Digital Commons Network^™

Essays On Economics Of The Family, Yinlin Dai

All Dissertations

In the first chapter, I explore the role of gender discrimination in children’s investments by parents. I specifically examine whether parents in urban China devote more household resources, specifically education, health, and total expenditures, to girls than to boys. The empirical literature has extensively examined trends in the sex ratio at birth and the effect of gender on the extensive margin of fertility. Much less of the existing literature has explored the impact of gender on the intensive margin of parental inputs mainly because of lack of individual child-level data, especially in urban China. This is an important area for …

Teacher Enactment Of The Geospatial Inquiry Cycle In Classrooms Following Scaled Up Professional Learning And Development, Brooke A. Whitworth, Lori Rubino-Hare, Francis Boateng, Anne Hamlin, Nena E. Bloom, Eric Nolan

Publications

The current study examined the effects of a nationally scaled up Professional Learning and Development (PLD) model on teachers’ classroom implementation of the Geospatial Inquiry instructional framework. Geospatial Inquiry is defined as: asking and answering a research question through the analysis and communication of data that is linked to a geographic location on, above, or near Earth. These data are often represented visually via maps and explored with geospatial technologies. It also examined the relationships between Geospatial Inquiry Teacher Workshop (GITW) implementation and teacher implementation of the Geospatial Inquiry Cycle. Situated cognition provided a theoretical framework for the design, development, …

Using Knowledgeable Agents Of The Digital And Data Feminism To Uncover Social Identities In The #Blackgirlmagic Twitter Community, Golnaz Arastoopour Irgens

Publications

Online spaces have the capacity to be powerful informal learning and identity development spaces for marginalized communities. However, there is still much work to be done to uncover these complex social identities using ethical big data analyses. In this study, I draw on the theory of Knowledgeable Agents of the Digital, data feminism, and critical reflexivity practices to engage with a #blackgirlmagic Twitter dataset from 2016 to 2019. Using Epistemic Network Analysis, findings suggest that the #blackgirlmagic community self-defined their social identities around Black beauty, academic/professional accomplishments, and social justice. Because the women and girls of #blackgirlmagic were agentive in …

Annotated Bibliography Of Research In The Teaching Of English, Lisa Ortmann, Anne Crampton, Erin Stutelberg, Richard Beach, Keitha-Gail Martin-Kerr, Debra Peterson, Anna Schick, Bridget Kelley, Charles Lambert, Tracey Pyscher, Leanne Robinson, Andrea Gambino, Jeff Share, Stephanie M. Madison

Publications

Since 2003, RTE has published the annual “Annotated Bibliography of Research in the Teaching of English,” a list of curated and annotated works reviewed and selected by a large group of dedicated educator-scholars in our field. The goal of the annual bibliography is to offer a synthesis of the research published in the area of English language arts within the past year for RTE readers’ consideration. Abstracted citations and those featured in the “Other Related Research” sections were published, either in print or online, between June 2020 and June 2021. The bibliography is divided into nine sections, with some changes …

Talking Is Thinking: Supporting Student Sense-Making Through Discourse And Assessment, Whitney Jackson, Lauren A. Simpson, Brooke A. Whitworth

Publications

Learning in the classroom is highly influenced by the experiences a teacher plans for students. Concerned that students were not achieving adequate conceptual knowledge during traditional undergraduate physics courses, the authors used the Making Sense of SCIENCE curriculum to tailor a course for 21 pre-service elementary teachers at the University of Mississippi. The organization of instruction, facilitation practices, discussion opportunities, and assessment of content are all important aspects of the learning process. We found the changes we implemented significantly impacted the learning of students enrolled in this course.

2022, Camp Research Forum Book Of Abstracts, American Camp Association

ACA National Camp Research Forum Abstracts

This book includes 19 abstracts that will be presented at the 2022 American Camp Association (ACA) Research Forum to be held during the ACA annual conference from February 8-11, 2022 in Portland, OR. This year’s Camp Research Forum features a panel session on managing camps for justice, equity, diversity, and inclusion, moderated by Victor Rivera. Abstracts have been grouped into similar areas and will be verbally presented in four sessions.

