Digital Commons Network^™

Visualizing Literary Narratives With A Graph-Centered Approach., Meg Ermer

Campus Research Month

The art of storytelling is multifaceted and nonlinear, involving multiple characters, themes, and symbols while often jumping between the present and past. While media forms such as novels can encapsulate these complexities, it is often difficult to visualize a narrative in an easy-to-understand format. Our contribution is a graph-based system to let users organize and visualize those narratives. Events and characters are represented as nodes and their relationships are represented as edges. Neo4J is used as a database management system to store the graph and to run queries on it, and Streamlit and Pyvis are used to represent the database …

Analysis The Role Of The Internet Of Things And Industry 4.0 In Healthcare Supply Chain Using Neutrosophic Sets, Ahmed M. Abdelmouty, Ahmed Abdel-Monem, Samah Ibrahim Abdel Aal, Mahmoud M. Ismail

Neutrosophic Systems with Applications

In today's global economy, the Healthcare supply chain (HCSC) must be aware of a market that is both complicated and ever-changing. The HCSC in Industry 4.0 aims to give patients the medicine they need as quickly and cheaply as possible. The HCSC can improve operations by automating routine tasks and reducing human error by using new technologies like the "Internet of Things" (IoT); so, there is a need to analyze the role of IoT and Industry 4.0 in the Healthcare Supply Chain. This paper aims to analyze the role of IoT and Industry 4.0 in HCSC. Also, this paper proposes …

Question Answering With Distilled Bert Models: A Case Study For Biomedical Data, Brittany Lewandowski, Rayon Morris, Pearly Merin Paul, Robert Slater

SMU Data Science Review

In the healthcare industry today, 80% of data is unstructured (Razzak et al., 2019). The challenge this imposes on healthcare providers is that they rely on unstructured data to inform their decision-making. Although Electronic Health Records (EHRs) exist to integrate patient data, healthcare providers are still challenged with searching for information and answers contained within unstructured data. Prior NLP and Deep Learning research has shown that these methods can improve information extraction on unstructured medical documents. This research expands upon those studies by developing a Question Answering system using distilled BERT models. Healthcare providers can use this system on their …

Content-Based Unsupervised Fake News Detection On Ukraine-Russia War, Yucheol Shin, Yvan Sojdehei, Limin Zheng, Brad Blanchard

SMU Data Science Review

The Ukrainian-Russian war has garnered significant attention worldwide, with fake news obstructing the formation of public opinion and disseminating false information. This scholarly paper explores the use of unsupervised learning methods and the Bidirectional Encoder Representations from Transformers (BERT) to detect fake news in news articles from various sources. BERT topic modeling is applied to cluster news articles by their respective topics, followed by summarization to measure the similarity scores. The hypothesis posits that topics with larger variances are more likely to contain fake news. The proposed method was evaluated using a dataset of approximately 1000 labeled news articles related …

Professor Text: University Fundraising Optimization, Braden Anderson, Connor Dobbs, Hien Lam, John Santerre

SMU Data Science Review

University fundraising campaigns are a unique type of cause-related marketing with its own challenges and opportunities. Campaigns like this typically last an extended period, such as five or more years, and goals exist beyond the dollar amount raised. These supplemental goals, such as awareness among potential future donators or brand reputation within the local community, are important to consider and strategize. There can also be unique limitations, such as requiring advertising specifically on recent large gifts or endowment programs. This research explores how machine learning techniques such as natural language processing can be used to optimize a fundraising campaign strategy, …

A Statistical Comparison Of Hebrews To Accepted Pauline And Lukan Corpora, Benjamin Erickson

Liberty University Research Week

Undergraduate

Applied

How Resilience Is Framed Matters For Governance Of Coastal Social-Ecological Systems, Sarah Clement, Javad Jozaei, Michael Mitchell, Craig R. Allen, Ahjond S. Garmestani

School of Natural Resources: Faculty Publications

Effective governance of social-ecological systems (SES) is an enduring challenge, especially in coastal environments where accelerating impacts of climate change are increasing pressure on already stressed systems. While resilience is often proposed as a suitable framing to re-orient governance and management, the literature includes many different, and sometimes conflicting, definitions and ideas that influence how the concept is applied, especially in coastal environments. This study combines discourse analysis of the coastal governance literature and key informant interviews in Tasmania, Australia, demonstrating inconsistencies and confusion in the way that resilience is framed in coastal governance research and practice. We find that …

Volume 9 Full Text, Bjur Staff

Butler Journal of Undergraduate Research

No abstract provided.

