Physical Sciences and Mathematics Commons^™

Meet Me In The Middle: A Scoping Review On Understanding Adolescent Needs In Climate Communication, Gwendolyn Monica Hoff Anderson

Master's Projects and Capstones

The greatest effects of climate change are likely to be felt by youth. Young people are disproportionately affected by climate change due to their critical developmental stage and lack of power, and they experience both higher severity and prevalence of mental health issues related to climate change. Strong emotions have long been recognized as potential catalysts for action, or they may lead to paralyzing feelings of being overwhelmed. Climate communication is a critical tool to spark climate concern and encourage action. Activism, in turn, may help youth manage their anxiety about climate change. This scoping review examines emerging evidence on …

The Loneliest Galaxies In The Universe: A Gama And Galaxy Zoo Study On Void Galaxy Morphology., Lori E. Porter

College of Arts & Sciences Senior Honors Theses

The large-scale structure (LSS) of the Universe is comprised of galaxy filaments, tendrils, and voids. The majority of the Universe’s volume is taken up by these voids, which exist as underdense, but not empty, regions. The galaxies found inside voids are void galaxies and expected to be some of the most isolated objects in the Universe. However, their standard morphology remains poorly studied. This study, using the Galaxy and Mass Assembly (GAMA) data and Galaxy Zoo survey, aims to remedy this. For completeness purposes, we use void galaxies identified by Alpaslan et al. (2014) with stellar masses (M*) of 10 …

Soil Health And Remediation For Urban Gardens In Utah, Melissa Chilinski

All Graduate Plan B and other Reports

Urban environments are at an increased risk of soil contamination and poor soil health due to anthropogenic causes. As healthy farmland is developed, new urban farmers and gardeners are often left growing food on unwanted land with unknown histories of previous use. Varied research and methods for obtaining healthy soils can cause new growers to make decisions that negatively impact soil health and fertility, or on the other hand, conflicting information can cause individuals to become unnecessarily fearful of common soil contaminants and their effect on human health. Common soil contaminants, like trace metals (often referred to as heavy metals) …

The Novel Chlorination Of Zirconium Metal And Its Application To A Recycling Protocol For Zircaloy Cladding From Spent Nuclear Fuel Rods, Breanna K. Vestal

Doctoral Dissertations

A novel protocol has been developed for the chemical removal of zirconium alloy (Zircaloy) cladding from spent nuclear fuel rods and subsequent isolation and purification of nuclear-grade zirconium chloride derived therefrom. This protocol is based on the chemistry developed from two new scientific findings.

First, two new oxidative chlorination reactions have been discovered for zirconium metal. In both solvents, zirconium can be quantitatively chlorinated at temperatures less than 150°C, with the operative equations seen below. In sulfur monochloride, the reaction is completed in 2 – 4 hours via surface etching, exhibiting 0^th order kinetic behavior. The elemental sulfur byproduct …

Subterraneans: A Regional Earth Dwelling For Comfort And Beauty, Isaak Benchoff

Architecture Undergraduate Honors Theses

Subterraneans is a study of an affordable, self-sufficient, sustainable, and dignified housing prototype for the region of Northwest Arkansas. It is a design process investigation based on the ideas of turning a local, sustainable material into affordable homes that can be built within a community of people sharing land and resources. The homes would utilize as many natural materials as possible to minimize the impact on the Earth and the cost to the owners.

Research looked at many different vernacular building precedents as well as the work done by contemporary design firms in the area of economical, low-impact, and passively …

Deephtlv: A Deep Learning Framework For Detecting Human T-Lymphotrophic Virus 1 Integration Sites, Johnathan Jia, Johnathan Jia

The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences Dissertations and Theses (Open Access)

In the 1980s, researchers found the first human oncogenic retrovirus called human T-lymphotrophic virus type 1 (HTLV-1). Since then, HTLV-1 has been identified as the causative agent behind several diseases such as adult T-cell leukemia/lymphoma (ATL) and a HTLV-1 associated myelopathy or tropical spastic paraparesis (HAM/TSP). As part of its normal replication cycle, the genome is converted into DNA and integrated into the genome. With several hundreds to thousands of unique viral integration sites (VISs) distributed with indeterminate preference throughout the genome, detection of HTLV-1 VISs is a challenging task. Experimental studies typically use molecular biology …

Leveraging Aruco Fiducial Marker System For Bridge Displacement Estimation Using Unmanned Aerial Vehicles, Mohamed Aly

