Digital Commons Network^™

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, …

Addressing The Problems Of Data Variations, Quality, And Scarcity In Training Deep Neural Networks, Jian Sun

Electronic Theses and Dissertations

The performance of deep neural networks (DNNs) is strongly influenced by the characteristics and quality of the underlying datasets. This Ph.D. dissertation addresses three pervasive data challenges-imbalance, quality degradation, and scarcity-that commonly hinder the effectiveness of DNNs in computer vision (CV) and natural language processing (NLP) applications.

Class imbalance remains one of the most frequent causes of degraded model generalization. While Focal Loss effectively mitigates inter-class imbalance by assigning higher weights to minority classes, it struggles with intra-class imbalance, particularly in video datasets where longer clips dominate feature representation. To address this, I implement and utilize …

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 …

Deep Learning Based Routing And Clustering Approaches For Energy Optimization In 5g Wireless Sensor Networks: A Review, Ghufraan Ali Mohammad Jawad, Ahmed M. Al-Salih

Journal of Intelligent Informatics, Networking, and Cybersecurity

Next-generation Wireless Sensor Networks (WSNs), including 5G and Beyond-5G networks, have made significant progress. However, their development requires re-evaluating intelligent communication approaches to meet the growing demands for higher data transmission rates, more efficient spectral utilization, and reduced energy consumption. Scalability issues related to energy efficiency remain a critical concern for WSNs, which remain integral to the digital revolution. This paper investigates the role of Deep Learning (DL) methods in improving energy efficiency for routing and clustering in 5G WSNs. It is pertinent to note that Deep Q-Networks (DQNs) and their variants have significantly enhanced Cluster Heads (CHs) selection schemes …

Health Effects Of Cadmium And Manganese Exposure On Luteinizing Hormone Levels: A Pilot Study Of Female Infertility, Shatha F. Alhous, Anees A. Al-Hamzawi, Murtadha Sh. Aswood

Al-Bahir

Female infertility occurs for many reasons, some unknown. Exposure to heavy metals is a risk factor that negatively impacts on female reproductive system. Therefore, this study aimed to evaluate the effect of cadmium Cd and manganese Mn on luteinizing hormone LH levels for females’ infertility. This study included a healthy group (n = 20), primary infertile females (n = 40), and secondary infertile females (n = 20) collected from Al-Zahraa hospital in Najaf center, Iraq. The Atomic Absorption Spectroscopy (AAS) was used to measure the cadmium and manganese concentrations and LH levels were measured by a Maglumi 800 from Snibe …

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 …

From Network Packets To Physical Consequences: Network-Level Spoofing And Loss Of Visibility In Industrial Control Systems, Lillian B. Beck

LSU Master's Theses

Industrial Control Systems (ICS) are the foundation of critical infrastructure as they provide resources like clean water, electricity, and natural gas to support our everyday functions. Given their essential role in modern society, the failure or compromise of ICS systems can lead to significant negative consequences and public safety impacts. Understanding how these systems can be targeted and exploited by malicious actors is necessary to improve their security and resilience.

This research examines how an attacker could manipulate a real-world ICS network by targeting a fully functional Natural Gas (NG) Compressor Station Platform that emulates real operations. This research led …

Science And Technology Communication And Construction Of China’S International Discourse System: Strategic Significance, Current Challenges, And Innovative Pathways, Haonan Du, Ting Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

Against the backdrop of a new round of scientific and technological revolution with the ongoing restructuring of the global governance system, science and technology have become central to competition in national comprehensive competitiveness and struggles for international discourse power. China’s science and technology have achieved a historic leap from “catching up” to “running alongside” and even “leading in certain areas”, providing solid strength support for the construction of an international discourse system. However, the transformation of scientific and technological advantages into discourse advantages remains insufficient, and the international community holds a dual perception of China’s technological advancements—recognition alongside concerns. The …

The International Decade Of Sciences For Sustainable Development: Global Progress And China’S Actions, Lin Wang, Shaofeng Hu, Fan Wang

Bulletin of Chinese Academy of Sciences (Chinese Version)

