Digital Commons Network^™

Moral Responsibility And Other Visceral Attitudes Of Western Michigan University Students Toward Food Waste, Quinn Heiser

Masters Theses

Despite the large number of people that go hungry on a regular basis in America, food waste remains a looming issue, globally and nationally. Both American college students and the universities themselves contribute a large portion to the national food waste totals. A dichotomy that is especially curious is the difference between students who live on-campus and whose main source of meals is the dining centers, versus students who live off campus and rely mainly on groceries to make meals independently. However, food waste has seldom been studied in the context of the fact that college is a major transition …

Digital Transformation: Two Sides Of A Coin, Tze K Koh

Research Collection College of Integrative Studies

It is of paramount importance to examine the intersection of digital transformation and sustainability. At the same time, there is a growing imbalance between digitalisation within the workforce and the pace at which sustainability awareness is picking up. Addressing this gap is crucial.

Network-Based Representations And Dynamic Discrete Choice Models For Multiple Discrete Choice Analysis, Huy Hung Tran, Tien Mai

Research Collection School Of Computing and Information Systems

In many choice modeling applications, consumer demand is frequently characterized as multiple discrete, which means that consumer choose multiple items simultaneously. The analysis and prediction of consumer behavior in multiple discrete choice situations pose several challenges. In this paper, to address this, we propose a random utility maximization (RUM) based model that considers each subset of choice alternatives as a composite alternative, where individuals choose a subset according to the RUM framework. While this approach offers a natural and intuitive modeling approach for multiple-choice analysis, the large number of subsets of choices in the formulation makes its estimation and application …

Let’S Think Outside The Box: Exploring Leap-Of-Thought In Large Language Models With Multimodal Humor Generation, Shanshan Zhong, Zhongzhan Huang, Shanghua Gao, Wushao Wen, Liang Lin, Marinka Zitnik, Pan Zhou

Research Collection School Of Computing and Information Systems

Chain-of-Thought (CoT) [2, 3] guides large language models (LLMs) to reason step-by-step, and can motivate their logical reasoning ability. While effective for logical tasks, CoT is not conducive to creative problem-solving which often requires out-of-box thoughts and is crucial for innovation advancements. In this paper, we explore the Leap-of-Thought (LoT) abilities within LLMs — a nonsequential, creative paradigm involving strong associations and knowledge leaps. To this end, we study LLMs on the popular Oogiri game which needs participants to have good creativity and strong associative thinking for responding unexpectedly and humorously to the given image, text, or both, and thus …

Me And Mathematics: “Doing What You’Re Talking About”: In Dialogue With My Family, Eden Morris

Dissertations, Theses, and Capstone Projects

This paper is a philosophically oriented accompaniment to my audio project (accessible through the following link: https://cuny.manifoldapp.org/projects/me-and-mathematics). Working together, the paper and audio collages form a call to action and a resource. My primary finding is the importance of doing what you’re talking about or exploring and implementing your ideas experientially. Doing what you’re talking about is important for effective teaching/learning and feeling in line with oneself. This working concept came to my attention during my research conversation with my oldest living relative, and then, again, with my youngest (non-baby) relative. This doing what you’re talking about is a way …

Cyberbullying Detection On Twitter Data Using Machine Learning Classifiers, Pradip Dhakal

Data Science and Data Mining

This study compares some of the popular machine learning techniques like Logistic Regression, Multinomial Naive Bayes, K-Nearest Neighbor, and Extreme Gradient Boosting to classify the tweets into three different categories: cyberbullying based on religion, cyberbullying based on ethnicity, or no cyberbullying. First, various data-cleaning approaches are used to clean the tweet data. After the data is clean and ready, the word embedding techniques, such as a bag of words and term frequency-Inverse document frequency, are used to convert the words into mathematical vectors. Finally, the model will be fitted using the combination of the above-mentioned word embedding techniques and machine …

