Digital Commons Network^™

Populations Digitally Excluded From Education: Issues, Factors, Contributions And Actions For Policy, Practice And Research In A Post-Pandemic Era, Don Passey, Jean Gabin Ntebutse, Manal Yazbak Abu Ahmad, Janet Cochrane, Simon Collin, Asmaa Ganayem, Elizabeth Langran, Sadaqat Mulla, Ma. Mercedes T. Rodrigo, Toshinori Saito, Miri Shonfeld, Saunand Somasi

Department of Information Systems & Computer Science Faculty Publications

This conceptual paper draws on a wide range of research and policy literature, providing a contemporary view of issues, factors and practices that affect education for digitally excluded populations. Concern for how education for digitally excluded populations can be supported is focal to this paper, with different sections offering key related perspectives. From an analysis of issues, factors and practices, actions for policy, practice and research are identified. Given a key finding that power issues can have major effects on plans, implementation processes and outcomes when addressing needs of education for digitally excluded populations, the paper concludes by offering frameworks …

Modelling Tinnitus Functional Index Reduction Using Supervised Machine Learning Algorithms, Edmund F. Agyemang

School of Mathematical & Statistical Sciences Faculty Publications

This study aims to model the reduction in the Tinnitus Functional Index (TFI) utilizing supervised machine learning algorithms, focusing primarily on Ordinary Least Squares (OLS), K-Nearest Neighbor (KNN), Ridge, and Lasso regressions. Our analysis highlighted Group, ISI, and SWLS as significant predictors of TFI reduction, identified through the best subset selection and confirmed by both forward and backward selection criteria in the OLS regression. Notably, the shrinkage methods, Ridge and Lasso regressions, demonstrated superior performance compared to OLS and KNN, with the Ridge regression presenting the smallest test mean square error (MSE) of 318.30. This finding establishes the Ridge regression …

The Significance Of Continuous User Authentication On Mobile Devices, Mikayla Lawrence

Electronic Theses, Projects, and Dissertations

With the constant evolution of technology specifically on mobile devices, keeping personal and sensitive information safe has become increasingly vital. Continuous user authentication marks a major step forward in mobile security because it provides ongoing verification of user identity beyond the initial log in. This research explores the significance of continuous user authentication systems across mobile devices through literature-based analysis. The following research questions are addressed: (Q1) How effective are continuous user authentication methods in mitigating mobile device threats? (Q2) What are the vulnerabilities associated with continuous user authentication systems on mobile devices? (Q3) How do different continuous user authentication …

Shifting Perspectives With Procedural Modeling Techniques And Vertex Animated Textures For Real-Time Interactive Morphing, Stephanie Schulze

All Theses

As humans experience reality, they intake external stimuli using sensory receptors to process information, forming a perception. Perceptions are subjective and shape each individual’s reality. Naturally then, by changing one’s perceptions, their experience of reality is altered, for better or worse. To emphasize the idea that perception is malleable and encourage a mindset of questioning alternative ways to look at a situation, an interactive experience in Unreal Engine is developed where a dull cityscape morphs and transforms into a surreal oversized nature scene. Procedural modeling techniques are used to create a variety of morphing assets, while Vertex Animated Textures are …

Thermal Inequity Along The Us-Mexico Border: An Analysis Of El Paso, Texas, Mia Alexandra Trevino

Open Access Theses & Dissertations

The Urban Heat Island effect (UHI) combined with rising average global temperatures invariably results in thermal inequality, the unequal distribution of temperature patterns by different socioeconomic and sociodemographic groups, resulting in an array of negative public health impacts. This thesis research focused on the historical factors that contribute to UHI and tree cover in historically underserved neighborhoods in El Paso, Texas. The impact of maps from 1933-1954 created by the Home Ownerâ??s Loan Corporation (HOLC), a federal selective lending program, resulted in decades of disinvestment and inequality especially in redlined areas. Geospatial analyses of environmental and socioeconomic indicators such as …

Functionalized Carbon Quantum Dots: A Promising Nanomaterial For Investigating Their Potential In Neurodegenerative Disease Treatment, Sherin M. El Morsy

