Physical Sciences and Mathematics Commons^™

Unraveling The History Of Deforestation In The Amazon Rainforest With Statistical Modeling, Ryan Destefano

Master's Theses

The Amazon rainforest, a vital ecosystem of immense biodiversity and global climate significance, faces the ongoing threat of deforestation driven by agricultural expansion. This thesis employs remote sensing techniques, focusing on the Enhanced Vegetation Index (EVI) derived from Landsat satellite imagery, to track land cover dynamics within the Amazon. The study examines historical land cover changes in current plantations in Peru and Brazil, regions where the exact timing of deforestation is uncertain. By analyzing EVI measurements dating back to 1984, inflection points indicative of deforestation events preceding plantation establishment are identified. Statistical modeling techniques, including spline fitting to analyze time …

Matrix Approximation And Image Compression, Isabella R. Padavana

Master's Theses

This thesis concerns the mathematics and application of various methods for approximating matrices, with a particular eye towards the role that such methods play in image compression. An image is stored as a matrix of values with each entry containing a value recording the intensity of a corresponding pixel, so image compression is essentially equivalent to matrix approximation. First, we look at the singular value decomposition, one of the central tools for analyzing a matrix. We show that, in a sense, the singular value decomposition is the best low-rank approximation of any matrix. However, the singular value decomposition has some …

Assessing The Efficacy Of Hydraulic Pumping As A Remediation Method Of A Subsurface Light Non-Aqueous Phase Liquid Spill In Arroyo Grande, California, James M. Raney

Master of Science in Environmental Sciences and Management Projects

The efficacy of hydraulic pumping as a remediation method of a petroleum, or Light Non-Aqueous Phase Liquid (LNAPL) spill in Arroyo Grande, California will be assessed by determining aquifer properties, assessing the chemical properties of the contaminant, recovering the contaminant from the subsurface, and proposing alternative remediation techniques. Soil, groundwater and contaminant characteristics, cumulative volume of LNAPL skimming test data, pumping rates, and LNAPL thicknesses in wells installed within the contaminant plume were collected. Sediments around the LNAPL source are contaminated with hydrocarbons in the gas and diesel range. Pumping efficacy is expected to continue to decrease at the site, …

Using Bayesian Multispecies Models To Evaluate Fish And Invertebrate Detection Probability And Distribution In The Hypersaline Bahia Grande Tidal Basin, Roy M. Ulibarri, Catherine M. Eckert, David Hicks, David Montagne, Brandon Jones, David R. Stewart

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

Objective

In 2000, the Laguna Atascosa National Wildlife Refuge acquired the Bahia Grande (Texas) management unit, a space that had lain barren and arid for 70 years. A large cooperative partnership launched a restoration project to replenish the basin and recover its original tidal hydrology. In 2005, the construction of a pilot channel successfully restored water throughout the basin, and plans to eventually widen the channel were developed. Our study aims to evaluate an estuarine habitat restoration by assessing ecological drivers and the impacts on species diversity.

Methods

We evaluated species richness, detection/occupancy rates, and species–habitat relationships, and we estimated …

Santa Maria Climate Action Plan Recommendations: Building Energy And Transportation, Thomas Zimmerman, Elena Blewett

City and Regional Planning

The Santa Maria Climate Action Plan Recommendations addresses GHG emissions reduction for the largest sectors in the City of Santa Maria- Building Energy and Transportation. The project includes GHG forecasts and reduction targets from the City’s Draft 2020 Community-Wide Greenhouse Gas Inventory Report. The reduction targets are met through a series of actionable measures to help the City meet aggressive reduction targets by 2030 and 2045.

On Near-Linear Cellular Automata Over Near Spaces, Abdul-Rahman M. Nasser

Dissertations

Cellular Automata can be considered as examples of massively parallel machines. They are computational mathematical objects consisting of a grid of cells, each of which can exist in a finite number of states. These cells evolve over discrete time steps according to a set of predefined rules based on the states of neighboring cells. The notion of cellular automata was first introduced by Ulam and von Neumann and then popularized by John H. Conway in the 1970s with one of the most famous examples being The Game of Life.

