Physical Sciences and Mathematics Commons^™

Supplementary Files For "Impact Of Snow Accumulation On Structural Integrity: Present And Future Perspectives", Kenneth Pomeyie, Brennan Bean

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Evaluating the impact of weight exerted by settled snow (i.e., snow load) on structures poses numerous statistical challenges, including missing data, biased distribution parameters, and the influence of climate change. This dissertation aims to address challenges related to the use both direct and indirect measurements of snow load (or equivalently, snow water equivalent), as well as the anticipated impact of climate change on future extreme snow loads. The first paper within this dissertation investigates short-term snow loads by comparing various techniques for estimating extreme values of short-term snow accumulations. Additionally, the first paper includes a comparative analysis of short-term and …

Minimal Separating Sets In Surfaces, Christopher Nelson Aagaard

Dissertations and Theses

Given a connected topolgical space X, we say that L ⊆ X is a minimal separating set if removing L from X gives a disconnected surface, butremoving any proper subset of L leaves the surface connected. We classify which embeddings of topological graphs are minimal separating in an orientable surface X with genus g, and construct a computer program to compute the number of such embeddings, and the number of topological graphs which admit such an embedding for g ≤ 5.

Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Insufficiently Reclaimed Sites Belle Of Butte (Bres No. 8 & Ur-39) Remedial Action Work Plan (Rawp), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

09.09.2024 Orsp Connect, Liz Williamson

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NSF Sessions on Phase 1 ISBIR/STTR Proposals

Assessing Prevalence Of Blood Parasites And Ranaviruses In Hong Kong Freshwater Turtles, Julia Leung

Lingnan Theses (MPhil & PhD)

Blood parasites and ranaviruses are pathogens that impact freshwater turtles worldwide. Given that native turtle species in Hong Kong are already at a high risk of extinction, their survival becomes even more threatened in the event of a disease outbreak. However, prevalence of these pathogens among the native population in Hong Kong remains unstudied.

In this study, I aim to (1) obtain baseline prevalence data of blood parasites and ranaviruses in Hong Kong freshwater turtles, (2) compare different methods for detecting blood parasites and ranaviruses, (3) evaluate the applicability of using blood parasites as a wildlife forensic tool, assess and …

Optimization And Machine Learning Techniques For Analyzing Spatiotemporal Dynamics, Dipak Prasad Dulal

All ETDs from UAB

In a numerical context, the tensor CP decomposition challenge can be reformulated into a series of least squares subproblems, which can be addressed using the renowned Alternating Least Square algorithm (ALS). The ALS algorithm is often characterized by a 'swamp phenomenon' that slows down its convergence, especially when dealing with extensive data structures. One of the goals of our research is to find ways to speed up the convergence of the ALS algorithm. This thesis discusses the use of Canonical Polyadic decomposition techniques and machine learning models in various data-driven domains, such as COVID-19, higher-order images and videos (e.g. RGB …

Effect Of Correlation Boundaries On Collinearity And Bias In Ordinary Least Square Regression, Yumo Xue

All ETDs from UAB

Linear regression (LM) stands as one of the prevailing methods used to assess the association between a dependent variable and independent variables, typically estimated using ordinary least squares. However, this approach frequently faces obstacles when applied to biomedical data, due to the issue of correlated independent variables (collinearity). Collinearity is a potential issue in observational studies, where researchers might omit less significant correlated variables from their model. This is often guided by the rule of thumb that a Variance Inflation Factor (VIF) of 10 indicates severe collinearity. Our hypothesis is that relying on this rule of thumb is arbitrary, and …

Symmetric Laminations Of Degree D And Identity Return Triangles In Degree 3, Thomas Sirna

All ETDs from UAB

Laminations of the unit disc were introduced by Thurston in the 1980s as a tool to study the Julia sets and the parameter spaces of complex polynomials. In general, a lamination will be the unit disc D (considered as a subset of the complex plane C, with the boundary of D denoted by S) along with a collection of chords in D that can only intersect at their endpoints on S. We call the chords of a lamination leaves. In most situations we also consider a map σd : S → S on the endpoints of the leaves defined by …

A Visual Guide To Balancing Latency And Bandwidth In Mpi All-To-All, Naeris Netterville

