Digital Commons Network^™

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 …

Analogy2kg: An Automatic Pipeline For Deriving Knowledge Graphs From Long-Text Analogies, Kara Combs, Lance E. Champagne, Bruce A. Cox, Christine M. Schubert Kabban, Trevor Bihl, Grace Lemming

Faculty Publications

Analogical reasoning is an increasingly popular, lightweight solution to enable large language model (LLM)-level reasoning without computational complexity. Still, it has yet to be adopted due to its reliance on strictly hand-formatted data. Therefore, we propose Analogy2KG (“Analogy to Knowledge Graph”), as an automatic pipeline that transforms text into a KG format via a fine-tuned version of information extraction (IE) algorithms for long-text analogies. The need to verify that the complex underlying analogical structure of the data is maintained was done via paired samples tests in the creation and validation of this pipeline. Graph density was used to evaluate the …

Happy Belated Iep: How A Notice Of Procedural Safeguards Fails Children With Specific Learning Disabilities, Chrystal Clodomir

Kentucky Law Journal

No abstract provided.

Optimizing Clutch Performance In Euroleague Basketball: A Data-Driven Analysis Of Late-Game Decision-Making, Panagiotis F. Foteinakis, Stefania P. Pavlidou, Athanasios Chatzinikolaou, Nikolaos Stavropoulos, Maria Michalopoulou

Baltic Journal of Health and Physical Activity

Background: Decision-making during late-game possessions in basketball is considered one of the most essential aspects of winning a game. This study examined key determinants of late-game shot-making success in closely contested EuroLeague basketball matches, aiming to optimize offensive decision-making in clutch situations. Material and Methods: An observational analysis from the last two minutes of 83 EuroLeague games recorded 471 clutch shot attempts. Logistic regression and chi-square analyses assessed the impact of offense time, shot range, defensive pressure, game status, and offensive tactical strategies on shot success. Results: The results showed that paint clutch shots (63.9% success) were significantly more effective …

Educating For Responsible Ai Governance - Building Interdisciplinary Frameworks For The Management Of Artificial Intelligence, Grace Eboh

Southwestern Business Administration Journal

As Artificial Intelligence (AI) becomes increasingly prevalent across industries, there is a critical need for educational programs that teach effective AI governance and management. This article examines how educational institutions can develop comprehensive curricula to prepare professionals for the complex challenges of overseeing AI systems responsibly. It analyzes current gaps in AI governance education, proposes frameworks for curriculum design, and identifies key competencies required for effective AI stewardship. The findings suggest that successful AI governance education must adopt an interdisciplinary approach that integrates technical literacy, policy understanding, ethical reasoning, and organizational management.

Utilizing The Financial Calculator For Graduated Annuities: Compound Rate, Discount Rate, Present Value, And Future Value, Su-Jane Chen

Southwestern Business Administration Journal

This paper lays out a comprehensive, systemic, and conceptual framework for applying a financial calculator to handle graduated (growing) annuities, a practically important topic that has not received its due attention in finance textbooks. It introduces an alternative to the conventional approach in transforming the growth rate and the interest rate into a single rate as I in the calculator. It then shows that both approaches give the same answer and demonstrates how they can be used interchangeably with the illustration of several numerical examples. In short, this article provides a thorough rationale and gives a clear presentation for the …

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 …

Modeling And Optimization Of Ppsu/Cu-Bdc Mmms And Ppsu/Cooh-Mwcnt@Cu-Bdc Mmms For Enhanced Water Treatment Performance, Ghaidaa M. Jaid, Adnan A. Abdulrazak, Sunarti Abdul Rahman, Muayad Al-Shaeli, Vahid Vatanpour, Qusay F. Alsalhy

Engineering and Technology Journal

Water quality is increasingly of concern today due to industrial wastewater that contains heavy metals, particularly lead (Pb²⁺). What follows is a study aiming at adjusting operational variables affecting the performance of two types of mixed-matrix membranes (MMMs) used for lead ion removal from simulated wastewater. The first employs polymer polyphenylsulfone (PPSU) by embedding copper-organic frameworks (Cu-BDC), and the second MMMs incorporate a novel COOH-MWCNT@Cu-BDC nanocomposite in the same polymer. MOF nanoparticles were added to the matrix to improve membrane performance, hydrophilicity, contact angle, porosity, and fouling resistance. Three operating parameters were modeled and optimized for their influence …