This research builds on and generalizes the work of Tullio Ceccherini-Silberstein …

Alternative Adjacency Matrices And Spatial Analysis, Jaeseong Hwang

Dissertations

Spatial analysis is essential for comprehending the spatial distribution of diseases and various phenomena across geographic regions. This study investigates the utilization of alternative adjacency matrices in spatial analysis, with a specific focus on implementing Poisson regression models. This study intricately explores the methodology behind constructing alternative weight matrices, specifying weight matrices, and comparing the performance of Poisson models using five different weight matrices.

The popular Poisson model model is described, and five different definitions of weight matrices are defined, which are the following: binary weight matrix, inverse distance weight matrix using Euclidean distance, Graph distance matrix, Path matrix, and …

Quasi-Monte Carlo Estimation For Functional Generalized Linear Mixed Models., Ruvini Kumari Jayamaha Hitihamilage

Dissertations

Functional Data Analysis (FDA) is a topic of growing interest in the statistics community and is applied in a wide range of fields such as Anthropology, Epidemiology, Meteorology, Neurology and Engineering. The data in FDA are smooth curves or surfaces in time or space which can be conceptualized as functions. Because of the smooth nature of the data and the measurements are highly correlated, making the classical methods such as univariate or multivariate analysis are infeasible for such data. Functional data Analysis (FDA) deals with these kinds of more detailed, complex, and structured data.

In this dissertation, we propose a …

A Microgenetic Learning Analysis Of Contextuality In Reasoning About Exponential Modeling, Elahe Allahyari

Dissertations

This work explores the complex cognitive processes students engage in when addressing contextual tasks requiring linear and exponential models. Grounded within Piagetian constructivism and the Knowledge in Pieces (KiP) epistemological perspective (diSessa, 1993, 2018), this empirical study in a clinical setting develops a Microgenetic Learning Analysis (MLA) of the reasoning of 14 students from an Algebra II course. It reveals the critical role of cognitive disequilibrium as an essential cognitive state for conceptual development and the process of reorganizing knowledge systems. The study uncovers the fluctuations in students’ reasoning patterns and the significant impact on students’ reasoning patterns of task-specific …

An Experimental Study Of Supervised Machine Learning Techniques For Minor Class Prediction Utilizing Kernel Density Estimation: Factors Impacting Model Performance, Abdullah Mana Alfarwan

Dissertations

This dissertation examined classification outcome differences among four popular individual supervised machine learning (ISML) models (logistic regression, decision tree, support vector machine, and multilayer perceptron) when predicting minor class membership within imbalanced datasets. The study context and the theoretical population sampled focus on one aspect of the larger problem of student retention and dropout prediction in higher education (HE): identification.

This study differs from current literature by implementing an experimental design approach with simulated student data that closely mirrors HE situational and student data. Specifically, this study tested the predictive ability of the four ISML classification models (CLS) under experimentally …

Multivalued Variational Inequalities With Generalized Fractional Φ-Laplacians, Vy Khoi Le

Mathematics and Statistics Faculty Research & Creative Works

In this article, we examine variational inequalities of the form (Formula presented.), where (Formula presented.) is a generalized fractional (Formula presented.) -Laplace operator, K is a closed convex set in a fractional Musielak–Orlicz–Sobolev space, and (Formula presented.) is a multivalued integral operator. We consider a functional analytic framework for the above problem, including conditions on the multivalued lower order term (Formula presented.) such that the problem can be properly formulated in a fractional Musielak–Orlicz–Sobolev space, and the involved mappings have certain useful monotonicity–continuity properties. Furthermore, we investigate the existence of solutions contingent upon certain coercivity conditions.

Differential Methylation Region Detection Via An Array-Adaptive Normalized Kernelweighted Model, Daniel Alhassan, Gayla R. Olbricht, Akim Adekpedjou

Mathematics and Statistics Faculty Research & Creative Works

A differentially methylated region (DMR) is a genomic region that has significantly different methylation patterns between biological conditions. Identifying DMRs between different biological conditions is critical for developing disease biomarkers. Although methods for detecting DMRs in microarray data have been introduced, developing methods with high precision, recall, and accuracy in determining the true length of DMRs remains a challenge. In this study, we propose a normalized kernel-weighted model to account for similar methylation profiles using the relative probe distance from "nearby" CpG sites. We also extend this model by proposing an array-adaptive version in attempt to account for the differences …

