Digital Commons Network^™

Final Butte Priority Soils Operable Unit (Bpsou) Insufficiently Reclaimed Sites Remedial Action Work Plan (Rawp): Bres No. 104 (Colorado Dump) North Slope, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Newsletter 2025.11.24, Fcrh Honors Program

What's Going On, Honors? (2025-26)

No abstract provided.

Modified Artificial Neural Networks In Stochastic Differential Equations To Estimate The Occurrence Rate Of A New Process For Software Reliability Growth Modelling, Adel Sufyan Hussain, Zedan Zubair Mashikhin, Noora Taha Abduirazzaq

Baghdad Science Journal

This paper aims to utilize modified artificial neural networks under stochastic differential equations to improve the estimation of occurrence rates on models towards the growth of software reliability through such models. There has never been a time when reliable assessment methods have been more important as software systems grow ever more sophisticated. This study covers the risks arising from software bugs, security weaknesses, and the need to meet legal requirements. The authors use a new method that combines artificial intelligence techniques with classical reliability models to achieve their goal of a more efficient computational tool for predicting software reliability. It …

Enhancing Brain Mri Classification With Gray Wolf Optimization And Swin Transformers, Lamyaa Fahem Katran, Ebtesam N. Alshemmary, Waleed A. Al-Jawher

Baghdad Science Journal

With the rapid advancement of computational power, deep learning has become integral to medical imaging. Convolutional Neural Networks (CNNs) are widely applied to brain MRI scans for tumor classification due to their strong localization and recognition capabilities. However, their limited ability to capture long-range dependencies often leads to information loss and reduced performance in complex feature extraction. To overcome this, the Swin Transformer introduces a hierarchical attention mechanism with shifted windows that preserves spatial relationships and enhances the modeling of global contexts. This architecture improves the detection of intricate tissue textures and supports high-resolution reconstruction of MRI images. Furthermore, integrating …

Transformer Network On Global Self-Attention Mechanism For Brain Tumor Segmentation, Ammar Awni Abbas Baghdadi, Mohammed Al-Mukhtar, Ammar S Al-Zubaidi

Baghdad Science Journal

Transformers are a specific category of neural network design. Transformers often depend on extensive pre-training on a large scale and exhibit a notable degree of computational complexity. The disadvantage of using this method is a significant increase in computational complexity, which necessitates a significant commitment of time and computing resources in order to successfully work with these models. Transformer networks possess the desirable benefit of extracting distant characteristics effectively via their self-attention mechanism. In this paper, the Global Self-Attention Transformer module is applied to tackle these issues. The model is based on a segmentation problem called Brain-GS that works as …

The Environmental Impacts Of Super Bowl Host City Location, Joshua Sheibley, Charles Mango

Montserrat Annual Writing Prize

No abstract provided.

Low-Energy Multiphoton Scattering At Tree-Level And One-Loop Order In A Homogeneous Electromagnetic Field, James Edwards, Ivan Ahumada Hernandez, Patrick Copinger

School of Engineering, Computing and Mathematics

We study low energy photons coupled to scalar and spinor matter in the presence of an arbitrary homogeneous electromagnetic field in a first-quantized (worldline) approach. Utilizing a Fock-Schwinger gauge for both the scattering photons and homogeneous background, simple compact expressions are found for both the photon- and background-dressed effective action and propagator in scalar and spinor quantum electrodynamics. The low-energy limit allows identification of the coupling of the scattering photons as one of an effective homogeneous superposition of their field strengths, with amplitudes following from application of a suitable linearization operator. To treat the linearization, several techniques are employed, including …

On Iterative Method For The Solution Of Non-Linear Equations Using Anti-Lobatto Four Point Quadrature Rule, Tusar Singh, Dwiti Krushna Behera

Baghdad Science Journal

By harnessing the classic anti-Lobatto four-point quadrature rule of degree of precision three, the order of convergence of the Newton-Raphson method has been profoundly enhanced. This newly developed iterative scheme reveals a remarkable order of convergence, reaching three and far surpassing the original Newton-Raphson method. It operates as a two-step iterative method that elevates Newton’s approach by integrating the quadrature rule. A theorem related to this innovative iterative method has been formulated, confirming that its order of convergence is indeed three. In the numerical computation section, insightful scenarios demonstrate the remarkable numerical efficiency of the new method. Through the power …

Innovation Curse: The Wastefulness Of Technologies Believed To Mitigate Climate Change, Minh Hoang Nguyen, Valoree Gagnon, Thanh Tu Tran, Thi Mai Anh Tran

