Digital Commons Network^™

Butte Priority Soils Operable Unit Diggings East Final 95% Remedial Design Package Submittal, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Multi-Modal Tensor Fusion For Alzheimer’S Disease Recognition, Mason Li, Tiffany Le, Jiajing Huang, Yuxin Wen

Engineering Faculty Articles and Research

Accurate and early diagnosis of Alzheimer’s disease (AD) is critical for effective intervention, disease monitoring, and patient care. Traditional diagnostic approaches rely on a single modality, such as clinical assessments, neuroimaging, or genetic markers, which may fail to capture the complex, multifaceted nature of AD. Multimodal learning has therefore been explored to integrate complementary information across data sources. However, conventional fusion strategies, including early feature concatenation and late decision-level fusion, often model modalities independently and fail to capture high-order cross-modal interactions. To address these limitations, we propose a multimodal tensor fusion network (MTFN) that integrates heterogeneous data sources, including visual …

Beyond The Survey: Performance Assessments For Higher-Order Sustainability Literacy In Higher Education, Gregory Vincent Massara, Courtney B. Ryan, Mary Ellen Mallia

Educational Policy & Leadership Other Graduate Student Scholarship

Purpose This study explores how a performance-based assessment measures students’ higher-order sustainability competencies in ways that multiple-choice or scaled-survey tools, common ways to assess sustainability literacy, may not.

Design/Methodology/Approach This exploratory case study created a performance task for a first-year honors writing and critical inquiry course. Students (n=9) analyzed a scenario across environmental, social, and economic domains. A rubric measured students’ abilities to address all three domains and articulate a feasible and balanced solution supported by credible evidence.

Findings Students demonstrated proficiency in defining the three sustainability domains but tended to struggle to balance them. Choosing scenarios in familiar local …

Marine Vehicle Dynamics Using Koopman Operator Theory With Hybrid Observables, Mikhalib A L Green

LSU Master's Theses

Accurate modeling of marine vehicle dynamics remains challenging due to strong nonlinear hydrodynamic effects, environmental disturbances, and sensitivity to configuration changes, particularly for small-scale platforms. Classical physics-based models require extensive parameter identification and often exhibit degraded performance outside narrow operating regimes, while purely data-driven approaches may lack structure or impose high computational cost. This thesis presents a data-driven Koopman operator framework with hybrid observables for modeling the dynamics of unmanned marine vehicles. The proposed approach combines structured monomial observables with a learned neural network embedding to construct a lifted state representation in which the nonlinear vehicle dynamics are approximated by …

Large-Scale File Fragment Classification Via Multi-View Learning, Samuel Hildebrand

LSU Master's Theses

File reassembly is one of the most fundamental tasks in digital forensics, enabling recovery of data from potentially damaged storage media even when file system metadata is unavailable. This thesis reviews more than two decades of work in the realm of file carving, with a particular focus on fragmented file carving, which remains a focus of research, and file fragment classification, a principal component of fragmented file carving. This thesis serves a literature review of both file carving and fragmented file carving, surveys the massive amounts of data needed for the task of fragment classification and the datasets that serve …

Revised Draft Final Butte Priority Soils Operable Unit (Bpsou) Insufficiently Reclaimed Sites Josephine Shaft (Bres No. 37) Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Butte Priority Soils Operable Unit Final Butte Hill Revegetation Specifications, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Cdj-Pontryagin Optimal Control For General Continuously Monitored Quantum Systems, Tathagata Karmakar, Andrew N. Jordan

Mathematics, Physics, and Computer Science Faculty Articles and Research

The Chantasri-Dressel-Jordan (CDJ) stochastic path integral formalism (Chantasri et al. 2013 and 2015) characterizes the statistics of the readouts and the most likely conditional evolution of continuously monitored quantum systems involving a few qubits or quantum harmonic oscillators in Gaussian states. In our work, we generalize the CDJ formalism to arbitrary continuously monitored systems by introducing a costate operator. We then prescribe a generalized Pontryagin's maximum principle for quantum systems undergoing arbitrary evolution and find conditions on optimal control protocols. We show that the CDJ formalism's most likely path can be cast as a quantum Pontryagin's maximum principle, where the …

Best Integrated Writing Spring 2026 - Complete Edition, Wright State University School Of Humanities And Cultural Studies, Tracy Smith, Kristie Mckiernan

Best Integrated Writing

Best Integrated Writing includes excellent student writing from Integrated Writing courses taught at Wright State University.

