Binder, Tyler A. Peaster, Lindsey M. Davenport, Madelyn Little, Alex Bales

ATU Scholars Symposium

Binder is a mobile application that aims to introduce readers to a book recommendation service that appeals to devoted and casual readers. The main goal of Binder is to enrich book selection and reading experience. This project was created in response to deficiencies in the mobile space for book suggestions, library management, and reading personalization. The tools we used to create the project include Visual Studio, .Net Maui Framework, C#, XAML, CSS, MongoDB, NoSQL, Git, GitHub, and Figma. The project’s selection of books were sourced from the Google Books repository. Binder aims to provide an intuitive interface that allows users …

Techniques To Detect Fake Profiles On Social Media Using The New Age Algorithms – A Survey, A K M Rubaiyat Reza Habib, Edidiong Elijah Akpan

ATU Scholars Symposium

This research explores the growing issue of fake accounts in Online Social Networks [OSNs]. While platforms like Twitter, Instagram, and Facebook foster connections, their lax authentication measures have attracted many scammers and cybercriminals. Fake profiles conduct malicious activities, such as phishing, spreading misinformation, and inciting social discord. The consequences range from cyberbullying to deceptive commercial practices. Detecting fake profiles manually is often challenging and causes considerable stress and trust issues for the users. Typically, a social media user scrutinizes various elements like the profile picture, bio, and shared posts to identify fake profiles. These evaluations sometimes lead users to conclude …

Advanced Nano-Drug Delivery Systems In The Treatment Of Ischemic Stroke, Jiajie Zhang, Zhong Chen, Qi Chen

Faculty, Staff and Student Publications

In recent years, the frequency of strokes has been on the rise year by year and has become the second leading cause of death around the world, which is characterized by a high mortality rate, high recurrence rate, and high disability rate. Ischemic strokes account for a large percentage of strokes. A reperfusion injury in ischemic strokes is a complex cascade of oxidative stress, neuroinflammation, immune infiltration, and mitochondrial damage. Conventional treatments are ineffective, and the presence of the blood-brain barrier (BBB) leads to inefficient drug delivery utilization, so researchers are turning their attention to nano-drug delivery systems. Functionalized nano-drug …

Determining Reading Complexity Using Regression Models, Joshua Talamayan

Seton Hall University Dissertations and Theses (ETDs)

Reading is an essential skill when pursuing academic success. In order to assist students in developing their critical reading skills, it is essential to offer texts that are both within their capability, yet challenging enough to push them beyond their boundaries. At the moment, the majority of excerpts are matched to readability scores utilizing tools such as the Flesch-Kincaid Grade Level scoring in order to determine reader level. The core issue with reading scores structured around the Flesch-Kincaid Grade Level scoring is that the scoring process is not readily available to the public while also lacking validation studies. In this …

Accessing Advanced National Supercomputing And Storage Resources For Computational Research, Ramazan Aygun

All Things Open

This presentation will cover ACCESS (Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support), and Kennesaw State University's involvement in Open Science Data Federation program as a data origin to help researchers and educators with or without supporting grants to utilize the nation’s advanced computing systems and services. ACCESS, a program established and funded by the National Science Foundation, is an ecosystem with capabilities for new modes of research and further democratizing participation. The presentation covers how to apply for allocations on ACCESS. The last part of the presentation will briefly explain Open Science Data Federation and Kennesaw State University's involvement as …

Ml241 Antagonizes Erk 1/2 Activation And Inhibits Rotavirus Proliferation, Jinlan Wang, Xiaoqing Hu, Jinyuan Wu, Xiaochen Lin, Rong Chen, Chenxing Lu, Xiaopeng Song, Qingmei Leng, Yan Li, Xiangjing Kuang, Jinmei Li, Lida Yao, Xianqiong Tang, Jun Ye, Guangming Zhang, Maosheng Sun, Yan Zhou, Hongjun Li

