Digital Commons Network^™

Untraining Gender Bias: An Eye-Tracking Study, Ripujit S. Bamrah

Master's Projects

In recent years, social cognitive theory has emphasized the role of cognitive processes in shaping perceptions and behavior related to gender bias. By examining the impact of targeted training interventions, this study seeks to better understand the influence of such processes on decision-making in the context of character selection. This human-computer interaction study explores the potential of intervention-based training to untraining gender bias in character selection. With an increasing need to address gender bias in various domains, understanding the impact of gender-based training becomes crucial. According to our hypothesis, exposure to masculine characters would boost people’s preference for female- intellectualized …

Document-Level Machine Translation With Hierarchical Attention, Yu-Tang Shen

Master's Projects

Machine translation (MT) aims to translate texts with minimal human involvement, and the utilization of machine learning methods is pivotal to its success. Sentence-level and paragraph-level translations were well-explored in the past decade, such as the Transformer and its variations, but less research was done on the document level. From reading a piece of news in a different language to trying to understand foreign research, document-level translation can be helpful.

This project utilizes a hierarchical attention (HAN) mechanism to abstract context information making document-level translation possible. It further utilizes the Big Bird attention mask in the hope of reducing memory …

Steganographic Capacity Of Selected Machine Learning And Deep Learning Models, Lei Zhang

Master's Projects

As machine learning and deep learning models become ubiquitous, it is inevitable that there will be attempts to exploit such models in various attack scenarios. For example, in a steganographic based attack, information would be hidden in a learning model, which might then be used to gain unauthorized access to a computer, or for other malicious purposes. In this research, we determine the steganographic capacity of various classic machine learning and deep learning models. Specifically, we determine the number of low-order bits of the trained parameters of a given model that can be altered without significantly affecting the performance of …

Federated Learning For Protecting Medical Data Privacy, Abhishek Reddy Punreddy

Master's Projects

Deep learning is one of the most advanced machine learning techniques, and its prominence has increased in recent years. Language processing, predictions in medical research and pattern recognition are few of the numerous fields in which it is widely utilized. Numerous modern medical applications benefit greatly from the implementation of machine learning (ML) models and the disruptive innovations in the entire modern health care system. It is extensively used for constructing accurate and robust statistical models from large volumes of medical data collected from a variety of sources in contemporary healthcare systems [1]. Due to privacy concerns that restrict access …

Keystroke Dynamics And User Identification, Atharva Sharma

Master's Projects

We consider the potential of keystroke dynamics for user identification and authentication. We work with a fixed-text dataset, and focus on clustering users based on the difficulty of distinguishing their typing characteristics. After obtaining a confusion matrix, we cluster users into different levels of classification difficulty based on their typing patterns. Our goal is to create meaningful clusters that enable us to apply appropriate authentication methods to specific user clusters, resulting in an optimized balance between security and efficiency. We use a novel feature engineering method that generates image-like features from keystrokes and employ multiclass Convolutional Neural Networks (CNNs) to …

Cultural Perspectives In Pain And Palliative Care, Loan Lagué

Master's Projects

Culturally and linguistically diverse (CALD) patients are constantly challenged by the different levels on which lack of cultural competency or bias occurs in healthcare. This literature review focuses on the healthcare providers’ experiences when providing pain and palliative care to CALD populations and explores the challenges that may result in health inequalities. A review of current literature was conducted using PubMed, CINHAL, Sage Journals, Ovid, and Science Direct electronic databases. Sixteen published articles between 2015-2023 were reviewed. Findings from this review identified factors that induce poor quality palliative, pain, and end-of-life (EOL) care among culturally diverse groups. Improving quality of …

Deep Learning Neural Machine Translation Conversational Agent, Abhishek Vaid

Master's Projects

Neural Machine Translation (NMT) is a prominent natural language processing technique that is being used to develop conversational AI technology. However, most chatbots do not provide live API features and have list-based scripted responses. Most chatbots are majorly restricted by the training data on which they were trained on and have no knowledge of current events. This research project intends to research and develop an approach to providing live information. We experiment with various techniques in terms of the type of data being used to harness live capabilities. We optimize the hyperparameters that are needed for a Conversational AI agent …

