Digital Commons Network^™

Perceptions Of Substance Use Among The Latino Community In Massachusetts: A Qualitative Analysis, Fabián Torres-Ardila, Mariana Beu Rae, Germán Chiriboga, Kathryn G. Bateman, Daniela Bravo, Astha Lama, Leandra Vallejo

Gastón Institute Publications

The Mauricio Gastón Institute is a part of the Collaborative of Asian American, Native American, and Latino and African American Institutes (CANALA), linking institutes at the University of Massachusetts Boston that are dedicated to serving communities of color.1 In collaboration with CANALA, the Gastón Institute took part in a project that aims to help the Massachusetts Bureau of Substance Addiction Services (BSAS) better understand how Latino, Black, and Asian American communities in Massachusetts perceive and experience the opioid crisis. The Gastón Institute’s study focused on the Latino community and aimed to answer the following questions: 1. To what extent, and …

Navigating Race, Equity, And Whiteness: A Case Study Exploring The Culturally Relevant Practices Of English And Social Studies Teachers In A Long Island School District, Betyne Bordes Farrell

Theses & Dissertations

Today, American K-12 classrooms are becoming increasingly racially and ethnically diverse, creating a vital need for culturally relevant pedagogical (CRP) approaches and teacher training to support the achievement of all students. However, despite an expanding body of literature on creating culturally responsive schools, implementation remains challenging for many educators. The purpose of this qualitative case study was to understand how, if at all, a group of six English and Social Studies teachers in two demographically different high schools, one a predominantly Black school and the other a predominantly Asian school, within the same district enact CRP and navigate issues of …

Unlocking Markets: A Multilingual Benchmark To Cross-Market Question Answering, Yifei Yuan, Yang Deng, Anders Sogaard, Mohammad Alliannejadi

Research Collection School Of Computing and Information Systems

Users post numerous product-related questions on e-commerce platforms, affecting their purchase decisions. Product-related question answering (PQA) entails utilizing product-related resources to provide precise responses to users. Wepropose a novel task of Multilingual Crossmarket Product-based Question Answering (MCPQA) and define the task as providing answers to product-related questions in a main marketplace by utilizing information from another resource-rich auxiliary marketplace in a multilingual context. We introduce a largescale dataset comprising over 7 million questions from 17 marketplaces across 11 languages. We then perform automatic translation on the Electronics category of our dataset, naming it as McMarket. We focus on two subtasks: …

Ask-Before-Plan : Proactive Language Agents For Real-World Planning, Xuan Zhang, Yang Deng, Zifeng Ren, See-Kiong Ng, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

The evolution of large language models (LLMs) has enhanced the planning capabilities of language agents in diverse real-world scenarios. Despite these advancements, the potential of LLM-powered agents to comprehend ambiguous user instructions for reasoning and decision-making is still under exploration. In this work, we introduce a new task, Proactive Agent Planning, which requires language agents to predict clarification needs based on user-agent conversation and agent-environment interaction, invoke external tools to collect valid information, and generate a plan to fulfill the user's demands. To study this practical problem, we establish a new benchmark dataset, Ask-before-Plan. To tackle the deficiency of LLMs …

Word Play: A Top-Down Approach To Text Analysis Of Bdsm Practitioners’ Written Language, Phoenix Crane

Psychology and Neuroscience Faculty Publications

Power play, or consensual power changing between “Dominant” and “submissive” role partners, is common practice within BDSM culture. In fact, to many BDSM practitioners, their D/s role is an integral part of their sexual identity and behavior, which informs not only their sexual scripts, but also their non-sexual social interactions. This two-part research study used computerized text analysis to determine whether BDSM practitioners relative to non-practitioners, and among D/s role identities, differed in their language use. Study 1 utilized a sample of 13,374 web-scraped comments from BDSM- and non-BDSM-related subreddits. Study 2 used a recruited sample of 285 self-identified Dominants, …