Maximizing Network Throughput In Heterogeneous Uav Networks, Shuyue Li, Jing Li, Chaocan Xiang, Wenzheng Xu, Jian Peng, Ziming Wang, Weifa Liang, Xinwei Yao, Xiaohua Jia, Sajal K. Das

Computer Science Faculty Research & Creative Works

In this paper we study the deployment of an Unmanned Aerial Vehicle (UAV) network that consists of multiple UAVs to provide emergent communication service for people who are trapped in a disaster area, where each UAV is equipped with a base station that has limited computing capacity and power supply, and thus can only serve a limited number of people. Unlike most existing studies that focused on homogeneous UAVs, we consider the deployment of heterogeneous UAVs where different UAVs have different computing capacities. We study a problem of deploying K heterogeneous UAVs in the air to form a temporarily connected …

A Sentiment Analysis Approach For Understanding Users’ Perception Of Metaverse Marketplace, Ahmed Al-Adaileh, Mousa Al-Kfairy, Mohammad Tubishat, Omar Alfandi

All Works

This research explores the user perceptions of the Metaverse Marketplace, analyzing a substantial dataset of over 860,000 Twitter posts through sentiment analysis and topic modeling techniques. The study aims to uncover the driving factors behind user engagement and sentiment in this novel digital trading space. Key findings highlight a predominantly positive user sentiment, with significant enthusiasm for the marketplace's revenue generation and entertainment potential, particularly within the gaming sector. Users express appreciation for the innovative opportunities the Metaverse Marketplace offers for artists, designers, and traders in handling and trading digital assets. This positive outlook is tempered by notable concerns regarding …

Remediating History: A Review Of Restoration For Creeks Polluted From Historical Mining Sites, With The Red Boy Mine As A Primary Case Study, Kara Atiyeh

University Honors Theses

I conducted a literature review to examine the key aspects of restoring watersheds affected by pollution from historical mining. This review is then applied to a case study discussion of the Red Boy Mine and Clear Creek remediation project in Granite, Oregon. The goal of this discussion is to explore how an analysis of site conditions along with current literature on management practices can help guide these projects. Thousands of abandoned hard rock mines remain throughout the country, and many pose serious environmental health effects. Heavy metals like cadmium, nickel, and copper are brought to the surface from mining activity, …

The Cascading Effects Of Database Design, Liam Mccracken

University Honors Theses

This paper details how a relational database influenced the design of the rest of a software project. The software project in question is WonderTix, an open-source ticketing and donation platform for the use of Portland Playhouse under continuous development by teams of Portland State students as their computer science capstone project. The paper, a capstone review thesis, examines WonderTix as an instantiation of the Model-View-Controller design pattern, noting how the model, a relational database based on the SQL standard, influenced the design of the view and controller components. This influence is explored from three angles. First, when the implementation of …

Comparison Between Galfit And Lenstronomy To Analyze The Host Galaxies Of Reverberation Mapped Active Galactic Nuclei, Samantha Kay Allen

Physics

Active Galactic Nuclei (AGN) are some of the brightest objects within our Universe. Most galaxies contain a supermassive black hole (SMBH) at their center, but not all are powered by active accretion which can form an AGN. Due to the conservation of angular momentum, dust and gas rotate around the SMBH to form a disk. The large gravitational potential energy from the SMBH is converted into heat through friction, which produces a hot and luminous source of light. As a result, the SMBH is unresolved. Through a technique known as reverberation mapping (RM), the mass of the SMBH has been …

Investigating The Relationship Between Single And Multiple Sersic Models Of Active Galaxies Using Galfit, Ellie H. Johnson

Physics

Supermassive Black Holes (SMBHs) can be found in the center of almost every galaxy, and in some cases, can form Active Galactic Nuclei (AGNs). AGNs are some of the brightest objects in our observable Universe and are distinguished from quiescent galaxies by accretion onto the central SMBH, which forms a disk where the luminosity is produced. Reverberation mapping (RM) of broad-line AGNs determines the mass of the SMBH by resolving the gravitational sphere of influence of the BH ``in time". In this study, GALFIT is used to fit 2D analytic functions to existing Hubble Space Telescope (HST) images for 23 …

Identifying Ion-Scale Waves In Parker Solar Probe Sub-Alfvénic Intervals, Nicholas Henry Androski, Kristoff Paulson

