Digital Commons Network^™

Web 3.0 Tools Employed In Private High School Library Media Centres In Zimbabwe: The Case Of Bulawayo Metropolitan Province, Elton Tafataona Moyo, Takawira Machimbidza

Library Philosophy and Practice (e-journal)

The study was carried out to gain insight into the Web 3.0 technologies used by high school library media specialists in private schools around Bulawayo Metropolitan Province in Zimbabwe. The study adopted the interpretivist paradigm with a qualitative approach and a multiple-case study research strategy. The population of this study comprised of school library media specialists from ten private high schools in Bulawayo Metropolitan Province. Semi-structured interviews were used to collect data. Data were analysed using content analysis. Findings reveal that school library media specialists use a cocktail of Web 3.0 tools which include WhatsApp, Google Classroom, Facebook, Zoom, wikis, …

A Framework For Scientific Data Indexing, Searching And Sharing, Apoorva Mohite

Master's Projects

Scientific data continues to grow. Wildfire simulation experiments performed by the WIRC team at SJSU have generated over 138 TB of data so far and it is expected to keep growing. It becomes difficult for researchers to search through that data to find the data of their interest. This data is stored on an HPC cluster that external users do not have access to. The WIRC team also conducts experiments and publishes their research, but the size of data makes it difficult to share these datasets. This project introduces a novel solution to indexing scientific data, searching through the data …

Credit Score-Based Lending System On The Ethereum Platform, Mayuri Shimpi

Master's Projects

Traditional banking systems act as intermediaries, assessing risks and profiting from interest rate differentials. Credit scores, provided by trusted bureaus, are commonly used to evaluate the creditworthiness of borrowers. Cryptocurrencies have emerged as a significant and innovative medium due to their decentralized nature, operating without reliance on a central authority, such as a government.

This report describes a project to implement the Autonomous Lending system on the Ethereum Platform (ALOE), as proposed in [1], aiming to seamlessly integrate traditional credit scoring methodologies for evaluating a borrower's risk of default. The objective of this project report is to establish a robust …

Ml-Based User Identification Through Mouse Dynamics, Rakshit Gupta

Master's Projects

User authentication and identification plays a crucial role in ensuring the security and integrity of digital systems. Traditional authentication methods, such as passwords and biometrics, have inherent limitations that can compromise system security. This research proposes a novel approach to user authentication by leveraging machine learning techniques and behavioral biometrics, specifically mouse dynamics. The primary objective is to develop a sophisticated framework that can accurately identify individuals based on their unique mouse behavior patterns. The study explores and compares multiple deep learning architectures, including Convolutional Neural Networks (CNN), Long Short-Term Memory networks (LSTM), and Transformer models, to generate embeddings from …

Analysis And Application Of Adaptive Ml Algorithms For Malware Classification, Rashmi Boddukuri

Master's Projects

Malware classification is the process of distinguishing malware samples into categories of malware families that it is associated with and remains a critical step in the process of mitigating malware-related threats. In recent years, machine learning techniques have emerged as a powerful tool for such malware classification tasks. In this study, we explore the application of adaptive machine learning models to malware classification in order to analyze and determine how they compare in performance to similar but non-adaptive algorithms. The results achieved in this study share insight into the strengths and limitations of adaptive learning models when applied towards malware …

Distinguishing Chatbot From Human, Gauri Anil Godghase

Master's Projects

There have been many recent advances in the field of Generative Artificial Intelligence and Large Language Models, with GPT 3 or ChatGPT model being one of the frontrunners in this field. These large language models have become so powerful that it has become difficult to differentiate between text written by humans and machine-generated text. This paper proposes a solution to the problem of classification of the origin of data (human or chatbot) by using Machine Learning. In addition, the proposed solution also helps us analyze the text generated by such Language Models and understand the underlying patterns present in the …

California Carbon Sequestration And Carbon Dioxide Pipeline Regulation In An Era Of Climate Change: Technology And Policy, Robert A. Mason

Master's Projects

This report serves primary purpose of finding prospective policies that could be useful in CARB’s new carbon sequestration program as mandated by S. B. 905. The bill states program goals and provides several objectives that direct the California Natural Resources Agency (CNRA), the California Air Resource Board (CARB), and the California Geological Survey (CGS, or just Survey) with various responsibilities. Curiously, S.B. 905 does not mention the Office of State Fire Marshal (OSFM or CalFire), although it has primary responsibility for issuing permits for hazardous pipelines as an agent of the federal Pipelines and Hazardous Materials Safety Administration (PHMSA).

