Digital Commons Network^™

Towards A Model Of The Mapping Between English And Spanish Prosody, Jonathan Avila

Open Access Theses & Dissertations

Current speech-to-speech translation systems face challenges in effectively translating the nuances of prosody, which plays a pivotal role in conveying speaker intent and stance in dialog. This limitation restricts cross-lingual communication, especially in situations demanding deeper interpersonal understanding. To address this, this research delves into the relationships between prosody and its pragmatic functions, in English and Spanish. First, I discuss a data collection protocol in which bilingual speakers re-enact utterances from an earlier conversation in their other language, then describe an English-Spanish corpus, consisting of 3816 matched utterance pairs. Second, I describe a prosodic dissimilarity metric based on Euclidean distance …

How An Instructor's Noticing For Equity Can Foster Students' Sense Of Belonging And Mathematical Confidence, Sthefania Espinosa

Theses and Dissertations

There are many aspects a teacher can notice inside the mathematics classroom, and the more a teacher notices, the more difficult it is to teach. In this study, I particularly focus on noticing for equity, which describes the role of the teacher in attending to students’ mathematical thinking through an equity lens that can allow the instructor to notice the aspects of classroom mathematical activity that can make students feel less or more empowered in their mathematical practices (van Es et al., 2017). There exists few research about how students perceive their instructor’s effort to promote equity and …

The Persuasive Effect Of Ai-Synthesized Voices, Hannah H. Chang, Anirban Mukherjee

Research Collection Lee Kong Chian School Of Business

Artificial intelligence (AI) technology seeks to emulate humans. One aspect is AI-synthesized voices, used in voice assistants (such as Amazon Alexa, Apple Siri, and Google Assistant) to assistive technologies (such as voiceover narration in product videos). For example, there are currently more than 3.25 billion voice assistants; a number that is expected to touch about 8 billion by next year (i.e., 2023) (Statista 2022). With the extensive availability and enhanced accuracy of AI-synthesized voices, consumer research is starting to examine the impact of AI-synthesized voices on consumer information processing and decision making. The extant literature, however, is relatively limited because …

A Black-Box Attack On Code Models Via Representation Nearest Neighbor Search, Jie Zhang, Wei Ma, Qiang Hu, Shangqing Liu, Xiaofei Xie, Yves Le Traon, Yang Liu

Research Collection School Of Computing and Information Systems

Existing methods for generating adversarial code examples face several challenges: limted availability of substitute variables, high verification costs for these substitutes, and the creation of adversarial samples with noticeable perturbations. To address these concerns, our proposed approach, RNNS, uses a search seed based on historical attacks to find potential adversarial substitutes. Rather than directly using the discrete substitutes, they are mapped to a continuous vector space using a pre-trained variable name encoder. Based on the vector representation, RNNS predicts and selects better substitutes for attacks. We evaluated the performance of RNNS across six coding tasks encompassing three programming languages: Java, …

Do Contributing Files Provide Information About Oss Newcomers' Onboarding Barriers?, Felipe Fronchetti, David Shepherd, Igor Wiese, Christoph Treude, Marco Gerosa, Igor Steinmacher

Research Collection School Of Computing and Information Systems

Effectively onboarding newcomers is essential for the success of open source projects. These projects often provide onboarding guidelines in their ‘CONTRIBUTING’ files (e.g., CONTRIBUTING.md on GitHub). These files explain, for example, how to find open tasks, implement solutions, and submit code for review. However, these files often do not follow a standard structure, can be too large, and miss barriers commonly found by newcomers. In this paper, we propose an automated approach to parse these CONTRIBUTING files and assess how they address onboarding barriers. We manually classified a sample of files according to a model of onboarding barriers from the …

Development, Voice, And Vulnerability: A Rhetorical Analysis Of The Policy-Making Discourse Regarding The Paris Agreement As An Organizational Response To Climate Change, David Almanza-Canas

UNLV Theses, Dissertations, Professional Papers, and Capstones

On December 12, 2015, the Paris Agreement was officially ratified by 196 sovereign entities. This treaty represents a global call to action to ameliorate the impact of human activities on our environment, and it creates a means of cooperation through financial support and transparent industrial practices with the goal of promoting accountability across the world. This treaty and the discourse surrounding it present fertile ground for the academic understanding of persuasive practices in policy-making. By examining the rhetorical implications of the Paris Agreement as a global policy, scholars can gain new insight about the communities represented in the conversation as …