Sensing With Integrity: Responsible Sensor Systems In An Era Of Ai, David Eisenberg

Dissertations

Deep and machine learning now offer immense benefits for consumer choice, decision-making, medicine, mental health and education, smart cities, and intelligent transportation and driver safety. However, as communication and Internet technology further advances, these benefits have the potential to be outweighed by compromises to privacy, personal freedom, consumer trust, and discrimination. While ethical consequences for personal freedom and equity rise from these technological advances, the issue may not be the technology itself but a lack of regulation and policy that allow abuses to occur. A first study examines how emerging sensor-based technologies, limited to only accelerometer and gyroscope data from …

A Comparisons Of The Covariate Types In Applications Of Semtree Model To Educational Studies, Minju Hong, Juyeon Lee

Counseling, Leadership, and Research Methods Faculty Publications and Presentations

In this study, we investigated the applicability of the SEMtree model to analyze the longitudinal data analysis in educational studies. SEMtree is one of the advanced approaches to incorporate the advantages of structural equation modeling and decision tree models under confirmatory and exploratory data analysis frameworks. The main purpose of this study is to figure out how the researcher deals with the data conditions of covariates when using the SEMtree model. By analyzing KCYPS 2018 the 4th-grade elementary school students' panel, we found that there were differences of the duplicated selected covariates when splitting the nodes in the SEMtree model …

A Qualitative Exploration Of Factors Associated With Covid-19 Vaccine Uptake And Hesitancy In Selected Rural Communities In Kenya, Fletcher J. Njororai, Walter Amulla, Caleb Kogutu Nyaranga, Wilberforce Cholo, Toluwani Adekunle

Health & Kinesiology Faculty Publications and Presentations

Purpose: The post-pandemic management of COVID-19 infections and any emergent outbreaks is because this endemic disease remains a public health concern. Vaccine hesitancy may continue to hamper efforts to respond to any new disease outbreaks and future epidemics. This qualitative study aimed to explore the factors influencing COVID-19 vaccine acceptance and hesitancy in Kenya to gain deeper insights into this issue. Methods: This study was implemented in western Kenya using key informant interviews. Fourteen (14) key informants were purposively selected for this study. All interviews were transcribed and analyzed using thematic analysis. The interpretation of findings was conducted within the …

Plas 439: Organic Farming And Food Systems Faculty-Led Inquiry Into Reflective Scholarly Teaching Benchmark Portfolio, Christian Stephenson

UNL Faculty Course Portfolios

Organic Farming and Food Systems is a senior and graduate level course for students in the Department of Agronomy and Horticulture. This course was previously offered but has been significantly modified as I have taken on responsibility for the course. Goals for the course include student comprehension of the methods of organic and regenerative farming and the impacts of those methods on economic, environmental, and social sustainability. An additional goal is to build student competency in the evaluation of primary, secondary, and tertiary information resources and critical thinking surrounding issues in food production. Assessment for the course was through diverse …

Risk Factors For Pediatric Ischemic Stroke And Intracranial Hemorrhage: A National Electronic Health Record Based Study, Sean Savitz, Alicia Zha, Hulin Wu

Faculty, Staff and Student Publications

BACKGROUND: Stroke is an important cause of morbidity in pediatrics. Large studies are needed to better understand the epidemiology, pathogenesis and risk factors associated with pediatric stroke. Large administrative datasets can provide information on risk factors in perinatal and childhood stroke at low cost. The aim of this hypothesis-generating study was to use a large administrative dataset to assess for prevalence and odds-ratios of rare exposures associated with pediatric stroke.