Variational Bayesian Dropout With A Gaussian Prior For Recurrent Neural Networks Application In Rainfall–Runoff Modeling, S. Sadeghi Tabas, S. Samadi

Open Access Publishing Fund

Recurrent neural networks (RNNs) are a class of artificial neural networks capable of learning complicated nonlinear relationships and functions from a set of data. Catchment scale daily rainfall–runoff relationship is a nonlinear and sequential process that can potentially benefit from these intelligent algorithms. However, RNNs are perceived as being difficult to parameterize, thus translating into significant epistemic (lack of knowledge about a physical system) and aleatory (inherent randomness in a physical system) uncertainties in modeling. The current study investigates a variational Bayesian dropout (or Monte Carlo dropout (MC-dropout)) as a diagnostic approach to the RNNs evaluation that is able to …

Designing With And For Youth: A Participatory Design Research Approach For Critical Machine Learning Education, Golnaz Arastoopour Irgens, Ibrahim Adisa, Cinamon Bailey, Hazel Vega Quesada

Publications

As big data algorithm usage becomes more ubiquitous, it will become critical for all young people, particularly those from historically marginalized populations, to have a deep understanding of data science that empowers them to enact change in their local communities and globally. In this study, we explore the concept of critical machine learning: integrating machine learning knowledge content with social, ethical, and political effects of algorithms. We modified an intergenerational participatory design approach known as cooperative inquiry to co-design a critical machine learning educational program with and for youth ages 9 - 13 in two after-school centers in the southern …

Clemson University’S Teacher Learning Progression Program: Personalized Advanced Credentials For Teachers, Luke J. Rapa, Jeff C. Marshall, Stephanie M. Madison, Christopher Flathmann, Bart Knijnenburg, Nathan J. Mcneese

Publications

This chapter provides an overview of Clemson University's Teacher Learning Progression program, which offers participating middle school science, technology, engineering, and/or mathematics (STEM) teachers with personalized advanced credentials. In contrast to typical professional development (PD) approaches, this program identifies individualized pathways for PD based on teachers' unique interests and needs and offers PD options through the use of a “recommender system”—a system providing context-specific recommendations to guide teachers toward the identification of preferred PD pathways and content. In this chapter, the authors introduce the program and highlight (1) the data collection and instrumentation needed to make personalized PD recommendations, (2) …

The Pauline Tradition, Benjamin L. White

Publications

No abstract provided.

Tunable Blood Shunt For Neonates With Complex Congenital Heart Defects, Ellen Garver, Christopher B. Rodell, Kristen Shema, Krianthan Govender, Samantha E. Cassel, Bryan Ferrick, Gabriella Kupsho, Ethan Kung, Kara L. Spiller, Randy Stevens, Amy L. Throckmorton

Publications

Despite advancements in procedures and patient care, mortality rates for neonatal recipients of the Norwood procedure, a palliation for single ventricle congenital malformations, remain high due to the use of a fixed-diameter blood shunt. In this study, a new geometrically tunable blood shunt was investigated to address limitations of the current treatment paradigm (e.g., Modified Blalock-Taussig Shunt) by allowing for controlled modulation of blood flow through the shunt to accommodate physiological changes due to the patient’s growth. First, mathematical and computational cardiovascular models were established to investigate the hemodynamic requirements of growing neonatal patients with shunts and to inform design …

A Comparison Of Drill And Broadcast Planting Methods Forbiomass Production Of Two Legume Cover Crops, Ricardo St Aime, Enoch Noh, William C. Bridges, Sruthi Narayanan

Open Access Publishing Fund

The effects of drill and broadcast planting methods on cover crop biomass production depend on various environmental and operational factors. We investigated whether drilling and broadcasting result in different amounts of biomass production by crimson clover (Trifolium incarnatum L.) and hairy vetch (Vicia villosa Roth) in the upstate of South Carolina, and results vary when seeding rates are increased by 50% from the standard value (22.4 kg ha−1). Field trials were conducted during the fall–winter of 2019–2020 (season one) and 2020–2021 (season two) at the Piedmont Research and Education Center in Pendleton, SC, USA. Cover crop (hairy vetch, crimson clover), …

Application Of Image Processing And Convolutional Neural Networks For Flood Image Classification And Semantic Segmentation, Jaku Rabinder Rakshit Pally

All Theses

Floods are among the most destructive natural hazards that affect millions of people across the world leading to severe loss of life and damage to property, critical infrastructure, and the environment. Deep learning algorithms are exceptionally valuable tools for collecting and analyzing the catastrophic readiness and countless actionable flood data. Convolutional neural networks (CNNs) are one form of deep learning algorithms widely used in computer vision which can be used to study flood images and assign learnable weights and biases to various objects in the image. Here, we leveraged and discussed how connected vision systems can be used to embed …

Clemson Commencement Program, December 2021, Clemson University

Clemson Commencement Programs

No abstract provided.

A Human-Centric System For Symbolic Reasoning About Code, Megan Fowler

All Dissertations

While testing and tracing on specific input values are useful starting points for students to understand program behavior, ultimately students need to be able to reason rigorously and logically about the correctness of their code on all inputs without having to run the code. Symbolic reasoning is reasoning abstractly about code using arbitrary symbolic input values, as opposed to specific concrete inputs.

