Digital Commons Network^™

The Contribution Of Phonological Overlap To The Cognate Effect: An Event-Related Potential Study Of Persian-English Bilinguals, Zahra Fotovatnia

Theses and Dissertations (Comprehensive)

The purpose of this dissertation was to examine the contribution of phonological overlap to visual word recognition. More specifically, this study aimed at testing the phonological account of the cognate effect (i.e., faster and more accurate mental processing of cognates than noncognates) in visual word recognition in Persian and English, which are languages with different scripts. The phonological account attributes the cognate effect to the phonological similarity of cognates (form and semantically related words) in addition to the conceptual similarity that cognates and noncognates (semantically related words) have and to the degree of phonological similarity between cognates in two languages. …

Nomological Network Retrieval: The Development Of A Methodological Process For The Review Of Knowledge Structures In Academia And Its Application To Marketing Scholarship, Mohammad Ali Simjour

Theses and Dissertations (Comprehensive)

The increasing supply of peer-reviewed marketing publications indicates that the scholarly community’s understanding of marketing phenomena has increased significantly. However, this significant increase also prevents individual scholars from gaining insight into marketing phenomena simply because the sheer number of publications make a manual review of the literature impossible. This is an important limitation mainly because the validity of knowledge development processes in marketing partially depend on the scholars’ comprehensive understanding of extant knowledge. In this dissertation, I develop a methodological process to address this limitation and enable scholars to gain insight into large samples of peer-reviewed publications. I then apply …

A Close Look At The Connections Between Mental-State Talk, Theory Of Mind, And Source Monitoring During Parent-Child Reminiscing Of Emotional Events, Mallory Earnshaw

Theses and Dissertations (Comprehensive)

Autobiographical memories play a critical role in shaping personal identity, regulating emotions, and guiding future behaviour. Reminiscing about these memories can be particularly beneficial for coping with negative experiences. This study investigated the connections between mental-state talk, theory of mind, and source monitoring in parent-child reminiscing, and how it can be influenced by remembering enjoyable versus frustrating events. This study involved children ages 3-8 (N = 50) and consisted of two sessions. In the first session, the child reminisced with their parent about an enjoyable and frustrating event and completed two source-monitoring tasks. In the second session, the child …

Brazilian Portuguese-Russian (Braporus) Corpus: Automatic Transcription And Acoustic Quality Of Elderly Speech During Covid-19 Pandemic, Irina A. Sekerina, Anna Smirnova Henriques, Aleksandra Skorobogatova, Natalia Tyulina, Tatiana V. Kachkovskaia, Svetlana Ruseishvili, Sandra Madureira

Publications and Research

This article presents the Brazilian Portuguese-Russian (BraPoRus) corpus, whose goal is to collect, analyze, and preserve for posterity the spoken heritage Russian still used today in Brazil by approximately 1,500 elderly bilingual heritage Russian–Brazilian Portuguese speakers. Their unique 100-year-old variety of moribund Russian is disappearing because it has not been passed to their descendants born in Brazil. During the COVID-19 pandemic, we remotely collected 170 h of speech samples in heritage Russian from 26 participants (Mage = 75.7 years) in naturalistic settings using Zoom or a phone call. To estimate the quality of collected data, we focus on two methodological …

Rethinking First Language–Second Language Similarities And Differences In English Proficiency: Insights From The English Reading Online (Enro) Project, Noam Siegelman, Irina Elgort, Marc Brysbaert, Niket Agrawal, Simona Amenta, Jasmina Arsenijevic Mijalkovic, Christine S. Chang, Daria Chernova, Fabienne Chetail, A. J. Benjamin Clarke, Alain Content, Davide Crepaldi, Nastag Davaabold, Shurentsetseg Delgersuren, Avital Deutsch, Veronika Dibrova, Denis Drieghe, Dušica Filipovic Ðurđevic, Brittany Finch, Ram Frost, Carolina A. Gattei, Esther Geva, Aline Aline Godfroid, Lindsay Griener, Esteban Hernández-Rivera, Anastasia Ivanenko, Juhani Järvikivi, Lea Kawaletz, Anurag Khare, Jun Ren Lee, Charlotte E. Lee, Christina Manouilidou, Marco Marelli, Timur Mashanlo, Ksenija Mišic, Koji Miwa, Pauline Palma, Ingo Plag, Zoya Rezanova, Enkhzaya Riimed, Jay Rueckl, Sascha Schroeder, Irina A. Sekerina, Diego E. Shalom, Natalia Slioussar, Neža Marija Slosar, Vanessa Taler, Kim Thériault, Debra Titone, Odonchimeg Tumee, Ross Van De Wetering, Ark Verma, Anna Fiona Weiss, Denise Hsien Wu, Victor Kuperman