All ETDs from UAB

The complex nature of parallel algorithms in the Message Passing Interface (MPI) standard challenges the ability of trivially visualizing them. Within MPI libaries (e.g., MPICH, Open-MPI), there are many collectives that offer different solutions for communicating data between processes. The collective MPI_Alltoall uses various techniques such as the spread-out and Bruck algorithms to have processes transfer data between all processes. Each technique within MPI_Alltoall is best suited for different scenarios. The spread-out algorithm uses a linear number of iterations, in process count P, while the Bruck algorithm is logarithmic. The Bruck algorithm transfers more data overall, but with fewer communication …

Radiotherapy Dose Calculation Algorithm Sensitivity To High-Density Artifacts, Kylie Blue

All ETDs from UAB

Radiotherapy planning can be adversely affected by inaccurate dose calculations due to the presence of high-density objects. High-density objects, such as surgical clips, produce artifacts in CT images which can result in errors in dose calculation. Manual correction of voxels containing incorrect information is recommended to prevent calculation errors, but this process can be cumbersome and sometimes results in planners compromising with crude corrections to save time. In this study we aim to determine the significance of small high-density objects and the artifacts they cause in radiotherapy treatment plans. To evaluate the impact of density overrides on calculations, a phantom …

A Case Demonstration Of The Open Health Natural Language Processing Toolkit From The National Covid-19 Cohort Collaborative And The Researching Covid To Enhance Recovery Programs For A Natural Language Processing System For Covid-19 Or Postacute Sequelae Of Sars Cov-2 Infection: Algorithm Development And Validation, Sijia Liu, David A Hanauer, Daniel R Harris, Ramakanth Kavuluru, Rui Zhang, Karthik Natarajan, Nishanth P Pavinkurve, Janos Hajagos, Sritha Rajupet, Veena Lingam, Mary Saltz, Corey Elowsky, Richard A Moffitt, Farrukh M Koraishy, Matvey B Palchuk, Jordan Donovan, Lora Lingrey, Garo Stone-Derhagopian, Robert T Miller, Andrew E Williams, Peter J Leese, Paul I Kovach, Emily R Pfaff, Mikhail Zemmel, Robert D Pates, Nick Guthe, Melissa A Haendel, Christopher G Chute, Hongfang Liu, National Covid Cohort Collaborative, Recover Initiative

Faculty, Staff and Student Publications

BACKGROUND: A wealth of clinically relevant information is only obtainable within unstructured clinical narratives, leading to great interest in clinical natural language processing (NLP). While a multitude of approaches to NLP exist, current algorithm development approaches have limitations that can slow the development process. These limitations are exacerbated when the task is emergent, as is the case currently for NLP extraction of signs and symptoms of COVID-19 and postacute sequelae of SARS-CoV-2 infection (PASC).

OBJECTIVE: This study aims to highlight the current limitations of existing NLP algorithm development approaches that are exacerbated by NLP tasks surrounding emergent clinical concepts and …

Analyzing Student Prompts And Their Effect On Chatgpt’S Performance, Ghadeer Sawalha, Imran Taj, Abdulhadi Shoufan

All Works

Large language models present new opportunities for teaching and learning. The response accuracy of these models, however, is believed to depend on the prompt quality which can be a challenge for students. In this study, we aimed to explore how undergraduate students use ChatGPT for problem-solving, what prompting strategies they develop, the link between these strategies and the model’s response accuracy, the existence of individual prompting tendencies, and the impact of gender in this context. Our students used ChatGPT to solve five problems related to embedded systems and provided the solutions and the conversations with this model. We analyzed the …

Domain-Based Nucleic-Acid Minimum Free Energy: Algorithmic Hardness And Parameterized Bounds, Erik D. Demaine, Elize Grizzell, Jayson Lynch, Ahmed Shalaby, Timothy Gomez, Markus Hecher, Robert Schweller, Damien Woods

Computer Science Faculty Publications

Molecular programmers and nanostructure engineers use domain-level design to abstract away messy DNA/RNA sequence, chemical and geometric details. Such domain-level abstractions are enforced by sequence design principles and provide a key principle that allows scaling up of complex multistranded DNA/RNA programs and structures. Determining the most favoured secondary structure, or Minimum Free Energy (MFE), of a set of strands, is typically studied at the sequence level but has seen limited domain-level work. We analyse the computational complexity of MFE for multistranded systems in a simple setting were we allow only 1 or 2 domains per strand. On the one hand, …

