Digital Commons Network^™

Barriers To Machine Learning Adoption In Regulated Electric Utilities, Donald R. Shiflet Jr.

USF Tampa Graduate Theses and Dissertations

Machine learning (ML) technologies have the potential to revolutionize regulated electric utilities by improving operational efficiency, enabling predictive maintenance, and optimizing energy management. Despite these advantages, the adoption of ML in this sector lags other industries due to technical, organizational, and regulatory barriers. This research, grounded in the Technology-Organization-Environment (TOE) framework, explores these barriers to uncover actionable solutions for integration. The study identifies key challenges, including explainability, cybersecurity, workforce resistance, and regulatory ambiguity to ML adoption in electric utilities. Utilizing an exploratory qualitative methodology, this approach integrates insights from the literature and industry interviews to rank barriers by frequency, severity, …

Tableau Part Ii - October 2025, Rubab Shahzad

Day Family Research Lab Workshop Series

Part Two of Introduction to Tableau. Learn to make cool visualizations using Tableau. A hands-on opportunity where we will go over calculated fields, hierarchies, unions, dashboards, and stories.

Prior experience with Tableau is recommended

Skin Cancer Image Classification Using Deep Learning With Data Segmentation Technique, Akhilesh Kumar Shrivas, Hema Vastrakar

Karbala International Journal of Modern Science

The human skin is an impressive organ and structural element often impacted by a diverse range of recognized and unknown diseases. Diagnosing disorders that affect the outermost layer of the body is the most uncertain and difficult component in the scientific field. Dermatological diseases are one of the most significant health concerns in the 21st century since their identification is challenging and costly, plagued with challenges and the subjectivity that comes with human interpretation. The main objective of this piece of research work is to develop a robust model for the classification of skin cancer diseases using deep convolution neural …

Prompt Engineering For Genai In Cybersecurity Incident Response: A Multi-Platform Evaluation Based On Nice Pr-Ir-001, Yuanyuan Liu

Journal of Cybersecurity Education, Research and Practice

This study explores the application of prompt engineering in cybersecurity education, mainly by evaluating the performance of different generative artificial intelligence (GenAI) platforms when performing tasks consistent with the NICE framework role pr-ir-001 - Network Defense Incident Responder. The study employed structured prompts designed for a medical technology environment compliant with HIPAA and NIST SP 800-53, while the tasks of the three GenAI models (GPT-4, Gemini, and DeepSeek) were to generate event response scenarios. Their outputs will be evaluated from four aspects: accuracy, relevance, clarity and completeness.

The results show that the three models differ in depth and consistency, but …

An Integrated Pcb-Based Heating And Auto-Ranging Platform For Volatile Organic Compound (Voc) Detection Using Carbon Nanotube Based Sensors, Thomas Kalach

USF Tampa Graduate Theses and Dissertations

This thesis presents the development, characterization, and integration of a novel low-cost, high-dynamic-range sensor platform for the detection of volatile organic compounds (VOCs), leveraging the unique electrical properties of carbon nanotube (CNT) thin films. The platform introduces a fully integrated auto-ranging analog front-end circuit capable of real-time resistance measurement spanning over eight orders of magnitude ranging from tens of ohms to hundreds of megaohms, without compromising signal resolution or precision. This was achieved through a digitally controlled, multi-path feedback architecture and controllable current source.

To further enhance sensor performance, the system incorporates a copper trace heater beneath the sensor array, …

Development Of Natural Product Analogs As Therapeutic Agents, Jacob Mara

Theses and Dissertations

Cancer stem cells (CSC) are cancer cells in a tumor mass that may self-renew and develop into various cell types, resulting in a heterogeneous tumor. CSCs have been shown to have a role in many facets of cancer formation, including tumor genesis, proliferation, and metastatic activity. They are also implicated in chemotherapeutic treatment resistance and the recurrence of some malignancies. Based on these capacities, CSCs have been identified as the next target for cancer therapy and control. Salinomycin's potential for therapeutic use based on ongoing research, as well as the synthesis of its derivatives and their biological activity, will also …

10.13.2025 Ored Connect, Liz Williamson

ORED Newsletter

• ORED Small Grants Program RFP
• Mississippi Impact Grants RFP
• Contest to Promote Lab Practices
• Field Fest
• AAAS Membership for Faculty, Staff, and Students 

Draft Final 2024 Residential Metals Abatement Program (Rmap) Baptist Student Union (Former Mckinley School) Soil Remedial Action Construction Completion Report, Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Empirical Methods For Support System Design In Deep Serpentinite Excavations: A Critical Evaluation, Anas Driouch, Redouane Oubah, Abdelaziz Lahmili, Latifa Ouadif