Open Access Theses & Dissertations

Neurodegenerative diseases such as Parkinson's Disease (PD), Alzheimer's Disease (AD), and Huntington's Disease (HD) remain incurable, despite extensive research into therapeutic development. In the United States of America, the annual cost of PD and AD in terms of patient care and lost productivity is approximately $200 billion. Consequently, there is a critical and unaddressed need for the development of innovative drugs and drug delivery systems that can decelerate, stop, or ideally reverse neurodegenerative diseases. The dissertation presented here focuses on devising strategies to target PD through multiple mechanisms, including the inhibition of protein aggregation and the reduction of oxidative stress. …

Equitable Community-Based Participatory Research Engagement With Communities Of Color Drives All Of Us Wisconsin Genomic Research Priorities, Sheikh Iqbal Ahamed, Praveen Madiraju

Computer Science Faculty Research and Publications

Objective

The NIH All of Us Research Program aims to advance personalized medicine by not only linking patient records, surveys, and genomic data but also engaging with participants, particularly from groups traditionally underrepresented in biomedical research (UBR). This study details how the dialogue between scientists and community members, including many from communities of color, shaped local research priorities.

Materials and Methods

We recruited area quantitative, basic, and clinical scientists as well as community members from our Community and Participant Advisory Boards with a predetermined interest in All of Us research as members of a Special Interest Group (SIG). An expert …

Artificial Intelligence And Machine Learning In Cancer Pain: A Systematic Review, Vivian Salama, Brandon Godinich, Yimin Geng, Laia Humbert-Vidan, Laura Maule, Kareem A Wahid, Mohamed A Naser, Renjie He, Abdallah S R Mohamed, Clifton D Fuller, Amy C Moreno

Faculty, Staff and Student Publications

Background/objectives: Pain is a challenging multifaceted symptom reported by most cancer patients. This systematic review aims to explore applications of artificial intelligence/machine learning (AI/ML) in predicting pain-related outcomes and pain management in cancer.

Methods: A comprehensive search of Ovid MEDLINE, EMBASE and Web of Science databases was conducted using terms: "Cancer," "Pain," "Pain Management," "Analgesics," "Artificial Intelligence," "Machine Learning," and "Neural Networks" published up to September 7, 2023. AI/ML models, their validation and performance were summarized. Quality assessment was conducted using PROBAST risk-of-bias andadherence to TRIPOD guidelines.

Results: Forty four studies from 2006 to 2023 were included. Nineteen studies used …

Issue 41

The Synapse: Intercollegiate science magazine

No abstract provided.

The Care Crisis: The Neurology Of Dementia And International Solutions, Sophie Paton

The Synapse: Intercollegiate science magazine

No abstract provided.

On A Color Wheel: Adhd Under The Social Model's Scope, Ben Tran

The Synapse: Intercollegiate science magazine

No abstract provided.

Wired For Love: The Neuroscience Behind Romantic Attraction, Jacqueline Rogers

The Synapse: Intercollegiate science magazine

No abstract provided.

Correlation And Causation Analysis For Cross-Sectional And Panel Data, Barry Nuqoba

Dissertations and Theses Collection (Open Access)

This dissertation investigates how data, algorithms, and expert knowledge can be harnessed to better understand human behavior and enhance well-being. It emphasizes the critical importance of interdisciplinary collaboration to bridge knowledge gaps and foster insights that support preventive care, causal theory advancement, and policy development.

The first study, part of the SHINESeniors project, shed light on the potential usefulness of passive, unobtrusive sensors for detecting nocturia and poor sleep quality, symptoms commonly observed in chronic diseases, thereby enabling live-alone older adults to age in place. Utilizing machine learning techniques on sensor-derived features, the study can identify nocturia and poor sleep …

United We Stand, Divided We Fall: An Autogenic Perspective On Empowering Cybersecurity In Organizations, Alexandra Durcikova, Shayla M. Miranda, Matthew L. Jensen, Ryan T. Wright