Circulating Levels Of Insulin-Like Growth Factor I (Igf-I) And Risk Of Multiple Myeloma: An Observational And Mendelian Randomisation Study, Yolanda Benavente, Sara Hermosa, Nikos Papadimitriou, Alyssa I. Clay-Gilmour Ph.D., Elizabeth E. Brown, Jonathan N. Hofmann, Nathaniel Rothman, Qin Lan, Sonja I. Berndt, Demetrius Albanes, Mark Purdue, Mitchell J. Machiela, Stephen J. Chanock, Parveen Bhatti, Wendy Cozen, Aaron Norman, Susan L. Slager, James R. Cerhan, Vincent Rajkumar, Et. Al.

Faculty Publications

No abstract provided.

Quantifying Global Internal Displacement Risk At The Hazard-Vulnerability-Conflict Nexus, Wenzhao Li, Surendra Maharjan, Rejoice Thomas, Hesham Morgan, Ali Elgendy, Susan Mikhail, Hesham El-Askary

Mathematics, Physics, and Computer Science Faculty Articles and Research

This study introduces a novel, diagnostic hazard-specific displacement risk index that integrates high-resolution hazard data with social vulnerability metrics and historical displacement records, uncovering overlooked compound risks in conflict areas and links between environmental stress and instability. Our methodology combines historical displacement records with environmental, demographic, and socioeconomic indicators to identify high-risk regions and quantify interactions between hazards and conflict across six major hazard types. Results reveal floods as the primary displacement driver, particularly in South Asia (Bangladesh, India, Pakistan) and Sub-Saharan Africa (Nigeria, Ethiopia), where dense populations in flood-prone areas intersect with low socioeconomic resilience. Droughts disproportionately impact arid …

Advancing Environmental Justice Through Chemical Education: Perspective From New Orleans’ Water And Air Quality Challenges, Ja’Lynn Keller, Sita Aggarwal, Rami A. Al-Horani, Morewell Gasseller, Navneet Goyal

Faculty and Staff Publications

New Orleans, Louisiana, faces profound environmental vulnerabilities arising from the convergence of industrial pollution, urban runoff, and climate change–driven weather events. This paper examines systemic challenges affecting water and air quality in the region, with particular focus on low-income and marginalized communities disproportionately burdened by environmental degradation. Drawing on educational and community-based monitoring initiatives at Xavier University of Louisiana and Southeastern Louisiana University, we highlight the integration of student learning with real-time data collection of contaminants such as fecal coliforms, heavy metals, hydrocarbons, and polycyclic aromatic hydrocarbons (PAHs). The aftermath of Hurricane Katrina revealed significant fecal contamination in sediment layers, …

Secureai: Toward Experiential Security And Privacy Training For Ai Practitioners, Mujtaba Nazari, Eric Chan-Tin, Loretta Stalans, Mohammed Abuhamad

Computer Science: Faculty Publications and Other Works

The rapid adoption of artificial intelligence across industries has outpaced security and privacy training for AI practitioners. This paper presents methods, modules, and findings from an experiential training program designed to address security and privacy challenges in AI systems development and deployment. We conducted two program iterations: a comprehensive 12-workshop series (May-October 2024) and a condensed 6-workshop format (January-February 2025). The program combined expert-led panel sessions with hands-on laboratory activities, engaging 78 participants from diverse professional backgrounds. Evaluation through pre- and post-evaluation surveys and qualitative observations revealed improvements in cybersecurity knowledge and AI security awareness. Participants demonstrated enhanced ability to …

Clinical Prediction Of Posttreatment Migraine Recurrence Using Biofeedback Data: A Machine Learning Framework For Enhanced Patient Stratification And Treatment Monitoring, Shibbir Ahmed Arif, Ferdib-Al-Islam, Mehidy Hasan Sium

School of Computing Faculty Scholarship and Creative Works

Migraine is a complex neurological disorder with significant implications for individual well-being and public health. Predicting migraine occurrences after treatment is crucial for evaluating therapeutic efficacy and enabling personalized care, yet remains largely underexplored. This study proposes a robust machine learning framework to predict posttreatment migraine headache occurrences using real-world headache log data collected from 133 patients undergoing biofeedback therapy. The methodology includes rigorous data preprocessing, outlier removal via the interquartile range (IQR) method, and class imbalance correction through the synthetic minority oversampling technique (SMOTE). A total of 10 classical and a hybrid ensemble machine learning models were developed and …

