Digital Commons Network^™

The Distribution Of A-Numbers Of Hyperelliptic Curves In Characteristic Three, Derek Garton, Jeffrey Lin Thunder, Colin Weir

Mathematics and Statistics Faculty Publications and Presentations

In this paper we present a new approach to counting the proportion of hyperelliptic curves of genus g defined over a finite field Fq with a given a-number. In characteristic three this method gives exact probabilities for curves of the form Y 2 = f(X) with f(X) ∈ Fq[X] monic and cubefree, probabilities that match the data presented by Cais et al. in previous work. These results are sufficient to derive precise estimates (in terms of q) for these probabilities when restricting to squarefree f. As a consequence, for positive integers a and g we show that the nonempty strata …

Numerics: A .Net Library For Numerical Computing, Statistical Analysis, And Risk Assessment, C. Haden Smith, Woodrow L. Fields, Julian Gonzalez, Sadie Niblett, Brennan Beam, Brian Skahill

Mathematics and Statistics Faculty Publications and Presentations

Numerics is a free and open-source numerical computing library for .NET, developed by the U.S. Army Corps of Engineers Risk Management Center (USACE-RMC). The library provides 43 univariate probability distributions with L-moment and maximum likelihood parameter estimation, eight Markov Chain Monte Carlo (MCMC) samplers for Bayesian inference, bootstrap uncertainty quantification, bivariate copulas, optimization algorithms, and numerical methods for integration, differentiation, root finding, and linear algebra. Numerics targets engineers, scientists, and analysts working in infrastructure risk assessment, flood frequency analysis, and Monte Carlo simulation within .NET-based enterprise systems. The library supports .NET 8.0 through 10.0 and .NET Framework 4.8.1 and is …

Organizational Causes Of Chronic Absenteeism: Unpacking The Conditions For Learning To Increase Regular Attendance, Melissa Glover

Educational Leadership Professional Doctorate Dissertations

This study employed an improvement science methodology, using plan-do-study-act (PDSA) cycles of improvement, to address the persistent problem of chronic absenteeism within the Gateway School District, where annual absentee rates hovered around 45% and were historically 10% higher for students with disabilities compared to their nondisabled peers. The leadership team engaged in a thorough review of parent and student perceptions of school and aligned findings with Chang’s (2019) conditions for learning framework to pinpoint actionable areas for growth. These findings were then organized into a theory of action using a driver diagram approach. This foundational work led to the identification …

Key To Spartina Of The West Coast Based On Vegetative Characteristics, Mary Pfauth, Mark D. Sytsma, Mitchell Kloer, Jennifer Riddle, Jacob Rose, Gabriel E. Campbell

Center for Lakes and Reservoirs Publications and Presentations

In their natural condition, Pacific Coast estuaries have extensive open mudflats in the intertidal area that are important shorebird feeding habitat and are used for oystering and recreational fishing. Several non-native cordgrass species are invading Pacific estuaries and damaging these functions and uses. Early detection is critical to effective management of cordgrass infestation. This key is intended to provide an easy-to-use reference for quick identification of Spartina (synonym: Sporobolus) species on the Pacific coast. We choose to focus on vegetative characteristics here, since flowers are not always visible when it can be advantageous to survey.

This publication is intended to …

The Johnson-Křížek-Mercier Elasticity Element In Higher Dimensions, Jay Gopalakrishnan, Johnny Guzman, Jeonghun J. Lee

Mathematics and Statistics Faculty Publications and Presentations

Mixed methods for linear elasticity with strongly symmetric stresses of lowest order are studied in this paper. On each simplex, the stress space has piecewise linear components with respect to its Alfeld split (which connects the vertices to barycenter), generalizing the Johnson–Mercier two-dimensional element to higher dimensions. Further reductions in the stress space in the three-dimensional case (to 24 degrees of freedom per tetrahedron) are possible when the displacement space is reduced to local rigid displacements. Proofs of optimal error estimates of numerical solutions and improved error estimates via postprocessing and the duality argument are presented.