Using Virtual Learning Labs To (Re)Mediate Exclusionary Discipline Practices For Young Children Of Color With Disabilities, Saili Kulkarni, Sunyoung Kim, Nicola Holdman

Faculty Research, Scholarly, and Creative Activity

Disabled children of color (ages 3-8) face multiple, intersecting oppressions in schools and are more likely to be excluded and/or harshly punished for minor behavioral issues compared to white and/or non-disabled peers. Approaches that center multiple stakeholders (families, teachers, and administrators) using a formative intervention called a Learning Lab (LL) have worked to reduce discipline disparities among secondary and upper primary students of color with disabilities (Bal, 2016). Knowing that discipline disparities can start as early as preschool (Kulkarni et al., 2021), however, we examined how LL (re)mediates exclusionary and harsh discipline practices for young children of color with disabilities. …

Genie: Enhancing Information Management In The Restaurant Industry Through Ai-Powered Chatbot, Megha Gupta, Venkatasai Dheekonda, Mohammad Masum

Faculty Research, Scholarly, and Creative Activity

In the dynamic restaurant industry, we introduce "Genie," an AI-powered chatbot, represents an advancement in customer service efficiency through technological innovation. Designed to enhance restaurant operations including order processing, reservations, and FAQs management, Genie leverages advanced Natural Language Processing (NLP) techniques. By converting input queries into word embeddings and applying a sophisticated tag classification system, Genie precisely interprets customer intents and generates accurate responses, thereby markedly improving the dining experience. Our thorough examination of various word embeddings and classifiers—Word2Vec, Glove, BERT, Gaussian Naive Bayes, XGB, Artificial Neural Networks (ANN), and Recurrent Neural Networks—revealed that the combination of Word2Vec and ANN …

Championing Food Studies Within The Field Of Irish Studies: A Serendipitous Autoethnographic Journey, Mairtin Macconiomaire

Doctoral

Food permeates every aspect of life and society, from birth to death—from the new-born’s first suckle to the food traditions associated with Irish wakes and funerals. Essential for survival, it has historically proven academically elusive, hidden in plain sight. Entangled with the domestic and the feminine, it was traditionally regarded as too mundane and too quotidian for consideration. Depending on how you define it, Irish Studies has somewhere between 50 and 100 years of history as an academic discipline. Food Studies is a more recent academic phenomenon, which has been steadily growing internationally since last decade of the twentieth century. …

Enhancedbert: A Python Software Tailored For Arabic Word Sense Disambiguation, Sanaa Kaddoura, Reem Nassar

All Works

EnhancedBERT is a software framework designed to disambiguate Arabic polysemous terms using advanced natural language processing techniques. It integrates transformer architectures with ensemble methods to achieve high performance in understanding and processing Arabic text. The framework provides a flexible pipeline that can be directly utilized or fine-tuned according to specific needs. EnhancedBERT stands out for its ease of use, leveraging transformer-based models combined with ensemble strategies to provide superior contextual understanding. This contextual awareness makes it an invaluable tool for researchers and practitioners tackling complexities in Arabic language processing.

A Community-Engaged Interprofessional Project Led By Medical Students, School Of Social Work Students, And Resident Physicians: Lessons Learned And Recommendations For Success, Sabrina Orta, Daniela Santos Cantu, Giuiseppe Allan Fonseca, Luis R. Torres-Hostos, Chelsea Chang

School of Medicine Publications

Addressing health disparities through community engagement and interprofessional partnerships is increasingly critical. However, learner-led approaches that integrate medical students, resident physicians, and social work students are not well-studied. We designed a learner-led, interprofessional, public health campaign for a majority Hispanic community, with the goals of building interprofessional leadership skills, engaging learners to address COVID-19 inequities, and disseminating lessons learned. Faculty and students from the University of Texas Rio Grande Valley Schools of Medicine and Social Work partnered with community leaders to pilot an interprofessional project supported by the American Association of Medical Colleges’ Nurturing Experiences for Tomorrow’s Community Leaders (AAMC …