Information Systems Faculty Publications and Presentations

Cybersecurity groups navigate complex, challenging environments in their mission to protect their organizations. They experience uncertainty from adaptive threats from external attackers and unpredictable stakeholders. Under such volatility, business groups operate best when they are psychologically empowered. Recognizing the potential for empowerment to reduce organizational risk, we sought to learn how cybersecurity groups come to be (dis)empowered and how this (dis)empowerment is sustained. Instead of the conventional view of the empowerment process as designed, we advance an emergent view of the empowerment process. We abductively surface this process from our case analyses of 15 U.S. organizations. We offer three insights: …

Prevalence Of Autism Spectrum Characteristics In Students Taking Undergraduate Computing Courses, Rachel Michaela Mettenbrink

School of Computing: Dissertations, Theses, and Student Research

The incidence rate of autism spectrum condition (ASC) has increased significantly in recent decades, as awareness of the condition and its impacts increases amongst clinicians, parents, and the general population. Medical literature has proposed that there may be a relationship between ASC and participation in the computing field. This study tests for the prevalence of autism spectrum condition traits measured by delivering the Autism Spectrum Quotient (AQ) to a population of undergraduate computer science students. We examine the relationships between AQ scores and students taking undergraduate computer science classes, sex, socioeconomic status, and parents in the computing industry. Additionally, we …

Understanding And Influencing Public Concerns About Prescribed Fire Use In Utah, Brooke Richards

All Graduate Theses and Dissertations, Fall 2023 to Present

Prescribed fire is beneficial for improving forest health and reducing wildfire risk, which is especially important for residents who live near forested areas. To expand the use of prescribed fire, Utah land managers must first ensure there is public support. Therefore, better understanding public concerns and what shapes their beliefs about prescribed fire can help managers improve outreach and education methods. Through interviews with south-central Utah land managers, private landowners, and Health departments employees, a focus group discussion with Park City natural resource managers, and observation of Summit County public commentary, two outreach messages were suggested to address the five …

Classification Of Anxiety Levels Entering The World Of Work In Final Year Students Using The Neighbor Weighted K-Nearest Neighbor Method, Awang Hendrianto Pratomo, Muhammad Fahmi Adam, Dessyanto Boedi Prasetyo

Knowledge Engineering and Data Science

This study evaluates the accuracy of the Neighbor Weighted K-Nearest Neighbor (NWKNN) method in classifying the anxiety levels of final-year students as they prepare to enter the workforce, particularly in cases of unbalanced data distribution. The system was developed using the prototype method, and NWKNN was applied to classify anxiety levels into low, medium, and high categories. Testing using the Confusion Matrix demonstrated strong performance, achieving an accuracy of 94% based on a dataset of 1009 students, with a 90:10 ratio of training to test data. The results indicate that NWKNN effectively provides classification input values, making it a reliable …

Reference Dependence In Queue Design And Pricing Strategies, Jian Liu, Yongpin Zhou, Jian Chen, Peng Li

Electrical and Computer Engineering Faculty Research & Creative Works

This research investigates the effect of reference dependence on waiting times in service systems which formerly used a first-in-first-out (FIFO) service but have introduced a priority line with a fee. Our model combines reference-dependent gain-loss utility with standard customer utility, and we posit that customers are pleased with shorter-than-expected waiting times, whereas longer-than-expected times lead to dissatisfaction and an increased likelihood of balking. The study explores two scenarios: a captive customer system (CCS) and a noncaptive customer system (NCCS), with a focus on optimal pricing and segmentation strategies for revenue and social welfare maximization. The results reveal that, in a …

Meta-Entrepreneurship: An Analysis Theory On Integrating Generative Ai, Agentic Ai, And Metaverse For Entrepreneurship, Yingying Zhang, Keng Siau

Research Collection School Of Computing and Information Systems

Metaverse entrepreneurship has emerged as an innovative topic alongside the development of generative AI, agentic AI and metaverse. This study conceptualizes meta-entrepreneurship as a novel form of entrepreneurial activity that enables value creation within virtual and physical realms and proposes an analytical theoretical framework based on a systematic literature review, observations, and focus group study. Our framework is structured around three layers (infrastructure, content, and experience) and two domains (metaverse-based operational domain and AI-based production domain), aims to conceptualize “what is meta-entrepreneurship” and identify new possibilities. The research highlights the multifaceted impact of meta-entrepreneurship on individuals, corporations, industries, societies, and …

