The Baltic Bear Trap Wargame, Connor Crookham

Space and Defense

Modern military education increasingly relies on experiential tools that allow students to explore the complexity of contemporary conflict in ways that lectures and readings alone cannot achieve. Nowhere is this more evident than in the emerging emphasis on multi-domain operations, integrated deterrence, and the blurred boundaries between competition and armed conflict. The Baltic Bear Trap wargame was developed as a student design project to meet this instructional need, offering a structured environment in which players must think, plan, and act as operational-level decision makers confronting a deteriorating security situation in the Nordic–Baltic region. Built for use at the Swedish Defense …

Geographical Pattern Analysis Of Gis Images With Deep Learning And Voronoi Network, Nidaa Kareem, Tawfiq A. Al-Assadi

Journal of Intelligent Informatics, Networking, and Cybersecurity

Localization is not enough for the analysis of spatial patterns; a principled geometric and statistical framework is required. This paper proposes an integrated spatial intelligence system combining deep learning, computational geometry, and spatial statistics, which is a unified and interpretable system. It is based on segmentation localization that accurately localizes the centroid of each object without the disadvantages of the bounding box. These centroids form a natural Voronoi tessellation of regions of spatial influence intrinsic to the data instead of imposing any artificial restrictions. A geometry-based density formulation is used to improve representation, which includes Voronoi cell areas and neighborhood …

Deterministic Multi-Domain Computational Framework For Bi-Ionic Propulsion And Thermoelectric Resonance (Stalwart V18.1), Daniel Schramm

Defensive Publications Series

This paper details the mathematical and computational architecture of a multi-domain physics engine designed to validate interrelated aerospace systems, specifically bi-ionic vector thrust and solid-state thermoelectric energy recycling. To eliminate computational hallucination and enforce strict physical boundaries, the engine is constructed utilizing highly deterministic Python libraries: SciPy for immutable, universally accepted physical constants; SymPy for strict, symbolic equation rendering and mathematical proofs; and NumPy for continuous spatial array generation. This framework interlinks discrete physical phenomena (magnetic containment, plasma gyration, kinetic wave damping, and thermal energy harvesting) into a singular, codependent mathematical ecosystem. The novel contribution is the Master Resonance Equation …

System And Method For Statistical Modeling And Automated Lifecycle Refresh Detection Of Digital Media Assets, Manisha Arora, Yassine Idrissi, Bruno Caforio

Defensive Publications Series

A data-driven, statistically rigorous analytical framework is disclosed for determining performance decay and optimizing the replacement timing of digital media assets (such as images and videos) in digital media campaigns. The system ingests campaign-level and asset-level metrics on a daily basis and extracts high-dimensional visual and semantic embedding vectors from the media assets using a deep neural network feature extractor. A visual taxonomy is constructed by clustering similar assets into visual archetypes using K-Means clustering, allowing for aggregate fatigue analysis within specific thematic content clusters. The statistical decay engine fits a non-linear saturation model (e.g., a Hill function S-curve) to …

The Prospector, September 1, 2026, Student Publications

The Prospector

No abstract provided.

Generalized Logit Adjustment: Improved Fine-Tuning By Mitigating Label Bias In Zero-Shot Vision Models, Beier Zhu, Qianru Sun, Xun Yang, Hanwang Zhang

Research Collection School Of Computing and Information Systems

Foundation models like CLIP allow zero-shot transfer on various tasks without additional training data. Yet, the zero-shot performance is less competitive than a fully supervised one. Thus, fine-tuning and ensembling are also commonly adopted to better fit the downstream tasks. However, we argue that such prior work has overlooked the inherent biases in foundation models. Due to the highly imbalanced Web-scale training set, foundation models are inevitably skewed toward frequent semantics, and thus the subsequent fine-tuning or ensembling is still biased. In this study, we systematically examine the biases in foundation models and demonstrate the efficacy of our proposed Generalized …

Stat 216.51: Introduction To Statistics, Blake P. Miller

University of Montana Course Syllabi, 2026-2030

No abstract provided.

Readme Template For Geospatial Data, Alyssa Renteria

Library Faculty Research

A readme file provides descriptive information about a dataset, file(s), or software. The goal is to ensure that the files and data can be correctly interpreted by your future self or others when sharing or publishing data, code, or software.

Revisiting The Secretary Problem, Steven J. Brams, D. Marc Kilgour

The Mathematics Enthusiast

The venerable Secretary Problem asks how a decision maker (DM) should select one of n candidates, who come up randomly, when the only information available is each candidate’s strict rank within the set of previous applicants. Moreover, DM may select only the current candidate. Our illustrative case has n = 9 candidates, for which the Standard Method is to reject outright the first 3 candidates and then choose the first of the 4th through 8th candidates who is better than all of the first three, or the 9th candidate if none of them is. We compare the Standard Method with …

Resource-Efficient Sustainable Farming Systems: A Comparative Study Of Natural And Chemical Farming Practices In Western Himalayas, Rohit Kumar Vashishat, Divyanshu Divyanshu, Subhash Sharma, Inder Dev, Rajeshwar Singh Chandel, Ashu Chandel, Shraddha Shraddha, Xiao-Mei Yang, Kovács András, Rohit Khargotra

Artículos científicos

A revolutionary transformation is underway in agricultural systems, with Natural Farming (NF) being promoted as an agrochemical-free, agroecological alternative to conventional Chemical Farming (CF) in several states of India. To assess the successful adoption of NF among smallholder farming systems in the Himalayan region, this study was conducted in Himachal Pradesh, India. Primary data were collected from 360 randomly selected farmers across six districts using a simple random sampling technique. The study mainly focused on the marginal and small farmers, because 80% of farmers in state are marginal and small. The study evaluated the comparative economics NF and CF, corelation …

September 2026, Denise Landrum-Geyer

aCAdemicS: The Newsletter of the SWOSU College of Arts & Sciences

The more things change...