A Multi-Task Cnn-Lstm Model With Attention Mechanism For Climate Temperature Forecasting Over Iraq, Salim M. Mohammed, Omar M. Mustafa, Lailan M. Haji, Omar M. Ahmed

Al-Bahir

Accurate forecasting of climate temperature at the regional scale is crucial to agriculture planning, water resource management, and disaster preparedness. Still, due to the nonlinear and complicated temporal patterns in regions such as Iraq, conventional climate models fail to meet this imperative. This paper presents a novel deep learning model that not only predicts monthly average temperature values but also predicts the temperature trend, hence addressing the regional climate prediction problem holistically. The proposed model is designed as a multi-task deep learning framework integrating Convolutional Neural Networks, Long Short-Term Memory networks, and an attention mechanism to process historical monthly temperature …

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 …

Enhanced Cuckoo Search-Based Optimization For Single Distributed Generation Placement And Sizing In Radial Distribution Systems, Samson Oladayo Ayanlade, Abdulrasaq Jimoh, Richard Oladayo Olarewaju, Ignatius Kema Okakwu, Israel O. Adejumobi, Joseph B. Samson, Oluwadare A. Adebisi, Oluwadare O. Akinrogunde

Al-Bahir

This paper presents an Enhanced Cuckoo Search Algorithm (ECSA) to optimally place and size Distributed Generation (DG) in radial distribution systems to minimize real power loss within operating constraints. The proposed ECSA has exponentially decaying adaptive Lévy flights, constraint-aware solution repair with dynamic penalty coefficients, and diversity-directed stochastic replacement to enhance search robustness and convergence speed. It was tested with 30 independent runs on the IEEE 33-bus, IEEE 69-bus, and a practical Nigerian 32-bus distribution network. The simulations show that the ECSA lowers the active power loss of the IEEE 33-bus system from 201.58 kW to 102.75 kW (49.03%), and …

Effects Of Technology-Integrated Science Of Reading And Kindergarten Readiness On Reading Fluency, Jeffrey Maxey

Walden Dissertations and Doctoral Studies

The Science of Reading (SoR) model has influenced curriculum reform through state mandates and classroom practices emphasizing explicit, systematic phonics instruction in response to national trends indicating significant deficits in students’ reading abilities. The problem addressed through this study was the gap in knowledge on the effect of technology-integrated SoR on early elementary students’ reading skills at a large southeastern U.S. public school district. Grounded in Gough and Tunmer’s simple view of reading theory, the purpose of this quantitative study was to explore the main and interaction effects of students’ Kindergarten Readiness Assessment (KRA) levels and 2 years of technology-integrated …

2026-03-20 Minutes & Appendices, Longwood University

Board of Visitors Meeting Minutes 1964-

No abstract provided.

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 …

Chatgpt Versus Uptodate In Preclinical Medical Education: Cross-Sectional Analysis Using Term Frequency-Inverse Document Frequency Cosine Similarity, Shankar S. Thiru, Nicholas E. Aksu, Matthew Chiang, Daniel O. Gallagher, Mary Furlong, Elizabeth R. Prevou, Akhil Jay Khanna

Rothman Institute Papers

BACKGROUND: Generative artificial intelligence tools such as ChatGPT are increasingly used by medical students for self-directed learning. Although these models demonstrate linguistic fluency, their reliability as supplementary resources for preclinical education remains uncertain. In particular, comparisons with evidence-based references such as UpToDate are lacking.

OBJECTIVE: This study evaluated the similarity between responses generated by ChatGPT (with GPT-4o mini) and those from UpToDate to preclinical medical education questions to assess ChatGPT's potential as an adjunctive learning tool.

METHODS: We conducted a cross-sectional comparison study using 150 first-order questions derived from a preclinical question bank at a single allopathic institution under the …

Redefining Online Education: Integrating A Quality Assurance Rubric Process In A Community College Setting, Judy K. Howell

Morehead State Theses and Dissertations

A capstone submitted in partial fulfillment of the requirements for the degree of Doctor of Education in the Ernst and Sara Lane Volgenau College of Education At Morehead State University by Judy K. Howell on Kentucky March 20, 2026.

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 …

Una Student Organizations, Student Engagement Center, University Of North Alabama

Documents

No abstract provided.

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 …

Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft 2023 Stormwater Evaluation And Maintenance Report (Dated February 27, 2026), Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

The Evolution Of Science And The Transformation Of Human Understanding: Toward A Generative Framework Of Learning And Reality, Yoshihiko Ariizumi

Spiritual Proficiency

This essay argues that the development of science can be understood not as linear accumulation, but as a sequence of structural transformations in human understanding. Such a view aligns with a generative framework in which knowledge is not passively received or merely constructed, but emerges through dynamic interactions that reorganize cognitive and experiential structures. By situating this framework within the history of science, we can better understand both the nature of scientific progress and its indispensable role in human development.