Michigan Tech Publications

Technological innovations are increasingly promoted as solutions to climate change. However, many innovations, including Carbon Capture and Storage, bioplastics, and glacier geo-engineering, suffer significant limitations from high costs, speculative efficacy, and adverse ecological consequences. Using Granular Interaction Thinking Theory (GITT), a transdisciplinary framework grounded in information theory, quantum mechanics, and mindsponge theory, in this study, we explain how such technological innovations become systemically favored despite their flaws. We introduce the concept of the “innovation curse,” which arises when institutional and cognitive filtering systems, operating under high informational entropy, default to familiar but ineffective techno-solutions while marginalizing Indigenous and Local Knowledges …

Designing Culturally Responsive Classrooms: Breaking Boundaries Using Bilingual Children’S Literature, Maryann Huebner

Honors Projects

The purpose of this study was to educate and empower teachers to implement culturally responsive teaching practices in the elementary classroom to create inclusive learning environments. With an emphasis on high-quality instruction and meaningful materials, the research aimed to support equitable learning opportunities for all students. The study had a specific focus on how the use of bilingual, culturally relevant children’s literature can be a powerful resource for developing bilingual abilities in students, enabling them to meaningfully and confidently participate in the multicultural classroom. To explore how children’s literature can foster bilingualism and biculturalism in students, I collected daily, reflective …

Spatial–Temporal Deep Learning For Electric-Vehicle Charging Demand: An Exploratory Study Of Graph Convolutional And Lstm Networks Performance, Maher Alaraj, Carla Martins, Mohammed Radi, Mohamed Darwish, Munir Majdalawieh

All Works

Electric-vehicle (EV) charging is a localized, time-varying load that challenges distribution networks. This study offers practical insights into when spatial graph structure adds value beyond temporal context, utilizing real-world data and a transparent evaluation. We compare Long Short-Term Memory (LSTM) and Graph Convolutional Network (GCN) models for hourly EV-charging energy forecasting, based on 145,778 sessions recorded in Boulder, Colorado (2018–2023). After preprocessing and temporal alignment, temporal covariates (hour, day, month, year) and, when applicable, ZIP-code indicators were engineered. LSTMs were trained with 1 h and 24 h input windows, with or without ZIP features, and evaluated through 5-fold cross-validation. GCNs …

Career Interest And Work Values Of Online Filipino Psychology Graduates: Basis For Retention Program, Henmar C. Cardiño, Erwin B. Sario, Rommel P. Sergio

Social Sciences and Development Review

The main objective of the study is to evaluate the significant association between career interests and workplace values among Filipino online psychology graduates in 2022 and to provide retention strategies for diverse organizations. The study’s goal was to identify the gap between the participants’ career interests and their work values and offer possible retention programs to bridge the gap. The researcher employed a quantitative correlational research design and utilized two research instruments, the RIASEC Test by John L. Holland and the Work Values Inventory by Ronald E. Super, to measure career interest and work values, respectively. In August 2022, a …

Saussure’S Universal Distinctive Feature Dimensions, Thomas M. Eccardt

Publications and Research

This paper revisits Saussure’s scalar analysis of phonemes, offering a modern reinterpretation that replaces binary features with phonological dimensions grounded in measurement theory. By redefining Saussure’s [openness] and [backness] as ordered scales and Chomsky and Halle’s “combination and concatenation” as partially ordered scales, the paper introduces a notion of “[phono]logical simultaneity.” This framework renders the variously-defined phoneme and segment redundant, and shifts the focus of distinctiveness to the linguistic sign, the morpheme. It demonstrates how phonological dimensions link continuous articulations and acoustic signals (e.g., F1 and F2) with discrete linguistic signs through calibrated distinctive features. The analysis identifies Saussure’s two …

Forecasting Big Data Daily Silver Price Based On Hybridizing Support Vector Regression And Meta-Heuristic Algorithms, Ibtihal Muneeb Yahya, Zakariya Yahya Algamal

Baghdad Science Journal

Because commodities are prone to large price swings, forecasting their prices can be extremely difficult. Similar to other commodities, the price of silver is determined by a complicated interplay between a number of factors, including time-lag. Precise forecasting of the silver price is essential for the stable and effective functioning of silver markets. The time series that metal prices follow is non-stationary, nonlinear, and contains periods that fluctuate due to possible growth. Accurate forecasting of silver prices is difficult since they are consistently highly nonlinear and non-stationary. Forecasting metal prices, in general, have been predicted by support vector regression (SVR). …

Optimizing Artificial Neural Networks For Smart Grid Stability Analysis Using Tabu Search-Based Hyperparameter Tuning, Salwa Khalid Abdulateef, Armaneesa Naaman Hasoon, Moceheb Lazam Shuwandy

Baghdad Science Journal

Smart grids are supposed to make electricity networks more reliable, yet in practice their behavior can be surprisingly unstable when the load changes too quickly. During this work, we tried to understand that instability and to build a model that predicts when a grid remains stable or begins to drift. We used an Artificial Neural Network and tuned it with a Tabu Search routine that keeps adjusting the number of neurons and the activation functions until the results stop improving. It was not a single run; several training attempts were needed before the model settled. After applying the Tabu optimization, …