An Exhaustive Review Of Neutrosophic Logic In Addressing Image Processing Issues, Samia Mandour

Neutrosophic Systems with Applications

Since the importance of images in our lives and the advancements in computer data gathering methods, anyone can collect a large number of images, but most of them cannot be processed manually. Image processing therefore becomes appealing since various types of data may be represented and processed digitally. Image processing has become the most popular processing method, employed in security camera films, healthcare images, images from remote sensors, and naturalistic image/videos because of fast computers and processors. In order to raise cognitive function and speed up decision-making, image processing is crucial to many information access systems. Since ambiguity now permeates …

Development Of Back-Scatter And Pile-Up Identification For Ucna+, Amelia Greathouse

Undergraduate Honors Theses

The UCNA Experiment at the Los Alamos Neutron Science Center (LANSCE) uses

an electron spectrometer to observe angular correlations between the neutron spin and the momenta of beta particles emitted during the process of beta (β) decay. Combined with neutron lifetime measurements, these observations probe physics beyond the standard model. In recent years there has been an effort to modernize the equipment to reduce the physical limitations of the experiment. The new prototype helps to reduce error via use of silicon photo-multipliers (SiPMs) and the SiPMs also have a greater quantum efficiency than the photomultiplier tubes (PMTs). However, there is …

Systematic Literature Review On Ontology-Based Indonesian Question Answering System, Fadhila Tangguh Admojo, Adidah Lajis, Haidawati Nasir

Knowledge Engineering and Data Science

Question-Answering (QA) systems at the intersection of natural language processing, information retrieval, and knowledge representation aim to provide efficient responses to natural language queries. These systems have seen extensive development in English and languages like Indonesian present unique challenges and opportunities. This literature review paper delves into the state of ontology-based Indonesian QA systems, highlighting critical challenges. The first challenge lies in sentence understanding, variations, and complexity. Most systems rely on syntactic analysis and struggle to grasp sentence semantics. Complex sentences, especially in Indonesian, pose difficulties in parsing, semantic interpretation, and knowledge extraction. Addressing these linguistic intricacies is pivotal for …

Supporting Software Engineers With Large Language Model-Based Automation, Ting Zhang

Dissertations and Theses Collection (Open Access)

In recent years, software engineering (SE) has witnessed significant growth, leading to the creation and sharing of an abundance of software artifacts such as source code, bug reports, and pull requests. Analyzing these artifacts is crucial for comprehending the sentiments of software developers and automating various SE tasks, ultimately leading to more human-centered automated SE and enhancing software development efficiency. However, the diverse and unstructured nature of software text poses a significant challenge to this analysis. In response, researchers have investigated a variety of approaches, including the utilization of natural language processing techniques. The advent of large language models (LLMs), …

Gr-450 Enhancing Sarcasm Detection With Context Sensitivity, Sai Chandana Koganti, Varshini Yaganti, Venkata Sai Ashik Yadali, Vinesh Babu Yaganti, Hemanth Borra

C-Day Computing Showcase

Sarcasm identification is a vital challenge in natural language processing. In this project, we address this challenge by employing a context-sensitive approach that leverages deep learning, transformer learning, and conventional machine learning models. We conducted our research using two benchmark datasets: Twitter and Internet Argument Corpus (IAC-v2). Our three primary models—Bi-LSTM with GloVe embeddings, BERT, and feature fusion—outperformed baseline methods, achieving an 89.4% highest accuracy on Twitter datasets and an 81.2% highest precision on IAC-v2. These results highlight the effectiveness of our approach in sarcasm detection, with significant implications for sentiment analysis and opinion mining. While our project provides promising …

Gr-485 Email Summarizer And Action Item Extractor, Ryan Deem, Eric C Weese

C-Day Computing Showcase

Countless emails are sent and received daily, and a lot of time is spent reading through and understanding the content of these emails. This project aims to increase the efficiency of reading and gathering relevant email information. Our solution includes two parts: abstractive text summarization and action item extraction. Currently, these two items are common in different domains, however, they have not been combined and used with email understanding. Abstractive text summarization is the process of outputting the ideas of the emails using different words without giving quotes from the document. In this way, a person would be able to …