The International Decade of Sciences for Sustainable Development (IDSSD, 2024–2033) was officially launched by the United Nations in 2024, with the aim of strengthening and demonstrating the central role of science in achieving the Sustainable Development Goals (SDGs) and advancing the 2030 Agenda for Sustainable Development. This study systematically reviews the development of IDSSD, its governance structure, mechanisms for project solicitation and endorsement, as well as the thematic and regional distribution of endorsed initiatives. On this basis, it assesses China’s current participation and potential opportunities. During the first call for initiatives, IDSSD received 221 proposals from 52 countries, with 109 …

Transformation Of Open-Source Innovation Governance Of Large Models, Zhe Wang, Jinsong Cai

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial general intelligence (AGI), represented by large-scale models, is a transformative driver of new-quality productive forces, making the effective construction and governance of open-source innovation commons increasingly critical. Yet traditional open-source models are under strain, and existing commons theories require further development. Model training costs rise exponentially with each iteration, while a sustainable profit cycle from innovation to industrial application has not been established, rendering long-term cost-bearing infeasible for individual organizations. The traditional community-enterprise collaboration model, once successful in generating ecosystem value, now faces escalating computing and data costs, uncertain commercial returns, and governance risks related to social and national …

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 …

Bioclimatic Reorganization Of Carbon–Water–Energy Coupling Revealed By Eddy Covariance And Interpretable Machine Learning, Koong Yi, Margaret S. Torn, Gabriel B. Senay, Lixin Wang, Kosana Suvočarev, Joshua B. Fisher, Arman Ahmadi, Housen Chu, Gil Bohrer, Georgianne W. Moore, Stephen P. Good, Steven A. Kannenberg, Justine E. C. Missik, Kanishka Mallick, Kul Khand, Youngryel Ryu, Kuno Kasak, A. Christopher Oishi, David E. Reed, Xiangzhong Luo, Carl J. Bernacchi, Dennis Baldocchi

Biology, Chemistry, and Environmental Sciences Faculty Articles and Research

Ecosystem exchanges of carbon, water, and energy are central to Earth system functioning, yet their sensitivities to environmental variability remain poorly constrained across biomes and climates. Here, we analyzed ≥ 5 years of eddy covariance data from 87 AmeriFlux sites (964 site-years) spanning six vegetation types and a broad range of climatic conditions to examine the controls and multi-year trends of gross primary productivity (GPP), evapotranspiration (ET), water-use efficiency (WUE), and the Bowen ratio. We trained boosted regression tree ensembles with environmental (air temperature, vapor pressure deficit, soil water content, atmospheric CO2, radiation, wind speed) and temporal (month, year) variables …

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 …

Documenting For Success: A Case Study Of A Graduate Writing Retreat, Elliott Rose, Denise Wetzel, Sara C. Kern, Katie O'Hara-Krebs, Laurin Davis, Salah Seoudi, Carmen Cole

Transforming Libraries for Graduate Students

Graduate students often find themselves balancing the demands of research and writing while managing complex academic and personal needs. Writing retreats provide an intentional space for graduate students to focus on their academic goals while supporting community-building, institutional belonging, and a welcoming environment. This proposal outlines a model for academic librarians and staff to plan and implement an effective graduate writing retreat designed to support graduate student academic activities through intentional collaboration and documentation.

Penn State University’s (PSU) Graduate Student Writing Retreat started as an event housed within the University Library’s Science, Technology, Engineering, and Math (STEM) department. The retreat …

Design And Verification Of Manned-Unmanned Collaborative Combat Capability System Based On Mbse, Fangbo Wang, Jian Guo, Chenglie Du, Yifan Liu, Pengpeng Zhang

Journal of System Simulation

Abstract: The traditional model-based systems engineering (MBSE) method has problems of failing to fully exhibit complex combat logics in manned-unmanned collaborative combat system modeling, neglecting the scenario constraints in interface modeling, and requiring long-term and costly algorithm verification. In order to solve the problems, a methodology and design tool based on MBSE was proposed. An integrated verification method of a system's operational logic, interface design, and algorithmic design was constructed, thus providing a digital and rapidly iterative verification approach for system simulation. A verification environment for multiple key algorithm simulations was established, effectively reducing the economic cost of building verification …