Microbial Communities Of Selected Regions Of The Deep Springs Lake Aquifer System, Rania Zaki, Emma Bourne, Andrew Storino, Jay Nadeau

Physics Faculty Publications and Presentations

Deep Springs Lake is a small, isolated, highly alkaline soda lake in Inyo County of Eastern California, USA. It is a seasonally filled salt lake or playa, and is part of a closed aquifer system. Such closed systems are globally rare, occurring only in arid zones where annual evaporation is greater than annual rainfall. Deep Springs Lake’s hydrology and geology have been well studied, and it is home to a unique toad species, but its microbiome remains unexplored. Here we perform 16S, 18S, and ITS amplicon sequencing of the lake water, dried salt crust at the edges the lake, and …

Leveraging High-Performance Cloud Computing To Model Underwater Acoustic Propagation And Scattering From Time-Evolving Rough Sea-Surfaces Using The Finite-Difference Time-Domain Method, James Alexander Higgins

Dissertations and Theses

This dissertation presents a two-dimensional (2D) Finite-difference Time-domain (FDTD) model for simulating underwater acoustic propagation and scattering from a one-dimensional (1D) time-evolving rough sea-surface. The techniques discussed are extendable to three spatial dimensions. Traditional acoustic modeling techniques often rely on a "frozen" sea-surface assumption, which proves inadequate for long-duration signals interacting with the time-evolving boundary at many different wave height displacements during its transit. To address this, a new FDTD update equation incorporating a variable subgrid is developed, significantly enhancing spatial accuracy at the boundary without increasing computational cost or compromising stability.

The model's accuracy is rigorously validated against established …

Oregon State Rank Assessment For Plumed Clover (Trifolium Plumosum Var. Plumosum), Nora Dunkirk

Institute for Natural Resources Publications

Oregon state conservation status assessment for Plumed Clover (Trifolium plumosum var. plumosum) using NatureServe methodology, 2025.

Online Decision Mamba, Trenton W. Ruf

Dissertations and Theses

Online in-context reinforcement learning enhances offline-trained policies through online fine-tuning. We introduce Online Decision Mamba (ODM), an architecture that replaces the attention mechanism in Online Decision Transformers (ODT) with the Mamba module to improve long-context sequence modeling and overall RL performance. We performed in-depth evaluations on MuJoCo (OpenAI Gym) and Atari benchmarks, comparing ODM against state-of-the-art offline and online baselines—including Decision Mamba (DM) and ODT. Our results show that ODM achieves competitive or superior performance, with particularly robust gains when initial datasets lack expert demonstrations. In the Qbert Atari environment, ODM shows context-length sensitivity similar to offline DM; however, we …

Citizen's Rare Plant Watch 2025 Recap, Nora Dunkirk

Rae Selling Berry Seed Bank and Plant Conservation Program

Citizen's Rare Plant Watch (CRPW) is a community science program which takes volunteers out to visit populations of rare and threatened Oregon native plant species. Volunteers assess their health and viability, update the Oregon Biodiversity Information Center (ORBIC) state database for rare species, and help contribute to data driven management decisions throughout the state. Housed at Portland State University, this program is open to the public and attracts plant lovers from diverse backgrounds. Each spring, CRPW trains volunteers on methods of data collection, and this year we implemented new technology using Survey123 to streamline population assessments. We focus on species …

Spike Timing Depended Plasticity Produces Unsupervised Learning Of Synergistic Muscle Feedback In A Synthetical Neural Network, Mark Allen Pupkiewicz

Dissertations and Theses

This study investigates how type Ia feedback from muscle spindles can be organized into groups representing agonistic muscle pairs through Spike Timing Dependent Plasticity (STDP). A single degree of freedom joint is actuated with four biologically modeled muscles forming two agonistic pairs. In order to emulate the sensory dynamics of biological muscle spindles, sensors in the model record the active length and velocity states of each muscle, the two primary factors eliciting type Ia afferent responses. In biological networks, synapses from Ia sensory neurons frequently activate interneurons representing agonistic muscle sources. This research investigates whether this organization can emerge in …

Systematics And Systems Theory: Reconstructability Analysis Of The Tetrad, Martin Zwick

Complex Systems Faculty Publications and Presentations

This talk discusses the relationship between systems theory, specifically Reconstructability Analysis, and Systematics, a systems theory-like framework of number symbolism developed by John G. Bennett, which he presented in his four-volume magnum opus, The Dramatic Universe. The talk, given to a community of people interested in Bennett's ideas, focuses on Martin Zwick's paper "Ideas and Graphs: the Tetrad of Activity" archived at https://archives.pdx.edu/ds/psu/36249.