The overarching goal of this research is to help students learn symbolic reasoning, beginning with code containing simple assertions as a foundation and proceeding to code involving data abstractions and loop invariants. Toward achieving this goal, this research …

Parametric Study Of Orthogonal Pantographic Lattice With Non-Linear Torsional Resistance At Pivots, Mahendra Singh Bisht

All Theses

Pantographic lattices are cellular solids comprised of continuous beam fibers intersecting at periodically spaced pivots. The pivots are simulated in the discrete finite element beam model as torsional springs with varied torsional stiffness across orders of magnitude. An important functional performance feature of pantographic lattices is their ability to undergo large deformation without inducing large stresses at the pivots. There is a need for predictive models of this nonlinear behavior. In this study, parameter studies on the order of magnitude and nonlinear material behavior of the torsional stiffness at the pivots, combined with and without nonlinear geometric beam kinematic behavior …

Soil Moisture And Light Conditions Impact Digital And Visual Soil Color Assessments, Isabella Hill

All Theses

Determining soil color has traditionally been done visually, but inaccuracies with this method have been documented, including disagreement in evaluators, to differences in physical color books. Determining Munsell soil color in the field is also subject to environmental conditions, including soil water content (SWC) and light intensity. New digital spectral technology designed for determining soil color may offer accurate assessments regardless of human inaccuracies and environmental conditions. This research aimed to assess if visual observations differed from digital measurements of Munsell soil color as well as, the impacts of SWC and light on visual observations and digital measurements of soil …

Using Transfer Learning To Train Individualized Models To Detect Eating Episodes From Daily Wrist Motion, Cole Hilton Younginer

All Theses

This thesis considers the problem of detecting periods of eating in free-living conditions by analyzing wrist motion data collected using sensors embedded within a typical smartwatch. Previous work by our research group included the collection of a dataset containing 354 days of recorded wrist motion data from 351 different people (approximately one day of data per person) [42]. A machine learning model was then trained to classify this wrist motion data as either eating or non-eating [40]. We refer to this model as the group model. Subsequent work in our research group collected approximately ten days of data each for …

Reinforcement Learning Policy Gradient Methods For Reservoir Operation Management And Control, Sadegh Sadeghi Tabas

All Theses

Changes in demand, various hydrological inputs, and environmental stressors are among issues that water managers and policymakers face on a regular basis. These concerns have sparked interest in applying different techniques to determine reservoir operation policy and improve reservoir release decisions. As the resolution of the analysis rises, it becomes more difficult to effectively represent a real-world system using traditional approaches for determining the best reservoir operation policy. One of the challenges is the “curse of dimensionality,” which occurs when the discretization of the state and action spaces becomes finer or when more state or action variables are taken into …

Product Lifecycle Management - Application Of Patterning Methods To Gas Turbine Blades And Creation Of Learning Materials, David Procopio

All Theses

To compete in the global marketplace, companies need to embrace virtual design and manufacturing methods. Product Lifecycle Management (PLM) embodies both the workflow processes and tools to bring forth products from conception to design to fabrication to service to decommissioning, and to eventual recycling. In response to the growing demand for engineers and technicians with these critical skills, colleges and universities should introduce these virtual tools through seminars, software workshops, and computer laboratory sessions. Some of the opportunities in the PLM Center at Clemson University include short courses on PLM practices, focused software training sessions, hands-on exploration activities, and research …

Development And Validation Of An Analytical Modeling Tool For Solar Borehole Heat Exchangers, Adam Ornelles

All Theses

Current numerical modeling solutions used for subsurface heat flow, such as the Berkeley TOUGH codes, are often difficult to use and time-consuming compared to analytical modeling methods. However, current analytical modeling methods for subsurface heat flow and groundwater cannot accurately model the subsurface in 3 dimensions, a feature paramount to the planning and installation of thermal borehole heat exchangers used in environmental remediation.

This research developed a novel 3-dimensional analytical modeling tool for solar-powered borehole heat exchangers. The analytical modeling tool can plan thermal remediation systems while being more straightforward to operate than current numerical modeling software. By creating a …

Studies In Consumption And Production Of South Carolina Aquaculture Products, David Cheplick

All Theses

Market demand for seafood products among South Carolina (SC) consumers has led to increased aquaculture production as a means of supporting the seafood supply chain across the state. Our objective is broken into four distinct parts; (1) understanding consumer’s preferences and perceptions of seafood, (2) calculating their willingness to pay (WTP) for seafood products available in SC using attributes of sustainability and locality; and (3) gathering production metric and anecdotal data from SC oyster growers. Previous research assessing the market channels of seafood in South Carolina is compared to survey results. Respondents indicated that taste and quality were the most …

Covid Response: Iterative Model Development In The Deployment Of Hand Sanitation Stations At A Large Public University, Tyler Obrien