METHODS: The data for patients aged 0-18 with a diagnosis of either ischemic stroke or intracranial hemorrhage were extracted from the Cerner Health Facts EMR Database from 2000 to 2018. …

Unveiling The Metaverse: A Survey Of User Perceptions And The Impact Of Usability, Social Influence And Interoperability, Mousa Al-Kfairy, Ayham Alomari, Mahmood Al-Bashayreh, Omar Alfandi, Mohammad Tubishat

All Works

This review explores the Metaverse, focusing on user perceptions and emphasizing the critical aspects of usability, social influence, and interoperability within this emerging digital ecosystem. By integrating various academic perspectives, this analysis highlights the Metaverse's significant impact across various sectors, emphasizing its potential to reshape digital interaction paradigms. The investigation reveals usability as a cornerstone for user engagement, demonstrating how social dynamics profoundly influence user behaviors and choices within virtual environments. Furthermore, the study outlines interoperability as a paramount challenge, advocating for establishing unified protocols and technologies to facilitate seamless experiences across disparate Metaverse platforms. It advocates for the adoption …

Multi-Class Emotion Classification With Xgboost Model Using Wearable Eeg Headband Data, James Khamthung, Nibhrat Lohia, Seement Srivastava

SMU Data Science Review

Electroencephalography (EEG) or brainwave signals serve as a valuable source for discerning human activities, thoughts, and emotions. This study explores the efficacy of EXtreme Gradient Boosting (XGBoost) models in sentiment classification using EEG signals, specifically those captured by the MUSE EEG headband. The MUSE device, equipped with four EEG electrodes (TP9, AF7, AF8, TP10), offers a cost-effective alternative to traditional EEG setups, which often utilize over 60 channels in laboratory-grade settings. Leveraging a dataset from previous MUSE research (Bird, J. et al., 2019), emotional states (positive, neutral, and negative) were observed in a male and a female participant, each for …

Building Effective Large Language Model Agents, Sydney Holder, Shreyash Taywade

SMU Data Science Review

The advancement of large language models (LLMs) has significantly expanded the influence of artificial intelligence across various sectors. This paper explores building LLM agents to power applications and examines what is necessary to build an efficient and helpful AI assistant. The research investigates the core components necessary to create specialized agents, facilitate collaboration in problem-solving, and improve human task performance. The development and application of tools designed to augment the capabilities of LLM agents are also explored. The paper addresses the potential risks of the unknowns, such as hallucinations, which can compromise the success of agent-based solutions within LLM applications. …

Emotional Regulation On Modulating Associations Between Depression And Physical Activity As Characterized Via Deep Learning, Franklin Ye Ruan

Computer Science Senior Theses

Emotional regulation and physical activity are known to be associated with depression; however, a deeper understanding of how emotional regulation may strengthen or weaken the bonds between depressive symptoms and physical activity may aid clinicians and researchers in developing cognitive behavioral therapy (CBT) for those adversely affected by depression. As part of the Tracking Depression Study, this analysis uses data collected from 306 participants diagnosed with Major Depressive Disorder. To study their behavior, we analyze actigraphy data, or longitudinal physical activity intensity data, as it relates to depression severity, quantified by the daily PHQ-9 questionnaires. We study these associations through …

Crisis Management: Unveiling Information And Communication Technologies’ Revamped Role Through The Lens Of Sub-Saharan African Countries During Covid-19, Ruthbetha Kateule, Egidius Kamanyi, Mahadia Tunga

The African Journal of Information Systems

The management of COVID-19 pandemic has revealed inefficiencies in coordinating global response, particularly in African countries. Therefore, creating an urgent need to examine the literature on Information and Communication Technologies (ICT) in crisis management to appreciate its contextual role. Employing a systematic review, using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), this paper critically assessed the extent of the use of ICT in crisis management in Africa’s response to COVID-19 to reconstruct its resilience against future crises. Findings indicate that while countries with limited ICT infrastructure faced considerable challenges in utilizing ICT solutions in COVID-19 management, countries …

The Santa Clara, 2024-05-28, Santa Clara University

The Santa Clara

No abstract provided.