Faculty, Staff and Student Publications

Rotavirus (RV) is the main pathogen that causes severe diarrhea in infants and children under 5 years of age. No specific antiviral therapies or licensed anti-rotavirus drugs are available. It is crucial to develop effective and low-toxicity anti-rotavirus small-molecule drugs that act on novel host targets. In this study, a new anti-rotavirus compound was selected by ELISA, and cell activity was detected from 453 small-molecule compounds. The anti-RV effects and underlying mechanisms of the screened compounds were explored. In vitro experimental results showed that the small-molecule compound ML241 has a good effect on inhibiting rotavirus proliferation and has low cytotoxicity …

Tissue-Specific Atlas Of Trans-Models For Gene Regulation Elucidates Complex Regulation Patterns, Robert Dagostino, Assaf Gottlieb

Faculty, Staff and Student Publications

BACKGROUND: Deciphering gene regulation is essential for understanding the underlying mechanisms of healthy and disease states. While the regulatory networks formed by transcription factors (TFs) and their target genes has been mostly studied with relation to cis effects such as in TF binding sites, we focused on trans effects of TFs on the expression of their transcribed genes and their potential mechanisms.

RESULTS: We provide a comprehensive tissue-specific atlas, spanning 49 tissues of TF variations affecting gene expression through computational models considering two potential mechanisms, including combinatorial regulation by the expression of the TFs, and by genetic variants within the …

A Holistic And Collaborative Behavioral Health Detection Framework Using Sensitive Police Narratives, Martin Keagan Wynne Brown

Dissertations

Identifying behavioral health is paramount for law enforcement officers to provide appropriate follow-up community care. In the current practice, law enforcement offices manually identify these behavioral health cases to allow the designation of the relevant follow-up resources. Police reports generated by officers' response to 911 calls remain an untapped resource for identifying such incidents. Therefore, we advocate for the incorporation of manual annotations from experts, natural language processing (NLP), active learning, advanced machine learning, and ensemble techniques to detect behavioral health cases within police reports. In this dissertation, we develop tools and frameworks to automatically detect behavioral health cases from …

5675 Wiredcats Scouting Hub, Sebastian Smiley

Honors Theses

The WiredCats Scouting Hub was created to provide FIRST team 5675 with an application that allows them to make more informed strategic decisions regarding their competitive play. The app synthesizes data from multiple sources, parsing multiple data formats into a single source of truth. It also presents data to users through graphs and charts and provides interactive tables. The application meets the requirements set forth by the leadership of team 5675, effectively providing the capabilities they seek.

The Vulnerabilities Of Artificial Intelligence Models And Potential Defenses, Felix Iov

Cybersecurity Undergraduate Research Showcase

The rapid integration of artificial intelligence (AI) into various commercial products has raised concerns about the security risks posed by adversarial attacks. These attacks manipulate input data to disrupt the functioning of AI models, potentially leading to severe consequences such as self-driving car crashes, financial losses, or data breaches. We will explore neural networks, their weaknesses, and potential defenses. We will discuss adversarial attacks including data poisoning, backdoor attacks, evasion attacks, and prompt injection. Then, we will explore defense strategies such as data protection, input sanitization, and adversarial training. By understanding how adversarial attacks work and the defenses against them, …

The Study On Mechanical Model Considering Optimal Self-Adaption In The Bottleneck Area, Longcheng Yang, Huajun Wang, Jun Hu, Hongyu Pan, Juan Wei, Lei You, Hao Zhang, Junxi Wang

Faculty, Staff and Student Publications

It aims to solve the problem that the evacuation state of pedestrians depicted by the traditional social force model in a crowded multiexit scenario has a relatively large difference with the actual state, especially the 'optimal path' considered by the self-driving force is the problem of shortest path, and the multiexit evacuation mode depicted by the 'herd behavior' is the local optimum problem. Through in-depth analysis of actual evacuation data of pedestrians and causes of problem, a new crowd evacuation optimization model is established in order to effectively improve the simulation accuracy of crowd evacuation in a multi-exit environment. The …

Urinalysis Test Data Analysis And Prediction, Nikhil Mhatre

2024 Datathon Challenges-Archive

OUTLIERS Team submission to the Urinalysis Test Results Timed Challenge

Researched various algorithms like boosting and random forest. We learned a lot about their strength and weaknesses, and used these algorithms accordingly to solve the issues faced in the dataset.