Adaptive Image Acquisition Algorithms For Resource-Constrained Single-Photon Cameras, Yeganeh Jalalpour, Wu-Chi Feng

Computer Science Faculty Publications and Presentations

Emerging single-photon camera (SPC) technologies have unique challenges in data acquisition and processing. Unlike conventional sensors that produce a single 8- to 16-bit brightness value per pixel, SPCs record photon arrivals with many more samples per pixel, using high floating-point precision for each photon collected. This means that they must handle potentially millions of timestamps, especially at higher spatial resolutions and in the presence of ambient light, creating bottlenecks within the pixel circuitry. To address these challenges associated with SPCs, this paper proposes adaptive algorithms designed to efficiently distribute hardware resources among groups of pixels. By selectively subsampling the data …

Hint-Guided Video Frame Interpolation For Video Compression, Pan Tan, Wu-Chi Feng

Computer Science Faculty Publications and Presentations

Traditional video compression continues to advance, but the gainsin efficiency are diminishing and come at the cost of higher compu-tational complexity. Despite achieving competitive rate-distortionresults, current neural video codecs (NVCs) generally lack sup-port for a wide range of quality levels, often requiring multiplemodels to achieve flexible rate control, which increases both train-ing cost and deployment complexity. To address the limitations ofboth traditional codecs and current NVCs, we propose a hybridvideo compression framework that integrates traditional codecswith hint-guided video frame interpolation (VFI), a learning-basedtechnique for synthesizing intermediate frames. By using decodedreference frames and leveraging compressed-domain hints to guideinterpolation, our method improves …

An Innovative Hdm Model For Assessing Renewable Heat Energy Resources In Utility Energy Systems, Mark Alan Ryan

Dissertations and Theses

Renewable Heat Energy projects exhibit numerous unique, complex, and often conflicting characteristics, including varying project sizes, diverse energy resources, stakeholder demands, and significant challenges in energy conversion applications. Traditionally, cash flow analysis and return on investment are the most widely recognized metrics for evaluating remote energy projects. However, numerous quantitative and qualitative factors influence the overall performance and success of Renewable Heat Energy System (RHES) projects. A comprehensive approach using advanced tools is essential for assessing the factors and criteria that significantly impact these projects.

This research investigates the key quantitative and qualitative factors that contribute to the successful implementation …

Human Evil (In The Weird), Lucas Ethridge

University Honors Theses

This paper examines a trending doom in speculative fiction: the post-human age. Many modern works have started to look past human civilization as humans surrender all hope and faith in a climate-doomed world. Honing in on core concepts in Weird fiction, this paper explores human merit through Old and New Weird. A good part spends time establishing the canon, looking at similar patterns across age, philosophy, war and genre. The chief question asks if humankind was ever worth saving.

Capstone Reflection: Developing A Muslim Prayer App For Psu Students, Jeremiah Su

University Honors Theses

This thesis examines the development process of the Muslim Student Association (MSA) App, a computer science capstone project. The app strives to help the Muslim community at Portland State University (PSU) and the Portland area by consolidating essential information for prayers, such as local prayer times, nearby masjids, and the direction of Qibla. The team behind this project was developed by 6 computer science developers, a majority of whom were from the Muslim culture and background. This paper describes the entire capstone development process from the perspective of a developer who is not rooted in Muslim customs. It also describes …

Experience From A Distance: Improving Transparency For The Multnomah Athletic Club, Matthew Penner

University Honors Theses

Portland is home to the largest and one of the most prestigious athletic clubs in the world: Multnomah Athletic Club. In many ways, it is the pinnacle of luxury and innovation, and over time, it finds any way to entice prospective members to pay the expensive upfront fee of $6000 and monthly membership fees exceeding $300. Due to the previous technological barrier, which was not being able to see the full extent of what amenities the club had to offer, the club faced major challenges in recruitment and marketing. Over two academic terms, a team of six computer science capstone …