A Secure And Effective Framework For Key Concept Mining From Educational Content Using Large Language Models, Ashika Sameem Abdul Rasheed

Theses

This thesis examines the use of Large Language Models (LLMs) in education, with a focus on improving performance and implementing strong security measures. The research has two main goals, namely, the development of an effective lecture summarization technique using LLMs and identifying and addressing security vulnerabilities in LLM applications according to OWASP (Open Web Application Security Project) guidelines. For the former goal, we have proposed an effective framework for fine-tuning LLMs using real lecture datasets and compared the performance of different LLMs. For the latter goal, we conducted a thorough review of the application dataflow of the proposed framework and …

Developing Policies For Digital Twin Data Quality And Security Controls, Ahmad Abdelbaset Hassan

Theses

This thesis is concerned with the data quality and security of the digital twin and how it is going to impact its adoption, trustworthiness, and potential for real-world applications. By addressing the potential vulnerabilities and ensuring the integrity of data, this research aims to contribute to the development of robust and trustworthy digital twin policies that to complement the existing international standards across different domains. Moreover, it underscores the important need to establish robust policies to ensure the successful and secure deployment of digital twins across industries. Previous research, while valuable, may not have fully addressed the critical interplay between …

The Mediational Role Of Religiosity In The Relationship Between Emotional Regulation And Relationship Satisfaction In Uae And Turkey: A Cross-Sectional Study, Beril Berksu

Theses

Marriage and romantic relationships are significant turning points in personal and social development, contributing to overall well-being and health. In romantic relationship studies, relationship satisfaction is one of the most researched aspects and is affected by various variables, which are gender, relationship duration, and other factors. Among these, religiosity and emotional regulation have been proposed as important aspects as well. However, there is still a gap in the literature to understand how these aspects are connected in non-Western countries like Turkey and the UAE regarding cultural differences. The study aims to explore the mediating role of religiosity in the relationship …

Navigating The Beliefs, Practices, And Challenges Of High School Principals And Teachers Within Culturally Diverse Contexts: A Mixed-Method Study, Mouza Alketbi

Dissertations

The main objective of this study is to understand the practices, beliefs, and challenges related to cultural diversity among high school principals. It also examines the cultural diversity practices of high school principals from the perspective of teachers, as well as the challenges they encounter when interacting with principals and teaching staff. The study used an exploratory sequential mixed method design, incorporating both qualitative and quantitative methods to gain a better understanding of how high school principals handle their culturally diverse teachers. The first phase involved qualitative research, where (n=5) principals and (n=7) teachers were purposively selected. Semistructured interviews were …

Experience As Source For Anticipation And Planning : Experiential Policy Learning For Target-Driven Recommendation Dialogues, Quang Huy Dao, Yang Deng, Khanh-Huyen Bui, Dung D. Le, Lizi Liao

Research Collection School Of Computing and Information Systems

Target-driven recommendation dialogues present unique challenges in dialogue management due to the necessity of anticipating user interactions for successful conversations. Current methods face significant limitations: (I) inadequate capabilities for conversation anticipation, (II) computational inefficiencies due to costly simulations, and (III) neglect of valuable past dialogue experiences. To address these limitations, we propose a new framework, Experiential Policy Learning (EPL), for enhancing such dialogues. EPL embodies the principle of Learning From Experience, facilitating anticipation with an experiential scoring function that estimates dialogue state potential using similar past interactions stored in long-term memory. To demonstrate its flexibility, we introduce Tree-structured EPL (T-EPL) …

Context-Aware Adapter Tuning For Few-Shot Relation Learning In Knowledge Graphs, Ran Liu, Zhongzhou Liu, Xiaoli Li, Yuan Fang