Recovery And Validation Of Fragmented Rar Files Through The Scalpel3 Application, Thomas L. Landaiche Iii

LSU Master's Theses

A core component of filesystems includes an address table or other means of tracking metadata on where a given file resides within a disk image. This is crucial for regular operation of a computer, or disk analysis in digital forensics. When filesystem information is missing or corrupted, locating saved files on a disk becomes challenging. Whether the disk was accidentally wiped or intentionally tampered with, data still present on the disk, even while untracked, can possibly be recovered beyond what the filesystem registers. File carving in digital forensics is important for these scenarios when data recovery is necessary but address …

Survival Politics On A Working Waterfront: Rules Change Faster Than Prices In The South Texas Shrimp Fishery, Owen Temby, Anthony R. Lima

School of Earth, Environmental, & Marine Sciences Faculty Publications

In 2024–2025, the U.S. and Texas governments raced to save Gulf shrimp. Texas passed a truth-in labeling law for food service in restaurants. Federal agencies added antidumping and countervailing duty orders and new tariffs. This case follows Brownsville and Port Isabel, where dock prices slid while boats and crews aged. We frame the response as survival politics: urgent and improvised moves to keep a livelihood going even when imports set the price. Using legislative hearings, agency notices, local reporting, and port records, we show that rules reset faster than prices. Inventories, contracts, and supplier substitution delay any lift at the …

Microstructural Evolution And Precipitate Control In Boron-Doped Ni-Mn-Ti Shape Memory Alloys Via Thermal Processing, Na Liu, Marcia Ahn, Subrata Ghosh, Dipika Mandal, Bed Poudel, Wenjie Li

Biochemistry, Chemistry & Physics: Faculty Publications

Elastocaloric cooling, which leverages stress-induced phase transformation in shape memory materials, represents a sustainable and energy-efficient alternative to conventional vapor-compression cooling systems. Central to optimizing these materials is understanding how thermal processing history dictates phase formation, microstructure, and thermal properties. In this study, we investigated the (Ni50Mn31.5Ti18)99.8B0.2 compound synthesized via vacuum induction melting and arc melting, followed by water quenching. Induction melting results in needle-like, boron-rich precipitates within the martensite lattice. In contrast, vacuum arc melting promoted precipitate growth at the grain boundaries. The vacuum arc melting sample exhibits ~82% martensite phase fraction, a near-ambient transformation temperature of ~277 K, …

A Taxonomy Of Generative Models With A Focus On Diffusion Models And Denoising Techniques, Aditi Singh, Nikhil Kumar Chatta, Yuvaraj Vagula, Abul Ehtesham, Saket Kumar, Tala Talaei Khoei

Computer Science Faculty Publications

Diffusion models have emerged as a powerful class of generative models, demonstrating impressive results across visual domains such as image and video synthesis. This survey provides a comprehensive taxonomy of generative models, with a particular focus on diffusion models and their applications in enhancing visual fidelity for text-to-image and text-to-video generation. We discuss the theoretical foundations of diffusion models, including their formulation through stochastic differential equations, and analyze the forward noising and reverse denoising processes that enable stable training and high-quality generation. The survey further categorizes diffusion architectures, including pixel-space and latent-space models, and examines their design choices, training strategies, …

Perturbations To Horizontal Gnss Position Time Series By Atmospheric Lee Waves In The San Bernardino Valley, California, Walter Szeliga, Logan Grey

All Faculty Scholarship for the College of the Sciences

Anomalous systematic position offsets have been noted in GNSS time series from a variety of locations around the globe. In many regions, these time series anomalies coincide with the presence of cloud streets in visible satellite imagery, implicating atmospheric lee waves as the source of the position offsets. We report here on seasonal anomalous position offsets from the San Bernardino Basin of southern California that occur during clear skies. Modeling of the troposphere on days with anomalous positions shows the presence of atmospheric lee waves. Ray tracing through these tropospheric models suggests that atmospheric lee waves create low elevation perturbations …

Graph Neural Networks Predict Anti-Epileptic Treatment Response In Non-Lesional Infantile Epileptic Spasm Syndrome, Karen K. Wurzel

Master's Theses (2009 -)