Virtual Conferencing Fatigue: Look‑Alike Avatar And Facial Attractiveness, Yuxin Liu, Keng Siau, Xueqing Wang, Yang Yang

Research Collection School Of Computing and Information Systems

The rapid evolution of avatar-related technologies provides extensive opportunities for diverse avatar applications in various areas. This study aims to investigate the innovative use of avatars to mitigate virtual conferencing fatigue, which refers to the physical and mental exhaustion from the inappropriate use of virtual conferencing applications. Grounded in Self-Awareness Theory, the research compares the impact of using real faces and user-look-alike avatars on virtual conferencing fatigue, delving into its underlying factors. In addition, the study examines the role of facial attractiveness enhancement on virtual conferencing fatigue. Laboratory experiments with a 2-by-2 between-subject design are employed to test hypotheses. The …

Early Detection Of Risk Factor For Suicidal Ideation Among Senior High School Students In Jakarta: Updated Measurement, Nova R. Yusuf, Sabarinah Prasetyo, Byron J. Good

Kesmas

The key strategy to address suicide in adolescents is school-based suicidal prevention by adapting a screening instrument to the local culture and policymakers’ perception of suicide. This study aimed to develop an instrument for the early detection of risk for suicidal ideation and identify influential risk factors for suicidal ideation among high school students in Jakarta, Indonesia. This study was conducted in 2018 with a mixed-method design (quantitative and qualitative approaches). It was found that 5% of students had suicidal ideation in July–November 2018, and 13.8% had a high-risk factor for suicidal ideation. The instrument developed in this study consisted …

Habit Coach: Customising Rag-Based Chatbots To Support Behavior Change, Arian Fooroogh Mand Arabi, Cansu Koyuturk, Michael O'Mahony, Raffaella Calati, Dimitri Ognibene

Conference papers

This paper presents the iterative development of Habit Coach, a GPT-based chatbot designed to support users in habit change through personalized interaction. Employing a user-centered design approach, we developed the chatbot using a Retrieval-Augmented Generation (RAG) system, which enables behavior personalization without retraining the underlying language model (GPT-4). The system leverages document retrieval and specialized prompts to tailor interactions, drawing from Cognitive Behavioral Therapy (CBT) and narrative therapy techniques. A key challenge in the development process was the difficulty of translating declarative knowledge into effective interaction behaviors. In the initial phase, the chatbot was provided with declarative knowledge about CBT …

Heroic Virtues In Space Exploration: Everydayness And Supererogation On Earth And Beyond, John N. Nielsen

Heroism Science

The space environment poses significant dangers and difficulties for human explorers—difficulties so great that it has been argued that space exploration should be exclusively conducted by automated spacecraft. The possibility of space science conducted by human astronauts in spite of these dangers presents the opportunity for individuals to exhibit traditional heroic virtues—presumably, supererogatory forms of prudence, temperance, fortitude, and justice—in the pursuit of science. In particular, the difficulties of pursuing science in the hostile conditions of extraterrestrial environments will call for physical courage in the face of personal danger, patience with the painstaking procedures of technically difficult scientific experiments performed …

The Effects Of Personality Type On Decision Making, Meghan Cemke, Kya Cousino, Aubrey Kelly, Mckenna Prouty

Science University Research Symposium (SURS)

A person’s personality encompasses many aspects of their life including how they act and how they think. It is common for people to fail to recognize that their personality is at work, or even that it could have an effect on their cognitive decision-making. Particularly, moral decision-making and the effects of personality on their collectivist or individualist mindset. Previous research has shown that certain aspects of a person’s Big Five personality (openness, conscientiousness, extraversion, agreeableness, and neuroticism) have the ability to impact the way that people make decisions that benefit themselves or others (Saha, 2018). The goal of the current …

Developing Linguistic Patterns To Mitigate Inherent Human Bias In Offensive Language Detection, Toygar Tanyel, Besher Alkurdi, Serkan Ayvaz

