Digital Commons Network^™

Hierarchical Bloom Filter Tree (Hbft): Scalable Geospatial Metadata Indexing For Bigdata Systems, Mrudula Patteparapu

Master's Projects

Big Data infrastructure growth has produced overwhelming metadata volumes which create extensive problems for spatial indexing and both system scalability and database queries. Traditional solutions consisting of R-trees and conventional Bloom filters manage to provide either range query support or approximate membership testing, yet they face performance issues when used at large-scale metadata management. This research proposes Hierarchical Bloom Filter Tree (HBFT) as an improved framework that integrates hierarchical spatial partitioning with partitioned, scalable, cuckoo, and striped Bloom filter variants based on existing studies in hierarchical and probabilistic indexing. The complete evaluation process shows that HBFT outperforms PostGIS (an industry-standard …

Medilightrag: A System For Medical Query Response Using Fine-Tuned Llms And Graph Based Retrieval, Rajiv Karthik Reddy Kodimala

Master's Projects

The exponential increase in medical data has created a greater demand for precise and efficient information retrieval systems. Existing Large Language Models (LLMs) face domain-specific difficulties such as sophisticated medical jargon, situational comprehension, and the continual advancement of healthcare knowledge. To tackle these challenges, we present MediLightRAG, an innovative two-stage system which integrates parameter-efficient fine-tuning of Large Language models with LightRAG’s graph-based retrieval. The first stage focuses on enabling accurate resource-efficient model adaptation for the medical domain through QLoRA fine-tuning. In the second stage, LightRAG’s two-tiered retrieval architecture that combines graph-based indexing with dynamic knowledge retrieval is employed to enhance …

Edurag: Improving Ai Teaching Assistants With Retrieval-Augmented Generation, Geethika Vadlamudi

Master's Projects

This paper is based on the emerging need for AI-driven teaching assistants to deliver personalized, effective, and responsive educational assistance. Earlier proposals for educational technology such as rule-based systems and adaptive learning platforms have been limited by the lack of flexibility, domain accuracy, and slow, non-interactive support. With the launch of large language models (LLMs) like GPT-3, GPT-4, they have demonstrated that they can generate the kind of human-responsive text. When it comes to more substantive education matters, though, such models suffer from domain accuracy, in addition to whether accurate information can be imparted. And that is where the aspect …

Semanticgraphrec: Lightweight Hybrid Recommendations Powered By Semantic Item Representations And Graph Collaborative Filtering, Devi Surya Kumari Akula

Master's Projects

Graph neural networks (GNNs) have emerged as a powerful paradigm for collaborative filtering. However, they often fall short in fully leveraging side textual content, resulting in suboptimal recommendations. To address this limitation, we explore the synergy between GNNs and deep contextual embeddings of item descriptions, aiming to enhance recommendation quality on the Amazon-Books dataset. We propose SemanticGraphRec, which combines GNNs with Large Language Models (LLMs) to leverage both collaborative filtering and textual item content. Experimental results demonstrate that incorporating semantic item embeddings produced by fine-tuning LLMs consistently improves performance. Our approach enhances recommendation relevance in sparse data scenarios by leveraging …

Image-To-Text Transcription: Analyzing And Describing Visual Content, Zixiao Fan

Master's Projects

Image captioning, which provides a textual understanding of visual content, is the fundamental support for the advancement of Human-A.I. Interaction technology. In the hope of exploring the application of such technology, this project focuses on two specific goals. One is to directly explore the application of the image informationretrieving abilities, and the other is to dive into the specifics of the pipeline and components of image captioning models. As a result, this project presents a working app that exploits the text retrieval functionalities to enable image storage with functions like tagging and transcription. It also supports search functionality with a …

