A Machine Learning-Based Wrapper Method For Feature Selection, Damodar Patel, Amit Saxena, John Wang

Department of Information Management and Business Analytics Faculty Scholarship and Creative Works

This paper presents a two-stage feature selection scheme using machine learning techniques. In the first stage a wrapper method is adopted to select various combinations of subsets of features from the original dataset. The performance of the model is evaluated by three classifiers: K-Nearest Neighbor (KNN), Support Vector Machines (SVM), and Random Forest (RF). In the second and final stage, a sequential backward feature selection Method is applied. The proposed method is demonstrated on eighteen datasets and the average classification accuracy of eighteen datasets achieved is 89.81%, 87.55%, and 89.82% using the KNN, SVM, and RF classifiers, respectively with a …

Analyzing The Complexity Of Us Federal Debt: A Mathematical Approach, John Wang, Arti Jain, Arun Kumar Yadav, Divakar Yadav

Department of Information Management and Business Analytics Faculty Scholarship and Creative Works

The United States federal debt has witnessed a significant surge over recent decades. This study delves into inquiries regarding the persistent patterns in federal debt, key factors driving this alarming trend, and the optimal timing for implementing corrective measures to mitigate its speeding flight. Utilizing modern machine learning techniques, notably Random Forest (RF) and Support Vector Regression (SVR), alongside conventional statistical forecasting techniques, the research aims to predict future trends. It emphasizes the critical role of business analytic thinking in deciphering fiscal system-based complexities. To address the mounting challenges, these research findings underscore the urgent necessity for efficacious policies to …

A Case Study On Variations In Network Structure And Cross- Sector Alignment In Two Local Systems Serving Pregnant And Parenting Women In Recovery, Liza M. Creel, Yana Feygin, Madeline Shipley, Deborah Winders Davis, Tiffany Cole Hall, Chaly Downs, Stephanie Hoskins, Natalie Pasquenza, Scott D. Duncan

Biostatistics Faculty Publications

Objective: To describe network structure and alignment across organizations in healthcare, public health, and social services sectors that serve pregnant and parenting women with substance use disorder (SUD) in an urban and a rural community.

Data Sources and Study Settings: Two community networks, one urban and one rural with each including a residential substance use treatment program, in Kentucky during 2021.

Study Design: Social network analysis measured system collaboration and cross-sector alignment between healthcare, public health, and social services organizations, applying the Framework for Aligning Sectors. To understand the alignment and structure of each network, we measured network density overall …

Higher First 30-Day Dose Of Buprenorphine For Opioid Use Disorder Treatment Is Associated With Decreased Mortality, Feitong Lei, Michelle R. Lofwall, Jana Mcanich, Reuben Adatorwovor, Emily Slade, Patricia R. Freeman, Daniela Moga, Nabarun Dasgupta, Sharon L. Walsh, Rachel Vickers-Smith, Svetla Slavova

Biostatistics Faculty Publications

Objective: Buprenorphine is a medication for opioid use disorder that reduces mortality. This study aims to investigate the less well-understood relationship between the dose in the early stages of treatment and the subsequent risk of death.

Methods: We used Kentucky prescription monitoring data to identify adult Kentucky residents initiating transmucosal buprenorphine medication for opioid use disorder (January 2017 to November 2019). Average daily buprenorphine dose for days covered in the first 30 days of treatment was categorized as ≤8 mg, >8 to ≤16 mg, and >16 mg. Patients were followed for 365 days after the first 30 days of buprenorphine …

Fractal Surface Recovery And Self-Healing Contributed To Sustainable Superhydrophobicity: A Review, Yunfei Peng, Zhihang Ma, Xiao Wang, Junru Li, Xinlin Li, Chuanwei Zhang, Tian He, Guoqiang Li, Pengfei Zhang

Faculty Publications

The concept of superhydrophobicity has been widely used after years of theoretical and experimental exploration. Researchers have obtained materials with excellent surface superhydrophobicity for numerous areas (e.g. textiles, paints, and coatings industries), through different design and synthesis methods using low surface energy components (LSECs) and micro/nanohierarchy composite structures. However, the durability of superhydrophobic material surfaces has gradually become a prominent obstacle to restricting applications. In this paper, advances in improving the durability of superhydrophobic surfaces in the past decade are reviewed, covering different schemes for recovering fractal surfaces based on the LSECs and micro/nanocomposite structures. It also presents a balanced …

