Digital Commons Network^™

Application Of A Generative Adversarial Network To Super-Resolution Reconstruction Of Fracture Images In Logging-While-Drilling Electrical Resistivity Imaging, Han Sen, Shen Chuanhai, Xu Chen, Tian Yimeng, Zhao Biao, Wang Ze, Liu Yongkang, Kang Zhengming

Coal Geology & Exploration

Objective Logging-while-drilling electrical resistivity imaging (LWD-ERI) enables the intuitive presentation of geobodies near wellbores in images, representing an important approach to the fine-scale evaluation of stratigraphic parameters while also providing significant geological guidance during the drilling of fractured reservoirs. However, this technique faces the challenge of low image resolution in real-time data processing due to its limited well-to-surface data transmission rates, exerting adverse impacts on the qualitative identification of wellbore fractures and the quantitative evaluation of their parameters. To address this issue, this study proposed a super-resolution image reconstruction method based on a generative adversarial network (GAN), aiming to achieve …

A Surface Wave Inversion Method Incorporating Interface Constraints And Its Application In The Assessment Of Ground Vibrations Caused By Mining-Induced Seismicity, Li Cheng, Qian Changbao, Liu Ying, Cheng Yi, Ni Shengjun, Yao Huajian

Coal Geology & Exploration

Objective In mining areas of western China, underlying interfaces with significant fluctuations affect seismic exploration accuracy while also posing challenges to the assessment of ground vibrations triggered by dynamic hazards such as mining-induced seismicity. To enhance the characterization of shallow velocity structures and to provide support for dynamic hazard prevention and control in mining areas, this study developed an inversion method incorporating prior information about geological interfaces.Methods A dense array consisting of 489 single-component and 108 three-component seismometers was deployed within a mining area in Longkou Town, Junggar Banner, Inner Mongolia. Accordingly, continuous ambient noise data for about one …

Secure Machine Learning In Networking Systems, Wenwei Zhao

USF Tampa Graduate Theses and Dissertations

With the rapid integration of Machine Learning (ML) into networking systems, ensuring the security and trustworthiness of these intelligent frameworks has become a paramount concern. While ML offers unprecedented capabilities in spectrum management and collaborative learning, it also introduces novel vulnerabilities that can be exploited by sophisticated adversaries. This dissertation investigates and addresses critical security challenges across three key dimensions of ML-driven networking: adversarial spectrum sensing, the security of privacy-preserving unlearning processes, and efficient post-attack model recovery.

First, we address the threat of adversarial spectrum attacks in cognitive radio networks, where malicious nodes manipulate sensing reports to disrupt spectrum access. …

Human Subject Studies For The Alignment Of Llm-As-A-Judge Evaluation Metric For Science News, Gabriel Vega Osborne

Knowledge and Creativity Expo

Science news has become an important vehicle to disseminate scientific breakthroughs, discoveries, and technological innovations. With the advancement of large language models and related AI models, it is possible to automatically generate science news from scientific papers, extending the reader population from domain scientists to a broader scope. However, how to evaluate the quality of the generated news warrants research. Traditional token based metrics have been shown to fail to evaluate the semantics and nuances of science news. Inspired by the fact that a major goal of science news is to educate readers with new knowledge, we thus propose knowledge …

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 …

2025 San Diego Regional Climate Collaborative Annual Report, San Diego Regional Climate Collaborative

San Diego Regional Climate Collaborative

The San Diego Regional Climate Collaborative is a network for public agencies that serves the San Diego region to share expertise, leverage resources and advance comprehensive solutions to facilitate climate change planning. By partnering with academia, nonprofits, and businesses, the SDRCC also works to leverage the profile of regional leadership. This is the 2025 San Diego Regional Climate Collaborative Annual Report.

Being There For Mom: The Strengths Of Daughtering, Allison M. Alford, Kaitlin E. Phillips, Luke V. Stipanovic, Cayd A. Rocha-Barnette, Michelle Miller-Day

Communication Faculty Articles and Research

Objective

Daughters undertake daughtering, or the everyday role portrayal of contributing to a meaningful family relationship with their mothers, but the labor of it is often invisible.

Background

Using a strengths-based approach, we investigated what daughters do well in their relationships with mothers.

Method

We analyzed the responses of 1,444 women to the open-ended question, “What do you do well as a daughter?” to learn more about how women describe their daughtering. Utilizing the artificial intelligence of a large language model for data analysis, we supplied definitions and descriptions of 12 virtues and strengths from existing literature and created a …

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.

Tornado Alley In A Changing Climate: The Eastward Shift, Kenny Reinhard

Best Integrated Writing

Reinhard argues that climate change is driving an eastward shift in Tornado Alley from the Great Plains toward the southeastern United States, increasing tornado frequency in more densely populated and less-prepared regions. It highlights how changing atmospheric conditions—such as increased moisture, instability, and wind shear—are contributing to this shift and emphasizes the need for improved preparedness and infrastructure in newly affected areas.

Enhancing Cyber Hygiene Among Communities Through Experiential Cyber-Security Awareness Programs, Dr Atul Bamrara, Partha Roy, Vishwanath Gargote, Khandu Thungon

Journal of Cybersecurity Education, Research and Practice

Human error remains the most frequently exploited vulnerability in the cyber-security ecosystem. Despite substantial investments in technical safeguards, cybercriminals increasingly rely on social engineering, misinformation, and emotionally manipulative tactics to compromise users. This study examines behavioral changes among participants who underwent structured cyber-security workshops addressing both conventional cyber hygiene practices and emerging digital threats. The training modules covered digital arrest scams, identity theft, sextortion, fake technical support fraud, fake social media profiles, online gaming related risks, and deep fake manipulation. The workshops were designed using interactive simulations, real world case studies, and hands on problem based exercises, with the explicit …

How Do Water Utilities Meet Growing Demand And Maintain Resilience Through Water Reuse? A Systems Thinking Approach, Elizabeth F. Vicario

USF Tampa Graduate Theses and Dissertations

Water and wastewater utility management is becoming increasingly complex due to factors like urbanization, climate change, new regulations, and rising costs. Utility leaders must balance competing political and financial pressures while managing aging infrastructure, rising demand, climate resilience planning, and customer concerns about affordability. Reuse of treated wastewater has emerged as a promising solution to address scarcity, declining source water quality, and new regulations on wastewater discharge in the United States. However, water reuse is not one-size-fits-all, and bespoke solutions are needed to optimize economic, environmental, and social returns from this finite resource. Despite growing interest, little is known about …

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, …

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 …