Modulation Of The Semi-Annual Oscillation By Stratospheric Sudden Warmings As Seen In The High-Altitude Jawara Re-Analyses, Jiarong Zhang, Yvan Orsolini, Kaoru Sato

All Physics Faculty Publications

The semi-annual oscillation (SAO) dominates seasonal variability in the equatorial stratosphere and mesosphere. However, the seasonally dependent modulation of the SAO in the stratosphere (SSAO) and mesosphere (MSAO) by sudden stratospheric warmings (SSWs) in the Arctic has not been investigated in detail. In this study, we examine the seasonal evolution of the SAO during 16 major SSW events spanning 2004 to 2024 using the Japanese Atmospheric General Circulation Model for Upper Atmosphere Research Data Assimilation System Whole Neutral Atmosphere Re-analysis (JAWARA). Basic features of the SAO are well captured by JAWARA, as evidenced by the SSAO and MSAO appearing at …

2025 - The Sixth Annual Fall Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the Fall 2025 Symposium of Student Scholars, held in November 2025. Includes abstracts from the presentations and posters.

Fish-Spec: Fast Identification System For Handheld Spectroscopy And Species Classification, Mitchell Sueker, Nicholas Mackinnon, Gregory Bearman, Amanda Tabb, Diane Kim, Rosalee S. Hellberg, Alireza Akhbardeh, Hamid Reza Marateb, Jianwei Qin, Moon Kim, Fartash Vasefi, Hossein Kashani Zadeh

Food Science Faculty Articles and Research

Accurate fish species identification is critical to prevent mislabeling and fraud in the seafood industry. We present a handheld multi-mode point spectroscopy system that combines fluorescence (365 and 395 nm excitation) and reflectance measurements in the visible to near-infrared (∼350–900 nm) and short-wave infrared (∼900–1700 nm) regions for rapid, non-destructive classification of fish fillets. Tissue spectra were acquired at 25 positions on 68 fillets from 11 species, in both frozen and thawed states. Feature-level fusion across all four modes enabled higher classification accuracy than any single mode alone. A global machine-learning model classified all species with 85 ± 2.8 %, …

Proud Larry's Owners Support Southern Culture, Rebecca Lauck Cleary

University of Mississippi News

OXFORD, Miss. – Enjoying a slice of pizza or a burger with seasoned fries while listening to a live band at Proud Larry's is a quintessential Oxford experience. A gift from Lisa and Scott Caradine, who opened the restaurant and music venue in 1993, promises to help document and preserve such iconic Southern experiences.

Leveraging Consistency: Evaluating Ai Coders For Qualitative Research, Saríah López-Fierro, Carlos Chiriboga-Calderón, José López-Fierro, Rubén Pacheco-Villamar

Instructional Technology and Learning Sciences Faculty Publications

This study provides insights of using Large Language Models (LLMs) for deductive coding tasks in market research. Deductive coding, which applies predefined codes to text, often demands consistency rather than interpretive nuance. 

We compare five closed-weight LLMs with a group of human coders in tagging instances of “Expansive Framing” across qualitative excerpts, using Fleiss’ Kappa, ANOVA, and Estimated Marginal Means. Results reveal that LLMs exhibit higher consistency and faster processing than humans. These findings suggest that integrating LLMs can improve efficiency, making them an attractive asset for firms managing large datasets.

Gboost-Ctl: A Novel Method In Multi-Tissue Transcriptome-Wide Associations Studies In Cross-Tissue Learner Incorporating Gwas Information, Md Mutasim Billah, Hairong Wei, Fengzhu Sun, Kui Zhang

Michigan Tech Publications

Genome-wide association studies (GWAS) have uncovered numerous genetic variants linked to complex human diseases, yet linking these variants to transcripts and tissues that drive pathology remains difficult. Multi-tissue transcriptome-wide association studies (TWAS) offer a powerful bridge, but existing analytical methods have some limitations, either by discarding important signals by separately analyzing and then aggregating results across tissues, implying imputation models in individual tissues, or fusing them with weights that ignore how much GWAS signal each tissue actually carries. Therefore, most of the existing methods do not work uniformly across different GWAS cohorts. Here, we propose GBoost-CTL - a GWAS-boosted cross-tissue …

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 …

Harnessing Hyperspectral Imaging And Deep Learning For Terrestrial Habitat Mapping In Arid Landscapes: A Case Study In Saudi Arabia, Ali Elgendy, Hesham Morgan, Brandon Tran, Rejoice Thomas, Tamer Ismail, Yehya Kh. Shehadeh, Ahmed Elgharib, Ahmed Abdullah Al-Dughairi, Ali El Muburak, Khaled Allam Harhash, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