Review Of Artificial Neural Networks For Wind Turbine Fatigue Prediction, Alshannaq, Aly Mousaad Aly

Faculty Publications

Wind turbines have emerged as a prominent renewable energy source globally. Efficient monitoring and detection methods are crucial to enhance their operational effectiveness, particularly in identifying fatigue-related issues. This review focuses on leveraging artificial neural networks (ANNs) for wind turbine monitoring and fatigue detection, aiming to provide a valuable reference for researchers in this domain and related areas. Employing various ANN techniques, including General Regression Neural Network (GRNN), Support Vector Machine (SVM), Cuckoo Search Neural Network (CSNN), Backpropagation Neural Network (BPNN), Particle Swarm Optimization Artificial Neural Network (PSO-ANN), Convolutional Neural Network (CNN), and nonlinear autoregressive networks with exogenous inputs (NARX), …

Slope Unit Maker (Sumak): An Efficient And Parameter-Free Algorithm For Delineating Slope Units To Improve Landslide Modeling, Jacob B. Woodard, Benjamin B. Mirus, Nathan J. Wood, Kate E. Allstadt, Benjamin A. Leshchinsky, Matthew M. Crawford

Faculty, Staff, and Affiliated Publications--KGS

Slope units are terrain partitions bounded by drainage and divide lines. In landslide modeling, including susceptibility modeling and event-specific modeling of landslide occurrence, slope units provide several advantages over gridded units, such as better capturing terrain geometry, improved incorporation of geospatial landslide-occurrence data in different formats (e.g., point and polygon), and better accommodating the varying data accuracy and precision in landslide inventories. However, the use of slope units in regional (> 100 km²) landslide studies remains limited due, in part, to the large computational costs and/or poor reproducibility with current delineation methods. We introduce a computationally efficient algorithm …

Reliability Analysis Of End Cracking In Continuous Prestressed Concrete Girders, A. M. Okeil, S. Ghimire

Faculty Publications

Constructing bridges using precast prestressed concrete girders is extremely popular because of their durability and ease of construction. Establishing continuity between precast girders has its advantages and has been employed in many projects. It causes the development of positive restraint moments at intermediate supports as a result of long-term effects such as creep, shrinkage and thermal gradients. Prestressed concrete girder end cracking occurs if the positive restraint moments exceed the girder’s cracking moment. In this study, the probability of girder end cracking in continuous prestressed concrete bridges is assessed using structural reliability concepts. This study focuses on two bridge configurations …

Water Wave Optimization Algorithm-Based Dynamic Optimal Dispatch Considering A Day-Ahead Load Forecasting In A Microgrid, Duy C. Huynh, Loc D. Ho, Hieu M. Pham, Matthew W. Dunnigan, Corina Barbalata

Faculty Publications

A novel strategy is proposed to tackle an optimal dispatch of a microgrid in response to dynamic conditions, utilizing a water wave optimization (WWO) algorithm and considering a day-ahead load forecasting. Amongst meta-heuristic algorithms, the WWO algorithm stands out in terms of population size, parameter tuning, exploitation and exploration, convergence speed, as well as optimization mechanism. It leverages its ability to efficiently explore solution spaces and adapt to changing conditions. It is applied to the dynamic optimal dispatch of a microgrid with the uncertainty of load power considered and solved by day-ahead load forecasting. It dynamically adjusts the microgrid operation …

Pices At 32: An External Review, Eileen E. Hofmann, David Checkley, Fangli Qiao, Jörn Schmidt, Sinjae Yoo

CCPO Publications

[Introduction] The North Pacific Marine Science Organization (Pacific ICES, PICES) has been an effective voice and proponent for North Pacific marine science for more than 30 years. During this time, PICES has provided a safe and active venue for the open exchange of science, developed an international science network that includes participants from academic and government institutions, and non- and inter-governmental organizations, and has taken on leadership roles in studying North Pacific ecosystems.