Job Tailored Resume Content Generation, Sumedh Kale

Master's Projects

Generally candidates apply to multiple jobs with a single resume and do not tend to customize their resume to match the job description. This hampers their chances of getting a resume shortlisted for the job. The project aims to help such candidates build job tailored resumes that help them create a customized and targeted resume for a specific job or industry. The tool specifically targets candidates’ employment history, for resume content generation. We then use natural language processing

(NLP) techniques to extract and organize this data into a structured format for the dataset. We experiment with multiple variations of the …

Unlearning Hidden Bias Between Refugees : An Initial Empirical Investigation, Akshay Sunil Gurnaney

Master's Projects

The challenges that refugees in various regions encounter are common knowledge. One such challenge is a bias among refugees on ethnocentric grounds. In particular, there are various articles that have pointed out the struggles faced by Syrian refugees in countries like Europe as a result of implicit bias. In fact, the media coverage of Syrian crises and the government responses to the same shed negative light on the refugees themselves. On the contrary, the media coverage of Ukrainian crises is very different with lesser restrictions from the governments.

This research attempts to identify the extent of implicit bias between Ukrainian …

Temporal Dilation In Video Resnet For Sign Language Translation, Xiaoqian Yang

Master's Projects

Sign languages, vital for communication among the deaf and hard-of-hearing (DHH) people, face a significant linguistic diversity challenge with over 200 distinct sign languages worldwide. Bridging this communication gap is a priority. Traditional tools like interpreters and costly translation devices have limitations. This project aims to use deep learning techniques to develop a model capable of recognizing sign language from short videos. Our model not only recognizes the sign from a single video clip, but is also capable of making prediction of consecutive pairs of signs. To achieve zero-short gesture sequence recognition, we propose a novel temporal dilation strategy, converting …

Ensemble Transformer Architecture For Efficient And Real Time Sign Language Translation, Sumeet Ghegade

Master's Projects

Sign language is a form of visual language that uses face expression and hand gestures to communicate thoughts and concepts. The term refers to multiple visual languages that share some common visual cues but differ in their grammar and syntax. Sign language translation (SLT) is a crucial step in closing the communication gap between hearing and hearingimpaired people. The study of SLT using machine learning has gotten a lot of interest during the last three years but despite progress, SLT research is still in its early phases. Most of the previous approaches first convert the signs to glosses and then …

Nuancenet: Comparative Analysis Of Ai In Complex Language Interpretation For Disaster Detection, Pavan Koushik Kommuri

Master's Projects

Disaster Detection using Twitter content is critical for emergency response, but accurately identifying relevant tweets remains challenging due to nuances, informal language, and emotional expressions. This paper presents a comparative analysis between traditional Machine Learning models, Deep Learning models and Large Language Models (LLM) for classifying disaster vs. non-disaster tweets. While existing works have applied pattern recognition and dataset-specific learning, LLMs with their deeper understanding of linguistics and semantics can potentially handle the complexities of tweets more effectively. This study leverages LLMs including Llama2, Mistral, and Falcon, Open AI GPT 3.5, hypothesizing their superior contextual comprehension will excel in tweets …

“The Issue Is Already There; Just Have The Conversation!”: Culturally Sustaining Reflection In The Student Teaching Triad, Hanna M. Asrat

Dissertations

There is a vast demographic mismatch between California’s public school teachers (who are majority White, mono-lingual English-speaking women) and California’s public school students. Though universities responsible for educating preservice teachers often include coursework that attempts to help address this demographic mismatch, such as instruction about Culturally Sustaining Pedagogy, if preservice teachers do not get the chance to practice this pedagogy in their fieldwork placement, they tend to fall into to the two-worlds problem. The two-worlds problem posits that preservice teachers view constructivist and Culturally Sustaining Pedagogies learned at the university as theoretical and incompatible with actual teaching, and so they …