Mathematically Rigorous Deep Learning Paradigms For Data-Driven Scientific Modeling, Owen Nicholas Davis

Mathematics & Statistics ETDs

This dissertation explores the crucial role of data-driven modeling in science and engineering, with a focus on developing surrogate models to accelerate large-scale computational tasks, aiding in both outer-loop functions like uncertainty quantification and expensive inner-loop tasks within broader computational frameworks. Challenges arise with increased problem dimension and sparse, noisy training data, particularly significant when constructing surrogates for very expensive computational models where acquiring sufficient high-fidelity training data is unfeasible. In such scenarios, training surrogates from an ensemble of multifidelity information sources of varying accuracy and cost becomes essential. We emphasize neural network-based modeling paradigms, which are flexible in integrating …

Non-Traumatic Osteonecrosis Of The Femoral Head Induced By Steroid And Alcohol Exposure Is Associated With Intestinal Flora Alterations And Metabolomic Profiles, Qing-Yuan Zheng, Ye Tao, Lei Geng, Peng Ren, Ming Ni, Guo-Qiang Zhang

Faculty, Staff and Student Publications

OBJECTIVE: Osteonecrosis of the femoral head (ONFH) is a severe disease that primarily affects the middle-aged population, imposing a significant economic and social burden. Recent research has linked the progression of non-traumatic osteonecrosis of the femoral head (NONFH) to the composition of the gut microbiota. Steroids and alcohol are considered major contributing factors. However, the relationship between NONFH caused by two etiologies and the microbiota remains unclear. In this study, we examined the gut microbiota and fecal metabolic phenotypes of two groups of patients, and analyzed potential differences in the pathogenic mechanisms from both the microbial and metabolic perspectives.

METHODS: …

Genomic Population Structure Of Great Hammerhead Sharks (Sphyrna Mokarran) Across The Indo-Pacific, Naomi L. Brunjes, Samuel M. Williams, Alexis L. Levengood, Matt K. Broadhurst, Vincent Raoult, Alastair V. Harry, Matias Braccini, Madeline E. Green, Julia L. Y. Spaet, Michael J. Travers, Bonnie J. Holmes

Fisheries Research Articles

Context

Currently, little information exists describing the population structure of great hammerhead sharks (Sphyrna mokarran) in Australian waters. Aims

This study used single nucleotide polymorphisms to investigate fine-scale population structure in S. mokarran across the Indo-Pacific. Methods

DNA was extracted from 235 individuals across six Australian locations and a Red Sea outgroup. Population parameters were calculated and visualised to test structuring across locations. Key results

No fine-scale population structuring was observed for S. mokarran across the Indo-Pacific. However, population structuring occurred for all Australian locations when compared to the Red Sea outgroup. Conclusions

Findings suggest a single stock …

Cloud Solutions For Clinical Trial Data Analysis, Kelli Nelson

Student Research Symposium

In clinical trials, how can we determine whether "rare but serious side effects" are results of the treatment or just random?

Meta-Analysis: Understanding The Effects Of Assumption Violations, Wyatt Williams

Student Research Symposium

Overview

• Clouds Scenario
• Why Meta-Analysis Matters
• What Assumptions are Being Violated
• Our Current Research
• Conclusion

Gender Detection In Facial Images: A Comprehensive Cnn Analysis, Jose N T Ambrosio, Anas Hourani, Magdalene Moy

SACAD: Scholarly Activities

This research investigates the construction of a robust gender detection system using facial features and Convolutional Neural Networks (CNNs), exploring the impact of different layer configurations on accuracy and computational efficiency. With a validation accuracy of 91%, findings illuminate the nuanced relationship between precision and computational resources, enriching discussions on facial recognition technologies.

Optimizing Nba Roster Construction, Nick R. Riccardi

Sport Management - All Scholarship

This study aims to quantify the effect that complementary player types have on team success in the National Basketball Association. Using cluster analysis, player-seasons are redefined from their traditional basketball positions to better encompass the roles that players play. For the 10 seasons of data, the best player for each of the 30 teams in the league is determined and teams are grouped based on the cluster of their best player. Ordinary Least Squares regressions are performed to test what player types fit together best. The results of this study show the importance of complementary workers to a firm’s success.

