Digital Commons Network^™

Medilink: A Secure Blockchain Framework For Multi-Institutional Healthcare, Jorge Castillo, Qian Chen

Informatics and Engineering Systems Faculty Publications

The use of Electronic Medical Records (EMRs) in the healthcare industry has proven to be critical for storing highly sensitive information. Disseminating and protecting healthcare data poses major challenges for the current healthcare information system. Blockchain technology provides solutions to these challenges with its inherited properties, such as decentralization, immutability, and transparency. This provides a unique opportunity to improve data sharing among stakeholders. We propose MediLink, a blockchain-based framework for secure collaborative medical storage. MediLink is designed to (1) protect EMR data from cyber attacks, (2) share healthcare information of patients with different stakeholders, and (3) enable the Internet of …

Unleaded Fuel For General Aviation, Carolina Anderson, Laura Garcia

Sustainability Conference

The Clean Air Act, passed in the late 1970s, mandating the removal of lead from most fuels due its detrimental effects on public health, yet piston-driven aircraft continue to rely on leaded aviation gas (AvGas 100LL). This fuel remains the last lead-containing fuel regulated by the Department of Transportation (DOT). Lead, added as tetraethyl lead (TEL), enhances octane levels and prevents engine detonation, vital for high-compression aircraft engines. In response to the health effects, regulating bodies like the Environmental Protection Agency (EPA) have tightened lead standards and are assessing the risk posed by AvGas. Research links even low-level lead exposure …

Phr-Nft: Decentralized Blockchain Framework With Hyperledger And Nfts For Secure And Transparent Patient Health Records, Huwida E. Said, Nedaa B. Al Barghuthi, Sulafa M. Badi, Faiza Hashim, Shini Girija

All Works

Blockchain technology holds significant promise for healthcare by enhancing the security and integrity of patient health records (PHRs) through decentralized storage and transparent access. However, it has substantial limitations, including problems with scalability, high transaction costs, privacy concerns, and intricate stakeholder access management. This study presents PHR-NFT, a novel framework that strengthens PHR privacy by utilizing Hyperledger Fabric and non-fungible tokens (NFTs) to address these issues. PHR-NFT improves privacy and communication by letting patients keep control of their medical records while permitting temporary, permission-based access by medical professionals. PHR-NFT offers a transparent solution that increases trust among healthcare stakeholders through …

Red Harvester Ants Pogonomyrmex Barbatus (Smith, 1858) (Hymenoptera: Formicidae) Do Not Distinguish Between Sorghum Head Mold Symptomatic And Asymptomatic Seeds, Lilly Victoria Elliott-Vidaurri, Hannah J. Penn, Robin A. Choudhury

School of Earth, Environmental, & Marine Sciences Faculty Publications

Red harvester ants, Pogonomyrmex barbatus (Smith, 1858) (Hymenoptera: Formicidae), common in the Lower Rio Grande Valley of Texas, are known to gather seeds from areas around their nests and store the seeds inside their nests for later consumption. As these ants often nest in and near agricultural fields, some of these seeds may be from crops and may also be infected with fungal plant pathogens. These pathogens can degrade seed coats and may cause the seeds to rot within the ant nests, decreasing storage time and potentially spreading the pathogen to other stored seeds. We studied how head mold, a …

Novel Nanocomposite Of Carbonized Chitosan-Zinc Oxide-Magnetite For Adsorption Of Toxic Elements From Aqueous Solutions, Dalia A. Ali Eng, Ganna Gaber Ismail Eng.

Chemical Engineering

Herein, a novel nanocomposite (carbonized chitosan-zinc oxide-magnetite, CCZF) was developed to effectively remove toxic elements in water remediation. Combining the high adsorption capacities of chitosan with the magnetic properties of magnetite and the chemical stability of zinc oxide, the combination of these unique properties makes it an efficient and versatile material that offers a sustainable solution for water purification. The (CCZF) nanocomposite was synthesized through the coprecipitation method and characterized using various techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), Brunauer–Emmett–Teller (BET) analysis, X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, and zeta potential analysis. The results showed …

Participatory Ethical Regulations: Risk Challenges Of Artificial Intelligence Era And Construction Of Governance Logic, Chenggang Zhang, Lu Pan

Bulletin of Chinese Academy of Sciences (Chinese Version)