Computer Science and Engineering: Theses, Dissertations, and Student Research

The use of unmanned aerial vehicles (UAVs) in construction sites has been widely growing for surveying and inspection purposes. Their mobility and agility have enabled engineers to use UAVs in Structural Health Monitoring (SHM) applications to overcome the limitations of traditional approaches that require labor-intensive installation, extended time, and long-term maintenance. One of the critical applications of SHM is measuring bridge deflections during the bridge operation period. Due to the complex remote sites of bridges, remote sensing techniques, such as camera-equipped drones, can facilitate measuring bridge deflections. This work takes a step to build a pipeline using the state-of-the-art computer …

Using Object Detection To Navigate A Game Playfield, Peter Kearnan Hyde-Smith

Master's Theses (2009 -)

Perhaps the crown jewel of AI is the self-navigating agent. To take many sources of data as input and use it to traverse complex and varied areas while mitigating risk and damage to the vehicle that is being controlled, visual object detection is a key part of the overall suite of this technology. While much efforts are being put towards real-world applications, for example self-driving cars, healthcare related issues and automated manufacturing, we apply object detection in a different way; the automation of movement across a video game play field. We take the TensorFlow Object Detection API and use it …

An Analysis Of Energy Production And Efficiency In Various Longbow Archery Models, Hannah Mcpherson

Honors Projects

An analysis of the energy production and efficiency of three lab-tested longbow models is undertaken. The first model, which is constructed to not allow flexing of limbs and which uses a frictionless cart and track in place of an arrow, demonstrated an efficiency of 50% +/- 40%. The second model, which is constructed similarly to the first with the exception of a wooden dowel now being used as an arrow-like object, demonstrated an efficiency of 13% +/- 3%. The last model, a 3D printed longbow with flexible limbs using the wooden dowel as an arrow-like object, demonstrated an efficiency of …

Logic And Rationality, Rohit J. Parikh

Publications and Research

Logic aims at truth, or more accurately, at deriving some truths from other truths. But why are we interested in truth in the first place? Surely one reason is that relying on truth makes it easier to make better choices.

One could think of Game theory as a tool which bridges the gap between logic and rationality.

Decision theory - or single agent game theory tells us when to make the best choice in a game of us against nature. But nature has no desire to further or frustrate our efforts. Nature is mysterious but not malign. Things change when …

The Vehicle Routing Problem With Simultaneous Pickup And Delivery And Occasional Drivers, Vincent F. Yu, Grace Aloina, Panca Jodiawan, Aldy Gunawan, Tsung-C. Huang

Research Collection School Of Computing and Information Systems

This research addresses the Vehicle Routing Problem with Simultaneous Pickup and Delivery and Occasional Drivers (VRPSPDOD), which is inspired from the importance of addressing product returns and the emerging notion of involving available crowds to perform pickup and delivery activities in exchange for some compensation. At the depot, a set of regular vehicles is available to deliver and/or pick up customers’ goods. A set of occasional drivers, each defined by their origin, destination, and flexibility, is also able to help serve the customers. The objective of VRPSPDOD is to minimize the total traveling cost of operating regular vehicles and total …

Named Entity Recognition From Biomedical Text, Maged Guirguis

Theses and Dissertations

As vast amounts of unstructured data are becoming available digitally, computer-based methods to extract relevant and meaningful information are needed. Named entity recognition (NER) is the task of identifying text spans that mention named entities, and to classify them into predefined categories. Despite the existence of numerous and well-versed NER methods, the bio-medical domain remains under-studied. The objective of this research is to identify an efficient technique for NER tasks from biomedical data. This is achieved by investigating using deep learning technologies namely pre-trained BERT [1] model and its variances SciBERT [2] and BioBERT [3]. Preprocessing the data before passing …

Evidence Of Sea Level Rise At The Peruvian Coast (1942-2019), Bismarck Jigena-Antelo, Carol Estrada-Ludeña, Stephan Howden, Wilmer Rey, Jorge Paz-Acosta, Patricia Lopez-García, Eric Salazar-Rodriguez, Nieves Endrina, Juan J. Muñoz-Pérez

Faculty Publications

The present work aims to analyze the variability of the sea level of the Peruvian coast with time series over a long observation period (Seventy-eight years, from 1942 to 2019). Data came from the Talara, Callao and Matarani tide gauge stations located at the north, center and south of the coast. Variations of sea level as well as air and seawater surface temperature were analyzed. Among the different scenarios studied, a sea level rise of 6.79, 4.21 and 5.16 mm/year for Talara, Callao and Matarani, respectively was found during the 1979–1997 nodal cycle. However, these results decreased significantly during the …