Pipelines …

Adaptive Metric-Driven Load Balancing For Specialized Clusters Using Nginx, Juhi Raju Malkani

Master's Projects

Adaptive Metric-Driven Load Balancer is an innovative two-tier load-balancing system that uses NGINX and Prometheus to optimize resource allocation in specialized cloud clusters. This framework is built to give great performance and flexibility and runs on Google Kubernetes Engine (GKE), but it may also be deployed on local cloud environments for added security. The first tier of our system uses an NGINX-based load balancer to route incoming requests based on content type, sending traffic to hardware-optimized clusters for processing requests through specialized hardware. In our algorithm, the second tier dynamically modifies load distribution throughout each cluster by calculating pod weights …

Embracing Mindfulness-Based Professional Development In Early Childhood Education, Drew Giles

Dissertations

There is a growing need for school districts to identify additional strategies to support the work-related stress and emotional labor ingrained in an early educator’s career. By orienting early childhood education (ECE) staff to mindfulness practices, education leaders may identify new approaches to assist early childhood educators’ well-being, building healthy work atmospheres, and activities to shift the culture in early childhood settings. This study employs a qualitative exploratory research design, specifically video documentary methodology to better understand how early childhood educators experience a mindfulness-based professional development (MBPD) program designed for ECE staff, explore what they say education leaders should know …

(Miss)Educated Latino Males: Academic Preparedness, Navigation, And Retention At 2-Year Colleges, Nannette Stephanie Regua

Dissertations

This study centers Latino males, first generation, first year students at four 2-year colleges in the Silicon Valley by understanding their experiences in transferable English 1A Writing Composition course and looking at the acts of instilling a sense of belonging and mattering by institutional agents and support services that are invaluable to student retention and success. The purpose of this study is to determine Latino male students’ perceptions of academic preparation, navigation, and success in higher education after the implementation of California Assembly Bill 705. My findings revealed important themes that map onto conceptual frameworks, most notably the Community Cultural …

Monolithic Bubble Trap With Partitioned Inner Chamber For Roburst Operation Of Microfluidic Systems, Bhavagyna Vegunta, Charmaine Lui, Max S. Kim, Joshua Tran, Maya Papez, Anand K. Ramasubramanian, Sang Joon John Lee

Data

This data set includes experimental flow rate recordings in comma-separated values (CSV) files, fluorescence microscopy images of endothelial cells as TIF images, and orientation parameters for cell nuclei from the same images in spreadsheet (XLSX) files. These data files are in support of documenting the performance of a novel bubble trap designed by the authors, as described in the associated publication. File names in this data set correspond to figures in the associated publication.

Optimizing Field-Linked Simulations Of Dry Season Uptake And Monsoon Infiltration Within An Aspen-Mixed Conifer Forest, Raymond J. Hess

Master's Theses

Climate models forecast that headwater catchments in the western U.S. will undergo a reduction in snowpack, early season snowmelt, and increases in evapotranspiration. The resulting extended dry season will stress vegetation in mountainous watersheds throughout the Upper Colorado River Basin. We investigate infiltration patterns and root water uptake in response to dry season disturbances within the East River watershed in Colorado. To do this, we collected soil cores, measured matric potential and sap flow, and monitored tree xylem and soil for stable isotopes of water (2H, 18O) in two soil profiles to 90 cm depth (with three Engelmann spruce and …

Roundtable On Warhol V. Goldsmith: An Introduction To Warhol V. Goldsmith, Amy Adler, Lionel Bently, Susan Bielstein, Johanna Burton, Martha Buskirk, Noam M. Elcott, Jane Ginsburg, Branden W. Joseph, Joan Kee, Liz Linden, Rebecca Tushnet, Graeme Williams, Winnie Wong

Faculty Research, Scholarly, and Creative Activity

No abstract provided.

Youth Experiences In Gender–Sexuality Alliances Predict Academic Engagement But Not Disaffection Through Social–Emotional Wellbeing, V. Paul Poteat, Jerel P. Calzo, Hirokazu Yoshikawa, Daniel Kellogg, Robert A. Marx, Abigail Richburg, Arthur Lipkin

Faculty Research, Scholarly, and Creative Activity

Experiences in gender–sexuality alliances (GSAs) could predict youth's academic engagement through improved social–emotional wellbeing (indicated by school belonging, hope, and positive and negative affect). This study utilized three waves of data, each spaced 2–3 months apart, among 627 youth (87% LGBQ+, 45% trans/nonbinary, 48% youth of color) ages 11–22 (Mage = 15.13) in 51 GSAs in the United States in 2021–2022. Greater peer responsiveness in the GSA predicted increased academic engagement through increased wellbeing overall and specifically through hope and decreased negative affect. Advisor responsiveness and GSA leadership correlated with wellbeing and academic engagement in bivariate analyses but were not …