Higher Education Students’ Perceptions Of Online Learning During The Covid-19 Pandemic, Abby O’Bryant

Butler Journal of Undergraduate Research

This article focuses on the impacts of online learning during the COVID-19 pandemic on students at the University of Hawai‘i at Hilo. Using survey data (n = 64) and semistructured interviews with currently enrolled students (n = 17), key impacts of online learning on the student body were analyzed. The respondents reported disengagement in lectures, negative impacts on their mental and physical health, negative thoughts about dropping out and transferring, apprehension about the quality of course content, and dissatisfaction with tuition. The paper utilizes qualitative data analysis to report the findings.

Bad Boy Bias: Linguistic Bias In The Law, Parth Sharma

Butler Journal of Undergraduate Research

This paper seeks to establish and put in use methodology capable of analyzing the significant linguistic bias found within American jurisprudence. It summarizes the limited preexisting empirical work done and adds a new original empirical study on linguistic bias in the courtroom. It examines a large number of cases through various software and examines the prevalence of certain labels (badges of bias). In doing so, this paper seeks to find the most common labels and seeks to determine the amount of emotional variability present within the courtroom. Based on these results, the paper provides recommendations, answering how best to efficiently …

Table Of Contents And Front Matter, Bjur Staff

Butler Journal of Undergraduate Research

No abstract provided.

The Impact Of Prc Language Policies On Minority Languages Of China, Margaret Shoop

Undergraduate Research Competition

While language is often used as a tool to bring people together and celebrate differences, language can also be weaponized and used to suppress minority groups of people. There are over three hundred unique languages and dialects spoken in Mainland China, with Mandarin Chinese being the most widely spoken of the languages. Mandarin is the official state language of the People’s Republic of China (PRC), and it is also the primary language taught in schools across the country. Despite official Chinese policy of teaching Mandarin Chinese alongside local dialects, Mandarin is favored over minority languages. The unequal emphasis on Mandarin …

"Challenging The Known." 16th Annual Research Week: Event Proceedings, University Of The Incarnate Word

Excellence Summit (Research Week) Archived Proceedings

Presentations of completed and ongoing research activity conducted by graduate students, undergraduate students, and faculty at University of the Incarnate Word. Includes poster, podium, visual arts, interactive demo, and creative and performing arts presentations. Coordinated and presented by the Office of Research and Graduate Studies.

Neutrosophic Marcos In Decision Making On Smart Manufacturing System, Nivetha Martin, Said Broumi, S. Sudha, R. Priya

Neutrosophic Systems with Applications

Business firms prefer software-based smart manufacturing systems to monitor and supervise all production activities in a decentralized manner. The choice of software decides the degree of manufacturing robustness. This paper proposes a neutrosophic-based MARCOS (Measurement of Alternatives and Ranking according to COmpromise Solution) method of MCDM with single-valued triangular neutrosophic numbers to solve the software selection problem. The proposed neutrosophic method is applied to hypothetical data to test the efficacy of the method. The results obtained using the proposed method are compared with crisp, fuzzy, and intuitionistic data representations, and suitable inferences are acquired. The proposed method has several industrial …

A Language-Model-Based Chatbot That Considers The User's Personality Profile And Emotions To Support Caregivers Of People With Dementia, Yeganeh Nasiri

Theses and Dissertations

Chatbots are programs that mimic human conversation using Artificial Intelligence (AI). Recent advances in natural language pro- cessing pave the way for chatbots to generate more human-like responses. Therefore, chatbots are finding more complex tasks to perform, such as emotional support which requires both understanding emotions and the ability to properly respond to them. This work presents a chatbot capable of identifying the user's personality and creating responses based on that. During this process, emotion detection is being used to detect and react to users' emotions. The chatbot uses a dynamic knowledge graph to save information as the conversation goes …

Multi-Modal Knowledge Graph Inference Via Media Convergence And Logic Rule, Feng Lin, Dongmei Li, Wenbin Zhang, Dongsheng Shi, Yuanzhou Jiao, Qianzhong Chen, Yiying Lin, Wentao Zhu

Michigan Tech Publications, Part 1

Media convergence works by processing information from different modalities and applying them to different domains. It is difficult for the conventional knowledge graph to utilise multi-media features because the introduction of a large amount of information from other modalities reduces the effectiveness of representation learning and makes knowledge graph inference less effective. To address the issue, an inference method based on Media Convergence and Rule-guided Joint Inference model (MCRJI) has been proposed. The authors not only converge multi-media features of entities but also introduce logic rules to improve the accuracy and interpretability of link prediction. First, a multi-headed self-attention approach …