Journal of Sustainable Mining

Underground mining excavations in fragile serpentinite rock masses represent a significant challenge today. The complicated features of these rock formations, especially at great depths, make it difficult to classify them using commonly employed methods. This paper focuses on the application of empirical methods for the classification of serpentinite rock masses and the design of support systems in underground mining excavations. Specifically, it concerns an access tunnel excavated entirely in serpentinite at a depth of 460 m. Geomechanical classification systems indicate that the Tunnelling Quality Index (Q-system) and Rock Mass Rating (RMR) evaluate serpentinites as rock masses of exceptionally poor to …

Building Resilient And Sustainable Supply Chains: A Distributed Ledger-Based Learning Feedback Loop, Tan Gürpinar, Mehmet A. Gulum

Computer Science Faculty publications

Global supply chains face increasing disruptions from cyber threats, geopolitical instability, extreme weather events, and a range of economic, social, and environmental sustainability challenges. As these disruptions intensify, enhancing Supply Chain Resilience (SCR) has become a strategic priority. This study investigates how Distributed Ledger Technology (DLT) can contribute to SCR by mitigating vulnerabilities and strengthening key capabilities within global supply chains. A qualitative research approach is employed, utilizing expert evaluations to examine DLT’s impact on supply chain vulnerabilities and capabilities. Five workshops were conducted with 25 industry professionals from logistics, IT, procurement, and risk management. Experts examined how DLT could …

Bifusenet: A Multimodal Network For Estimating Blood Alcohol Concentration Via Bidirectional Hierarchical Fusion, Abdullah Tariq, Arooba Maqsood, Martin Masek, Syed Zulqarnain Gilani

Research outputs 2022 to 2026

Drunk driving remains a significant public safety challenge, demanding innovative alternatives to conventional methods such as field sobriety tests and breathalysers. Estimating a driver's level of intoxication through facial cues is particularly challenging due to the subtle and person-specific nature of alcohol-induced behaviours. In this paper, we present BiFuseNet, a 3D spatio-temporal multi-modal network designed to classify alcohol impairment levels into three categories: sober, moderate, and severe. Unlike prior approaches that rely on either uni-modal RGB video or hand-crafted facial features, our method exploits complementary physiological cues from RGB and infrared (IR) facial videos. We introduce a Bi-directional Hierarchical Fusion …

Improved Streamflow Forecasting Through Swe-Augmented Spatio-Temporal Graph Neural Networks, Akhila Akkala, Soukaina Filali Boubrahimi, Shah Muhammad Hamdi, Pouya Hosseinzadeh, Ayman Nassar

Computer Science Student Research

Streamflow forecasting in snowmelt-dominated basins is essential for water resource planning, flood mitigation, and ecological sustainability. This study presents a comparative evaluation of statistical, machine learning (Random Forest), and deep learning models (Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Spatio-Temporal Graph Neural Network (STGNN)) using 30 years of data from 20 monitoring stations across the Upper Colorado River Basin (UCRB). We assess the impact of integrating meteorological variables—particularly, the Snow Water Equivalent (SWE)—and spatial dependencies on predictive performance. Among all models, the Spatio-Temporal Graph Neural Network (STGNN) achieved the highest accuracy, with a Nash–Sutcliffe Efficiency (NSE) of 0.84 …

Discriminative Accuracy Of Cha2ds2-Vasc Score, And Development Of Predictive Accuracy Model Using Machine Learning For Ischemic Stroke Risk In Cardiac Amyloidosis And Atrial Fibrillation, Waqas Ullah, Abhinav Nair, Eric Warner, Salman Zahid, Mansoor Rahman, Palwasha Khan, Indranee Rajapreyar, Sridhara S. Yaddanapudi, M. Chadi Alraies, Said Ashraf, Jeffery Van Hook, Yegeny Brailovsky

Department of Medicine Faculty Papers

BACKGROUND: CHA2DS2-VASc score in cardiac amyloidosis (CA) with atrial fibrillation (AF) is believed to underestimate ischemic stroke risk, necessitating a better predictive model.

METHODS: Data were obtained from the National Readmission Database (NRD). Outcomes between CA-AF and no-CA-AF were compared using multivariate regression analysis to calculate adjusted odds ratios (aORs). AutoScore, an interpretable machine learning framework, was used to develop a stroke risk prediction model, and its predictive accuracy was evaluated with an area under the curve (AUC) using the receiver operating characteristic analysis.