Participatory ethical norms emphasize the involvement of diverse stakeholders, aiming to construct a more comprehensive and balanced ethical governance framework. The rapid development of artificial intelligence (AI) technology is leading society through unprecedented transformations, significantly impacting ethical perspectives, social governance models, and the symbiotic relationship between humans and technology. The participatory ethical norms, characterized by multi-stakeholder participation, interactivity, and openness, represent a crucial pathway for addressing the challenges posed by the rapid development of AI technology. Constructing an AI governance framework based on participatory ethical norms provides solutions for the sustainable, fair, and transparent development of AI from multiple aspects …

Overview On Autonomous Machine Computing, Shaoshan Liu, Yiming Gan, Yinhe Han

Bulletin of Chinese Academy of Sciences (Chinese Version)

Autonomous machine computing, an innovative blend of algorithms, software, and cutting-edge computing hardware, is poised to be the next major paradigm shift in the global economy, following personal, mobile, and cloud computing. This study delves into the research and commercialization of the robotics industry, underscoring the critical importance of establishing a comprehensive autonomous machine computing ecosystem. This study argues that autonomous machine computing necessitates a complete ecosystem that encompasses applications, programming languages, and the foundational hardware architectures, and presents a comprehensive review of significant research contributions across these areas. Moreover, the study explores the synergy between autonomous machine computing and …

Prospect And Problem Analysis Of Industry Data Application In Livestock And Poultry Breeding, Yiran Chen, Zhuqing Xiong, Jiaogen Zhou, Quan Wang, Jiancheng Shu, Yinfa Yan, Lanlin Yang, Zemeng Feng, Benhai Xiong, Yulong Yin

Bulletin of Chinese Academy of Sciences (Chinese Version)

Livestock and poultry breeding is a pillar industry in China. The massive data in livestock and poultry breeding is a valuable resource. The market-oriented utilization of livestock and poultry breeding data plays an important role in improving industry standards, increasing industry profits, and driving the development of the entire industry chain. Currently, based on the demand for marketization of livestock and poultry breeding data, the application of new generation information technologies such as artificial intelligence and the Internet of Things in the process of livestock and poultry breeding to collect breeding process data, after de-sensitization and de-classification, through cloud computing, …

Ptsd Increases Risk For Hypertension Development Through Pvn Activation And Vascular Dysfunction In Sprague Dawley Rats, Xinqian Chen, Xin Yan, Chunxiu Yu, Qing-Hui Chen, Lanrong Bi, Zhiying Shan

Michigan Tech Publications

This study investigates the impact of single prolonged stress (SPS), a model of post-traumatic stress disorder (PTSD), on cardiovascular responses, hypothalamic paraventricular nucleus (PVN) activity, and vascular function to elucidate the mechanisms linking traumatic stress to hypertension. Although SPS did not directly cause chronic hypertension in male Sprague Dawley (SD) rats, it induced acute but transient increases in blood pressure and heart rate and significantly altered the expression of hypertension-associated genes, such as vasopressin, angiotensin II type 1 receptor (AT1R), and FOSL1 in the PVN. Notably, mitochondrial reactive oxygen species (mtROS) were predominantly elevated in the pre-autonomic regions of the …

Gpr-1194 Computer Vision-Enhanced Spectroscopy For Glucose Prediction: An In Vitro Validation Study, El Arbi Belfarsi

C-Day Computing Showcase

This study introduces a novel computer vision-based spectral approach for non-invasive glucose detection using synthetic blood samples. We developed an experimental setup with glucose concentrations from 70 to 120 mg/dL, using two dye methods. Light sources tested included an 850 nm LED, 850 nm laser, 808 nm laser, and 650 nm laser, with image capture via a 1080p IR camera. Data augmentation, including Gaussian noise, contrast and brightness adjustments, rotations, and zooming, produced seven variants per image. Three machine learning models—CNN, AdaBoost, and ResNet—were evaluated, with the 850 nm light source yielding the best results: 87.5% of predictions fell within …

Ur-172 A Comparative Study Of Llm Effectiveness In Mental Health Assistance​, Kris Prasad

C-Day Computing Showcase

This study evaluates the effectiveness of LLMs in supporting mental health applications by analyzing their performance in understanding and categorizing user (mental health-related) inputs. We collected data from various mental health apps on the Google Play Store, including user reviews and app descriptions, and filtered content using a targeted mental health keyword bank. Sentiment analysis and keyword similarity scores were generated for reviews using RoBERTa-based models, this showed us how each review aligned with the mental health keywords advertised by the app and how users felt about the app. We prompted four modern LLMs: GPT-4o, Claude 3.5 Sonnet, Gemma 2, …