Coarse-Gridded Simulation Of The Nonlinear Schrödinger Equation With Machine Learning, Benjamin F. Akers, Kristina O. F. Williams

Faculty Publications

A numerical method for evolving the nonlinear Schrödinger equation on a coarse spatial grid is developed. This trains a neural network to generate the optimal stencil weights to discretize the second derivative of solutions to the nonlinear Schrödinger equation. The neural network is embedded in a symmetric matrix to control the scheme’s eigenvalues, ensuring stability. The machine-learned method can outperform both its parent finite difference method and a Fourier spectral method. The trained scheme has the same asymptotic operation cost as its parent finite difference method after training. Unlike traditional methods, the performance depends on how close the initial data …

Integrated Environmental Vulnerability Assessment And Adaptation Strategies For Coastal Areas Under Sustainable Development, Lien-Kwei Chien, Yu-Chi Li, Chia-Feng Hsu

Journal of Marine Science and Technology–Taiwan

This research focuses on the holistic management and environmental vulnerability of coastal areas in Taiwan within the framework of sustainable development. With economic and social growth gravitating towards coastal regions, the strain on the natural environment is increasing. Therefore, discovering a balance between economic progress and environmental conservation is paramount. To decipher the vulnerability of Taiwan's coastal zones, this study first defines ‘Integrated Environmental Vulnerability of Coastal Areas.’Key vulnerability factors were identified across environmental, social, and economic dimensions. Seven core determinants were determined using the Fuzzy Delphi method: biodiversity, coastal erosion, water pollution, population density, population aging, land utilization, and …

Evalution Of The Ability To Infer Tilt Angle And Size Distributions Of Fish Using A Broadband Scientific Echosounder Based On Simulation, Jing Liu

Journal of Marine Science and Technology–Taiwan

The biological information, such as species, size, and tilt angle, is crucial for converting the echo data into biomass information in acoustic surveys. Typically, the information can be obtained through trawl net sampling or underwater camera observations. However, both methods have some limitations. To overcome these limitations, scientists have utilized inversion methods with multi-frequency and broadband echosounders to derive biological information about fish, plankton, and krill. However, evaluating the reliability and accuracy of these inversion methods has been challenging due to the difficulty in obtaining accurate biological information. In this study, a numerical simulation method was used to generate fish …

A Forest Management Evaluation System For Small Private Forest Landowners, Pete Bettinger, Taeyoon Lee, Krista Merry, Daniel Drummond

Journal of Extension

When small private forest landowners have a need to address jointly economic and sustainability objectives, efficiency in both respects becomes important given limitations on the land, budget, time, and other resources that are available. The suite of forest management options available to a landowner may be vast and complex, therefore a tool to assist and inform their potential management activities can be of value. The eYield model was developed as an application (app) to assess forest management options on many different computing devices, from cellphones to desktop computers. Within eYield, a person can define a management situation, specify prices and …

Adaptive Worlds: Generative Ai In Game Design And Future Of Gaming, And Interactive Media, Jay Ratican, James Hutson

Faculty Scholarship

Generative AI is revolutionizing the field of game design, introducing unprecedented adaptability and personalization in gameplay. The latest advancements in AI-driven engines enable real-time content creation, offering dynamic, player-driven experiences that diverge from traditional pre-programmed narratives. This shift marks a transition toward "choose your own adventure" formats, with an unlimited number of variations in levels, enemies, collectibles, and weaponry, tailored to each player's decisions. Google's GameNGen, for example, showcases AI's capacity to recreate classic games like DOOM, learning and generating gameplay in real time. These innovations are not restricted to gaming alone; they extend to edutainment, television, and film, where …

Overview For Exploring The Multisensory Landscape, Brent Chamberlain, Richard Smardon

Landscape Architecture and Environmental Planning Faculty Publications

Land use change has had a fundamental impact on the livelihoods of people throughout the world. This Special Issue focuses on the research being conducted at the intersection of this land use change and the importance of maintaining landscapes that enrich humanity and our engagement with nature. Within this Special Issue, we explored the value of landscapes that heighten the senses. Visual Resource Stewardship is an area of research that closely aligns with understanding how changes in the environment may be perceived and experienced. Understanding the tools, processes, and theories involved helps us to better understand how land use change …

Locating Diversity In Reservoir Computing Using Bayesian Hyperparameter Optimization, Whitney Lunceford