Ai Assisted Workflows For Computational Electromagnetics And Antenna Design, Oameed Noakoasteen

Electrical and Computer Engineering ETDs

These days large volumes of data can be recorded and manipulated with relative ease. If valuable information can be extracted from them, these vast amounts of data can be a rich resource not just for the digital economy but also for scientific discovery and development of technology. When it comes to deriving valuable information from data, Machine Learning (ML) emerges as the key solution. To unlock the potential benefits of ML to science and technology, extensive research is needed to explore what algorithms are suitable and how they can be applied.

To shine light on various ways that ML can …

Exploring The Impact Of Training Datasets On Turkish Stance Detection, Muhammed Sai̇d Zengi̇n, Berk Utku Yeni̇sey, Mücahi̇d Kutlu

Turkish Journal of Electrical Engineering and Computer Sciences

Stance detection has garnered considerable attention from researchers due to its broad range of applications, including fact-checking and social computing. While state-of-the-art stance detection models are usually based on supervised machine learning methods, their effectiveness is heavily reliant on the quality of training data. This problem is more prevalent in stance detection task because the stance of a text is intimately tied to the target under consideration. While numerous datasets exist for stance detection, determining their suitability for a specific target can be challenging. In this work, we focus on Turkish stance detection and explore the impact of training data …

Offenseval 2023: Offensive Language Identification In The Age Of Large Language Models, Marcos Zampieri, Sara Rosenthal, Preslav Nakov, Alphaeus Dmonte, Tharindu Ranasinghe

Natural Language Processing Faculty Publications

The OffensEval shared tasks organized as part of SemEval-2019-2020 were very popular, attracting over 1300 participating teams. The two editions of the shared task helped advance the state of the art in offensive language identification by providing the community with benchmark datasets in Arabic, Danish, English, Greek, and Turkish. The datasets were annotated using the OLID hierarchical taxonomy, which since then has become the de facto standard in general offensive language identification research and was widely used beyond OffensEval. We present a survey of OffensEval and related competitions, and we discuss the main lessons learned. We further evaluate the performance …

Recognition Of Arabic Air-Written Letters: Machine Learning, Convolutional Neural Networks, And Optical Character Recognition (Ocr) Techniques, Khalid Nahar, Izzat Alsmadi, Rabia Emhamed Al Mamlook, Ahmad Nasayreh, Hasan Gharaibeh, Ali Saeed Almuflih, Fahad Alasim

All Faculty Scholarship (Archived)

Air writing is one of the essential fields that the world is turning to, which can benefit from the world of the metaverse, as well as the ease of communication between humans and machines. The research literature on air writing and its applications shows significant work in English and Chinese, while little research is conducted in other languages, such as Arabic. To fill this gap, we propose a hybrid model that combines feature extraction with deep learning models and then uses machine learning (ML) and optical character recognition (OCR) methods and applies grid and random search optimization algorithms to obtain …

The How And Why Of Visual Practice At Un Climate Negotiations, Stéphanie Heckman

New England Journal of Public Policy

In this article Stéphanie Heckman examines the process and outcomes of her graphic recording work and other forms of visual practice in the context of UN climate negotiations, reflecting on three years of collaboration with the UN Climate Change Secretariat, particularly during the eighteen-month Global Stocktake process. After a review of the history and science behind visual storytelling, she analyses one of the graphic recordings made for the third meeting of the Technical Dialogue of the Global Stocktake through the lens of Kelvy Bird’s ‘Levels of Scribing’ model. Drawing on comments from delegates at COP27 in Sharm el-Sheikh, Egypt and …

Intelligent Healthcare: Evaluation Potential Implications Of Metaverse In Healthcare Based On Mathematical Decision-Making Framework, Ibrahim Elhenawy, Sara Fawaz Al-Baker, Mona Mohamed