Background: With an incidence rate of approximately three out of 10,000 live births, Infantile Epileptic Spasm Syndrome (IESS) is a rare form of epilepsy with about 2,000 to 2,500 new cases in the United States annually. Each year, thousands of infants and families face uncertainty, often requiring multiple medication regimens before finding an effective treatment. This thesis uses pretreatment structural brain connectivity data to train Graph Neural Networks (GNN) to predict antiepileptic drug response in infants with IESS, aiming to reduce the trial-and-error approach and improve care for those with IESS. Method: The dataset used in this thesis contains de-identified …

Deadmap: Open Yet Locked—Key-Controlled Dataset Protection With Feature-Level Collisions, Ting Yang, Mahabubur Rahman Miraj, Xinyu Lei, Nankun Mu, Hongyu Huang

Michigan Tech Publications

The performance of deep learning models relies heavily on high-quality datasets. However, under the prevailing paradigm of pretrained-model–based applications, once a dataset is publicly released, data owners largely lose control over how it is used for model training. Existing data protection approaches either focus on post hoc accountability or irreversibly destroy the training utility of the data through perturbations, making it difficult to simultaneously satisfy the dual requirements of offline public sharing, authorized and controllable usage. In this paper, we propose DeadMap, a reversible training usability control framework designed for model fine-tuning scenarios. DeadMap introduces a secret label permutation combined …

What Would It Take To Compose The Ideal Library Dashboard As A 'Symphony' Of Library Data?, Evan Rusch, Heidi J. Southworth, Nat Gustafson-Sundell

Library Services Publications

Most areas of the library produce data informative about the scope and success of library services. Many areas use that data, but there might be a variety of approaches. In our library, we have developed online, interactive dashboards to understand the value of collections on our campus. Other library service areas might produce one-shot reports encapsulating their data, or they rely on analytics silos specific to their services. Our hope is to work toward a dashboard of all or most library services, possibly to include other learning services under the library roof. Instead of a ‘battle of the bands,’ we …

Geology Lab Activities An Open Educational Resource For Community College Students And Instructors, Rondi Davies, Ari Nakamura

Open Educational Resources

I'm delighted to present the updated version of Geology Lab Activities, initially developed during the COVID-19 pandemic for online learning. As we have returned to the classroom, this revised edition remains a versatile educational tool for community college students, adaptable for both online and in-person classes.

This manual combines my preferred open-access materials with my own contributions, forming a cohesive resource for non-major geology students. Thanks to a CUNY OER grant, I partnered with graphic designer Ari Nakamura, whose innovative and elegant design has truly elevated the book.

Our labs are crafted to be engaging and relevant for non-major …

Determination Of Trace Amounts Of Pb2+ And Cu2+ Ions In The Ohio River With Anodic Stripping Voltammetry And Flame Atomic Absorption Spectroscopy To Test Water Contamination From Factories., Eliana Purcell

The Cardinal Edge

In this project, water near factories in Rubbertown, Louisville, KY were tested to see if a significant enough amount of waste is deposited in the Ohio River that the concentrations of Pb2+ and Cu2+ exceed the maximum contaminant levels the World Health Organization (WHO) and the United States Environmental Protection Agency (EPA) have set in place. Waste from industrial factories may contain contaminants that have negative effects on aquatic ecosystems and even human health, so two potentially harmful metal ions were tested. The concentration of Cu2+ in water samples was detected through flame atomic absorption spectroscopy (FAAS), and the concentration …

Neotectonics Of The Malatya Basin, Se Türkiye; Implications Of The Reactivations Of The Faults Of The Basin During 6 February 2023 Earthquakes Of The East Anatolian Fault System, Yaşar Ergun Gökten, Doğan Kalafat

Turkish Journal of Earth Sciences

The Malatya Basin (MB) is a fault-controlled superimposed sedimentary basin situated in the SE of Anatolia, near and to the north of the East Anatolian Fault System (EAFS). The rock units ranging from the Permo–Carboniferous to the Upper Miocene form the basin’s basement. The thickening of the Upper Cretaceous–Upper Miocene sequence toward the Malatya Fault (MF), the basin’s northwestern boundary, indicates a dip-slip-dominated character for the MF and its control on the first-step sedimentation of the basin. The MF changes its character from dip-slip normal to the strike-slip in the Late Pliocene, and today presents a 1700-m left lateral offset, …

Effects Of Seismic Filters On Pretrained Cnn Models For Fault Detection: Application To The Delft 3d Seismic Volume, The Netherlands, Süleyman Alemdar, Ertan Pekşen

