Physical Sciences and Mathematics Commons^™

Stable Trace Ideals And Applications, Haydee Lindo, Hai Long Dao

All HMC Faculty Publications and Research

We study stable trace ideals in one dimensional local Cohen–Macaulay rings and give numerous applications.

The Use Of Probability In Quantum Mechanics To Calculate Measurement Outcomes, Hannah E. Collins

CAFE Symposium 2023

The concept of probability can help measure some of the possible outcomes of different experiments in the field of quantum mechanics. Those experiments include Thomas Young's double slit experiment, the Schrödinger equation, the wave function, and the Born Rule, which all make use of probability to predict the placement of certain subatomic particles including photons of light, in the experiments. In this project, the manner in which probability does this is explored in depth.

Analysis Of “A Forest Under The Sea”- Studying Giant Kelp’S Benefits To Ecosystems, And Evaluating Kelp Restoration, Natalie V. Boyd

CAFE Symposium 2023

I wrote a research paper on how Giant Kelp needs to be restored due to the rising ocean temperatures. There are two methods that I specifically focused on and learned about which are "Super Kelp" and "Green Gravel." Giant Kelp is critical to our ecosystem and marine life specifically due to all the benefits that it supplies. For example, kelp forests can sequester up to 20 times more carbon than a land forest. Unfortunately, the kelp is dying off rapidly now because of climate change; specifically the rising temperatures and increased ocean acidification. In order to save the kelp, action …

The Probability Of Miracles, Lewis A. Pummell

CAFE Symposium 2023

An insight into the probability that we will experience a miracle within our lives. This project considers different ways of defining a miracle, and how this impacts how we consider them in our lives. They are paradoxical, and completely subjective - although there are key concepts of probability which will guide opinion.

Looking For Life, Conor C. Grubb

CAFE Symposium 2023

The topic of aliens is not just about conspiracy theories and tinfoil hats, through the years numerous respected scientists have weighed in and put thought into the topic. The Search for Extraterrestrial Intelligence (SETI) is closely tied to the Fermi Paradox and the Drake Equation. The Fermi Paradox considers why humans haven't already interacted with aliens if they exist, and the Drake Equation outlines potential variables that would influence the chances of humanity receiving radio contact from an alien civilization.

Expedition To Washington State: The Pacific Crest Trail, Mt. Rainier, Okanogan-Wenatchee, And Lake Chelan, Riley J. Nolan

CAFE Symposium 2023

Within the United States there are many different agencies that have been tasked with the management of America's Public Lands. Due to America's unique inception, there are many different ideas and concepts that affect how we view these same land units today. This poster delves into four specific land units in Washington State (The Pacific Crest National Trail, the Lake Chelan National Recreation Area, The Okanogan-Wenatchee National Forest, and Mount Rainier National Park) to discuss each area's history and management issues, as well as discuss the effects of society's preconceived notions on each destination. Finally, the poster also discusses what …

Leaf-Counting In Monocot Plants Using Deep Regression Models, Xinyan Xie, Yufeng Ge, Harkamal Walia, Jinliang Yang, Hongfeng Yu

School of Computing: Faculty Publications

Leaf numbers are vital in estimating the yield of crops. Traditional manual leaf-counting is tedious, costly, and an enormous job. Recent convolutional neural network-based approaches achieve promising results for rosette plants. However, there is a lack of effective solutions to tackle leaf counting for monocot plants, such as sorghum and maize. The existing approaches often require substantial training datasets and annotations, thus incurring significant overheads for labeling. Moreover, these approaches can easily fail when leaf structures are occluded in images. To address these issues, we present a new deep neural network-based method that does not require any effort to label …

Coral Gardens Reef, Belize: An Acropora Spp. Refugium Under Threat In A Warming World, Lisa Greer, H. Allen Curran, Karl Wirth, Robert Humston, Ginny Johnson, Lauren Mcmanus, Candice Stefanic, Tara Clark, Halard Lescinsky, Kirah Forman-Castillo

Geosciences: Faculty Publications

Live coral cover has declined precipitously on Caribbean reefs in recent decades. Acropora cervicornis coral has been particularly decimated, and few Western Atlantic Acropora spp. refugia remain. Coral Gardens, Belize, was identified in 2020 as a long-term refugium for this species. This study assesses changes in live A. cervicornis coral abundance over time at Coral Gardens to monitor the stability of A. cervicornis corals, and to explore potential threats to this important refugium. Live coral cover was documented annually from 2012– 2019 along five permanent transects. In situ sea-surface temperature data were collected at Coral Gardens throughout the study period …

Quadcopter Control Using Single Network Adaptive Critics, Alberto Velazquez, Lei Xu, Tohid Sardarmehni