A Comparative Multivariate Analysis Of Var And Deep Learning-Based Models For Forecasting Volatile Time Series Data, Saroj Gopali, Sima Siami-Namini, Faranak Abri, Akbar Siami Namin

Faculty Research, Scholarly, and Creative Activity

The existing literature on forecasting time series data is primarily based on univariate analysis and techniques such as Univariate Autoregressive (UAR), Univariate Moving Average (UMA), Simple Exponential Smoothing (SES), deep learning models, and, most notably, univariate Long Short-Term Memory (LSTM) built based on univariate variable where the next lag of time series is leveraged for forecasting the next cycle of data. This paper takes this line of research to the next level by focusing on forecasting time series data based on “multivariate” modeling and analysis. To have a better insight of the performance of various deep learning-based models when multivariate …

Evaluating The Influence Of Marine Protected Areas On Surf Zone Fish, M. L. Marraffini, S. L. Hamilton, J. R. Marin Jarrin, M. Ladd, G. Koval, J. R. Madden, I. Mangino, L. M. Parker, K. A. Emery, K. Terhaar, D. M. Hubbard, R. J. Miller, J. E. Dugan

Faculty Research, Scholarly, and Creative Activity

Marine protected areas (MPAs) globally serve conservation and fisheries management goals, generating positive effects in some marine ecosystems. Surf zones and sandy beaches, critical ecotones bridging land and sea, play a pivotal role in the life cycles of numerous fish species and serve as prime areas for subsistence and recreational fishing. Despite their significance, these areas remain understudied when evaluating the effects of MPAs. We compared surf zone fish assemblages inside and outside MPAs across 3 bioregions in California (USA). Using seines and baited remote underwater videos (BRUVs), we found differences in surf zone fish inside and outside MPAs in …

Use Or Not: A Qualitative Study On The User Adoption And Abandonment Of Voice Shopping With Smart Speakers, Jiahe Lan, Yu Chen, Zheng Yan

Faculty Research, Scholarly, and Creative Activity

The recent advances in smart speakers impel the emergence and prevalence of voice shopping - placing orders on voice assistants. Previous work has studied user acceptance of voice shopping and the factors influencing users' experience of voice shopping. However, despite the growing interest in the use of voice shopping, little is known about the limited usage or abandonment of voice shopping. In this paper, we address this research gap through a qualitative study of 43 users of Tmall Genie, a smart speaker popular in China. We found that participants are willing to make low-involvement purchases via voice shopping. However, after …

True Grit: Exploring Nonprofit Sector Resilience Following Economic Recessions, Xintong Chen, Kerry Kuenzi, Lindsey Evans, Amanda Stewart

Faculty Research, Scholarly, and Creative Activity

The nonprofit sector has been portrayed as resilient, describing a sector that persists despite challenges. We investigate nonprofit resiliency by examining how organizational characteristics, strategies, and community factors equipped organizations to recover following economic recessions. Utilizing a fixed effects panel regression model, our study covers a period of 29 years (1989–2018), encompassing three economic crises in the United States. The primary focus is examining the sector’s financial health and the resilience of the constituent organizations. Our findings describe a sector buoyed by the resilience of larger and older organizations, earned revenue, and contribution revenue, as well as the role of …

Tracked Gulls Help Identify Potential Zones Of Interaction Between Whales And Shipping Traffic, Megan A. Cimino, Heather Welch, Jarrod A. Santora, David Kroodsma, Elliott L. Hazen, Steven J. Bograd, Pete Warzybok, Jaime Jahncke, Scott A. Shaffer

Faculty Research, Scholarly, and Creative Activity

Seabird-vessel interactions are often studied through the lens of fisheries bycatch, but seabirds encounter many watercraft types. Western Gulls Larus occidentalis breeding on the Farallon Islands (California, USA) have a foraging domain that encompasses both shipping lanes and productive fishing grounds, resulting in ample opportunities for vessel encounters. Previous research showed that these Western Gulls can serve as ecosystem indicators because their foraging behavior is linked to ocean prey conditions, and because their foraging grounds overlap with that of Humpback Whales Megaptera novaeangliae, which can make prey accessible. Because ship strikes and entanglement in fishing gear are concerns for whales …

Tiktok As Social Communication Tool To Encourage Participation In Volunteering Projects, Belén Moreno-Albarracín, Tania Blanco-Sánchez