Extraction Of A Knowledge Graph Of Biomedical Relationships, Brian Tran

Master's Projects

Rapid release in biomedical literature poses a challenge in linking information. This thesis aims to extract data from expanding datasets to identify and form meaningful relationships between biomedical entities. Large language models (LLMs) enable us to learn at a rapid pace. Creation of LLms from scratch are impractical. This thesis aims to collect a small dataset, containing biomedical papers, and use it to train large language models (LLMs) to extract entities from the text and learn the relationships between these entities. The experiment will be divided into two stages and utilize EU-ADR and ChemProt dataset. Starting with named entity recognition …

Galora: A Lightweight Graph-Aware Llm Framework For Node Classification On Text-Attributed Graphs, Mayur Choudhary

Master's Projects

With the exponential rise of language models (LMs) and their potential to understand semantic relationships, large LMs are being used across a wide range of applications. Text-attributed graphs (TAGs) are one notable example where LLMs can be combined with Graph Neural Networks (GNNs) to enhance node classification results. TAGs associate textual content with each node and are commonly seen in various domains such as social networks, citation graphs, recommendation systems, etc. Effectively modeling TAGs would enable deeper insights into different aspects of the graph and improve decision-making in relevant domains. We present GaLoRA, a parameter-efficient framework to integrate structural information …

Maple: Malware Analysis Through Projection Of Low-Dimensional Embeddings, Quang Duy Tran

Master's Projects

Machine learning has become a popular and powerful tool for malware analysis and detection. With the rise in popularity of natural language processing (NLP) techniques, researchers can now extract contextual embeddings from malware opcode sequences, enabling the capability to analyze hidden malware patterns and advanced code obfuscation strategies. However, unlike malware binaries, which can be directly visualized as images, these embeddings exist in high-dimensional spaces, making it difficult to observe their global patterns or spatial structures. In this paper, we propose a framework for visualizing malware embeddings in lower-dimensional space using various dimensionality reduction techniques. Our approach converts malware binaries …

Large Language Models For Bacterial Genomic Analysis, Manvendra Chavan

Master's Projects

Identification of bacterial gene sequences with agricultural applications has the potential to transform agricultural biotechnology. These genes can be used in environmentally friendly pest control strategies. One such use case is identifying genes with potential insecticidal properties. With an increasing number of genomic information and decreasing numbers of available annotated sequences, finding new insecticidal genes has become more challenging.The traditional methods relying on sequence alignment and annotated databases are not effective in detecting functionally relevant genes lacking close homology to known cases. This project investigates the data-driven classification of genes by sequence modeling. This research is focused on learning DNA …

Equity In Public Budgeting: Community Engagement In Morgan Hill, Ariana Perez

Master's Projects

Through this research, I will examine what citizen participation strategies have been implemented and their role and effectiveness in addressing wealth inequities. My research will explore these topics and examine what programs and policies the City of Morgan Hill can implement to increase residents' sense of belonging and ultimately push for greater social equity. My primary research question is, what are the programs and policies that the City of Morgan Hill can implement to engage immigrant communities, specifically Spanish-speaking residents, and low-income residents in shaping decisions around public investments and funding? This project will serve as a needs assessment to …

What We Owe Each Other: An Examination Of Social Exchange Theory And Public Perception Of Healthy Relationships, Sarah R. Korbich

West Chester University Graduate Theses, Dissertations, and Final Projects

This study uses prior literature on social exchange theory and uses various frameworks to examine the public’s perception and comprehension of SET through examining user-generated content on TikTok. Social exchange theory is based upon the idea that when interacting with other persons, you are exchanging rewards and costs. This study was guided by two questions that explore how social exchange is generalized and understood by the public, and how well the public’s ideas of positively contributing to a healthy relationship aligns with operational measures of SET. This study’s intention is to encourage SET’s usage in application to relational contexts as …

An Exploratory Study Of Ukrainian Refugee Resettlement Patterns And Education Resource Needs In Poland, Marta Gintowt

West Chester University Graduate Theses, Dissertations, and Final Projects

The ongoing Russian invasion of Ukraine that started in late February 2022 triggered a refugee crisis that reverberated throughout Europe. During the onset of the invasion, an estimated five million Ukrainian refugees, mostly women, children, and the elderly, fled to countries in Europe and beyond. Countries were not prepared for the magnitude of the initial influx of refugees, who are a vulnerable population who require specific immediate and long-term supports. As three years have passed since the start of the war, the needs of refugees have evolved, and resources providing educational support to refugee children have taken on increased importance. …

Bot Detection In Social Media Using Graphsage And Bert, Abhishek Deshmukh

Master's Projects

This project details a novel bot detection system developed to battle the ever- changing challenge of disinformation, misinformation, and other bot-generated content.