Publications and Research

This article presents the ENglish Reading Online (ENRO) project that offers data on English reading and listening comprehension from 7,338 university-level advanced learners and native speakers of English representing 19 countries. The database also includes estimates of reading rate and seven component skills of English, including vocabulary, spelling, and grammar, as well as rich demographic and language background data. We first demonstrate high reliability for ENRO tests and their convergent validity with existing meta-analyses.We then provide a bird’s-eye view of first (L1) and second (L2) language comparisons and examine the relative role of various predictors of reading and listening comprehension …

Psalm 1a–B (1:1–2:12 As Combined And A Chiasm): What Yhwh Knows About People’S Paths And Plans That Will Perish, W. Creighton Marlowe

The Asbury Journal

This article seeks to explore whether a division really exists between Psalm 1 and Psalm 2. The author argues that the presence of a chiasm which extends throughout the two psalms gives potential further evidence for the argument that the two psalms where once part of one continuous literary creation. The themes involve the laws of YHWH and the consequences of breaking these laws both for individuals and for nations.

Δικαιοσύνη Θεοῦ: The Holistic Connotation Of The Term ‘Righteousness’ And Its Implications For Social Service, Uma John

The Asbury Journal

The concept “righteousness” is weighty and indispensable in the biblical tradition and understanding the concept has changed and developed through the centuries. The current article explores the topic from the ancient to modern canonical and non-canonical literature on the concept of righteousness to seek its wide range of meanings. Traditionally, the term “righteousness” has forensic, and religious connotations, but this paper argues that alongside these, the legal and social aspects of human beings i.e., the aspect of fulfilling communal obligations and the acts of philanthropy to those who are poor, oppressed, and deprived are standard expectations connoted into the term …

Exploring Professional Dispositions With Preservice Teachers Assignment Description, David Wolff

Open Educational Resources - Teaching and Learning

The dispositions needed to be an educator is vast. Some dispositions come naturally to teacher candidates and others are nurtured by teacher education programs. According to the National Council for Accreditation of Teacher Education (2008), professional dispositions expected of teacher candidates include “the ideal of fairness and the belief that all students can learn (p. 22). This assignment provides teacher candidates an opportunity to explore, analyze, and discuss various professional dispositions needed by educators using six examples of children’s literature, all of which by the author, Patricia Polacco.

The Journey Box: Promoting Language Development While Exploring One’S Identity, David Wolff

Open Educational Resources - Teaching and Learning

A Journey Box allows students to explore and share their family’s historical narrative using primary sources like interviews and artifacts. Students explore different facets of their own family’s history and journey to America while engaging in a larger shared experience among classmates to understand different perspectives. The Journey Box develops oral and written language skills while supporting individual’s exploration of their culture and identity.

Factor Structure Of The International Trauma Questionnaire In Trauma Exposed Lgbtq Plus Adults: Role Of Cumulative Traumatic Events And Minority Stress Heterosexist Experiences, Ruby Charak, Ines Cano-Gonzalez, Roman Ronzón-Tirado, Julian D. Ford, Brianna M. Byllesby, Mark Shevlin, Thanos Karatzias, Philip Hyland, Marylene Cloitre

Psychological Science Faculty Publications

Exposure to prolonged and/or multiple types of psychological trauma and stressors has been shown to be more strongly associated with ICD-11 complex posttraumatic stress disorder (CPTSD) than posttraumatic stress disorder (PTSD). Lesbian, gay, bisexual, trans- and queer adults (LGBTQ+) are at a heightened risk of exposure to traumatic events, and minority stressors including harassment, discrimination, rejection by family, and isolation. Objective: To examine the factor structure of the international trauma questionnaire (ITQ), a self-report measure of PTSD and CPTSD, and the associations of cumulative lifetime trauma exposure assessed via the life events checklist and minority stress assessed via the daily …

Personalized Tweet Recommendation Using Users’ Image Preferences, Shashwat Avinash Kadam

Master's Projects

In the era of information explosion, the vast amount of data on social media platforms can overwhelm users. Not only does this information explosion contain irrelevant content, but also intentionally fabricated articles and images. As a result, personalized recommendation systems have become increasingly important to help users navigate and make sense of this data. We propose a novel technique to use users’ image preferences to recommend tweets. We extract vital information by analyzing images liked by users and use it to recommend tweets from Twitter. As many images online have no descriptive metadata associated with them, in this framework, we …