Gmc-130 School Bus Monitoring Simulation W/ Apache Kafka, John Blake, Hudson Topping, Eun Sik Kim, Tiep Bui, Julio Lois

C-Day Computing Showcase

Our project is a proof-of-concept of event-streaming bus telemetry data using Apache Kafka (Kafka), as requested by our client, Gwinnett County Public Schools (GCPS). The Kafka event stream is more efficient than GCPS’s current process of pulling bus telemetry data: calling APIs every 5 seconds. Moving to Kafka will provide GCPS near real-time insights into bus locations and speeds, giving visibility to whether buses drive safely and punctually. Our simulation produces synthetic bus data to be passed through Kafka and consumed. It features two UIs for system monitoring and data visualization.

Gmr-216 Ai/Ml-Based Water Quality Monitoring Mobile App For Predicting E.Coli In Surface Waters, Keerthi Priya Karumanchi

C-Day Computing Showcase

E.coli contamination in surface waters has proven to be a significant public health concern, requiring innovative monitoring solutions. This paper presents the design of an AI-driven mobile application to predict whether E.coli bacteria are present at levels exceeding acceptable thresholds in surface waters. The methodology employs sensor devices to collect water quality data parameters, such as water temperature, pH, dissolved oxygen, and turbidity. A dataset is generated based on these parameters, and machine learning (ML) algorithms are applied to evaluate accuracy, precision, recall, and processing time. Additionally, our ML algorithms establish a correlation matrix among water quality parameters to identify …

Gmr-7175 Enhancing Alzheimer’S Diagnosis Through Spontaneous Speech Recognition: A Deep Learning Approach With Data Augmentation, Venkata Sai Bhargav Mutala

C-Day Computing Showcase

Alzheimer’s disease (AD) is a growing public health issue due to its progressive nature and rising prevalence. This study explores a neural network model trained on speech data from the ADReSS2020 Challenge dataset to distinguish AD patients from healthy individuals, using log-Mel spectrogram features. To improve accuracy, five data augmentation methods, including pitch and time shifting, were used. The results highlight deep learning, combined with data augumentation, as a promising, scalable, and noninvasive approach for early AD diagnosis

Gpr-2212 Explainable Multi-Label Classification Framework For Behavioral Health Based On Domain Concepts, Francis E Nweke, Abm Adnan Azmee

C-Day Computing Showcase

Behavioral health, which covers mental health, lifestyle choices, addictions, and crises, poses serious issues in the community. Thus, appropriately analyzing and classifying behavioral health data is crucial for making informed healthcare decisions. Traditional deep learning and natural language processing approaches struggle to effectively identify behavioral health issues because the data is unstructured, complex, and lacks sufficient context. Furthermore, subject matter experts must be consulted to ensure effective identification. In this work, we proposed a deep learning-based framework consisting of several modules: A) domain concept encoder converts the keywords and their evidence types to vectors, which were predefined by a subject …

Uc-166 The Eternal Guest - A 2d Hack-And-Slash Game, Luke H Gamage, Zion Johnson, Benjamin J Hedges, Bryanna N Walker, Avis A. Ewing

C-Day Computing Showcase

The Eternal Guest is a narrative-driven, hack-and-slash combat and exploration game where you make meaningful friendships, battle enemies, and regain lost memories as you traverse a strange, non-euclidian hotel. Use a wide array of weapons and abilities alongside the knowledge you gain from other guests to attempt to escape the bloodlust of a homicidal vampire. The Eternal Guest emphasizes 2D, top-down, melee combat in combination with ranged abilities, offering an exciting dynamic to gameplay. Our game also presents a unique spin on randomized exploration through its unique D.R.E.A.D. system, creating a sense of unease and uncertainty when exploring. This unique …

Uc-173 Leveraging Large Language Models To Empower Caretakers Of People With Dementia, Mercy Olaniran, Emily A Centeno

C-Day Computing Showcase

Behavioral symptoms of Alzheimer's Disease and Related Dementias (ADRD) are detrimental to the quality of life for individuals with ADRD and their caregivers. Symptoms such as wandering, agitation, and confusion can often overwhelm caregivers leading to stress, depression, or burnout which can lead to a decrease in the quality of care. These challenges often result in increased hospitalizations and care costs, creating a need for a solution to support informal caregivers. This project proposes the development of an AI-based Dementia Care Voice Assistant application to meet the needs of caregivers. Using large language models, the application will provide real-time and …