The methodology employed in this project combines the text-based analytical strength of BERT (Bidirectional Encoder Representations from Transformers) with the strength of GraphSage (Graph Sample and Aggregation) for analyzing network structures. The project concatenates BERT and GraphSage vectors to create an 896-size feature embedding with a rich blend of network and text features. This project employs a Support Vector Machine to process the concatenated embeddings, as SVM works well with high-dimensional data. This project was evaluated on two …

Ai Powered Legal Decision Support System, Alisha Rath

Master's Projects

The large volume of legal cases presented by judicial professionals has made it
challenging to study and predict results. With advances in research methods and
technology, predicting law cases in a more accurate manner has become an important
trend. Prediction tools based on AI may help manage a large number of legislative
texts and documents that cannot possibly be fully read, reduce the number of cases
to be seen, and give accurate outcomes of how cases may turn out. Now, when
we look into the current AI legal prediction tools in this domain, they mostly lack
efficiency and interpretability, the …

Consensus And Conflict Over Context: Select Criminal Law And Procedure Cases From The Supreme Court's 2024-25 Term, Eve Brensike Primus, Elena Schultz

Articles

In its 2024-2025 Term, the Supreme Court emphasized the utility—and necessity—of context-based, fact-sensitive analyses throughout its criminal law and procedure cases. Though the Justices sparred over how to derive meaning from factual, structural, legal, and historical contexts, they tended to agree that courts should not be artificially restricted from considering the breadth of the record before them.

Fake News Detection In Arabic Media Using Machine Learning And The Afnd Dataset, Hussain Ali Bahri

Theses

The proliferation of fake news in digital media poses a significant challenge to information credibility, particularly in linguistically diverse regions such as the Arab world. This study addresses the critical problem of detecting fake news in Arabic media by leveraging advanced natural language processing (NLP) techniques and the AFND dataset, which contains over 600,000 news articles categorized into "credible," "not credible," and "undecided" classes. The research focuses on developing a robust system using AraBERT, a transformer-based model specifically pre-trained for Arabic text. Key contributions of this work include a comprehensive preprocessing pipeline tailored to Arabic linguistic complexities, incorporating stopword removal, …

Antenatal Interventions To Improve Breastfeeding In High-Risk Pregnancies: An Outpatient Clinic Perspective, Lina Saeday

Doctor of Nursing Practice Projects

High-risk pregnancies often face unique challenges when it comes to breastfeeding, yet few antenatal interventions specifically target this population. This quality improvement project aimed to improve breastfeeding knowledge, confidence, and attitudes among high-risk pregnant individuals through a brief educational intervention. Ten participants between 33 and 36 weeks gestation with diagnoses including GDM, gestational hypertension, multiple gestations and IVF pregnancies were recruited from an outpatient maternal-fetal medicine clinic. A printed educational brochure and a brief in-person teaching session were provided. Participants completed pre- and post-intervention surveys assessing their knowledge, perceived support, and attitudes toward breastfeeding. Post-intervention survey responses revealed statistically significant …

Identifying Barriers To Breast Cancer Screening In Asian American Women, Emily Dao

Doctor of Nursing Practice Projects

Background: Breast cancer is the most diagnosed cancer among Asian American women, yet have lower screening rates than non-Hispanic Americans.

Objective: This project evaluated mammogram rates among Asian American women at a Federally Qualified Health Center, assessed demographic factors affecting screening, and identified perceived barriers through a survey.

