHub have provided software developers with the ability to easily reuse and share code between repositories. With clone-and-own and forking becoming prevalent, maintaining these shared files is important, especially for keeping the most up-to-date version of reused code. Different to related work, we propose the concept of meta-maintenance-i.e., tracking how the same files evolve in different repositories with the aim to provide useful maintenance opportunities to those files. We conduct an exploratory study by analyzing repositories from seven different programming languages to explore the potential of meta-maintenance. Our results indicate that a majority of active …

Working Children On Java Island 2017, Yuniarti

English Language Institute

Children's wellbeing has currently become a global concern as many of them are engaged in the labor force. A small area estimation (SAE) technique, EBLUP under Fey Herriot model, is employed to reveal their number in regencies of Java Island. Statistics have been disaggregated by geographical location (urban/rural) and gender. These statistics are required by the government as the basis for policy making.

To What Extent Can Mine Rehabilitation Restore Recreational Use Of Forest Land? Learning From 50 Years Of Practice In Southwest Australia, Josianne Claudia Sales Rosa, Davide Geneletti, Angus Morrison-Saunders, Luis Enrique Sánchez, Michael Hughes

Research outputs 2014 to 2021

When mining affects natural or semi-natural ecosystems such as forests, rehabilitation often aims at restoring biodiversity. However, to what extent does rehabilitation also restore cultural ecosystem services? This paper investigates the perception of two groups of recreationists that use rehabilitated bauxite mine areas in southwest Australia, bushwalkers and mountain bikers. The area has been continuously mined and progressively rehabilitated for over 50 years. Research was developed through: (i) mapping the distribution of recreation trails, mined areas and rehabilitated areas; (ii) conducting in-depth interviews with recreationists regarding perceptions and usage of forest areas and; (iii) an online survey to gauge forest …

Estuarine Dissolved Organic Carbon Flux From Space: With Application To Chesapeake And Delaware Bays, Sergio R. Signorini, Antonio Mannino, Marjorie A.M. Friedrichs, Pierre St-Laurent, John Wilkin, Aboozar Tabatabai, Raymond G. Najjar, Eileen E. Hofmann, Fei Da, Hanqin Tian, Yuanzhi Yao

CCPO Publications

This study uses a neural network model trained with in situ data, combined with satellite data and hydrodynamic model products, to compute the daily estuarine export of dissolved organic carbon (DOC) at the mouths of Chesapeake Bay (CB) and Delaware Bay (DB) from 2007 to 2011. Both bays show large flux variability with highest fluxes in spring and lowest in fall as well as interannual flux variability (0.18 and 0.27 Tg C/year in 2008 and 2010 for CB; 0.04 and 0.09 Tg C/year in 2008 and 2011 for DB). Based on previous estimates of total organic carbon (TOCexp) exported by …

Demonstrating The Efficacy Of The Health Sciences And Technology Academy: Using Archival Standardized Test Scores To Analyze An Ost College-Preparatory Program For Underserved Youth, Feon Smith, Sherron Mckendall, Ann Chester, Bethany Hornbeck, Alan Mckendall

Faculty & Staff Scholarship

To combat educational and health disparities, out-of-school-time (OST) STEM enrichment programs provide services to underserved youth to encourage them to pursue college and health careers. This article describes a study conducted to determine if the Health Sciences and Technology Academy (HSTA) program participants who receive year-round educational interventions to prepare them for STEM and health sciences majors performed better on the West Virginia Educational Standards Test (WESTEST2) than non-participants. This study provides descriptive and inferential statistics, specifically one-way ANOVAs with one-to-one matching based on grade level, gender, race, and GPA at the end of the 8th grade year for 336 …

Identification Of Biologically Essential Nodes Via Determinative Power In Logical Models Of Cellular Processes, Trevor Pentzien, Bhanwar L. Puniya, Tomáš Helikar, Mihaela Teodora Matache

Mathematics Faculty Publications

A variety of biological networks can bemodeled as logical or Boolean networks. However, a simplification of the reality to binary states of the nodes does not ease the difficulty of analyzing the dynamics of large, complex networks, such as signal transduction networks, due to the exponential dependence of the state space on the number of nodes. This paper considers a recently introduced method for finding a fairly small subnetwork, representing a collection of nodes that determine the states of most other nodes with a reasonable level of entropy. The subnetwork contains the most determinative nodes that yield the highest information …

Probing High-Momentum Protons And Neutrons In Neutron-Rich Nuclei, M. Duer, C. L. A. S. Collaboration, O. Hen, E. Piasetzky, H. Hakobyan, L. B. Weistein, M. Braverman, Gerard P. Gilfoyle, Et. Al.