Research Collection School Of Computing and Information Systems

Knowledge graphs (KGs) are instrumental in various real-world applications, yet they often suffer from incompleteness due to missing relations. To predict instances for novel relations with limited training examples, few-shot relation learning approaches have emerged, utilizing techniques such as meta-learning. However, the assumption is that novel relations in meta-testing and base relations in meta-training are independently and identically distributed, which may not hold in practice. To address the limitation, we propose RelAdapter, a context-aware adapter for few-shot relation learning in KGs designed to enhance the adaptation process in meta-learning. First, RelAdapter is equipped with a lightweight adapter module that facilitates …

Dc-Instruct : An Effective Framework For Generative Multi-Intent Spoken Language Understanding, Bowen Xing, Lizi Liao, Minlie Huang

Research Collection School Of Computing and Information Systems

In the realm of multi-intent spoken language understanding, recent advancements have leveraged the potential of prompt learning frameworks. However, critical gaps exist in these frameworks: the lack of explicit modeling of dual-task dependencies and the oversight of task-specific semantic differences among utterances. To address these shortcomings, we propose DC-Instruct, a novel generative framework based on Dual-task Inter-dependent Instructions (DII) and Supervised Contrastive Instructions (SCI). Specifically, DII guides large language models (LLMs) to generate labels for one task based on the other task’s labels, thereby explicitly capturing dual-task inter-dependencies. Moreover, SCI leverages utterance semantics differences by guiding LLMs to determine whether …

Multimodal Misinformation Detection By Learning From Synthetic Data With Multimodal Llms, Fengzhu Zeng, Wenqian Li, Wei Gao, Yan Pang

Research Collection School Of Computing and Information Systems

Detecting multimodal misinformation, especially in the form of image-text pairs, is crucial. Obtaining large-scale, high-quality real-world fact-checking datasets for training detectors is costly, leading researchers to use synthetic datasets generated by AI technologies. However, the generalizability of detectors trained on synthetic data to real-world scenarios remains unclear due to the distribution gap. To address this, we propose learning from synthetic data for detecting real-world multimodal misinformation through two model-agnostic data selection methods that match synthetic and real-world data distributions. Experiments show that our method enhances the performance of a small MLLM (13B) on real-world fact-checking datasets, enabling it to even …

A Comprehensive Survey On Relation Extraction: Recent Advances And New Frontiers, Xiaoyan Zhao, Yang Deng, Min Yang, Lingzhi Wang, Rui Zhang, Hong Cheng, Wai Lam, Ying Shen, Ruifeng Xu

Research Collection School Of Computing and Information Systems

Relation extraction (RE) involves identifying the relations between entities from underlying content. RE serves as the foundation for many natural language processing (NLP) and information retrieval applications, such as knowledge graph completion and question answering. In recent years, deep neural networks have dominated the field of RE and made noticeable progress. Subsequently, the large pre-trained language models (PLMs) have taken the state-of-the-art RE to a new level. This survey provides a comprehensive review of existing deep learning techniques for RE. First, we introduce RE resources, including datasets and evaluation metrics. Second, we propose a new taxonomy to categorize existing works …

The New Social Contracts, Andrew Keane Woods Professor Of Law

Vanderbilt Law Review

Contracts rule our digital world. Platform terms of service determine speech rights, privacy rights, and much more. This is no accident—from the very beginning, the U.S. model of internet governance was explicitly built around private ordering. In this context, it is worth asking what contract law and contract scholarship have to say about the public harms of digital dealmaking.

The answer, quite surprisingly, is: not much. To be sure, the rise of the digital economy has generated over two decades of sustained scholarship and several huge national reform efforts aimed at updating contract law. But this work has largely focused …

Adapting Emergency Response: A Nationwide Study Of Disability Accommodation Practices Among Local Emergency Managers, Iskender Mambetkadyrov

Theses

Local emergency management agencies (EMAs), who are critical in disaster response and management in the US, frequently underserve their constituencies who identify as people with disabilities (PWD) and, more specifically, as deaf and hard of hearing (DHH). These shortfalls have still persisted even after policies such as the Americans with Disabilities Act have passed in an attempt to bridge these gaps. This thesis aims to explore the organizational actions & strategies local EMAs have taken towards disability inclusion, the barriers they run into, and explore whether increases in general disability-inclusive actions lead to increased DHH-specific inclusive actions to steer local …