Physics

Identification of coherent quasi-parallel ion-scale (1-32 Hz) wave activity in sub-Alfvénic regions of the solar wind observed by NASA's Parker Solar Probe during perihelion encounters 8 to 16. Wave activity is filtered computationally by coherency, circular polarization and propagation angle with respect to the mean magnetic field. Initial statistical results are presented with suggestions for future improvements and studies. A general overview of the heliosphere and the context of ion-cyclotron waves (an ion-scale wave) in the coronal heating problem. Along the way to identify ion-scale wave activity, tables of sub-Alfvénic intervals and current sheet crossings for encounters 8 to 16 …

Matching The Scales Of Planning And Environmental Risk: An Evaluation Of Community Wildfire Protection Plans In The Western Us, Matthew Hamilton, Cody Evers, Max Nielsen-Pincus, Alan Ager

Environmental Science and Management Faculty Publications and Presentations

Theory predicts that effective environmental governance requires that the scales of management account for the scales of environmental processes. A good example is community wildfire protection planning. Plan boundaries that are too narrowly defined may miss sources of wildfire risk originating at larger geographic scales whereas boundaries that are too broadly defined dilute resources. Although the concept of scale (mis)matches is widely discussed in literature on risk mitigation as well as environmental governance more generally, rarely has the concept been rigorously quantified. We introduce methods to address this limitation, and we apply our approach to assess scale matching among Community …

Parabolic And Non-Parabolic Surfaces With Small Or Large End Spaces Via Fenchel-Nielsen Parameters, Michael Antony Pandazis

Dissertations, Theses, and Capstone Projects

We consider conditions on the Fenchel-Nielsen parameters of a Riemann surface X that determine whether or not a surface X is parabolic. Fix a geodesic pants decomposition of a surface and call the boundary geodesics in the decomposition cuffs. For a zero or half-twist flute surface, we prove that parabolicity is equivalent to the surface having a covering group of the first kind. Using that result, we give necessary and sufficient conditions on the Fenchel-Nielsen parameters of a half-twist flute surface X with increasing cuff lengths such that X is parabolic. As an application, we determine whether or not each …

Environmental Fate And Transport Of Pfas In Wastewater Treatment Plant Effluent Discharged To Rapid Infiltration Basins, Kai M. Trobisch

Masters Theses

Fate and transport of per- and polyfluoroalkyl substances (PFAS) in wastewater treatment plant (WWTP) effluent discharged to rapid infiltration basins (RIBs) is investigated using data from 26 WWTPs in Michigan and numerical modeling to assess the role of air-water interface (AWI) sorption in modulating mass fluxes to the saturated zone. Analysis of RIB physical properties yields a median separation distance of 6.5 meters between land surface and the water table, and a continuum of area-normalized effluent fluxes ranging from 0.01 to 0.62 meters per day. A subset of WWTPs with RIBs indicate higher PFAS concentrations in groundwater than effluent with …

Moral Responsibility And Other Visceral Attitudes Of Western Michigan University Students Toward Food Waste, Quinn Heiser

Masters Theses

Despite the large number of people that go hungry on a regular basis in America, food waste remains a looming issue, globally and nationally. Both American college students and the universities themselves contribute a large portion to the national food waste totals. A dichotomy that is especially curious is the difference between students who live on-campus and whose main source of meals is the dining centers, versus students who live off campus and rely mainly on groceries to make meals independently. However, food waste has seldom been studied in the context of the fact that college is a major transition …

Causal Inference Using Bayesian Network For Search And Rescue, Amanda Belden

Master's Theses

People who are considered missing have much higher probabilities of being found dead compared to those who are not considered missing in terms of Search and Rescue (SAR) missions. Dementia patients are incredibly likely to be declared missing, and in fact after removing those with dementia the probability of the mission being regarded as missing person case is only about 10%. Additionally, those who go missing are much more likely to be on private land than on protected areas such as forests and parks. These and similar associations can be represented and investigated using a Bayesian network that has been …

Unmasking The Lurking: Malicious Behavior Detection For Iot Malware With Multi-Label Classification, Ruitao Feng, Sen Li, Sen Chen, Mengmeng Ge, Xuewei Li, Xiaohong Li