Physics Faculty Publications

The atomic nucleus is one of the densest and most complex quantum-mechanical systems in nature. Nuclei account for nearly all the mass of the visible Universe. The properties of individual nucleons (protons and neutrons) in nuclei can be probed by scattering a high-energy particle from the nucleus and detecting this particle after it scatters, often also detecting an additional knocked-out proton. Analysis of electron- and proton-scattering experiments suggests that some nucleons in nuclei form close-proximity neutron–proton pairs with high nucleon momentum, greater than the nuclear Fermi momentum. However, how excess neutrons in neutron-rich nuclei form such close-proximity pairs remains unclear. …

The Role Of Surface Vorticity During Unsteady Separation, Matthew Scott Melius, Karen Mulleners, Raul Bayoan Cal

Mechanical and Materials Engineering Faculty Publications and Presentations

Unsteady flow separation in rotationally augmented flow fields plays a significant role in a variety of fundamental flows. Through the use of time-resolved particle image velocimetry, vorticity accumulation and vortex shedding during unsteady separation over a three-dimensional airfoil are examined. The results of the study describe the critical role of surface vorticity accumulation during unsteady separation and reattachment. Through evaluation of the unsteady characteristics of the shear layer, it is demonstrated that the buildup and shedding of surface vorticity directly influence the dynamic changes of the separation point location. The quantitative characterization of surface vorticity and shear layer stability enables …

Load Model Verification, Validation And Calibration Framework By Statistical Analysis On Field Data, Xiangqing Jiao, Yuan Liao, Thai Nguyen

Electrical and Computer Engineering Faculty Publications

Accurate load models are critical for power system analysis and operation. A large amount of research work has been done on load modeling. Most of the existing research focuses on developing load models, while little has been done on developing formal load model verification and validation (V&V) methodologies or procedures. Most of the existing load model validation is based on qualitative rather than quantitative analysis. In addition, not all aspects of model V&V problem have been addressed by the existing approaches. To complement the existing methods, this paper proposes a novel load model verification and validation framework that can systematically …

Anomalydetection: Implementation Of Augmented Network Log Anomaly Detection Procedures, Robert J. Gutierrez, Bradley C. Boehmke, Kenneth W. Bauer, Cade M. Saie, Trevor J. Bihl

Faculty Publications

As the number of cyber-attacks continues to grow on a daily basis, so does the delay in threat detection. For instance, in 2015, the Office of Personnel Management discovered that approximately 21.5 million individual records of Federal employees and contractors had been stolen. On average, the time between an attack and its discovery is more than 200 days. In the case of the OPM breach, the attack had been going on for almost a year. Currently, cyber analysts inspect numerous potential incidents on a daily basis, but have neither the time nor the resources available to perform such a task. …

An Investigation Of The Accuracy Of Parallel Analysis For Determining The Number Of Factors In A Factor Analysis, Mandy Matsumoto

Mahurin Honors College Capstone Experience/Thesis Projects

Exploratory factor analysis is an analytic technique used to determine the number of factors in a set of data (usually items on a questionnaire) for which the factor structure has not been previously analyzed. Parallel analysis (PA) is a technique used to determine the number of factors in a factor analysis. There are a number of factors that affect the results of a PA: the choice of the eigenvalue percentile, the strength of the factor loadings, the number of variables, and the sample size of the study. Although PA is the most accurate method to date to determine which factors …

Lake Michigan Wind Assessment Analysis, 2012 And 2013, Charles R. Standridge Ph.D., David Zeitler, Aaron Clark, Tyson Spoelma, Erik E. Nordman, T. Arnold Boezaart, Jim Edmonson, Graham Howe, Guy Meadows, Aline Cotel, Frank Marsik

Peer Reviewed Articles

A study was conducted to address the wind energy potential over Lake Michigan to support a commercial wind farm. Lake Michigan is an inland sea in the upper mid-western United States. A laser wind sensor mounted on a floating platform was located at the mid-lake plateau in 2012 and about 10.5 kilometers from the eastern shoreline near Muskegon Michigan in 2013. Range gate heights for the laser wind sensor were centered at 75, 90, 105, 125, 150, and 175 meters. Wind speed and direction were measured once each second and aggregated into 10 minute averages. The two sample t-test and …

Recommendation To Use Exact P-Values In Biomarker Discovery Research, Margaret Sullivan Pepe, Matthew F. Buas, Christopher I. Li, Garnet L. Anderson

UW Biostatistics Working Paper Series

Background: In biomarker discovery studies, markers are ranked for validation using P-values. Standard P-value calculations use normal approximations that may not be valid for small P-values and small sample sizes common in discovery research.