School Administrators’ Perspectives On Dyslexia And Transformational Leadership And Implications For Teacher Placement, Christina M. Walker

Electronic Theses and Dissertations

This study focused on the perceptions of secondary-level administrators about dyslexia instruction and their decision-making process in teacher placement within a Texas school district. Using transformative leadership theory, the researcher’s aim was to address the instructional needs of students with dyslexia and help catalyze educational change. The research involved a qualitative descriptive approach to explore administrators’ perspectives and practices. Findings revealed that dyslexia affects approximately 15%–20% of the U.S. population. Despite intellectual capabilities, individuals with dyslexia face persistent struggles in reading and writing because of neurobiological differences. The specific problem addressed was the lack of understanding among school administrators about …

A Neutrosophic Model For Measuring Evolution, Involution, And Indeterminacy In Species: Integrating Common And Uncommon Traits In Environmental Adaptation, Antonios Paraskevas, Michael Madas

Neutrosophic Systems with Applications

In 2017, Professor F. Smarandache introduced the Neutrosophic Theory of Evolution, Involution, and Indeterminacy (or Neutrality) (NToEIaI). He concluded that every theory of evolution is characterized by a certain degree of truth, indeterminacy, and untruth, as in neutrosophic logic. In this perspective, he raised several open questions on evolution, neutrality, and involution that required further research effort. Very recently, in 2024, Smarandache conducted research, from a soft sciences/philosophical viewpoint, on identifying and studying common parts in uncommon things and uncommon parts in common things emphasizing the complexity and interconnectedness of concepts within the context of neutrosophy. In this article, we …

Assessing The Maturity Of The “Family Centered Care” Concept: A Review Of Concept Analyses Studies, Sarah Neill, Mohammad Al-Motlaq, Mandie Foster, Maggie Zgambo

School of Nursing and Midwifery

Background: Concept analysis studies play major role in clarifying and operationalizing concepts. This approach has been used to clarify and advance knowledge about the concept of Family Centred Care (FCC). The concept of FCC has been studied by many nursing scholars using different methods. Aim: This review aimed to combine outcomes of concept analysis studies to assess the level of maturity of the concept of Family Centred Care. Methods: Formal electronic databases (MEDLINE and CINAHL) and informal (Google Scholar) were searched using the terms “Family Centred Care” and “concept analysis”. The Morse concept maturity evaluation approach was used to appraise …

A Qualitative Study Of The Career Experiences Of Asian And Asian American Female Administrators In U.S. Higher Education, Yunru Shen

Electronic Theses and Dissertations

This qualitative phenomenological study explored the experiences of Asian and Asian American women administrators’ career paths in U.S. higher education. The research fills a gap in the literature regarding the careers of Asian and Asian American women administrators. The recruitment process was completed between May 13 and July 9, 2024. Recruitment emails were sent to 25 potentially qualified participants, including a network of 17 people made up of mentors, professors, and colleagues, as well as eight professional associations and LinkedIn. The participants were six Asian and Asian American biologically female administrators at U.S. colleges and universities. These participants currently hold …

Raas Festival: A Catalyst For Tourism Development In Assam, India, Madhuchhanda Das Gupta Dr., Chandana Bhattacharjee Dr., Rosemary Debbarma

Journal of Tourism Insights

Traditionally religious practices have been central to any celebration and have greatly influenced the shaping of the cultural identity of any society. With time, these celebrations have transitioned into mega festivals with larger participation from within and outside the community. Through the display of songs, dances, and other art forms, these festivals are upholding and preserving the ethnic identity and culture of the community. They are not only sources of relaxation and entertainment, but also provide visitors with unique cultural experience. By attracting tourists, festivals exert strong influence on the local economy, thereby, driving growth and development. The paper attempts …

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