Mechanical Engineering Faculty Publications and Presentations

In this paper, optimal tracking control is found for an inputaffine nonlinear quadcopter using Single Network Adaptive Critics (SNAC). The quadcopter dynamics consists of twelve states and four controls. The states are defined using two related reference frames: the earth frame, which describes the position and angles, and the body frame, which describes the linear and angular velocities. The quadcopter has six outputs and four controls, so it is an underactuated nonlinear system. The optimal control for the system is derived by solving a discrete-time recursive Hamilton-Jacobi-Bellman equation using a linear in-parameter neural network. The neural network is trained to …

Robust Explicit Estimation Of The Log-Logistic Distribution With Applications, Zhuanzhuan Ma, Min Wang, Chanseok Park

School of Mathematical and Statistical Sciences Faculty Publications and Presentations

The parameters of the log-logistic distribution are generally estimated based on classical methods such as maximum likelihood estimation, whereas these methods usually result in severe biased estimates when the data contain outliers. In this paper, we consider several alternative estimators, which not only have closed-form expressions, but also are quite robust to a certain level of data contamination. We investigate the robustness property of each estimator in terms of the breakdown point. The finite sample performance and effectiveness of these estimators are evaluated through Monte Carlo simulations and a real-data application. Numerical results demonstrate that the proposed estimators perform favorably …

Plmsnosite: An Ensemble-Based Approach For Predicting Protein S-Nitrosylation Sites By Integrating Supervised Word Embedding And Embedding From Pre-Trained Protein Language Model, Pawel Pratyush, Suresh Pokharel, Hiroto Saigo, Dukka Kc

Michigan Tech Publications

Background: Protein S-nitrosylation (SNO) plays a key role in transferring nitric oxide-mediated signals in both animals and plants and has emerged as an important mechanism for regulating protein functions and cell signaling of all main classes of protein. It is involved in several biological processes including immune response, protein stability, transcription regulation, post translational regulation, DNA damage repair, redox regulation, and is an emerging paradigm of redox signaling for protection against oxidative stress. The development of robust computational tools to predict protein SNO sites would contribute to further interpretation of the pathological and physiological mechanisms of SNO. Results: Using an …

Session 12: Analysis Of State And Parameter Estimation Techniques Using Dynamic Perturbation Signals, Timothy M. Hansen

SDSU Data Science Symposium

The trend in electric power systems is the displacement of traditional synchronous generation (e.g., coal, natural gas) with renewable energy resources (e.g., wind, solar photovoltaic) and battery energy storage. These energy resources require power electronic converters (PECs) to interconnect to the grid and have different response characteristics and dynamic stability issues compared to conventional synchronous generators. As a result, there is a need for validated models to study and mitigate PEC-based stability issues, especially for converter dominated power systems (e.g., island power systems, remote microgrids).

This presentation will introduce methods related to dynamic state and parameter estimation via the design …

Session11: 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 …

The Fate Of Carbonate Rocks During Hypervelocity Impacts: Case Studies From Three Impact Structures On Earth, Nicolas D. Garroni

Electronic Thesis and Dissertation Repository

Approximately 28% of all hypervelocity impact structures discovered on Earth exist in a carbonate-dominated target sequence. Despite decades of research, how carbonate rocks and minerals react to shock metamorphism is still poorly understood. In this contribution, three impact structures on Earth were studied to determine the effects of shock metamorphism on carbonate minerals: Chicxulub, Crooked Creek and Jebel Waqf as Suwwan.

At Chicxulub, carbonates from the impact-melt bearing breccia of drill core, M0077A were characterized petrographically and geochemically. Calcite was the only carbonate mineral present and is abundant throughout the impact breccia in five distinct varieties: limestone clasts …

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 …

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 …

A Characterization Of Bias Introduced Into Forensic Source Identification When There Is A Subpopulation Structure In The Relevant Source Population., Dylan Borchert, Semhar Michael, Christopher Saunders

SDSU Data Science Symposium

In forensic source identification the forensic expert is responsible for providing a summary of the evidence that allows for a decision maker to make a logical and coherent decision concerning the source of some trace evidence of interest. The academic consensus is usually that this summary should take the form of a likelihood ratio (LR) that summarizes the likelihood of the trace evidence arising under two competing propositions. These competing propositions are usually referred to as the prosecution’s proposition, that the specified source is the actual source of the trace evidence, and the defense’s proposition, that another source in a …

Application Of Gaussian Mixture Models To Simulated Additive Manufacturing, Jason Hasse, Semhar Michael, Anamika Prasad

SDSU Data Science Symposium

Additive manufacturing (AM) is the process of building components through an iterative process of adding material in specific designs. AM has a wide range of process parameters that influence the quality of the component. This work applies Gaussian mixture models to detect clusters of similar stress values within and across components manufactured with varying process parameters. Further, a mixture of regression models is considered to simultaneously find groups and also fit regression within each group. The results are compared with a previous naive approach.