Gmr-159 Llm Enabled Synthetic Dataset Generation For Human-Ai Teaming Algorithm, Sai Sanjay Potluri

C-Day Computing Showcase

This research explores using Large Language Models (LLMs) to generate synthetic datasets for Human-AI teaming algorithms, focusing on mental health assessments. We create a diverse dataset simulating human-AI collaboration scenarios in diagnostic processes. The synthetic data is labeled through an innovative approach involving two human annotators and three LLMs, using majority voting for consensus-based annotations. This dataset serves as a resource for training and evaluating Human- AI teaming algorithms, enabling exploration of collaboration dynamics between human expertise and AI in complex decision-making. Our approach addresses the scarcity of real-world data in Human-AI teaming scenarios and provides a controlled environment for …

Gmr-208 Automatic Categorization Of Behavioral Health Issues In Police Reports, Mason V Pederson, Abm Adnan Azmee, Francis E Nweke

C-Day Computing Showcase

911 is often the first place contacted for dealing with behavioral health related (BHR) issues. Its estimated at least a fifth of all calls are related to behavioral health, and with BHR affected convicts having a recidivism rate of around 30%, its not hard to see how straining these issues can become on systems already stretched thin, where chronic understaffing is often a reality. A great solution would be if we could intervene as soon as possible to get people the treatment they need, police reports would be excellent for identifying and treating these individuals, but annotation is a long …

Gpr-151 Compassionate Digital Assistant: Anchor, Christopher M Regan, Navneet Verma

C-Day Computing Showcase

Mental health support is crucial, but access to professional care can be limited by cost, availability, and social stigma. Digital solutions, particularly chatbots, offer an accessible and scalable approach to providing mental health support. However, current chatbot solutions may not always reflect the diversity of users' emotional experiences, and they may lack the specialized domain knowledge and adaptability required for effective mental health counseling. This research project aims to address these challenges by developing a compassionate AI digital assistant that can use specialized natural language processing (NLP) models to provide empathetic and targeted responses based on the nature of the …

Gpr-233 Human-Assisted Ai For Detecting Mental Health Indicators In Social Media, Abm Adnan Azmee, Francis E Nweke, Mason V Pederson

C-Day Computing Showcase

Mental health is essential to overall well-being, and mental illness includes conditions that affect a person’s psychological health, causing significant distress and limiting daily functioning. With advancements in technology, social media has become a platform where individuals openly share their emotions and thoughts, offering a unique window into their psychological states. However, traditional machine learning models struggle to interpret social media data's wide range of linguistic nuances. To analyze this data effectively, collaboration with human experts is crucial. This study proposes an innovative human-AI teaming framework that integrates human expertise with artificial intelligence (AI) to address these challenges. Our framework …

Uc-140 Streamlining School Bus Monitoring: Gcps's Transition To Real-Time Kafka Event Processing​, Sarah Fashinasi, Tyler J Hood, Jeffrey Sanderson, Amali B Mchie, Alexandra Baker

C-Day Computing Showcase

This project develops a prototype real-time bus monitoring system for Gwinnett County Public Schools using simulated Kafka event streaming to replace current API polling methods. The system processes simulated Asset Location and Speed events, mimicking Samsara's Kafka Connector, performing data validation before storing in SQL Server. The containerized solution demonstrates the potential for near real-time visibility into school bus operations.

Uc-247 Using Dynamic Difficulty Adjustment (Dda) To Improve Health And Wellness Apps And Programs, Fernando Orfila

C-Day Computing Showcase

Physical inactivity, obesity and Type 2 Diabetes cost the United States’ economy more than $700 billion a year (CDC). Yet, individuals spend $137 billion dollars a year on gym memberships to get in shape and feel better, without attaining results and dropping out. “…63% of new members will abandon activities before the third month, and less than 4% will remain for more than 12 months of continuous activity.” (Sperandei et al). The personal training apps don’t fare better, with 71% of users disengaging within 90 days (Amagai et al). The higher chances of people dropping out are due to "a …

Ur-239 Human-Ai Annotator Tool​, Anh Duong, Habeebah Muse, Chase Castro

C-Day Computing Showcase

The HK-01 Human-AI Annotator Tool is a web-based system developed to facilitate the annotation of Electronic Health Records (EHRs) for mental and behavioral health, using ICD-10 codes. The tool allows multiple expert annotators to tag critical information, making it easier to catalog patient data accurately. Future plans include integrating AI to streamline and scale the annotation process, improving both efficiency and accuracy.