RESULTS: A total of 11,860,804 (CA-AF 22,687 (0.19%) and no-CA-AF 11,838,117) patients were identified from 2015 …

Butte Priority Soils Operable Unit (Bpsou) 2025 Monthly Progress Report. Consent Decree For The Butte Priority Soils Operable Unit. Civil Action No. Cv 89-039-Bu-Seh, Josh Bryson

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Factors Influencing Plant Community Structure And Composition Of Restored Tamaulipan Thornscrub Forests, Jerald T. Garrett, Audrey J. Hicks, Christopher A. Gabler

School of Earth, Environmental, & Marine Sciences Faculty Publications

The Lower Rio Grande Valley (LRGV) of Texas is a biodiversity hotspot due to its high alpha, beta, and gamma diversity and high regional endemism, which are at high risk of degradation. The region has lost 95% of its native thornforest habitat primarily due to agricultural and urban expansion. This study aims to evaluate the current vegetative structure and composition of restored thornforest sites located in the LRGV to identify restoration methods and site characteristics that affect forest restoration outcomes. Twelve restored thornforest sites were selected for this study that varied in time since restoration, patch size, degree of isolation, …

Problem-Based Learning Assisted By Augmented Reality On The Respiratory System Topic: A Study Of Students’ Critical Thinking Skills And Learning Motivation, Nyimas Dilviana, Ade Yeti Nuryantini, Sumiyati Sa'adah

Jurnal Pendidikan Sains

This study aims to examine the effectiveness of the Problem-Based Learning (PBL) model assisted by Augmented Reality (AR) technology regarding the respiratory system in improving students’ critical thinking skills and learning motivation. The research method used was a quasi-experimental design with a one-group pretest-posttest model. The subjects were 30 eleventh-grade students from a public high school in Garut City. Research instruments included a critical thinking test and a learning motivation questionnaire. The results showed a significant improvement in students’ critical thinking scores after the implementation of PBL with AR support. Additionally, learning motivation data analyzed from 16 statement items revealed …

Day-Night Shifts In Water-Soluble Ions Of Size-Resolved Aerosols Before And After The Covid-19 Lockdown In A Coastal Megacity: Metro Manila, Philippines, Grace Betito, Paola Angela Bañaga, Rachel A. Braun, Maria Obiminda Cambaliza, Melliza Templonuevo Cruz, Alexander B. Macdonald, James Bernard Simpas, Connor Stahl, Armin Sooroshian

SOSE Affiliate: Manila Observatory

The COVID-19 pandemic-driven lockdowns offer a unique opportunity to examine how reductions in anthropogenic emissions impacted atmospheric aerosol composition in urban environments. This study investigates the day-night variability of size-resolved water-soluble ions in ambient particulate matter (PM) collected in Metro Manila before (November 2019–February 2020) and after (November 2020–February 2021) lockdown implementation. Using tandem Micro-Orifice Uniform Deposit Impactors (MOUDIs), aerosol samples were collected during daytime (06:00–18:00) and nighttime (18:00–06:00) periods and analyzed for key ionic species (sulfate, ammonium, nitrate, oxalate, sodium, chloride, calcium, and magnesium) via ion chromatography. Submicrometer water-soluble mass declined post-lockdown, particularly during daytime, reflecting suppressed secondary formation …

Final 2025 Residential Metals Abatement Program (Rmap) Butte Koa Playground Soil Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Ophthoacr (Ophthalmology Automated Chart Review): An Ai-Powered Tool For Complete Automation Of Ophthalmology Chart Reviews And Cohort Data Analysis, Karen M. Chen, Kevin W. Chen, Vlad Diaconita, Stanley Chang, Leejee H. Suh

School of Medicine Faculty Publications

Purpose: Retrospective chart reviews in ophthalmology are essential for gaining clinical insights, but they remain labor-intensive and prone to error. Despite digitization through electronic health records, extracting and interpreting lengthy, unstructured patient histories remains challenging, particularly in ophthalmology, which relies heavily on both imaging and text-based reports. We introduce OphthoACR, a Health Insurance Portability and Accountability Act-compliant artificial intelligence (AI)-powered tool for automated chart review and cohort analyses in ophthalmology. Methods: OphthoACR was applied to extract 16 variables of increasing task difficulty from the complete chart histories of 91 patients who underwent secondary intraocular lens surgery at the Columbia University …

Final 2025 Residential Metals Abatement Program (Rmap) Cccs Gymnasium Soil Remedial Action Work Plan (Rawp), Pioneer Technical Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Mechanistic Distinction Between Oxidative And Chlorination Transformations Of Chloroperoxidase From Caldariomyces Fumago Demonstrated By Dye Decolorization, Norman Paz-Ramirez, Jacob Redwinski, Matthew A. Cranswick, Kyle A. Grice, Kari Stone