Arid ecosystems remain under-mapped at actionable scales despite their ecological importance. Decision makers lack reliable, high-resolution habitat maps in drylands to prioritize protection and target restoration. This research integrates spaceborne hyperspectral imaging from the Environmental Mapping and Analysis Program (EnMAP) with deep learning semantic segmentation models to produce an updated level of habitat classification based on the International Union for Conservation of Nature (IUCN) for part of the Imam Turki bin Abdullah Royal Reserve, Saudi Arabia. Using ground control points and the full EnMAP spectral cube without band selection, U-Net and DeepLabV3+ architectures were each implemented with VGG19 and ResNet-101 …

New Local Function In Grill Topological Spaces, Alyasaa Jassim Bidaiwi, R. B. Esmaeel

Baghdad Science Journal

This Paper introduces a new local function φ_Sζ*in a Grill topological space (X˙, ζ,τ) by using a semi open set, which is a superset of the local function φ_ζ. Additionally, two equivalent operators, Ψs and Γ_Sthat define topology τ_Sζ, were devised based on φ_Sζ*, along with the presentation of various characteristics and properties of φ_Sζ* and the two equivalent operators, Ψ_s and Γ_S. Additionally, newly created sets with weakly open properties (φ_{Sζ …}

Impact Of Fear Cost And Time Lag On The Dynamics Of An Ecological System Of Two Competing Predators And One Prey, Arkan Nawzad Mustafa

Baghdad Science Journal

The aim of this paper is to discover the impact of the fear of predators in prey and time lag corresponding to the gestation period on the dynamics of a food web model including two competing predator species and one prey species. Existence, non-negativity and boundedness of the model solutions are examined. An attractive region for the model is found. The permanence of the model, under certain conditions is proved. The criteria for the existence of all biologically feasible equilibrium points of the proposed model are determined. Locally asymptotically stability as well as globally stability of the model equilibrium points …

The Dynamic Of A Three Species Food Chain Model Under The Influence Of Fear And Wind, Kaherah Ibrahim Hadib, Hiba Abdullah Ibrahim

Baghdad Science Journal

This work suggests a system of ordinary differential equations (ODEs) containing a three-species food chain model incorporating wind and fear effects. The properties of the solution, like positivity and bound-ness, were investigated. All equilibrium points (biologically feasible) have been obtained, and the local stability of these equilibriums has been carried out. The global stability outcomes on the equilibrium points under specific restrictions have been established. Also, the persistence restrictions have been investigated. By utilizing Sotomayor’s theorem, the local bifurcation of the suggested model has been inspected. Furthermore, numerical analysis was carried out to ensure the theoretical results obtained by utilizing …

Computer Problems? Must Have Been The Sun How Solar Particles And Cosmic Rays Affect The Future Of Computing, Ned Markham

Osmosis Magazine

Imagine playing your favorite video game, when suddenly, your character teleports to the top of the level. One may be quick to blame the software for faulty code, clueless that this error may have originated from an unlikely source: the sun. That’s right, during a speed run of Nintendo’s Super Mario 64, one stray cosmic ray flipped a single bit (a bit is the most basic unit of information inside a computer, storing one of only two possible values of 0 and 1), causing a streamer’s character to glitch in front of him and a live audience. This phenomenon, however, …

A Journey Into The Mysterious Quantum Realm, Kien Bui

Osmosis Magazine

Toward the end of the 18th century, many scientists believed that all the fundamental laws of physics had already been discovered. Falling apples obeyed Newton’s laws of motion, spinning compasses were explained by Maxwell’s unification of electricity and magnetism, and steam engines drove the first industrial revolution through the rise of thermodynamics. Lord Kelvin stated, “[t]here is nothing new to be discovered in physics now, all that remains is more and more precise measurement.” Only “two small clouds,” he warned, were the two remaining mysteries: black-body radiation and the theory of light. These small clouds, however, turned out to be …

Stem Cells: Potent Potential For Disease Treatment, Natalie Small

Osmosis Magazine

Different cells in the body serve a variety of functions. Cardiac muscle cells contract to pump blood through the heart. Nerve cells transmit electrical and chemical signals throughout the body. Lymphocytes play a role in the immune system to fight infections (Mostafa, 2022). But how do these different cell types arise? The answer is a special type of cell: stem cells.

The Math That Keeps Your Money Safe: Why A Few Extra Characters Could Save You, Joanna Petridi

Osmosis Magazine

Imagine a cracker (yes—that is what malicious hackers are named) sitting behind a screen. Their computer is trying millions of password combinations every minute. Your bank account password, just eight characters long, is the only thing standing between them and your savings. The difference between a password that takes a week to crack and one that would take longer than the universe has existed isn’t magic or luck. It’s simply math.