Faculty Research, Scholarly, and Creative Activity

Social media are regarded as tools of communication and social influence. Notwithstanding this, TikTok’s majority audience in 2023 is made up of members of generations Z and Alpha, associated in previous studies with a participatory crisis. Given this contradiction, a research question is proposed: do young people use TikTok to consolidate social values such as solidarity? To answer it, the main objective is to analyse the use of TikTok as an instrument for youth participation in volunteer projects. A mixed methodology is used, based on a content analysis of the 150 videos uploaded to TikTok with the hashtag #voluntariado and …

Cross-Cultural Adaptation Of The Voice-Related Experiences Of Nonbinary Individuals - Veni To Brazilian Portuguese, Isabela Dos Santos, Mara Behlau, Grace Shefcik, Pei Tzu Tsai, Vanessa Veis Ribeiro

Faculty Research, Scholarly, and Creative Activity

Purpose: This study aimed to translate and cross-culturally adapt the “Voice-related Experiences of Nonbinary Individuals” (VENI) to Brazilian Portuguese (BP). Methods: Cross-cultural adaptation was performed based on the combined guidelines of the World Health Organization’s (WHO) Translation Recommendations and the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN). The process included five stages: a) Translation of the instrument into BP by a translator specialized in the construct and a non-specialist, both native BP speakers and fluent in English; b) Synthesis of the two translations by consensus; c) Back-translation by a translator specialized in the construct and a non-specialist, …

Improving Field Education For Social Work In Vietnam: Intern Supervisors’ Perspectives Of The Current State And Potential Solutions, Megan Aikawa, Meekyung Han, Trang T. Nguyen, Linh Dinh, Minh Thanh Bui

Faculty Research, Scholarly, and Creative Activity

Research has identified challenges associated with the implementation of competency-based social work field education in Vietnam. However, there is limited information available from intern supervisors, who have unique perspectives at the crux of social work training and service delivery. An exploratory phenomenological qualitative approach was used to explore their experiences and perceptions through online interviews. Four categories were identified: diverse implementation of a common framework, rudimentary expectations and activities, challenges to implementation, and opportunities for improvement. These findings suggest that a multidimensional approach is needed, including improved collaborations between field agencies and universities to empower students, intern supervisors, and faculty.

Incorporating Uas Traffic Management Into Wildland Firefighting Operations: Initial Findings Of Subject Matter Expert Interviews, Deborah L. Bakowski, Lynne Martin, Gil Dustin, Chris Mariano

Faculty Research, Scholarly, and Creative Activity

Uncrewed Aircraft Systems (UASs) are being utilized throughout the disaster and emergency response domain, including in wildland firefighting operations. While UASs can offer safety benefits in comparison to crewed aircraft, such as removing the human pilot from the vehicle so that they are not exposed to the same risks and the ability to operate in low-visibility conditions, they are not without tradeoffs. For example, it can be challenging for UAS pilots (UASPs) to build situation awareness of the airspace in which their UAS is operating. In order to address some of the challenges associated with using UASs and provide greater …

Mitigating Risk: Predicting H5n1 Avian Influenza Spread With An Empirical Model Of Bird Movement, Fiona Mcduie, Cory T. Overton, Austen A. Lorenz, Elliott L. Matchett, Andrea L. Mott, Desmond A. Mackell, Joshua T. Ackerman, Susan E.W. De La Cruz, Vijay P. Patil, Diann J. Prosser, John Y. Takekawa, Dennis L. Orthmeyer, Maurice E. Pitesky, Samuel L. Díaz-Muñoz, Brock M. Riggs, Joseph Gendreau, Eric T. Reed, Mark J. Petrie, Chris K. Williams

Faculty Research, Scholarly, and Creative Activity

Understanding timing and distribution of virus spread is critical to global commercial and wildlife biosecurity management. A highly pathogenic avian influenza virus (HPAIv) global panzootic, affecting 600 bird and mammal species globally and over 83 million birds across North America (December 2023), poses a serious global threat to animals and public health. We combined a large, long-term waterfowl GPS tracking dataset (16 species) with on-ground disease surveillance data (county-level HPAIv detections) to create a novel empirical model that evaluated spatiotemporal exposure and predicted future spread and potential arrival of HPAIv via GPS tracked migratory waterfowl through 2022. Our model was …

Next Steps For Assessing Ocean Iron Fertilization For Marine Carbon Dioxide Removal, Ken O. Buesseler, Daniele Bianchi, Fei Chai, Jay T. Cullen, Margaret Estapa, Nicholas Hawco, Seth John, Dennis J. Mcgillicuddy, Paul J. Morris, Sara Nawaz, Nishioka, Anh Pham, Kilaparti Ramakrishna, David A. Siegel, Sarah R. Smith, Deborah Steinberg, Kendra A. Turk-Kubo, Benjamin S. Twining, Romany M. Webb