Image Captioning Using Reinforcement Learning, Venkat Teja Golamaru

Master's Projects

Image captioning is a crucial technology with numerous applications, including enhancing accessibility for the visually impaired, developing automated image indexing and retrieval systems, and enriching social media experiences. However, accurately describing the content of an image in natural language remains a challenge, particularly in low-resource settings where data and computational power are limited. The most advanced image captioning architectures currently use encoder-decoder structures that incorporate a sequential recurrent prediction model. This study adopts a typical Convolutional Neural Network (CNN) encoder Recurrent Neural Network (RNN) decoder structure for image captioning, but it has framed the problem as a sequential decision-making task. …

Application Of Knowledge Graph Techniques On Textbooks, Yutong Yao

Master's Projects

Textbooks are written and organized in a way that facilitates learning and understanding. Sections like glossary terms at the end of a textbook provide guidance on the topic of interest. However, it takes manual effort to create the index terms in the glossary that highlight the key referenced terminologies and related terms. Knowledge graphs, which have been used to represent and even reason over data and knowledge, can potentially capture textbook’s important terms, concepts, and their relations. Popular since the initial introduction by Google Knowledge Graphs (KGs), they combine graph and data to capture and model enormous amounts of relational …

Relationalnet Using Graph Neural Networks For Social Recommendations, Dharahas Tallapally

Master's Projects

Traditional recommender systems create models that can predict user interests based on the user-item relationships. However, these systems often have limited performance due to sparse user behavior data. To address this challenge, researchers are now exploring models for social recommendation that can account for both user- user and user-item relationships based on social networks, and user past behavior, respectively. These models aim to understand each user’s behavior by considering their trusted neighbors and their influence on each other. Specifically, the potential embedding of each user is influenced by their trusted neighbors, who are, in turn, influenced by their own trusted …

Comparative Analysis Of Transformer-Based Models For Text-To-Speech Normalization, Pankti Dholakia

Master's Projects

Text-to-Speech (TTS) normalization is an essential component of natural language processing (NLP) that plays a crucial role in the production of natural-sounding synthesized speech. However, there are limitations to the TTS normalization procedure. Lengthy input sequences and variations in spoken language can present difficulties. The motivation behind this research is to address the challenges associated with TTS normalization by evaluating and comparing the performance of various models. The aim is to determine their effectiveness in handling language variations. The models include LSTM-GRU, Transformer, GCN-Transformer, GCNN-Transformer, Reformer, and a BERT language model that has been pre-trained. The research evaluates the performance …

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 …

Perspective: Dimensions Of Environment And Health In Arctic Communities, Rainer Lohmann, Bonita Beatty, Jessica Graybill, Elena Grigorieva, Ketil Lenert Hansen, Anu Soikkeli

Graduate School of Oceanography Faculty Publications

In the Arctic, environment and health are linked in myriad ways. A key emphasis has been on numerous long-lived contaminants in traditional foods, particularly marine mammals, and their well-documented impacts on human, animal and environmental health (“One health approach”). More recent concerns for Indigenous communities focus on the (side) effects of the switch to a modern, processed diet, which is accompanied by a loss of tradition and emerging health impacts. Furthermore, the availability of traditional foods is increasingly threatened by the impacts of climate change, which also causes the emergence and spread of new and old diseases, such as anthrax. …

The King And His Court: The Culture Of Royal Power And The Creation Of The Angevin Empire Under Henry Ii, Joseph Jarrell

Master's Theses

Legal codes, literature, history, and violence were necessary aspects of royal power that in conjunction with resources gained from familial inheritance and a fortunate marriage allowed King Henry II to build, govern, and legitimize his rule over the Angevin Empire, as well as attempt to create an Angevin dynasty. Examining these subjects advances ideas about medieval royal culture and its relation to political power and legal power in the twelfth century Angevin Empire.

Historiography has long examined this period as the histories of great men, but recent trends have examined the interplay of power, politics, and gender during the Middle …

Obfuscating Systemic Racism: A Critical Policy Discourse Analysis On The Operation Of Neoliberal Ideas In Media Representation Of A School District State Takeover, Trish A. Lopez, Holly Sheppard Riesco, Christian Z. Goering

Curriculum and Instruction Faculty Publications and Presentations

Education reform in the United States has unwisely focused attention on standards and accountability to the state as determined by standardized testing (Berliner & Biddle, 1995; Mehta, 2013). Stemming from the emphasis on standards-based accountability are the ideas of rapid school turnaround and the state’s role in this process (Peck & Reitzug, 2014; VanGronigen & Meyers, 2019). The current study employed critical policy discourse analysis to examine the media’s portrayal of the 2019 determination to continue or terminate state control of the Little Rock School District. The analysis highlights two argumentative frames—one that emphasized neoliberal values in support of continued …