Turkish Journal of Earth Sciences

Accurate mapping of faults from 3D seismic volumes is critical for identifying structural traps, assessing reservoir compartmentalization, and guiding drilling decisions. This study evaluates how common seismic conditioning filters affect both the visual quality of a production Delft 3D poststack time-migrated volume and the outputs of two pretrained 3D CNN fault detectors: UNet3D and FaultNet. Seven filters were applied independently—AJAX, DeSmile, SimpleDenoise, Dip-Steered Median Filter (DSMF), Edge-Preserving Smoother (EPS), Fault Enhancement, and Ridge Enhancement—and results were inspected across inline, crossline, time-slice, and full-cube perspectives. The analysis is image-driven, supported by high-resolution comparison figures and view-specific interpretations.Filters that suppress incoherent noise …

Integrated Dinsar And Hvsr Microtremor Analysis For Understanding Ground Deformation And Site Effects: Case Study Of The Bawean Earthquake (M6.5), Joshua Purba, Muhammad Fikri Hayqal Hiola, Ramadhan Priadi, Riska Yulinda, Iham Ilham, Rosa Amelia

Turkish Journal of Earth Sciences

This study investigates the seismic hazards of Bawean Island following a recent M6.5 earthquake using an integrated approach combining differential interferometric synthetic aperture radar (DInSAR) and horizontal-to-vertical spectral ratio (HVSR) methodologies. The DInSAR analysis revealed ground deformation characterized by subsidence up to 10 cm and uplift up to 8 cm, correlating with the region’s strike-slip fault dynamics. HVSR analysis provided insights into site amplification effects, identifying zones with low Vs30 values (153.77–454.72 m/s), high amplification factors (A0), and elevated seismic vulnerability index values (Kg). The dominant frequency (f0) on Bawean Island ranges from 0.64 to 17.76 Hz, with most areas …

Kms-Net: Kolmogorov–Arnold-Based Multi-Scale Attention Network For Cardiac Segmentation, Abid Mehmood, Hassan Ali, David Noule Tolno, Sery Gahouidi Thierry S, Muhammad Saeed, Naeem Ahmed

Research & Publications

Accurate segmentation of cardiac structures in 2D echocardiography is essential for diagnosing cardiovascular disease and computing clinical metrics such as chamber volumes and ejection fraction. Conventional U-Net architectures excel at extracting local spatial features but struggle with long-range dependencies inherent in noisy ultrasound images, while pure Transformer-based models capture global context at the expense of fine boundary detail. To address these limitations, we propose KMS-Net, a novel hybrid segmentation architecture that integrates Kolmogorov–Arnold Networks (KANs), a class of learnable, spline-based function approximators that replace fixed activation functions with trainable nonlinear mappings, alongside multi-scale attention mechanisms. Specifically, spline-based KAN layers (grid …

Understanding And Defending Large-Scale Networked Systems: From Wi-Fi Localization To Provenance- Based Intrusion Detection, Xiao Han

USF Tampa Graduate Theses and Dissertations

Modern networked systems increasingly depend on wireless sensing and large-scale telemetry to provide critical services and maintain security. However, many of these systems function as black boxes or encounter significant scalability limitations, which leave them vulnerable to sophisticated adversaries. In this dissertation, I present my research on enhancing the security and efficiency of networked systems through measurement-driven vulnerability analysis and the design of scalable defense mechanisms.

First, I present my research on the security and privacy risks of Wi-Fi–based localization services. Although location spoofing attacks against Wi-Fi positioning systems have been studied for over a decade, constructing practical attacks in …

Charisma As A Branch Outcome: A Structural Account Of Constraint-Driven Correction, Griselda Poe

Publications and Research

Communication across cognitive layers requires translation. Agents operating under strong layer foregrounding interpret other-layer signals by converting them into their own layer's representational format. In Empathic-modulation-foregrounded (EF) processing, translation terminates once a socially interpretable result is achieved. In Core-foregrounded (CF) processing, translation preserves structural constraints, and processing continues when those constraints are not satisfied. Extreme CF cognition produces two distinct types of mismatch: incoming signals from the Modulation layer fail to satisfy Core constraints, and Core-generated outputs are structurally distorted when interpreted through EF processing. Both mismatches trigger correction attempts. Because the surrounding social environment operates through Modulation-layer communication, correction …