Faculty Research, Scholarly, and Creative Activity

There are many potential approaches to marine carbon dioxide removal (mCDR), of which ocean iron fertilization (OIF) has the longest history of study. However, OIF studies to date were not primarily designed to quantify the durability of carbon (C) storage, nor how wise OIF might be as an mCDR approach. To quantify C sequestration, we introduce a metric called the “centennial tonne,” defined as 1,000 kg of C isolated from atmospheric contact for on average at least 100 years. We present the activities needed to assess OIF from a scientific and technological perspective, and additionally, how it might be responsibly …

Public Libraries Encouraged To Meet The Health Information Needs Of Tribal Women In Bangladesh, Lili Luo

Faculty Research, Scholarly, and Creative Activity

Objective – To investigate public libraries’ existing community engagement practices, explore their willingness to provide health information services to tribal communities in Bangladesh, and examine tribal women’s health information-seeking behavior and interest in obtaining health information from public libraries. Design – A cross-sectional study using online interviews and structured questionnaires. Setting – Public libraries and tribal communities in tribal regions of Bangladesh. Subjects – Public librarians (n=11) and tribal women (n=276) from three tribal districts in Bangladesh (Bandarban, Khagrachari, and Mymensingh). Methods – Interviews were conducted with librarians via Zoom in January 2023. Survey questionnaires were distributed to a convenience …

Sample Sizes For 10 Types Of Qualitative Data Analysis: An Integrative Review, Empirical Guidance, And Next Steps, Amber Wutich, Melissa Beresford, H. Russell Bernard

Faculty Research, Scholarly, and Creative Activity

There has been a recent explosion of articles on minimum sample sizes needed for analyzing qualitative data. The purpose of this integrated review is to examine this literature for 10 types of qualitative data analysis (5 types of saturation and 5 common methods). Building on established reviews and expanding to new methods, our findings extract the following sample size guidelines: theme saturation (9 interviews; 4 focus groups), meaning saturation (24 interviews; 8 focus groups), theoretical saturation (20–30+ interviews), metatheme saturation (20–40 interviews per site), and saturation in salience (10 exhaustive free lists); two methods where power analysis determines sample size: …

The Applicability Of Llms In Generating Textual Samples For Analysis Of Imbalanced Datasets, Saroj Gopali, Faranak Abri, Akbar Siami Namin, Keith S. Jones

Faculty Research, Scholarly, and Creative Activity

In machine learning class imbalance is a pressing issue, where the model is biased towards the majority classes and underperforms in the minority classes. In textual data, the natural language processing (NLP) model bias significantly reduces overall accuracy, along with poor performance in minority classes. This paper investigates and compares the performance of transformer-based models, such as Multi-head Attention with the data levels and algorithmic levels approaches and BERT (Bidirectional Encoder Representations from Transformers) with LLM-based data augmentation. The research utilized the approaches, such as Random Over Sampler, Synthetic Minority Over-sampling Technique (SMOTE), SMOTEENN, data augmentation at word level, class …

The Role Of Paradata In Algorithmic Accountability, Ciaran B. Trace, James A. Hodges

Faculty Research, Scholarly, and Creative Activity

This chapter examines how the doings of the algorithm (instantiated through its operations, actions, and steps) and its accompanying algorithmic system are revealed and explored through an engagement with the paradata created as a part of this data-making effort. In doing so, the chapter explores how the concept of paradata helps us understand how information professionals and domain stakeholders conceptualize accountable algorithmic entities and how this influences how they emerge as documented and describable entities. Two complementary frameworks for capturing and preserving paradata for accountability purposes are examined in the process. The first is associated with diplomatic theory and archival …

Enhancing Diagnostic Accuracy: A Hybrid Approach To Mitigate Speckle And Rician Noise In Medical Images, Naveenkumar Jayakumar, Saurabh Saoji, Sagar V. Joshi, Hemlata Mane, Roshni Narkhede, Shrikant Jadhav

Faculty Research, Scholarly, and Creative Activity

This research explores the detrimental effects of Rician and speckle noise in medical imaging, particularly within MRI and radiographic modalities. Such noise can significantly obscure critical details, potentially leading to misdiagnoses and inaccurate measurements. Rician noise candidly dangles on the signal strength. Removing this noise affects the origial information in image that makes this noise removal perplexing. On other hand speckle noise is visualised like granular clog in ultrasound imageries. It creates ambiguous details and edges in the images. To address this challenge, the study introduces a novel hybrid method implemented in Java. The method employs a frequency-based decomposition approach …