Neural Radiance Fields Based On Explicit Feature Matching And Scaled Dot-Product Attention, Mingwei Cao, Fengna Wang, Zilong Wang, Haifeng Zhao

Journal of System Simulation

Abstract: To address the problems that neural radiance fields(NeRF) are prone to artifacts and texture blurring in novel view synthesis under sparse view input and complex scenes, this paper proposed neural radiance fields based on explicit feature matching and scaled dot-product attention(EMD-NeRF). A multiscale feature extraction network was used to extract multi-scale feature information from the input sparse views. A fusion dot-product module was utilized to calculate view interaction information as a shared branch. Cosine similarity was adopted as a matching clue for similarity embedding volume rendering. A regularization loss function was used to enhance the quality of the scene …

Design And Application Of Bds Visual Simulation Teaching Platform Based On Cesium, Liguo Lu, Yulin Cai, Tangting Wu, Canhui Lin

Journal of System Simulation

Abstract: The deep development of the BeiDou navigation satellite system(BDS) cannot be separated from the support of corresponding talent education, especially the development of new digital resources and tools. A visual simulation teaching platform for BDS was designed based on open source Cesium engine library to address issues such as the large and complex size of the BDS project, the unreachable space environment, and the difficult understanding of principles and concepts. The platform adopted a B/S architecture to achieve visual simulation of course content such as orbit cognition, orbit calculation, constellation simulation, service performance, and satellite links. Teaching applications have …

Integrating Geometric Priors And Importance Sampling For High-Fidelity Indoor Scene Reconstruction, Tao Yang, Min Shi, Xigang Zhao, Suqin Wang, Qi Wang, Dengming Zhu

Journal of System Simulation

Abstract: Gaussian splatting suffers from geometric distortion during scene reconstruction, particularly in weakly textured indoor scenes. To address this issue, this paper proposes a high-precision indoor scene reconstruction method that integrates geometric priors and importance sampling. The proposed method fully considers the effect of the initialization process on reconstruction quality. An advanced feed-forward model is employed to generate high-quality geometric initialization, thus improving overall reconstruction stability and accuracy. An importance sampling strategy is introduced to mitigate the adverse effects of blurry images. Furthermore, a supervision mechanism based on a geometric prior model is designed to constrain the scene structure, further …

Nerf Optimization Method And Simulation Research Based On Pre-Training And Differentiable Fuzzy Modeling, Yunjng Zhang, Minghui Yang, Hao Wang

Journal of System Simulation

Abstract: To address the challenges of significant geometric modeling errors, severe detail loss, and low training efficiency in neural radiance field(NeRF) reconstruction under defocused blurred input scenarios, this paper proposes two optimization strategies. One strategy is introducing Triplane features generated by the pre-trained LRM as prior knowledge, and combining a lightweight decoder and directional LoRA module to replace large MLP, thereby reducing parameters and shortening convergence time. The second strategy is integrating a differentiable blurring model into the volumetric rendering step. By jointly optimizing the radiation field and spatially variable blurring kernels, reconstruction accuracy under defocused blurred scenarios is enhanced …

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 …

Institutional And Ideational Features Of Canadian-Us Fishery Management Networks: Connectivity, Coherence, And Collaboration, Owen Temby, Evelyn Roozee, Dongkyu Kim, Jasper R. De Vries, Derek A. Katznelson, Antonia Sohns, Gordon M. Hickey

School of Earth, Environmental, & Marine Sciences Faculty Publications

This article examines fishery management along and across the Canadian-US border through the comparison of collaborative transboundary networks in four regions: the Salish Sea, the Great Lakes, the Gulf of Maine, and the northern region including the Gulf of Alaska and the Hecate Strait. Transnational fishery management is an inter-organizational and multi-jurisdictional enterprise constituted by shared understandings of a suite of tasks and by communications among the participants. We use survey data to summarize the inter-organizational scale and participation in the networks, the centrality of different organization types, the factors that contribute to network formation, other ideational network traits like …