Methods: A chart review was conducted to assess rates of mammogram screenings rates, the percent difference between planned and actual screenings, and patient demographics that may affect screening rates. A 13-question quantitative survey was developed and completed by participants to assess common barriers and identify potential strategies to reduce barriers to screening. …

Reducing Perinatal Mood And Anxiety Disorder (Pmad) Amongst Latina Women Through A Nurse-Led Intervention In A Clinic Setting, Daniella Navarrao Naujokt

Doctor of Nursing Practice Projects

The purpose of this study was to evaluate the impact of the implementation of the Reach Out, Stay Strong, Essentials for mothers of newborns (ROSE) curriculum amongst pregnant Latina’s in their third trimester, and to determine if participation in these classes increases patient awareness and management of perinatal mood and anxiety disorders. Using a nurse-led prenatal group setting, pregnant Latinas who are 18 years of age or older, are Spanish speakers, and at least 28 weeks gestation in pregnancy were presented with information about the intervention by their provider. Following informed consent, patients were to be asked to participate in …

Improving Dementia Literacy In Direct Care Workers In Independent Senior Communities, Rachael Kauffung, Rosalie Monkono

Doctor of Nursing Practice Projects

No abstract provided.

Asian American Mental Health Detection, Treatment, And Adherence In Primary Care, Kimberly Ha, Jenny Tran

Doctor of Nursing Practice Projects

Background: Asian Americans are understudied in the field of mental healthcare. Barriers to care include stigma, acculturative stress, and community expectations, coupled with structural limitations such as culturally insensitive care and knowledge gaps, which contribute to decreased rates of mental health access and utilization for this population.

Objective: Identify gaps in the diagnosis, and treatment pathways for Asian Americans receiving mental health services in the primary care setting.

Methods: A retrospective chart review was conducted through a group of community health clinics in Seattle, Washington. Race, preferred language, English-proficiency, age, income, insurance-type, and ethnic subgroups were identified and compared …

End-Of-Life Care Educational Program For Neuro Nurses, Shiyue (Sophie) Wang, Thu Le

Doctor of Nursing Practice Projects

Introduction: High-quality end-of-life (EOL) care necessitates both effective symptom management and therapeutic communication with patients and families. Nurses often report knowledge gaps in symptom management and discomfort when engaging in sensitive conversations during EOL care.

Methods: Neuro-nurses at a tertiary care hospital were invited to participate in an educational intervention focused on EOL symptom management and communication. The training occurred during both day and night clinical shifts. Effectiveness was measured using pre- and postintervention assessments adapted from validated questionnaires. All responses collected anonymously via REDCap.

Results: Post-intervention, 83% of participants showed improved scores in the knowledge assessment, with an average …

Addressing Mental Healthcare Barriers Among Bipoc Perinatal Patients In A Community Health Setting, Aimee Nguyen, Ezinne Ndibeshe, Vedika Iyer

Doctor of Nursing Practice Projects

Objective. BIPOC (Black, Indigenous, and People of Color) perinatal patients often face systemic, cultural, and logistical barriers to accessing mental health care during pregnancy and postpartum. These challenges contribute to disparities in outcomes, yet patient perspectives remain underrepresented in community health settings. This quality improvement initiative aimed to identify key barriers, raise awareness about perinatal mental health, and improve access to care at a community health clinic in Shoreline, Washington. A culturally inclusive educational handout was developed to support awareness and connect patients with mental health resources.

Methods. A mixed-methods approach was used to explore barriers both quantitatively and qualitatively. …

Investing In The Development Of The Next Generation Of Mch Leaders, Karen A. Mcdonnell, Jamal Percy, Lisa Anders, Monique J. Brown Ph.D., Mph, Alice R. Richman, Julianna Deardorff, Monica S. Ruiz, Jihong Liu Sc.D., Kelli Russell, Audrey Snyder, Cassondra Marshall

Faculty Publications

The public health landscape is constantly evolving to address the strengths and needs of the community. Training for the public health workforce is leading the way, establishing an ecosystem approach that integrates individuals within social, political, and environmental contexts to promote health equity within a framework of social justice. One area of public health that is innovatively preparing the next generation of leaders is maternal and child health (MCH). In the United States, key indicators of health disparities within MCH remain stagnant, highlighting the need for training programs that develop future MCH professionals from diverse backgrounds. These professionals will deliver …

Scientific Kenyon: Neuroscience Edition (Full Issue)

Scientific Kenyon: The Neuroscience Edition

No abstract provided.