Finite Mixture Modeling For Hierarchically Structured Data With Application To Keystroke Dynamics, Andrew Simpson, Semhar Michael

SDSU Data Science Symposium

Keystroke dynamics has been used to both authenticate users of computer systems and detect unauthorized users who attempt to access the system. Monitoring keystroke dynamics adds another level to computer security as passwords are often compromised. Keystrokes can also be continuously monitored long after a password has been entered and the user is accessing the system for added security. Many of the current methods that have been proposed are supervised methods in that they assume that the true user of each keystroke is known apriori. This is not always true for example with businesses and government agencies which have internal …

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 …

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 …

Bridging The Cultural Divide: A Single Case Study Exploring Connections Between Multi-Cultural Education, Identity, Self-Esteem And Leadership, Amy Britton

Journal of Multicultural Affairs

This qualitative single case study explores connections between multicultural education, identity development, self-esteem, and leadership. The study focuses on the lived experiences of a lifelong learner, educator, and leader in higher education with the pseudonym, Rachel. The interview with Rachel traced how she experiences diversity within her academic experiences as a learner and her professional experiences as an educator and leader.

Session 8: Ensemble Of Score Likelihood Ratios For The Common Source Problem, Federico Veneri, Danica M. Ommen

SDSU Data Science Symposium

Machine learning-based Score Likelihood Ratios have been proposed as an alternative to traditional Likelihood Ratios and Bayes Factor to quantify the value of evidence when contrasting two opposing propositions.

Under the common source problem, the opposing proposition relates to the inferential problem of assessing whether two items come from the same source. Machine learning techniques can be used to construct a (dis)similarity score for complex data when developing a traditional model is infeasible, and density estimation is used to estimate the likelihood of the scores under both propositions.

In practice, the metric and its distribution are developed using pairwise comparisons …

Session 2: The Effect Of Boom Leveling On Spray Dispersion, Travis A. Burgers, Miguel Bustamante, Juan F. Vivanco

SDSU Data Science Symposium

Self-propelled sprayers are commonly used in agriculture to disperse agrichemicals. These sprayers commonly have two boom wings with dozens of nozzles that disperse the chemicals. Automatic boom height systems reduce the variability of agricultural sprayer boom height, which is important to reduce uneven spray dispersion if the boom is not at the target height.

A computational model was created to simulate the spray dispersion under the following conditions: a) one stationary nozzle based on the measured spray pattern from one nozzle, b) one stationary model due to an angled boom, c) superposition of multiple stationary nozzles due an angled boom, …

Mathematics Tracking: Policy Brief, Melissa P. Donham

Journal of Multicultural Affairs

Tracking is a long-standing practice in schools. Students are often placed in tracks beginning in upper elementary or middle school. The tracks in which students are placed in earlier grades set them up for the mathematics courses they are able to take in high school. The number of mathematics tracks for students can differ from school to school, but the policy of having mathematics tracks is common throughout schools in the United States. This policy brief will discuss the arguments for and against mathematics tracking policies, implications for educators and policymakers, and future directions.

The Emerging Scholars Issue: Insights On Teaching And Leading Through Reshaping Policy And Practice, Lakia M. Scott, Taylor D. Bunn

Journal of Multicultural Affairs

The Emerging Scholars program began at the 2019 Texas-NAME conference with five graduate students, four of which were enrolled in a doctoral program. Students participated in preconference workshops on establishing a research agenda, understanding academia and higher education institutions, and creating a network as an education researcher. Since its inception, the program has continued introducing students to collaborations and publication opportunities through Texas-NAME. This special issue provides doctoral students (some of whom have since graduated) with an opportunity to be single-authors in their scholar. Organized in three distinct sections, readers will be exposed to research and policy briefs and critical …

A Critical Review On Water Overconsumption In Lignocellulosic Biomass Pretreatment For Ethanol Production Through Enzymic Hydrolysis And Fermentation, Jikai Zhao, Juhee Lee, Donghai Wang

School of Earth, Environmental, and Marine Sciences Faculty Publications and Presentations

Global demand for renewable and sustainable energy fostered the considerable development of biomass-to-ethanol valorization strategies. Thermochemical pretreatment methods have been proposed to render biomass more amenable to enzymatic and microbial digestion. However, the efforts have not led to its industrial-scale worldwide realization. One of the obstacles to commercialization could be related to water overconsumption, as excessive water washing of the pretreated slurry is often performed to remove inhibitory compounds and residual chemicals after biomass pretreatment. Only increasing solid loading for biomass pretreatment results in ineffective pretreatment performance, more inhibitors formation, and high viscosity, which in turn necessitates the water washing …

Final 2021 Unreclaimed Sites Sampling Ur-38 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final 2021 Unreclaimed Sites Sampling Ur-36 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Final 2021 Unreclaimed Sites Sampling Ur-35 Site Evaluation Summary Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.