Neutrosophic Systems with Applications

The Metaverse has the ability to restructure and change the manner in which individuals connect with one another as well as the activities that they carry out on a daily basis. One definition of a Metaverse describes it as "a virtual, digital, and three-dimensional universe formed by the integration of various cutting-edge technologies and virtual places." In this piece, we will explore the potential applications of the Metaverse in the medical field. Our conversations on the notion of the Metaverse and the primary technologies that make it possible are both thought-provoking and in-depth. In this article, we study and analyze …

An Open Natural Language Processing (Nlp) Framework For Ehr-Based Clinical Research: A Case Demonstration Using The National Covid Cohort Collaborative (N3c), Sijia Liu, Andrew Wen, Liwei Wang, Huan He, Sunyang Fu, Robert Miller, Andrew Williams, Daniel Harris, Ramakanth Kavuluru, Mei Liu, Noor Abu-El-Rub, Dalton Schutte, Rui Zhang, Masoud Rouhizadeh, John D Osborne, Yongqun He, Umit Topaloglu, Stephanie S Hong, Joel H Saltz, Thomas Schaffter, Emily Pfaff, Christopher G Chute, Tim Duong, Melissa A Haendel, Rafael Fuentes, Peter Szolovits, Hua Xu, Hongfang Liu

Faculty, Staff and Student Publications

Despite recent methodology advancements in clinical natural language processing (NLP), the adoption of clinical NLP models within the translational research community remains hindered by process heterogeneity and human factor variations. Concurrently, these factors also dramatically increase the difficulty in developing NLP models in multi-site settings, which is necessary for algorithm robustness and generalizability. Here, we reported on our experience developing an NLP solution for Coronavirus Disease 2019 (COVID-19) signs and symptom extraction in an open NLP framework from a subset of sites participating in the National COVID Cohort (N3C). We then empirically highlight the benefits of multi-site data for both …

Cognitive Engagement During Group Learning Activities In Chemistry Courses: An Analysis Of Student Discourse, Safaa Youssef El-Mansy

Dissertations and Theses

As educators, our goal is to help our students be successful, but in order to accomplish this, we need to understand what factors contribute to student success. One factor, small-group active learning, has been correlated to improved academic outcomes; however, the magnitude of this improvement can vary across different courses, different types of group work, and even across courses that use the same group work structure. Therefore, it is important to understand what aspects of group work contribute to its effectiveness. The work presented in this dissertation investigated one specific aspect: students’ cognitive engagement. This was done by analyzing the …

The View From Ventress - 2022-23 Academic Year, University Of Mississippi, College Of Liberal Arts

Liberal Arts Newsletters

News from the College of Liberal Arts

Dispensing With Humans In Human-Computer Interaction Research, Courtni L. Byun

Theses and Dissertations

Machine Learning models have become more advanced than could have been supposed even a few years ago, often surpassing human performance on many tasks. Large language models (LLM) can produce text indistinguishable from human-produced text. This begs the question, how necessary are humans - even for tasks where humans appear indispensable? Qualitative Analysis (QA) is integral to human-computer interaction research, requiring both human-produced data and human analysis of that data to illuminate human opinions about and experiences with technology. We use GPT-3 and ChatGPT to replace human analysis and then to dispense with human-produced text altogether. We find GPT-3 is …

All Quiet On The Digital Front: The Unseen Psychological Impacts On Cybersecurity First Responders, Tammie R. Hollis

USF Tampa Graduate Theses and Dissertations

Driven by the increasing frequency of cyberattacks and the existing talent gap between industry needs and skilled professionals, this research study focused on the crucial human element in the domain of cybersecurity incident response. The objective of this dissertation was to offer a meaningful exploration of the lived experiences encountered by cybersecurity incident responders and an assessment of the subsequent impacts on their well-being. Additionally, this study sought to draw comparisons between the experiences of cybersecurity incident responders and their counterparts in traditional emergency response roles. Semi-structured interviews were conducted with a cohort of 22 individuals with first-hand experience working …

More On Complex Hesitant Fuzzy Graphs, Abdulazeez Alkouri, Eman A. Abuhijleh, Ghada Alafifi, Eman Almuhur, Fadi M.A. Al-Zubi