We’ve seen a lot of changes on campus over the last year. As the dust settles after all kinds of moves and transitions, now seems as good a time as any to reintroduce the aCAdemicS newsletter. This newsletter, the brainchild of Dr. Peter Grant, originally ran from 2015-2019 (check out older issues in SWOSU’s Digital Commons).

As a writer and writing teacher at heart, I cannot help but try to revive this newsletter to celebrate all things CAS and document the amazing things happening in our college. In between newsletters, you can also find SWOSU …

Methodological Optimization Of Microplastic Visualization For The Comparison Of Eastern Oysters Cultivated In Traditional Plastic Or Novel Non-Plastic Aquaculture Farm Gear, Mikayla Straube

All Theses And Dissertations

Microplastics (< 5 mm) are a pervasive physical pollutant. This study was predominately focused on the development and utilization of fluorescence microscopy to locate and identify microplastics and other particles in the presence of a background autofluorescing biogenic precipitate. Oyster digest samples are visualized with fluorescent microscopy using Nile Red (NR). Photobleaching, or concentrated light exposure, of the filters was tested to determine if it can quench the autofluorescence signal. It was found that photobleaching significantly decreased autofluorescence intensity of the biogenic precipitate in emission wavelengths 518, 580, and 670 nm even with the application of NR, while minimally impacting the fluorescence behavior when bound to plastic particles. In application, fluorescence microscopy still yields some gaps in microplastic identification  when compared to Raman spectral results. This methodology was broadly developed to be able to quantify ambient microplastic quantities in farmed oyster samples. The specific level of aquaculture’s contribution to plastic pollution in global waterways is difficult to estimate. The methodology was applied to a local case study that compared microplastic loading in cultured eastern oysters raised in traditional plastic farm gear and novel plastic-free farm gear. Marginal trends in the gear type treatment and microparticles identified across the harvest season were identified, however effect sizes were too weak, and evidence was too inconsistent to currently suggest that gear type and harvest date affect microplastics and other particle quantities g^-1 oyster tissue (d.w.).

Waste Streams From Next Generation Molten Salt Reactors: The Challenge Of Creating An Insoluble Ceramic For Chloride Salt Waste, Alevtina A. Maksimova, Jake W. Amoroso, Matthew Page, Gregory Morrison, Hans Conrad Zur Loye

Faculty Publications

Molten salt reactors (MSRs) design development is of interest to many research groups and companies. Waste management for MSRs is one of the most important issues that needs to be resolved due to its impact on environmental safety, primarily via the dissolution of radionuclides in water. Furthermore, the waste treatment strategy will have a significant influence on the operating cost of MSRs, which is why a reliable process for the immobilization, transportation, storage and disposal of MSR waste must be addressed. This work presents a new approach for the immobilization of chloride salts from molten salt reactors in stable oxyhalide …

The Jefferson-D’Hondt Method And Majorization, Stanley Chang

The Mathematics Enthusiast

This article investigates the interplay between apportionment functions and order-theoretic structures on population and allocation vectors. We define a class of functions, called apportionment maps, that respect population monotonicity, house monotonicity, and size monotonicity. A central focus is placed on the preservation or violation of majorization under these functions, with particular attention to the Jefferson method and related divisor schemes. By applying tools from convex analysis and the theory of Schur-convex functions, we characterize the extent to which fairness criteria are preserved under apportionment.

Standard Monomials For Positroid Varieties, Ayah Almousa, Shiliang Gao, Daoji Huang

Mathematics Faculty Publications

We give an explicit characterization of the standard monomials for positroid varieties with respect to the Hodge degeneration and give a Gröbner basis. Furthermore, we show that promotion and evacuation biject standard monomials of a positroid variety with those of its cyclic shifts and w₀-reflection, respectively. The connection to promotion allows us to identify standard monomials of a positroid variety with Lam's cyclic Demazure crystal. Using a recurrence on the Hilbert series, we give an inductive formula for the character of cyclic Demazure modules.

Enhancing Programming Productivity For Individuals With Adhd Through Generative Artificial Intelligence: An Inductive Analysis, Lionel Mew

School of Professional and Continuing Studies Faculty Publications

Attention-deficit/hyperactivity disorder (ADHD) significantly impacts computer programmers through challenges in sustained attention, executive functioning, and organizational skills. While traditional intervention strategies have shown varying degrees of success, the emergence of generative artificial intelligence (AI) presents novel opportunities to address ADHD-related programming challenges. This paper presents an inductive analysis synthesizing current research on ADHD's effects on programming, traditional productivity enhancement techniques, and the potential of generative AI tools. Through examination of recent literature and field studies, we propose that generative AI can serve as a transformative intervention by providing personalized cognitive support, reducing executive function demands, and enhancing code generation efficiency. …

Bridging Data Gaps In Retinal Imaging: From Structural Domain Adaptation To Topology-Aware Synthesis, Gözde Merve Demirci

Dissertations, Theses, and Capstone Projects

Comprehensive visualization of the retina is essential for diagnosing and monitoring blinding diseases such as Diabetic Retinopathy and Retinopathy of Prematurity (ROP), where pathological changes often extend beyond a single field of view. Despite significant advances in automated retinal image analysis, clinical deployment remains limited by two fundamental data gaps: a structural learning gap, arising from scarce expert annotations and poor generalization across imaging domains, and a spatial coverage gap, caused by the difficulty of acquiring multi-view retinal images in fragile populations. Although these challenges are often addressed independently, this dissertation argues that they are tightly coupled: accurate, …