Older Women Workers, The Pandemic, Employment Discrimination And Lifetime Disadvantage, Susan Bisom-Rapp

Faculty Scholarship

As a group, older women workers were among those most severely impacted by the COVID-19 crisis. Drawing from both intersectionality and cumulative disadvantage theory, the Model of Lifetime Disadvantage created by Bisom-Rapp and Sargeant helps frame the position of these workers in the labor market prior to and during the pandemic. The model also explains why and how disjointed, incremental legal interventions are unable to meet the challenge of gendered ageism, which surged during the crisis. Disasters produce impacts unevenly on individuals and communities. Older women are a diverse group, whose social position is mediated by race, ethnicity, sexual orientation …

Reconciling Calculus Students’ Understanding Of Average Across Multiple Contexts, Franklin Yu

Journal of Mathematics and Science: Collaborative Explorations

The idea of average is utilized in a variety of scenarios, yet the literature has indicated that students have multiple disconnected understandings for the concept of average. In this study, I provide an account of two students who reconciled their meanings for average by considering an average as a replacement with a constant value. This report discusses an intervention that teachers can leverage to help their students make their meanings for average coherent and conceptually based.

Full Issue

Journal of Mathematics and Science: Collaborative Explorations

No abstract provided.

Two Decades Of Supporting Excellence In Stem Through Programs That Work: A History Of High-Quality Stem Programming In The Commonwealth Of Virginia, Bill Haver, Deborah Neely-Fisher

Journal of Mathematics and Science: Collaborative Explorations

The Virginia Mathematics and Science Coalition annually recognizes effective science, technology, engineering, and mathematics (STEM) programs. The leaders of these Programs That Work receive recognition and others gain ideas to incorporate into their STEM programs. Programs That Work was initiated in March 2000 as a part of a statewide conference designed to better understand effective strategies to increase the success of women, minorities and members of other groups who had been underrepresented in STEM. Programs That Work has since expanded to include effective STEM programming for all students and teachers at all levels by recognizing school systems, colleges and universities …

Engaging Aural Skills Students With Model-Eliciting Activities, Aaron Galliher

Journal of Music Theory Pedagogy

This mixed-methods study explores how using Model-Eliciting Activities (MEAs) in an aural skills classroom can promote student motivation and engagement. MEAs require students to create models to solve progressively complex problems. As students develop and refine their models, they engage in a testing and iteration process that prioritizes learning over final outcomes, which fosters student empowerment. The specific MEA implemented was focused on music transcription skills and used the MUSIC Inventory of Motivation survey to assess student motivation and engagement, complemented by follow-up interviews that explain the results of the survey. Many students scored high on this survey and expressed …

Neurodiversity In Workplace, Jacqueline L. Zindell

M.S. in Leadership

This research paper explores the intricate relationships between neurodiverse and neurotypical individuals within the workplace. Through an exploration of the literature, the research focuses on the specific challenges faced by neurodiverse individuals, including those with conditions such as autism, attention-deficit/hyperactivity disorder (ADHD), and dyslexia. The topic of neurodiversity will provide support to leaders in navigating interactions with neurodiverse individuals and fostering inclusivity in the workplace. This research serves as a foundational step towards creating a toolbox for the workplace. A survey was conducted using Survey Monkey to gauge respondents' familiarity with the concept of Neurodiversity and to identify effective strategies …

Artificial Intelligence Is Like A Perpetual Stew, Nathan Reitinger

American University Law Review

Artificial intelligence is inescapable. It is in our phones, fridges, and most of the businesses we engage with use it to “improve” their services. From deciding on what YouTube video to watch next to driving vehicles or firing weapons, artificial intelligence is a linchpin in our society. But what is artificial intelligence? And, more importantly, why does that matter? It matters because we are currently unprepared to deal with the paradigm-shifting legal issues brought about by artificial intelligence. And without this understanding, we are nearly certainly going to make mistakes. The bright side is that artificial intelligence is not complicated. …

Coastal Forest Change And Shoreline Erosion Across A Salinity Gradient In A Micro-Tidal Estuary System, Lori E. Gorczynski, A. Reuben Wilson, Ben K. Odhiambo, Matthew C. Ricker