All Works

Correctly determining a company’s market worth during an entire year or a certain period presents a difficulty to decision-makers. In the case of the merger of companies, the need performs heavier when both the companies’ owners are attracted to establishing a fair price at the optimal time to merge. The effectiveness of representing, connecting and manipulating both uncertainty and periodicity information becomes highly required. Hence, study and nhance some properties and conditions of the algebraic structure of complex hesitant fuzzy graphs. Therefore, the degree of composition between two complex hesitant fuzzy graphs is proposed. Also, the formal definitions of union, …

Big Data Analytics For Healthcare Social Media: New Algorithms And Insights, Negar Maleki

USF Tampa Graduate Theses and Dissertations

Over the last two decades, there has been a rapid evolution in information and communication technology, including the emergence of social media. Social media has a significant impact on various fields such as politics, business, culture, education, careers, innovation, and especially healthcare. This influence is not a new phenomenon since a survey from ten years ago showed that up to 78\% of American adults used the internet to look for health-related information for themselves or someone else. With the shift towards on-demand services in society, healthcare is also affected by this trend. Instead of waiting for weeks or months to …

The Age Of Synthetic Realities: Challenges And Opportunities, João Phillipe Cardenuto, Jing Yang, Rafael Padilha, Renjie Wan, Daniel Moreira, Haoliang Li, Shiqi Wang, Fernanda Andaló, Sébastien Marcel, Anderson Rocha

Computer Science: Faculty Publications and Other Works

Synthetic realities are digital creations or augmentations that are contextually generated through the use of Artificial Intelligence (AI) methods, leveraging extensive amounts of data to construct new narratives or realities, regardless of the intent to deceive. In this paper, we delve into the concept of synthetic realities and their implications for Digital Forensics and society at large within the rapidly advancing field of AI. We highlight the crucial need for the development of forensic techniques capable of identifying harmful synthetic creations and distinguishing them from reality. This is especially important in scenarios involving the creation and dissemination of fake news, …

Individuality And The Collective In Ai Agents: Explorations Of Shared Consciousness And Digital Homunculi In The Metaverse For Cultural Heritage, James Hutson, Jay Ratican

Faculty Scholarship

The confluence of extended reality (XR) technologies, including augmented and virtual reality, with large language models (LLM) marks a significant advancement in the field of digital humanities, opening uncharted avenues for the representation of cultural heritage within the burgeoning metaverse. This paper undertakes an examination of the potentialities and intricacies of such a convergence, focusing particularly on the creation of digital homunculi or changelings. These virtual beings, remarkable for their sentience and individuality, are also part of a collective consciousness, a notion explored through a thematic comparison in science fiction with the Borg and the Changelings in the Star Trek …

Novus Ex Machina: Realise Your Organisation’S Creative Potential With Ai, Adam Tatarynowicz, Utz Claassen

Asian Management Insights

Innovation managers must learn how to harness AI’s transformative potential.

Designing Secure Mental Healthcare Chatbots For Older Adults, Aishwarya Surani

Electronic Theses and Dissertations

The landscape of mental health support has evolved as a result of the rising demand for digital mental healthcare services. Users now have an opportunity to seek mental health support online due to the growth of digital platforms. For those looking for mental health treatments, chatbots have evolved as user-friendly, accessible platforms that provide remote access and convenience. However, for chatbots to be effective, users must divulge personal and sensitive information, such as demographics, insurance information, and a history of mental illness. While chatbots offer services to a variety of demographic users, older adults face unique challenges related to usability, …

Followupqg: Towards Information-Seeking Follow-Up Question Generation, Yan Meng, Liangming Pan, Yixin Cao, Min-Yen Kan

Research Collection School Of Computing and Information Systems

Humans ask follow-up questions driven by curiosity, which reflects a creative human cognitive process. We introduce the task of realworld information-seeking follow-up question generation (FQG), which aims to generate follow-up questions seeking a more in-depth understanding of an initial question and answer. We construct FOLLOWUPQG, a dataset1 of over 3K real-world (initial question, answer, follow-up question) tuples collected from a Reddit forum providing layman-friendly explanations for open-ended questions. In contrast to existing datasets, questions in FOLLOWUPQG use more diverse pragmatic strategies to seek information, and they also show higher-order cognitive skills (such as applying and relating). We evaluate current question …