Methods: We compared exact P-values, valid by definition, with normal and logit-normal approximations in a simulated study of 40 cases and 160 controls. The key measure of biomarker performance was sensitivity at 90% specificity. Data for 3000 uninformative markers and 30 true markers were generated randomly, with 10 replications of the simulation. We also analyzed real data on 2371 antibody array markers …

Using Remote Sensing Data To Predict The Spread Of Mosquito Borne Disease, Mary Ellen O'Donnell, Erika Podest

STAR Program Research Presentations

There is interest in how environmental variables derived from satellite data such as temperature, vegetation cover, and precipitation correlate to vector borne disease occurrence such as malaria and dengue fever. This study will be carried out using a decision tree based open source software called Random Forests to find correlations between the remote sensing variables and mosquito abundance. Software will be written in C# to take large amounts of data from the NASA satellite database and automatically format it for the Random Forest Software input. Correlations found, using Random Forests, between disease incidence and the variables can be used as …

Mining Branching-Time Scenarios, Dirk Fahland, David Lo, Shahar Maoz

Research Collection School Of Computing and Information Systems

Specification mining extracts candidate specification from existing systems, to be used for downstream tasks such as testing and verification. Specifically, we are interested in the extraction of behavior models from execution traces. In this paper we introduce mining of branching-time scenarios in the form of existential, conditional Live Sequence Charts, using a statistical data-mining algorithm. We show the power of branching scenarios to reveal alternative scenario-based behaviors, which could not be mined by previous approaches. The work contrasts and complements previous works on mining linear-time scenarios. An implementation and evaluation over execution trace sets recorded from several real-world applications shows …

The Bench Scientist's Guide To Statistical Analysis Of Rna-Seq Data, Craig R. Yendrek, Elizabeth A. Ainsworth, Jyothi Thimmapuram

Cyber Center Publications

RNA sequencing (RNA-Seq) is emerging as a highly accurate method to quantify transcript abundance. However, analyses of the large data sets obtained by sequencing the entire transcriptome of organisms have generally been performed by bioinformatics specialists. Here we provide a step-by-step guide and outline a strategy using currently available statistical tools that results in a conservative list of differentially expressed genes. We also discuss potential sources of error in RNA-Seq analysis that could alter interpretation of global changes in gene expression.

On The Fundamentals Of Stochastic Spatial Modeling And Analysis Of Wireless Networks And Its Impact To Channel Losses, Mouhamed Abdulla

Publications and Scholarship

With the rapid evolution of wireless networking, it becomes vital to ensure transmission reliability, enhanced connectivity, and efficient resource utilization. One possible pathway for gaining insight into these critical requirements would be to explore the spatial geometry of the network. However, tractably characterizing the actual position of nodes for large wireless networks (LWNs) is technically unfeasible. Thus, stochastical spatial modeling is commonly considered for emulating the random pattern of mobile users. As a result, the concept of random geometry is gaining attention in the field of cellular systems in order to analytically extract hidden features and properties useful for assessing …

Being Seen: An Art Historical And Statistical Analysis Of Feminized Worship In Early Modern Rome, Olivia J. Belote

History Honors Projects

Female saints in early Christianity found their place in public veneration often through violent means, martyrdom. These saints, while publicly suffering in the imitation of Christ, were the original agents to navigate the gendered hierarchy within the religion. Female saints created an avenue for later female worshippers to understand Christianity on a strictly feminine level. Through the frescoed depictions of these female saints in 18 churches throughout Rome, this paper historically and statistically analyzes how the artistic representations of female saints added to or created a space for feminized worship.

The Minimization Of The Screen Bias From Ancient Western Mediterranean Air Temperature Records: An Exploratory Statistical Analysis, Manola Brunet, Jesús Asin, Javier Sigró, Manuel Bañón, Francisco García, Enric Aguilar, Juan Esteban Palenzuela, Thomas C. Peterson, Phil Jones

United States Department of Commerce: Staff Publications

Here we present an exploratory statistical analysis aimed at the minimization of the ‘screen bias’ from affected ancient air temperature time series over the Western Mediterranean. Our approach lies in the statistical analysis of about 6 years of daily paired temperature observations taken using the ancient Montsouri shelter and the modern Stevenson screen for daily maximum (T_x) and minimum (T_n) temperature data recorded at two experimental sites: the meteorological gardens of La Coruña and Murcia, Spain (locations under the influence of the Oceanic/Atlantic/Galician and Mediterranean arid and semi-arid climate types, respectively), where ongoing field trials have …

Comprehensive Evaluation Of Association Measures For Fault Localization, Lucia Lucia, David Lo, Lingxiao Jiang, Aditya Budi

Research Collection School Of Computing and Information Systems

In statistics and data mining communities, there have been many measures proposed to gauge the strength of association between two variables of interest, such as odds ratio, confidence, Yule-Y, Yule-Q, Kappa, and gini index. These association measures have been used in various domains, for example, to evaluate whether a particular medical practice is associated positively to a cure of a disease or whether a particular marketing strategy is associated positively to an increase in revenue, etc. This paper models the problem of locating faults as association between the execution or non-execution of particular program elements with failures. There have been …