Advancing Objective Mobile Device Use Measurement Inchildren Ages 6–11 Through Built-In Device Sensors: A Proof-Of-Concept Study, Olivia L. Finnegan, Robert Glenn Weaver Med, Phd, Hongpeng Yang, James W. White, Srihari Nelakuditi, Zifei Zhong, Rahul Ghosal Ph.D., Yan Tong, Aliye B. Cepni, Elizabeth L. Adams, Sarah Burkart Mph, Ph.D., Michael W. Beets Med, Mph, Phd, Bridget Armstrong Ph.D.

Faculty Publications

Mobile devices (e.g., tablets and smartphones) have been rapidly integrated into the lives of children and have impacted howchildren engage with digital media. The portability of these devices allows for sporadic, on-demand interaction, reducing theaccuracy of self-report estimates of mobile device use. Passive sensing applications objectively monitor time spent on a givendevice but are unable to identify who is using the device, a significant limitation in child screen time research. Behavioralbiometric authentication, using embedded mobile device sensors to continuously authenticate users, could be applied toaddress this limitation. This study examined the preliminary accuracy of machine learning models trained on iPad …

Examining Differences In Concept Representation Across Similarity Spaces Between Humans And Large Language Models, Krishnachandra Nair

Computer Science Senior Theses

The replication of human concept representation is a critical task for the pursuit of artificial general intelligence. With the recent influx of large language models that demonstrate text-generation capabilities nearly on par with humans, the question stands on whether these large language models can capture concepts within language. We examine this question by exploring differences in concept representation across similarity spaces between humans and LLMs. We find that, while concept representation within LLMs does partially mimic human concept representation, LLMs are greatly limited by their dependence on semantic information and cannot therefore develop an understanding of human social code or …

Ripl: Recursive Inference For Policy Learning, Kunal Jha, Jeremy R. Manning, Alberto Quattrini Li

Computer Science Senior Theses

Humans excel at understanding the thoughts and intentions of others (theory of mind) and leverage this ability to learn and adapt in social environments. However, replicating this capability in artificial agents remains a challenge. This paper explores the gap between fast, efficient learning often achieved by Reinforcement Learning (RL) algorithms and the interpretability and adaptability desired in agents interacting with humans. We propose a novel approach that integrates an inference network within existing RL frameworks. This allows agents to reason about the beliefs of others (nested reasoning) while learning optimal actions. Our method leverages approximate solutions to the I-POMDP framework, …

Entertainment-Education And Climate Change: Program Examples, Evidence, And Best Practices From Around The World, Suruchi Sood, Amy Henderson Riley, Lyena Birkenstock

College of Population Health Faculty Papers

Entertainment-education is a global theory-driven and evidence-based storytelling strategy that promotes social and behavioral change. A formal review of the peer-reviewed and grey literature, alongside consultations with program and industry experts, revealed several contemporary examples of entertainment-education and climate change. Late-night comedy, with the inclusion of climate change storylines within popular entertainment, is common in the Global North. In the Global South, climate adaptation and mitigation narratives are situated in formats portraying audiences’ lived experiences. Crosscutting trends relate to documentary storytelling, children’s programming, and future efforts. Recommendations include re-examining theories across the social-ecological model; placing entertainment front and center; including …