Ethnic Studies Implementation In A K-8 District: Culture, Critical Consciousness And Collective Efficacy, Genvieve Dorsey

Dissertations

This research was a descriptive study in which the researcher explored the beginning phases of Ethnic Studies implementation in a Kindergarten through Eighth grade (K-8) school district in Northern California. Using a social justice lens, and through a review of Ethnic Studies, Collective Efficacy, Critical Consciousness, and School Culture constructs, the researcher attempted to capture and articulate a cultural profile of the school district and the degree to which it aligned to the cultural typologies articulated among Ethnic Studies scholars.The study included the collection of several types of data, including: (1) archival documents; (2) teacher focus groups; and (3) administrator …

How Can I Help You Today? How First-Generation Latinx/A/O Community College Students Perceive Counseling, Isaac Escoto

Dissertations

Latinx/a/o students make up almost half of the California Community College system’s population. However, Latinx/a/o students account for about 15% of three-year completion rates (certificate, degree, or transfer). In support of student success strategies, the literature describes the role of counselors and how they help students navigate the complexities of higher education. This mixed-methods study investigated how community college counseling practices and services are perceived by Latinx/a/o students; and which of those practices and services best supported the success of this student population. Key findings included the importance of counseling services, as well as preferred counseling appointment logistics and topics …

Never Too Young: The Existence, Impact, And Sustainability Of Ethnic Studies In Elementary School, Angela R. Guzmán

Dissertations

Ethnic Studies has existed in higher education for more than fifty years. In high school, critical education researchers have recognized Ethnic Studies as vital to improving attendance, lowering suspension rates, and boosting GPAs for BIPOC students. This has given rise to the recent K-12 Ethnic Studies model curriculum adoption by the State Board of Education, and the signing of Assembly Bill 101, making California the first state to require that all high school students complete a semester-long course in Ethnic Studies. Regrettably, Ethnic Studies continues to be mostly limited to higher education and grades 9-12 in public schools despite research …

Voice Of The Inaudible: Well-Being Of Chinese American Young Adults, Chinese American Parents’ Parenting Competency, And The Correlation Of The Two, Diana Huang

Dissertations

Violence against Asian Americans since the beginning of the COVID-19 pandemic has become a national crisis in the United States. Racism against Asian Americans in the country, however, has been deep-rooted since the nineteenth century. Chinese American adolescents, who are susceptible to identity crisis as young adults and confront racial discrimination as a minority race, face distressing challenges. It is critical to inquire into their lived narratives and hear their voices. The author investigated the early life experiences of nine Chinese Americans and identified how racial identity is shaped at a young age with negative external inputs, as well as …

Beyond Social Emotional Learning: Toward A Humanizing And Transformative Teacher Sel, Ash Ray Busby

Dissertations

The purpose of this study was to bring to life the experiences of how the development of a Social, Emotional and Cultural lens prepares teachers to meet their own social and emotional needs in the classroom and consequently be better prepared to meet their students’ social and emotional needs in ways that are culturally sustaining. This qualitative research study explored these phenomena through a series of three in-depth interviews and a classroom observation with four in-service teachers in a Northern California school district that prioritizes social emotional learning (SEL) for students and teachers. The insights from this research may inform …

Twitter Bot Detection Using Nlp And Graph Classification, Warada Jayant Kulkarni

Master's Projects

Social media platforms are one of the primary resources for information as it is easily accessible, low in cost, and provides a high rate of information spread. Online social media (OSM) have become the main source of news information around the world, but because of the distributed nature of the web, it has increased the risk of fake news spread. Fake news is misleading information that is published as real news. Therefore, identifying fake news and flagging them as such, as well as detecting sources that generate them is an ongoing task for researchers and OSM companies. Bots are artificial …

Adoption And Utilisation Of Artificial Intelligence By Librarians In University Libraries In Southern Nigeria, Ogochukwu T. Emiri

Library Philosophy and Practice (e-journal)