The Integration Of Artificial Intelligence And Ontologies: Transformations In Knowledge Representation And Application, Grazia Serratore, Julaine Clunis

STEMPS Faculty Publications

Artificial Intelligence (AI) is reshaping the landscape of knowledge representation. There is an increasingly strong bidirectional relationship, between AI techniques and ontologies. AI techniques revolutionized traditional, manual ontology development and contribute to automated ontology construction, while ontologies enhance the performance of AI systems and their semantic accuracy. Through a comprehensive review of current literature, this paper aims to examine: i) how Machine Learning (ML) techniques contribute to the automated construction, refinement, and validation of ontologies; ii) the most widely used and effective ML approaches for ontology construction; iii) how domain-specific requirements influence the selection and adaptation of AI techniques for …

Bridging The Gap: The Role Of Parent-Teacher Perception In Child Developmental Outcomes, Mckayla Jensen, Mikaela J. Dufur, Jonathan A. Jarvis, Shana L. Pribesh

STEMPS Faculty Publications

Background/Objectives: Time spent with parents and educators encompasses a large portion of a child’s waking hours, with the home and early childhood education and care serving as two of the first settings in which children develop social and cognitive abilities. While previous studies have used social and cognitive tests to examine antecedents of child behavior, we extend such studies to take into account the congruence and incongruence of parents’ and teachers’ views on those antecedents. We examine the importance of parent-teacher alignment on the perceptions of a child’s personality and abilities in early development. Methods: Parents and teachers of 2968 …

The (Im)Possibility Of Separating Rabbinic Texts Into Literary Genres: Form Analysis And Text Linguisticslysis And Text Linguistics, Rivka Ulmer

Faculty Journal Articles

This paper analyzes rabbinic homiletic texts from the perspective of form analysis in combination with text-linguistic theories. My study indicates that, from the perspective of functional considerations, it is not meaningful to lift small literary forms from a coherent text that depends on a co-text to create meaning. Additionally, the concepts of genre and parable need to be abandoned and replaced by text-type and mashal. The form-analytical description of rabbinic homilies is based on research performed at the Institute of Judaic Studies in Frankfurt am Main. The text-linguistic concepts are based on strict formalizations that demonstrate textual relations.These theories were …

Privileging Genetic Privacy, Natalie Ram

Emory Law Journal

Right now, research is being done on the genetic material or genetic information of practically every person in the United States, often without their knowledge or consent. These vast stores of research materials offer a tempting target for law enforcement, who have sought to obtain DNA profiles from as many sources as possible. This Article makes the case that this scenario should trouble us—and also that there are existing legal tools that could guard against it.

In so doing, it makes four contributions to the existing literature. First, it identifies the unique features of research genetic data that make …

Spanish-Speaking Interpreters’ Perspectives: How Latinx Immigrant Caregivers Navigate The Special Education Process, Lizeth B. Tomas Flores

Theses and Dissertations--Educational, School, and Counseling Psychology

The study examined the experiences of Spanish-speaking interpreters working with Latinx immigrant caregivers during the special education process, their perspectives on how caregivers and the IEP professional committee members participate in the process, aiming to gain a better understanding of how Latinx immigrant families navigate the special education process. Interpreters play a crucial role in the special education process for families from culturally and linguistically diverse backgrounds, as they facilitate the transmission of information between caregivers and special education teams. Interviews were conducted with six special education interpreters in a southwestern suburban school district in the United States. A qualitative …