Earth and Environmental Sciences

Coastal Zone Soil Survey mapping provides interpretive information that can be used to increase coastal resiliency and quantify how coastal ecosystems are changing over time. North Carolina has approximately 400,500 ha of land within 500 m of the tidal coastline that is expected to undergo some degree of salinization in the next century. This study examined 33 tidal wetlands in the Albemarle–Pamlico Sound along a salinity gradient to provide a coastal zone mapping framework to quantify shoreline change rates. The primary ecosystems evaluated include intact tidal forested wetlands (average water salinity, 0.15–1.61 ppt), degraded “ghost forest” wetlands (3.51–8.28 ppt), and …

Investigating Tuberculosis Dynamics Using Surveillance Data And Statistical Modeling: Studies In Three High Burden Settings, Melanie Hunter Chitwood

Yale Graduate School of Arts and Sciences Dissertations

Tuberculosis (TB) is a leading cause of death from infectious disease globally, despite the availability of effective antibiotic treatment. Control efforts focus on the rapid diagnosis and treatment of individuals with TB, which reduces both disease-related morbidity and mortality and onward transmission. In addition to passive case finding, the World Health Organization recommends active case finding for high-risk individuals and their contacts. Expanding these activities to populations in which there is evidence of recent transmission may be a suitable strategy to reduce TB burden, but identifying these populations is a persistent challenge. Statistical analyses, informed by high quality surveillance data, …

A Class Of Game-Theoretic And Fokker-Planck Optimal Control Frameworks In Colon And Esophageal Cancer, Mesfer Alajmi Phd

Mathematics Dissertations - Archive

In this dissertation, we first present a new stochastic framework for parameter estimation and uncertainty quantification in colon cancer-induced immune responses. A stochastic process that captures the system's inherent randomness determines the dynamics of colon cancer. The stochastic framework is based on the Fokker-Planck equation, which represents the evolution of the probability density function corresponding to the stochastic process. We formulate an optimization problem that takes individual patient data with randomness present and solves it to obtain the unknown parameters corresponding to the individual tumor characteristics. Furthermore, we perform a sensitivity analysis of the optimal parameter set to identify the …

Batch Culture Models Of The Murine Gut Microbiome & The Impact Of Simple Dormancy On Dormancy-Capable Microorganisms Models, Ana C. Mendez

Mathematics Dissertations - Archive

The proposed mathematical biology research utilizes mathematical models to gain insight into biological systems. These systems of ordinary differential equations model diverse topics, ranging from gut microbiomes to harmful algal blooms. A complete stability analysis, supporting phase plane portraits, bifurcation diagrams, and numerical simulations will accompany the models presented. In Chapter 2, the murine gut microbiome is modeled to match laboratory experiments in the literature. In these experiments, mice eat plasmid-carrying “donor” bacteria and naturally carry plasmid-free “resident” bacteria in their gut. The models aim to capture the behavior of plasmids, donor bacteria, and resident bacteria. Chapter 3 explores dormancy …

Safe Human-Robot Collaboration: A Systematic Review Of Risk Assessment Methods With Ai Integration And Standardization Considerations, Morteza Jalali Alenjareghi, Samira Keivanpour, Yuvin Adnarain Chinniah, Sabrina Jocelyn, Abdelhak Oulmane

Revues de littérature, synthèses de connaissances

Improving risk assessment (RA) for human-robot collaboration (HRC) is crucial, given challenges in existing RA tools. For example, simulation and testing RA tools lack realism due to simplified models, limited dynamic realism, and sensor integration constraints. This study explores how Artificial Intelligence (AI) can enhance risk assessment methods. Using a systematic literature review, the study analyzes three risk assessment methods: PFMEA, HAZOP, and FTA to which AI has been integrated. Results highlight strengths (e.g., systematic process failure identification, thorough hazard identification, complex system modeling) and limitations (e.g., limited coverage of human-robot dynamics, reliance on historical data, adaptability constraints, resource intensity, …

Centers Of N-Degree Poncelet Circles, Georgia Corbett

Honors Theses

Given a circle inscribed in a polygon inscribed in the unit circle, if one connects all the vertices with line segments we get a family of circles called a package of Poncelet circles, due to its connection to a theorem of Poncelet. We are interested in where the centers of the Poncelet circles can be. Specifically, we have shown that if one of the circles in the Poncelet package is centered at 0, then all of the circles must be centered at 0 as well. This was proven by Spitkovsky and Wegert in 2021 using elliptic integrals but we …