Models For Predicting Maximum Potential Intensity Of Tropical Cyclones, Iftekhar Chowdhury, Gemechis Djira

SDSU Data Science Symposium

Tropical cyclones (TCs) are considered as extreme weather events, which has a low-pressure center, namely an eye, strong winds, and a spiral arrangement of thunderstorms that produces heavy rain, storm surges, and can cause severe destruction in coastal areas worldwide. Therefore, reliable forecasts of the maximum potential intensity (MPI) of TCs are critical to estimate the damages to properties, lives, and risk assessment. In this study, we explore and propose various regression models, to predict the potential intensity of TCs in the North Atlantic at 12, 24, 36, 48, 60, and 72- hour forecasting lead time. In addition, a popular …

2d Respiratory Sound Analysis To Detect Lung Abnormalities, Rafia Sharmin Alice, Kc Santosh

SDSU Data Science Symposium

Abstract. In this paper, we analyze deep visual features from 2D data representation(s) of the respiratory sound to detect evidence of lung abnormalities. The primary motivation behind this is that visual cues are more important in decision-making than raw data (lung sound). Early detection and prompt treatments are essential for any future possible respiratory disorders, and respiratory sound is proven to be one of the biomarkers. In contrast to state-of-the-art approaches, we aim at understanding/analyzing visual features using our Convolutional Neural Networks (CNN) tailored Deep Learning Models, where we consider all possible 2D data such as Spectrogram, Mel-frequency Cepstral Coefficients …

Two-Stage Approach For Forensic Handwriting Analysis, Ashlan J. Simpson, Danica M. Ommen

SDSU Data Science Symposium

Trained experts currently perform the handwriting analysis required in the criminal justice field, but this can create biases, delays, and expenses, leaving room for improvement. Prior research has sought to address this by analyzing handwriting through feature-based and score-based likelihood ratios for assessing evidence within a probabilistic framework. However, error rates are not well defined within this framework, making it difficult to evaluate the method and can lead to making a greater-than-expected number of errors when applying the approach. This research explores a method for assessing handwriting within the Two-Stage framework, which allows for quantifying error rates as recommended by …

Temporal Tensor Factorization For Multidimensional Forecasting, Jackson Cates, Karissa Scipke, Randy Hoover, Kyle Caudle

SDSU Data Science Symposium

In the era of big data, there is a need for forecasting high-dimensional time series that might be incomplete, sparse, and/or nonstationary. The current research aims to solve this problem for two-dimensional data through a combination of temporal matrix factorization (TMF) and low-rank tensor factorization. From this method, we propose an expansion of TMF to two-dimensional data: temporal tensor factorization (TTF). The current research aims to interpolate missing values via low-rank tensor factorization, which produces a latent space of the original multilinear time series. We then can perform forecasting in the latent space. We present experimental results of the proposed …

Session 4: Skip-Gcn : A Framework For Hierarchical Graph Representation Learning, Jackson Cates, Justin Lewis, Randy Hoover, Kyle Caudle

SDSU Data Science Symposium

Recently there has been high demand for the representation learning of graphs. Graphs are a complex data structure that contains both topology and features. There are first several domains for graphs, such as infectious disease contact tracing and social media network communications interactions. The literature describes several methods developed that work to represent nodes in an embedding space, allowing for classical techniques to perform node classification and prediction. One such method is the graph convolutional neural network that aggregates the node neighbor’s features to create the embedding. Another method, Walklets, takes advantage of the topological information stored in a graph …

Between Heaven And Earth! A Poem-Collage Pair About Hypatia Of Alexandria, Sarah Glaz, Mark Sanders

Journal of Humanistic Mathematics

The poem-collage pair presented here is a work of collaboration between the mathematician and poet, Sarah Glaz, and the collage and ceramic artist, Mark Sanders. The piece is part of their larger joint poem-collage project involving the history of mathematics. Included as background is a brief discussion on the history and mathematics involved, and a reflection on several landmark locations and some of the relevant imagery appearing in the poem and the collage.

The Babelogic Of Mathematics, Vijay Fafat

Journal of Humanistic Mathematics

How would the Bible written about a Mathematical God start, describing the Creation of Mathematics and Logic? How would Rigveda's "Nasadiya sukta" read if it were describing the Void before mathematics was "born"? Here is an attempt at a partial answer, one which takes the original Genesis chapter and the Nasadiya sukta and makes suitable changes to create a fairly consistent, if somewhat anachronistic narrative (with the slight mixing up of Bertrand Russell and Lobachevsky / Bolyai attributable to "Babelogic"), along with a new ending to the Beginning...