Theses and Dissertations

Reservoir computers rely on an internal network to predict the future state(s) of dynamical processes. To understand how a reservoir's accuracy depends on this network, we study how varying the networ's topology and scaling affects the reservoir's ability to predict the chaotic dynamics on the Lorenz attractor. We define a metric for diversity, the property describing the variety of the responses of the nodes that make up reservoir's internal network. We use Bayesian hyperparameter optimization to find optimal hyperparameters and explore the relationships between diversity, accuracy of model predictions, and model hyperparameters. The content regarding the VPT metric, the effects …

Designing Cybersecurity Escape Rooms: A Gamified Approach To Undergraduate Learning, Thitima Srivatanakul

Journal of Cybersecurity Education, Research and Practice

Gamification, including game-based learning (GBL), is a widely recognized pedagogical approach used for imparting and reinforcing cybersecurity knowledge and skills to learners. One innovative form of GBL gaining popularity across various educational levels, from secondary schools to professional development, is escape room-style education. This study is centered on the development and design of escape room activities tailored for teaching cybersecurity concepts, with a particular focus on web and software security, to undergraduate students at York College. The primary objectives of this research are twofold: firstly, to evaluate the effectiveness of educational escape room activities in reinforcing cybersecurity concepts taught in …

Density-Dependence Inside A Marine Protected Area Increases Natural Mortality And Stunts The Growth Of A Spiny Lobster, Emma-Jade Tuffley, Simon De Lestang

Fisheries Research Articles

Sustainable fisheries management often requires the modelling of stocks under unfished conditions, when the influence of population densities on animal growth and mortality can be substantial. This can be especially true for species such as spiny rock lobster, which are very habitat specific. Using western rock lobster (Panulirus cygnus) tag-recapture data from adjacent and similar fished and unfished areas, the key life history parameters of natural mortality and growth were examined and compared under different population density scenarios. In an area representative of virgin biomass levels, lobsters exhibited reduced growth rates and a substantially higher rate of natural mortality …

C-H Amination Chemistry Mediated By Trinuclear Cu(I) Sites Supported By A Ligand Scaffold Featuring An Arene Platform And Tetramethylguanidinyl Residues, Meenakshi Sharma, Reece M. Fritz, Himanshu Bhatia, Joseph O. Adebanjo, Zhou Lu, Mohammad A. Omary, Thomas R. Cundari, Amitava Choudhury, Pericles Stavropoulos

Chemistry Faculty Research & Creative Works

Tripodal ligands that can encapsulate single or multiple metal sites in C3-symmetric geometric configurations constitute valuable targets for novel catalysts. Of particular interest in ligand development are efforts toward incorporating apical elements that exhibit little if any electron donicity, to enhance the electrophilic nature of a trans positioned active oxidant (e.g., metal-oxo, -nitrene). The tripodal ligand TMG3trphen-Arene has been synthesized, featuring an arene platform 1,3,5-substituted with phenylene arms possessing tetramethylguanidinyl (TMG) residues. Compound [(TMG3trphen-Arene) Cu₃(μ-Cl)₃] has been subsequently synthesized by extracting a Cu₃(μ-Cl)₃ cluster from anhydrous CuCl and shown to encapsulate a crown-shaped …

Size Fractionation Informs Microbial Community Composition And Interactions In The Eastern Tropical North Pacific Ocean, Madeleine A. Thompson, David L. Valentine, Xuefeng Peng

Faculty Publications

Marine microorganisms are drivers of biogeochemical cycles in the world’s oceans, including oxygen minimum zones (OMZs). Using a metabarcoding survey of the 16S rRNA gene, we investigated prokaryotic communities, as well as their potential interactions with fungi, at the coastal, offshore, and peripheral OMZ of the eastern tropical North Pacific. Water samples were collected along a vertical oxygen gradient, and large volumes were filtered through three size fractions, 0.22, 2, and 22 µm. The changes in community composition along the oxygen gradient were driven by Planctomycetota, Bacteroidota, Verrucomicrobiota, and Gammaproteobacteria; most are known degraders of marine polysaccharides and usually associated …