Bridging Boundaries: Integration Of Culturally Relevant Resources, James D. Ware, Evan W. Stokes

Northwest Journal of Teacher Education

This qualitative study examines the impact of culturally relevant resources on student engagement, motivation, and academic achievement in a language arts classroom. Since school curricula are increasingly scrutinized for their ability to reflect the historical and cultural diversity of student populations, this study investigates how integrating culturally relevant pedagogy can enhance learning outcomes. The study explores the student impact of blending culturally relevant teaching materials with traditional educational frameworks to foster a more inclusive and equitable classroom environment. By analyzing student feedback from a writing-intensive English course that utilized culturally relevant resources, the study seeks to provide insights into how …

Undergraduate Stem Student Reflections On The Academic Support Ecosystem At A Rural Minority Serving Institution: The Importance Of Relationship, Stephany Runninghawk Johnson, Jessica L. Black, Karolynn Tom

Northwest Journal of Teacher Education

This paper presents a research project with a group of STEM majoring undergraduates attending a Hispanic Serving Institution participating in the CRESCENT program intended to support undergraduates through their basic math and science courses. The research questions addressed in this paper include: What part of CRESCENT were students utilizing the most and how were they helpful? How did CRESCENT support students through COVID? What can we learn from this data to make future programs more responsive and relevant to STEM majoring students? We found that during COVID students were missing in person contact, had heightened responsibilities and distractions at home, …

Introduction: The Time Is Now, Kimberly J. Pfeifer

Northwest Journal of Teacher Education

No abstract provided.

Realization Of Deterministic Quantum Circuits For Non-Deterministic Or Incompletely Specified Quantum State Machines, Manjith Kumar, Marek Perkowski

Electrical and Computer Engineering Faculty Publications and Presentations

In classical logic design, there are machine learning methods based on converting a set of input-output traces to non-deterministic automata that are then converted to deterministic automata and synthesized using logic gates. This approach has not yet been extended to quantum automata. In this paper, we present a method to convert a set of input-output traces to a non-deterministic automaton, which is then converted to an incompletely specified multi-output Boolean function. The existing logic synthesis approaches for designing quantum circuits are insufficient to handle incompletely specified functions. So, we present a novel algorithm to synthesize logic functions with don’t cares …

Information Literacy In The Artificial Intelligence Era: A Proposed Framework, Radwan Ali, Matthew L. Wilson

Communications in Information Literacy

Artificial intelligence (AI) systems and applications have become ubiquitous across daily life. While AI offers numerous positive opportunities, it also presents numerous challenges. Information literacy (IL) advocates are concerned about the risks that accompany AI systems. Given the universal reach of AI with its potential pitfalls and perils, researchers and practitioners from various fields and disciplines should inform the dialogue on AI’s development and application. A critical aspect of this dialogue comes in the form of information literacy. Our paper aims to answer the question “How can information literacy guide users in navigating and shaping artificial intelligence technologies?” by establishing …

Fractional Order Hierarchical Decompositions Using Multigrid Components, Panayot S. Vassilevski

Mathematics and Statistics Faculty Publications and Presentations

Motivated by the fractional order multilevel decompositions of finite element spaces developed previously, we exploit additive representations of popular multigrid (MG) cycles to design fractional order MG decompositions. The additive representations enable us to scale the individual hierarchical components thus ending up with fractional order hierarchical decompositions that are based on the readily available MG components. This results in a highly efficient and scalable (in terms of high-performance) fractional order hierarchical MG decompositions that we tested in the setting of finite element white noise sampling as an alternative to PDE-based white noise sampling using fractional order shifted Laplacians.