All Theses

This study illustrates the significance of iterative model development using the deployment of hand sanitizer stations in buildings at Clemson University as a case study. The COVID-19 problem affected Clemson University, a major institution, in several ways requiring adaptations to existing policies and procedures to take place. Following guidelines provided by the Centers for Disease and Control (CDC), the university implemented several new strategies including placing hand sanitizer stations in several buildings on campus in order to try and mitigate the transmission of the virus. This study focuses on learning how the initial decision-making took place to then design a …

A Parallelized And Layered Model For The Shallow-Water Equations, Alexander Stevens

All Theses

An energy- and enstrophy-conserving and optimally-dispersive numerical scheme for the shallow- water equations is accelerated through implementation in the GPU environment. Previous research showed the viability of the numerical scheme under standard shallow-water test cases, but was limited in applications by computation time constraints. We overcome these limitations by paral- lelizing the numerical computation in the GPU environment. We also extend the capabilities of the implementation to support not just a single shallow-water layer, but multiple. These improvements significantly expand the range of tests that can be used to exercise the model, and enable better understanding of the power of …

Integrating Degradation Forecasting And Abatement Framework Into Advanced Distribution Management System, Huu Phuong Hoang

All Dissertations

Future distribution grids are expected to face an increasing penetration of heterogeneous distributed energy resources (DERs) and electric vehicles (EVs). This landscape change will pose challenges to the control and management of distribution grids because of the variability of renewable energy resources and EV charging. In addition, multiple DERs dispersed over networks can also challenge the grid operation and maintenance as various DERs at various locations are needed to be monitored and managed. However, customers will not be content with reductions in power quality, reliability, economy, safety, or security. To enhance the effectiveness of grid control and management, future grids …

Intelligent Resource Prediction For Hpc And Scientific Workflows, Benjamin Shealy

All Dissertations

Scientific workflows and high-performance computing (HPC) platforms are critically important to modern scientific research. In order to perform scientific experiments at scale, domain scientists must have knowledge and expertise in software and hardware systems that are highly complex and rapidly evolving. While computational expertise will be essential for domain scientists going forward, any tools or practices that reduce this burden for domain scientists will greatly increase the rate of scientific discoveries. One challenge that exists for domain scientists today is knowing the resource usage patterns of an application for the purpose of resource provisioning. A tool that accurately estimates these …

Cloud Based Collaborative Road Surface Monitoring Using Deep Learning And Smartphones, Akshatha Ramesh

All Theses

Road accidents are one of the major causes of death in the United states of America. Vast majority of everyday deaths in US occur by road accidents. And poorly managed roads are one of the main reasons for it. Safety is the ultimate priority. Safety in this aspect can be ensured only with proper management of roads on a regular basis. Proper maintenance of road conditions can not only ensure safety but also increase rider comfort, fuel economy and provide better driving experience. Traditional methods of surveying is very time consuming, expensive, and require lot of human efforts. Existing methods …

Real-Time Battery Energy Storage Scheduling For An Educational Building, Armien Harrell

All Theses

Special electricity rates are offered by some utilities to incentivize certain energy consumption behaviors in an attempt to garner a cost effective demand profile to service. One area of concern for a utility is the maximum demand of a building during the times of day when electricity usage is typically at its peak. Regulated utilities are required to have the capacity to meet the electrical demand of customers, though, the peak demand of customers can oftentimes be relatively brief. Therefore, it is not cost effective for a utility to have generation units online to only cover momentary peak demands. Electricity …

Determining States Of Movement In Humans Using Minimally Processed Eeg Signals And Various Classification Methods, Maurice Barnett

All Theses

Electroencephalography (EEG) is a non-invasive technique used in both clinical and research settings to record neuronal signaling in the brain. The location of an EEG signal as well as the frequencies at which its neuronal constituents fire correlate with behavioral tasks, including discrete states of motor activity. Due to the number of channels and fine temporal resolution of EEG, a dense, high-dimensional dataset is collected. Transcranial direct current stimulation (tDCS) is a treatment that has been suggested to improve motor functions of Parkinson’s disease and chronic stroke patients when stimulation occurs during a motor task. tDCS is commonly administered without …

Tradespace Exploration Of A Uav Conceptual Design Using Model-Based Systems Engineering, Ayan Srivastava

All Theses

The objective of this research is to apply model-based systems engineering approaches to the conceptual design of unmanned aerial vehicles. This is accomplished by evaluating the models of aircraft performance, extracting input and output parameters from the models, creating chains of models, and implementing the models in the MATLAB programming language. By following this process, it is possible to identify the global parameters that remain constant across models, the shared input parameters, the dependencies between models, and the feedback loops with the systems models.

The models are currently implemented in two files using Microsoft MS Excel, one is focused on …