The study investigated how librarians working in the various university libraries in Southern Nigeria adopted and used artificial intelligence. The researcher was able to retrieve 704 copies of the 848 questionnaires that were given to the responders. However, the return rate was 83%, which is a respectable amount. The descriptive statistics approach was used to analyse the data that the questionnaire produced. The results showed that there has been little adoption of AI in university libraries in Southern Nigeria. The research also reveals that security scanning devices at university libraries' entrances and exits are the most prevalent AIs, while other …

Reconstructing Auditory Evoked Cortical Response With Fewer Trials, Zoey Y. Zhang

Master's Theses

Auditory evoked fields (AEF) paradigm is a common research tool to study human auditory responses by using Magnetoencephalography (MEG), a neuroimaging tool. AEF paradigm requires repetition over many trials to achieve adequate signal-to-noise ratio (SNR), but Autistic children and some other populations cannot tolerate prolonged exam time due to various reasons. To address these challenges, this project uses a novel machine learning algorithm, Champagne with baseline noise learning, to reconstruct AEF data with fewer trials (80%, 60%, 40%, 20%) but produce the same results as using all AEF trials (100%). The results show that this novel machine learning algorithm can …

Misinformation Containment Using Nlp And Machine Learning: Why The Problem Is Still Unsolved, Vishnu S. Pendyala

Faculty Research, Scholarly, and Creative Activity

Despite the increased attention and substantial research into it claiming outstanding successes, the problem of misinformation containment has only been growing in the recent years with not many signs of respite. Misinformation is rapidly changing its latent characteristics and spreading vigorously in a multi-modal fashion, sometimes in a more damaging manner than viruses and other malicious programs on the internet. This chapter examines the existing research in natural language processing and machine learning to stop the spread of misinformation, analyzes why the research has not been practical enough to be incorporated into social media platforms, and provides future research directions. …

Factors Influencing Educational Equity In Online Instruction For Students During Covid-19, Sudha Krishnan

Faculty Research, Scholarly, and Creative Activity

This qualitative study examined special education teachers’ perceptions of student success in online instruction during the pandemic school closures to isolate the key determinants in the differential student outcomes reported by the teachers. Data were collected from 16 teachers using semi-structured interviews and analyzed using thematic coding. The six themes that emerged from the data were that the key determinants of student outcomes were variables related to teacher, school administrator, district, student, parent, and pedagogy. The study showed that underlying deficit thinking in school professionals, lack of planned support for those parents and students needing the most support, and limited …

Tesol Programs In Flux, Priyanvada Abeywickrama, Stefan Frazier, David Malinowski, Scott Phillabaum

Faculty Research, Scholarly, and Creative Activity

TESOL graduate programs in the U.S. have seen a steady decline in international and domestic student applications over the past several years. Among the possible causes of this decline are economic turmoil, changing immigration policies and politics, and broader social turbulence, issues that were present before the COVID-19 pandemic but which have been exacerbated by its persistence, forever changing education and learning. As we look forward, TESOL graduate programs must rethink, re-envision, and reconsider how they prepare teachers for a changing world. This chapter discusses ways that two well-established graduate TESOL programs have confronted the changes mentioned above, and presents …

Conceptualizing Socio-Emotional Disablism: A Duoethnography Of Crohn’S Disease And Ocd During Covid-19, Kristen L. Cole, Brandi Lawless

Faculty Research, Scholarly, and Creative Activity

We utilize duoethnography to help readers better understand the constitutive nature of disability in the contexts of chronic illness and mental health. By doing so, we articulate the concept of socio-emotional disablism, which expands structural and psycho-emotional theories of disablism to account for the ways socio-material interactions trigger emotion-work—the communicative labor and fatigue that accompanies negotiating our own emotions as well as the emotions of others in disabling contexts—thus limiting relational and ideological engagement with disability. We conclude by discussing what the concept of socio-emotional disablism teaches us about how to build more inclusive social futures through deeper interpersonal engagement …