Du Undergraduate Showcase Abstracts: Research, Scholarship, And Creative Works, August Alexander, Kevin Summers, E. Paige Lloyd, Alyssa Aragon, Lauren Wols, Erica Larson, Colton Arciniaga, Lily Baeza, Ellie Barnett-Cashman, Sidney Barbier, Maverick Bartholomew, Ryan Bell, Trevor Briggs, Amanda Brown, Cory Marchi, Maddy Pontius, Jennifer Gallagher, Claire Kwok, Channing Bullock, Alex Mccollister, Kim Gorgens, Daniela Chavez, Yamilet Espinoza Nuñez, Giovanni Valladares Giron, William Christensen, Olivia Kachulis, Daniel Cierasynski, Brandon Cohen, Spenser Dobbs, Lindsay Goolsby, Noah Craver, Nyah Cubbison, Liam Doherty, Nicole Doris, Yan Qin, Alexander Nguyen, Lily Harmon, Shubh Todi, Naichen Zhao, Noah Fagello, Stacia Fritz, Paola Gascot-Chinea, Alex Volkova, Janelyn Geronimo, Elsie Harrington, Shane Simmons, Clarice Hise, Laura Moreno Palmer, Henry Xu, Yesu Leela Pasupula, Emily Fisher, Zachary Hogan, Colin Kleckner, Alyssa Knaus, Erin Kubat, Sam Werkema, Katie Lamberton, Lilliya Larson, Allie Leary, Vanessa Leon-Gamez, James H. Gallagher, E. Dale Broder, Robin M. Tinghitella, Emma Loeber, Alina Mali, Ixchel Marquez, Lauren Mcgrath, Ella Matthews, Grace Naegelen, Audrey Ng, Megan Lucyshyn, Rachel Brough, Alexandra Norman, Joe Ontiveros Rodriguez, Ben Dossett, Ori Miller, Janamejay Sharma, Christopher Reardon, Vincent Pandey, Regan Parish, Ren Pratt, Alisha Pravasi, Sanchari Das, Cari Reichel, Emma Robson, Victoria Rockwell, Jayce Rumsey, Steven Said, Norah Schroder, Alaina Smith, Shannon Murphy, Shujan A. Sharafeldeen, Stanley M. Kanai, James T. Nichols, David E. Clouthier, Macalia R. Augustus, Daniel Silva Rios, Scott Simpson, Anna Sparling, Chase Spurbeck, Kimberly Chiew, Christine Stadnik-Poteroba, Jacqueline Stephenson, Evelyn Stovin, Mia Supan, Lauren Tapper, Will Thrush, Anna Vogt, Michaela Walheim, Jon Weber, Hunter Whitehouse, Kansas Wood, Hayley Sayre, Lydia Mccann, Maread Mclaughlin, Kelly Krumrie, Olivia Wuttke

DU Undergraduate Research Journal Archive

Abstracts from the DU Undergraduate Research Showcase.

A Systems Theoretic View Of Speculative Realism, Martin Zwick

Complex Systems Faculty Publications and Presentations

Recent developments in Continental philosophy have included the emergence of a school of “speculative realism,” which rejects the human-centered orientation that has long dominated Continental thought. Proponents of speculative realism differ on several issues, but many agree on the need for an object-oriented ontology. Some speculative realists identify realism with materialism, while others accord equal reality to objects that are non-material, even fictional. Several thinkers retain a focus on difference, a well-established theme in Continental thought. This paper looks at speculative realism from the perspective of systems theory. Many of the tenets of speculative realism have long been features of …

Queering Futures With Data-Driven Speculation: The Design Of An Expanded Mixed Methods Research Framework Integrating Quantitative, Qualitative, And Practice-Based Modes, Jess Parris Westbrook

College of Education Theses and Dissertations

Queering’ questions, unlearns, disrupts, and transforms approaches, expectations, and realities. Futures are time and change. The approach I have designed to operationalize Queering and futures, or Queering futures, is the Queering Futures Framework (QFF). The Queering Futures Framework (QFF) is a brand-new transdisciplinary research framework intersecting values, positionality, complexity, Queerness themes, and futures praxis. This framework expands traditional mixed methods research conventions by integrating quantitative, qualitative, and practice-based research modes and mindsets. The Queering Futures Framework (QFF) prototype presented in this dissertation functions as a test case and proof of concept. The prototype quantitative mode measures attitudes towards AI, and …