Turkish Journal of Electrical Engineering and Computer Sciences

With the proliferation of social media, there has been a sharp increase in offensive content, particularly targeting vulnerable groups, exacerbating social problems such as hatred, racism, and sexism. Detecting offensive language use is crucial to prevent offensive language from being widely shared on social media. However, the accurate detection of irony, implication, and various forms of hate speech on social media remains a challenge. Natural language-based deep learning models require extensive training with large, comprehensive, and labeled datasets. Unfortunately, manually creating such datasets is both costly and error-prone. Additionally, the presence of human-bias in offensive language datasets is a major …

A Systematic Review Of The Effects Of Ai-Assisted Moderation On Individuals And Groups, Zehui Yu, Lukas Otto, Dennis Assenmacher, Claudia Wagner

Human-Machine Communication

This review paper provides a conceptualization of AI-assisted content moderation with various degrees of autonomy and summarizes experimental evidence for how different levels of automation in content moderation and related losses of autonomy affect individuals and groups. Our results show that current research predominantly focuses on individuallevel effects, necessitating a shift toward understanding the impact on groups. The study highlights gaps in exploring different levels of AI-assisted moderation interventions and misalignments of different conceptualizations that make comparing research results difficult. The discussion underscores the prevailing emphasis on harmful content removal and advocates for investigating more constructive moderation techniques, emphasizing the …

Relationship-Influenced Cyber Hygiene (Rich) In Community Banks, Monte L. Ward

USF Tampa Graduate Theses and Dissertations

This dissertation is a research study that introduces the theoretical model of Relationship-Influenced Cyber Hygiene (RICH) through its investigation of the phenomenon the researcher experienced: how the interpersonal relationship between top management and cybersecurity personnel within smaller community banks influences the cyber hygiene of top management. Due to the value proposition of community banks to their clients and the limited budget of smaller institutions for investment in cybersecurity controls and initiates, community banks need additional strategies to achieve stronger cyber hygiene, especially as it relates the greatest weakness in most cybersecurity infrastructures—the human element. This study identifies and addresses a …

Analysing Sound Characteristics Of Cello And Violin Using Fast Fourier Transform, Sinin Hamdan, Khairul Anwar Mohamad Said, Ahmad Faudzi Musib, Marini Sawawi, Aaliyawani Ezzerin Sinin

ASEAN Journal on Science and Technology for Development

The unique sound characteristics of music are based on multiple harmonic frequencies that exist within the sound waves. Through Fast Fourier Transform (FFT) software, the wave can be broken down into frequency and amplitude components. Spectrum analysis can be used quantitatively to describe these sound characteristics. In this paper, the frequency range present in the spectrum and the average intensity of the first 10 high notes in the sound are used to classify the sound characteristics of the cello and violin. This is done by generating a frequency (x-axis) and amplitude (y-axis) graph for the sounds of the cello and …

Evaluating Trauma-Informed Design In A Mental Health Setting: A Community-Based Research Case Study, Marie Spence

Electronic Theses and Dissertations

This case study utilized a community-based research framework to explore how the Trauma-Informed Design framework can be implemented in a mental health setting. This study focused on the site of Empower Therapy Practice, a private mental health practice in the Denver Metro Area, to engage clients and staff to participate in advisory boards and inform the interior design of a new office space. To explore the application of Trauma-Informed Design, participants engaged in a variety of research activities, including an evaluative questionnaire, Photovoice, and focus group. Advisory board members identified various aspects of Trauma-Informed Design which meaningfully translate to therapeutic …

Exploring Customer Behavior Through Emotion Detection, Darlington Omoifo

Master's Theses

This thesis investigates the potential of emotion detection, gaze tracking, and hand movement analysis as tools to enhance understanding of customer behavior in retail environments. In retail, subtle indicators such as facial expressions, gaze direction, and hand gestures provide valuable insights into customer preferences and decision-making processes. The study leverages real-time video processing with a multithreaded approach on a Raspberry Pi-powered system embedded in a gift cart equipped with dual cameras. Using FER for emotion detection and a custom model for gaze and hand tracking, this research identifies customer engagement patterns, focusing on how emotions like happiness correlate with purchasing …