Artificial Intelligence Could Probably Write This Essay Better Than Me, Claire Martino

Augustana Center for the Study of Ethics Essay Contest

No abstract provided.

Nanocavity-Mediated Purcell Enhancement Of Er In Tio2 Thin Films Grown Via Atomic Layer Deposition, Cheng Ji, Michael T Solomon, Gregory D Grant, Koichi Tanaka, Muchuan Hua, Jianguo Wen, Sagar Kumar Seth, Connor P Horn, Ignas Masiulionis, Manish Kumar Singh, Sean E Sullivan, F Joseph Heremans, David D Awschalom, Supratik Guha, Alan M Dibos

Faculty, Staff and Student Publications

The use of trivalent erbium (Er3+), typically embedded as an atomic defect in the solid-state, has widespread adoption as a dopant in telecommunication devices and shows promise as a spin-based quantum memory for quantum communication. In particular, its natural telecom C-band optical transition and spin-photon interface make it an ideal candidate for integration into existing optical fiber networks without the need for quantum frequency conversion. However, successful scaling requires a host material with few intrinsic nuclear spins, compatibility with semiconductor foundry processes, and straightforward integration with silicon photonics. Here, we present Er-doped titanium dioxide (TiO2) thin film growth on silicon …

The Social And Economic Dimensions Of One Of The World’S Longest-Operating Shark Fisheries, Matias Braccini, Maddison Watt, Clinton Syers, Nick Blay, Matthew Navarro, Michael Burton

Fisheries Research Articles

Context

Social and economic information is limited for coastal commercial and recreational fisheries, particularly shark fisheries, which are perceived as unsustainable and as targeting sharks for fins.

Aims

To characterise the social and economic dimensions of one of the world’s few long-standing sustainable shark fisheries.

Methods

We reviewed historic data and surveyed stakeholders to understand the economic and social dimensions of the shark fishery currently operating in Western Australia.

Key results

Since the fishery’s historic peak, there has been a substantial reduction in the number of operating vessels and ports due to management intervention. For the vessels that have remained, …

Localized Collocation Meshless Method For Modeling Transdermal Pharmacokinetics In Multiphase Skin Structures, Eduardo Divo

Math Department Colloquium Series

The human skin has a complicated structure with many multi-scale, biophysical effects impacting the propagation of skin-injected substances, such as partitioning, metabolic reactions, adsorption and elimination. An extended version of Fick’s second law governing the process of the compound diffusion in various skin layer is employed in the current work by considering the conservation of mass of the substance and the metabolic reaction of the substance in viable skin. Additionally, a model assuming linear coupling between the substance concentrations that are bound and unbound with blood was developed. Using such a model, a set of coupled partial differential equations are …

Leveraging Explainable Artificial Intelligence To Optimize Clinical Decision Support, Siru Liu, Allison B Mccoy, Josh F Peterson, Thomas A Lasko, Dean F Sittig, Scott D Nelson, Jennifer Andrews, Lorraine Patterson, Cheryl M Cobb, David Mulherin, Colleen T Morton, Adam Wright

Faculty, Staff and Student Publications

OBJECTIVE: To develop and evaluate a data-driven process to generate suggestions for improving alert criteria using explainable artificial intelligence (XAI) approaches.

METHODS: We extracted data on alerts generated from January 1, 2019 to December 31, 2020, at Vanderbilt University Medical Center. We developed machine learning models to predict user responses to alerts. We applied XAI techniques to generate global explanations and local explanations. We evaluated the generated suggestions by comparing with alert's historical change logs and stakeholder interviews. Suggestions that either matched (or partially matched) changes already made to the alert or were considered clinically correct were classified as helpful. …

Uncertainty Analysis In Machine Learning Models, Ayorinde E. Olatunde, Weiqi Yue, Pawan K. Tripathi, Roger H. French, Anirban Mondal

Faculty Scholarship

No abstract provided.