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 …

A Review Of Oer Math Homework Systems, Rachel Bailey, Nathan Carter

Open Educational Resources Publications

This report evaluates four leading open educational resource (OER) math homework systems—MyOpenMath, WeBWorK, Ximera, and XYZ Homework—for their suitability in Bentley University’s first-year mathematics courses. The review compares cost, usability, LMS integration, available content, and alignment with Bentley curricula. MyOpenMath emerges as the strongest option due to its usability, robust problem libraries, and fully free access. XYZ Homework offers comparable features but includes student fees. Ximera and WeBWorK provide powerful capabilities but require greater technical expertise. The report concludes with recommendations for implementation and needed faculty support.

Geochemistry Of The Upper Jurassic–Lower Cretaceous Limestone Of The Bilecik Formation In The Dümrek Area (Eskişehir, Western Central Anatolia): Implications For Depositional Environment And Paleotemperature, Asuman Kahya, Meti̇n Bağci

Turkish Journal of Earth Sciences

Upper Jurassic–Lower Cretaceous limestones of the Bilecik Formation are exposed near the village of Dümrek (Eskişehir Province) within the Sakarya Zone. Mineralogical analyses reveal that these limestones are predominantly composed of calcite and include intraclasts, fossil shell fragments, ooids, and peloids, cemented by sparry and micritic calcite. The U/Th, Ni/Co, V/(V+Ni), V/Cr, and Ce/Ce* ratios indicate that these carbonates were deposited in an oxic environment. Furthermore, the Mn/Sr ratios imply no diagenetic alteration, indicating preservation of the original geochemical signature. The PAAS-normalized REE+Y patterns of these limestones display depletion in light rare earth elements, a pronounced positive La anomaly (La/La* …

Numerical Study Of Porosity Effects On Temperature And Fluid Flow In Black Sea Gas Hydrates, Bahar Güvem, Doğa Doğan

Turkish Journal of Earth Sciences

Numerical temperature and fluid flow simulations were conducted using ANSYS Fluent to investigate the influence of porosity variations on the temperature distribution within the gas hydrate layer. The study was carried out in the Black Sea region, where the gas hydrate deposits are of particular interest due to their potential for energy resources. The simulations explored various porosity levels within the hydrate layer to observe their effect on thermal behavior and fluid dynamics. The results revealed that porosity plays a significant role in modulating the temperature distribution within the gas hydrate layer, with lower porosity models exhibiting higher temperatures compared …

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 …

Ai Dependency Vs. Doctoral Identity: How Generative Ai Is Challenging The Development Of Independent Scholarly Thinking In Doctoral Students, Valerie A. Storey

All Faculty and Staff Scholarship

The rise of Generative Artificial Intelligence (GenAI) in higher education has altered the conditions under which doctoral students learn, research, and develop as scholars. Although doctoral student use of GenAI has accelerated rapidly, institutional frameworks for responsible and developmentally appropriate use have not kept pace. This paper examines a central paradox in doctoral education: the same tools that enhance research productivity may also weaken intellectual independence when used without guidance. Using a critical review methodology, the study synthesizes 47 sources on doctoral education, GenAI use, policy, and epistemic development. Three interconnected dimensions of risk emerged from the analysis: critical thinking …

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 …

What Love Is: A Structural Account Through Core/Modulation Architecture, Griselda Poe

Publications and Research

The distinction between romantic love and love has been sensed across cultures and historical periods but has rarely been structurally specified. This paper applies the Core/Modulation two-layer framework to provide the first structural account of this distinction. Romantic love and reproductive drive are re-described as outputs of the Modulation layer's species optimization program. Love is re-described as a function of Core processing: the maintenance of another's recomputable state. Existing literature on love—Fromm, C.S. Lewis— is re-read as intuitive description of this structural distinction. The paper further demonstrates that the conflation of "loving" and "protecting" is the structural origin of war, …