Security Vulnerabilities And Defense Tactics For Generative Ai Application Development, Kyle Klein

University Honors Theses

Generative AI (GenAI) applications such as OpenAI's ChatGPT leverage large language models (LLMs) trained on enormous amounts of data to accomplish tasks such as document editing, summarization, and query response. Chatbots and LLM programs that are equipped with retrieval-augmented generation (RAG) have the ability to draw upon data provided by developers and users to improve the quality of the program's responses. LLM technology has even expanded to generate images, audio, and video from user instructions. Designed around unpredictable user input and typically composed of many opaque components, LLM software products face a paradigm shift of new, constantly evolving security challenges. …

Jhtdb-Wind: A Web-Accessible Large-Eddy Simulation Database Of A Wind Farm With Virtual Sensor Querying, Xiaowei Zhu, Shuolin Xiao, Ghanesh Narasimhan, Luia A. Martinez-Tossas, Michael Schnaubelt, Gerard Lemson, Hanxun Yao, Alexander S. Szalay, Dennice F. Gayme, Charles Meneveau

Mechanical and Materials Engineering Faculty Publications and Presentations

This paper introduces JHTDB-wind (https://turbulence.idies.jhu.edu/datasets/windfarms), a publicly accessible database containing large-eddy simulation (LES) data from wind farms. Building on the framework of the Johns Hopkins Turbulence Database (JHTDB), which hosts direct numerical and some large-eddy simulation datasets of canonical turbulent flows, JHTDB-wind stores the full space-time (4D) history of the flow and provides users the ability to access and query the data via a web-based virtual sensor interface. The initial dataset comprises LES results from a large wind farm with 6 X 10 turbines, modeled using a filtered actuator line method, under conventionally neutral atmospheric conditions. This data comprises one …

Flow Control Tactics For Photovoltaic Modules: Coherent Structure And Heat Shedding Amplification, Sarah Elizabeth Smith

Dissertations and Theses

Solar photovoltaic systems have become the fastest growing renewable technology in the last several years. However, large-scale systems are at the mercy of their external environments, where extreme heating and wind-flung debris impact their efficiency and useable life. The work in this dissertation presents studies aimed to both understand and mitigate for these effects by identifying the underlying physics which govern them. Exploring flow control as a tactic to combat environmental heating, collective work discusses the role of turbulent fluid dynamics within large-scale systems as pertains to convective heat transfer, turbulent structure formation, and particle-laden environments. Wind tunnel experiments on …

Field Canals Improvement Projects Duration Prediction: A Comparative Analysis Of Machine Learning Models, Hania Ghouse, Ukaegbu Chinonso Ishmael, Edgar Dario Obando-Paredes, Hashem Shafik Shakir, Ali Al-Bayaty

Electrical and Computer Engineering Faculty Publications and Presentations

There are several essential elements in project construction management to be studied appropriately, and priority to these elements, such as cost and duration, is predominantly interesting to be investigated. In this research, the duration of field canal improvement projects (DFCIP) was predicted using two relatively new machine learning (ML) models - the Multivariate Adaptive Regression Spline (MARS) and Extreme Learning Machine (ELM). The targeted DFCIP was calculated using other dependent parameters, such as the length of the pipe, years of construction, the geographical zone of the network, the supplied area with water, and finally the actual cost of the field …

Future Vision And Action Recommendations, Sondoss Elsawah, Melissa Haeffner, Anthony Jakeman

Environmental Science and Management Faculty Publications and Presentations

Let us imagine a future world where water management is more fully integrated and supported by the science of sociohydrology and related metadisciplines. This is a vision for the future where the social, cultural, environmental, and economic values of water are explicitly considered through the lens of the science–water policy interface. The ultimate value of research will be measured by how much it supports improvements in water resources and hazards management and, in particular, completes and enriches the science–water policy interface.

Human-Drought Systems, Margaret Garcia, Elizabeth Koebele, Melissa Haeffner, Anne F. Van Loon, Newsha Ajami, Claudia Teutschbein, Marjolein Mens, Sylvain Massuel, Christopher White, Burcu Tezcan

Environmental Science and Management Faculty Publications and Presentations

Advancing our understanding of the processes linking social and hydrological systems is an essential step toward managing drought risk and increasing drought resilience. Over the past decade, numerous studies have advanced our understanding of human influences on drought propagation, drought responses and their immediate and long-term consequences, and decisions and conditions leading to drought resilience. These advances have been achieved through: (1) the development of datasets that document drought progression, hazards, risk, vulnerability, and adaptation capacity; (2) creation of new modeling methods and application of models to build and test theory; and (3) empirical analyses from in depth case studies …