Network Anatomy In Logopenic Variant Of Primary Progressive Aphasia, Maria Luisa Mandelli, Diego L. Lorca-Puls, Sladjana Lukic, Maxime Montembeault, Andrea Gajardo-Vidal, Abigail Licata, Aaron Scheffler, Giovanni Battistella, Stephanie M. Grasso, Rian Bogley, Buddhika M. Ratnasiri, Renaud La Joie, Nidhi S. Mundada, Eduardo Europa, Gil Rabinovici, Bruce L. Miller, Jessica De Leon, Maya L. Henry, Zachary Miller, Maria Luisa Gorno-Tempini

Faculty Research, Scholarly, and Creative Activity

The logopenic variant of primary progressive aphasia (lvPPA) is a neurodegenerative syndrome characterized linguistically by gradual loss of repetition and naming skills resulting from left posterior temporal and inferior parietal atrophy. Here, we sought to identify which specific cortical loci are initially targeted by the disease (epicenters) and investigate whether atrophy spreads through predetermined networks. First, we used cross-sectional structural MRI data from individuals with lvPPA to define putative disease epicenters using a surface-based approach paired with an anatomically fine-grained parcellation of the cortical surface (i.e., HCP-MMP1.0 atlas). Second, we combined cross-sectional functional MRI data from healthy controls and longitudinal …

Effectiveness Of In-Person Versus Online Negotiation Teaching For Practitioners, Patricia Oehlschläger, Michael A. Merz

Faculty Research, Scholarly, and Creative Activity

Most negotiation courses have been taught in person. However, online education has become more prevalent over the past decade due to its flexibility, cost and time efficiency, and new digital technologies designed to compensate for the lack of personal contact. The global pandemic has accelerated this trend, raising the question of whether negotiation courses taught online are as effective as those taught in person. The few studies that have examined the effect of teaching modality on student performance were limited to undergraduate and graduate student samples and the results have been mixed. To contribute to this discussion, we conducted two …

Shifting Mediates Gendered Racial Microaggressions And Perceived Racism Among Asian American Women, Glenn Gamst, Christine Ma-Kellams, Lawrence S. Meyers, Leticia Arellano-Morales

Faculty Research, Scholarly, and Creative Activity

Introduction: Microaggressive attacks on Asian American women increased during the COVID-19 pandemic. The present study tested whether Asian American women's shifting, a coping strategy employed by some women of color to alter their self-presentation in response to perceived racism, mediated the association between gendered racial microaggressions and self-perceived subtle and blatant racism. Methods: A convenience sample of 253 Asian American adult women completed the gendered racial microaggressions scale for Asian American women (GRMSAAW), the Asian American women's shifting scale (AsAWSS), and the subtle and blatant racism scale for Asian American college students (SABR-A2). Results: Results from a structural equation model …

Students’ Knowledge And Attitudes Towards Plagiarism At The Faculty Of Engineering Kyambogo University, Bonniface Agungi, Bonny Ongora

Library Philosophy and Practice (e-journal)

Students’ Knowledge and attitudes towards plagiarism at the Faculty of Engineering, Kyambogo University. The findings of the study revealed that the forms of plagiarism are copying work from the internet, submitting similar coursework and copying during test and exams, because of desire to get good grade, fear of failing, disinterest in the assignment, procrastination or poor time management and laziness encourage students to plagiarize therefore putting plagiarism as a course unit, conducting seminars to orient people about plagiarism, putting in place plagiarism detection software, motivating lecturers to teach students about plagiarism and training students on how to avoid plagiarism will …

Towards An Open And Inclusive Digital Humanities: Policies And Initiatives For Open Data Promotion In India, Mumtaj Mumtaj

Library Philosophy and Practice (e-journal)

The paper discusses about background of open data, policies and initiatives in the field of digital humanities in India. The article highlights the significance of open data on mankind and its potential in advancing research, promoting transparency, and encouraging collaborations. The article analyzes the current state of open data policies and initiatives in world as well as in India .The paper accentuates the significance of open data in enabling greater collaboration and inclusivity in the Digital Humanities in India, and calls for increased efforts to promote open data policies and initiatives in the country .The article talked about the successful …