First Amendment Roadblock? Regulating The Misuse Of Generative Ai Technologies: Impersonation And Appropriation Of Likeness Without Permission, Muhammad Rabiu

Cybersecurity Undergraduate Research Showcase

This paper initially explores the misuse of generative AI technologies, particularly their role in impersonating or appropriating individuals' likeness without consent. It will then analyze technical and legal mitigation strategies and propose recommendations to address this issue in light of the First Amendment’s constitutional Freedom of Speech provision.

From Classroom To Cloud: Why Cybersecurity Education Is Crucial For Tomorrow's Learners, Kiori Edwards

Cybersecurity Undergraduate Research Showcase

This paper examines the transformative impact of cloud computing on education, highlighting how cloud technologies are reshaping teaching and learning environments, making education more accessible, flexible, and collaborative. It also explores the critical importance of incorporating cybersecurity education into school curricula. As digital devices and cloud-based platforms become integral to students' daily lives, they are increasingly vulnerable to cyber threats. This paper argues that early cybersecurity education, starting at the elementary level, is essential for equipping future generations with the knowledge and skills needed to navigate the digital world safely, protect their personal information, and avoid cybercrime.

Disparities In The Prevalence Of Hospitalizations And In-Hospital Mortality Due To Acute Myocardial Infarction Among Patients With Non-Alcoholic Fatty Liver Disease: A Nationwide Retrospective Study, Umar Hayat, Faisal Kamal, Muhammad Kamal, Wasique Mirza, Tariq Ahmad, Manesh Gangwani, Dushyant Dahiya, Hassam Ali, Shiva Naidoo, Sara Humayun, Hayrettin Okut, Muhammad Aziz

Division of Gastroenterology and Hepatology Faculty Papers

Background: Non-alcoholic liver disease (NAFLD) may be associated with cardiovascular diseases; however, only a few studies have analyzed this relationship. We aimed to assess the epidemiologic data and the association between NAFLD and acute myocardial infarction (AMI) in the United States. Methods: The National Inpatient Sample (NIS) database 2016-2019 was queried using ICD10-CM diagnostic codes to identify hospitalizations of AMI + NAFLD. Essential demographic variables were analyzed to determine the disparities in the prevalence of AMI hospitalizations and deaths among NAFLD patients. Univariate and multivariate logistic regression models determined the association between NAFLD and AMI hospitalizations and death. …

11.18.2024 Orsp Connect, Liz Williamson

ORED Newsletter

Director of Research Lab Safety

GIS Day

Tech Startup Weekend

NSF Virtual Grants Conference

Performance And Trihalomethane Formation Potential Of Alternative Electron Donors For Wastewater Denitrification, Bruno Fulco Mancini

USF Tampa Graduate Theses and Dissertations

Nitrogen removal from wastewater is critical to preserve ecosystems, as well as human health and welfare. Excess nutrients in receiving waters can cause many problems to the environment, such as algal blooms, drinking water contamination, and economic losses. Nitrogen removal in wastewater occurs mainly through the oxidation and reduction processes of nitrification and denitrification, which occur in engineered systems at wastewater treatment plants or water reclamation facilities.

The site for this research was the South Cross Bayou (SCB) Water Reclamation Facility, located in Pinellas County, FL, USA. At SCB, nitrogen is removed through a Modified Ludzak-Ettinger (MLE) process with the …

Changing Characteristics Of Land Cover, Landscape Pattern And Ecosystem Services In The Bohai Rim Region Of China, Jiaqi Liu, Wei Chen, Hu Ding, Zhanhang Liu, Min Xu, Ramesh P. Singh, Congqiang Liu

Mathematics, Physics, and Computer Science Faculty Articles and Research

Since the Anthropocene, ecosystems have been continuously deteriorating due to global climate change and human intervention. Exploring the changing characteristics of land use/land cover (LULC), landscape pattern and ecosystem service (ES) and their drivers is crucial for regional ecosystem management and sustainable development. Taking the Bohai Rim region of China as an example, we used the land use transfer matrix, landscape pattern index and InVEST model to analyze the changing characteristics of LULC, landscape pattern and six key ESs [crop production (CP), water yield (WY), carbon storage (CS), soil conservation (SC), habitat quality (HQ), landscape aesthetics (LA)] during 2000–2020. Detailed …