Research Collection School Of Computing and Information Systems

Current methods for classifying IoT malware predominantly utilize binary and family classifications. However, these outcomes lack the detailed granularity to describe malicious behavior comprehensively. This limitation poses challenges for security analysts, failing to support further analysis and timely preventive actions. To achieve fine-grained malicious behavior identification in the lurking stage of IoT malware, we propose MaGraMal. This approach, leveraging masked graph representation, supplements traditional classification methodology, empowering analysts with critical insights for rapid responses. Through the empirical study, which took three person-months, we identify and summarize four fine-grained malicious behaviors during the lurking stage, constructing an annotated dataset. Our evaluation …

Let’S Think Outside The Box: Exploring Leap-Of-Thought In Large Language Models With Multimodal Humor Generation, Shanshan Zhong, Zhongzhan Huang, Shanghua Gao, Wushao Wen, Liang Lin, Marinka Zitnik, Pan Zhou

Research Collection School Of Computing and Information Systems

Chain-of-Thought (CoT) [2, 3] guides large language models (LLMs) to reason step-by-step, and can motivate their logical reasoning ability. While effective for logical tasks, CoT is not conducive to creative problem-solving which often requires out-of-box thoughts and is crucial for innovation advancements. In this paper, we explore the Leap-of-Thought (LoT) abilities within LLMs — a nonsequential, creative paradigm involving strong associations and knowledge leaps. To this end, we study LLMs on the popular Oogiri game which needs participants to have good creativity and strong associative thinking for responding unexpectedly and humorously to the given image, text, or both, and thus …

Learning Dynamic Multimodal Network Slot Concepts From The Web For Forecasting Environmental, Social And Governance Ratings, Meng Kiat Gary Ang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Dynamic multimodal networks are networks with node attributes from different modalities where the at- tributes and network relationships evolve across time, i.e., both networks and multimodal attributes are dynamic; for example, dynamic relationship networks between companies that evolve across time due to changes in business strategies and alliances, which are associated with dynamic company attributes from multiple modalities such as textual online news, categorical events, and numerical financial-related data. Such information can be useful in predictive tasks involving companies. Environmental, social, and gov- ernance (ESG) ratings of companies are important for assessing the sustainability risks of companies. The process of …

Few-Shot Learner Parameterization By Diffusion Time-Steps, Zhongqi Yue, Pan Zhou, Richang Hong, Hanwang Zhang, Sun Qianru

Research Collection School Of Computing and Information Systems

Even when using large multi-modal foundation models, few-shot learning is still challenging—if there is no proper inductive bias, it is nearly impossible to keep the nuanced class attributes while removing the visually prominent attributes that spuriously correlate with class labels. To this end, we find an inductive bias that the time-steps of a Diffusion Model (DM) can isolate the nuanced class attributes, i.e., as the forward diffusion adds noise to an image at each time-step, nuanced attributes are usually lost at an earlier time-step than the spurious attributes that are visually prominent. Building on this, we propose Time-step Few-shot (TiF) …

Gts: Gpu-Based Tree Index For Fast Similarity Search, Yifan Zhu, Ruiyao Ma, Baihua Zheng, Xiangyu Ke, Lu Chen, Yunjun Gao

Research Collection School Of Computing and Information Systems

Similarity search, the task of identifying objects most similar to a given query object under a specific metric, has gathered significant attention due to its practical applications. However, the absence of coordinate information to accelerate similarity search and the high computational cost of measuring object similarity hinder the efficiency of existing CPU-based methods. Additionally, these methods struggle to meet the demand for high throughput data management. To address these challenges, we propose GTS, a GPU-based tree index designed for the parallel processing of similarity search in general metric spaces, where only the distance metric for measuring object similarity is known. …

Navigating The Ethical Terrain Of Ai In Higher Education: Strategies For Mitigating Bias And Promoting Fairness, Emily Barnes, James Hutson

Faculty Scholarship

Artificial intelligence (AI) and machine learning (ML) are transforming higher education by enhancing personalized learning and academic support, yet they pose significant ethical challenges, particularly in terms of inherent biases. This review critically examines the integration of AI in higher education, underscoring the dual aspects of its potential to innovate educational paradigms and the essential need to address ethical implications to avoid perpetuating existing inequalities. The researchers employed a methodological approach that analyzed case studies and literature as primary data collection methods, focusing on strategies to mitigate biases through technical solutions, diverse datasets, and strict adherence to ethical guidelines. Their …