Development And Benchmark Of Polarizable Models For Ions, Luke Landry

Dissertations

Metalloproteins are ubiquitous in biology, playing crucial roles in diverse processes. Meanwhile, molecular simulations have become an important tool in scientific research. To accurately simulate metalloprotein systems, accounting for polarization and charge transfer effects is required. The fluctuating charge (FQ) model can effectively simulate the charge transfer effect, but the existing models often lack specificity for metalloproteins. In our research, a tailored FQ model for zinc-containing metalloproteins, leveraging the extended charge equilibration (EQeq) scheme, was introduced. CM5 charges were used as the target in our model parameterization, which offers advantages over RESP/CHELPG charges. Most notably, CM5 charges hold independence over …

Saas Application Maturity Assessment Model, Saiqa Aleem, Rabia Batool, Shayma Alkobaisi, Faheem Ahmed, Asad Masood Khattak

All Works

Software-as-a-service (SaaS), as a software delivery model, has received substantial attention from software providers and users alike. In recent years, it has become one of the most promising service delivery models in cloud computing. Many existing companies are transferring their business into the SaaS delivery model. Network vendors also migrate to a SaaS business model by offering on-demand remote IT support. This increasingly competitive landscape and the variety in markets have imposed many challenges for SaaS developers and vendors and made it difficult to find a consensus on the factors contributing to the positive performance of SaaS businesses. This paper …

Multimodal Mixing Convolutional Neural Network And Transformer For Alzheimer’S Disease Recognition, Junde Chen, Yun Wang, Adnan Zeb, M. D. Suzauddola, Yuxin Wen

Engineering Faculty Articles and Research

Early recognition of Alzheimer’s disease (AD) and its precursor state, mild cognitive impairment (MCI), is pivotal in interrupting the progression of the disease and providing suitable treatment. Recent development in deep learning techniques has drawn great research attention for improving the efficacy of AD recognition. However, numerous current methods solely utilize data from a single auxiliary domain, limiting their ability to harness valuable intrinsic insights from multiple domains. To cope with the challenge, this paper is devoted to establishing an innovative multimodal medical data fusion model, termed as MMDF, to perform Alzheimer’s disease recognition. Multimodal data including clinical records and …

Cyberattack Detection And Handling For Neural Network-Approximated Economic Model Predictive Control, Jihan Abou Halloun, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Cyberattacks on control systems can create unprofitable and unsafe operating conditions. To enhance safety and attack resiliency of control systems, cyberattack detection strategies can be developed. Prior work in our group has sought to develop cyberattack detection strategies that are integrated with an advanced control formulation known as Lyapunov-based economic model predictive control (LEMPC), in the sense that the controller properties can be used to analyze closed-loop stability in the presence or absence of undetected attacks. In this work, we consider neural network-approximated control laws, concepts for mitigating cyberattacks on such control laws, and how these ideas elucidate concepts in …

Lyapunov-Based Cyberattack Detection For Distinguishing Between Sensor And Actuator Attacks, Dominic Messina, Helen E. Durand

Chemical Engineering and Materials Science Faculty Research Publications

Control-theoretic cyberattack detection strategies are control strategies where control theory can be used in the design of the detection policies and analysis of stability properties with and without cyberattacks. This work provides a step toward understanding how to diagnose cyberattacks using control-theoretic cyberattack detection mechanisms. Specifically, we analyze the conditions under which a control-theoretic cyberattack detection strategy developed in our prior work to handle detection of simultaneous actuator and sensor attacks can be extended to distinguish between whether attacks are occurring on sensors or actuators. We present and evaluate heuristic concepts for attempting to diagnose sensor attacks; these again demonstrate …

Scientific History, Sampling Approach, And Physical Characterization Of The Camp Century Subglacial Material, A Rare Archive From Beneath The Greenland Ice Sheet, Paul R. Bierman, Andrew J. Christ, Catherine M. Collins, Halley M. Mastro, Juliana Souza, Pierre Henri Blard, Stefanie Brachfeld, Zoe R. Courville, Tammy M. Rittenour, Elizabeth K. Thomas, Jean Louis Tison, François Fripiat

Department of Earth and Environmental Studies Faculty Scholarship and Creative Works

Basal materials in ice cores hold information about paleoclimate conditions, glacial processes, and the timing of past ice-free intervals, all of which aid understanding of ice sheet stability and its contribution to sea level rise in a warming climate. Only a few cores have been drilled through ice sheets into the underlying sediment and bedrock, producing limited material for analysis. The last of three Camp Century ice cores, which the U.S. Army collected in northwestern Greenland from 1963-1966 CE, recovered about 3.5 m of subglacial material, including ice and sediment. Here, we document the scientific history of the Camp Century …