A Hybrid Mcdm Approach For Industrial Robots Selection For The Automotive Industry, Abduallah Gamal, Mona Mohamed

Neutrosophic Systems with Applications

The use of robots in various stages of the production process is now commonplace across practically all sectors of the economy. Additionally, even for present-day small and medium-sized businesses, this has developed into a very powerful need in recent years and continues to grow in importance. The selection of an industrial robot is a very complicated decision-making issue due to the fact that there are numerous aspects and criteria that are in conflict with one another, as almost all of the earlier research emphasized. In addition, the many sophisticated requirements that have been added to these robots by the makers …

Language Modeling Using Image Representations Of Natural Language, Seong Eun Cho

Theses and Dissertations

This thesis presents training of an end-to-end autoencoder model using the transformer, with an encoder that can encode sentences into fixed-length latent vectors and a decoder that can reconstruct the sentences using image representations. Encoding and decoding sentences to and from these image representations are central to the model design. This method allows new sentences to be generated by traversing the Euclidean space, which makes vector arithmetic possible using sentences. Machines excel in dealing with concrete numbers and calculations, but do not possess an innate infrastructure designed to help them understand abstract concepts like natural language. In order for a …

Tc-Net: A Modest & Lightweight Emotion Recognition System Using Temporal Convolution Network, Muhammad Ishaq, Mustaqeem Khan, Soonil Kwon

Computer Vision Faculty Publications

Speech signals play an essential role in communication and provide an efficient way to exchange information between humans and machines. Speech Emotion Recognition (SER) is one of the critical sources for human evaluation, which is applicable in many real-world applications such as healthcare, call centers, robotics, safety, and virtual reality. This work developed a novel TCN-based emotion recognition system using speech signals through a spatial-temporal convolution network to recognize the speaker's emotional state. The authors designed a Temporal Convolutional Network (TCN) core block to recognize long-term dependencies in speech signals and then feed these temporal cues to a dense network …

Automatic Assessment Of Oral Reading Fluency From Children's Read Speech In The Filipino Language, Francis Dimzon

Software Technology Dissertations

With the end view of helping the Philippine education system in its literacy initiatives, this study aims to develop methods for automatic assessment of oral reading fluency from children's read speech in the Filipino language. Thus, this study seeks to design methods of automatically extracting and analyzing prosodic features of children's read speech in Filipino. To achieve this, the four-fold set of research activities was conducted to describe an automated oral reading fluency assessment system. It consisted of 1) building a children's Filipino speech corpus, 2) designing methods of extracting and analyzing prosodic features, 3) developing methods of automatically assessing …

2023- The Twenty-Seventh Annual Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the Twenty-seventh Annual Symposium of Student Scholars, held on April 18-21, 2023. Includes abstracts from the presentations and posters.

Para Cima Y Pa’ Abajo: Building Bridges Between Hci Research In Latin America And In The Global North, Pedro Reynolds-Cuéllar, Marisol Wong-Villacres, Karla A. Badillo-Urquiola, Mayra Donaji Barrera-Machuca, Franceli L. Cibrian, Marianela Ciolfi Felice, Carolina Fuentes, Laura Sanely Gaytán-Lugo, Vivian Genaro Motti, Monica Perusquía-Hernández, Oscar A. Lemus

Engineering Faculty Articles and Research

The Human-computer Interaction (HCI) community has the opportunity to foster the integration of research practices across the Global South and North to begin overcoming colonial relationships. In this paper, we focus on the case of Latin America (LATAM), where initiatives to increase the representation of HCI practitioners lack a consolidated understanding of the practices they employ, the factors that influence them, and the challenges that practitioners face. To address this knowledge gap, we employ a mixed-methods approach, comprising a survey (66 respondents) and in-depth interviews (19 interviewees). Our analyses characterize a set of research perspectives on how HCI is practiced …

Belonging And Identity In Mustang: Lived Experiences, Social Identities, And Mobility Patterns Among Himalayan Peoples Of Nepal, Lauren Carter

Independent Study Project (ISP) Collection

This paper delves into an immersive exploration and contemplation of a pivotal transformation unfolding in the heartland of Lower Mustang, Nepal. What began as an endeavor to channel my creative expression and unearth the diminishing world of yak herding soon necessitated a broader, more nuanced analysis of the profound changes sweeping across the region. This paper, mainly drawing upon the narratives of the inhabitants, seeks to portray the contemporary cultural and capital significance of yaks, as well as the various factors— climate change, outmigration, national policy discrepancies, conservation initiatives, and shifting cultural paradigms— that render specific patterns of movement increasingly …