Synergetic Effects Of Democracy And Economic Development On Income Inequality And The Role Of Relative Political Capacity, Nazif Sali

CGU Theses & Dissertations

Diving into the complex dynamics of income inequality, this dissertation studies the multifaceted relationships between democracy, economic development, and inequality, placing a spotlight on the mediating influence of Relative Political Capacity (RPC). Uncovering the pivotal role of RPC as democracies advance and economies progress, this research navigates the contours of income inequality. By dissecting distinct sub-samples of OECD and non-OECD countries, nuanced insights surface. Employing robust methodologies such as ordinary least squares regressions and fixed effects analysis, I argue that targeted policies addressing inequality can not only foster inclusive economic growth but also fortify the foundations of democratic institutions. As …

Applications And Analysis Of Nlp Deep Learning Models For Antibiotic's Side Effects Classifications, An Ly

CGU Theses & Dissertations

I introduce a novel recursive modification to the classical Goemans-Williamson MaxCut algorithm, offering improved performance in vectorized data clustering tasks. Focusing on the clustering of medical publications, I suggest to employ recursive iterations in conjunction with a dimension relaxation method to enhance density of clustering results. Furthermore, I propose a new vectorization technique for articles, leveraging conditional probabilities for more effective clustering. I believe that these methods will provide advantages in both computational efficiency and clustering accuracy. I will analyze the effectiveness of recursive iterations and higher-dimensional generalizations of the GWA in the hopes of achieving more accurate dissimilarity-based clustering. …

Self-Quenching Of Carbon Monoxide In The Presence Of Noble Gases, Madeline V. Hinkle

Honors Theses

Precise rate coefficients for the vibrational relaxation pathways of CO(v)-CO in the presence of Ar and Kr have been determined through the work of this thesis. This work was motivated by the need to find a more cost-effective alternative to using xenon as a bath gas, which has increased significantly in price in the past few years. Similar experiments within this lab at Bucknell have been conducted in the past using argon, which can be used in the same manner as xenon but comes at a much lower price, but the experiments yielded inferior results compared to those using xenon. …

Computational Study Of Proton Transfer At Transition Metal Hydrides, Megan Ford

Honors Theses

Energy storage in the bonds of common chemical feedstocks is an attractive solution to the unreliability of wind and solar power due to its long term efficiency and easy recoverability. Energy is stored by reducing chemicals like ammonia, formic acid, and hydrogen, the reaction of which is dependent on a catalyst. To catalyze the reaction, the catalyst undergoes a slow proton transfer (PT) step to form what is known as a metal hydride. The sluggish kinetics of this step lower the effectiveness of the catalyst, and therefore must be better understood in order to improve the efficiency of energy storage …

Our Journey To Valuing Computational Thinking As A Tool To Address Inequity And Cultivate Well-Being In Urban Education, Malgorzata Powietrzynska Ph.D., Linda Noble

Publications and Research

An Exploratory Study Of The Influence Of Celta/Tesol Certification On Non-Native English Teachers’ Practical Teaching Knowledge, Yousef Mousavi, Peyman Rajabi, Hamid Reza Khalaji

PASAA

The demand for proficient English language teachers has increased significantly in non-native English-speaking countries, emphasizing the need for effective teacher training programs. This study investigated the influence of the CELTA/TESOL certification on non-native English teachers’ practical teaching knowledge and efficacy perceptions in an English as a Foreign Language (EFL) setting. A qualitative approach was employed, and data were collected via semistructured interviews. The participants comprised eight Iranian EFL teachers who completed the CELTA/TESOL certification program. Before the certification course, the teachers exhibited diverse teaching approaches, emphasizing teacher-centered methods. Their confidence levels varied, and they faced challenges in classroom management and …

An Investigation Of Global Englishes-Informed Assessment Perceptions And Practices Among Secondary School Teachers In Thailand, Pongpol Suansri, Supong Tangkiengsirisin

PASAA

No abstract provided.