Context Aware Music Recommendation And Playlist Generation, Elias Mann

SMU Journal of Undergraduate Research

There are many reasons people listen to music, and the type of music is largely determined by what the listener may be doing while they listen. For example, one may listen to one type of music while commuting, another while exercising, and yet another while relaxing. Without access to the physiological state of the user, current music recommendation methods rely on collaborative filtering - recommending music based on what other similar users listen to - and content based filtering - recommending songs based on their similarities to songs the user already prefers. With the rise in popularity of smart devices …

A Computational Investigation Of Wood Selection For Acoustic Guitar, Jonah Osterhus

Senior Honors Theses

The acoustic guitar is a stringed instrument, often made of wood, that transduces vibrational energy of steel strings into coupled vibrations of the wood and acoustic pressure waves in the air. Variations in wood selection and instrument geometry have been shown to affect the timbre of the acoustic guitar. Computational methods were utilized to investigate the impact of material properties on acoustic performance. Sitka spruce was deemed the most suitable wood for guitar soundboards due to its acoustic characteristics, strength, and uniform aesthetic. Mahogany was deemed to be the best wood for the back and sides of the guitar body …

The Hodgkin-Huxley Model For Neuron Action Potentials: A Computational Study, Uditi Chandrashekhar

Macalester Journal of Physics and Astronomy

Neurons are the fundamental units of the nervous system that receive stimuli as signals and pass on this information to other cells in different parts of the body. An action potential refers to the transmission of the electrical nerve impulse along the neuron. In their seminal work published in 1952, Alan L. Hodgkin and Andrew Huxley proposed a mathematical model of neuronal membrane action potentials based on a series of experiments they conducted using the giant squid neuron. This thesis is a study of the nature of the action potential used to transfer signals along the neuron based on the …

Operation Shark: Addressing The Negative Portrayal Of Sharks In Media, Michael R. O'Shea

Masters Theses

Sharks are some of the most well adapted and effective animals in the animal kingdom. Unfortunately, they are also some of the most feared. For many people the word shark evokes images of vicious attacks like those seen in movies such as Jaws. Sharks have also been negatively portrayed in the media. This negative portrayal of sharks has led to misconceptions about sharks that have damaged their populations. Efforts have been made to raise awareness and fight common misconceptions of sharks. However, many people still hold on to the incorrect ideas they have about sharks. This thesis will examine the …

Security Fusion Method Of Physical Fitness Training Data Based On The Internet Of Things, Bin Zhou

Turkish Journal of Electrical Engineering and Computer Sciences

Physical fitness training, an important way to improve physical fitness, is the basic guarantee for forming combat effectiveness. At present, the evaluation types of physical fitness training are mostly conducted manually. It has problems such as low efficiency, high consumption of human and material resources, and subjective factors affecting the evaluation results. ”Internet+” has greatly expanded the traditional network from the perspective of technological convergence and network coverage objects. It has expedited and promoted the rapid development of Internet of Things (IoT) technology and its applications. The IoT with many sensor nodes shows the characteristics of acquisition information redundancy, node …

Deep Learning-Based Breast Cancer Diagnosis With Multiview Of Mammography Screening To Reduce False Positive Recall Rate, Meryem Altın Karagöz, Özkan Ufuk Nalbantoğlu, Derviş Karaboğa, Bahriye Akay, Alper Baştürk, Halil Ulutabanca, Serap Doğan, Damla Coşkun, Osman Demi̇r

Turkish Journal of Electrical Engineering and Computer Sciences

Breast cancer is the most prevalent and crucial cancer type that should be diagnosed early to reduce mortality. Therefore, mammography is essential for early diagnosis owing to high-resolution imaging and appropriate visualization. However, the major problem of mammography screening is the high false positive recall rate for breast cancer diagnosis. High false positive recall rates psychologically affect patients, leading to anxiety, depression, and stress. Moreover, false positive recalls increase costs and create an unnecessary expert workload. Thus, this study proposes a deep learning based breast cancer diagnosis model to reduce false positive and false negative rates. The proposed model has …