Defining Safe Training Datasets For Machine Learning Models Using Ontologies, Lynn C. Vonder Haar

Doctoral Dissertations and Master's Theses

Machine Learning (ML) models have been gaining popularity in recent years in a wide variety of domains, including safety-critical domains. While ML models have shown high accuracy in their predictions, they are still considered black boxes, meaning that developers and users do not know how the models make their decisions. While this is simply a nuisance in some domains, in safetycritical domains, this makes ML models difficult to trust. To fully utilize ML models in safetycritical domains, there needs to be a method to improve trust in their safety and accuracy without human experts checking each decision. This research proposes …

Socially Aware Natural Language Processing With Commonsense Reasoning And Fairness In Intelligent Systems, Sirwe Saeedi

Dissertations

Although Artificial Intelligence (AI) promises to deliver ever more user-friendly consumer applications, recent mishaps involving fake information and biased treatment serve as vivid reminders of the pitfalls of AI. AI can harbor latent biases and flaws that can cause harm in diverse and unexpected ways. It is crucial to understand the reasons for, mechanisms behind, and circumstances under which AI can fail. For instance, a lack of commonsense reasoning can lead to biased or unfair decisions made by Machine Learning (ML) systems. For example, if an ML system is trained on data that is biased or unrepresentative of the real …

Evaluating The On-Site Impacts Of The Ambatovy Project Through The Lens Of Environmental Justice, Nick Karlik

Independent Study Project (ISP) Collection

In Madagascar, sustainable development has been established and maintained by dominant foreign actors to reconcile neoliberalism with globalized conceptions of environmental protection. The Ambatovy mining and refining project has emerged as a prominent example of this developmental mode; Ambatovy is the largest economic enterprise in the history of the country and one of the largest and most productive mining operations in the world, generating billions of dollars in revenue for a country that remains among the poorest in the world while offsetting its impact on endemic biodiversity and forest habitat through conservation initiatives. At the same time, the evaluative framework …

The Australian News Media And Climate Change: How Frames Impact The Response Of Individuals In An Anthropocentric Society, Laura Joelsson

Independent Study Project (ISP) Collection

News media plays an instrumental role in shaping opinions and perceptions on climate change due to it being such a wide-reaching institution. The discourses of news media are able to use frames to determine the discursive context in which a concept or issue is discussed by promoting a central theme or message. This study aims to use critical discourse analysis to determine how climate change is framed in news media, and how these frames depict the forms and scope of possible climate action. The study also analyzes if these forms of action are predominantly anthropocentric in nature. Critical discourse analysis …

Talking To The Earth: A Digital Documentation Of Biodiversity In The Sherpa Language, Dvij Sharma

Independent Study Project (ISP) Collection

Identified as a pressing matter by organizations as prominent as the UN, the conservation of minority and indigenous languages “is essential for ensuring the continuation and transmission of culture, customs, and history, but it is also important to address biodiversity loss and climate change.” This project focuses on one of the latter issues, biodiversity loss, as it relates to Sherpa, a minority language spoken primarily in Eastern Nepal. In an effort to help preserve the native vocabulary and descriptions of basic plants and animals found in Sherpa-speaking regions, primarily interview-based fieldwork was conducted in the lower Solu regions of Lumsa, …

Supporting Novices Author Audio Descriptions Via Automatic Feedback, Rosiana Natalie, Joshua Shi-Hao Tseng, Hernisa Kacorri, Kotaro Hara

Research Collection School Of Computing and Information Systems

Audio descriptions (AD) make videos accessible to those who cannot see them. But many videos lack AD and remain inaccessible as traditional approaches involve expensive professional production. We aim to lower production costs by involving novices in this process. We present an AD authoring system that supports novices to write scene descriptions (SD)—textual descriptions of video scenes—and convert them into AD via text-to-speech. The system combines video scene recognition and natural language processing to review novice-written SD and feeds back what to mention automatically. To assess the effectiveness of this automatic feedback in supporting novices, we recruited 60 participants to …

Restructuring Pedagogical Norms In Stem: Towards A Socially And Ethically Conscious Approach To Computer Science Higher Education, Alison Kim , '23

Senior Theses, Projects, and Awards

No abstract provided.