Health And Healthcare: Designing For The Social Determinants Of Health And Blue Zones In North Nashville, Rebecca Tonguis, Honor Thomas, Olivia Hobbs

[Archive] Belmont University Research Symposium (BURS)

Owned by North Nashville’s First Community Church, a now empty site in the Osage-North Fisk neighborhood of North Nashville has been identified as a potential site for a new location of The Store, in addition to a community-centric architectural development based on the social determinants of health and informed by the principles behind Blue Zones, the locations with the highest lifespans in the world. Opened by Brad Paisley and Kimberly Williams-Paisley, The Store is a free grocery store that “allow[s] people to shop for their basic needs in a way that protects dignity and fosters hope”, for which North Nashville …

Demographic Data Analysis For Measuring Economic Impact Of The Branch Of Nashville, Tessa Pendleton, Annie Wardroup, Nicole Speyrer, Kimberly Amaya Hernandez

[Archive] Belmont University Research Symposium (BURS)

As part of the Global Honors Scholars Collaborative, researchers aggregated data from The Belmont Data Collaborative to analyze the three primary ZIP codes (37211, 37013, 37217) served by The Branch of Nashville. These communities include immigrant and refugee populations, whom The Branch supports through its food bank, English classes, and further comprehensive care. Future program development will rely on the analysis of the current client base and eventual assessment of The Branch’s economic impact on the surrounding community. The goal of this research for The Branch of Nashville is twofold: (1) analyze the existing demographics within the above ZIP codes …

Exploring Lstm-Based Attention Mechanisms With Pso And Grid Search Under Different Normalization Techniques For Energy Demands Time Series Forecasting, Andri Pranolo, Xiaofeng Zhou, Yingchi Mao, Bambang Widi Pratolo, Aji Prasetya Wibawa, Agung Bella Putra Utama, Abdoul Fatakhou Ba, Abdullahi Uwaisu Muhammad

Knowledge Engineering and Data Science

Advanced analytical approaches are required to accurately forecast the energy sector's rising complexity and volume of time series data. This research aims to forecast the energy demand utilising sophisticated Long Short-Term Memory (LSTM) configurations with Attention mechanisms (Att), Grid search, and Particle Swarm Optimization (PSO). In addition, the study also examines the influence of Min-Max and Z-Score normalization approaches in the preprocessing stage on the accuracy performances of the baselines and the proposed models. PSO and Grid Search techniques are used to select the best hyperparameters for LSTM models, while the attention mechanism selects the important input for the LSTM. …

Hybrid Method For User Review Sentiment Categorization In Chatgpt Application Using N-Gram And Word2vec Features, Husna Luthfiatun Nisa, Atina Ahdika

Knowledge Engineering and Data Science

The rapid development of Artificial Intelligence (AI) has significantly influenced nearly all aspects of life. One AI product widely used by people worldwide is the Chat Generative Pre-Training Transformer (ChatGPT), which can respond to questions conversationally. Although data indicates that the use of ChatGPT in Indonesia is less widespread than in other countries, a Populix survey reveals that half of the respondents have utilized ChatGPT, using AI more than once a month. This indicates its crucial role among the Indonesian population. ChatGPT is not limited to browsers; it is also available as a downloadable application on the Google Play Store. …

Convolutional Neural Network In Motion Detection For Physiotherapy Exercise Movement, Dika Fikri Laistulloh, Anik Nur Handayani, Rosa Andrie Asmara, Phillip Taw

Knowledge Engineering and Data Science

Physiotherapy focuses on movement and optimal utilization of the patient's potential. Exercise Therapy is a physiotherapy procedure that specifically focuses exercises on active and passive movements. Cerebral Palsy (CP) patients are one of the sufferers of motor disorders of the upper extremities. Cerebral Palsy (CP) patients suffer from disorders in motor functions of the upper extremities. Physiotherapy Exercise Movement has 4 categories of movement exercises for the therapy of people with upper extremity body disorders: Elbow flexor strengthening in sitting using free weights, lifting an object up, reaching diagonally in sitting, and reaching from a low surface to a high …