Learning As Becoming: A Restored Gospel-Based Reinterpretation Of Scientific Discovery And Human Growth, Yoshihiko Ariizumi

Spiritual Proficiency

For many educators of the Church of Jesus Christ of the Latter-day Saints, a persistent dissonance exists between the secular textbooks we utilize and the restored truths we cherish. Traditional science often presents the universe as a closed, material system where learning is merely the acquisition of data. However, as we align our academic pursuits with the light of the Restored Gospel, we discover that scientific inquiry is not independent of spiritual growth. Rather, it is a primary mechanism through which we experience a fundamental shift in our very nature—moving from "knowing" to "becoming."

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 …

Combatting Desertification Scientifically: Where Feasible, Where Necessary, Bojie Fu, Yanxu Liu, Shuai Wang, Yijia Wang, Guipeng Cui, Yue Guo

Bulletin of Chinese Academy of Sciences (Chinese Version)

China has made remarkable achievements in combating desertification, achieving “zero net growth” in land degradation. With the goal of scientifically improving the relationship between humans and nature in drylands, the continuous exploration of new concepts, methods, and pathways for scientific desertification control will contribute to advancing the harmony between humans and nature in China’s drylands. Based on the definitions of desertification, ecological restoration baselines, and the contributions of nature to humans, we clarified the scientific implications of “controlling desertification where it is feasible and necessary”. We discussed the shift in China’s desertification prevention and control direction from “humans advancing while …

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 …

Understanding Key Lssues In Current Artificial Intelligence Development And Governance, Meng Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

At present, as global artificial intelligence advances vigorously, the industry is engaged in intense discussions about the future direction of its development and governance, where certain consensus has been reached alongside notable divergences and controversies. This study focuses on several key contentious issues in the current development and governance of artificial intelligence, analyzes their inherent logic by combining the laws of scientific and technological progress, and puts forward corresponding solutions. Regarding the potential bubble risk, it emphasizes the need to strengthen the application of artificial intelligence in the real economy to channel and guide its development momentum. For the future …

Construction Of Emerging Contaminants Risk Governance System, Cheng Li, Mingcheng Wang, Chunlei Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

Emerging contaminants pose considerable risks to the ecological environment, human health, and social safety. The establishment of an emerging contaminants risk governance system constitutes a crucial component of the national ecological security strategy and the ecological civilization framework in the new era. When examined through the lens of the holistic view of national security and guided by the ecological civilization philosophy of the new era, China’s current efforts in managing emerging contaminants reveal several shortcomings—including a fragmented and incomplete risk management system, as well as preliminary stages in chemical environmental management policies and related technologies. Therefore, grounded in national conditions …

Comparative Study On Ai Talent Cultivation In China And The United States: Strategies And Recommendations, Lexuan Li, Ke Wen, Wenjie Liu, Wei Shen, Zhenguo Li

Bulletin of Chinese Academy of Sciences (Chinese Version)

Artificial intelligence (AI), as the core driving force of the new industrial revolution, has become a strategic pillar for enhancing national competitiveness, with the cultivation of AI talent being a decisive factor. This study systematically compares the AI talent cultivation systems of China and the United States from three perspectives: strategic planning, formal education, and practical domains. The findings reveal that the U.S. has continuously and systematically advanced AI talent cultivation plans at the national level, granted institutions substantial autonomy in talent cultivation with deep integration of industry-academia-research collaboration, and established a well-developed AI innovation and entrepreneurship environment. Accordingly, the …

Research And Reflections On Model Of China’S Ai Open-Source Innovation Ecosystem, Yuntao Long, Haibo Liu, Qigang Zhu, Xudong Ren, Yanjun Wu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Open-source innovation, leveraging its strengths in collective collaboration and agile development, is increasingly becoming a core driver reshaping innovation paradigms and industrial ecosystems in the global artificial intelligence field. As a significant force in global technological development, China is actively promoting technology enterprises, research institutes, universities, and other diverse entities to deeply integrate into the construction of the global AI open-source innovation system through policy guidance, community building, and breakthroughs in large models. Based on the practical experience of building China’s AI open-source innovation ecosystem, this study systematically examines the current development status and challenges. By analyzing the operational models …

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 …