Chemistry Department Faculty Articles

Effluents from the textile industry, particularly those containing synthetic azo dyes, poses a significant environmental threat, necessitating the development of more effective and sustainable pollutant removal methods. Traditional dye removal techniques often fall short in efficiency and environmental impact, prompting the exploration of enzymatic degradation as a promising alternative. This study focuses on chloroperoxidase, a natural biocatalyst recognized for its ability to oxidize synthetic dyes into less harmful products. By exploring the mechanistic distinction between chlorination and oxidative processes, we investigate the enzyme’s specific degradation pathways for azo dyes and the resulting by-products. Utilizing analytical techniques, including liquid chromatography/mass spectrometry …

Re: Butte Priority Soil Operable Unit (Bpsou) Final Insufficiently Reclaimed Sites Field Sampling Plan (Fsp): Bres No. 177 – North Alice Culvert, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Approval Letter For The Butte Priority Soils Operable Unit (Bpsou) Final Insufficiently Reclaimed Sites Field Sampling Plan (Fsp): Ur- 19 – Butte, Anaconda & Pacific Railway From Montana Street To South Arizona Avenue – Montana Street Adjacent Parcel (Dated August 13, 2025), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Investigating The Organs At Risk (Oar) Received Dose During Prostate Cancer Therapy Using Intensity Modulated Radiation Therapy (Imrt) And 3d Conformal Radiotherapy (3dcrt): A Comparison Study, Talib Abdulwahid, Hussein Mraity, Mustafa Al-Aseebee, Zeyad Al-Dulaimi, Ali Abid Abojassim

Chulalongkorn Medical Journal

Radiotherapy domain is known to impose undesired risk of radiation to normal tissue surrounding the tumor. So, the treatment planning systems are developing with time to introduce a perfect treatment. Organs at risks surrounding prostate tumors are sensitive to high doses of radiation. This study is aimed at comparing the efficiency of the three-dimensional conformal radiotherapy (3DCRT) and intensity-modulated radiation therapy (IMRT) techniques during the treatment of prostate cancer. A cross-sectional study was performed in Middel Euphrate Csancer Center, Najaf , Iraq. A 25 patients with prostate tumor were enrolled. They underwent CT scans from imaging then treated with x-ray …

Re: Butte Priority Soil Operable Unit (Bpsou) Final Bres No. 35 Del Monte Reclamation Improvement Field Sampling Plan, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Scientific Authority In The Public Sphere: The Heroic Legacies Of Carl Sagan And Philip Zimbardo, Scott T. Allison

Heroism Science

This article examines the parallel trajectories of Carl Sagan and Philip Zimbardo as scientists who assumed the role of public intellectuals. Their careers highlighted the tensions and opportunities inherent in bridging scholarly research and public engagement. Sagan, an astronomer, popularized the cosmic perspective to promote planetary stewardship, while Zimbardo, a social psychologist, used compelling methodologies to explore the psychological underpinnings of cruelty and heroism. Both were, in their own ways, heroic in their commitment to making science accessible, employing storytelling and mass media to render complex concepts understandable and relevant, thereby expanding the societal relevance of their disciplines. However, their …

10.06.2025 Ored Connect, Liz Williamson

ORED Newsletter

• Field Fest
• AAAS Membership
• MIG Application Opportunity
• Contest to Promote Safe Lab Practices

Re: Butte Priority Soils Operable Unit (Bpsou) Final Reclamation Improvement Sites Field Sampling And Investigation Plan (Fsp): Bres No. 45 – Garfield, Mike Mcanulty

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

The Effects Of Plastic Mulch And Irrigation On Hemp Chemistry And Leaf Endophytes, Allison Rietman, Connor Morozumi, Robert C. Pearce, Natalie Christian

Journal of Agricultural Hemp Research

As an emerging crop, cultivation techniques for industrial hemp (Cannabis sativa L.) are still being developed and optimized. For example, irrigation and plastic mulching are some management practices that have been touted for their benefits in improving crop quality. Both techniques ensure ample water availability, which has often been attributed to improving hemp cannabinoid and terpene composition. In this study, we examined how supplemental irrigation implemented in a plastic mulch system influenced the cannabinoid and terpene profiles of one cultivar of CBD hemp, Lifter. We grew industrial hemp in field with plastic mulch and applied regular irrigation to one group …

A Review Of Research And Practices On Teaching Data Visualizations For Blind And Visually Impaired Students, Shiya Cao

Statistical and Data Sciences: Faculty Publications

Around 36 million people in the world are blind and an additional 217 million have moderate to severe vision impairment. In higher education, four percent of 54,204 undergraduates who participated in the 2022 American College Health Association survey reported to be blind or have low vision. Those students frequently do not have access to data visualizations we generally teach and use in postsecondary statistics and data science classes. The design of those visualizations is premised on implicit assumptions about the user’s visual ability. Making data visualizations accessible to blind and visually impaired (BVI) people would help improve equity in higher …